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Sample records for samples-in proteomic biomarker

  1. Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

    Science.gov (United States)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John; Oller Moreno, Sergio; Irincheeva, Irina; Valsesia, Armand; Astrup, Arne; Saris, Wim H M; Hager, Jörg; Kussmann, Martin; Dayon, Loïc

    2016-02-05

    The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

  2. Proteomic biomarker discovery in 1000 human plasma samples with mass spectrometry

    DEFF Research Database (Denmark)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John

    2016-01-01

    automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked...

  3. Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Ahmed, Farid E

    2009-03-01

    Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

  4. Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Proteomic and metabolomic approaches to biomarker discovery

    CERN Document Server

    Issaq, Haleem J

    2013-01-01

    Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

  6. Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.

    Science.gov (United States)

    Galazis, Nicolas; Olaleye, Olalekan; Haoula, Zeina; Layfield, Robert; Atiomo, William

    2012-12-01

    To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS). Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS. Academic department of obstetrics and gynecology in the United Kingdom. A total of 180 women identified in the six studies. Tissue samples from women with OC vs. tissue samples from women without OC. Proteomic biomarkers, proteomic technique used, and methodologic quality score. A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2. These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  7. Mass spectrometry-based proteomic quest for diabetes biomarkers.

    Science.gov (United States)

    Shao, Shiying; Guo, Tiannan; Aebersold, Ruedi

    2015-06-01

    Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Proteomic Biomarkers for Spontaneous Preterm Birth

    DEFF Research Database (Denmark)

    Kacerovsky, Marian; Lenco, Juraj; Musilova, Ivana

    2014-01-01

    This review aimed to identify, synthesize, and analyze the findings of studies on proteomic biomarkers for spontaneous preterm birth (PTB). Three electronic databases (Medline, Embase, and Scopus) were searched for studies in any language reporting the use of proteomic biomarkers for PTB published...

  9. Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation.

    Science.gov (United States)

    Bhosale, Santosh D; Moulder, Robert; Kouvonen, Petri; Lahesmaa, Riitta; Goodlett, David R

    2017-01-01

    Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

  10. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

    Science.gov (United States)

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

    2014-09-09

    Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

  11. Overlap of proteomics biomarkers between women with pre-eclampsia and PCOS: a systematic review and biomarker database integration.

    Science.gov (United States)

    Khan, Gulafshana Hafeez; Galazis, Nicolas; Docheva, Nikolina; Layfield, Robert; Atiomo, William

    2015-01-01

    Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. A systematic review and update of our PCOS proteomic biomarker database was performed, along with a parallel review of PE biomarkers. The study included papers from 1980 to December 2013. In all the studies analysed, there were a total of 1423 patients and controls. The number of proteomic biomarkers that were catalogued for PE was 192. Five proteomic biomarkers were shown to be differentially expressed in women with PE and PCOS when compared with controls: transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. In PE, the biomarkers were identified in serum, plasma and placenta and in PCOS, the biomarkers were identified in serum, follicular fluid, and ovarian and omental biopsies. The techniques employed to detect proteomics have limited ability in identifying proteins that are of low abundance, some of which may have a diagnostic potential. The sample sizes and number of biomarkers identified from these studies do not exclude the risk of false positives, a limitation of all biomarker studies. The biomarkers common to PE and PCOS were identified from proteomic analyses of different tissues. This data amalgamation of the proteomic studies in PE and in PCOS, for the first time, discovered a panel of five biomarkers for PE which are common to women with PCOS, including transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. If validated, these biomarkers could provide a useful framework for the knowledge infrastructure in this area. To accomplish this goal, a

  12. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Larry Gold

    2010-12-01

    Full Text Available The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma. Our current assay measures 813 proteins with low limits of detection (1 pM median, 7 logs of overall dynamic range (~100 fM-1 µM, and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD. We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

  13. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Science.gov (United States)

    Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

    2010-12-07

    The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

  14. Proteomics for discovery of candidate colorectal cancer biomarkers

    Science.gov (United States)

    Álvarez-Chaver, Paula; Otero-Estévez, Olalla; Páez de la Cadena, María; Rodríguez-Berrocal, Francisco J; Martínez-Zorzano, Vicenta S

    2014-01-01

    Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers. PMID:24744574

  15. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Directory of Open Access Journals (Sweden)

    Debasish Paul

    2013-01-01

    Full Text Available Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

  16. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Science.gov (United States)

    Paul, Debasish; Kumar, Avinash; Gajbhiye, Akshada; Santra, Manas K.; Srikanth, Rapole

    2013-01-01

    Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches. PMID:23586059

  17. Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers

    LENUS (Irish Health Repository)

    Dakna, Mohammed

    2010-12-10

    Abstract Background The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of sets of clinically relevant biomarkers. As tractable example we define the measurable proteomic differences between apparently healthy adult males and females. We choose urine as body-fluid of interest and CE-MS, a thoroughly validated platform technology, allowing for routine analysis of a large number of samples. The second urine of the morning was collected from apparently healthy male and female volunteers (aged 21-40) in the course of the routine medical check-up before recruitment at the Hannover Medical School. Results We found that the Wilcoxon-test is best suited for the definition of potential biomarkers. Adjustment for multiple testing is necessary. Sample size estimation can be performed based on a small number of observations via resampling from pilot data. Machine learning algorithms appear ideally suited to generate classifiers. Assessment of any results in an independent test-set is essential. Conclusions Valid proteomic biomarkers for diagnosis and prognosis only can be defined by applying proper statistical data mining procedures. In particular, a justification of the sample size should be part of the study design.

  18. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

    DEFF Research Database (Denmark)

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn

    2016-01-01

    and Results Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFr......Background Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. Methods.......6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin. Conclusion CE-MS based urine proteome analysis served as a sensitive tool...

  19. Novel TIA biomarkers identified by mass spectrometry-based proteomics.

    Science.gov (United States)

    George, Paul M; Mlynash, Michael; Adams, Christopher M; Kuo, Calvin J; Albers, Gregory W; Olivot, Jean-Marc

    2015-12-01

    Transient ischemic attacks remain a clinical diagnosis with significant variability between physicians. Finding reliable biomarkers to identify transient ischemic attacks would improve patient care and optimize treatment. Our aim is to identify novel serum TIA biomarkers through the use of mass spectroscopy-based proteomics. Patients with transient neurologic symptoms were prospectively enrolled. Mass spectrometry-based proteomics, an unbiased method to identify candidate proteins, was used to test the serum of the patients for biomarkers of cerebral ischemia. Three candidate proteins were found, and serum concentrations of these proteins were measured by enzyme-linked immunosorbent assay in a second cohort of prospectively enrolled patients. The Student's t-test was used for comparison. The Benjamini-Hochberg false discovery rate controlling procedure for multiple comparison adjustments determined significance for the proteomic screen. Patients with transient ischemic attacks (n = 20), minor strokes (n = 15), and controls (i.e. migraine, seizure, n = 12) were enrolled in the first cohort. Ceruloplasmin, complement component C8 gamma (C8γ), and platelet basic protein were significantly different between the ischemic group (transient ischemic attack and minor stroke) and the controls (P = 0·0001, P = 0·00027, P = 0·00105, respectively). A second cohort of patients with transient ischemic attack (n = 22), minor stroke (n = 20), and controls' (n = 12) serum was enrolled. Platelet basic protein serum concentrations were increased in the ischemic samples compared with control (for transient ischemic attack alone, P = 0·019, for the ischemic group, P = 0·046). Ceruloplasmin trended towards increased concentrations in the ischemic group (P = 0·127); no significant difference in C8γ (P = 0·44) was found. Utilizing mass spectrometry-based proteomics, platelet basic protein has been identified as a candidate serum

  20. Systemic sclerosis biomarkers discovered using mass-spectrometry-based proteomics: a systematic review.

    Science.gov (United States)

    Bălănescu, Paul; Lădaru, Anca; Bălănescu, Eugenia; Băicuş, Cristian; Dan, Gheorghe Andrei

    2014-08-01

    Systemic sclerosis (SSc) is an autoimmune disease with incompletely known physiopathology. There is a great challenge to predict its course and therapeutic response using biomarkers. To critically review proteomic biomarkers discovered from biological specimens from systemic sclerosis patients using mass spectrometry technologies. Medline and Embase databases were searched in February 2014. Out of the 199 records retrieved, a total of 20 records were included, identifying 116 candidate proteomic biomarkers. Research in SSc proteomic biomarkers should focus on biomarker validation, as there are valuable mass-spectrometry proteomics studies in the literature.

  1. Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

    Directory of Open Access Journals (Sweden)

    Venugopal Abhilash

    2009-01-01

    Full Text Available Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS. Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

  2. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

    Full Text Available The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

  3. A Pilot Proteomic Analysis of Salivary Biomarkers in Autism Spectrum Disorder.

    Science.gov (United States)

    Ngounou Wetie, Armand G; Wormwood, Kelly L; Russell, Stefanie; Ryan, Jeanne P; Darie, Costel C; Woods, Alisa G

    2015-06-01

    Autism spectrum disorder (ASD) prevalence is increasing, with current estimates at 1/68-1/50 individuals diagnosed with an ASD. Diagnosis is based on behavioral assessments. Early diagnosis and intervention is known to greatly improve functional outcomes in people with ASD. Diagnosis, treatment monitoring and prognosis of ASD symptoms could be facilitated with biomarkers to complement behavioral assessments. Mass spectrometry (MS) based proteomics may help reveal biomarkers for ASD. In this pilot study, we have analyzed the salivary proteome in individuals with ASD compared to neurotypical control subjects, using MS-based proteomics. Our goal is to optimize methods for salivary proteomic biomarker discovery and to identify initial putative biomarkers in people with ASDs. The salivary proteome is virtually unstudied in ASD, and saliva could provide an easily accessible biomaterial for analysis. Using nano liquid chromatography-tandem mass spectrometry, we found statistically significant differences in several salivary proteins, including elevated prolactin-inducible protein, lactotransferrin, Ig kappa chain C region, Ig gamma-1 chain C region, Ig lambda-2 chain C regions, neutrophil elastase, polymeric immunoglobulin receptor and deleted in malignant brain tumors 1. Our results indicate that this is an effective method for identification of salivary protein biomarkers, support the concept that immune system and gastrointestinal disturbances may be present in individuals with ASDs and point toward the need for larger studies in behaviorally-characterized individuals. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  4. Revisiting biomarker discovery by plasma proteomics

    DEFF Research Database (Denmark)

    Geyer, Philipp E; Holdt, Lesca M; Teupser, Daniel

    2017-01-01

    slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker...

  5. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    Science.gov (United States)

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150

  6. Plasma proteomics to identify biomarkers - Application to cardiovascular diseases

    DEFF Research Database (Denmark)

    Beck, Hans Christian; Overgaard, Martin; Melholt Rasmussen, Lars

    2015-01-01

    There is an unmet need for new cardiovascular biomarkers. Despite this only few biomarkers for the diagnosis or screening of cardiovascular diseases have been implemented in the clinic. Thousands of proteins can be analysed in plasma by mass spectrometry-based proteomics technologies. Therefore......, this technology may therefore identify new biomarkers that previously have not been associated with cardiovascular diseases. In this review, we summarize the key challenges and considerations, including strategies, recent discoveries and clinical applications in cardiovascular proteomics that may lead...

  7. Proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Xing [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China); Xu, Yanli [Fuyang People’s Hospital (China); Meng, Qian [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China); Zheng, Qingqing [Digestive Endoscopic Center, Shanghai Jiaotong University Affiliated Sixth People’s Hospital (China); Wu, Jianhong [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China); Wang, Chen; Jia, Weiping [Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital (China); Figeys, Daniel [Department of Biochemistry, Microbiology and Immunology, and Department of Chemistry and Biomolecular Sciences, University of Ottawa (Canada); Chang, Ying, E-mail: emulan@163.com [Digestive Endoscopic Center, Shanghai Jiaotong University Affiliated Sixth People’s Hospital (China); Zhou, Hu, E-mail: zhouhu@simm.ac.cn [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China)

    2016-08-05

    Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP and NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.

  8. Proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling

    International Nuclear Information System (INIS)

    Liu, Xing; Xu, Yanli; Meng, Qian; Zheng, Qingqing; Wu, Jianhong; Wang, Chen; Jia, Weiping; Figeys, Daniel; Chang, Ying; Zhou, Hu

    2016-01-01

    Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP and NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.

  9. Implementation of proteomic biomarkers : Making it work

    NARCIS (Netherlands)

    Mischak, Harald; Ioannidis, John P. A.; Argiles, Angel; Attwood, Teresa K.; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P.; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W.; Julien, Bruce A.; Lankisch, Tim; Leung, Hing Y.; Maahs, David; Magni, Fulvio; Manns, Michael P.; Manolis, Efthymios; Mayer, Gert; Navis, Gerarda; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H.; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P.; Vlahou, Antonia

    Eur J Clin Invest 2012; 42 (9): 10271036 Abstract While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe

  10. Major depressive disorder: insight into candidate cerebrospinal fluid protein biomarkers from proteomics studies.

    Science.gov (United States)

    Al Shweiki, Mhd Rami; Oeckl, Patrick; Steinacker, Petra; Hengerer, Bastian; Schönfeldt-Lecuona, Carlos; Otto, Markus

    2017-06-01

    Major Depressive Disorder (MDD) is the leading cause of global disability, and an increasing body of literature suggests different cerebrospinal fluid (CSF) proteins as biomarkers of MDD. The aim of this review is to summarize the suggested CSF biomarkers and to analyze the MDD proteomics studies of CSF and brain tissues for promising biomarker candidates. Areas covered: The review includes the human studies found by a PubMed search using the following terms: 'depression cerebrospinal fluid biomarker', 'major depression biomarker CSF', 'depression CSF biomarker', 'proteomics depression', 'proteomics biomarkers in depression', 'proteomics CSF biomarker in depression', and 'major depressive disorder CSF'. The literature analysis highlights promising biomarker candidates and demonstrates conflicting results on others. It reveals 42 differentially regulated proteins in MDD that were identified in more than one proteomics study. It discusses the diagnostic potential of the biomarker candidates and their association with the suggested pathologies. Expert commentary: One ultimate goal of finding biomarkers for MDD is to improve the diagnostic accuracy to achieve better treatment outcomes; due to the heterogeneous nature of MDD, using bio-signatures could be a good strategy to differentiate MDD from other neuropsychiatric disorders. Notably, further validation studies of the suggested biomarkers are still needed.

  11. Plasma Proteome Biomarkers of Inflammation in School Aged Children in Nepal.

    Directory of Open Access Journals (Sweden)

    Sun Eun Lee

    Full Text Available Inflammation is a condition stemming from complex host defense and tissue repair mechanisms, often simply characterized by plasma levels of a single acute reactant. We attempted to identify candidate biomarkers of systemic inflammation within the plasma proteome. We applied quantitative proteomics using isobaric mass tags (iTRAQ tandem mass spectrometry to quantify proteins in plasma of 500 Nepalese children 6-8 years of age. We evaluated those that co-vary with inflammation, indexed by α-1-acid glycoprotein (AGP, a conventional biomarker of inflammation in population studies. Among 982 proteins quantified in >10% of samples, 99 were strongly associated with AGP at a family-wise error rate of 0.1%. Magnitude and significance of association varied more among proteins positively (n = 41 than negatively associated (n = 58 with AGP. The former included known positive acute phase proteins including C-reactive protein, serum amyloid A, complement components, protease inhibitors, transport proteins with anti-oxidative activity, and numerous unexpected intracellular signaling molecules. Negatively associated proteins exhibited distinct differences in abundance between secretory hepatic proteins involved in transporting or binding lipids, micronutrients (vitamin A and calcium, growth factors and sex hormones, and proteins of largely extra-hepatic origin involved in the formation and metabolic regulation of extracellular matrix. With the same analytical approach and the significance threshold, seventy-two out of the 99 proteins were commonly associated with CRP, an established biomarker of inflammation, suggesting the validity of the identified proteins. Our findings have revealed a vast plasma proteome within a free-living population of children that comprise functional biomarkers of homeostatic and induced host defense, nutrient metabolism and tissue repair, representing a set of plasma proteins that may be used to assess dynamics and extent of

  12. Candidate proteomic biomarkers for non-alcoholic fatty liver disease (steatosis and non-alcoholic steatohepatitis) discovered with mass-spectrometry: a systematic review.

    Science.gov (United States)

    Lădaru, Anca; Bălănescu, Paul; Stan, Mihaela; Codreanu, Ioana; Anca, Ioana Alina

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is characterized by lipid accumulation in the liver which is accompanied by a series of metabolic deregulations. There are sustained research efforts focusing upon biomarker discovery for NAFLD diagnosis and its prognosis in order investigate and follow-up patients as minimally invasive as possible. The objective of this study is to critically review proteomic studies that used mass spectrometry techniques and summarize relevant proteomic NAFLD candidate biomarkers. Medline and Embase databases were searched from inception to December 2014. A final number of 22 records were included that identified 251 candidate proteomic biomarkers. Thirty-three biomarkers were confirmed - 14 were found in liver samples, 21 in serum samples, and two from both serum and liver samples. Some of the biomarkers identified have already been extensively studied regarding their diagnostic and prognostic capacity. However, there are also more potential biomarkers that still need to be addressed in future studies.

  13. Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

    Science.gov (United States)

    Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

    2015-11-01

    Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Proteomic analysis of tissue samples in translational breast cancer research

    DEFF Research Database (Denmark)

    Gromov, Pavel; Moreira, José; Gromova, Irina

    2014-01-01

    In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis...... the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens....

  15. Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

    DEFF Research Database (Denmark)

    Kristiansen, Troels Zakarias; Harsha, H C; Grønborg, Mads

    2008-01-01

    Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based...

  16. Bayesian methods for proteomic biomarker development

    Directory of Open Access Journals (Sweden)

    Belinda Hernández

    2015-12-01

    In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.

  17. Proteomic Approaches in Biomarker Discovery: New Perspectives in Cancer Diagnostics

    Science.gov (United States)

    Kocevar, Nina; Komel, Radovan

    2014-01-01

    Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697

  18. Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue

    NARCIS (Netherlands)

    N.Q. Liu (Ning Qing); R.B.H. Braakman (René); C. Stingl (Christoph); T.M. Luider (Theo); J.W.M. Martens (John); J.A. Foekens (John); A. Umar (Arzu)

    2012-01-01

    textabstractMass spectrometry (MS)-based label-free proteomics offers an unbiased approach to screen biomarkers related to disease progression and therapy-resistance of breast cancer on the global scale. However, multi-step sample preparation can introduce large variation in generated data, while

  19. Urine sample preparation for proteomic analysis.

    Science.gov (United States)

    Olszowy, Pawel; Buszewski, Boguslaw

    2014-10-01

    Sample preparation for both environmental and more importantly biological matrices is a bottleneck of all kinds of analytical processes. In the case of proteomic analysis this element is even more important due to the amount of cross-reactions that should be taken into consideration. The incorporation of new post-translational modifications, protein hydrolysis, or even its degradation is possible as side effects of proteins sample processing. If protocols are evaluated appropriately, then identification of such proteins does not bring difficulties. However, if structural changes are provided without sufficient attention then protein sequence coverage will be reduced or even identification of such proteins could be impossible. This review summarizes obstacles and achievements in protein sample preparation of urine for proteome analysis using different tools for mass spectrometry analysis. The main aim is to present comprehensively the idea of urine application as a valuable matrix. This article is dedicated to sample preparation and application of urine mainly in novel cancer biomarkers discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

    Directory of Open Access Journals (Sweden)

    Peter Feist

    2015-02-01

    Full Text Available Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

  1. Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

    Science.gov (United States)

    Feist, Peter; Hummon, Amanda B.

    2015-01-01

    Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed. PMID:25664860

  2. Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples.

    Science.gov (United States)

    Feist, Peter; Hummon, Amanda B

    2015-02-05

    Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

  3. Mass Spectrometry–Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

    Science.gov (United States)

    Hawkridge, Adam M.; Muddiman, David C.

    2011-01-01

    Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry–based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed. PMID:20636062

  4. Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review.

    Science.gov (United States)

    Nicolaou, Orthodoxia; Kousios, Andreas; Hadjisavvas, Andreas; Lauwerys, Bernard; Sokratous, Kleitos; Kyriacou, Kyriacos

    2017-05-01

    Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry-based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Twenty-five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  5. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction.

    Directory of Open Access Journals (Sweden)

    Kasper Rossing

    Full Text Available Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972 discriminated between HFrEF patients (N = 94, sensitivity = 93.6% and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%. Interestingly, HFrEF103 showed low sensitivity (12.6% in individuals with diastolic left ventricular dysfunction (N = 176. The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

  6. The potential biomarkers of drug addiction: proteomic and metabolomics challenges.

    Science.gov (United States)

    Wang, Lv; Wu, Ning; Zhao, Tai-Yun; Li, Jin

    2016-07-28

    Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

  7. An individual urinary proteome analysis in normal human beings to define the minimal sample number to represent the normal urinary proteome

    Directory of Open Access Journals (Sweden)

    Liu Xuejiao

    2012-11-01

    Full Text Available Abstract Background The urinary proteome has been widely used for biomarker discovery. A urinary proteome database from normal humans can provide a background for discovery proteomics and candidate proteins/peptides for targeted proteomics. Therefore, it is necessary to define the minimum number of individuals required for sampling to represent the normal urinary proteome. Methods In this study, inter-individual and inter-gender variations of urinary proteome were taken into consideration to achieve a representative database. An individual analysis was performed on overnight urine samples from 20 normal volunteers (10 males and 10 females by 1DLC/MS/MS. To obtain a representative result of each sample, a replicate 1DLCMS/MS analysis was performed. The minimal sample number was estimated by statistical analysis. Results For qualitative analysis, less than 5% of new proteins/peptides were identified in a male/female normal group by adding a new sample when the sample number exceeded nine. In addition, in a normal group, the percentage of newly identified proteins/peptides was less than 5% upon adding a new sample when the sample number reached 10. Furthermore, a statistical analysis indicated that urinary proteomes from normal males and females showed different patterns. For quantitative analysis, the variation of protein abundance was defined by spectrum count and western blotting methods. And then the minimal sample number for quantitative proteomic analysis was identified. Conclusions For qualitative analysis, when considering the inter-individual and inter-gender variations, the minimum sample number is 10 and requires a balanced number of males and females in order to obtain a representative normal human urinary proteome. For quantitative analysis, the minimal sample number is much greater than that for qualitative analysis and depends on the experimental methods used for quantification.

  8. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  9. Biomarkers in Alzheimer’s Disease Analysis by Mass Spectrometry-Based Proteomics

    Directory of Open Access Journals (Sweden)

    Yahui Liu

    2014-05-01

    Full Text Available Alzheimer’s disease (AD is a common chronic and destructive disease. The early diagnosis of AD is difficult, thus the need for clinically applicable biomarkers development is growing rapidly. There are many methods to biomarker discovery and identification. In this review, we aim to summarize Mass spectrometry (MS-based proteomics studies on AD and discuss thoroughly the methods to identify candidate biomarkers in cerebrospinal fluid (CSF and blood. This review will also discuss the potential research areas on biomarkers.

  10. Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery.

    Science.gov (United States)

    Krüger, Thomas; Lautenschläger, Janin; Grosskreutz, Julian; Rhode, Heidrun

    2013-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2-5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Biomarker discovery and applications for foods and beverages: proteomics to nanoproteomics.

    Science.gov (United States)

    Agrawal, Ganesh Kumar; Timperio, Anna Maria; Zolla, Lello; Bansal, Vipul; Shukla, Ravi; Rakwal, Randeep

    2013-11-20

    Foods and beverages have been at the heart of our society for centuries, sustaining humankind - health, life, and the pleasures that go with it. The more we grow and develop as a civilization, the more we feel the need to know about the food we eat and beverages we drink. Moreover, with an ever increasing demand for food due to the growing human population food security remains a major concern. Food safety is another growing concern as the consumers prefer varied foods and beverages that are not only traded nationally but also globally. The 21st century science and technology is at a new high, especially in the field of biological sciences. The availability of genome sequences and associated high-throughput sensitive technologies means that foods are being analyzed at various levels. For example and in particular, high-throughput omics approaches are being applied to develop suitable biomarkers for foods and beverages and their applications in addressing quality, technology, authenticity, and safety issues. Proteomics are one of those technologies that are increasingly being utilized to profile expressed proteins in different foods and beverages. Acquired knowledge and protein information have now been translated to address safety of foods and beverages. Very recently, the power of proteomic technology has been integrated with another highly sensitive and miniaturized technology called nanotechnology, yielding a new term nanoproteomics. Nanoproteomics offer a real-time multiplexed analysis performed in a miniaturized assay, with low-sample consumption and high sensitivity. To name a few, nanomaterials - quantum dots, gold nanoparticles, carbon nanotubes, and nanowires - have demonstrated potential to overcome the challenges of sensitivity faced by proteomics for biomarker detection, discovery, and application. In this review, we will discuss the importance of biomarker discovery and applications for foods and beverages, the contribution of proteomic technology in

  12. Role of proteomics in the discovery of autism biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Ayadhi, L. A.; Halepoto, D. M. [King Saud Univ., Riyadh (Saudi Arabia). Dept. of Physiology

    2013-02-15

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  13. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

    Ayadhi, L.A.; Halepoto, D.M.

    2013-01-01

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  14. Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

    Science.gov (United States)

    Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

    2013-01-01

    Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

  15. One Sample, One Shot - Evaluation of sample preparation protocols for the mass spectrometric proteome analysis of human bile fluid without extensive fractionation.

    Science.gov (United States)

    Megger, Dominik A; Padden, Juliet; Rosowski, Kristin; Uszkoreit, Julian; Bracht, Thilo; Eisenacher, Martin; Gerges, Christian; Neuhaus, Horst; Schumacher, Brigitte; Schlaak, Jörg F; Sitek, Barbara

    2017-02-10

    The proteome analysis of bile fluid represents a promising strategy to identify biomarker candidates for various diseases of the hepatobiliary system. However, to obtain substantive results in biomarker discovery studies large patient cohorts necessarily need to be analyzed. Consequently, this would lead to an unmanageable number of samples to be analyzed if sample preparation protocols with extensive fractionation methods are applied. Hence, the performance of simple workflows allowing for "one sample, one shot" experiments have been evaluated in this study. In detail, sixteen different protocols implying modifications at the stages of desalting, delipidation, deglycosylation and tryptic digestion have been examined. Each method has been individually evaluated regarding various performance criteria and comparative analyses have been conducted to uncover possible complementarities. Here, the best performance in terms of proteome coverage has been assessed for a combination of acetone precipitation with in-gel digestion. Finally, a mapping of all obtained protein identifications with putative biomarkers for hepatocellular carcinoma (HCC) and cholangiocellular carcinoma (CCC) revealed several proteins easily detectable in bile fluid. These results can build the basis for future studies with large and well-defined patient cohorts in a more disease-related context. Human bile fluid is a proximal body fluid and supposed to be a potential source of disease markers. However, due to its biochemical composition, the proteome analysis of bile fluid still represents a challenging task and is therefore mostly conducted using extensive fractionation procedures. This in turn leads to a high number of mass spectrometric measurements for one biological sample. Considering the fact that in order to overcome the biological variability a high number of biological samples needs to be analyzed in biomarker discovery studies, this leads to the dilemma of an unmanageable number of

  16. Defining Diagnostic Biomarkers Using Shotgun Proteomics and MALDI-TOF Mass Spectrometry.

    Science.gov (United States)

    Armengaud, Jean

    2017-01-01

    Whole-cell MALDI-TOF has become a robust and widely used tool to quickly identify any pathogen. In addition to being routinely used in hospitals, it is also useful for low cost dereplication in large scale screening procedures of new environmental isolates for environmental biotechnology or taxonomical applications. Here, I describe how specific biomarkers can be defined using shotgun proteomics and whole-cell MALDI-TOF mass spectrometry. Based on MALDI-TOF spectra recorded on a given set of pathogens with internal calibrants, m/z values of interest are extracted. The proteins which contribute to these peaks are deduced from label-free shotgun proteomics measurements carried out on the same sample. Quantitative information based on the spectral count approach allows ranking the most probable candidates. Proteogenomic approaches help to define whether these proteins give the same m/z values along the whole taxon under consideration or result in heterogeneous lists. These specific biomarkers nicely complement conventional profiling approaches and may help to better define groups of organisms, for example at the subspecies level.

  17. Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

    Science.gov (United States)

    Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

    2004-01-01

    The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

  18. Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease.

    Directory of Open Access Journals (Sweden)

    Esther Nkuipou-Kenfack

    Full Text Available Chronic kidney disease (CKD is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR at mild (59.9±16.5 mL/min/1.73 m2; n = 10 or advanced (8.9±4.5 mL/min/1.73 m2; n = 10 CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = -0.8031; p<0.0001 and ρ = -0.6009; p = 0.0019, respectively. Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = -0.6557; p = 0.0001 and ρ = -0.6574; p = 0.0005. A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = -0.7752; p<0.0001 and ρ = -0.8400; p<0.0001. The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In

  19. Implementation of proteomic biomarkers: making it work

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John PA; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia

    2012-01-01

    While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. PMID:22519700

  20. Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

    DEFF Research Database (Denmark)

    Alkhalaf, Alaa; Zürbig, Petra; Bakker, Stephan J L

    2010-01-01

    /d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). METHODOLOGY/PRINCIPAL FINDINGS: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously......BACKGROUND: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers...... with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg...

  1. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer.

    Directory of Open Access Journals (Sweden)

    Rachel M Ostroff

    Full Text Available BACKGROUND: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. CONCLUSIONS/SIGNIFICANCE: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels

  2. Noninvasive diagnosis of intraamniotic infection: proteomic biomarkers in vaginal fluid.

    Science.gov (United States)

    Hitti, Jane; Lapidus, Jodi A; Lu, Xinfang; Reddy, Ashok P; Jacob, Thomas; Dasari, Surendra; Eschenbach, David A; Gravett, Michael G; Nagalla, Srinivasa R

    2010-07-01

    We analyzed the vaginal fluid proteome to identify biomarkers of intraamniotic infection among women in preterm labor. Proteome analysis was performed on vaginal fluid specimens from women with preterm labor, using multidimensional liquid chromatography, tandem mass spectrometry, and label-free quantification. Enzyme immunoassays were used to quantify candidate proteins. Classification accuracy for intraamniotic infection (positive amniotic fluid bacterial culture and/or interleukin-6 >2 ng/mL) was evaluated using receiver-operator characteristic curves obtained by logistic regression. Of 170 subjects, 30 (18%) had intraamniotic infection. Vaginal fluid proteome analysis revealed 338 unique proteins. Label-free quantification identified 15 proteins differentially expressed in intraamniotic infection, including acute-phase reactants, immune modulators, high-abundance amniotic fluid proteins and extracellular matrix-signaling factors; these findings were confirmed by enzyme immunoassay. A multi-analyte algorithm showed accurate classification of intraamniotic infection. Vaginal fluid proteome analyses identified proteins capable of discriminating between patients with and without intraamniotic infection. Copyright (c) 2010 Mosby, Inc. All rights reserved.

  3. The Urine Proteome as a Biomarker of Radiation Injury

    Science.gov (United States)

    Sharma, Mukut; Halligan, Brian D.; Wakim, Bassam T.; Savin, Virginia J.; Cohen, Eric P.; Moulder, John E.

    2009-01-01

    Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury. PMID:19746194

  4. Implementation of proteomic biomarkers: making it work.

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John P A; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia

    2012-09-01

    While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. © 2012 The Authors. European Journal of Clinical Investigation © 2012 Stichting European Society for Clinical Investigation Journal Foundation.

  5. Selecting Sample Preparation Workflows for Mass Spectrometry-Based Proteomic and Phosphoproteomic Analysis of Patient Samples with Acute Myeloid Leukemia.

    Science.gov (United States)

    Hernandez-Valladares, Maria; Aasebø, Elise; Selheim, Frode; Berven, Frode S; Bruserud, Øystein

    2016-08-22

    Global mass spectrometry (MS)-based proteomic and phosphoproteomic studies of acute myeloid leukemia (AML) biomarkers represent a powerful strategy to identify and confirm proteins and their phosphorylated modifications that could be applied in diagnosis and prognosis, as a support for individual treatment regimens and selection of patients for bone marrow transplant. MS-based studies require optimal and reproducible workflows that allow a satisfactory coverage of the proteome and its modifications. Preparation of samples for global MS analysis is a crucial step and it usually requires method testing, tuning and optimization. Different proteomic workflows that have been used to prepare AML patient samples for global MS analysis usually include a standard protein in-solution digestion procedure with a urea-based lysis buffer. The enrichment of phosphopeptides from AML patient samples has previously been carried out either with immobilized metal affinity chromatography (IMAC) or metal oxide affinity chromatography (MOAC). We have recently tested several methods of sample preparation for MS analysis of the AML proteome and phosphoproteome and introduced filter-aided sample preparation (FASP) as a superior methodology for the sensitive and reproducible generation of peptides from patient samples. FASP-prepared peptides can be further fractionated or IMAC-enriched for proteome or phosphoproteome analyses. Herein, we will review both in-solution and FASP-based sample preparation workflows and encourage the use of the latter for the highest protein and phosphorylation coverage and reproducibility.

  6. Shotgun Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    W. Hayes McDonald

    2002-01-01

    Full Text Available Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC and multidimensional LC (LC/LC can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology, show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.

  7. Identification of Biomarkers for Endometriosis Using Clinical Proteomics

    Directory of Open Access Journals (Sweden)

    Yang Zhao

    2015-01-01

    Full Text Available Background: We investigated possible biomarkers for endometriosis (EM using the ClinProt technique and proteomics methods. Methods: We enrolled 50 patients with EM, 34 with benign ovarian neoplasms and 40 healthy volunteers in this study. Serum proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS combined with weak cationic exchange (WCX magnetic beads. Possible biomarkers were analyzed by a random and repeat pattern model-validation method that we designed, and ClinProtools software, results were refined using online liquid chromatography-tandem MS. Results: We found a cluster of 5 peptides (4210, 5264, 2660, 5635, and 5904 Da, using 3 peptides (4210, 5904, 2660 Da to discriminate EM patients from healthy volunteers, with 96.67% sensitivity and 100% specificity. We selected 4210 and 5904 m/z, which differed most between patients with EM and controls, and identified them as fragments of ATP1B4, and the fibrinogen alpha (FGA isoform 1/2 of the FGA chain precursor, respectively. Conclusions: ClinProt can identify EM biomarkers, which - most notably - distinguish even early-stage or minimal disease. We found 5 stable peaks at 4210, 5264, 2660, 5635, and 5904 Da as potential EM biomarkers, the strongest of which were associated with ATP1B4 (4210 Da and FGA (5904 Da; this indicates that ATP1B4 and FGA are associated with EM pathogenesis.

  8. Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.

    Science.gov (United States)

    Mundt, Filip; Johansson, Henrik J; Forshed, Jenny; Arslan, Sertaç; Metintas, Muzaffer; Dobra, Katalin; Lehtiö, Janne; Hjerpe, Anders

    2014-03-01

    Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome

  9. Sample handling for mass spectrometric proteomic investigations of human sera.

    NARCIS (Netherlands)

    West-Nielsen, M.; Hogdall, E.V.; Marchiori, E.; Hogdall, C.K.; Schou, C.; Heegaard, N.H.H.

    2005-01-01

    Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers

  10. Proteomic candidate biomarkers of drug-induced nephrotoxicity in the rat.

    Directory of Open Access Journals (Sweden)

    Rodney Rouse

    Full Text Available Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10-20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity.

  11. The Urine Proteome as a Biomarker of Radiation Injury: Submitted to Proteomics- Clinical Applications Special Issue: "Renal and Urinary Proteomics (Thongboonkerd)"

    Science.gov (United States)

    Sharma, Mukut; Halligan, Brian D; Wakim, Bassam T; Savin, Virginia J; Cohen, Eric P; Moulder, John E

    2008-06-18

    Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury.

  12. Selecting Sample Preparation Workflows for Mass Spectrometry-Based Proteomic and Phosphoproteomic Analysis of Patient Samples with Acute Myeloid Leukemia

    Directory of Open Access Journals (Sweden)

    Maria Hernandez-Valladares

    2016-08-01

    Full Text Available Global mass spectrometry (MS-based proteomic and phosphoproteomic studies of acute myeloid leukemia (AML biomarkers represent a powerful strategy to identify and confirm proteins and their phosphorylated modifications that could be applied in diagnosis and prognosis, as a support for individual treatment regimens and selection of patients for bone marrow transplant. MS-based studies require optimal and reproducible workflows that allow a satisfactory coverage of the proteome and its modifications. Preparation of samples for global MS analysis is a crucial step and it usually requires method testing, tuning and optimization. Different proteomic workflows that have been used to prepare AML patient samples for global MS analysis usually include a standard protein in-solution digestion procedure with a urea-based lysis buffer. The enrichment of phosphopeptides from AML patient samples has previously been carried out either with immobilized metal affinity chromatography (IMAC or metal oxide affinity chromatography (MOAC. We have recently tested several methods of sample preparation for MS analysis of the AML proteome and phosphoproteome and introduced filter-aided sample preparation (FASP as a superior methodology for the sensitive and reproducible generation of peptides from patient samples. FASP-prepared peptides can be further fractionated or IMAC-enriched for proteome or phosphoproteome analyses. Herein, we will review both in-solution and FASP-based sample preparation workflows and encourage the use of the latter for the highest protein and phosphorylation coverage and reproducibility.

  13. Biomarkers: in medicine, drug discovery, and environmental health

    National Research Council Canada - National Science Library

    Vaidya, Vishal S; Bonventre, Joseph V

    2010-01-01

    ... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

  14. Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

    2015-11-06

    Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

  15. Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma.

    Science.gov (United States)

    Fujii, Kiyonaga; Nakamura, Haruhiko; Nishimura, Toshihide

    2017-04-01

    Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

  16. A single lysis solution for the analysis of tissue samples by different proteomic technologies

    DEFF Research Database (Denmark)

    Gromov, P.; Celis, J.E.; Gromova, I.

    2008-01-01

    -based proteomics (reverse-phase lysate arrays or direct antibody arrays), allowing the direct comparison of qualitative and quantitative data yielded by these technologies when applied to the same samples. The usefulness of the CLB1 solution for gel-based proteomics was further established by 2D PAGE analysis...... dissease, is driving scientists to increasingly use clinically relevant samples for biomarker and target discovery. Tissues are heterogeneous and as a result optimization of sample preparation is critical for generating accurate, representative, and highly reproducible quantitative data. Although a large...... number of protocols for preparation of tissue lysates has been published, so far no single recipe is able to provide a "one-size fits all" solubilization procedure that can be used to analyse the same lysate using different proteomics technologies. Here we present evidence showing that cell lysis buffer...

  17. Proteomic profiling of renal allograft rejection in serum using magnetic bead-based sample fractionation and MALDI-TOF MS.

    Science.gov (United States)

    Sui, Weiguo; Huang, Liling; Dai, Yong; Chen, Jiejing; Yan, Qiang; Huang, He

    2010-12-01

    Proteomics is one of the emerging techniques for biomarker discovery. Biomarkers can be used for early noninvasive diagnosis and prognosis of diseases and treatment efficacy evaluation. In the present study, the well-established research systems of ClinProt Micro solution incorporated unique magnetic bead sample preparation technology, which, based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), have become very successful in bioinformatics due to its outstanding performance and reproducibility for discovery disease-related biomarker. We collected fasting blood samples from patients with biopsy-confirmed acute renal allograft rejection (n = 12), chronic rejection (n = 12), stable graft function (n = 12) and also from healthy volunteers (n = 13) to study serum peptidome patterns. Specimens were purified with magnetic bead-based weak cation exchange chromatography and analyzed with a MALDI-TOF mass spectrometer. The results indicated that 18 differential peptide peaks were selected as potential biomarkers of acute renal allograft rejection, and 6 differential peptide peaks were selected as potential biomarkers of chronic rejection. A Quick Classifier Algorithm was used to set up the classification models for acute and chronic renal allograft rejection. The algorithm models recognize 82.64% of acute rejection and 98.96% of chronic rejection episodes, respectively. We were able to identify serum protein fingerprints in small sample sizes of recipients with renal allograft rejection and establish the models for diagnosis of renal allograft rejection. This preliminary study demonstrated that proteomics is an emerging tool for early diagnosis of renal allograft rejection and helps us to better understand the pathogenesis of disease process.

  18. Data from a targeted proteomics approach to discover biomarkers in saliva for the clinical diagnosis of periodontitis

    Directory of Open Access Journals (Sweden)

    V. Orti

    2018-06-01

    Full Text Available This study focused on the search for new biomarkers based on liquid chromatography-multiple reaction monitoring (LC-MRM proteomics profiling of whole saliva from patients with periodontitis compared to healthy subjects. The LC-MRM profiling approach is a new and innovative method that has already been validated for the absolute and multiplexed quantification of biomarkers in several diseases. The dataset for this study was produced using LC-MRM to monitor protein levels in a multiplex assay, it provides clinical information on salivary biomarkers of periodontitis. The data presented here is an extension of our recently published research article (Mertens et al., 2017 [1]. Keywords: Clinical chemistry, Mass spectrometry, Proteomics, Saliva biochemistry, Oral disease, Periodontitis

  19. Using a novel "Integrated Biomarker Proteomic" index to assess the effects of freshwater pollutants in European eel peripheral blood mononuclear cells.

    Science.gov (United States)

    Roland, Kathleen; Kestemont, Patrick; Dieu, Marc; Raes, Martine; Silvestre, Frédéric

    2016-03-30

    Using proteomic data as biomarkers of environmental pollution has the potential to be of a great interest in ecological risk assessment as they constitute early warning indicators of ecologically relevant effects on biological systems. To develop such specific and sensitive biomarkers, the use of a set of proteins is required and the identification of protein expression signatures (PES) may reflect the exposure to specific classes of pollutants. Using 2D-DIGE (Differential in Gel Electrophoresis) methodology, this study aimed at identifying specific PES on European eel (Anguilla anguilla) peripheral blood mononuclear cells (PBMC) after 48 h in vitro exposure to two sublethal concentrations of dichlorodiphenyltrichloroethane (p,p'-DDT) (10 μg/L and 1mg/L) or cadmium (Cd) (1 μg/L and 100 μg/L). The present results have been supplemented with data of a first in vitro study on cells exposed to perfluorooctane sulfonate (PFOS) (10 μg/L and 1mg/L). A total of thirty-four protein spots, belonging to 18 different identified proteins found in all conditions, have been selected as possible biomarkers to develop a synthetic Integrated Biomarker Proteomic (IBP) index. IBP follows a dose-response relationship with higher values at the highest tested concentration for each pollutant (Cd: 9.96; DDT: 7.44; PFOS: 7.94) compared to the lowest tested concentration (Cd: 3.81; DDT: 2.91; PFOS: 2.06). In a second step, star plot graphs have been applied to proteomic data in order to allow visual integration of a set of early warning responses measured with protein biomarkers. Such star plots permit to discriminate the type of pollutant inducing a proteomic response. We conclude that using IBP is relevant in environmental risk assessment, giving to this index the potential to be applied as a global index of proteome alteration in endangered species such as the European eel. In this study, 34 protein spots have been selected as possible biomarkers to develop a synthetic Integrated

  20. Characterization of potential ionizing radiation biomarkers by a proteomic approach

    Energy Technology Data Exchange (ETDEWEB)

    Guipaud, O; Vereycken-Holler, V; Benderitter, M [Institut de Radioprotection et de Surete Nucleaire, Lab. de Radiopathologie, 92 - Fontenay aux Roses (France); Royer, N; Vinh, J [Ecole Superieure de Physique et de Chimie Industrielles, 75 - Paris (France)

    2006-07-01

    Radio-induced lesions are tissue specific, hardly predictable, and can arise months or years later. The finding of prognostic bio-markers is of fundamental relevance for the settlement of therapeutic or preventive strategies. Using two-dimensional gel electrophoresis and mass spectrometry, a proteomic study was applied to look for differentially expressed proteins, i.e. potential bio-markers candidates, in mouse serums after a local irradiation of the dorsal skin. Our results clearly indicated that serum protein content was dynamically modified after a local skin irradiation. A set of specific proteins were early down- or up-regulated and could turn out to be good candidates as diagnostic or prognostic bio-markers. (author)

  1. Characterization of potential ionizing radiation biomarkers by a proteomic approach

    International Nuclear Information System (INIS)

    Guipaud, O.; Vereycken-Holler, V.; Benderitter, M.; Royer, N.; Vinh, J.

    2006-01-01

    Radio-induced lesions are tissue specific, hardly predictable, and can arise months or years later. The finding of prognostic bio-markers is of fundamental relevance for the settlement of therapeutic or preventive strategies. Using two-dimensional gel electrophoresis and mass spectrometry, a proteomic study was applied to look for differentially expressed proteins, i.e. potential bio-markers candidates, in mouse serums after a local irradiation of the dorsal skin. Our results clearly indicated that serum protein content was dynamically modified after a local skin irradiation. A set of specific proteins were early down- or up-regulated and could turn out to be good candidates as diagnostic or prognostic bio-markers. (author)

  2. Identification of 10 Candidate Biomarkers Distinguishing Tuberculous and Malignant Pleural Fluid by Proteomic Methods

    OpenAIRE

    Lee, Chang Youl; Hong, Ji Young; Lee, Myung-Goo; Suh, In-Bum

    2017-01-01

    Purpose Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. Materials and Methods We used samples from five patients with t...

  3. Proteomic identification of host and parasite biomarkers in saliva from patients with uncomplicated Plasmodium falciparum malaria

    Directory of Open Access Journals (Sweden)

    Huang Honglei

    2012-05-01

    Full Text Available Abstract Background Malaria cases attributed to Plasmodium falciparum account for approximately 600,000 deaths yearly, mainly in African children. The gold standard method to diagnose malaria requires the visualization of the parasite in blood. The role of non-invasive diagnostic methods to diagnose malaria remains unclear. Methods A protocol was optimized to deplete highly abundant proteins from saliva to improve the dynamic range of the proteins identified and assess their suitability as candidate biomarkers of malaria infection. A starch-based amylase depletion strategy was used in combination with four different lectins to deplete glycoproteins (Concanavalin A and Aleuria aurantia for N-linked glycoproteins; jacalin and peanut agglutinin for O-linked glycoproteins. A proteomic analysis of depleted saliva samples was performed in 17 children with fever and a positive–malaria slide and compared with that of 17 malaria-negative children with fever. Results The proteomic signature of malaria-positive patients revealed a strong up-regulation of erythrocyte-derived and inflammatory proteins. Three P. falciparum proteins, PFL0480w, PF08_0054 and PFI0875w, were identified in malaria patients and not in controls. Aleuria aurantia and jacalin showed the best results for parasite protein identification. Conclusions This study shows that saliva is a suitable clinical specimen for biomarker discovery. Parasite proteins and several potential biomarkers were identified in patients with malaria but not in patients with other causes of fever. The diagnostic performance of these markers should be addressed prospectively.

  4. Urinary proteomic biomarkers for diagnosis and risk stratification of autosomal dominant polycystic kidney disease: a multicentric study.

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    Andreas D Kistler

    Full Text Available Treatment options for autosomal dominant polycystic kidney disease (ADPKD will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS, we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI. The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001 with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD.

  5. [Search for potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry].

    Science.gov (United States)

    Shevchenko, V E; Arnotskaia, N E; Ogorodnikova, E V; Davydov, M M; Ibraev, M A; Turkin, I N; Davydov, M I

    2014-01-01

    Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1-17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.

  6. Exhaled Breath Condensate for Proteomic Biomarker Discovery

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    Sean W. Harshman

    2014-07-01

    Full Text Available Exhaled breath condensate (EBC has been established as a potential source of respiratory biomarkers. Compared to the numerous small molecules identified, the protein content of EBC has remained relatively unstudied due to the methodological and technical difficulties surrounding EBC analysis. In this review, we discuss the proteins identified in EBC, by mass spectrometry, focusing on the significance of those proteins identified. We will also review the limitations surrounding mass spectral EBC protein analysis emphasizing recommendations to enhance EBC protein identifications by mass spectrometry. Finally, we will provide insight into the future directions of the EBC proteomics field.

  7. Proteomic workflow for analysis of archival formalin-fixed and paraffin-embedded clinical samples to a depth of 10 000 proteins.

    Science.gov (United States)

    Wiśniewski, Jacek R; Duś, Kamila; Mann, Matthias

    2013-04-01

    Archival formalin-fixed and paraffin-embedded clinical samples represent a very diverse source of material for proteomic investigation of diseases, often with follow-up patient information. Here, we describe an analytical workflow for analysis of laser-capture microdissected formalin-fixed and paraffin-embedded samples that allows studying proteomes to a depth of 10 000 proteins per sample. The workflow involves lysis of tissue in SDS-containing buffer, detergent removal, and consecutive digestion of the proteins with two enzymes by the multienzyme digestion filter-aided sample preparation method. Resulting peptides are fractionated by pipette-tip based strong anion exchange into six fractions and analyzed by LC-MS/MS on a bench top quadrupole Orbitrap mass spectrometer. Analysis of the data using the MaxQuant software resulted in the identification of 9502 ± 28 protein groups per a 110 nL sample of microdissected cells from human colonic adenoma. This depth of proteome analysis enables systemic insights into the organization of the adenoma cells and an estimation of the abundances of known biomarkers. It also allows the identification of proteins expressed from tumor suppressors, oncogenes, and other key players in the development and progression of the colorectal cancer. Our proteomic platform can be used for quantitative comparisons between samples representing different stages of diseases and thus can be applied to the discovery of biomarkers or drug targets. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Proteomics analysis after traumatic brain injury in rats: the search for potential biomarkers

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    Jun Ding

    2015-04-01

    Full Text Available Many studies of protein expression after traumatic brain injury (TBI have identified biomarkers for diagnosing or determining the prognosis of TBI. In this study, we searched for additional protein markers of TBI using a fluid perfusion impact device to model TBI in S-D rats. Two-dimensional gel electrophoresis and mass spectrometry were used to identify differentially expressed proteins. After proteomic analysis, we detected 405 and 371 protein spots within a pH range of 3-10 from sham-treated and contused brain cortex, respectively. Eighty protein spots were differentially expressed in the two groups and 20 of these proteins were identified. This study validated the established biomarkers of TBI and identified potential biomarkers that could be examined in future work.

  9. High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

    Science.gov (United States)

    Lin, Lin; Zheng, Jiaxin; Yu, Quan; Chen, Wendong; Xing, Jinchun; Chen, Chenxi; Tian, Ruijun

    2018-03-01

    Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application

  10. The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

    Directory of Open Access Journals (Sweden)

    Pierre-Olivier Gaudreau

    2016-01-01

    Full Text Available Prostate cancer (PC is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development.

  11. Proteomic analysis identifies galectin-1 as a predictive biomarker for relapsed/refractory disease in classical Hodgkin lymphoma

    DEFF Research Database (Denmark)

    Kamper, Peter; Ludvigsen, Maja; Bendix, Knud

    2011-01-01

    Considerable effort has been spent identifying prognostic biomarkers in classic Hodgkin lymphoma (cHL). The aim of our study was to search for possible prognostic parameters in advanced-stage cHL using a proteomics-based strategy. A total of 14 cHL pretreatment tissue samples from younger, advanced......-stage patients were included. Patients were grouped according to treatment response. Proteins that were differentially expressed between the groups were analyzed using 2D-PAGE and identified by liquid chromatography mass spectrometry. Selected proteins were validated using Western blot analysis. One...

  12. PeptideManager: A Peptide Selection Tool for Targeted Proteomic Studies Involving Mixed Samples from Different Species

    Directory of Open Access Journals (Sweden)

    Kevin eDemeure

    2014-09-01

    Full Text Available The search for clinically useful protein biomarkers using advanced mass spectrometry approaches represents a major focus in cancer research. However, the direct analysis of human samples may be challenging due to limited availability, the absence of appropriate control samples, or the large background variability observed in patient material. As an alternative approach, human tumors orthotopically implanted into a different species (xenografts are clinically relevant models that have proven their utility in pre-clinical research. Patient derived xenografts for glioblastoma have been extensively characterized in our laboratory and have been shown to retain the characteristics of the parental tumor at the phenotypic and genetic level. Such models were also found to adequately mimic the behavior and treatment response of human tumors. The reproducibility of such xenograft models, the possibility to identify their host background and perform tumor-host interaction studies, are major advantages over the direct analysis of human samples.At the proteome level, the analysis of xenograft samples is challenged by the presence of proteins from two different species which, depending on tumor size, type or location, often appear at variable ratios. Any proteomics approach aimed at quantifying proteins within such samples must consider the identification of species specific peptides in order to avoid biases introduced by the host proteome. Here, we present an in-house methodology and tool developed to select peptides used as surrogates for protein candidates from a defined proteome (e.g., human in a host proteome background (e.g., mouse, rat suited for a mass spectrometry analysis. The tools presented here are applicable to any species specific proteome, provided a protein database is available. By linking the information from both proteomes, PeptideManager significantly facilitates and expedites the selection of peptides used as surrogates to analyze

  13. Time- and radiation-dose dependent changes in the plasma proteome after total body irradiation of non-human primates: Implications for biomarker selection.

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    Stephanie D Byrum

    Full Text Available Acute radiation syndrome (ARS is a complex multi-organ disease resulting from total body exposure to high doses of radiation. Individuals can be exposed to total body irradiation (TBI in a number of ways, including terrorist radiological weapons or nuclear accidents. In order to determine whether an individual has been exposed to high doses of radiation and needs countermeasure treatment, robust biomarkers are needed to estimate radiation exposure from biospecimens such as blood or urine. In order to identity such candidate biomarkers of radiation exposure, high-resolution proteomics was used to analyze plasma from non-human primates following whole body irradiation (Co-60 at 6.7 Gy and 7.4 Gy with a twelve day observation period. A total of 663 proteins were evaluated from the plasma proteome analysis. A panel of plasma proteins with characteristic time- and dose-dependent changes was identified. In addition to the plasma proteomics study reported here, we recently identified candidate biomarkers using urine from these same non-human primates. From the proteomic analysis of both plasma and urine, we identified ten overlapping proteins that significantly differentiate both time and dose variables. These shared plasma and urine proteins represent optimal candidate biomarkers of radiation exposure.

  14. Comparative Tissue Proteomics of Microdissected Specimens Reveals Novel Candidate Biomarkers of Bladder Cancer*

    Science.gov (United States)

    Chen, Chien-Lun; Chung, Ting; Wu, Chih-Ching; Ng, Kwai-Fong; Yu, Jau-Song; Tsai, Cheng-Han; Chang, Yu-Sun; Liang, Ying; Tsui, Ke-Hung; Chen, Yi-Ting

    2015-01-01

    More than 380,000 new cases of bladder cancer are diagnosed worldwide, accounting for ∼150,200 deaths each year. To discover potential biomarkers of bladder cancer, we employed a strategy combining laser microdissection, isobaric tags for relative and absolute quantitation labeling, and liquid chromatography-tandem MS (LC-MS/MS) analysis to profile proteomic changes in fresh-frozen bladder tumor specimens. Cellular proteins from four pairs of surgically resected primary bladder cancer tumor and adjacent nontumorous tissue were extracted for use in two batches of isobaric tags for relative and absolute quantitation experiments, which identified a total of 3220 proteins. A DAVID (database for annotation, visualization and integrated discovery) analysis of dysregulated proteins revealed that the three top-ranking biological processes were extracellular matrix organization, extracellular structure organization, and oxidation-reduction. Biological processes including response to organic substances, response to metal ions, and response to inorganic substances were highlighted by up-expressed proteins in bladder cancer. Seven differentially expressed proteins were selected as potential bladder cancer biomarkers for further verification. Immunohistochemical analyses showed significantly elevated levels of three proteins—SLC3A2, STMN1, and TAGLN2—in tumor cells compared with noncancerous bladder epithelial cells, and suggested that TAGLN2 could be a useful tumor tissue marker for diagnosis (AUC = 0.999) and evaluating lymph node metastasis in bladder cancer patients. ELISA results revealed significantly increased urinary levels of both STMN1 and TAGLN2 in bladder cancer subgroups compared with control groups. In comparisons with age-matched hernia urine specimens, urinary TAGLN2 in bladder cancer samples showed the largest fold change (7.13-fold), with an area-under-the-curve value of 0.70 (p < 0.001, n = 205). Overall, TAGLN2 showed the most significant

  15. Urine Proteomics in the Era of Mass Spectrometry

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    Ashley Beasley-Green

    2016-11-01

    Full Text Available With the technological advances of mass spectrometry (MS-based platforms, clinical proteomics is one of the most rapidly growing areas in biomedical research. Urine proteomics has become a popular subdiscipline of clinical proteomics because it is an ideal source for the discovery of noninvasive disease biomarkers. The urine proteome offers a comprehensive view of the local and systemic physiology since the proteome is primarily composed of proteins/peptides from the kidneys and plasma. The emergence of MS-based proteomic platforms as prominent bioanalytical tools in clinical applications has enhanced the identification of protein-based urinary biomarkers. This review highlights the characteristics of urine that make it an attractive biofluid for biomarker discovery and the impact of MS-based technologies on the clinical assessment of urinary protein biomarkers.

  16. A Selected Reaction Monitoring Mass Spectrometry Protocol for Validation of Proteomic Biomarker Candidates in Studies of Psychiatric Disorders.

    Science.gov (United States)

    Reis-de-Oliveira, Guilherme; Garcia, Sheila; Guest, Paul C; Cassoli, Juliana S; Martins-de-Souza, Daniel

    2017-01-01

    Most biomarker candidates arising from proteomic studies of psychiatric disorders have not progressed for use in clinical studies due to insufficient validation steps. Here we describe a selective reaction monitoring mass spectrometry (SRM-MS) approach that could be used as a follow-up validation tool of proteins identified in blood serum or plasma. This protocol specifically covers the stages of peptide selection and optimization. The increasing application of SRM-MS should enable fast, sensitive, and robust methods with the potential for use in clinical studies involving sampling of serum or plasma. Understanding the molecular mechanisms and identifying potential biomarkers for risk assessment, diagnosis, prognosis, and prediction of drug response goes toward the implementation of translational medicine strategies for improved treatment of patients with psychiatric disorders and other debilitating diseases.

  17. A novel proteomic biomarker panel as a diagnostic tool for patients with ovarian cancer

    DEFF Research Database (Denmark)

    Høgdall, Claus; Fung, Eric T; Christensen, Ib J

    2011-01-01

    Previous reports have shown that the proteomic markers apolipoprotein A1, hepcidin, transferrin, inter-alpha trypsin IV internal fragment, transthyretin, connective-tissue activating protein 3 and beta-2 microglobulin may discriminate between a benign pelvic mass and ovarian cancer (OC). The aim...... was to determine if these serum proteomic biomarkers alone as well as in combination with age and serum CA125, could be helpful in triage of women with a pelvic mass....

  18. Identification of candidate diagnostic serum biomarkers for Kawasaki disease using proteomic analysis

    Science.gov (United States)

    Kimura, Yayoi; Yanagimachi, Masakatsu; Ino, Yoko; Aketagawa, Mao; Matsuo, Michie; Okayama, Akiko; Shimizu, Hiroyuki; Oba, Kunihiro; Morioka, Ichiro; Imagawa, Tomoyuki; Kaneko, Tetsuji; Yokota, Shumpei; Hirano, Hisashi; Mori, Masaaki

    2017-01-01

    Kawasaki disease (KD) is a systemic vasculitis and childhood febrile disease that can lead to cardiovascular complications. The diagnosis of KD depends on its clinical features, and thus it is sometimes difficult to make a definitive diagnosis. In order to identify diagnostic serum biomarkers for KD, we explored serum KD-related proteins, which differentially expressed during the acute and recovery phases of two patients by mass spectrometry (MS). We identified a total of 1,879 proteins by MS-based proteomic analysis. The levels of three of these proteins, namely lipopolysaccharide-binding protein (LBP), leucine-rich alpha-2-glycoprotein (LRG1), and angiotensinogen (AGT), were higher in acute phase patients. In contrast, the level of retinol-binding protein 4 (RBP4) was decreased. To confirm the usefulness of these proteins as biomarkers, we analyzed a total of 270 samples, including those collected from 55 patients with acute phase KD, by using western blot analysis and microarray enzyme-linked immunosorbent assays (ELISAs). Over the course of this experiment, we determined that the expression level of these proteins changes specifically in the acute phase of KD, rather than the recovery phase of KD or other febrile illness. Thus, LRG1 could be used as biomarkers to facilitate KD diagnosis based on clinical features. PMID:28262744

  19. Protein corona as a proteome fingerprint: The example of hidden biomarkers for cow mastitis.

    Science.gov (United States)

    Miotto, Giovanni; Magro, Massimiliano; Terzo, Milo; Zaccarin, Mattia; Da Dalt, Laura; Bonaiuto, Emanuela; Baratella, Davide; Gabai, Gianfranco; Vianello, Fabio

    2016-04-01

    Proteome modifications in a biological fluid can potentially indicate the occurrence of pathologies, even if the identification of a proteome fingerprint correlated to a specific disease represents a very difficult task. When a nanomaterial is introduced into a biological fluid, macromolecules compete to form a protein corona on the nanoparticle surface, and depending on the specific proteome, different patterns of proteins will form the final protein corona shell depending on their affinity for the nanoparticle surface. Novel surface active maghemite nanoparticles (SAMNs) display a remarkable selectivity toward protein corona formation, and they are able to concentrate proteins and peptides presenting high affinities for their surface even if they are present in very low amounts. Thus, SAMNs may confer visibility to hidden biomarkers correlated to the occurrence of a pathology. In the present report, SAMNs were introduced into milk samples from healthy cows and from animals affected by mastitis, and the selectively bound protein corona shell was easily analyzed and quantified by gel electrophoresis and characterized by mass spectrometry. Upon incubation in mastitic milk, SAMNs were able to selectively bind αs2-casein fragments containing the FALPQYLK sequence, as part of the larger casocidin-1 peptide with strong antibacterial activity, which were not present in healthy samples. Thus, SAMNs can be used as a future candidate for the rapid diagnosis of mastitis in bovine milk. The present report proposes protein competition for SAMN protein corona formation as a means of mirroring proteome modifications. Thus, the selected protein shell on the nanoparticles results in a fingerprint of the specific pathology. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Glyco-centric lectin magnetic bead array (LeMBA − proteomics dataset of human serum samples from healthy, Barrett׳s esophagus and esophageal adenocarcinoma individuals

    Directory of Open Access Journals (Sweden)

    Alok K. Shah

    2016-06-01

    Full Text Available This data article describes serum glycoprotein biomarker discovery and qualification datasets generated using lectin magnetic bead array (LeMBA – mass spectrometry techniques, “Serum glycoprotein biomarker discovery and qualification pipeline reveals novel diagnostic biomarker candidates for esophageal adenocarcinoma” [1]. Serum samples collected from healthy, metaplastic Barrett׳s esophagus (BE and esophageal adenocarcinoma (EAC individuals were profiled for glycoprotein subsets via differential lectin binding. The biomarker discovery proteomics dataset consisting of 20 individual lectin pull-downs for 29 serum samples with a spiked-in internal standard chicken ovalbumin protein has been deposited in the PRIDE partner repository of the ProteomeXchange Consortium with the data set identifier PRIDE: http://www.ebi.ac.uk/pride/archive/projects/PXD002442. Annotated MS/MS spectra for the peptide identifications can be viewed using MS-Viewer (〈http://prospector2.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msviewer〉 using search key “jn7qafftux”. The qualification dataset contained 6-lectin pulldown-coupled multiple reaction monitoring-mass spectrometry (MRM-MS data for 41 protein candidates, from 60 serum samples. This dataset is available as a supplemental files with the original publication [1].

  1. Infectious Disease Proteome Biomarkers: Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, Charles L.

    2011-12-31

    Research for the DOE Infectious Disease Proteome Biomarkers focused on Rift Valley fever virus (RVFV) and Venezuelan Equine Encephalitis Virus (VEEV). RVFV and VEEV are Category A and B pathogens respectively. Among the priority threats, RVFV and VEEV rank high in their potential for being weaponized and introduced to the United States, spreading quickly, and having a large health and economic impact. In addition, they both have live attenuated vaccine, which allows work to be performed at BSL-2. While the molecular biology of RVFV and VEEV are increasingly well-characterized, little is known about its host-pathogen interactions. Our research is aimed at determining critical alterations in host signaling pathways to identify therapeutics targeted against the host.

  2. Differential Proteomics Identification of HSP90 as Potential Serum Biomarker in Hepatocellular Carcinoma by Two-dimensional Electrophoresis and Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Yiyi Sun

    2010-03-01

    Full Text Available The aim of the current study is to identify the potential biomarkers involved in Hepatocellular carcinoma (HCC carcinogenesis. A comparative proteomics approach was utilized to identify the differentially expressed proteins in the serum of 10 HCC patients and 10 controls. A total of 12 significantly altered proteins were identified by mass spectrometry. Of the 12 proteins identified, HSP90 was one of the most significantly altered proteins and its over-expression in the serum of 20 HCC patients was confirmed using ELISA analysis. The observations suggest that HSP90 might be a potential biomarker for early diagnosis, prognosis, and monitoring in the therapy of HCC. This work demonstrates that a comprehensive strategy of proteomic identification combined with further validation should be adopted in the field of cancer biomarker discovery.

  3. Regional differences of the urinary proteomes in healthy Chinese individuals

    OpenAIRE

    Qin, Weiwei; Wu, Jianqiang; Pan, Li; Zhang, Fanshuang; Wang, Xiaorong; Zhang, Biao; Shan, Guangliang; Gao, Youhe

    2017-01-01

    Urine is a promising biomarker source for clinical proteomics studies. Although regional physiological differences are common in multi-center clinical studies, the presence of significant differences in the urinary proteomes of individuals from different regions remains unknown. In this study, morning urine samples were collected from healthy urban residents in three regions of China and urinary proteins were preserved using a membrane-based method (Urimem). The urine proteomes of 27 normal s...

  4. Gel-free proteomics reveal potential biomarkers of priming-induced salt tolerance in durum wheat.

    Science.gov (United States)

    Fercha, Azzedine; Capriotti, Anna Laura; Caruso, Giuseppe; Cavaliere, Chiara; Gherroucha, Hocine; Samperi, Roberto; Stampachiacchiere, Serena; Lagana, Aldo

    2013-10-08

    Seed priming has been successfully demonstrated to be an efficient method to improve crop productivity under stressful conditions. As a first step toward better understanding of the mechanisms underlying the priming-induced salt stress tolerance in durum wheat, and to overcome the limitations of the gel-based approach, a comparative gel-free proteomic analysis was conducted with durum wheat seed samples of varying vigor as generated by hydro- and ascorbate-priming treatments. Results indicate that hydro-priming was accompanied by significant changes of 72 proteins, most of which are involved in proteolysis, protein synthesis, metabolism and disease/defense response. Ascorbate-priming was, however, accompanied by significant changes of 83 proteins, which are mainly involved in protein metabolism, antioxidant protection, repair processes and, interestingly, in methionine-related metabolism. The present study provides new information for understanding how 'priming-memory' invokes seed stress tolerance. The current work describes the first study in which gel-free shotgun proteomics were used to investigate the metabolic seed protein fraction in durum wheat. A combined approach of protein fractionation, hydrogel nanoparticle enrichment technique, and gel-free shotgun proteomic analysis allowed us to identify over 380 proteins exhibiting greater molecular weight diversity (ranging from 7 to 258kDa). Accordingly, we propose that this approach could be useful to acquire a wider perspective and a better understanding of the seed proteome. In the present work, we employed this method to investigate the potential biomarkers of priming-induced salt tolerance in durum wheat. In this way, we identified several previously unrecognized proteins which were never been reported before, particularly for the ascorbate-priming treatment. These findings could provide new avenues for improving crop productivity, particularly under unfavorable environmental conditions. © 2013.

  5. Mass Spectrometry-Based Biomarker Discovery.

    Science.gov (United States)

    Zhou, Weidong; Petricoin, Emanuel F; Longo, Caterina

    2017-01-01

    The discovery of candidate biomarkers within the entire proteome is one of the most important and challenging goals in proteomic research. Mass spectrometry-based proteomics is a modern and promising technology for semiquantitative and qualitative assessment of proteins, enabling protein sequencing and identification with exquisite accuracy and sensitivity. For mass spectrometry analysis, protein extractions from tissues or body fluids and subsequent protein fractionation represent an important and unavoidable step in the workflow for biomarker discovery. Following extraction of proteins, the protein mixture must be digested, reduced, alkylated, and cleaned up prior to mass spectrometry. The aim of our chapter is to provide comprehensible and practical lab procedures for sample digestion, protein fractionation, and subsequent mass spectrometry analysis.

  6. Detecting differential protein expression in large-scale population proteomics

    Energy Technology Data Exchange (ETDEWEB)

    Ryu, Soyoung; Qian, Weijun; Camp, David G.; Smith, Richard D.; Tompkins, Ronald G.; Davis, Ronald W.; Xiao, Wenzhong

    2014-06-17

    Mass spectrometry-based high-throughput quantitative proteomics shows great potential in clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, methods are needed to appropriately handle issues/challenges unique to mass spectrometry data in order to detect as many biomarker proteins as possible. One issue is that different mass spectrometry experiments generate quite different total numbers of quantified peptides, which can result in more missing peptide abundances in an experiment with a smaller total number of quantified peptides. Another issue is that the quantification of peptides is sometimes absent, especially for less abundant peptides and such missing values contain the information about the peptide abundance. Here, we propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients’ sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data.

  7. Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Duijvesz, Diederick; Burnum-Johnson, Kristin E.; Gritsenko, Marina A.; Hoogland, Marije; Vredenbregt-van den Berg, Mirella S.; Willemsen, Rob; Luider, Theo N.; Pasa-Tolic, Ljiljana; Jenster, Guido

    2013-12-31

    Introduction: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, biomarker discovery from body fluids is often hampered by the high abundance of many proteins unrelated to disease. An attractive alternative biomarker discovery approach is the isolation of small vesicles (exosomes, ~100 nm). They contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific marker discovery. Profiling prostate cancer-derived exosomes could reveal new markers for this malignancy. Materials and Methods: Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. Proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode, followed by the Accurate Mass and Time (AMT) tag approach. Exosomal proteins were validated by Western blotting. A Tissue Micro Array, containing 481 different PCa samples (radical prostatectomy), was used to correlate candidate markers with several clinical-pathological parameters such as PSA, Gleason score, biochemical recurrence, and (PCa-related) death. Results: Proteomic characterization resulted in the identification of 263 proteins by at least 2 peptides. Specifically analysis of exosomes from PNT2C2, RWPE-1, PC346C, and VCaP identified 248, 233, 169, and 216 proteins, respectively. Statistical analyses revealed 52 proteins differently expressed between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes. The Tissue Micro 4 Array showed strong correlation of higher Gleason scores and local recurrence with increased cytoplasmic XPO1 (P<0.001). Conclusions: Differentially abundant proteins of cell line-derived exosomes make a clear subdivision between

  8. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

    OpenAIRE

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M

    2014-01-01

    Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectom...

  9. A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

    Science.gov (United States)

    Reis, Henning; Pütter, Carolin; Megger, Dominik A; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-C; Bertram, Stefanie; Wohlschläger, Jeremias; Hagemann, Sascha; Eisenacher, Martin; Scherag, André; Schlaak, Jörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

    2015-06-01

    Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. One Sample, One Shot - Evaluation of sample preparation protocols for the mass spectrometric proteome analysis of human bile fluid without extensive fractionation

    NARCIS (Netherlands)

    Megger, D.A.; Padden, J.; Rosowski, K.; Uszkoreit, J.; Bracht, T.; Eisenacher, M.; Gerges, C.; Neuhaus, H.; Schumacher, B.; Schlaak, J.F.; Sitek, B.

    2017-01-01

    The proteome analysis of bile fluid represents a promising strategy to identify biomarker candidates for various diseases of the hepatobiliary system. However, to obtain substantive results in biomarker discovery studies large patient cohorts necessarily need to be analyzed. Consequently, this would

  11. The Proteome of Primary Prostate Cancer

    DEFF Research Database (Denmark)

    Iglesias-Gato, Diego; Wikström, Pernilla; Tyanova, Stefka

    2016-01-01

    for disease aggressiveness. DESIGN, SETTING, AND PARTICIPANTS: Mass spectrometry was used for genome-scale quantitative proteomic profiling of 28 prostate tumors (Gleason score 6-9) and neighboring nonmalignant tissue in eight cases, obtained from formalin-fixed paraffin-embedded prostatectomy samples. Two...... changes occurring during prostate cancer (PCa) initiation and progression can result in clinically relevant discoveries. OBJECTIVES: To study cellular processes altered in PCa using system-wide quantitative analysis of changes in protein expression in clinical samples and to identify prognostic biomarkers......BACKGROUND: Clinical management of the prostate needs improved prognostic tests and treatment strategies. Because proteins are the ultimate effectors of most cellular reactions, are targets for drug actions and constitute potential biomarkers; a quantitative systemic overview of the proteome...

  12. Adapting mass spectrometry-based platforms for clinical proteomics applications: The capillary electrophoresis coupled mass spectrometry paradigm

    Science.gov (United States)

    Metzger, Jochen; Luppa, Peter B.; Good, David M.; Mischak, Harald

    2018-01-01

    Single biomarker detection is common in clinical laboratories due to the currently available method spectrum. For various diseases, however, no specific single biomarker could be identified. A strategy to overcome this diagnostic void is to shift from single analyte detection to multiplexed biomarker profiling. Mass spectrometric methods were employed for biomarker discovery in body fluids. The enormous complexity of biofluidic proteome compartments implies upstream fractionation. For this reason, mass spectrometry (MS) was coupled to two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization, or capillary electrophoresis (CE). Differences in performance and operating characteristics make them differentially suited for routine laboratory applications. Progress in the field of clinical proteomics relies not only on the use of an adequate technological platform, but also on a fast and efficient proteomic workflow including standardized sample preparation, proteomic data processing, statistical validation of biomarker selection, and sample classification. Based on CE-MS analysis, we describe how proteomic technology can be implemented in a clinical laboratory environment. In the last part of this review, we give an overview of CE-MS-based clinical studies and present information on identity and biological significance of the identified peptide biomarkers providing evidence of disease-induced changes in proteolytic processing and posttranslational modification. PMID:19404829

  13. Quantitative Tissue Proteomics Analysis Reveals Versican as Potential Biomarker for Early-Stage Hepatocellular Carcinoma.

    Science.gov (United States)

    Naboulsi, Wael; Megger, Dominik A; Bracht, Thilo; Kohl, Michael; Turewicz, Michael; Eisenacher, Martin; Voss, Don Marvin; Schlaak, Jörg F; Hoffmann, Andreas-Claudius; Weber, Frank; Baba, Hideo A; Meyer, Helmut E; Sitek, Barbara

    2016-01-04

    Hepatocellular carcinoma (HCC) is one of the most aggressive tumors, and the treatment outcome of this disease is improved when the cancer is diagnosed at an early stage. This requires biomarkers allowing an accurate and early tumor diagnosis. To identify potential markers for such applications, we analyzed a patient cohort consisting of 50 patients (50 HCC and 50 adjacent nontumorous tissue samples as controls) using two independent proteomics approaches. We performed label-free discovery analysis on 19 HCC and corresponding tissue samples. The data were analyzed considering events known to take place in early events of HCC development, such as abnormal regulation of Wnt/b-catenin and activation of receptor tyrosine kinases (RTKs). 31 proteins were selected for verification experiments. For this analysis, the second set of the patient cohort (31 HCC and corresponding tissue samples) was analyzed using selected (multiple) reaction monitoring (SRM/MRM). We present the overexpression of ATP-dependent RNA helicase (DDX39), Fibulin-5 (FBLN5), myristoylated alanine-rich C-kinase substrate (MARCKS), and Serpin H1 (SERPINH1) in HCC for the first time. We demonstrate Versican core protein (VCAN) to be significantly associated with well differentiated and low-stage HCC. We revealed for the first time the evidence of VCAN as a potential biomarker for early-HCC diagnosis.

  14. Mass spectrometry for biomarker development

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Chaochao; Liu, Tao; Baker, Erin Shammel; Rodland, Karin D.; Smith, Richard D.

    2015-06-19

    Biomarkers potentially play a crucial role in early disease diagnosis, prognosis and targeted therapy. In the past decade, mass spectrometry based proteomics has become increasingly important in biomarker development due to large advances in technology and associated methods. This chapter mainly focuses on the application of broad (e.g. shotgun) proteomics in biomarker discovery and the utility of targeted proteomics in biomarker verification and validation. A range of mass spectrometry methodologies are discussed emphasizing their efficacy in the different stages in biomarker development, with a particular emphasis on blood biomarker development.

  15. A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

    Science.gov (United States)

    Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

    2017-07-01

    Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

  16. Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer.

    Science.gov (United States)

    Song, Yimeng; Zhong, Lijun; Zhou, Juntuo; Lu, Min; Xing, Tianying; Ma, Lulin; Shen, Jing

    2017-12-01

    Renal cell carcinoma (RCC) is a malignant and metastatic cancer with 95% mortality, and clear cell RCC (ccRCC) is the most observed among the five major subtypes of RCC. Specific biomarkers that can distinguish cancer tissues from adjacent normal tissues should be developed to diagnose this disease in early stages and conduct a reliable prognostic evaluation. Data-independent acquisition (DIA) strategy has been widely employed in proteomic analysis because of various advantages, including enhanced protein coverage and reliable data acquisition. In this study, a DIA workflow is constructed on a quadrupole-Orbitrap LC-MS platform to reveal dysregulated proteins between ccRCC and adjacent normal tissues. More than 4000 proteins are identified, 436 of these proteins are dysregulated in ccRCC tissues. Bioinformatic analysis reveals that multiple pathways and Gene Ontology items are strongly associated with ccRCC. The expression levels of L-lactate dehydrogenase A chain, annexin A4, nicotinamide N-methyltransferase, and perilipin-2 examined through RT-qPCR, Western blot, and immunohistochemistry confirm the validity of the proteomic analysis results. The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  18. Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation.

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

    Full Text Available Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS for CSF biomarker discovery by (1 identifying reparable sources of technical variability, (2 assessing subject variance and residual technical variability for numerous CSF proteins, and (3 testing its ability to segregate samples on the basis of desired biomarker characteristics.Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i incomplete MAF and keratins; ii globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5% whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and

  19. Identification of Potential Plasma Biomarkers for Nonalcoholic Fatty Liver Disease by Integrating Transcriptomics and Proteomics in Laying Hens.

    Science.gov (United States)

    Tsai, Meng-Tsz; Chen, Yu-Jen; Chen, Ching-Yi; Tsai, Mong-Hsun; Han, Chia-Li; Chen, Yu-Ju; Mersmann, Harry J; Ding, Shih-Torng

    2017-03-01

    Background: Prevalent worldwide obesity is associated with increased incidence of nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome. The identification of noninvasive biomarkers for NAFLD is of recent interest. Because primary de novo lipogenesis occurs in chicken liver as in human liver, adult chickens with age-associated steatosis resembling human NAFLD is an appealing animal model. Objective: The objective of this study was to screen potential biomarkers in the chicken model for NAFLD by transcriptomic and proteomic analysis. Methods: Hy-Line W-36 laying hens were fed standard feed from 25 to 45 wk of age to induce fatty liver. They were killed every 4 wk, and liver and plasma were collected at each time point to assess fatty liver development and for transcriptomic and proteomic analysis. Next, selected biomarkers were confirmed in additional experiments by providing supplements of the hepatoprotective nutrients betaine [300, 600, or 900 parts per million (ppm) in vivo; 2 mM in vitro] or docosahexaenoic acid (DHA; 1% in vivo; 100 μM in vitro) to 30-wk-old Hy-Line W-36 laying hens for 4 mo and to Hy-Line W-36 chicken primary hepatocytes with oleic acid-induced steatosis. Liver or hepatocyte lipid contents and the expression of biomarkers were then examined. Results: Plasma acetoacetyl-CoA synthetase (AACS), dipeptidyl-peptidase 4 (DPP4), glutamine synthetase (GLUL), and glutathione S -transferase (GST) concentrations are well-established biomarkers for NAFLD. Selected biomarkers had significant positive associations with hepatic lipid deposition ( P steatosis accompanied by the reduced expression of selected biomarkers in vivo and in vitro ( P < 0.05). Conclusion: This study used adult laying hens to identify biomarkers for NAFLD and indicated that AACS, DPP4, GLUL, and GST could be considered to be potential diagnostic indicators for NAFLD in the future. © 2017 American Society for Nutrition.

  20. Proteomic analyses of host and pathogen responses during bovine mastitis.

    Science.gov (United States)

    Boehmer, Jamie L

    2011-12-01

    The pursuit of biomarkers for use as clinical screening tools, measures for early detection, disease monitoring, and as a means for assessing therapeutic responses has steadily evolved in human and veterinary medicine over the past two decades. Concurrently, advances in mass spectrometry have markedly expanded proteomic capabilities for biomarker discovery. While initial mass spectrometric biomarker discovery endeavors focused primarily on the detection of modulated proteins in human tissues and fluids, recent efforts have shifted to include proteomic analyses of biological samples from food animal species. Mastitis continues to garner attention in veterinary research due mainly to affiliated financial losses and food safety concerns over antimicrobial use, but also because there are only a limited number of efficacious mastitis treatment options. Accordingly, comparative proteomic analyses of bovine milk have emerged in recent years. Efforts to prevent agricultural-related food-borne illness have likewise fueled an interest in the proteomic evaluation of several prominent strains of bacteria, including common mastitis pathogens. The interest in establishing biomarkers of the host and pathogen responses during bovine mastitis stems largely from the need to better characterize mechanisms of the disease, to identify reliable biomarkers for use as measures of early detection and drug efficacy, and to uncover potentially novel targets for the development of alternative therapeutics. The following review focuses primarily on comparative proteomic analyses conducted on healthy versus mastitic bovine milk. However, a comparison of the host defense proteome of human and bovine milk and the proteomic analysis of common veterinary pathogens are likewise introduced.

  1. Preparation of the low molecular weight serum proteome for mass spectrometry analysis.

    Science.gov (United States)

    Waybright, Timothy J; Chan, King C; Veenstra, Timothy D; Xiao, Zhen

    2013-01-01

    The discovery of viable biomarkers or indicators of disease states is complicated by the inherent complexity of the chosen biological specimen. Every sample, whether it is serum, plasma, urine, tissue, cells, or a host of others, contains thousands of large and small components, each interacting in multiple ways. The need to concentrate on a group of these components to narrow the focus on a potential biomarker candidate becomes, out of necessity, a priority, especially in the search for immune-related low molecular weight serum biomarkers. One such method in the field of proteomics is to divide the sample proteome into groups based on the size of the protein, analyze each group, and mine the data for statistically significant items. This chapter details a portion of this method, concentrating on a method for fractionating and analyzing the low molecular weight proteome of human serum.

  2. Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

    Science.gov (United States)

    Barkla, Bronwyn J

    2016-09-08

    Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

  3. Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

    Directory of Open Access Journals (Sweden)

    Bronwyn J. Barkla

    2016-09-01

    Full Text Available Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

  4. Effects of Three Commonly-used Diuretics on the Urinary Proteome

    Directory of Open Access Journals (Sweden)

    Xundou Li

    2014-06-01

    Full Text Available Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography–tandem mass spectrometry (LC–MS/MS. Based on the criteria of P ⩽ 0.05, a fold change ⩾2, a spectral count ⩾5, and false positive rate (FDR ⩽1%, 14 proteins (seven for F, five for H, and two for S were identified by Progenesis LC–MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics.

  5. Effects of three commonly-used diuretics on the urinary proteome.

    Science.gov (United States)

    Li, Xundou; Zhao, Mindi; Li, Menglin; Jia, Lulu; Gao, Youhe

    2014-06-01

    Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the criteria of P≤0.05, a fold change ≥2, a spectral count ≥5, and false positive rate (FDR) ≤1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC-MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. Copyright © 2014. Production and hosting by Elsevier Ltd.

  6. Identification of Novel Translational Urinary Biomarkers for Acetaminophen-Induced Acute Liver Injury Using Proteomic Profiling in Mice

    NARCIS (Netherlands)

    van Swelm, Rachel P. L.; Laarakkers, Coby M. M.; van der Kuur, Ellen C.; Morava-Kozicz, Eva; Wevers, Ron A.; Augustijn, Kevin D.; Touw, Daan J.; Sandel, Maro H.; Masereeuw, Rosalinde; Russel, Frans G. M.

    2012-01-01

    Drug-induced liver injury (DILI) is the leading cause of acute liver failure. Currently, no adequate predictive biomarkers for DILI are available. This study describes a translational approach using proteomic profiling for the identification of urinary proteins related to acute liver injury induced

  7. Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics

    Directory of Open Access Journals (Sweden)

    Sorette M

    2004-12-01

    Full Text Available Abstract Background Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. Results Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. Conclusion The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings.

  8. Integrative analysis to select cancer candidate biomarkers to targeted validation

    Science.gov (United States)

    Heberle, Henry; Domingues, Romênia R.; Granato, Daniela C.; Yokoo, Sami; Canevarolo, Rafael R.; Winck, Flavia V.; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Filgueiras, Paulo R.; Cruz, Karen S. P.; Barbuto, José Alexandre; Poppi, Ronei J.; Minghim, Rosane; Telles, Guilherme P.; Fonseca, Felipe Paiva; Fox, Jay W.; Santos-Silva, Alan R.; Coletta, Ricardo D.; Sherman, Nicholas E.; Paes Leme, Adriana F.

    2015-01-01

    Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS. PMID:26540631

  9. Quantitative proteomic analysis for novel biomarkers of buccal squamous cell carcinoma arising in background of oral submucous fibrosis

    International Nuclear Information System (INIS)

    Liu, Wen; Zeng, Lijuan; Li, Ning; Wang, Fei; Jiang, Canhua; Guo, Feng; Chen, Xinqun; Su, Tong; Xu, Chunjiao; Zhang, Shanshan; Fang, Changyun

    2016-01-01

    In South and Southeast Asian, the majority of buccal squamous cell carcinoma (BSCC) can arise from oral submucous fibrosis (OSF). BSCCs develop in OSF that are often not completely resected, causing local relapse. The aim of our study was to find candidate protein biomarkers to detect OSF and predict prognosis in BSCCs by quantitative proteomics approaches. We compared normal oral mucosa (NBM) and paired biopsies of BSCC and OSF by quantitative proteomics using isobaric tags for relative and absolute quantification (iTRAQ) to discover proteins with differential expression. Gene Ontology and KEGG networks were analyzed. The prognostic value of biomarkers was evaluated in 94 BSCCs accompanied with OSF. Significant associations were assessed by Kaplan-Meier survival and Cox-proportional hazards analysis. In total 30 proteins were identified with significantly different expression (false discovery rate < 0.05) among three tissues. Two consistently upregulated proteins, ANXA4 and FLNA, were validated. The disease-free survival was negatively associated with the expression of ANXA4 (hazard ratio, 3.4; P = 0.000), FLNA (hazard ratio, 2.1; P = 0.000) and their combination (hazard ratio, 8.8; P = 0.002) in BSCCs. The present study indicates that iTRAQ quantitative proteomics analysis for tissues of BSCC and OSF is a reliable strategy. A significantly up-regulated ANXA4 and FLNA could be not only candidate biomarkers for BSCC prognosis but also potential targets for its therapy. The online version of this article (doi:10.1186/s12885-016-2650-1) contains supplementary material, which is available to authorized users

  10. Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

    DEFF Research Database (Denmark)

    Overgaard, Anne Julie; Thingholm, Tine Engberg; Larsen, Martin R

    2010-01-01

    INTRODUCTION: As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy. METHODS: Proteins derived from plasma from a cross-sectional co...... nephropathy; however, they need to be confirmed in a longitudinal cohort. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12014-010-9053-0) contains supplementary material, which is available to authorized users....

  11. Serum quantitative proteomic analysis reveals potential zinc-associated biomarkers for nonbacterial prostatitis.

    Science.gov (United States)

    Yang, Xiaoli; Li, Hongtao; Zhang, Chengdong; Lin, Zhidi; Zhang, Xinhua; Zhang, Youjie; Yu, Yanbao; Liu, Kun; Li, Muyan; Zhang, Yuening; Lv, Wenxin; Xie, Yuanliang; Lu, Zheng; Wu, Chunlei; Teng, Ruobing; Lu, Shaoming; He, Min; Mo, Zengnan

    2015-10-01

    Prostatitis is one of the most common urological problems afflicting adult men. The etiology and pathogenesis of nonbacterial prostatitis, which accounts for 90-95% of cases, is largely unknown. As serum proteins often indicate the overall pathologic status of patients, we hypothesized that protein biomarkers of prostatitis might be identified by comparing the serum proteomes of patients with and without nonbacterial prostatitis. All untreated samples were collected from subjects attending the Fangchenggang Area Male Health and Examination Survey (FAMHES). We profiled pooled serum samples from four carefully selected groups of patients (n = 10/group) representing the various categories of nonbacterial prostatitis (IIIa, IIIb, and IV) and matched healthy controls using a mass spectrometry-based 4-plex iTRAQ proteomic approach. More than 160 samples were validated by ELISA. Overall, 69 proteins were identified. Among them, 42, 52, and 37 proteins were identified with differential expression in Category IIIa, IIIb, and IV prostatitis, respectively. The 19 common proteins were related to immunity and defense, ion binding, transport, and proteolysis. Two zinc-binding proteins, superoxide dismutase 3 (SOD3), and carbonic anhydrase I (CA1), were significantly higher in all types of prostatitis than in the control. A receiver operating characteristic curve estimated sensitivities of 50.4 and 68.1% and specificities of 92.1 and 83.8% for CA1 and SOD3, respectively, in detecting nonbacterial prostatitis. The serum CA1 concentration was inversely correlated to the zinc concentration in expressed-prostatic secretions. Our findings suggest that SOD3 and CA1 are potential diagnostic markers of nonbacterial prostatitis, although further large-scale studies are required. The molecular profiles of nonbacterial prostatitis pathogenesis may lay a foundation for discovery of new therapies. © 2015 Wiley Periodicals, Inc.

  12. The distinctive gastric fluid proteome in gastric cancer reveals a multi-biomarker diagnostic profile

    Directory of Open Access Journals (Sweden)

    Eng Alvin KH

    2008-10-01

    Full Text Available Abstract Background Overall gastric cancer survival remains poor mainly because there are no reliable methods for identifying highly curable early stage disease. Multi-protein profiling of gastric fluids, obtained from the anatomic site of pathology, could reveal diagnostic proteomic fingerprints. Methods Protein profiles were generated from gastric fluid samples of 19 gastric cancer and 36 benign gastritides patients undergoing elective, clinically-indicated gastroscopy using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry on multiple ProteinChip arrays. Proteomic features were compared by significance analysis of microarray algorithm and two-way hierarchical clustering. A second blinded sample set (24 gastric cancers and 29 clinically benign gastritides was used for validation. Results By significance analysyis of microarray, 60 proteomic features were up-regulated and 46 were down-regulated in gastric cancer samples (p Conclusion This simple and reproducible multimarker proteomic assay could supplement clinical gastroscopic evaluation of symptomatic patients to enhance diagnostic accuracy for gastric cancer and pre-malignant lesions.

  13. Proteomics and metabolomics in ageing research: from biomarkers to systems biology.

    Science.gov (United States)

    Hoffman, Jessica M; Lyu, Yang; Pletcher, Scott D; Promislow, Daniel E L

    2017-07-15

    Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible 'biomarkers', which are predictors of one's biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying 'endophenotypes' in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  14. Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

    Full Text Available Abstract The field of proteomics has made leaps and bounds in the last 10 years particularly in the fields of oncology and cardiovascular medicine. In comparison, neuroproteomics is still playing catch up mainly due to the relative complexity of neurological disorders. Schizophrenia is one such disorder, believed to be the results of multiple factors both genetic and environmental. Affecting over 2 million people in the US alone, it has become a major clinical and public health concern worldwide. This paper gives an update of schizophrenia biomarker research as reviewed by Lakhan in 2006 and gives us a rundown of the progress made during the last two years. Several studies demonstrate the potential of cerebrospinal fluid as a source of neuro-specific biomarkers. Genetic association studies are making headway in identifying candidate genes for schizophrenia. In addition, metabonomics, bioinformatics, and neuroimaging techniques are aiming to complete the picture by filling in knowledge gaps. International cooperation in the form of genomics and protein databases and brain banks is facilitating research efforts. While none of the recent developments described here in qualifies as biomarker discovery, many are likely to be stepping stones towards that goal.

  15. Identification of azurocidin as a potential periodontitis biomarker by a proteomic analysis of gingival crevicular fluid

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    Lee Jae-Mok

    2011-07-01

    Full Text Available Abstract Background The inflammatory disease periodontitis results in tooth loss and can even lead to diseases of the whole body if not treated. Gingival crevicular fluid (GCF reflects the condition of the gingiva and contains proteins transuded from serum or cells at inflamed sites. In this study, we aimed to discover potential protein biomarkers for periodontitis in GCF proteome using LC-MS/MS. Results We identified 305 proteins from GCF of healthy individuals and periodontitis patients collected using a sterile gel loading tip by ESI-MS/MS coupled to nano-LC. Among these proteins, about 45 proteins were differentially expressed in the GCF proteome of moderate periodontitis patients when compared to the healthy individuals. We first identified azurocidin in the GCF, but not the saliva, as an upregulated protein in the periodontitis patients and verified its increased expression during periodontitis by ELISA using the GCF of the classified periodontitis patients compared to the healthy individuals. In addition, we found that azurocidin inhibited the differentiation of bone marrow-derived macrophages to osteoclasts. Conclusions Our results show that GCF collection using a gel loading tip and subsequent LC-MS/MS analysis following 1D-PAGE proteomic separation are effective for the analysis of the GCF proteome. Our current results also suggest that azurocidin could be a potential biomarker candidate for the early detection of inflammatory periodontal destruction by gingivitis and some chronic periodontitis. Our data also suggest that azurocidin may have an inhibitory role in osteoclast differentiation and, thus, a protective role in alveolar bone loss during the early stages of periodontitis.

  16. Comparative proteomic analysis of human malignant ascitic fluids for the development of gastric cancer biomarkers.

    Science.gov (United States)

    Jin, Jonghwa; Son, Minsoo; Kim, Hyeyoon; Kim, Hyeyeon; Kong, Seong-Ho; Kim, Hark Kyun; Kim, Youngsoo; Han, Dohyun

    2018-04-11

    Malignant ascites is a sign of peritoneal seeding, which is one of the most frequent forms of incurable distant metastasis. Because the development of malignant ascites is associated with an extremely poor prognosis, determining whether it resulted from peritoneal seeding has critical clinical implications in diagnosis, choice of treatment, and active surveillance. At present, the molecular characterizations of malignant ascites are especially limited in case of gastric cancer. We aimed to identify malignant ascites-specific proteins that may contribute to the development of alternative methods for diagnosis and therapeutic monitoring and also increase our understanding of the pathophysiology of peritoneal seeding. First, comprehensive proteomic strategies were employed to construct an in-depth proteome of ascitic fluids. Label-free quantitative proteomic analysis was subsequently performed to identify candidates that can differentiate between malignant ascitic fluilds of gastric cancer patients from benign ascitic fluids. Finally, two candidate proteins were verified by ELISA in 84 samples with gastric cancer or liver cirrhosis. Comprehensive proteome profiling resulted in the identification of 5347 ascites proteins. Using label-free quantification, we identified 299 proteins that were differentially expressed in ascitic fluids between liver cirrhosis and stage IV gastric cancer patients. In addition, we identified 645 proteins that were significantly expressed in ascitic fluids between liver cirrhosis and gastric cancer patients with peritoneal seeding. Finally, Gastriscin and Periostin that can distinguish malignant ascites from benign ascites were verified by ELISA. This study identified and verified protein markers that can distinguish malignant ascites with or without peritoneal seeding from benign ascites. Consequently, our results could be a significant resource for gastric cancer research and biomarker discovery in the diagnosis of malignant ascites

  17. Tear film proteome in age-related macular degeneration.

    Science.gov (United States)

    Winiarczyk, Mateusz; Kaarniranta, Kai; Winiarczyk, Stanisław; Adaszek, Łukasz; Winiarczyk, Dagmara; Mackiewicz, Jerzy

    2018-06-01

    Age-related macular degeneration (AMD) is the main reason for blindness in elderly people in the developed countries. Current screening protocols have limitations in detecting the early signs of retinal degeneration. Therefore, it would be desirable to find novel biomarkers for early detection of AMD. Development of novel biomarkers would help in the prevention, diagnostics, and treatment of AMD. Proteomic analysis of tear film has shown promise in this research area. If an optimal set of biomarkers could be obtained from accessible body fluids, it would represent a reliable way to monitor disease progression and response to novel therapies. Tear films were collected on Schirmer strips from a total of 22 patients (8 with wet AMD, 6 with dry AMD, and 8 control individuals). 2D electrophoresis was used to separate tear film proteins prior to their identification with matrix-assisted laser desorption/ionization time of flight spectrometer (MALDI-TOF/TOF) and matching with functional databases. A total of 342 proteins were identified. Most of them were previously described in various proteomic studies concerning AMD. Shootin-1, histatin-3, fidgetin-like protein 1, SRC kinase signaling inhibitor, Graves disease carrier protein, actin cytoplasmic 1, prolactin-inducible protein 1, and protein S100-A7A were upregulated in the tear film samples isolated from AMD patients and were not previously linked with this disease in any proteomic analysis. The upregulated proteins supplement our current knowledge of AMD pathogenesis, providing evidence that certain specific proteins are expressed into the tear film in AMD. As far we are aware, this is the first study to have undertaken a comprehensive in-depth analysis of the human tear film proteome in AMD patients.

  18. Urinary proteomics to support diagnosis of stroke.

    Directory of Open Access Journals (Sweden)

    Jesse Dawson

    Full Text Available Accurate diagnosis in suspected ischaemic stroke can be difficult. We explored the urinary proteome in patients with stroke (n = 69, compared to controls (n = 33, and developed a biomarker model for the diagnosis of stroke. We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Potentially disease-specific peptides were identified and a classifier based on these was generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. We developed two biomarker-based classifiers, employing 14 biomarkers (nominal p-value <0.004 or 35 biomarkers (nominal p-value <0.01. When tested on a blinded test set of 47 independent samples, the classification factor was significantly different between groups; for the 35 biomarker model, median value of the classifier was 0.49 (-0.30 to 1.25 in cases compared to -1.04 (IQR -1.86 to -0.09 in controls, p<0.001. The 35 biomarker classifier gave sensitivity of 56%, specificity was 93% and the AUC on ROC analysis was 0.86. This study supports the potential for urinary proteomic biomarker models to assist with the diagnosis of acute stroke in those with mild symptoms. We now plan to refine further and explore the clinical utility of such a test in large prospective clinical trials.

  19. Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

    Science.gov (United States)

    Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

    2018-05-15

    Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several

  20. A novel method for sample preparation of fresh lung cancer tissue for proteomics analysis by tumor cell enrichment and removal of blood contaminants

    Directory of Open Access Journals (Sweden)

    Orre Lotta

    2010-02-01

    was an effective removal of contaminants from red blood cells and plasma proteins resulting in larger proteome coverage compared to the direct lysis of frozen samples. This sample preparation method may be successfully implemented for the discovery of lung cancer biomarkers on tissue samples using mass spectrometry-based proteomics.

  1. Mass spectrometry for protein quantification in biomarker discovery.

    Science.gov (United States)

    Wang, Mu; You, Jinsam

    2012-01-01

    Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

  2. Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

    Science.gov (United States)

    Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana; Hu, Shen

    2017-01-01

    Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients' saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects ( p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

  3. Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

    Science.gov (United States)

    Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

    2018-03-01

    In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Comprehensive proteomic analysis of human pancreatic juice

    DEFF Research Database (Denmark)

    Grønborg, Mads; Bunkenborg, Jakob; Kristiansen, Troels Zakarias

    2004-01-01

    Proteomic technologies provide an excellent means for analysis of body fluids for cataloging protein constituents and identifying biomarkers for early detection of cancers. The biomarkers currently available for pancreatic cancer, such as CA19-9, lack adequate sensitivity and specificity...... contributing to late diagnosis of this deadly disease. In this study, we carried out a comprehensive characterization of the "pancreatic juice proteome" in patients with pancreatic adenocarcinoma. Pancreatic juice was first fractionated by 1-dimensional gel electrophoresis and subsequently analyzed by liquid...... in this study could be directly assessed for their potential as biomarkers for pancreatic cancer by quantitative proteomics methods or immunoassays....

  5. Mining novel biomarkers for prognosis of gastric cancer with serum proteomics

    Directory of Open Access Journals (Sweden)

    Sui Mei-Hua

    2009-09-01

    Full Text Available Abstract Background Although gastric caner (GC remains the second cause of cancer-related death, useful biomarkers for prognosis are still unavailable. We present here the attempt of mining novel biomarkers for GC prognosis by using serum proteomics. Methods Sera from 43 GC patients and 41 controls with gastritis as Group 1 and 11 GC patients as Group 2 was successively detected by Surface Enhanced Laser Desorption/ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS with Q10 chip. Peaks were acquired by Ciphergen ProteinChip Software 3.2.0 and analyzed by Zhejiang University-ProteinChip Data Analysis System (ZJU-PDAS. CEA level were evaluated by chemiluminescence immunoassay. Results After median follow-up periods of 33 months, Group 1 with 4 GC patients lost was divided into 20 good-prognosis GC patients (overall survival more than 24 months and 19 poor-prognosis GC patients (no more than 24 months. The established prognosis pattern consisted of 5 novel prognosis biomarkers with 84.2% sensitivity and 85.0% specificity, which were significantly higher than those of carcinoembryonic antigen (CEA and TNM stage. We also tested prognosis pattern blindly in Group 2 with 66.7% sensitivity and 80.0% specificity. Moreover, we found that 4474-Da peak elevated significantly in GC and was associated with advanced stage (III+IV and short survival (p Conclusion We have identified a number of novel biomarkers for prognosis prediction of GC by using SELDI-TOF-MS combined with sophisticated bioinformatics. Particularly, elevated expression of 4474-Da peak showed very promising to be developed into a novel biomarker associated with biologically aggressive features of GC.

  6. Dried Blood Spot Proteomics: Surface Extraction of Endogenous Proteins Coupled with Automated Sample Preparation and Mass Spectrometry Analysis

    Science.gov (United States)

    Martin, Nicholas J.; Bunch, Josephine; Cooper, Helen J.

    2013-08-01

    Dried blood spots offer many advantages as a sample format including ease and safety of transport and handling. To date, the majority of mass spectrometry analyses of dried blood spots have focused on small molecules or hemoglobin. However, dried blood spots are a potentially rich source of protein biomarkers, an area that has been overlooked. To address this issue, we have applied an untargeted bottom-up proteomics approach to the analysis of dried blood spots. We present an automated and integrated method for extraction of endogenous proteins from the surface of dried blood spots and sample preparation via trypsin digestion by use of the Advion Biosciences Triversa Nanomate robotic platform. Liquid chromatography tandem mass spectrometry of the resulting digests enabled identification of 120 proteins from a single dried blood spot. The proteins identified cross a concentration range of four orders of magnitude. The method is evaluated and the results discussed in terms of the proteins identified and their potential use as biomarkers in screening programs.

  7. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.

    2015-12-04

    Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.

  8. Novel ageing-biomarker discovery using data-intensive technologies.

    Science.gov (United States)

    Griffiths, H R; Augustyniak, E M; Bennett, S J; Debacq-Chainiaux, F; Dunston, C R; Kristensen, P; Melchjorsen, C J; Navarrete, Santos A; Simm, A; Toussaint, O

    2015-11-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for biomarker discovery; (1) microarray analyses and/or proteomics in cell systems e.g. endothelial progenitor cells or T cell ageing including a stress model; and (2) investigation of cellular material and plasma directly from tightly-defined proband subsets of different ages using proteomic, transcriptomic and miR array. The first approach provided longitudinal insight into endothelial progenitor and T cell ageing. This review describes the strategy and use of hypothesis-free, data-intensive approaches to explore cellular proteins, miR, mRNA and plasma proteins as healthy ageing biomarkers, using ageing models and directly within samples from adults of different ages. It considers the challenges associated with integrating multiple models and pilot studies as rational biomarkers for a large cohort study. From this approach, a number of high-throughput methods were developed to evaluate novel, putative biomarkers of ageing in the MARK-AGE cohort. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

  9. Advances of Proteomic Sciences in Dentistry.

    Science.gov (United States)

    Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur

    2016-05-13

    Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.

  10. Application of Proteomics and Peptidomics to COPD

    Directory of Open Access Journals (Sweden)

    Girolamo Pelaia

    2014-01-01

    Full Text Available Chronic obstructive pulmonary disease (COPD is a complex disorder involving both airways and lung parenchyma, usually associated with progressive and poorly reversible airflow limitation. In order to better characterize the phenotypic heterogeneity and the prognosis of patients with COPD, there is currently an urgent need for discovery and validation of reliable disease biomarkers. Within this context, proteomic and peptidomic techniques are emerging as very valuable tools that can be applied to both systemic and pulmonary samples, including peripheral blood, induced sputum, exhaled breath condensate, bronchoalveolar lavage fluid, and lung tissues. Identification of COPD biomarkers by means of proteomic and peptidomic approaches can thus also lead to discovery of new molecular targets potentially useful to improve and personalize the therapeutic management of this widespread respiratory disease.

  11. Mining the granule proteome

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Goetze, Jens P; Johnsen, Anders H

    2015-01-01

    Proteomics of secretory granules is an emerging strategy for identifying secreted proteins, including potentially novel candidate biomarkers and peptide hormones. In addition, proteomics can provide information about the abundance, localization and structure (post-translational modification) of g...

  12. Comparative proteomics in alkaptonuria provides insights into inflammation and oxidative stress.

    Science.gov (United States)

    Braconi, Daniela; Bernardini, Giulia; Paffetti, Alessandro; Millucci, Lia; Geminiani, Michela; Laschi, Marcella; Frediani, Bruno; Marzocchi, Barbara; Santucci, Annalisa

    2016-12-01

    Alkaptonuria (AKU) is an ultra-rare inborn error of metabolism associated with a defective catabolism of phenylalanine and tyrosine leading to increased systemic levels of homogentisic acid (HGA). Excess HGA is partly excreted in the urine, partly accumulated within the body and deposited onto connective tissues under the form of an ochronotic pigment, leading to a range of clinical manifestations. No clear genotype/phenotype correlation was found in AKU, and today there is the urgent need to identify biomarkers able to monitor AKU progression and evaluate response to treatment. With this aim, we provided the first proteomic study on serum and plasma samples from alkaptonuric individuals showing pathological SAA, CRP and Advanced Oxidation Protein Products (AOPP) levels. Interesting similarities with proteomic studies on other rheumatic diseases were highlighted together with proteome alterations supporting the existence of oxidative stress and inflammation in AKU. Potential candidate biomarkers to assess disease severity, monitor disease progression and evaluate response to treatment were identified as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Autoantibody profiling on human proteome microarray for biomarker discovery in cerebrospinal fluid and sera of neuropsychiatric lupus.

    Directory of Open Access Journals (Sweden)

    Chaojun Hu

    Full Text Available Autoantibodies in cerebrospinal fluid (CSF from patients with neuropsychiatric systemic lupus erythematosus (NPSLE may be potential biomarkers for prediction, diagnosis, or prognosis of NPSLE. We used a human proteome microarray with~17,000 unique full-length human proteins to investigate autoantibodies associated with NPSLE. Twenty-nine CSF specimens from 12 NPSLE, 7 non-NPSLE, and 10 control (non-systemic lupus erythematosuspatients were screened for NPSLE-associated autoantibodies with proteome microarrays. A focused autoantigen microarray of candidate NPSLE autoantigens was applied to profile a larger cohort of CSF with patient-matched sera. We identified 137 autoantigens associated with NPSLE. Ingenuity Pathway Analysis revealed that these autoantigens were enriched for functions involved in neurological diseases (score = 43.Anti-proliferating cell nuclear antigen (PCNA was found in the CSF of NPSLE and non-NPSLE patients. The positive rates of 4 autoantibodies in CSF specimens were significantly different between the SLE (i.e., NPSLE and non-NPSLE and control groups: anti-ribosomal protein RPLP0, anti-RPLP1, anti-RPLP2, and anti-TROVE2 (also known as anti-Ro/SS-A. The positive rate for anti-SS-A associated with NPSLE was higher than that for non-NPSLE (31.11% cf. 10.71%; P = 0.045.Further analysis showed that anti-SS-A in CSF specimens was related to neuropsychiatric syndromes of the central nervous system in SLE (P = 0.009. Analysis with Spearman's rank correlation coefficient indicated that the titers of anti-RPLP2 and anti-SS-A in paired CSF and serum specimens significantly correlated. Human proteome microarrays offer a powerful platform to discover novel autoantibodies in CSF samples. Anti-SS-A autoantibodies may be potential CSF markers for NPSLE.

  14. Comprehensive data analysis of human ureter proteome

    Directory of Open Access Journals (Sweden)

    Sameh Magdeldin

    2016-03-01

    Full Text Available Comprehensive human ureter proteome dataset was generated from OFFGel fractionated ureter samples. Our result showed that among 2217 non-redundant ureter proteins, 751 protein candidates (33.8% were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48 that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, Cytoscape GO annotation was examined on the final ureter dataset to better understand proteins molecular function, biological processes, and cellular component. The ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery.

  15. The application of mass-spectrometry-based protein biomarker discovery to theragnostics

    OpenAIRE

    Street, Jonathan M; Dear, James W

    2010-01-01

    Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed ‘theragnostics’). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

  16. Mining the human urine proteome for monitoring renal transplant injury

    Energy Technology Data Exchange (ETDEWEB)

    Sigdel, Tara K.; Gao, Yuqian; He, Jintang; Wang, Anyou; Nicora, Carrie D.; Fillmore, Thomas L.; Shi, Tujin; Webb-Robertson, Bobbie-Jo; Smith, Richard D.; Qian, Wei-Jun; Salvatierra, Oscar; Camp, David G.; Sarwal, Minnie M.

    2016-06-01

    The human urinary proteome reflects systemic and inherent renal injury perturbations and can be analyzed to harness specific biomarkers for different kidney transplant injury states. 396 unique urine samples were collected contemporaneously with an allograft biopsy from 396 unique kidney transplant recipients. Centralized, blinded histology on the graft was used to classify matched urine samples into categories of acute rejection (AR), chronic allograft nephropathy (CAN), BK virus nephritis (BKVN), and stable graft (STA). Liquid chromatography–mass spectrometry (LC-MS) based proteomics using iTRAQ based discovery (n=108) and global label-free LC-MS analyses of individual samples (n=137) for quantitative proteome assessment were used in the discovery step. Selected reaction monitoring (SRM) was applied to identify and validate minimal urine protein/peptide biomarkers to accurately segregate organ injury causation and pathology on unique urine samples (n=151). A total of 958 proteins were initially quantified by iTRAQ, 87% of which were also identified among 1574 urine proteins detected in LC-MS validation. 103 urine proteins were significantly (p<0.05) perturbed in injury and enriched for humoral immunity, complement activation, and lymphocyte trafficking. A set of 131 peptides corresponding to 78 proteins were assessed by SRM for their significance in an independent sample cohort. A minimal set of 35 peptides mapping to 33 proteins, were modeled to segregate different injury groups (AUC =93% for AR, 99% for CAN, 83% for BKVN). Urinary proteome discovery and targeted validation identified urine protein fingerprints for non-invasive differentiation of kidney transplant injuries, thus opening the door for personalized immune risk assessment and therapy.

  17. Network-based analysis of proteomic profiles

    KAUST Repository

    Wong, Limsoon

    2016-01-26

    Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

  18. Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

    International Nuclear Information System (INIS)

    Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M.; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan

    2016-01-01

    Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted

  19. Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

    Energy Technology Data Exchange (ETDEWEB)

    Kulkarni, Shilpa [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Koller, Antonius [Proteomics Center, Stony Brook University School of Medicine, Stony Brook, New York (United States); Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York (United States); Mani, Kartik M. [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Wen, Ruofeng [Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York (United States); Alfieri, Alan; Saha, Subhrajit [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Wang, Jian [Center for Computational Mass Spectrometry, University of California, San Diego, California (United States); Department of Computer Science and Engineering, University of California, San Diego, California (United States); Patel, Purvi [Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York (United States); Department of Pharmacological Sciences, Stony Brook University, Stony Brook, New York (United States); Bandeira, Nuno [Center for Computational Mass Spectrometry, University of California, San Diego, California (United States); Department of Computer Science and Engineering, University of California, San Diego, California (United States); Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, California (United States); Guha, Chandan, E-mail: cguha@montefiore.org [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); and others

    2016-11-01

    Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted

  20. Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

    Science.gov (United States)

    Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

    2015-10-01

    The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

  1. Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer

    Directory of Open Access Journals (Sweden)

    Stobiecki Maciej

    2009-07-01

    Full Text Available Abstract Background Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry. Methods Blood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women. Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other high-molecular-weight serum proteins. Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves. Results We have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients. The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity. Spectral components (i.e., protein ions that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity. Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression. In addition, we observed a significantly (p = 0

  2. PODCAST: From Lost in Translation to Paradise Found: Enabling Protein Biomarker Method Transfer by Mass Spectrometry | Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    Translation of novel biomarkers into clinical care for the evaluation of therapeutic safety and efficacy has been slow, partly attributable to the cost and complexity of immunoassay development.  The potential for liquid chromatography-tandem mass spectrometry (LC-MS/MS) to streamline the translation of novel protein biomarkers is profound.  Drs. Henry Rodriguez and Andrew Hoofnagle discuss what the future may be for clinical proteomics. This is an American Association for Clinical Chemistry (AACC) podcast.

  3. A Method for Microalgae Proteomics Analysis Based on Modified Filter-Aided Sample Preparation.

    Science.gov (United States)

    Li, Song; Cao, Xupeng; Wang, Yan; Zhu, Zhen; Zhang, Haowei; Xue, Song; Tian, Jing

    2017-11-01

    With the fast development of microalgal biofuel researches, the proteomics studies of microalgae increased quickly. A filter-aided sample preparation (FASP) method is widely used proteomics sample preparation method since 2009. Here, a method of microalgae proteomics analysis based on modified filter-aided sample preparation (mFASP) was described to meet the characteristics of microalgae cells and eliminate the error caused by over-alkylation. Using Chlamydomonas reinhardtii as the model, the prepared sample was tested by standard LC-MS/MS and compared with the previous reports. The results showed mFASP is suitable for most of occasions of microalgae proteomics studies.

  4. Prediction of acute coronary syndromes by urinary proteome analysis.

    Directory of Open Access Journals (Sweden)

    Nay M Htun

    Full Text Available Identification of individuals who are at risk of suffering from acute coronary syndromes (ACS may allow to introduce preventative measures. We aimed to identify ACS-related urinary peptides, that combined as a pattern can be used as prognostic biomarker. Proteomic data of 252 individuals enrolled in four prospective studies from Australia, Europe and North America were analyzed. 126 of these had suffered from ACS within a period of up to 5 years post urine sampling (cases. Proteomic analysis of 84 cases and 84 matched controls resulted in the discovery of 75 ACS-related urinary peptides. Combining these to a peptide pattern, we established a prognostic biomarker named Acute Coronary Syndrome Predictor 75 (ACSP75. ACSP75 demonstrated reasonable prognostic discrimination (c-statistic = 0.664, which was similar to Framingham risk scoring (c-statistics = 0.644 in a validation cohort of 42 cases and 42 controls. However, generating by a composite algorithm named Acute Coronary Syndrome Composite Predictor (ACSCP, combining the biomarker pattern ACSP75 with the previously established urinary proteomic biomarker CAD238 characterizing coronary artery disease as the underlying aetiology, and age as a risk factor, further improved discrimination (c-statistic = 0.751 resulting in an added prognostic value over Framingham risk scoring expressed by an integrated discrimination improvement of 0.273 ± 0.048 (P < 0.0001 and net reclassification improvement of 0.405 ± 0.113 (P = 0.0007. In conclusion, we demonstrate that urinary peptide biomarkers have the potential to predict future ACS events in asymptomatic patients. Further large scale studies are warranted to determine the role of urinary biomarkers in clinical practice.

  5. Proteomic-Based Approaches for the Study of Cytokines in Lung Cancer

    Directory of Open Access Journals (Sweden)

    Ángela Marrugal

    2016-01-01

    Full Text Available Proteomic techniques are currently used to understand the biology of different human diseases, including studies of the cell signaling pathways implicated in cancer progression, which is important in knowing the roles of different proteins in tumor development. Due to its poor prognosis, proteomic approaches are focused on the identification of new biomarkers for the early diagnosis, prognosis, and targeted treatment of lung cancer. Cytokines are proteins involved in inflammatory processes and have been proposed as lung cancer biomarkers and therapeutic targets because it has been reported that some cytokines play important roles in tumor development, invasion, and metastasis. In this review, we aim to summarize the different proteomic techniques used to discover new lung cancer biomarkers and therapeutic targets. Several cytokines have been identified as important players in lung cancer using these techniques. We underline the most important cytokines that are useful as biomarkers and therapeutic targets. We also summarize some of the therapeutic strategies targeted for these cytokines in lung cancer.

  6. Proteomics mapping of cord blood identifies haptoglobin "switch-on" pattern as biomarker of early-onset neonatal sepsis in preterm newborns.

    Science.gov (United States)

    Buhimschi, Catalin S; Bhandari, Vineet; Dulay, Antonette T; Nayeri, Unzila A; Abdel-Razeq, Sonya S; Pettker, Christian M; Thung, Stephen; Zhao, Guomao; Han, Yiping W; Bizzarro, Matthew; Buhimschi, Irina A

    2011-01-01

    Intra-amniotic infection and/or inflammation (IAI) are important causes of preterm birth and early-onset neonatal sepsis (EONS). A prompt and accurate diagnosis of EONS is critical for improved neonatal outcomes. We sought to explore the cord blood proteome and identify biomarkers and functional protein networks characterizing EONS in preterm newborns. We studied a prospective cohort of 180 premature newborns delivered May 2004-September 2009. A proteomics discovery phase employing two-dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry identified 19 differentially-expressed proteins in cord blood of newborns with culture-confirmed EONS (n = 3) versus GA-matched controls (n = 3). Ontological classifications of the proteins included transfer/carrier, immunity/defense, protease/extracellular matrix. The 1(st)-level external validation conducted in the remaining 174 samples confirmed elevated haptoglobin and haptoglobin-related protein immunoreactivity (Hp&HpRP) in newborns with EONS (presumed and culture-confirmed) independent of GA at birth and birthweight (PLCA) was further used for unbiased classification of all 180 cases based on probability of "antenatal IAI exposure" as latent variable. This was then subjected to 2(nd)-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. This approach reclassified ∼30% of clinical EONS diagnoses lowering the number needed to harm and increasing the odds ratios for several adverse outcomes including intra-ventricular hemorrhage. Antenatal exposure to IAI results in precocious switch-on of Hp&HpRP expression. As EONS biomarker, cord blood Hp&HpRP has potential to improve the selection of newborns for prompt and targeted treatment at birth.

  7. Quantitative proteomic analysis by iTRAQ® for the identification of candidate biomarkers in ovarian cancer serum

    Directory of Open Access Journals (Sweden)

    Higgins LeeAnn

    2010-06-01

    Full Text Available Abstract Background Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ®. Results Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified. Conclusions This study provides the first analysis of immunodepleted serum in combination with iTRAQ® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

  8. Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Campos, Benito; Winther, Ole

    2014-01-01

    directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found......Background: The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic....... Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature...

  9. Current and Future Applications of Biomedical Engineering for Proteomic Profiling: Predictive Biomarkers in Neuro-Traumatology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers in patients with traumatic brain injury (TBI, a critical worldwide health problem with an estimated 10 billion people affected annually worldwide. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials. Only experimental articles revolving around the management of TBI, in which the role of new devices based on innovative discoveries coming from the field of nanotechnology and biomedical engineering were highlighted, have been included and analyzed in this study. Based on theresults gathered from this research on innovative methods for genomics, epigenomics, and proteomics, their future application in this field seems promising. Despite the outstanding technical challenges of identifying reliable biosignatures for TBI and the mixed nature of studies herein described (single cells proteomics, biofilms, sensors, etc., the clinical implementation of those discoveries will allow us to gain confidence in the use of advanced neuromonitoring modalities with a potential dramatic improvement in the management of those patients.

  10. Cross-sample validation provides enhanced proteome coverage in rat vocal fold mucosa.

    Directory of Open Access Journals (Sweden)

    Nathan V Welham

    2011-03-01

    Full Text Available The vocal fold mucosa is a biomechanically unique tissue comprised of a densely cellular epithelium, superficial to an extracellular matrix (ECM-rich lamina propria. Such ECM-rich tissues are challenging to analyze using proteomic assays, primarily due to extensive crosslinking and glycosylation of the majority of high M(r ECM proteins. In this study, we implemented an LC-MS/MS-based strategy to characterize the rat vocal fold mucosa proteome. Our sample preparation protocol successfully solubilized both proteins and certain high M(r glycoconjugates and resulted in the identification of hundreds of mucosal proteins. A straightforward approach to the treatment of protein identifications attributed to single peptide hits allowed the retention of potentially important low abundance identifications (validated by a cross-sample match and de novo interpretation of relevant spectra while still eliminating potentially spurious identifications (global single peptide hits with no cross-sample match. The resulting vocal fold mucosa proteome was characterized by a wide range of cellular and extracellular proteins spanning 12 functional categories.

  11. Proteomic and metabolomic biomarkers for III-V semiconductors: And prospects for application to nano-materials

    International Nuclear Information System (INIS)

    Fowler, Bruce A.; Conner, Elizabeth A.; Yamauchi, Hiroshi

    2008-01-01

    There has been an increased appreciation over the last 20 years that chemical agents at very low dose levels can produce biological responses in protein expression patterns (proteomic responses) or alterations in sensitive metabolic pathways (metabolomic responses). Marked improvements in analytical methodologies, such as 2-D gel electrophoresis, matrix-assisted laser desorption-time of flight (MALDI-TOF) and surface enhanced laser desorption-time of flight (SELDI-TOF) technologies are capable of identifying specific protein patterns related to exposure to chemicals either alone or as mixtures. The detection and interpretation of early cellular responses to chemical agents have also made great advances through correlative ultrastructural morphometric and biochemical studies. Similarly, advances in analytical technologies such as HPLC, proton NMR, MALDI-TOF, and SELDI-TOF have permitted early detection of changes in a number of essential metabolic pathways following chemical exposures by measurement of alterations in metabolic products from those pathways. Data from these approaches are increasingly regarded as potentially useful biomarkers of chemical exposure and early cellular responses. Validation and establishment of linkages to biological outcomes are needed in order for biomarkers of effect to be established. This short review will cover a number of the above techniques and report data from chemical exposures to two binary III-V semiconductor compounds to illustrate gender differences in proteomic responses. In addition, the use of these methodologies in relation to rapid safety evaluations of nanotechnology products will be discussed. (Supported in part by NIH R01-ES4879)

  12. A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples

    Directory of Open Access Journals (Sweden)

    Rígel Licier

    2016-10-01

    Full Text Available The proper handling of samples to be analyzed by mass spectrometry (MS can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

  13. A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples.

    Science.gov (United States)

    Licier, Rígel; Miranda, Eric; Serrano, Horacio

    2016-10-17

    The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

  14. Proteomics Mapping of Cord Blood Identifies Haptoglobin “Switch-On” Pattern as Biomarker of Early-Onset Neonatal Sepsis in Preterm Newborns

    Science.gov (United States)

    Buhimschi, Catalin S.; Bhandari, Vineet; Dulay, Antonette T.; Nayeri, Unzila A.; Abdel-Razeq, Sonya S.; Pettker, Christian M.; Thung, Stephen; Zhao, Guomao; Han, Yiping W.; Bizzarro, Matthew; Buhimschi, Irina A.

    2011-01-01

    Background Intra-amniotic infection and/or inflammation (IAI) are important causes of preterm birth and early-onset neonatal sepsis (EONS). A prompt and accurate diagnosis of EONS is critical for improved neonatal outcomes. We sought to explore the cord blood proteome and identify biomarkers and functional protein networks characterizing EONS in preterm newborns. Methodology/Principal Findings We studied a prospective cohort of 180 premature newborns delivered May 2004-September 2009. A proteomics discovery phase employing two-dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry identified 19 differentially-expressed proteins in cord blood of newborns with culture-confirmed EONS (n = 3) versus GA-matched controls (n = 3). Ontological classifications of the proteins included transfer/carrier, immunity/defense, protease/extracellular matrix. The 1st-level external validation conducted in the remaining 174 samples confirmed elevated haptoglobin and haptoglobin-related protein immunoreactivity (Hp&HpRP) in newborns with EONS (presumed and culture-confirmed) independent of GA at birth and birthweight (PLCA) was further used for unbiased classification of all 180 cases based on probability of “antenatal IAI exposure” as latent variable. This was then subjected to 2nd-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. This approach reclassified ∼30% of clinical EONS diagnoses lowering the number needed to harm and increasing the odds ratios for several adverse outcomes including intra-ventricular hemorrhage. Conclusions/Significance Antenatal exposure to IAI results in precocious switch-on of Hp&HpRP expression. As EONS biomarker, cord blood Hp&HpRP has potential to improve the

  15. Application of Fluorescence Two-Dimensional Difference In-Gel Electrophoresis as a Proteomic Biomarker Discovery Tool in Muscular Dystrophy Research

    Science.gov (United States)

    Carberry, Steven; Zweyer, Margit; Swandulla, Dieter; Ohlendieck, Kay

    2013-01-01

    In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue. PMID:24833232

  16. Characterization of Foodborne Strains of Staphylococcus aureus by Shotgun Proteomics: Functional Networks, Virulence Factors and Species-Specific Peptide Biomarkers

    Science.gov (United States)

    Carrera, Mónica; Böhme, Karola; Gallardo, José M.; Barros-Velázquez, Jorge; Cañas, Benito; Calo-Mata, Pilar

    2017-01-01

    In the present work, we applied a shotgun proteomics approach for the fast and easy characterization of 20 different foodborne strains of Staphylococcus aureus (S. aureus), one of the most recognized foodborne pathogenic bacteria. A total of 644 non-redundant proteins were identified and analyzed via an easy and rapid protein sample preparation procedure. The results allowed the differentiation of several proteome datasets from the different strains (common, accessory, and unique datasets), which were used to determine relevant functional pathways and differentiate the strains into different Euclidean hierarchical clusters. Moreover, a predicted protein-protein interaction network of the foodborne S. aureus strains was created. The whole confidence network contains 77 nodes and 769 interactions. Most of the identified proteins were surface-associated proteins that were related to pathways and networks of energy, lipid metabolism and virulence. Twenty-seven virulence factors were identified, and most of them corresponded to autolysins, N-acetylmuramoyl-L-alanine amidases, phenol-soluble modulins, extracellular fibrinogen-binding proteins and virulence factor EsxA. Potential species-specific peptide biomarkers were screened. Twenty-one species-specific peptide biomarkers, belonging to eight different proteins (nickel-ABC transporter, N-acetylmuramoyl-L-alanine amidase, autolysin, clumping factor A, gram-positive signal peptide YSIRK, cysteine protease/staphopain, transcriptional regulator MarR, and transcriptional regulator Sar-A), were proposed to identify S. aureus. These results constitute the first major dataset of peptides and proteins of foodborne S. aureus strains. This repository may be useful for further studies, for the development of new therapeutic treatments for S. aureus food intoxications and for microbial source-tracking in foodstuffs. PMID:29312172

  17. Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective.

    Science.gov (United States)

    Findeisen, Peter; Neumaier, Michael

    2009-01-01

    Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

  18. Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Ying; Zhao, Rui; Piehowski, Paul D.; Moore, Ronald J.; Lim, Sujung; Orphan, Victoria J.; Paša-Tolić, Ljiljana; Qian, Wei-Jun; Smith, Richard D.; Kelly, Ryan T.

    2018-04-01

    One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.

  19. Peripheral biomarkers revisited: integrative profiling of peripheral samples for psychiatric research.

    Science.gov (United States)

    Hayashi-Takagi, Akiko; Vawter, Marquis P; Iwamoto, Kazuya

    2014-06-15

    Peripheral samples, such as blood and skin, have been used for decades in psychiatric research as surrogates for central nervous system samples. Although the validity of the data obtained from peripheral samples has been questioned and other state-of-the-art techniques, such as human brain imaging, genomics, and induced pluripotent stem cells, seem to reduce the value of peripheral cells, accumulating evidence has suggested that revisiting peripheral samples is worthwhile. Here, we re-evaluate the utility of peripheral samples and argue that establishing an understanding of the common signaling and biological processes in the brain and peripheral samples is required for the validity of such models. First, we present an overview of the available types of peripheral cells and describe their advantages and disadvantages. We then briefly summarize the main achievements of omics studies, including epigenome, transcriptome, proteome, and metabolome analyses, as well as the main findings of functional cellular assays, the results of which imply that alterations in neurotransmission, metabolism, the cell cycle, and the immune system may be partially responsible for the pathophysiology of major psychiatric disorders such as schizophrenia. Finally, we discuss the future utility of peripheral samples for the development of biomarkers and tailor-made therapies, such as multimodal assays that are used as a battery of disease and trait pathways and that might be potent and complimentary tools for use in psychiatric research. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

  20. Preliminary characterizations of a serum biomarker for sarcoidosis by comparative proteomic approach with tandem-mass spectrometry in ethnic Han Chinese patients.

    Science.gov (United States)

    Zhang, Yuan; Chen, Xianqiu; Hu, Yang; Du, Shanshan; Shen, Li; He, Yifan; Zhang, Yuxuan; Zhang, Xia; Li, Huiping; Yung, Rex C

    2013-02-11

    The diagnosis of sarcoidosis is still a significant challenge in China because of the need to exclude other diseases including granulomatous infections and malignancies that may be clinically and radiographically similar. The specific aim of the study is to search for serum protein biomarkers of sarcoidosis and to validate their clinical usefulness in differential diagnosis. Serum samples were collected from patients with sarcoidosis (n = 37), and compared to those from patients with tuberculosis (n = 20), other pulmonary diseases (n = 20), and healthy volunteers (n = 20) for determination of sarcoidosis-specific or -associated protein expression profiles. The first part of this study focused on proteomic analysis of serum from patients with sarcoidosis to identify a pattern of peptides capable of differentiating the studied populations using the ClinProt profiling technology based on mass spectrometry. Enzyme Linked Immunosorbent Assay (ELISA) was then used to verify corresponding elevation of the serum protein concentration of the potential biomarkers in the same patients sets. Receiver operating characteristic curve (ROC) analyses was performed to determine the optimal cutoff value for diagnosis. Immunohistochemistry was carried out to further confirm the protein expression patterns of the biomarkers in lung tissue. An unique protein peak of M/Z 3,210 Daltons (Da) was found to be differentially expressed between the sarcoidosis and control groups and was identified as the N-terminal peptide of 29 amino acids (94-122) of serum amyloid A (SAA). ELISA confirmed that the serum SAA level was significantly higher in the sarcoidosis group than that of the other 3 control groups (p biomarker for ruling-out the diagnosis of sarcoidosis in Chinese subjects.

  1. Discovery of prognostic biomarker candidates of lacunar infarction by quantitative proteomics of microvesicles enriched plasma.

    Directory of Open Access Journals (Sweden)

    Arnab Datta

    Full Text Available Lacunar infarction (LACI is a subtype of acute ischemic stroke affecting around 25% of all ischemic stroke cases. Despite having an excellent recovery during acute phase, certain LACI patients have poor mid- to long-term prognosis due to the recurrence of vascular events or a decline in cognitive functions. Hence, blood-based biomarkers could be complementary prognostic and research tools.Plasma was collected from forty five patients following a non-disabling LACI along with seventeen matched control subjects. The LACI patients were monitored prospectively for up to five years for the occurrence of adverse outcomes and grouped accordingly (i.e., LACI-no adverse outcome, LACI-recurrent vascular event, and LACI-cognitive decline without any recurrence of vascular events. Microvesicles-enriched fractions isolated from the pooled plasma of four groups were profiled by an iTRAQ-guided discovery approach to quantify the differential proteome. The data have been deposited to the ProteomeXchange with identifier PXD000748. Bioinformatics analysis and data mining revealed up-regulation of brain-specific proteins including myelin basic protein, proteins of coagulation cascade (e.g., fibrinogen alpha chain, fibrinogen beta chain and focal adhesion (e.g., integrin alpha-IIb, talin-1, and filamin-A while albumin was down-regulated in both groups of patients with adverse outcome.This data set may offer important insight into the mechanisms of poor prognosis and provide candidate prognostic biomarkers for validation on larger cohort of individual LACI patients.

  2. Identification of proteomic biomarkers of preeclampsia using protein microarray and tandem mass spectrometry

    Directory of Open Access Journals (Sweden)

    Karol Charkiewicz

    2015-05-01

    Full Text Available Preeclampsia (PE is the leading cause of death of the fetus and the mother. The exact pathomechanism has not so far been clarified. PE coexists with many other diseases, but it is often difficult to explain the association between them and find a clear reason for their occurrence. There are many predictive factors, but none are highly specific in preeclampsia. The diagnosis of preeclampsia seems to be very complex, which is another argument for the exploration of knowledge on this subject. Although many of the discoveries have hitherto been made in the field of proteomics, still no single specific biomarker of preeclampsia has been discovered. Research at the genome level is important because it can help us understand the genetic predisposition of patients affected by this disease. Nevertheless, researchers have recently become more interested in the pathophysiology of PE, and they are trying to answer the question: what is the real, direct cause of preeclampsia? Thus, the discovery of a protein that is a good predictor of preeclampsia development would significantly accelerate the medical care of pregnant women, and consequently reduce the risk of occurrence of HELLP syndrome and fetal death. Apart from the predictive and diagnostic function, such a discovery would help us to better understand the pathogenesis of preeclampsia and to find in the future a medical drug to suppress this disease. In order to make a breakthrough in this field, scientists need to use the most modern methods of proteomics, which allow for the analysis of small amounts of biological material in the shortest possible time, thereby giving a lot of information about existing proteins in the sample. Such optimization allows two methods, most commonly used by researchers: tandem mass spectrometry and protein microarray technique.

  3. Diagnosing phenotypes of single-sample individuals by edge biomarkers.

    Science.gov (United States)

    Zhang, Wanwei; Zeng, Tao; Liu, Xiaoping; Chen, Luonan

    2015-06-01

    Network or edge biomarkers are a reliable form to characterize phenotypes or diseases. However, obtaining edges or correlations between molecules for an individual requires measurement of multiple samples of that individual, which are generally unavailable in clinical practice. Thus, it is strongly demanded to diagnose a disease by edge or network biomarkers in one-sample-for-one-individual context. Here, we developed a new computational framework, EdgeBiomarker, to integrate edge and node biomarkers to diagnose phenotype of each single test sample. By applying the method to datasets of lung and breast cancer, it reveals new marker genes/gene-pairs and related sub-networks for distinguishing earlier and advanced cancer stages. Our method shows advantages over traditional methods: (i) edge biomarkers extracted from non-differentially expressed genes achieve better cross-validation accuracy of diagnosis than molecule or node biomarkers from differentially expressed genes, suggesting that certain pathogenic information is only present at the level of network and under-estimated by traditional methods; (ii) edge biomarkers categorize patients into low/high survival rate in a more reliable manner; (iii) edge biomarkers are significantly enriched in relevant biological functions or pathways, implying that the association changes in a network, rather than expression changes in individual molecules, tend to be causally related to cancer development. The new framework of edge biomarkers paves the way for diagnosing diseases and analyzing their molecular mechanisms by edges or networks in one-sample-for-one-individual basis. This also provides a powerful tool for precision medicine or big-data medicine. © The Author (2015). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.

  4. Subnuclear proteomics in colorectal cancer

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Knol, Jaco C; Piersma, Sander R

    2010-01-01

    for early cancer detection. Here we evaluate a proteomics work flow for profiling protein constituents in subnuclear domains in colorectal cancer tissues and apply this work flow to a comparative analysis of the nuclear matrix fraction in colorectal adenoma and carcinoma tissue samples. First, we......Abnormalities in nuclear phenotype and chromosome structure are key features of cancer cells. Investigation of the protein determinants of nuclear subfractions in cancer may yield molecular insights into aberrant chromosome function and chromatin organization and in addition may yield biomarkers...... with statistics, we identified proteins that are significantly enriched in the nuclear matrix fraction relative to two earlier fractions (the chromatin-binding and intermediate filament fractions) isolated from six colorectal tissue samples. The total data set contained 2,059 non-redundant proteins. Gene ontology...

  5. GeLC-MS: A Sample Preparation Method for Proteomics Analysis of Minimal Amount of Tissue.

    Science.gov (United States)

    Makridakis, Manousos; Vlahou, Antonia

    2017-10-10

    Application of various proteomics methodologies have been implemented for the global and targeted proteome analysis of many different types of biological samples such as tissue, urine, plasma, serum, blood, and cell lines. Among the aforementioned biological samples, tissue has an exceptional role into clinical research and practice. Disease initiation and progression is usually located at the tissue level of different organs, making the analysis of this material very important for the understanding of the disease pathophysiology. Despite the significant advances in the mass spectrometry instrumentation, tissue proteomics still faces several challenges mainly due to increased sample complexity and heterogeneity. However, the most prominent challenge is attributed to the invasive procedure of tissue sampling which restricts the availability of fresh frozen tissue to minimal amounts and limited number of samples. Application of GeLC-MS sample preparation protocol for tissue proteomics analysis can greatly facilitate making up for these difficulties. In this chapter, a step by step guide for the proteomics analysis of minute amounts of tissue samples using the GeLC-MS sample preparation protocol, as applied by our group in the analysis of multiple different types of tissues (vessels, kidney, bladder, prostate, heart) is provided.

  6. Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio.

    Directory of Open Access Journals (Sweden)

    Ozlem Yilmaz

    Full Text Available Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chromatography and tandem mass spectrometry. Obtained spectra were searched against a zebrafish proteome database and detected proteins were annotated, categorized and quantified based on normalized spectral counts. Manually curated and automated enrichment analyses revealed poor quality eggs to be deficient of proteins involved in protein synthesis and energy and lipid metabolism, and of some vitellogenin products and lectins, and to have a surfeit of proteins involved in endo-lysosomal activities, autophagy, and apoptosis, and of some oncogene products, lectins and egg envelope proteins. Results of pathway and network analyses suggest that this aberrant proteomic profile results from failure of oocytes giving rise to poor quality eggs to properly transit through final maturation, and implicated Wnt signaling in the etiology of this defect. Quantitative comparisons of abundant proteins in good versus poor quality eggs revealed 17 candidate egg quality markers. Thus, the zebrafish egg proteome is clearly linked to embryo developmental potential, a phenomenon that begs further investigation to elucidate the root causes of poor egg quality, presently a serious and intractable problem in livestock and human reproductive medicine.

  7. Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio).

    Science.gov (United States)

    Yilmaz, Ozlem; Patinote, Amélie; Nguyen, Thao Vi; Com, Emmanuelle; Lavigne, Regis; Pineau, Charles; Sullivan, Craig V; Bobe, Julien

    2017-01-01

    Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chromatography and tandem mass spectrometry. Obtained spectra were searched against a zebrafish proteome database and detected proteins were annotated, categorized and quantified based on normalized spectral counts. Manually curated and automated enrichment analyses revealed poor quality eggs to be deficient of proteins involved in protein synthesis and energy and lipid metabolism, and of some vitellogenin products and lectins, and to have a surfeit of proteins involved in endo-lysosomal activities, autophagy, and apoptosis, and of some oncogene products, lectins and egg envelope proteins. Results of pathway and network analyses suggest that this aberrant proteomic profile results from failure of oocytes giving rise to poor quality eggs to properly transit through final maturation, and implicated Wnt signaling in the etiology of this defect. Quantitative comparisons of abundant proteins in good versus poor quality eggs revealed 17 candidate egg quality markers. Thus, the zebrafish egg proteome is clearly linked to embryo developmental potential, a phenomenon that begs further investigation to elucidate the root causes of poor egg quality, presently a serious and intractable problem in livestock and human reproductive medicine.

  8. Proteomics Mapping of Cord Blood Identifies Haptoglobin ?Switch-On? Pattern as Biomarker of Early-Onset Neonatal Sepsis in Preterm Newborns

    OpenAIRE

    Buhimschi, Catalin S.; Bhandari, Vineet; Dulay, Antonette T.; Nayeri, Unzila A.; Abdel-Razeq, Sonya S.; Pettker, Christian M.; Thung, Stephen; Zhao, Guomao; Han, Yiping W.; Bizzarro, Matthew; Buhimschi, Irina A.

    2011-01-01

    Background Intra-amniotic infection and/or inflammation (IAI) are important causes of preterm birth and early-onset neonatal sepsis (EONS). A prompt and accurate diagnosis of EONS is critical for improved neonatal outcomes. We sought to explore the cord blood proteome and identify biomarkers and functional protein networks characterizing EONS in preterm newborns. Methodology/Principal Findings We studied a prospective cohort of 180 premature newborns delivered May 2004-September 2009. A prote...

  9. MALDI-TOF mass spectrometry analysis of small molecular weight compounds (under 10 KDa) as biomarkers of rat hearts undergoing arecoline challenge.

    Science.gov (United States)

    Chen, Tung-Sheng; Chang, Mu-Hsin; Kuo, Wei-Wen; Lin, Yueh-Min; Yeh, Yu-Lan; Day, Cecilia Hsuan; Lin, Chien-Chung; Tsai, Fuu-Jen; Tsai, Chang-Hai; Huang, Chih-Yang

    2013-04-01

    Statistical and clinical reports indicate that betel nut chewing is strongly associated with progression of oral cancer because some ingredients in betel nuts are potential cancer promoters, especially arecoline. Early diagnosis for cancer biomarkers is the best strategy for prevention of cancer progression. Several methods are suggested for investigating cancer biomarkers. Among these methods, gel-based proteomics approach is the most powerful and recommended tool for investigating biomarkers due to its high-throughput. However, this proteomics approach is not suitable for screening biomarkers with molecular weight under 10 KDa because of the characteristics of gel electrophoresis. This study investigated biomarkers with molecular weight under 10 KDa in rats with arecoline challenge. The centrifuging vials with membrane (10 KDa molecular weight cut-off) played a crucial role in this study. After centrifuging, the filtrate (containing compounds with molecular weight under 10 KDa) was collected and spotted on a sample plate for MALDI-TOF mass spectrometry analysis. Compared to control, three extra peaks (m/z values were 1553.1611, 1668.2097 and 1740.1832, respectively) were found in sera and two extra peaks were found in heart tissue samples (408.9719 and 524.9961, respectively). These small compounds should play important roles and may be potential biomarker candidates in rats with arecoline. This study successfully reports a mass-based method for investigating biomarker candidates with small molecular weight in different types of sample (including serum and tissue). In addition, this reported method is more time-efficient (1 working day) than gel-based proteomics approach (5~7 working days).

  10. An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

    Directory of Open Access Journals (Sweden)

    Albert-Baskar Arul

    2013-06-01

    Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

  11. Clinical proteomic analysis of scrub typhus infection.

    Science.gov (United States)

    Park, Edmond Changkyun; Lee, Sang-Yeop; Yun, Sung Ho; Choi, Chi-Won; Lee, Hayoung; Song, Hyun Seok; Jun, Sangmi; Kim, Gun-Hwa; Lee, Chang-Seop; Kim, Seung Il

    2018-01-01

    Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection. Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis. Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi , and normal expression was largely rescued by antibiotic treatment. This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

  12. Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases.

    Science.gov (United States)

    Pieragostino, Damiana; D'Alessandro, Michele; di Ioia, Maria; Di Ilio, Carmine; Sacchetta, Paolo; Del Boccio, Piero

    2015-02-01

    Proteomics and metabolomics investigations of body fluids present several challenges for biomarker discovery of several diseases. The search for biomarkers is actually conducted in different body fluids, even if the ideal biomarker can be found in an easily accessible biological fluid, because, if validated, the biomarker could be sought in the healthy population. In this regard, tears could be considered an optimum material obtained by noninvasive procedures. In the past years, the scientific community has become more interested in the study of tears for the research of new biomarkers not only for ocular diseases. In this review, we provide a discussion on the current state of biomarkers research in tears and their relevance for clinical practice, and report the main results of clinical proteomics studies on systemic and eye diseases. We summarize the main methods for tear samples analyses and report recent advances in "omics" platforms for tears investigations. Moreover, we want to take stock of the emerging field of metabolomics and lipidomics as a new and integrated approach to study protein-metabolites interplay for biomarkers research, where tears represent a still unexplored and attractive field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Gene Expression and Proteome Analysis as Sources of Biomarkers in Basal Cell Carcinoma

    Science.gov (United States)

    Ghita, Mihaela Adriana; Voiculescu, Suzana; Rosca, Adrian E.; Moraru, Liliana; Greabu, Maria

    2016-01-01

    Basal cell carcinoma (BCC) is the world's leading skin cancer in terms of frequency at the moment and its incidence continues to rise each year, leading to profound negative psychosocial and economic consequences. UV exposure is the most important environmental factor in the development of BCC in genetically predisposed individuals, this being reflected by the anatomical distribution of lesions mainly on sun-exposed skin areas. Early diagnosis and prompt management are of crucial importance in order to prevent local tissue destruction and subsequent disfigurement. Although various noninvasive or minimal invasive techniques have demonstrated their utility in increasing diagnostic accuracy of BCC and progress has been made in its treatment options, recurrent, aggressive, and metastatic variants of BCC still pose significant challenge for the healthcare system. Analysis of gene expression and proteomic profiling of tumor cells and of tumoral microenvironment in various tissues strongly suggests that certain molecules involved in skin cancer pathogenic pathways might represent novel predictive and prognostic biomarkers in BCC. PMID:27578920

  14. Gene Expression and Proteome Analysis as Sources of Biomarkers in Basal Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    Mihai Lupu

    2016-01-01

    Full Text Available Basal cell carcinoma (BCC is the world’s leading skin cancer in terms of frequency at the moment and its incidence continues to rise each year, leading to profound negative psychosocial and economic consequences. UV exposure is the most important environmental factor in the development of BCC in genetically predisposed individuals, this being reflected by the anatomical distribution of lesions mainly on sun-exposed skin areas. Early diagnosis and prompt management are of crucial importance in order to prevent local tissue destruction and subsequent disfigurement. Although various noninvasive or minimal invasive techniques have demonstrated their utility in increasing diagnostic accuracy of BCC and progress has been made in its treatment options, recurrent, aggressive, and metastatic variants of BCC still pose significant challenge for the healthcare system. Analysis of gene expression and proteomic profiling of tumor cells and of tumoral microenvironment in various tissues strongly suggests that certain molecules involved in skin cancer pathogenic pathways might represent novel predictive and prognostic biomarkers in BCC.

  15. Bioinformatical Analysis of Organ-Related (Heart, Brain, Liver, and Kidney and Serum Proteomic Data to Identify Protein Regulation Patterns and Potential Sepsis Biomarkers

    Directory of Open Access Journals (Sweden)

    Andreas Hohn

    2018-01-01

    Full Text Available During the last years, proteomic studies have revealed several interesting findings in experimental sepsis models and septic patients. However, most studies investigated protein alterations only in single organs or in whole blood. To identify possible sepsis biomarkers and to evaluate the relationship between protein alteration in sepsis affected organs and blood, proteomics data from the heart, brain, liver, kidney, and serum were analysed. Using functional network analyses in combination with hierarchical cluster analysis, we found that protein regulation patterns in organ tissues as well as in serum are highly dynamic. In the tissue proteome, the main functions and pathways affected were the oxidoreductive activity, cell energy generation, or metabolism, whereas in the serum proteome, functions were associated with lipoproteins metabolism and, to a minor extent, with coagulation, inflammatory response, and organ regeneration. Proteins from network analyses of organ tissue did not correlate with statistically significantly regulated serum proteins or with predicted proteins of serum functions. In this study, the combination of proteomic network analyses with cluster analyses is introduced as an approach to deal with high-throughput proteomics data to evaluate the dynamics of protein regulation during sepsis.

  16. Longitudinal quantification of the gingival crevicular fluid proteome during progression from gingivitis to periodontitis in a canine model.

    Science.gov (United States)

    Davis, Ian J; Jones, Andrew W; Creese, Andrew J; Staunton, Ruth; Atwal, Jujhar; Chapple, Iain L C; Harris, Stephen; Grant, Melissa M

    2016-07-01

    Inflammatory periodontal disease is widespread in dogs. This study evaluated site-specific changes in the canine gingival crevicular fluid (GCF) proteome during longitudinal progression from very mild gingivitis to mild periodontitis. Periodontitis diagnosis in dogs requires general anaesthesia with associated risks and costs; our ultimate aim was to develop a periodontitis diagnostic for application in conscious dogs. The objective of this work was to identify potential biomarkers of periodontal disease progression in dogs. Gingival crevicular fluid was sampled from a total of 10 teeth in eight dogs at three different stages of health/disease and samples prepared for quantitative mass spectrometry (data available via ProteomeXchange; identifier PXD003337). A univariate mixed model analysis determined significantly altered proteins between health states and six were evaluated by ELISA. Four hundred and six proteins were identified with 84 present in all samples. The prevalence of 40 proteins was found to be significantly changed in periodontitis relative to gingivitis. ELISA measurements confirmed that haptoglobin was significantly increased. This study demonstrates for the first time that proteins detected by mass spectrometry have potential to identify novel biomarkers for canine periodontal disease. Further work is required to validate additional biomarkers for a periodontitis diagnostic. © 2016 The Authors. Journal of Clinical Periodontology Published by John Wiley & Sons Ltd.

  17. Sample handling for mass spectrometric proteomic investigations of human urine.

    Science.gov (United States)

    Petri, Anette Lykke; Høgdall, Claus; Christensen, Ib Jarle; Simonsen, Anja Hviid; T'jampens, Davy; Hellmann, Marja-Leena; Kjaer, Susanne Krüger; Fung, Eric T; Høgdall, Estrid

    2008-09-01

    Because of its non-invasive sample collection method, human urine is an attractive biological material both for discovering biomarkers and for use in future screening trials for different diseases. Before urine can be used for these applications, standardized protocols for sample handling that optimize protein stability are required. In this explorative study, we examine the influence of different urine collection methods, storage temperatures, storage times, and repetitive freeze-thaw procedures on the protein profiles obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Prospectively collected urine samples from 11 women were collected as either morning or midday specimens. The effects of storage temperature, time to freezing, and freeze-thaw cycles were assessed by calculating the number, intensity, and reproducibility of peaks visualized by SELDI-TOF-MS. On the CM10 array, 122 peaks were detected and 28 peaks were found to be significantly different between urine types, storage temperature and time to freezing. On the IMAC-Cu array, 65 peaks were detected and 1 peak was found to be significantly different according to time to freezing. No significant differences were demonstrated for freeze-thaw cycles. Optimal handling and storage conditions are necessary in clinical urine proteomic investigations. Collection of urine with a single and consistently performed protocol is needed to reduce analytical bias. Collecting only one urine type, which is stored for a limited period at 4°C until freezing at -80°C prior to analysis will provide the most stable profiles. Copyright © 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Identification of EBP50 as a Specific Biomarker for Carcinogens Via the Analysis of Mouse Lymphoma Cellular Proteome

    Science.gov (United States)

    Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

    2012-01-01

    To identify specific biomarkers generated upon exposure of L5178Y mouse lymphoma cells to carcinogens, 2-DE and MALDI-TOF MS analysis were conducted using the cellular proteome of L5178Y cells that had been treated with the known carcinogens, 1,2-dibromoethane and O-nitrotoluene and the noncarcinogens, emodin and D-mannitol. Eight protein spots that showed a greater than 1.5-fold increase or decrease in intensity following carcinogen treatment compared with treatment with noncarcinogens were selected. Of the identified proteins, we focused on the candidate biomarker ERM-binding phosphoprotein 50 (EBP50), the expression of which was specifically increased in response to treatment with the carcinogens. The expression level of EBP50 was determined by western analysis using polyclonal rabbit anti-EBP50 antibody. Further, the expression level of EBP50 was increased in cells treated with seven additional carcinogens, verifying that EBP50 could serve as a specific biomarker for carcinogens. PMID:22434383

  19. Towards a better understanding of biomarker response in field survey: a case study in eight populations of zebra mussels.

    Science.gov (United States)

    Pain-Devin, S; Cossu-Leguille, C; Geffard, A; Giambérini, L; Jouenne, T; Minguez, L; Naudin, B; Parant, M; Rodius, F; Rousselle, P; Tarnowska, K; Daguin-Thiébaut, C; Viard, F; Devin, S

    2014-10-01

    In order to provide reliable information about responsiveness of biomarkers during environmental monitoring, there is a need to improve the understanding of inter-population differences. The present study focused on eight populations of zebra mussels and aimed to describe how variable are biomarkers in different sampling locations. Biomarkers were investigated and summarised through the Integrated Biomarker Response (IBR index). Inter-site differences in IBR index were analysed through comparisons with morphological data, proteomic profiles and genetic background of the studied populations. We found that the IBR index was a good tool to inform about the status of sites. It revealed higher stress in more polluted sites than in cleaner ones. It was neither correlated to proteomic profiles nor to genetic background, suggesting a stronger influence of environment than genes. Meanwhile, morphological traits were related to both environment and genetic background influence. Together these results attest the benefit of using biological tools to better illustrate the status of a population and highlight the need of consider inter-population difference in their baselines. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Mass Spectrometry for Translational Proteomics: Progress and Clinical Implications

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Erin Shammel; Liu, Tao; Petyuk, Vladislav A.; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; Anderson, Gordon A.; Smith, Richard D.

    2012-08-31

    Mass spectrometry (MS)-based proteomics measurements have become increasingly utilized in a wide range of biological and biomedical applications, and have significantly enhanced the understanding of the complex and dynamic nature of the proteome and its connections to biology and diseases. While some MS techniques such as those for targeted analysis are increasingly applied with great success, others such as global quantitative analysis (for e.g. biomarker discovery) are more challenging and continue to be developed and refined to provide the desired throughput, sensitivity and/ or specificity. New MS capabilities and proteomics-based pipelines/strategies also keep enhancing for the advancement of clinical proteomics applications such as protein biomarker discovery and validation. Herein, we provide a brief review to summarize the current state of MS-based proteomics with respect to its advantages and present limitations, while highlighting its potential in future clinical applications.

  1. Optimized Clinical Use of RNALater and FFPE Samples for Quantitative Proteomics

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Kastaniegaard, Kenneth; Padurariu, Simona

    2015-01-01

    Introduction and Objectives The availability of patient samples is essential for clinical proteomic research. Biobanks worldwide store mainly samples stabilized in RNAlater as well as formalin-fixed and paraffin embedded (FFPE) biopsies. Biobank material is a potential source for clinical...... we compare to FFPE and frozen samples being the control. Methods From the sigmoideum of two healthy participants’ twenty-four biopsies were extracted using endoscopy. The biopsies was stabilized either by being directly frozen, RNAlater, FFPE or incubated for 30 min at room temperature prior to FFPE...... information. Conclusion We have demonstrated that quantitative proteome analysis and pathway mapping of samples stabilized in RNAlater as well as by FFPE is feasible with minimal impact on the quality of protein quantification and post-translational modifications....

  2. Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

    Science.gov (United States)

    Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

    2016-11-01

    Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

  3. Analytical methods for proteome data obtained from SDS-PAGE multi-dimensional separation and mass spectrometry

    Directory of Open Access Journals (Sweden)

    Gun Wook Park

    2010-03-01

    Full Text Available For proteome analysis, various experimental protocols using mass spectrometry have been developed over thelast decade. The different protocols have differing performances and degrees of accuracy. Furthermore, the “best”protocol for a proteomic analysis of a sample depends on the purpose of the analysis, especially in connection withdisease proteomics, including biomarker discovery and therapeutics analyses of human serum or plasma. Theprotein complexity and the wide dynamic range of blood samples require high-dimensional separation technology.In this article, we review proteome analysis protocols in which both Sodium Dodecyl Sulfate-Polyacryl Amide GelElectrophoresis(SDS-PAGE and liquid chromatography are used for peptide and protein separations. Multidimensionalseparation technology supplies a high-quality dataset of tandem mass spectra and reveals signals fromlow-abundance proteins, although it can be time-consuming and laborious work. We survey shotgun proteomicsprotocols using SDS-PAGE and liquid chromatography and introduce bioinformatics tools for the analysis ofproteomics data. We also review efforts toward the biological interpretation of the proteome.

  4. Multiplexed mass spectrometry monitoring of biomarker candidates for osteoarthritis.

    Science.gov (United States)

    Fernández-Puente, Patricia; Calamia, Valentina; González-Rodríguez, Lucía; Lourido, Lucía; Camacho-Encina, María; Oreiro, Natividad; Ruiz-Romero, Cristina; Blanco, Francisco J

    2017-01-30

    The methods currently available for the diagnosis and monitoring of osteoarthritis (OA) are very limited and lack sensitivity. Being the most prevalent rheumatic disease, one of the most disabling pathologies worldwide and currently untreatable, there is a considerable interest pointed in the verification of specific biological markers for improving its diagnosis and disease progression studies. Considering the remarkable development of targeted proteomics methodologies in the frame of the Human Proteome Project, the aim of this work was to develop and apply a MRM-based method for the multiplexed analysis of a panel of 6 biomarker candidates for OA encoded by the Chromosome 16, and another 8 proteins identified in previous shotgun studies as related with this pathology, in specimens derived from the human joint and serum. The method, targeting 35 different peptides, was applied to samples from human articular chondrocytes, healthy and osteoarthritic cartilage, synovial fluid and serum. Subsequently, a verification analysis of the biomarker value of these proteins was performed by single point measurements on a set of 116 serum samples, leading to the identification of increased amounts of Haptoglobin and von Willebrand Factor in OA patients. Altogether, the present work provides a tool for the multiplexed monitoring of 14 biomarker candidates for OA, and verifies for the first time the increased amount of two of these circulating markers in patients diagnosed with this disease. We have developed an MRM method for the identification and relative quantification of a panel of 14 protein biomarker candidates for osteoarthritis. This method has been applied to analyze human articular chondrocytes, articular cartilage, synovial fluid, and finally a collection of 116 serum samples from healthy controls and patients suffering different degrees of osteoarthritis, in order to verify the biomarker usefulness of the candidates. HPT and VWF were validated as increased in OA

  5. RAPID PROCESSING OF ARCHIVAL TISSUE SAMPLES FOR PROTEOMIC ANALYSIS USING PRESSURE-CYCLING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    Vinuth N. Puttamallesh1,2

    2017-06-01

    Full Text Available Advent of mass spectrometry based proteomics has revolutionized our ability to study proteins from biological specimen in a high-throughput manner. Unlike cell line based studies, biomedical research involving tissue specimen is often challenging due to limited sample availability. In addition, investigation of clinically relevant research questions often requires enormous amount of time for sample collection prospectively. Formalin fixed paraffin embedded (FFPE archived tissue samples are a rich source of tissue specimen for biomedical research. However, there are several challenges associated with analysing FFPE samples. Protein cross-linking and degradation of proteins particularly affects proteomic analysis. We demonstrate that barocycler that uses pressure-cycling technology enables efficient protein extraction and processing of small amounts of FFPE tissue samples for proteomic analysis. We identified 3,525 proteins from six 10µm esophageal squamous cell carcinoma (ESCC tissue sections. Barocycler allows efficient protein extraction and proteolytic digestion of proteins from FFPE tissue sections at par with conventional methods.

  6. Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

    Science.gov (United States)

    Parker, Carol E; Borchers, Christoph H

    2014-06-01

    In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  7. Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

    Science.gov (United States)

    Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

    2014-07-01

    Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

  8. Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

    Science.gov (United States)

    Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

    2018-01-10

    Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

  9. A comparative proteomic study on the effects of metal pollution in oysters Crassostrea hongkongensis.

    Science.gov (United States)

    Xu, Lanlan; Ji, Chenglong; Wu, Huifeng; Tan, Qiaoguo; Wang, Wen-Xiong

    2016-11-15

    The metal pollution has posed great risk on the coastal organisms along the Jiulongjiang Estuary in South China. In this work, two-dimensional electrophoresis-based proteomics was applied to the oysters Crassostrea hongkongensis from metal pollution sites to characterize the proteomic responses to metal pollution. Metal accumulation and proteomic responses indicated that the oysters from BJ site were more severely contaminated than those from FG site. Compared with those oyster samples from the clean site (JZ), metal pollution induced cellular injuries, oxidative and immune stresses in oyster heapatopancreas from both BJ and FG sites via differential metabolic pathways. In addition, metal pollution in BJ site induced disturbance in energy and lipid metabolisms in oysters. Results indicated that cathepsin L and ferritin GF1 might be the biomarkers of As and Fe in oyster C. hongkongensis, respectively. This study demonstrates that proteomics is a useful tool for investigating biological effects induced by metal pollution. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Marine proteomics: a critical assessment of an emerging technology.

    Science.gov (United States)

    Slattery, Marc; Ankisetty, Sridevi; Corrales, Jone; Marsh-Hunkin, K Erica; Gochfeld, Deborah J; Willett, Kristine L; Rimoldi, John M

    2012-10-26

    The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for eco-physiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several "model species". Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.

  11. Lessons from the proteomic study of osteoarthritis.

    Science.gov (United States)

    Ruiz-Romero, Cristina; Fernández-Puente, Patricia; Calamia, Valentina; Blanco, Francisco J

    2015-08-01

    Osteoarthritis is the most common rheumatic pathology and one of the leading causes of disability worldwide. It is a very complex disease whose etiopathogenesis is not fully understood. Furthermore, there are serious limitations for its management, since it lacks specific and sensitive biomarkers for early diagnosis, prognosis and therapeutic monitoring. Proteomic approaches performed in the last few decades have contributed to the knowledge on the molecular mechanisms that participate in this pathology and they have also led to interesting panels of putative biomarker candidates. In the next few years, further efforts should be made for translating these findings into the clinical routines. It is expected that targeted proteomics strategies will be highly valuable for the verification and qualification of biomarkers of osteoarthritis.

  12. Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

    Science.gov (United States)

    Lehmann, Sylvain; Hoofnagle, Andrew; Hochstrasser, Denis; Brede, Cato; Glueckmann, Matthias; Cocho, José A; Ceglarek, Uta; Lenz, Christof; Vialaret, Jérôme; Scherl, Alexander; Hirtz, Christophe

    2013-05-01

    Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).

  13. Biomarkers for AAA: Encouraging steps but clinical relevance still to be delivered.

    Science.gov (United States)

    Htun, Nay Min; Peter, Karlheinz

    2014-10-01

    Potential biomarkers have been investigated using proteomic studies in a variety of diseases. Some biomarkers have central roles in both diagnosis and monitoring of various disorders in clinical medicine, such as troponins, brain natriuretic peptide, and C-reactive protein. Although several biomarkers have been suggested in human abdominal aortic aneurysm (AAA), reliable markers have been lacking. In this issue, Moxon et al. [Proteomics Clin Appl. 2014, 8, 762-772] undertook a broad and systematic proteomic approach toward identification of biomarkers in a commonly used AAA mouse model (AAA created by angiotensin-II infusion). In this mouse model, apolipoprotein C1 and matrix metalloproteinase-9 were identified as novel biomarkers of stable AAA. This finding represents an important step forward, toward a clinically relevant role of biomarkers in AAA. This also encourages for further studies toward the identification of biomarkers (or their combinations) that can predict AAA progression and rupture, which would represent a major progress in AAA management and would establish an AAA biomarker as a much anticipated clinical tool. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

    Science.gov (United States)

    Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

    2016-08-18

    A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed

  15. Allergic asthma biomarkers using systems approaches

    Directory of Open Access Journals (Sweden)

    Gaurab eSircar

    2014-01-01

    Full Text Available Asthma is characterized by lung inflammation caused by complex interaction between the immune system and environmental factors such as allergens and inorganic pollutants. Recent research in this field is focused on discovering new biomarkers associated with asthma pathogenesis. This review illustrates updated research associating biomarkers of allergic asthma and their potential use in systems biology of the disease. We focus on biomolecules with altered expression, which may serve as inflammatory, diagnostic and therapeutic biomarkers of asthma discovered in human or experimental asthma model using genomic, proteomic and epigenomic approaches for gene and protein expression profiling. These include high-throughput technologies such as state of the art microarray and proteomics Mass Spectrometry (MS platforms. Emerging concepts of molecular interactions and pathways may provide new insights in searching potential clinical biomarkers. We summarized certain pathways with significant linkage to asthma pathophysiology by analyzing the compiled biomarkers. Systems approaches with this data can identify the regulating networks, which will eventually identify the key biomarkers to be used for diagnostics and drug discovery.

  16. Comparison of serum fractionation methods by data independent label-free proteomics

    Directory of Open Access Journals (Sweden)

    D. Baiwir

    2015-12-01

    Full Text Available Off-line sample prefractionations applied prior to biomarker discovery proteomics are options to enable more protein identifications and detect low-abundance proteins. This work compared five commercial methods efficiency to raw serum analysis using label-free proteomics. The variability of the protein quantities determined for each process was similar to the unprefractionated serum. A 49% increase in protein identifications and 12.2% of reliable quantification were obtained. A 61 times lower limit of protein quantitation was reached compared to protein concentrations observed in raw serum. The concentrations of detected proteins were confronted to estimated reference values.

  17. Multidimensional chromatography coupled to mass spectrometry in analysing complex proteomics samples

    NARCIS (Netherlands)

    Horvatovich, Peter; Hoekman, Berend; Govorukhina, Natalia; Bischoff, Rainer

    Multidimensional chromatography coupled to mass spectrometry (LC(n)-MS) provides more separation power and an extended measured dynamic concentration range to analyse complex proteomics samples than one dimensional liquid chromatography coupled to mass spectrometry (1D-LC-MS). This review gives an

  18. Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker

    International Nuclear Information System (INIS)

    Kang, Un-Beom; Ahn, Younghee; Lee, Jong Won; Kim, Yong-Hak; Kim, Joon; Yu, Myeong-Hee; Noh, Dong-Young; Lee, Cheolju

    2010-01-01

    Breast cancer is one of the leading causes of women's death worldwide. It is important to discover a reliable biomarker for the detection of breast cancer. Plasma is the most ideal source for cancer biomarker discovery since many cells cross-communicate through the secretion of soluble proteins into blood. Plasma proteomes obtained from 6 breast cancer patients and 6 normal healthy women were analyzed by using the isotope-coded affinity tag (ICAT) labeling approach and tandem mass spectrometry. All the plasma samples used were depleted of highly abundant 6 plasma proteins by immune-affinity column chromatography before ICAT labeling. Several proteins showing differential abundance level were selected based on literature searches and their specificity to the commercially available antibodies, and then verified by immunoblot assays. A total of 155 proteins were identified and quantified by ICAT method. Among them, 33 proteins showed abundance changes by more than 1.5-fold between the plasmas of breast cancer patients and healthy women. We chose 5 proteins for the follow-up confirmation in the individual plasma samples using immunoblot assay. Four proteins, α1-acid glycoprotein 2, monocyte differentiation antigen CD14, biotinidase (BTD), and glutathione peroxidase 3, showed similar abundance ratio to ICAT result. Using a blind set of plasmas obtained from 21 breast cancer patients and 21 normal healthy controls, we confirmed that BTD was significantly down-regulated in breast cancer plasma (Wilcoxon rank-sum test, p = 0.002). BTD levels were lowered in all cancer grades (I-IV) except cancer grade zero. The area under the receiver operating characteristic curve of BTD was 0.78. Estrogen receptor status (p = 0.940) and progesterone receptor status (p = 0.440) were not associated with the plasma BTD levels. Our study suggests that BTD is a potential serological biomarker for the detection of breast cancer

  19. Correspondence between salivary proteomic pattern and clinical course in primary Sjögren syndrome and non-Hodgkin's lymphoma: a case report

    Directory of Open Access Journals (Sweden)

    Baldini Chiara

    2011-11-01

    Full Text Available Abstract Background In the last years human proteomic has represented a promising tool to promote the communication between basic and clinical science. Methods To explore the correspondence between salivary proteomic profile and clinical response, herein, we used a proteomic approach to analyse the whole saliva of a patient with primary Sjögren's Syndrome (pSS and non-Hodgkin's-MALT type parotid lymphoma before, during and after a standard treatment with cyclophosphamide (CTX and rituximab (RTX. To identify any discriminatory therapeutic salivary biomarker patient's whole saliva was collected at the baseline, after the fourth infusion of rituximab, and on remission and analysed combining two-dimensional electrophoresis (2DE and MALDI-TOF/TOF mass spectrometry. Results Proteomic results obtained from the comparison of salivary samples indicated several qualitative and quantitative modifications in the salivary expression of putative albumin, immunoglobulin J chain, Ig kappa chain C region, alpha-1-antitrypsin, haptoglobin and Ig alpha-1 chain C region. Conclusion This study suggests that clinical and functional changes of the salivary glands driven by autoimmune and lymphoproliferative processes might be reflected in patients' whole saliva proteins, shedding new light on the potential usefulness of salivary proteomic analysis in the identification of prognostic and therapeutic biomarkers for patients with pSS and non Hodgkin's lymphomas.

  20. Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio)

    OpenAIRE

    Yilmaz, Ozlem; Patinote, Amélie; Nguyen, Thao Vi; Com, Emmanuelle; Lavigne, Regis; Pineau, Charles; Sullivan, Craig V.; Bobe, Julien

    2017-01-01

    Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chr...

  1. Non-invasively collected amniotic fluid as a source of possible biomarkers for premature rupture of membranes investigated by proteomic approach.

    Science.gov (United States)

    Consonni, Sara; Mainini, Veronica; Pizzardi, Agnese; Gianazza, Erica; Chinello, Clizia; Locatelli, Anna; Magni, Fulvio

    2014-02-01

    Preterm delivery is one of the main causes of perinatal morbidity and mortality and it accounts for 75 % of perinatal mortality and more than half of the long-term morbidity. We applied a proteomic approach based on mass spectrometry (MS) for biomarkers discovery of preterm premature rupture of membranes (pPROM) by investigating amniotic fluid (AF) invasively and non-invasively collected. Amniotic fluid was obtained from vagina of women with pPROM (group 1), PROM at term (group 2) and by genetic amniocentesis (group 3). Pre-fractionated AF proteome was analyzed through matrix assisted laser desorption ionization-time of flight (MALDI-TOF) MS. The characterization of proteins/peptides of interest was obtained by high performance liquid chromatography-electrospray tandem MS. Three peptides overexpressed in pPROM and able to discriminate the groups 1 and 2 were detected. One peptide was identified as the fragment Gly452LAVPDGPLGLPPKPro466 of the protein KIAA1522, expressed by fetal brain and liver. This peptide was overexpressed in a patient of the group 3, completely asymptomatic at the time of the amniocentesis, who later developed pPROM. Amniotic fluid invasively and non-invasively collected can be analyzed by MALDI-TOF MS to obtain proteomic profiles. Proteomic analysis identified a peptide with promising diagnostic capability for pPROM.

  2. Identification of peroxiredoxin-1 as a novel biomarker of abdominal aortic aneurysm

    DEFF Research Database (Denmark)

    Martinez-Pinna, Roxana; Ramos-Mozo, Priscila; Madrigal-Matute, Julio

    2011-01-01

    In the search of novel biomarkers of abdominal aortic aneurysm (AAA) progression, proteins released by intraluminal thrombus (ILT) were analyzed by a differential proteomic approach.......In the search of novel biomarkers of abdominal aortic aneurysm (AAA) progression, proteins released by intraluminal thrombus (ILT) were analyzed by a differential proteomic approach....

  3. Preliminary characterizations of a serum biomarker for sarcoidosis by comparative proteomic approach with tandem-mass spectrometry in ethnic Han Chinese patients

    Directory of Open Access Journals (Sweden)

    Zhang Yuan

    2013-02-01

    Full Text Available Abstract Background The diagnosis of sarcoidosis is still a significant challenge in China because of the need to exclude other diseases including granulomatous infections and malignancies that may be clinically and radiographically similar. The specific aim of the study is to search for serum protein biomarkers of sarcoidosis and to validate their clinical usefulness in differential diagnosis. Methods Serum samples were collected from patients with sarcoidosis (n = 37, and compared to those from patients with tuberculosis (n = 20, other pulmonary diseases (n = 20, and healthy volunteers (n = 20 for determination of sarcoidosis-specific or -associated protein expression profiles. The first part of this study focused on proteomic analysis of serum from patients with sarcoidosis to identify a pattern of peptides capable of differentiating the studied populations using the ClinProt profiling technology based on mass spectrometry. Enzyme Linked Immunosorbent Assay (ELISA was then used to verify corresponding elevation of the serum protein concentration of the potential biomarkers in the same patients sets. Receiver operating characteristic curve (ROC analyses was performed to determine the optimal cutoff value for diagnosis. Immunohistochemistry was carried out to further confirm the protein expression patterns of the biomarkers in lung tissue. Results An unique protein peak of M/Z 3,210 Daltons (Da was found to be differentially expressed between the sarcoidosis and control groups and was identified as the N-terminal peptide of 29 amino acids (94-122 of serum amyloid A (SAA. ELISA confirmed that the serum SAA level was significantly higher in the sarcoidosis group than that of the other 3 control groups (p p  Conclusion This is the first study to investigate serum protein markers in Chinese subjects with sarcoidosis. This study shows that the serum SAA expression profiles were different between the sarcoidosis and non

  4. Semen proteomics and male infertility.

    Science.gov (United States)

    Jodar, Meritxell; Soler-Ventura, Ada; Oliva, Rafael

    2017-06-06

    Semen is a complex body fluid containing an admixture of spermatozoa suspended in secretions from the testes and epididymis which are mixed at the time of ejaculation with secretions from other accessory sex glands such as the prostate and seminal vesicles. High-throughput technologies have revealed that, contrary to the idea that sperm cells are simply a silent delivery vehicle of the male genome to the oocyte, the sperm cells in fact provide both a specific epigenetically marked DNA together with a complex population of proteins and RNAs crucial for embryogenesis. Similarly, -omic technologies have also enlightened that seminal fluid seems to play a much greater role than simply being a medium to carry the spermatozoa through the female reproductive tract. In the present review, we briefly overview the sperm cell biology, consider the key issues in sperm and seminal fluid sample preparation for high-throughput proteomic studies, describe the current state of the sperm and seminal fluid proteomes generated by high-throughput proteomic technologies and provide new insights into the potential communication between sperm and seminal fluid. In addition, comparative proteomic studies open a window to explore the potential pathogenic mechanisms of infertility and the discovery of potential biomarkers with clinical significance. The review updates the numerous proteomics studies performed on semen, including spermatozoa and seminal fluid. In addition, an integrative analysis of the testes, sperm and seminal fluid proteomes is also included providing insights into the molecular mechanisms that regulate the generation, maturation and transit of spermatozoa. Furthermore, the compilation of several differential proteomic studies focused on male infertility reveals potential pathways disturbed in specific subtypes of male infertility and points out towards future research directions in the field. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. The 3rd Central and Eastern European Proteomic Conference

    Czech Academy of Sciences Publication Activity Database

    Gadher, S. J.; Martinková, Jiřina; Drahoš, L.; Vékey, K.; Allmaier, G.; Kovářová, Hana

    2010-01-01

    Roč. 7, č. 1 (2010), s. 15-17 ISSN 1478-9450 Institutional research plan: CEZ:AV0Z50450515 Keywords : proteomics * proteome research * biomarkers Subject RIV: CE - Biochemistry Impact factor: 4.406, year: 2010

  6. Gel-aided sample preparation (GASP)--a simplified method for gel-assisted proteomic sample generation from protein extracts and intact cells.

    Science.gov (United States)

    Fischer, Roman; Kessler, Benedikt M

    2015-04-01

    We describe a "gel-assisted" proteomic sample preparation method for MS analysis. Solubilized protein extracts or intact cells are copolymerized with acrylamide, facilitating denaturation, reduction, quantitative cysteine alkylation, and matrix formation. Gel-aided sample preparation has been optimized to be highly flexible, scalable, and to allow reproducible sample generation from 50 cells to milligrams of protein extracts. This methodology is fast, sensitive, easy-to-use on a wide range of sample types, and accessible to nonspecialists. © 2014 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

    Science.gov (United States)

    Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

    2016-01-01

    Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

  8. Biomarkers in rheumatic diseases: how can they facilitate diagnosis and assessment of disease activity?

    Science.gov (United States)

    Mohan, Chandra; Assassi, Shervin

    2015-11-26

    Serological and proteomic biomarkers can help clinicians diagnose rheumatic diseases earlier and assess disease activity more accurately. These markers have been incorporated into the recently revised classification criteria of several diseases to enable early diagnosis and timely initiation of treatment. Furthermore, they also facilitate more accurate subclassification and more focused monitoring for the detection of certain disease manifestations, such as lung and renal involvement. These biomarkers can also make the assessment of disease activity and treatment response more reliable. Simultaneously, several new serological and proteomic biomarkers have become available in the routine clinical setting--for example, a protein biomarker panel for rheumatoid arthritis and a myositis antibody panel for dermatomyositis and polymyositis. This review will focus on commercially available antibody and proteomic biomarkers in rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis (scleroderma), dermatomyositis and polymyositis, and axial spondyloarthritis (including ankylosing spondylitis). It will discuss how these markers can facilitate early diagnosis as well as more accurate subclassification and assessment of disease activity in the clinical setting. The ultimate goal of current and future biomarkers in rheumatic diseases is to enable early detection of these diseases and their clinical manifestations, and to provide effective monitoring and treatment regimens that are tailored to each patient's needs and prognosis. © BMJ Publishing Group Ltd 2015.

  9. Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology.

    Science.gov (United States)

    Wesseling, Hendrik; Guest, Paul C; Lago, Santiago G; Bahn, Sabine

    2014-08-01

    Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

  10. Proteomic Analysis of Saliva Identifies Potential Biomarkers for Orthodontic Tooth Movement

    Science.gov (United States)

    Ellias, Mohd Faiz; Zainal Ariffin, Shahrul Hisham; Karsani, Saiful Anuar; Abdul Rahman, Mariati; Senafi, Shahidan; Megat Abdul Wahab, Rohaya

    2012-01-01

    Orthodontic treatment has been shown to induce inflammation, followed by bone remodelling in the periodontium. These processes trigger the secretion of various proteins and enzymes into the saliva. This study aims to identify salivary proteins that change in expression during orthodontic tooth movement. These differentially expressed proteins can potentially serve as protein biomarkers for the monitoring of orthodontic treatment and tooth movement. Whole saliva from three healthy female subjects were collected before force application using fixed appliance and at 14 days after 0.014′′ Niti wire was applied. Salivary proteins were resolved using two-dimensional gel electrophoresis (2DE) over a pH range of 3–10, and the resulting proteome profiles were compared. Differentially expressed protein spots were then identified by MALDI-TOF/TOF tandem mass spectrometry. Nine proteins were found to be differentially expressed; however, only eight were identified by MALDI-TOF/TOF. Four of these proteins—Protein S100-A9, immunoglobulin J chain, Ig alpha-1 chain C region, and CRISP-3—have known roles in inflammation and bone resorption. PMID:22919344

  11. Positional proteomics in the era of the human proteome project on the doorstep of precision medicine.

    Science.gov (United States)

    Eckhard, Ulrich; Marino, Giada; Butler, Georgina S; Overall, Christopher M

    2016-03-01

    Proteolytic processing is a pervasive and irreversible post-translational modification that expands the protein universe by generating new proteoforms (protein isoforms). Unlike signal peptide or prodomain removal, protease-generated proteoforms can rarely be predicted from gene sequences. Positional proteomic techniques that enrich for N- or C-terminal peptides from proteomes are indispensable for a comprehensive understanding of a protein's function in biological environments since protease cleavage frequently results in altered protein activity and localization. Proteases often process other proteases and protease inhibitors which perturbs proteolytic networks and potentiates the initial cleavage event to affect other molecular networks and cellular processes in physiological and pathological conditions. This review is aimed at researchers with a keen interest in state of the art systems level positional proteomic approaches that: (i) enable the study of complex protease-protease, protease-inhibitor and protease-substrate crosstalk and networks; (ii) allow the identification of proteolytic signatures as candidate disease biomarkers; and (iii) are expected to fill the Human Proteome Project missing proteins gap. We predict that these methodologies will be an integral part of emerging precision medicine initiatives that aim to customize healthcare, converting reactive medicine into a personalized and proactive approach, improving clinical care and maximizing patient health and wellbeing, while decreasing health costs by eliminating ineffective therapies, trial-and-error prescribing, and adverse drug effects. Such initiatives require quantitative and functional proteome profiling and dynamic disease biomarkers in addition to current pharmacogenomics approaches. With proteases at the pathogenic center of many diseases, high-throughput protein termini identification techniques such as TAILS (Terminal Amine Isotopic Labeling of Substrates) and COFRADIC (COmbined

  12. Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

    Directory of Open Access Journals (Sweden)

    Kai P. Law

    2015-05-01

    Full Text Available Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered.

  13. Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

    Science.gov (United States)

    Law, Kai P.; Han, Ting-Li; Tong, Chao; Baker, Philip N.

    2015-01-01

    Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered. PMID:26006232

  14. Investigating the emerging role of comparative proteomics in the search for new biomarkers of metal contamination under varying abiotic conditions

    Energy Technology Data Exchange (ETDEWEB)

    Vellinger, Céline, E-mail: celine.vellinger@gmail.com [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Sohm, Bénédicte, E-mail: benedicte.sohm@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Parant, Marc, E-mail: marc.parant@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Immel, Françoise, E-mail: Francoise.Immel@u-bourgogne.fr [Biogéosciences, CNRS UMR 6282, Université de Bourgogne – Dijon (France); Usseglio-Polatera, Philippe, E-mail: philippe.usseglio-polatera@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France)

    2016-08-15

    This study aims at investigating the potential use of comparative proteomics as a multi-marker approach of metal contamination, taking into account the potential confounding effect of water temperature. The major objective was to identify combinations of proteins specifically responding to a given metal, even if included in a metal mixture. The diagnostic approach was performed via the comparative analysis of protein expression on spot mapping provided by adult males of Gammarus pulex (Amphipoda, Crustacea) respectively exposed to arsenate (As), cadmium (Cd) or a binary mixture of these metals (AsCd) at three realistic temperatures (5, 10 and 15 °C). Proteomic expression analysis was performed by Differential in-Gel Electrophoresis (2D-DiGE), and completed by an adapted inferential statistical approach. Combinations of under/over-expressed protein spots discriminated the metal identity. However, none of these spots discriminated both the individual metal effect (As or Cd) and its effect in metal mixture (AsCd) whatever the tested temperature. Some limits of the two-dimensional analysis of protein spot maps in G. pulex have been highlighted: (i) the presence of contaminating peptides and/or abundant “déja-vu” proteins which can mask the responses of other proteins of interest or (ii) the presence of post-translational modifications. An optimization of the experimental design (especially during the sample preparation) has been described for future investigations. This study has also highlighted (i) the importance of precisely identifying the protein spots of interest to avoid erroneous interpretations in terms of action mechanisms of chemicals and (ii) the importance of working under controlled laboratory conditions with a temperature close to 10 °C. In such conditions, we have demonstrated a higher impact of As than Cd on the energetic metabolism of Gammarus. This As impact is reduced in AsCd mixture confirming the antagonistic interaction of this binary

  15. Investigating the emerging role of comparative proteomics in the search for new biomarkers of metal contamination under varying abiotic conditions

    International Nuclear Information System (INIS)

    Vellinger, Céline; Sohm, Bénédicte; Parant, Marc; Immel, Françoise; Usseglio-Polatera, Philippe

    2016-01-01

    This study aims at investigating the potential use of comparative proteomics as a multi-marker approach of metal contamination, taking into account the potential confounding effect of water temperature. The major objective was to identify combinations of proteins specifically responding to a given metal, even if included in a metal mixture. The diagnostic approach was performed via the comparative analysis of protein expression on spot mapping provided by adult males of Gammarus pulex (Amphipoda, Crustacea) respectively exposed to arsenate (As), cadmium (Cd) or a binary mixture of these metals (AsCd) at three realistic temperatures (5, 10 and 15 °C). Proteomic expression analysis was performed by Differential in-Gel Electrophoresis (2D-DiGE), and completed by an adapted inferential statistical approach. Combinations of under/over-expressed protein spots discriminated the metal identity. However, none of these spots discriminated both the individual metal effect (As or Cd) and its effect in metal mixture (AsCd) whatever the tested temperature. Some limits of the two-dimensional analysis of protein spot maps in G. pulex have been highlighted: (i) the presence of contaminating peptides and/or abundant “déja-vu” proteins which can mask the responses of other proteins of interest or (ii) the presence of post-translational modifications. An optimization of the experimental design (especially during the sample preparation) has been described for future investigations. This study has also highlighted (i) the importance of precisely identifying the protein spots of interest to avoid erroneous interpretations in terms of action mechanisms of chemicals and (ii) the importance of working under controlled laboratory conditions with a temperature close to 10 °C. In such conditions, we have demonstrated a higher impact of As than Cd on the energetic metabolism of Gammarus. This As impact is reduced in AsCd mixture confirming the antagonistic interaction of this binary

  16. Analysis of the variability of human normal urine by 2D-GE reveals a "public" and a "private" proteome.

    Science.gov (United States)

    Molina, Laurence; Salvetat, Nicolas; Ameur, Randa Ben; Peres, Sabine; Sommerer, Nicolas; Jarraya, Fayçal; Ayadi, Hammadi; Molina, Franck; Granier, Claude

    2011-12-10

    The characterization of the normal urinary proteome is steadily progressing and represents a major interest in the assessment of clinical urinary biomarkers. To estimate quantitatively the variability of the normal urinary proteome, urines of 20 healthy people were collected. We first evaluated the impact of the sample conservation temperature on urine proteome integrity. Keeping the urine sample at RT or at +4°C until storage at -80°C seems the best way for long-term storage of samples for 2D-GE analysis. The quantitative variability of the normal urinary proteome was estimated on the 20 urines mapped by 2D-GE. The occurrence of the 910 identified spots was analysed throughout the gels and represented in a virtual 2D gel. Sixteen percent of the spots were found to occur in all samples and 23% occurred in at least 90% of urines. About 13% of the protein spots were present only in 10% or less of the samples, thus representing the most variable part of the normal urinary proteome. Twenty proteins corresponding to a fraction of the fully conserved spots were identified by mass spectrometry. In conclusion, a "public" urinary proteome, common to healthy individuals, seems to coexist with a "private" urinary proteome, which is more specific to each individual. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Approach to cerebrospinal fluid (CSF) biomarker discovery and evaluation in HIV infection.

    Science.gov (United States)

    Price, Richard W; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena; Smith, Richard D; Jacobs, Jon M; Brown, Joseph N; Gisslen, Magnus

    2013-12-01

    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previously-defined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  18. Approach to Cerebrospinal Fluid (CSF) Biomarker Discovery and Evaluation in HIV Infection

    Energy Technology Data Exchange (ETDEWEB)

    Price, Richard W.; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E.; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena S.; Smith, Richard D.; Jacobs, Jon M.; Brown, Joseph N.; Gisslen, Magnus

    2013-12-13

    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previouslydefined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  19. Complete solubilization of formalin-fixed, paraffin-embedded tissue may improve proteomic studies.

    Science.gov (United States)

    Shi, Shan-Rong; Taylor, Clive R; Fowler, Carol B; Mason, Jeffrey T

    2013-04-01

    Tissue-based proteomic approaches (tissue proteomics) are essential for discovering and evaluating biomarkers for personalized medicine. In any proteomics study, the most critical issue is sample extraction and preparation. This problem is especially difficult when recovering proteins from formalin-fixed, paraffin-embedded (FFPE) tissue sections. However, improving and standardizing protein extraction from FFPE tissue is a critical need because of the millions of archival FFPE tissues available in tissue banks worldwide. Recent progress in the application of heat-induced antigen retrieval principles for protein extraction from FFPE tissue has resulted in a number of published FFPE tissue proteomics studies. However, there is currently no consensus on the optimal protocol for protein extraction from FFPE tissue or accepted standards for quantitative evaluation of the extracts. Standardization is critical to ensure the accurate evaluation of FFPE protein extracts by proteomic methods such as reverse phase protein arrays, which is now in clinical use. In our view, complete solubilization of FFPE tissue samples is the best way to achieve the goal of standardizing the recovery of proteins from FFPE tissues. However, further studies are recommended to develop standardized protein extraction methods to ensure quantitative and qualitative reproducibility in the recovery of proteins from FFPE tissues. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Unrestrictive identification of post-translational modifications in the urine proteome without enrichment

    Science.gov (United States)

    2013-01-01

    Background Research on the human urine proteome may lay the foundation for the discovery of relevant disease biomarkers. Post-translational modifications (PTMs) have important effects on the functions of protein biomarkers. Identifying PTMs without enrichment adds no extra steps to conventional identification procedures for urine proteomics. The only difference is that this method requires software that can conduct unrestrictive identifications of PTMs. In this study, routine urine proteomics techniques were used to identify urine proteins. Unspecified PTMs were searched by MODa and PEAKS 6 automated software, followed by a manual search to screen out in vivo PTMs by removing all in vitro PTMs and amino acid substitutions. Results There were 75 peptides with 6 in vivo PTMs that were found by both MODa and PEAKS 6. Of these, 34 peptides in 18 proteins have novel in vivo PTMs compared with the annotation information of these proteins on the Universal Protein Resource website. These new in vivo PTMs had undergone methylation, dehydration, oxidation, hydroxylation, phosphorylation, or dihydroxylation. Conclusions In this study, we identified PTMs of urine proteins without the need for enrichment. Our investigation may provide a useful reference for biomarker discovery in the future. PMID:23317149

  1. Proteomic profiling reveals candidate markers for arsenic-induced skin keratosis.

    Science.gov (United States)

    Guo, Zhiling; Hu, Qin; Tian, Jijing; Yan, Li; Jing, Chuanyong; Xie, Heidi Qunhui; Bao, Wenjun; Rice, Robert H; Zhao, Bin; Jiang, Guibin

    2016-11-01

    Proteomics technology is an attractive biomarker candidate discovery tool that can be applied to study large sets of biological molecules. To identify novel biomarkers and molecular targets in arsenic-induced skin lesions, we have determined the protein profile of arsenic-affected human epidermal stratum corneum by shotgun proteomics. Samples of palm and foot sole from healthy subjects were analyzed, demonstrating similar protein patterns in palm and sole. Samples were collected from the palms of subjects with arsenic keratosis (lesional and adjacent non-lesional samples) and arsenic-exposed subjects without lesions (normal). Samples from non-exposed healthy individuals served as controls. We found that three proteins in arsenic-exposed lesional epidermis were consistently distinguishably expressed from the unaffected epidermis. One of these proteins, the cadherin-like transmembrane glycoprotein, desmoglein 1 (DSG1) was suppressed. Down-regulation of DSG1 may lead to reduced cell-cell adhesion, resulting in abnormal epidermal differentiation. The expression of keratin 6c (KRT6C) and fatty acid binding protein 5 (FABP5) were significantly increased. FABP5 is an intracellular lipid chaperone that plays an essential role in fatty acid metabolism in human skin. This raises a possibility that overexpression of FABP5 may affect the proliferation or differentiation of keratinocytes by altering lipid metabolism. KRT6C is a constituent of the cytoskeleton that maintains epidermal integrity and cohesion. Abnormal expression of KRT6C may affect its structural role in the epidermis. Our findings suggest an important approach for future studies of arsenic-mediated toxicity and skin cancer, where certain proteins may represent useful biomarkers of early diagnoses in high-risk populations and hopefully new treatment targets. Further studies are required to understand the biological role of these markers in skin pathogenesis from arsenic exposure. Copyright © 2016 Elsevier Ltd

  2. Catch and measure-mass spectrometry-based immunoassays in biomarker research.

    Science.gov (United States)

    Weiß, Frederik; van den Berg, Bart H J; Planatscher, Hannes; Pynn, Christopher J; Joos, Thomas O; Poetz, Oliver

    2014-05-01

    Mass spectrometry-based (MS) methods are effective tools for discovering protein biomarker candidates that can differentiate between physiological and pathophysiological states. Promising candidates are validated in studies comprising large patient cohorts. Here, targeted protein analytics are used to increase sample throughput. Methods involving antibodies, such as sandwich immunoassays or Western blots, are commonly applied at this stage. Highly-specific and sensitive mass spectrometry-based immunoassays that have been established in recent years offer a suitable alternative to sandwich immunoassays for quantifying proteins. Mass Spectrometric ImmunoAssays (MSIA) and Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA/iMALDI) are two prominent types of MS-based immunoassays in which the capture is done either at the protein or the peptide level. We present an overview of these emerging types of immunoassays and discuss their suitability for the discovery and validation of protein biomarkers. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

  3. Identification of Host Defense-Related Proteins Using Label-Free Quantitative Proteomic Analysis of Milk Whey from Cows with Staphylococcus aureus Subclinical Mastitis

    Directory of Open Access Journals (Sweden)

    Shaimaa Abdelmegid

    2017-12-01

    Full Text Available Staphylococcus aureus is the most common contagious pathogen associated with bovine subclinical mastitis. Current diagnosis of S. aureus mastitis is based on bacteriological culture of milk samples and somatic cell counts, which lack either sensitivity or specificity. Identification of milk proteins that contribute to host defense and their variable responses to pathogenic stimuli would enable the characterization of putative biomarkers of subclinical mastitis. To accomplish this, milk whey samples from healthy and mastitic dairy cows were analyzed using a label-free quantitative proteomics approach. In total, 90 proteins were identified, of which 25 showed significant differential abundance between healthy and mastitic samples. In silico functional analyses indicated the involvement of the differentially abundant proteins in biological mechanisms and signaling pathways related to host defense including pathogen-recognition, direct antimicrobial function, and the acute-phase response. This proteomics and bioinformatics analysis not only facilitates the identification of putative biomarkers of S. aureus subclinical mastitis but also recapitulates previous findings demonstrating the abundance of host defense proteins in intramammary infection. All mass spectrometry data are available via ProteomeXchange with identifier PXD007516.

  4. Plasma low-molecular-weight proteome profiling identified neuropeptide-Y as a prostate cancer biomarker polypeptide.

    Science.gov (United States)

    Ueda, Koji; Tatsuguchi, Ayako; Saichi, Naomi; Toyama, Atsuhiko; Tamura, Kenji; Furihata, Mutsuo; Takata, Ryo; Akamatsu, Shusuke; Igarashi, Masahiro; Nakayama, Masato; Sato, Taka-Aki; Ogawa, Osamu; Fujioka, Tomoaki; Shuin, Taro; Nakamura, Yusuke; Nakagawa, Hidewaki

    2013-10-04

    In prostate cancer diagnosis, PSA test has greatly contributed to the early detection of prostate cancer; however, expanding overdiagnosis and unnecessary biopsies have emerged as serious issues. To explore plasma biomarkers complementing the specificity of PSA test, we developed a unique proteomic technology QUEST-MS (Quick Enrichment of Small Targets for Mass Spectrometry). The QUEST-MS method based on 96-well formatted sequential reversed-phase chromatography allowing efficient enrichment of <20 kDa proteins quickly and reproducibly. Plasma from 24 healthy controls, 19 benign prostate hypertrophy patients, and 73 prostate cancer patients were purified with QUEST-MS and analyzed by LC/MS/MS. Among 153 057 nonredundant peptides, 189 peptides showed prostate cancer specific detection pattern, which included a neurotransmitter polypeptide neuropeptide-Y (NPY). We further validated the screening results by targeted multiple reaction monitoring technology using independent sample set (n = 110). The ROC curve analysis revealed that logistic regression-based combination of NPY, and PSA showed 81.5% sensitivity and 82.2% specificity for prostate cancer diagnosis. Thus QUEST-MS technology allowed comprehensive and high-throughput profiling of plasma polypeptides and had potential to effectively uncover very low abundant tumor-derived small molecules, such as neurotransmitters, peptide hormones, or cytokines.

  5. Proteomic profile of acute myeloid leukaemia: A review update ...

    African Journals Online (AJOL)

    This review draws attention to the progress and advancements in cancer proteomics technology with the aim of simplifying the understanding of the mechanisms underlying the disease and to contribute to detection of biomarkers in addition to the development of novel treatments. Given that proteome is a dynamic entity of ...

  6. Innovative biomarkers in psychiatric disorders: a major clinical challenge in psychiatry.

    Science.gov (United States)

    Lozupone, Madia; Seripa, Davide; Stella, Eleonora; La Montagna, Maddalena; Solfrizzi, Vincenzo; Quaranta, Nicola; Veneziani, Federica; Cester, Alberto; Sardone, Rodolfo; Bonfiglio, Caterina; Giannelli, Gianluigi; Bisceglia, Paola; Bringiotti, Roberto; Daniele, Antonio; Greco, Antonio; Bellomo, Antonello; Logroscino, Giancarlo; Panza, Francesco

    2017-09-01

    Currently, the diagnosis of psychiatric illnesses is based upon DSM-5 criteria. Although endophenotype-specificity for a particular disorder is discussed, the identification of objective biomarkers is ongoing for aiding diagnosis, prognosis, or clinical response to treatment. We need to improve the understanding of the biological abnormalities in psychiatric illnesses across conventional diagnostic boundaries. The present review investigates the innovative post-genomic knowledge used for psychiatric illness diagnostics and treatment response, with a particular focus on proteomics. Areas covered: This review underlines the contribution that psychiatric innovative biomarkers have reached in relation to diagnosis and theragnosis of psychiatric illnesses. Furthermore, it encompasses a reliable representation of their involvement in disease through proteomics, metabolomics/pharmacometabolomics and lipidomics techniques, including the possible role that gut microbiota and CYP2D6 polimorphisms may play in psychiatric illnesses. Expert opinion: Etiologic heterogeneity, variable expressivity, and epigenetics may impact clinical manifestations, making it difficult for a single measurement to be pathognomonic for multifaceted psychiatric disorders. Academic, industry, or government's partnerships may successfully identify and validate new biomarkers so that unfailing clinical tests can be developed. Proteomics, metabolomics, and lipidomics techniques are considered to be helpful tools beyond neuroimaging and neuropsychology for the phenotypic characterization of brain diseases.

  7. Liver proteome response of largemouth bass (Micropterus salmoides) exposed to several environmental contaminants: Potential insights into biomarker development

    International Nuclear Information System (INIS)

    Sanchez, Brian C.; Ralston-Hooper, Kimberly J.; Kowalski, Kevin A.; Dorota Inerowicz, H.; Adamec, Jiri; Sepulveda, Maria S.

    2009-01-01

    Liver proteome response of largemouth bass (Micropterus salmoides) exposed to environmental contaminants was analyzed to identify novel biomarkers of exposure. Adult male bass were exposed to cadmium chloride (CdCl 2 ), atrazine, PCB 126, phenanthrene, or toxaphene via intraperitoneal injection with target body burdens of 0.00067, 3.0, 2.5, 50, and 100 μg/g, respectively. After a 96 h exposure, hepatic proteins were separated with two-dimensional gel electrophoresis and differentially expressed proteins (vs. controls) recognized and identified with MALDI-TOF/TOF mass spectrometry. We identified, 30, 18, eight, 19, and five proteins as differentially expressed within the CdCl 2 , atrazine, PCB 126, phenanthrene, and toxaphene treatments, respectively. Alterations were observed in the expression of proteins associated with cellular ion homeostasis (toxaphene), oxidative stress (phenanthrene, PCB 126), and energy production including glycolysis (CdCl 2 , atrazine) and ATP synthesis (atrazine). This work supports the further evaluation of several of these proteins as biomarkers of contaminant exposure in fish.

  8. Gross cystic disease fluid protein-15/prolactin-inducible protein as a biomarker for keratoconus disease.

    Directory of Open Access Journals (Sweden)

    Shrestha Priyadarsini

    Full Text Available Keratoconus (KC is a bilateral degenerative disease of the cornea characterized by corneal bulging, stromal thinning, and scarring. The etiology of the disease is unknown. In this study, we identified a new biomarker for KC that is present in vivo and in vitro. In vivo, tear samples were collected from age-matched controls with no eye disease (n = 36 and KC diagnosed subjects (n = 17. Samples were processed for proteomics using LC-MS/MS. In vitro, cells were isolated from controls (Human Corneal Fibroblasts-HCF and KC subjects (Human Keratoconus Cells-HKC and stimulated with a Vitamin C (VitC derivative for 4 weeks, and with one of the three transforming growth factor-beta (TGF-β isoforms. Samples were analyzed using real-time PCR and Western Blots. By using proteomics analysis, the Gross cystic disease fluid protein-15 (GCDFP-15 or prolactin-inducible protein (PIP was found to be the best independent biomarker able to discriminate between KC and controls. The intensity of GCDFP-15/PIP was significantly higher in healthy subjects compared to KC-diagnosed. Similar findings were seen in vitro, using a 3D culture model. All three TGF-β isoforms significantly down-regulated the expression of GCDFP-15/PIP. Zinc-alpha-2-glycoprotein (AZGP1, a protein that binds to PIP, was identified by proteomics and cell culture to be highly regulated. In this study by different complementary techniques we confirmed the potential role of GCDFP-15/PIP as a novel biomarker for KC disease. It is likely that exploring the GCDFP-15/PIP-AZGP1 interactions will help better understand the mechanism of KC disease.

  9. Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer.

    Directory of Open Access Journals (Sweden)

    Meredith C Henderson

    Full Text Available Despite significant advances in breast imaging, the ability to accurately detect Breast Cancer (BC remains a challenge. With the discovery of key biomarkers and protein signatures for BC, proteomic technologies are currently poised to serve as an ideal diagnostic adjunct to imaging. Research studies have shown that breast tumors are associated with systemic changes in levels of both serum protein biomarkers (SPB and tumor associated autoantibodies (TAAb. However, the independent contribution of SPB and TAAb expression data for identifying BC relative to a combinatorial SPB and TAAb approach has not been fully investigated. This study evaluates these contributions using a retrospective cohort of pre-biopsy serum samples with known clinical outcomes collected from a single site, thus minimizing potential site-to-site variation and enabling direct assessment of SPB and TAAb contributions to identify BC. All serum samples (n = 210 were collected prior to biopsy. These specimens were obtained from 18 participants with no evidence of breast disease (ND, 92 participants diagnosed with Benign Breast Disease (BBD and 100 participants diagnosed with BC, including DCIS. All BBD and BC diagnoses were based on pathology results from biopsy. Statistical models were developed to differentiate BC from non-BC (i.e., BBD and ND using expression data from SPB alone, TAAb alone, and a combination of SPB and TAAb. When SPB data was independently used for modeling, clinical sensitivity and specificity for detection of BC were 74.7% and 77.0%, respectively. When TAAb data was independently used, clinical sensitivity and specificity for detection of BC were 72.2% and 70.8%, respectively. When modeling integrated data from both SPB and TAAb, the clinical sensitivity and specificity for detection of BC improved to 81.0% and 78.8%, respectively. These data demonstrate the benefit of the integration of SPB and TAAb data and strongly support the further development of

  10. Opportunities and Challenges of Proteomics in Pediatric Patients: Circulating Biomarkers After Hematopoietic Stem Cell Transplantation As a Successful Example

    Science.gov (United States)

    Paczesny, Sophie; Duncan, Christine; Jacobsohn, David; Krance, Robert; Leung, Kathryn; Carpenter, Paul; Bollard, Catherine; Renbarger, Jamie; Cooke, Kenneth

    2015-01-01

    Biomarkers have the potential to improve diagnosis and prognosis, facilitate targeted treatment, and reduce health care costs. Thus, there is great hope that biomarkers will be integrated in all clinical decisions in the near future. A decade ago, the biomarker field was launched with great enthusiasm because mass spectrometry revealed that blood contains a rich library of candidate biomarkers. However, biomarker research has not yet delivered on its promise due to several limitations: (i) improper sample handling and tracking as well as limited sample availability in the pediatric population, (ii) omission of appropriate controls in original study designs, (iii) lability and low abundance of interesting biomarkers in blood, and (iv) the inability to mechanistically tie biomarker presence to disease biology. These limitations as well as successful strategies to overcome them are discussed in this review. Several advances in biomarker discovery and validation have been made in hematopoietic stem cell transplantation, the current most effective tumor immunotherapy, and these could serve as examples for other conditions. This review provides fresh optimism that biomarkers clinically relevant in pediatrics are closer to being realized based on: (i) a uniform protocol for low-volume blood collection and preservation, (ii) inclusion of well-controlled independent cohorts, (iii) novel technologies and instrumentation with low analytical sensitivity, and (iv) integrated animal models for exploring potential biomarkers and targeted therapies. PMID:25196024

  11. The cerebrospinal fluid proteome in HIV infection: change associated with disease severity.

    Energy Technology Data Exchange (ETDEWEB)

    Angel, Thomas E.; Jacobs, Jon M.; Spudich, Serena S.; Gritsenko, Marina A.; Fuchs, Dietmar; Liegler, Teri; Zetterberg, Henrik; Camp, David G.; Price, Richard W.; Smith, Richard D.

    2012-03-20

    Central nervous system (CNS) infection is a constant feature of systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment. After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral and correlated abundances of identified proteins (a) within and between subjects, (b) with all other proteins across the entire sample set, and (c) with 'external' CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) {le}0.3 and {ge}0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with

  12. The Use of Proteomics in Assisted Reproduction.

    Science.gov (United States)

    Kosteria, Ioanna; Anagnostopoulos, Athanasios K; Kanaka-Gantenbein, Christina; Chrousos, George P; Tsangaris, George T

    2017-01-01

    Despite the explosive increase in the use of Assisted Reproductive Technologies (ART) over the last 30 years, their success rates remain suboptimal. Proteomics is a rapidly-evolving technology-driven science that has already been widely applied in the exploration of human reproduction and fertility, providing useful insights into its physiology and leading to the identification of numerous proteins that may be potential biomarkers and/or treatment targets of a successful ART pregnancy. Here we present a brief overview of the techniques used in proteomic analyses and attempt a comprehensive presentation of recent data from mass spectrometry-based proteomic studies in humans, regarding all components of ARTs, including the male and female gamete, the derived zygote and embryo, the endometrium and, finally, the ART offspring both pre- and postnatally. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  13. Effects of High-Pressure Treatment on the Muscle Proteome of Hake by Bottom-Up Proteomics.

    Science.gov (United States)

    Carrera, Mónica; Fidalgo, Liliana G; Saraiva, Jorge A; Aubourg, Santiago P

    2018-05-02

    A bottom-up proteomics approach was applied for the study of the effects of high-pressure (HP) treatment on the muscle proteome of fish. The performance of the approach was established for a previous HP treatment (150-450 MPa for 2 min) on frozen (up to 5 months at -10 °C) European hake ( Merluccius merluccius). Concerning possible protein biomarkers of quality changes, a significant degradation after applying a pressure ≥430 MPa could be observed for phosphoglycerate mutase-1, enolase, creatine kinase, fructose bisphosphate aldolase, triosephosphate isomerase, and nucleoside diphosphate kinase; contrary, electrophoretic bands assigned to tropomyosin, glyceraldehyde-3-phosphate dehydrogenase, and beta parvalbumin increased their intensity after applying a pressure ≥430 MPa. This repository of potential protein biomarkers may be very useful for further HP investigations related to fish quality.

  14. Environmental monitoring of Domingo Rubio stream (Huelva Estuary, SW Spain) by combining conventional biomarkers and proteomic analysis in Carcinus maenas

    Energy Technology Data Exchange (ETDEWEB)

    Montes Nieto, Rafael [Department of Biochemistry and Molecular Biology, University of Cordoba, Severo Ochoa Building, Rabanales Campus, Highway A4 Km 396a, 14071 Cordoba (Spain); Garcia-Barrera, Tamara; Gomez-Ariza, Jose-Luis [Department of Chemistry and Materials Sciences, University of Huelva, Faculty of Experimental Sciences, El Carmen Campus, 21007 Huelva (Spain); Lopez-Barea, Juan, E-mail: bb1lobaj@uco.e [Department of Biochemistry and Molecular Biology, University of Cordoba, Severo Ochoa Building, Rabanales Campus, Highway A4 Km 396a, 14071 Cordoba (Spain)

    2010-02-15

    Element load, conventional biomarkers and altered protein expression profiles were studied in Carcinus maenas crabs, to assess contamination of 'Domingo Rubio' stream, an aquatic ecosystem that receives pyritic metals, industrial contaminants, and pesticides. Lower antioxidative activities - glucose-6-phosphate and 6-phosphogluconate dehydrogenases, catalase - were found in parallel to higher levels of damaged biomolecules - malondialdehyde, oxidized glutathione -, due to oxidative lesions promoted by contaminants, as the increased levels of essential - Zn, Cu, Co - and nonessential - Cr, Ni, Cd - elements. Utility of Proteomics to assess environmental quality was confirmed, especially after considering the six proteins identified by de novo sequencing through capLC-muESI-ITMS/MS and homology search on databases. They include tripartite motif-containing protein 11 and ATF7 transcription factor (upregulated), plus CBR-NHR-218 nuclear hormone receptor, two components of the ABC transporters and aldehyde dehydrogenase (downregulated). These proteins could be used as novel potential biomarkers of the deleterious effects of pollutants present in the area. - Pollution assessment at 'Domingo Rubio' stream (Spain).

  15. Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

    Science.gov (United States)

    Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva

    2017-01-01

    No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as

  16. Evaluation of FASP, SP3, and iST Protocols for Proteomic Sample Preparation in the Low Microgram Range.

    Science.gov (United States)

    Sielaff, Malte; Kuharev, Jörg; Bohn, Toszka; Hahlbrock, Jennifer; Bopp, Tobias; Tenzer, Stefan; Distler, Ute

    2017-11-03

    Efficient and reproducible sample preparation is a prerequisite for any robust and sensitive quantitative bottom-up proteomics workflow. Here, we performed an independent comparison between single-pot solid-phase-enhanced sample preparation (SP3), filter-aided sample preparation (FASP), and a commercial kit based on the in-StageTip (iST) method. We assessed their performance for the processing of proteomic samples in the low μg range using varying amounts of HeLa cell lysate (1-20 μg of total protein). All three workflows showed similar performances for 20 μg of starting material. When handling sample sizes below 10 μg, the number of identified proteins and peptides as well as the quantitative reproducibility and precision drastically dropped in case of FASP. In contrast, SP3 and iST provided high proteome coverage even in the low μg range. Even when digesting 1 μg of starting material, both methods still enabled the identification of over 3000 proteins and between 25 000 and 30 000 peptides. On average, the quantitative reproducibility between experimental replicates was slightly higher in case of SP3 (R 2 = 0.97 (SP3); R 2 = 0.93 (iST)). Applying SP3 toward the characterization of the proteome of FACS-sorted tumor-associated macrophages in the B16 tumor model enabled the quantification of 2965 proteins and revealed a "mixed" M1/M2 phenotype.

  17. A Proteomics Sample Preparation Method for Mature, Recalcitrant Leaves of Perennial Plants

    Science.gov (United States)

    Na, Zhang; Chengying, Lao; Bo, Wang; Dingxiang, Peng; Lijun, Liu

    2014-01-01

    Sample preparation is key to the success of proteomics studies. In the present study, two sample preparation methods were tested for their suitability on the mature, recalcitrant leaves of six representative perennial plants (grape, plum, pear, peach, orange, and ramie). An improved sample preparation method was obtained: Tris and Triton X-100 were added together instead of CHAPS to the lysis buffer, and a 20% TCA-water solution and 100% precooled acetone were added after the protein extraction for the further purification of protein. This method effectively eliminates nonprotein impurities and obtains a clear two-dimensional gel electrophoresis array. The method facilitates the separation of high-molecular-weight proteins and increases the resolution of low-abundance proteins. This method provides a widely applicable and economically feasible technology for the proteomic study of the mature, recalcitrant leaves of perennial plants. PMID:25028960

  18. A proteomics sample preparation method for mature, recalcitrant leaves of perennial plants.

    Directory of Open Access Journals (Sweden)

    Deng Gang

    Full Text Available Sample preparation is key to the success of proteomics studies. In the present study, two sample preparation methods were tested for their suitability on the mature, recalcitrant leaves of six representative perennial plants (grape, plum, pear, peach, orange, and ramie. An improved sample preparation method was obtained: Tris and Triton X-100 were added together instead of CHAPS to the lysis buffer, and a 20% TCA-water solution and 100% precooled acetone were added after the protein extraction for the further purification of protein. This method effectively eliminates nonprotein impurities and obtains a clear two-dimensional gel electrophoresis array. The method facilitates the separation of high-molecular-weight proteins and increases the resolution of low-abundance proteins. This method provides a widely applicable and economically feasible technology for the proteomic study of the mature, recalcitrant leaves of perennial plants.

  19. Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes.

    Science.gov (United States)

    Wen, Li; Liu, Ye-Fang; Jiang, Cen; Zeng, Shao-Qian; Su, Yue; Wu, Wen-Jun; Liu, Xi-Yang; Wang, Jian; Liu, Ying; Su, Chen; Li, Bai-Xue; Feng, Quan-Sheng

    2018-03-08

    Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.

  20. Evaluation of mass spectrometry of urinary proteins and peptides as biomarkers for cats at risk of developing azotemia.

    Science.gov (United States)

    Jepson, Rosanne E; Coulton, Gary R; Cowan, Matthew L; Markwell, Peter; Syme, Harriet M; Elliott, Jonathan

    2013-02-01

    To evaluate proteomic delineation of feline urine by mass spectrometry as a method for identifying biomarkers in cats at risk of developing azotemia. Urine samples from geriatric cats (> 9 years old) with chronic kidney disease and nonazotemic cats that either remained nonazotemic (n = 10) or developed azotemia (10) within 1 year. Optimization studies with pooled urine were performed to facilitate the use of surface enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF-MS) for analysis of the urinary proteome of cats. Urine samples from nonazotemic cats at entry to the study were analyzed via SELDI-TOF-MS with weak cation exchange and strong anion exchange arrays. Spectral data were compared to identify biomarkers for development of azotemia. Low protein concentration in feline urine precluded direct application to array surfaces, and a buffer exchange and concentration step was required prior to SELDI-TOF-MS analysis. Three preparation conditions by use of weak cation and strong anion exchange arrays were selected on the basis of optimization studies for detection of biomarkers. Eight potential biomarkers with an m/z of 2,822, 9,886, 10,033, 10,151, 10,234, 11,653, 4,421, and 9,505 were delineated. SELDI-TOF-MS can be used to detect urinary low-molecular weight peptides and proteins that may represent biomarkers for early detection of renal damage. Further study is required to purify and identify potential biomarkers before their use in a clinical setting.

  1. Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

    Directory of Open Access Journals (Sweden)

    Anjali K Nath

    Full Text Available Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs. However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies.Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1 as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF samples from women carrying normal fetuses and those with CHDs.The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs.

  2. Identification of plasma biomarker candidates in glioblastoma using an antibody-array-based proteomic approach

    International Nuclear Information System (INIS)

    Zupancic, Klemen; Blejec, Andrej; Herman, Ana; Veber, Matija; Verbovsek, Urska; Korsic, Marjan; Knezevic, Miomir; Rozman, Primoz; Turnsek, Tamara Lah; Gruden, Kristina; Motaln, Helena

    2014-01-01

    Glioblastoma multiforme (GBM) is a brain tumour with a very high patient mortality rate, with a median survival of 47 weeks. This might be improved by the identification of novel diagnostic, prognostic and predictive therapy-response biomarkers, preferentially through the monitoring of the patient blood. The aim of this study was to define the impact of GBM in terms of alterations of the plasma protein levels in these patients. We used a commercially available antibody array that includes 656 antibodies to analyse blood plasma samples from 17 healthy volunteers in comparison with 17 blood plasma samples from patients with GBM. We identified 11 plasma proteins that are statistically most strongly associated with the presence of GBM. These proteins belong to three functional signalling pathways: T-cell signalling and immune responses; cell adhesion and migration; and cell-cycle control and apoptosis. Thus, we can consider this identified set of proteins as potential diagnostic biomarker candidates for GBM. In addition, a set of 16 plasma proteins were significantly associated with the overall survival of these patients with GBM. Guanine nucleotide binding protein alpha (GNAO1) was associated with both GBM presence and survival of patients with GBM. Antibody array analysis represents a useful tool for the screening of plasma samples for potential cancer biomarker candidates in small-scale exploratory experiments; however, clinical validation of these candidates requires their further evaluation in a larger study on an independent cohort of patients

  3. Combining Search Engines for Comparative Proteomics

    Science.gov (United States)

    Tabb, David

    2012-01-01

    Many proteomics laboratories have found spectral counting to be an ideal way to recognize biomarkers that differentiate cohorts of samples. This approach assumes that proteins that differ in quantity between samples will generate different numbers of identifiable tandem mass spectra. Increasingly, researchers are employing multiple search engines to maximize the identifications generated from data collections. This talk evaluates four strategies to combine information from multiple search engines in comparative proteomics. The “Count Sum” model pools the spectra across search engines. The “Vote Counting” model combines the judgments from each search engine by protein. Two other models employ parametric and non-parametric analyses of protein-specific p-values from different search engines. We evaluated the four strategies in two different data sets. The ABRF iPRG 2009 study generated five LC-MS/MS analyses of “red” E. coli and five analyses of “yellow” E. coli. NCI CPTAC Study 6 generated five concentrations of Sigma UPS1 spiked into a yeast background. All data were identified with X!Tandem, Sequest, MyriMatch, and TagRecon. For both sample types, “Vote Counting” appeared to manage the diverse identification sets most effectively, yielding heightened discrimination as more search engines were added.

  4. Gel-based proteomics of liver cancer progression in rat

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Miller, Leah M; Novikoff, Phyllis M

    2011-01-01

    A significant challenge in proteomics biomarker research is to identify the changes that are of highest diagnostic interest, among the many unspecific aberrations associated with disease burden and inflammation. In the present study liver tissue specimens (n=18) from six experimental stages were ...

  5. Identification of candidate biomarkers of the exposure to PCBs in contaminated cattle: A gene expression- and proteomic-based approach.

    Science.gov (United States)

    Girolami, F; Badino, P; Spalenza, V; Manzini, L; Renzone, G; Salzano, A M; Dal Piaz, F; Scaloni, A; Rychen, G; Nebbia, C

    2018-05-28

    Dioxins and polychlorinated biphenyls (PCBs) are widespread and persistent contaminants. Through a combined gene expression/proteomic-based approach, candidate biomarkers of the exposure to such environmental pollutants in cattle subjected to a real eco-contamination event were identified. Animals were removed from the polluted area and fed a standard ration for 6 months. The decontamination was monitored by evaluating dioxin and PCB levels in pericaudal fat two weeks after the removal from the contaminated area (day 0) and then bimonthly for six months (days 59, 125 and 188). Gene expression measurements demonstrated that CYP1B1 expression was significantly higher in blood lymphocytes collected in contaminated animals (day 0), and decreased over time during decontamination. mRNA levels of interleukin 2 showed an opposite quantitative trend. MALDI-TOF-MS polypeptide profiling of serum samples ascertained a progressive decrease (from day 0 to 188) of serum levels of fibrinogen β-chain and serpin A3-7-like fragments, apolipoprotein (APO) C-II and serum amyloid A-4 protein, along with an augmented representation of transthyretin isoforms, as well as APOC-III and APOA-II proteins during decontamination. When differentially represented species were combined with serum antioxidant, acute phase and proinflammatory protein levels already ascertained in the same animals (Cigliano et al., 2016), bioinformatics unveiled an interaction network linking together almost all components. This suggests the occurrence of a complex PCB-responsive mechanism associated with animal contamination/decontamination, including a cohort of protein/polypeptide species involved in blood redox homeostasis, inflammation and lipid transport. All together, these results suggest the use in combination of such biomarkers for identifying PCB-contaminated animals, and for monitoring the restoring of their healthy condition following a decontamination process. Copyright © 2018 Elsevier B.V. All

  6. Targeted proteomics guided by label-free global proteome analysis in saliva reveal transition signatures from health to periodontal disease.

    Science.gov (United States)

    Bostanci, Nagihan; Selevsek, Nathalie; Wolski, Witold; Grossmann, Jonas; Bao, Kai; Wahlander, Asa; Trachsel, Christian; Schlapbach, Ralph; Özturk, Veli Özgen; Afacan, Beral; Emingil, Gulnur; Belibasakis, Georgios N

    2018-04-02

    Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. We carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n=67, health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n=82). The LFQ platform led to the discovery of 119 proteins with at least two-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1), with maximum area under the receiver operating curve >0.97. This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum

  7. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Astrid Wachter

    2015-11-01

    Full Text Available Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

  8. Identification of 10 Candidate Biomarkers Distinguishing Tuberculous and Malignant Pleural Fluid by Proteomic Methods.

    Science.gov (United States)

    Lee, Chang Youl; Hong, Ji Young; Lee, Myung Goo; Suh, In Bum

    2017-11-01

    Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. We used samples from five patients with transudative pleural effusions for internal standard, five patients with tuberculous pleurisy, and the same numbers of patients having malignant effusions were enrolled in the study. We analyzed the proteins in pleural fluid from patients using a technique that combined two-dimensional liquid-phase electrophoresis and matrix assisted laser desorption/ionization-time of flight-mass spectrometry. We identified a total of 10 proteins with statistical significance. Among 10 proteins, trasthyretin, haptoglobin, metastasis-associated protein 1, t-complex protein 1, and fibroblast growth factor-binding protein 1 were related with malignant pleural effusions and human ceruloplasmin, lysozyme precursor, gelsolin, clusterin C complement lysis inhibitor, and peroxirexdoxin 3 were expressed several times or more in tuberculous pleural effusions. Highly expressed proteins in malignant pleural effusion were associated with carcinogenesis and cell growth, and proteins associated with tuberculous pleural effusion played a role in the response to inflammation and fibrosis. These findings will aid in the development of novel diagnostic tools for tuberculous pleurisy and malignant pleural effusion of lung cancer. © Copyright: Yonsei University College of Medicine 2017

  9. Proteomic study on gender differences in aging kidney of mice

    Directory of Open Access Journals (Sweden)

    Cristobal Susana

    2009-04-01

    Full Text Available Abstract Background This study aims to analyze sex differences in mice aging kidney. We applied a proteomic technique based on subfractionation, and liquid chromatography coupled with 2-DE. Samples from male and female CD1-Swiss outbred mice from 28 weeks, 52 weeks, and 76 weeks were analysed by 2-DE, and selected proteins were identified by matrix assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS. Results This proteomic analysis detected age-related changes in protein expression in 55 protein-spots, corresponding to 22 spots in males and 33 spots in females. We found a protein expression signature (PES of aging composed by 8 spots, common for both genders. The identified proteins indicated increases in oxidative and proteolytic proteins and decreases in glycolytic proteins, and antioxidant enzymes. Conclusion Our results provide insights into the gender differences associated to the decline of kidney function in aging. Thus, we show that proteomics can provide valuable information on age-related changes in expression levels of proteins and related modifications. This pilot study is still far from providing candidates for aging-biomarkers. However, we suggest that the analysis of these proteins could suggest mechanisms of cellular aging in kidney, and improve the kidney selection for transplantation.

  10. A multiplex quantitative proteomics strategy for protein biomarker studies in urinary exosomes.

    Science.gov (United States)

    Raj, Delfin A A; Fiume, Immacolata; Capasso, Giovambattista; Pocsfalvi, Gabriella

    2012-06-01

    Urinary exosomes have received considerable attention as a potential biomarker source for the diagnosis of renal diseases. Notwithstanding, their use in protein biomarker research is hampered by the lack of efficient methods for vesicle isolation, lysis, and protein quantification. Here we report an improved ultracentrifugation-based method that facilitates the solubilization and removal of major impurities associated with urinary exosomes. A double-cushion sucrose/D(2)O centrifugation step was used after a two-step differential centrifugation to separate exosomes from the heavier vesicles. After the removal of uromodulin, 378 and 79 unique proteins were identified, respectively, in low- and high-density fractions. Comparison of our data with two previously published data sets helped to define proteins commonly found in urinary exosomes. Lysis, protein extraction, and in-solution digestion of exosomes were then optimized for MudPIT application. More than a hundred exosomal proteins were quantified by four-plex iTRAQ analysis of single and pooled samples from two different age groups. For healthy men, six proteins (TSN1, PODXL, IDHC, PPAP, ACBP, and ANXA5) showed significant expression differences between exosome pools of those aged 25-50 and 50-70 years old. Thus, exosomes isolated by our method provide the basis for the development of robust quantitative methods for protein biomarker research.

  11. Ocular Proteomics with Emphasis on Two-Dimensional Gel Electrophoresis and Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Honoré Bent

    2010-01-01

    Full Text Available Abstract The intention of this review is to provide an overview of current methodologies employed in the rapidly developing field of ocular proteomics with emphasis on sample preparation, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE and mass spectrometry (MS. Appropriate sample preparation for the diverse range of cells and tissues of the eye is essential to ensure reliable results. Current methods of protein staining for 2D-PAGE, protein labelling for two-dimensional difference gel electrophoresis, gel-based expression analysis and protein identification by MS are summarised. The uses of gel-free MS-based strategies (MuDPIT, iTRAQ, ICAT and SILAC are also discussed. Proteomic technologies promise to shed new light onto ocular disease processes that could lead to the discovery of strong novel biomarkers and therapeutic targets useful in many ophthalmic conditions.

  12. The proteome of human saliva

    Science.gov (United States)

    Griffin, Timothy J.

    2013-05-01

    Human saliva holds tremendous potential for transforming disease and health diagnostics given its richness of molecular information and non-invasive collection. Enumerating its molecular constituents is an important first step towards reaching this potential. Among the molecules in saliva, proteins and peptides arguably have the most value: they can directly indicate biochemical functions linked to a health condition/disease state, and they are attractive targets for biomarker assay development. However, cataloging and defining the human salivary proteome is challenging given the dynamic, chemically heterogeneous and complex nature of the system. In addition, the overall human saliva proteome is composed of several "sub-proteomes" which include: intact full length proteins, proteins carrying post-translational modifications (PTMs), low molecular weight peptides, and the metaproteome, derived from protein products from nonhuman organisms (e.g. microbes) present in the oral cavity. Presented here will be a summary of communal efforts to meet the challenge of characterizing the multifaceted saliva proteome, focusing on the use of mass spectrometry as the proteomic technology of choice. Implications of these efforts to characterize the salivary proteome in the context of disease diagnostics will also be discussed.

  13. Advances of Salivary Proteomics in Oral Squamous Cell Carcinoma (OSCC Detection: An Update

    Directory of Open Access Journals (Sweden)

    Rabia Sannam Khan

    2016-12-01

    Full Text Available Oral cancer refers to malignancies that have higher morbidity and mortality rates due to the late stage diagnosis and no early detection of a reliable diagnostic marker, while oral squamous cell carcinoma (OSCC is amongst the world’s top ten most common cancers. Diagnosis of cancer requires highly sensitive and specific diagnostic tools which can support untraceable hidden sites of OSCC, yet to be unleashed, for which plenty of biomarkers are identified; the most recommended biomarker detection medium for OSCC includes biological fluids, such as blood and saliva. Saliva holds a promising future in the search for new clinical biomarkers that are easily accessible, less complex, accurate, and cost effective as well as being a non-invasive technique to follow, by analysing the malignant cells’ molecular pathology obtained from saliva through proteomic, genomic and transcriptomic approaches. However, protein biomarkers provide an immense potential for developing novel marker-based assays for oral cancer, hence this current review offers an overall focus on the discovery of a panel of candidates as salivary protein biomarkers, as well as the proteomic tools used for their identification and their significance in early oral cancer detection.

  14. Anthelmintic metabolism in parasitic helminths: proteomic insights.

    Science.gov (United States)

    Brophy, Peter M; MacKintosh, Neil; Morphew, Russell M

    2012-08-01

    Anthelmintics are the cornerstone of parasitic helminth control. Surprisingly, understanding of the biochemical pathways used by parasitic helminths to detoxify anthelmintics is fragmented, despite the increasing global threat of anthelmintic resistance within the ruminant and equine industries. Reductionist biochemistry has likely over-estimated the enzymatic role of glutathione transferases in anthelmintic metabolism and neglected the potential role of the cytochrome P-450 superfamily (CYPs). Proteomic technologies offers the opportunity to support genomics, reverse genetics and pharmacokinetics, and provide an integrated insight into both the cellular mechanisms underpinning response to anthelmintics and also the identification of biomarker panels for monitoring the development of anthelmintic resistance. To date, there have been limited attempts to include proteomics in anthelmintic metabolism studies. Optimisations of membrane, post-translational modification and interaction proteomic technologies in helminths are needed to especially study Phase I CYPs and Phase III ABC transporter pumps for anthelmintics and their metabolites.

  15. Biomarkers of Therapeutic Response in the IL-23 Pathway in Inflammatory Bowel Disease

    OpenAIRE

    Cayatte, Corinne; Joyce-Shaikh, Barbara; Vega, Felix; Boniface, Katia; Grein, Jeffrey; Murphy, Erin; Blumenschein, Wendy M; Chen, Smiley; Malinao, Maria-Christina; Basham, Beth; Pierce, Robert H; Bowman, Edward P; McKenzie, Brent S; Elson, Charles O; Faubion, William A

    2012-01-01

    OBJECTIVES: Interleukin-23 (IL-23) has emerged as a new therapeutic target for the treatment of inflammatory bowel disease (IBD). As biomarkers of disease state and treatment efficacy are becoming increasingly important in drug development, we sought to identify efficacy biomarkers for anti-IL-23 therapy in Crohn's disease (CD). METHODS: Candidate IL-23 biomarkers, downstream of IL-23 signaling, were identified using shotgun proteomic analysis of feces and colon lavages obtained from a short-...

  16. Proteomic biomarkers predicting lymph node involvement in serum of cervical cancer patients. Limitations of SELDI-TOF MS

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    Van Gorp Toon

    2012-06-01

    Full Text Available Abstract Background Lymph node status is not part of the staging system for cervical cancer, but provides important information for prognosis and treatment. We investigated whether lymph node status can be predicted with proteomic profiling. Material & methods Serum samples of 60 cervical cancer patients (FIGO I/II were obtained before primary treatment. Samples were run through a HPLC depletion column, eliminating the 14 most abundant proteins ubiquitously present in serum. Unbound fractions were concentrated with spin filters. Fractions were spotted onto CM10 and IMAC30 surfaces and analyzed with surface-enhanced laser desorption time of flight (SELDI-TOF mass spectrometry (MS. Unsupervised peak detection and peak clustering was performed using MASDA software. Leave-one-out (LOO validation for weighted Least Squares Support Vector Machines (LSSVM was used for prediction of lymph node involvement. Other outcomes were histological type, lymphvascular space involvement (LVSI and recurrent disease. Results LSSVM models were able to determine LN status with a LOO area under the receiver operating characteristics curve (AUC of 0.95, based on peaks with m/z values 2,698.9, 3,953.2, and 15,254.8. Furthermore, we were able to predict LVSI (AUC 0.81, to predict recurrence (AUC 0.92, and to differentiate between squamous carcinomas and adenocarcinomas (AUC 0.88, between squamous and adenosquamous carcinomas (AUC 0.85, and between adenocarcinomas and adenosquamous carcinomas (AUC 0.94. Conclusions Potential markers related with lymph node involvement were detected, and protein/peptide profiling support differentiation between various subtypes of cervical cancer. However, identification of the potential biomarkers was hampered by the technical limitations of SELDI-TOF MS.

  17. Proteomic study of benign and malignant pleural effusion.

    Science.gov (United States)

    Li, Hongqing; Tang, Zhonghao; Zhu, Huili; Ge, Haiyan; Cui, Shilei; Jiang, Weiping

    2016-06-01

    Lung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion. This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model. We chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker. A GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion. This model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

  18. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 [1]), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 [2])...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  19. Unravelling the nuclear matrix proteome

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Knol, Jaco C; Jimenez, Connie R

    2009-01-01

    The nuclear matrix (NM) model posits the presence of a protein/RNA scaffold that spans the mammalian nucleus. The NM proteins are involved in basic nuclear function and are a promising source of protein biomarkers for cancer. Importantly, the NM proteome is operationally defined as the proteins...

  20. Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease.

    Directory of Open Access Journals (Sweden)

    Jochen Neuhaus

    Full Text Available BACKGROUND: Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease. METHODOLOGY/PRINCIPAL FINDINGS: In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls were enrolled in 3 centres. Biomarker panels a for PCa diagnosis (comparison of PCa patients versus benign controls and b for advanced disease (comparison of patients with post surgery Gleason score 7 were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (in a preliminary validation setting. Seminal profiles showed excellent pre-analytical stability. Eight biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase, prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study. CONCLUSIONS/SIGNIFICANCE: Seminal plasma represents a robust source of potential peptide makers

  1. Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

    Science.gov (United States)

    Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

    2017-06-02

    Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. The Urine Proteome Profile Is Different in Neuromyelitis Optica Compared to Multiple Sclerosis: A Clinical Proteome Study.

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    Helle H Nielsen

    Full Text Available Inflammatory demyelinating diseases of the CNS comprise a broad spectrum of diseases like neuromyelitis optica (NMO, NMO spectrum disorders (NMO-SD and multiple sclerosis (MS. Despite clear classification criteria, differentiation can be difficult. We hypothesized that the urine proteome may differentiate NMO from MS.The proteins in urine samples from anti-aquaporin 4 (AQP4 seropositive NMO/NMO-SD patients (n = 32, patients with MS (n = 46 and healthy subjects (HS, n = 31 were examined by quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS after trypsin digestion and iTRAQ labelling. Immunoglobulins (Ig in the urine were validated by nephelometry in an independent cohort (n = 9-10 pr. groups.The analysis identified a total of 1112 different proteins of which 333 were shared by all 109 subjects. Cluster analysis revealed differences in the urine proteome of NMO/NMO-SD compared to HS and MS. Principal component analysis also suggested that the NMO/NMO-SD proteome profile was useful for classification. Multivariate regression analysis revealed a 3-protein profile for the NMO/NMO-SD versus HS discrimination, a 6-protein profile for NMO/NMO-SD versus MS discrimination and an 11-protein profile for MS versus HS discrimination. All protein panels yielded highly significant ROC curves (AUC in all cases >0.85, p≤0.0002. Nephelometry confirmed the presence of increased Ig-light chains in the urine of patients with NMO/NMO-SD.The urine proteome profile of patients with NMO/NMO-SD is different from MS and HS. This may reflect differences in the pathogenesis of NMO/NMO-SD versus MS and suggests that urine may be a potential source of biomarkers differentiating NMO/NMO-SD from MS.

  3. Improving the quality of biomarker discovery research: the right samples and enough of them.

    Science.gov (United States)

    Pepe, Margaret S; Li, Christopher I; Feng, Ziding

    2015-06-01

    Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

  4. Clinical proteomics identifies urinary CD14 as a potential biomarker for diagnosis of stable coronary artery disease.

    Directory of Open Access Journals (Sweden)

    Min-Yi Lee

    Full Text Available Inflammation plays a key role in coronary artery disease (CAD and other manifestations of atherosclerosis. Recently, urinary proteins were found to be useful markers for reflecting inflammation status of different organs. To identify potential biomarker for diagnosis of CAD, we performed one-dimensional SDS-gel electrophoresis followed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS. Among the proteins differentially expressed in urine samples, monocyte antigen CD14 was found to be consistently expressed in higher amounts in the CAD patients as compared to normal controls. Using enzyme-linked immunosorbent assays to analyze the concentrations of CD14 in urine and serum, we confirmed that urinary CD14 levels were significantly higher in patients (n = 73 with multi-vessel and single vessel CAD than in normal control (n = 35 (P < 0.001. Logistic regression analysis further showed that urinary CD14 concentration level is associated with severity or number of diseased vessels and SYNTAX score after adjustment for potential confounders. Concomitantly, the proportion of CD14+ monocytes was significantly increased in CAD patients (59.7 ± 3.6% as compared with healthy controls (14.9 ± 2.1% (P < 0.001, implicating that a high level of urinary CD14 may be potentially involved in mechanism(s leading to CAD pathogenesis. By performing shotgun proteomics, we further revealed that CD14-associated inflammatory response networks may play an essential role in CAD. In conclusion, the current study has demonstrated that release of CD14 in urine coupled with more CD14+ monocytes in CAD patients is significantly correlated with severity of CAD, pointing to the potential application of urinary CD14 as a novel noninvasive biomarker for large-scale diagnostic screening of susceptible CAD patients.

  5. Methodologies and Perspectives of Proteomics Applied to Filamentous Fungi: From Sample Preparation to Secretome Analysis

    Science.gov (United States)

    Bianco, Linda; Perrotta, Gaetano

    2015-01-01

    Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation. PMID:25775160

  6. Methodologies and perspectives of proteomics applied to filamentous fungi: from sample preparation to secretome analysis.

    Science.gov (United States)

    Bianco, Linda; Perrotta, Gaetano

    2015-03-12

    Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation.

  7. Identification of cancer protein biomarkers using proteomic techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

    2016-10-18

    The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

  8. A high-throughput sample preparation method for cellular proteomics using 96-well filter plates.

    Science.gov (United States)

    Switzar, Linda; van Angeren, Jordy; Pinkse, Martijn; Kool, Jeroen; Niessen, Wilfried M A

    2013-10-01

    A high-throughput sample preparation protocol based on the use of 96-well molecular weight cutoff (MWCO) filter plates was developed for shotgun proteomics of cell lysates. All sample preparation steps, including cell lysis, buffer exchange, protein denaturation, reduction, alkylation and proteolytic digestion are performed in a 96-well plate format, making the platform extremely well suited for processing large numbers of samples and directly compatible with functional assays for cellular proteomics. In addition, the usage of a single plate for all sample preparation steps following cell lysis reduces potential samples losses and allows for automation. The MWCO filter also enables sample concentration, thereby increasing the overall sensitivity, and implementation of washing steps involving organic solvents, for example, to remove cell membranes constituents. The optimized protocol allowed for higher throughput with improved sensitivity in terms of the number of identified cellular proteins when compared to an established protocol employing gel-filtration columns. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Low molecular weight protein enrichment on mesoporous silica thin films for biomarker discovery.

    Science.gov (United States)

    Fan, Jia; Gallagher, James W; Wu, Hung-Jen; Landry, Matthew G; Sakamoto, Jason; Ferrari, Mauro; Hu, Ye

    2012-04-17

    The identification of circulating biomarkers holds great potential for non invasive approaches in early diagnosis and prognosis, as well as for the monitoring of therapeutic efficiency.(1-3) The circulating low molecular weight proteome (LMWP) composed of small proteins shed from tissues and cells or peptide fragments derived from the proteolytic degradation of larger proteins, has been associated with the pathological condition in patients and likely reflects the state of disease.(4,5) Despite these potential clinical applications, the use of Mass Spectrometry (MS) to profile the LMWP from biological fluids has proven to be very challenging due to the large dynamic range of protein and peptide concentrations in serum.(6) Without sample pre-treatment, some of the more highly abundant proteins obscure the detection of low-abundance species in serum/plasma. Current proteomic-based approaches, such as two-dimensional polyacrylamide gel-electrophoresis (2D-PAGE) and shotgun proteomics methods are labor-intensive, low throughput and offer limited suitability for clinical applications.(7-9) Therefore, a more effective strategy is needed to isolate LMWP from blood and allow the high throughput screening of clinical samples. Here, we present a fast, efficient and reliable multi-fractionation system based on mesoporous silica chips to specifically target and enrich LMWP.(10,11) Mesoporous silica (MPS) thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different polymer templates and polymer concentrations in the precursor solution, various pore size distributions, pore structures, connectivity and surface properties were determined and applied for selective recovery of low mass proteins. The selective parsing of the enriched peptides into different subclasses according to their physicochemical properties will enhance the efficiency of recovery and detection of low abundance species. In combination with mass

  10. Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography—Tandem Mass Spectrometry

    Science.gov (United States)

    Tabb, David L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Variyath, Asokan Mulayath; Ham, Amy-Joan L.; Bunk, David M.; Kilpatrick, Lisa E.; Billheimer, Dean D.; Blackman, Ronald K.; Cardasis, Helene L.; Carr, Steven A.; Clauser, Karl R.; Jaffe, Jacob D.; Kowalski, Kevin A.; Neubert, Thomas A.; Regnier, Fred E.; Schilling, Birgit; Tegeler, Tony J.; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fisher, Susan J.; Gibson, Bradford W.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Steven E.; Tempst, Paul; Paulovich, Amanda G.; Liebler, Daniel C.; Spiegelman, Cliff

    2009-01-01

    The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35–60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind

  11. Dithiothreitol-based protein equalization technology to unravel biomarkers for bladder cancer.

    Science.gov (United States)

    Araújo, J E; López-Fernández, H; Diniz, M S; Baltazar, Pedro M; Pinheiro, Luís Campos; da Silva, Fernando Calais; Carrascal, Mylène; Videira, Paula; Santos, H M; Capelo, J L

    2018-04-01

    This study aimed to assess the benefits of dithiothreitol (DTT)-based sample treatment for protein equalization to assess potential biomarkers for bladder cancer. The proteome of plasma samples of patients with bladder carcinoma, patients with lower urinary tract symptoms (LUTS) and healthy volunteers, was equalized with dithiothreitol (DTT) and compared. The equalized proteomes were interrogated using two-dimensional gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry. Six proteins, namely serum albumin, gelsolin, fibrinogen gamma chain, Ig alpha-1 chain C region, Ig alpha-2 chain C region and haptoglobin, were found dysregulated in at least 70% of bladder cancer patients when compared with a pool of healthy individuals. One protein, serum albumin, was found overexpressed in 70% of the patients when the equalized proteome of the healthy pool was compared with the equalized proteome of the LUTS patients. The pathways modified by the proteins differentially expressed were analyzed using Cytoscape. The method here presented is fast, cheap, of easy application and it matches the analytical minimalism rules as outlined by Halls. Orthogonal validation was done using western-blot. Overall, DTT-based protein equalization is a promising methodology in bladder cancer research. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Solid-Phase Extraction Strategies to Surmount Body Fluid Sample Complexity in High-Throughput Mass Spectrometry-Based Proteomics

    Science.gov (United States)

    Bladergroen, Marco R.; van der Burgt, Yuri E. M.

    2015-01-01

    For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations. PMID:25692071

  13. Evaluation of six sample preparation procedures for qualitative and quantitative proteomics analysis of milk fat globule membrane.

    Science.gov (United States)

    Yang, Yongxin; Anderson, Elizabeth; Zhang, Sheng

    2018-04-12

    Proteomic analysis of membrane proteins is challenged by the proteins solubility and detergent incompatibility with MS analysis. No single perfect protocol can be used to comprehensively characterize the proteome of membrane fraction. Here, we used cow milk fat globule membrane (MFGM) proteome analysis to assess six sample preparation procedures including one in-gel and five in-solution digestion approaches prior to LC-MS/MS analysis. The largest number of MFGM proteins were identified by suspension trapping (S-Trap) and filter-aided sample preparation (FASP) methods, followed by acetone precipitation without clean-up of tryptic peptides method. Protein identifications with highest average coverage was achieved by Chloroform/MeOH, in-gel and S-Trap methods. Most distinct proteins were identified by FASP method, followed by S-Trap. Analyses by Venn diagram, principal-component analysis, hierarchical clustering and the abundance ranking of quantitative proteins highlight differences in the MFGM fraction by the all sample preparation procedures. These results reveal the biased proteins/peptides loss occurred in each protocol. In this study, we found several novel proteins that were not observed previously by in-depth proteomics characterization of MFGM fraction in milk. Thus, a combination of multiple procedures with orthologous properties of sample preparation was demonstrated to improve the protein sequence coverage and expression level accuracy of membrane samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

    Science.gov (United States)

    Borrebaeck, Carl A K

    2017-03-01

    Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

  15. Proteomic tools for environmental microbiology--a roadmap from sample preparation to protein identification and quantification.

    Science.gov (United States)

    Wöhlbrand, Lars; Trautwein, Kathleen; Rabus, Ralf

    2013-10-01

    The steadily increasing amount of (meta-)genomic sequence information of diverse organisms and habitats has a strong impact on research in microbial physiology and ecology. In-depth functional understanding of metabolic processes and overall physiological adaptation to environmental changes, however, requires application of proteomics, as the context specific proteome constitutes the true functional output of a cell. Considering the enormous structural and functional diversity of proteins, only rational combinations of various analytical approaches allow a holistic view on the overall state of the cell. Within the past decade, proteomic methods became increasingly accessible to microbiologists mainly due to the robustness of analytical methods (e.g. 2DE), and affordability of mass spectrometers and their relative ease of use. This review provides an overview on the complex portfolio of state-of-the-art proteomics and highlights the basic principles of key methods, ranging from sample preparation of laboratory or environmental samples, via protein/peptide separation (gel-based or gel-free) and different types of mass spectrometric protein/peptide analyses, to protein identification and abundance determination. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Proteomic analysis in type 2 diabetes patients before and after a very low calorie diet reveals potential disease state and intervention specific biomarkers.

    Directory of Open Access Journals (Sweden)

    Maria A Sleddering

    Full Text Available Very low calorie diets (VLCD with and without exercise programs lead to major metabolic improvements in obese type 2 diabetes patients. The mechanisms underlying these improvements have so far not been elucidated fully. To further investigate the mechanisms of a VLCD with or without exercise and to uncover possible biomarkers associated with these interventions, blood samples were collected from 27 obese type 2 diabetes patients before and after a 16-week VLCD (Modifast ∼ 450 kcal/day. Thirteen of these patients followed an exercise program in addition to the VCLD. Plasma was obtained from 27 lean and 27 obese controls as well. Proteomic analysis was performed using mass spectrometry (MS and targeted multiple reaction monitoring (MRM and a large scale isobaric tags for relative and absolute quantitation (iTRAQ approach. After the 16-week VLCD, there was a significant decrease in body weight and HbA1c in all patients, without differences between the two intervention groups. Targeted MRM analysis revealed differences in several proteins, which could be divided in diabetes-associated (fibrinogen, transthyretin, obesity-associated (complement C3, and diet-associated markers (apolipoproteins, especially apolipoprotein A-IV. To further investigate the effects of exercise, large scale iTRAQ analysis was performed. However, no proteins were found showing an exercise effect. Thus, in this study, specific proteins were found to be differentially expressed in type 2 diabetes patients versus controls and before and after a VLCD. These proteins are potential disease state and intervention specific biomarkers.Controlled-Trials.com ISRCTN76920690.

  17. Detection of acute renal allograft rejection by analysis of Renal TissueProteomics in rat models of renal transplantation

    International Nuclear Information System (INIS)

    Dai, Y.; Lv, T.; Wang, K.; Li, D.; Huang, Y.; Liu, J.

    2008-01-01

    At present, the diagnosis of renal allograft rejection requires a renalbiopsy. Clinical management of renal transplant patients would be improved ifrapid, noninvasive and reliable biomarkers of rejection were available. Thisstudy is designed to determine whether such protein biomarkers can be foundin renal graft tissue proteomic approach. Orthotopic kidney transplantationswere performed using Fisher (F344) or Lewis rats as donors and Lewis rats asrecipients. Hence, there were two groups of renal transplant models: one isallograft (from F344 to Lewis rats); another is syngrafts (from Lewis toLewis rats) serving as control. Renal tissues were collected 3, 7 and 14 daysafter transplantation. As many 18 samples were analyzed by 2-DElectrophoresis and mass spectrometry (MALDI-TOF-TOF-MS). Elevendifferentially expressed proteins were identified between groups. Inconclusion, proteomic technology can detect renal tissue proteins associatedwith acute renal allograft rejection. Identification of these proteins asdiagnostic markers for rejection in patient's urine or sera may be useful andnon-invasive, and these proteins might serve as novel therapeutic targetsthat also help to improve the understanding of mechanisms of renal rejection.(author)

  18. Proteomic Changes in Cerebrospinal Fluid of Presymptomatic and Affected Persons Carrying Familial Alzheimer Disease Mutations

    Science.gov (United States)

    Ringman, John M.; Schulman, Howard; Becker, Chris; Jones, Ted; Bai, Yuchen; Immermann, Fred; Cole, Gregory; Sokolow, Sophie; Gylys, Karen; Geschwind, Daniel H.; Cummings, Jeffrey L.; Wan, Hong I.

    2013-01-01

    Objective To identify cerebrospinal fluid (CSF) protein changes in persons who will develop familial Alzheimer disease (FAD) due to PSEN1 and APP mutations, using unbiased proteomics. Design We compared proteomic profiles of CSF from individuals with FAD who were mutation carriers (MCs) and related noncarriers (NCs). Abundant proteins were depleted and samples were analyzed using liquid chromatography– electrospray ionization–mass spectrometry on a high-resolution time-of-flight instrument. Tryptic peptides were identified by tandem mass spectrometry. Proteins differing in concentration between the MCs and NCs were identified. Setting A tertiary dementia referral center and a proteomic biomarker discovery laboratory. Participants Fourteen FAD MCs (mean age, 34.2 years; 10 are asymptomatic, 12 have presenilin-1 [PSEN1] gene mutations, and 2 have amyloid precursor protein [APP] gene mutations) and 5 related NCs (mean age, 37.6 years). Results Fifty-six proteins were identified, represented by multiple tryptic peptides showing significant differences between MCs and NCs (46 upregulated and 10 downregulated); 40 of these proteins differed when the analysis was restricted to asymptomatic individuals. Fourteen proteins have been reported in prior proteomic studies in late-onset AD, including amyloid precursor protein, transferrin, α1β-glycoprotein, complement components, afamin precursor, spondin 1, plasminogen, hemopexin, and neuronal pentraxin receptor. Many other proteins were unique to our study, including calsyntenin 3, AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) 4 glutamate receptor, CD99 antigen, di-N-acetyl-chitobiase, and secreted phosphoprotein 1. Conclusions We found much overlap in CSF protein changes between individuals with presymptomatic and symptomatic FAD and those with late-onset AD. Our results are consistent with inflammation and synaptic loss early in FAD and suggest new presymptomatic biomarkers of potential usefulness in drug

  19. Differential proteomics of human seminal plasma: A potential target for searching male infertility marker proteins.

    Science.gov (United States)

    Tomar, Anil Kumar; Sooch, Balwinder Singh; Singh, Sarman; Yadav, Savita

    2012-04-01

    The clinical fertility tests, available in the market, fail to define the exact cause of male infertility in almost half of the cases and point toward a crucial need of developing better ways of infertility investigations. The protein biomarkers may help us toward better understanding of unknown cases of male infertility that, in turn, can guide us to find better therapeutic solutions. Many clinical attempts have been made to identify biomarkers of male infertility in sperm proteome but only few studies have targeted seminal plasma. Human seminal plasma is a rich source of proteins that are essentially required for development of sperm and successful fertilization. This viewpoint article highlights the importance of human seminal plasma proteome in reproductive physiology and suggests that differential proteomics integrated with functional analysis may help us in searching potential biomarkers of male infertility. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. The proteome of neurofilament-containing protein aggregates in blood

    Directory of Open Access Journals (Sweden)

    Rocco Adiutori

    2018-07-01

    Full Text Available Protein aggregation in biofluids is a poorly understood phenomenon. Under normal physiological conditions, fluid-borne aggregates may contain plasma or cell proteins prone to aggregation. Recent observations suggest that neurofilaments (Nf, the building blocks of neurons and a biomarker of neurodegeneration, are included in high molecular weight complexes in circulation. The composition of these Nf-containing hetero-aggregates (NCH may change in systemic or organ-specific pathologies, providing the basis to develop novel disease biomarkers. We have tested ultracentrifugation (UC and a commercially available protein aggregate binder, Seprion PAD-Beads (SEP, for the enrichment of NCH from plasma of healthy individuals, and then characterised the Nf content of the aggregate fractions using gel electrophoresis and their proteome by mass spectrometry (MS. Western blot analysis of fractions obtained by UC showed that among Nf isoforms, neurofilament heavy chain (NfH was found within SDS-stable high molecular weight aggregates. Shotgun proteomics of aggregates obtained with both extraction techniques identified mostly cell structural and to a lesser extent extra-cellular matrix proteins, while functional analysis revealed pathways involved in inflammatory response, phagosome and prion-like protein behaviour. UC aggregates were specifically enriched with proteins involved in endocrine, metabolic and cell-signalling regulation. We describe the proteome of neurofilament-containing aggregates isolated from healthy individuals biofluids using different extraction methods.

  1. A Review of the “Omics” Approach to Biomarkers of Oxidative Stress in Oryza sativa

    Directory of Open Access Journals (Sweden)

    Su Shiung Lam

    2013-04-01

    Full Text Available Physiological and ecological constraints that cause the slow growth and depleted production of crops have raised a major concern in the agriculture industry as they represent a possible threat of short food supply in the future. The key feature that regulates the stress signaling pathway is always related to the reactive oxygen species (ROS. The accumulation of ROS in plant cells would leave traces of biomarkers at the genome, proteome, and metabolome levels, which could be identified with the recent technological breakthrough coupled with improved performance of bioinformatics. This review highlights the recent breakthrough in molecular strategies (comprising transcriptomics, proteomics, and metabolomics in identifying oxidative stress biomarkers and the arising opportunities and obstacles observed in research on biomarkers in rice. The major issue in incorporating bioinformatics to validate the biomarkers from different omic platforms for the use of rice-breeding programs is also discussed. The development of powerful techniques for identification of oxidative stress-related biomarkers and the integration of data from different disciplines shed light on the oxidative response pathways in plants.

  2. Biology and Biomarkers for Wound Healing

    Science.gov (United States)

    Lindley, Linsey E.; Stojadinovic, Olivera; Pastar, Irena; Tomic-Canic, Marjana

    2016-01-01

    Background As the population grows older, the incidence and prevalence of conditions which lead to a predisposition for poor wound healing also increases. Ultimately, this increase in non-healing wounds has led to significant morbidity and mortality with subsequent huge economic ramifications. Therefore, understanding specific molecular mechanisms underlying aberrant wound healing is of great importance. It has, and will continue to be the leading pathway to the discovery of therapeutic targets as well as diagnostic molecular biomarkers. Biomarkers may help identify and stratify subsets of non-healing patients for whom biomarker-guided approaches may aid in healing. Methods A series of literature searches were performed using Medline, PubMed, Cochrane Library, and Internet searches. Results Currently, biomarkers are being identified using biomaterials sourced locally, from human wounds and/or systemically using systematic high-throughput “omics” modalities (genomic, proteomic, lipidomic, metabolomic analysis). In this review we highlight the current status of clinically applicable biomarkers and propose multiple steps in validation and implementation spectrum including those measured in tissue specimens e.g. β-catenin and c-myc, wound fluid e.g. MMP’s and interleukins, swabs e.g. wound microbiota and serum e.g. procalcitonin and MMP’s. Conclusions Identification of numerous potential biomarkers utilizing different avenues of sample collection and molecular approaches is currently underway. A focus on simplicity, and consistent implementation of these biomarkers as well as an emphasis on efficacious follow-up therapeutics is necessary for transition of this technology to clinically feasible point-of-care applications. PMID:27556760

  3. Differential proteomic analysis of noncardia gastric cancer from individuals of northern Brazil.

    Science.gov (United States)

    Leal, Mariana Ferreira; Chung, Janete; Calcagno, Danielle Queiroz; Assumpção, Paulo Pimentel; Demachki, Samia; da Silva, Ismael Dale Cotrim Guerreiro; Chammas, Roger; Burbano, Rommel Rodríguez; de Arruda Cardoso Smith, Marília

    2012-01-01

    Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in larger clinical study

  4. Differential proteomic analysis of noncardia gastric cancer from individuals of northern Brazil.

    Directory of Open Access Journals (Sweden)

    Mariana Ferreira Leal

    Full Text Available Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in

  5. A proteomic strategy to identify novel serum biomarkers for liver cirrhosis and hepatocellular cancer in individuals with fatty liver disease

    Directory of Open Access Journals (Sweden)

    Stewart Stephen

    2009-08-01

    Full Text Available Abstract Background Non-alcoholic fatty liver disease (NAFLD has a prevalence of over 20% in Western societies. Affected individuals are at risk of developing both cirrhosis and hepatocellular cancer (HCC. Presently there is no cost effective population based means of identifying cirrhotic individuals and even if there were, our ability to perform HCC surveillance in the at risk group is inadequate. We have performed a pilot proteomic study to assess this as a strategy for serum biomarker detection. Methods 2D Gel electrophoresis was performed on immune depleted sera from 3 groups of patients, namely those with (1 pre-cirrhotic NAFLD (2 cirrhotic NAFLD and (3 cirrhotic NAFLD with co-existing HCC. Five spots differentiating at least one of these three groups were characterised by mass spectroscopy. An ELISA assay was optimised and a cross sectional study assessing one of these serum spots was performed on serum from 45 patients with steatohepatitis related cirrhosis and HCC and compared to 77 patients with histologically staged steatohepatitis. Results Four of the spots identified were apolipoprotein isoforms, the pattern of which was able to differentiate the three groups. The 5th spot, seen in the serum of cirrhotic individuals and more markedly in those with HCC, was identified as CD5 antigen like (CD5L. By ELISA assay, although CD5L was markedly elevated in a number of cirrhotic individuals with HCC, its overall ability to distinguish non-cancer from cancer individuals as determined by AUC ROC analysis was poor. However, serum CD5L was dramatically increased, independently of age, sex, and the presence of necroinflammation, in the serum of individuals with NAFLD cirrhosis relative to those with pre-cirrhotic disease. Conclusion This novel proteomic strategy has identified a number of candidate biomarkers which may have benefit in the surveillance and diagnosis of individuals with chronic liver disease and/or HCC.

  6. Meeting Report--NASA Radiation Biomarker Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Straume, Tore; Amundson, Sally A,; Blakely, William F.; Burns, Frederic J.; Chen, Allen; Dainiak, Nicholas; Franklin, Stephen; Leary, Julie A.; Loftus, David J.; Morgan, William F.; Pellmar, Terry C.; Stolc, Viktor; Turteltaub, Kenneth W.; Vaughan, Andrew T.; Vijayakumar, Srinivasan; Wyrobek, Andrew J.

    2008-05-01

    A summary is provided of presentations and discussions from the NASA Radiation Biomarker Workshop held September 27-28, 2007, at NASA Ames Research Center in Mountain View, California. Invited speakers were distinguished scientists representing key sectors of the radiation research community. Speakers addressed recent developments in the biomarker and biotechnology fields that may provide new opportunities for health-related assessment of radiation-exposed individuals, including for long-duration space travel. Topics discussed include the space radiation environment, biomarkers of radiation sensitivity and individual susceptibility, molecular signatures of low-dose responses, multivariate analysis of gene expression, biomarkers in biodefense, biomarkers in radiation oncology, biomarkers and triage following large-scale radiological incidents, integrated and multiple biomarker approaches, advances in whole-genome tiling arrays, advances in mass-spectrometry proteomics, radiation biodosimetry for estimation of cancer risk in a rat skin model, and confounding factors. Summary conclusions are provided at the end of the report.

  7. Partitioning the proteome: phase separation for targeted analysis of membrane proteins in human post-mortem brain.

    Directory of Open Access Journals (Sweden)

    Jane A English

    Full Text Available Neuroproteomics is a powerful platform for targeted and hypothesis driven research, providing comprehensive insights into cellular and sub-cellular disease states, Gene × Environmental effects, and cellular response to medication effects in human, animal, and cell culture models. Analysis of sub-proteomes is becoming increasingly important in clinical proteomics, enriching for otherwise undetectable proteins that are possible markers for disease. Membrane proteins are one such sub-proteome class that merit in-depth targeted analysis, particularly in psychiatric disorders. As membrane proteins are notoriously difficult to analyse using traditional proteomics methods, we evaluate a paradigm to enrich for and study membrane proteins from human post-mortem brain tissue. This is the first study to extensively characterise the integral trans-membrane spanning proteins present in human brain. Using Triton X-114 phase separation and LC-MS/MS analysis, we enriched for and identified 494 membrane proteins, with 194 trans-membrane helices present, ranging from 1 to 21 helices per protein. Isolated proteins included glutamate receptors, G proteins, voltage gated and calcium channels, synaptic proteins, and myelin proteins, all of which warrant quantitative proteomic investigation in psychiatric and neurological disorders. Overall, our sub-proteome analysis reduced sample complexity and enriched for integral membrane proteins by 2.3 fold, thus allowing for more manageable, reproducible, and targeted proteomics in case vs. control biomarker studies. This study provides a valuable reference for future neuroproteomic investigations of membrane proteins, and validates the use Triton X-114 detergent phase extraction on human post mortem brain.

  8. A Hybrid Feature Subset Selection Algorithm for Analysis of High Correlation Proteomic Data

    Science.gov (United States)

    Kordy, Hussain Montazery; Baygi, Mohammad Hossein Miran; Moradi, Mohammad Hassan

    2012-01-01

    Pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. The surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) has been used to generate proteomic profiles from biological fluids. Mass spectrometry yields redundant noisy data that the most data points are irrelevant features for differentiating between cancer and normal cases. In this paper, we have proposed a hybrid feature subset selection algorithm based on maximum-discrimination and minimum-correlation coupled with peak scoring criteria. Our algorithm has been applied to two independent SELDI-TOF MS datasets of ovarian cancer obtained from the NCI-FDA clinical proteomics databank. The proposed algorithm has used to extract a set of proteins as potential biomarkers in each dataset. We applied the linear discriminate analysis to identify the important biomarkers. The selected biomarkers have been able to successfully diagnose the ovarian cancer patients from the noncancer control group with an accuracy of 100%, a sensitivity of 100%, and a specificity of 100% in the two datasets. The hybrid algorithm has the advantage that increases reproducibility of selected biomarkers and able to find a small set of proteins with high discrimination power. PMID:23717808

  9. Dehalococcoides as a Potential Biomarker Evidence for Uncharacterized Organohalides in Environmental Samples

    Directory of Open Access Journals (Sweden)

    Qihong Lu

    2017-09-01

    Full Text Available The massive production and improper disposal of organohalides resulted in worldwide contamination in soil and water. However, their environmental survey based on chromatographic methods was hindered by challenges in testing the extremely wide variety of organohalides. Dehalococcoides as obligate organohalide-respiring bacteria exclusively use organohalides as electron acceptors to support their growth, of which the presence could be coupled with organohalides and, therefore, could be employed as a biomarker of the organohalide pollution. In this study, Dehalococcoides was screened in various samples of bioreactors and subsurface environments, showing the wide distribution of Dehalococcoides in sludge and sediment. Further laboratory cultivation confirmed the dechlorination activities of those Dehalococcoides. Among those samples, Dehalococcoides accounting for 1.8% of the total microbial community was found in an anaerobic granular sludge sample collected from a full-scale bioreactor treating petroleum wastewater. Experimental evidence suggested that the influent wastewater in the bioreactor contained bromomethane which support the growth of Dehalococcoides. This study demonstrated that Dehalococcoides could be employed as a promising biomarker to test the present of organohalides in wastestreams or other environmental samples.

  10. Amyloid Biomarkers in Conformational Diseases at Face Value: A Systematic Review

    OpenAIRE

    Maria Fernanda Avila-Vazquez; Nelly F. Altamirano-Bustamante; Myriam M. Altamirano-Bustamante

    2017-01-01

    Conformational diseases represent a new aspect of proteomic medicine where diagnostic and therapeutic paradigms are evolving. In this context, the early biomarkers for target cell failure (neurons, β-cells, etc.) represent a challenge to translational medicine and play a multidimensional role as biomarkers and potential therapeutic targets. This systematic review, which follows the PICO and Prisma methods, analyses this new-fangled multidimensionality, its strengths and limitations, and prese...

  11. Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase.

    Science.gov (United States)

    Sanchez-Niño, Maria Dolores; Sanz, Ana B; Ramos, Adrian M; Fernandez-Fernandez, Beatriz; Ortiz, Alberto

    2017-04-01

    Exponential technologies double in power or processing speed every year, whereas their cost halves. Deception and disruption are two key stages in the development of exponential technologies. Deception occurs when, after initial introduction, technologies are dismissed as irrelevant, while they continue to progress, perhaps not as fast or with so many immediate practical applications as initially thought. Twenty years after the first publications, clinical proteomics is still not available in most hospitals and some clinicians have felt deception at unfulfilled promises. However, there are indications that clinical proteomics may be entering the disruptive phase, where, once refined, technologies disrupt established industries or procedures. In this regard, recent manuscripts in CKJ illustrate how proteomics is entering the clinical realm, with applications ranging from the identification of amyloid proteins in the pathology lab, to a new generation of urinary biomarkers for chronic kidney disease (CKD) assessment and outcome prediction. Indeed, one such panel of urinary peptidomics biomarkers, CKD273, recently received a Food and Drug Administration letter of support, the first ever in the CKD field. In addition, a must-read resource providing information on kidney disease-related proteomics and systems biology databases and how to access and use them in clinical decision-making was also recently published in CKJ .

  12. Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

    Science.gov (United States)

    Page, Sandra; Birerdinc, Aybike; Estep, Michael; Stepanova, Maria; Afendy, Arian; Petricoin, Emanuel; Younossi, Zobair; Chandhoke, Vikas; Baranova, Ancha

    2013-01-01

    The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

  13. Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

    Directory of Open Access Journals (Sweden)

    Sandra Page

    Full Text Available The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1 NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2 biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

  14. Large-scale proteomic identification of S100 proteins in breast cancer tissues

    International Nuclear Information System (INIS)

    Cancemi, Patrizia; Di Cara, Gianluca; Albanese, Nadia Ninfa; Costantini, Francesca; Marabeti, Maria Rita; Musso, Rosa; Lupo, Carmelo; Roz, Elena; Pucci-Minafra, Ida

    2010-01-01

    Attempts to reduce morbidity and mortality in breast cancer is based on efforts to identify novel biomarkers to support prognosis and therapeutic choices. The present study has focussed on S100 proteins as a potentially promising group of markers in cancer development and progression. One reason of interest in this family of proteins is because the majority of the S100 genes are clustered on a region of human chromosome 1q21 that is prone to genomic rearrangements. Moreover, there is increasing evidence that S100 proteins are often up-regulated in many cancers, including breast, and this is frequently associated with tumour progression. Samples of breast cancer tissues were obtained during surgical intervention, according to the bioethical recommendations, and cryo-preserved until used. Tissue extracts were submitted to proteomic preparations for 2D-IPG. Protein identification was performed by N-terminal sequencing and/or peptide mass finger printing. The majority of the detected S100 proteins were absent, or present at very low levels, in the non-tumoral tissues adjacent to the primary tumor. This finding strengthens the role of S100 proteins as putative biomarkers. The proteomic screening of 100 cryo-preserved breast cancer tissues showed that some proteins were ubiquitously expressed in almost all patients while others appeared more sporadic. Most, if not all, of the detected S100 members appeared reciprocally correlated. Finally, from the perspective of biomarkers establishment, a promising finding was the observation that patients which developed distant metastases after a three year follow-up showed a general tendency of higher S100 protein expression, compared to the disease-free group. This article reports for the first time the comparative proteomic screening of several S100 protein members among a large group of breast cancer patients. The results obtained strongly support the hypothesis that a significant deregulation of multiple S100 protein members is

  15. Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013.

    Science.gov (United States)

    Viglio, Simona; Stolk, Jan; Iadarola, Paolo; Giuliano, Serena; Luisetti, Maurizio; Salvini, Roberta; Fumagalli, Marco; Bardoni, Anna

    2014-01-22

    To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

  16. Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

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    Parida Shreemanta K

    2010-01-01

    Full Text Available Abstract Background For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available. Conclusions The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in

  17. Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals

    DEFF Research Database (Denmark)

    Delles, Christian; Schiffer, Eric; von Zur Muhlen, Constantin

    2010-01-01

    We studied the urinary proteome in a total of 623 individuals with and without coronary artery disease (CAD) in order to characterize multiple biomarkers that enable prediction of the presence of CAD....

  18. Plasma membrane proteomics and its application in clinical cancer biomarker discovery

    DEFF Research Database (Denmark)

    Leth-Larsen, Rikke; Lund, Rikke; Ditzel, Henrik J

    2010-01-01

    Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions...... targeted by protein drugs, such as human antibodies, that have enhanced survival of several groups of cancer patients. The combination of novel analytical approaches and subcellular fractionation procedures has made it possible to study the plasma membrane proteome in more detail, which will elucidate...... cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal...

  19. Urinary Biomarkers of Brain Diseases

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    Manxia An

    2015-12-01

    Full Text Available Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome.

  20. iTRAQ-Based Proteomics Analysis of Serum Proteins in Wistar Rats Treated with Sodium Fluoride: Insight into the Potential Mechanism and Candidate Biomarkers of Fluorosis

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    Yan Wei

    2016-09-01

    Full Text Available Fluorosis induced by exposure to high level fluoride is quite widespread in the world. The manifestations of fluorosis include dental mottling, bone damage, and impaired malfunction of soft tissues. However, the molecular mechanism of fluorosis has not been clarified until now. To explore the underlying mechanisms of fluorosis and screen out serum biomarkers, we carried out a quantitative proteomics study to identify differentially expressed serum proteins in Wistar rats treated with sodium fluoride (NaF by using a proteomics approach of isobaric tagging for relative and absolute quantitation (iTRAQ. We fed Wistar rats drinking water that had 50, 150, and 250 mg/L of dissolved NaF for 24 weeks. For the experimental duration, each rat was given an examination of the lower incisors to check for the condition of dental fluorosis (DF. By the end of the treatment, fluoride ion concentration in serum and lower incisors were detected. The results showed that NaF treatment can induce rat fluorosis. By iTRAQ analysis, a total of 37 differentially expressed serum proteins were identified between NaF-treated and control rats. These proteins were further analyzed by bioinformatics, out of which two proteins were validated by enzyme-linked immunoadsorbent assays (ELISA. The major proteins were involved in complement and coagulation cascade, inflammatory response, complement activation, defense response, and wound response, suggesting that inflammation and immune reactions may play a key role in fluorosis pathogenesis. These proteins may contribute to the understanding of the mechanism of fluoride toxicity, and may serve as potential biomarkers for fluorosis.

  1. Proteomic and metabolomic responses in hepatopancreas of Mytilus galloprovincialis challenged by Micrococcus luteus and Vibrio anguillarum.

    Science.gov (United States)

    Wu, Huifeng; Ji, Chenglong; Wei, Lei; Zhao, Jianmin; Lu, Hongjian

    2013-12-06

    The outbreak of pathogens can induce diseases and lead to massive mortalities of aquaculture animals including fish, mollusk and shrimp. In this work, the responses induced by Micrococcus luteus and Vibrio anguillarum were investigated in hepatopancreas of mussel Mytilus galloprovincialis using proteomics and metabolomics. Metabolic biomarkers demonstrated that M. luteus and V. anguillarum injections could induce osmotic stress and disturbance in energy metabolism. And the uniquely and more markedly altered metabolic biomarkers (glutamine, succinate, aspartate, glucose, ATP, homarine and tyrosine) indicated that V. anguillarum could cause more severe disturbances in osmotic regulation and energy metabolism. The differentially altered proteins meant that M. luteus and V. anguillarum induced different effects in mussels. However, the common proteomic biomarkers, arginine kinase and small heat shock protein, demonstrated that these two bacteria induced similar effects including oxidative stress and disturbance in energy metabolism in M. galloprovincialis. In addition, some metabolic biomarkers, ATP and glutamine, were confirmed by related proteins including arginine kinase, ATP synthase, nucleoside diphosphate kinase and glutamine synthetase in bacteria-challenged mussels. This study demonstrated that proteomics and metabolomics could provide an insightful view into the effects of environmental pathogens to the marine mussel M. galloprovincialis. The outbreak of pathogens can lead to diseases and massive mortalities of aquaculture animals including fish, mollusk and shrimp. The mussel M. galloprovincialis distributes widely along the Bohai coast and is popularly consumed as delicious seafood by local residents. This bivalve has become one of the important species in marine aquaculture industry in China. Therefore a study on pathogen-induced effects is necessary. In the present study, an integrated metabolomic and proteomic approach was used to elucidate the

  2. Application of serum SELDI proteomic patterns in diagnosis of lung cancer

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    Zhou Bin

    2005-07-01

    Full Text Available Abstract Background Currently, no satisfactory biomarkers are available to screen for lung cancer. Surface-Enhanced Laser Desorption/ionization Time-of- Flight Mass Spectrometry ProteinChip system (SELDI-TOF-MS is one of the currently used techniques to identify biomarkers for cancers. The aim of this study is to explore the application of serum SELDI proteomic patterns to distinguish lung cancer patients from healthy individuals. Methods A total of 208 serum samples, including 158 lung cancer patients and 50 healthy individuals, were randomly divided into a training set (including 11 sera from patients with stages I/II lung cancer, 63 from patients with stages III/IV lung cancer and 20 from healthy controls and a blinded test set (including 43 sera from patients with stages I/II lung cancer, 41 from patients with stages III/IV lung cancer and 30 from healthy controls. All samples were analyzed by SELDI technology. The spectra were generated on weak cation exchange (WCX2 chips, and protein peaks clustering and classification analyses were made using Ciphergen Biomarker Wizard and Biomarker Pattern software, respectively. We additionally determined Cyfra21-1 and NSE in the 208 serum samples included in this study using an electrochemiluminescent immunoassay. Results Five protein peaks at 11493, 6429, 8245, 5335 and 2538 Da were automatically chosen as a biomarker pattern in the training set. When the SELDI marker pattern was tested with the blinded test set, it yielded a sensitivity of 86.9%, a specificity of 80.0% and a positive predictive value of 92.4%. The sensitivities provided by Cyfra21-1 and NSE used individually or in combination were significantly lower than that of the SELDI marker pattern (P P Conclusion These results suggest that serum SELDI protein profiling can distinguish lung cancer patients, especially NSCLC patients, from normal subjects with relatively high sensitivity and specificity, and the SELDI-TOF-MS is a potential tool

  3. Serum protein profiling and proteomics in autistic spectrum disorder using magnetic bead-assisted mass spectrometry.

    Science.gov (United States)

    Taurines, Regina; Dudley, Edward; Conner, Alexander C; Grassl, Julia; Jans, Thomas; Guderian, Frank; Mehler-Wex, Claudia; Warnke, Andreas; Gerlach, Manfred; Thome, Johannes

    2010-04-01

    The pathophysiology of autistic spectrum disorder (ASD) is not fully understood and there are no diagnostic or predictive biomarkers. Proteomic profiling has been used in the past for biomarker research in several non-psychiatric and psychiatric disorders and could provide new insights, potentially presenting a useful tool for generating such biomarkers in autism. Serum protein pre-fractionation with C8-magnetic beads and protein profiling by matrix-assisted laser desorption/ionisation-time of flight-mass spectrometry (MALDI-ToF-MS) were used to identify possible differences in protein profiles in patients and controls. Serum was obtained from 16 patients (aged 8-18) and age-matched controls. Three peaks in the MALDI-ToF-MS significantly differentiated the ASD sample from the control group. Sub-grouping the ASD patients into children with and without comorbid Attention Deficit and Hyperactivity Disorder, ADHD (ASD/ADHD+ patients, n = 9; ASD/ADHD- patients, n = 7), one peak distinguished the ASD/ADHD+ patients from controls and ASD/ADHD- patients. Our results suggest that altered protein levels in peripheral blood of patients with ASD might represent useful biomarkers for this devastating psychiatric disorder.

  4. The use of time-resolved fluorescence in gel-based proteomics for improved biomarker discovery

    Science.gov (United States)

    Sandberg, AnnSofi; Buschmann, Volker; Kapusta, Peter; Erdmann, Rainer; Wheelock, Åsa M.

    2010-02-01

    This paper describes a new platform for quantitative intact proteomics, entitled Cumulative Time-resolved Emission 2-Dimensional Gel Electrophoresis (CuTEDGE). The CuTEDGE technology utilizes differences in fluorescent lifetimes to subtract the confounding background fluorescence during in-gel detection and quantification of proteins, resulting in a drastic improvement in both sensitivity and dynamic range compared to existing technology. The platform is primarily designed for image acquisition in 2-dimensional gel electrophoresis (2-DE), but is also applicable to 1-dimensional gel electrophoresis (1-DE), and proteins electroblotted to membranes. In a set of proof-of-principle measurements, we have evaluated the performance of the novel technology using the MicroTime 100 instrument (PicoQuant GmbH) in conjunction with the CyDye minimal labeling fluorochromes (GE Healthcare, Uppsala, Sweden) to perform differential gel electrophoresis (DIGE) analyses. The results indicate that the CuTEDGE technology provides an improvement in the dynamic range and sensitivity of detection of 3 orders of magnitude as compared to current state-of-the-art image acquisition instrumentation available for 2-DE (Typhoon 9410, GE Healthcare). Given the potential dynamic range of 7-8 orders of magnitude and sensitivities in the attomol range, the described invention represents a technological leap in detection of low abundance cellular proteins, which is desperately needed in the field of biomarker discovery.

  5. STATE OF THE ART IN PROTEOMICS FOR CANCER DETECTION

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    Syafrizayanti Syafrizayanti

    2014-12-01

    Full Text Available The earliest stages of cancer detection determine the successful of cancer treatment andtherapy. The existing cancer test or detection methods have been routinely used, but they arelack of sensitivity and specificity that are needed to avoid false positive or negative results. Thegenomic basedtechniques have been applied, although molecular understandings of cancerfar from complete, but few genomic platforms are becoming routine. Application of proteomicsbasedtechniques provide intriguing outcome, which is cancer detection at their earliest stages.Proteomics have exposed a new perspective into the phases of tumorigenesis and depictedmore detailed molecular network scheme, which made important contributions in the discoveryof biomarker of early diagnosis, prognosis and prediction outcome of cancer therapies.The noticeable proteomic platforms to achieve these goals are protein microarray, tissuemicroarray, mass spectrometry-based proteomic, and two-dimensionalgel electrophoresis (2-DE. The application of these techniques will be overviewed, providing a general review ofcurrent proteomic methods in cancer detection and subsequently improvement in prognosisand prediction of cancer therapies.Keywords: proteomics, protein microarrays, mass spectrometry, cancer biomarkerAbstrakDeteksi dini kanker sangat menentukan keberhasilan penanganan dan terapi kanker. Hinggasaat ini, telah banyak jenis metoda deteksi dan uji kanker yang sudah rutin digunakan, akantetapi metoda-metoda tersebut memiliki tingkat sensitifitas dan spesifikasi yang rendah,sehingga sering menyebabkan terjadi kesalahan hasil uji baik secara positif ataupun negatif.Bidang genomik telah banyak digunakan untuk lebih memahami kanker pada level molekuler,meskipun hasil yang diperoleh belum mendalam, akan tetapi beberapa metoda berbasiskangenomik telah mulai rutin digunakan. Bidang pioteomik mulai banyak diaplikasikan untukkeperluan deteksi kankersedini mungkin. Proteomik memberikan perspektif

  6. Global phosphotyrosine proteomics identifies PKCδ as a marker of responsiveness to Src inhibition in colorectal cancer.

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    Eliot T McKinley

    Full Text Available Sensitive and specific biomarkers of protein kinase inhibition can be leveraged to accelerate drug development studies in oncology by associating early molecular responses with target inhibition. In this study, we utilized unbiased shotgun phosphotyrosine (pY proteomics to discover novel biomarkers of response to dasatinib, a small molecule Src-selective inhibitor, in preclinical models of colorectal cancer (CRC. We performed unbiased mass spectrometry shotgun pY proteomics to reveal the pY proteome of cultured HCT-116 colonic carcinoma cells, and then extended this analysis to HCT-116 xenograft tumors to identify pY biomarkers of dasatinib-responsiveness in vivo. Major dasatinib-responsive pY sites in xenograft tumors included sites on delta-type protein kinase C (PKCδ, CUB-domain-containing protein 1 (CDCP1, Type-II SH2-domain-containing inositol 5-phosphatase (SHIP2, and receptor protein-tyrosine phosphatase alpha (RPTPα. The pY313 site PKCδ was further supported as a relevant biomarker of dasatinib-mediated Src inhibition in HCT-116 xenografts by immunohistochemistry and immunoblotting with a phosphospecific antibody. Reduction of PKCδ pY313 was further correlated with dasatinib-mediated inhibition of Src and diminished growth as spheroids of a panel of human CRC cell lines. These studies reveal PKCδ pY313 as a promising readout of Src inhibition in CRC and potentially other solid tumors and may reflect responsiveness to dasatinib in a subset of colorectal cancers.

  7. What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema.

    Science.gov (United States)

    Ptolemy, Adam S; Rifai, Nader

    2010-01-01

    A continual trend of annual growth can be seen within research devoted to the discovery and validation of disease biomarkers within both the natural and clinical sciences. This expansion of intellectual endeavours was quantified through database searches of (a) research grant awards provided by the various branches of the National Institutes of Health (NIH) and (b) academic publications. A search of awards presented between 1986 and 2009 revealed a total of 28,856 grants awarded by the NIH containing the term "biomarker". The total funds for these awards in 2008 and 2009 alone were over $2.5 billion. During the same respective time frames, searches of "biomarker" and either "discovery", "genomics", "proteomics" or "metabolomics" yielded a total of 4,928 NIH grants whose combined funding exceeded $1.2 billion. The derived trend in NIH awards paralleled the annual expansion in "biomarker" literature. A PubMed search for the term, between 1990 and 2009, revealed a total of 441,510 published articles, with 38,457 published in 2008. These enormous investments and academic outputs however have not translated into the expected integration of new biomarkers for patient care. For example no proteomics derived biomarkers are currently being utilized in routine clinical management. This translational chasm necessitates a review of the previously proposed biomarker definitions and evaluation schema. A subsequent discussion of both the analytical and pre-analytical considerations for such research is also presented within. This required knowledge should aid scientists in their pursuit and validation of new biological markers of disease.

  8. Detection of acute renal allograft rejection by analysis of renal tissue proteomics in rat models of renal transplantation

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    Dai Yong

    2008-01-01

    Full Text Available At present, the diagnosis of renal allograft rejection requires a renal biopsy. Clinical management of renal transplant patients would be improved if rapid, noninvasive and reliable biomarkers of rejection were available. This study is designed to determine whether such protein biomarkers can be found in renal-graft tissue proteomic approach. Orthotopic kidney transplantations were performed using Fisher (F344 or Lewis rats as donors and Lewis rats as recipients. Hence, there were two groups of renal transplant models: one is allograft (from F344 to Lewis rats; another is syngrafts (from Lewis to Lewis rats serving as control. Renal tissues were collected 3, 7 and 14 days after transplantation. As many as 18 samples were analyzed by 2-D Electrophoresis and mass spectrometry (MALDI-TOF-TOF-MS. Eleven differentially expressed proteins were identified between groups. In conclusion, proteomic technology can detect renal tissue proteins associated with acute renal allograft rejection. Identification of these proteins as diagnostic markers for rejection in patients′ urine or sera may be useful and non-invasive, and these proteins might serve as novel therapeutic targets that also help to improve the understanding of mechanism of renal rejection.

  9. Proteomic interactions in the mouse vitreous-retina complex.

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    Jessica M Skeie

    Full Text Available Human vitreoretinal diseases are due to presumed abnormal mechanical interactions between the vitreous and retina, and translational models are limited. This study determined whether nonstructural proteins and potential retinal biomarkers were expressed by the normal mouse vitreous and retina.Vitreous and retina samples from mice were collected by evisceration and analyzed by liquid chromatography-tandem mass spectrometry. Identified proteins were further analyzed for differential expression and functional interactions using bioinformatic software.We identified 1,680 unique proteins in the retina and 675 unique proteins in the vitreous. Unbiased clustering identified protein pathways that distinguish retina from vitreous including oxidative phosphorylation and neurofilament cytoskeletal remodeling, whereas the vitreous expressed oxidative stress and innate immunology pathways. Some intracellular protein pathways were found in both retina and vitreous, such as glycolysis and gluconeogenesis and neuronal signaling, suggesting proteins might be shuttled between the retina and vitreous. We also identified human disease biomarkers represented in the mouse vitreous and retina, including carbonic anhydrase-2 and 3, crystallins, macrophage inhibitory factor, glutathione peroxidase, peroxiredoxins, S100 precursors, and von Willebrand factor.Our analysis suggests the vitreous expresses nonstructural proteins that functionally interact with the retina to manage oxidative stress, immune reactions, and intracellular proteins may be exchanged between the retina and vitreous. This novel proteomic dataset can be used for investigating human vitreoretinopathies in mouse models. Validation of vitreoretinal biomarkers for human ocular diseases will provide a critical tool for diagnostics and an avenue for therapeutics.

  10. Proteomic interactions in the mouse vitreous-retina complex.

    Science.gov (United States)

    Skeie, Jessica M; Mahajan, Vinit B

    2013-01-01

    Human vitreoretinal diseases are due to presumed abnormal mechanical interactions between the vitreous and retina, and translational models are limited. This study determined whether nonstructural proteins and potential retinal biomarkers were expressed by the normal mouse vitreous and retina. Vitreous and retina samples from mice were collected by evisceration and analyzed by liquid chromatography-tandem mass spectrometry. Identified proteins were further analyzed for differential expression and functional interactions using bioinformatic software. We identified 1,680 unique proteins in the retina and 675 unique proteins in the vitreous. Unbiased clustering identified protein pathways that distinguish retina from vitreous including oxidative phosphorylation and neurofilament cytoskeletal remodeling, whereas the vitreous expressed oxidative stress and innate immunology pathways. Some intracellular protein pathways were found in both retina and vitreous, such as glycolysis and gluconeogenesis and neuronal signaling, suggesting proteins might be shuttled between the retina and vitreous. We also identified human disease biomarkers represented in the mouse vitreous and retina, including carbonic anhydrase-2 and 3, crystallins, macrophage inhibitory factor, glutathione peroxidase, peroxiredoxins, S100 precursors, and von Willebrand factor. Our analysis suggests the vitreous expresses nonstructural proteins that functionally interact with the retina to manage oxidative stress, immune reactions, and intracellular proteins may be exchanged between the retina and vitreous. This novel proteomic dataset can be used for investigating human vitreoretinopathies in mouse models. Validation of vitreoretinal biomarkers for human ocular diseases will provide a critical tool for diagnostics and an avenue for therapeutics.

  11. Quantitative proteomic analysis for high-throughput screening of differential glycoproteins in hepatocellular carcinoma serum

    International Nuclear Information System (INIS)

    Gao, Hua-Jun; Chen, Ya-Jing; Zuo, Duo; Xiao, Ming-Ming; Li, Ying; Guo, Hua; Zhang, Ning; Chen, Rui-Bing

    2015-01-01

    Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC

  12. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

    2017-08-01

    Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of 4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

  13. The importance of accounting for sex in the search of proteomic signatures of mycotoxin exposure.

    Science.gov (United States)

    Soler, L; Oswald, I P

    2018-04-30

    Mycotoxins are natural food and feed contaminants that are toxic to human and animals. Proteomics is an adequate toolbox to investigate the mode of action and the effects of mycotoxins, as these toxicants often alter protein synthesis and degradation, as well as induce changes of important post-translational modifications. For instance, the contaminant deoxynivalenol induces a severe ribosomal stress that affects protein production, whereas the toxin Fumonisin B1 can alter the phosphorylation of a large number of proteins, and patulin is a potent proteotoxic molecule. The response to most mycotoxins is sex-dependent, males being generally more sensitive than females. In addition, for some toxins, the toxic effects observed were different for each sex. Nevertheless, the importance of accounting for a sex-dependent response is often overlooked in toxicology studies involving mycotoxins. Here we review the information that proteomics has provided in pre-clinical studies of mycotoxin exposure as well as the differential response of males and females to these molecules to highlight the need of including male and female individuals when evaluating the impact of mycotoxins in the cell proteome. The current trend in mycotoxicology is the combination of several -omics techniques in order to understand the mechanism of action and effects of these toxic natural food contaminants. One of the goals of these experiments is to determine "potential biomarkers" of mycotoxicoses. Nevertheless, the strategy followed in biomarker research must take into account as many possible factors as possible in order to find robust biomarkers for differential diagnosis. Among the factors that can have an influence in the response to mycotoxins, one of the most important is sex. Traditionally, males are preferentially used in research, as they are more sensitive to mycotoxins and their response is not dependent on hormonal levels, thus less variable. However the intrinsic and hormonal differences

  14. Proteomic analysis of urine in rats chronically exposed to fluoride.

    Science.gov (United States)

    Kobayashi, Claudia Ayumi Nakai; Leite, Aline de Lima; da Silva, Thelma Lopes; dos Santos, Lucilene Delazari; Nogueira, Fábio César Sousa; Santos, Keity Souza; de Oliveira, Rodrigo Cardoso; Palma, Mario Sérgio; Domont, Gilberto Barbosa; Buzalaf, Marília Afonso Rabelo

    2011-01-01

    Urine is an ideal source of materials to search for potential disease-related biomarkers as it is produced by the affected tissues and can be easily obtained by noninvasive methods. 2-DE-based proteomic approach was used to better understand the molecular mechanisms of injury induced by fluoride (F(-)) and define potential biomarkers of dental fluorosis. Three groups of weanling male Wistar rats were treated with drinking water containing 0 (control), 5, or 50 ppm F(-) for 60 days (n = 15/group). During the experimental period, the animals were kept individually in metabolic cages, to analyze the water and food consumption, as well as fecal and urinary F(-) excretion. Urinary proteome profiles were examined using 2-DE and Colloidal Coomassie Brilliant Blue staining. A dose-response regarding F(-) intake and excretion was detected. Quantitative intensity analysis revealed 8, 11, and 8 significantly altered proteins between control vs. 5 ppm F(-), control vs. 50 ppm F(-) and 5 ppm F(-) vs. 50 ppm F(-) groups, respectively. Two proteins regulated by androgens (androgen-regulated 20-KDa protein and α-2μ-globulin) and one related to detoxification (aflatoxin-B1-aldehyde-reductase) were identified by MALDI-TOF-TOF MS/MS. Thus, proteomic analysis can help to better understand the mechanisms underlying F(-) toxicity, even in low doses. Copyright © 2010 Wiley Periodicals, Inc.

  15. Verification of protein biomarker specificity for the identification of biological stains by quadrupole time-of-flight mass spectrometry.

    Science.gov (United States)

    Legg, Kevin M; Powell, Roger; Reisdorph, Nichole; Reisdorph, Rick; Danielson, Phillip B

    2017-03-01

    Advances in proteomics technology over the past decade offer forensic serologists a greatly improved opportunity to accurately characterize the tissue source from which a DNA profile has been developed. Such information can provide critical context to evidence and can help to prioritize downstream DNA analyses. Previous proteome studies compiled panels of "candidate biomarkers" specific to each of five body fluids (i.e., peripheral blood, vaginal/menstrual fluid, seminal fluid, urine, and saliva). Here, a multiplex quadrupole time-of-flight mass spectrometry assay has been developed in order to verify the tissue/body fluid specificity the 23 protein biomarkers that comprise these panels and the consistency with which they can be detected across a sample population of 50 humans. Single-source samples of these human body fluids were accurately identified by the detection of one or more high-specificity biomarkers. Recovery of body fluid samples from a variety of substrates did not impede accurate characterization and, of the potential inhibitors assayed, only chewing tobacco juice appeared to preclude the identification of a target body fluid. Using a series of 2-component mixtures of human body fluids, the multiplex assay accurately identified both components in a single-pass. Only in the case of saliva and peripheral blood did matrix effects appear to impede the detection of salivary proteins. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment

    DEFF Research Database (Denmark)

    Welker, F.

    2018-01-01

    Background: The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identificati......Background: The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein...... not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against......), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations...

  17. Skeletal muscle proteomics: current approaches, technical challenges and emerging techniques

    LENUS (Irish Health Repository)

    Ohlendieck, Kay

    2011-02-01

    Abstract Background Skeletal muscle fibres represent one of the most abundant cell types in mammals. Their highly specialised contractile and metabolic functions depend on a large number of membrane-associated proteins with very high molecular masses, proteins with extensive posttranslational modifications and components that exist in highly complex supramolecular structures. This makes it extremely difficult to perform conventional biochemical studies of potential changes in protein clusters during physiological adaptations or pathological processes. Results Skeletal muscle proteomics attempts to establish the global identification and biochemical characterisation of all members of the muscle-associated protein complement. A considerable number of proteomic studies have employed large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography, and combined them with mass spectrometry as the method of choice for high-throughput protein identification. Muscle proteomics has been applied to the comprehensive biochemical profiling of developing, maturing and aging muscle, as well as the analysis of contractile tissues undergoing physiological adaptations seen in disuse atrophy, physical exercise and chronic muscle transformation. Biomedical investigations into proteome-wide alterations in skeletal muscle tissues were also used to establish novel biomarker signatures of neuromuscular disorders. Importantly, mass spectrometric studies have confirmed the enormous complexity of posttranslational modifications in skeletal muscle proteins. Conclusions This review critically examines the scientific impact of modern muscle proteomics and discusses its successful application for a better understanding of muscle biology, but also outlines its technical limitations and emerging techniques to establish new biomarker candidates.

  18. Stage-Specific Transcriptome and Proteome Analyses of the Filarial Parasite Onchocerca volvulus and Its Wolbachia Endosymbiont

    Science.gov (United States)

    Bennuru, Sasisekhar; Cotton, James A.; Ribeiro, Jose M. C.; Grote, Alexandra; Harsha, Bhavana; Holroyd, Nancy; Mhashilkar, Amruta; Molina, Douglas M.; Randall, Arlo Z.; Shandling, Adam D.; Unnasch, Thomas R.; Ghedin, Elodie; Berriman, Matthew

    2016-01-01

    ABSTRACT Onchocerciasis (river blindness) is a neglected tropical disease that has been successfully targeted by mass drug treatment programs in the Americas and small parts of Africa. Achieving the long-term goal of elimination of onchocerciasis, however, requires additional tools, including drugs, vaccines, and biomarkers of infection. Here, we describe the transcriptome and proteome profiles of the major vector and the human host stages (L1, L2, L3, molting L3, L4, adult male, and adult female) of Onchocerca volvulus along with the proteome of each parasitic stage and of its Wolbachia endosymbiont (wOv). In so doing, we have identified stage-specific pathways important to the parasite’s adaptation to its human host during its early development. Further, we generated a protein array that, when screened with well-characterized human samples, identified novel diagnostic biomarkers of O. volvulus infection and new potential vaccine candidates. This immunomic approach not only demonstrates the power of this postgenomic discovery platform but also provides additional tools for onchocerciasis control programs. PMID:27881553

  19. Salivary proteomic and genomic biomarkers for primary Sjogren's syndrome

    NARCIS (Netherlands)

    Hu, Shen; Wang, Jianghua; Leong, Sonya; Xie, Yongming; Yu, Tianwei; Zhou, Hui; Henry, Sharon; Vissink, Arjan; Pijpe, Justin; Kallenberg, Cees; Elashoff, David; Loo, Joseph A.; Wong, David T.

    2007-01-01

    Objective. To identify a panel of protein and messenger RNA (mRNA) biomarkers in human whole saliva (WS) that may be used in the detection of primary Sjogren's syndrome (SS). Methods. Mass spectrometry and expression microarray profiling were used to identify candidate protein and mRNA, biomarkers

  20. Salivary proteomic and genomic biomarkers for primary Sjogren's syndrome

    NARCIS (Netherlands)

    Hu, Shen; Wang, Jianghua; Leong, Sonya; Xie, Yongming; Yu, Tianwei; Zhou, Hui; Henry, Sharon; Vissink, Arjan; Pijpe, Justin; Kallenberg, Cees; Elashoff, David; Loo, Joseph A.; Wong, David T.

    Objective. To identify a panel of protein and messenger RNA (mRNA) biomarkers in human whole saliva (WS) that may be used in the detection of primary Sjogren's syndrome (SS). Methods. Mass spectrometry and expression microarray profiling were used to identify candidate protein and mRNA, biomarkers

  1. Comparative proteomic analysis of ductal and lobular invasive breast carcinoma.

    Science.gov (United States)

    Oliveira, N C S; Gomig, T H B; Milioli, H H; Cordeiro, F; Costa, G G; Urban, C A; Lima, R S; Cavalli, I J; Ribeiro, E M S F

    2016-04-04

    Breast cancer is the second most common cancer worldwide and the first among women. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two major histological subtypes, and the clinical and molecular differences between them justify the search for new markers to distinguish them. As proteomic analysis allows for a powerful and analytical approach to identify potential biomarkers, we performed a comparative analysis of IDC and ILC samples by using two-dimensional electrophoresis and mass spectrometry. Twenty-three spots were identified corresponding to 10 proteins differentially expressed between the two subtypes. ACTB, ACTG, TPM3, TBA1A, TBA1B, VIME, TPIS, PDIA3, PDIA6, and VTDB were upregulated in ductal carcinoma compared to in lobular carcinoma samples. Overall, these 10 proteins have a key role in oncogenesis. Their specific functions and relevance in cancer initiation and progression are further discussed in this study. The identified peptides represent promising biomarkers for the differentiation of ductal and lobular breast cancer subtypes, and for future interventions based on tailored therapy.

  2. Proteomics of anti-cancer drugs

    Czech Academy of Sciences Publication Activity Database

    Kovářová, Hana; Martinková, Jiřina; Hrabáková, Rita; Skalníková, Helena; Novák, Petr; Hajdůch, M.; Gadher, S. J.

    2009-01-01

    Roč. 276, Supplement 1 (2009), s. 84-84 E-ISSN 1742-4658. [34th FEBS Congress. 04.07.2009-09.07.2009, Praha] R&D Projects: GA MŠk LC07017 Institutional research plan: CEZ:AV0Z50450515; CEZ:AV0Z50200510 Keywords : proteomics * anti-cancer drugs * biomarkers Subject RIV: FD - Oncology ; Hematology

  3. Comparing the proteome of snap frozen, RNAlater preserved, and formalin-fixed paraffin-embedded human tissue samples

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Kastaniegaard, Kenneth; Padurariu, Simona

    2016-01-01

    Large biobanks exist worldwide containing formalin-fixed, paraffin-embedded samples and samples stored in RNAlater. However, the impact of tissue preservation on the result of a quantative proteome analysis remains poorly described.Human colon mucosal biopsies were extracted from the sigmoideum...

  4. Human cervicovaginal fluid biomarkers to predict term and preterm labor

    Science.gov (United States)

    Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

    2015-01-01

    Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

  5. A Timely shift from shotgun to targeted proteomics and how it can be groundbreaking for cancer research

    DEFF Research Database (Denmark)

    Faria, Sara S.; Morris, Carlos F.M.; Silva, Adriano R.

    2017-01-01

    shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated...... to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples...... applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm...

  6. Serum proteomic changes after randomized prolonged erythropoietin treatment and/or endurance training: detection of novel biomarkers.

    Directory of Open Access Journals (Sweden)

    Britt Christensen

    Full Text Available Despite implementation of the biological passport to detect erythropoietin abuse, a need for additional biomarkers remains. We used a proteomic approach to identify novel serum biomarkers of prolonged erythropoiesis-stimulating agent (ESA exposure (Darbepoietin-α and/or aerobic training.Thirty-six healthy young males were randomly assigned to the following groups: Sedentary-placebo (n = 9, Sedentary-ESA (n = 9, Training-placebo (n = 10, or Training-ESA (n = 8. They were treated with placebo/Darbepoietin-α subcutaneously once/week for 10 weeks followed by a 3-week washout period. Training consisted of supervised biking 3/week for 13 weeks at the highest possible intensity. Serum was collected at baseline, week 3 (high dose Darbepoietin-α, week 10 (reduced dose Darbepoietin-α, and after a 3-week washout period.Serum proteins were separated according to charge and molecular mass (2D-gel electrophoresis. The identity of proteins from spots exhibiting altered intensity was determined by mass spectrometry.Six protein spots changed in response to Darbepoietin-α treatment. Comparing all 4 experimental groups, two protein spots (serotransferrin and haptoglobin/haptoglobin related protein showed a significant response to Darbepoietin-α treatment. The haptoglobin/haptoglobin related protein spot showed a significantly lower intensity in all subjects in the training-ESA group during the treatment period and increased during the washout period.An isoform of haptoglobin/haptoglobin related protein could be a new anti-doping marker and merits further research.ClinicalTrials.gov NCT01320449.

  7. Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

    Science.gov (United States)

    Großerueschkamp, Frederik; Bracht, Thilo; Diehl, Hanna C.; Kuepper, Claus; Ahrens, Maike; Kallenbach-Thieltges, Angela; Mosig, Axel; Eisenacher, Martin; Marcus, Katrin; Behrens, Thomas; Brüning, Thomas; Theegarten, Dirk; Sitek, Barbara; Gerwert, Klaus

    2017-03-01

    Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

  8. Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics.

    Science.gov (United States)

    Gao, Yan; Lim, Teck Kwang; Lin, Qingsong; Li, Sam Fong Yau

    2016-04-29

    Cypermethrin (CYP) is one of the most widely used pesticides in large scale for agricultural and domestic purpose and the residue often seriously affects aquatic system. Environmental pollutant-induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of action. While proteomics investigations of CYP stress in some animal models have been well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001μg/L, 0.01μg/L and 1μg/L) of CYP on green algae Chlorella vulgaris for 24h and 96h was investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrate metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticide-exposed plant and algae. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Toxicoproteomics: serum proteomic pattern diagnostics for early detection of drug induced cardiac toxicities and cardioprotection.

    Science.gov (United States)

    Petricoin, Emanuel F; Rajapaske, Vinodh; Herman, Eugene H; Arekani, Ali M; Ross, Sally; Johann, Donald; Knapton, Alan; Zhang, J; Hitt, Ben A; Conrads, Thomas P; Veenstra, Timothy D; Liotta, Lance A; Sistare, Frank D

    2004-01-01

    Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry which communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity based processes as cascades of reinforcing information percolate through the system and become reflected in changing proteomic information content of the circulation. Serum Proteomic Pattern Diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. While this approach has shown tremendous promise in early detection of cancers, detection of drug-induced toxicity may also be possible with this same technology. Analysis of serum from rat models of anthracycline and anthracenedione induced cardiotoxicity indicate the potential clinical utility of diagnostic proteomic patterns where low molecular weight peptides and protein fragments may have higher accuracy than traditional biomarkers of cardiotoxicity such as troponins. These fragments may one day be harvested by circulating nanoparticles designed to absorb, enrich and amplify the diagnostic biomarker repertoire generated even at the critical initial stages of toxicity.

  10. Identifying Predictors of Taxane-Induced Peripheral Neuropathy Using Mass Spectrometry-Based Proteomics Technology.

    Directory of Open Access Journals (Sweden)

    Emily I Chen

    Full Text Available Major advances in early detection and therapy have significantly increased the survival of breast cancer patients. Unfortunately, most cancer therapies are known to carry a substantial risk of adverse long-term treatment-related effects. Little is known about patient susceptibility to severe side effects after chemotherapy. Chemotherapy-induced peripheral neuropathy (CIPN is a common side effect of taxanes. Recent advances in genome-wide genotyping and sequencing technologies have supported the discoveries of a number of pharmacogenetic markers that predict response to chemotherapy. However, effectively implementing these pharmacogenetic markers in the clinic remains a major challenge. On the other hand, recent advances in proteomic technologies incorporating mass spectrometry (MS for biomarker discovery show great promise to provide clinically relevant protein biomarkers. In this study, we evaluated the association between protein content in serum exosomes and severity of CIPN. Women with early stage breast cancer receiving adjuvant taxane chemotherapy were assessed with the FACT-Ntx score and serum was collected before and after the taxane treatment. Based on the change in FACT-Ntx score from baseline to 12 month follow-up, we separated patients into two groups: those who had no change (Group 1, N = 9 and those who had a ≥20% worsening (Group 1, N = 8. MS-based proteomics technology was used to identify proteins present in serum exosomes to determine potential biomarkers. Mann-Whitney-Wilcoxon analysis was applied and maximum FDR was controlled at 20%. From the serum exosomes derived from this cohort, we identified over 700 proteins known to be in different subcellular locations and have different functions. Statistical analysis revealed a 12-protein signature that resulted in a distinct separation between baseline serum samples of both groups (q<0.2 suggesting that the baseline samples can predict subsequent neurotoxicity. These toxicity

  11. The Landscape of Protein Biomarkers Proposed for Periodontal Disease: Markers with Functional Meaning

    Directory of Open Access Journals (Sweden)

    Nuno Rosa

    2014-01-01

    Full Text Available Periodontal disease (PD is characterized by a deregulated inflammatory response which fails to resolve, activating bone resorption. The identification of the proteomes associated with PD has fuelled biomarker proposals; nevertheless, many questions remain. Biomarker selection should favour molecules representing an event which occurs throughout the disease progress. The analysis of proteome results and the information available for each protein, including its functional role, was accomplished using the OralOme database. The integrated analysis of this information ascertains if the suggested proteins reflect the cell and/or molecular mechanisms underlying the different forms of periodontal disease. The evaluation of the proteins present/absent or with very different concentrations in the proteome of each disease state was used for the identification of the mechanisms shared by different PD variants or specific to such state. The information presented is relevant for the adequate design of biomarker panels for PD. Furthermore, it will open new perspectives and help envisage future studies targeted to unveil the functional role of specific proteins and help clarify the deregulation process in the PD inflammatory response.

  12. Differential proteomic profiling of primary and recurrent chordomas.

    Science.gov (United States)

    Chen, Su; Xu, Wei; Jiao, Jian; Jiang, Dongjie; Liu, Jian; Chen, Tenghui; Wan, Zongmiao; Xu, Leqin; Zhou, Zhenhua; Xiao, Jianru

    2015-05-01

    Chordomas are locally destructive tumors with high rates of recurrence and a poor prognosis. The mechanisms involved in chordoma recurrence remain largely unknown. In the present study, we examined the proteomic profile of a chordoma primary tumor (CSO) and a recurrent tumor (CSR) through mass spectrum in a chordoma patient who underwent surgery. Bioinformatic analysis of the profile showed that 359 proteins had a significant expression difference and 21 pathways had a striking alteration between the CSO and the CSR. The CSR showed a significant increase in carbohydrate metabolism. Immunohistochemistry (IHC) confirmed that the cancer stem cell marker activated leukocyte cell adhesion molecule (ALCAM or CD166) expression level was higher in the recurrent than that in the primary tumor. The present study analyzed the proteomic profile change between CSO and CSR and identified a new biomarker ALCAM in recurrent chordomas. This finding sheds light on unraveling the pathophysiology of chordoma recurrence and on exploring more effective prognostic biomarkers and targeted therapies against this devastating disease.

  13. Mass Spectrometry–based Proteomic Profiling of Lung Cancer

    Science.gov (United States)

    Ocak, Sebahat; Chaurand, Pierre; Massion, Pierre P.

    2009-01-01

    In an effort to further our understanding of lung cancer biology and to identify new candidate biomarkers to be used in the management of lung cancer, we need to probe these tissues and biological fluids with tools that address the biology of lung cancer directly at the protein level. Proteins are responsible of the function and phenotype of cells. Cancer cells express proteins that distinguish them from normal cells. Proteomics is defined as the study of the proteome, the complete set of proteins produced by a species, using the technologies of large-scale protein separation and identification. As a result, new technologies are being developed to allow the rapid and systematic analysis of thousands of proteins. The analytical advantages of mass spectrometry (MS), including sensitivity and high-throughput, promise to make it a mainstay of novel biomarker discovery to differentiate cancer from normal cells and to predict individuals likely to develop or recur with lung cancer. In this review, we summarize the progress made in clinical proteomics as it applies to the management of lung cancer. We will focus our discussion on how MS approaches may advance the areas of early detection, response to therapy, and prognostic evaluation. PMID:19349484

  14. Informatics-guided procurement of patient samples for biomarker discovery projects in cancer research.

    Science.gov (United States)

    Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H

    2009-02-01

    Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.

  15. Comparative proteomic analysis reveals heart toxicity induced by chronic arsenic exposure in rats

    International Nuclear Information System (INIS)

    Huang, Qingyu; Xi, Guochen; Alamdar, Ambreen; Zhang, Jie; Shen, Heqing

    2017-01-01

    Arsenic is a widespread metalloid in the environment, which poses a broad spectrum of adverse effects on human health. However, a global view of arsenic-induced heart toxicity is still lacking, and the underlying molecular mechanisms remain unclear. By performing a comparative quantitative proteomic analysis, the present study aims to investigate the alterations of proteome profile in rat heart after long-term exposure to arsenic. As a result, we found that the abundance of 81 proteins were significantly altered by arsenic treatment (35 up-regulated and 46 down-regulated). Among these, 33 proteins were specifically associated with cardiovascular system development and function, including heart development, heart morphology, cardiac contraction and dilation, and other cardiovascular functions. It is further proposed that the aberrant regulation of 14 proteins induced by arsenic would disturb cardiac contraction and relaxation, impair heart morphogenesis and development, and induce thrombosis in rats, which is mediated by the Akt/p38 MAPK signaling pathway. Overall, these findings will augment our knowledge of the involved mechanisms and develop useful biomarkers for cardiotoxicity induced by environmental arsenic exposure. - Highlights: • Arsenic exposure has been associated with a number of adverse health effects. • The molecular mechanisms involved in arsenic-induced cardiotoxicity remain unclear. • Differential proteins were identified in arsenic-exposed rat heart by proteomics. • Arsenic induces heart toxicity through the Akt/p38 MAPK signaling pathway. - Label-free quantitative proteomic analysis of rat heart reveals putative mechanisms and biomarkers for arsenic-induced cardiotoxicity.

  16. Integrated multi-level quality control for proteomic profiling studies using mass spectrometry

    Directory of Open Access Journals (Sweden)

    Barrett Jennifer H

    2008-12-01

    Full Text Available Abstract Background Proteomic profiling using mass spectrometry (MS is one of the most promising methods for the analysis of complex biological samples such as urine, serum and tissue for biomarker discovery. Such experiments are often conducted using MALDI-TOF (matrix-assisted laser desorption/ionisation time-of-flight and SELDI-TOF (surface-enhanced laser desorption/ionisation time-of-flight MS. Using such profiling methods it is possible to identify changes in protein expression that differentiate disease states and individual proteins or patterns that may be useful as potential biomarkers. However, the incorporation of quality control (QC processes that allow the identification of low quality spectra reliably and hence allow the removal of such data before further analysis is often overlooked. In this paper we describe rigorous methods for the assessment of quality of spectral data. These procedures are presented in a user-friendly, web-based program. The data obtained post-QC is then examined using variance components analysis to quantify the amount of variance due to some of the factors in the experimental design. Results Using data from a SELDI profiling study of serum from patients with different levels of renal function, we show how the algorithms described in this paper may be used to detect systematic variability within and between sample replicates, pooled samples and SELDI chips and spots. Manual inspection of those spectral data that were identified as being of poor quality confirmed the efficacy of the algorithms. Variance components analysis demonstrated the relatively small amount of technical variance attributable to day of profile generation and experimental array. Conclusion Using the techniques described in this paper it is possible to reliably detect poor quality data within proteomic profiling experiments undertaken by MS. The removal of these spectra at the initial stages of the analysis substantially improves the

  17. Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

    Science.gov (United States)

    Martyanov, Viktor; Whitfield, Michael L

    2016-01-01

    The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

  18. Comparison of proteomic biomarker panels in urine and serum for ovarian cancer diagnosis

    DEFF Research Database (Denmark)

    Petri, Anette Lykke; Simonsen, Anja Hviid; Høgdall, Estrid

    2010-01-01

    The purposes of this study were to confirm previously found candidate epithelial ovarian cancer biomarkers in urine and to compare a paired serum biomarker panel and a urine biomarker panel from the same study cohort with regard to the receiver operating characteristic curve (ROC) area under the ...

  19. Biomarker discovery in low-grade breast cancer using isobaric stable isotope tags and two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS) based quantitative proteomic analysis.

    Science.gov (United States)

    Bouchal, Pavel; Roumeliotis, Theodoros; Hrstka, Roman; Nenutil, Rudolf; Vojtesek, Borivoj; Garbis, Spiros D

    2009-01-01

    The present pilot study constitutes a proof-of-principle in the use of a quantitative LC-MS/MS based proteomic method for the comparative analysis of representative low-grade breast primary tumor tissues with and without metastases and metastasis in lymph node relative to the nonmetastatic tumor type. The study method incorporated iTRAQ stable isotope labeling, two-dimensional liquid chromatography, nanoelectrospray ionization and high resolution tandem mass spectrometry using the hybrid QqTOF platform (iTRAQ-2DLC-MS/MS). The principal aims of this study were (1) to define the protein spectrum obtainable using this approach, and (2) to highlight potential candidates for verification and validation studies focused on biomarkers involved in metastatic processes in breast cancer. The study resulted in the reproducible identification of 605 nonredundant proteins (p biomarker discovery program.

  20. A proteomic-based characterization of liver metabolism in dairy cows and young pigs

    DEFF Research Database (Denmark)

    Sejersen, Henrik

    This thesis deals with studies on liver metabolism in cows and pigs. Proteome analysis was used to quantify a large number of proteins involved in metabolic pathways. In cows, the objective was to characterize differences in the liver proteome between early lactation dairy cows with low or high...... liver fat content and suggest potential blood-based biomarkers for early detection of fatty liver to substantiate prevention strategies. Our results show that several proteins in liver metabolic pathways are affected by liver fat content and that blood aspartate aminotransferase, ß...

  1. Multiplex array proteomics detects increased MMP-8 in CSF after spinal cord injury.

    Science.gov (United States)

    Light, Matthew; Minor, Kenneth H; DeWitt, Peter; Jasper, Kyle H; Davies, Stephen J A

    2012-06-11

    A variety of methods have been used to study inflammatory changes in the acutely injured spinal cord. Recently novel multiplex assays have been used in an attempt to overcome limitations in numbers of available targets studied in a single experiment. Other technical challenges in developing pre-clinical rodent models to investigate biomarkers in cerebrospinal fluid (CSF) include relatively small volumes of sample and low concentrations of target proteins. The primary objective of this study was to characterize the inflammatory profile present in CSF at a subacute time point in a clinically relevant rodent model of traumatic spinal cord injury (SCI). Our other aim was to test a microarray proteomics platform specifically for this application. A 34 cytokine sandwich ELISA microarray was used to study inflammatory changes in CSF samples taken 12 days post-cervical SCI in adult rats. The difference between the median foreground signal and the median background signal was measured. Bonferroni and Benjamini-Hochburg multiple testing corrections were applied to limit the False Discovery Rate (FDR), and a linear mixed model was used to account for repeated measures in the array. We report a novel subacute SCI biomarker, elevated levels of matrix metalloproteinase-8 protein in CSF, and discuss application of statistical models designed for multiplex testing. Major advantages of this assay over conventional methods include high-throughput format, good sensitivity, and reduced sample consumption. This method can be useful for creating comprehensive inflammatory profiles, and biomarkers can be used in the clinic to assess injury severity and to objectively grade response to therapy.

  2. Proteomic profiling of the amniotic fluid to detect inflammation, infection, and neonatal sepsis.

    Directory of Open Access Journals (Sweden)

    Catalin S Buhimschi

    2007-01-01

    Full Text Available Proteomic analysis of amniotic fluid shows the presence of biomarkers characteristic of intrauterine inflammation. We sought to validate prospectively the clinical utility of one such proteomic profile, the Mass Restricted (MR score.We enrolled 169 consecutive women with singleton pregnancies admitted with preterm labor or preterm premature rupture of membranes. All women had a clinically indicated amniocentesis to rule out intra-amniotic infection. A proteomic fingerprint (MR score was generated from fresh samples of amniotic fluid using surface-enhanced laser desorption ionization (SELDI mass spectrometry. Presence or absence of the biomarkers of the MR score was interpreted in relationship to the amniocentesis-to-delivery interval, placental inflammation, and early-onset neonatal sepsis for all neonates admitted to the Newborn Special Care Unit (n = 104. Women with "severe" amniotic fluid inflammation (MR score of 3 or 4 had shorter amniocentesis-to-delivery intervals than women with "no" (MR score of 0 inflammation or even "minimal" (MR score of 1 or 2 inflammation (median [range] MR 3-4: 0.4 d [0.0-49.6 d] versus MR 1-2: 3.8 d [0.0-151.2 d] versus MR 0: 17.0 d [0.1-94.3 d], p 100 cells/mm3, whereas the combination of Gram stain and MR score was best for rapid prediction of intra-amniotic infection (positive amniotic fluid culture.High MR scores are associated with preterm delivery, histological chorioamnionitis, and early-onset neonatal sepsis. In this study, proteomic analysis of amniotic fluid was shown to be the most accurate test for diagnosis of intra-amniotic inflammation, whereas addition of the MR score to the Gram stain provides the best combination of tests to rapidly predict infection.

  3. Emerging Biomarkers and Metabolomics for Assessing Toxic Nephropathy and Acute Kidney Injury (AKI in Neonatology

    Directory of Open Access Journals (Sweden)

    M. Mussap

    2014-01-01

    Full Text Available Identification of novel drug-induced toxic nephropathy and acute kidney injury (AKI biomarkers has been designated as a top priority by the American Society of Nephrology. Increasing knowledge in the science of biology and medicine is leading to the discovery of still more new biomarkers and of their roles in molecular pathways triggered by physiological and pathological conditions. Concomitantly, the development of the so-called “omics” allows the progressive clinical utilization of a multitude of information, from those related to the human genome (genomics and proteome (proteomics, including the emerging epigenomics, to those related to metabolites (metabolomics. In preterm newborns, one of the most important factors causing the pathogenesis and the progression of AKI is the interaction between the individual genetic code, the environment, the gestational age, and the disease. By analyzing a small urine sample, metabolomics allows to identify instantly any change in phenotype, including changes due to genetic modifications. The role of liquid chromatography-mass spectrometry (LC-MS, proton nuclear magnetic resonance (1H NMR, and other emerging technologies is strategic, contributing basically to the sudden development of new biochemical and molecular tests. Urine neutrophil gelatinase-associated lipocalin (uNGAL and kidney injury molecule-1 (KIM-1 are closely correlated with the severity of kidney injury, representing noninvasive sensitive surrogate biomarkers for diagnosing, monitoring, and quantifying kidney damage. To become routine tests, uNGAL and KIM-1 should be carefully tested in multicenter clinical trials and should be measured in biological fluids by robust, standardized analytical methods.

  4. Proteomic Profiling of the Pituitary Gland in Studies of Psychiatric Disorders.

    Science.gov (United States)

    Krishnamurthy, Divya; Rahmoune, Hassan; Guest, Paul C

    2017-01-01

    Psychiatric disorders have been associated with perturbations of the hypothalamic-pituitary-adrenal axis. Therefore, proteomic studies of the pituitary gland have the potential to provide new insights into the underlying pathways affected in these conditions as well as identify new biomarkers or targets for use in developing improved medications. This chapter describes a protocol for preparation of pituitary protein extracts followed by characterization of the pituitary proteome by label-free liquid chromatography-tandem mass spectrometry in expression mode (LC-MS E ). The main focus was on establishing a method for identifying the major pituitary hormones and accessory proteins as many of these have already been implicated in psychiatric diseases.

  5. Renal Cancer Biomarkers | NCI Technology Transfer Center | TTC

    Science.gov (United States)

    The National Cancer Institute's Laboratory of Proteomics and Analytical Technologies is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize diagnostic, therapeutic and prognostic cancer biomarkers from clinical specimens.

  6. Defining the Adipose Tissue Proteome of Dairy Cows to Reveal Biomarkers Related to Peripartum Insulin Resistance and Metabolic Status.

    Science.gov (United States)

    Zachut, Maya

    2015-07-02

    Adipose tissue is a central regulator of metabolism in dairy cows; however, little is known about the association between various proteins in adipose tissue and the metabolic status of peripartum cows. Therefore, the objectives were to (1) examine total protein expression in adipose tissue of dairy cows and (2) identify biomarkers in adipose that are linked to insulin resistance and to cows' metabolic status. Adipose tissue biopsies were obtained from eight multiparous cows at -17 and +4 days relative to parturition. Proteins were analyzed by intensity-based, label-free, quantitative shotgun proteomics (nanoLC-MS/MS). Cows were divided into groups with insulin-resistant (IR) and insulin-sensitive (IS) adipose according to protein kinase B phosphorylation following insulin stimulation. Cows with IR adipose lost more body weight postpartum compared with IS cows. Differential expression of 143 out of 586 proteins was detected in prepartum versus postpartum adipose. Comparing IR to IS adipose revealed differential expression of 18.9% of the proteins; those related to lipolysis (hormone-sensitive lipase, perilipin, monoglycerol lipase) were increased in IR adipose. In conclusion, we found novel biomarkers related to IR in adipose and to metabolic status that could be used to characterize high-yielding dairy cows that are better adapted to peripartum metabolic stress.

  7. Proteoglycan and proteome profiling of central human pulmonary fibrotic tissue utilizing miniaturized sample preparation

    DEFF Research Database (Denmark)

    Malmström, Johan; Larsen, Kristoffer; Hansson, Lennart

    2002-01-01

    -dimensional electrophoresis was interfaced to miniaturized sample preparation techniques using microcapillary extraction. Four protein groups were identified; cytoskeletal, adhesion, scavenger and metabolic proteins. These patient's proteomes showed a high degree of heterogeneity between patients but larger homogeneity...

  8. Identification of novel biomarkers for sepsis prognosis via urinary proteomic analysis using iTRAQ labeling and 2D-LC-MS/MS.

    Directory of Open Access Journals (Sweden)

    Longxiang Su

    Full Text Available Sepsis is the major cause of death for critically ill patients. Recent progress in proteomics permits a thorough characterization of the mechanisms associated with critical illness. The purpose of this study was to screen potential biomarkers for early prognostic assessment of patients with sepsis.For the discovery stage, 30 sepsis patients with different prognoses were selected. Urinary proteins were identified using isobaric tags for relative and absolute quantitation (iTRAQ coupled with LC-MS/MS. Mass spec instrument analysis were performed with Mascot software and the International Protein Index (IPI; bioinformatic analyses were used by the algorithm of set and the Gene Ontology (GO Database. For the verification stage, the study involved another 54 sepsis-hospitalized patients, with equal numbers of patients in survivor and non-survivor groups based on 28-day survival. Differentially expressed proteins were verified by Western Blot.A total of 232 unique proteins were identified. Proteins that were differentially expressed were further analyzed based on the pathophysiology of sepsis and biomathematics. For sepsis prognosis, five proteins were significantly up-regulated: selenium binding protein-1, heparan sulfate proteoglycan-2, alpha-1-B glycoprotein, haptoglobin, and lipocalin; two proteins were significantly down-regulated: lysosome-associated membrane proteins-1 and dipeptidyl peptidase-4. Based on gene ontology clustering, these proteins were associated with the biological processes of lipid homeostasis, cartilage development, iron ion transport, and certain metabolic processes. Urinary LAMP-1 was down-regulated, consistent with the Western Blot validation.This study provides the proteomic analysis of urine to identify prognostic biomarkers of sepsis. The seven identified proteins provide insight into the mechanism of sepsis. Low urinary LAMP-1 levels may be useful for early prognostic assessment of sepsis.ClinicalTrial.gov NCT01493492.

  9. imFASP: An integrated approach combining in-situ filter-aided sample pretreatment with microwave-assisted protein digestion for fast and efficient proteome sample preparation.

    Science.gov (United States)

    Zhao, Qun; Fang, Fei; Wu, Ci; Wu, Qi; Liang, Yu; Liang, Zhen; Zhang, Lihua; Zhang, Yukui

    2016-03-17

    An integrated sample preparation method, termed "imFASP", which combined in-situ filter-aided sample pretreatment and microwave-assisted trypsin digestion, was developed for preparation of microgram and even nanogram amounts of complex protein samples with high efficiency in 1 h. For imFASP method, proteins dissolved in 8 M urea were loaded onto a filter device with molecular weight cut off (MWCO) as 10 kDa, followed by in-situ protein preconcentration, denaturation, reduction, alkylation, and microwave-assisted tryptic digestion. Compared with traditional in-solution sample preparation method, imFASP method generated more protein and peptide identifications (IDs) from preparation of 45 μg Escherichia coli protein sample due to the higher efficiency, and the sample preparation throughput was significantly improved by 14 times (1 h vs. 15 h). More importantly, when the starting amounts of E. coli cell lysate decreased to nanogram level (50-500 ng), the protein and peptide identified by imFASP method were improved at least 30% and 44%, compared with traditional in-solution preparation method, suggesting dramatically higher peptide recovery of imFASP method for trace amounts of complex proteome samples. All these results demonstrate that the imFASP method developed here is of high potential for high efficient and high throughput preparation of trace amounts of complex proteome samples. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Proteomics analysis of dendritic cell activation by contact allergens reveals possible biomarkers regulated by Nrf2

    Energy Technology Data Exchange (ETDEWEB)

    Mussotter, Franz, E-mail: franz.mussotter@bfr.bund.de [German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin (Germany); Tomm, Janina Melanie [Helmholtz Centre for Environmental Research (UFZ), Department of Molecular Systems Biology, Leipzig (Germany); El Ali, Zeina; Pallardy, Marc; Kerdine-Römer, Saadia [INSERM UMR 996, Univ Paris-Sud, Université Paris-Saclay, Chátenay-Malabry (France); Götz, Mario [German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin (Germany); Bergen, Martin von [Helmholtz Centre for Environmental Research (UFZ), Department of Molecular Systems Biology, Leipzig (Germany); University of Leipzig, Institute of Biochemistry, Leipzig (Germany); Aalborg University, Department of Chemistry and Bioscience, Aalborg (Denmark); Haase, Andrea; Luch, Andreas [German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin (Germany)

    2016-12-15

    Allergic contact dermatitis is a widespread disease with high clinical relevance affecting approximately 20% of the general population. Typically, contact allergens are low molecular weight electrophilic compounds which can activate the Keap1/Nrf2 pathway. We performed a proteomics study to reveal possible biomarkers for dendritic cell (DC) activation by contact allergens and to further elucidate the role of Keap1/Nrf2 signaling in this process. We used bone marrow derived dendritic cells (BMDCs) of wild-type (nrf2{sup +/+}) and Nrf2 knockout (nrf2{sup −/−}) mice and studied their response against the model contact sensitizers 2,4-dinitrochlorobenzene (DNCB), cinnamaldehyde (CA) and nickel(II) sulfate by 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) in combination with electrospray ionization tandem mass spectrometry (ESI-MS/MS). Sodium dodecyl sulfate (SDS, 100 μM) served as irritant control. While treatment with nickel(II) sulfate and SDS had only little effects, CA and DNCB led to significant changes in protein expression. We found 18 and 30 protein spots up-regulated in wild-type cells treated with 50 and 100 μM CA, respectively. For 5 and 10 μM DNCB, 32 and 37 spots were up-regulated, respectively. Almost all of these proteins were not differentially expressed in nrf2{sup −/−} BMDCs, indicating an Nrf2-dependent regulation. Among them proteins were detected which are involved in oxidative stress and heat shock responses, as well as in signal transduction or basic cellular pathways. The applied approach allowed us to differentiate between Nrf2-dependent and Nrf2-independent cellular biomarkers differentially regulated upon allergen-induced DC activation. The data presented might contribute to the further development of suitable in vitro testing methods for chemical-mediated sensitization. - Highlights: • Contact allergens induce proteins involved in DC maturation Nrf2-dependently. • Induction of these proteins points to a functional

  11. MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

    Science.gov (United States)

    Berger, Sebastian T; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

    2015-10-01

    We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  12. CURRENT APPROACHES FOR RESEARCH OF MULTIPLE SCLEROSIS BIOMARKERS

    Directory of Open Access Journals (Sweden)

    Kolyada T.I

    2016-12-01

    Full Text Available Current data concerning features of multiple sclerosis (MS etiology, pathogenesis, clinical course and treatment of disease indicate the necessity of personalized approach to the management of MS patients. These features are the variety of possible etiological factors and mechanisms that trigger the development of MS, different courses of disease, and significant differences in treatment efficiency. Phenotypic and pathogenetic heterogeneity of MS requires, on the one hand, the stratification of patients into groups with different treatment depending on a number of criteria including genetic characteristics, disease course, stage of the pathological process, and forms of the disease. On the other hand, it requires the use of modern methods for assessment of individual risk of developing MS, its early diagnosis, evaluation and prognosis of the disease course and the treatment efficiency. This approach is based on the identification and determination of biomarkers of MS including the use of systems biology technology platforms such as genomics, proteomics, metabolomics and bioinformatics. Research and practical use of biomarkers of MS in clinical and laboratory practice requires the use of a wide range of modern medical and biological, mathematical and physicochemical methods. The group of "classical" methods used to study MS biomarkers includes physicochemical and immunological methods aimed at the selection and identification of single molecular biomarkers, as well as methods of molecular genetic analysis. This group of methods includes ELISA, western blotting, isoelectric focusing, immunohistochemical methods, flow cytometry, spectrophotometric and nephelometric methods. These techniques make it possible to carry out both qualitative and quantitative assay of molecular biomarkers. The group of "classical methods" can also include methods based on polymerase chain reaction (including multiplex and allele-specific PCR and genome sequencing

  13. Calorimetric monitoring of the serum proteome in schizophrenia patients

    Energy Technology Data Exchange (ETDEWEB)

    Krumova, Sashka [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria); Rukova, Blaga [Department of Medical Genetics, Medical University of Sofia, 2 Zdrave Str., Sofia 1431 (Bulgaria); Todinova, Svetla [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria); Gartcheva, Lidia [National Specialized Hospital for Active Treating of Haematological Diseases, 6 Plovdivsko pole Str., Sofia 1756 (Bulgaria); Milanova, Vihra [Department of Psychiatry, Medical University of Sofia, 1 Sv. Georgi Sofiiski Str., Sofia 1431 (Bulgaria); Toncheva, Draga [Department of Medical Genetics, Medical University of Sofia, 2 Zdrave Str., Sofia 1431 (Bulgaria); Taneva, Stefka G., E-mail: stefka.germanova@ehu.es [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria)

    2013-11-20

    Highlights: • DSC reveals modified thermal behavior of blood serum from schizophrenic patients. • The high-abundance portion of the serum proteome is thermally stabilized in Sz. • The Sz plasma thermograms are classified in four distinct calorimetric groups. • The effectiveness of drug treatment correlates with the plasma thermodynamic behavior. - Abstract: Schizophrenia (Sz) is a multifactorial mental disorder with high frequency. Due to its chronic and relapsing nature there is a strong need for biomarkers for early psychosis detection and objective evaluation of drug (usually antipsychotics) treatment effect. Here differential scanning calorimetry (DSC) is applied to thermodynamically characterize the blood serum proteome of paranoid schizophrenia patients on routine antipsychotic treatment in comparison to healthy controls. DSC revealed significant modifications in the thermodynamic behavior of blood sera from Sz patients, the overall thermal profile being changed in all Sz cases under study. The calorimetric profiles were classified in four distinct groups, reflecting different thermal stabilization of the high-abundance portion of the serum proteome. The observed positive (thermograms becoming closer to the healthy profile) or negative (thermograms deviating stronger from the healthy profile) proteome thermal stability switches and the Sz thermograms persistence in patients’ follow-up corresponded well with the effect of drug treatment.

  14. Calorimetric monitoring of the serum proteome in schizophrenia patients

    International Nuclear Information System (INIS)

    Krumova, Sashka; Rukova, Blaga; Todinova, Svetla; Gartcheva, Lidia; Milanova, Vihra; Toncheva, Draga; Taneva, Stefka G.

    2013-01-01

    Highlights: • DSC reveals modified thermal behavior of blood serum from schizophrenic patients. • The high-abundance portion of the serum proteome is thermally stabilized in Sz. • The Sz plasma thermograms are classified in four distinct calorimetric groups. • The effectiveness of drug treatment correlates with the plasma thermodynamic behavior. - Abstract: Schizophrenia (Sz) is a multifactorial mental disorder with high frequency. Due to its chronic and relapsing nature there is a strong need for biomarkers for early psychosis detection and objective evaluation of drug (usually antipsychotics) treatment effect. Here differential scanning calorimetry (DSC) is applied to thermodynamically characterize the blood serum proteome of paranoid schizophrenia patients on routine antipsychotic treatment in comparison to healthy controls. DSC revealed significant modifications in the thermodynamic behavior of blood sera from Sz patients, the overall thermal profile being changed in all Sz cases under study. The calorimetric profiles were classified in four distinct groups, reflecting different thermal stabilization of the high-abundance portion of the serum proteome. The observed positive (thermograms becoming closer to the healthy profile) or negative (thermograms deviating stronger from the healthy profile) proteome thermal stability switches and the Sz thermograms persistence in patients’ follow-up corresponded well with the effect of drug treatment

  15. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  16. [Proteomics and transfusion medicine].

    Science.gov (United States)

    Lion, N; Prudent, M; Crettaz, D; Tissot, J-D

    2011-04-01

    The term "proteomics" covers tools and techniques that are used to analyze and characterize complex mixtures of proteins from various biological samples. In this short review, a typical proteomic approach, related to the study of particular and illustrative situation related to transfusion medicine is reported. This "case report" will allow the reader to be familiar with a practical proteomic approach of a real situation, and will permit to describe the tools that are usually used in proteomic labs, and, in a second part, to present various proteomic applications in transfusion medicine. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

  17. Towards an animal model of ovarian cancer: cataloging chicken blood proteins using combinatorial peptide ligand libraries coupled with shotgun proteomic analysis for translational research.

    Science.gov (United States)

    Ma, Yingying; Sun, Zeyu; de Matos, Ricardo; Zhang, Jing; Odunsi, Kunle; Lin, Biaoyang

    2014-05-01

    Epithelial ovarian cancer is the most deadly gynecological cancer around the world, with high morbidity in industrialized countries. Early diagnosis is key in reducing its morbidity rate. Yet, robust biomarkers, diagnostics, and animal models are still limited for ovarian cancer. This calls for broader omics and systems science oriented diagnostics strategies. In this vein, the domestic chicken has been used as an ovarian cancer animal model, owing to its high rate of developing spontaneous epithelial ovarian tumors. Chicken blood has thus been considered a surrogate reservoir from which cancer biomarkers can be identified. However, the presence of highly abundant proteins in chicken blood has compromised the applicability of proteomics tools to study chicken blood owing to a lack of immunodepletion methods. Here, we demonstrate that a combinatorial peptide ligand library (CPLL) can efficiently remove highly abundant proteins from chicken blood samples, consequently doubling the number of identified proteins. Using an integrated CPLL-1DGE-LC-MSMS workflow, we identified a catalog of 264 unique proteins. Functional analyses further suggested that most proteins were coagulation and complement factors, blood transport and binding proteins, immune- and defense-related proteins, proteases, protease inhibitors, cellular enzymes, or cell structure and adhesion proteins. Semiquantitative spectral counting analysis identified 10 potential biomarkers from the present chicken ovarian cancer model. Additionally, many human homologs of chicken blood proteins we have identified have been independently suggested as diagnostic biomarkers for ovarian cancer, further triangulating our novel observations reported here. In conclusion, the CPLL-assisted proteomic workflow using the chicken ovarian cancer model provides a feasible platform for translational research to identify ovarian cancer biomarkers and understand ovarian cancer biology. To the best of our knowledge, we report here

  18. Effects of tetracycline administration on the proteomic profile of pig muscle samples (L. dorsi)

    DEFF Research Database (Denmark)

    Gratacos-Cubarsi, M.; Castellari, M.; Hortos, M.

    2008-01-01

    Effect of tetracycline (TC) administration on the proteomic profile of pig muscle was evaluated by 2D electrophoresis and MALDI-TOF mass spectrometry. The TC content at slaughter was determined in L. dorsi samples by HPLC-DAD. Mean residual concentration of TC in the muscle of treated animals, ca...

  19. MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.; Metz, Thomas O.; Chia, Nicholas

    2016-05-03

    ABSTRACT

    Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. Themetabolite,protein, andlipidextraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental,in vitro, and clinical).

    IMPORTANCEIn systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated

  20. MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes

    DEFF Research Database (Denmark)

    Zhang, Yanling; Zhang, Yong; Adachi, Jun

    2007-01-01

    and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http......://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic...... annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools....

  1. Mass spectral analysis of urine proteomic profiles of dairy cows suffering from clinical ketosis.

    Science.gov (United States)

    Xu, Chuang; Shu, Shi; Xia, Cheng; Wang, Pengxian; Sun, Yuhang; Xu, Chuchu; Li, Changsheng

    2015-01-01

    Ketosis is an important metabolic disorder in dairy cows during the transition period. The urine proteomics of ketosis has not been investigated using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The aim is to determine differences between urine proteomic profiles of healthy cows and those with clinical ketosis, and facilitate studies of the underlying physiological and biochemical mechanisms that lead to liver pathology in ketosis. We analyzed the urine samples of 20 cows with clinical ketosis (group 1) and 20 control cows (group 2) using SELDI-TOF-MS. Thirty-nine peptide peaks differed between both groups. Polypeptides corresponding to 26 of these differential peptide peaks were identified using the SWISS-PROT protein database. We found that the peaks of 11 distinct polypeptides from the urine samples of the ketosis group were significantly reduced, compared with those of the control group as based on the Wilcoxon rank sum test. Among these were VGF (non-acronymic) protein, amyloid precursor protein, serum amyloid A (SAA), fibrinogen, C1INH, apolipoprotein C-III, cystatin C, transthyretin, hepcidin, human neutrophil peptides, and osteopontin. These proteins may represent novel biomarkers of the metabolic changes that occur in dairy cows with ketosis. Our results will help to better understand the physiological changes and pathogenesis observed in cows with ketosis. The SELDI-TOF-MS can be used to understand the physiological and biochemical mechanisms of ketosis and identify biomarkers of the disease.

  2. Liver Proteome in Diabetes Type 1 Rat Model: Insulin-Dependent and -Independent Changes.

    Science.gov (United States)

    Braga, Camila Pereira; Boone, Cory H T; Grove, Ryan A; Adamcova, Dana; Fernandes, Ana Angélica Henrique; Adamec, Jiri; de Magalhães Padilha, Pedro

    2016-12-01

    Diabetes mellitus type 1 (DM1) is a major public health problem that continues to burden the healthcare systems worldwide, costing exponentially more as the epidemic grows. Innovative strategies and omics system diagnostics for earlier diagnosis or prognostication of DM1 are essential to prevent secondary complications and alleviate the associated economic burden. In a preclinical study design that involved streptozotocin (STZ)-induced DM1, insulin-treated STZ-induced DM1, and control rats, we characterized the insulin-dependent and -independent changes in protein profiles in liver samples. Digested proteins were subjected to LC-MS E for proteomic data. Progenesis QI data processing and analysis of variance were utilized for statistical analyses. We found 305 proteins with significantly altered abundance among the control, DM1, and insulin-treated DM1 groups (p < 0.05). These differentially regulated proteins were related to enzymes that function in key metabolic pathways and stress responses. For example, gluconeogenesis appeared to return to control levels in the DM1 group after insulin treatment, with the restoration of gluconeogenesis regulatory enzyme, FBP1. Insulin administration to DM1 rats also restored the blood glucose levels and enzymes of general stress and antioxidant response systems. These observations are crucial for insights on DM1 pathophysiology and new molecular targets for future clinical biomarkers, drug discovery, and development. Additionally, we underscore that proteomics offers much potential in preclinical biomarker discovery for diabetes as well as common complex diseases such as cancer, dementia, and infectious disorders.

  3. Metabolomic and proteomic biomarkers for III-V semiconductors: Chemical-specific porphyrinurias and proteinurias

    International Nuclear Information System (INIS)

    Fowler, Bruce A.; Conner, Elizabeth A.; Yamauchi, Hiroshi

    2005-01-01

    . Western blot analyses of the urines with antibodies to the 32-, 70-, and 90-kDa stress protein families did not show the presence of these molecules, indicating that these proteins were not excreted in the urine samples. These data suggest that the observed proteinuria patterns were not a result of cell death and that the observed chemical-specific proteinurias were produced before marked cellular toxicity. These findings suggest a hypothesis involving GaAs and InAs interference with stress protein chaperoning of reabsorbed proteins for proteosomic degradation and the probable chaperoning of damaged intracellular proteins from renal proximal tubule cells into the urinary filtrate. Overall, the results of these studies provide further information on the nephrotoxicity of these semiconductor compounds. They also suggest the use of two-dimensional gel electrophoresis with silver staining of urinary protein patterns as a potentially useful proteomic approach to renal damage early in relation to intracellular proteotoxicity in kidney tubule cells

  4. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  5. Maternal serum proteome changes between the first and third trimester of pregnancy in rural southern Nepal.

    Science.gov (United States)

    Scholl, P F; Cole, R N; Ruczinski, I; Gucek, M; Diez, R; Rennie, A; Nathasingh, C; Schulze, K; Christian, P; Yager, J D; Groopman, J D; West, K P

    2012-05-01

    Characterization of normal changes in the serum proteome during pregnancy may enhance understanding of maternal physiology and lead to the development of new gestational biomarkers. In 23 Nepalese pregnant women who delivered at term, two-dimensional difference in-gel electrophoresis (DIGE) was used to assess changes in relative protein abundance between paired serum samples collected in the first and third trimesters. One-hundred and forty-five of over 700 protein spots in DIGE gels (pI 4.2-6.8) exhibited nominally significant (p < 0.05) differences in abundance across trimesters. Additional filtering using a Bonferroni correction reduced the number of significant (p < 0.00019) spots to 61. Mass spectrometric analysis detected 38 proteins associated with gestational age, cytoskeletal remodeling, blood pressure regulation, lipid and nutrient transport, and inflammation. One new protein, pregnancy-specific β-glycoprotein 4 was detected. A follow-up isotope tagging for relative and absolute quantitation (iTRAQ) experiment of six mothers from the DIGE study revealed 111 proteins, of which 11 exhibited significant (p < 0.05) differences between trimesters. Four of these proteins: gelsolin, complement C1r subcomponent, α-1-acid glycoprotein, and α-1B-glycoprotein also changed in the DIGE analysis. Although not previously associated with normal pregnancy, gelsolin decreased in abundance by the third trimester (p < 0.01) in DIGE, iTRAQ and Western analyses. Changes in abundance of proteins in serum that are associated with syncytiotrophoblasts (gelsolin, pregnancy-specific β-1 glycoprotein 1 and β-2-glycoprotein I) probably reflect dynamics of a placental proteome shed into maternal circulation during pregnancy. Measurement of changes in the maternal serum proteome, when linked with birth outcomes, may yield biomarkers for tracking reproductive health in resource poor settings in future studies. Published by Elsevier Ltd.

  6. Investigation of Pokemon-regulated proteins in hepatocellular carcinoma using mass spectrometry-based multiplex quantitative proteomics.

    Science.gov (United States)

    Bi, Xin; Jin, Yibao; Gao, Xiang; Liu, Feng; Gao, Dan; Jiang, Yuyang; Liu, Hongxia

    2013-01-01

    Pokemon is a transcription regulator involved in embryonic development, cellular differentiation and oncogenesis. It is aberrantly overexpressed in multiple human cancers including Hepatocellular carcinoma (HCC) and is considered as a promising biomarker for HCC. In this work, the isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy was used to investigate the proteomic profile associated with Pokemon in human HCC cell line QGY7703 and human hepatocyte line HL7702. Samples were labeled with four-plex iTRAQ reagents followed by two-dimensional liquid chromatography coupled with tandem mass spectrometry analysis. A total of 24 differentially expressed proteins were selected as significant. Nine proteins were potentially up-regulated by Pokemon while 15 proteins were potentially down-regulated and many proteins were previously identified as potential biomarkers for HCC. Gene ontology (GO) term enrichment revealed that the listed proteins were mainly involved in DNA metabolism and biosynthesis process. The changes of glucose-6-phosphate 1-dehydrogenase (G6PD, up-regulated) and ribonucleoside-diphosphate reductase large sub-unit (RIM1, down-regulated) were validated by Western blotting analysis and denoted as Pokemon's function of oncogenesis. We also found that Pokemon potentially repressed the expression of highly clustered proteins (MCM3, MCM5, MCM6, MCM7) which played key roles in promoting DNA replication. Altogether, our results may help better understand the role of Pokemon in HCC and promote the clinical applications.

  7. Multiplex array proteomics detects increased MMP-8 in CSF after spinal cord injury

    Directory of Open Access Journals (Sweden)

    Light Matthew

    2012-06-01

    Full Text Available Abstract Introduction A variety of methods have been used to study inflammatory changes in the acutely injured spinal cord. Recently novel multiplex assays have been used in an attempt to overcome limitations in numbers of available targets studied in a single experiment. Other technical challenges in developing pre-clinical rodent models to investigate biomarkers in cerebrospinal fluid (CSF include relatively small volumes of sample and low concentrations of target proteins. The primary objective of this study was to characterize the inflammatory profile present in CSF at a subacute time point in a clinically relevant rodent model of traumatic spinal cord injury (SCI. Our other aim was to test a microarray proteomics platform specifically for this application. Methods A 34 cytokine sandwich ELISA microarray was used to study inflammatory changes in CSF samples taken 12 days post-cervical SCI in adult rats. The difference between the median foreground signal and the median background signal was measured. Bonferroni and Benjamini-Hochburg multiple testing corrections were applied to limit the False Discovery Rate (FDR, and a linear mixed model was used to account for repeated measures in the array. Results We report a novel subacute SCI biomarker, elevated levels of matrix metalloproteinase-8 protein in CSF, and discuss application of statistical models designed for multiplex testing. Conclusions Major advantages of this assay over conventional methods include high-throughput format, good sensitivity, and reduced sample consumption. This method can be useful for creating comprehensive inflammatory profiles, and biomarkers can be used in the clinic to assess injury severity and to objectively grade response to therapy.

  8. Intraluminal proteome and peptidome of human urinary extracellular vesicles.

    Science.gov (United States)

    Liu, Xinyu; Chinello, Clizia; Musante, Luca; Cazzaniga, Marta; Tataruch, Dorota; Calzaferri, Giulio; James Smith, Andrew; De Sio, Gabriele; Magni, Fulvio; Zou, Hequn; Holthofer, Harry

    2015-06-01

    Urinary extracellular vesicles (UEVs) are a novel source for disease biomarker discovery. However, Tamm-Horsfall protein (THP) is still a challenge for proteomic analysis since it can inhibit detection of low-abundance proteins. Here, we introduce a new approach that does not involve an ultracentrifugation step to enrich vesicles and that reduces the amount of THP to manageable levels. UEVs were dialyzed and ultrafiltered after reduction and alkylation. The retained fraction was digested with trypsin to reduce the remaining THP and incubated with deoxycholate (DOC). The internal peptidome and internal proteome were analyzed by LC-ESI-MS. A total of 942 different proteins and 3115 unique endogenous peptide fragments deriving from 973 different protein isoforms were identified. Around 82% of the key endosomal sorting complex required for transport components of UEVs generation could be detected from the intraluminal content. Our UEVs preparation protocol provides a simplified way to investigate the intraluminal proteome and peptidome, in particular the subpopulation of UEVs of the trypsin-resistant class of exosomes (positive for tumor susceptibility gene101) and eliminates the majority of interfering proteins such as THP. This method allows the possibility to study endoproteome and endopeptidome of UEVs, thus greatly facilitating biomarker discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Integrated Detection of Pathogens and Host Biomarkers for Wounds

    Energy Technology Data Exchange (ETDEWEB)

    Jaing, C

    2012-03-19

    The increasing incidence and complications arising from combat wounds has necessitated a reassessment of methods for effective treatment. Infection, excessive inflammation, and incidence of drug-resistant organisms all contribute toward negative outcomes for afflicted individuals. The organisms and host processes involved in wound progression, however, are incompletely understood. We therefore set out, using our unique technical resources, to construct a profile of combat wounds which did or did not successfully resolve. We employed the Lawrence Livermore Microbial Detection Array and identified a number of nosocomial pathogens present in wound samples. Some of these identities corresponded with bacterial isolates previously cultured, while others were not obtained via standard microbiology. Further, we optimized proteomics protocols for the identification of host biomarkers indicative of various stages in wound progression. In combination with our pathogen data, our biomarker discovery efforts will provide a profile corresponding to wound complications, and will assist significantly in treatment of these complex cases.

  10. A DATABASE FOR TRACKING TOXICOGENOMIC SAMPLES AND PROCEDURES WITH GENOMIC, PROTEOMIC AND METABONOMIC COMPONENTS

    Science.gov (United States)

    A Database for Tracking Toxicogenomic Samples and Procedures with Genomic, Proteomic and Metabonomic Components Wenjun Bao1, Jennifer Fostel2, Michael D. Waters2, B. Alex Merrick2, Drew Ekman3, Mitchell Kostich4, Judith Schmid1, David Dix1Office of Research and Developmen...

  11. Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment.

    Science.gov (United States)

    Welker, F

    2018-02-20

    The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized

  12. C-STrap Sample Preparation Method--In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format.

    Directory of Open Access Journals (Sweden)

    Alexandre Zougman

    Full Text Available Recently we introduced the concept of Suspension Trapping (STrap for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method's use in qualitative and semi-quantitative proteomics experiments.

  13. C-STrap Sample Preparation Method--In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format.

    Science.gov (United States)

    Zougman, Alexandre; Banks, Rosamonde E

    2015-01-01

    Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method's use in qualitative and semi-quantitative proteomics experiments.

  14. Potential Peripheral Biomarkers for the Diagnosis of Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Seema Patel

    2011-01-01

    Full Text Available Advances in the discovery of a peripheral biomarker for the diagnosis of Alzheimer's would provide a way to better detect the onset of this debilitating disease in a manner that is both noninvasive and universally available. This paper examines the current approaches that are being used to discover potential biomarker candidates available in the periphery. The search for a peripheral biomarker that could be utilized diagnostically has resulted in an extensive amount of studies that employ several biological approaches, including the assessment of tissues, genomics, proteomics, epigenetics, and metabolomics. Although a definitive biomarker has yet to be confirmed, advances in the understanding of the mechanisms of the disease and major susceptibility factors have been uncovered and reveal promising possibilities for the future discovery of a useful biomarker.

  15. Proteomic Analysis of Early Mid-Trimester Amniotic Fluid Does Not Predict Spontaneous Preterm Delivery

    Science.gov (United States)

    Lenco, Juraj; Vajrychova, Marie; Link, Marek; Tambor, Vojtech; Liman, Victor; Bullarbo, Maria; Nilsson, Staffan; Tsiartas, Panagiotis; Cobo, Teresa; Kacerovsky, Marian; Jacobsson, Bo

    2016-01-01

    Objective The aim of this study was to identify early proteomic biomarkers of spontaneous preterm delivery (PTD) in mid-trimester amniotic fluid from asymptomatic women. Methods This is a case-cohort study. Amniotic fluid from mid-trimester genetic amniocentesis (14–19 weeks of gestation) was collected from 2008 to 2011. The analysis was conducted in 24 healthy women with subsequent spontaneous PTD (cases) and 40 randomly selected healthy women delivering at term (controls). An exploratory phase with proteomics analysis of pooled samples was followed by a verification phase with ELISA of individual case and control samples. Results The median (interquartile range (IQR: 25th; 75th percentiles) gestational age at delivery was 35+5 (33+6–36+6) weeks in women with spontaneous PTD and 40+0 (39+1–40+5) weeks in women who delivered at term. In the exploratory phase, the most pronounced differences were found in C-reactive protein (CRP) levels, that were approximately two-fold higher in the pooled case samples than in the pooled control samples. However, we could not verify these differences with ELISA. The median (25th; 75th IQR) CRP level was 95.2 ng/mL (64.3; 163.5) in women with spontaneous PTD and 86.0 ng/mL (51.2; 145.8) in women delivering at term (p = 0.37; t-test). Conclusions Proteomic analysis with mass spectrometry of mid-trimester amniotic fluid suggests CRP as a potential marker of spontaneous preterm delivery, but this prognostic potential was not verified with ELISA. PMID:27214132

  16. Data for a comprehensive map and functional annotation of the human cerebrospinal fluid proteome

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2015-06-01

    Full Text Available Knowledge about the normal human cerebrospinal fluid (CSF proteome serves as a baseline reference for CSF biomarker discovery and provides insight into CSF physiology. In this study, high-pH reverse-phase liquid chromatography (hp-RPLC was first integrated with a TripleTOF 5600 mass spectrometer to comprehensively profile the normal CSF proteome. A total of 49,836 unique peptides and 3256 non-redundant proteins were identified. To obtain high-confidence results, 2513 proteins with at least 2 unique peptides were further selected as bona fide CSF proteins. Nearly 30% of the identified CSF proteins have not been previously reported in the normal CSF proteome. More than 25% of the CSF proteins were components of CNS cell microenvironments, and network analyses indicated their roles in the pathogenesis of neurological diseases. The top canonical pathway in which the CSF proteins participated was axon guidance signaling. More than one-third of the CSF proteins (788 proteins were related to neurological diseases, and these proteins constitute potential CSF biomarker candidates. The mapping results can be freely downloaded at http://122.70.220.102:8088/csf/, which can be used to navigate the CSF proteome. For more information about the data, please refer to the related original article [1], which has been recently accepted by Journal of Proteomics.

  17. Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications.

    Science.gov (United States)

    Sajic, Tatjana; Liu, Yansheng; Aebersold, Ruedi

    2015-04-01

    In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. The Proteome of Ulcerative Colitis in Colon Biopsies from Adults - Optimized Sample Preparation and Comparison with Healthy Controls.

    Science.gov (United States)

    Schniers, Armin; Anderssen, Endre; Fenton, Christopher Graham; Goll, Rasmus; Pasing, Yvonne; Paulssen, Ruth Hracky; Florholmen, Jon; Hansen, Terkel

    2017-12-01

    The purpose of the study was to optimize the sample preparation and to further use an improved sample preparation to identify proteome differences between inflamed ulcerative colitis tissue from untreated adults and healthy controls. To optimize the sample preparation, we studied the effect of adding different detergents to a urea containing lysis buffer for a Lys-C/trypsin tandem digestion. With the optimized method, we prepared clinical samples from six ulcerative colitis patients and six healthy controls and analysed them by LC-MS/MS. We examined the acquired data to identify differences between the states. We improved the protein extraction and protein identification number by utilizing a urea and sodium deoxycholate containing buffer. Comparing ulcerative colitis and healthy tissue, we found 168 of 2366 identified proteins differently abundant. Inflammatory proteins are higher abundant in ulcerative colitis, proteins related to anion-transport and mucus production are lower abundant. A high proportion of S100 proteins is differently abundant, notably with both up-regulated and down-regulated proteins. The optimized sample preparation method will improve future proteomic studies on colon mucosa. The observed protein abundance changes and their enrichment in various groups improve our understanding of ulcerative colitis on protein level. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Molecular biomarkers to guide precision medicine in localized prostate cancer.

    Science.gov (United States)

    Smits, Minke; Mehra, Niven; Sedelaar, Michiel; Gerritsen, Winald; Schalken, Jack A

    2017-08-01

    Major advances through tumor profiling technologies, that include next-generation sequencing, epigenetic, proteomic and transcriptomic methods, have been made in primary prostate cancer, providing novel biomarkers that may guide precision medicine in the near future. Areas covered: The authors provided an overview of novel molecular biomarkers in tissue, blood and urine that may be used as clinical tools to assess prognosis, improve selection criteria for active surveillance programs, and detect disease relapse early in localized prostate cancer. Expert commentary: Active surveillance (AS) in localized prostate cancer is an accepted strategy in patients with very low-risk prostate cancer. Many more patients may benefit from watchful waiting, and include patients of higher clinical stage and grade, however selection criteria have to be optimized and early recognition of transformation from localized to lethal disease has to be improved by addition of molecular biomarkers. The role of non-invasive biomarkers is challenging the need for repeat biopsies, commonly performed at 1 and 4 years in men under AS programs.

  20. Profilin-1 overexpression in MDA-MB-231 breast cancer cells is associated with alterations in proteomics biomarkers of cell proliferation, survival, and motility as revealed by global proteomics analyses.

    Science.gov (United States)

    Coumans, Joëlle V F; Gau, David; Poljak, Anne; Wasinger, Valerie; Roy, Partha; Moens, Pierre D J

    2014-12-01

    Despite early screening programs and new therapeutic strategies, metastatic breast cancer is still the leading cause of cancer death in women in industrialized countries and regions. There is a need for novel biomarkers of susceptibility, progression, and therapeutic response. Global analyses or systems science approaches with omics technologies offer concrete ways forward in biomarker discovery for breast cancer. Previous studies have shown that expression of profilin-1 (PFN1), a ubiquitously expressed actin-binding protein, is downregulated in invasive and metastatic breast cancer. It has also been reported that PFN1 overexpression can suppress tumorigenic ability and motility/invasiveness of breast cancer cells. To obtain insights into the underlying molecular mechanisms of how elevating PFN1 level induces these phenotypic changes in breast cancer cells, we investigated the alteration in global protein expression profiles of breast cancer cells upon stable overexpression of PFN1 by a combination of three different proteome analysis methods (2-DE, iTRAQ, label-free). Using MDA-MB-231 as a model breast cancer cell line, we provide evidence that PFN1 overexpression is associated with alterations in the expression of proteins that have been functionally linked to cell proliferation (FKPB1A, HDGF, MIF, PRDX1, TXNRD1, LGALS1, STMN1, LASP1, S100A11, S100A6), survival (HSPE1, HSPB1, HSPD1, HSPA5 and PPIA, YWHAZ, CFL1, NME1) and motility (CFL1, CORO1B, PFN2, PLS3, FLNA, FLNB, NME2, ARHGDIB). In view of the pleotropic effects of PFN1 overexpression in breast cancer cells as suggested by these new findings, we propose that PFN1-induced phenotypic changes in cancer cells involve multiple mechanisms. Our data reported here might also offer innovative strategies for identification and validation of novel therapeutic targets and companion diagnostics for persons with, or susceptibility to, breast cancer.

  1. Miniaturizing EM Sample Preparation: Opportunities, Challenges, and "Visual Proteomics".

    Science.gov (United States)

    Arnold, Stefan A; Müller, Shirley A; Schmidli, Claudio; Syntychaki, Anastasia; Rima, Luca; Chami, Mohamed; Stahlberg, Henning; Goldie, Kenneth N; Braun, Thomas

    2018-03-01

    This review compares and discusses conventional versus miniaturized specimen preparation methods for transmission electron microscopy (TEM). The progress brought by direct electron detector cameras, software developments and automation have transformed transmission cryo-electron microscopy (cryo-EM) and made it an invaluable high-resolution structural analysis tool. In contrast, EM specimen preparation has seen very little progress in the last decades and is now one of the main bottlenecks in cryo-EM. Here, we discuss the challenges faced by specimen preparation for single particle EM, highlight current developments, and show the opportunities resulting from the advanced miniaturized and microfluidic sample grid preparation methods described, such as visual proteomics and time-resolved cryo-EM studies. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Database-augmented Mass Spectrometry Analysis of Exosomes Identifies Claudin 3 as a Putative Prostate Cancer Biomarker.

    Science.gov (United States)

    Worst, Thomas Stefan; von Hardenberg, Jost; Gross, Julia Christina; Erben, Philipp; Schnölzer, Martina; Hausser, Ingrid; Bugert, Peter; Michel, Maurice Stephan; Boutros, Michael

    2017-06-01

    In prostate cancer and other malignancies sensitive and robust biomarkers are lacking or have relevant limitations. Prostate specific antigen (PSA), the only biomarker widely used in prostate cancer, is suffering from low specificity. Exosomes offer new perspectives in the discovery of blood-based biomarkers. Here we present a proof-of principle study for a proteomics-based identification pipeline, implementing existing data sources, to exemplarily identify exosome-based biomarker candidates in prostate cancer.Exosomes from malignant PC3 and benign PNT1A cells and from FBS-containing medium were isolated using sequential ultracentrifugation. Exosome and control samples were analyzed on an LTQ-Orbitrap XL mass spectrometer. Proteomic data is available via ProteomeXchange with identifier PXD003651. We developed a scoring scheme to rank 64 proteins exclusively found in PC3 exosomes, integrating data from four public databases and published mass spectrometry data sets. Among the top candidates, we focused on the tight junction protein claudin 3. Retests under serum-free conditions using immunoblotting and immunogold labeling confirmed the presence of claudin 3 on PC3 exosomes. Claudin 3 levels were determined in the blood plasma of patients with localized ( n = 58; 42 with Gleason score 6-7, 16 with Gleason score ≥8) and metastatic prostate cancer ( n = 11) compared with patients with benign prostatic hyperplasia ( n = 15) and healthy individuals ( n = 15) using ELISA, without prior laborious exosome isolation. ANOVA showed different CLDN3 plasma levels in these groups ( p = 0.004). CLDN3 levels were higher in patients with Gleason ≥8 tumors compared with patients with benign prostatic hyperplasia ( p = 0.012) and Gleason 6-7 tumors ( p = 0.029). In patients with localized tumors CLDN3 levels predicted a Gleason score ≥ 8 (AUC = 0.705; p = 0.016) and did not correlate with serum PSA.By using the described workflow claudin 3 was identified and validated as a

  3. SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

    Science.gov (United States)

    Petricoin, Emanuel F; Liotta, Lance A

    2004-02-01

    Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

  4. Method and platform standardization in MRM-based quantitative plasma proteomics.

    Science.gov (United States)

    Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

    2013-12-16

    There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This

  5. Ultrasonic-based membrane aided sample preparation of urine proteomes.

    Science.gov (United States)

    Jesus, Jemmyson Romário; Santos, Hugo M; López-Fernández, H; Lodeiro, Carlos; Arruda, Marco Aurélio Zezzi; Capelo, J L

    2018-02-01

    A new ultrafast ultrasonic-based method for shotgun proteomics as well as label-free protein quantification in urine samples is developed. The method first separates the urine proteins using nitrocellulose-based membranes and then proteins are in-membrane digested using trypsin. The enzymatic digestion process is accelerated from overnight to four minutes using a sonoreactor ultrasonic device. Overall, the sample treatment pipeline comprising protein separation, digestion and identification is done in just 3h. The process is assessed using urine of healthy volunteers. The method shows that male can be differentiated from female using the protein content of urine in a fast, easy and straightforward way. 232 and 226 proteins are identified in urine of male and female, respectively. From this, 162 are common to both genders, whilst 70 are unique to male and 64 to female. From the 162 common proteins, 13 are present at levels statistically different (p minimalism concept as outlined by Halls, as each stage of this analysis is evaluated to minimize the time, cost, sample requirement, reagent consumption, energy requirements and production of waste products. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Modern Biotechnology of Phellinus baumii – From Fermentation to Proteomics

    Directory of Open Access Journals (Sweden)

    Hye Jin Hwang

    2007-01-01

    Full Text Available Phellinus baumii is a mushroom used as a folk medicine for a variety of human diseases in several Asian countries. Recently we have reported for the first time about the antidiabetic effect of the crude exopolysaccharides (EPS produced from submerged mycelial culture of P. baumii in streptozotocin (STZ-induced diabetic rats. The diabetic rats study revealed that orally administrated P. baumii EPS lowered the blood glucose levels and stimulated insulin excretion in diabetic rats, and consequently restored the functions of pancreas, liver, and kidney, suggesting that the EPS might be useful for the management of human diabetes mellitus. We undertook proteomic analyses for plasma, pancreas, liver, and kidney of the rats to search for novel biomarkers for monitoring diabetes before and after EPS treatments. In this article, we describe the production of EPS in submerged culture of P. baumii and studies of their hypoglycemic activity. We also explore the issue of proteomic analyses for mining biomarkers of diabetes.

  7. Profiling the Aspergillus fumigatus Proteome in Response to Caspofungin ▿ †

    Science.gov (United States)

    Cagas, Steven E.; Jain, Mohit Raja; Li, Hong; Perlin, David S.

    2011-01-01

    The proteomic response of Aspergillus fumigatus to caspofungin was evaluated by gel-free isobaric tagging for relative and absolute quantitation (iTRAQ) as a means to determine potential biomarkers of drug action. A cell fractionation approach yielding 4 subcellular compartment fractions was used to enhance the resolution of proteins for proteomic analysis. Using iTRAQ, a total of 471 unique proteins were identified in soluble and cell wall/plasma membrane fractions at 24 and 48 h of growth in rich media in a wild-type drug-susceptible strain. A total of 122 proteins showed at least a 2-fold change in relative abundance following exposure to caspofungin (CSF) at just below the minimum effective concentration (0.12 μg/ml). The largest changes were seen in the mitochondrial hypoxia response domain protein (AFUA_1G12250), the level of which decreased >16-fold in the secreted fraction, and ChiA1, the level of which decreased 12.1-fold in the cell wall/plasma membrane fraction. The level of the major allergen and cytotoxin AspF1 was also shown to decrease by 12.1-fold upon the addition of drug. A subsequent iTRAQ analysis of an echinocandin-resistant strain (fks1-S678P) was used to validate proteins specific to drug action. A total of 103 proteins in the 2 fractions tested by iTRAQ were differentially expressed in the wild-type susceptible strain but not significantly changed in the resistant strain. Of these potential biomarkers, 11 had levels that changed at least 12-fold. Microarray analysis of the susceptible strain was performed to evaluate the correlation between proteomics and genomics, with a total of 117 genes found to be changing at least 2-fold. Of these, a total of 22 proteins with significant changes identified by iTRAQ also showed significant gene expression level changes by microarray. Overall, these data have the potential to identify biomarkers that assess the relative efficacy of echinocandin drug therapy. PMID:20974863

  8. Three new potential ovarian cancer biomarkers detected in human urine with equalizer bead technology

    DEFF Research Database (Denmark)

    Petri, Anette Lykke; Simonsen, Anja Hviid; Yip, Tai-Tung

    2008-01-01

    samples were aliquotted and frozen at -80 degrees until the time of analysis. The urine was fractionated using equalizer bead technology and then analyzed with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Biomarkers were purified and identified using combinations...... of chromatographic techniques and tandem mass spectrometry. RESULTS: Benign and malignant ovarian cancer cases were compared; 21 significantly different peaks (p...OBJECTIVE: To examine whether urine can be used to measure specific ovarian cancer proteomic profiles and whether one peak alone or in combination with other peaks or CA125 has the sensitivity and specificity to discriminate between ovarian cancer pelvic mass and benign pelvic mass. METHODS...

  9. Proteomic profile of serum of pregnant women carring a fetus with Down syndrome using nano uplc Q-tof ms/ms technology.

    Science.gov (United States)

    López Uriarte, Graciela Arelí; Burciaga Flores, Carlos Horacio; Torres de la Cruz, Víctor Manuel; Medina Aguado, María Magdalena; Gómez Puente, Viviana Maricela; Romero Gutiérrez, Liliana Nayeli; Martínez de Villarreal, Laura Elia

    2018-06-01

    Prenatal diagnosis of Down syndrome (DS) is based on the calculated risk of maternal age, biochemical and ultrasonographic markers and recently by cfDNA. Differences in proteomic profiles may give an opportunity to find new biomarkers. Characterize proteome of serum of mothers carrying DS fetus. Blood serum samples of three groups of women were obtained, (a) 10 non-pregnant, (b) 10 pregnant with healthy fetus by ultrasound evaluation, (c) nine pregnant with DS fetus. Sample preparation was as follows: Albumin/IgG depletion, desalting, and trypsin digestion; the process was performed in nanoUPLC MS/MS. Data analysis was made with Mass Lynx 4.1 and ProteinLynx Global Server 3.0, peptide and protein recognition by MASCOT algorithm and UNIPROT-Swissprot database. Each group showed different protein profiles. Some proteins were shared between groups. Only sera from pregnant women showed proteins related to immune and clot pathways. Mothers with DS fetus had 42 specific proteins. We found a different serum protein profile in mothers carrying DS fetuses that do not reflect expression of genes in the extra chromosome. Further studies will be necessary to establish the role of these proteins in aneuploid fetus and analyze their possible use as potential biomarkers.

  10. MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

    Science.gov (United States)

    Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias

    2007-01-01

    Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

  11. Application of serum SELDI proteomic patterns in diagnosis of lung cancer

    International Nuclear Information System (INIS)

    Yang, Shuan-ying; Xiao, Xue-yuan; Zhang, Wang-gang; Zhang, Li-juan; Zhang, Wei; Zhou, Bin; Chen, Guoan; He, Da-cheng

    2005-01-01

    Currently, no satisfactory biomarkers are available to screen for lung cancer. Surface-Enhanced Laser Desorption/ionization Time-of- Flight Mass Spectrometry ProteinChip system (SELDI-TOF-MS) is one of the currently used techniques to identify biomarkers for cancers. The aim of this study is to explore the application of serum SELDI proteomic patterns to distinguish lung cancer patients from healthy individuals. A total of 208 serum samples, including 158 lung cancer patients and 50 healthy individuals, were randomly divided into a training set (including 11 sera from patients with stages I/II lung cancer, 63 from patients with stages III/IV lung cancer and 20 from healthy controls) and a blinded test set (including 43 sera from patients with stages I/II lung cancer, 41 from patients with stages III/IV lung cancer and 30 from healthy controls). All samples were analyzed by SELDI technology. The spectra were generated on weak cation exchange (WCX2) chips, and protein peaks clustering and classification analyses were made using Ciphergen Biomarker Wizard and Biomarker Pattern software, respectively. We additionally determined Cyfra21-1 and NSE in the 208 serum samples included in this study using an electrochemiluminescent immunoassay. Five protein peaks at 11493, 6429, 8245, 5335 and 2538 Da were automatically chosen as a biomarker pattern in the training set. When the SELDI marker pattern was tested with the blinded test set, it yielded a sensitivity of 86.9%, a specificity of 80.0% and a positive predictive value of 92.4%. The sensitivities provided by Cyfra21-1 and NSE used individually or in combination were significantly lower than that of the SELDI marker pattern (P < 0.005 or 0.05, respectively). Based on the results of the test set, we found that the SELDI marker pattern showed a sensitivity of 91.4% in the detection of non-small cell lung cancers (NSCLC), which was significantly higher than that in the detection of small cell lung cancers (P < 0.05); The

  12. A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome.

    Science.gov (United States)

    D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

    2017-06-06

    Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3-10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7-20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

  13. Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

    Science.gov (United States)

    El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

    2017-01-01

    The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

  14. Proteomics of drug resistance in Candida glabrata biofilms.

    Science.gov (United States)

    Seneviratne, C Jayampath; Wang, Yu; Jin, Lijian; Abiko, Y; Samaranayake, Lakshman P

    2010-04-01

    Candida glabrata is a fungal pathogen that causes a variety of mucosal and systemic infections among compromised patient populations with higher mortality rates. Previous studies have shown that biofilm mode of the growth of the fungus is highly resistant to antifungal agents compared with the free-floating or planktonic mode of growth. Therefore, in the present study, we used 2-D DIGE to evaluate the differential proteomic profiles of C. glabrata under planktonic and biofilm modes of growth. Candida glabrata biofilms were developed on polystyrene surfaces and age-matched planktonic cultures were obtained in parallel. Initially, biofilm architecture, viability, and antifungal susceptibility were evaluated. Differentially expressed proteins more than 1.5-fold in DIGE analysis were subjected to MS/MS. The transcriptomic regulation of these biomarkers was evaluated by quantitative real-time PCR. Candida glabrata biofilms were highly resistant to the antifungals and biocides compared with the planktonic mode of growth. Candida glabrata biofilm proteome when compared with its planktonic proteome showed upregulation of stress response proteins, while glycolysis enzymes were downregulated. Similar trend could be observed at transcriptomic level. In conclusion, C. glabrata biofilms possess higher amount of stress response proteins, which may potentially contribute to the higher antifungal resistance seen in C. glabrata biofilms.

  15. Advancement of mass spectrometry-based proteomics technologies to explore triple negative breast cancer.

    Science.gov (United States)

    Miah, Sayem; Banks, Charles A S; Adams, Mark K; Florens, Laurence; Lukong, Kiven E; Washburn, Michael P

    2016-12-20

    Understanding the complexity of cancer biology requires extensive information about the cancer proteome over the course of the disease. The recent advances in mass spectrometry-based proteomics technologies have led to the accumulation of an incredible amount of such proteomic information. This information allows us to identify protein signatures or protein biomarkers, which can be used to improve cancer diagnosis, prognosis and treatment. For example, mass spectrometry-based proteomics has been used in breast cancer research for over two decades to elucidate protein function. Breast cancer is a heterogeneous group of diseases with distinct molecular features that are reflected in tumour characteristics and clinical outcomes. Compared with all other subtypes of breast cancer, triple-negative breast cancer is perhaps the most distinct in nature and heterogeneity. In this review, we provide an introductory overview of the application of advanced proteomic technologies to triple-negative breast cancer research.

  16. Amyloid Biomarkers in Conformational Diseases at Face Value: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Maria Fernanda Avila-Vazquez

    2017-12-01

    Full Text Available Conformational diseases represent a new aspect of proteomic medicine where diagnostic and therapeutic paradigms are evolving. In this context, the early biomarkers for target cell failure (neurons, β-cells, etc. represent a challenge to translational medicine and play a multidimensional role as biomarkers and potential therapeutic targets. This systematic review, which follows the PICO and Prisma methods, analyses this new-fangled multidimensionality, its strengths and limitations, and presents the future possibilities it opens up. The nuclear diagnosis methods are immunoassays: ELISA, immunodot, western blot, etc., while the therapeutic approach is focused on pharmaco- and molecular chaperones.

  17. A Proteomic Approach Identifies Candidate Early Biomarkers to Predict Severe Dengue in Children.

    Directory of Open Access Journals (Sweden)

    Dang My Nhi

    2016-02-01

    Full Text Available Severe dengue with severe plasma leakage (SD-SPL is the most frequent of dengue severe form. Plasma biomarkers for early predictive diagnosis of SD-SPL are required in the primary clinics for the prevention of dengue death.Among 63 confirmed dengue pediatric patients recruited, hospital based longitudinal study detected six SD-SPL and ten dengue with warning sign (DWS. To identify the specific proteins increased or decreased in the SD-SPL plasma obtained 6-48 hours before the shock compared with the DWS, the isobaric tags for relative and absolute quantification (iTRAQ technology was performed using four patients each group. Validation was undertaken in 6 SD-SPL and 10 DWS patients.Nineteen plasma proteins exhibited significantly different relative concentrations (p<0.05, with five over-expressed and fourteen under-expressed in SD-SPL compared with DWS. The individual protein was classified to either blood coagulation, vascular regulation, cellular transport-related processes or immune response. The immunoblot quantification showed angiotensinogen and antithrombin III significantly increased in SD-SPL whole plasma of early stage compared with DWS subjects. Even using this small number of samples, antithrombin III predicted SD-SPL before shock occurrence with accuracy.Proteins identified here may serve as candidate predictive markers to diagnose SD-SPL for timely clinical management. Since the number of subjects are small, so further studies are needed to confirm all these biomarkers.

  18. Toxicogenomic analysis of N-nitrosomorpholine induced changes in rat liver: Comparison of genomic and proteomic responses and anchoring to histopathological parameters

    International Nuclear Information System (INIS)

    Oberemm, A.; Ahr, H.-J.; Bannasch, P.; Ellinger-Ziegelbauer, H.; Glueckmann, M.; Hellmann, J.; Ittrich, C.; Kopp-Schneider, A.; Kramer, P.-J.; Krause, E.; Kroeger, M.; Kiss, E.; Richter-Reichhelm, H.-B.; Scholz, G.; Seemann, K.; Weimer, M.; Gundert-Remy, U.

    2009-01-01

    A common animal model of chemical hepatocarcinogenesis was used to examine the utility of transcriptomic and proteomic data to identify early biomarkers related to chemically induced carcinogenesis. N-nitrosomorpholine, a frequently used genotoxic model carcinogen, was applied via drinking water at 120 mg/L to male Wistar rats for 7 weeks followed by an exposure-free period of 43 weeks. Seven specimens of each treatment group (untreated control and 120 mg/L N-nitrosomorpholine in drinking water) were sacrificed at nine time points during and after N-nitrosomorpholine treatment. Individual samples from the liver were prepared for histological and toxicogenomic analyses. For histological detection of preneoplastic and neoplastic tissue areas, sections were stained using antibodies against the placental form of glutathione-S-transferase (GST-P). Gene and protein expression profiles of liver tissue homogenates were analyzed using RG-U34A Affymetrix rat gene chips and two-dimensional gel electrophoresis-based proteomics, respectively. In order to compare results obtained by histopathology, transcriptomics and proteomics, GST-P-stained liver sections were evaluated morphometrically, which revealed a parallel time course of the area fraction of preneoplastic lesions and gene plus protein expression patterns. On the transcriptional level, an increase of hepatic GST-P expression was detectable as early as 3 weeks after study onset. Comparing deregulated genes and proteins, eight species were identified which showed a corresponding expression profile on both expression levels. Functional analysis suggests that these genes and corresponding proteins may be useful as biomarkers of early hepatocarcinogenesis.

  19. Proteomic characterization of intermediate and advanced glycation end-products in commercial milk samples.

    Science.gov (United States)

    Renzone, Giovanni; Arena, Simona; Scaloni, Andrea

    2015-03-18

    The Maillard reaction consists of a number of chemical processes affecting the structure of the proteins present in foods. We previously accomplished the proteomic characterization of the lactosylation targets in commercial milk samples. Although characterizing the early modification derivatives, this analysis did not describe the corresponding advanced glycation end-products (AGEs), which may be formed from the further oxidation of former ones or by reaction of oxidized sugars with proteins, when high temperatures are exploited. To fill this gap, we have used combined proteomic procedures for the systematic characterization of the lactosylated and AGE-containing proteins from the soluble and milk fat globule membrane fraction of various milk products. Besides to confirm all lactulosyl-lysines described previously, 40 novel lactosylation sites were identified. More importantly, 308 additional intermediate and advanced glyco-oxidation derivatives (including cross-linking adducts) were characterized in 31 proteins, providing the widest qualitative inventory of modified species ascertained in commercial milk samples so far. Amadori adducts with glucose/galactose, their dehydration products, carboxymethyllysine and glyoxal-, 3-deoxyglucosone/3-deoxygalactosone- and 3-deoxylactosone-derived dihydroxyimidazolines and/or hemiaminals were the most frequent derivatives observed. Depending on thermal treatment, a variable number of modification sites was identified within each protein; their number increased with harder food processing conditions. Among the modified proteins, species involved in assisting the delivery of nutrients, defense response against pathogens and cellular proliferation/differentiation were highly affected by AGE formation. This may lead to a progressive decrease of the milk nutritional value, as it reduces the protein functional properties, abates the bioavailability of the essential amino acids and eventually affects food digestibility. These aspects

  20. Identification of prostate cancer biomarkers in urinary exosomes.

    Science.gov (United States)

    Øverbye, Anders; Skotland, Tore; Koehler, Christian J; Thiede, Bernd; Seierstad, Therese; Berge, Viktor; Sandvig, Kirsten; Llorente, Alicia

    2015-10-06

    Exosomes have recently appeared as a novel source of non-invasive cancer biomarkers since tumour-specific molecules can be found in exosomes isolated from biological fluids. We have here investigated the proteome of urinary exosomes by using mass spectrometry to identify proteins differentially expressed in prostate cancer patients compared to healthy male controls. In total, 15 control and 16 prostate cancer samples of urinary exosomes were analyzed. Importantly, 246 proteins were differentially expressed in the two groups. The majority of these proteins (221) were up-regulated in exosomes from prostate cancer patients. These proteins were analyzed according to specific criteria to create a focus list that contained 37 proteins. At 100% specificity, 17 of these proteins displayed individual sensitivities above 60%. Even though several of these proteins showed high sensitivity and specificity for prostate cancer as individual biomarkers, combining them in a multi-panel test has the potential for full differentiation of prostate cancer from non-disease controls. The highest sensitivity, 94%, was observed for transmembrane protein 256 (TM256; chromosome 17 open reading frame 61). LAMTOR proteins were also distinctly enriched with very high specificity for patient samples. TM256 and LAMTOR1 could be used to augment the sensitivity to 100%. Other prominent proteins were V-type proton ATPase 16 kDa proteolipid subunit (VATL), adipogenesis regulatory factor (ADIRF), and several Rab-class members and proteasomal proteins. In conclusion, this study clearly shows the potential of using urinary exosomes in the diagnosis and clinical management of prostate cancer.

  1. MStern Blotting–High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates*

    OpenAIRE

    Berger, Sebastian T.; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

    2015-01-01

    We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used mem...

  2. Targeted proteomics as a tool for porcine acute phase proteins measurements

    DEFF Research Database (Denmark)

    Marco-Ramell, Anna; Bassols, Anna; Bislev, Stine Lønnerup

    2013-01-01

    . Selected reaction monitoring (SRM), a targeted quantitative proteomic technique, may be used as an alternative to commercial kits for the measurement and validation of target proteins. Acute phase proteins (APPs) are widely recognized inflammation and infection biomarkers (Eckersall, 2010...

  3. Secreted proteins as a fundamental source for biomarker discovery

    Czech Academy of Sciences Publication Activity Database

    Šťastná, Miroslava; Van Eyk, J.E.

    2012-01-01

    Roč. 12, 4-5 (2012), s. 722-735 ISSN 1615-9853 Institutional research plan: CEZ:AV0Z40310501 Keywords : conditioned media * secreted proteins * proteomics * biomarker discovery Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 4.132, year: 2012

  4. Proteomics in quality control: Whey protein-based supplements.

    Science.gov (United States)

    Garrido, Bruno Carius; Souza, Gustavo H M F; Lourenço, Daniela C; Fasciotti, Maíra

    2016-09-16

    The growing consumption of nutritional supplements might represent a problem, given the concern about the quality of these supplements. One of the most used supplements is whey protein (WP); because of its popularity, it has been a target of adulteration with substitute products, such as cheaper proteins with lower biological value. To investigate this type of adulteration, this study used shotgun proteomics analyses by MS(E) (multiplexed, low- and high-collision energy, data-independent acquisition) of WP-based supplements. Seventeen WP-based supplement samples were evaluated. Chicken, maize, rice, potato, soybean, and wheat proteins were considered as probable sources of bovine whey adulteration. Collectively, 523 proteins were identified across all 16 samples and replicates, with 94% of peptides inside a normal distribution within 10ppm of maximum error. In 10 of the 16 samples analyzed, only proteins from bovine whey could be detected, while in the other samples several other protein sources were detected in high concentrations, especially soybean, wheat, and rice. These results point out a probable adulteration and/or sample contamination during manufacturing that could only be detected using this proteomic approach. The present work shows how shotgun proteomics can be used to provide reliable answers in quality control matters, especially focusing on Whey Protein nutritional supplements which are a very popular subject in food and nutrition. In order to achieve an appropriate methodology, careful evaluation was performed applying extremely rigorous quality criteria, established for the proteomic analysis. These criteria and the methodological approach used in this work might serve as a guide for other authors seeking to use proteomics in quality control. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Impact of pre-analytical factors on the proteomic analysis of formalin-fixed paraffin-embedded tissue.

    Science.gov (United States)

    Thompson, Seonaid M; Craven, Rachel A; Nirmalan, Niroshini J; Harnden, Patricia; Selby, Peter J; Banks, Rosamonde E

    2013-04-01

    Formalin-fixed paraffin-embedded (FFPE) tissue samples represent a tremendous potential resource for biomarker discovery, with large numbers of samples in hospital pathology departments and links to clinical information. However, the cross-linking of proteins and nucleic acids by formalin fixation has hampered analysis and proteomic studies have been restricted to using frozen tissue, which is more limited in availability as it needs to be collected specifically for research. This means that rare disease subtypes cannot be studied easily. Recently, improved extraction techniques have enabled analysis of FFPE tissue by a number of proteomic techniques. As with all clinical samples, pre-analytical factors are likely to impact on the results obtained, although overlooked in many studies. The aim of this review is to discuss the various pre-analytical factors, which include warm and cold ischaemic time, size of sample, fixation duration and temperature, tissue processing conditions, length of storage of archival tissue and storage conditions, and to review the studies that have considered these factors in more detail. In those areas where investigations are few or non-existent, illustrative examples of the possible importance of specific factors have been drawn from studies using frozen tissue or from immunohistochemical studies of FFPE tissue. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Screening and identification of APOC1 as a novel potential biomarker for differentiate of mycoplasma pneumoniae in children

    Directory of Open Access Journals (Sweden)

    Jieqiong Li

    2016-12-01

    Full Text Available Background: Although mycoplasma pneumoniae (MP is a common cause of community-acquired pneumonia in children, the currently used diagnostic methods are not optimal. Proteomics is increasingly being used to study the biomarkers of infectious diseases. Methods: Label-free quantitative proteomics and liquid chromatography-mass/mass spectrometry were used to analyze the fold change of protein expression in plasma of children with MP pneumonia (MPP, infectious disease control (IDC, and healthy control (HC groups. Selected proteins that can distinguish MPP from HC and IDC were further validated by enzyme-linked immunosorbent assay (ELISA.Results: After multivariate analyses, 27 potential plasma biomarkers were identified to be expressed differently among child MPP, HC, and IDC groups. Among these proteins, SERPINA3, APOC1, ANXA6, KNTC1, and CFLAR were selected for ELISA verification. SERPINA3, APOC1, and CFLAR levels were significantly different among the three groups and the ratios were consistent with the trends of proteomics results. A comparison of MPP patients and HC showed APOC1 had the largest area under the curve (AUC of 0.853, with 77.6% sensitivity and 81.1% specificity. When APOC1 levels were compared between MPP and IDC patients, it also showed a relatively high AUC of 0.882, with 77.6% sensitivity and 88.3% specificity. Conclusion: APOC1 is a potential biomarker for the rapid and noninvasive diagnosis of MPP in children. The present finding may offer new insights into the pathogenesis and biomarker selection of MPP in children.

  7. The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

    Science.gov (United States)

    Campbell, Kate; Deery, Michael J.; Lilley, Kathryn S.; Ralser, Markus

    2014-01-01

    The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides. PMID:24741437

  8. Multiple nutrient stresses at intersecting Pacific Ocean biomes detected by protein biomarkers.

    Science.gov (United States)

    Saito, Mak A; McIlvin, Matthew R; Moran, Dawn M; Goepfert, Tyler J; DiTullio, Giacomo R; Post, Anton F; Lamborg, Carl H

    2014-09-05

    Marine primary productivity is strongly influenced by the scarcity of required nutrients, yet our understanding of these nutrient limitations is informed by experimental observations with sparse geographical coverage and methodological limitations. We developed a quantitative proteomic method to directly assess nutrient stress in high-light ecotypes of the abundant cyanobacterium Prochlorococcus across a meridional transect in the central Pacific Ocean. Multiple peptide biomarkers detected widespread and overlapping regions of nutritional stress for nitrogen and phosphorus in the North Pacific Subtropical Gyre and iron in the equatorial Pacific. Quantitative protein analyses demonstrated simultaneous stress for these nutrients at biome interfaces. This application of proteomic biomarkers to diagnose ocean metabolism demonstrated Prochlorococcus actively and simultaneously deploying multiple biochemical strategies for low-nutrient conditions in the oceans. Copyright © 2014, American Association for the Advancement of Science.

  9. Reducing the cost of semi-automated in-gel tryptic digestion and GeLC sample preparation for high-throughput proteomics.

    Science.gov (United States)

    Ruelcke, Jayde E; Loo, Dorothy; Hill, Michelle M

    2016-10-21

    Peptide generation by trypsin digestion is typically the first step in mass spectrometry-based proteomics experiments, including 'bottom-up' discovery and targeted proteomics using multiple reaction monitoring. Manual tryptic digest and the subsequent clean-up steps can add variability even before the sample reaches the analytical platform. While specialized filter plates and tips have been designed for automated sample processing, the specialty reagents required may not be accessible or feasible due to their high cost. Here, we report a lower-cost semi-automated protocol for in-gel digestion and GeLC using standard 96-well microplates. Further cost savings were realized by re-using reagent tips with optimized sample ordering. To evaluate the methodology, we compared a simple mixture of 7 proteins and a complex cell-lysate sample. The results across three replicates showed that our semi-automated protocol had performance equal to or better than a manual in-gel digestion with respect to replicate variability and level of contamination. In this paper, we also provide the Agilent Bravo method file, which can be adapted to other liquid handlers. The simplicity, reproducibility, and cost-effectiveness of our semi-automated protocol make it ideal for routine in-gel and GeLC sample preparations, as well as high throughput processing of large clinical sample cohorts. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Investigation of serum biomarkers in primary gout patients using iTRAQ-based screening.

    Science.gov (United States)

    Ying, Ying; Chen, Yong; Zhang, Shun; Huang, Haiyan; Zou, Rouxin; Li, Xiaoke; Chu, Zanbo; Huang, Xianqian; Peng, Yong; Gan, Minzhi; Geng, Baoqing; Zhu, Mengya; Ying, Yinyan; Huang, Zuoan

    2018-03-21

    Primary gout is a major disease that affects human health; however, its pathogenesis is not well known. The purpose of this study was to identify biomarkers to explore the underlying mechanisms of primary gout. We used the isobaric tags for relative and absolute quantitation (iTRAQ) technique combined with liquid chromatography-tandem mass spectrometry to screen differentially expressed proteins between gout patients and controls. We also identified proteins potentially involved in gout pathogenesis by analysing biological processes, cellular components, molecular functions, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interactions. We further verified some samples using enzyme-linked immunosorbent assay (ELISA). Statistical analyses were carried out using SPSS v. 20.0 and ROC (receiver operating characterstic) curve analyses were carried out using Medcalc software. Two-sided p-values gout than in controls (p=0.023). iTRAQ technology was useful in the selection of differentially expressed proteins from proteomes, and provides a strong theoretical basis for the study of biomarkers and mechanisms in primary gout. In addition, TBB4A protein may be associated with primary gout.

  11. Plasma proteome profiles associated with diet-induced metabolic syndrome and the early onset of metabolic syndrome in a pig model.

    Directory of Open Access Journals (Sweden)

    Marinus F W te Pas

    Full Text Available Obesity and related diabetes are important health threatening multifactorial metabolic diseases and it has been suggested that 25% of all diabetic patients are unaware of their patho-physiological condition. Biomarkers for monitoring and control are available, but early stage predictive biomarkers enabling prevention of these diseases are still lacking. We used the pig as a model to study metabolic disease because humans and pigs share a multitude of metabolic similarities. Diabetes was chemically induced and control and diabetic pigs were either fed a high unsaturated fat (Mediterranean diet or a high saturated fat/cholesterol/sugar (cafeteria diet. Physiological parameters related to fat metabolism and diabetes were measured. Diabetic pigs' plasma proteome profiles differed more between the two diets than control pigs plasma proteome profiles. The expression levels of several proteins correlated well with (pathophysiological parameters related to the fat metabolism (cholesterol, VLDL, LDL, NEFA and diabetes (Glucose and to the diet fed to the animals. Studying only the control pigs as a model for metabolic syndrome when fed the two diets showed correlations to the same parameters but now more focused on insulin, glucose and abdominal fat depot parameters. We conclude that proteomic profiles can be used as a biomarker to identify pigs with developing metabolic syndrome (prediabetes and diabetes when fed a cafeteria diet. It could be developed into a potential biomarkers for the early recognition of metabolic diseases.

  12. Blood-Based Biomarker Candidates of Cerebral Amyloid Using PiB PET in Non-Demented Elderly

    Science.gov (United States)

    Westwood, Sarah; Leoni, Emanuela; Hye, Abdul; Lynham, Steven; Khondoker, Mizanur R.; Ashton, Nicholas J.; Kiddle, Steven J.; Baird, Alison L.; Sainz-Fuertes, Ricardo; Leung, Rufina; Graf, John; Hehir, Cristina Tan; Baker, David; Cereda, Cristina; Bazenet, Chantal; Ward, Malcolm; Thambisetty, Madhav; Lovestone, Simon

    2018-01-01

    Increasingly, clinical trials for Alzheimer’s disease (AD) are being conducted earlier in the disease phase and with biomarker confirmation using in vivo amyloid PET imaging or CSF tau and Aβ measures to quantify pathology. However, making such a pre-clinical AD diagnosis is relatively costly and the screening failure rate is likely to be high. Having a blood-based marker that would reduce such costs and accelerate clinical trials through identifying potential participants with likely pre-clinical AD would be a substantial advance. In order to seek such a candidate biomarker, discovery phase proteomic analyses using 2DGE and gel-free LC-MS/MS for high and low molecular weight analytes were conducted on longitudinal plasma samples collected over a 12-year period from non-demented older individuals who exhibited a range of 11C-PiB PET measures of amyloid load. We then sought to extend our discovery findings by investigating whether our candidate biomarkers were also associated with brain amyloid burden in disease, in an independent cohort. Seven plasma proteins, including A2M, Apo-A1, and multiple complement proteins, were identified as pre-clinical biomarkers of amyloid burden and were consistent across three time points (p biomarker signature indicative of AD pathology at a stage long before the onset of clinical disease manifestation. As in previous studies, acute phase reactants and inflammatory markers dominate this signature. PMID:27031486

  13. Integration of metabolomics and proteomics in molecular plant physiology--coping with the complexity by data-dimensionality reduction.

    Science.gov (United States)

    Weckwerth, Wolfram

    2008-02-01

    In recent years, genomics has been extended to functional genomics. Toward the characterization of organisms or species on the genome level, changes on the metabolite and protein level have been shown to be essential to assign functions to genes and to describe the dynamic molecular phenotype. Gas chromatography (GC) and liquid chromatography coupled to mass spectrometry (GC- and LC-MS) are well suited for the fast and comprehensive analysis of ultracomplex metabolite samples. For the integration of metabolite profiles with quantitative protein profiles, a high throughput (HTP) shotgun proteomics approach using LC-MS and label-free quantification of unique proteins in a complex protein digest is described. Multivariate statistics are applied to examine sample pattern recognition based on data-dimensionality reduction and biomarker identification in plant systems biology. The integration of the data reveal multiple correlative biomarkers providing evidence for an increase of information in such holistic approaches. With computational simulation of metabolic networks and experimental measurements, it can be shown that biochemical regulation is reflected by metabolite network dynamics measured in a metabolomics approach. Examples in molecular plant physiology are presented to substantiate the integrative approach.

  14. Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Sylvia G. Lehmann

    2017-01-01

    Full Text Available Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging.

  15. Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

    KAUST Repository

    Komatsu, Setsuko

    2017-05-10

    The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max ‘Enrei’). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. Biological significanceThe Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all

  16. Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database.

    Science.gov (United States)

    Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

    2017-06-23

    The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from

  17. Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

    KAUST Repository

    Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

    2017-01-01

    The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max ‘Enrei’). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. Biological significanceThe Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all

  18. Cyclization of the N-Terminal X-Asn-Gly Motif during Sample Preparation for Bottom-Up Proteomics

    DEFF Research Database (Denmark)

    Zhang, Xumin; Højrup, Peter

    2010-01-01

    We, herein, report a novel -17 Da peptide modification corresponding to an N-terminal cyclization of peptides possessing the N-terminal motif of X-Asn-Gly. The cyclization occurs spontaneously during sample preparation for bottom-up proteomics studies. Distinct from the two well-known N-terminal ......We, herein, report a novel -17 Da peptide modification corresponding to an N-terminal cyclization of peptides possessing the N-terminal motif of X-Asn-Gly. The cyclization occurs spontaneously during sample preparation for bottom-up proteomics studies. Distinct from the two well-known N......-terminal cyclizations, cyclization of N-terminal glutamine and S-carbamoylmethylcysteine, it is dependent on pH instead of [NH(4)(+)]. The data set from our recent study on large-scale N(α)-modified peptides revealed a sequence requirement for the cyclization event similar to the well-known deamidation of Asn to iso...

  19. Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics.

    Science.gov (United States)

    Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

    2016-09-01

    Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

  20. Application of a new procedure for liquid chromatography/mass spectrometry profiling of plasma amino acid-related metabolites and untargeted shotgun proteomics to identify mechanisms and biomarkers of calcific aortic stenosis.

    Science.gov (United States)

    Olkowicz, Mariola; Debski, Janusz; Jablonska, Patrycja; Dadlez, Michal; Smolenski, Ryszard T

    2017-09-29

    Calcific aortic valve stenosis (CAS) increasingly affects our ageing population, but the mechanisms of the disease and its biomarkers are not well established. Recently, plasma amino acid-related metabolite (AA) profiling has attracted attention in studies on pathology and development of biomarkers of cardiovascular diseases, but has not been studied in CAS. To evaluate the potential relationship between CAS and AA metabolome, a new ion-pairing reversed-phase liquid chromatography-tandem mass spectrometry (IP-RPLC-MS/MS) method has been developed and validated for simultaneous determination of 43 AAs in plasma of stenotic patients and age-matched control subjects. Furthermore, untargeted mass spectrometry-based proteomic analysis and confirmatory ELISA assays were performed. The method developed offered high accuracy (intra-assay imprecision averaged 4.4% for all compounds) and sensitivity (LOQ within 0.01-0.5μM). We found that 22 AAs and three AA ratios significantly changed in the CAS group as compared to control. The most pronounced differences were observed in urea cycle-related AAs and branched-chain AA (BCAA)-related AAs. The contents of asymmetric dimethylarginine (ADMA) and its monomethylated derivative (NMMA) were increased by 30-64% with CAS. The arginine/ADMA and Fischer's ratios as well as arginine, homoarginine, ADMA, symmetric dimethylarginine, hydroxyproline, betaine and 3-methylhistidine correlated with cardiac function-related parameters and concomitant systemic factors in the CAS patients. The results of proteomic analysis were consistent with involvement of inflammation, lipid abnormalities, hemostasis and extracellular matrix remodeling in CAS. In conclusion, changes in plasma AA profile and protein pattern that we identified in CAS provide information relevant to pathomechanisms and may deliver new biomarkers of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Screening of plasma biomarkers in patients with unstable angina pectoris with proteomics analysis

    Directory of Open Access Journals (Sweden)

    Shui-wang HU

    2017-08-01

    Full Text Available Objective To analyze and compare the differentially expressed plasma proteins between patients with stable angina pectoris (SAP and unstable angina pectoris (UAP, and search for the biomarkers that maybe used for early diagnosis of UAP. Methods Sixty plasma samples were collected respectively from normal controls group (N group, SAP group and UAP group during Jun. 2014 to Apr. 2015 from the Third Affiliated Hospital of Southern Medical University. Ten samples (100μl of each group were selected randomly to pool into 3 groups severally. After removing high-abundance proteins from plasma, two- dimensional difference gel electrophoresis (DIGE was used to isolate the total proteins, and then the protein spots with more than 2-fold changes between UAP and SAP were picked up after the differential software analysis. Afterward, the varied proteins were identified by matrix assisted laser desorption ionization-time of flight/time of flight (MALDI-TOF/TOF mass spectrometry (MS. Finally, 40 plasma samples were collected respectively from N, SAP and UAP group, and the UAP specific differential proteins were selected to be verified by ELISA. Results A total of 10 varied protein spots with more than 2-fold changes in UAP and SAP were found including 9 up-regulated proteins and 1 down-regulated one. MS identification indicated that the up-regulated proteins included fibrinogen gamma chain (FGG, complement C4-B (C4B, immunoglobulin (Ig kappa chain C region (IGKC and hemoglobin subunit alpha (HBA1, whereas the down-regulated one was haptoglobin (HP. After comparing the varied proteins with that in N group, 2 specifically UAP-related proteins, IGKC and HP, were detected totally. IGKC was selected to validate by ELISA, and the corresponding results showed that IGKC was increased specifically in UAP plasma (P<0.05 when compared with N and SAP group, which was consistent with DIGE. Conclusion IGKC and HP have been detected as specifically related proteins to UAP

  2. Serum amyloid A as a prognostic marker in melanoma identified by proteomic profiling.

    Science.gov (United States)

    Findeisen, Peter; Zapatka, Marc; Peccerella, Teresa; Matzk, Heike; Neumaier, Michael; Schadendorf, Dirk; Ugurel, Selma

    2009-05-01

    Currently known prognostic serum biomarkers of melanoma are powerful in metastatic disease, but weak in early-stage patients. This study was aimed to identify new prognostic biomarkers of melanoma by serum mass spectrometry (MS) proteomic profiling, and to validate candidates compared with established markers. Two independent sets of serum samples from 596 melanoma patients were investigated. The first set (stage I = 102; stage IV = 95) was analyzed by matrix assisted laser desorption and ionization time of flight (MALDI TOF) MS for biomarkers differentiating between stage I and IV. In the second set (stage I = 98; stage II = 91; stage III = 87; stage IV = 103), the serum concentrations of the candidate marker serum amyloid A (SAA) and the known biomarkers S100B, lactate dehydrogenase, and C reactive protein (CRP) were measured using immunoassays. MALDI TOF MS revealed a peak at m/z 11.680 differentiating between stage I and IV, which could be identified as SAA. High peak intensities at m/z 11.680 correlated with poor survival. In univariate analysis, SAA was a strong prognostic marker in stage I to III (P = .043) and stage IV (P = .000083) patients. Combination of SAA and CRP increased the prognostic impact to P = .011 in early-stage (I to III) patients. Multivariate analysis revealed sex, stage, tumor load, S100B, SAA, and CRP as independent prognostic factors, with an interaction between SAA and CRP. In stage I to III patients, SAA combined with CRP was superior to S100B in predicting patients' progression-free and overall survival. SAA combined with CRP might be used as prognostic serological biomarkers in early-stage melanoma patients, helping to discriminate low-risk patients from high-risk patients needing adjuvant treatment.

  3. State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics.

    Science.gov (United States)

    Gopal, Judy; Muthu, Manikandan; Chun, Se-Chul; Wu, Hui-Fen

    2015-06-01

    Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Simplifying the human serum proteome for discriminating patients with bipolar disorder of other psychiatry conditions.

    Science.gov (United States)

    de Jesus, Jemmyson Romário; Galazzi, Rodrigo Moretto; de Lima, Tatiani Brenelli; Banzato, Cláudio Eduardo Muller; de Almeida Lima E Silva, Luiz Fernando; de Rosalmeida Dantas, Clarissa; Gozzo, Fábio Cézar; Arruda, Marco Aurélio Zezzi

    2017-12-01

    An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  5. Identification of protein biomarkers in Dupuytren's contracture using surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS).

    Science.gov (United States)

    O'Gorman, David; Howard, Jeffrey C; Varallo, Vincenzo M; Cadieux, Peter; Bowley, Erin; McLean, Kris; Pak, Brian J; Gan, Bing Siang

    2006-06-01

    To study the protein expression profiles associated with Dupuytren's contracture (DC) to identify potential disease protein biomarkers (PBM) using a proteomic technology--Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). Normal and disease palmar fascia from DC patients were analyzed using Ciphergen's SELDI-TOF-MS Protein Biological System II (PBSII) ProteinChip reader. Analysis of the resulting SELDI-TOF spectra was carried out using the peak cluster analysis program (BioMarker Wizard, Ciphergen). Common peak clusters were then filtered using a bootstrap algorithm called SAM (Significant Analysis of Microarrays) for increased fidelity in our analysis. Several differentially expressed low molecular weight (mass standard deviation for both methods of biomarker-rich low molecular weight region of the human proteome. Application of such novel technology may help clinicians to focus on specific molecular abnormalities in diseases with no known molecular pathogenesis, and uncover therapeutic and/or diagnostic targets.

  6. Proteomics of Trypanosoma evansi infection in rodents.

    Science.gov (United States)

    Roy, Nainita; Nageshan, Rishi Kumar; Pallavi, Rani; Chakravarthy, Harshini; Chandran, Syama; Kumar, Rajender; Gupta, Ashok Kumar; Singh, Raj Kumar; Yadav, Suresh Chandra; Tatu, Utpal

    2010-03-22

    Trypanosoma evansi infections, commonly called 'surra', cause significant economic losses to livestock industry. While this infection is mainly restricted to large animals such as camels, donkeys and equines, recent reports indicate their ability to infect humans. There are no World Animal Health Organization (WAHO) prescribed diagnostic tests or vaccines available against this disease and the available drugs show significant toxicity. There is an urgent need to develop improved methods of diagnosis and control measures for this disease. Unlike its related human parasites T. brucei and T. cruzi whose genomes have been fully sequenced T. evansi genome sequence remains unavailable and very little efforts are being made to develop improved methods of prevention, diagnosis and treatment. With a view to identify potential diagnostic markers and drug targets we have studied the clinical proteome of T. evansi infection using mass spectrometry (MS). Using shot-gun proteomic approach involving nano-lc Quadrupole Time Of Flight (QTOF) mass spectrometry we have identified over 160 proteins expressed by T. evansi in mice infected with camel isolate. Homology driven searches for protein identification from MS/MS data led to most of the matches arising from related Trypanosoma species. Proteins identified belonged to various functional categories including metabolic enzymes; DNA metabolism; transcription; translation as well as cell-cell communication and signal transduction. TCA cycle enzymes were strikingly missing, possibly suggesting their low abundances. The clinical proteome revealed the presence of known and potential drug targets such as oligopeptidases, kinases, cysteine proteases and more. Previous proteomic studies on Trypanosomal infections, including human parasites T. brucei and T. cruzi, have been carried out from lab grown cultures. For T. evansi infection this is indeed the first ever proteomic study reported thus far. In addition to providing a glimpse into the

  7. Proteomics of Trypanosoma evansi infection in rodents.

    Directory of Open Access Journals (Sweden)

    Nainita Roy

    2010-03-01

    Full Text Available Trypanosoma evansi infections, commonly called 'surra', cause significant economic losses to livestock industry. While this infection is mainly restricted to large animals such as camels, donkeys and equines, recent reports indicate their ability to infect humans. There are no World Animal Health Organization (WAHO prescribed diagnostic tests or vaccines available against this disease and the available drugs show significant toxicity. There is an urgent need to develop improved methods of diagnosis and control measures for this disease. Unlike its related human parasites T. brucei and T. cruzi whose genomes have been fully sequenced T. evansi genome sequence remains unavailable and very little efforts are being made to develop improved methods of prevention, diagnosis and treatment. With a view to identify potential diagnostic markers and drug targets we have studied the clinical proteome of T. evansi infection using mass spectrometry (MS.Using shot-gun proteomic approach involving nano-lc Quadrupole Time Of Flight (QTOF mass spectrometry we have identified over 160 proteins expressed by T. evansi in mice infected with camel isolate. Homology driven searches for protein identification from MS/MS data led to most of the matches arising from related Trypanosoma species. Proteins identified belonged to various functional categories including metabolic enzymes; DNA metabolism; transcription; translation as well as cell-cell communication and signal transduction. TCA cycle enzymes were strikingly missing, possibly suggesting their low abundances. The clinical proteome revealed the presence of known and potential drug targets such as oligopeptidases, kinases, cysteine proteases and more.Previous proteomic studies on Trypanosomal infections, including human parasites T. brucei and T. cruzi, have been carried out from lab grown cultures. For T. evansi infection this is indeed the first ever proteomic study reported thus far. In addition to providing a

  8. Decoding the Proteome of In-Vitro Fertilization Ovarian Follicular Fluid for Women Over 35 Years

    Directory of Open Access Journals (Sweden)

    Mohamed Sabry

    2014-12-01

    Full Text Available Aim: The study of follicular fluid using proteomic techniques could provide a useful tool for understanding follicular fluid components and their effect on pregnancy outcome. The aim of the study is to identify and catalog follicular fluid proteins in women 35 years of age or older. Material and Method: Follicular fluid was collected from 21 couples, of which 11 couples achieved successful pregnancy and 10 couples failed to get pregnant. Samples were analyzed by multidimensional chromatography coupled with in-line nano-spray ionization mass spectrometry on an LTQ XL ion trap mass spectrometer. We used the Biomarker Analysis Program from PDQuest software to identify protein constituents in pregnant and non-pregnant groups. Results: In total, 1024 protein specimens were identified. The proteins identified were consistent throughout the experiment and within each of the analyzed specimens. Discussion: A compiled listing of follicular fluid proteins could be a potential starting point for the identification and evaluation of important proteins involved in the development of oocytes; the results of our study may fill a noticeable knowledge-gap in the understanding of follicular fluid proteome.

  9. Identification of biomarkers for radiation-induced acute intestinal symptoms (RIAISs) in cervical cancer patients by serum protein profiling

    International Nuclear Information System (INIS)

    Chai Yanlan; Wang Juan; Gao Ying

    2015-01-01

    Radiation-induced acute intestinal symptoms (RIAISs) are the most frequent complication of radiotherapy that causes great pain and limits the treatment efficacy. The aim of this study was to identify serum biomarkers of RIAISs in cervical cancer patients by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Serum samples were collected from 66 cervical cancer patients prior to pelvic radiotherapy. In our study, RIAISs occurred in 11 patients. An additional 11 patients without RIAISs were selected as controls, whose age, stage, histological type and treatment methods were matched to RIAISs patients. The 22 sera were subsequently analyzed by SELDI-TOF MS, and the resulting protein profiles were evaluated to identify biomarkers using appropriate bioinformatics tools. Comparing the protein profiles of serum samples from the RIAIS group and the control group, it was found that 22 protein peaks were significantly different (P < 0.05), and six of these peaks with mass-to-charge (m/z) ratios of 7514.9, 4603.94, 6887.41, 2769.21, 3839.72 and 4215.7 were successfully identified. A decision tree model of biomarkers was constructed based on three biomarkers (m/z 1270.88, 1503.23 and 7514.90), which separated RIAIS-affected patients from the control group with an accuracy of 81%. This study suggests that serum proteomic analysis by SELDI-TOF MS can identify cervical cancer patients that are susceptible to RIAISs prior to pelvic radiotherapy. (author)

  10. Proteomics as a Tool for Understanding Schizophrenia

    OpenAIRE

    Martins-de-Souza, Daniel

    2011-01-01

    Schizophrenia is likely to be a multifactorial disorder, consequence of alterations in gene and protein expression since the neurodevelopment that together to environmental factors will trigger the establishment of the disease. In the post-genomic era, proteomics has emerged as a promising strategy for revealing disease and treatment biomarkers as well as a tool for the comprehension of the mechanisms of schizophrenia pathobiology. Here, there is a discussion of the potential pathways and str...

  11. The inflammatory cytokines: molecular biomarkers for major depressive disorder?

    Science.gov (United States)

    Martin, Charlotte; Tansey, Katherine E; Schalkwyk, Leonard C; Powell, Timothy R

    2015-01-01

    Cytokines are pleotropic cell signaling proteins that, in addition to their role as inflammatory mediators, also affect neurotransmitter systems, brain functionality and mood. Here we explore the potential utility of cytokine biomarkers for major depressive disorder. Specifically, we explore how genetic, transcriptomic and proteomic information relating to the cytokines might act as biomarkers, aiding clinical diagnosis and treatment selection processes. We advise future studies to investigate whether cytokine biomarkers might differentiate major depressive disorder patients from other patient groups with overlapping clinical characteristics. Furthermore, we invite future pharmacogenetic studies to investigate whether early antidepressant-induced changes to cytokine mRNA or protein levels precede behavioral changes and act as longer-term predictors of clinical antidepressant response.

  12. Liver proteomics in progressive alcoholic steatosis

    Energy Technology Data Exchange (ETDEWEB)

    Fernando, Harshica [Department of Pathology, The University of Texas Medical Branch, Galveston, TX 77555 (United States); Wiktorowicz, John E.; Soman, Kizhake V. [Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, Galveston, TX 77555 (United States); Kaphalia, Bhupendra S.; Khan, M. Firoze [Department of Pathology, The University of Texas Medical Branch, Galveston, TX 77555 (United States); Shakeel Ansari, G.A., E-mail: sansari@utmb.edu [Department of Pathology, The University of Texas Medical Branch, Galveston, TX 77555 (United States)

    2013-02-01

    Fatty liver is an early stage of alcoholic and nonalcoholic liver disease (ALD and NALD) that progresses to steatohepatitis and other irreversible conditions. In this study, we identified proteins that were differentially expressed in the livers of rats fed 5% ethanol in a Lieber–DeCarli diet daily for 1 and 3 months by discovery proteomics (two-dimensional gel electrophoresis and mass spectrometry) and non-parametric modeling (Multivariate Adaptive Regression Splines). Hepatic fatty infiltration was significantly higher in ethanol-fed animals as compared to controls, and more pronounced at 3 months of ethanol feeding. Discovery proteomics identified changes in the expression of proteins involved in alcohol, lipid, and amino acid metabolism after ethanol feeding. At 1 and 3 months, 12 and 15 different proteins were differentially expressed. Of the identified proteins, down regulation of alcohol dehydrogenase (− 1.6) at 1 month and up regulation of aldehyde dehydrogenase (2.1) at 3 months could be a protective/adaptive mechanism against ethanol toxicity. In addition, betaine-homocysteine S-methyltransferase 2 a protein responsible for methionine metabolism and previously implicated in fatty liver development was significantly up regulated (1.4) at ethanol-induced fatty liver stage (1 month) while peroxiredoxin-1 was down regulated (− 1.5) at late fatty liver stage (3 months). Nonparametric analysis of the protein spots yielded fewer proteins and narrowed the list of possible markers and identified D-dopachrome tautomerase (− 1.7, at 3 months) as a possible marker for ethanol-induced early steatohepatitis. The observed differential regulation of proteins have potential to serve as biomarker signature for the detection of steatosis and its progression to steatohepatitis once validated in plasma/serum. -- Graphical abstract: The figure shows the Hierarchial cluster analysis of differentially expressed protein spots obtained after ethanol feeding for 1 (1–3

  13. Proteomic analysis of human tooth pulp: proteomics of human tooth.

    Science.gov (United States)

    Eckhardt, Adam; Jágr, Michal; Pataridis, Statis; Mikšík, Ivan

    2014-12-01

    The unique pulp-dentin complex demonstrates strong regenerative potential, which enables it to respond to disease and traumatic injury. Identifying the proteins of the pulp-dentin complex is crucial to understanding the mechanisms of regeneration, tissue calcification, defense processes, and the reparation of dentin by dental pulp. The lack of knowledge of these proteins limits the development of more efficient therapies. The proteomic profile of human tooth pulp was investigated and compared with the proteome of human dentin and blood. The samples of tooth pulp were obtained from 5 sound permanent human third molars of 5 adults (n = 5). The extracted proteins were separated by 2-dimensional gel electrophoresis, analyzed by nano-liquid chromatography tandem mass spectrometry, and identified by correlating mass spectra to the proteomic databases. A total of 342 proteins were identified with high confidence, and 2 proteins were detected for the first time in an actual human sample. The identified tooth pulp proteins have a variety of functions: structural, catalytic, transporter, protease activity, immune response, and many others. In a comparison with dentin and blood plasma, 140 (pulp/dentin) shared proteins were identified, 37 of which were not observed in plasma. It can be suggested that they might participate in the unique pulp-dentin complex. This proteomic investigation of human tooth pulp, together with the previously published study of human dentin, is one of the most comprehensive proteome lists of human teeth to date. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

  14. Development of a Rapid Salivary Proteomic Platform for Oral Feeding Readiness in the Preterm Newborn

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    Prarthana Khanna

    2017-12-01

    Full Text Available Oral feeding competency is a major determinant of length of stay in the neonatal intensive care unit. An infant must be able to consistently demonstrate the ability to take all required enteral nutrition by mouth before discharge home. Most infants born prematurely (<37 weeks will require days, if not weeks, to master this oral feeding competency skill. Inappropriately timed feeding attempts can lead to acute and long-term morbidities, prolonged hospitalizations, and increased health-care costs. Previously, a panel of five genes involved in essential developmental pathways including sensory integration (nephronophthisis 4, Plexin A1, hunger signaling [neuropeptide Y2 receptor (NPY2R, adenosine-monophosphate-activated protein kinase (AMPK], and facial development (wingless-type MMTV integration site family, member 3 required for oral feeding success were identified in neonatal saliva. This study aimed to translate these five transcriptomic biomarkers into a rapid proteomic platform to provide objective, real-time assessment of oral feeding skills, to better inform care, and to improve neonatal outcomes. Total protein was extracted from saliva of 10 feeding-successful and 10 feeding-unsuccessful infants matched for age, sex, and post-conceptional age. Development of immunoassays was attempted for five oral feeding biomarkers and two reference biomarkers (GAPDH and YWHAZ to normalize for starting protein concentrations. Normalized protein concentrations were correlated to both feeding status at time of sample collection and previously described gene expression profiles. Only the reference proteins and those involved in hunger signaling were detected in neonatal saliva at measurable levels. Expression patterns for NPY2R and AMPK correlated with the gene expression patterns previously seen between successful and unsuccessful feeders and predicted feeding outcome. Salivary proteins associated with hunger signaling are readily quantifiable in

  15. Proteomic Profiling of Mitochondrial Enzymes during Skeletal Muscle Aging

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    Lisa Staunton

    2011-01-01

    Full Text Available Mitochondria are of central importance for energy generation in skeletal muscles. Expression changes or functional alterations in mitochondrial enzymes play a key role during myogenesis, fibre maturation, and various neuromuscular pathologies, as well as natural fibre aging. Mass spectrometry-based proteomics suggests itself as a convenient large-scale and high-throughput approach to catalogue the mitochondrial protein complement and determine global changes during health and disease. This paper gives a brief overview of the relatively new field of mitochondrial proteomics and discusses the findings from recent proteomic surveys of mitochondrial elements in aged skeletal muscles. Changes in the abundance, biochemical activity, subcellular localization, and/or posttranslational modifications in key mitochondrial enzymes might be useful as novel biomarkers of aging. In the long term, this may advance diagnostic procedures, improve the monitoring of disease progression, help in the testing of side effects due to new drug regimes, and enhance our molecular understanding of age-related muscle degeneration.

  16. Risk Factors and Biomarkers of Age-Related Macular Degeneration

    Science.gov (United States)

    Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

    2016-01-01

    A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

  17. NeuCode Proteomics Reveals Bap1 Regulation of Metabolism

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    Joshua M. Baughman

    2016-07-01

    Full Text Available We introduce neutron-encoded (NeuCode amino acid labeling of mice as a strategy for multiplexed proteomic analysis in vivo. Using NeuCode, we characterize an inducible knockout mouse model of Bap1, a tumor suppressor and deubiquitinase whose in vivo roles outside of cancer are not well established. NeuCode proteomics revealed altered metabolic pathways following Bap1 deletion, including profound elevation of cholesterol biosynthetic machinery coincident with reduced expression of gluconeogenic and lipid homeostasis proteins in liver. Bap1 loss increased pancreatitis biomarkers and reduced expression of mitochondrial proteins. These alterations accompany a metabolic remodeling with hypoglycemia, hypercholesterolemia, hepatic lipid loss, and acinar cell degeneration. Liver-specific Bap1 null mice present with fully penetrant perinatal lethality, severe hypoglycemia, and hepatic lipid deficiency. This work reveals Bap1 as a metabolic regulator in liver and pancreas, and it establishes NeuCode as a reliable proteomic method for deciphering in vivo biology.

  18. Integrated proteomic and transcriptomic investigation of the acetaminophen toxicity in liver microfluidic biochip.

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    Jean Matthieu Prot

    Full Text Available Microfluidic bioartificial organs allow the reproduction of in vivo-like properties such as cell culture in a 3D dynamical micro environment. In this work, we established a method and a protocol for performing a toxicogenomic analysis of HepG2/C3A cultivated in a microfluidic biochip. Transcriptomic and proteomic analyses have shown the induction of the NRF2 pathway and the related drug metabolism pathways when the HepG2/C3A cells were cultivated in the biochip. The induction of those pathways in the biochip enhanced the metabolism of the N-acetyl-p-aminophenol drug (acetaminophen-APAP when compared to Petri cultures. Thus, we observed 50% growth inhibition of cell proliferation at 1 mM in the biochip, which appeared similar to human plasmatic toxic concentrations reported at 2 mM. The metabolic signature of APAP toxicity in the biochip showed similar biomarkers as those reported in vivo, such as the calcium homeostasis, lipid metabolism and reorganization of the cytoskeleton, at the transcriptome and proteome levels (which was not the case in Petri dishes. These results demonstrate a specific molecular signature for acetaminophen at transcriptomic and proteomic levels closed to situations found in vivo. Interestingly, a common component of the signature of the APAP molecule was identified in Petri and biochip cultures via the perturbations of the DNA replication and cell cycle. These findings provide an important insight into the use of microfluidic biochips as new tools in biomarker research in pharmaceutical drug studies and predictive toxicity investigations.

  19. Circulating extracellular vesicles with specific proteome and liver microRNAs are potential biomarkers for liver injury in experimental fatty liver disease.

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    Davide Povero

    Full Text Available Nonalcoholic fatty liver disease (NAFLD is the most common chronic liver disease in both adult and children. Currently there are no reliable methods to determine disease severity, monitor disease progression, or efficacy of therapy, other than an invasive liver biopsy.Choline Deficient L-Amino Acid (CDAA and high fat diets were used as physiologically relevant mouse models of NAFLD. Circulating extracellular vesicles were isolated, fully characterized by proteomics and molecular analyses and compared to control groups. Liver-related microRNAs were isolated from purified extracellular vesicles and liver specimens.We observed statistically significant differences in the level of extracellular vesicles (EVs in liver and blood between two control groups and NAFLD animals. Time-course studies showed that EV levels increase early during disease development and reflect changes in liver histolopathology. EV levels correlated with hepatocyte cell death (r2 = 0.64, p<0.05, fibrosis (r2 = 0.66, p<0.05 and pathological angiogenesis (r2 = 0.71, p<0.05. Extensive characterization of blood EVs identified both microparticles (MPs and exosomes (EXO present in blood of NAFLD animals. Proteomic analysis of blood EVs detected various differentially expressed proteins in NAFLD versus control animals. Moreover, unsupervised hierarchical clustering identified a signature that allowed for discrimination between NAFLD and controls. Finally, the liver appears to be an important source of circulating EVs in NAFLD animals as evidenced by the enrichment in blood with miR-122 and 192--two microRNAs previously described in chronic liver diseases, coupled with a corresponding decrease in expression of these microRNAs in the liver.These findings suggest a potential for using specific circulating EVs as sensitive and specific biomarkers for the noninvasive diagnosis and monitoring of NAFLD.

  20. A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

    Science.gov (United States)

    Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

    2017-08-15

    Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Identification of potential urine proteins and microRNA biomarkers for the diagnosis of pulmonary tuberculosis patients.

    Science.gov (United States)

    Wang, Jieru; Zhu, Xiaojie; Xiong, Xuekai; Ge, Pan; Liu, Han; Ren, Ningning; Khan, Farhan Anwar; Zhou, Xia; Zhang, Li; Yuan, Xu; Chen, Xi; Chen, Yingyu; Hu, Changmin; Robertson, Ian D; Chen, Huanchun; Guo, Aizhen

    2018-04-11

    This study identified urinary biomarkers for tuberculosis (TB) diagnosis. The urine proteomic profiles of 45 pulmonary tuberculosis patients prior to anti-TB treatment and 45 healthy controls were analyzed and compared using two-dimensional electrophoresis with matrix-assisted laser desorption/ionization time of flight mass spectrometry. Nineteen differentially expressed proteins were identified preliminarily, and western blotting and qRT-PCR were performed to confirm these changes at the translational and transcriptional levels, respectively, using samples from 122 additional pulmonary tuberculosis patients and 73 additional healthy controls. Two proteins, mannose-binding lectin 2 and a 35-kDa fragment of inter-α-trypsin inhibitor H4, exhibited the highest differential expression. We constructed a protein-microRNA interaction network that primarily involved complement and inflammatory responses. Eleven microRNAs from microRNA-target protein interactions were screened and validated using qRT-PCR with some of the above samples, including 97 pulmonary tuberculosis patients and 48 healthy controls. Only miR-625-3p exhibited significant differential expression (p tuberculosis diagnosis than individual biomarkers or any two-biomarker combination and generated a diagnostic sensitivity of 85.87% and a specificity of 87.50%. These novel urine biomarkers may significantly improve tuberculosis diagnosis.

  2. Proteomics and the search for welfare and stress biomarkers in animal production in the one-health context.

    Science.gov (United States)

    Marco-Ramell, A; de Almeida, A M; Cristobal, S; Rodrigues, P; Roncada, P; Bassols, A

    2016-06-21

    Stress and welfare are important factors in animal production in the context of growing production optimization and scrutiny by the general public. In a context in which animal and human health are intertwined aspects of the one-health concept it is of utmost importance to define the markers of stress and welfare. These are important tools for producers, retailers, regulatory agents and ultimately consumers to effectively monitor and assess the welfare state of production animals. Proteomics is the science that studies the proteins existing in a given tissue or fluid. In this review we address this topic by showing clear examples where proteomics has been used to study stress-induced changes at various levels. We adopt a multi-species (cattle, swine, small ruminants, poultry, fish and shellfish) approach under the effect of various stress inducers (handling, transport, management, nutritional, thermal and exposure to pollutants) clearly demonstrating how proteomics and systems biology are key elements to the study of stress and welfare in farm animals and powerful tools for animal welfare, health and productivity.

  3. Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

    Science.gov (United States)

    Lam, Raymond W; Milev, Roumen; Rotzinger, Susan; Andreazza, Ana C; Blier, Pierre; Brenner, Colleen; Daskalakis, Zafiris J; Dharsee, Moyez; Downar, Jonathan; Evans, Kenneth R; Farzan, Faranak; Foster, Jane A; Frey, Benicio N; Geraci, Joseph; Giacobbe, Peter; Feilotter, Harriet E; Hall, Geoffrey B; Harkness, Kate L; Hassel, Stefanie; Ismail, Zahinoor; Leri, Francesco; Liotti, Mario; MacQueen, Glenda M; McAndrews, Mary Pat; Minuzzi, Luciano; Müller, Daniel J; Parikh, Sagar V; Placenza, Franca M; Quilty, Lena C; Ravindran, Arun V; Salomons, Tim V; Soares, Claudio N; Strother, Stephen C; Turecki, Gustavo; Vaccarino, Anthony L; Vila-Rodriguez, Fidel; Kennedy, Sidney H

    2016-04-16

    Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants

  4. Secreted autoantibody repertoires in Sjögren's syndrome and systemic lupus erythematosus: A proteomic approach.

    Science.gov (United States)

    Al Kindi, Mahmood A; Colella, Alex D; Chataway, Tim K; Jackson, Michael W; Wang, Jing J; Gordon, Tom P

    2016-04-01

    The structures of epitopes bound by autoantibodies against RNA-protein complexes have been well-defined over several decades, but little is known of the clonality, immunoglobulin (Ig) variable (V) gene usage and mutational status of the autoantibodies themselves at the level of the secreted (serum) proteome. A novel proteomic workflow is presented based on affinity purification of specific Igs from serum, high-resolution two-dimensional gel electrophoresis, and de novo and database-driven sequencing of V-region proteins by mass spectrometry. Analysis of anti-Ro52/Ro60/La proteomes in primary Sjögren's syndrome (SS) and anti-Sm and anti-ribosomal P proteomes in systemic lupus erythematosus (SLE) has revealed that these antibody responses are dominated by restricted sets of public (shared) clonotypes, consistent with common pathways of production across unrelated individuals. The discovery of shared sets of specific V-region peptides can be exploited for diagnostic biomarkers in targeted mass spectrometry platforms and for tracking and removal of pathogenic clones. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

    Science.gov (United States)

    Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

    2008-02-01

    Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

  6. Identification of Hip BMD Loss and Fracture Risk Markers Through Population-Based Serum Proteomics: HIP BMD LOSS & FRACTURE RISK MARKERS BY POPULATION-BASED SERUM PROTEOMICS

    Energy Technology Data Exchange (ETDEWEB)

    Nielson, Carrie; Wiedrick, Jack; Shen, Jian; Jacobs, Jon M.; Baker, Erin M.; Baraff, Aaron; Piehowski, Paul D.; Lee, Christine; Baratt, Arie; Petyuk, Vladislav A.; Mcweeney, Shannon K.; Lim, Jeong Youn; Bauer, Douglas C.; Lane, Nancy E.; Cawthon, Peggy M.; Smith, Richard D.; Lapidus, Jodi; Orwoll, Eric S.

    2017-04-06

    Accelerated bone loss significantly increases the risk of osteoporosis and fracture. The mechanisms underlying bone loss remain incompletely understood, and there are few available biomarkers. We utilized a novel proteomics approach to identify serum peptides and proteins associated with bone loss in 1967 older men who were randomly chosen from the Osteoporotic Fracture in Men Study (MrOS study) (age ≥ 65 yrs). Men had 2-3 measures of femoral neck BMD over an average follow-up of 4.6 years. Change in BMD was estimated and then categorized into three groups: maintained BMD (n=453), expected loss (n=1185) and accelerated loss (n=237). A liquid chromatography–ion mobility separation-mass spectrometry (LC-IMS-MS) proteomics platform was used to identify and quantify peptides from serum proteins. The whole cohort was randomly divided into discovery (N= 960) and validation (N= 915) sub-cohorts. Linear regression models and a random forest approach were used to discover differentially abundant individual peptides and a proteomic signature that distinguished individuals with accelerated bone loss from those who maintained BMD. Network analyses were performed using the MetaCore knowledgebase. We identified 12 peptides that were associated with BMD loss in both discovery (P< 0.1 FDR) and replication sub-cohorts (P<0.05). Those 12 peptides mapped to the following proteins: ALS, LYVE1, RNAS1, C2, ICOSL, C163A, C7, HEMO, CD14, CERU, CRAC1 and CD59. Meta-analysis of peptidesassociated with bone loss identified 6 additional proteins including GRP78, IGF-2, SHBG, ENPP2, IBP2 and IBP6. We also identified a proteomic signature that was predictive of BMD loss with a discriminative value similar to serum bone marker carboxy-terminal collagen crosslink peptide (CTX). Interestingly, combining the proteomic signature with CTX significantly improved the ability to discriminate men with accelerated loss. In summary, we have identified potential new biomarkers for bone loss that provide

  7. Power of Proteomics in Linking Oxidative Stress and Female Infertility

    Science.gov (United States)

    Gupta, Sajal; Sharma, Rakesh; Agarwal, Ashok

    2014-01-01

    Endometriosis, PCOS, and unexplained infertility are currently the most common diseases rendering large numbers of women infertile worldwide. Oxidative stress, due to its deleterious effects on proteins and nucleic acids, is postulated to be the one of the important mechanistic pathways in differential expression of proteins and in these diseases. The emerging field of proteomics has allowed identification of proteins involved in cell cycle, as antioxidants, extracellular matrix (ECM), cytoskeleton, and their linkage to oxidative stress in female infertility related diseases. The aim of this paper is to assess the association of oxidative stress and protein expression in the reproductive microenvironments such as endometrial fluid, peritoneal fluid, and follicular fluid, as well as reproductive tissues and serum. The review also highlights the literature that proposes the use of the fertility related proteins as potential biomarkers for noninvasive and early diagnosis of the aforementioned diseases rather than utilizing the more invasive methods used currently. The review will highlight the power of proteomic profiles identified in infertility related disease conditions and their linkage with underlying oxidative stress. The power of proteomics will be reviewed with regard to eliciting molecular mechanisms for early detection and management of these infertility related conditions. PMID:24900998

  8. Power of Proteomics in Linking Oxidative Stress and Female Infertility

    Directory of Open Access Journals (Sweden)

    Sajal Gupta

    2014-01-01

    Full Text Available Endometriosis, PCOS, and unexplained infertility are currently the most common diseases rendering large numbers of women infertile worldwide. Oxidative stress, due to its deleterious effects on proteins and nucleic acids, is postulated to be the one of the important mechanistic pathways in differential expression of proteins and in these diseases. The emerging field of proteomics has allowed identification of proteins involved in cell cycle, as antioxidants, extracellular matrix (ECM, cytoskeleton, and their linkage to oxidative stress in female infertility related diseases. The aim of this paper is to assess the association of oxidative stress and protein expression in the reproductive microenvironments such as endometrial fluid, peritoneal fluid, and follicular fluid, as well as reproductive tissues and serum. The review also highlights the literature that proposes the use of the fertility related proteins as potential biomarkers for noninvasive and early diagnosis of the aforementioned diseases rather than utilizing the more invasive methods used currently. The review will highlight the power of proteomic profiles identified in infertility related disease conditions and their linkage with underlying oxidative stress. The power of proteomics will be reviewed with regard to eliciting molecular mechanisms for early detection and management of these infertility related conditions.

  9. Current status of fluid biomarkers in mild traumatic brain injury

    Science.gov (United States)

    Kulbe, Jacqueline R.; Geddes, James W.

    2015-01-01

    Mild traumatic brain injury (mTBI) affects millions of people annually and is difficult to diagnose. Mild injury is insensitive to conventional imaging techniques and diagnoses are often made using subjective criteria such as self-reported symptoms. Many people who sustain a mTBI develop persistent post-concussive symptoms. Athletes and military personnel are at great risk for repeat injury which can result in second impact syndrome or chronic traumatic encephalopathy. An objective and quantifiable measure, such as a serum biomarker, is needed to aid in mTBI diagnosis, prognosis, return to play/duty assessments, and would further elucidate mTBI pathophysiology. The majority of TBI biomarker research focuses on severe TBI with few studies specific to mild injury. Most studies use a hypothesis-driven approach, screening biofluids for markers known to be associated with TBI pathophysiology. This approach has yielded limited success in identifying markers that can be used clinically, additional candidate biomarkers are needed. Innovative and unbiased methods such as proteomics, microRNA arrays, urinary screens, autoantibody identification and phage display would complement more traditional approaches to aid in the discovery of novel mTBI biomarkers. PMID:25981889

  10. Improvement of a sample preparation method assisted by sodium deoxycholate for mass-spectrometry-based shotgun membrane proteomics.

    Science.gov (United States)

    Lin, Yong; Lin, Haiyan; Liu, Zhonghua; Wang, Kunbo; Yan, Yujun

    2014-11-01

    In current shotgun-proteomics-based biological discovery, the identification of membrane proteins is a challenge. This is especially true for integral membrane proteins due to their highly hydrophobic nature and low abundance. Thus, much effort has been directed at sample preparation strategies such as use of detergents, chaotropes, and organic solvents. We previously described a sample preparation method for shotgun membrane proteomics, the sodium deoxycholate assisted method, which cleverly circumvents many of the challenges associated with traditional sample preparation methods. However, the method is associated with significant sample loss due to the slightly weaker extraction/solubilization ability of sodium deoxycholate when it is used at relatively low concentrations such as 1%. Hence, we present an enhanced sodium deoxycholate sample preparation strategy that first uses a high concentration of sodium deoxycholate (5%) to lyse membranes and extract/solubilize hydrophobic membrane proteins, and then dilutes the detergent to 1% for a more efficient digestion. We then applied the improved method to shotgun analysis of proteins from rat liver membrane enriched fraction. Compared with other representative sample preparation strategies including our previous sodium deoxycholate assisted method, the enhanced sodium deoxycholate method exhibited superior sensitivity, coverage, and reliability for the identification of membrane proteins particularly those with high hydrophobicity and/or multiple transmembrane domains. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Eosinophilia in routine blood samples as a biomarker for solid tumor development

    DEFF Research Database (Denmark)

    Andersen, Christen Bertel L; Siersma, V.D.; Hasselbalch, H.C.

    2014-01-01

    eosinophilia in routine blood samples as a potential biomarker of solid tumor development in a prospective design. MATERIAL AND METHODS: From the Copenhagen Primary Care Differential Count (CopDiff) Database, we identified 356 196 individuals with at least one differential cell count (DIFF) encompassing...... was increased with mild eosinophilia [OR 1.93 (CI 1.29-2.89), p = 0.0013]. No associations with eosinophilia were observed for the remaining solid cancers. CONCLUSION: We demonstrate that eosinophilia in routine blood samples associates with an increased risk of bladder cancer. Our data emphasize...... that additional preclinical studies are needed in order to shed further light on the role of eosinophils in carcinogenesis, where it is still unknown whether the cells contribute to tumor immune surveillance or neoplastic evolution....

  12. Bacterial membrane proteomics.

    Science.gov (United States)

    Poetsch, Ansgar; Wolters, Dirk

    2008-10-01

    About one quarter to one third of all bacterial genes encode proteins of the inner or outer bacterial membrane. These proteins perform essential physiological functions, such as the import or export of metabolites, the homeostasis of metal ions, the extrusion of toxic substances or antibiotics, and the generation or conversion of energy. The last years have witnessed completion of a plethora of whole-genome sequences of bacteria important for biotechnology or medicine, which is the foundation for proteome and other functional genome analyses. In this review, we discuss the challenges in membrane proteome analysis, starting from sample preparation and leading to MS-data analysis and quantification. The current state of available proteomics technologies as well as their advantages and disadvantages will be described with a focus on shotgun proteomics. Then, we will briefly introduce the most abundant proteins and protein families present in bacterial membranes before bacterial membrane proteomics studies of the last years will be presented. It will be shown how these works enlarged our knowledge about the physiological adaptations that take place in bacteria during fine chemical production, bioremediation, protein overexpression, and during infections. Furthermore, several examples from literature demonstrate the suitability of membrane proteomics for the identification of antigens and different pathogenic strains, as well as the elucidation of membrane protein structure and function.

  13. Development stage-specific proteomic profiling uncovers small, lineage specific proteins most abundant in the Aspergillus Fumigatus conidial proteome

    Directory of Open Access Journals (Sweden)

    Suh Moo-Jin

    2012-04-01

    Full Text Available Abstract Background The pathogenic mold Aspergillus fumigatus is the most frequent infectious cause of death in severely immunocompromised individuals such as leukemia and bone marrow transplant patients. Germination of inhaled conidia (asexual spores in the host is critical for the initiation of infection, but little is known about the underlying mechanisms of this process. Results To gain insights into early germination events and facilitate the identification of potential stage-specific biomarkers and vaccine candidates, we have used quantitative shotgun proteomics to elucidate patterns of protein abundance changes during early fungal development. Four different stages were examined: dormant conidia, isotropically expanding conidia, hyphae in which germ tube emergence has just begun, and pre-septation hyphae. To enrich for glycan-linked cell wall proteins we used an alkaline cell extraction method. Shotgun proteomic resulted in the identification of 375 unique gene products with high confidence, with no evidence for enrichment of cell wall-immobilized and secreted proteins. The most interesting discovery was the identification of 52 proteins enriched in dormant conidia including 28 proteins that have never been detected in the A. fumigatus conidial proteome such as signaling protein Pil1, chaperones BipA and calnexin, and transcription factor HapB. Additionally we found many small, Aspergillus specific proteins of unknown function including 17 hypothetical proteins. Thus, the most abundant protein, Grg1 (AFUA_5G14210, was also one of the smallest proteins detected in this study (M.W. 7,367. Among previously characterized proteins were melanin pigment and pseurotin A biosynthesis enzymes, histones H3 and H4.1, and other proteins involved in conidiation and response to oxidative or hypoxic stress. In contrast, expanding conidia, hyphae with early germ tubes, and pre-septation hyphae samples were enriched for proteins responsible for

  14. High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples.

    Science.gov (United States)

    Reiser, Vladimír; Smith, Ryan C; Xue, Jiyan; Kurtz, Marc M; Liu, Rong; Legrand, Cheryl; He, Xuanmin; Yu, Xiang; Wong, Peggy; Hinchcliffe, John S; Tanen, Michael R; Lazar, Gloria; Zieba, Renata; Ichetovkin, Marina; Chen, Zhu; O'Neill, Edward A; Tanaka, Wesley K; Marton, Matthew J; Liao, Jason; Morris, Mark; Hailman, Eric; Tokiwa, George Y; Plump, Andrew S

    2011-11-01

    With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD). We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured. The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting. The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

  15. Virtual Labs in proteomics: new E-learning tools.

    Science.gov (United States)

    Ray, Sandipan; Koshy, Nicole Rachel; Reddy, Panga Jaipal; Srivastava, Sanjeeva

    2012-05-17

    Web-based educational resources have gained enormous popularity recently and are increasingly becoming a part of modern educational systems. Virtual Labs are E-learning platforms where learners can gain the experience of practical experimentation without any direct physical involvement on real bench work. They use computerized simulations, models, videos, animations and other instructional technologies to create interactive content. Proteomics being one of the most rapidly growing fields of the biological sciences is now an important part of college and university curriculums. Consequently, many E-learning programs have started incorporating the theoretical and practical aspects of different proteomic techniques as an element of their course work in the form of Video Lectures and Virtual Labs. To this end, recently we have developed a Virtual Proteomics Lab at the Indian Institute of Technology Bombay, which demonstrates different proteomics techniques, including basic and advanced gel and MS-based protein separation and identification techniques, bioinformatics tools and molecular docking methods, and their applications in different biological samples. This Tutorial will discuss the prominent Virtual Labs featuring proteomics content, including the Virtual Proteomics Lab of IIT-Bombay, and E-resources available for proteomics study that are striving to make proteomic techniques and concepts available and accessible to the student and research community. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 14). Details can be found at: http://www.proteomicstutorials.org/. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. A novel approach to the study of the functional proteome in breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Hennessy, Bryan; Lu, Yiling; Gonzalez-Angulo, Ana Maria; Carey, Mark; Myhre, Simen; Ju, Zhenlin; Coombes, Kevin; Meric-Bernstam, Funda; Bedrosian, Isabelle; Davies, Michael A.; Siwak, Doris; Agarwal, Roshan; Zhang, Fan; Overgaard, Jens; Alsner, Jan; Neve, Richard M.; Kuo, Wen-Lin; Gray, Joe W.; Borresen-Dale, Anne-Lise; Mills, Gordon B.

    2008-10-10

    Factors including intratumoral heterogeneity and variability in tissue handling potentially hamper the application of reverse phase protein arrays (RPPA) to study of the solid tumor functional proteome. To address this, RPPA was applied to quantify protein expression and activation in 233 human breast tumors and 52 breast cancer cell lines. Eighty-two antibodies that recognize kinase and steroid signaling events and their effectors were validated for RPPA because of the importance of these proteins to breast carcinogenesis. Reproducibility in replicate lysates was excellent. Intratumoral protein expression was less variable than intertumoral expression, and prognostic biomarkers retained the ability to accurately predict patient outcomes when analyzed in different tumor sites. Although 21/82 total and phosphoproteins demonstrated time-dependent instability in breast tumors that were placed at room temperature after surgical excision for 24 hours prior to freezing, the functional proteomic 'fingerprint' was robust in most tumors until at least 24 hours before tissue freezing. Correlations between RPPA and immunohistochemistry were statistically significant for assessed proteins but RPPA demonstrated a superior dynamic range and detected, for example, an 866-fold difference in estrogen receptor alpha level across breast tumors. Protein and mRNA levels were concordant (at p {le} 0.05) for 41.3% and 61.1% of assayed targets in breast tumors and cell lines, respectively. Several phosphorylation and cleavage products did not correlate with the corresponding transcript levels. In conclusion, the reproducibility of RPPA, the faithfulness with which proteins and the functional proteomic 'fingerprint' are preserved in different sections derived from primary breast tumors, and the surprising stability of this 'fingerprint' with increasing time to freezing all facilitate the application of RPPA to the accurate study of protein biomarkers in non

  17. Human Brain Proteome Project - 12th HUPO BPP Workshop. 26 September 2009, Toronto, Canada.

    Science.gov (United States)

    Gröttrup, Bernd; Eisenacher, Martin; Stephan, Christian; Marcus, Katrin; Lee, Bonghee; Meyer, Helmut E; Park, Young Mok

    2010-06-01

    The HUPO Brain Proteome Project (HUPO BPP) held its 12th workshop in Toronto on 26 September 2009 prior to the HUPO VIII World Congress. The principal aim of this project is to obtain a better understanding of neurodiseases and ageing, with the ultimate objective of discovering prognostic and diagnostic biomarkers, in addition to the development of novel diagnostic techniques and new medications. The attendees came together to discuss progress in the human clinical neuroproteomics and to define the needs and guidelines required for more advanced proteomic approaches.

  18. Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance : Simultaneous Component Analysis

    NARCIS (Netherlands)

    Mitra, V.; Govorukhina, N.; Zwanenburg, G.; Hoefsloot, H.; Westra, I.; Smilde, A.; Reijmers, T.; van der Zee, A.G.J.; Suits, F.; Bischoff, R.; Horvatovich, P.

    2016-01-01

    Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome

  19. Single-Nucleotide Variations in Cardiac Arrhythmias: Prospects for Genomics and Proteomics Based Biomarker Discovery and Diagnostics

    Directory of Open Access Journals (Sweden)

    Ayman Abunimer

    2014-03-01

    Full Text Available Cardiovascular diseases are a large contributor to causes of early death in developed countries. Some of these conditions, such as sudden cardiac death and atrial fibrillation, stem from arrhythmias—a spectrum of conditions with abnormal electrical activity in the heart. Genome-wide association studies can identify single nucleotide variations (SNVs that may predispose individuals to developing acquired forms of arrhythmias. Through manual curation of published genome-wide association studies, we have collected a comprehensive list of 75 SNVs associated with cardiac arrhythmias. Ten of the SNVs result in amino acid changes and can be used in proteomic-based detection methods. In an effort to identify additional non-synonymous mutations that affect the proteome, we analyzed the post-translational modification S-nitrosylation, which is known to affect cardiac arrhythmias. We identified loss of seven known S-nitrosylation sites due to non-synonymous single nucleotide variations (nsSNVs. For predicted nitrosylation sites we found 1429 proteins where the sites are modified due to nsSNV. Analysis of the predicted S-nitrosylation dataset for over- or under-representation (compared to the complete human proteome of pathways and functional elements shows significant statistical over-representation of the blood coagulation pathway. Gene Ontology (GO analysis displays statistically over-represented terms related to muscle contraction, receptor activity, motor activity, cystoskeleton components, and microtubule activity. Through the genomic and proteomic context of SNVs and S-nitrosylation sites presented in this study, researchers can look for variation that can predispose individuals to cardiac arrhythmias. Such attempts to elucidate mechanisms of arrhythmia thereby add yet another useful parameter in predicting susceptibility for cardiac diseases.

  20. Integrated transcriptomic and proteomic evaluation of gentamicin nephrotoxicity in rats

    International Nuclear Information System (INIS)

    Com, Emmanuelle; Boitier, Eric; Marchandeau, Jean-Pierre; Brandenburg, Arnd; Schroeder, Susanne; Hoffmann, Dana; Mally, Angela; Gautier, Jean-Charles

    2012-01-01

    Gentamicin is an aminoglycoside antibiotic, which induces renal tubular necrosis in rats. In the context of the European InnoMed PredTox project, transcriptomic and proteomic studies were performed to provide new insights into the molecular mechanisms of gentamicin-induced nephrotoxicity. Male Wistar rats were treated with 25 and 75 mg/kg/day subcutaneously for 1, 3 and 14 days. Histopathology observations showed mild tubular degeneration/necrosis and regeneration and moderate mononuclear cell infiltrate after long-term treatment. Transcriptomic data indicated a strong treatment-related gene expression modulation in kidney and blood cells at the high dose after 14 days of treatment, with the regulation of 463 and 3241 genes, respectively. Of note, the induction of NF-kappa B pathway via the p38 MAPK cascade in the kidney, together with the activation of T-cell receptor signaling in blood cells were suggestive of inflammatory processes in relation with the recruitment of mononuclear cells in the kidney. Proteomic results showed a regulation of 163 proteins in kidney at the high dose after 14 days of treatment. These protein modulations were suggestive of a mitochondrial dysfunction with impairment of cellular energy production, induction of oxidative stress, an effect on protein biosynthesis and on cellular assembly and organization. Proteomic results also provided clues for potential nephrotoxicity biomarkers such as AGAT and PRBP4 which were strongly modulated in the kidney. Transcriptomic and proteomic data turned out to be complementary and their integration gave a more comprehensive insight into the putative mode of nephrotoxicity of gentamicin which was in accordance with histopathological findings. -- Highlights: ► Gentamicin induces renal tubular necrosis in rats. ► The mechanisms of gentamicin nephrotoxicity remain still elusive. ► Transcriptomic and proteomic analyses were performed to study this toxicity in rats. ► Transcriptomic and proteomic

  1. Metabolomics approaches for discovering biomarkers of drug-induced hepatotoxicity and nephrotoxicity

    International Nuclear Information System (INIS)

    Beger, Richard D.; Sun, Jinchun; Schnackenberg, Laura K.

    2010-01-01

    Hepatotoxicity and nephrotoxicity are two major reasons that drugs are withdrawn post-market, and hence it is of major concern to both the FDA and pharmaceutical companies. The number of cases of serious adverse effects (SAEs) in marketed drugs has climbed faster than the number of total drug prescriptions issued. In some cases, preclinical animal studies fail to identify the potential toxicity of a new chemical entity (NCE) under development. The current clinical chemistry biomarkers of liver and kidney injury are inadequate in terms of sensitivity and/or specificity, prompting the need to discover new translational specific biomarkers of organ injury. Metabolomics along with genomics and proteomics technologies have the capability of providing translational diagnostic and prognostic biomarkers specific for early stages of liver and kidney injury. Metabolomics has several advantages over the other omics platforms such as ease of sample preparation, data acquisition and use of biofluids collected through minimally invasive procedures in preclinical and clinical studies. The metabolomics platform is reviewed with particular emphasis on applications involving drug-induced hepatotoxicity and nephrotoxicity. Analytical platforms for metabolomics, chemometrics for mining metabolomics data and the applications of the metabolomics technologies are covered in detail with emphasis on recent work in the field.

  2. Biomarkers in cancer screening: a public health perspective.

    Science.gov (United States)

    Srivastava, Sudhir; Gopal-Srivastava, Rashmi

    2002-08-01

    The last three decades have witnessed a rapid advancement and diffusion of technology in health services. Technological innovations have given health service providers the means to diagnose and treat an increasing number of illnesses, including cancer. In this effort, research on biomarkers for cancer detection and risk assessment has taken a center stage in our effort to reduce cancer deaths. For the first time, scientists have the technologies to decipher and understand these biomarkers and to apply them to earlier cancer detection. By identifying people at high risk of developing cancer, it would be possible to develop intervention efforts on prevention rather than treatment. Once fully developed and validated, then the regular clinical use of biomarkers in early detection and risk assessment will meet nationally recognized health care needs: detection of cancer at its earliest stage. The dramatic rise in health care costs in the past three decades is partly related to the proliferation of new technologies. More recent analysis indicates that technological change, such as new procedures, products and capabilities, is the primary explanation of the historical increase in expenditure. Biomarkers are the new entrants in this competing environment. Biomarkers are considered as a competing, halfway or add-on technology. Technology such as laboratory tests of biomarkers will cost less compared with computed tomography (CT) scans and other radiographs. However, biomarkers for earlier detection and risk assessment have not achieved the level of confidence required for clinical applications. This paper discusses some issues related to biomarker development, validation and quality assurance. Some data on the trends of diagnostic technologies, proteomics and genomics are presented and discussed in terms of the market share. Eventually, the use of biomarkers in health care could reduce cost by providing noninvasive, sensitive and reliable assays at a fraction of the cost of

  3. Biomarker Analysis of Samples Visually Identified as Microbial in the Eocene Green River Formation: An Analogue for Mars.

    Science.gov (United States)

    Olcott Marshall, Alison; Cestari, Nicholas A

    2015-09-01

    One of the major exploration targets for current and future Mars missions are lithofacies suggestive of biotic activity. Although such lithofacies are not confirmation of biotic activity, they provide a way to identify samples for further analyses. To test the efficacy of this approach, we identified carbonate samples from the Eocene Green River Formation as "microbial" or "non-microbial" based on the macroscale morphology of their laminations. These samples were then crushed and analyzed by gas chromatography/mass spectroscopy (GC/MS) to determine their lipid biomarker composition. GC/MS analysis revealed that carbonates visually identified as "microbial" contained a higher concentration of more diverse biomarkers than those identified as "non-microbial," suggesting that this could be a viable detection strategy for selecting samples for further analysis or caching on Mars.

  4. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  5. Global Proteome Analysis of the NCI-60 Cell Line Panel

    Directory of Open Access Journals (Sweden)

    Amin Moghaddas Gholami

    2013-08-01

    Full Text Available The NCI-60 cell line collection is a very widely used panel for the study of cellular mechanisms of cancer in general and in vitro drug action in particular. It is a model system for the tissue types and genetic diversity of human cancers and has been extensively molecularly characterized. Here, we present a quantitative proteome and kinome profile of the NCI-60 panel covering, in total, 10,350 proteins (including 375 protein kinases and including a core cancer proteome of 5,578 proteins that were consistently quantified across all tissue types. Bioinformatic analysis revealed strong cell line clusters according to tissue type and disclosed hundreds of differentially regulated proteins representing potential biomarkers for numerous tumor properties. Integration with public transcriptome data showed considerable similarity between mRNA and protein expression. Modeling of proteome and drug-response profiles for 108 FDA-approved drugs identified known and potential protein markers for drug sensitivity and resistance. To enable community access to this unique resource, we incorporated it into a public database for comparative and integrative analysis (http://wzw.tum.de/proteomics/nci60.

  6. Proteomic profiling of white muscle from freshwater catfish Rita rita.

    Science.gov (United States)

    Mohanty, Bimal Prasanna; Mitra, Tandrima; Banerjee, Sudeshna; Bhattacharjee, Soma; Mahanty, Arabinda; Ganguly, Satabdi; Purohit, Gopal Krishna; Karunakaran, Dhanasekar; Mohanty, Sasmita

    2015-06-01

    Muscle tissues contribute 34-48 % of the total body mass in fish. Proteomic analysis enables better understanding of the skeletal muscle physiology and metabolism. A proteome map reflects the general fingerprinting of the fish species and has the potential to identify novel proteins which could serve as biomarkers for many aspects of aquaculture including fish physiology and growth, flesh quality, food safety and aquatic environmental monitoring. The freshwater catfish Rita rita of the family Bagridae inhabiting the tropical rivers and estuaries is an important food fish with high nutritive value and is also considered a species of choice in riverine pollution monitoring. Omics information that could enhance utility of this species in molecular research is meager. Therefore, in the present study, proteomic analysis of Rita rita muscle has been carried out and functional genomics data have been generated. A reference muscle proteome has been developed, and 23 protein spots, representing 18 proteins, have been identified by MALDI-TOF/TOF-MS and LC-MS/MS. Besides, transcript information on a battery of heat shock proteins (Hsps) has been generated. The functional genomics information generated could act as the baseline data for further molecular research on this species.

  7. Proteomic profiling of urine for the detection of colon cancer

    Directory of Open Access Journals (Sweden)

    Wakelam Michael JO

    2008-06-01

    Full Text Available Abstract Background Colorectal cancer is the second most common cause of cancer related death in the developed world. To date, no blood or stool biomarkers with both high sensitivity and specificity for potentially curable early stage disease have been validated for clinical use. SELDI and MALDI profiling are being used increasingly to search for biomarkers in both blood and urine. Both techniques provide information predominantly on the low molecular weight proteome ( Results We collected urine from 67 patients with colorectal cancer and 72 non-cancer control subjects, diluted to a constant protein concentration and generated MALDI and SELDI spectra. The intensities of 19 peaks differed significantly between cancer and non-cancer patients by both t-tests and after adjusting for confounders using multiple linear regressions. Logistic regression classifiers based on peak intensities identified colorectal cancer with up to 78% sensitivity at 87% specificity. We identified and independently quantified 3 of the discriminatory peaks using synthetic stable isotope peptides (an 1885 Da fragment of fibrinogen and hepcidin-20 or ELISA (β2-microglobulin. Conclusion Changes in the urine proteome may aid in the early detection of colorectal cancer.

  8. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

    Boot, Rolf G; van Breemen, Mariëlle J; Wegdam, Wouter

    2009-01-01

    Gaucher disease is an inherited lysosomal storage disorder, characterized by massive accumulation of glucosylceramide-laden macrophages in the spleen, liver and bone marrow as a consequence of deficient activity of glucocerebrosidase. Gaucher disease has been the playground to develop new therape...... in clinical management of Gaucher patients are discussed. Moreover, the use of several modern proteomic technologies for the identification of Gaucher biomarkers is reviewed....

  9. HCC Biomarkers in China and Taiwan

    Directory of Open Access Journals (Sweden)

    Regina M. Santella

    2007-02-01

    Full Text Available

    A number of different types of biomarkers have been used to understand the etiology and progression of hepatocellular cancer (HCC. Perhaps the most well known are the serum/ plasma markers of HBV or HCV infection. These markers include analysis of viral DNA or proteins or antibodies produced against the viral proteins. HBV surface antigen (HBsAg is most frequently used to determine chronic infection with high or low viral replication, while HBeAg is a measure of chronic infection with high viral replication. Analysis of antibodies includes measurement of anti-HBV core antigen, anti-HBV e antigen and anti-HBsAg. The response to immunization can be monitored by analysis of anti-HBsAg. The other major classes of biomarkers used in studies of HCC are biomarkers of exposure to environmental, lifestyle or dietary carcinogens, biomarkers of oxidative stress and early biologic response. In addition, studies of genetic susceptibility have studied polymorphisms in a number of pathways and their role in HCC risk. The biomarkers of exposure include the measurement of carcinogens in urine and carcinogen-DNA and protein adducts. Examples are measurement of aflatoxin and polycyclic aromatic hydrocarbon metabolites, and DNA and protein adducts.

    Biomarkers of oxidative stress include urinary isoprostanes and 8-oxodeoxyguanosine and oxidized plasma proteins. Most of these assays are immunologic although the use of high performance liquid chromatograph (HPLC as well as gas chromatography/mass spectroscopy (GC/MS have been utilized. In nested case-control studies, many of these markers are associated with elevated risk. For example, elevated aflatoxin and polycyclic aromatic hydrocarbon-albumin adducts, aflatoxin metabolites in urine and urinary isoprostanes were observed in baseline samples from

  10. Systemic effects of ionizing radiation at the proteome and metabolome levels in the blood of cancer patients treated with radiotherapy: the influence of inflammation and radiation toxicity.

    Science.gov (United States)

    Jelonek, Karol; Pietrowska, Monika; Widlak, Piotr

    2017-07-01

    Blood is the most common replacement tissue used to study systemic responses of organisms to different types of pathological conditions and environmental insults. Local irradiation during cancer radiotherapy induces whole body responses that can be observed at the blood proteome and metabolome levels. Hence, comparative blood proteomics and metabolomics are emerging approaches used in the discovery of radiation biomarkers. These techniques enable the simultaneous measurement of hundreds of molecules and the identification of sets of components that can discriminate different physiological states of the human body. Radiation-induced changes are affected by the dose and volume of irradiated tissues; hence, the molecular composition of blood is a hypothetical source of biomarkers for dose assessment and the prediction and monitoring of systemic responses to radiation. This review aims to provide a comprehensive overview on the available evidence regarding molecular responses to ionizing radiation detected at the level of the human blood proteome and metabolome. It focuses on patients exposed to radiation during cancer radiotherapy and emphasizes effects related to radiation-induced toxicity and inflammation. Systemic responses to radiation detected at the blood proteome and metabolome levels are primarily related to the intensity of radiation-induced toxicity, including inflammatory responses. Thus, several inflammation-associated molecules can be used to monitor or even predict radiation-induced toxicity. However, these abundant molecular features have a rather limited applicability as universal biomarkers for dose assessment, reflecting the individual predisposition of the immune system and tissue-specific mechanisms involved in radiation-induced damage.

  11. Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.

    Directory of Open Access Journals (Sweden)

    Yansheng Liu

    Full Text Available Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA and Multiple reaction monitoring (MRM assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG and Leucine-rich alpha-2-glycoprotein (LRG1, two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

  12. Creating a human brain proteome atlas--13th HUPO BPP Workshop March 30-31, 2010, Ochang, Korea.

    Science.gov (United States)

    Gröttrup, Bernd; Stephan, Christian; Marcus, Katrin; Grinberg, Lea T; Wiltfang, Jens; Lee, Sang K; Kim, Young H; Meyer, Helmut E; Park, Young M

    2011-07-01

    The HUPO Brain Proteome Project (HUPO BPP) held its 13th workshop in Ochang from March 30th to 31st, 2010 prior to the Korean HUPO 10th Annual International Proteomics Conference. The principal aim of this project is to obtain a better understanding of neurodiseases and aging with the ultimate objective of discovering prognostic and diagnostic biomarkers, in addition to the development of novel diagnostic techniques and new medications. The attendees came together to discuss progress in the clinical neuroproteomics of human and to define the needs and guidelines required for more advanced proteomics approaches. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Network analysis of quantitative proteomics on asthmatic bronchi: effects of inhaled glucocorticoid treatment

    Directory of Open Access Journals (Sweden)

    Sihlbom Carina

    2011-09-01

    Full Text Available Abstract Background Proteomic studies of respiratory disorders have the potential to identify protein biomarkers for diagnosis and disease monitoring. Utilisation of sensitive quantitative proteomic methods creates opportunities to determine individual patient proteomes. The aim of the current study was to determine if quantitative proteomics of bronchial biopsies from asthmatics can distinguish relevant biological functions and whether inhaled glucocorticoid treatment affects these functions. Methods Endobronchial biopsies were taken from untreated asthmatic patients (n = 12 and healthy controls (n = 3. Asthmatic patients were randomised to double blind treatment with either placebo or budesonide (800 μg daily for 3 months and new biopsies were obtained. Proteins extracted from the biopsies were digested and analysed using isobaric tags for relative and absolute quantitation combined with a nanoLC-LTQ Orbitrap mass spectrometer. Spectra obtained were used to identify and quantify proteins. Pathways analysis was performed using Ingenuity Pathway Analysis to identify significant biological pathways in asthma and determine how the expression of these pathways was changed by treatment. Results More than 1800 proteins were identified and quantified in the bronchial biopsies of subjects. The pathway analysis revealed acute phase response signalling, cell-to-cell signalling and tissue development associations with proteins expressed in asthmatics compared to controls. The functions and pathways associated with placebo and budesonide treatment showed distinct differences, including the decreased association with acute phase proteins as a result of budesonide treatment compared to placebo. Conclusions Proteomic analysis of bronchial biopsy material can be used to identify and quantify proteins using highly sensitive technologies, without the need for pooling of samples from several patients. Distinct pathophysiological features of asthma can be

  14. The Impact of Mobile Phone Dependency on Health and Biomarkers in a Greek University Student Sample

    OpenAIRE

    Eugenia Minasidou; Athanasios Mastrokostas; Maria Gkrizioti; Faidra Eleftheriou; Thalia Bellali

    2015-01-01

    Introduction: Mobile phone use can be addictive for the young. However, little is known about the behavioral and biological effects of this addiction among the student population. Aim: The purpose of this study was to explore the effects of mobile phone use on the health behaviors and specific biomarkers in a sample of Greek students. Methods: Sample included 104 Nursing students from a stratified randomised sample. In 30 ran- domly selected out of the 104 students, melatonin and total antiox...

  15. Label-Free Quantitative Analysis of Mitochondrial Proteomes Using the Multienzyme Digestion-Filter Aided Sample Preparation (MED-FASP) and "Total Protein Approach".

    Science.gov (United States)

    Wiśniewski, Jacek R

    2017-01-01

    Determination of proteome composition and measuring of changes in protein titers provide important information with a substantial value for studying mitochondria.This chapter describes a workflow for the quantitative analysis of mitochondrial proteome with a focus on sample preparation and quantitative analysis of the data. The workflow involves the multienzyme digestion-filter aided sample preparation (MED-FASP) protocol enabling efficient extraction of proteins and high rate of protein-to-peptide conversion. Consecutive protein digestion with Lys C and trypsin enables generation of peptide fractions with minimal overlap, largely increases the number of identified proteins, and extends their sequence coverage. Abundances of proteins identified by multiple peptides can be assessed by the "Total Protein Approach."

  16. Tools for monitoring system suitability in LC MS/MS centric proteomic experiments.

    Science.gov (United States)

    Bereman, Michael S

    2015-03-01

    With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma

    Science.gov (United States)

    Ueda, Koji; Saichi, Naomi; Takami, Sachiko; Kang, Daechun; Toyama, Atsuhiko; Daigo, Yataro; Ishikawa, Nobuhisa; Kohno, Nobuoki; Tamura, Kenji; Shuin, Taro; Nakayama, Masato; Sato, Taka-Aki; Nakamura, Yusuke; Nakagawa, Hidewaki

    2011-01-01

    The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens. PMID:21533267

  18. Characterization of the canine urinary proteome.

    Science.gov (United States)

    Brandt, Laura E; Ehrhart, E J; Scherman, Hataichanok; Olver, Christine S; Bohn, Andrea A; Prenni, Jessica E

    2014-06-01

    Urine is an attractive biofluid for biomarker discovery as it is easy and minimally invasive to obtain. While numerous studies have focused on the characterization of human urine, much less research has focused on canine urine. The objectives of this study were to characterize the universal canine urinary proteome (both soluble and exosomal), to determine the overlap between the canine proteome and a representative human urinary proteome study, to generate a resource for future canine studies, and to determine the suitability of the dog as a large animal model for human diseases. The soluble and exosomal fractions of normal canine urine were characterized using liquid chromatography tandem mass spectrometry (LC-MS/MS). Biological Networks Gene Ontology (BiNGO) software was utilized to assign the canine urinary proteome to respective Gene Ontology categories, such as Cellular Component, Molecular Function, and Biological Process. Over 500 proteins were confidently identified in normal canine urine. Gene Ontology analysis revealed that exosomal proteins were largely derived from an intracellular location, while soluble proteins included both extracellular and membrane proteins. Exosome proteins were assigned to metabolic processes and localization, while soluble proteins were primarily annotated to specific localization processes. Several proteins identified in normal canine urine have previously been identified in human urine where these proteins are related to various extrarenal and renal diseases. The results of this study illustrate the potential of the dog as an animal model for human disease states and provide the framework for future studies of canine renal diseases. © 2014 American Society for Veterinary Clinical Pathology and European Society for Veterinary Clinical Pathology.

  19. Towards Improved Biomarker Research

    DEFF Research Database (Denmark)

    Kjeldahl, Karin

    This thesis takes a look at the data analytical challenges associated with the search for biomarkers in large-scale biological data such as transcriptomics, proteomics and metabolomics data. These studies aim to identify genes, proteins or metabolites which can be associated with e.g. a diet...... with very specific competencies. In order to optimize the basis of a sound and fruitful data analysis, suggestions are givenwhich focus on (1) collection of good data, (2) preparation of data for the data analysis and (3) a sound data analysis. If these steps are optimized, PLS is a also a very goodmethod...

  20. Proteomics Analysis for Finding Serum Markers of Ovarian Cancer

    Directory of Open Access Journals (Sweden)

    Yushan Cheng

    2014-01-01

    Full Text Available A combination of peptide ligand library beads (PLLB and 1D gel liquid chromatography-mass spectrometry/mass spectrometry (1DGel-LC-MS/MS was employed to analyze serum samples from patients with ovarian cancer and from healthy controls. Proteomic analysis identified 1200 serum proteins, among which 57 proteins were upregulated and 10 were downregulated in the sera from cancer patients. Retinol binding protein 4 (RBP4 is highly upregulated in the ovarian cancer serum samples. ELISA was employed to measure plasma concentrations of RBP4 in 80 samples from ovarian cancer patients, healthy individuals, myoma patients, and patients with benign ovarian tumor, respectively. The plasma concentrations of RBP4 ranging from 76.91 to 120.08 ng/mL with the mean value 89.13±1.67 ng/mL in ovarian cancer patients are significantly higher than those in healthy individuals (10.85±2.38 ng/mL. Results were further confirmed with immunohistochemistry, demonstrating that RBP4 expression levels in normal ovarian tissue were lower than those in ovarian cancer tissues. Our results suggested that RBP4 is a potential biomarker for diagnostic of screening ovarian cancer.