WorldWideScience

Sample records for widely targeted metabolomics

  1. Highly sensitive and selective analysis of widely targeted metabolomics using gas chromatography/triple-quadrupole mass spectrometry.

    Science.gov (United States)

    Tsugawa, Hiroshi; Tsujimoto, Yuki; Sugitate, Kuniyo; Sakui, Norihiro; Nishiumi, Shin; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-01-01

    In metabolomics studies, gas chromatography coupled with time-of-flight or quadrupole mass spectrometry has frequently been used for the non-targeted analysis of hydrophilic metabolites. However, because the analytical platform employs the deconvolution method to extract single-metabolite information from co-eluted peaks and background noise, the extracted peak is artificial product depending on the mathematical parameters and is not completely compatible with the pure component obtained by analyzing a standard compound. Moreover, it has insufficient ability for quantitative metabolomics. Therefore, highly sensitive and selective methods capable of pure peak extraction without any complicated mathematical techniques are needed. For this purpose, we have developed a novel analytical method using gas chromatography coupled with triple-quadrupole mass spectrometry (GC-QqQ/MS). We developed a selected reaction monitoring (SRM) method to analyze the trimethylsilyl derivatives of 110 metabolites, using electron ionization. This methodology enables us to utilize two complementary techniques-non-targeted and widely targeted metabolomics in the same sample preparation protocol, which would facilitate the formulation or verification of novel hypotheses in biological sciences. The GC-QqQ/MS analysis can accurately identify a metabolite using multichannel SRM transitions and intensity ratios in the analysis of living organisms. In addition, our methodology offers a wide dynamic range, high sensitivity, and highly reproducible metabolite profiles, which will contribute to the biomarker discoveries and quality evaluations in biology, medicine, and food sciences. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  2. Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality.

    Directory of Open Access Journals (Sweden)

    Johannes Raffler

    2015-09-01

    Full Text Available Genome-wide association studies with metabolic traits (mGWAS uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3. Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13, pulmonary hypertension (CPS1, and ischemic stroke (XYLB. By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular

  3. Targeting of the hydrophobic metabolome by pathogens.

    Science.gov (United States)

    Helms, J Bernd; Kaloyanova, Dora V; Strating, Jeroen R P; van Hellemond, Jaap J; van der Schaar, Hilde M; Tielens, Aloysius G M; van Kuppeveld, Frank J M; Brouwers, Jos F

    2015-05-01

    The hydrophobic molecules of the metabolome - also named the lipidome - constitute a major part of the entire metabolome. Novel technologies show the existence of a staggering number of individual lipid species, the biological functions of which are, with the exception of only a few lipid species, unknown. Much can be learned from pathogens that have evolved to take advantage of the complexity of the lipidome to escape the immune system of the host organism and to allow their survival and replication. Different types of pathogens target different lipids as shown in interaction maps, allowing visualization of differences between different types of pathogens. Bacterial and viral pathogens target predominantly structural and signaling lipids to alter the cellular phenotype of the host cell. Fungal and parasitic pathogens have complex lipidomes themselves and target predominantly the release of polyunsaturated fatty acids from the host cell lipidome, resulting in the generation of eicosanoids by either the host cell or the pathogen. Thus, whereas viruses and bacteria induce predominantly alterations in lipid metabolites at the host cell level, eukaryotic pathogens focus on interference with lipid metabolites affecting systemic inflammatory reactions that are part of the immune system. A better understanding of the interplay between host-pathogen interactions will not only help elucidate the fundamental role of lipid species in cellular physiology, but will also aid in the generation of novel therapeutic drugs. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Secondary Metabolic Pathway-Targeted Metabolomics.

    Science.gov (United States)

    Vizcaino, Maria I; Crawford, Jason M

    2016-01-01

    This chapter provides step-by-step methods for building secondary metabolic pathway-targeted molecular networks to assess microbial natural product biosynthesis at a systems level and to aid in downstream natural product discovery efforts. Methods described include high-resolution mass spectrometry (HRMS)-based comparative metabolomics, pathway-targeted tandem MS (MS/MS) molecular networking, and isotopic labeling for the elucidation of natural products encoded by orphan biosynthetic pathways. The metabolomics network workflow covers the following six points: (1) method development, (2) bacterial culture growth and organic extraction, (3) HRMS data acquisition and analysis, (4) pathway-targeted MS/MS data acquisition, (5) mass spectral network building, and (6) network enhancement. This chapter opens with a discussion on the practical considerations of natural product extraction, chromatographic processing, and enhanced detection of the analytes of interest within complex organic mixtures using liquid chromatography (LC)-HRMS. Next, we discuss the utilization of a chemometric platform, focusing on Agilent Mass Profiler Professional software, to run MS-based differential analysis between sample groups and controls to acquire a unique set of molecular features that are dependent on the presence of a secondary metabolic pathway. Using this unique list of molecular features, the chapter then details targeted MS/MS acquisition for subsequent pathway-dependent network clustering through the online Global Natural Products Social Molecular Networking (GnPS) platform. Genetic information, ionization intensities, isotopic labeling, and additional experimental data can be mapped onto the pathway-dependent network, facilitating systems biosynthesis analyses. The finished product will provide a working molecular network to assess experimental perturbations and guide novel natural product discoveries.

  5. Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays

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    High-throughput metabolomic assays that allow simultaneous targeted screening of hundreds of metabolites have recently become available in kit form. Such assays provide a window into understanding changes to biochemical pathways due to chemical exposure or disease, and are usefu...

  6. Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches

    Science.gov (United States)

    Checkley, William; Deza, Maria P.; Klawitter, Jost; Romero, Karina M.; Klawitter, Jelena; Pollard, Suzanne L.; Wise, Robert A.; Christians, Uwe; Hansel, Nadia N.

    2017-01-01

    Background The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods. Methods We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry. Results A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40–50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second). Conclusions By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that serum metabolomics may represent a diagnostic tool for

  7. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    Metabolomics is the analysis of the whole metabolome and the focus in metabolomics studies is to measure as many metabolites as possible. The use of chemometrics in metabolomics studies is widespread, but there is a clear lack of validation in the developed models. The focus in this thesis has been...... how to properly handle complex metabolomics data, in order to achieve reliable and valid multivariate models. This has been illustrated by three case studies with examples of forecasting breast cancer and early detection of colorectal cancer based on data from nuclear magnetic resonance (NMR...... is a presentation of a core consistency diagnostic aiding in determining the number of components in a PARAFAC2 model. It is of great importance to validate especially PLS-DA models and if not done properly, the developed models might reveal spurious groupings. Furthermore, data from metabolomics studies contain...

  8. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    Metabolomics is the analysis of the whole metabolome and the focus in metabolomics studies is to measure as many metabolites as possible. The use of chemometrics in metabolomics studies is widespread, but there is a clear lack of validation in the developed models. The focus in this thesis has been...... how to properly handle complex metabolomics data, in order to achieve reliable and valid multivariate models. This has been illustrated by three case studies with examples of forecasting breast cancer and early detection of colorectal cancer based on data from nuclear magnetic resonance (NMR......) spectroscopy (Paper II), fluorescence spectroscopy (Paper III) and gas chromatography coupled to mass spectrometry (GC-MS). The principles of the three data acquisition techniques have been briefly described and the methods have been compared. The techniques complement each other, which makes room for data...

  9. Targeted metabolomics profiles are strongly correlated with nutritional patterns in women

    OpenAIRE

    Menni, Cristina; Zhai, Guangju; MacGregor, Alexander; Prehn, Cornelia; Römisch-Margl, Werner; Suhre, Karsten; Adamski, Jerzy; Cassidy, Aedin; Illig, Thomas; Tim D Spector; Valdes, Ana M.

    2013-01-01

    Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targete...

  10. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    is a presentation of a core consistency diagnostic aiding in determining the number of components in a PARAFAC2 model. It is of great importance to validate especially PLS-DA models and if not done properly, the developed models might reveal spurious groupings. Furthermore, data from metabolomics studies contain...

  11. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    and the results indicate that GC-MS-based metabolomics in combination with PARAFAC2 modelling is applicable for extracting relevant biological information from the plasma samples. Overall, the work in this thesis shows that suitable and properly validated chemometrics models used in metabolomics are very useful......) spectroscopy (Paper II), fluorescence spectroscopy (Paper III) and gas chromatography coupled to mass spectrometry (GC-MS). The principles of the three data acquisition techniques have been briefly described and the methods have been compared. The techniques complement each other, which makes room for data...... fusion where data from different platforms can be combined. Complex data are obtained when samples are analysed using NMR, fluorescence and GC-MS. Chemometrics methods which can be used to extract the relevant information from the obtained data are presented. Focus has been on principal component...

  12. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    and the results indicate that GC-MS-based metabolomics in combination with PARAFAC2 modelling is applicable for extracting relevant biological information from the plasma samples. Overall, the work in this thesis shows that suitable and properly validated chemometrics models used in metabolomics are very useful...... fusion where data from different platforms can be combined. Complex data are obtained when samples are analysed using NMR, fluorescence and GC-MS. Chemometrics methods which can be used to extract the relevant information from the obtained data are presented. Focus has been on principal component...... many redundant variables. These have been suggested to be eliminated using an approach termed reduction of redundant variables (RRV), which is time consuming but efficient, since the curse of dimensionality is reduced and the risk of over-fit is decreased. The use of appropriate multivariate models...

  13. What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

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    Hamzeiy, Hamid; Cox, Jürgen

    2017-02-01

    Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  14. The Uses and Future Prospects of Metabolomics and Targeted Metabolite Profiling in Cell Factory Development

    DEFF Research Database (Denmark)

    Harrison, Scott James; Herrgard, Markus

    2013-01-01

    , these broader measurements of the cellular metabolic state are now becoming part of the toolbox used to characterize cell factories. In this review we briefly summarize the benefits and challenges of global metabolomics and targeted metabolite profiling methods and discuss the application of these methods......The development of cell factories for the production of chemicals has traditionally relied on measurements of product metabolite titers to assess the performance of genetically manipulated strains. With the development of improved metabolomics and targeted metabolite profiling methods...... in both pathway discovery and cell factory engineering. We focus particularly on exploring the potential of global metabolomics to complement more traditional targeted methods. We conclude the review by discussing emerging trends in metabolomics and how these developments can aid the engineering of better...

  15. The effect of antibiotics and diet on enterolactone concentration and metabolome studied by targeted and non-targeted LC-MS metabolomics

    DEFF Research Database (Denmark)

    Bolvig, Anne Katrine; Nørskov, Natalja; Hedemann, Mette Skou

    2017-01-01

    with lower levels of ENL. Here, we investigate the link between antibiotic use and lignan metabolism in pigs using LC-MS/MS. The effect of lignan intake and antibiotic use on the gut microbial community and the pig metabolome is studied by 16S rRNA sequencing and non-targeted LC-MS. Treatment...

  16. Identification of drug targets by chemogenomic and metabolomic profiling in yeast

    KAUST Repository

    Wu, Manhong

    2012-12-01

    OBJECTIVE: To advance our understanding of disease biology, the characterization of the molecular target for clinically proven or new drugs is very important. Because of its simplicity and the availability of strains with individual deletions in all of its genes, chemogenomic profiling in yeast has been used to identify drug targets. As measurement of drug-induced changes in cellular metabolites can yield considerable information about the effects of a drug, we investigated whether combining chemogenomic and metabolomic profiling in yeast could improve the characterization of drug targets. BASIC METHODS: We used chemogenomic and metabolomic profiling in yeast to characterize the target for five drugs acting on two biologically important pathways. A novel computational method that uses a curated metabolic network was also developed, and it was used to identify the genes that are likely to be responsible for the metabolomic differences found. RESULTS AND CONCLUSION: The combination of metabolomic and chemogenomic profiling, along with data analyses carried out using a novel computational method, could robustly identify the enzymes targeted by five drugs. Moreover, this novel computational method has the potential to identify genes that are causative of metabolomic differences or drug targets. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.

  17. Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

    Science.gov (United States)

    Reisetter, Anna C; Muehlbauer, Michael J; Bain, James R; Nodzenski, Michael; Stevens, Robert D; Ilkayeva, Olga; Metzger, Boyd E; Newgard, Christopher B; Lowe, William L; Scholtens, Denise M

    2017-02-02

    Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.

  18. Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method

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    Riera-Borrull, Marta; Rodríguez-Gallego, Esther; Hernández-Aguilera, Anna; Luciano, Fedra; Ras, Rosa; Cuyàs, Elisabet; Camps, Jordi; Segura-Carretero, Antonio; Menendez, Javier A.; Joven, Jorge; Fernández-Arroyo, Salvador

    2016-01-01

    Abnormalities in mitochondrial metabolism and regulation of energy balance contribute to human diseases. The consequences of high fat and other nutrient intake, and the resulting acquired mitochondrial dysfunction, are essential to fully understand common disorders, including obesity, cancer, and atherosclerosis. To simultaneously and noninvasively measure and quantify indirect markers of mitochondrial function, we have developed a method based on gas chromatography coupled to quadrupole-time of flight mass spectrometry and an electron ionization interface, and validated the system using plasma from patients with peripheral artery disease, human cancer cells, and mouse tissues. This approach was used to increase sensibility in the measurement of a wide dynamic range and chemical diversity of multiple intermediate metabolites used in energy metabolism. We demonstrate that our targeted metabolomics method allows for quick and accurate identification and quantification of molecules, including the measurement of small yet significant biological changes in experimental samples. The apparently low process variability required for its performance in plasma, cell lysates, and tissues allowed a rapid identification of correlations between interconnected pathways. Our results suggest that delineating the process of energy generation by targeted metabolomics can be a valid surrogate for predicting mitochondrial dysfunction in biological samples. Importantly, when used in plasma, targeted metabolomics should be viewed as a robust and noninvasive source of biomarkers in specific pathophysiological scenarios.

  19. A targeted metabolomics assay for cardiac metabolism and demonstration using a mouse model of dilated cardiomyopathy

    NARCIS (Netherlands)

    West, James A.; Beqqali, Abdelaziz; Ament, Zsuzsanna; Elliott, Perry; Pinto, Yigal M.; Arbustini, Eloisa; Griffin, Julian L.

    2016-01-01

    Metabolomics can be performed either as an 'open profiling' tool where the aim is to measure, usually in a semi-quantitative manner, as many metabolites as possible or perform 'closed' or 'targeted' analyses where instead a pre-defined set of metabolites are measured. Targeted methods can be

  20. Non-targeted plasma metabolome of early and late lactation gilts

    Science.gov (United States)

    Female pigs nursing their first litter (first-parity gilts) have increased energy requirements not only to support their piglets, but they themselves are still maturing. Non-targeted plasma metabolomics were used to investigate the differences between (1) post-farrowing and weaning (early or late l...

  1. Metabolomics by Gas Chromatography-Mass Spectrometry: the combination of targeted and untargeted profiling

    Science.gov (United States)

    Fiehn, Oliver

    2016-01-01

    Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small molecular metabolites (metabolomics easily allows integrating targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated, standardized standard operating procedures, GC-MS can identify and semi-quantify over 200 compounds per study in human body fluids (e.g., plasma, urine or stool) samples. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to liquid chromatography-MS untargeted profiling (LC-MS). Hence, GC-MS is a mature technology that not only uses classic detectors (‘quadrupole’) but also target mass spectrometers (‘triple quadrupole’) and accurate mass instruments (‘quadrupole-time of flight’). This unit covers the following aspects of GC-MS-based metabolomics: (i) sample preparation from mammalian samples, (ii) acquisition of data, (iii) quality control, and (iv) data processing. PMID:27038389

  2. High-throughput extraction and quantification method for targeted metabolomics in murine tissues.

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    Zukunft, Sven; Prehn, Cornelia; Röhring, Cornelia; Möller, Gabriele; Hrabě de Angelis, Martin; Adamski, Jerzy; Tokarz, Janina

    2018-01-01

    Global metabolomics analyses using body fluids provide valuable results for the understanding and prediction of diseases. However, the mechanism of a disease is often tissue-based and it is advantageous to analyze metabolomic changes directly in the tissue. Metabolomics from tissue samples faces many challenges like tissue collection, homogenization, and metabolite extraction. We aimed to establish a metabolite extraction protocol optimized for tissue metabolite quantification by the targeted metabolomics AbsoluteIDQ™ p180 Kit (Biocrates). The extraction method should be non-selective, applicable to different kinds and amounts of tissues, monophasic, reproducible, and amenable to high throughput. We quantified metabolites in samples of eleven murine tissues after extraction with three solvents (methanol, phosphate buffer, ethanol/phosphate buffer mixture) in two tissue to solvent ratios and analyzed the extraction yield, ionization efficiency, and reproducibility. We found methanol and ethanol/phosphate buffer to be superior to phosphate buffer in regard to extraction yield, reproducibility, and ionization efficiency for all metabolites measured. Phosphate buffer, however, outperformed both organic solvents for amino acids and biogenic amines but yielded unsatisfactory results for lipids. The observed matrix effects of tissue extracts were smaller or in a similar range compared to those of human plasma. We provide for each murine tissue type an optimized high-throughput metabolite extraction protocol, which yields the best results for extraction, reproducibility, and quantification of metabolites in the p180 kit. Although the performance of the extraction protocol was monitored by the p180 kit, the protocol can be applicable to other targeted metabolomics assays.

  3. Genome-enabled plant metabolomics.

    Science.gov (United States)

    Tohge, Takayuki; de Souza, Leonardo Perez; Fernie, Alisdair R

    2014-09-01

    The grand challenge currently facing metabolomics is that of comprehensitivity whilst next generation sequencing and advanced proteomics methods now allow almost complete and at least 50% coverage of their respective target molecules, metabolomics platforms at best offer coverage of just 10% of the small molecule complement of the cell. Here we discuss the use of genome sequence information as an enabling tool for peak identity and for translational metabolomics. Whilst we argue that genome information is not sufficient to compute the size of a species metabolome it is highly useful in predicting the occurrence of a wide range of common metabolites. Furthermore, we describe how via gene functional analysis in model species the identity of unknown metabolite peaks can be resolved. Taken together these examples suggest that genome sequence information is current (and likely will remain), a highly effective tool in peak elucidation in mass spectral metabolomics strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. The Future of NMR Metabolomics in Cancer Therapy: Towards Personalizing Treatment and Developing Targeted Drugs?

    Science.gov (United States)

    Palmnas, Marie S.A.; Vogel, Hans J

    2013-01-01

    There has been a recent shift in how cancers are defined, where tumors are no longer simply classified by their tissue origin, but also by their molecular characteristics. Furthermore, personalized medicine has become a popular term and it could start to play an important role in future medical care. However, today, a “one size fits all” approach is still the most common form of cancer treatment. In this mini-review paper, we report on the role of nuclear magnetic resonance (NMR) metabolomics in drug development and in personalized medicine. NMR spectroscopy has successfully been used to evaluate current and potential therapies, both single-agents and combination therapies, to analyze toxicology, optimal dose, resistance, sensitivity, and biological mechanisms. It can also provide biological insight on tumor subtypes and their different responses to drugs, and indicate which patients are most likely to experience off-target effects and predict characteristics for treatment efficacy. Identifying pre-treatment metabolic profiles that correlate to these events could significantly improve how we view and treat tumors. We also briefly discuss several targeted cancer drugs that have been studied by metabolomics. We conclude that NMR technology provides a key platform in metabolomics that is well-positioned to play a crucial role in realizing the ultimate goal of better tailored cancer medicine. PMID:24957997

  5. Metabolomics and proteomics annotate therapeutic properties of geniposide: targeting and regulating multiple perturbed pathways.

    Directory of Open Access Journals (Sweden)

    Xijun Wang

    Full Text Available Geniposide is an important constituent of Gardenia jasminoides Ellis, a famous Chinese medicinal plant, and has displayed bright prospects in prevention and therapy of hepatic injury (HI. Unfortunately, the working mechanisms of this compound are difficult to determine and thus remain unknown. To determine the mechanisms that underlie this compound, we conducted a systematic analysis of the therapeutic effects of geniposide using biochemistry, metabolomics and proteomics. Geniposide significantly intensified the therapeutic efficacy as indicated by our modern biochemical analysis. Metabolomics results indicate 9 ions in the positive mode as differentiating metabolites which were associated with perturbations in primary bile acid biosynthesis, butanoate metabolism, citrate cycle (TCA cycle, alanine, aspartate and glutamate metabolism. Of note, geniposide has potential pharmacological effect through regulating multiple perturbed pathways to normal state. In an attempt to address the benefits of geniposide based on the proteomics approaches, the protein-interacting networks were constructed to aid identifying the drug targets of geniposide. Six identified differential proteins appear to be involved in antioxidation and signal transduction, energy production, immunity, metabolism, chaperoning. These proteins were closely related in the protein-protein interaction network and the modulation of multiple vital physiological pathways. These data will help to understand the molecular therapeutic mechanisms of geniposide on hepatic damage rats. We also conclude that metabolomics and proteomics are powerful and versatile tools for both biomarker discovery and exploring the complex relationships between biological pathways and drug response, highlighting insights into drug discovery.

  6. Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry.

    Science.gov (United States)

    Chen, Yanhua; Zhou, Zhi; Yang, Wei; Bi, Nan; Xu, Jing; He, Jiuming; Zhang, Ruiping; Wang, Lvhua; Abliz, Zeper

    2017-07-05

    Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications.

  7. Livestock metabolomics and the livestock metabolome: A systematic review.

    Science.gov (United States)

    Goldansaz, Seyed Ali; Guo, An Chi; Sajed, Tanvir; Steele, Michael A; Plastow, Graham S; Wishart, David S

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

  8. Livestock metabolomics and the livestock metabolome: A systematic review.

    Directory of Open Access Journals (Sweden)

    Seyed Ali Goldansaz

    Full Text Available Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production. A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs. These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca. The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

  9. System-Wide Hypersensitive Response-Associated Transcriptome and Metabolome Reprogramming in Tomato

    NARCIS (Netherlands)

    Etalo, D.W.; Stulemeijer, I.J.E.; Esse, van H.P.; Vos, de R.C.H.; Bouwmeester, H.J.; Joosten, M.H.A.J.

    2013-01-01

    The hypersensitive response (HR) is considered to be the hallmark of the resistance response of plants to pathogens. To study HR-associated transcriptome and metabolome reprogramming in tomato (Solanum lycopersicum), we used plants that express both a resistance gene to Cladosporium fulvum and the

  10. Semi-automated non-target processing in GC × GC–MS metabolomics analysis: applicability for biomedical studies

    OpenAIRE

    Koek, Maud M.; Kloet, Frans M; Kleemann, Robert; Kooistra, Teake; Verheij, Elwin R; Hankemeier, Thomas

    2010-01-01

    Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC–MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC–MS data still poses a major challenge in metabolomics analysis. The feasibility of using commercially available software for non-target processing of GC × GC–MS data was assessed. For this purpose a set of mouse liver samples (24 study samples and f...

  11. Acclimation to UV-B radiation and visible light in Lactuca sativa involves up-regulation of photosynthetic performance and orchestration of metabolome-wide responses.

    Science.gov (United States)

    Wargent, J J; Nelson, B C W; McGhie, T K; Barnes, P W

    2015-05-01

    UV-B radiation is often viewed as a source of stress for higher plants. In particular, photosynthetic function has been described as a common target for UV-B impairment; yet as our understanding of UV-B photomorphogenesis increases, there are opportunities to expand the emerging paradigm of regulatory UV response. Lactuca sativa is an important dietary crop species and is often subjected to rapid sunlight exposure at field transfer. Acclimation to UV-B and visible light conditions in L. sativa was dissected using gas exchange and chlorophyll fluorescence measurements, in addition to non-destructive assessments of UV epidermal shielding (SUV ). After UV-B treatment, seedlings were subjected to wide-range metabolomic analysis using liquid chromatography hybrid quadrupole time-of-flight high-resolution mass spectrometry (LC-QTOF-HRMS). During the acclimation period, net photosynthetic rate increased in UV-treated plants, epidermal UV shielding increased in both subsets of plants transferred to the acclimatory conditions (UV+/UV- plants) and Fv /Fm declined slightly in UV+/UV- plants. Metabolomic analysis revealed that a key group of secondary compounds was up-regulated by higher light conditions, yet several of these compounds were elevated further by UV-B radiation. In conclusion, acclimation to UV-B radiation involves co-protection from the effects of visible light, and responses to UV-B radiation at a photosynthetic level may not be consistently viewed as damaging to plant development. © 2014 John Wiley & Sons Ltd.

  12. Molecular cartography in acute Chlamydia pneumoniae infections--a non-targeted metabolomics approach.

    Science.gov (United States)

    Müller, Constanze; Dietz, Inga; Tziotis, Dimitrios; Moritz, Franco; Rupp, Jan; Schmitt-Kopplin, Philippe

    2013-06-01

    Infections with Chlamydia pneumoniae cause several respiratory diseases, such as community-acquired pneumonia, bronchitis or sinusitis. Here, we present an integrated non-targeted metabolomics analysis applying ultra-high-resolution mass spectrometry and ultra-performance liquid chromatography mass spectrometry to determine metabolite alterations in C. pneumoniae-infected HEp-2 cells. Most important permutations are elaborated using uni- and multivariate statistical analysis, logD retention time regression and mass defect-based network analysis. Classes of metabolites showing high variations upon infection are lipids, carbohydrates and amino acids. Moreover, we observed several non-annotated compounds as predominantly abundant after infection, which are promising biomarker candidates for drug-target and diagnostic research.

  13. Targeted Metabolomics Identifies Pharmacodynamic Biomarkers for BIO 300 Mitigation of Radiation-Induced Lung Injury.

    Science.gov (United States)

    Jones, Jace W; Jackson, Isabel L; Vujaskovic, Zeljko; Kaytor, Michael D; Kane, Maureen A

    2017-10-02

    Biomarkers serve a number of purposes during drug development including defining the natural history of injury/disease, serving as a secondary endpoint or trigger for intervention, and/or aiding in the selection of an effective dose in humans. BIO 300 is a patent-protected pharmaceutical formulation of nanoparticles of synthetic genistein being developed by Humanetics Corporation. The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiation-induced lung injury and BIO 300 efficacy for mitigating tissue damage based upon the primary endpoint of survival. High-throughput targeted metabolomics of lung tissue from male C57L/J mice exposed to 12.5 Gy whole thorax lung irradiation, treated daily with 400 mg/kg BIO 300 for either 2 weeks or 6 weeks starting 24 h post radiation exposure, were assayed at 180 d post-radiation to identify potential biomarkers. A panel of lung metabolites that are responsive to radiation and able to distinguish an efficacious treatment schedule of BIO 300 from a non-efficacious treatment schedule in terms of 180 d survival were identified. These metabolites represent potential biomarkers that could be further validated for use in drug development of BIO 300 and in the translation of dose from animal to human.

  14. Plant metabolomics and its potential application for human nutrition

    NARCIS (Netherlands)

    Hall, R.D.; Brouwer, I.D.; Fitzgerald, M.A.

    2008-01-01

    With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental

  15. Semi-automated non-target processing in GC × GC-MS metabolomics analysis: Applicability for biomedical studies

    NARCIS (Netherlands)

    Koek, M.M.; Kloet, F.M. van der; Kleemann, R.; Kooistra, T.; Verheij, E.R.; Hankemeier, T.

    2011-01-01

    Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC-MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC-MS data still poses a major challenge in

  16. Metabolome-wide association study of neovascular age-related macular degeneration.

    Directory of Open Access Journals (Sweden)

    Melissa P Osborn

    Full Text Available To determine if plasma metabolic profiles can detect differences between patients with neovascular age-related macular degeneration (NVAMD and similarly-aged controls.Metabolomic analysis using liquid chromatography with Fourier-transform mass spectrometry (LC-FTMS was performed on plasma samples from 26 NVAMD patients and 19 controls. Data were collected from mass/charge ratio (m/z 85 to 850 on a Thermo LTQ-FT mass spectrometer, and metabolic features were extracted using an adaptive processing software package. Both non-transformed and log2 transformed data were corrected using Benjamini and Hochberg False Discovery Rate (FDR to account for multiple testing. Orthogonal Partial Least Squares-Discriminant Analysis was performed to determine metabolic features that distinguished NVAMD patients from controls. Individual m/z features were matched to the Kyoto Encyclopedia of Genes and Genomes database and the Metlin metabolomics database, and metabolic pathways associated with NVAMD were identified using MetScape.Of the 1680 total m/z features detected by LC-FTMS, 94 unique m/z features were significantly different between NVAMD patients and controls using FDR (q = 0.05. A comparison of these features to those found with log2 transformed data (n = 132, q = 0.2 revealed 40 features in common, reaffirming the involvement of certain metabolites. Such metabolites included di- and tripeptides, covalently modified amino acids, bile acids, and vitamin D-related metabolites. Correlation analysis revealed associations among certain significant features, and pathway analysis demonstrated broader changes in tyrosine metabolism, sulfur amino acid metabolism, and amino acids related to urea metabolism.These data suggest that metabolomic analysis can identify a panel of individual metabolites that differ between NVAMD cases and controls. Pathway analysis can assess the involvement of certain metabolic pathways, such as tyrosine and urea metabolism, and can

  17. Targeted, LCMS-based Metabolomics for Quantitative Measurement of NAD(+) Metabolites.

    Science.gov (United States)

    Trammell, Samuel Aj; Brenner, Charles

    2013-01-01

    Nicotinamide adenine dinucleotide (NAD(+)) is a coenzyme for hydride transfer reactions and a substrate for sirtuins and other NAD(+)-consuming enzymes. The abundance of NAD (+), NAD(+) biosynthetic intermediates, and related nucleotides reflects the metabolic state of cells and tissues. High performance liquid chromatography (HPLC) followed by ultraviolet-visible (UV-Vis) spectroscopic analysis of NAD(+) metabolites does not offer the specificity and sensitivity necessary for robust quantification of complex samples. Thus, we developed a targeted, quantitative assay of the NAD(+) metabolome with the use of HPLC coupled to mass spectrometry. Here we discuss NAD(+) metabolism as well as the technical challenges required for reliable quantification of the NAD(+) metabolites. The new method incorporates new separations and improves upon a previously published method that suffered from the problem of ionization suppression for particular compounds.

  18. Use of NMR Metabolomics to Analyze the Targets of D-cycloserine in Mycobacteria: Role of D-Alanine Racemase

    Science.gov (United States)

    Halouska, Steven; Chacon, Ofelia; Fenton, Robert J.; Zinniel, Denise K.; Barletta, Raul G.; Powers, Robert

    2008-01-01

    D-cycloserine (DCS) is only used with multi-drug resistant strains of tuberculosis because of serious side-effects. DCS is known to inhibit cell wall biosynthesis, but the in vivo lethal target is still unknown. We have applied NMR-based metabolomics combined with principal component analysis to monitor the in vivo affect of DCS on M. smegmatis. Our analysis suggests DCS functions by inhibiting multiple protein targets. PMID:17979227

  19. Reliability of serum metabolite concentrations over a 4-month period using a targeted metabolomic approach.

    Directory of Open Access Journals (Sweden)

    Anna Floegel

    Full Text Available Metabolomics is a promising tool for discovery of novel biomarkers of chronic disease risk in prospective epidemiologic studies. We investigated the between- and within-person variation of the concentrations of 163 serum metabolites over a period of 4 months to evaluate the metabolite reliability expressed by the intraclass-correlation coefficient (ICC: the ratio of between-person variance and total variance. The analyses were performed with the BIOCRATES AbsoluteIDQ™ targeted metabolomics technology, including acylcarnitines, amino acids, glycerophospholipids, sphingolipids and hexose in 100 healthy individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC-Potsdam study who had provided two fasting blood samples 4 months apart. Overall, serum reliability of metabolites over a 4-month period was good. The median ICC of the 163 metabolites was 0.57. The highest ICC was observed for hydroxysphingomyelin C14:1 (ICC = 0.85 and the lowest was found for acylcarnitine C3:1 (ICC = 0. Reliability was high for hexose (ICC = 0.76, sphingolipids (median ICC = 0.66; range: 0.24-0.85, amino acids (median ICC = 0.58; range: 0.41-0.72 and glycerophospholipids (median ICC = 0.58; range: 0.03-0.81. Among acylcarnitines, reliability of short and medium chain saturated compounds was good to excellent (ICC range: 0.50-0.81. Serum reliability was lower for most hydroxyacylcarnitines and monounsaturated acylcarnitines (ICC range: 0.11-0.45 and 0.00-0.63, respectively. For most of the metabolites a single measurement may be sufficient for risk assessment in epidemiologic studies with healthy subjects.

  20. Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

    Science.gov (United States)

    Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

    2015-02-01

    Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides

  1. Combining Targeted Metabolomic Data with a Model of Glucose Metabolism: Toward Progress in Chondrocyte Mechanotransduction.

    Science.gov (United States)

    Salinas, Daniel; Minor, Cody A; Carlson, Ross P; McCutchen, Carley N; Mumey, Brendan M; June, Ronald K

    2017-01-01

    Osteoarthritis is a debilitating disease likely involving altered metabolism of the chondrocytes in articular cartilage. Chondrocytes can respond metabolically to mechanical loads via cellular mechanotransduction, and metabolic changes are significant because they produce the precursors to the tissue matrix necessary for cartilage health. However, a comprehensive understanding of how energy metabolism changes with loading remains elusive. To improve our understanding of chondrocyte mechanotransduction, we developed a computational model to calculate the rate of reactions (i.e. flux) across multiple components of central energy metabolism based on experimental data. We calculated average reaction flux profiles of central metabolism for SW1353 human chondrocytes subjected to dynamic compression for 30 minutes. The profiles were obtained solving a bounded variable linear least squares problem, representing the stoichiometry of human central energy metabolism. Compression synchronized chondrocyte energy metabolism. These data are consistent with dynamic compression inducing early time changes in central energy metabolism geared towards more active protein synthesis. Furthermore, this analysis demonstrates the utility of combining targeted metabolomic data with a computational model to enable rapid analysis of cellular energy utilization.

  2. Arsenite response in Coccomyxa sp. Carn explored by transcriptomic and non-targeted metabolomic approaches.

    Science.gov (United States)

    Koechler, Sandrine; Bertin, Philippe N; Plewniak, Frédéric; Baltenweck, Raymonde; Casiot, Corinne; Heipieper, Hermann J; Bouchez, Olivier; Arsène-Ploetze, Florence; Hugueney, Philippe; Halter, David

    2016-04-01

    Arsenic is a toxic metalloid known to generate an important oxidative stress in cells. In the present study, we focused our attention on an alga related to the genus Coccomyxa, exhibiting an extraordinary capacity to resist high concentrations of arsenite and arsenate. The integrated analysis of high-throughput transcriptomic data and non-targeted metabolomic approaches highlighted multiple levels of protection against arsenite. Indeed, Coccomyxa sp. Carn induced a set of transporters potentially preventing the accumulation of this metalloid in the cells and presented a distinct arsenic metabolism in comparison to another species more sensitive to that compound, i.e. Euglena gracilis, especially in regard to arsenic methylation. Interestingly, Coccomyxa sp. Carn was characterized by a remarkable accumulation of the strong antioxidant glutathione (GSH). Such observation could explain the apparent low oxidative stress in the intracellular compartment, as suggested by the transcriptomic analysis. In particular, the high amount of GSH in the cell could play an important role for the tolerance to arsenate, as suggested by its partial oxidation into oxidized glutathione in presence of this metalloid. Our results therefore reveal that this alga has acquired multiple and original defence mechanisms allowing the colonization of extreme ecosystems such as acid mine drainages. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

  3. Benznidazole biotransformation and multiple targets in Trypanosoma cruzi revealed by metabolomics.

    Directory of Open Access Journals (Sweden)

    Andrea Trochine

    2014-05-01

    Full Text Available The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, involves administration of benznidazole (Bzn. Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active, although its mode of action is not fully understood. In the present work we used a non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols trypanothione, homotrypanothione and cysteine were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment. These metabolites included reduction products, fragments and covalent adducts of reduced Bzn linked to each of the major low molecular weight thiols: trypanothione, glutathione, γ-glutamylcysteine, glutathionylspermidine, cysteine and ovothiol A. Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI, were found within the parasites, but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.Our data is indicative of a major role of the thiol binding capacity of Bzn reduction products in the mechanism of Bzn toxicity against T. cruzi.

  4. PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

    Directory of Open Access Journals (Sweden)

    Renata Bujak

    2016-07-01

    Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

  5. Variation of serum metabolites related to habitual diet: a targeted metabolomic approach in EPIC-Potsdam.

    Science.gov (United States)

    Floegel, A; von Ruesten, A; Drogan, D; Schulze, M B; Prehn, C; Adamski, J; Pischon, T; Boeing, H

    2013-10-01

    Serum metabolites have been linked to higher risk of chronic diseases but determinants of serum metabolites are not clear. We aimed to investigate the association between habitual diet as a modifiable risk factor and relevant serum metabolites. This cross-sectional study comprised 2380 EPIC-Potsdam participants. Intake of 45 food groups was assessed by food frequency questionnaire and concentrations of 127 serum metabolites were measured by targeted metabolomics. Reduced rank regression was used to find dietary patterns that explain the maximum variation of metabolites. In the multivariable-adjusted model, the proportion of explained variation by habitual diet was ranked as follows: acyl-alkyl-phosphatidylcholines (5.7%), sphingomyelins (5.1%), diacyl-phosphatidylcholines (4.4%), lyso-phosphatidylcholines (4.1%), acylcarnitines (3.5%), amino acids (2.2%) and hexose (1.6%). A pattern with high intake of butter and low intake of margarine was related to acylcarnitines, acyl-alkyl-phosphatidylcholines, lyso-phosphatidylcholines and hydroxy-sphingomyelins, particularly with saturated and monounsaturated fatty acid side chains. A pattern with high intake of red meat and fish and low intake of whole-grain bread and tea was related to hexose and phosphatidylcholines. A pattern consisting of high intake of potatoes, dairy products and cornflakes particularly explained methionine and branched chain amino acids. Dietary patterns related to type 2 diabetes-relevant metabolites included high intake of red meat and low intake of whole-grain bread, tea, coffee, cake and cookies, canned fruits and fish. Dietary patterns characterized by intakes of red meat, whole-grain bread, tea and coffee were linked to relevant metabolites and could be potential targets for chronic disease prevention.

  6. Targeted High Performance Liquid Chromatography Tandem Mass Spectrometry-based Metabolomics differentiates metabolic syndrome from obesity.

    Science.gov (United States)

    Zhong, Fanyi; Xu, Mengyang; Bruno, Richard S; Ballard, Kevin D; Zhu, Jiangjiang

    2017-04-01

    Both obesity and the metabolic syndrome are risk factors for type 2 diabetes and cardiovascular disease. Identification of novel biomarkers are needed to distinguish metabolic syndrome from equally obese individuals in order to direct them to early interventions that reduce their risk of developing further health problems. We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established metabolic syndrome criteria (i.e. elevated waist circumference, hypertension, elevated fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol) in plasma samples from obese men ( n = 29; BMI = 35.5 ± 5.2 kg/m 2 ) and women ( n = 40; 34.9 ± 6.7 kg/m 2 ), of which 26 met the criteria for metabolic syndrome (17 men and 9 women). Compared to obese individuals without metabolic syndrome, univariate statistical analysis and partial least squares discriminant analysis showed that a specific group of metabolites from multiple metabolic pathways (i.e. purine metabolism, valine, leucine and isoleucine degradation, and tryptophan metabolism) were associated with the presence of metabolic syndrome. Receiver operating characteristic curves generated based on the PLS-DA models showed excellent areas under the curve (0.85 and 0.96, for metabolites only model and enhanced metabolites model, respectively), high specificities (0.86 and 0.93), and good sensitivities (0.71 and 0.91). Moreover, principal component analysis revealed that metabolic profiles can be used to further differentiate metabolic syndrome with 3 versus 4-5 metabolic syndrome criteria. Collectively, these findings support targeted metabolomics approaches to distinguish metabolic syndrome from obesity alone, and to stratify metabolic syndrome status based on the number of criteria met. Impact statement We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to

  7. Metabolome-wide association study identified the association between a circulating polyunsaturated fatty acids variant rs174548 and lung cancer.

    Science.gov (United States)

    Wang, Cheng; Qin, Na; Zhu, Meng; Chen, Minjian; Xie, Kaipeng; Cheng, Yang; Dai, Juncheng; Liu, Jia; Xia, Yankai; Ma, Hongxia; Jin, Guangfu; Amos, Christopher I; Hu, Zhibin; Lin, Dongxin; Shen, Hongbing

    2017-10-26

    Quantitative trait loci (QTLs) are widely used as instruments to infer causal risk factors of diseases based on the idea of mendelian randomization. Plasma metabolites can serve as risk factors of cancer, and the heritability of many circulating metabolites was high. We conducted a metabolome-wide association study (MWAS) to systematically investigate the effects of genetic variants on metabolites and lung cancer based on published genome-wide association study (GWASs) and metabolic-QTL (mQTL) study. Then we confirmed the results by subsequent genetic and metabolic validations and inferred the causal relationship between identified metabolites and lung cancer through genetic variant(s). We firstly identified six polyunsaturated fatty acids (PUFAs) represented by rs174548-linked haplotype were significantly associated with lung cancer risk in a Chinese GWAS (2311 cases and 3077 controls). Rs174548 was further confirmed to be associated with lung cancer in 13 821 Europeans and 18 471 Asians (ORmeta = 0.87, Pmeta = 1.76 × 10-15) and the effect was much stronger in females (Pinteraction = 6.00 × 10-4). We next validated rs174548-plasma PUFA association in 253 Chinese subjects (β = -0.57, P = 1.68 × 10-3). Rs174548 was also found associated with FADS1 (the major fatty acid desaturase of identified PUFAs) expression in liver tissues. Taken together, we found that rs174548 was associated with both PUFAs and lung cancer. Because rs174548 was the only mQTL variant of PUFAs reported by previous GWASs and explained a large proportion of heritability, we proposed that plasma PUFAs could be causally associated with lung cancer based on the idea of mendelian randomization. These findings provide a diet-related risk factor and may have important implications for prevention on lung cancer. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome.

    Science.gov (United States)

    Chang, Alice Y; Lalia, Antigoni Z; Jenkins, Gregory D; Dutta, Tumpa; Carter, Rickey E; Singh, Ravinder J; Nair, K Sreekumaran

    2017-06-01

    Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. This multiethnic, obese sample was matched by age (PCOS, 37±6; MetS, 40±6years) and body mass index (BMI) (PCOS, 34.6±5.1; MetS, 33.7±5.2kg/m 2 ). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P=.02), essential amino acids (P=.03), the essential amino acid lysine (P=.02), and the lysine metabolite α-aminoadipic acid (P=.02) in models adjusted for surrogate variables representing technical variation in metabolites. No significant differences between

  9. Differentiating signals to make biological sense - A guide through databases for MS-based non-targeted metabolomics.

    Science.gov (United States)

    Gil de la Fuente, Alberto; Grace Armitage, Emily; Otero, Abraham; Barbas, Coral; Godzien, Joanna

    2017-09-01

    Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their online ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as identifier assignment, structural assignment and interpretation of results. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Targeted Metabolomics Approach To Detect the Misuse of Steroidal Aromatase Inhibitors in Equine Sports by Biomarker Profiling.

    Science.gov (United States)

    Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming

    2016-01-05

    The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups

  11. Liver enzymes, metabolomics and genome-wide association studies: from systems biology to the personalized medicine.

    Science.gov (United States)

    Sookoian, Silvia; Pirola, Carlos J

    2015-01-21

    For several decades, serum levels of alanine (ALT) and aspartate (AST) aminotransferases have been regarded as markers of liver injury, including a wide range of etiologies from viral hepatitis to fatty liver. The increasing worldwide prevalence of metabolic syndrome and cardiovascular disease revealed that transaminases are strong predictors of type 2 diabetes, coronary heart disease, atherothrombotic risk profile, and overall risk of metabolic disease. Therefore, it is plausible to suggest that aminotransferases are surrogate biomarkers of "liver metabolic functioning" beyond the classical concept of liver cellular damage, as their enzymatic activity might actually reflect key aspects of the physiology and pathophysiology of the liver function. In this study, we summarize the background information and recent findings on the biological role of ALT and AST, and review the knowledge gained from the application of genome-wide approaches and "omics" technologies that uncovered new concepts on the role of aminotransferases in human diseases and systemic regulation of metabolic functions. Prediction of biomolecular interactions between the candidate genes recently discovered to be associated with plasma concentrations of liver enzymes showed interesting interconnectivity nodes, which suggest that regulation of aminotransferase activity is a complex and highly regulated trait. Finally, links between aminotransferase genes and metabolites are explored to understand the genetic contributions to the metabolic diversity.

  12. Non-target effects of GM potato : an eco-metabolomics approach

    NARCIS (Netherlands)

    Plischke, Andreas

    2013-01-01

    In this thesis, patterns of variation in plant metabolomes and insect communities were described in GM and non-GM potato plants in both laboratory and field experiments. Differences between plant genotypes in insect abundances were small when compared to year-to-year differences, location effects

  13. Tracking small targets in wide area motion imagery data

    Science.gov (United States)

    Mathew, Alex; Asari, Vijayan K.

    2013-03-01

    Object tracking in aerial imagery is of immense interest to the wide area surveillance community. In this paper, we propose a method to track very small targets such as pedestrians in AFRL Columbus Large Image Format (CLIF) Wide Area Motion Imagery (WAMI) data. Extremely small target sizes, combined with low frame rates and significant view changes, make tracking a very challenging task in WAMI data. Two problems should be tackled for object tracking frame registration and feature extraction. We employ SURF for frame registration. Although there are several feature extraction methods that work reasonably well when the scene is of high resolution, most methods fail when the resolution is very low. In our approach, we represent the target as a collection of intensity histograms and use a robust statistical distance to distinguish between the target and the background. We divide the object into m ×n regions and compute the normalized intensity histogram in each region to build a histogram matrix. The features can be compared using the histogram comparison techniques. For tracking, we use a combination of a bearing-only Kalman filter and the proposed feature extraction technique. The problem of template drift is solved by further localizing the target with a blob detection algorithm. The new template is taken as the detected blob. We show the robustness of the algorithm by giving a comparison of feature extraction part of our method with other feature extraction methods like SURF, SIFT and HoG and tracking part with mean-shift tracking.

  14. Targeted metabolomic analyses of cellular models of pelizaeus-merzbacher disease reveal plasmalogen and myo-inositol solute carrier dysfunction

    Directory of Open Access Journals (Sweden)

    Pelzer Lindsay

    2011-06-01

    Full Text Available Abstract Background Leukodystrophies are devastating diseases characterized by dys- and hypo-myelination. While there are a number of histological and imaging studies of these disorders, there are limited biochemical data available. We undertook targeted lipidomic analyses of Pelizaeus-Merzbacher disease (PMD fibroblasts, PMD lymphocytes, and 158JP oligodendrocytes, a murine model of PMD, to define the lipid changes in these cell models. Further targeted metabolomics analyses were conducted to obtain a preliminary evaluation of the metabolic consequences of lipid changes and gene mutations in these cell models. Results In both PMD fibroblasts and lymphocytes, and 158JP oligodendrocytes, ethanolamine plasmalogens were significantly decreased. Labeling studies with 158JP oligodendrocytes further demonstrated a decreased rate of lipid remodeling at sn-2. Targeted metabolomics analyses of these cells revealed dramatic increases in cellular levels of myo-inositol. Further uptake studies demonstrated increased rates of myo-inositol uptake by PMD lymphocytes. Conclusions Our data demonstrating PlsEtn decrements, support previous studies indicating leukodystrophy cells possess significant peroxisomal deficits. Our data for the first time also demonstrate that decrements in peroxisomal function coupled with the PLP1 gene defects of PMD, result in changes in the function of membrane myo-inositol solute carriers resulting in dramatic increases in cellular myo-inositol levels.

  15. Metabolomic Studies in Drosophila.

    Science.gov (United States)

    Cox, James E; Thummel, Carl S; Tennessen, Jason M

    2017-07-01

    Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila, often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research. Copyright © 2017 by the Genetics Society of America.

  16. Non-targeted Plasma Metabolome of Early and Late Lactation Gilts.

    Science.gov (United States)

    Rempel, Lea A; Miles, Jeremy R; Oliver, William T; Broeckling, Corey D

    2016-01-01

    Female pigs nursing their first litter (first-parity gilts) have increased energy requirements not only to support their piglets, but they themselves are still maturing. Non-targeted plasma metabolomics were used to investigate the differences between (1) post-farrowing and weaning (early or late lactation), (2) degree of body condition loss after lactation (extreme or minimal), and (3) interactions; to potentially identify compounds or pathways that could aide in alleviating energetic demands of lactation in gilts. Twenty first-parity gilts were selected with similar ( P ≥ 0.4475) number of piglets born and nursed, and similar ( P ≥ 0.3141) body condition traits (e.g., body weight and backfat thickness) post-farrowing, yet exhibited minimal or extreme loss ( P ≤ 0.0094) in body weight (8.6 ± 1.48 kg and 26.1 ± 1.90 kg, respectively) and backfat thickness (1.3 ± 0.67 mm and 4.7 ± 0.86 mm, respectively) following lactation (weaning). Plasma samples from first-parity gilts at post-farrowing and weaning were investigated using UPLC-MS and GC-MS to generate a comprehensive metabolic profile. Each approach yielded approximately 700 detected features. An ANOVA was performed on each detected compound in R for time of collection, body condition change, and the interaction, followed by a false discovery correction. Two unknown features were different ( P ≤ 0.05) for extreme vs. minimal body condition change. Several compound differences ( P ≤ 0.05) were identified between post-farrowing and weaning. Thirty-two features detected by UPLC-MS had at least a log 2 fold-change of ±1.0 while only 18 features had a log 2 fold-change of ±0.6 or more for the significant GC-MS features. Annotation implicated various metabolic pathways. Creatinine was greater at weaning ( P = 0.0224) and others have reported increased serum concentrations of creatinine in response to body weight loss. Hippurate and caprolactam, associated with protein catabolism, were also greater ( P

  17. Non-targeted plasma metabolome of early and late lactation gilts

    Directory of Open Access Journals (Sweden)

    Lea A Rempel

    2016-11-01

    Full Text Available Female pigs nursing their first litter (first-parity gilts have increased energy requirements not only to support their piglets, but they themselves are still maturing. Non-targeted plasma metabolomics were used to investigate the differences between 1 post-farrowing and weaning (early or late lactation, 2 degree of body condition loss after lactation (extreme or minimal, and 3 interactions; to potentially identify compounds or pathways that could aide in alleviating energetic demands of lactation in gilts. Twenty first-parity gilts were selected with similar (P ≥ 0.4475 number of piglets born and nursed, and similar (P ≥ 0.3141 body condition traits (e.g. body weight and backfat thickness post-farrowing, yet exhibited minimal or extreme loss (P ≤ 0.0094 in body weight (8.6 ± 1.48 kg and 26.1 ± 1.90 kg, respectively and backfat thickness (1.3 ± 0.67 mm and 4.7 ± 0.86 mm, respectively following lactation (weaning. Plasma samples from first-parity gilts at post-farrowing and weaning were investigated using UPLC-MS and GC-MS to generate a comprehensive metabolic profile. Each approach yielded approximately 700 detected compounds. An ANOVA was performed on each detected compound in R for time of collection, body condition change, and the interaction, followed by a false discovery correction. Two unknown compounds were different (P ≤ 0.05 for extreme versus minimal body condition change. Several compound differences (P ≤ 0.05 were identified between post-farrowing and weaning. Thirty-two compounds detected by UPLC-MS had at least a log2 fold-change of ±1.0 while only 18 compounds had a log2 fold-change of ±0.6 for the significant GC-MS compounds. Annotation implicated various metabolic pathways. Creatinine was greater at weaning (P = 0.0224 and others have reported increased serum concentrations of creatinine in response to body weight loss. Hippurate and caprolactam, associated with protein catabolism, were also greater (P ≤ 0

  18. Hypothalamus metabolomic profiling to elucidate the tissue-targeted biochemical basis of febrile response in yeast-induced pyrexia rats.

    Science.gov (United States)

    Liu, Haiyu; Zhang, Li; Zhao, Baosheng; Zhang, Zhixin; Qin, Lingling; Zhang, Qingqing; Wang, Qing; Lu, Zhiwei; Gao, Xiaoyan

    2015-04-25

    In the previous reports regarding thermoregulation, the hypothalamus is thought to be the primary centre in the central nervous system for controlling the body temperature. However, to date, there has not been sufficient evidence to reveal its thermoregulatory mechanism. In the current study, we utilised a tissue-targeted metabolomics strategy to elucidate the underlying biochemical mechanisms of thermoregulation in the fever process by analysing the global metabolic profile of the hypothalamus in yeast-induced pyrexia rats. Data acquisition was completed using the HPLC-LTQ-Orbitrap/MS in both positive and negative ion mode. Principal component analysis was used to observe the cluster characteristics between the control group and the pyrexia group. Potential biomarkers were screened using orthogonal partial least-squares-discriminant analysis. Seventeen potential biomarkers were identified in the hypothalamus samples to discriminate the control and pyrexia groups, including amino acids, nucleic acids, vitamins, carbohydrates, and phospholipids. As a result, purine metabolism was enhanced pronouncedly, and perturbation of lipid metabolism was also observed. Meanwhile, amino acid metabolism and energy metabolism were also activated significantly. In conclusion, the study indicated that hypothalamus-targeted metabolomics could provide a powerful tool to further understand the pathogenesis of febrile response. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  19. Genome-wide identification of KANADI1 target genes.

    Directory of Open Access Journals (Sweden)

    Paz Merelo

    Full Text Available Plant organ development and polarity establishment is mediated by the action of several transcription factors. Among these, the KANADI (KAN subclade of the GARP protein family plays important roles in polarity-associated processes during embryo, shoot and root patterning. In this study, we have identified a set of potential direct target genes of KAN1 through a combination of chromatin immunoprecipitation/DNA sequencing (ChIP-Seq and genome-wide transcriptional profiling using tiling arrays. Target genes are over-represented for genes involved in the regulation of organ development as well as in the response to auxin. KAN1 affects directly the expression of several genes previously shown to be important in the establishment of polarity during lateral organ and vascular tissue development. We also show that KAN1 controls through its target genes auxin effects on organ development at different levels: transport and its regulation, and signaling. In addition, KAN1 regulates genes involved in the response to abscisic acid, jasmonic acid, brassinosteroids, ethylene, cytokinins and gibberellins. The role of KAN1 in organ polarity is antagonized by HD-ZIPIII transcription factors, including REVOLUTA (REV. A comparison of their target genes reveals that the REV/KAN1 module acts in organ patterning through opposite regulation of shared targets. Evidence of mutual repression between closely related family members is also shown.

  20. Interlaboratory Reproducibility of a Targeted Metabolomics Platform for Analysis of Human Serum and Plasma.

    Science.gov (United States)

    Siskos, Alexandros P; Jain, Pooja; Römisch-Margl, Werner; Bennett, Mark; Achaintre, David; Asad, Yasmin; Marney, Luke; Richardson, Larissa; Koulman, Albert; Griffin, Julian L; Raynaud, Florence; Scalbert, Augustin; Adamski, Jerzy; Prehn, Cornelia; Keun, Hector C

    2017-01-03

    A critical question facing the field of metabolomics is whether data obtained from different centers can be effectively compared and combined. An important aspect of this is the interlaboratory precision (reproducibility) of the analytical protocols used. We analyzed human samples in six laboratories using different instrumentation but a common protocol (the AbsoluteIDQ p180 kit) for the measurement of 189 metabolites via liquid chromatography (LC) or flow injection analysis (FIA) coupled to tandem mass spectrometry (MS/MS). In spiked quality control (QC) samples 82% of metabolite measurements had an interlaboratory precision of metabolomics assay illustrating the reproducibility of the protocol and how data generated on different instruments could be directly integrated in large-scale epidemiological studies.

  1. Non-target effects of GM potato: an eco-metabolomics approach

    OpenAIRE

    Plischke, Andreas

    2013-01-01

    In this thesis, patterns of variation in plant metabolomes and insect communities were described in GM and non-GM potato plants in both laboratory and field experiments. Differences between plant genotypes in insect abundances were small when compared to year-to-year differences, location effects and differences between developmental stages of plants. Standardized effect sizes are discussed as an alternative scale for measuring effects. Leaf age, aphid infestation and virus infection were fou...

  2. Capillary electrophoresis mass spectrometry based metabolomics

    Directory of Open Access Journals (Sweden)

    Alexander M. Buko

    2017-03-01

    Full Text Available Capillary electrophoresis–mass spectrometry (CE-MS is a powerful orthogonal technique capable of filling in gaps in the identification, quantitation and isomeric resolution of many small hydrophilic and charged metabolites. The metabolome is a large complex mixture of molecules for which not one technique nor a combination of techniques can optimally identify and measure it in it’s entirety. LC-MS, GC-MS and NMR have been the widely used for metabolomics for the past 20 years for a wide range of applications, each technique having shown uniqueness and advantages, for specific applications or target metabolic chemical space. CE-MS captures a unique metabolic chemical space beyond these standard methods providing another window into metabolomics profiling. This review will focus on the recent publications published within 2016 focusing on biotechnology and pharmaceutical applications of CE-MS.

  3. Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study

    Science.gov (United States)

    Oommen, Anup M.; Varma, Sudhir; Casanova, Ramon; An, Yang; O’Brien, Richard; Pletnikova, Olga; Kastenmueller, Gabi; Doraiswamy, P. Murali; Kaddurah-Daouk, Rima; Thambisetty, Madhav

    2018-01-01

    Background The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. Methods and findings Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and “asymptomatic Alzheimer’s disease” (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes—sphingolipids and glycerophospholipids—that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer’s Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that

  4. One-pot microwave derivatization of target compounds relevant to metabolomics with comprehensive two-dimensional gas chromatography.

    Science.gov (United States)

    Kouremenos, Konstantinos A; Harynuk, James J; Winniford, William L; Morrison, Paul D; Marriott, Philip J

    2010-07-01

    Metabolomics has been defined as the quantitative measurement of all low molecular weight metabolites (sugars, amino acids, organic acids, fatty acids and others) in an organism's cells at a specified time under specific environmental/biological conditions. Currently, there is considerable interest in developing a single method of derivatization and separation that satisfies the needs for metabolite analysis while recognizing the many chemical classes that constitute the metabolome. Chemical derivatization considerably increases the sensitivity and specificity of gas chromatography-mass spectrometry for compounds that are polar and have derivatizable groups. Microwave-assisted derivatization (MAD) of a set of standards spanning a wide range of metabolites of interest demonstrates the potential of MAD for metabolic profiling. A final protocol of 150 W power for 90 s was selected as the derivatization condition, based upon the study of each chemical class. A study of the generation of partially derivatized components established the conditions where this could potentially be a problem; the use of greater volumes of reagent ensured this would not arise. All compounds analyzed by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry in a standard mixture showed good area ratio reproducibility against a naphthalene internal standard (RSDmetabolomics is demonstrated. Copyright 2010 Elsevier B.V. All rights reserved.

  5. Evaluating plant immunity using mass spectrometry-based metabolomics workflows

    Directory of Open Access Journals (Sweden)

    Adam L Heuberger

    2014-06-01

    Full Text Available Metabolic processes in plants are key components of physiological and biochemical disease resistance. Metabolomics, the analysis of a broad range of small molecule compounds in a biological system, has been used to provide a systems-wide overview of plant metabolism associated with defense responses. Plant immunity has been examined using multiple metabolomics workflows that vary in methods of detection, annotation, and interpretation, and the choice of workflow can significantly impact the conclusions inferred from a metabolomics investigation. The broad range of metabolites involved in plant defense often supports the need for multiple chemical detection platforms and implementation of a non-targeted approach. A review of the current literature reveals a wide range of workflows that are currently used in plant metabolomics, and new methods for analyzing and reporting mass spectrometry data can improve the ability to translate investigative findings among different plant-pathogen systems.

  6. The human urine metabolome

    National Research Council Canada - National Science Library

    Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R; Knox, Craig; Bjorndahl, Trent C; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S

    2013-01-01

    .... Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine...

  7. Genome-wide identification of direct HBx genomic targets

    KAUST Repository

    Guerrieri, Francesca

    2017-02-17

    Background The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post-translational modifications and to regulate viral cccDNA transcription and cellular gene expression. Aiming to identify genes and non-coding RNAs (ncRNAs) directly targeted by HBx, we performed a chromatin immunoprecipitation sequencing (ChIP-Seq) to analyse HBV recruitment on host cell chromatin in cells replicating HBV. Results ChIP-Seq high throughput sequencing of HBx-bound fragments was used to obtain a high-resolution, unbiased, mapping of HBx binding sites across the genome in HBV replicating cells. Protein-coding genes and ncRNAs involved in cell metabolism, chromatin dynamics and cancer were enriched among HBx targets together with genes/ncRNAs known to modulate HBV replication. The direct transcriptional activation of genes/miRNAs that potentiate endocytosis (Ras-related in brain (RAB) GTPase family) and autophagy (autophagy related (ATG) genes, beclin-1, miR-33a) and the transcriptional repression of microRNAs (miR-138, miR-224, miR-576, miR-596) that directly target the HBV pgRNA and would inhibit HBV replication, contribute to HBx-mediated increase of HBV replication. Conclusions Our ChIP-Seq analysis of HBx genome wide chromatin recruitment defined the repertoire of genes and ncRNAs directly targeted by HBx and led to the identification of new mechanisms by which HBx positively regulates cccDNA transcription and HBV replication.

  8. Complexity and pitfalls of mass spectrometry-based targeted metabolomics in brain research.

    Science.gov (United States)

    Urban, Michael; Enot, David P; Dallmann, Guido; Körner, Lisa; Forcher, Verena; Enoh, Peter; Koal, Therese; Keller, Matthias; Deigner, Hans-Peter

    2010-11-15

    Current quantitative metabolomic research in brain tissue is challenged by several analytical issues. To compare data of metabolite pattern, ratios of individual metabolite concentrations and composed classifiers characterizing a distinct state, standardized workup conditions, and extraction medium are crucial. Differences in physicochemical properties of individual compounds and compound classes such as polarity determine extraction yields and, thus, ratios of compounds with varying properties. Also, variations in suppressive effects related to coextracted matrix components affect standards or references and their concentration-dependent responses.The selection of a common tissue extraction protocol is an ill-posed problem because it can be regarded as a multiple objective decision depending on factors such as sample handling practicability, measurement precision, control of matrix effects, and relevance of the chemical assay. This study systematically evaluates the impact of extraction solvents and the impact of the complex brain tissue on measured metabolite levels, taking into account ionization efficiency as well as challenges encountered in the trace-level quantification of the analytes in brain matrices. In comparison with previous studies that relied on nontargeted platforms, consequently emphasizing the global behavior of the metabolomic fingerprint, here we focus on several series of metabolites spanning over extensive polarity, concentration, and molecular mass ranges. Copyright 2010 Elsevier Inc. All rights reserved.

  9. Mapping Proteome-wide Targets of Glyphosate in Mice.

    Science.gov (United States)

    Ford, Breanna; Bateman, Leslie A; Gutierrez-Palominos, Leilani; Park, Robin; Nomura, Daniel K

    2017-02-16

    Glyphosate, the active ingredient in the herbicide Roundup, is one of the most widely used pesticides in agriculture and home garden use. Whether glyphosate causes any mammalian toxicity remains highly controversial. While many studies have associated glyphosate with numerous adverse health effects, the mechanisms underlying glyphosate toxicity in mammals remain poorly understood. Here, we used activity-based protein profiling to map glyphosate targets in mice. We show that glyphosate at high doses can be metabolized in vivo to reactive metabolites such as glyoxylate and react with cysteines across many proteins in mouse liver. We show that glyoxylate inhibits liver fatty acid oxidation enzymes and glyphosate treatment in mice increases the levels of triglycerides and cholesteryl esters, likely resulting from diversion of fatty acids away from oxidation and toward other lipid pathways. Our study highlights the utility of using chemoproteomics to identify novel toxicological mechanisms of environmental chemicals such as glyphosate. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Comprehensive Metabolomic, Lipidomic and Microscopic Profiling of Yarrowia lipolytica during Lipid Accumulation Identifies Targets for Increased Lipogenesis.

    Directory of Open Access Journals (Sweden)

    Kyle R Pomraning

    Full Text Available Yarrowia lipolytica is an oleaginous ascomycete yeast that accumulates large amounts of lipids and has potential as a biofuel producing organism. Despite a growing scientific literature focused on lipid production by Y. lipolytica, there remain significant knowledge gaps regarding the key biological processes involved. We applied a combination of metabolomic and lipidomic profiling approaches as well as microscopic techniques to identify and characterize the key pathways involved in de novo lipid accumulation from glucose in batch cultured, wild-type Y. lipolytica. We found that lipids accumulated rapidly and peaked at 48 hours during the five day experiment, concurrent with a shift in amino acid metabolism. We also report that exhaustion of extracellular sugars coincided with thickening of the cell wall, suggesting that genes involved in cell wall biogenesis may be a useful target for improving the efficiency of lipid producing yeast strains.

  11. Targeted and Untargeted Metabolomics to Explore the Bioavailability of the Secoiridoids from a Seed/Fruit Extract (Fraxinus angustifolia Vahl in Human Healthy Volunteers: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Rocío García-Villalba

    2015-12-01

    Full Text Available The bark, seeds, fruits and leaves of the genus Fraxinus (Oleaceae which contain a wide range of phytochemicals, mostly secoiridoid glucosides, have been widely used in folk medicine against a number of ailments, yet little is known about the metabolism and uptake of the major Fraxinus components. The aim of this work was to advance in the knowledge on the bioavailability of the secoiridoids present in a Fraxinus angustifolia Vahl seed/fruit extract using both targeted and untargeted metabolomic analyses. Plasma and urine samples from nine healthy volunteers were taken at specific time intervals following the intake of the extract and analyzed by UPLC-ESI-QTOF. Predicted metabolites such as tyrosol and ligstroside-aglycone glucuronides and sulfates were detected at low intensity. These compounds reached peak plasma levels 2 h after the intake and exhibited high variability among the participants. The ligstroside-aglycone conjugates may be considered as potential biomarkers of the Fraxinus secoiridoids intake. Using the untargeted approach we additionally detected phenolic conjugates identified as ferulic acid and caffeic acid sulfates, as well as hydroxybenzyl and hydroxyphenylacetaldehyde sulfate derivatives which support further metabolism of the secoiridoids by phase I and (or microbial enzymes. Overall, the results of this study suggest low uptake of intact secoiridoids from a Fraxinus angustifolia Vahl extract in healthy human volunteers and metabolic conversion by esterases, glycosidases, and phase II sulfo- and glucuronosyl transferases to form smaller conjugated derivatives.

  12. Impact of targeted UPLC-MS/MS metabolomics on chemical and biochemical characterisation of MAPs

    Directory of Open Access Journals (Sweden)

    Martens, Stefan

    2016-07-01

    Full Text Available Analysis of natural product pattern (metabolites; metabolomics and its formation (pathway; biosynthesis in plants, especially in non-model or crop plants such as medicinal and aromatic plants (MAPs, is a research field with significant potential for breeders, growers and consumers. There is an increasing importance for constant and sustainable quality of MAPs final products. Polyphenols are one of the most important compounds for the antioxidant properties of MAPs and are often, if not identified as active principle, used as lead compounds in quality assessment of herbal drugs and related preparation (herbal tea, alcoholic extracts etc.. Therefore, offering an efficient, robust and reliable fast tool to determine these quality features of MAPs will guarantee the growers, industrial users and the consumers from possible frauds.

  13. Measurement of 1,5-anhydroglucitol in blood and saliva: from non-targeted metabolomics to biochemical assay.

    Science.gov (United States)

    Halama, Anna; Kulinski, Michal; Kader, Sara Abdul; Satheesh, Noothan J; Abou-Samra, Abdul Badi; Suhre, Karsten; Mohammad, Ramzi M

    2016-05-18

    Diabetes testing using saliva, rather than blood and urine, could facilitate diabetes screening in public spaces. We previously identified 1,5-anhydro-D-glucitol (1,5-AG) in saliva as a diabetes biomarker. The Glycomark™ assay kit is FDA approved for 1,5-AG measurement in blood. Here we evaluated its applicability for 1,5-AG quantification in saliva. Using pooled saliva samples, we validated Glycomark™ assay use with a RX Daytona(+) clinical chemistry analyser. We then used this set-up to analyse 82 paired blood and saliva samples from a diabetes case-control study, for which broad mass spectrometry-based characterization of the blood and saliva metabolome was also available. Osmolality was measured to account for potential variability in saliva samples. The technical variability of the read-outs for the pooled saliva samples (CV = 2.05 %) was comparable to that obtained with manufacturer-provided blood surrogate quality controls (CV = 1.38-1.8 %). We found a high correlation between Glycomark assay and mass spectrometry measurements of serum 1,5-AG (r(2) = 0.902), showing reproducibility of the non-targeted metabolomics results. The significant correlation between the osmolality measurements performed at two independent platforms with the time interval of 2 years (r(2) = 0.887), also indicates the sample integrity. The assay read-out for saliva was not correlated with the mass spectrometry-based 1,5-AG saliva measurements. Comparison with the full saliva metabolome revealed a high correlation of the saliva assay read-outs with galactose. Glycomark™ assay read-outs for saliva were stable and replicable. However, the signal was dominated by galactose, which is biochemically similar to 1,5-AG and absent in blood. Adapting the 1,5-AG kit for saliva analysis will require enzymatic depletion of galactose. This should be feasible, since the assay already includes a similar step for glucose depletion from blood samples.

  14. The human serum metabolome.

    Directory of Open Access Journals (Sweden)

    Nikolaos Psychogios

    2011-02-01

    Full Text Available Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.

  15. Targeted Metabolomics Reveals Early Dominant Optic Atrophy Signature in Optic Nerves of Opa1delTTAG/+ Mice.

    Science.gov (United States)

    Chao de la Barca, Juan Manuel; Simard, Gilles; Sarzi, Emmanuelle; Chaumette, Tanguy; Rousseau, Guillaume; Chupin, Stéphanie; Gadras, Cédric; Tessier, Lydie; Ferré, Marc; Chevrollier, Arnaud; Desquiret-Dumas, Valérie; Gueguen, Naïg; Leruez, Stéphanie; Verny, Christophe; Miléa, Dan; Bonneau, Dominique; Amati-Bonneau, Patrizia; Procaccio, Vincent; Hamel, Christian; Lenaers, Guy; Reynier, Pascal; Prunier-Mirebeau, Delphine

    2017-02-01

    Dominant optic atrophy (MIM No. 165500) is a blinding condition related to mutations in OPA1, a gene encoding a large GTPase involved in mitochondrial inner membrane dynamics. Although several mouse models mimicking the disease have been developed, the pathophysiological mechanisms responsible for retinal ganglion cell degeneration remain poorly understood. Using a targeted metabolomic approach, we measured the concentrations of 188 metabolites in nine tissues, that is, brain, three types of skeletal muscle, heart, liver, retina, optic nerve, and plasma in symptomatic 11-month-old Opa1delTTAG/+ mice. Significant metabolic signatures were found only in the optic nerve and plasma of female mice. The optic nerve signature was characterized by altered concentrations of phospholipids, amino acids, acylcarnitines, and carnosine, whereas the plasma signature showed decreased concentrations of amino acids and sarcosine associated with increased concentrations of several phospholipids. In contrast, the investigation of 3-month-old presymptomatic Opa1delTTAG/+ mice showed no specific plasma signature but revealed a significant optic nerve signature in both sexes, although with a sex effect. The Opa1delTTAG/+ versus wild-type optic nerve signature was characterized by the decreased concentrations of 10 sphingomyelins and 10 lysophosphatidylcholines, suggestive of myelin sheath alteration, and by alteration in the concentrations of metabolites involved in neuroprotection, such as dimethylarginine, carnitine, spermine, spermidine, carnosine, and glutamate, suggesting a concomitant axonal metabolic dysfunction. Our comprehensive metabolomic investigations revealed in symptomatic as well as in presymptomatic Opa1delTTAG/+ mice, a specific sensitiveness of the optic nerve to Opa1 insufficiency, opening new routes for protective therapeutic strategies.

  16. Metabolomics strategy for the mapping of volatile exometabolome from Saccharomyces spp. widely used in the food industry based on comprehensive two-dimensional gas chromatography.

    Science.gov (United States)

    Martins, Cátia; Brandão, Tiago; Almeida, Adelaide; Rocha, Sílvia M

    2017-05-01

    Saccharomyces spp. are widely used in the food and beverages industries. Their cellular excreted metabolites are important for general quality of products and can contribute to product differentiation. This exploratory study presents a metabolomics strategy for the comprehensive mapping of cellular metabolites of two yeast species, Saccharomyces cerevisiae and S. pastorianus (both collected in an industrial context) through a multidimensional chromatography platform. Solid-phase microextraction was used as a sample preparation method. The yeast viability, a specific technological quality parameter, was also assessed. This untargeted analysis allowed the putative identification of 525 analytes, distributed over 14 chemical families, the origin of which may be explained through the pathways network associated with yeasts metabolism. The expression of the different metabolic pathways was similar for both species, event that seems to be yeast genus dependent. Nevertheless, these species showed different growth rates, which led to statistically different metabolites content. This was the first in-depth approach that characterizes the headspace content of S. cerevisiae and S. pastorianus species cultures. The combination of a sample preparation method capable of providing released volatile metabolites directly from yeast culture headspace with comprehensive two-dimensional gas chromatography was successful in uncovering a specific metabolomic pattern for each species. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Metabolomics studies in brain tissue: A review.

    Science.gov (United States)

    Gonzalez-Riano, Carolina; Garcia, Antonia; Barbas, Coral

    2016-10-25

    Brain is still an organ with a composition to be discovered but beyond that, mental disorders and especially all diseases that curse with dementia are devastating for the patient, the family and the society. Metabolomics can offer an alternative tool for unveiling new insights in the discovery of new treatments and biomarkers of mental disorders. Until now, most of metabolomic studies have been based on biofluids: serum/plasma or urine, because brain tissue accessibility is limited to animal models or post mortem studies, but even so it is crucial for understanding the pathological processes. Metabolomics studies of brain tissue imply several challenges due to sample extraction, along with brain heterogeneity, sample storage, and sample treatment for a wide coverage of metabolites with a wide range of concentrations of many lipophilic and some polar compounds. In this review, the current analytical practices for target and non-targeted metabolomics are described and discussed with emphasis on critical aspects: sample treatment (quenching, homogenization, filtration, centrifugation and extraction), analytical methods, as well as findings considering the used strategies. Besides that, the altered analytes in the different brain regions have been associated with their corresponding pathways to obtain a global overview of their dysregulation, trying to establish the link between altered biological pathways and pathophysiological conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels: A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study.

    Directory of Open Access Journals (Sweden)

    Christoph Nowak

    2016-10-01

    Full Text Available Insulin resistance (IR and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or β-cell responsiveness (disposition index during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613 followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330, we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining "gold standard" measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.

  19. Targeted metabolomics shows plasticity in the evolution of signaling lipids and uncovers old and new endocannabinoids in the plant kingdom.

    Science.gov (United States)

    Gachet, María Salomé; Schubert, Alexandra; Calarco, Serafina; Boccard, Julien; Gertsch, Jürg

    2017-01-25

    The remarkable absence of arachidonic acid (AA) in seed plants prompted us to systematically study the presence of C20 polyunsaturated fatty acids, stearic acid, oleic acid, jasmonic acid (JA), N-acylethanolamines (NAEs) and endocannabinoids (ECs) in 71 plant species representative of major phylogenetic clades. Given the difficulty of extrapolating information about lipid metabolites from genetic data we employed targeted metabolomics using LC-MS/MS and GC-MS to study these signaling lipids in plant evolution. Intriguingly, the distribution of AA among the clades showed an inverse correlation with JA which was less present in algae, bryophytes and monilophytes. Conversely, ECs co-occurred with AA in algae and in the lower plants (bryophytes and monilophytes), thus prior to the evolution of cannabinoid receptors in Animalia. We identified two novel EC-like molecules derived from the eicosatetraenoic acid juniperonic acid, an omega-3 structural isomer of AA, namely juniperoyl ethanolamide and 2-juniperoyl glycerol in gymnosperms, lycophytes and few monilophytes. Principal component analysis of the targeted metabolic profiles suggested that distinct NAEs may occur in different monophyletic taxa. This is the first report on the molecular phylogenetic distribution of apparently ancient lipids in the plant kingdom, indicating biosynthetic plasticity and potential physiological roles of EC-like lipids in plants.

  20. Microbial metabolomics: Replacing trial-and-error by the unbiased selection and ranking of targets

    NARCIS (Netherlands)

    Werf, M.J. van der; Jellema, R.H.; Hankemeier, T.

    2005-01-01

    Microbial production strains are currently improved using a combination of random and targeted approaches. In the case of a targeted approach, potential bottlenecks, feed-back inhibition, and side-routes are removed, and other processes of interest are targeted by overexpressing or knocking-out the

  1. Wide field-of-view target detection and simultaneous narrow field of view target analysis

    Science.gov (United States)

    Nichols, Richard W.; Miller, Geoffrey M.

    2009-05-01

    Protecting national borders, military and industrial complexes, national Infrastructure and high-value targets is critical to national security. Traditional solutions use a combination of ground surveillance radar, motion detection systems and video surveillance systems. Our development objective was to provide wide area 360-degree surveillance and ground-moving target detection using a passive optical system. In order to meet this objective, the development of an optical system capable of wide-area surveillance with intelligent cueing, high-resolution tracking and target identification is required. The predominant approach to optical surveillance has traditionally been gimbaled narrow field-of-view systems. These systems miss the majority of events occurring around them because of their inability to focus on anything other than a single event or object at any one time. Details of the system requirements definition, design trade studies and selected design configurations are discussed. The experimental results obtained during the current development phase have provided consistently high quality images and enhanced situational awareness. A summary of field validation methods and results is provided.

  2. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

    Science.gov (United States)

    Carroll, Adam J; Badger, Murray R; Harvey Millar, A

    2010-07-14

    Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published

  3. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

    Directory of Open Access Journals (Sweden)

    Carroll Adam J

    2010-07-01

    Full Text Available Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Description Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.. Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP their own data to the server for online processing via a novel raw data processing pipeline. Conclusions MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to

  4. The food metabolome

    DEFF Research Database (Denmark)

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine

    2014-01-01

    The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according...... to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food...... by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still...

  5. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Bhowmik Salil [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of); Lee, Young-Joo; Yi, Hong Jae [College of Pharmacy, Kyung Hee University, Hoegi-dong, Dongdaemun-gu, Seoul 130-791 (Korea, Republic of); Chung, Bong Chul [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); Jung, Byung Hwa, E-mail: jbhluck@kist.re.kr [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of)

    2010-02-19

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg{sup -1} day{sup -1} or 250 mg kg{sup -1} day{sup -1} for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  6. Plasma biomarker discovery for early chronic kidney disease diagnosis based on chemometric approaches using LC-QTOF targeted metabolomics data.

    Science.gov (United States)

    Benito, S; Sánchez-Ortega, A; Unceta, N; Jansen, J J; Postma, G; Andrade, F; Aldámiz-Echevarria, L; Buydens, L M C; Goicolea, M A; Barrio, R J

    2018-02-05

    Chronic kidney disease (CKD) is a progressive pathological condition in which renal function deteriorates in time. The first diagnosis of CKD is often carried out in general care attention by general practitioners by means of serum creatinine (CNN) levels. However, it lacks sensitivity and thus, there is a need for new robust biomarkers to allow the detection of kidney damage particularly in early stages. Multivariate data analysis of plasma concentrations obtained from LC-QTOF targeted metabolomics method may reveal metabolites suspicious of being either up-regulated or down-regulated from urea cycle, arginine methylation and arginine-creatine metabolic pathways in CKD pediatrics and controls. The results show that citrulline (CIT), symmetric dimethylarginine (SDMA) and S-adenosylmethionine (SAM) are interesting biomarkers to support diagnosis by CNN: early CKD samples and controls were classified with an increase in classification accuracy of 18% when using these 4 metabolites compared to CNN alone. These metabolites together allow classification of the samples into a definite stage of the disease with an accuracy of 74%, being the 90% of the misclassifications one level above or below the CKD stage set by the nephrologists. Finally, sex-related, age-related and treatment-related effects were studied, to evaluate whether changes in metabolite concentration could be attributable to these factors, and to correct them in case a new equation is developed with these potential biomarkers for the diagnosis and monitoring of pediatric CKD. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. A Non-targeted Metabolomics Approach Unravels the VOCs Associated with the Tomato Immune Response against Pseudomonas syringae

    Directory of Open Access Journals (Sweden)

    María Pilar López-Gresa

    2017-07-01

    Full Text Available Volatile organic compounds (VOCs emitted by plants are secondary metabolites that mediate the plant interaction with pathogens and herbivores. These compounds may perform direct defensive functions, i.e., acting as antioxidant, antibacterial, or antifungal agents, or indirectly by signaling the activation of the plant’s defensive responses. Using a non-targeted GC-MS metabolomics approach, we identified the profile of the VOCs associated with the differential immune response of the Rio Grande tomato leaves infected with either virulent or avirulent strains of Pseudomonas syringae DC3000 pv. tomato. The VOC profile of the tomato leaves infected with avirulent bacteria is characterized by esters of (Z-3-hexenol with acetic, propionic, isobutyric or butyric acids, and several hydroxylated monoterpenes, e.g., linalool, α-terpineol, and 4-terpineol, which defines the profile of an immunized plant response. In contrast, the same tomato cultivar infected with the virulent bacteria strain produced a VOC profile characterized by monoterpenes and SA derivatives. Interestingly, the differential VOCs emission correlated statistically with the induction of the genes involved in their biosynthetic pathway. Our results extend plant defense system knowledge and suggest the possibility for generating plants engineered to over-produce these VOCs as a complementary strategy for resistance.

  8. Characterisation of genome-wide PLZF/RARA target genes.

    Directory of Open Access Journals (Sweden)

    Salvatore Spicuglia

    Full Text Available The PLZF/RARA fusion protein generated by the t(11;17(q23;q21 translocation in acute promyelocytic leukaemia (APL is believed to act as an oncogenic transcriptional regulator recruiting epigenetic factors to genes important for its transforming potential. However, molecular mechanisms associated with PLZF/RARA-dependent leukaemogenesis still remain unclear.We searched for specific PLZF/RARA target genes by ChIP-on-chip in the haematopoietic cell line U937 conditionally expressing PLZF/RARA. By comparing bound regions found in U937 cells expressing endogenous PLZF with PLZF/RARA-induced U937 cells, we isolated specific PLZF/RARA target gene promoters. We next analysed gene expression profiles of our identified target genes in PLZF/RARA APL patients and analysed DNA sequences and epigenetic modification at PLZF/RARA binding sites. We identify 413 specific PLZF/RARA target genes including a number encoding transcription factors involved in the regulation of haematopoiesis. Among these genes, 22 were significantly down regulated in primary PLZF/RARA APL cells. In addition, repressed PLZF/RARA target genes were associated with increased levels of H3K27me3 and decreased levels of H3K9K14ac. Finally, sequence analysis of PLZF/RARA bound sequences reveals the presence of both consensus and degenerated RAREs as well as enrichment for tissue-specific transcription factor motifs, highlighting the complexity of targeting fusion protein to chromatin. Our study suggests that PLZF/RARA directly targets genes important for haematopoietic development and supports the notion that PLZF/RARA acts mainly as an epigenetic regulator of its direct target genes.

  9. Genome-wide analysis of Polycomb targets in Drosophila

    Energy Technology Data Exchange (ETDEWEB)

    Schwartz, Yuri B.; Kahn, Tatyana G.; Nix, David A.; Li,Xiao-Yong; Bourgon, Richard; Biggin, Mark; Pirrotta, Vincenzo

    2006-04-01

    Polycomb Group (PcG) complexes are multiprotein assemblages that bind to chromatin and establish chromatin states leading to epigenetic silencing. PcG proteins regulate homeotic genes in flies and vertebrates but little is known about other PcG targets and the role of the PcG in development, differentiation and disease. We have determined the distribution of the PcG proteins PC, E(Z) and PSC and of histone H3K27 trimethylation in the Drosophila genome. At more than 200 PcG target genes, binding sites for the three PcG proteins colocalize to presumptive Polycomb Response Elements (PREs). In contrast, H3 me3K27 forms broad domains including the entire transcription unit and regulatory regions. PcG targets are highly enriched in genes encoding transcription factors but receptors, signaling proteins, morphogens and regulators representing all major developmental pathways are also included.

  10. Functional metabolomics: from biomarker discovery to metabolome reprogramming.

    Science.gov (United States)

    Peng, Bo; Li, Hui; Peng, Xuan-Xian

    2015-09-01

    Metabolomics is emerging as a powerful tool for studying metabolic processes, identifying crucial biomarkers responsible for metabolic characteristics and revealing metabolic mechanisms, which construct the content of discovery metabolomics. The crucial biomarkers can be used to reprogram a metabolome, leading to an aimed metabolic strategy to cope with alteration of internal and external environments, naming reprogramming metabolomics here. The striking feature on the similarity of the basic metabolic pathways and components among vastly different species makes the reprogramming metabolomics possible when the engineered metabolites play biological roles in cellular activity as a substrate of enzymes and a regulator to other molecules including proteins. The reprogramming metabolomics approach can be used to clarify metabolic mechanisms of responding to changed internal and external environmental factors and to establish a framework to develop targeted tools for dealing with the changes such as controlling and/or preventing infection with pathogens and enhancing host immunity against pathogens. This review introduces the current state and trends of discovery metabolomics and reprogramming metabolomics and highlights the importance of reprogramming metabolomics.

  11. Integrative metabolomics as emerging tool to study autophagy regulation

    Directory of Open Access Journals (Sweden)

    Sarah Stryeck

    2017-07-01

    Full Text Available Recent technological developments in metabolomics research have enabled in-depth characterization of complex metabolite mixtures in a wide range of biological, biomedical, environmental, agricultural, and nutritional research fields. Nuclear magnetic resonance spectroscopy and mass spectrometry are the two main platforms for performing metabolomics studies. Given their broad applicability and the systemic insight into metabolism that can be ob-tained it is not surprising that metabolomics becomes increasingly popular in basic biological research. In this review, we provide an overview on key me-tabolites, recent studies, and future opportunities for metabolomics in stud-ying autophagy regulation. Metabolites play a pivotal role in autophagy regulation and are therefore key targets for autophagy research. Given the recent success of metabolomics, it can be expected that metabolomics ap-proaches will contribute significantly to deciphering the complex regulatory mechanisms involved in autophagy in the near future and promote under-standing of autophagy and autophagy-related diseases in living cells and or-ganisms.

  12. Nutritional metabolomics: Progress in addressing complexity in diet and health

    Science.gov (United States)

    Jones, Dean P.; Park, Youngja; Ziegler, Thomas R.

    2013-01-01

    Nutritional metabolomics is rapidly maturing to use small molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health and complex pathobiology, serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and non-targeted metabolic profiling, along with bioinformatics, pathway mapping and computational modeling, are now used for nutrition research on diet, metabolism, microbiome and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics and health phenotyping, to support integrated models required for personalized diet and nutrition forecasting. PMID:22540256

  13. In-silico Metabolome Target Analysis Towards PanC-based Antimycobacterial Agent Discovery.

    Science.gov (United States)

    Khoshkholgh-Sima, Baharak; Sardari, Soroush; Izadi Mobarakeh, Jalal; Khavari-Nejad, Ramezan Ali

    2015-01-01

    Mycobacterium tuberculosis, the main cause of tuberculosis (TB), has still remained a global health crisis especially in developing countries. Tuberculosis treatment is a laborious and lengthy process with high risk of noncompliance, cytotoxicity adverse events and drug resistance in patient. Recently, there has been an alarming rise of drug resistant in TB. In this regard, it is an unmet need to develop novel antitubercular medicines that target new or more effective biochemical pathways to prevent drug resistant Mycobacterium. Integrated study of metabolic pathways through in-silico approach played a key role in antimycobacterial design process in this study. Our results suggest that pantothenate synthetase (PanC), anthranilate phosphoribosyl transferase (TrpD) and 3-isopropylmalate dehydratase (LeuD) might be appropriate drug targets. In the next step, in-silico ligand analysis was used for more detailed study of chemical tractability of targets. This was helpful to identify pantothenate synthetase (PanC, Rv3602c) as the best target for antimycobacterial design procedure. Virtual library screening on the best ligand of PanC was then performed for inhibitory ligand design. At the end, five chemical intermediates showed significant inhibition of Mycobacterium bovis with good selectivity indices (SI) ≥10 according to Tuberculosis Antimicrobial Acquisition & Coordinating Facility of US criteria for antimycobacterial screening programs.

  14. Targeted genome-wide enrichment of functional regions.

    Directory of Open Access Journals (Sweden)

    Periannan Senapathy

    Full Text Available Only a small fraction of large genomes such as that of the human contains the functional regions such as the exons, promoters, and polyA sites. A platform technique for selective enrichment of functional genomic regions will enable several next-generation sequencing applications that include the discovery of causal mutations for disease and drug response. Here, we describe a powerful platform technique, termed "functional genomic fingerprinting" (FGF, for the multiplexed genomewide isolation and analysis of targeted regions such as the exome, promoterome, or exon splice enhancers. The technique employs a fixed part of a uniquely designed Fixed-Randomized primer, while the randomized part contains all the possible sequence permutations. The Fixed-Randomized primers bind with full sequence complementarity at multiple sites where the fixed sequence (such as the splice signals occurs within the genome, and multiplex amplify many regions bounded by the fixed sequences (e.g., exons. Notably, validation of this technique using cardiac myosin binding protein-C (MYBPC3 gene as an example strongly supports the application and efficacy of this method. Further, assisted by genomewide computational analyses of such sequences, the FGF technique may provide a unique platform for high-throughput sample production and analysis of targeted genomic regions by the next-generation sequencing techniques, with powerful applications in discovering disease and drug response genes.

  15. Targeted metabolomics reveals differences in the extended postprandial plasma metabolome of healthy subjects after intake of whole-grain rye porridges versus refined wheat bread.

    Science.gov (United States)

    Shi, Lin; Brunius, Carl; Lindelöf, Magnus; Shameh, Souad Abou; Wu, Huaxing; Lee, Isabella; Landberg, Rikard; Moazzami, Ali A

    2017-07-01

    We previously found that whole-grain (WG) rye porridges suppressed appetite and improved glucose metabolism. This study aimed to investigate potential plasma metabolites that may be related to differences in those appetite and glucose responses. Twenty-one health subjects consumed six isocaloric breakfasts in a randomized cross-over study. Plain WG rye porridges (40 and 55 g), rye porridge enriched with different inulin: gluten proportions (9:3 g; 6:6 g; 3:9 g), and a 55 g refined wheat bread (control) were served as part of complete breakfast, followed by a standardized lunch. NMR metabolomics assessed 36 plasma metabolites and short chain fatty acids were measured by GC-MS from baseline up to 8 h. Pre-lunch plasma essential amino acids reflected protein composition and post-lunch plasma short chain fatty acids varied with fiber content in breakfasts. No correlations were observed between measured metabolites and glucose, insulin, or appetite responses. Differences in protein and fiber contents in breakfasts altered postprandial plasma amino acids and short chain fatty acids, respectively, but were unrelated to appetite and glucose responses. Further studies are warrant to identify the underlying mechanisms for the beneficial effects on appetite and second meal glucose responses after rye-based foods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Candidate mediators of chondrocyte mechanotransduction via targeted and untargeted metabolomic measurements.

    Science.gov (United States)

    Jutila, Aaron A; Zignego, Donald L; Hwang, Bradley K; Hilmer, Jonathan K; Hamerly, Timothy; Minor, Cody A; Walk, Seth T; June, Ronald K

    2014-03-01

    Chondrocyte mechanotransduction is the process by which cartilage cells transduce mechanical loads into biochemical and biological signals. Previous studies have identified several pathways by which chondrocytes transduce mechanical loads, yet a general understanding of which signals are activated and in what order remains elusive. This study was performed to identify candidate mediators of chondrocyte mechanotransduction using SW1353 chondrocytes embedded in physiologically stiff agarose. Dynamic compression was applied to cell-seeded constructs for 0-30min, followed immediately by whole-cell metabolite extraction. Metabolites were detected via LC-MS, and compounds of interest were identified via database searches. We found several metabolites which were statistically different between the experimental groups, and we report the detection of 5 molecules which are not found in metabolite databases of known compounds indicating potential novel molecules. Targeted studies to quantify the response of central energy metabolites to compression found a transient increase in the ratio of NADP+ to NADPH and a continual decrease in the ratio of GDP to GTP, suggesting a flux of energy into the TCA cycle. These data are consistent with the remodeling of cytoskeletal components by mechanically induced signaling, and add substantial new data to a complex picture of how chondrocytes transduce mechanical loads. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Targeted Metabolomic Analysis of Polyphenols with Antioxidant Activity in Sour Guava (Psidium friedrichsthalianum Nied. Fruit

    Directory of Open Access Journals (Sweden)

    Carmen Tatiana Cuadrado-Silva

    2016-12-01

    Full Text Available Psidium is a genus of tropical bushes belonging to the Myrtaceae family distributed in Central and South America. The polar extract of Psidium friedrichsthalianum Nied. was partitioned with ethyl ether, ethyl acetate, and n-butanol, and the total phenolic content and antioxidant activity were measured by Folin-Ciocalteu and ABTS assays, respectively. The ethyl acetate fraction exhibited both the highest phenolic content and antioxidant activity. Due to the complexity of this fraction, an analytical method for the comprehensive profiling of phenolic compounds was done by UPLC-ESI/QqQ in MRM (multiple reaction monitoring mode. In this targeted analysis, 22 phenolic compounds were identified, among which several hydroxybenzoic, phenylacetic, and hydroxycinnamic acid derivatives were found. This is the first time that (+-catechin, procyanidin B1, procyanidin B2, and (−-epicatechin have been reported as constituents of sour guava. A fractionation by exclusion size, C18-column chromatography, and preparative RRLC (rapid resolution liquid chromatography allowed us to confirm the presence of ellagic acid and isomeric procyanidins B, well-known bioactive compounds. The content of phenolic compounds in this fruit shows its potential for the development of functional foods.

  18. Screening for biomarkers of liver injury induced by Polygonum multiflorum: a targeted metabolomic study

    Directory of Open Access Journals (Sweden)

    Qin eDong

    2015-10-01

    Full Text Available Heshouwu (HSW, the dry roots of Polygonum multiflorum, a classical traditional Chinese medicine is used as a tonic for a wide range of conditions,particularly those associated with aging. However, it tends to be taken overdose or long term in these years, which has resulted in liver damage reported in many countries. In this study, the indicative roles of nine bile acids (BAs were evaluated to offer potential biomarkers for HSW induced liver injury. Nine BAs including cholic acid (CA and chenodeoxycholic acid (CDCA, taurocholic acid (TCA, glycocholic acid (GCA, glycochenodeoxycholic acid (GCDCA, deoxycholic acid (DCA, glycodeoxycholic acid (GDCA, ursodeoxycholic acid (UDCA and hyodeoxycholic acid (HDCA in rat bile and serum were detected by a developed LC-MS method after 42 days treatment. Partial least square-discriminate analysis (PLS-DA was applied to evaluate the indicative roles of the nine BAs, and metabolism of the nine BAs was summarized. Significant change was observed for the concentrations of nine BAs in treatment groups compared with normal control; In the PLS-DA plots of nine BAs in bile, normal control and raw HSW groups were separately clustered and could be clearly distinguished, GDCA was selected as the distinguished components for raw HSW overdose treatment group. In the PLS-DA plots of nine BAs in serum, the normal control and raw HSW overdose treatment group were separately clustered and could be clearly distinguished, and HDCA was selected as the distinguished components for raw HSW overdose treatment group. The results indicated the perturbation of nine BAs was associated with HSW induced liver injury; GDCA in bile, as well as HDCA in serum could be selected as potential biomarkers for HSW induced liver injury; it also laid the foundation for the further search on the mechanisms of liver injury induced by HSW .

  19. Screening for biomarkers of liver injury induced by Polygonum multiflorum: a targeted metabolomic study

    Science.gov (United States)

    Dong, Qin; Li, Na; Li, Qi; Zhang, Cong-En; Feng, Wu-Wen; Li, Guang-Quan; Li, Rui-Yu; Tu, Can; Han, Xue; Bai, Zhao-Fang; Zhang, Ya-Ming; Niu, Ming; Ma, Zhi-Jie; Xiao, Xiao-He; Wang, Jia-Bo

    2015-01-01

    Heshouwu (HSW), the dry roots of Polygonum multiflorum, a classical traditional Chinese medicine is used as a tonic for a wide range of conditions, particularly those associated with aging. However, it tends to be taken overdose or long term in these years, which has resulted in liver damage reported in many countries. In this study, the indicative roles of nine bile acids (BAs) were evaluated to offer potential biomarkers for HSW induced liver injury. Nine BAs including cholic acid (CA) and chenodeoxycholic acid (CDCA), taurocholic acid (TCA), glycocholic acid (GCA), glycochenodeoxycholic acid (GCDCA), deoxycholic acid (DCA), glycodeoxycholic acid (GDCA), ursodeoxycholic acid (UDCA), and hyodeoxycholic acid (HDCA) in rat bile and serum were detected by a developed LC-MS method after 42 days treatment. Partial least square-discriminate analysis (PLS-DA) was applied to evaluate the indicative roles of the nine BAs, and metabolism of the nine BAs was summarized. Significant change was observed for the concentrations of nine BAs in treatment groups compared with normal control; In the PLS-DA plots of nine BAs in bile, normal control and raw HSW groups were separately clustered and could be clearly distinguished, GDCA was selected as the distinguished components for raw HSW overdose treatment group. In the PLS-DA plots of nine BAs in serum, the normal control and raw HSW overdose treatment group were separately clustered and could be clearly distinguished, and HDCA was selected as the distinguished components for raw HSW overdose treatment group. The results indicated the perturbation of nine BAs was associated with HSW induced liver injury; GDCA in bile, as well as HDCA in serum could be selected as potential biomarkers for HSW induced liver injury; it also laid the foundation for the further search on the mechanisms of liver injury induced by HSW. PMID:26483689

  20. Investigation of ground target detection methods in fully polarimetric wide angle synthetic aperture radar images

    Science.gov (United States)

    Laggan, Wayne B.

    1995-03-01

    Target detection is a high priority of the Air Force for the purpose of reconnaissance and bombardment. This research investigates and develops methods to distinguish ground targets from clutter (i.e. foliage, landscape etc.) in Wide Angle Synthetic Aperture Radar (WASAR) images. WASAR uses multiple aspect angle SAR images of the same target scene. The WASAR data was generated from a pre-release software package (XPATCH-ES) provided by the sponsor (WL-AARA). A statistical analysis and feature extraction is performed on the XPATCH-ES data. Polarimetric and wide angle covariance matrices are estimated and analyzed. From an analysis of the wide angle covariance matrix it is shown that natural clutter has in general a uniform radar return for changing aspect angles, whereas the radar return for a target varies. Based on this analysis, two new wide angle algorithms, the WASAR Whitening Filter and the Adaptive WASAR Whitening Filter (AWWF) are developed. The target detection performance of polarimetric and multi aspect angle image combining algorithms are quantified using Receiver Operating Characteristic curves and target to clutter ratios. It is shown that wide angle processing provides superior target detection performance over polarimetric processing. Combinations of wide angle and polarimetric algorithms were used to achieve a 13.7 dB processing gain in target to clutter ratio when compared to unprocessed images of the target scene. This represents a significant improvement in target detection capabilities.

  1. Associations of anthropometric markers with serum metabolites using a targeted metabolomics approach: results of the EPIC-potsdam study.

    Science.gov (United States)

    Bachlechner, U; Floegel, A; Steffen, A; Prehn, C; Adamski, J; Pischon, T; Boeing, H

    2016-06-27

    The metabolic consequences of type of body shape need further exploration. Whereas accumulation of body mass in the abdominal area is a well-established metabolic risk factor, accumulation in the gluteofemoral area is controversially debated. We evaluated the associations of anthropometric markers of overall body mass and body shape with 127 serum metabolites within a sub-sample of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. The cross-sectional analysis was conducted in 2270 participants, randomly drawn from the EPIC-Potsdam cohort. Metabolites were measured by targeted metabolomics. To select metabolites related with both waist circumference (WC) (abdominal subcutaneous and visceral fat) and hip circumference (HC) (gluteofemoral fat, muscles and bone structure) correlations (r) with body mass index (BMI) as aggregating marker of body mass (lean and fat mass) were calculated. Relations with body shape were assessed by median metabolite concentrations across tertiles of WC and HC, mutually adjusted to each other. Correlations revealed 23 metabolites related to BMI (r⩾I0.20 I). Metabolites showing relations with BMI were showing similar relations with HC adjusted WC (WCHC). In contrast, relations with WC adjusted HC (HCWC) were less concordant with relations of BMI and WCHC. In both sexes, metabolites with concordant relations regarding WCHC and HCWC included tyrosine, diacyl-phosphatidylcholine C38:3, C38:4, lyso-phosphatidylcholine C18:1, C18:2 and sphingomyelin C18:1; metabolites with opposite relations included isoleucine, diacyl-phosphatidylcholine C42:0, acyl-alkyl-phosphatidylcholine C34:3, C42:4, C42:5, C44:4 and C44:6. Metabolites specifically related to HCWC included acyl-alkyl-phosphatidylcholine C34:2, C36:2, C38:2 and C40:4, and were solely observed in men. Other metabolites were related to WCHC only. The study revealed specific metabolic profiles for HCWC as marker of gluteofemoral body mass differing from

  2. The ABRF Metabolomics Research Group 2013 Study: Investigation of Spiked Compound Differences in a Human Plasma Matrix

    OpenAIRE

    Cheema, Amrita K.; Asara, John M.; Wang, Yiwen; Neubert, Thomas A.; Tolstikov, Vladimir; Turck, Chris W.

    2015-01-01

    Metabolomics is an emerging field that involves qualitative and quantitative measurements of small molecule metabolites in a biological system. These measurements can be useful for developing biomarkers for diagnosis, prognosis, or predicting response to therapy. Currently, a wide variety of metabolomics approaches, including nontargeted and targeted profiling, are used across laboratories on a routine basis. A diverse set of analytical platforms, such as NMR, gas chromatography-mass spectrom...

  3. Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women.

    Science.gov (United States)

    Luan, Hemi; Meng, Nan; Liu, Ping; Fu, Jin; Chen, Xiaomin; Rao, Weiqiao; Jiang, Hui; Xu, Xun; Cai, Zongwei; Wang, Jun

    2015-01-01

    Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy. In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy. As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

  4. Nutritional Metabolomics

    DEFF Research Database (Denmark)

    Gürdeniz, Gözde

    . Application of multiple analytical strategies may provide comprehensive information to reach a valid answer to these research questions. In this thesis, I investigated several analytical technologies and data handling strategies in order to evaluate their effects on the biological answer. In metabolomics, one......Metabolomics provides a holistic approach to investigate the perturbations in human metabolism with respect to a specific exposure. In nutritional metabolomics, the research question is generally related to the effect of a specific food intake on metabolic profiles commonly of plasma or urine...... purposes and partial least squares discriminant analysis (PLSDA) for classification and variable selection purposes; both have been used in PAPER I and II. In PAPER III, the application potential of sparse principal component analysis (SPCA) on LC-MS based metabolomics data as a pattern recognition...

  5. Metabolomics of Genetically Modified Crops

    Directory of Open Access Journals (Sweden)

    Carolina Simó

    2014-10-01

    Full Text Available Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  6. Metabolomics of genetically modified crops.

    Science.gov (United States)

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-10-20

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  7. Metabolomics of Genetically Modified Crops

    Science.gov (United States)

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-01-01

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064

  8. Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics

    OpenAIRE

    Altmaier, Elisabeth; Kastenmüller, Gabi; Römisch-Margl, Werner; Thorand, Barbara; Weinberger, Klaus M; Illig, Thomas; Adamski, Jerzy; Döring, Angela; Suhre, Karsten

    2010-01-01

    Abstract Nutrition plays an important role in human metabolism and health. However, it is unclear in how far self-reported nutrition intake reflects de facto differences in body metabolite composition. To investigate this question on an epidemiological scale we conducted a metabolomics study analyzing the association of self-reported nutrition habits with 363 metabolites quantified in blood serum of 284 male participants of the KORA population study, aged between 55 and 79 years. U...

  9. LC-MS-BASED METABOLOMICS OF XENOBIOTIC-INDUCED TOXICITIES

    Directory of Open Access Journals (Sweden)

    Chi Chen

    2013-01-01

    Full Text Available Xenobiotic exposure, especially high-dose or repeated exposure of xenobiotics, can elicit detrimental effects on biological systems through diverse mechanisms. Changes in metabolic systems, including formation of reactive metabolites and disruption of endogenous metabolism, are not only the common consequences of toxic xenobiotic exposure, but in many cases are the major causes behind development of xenobiotic-induced toxicities (XIT. Therefore, examining the metabolic events associated with XIT generates mechanistic insights into the initiation and progression of XIT, and provides guidance for prevention and treatment. Traditional bioanalytical platforms that target only a few suspected metabolites are capable of validating the expected outcomes of xenobiotic exposure. However, these approaches lack the capacity to define global changes and to identify unexpected events in the metabolic system. Recent developments in high-throughput metabolomics have dramatically expanded the scope and potential of metabolite analysis. Among all analytical techniques adopted for metabolomics, liquid chromatography-mass spectrometry (LC-MS has been most widely used for metabolomic investigations of XIT due to its versatility and sensitivity in metabolite analysis. In this review, technical platform of LC-MS-based metabolomics, including experimental model, sample preparation, instrumentation, and data analysis, are discussed. Applications of LC-MS-based metabolomics in exploratory and hypothesis-driven investigations of XIT are illustrated by case studies of xenobiotic metabolism and endogenous metabolism associated with xenobiotic exposure.

  10. Non-targeted metabolomics analysis of cardiac Muscle Ring Finger-1 (MuRF1), MuRF2, and MuRF3 in vivo reveals novel and redundant metabolic changes.

    Science.gov (United States)

    Banerjee, Ranjan; He, Jun; Spaniel, Carolyn; Quintana, Megan T; Wang, Zhongjing; Bain, James; Newgard, Christopher B; Muehlbauer, Michael J; Willis, Monte S

    2015-04-01

    The muscle-specific ubiquitin ligases MuRF1, MuRF2, MuRF3 have been reported to have overlapping substrate specificities, interacting with each other as well as proteins involved in metabolism and cardiac function. In the heart, all three MuRF family proteins have proven critical to cardiac responses to ischemia and heart failure. The non-targeted metabolomics analysis of MuRF1-/-, MuRF2-/-, and MuRF3-/- hearts was initiated to investigate the hypothesis that MuRF1, MuRF2, and MuRF3 have a similarly altered metabolome, representing alterations in overlapping metabolic processes. Ventricular tissue was flash frozen and quantitatively analyzed by GC/MS using a library built upon the Fiehn GC/MS Metabolomics RTL Library. Non-targeted metabolomic analysis identified significant differences (via VIP statistical analysis) in taurine, myoinositol, and stearic acid for the three MuRF-/- phenotypes relative to their matched controls. Moreover, pathway enrichment analysis demonstrated that MuRF1-/- had significant changes in metabolite(s) involved in taurine metabolism and primary acid biosynthesis while MuRF2-/- had changes associated with ascorbic acid/aldarate metabolism (via VIP and t-test analysis vs. sibling-matched wildtype controls). By identifying the functional metabolic consequences of MuRF1, MuRF2, and MuRF3 in the intact heart, non-targeted metabolomics analysis discovered common pathways functionally affected by cardiac MuRF family proteins in vivo. These novel metabolomics findings will aid in guiding the molecular studies delineating the mechanisms that MuRF family proteins regulate metabolic pathways. Understanding these mechanism is an important key to understanding MuRF family proteins' protective effects on the heart during cardiac disease.

  11. The need and necessity of an EU-wide renewable energy target for 2030. Discussion paper

    Energy Technology Data Exchange (ETDEWEB)

    De Vos, R.; Winkel, T.; Klessmann, C. [Ecofys Netherlands, Utrecht (Netherlands)

    2013-04-15

    In 2020, some leading EU energy and climate policies will expire. At present, the EU and its Member States are discussing the design of a post-2020 policy portfolio. In a discussion paper commissioned by the European Copper Institute, Ecofys shows that an EU-wide renewable energy target is a necessary part of a 2030 portfolio. The paper analyses, in detail, two realistic policy portfolio options for renewable energy, target-setting in particular: one 'decarbonisation-only' EU target with voluntary national targets for renewable energy, and one that includes an EU-wide renewable energy target, broken down into binding national targets. The analysis shows that the latter option, when supported by appropriate and improved EU and Member States' policies and measures, is most suitable in facilitating a European low-carbon economy.

  12. Metabolomics of medicinal plants: the importance of multivariate analysis of analytical chemistry data.

    Science.gov (United States)

    Okada, Taketo; Afendi, Farit Mochamad; Altaf-Ul-Amin, Md; Takahashi, Hiroki; Nakamura, Kensuke; Kanaya, Shigehiko

    2010-09-01

    Metabolomics, the comprehensive and global analysis of diverse metabolites produced in cells and organisms, has greatly expanded metabolite fingerprinting and profiling as well as the selection and identification of marker metabolites. The methodology typically employs multivariate analysis to statistically process the massive amount of analytical chemistry data resulting from high-throughput and simultaneous metabolite analysis. Although the technology of plant metabolomics has mainly developed with other post-genomics in systems biology and functional genomics, it is independently applied to the evaluation of the qualities of medicinal plants, based on the diversity of metabolite fingerprints resulting from multivariate analysis of non-targeted or widely targeted metabolite analysis. One advantage of applying metabolomics is that medicinal plants are evaluated based not only on the limited number of metabolites that are pharmacologically important chemicals, but also on the fingerprints of minor metabolites and bioactive chemicals. In particular, score plot and loading plot analyses e.g. principal component analysis (PCA), partial-least-squares discriminant analysis (PLS-DA), and discrimination map analysis such as batch-learning self-organizing map (BL-SOM) analysis, are often employed for the reduction of a metabolite fingerprint and the classification of analyzed samples. Based on recent studies, we now understand that metabolomics can be an effective approach for comprehensive evaluation of the qualities of medicinal plants. In this review, we describe practical cases in which metabolomic study was performed on medicinal plants, and discuss the utility of metabolomics for this research field, with focus on multivariate analysis.

  13. Error Analysis of Fast Moving Target Geo-location in Wide Area Surveillance Ground Moving Target Indication Mode

    Directory of Open Access Journals (Sweden)

    Zheng Shi-chao

    2013-12-01

    Full Text Available As an important mode in airborne radar systems, Wide Area Surveillance Ground Moving Target Indication (WAS-GMTI mode has the ability of monitoring a large area in a short time, and then the detected moving targets can be located quickly. However, in real environment, many factors introduce considerable errors into the location of moving targets. In this paper, a fast location method based on the characteristics of the moving targets in WAS-GMTI mode is utilized. And in order to improve the location performance, those factors that introduce location errors are analyzed and moving targets are relocated. Finally, the analysis of those factors is proved to be reasonable by simulation and real data experiments.

  14. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

    OpenAIRE

    Carroll Adam J; Badger Murray R; Harvey Millar A

    2010-01-01

    Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or t...

  15. Metabolomics in Toxicology and Preclinical Research

    Science.gov (United States)

    Ramirez, Tzutzuy; Daneshian, Mardas; Kamp, Hennicke; Bois, Frederic Y.; Clench, Malcolm R.; Coen, Muireann; Donley, Beth; Fischer, Steven M.; Ekman, Drew R.; Fabian, Eric; Guillou, Claude; Heuer, Joachim; Hogberg, Helena T.; Jungnickel, Harald; Keun, Hector C.; Krennrich, Gerhard; Krupp, Eckart; Luch, Andreas; Noor, Fozia; Peter, Erik; Riefke, Bjoern; Seymour, Mark; Skinner, Nigel; Smirnova, Lena; Verheij, Elwin; Wagner, Silvia; Hartung, Thomas; van Ravenzwaay, Bennard; Leist, Marcel

    2013-01-01

    Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context. PMID:23665807

  16. Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast.

    Directory of Open Access Journals (Sweden)

    Elke Ericson

    2008-08-01

    Full Text Available To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac interfered with establishment of cell polarity, cyproheptadine (Periactin targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol and pimozide (Orap. Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.

  17. Hardware-in-the-loop simulation technology of wide-band radar targets based on scattering center model

    Directory of Open Access Journals (Sweden)

    Huang Hao

    2015-10-01

    Full Text Available Hardware-in-the-loop (HWIL simulation technology can verify and evaluate the radar by simulating the radio frequency environment in an anechoic chamber. The HWIL simulation technology of wide-band radar targets can accurately generate wide-band radar target echo which stands for the radar target scattering characteristics and pulse modulation of radar transmitting signal. This paper analyzes the wide-band radar target scattering properties first. Since the responses of target are composed of many separate scattering centers, the target scattering characteristic is restructured by scattering centers model. Based on the scattering centers model of wide-band radar target, the wide-band radar target echo modeling and the simulation method are discussed. The wide-band radar target echo is reconstructed in real-time by convoluting the transmitting signal to the target scattering parameters. Using the digital radio frequency memory (DRFM system, the HWIL simulation of wide-band radar target echo with high accuracy can be actualized. A typical wide-band radar target simulation is taken to demonstrate the preferable simulation effect of the reconstruction method of wide-band radar target echo. Finally, the radar target time-domain echo and high-resolution range profile (HRRP are given. The results show that the HWIL simulation gives a high-resolution range distribution of wide-band radar target scattering centers.

  18. New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects.

    Directory of Open Access Journals (Sweden)

    Joseph A Rothwell

    Full Text Available Coffee contains various bioactives implicated with human health and disease risk. To accurately assess the effects of overall consumption upon health and disease, individual intake must be measured in large epidemiological studies. Metabolomics has emerged as a powerful approach to discover biomarkers of intake for a large range of foods. Here we report the profiling of the urinary metabolome of cohort study subjects to search for new biomarkers of coffee intake. Using repeated 24-hour dietary records and a food frequency questionnaire, 20 high coffee consumers (183-540 mL/d and 19 low consumers were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subject were profiled by high-resolution mass spectrometry. Partial least-square discriminant analysis of multidimensional liquid chromatography-mass spectrometry data clearly distinguished high consumers from low via 132 significant (p-value<0.05 discriminating features. Ion clusters whose intensities were most elevated in the high consumers were annotated using online and in-house databases and their identities checked using commercial standards and MS-MS fragmentation. The best discriminants, and thus potential markers of coffee consumption, were the glucuronide of the diterpenoid atractyligenin, the diketopiperazine cyclo(isoleucyl-prolyl, and the alkaloid trigonelline. Some caffeine metabolites, such as 1-methylxanthine, were also among the discriminants, however caffeine may be consumed from other sources and its metabolism is subject to inter-individual variation. Receiver operating characteristics curve analysis showed that the biomarkers identified could be used effectively in combination for increased sensitivity and specificity. Once validated in other cohorts or intervention studies, these specific single or combined biomarkers will become a valuable alternative to assessment of coffee intake by dietary survey and finally lead to a better understanding of

  19. Non-Targeted Metabolomics Analysis of the Effects of Tyrosine Kinase Inhibitors Sunitinib and Erlotinib on Heart, Muscle, Liver and Serum Metabolism In Vivo

    Directory of Open Access Journals (Sweden)

    Brian C. Jensen

    2017-06-01

    Full Text Available Background: More than 90 tyrosine kinases have been implicated in the pathogenesis of malignant transformation and tumor angiogenesis. Tyrosine kinase inhibitors (TKIs have emerged as effective therapies in treating cancer by exploiting this kinase dependency. The TKI erlotinib targets the epidermal growth factor receptor (EGFR, whereas sunitinib targets primarily vascular endothelial growth factor receptor (VEGFR and platelet-derived growth factor receptor (PDGFR.TKIs that impact the function of non-malignant cells and have on- and off-target toxicities, including cardiotoxicities. Cardiotoxicity is very rare in patients treated with erlotinib, but considerably more common after sunitinib treatment. We hypothesized that the deleterious effects of TKIs on the heart were related to their impact on cardiac metabolism. Methods: Female FVB/N mice (10/group were treated with therapeutic doses of sunitinib (40 mg/kg, erlotinib (50 mg/kg, or vehicle daily for two weeks. Echocardiographic assessment of the heart in vivo was performed at baseline and on Day 14. Heart, skeletal muscle, liver and serum were flash frozen and prepped for non-targeted GC-MS metabolomics analysis. Results: Compared to vehicle-treated controls, sunitinib-treated mice had significant decreases in systolic function, whereas erlotinib-treated mice did not. Non-targeted metabolomics analysis of heart identified significant decreases in docosahexaenoic acid (DHA, arachidonic acid (AA/ eicosapentaenoic acid (EPA, O-phosphocolamine, and 6-hydroxynicotinic acid after sunitinib treatment. DHA was significantly decreased in skeletal muscle (quadriceps femoris, while elevated cholesterol was identified in liver and elevated ethanolamine identified in serum. In contrast, erlotinib affected only one metabolite (spermidine significantly increased. Conclusions: Mice treated with sunitinib exhibited systolic dysfunction within two weeks, with significantly lower heart and skeletal muscle

  20. Non-Targeted Metabolomics Analysis of the Effects of Tyrosine Kinase Inhibitors Sunitinib and Erlotinib on Heart, Muscle, Liver and Serum Metabolism In Vivo.

    Science.gov (United States)

    Jensen, Brian C; Parry, Traci L; Huang, Wei; Ilaiwy, Amro; Bain, James R; Muehlbauer, Michael J; O'Neal, Sara K; Patterson, Cam; Johnson, Gary L; Willis, Monte S

    2017-06-22

    Background: More than 90 tyrosine kinases have been implicated in the pathogenesis of malignant transformation and tumor angiogenesis. Tyrosine kinase inhibitors (TKIs) have emerged as effective therapies in treating cancer by exploiting this kinase dependency. The TKI erlotinib targets the epidermal growth factor receptor (EGFR), whereas sunitinib targets primarily vascular endothelial growth factor receptor (VEGFR) and platelet-derived growth factor receptor (PDGFR).TKIs that impact the function of non-malignant cells and have on- and off-target toxicities, including cardiotoxicities. Cardiotoxicity is very rare in patients treated with erlotinib, but considerably more common after sunitinib treatment. We hypothesized that the deleterious effects of TKIs on the heart were related to their impact on cardiac metabolism. Methods: Female FVB/N mice (10/group) were treated with therapeutic doses of sunitinib (40 mg/kg), erlotinib (50 mg/kg), or vehicle daily for two weeks. Echocardiographic assessment of the heart in vivo was performed at baseline and on Day 14. Heart, skeletal muscle, liver and serum were flash frozen and prepped for non-targeted GC-MS metabolomics analysis. Results: Compared to vehicle-treated controls, sunitinib-treated mice had significant decreases in systolic function, whereas erlotinib-treated mice did not. Non-targeted metabolomics analysis of heart identified significant decreases in docosahexaenoic acid (DHA), arachidonic acid (AA)/ eicosapentaenoic acid (EPA), O-phosphocolamine, and 6-hydroxynicotinic acid after sunitinib treatment. DHA was significantly decreased in skeletal muscle (quadriceps femoris), while elevated cholesterol was identified in liver and elevated ethanolamine identified in serum. In contrast, erlotinib affected only one metabolite (spermidine significantly increased). Conclusions: Mice treated with sunitinib exhibited systolic dysfunction within two weeks, with significantly lower heart and skeletal muscle levels of

  1. Statistical methods for handling unwanted variation in metabolomics data.

    Science.gov (United States)

    De Livera, Alysha M; Sysi-Aho, Marko; Jacob, Laurent; Gagnon-Bartsch, Johann A; Castillo, Sandra; Simpson, Julie A; Speed, Terence P

    2015-04-07

    Metabolomics experiments are inevitably subject to a component of unwanted variation, due to factors such as batch effects, long runs of samples, and confounding biological variation. Although the removal of this unwanted variation is a vital step in the analysis of metabolomics data, it is considered a gray area in which there is a recognized need to develop a better understanding of the procedures and statistical methods required to achieve statistically relevant optimal biological outcomes. In this paper, we discuss the causes of unwanted variation in metabolomics experiments, review commonly used metabolomics approaches for handling this unwanted variation, and present a statistical approach for the removal of unwanted variation to obtain normalized metabolomics data. The advantages and performance of the approach relative to several widely used metabolomics normalization approaches are illustrated through two metabolomics studies, and recommendations are provided for choosing and assessing the most suitable normalization method for a given metabolomics experiment. Software for the approach is made freely available.

  2. Genome-wide mapping of Polycomb target genes unravels their roles in cell fate transitions

    DEFF Research Database (Denmark)

    Bracken, Adrian P; Dietrich, Nikolaj; Pasini, Diego

    2006-01-01

    The Polycomb group (PcG) proteins form chromatin-modifying complexes that are essential for embryonic development and stem cell renewal and are commonly deregulated in cancer. Here, we identify their target genes using genome-wide location analysis in human embryonic fibroblasts. We find that Pol...

  3. Genome-wide identification of structural variants in genes encoding drug targets

    DEFF Research Database (Denmark)

    Rasmussen, Henrik Berg; Dahmcke, Christina Mackeprang

    2012-01-01

    The objective of the present study was to identify structural variants of drug target-encoding genes on a genome-wide scale. We also aimed at identifying drugs that are potentially amenable for individualization of treatments based on knowledge about structural variation in the genes encoding...

  4. Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

    Science.gov (United States)

    Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

    2014-10-27

    In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

  5. The human urine metabolome.

    Directory of Open Access Journals (Sweden)

    Souhaila Bouatra

    Full Text Available Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS, direct flow injection mass spectrometry (DFI/LC-MS/MS, inductively coupled plasma mass spectrometry (ICP-MS and high performance liquid chromatography (HPLC experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify a total of: 209 (209 by NMR, 179 (85 by GC-MS, 127 (127 by DFI/LC-MS/MS, 40 (40 by ICP-MS and 10 (10 by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database

  6. Genome-Wide Analysis of miRNA targets in Brachypodium and Biomass Energy Crops

    Energy Technology Data Exchange (ETDEWEB)

    Green, Pamela J. [Univ. of Delaware, Newark, DE (United States)

    2015-08-11

    MicroRNAs (miRNAs) contribute to the control of numerous biological processes through the regulation of specific target mRNAs. Although the identities of these targets are essential to elucidate miRNA function, the targets are much more difficult to identify than the small RNAs themselves. Before this work, we pioneered the genome-wide identification of the targets of Arabidopsis miRNAs using an approach called PARE (German et al., Nature Biotech. 2008; Nature Protocols, 2009). Under this project, we applied PARE to Brachypodium distachyon (Brachypodium), a model plant in the Poaceae family, which includes the major food grain and bioenergy crops. Through in-depth global analysis and examination of specific examples, this research greatly expanded our knowledge of miRNAs and target RNAs of Brachypodium. New regulation in response to environmental stress or tissue type was found, and many new miRNAs were discovered. More than 260 targets of new and known miRNAs with PARE sequences at the precise sites of miRNA-guided cleavage were identified and characterized. Combining PARE data with the small RNA data also identified the miRNAs responsible for initiating approximately 500 phased loci, including one of the novel miRNAs. PARE analysis also revealed that differentially expressed miRNAs in the same family guide specific target RNA cleavage in a correspondingly tissue-preferential manner. The project included generation of small RNA and PARE resources for bioenergy crops, to facilitate ongoing discovery of conserved miRNA-target RNA regulation. By associating specific miRNA-target RNA pairs with known physiological functions, the research provides insights about gene regulation in different tissues and in response to environmental stress. This, and release of new PARE and small RNA data sets should contribute basic knowledge to enhance breeding and may suggest new strategies for improvement of biomass energy crops.

  7. Revisiting rose: comparing the benefits and costs of population-wide and targeted interventions.

    Science.gov (United States)

    Ahern, Jennifer; Jones, Matthew R; Bakshis, Erin; Galea, Sandro

    2008-12-01

    Geoffrey Rose's two principal approaches to public health intervention are (1) targeted strategies focusing on individuals at a personal increased risk of disease and (2) population-wide approaches focusing on the whole population. Beyond his discussion of the strengths and weaknesses of these approaches, there is no empiric work examining the conditions under which one of these approaches may be better than the other. This article uses mathematical simulations to model the benefits and costs of the two approaches, varying the cut points for treatment, effect magnitudes, and costs of the interventions. These techniques then were applied to the specific example of an intervention on blood pressure to reduce cardiovascular disease. In the general simulation (using an inverse logit risk curve), lower costs of intervention, treating people with risk factor values at or above where the slope on the risk curve is at its steepest (for targeted interventions), and interventions with larger effects on reducing the risk factor (for population-wide interventions) provided benefit/cost advantages. In the specific blood pressure intervention example, lower-cost population-wide interventions had better benefit/cost ratios, but some targeted treatments with lower cutoffs prevented more absolute cases of disease. These simulations empirically evaluate some of Rose's original arguments. They can be replicated for particular interventions being considered and may be useful in helping public health decision makers assess potential intervention strategies.

  8. Urine Metabolomics in Hypertension Research.

    Science.gov (United States)

    Tsiropoulou, Sofia; McBride, Martin; Padmanabhan, Sandosh

    2017-01-01

    Functional genomics requires an understanding of the complete network of changes within an organism by extensive measurements of moieties from mRNA, proteins, and metabolites. Metabolomics utilizes analytic chemistry tools to profile the complete spectrum of metabolites found in a tissue, cells, or biofluids using a wide range of tools from infrared spectroscopy, fluorescence spectroscopy, NMR spectroscopy, and mass spectrometry. In this protocol, we outline a procedure for performing metabolomic analysis of urine samples using liquid chromatography-mass spectrometry (LC-MS). We outline the advantages of using this approach and summarize some of the early promising studies in cardiovascular diseases using this approach.

  9. NMR-based metabolomics applications

    DEFF Research Database (Denmark)

    Iaccarino, Nunzia

    ’s phenotype. This approach finds an increasing number of applications in many areas including medical, pharmaceutical, food and environmental sciences. The combined use of NMR spectroscopy and chemometrics techniques, is able to provide the metabolic “fingerprint” of the various samples. This PhD project...... focused on the analysis of various samples covering a wide range of fields, namely, food and nutraceutical sciences, cell metabolomics and medicine using a metabolomics approach. Indeed, the first part of the thesis describes two exploratory studies performed on Algerian extra virgin olive oil and apple...... juice from ancient Danish apple cultivars. Both studies revealed variety-related peculiarities that would have been difficult to detect by means of traditional analysis. The second part of the project includes four metabolomics studies performed on samples of biological origin. In particular, the first...

  10. Non-targeted metabolomic profile of Fagus sylvatica L. leaves using liquid chromatography with mass spectrometry and gas chromatography with mass spectrometry.

    Science.gov (United States)

    Cadahía, Estrella; Fernández de Simón, Brígida; Aranda, Ismael; Sanz, Miriam; Sánchez-Gómez, David; Pinto, Ernani

    2015-01-01

    Fagus sylvatica L. is one of the most widely distributed broad-leaved tree species in central and western Europe, important to the forest sector and an accurate biomarker of climate change. To profile the beech leaf metabolome for future studies in order to investigate deeper into the characterisation of its metabolic response. Leaf extracts were analysed using LC-MS by electrospray ionisation in negative mode from m/z 100-1700 and GC-MS by electron ionisation in scan mode from m/z 35-800. The LC-MS profile resulted in 56 compounds, of which 43 were identified and/or structurally characterised, including hydroxycinnamic acid derivatives, flavan-3-ols and proanthocyanidins, and flavonols. From a second analysis based on GC-MS, a total of 111 compounds were identified, including carbohydrates, polyalcohols, amino acids, organic acids, fatty acids, phenolic compounds, terpenoids, sterols and other related compounds. Many of the compounds identified were primary metabolites involved in major plant metabolic pathways, however, some secondary metabolites were also detected. Some of them play roles as tolerance-response osmoregulators and osmoprotectors in abiotic stress, or as anti-oxidants that reduce the effect of reactive oxygen species and promote many protective functions in plants. This study provides a broad and relevant insight into the metabolic status of F. sylvatica leaves, and serves as a base for future studies on physiological and molecular mechanisms involved in biotic or abiotic stress. Copyright © 2014 John Wiley & Sons, Ltd.

  11. Targeted metabolomic analysis reveals the association between the postprandial change in palmitic acid, branched-chain amino acids and insulin resistance in young obese subjects.

    Science.gov (United States)

    Liu, Liyan; Feng, Rennan; Guo, Fuchuan; Li, Ying; Jiao, Jundong; Sun, Changhao

    2015-04-01

    Obesity is the result of a positive energy balance and often leads to difficulties in maintaining normal postprandial metabolism. The changes in postprandial metabolites after an oral glucose tolerance test (OGTT) in young obese Chinese men are unclear. In this work, the aim is to investigate the complex metabolic alterations in obesity provoked by an OGTT using targeted metabolomics. We used gas chromatography-mass spectrometry and ultra high performance liquid chromatography-triple quadrupole mass spectrometry to analyze serum fatty acids, amino acids and biogenic amines profiles from 15 control and 15 obese subjects at 0, 30, 60, 90 and 120 min during an OGTT. Metabolite profiles from 30 obese subjects as independent samples were detected in order to validate the change of metabolites. There were the decreased levels of fatty acid, amino acids and biogenic amines after OGTT in obesity. At 120 min, percent change of 20 metabolites in obesity has statistical significance when comparing with the controls. The obese parameters was positively associated with changes in arginine and histidine (Pchange in palmitic acid (PA), branched-chain amino acids (BCAAs) and phenylalanine between 1 and 120 min were positively associated with fasting insulin and HOMA-IR (all Presistance in obesity. Our findings offer new insights in the complex physiological regulation of the metabolism during an OGTT in obesity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. Evaluation of approaches to identify the targets of cellular immunity on a proteome-wide scale.

    Directory of Open Access Journals (Sweden)

    Fernanda C Cardoso

    Full Text Available BACKGROUND: Vaccine development against malaria and other complex diseases remains a challenge for the scientific community. The recent elucidation of the genome, proteome and transcriptome of many of these complex pathogens provides the basis for rational vaccine design by identifying, on a proteome-wide scale, novel target antigens that are recognized by T cells and antibodies from exposed individuals. However, there is currently no algorithm to effectively identify important target antigens from genome sequence data; this is especially challenging for T cell targets. Furthermore, for some of these pathogens, such as Plasmodium, protein expression using conventional platforms has been problematic but cell-free in vitro transcription translation (IVTT strategies have recently proved successful. Herein, we report a novel approach for proteome-wide scale identification of the antigenic targets of T cell responses using IVTT products. PRINCIPAL FINDINGS: We conducted a series of in vitro and in vivo experiments using IVTT proteins either unpurified, absorbed to carboxylated polybeads, or affinity purified through nickel resin or magnetic beads. In vitro studies in humans using CMV, EBV, and Influenza A virus proteins showed antigen-specific cytokine production in ELIspot and Cytometric Bead Array assays with cells stimulated with purified or unpurified IVTT antigens. In vitro and in vivo studies in mice immunized with the Plasmodium yoelii circumsporozoite DNA vaccine with or without IVTT protein boost showed antigen-specific cytokine production using purified IVTT antigens only. Overall, the nickel resin method of IVTT antigen purification proved optimal in both human and murine systems. CONCLUSIONS: This work provides proof of concept for the potential of high-throughput approaches to identify T cell targets of complex parasitic, viral or bacterial pathogens from genomic sequence data, for rational vaccine development against emerging and re

  13. CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing.

    Directory of Open Access Journals (Sweden)

    Eric Talevich

    2016-04-01

    Full Text Available Germline copy number variants (CNVs and somatic copy number alterations (SCNAs are of significant importance in syndromic conditions and cancer. Massively parallel sequencing is increasingly used to infer copy number information from variations in the read depth in sequencing data. However, this approach has limitations in the case of targeted re-sequencing, which leaves gaps in coverage between the regions chosen for enrichment and introduces biases related to the efficiency of target capture and library preparation. We present a method for copy number detection, implemented in the software package CNVkit, that uses both the targeted reads and the nonspecifically captured off-target reads to infer copy number evenly across the genome. This combination achieves both exon-level resolution in targeted regions and sufficient resolution in the larger intronic and intergenic regions to identify copy number changes. In particular, we successfully inferred copy number at equivalent to 100-kilobase resolution genome-wide from a platform targeting as few as 293 genes. After normalizing read counts to a pooled reference, we evaluated and corrected for three sources of bias that explain most of the extraneous variability in the sequencing read depth: GC content, target footprint size and spacing, and repetitive sequences. We compared the performance of CNVkit to copy number changes identified by array comparative genomic hybridization. We packaged the components of CNVkit so that it is straightforward to use and provides visualizations, detailed reporting of significant features, and export options for integration into existing analysis pipelines. CNVkit is freely available from https://github.com/etal/cnvkit.

  14. K-targeted metabolomic analysis extends chemical subtraction to DESIGNER extracts: selective depletion of extracts of hops (Humulus lupulus).

    Science.gov (United States)

    Ramos Alvarenga, René F; Friesen, J Brent; Nikolić, Dejan; Simmler, Charlotte; Napolitano, José G; van Breemen, Richard; Lankin, David C; McAlpine, James B; Pauli, Guido F; Chen, Shao-Nong

    2014-12-26

    This study introduces a flexible and compound targeted approach to Deplete and Enrich Select Ingredients to Generate Normalized Extract Resources, generating DESIGNER extracts, by means of chemical subtraction or augmentation of metabolites. Targeting metabolites based on their liquid-liquid partition coefficients (K values), K targeting uses countercurrent separation methodology to remove single or multiple compounds from a chemically complex mixture, according to the following equation: DESIGNER extract = total extract ± target compound(s). Expanding the scope of the recently reported depletion of extracts by immunoaffinity or solid phase liquid chromatography, the present approach allows a more flexible, single- or multi-targeted removal of constituents from complex extracts such as botanicals. Chemical subtraction enables both chemical and biological characterization, including detection of synergism/antagonism by both the subtracted targets and the remaining metabolite mixture, as well as definition of the residual complexity of all fractions. The feasibility of the DESIGNER concept is shown by K-targeted subtraction of four bioactive prenylated phenols, isoxanthohumol (1), 8-prenylnaringenin (2), 6-prenylnaringenin (3), and xanthohumol (4), from a standardized hops (Humulus lupulus L.) extract using specific solvent systems. Conversely, adding K-targeted isolates allows enrichment of the original extract and hence provides an augmented DESIGNER material. Multiple countercurrent separation steps were used to purify each of the four compounds, and four DESIGNER extracts with varying depletions were prepared. The DESIGNER approach innovates the characterization of chemically complex extracts through integration of enabling technologies such as countercurrent separation, K-by-bioactivity, the residual complexity concepts, as well as quantitative analysis by (1)H NMR, LC-MS, and HiFSA-based NMR fingerprinting.

  15. Endogenous and xenobiotic metabolic stability of primary human hepatocytes in long-term 3D spheroid cultures revealed by a combination of targeted and untargeted metabolomics.

    Science.gov (United States)

    Vorrink, Sabine U; Ullah, Shahid; Schmidt, Staffan; Nandania, Jatin; Velagapudi, Vidya; Beck, Olof; Ingelman-Sundberg, Magnus; Lauschke, Volker M

    2017-06-01

    Adverse reactions or lack of response to medications are important concerns for drug development programs. However, faithful predictions of drug metabolism and toxicity are difficult because animal models show only limited translatability to humans. Furthermore, current in vitro systems, such as hepatic cell lines or primary human hepatocyte (PHH) 2-dimensional (2D) monolayer cultures, can be used only for acute toxicity tests because of their immature phenotypes and inherent instability. Therefore, the migration to novel phenotypically stable models is of prime importance for the pharmaceutical industry. Novel 3-dimensional (3D) culture systems have been shown to accurately mimic in vivo hepatic phenotypes on transcriptomic and proteomic level, but information about their metabolic stability is lacking. Using a combination of targeted and untargeted high-resolution mass spectrometry, we found that PHHs in 3D spheroid cultures remained metabolically stable for multiple weeks, whereas metabolic patterns of PHHs from the same donors cultured as conventional 2D monolayers rapidly deteriorated. Furthermore, pharmacokinetic differences between donors were maintained in 3D spheroid cultures, enabling studies of interindividual variability in drug metabolism and toxicity. We conclude that the 3D spheroid system is metabolically stable and constitutes a suitable model for in vitro studies of long-term drug metabolism and pharmacokinetics.-Vorrink, S. U., Ullah, S., Schmid, S., Nandania, J., Velagapudi, V., Beck, O., Ingelman-Sundberg, M., Lauschke, V. M. Endogenous and xenobiotic metabolic stability of primary human hepatocytes in long-term 3D spheroid cultures revealed by a combination of targeted and untargeted metabolomics. © The Author(s).

  16. Multi-targeted priming for genome-wide gene expression assays.

    Science.gov (United States)

    Adomas, Aleksandra B; Lopez-Giraldez, Francesc; Clark, Travis A; Wang, Zheng; Townsend, Jeffrey P

    2010-08-17

    Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of Saccharomyces cerevisiae and of Neurospora crassa, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays. We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of Saccharomyces cerevisiae and Neurospora crassa while avoiding priming ribosomal RNA or transfer RNA. Examining the response of Saccharomyces cerevisiae to nitrogen deficiency and profiling Neurospora crassa early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression. Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and N. crassa early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and precise assay of the transcribed sequences within the genome.

  17. Identifying Human Genome-Wide CNV, LOH and UPD by Targeted Sequencing of Selected Regions.

    Directory of Open Access Journals (Sweden)

    Wei Li

    Full Text Available Copy-number variations (CNV, loss of heterozygosity (LOH, and uniparental disomy (UPD are large genomic aberrations leading to many common inherited diseases, cancers, and other complex diseases. An integrated tool to identify these aberrations is essential in understanding diseases and in designing clinical interventions. Previous discovery methods based on whole-genome sequencing (WGS require very high depth of coverage on the whole genome scale, and are cost-wise inefficient. Another approach, whole exome genome sequencing (WEGS, is limited to discovering variations within exons. Thus, we are lacking efficient methods to detect genomic aberrations on the whole genome scale using next-generation sequencing technology. Here we present a method to identify genome-wide CNV, LOH and UPD for the human genome via selectively sequencing a small portion of genome termed Selected Target Regions (SeTRs. In our experiments, the SeTRs are covered by 99.73%~99.95% with sufficient depth. Our developed bioinformatics pipeline calls genome-wide CNVs with high confidence, revealing 8 credible events of LOH and 3 UPD events larger than 5M from 15 individual samples. We demonstrate that genome-wide CNV, LOH and UPD can be detected using a cost-effective SeTRs sequencing approach, and that LOH and UPD can be identified using just a sample grouping technique, without using a matched sample or familial information.

  18. Probabilistic Principal Component Analysis for Metabolomic Data.

    LENUS (Irish Health Repository)

    Nyamundanda, Gift

    2010-11-23

    Abstract Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field.

  19. Metabolomics for laboratory diagnostics.

    Science.gov (United States)

    Bujak, Renata; Struck-Lewicka, Wiktoria; Markuszewski, Michał J; Kaliszan, Roman

    2015-09-10

    Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Selectivity issues in targeted metabolomics: Separation of phosphorylated carbohydrate isomers by mixed-mode hydrophilic interaction/weak anion exchange chromatography

    NARCIS (Netherlands)

    Hinterwirth, Helmut; Lämmerhofer, Michael; Preinerstorfer, Beatrix; Gargano, Andrea; Reischl, Roland; Bicker, Wolfgang; Trapp, Oliver; Brecker, Lothar; Lindner, Wolfgang

    2010-01-01

    Phosphorylated carbohydrates are important intracellular metabolites and thus of prime interest in metabolomics research. Complications in their analysis arise from the existence of structural isomers that do have similar fragmentation patterns in MS/MS and are hard to resolve chromatographically.

  1. Non-target metabolomic profiling of the marine microalgae dunaliella tertiolecta after exposure to diuron using complementary high-resolution analytical techniques

    NARCIS (Netherlands)

    Booij, P; Lamoree, M.H.; Sjollema, S.B.; de Voogt, P.; Schollée, J.E.; Vethaak, A.D.; Leonards, P.E.G.

    2014-01-01

    Traditionally, bioassays are used to assess the toxicity of chemicals. Bioassays often focus on one specific mode of action or end point and their responses offer a limited understanding of the health status and underlying pathways of the species under consideration. Metabolomics can be used to

  2. The metabolomic profile of red non-V. vinifera genotypes.

    Science.gov (United States)

    Ruocco, Silvia; Stefanini, Marco; Stanstrup, Jan; Perenzoni, Daniele; Mattivi, Fulvio; Vrhovsek, Urska

    2017-08-01

    Wild American genotypes represent an important part of the Vitis germplasm in relation to grape improvement. Today, these genotypes are currently involved in breeding programmes in order to introgress traits resistant to pests and diseases in V. vinifera cultivars. Nevertheless, the metabolic composition of their grapes has not been widely investigated. This study aimed to explore in detail the metabolomic profile in terms of simple phenolic, proanthocyanidin, anthocyanin and lipid compounds in two hybrids and five American genotypes. The results were compared with those of two V. vinifera cultivars. A multi-targeted metabolomics approach using a combination of LC-MS and LC-DAD methods was used to identify and quantify 124 selected metabolites. The genotypes studied showed considerable variability in the metabolomic profile according to the grape composition of V. vinifera and other Vitis genotypes. As regards the composition of anthocyanins, not all wild genotypes contained both mono- and di-glucoside derivatives. Wild genotype 41B and V. vinifera cultivars contained only monoglucoside anthocyanins. The proanthocyanidins of non-V. vinifera genotypes were mainly rich in oligomers and short-chain polymers. The analysis of lipids in wild Vitis genotypes, here reported for the first time, showed the existence of a certain diversity in their composition suggesting a strong influence of the environmental conditions on the general lipid pattern. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Metabolomics in Plants and Humans: Applications in the Prevention and Diagnosis of Diseases

    OpenAIRE

    Diego F Gomez-Casati; Zanor, Maria I.; Busi, María V.

    2013-01-01

    In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, toimprove their diagnosis and prevention, and to design better therapeutic strategies. In addition,metabolomic studi...

  4. Metabolomics and Epidemiology Working Group

    Science.gov (United States)

    The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

  5. Clinical impact of human breast milk metabolomics.

    Science.gov (United States)

    Cesare Marincola, Flaminia; Dessì, Angelica; Corbu, Sara; Reali, Alessandra; Fanos, Vassilios

    2015-12-07

    Metabolomics is a research field concerned with the analysis of metabolome, the complete set of metabolites in a given cell, tissue, or biological sample. Being able to provide a molecular snapshot of biological systems, metabolomics has emerged as a functional methodology in a wide range of research areas such as toxicology, pharmacology, food technology, nutrition, microbial biotechnology, systems biology, and plant biotechnology. In this review, we emphasize the applications of metabolomics in investigating the human breast milk (HBM) metabolome. HBM is the recommended source of nutrition for infants since it contains the optimal balance of nutrients for developing babies, and it provides a range of benefits for growth, immunity, and development. The molecular mechanisms beyond the inter- and intra-variability of HBM that make its composition unique are yet to be well-characterized. Although still in its infancy, the study of HBM metabolome has already proven itself to be of great value in providing insights into this biochemical variability in relation to mother phenotype, diet, disease, and lifestyle. The results of these investigations lay the foundation for further developments useful to identify normal and aberrant biochemical changes as well as to develop strategies to promote healthy infant feeding practices. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Impact of Anesthesia and Euthanasia on Metabolomics of Mammalian Tissues: Studies in a C57BL/6J Mouse Model

    Science.gov (United States)

    Overmyer, Katherine A.; Thonusin, Chanisa; Qi, Nathan R.; Burant, Charles F.; Evans, Charles R.

    2015-01-01

    A critical application of metabolomics is the evaluation of tissues, which are often the primary sites of metabolic dysregulation in disease. Laboratory rodents have been widely used for metabolomics studies involving tissues due to their facile handing, genetic manipulability and similarity to most aspects of human metabolism. However, the necessary step of administration of anesthesia in preparation for tissue sampling is not often given careful consideration, in spite of its potential for causing alterations in the metabolome. We examined, for the first time using untargeted and targeted metabolomics, the effect of several commonly used methods of anesthesia and euthanasia for collection of skeletal muscle, liver, heart, adipose and serum of C57BL/6J mice. The data revealed dramatic, tissue-specific impacts of tissue collection strategy. Among many differences observed, post-euthanasia samples showed elevated levels of glucose 6-phosphate and other glycolytic intermediates in skeletal muscle. In heart and liver, multiple nucleotide and purine degradation metabolites accumulated in tissues of euthanized compared to anesthetized animals. Adipose tissue was comparatively less affected by collection strategy, although accumulation of lactate and succinate in euthanized animals was observed in all tissues. Among methods of tissue collection performed pre-euthanasia, ketamine showed more variability compared to isoflurane and pentobarbital. Isoflurane induced elevated liver aspartate but allowed more rapid initiation of tissue collection. Based on these findings, we present a more optimal collection strategy mammalian tissues and recommend that rodent tissues intended for metabolomics studies be collected under anesthesia rather than post-euthanasia. PMID:25658945

  7. Metabolomic signature of brain cancer.

    Science.gov (United States)

    Pandey, Renu; Caflisch, Laura; Lodi, Alessia; Brenner, Andrew J; Tiziani, Stefano

    2017-11-01

    Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed. © 2017 Wiley Periodicals, Inc.

  8. Genome-wide identification of the regulatory targets of a transcription factor using biochemical characterization and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Jolly Emmitt R

    2005-11-01

    Full Text Available Abstract Background A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis. Results Our method identified potential target genes of the transcription factor Ndt80, a key transcriptional regulator involved in yeast sporulation, using the combined information of binding affinity, positional distribution, and conservation of the binding sites across multiple species. We have also developed a mathematical approach to compute the false positive rate and the total number of targets in the genome based on the multiple selection criteria. Conclusion We have shown that combining biochemical characterization and computational genomic analysis leads to accurate identification of the genome-wide targets of a transcription factor. The method can be extended to other transcription factors and can complement other genomic approaches to transcriptional regulation.

  9. Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data.

    Directory of Open Access Journals (Sweden)

    Andreas Kuehne

    2017-06-01

    Full Text Available In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.

  10. Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data.

    Science.gov (United States)

    Kuehne, Andreas; Mayr, Urs; Sévin, Daniel C; Claassen, Manfred; Zamboni, Nicola

    2017-06-01

    In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved) data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.

  11. Wide screening of phage-displayed libraries identifies immune targets in planta.

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    Cristina Rioja

    Full Text Available Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2 × 10(7 different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes

  12. Wide screening of phage-displayed libraries identifies immune targets in planta.

    Science.gov (United States)

    Rioja, Cristina; Van Wees, Saskia C; Charlton, Keith A; Pieterse, Corné M J; Lorenzo, Oscar; García-Sánchez, Susana

    2013-01-01

    Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2 × 10(7) different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well

  13. Wide Screening of Phage-Displayed Libraries Identifies Immune Targets in Planta

    Science.gov (United States)

    Rioja, Cristina; Van Wees, Saskia C.; Charlton, Keith A.; Pieterse, Corné M. J.; Lorenzo, Oscar; García-Sánchez, Susana

    2013-01-01

    Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2×107 different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well

  14. Genome-wide dynamics of a bacterial response to antibiotics that target the cell envelope

    Directory of Open Access Journals (Sweden)

    Tran Ngat

    2011-05-01

    Full Text Available Abstract Background A decline in the discovery of new antibacterial drugs, coupled with a persistent rise in the occurrence of drug-resistant bacteria, has highlighted antibiotics as a diminishing resource. The future development of new drugs with novel antibacterial activities requires a detailed understanding of adaptive responses to existing compounds. This study uses Streptomyces coelicolor A3(2 as a model system to determine the genome-wide transcriptional response following exposure to three antibiotics (vancomycin, moenomycin A and bacitracin that target distinct stages of cell wall biosynthesis. Results A generalised response to all three antibiotics was identified which involves activation of transcription of the cell envelope stress sigma factor σE, together with elements of the stringent response, and of the heat, osmotic and oxidative stress regulons. Attenuation of this system by deletion of genes encoding the osmotic stress sigma factor σB or the ppGpp synthetase RelA reduced resistance to both vancomycin and bacitracin. Many antibiotic-specific transcriptional changes were identified, representing cellular processes potentially important for tolerance to each antibiotic. Sensitivity studies using mutants constructed on the basis of the transcriptome profiling confirmed a role for several such genes in antibiotic resistance, validating the usefulness of the approach. Conclusions Antibiotic inhibition of bacterial cell wall biosynthesis induces both common and compound-specific transcriptional responses. Both can be exploited to increase antibiotic susceptibility. Regulatory networks known to govern responses to environmental and nutritional stresses are also at the core of the common antibiotic response, and likely help cells survive until any specific resistance mechanisms are fully functional.

  15. Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases.

    Science.gov (United States)

    Gomez-Casati, Diego F; Zanor, Maria I; Busi, María V

    2013-01-01

    In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

  16. Statistical methods in metabolomics.

    Science.gov (United States)

    Korman, Alexander; Oh, Amy; Raskind, Alexander; Banks, David

    2012-01-01

    Metabolomics is the relatively new field in bioinformatics that uses measurements on metabolite abundance as a tool for disease diagnosis and other medical purposes. Although closely related to proteomics, the statistical analysis is potentially simpler since biochemists have significantly more domain knowledge about metabolites. This chapter reviews the challenges that metabolomics poses in the areas of quality control, statistical metrology, and data mining.

  17. Metabolomics across the globe

    NARCIS (Netherlands)

    Summer, L.W.; Hall, R.D.

    2013-01-01

    This article highlights some of the larger and more recent metabolomics activities which are funded and organised at local (mostly national) level. While being just a snap-shot, and far from exhaustive, the details clearly illustrate the extent to which metabolomics has already become established

  18. Metabolomics: A Primer.

    Science.gov (United States)

    Liu, Xiaojing; Locasale, Jason W

    2017-04-01

    Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. CisOrtho: A program pipeline for genome-wide identification of transcription factor target genes using phylogenetic footprinting

    Directory of Open Access Journals (Sweden)

    Hobert Oliver

    2004-03-01

    Full Text Available Abstract Background All known genomes code for a large number of transcription factors. It is important to develop methods that will reveal how these transcription factors act on a genome wide level, that is, through what target genes they exert their function. Results We describe here a program pipeline aimed at identifying transcription factor target genes in whole genomes. Starting from a consensus binding site, represented as a weight matrix, potential sites in a pre-filtered genome are identified and then further filtered by assessing conservation of the putative site in the genome of a related species, a process called phylogenetic footprinting. CisOrtho has been successfully used to identify targets for two homeodomain transcription factors in the genomes of the nematodes Caenorhabditis elegans and Caenorhabditis briggsae. Conclusions CisOrtho will identify targets of other nematode transcription factors whose DNA binding specificity is known and can be easily adapted to search other genomes for transcription factor targets.

  20. Error Analysis and Propagation in Metabolomics Data Analysis.

    Science.gov (United States)

    Moseley, Hunter N B

    2013-01-01

    Error analysis plays a fundamental role in describing the uncertainty in experimental results. It has several fundamental uses in metabolomics including experimental design, quality control of experiments, the selection of appropriate statistical methods, and the determination of uncertainty in results. Furthermore, the importance of error analysis has grown with the increasing number, complexity, and heterogeneity of measurements characteristic of 'omics research. The increase in data complexity is particularly problematic for metabolomics, which has more heterogeneity than other omics technologies due to the much wider range of molecular entities detected and measured. This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis. These methodologies include analytical derivation and approximation techniques, Monte Carlo error analysis, and error analysis in metabolic inverse problems. Current limitations of each methodology with respect to metabolomics data analysis are also discussed.

  1. NMR-based Metabolomics for Cancer Research

    Science.gov (United States)

    Metabolomics is considered as a complementary tool to other omics platforms to provide a snapshot of the cellular biochemistry and physiology taking place at any instant. Metabolmics approaches have been widely used to provide comprehensive and quantitative analyses of the metabo...

  2. Metabolomics for the masses: The future of metabolomics in a personalized world.

    Science.gov (United States)

    Trivedi, Drupad K; Hollywood, Katherine A; Goodacre, Royston

    2017-03-01

    Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

  3. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    Science.gov (United States)

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    2016-12-01

    Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

  4. Circadian Metabolomics in Time and Space.

    Science.gov (United States)

    Dyar, Kenneth A; Eckel-Mahan, Kristin L

    2017-01-01

    Circadian rhythms are widely known to govern human health and disease, but specific pathogenic mechanisms linking circadian disruption to metabolic diseases are just beginning to come to light. This is thanks in part to the development and application of various "omics"-based tools in biology and medicine. Current high-throughput technologies allow for the simultaneous monitoring of multiple dynamic cellular events over time, ranging from gene expression to metabolite abundance and sub-cellular localization. These fundamental temporal and spatial perspectives have allowed for a more comprehensive understanding of how various dynamic cellular events and biochemical processes are related in health and disease. With advances in technology, metabolomics has become a more routine "omics" approach for studying metabolism, and "circadian metabolomics" (i.e., studying the 24-h metabolome) has recently been undertaken by several groups. To date, circadian metabolomes have been reported for human serum, saliva, breath, and urine, as well as tissues from several species under specific disease or mutagenesis conditions. Importantly, these studies have consistently revealed that 24-h rhythms are prevalent in almost every tissue and metabolic pathway. Furthermore, these circadian rhythms in tissue metabolism are ultimately linked to and directed by internal 24-h biological clocks. In this review, we will attempt to put these data-rich circadian metabolomics experiments into perspective to find out what they can tell us about metabolic health and disease, and what additional biomarker potential they may reveal.

  5. Review of sample preparation strategies for MS-based metabolomic studies in industrial biotechnology.

    Science.gov (United States)

    Causon, Tim J; Hann, Stephan

    2016-09-28

    Fermentation and cell culture biotechnology in the form of so-called "cell factories" now play an increasingly significant role in production of both large (e.g. proteins, biopharmaceuticals) and small organic molecules for a wide variety of applications. However, associated metabolic engineering optimisation processes relying on genetic modification of organisms used in cell factories, or alteration of production conditions remain a challenging undertaking for improving the final yield and quality of cell factory products. In addition to genomic, transcriptomic and proteomic workflows, analytical metabolomics continues to play a critical role in studying detailed aspects of critical pathways (e.g. via targeted quantification of metabolites), identification of biosynthetic intermediates, and also for phenotype differentiation and the elucidation of previously unknown pathways (e.g. via non-targeted strategies). However, the diversity of primary and secondary metabolites and the broad concentration ranges encompassed during typical biotechnological processes means that simultaneous extraction and robust analytical determination of all parts of interest of the metabolome is effectively impossible. As the integration of metabolome data with transcriptome and proteome data is an essential goal of both targeted and non-targeted methods addressing production optimisation goals, additional sample preparation steps beyond necessary sampling, quenching and extraction protocols including clean-up, analyte enrichment, and derivatisation are important considerations for some classes of metabolites, especially those present in low concentrations or exhibiting poor stability. This contribution critically assesses the potential of current sample preparation strategies applied in metabolomic studies of industrially-relevant cell factory organisms using mass spectrometry-based platforms primarily coupled to liquid-phase sample introduction (i.e. flow injection, liquid

  6. Metabolomic heterogeneity of pulmonary arterial hypertension.

    Directory of Open Access Journals (Sweden)

    Yidan Zhao

    Full Text Available Although multiple gene and protein expression have been extensively profiled in human pulmonary arterial hypertension (PAH, the mechanism for the development and progression of pulmonary hypertension remains elusive. Analysis of the global metabolomic heterogeneity within the pulmonary vascular system leads to a better understanding of disease progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we showed unbiased metabolomic profiles of disrupted glycolysis, increased TCA cycle, and fatty acid metabolites with altered oxidation pathways in the human PAH lung. The results suggest that PAH has specific metabolic pathways contributing to increased ATP synthesis for the vascular remodeling process in severe pulmonary hypertension. These identified metabolites may serve as potential biomarkers for the diagnosis of PAH. By profiling metabolomic alterations of the PAH lung, we reveal new pathogenic mechanisms of PAH, opening an avenue of exploration for therapeutics that target metabolic pathway alterations in the progression of PAH.

  7. Metabolomics in pediatric nephrology: Emerging concepts

    Science.gov (United States)

    Hanna, Mina H; Brophy, Patrick D

    2014-01-01

    Metabolomics, the latest of the “omics” sciences, refers to the systematic study of metabolites and their changes in biological samples due to physiological stimuli and/or genetic modification. Because metabolites represent the downstream expression of genome, transcriptome and proteome, they can closely reflect the phenotype of an organism at a specific time. As an emerging field in analytical biochemistry; metabolomics has the potential to play a major role for monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights for novel biomarkers of kidney diseases, given the limitations of the current traditional markers. The clinical utility of metabolomics in the field of pediatric nephrology includes biomarker discovery, defining as yet unrecognized biologic therapeutic targets, linking of metabolites to relevant standard indices and clinical outcomes, and providing a window of opportunity to investigate the intricacies of environment/genetic interplay in specific disease states. PMID:25027575

  8. Metabolomic Heterogeneity of Pulmonary Arterial Hypertension

    Science.gov (United States)

    Zhao, Yidan; Peng, Jenny; Lu, Catherine; Hsin, Michael; Mura, Marco; Wu, Licun; Chu, Lei; Zamel, Ricardo; Machuca, Tiago; Waddell, Thomas; Liu, Mingyao; Keshavjee, Shaf; Granton, John; de Perrot, Marc

    2014-01-01

    Although multiple gene and protein expression have been extensively profiled in human pulmonary arterial hypertension (PAH), the mechanism for the development and progression of pulmonary hypertension remains elusive. Analysis of the global metabolomic heterogeneity within the pulmonary vascular system leads to a better understanding of disease progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we showed unbiased metabolomic profiles of disrupted glycolysis, increased TCA cycle, and fatty acid metabolites with altered oxidation pathways in the human PAH lung. The results suggest that PAH has specific metabolic pathways contributing to increased ATP synthesis for the vascular remodeling process in severe pulmonary hypertension. These identified metabolites may serve as potential biomarkers for the diagnosis of PAH. By profiling metabolomic alterations of the PAH lung, we reveal new pathogenic mechanisms of PAH, opening an avenue of exploration for therapeutics that target metabolic pathway alterations in the progression of PAH. PMID:24533144

  9. Told through the wine: A liquid chromatography-mass spectrometry interplatform comparison reveals the influence of the global approach on the final annotated metabolites in non-targeted metabolomics.

    Science.gov (United States)

    Díaz, Ramon; Gallart-Ayala, Hector; Sancho, Juan V; Nuñez, Oscar; Zamora, Tatiana; Martins, Claudia P B; Hernández, Félix; Hernández-Cassou, Santiago; Saurina, Javier; Checa, Antonio

    2016-02-12

    This work focuses on the influence of the selected LC-HRMS platform on the final annotated compounds in non-targeted metabolomics. Two platforms that differed in columns, mobile phases, gradients, chromatographs, mass spectrometers (Orbitrap [Platform#1] and Q-TOF [Platform#2]), data processing and marker selection protocols were compared. A total of 42 wines samples from three different protected denomination of origin (PDO) were analyzed. At the feature level, good (O)PLS-DA models were obtained for both platforms (Q(2)[Platform#1]=0.89, 0.83 and 0.72; Q(2)[Platform#2]=0.86, 0.86 and 0.77 for Penedes, Ribera del Duero and Rioja wines respectively) with 100% correctly classified samples in all cases. At the annotated metabolite level, platforms proposed 9 and 8 annotated metabolites respectively which were identified by matching standards or the MS/MS spectra of the compounds. At this stage, there was no coincidence among platforms regarding the suggested metabolites. When screened on the raw data, 6 and 5 of these compounds were detected on the other platform with a similar trend. Some of the detected metabolites showed complimentary information when integrated on biological pathways. Through the use of some examples at the annotated metabolite level, possible explanations of this initial divergence on the results are presented. This work shows the complications that may arise on the comparison of non-targeted metabolomics platforms even when metabolite focused approaches are used in the identification. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Metabolomics in chemical ecology.

    Science.gov (United States)

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  11. Genome-wide Analysis of for the Identification of Putative Therapeutic Targets

    Directory of Open Access Journals (Sweden)

    Md. Masud Parvege

    2014-01-01

    Full Text Available Ever increasing propensity of antibiotic resistance among pathogenic bacteria raises the demand for the development of novel therapeutic agents to control this grave problem. Advances in the field of bioinformatics, genomics, and proteomics have greatly facilitated the discovery of alternative drugs by swift identification of new drug targets. In the present study, we employed comparative genomics and metabolic pathway analysis with an aim of identifying therapeutic targets in Mycoplasma hominis. Our study has revealed 40 annotated metabolic pathways, including five unique pathways of M. hominis. Our study also identified 179 essential proteins, including 59 proteins having no similarity with human proteins. Further filtering by molecular weight, subcellular localization, functional analysis, and protein network interaction, we identified 57 putative candidates for which new drugs can be developed. Druggability analysis for each of the identified targets has prioritized 16 proteins as suitable for potential drug development.

  12. [Application and research advances of metabolomics in the field of orthopedics].

    Science.gov (United States)

    Sun, Zhijian; Qiu, Guixing; Zhao, Yu

    2015-06-01

    Metabolomics is a subject of systematic, qualitative and quantitative analysis of all metabolites in all organisms, which is applied to finding biomarkers and studying pathogenesis of diseases. Study procedures of metabolomics include data acquisition by spectroscopic/spectrometric techniques, multivariate statistical analysis and projection of the acquired metabolomic information. In recent years, metabolomics have gained popularity in orthopedic field. Metabolomic study of osteoarthritis was firstly conducted and widely developed. Metabolite profiles of different samples, including serum/plasma, urine, synovial fluid and synovial tissue, were studied and dozens of differential metabolites and several disturbed metabolic pathways were found. In addition, metabolomic studies of osteoporosis, ankylosing spondylitis and bone tumors were also conducted, which identified many potential biomarkers and made further understanding of pathogenesis of corresponding disease. However, metabolomic studies in orthopedic field just begin. More orthopedic diseases will be researched thank to the satisfactory results of previous reports.

  13. E-Cigarette Affects the Metabolome of Primary Normal Human Bronchial Epithelial Cells.

    Directory of Open Access Journals (Sweden)

    Argo Aug

    Full Text Available E-cigarettes are widely believed to be safer than conventional cigarettes and have been even suggested as aids for smoking cessation. However, while reasonable with some regards, this judgment is not yet supported by adequate biomedical research data. Since bronchial epithelial cells are the immediate target of inhaled toxicants, we hypothesized that exposure to e-cigarettes may affect the metabolome of human bronchial epithelial cells (HBEC and that the changes are, at least in part, induced by oxidant-driven mechanisms. Therefore, we evaluated the effect of e-cigarette liquid (ECL on the metabolome of HBEC and examined the potency of antioxidants to protect the cells. We assessed the changes of the intracellular metabolome upon treatment with ECL in comparison of the effect of cigarette smoke condensate (CSC with mass spectrometry and principal component analysis on air-liquid interface model of normal HBEC. Thereafter, we evaluated the capability of the novel antioxidant tetrapeptide O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1 to attenuate the effect of ECL. ECL caused a significant shift in the metabolome that gradually gained its maximum by the 5th hour and receded by the 7th hour. A second alteration followed at the 13th hour. Treatment with CSC caused a significant initial shift already by the 1st hour. ECL, but not CSC, significantly increased the concentrations of arginine, histidine, and xanthine. ECL, in parallel with CSC, increased the content of adenosine diphosphate and decreased that of three lipid species from the phosphatidylcholine family. UPF1 partially counteracted the ECL-induced deviations, UPF1's maximum effect occurred at the 5th hour. The data support our hypothesis that ECL profoundly alters the metabolome of HBEC in a manner, which is comparable and partially overlapping with the effect of CSC. Hence, our results do not support the concept of harmlessness of e-cigarettes.

  14. Enzymatically Modified Starch Ameliorates Postprandial Serum Triglycerides and Lipid Metabolome in Growing Pigs.

    Science.gov (United States)

    Metzler-Zebeli, Barbara U; Eberspächer, Eva; Grüll, Dietmar; Kowalczyk, Lidia; Molnar, Timea; Zebeli, Qendrim

    2015-01-01

    Developing host digestion-resistant starches to promote human health is of great research interest. Chemically modified starches (CMS) are widely used in processed foods and although the modification of the starch molecule allows specific reduction in digestibility, the metabolic effects of CMS have been less well described. This short-term study evaluated the impact of enzymatically modified starch (EMS) on fasting and postprandial profiles of blood glucose, insulin and lipids, and serum metabolome in growing pigs. Eight jugular-vein catheterized pigs (initial body weight, 37.4 kg; 4 months of age) were fed 2 diets containing 72% purified starch (EMS or waxy corn starch (control)) in a cross-over design for 7 days. On day 8, an 8-hour meal tolerance test (MTT) was performed with serial blood samplings. Besides biochemical analysis, serum was analysed for 201 metabolites through targeted mass spectrometry-based metabolomic approaches. Pigs fed the EMS diet showed increased (P<0.05) immediate serum insulin and plasma glucose response compared to pigs fed the control diet; however, area-under-the-curves for insulin and glucose were not different among diets. Results from MTT indicated reduced postprandial serum triglycerides with EMS versus control diet (P<0.05). Likewise, serum metabolome profiling identified characteristic changes in glycerophospholipid, lysophospholipids, sphingomyelins and amino acid metabolome profiles with EMS diet compared to control diet. Results showed rapid adaptations of blood metabolites to dietary starch shifts within 7 days. In conclusion, EMS ingestion showed potential to attenuate postprandial raise in serum lipids and suggested constant alteration in the synthesis or breakdown of sphingolipids and phospholipids which might be a health benefit of EMS consumption. Because serum insulin was not lowered, more research is warranted to reveal possible underlying mechanisms behind the observed changes in the profile of serum lipid

  15. Persistent Target Tracking Using Likelihood Fusion in Wide-Area and Full Motion Video Sequences

    Science.gov (United States)

    2012-07-01

    problems associated with a moving platform including gimbal -based stabilization errors, relative motion where sensor and target are both moving, seams in...Image Processing, 2000, pp. 561–564. [46] A. Hafiane, K. Palaniappan, and G. Seetharaman, “ UAV -video registra- tion using block-based features,” in IEEE

  16. Metabolomic studies in pulmonology

    Directory of Open Access Journals (Sweden)

    R. R. Furina

    2015-01-01

    Full Text Available The review shows the results of metabolomic studies in pulmonology. The key idea of metabolomics is to detect specific biomarkers in a biological sample for the diagnosis of diseases of the bronchi and lung. Main methods for the separation and identification of volatile organic substances as biomarkers (gas chromatography, mass spectrometry, and nuclear magnetic resonance spectrometry used in metabolomics are given. A solid-phase microextraction method used to pre-prepare a sample is also covered. The results of laboratory tests for biomarkers for lung cancer, acute respiratory distress syndrome, chronic obstructive pulmonary disease, cystic fibrosis, chronic infections, and pulmonary tuberculosis are presented. In addition, emphasis is placed on the possibilities of metabolomics used in experimental medicine, including to the study of asthma. The information is of interest to both theorists and practitioners.

  17. Metabolomics in dyslipidemia.

    Science.gov (United States)

    Chen, Hua; Miao, Hua; Feng, Ya-Long; Zhao, Ying-Yong; Lin, Rui-Chao

    2014-01-01

    Hyperlipidemia is an important public health problem with increased incidence and prevalence worldwide. Current clinical biomarkers, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol lack the necessary specificity and sensitivity and only increase significantly after serious dyslipidemia. Therefore, sensitive biomarkers are needed for hyperlipidemia. Hyperlipidemia-specific biomarkers would improve clinical diagnosis and therapeutic treatment at early disease stages. The aim of metabolomics is to identify untargeted and global small-molecule metabolite profiles from cells, biofluids, and tissues. This method offers the potential for a holistic approach to improve disease diagnoses and our understanding of underlying pathologic mechanisms. This review summarizes analytical techniques, data collection and analysis for metabolomics, and metabolomics in hyperlipidemia animal models and clinical studies. Mechanisms of hypolipemia and antilipemic drug therapy are also discussed. Metabolomics provides a new opportunity to gain insight into metabolic profiling and pathophysiologic mechanisms of hyperlipidemia.

  18. Metabolomics er fremtiden

    DEFF Research Database (Denmark)

    Pedersern, Birger

    2010-01-01

    Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet......Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet...

  19. Quality assurance of metabolomics.

    Science.gov (United States)

    Bouhifd, Mounir; Beger, Richard; Flynn, Thomas; Guo, Lining; Harris, Georgina; Hogberg, Helena; Kaddurah-Daouk, Rima; Kamp, Hennicke; Kleensang, Andre; Maertens, Alexandra; Odwin-DaCosta, Shelly; Pamies, David; Robertson, Donald; Smirnova, Lena; Sun, Jinchun; Zhao, Liang; Hartung, Thomas

    2015-01-01

    Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.

  20. Genome-wide search for miRNA-target interactions in Arabidopsis thaliana with an integrated approach

    Directory of Open Access Journals (Sweden)

    Ding Jiandong

    2012-06-01

    Full Text Available Abstract Background MiRNA are about 22nt long small noncoding RNAs that post transcriptionally regulate gene expression in animals, plants and protozoa. Confident identification of MiRNA-Target Interactions (MTI is vital to understand their function. Currently, several integrated computational programs and databases are available for animal miRNAs, the mechanisms of which are significantly different from plant miRNAs. Methods Here we present an integrated MTI prediction and analysis toolkit (imiRTP for Arabidopsis thaliana. It features two important functions: (i combination of several effective plant miRNA target prediction methods provides a sufficiently large MTI candidate set, and (ii different filters allow for an efficient selection of potential targets. The modularity of imiRTP enables the prediction of high quality targets on genome-wide scale. Moreover, predicted MTIs can be presented in various ways, which allows for browsing through the putative target sites as well as conducting simple and advanced analyses. Results Results show that imiRTP could always find high quality candidates compared with single method by choosing appropriate filter and parameter. And we also reveal that a portion of plant miRNA could bind target genes out of coding region. Based on our results, imiRTP could facilitate the further study of Arabidopsis miRNAs in real use. All materials of imiRTP are freely available under a GNU license at (http://admis.fudan.edu.cn/projects/imiRTP.htm.

  1. Genome-wide identification of Bcl11b gene targets reveals role in brain-derived neurotrophic factor signaling.

    Directory of Open Access Journals (Sweden)

    Bin Tang

    Full Text Available B-cell leukemia/lymphoma 11B (Bcl11b is a transcription factor showing predominant expression in the striatum. To date, there are no known gene targets of Bcl11b in the nervous system. Here, we define targets for Bcl11b in striatal cells by performing chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq in combination with genome-wide expression profiling. Transcriptome-wide analysis revealed that 694 genes were significantly altered in striatal cells over-expressing Bcl11b, including genes showing striatal-enriched expression similar to Bcl11b. ChIP-seq analysis demonstrated that Bcl11b bound a mixture of coding and non-coding sequences that were within 10 kb of the transcription start site of an annotated gene. Integrating all ChIP-seq hits with the microarray expression data, 248 direct targets of Bcl11b were identified. Functional analysis on the integrated gene target list identified several zinc-finger encoding genes as Bcl11b targets, and further revealed a significant association of Bcl11b to brain-derived neurotrophic factor/neurotrophin signaling. Analysis of ChIP-seq binding regions revealed significant consensus DNA binding motifs for Bcl11b. These data implicate Bcl11b as a novel regulator of the BDNF signaling pathway, which is disrupted in many neurological disorders. Specific targeting of the Bcl11b-DNA interaction could represent a novel therapeutic approach to lowering BDNF signaling specifically in striatal cells.

  2. Compressive imaging for difference image formation and wide-field-of-view target tracking

    Science.gov (United States)

    Shikhar

    2010-11-01

    Use of imaging systems for performing various situational awareness tasks in military and commercial settings has a long history. There is increasing recognition, however, that a much better job can be done by developing non-traditional optical systems that exploit the task-specific system aspects within the imager itself. In some cases, a direct consequence of this approach can be real-time data compression along with increased measurement fidelity of the task-specific features. In others, compression can potentially allow us to perform high-level tasks such as direct tracking using the compressed measurements without reconstructing the scene of interest. In this dissertation we present novel advancements in feature-specific (FS) imagers for large field-of-view surveillence, and estimation of temporal object-scene changes utilizing the compressive imaging paradigm. We develop these two ideas in parallel. In the first case we show a feature-specific (FS) imager that optically multiplexes multiple, encoded sub-fields of view onto a common focal plane. Sub-field encoding enables target tracking by creating a unique connection between target characteristics in superposition space and the target's true position in real space. This is accomplished without reconstructing a conventional image of the large field of view. System performance is evaluated in terms of two criteria: average decoding time and probability of decoding error. We study these performance criteria as a function of resolution in the encoding scheme and signal-to-noise ratio. We also include simulation and experimental results demonstrating our novel tracking method. In the second case we present a FS imager for estimating temporal changes in the object scene over time by quantifying these changes through a sequence of difference images. The difference images are estimated by taking compressive measurements of the scene. Our goals are twofold. First, to design the optimal sensing matrix for taking

  3. Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-02-01

    Full Text Available With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA. Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.

  4. COnsortium of METabolomics Studies (COMETS)

    Science.gov (United States)

    The COnsortium of METabolomics Studies (COMETS) is an extramural-intramural partnership that promotes collaboration among prospective cohort studies that follow participants for a range of outcomes and perform metabolomic profiling of individuals.

  5. Metabolomics approach for discovering disease biomarkers and understanding metabolic pathway

    Directory of Open Access Journals (Sweden)

    Jeeyoun Jung

    2011-12-01

    Full Text Available Metabolomics, the multi-targeted analysis of endogenous metabolites from biological samples, can be efficiently applied to screen disease biomarkers and investigate pathophysiological processes. Metabolites change rapidly in response to physiological perturbations, making them the closest link to disease phenotypes. This study explored the role of metabolomics in gaining mechanistic insight into disease processes and in searching for novel biomarkers of human diseases

  6. The ABRF Metabolomics Research Group 2013 Study: Investigation of Spiked Compound Differences in a Human Plasma Matrix.

    Science.gov (United States)

    Cheema, Amrita K; Asara, John M; Wang, Yiwen; Neubert, Thomas A; Tolstikov, Vladimir; Turck, Chris W

    2015-09-01

    Metabolomics is an emerging field that involves qualitative and quantitative measurements of small molecule metabolites in a biological system. These measurements can be useful for developing biomarkers for diagnosis, prognosis, or predicting response to therapy. Currently, a wide variety of metabolomics approaches, including nontargeted and targeted profiling, are used across laboratories on a routine basis. A diverse set of analytical platforms, such as NMR, gas chromatography-mass spectrometry, Orbitrap mass spectrometry, and time-of-flight-mass spectrometry, which use various chromatographic and ionization techniques, are used for resolution, detection, identification, and quantitation of metabolites from various biological matrices. However, few attempts have been made to standardize experimental methodologies or comparative analyses across different laboratories. The Metabolomics Research Group of the Association of Biomolecular Resource Facilities organized a "round-robin" experiment type of interlaboratory study, wherein human plasma samples were spiked with different amounts of metabolite standards in 2 groups of biologic samples (A and B). The goal was a study that resembles a typical metabolomics analysis. Here, we report our efforts and discuss challenges that create bottlenecks for the field. Finally, we discuss benchmarks that could be used by laboratories to compare their methodologies.

  7. DMS-MaPseq for genome-wide or targeted RNA structure probing in vivo.

    Science.gov (United States)

    Zubradt, Meghan; Gupta, Paromita; Persad, Sitara; Lambowitz, Alan M; Weissman, Jonathan S; Rouskin, Silvi

    2017-01-01

    Coupling of structure-specific in vivo chemical modification to next-generation sequencing is transforming RNA secondary structure studies in living cells. The dominant strategy for detecting in vivo chemical modifications uses reverse transcriptase truncation products, which introduce biases and necessitate population-average assessments of RNA structure. Here we present dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq), which encodes DMS modifications as mismatches using a thermostable group II intron reverse transcriptase. DMS-MaPseq yields a high signal-to-noise ratio, can report multiple structural features per molecule, and allows both genome-wide studies and focused in vivo investigations of even low-abundance RNAs. We apply DMS-MaPseq for the first analysis of RNA structure within an animal tissue and to identify a functional structure involved in noncanonical translation initiation. Additionally, we use DMS-MaPseq to compare the in vivo structure of pre-mRNAs with their mature isoforms. These applications illustrate DMS-MaPseq's capacity to dramatically expand in vivo analysis of RNA structure.

  8. DMS-MaPseq for genome-wide or targeted RNA structure probing in vivo

    Science.gov (United States)

    Zubradt, Meghan; Gupta, Paromita; Persad, Sitara; Lambowitz, Alan M.; Weissman, Jonathan S.; Rouskin, Silvi

    2017-01-01

    Coupling structure-specific in vivo chemical modification to next-generation sequencing is transforming RNA secondary structural studies in living cells. The dominant strategy for detecting in vivo chemical modifications uses reverse transcriptase truncation products, which introduces biases and necessitates population-average assessments of RNA structure. Here we present dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq), which encodes DMS modifications as mismatches using a thermostable group II intron reverse transcriptase (TGIRT). DMS-MaPseq yields a high signal-to-noise ratio, can report multiple structural features per molecule, and allows both genome-wide studies and focused in vivo investigations of even low abundance RNAs. We apply DMS-MaPseq for the first analysis of RNA structure within an animal tissue and to identify a functional structure involved in non-canonical translation initiation. Additionally, we use DMS-MaPseq to compare the in vivo structure of pre-mRNAs to their mature isoforms. These applications illustrate DMS-MaPseq’s capacity to dramatically expand in vivo analysis of RNA structure. PMID:27819661

  9. Can Untargeted Metabolomics Be Utilized in Drug Discovery/Development?

    Science.gov (United States)

    Caldwell, Gary W; Leo, Gregory C

    2017-01-01

    Untargeted metabolomics is a promising approach for reducing the significant attrition rate for discovering and developing drugs in the pharmaceutical industry. This review aims to highlight the practical decision-making value of untargeted metabolomics for the advancement of drug candidates in drug discovery/development including potentially identifying and validating novel therapeutic targets, creating alternative screening paradigms, facilitating the selection of specific and translational metabolite biomarkers, identifying metabolite signatures for the drug efficacy mechanism of action, and understanding potential drug-induced toxicity. The review provides an overview of the pharmaceutical process workflow to discover and develop new small molecule drugs followed by the metabolomics process workflow that is involved in conducting metabolomics studies. The pros and cons of the major components of the pharmaceutical and metabolomics workflows are reviewed and discussed. Finally, selected untargeted metabolomics literature examples, from primarily 2010 to 2016, are used to illustrate why, how, and where untargeted metabolomics can be integrated into the drug discovery/preclinical drug development process. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  10. Investigation on wide-band scattering of a 2-D target above 1-D randomly rough surface by FDTD method.

    Science.gov (United States)

    Li, Juan; Guo, Li-Xin; Jiao, Yong-Chang; Li, Ke

    2011-01-17

    Finite-difference time-domain (FDTD) algorithm with a pulse wave excitation is used to investigate the wide-band composite scattering from a two-dimensional(2-D) infinitely long target with arbitrary cross section located above a one-dimensional(1-D) randomly rough surface. The FDTD calculation is performed with a pulse wave incidence, and the 2-D representative time-domain scattered field in the far zone is obtained directly by extrapolating the currently calculated data on the output boundary. Then the 2-D wide-band scattering result is acquired by transforming the representative time-domain field to the frequency domain with a Fourier transform. Taking the composite scattering of an infinitely long cylinder above rough surface as an example, the wide-band response in the far zone by FDTD with the pulsed excitation is computed and it shows a good agreement with the numerical result by FDTD with the sinusoidal illumination. Finally, the normalized radar cross section (NRCS) from a 2-D target above 1-D rough surface versus the incident frequency, and the representative scattered fields in the far zone versus the time are analyzed in detail.

  11. The influence of different diets on metabolism and atherosclerosis processes-A porcine model: Blood serum, urine and tissues 1H NMR metabolomics targeted analysis.

    Directory of Open Access Journals (Sweden)

    Adam Zabek

    Full Text Available The global epidemic of cardiovascular diseases leads to increased morbidity and mortality caused mainly by myocardial infarction and stroke. Atherosclerosis is the major pathological process behind this epidemic. We designed a novel model of atherosclerosis in swine. Briefly, the first group (11 pigs received normal pig feed (balanced diet group-BDG for 12 months, the second group (9 pigs was fed a Western high-calorie diet (unbalanced diet group-UDG for 12 months, the third group (8 pigs received a Western type high-calorie diet for 9 months later replaced by a normal diet for 3 months (regression group-RG. Clinical measurements included zoometric data, arterial blood pressure, heart rate and ultrasonographic evaluation of femoral arteries. Then, the animals were sacrificed and the blood serum, urine and skeletal muscle tissue were collected and 1H NMR based metabolomics studies with the application of fingerprinting PLS-DA and univariate analysis were done. Our results have shown that the molecular disturbances might overlap with other diseases such as onset of diabetes, sleep apnea and other obesity accompanied diseases. Moreover, we revealed that once initiated, molecular changes did not return to homeostatic equilibrium, at least for the duration of this experiment.

  12. Better Targeting, Better Efficiency for Wide-scale Neuronal Transduction with the Synapsin Promoter and AAV-PHP.B

    Directory of Open Access Journals (Sweden)

    Kasey L Jackson

    2016-11-01

    Full Text Available Widespread genetic modification of cells in the central nervous system (CNS with a viral vector has become possible and increasingly more efficient. We previously applied an AAV9 vector with the cytomegalovirus/chicken beta-actin hybrid (CBA promoter and achieved wide-scale CNS transduction in neonatal and adult rats. However, this method transduces a variety of tissues in addition to the CNS. Thus we studied intravenous AAV9 gene transfer with a synapsin promoter to better target the neurons. We noted in systematic comparisons that the synapsin promoter drives lower level expression than does the CBA promoter. The engineered AAV-PHP.B serotype was compared with AAV9, and AAV-PHP.B did enhance the efficiency of expression. Combining the synapsin promoter with AAV-PHP.B could therefore be advantageous in terms of combining two refinements of targeting and efficiency. Wide-scale expression was used to model a disease with widespread pathology. Vectors encoding the amyotrophic lateral sclerosis (ALS-related protein TDP-43 with the synapsin promoter and AAV-PHP.B were used for efficient CNS-targeted TDP-43 expression. Intracerebroventricular injections were also explored to limit TDP-43 expression to the CNS. The neuron-selective promoter and the AAV-PHP.B enhanced gene transfer and ALS disease modeling in adult rats.

  13. Better Targeting, Better Efficiency for Wide-Scale Neuronal Transduction with the Synapsin Promoter and AAV-PHP.B.

    Science.gov (United States)

    Jackson, Kasey L; Dayton, Robert D; Deverman, Benjamin E; Klein, Ronald L

    2016-01-01

    Widespread genetic modification of cells in the central nervous system (CNS) with a viral vector has become possible and increasingly more efficient. We previously applied an AAV9 vector with the cytomegalovirus/chicken beta-actin (CBA) hybrid promoter and achieved wide-scale CNS transduction in neonatal and adult rats. However, this method transduces a variety of tissues in addition to the CNS. Thus we studied intravenous AAV9 gene transfer with a synapsin promoter to better target the neurons. We noted in systematic comparisons that the synapsin promoter drives lower level expression than does the CBA promoter. The engineered adeno-associated virus (AAV)-PHP.B serotype was compared with AAV9, and AAV-PHP.B did enhance the efficiency of expression. Combining the synapsin promoter with AAV-PHP.B could therefore be advantageous in terms of combining two refinements of targeting and efficiency. Wide-scale expression was used to model a disease with widespread pathology. Vectors encoding the amyotrophic lateral sclerosis (ALS)-related protein transactive response DNA-binding protein, 43 kDa (TDP-43) with the synapsin promoter and AAV-PHP.B were used for efficient CNS-targeted TDP-43 expression. Intracerebroventricular injections were also explored to limit TDP-43 expression to the CNS. The neuron-selective promoter and the AAV-PHP.B enhanced gene transfer and ALS disease modeling in adult rats.

  14. Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome.

    Science.gov (United States)

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2017-08-24

    Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

  15. Combined genome-wide linkage and targeted association analysis of head circumference in autism spectrum disorder families.

    Science.gov (United States)

    Woodbury-Smith, M; Bilder, D A; Morgan, J; Jerominski, L; Darlington, T; Dyer, T; Paterson, A D; Coon, H

    2017-01-01

    It has long been recognized that there is an association between enlarged head circumference (HC) and autism spectrum disorder (ASD), but the genetics of HC in ASD is not well understood. In order to investigate the genetic underpinning of HC in ASD, we undertook a genome-wide linkage study of HC followed by linkage signal targeted association among a sample of 67 extended pedigrees with ASD. HC measurements on members of 67 multiplex ASD extended pedigrees were used as a quantitative trait in a genome-wide linkage analysis. The Illumina 6K SNP linkage panel was used, and analyses were carried out using the SOLAR implemented variance components model. Loci identified in this way formed the target for subsequent association analysis using the Illumina OmniExpress chip and imputed genotypes. A modification of the qTDT was used as implemented in SOLAR. We identified a linkage signal spanning 6p21.31 to 6p22.2 (maximum LOD = 3.4). Although targeted association did not find evidence of association with any SNP overall, in one family with the strongest evidence of linkage, there was evidence for association (rs17586672, p = 1.72E-07). Although this region does not overlap with ASD linkage signals in these same samples, it has been associated with other psychiatric risk, including ADHD, developmental dyslexia, schizophrenia, specific language impairment, and juvenile bipolar disorder. The genome-wide significant linkage signal represents the first reported observation of a potential quantitative trait locus for HC in ASD and may be relevant in the context of complex multivariate risk likely leading to ASD.

  16. Circadian Metabolomics in Time and Space

    Directory of Open Access Journals (Sweden)

    Kenneth A. Dyar

    2017-07-01

    Full Text Available Circadian rhythms are widely known to govern human health and disease, but specific pathogenic mechanisms linking circadian disruption to metabolic diseases are just beginning to come to light. This is thanks in part to the development and application of various “omics”-based tools in biology and medicine. Current high-throughput technologies allow for the simultaneous monitoring of multiple dynamic cellular events over time, ranging from gene expression to metabolite abundance and sub-cellular localization. These fundamental temporal and spatial perspectives have allowed for a more comprehensive understanding of how various dynamic cellular events and biochemical processes are related in health and disease. With advances in technology, metabolomics has become a more routine “omics” approach for studying metabolism, and “circadian metabolomics” (i.e., studying the 24-h metabolome has recently been undertaken by several groups. To date, circadian metabolomes have been reported for human serum, saliva, breath, and urine, as well as tissues from several species under specific disease or mutagenesis conditions. Importantly, these studies have consistently revealed that 24-h rhythms are prevalent in almost every tissue and metabolic pathway. Furthermore, these circadian rhythms in tissue metabolism are ultimately linked to and directed by internal 24-h biological clocks. In this review, we will attempt to put these data-rich circadian metabolomics experiments into perspective to find out what they can tell us about metabolic health and disease, and what additional biomarker potential they may reveal.

  17. Metabolomics in the fight against malaria.

    Science.gov (United States)

    Salinas, Jorge L; Kissinger, Jessica C; Jones, Dean P; Galinski, Mary R

    2014-08-01

    Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host's metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC), a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP) malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

  18. Metabolomics in the fight against malaria

    Directory of Open Access Journals (Sweden)

    Jorge L Salinas

    2014-08-01

    Full Text Available Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC, a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

  19. Selectivity issues in targeted metabolomics: Separation of phosphorylated carbohydrate isomers by mixed-mode hydrophilic interaction/weak anion exchange chromatography.

    Science.gov (United States)

    Hinterwirth, Helmut; Lämmerhofer, Michael; Preinerstorfer, Beatrix; Gargano, Andrea; Reischl, Roland; Bicker, Wolfgang; Trapp, Oliver; Brecker, Lothar; Lindner, Wolfgang

    2010-11-01

    Phosphorylated carbohydrates are important intracellular metabolites and thus of prime interest in metabolomics research. Complications in their analysis arise from the existence of structural isomers that do have similar fragmentation patterns in MS/MS and are hard to resolve chromatographically. Herein, we present selective methods for the liquid chromatographic separation of sugar phosphates, such as hexose and pentose phosphates, 2- and 3-phosphoglycerate, dihydroxyacetone phosphate and glyceraldehyde 3-phosphate, as well as glucosamine 1- and 6-phosphate utilizing mixed-mode chromatography with reversed-phase/weak anion-exchangers and a charged aerosol detector. The best results were obtained when the reversed-phase/weak anion-exchanger column was operated under hydrophilic interaction liquid chromatography elution conditions. The effects of various chromatographic parameters were examined and are discussed on the basis of a simple stoichiometric displacement model for explaining ion-exchange processes. Employed acidic conditions have led to the complete separation of α- and β-anomers of glucose 6-phosphate at low temperature. The anomers coeluted in a single peak at elevated temperatures (>40°C) (peak coalescence), while at intermediate temperatures on-column interconversion with a plateau in-between resolved anomer peaks was observed with apparent reaction rate constants between 0.1 and 27.8×10(-4) s(-1). Dynamic HPLC under specified conditions enabled to investigate mutarotation of phosphorylated carbohydrates, their interconversion kinetics, and energy barriers for interconversion. A complex mixture of six hexose phosphate structural isomers could be resolved almost completely.

  20. SWAPDT: A method for Short-time Withering Assessment of Probability for Drought Tolerance in Camellia sinensis validated by targeted metabolomics.

    Science.gov (United States)

    Nyarukowa, Christopher; Koech, Robert; Loots, Theodor; Apostolides, Zeno

    2016-07-01

    Climate change is causing droughts affecting crop production on a global scale. Classical breeding and selection strategies for drought-tolerant cultivars will help prevent crop losses. Plant breeders, for all crops, need a simple and reliable method to identify drought-tolerant cultivars, but such a method is missing. Plant metabolism is often disrupted by abiotic stress conditions. To survive drought, plants reconfigure their metabolic pathways. Studies have documented the importance of metabolic regulation, i.e. osmolyte accumulation such as polyols and sugars (mannitol, sorbitol); amino acids (proline) during drought. This study identified and quantified metabolites in drought tolerant and drought susceptible Camellia sinensis cultivars under wet and drought stress conditions. For analyses, GC-MS and LC-MS were employed for metabolomics analysis.%RWC results show how the two drought tolerant and two drought susceptible cultivars differed significantly (p≤0.05) from one another; the drought susceptible exhibited rapid water loss compared to the drought tolerant. There was a significant variation (p<0.05) in metabolite content (amino acid, sugars) between drought tolerant and drought susceptible tea cultivars after short-time withering conditions. These metabolite changes were similar to those seen in other plant species under drought conditions, thus validating this method. The Short-time Withering Assessment of Probability for Drought Tolerance (SWAPDT) method presented here provides an easy method to identify drought tolerant tea cultivars that will mitigate the effects of drought due to climate change on crop losses. Copyright © 2016. Published by Elsevier GmbH.

  1. Single-Cell Metabolomics.

    Science.gov (United States)

    Emara, Samy; Amer, Sara; Ali, Ahmed; Abouleila, Yasmine; Oga, April; Masujima, Tsutomu

    2017-01-01

    The dynamics of a cell is always changing. Cells move, divide, communicate, adapt, and are always reacting to their surroundings non-synchronously. Currently, single-cell metabolomics has become the leading field in understanding the phenotypical variations between them, but sample volumes, low analyte concentrations, and validating gentle sample techniques have proven great barriers toward achieving accurate and complete metabolomics profiling. Certainly, advanced technologies such as nanodevices and microfluidic arrays are making great progress, and analytical techniques, such as matrix-assisted laser desorption ionization (MALDI), are gaining popularity with high-throughput methodology. Nevertheless, live single-cell mass spectrometry (LCSMS) values the sample quality and precision, turning once theoretical speculation into present-day applications in a variety of fields, including those of medicine, pharmaceutical, and agricultural industries. While there is still room for much improvement, it is clear that the metabolomics field is progressing toward analysis and discoveries at the single-cell level.

  2. Metabolomics in Newborns.

    Science.gov (United States)

    Noto, Antonio; Fanos, Vassilios; Dessì, Angelica

    2016-01-01

    Metabolomics is the quantitative analysis of a large number of low molecular weight metabolites that are intermediate or final products of all the metabolic pathways in a living organism. Any metabolic profiles detectable in a human biological fluid are caused by the interaction between gene expression and the environment. The metabolomics approach offers the possibility to identify variations in metabolite profile that can be used to discriminate disease. This is particularly important for neonatal and pediatric studies especially for severe ill patient diagnosis and early identification. This property is of a great clinical importance in view of the newer definitions of health and disease. This review emphasizes the workflow of a typical metabolomics study and summarizes the latest results obtained in neonatal studies with particular interest in prematurity, intrauterine growth retardation, inborn errors of metabolism, perinatal asphyxia, sepsis, necrotizing enterocolitis, kidney disease, bronchopulmonary dysplasia, and cardiac malformation and dysfunction. © 2016 Elsevier Inc. All rights reserved.

  3. Establishing Substantial Equivalence: Metabolomics

    Science.gov (United States)

    Beale, Michael H.; Ward, Jane L.; Baker, John M.

    Modern ‘metabolomic’ methods allow us to compare levels of many structurally diverse compounds in an automated fashion across a large number of samples. This technology is ideally suited to screening of populations of plants, including trials where the aim is the determination of unintended effects introduced by GM. A number of metabolomic methods have been devised for the determination of substantial equivalence. We have developed a methodology, using [1H]-NMR fingerprinting, for metabolomic screening of plants and have applied it to the study of substantial equivalence of field-grown GM wheat. We describe here the principles and detail of that protocol as applied to the analysis of flour generated from field plots of wheat. Particular emphasis is given to the downstream data processing and comparison of spectra by multivariate analysis, from which conclusions regarding metabolome changes due to the GM can be assessed against the background of natural variation due to environment.

  4. Genome-wide analysis of murine renal distal convoluted tubular cells for the target genes of mineralocorticoid receptor

    Energy Technology Data Exchange (ETDEWEB)

    Ueda, Kohei [Department of Nephrology and Endocrinology, The University of Tokyo, Tokyo (Japan); Fujiki, Katsunori; Shirahige, Katsuhiko [Research Center for Epigenetic Disease, Institute of Molecular and Cellular Biosciences, The University of Tokyo, Tokyo (Japan); Gomez-Sanchez, Celso E. [Endocrine Section, G.V. (Sonny) Montgomery VA Medical Center, MS (United States); Endocrinology, University of Mississippi Medical Center, MS (United States); Fujita, Toshiro [Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo (Japan); Nangaku, Masaomi [Department of Nephrology and Endocrinology, The University of Tokyo, Tokyo (Japan); Nagase, Miki, E-mail: mnagase-tky@umin.ac.jp [Department of Nephrology and Endocrinology, The University of Tokyo, Tokyo (Japan); Department of Anatomy and Life Structure, School of Medicine Juntendo University, Tokyo (Japan)

    2014-02-28

    Highlights: • We define a target gene of MR as that with MR-binding to the adjacent region of DNA. • We use ChIP-seq analysis in combination with microarray. • We, for the first time, explore the genome-wide binding profile of MR. • We reveal 5 genes as the direct target genes of MR in the renal epithelial cell-line. - Abstract: Background and objective: Mineralocorticoid receptor (MR) is a member of nuclear receptor family proteins and contributes to fluid homeostasis in the kidney. Although aldosterone-MR pathway induces several gene expressions in the kidney, it is often unclear whether the gene expressions are accompanied by direct regulations of MR through its binding to the regulatory region of each gene. The purpose of this study is to identify the direct target genes of MR in a murine distal convoluted tubular epithelial cell-line (mDCT). Methods: We analyzed the DNA samples of mDCT cells overexpressing 3xFLAG-hMR after treatment with 10{sup −7} M aldosterone for 1 h by chromatin immunoprecipitation with deep-sequence (ChIP-seq) and mRNA of the cell-line with treatment of 10{sup −7} M aldosterone for 3 h by microarray. Results: 3xFLAG-hMR overexpressed in mDCT cells accumulated in the nucleus in response to 10{sup −9} M aldosterone. Twenty-five genes were indicated as the candidate target genes of MR by ChIP-seq and microarray analyses. Five genes, Sgk1, Fkbp5, Rasl12, Tns1 and Tsc22d3 (Gilz), were validated as the direct target genes of MR by quantitative RT-qPCR and ChIP-qPCR. MR binding regions adjacent to Ctgf and Serpine1 were also validated. Conclusions: We, for the first time, captured the genome-wide distribution of MR in mDCT cells and, furthermore, identified five MR target genes in the cell-line. These results will contribute to further studies on the mechanisms of kidney diseases.

  5. A Review of Applications of Metabolomics in Cancer

    Directory of Open Access Journals (Sweden)

    Richard D. Beger

    2013-07-01

    Full Text Available Cancer is a devastating disease that alters the metabolism of a cell and the surrounding milieu. Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids. The recent advances in metabolomics technologies have enabled a deeper investigation into the metabolism of cancer and a better understanding of how cancer cells use glycolysis, known as the “Warburg effect,” advantageously to produce the amino acids, nucleotides and lipids necessary for tumor proliferation and vascularization. Currently, metabolomics research is being used to discover diagnostic cancer biomarkers in the clinic, to better understand its complex heterogeneous nature, to discover pathways involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide clues to personalized cancer treatments by providing useful information to the clinician about the cancer patient’s response to medical interventions.

  6. Metabolomics Toward Biomarker Discovery.

    Science.gov (United States)

    Yin, Peiyuan; Xu, Guowang

    2017-01-01

    Metabolomics has been used as practical tool in the discovery of novel biomarkers in a broad area in the clinic. The analytical platforms including nuclear magnetic resonance (NMR) and mass spectrometry (MS) can cover thousands of metabolites. With the help of multivariate data analysis, many potential biomarkers can be defined in the studies. Since metabolites stand at the end point of metabolism, it remains difficult to find novel biomarkers with good diagnostic or prognostic performance. In this chapter, we will introduce a general protocol for biomarker discovery within the scope of metabolomics using MS.

  7. metaMS: An open-source pipeline for GC–MS-based untargeted metabolomics

    NARCIS (Netherlands)

    Wehrens, H.R.M.J.; Weingart, G.; Mattivi, F.

    2014-01-01

    Untargeted metabolomics are rapidly becoming an important tool for studying complex biological samples. Gas chromatography–mass spectrometry (GC–MS) is the most widely used analytical technology for metabolomic analysis of compounds that are volatile or can be chemically derivatised into volatile

  8. Enhancing metabolomics research through data mining.

    Science.gov (United States)

    Martínez-Arranz, Ibon; Mayo, Rebeca; Pérez-Cormenzana, Miriam; Mincholé, Itziar; Salazar, Lorena; Alonso, Cristina; Mato, José M

    2015-09-08

    Metabolomics research, like other disciplines utilizing high-throughput technologies, generates a large amount of data for every sample. Although handling this data is a challenge and one of the biggest bottlenecks of the metabolomics workflow, it is also the clue to accomplish valuable results. This work has been designed to supply methodological data mining guidelines, describing systematically the steps to be followed in metabolomics data exploration. Instrumental raw data refinement in the pre-processing step and assessment of the statistical assumptions in pre-treatment directly affect the results of subsequent univariate and multivariate analyses. A study of aging in a healthy population was selected to represent this data mining process. Multivariate analysis of variance and linear regression methods were used to analyze the metabolic changes underlying aging. Selection of both multivariate methods aims to illustrate the treatment of age from two rather different perspectives, as a categorical variable and a continuous variable. Metabolomics is a discipline involving the analysis of a large amount of data to gather relevant information. Researchers in this field have to overcome the challenges of complex data processing and statistical analysis issues. A wide range of tasks has to be executed, from the minimization of batch-to-batch/systematic variations in pre-processing, to the application of common data analysis techniques relying on statistical assumptions. In this work, a real-data metabolic profiling research on aging was used to illustrate the proposed workflow and suggest a set of guidelines for analyzing metabolomics data. This article is part of a Special Issue entitled: HUPO 2014. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

    Science.gov (United States)

    Alonso, Cristina; Fernández-Ramos, David; Varela-Rey, Marta; Martínez-Arranz, Ibon; Navasa, Nicolás; Van Liempd, Sebastiaan M; Lavín Trueba, José L; Mayo, Rebeca; Ilisso, Concetta P; de Juan, Virginia G; Iruarrizaga-Lejarreta, Marta; delaCruz-Villar, Laura; Mincholé, Itziar; Robinson, Aaron; Crespo, Javier; Martín-Duce, Antonio; Romero-Gómez, Manuel; Sann, Holger; Platon, Julian; Van Eyk, Jennifer; Aspichueta, Patricia; Noureddin, Mazen; Falcón-Pérez, Juan M; Anguita, Juan; Aransay, Ana M; Martínez-Chantar, María Luz; Lu, Shelly C; Mato, José M

    2017-05-01

    Nonalcoholic fatty liver disease (NAFLD) is a consequence of defects in diverse metabolic pathways that involve hepatic accumulation of triglycerides. Features of these aberrations might determine whether NAFLD progresses to nonalcoholic steatohepatitis (NASH). We investigated whether the diverse defects observed in patients with NAFLD are caused by different NAFLD subtypes with specific serum metabolomic profiles, and whether these can distinguish patients with NASH from patients with simple steatosis. We collected liver and serum from methionine adenosyltransferase 1a knockout (MAT1A-KO) mice, which have chronically low levels of hepatic S-adenosylmethionine (SAMe) and spontaneously develop steatohepatitis, as well as C57Bl/6 mice (controls); the metabolomes of all samples were determined. We also analyzed serum metabolomes of 535 patients with biopsy-proven NAFLD (353 with simple steatosis and 182 with NASH) and compared them with serum metabolomes of mice. MAT1A-KO mice were also given SAMe (30 mg/kg/day for 8 weeks); liver samples were collected and analyzed histologically for steatohepatitis. Livers of MAT1A-KO mice were characterized by high levels of triglycerides, diglycerides, fatty acids, ceramides, and oxidized fatty acids, as well as low levels of SAMe and downstream metabolites. There was a correlation between liver and serum metabolomes. We identified a serum metabolomic signature associated with MAT1A-KO mice that also was present in 49% of the patients; based on this signature, we identified 2 NAFLD subtypes. We identified specific panels of markers that could distinguish patients with NASH from patients with simple steatosis for each subtype of NAFLD. Administration of SAMe reduced features of steatohepatitis in MAT1A-KO mice. In an analysis of serum metabolomes of patients with NAFLD and MAT1A-KO mice with steatohepatitis, we identified 2 major subtypes of NAFLD and markers that differentiate steatosis from NASH in each subtype. These might be

  10. Impact of anesthesia and euthanasia on metabolomics of mammalian tissues: studies in a C57BL/6J mouse model.

    Directory of Open Access Journals (Sweden)

    Katherine A Overmyer

    Full Text Available A critical application of metabolomics is the evaluation of tissues, which are often the primary sites of metabolic dysregulation in disease. Laboratory rodents have been widely used for metabolomics studies involving tissues due to their facile handing, genetic manipulability and similarity to most aspects of human metabolism. However, the necessary step of administration of anesthesia in preparation for tissue sampling is not often given careful consideration, in spite of its potential for causing alterations in the metabolome. We examined, for the first time using untargeted and targeted metabolomics, the effect of several commonly used methods of anesthesia and euthanasia for collection of skeletal muscle, liver, heart, adipose and serum of C57BL/6J mice. The data revealed dramatic, tissue-specific impacts of tissue collection strategy. Among many differences observed, post-euthanasia samples showed elevated levels of glucose 6-phosphate and other glycolytic intermediates in skeletal muscle. In heart and liver, multiple nucleotide and purine degradation metabolites accumulated in tissues of euthanized compared to anesthetized animals. Adipose tissue was comparatively less affected by collection strategy, although accumulation of lactate and succinate in euthanized animals was observed in all tissues. Among methods of tissue collection performed pre-euthanasia, ketamine showed more variability compared to isoflurane and pentobarbital. Isoflurane induced elevated liver aspartate but allowed more rapid initiation of tissue collection. Based on these findings, we present a more optimal collection strategy mammalian tissues and recommend that rodent tissues intended for metabolomics studies be collected under anesthesia rather than post-euthanasia.

  11. Advances in Ginkgo biloba research: Genomics and metabolomics ...

    African Journals Online (AJOL)

    The maiden hair tree, Ginkgo biloba is very much resistant to a wide spectrum of biotic and abiotic stress conditions. It hardly seems to be attacked by any herbivore or microbe. In spite of its strong resistant nature to wide stress conditions, only little research has been carried out at genomics and metabolomics level to ...

  12. Plant Metabolomics in a nutshell: Potential and Future Challenges

    NARCIS (Netherlands)

    Hall, R.D.

    2011-01-01

    In just 10 years, plantmetabolomics has been transformed from a purely theoretical concept into a highly valued and widely exploited technology. Moving on from the many and wide-ranging hopes, enthused upon in a multitude of early reviews, metabolomics for plant research has already proved itself

  13. Single cell metabolomics

    NARCIS (Netherlands)

    Heinemann, Matthias; Zenobi, Renato

    Recent discoveries suggest that cells of a clonal population often display multiple metabolic phenotypes at the same time. Motivated by the success of mass spectrometry (MS) in the investigation of population-level metabolomics, the analytical community has initiated efforts towards MS-based single

  14. Non-Targeted Metabolomics Analysis of the Effects of Tyrosine Kinase Inhibitors Sunitinib and Erlotinib on Heart, Muscle, Liver and Serum Metabolism In Vivo

    OpenAIRE

    Jensen, Brian C; Parry, Traci L; Wei Huang; Amro Ilaiwy; Bain, James R; Muehlbauer, Michael J.; O’Neal, Sara K.; Cam Patterson; Johnson, Gary L; Monte S. Willis

    2017-01-01

    Background: More than 90 tyrosine kinases have been implicated in the pathogenesis of malignant transformation and tumor angiogenesis. Tyrosine kinase inhibitors (TKIs) have emerged as effective therapies in treating cancer by exploiting this kinase dependency. The TKI erlotinib targets the epidermal growth factor receptor (EGFR), whereas sunitinib targets primarily vascular endothelial growth factor receptor (VEGFR) and platelet-derived growth factor receptor (PDGFR).TKIs that impact the fun...

  15. K-Targeted Metabolomic Analysis Extends Chemical Subtraction to DESIGNER Extracts: Selective Depletion of Extracts of Hops (Humulus lupulus)⊥

    Science.gov (United States)

    2015-01-01

    This study introduces a flexible and compound targeted approach to Deplete and Enrich Select Ingredients to Generate Normalized Extract Resources, generating DESIGNER extracts, by means of chemical subtraction or augmentation of metabolites. Targeting metabolites based on their liquid–liquid partition coefficients (K values), K targeting uses countercurrent separation methodology to remove single or multiple compounds from a chemically complex mixture, according to the following equation: DESIGNER extract = total extract ± target compound(s). Expanding the scope of the recently reported depletion of extracts by immunoaffinity or solid phase liquid chromatography, the present approach allows a more flexible, single- or multi-targeted removal of constituents from complex extracts such as botanicals. Chemical subtraction enables both chemical and biological characterization, including detection of synergism/antagonism by both the subtracted targets and the remaining metabolite mixture, as well as definition of the residual complexity of all fractions. The feasibility of the DESIGNER concept is shown by K-targeted subtraction of four bioactive prenylated phenols, isoxanthohumol (1), 8-prenylnaringenin (2), 6-prenylnaringenin (3), and xanthohumol (4), from a standardized hops (Humulus lupulus L.) extract using specific solvent systems. Conversely, adding K-targeted isolates allows enrichment of the original extract and hence provides an augmented DESIGNER material. Multiple countercurrent separation steps were used to purify each of the four compounds, and four DESIGNER extracts with varying depletions were prepared. The DESIGNER approach innovates the characterization of chemically complex extracts through integration of enabling technologies such as countercurrent separation, K-by-bioactivity, the residual complexity concepts, as well as quantitative analysis by 1H NMR, LC-MS, and HiFSA-based NMR fingerprinting. PMID:25437744

  16. Metabolomics through the lens of precision cardiovascular medicine.

    Science.gov (United States)

    Lam, Sin Man; Wang, Yuan; Li, Bowen; Du, Jie; Shui, Guanghou

    2017-03-20

    Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

  17. Wide-field retinal optical coherence tomography with wavefront sensorless adaptive optics for enhanced imaging of targeted regions.

    Science.gov (United States)

    Polans, James; Keller, Brenton; Carrasco-Zevallos, Oscar M; LaRocca, Francesco; Cole, Elijah; Whitson, Heather E; Lad, Eleonora M; Farsiu, Sina; Izatt, Joseph A

    2017-01-01

    The peripheral retina of the human eye offers a unique opportunity for assessment and monitoring of ocular diseases. We have developed a novel wide-field (>70°) optical coherence tomography system (WF-OCT) equipped with wavefront sensorless adaptive optics (WSAO) for enhancing the visualization of smaller (23°) retina. We demonstrated the ability of our WF-OCT system to acquire non wavefront-corrected wide-field images rapidly, which could then be used to locate regions of interest, zoom into targeted features, and visualize the same region at different time points. A pilot clinical study was conducted on seven healthy volunteers and two subjects with prodromal Alzheimer's disease which illustrated the capability to image Drusen-like pathologies as far as 32.5° from the fovea in un-averaged volume scans. This work suggests that the proposed combination of WF-OCT and WSAO may find applications in the diagnosis and treatment of ocular, and potentially neurodegenerative, diseases of the peripheral retina, including diabetes and Alzheimer's disease.

  18. Stable isotope-resolved metabolomics and applications for drug development

    Science.gov (United States)

    Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

    2012-01-01

    Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

  19. Genome-Wide Identification of the Target Genes of AP2-O, a Plasmodium AP2-Family Transcription Factor.

    Directory of Open Access Journals (Sweden)

    Izumi Kaneko

    2015-05-01

    Full Text Available Stage-specific transcription is a fundamental biological process in the life cycle of the Plasmodium parasite. Proteins containing the AP2 DNA-binding domain are responsible for stage-specific transcriptional regulation and belong to the only known family of transcription factors in Plasmodium parasites. Comprehensive identification of their target genes will advance our understanding of the molecular basis of stage-specific transcriptional regulation and stage-specific parasite development. AP2-O is an AP2 family transcription factor that is expressed in the mosquito midgut-invading stage, called the ookinete, and is essential for normal morphogenesis of this stage. In this study, we identified the genome-wide target genes of AP2-O by chromatin immunoprecipitation-sequencing and elucidate how this AP2 family transcription factor contributes to the formation of this motile stage. The analysis revealed that AP2-O binds specifically to the upstream genomic regions of more than 500 genes, suggesting that approximately 10% of the parasite genome is directly regulated by AP2-O. These genes are involved in distinct biological processes such as morphogenesis, locomotion, midgut penetration, protection against mosquito immunity and preparation for subsequent oocyst development. This direct and global regulation by AP2-O provides a model for gene regulation in Plasmodium parasites and may explain how these parasites manage to control their complex life cycle using a small number of sequence-specific AP2 transcription factors.

  20. Genome-Wide Identification of the Target Genes of AP2-O, a Plasmodium AP2-Family Transcription Factor.

    Science.gov (United States)

    Kaneko, Izumi; Iwanaga, Shiroh; Kato, Tomomi; Kobayashi, Issei; Yuda, Masao

    2015-05-01

    Stage-specific transcription is a fundamental biological process in the life cycle of the Plasmodium parasite. Proteins containing the AP2 DNA-binding domain are responsible for stage-specific transcriptional regulation and belong to the only known family of transcription factors in Plasmodium parasites. Comprehensive identification of their target genes will advance our understanding of the molecular basis of stage-specific transcriptional regulation and stage-specific parasite development. AP2-O is an AP2 family transcription factor that is expressed in the mosquito midgut-invading stage, called the ookinete, and is essential for normal morphogenesis of this stage. In this study, we identified the genome-wide target genes of AP2-O by chromatin immunoprecipitation-sequencing and elucidate how this AP2 family transcription factor contributes to the formation of this motile stage. The analysis revealed that AP2-O binds specifically to the upstream genomic regions of more than 500 genes, suggesting that approximately 10% of the parasite genome is directly regulated by AP2-O. These genes are involved in distinct biological processes such as morphogenesis, locomotion, midgut penetration, protection against mosquito immunity and preparation for subsequent oocyst development. This direct and global regulation by AP2-O provides a model for gene regulation in Plasmodium parasites and may explain how these parasites manage to control their complex life cycle using a small number of sequence-specific AP2 transcription factors.

  1. Genome-wide transcriptional profiling of Botrytis cinerea genes targeting plant cell walls during infections of different hosts

    Science.gov (United States)

    Blanco-Ulate, Barbara; Morales-Cruz, Abraham; Amrine, Katherine C. H.; Labavitch, John M.; Powell, Ann L. T.; Cantu, Dario

    2014-01-01

    Cell walls are barriers that impair colonization of host tissues, but also are important reservoirs of energy-rich sugars. Growing hyphae of necrotrophic fungal pathogens, such as Botrytis cinerea (Botrytis, henceforth), secrete enzymes that disassemble cell wall polysaccharides. In this work we describe the annotation of 275 putative secreted Carbohydrate-Active enZymes (CAZymes) identified in the Botrytis B05.10 genome. Using RNAseq we determined which Botrytis CAZymes were expressed during infections of lettuce leaves, ripe tomato fruit, and grape berries. On the three hosts, Botrytis expressed a common group of 229 potentially secreted CAZymes, including 28 pectin backbone-modifying enzymes, 21 hemicellulose-modifying proteins, 18 enzymes that might target pectin and hemicellulose side-branches, and 16 enzymes predicted to degrade cellulose. The diversity of the Botrytis CAZymes may be partly responsible for its wide host range. Thirty-six candidate CAZymes with secretion signals were found exclusively when Botrytis interacted with ripe tomato fruit and grape berries. Pectin polysaccharides are notably abundant in grape and tomato cell walls, but lettuce leaf walls have less pectin and are richer in hemicelluloses and cellulose. The results of this study not only suggest that Botrytis targets similar wall polysaccharide networks on fruit and leaves, but also that it may selectively attack host wall polysaccharide substrates depending on the host tissue. PMID:25232357

  2. Genome-wide identification of polycomb target genes reveals a functional association of Pho with Scm in Bombyx mori.

    Science.gov (United States)

    Li, Zhiqing; Cheng, Daojun; Mon, Hiroaki; Tatsuke, Tsuneyuki; Zhu, Li; Xu, Jian; Lee, Jae Man; Xia, Qingyou; Kusakabe, Takahiro

    2012-01-01

    Polycomb group (PcG) proteins are evolutionarily conserved chromatin modifiers and act together in three multimeric complexes, Polycomb repressive complex 1 (PRC1), Polycomb repressive complex 2 (PRC2), and Pleiohomeotic repressive complex (PhoRC), to repress transcription of the target genes. Here, we identified Polycomb target genes in Bombyx mori with holocentric centromere using genome-wide expression screening based on the knockdown of BmSCE, BmESC, BmPHO, or BmSCM gene, which represent the distinct complexes. As a result, the expressions of 29 genes were up-regulated after knocking down 4 PcG genes. Particularly, there is a significant overlap between targets of BmPho (331 out of 524) and BmScm (331 out of 532), and among these, 190 genes function as regulator factors playing important roles in development. We also found that BmPho, as well as BmScm, can interact with other Polycomb components examined in this study. Further detailed analysis revealed that the C-terminus of BmPho containing zinc finger domain is involved in the interaction between BmPho and BmScm. Moreover, the zinc finger domain in BmPho contributes to its inhibitory function and ectopic overexpression of BmScm is able to promote transcriptional repression by Gal4-Pho fusions including BmScm-interacting domain. Loss of BmPho expression causes relocalization of BmScm into the cytoplasm. Collectively, we provide evidence of a functional link between BmPho and BmScm, and propose two Polycomb-related repression mechanisms requiring only BmPho associated with BmScm or a whole set of PcG complexes.

  3. A resource for characterizing genome-wide binding and putative target genes of transcription factors expressed during secondary growth and wood formation in Populus

    Science.gov (United States)

    Lijun Liu; Trevor Ramsay; Matthew S. Zinkgraf; David Sundell; Nathaniel Robert Street; Vladimir Filkov; Andrew Groover

    2015-01-01

    Identifying transcription factor target genes is essential for modeling the transcriptional networks underlying developmental processes. Here we report a chromatin immunoprecipitation sequencing (ChIP-seq) resource consisting of genome-wide binding regions and associated putative target genes for four Populus homeodomain transcription factors...

  4. Metabolomics in transfusion medicine.

    Science.gov (United States)

    Nemkov, Travis; Hansen, Kirk C; Dumont, Larry J; D'Alessandro, Angelo

    2016-04-01

    Biochemical investigations on the regulatory mechanisms of red blood cell (RBC) and platelet (PLT) metabolism have fostered a century of advances in the field of transfusion medicine. Owing to these advances, storage of RBCs and PLT concentrates has become a lifesaving practice in clinical and military settings. There, however, remains room for improvement, especially with regard to the introduction of novel storage and/or rejuvenation solutions, alternative cell processing strategies (e.g., pathogen inactivation technologies), and quality testing (e.g., evaluation of novel containers with alternative plasticizers). Recent advancements in mass spectrometry-based metabolomics and systems biology, the bioinformatics integration of omics data, promise to speed up the design and testing of innovative storage strategies developed to improve the quality, safety, and effectiveness of blood products. Here we review the currently available metabolomics technologies and briefly describe the routine workflow for transfusion medicine-relevant studies. The goal is to provide transfusion medicine experts with adequate tools to navigate through the otherwise overwhelming amount of metabolomics data burgeoning in the field during the past few years. Descriptive metabolomics data have represented the first step omics researchers have taken into the field of transfusion medicine. However, to up the ante, clinical and omics experts will need to merge their expertise to investigate correlative and mechanistic relationships among metabolic variables and transfusion-relevant variables, such as 24-hour in vivo recovery for transfused RBCs. Integration with systems biology models will potentially allow for in silico prediction of metabolic phenotypes, thus streamlining the design and testing of alternative storage strategies and/or solutions. © 2015 AABB.

  5. Microbial metabolomics : Toward a platform with full metabolome coverage

    NARCIS (Netherlands)

    Werf, M.J.v.d.; Overkamp, K.M.; Muilwijk, B.; Coulier, L.; Hankemeier, T.

    2007-01-01

    Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial

  6. Diagnosis of adenylosuccinate lyase deficiency by metabolomic profiling in plasma reveals a phenotypic spectrum

    Directory of Open Access Journals (Sweden)

    Taraka R. Donti

    2016-09-01

    Full Text Available Adenylosuccinate lyase (ADSL deficiency is a rare autosomal recessive neurometabolic disorder that presents with a broad-spectrum of neurological and physiological symptoms. The ADSL gene produces an enzyme with binary molecular roles in de novo purine synthesis and purine nucleotide recycling. The biochemical phenotype of ADSL deficiency, accumulation of SAICAr and succinyladenosine (S-Ado in biofluids of affected individuals, serves as the traditional target for diagnosis with targeted quantitative urine purine analysis employed as the predominate method of detection. In this study, we report the diagnosis of ADSL deficiency using an alternative method, untargeted metabolomic profiling, an analytical scheme capable of generating semi-quantitative z-score values for over 1000 unique compounds in a single analysis of a specimen. Using this method to analyze plasma, we diagnosed ADSL deficiency in four patients and confirmed these findings with targeted quantitative biochemical analysis and molecular genetic testing. ADSL deficiency is part of a large a group of neurometabolic disorders, with a wide range of severity and sharing a broad differential diagnosis. This phenotypic similarity among these many inborn errors of metabolism (IEMs has classically stood as a hurdle in their initial diagnosis and subsequent treatment. The findings presented here demonstrate the clinical utility of metabolomic profiling in the diagnosis of ADSL deficiency and highlights the potential of this technology in the diagnostic evaluation of individuals with neurologic phenotypes.

  7. Development of Chemical Isotope Labeling LC-MS for Milk Metabolomics: Comprehensive and Quantitative Profiling of the Amine/Phenol Submetabolome.

    Science.gov (United States)

    Mung, Dorothea; Li, Liang

    2017-04-18

    Milk is a complex sample containing a variety of proteins, lipids, and metabolites. Studying the milk metabolome represents an important application of metabolomics in the general area of nutritional research. However, comprehensive and quantitative analysis of milk metabolites is a challenging task due to the wide range of variations in chemical/physical properties and concentrations of these metabolites. We report an analytical workflow for in-depth profiling of the milk metabolome based on chemical isotope labeling (CIL) and liquid chromatography mass spectrometry (LC-MS) with a focus of using dansylation labeling to target the amine/phenol submetabolome. An optimal sample preparation method, including the use of methanol at a 3:1 ratio of solvent to milk for protein precipitation and dichloromethane for lipid removal, was developed to detect and quantify as many metabolites as possible. This workflow was found to be generally applicable to profile milk metabolomes of different species (cow, goat, and human) and types. Results from experimental replicate analysis (n = 5) of 1:1, 2:1, and 1:2 (12)C-/(13)C-labeled cow milk samples showed that 95.7%, 94.3%, and 93.2% of peak pairs, respectively, had ratio values within ±50% accuracy range and 90.7%, 92.6%, and 90.8% peak pairs had RSD values of less than 20%. In the metabolomic analysis of 36 samples from different categories of cow milk (brands, batches, and fat percentages) with experimental triplicates, a total of 7104 peak pairs or metabolites could be detected with an average of 4573 ± 505 (n = 108) pairs detected per LC-MS run. Among them, 3820 peak pairs were commonly detected in over 80% of the samples with 70 metabolites positively identified by mass and retention time matches to the dansyl standard library and 2988 pairs with their masses matched to the human metabolome libraries. This unprecedentedly high coverage of the amine/phenol submetabolome illustrates the complexity of the milk metabolome

  8. Metabolomics technologies and metabolite identification

    NARCIS (Netherlands)

    Moco, S.I.A.; Bino, R.J.; Vos, de C.H.; Vervoort, J.J.M.

    2007-01-01

    Metabolomics studies rely on the analysis of the multitude of small molecules (metabolites) present in a biological system. Most commonly, metabolomics is heavily supported by mass spectrometry (MS) and nuclear magnetic resonance (NMR) as parallel technologies that provide an overview of the

  9. Systems Metabolomics for Prediction of Metabolic Syndrome.

    Science.gov (United States)

    Pujos-Guillot, Estelle; Brandolini, Marion; Pétéra, Mélanie; Grissa, Dhouha; Joly, Charlotte; Lyan, Bernard; Herquelot, Éléonore; Czernichow, Sébastien; Zins, Marie; Goldberg, Marcel; Comte, Blandine

    2017-06-02

    The evolution of human health is a continuum of transitions, involving multifaceted processes at multiple levels, and there is an urgent need for integrative biomarkers that can characterize and predict progression toward disease development. The objective of this work was to perform a systems metabolomics approach to predict metabolic syndrome (MetS) development. A case-control design was used within the French occupational GAZEL cohort (n = 112 males: discovery study; n = 94: replication/validation study). Our integrative strategy was to combine untargeted metabolomics with clinical, sociodemographic, and food habit parameters to describe early phenotypes and build multidimensional predictive models. Different models were built from the discriminant variables, and prediction performances were optimized either when reducing the number of metabolites used or when keeping the associated signature. We illustrated that a selected reduced metabolic profile was able to reveal subtle phenotypic differences 5 years before MetS occurrence. Moreover, resulting metabolomic markers, when combined with clinical characteristics, allowed improving the disease development prediction. The validation study showed that this predictive performance was specific to the MetS component. This work also demonstrates the interest of such an approach to discover subphenotypes that will need further characterization to be able to shift to molecular reclassification and targeting of MetS.

  10. Non-Targeted Metabolomics Analysis of Golden Retriever Muscular Dystrophy-Affected Muscles Reveals Alterations in Arginine and Proline Metabolism, and Elevations in Glutamic and Oleic Acid In Vivo.

    Science.gov (United States)

    Abdullah, Muhammad; Kornegay, Joe N; Honcoop, Aubree; Parry, Traci L; Balog-Alvarez, Cynthia J; O'Neal, Sara K; Bain, James R; Muehlbauer, Michael J; Newgard, Christopher B; Patterson, Cam; Willis, Monte S

    2017-07-29

    Like Duchenne muscular dystrophy (DMD), the Golden Retriever Muscular Dystrophy (GRMD) dog model of DMD is characterized by muscle necrosis, progressive paralysis, and pseudohypertrophy in specific skeletal muscles. This severe GRMD phenotype includes moderate atrophy of the biceps femoris (BF) as compared to unaffected normal dogs, while the long digital extensor (LDE), which functions to flex the tibiotarsal joint and serves as a digital extensor, undergoes the most pronounced atrophy. A recent microarray analysis of GRMD identified alterations in genes associated with lipid metabolism and energy production. We, therefore, undertook a non-targeted metabolomics analysis of the milder/earlier stage disease GRMD BF muscle versus the more severe/chronic LDE using GC-MS to identify underlying metabolic defects specific for affected GRMD skeletal muscle. Untargeted metabolomics analysis of moderately-affected GRMD muscle (BF) identified eight significantly altered metabolites, including significantly decreased stearamide (0.23-fold of controls, p = 2.89 × 10-3), carnosine (0.40-fold of controls, p = 1.88 × 10-2), fumaric acid (0.40-fold of controls, p = 7.40 × 10-4), lactamide (0.33-fold of controls, p = 4.84 × 10-2), myoinositol-2-phosphate (0.45-fold of controls, p = 3.66 × 10-2), and significantly increased oleic acid (1.77-fold of controls, p = 9.27 × 10-2), glutamic acid (2.48-fold of controls, p = 2.63 × 10-2), and proline (1.73-fold of controls, p = 3.01 × 10-2). Pathway enrichment analysis identified significant enrichment for arginine/proline metabolism (p = 5.88 × 10-4, FDR 4.7 × 10-2), where alterations in L-glutamic acid, proline, and carnosine were found. Additionally, multiple Krebs cycle intermediates were significantly decreased (e.g., malic acid, fumaric acid, citric/isocitric acid, and succinic acid), suggesting that altered energy metabolism may be underlying the observed GRMD BF muscle dysfunction. In contrast, two pathways, inosine-5

  11. Non-Targeted Metabolomics Analysis of Golden Retriever Muscular Dystrophy-Affected Muscles Reveals Alterations in Arginine and Proline Metabolism, and Elevations in Glutamic and Oleic Acid In Vivo

    Science.gov (United States)

    Abdullah, Muhammad; Kornegay, Joe N.; Honcoop, Aubree; Parry, Traci L.; Balog-Alvarez, Cynthia J.; Muehlbauer, Michael J.; Newgard, Christopher B.; Patterson, Cam

    2017-01-01

    Background: Like Duchenne muscular dystrophy (DMD), the Golden Retriever Muscular Dystrophy (GRMD) dog model of DMD is characterized by muscle necrosis, progressive paralysis, and pseudohypertrophy in specific skeletal muscles. This severe GRMD phenotype includes moderate atrophy of the biceps femoris (BF) as compared to unaffected normal dogs, while the long digital extensor (LDE), which functions to flex the tibiotarsal joint and serves as a digital extensor, undergoes the most pronounced atrophy. A recent microarray analysis of GRMD identified alterations in genes associated with lipid metabolism and energy production. Methods: We, therefore, undertook a non-targeted metabolomics analysis of the milder/earlier stage disease GRMD BF muscle versus the more severe/chronic LDE using GC-MS to identify underlying metabolic defects specific for affected GRMD skeletal muscle. Results: Untargeted metabolomics analysis of moderately-affected GRMD muscle (BF) identified eight significantly altered metabolites, including significantly decreased stearamide (0.23-fold of controls, p = 2.89 × 10−3), carnosine (0.40-fold of controls, p = 1.88 × 10−2), fumaric acid (0.40-fold of controls, p = 7.40 × 10−4), lactamide (0.33-fold of controls, p = 4.84 × 10−2), myoinositol-2-phosphate (0.45-fold of controls, p = 3.66 × 10−2), and significantly increased oleic acid (1.77-fold of controls, p = 9.27 × 10−2), glutamic acid (2.48-fold of controls, p = 2.63 × 10−2), and proline (1.73-fold of controls, p = 3.01 × 10−2). Pathway enrichment analysis identified significant enrichment for arginine/proline metabolism (p = 5.88 × 10−4, FDR 4.7 × 10−2), where alterations in L-glutamic acid, proline, and carnosine were found. Additionally, multiple Krebs cycle intermediates were significantly decreased (e.g., malic acid, fumaric acid, citric/isocitric acid, and succinic acid), suggesting that altered energy metabolism may be underlying the observed GRMD BF muscle

  12. Non-Targeted Metabolomics Analysis of Golden Retriever Muscular Dystrophy-Affected Muscles Reveals Alterations in Arginine and Proline Metabolism, and Elevations in Glutamic and Oleic Acid In Vivo

    Directory of Open Access Journals (Sweden)

    Muhammad Abdullah

    2017-07-01

    Full Text Available Background: Like Duchenne muscular dystrophy (DMD, the Golden Retriever Muscular Dystrophy (GRMD dog model of DMD is characterized by muscle necrosis, progressive paralysis, and pseudohypertrophy in specific skeletal muscles. This severe GRMD phenotype includes atrophy of the biceps femoris (BF as compared to unaffected normal dogs, while the long digital extensor (LDE, which functions to flex the tibiotarsal joint and serves as a digital extensor, undergoes the most pronounced atrophy. A recent microarray analysis of GRMD identified alterations in genes associated with lipid metabolism and energy production. Methods: We, therefore, undertook a non-targeted metabolomics analysis of the milder/earlier stage disease GRMD BF muscle versus the more severe/chronic LDE using GC-MS to identify underlying metabolic defects specific for affected GRMD skeletal muscle. Results: Untargeted metabolomics analysis of moderately-affected GRMD muscle (BF identified eight significantly altered metabolites, including significantly decreased stearamide (0.23-fold of controls, p = 2.89 × 10−3, carnosine (0.40-fold of controls, p = 1.88 × 10−2, fumaric acid (0.40-fold of controls, p = 7.40 × 10−4, lactamide (0.33-fold of controls, p = 4.84 × 10−2, myoinositol-2-phosphate (0.45-fold of controls, p = 3.66 × 10−2, and significantly increased oleic acid (1.77-fold of controls, p = 9.27 × 10−2, glutamic acid (2.48-fold of controls, p = 2.63 × 10−2, and proline (1.73-fold of controls, p = 3.01 × 10−2. Pathway enrichment analysis identified significant enrichment for arginine/proline metabolism (p = 5.88 × 10−4, FDR 4.7 × 10−2, where alterations in L-glutamic acid, proline, and carnosine were found. Additionally, multiple Krebs cycle intermediates were significantly decreased (e.g., malic acid, fumaric acid, citric/isocitric acid, and succinic acid, suggesting that altered energy metabolism may be underlying the observed GRMD BF muscle

  13. Navigating freely-available software tools for metabolomics analysis.

    Science.gov (United States)

    Spicer, Rachel; Salek, Reza M; Moreno, Pablo; Cañueto, Daniel; Steinbeck, Christoph

    2017-01-01

    The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools. To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics. The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for. A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary. This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.

  14. Metabolomics in Plants and Humans: Applications in the Prevention and Diagnosis of Diseases

    Directory of Open Access Journals (Sweden)

    Diego F. Gomez-Casati

    2013-01-01

    Full Text Available In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

  15. NMR-based metabolomics: from sample preparation to applications in nutrition research.

    Science.gov (United States)

    Brennan, Lorraine

    2014-11-01

    Metabolomics is the study of metabolites present in biological samples such as biofluids, tissue/cellular extracts and culture media. Measurement of these metabolites is achieved through use of analytical techniques such as NMR and mass spectrometry coupled to liquid chromatography. Combining metabolomic data with multivariate data analysis tools allows the elucidation of alterations in metabolic pathways under different physiological conditions. Applications of NMR-based metabolomics have grown in recent years and it is now widely used across a number of disciplines. The present review gives an overview of the developments in the key steps involved in an NMR-based metabolomics study. Furthermore, there will be a particular emphasis on the use of NMR-based metabolomics in nutrition research. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action

    Science.gov (United States)

    Vincent, Isabel M.; Ehmann, David E.; Mills, Scott D.; Perros, Manos

    2016-01-01

    Deciphering the mode of action (MOA) of new antibiotics discovered through phenotypic screening is of increasing importance. Metabolomics offers a potentially rapid and cost-effective means of identifying modes of action of drugs whose effects are mediated through changes in metabolism. Metabolomics techniques also collect data on off-target effects and drug modifications. Here, we present data from an untargeted liquid chromatography-mass spectrometry approach to identify the modes of action of eight compounds: 1-[3-fluoro-4-(5-methyl-2,4-dioxo-pyrimidin-1-yl)phenyl]-3-[2-(trifluoromethyl)phenyl]urea (AZ1), 2-(cyclobutylmethoxy)-5′-deoxyadenosine, triclosan, fosmidomycin, CHIR-090, carbonyl cyanide m-chlorophenylhydrazone (CCCP), 5-chloro-2-(methylsulfonyl)-N-(1,3-thiazol-2-yl)-4-pyrimidinecarboxamide (AZ7), and ceftazidime. Data analysts were blind to the compound identities but managed to identify the target as thymidylate kinase for AZ1, isoprenoid biosynthesis for fosmidomycin, acyl-transferase for CHIR-090, and DNA metabolism for 2-(cyclobutylmethoxy)-5′-deoxyadenosine. Changes to cell wall metabolites were seen in ceftazidime treatments, although other changes, presumably relating to off-target effects, dominated spectral outputs in the untargeted approach. Drugs which do not work through metabolic pathways, such as the proton carrier CCCP, have no discernible impact on the metabolome. The untargeted metabolomics approach also revealed modifications to two compounds, namely, fosmidomycin and AZ7. An untreated control was also analyzed, and changes to the metabolome were seen over 4 h, highlighting the necessity for careful controls in these types of studies. Metabolomics is a useful tool in the analysis of drug modes of action and can complement other technologies already in use. PMID:26833150

  17. The application of skin metabolomics in the context of transdermal drug delivery.

    Science.gov (United States)

    Li, Jinling; Xu, Weitong; Liang, Yibiao; Wang, Hui

    2017-04-01

    Metabolomics is a powerful emerging tool for the identification of biomarkers and the exploration of metabolic pathways in a high-throughput manner. As an administration site for percutaneous absorption, the skin has a variety of metabolic enzymes, except other than hepar. However, technologies to fully detect dermal metabolites remain lacking. Skin metabolomics studies have mainly focused on the regulation of dermal metabolites by drugs or on the metabolism of drugs themselves. Skin metabolomics techniques include collection and preparation of skin samples, data collection, data processing and analysis. Furthermore, studying dermal metabolic effects via metabolomics can provide novel explanations for the pathogenesis of some dermatoses and unique insights for designing targeted prodrugs, promoting drug absorption and controlling drug concentration. This paper reviews current progress in the field of skin metabolomics, with a specific focus on dermal drug delivery systems and dermatosis. Copyright © 2016. Published by Elsevier Urban & Partner Sp. z o.o.

  18. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

    OpenAIRE

    Adkins, Daniel E.; McClay, Joseph L.; VUNCK, SARAH A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; SOUZA,RENAN P. DE; Crowley, James J.; Sullivan, Patrick F; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2013-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphe...

  19. Bridging the gap between comprehensive extraction protocols in plant metabolomics studies and method validation.

    Science.gov (United States)

    Bijttebier, Sebastiaan; Van der Auwera, Anastasia; Foubert, Kenn; Voorspoels, Stefan; Pieters, Luc; Apers, Sandra

    2016-09-07

    It is vital to pay much attention to the design of extraction methods developed for plant metabolomics, as any non-extracted or converted metabolites will greatly affect the overall quality of the metabolomics study. Method validation is however often omitted in plant metabolome studies, as the well-established methodologies for classical targeted analyses such as recovery optimization cannot be strictly applied. The aim of the present study is to thoroughly evaluate state-of-the-art comprehensive extraction protocols for plant metabolomics with liquid chromatography-photodiode array-accurate mass mass spectrometry (LC-PDA-amMS) by bridging the gap with method validation. Validation of an extraction protocol in untargeted plant metabolomics should ideally be accomplished by validating the protocol for all possible outcomes, i.e. for all secondary metabolites potentially present in the plant. In an effort to approach this ideal validation scenario, two plant matrices were selected based on their wide versatility of phytochemicals: meadowsweet (Filipendula ulmaria) for its polyphenols content, and spicy paprika powder (from the genus Capsicum) for its apolar phytochemicals content (carotenoids, phytosterols, capsaicinoids). These matrices were extracted with comprehensive extraction protocols adapted from literature and analysed with a generic LC-PDA-amMS characterization platform that was previously validated for broad range phytochemical analysis. The performance of the comprehensive sample preparation protocols was assessed based on extraction efficiency, repeatability and intermediate precision and on ionization suppression/enhancement evaluation. The manuscript elaborates on the finding that none of the extraction methods allowed to exhaustively extract the metabolites. Furthermore, it is shown that depending on the extraction conditions enzymatic degradation mechanisms can occur. Investigation of the fractions obtained with the different extraction methods

  20. High-resolution metabolomics of occupational exposure to trichloroethylene

    NARCIS (Netherlands)

    Walker, Douglas I; Uppal, Karan; Zhang, Luoping; Vermeulen, Roel; Smith, Martyn; Hu, Wei; Purdue, Mark P; Tang, Xiaojiang; Reiss, Boris; Kim, Sungkyoon; Li, Laiyu; Huang, Hanlin; Pennell, Kurt D; Jones, Dean P; Rothman, Nathaniel; Lan, Qing

    2016-01-01

    BACKGROUND: Occupational exposure to trichloroethylene (TCE) has been linked to adverse health outcomes including non-Hodgkin's lymphoma and kidney and liver cancer; however, TCE's mode of action for development of these diseases in humans is not well understood. METHODS: Non-targeted metabolomics

  1. Human gut microbes impact host serum metabolome and insulin sensitivity

    DEFF Research Database (Denmark)

    Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Nielsen, Henrik Bjørn

    2016-01-01

    Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin-resistant...... are identified as the main species driving the association between biosynthesis of BCAAs and insulin resistance, and in mice we demonstrate that P. copri can induce insulin resistance, aggravate glucose intolerance and augment circulating levels of BCAAs. Our findings suggest that microbial targets may have...... the potential to diminish insulin resistance and reduce the incidence of common metabolic and cardiovascular disorders....

  2. Can NMR solve some significant challenges in metabolomics?

    Science.gov (United States)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

    The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

  3. Metabolomics Workbench (MetWB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Metabolomics Program's Data Repository and Coordinating Center (DRCC), housed at the San Diego Supercomputer Center (SDSC), University of California, San Diego,...

  4. The biology of plant metabolomics

    NARCIS (Netherlands)

    Hall, R.D.

    2011-01-01

    Following a general introduction, this book includes details of metabolomics of model species including Arabidopsis and tomato. Further chapters provide in-depth coverage of abiotic stress, data integration, systems biology, genetics, genomics, chemometrics and biostatisitcs. Applications of plant

  5. Metabolic screening and metabolomics analysis in the Intellectual Developmental Disorders Mexico Study

    Directory of Open Access Journals (Sweden)

    Isabel Ibarra-González

    2017-07-01

    Full Text Available Objective. Inborn errors of metabolism (IEM are genetic conditions that are sometimes associated with intellectual  developmental disorders (IDD. The aim of this study is to contribute to the metabolic characterization of IDD of unknown etiology in Mexico. Materials and methods. Metabolic screening using tandem mass spectrometry and fluorometry will be performed to rule out IEM. In addition,target metabolomic analysis will be done to characterize the metabolomic profile of patients with IDD. Conclusion. Identification of new metabolomic profiles associated withIDD of unknown etiology and comorbidities will contribute to the development of novel diagnostic and therapeutic schemes for the prevention and treatment of IDD in Mexico.

  6. CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets.

    Science.gov (United States)

    Tsai, Shengdar Q; Nguyen, Nhu T; Malagon-Lopez, Jose; Topkar, Ved V; Aryee, Martin J; Joung, J Keith

    2017-06-01

    Sensitive detection of off-target effects is important for translating CRISPR-Cas9 nucleases into human therapeutics. In vitro biochemical methods for finding off-targets offer the potential advantages of greater reproducibility and scalability while avoiding limitations associated with strategies that require the culture and manipulation of living cells. Here we describe circularization for in vitro reporting of cleavage effects by sequencing (CIRCLE-seq), a highly sensitive, sequencing-efficient in vitro screening strategy that outperforms existing cell-based or biochemical approaches for identifying CRISPR-Cas9 genome-wide off-target mutations. In contrast to previously described in vitro methods, we show that CIRCLE-seq can be practiced using widely accessible next-generation sequencing technology and does not require reference genome sequences. Importantly, CIRCLE-seq can be used to identify off-target mutations associated with cell-type-specific single-nucleotide polymorphisms, demonstrating the feasibility and importance of generating personalized specificity profiles. CIRCLE-seq provides an accessible, rapid, and comprehensive method for identifying genome-wide off-target mutations of CRISPR-Cas9.

  7. Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine.

    Science.gov (United States)

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-04-14

    Uropathogenic Escherichia coli (UPEC) growth in women's bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the "interactive metabolome", which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI.

  8. Transcriptome-Wide Identification of miRNA Targets under Nitrogen Deficiency in Populus tomentosa Using Degradome Sequencing.

    Science.gov (United States)

    Chen, Min; Bao, Hai; Wu, Qiuming; Wang, Yanwei

    2015-06-18

    miRNAs are endogenous non-coding small RNAs with important regulatory roles in stress responses. Nitrogen (N) is an indispensable macronutrient required for plant growth and development. Previous studies have identified a variety of known and novel miRNAs responsive to low N stress in plants, including Populus. However, miRNAs involved in the cleavage of target genes and the corresponding regulatory networks in response to N stress in Populus remain largely unknown. Consequently, degradome sequencing was employed for global detection and validation of N-responsive miRNAs and their targets. A total of 60 unique miRNAs (39 conserved, 13 non-conserved, and eight novel) were experimentally identified to target 64 mRNA transcripts and 21 precursors. Among them, we further verified the cleavage of 11 N-responsive miRNAs identified previously and provided empirical evidence for the cleavage mode of these miRNAs on their target mRNAs. Furthermore, five miRNA stars (miRNA*s) were shown to have cleavage function. The specificity and diversity of cleavage sites on the targets and miRNA precursors in P. tomentosa were further detected. Identification and annotation of miRNA-mediated cleavage of target genes in Populus can increase our understanding of miRNA-mediated molecular mechanisms of woody plants adapted to low N environments.

  9. Medicinal Plants: A Public Resource for Metabolomics and Hypothesis Development

    Directory of Open Access Journals (Sweden)

    Eve Syrkin Wurtele

    2012-11-01

    Full Text Available Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range of antioxidant, antiviral, tumoricidal and anti-inflammatory constituents, provide a case study of obtaining biosystematic and developmental fingerprint information from metabolite accumulation data in a little studied species. Digitalis purpurea, well known as a source of cardiac glycosides, is used to illustrate how integrating metabolomics and transcriptomics data can lead to identification of candidate genes encoding biosynthetic enzymes in the cardiac glycoside pathway. Medicinal Plant Metabolomics Resource (MPM [1] provides a framework for generating experimentally testable hypotheses about the metabolic networks that lead to the generation of specialized compounds, identifying genes that control their biosynthesis and establishing a basis for modeling metabolism in less

  10. Transcriptomic-Wide Discovery of Direct and Indirect HuR RNA Targets in Activated CD4+ T Cells.

    Directory of Open Access Journals (Sweden)

    Patsharaporn Techasintana

    Full Text Available Due to poor correlation between steady state mRNA levels and protein product, purely transcriptomic profiling methods may miss genes posttranscriptionally regulated by RNA binding proteins (RBPs and microRNAs (miRNAs. RNA immunoprecipitation (RIP methods developed to identify in vivo targets of RBPs have greatly elucidated those mRNAs which may be regulated via transcript stability and translation. The RBP HuR (ELAVL1 and family members are major stabilizers of mRNA. Many labs have identified HuR mRNA targets; however, many of these analyses have been performed in cell lines and oftentimes are not independent biological replicates. Little is known about how HuR target mRNAs behave in conditional knock-out models. In the present work, we performed HuR RIP-Seq and RNA-Seq to investigate HuR direct and indirect targets using a novel conditional knock-out model of HuR genetic ablation during CD4+ T activation and Th2 differentiation. Using independent biological replicates, we generated a high coverage RIP-Seq data set (>160 million reads that was analyzed using bioinformatics methods specifically designed to find direct mRNA targets in RIP-Seq data. Simultaneously, another set of independent biological replicates were sequenced by RNA-Seq (>425 million reads to identify indirect HuR targets. These direct and indirect targets were combined to determine canonical pathways in CD4+ T cell activation and differentiation for which HuR plays an important role. We show that HuR may regulate genes in multiple canonical pathways involved in T cell activation especially the CD28 family signaling pathway. These data provide insights into potential HuR-regulated genes during T cell activation and immune mechanisms.

  11. Transcriptome-wide identification of host genes targeted by tomato spotted wilt virus-derived small interfering RNAs.

    Science.gov (United States)

    Ramesh, Shunmugiah V; Williams, Sarah; Kappagantu, Madhu; Mitter, Neena; Pappu, Hanu R

    2017-06-15

    RNA silencing mechanism functions as a major defense against invading viruses. The caveat in the RNA silencing mechanism is that the effector small interfering RNAs (siRNAs) act on any RNA transcripts with sequence complementarity irrespective of target's origin. A subset of highly expressed viral small interfering RNAs (vsiRNAs) derived from the tomato spotted wilt virus (TSWV; Tospovirus: Bunyaviridae) genome was analyzed for their propensity to downregulate the tomato transcriptome. A total of 11898 putative target sites on tomato transcripts were found to exhibit a propensity for down regulation by TSWV-derived vsiRNAs. In total, 2450 unique vsiRNAs were found to have potential cross-reacting capability with the tomato transcriptome. VsiRNAs were found to potentially target a gamut of host genes involved in basal cellular activities including enzymes, transcription factors, membrane transporters, and cytoskeletal proteins. KEGG pathway annotation of targets revealed that the vsiRNAs were mapped to secondary metabolite biosynthesis, amino acids, starch and sucrose metabolism, and carbon and purine metabolism. Transcripts for protein processing, hormone signalling, and plant-pathogen interactions were the most likely targets from the genetic, environmental information processing, and organismal systems, respectively. qRT-PCR validation of target gene expression showed that none of the selected transcripts from tomato cv. Marglobe showed up regulation, and all were down regulated even upto 20 folds (high affinity glucose transporter). However, the expression levels of transcripts from cv. Red Defender revealed differential regulation as three among the target transcripts showed up regulation (Cc-nbs-lrr, resistance protein, AP2-like ethylene-responsive transcription factor, and heat stress transcription factor A3). Accumulation of tomato target mRNAs of corresponding length was proved in both tomato cultivars using 5' RACE analysis. The TSWV-tomato interaction at

  12. Genome wide identification of cotton (Gossypium hirsutum)-encoded microRNA targets against Cotton leaf curl Burewala virus.

    Science.gov (United States)

    Shweta; Akhter, Yusuf; Khan, Jawaid Ahmad

    2018-01-05

    Cotton leaf curl Burewala virus (CLCuBV, genus Begomovirus) causes devastating cotton leaf curl disease. Among various known virus controlling strategies, RNAi-mediated one has shown potential to protect host crop plants. Micro(mi) RNAs, are the endogenous small RNAs and play a key role in plant development and stress resistance. In the present study we have identified cotton (Gossypium hirsutum)-encoded miRNAs targeting the CLCuBV. Based on threshold free energy and maximum complementarity scores of host miRNA-viral mRNA target pairs, a number of potential miRNAs were annotated. Among them, ghr-miR168 was selected as the most potent candidate, capable of targeting several vital genes namely C1, C3, C4, V1 and V2 of CLCuBV genome. In addition, ghr-miR395a and ghr-miR395d were observed to target the overlapping transcripts of C1 and C4 genes. We have verified the efficacy of these miRNA targets against CLCuBV following suppression of RNAi-mediated virus control through translational inhibition or cleavage of viral mRNA. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Metabolomics Society’s International Affiliations

    NARCIS (Netherlands)

    Roessner, U.; Rolin, D.; Rijswijk, van M.E.C.; Hall, R.D.; Hankemeier, T.

    2015-01-01

    In 2012 the Metabolomics Society established a more formal system for national and regional metabolomics initiatives, interest groups, societies and networks to become an International Affiliate of the Society. A number of groups (http://metabolomicssociety.org/international-affilia

  14. Polarization Utilization in Radar Target Reconstruction: C-Wide (Multi-Frequency) Band Relationship of a Target’s Characteristic Operators with Its Unique Set of Natural Eigenfrequencies.

    Science.gov (United States)

    1983-12-14

    Science Department, University of Illinois at Chicago, and compared with measurement data for missile-type composite targets by Teledyne Micronetics ...dB level, of 100% which we found to correspond with the data we had analyzed. As a measure of the resolution achievable with the Teledyne- Micronetics ... Micronetics Measurement Range in collaboration with NAV-AIR (6.2), NAV-SEA (6.2), and at the ESL-OSU indoor compact RCS Range in collaboration with Dr

  15. Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets

    NARCIS (Netherlands)

    Wain, Louise V.; Shrine, Nick R. G.; Artigas, Maria Soler; Erzurumluoglu, A Mesut; Noyvert, Boris; Bossini-Castillo, Lara; Obeidat, Ma'en; Henrys, Amanda P.; Portelli, Michael A.; Hall, Robert J; Billington, Charlotte K.; Rimington, Tracy L; Fenech, Anthony G; John, Catherine; Blake, Tineka; Jackson, Victoria E.; Allen, Richard J; Prins, Bram P.; Campbell, Archie; Porteous, David J.; Jarvelin, Marjo-Riitta; Wielscher, Matthias; Jamess, Alan L.; Hui, Jennie; Wareham, Nicholas J.; Zhao, Jing Hua; Wilson, James F.; Joshi, Peter K.; Stubbe, Beate; Rawal, Rajesh; Schulz, Holger; Imboden, Medea; Probst-Hensch, Nicole M.; Karrasch, Stefan; Gieger, Christian; Deary, Ian J.; Harris, Sarah E.; Marten, Jonathan; Rudan, Igor; Enroth, Stefan; Gyllensten, Ulf; Kerr, Shona M.; Polasek, Ozren; Kahonen, Mika; Surakka, Ida; Vitart, Veronique; Hayward, Caroline; Lehtimaki, Terho; Raitakari, Olli T.; Evans, David M.; Henderson, A. John; Pennell, Craig E.; Wang, Carol A.; Sly, Peter D.; Wan, Emily S; Busch, Robert; Hobbs, Brian D; Litonjua, Augusto; Sparrow, David W; Gulsvik, Amund; Bakke, Per S.; Crapo, James D.; Beaty, Terri H.; Hansel, Nadia N.; Mathias, Rasika A.; Ruczinski, Ingo; Barnes, Kathleen C.; Bosse, Yohan; Joubert, Philippe; van den Berge, Maarten; Brandsma, Corry-Anke; Pare, Peter D.; Sin, Don; Nickle, David C.; Hao, Ke; Gottesman, Omri; Dewey, Frederick E; Bruse, Shannon E; Carey, David J.; Kirchner, H Lester; Jonsson, Stefan; Thorleifsson, Gudmar; Jonsdottir, Ingileif; Gislason, Thorarinn; Stefansson, Kari; Schurmann, Claudia; Nadkarni, Girish N; Bottinger, Erwin P.; Loos, Ruth J. F.; Walters, Robin G.; Chen, Zhengming; Millwood, Iona Y; Vaucher, Julien; Kurmi, Om P; Li, Liming; Hansell, Anna L.; Brightling, Chris; Zeggini, Eleftheria; Cho, Michael H.; Silverman, Edwin K.; Sayers, Ian; Trynka, Gosia; Morris, Andrew P.; Strachan, David P.; Halls, Ian P.; Tobin, Martin D.

    Chronic obstructive pulmonary disease (COPD) is characterized by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375

  16. Transcriptome-wide analysis of dynamic variations in regulation modes of grapevine microRNAs on their target genes during grapevine development.

    Science.gov (United States)

    Wang, Chen; Leng, Xiangpeng; Zhang, Yanyi; Kayesh, Emrul; Zhang, Yanping; Sun, Xin; Fang, Jinggui

    2014-02-01

    MicroRNAs (miRNAs) play critical regulatory roles mainly through cleaving their target mRNAs or repressing gene translation during plant development. Grapevines are among the most economically important fruit crops with available whole genome sequences. Studies on grapevine miRNAs (Vv-miRNAs) are also widely available. However, studies on the regulation mode of Vv-miRNAs on their target mRNAs during grapevine development have not been studied well, especially at the transcriptome-wide level. Here, six small RNA and mRNA libraries from various grapevine tissues were constructed for Illumina and Degradome sequencing. Subsequently, we systematically analyzed the spatiotemporal variations in the regulation of the target genes of regulation of Vv-miRNAs. In total, 242 known and 132 novel Vv-miRNAs and 193 target mRNAs were identified, including 103 target mRNAs for known and 90 target mRNAs for novel miRNAs, were validated in one or more of the tissues examined. More than 50 % of novel miRNAs were expressed exclusively in the flowers and berries, where they cleaved their target genes in a tissue-specific manner, especially, the breadth of their cleavage sites in flower tissues. Moreover, six novel miRNAs in berries responded to exogenous gibberellin and/or ethylene under a quantitative real time RT-PCR analysis, which confirmed their regulatory functions during berry development. Up to 93.6 % of the known miRNAs were highly conserved in various tissues, where their expression levels exhibited dynamic variations during grapevine development. Significantly, some Vv-miRNA families had one key member that acted as the main regulator of their target genes during grapevine development.

  17. Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

    Science.gov (United States)

    Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

    2018-01-05

    Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

  18. Metabolomic application in toxicity evaluation and toxicological biomarker identification of natural product.

    Science.gov (United States)

    Chen, Dan-Qian; Chen, Hua; Chen, Lin; Tang, Dan-Dan; Miao, Hua; Zhao, Ying-Yong

    2016-05-25

    Natural product plays a vital role in disease prevention and treatment since the appearance of civilization, but the toxicity severely hinders its wide use. In order to avoid toxic effect as far as possible and use natural product safely, more comprehensive understandings of toxicity are urgently required. Since the metabolome represents the physiological or pathological status of organisms, metabolomics-based toxicology is of significance to observe potential injury before toxins have caused physiological or pathological damages. Metabolomics-based toxicology can evaluate toxicity and identify toxicological biomarker of natural product, which is helpful to guide clinical medication and reduce adverse drug reactions. In the past decades, dozens of metabolomic researches have been implemented on toxicity evaluation, toxicological biomarker identification and potential mechanism exploration of nephrotoxicity, hepatotoxicity, cardiotoxicity and central nervous system toxicity induced by pure compounds, extracts and compound prescriptions. In this paper, metabolomic technology, sample preparation, data process and analysis, and metabolomics-based toxicological research of natural product are reviewed, and finally, the potential problems and further perspectives in toxicological metabolomic investigations of natural product are discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. Proteome-wide analysis of SUMO2 targets in response to pathological DNA replication stress in human cells

    DEFF Research Database (Denmark)

    Bursomanno, Sara; Beli, Petra; Khan, Asif M

    2015-01-01

    SUMOylation is a form of post-translational modification involving covalent attachment of SUMO (Small Ubiquitin-like Modifier) polypeptides to specific lysine residues in the target protein. In human cells, there are four SUMO proteins, SUMO1-4, with SUMO2 and SUMO3 forming a closely related subf...

  20. The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

    Science.gov (United States)

    Serkova, Natalie J.; Standiford, Theodore J.

    2011-01-01

    Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

  1. Metabolomics: the chemistry between ecology and genetics

    NARCIS (Netherlands)

    Macel, M.; Van Dam, N.M.; Keurentjes, J.J.B.

    2010-01-01

    Metabolomics is a fast developing field of comprehensive untargeted chemical analyses. It has many applications and can in principle be used on any organism without prior knowledge of the metabolome or genome. The amount of functional information that is acquired with metabolomics largely depends on

  2. A Metabolomic Perspective on Coeliac Disease

    NARCIS (Netherlands)

    Calabrò, A.; Gralka, E.; Luchinat, C.; Saccenti, E.; Tenori, L.

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already

  3. Current Trends and Innovations in Bioanalytical Techniques of Metabolomics.

    Science.gov (United States)

    Zhang, Tianlei; Zhang, Aihua; Qiu, Shi; Yang, Suqing; Wang, Xijun

    2016-07-03

    The advancement of omics technology has vigorously promoted the development of the life sciences; metabolomics in particular has emerged as a powerful tool that has a promising future in scientific research and clinical practice. As terminal products of complex biochemical networks, endogenous low-molecular-weight metabolites contain rich information about the physiological status of an individual or group of people. Also, this information has more practical significance in that we know "what happened" instead of "what might happen" to some degree. Rapid and accurate screening of metabolites on a large scale was beyond imagining in the past; however, benefiting from high-throughput technical means, the overall disturbance of metabolites induced by environmental stimulus or treatments can now be well analyzed. After appropriate bioinformatic analysis, clinically relevant biomarkers of a disease can be found, and an accurate and dynamic picture of metabolic disturbance that contributes to a phenotype of a certain organism can be constructed. Biomarkers can also reveal the general metabolic condition by pathways that correlate with disease progression, or even with the risk of certain diseases. Thus, as an indispensable part of the framework of systems biology, metabolomics has been widely used in, but not limited to, the fields of medical science, pharmaceuticals, botany, and microbiology. In this article, we focus on metabolomics' mainstream research content and technical innovations such as determination methods for biologically active compounds; further, we pay more attention to the future trends and various possibilities for metabolomics study.

  4. Computational Tools for the Secondary Analysis of Metabolomics Experiments

    Directory of Open Access Journals (Sweden)

    Sean Cameron Booth

    2013-01-01

    Full Text Available Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before.

  5. COMPUTATIONAL TOOLS FOR THE SECONDARY ANALYSIS OF METABOLOMICS EXPERIMENTS

    Directory of Open Access Journals (Sweden)

    Sean C. Booth

    2013-01-01

    Full Text Available Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before.

  6. Proteome-wide analysis of SUMO2 targets in response to pathological DNA replication stress in human cells.

    Science.gov (United States)

    Bursomanno, Sara; Beli, Petra; Khan, Asif M; Minocherhomji, Sheroy; Wagner, Sebastian A; Bekker-Jensen, Simon; Mailand, Niels; Choudhary, Chunaram; Hickson, Ian D; Liu, Ying

    2015-01-01

    SUMOylation is a form of post-translational modification involving covalent attachment of SUMO (Small Ubiquitin-like Modifier) polypeptides to specific lysine residues in the target protein. In human cells, there are four SUMO proteins, SUMO1-4, with SUMO2 and SUMO3 forming a closely related subfamily. SUMO2/3, in contrast to SUMO1, are predominantly involved in the cellular response to certain stresses, including heat shock. Substantial evidence from studies in yeast has shown that SUMOylation plays an important role in the regulation of DNA replication and repair. Here, we report a proteomic analysis of proteins modified by SUMO2 in response to DNA replication stress in S phase in human cells. We have identified a panel of 22 SUMO2 targets with increased SUMOylation during DNA replication stress, many of which play key functions within the DNA replication machinery and/or in the cellular response to DNA damage. Interestingly, POLD3 was found modified most significantly in response to a low dose aphidicolin treatment protocol that promotes common fragile site (CFS) breakage. POLD3 is the human ortholog of POL32 in budding yeast, and has been shown to act during break-induced recombinational repair. We have also shown that deficiency of POLD3 leads to an increase in RPA-bound ssDNA when cells are under replication stress, suggesting that POLD3 plays a role in the cellular response to DNA replication stress. Considering that DNA replication stress is a source of genome instability, and that excessive replication stress is a hallmark of pre-neoplastic and tumor cells, our characterization of SUMO2 targets during a perturbed S-phase should provide a valuable resource for future functional studies in the fields of DNA metabolism and cancer biology. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Food metabolomics: from farm to human.

    Science.gov (United States)

    Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

    2016-02-01

    Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Plasma metabolomics reveals biomarkers of the atherosclerosis.

    Science.gov (United States)

    Chen, Xi; Liu, Lian; Palacios, Gustavo; Gao, Jie; Zhang, Ning; Li, Guang; Lu, Juan; Song, Ting; Zhang, Yingzhi; Lv, Haitao

    2010-09-01

    Atherosclerotic cardiovascular disease remains the leading cause of morbidity and mortality in industrialized societies. The lack of metabolite biomarkers has impeded the clinical diagnosis of atherosclerosis so far. In this study, stable atherosclerosis patients (n=16) and age- and sex-matched non-atherosclerosis healthy subjects (n=28) were recruited from the local community (Harbin, P. R. China). The plasma was collected from each study subject and was subjected to metabolomics analysis by GC/MS. Pattern recognition analyses (principal components analysis, orthogonal partial least-squares discriminate analysis, and hierarchical clustering analysis) commonly demonstrated plasma metabolome, which was significantly different from atherosclerotic and non-atherosclerotic subjects. The development of atherosclerosis-induced metabolic perturbations of fatty acids, such as palmitate, stearate, and 1-monolinoleoylglycerol, was confirmed consistent with previous publication, showing that palmitate significantly contributes to atherosclerosis development via targeting apoptosis and inflammation pathways. Altogether, this study demonstrated that the development of atherosclerosis directly perturbed fatty acid metabolism, especially that of palmitate, which was confirmed as a phenotypic biomarker for clinical diagnosis of atherosclerosis.

  9. Metabolomics in cell culture--a strategy to study crucial metabolic pathways in cancer development and the response to treatment.

    Science.gov (United States)

    Halama, Anna

    2014-12-15

    Metabolomics is a comprehensive tool for monitoring processes within biological systems. Thus, metabolomics may be widely applied to the determination of diagnostic biomarkers for certain diseases or treatment outcomes. There is significant potential for metabolomics to be implemented in cancer research because cancer may modify metabolic pathways in the whole organism. However, not all biological questions can be answered solely by the examination of small molecule composition in biofluids; in particular, the study of cellular processes or preclinical drug testing requires ex vivo models. The major objective of this review was to summarise the current achievement in the field of metabolomics in cancer cell culture-focusing on the metabolic pathways regulated in different cancer cell lines-and progress that has been made in the area of drug screening and development by the implementation of metabolomics in cell lines. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Preprocessing of NMR metabolomics data.

    Science.gov (United States)

    Euceda, Leslie R; Giskeødegård, Guro F; Bathen, Tone F

    2015-05-01

    Metabolomics involves the large scale analysis of metabolites and thus, provides information regarding cellular processes in a biological sample. Independently of the analytical technique used, a vast amount of data is always acquired when carrying out metabolomics studies; this results in complex datasets with large amounts of variables. This type of data requires multivariate statistical analysis for its proper biological interpretation. Prior to multivariate analysis, preprocessing of the data must be carried out to remove unwanted variation such as instrumental or experimental artifacts. This review aims to outline the steps in the preprocessing of NMR metabolomics data and describe some of the methods to perform these. Since using different preprocessing methods may produce different results, it is important that an appropriate pipeline exists for the selection of the optimal combination of methods in the preprocessing workflow.

  11. Loss of Merlin induces metabolomic adaptation that engages dependence on Hedgehog signaling.

    Science.gov (United States)

    Das, Shamik; Jackson, William P; Prasain, Jeevan K; Hanna, Ann; Bailey, Sarah K; Tucker, J Allan; Bae, Sejong; Wilson, Landon S; Samant, Rajeev S; Barnes, Stephen; Shevde, Lalita A

    2017-01-23

    The tumor suppressor protein Merlin is proteasomally degraded in breast cancer. We undertook an untargeted metabolomics approach to discern the global metabolomics profile impacted by Merlin in breast cancer cells. We discerned specific changes in glutathione metabolites that uncovered novel facets of Merlin in impacting the cancer cell metabolome. Concordantly, Merlin loss increased oxidative stress causing aberrant activation of Hedgehog signaling. Abrogation of GLI-mediated transcription activity compromised the aggressive phenotype of Merlin-deficient cells indicating a clear dependence of cells on Hedgehog signaling. In breast tumor tissues, GLI1 expression enhanced tissue identification and discriminatory power of Merlin, cumulatively presenting a powerful substantiation of the relationship between these two proteins. We have uncovered, for the first time, details of the tumor cell metabolomic portrait modulated by Merlin, leading to activation of Hedgehog signaling. Importantly, inhibition of Hedgehog signaling offers an avenue to target the vulnerability of tumor cells with loss of Merlin.

  12. Genome-Wide Prediction of SH2 Domain Targets Using Structural Information and the FoldX Algorithm

    DEFF Research Database (Denmark)

    Sanchez, Ignacio E.; Beltrao, Pedro; Stricher, Francois

    2008-01-01

    Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly to exper......Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly...... to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We...

  13. Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

    Science.gov (United States)

    Cheng, Susan; Shah, Svati H; Corwin, Elizabeth J; Fiehn, Oliver; Fitzgerald, Robert L; Gerszten, Robert E; Illig, Thomas; Rhee, Eugene P; Srinivas, Pothur R; Wang, Thomas J; Jain, Mohit

    2017-04-01

    Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine- N -oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine. © 2017 American Heart Association, Inc.

  14. Ewald: an extended wide-angle Laue diffractometer for the second target station of the Spallation Neutron Source.

    Science.gov (United States)

    Coates, Leighton; Robertson, Lee

    2017-08-01

    Visualizing hydrogen atoms in biological materials is one of the biggest remaining challenges in biophysical analysis. While X-ray techniques have unrivaled capacity for high-throughput structure determination, neutron diffraction is uniquely sensitive to hydrogen atom positions in crystals of biological materials and can provide a more complete picture of the atomic and electronic structures of biological macromolecules. This information can be essential in providing predictive understanding and engineering control of key biological processes, for example, in catalysis, ligand binding and light harvesting, and to guide bioengineering of enzymes and drug design. One very common and large capability gap for all neutron atomic resolution single-crystal diffractometers is the weak flux of available neutron beams, which results in limited signal-to-noise ratios giving a requirement for sample volumes of at least 0.1 mm3. The ability to operate on crystals an order of magnitude smaller (0.01 mm3) will open up new and more complex systems to studies with neutrons which will help in our understanding of enzyme mechanisms and enable us to improve drugs against multi resistant bacteria. With this is mind, an extended wide-angle Laue diffractometer, 'Ewald', has been designed, which can collect data using crystal volumes below 0.01 mm3.

  15. Computational prediction of the Crc regulon identifies genus-wide and species-specific targets of catabolite repression control in Pseudomonas bacteria

    LENUS (Irish Health Repository)

    Browne, Patrick

    2010-11-25

    Abstract Background Catabolite repression control (CRC) is an important global control system in Pseudomonas that fine tunes metabolism in order optimise growth and metabolism in a range of different environments. The mechanism of CRC in Pseudomonas spp. centres on the binding of a protein, Crc, to an A-rich motif on the 5\\' end of an mRNA resulting in translational down-regulation of target genes. Despite the identification of several Crc targets in Pseudomonas spp. the Crc regulon has remained largely unexplored. Results In order to predict direct targets of Crc, we used a bioinformatics approach based on detection of A-rich motifs near the initiation of translation of all protein-encoding genes in twelve fully sequenced Pseudomonas genomes. As expected, our data predict that genes related to the utilisation of less preferred nutrients, such as some carbohydrates, nitrogen sources and aromatic carbon compounds are targets of Crc. A general trend in this analysis is that the regulation of transporters is conserved across species whereas regulation of specific enzymatic steps or transcriptional activators are often conserved only within a species. Interestingly, some nucleoid associated proteins (NAPs) such as HU and IHF are predicted to be regulated by Crc. This finding indicates a possible role of Crc in indirect control over a subset of genes that depend on the DNA bending properties of NAPs for expression or repression. Finally, some virulence traits such as alginate and rhamnolipid production also appear to be regulated by Crc, which links nutritional status cues with the regulation of virulence traits. Conclusions Catabolite repression control regulates a broad spectrum of genes in Pseudomonas. Some targets are genus-wide and are typically related to central metabolism, whereas other targets are species-specific, or even unique to particular strains. Further study of these novel targets will enhance our understanding of how Pseudomonas bacteria integrate

  16. Genome-Wide Association Studies Reveal New Genetic Targets for Five Panicle Traits of International Rice Varieties

    Directory of Open Access Journals (Sweden)

    ZHANG Ya-fang

    2015-09-01

    Full Text Available Narrow genetic background is a key limiting factor in breeding stable high-yielding rice. The introduction and utilization of international rice core germplasm is an important way to increase the genetic diversity of domestic rice varieties. We conducted a genome-wide association study on 5 panicle traits of 315 rice accessions introduced from the international rice micro-core germplasm bank. Based on the tests from Yangzhou of China and Arkansas of American, environment exhibited a significant impacts on panicle length and primary branch number, while grain length, grain width and grain length/width ratio were insensitive to environment changes. We discovered a total of 7, 5, 10, 8 and 6 chromosomal regions or single nucleotide polymorphism marker loci that were significantly associated with primary branch number, panicle length, grain length, grain width and grain length/width ratio, respectively. Among them, eleven regions were associated with grain shape and one region associated with primary branch number, showing the good consistence in two different environments. Significant linear correlation was discovered between the average trait value and the number of favorable alleles carried by the varieties in all associated loci. Among the associated loci, varieties in aromatic and tropical japonica sub-groups possessed most favorable alleles, while those in temperate japonica sub-group contained the least. The domestic varieties mainly harbored unfavorable alleles in six of the associated loci being detected. On the contrary, 15 varieties from 11 different countries harbored more favorable alleles (as many as 30 or more than the others. Remarkably, all these 15 varieties belonged to the tropical japonica sub-group. In conclusion, our study demonstrates that varieties in the tropical japonica sub-group had high potentials for breeding stable high-yielding rice. Based on this discovery, we proposed a new approach for improving the panicle traits

  17. Food Metabolomics: Fact or Fiction?

    NARCIS (Netherlands)

    Coulier, L.; Tas, A.; Thissen, U.

    2011-01-01

    Comprehensive analysis of both volatile and non-volatile metabolites in food combined with information on sensory properties and multivariate statistics can be a valuable tool in understanding and improving the taste of food. Performing food metabolomics studies is, however, challenging and requires

  18. The future of NMR-based metabolomics.

    Science.gov (United States)

    Markley, John L; Brüschweiler, Rafael; Edison, Arthur S; Eghbalnia, Hamid R; Powers, Robert; Raftery, Daniel; Wishart, David S

    2017-02-01

    The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  19. Identification of the RNA recognition element of the RBPMS family of RNA-binding proteins and their transcriptome-wide mRNA targets

    Science.gov (United States)

    Farazi, Thalia A.; Leonhardt, Carl S.; Mukherjee, Neelanjan; Mihailovic, Aleksandra; Li, Song; Max, Klaas E.A.; Meyer, Cindy; Yamaji, Masashi; Cekan, Pavol; Jacobs, Nicholas C.; Gerstberger, Stefanie; Bognanni, Claudia; Larsson, Erik; Ohler, Uwe; Tuschl, Thomas

    2014-01-01

    Recent studies implicated the RNA-binding protein with multiple splicing (RBPMS) family of proteins in oocyte, retinal ganglion cell, heart, and gastrointestinal smooth muscle development. These RNA-binding proteins contain a single RNA recognition motif (RRM), and their targets and molecular function have not yet been identified. We defined transcriptome-wide RNA targets using photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) in HEK293 cells, revealing exonic mature and intronic pre-mRNA binding sites, in agreement with the nuclear and cytoplasmic localization of the proteins. Computational and biochemical approaches defined the RNA recognition element (RRE) as a tandem CAC trinucleotide motif separated by a variable spacer region. Similar to other mRNA-binding proteins, RBPMS family of proteins relocalized to cytoplasmic stress granules under oxidative stress conditions suggestive of a support function for mRNA localization in large and/or multinucleated cells where it is preferentially expressed. PMID:24860013

  20. Transcriptome-Wide Analysis of Botrytis elliptica Responsive microRNAs and Their Targets in Lilium Regale Wilson by High-Throughput Sequencing and Degradome Analysis

    Directory of Open Access Journals (Sweden)

    Xue Gao

    2017-05-01

    Full Text Available MicroRNAs, as master regulators of gene expression, have been widely identified and play crucial roles in plant-pathogen interactions. A fatal pathogen, Botrytis elliptica, causes the serious folia disease of lily, which reduces production because of the high susceptibility of most cultivated species. However, the miRNAs related to Botrytis infection of lily, and the miRNA-mediated gene regulatory networks providing resistance to B. elliptica in lily remain largely unexplored. To systematically dissect B. elliptica-responsive miRNAs and their target genes, three small RNA libraries were constructed from the leaves of Lilium regale, a promising Chinese wild Lilium species, which had been subjected to mock B. elliptica treatment or B. elliptica infection for 6 and 24 h. By high-throughput sequencing, 71 known miRNAs belonging to 47 conserved families and 24 novel miRNA were identified, of which 18 miRNAs were downreguleted and 13 were upregulated in response to B. elliptica. Moreover, based on the lily mRNA transcriptome, 22 targets for 9 known and 1 novel miRNAs were identified by the degradome sequencing approach. Most target genes for elliptica-responsive miRNAs were involved in metabolic processes, few encoding different transcription factors, including ELONGATION FACTOR 1 ALPHA (EF1a and TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR 2 (TCP2. Furthermore, the expression patterns of a set of elliptica-responsive miRNAs and their targets were validated by quantitative real-time PCR. This study represents the first transcriptome-based analysis of miRNAs responsive to B. elliptica and their targets in lily. The results reveal the possible regulatory roles of miRNAs and their targets in B. elliptica interaction, which will extend our understanding of the mechanisms of this disease in lily.

  1. A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units

    Directory of Open Access Journals (Sweden)

    Kui Liu

    2017-02-01

    Full Text Available This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI. More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©. The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs. The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

  2. A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units.

    Science.gov (United States)

    Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

    2017-02-12

    This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

  3. Genome-wide Investigation of microRNAs and Their Targets in Brassica rapa ssp. pekinensis Root with Plasmodiophora brassicae Infection

    Directory of Open Access Journals (Sweden)

    Xiaochun Wei

    2016-07-01

    Full Text Available Increasing evidence has revealed that microRNAs play a pivotal role in the post transcriptional regulation of gene expression in response to pathogens in plants. However, there is little information available about the expression patterns of miRNAs and their targets in Chinese cabbage (Brassica rapa ssp. pekinensis under Plasmodiophora brassicae stress. In the present study, using deep sequencing and degradome analysis, a genome-wide identification of miRNAs and their targets during P. brassicae stress was performed. A total of 221 known and 93 potentially novel miRNAs were successfully identified from two root libraries of one control (635-10CK and P. brassicae-treated Chinese cabbage samples (635-10T. Of these, 14 known and 10 potentially novel miRNAs were found to be differentially expressed after P. brassicae treatment. Degradome analysis revealed that the 223 target genes of the 75 miRNAs could be potentially cleaved. KEGG (Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that the putative target genes of the miRNAs were predominately involved in selenocompound metabolism and plant hormone signal transduction. Then the expression of 12 miRNAs was validated by quantitative real-time PCR (qRT-PCR. These results provide insights into the miRNA-mediated regulatory networks underlying the stress response to the plant pathogen P. brassicae.

  4. Nuclear magnetic resonance spectroscopy based metabolomics to identify novel biomarkers of alcohol-dependence

    Directory of Open Access Journals (Sweden)

    Hamza Mostafa

    2017-04-01

    Full Text Available Alcohol misuse is a ravaging public health and social problem. Its harm can affect the drinkers and the whole society. Alcohol-dependence is a phase of alcohol misuse in which the drinker consumes excessive amounts of alcohol and has a continuous urge to consume alcohol. Current methods of alcohol dependence diagnoses are questionnaires and some biomarkers. However, both methods lack specificity and sensitivity. Metabolomics is a scientific field which deals with the identification and the quantification of the metabolites present in the metabolome using spectroscopic techniques such as nuclear magnetic resonance (NMR. Metabolomics helps to indicate the perturbation in the levels of metabolites in cells and tissues due to diseases or ingestion of any substances. NMR is one of the most widely used spectroscopic techniques in metabolomics because of its reproducibility and speed. Some recent metabolomics studies were conducted on alcohol consumption and alcohol misuse in animals and humans. However, few focused on identifying alcohol dependence novel biomarkers. A sensitive and specific technique such as NMR based metabolomics applied to find novel biomarkers in plasma and urine can be useful to diagnose alcohol-dependence.

  5. Metabolomics as a tool to identify biomarkers to predict and improve outcomes in reproductive medicine: a systematic review.

    Science.gov (United States)

    Bracewell-Milnes, Timothy; Saso, Srdjan; Abdalla, Hossam; Nikolau, Dimitrios; Norman-Taylor, Julian; Johnson, Mark; Holmes, Elaine; Thum, Meen-Yau

    2017-11-01

    reproductive tract, with a summary of the current findings, promise and pitfalls in metabolomic techniques. The approaches discussed can be adapted by other metabolomic studies. A range of sophisticated modern metabolomic techniques are now more widely available and have been applied to the analysis of the female reproductive tract. However, this review has revealed the paucity of metabolomic studies in the field of fertility and the inconsistencies of findings between different studies, as well as a lack of research examining the metabolic effects of various gynecological diseases. By incorporating metabolomic technology into an increased number of well designed studies, a much greater understanding of infertility at a molecular level could be achieved. However, there is currently no evidence for the use of metabolomics in clinical practice to improve fertility outcomes.

  6. MetaboLights: An Open-Access Database Repository for Metabolomics Data.

    Science.gov (United States)

    Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

    2016-03-24

    MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

  7. NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review.

    Science.gov (United States)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M C; Wijmenga, Sybren S

    2012-10-31

    Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl). Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Applications of Metabolomics in Cancer Studies.

    Science.gov (United States)

    Armitage, Emily Grace; Ciborowski, Michal

    2017-01-01

    Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

  9. Metabolomics of Clostridial Biofuel Production

    Energy Technology Data Exchange (ETDEWEB)

    Rabinowitz, Joshua D [Princeton Univ., NJ (United States); Aristilde, Ludmilla [Cornell Univ., Ithaca, NY (United States); Amador-Noguez, Daniel [Univ. of Wisconsin, Madison, WI (United States)

    2015-09-08

    Members of the genus Clostridium collectively have the ideal set of the metabolic capabilities for fermentative biofuel production: cellulose degradation, hydrogen production, and solvent excretion. No single organism, however, can effectively convert cellulose into biofuels. Here we developed, using metabolomics and isotope tracers, basic science knowledge of Clostridial metabolism of utility for future efforts to engineer such an organism. In glucose fermentation carried out by the biofuel producer Clostridium acetobutylicum, we observed a remarkably ordered series of metabolite concentration changes as the fermentation progressed from acidogenesis to solventogenesis. In general, high-energy compounds decreased while low-energy species increased during solventogenesis. These changes in metabolite concentrations were accompanied by large changes in intracellular metabolic fluxes, with pyruvate directed towards acetyl-CoA and solvents instead of oxaloacetate and amino acids. Thus, the solventogenic transition involves global remodeling of metabolism to redirect resources from biomass production into solvent production. In contrast to C. acetobutylicum, which is an avid fermenter, C. cellulolyticum metabolizes glucose only slowly. We find that glycolytic intermediate concentrations are radically different from fast fermenting organisms. Associated thermodynamic and isotope tracer analysis revealed that the full glycolytic pathway in C. cellulolyticum is reversible. This arises from changes in cofactor utilization for phosphofructokinase and an alternative pathway from phosphoenolpyruvate to pyruvate. The net effect is to increase the high-energy phosphate bond yield of glycolysis by 150% (from 2 to 5) at the expense of lower net flux. Thus, C. cellulolyticum prioritizes glycolytic energy efficiency over speed. Degradation of cellulose results in other sugars in addition to glucose. Simultaneous feeding of stable isotope-labeled glucose and unlabeled pentose sugars

  10. Gender-specific pathway differences in the human serum metabolome.

    Science.gov (United States)

    Krumsiek, Jan; Mittelstrass, Kirstin; Do, Kieu Trinh; Stückler, Ferdinand; Ried, Janina; Adamski, Jerzy; Peters, Annette; Illig, Thomas; Kronenberg, Florian; Friedrich, Nele; Nauck, Matthias; Pietzner, Maik; Mook-Kanamori, Dennis O; Suhre, Karsten; Gieger, Christian; Grallert, Harald; Theis, Fabian J; Kastenmüller, Gabi

    The susceptibility for various diseases as well as the response to treatments differ considerably between men and women. As a basis for a gender-specific personalized healthcare, an extensive characterization of the molecular differences between the two genders is required. In the present study, we conducted a large-scale metabolomics analysis of 507 metabolic markers measured in serum of 1756 participants from the German KORA F4 study (903 females and 853 males). One-third of the metabolites show significant differences between males and females. A pathway analysis revealed strong differences in steroid metabolism, fatty acids and further lipids, a large fraction of amino acids, oxidative phosphorylation, purine metabolism and gamma-glutamyl dipeptides. We then extended this analysis by a network-based clustering approach. Metabolite interactions were estimated using Gaussian graphical models to get an unbiased, fully data-driven metabolic network representation. This approach is not limited to possibly arbitrary pathway boundaries and can even include poorly or uncharacterized metabolites. The network analysis revealed several strongly gender-regulated submodules across different pathways. Finally, a gender-stratified genome-wide association study was performed to determine whether the observed gender differences are caused by dimorphisms in the effects of genetic polymorphisms on the metabolome. With only a single genome-wide significant hit, our results suggest that this scenario is not the case. In summary, we report an extensive characterization and interpretation of gender-specific differences of the human serum metabolome, providing a broad basis for future analyses.

  11. Dynamic metabolomic data analysis: a tutorial review.

    Science.gov (United States)

    Smilde, A K; Westerhuis, J A; Hoefsloot, H C J; Bijlsma, S; Rubingh, C M; Vis, D J; Jellema, R H; Pijl, H; Roelfsema, F; van der Greef, J

    2010-03-01

    In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic metabolomic data. Moreover, some methods from other fields of science that may be of use to analyze such dynamic metabolomics data are described in some detail. The methods are put in a general framework after providing a formal definition on what constitutes a 'dynamic' method. Some of the methods are illustrated with real-life metabolomics examples.

  12. NMR-Based Metabolomics of Oral Biofluids.

    Science.gov (United States)

    Schirra, Horst Joachim; Ford, Pauline J

    2017-01-01

    NMR-based metabolomics is an established technique for characterizing the metabolite profile of biological fluids and investigating how metabolite profiles change in response to biological and/or clinical stimuli. Thus, NMR-based metabolomics has the potential to discover biomarkers for diagnosis, prognosis, and/or therapy of clinical conditions, as well as to unravel the physiology underlying clinical conditions. Here, we describe a detailed protocol for NMR-based metabolomics of oral biofluids, including sample collection, sample handling, NMR data acquisition, and processing. In addition, we give a general overview of the statistical analysis of the resulting metabolomic data.

  13. ChIP-seq defined genome-wide map of TGFβ/SMAD4 targets: implications with clinical outcome of ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Brian A Kennedy

    Full Text Available Deregulation of the transforming growth factor-β (TGFβ signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGFβ signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq to investigate genome-wide screening of TGFβ-induced SMAD4 binding in epithelial ovarian cancer. Following TGFβ stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1 Basal; 2 Shift; 3 Stimulated Only; 4 Unstimulated Only. TGFβ stimulated SMAD4-bound loci were primarily classified as either Stimulated only (74% or Shift (25%, indicating that TGFβ-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells. Furthermore, based on gene regulatory network analysis, we determined that the TGFβ-induced, SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGFβ/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer and link aberrant TGFβ/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers.

  14. Genome-wide mapping indicates that p73 and p63 co-occupy target sites and have similar dna-binding profiles in vivo.

    Directory of Open Access Journals (Sweden)

    Annie Yang

    2010-07-01

    Full Text Available The p53 homologs, p63 and p73, share approximately 85% amino acid identity in their DNA-binding domains, but they have distinct biological functions.Using chromatin immunoprecipitation and high-resolution tiling arrays covering the human genome, we identify p73 DNA binding sites on a genome-wide level in ME180 human cervical carcinoma cells. Strikingly, the p73 binding profile is indistinguishable from the previously described binding profile for p63 in the same cells. Moreover, the p73:p63 binding ratio is similar at all genomic loci tested, suggesting that there are few, if any, targets that are specific for one of these factors. As assayed by sequential chromatin immunoprecipitation, p63 and p73 co-occupy DNA target sites in vivo, suggesting that p63 and p73 bind primarily as heterotetrameric complexes in ME180 cells.The observation that p63 and p73 associate with the same genomic targets suggest that their distinct biological functions are due to cell-type specific expression and/or protein domains that involve functions other than DNA binding.

  15. An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

    Directory of Open Access Journals (Sweden)

    Tingting Jin

    2017-04-01

    Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

  16. Functional metabolomics reveals novel active products in the DHA metabolome

    Directory of Open Access Journals (Sweden)

    Masakazu eShinohara

    2012-04-01

    Full Text Available Endogenous mechanisms for successful resolution of an acute inflammatory response and the local return to homeostasis are of interest because excessive inflammation underlies many human diseases. In this review, we provide an update and overview of functional metabolomics that identified a new bioactive metabolome of docosahexaenoic acid (DHA. Systematic studies revealed that DHA was converted to DHEA-derived novel bioactive products as well as aspirin-triggered (AT forms of protectins. The new oxygenated DHEA derived products blocked PMN chemotaxis, reduced P-selectin expression and platelet-leukocyte adhesion, and showed organ protection in ischemia/reperfusion injury. These products activated cannabinoid receptor (CB2 receptor and not CB1 receptors. The AT-PD1 reduced neutrophil (PMN recruitment in murine peritonitis. With human cells, AT-PD1 decreased transendothelial PMN migration as well as enhanced efferocytosis of apoptotic human PMN by macrophages. The recent findings reviewed here indicate that DHEA oxidative metabolism and aspirin-triggered conversion of DHA produce potent novel molecules with anti-inflammatory and organ-protective properties, opening the DHA metabolome functional roles.

  17. A systems-wide comparison of red rice (Oryza longistaminata) tissues identifies rhizome specific genes and proteins that are targets for cultivated rice improvement.

    Science.gov (United States)

    He, Ruifeng; Salvato, Fernanda; Park, Jeong-Jin; Kim, Min-Jeong; Nelson, William; Balbuena, Tiago S; Willer, Mark; Crow, John A; May, Greg D; Soderlund, Carol A; Thelen, Jay J; Gang, David R

    2014-02-12

    The rhizome, the original stem of land plants, enables species to invade new territory and is a critical component of perenniality, especially in grasses. Red rice (Oryza longistaminata) is a perennial wild rice species with many valuable traits that could be used to improve cultivated rice cultivars, including rhizomatousness, disease resistance and drought tolerance. Despite these features, little is known about the molecular mechanisms that contribute to rhizome growth, development and function in this plant. We used an integrated approach to compare the transcriptome, proteome and metabolome of the rhizome to other tissues of red rice. 116 Gb of transcriptome sequence was obtained from various tissues and used to identify rhizome-specific and preferentially expressed genes, including transcription factors and hormone metabolism and stress response-related genes. Proteomics and metabolomics approaches identified 41 proteins and more than 100 primary metabolites and plant hormones with rhizome preferential accumulation. Of particular interest was the identification of a large number of gene transcripts from Magnaportha oryzae, the fungus that causes rice blast disease in cultivated rice, even though the red rice plants showed no sign of disease. A significant set of genes, proteins and metabolites appear to be specifically or preferentially expressed in the rhizome of O. longistaminata. The presence of M. oryzae gene transcripts at a high level in apparently healthy plants suggests that red rice is resistant to this pathogen, and may be able to provide genes to cultivated rice that will enable resistance to rice blast disease.

  18. NMR-based milk metabolomics

    DEFF Research Database (Denmark)

    Sundekilde, Ulrik; Larsen, Lotte Bach; Bertram, Hanne Christine S.

    2013-01-01

    Milk is a key component in infant nutrition worldwide and, in the Western parts of the world, also in adult nutrition. Milk of bovine origin is both consumed fresh and processed into a variety of dairy products including cheese, fermented milk products, and infant formula. The nutritional quality...... and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking...... the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive...

  19. Metabolomics investigation of whey intake

    DEFF Research Database (Denmark)

    Stanstrup, Jan

    interest since it has been shown that it is possible to achieve greater weight loss on a high protein diet as oppose to a high carbohydrate diet. Furthermore, it has been demonstrated that specifically milk-derived whey proteins have certain biological properties that might be beneficial in the treatment...... syndrome are complex disorders and are not caused by a high-calorie diet and low exercise level alone. The specific nature of the nutrients, independent of their caloric value, also play a role. The question is which. In the quest to answer this question the qualitative intake of protein is of special...... and prevention of the metabolic syndrome related to obesity and diabetes. In this thesis the effects of whey intake on the human metabolome was investigated using a metabolomics approach. We demonstrated that intake of whey causes a decreased rate of gastric emptying compared to other protein sources...

  20. A resource for characterizing genome-wide binding and putative target genes of transcription factors expressed during secondary growth and wood formation in Populus.

    Science.gov (United States)

    Liu, Lijun; Ramsay, Trevor; Zinkgraf, Matthew; Sundell, David; Street, Nathaniel Robert; Filkov, Vladimir; Groover, Andrew

    2015-06-01

    Identifying transcription factor target genes is essential for modeling the transcriptional networks underlying developmental processes. Here we report a chromatin immunoprecipitation sequencing (ChIP-seq) resource consisting of genome-wide binding regions and associated putative target genes for four Populus homeodomain transcription factors expressed during secondary growth and wood formation. Software code (programs and scripts) for processing the Populus ChIP-seq data are provided within a publically available iPlant image, including tools for ChIP-seq data quality control and evaluation adapted from the human Encyclopedia of DNA Elements (ENCODE) project. Basic information for each transcription factor (including members of Class I KNOX, Class III HD ZIP, BEL1-like families) binding are summarized, including the number and location of binding regions, distribution of binding regions relative to gene features, associated putative target genes, and enriched functional categories of putative target genes. These ChIP-seq data have been integrated within the Populus Genome Integrative Explorer (PopGenIE) where they can be analyzed using a variety of web-based tools. We present an example analysis that shows preferential binding of transcription factor ARBORKNOX1 to the nearest neighbor genes in a pre-calculated co-expression network module, and enrichment for meristem-related genes within this module including multiple orthologs of Arabidopsis KNOTTED-like Arabidopsis 2/6. © 2015 Society for Experimental Biology and John Wiley & Sons Ltd This article has been contributed to by US Government employees and their work is in the public domain in the USA.

  1. Long-range and depth-selective imaging of macroscopic targets using low-coherence and wide-field interferometry (Conference Presentation)

    Science.gov (United States)

    Woo, Sungsoo; Kang, Sungsam; Yoon, Changhyeong; Choi, Wonshik

    2016-03-01

    With the advancement of 3D display technology, 3D imaging of macroscopic objects has drawn much attention as they provide the contents to display. The most widely used imaging methods include a depth camera, which measures time of flight for the depth discrimination, and various structured illumination techniques. However, these existing methods have poor depth resolution, which makes imaging complicated structures a difficult task. In order to resolve this issue, we propose an imaging system based upon low-coherence interferometry and off-axis digital holographic imaging. By using light source with coherence length of 200 micro, we achieved the depth resolution of 100 micro. In order to map the macroscopic objects with this high axial resolution, we installed a pair of prisms in the reference beam path for the long-range scanning of the optical path length. Specifically, one prism was fixed in position, and the other prism was mounted on a translation stage and translated in parallel to the first prism. Due to the multiple internal reflections between the two prisms, the overall path length was elongated by a factor of 50. In this way, we could cover a depth range more than 1 meter. In addition, we employed multiple speckle illuminations and incoherent averaging of the acquired holographic images for reducing the specular reflections from the target surface. Using this newly developed system, we performed imaging targets with multiple different layers and demonstrated imaging targets hidden behind the scattering layers. The method was also applied to imaging targets located around the corner.

  2. [The use of metabolomics in medicine - some examples of oncological and metabolic diseases].

    Science.gov (United States)

    Zimny, Dominika; Szatkowska, Marta; Połubok, Joanna; Maciaszek, Julian; Machaj, Mikołaj; Barg, Ewa

    2015-01-01

    Metabolomics is a new field of medicine focused on examining and analyzing metabolites produced in biological cells. Biological fluids primarily used in this method include: plasma, cerebrospinal fluid, saliva and urine. The most common methods of evaluating the composition involve nuclear magnetic resonance (NMR) and magnetic resonance (MR) with addition of gas chromatography (GC-MS) or liquid chromatography (LC-MS). Metabolomics is used in a wide variety of medicine disciplines. The variability of biochemical processes in tumor cells in comparison to normal cells is the starting point of such studies. The metabolomic changes are observed not only in solid tumors, like the mammary tumor, ovarian cancer, prostate cancer but also in tumors of the hematopoietic and lymphoid tissues. Nowadays, the aim of studies is to find biomarkers which would help to diagnose a disease quickly, assess its progression, and implement effective treatment. Metabolomics is also widely applied in metabolic diseases, mainly the diabetes. The list of examined metabolites gives promising chances for a successful prognosis, diagnosis and comprehensive monitoring of the progression of this civilization disease. The development of metabolomics will also contribute to the individualization of treatment, proper drugs adjustment, which will make a therapy more successful, cause less side effects and improve the quality of patient's life. © Polish Society for Pediatric Endocrinology and Diabetology.

  3. Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology.

    Science.gov (United States)

    Wood, Paul L

    2014-01-01

    Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed.

  4. Sweat: a sample with limited present applications and promising future in metabolomics.

    Science.gov (United States)

    Mena-Bravo, A; Luque de Castro, M D

    2014-03-01

    Sweat is a biofluid with present scant use as clinical sample. This review tries to demonstrate the advantages of sweat over other biofluids such as blood or urine for routine clinical analyses and the potential when related to metabolomics. With this aim, critical discussion of sweat samplers and equipment for analysis of target compounds in this sample is made. Well established routine analyses in sweat as is that to diagnose cystic fibrosis, and the advantages and disadvantages of sweat versus urine or blood for doping control have also been discussed. Methods for analytes such as essential metals and xenometals, ethanol and electrolytes in sweat in fact constitute target metabolomics approaches or belong to any metabolomics subdiscipline such as metallomics, ionomics or xenometabolomics. The higher development of biomarkers based on genomics or proteomics as omics older than metabolomics is discussed and also the potential role of metabolomics in systems biology taking into account its emergent implementation. Normalization of the volume of sampled sweat constitutes a present unsolved shortcoming that deserves investigation. Foreseeable trends in this area are outlined. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Development of isotope labeling liquid chromatography mass spectrometry for mouse urine metabolomics: quantitative metabolomic study of transgenic mice related to Alzheimer's disease.

    Science.gov (United States)

    Peng, Jun; Guo, Kevin; Xia, Jianguo; Zhou, Jianjun; Yang, Jing; Westaway, David; Wishart, David S; Li, Liang

    2014-10-03

    Because of a limited volume of urine that can be collected from a mouse, it is very difficult to apply the common strategy of using multiple analytical techniques to analyze the metabolites to increase the metabolome coverage for mouse urine metabolomics. We report an enabling method based on differential isotope labeling liquid chromatography mass spectrometry (LC-MS) for relative quantification of over 950 putative metabolites using 20 μL of urine as the starting material. The workflow involves aliquoting 10 μL of an individual urine sample for ¹²C-dansylation labeling that target amines and phenols. Another 10 μL of aliquot was taken from each sample to generate a pooled sample that was subjected to ¹³C-dansylation labeling. The ¹²C-labeled individual sample was mixed with an equal volume of the ¹³C-labeled pooled sample. The mixture was then analyzed by LC-MS to generate information on metabolite concentration differences among different individual samples. The interday repeatability for the LC-MS runs was assessed, and the median relative standard deviation over 4 days was 5.0%. This workflow was then applied to a metabolomic biomarker discovery study using urine samples obtained from the TgCRND8 mouse model of early onset familial Alzheimer's disease (FAD) throughout the course of their pathological deposition of beta amyloid (Aβ). It was showed that there was a distinct metabolomic separation between the AD prone mice and the wild type (control) group. As early as 15-17 weeks of age (presymptomatic), metabolomic differences were observed between the two groups, and after the age of 25 weeks the metabolomic alterations became more pronounced. The metabolomic changes at different ages corroborated well with the phenotype changes in this transgenic mice model. Several useful candidate biomarkers including methionine, desaminotyrosine, taurine, N1-acetylspermidine, and 5-hydroxyindoleacetic acid were identified. Some of them were found in previous

  6. Symbiosis of chemometrics and metabolomics: Past, present, and future

    NARCIS (Netherlands)

    Greef, J. van der; Smilde, A.K.

    2005-01-01

    Metabolomics is a growing area in the field of systems biology. Metabolomics has already a long history and also the connection of metabolomics with chemometrics goes back some time. This review discusses the symbiosis of metabolomics and chemometrics with emphasis on the medical domain, puts the

  7. The future of metabolomics in ELIXIR.

    Science.gov (United States)

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B; Ebbels, Timothy M D; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L; Jimenez, Rafael C; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K; Neumann, Steffen; O'Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A; Spjuth, Ola; Thévenot, Etienne A; Viant, Mark R; Weber, Ralf J M; Willighagen, Egon L; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

  8. The future of metabolomics in ELIXIR

    Science.gov (United States)

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B.; Ebbels, Timothy M. D.; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L.; Jimenez, Rafael C.; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I.; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moschonas, Nicholas K.; Neumann, Steffen; O’Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M.; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A.; Spjuth, Ola; Thévenot, Etienne A.; Viant, Mark R.; Weber, Ralf J. M.; Willighagen, Egon L.; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. PMID:29043062

  9. Metabolomics of a model fruit: tomato

    NARCIS (Netherlands)

    Vos, de R.C.H.; Hall, R.D.; Moing, A.

    2011-01-01

    Tomato has quickly become a favoured species for metabolomics research. Tomato fills a niche that cannot be occupied by Arabidopsis, particularly regarding studies on fleshy fruit. Variations in genotype and phenotype have been broadly exploited using metabolomics approaches in order to gain a

  10. Identification of the RNA recognition element of the RBPMS family of RNA-binding proteins and their transcriptome-wide mRNA targets.

    Science.gov (United States)

    Farazi, Thalia A; Leonhardt, Carl S; Mukherjee, Neelanjan; Mihailovic, Aleksandra; Li, Song; Max, Klaas E A; Meyer, Cindy; Yamaji, Masashi; Cekan, Pavol; Jacobs, Nicholas C; Gerstberger, Stefanie; Bognanni, Claudia; Larsson, Erik; Ohler, Uwe; Tuschl, Thomas

    2014-07-01

    Recent studies implicated the RNA-binding protein with multiple splicing (RBPMS) family of proteins in oocyte, retinal ganglion cell, heart, and gastrointestinal smooth muscle development. These RNA-binding proteins contain a single RNA recognition motif (RRM), and their targets and molecular function have not yet been identified. We defined transcriptome-wide RNA targets using photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) in HEK293 cells, revealing exonic mature and intronic pre-mRNA binding sites, in agreement with the nuclear and cytoplasmic localization of the proteins. Computational and biochemical approaches defined the RNA recognition element (RRE) as a tandem CAC trinucleotide motif separated by a variable spacer region. Similar to other mRNA-binding proteins, RBPMS family of proteins relocalized to cytoplasmic stress granules under oxidative stress conditions suggestive of a support function for mRNA localization in large and/or multinucleated cells where it is preferentially expressed. © 2014 Farazi et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  11. Integration of genome-wide of Stat3 binding and epigenetic modification mapping with transcriptome reveals novel Stat3 target genes in glioma cells.

    Science.gov (United States)

    Kruczyk, Marcin; Przanowski, Piotr; Dabrowski, Michal; Swiatek-Machado, Karolina; Mieczkowski, Jakub; Wallerman, Ola; Ronowicz, Anna; Piotrowski, Arkadiusz; Wadelius, Claes; Kaminska, Bozena; Komorowski, Jan

    2014-11-01

    Signal transducer and activator of transcription 3 (STAT3) is constitutively activated in many human tumors, including gliomas, and regulates the expression of genes implicated in proliferation, survival, apoptosis, angiogenesis and immune regulation. Only a small fraction of those genes has been proven to be direct STAT3 targets. In gliomas, STAT3 can play tumor suppressive or oncogenic roles depending on the tumor genetic background with target genes being largely unknown. We used chromatin immunoprecipitation, promoter microarrays and deep sequencing to assess the genome-wide occupancy of phospho (p)-Stat3 and epigenetic modifications of H3K4me3 and H3ac in C6 glioma cells. This combined assessment identified a list of 1200 genes whose promoters have both Stat3 binding sites and epigenetic marks characteristic for actively transcribed genes. The Stat3 and histone markings data were also intersected with a set of microarray data from C6 glioma cells after inhibition of Jak2/Stat3 signaling. Subsequently, we found 284 genes characterized by p-Stat3 occupancy, activating histone marks and transcriptional changes. Novel genes were screened for their potential involvement in oncogenesis, and the most interesting hits were verified by ChIP-PCR and STAT3 knockdown in human glioma cells. Non-random association between silent genes, histone marks and p-Stat3 binding near transcription start sites was observed, consistent with its repressive role in transcriptional regulation of target genes in glioma cells with specific genetic background. Copyright © 2014. Published by Elsevier B.V.

  12. Targeted capture sequencing in whitebark pine reveals range-wide demographic and adaptive patterns despite challenges of a large, repetitive genome

    Directory of Open Access Journals (Sweden)

    John eSyring

    2016-04-01

    Full Text Available Whitebark pine (Pinus albicaulis inhabits an expansive range in western North America, and it is a keystone species of subalpine environments. Whitebark is susceptible to multiple threats – climate change, white pine blister rust, mountain pine beetle, and fire exclusion – and it is suffering significant mortality range-wide, prompting the tree to be listed as ‘globally endangered’ by the International Union for Conservation of Nature (IUCN and ‘endangered’ by the Canadian government. Conservation collections (in situ and ex situ are being initiated to preserve the genetic legacy of the species. Reliable, transferrable, and highly variable genetic markers are essential for quantifying the genetic profiles of seed collections relative to natural stands, and ensuring the completeness of conservation collections. We evaluated the use of hybridization-based target capture to enrich specific genomic regions from the 30+ GB genome of whitebark pine, and to evaluate genetic variation across loci, trees, and geography. Probes were designed to capture 7,849 distinct genes, and screening was performed on 48 trees. Despite the inclusion of repetitive elements in the probe pool, the resulting dataset provided information on 4,452 genes and 32% of targeted positions (528,873 bp, and we were able to identify 12,390 segregating sites from 47 trees. Variations reveal strong geographic trends in heterozygosity and allelic richness, with trees from the southern Cascade and Sierra Range showing the greatest distinctiveness and differentiation. Our results show that even under non-optimal conditions (low enrichment efficiency; inclusion of repetitive elements in baits, targeted enrichment produces high quality, codominant genotypes from large genomes. The resulting data can be readily integrated into management and gene conservation activities for whitebark pine, and have the potential to be applied to other members of 5-needle pine group (Pinus subsect

  13. NMR Metabolomics Analysis of Parkinson's Disease

    Science.gov (United States)

    Lei, Shulei; Powers, Robert

    2015-01-01

    Parkinson's disease (PD) is a neurodegenerative disease, which is characterized by progressive death of dopaminergic neurons in the substantia nigra pars compacta. Although mitochondrial dysfunction and oxidative stress are linked to PD pathogenesis, its etiology and pathology remain to be elucidated. Metabolomics investigates metabolite changes in biofluids, cell lysates, tissues and tumors in order to correlate these metabolomic changes to a disease state. Thus, the application of metabolomics to investigate PD provides a systematic approach to understand the pathology of PD, to identify disease biomarkers, and to complement genomics, transcriptomics and proteomics studies. This review will examine current research into PD mechanisms with a focus on mitochondrial dysfunction and oxidative stress. Neurotoxin-based PD animal models and the rationale for metabolomics studies in PD will also be discussed. The review will also explore the potential of NMR metabolomics to address important issues related to PD treatment and diagnosis. PMID:26078917

  14. A Metabolomic Perspective on Coeliac Disease

    Directory of Open Access Journals (Sweden)

    Antonio Calabrò

    2014-01-01

    Full Text Available Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism.

  15. anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data

    Directory of Open Access Journals (Sweden)

    Zamboni Nicola

    2008-04-01

    Full Text Available Abstract Background Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification extremely difficult. Furthermore, not only the actual measurement but also the subsequent interpretation of quantitative metabolome data to obtain mechanistic insights is still lacking behind the current expectations. Recently, the method of network-embedded thermodynamic (NET analysis was introduced to address some of these open issues. Building upon principles of thermodynamics, this method allows for a quality check of measured metabolite concentrations and enables to spot metabolic reactions where active regulation potentially controls metabolic flux. So far, however, widespread application of NET analysis in metabolomics labs was hindered by the absence of suitable software. Results We have developed in Matlab a generalized software called 'anNET' that affords a user-friendly implementation of the NET analysis algorithm. anNET supports the analysis of any metabolic network for which a stoichiometric model can be compiled. The model size can span from a single reaction to a complete genome-wide network reconstruction including compartments. anNET can (i test quantitative data sets for thermodynamic consistency, (ii predict metabolite concentrations beyond the actually measured data, (iii identify putative sites of active regulation in the metabolic reaction network, and (iv help in localizing errors in data sets that were found to be thermodynamically infeasible. We demonstrate the application of anNET with three published Escherichia coli metabolome data sets. Conclusion Our user-friendly and generalized implementation of the NET analysis method in the software anNET allows users to rapidly integrate quantitative metabolome data obtained from virtually any organism. We envision that use of anNET in labs working on quantitative metabolomics will provide the

  16. Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics

    NARCIS (Netherlands)

    Wilmes, Anja; Bielow, Chris; Ranninger, Christina; Bellwon, Patricia; Aschauer, Lydia; Limonciel, Alice; Chassaigne, Hubert; Kristl, Theresa; Aiche, Stephan; Huber, Christian G; Guillou, Claude; Hewitt, Philipp; Leonard, Martin O; Dekant, Wolfgang; Bois, Frederic Y; Jennings, Paul

    2015-01-01

    Cisplatin is one of the most widely used chemotherapeutic agents for the treatment of solid tumours. The major dose-limiting factor is nephrotoxicity, in particular in the proximal tubule. Here, we use an integrated omics approach, including transcriptomics, proteomics and metabolomics coupled to

  17. Target-based metabolomics for the quantitative measurement of 37 pathway metabolites in rat brain and serum using hydrophilic interaction ultra-high-performance liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Chen, Jiahui; Hou, Waner; Han, Bo; Liu, Guanghui; Gong, Jin; Li, Yemeng; Zhong, Danmin; Liao, Qiongfeng; Xie, Zhiyong

    2016-04-01

    Amino acids, neurotransmitters, purines, and pyrimidines are bioactive molecules that play fundamental roles in maintaining various physiological functions. Their metabolism is closely related to the health, growth, development, reproduction, and homeostasis of organisms. Most recently, comprehensive measurements of these metabolites have shown their potential as innovative approaches in disease surveillance or drug intervention. However, simultaneous measurement of these metabolites presents great difficulties. Here, we report a novel quantitative method that uses hydrophilic interaction ultra-high-performance liquid chromatography-tandem mass spectrometry (HILIC-UPLC-MS/MS), which is highly selective, high throughput, and exhibits better chromatographic behavior than existing methods. The developed method enabled the rapid quantification of 37 metabolites, spanning amino acids, neurotransmitters, purines, and pyrimidines pathways, within 6.5 min. The compounds were separated on an ACQUITY UPLC® BEH Amide column. Serum and brain homogenate were extracted by protein precipitation. The intra- and interday precision of all of the analytes was less than 11.34 %, and the accuracy was between -11.74 and 11.51 % for all quality control (QC) levels. The extraction recoveries of serum ranged from 84.58 % to 116.43 % and those of brain samples from 80.80 % to 119.39 %, while the RSD was 14.61 % or less for all recoveries. This method was used to successfully characterize alterations in the rat brain and, in particular, their dynamics in serum. The following study was performed to simultaneously test global changes of these metabolites in a serotonin antagonist p-chlorophenylalanine (PCPA)-induced anxiety and insomnia rat model to understand the effect and mechanism of PCPA. Taken together, these results show that the method is able to simultaneously monitor a large panel of metabolites and that this protocol may represent a metabolomic method to diagnose toxicological and

  18. Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling

    Directory of Open Access Journals (Sweden)

    Craigon Marie

    2009-08-01

    Full Text Available Abstract Background Interferons (IFNs are potent antiviral cytokines capable of reprogramming the macrophage phenotype through the induction of interferon-stimulated genes (ISGs. Here we have used targeted RNA interference to suppress the expression of a number of key genes associated with IFN signalling in murine macrophages prior to stimulation with interferon-gamma. Genome-wide changes in transcript abundance caused by siRNA activity were measured using exon-level microarrays in the presence or absence of IFNγ. Results Transfection of murine bone-marrow derived macrophages (BMDMs with a non-targeting (control siRNA and 11 sequence-specific siRNAs was performed using a cationic lipid transfection reagent (Lipofectamine2000 prior to stimulation with IFNγ. Total RNA was harvested from cells and gene expression measured on Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. Network-based analysis of these data revealed six siRNAs to cause a marked shift in the macrophage transcriptome in the presence or absence IFNγ. These six siRNAs targeted the Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts. The perturbation of the transcriptome by the six siRNAs was highly similar in each case and affected the expression of over 600 downstream transcripts. Regulated transcripts were clustered based on co-expression into five major groups corresponding to transcriptional networks associated with the type I and II IFN response, cell cycle regulation, and NF-KB signalling. In addition we have observed a significant non-specific immune stimulation of cells transfected with siRNA using Lipofectamine2000, suggesting use of this reagent in BMDMs, even at low concentrations, is enough to induce a type I IFN response. Conclusion Our results provide evidence that the type I IFN response in murine BMDMs is dependent on Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2, and that siRNAs targeted to these genes results in perturbation of key transcriptional networks associated

  19. Assessment of protein modifications in liver of rats under chronic treatment with paracetamol (acetaminophen) using two complementary mass spectrometry-based metabolomic approaches.

    Science.gov (United States)

    Mast, Carole; Lyan, Bernard; Joly, Charlotte; Centeno, Delphine; Giacomoni, Franck; Martin, Jean-François; Mosoni, Laurent; Dardevet, Dominique; Pujos-Guillot, Estelle; Papet, Isabelle

    2015-04-29

    Liver protein can be altered under paracetamol (APAP) treatment. APAP-protein adducts and other protein modifications (oxidation/nitration, expression) play a role in hepatotoxicity induced by acute overdoses, but it is unknown whether liver protein modifications occur during long-term treatment with non-toxic doses of APAP. We quantified APAP-protein adducts and assessed other protein modifications in the liver from rats under chronic (17 days) treatment with two APAP doses (0.5% or 1% of APAP in the diet w/w). A targeted metabolomic method was validated and used to quantify APAP-protein adducts as APAP-cysteine adducts following proteolytic hydrolysis. The limit of detection was found to be 7ng APAP-cysteine/mL hydrolysate i.e. an APAP-Cys to tyrosine ratio of 0.016‰. Other protein modifications were assessed on the same protein hydrolysate by untargeted metabolomics including a new strategy to process the data and identify discriminant molecules. These two complementary mass spectrometry (MS)-based metabolic approaches enabled the assessment of a wide range of protein modifications induced by chronic treatment with APAP. APAP-protein adducts were detected even in the absence of glutathione depletion and hepatotoxicity, i.e. in the 0.5% APAP group, and increased by 218% in the 1% APAP group compared to the 0.5% APAP group. At the same time, the untargeted metabolomic method revealed a decrease in the binding of cysteine, cysteinyl-glycine and GSH to thiol groups of protein cysteine residues, an increase in the oxidation of tryptophan and proline residues and a modification in protein expression. This wide range of modifications in liver proteins occurred in rats under chronic treatment with APAP that did not induce hepatotoxicity. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice

    NARCIS (Netherlands)

    Lu, Y.; Boekschoten, M.V.; Wopereis, S.; Muller, M.R.; Kersten, A.H.

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 wk

  1. Comparative transcriptomics and metabolomic analysis of fenofibrate and fish oil treatments in mice

    NARCIS (Netherlands)

    Lu Yingchang (Kevin), Y.; Boekschoten, Mark; Wopereis, Suzan; Muller, Michael; Kersten, Sander

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 week

  2. Comprehensive metabolomics to evaluate the impact of industrial processing on the phytochemical composition of vegetable purees

    NARCIS (Netherlands)

    Lopez-Sanchez, P.; Vos, de R.C.H.; Jonker, H.H.; Mumm, R.; Hall, R.D.; Bialek, L.; Leenman, R.; Strassburg, K.; Vreeken, R.; Hankemeier, T.; Schumm, S.; Duynhoven, van J.P.M.

    2015-01-01

    The effects of conventional industrial processing steps on global phytochemical composition of broccoli, tomato and carrot purees were investigated by using a range of complementary targeted and untargeted metabolomics approaches including LC–PDA for vitamins, 1H NMR for polar metabolites, accurate

  3. Evaluation of coverage, retention patterns and selectivity of seven liquid chromatographic methods for metabolomics

    OpenAIRE

    Wernisch, Stefanie; Pennathur, Subramaniam

    2016-01-01

    Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics studies require highly selective and efficient chromatographic techniques. Typically employed reversed-phase (RP) methods fail to target polar metabolites but the introduction of hydrophilic interaction liquid chromatography (HILIC) is slow due to perceived issues of reproducibility and ruggedness and a limited understanding of the complex retention mechanisms.

  4. Towards the Fecal Metabolome Derived from Moderate Red Wine Intake

    Directory of Open Access Journals (Sweden)

    Ana Jiménez-Girón

    2014-12-01

    Full Text Available Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33. It assembles data from two analytical approaches: (1 UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis; and (2 UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis. Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota.

  5. Short overview on metabolomic approach and redox changes in psychiatric disorders

    Directory of Open Access Journals (Sweden)

    Gordana Nedic Erjavec

    2018-04-01

    Full Text Available Schizophrenia, depression and posttraumatic stress disorder (PTSD are severe mental disorders and complicated diagnostic entities, due to their phenotypic, biological and genetic heterogeneity, unknown etiology, and poorly understood alterations in biological pathways and biological mechanisms. Disturbed homeostasis between overproduction of oxidant species, overcoming redox regulation and a lack of cellular antioxidant defenses, resulting in free radical-mediated pathology and subsequent neurotoxicity contributes to development of depression, schizophrenia and PTSD, their heterogeneous clinical presentation and resistance to treatment. Metabolomics is a discipline that combines different strategies with the aim to extract, detect, identify and quantify all metabolites that are present in a biological sample and might provide mechanistic insights into the etiology of various psychiatric disorders. Therefore, oxidative stress research combined with metabolomics might offer a novel approach in dissecting psychiatric disorders, since these data-driven but not necessarily hypothesis-driven methods might identify new targets, molecules and pathways responsible for development of schizophrenia, depression or PTSD. Findings from the oxidative research in psychiatry together with metabolomics data might facilitate development of specific and validated prognostic, therapeutic and clinical biomarkers. These methods might reveal bio-signatures of individual patients, leading to individualized treatment approach. In reviewing findings related to oxidative stress and metabolomics in selected psychiatric disorders, we have highlighted how these novel approaches might make a unique contribution to deeper understanding of psychopathological alterations underlying schizophrenia, depression and PTSD. Keywords: Schizophrenia, Depression, Posttraumatic stress disorder, Oxidative stress, Lipid peroxidation, Metabolomics, Biomarkers

  6. Characterizing Alzheimer's disease through metabolomics and investigating anti-Alzheimer's disease effects of natural products.

    Science.gov (United States)

    Yi, Lunzhao; Liu, Wenbin; Wang, Zhe; Ren, Dabing; Peng, Weijun

    2017-06-01

    Alzheimer's disease (AD) is the most common cause of dementia in elderly people and is among the greatest healthcare challenges of the 21st century. However, the etiology and pathogenesis of AD remain poorly understood, and no curative treatments are available to slow down or stop the degenerative effects of AD. As a high-throughput approach, metabolomics is gaining significant attention in AD research, because it has a powerful potential to discover novel biomarkers, unravel new therapeutic targets for AD, and identify perturbed metabolic pathways involved in AD progression. Here, we systematically review metabolomics with regard to its recent advances and applications in the identification of potential biomarkers for early AD diagnosis and pathogenesis research. In addition, we illustrate the developments in metabolomics as an effective tool for understanding the anti-AD mechanisms of natural products. We believe that the insights from these advances can narrow the gap between metabolomics research and clinical applications of laboratory findings. Moreover, we discuss some limitations and perspectives of biomarker identification in metabolomics. © 2017 New York Academy of Sciences.

  7. Metabolomics and Integrative Omics for the Development of Thai Traditional Medicine

    Science.gov (United States)

    Khoomrung, Sakda; Wanichthanarak, Kwanjeera; Nookaew, Intawat; Thamsermsang, Onusa; Seubnooch, Patcharamon; Laohapand, Tawee; Akarasereenont, Pravit

    2017-01-01

    In recent years, interest in studies of traditional medicine in Asian and African countries has gradually increased due to its potential to complement modern medicine. In this review, we provide an overview of Thai traditional medicine (TTM) current development, and ongoing research activities of TTM related to metabolomics. This review will also focus on three important elements of systems biology analysis of TTM including analytical techniques, statistical approaches and bioinformatics tools for handling and analyzing untargeted metabolomics data. The main objective of this data analysis is to gain a comprehensive understanding of the system wide effects that TTM has on individuals. Furthermore, potential applications of metabolomics and systems medicine in TTM will also be discussed. PMID:28769804

  8. A Nontargeted UHPLC-HRMS Metabolomics Pipeline for Metabolite Identification: Application to Cardiac Remote Ischemic Preconditioning.

    Science.gov (United States)

    Kouassi Nzoughet, Judith; Bocca, Cinzia; Simard, Gilles; Prunier-Mirebeau, Delphine; Chao de la Barca, Juan Manuel; Bonneau, Dominique; Procaccio, Vincent; Prunier, Fabrice; Lenaers, Guy; Reynier, Pascal

    2017-02-07

    In recent years, the number of investigations based on nontargeted metabolomics has increased, although often without a thorough assessment of analytical strategies applied to acquire data. Following published guidelines for metabolomics experiments, we report a validated nontargeted metabolomics strategy with pipeline for unequivocal identification of metabolites using the MSMLS molecule library. We achieved an in-house database containing accurate m/z values, retention times, isotopic patterns, full MS, and MS/MS spectra. A UHPLC-HRMS Q-Exactive method was developed, and experimental variations were determined within and between 3 experimental days. The extraction efficiency as well as the accuracy, precision, repeatability, and linearity of the method were assessed, the method demonstrating good performances. The methodology was further blindly applied to plasma from remote ischemic pre-conditioning (RIPC) rats. Samples, previously analyzed by targeted metabolomics using completely different protocol, analytical strategy, and platform, were submitted to our analytical pipeline. A combination of multivariate and univariate statistical analyses was employed. Selection of putative biomarkers from OPLS-DA model and S-plot was combined to jack-knife confidence intervals, metabolites' VIP values, and univariate statistics. Only variables with strong model contribution and highly statistical reliability were selected as discriminated metabolites. Three biomarkers identified by the previous targeted metabolomics study were found in the current work, in addition to three novel metabolites, emphasizing the efficiency of the current methodology and its ability to identify new biomarkers of clinical interest, in a single sequence. The biomarkers were identified to level 1 according to the metabolomics standard initiative and confirmed by both RPLC and HILIC-HRMS.

  9. Genome-wide miRNA screening reveals miR-310 family members negatively regulate the immune response in Drosophila melanogaster via co-targeting Drosomycin.

    Science.gov (United States)

    Li, Yao; Li, Shengjie; Li, Ruimin; Xu, Jiao; Jin, Ping; Chen, Liming; Ma, Fei

    2017-03-01

    Although innate immunity mediated by Toll signaling has been extensively studied in Drosophila melanogaster, the role of miRNAs in regulating the Toll-mediated immune response remains largely unknown. In this study, following Gram-positive bacterial challenge, we identified 93 differentially expressed miRNAs via genome-wide miRNA screening. These miRNAs were regarded as immune response related (IRR). Eight miRNAs were confirmed to be involved in the Toll-mediated immune response upon Gram-positive bacterial infection through genetic screening of 41 UAS-miRNA lines covering 60 miRNAs of the 93 IRR miRNAs. Interestingly, four out of these eight miRNAs, miR-310, miR-311, miR-312 and miR-313, are clustered miRNAs and belong to the miR-310 family. These miR-310 family members were shown to target and regulate the expression of Drosomycin, an antimicrobial peptide produced by Toll signaling. Taken together, our study implies important regulatory roles of miRNAs in the Toll-mediated innate immune response of Drosophila upon Gram-positive bacterial infection. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Untargeted metabolomics reveals a lack of synergy between nifurtimox and eflornithine against Trypanosoma brucei.

    Science.gov (United States)

    Vincent, Isabel M; Creek, Darren J; Burgess, Karl; Woods, Debra J; Burchmore, Richard J S; Barrett, Michael P

    2012-01-01

    A non-targeted metabolomics-based approach is presented that enables the study of pathways in response to drug action with the aim of defining the mode of action of trypanocides. Eflornithine, a polyamine pathway inhibitor, and nifurtimox, whose mode of action involves its metabolic activation, are currently used in combination as first line treatment against stage 2, CNS-involved, human African trypanosomiasis (HAT). Drug action was assessed using an LC-MS based non-targeted metabolomics approach. Eflornithine revealed the expected changes to the polyamine pathway as well as several unexpected changes that point to pathways and metabolites not previously described in bloodstream form trypanosomes, including a lack of arginase activity and N-acetylated ornithine and putrescine. Nifurtimox was shown to be converted to a trinitrile metabolite indicative of metabolic activation, as well as inducing changes in levels of metabolites involved in carbohydrate and nucleotide metabolism. However, eflornithine and nifurtimox failed to synergise anti-trypanosomal activity in vitro, and the metabolomic changes associated with the combination are the sum of those found in each monotherapy with no indication of additional effects. The study reveals how untargeted metabolomics can yield rapid information on drug targets that could be adapted to any pharmacological situation.

  11. Untargeted metabolomics reveals a lack of synergy between nifurtimox and eflornithine against Trypanosoma brucei.

    Directory of Open Access Journals (Sweden)

    Isabel M Vincent

    Full Text Available A non-targeted metabolomics-based approach is presented that enables the study of pathways in response to drug action with the aim of defining the mode of action of trypanocides. Eflornithine, a polyamine pathway inhibitor, and nifurtimox, whose mode of action involves its metabolic activation, are currently used in combination as first line treatment against stage 2, CNS-involved, human African trypanosomiasis (HAT. Drug action was assessed using an LC-MS based non-targeted metabolomics approach. Eflornithine revealed the expected changes to the polyamine pathway as well as several unexpected changes that point to pathways and metabolites not previously described in bloodstream form trypanosomes, including a lack of arginase activity and N-acetylated ornithine and putrescine. Nifurtimox was shown to be converted to a trinitrile metabolite indicative of metabolic activation, as well as inducing changes in levels of metabolites involved in carbohydrate and nucleotide metabolism. However, eflornithine and nifurtimox failed to synergise anti-trypanosomal activity in vitro, and the metabolomic changes associated with the combination are the sum of those found in each monotherapy with no indication of additional effects. The study reveals how untargeted metabolomics can yield rapid information on drug targets that could be adapted to any pharmacological situation.

  12. Symposium 2: Modern approaches to nutritional research challenges Targeted and non-targeted approaches for metabolite profiling in nutritional research

    OpenAIRE

    Lodge, John

    2010-01-01

    The present report discusses targeted and non-targeted approaches to monitor single nutrients and global metabolite profiles in nutritional research. Non- targeted approaches such as metabolomics allow for the global description of metabolites in a biological sample and combine an analytical platform with multivariate data analysis to visualise patterns between sample groups. In nutritional research metabolomics has generated much interest as it has the potential to identify...

  13. The development of metabolomic sampling procedures for Pichia pastoris, and baseline metabolome data.

    Directory of Open Access Journals (Sweden)

    Gregory D Tredwell

    Full Text Available Metabolic profiling is increasingly being used to investigate a diverse range of biological questions. Due to the rapid turnover of intracellular metabolites it is important to have reliable, reproducible techniques for sampling and sample treatment. Through the use of non-targeted analytical techniques such as NMR and GC-MS we have performed a comprehensive quantitative investigation of sampling techniques for Pichia pastoris. It was clear that quenching metabolism using solutions based on the standard cold methanol protocol caused some metabolite losses from P. pastoris cells. However, these were at a low level, with the NMR results indicating metabolite increases in the quenching solution below 5% of their intracellular level for 75% of metabolites identified; while the GC-MS results suggest a slightly higher level with increases below 15% of their intracellular values. There were subtle differences between the four quenching solutions investigated but broadly, they all gave similar results. Total culture extraction of cells + broth using high cell density cultures typical of P. pastoris fermentations, was an efficient sampling technique for NMR analysis and provided a gold standard of intracellular metabolite levels; however, salts in the media affected the GC-MS analysis. Furthermore, there was no benefit in including an additional washing step in the quenching process, as the results were essentially identical to those obtained just by a single centrifugation step. We have identified the major high-concentration metabolites found in both the extra- and intracellular locations of P. pastoris cultures by NMR spectroscopy and GC-MS. This has provided us with a baseline metabolome for P. pastoris for future studies. The P. pastoris metabolome is significantly different from that of Saccharomyces cerevisiae, with the most notable difference being the production of high concentrations of arabitol by P. pastoris.

  14. Metabolomic phenotyping of a cloned pig model

    Directory of Open Access Journals (Sweden)

    Callesen Henrik

    2011-08-01

    Full Text Available Abstract Background Pigs are widely used as models for human physiological changes in intervention studies, because of the close resemblance between human and porcine physiology and the high degree of experimental control when using an animal model. Cloned animals have, in principle, identical genotypes and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5 was for the first time elucidated by nuclear magnetic resonance (NMR-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6 by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could not be established. Conclusions From the present study we conclude that cloned and normal outbred pigs are phenotypically different. However, it cannot be concluded that the use of cloned animals will reduce the inter-individual variation in intervention studies, though this is based on a limited number of animals.

  15. Metabolomic phenotyping of a cloned pig model

    Science.gov (United States)

    2011-01-01

    Background Pigs are widely used as models for human physiological changes in intervention studies, because of the close resemblance between human and porcine physiology and the high degree of experimental control when using an animal model. Cloned animals have, in principle, identical genotypes and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5) was for the first time elucidated by nuclear magnetic resonance (NMR)-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6) by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could not be established. Conclusions From the present study we conclude that cloned and normal outbred pigs are phenotypically different. However, it cannot be concluded that the use of cloned animals will reduce the inter-individual variation in intervention studies, though this is based on a limited number of animals. PMID:21859467

  16. Using metabolomics to evaluate food intake

    DEFF Research Database (Denmark)

    Manach, Claudine; Brennan, Lorraine; Dragsted, Lars Ove

    2015-01-01

    Improving dietary assessment is essential for modern nutritional epidemiology. This chapter discusses the potential of metabolomics for the identification of new biomarkers of intake and presents the first candidate biomarkers discovered using this approach. It then describes the challenges...

  17. Metabolomics Application in Maternal-Fetal Medicine

    Directory of Open Access Journals (Sweden)

    Vassilios Fanos

    2013-01-01

    Full Text Available Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, preterm delivery, premature rupture of membranes, gestational diabetes mellitus, preeclampsia, neonatal asphyxia, and hypoxic-ischemic encephalopathy. The aim of this review is to summarize and comment on original data available in relevant published works in order to emphasize the clinical potential of metabolomics in obstetrics in the immediate future.

  18. Metabolomics in Population-Based Research

    Science.gov (United States)

    Metabolomics is the study of small molecules of both endogenous and exogenous origin, such as metabolic substrates and their products, lipids, small peptides, vitamins and other protein cofactors generated by metabolism, which are downstream from genes.

  19. Development of quantitative metabolomics for Pichia pastoris

    NARCIS (Netherlands)

    Carnicer, M.; Canelas, A.B.; Ten Pierick, A.; Zeng, Z.; Van Dam, J.; Albiol, J.; Ferrer, P.; Heijnen, J.J.; Van Gulik, W.

    2011-01-01

    Accurate, reliable and reproducible measurement of intracellular metabolite levels has become important for metabolic studies of microbial cell factories. A first critical step for metabolomic studies is the establishment of an adequate quenching and washing protocol, which ensures effective arrest

  20. An Islet-Targeted Genome-Wide Association Scan Identifies Novel Genes Implicated in Cytokine-Mediated Islet Stress in Type 2 Diabetes.

    Science.gov (United States)

    Sharma, Poonam R; Mackey, Aaron J; Dejene, Eden A; Ramadan, James W; Langefeld, Carl D; Palmer, Nicholette D; Taylor, Kent D; Wagenknecht, Lynne E; Watanabe, Richard M; Rich, Stephen S; Nunemaker, Craig S

    2015-09-01

    Genome-wide association studies in human type 2 diabetes (T2D) have renewed interest in the pancreatic islet as a contributor to T2D risk. Chronic low-grade inflammation resulting from obesity is a risk factor for T2D and a possible trigger of β-cell failure. In this study, microarray data were collected from mouse islets after overnight treatment with cytokines at concentrations consistent with the chronic low-grade inflammation in T2D. Genes with a cytokine-induced change of >2-fold were then examined for associations between single nucleotide polymorphisms and the acute insulin response to glucose (AIRg) using data from the Genetics Underlying Diabetes in Hispanics (GUARDIAN) Consortium. Significant evidence of association was found between AIRg and single nucleotide polymorphisms in Arap3 (5q31.3), F13a1 (6p25.3), Klhl6 (3q27.1), Nid1 (1q42.3), Pamr1 (11p13), Ripk2 (8q21.3), and Steap4 (7q21.12). To assess the potential relevance to islet function, mouse islets were exposed to conditions modeling low-grade inflammation, mitochondrial stress, endoplasmic reticulum (ER) stress, glucotoxicity, and lipotoxicity. RT-PCR revealed that one or more forms of stress significantly altered expression levels of all genes except Arap3. Thapsigargin-induced ER stress up-regulated both Pamr1 and Klhl6. Three genes confirmed microarray predictions of significant cytokine sensitivity: F13a1 was down-regulated 3.3-fold by cytokines, Ripk2 was up-regulated 1.5- to 3-fold by all stressors, and Steap4 was profoundly cytokine sensitive (167-fold up-regulation). Three genes were thus closely associated with low-grade inflammation in murine islets and also with a marker for islet function (AIRg) in a diabetes-prone human population. This islet-targeted genome-wide association scan identified several previously unrecognized candidate genes related to islet dysfunction during the development of T2D.

  1. LC-Mass Spectrometry for Metabolomics.

    Science.gov (United States)

    Dailey, Allyson L

    2017-01-01

    The field of metabolomics is greatly being refined by the addition of new technologies. LC-MS has allowed researchers to explore additional metabolites which were not originally captured through GC-MS. Through the customizability of the LC columns and mass spectrometer, it is now easier to tailor the instrument to your research needs. Herein, we describe a protocol for sample preparation and data acquisition for a global metabolomic analysis of tissues or feces.

  2. Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify "connectivity constellation" and drug target genes with pleiotropic effects.

    Science.gov (United States)

    Uhl, George R; Drgon, Tomas; Johnson, Catherine; Li, Chuan-Yun; Contoreggi, Carlo; Hess, Judith; Naiman, Daniel; Liu, Qing-Rong

    2008-10-01

    Genome-wide association (GWA) can elucidate molecular genetic bases for human individual differences in complex phenotypes that include vulnerability to addiction. Here, we review (a) evidence that supports polygenic models with (at least) modest heterogeneity for the genetic architectures of addiction and several related phenotypes; (b) technical and ethical aspects of importance for understanding GWA data, including genotyping in individual samples versus DNA pools, analytic approaches, power estimation, and ethical issues in genotyping individuals with illegal behaviors; (c) the samples and the data that shape our current understanding of the molecular genetics of individual differences in vulnerability to substance dependence and related phenotypes; (d) overlaps between GWA data sets for dependence on different substances; and (e) overlaps between GWA data for addictions versus other heritable, brain-based phenotypes that include bipolar disorder, cognitive ability, frontal lobe brain volume, the ability to successfully quit smoking, neuroticism, and Alzheimer's disease. These convergent results identify potential targets for drugs that might modify addictions and play roles in these other phenotypes. They add to evidence that individual differences in the quality and quantity of brain connections make pleiotropic contributions to individual differences in vulnerability to addictions and to related brain disorders and phenotypes. A "connectivity constellation" of brain phenotypes and disorders appears to receive substantial pathogenic contributions from individual differences in a constellation of genes whose variants provide individual differences in the specification of brain connectivities during development and in adulthood. Heritable brain differences that underlie addiction vulnerability thus lie squarely in the midst of the repertoire of heritable brain differences that underlie vulnerability to other common brain disorders and phenotypes.

  3. The effect of Nipped-B-like (Nipbl) haploinsufficiency on genome-wide cohesin binding and target gene expression: modeling Cornelia de Lange syndrome.

    Science.gov (United States)

    Newkirk, Daniel A; Chen, Yen-Yun; Chien, Richard; Zeng, Weihua; Biesinger, Jacob; Flowers, Ebony; Kawauchi, Shimako; Santos, Rosaysela; Calof, Anne L; Lander, Arthur D; Xie, Xiaohui; Yokomori, Kyoko

    2017-01-01

    Cornelia de Lange syndrome (CdLS) is a multisystem developmental disorder frequently associated with heterozygous loss-of-function mutations of Nipped-B-like (NIPBL), the human homolog of Drosophila Nipped-B. NIPBL loads cohesin onto chromatin. Cohesin mediates sister chromatid cohesion important for mitosis but is also increasingly recognized as a regulator of gene expression. In CdLS patient cells and animal models, expression changes of multiple genes with little or no sister chromatid cohesion defect suggests that disruption of gene regulation underlies this disorder. However, the effect of NIPBL haploinsufficiency on cohesin binding, and how this relates to the clinical presentation of CdLS, has not been fully investigated. Nipbl haploinsufficiency causes CdLS-like phenotype in mice. We examined genome-wide cohesin binding and its relationship to gene expression using mouse embryonic fibroblasts (MEFs) from Nipbl+/- mice that recapitulate the CdLS phenotype. We found a global decrease in cohesin binding, including at CCCTC-binding factor (CTCF) binding sites and repeat regions. Cohesin-bound genes were found to be enriched for histone H3 lysine 4 trimethylation (H3K4me3) at their promoters; were disproportionately downregulated in Nipbl mutant MEFs; and displayed evidence of reduced promoter-enhancer interaction. The results suggest that gene activation is the primary cohesin function sensitive to Nipbl reduction. Over 50% of significantly dysregulated transcripts in mutant MEFs come from cohesin target genes, including genes involved in adipogenesis that have been implicated in contributing to the CdLS phenotype. Decreased cohesin binding at the gene regions is directly linked to disease-specific expression changes. Taken together, our Nipbl haploinsufficiency model allows us to analyze the dosage effect of cohesin loading on CdLS development.

  4. NMR- and LC-MS/MS-based urine metabolomic investigation of the subacute effects of hexabromocyclododecane in mice.

    Science.gov (United States)

    Wang, Dezhen; Zhang, Ping; Wang, Xinru; Wang, Yao; Zhou, Zhiqiang; Zhu, Wentao

    2016-05-01

    In the present study, both untargeted and targeted metabolomics approaches were used to evaluate the subacute effects of hexabromocyclododecane (HBCD) on mice urine metabolome. Untargeted metabolomics based on (1)H NMR showed that HBCD exposure disturbed mice metabolism in both dosed groups, especially in high dosed group. The low-dose HBCD led to a decrease in alanine, malonic acid, and trimethylamine (TMA). High-dose HBCD-treated mice developed high levels of citric acid and 2-ketoglutarate, together with decreased alanine, acetate, formate, TMA, 3-hydroxybutyrate, and malonic acid. Targeted metabolomics for metabolic profiling of 20 amino acids identified alanine, lysine, and phenylalanine as significantly disturbed metabolites. These results indicated that subchronic exposure to HBCD caused a disturbance of mice metabolism, especially in TCA cycle, lipid metabolism, gut microbial metabolism, and homeostasis of amino acids, and the application of untargeted and targeted metabolomics combined with conventional toxicology approaches to evaluate the subacute effects of pollutants will provide more comprehensive information and aid in predicting health risk of these pollutants.

  5. Sample normalization methods in quantitative metabolomics.

    Science.gov (United States)

    Wu, Yiman; Li, Liang

    2016-01-22

    To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Metabolomics continues to flourish: highlights from the 2014 Metabolomics Society Conference

    NARCIS (Netherlands)

    Roessner, U.; Hall, R.D.

    2014-01-01

    The Metabolomics Society has now been organising its annual meetings for 10 years! The 10th annual conference returned, in June, to Tsuruoka, Japan where the very first meeting was also held in 2005—just shortly after our society had been formally established and our journal Metabolomics had brought

  7. Discovery of Antimalarial Drugs from Streptomycetes Metabolites Using a Metabolomic Approach

    Directory of Open Access Journals (Sweden)

    Siti Junaidah Ahmad

    2017-01-01

    Full Text Available Natural products continue to play an important role as a source of biologically active substances for the development of new drug. Streptomyces, Gram-positive bacteria which are widely distributed in nature, are one of the most popular sources of natural antibiotics. Recently, by using a bioassay-guided fractionation, an antimalarial compound, Gancidin-W, has been discovered from these bacteria. However, this classical method in identifying potentially novel bioactive compounds from the natural products requires considerable effort and is a time-consuming process. Metabolomics is an emerging “omics” technology in systems biology study which integrated in process of discovering drug from natural products. Metabolomics approach in finding novel therapeutics agent for malaria offers dereplication step in screening phase to shorten the process. The highly sensitive instruments, such as Liquid Chromatography-Mass Spectrophotometry (LC-MS, Gas Chromatography-Mass Spectrophotometry (GC-MS, and Nuclear Magnetic Resonance (1H-NMR spectroscopy, provide a wide range of information in the identification of potentially bioactive compounds. The current paper reviews concepts of metabolomics and its application in drug discovery of malaria treatment as well as assessing the antimalarial activity from natural products. Metabolomics approach in malaria drug discovery is still new and needs to be initiated, especially for drug research in Malaysia.

  8. Metabolomics and lipidomics using traveling-wave ion mobility mass spectrometry.

    Science.gov (United States)

    Paglia, Giuseppe; Astarita, Giuseppe

    2017-04-01

    Metabolomics and lipidomics aim to profile the wide range of metabolites and lipids that are present in biological samples. Recently, ion mobility spectrometry (IMS) has been used to support metabolomics and lipidomics applications to facilitate the separation and the identification of complex mixtures of analytes. IMS is a gas-phase electrophoretic technique that enables the separation of ions in the gas phase according to their charge, shape and size. Occurring within milliseconds, IMS separation is compatible with modern mass spectrometry (MS) operating with microsecond scan speeds. Thus, the time required for acquiring IMS data does not affect the overall run time of traditional liquid chromatography (LC)-MS-based metabolomics and lipidomics experiments. The addition of IMS to conventional LC-MS-based metabolomics and lipidomics workflows has been shown to enhance peak capacity, spectral clarity and fragmentation specificity. Moreover, by enabling determination of a collision cross-section (CCS) value-a parameter related to the shape of ions-IMS can improve the accuracy of metabolite identification. In this protocol, we describe how to integrate traveling-wave ion mobility spectrometry (TWIMS) into traditional LC-MS-based metabolomic and lipidomic workflows. In particular, we describe procedures for the following: tuning and calibrating a SYNAPT High-Definition MS (HDMS) System (Waters) specifically for metabolomics and lipidomics applications; extracting polar metabolites and lipids from brain samples; setting up appropriate chromatographic conditions; acquiring simultaneously m/z, retention time and CCS values for each analyte; processing and analyzing data using dedicated software solutions, such as Progenesis QI (Nonlinear Dynamics); and, finally, performing metabolite and lipid identification using CCS databases and TWIMS-derived fragmentation information.

  9. Influence of the collection tube on metabolomic changes in serum and plasma.

    Science.gov (United States)

    López-Bascón, M A; Priego-Capote, F; Peralbo-Molina, A; Calderón-Santiago, M; Luque de Castro, M D

    2016-04-01

    Major threats in metabolomics clinical research are biases in sampling and preparation of biological samples. Bias in sample collection is a frequently forgotten aspect responsible for uncontrolled errors in metabolomics analysis. There is a great diversity of blood collection tubes for sampling serum or plasma, which are widely used in metabolomics analysis. Most of the existing studies dealing with the influence of blood collection on metabolomics analysis have been restricted to comparison between plasma and serum. However, polymeric gel tubes, which are frequently proposed to accelerate the separation of serum and plasma, have not been studied. In the present research, samples of serum or plasma collected in polymeric gel tubes were compared with those taken in conventional tubes from a metabolomics perspective using an untargeted GC-TOF/MS approach. The main differences between serum and plasma collected in conventional tubes affected to critical pathways such as the citric acid cycle, metabolism of amino acids, fructose and mannose metabolism and that of glycerolipids, and pentose and glucuronate interconversion. On the other hand, the polymeric gel only promoted differences at the metabolite level in serum since no critical differences were observed between plasma collected with EDTA tubes and polymeric gel tubes. Thus, the main changes were attributable to serum collected in gel and affected to the metabolism of amino acids such as alanine, proline and threonine, the glycerolipids metabolism, and two primary metabolites such as aconitic acid and lactic acid. Therefore, these metabolite changes should be taken into account in planning an experimental protocol for metabolomics analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. The Steroid Metabolome of Adrenarche

    Science.gov (United States)

    Rege, Juilee; Rainey, William E.

    2014-01-01

    Adrenarche is an endocrine developmental process whereby humans and select nonhuman primates increase adrenal output of a series of steroids, especially dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEAS). The timing of adrenarche varies between primates, but in humans, serum levels of DHEAS are seen to increase around 6 years of age. This phenomenon corresponds with the development and expansion of the zona reticularis (ZR) of the adrenal gland. The physiological phenomena that trigger the onset of adrenarche are still unknown; however the biochemical pathways leading to this event have been elucidated in detail. There are numerous reviews examining the process of adrenarche, most of which, have focused on the changes within the adrenal as well as the phenotypic results of adrenarche. This article reviews the recent and past studies that show the breadth of changes in the circulating steroid metabolome that occurs during the process of adrenarche. PMID:22715193

  11. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization.

    Science.gov (United States)

    Adkins, D E; McClay, J L; Vunck, S A; Batman, A M; Vann, R E; Clark, S L; Souza, R P; Crowley, J J; Sullivan, P F; van den Oord, E J C G; Beardsley, P M

    2013-11-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In this study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine (MA)-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate, FDR biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  12. MetabR: an R script for linear model analysis of quantitative metabolomic data

    Directory of Open Access Journals (Sweden)

    Ernest Ben

    2012-10-01

    Full Text Available Abstract Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

  13. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    Energy Technology Data Exchange (ETDEWEB)

    Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

    2012-10-31

    Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  14. Integrated work-flow for quantitative metabolome profiling of plants, Peucedani Radix as a case.

    Science.gov (United States)

    Song, Yuelin; Song, Qingqing; Liu, Yao; Li, Jun; Wan, Jian-Bo; Wang, Yitao; Jiang, Yong; Tu, Pengfei

    2017-02-08

    Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only

  15. Effect of sleep deprivation on the human metabolome.

    Science.gov (United States)

    Davies, Sarah K; Ang, Joo Ern; Revell, Victoria L; Holmes, Ben; Mann, Anuska; Robertson, Francesca P; Cui, Nanyi; Middleton, Benita; Ackermann, Katrin; Kayser, Manfred; Thumser, Alfred E; Raynaud, Florence I; Skene, Debra J

    2014-07-22

    Sleep restriction and circadian clock disruption are associated with metabolic disorders such as obesity, insulin resistance, and diabetes. The metabolic pathways involved in human sleep, however, have yet to be investigated with the use of a metabolomics approach. Here we have used untargeted and targeted liquid chromatography (LC)/MS metabolomics to examine the effect of acute sleep deprivation on plasma metabolite rhythms. Twelve healthy young male subjects remained in controlled laboratory conditions with respect to environmental light, sleep, meals, and posture during a 24-h wake/sleep cycle, followed by 24 h of wakefulness. Two-hourly plasma samples collected over the 48 h period were analyzed by LC/MS. Principal component analysis revealed a clear time of day variation with a significant cosine fit during the wake/sleep cycle and during 24 h of wakefulness in untargeted and targeted analysis. Of 171 metabolites quantified, daily rhythms were observed in the majority (n = 109), with 78 of these maintaining their rhythmicity during 24 h of wakefulness, most with reduced amplitude (n = 66). During sleep deprivation, 27 metabolites (tryptophan, serotonin, taurine, 8 acylcarnitines, 13 glycerophospholipids, and 3 sphingolipids) exhibited significantly increased levels compared with during sleep. The increased levels of serotonin, tryptophan, and taurine may explain the antidepressive effect of acute sleep deprivation and deserve further study. This report, to our knowledge the first of metabolic profiling during sleep and sleep deprivation and characterization of 24 h rhythms under these conditions, offers a novel view of human sleep/wake regulation.

  16. Structured plant metabolomics for the simultaneous exploration of multiple factors

    Science.gov (United States)

    Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

    2016-01-01

    Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor–metabolite crosstalk. However, unravelling all factor–metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset. PMID:27853298

  17. NMR-based Metabolomics Applications in Biological and Environmental Science

    Science.gov (United States)

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

  18. Haystack, a web-based tool for metabolomics research.

    Science.gov (United States)

    Grace, Stephen C; Embry, Stephen; Luo, Heng

    2014-01-01

    Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species. To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins. Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization options and supports non

  19. The Impact of GFP Reporter Gene Transduction and Expression on Metabolomics of Placental Mesenchymal Stem Cells Determined by UHPLC-Q/TOF-MS.

    Science.gov (United States)

    Yang, Jinfeng; Wang, Nan; Chen, Deying; Yu, Jiong; Pan, Qiaoling; Wang, Dan; Liu, Jingqi; Shi, Xiaowei; Dong, Xiaotian; Cao, Hongcui; Li, Liang; Li, Lanjuan

    2017-01-01

    Green fluorescent protein (GFP) is widely used as a reporter gene in regenerative medicine research to label and track stem cells. Here, we examined whether expressing GFP gene may impact the metabolism of human placental mesenchymal stem cells (hPMSCs). The GFP gene was transduced into hPMSCs using lentiviral-based infection to establish GFP+hPMSCs. A sensitive 13C/12C-dansyl labeling LC-MS method targeting the amine/phenol submetabolome was used for in-depth cell metabolome profiling. A total of 1151 peak pairs or metabolites were detected from 12 LC-MS runs. Principal component analysis and partial least squares discriminant analysis showed poor separation, and the volcano plots demonstrated that most of the metabolites were not significantly changed when hPMSCs were tagged with GFP. Overall, 739 metabolites were positively or putatively identified. Only 11 metabolites showed significant changes. Metabolic pathway analyses indicated that three of the identified metabolites were involved in nine pathways. However, these metabolites are unlikely to have a large impact on the metabolic pathways due to their nonessential roles and limited hits in pathway analysis. This study indicated that the expression of ectopic GFP reporter gene did not significantly alter the metabolomics pathways covered by the amine/phenol submetabolome.

  20. Fish mucus metabolome reveals fish life-history traits

    Science.gov (United States)

    Reverter, M.; Sasal, P.; Banaigs, B.; Lecchini, D.; Lecellier, G.; Tapissier-Bontemps, N.

    2017-06-01

    Fish mucus has important biological and ecological roles such as defense against fish pathogens and chemical mediation among several species. A non-targeted liquid chromatography-mass spectrometry metabolomic approach was developed to study gill mucus of eight butterflyfish species in Moorea (French Polynesia), and the influence of several fish traits (geographic site and reef habitat, species taxonomy, phylogeny, diet and parasitism levels) on the metabolic variability was investigated. A biphasic extraction yielding two fractions (polar and apolar) was used. Fish diet (obligate corallivorous, facultative corallivorous or omnivorous) arose as the main driver of the metabolic differences in the gill mucus in both fractions, accounting for 23% of the observed metabolic variability in the apolar fraction and 13% in the polar fraction. A partial least squares discriminant analysis allowed us to identify the metabolites (variable important in projection, VIP) driving the differences between fish with different diets (obligate corallivores, facultative corallivores and omnivorous). Using accurate mass data and fragmentation data, we identified some of these VIP as glycerophosphocholines, ceramides and fatty acids. Level of monogenean gill parasites was the second most important factor shaping the gill mucus metabolome, and it explained 10% of the metabolic variability in the polar fraction and 5% in the apolar fraction. A multiple regression tree revealed that the metabolic variability due to parasitism in the polar fraction was mainly due to differences between non-parasitized and parasitized fish. Phylogeny and butterflyfish species were factors contributing significantly to the metabolic variability of the apolar fraction (10 and 3%, respectively) but had a less pronounced effect in the polar fraction. Finally, geographic site and reef habitat of butterflyfish species did not influence the gill mucus metabolome of butterflyfishes.

  1. Metabolomics data normalization with EigenMS.

    Directory of Open Access Journals (Sweden)

    Yuliya V Karpievitch

    Full Text Available Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated. Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05 as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data.

  2. Metabolomics: Developing a chemical specific fingerprint

    Science.gov (United States)

    Putnam, Joel G.

    2016-01-01

    We combine cell assays and metabolomics to create a powerful tool, which emerges to elevate the identification of new control chemicals. We combined the use of bigheaded carp fry cell line with metabolite profiling to describe the dose response to thiram. Thiram is a registered pesticide commonly used as a fungicide in the field or as a seed protectant and is known to be toxic to fish. Seven concentrations of thiram were used to dose bighead carp fry cells and silver carp fry cells. We identified 700 metabolomic markers and 41 of those markers exhibited a dose response to thiram in the bighead carp fry cells. We identified 1590 metabolomic markers with 205 of those markers exhibited a dose response to thiram in the silver carp fry cells. When the metabolites of both cell lines are compared using volcano plots, 16 metabolomic markers were identified as significant. A smaller subset of metabolites indicate that a thiram specific metabolomic fingerprint exists that is not species specific, but instead toxin specific. Application of toxin fingerprints (toxin specific but species independent metabolites) can be used to address the cause of ecological significant events, such as mass fish kills.

  3. Application of Metabolomics in Thyroid Cancer Research

    Directory of Open Access Journals (Sweden)

    Anna Wojakowska

    2015-01-01

    Full Text Available Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

  4. Applying Metabolomics to differentiate amphibian responses ...

    Science.gov (United States)

    Introduction/Objectives/Methods One of the biggest challenges in ecological risk assessment is determining the impact of multiple stressors on individual organisms and populations in ‘real world’ scenarios. Emerging ‘omic technologies, notably, metabolomics, provides an opportunity to address the uncertainties surrounding ecological risk assessment of multiple stressors. The objective of this study was to use a metabolomics biomarker approach to investigate the effect of multiple stressors on amphibian metamorphs. To this end, metamorphs of Rana pipiens (northern leopard frogs) were exposed to the insecticide Carbaryl (0.32 μg/L), a conspecific predator alarm call (Lithobates catesbeianus), Carbaryl and the predator alarm call, and a control with no stressor. In addition to metabolomic fingerprinting, we measured corticosterone levels in each treatment to assess general stress response. We analyzed relative abundances of endogenous metabolites collected in liver tissue with gas chromatography coupled with mass spectrometry. Support vector machine (SVM) methods with recursive feature elimination (RFE) were applied to rank the metabolomic profiles produced. Results/Conclusions SVM-RFE of the acquired metabolomic spectra demonstrated 85-96% classification accuracy among control and all treatment groups when using the top 75 ranked retention time bins. Biochemical fluxes observed in the groups exposed to carbaryl, predation threat, and the combined treatmen

  5. Basics of mass spectrometry based metabolomics.

    Science.gov (United States)

    Courant, Frédérique; Antignac, Jean-Philippe; Dervilly-Pinel, Gaud; Le Bizec, Bruno

    2014-11-01

    The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Metabolomic profile of children with recurrent respiratory infections.

    Science.gov (United States)

    Bozzetto, Sara; Pirillo, Paola; Carraro, Silvia; Berardi, Mariangela; Cesca, Laura; Stocchero, Matteo; Giordano, Giuseppe; Zanconato, Stefania; Baraldi, Eugenio

    2017-01-01

    Recurrent respiratory infections (RRI) represent a widespread condition which has a severe social and economic impact. Immunostimulants are used for their prevention. It is crucial to better characterize children with RRI to refine their diagnosis and identify effective personalized prevention strategies. Metabolomics is a high-dimensional biological method that can be used for hypothesis-free biomarker profiling, examining a large number of metabolites in a given sample using spectroscopic techniques. Multivariate statistical data analysis then enables us to infer which metabolic information is relevant to the biological characterization of a given physiological or pathological condition. This can lead to the emergence of new, sometimes unexpected metabolites, and hitherto unknown metabolic pathways, enabling the formulation of new pathogenetic hypotheses, and the identification of new therapeutic targets. The aim of our pilot study was to apply mass-spectrometry-based metabolomics to the analysis of urine samples from children with RRI, comparing these children's biochemical metabolic profiles with those of healthy peers. We also compared the RRI children's and healthy controls' metabolomic urinary profiles after the former had received pidotimod treatment for 3 months to see whether this immunostimulant was associated with biochemical changes in the RRI children's metabolic profile. 13 children (age range 3-6 yeas) with RRI and 15 matched per age healthy peers with no history of respiratory diseases or allergies were enrolled. Their metabolomic urine samples were compared before and after the RRI children had been treated with pidotimod for a period of 3 months. Metabolomic analyses on the urine samples were done using mass spectrometry combined with ultra-performance liquid chromatography (UPLC-MS). The resulting spectroscopic data then underwent multivariate statistical analysis and the most relevant variables characterizing the two groups were identified

  7. Molecular genetics of addiction and related heritable phenotypes: genome wide association approaches identify “connectivity constellation” and drug target genes with pleiotropic effects

    OpenAIRE

    Uhl, George R; Drgon, Tomas; Johnson, Catherine; Li, Chuan-Yun; Contoreggi, Carlo; Hess, Judith; Naiman, Daniel; Liu, Qing-Rong

    2008-01-01

    Genome wide association (GWA) can elucidate molecular genetic bases for human individual differences in “complex” phenotypes that include vulnerability to addiction. Here, we review: a) evidence that supports polygenic models with (at least) modest heterogeneity for the genetic architectures of addiction and several related phenotypes; b) technical and ethical aspects of importance for understanding genome wide association data: genotyping in individual samples vs DNA pools, analytic approach...

  8. Metabolomics of human brain aging and age-related neurodegenerative diseases.

    Science.gov (United States)

    Jové, Mariona; Portero-Otín, Manuel; Naudí, Alba; Ferrer, Isidre; Pamplona, Reinald

    2014-07-01

    Neurons in the mature human central nervous system (CNS) perform a wide range of motor, sensory, regulatory, behavioral, and cognitive functions. Such diverse functional output requires a great diversity of CNS neuronal and non-neuronal populations. Metabolomics encompasses the study of the complete set of metabolites/low-molecular-weight intermediates (metabolome), which are context-dependent and vary according to the physiology, developmental state, or pathologic state of the cell, tissue, organ, or organism. Therefore, the use of metabolomics can help to unravel the diversity-and to disclose the specificity-of metabolic traits and their alterations in the brain and in fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of aging and neurodegenerative diseases. Here, we review the current applications of metabolomics in studies of CNS aging and certain age-related neurodegenerative diseases such as Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis. Neurometabolomics will increase knowledge of the physiologic and pathologic functions of neural cells and will place the concept of selective neuronal vulnerability in a metabolic context.

  9. Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana

    Science.gov (United States)

    Hirai, Masami Yokota; Yano, Mitsuru; Goodenowe, Dayan B.; Kanaya, Shigehiko; Kimura, Tomoko; Awazuhara, Motoko; Arita, Masanori; Fujiwara, Toru; Saito, Kazuki

    2004-01-01

    Plant metabolism is a complex set of processes that produce a wide diversity of foods, woods, and medicines. With the genome sequences of Arabidopsis and rice in hands, postgenomics studies integrating all “omics” sciences can depict precise pictures of a whole-cellular process. Here, we present, to our knowledge, the first report of investigation for gene-to-metabolite networks regulating sulfur and nitrogen nutrition and secondary metabolism in Arabidopsis, with integration of metabolomics and transcriptomics. Transcriptome and metabolome analyses were carried out, respectively, with DNA macroarray and several chemical analytical methods, including ultra high-resolution Fourier transform-ion cyclotron MS. Mathematical analyses, including principal component analysis and batch-learning self-organizing map analysis of transcriptome and metabolome data suggested the presence of general responses to sulfur and nitrogen deficiencies. In addition, specific responses to either sulfur or nitrogen deficiency were observed in several metabolic pathways: in particular, the genes and metabolites involved in glucosinolate metabolism were shown to be coordinately modulated. Understanding such gene-to-metabolite networks in primary and secondary metabolism through integration of transcriptomics and metabolomics can lead to identification of gene function and subsequent improvement of production of useful compounds in plants. PMID:15199185

  10. Metabolomic applications to decipher gut microbial metabolic influence in health and disease

    Directory of Open Access Journals (Sweden)

    Francois-Pierre eMartin

    2012-04-01

    Full Text Available Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial mammalian cross-talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease aetiology, diagnostic stratification and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR spectroscopy and mass spectrometry (MS provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation.

  11. Potential input from metabolomics for exploring and understanding the links between environment and health.

    Science.gov (United States)

    Bonvallot, Nathalie; Tremblay-Franco, Marie; Chevrier, Cecile; Canlet, Cecile; Debrauwer, Laurent; Cravedi, Jean-Pierre; Cordier, Sylvaine

    2014-01-01

    Humans may be exposed via their environment to multiple chemicals as a consequence of human activities and use of synthetic products. Little knowledge is routinely generated on the hazards of these chemical mixtures. The metabolomic approach is widely used to identify metabolic pathways modified by diseases, drugs, or exposures to toxicants. This review, based on the state of the art of the current applications of metabolomics in environmental health, attempts to determine whether metabolomics might constitute an original approach to the study of associations between multiple, low-dose environmental exposures in humans. Studying the biochemical consequences of complex environmental exposures is a challenge demanding the development of careful experimental and epidemiological designs, in order to take into account possible confounders associated with the high level of interindividual variability induced by different lifestyles. The choices of populations studied, sampling and storage procedures, statistical tools used, and system biology need to be considered. Suggestions for improved experimental and epidemiological designs are described. Evidence indicates that metabolomics may be a powerful tool in environmental health in the identification of both complex exposure biomarkers directly in human populations and modified metabolic pathways, in an attempt to improve understanding the underlying environmental causes of diseases. Nevertheless, the validity of biomarkers and relevancy of animal-to-human extrapolation remain key challenges that need to be properly explored.

  12. Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana.

    Science.gov (United States)

    Hirai, Masami Yokota; Yano, Mitsuru; Goodenowe, Dayan B; Kanaya, Shigehiko; Kimura, Tomoko; Awazuhara, Motoko; Arita, Masanori; Fujiwara, Toru; Saito, Kazuki

    2004-07-06

    Plant metabolism is a complex set of processes that produce a wide diversity of foods, woods, and medicines. With the genome sequences of Arabidopsis and rice in hands, postgenomics studies integrating all "omics" sciences can depict precise pictures of a whole-cellular process. Here, we present, to our knowledge, the first report of investigation for gene-to-metabolite networks regulating sulfur and nitrogen nutrition and secondary metabolism in Arabidopsis, with integration of metabolomics and transcriptomics. Transcriptome and metabolome analyses were carried out, respectively, with DNA macroarray and several chemical analytical methods, including ultra high-resolution Fourier transform-ion cyclotron MS. Mathematical analyses, including principal component analysis and batch-learning self-organizing map analysis of transcriptome and metabolome data suggested the presence of general responses to sulfur and nitrogen deficiencies. In addition, specific responses to either sulfur or nitrogen deficiency were observed in several metabolic pathways: in particular, the genes and metabolites involved in glucosinolate metabolism were shown to be coordinately modulated. Understanding such gene-to-metabolite networks in primary and secondary metabolism through integration of transcriptomics and metabolomics can lead to identification of gene function and subsequent improvement of production of useful compounds in plants.

  13. Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

    Science.gov (United States)

    Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

    2016-08-01

    Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  14. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    Science.gov (United States)

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Zinc Oxide Nanoparticle Caused Plasma Metabolomic Perturbations Correlate with Hepatic Steatosis

    Directory of Open Access Journals (Sweden)

    Weidong Zhang

    2018-01-01

    Full Text Available Zinc oxide nanoparticles (ZnO NPs, known for their chemical stability and strong adsorption, are used in everyday items such as cosmetics, sunscreens, and prophylactic drugs. However, they have also been found to adversely affect organisms; previously we found that ZnO NPs disrupt pubertal ovarian development, inhibit embryonic development by upsetting γ-H2AX and NF-κB pathways, and even disturb skin stem cells. Non-targeted metabolomic analysis of biological organisms has been suggested as an unbiased tool for the investigation of perturbations in response to NPs and their underlying mechanisms. Although metabolomics has been used in nanotoxicological studies, very few reports have used it to investigate the effects of ZnO NPs exposure. In the current investigation, through a metabolomics-based approach, we discovered that ZnO NPs caused changes in plasma metabolites involved in anti-oxidative mechanisms, energy metabolism, and lipid metabolism in hen livers. These results are in line with earlier findings that ZnO NPs perturb the tricarboxylic acid cycle and in turn result in the use of alternative energy sources. We also found that ZnO NPs disturbed lipid metabolism in the liver and consequently impacted blood lipid balance. Changes in plasma metabolomes were correlated with hepatic steatosis.

  16. Metabolomics highlights pharmacological bioactivity and biochemical mechanism of traditional Chinese medicine.

    Science.gov (United States)

    Wang, Ming; Chen, Lin; Liu, Dan; Chen, Hua; Tang, Dan-Dan; Zhao, Ying-Yong

    2017-08-01

    Traditional Chinese medicine (TCM) has attracted increasing interest throughout the world because of its potential complementary therapy and an abundant source for new drug discovery. TCM possesses the significant bioactivity of the use of multi-component drugs and can act multiple targets by multiple components. Metabolomics is a holistic investigation of numerous metabolite responses of complex biology systems to pathological stimuli and drug treatments based on the global metabolic profiles in complex biological matrixes. It provides variation of systematic metabolic networks for characterizing pathological states in animal models and clinical studies. In agreement with the holistic thinking of TCM, metabolomics has shown potential in bioactivity evaluation and action mechanism of TCM as well as pharmaceutical research and development. Recently, different metabolomic technologies have been applied to the modernization of TCM and treatments of different diseases such as cardiovascular disease, kidney disease, liver disease and metabolic disease. Based on the reported literature, this paper introduced the application of metabolomics in efficacy evaluation of TCM and its biochemical action mechanism. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. metaX: a flexible and comprehensive software for processing metabolomics data.

    Science.gov (United States)

    Wen, Bo; Mei, Zhanlong; Zeng, Chunwei; Liu, Siqi

    2017-03-21

    Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites. Computational analysis tools that are fully integrated with multiple functions and are easily operated by users who lack extensive knowledge in programing are needed in this research field. We herein developed an R package, metaX, that is capable of end-to-end metabolomics data analysis through a set of interchangeable modules. Specifically, metaX provides several functions, such as peak picking and annotation, data quality assessment, missing value imputation, data normalization, univariate and multivariate statistics, power analysis and sample size estimation, receiver operating characteristic analysis, biomarker selection, pathway annotation, correlation network analysis, and metabolite identification. In addition, metaX offers a web-based interface ( http://metax.genomics.cn ) for data quality assessment and normalization method evaluation, and it generates an HTML-based report with a visualized interface. The metaX utilities were demonstrated with a published metabolomics dataset on a large scale. The software is available for operation as either a web-based graphical user interface (GUI) or in the form of command line functions. The package and the example reports are available at http://metax.genomics.cn/ . The pipeline of metaX is platform-independent and is easy to use for analysis of metabolomics data generated from mass spectrometry.

  18. Fecal metabolome of the Hadza hunter-gatherers: a host-microbiome integrative view.

    Science.gov (United States)

    Turroni, Silvia; Fiori, Jessica; Rampelli, Simone; Schnorr, Stephanie L; Consolandi, Clarissa; Barone, Monica; Biagi, Elena; Fanelli, Flaminia; Mezzullo, Marco; Crittenden, Alyssa N; Henry, Amanda G; Brigidi, Patrizia; Candela, Marco

    2016-09-14

    The recent characterization of the gut microbiome of traditional rural and foraging societies allowed us to appreciate the essential co-adaptive role of the microbiome in complementing our physiology, opening up significant questions on how the microbiota changes that have occurred in industrialized urban populations may have altered the microbiota-host co-metabolic network, contributing to the growing list of Western diseases. Here, we applied a targeted metabolomics approach to profile the fecal metabolome of the Hadza of Tanzania, one of the world's few remaining foraging populations, and compared them to the profiles of urban living Italians, as representative of people in the post-industrialized West. Data analysis shows that during the rainy season, when the diet is primarily plant-based, Hadza are characterized by a distinctive enrichment in hexoses, glycerophospholipids, sphingolipids, and acylcarnitines, while deplete in the most common natural amino acids and derivatives. Complementary to the documented unique metagenomic features of their gut microbiome, our findings on the Hadza metabolome lend support to the notion of an alternate microbiome configuration befitting of a nomadic forager lifestyle, which helps maintain metabolic homeostasis through an overall scarcity of inflammatory factors, which are instead highly represented in the Italian metabolome.

  19. A strategy for sensitive, large scale quantitative metabolomics.

    Science.gov (United States)

    Liu, Xiaojing; Ser, Zheng; Cluntun, Ahmad A; Mentch, Samantha J; Locasale, Jason W

    2014-05-27

    Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.

  20. Metabolomic determination of pathogenesis of late-onset preeclampsia.

    Science.gov (United States)

    Bahado-Singh, Ray O; Syngelaki, Argyro; Mandal, Rupsari; Graham, Stewart F; Akolekar, Ranjit; Han, Beomsoo; Bjondahl, Trent C; Dong, Edison; Bauer, Samuel; Alpay-Savasan, Zeynep; Turkoglu, Onur; Ogunyemi, Dotun; Poon, Liona C; Wishart, David S; Nicolaides, Kypros H

    2017-03-01

    Our primary objective was to apply metabolomic pathway analysis of first trimester maternal serum to provide an insight into the pathogenesis of late-onset preeclampsia (late-PE) and thereby identify plausible therapeutic targets for PE. NMR-based metabolomics analysis was performed on 29 cases of late-PE and 55 unaffected controls. In order to achieve sufficient statistical power to perform the pathway analysis, these cases were combined with a group of previously analyzed specimens, 30 late-PE cases and 60 unaffected controls. Specimens from both groups of cases and controls were collected in the same clinical centers during the same time period. In addition, NMR analyses were performed in the same lab and using the same techniques. We identified abnormalities in branch chain amino acids (valine, leucine and isoleucine) and propanoate, glycolysis, gluconeogenesis and ketone body metabolic pathways. The results suggest insulin resistance and metabolic syndrome, mitochondrial dysfunction and disturbance of energy metabolism, oxidative stress and lipid dysfunction in the pathogenesis of late PE and suggest a potential role for agents that reduce insulin resistance in PE. Branched chain amino acids are known markers of insulin resistance and strongly predict future diabetes development. The analysis provides independent evidence linking insulin resistance and late-PE and suggests a potentially important therapeutic role for pharmacologic agents that reduce insulin resistance for late-PE.

  1. Validation of a dual LC-HRMS platform for clinical metabolic diagnosis in serum, bridging quantitative analysis and untargeted metabolomics.

    Science.gov (United States)

    Gertsman, Ilya; Gangoiti, Jon A; Barshop, Bruce A

    2014-04-04

    Mass spectrometry-based metabolomics is a rapidly growing field in both research and diagnosis. Generally, the methodologies and types of instruments used for clinical and other absolute quantification experiments are different from those used for biomarkers discovery and untargeted analysis, as the former requires optimal sensitivity and dynamic range, while the latter requires high resolution and high mass accuracy. We used a Q-TOF mass spectrometer with two different types of pentafluorophenyl (PFP) stationary phases, employing both positive and negative ionization, to develop and validate a hybrid quantification and discovery platform using LC-HRMS. This dual-PFP LC-MS platform quantifies over 50 clinically relevant metabolites in serum (using both MS and MS/MS acquisitions) while simultaneously collecting high resolution and high mass accuracy full scans to monitor all other co-eluting non-targeted analytes. We demonstrate that the linearity, accuracy, and precision results for the quantification of a number of metabolites, including amino acids, organic acids, acylcarnitines and purines/pyrimidines, meets or exceeds normal bioanalytical standards over their respective physiological ranges. The chromatography resolved highly polar as well as hydrophobic analytes under reverse-phase conditions, enabling analysis of a wide range of chemicals, necessary for untargeted metabolomics experiments. Though previous LC-HRMS methods have demonstrated quantification capabilities for various drug and small molecule compounds, the present study provides an HRMS quant/qual platform tailored to metabolic disease; and covers a multitude of different metabolites including compounds normally quantified by a combination of separate instrumentation.

  2. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

    Energy Technology Data Exchange (ETDEWEB)

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Gouveia-Figueira, Sandra [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå (Sweden); Pinto, Rui [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Bioinformatics Infrastructure for Life Sciences (Sweden); Trygg, Johan [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Zivkovic, Angela M. [Department of Nutrition, University of California, Davis, One Shields Ave, CA 95616 (United States); Nording, Malin L., E-mail: malin.nording@umu.se [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden)

    2016-02-18

    multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype. - Highlights: • GC-MS, LC-MS and NMR platforms to cover a wide range of metabolites in plasma. • Univariate and multivariate data analysis. • Stable postprandial response over time largely independent of the background diet.

  3. Metabolomics, a Powerful Tool for Agricultural Research

    Directory of Open Access Journals (Sweden)

    He Tian

    2016-11-01

    Full Text Available Metabolomics, which is based mainly on nuclear magnetic resonance (NMR, gas-chromatography (GC or liquid-chromatography (LC coupled to mass spectrometry (MS analytical technologies to systematically acquire the qualitative and quantitative information of low-molecular-mass endogenous metabolites, provides a direct snapshot of the physiological condition in biological samples. As complements to transcriptomics and proteomics, it has played pivotal roles in agricultural and food science research. In this review, we discuss the capacities of NMR, GC/LC-MS in the acquisition of plant metabolome, and address the potential promise and diverse applications of metabolomics, particularly lipidomics, to investigate the responses of Arabidopsis thaliana, a primary plant model for agricultural research, to environmental stressors including heat, freezing, drought, and salinity.

  4. Microbiome, Metabolome and Inflammatory Bowel Disease

    Directory of Open Access Journals (Sweden)

    Ishfaq Ahmed

    2016-06-01

    Full Text Available Inflammatory Bowel Disease (IBD is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD or Ulcerative Colitis (UC, two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis.

  5. Metabolomics to Explore Impact of Dairy Intake

    Science.gov (United States)

    Zheng, Hong; Clausen, Morten R.; Dalsgaard, Trine K.; Bertram, Hanne C.

    2015-01-01

    Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health. PMID:26091233

  6. Metabolomics to Explore Impact of Dairy Intake.

    Science.gov (United States)

    Zheng, Hong; Clausen, Morten R; Dalsgaard, Trine K; Bertram, Hanne C

    2015-06-17

    Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health.

  7. Metabolomics: Definitions and Significance in Systems Biology.

    Science.gov (United States)

    Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

    2017-01-01

    Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

  8. NMR metabolomics of renal cancer: an overview.

    Science.gov (United States)

    Gil, Ana M; de Pinho, Paula Guedes; Monteiro, Márcia S; Duarte, Iola F

    2015-09-23

    This paper reviews the use of NMR metabolomics for the metabolic characterization of renal cancer. The existing challenges in the clinical management of this disease are first presented, followed by a brief introduction to the metabolomics approach, in the context of cancer research. A subsequent review of the literature on NMR metabolic studies of renal cancer reveals that the subject has been clearly underdeveloped, compared with other types of cancer, particularly regarding cultured cells and tissue analysis. NMR analysis of biofluids has focused on blood (plasma or serum) metabolomics, comprising no account of studies on human urine, in spite of its noninvasiveness and physiological proximity to the affected organs. Finally, some areas of potential future development are identified.

  9. Metabolomics to Explore Impact of Dairy Intake

    Directory of Open Access Journals (Sweden)

    Hong Zheng

    2015-06-01

    Full Text Available Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health.

  10. Linking metabolomics data to underlying metabolic regulation

    Directory of Open Access Journals (Sweden)

    Thomas eNägele

    2014-11-01

    Full Text Available The comprehensive experimental analysis of a metabolic constitution plays a central role in approaches of organismal systems biology.Quantifying the impact of a changing environment on the homeostasis of cellular metabolism has been the focus of numerous studies applying various metabolomics techniques. It has been proven that approaches which integrate different analytical techniques, e.g. LC-MS, GC-MS, CE-MS and H-NMR, can provide a comprehensive picture of a certain metabolic homeostasis. Identification of metabolic compounds and quantification of metabolite levels represent the groundwork for the analysis of regulatory strategies in cellular metabolism. This significantly promotes our current understanding of the molecular organization and regulation of cells, tissues and whole organisms.Nevertheless, it is demanding to elicit the pertinent information which is contained in metabolomics data sets.Based on the central dogma of molecular biology, metabolite levels and their fluctuations are the result of a directed flux of information from gene activation over transcription to translation and posttranslational modification.Hence, metabolomics data represent the summed output of a metabolic system comprising various levels of molecular organization.As a consequence, the inverse assignment of metabolomics data to underlying regulatory processes should yield information which-if deciphered correctly-provides comprehensive insight into a metabolic system.Yet, the deduction of regulatory principles is complex not only due to the high number of metabolic compounds, but also because of a high level of cellular compartmentalization and differentiation.Motivated by the question how metabolomics approaches can provide a representative view on regulatory biochemical processes, this article intends to present and discuss current metabolomics applications, strategies of data analysis and their limitations with respect to the interpretability in context of

  11. Metabolomics data normalization with EigenMS.

    Science.gov (United States)

    Karpievitch, Yuliya V; Nikolic, Sonja B; Wilson, Richard; Sharman, James E; Edwards, Lindsay M

    2014-01-01

    Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated). Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (pmetabolomics data.

  12. Metabolomics of cerebrospinal fluid reveals changes in the central nervous system metabolism in a rat model of multiple sclerosis

    NARCIS (Netherlands)

    Noga, M.J.; Dane, A.; Shi, S.; Attali, A.; Aken, H. van; Suidgeest, E.; Tuinstra, T.; Muilwijk, B.; Coulier, L.; Luider, T.; Reijmers, T.H.; Vreeken, R.J.; Hankemeier, T.

    2012-01-01

    Experimental Autoimmune Encephalomyelitis (EAE) is the most commonly used animal model for Multiple Sclerosis (MScl). CSF metabolomics in an acute EAE rat model was investigated using targetted LC-MS and GC-MS. Acute EAE in Lewis rats was induced by co-injection of Myelin Basic Protein with Complete

  13. Metabolomics of cerebrospinal fluid reveals changes in the central nervous system metabolism in a rat model of multiple sclerosis

    NARCIS (Netherlands)

    M. Noga (Marek); A. Dane (Adrie); S. Shi (Shanna); A. Attali (Amos); H. van Aken (Hans); E. Suidgeest (Ernst); T. Tuinstra (Tinka); B. Muilwijk (Bas); L. Coulier (Leon); T.M. Luider (Theo); R.M. Reijmers (Rogier); R. Vreeken (Rob); T. Hankemeier (Thomas)

    2012-01-01

    textabstractExperimental Autoimmune Encephalomyelitis (EAE) is the most commonly used animal model for Multiple Sclerosis (MScl). CSF metabolomics in an acute EAE rat model was investigated using targetted LC-MS and GC-MS. Acute EAE in Lewis rats was induced by co-injection of Myelin Basic Protein

  14. System-wide Analysis of SUMOylation Dynamics in Response to Replication Stress Reveals Novel Small Ubiquitin-like Modified Target Proteins and Acceptor Lysines Relevant for Genome Stability

    DEFF Research Database (Denmark)

    Xiao, Zhenyu; Chang, Jer-Gung; Hendriks, Ivo A

    2015-01-01

    Genotoxic agents can cause replication fork stalling in dividing cells due to DNA lesions, eventually leading to replication fork collapse when the damage is not repaired. Small Ubiquitin-like Modifiers (SUMOs) are known to counteract replication stress, nevertheless, only a small number...... of relevant SUMO target proteins are known. To address this, we have purified and identified SUMO-2 target proteins regulated by replication stress in human cells. The developed methodology enabled single step purification of His10-SUMO-2 conjugates under denaturing conditions with high yield and high purity....... Following statistical analysis on five biological replicates, a total of 566 SUMO-2 targets were identified. After 2 hours of Hydroxyurea treatment, 10 proteins were up-regulated for SUMOylation and 2 proteins were down-regulated for SUMOylation, whereas after 24 hours, 35 proteins were up...

  15. COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access

    NARCIS (Netherlands)

    Salek, R.M.; Neumann, S.; Schober, D.; Hummel, J.; Billiau, K.; Kopka, J.; Correa, E.; Reijmers, T.; Rosato, A.; Tenori, L.; Turano, P.; Marin, S.; Deborde, C.; Jacob, D.; Rolin, D.; Dartigues, B.; Conesa, P.; Haug, K.; Rocca-Serra, P.; O’Hagan, S.; Hao, J.; Vliet, M. van; Sysi-Aho, M.; Ludwig, C.; Bouwman, J.; Cascante, M.; Ebbels, T.; Griffin, J.L.; Moing, A.; Nikolski, M.; Oresic, M.; Sansone, S.A.; Viant, M.R.; Goodacre, R.; Günther, U.L.; Hankemeier, T.; Luchinat, C.; Walther, D.; Steinbeck, C.

    2015-01-01

    Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and

  16. Metabolomic markers reveal novel pathways of ageing and early development in human populations

    OpenAIRE

    Menni, C.; Kastenmuller, G.; Petersen, A.K.; Bell, J.T.; Psatha, M.; Tsai, P.-C.; Gieger, C.; Schulz, H.; I. Erte; John, S.; Brosnan, M J; Wilson, S. G.; Tsaprouni, L.; Lim, E. M.; Stuckey, B.

    2013-01-01

    Background Human ageing is a complex, multifactorial process and early developmental factors affect health outcomes in old age. Methods Metabolomic profiling on fasting blood was carried out in 6055 individuals from the UK. Stepwise regression was performed to identify a panel of independent metabolites which could be used as a surrogate for age. We also investigated the association with birthweight overall and within identical discordant twins and with genome-wide methylation levels. Results...

  17. Annotation of plant gene function via combined genomics, metabolomics and informatics

    OpenAIRE

    Tohge, T.; Fernie, A.

    2012-01-01

    Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known functi...

  18. Nutrigenomics and metabolomics will change clinical nutrition and public health practice: insights from studies on dietary requirements for choline2

    Science.gov (United States)

    Zeisel, Steven H

    2008-01-01

    Science is beginning to understand how genetic variation and epigenetic events alter requirements for, and responses to, nutrients (nutrigenomics). At the same time, methods for profiling almost all of the products of metabolism in a single sample of blood or urine are being developed (metabolomics). Relations between diet and nutrigenomic and metabolomic profiles and between those profiles and health have become important components of research that could change clinical practice in nutrition. Most nutrition studies assume that all persons have average dietary requirements, and the studies often do not plan for a large subset of subjects who differ in requirements for a nutrient. Large variances in responses that occur when such a population exists can result in statistical analyses that argue for a null effect. If nutrition studies could better identify responders and differentiate them from nonresponders on the basis of nutrigenomic or metabolomic profiles, the sensitivity to detect differences between groups could be greatly increased, and the resulting dietary recommendations could be appropriately targeted. It is not certain that nutrition will be the clinical specialty primarily responsible for nutrigenomics or metabolomics, because other disciplines currently dominate the development of portions of these fields. However, nutrition scientists' depth of understanding of human metabolism can be used to establish a role in the research and clinical programs that will arise from nutrigenomic and metabolomic profiling. Investments made today in training programs and in research methods could ensure a new foundation for clinical nutrition in the future. PMID:17823415

  19. Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases

    Directory of Open Access Journals (Sweden)

    Jianhong Lu

    2017-08-01

    Full Text Available Coronary heart disease (CHD is a complex human disease associated with inflammation and oxidative stress. The underlying mechanisms and diagnostic biomarkers for the different types of CHD remain poorly defined. Metabolomics has been increasingly recognized as an enabling technique with the potential to identify key metabolomic features in an attempt to understand the pathophysiology and differentiate different stages of CHD. We performed comprehensive metabolomic analysis in human plasma from 28 human subjects with stable angina (SA, myocardial infarction (MI, and healthy control (HC. Subsequent analysis demonstrated a uniquely altered metabolic profile in these CHD: a total of 18, 37 and 36 differential metabolites were identified to distinguish SA from HC, MI from SA, and MI from HC groups respectively. Among these metabolites, glycerophospholipid (GPL metabolism emerged as the most significantly disturbed pathway. Next, we used a targeted metabolomic approach to systematically analyze GPL, oxidized phospholipid (oxPL, and downstream metabolites derived from polyunsaturated fatty acids (PUFAs, such as arachidonic acid and linoleic acid. Surprisingly, lipids associated with lipid peroxidation (LPO pathways including oxidized PL and isoprostanes, isomers of prostaglandins, were significantly elevated in plasma of MI patients comparing to HC and SA, consistent with the notion that oxidative stress-induced LPO is a prominent feature in CHD. Our studies using the state-of-the-art metabolomics help to understand the underlying biological mechanisms involved in the pathogenesis of CHD; LPO metabolites may serve as potential biomarkers to differentiation MI from SA and HC.

  20. Transcriptome/degradome-wide identification of R. glutinosa miRNAs and their targets: the role of miRNA activity in the replanting disease.

    Directory of Open Access Journals (Sweden)

    Ming Jie Li

    Full Text Available Rehmannia glutinosa, a traditional Chinese medicine herb, is unable to grow normally in a soil where the same species has recently been cultivated. The biological basis of this so called "replanting disease" is unknown, but it may involve the action of microRNAs (miRNAs, which are known to be important regulators of plant growth and development. High throughput Solexa/Illumina sequencing was used to generate a transcript library of the R. glutinosa transcriptome and degradome in order to identify possible miRNAs and their targets implicated in the replanting disease. A total of 87,665 unigenes and 589 miRNA families (17 of which have not been identified in plants to date was identified from the libraries made from a first year (FP and a second year (SP crop. A comparison between the FP and SP miRNAs showed that the abundance of eight of the novel and 295 of the known miRNA families differed between the FP and SP plants. Sequencing of the degradome sampled from FP and SP plants led to the identification of 165 transcript targets of 85 of the differentially abundant miRNA families. The interaction of some of these miRNAs with their target(s is likely to form an important part of the molecular basis of the replanting disease of R. glutinosa.

  1. Genome-wide identification and characterization of cadmium-responsive microRNAs and their target genes in radish (Raphanus sativus L.) roots.

    Science.gov (United States)

    Xu, Liang; Wang, Yan; Zhai, Lulu; Xu, Yuanyuan; Wang, Liangju; Zhu, Xianwen; Gong, Yiqin; Yu, Rugang; Limera, Cecilia; Liu, Liwang

    2013-11-01

    MicroRNAs (miRNAs) are endogenous non-coding small RNAs that play vital regulatory roles in plant growth, development, and environmental stress responses. Cadmium (Cd) is a non-essential heavy metal that is highly toxic to living organisms. To date, a number of conserved and non-conserved miRNAs have been identified to be involved in response to Cd stress in some plant species. However, the miRNA-mediated gene regulatory networks responsive to Cd stress in radish (Raphanus sativus L.) remain largely unexplored. To dissect Cd-responsive miRNAs and their targets systematically at the global level, two small RNA libraries were constructed from Cd-treated and Cd-free roots of radish seedlings. Using Solexa sequencing technology, 93 conserved and 16 non-conserved miRNAs (representing 26 miRNA families) and 28 novel miRNAs (representing 22 miRNA families) were identified. In all, 15 known and eight novel miRNA families were significantly differently regulated under Cd stress. The expression patterns of a set of Cd-responsive miRNAs were validated by quantitative real-time PCR. Based on the radish mRNA transcriptome, 18 and 71 targets for novel and known miRNA families, respectively, were identified by the degradome sequencing approach. Furthermore, a few target transcripts including phytochelatin synthase 1 (PCS1), iron transporter protein, and ABC transporter protein were involved in plant response to Cd stress. This study represents the first transcriptome-based analysis of miRNAs and their targets responsive to Cd stress in radish roots. These findings could provide valuable information for functional characterization of miRNAs and their targets in regulatory networks responsive to Cd stress in radish.

  2. Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M.

    Science.gov (United States)

    Pradeepkiran, Jangampalli Adi; Sainath, Sri Bhashyam; Kumar, Konidala Kranthi; Bhaskar, Matcha

    2015-01-01

    Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes) to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50%) to Silicibacter pomeroyi DUF1285 family protein (2RE3). A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the glycerol structural analogs from the PubChem database. We identified five best inhibitors with strong affinities, stable interactions, and also with reliable drug-like properties. Hence, these leads might be used as the most effective inhibitors of modeled protein. The outcome of the present work of virtual screening of putative gene targets might facilitate design of potential drugs for better treatment against brucellosis.

  3. NMR-based metabolomics in human disease diagnosis: Applications, limitations, and recommendations

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2013-04-03

    Metabolomics is a dynamic and emerging research field, similar to proteomics, transcriptomics and genomics in affording global understanding of biological systems. It is particularly useful in functional genomic studies in which metabolism is thought to be perturbed. Metabolomics provides a snapshot of the metabolic dynamics that reflect the response of living systems to both pathophysiological stimuli and/or genetic modification. Because this approach makes possible the examination of interactions between an organism and its diet or environment, it is particularly useful for identifying biomarkers of disease processes that involve the environment. For example, the interaction of a high fat diet with cardiovascular disease can be studied via such a metabolomics approach by modeling the interaction between genes and diet. The high reproducibility of NMR-based techniques gives this method a number of advantages over other analytical techniques in large-scale and long-term metabolomic studies, such as epidemiological studies. This approach has been used to study a wide range of diseases, through the examination of biofluids, including blood plasma/serum, urine, blister fluid, saliva and semen, as well as tissue extracts and intact tissue biopsies. However, complicating the use of NMR spectroscopy in biomarker discovery is the fact that numerous variables can effect metabolic composition including, fasting, stress, drug administration, diet, gender, age, physical activity, life style and the subject\\'s health condition. To minimize the influence of these variations in the datasets, all experimental conditions including sample collection, storage, preparation as well as NMR spectroscopic parameters and data analysis should be optimized carefully and conducted in an identical manner as described by the local standard operating protocol. This review highlights the potential applications of NMR-based metabolomics studies and gives some recommendations to improve sample

  4. Impact of Soil Warming on the Plant Metabolome of Icelandic Grasslands

    Science.gov (United States)

    Gargallo-Garriga, Albert; Ayala-Roque, Marta; Granda, Victor; Sigurdsson, Bjarni D.; Leblans, Niki I. W.; Oravec, Michal; Urban, Otmar; Janssens, Ivan A.

    2017-01-01

    Climate change is stronger at high than at temperate and tropical latitudes. The natural geothermal conditions in southern Iceland provide an opportunity to study the impact of warming on plants, because of the geothermal bedrock channels that induce stable gradients of soil temperature. We studied two valleys, one where such gradients have been present for centuries (long-term treatment), and another where new gradients were created in 2008 after a shallow crustal earthquake (short-term treatment). We studied the impact of soil warming (0 to +15 °C) on the foliar metabolomes of two common plant species of high northern latitudes: Agrostis capillaris, a monocotyledon grass; and Ranunculus acris, a dicotyledonous herb, and evaluated the dependence of shifts in their metabolomes on the length of the warming treatment. The two species responded differently to warming, depending on the length of exposure. The grass metabolome clearly shifted at the site of long-term warming, but the herb metabolome did not. The main up-regulated compounds at the highest temperatures at the long-term site were saccharides and amino acids, both involved in heat-shock metabolic pathways. Moreover, some secondary metabolites, such as phenolic acids and terpenes, associated with a wide array of stresses, were also up-regulated. Most current climatic models predict an increase in annual average temperature between 2–8 °C over land masses in the Arctic towards the end of this century. The metabolomes of A. capillaris and R. acris shifted abruptly and nonlinearly to soil warming >5 °C above the control temperature for the coming decades. These results thus suggest that a slight warming increase may not imply substantial changes in plant function, but if the temperature rises more than 5 °C, warming may end up triggering metabolic pathways associated with heat stress in some plant species currently dominant in this region. PMID:28832555

  5. Application of 1H-NMR metabolomic profiling for reef-building corals.

    Directory of Open Access Journals (Sweden)

    Emilia M Sogin

    Full Text Available In light of global reef decline new methods to accurately, cheaply, and quickly evaluate coral metabolic states are needed to assess reef health. Metabolomic profiling can describe the response of individuals to disturbance (i.e., shifts in environmental conditions across biological models and is a powerful approach for characterizing and comparing coral metabolism. For the first time, we assess the utility of a proton-nuclear magnetic resonance spectroscopy (1H-NMR-based metabolomics approach in characterizing coral metabolite profiles by 1 investigating technical, intra-, and inter-sample variation, 2 evaluating the ability to recover targeted metabolite spikes, and 3 assessing the potential for this method to differentiate among coral species. Our results indicate 1H-NMR profiling of Porites compressa corals is highly reproducible and exhibits low levels of variability within and among colonies. The spiking experiments validate the sensitivity of our methods and showcase the capacity of orthogonal partial least squares discriminate analysis (OPLS-DA to distinguish between profiles spiked with varying metabolite concentrations (0 mM, 0.1 mM, and 10 mM. Finally, 1H-NMR metabolomics coupled with OPLS-DA, revealed species-specific patterns in metabolite profiles among four reef-building corals (Pocillopora damicornis, Porites lobata, Montipora aequituberculata, and Seriatopora hystrix. Collectively, these data indicate that 1H-NMR metabolomic techniques can profile reef-building coral metabolomes and have the potential to provide an integrated picture of the coral phenotype in response to environmental change.

  6. Metabolomic biomarkers predictive of early structural lung disease in cystic fibrosis.

    Science.gov (United States)

    Esther, Charles R; Turkovic, Lidija; Rosenow, Tim; Muhlebach, Marianne S; Boucher, Richard C; Ranganathan, Sarath; Stick, Stephen M

    2016-12-01

    Neutrophilic airway inflammation plays a role in early structural lung disease in cystic fibrosis, but the mechanisms underlying this pathway are incompletely understood.Metabolites associated with neutrophilic inflammation were identified by discovery metabolomics on bronchoalveolar lavage fluid supernatant from 20 preschool children (2.9±1.3 years) with cystic fibrosis. Targeted mass-spectrometric detection of relevant metabolites was then applied to 34 children (3.5±1.5 years) enrolled in the Australian Respiratory Early Surveillance Team for Cystic Fibrosis (AREST CF) who underwent chest computed tomography and bronchoalveolar lavage from two separate lobes during 42 visits. Relationships between metabolites and localised structural lung disease were assessed using multivariate analyses.Discovery metabolomics identified 93 metabolites associated with neutrophilic inflammation, including pathways involved in metabolism of adenyl purines, amino acids and small peptides, cellular energy and lipids. In targeted mass spectrometry, products of adenosine metabolism, protein catabolism and oxidative stress were associated with structural lung disease and predicted future bronchiectasis, and activities of enzymes associated with adenosine metabolism were elevated in the samples with early disease.Metabolomics analyses revealed metabolites and pathways altered with neutrophilic inflammation and destructive lung disease. These pathways can serve as biomarkers and potential therapeutic targets for early cystic fibrosis lung disease. Copyright ©ERS 2016.

  7. Genome-wide identification of microRNAs and their targets in the leaves and fruit of Eucommia ulmoides using high-throughput sequencing

    Directory of Open Access Journals (Sweden)

    Lin Wang

    2016-11-01

    Full Text Available MicroRNAs (miRNAs, a group of endogenous small non-coding RNAs, play important roles in plant growth, development, and stress response processes. Eucommia ulmoides Oliver (hardy rubber tree is one of the few woody plants capable of producing trans-1, 4-polyisoprene (TPI, also known as Eu-rubber, which has been utilized as an industrial raw material and is extensively cultivated in China. However, the mechanism of TPI biosynthesis has not been identified in E. ulmoides. To characterize small RNAs and their targets with potential biological roles involved in the TPI biosynthesis in E. ulmoides, in the present study, eight small RNA libraries were constructed and sequenced from young and mature leaves and fruits of E. ulmoides. Further analysis identified 34 conserved miRNAs belonging to 20 families (two unclassified families, and 115 novel miRNAs seemed to be specific to E. ulmoides. Among these miRNAs, fourteen conserved miRNAs and 49 novel miRNAs were significantly differentially expressed and identified as Eu-rubber accumulation related miRNAs. Based on the E. ulmoides genomic data, 202 and 306 potential target genes were predicted for 33 conserved and 94 novel miRNAs, respectively; the predicted targets are mostly transcription factors and functional genes, which were enriched in metabolic pathways and biosynthesis of secondary metabolites. Noticeably, based on the expression patterns of miRNAs and their target genes in combination with the Eu-rubber accumulation, the negative correlation of expression of six miRNAs (Eu-miR14, Eu-miR91, miR162a, miR166a, miR172c, and miR396a and their predicted targets serving as potential regulators in Eu-rubber accumulation. This study is the first to detect conserved and novel miRNAs and their potential targets in E. ulmoides and identify several candidate genes potentially controlling rubber accumulation, and thus provide molecular evidence for understanding the roles of miRNAs in regulating the TPI

  8. Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M

    Directory of Open Access Journals (Sweden)

    Pradeepkiran JA

    2015-03-01

    Full Text Available Jangampalli Adi Pradeepkiran,1* Sri Bhashyam Sainath,2,3* Konidala Kranthi Kumar,1 Matcha Bhaskar1 1Division of Animal Biotechnology, Department of Zoology, Sri Venkateswara University, Tirupati, India; 2CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas, Porto, Portugal, 3Department of Biotechnology, Vikrama Simhapuri University, Nellore, Andhra Pradesh, India *These authors contributed equally to this work Abstract: Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50% to Silicibacter pomeroyi DUF1285 family protein (2RE3. A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the

  9. Development of a Postcolumn Infused-Internal Standard Liquid Chromatography Mass Spectrometry Method for Quantitative Metabolomics Studies.

    Science.gov (United States)

    Liao, Hsiao-Wei; Chen, Guan-Yuan; Wu, Ming-Shiang; Liao, Wei-Chih; Lin, Ching-Hung; Kuo, Ching-Hua

    2017-02-03

    Quantitative metabolomics has become much more important in clinical research in recent years. Individual differences in matrix effects (MEs) and the injection order effect are two major factors that reduce the quantification accuracy in liquid chromatography-electrospray ionization-mass spectrometry-based (LC-ESI-MS) metabolomics studies. This study proposed a postcolumn infused-internal standard (PCI-IS) combined with a matrix normalization factor (MNF) strategy to improve the analytical accuracy of quantitative metabolomics. The PCI-IS combined with the MNF method was applied for a targeted metabolomics study of amino acids (AAs). D8-Phenylalanine was used as the PCI-IS, and it was postcolumn-infused into the ESI interface for calibration purposes. The MNF was used to bridge the AA response in a standard solution with the plasma samples. The MEs caused signal changes that were corrected by dividing the AA signal intensities by the PCI-IS intensities after adjustment with the MNF. After the method validation, we evaluated the method applicability for breast cancer research using 100 plasma samples. The quantification results revealed that the 11 tested AAs exhibit an accuracy between 88.2 and 110.7%. The principal component analysis score plot revealed that the injection order effect can be successfully removed, and most of the within-group variation of the tested AAs decreased after the PCI-IS correction. Finally, targeted metabolomics studies on the AAs showed that tryptophan was expressed more in malignant patients than in the benign group. We anticipate that a similar approach can be applied to other endogenous metabolites to facilitate quantitative metabolomics studies.

  10. Genome-wide analysis reveals NRP1 as a direct HIF1 alpha-E2F7 target in the regulation of motorneuron guidance in vivo

    NARCIS (Netherlands)

    de Bruin, Alain; Cornelissen, Peter W. A.; Kirchmaier, Bettina C.; Mokry, Michal; Iich, Elhadi; Nirmala, Ella; Liang, Kuo-Hsuan; Vegh, Anna M. D.; Scholman, Koen T.; Koerkamp, Marian J. Groot; Holstege, Frank C.; Cuppen, Edwin; Schulte-Merker, Stefan; Bakker, Walbert J.

    2016-01-01

    In this study, we explored the existence of a transcriptional network co-regulated by E2F7 and HIF1 alpha, as we show that expression of E2F7, like HIF1 alpha, is induced in hypoxia, and because of the previously reported ability of E2F7 to interact with HIF1 alpha. Our genome-wide analysis uncovers

  11. Metabolome classification of Brassica napus L. organs via UPLC-QTOF-PDA-MS and their anti-oxidant potential.

    Science.gov (United States)

    Farag, Mohamed A; Sharaf Eldin, Mohamed G; Kassem, Hanaa; Abou el Fetouh, Mohamed

    2013-01-01

    Brassica napus L. is a crop widely grown for its oil production and other nutritional components in the seed. In addition to the seed, other organs contain a wide range of phenolic metabolites although they have not been investigated to the same extent as in seeds. To define and compare the phytochemical composition of B. napus L. organs, namely the root, stem, leaf, inflorescence and seeds. Non-targeted metabolomic analysis via UPLC-QTOF-MS was utilised in order to localise compounds belonging to various chemical classes (i.e. oxygenated fatty acids, flavonols, phenolic acids and sinapoyl choline derivatives). The vast majority of identified metabolites were flavonol glycosides that accumulated in most of the plant organs. Whereas other classes were detected predominantly in specific organs, i.e. sinapoyl cholines were present uniquely in seeds. Furthermore, variation in the accumulation pattern of metabolites from the same class was observed, particularly in the case of quercetin, kaempferol and isorhamnetin flavonols. Anti-oxidant activity, based on 2,2-diphenyl-1-picrylhdrazyl analysis was observed for all extracts, and correlated to some extent with total flavonoid content. This study provides the most complete map for polyphenol composition in B. napus L. organs. By describing the metabolites profile in B. napus L., this study provides the basis for future investigations of seeds for potential health and/or medicinal use. Copyright © 2012 John Wiley & Sons, Ltd.

  12. Dynamic metabolomic data analysis: a tutorial review

    NARCIS (Netherlands)

    Smilde, A.K.; Westerhuis, J.A.; Hoefsloot, H.C.J.; Bijlsma, S.; Rubingh, C.M.; Vis, D.J.; Jellema, R.H.; Pijl, H.; Roelfsema, F.; van der Greef, J.

    2010-01-01

    In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic

  13. Dynamic metabolomic data analysis : A tutorial review

    NARCIS (Netherlands)

    Smilde, A.K.; Westerhuis, J.A.; Hoefsloot, H.C.J.; Bijlsma, S.; Rubingh, C.M.; Vis, D.J.; Jellema, R.H.; Pijl, H.; Roelfsema, F.; Greef, J. van der

    2010-01-01

    In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic

  14. Exploring the analysis of structured metabolomics data

    NARCIS (Netherlands)

    Verouden, M.P.H.; Westerhuis, J.A.; Werf, M.J. van der; Smilde, A.K.

    2009-01-01

    In metabolomics research a large number of metabolites are measured that reflect the cellular state under the experimental conditions studied. In many occasions the experiments are performed according to an experimental design to make sure that sufficient variation is induced in the metabolite

  15. Chemometrics Methods and Strategies in Metabolomics.

    Science.gov (United States)

    Pinto, Rui Climaco

    2017-01-01

    Chemometrics has been a fundamental discipline for the development of metabolomics, while symbiotically growing with it. From design of experiments, through data processing, to data analysis, chemometrics tools are used to design, process, visualize, explore and analyse metabolomics data.In this chapter, the most commonly used chemometrics methods for data analysis and interpretation of metabolomics experiments will be presented, with focus on multivariate analysis. These are projection-based linear methods, like principal component analysis (PCA) and orthogonal projection to latent structures (OPLS), which facilitate interpretation of the causes behind the observed sample trends, correlation with outcomes or group discrimination analysis. Validation procedures for multivariate methods will be presented and discussed.Univariate analysis is briefly discussed in the context of correlation-based linear regression methods to find associations to outcomes or in analysis of variance-based and logistic regression methods for class discrimination. These methods rely on frequentist statistics, with the determination of p-values and corresponding multiple correction procedures.Several strategies of design-analysis of metabolomics experiments will be discussed, in order to guide the reader through different setups, adopted to better address some experimental issues and to better test the scientific hypotheses.

  16. Cellular Metabolomics for Exposure and Toxicity Assessment

    Science.gov (United States)

    We have developed NMR automation and cell quench methods for cell culture-based metabolomics to study chemical exposure and toxicity. Our flow automation method is robust and free of cross contamination. The direct cell quench method is rapid and effective. Cell culture-based met...

  17. Analysis of metabolomics data from twin families

    NARCIS (Netherlands)

    Draisma, Hermanus Henricus Maria

    2011-01-01

    Metabolomics is the comprehensive analysis of small molecules involved in metabolism, on the basis of samples that have been obtained from organisms in a given physiological state. Data obtained from measurements of trait levels in twin families can be used to elucidate the importance of genetic and

  18. Metabolomic phenotyping of af cloned pig model

    DEFF Research Database (Denmark)

    Clausen, Morten Rahr; Christensen, Kirstine Lykke; Hedemann, Mette Skou

    2011-01-01

    outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5) was for the first time elucidated by nuclear magnetic resonance (NMR)-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n...

  19. Human metabolomics: Strategies to understand biology

    NARCIS (Netherlands)

    Ramautar, R.; Berger, R.; Greef, J. van der; Hankemeier, T.

    2013-01-01

    Metabolomics provides a direct functional read-out of the physiological status of an organism and is in principle ideally suited to describe someone's health status. Whereas only a limited number of small metabolites are used in the clinics, in inborn errors of metabolism an extensive repertoire of

  20. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites

  1. Genome-Wide Investigation of MicroRNAs and Their Targets in Response to Freezing Stress in Medicago sativa L., Based on High-Throughput Sequencing.

    Science.gov (United States)

    Shu, Yongjun; Liu, Ying; Li, Wei; Song, Lili; Zhang, Jun; Guo, Changhong

    2016-01-22

    Winter damage, especially in northern climates, is a major limitation of the utilization of perennial forages such as alfalfa. Therefore, improving freezing tolerance is imperative in alfalfa genetic breeding. However, freezing tolerance is a complex trait that is determined by many genes. To understand the complex regulation mechanisms of freezing tolerance in alfalfa, we performed small RNA sequencing analysis under cold (4°) and freezing (-8°) stress. The sequencing results revealed that 173 known, and 24 novel miRNAs were expressed, and that the expression of 35 miRNAs was affected by cold and/or freezing stress. Meanwhile, 105 target genes cleaved by these miRNAs were characterized by degradome sequencing. These targets were associated with biological regulation, cellular processes, metabolic processes, and response to stress. Interestingly, most of them were characterized as transcription factors (TFs), including auxin response factors, SBP, NAC, AP2/ERF, and GRF, which play important roles in plant abiotic responses. In addition, important miRNAs and mRNAs involved in nodulation were also identified, for example, the relationship between miR169 and the TF CCAAT (also named as NF-YA/HAP2), which suggested that nodulation has an important function in freezing tolerance in alfalfa. Our results provide valuable information to help determine the molecular mechanisms of freezing tolerance in alfalfa, which will aid the application of these miRNAs and their targets in the improvement of freezing tolerance in alfalfa and related plants. Copyright © 2016 Shu et al.

  2. Metabolomics reveals distinct neurochemical profiles associated with stress resilience

    Directory of Open Access Journals (Sweden)

    Brooke N. Dulka

    2017-12-01

    Full Text Available Acute social defeat represents a naturalistic form of conditioned fear and is an excellent model in which to investigate the biological basis of stress resilience. While there is growing interest in identifying biomarkers of stress resilience, until recently, it has not been feasible to associate levels of large numbers of neurochemicals and metabolites to stress-related phenotypes. The objective of the present study was to use an untargeted metabolomics approach to identify known and unknown neurochemicals in select brain regions that distinguish susceptible and resistant individuals in two rodent models of acute social defeat. In the first experiment, male mice were first phenotyped as resistant or susceptible. Then, mice were subjected to acute social defeat, and tissues were immediately collected from the ventromedial prefrontal cortex (vmPFC, basolateral/central amygdala (BLA/CeA, nucleus accumbens (NAc, and dorsal hippocampus (dHPC. Ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS was used for the detection of water-soluble neurochemicals. In the second experiment, male Syrian hamsters were paired in daily agonistic encounters for 2 weeks, during which they formed stable dominant-subordinate relationships. Then, 24 h after the last dominance encounter, animals were exposed to acute social defeat stress. Immediately after social defeat, tissue was collected from the vmPFC, BLA/CeA, NAc, and dHPC for analysis using UPLC-HRMS. Although no single biomarker characterized stress-related phenotypes in both species, commonalities were found. For instance, in both model systems, animals resistant to social defeat stress also show increased concentration of molecules to protect against oxidative stress in the NAc and vmPFC. Additionally, in both mice and hamsters, unidentified spectral features were preliminarily annotated as potential targets for future experiments. Overall, these findings

  3. Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

    Science.gov (United States)

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide–consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry–based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level. PMID:25486521

  4. Metabolomics analysis of metabolic effects of nicotinamide phosphoribosyltransferase (NAMPT inhibition on human cancer cells.

    Directory of Open Access Journals (Sweden)

    Vladimir Tolstikov

    Full Text Available Nicotinamide phosphoribosyltransferase (NAMPT plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide-consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry-based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer and HCT-116 (colorectal cancer cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA, and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level.

  5. Time-resolved metabolomics reveals metabolic modulation in rice foliage

    Directory of Open Access Journals (Sweden)

    Arita Masanori

    2008-06-01

    Full Text Available Abstract Background To elucidate the interaction of dynamics among modules that constitute biological systems, comprehensive datasets obtained from "omics" technologies have been used. In recent plant metabolomics approaches, the reconstruction of metabolic correlation networks has been attempted using statistical techniques. However, the results were unsatisfactory and effective data-mining techniques that apply appropriate comprehensive datasets are needed. Results Using capillary electrophoresis mass spectrometry (CE-MS and capillary electrophoresis diode-array detection (CE-DAD, we analyzed the dynamic changes in the level of 56 basic metabolites in plant foliage (Oryza sativa L. ssp. japonica at hourly intervals over a 24-hr period. Unsupervised clustering of comprehensive metabolic profiles using Kohonen's self-organizing map (SOM allowed classification of the biochemical pathways activated by the light and dark cycle. The carbon and nitrogen (C/N metabolism in both periods was also visualized as a phenotypic linkage map that connects network modules on the basis of traditional metabolic pathways rather than pairwise correlations among metabolites. The regulatory networks of C/N assimilation/dissimilation at each time point were consistent with previous works on plant metabolism. In response to environmental stress, glutathione and spermidine fluctuated synchronously with their regulatory targets. Adenine nucleosides and nicotinamide coenzymes were regulated by phosphorylation and dephosphorylation. We also demonstrated that SOM analysis was applicable to the estimation of unidentifiable metabolites in metabolome analysis. Hierarchical clustering of a correlation coefficient matrix could help identify the bottleneck enzymes that regulate metabolic networks. Conclusion Our results showed that our SOM analysis with appropriate metabolic time-courses effectively revealed the synchronous dynamics among metabolic modules and elucidated the

  6. Genome-wide identification and in silico characterisation of microRNAs, their targets and processing pathway genes in Phaseolus vulgaris L.

    Science.gov (United States)

    de Sousa Cardoso, T C; Portilho, L G; de Oliveira, C L; McKeown, P C; Maluf, W R; Gomes, L A A; Teixeira, T A; do Amaral, L R; Spillane, C; de Souza Gomes, M

    2016-03-01

    Common bean (Phaseolus vulgaris L., Fabaceae) is a globally important staple crop, which is an important source of calories, protein and essential micronutrients. At the genomic level little is known regarding the small non-coding RNAs within the common bean genome. One of the most important classes of such small non-coding RNAs is microRNAs (miRNAs), which control mRNA and protein expression levels in many eukaryotes. Computational methods have been applied to identify putative miRNAs in the genomes of different organisms. In this study, our objective was to comprehensively identify and characterise miRNAs from the genome and transcriptome of P. vulgaris, including both mature and precursor miRNA forms. We also sought to identify the putative proteins involved in miRNA processing and the likely target genes of common bean miRNAs. We identified 221 mature miRNAs and 136 precursor miRNAs distributed across 52 different miRNA families in the P. vulgaris genome. Amongst these, we distinguished 129 novel mature miRNAs and 123 miRNA precursors belonging to 24 different miRNA families. We also identified 31 proteins predicted to participate in the miRNA-processing pathway in P. vulgaris. Finally, we also identified 483 predicted miRNA targets, including many which corroborate results from other species, suggesting that miRNA regulatory systems are evolutionarily conserved and important for plant development. Our results expand the study of miRNAs and their target genes in common bean, and provide new opportunities to understand their roles in the biology of this important staple crop. © 2015 German Botanical Society and The Royal Botanical Society of the Netherlands.

  7. Genome-Wide Mapping Targets of the Metazoan Chromatin Remodeling Factor NURF Reveals Nucleosome Remodeling at Enhancers, Core Promoters and Gene Insulators.

    Directory of Open Access Journals (Sweden)

    So Yeon Kwon

    2016-04-01

    Full Text Available NURF is a conserved higher eukaryotic ISWI-containing chromatin remodeling complex that catalyzes ATP-dependent nucleosome sliding. By sliding nucleosomes, NURF is able to alter chromatin dynamics to control transcription and genome organization. Previous biochemical and genetic analysis of the specificity-subunit of Drosophila NURF (Nurf301/Enhancer of Bithorax (E(bx has defined NURF as a critical regulator of homeotic, heat-shock and steroid-responsive gene transcription. It has been speculated that NURF controls pathway specific transcription by co-operating with sequence-specific transcription factors to remodel chromatin at dedicated enhancers. However, conclusive in vivo demonstration of this is lacking and precise regulatory elements targeted by NURF are poorly defined. To address this, we have generated a comprehensive map of in vivo NURF activity, using MNase-sequencing to determine at base pair resolution NURF target nucleosomes, and ChIP-sequencing to define sites of NURF recruitment. Our data show that, besides anticipated roles at enhancers, NURF interacts physically and functionally with the TRF2/DREF basal transcription factor to organize nucleosomes downstream of active promoters. Moreover, we detect NURF remodeling and recruitment at distal insulator sites, where NURF functionally interacts with and co-localizes with DREF and insulator proteins including CP190 to establish nucleosome-depleted domains. This insulator function of NURF is most apparent at subclasses of insulators that mark the boundaries of chromatin domains, where multiple insulator proteins co-associate. By visualizing the complete repertoire of in vivo NURF chromatin targets, our data provide new insights into how chromatin remodeling can control genome organization and regulatory interactions.

  8. Validation of Metabolic Alterations in Microscale Cell Culture Lysates Using Hydrophilic Interaction Liquid Chromatography (HILIC-Tandem Mass Spectrometry-Based Metabolomics.

    Directory of Open Access Journals (Sweden)

    Venugopal Gunda

    Full Text Available By standard convention, in order to increase the efficacy of metabolite detection from cell culture lysates, metabolite extracts from a large quantity of cells are utilized for multiple reaction monitoring-based metabolomic studies. Metabolomics from a small number of cell extracts offers a potential economical alternative to increased cell numbers, in turn increasing the utility of cell culture-based metabolomics. However, the effect of reduced cell numbers on targeted metabolomic profiling is relatively unstudied. Considering the limited knowledge available of the feasibility and accuracy of microscale cell culture metabolomics, the present study analyzes differences in metabolomic profiles of different cell numbers of three pancreatic cancer cell lines. Specifically, it examines the effects of reduced cell numbers on metabolite profiles by obtaining extracts either directly from microscale culture plates or through serial dilution of increased numbers of cellular metabolite extracts. Our results indicate reduced cell numbers only modestly affect the number of metabolites detected (93% of metabolites detected in cell numbers as low as 104 cells and 97% for 105 cells, independent of the method used to obtain the cells. However, metabolite peak intensities were differentially affected by the reduced cell numbers, with some peak intensities inversely proportional to the cell numbers. To help eliminate such potential inverse relationships, peak intensities for increased cell numbers were excluded from the comparative analysis. Overall, metabolite profiles from microscale culture plates were observed to differ from the serial dilution samples, which may be attributable to the medium-to-cell-number ratios. Finally, findings identify perturbations in metabolomic profiling for cellular extracts from reduced cell numbers, which offer future applications in microscale metabolomic evaluations.

  9. From models to crop species: caveats and solutions for translational metabolomics

    Directory of Open Access Journals (Sweden)

    Takayuki eTohge

    2011-10-01

    Full Text Available Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa that illustrate how such dangers can be detected and circumvented.

  10. The Use of Targeted Marker Subsets to Account for Population Structure and Relatedness in Genome-Wide Association Studies of Maize (Zea mays L.

    Directory of Open Access Journals (Sweden)

    Angela H. Chen

    2016-08-01

    Full Text Available A typical plant genome-wide association study (GWAS uses a mixed linear model (MLM that includes a trait as the response variable, a marker as an explanatory variable, and fixed and random effect covariates accounting for population structure and relatedness. Although effective in controlling for false positive signals, this model typically fails to detect signals that are correlated with population structure or are located in high linkage disequilibrium (LD genomic regions. This result likely arises from each tested marker being used to estimate population structure and relatedness. Previous work has demonstrated that it is possible to increase the power of the MLM by estimating relatedness (i.e., kinship with markers that are not located on the chromosome where the tested marker resides. To quantify the amount of additional significant signals one can expect using this so-called K_chr model, we reanalyzed Mendelian, polygenic, and complex traits in two maize (Zea mays L. diversity panels that have been previously assessed using the traditional MLM. We demonstrated that the K_chr model could find more significant associations, especially in high LD regions. This finding is underscored by our identification of novel genomic signals proximal to the tocochromanol biosynthetic pathway gene ZmVTE1 that are associated with a ratio of tocotrienols. We conclude that the K_chr model can detect more intricate sources of allelic variation underlying agronomically important traits, and should therefore become more widely used for GWAS. To facilitate the implementation of the K_chr model, we provide code written in the R programming language.

  11. Mass Spectrometry-Based Metabolomics to Elucidate Functions in Marine Organisms and Ecosystems

    Directory of Open Access Journals (Sweden)

    Sophie Goulitquer

    2012-04-01

    Full Text Available Marine systems are very diverse and recognized as being sources of a wide range of biomolecules. This review provides an overview of metabolite profiling based on mass spectrometry (MS approaches in marine organisms and their environments, focusing on recent advances in the field. We also point out some of the technical challenges that need to be overcome in order to increase applications of metabolomics in marine systems, including extraction of chemical compounds from different matrices and data management. Metabolites being important links between genotype and phenotype, we describe added value provided by integration of data from metabolite profiling with other layers of omics, as well as their importance for the development of systems biology approaches in marine systems to study several biological processes, and to analyze interactions between organisms within communities. The growing importance of MS-based metabolomics in chemical ecology studies in marine ecosystems is also illustrated.

  12. A metabolomic study on the effect of intravascular laser blood irradiation on type 2 diabetic patients.

    Science.gov (United States)

    Kazemi Khoo, N; Iravani, A; Arjmand, M; Vahabi, F; Lajevardi, M; Akrami, S M; Zamani, Z

    2013-11-01

    Intravenous laser blood irradiation (ILBI) is widely applied in the treatment of different pathologies including diabetes mellitus. The aim of this study is to evaluate the effects of ILBI on the metabolites of blood in diabetic type 2 patients using metabolomics. We compared blood samples of nine diabetic type 2 patients, using metabolomics, before and after ILBI with blue light laser. The results showed significant decrease in glucose, glucose 6 phosphate, dehydroascorbic acid, R-3-hydroxybutyric acid, L-histidine, and L-alanine and significant increase in L-arginine level in blood and blood sugar in the patients have reduced significantly (p blood in diabetic type 2 patients. These findings support the therapeutic potential of ILBI in diabetic patients.

  13. METABOLOMICS IN MEDICAL SCIENCES--TRENDS, CHALLENGES AND PERSPECTIVES.

    Science.gov (United States)

    Klupczyńska, Agnieszka; Dereziński, Paweł; Kokot, Zenon J

    2015-01-01

    Metabolomics is the latest of the "omic" technologies that involves comprehensive analysis of small molecule metabolites of an organism or a specific biological sample. Metabolomics provides an insight into the cell status and describes an actual health condition of organisms. Analysis of metabolome offers a unique opportunity to study the influence of genetic variation, disease, applied treatment or diet on endogenous metabolic state of organisms. There are many areas that might benefit from metabolomic research. In the article some applications of this novel "omic" technology in the field of medical sciences are presented. One of the most popular aims of metabolomic studies is biomarker discovery. Despite using the state-of-art analytical techniques along with advanced bioinformatic tools, metabolomic experiments encounter numerous difficulties and pitfalls. Challenges that researchers in the field of analysis of metabolome have to face include i.a., technical limitations, bioinformatic challenges and integration with other "omic" sciences. One of the grand challenges for studies in the field of metabolomics is to tackle the problem of data analysis, which is probably the most time consuming stage of metabolomic workflow and requires close collaboration between analysts, clinicians and experts in chemometric analysis. Implementation of metabolomics into clinical practice will be dependent on establishment of standardized protocols in analytical performance and data analysis and development of fit-for-purpose biomarker method validation. Metabolomics allows to achieve a sophisticated level of information about biological systems and opens up new perspectives in many fields of medicine, especially in oncology. Apart from its extensive cognitive significance, metabolomics manifests also a practical importance as it may lead to design of new non-invasive, sensitive and specific diagnostic techniques and development of new therapies.

  14. The Brain Metabolome of Male Rats across the Lifespan

    OpenAIRE

    Xiaojiao Zheng; Tianlu Chen; Aihua Zhao; Xiaoyan Wang; Guoxiang Xie; Fengjie Huang; Jiajian Liu; Qing Zhao; Shouli Wang; Chongchong Wang; Mingmei Zhou; Jun Panee; Zhigang He; Wei Jia

    2016-01-01

    Comprehensive and accurate characterization of brain metabolome is fundamental to brain science, but has been hindered by technical limitations. We profiled the brain metabolome in male Wistar rats at different ages (day 1 to week 111) using high-sensitivity and high-resolution mass spectrometry. Totally 380 metabolites were identified and 232 of them were quantitated. Compared with anatomical regions, age had a greater effect on variations in the brain metabolome. Lipids, fatty acids and ami...

  15. Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

    OpenAIRE

    Fujimura, Yoshinori; Kurihara, Kana; Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

    2011-01-01

    BACKGROUND: Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. MET...

  16. Assessing Heterogeneity of Osteolytic Lesions in Multiple Myeloma by 1H HR-MAS NMR Metabolomics

    Directory of Open Access Journals (Sweden)

    Laurette Tavel

    2016-10-01

    Full Text Available Multiple myeloma (MM is a malignancy of plasma cells characterized by multifocal osteolytic bone lesions. Macroscopic and genetic heterogeneity has been documented within MM lesions. Understanding the bases of such heterogeneity may unveil relevant features of MM pathobiology. To this aim, we deployed unbiased 1H high-resolution magic-angle spinning (HR-MAS nuclear magnetic resonance (NMR metabolomics to analyze multiple biopsy specimens of osteolytic lesions from one case of pathological fracture caused by MM. Multivariate analyses on normalized metabolite peak integrals allowed clusterization of samples in accordance with a posteriori histological findings. We investigated the relationship between morphological and NMR features by merging morphological data and metabolite profiling into a single correlation matrix. Data-merging addressed tissue heterogeneity, and greatly facilitated the mapping of lesions and nearby healthy tissues. Our proof-of-principle study reveals integrated metabolomics and histomorphology as a promising approach for the targeted study of osteolytic lesions.

  17. Targeted metabolomics to study lipid peroxidation in biological systems

    NARCIS (Netherlands)

    Labuschagne, C.F.

    2013-01-01

    During normal cellular metabolism reactive oxygen species (ROS) are inevitably formed as by-products of respiration. ROS are extremely reactive molecules and can react with and damage surrounding DNA, protein and lipid molecules and subsequently alter their normal function in the cell. This

  18. MVAPACK: a complete data handling package for NMR metabolomics.

    Science.gov (United States)

    Worley, Bradley; Powers, Robert

    2014-05-16

    Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set.

  19. Metabolomic profiles as reliable biomarkers of dietary composition.

    Science.gov (United States)

    Esko, Tõnu; Hirschhorn, Joel N; Feldman, Henry A; Hsu, Yu-Han H; Deik, Amy A; Clish, Clary B; Ebbeling, Cara B; Ludwig, David S

    2017-03-01

    Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects.Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol.Design: Twenty-one adults with a high body mass index (in kg/m(2); mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons.Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors.Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational

  20. Application of metabolomics: Focus on the quantification of organic acids in healthy adults

    Science.gov (United States)

    Tsoukalas, Dimitris; Alegakis, Athanasios; Fragkiadaki, Persefoni; Papakonstantinou, Evangelos; Nikitovic, Dragana; Karataraki, Aikaterini; Nosyrev, Alexander E.; Papadakis, Emmanouel G.; Spandidos, Demetrios A.; Drakoulis, Nikolaos; Tsatsakis, Aristides M.

    2017-01-01

    Metabolomics, a 'budding' discipline, may accurately reflect a specific phenotype which is sensitive to genetic and epigenetic interactions. This rapidly evolving field in science has been proposed as a tool for the evaluation of the effects of epigenetic factors, such as nutrition, environment, drug and lifestyle on phenotype. Urine, being sterile, is easy to obtain and as it contains metabolized or non-metabolized products, is a favored study material in the field of metabolomics. Urine organic acids (OAs) reflect the activity of main metabolic pathways and have been used to assess health status, nutritional status, vitamin deficiencies and response to xenobiotics. To date, a limited number of studies have been performed which actually define reference OA values in a healthy population and as reference range for epigenetic influences, and not as a reference to congenital metabolic diseases. The aim of the present study was thus the determination of reference values (RVs) for urine OA in a healthy adult population. Targeted metabolomics analysis of 22 OAs in the urine of 122 healthy adults by gas chromatography-mass spectrometry, was conducted. Percentile distributions of the OA concentrations in urine, as a base for determining the RVs in the respective population sample, were used. No significant differences were detected between female and male individuals. These findings can facilitate the more sensitive determination of OAs in pathological conditions. Therefore, the findings of this study may contribute or add to the information already available on urine metabolite databases, and may thus promote the use of targeted metabolomics for the evaluation of OAs in a clinical setting and for pathophysiological evaluation. However, further studies with well-defined patients groups exhibiting specific symptoms or diseases are warranted in order to discern between normal and pathological values. PMID:28498405

  1. Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra

    Energy Technology Data Exchange (ETDEWEB)

    Mercier, Pascal; Lewis, Michael J.; Chang, David, E-mail: dchang@chenomx.com [Chenomx Inc (Canada); Baker, David [Pfizer Inc (United States); Wishart, David S. [University of Alberta, Department of Computing Science and Biological Sciences (Canada)

    2011-04-15

    Nuclear magnetic resonance (NMR) and Mass Spectroscopy (MS) are the two most common spectroscopic analytical techniques employed in metabolomics. The large spectral datasets generated by NMR and MS are often analyzed using data reduction techniques like Principal Component Analysis (PCA). Although rapid, these methods are susceptible to solvent and matrix effects, high rates of false positives, lack of reproducibility and limited data transferability from one platform to the next. Given these limitations, a growing trend in both NMR and MS-based metabolomics is towards targeted profiling or 'quantitative' metabolomics, wherein compounds are identified and quantified via spectral fitting prior to any statistical analysis. Despite the obvious advantages of this method, targeted profiling is hindered by the time required to perform manual or computer-assisted spectral fitting. In an effort to increase data analysis throughput for NMR-based metabolomics, we have developed an automatic method for identifying and quantifying metabolites in one-dimensional (1D) proton NMR spectra. This new algorithm is capable of using carefully constructed reference spectra and optimizing thousands of variables to reconstruct experimental NMR spectra of biofluids using rules and concepts derived from physical chemistry and NMR theory. The automated profiling program has been tested against spectra of synthetic mixtures as well as biological spectra of urine, serum and cerebral spinal fluid (CSF). Our results indicate that the algorithm can correctly identify compounds with high fidelity in each biofluid sample (except for urine). Furthermore, the metabolite concentrations exhibit a very high correlation with both simulated and manually-detected values.

  2. A Genome-Wide Identification of the WRKY Family Genes and a Survey of Potential WRKY Target Genes in Dendrobium officinale.

    Science.gov (United States)

    He, Chunmei; Teixeira da Silva, Jaime A; Tan, Jianwen; Zhang, Jianxia; Pan, Xiaoping; Li, Mingzhi; Luo, Jianping; Duan, Jun

    2017-08-23

    The WRKY family, one of the largest families of transcription factors, plays important roles in the regulation of various biological processes, including growth, development and stress responses in plants. In the present study, 63 DoWRKY genes were identified from the Dendrobium officinale genome. These were classified into groups I, II, III and a non-group, each with 14, 28, 10 and 11 members, respectively. ABA-responsive, sulfur-responsive and low temperature-responsive elements were identified in the 1-k upstream regulatory region of DoWRKY genes. Subsequently, the expression of the 63 DoWRKY genes under cold stress was assessed, and the expression profiles of a large number of these genes were regulated by low temperature in roots and stems. To further understand the regulatory mechanism of DoWRKY genes in biological processes, potential WRKY target genes were investigated. Among them, most stress-related genes contained multiple W-box elements in their promoters. In addition, the genes involved in polysaccharide synthesis and hydrolysis contained W-box elements in their 1-k upstream regulatory regions, suggesting that DoWRKY genes may play a role in polysaccharide metabolism. These results provide a basis for investigating the function of WRKY genes and help to understand the downstream regulation network in plants within the Orchidaceae.

  3. MEET ISOLDE - Target Production

    CERN Multimedia

    2017-01-01

    MEET ISOLDE - Target Production. Everything at ISOLDE starts with a target and the target production team realise on more then 50 years of experience to build and develop new targets for ISOLDE’s wide physics program.

  4. A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice.

    Science.gov (United States)

    Marcobal, A; Kashyap, P C; Nelson, T A; Aronov, P A; Donia, M S; Spormann, A; Fischbach, M A; Sonnenburg, J L

    2013-10-01

    Defining the functional status of host-associated microbial ecosystems has proven challenging owing to the vast number of predicted genes within the microbiome and relatively poor understanding of community dynamics and community-host interaction. Metabolomic approaches, in which a large number of small molecule metabolites can be defined in a biological sample, offer a promising avenue to 'fingerprint' microbiota functional status. Here, we examined the effects of the human gut microbiota on the fecal and urinary metabolome of a humanized (HUM) mouse using an optimized ultra performance liquid chromatography-mass spectrometry-based method. Differences between HUM and conventional mouse urine and fecal metabolomic profiles support host-specific aspects of the microbiota's metabolomic contribution, consistent with distinct microbial compositions. Comparison of microbiota composition and metabolome of mice humanized with different human donors revealed that the vast majority of metabolomic features observed in donor samples are produced in the corresponding HUM mice, and individual-specific features suggest 'personalized' aspects of functionality can be reconstituted in mice. Feeding the mice a defined, custom diet resulted in modification of the metabolite signatures, illustrating that host diet provides an avenue for altering gut microbiota functionality, which in turn can be monitored via metabolomics. Using a defined model microbiota consisting of one or two species, we show that simplified communities can drive major changes in the host metabolomic profile. Our results demonstrate that metabolomics constitutes a powerful avenue for functional characterization of the intestinal microbiota and its interaction with the host.

  5. Identification of new therapeutic targets by genome-wide analysis of gene expression in the ipsilateral cortex of aged rats after stroke.

    Directory of Open Access Journals (Sweden)

    Ana-Maria Buga

    Full Text Available Because most human stroke victims are elderly, studies of experimental stroke in the aged rather than the young rat model may be optimal for identifying clinically relevant cellular responses, as well for pinpointing beneficial interventions.We employed the Affymetrix platform to analyze the whole-gene transcriptome following temporary ligation of the middle cerebral artery in aged and young rats. The correspondence, heat map, and dendrogram analyses independently suggest a differential, age-group-specific behaviour of major gene clusters after stroke. Overall, the pattern of gene expression strongly suggests that the response of the aged rat brain is qualitatively rather than quantitatively different from the young, i.e. the total number of regulated genes is comparable in the two age groups, but the aged rats had great difficulty in mounting a timely response to stroke. Our study indicates that four genes related to neuropathic syndrome, stress, anxiety disorders and depression (Acvr1c, Cort, Htr2b and Pnoc may have impaired response to stroke in aged rats. New therapeutic options in aged rats may also include Calcrl, Cyp11b1, Prcp, Cebpa, Cfd, Gpnmb, Fcgr2b, Fcgr3a, Tnfrsf26, Adam 17 and Mmp14. An unexpected target is the enzyme 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 in aged rats, a key enzyme in the cholesterol synthesis pathway. Post-stroke axonal growth was compromised in both age groups.We suggest that a multi-stage, multimodal treatment in aged animals may be more likely to produce positive results. Such a therapeutic approach should be focused on tissue restoration but should also address other aspects of patient post-stroke therapy such as neuropathic syndrome, stress, anxiety disorders, depression, neurotransmission and blood pressure.

  6. Metabolomic analysis of three Mollicute species.

    Directory of Open Access Journals (Sweden)

    Anna A Vanyushkina

    Full Text Available We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer.

  7. Menthol Smokers: Metabolomic Profiling and Smoking Behavior.

    Science.gov (United States)

    Hsu, Ping-Ching; Lan, Renny S; Brasky, Theodore M; Marian, Catalin; Cheema, Amrita K; Ressom, Habtom W; Loffredo, Christopher A; Pickworth, Wallace B; Shields, Peter G

    2017-01-01

    The use of menthol in cigarettes and marketing is under consideration for regulation by the FDA. However, the effects of menthol on smoking behavior and carcinogen exposure have been inconclusive. We previously reported metabolomic profiling for cigarette smokers, and novelly identified a menthol-glucuronide (MG) as the most significant metabolite directly related to smoking. Here, MG is studied in relation to smoking behavior and metabolomic profiles. This is a cross-sectional study of 105 smokers who smoked two cigarettes in the laboratory one hour apart. Blood nicotine, MG, and exhaled carbon monoxide (CO) boosts were determined (the difference before and after smoking). Spearman correlation, χ 2 , and ANCOVA adjusted for gender, race, and cotinine levels for menthol smokers assessed the relationship of MG boost, smoking behavior, and metabolic profiles. Multivariate metabolite characterization using supervised partial least squares-discriminant analysis (PLS-DA) was carried out for the classification of metabolomics profiles. MG boost was positively correlated with CO boost, nicotine boost, average puff volume, puff duration, and total smoke exposure. Classification using PLS-DA, MG was the top metabolite discriminating metabolome of menthol versus nonmenthol smokers. Among menthol smokers, 42 metabolites were significantly correlated with MG boost, which linked to cellular functions, such as of cell death, survival, and movement. Plasma MG boost is a new smoking behavior biomarker that may provide novel information over self-reported use of menthol cigarettes by integrating different smoking measures for understanding smoking behavior and harm of menthol cigarettes. These results provide insight into the biological effect of menthol smoking. Cancer Epidemiol Biomarkers Prev; 26(1); 51-60. ©2016 AACR. ©2016 American Association for Cancer Research.

  8. Recent advances of metabolomics in plant biotechnology

    OpenAIRE

    Okazaki, Yozo; Saito, Kazuki

    2011-01-01

    Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant...

  9. Metabolomics: the apogee of the omic triology

    Science.gov (United States)

    Patti, Gary J; Yanes, Oscar; Siuzdak, Gary

    2013-01-01

    Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and shaping our understanding of cell biology, physiology, and medicine. PMID:22436749

  10. Data fusion in metabolomic cancer diagnostics

    DEFF Research Database (Denmark)

    Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco

    2013-01-01

    We have recently shown that fluorescence spectroscopy of plasma samples has promising abilities regarding early detection of colorectal cancer. In the present paper, these results were further developed by combining fluorescence with the biomarkers, CEA and TIMP-1 and traditional metabolomic...... measurements in the form of (1)H NMR spectroscopy. The results indicate that using an extensive profile established by combining such measurements together with the biomarkers is better than using single markers....

  11. Obesity and Asthma: Microbiome–Metabolome Interactions

    OpenAIRE

    Shore, Stephanie A.; Cho, Youngji

    2016-01-01

    Obesity is a risk factor for asthma, but obese subjects with asthma respond poorly to standard asthma drugs. Obesity also alters gut bacterial community structure. Obesity-related changes in gut bacteria contribute to weight gain and other obesity-related conditions, including insulin resistance and systemic inflammation. Here, we review the rationale for the hypothesis that obesity-related changes in gut bacteria may also play a role in obesity-related asthma. The metabolomes of the liver, s...

  12. Impact of a cafeteria diet and daily physical training on the rat serum metabolome.

    Science.gov (United States)

    Suárez-García, Susana; Del Bas, Josep M; Caimari, Antoni; Escorihuela, Rosa M; Arola, Lluís; Suárez, Manuel

    2017-01-01

    Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS), which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST) or cafeteria diet (CAF) and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which moderate

  13. Impact of a cafeteria diet and daily physical training on the rat serum metabolome.

    Directory of Open Access Journals (Sweden)

    Susana Suárez-García

    Full Text Available Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS, which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST or cafeteria diet (CAF and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which

  14. Integration of datasets from different analytical techniques to assess the impact of nutrition on human metabolome

    Directory of Open Access Journals (Sweden)

    Pamela eVernocchi

    2012-12-01

    Full Text Available Bacteria colonizing the human intestinal tract exhibit a high phylogenetic diversity that reflects their immense metabolic potentials. The catalytic activity of gut microbes has an important impact on gastrointestinal (GI functions and host health. The microbial conversion of carbohydrates and other food components leads to the formation of a large number of compounds that affect the host metabolome and have beneficial or adverse effects on human health. Meabolomics is a metabolic-biology system approach focused on the metabolic responses understanding of living systems to physio-pathological stimuli by using multivariate statistical data on human body fluids obtained by different instrumental techniques. A metabolomic approach based on an analytical platform could be able to separate, detect, characterize and quantify a wide range of metabolites and its metabolic pathways. This approach has been recently applied to study the metabolic changes triggered in the gut microbiota by specific diet components and diet variations, specific diseases, probiotic and synbiotic food intake.This review describes the metabolomic data obtained by analyzing human fluids by using different techniques and particularly Gas Chromatography Mass Spectrometry Solid-phase Micro Extraction (GC-MS/SPME, Proton Nuclear Magnetic Resonance (1H-NMR Spectroscopy and Fourier Transform Infrared (FTIR Spectroscopy. This instrumental approach have a good potential in the identification and detection of specific food intake and diseases biomarkers.

  15. A review of blood sample handling and pre-processing for metabolomics studies.

    Science.gov (United States)

    Hernandes, Vinicius Veri; Barbas, Coral; Dudzik, Danuta

    2017-09-01

    Metabolomics has been found to be applicable to a wide range of clinical studies, bringing a new era for improving clinical diagnostics, early disease detection, therapy prediction and treatment efficiency monitoring. A major challenge in metabolomics, particularly untargeted studies, is the extremely diverse and complex nature of biological specimens. Despite great advances in the field there still exist fundamental needs for considering pre-analytical variability that can introduce bias to the subsequent analytical process and decrease the reliability of the results and moreover confound final research outcomes. Many researchers are mainly focused on the instrumental aspects of the biomarker discovery process, and sample related variables sometimes seem to be overlooked. To bridge the gap, critical information and standardized protocols regarding experimental design and sample handling and pre-processing are highly desired. Characterization of a range variation among sample collection methods is necessary to prevent results misinterpretation and to ensure that observed differences are not due to an experimental bias caused by inconsistencies in sample processing. Herein, a systematic discussion of pre-analytical variables affecting metabolomics studies based on blood derived samples is performed. Furthermore, we provide a set of recommendations concerning experimental design, collection, pre-processing procedures and storage conditions as a practical review that can guide and serve for the standardization of protocols and reduction of undesirable variation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Metabolomic Profiling of Prostate Cancer Progression During Active Surveillance

    Science.gov (United States)

    2012-10-01

    cancer or a history of transurethral resection of the prostate (TURP) for benign prostatic hypertrophy are excluded. Somewhat surprisingly...AD_________________ Award Number: W81XWH-11-1-0451 TITLE: Metabolomic Profiling of Prostate Cancer...29 September 2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Metabolomic Profiling of Prostate Cancer Progression During Active Surveillance 5b

  17. The metabolome 18 years on: a concept comes of age.

    Science.gov (United States)

    Kell, Douglas B; Oliver, Stephen G

    2016-01-01

    The term 'metabolome' was introduced to the scientific literature in September 1998. To mark its 18-year-old 'coming of age', two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

  18. A metabolomics study on human dietary intervention with apples

    DEFF Research Database (Denmark)

    Dragsted, L. O.; Kristensen, M.; Ravn-Haren, Gitte

    2009-01-01

    Metabolomics is a promising tool for searching out new biomarkers and the development of hypotheses in nutrition research. This chapter will describe the design of human dietary intervention studies where samples are collected for metabolomics analyses as well as the analytical issues and data...

  19. Environmental metabolomics: a SWOT analysis (strengths, weaknesses, opportunities, and threats).

    Science.gov (United States)

    Miller, Marion G

    2007-02-01

    Metabolomic approaches have the potential to make an exceptional contribution to understanding how chemicals and other environmental stressors can affect both human and environmental health. However, the application of metabolomics to environmental exposures, although getting underway, has not yet been extensively explored. This review will use a SWOT analysis model to discuss some of the strengths, weaknesses, opportunities, and threats that are apparent to an investigator venturing into this relatively new field. SWOT has been used extensively in business settings to uncover new outlooks and identify problems that would impede progress. The field of environmental metabolomics provides great opportunities for discovery, and this is recognized by a high level of interest in potential applications. However, understanding the biological consequence of environmental exposures can be confounded by inter- and intra-individual differences. Metabolomic profiles can yield a plethora of data, the interpretation of which is complex and still being evaluated and researched. The development of the field will depend on the availability of technologies for data handling and that permit ready access metabolomic databases. Understanding the relevance of metabolomic endpoints to organism health vs adaptation vs variation is an important step in understanding what constitutes a substantive environmental threat. Metabolomic applications in reproductive research are discussed. Overall, the development of a comprehensive mechanistic-based interpretation of metabolomic changes offers the possibility of providing information that will significantly contribute to the protection of human health and the environment.

  20. Potential of metabolomics as a functional genomics tool

    NARCIS (Netherlands)

    Bino, R.J.; Hall, R.D.; Fiehn, O.; Kopka, J.; Saito, K.; Draper, J.; Nikolau, B.J.; Mendes, P.; Roessner-Tunali, U.; Beale, M.; Trethewey, R.N.; Lange, B.M.; Wurtele, E.S.; Sumner, L.W.

    2004-01-01

    Metabolomics is developing as an important functional genomics tool; however, there is still room for technical improvements in both the large-scale determination of metabolites from complex plant tissues and the dissemination of metabolomics research data. For the continued maturation of

  1. Gas chromatography mass spectrometry : key technology in metabolomics

    NARCIS (Netherlands)

    Koek, Maud Marijtje

    2009-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues. Gas chromatography coupled to mass spectrometry (GC-MS) is very suitable for metabolomics analysis, as it combines high separation power with

  2. Metabolome and proteome profiling of complex I deficiency induced by rotenone.

    Science.gov (United States)

    Gielisch, Ina; Meierhofer, David

    2015-01-02

    Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

  3. Metabolomics reveals variation and correlation among different tissues of olive (Olea europaea L.).

    Science.gov (United States)

    Guodong, Rao; Xiaoxia, Liu; Weiwei, Zha; Wenjun, Wu; Jianguo, Zhang

    2017-09-15

    Metabolites in olives are associated with nutritional value and physiological properties. However, comprehensive information regarding the olive metabolome is limited. In this study, we identified 226 metabolites from three different tissues of olive using a non-targeted metabolomic profiling approach, of which 76 named metabolites were confirmed. Further statistical analysis revealed that these 76 metabolites covered different types of primary metabolism and some of the secondary metabolism pathways. One-way analysis of variance (ANOVA) statistical assay was performed to calculate the variations within the detected metabolites, and levels of 65 metabolites were differentially expressed in different samples. Hierarchical cluster analysis (HCA) dendrograms showed variations among different tissues that were similar to the metabolite profiles observed in new leaves and fruit. Additionally, 5776 metabolite-metabolite correlations were detected by a Pearson correlation coefficient approach. Screening of the calculated correlations revealed 3136, 3025, and 5184 were determined to metabolites and had significant correlations in three different combinations, respectively. This work provides the first comprehensive metabolomic of olive, which will provide new insights into understanding the olive metabolism, and potentially help advance studies in olive metabolic engineering. © 2017. Published by The Company of Biologists Ltd.

  4. Metabolomics reveals variation and correlation among different tissues of olive (Olea europaea L.

    Directory of Open Access Journals (Sweden)

    Rao Guodong

    2017-09-01

    Full Text Available Metabolites in olives are associated with nutritional value and physiological properties. However, comprehensive information regarding the olive metabolome is limited. In this study, we identified 226 metabolites from three different tissues of olive using a non-targeted metabolomic profiling approach, of which 76 named metabolites were confirmed. Further statistical analysis revealed that these 76 metabolites covered different types of primary metabolism and some of the secondary metabolism pathways. One-way analysis of variance (ANOVA statistical assay was performed to calculate the variations within the detected metabolites, and levels of 65 metabolites were differentially expressed in different samples. Hierarchical cluster analysis (HCA dendrograms showed variations among different tissues that were similar to the metabolite profiles observed in new leaves and fruit. Additionally, 5776 metabolite-metabolite correlations were detected by a Pearson correlation coefficient approach. Screening of the calculated correlations revealed 3136, 3025, and 5184 were determined to metabolites and had significant correlations in three different combinations, respectively. This work provides the first comprehensive metabolomic of olive, which will provide new insights into understanding the olive metabolism, and potentially help advance studies in olive metabolic engineering.

  5. Potential Impact of Nutrition on Immune System Recovery from Heavy Exertion: A Metabolomics Perspective.

    Science.gov (United States)

    Nieman, David C; Mitmesser, Susan Hazels

    2017-05-18

    This review describes effective and ineffective immunonutrition support strategies for the athlete, with a focus on the benefits of carbohydrates and polyphenols as determined from metabolomics-based procedures. Athletes experience regular cycles of physiological stress accompanied by transient inflammation, oxidative stress, and immune perturbations, and there are increasing data indicating that these are sensitive to nutritional influences. The most effective nutritional countermeasures, especially when considered from a metabolomics perspective, include acute and chronic increases in dietary carbohydrate and polyphenols. Carbohydrate supplementation reduces post-exercise stress hormone levels, inflammation, and fatty acid mobilization and oxidation. Ingestion of fruits high in carbohydrates, polyphenols, and metabolites effectively supports performance, with added benefits including enhancement of oxidative and anti-viral capacity through fruit metabolites, and increased plasma levels of gut-derived phenolics. Metabolomics and lipidomics data indicate that intensive and prolonged exercise is associated with extensive lipid mobilization and oxidation, including many components of the linoleic acid conversion pathway and related oxidized derivatives called oxylipins. Many of the oxylipins are elevated with increased adiposity, and although low in resting athletes, rise to high levels during recovery. Future targeted lipidomics-based studies will help discover whether n-3-polyunsaturated fatty acid (n-3-PUFA) supplementation enhances inflammation resolution in athletes post-exercise.

  6. Metabolomics of cancer cell cultures to assess the effects of dietary phytochemicals.

    Science.gov (United States)

    Brasili, Elisa; Filho, Valdir Cechinel

    2017-05-03

    Cancer is a multi-factorial disease and is a major cause of morbidity and mortality worldwide. Dietary phytochemicals have been used for the treatment of cancer throughout history due to their safety, low toxicity, and general availability. Several studies have been performed to elucidate the effects of dietary phytochemicals on cancer metabolism, and many molecular targets of phytochemicals have been discovered. In spite of remarkable progress, their effects on cancer metabolism have not yet been fully clarified. Recent developments in metabolomics allowed to probe much further the metabolism of cancer, highlighting altered metabolic pathways and offering a new powerful tool to investigate cancer disease. In this review, we discuss the main metabolic alterations of cancer cells and the potentiality of phytochemicals as promising modulators of cancer metabolism. We will focus on the application of nuclear magnetic resonance-based metabolomics on breast and hepatocellular cancer cell lines to evaluate the impact of curcumin and resveratrol on cancer metabolome with the aim to demonstrate the premise of this approach to provide useful information for a better understanding of impact of diet components on cancer disease.

  7. Metabolomics of autism spectrum disorders: early insights regarding mammalian-microbial cometabolites.

    Science.gov (United States)

    Mussap, Michele; Noto, Antonio; Fanos, Vassilios

    2016-08-01

    Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders consisting of delayed or impaired language development and difficulties in social interactions. The very high degree of phenotypic heterogeneity in ASD originates from the interaction between environmental risk factors and susceptible genetic loci, leading to epigenetic DNA methylation. Advances in system biology are becoming strategic for implementing knowledge on the ASD aetiology and for the early diagnosis of the disease after birth. We overhauled the value of either targeted or untargeted metabolomics studies in autism for identifying the most relevant metabolic pathways and key metabolites implicated in the disease, with special emphasis to mammalian-microbial metabolites. The most discriminant metabolites in ASD belong to amino acid metabolism, antioxidant status, nicotinic acid metabolism, and mitochondrial metabolism. Expert commentary: Most published studies point out the role of metabolites derived from the gut microbiota: they can modulate the behavioral phenotype of the autistic children, greatly influencing host metabolic pathways and the immune system, shaping the individual susceptibility to the disease. Pitfalls and caveats in metabolomics results across studies have been additionally recognized and discussed leading to the conclusion that metabolomics studies in ASD are far to be definitive and univocal.

  8. Short overview on metabolomics approach to study pathophysiology of oxidative stress in cancer

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    Luka Andrisic

    2018-04-01

    Full Text Available Association of oxidative stress with carcinogenesis is well known, but not understood well, as is pathophysiology of oxidative stress generated during different types of anti-cancer treatments. Moreover, recent findings indicate that cancer associated lipid peroxidation might eventually help defending adjacent nonmalignant cells from cancer invasion. Therefore, untargeted metabolomics studies designed for advanced translational and clinical studies are needed to understand the existing paradoxes in oncology, including those related to controversial usage of antioxidants aiming to prevent or treat cancer. In this short review we have tried to put emphasis on the importance of pathophysiology of oxidative stress and lipid peroxidation in cancer development in relation to metabolic adaptation of particular types of cancer allowing us to conclude that adaptation to oxidative stress is one of the main driving forces of cancer pathophysiology. With the help of metabolomics many novel findings are being achieved thus encouraging further scientific breakthroughs. Combined with targeted qualitative and quantitative methods, especially immunochemistry, further research might reveal bio-signatures of individual patients and respective malignant diseases, leading to individualized treatment approach, according to the concepts of modern integrative medicine. Keywords: Carcinogenesis, Cancer, Oxidative stress, Lipid peroxidation, 4-hydroxynonenal, Glutathione, Metabolomics, Immunochemistry, Biomarkers, Omics science

  9. The Human Serum Metabolome of Vitamin B-12 Deficiency and Repletion, and Associations with Neurological Function in Elderly Adults.

    Science.gov (United States)

    Brito, Alex; Grapov, Dmitry; Fahrmann, Johannes; Harvey, Danielle; Green, Ralph; Miller, Joshua W; Fedosov, Sergey N; Shahab-Ferdows, Setareh; Hampel, Daniela; Pedersen, Theresa L; Fiehn, Oliver; Newman, John W; Uauy, Ricardo; Allen, Lindsay H

    2017-08-09

    Background: The specific metabolomic perturbations that occur in vitamin B-12 deficiency, and their associations with neurological function, are not well characterized.Objective: We sought to characterize the human serum metabolome in subclinical vitamin B-12 deficiency and repletion.Methods: A before-and-after treatment study provided 1 injection of 10 mg vitamin B-12 (with 100 mg pyridoxine and 100 mg thiamin) to 27 community-dwelling elderly Chileans (∼74 y old) with vitamin B-12 deficiency, as evaluated with serum vitamin B-12, total plasma homocysteine (tHcy), methylmalonic acid (MMA), and holotranscobalamin. The combined indicator of vitamin B-12 status (cB-12) was computed. Targeted metabolites [166 acylcarnitines, amino acids, sugars, glycerophospholipids, and sphingolipids (liquid chromatography-tandem mass spectrometry)], and untargeted metabolites [247 chemical entities (gas chromatography time-of-flight mass spectrometry)] were measured at baseline and 4 mo after treatment. A peripheral nerve score was developed. Differences before and after treatment were examined. For targeted metabolomics, the data from 18 individuals with adequate vitamin B-12 status (selected from the same population) were added to the before-and-after treatment data set. Network visualizations and metabolic pathways are illustrated.Results: The injection increased serum vitamin B-12, holotranscobalamin, and cB-12 (P vitamin B-12 status and nerve function. Multiple connections were identified with primary metabolites (e.g., an inverse relation between vitamin B-12 markers and tryptophan, tyrosine, and pyruvic, succinic, and citric acids, and a direct correlation between the nerve score and arginine).Conclusions: The human serum metabolome in vitamin B-12 deficiency and the changes that occur after supplementation are characterized. Metabolomics revealed connections between vitamin B-12 status and serum metabolic markers of mitochondrial function, myelin integrity, oxidative

  10. Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

    Science.gov (United States)

    Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

    2016-07-01

    Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas

  11. Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis.

    Directory of Open Access Journals (Sweden)

    Ketki D Verkhedkar

    Full Text Available BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a

  12. Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis.

    Science.gov (United States)

    Verkhedkar, Ketki D; Raman, Karthik; Chandra, Nagasuma R; Vishveshwara, Saraswathi

    2007-09-12

    Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking

  13. Development of an NMR microprobe procedure for high-throughput environmental metabolomics of Daphnia magna.

    Science.gov (United States)

    Nagato, Edward G; Lankadurai, Brian P; Soong, Ronald; Simpson, André J; Simpson, Myrna J

    2015-09-01

    Nuclear magnetic resonance (NMR) is the primary platform used in high-throughput environmental metabolomics studies because its non-selectivity is well suited for non-targeted approaches. However, standard NMR probes may limit the use of NMR-based metabolomics for tiny organisms because of the sample volumes required for routine metabolic profiling. Because of this, keystone ecological species, such as the water flea Daphnia magna, are not commonly studied because of the analytical challenges associated with NMR-based approaches. Here, the use of a 1.7-mm NMR microprobe in analyzing tissue extracts from D. magna is tested. Three different extraction procedures (D2O-based buffer, Bligh and Dyer, and acetonitrile : methanol : water) were compared in terms of the yields and breadth of polar metabolites. The D2O buffer extraction yielded the most metabolites and resulted in the best reproducibility. Varying amounts of D. magna dry mass were extracted to optimize metabolite isolation from D. magna tissues. A ratio of 1-1.5-mg dry mass to 40 µl of extraction solvent provided excellent signal-to-noise and spectral resolution using (1)H NMR. The metabolite profile of a single daphnid was also investigated (approximately 0.2 mg). However, the signal-to-noise of the (1)H NMR was considerably lower, and while feasible for select applications would likely not be appropriate for high-throughput NMR-based metabolomics. Two-dimensional NMR experiments on D. magna extracts were also performed using the 1.7-mm NMR probe to confirm (1)H NMR metabolite assignments. This study provides an NMR-based analytical framework for future metabolomics studies that use D. magna in ecological and ecotoxicity studies. Copyright © 2015 John Wiley & Sons, Ltd.

  14. Integrated Metabolomics Assessment of Human Dried Blood Spots and Urine Strips.

    Science.gov (United States)

    Drolet, Jeremy; Tolstikov, Vladimir; Williams, Brian A; Greenwood, Bennett P; Hill, Collin; Vishnudas, Vivek K; Sarangarajan, Rangaprasad; Narain, Niven R; Kiebish, Michael A

    2017-07-15

    (1) Background: Interest in the application of metabolomics toward clinical diagnostics development and population health monitoring has grown significantly in recent years. In spite of several advances in analytical and computational tools, obtaining a sufficient number of samples from patients remains an obstacle. The dried blood spot (DBS) and dried urine strip (DUS) methodologies are a minimally invasive sample collection method allowing for the relative simplicity of sample collection and minimal cost. (2) Methods: In the current report, we compared results of targeted metabolomics analyses of four types of human blood sample collection methods (with and without DBS) and two types of urine sample collection (DUS and urine) across several parameters including th