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Sample records for accurate mass metabolomics

  1. Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'.

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    Draper, John; Enot, David P; Parker, David; Beckmann, Manfred; Snowdon, Stuart; Lin, Wanchang; Zubair, Hassan

    2009-07-21

    Metabolomics experiments using Mass Spectrometry (MS) technology measure the mass to charge ratio (m/z) and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of ionised. In reality the annotation process is confounded by the fact that many ionisation products will be not only molecular isotopes but also salt/solvent adducts and neutral loss fragments of original metabolites. This report describes an annotation strategy that will allow searching based on all potential ionisation products predicted to form during electrospray ionisation (ESI). Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50%) of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data. We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to

  2. LC-Mass Spectrometry for Metabolomics.

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    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.

  3. Capillary electrophoresis mass spectrometry based metabolomics

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    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.

  4. Accurate, fully-automated NMR spectral profiling for metabolomics.

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    Ravanbakhsh, Siamak; Liu, Philip; Bjorndahl, Trent C; Bjordahl, Trent C; Mandal, Rupasri; Grant, Jason R; Wilson, Michael; Eisner, Roman; Sinelnikov, Igor; Hu, Xiaoyu; Luchinat, Claudio; Greiner, Russell; Wishart, David S

    2015-01-01

    Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites) that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR) spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid), BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF), defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error), in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of NMR in

  5. Accurate, fully-automated NMR spectral profiling for metabolomics.

    Directory of Open Access Journals (Sweden)

    Siamak Ravanbakhsh

    Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

  6. 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...

  7. 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

  8. Two elephants in the room: new hybrid nuclear magnetic resonance and mass spectrometry approaches for metabolomics

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    Bingol, Kerem; Brüschweiler, Rafael

    2015-01-01

    Purpose of review This review describes some of the advances made over the past year in NMR-based metabolomics for the elucidation of known and unknown compounds, including new ways of how to combine this information with high-resolution mass spectrometry. Recent findings A new method allows the back-calculation of mass spectra from NMR spectra that have been queried against databases improving the accuracy of the identified compounds by validation and consistency analysis. For the de-novo characterization of unknown compounds, an algorithm has been introduced that predicts all viable NMR spectra from accurate masses allowing, by comparison with experimental NMR data, the determination of the structures of new metabolites in complex mixtures. Summary Recent advances in NMR and mass spectrometry-based metabolomics and their synergistic use promises to significantly improve metabolomics sample characterization both in terms of identification and quantitation, and accelerate metabolite discovery. PMID:26154280

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

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    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.

  10. Basics of mass spectrometry based metabolomics.

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    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.

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

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    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.

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

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    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

  13. 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...

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

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    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.

  15. A liquid chromatography-mass spectrometry-based metabolome database for tomato

    NARCIS (Netherlands)

    Moco, S.I.A.; Bino, R.J.; Vorst, O.F.J.; Verhoeven, H.A.; Groot, de J.C.W.; Beek, van T.A.; Vervoort, J.J.M.; Vos, de C.H.

    2006-01-01

    For the description of the metabolome of an organism, the development of common metabolite databases is of utmost importance. Here we present the Metabolome Tomato Database (MoTo DB), a metabolite database dedicated to liquid chromatography-mass spectrometry (LC-MS)- based metabolomics of tomato

  16. 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...

  17. High precision mass measurements for wine metabolomics

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    Roullier-Gall, Chloé; Witting, Michael; Gougeon, Régis; Schmitt-Kopplin, Philippe

    2014-11-01

    An overview of the critical steps for the non-targeted Ultra-High Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-ToF-MS) analysis of wine chemistry is given, ranging from the study design, data preprocessing and statistical analyses, to markers identification. UPLC-Q-ToF-MS data was enhanced by the alignment of exact mass data from FTICR-MS, and marker peaks were identified using UPLC-Q-ToF-MS². In combination with multivariate statistical tools and the annotation of peaks with metabolites from relevant databases, this analytical process provides a fine description of the chemical complexity of wines, as exemplified in the case of red (Pinot noir) and white (Chardonnay) wines from various geographic origins in Burgundy.

  18. High precision mass measurements for wine metabolomics

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    Chloé eRoullier-Gall

    2014-11-01

    Full Text Available An overview of the critical steps for the non-targeted Ultra-High Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-ToF-MS analysis of wine chemistry is given, ranging from the study design, data preprocessing and statistical analyses, to markers identification. UPLC-Q-ToF-MS data was enhanced by the alignment of exact mass data from FTICR-MS, and marker peaks were identified using UPLC-Q-ToF-MS². In combination with multivariate statistical tools and the annotation of peaks with metabolites from relevant databases, this analytical process provides a fine description of the chemical complexity of wines, as exemplified in the case of red (Pinot noir and white (Chardonnay wines from various geographic origins in Burgundy.

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

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    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.

  20. Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines

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    Walker L DeEtte

    2009-08-01

    Full Text Available Abstract Background The majority of ovarian cancer biomarker discovery efforts focus on the identification of proteins that can improve the predictive power of presently available diagnostic tests. We here show that metabolomics, the study of metabolic changes in biological systems, can also provide characteristic small molecule fingerprints related to this disease. Results In this work, new approaches to automatic classification of metabolomic data produced from sera of ovarian cancer patients and benign controls are investigated. The performance of support vector machines (SVM for the classification of liquid chromatography/time-of-flight mass spectrometry (LC/TOF MS metabolomic data focusing on recognizing combinations or "panels" of potential metabolic diagnostic biomarkers was evaluated. Utilizing LC/TOF MS, sera from 37 ovarian cancer patients and 35 benign controls were studied. Optimum panels of spectral features observed in positive or/and negative ion mode electrospray (ESI MS with the ability to distinguish between control and ovarian cancer samples were selected using state-of-the-art feature selection methods such as recursive feature elimination and L1-norm SVM. Conclusion Three evaluation processes (leave-one-out-cross-validation, 12-fold-cross-validation, 52-20-split-validation were used to examine the SVM models based on the selected panels in terms of their ability for differentiating control vs. disease serum samples. The statistical significance for these feature selection results were comprehensively investigated. Classification of the serum sample test set was over 90% accurate indicating promise that the above approach may lead to the development of an accurate and reliable metabolomic-based approach for detecting ovarian cancer.

  1. The Recent Developments in Sample Preparation for Mass Spectrometry-Based Metabolomics.

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    Gong, Zhi-Gang; Hu, Jing; Wu, Xi; Xu, Yong-Jiang

    2017-07-04

    Metabolomics is a critical member in systems biology. Although great progress has been achieved in metabolomics, there are still some problems in sample preparation, data processing and data interpretation. In this review, we intend to explore the roles, challenges and trends in sample preparation for mass spectrometry- (MS-) based metabolomics. The newly emerged sample preparation methods were also critically examined, including laser microdissection, in vivo sampling, dried blood spot, microwave, ultrasound and enzyme-assisted extraction, as well as microextraction techniques. Finally, we provide some conclusions and perspectives for sample preparation in MS-based metabolomics.

  2. 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...

  3. 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.

  4. Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry

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    Spur, Eva-Margarete [Massachusetts General Hospital, Harvard Medical School, Department of Pathology, Boston, MA (United States); Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Boston, MA (United States); Charite Universitaetsmedizin, Berlin (Germany); Decelle, Emily A.; Cheng, Leo L. [Massachusetts General Hospital, Harvard Medical School, Department of Pathology, Boston, MA (United States); Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Boston, MA (United States)

    2013-07-15

    Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases. (orig.)

  5. Gas chromatographic-mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism.

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    Kuhara, Tomiko

    2005-01-01

    Urine contains numerous metabolites, and can provide evidence for the screening or molecular diagnosis of many inborn errors of metabolism (IEMs). The metabolomic analysis of urine by the combined use of urease pretreatment, stable-isotope dilution, and capillary gas chromatography/mass spectrometry offers reliable and quantitative data for the simultaneous screening or molecular diagnosis of more than 130 IEMs. Those IEMs include hyperammonemias and lactic acidemias, and the IEMs of amino acids, pyrimidines, purines, carbohydrates, and others including primary hyperoxalurias, hereditary fructose intolerance, propionic acidemia, and methylmalonic acidemia. Metabolite analysis is comprehensive for mutant genotypes. Enzyme dysfunction-either by the abnormal structure of an enzyme/apoenzyme, the reduced quantity of a normal enzyme/apoenzyme, or the lack of a coenzyme-is involved. Enzyme dysfunction-either by an abnormal regulatory gene, abnormal sub-cellular localization, or by abnormal post-transcriptional or post-translational modification-is included. Mutations-either known or unknown, common or uncommon-are involved. If the urine metabolome approach can accurately observe quantitative abnormality for hundreds of metabolites, reflecting 100 different disease-causing reactions in a body, then it is possible to simultaneously detect different mutant genotypes of far more than tens of thousands. (c) 2004 Wiley Periodicals, Inc., Mass Spec Rev 24:814-827, 2005.

  6. Tailored liquid chromatography-mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells.

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    Cuykx, Matthias; Negreira, Noelia; Beirnaert, Charlie; Van den Eede, Nele; Rodrigues, Robim; Vanhaecke, Tamara; Laukens, Kris; Covaci, Adrian

    2017-03-03

    Metabolomics protocols are often combined with Liquid Chromatography-Mass Spectrometry (LC-MS) using mostly reversed phase chromatography coupled to accurate mass spectrometry, e.g. quadrupole time-of-flight (QTOF) mass spectrometers to measure as many metabolites as possible. In this study, we optimised the LC-MS separation of cell extracts after fractionation in polar and non-polar fractions. Both phases were analysed separately in a tailored approach in four different runs (two for the non-polar and two for the polar-fraction), each of them specifically adapted to improve the separation of the metabolites present in the extract. This approach improves the coverage of a broad range of the metabolome of the HepaRG cells and the separation of intra-class metabolites. The non-polar fraction was analysed using a C18-column with end-capping, mobile phase compositions were specifically adapted for each ionisation mode using different co-solvents and buffers. The polar extracts were analysed with a mixed mode Hydrophilic Interaction Liquid Chromatography (HILIC) system. Acidic metabolites from glycolysis and the Krebs cycle, together with phosphorylated compounds, were best detected with a method using ion pairing (IP) with tributylamine and separation on a phenyl-hexyl column. Accurate mass detection was performed with the QTOF in MS-mode only using an extended dynamic range to improve the quality of the dataset. Parameters with the greatest impact on the detection were the balance between mass accuracy and linear range, the fragmentor voltage, the capillary voltage, the nozzle voltage, and the nebuliser pressure. By using a tailored approach for the intracellular HepaRG metabolome, consisting of three different LC techniques, over 2200 metabolites can be measured with a high precision and acceptable linear range. The developed method is suited for qualitative untargeted LC-MS metabolomics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. 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...

  8. Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm

    Directory of Open Access Journals (Sweden)

    Fiehn Oliver

    2006-04-01

    Full Text Available Abstract Background Metabolomic studies are targeted at identifying and quantifying all metabolites in a given biological context. Among the tools used for metabolomic research, mass spectrometry is one of the most powerful tools. However, metabolomics by mass spectrometry always reveals a high number of unknown compounds which complicate in depth mechanistic or biochemical understanding. In principle, mass spectrometry can be utilized within strategies of de novo structure elucidation of small molecules, starting with the computation of the elemental composition of an unknown metabolite using accurate masses with errors Results High mass accuracy (95% of false candidates. This orthogonal filter can condense several thousand candidates down to only a small number of molecular formulas. Example calculations for 10, 5, 3, 1 and 0.1 ppm mass accuracy are given. Corresponding software scripts can be downloaded from http://fiehnlab.ucdavis.edu. A comparison of eight chemical databases revealed that PubChem and the Dictionary of Natural Products can be recommended for automatic queries using molecular formulae. Conclusion More than 1.6 million molecular formulae in the range 0–500 Da were generated in an exhaustive manner under strict observation of mathematical and chemical rules. Assuming that ion species are fully resolved (either by chromatography or by high resolution mass spectrometry, we conclude that a mass spectrometer capable of 3 ppm mass accuracy and 2% error for isotopic abundance patterns outperforms mass spectrometers with less than 1 ppm mass accuracy or even hypothetical mass spectrometers with 0.1 ppm mass accuracy that do not include isotope information in the calculation of molecular formulae.

  9. 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.

  10. Vinegar Metabolomics: An Explorative Study of Commercial Balsamic Vinegars Using Gas Chromatography-Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Farhana R. Pinu

    2016-07-01

    Full Text Available Balsamic vinegar is a popular food condiment produced from cooked grape must by two successive fermentation (anaerobic and aerobic processes. Although many studies have been performed to determine the composition of major metabolites, including sugars and aroma compounds, no study has been undertaken yet to characterize the comprehensive metabolite composition of balsamic vinegars. Here, we present the first metabolomics study of commercial balsamic vinegars by gas chromatography coupled to mass spectrometry (GC-MS. The combination of three GC-MS methods allowed us to detect >1500 features in vinegar samples, of which 123 metabolites were accurately identified, including 25 amino acids, 26 carboxylic acids, 13 sugars and sugar alcohols, four fatty acids, one vitamin, one tripeptide and over 47 aroma compounds. Moreover, we identified for the first time in vinegar five volatile metabolites: acetin, 2-methylpyrazine, 2-acetyl-1-pyroline, 4-anisidine and 1,3-diacetoxypropane. Therefore, we demonstrated the capability of metabolomics for detecting and identifying large number of metabolites and some of them could be used to distinguish vinegar samples based on their origin and potentially quality.

  11. Strategies Involving Mass Spectrometry Combined with Capillary Electrophoresis in Metabolomics.

    Science.gov (United States)

    Rodrigues, Karina Trevisan; Cieslarová, Zuzana; Tavares, Marina Franco Maggi; Simionato, Ana Valéria Colnaghi

    2017-01-01

    This chapter focuses on the important contribution of CE-MS in metabolomics, describing the nature of CE-MS coupling and the technical improvements that have led to the interfaces used in modern instrumentation. Moreover, it will discourse how the variety of electrolyte compositions and additives, which has conferred CE the exceptional selectivity of its multiple separation modes, has been handled to allow interfacing with MS without compromising ionization efficiency and the spectrometer integrity. Finally, the methodologies of CE-MS in current use for metabolomics will be discussed in detail. To verify the scope of CE-MS in clinical metabolomics, a myriad of representative applications has been compiled.

  12. Metabolome analysis - mass spectrometry and microbial primary metabolites

    DEFF Research Database (Denmark)

    Højer-Pedersen, Jesper Juul

    2008-01-01

    While metabolite profiling has been carried out for decades, the scope for metabolite analysis have recently been broadened to aim at all metabolites in a living organism – also referred to as the metabolome. This is a great challenge, which requires versatile analytical technologies...... for databases that contain metabolite specific information, which will speed up the identification of profiled metabolites. To address the capabilities of electrospray ionization (ESI)-MS in detecting the metabolome of S. cerevisiae, the in silico metabolome of this organism was used as a template to present....... Statistical analysis of the footprinting data revealed discriminating ions, which could be assigned using the in silico metabolome. By this approach metabolic footprinting can advance from a classification method that is used to derive biological information based on guilt-by-association, to a tool...

  13. Development of chemical isotope labeling liquid chromatography mass spectrometry for silkworm hemolymph metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Weifeng [Key Laboratory of Detection for Pesticide Residues, Ministry of Agriculture (China); Sericultural Research Institute, Zhejiang Academy of Agricultural Sciences, Hangzhou (China); Han, Wei; Li, Yunong [Department of Chemistry, University of Alberta, Edmonton, Alberta (Canada); Meng, Zhiqi [Sericultural Research Institute, Zhejiang Academy of Agricultural Sciences, Hangzhou (China); Cai, Leiming, E-mail: cailm@mail.zaas.ac.cn [Institute of Quality and Standard for Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou (China); Li, Liang, E-mail: Liang.Li@ualberta.ca [Department of Chemistry, University of Alberta, Edmonton, Alberta (Canada)

    2016-10-26

    Silkworm (Bombyx mori) is a very useful target insect for evaluation of endocrine disruptor chemicals (EDCs) due to mature breeding techniques, complete endocrine system and broad basic knowledge on developmental biology. Comparative metabolomics of silkworms with and without EDC exposure offers another dimension of studying EDCs. In this work, we report a workflow on metabolomic profiling of silkworm hemolymph based on high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) and demonstrate its application in studying the metabolic changes associated with the pesticide dichlorodiphenyltrichloroethane (DDT) exposure in silkworm. Hemolymph samples were taken from mature silkworms after growing on diet that contained DDT at four different concentrations (1, 0.1, 0.01, 0.001 ppm) as well as on diet without DDT as controls. They were subjected to differential {sup 12}C-/{sup 13}C-dansyl labeling of the amine/phenol submetabolome, LC-UV quantification of the total amount of labeled metabolites for sample normalization, and LC-MS detection and relative quantification of individual metabolites in comparative samples. The total concentration of labeled metabolites did not show any significant change between four DDT-treatment groups and one control group. Multivariate statistical analysis of the metabolome data set showed that there was a distinct metabolomic separation between the five groups. Out of the 2044 detected peak pairs, 338 and 1471 metabolites have been putatively identified against the HMDB database and the EML library, respectively. 65 metabolites were identified by the dansyl library searching based on the accurate mass and retention time. Among the 65 identified metabolites, 33 positive metabolites had changes of greater than 1.20-fold or less than 0.83-fold in one or more groups with p-value of smaller than 0.05. Several useful biomarkers including serine, methionine, tryptophan, asymmetric dimethylarginine, N

  14. The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research.

    Science.gov (United States)

    Emwas, Abdul-Hamid M

    2015-01-01

    Mass spectrometry (MS) and nuclear magnetic resonance (NMR) have evolved as the most common techniques in metabolomics studies, and each brings its own advantages and limitations. Unlike MS spectrometry, NMR spectroscopy is quantitative and does not require extra steps for sample preparation, such as separation or derivatization. Although the sensitivity of NMR spectroscopy has increased enormously and improvements continue to emerge steadily, this remains a weak point for NMR compared with MS. MS-based metabolomics provides an excellent approach that can offer a combined sensitivity and selectivity platform for metabolomics research. Moreover, different MS approaches such as different ionization techniques and mass analyzer technology can be used in order to increase the number of metabolites that can be detected. In this chapter, the advantages, limitations, strengths, and weaknesses of NMR and MS as tools applicable to metabolomics research are highlighted.

  15. Formation of dehydroalanine from mimosine and cysteine: artifacts in gas chromatography/mass spectrometry based metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young-Mo; Metz, Thomas O.; Hu, Zeping; Wiedner, Susan D.; Kim, Jong Seo; Smith, Richard D.; Morgan, William F.; Zhang, Qibin

    2011-08-15

    Trimethylsilyation is a chemical derivatization procedure routinely applied in gas chromatography-mass spectrometry (GC-MS)-based metabolomics. In this report, through de novo structural elucidation and comparison with authentic standards, we demonstrate that mimosine can be completely converted into dehydroalanine and 3,4-dihydroxypyridine during the trimethylsilyating process. Similarly, dehydroalanine can be formed from derivatization of cysteine. This conversion is a potential interference in GC-MS-based global metabolomics, as well as in analysis of amino acids.

  16. Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics

    Science.gov (United States)

    Vaniya, Arpana

    2015-01-01

    Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations. PMID:26213431

  17. 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.

  18. Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

    Directory of Open Access Journals (Sweden)

    Ina Aretz

    2016-04-01

    Full Text Available Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

  19. Mass accuracy improvement of reversed-phase liquid chromatography/electrospray ionization mass spectrometry based urinary metabolomic analysis by post-run calibration using sodium formate cluster ions.

    Science.gov (United States)

    Juo, Chiun-Gung; Chen, Chien-Lun; Lin, Shiang-Ting; Fu, Shu-Hsuan; Chen, Yi-Ting; Chang, Yu-Sun; Yu, Jau-Song

    2014-08-30

    Typically, a batch metabolomics analysis using liquid chromatography/electrospray ionization time-of-flight mass spectrometry (LC/ESI-TOF MS) takes 2 to 3 days. However, the mass accuracy - which has an important influence on metabolite identification - can drift by as much as about 17 ppm in such a time period. In an untargeted urinary metabolomics analysis by reversed-phase liquid chromatography (RPLC)/ESI-MS, the signals of sodium formate cluster ions were detected at the column-washing step. The cluster ions were used to calibrate the mass spectrometer for more accurate detection. The spectra were calibrated post-run by the sodium formate cluster ions, which were used as the internal standard, in order to improve the mass accuracy. In the analysis of urine samples, we calibrated the spectra acquired by the micrOTOF with the sodium cluster ions. In positive mode ESI, the average errors of these cluster ions were improved to ±0.48 ppm and in negative mode ESI, to ±0.94 ppm after calibration. The mass accuracy remained within ±0.01 ppm over the duration of 6.25 days. An error window of 4 ppm appears to be suitable for metabolite identification when using post-calibration. The results showed that sodium formate cluster ions could be utilized for the calibration of LC/ESI-TOF MS and the average instrumental errors could be maintained at low levels for long-term analyses. This method could be applied not only to urine sample, but also to low sodium samples, such as saliva, by dissolving the sample in 1 μM sodium formate solution. This method provides a good solution for accurate mass detection of metabolomic analysis. Copyright © 2014 John Wiley & Sons, Ltd.

  20. Conventional and Advanced Separations in Mass Spectrometry-Based Metabolomics: Methodologies and Applications

    Energy Technology Data Exchange (ETDEWEB)

    Heyman, Heino M.; Zhang, Xing; Tang, Keqi; Baker, Erin Shammel; Metz, Thomas O.

    2016-02-16

    Metabolomics is the quantitative analysis of all metabolites in a given sample. Due to the chemical complexity of the metabolome, optimal separations are required for comprehensive identification and quantification of sample constituents. This chapter provides an overview of both conventional and advanced separations methods in practice for reducing the complexity of metabolite extracts delivered to the mass spectrometer detector, and covers gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis (CE), supercritical fluid chromatography (SFC) and ion mobility spectrometry (IMS) separation techniques coupled with mass spectrometry (MS) as both uni-dimensional and as multi-dimensional approaches.

  1. Accurate mass measurements on neutron-deficient krypton isotopes

    CERN Document Server

    Rodríguez, D.; Äystö, J.; Beck, D.; Blaum, K.; Bollen, G.; Herfurth, F.; Jokinen, A.; Kellerbauer, A.; Kluge, H.-J.; Kolhinen, V.S.; Oinonen, M.; Sauvan, E.; Schwarz, S.

    2006-01-01

    The masses of $^{72–78,80,82,86}$Kr were measured directly with the ISOLTRAP Penning trap mass spectrometer at ISOLDE/CERN. For all these nuclides, the measurements yielded mass uncertainties below 10 keV. The ISOLTRAP mass values for $^{72–75}$Kr being more precise than the previous results obtained by means of other techniques, and thus completely determine the new values in the Atomic-Mass Evaluation. Besides the interest of these masses for nuclear astrophysics, nuclear structure studies, and Standard Model tests, these results constitute a valuable and accurate input to improve mass models. In this paper, we present the mass measurements and discuss the mass evaluation for these Kr isotopes.

  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

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a

  3. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal.

    Science.gov (United States)

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang; Gouveia-Figueira, Sandra; Pinto, Rui; Trygg, Johan; Zivkovic, Angela M; Nording, Malin L

    2016-02-18

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms - gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) - to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1-86% for GC-MS and 0.9-42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2-97% for the positive and 4-69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi

  4. Galaxy-M: a Galaxy workflow for processing and analyzing direct infusion and liquid chromatography mass spectrometry-based metabolomics data.

    Science.gov (United States)

    Davidson, Robert L; Weber, Ralf J M; Liu, Haoyu; Sharma-Oates, Archana; Viant, Mark R

    2016-01-01

    Metabolomics is increasingly recognized as an invaluable tool in the biological, medical and environmental sciences yet lags behind the methodological maturity of other omics fields. To achieve its full potential, including the integration of multiple omics modalities, the accessibility, standardization and reproducibility of computational metabolomics tools must be improved significantly. Here we present our end-to-end mass spectrometry metabolomics workflow in the widely used platform, Galaxy. Named Galaxy-M, our workflow has been developed for both direct infusion mass spectrometry (DIMS) and liquid chromatography mass spectrometry (LC-MS) metabolomics. The range of tools presented spans from processing of raw data, e.g. peak picking and alignment, through data cleansing, e.g. missing value imputation, to preparation for statistical analysis, e.g. normalization and scaling, and principal components analysis (PCA) with associated statistical evaluation. We demonstrate the ease of using these Galaxy workflows via the analysis of DIMS and LC-MS datasets, and provide PCA scores and associated statistics to help other users to ensure that they can accurately repeat the processing and analysis of these two datasets. Galaxy and data are all provided pre-installed in a virtual machine (VM) that can be downloaded from the GigaDB repository. Additionally, source code, executables and installation instructions are available from GitHub. The Galaxy platform has enabled us to produce an easily accessible and reproducible computational metabolomics workflow. More tools could be added by the community to expand its functionality. We recommend that Galaxy-M workflow files are included within the supplementary information of publications, enabling metabolomics studies to achieve greater reproducibility.

  5. 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.

  6. 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.

  7. Global mass spectrometry based metabolomics profiling of erythrocytes infected with Plasmodium falciparum.

    Directory of Open Access Journals (Sweden)

    Theodore R Sana

    Full Text Available Malaria is a global infectious disease that threatens the lives of millions of people. Transcriptomics, proteomics and functional genomics studies, as well as sequencing of the Plasmodium falciparum and Homo sapiens genomes, have shed new light on this host-parasite relationship. Recent advances in accurate mass measurement mass spectrometry, sophisticated data analysis software, and availability of biological pathway databases, have converged to facilitate our global, untargeted biochemical profiling study of in vitro P. falciparum-infected (IRBC and uninfected (NRBC erythrocytes. In order to expand the number of detectable metabolites, several key analytical steps in our workflows were optimized. Untargeted and targeted data mining resulted in detection of over one thousand features or chemical entities. Untargeted features were annotated via matching to the METLIN metabolite database. For targeted data mining, we queried the data using a compound database derived from a metabolic reconstruction of the P. falciparum genome. In total, over one hundred and fifty differential annotated metabolites were observed. To corroborate the representation of known biochemical pathways from our data, an inferential pathway analysis strategy was used to map annotated metabolites onto the BioCyc pathway collection. This hypothesis-generating approach resulted in over-representation of many metabolites onto several IRBC pathways, most prominently glycolysis. In addition, components of the "branched" TCA cycle, partial urea cycle, and nucleotide, amino acid, chorismate, sphingolipid and fatty acid metabolism were found to be altered in IRBCs. Interestingly, we detected and confirmed elevated levels for cyclic ADP ribose and phosphoribosyl AMP in IRBCs, a novel observation. These metabolites may play a role in regulating the release of intracellular Ca(2+ during P. falciparum infection. Our results support a strategy of global metabolite profiling by untargeted

  8. Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control

    Science.gov (United States)

    Kirwan, Jennifer A; Weber, Ralf J M; Broadhurst, David I; Viant, Mark R

    2014-01-01

    Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment. PMID:25977770

  9. Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control.

    Science.gov (United States)

    Kirwan, Jennifer A; Weber, Ralf J M; Broadhurst, David I; Viant, Mark R

    2014-01-01

    Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment.

  10. Exploration of candidate biomarkers for human psoriasis based on gas chromatography-mass spectrometry serum metabolomics.

    Science.gov (United States)

    Kang, H; Li, X; Zhou, Q; Quan, C; Xue, F; Zheng, J; Yu, Y

    2017-03-01

    Recent studies have shown that dysregulated metabolic pathways are linked to psoriasis pathogenesis. However, an extensive, unbiased metabolic analysis in patients with psoriasis has not been completely explored. The metabolome represents the end products of proteomics or cellular processes that may be closely associated with the pathogenesis of psoriasis. To determine the differences in serum metabolomic profiles among patients with psoriasis and healthy controls with the goal of identifying potential biomarkers in patients with psoriasis. Serum metabolomic profiles from 29 subjects (14 patients with psoriasis and 15 sex- and age-matched healthy controls). The serum metabolites were analysed by gas chromatography-mass spectrometry based on a combined full scan and selected-ion monitoring mode. Multivariate statistical analysis of metabolomics data revealed altered serum metabolites between the patients with psoriasis and healthy individuals. Compared with healthy individuals, patients with psoriasis had higher levels of amino acids including asparagine, aspartic acid, isoleucine, phenylalanine, ornithine and proline; higher levels of lactic acid and urea; and lower levels of crotonic acid, azelaic acid, ethanolamine and cholesterol. It appears that the glycolysis pathway and amino acid metabolic activity are increased in patients with psoriasis. These metabolic perturbations may stem from increased demand for protein biosynthesis and keratinocyte hyperproliferation. Our findings may help to elucidate the pathogenesis of psoriasis and provide insights into early diagnosis and therapeutic intervention. © 2016 British Association of Dermatologists.

  11. MassTRIX reloaded: combined analysis and visualization of transcriptome and metabolome data.

    Directory of Open Access Journals (Sweden)

    Brigitte Wägele

    Full Text Available Systems Biology is a field in biological science that focuses on the combination of several or all "omics"-approaches in order to find out how genes, transcripts, proteins and metabolites act together in the network of life. Metabolomics as analog to genomics, transcriptomics and proteomics is more and more integrated into biological studies and often transcriptomic and metabolomic experiments are combined in one setup. At a first glance both data types seem to be completely different, but both produce information on biological entities, either transcripts or metabolites. Both types can be overlaid on metabolic pathways to obtain biological information on the studied system. For the joint analysis of both data types the MassTRIX webserver was updated. MassTRIX is freely available at www.masstrix.org.

  12. Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity

    Directory of Open Access Journals (Sweden)

    Fumio eMatsuda

    2011-08-01

    Full Text Available A novel framework for automated elucidation of metabolite structures in liquid chromatography-mass spectrometer (LC-MS metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three distinct databases, KNApSAcK, ReSpect, and the PRIMe standard compound database, were employed for the structural elucidation. The outputs were retrieved using the CAS metabolite identifier for identification and putative annotation. A simple metabolite ontology system was also introduced to attain putative characterization of the metabolite signals. The automated method was applied for the metabolome data sets obtained from the rosette leaves of 20 Arabidopsis accessions. Phenotypic variations in novel Arabidopsis metabolites among these accessions could be investigated using this method.

  13. Quantitative proteomic analysis by accurate mass retention time pairs.

    Science.gov (United States)

    Silva, Jeffrey C; Denny, Richard; Dorschel, Craig A; Gorenstein, Marc; Kass, Ignatius J; Li, Guo-Zhong; McKenna, Therese; Nold, Michael J; Richardson, Keith; Young, Phillip; Geromanos, Scott

    2005-04-01

    Current methodologies for protein quantitation include 2-dimensional gel electrophoresis techniques, metabolic labeling, and stable isotope labeling methods to name only a few. The current literature illustrates both pros and cons for each of the previously mentioned methodologies. Keeping with the teachings of William of Ockham, "with all things being equal the simplest solution tends to be correct", a simple LC/MS based methodology is presented that allows relative changes in abundance of proteins in highly complex mixtures to be determined. Utilizing a reproducible chromatographic separations system along with the high mass resolution and mass accuracy of an orthogonal time-of-flight mass spectrometer, the quantitative comparison of tens of thousands of ions emanating from identically prepared control and experimental samples can be made. Using this configuration, we can determine the change in relative abundance of a small number of ions between the two conditions solely by accurate mass and retention time. Employing standard operating procedures for both sample preparation and ESI-mass spectrometry, one typically obtains under 5 ppm mass precision and quantitative variations between 10 and 15%. The principal focus of this paper will demonstrate the quantitative aspects of the methodology and continue with a discussion of the associated, complementary qualitative capabilities.

  14. Accurate mass and velocity functions of dark matter haloes

    Science.gov (United States)

    Comparat, Johan; Prada, Francisco; Yepes, Gustavo; Klypin, Anatoly

    2017-08-01

    N-body cosmological simulations are an essential tool to understand the observed distribution of galaxies. We use the MultiDark simulation suite, run with the Planck cosmological parameters, to revisit the mass and velocity functions. At redshift z = 0, the simulations cover four orders of magnitude in halo mass from ˜1011M⊙ with 8783 874 distinct haloes and 532 533 subhaloes. The total volume used is ˜515 Gpc3, more than eight times larger than in previous studies. We measure and model the halo mass function, its covariance matrix w.r.t halo mass and the large-scale halo bias. With the formalism of the excursion-set mass function, we explicit the tight interconnection between the covariance matrix, bias and halo mass function. We obtain a very accurate (Planck cosmology. Finally, we provide precise analytical fits of the Vmax maximum velocity function up to redshift z < 2.3 to push for the development of halo occupation distribution using Vmax. The data and the analysis code are made publicly available in the Skies and Universes data base.

  15. Mass appeal : metabolite identification in mass spectrometry-focused untargeted metabolomics

    NARCIS (Netherlands)

    Dunn, Warwick B.; Erban, Alexander; Weber, Ralf J.M.; Creek, Darren J.; Brown, Marie; Breitling, Rainer; Hankemeier, Thomas; Goodacre, Royston; Neumann, Steffen; Kopka, Joachim; Viant, Mark R.

    2013-01-01

    Metabolomics has advanced significantly in the past 10 years with important developments related to hardware, software and methodologies and an increasing complexity of applications. In discovery-based investigations, applying untargeted analytical methods, thousands of metabolites can be detected

  16. Neuronal metabolomics by ion mobility mass spectrometry in cocaine self-administering rats after early and late withdrawal.

    Science.gov (United States)

    Zhang, Xing; Chiu, Veronica M; Todd, Ryan P; Sorg, Barbara A; Hill, Herbert H

    2016-06-01

    The neuronal metabolomes in rat striatum (STR), prefrontal cortex (PFC), and nucleus accumbens (NAC) were analyzed by Hadamard transform ion mobility mass spectrometry (HT-IMMS) in order to reveal global and specific metabolic changes induced by cocaine self-administration after 1-day or 3-week withdrawal. Metabolite features were comprehensively separated and detected using HPLC-IMMS within minutes. Global metabolic differences were observed by PCA for comparisons between cocaine and saline treatments at 1-day withdrawal time. Metabolite features that were significantly changed were selected using PCA loadings' plot and unpaired LLL test and then tentatively identified by accurate m/z, yielding a complete profile of metabolic changes induced by cocaine self-administration. The majority of these changes were found at the 1-day withdrawal time, but several of them endured even after 3-week withdrawal from cocaine, and these changes were generally brain region specific. Putatively identified metabolites associated with oxidative stress and energy metabolism were also specifically investigated. We discovered that the dysregulation of creatine/creatinine was different between the STR and NAC, demonstrating that metabolic alterations are brain region specific. Glutathione and adenosine were also changed in their abundance, and the results agreed with previous studies. In general, this study provided a high-throughput analytical platform to perform metabolomics analyses with putative identifications for altered metabolite features induced by cocaine treatment, therefore revealing additional metabolic targets of cocaine-induced changes after early and extended withdrawal times.

  17. 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

  18. Statistical analysis of proteomics, metabolomics, and lipidomics data using mass spectrometry

    CERN Document Server

    Mertens, Bart

    2017-01-01

    This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass ...

  19. 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

  20. 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...

  1. 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.

  2. Accurate mass measurements of very short-lived nuclei

    CERN Document Server

    Herfurth, F; Ames, F; Audi, G; Beck, D; Blaum, K; Bollen, G; Engels, O; Kluge, H J; Lunney, M D; Moores, R B; Oinonen, M; Sauvan, E; Bolle, C A; Scheidenberger, C; Schwarz, S; Sikler, G; Weber, C

    2002-01-01

    Mass measurements of /sup 34/Ar, /sup 73-78/Kr, and /sup 74,76/Rb were performed with the Penning-trap mass spectrometer ISOLTRAP. Very accurate Q/sub EC/-values are needed for the investigations of the F /sub t/-value of 0/sup +/ to 0/sup +/ nuclear beta -decays used to test the standard model predictions for weak interactions. The necessary accuracy on the Q/sub EC/-value requires the mass of mother and daughter nuclei to be measured with delta m/mmass has been measured with a relative accuracy of 1.1.10/sup -8/. The Q/sub EC/-value of the /sup 34/Ar 0 /sup +/ to 0/sup +/ decay can now he determined with an uncertainty of about 0.01%. Furthermore, /sup 74/Rb is the shortest-lived nuclide ever investigated in a Penning trap. (18 refs).

  3. Quantification in untargeted mass spectrometry-based metabolomics

    NARCIS (Netherlands)

    Kloet, Frans Meindert van der

    2014-01-01

    The aim of this thesis was to develop concepts and methods to extract qualitative and quantitative information about metabolites from untargeted mass spectrometric data of biological samples. Several typical challenges in data handling were addressed that prevent a straightforward interpretation

  4. 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.

  5. Applications of Structural Mass Spectrometry to Metabolomics: Clarifying Bond Specific Spectral Signatures with Isotope Edited Spectroscopy

    Science.gov (United States)

    Gorlova, Olga; Wolke, Conrad T.; Fournier, Joseph; Colvin, Sean; Johnson, Mark; Miller, Scott

    2015-06-01

    Comprehensive FTIR, MS/MS and NMR of pharmaceuticals are generally readily available but characterization of their metabolites has been an obstacle. Atorvastatin is a statin drug responsible for the maintenance of cholesterol in the body. Diovan is an angiostensin receptor antagonist used to treat high blood pressure and congestive heart failure. The field of metabolomics, however, is struggling to obtain the identity of their structures. We implement mass spectrometry with cryogenic ion spectroscopy to study gaseous ions of the desired metabolites which, in combination, not only identify the mass of the metabolite but also elucidate their structures through isotope-specific infrared spectroscopy.

  6. Metabolomics, peptidomics and proteomics applications of capillary electrophoresis-mass spectrometry in Foodomics: A review

    Energy Technology Data Exchange (ETDEWEB)

    Ibáñez, Clara; Simó, Carolina; García-Cañas, Virginia; Cifuentes, Alejandro, E-mail: a.cifuentes@csic.es; Castro-Puyana, María

    2013-11-13

    Graphical abstract: -- Highlights: •Foodomics allows studying food and nutrition through the application of advanced omics approaches. •CE-MS plays a crucial role as analytical platform to carry out omics studies. •CE-MS applications for food metabolomics, proteomics and peptidomics are presented. -- Abstract: In the current post-genomic era, Foodomics has been defined as a discipline that studies food and nutrition through the application of advanced omics approaches. Foodomics involves the use of genomics, transcriptomics, epigenetics, proteomics, peptidomics, and/or metabolomics to investigate food quality, safety, traceability and bioactivity. In this context, capillary electrophoresis-mass spectrometry (CE-MS) has been applied mainly in food proteomics, peptidomics and metabolomics. The aim of this review work is to present an overview of the most recent developments and applications of CE-MS as analytical platform for Foodomics, covering the relevant works published from 2008 to 2012. The review provides also information about the integration of several omics approaches in the new Foodomics field.

  7. A complete workflow for high-resolution spectral-stitching nanoelectrospray direct-infusion mass-spectrometry-based metabolomics and lipidomics.

    Science.gov (United States)

    Southam, Andrew D; Weber, Ralf J M; Engel, Jasper; Jones, Martin R; Viant, Mark R

    2016-02-01

    Metabolomic and lipidomic studies measure and discover metabolic and lipid profiles in biological samples, enabling a better understanding of the metabolism of specific biological phenotypes. Accurate biological interpretations require high analytical reproducibility and sensitivity, and standardized and transparent data processing. Here we describe a complete workflow for nanoelectrospray ionization (nESI) direct-infusion mass spectrometry (DIMS) metabolomics and lipidomics. After metabolite and lipid extraction from tissues and biofluids, samples are directly infused into a high-resolution mass spectrometer (e.g., Orbitrap) using a chip-based nESI sample delivery system. nESI functions to minimize ionization suppression or enhancement effects as compared with standard electrospray ionization (ESI). Our analytical technique-named spectral stitching-measures data as several overlapping mass-to-charge (m/z) windows that are subsequently 'stitched' together, creating a complete mass spectrum. This considerably increases the dynamic range and detection sensitivity-about a fivefold increase in peak detection-as compared with the collection of DIMS data as a single wide mass-to-charge (m/z ratio) window. Data processing, statistical analysis and metabolite annotation are executed as a workflow within the user-friendly, transparent and freely available Galaxy platform (galaxyproject.org). Generated data have high mass accuracy that enables molecular formulae peak annotations. The workflow is compatible with any sample-extraction method; in this protocol, the examples are extracted using a biphasic method, with methanol, chloroform and water as the solvents. The complete workflow is reproducible, rapid and automated, which enables cost-effective analysis of >10,000 samples per year, making it ideal for high-throughput metabolomics and lipidomics screening-e.g., for clinical phenotyping, drug screening and toxicity testing.

  8. Ultraperformance liquid chromatography-mass spectrometry based comprehensive metabolomics combined with pattern recognition and network analysis methods for characterization of metabolites and metabolic pathways from biological data sets.

    Science.gov (United States)

    Zhang, Ai-hua; Sun, Hui; Han, Ying; Yan, Guang-li; Yuan, Ye; Song, Gao-chen; Yuan, Xiao-xia; Xie, Ning; Wang, Xi-jun

    2013-08-06

    Metabolomics is the study of metabolic changes in biological systems and provides the small molecule fingerprints related to the disease. Extracting biomedical information from large metabolomics data sets by multivariate data analysis is of considerable complexity. Therefore, more efficient and optimizing metabolomics data processing technologies are needed to improve mass spectrometry applications in biomarker discovery. Here, we report the findings of urine metabolomic investigation of hepatitis C virus (HCV) patients by high-throughput ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) coupled with pattern recognition methods (principal component analysis, partial least-squares, and OPLS-DA) and network pharmacology. A total of 20 urinary differential metabolites (13 upregulated and 7 downregulated) were identified and contributed to HCV progress, involve several key metabolic pathways such as taurine and hypotaurine metabolism, glycine, serine and threonine metabolism, histidine metabolism, arginine and proline metabolism, and so forth. Metabolites identified through metabolic profiling may facilitate the development of more accurate marker algorithms to better monitor disease progression. Network analysis validated close contact between these metabolites and implied the importance of the metabolic pathways. Mapping altered metabolites to KEGG pathways identified alterations in a variety of biological processes mediated through complex networks. These findings may be promising to yield a valuable and noninvasive tool that insights into the pathophysiology of HCV and to advance the early diagnosis and monitor the progression of disease. Overall, this investigation illustrates the power of the UPLC-MS platform combined with the pattern recognition and network analysis methods that can engender new insights into HCV pathobiology.

  9. mSpecs: a software tool for the administration and editing of mass spectral libraries in the field of metabolomics

    Directory of Open Access Journals (Sweden)

    Heinen Stephanie

    2009-07-01

    Full Text Available Abstract Background Metabolome analysis with GC/MS has meanwhile been established as one of the "omics" techniques. Compound identification is done by comparison of the MS data with compound libraries. Mass spectral libraries in the field of metabolomics ought to connect the relevant mass traces of the metabolites to other relevant data, e.g. formulas, chemical structures, identification numbers to other databases etc. Since existing solutions are either commercial and therefore only available for certain instruments or not capable of storing such information, there is need to provide a software tool for the management of such data. Results Here we present mSpecs, an open source software tool to manage mass spectral data in the field of metabolomics. It provides editing of mass spectra and virtually any associated information, automatic calculation of formulas and masses and is extensible by scripts. The graphical user interface is capable of common techniques such as copy/paste, undo/redo and drag and drop. It owns import and export filters for the major public file formats in order to provide compatibility to commercial instruments. Conclusion mSpecs is a versatile tool for the management and editing of mass spectral libraries in the field of metabolomics. Beyond that it provides capabilities for the automatic management of libraries though its scripting functionality. mSpecs can be used on all major platforms and is licensed under the GNU General Public License and available at http://mspecs.tu-bs.de.

  10. Relative quantitation in single-cell metabolomics by laser ablation electrospray mass spectrometry.

    Science.gov (United States)

    Shrestha, Bindesh; Vertes, Akos

    2014-01-01

    Single-cell analysis of metabolites by mass spectrometry (MS) is challenging due to the very limited volume and inherent molecular complexity of the sample. Quantitative metabolomic analysis of individual cells provides information on the metabolic heterogeneity of cells unattainable by aggregate analysis of multiple cells. Depending on the ionization method, MS can offer quantitative analysis for a broad class of metabolites exhibiting both high sensitivity and selectivity. Laser ablation electrospray ionization (LAESI) has been successfully exploited to analyze metabolites from broad range of biological samples, including single cells and small cell populations. In this work, we describe a protocol for the relative quantitation of metabolites in single cells by LAESI-mass spectrometry.

  11. Radiation Metabolomics. 3. Biomarker Discovery in the Urine of Gamma-Irradiated Rats Using a Simplified Metabolomics Protocol of Gas Chromatography-Mass Spectrometry Combined with Random Forests Machine Learning Algorithm

    OpenAIRE

    Lanz, Christian; Patterson, Andrew D.; Slavík, Josef; Krausz, Kristopher W.; Ledermann, Monika; Gonzalez, Frank J.; Idle, Jeffrey R.

    2009-01-01

    Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy γ radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to ...

  12. Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

    Directory of Open Access Journals (Sweden)

    Esther Imperlini

    2016-01-01

    Full Text Available Organic acidemias (OAs are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA, neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS- based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs.

  13. 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.

  14. Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics.

    Science.gov (United States)

    Olivon, Florent; Roussi, Fanny; Litaudon, Marc; Touboul, David

    2017-09-01

    New omics sciences generate massive amounts of data, requiring to be sorted, curated, and statistically analyzed by dedicated software. Data-dependent acquisition mode including inclusion and exclusion rules for tandem mass spectrometry is routinely used to perform such analyses. While acquisition parameters are well described for proteomics, no general rule is currently available to generate reliable metabolomic data for molecular networking analysis on the Global Natural Product Social Molecular Networking platform (GNPS). Following on from an exploration of key parameters influencing the quality of molecular networks, universal optimal acquisition conditions for metabolomic studies are suggested in the present paper. The benefit of data pre-clustering before initiating large datasets for GNPS analyses is also demonstrated. Moreover, an efficient workflow dedicated to Agilent Technologies instruments is described, making the dereplication process easier by unambiguously distinguishing isobaric isomers eluted at different retention times, annotating the molecular networks with chemical formulas, and giving access to semi-quantitative data. This specific workflow foreshadows future developments of the GNPS platform.

  15. Mass-Based Metabolomic Analysis of Lactobacillus sakei and Its Growth Media at Different Growth Phases.

    Science.gov (United States)

    Lee, Sang Bong; Rhee, Young Kyoung; Gu, Eun-Ji; Kim, Dong-Wook; Jang, Gwang-Ju; Song, Seong-Hwa; Lee, Jae-In; Kim, Bo-Min; Lee, Hyeon-Jeong; Hong, Hee-Do; Cho, Chang-Won; Kim, Hyun-Jin

    2017-05-28

    Changes in the metabolite profiles of Lactobacillus sakei and its growth media, based on different culture times (0, 6, 12, and 24 h), were investigated using gas chromatography-mass spectrometry (MS) and liquid chromatography-MS with partial least squares discriminant analysis, in order to understand the growth characteristics of this organism. Cell and media samples of L. sakei were significantly separated on PLS-DA score plots. Cell and media metabolites, including sugars, amino acids, and organic acids, were identified as major metabolites contributing to the difference among samples. The alteration of cell and media metabolites during cell growth was strongly associated with energy production. Glucose, fructose, carnitine, tryptophan, and malic acid in the growth media were used as primary energy sources during the initial growth stage, but after the exhaustion of these energy sources, L. sakei could utilize other sources such as trehalose, citric acid, and lysine in the cell. The change in the levels of these energy sources was inversely similar to the energy production, especially ATP. Based on these identified metabolites, the metabolomic pathway associated with energy production through lactic acid fermentation was proposed. Although further studies are required, these results suggest that MS-based metabolomic analysis might be a useful tool for understanding the growth characteristics of L. sakei, the most important bacterium associated with meat and vegetable fermentation, during growth.

  16. The future of liquid chromatography-mass spectrometry in metabolic profiling and metabolomic studies for biomarker discovery.

    Energy Technology Data Exchange (ETDEWEB)

    Metz, Thomas O.; Zhang, Qibin; Page, Jason S.; Shen, Yufeng; Callister, Stephen J.; Jacobs, Jon M.; Smith, Richard D.

    2007-06-01

    The future utility of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discover will be discussed, beginning with a brief description of the evolution of metabolomics and the utilization of the three most popular analytical platforms in such studies: NMR, GC-MS, and LC-MS. Emphasis is placed on recent developments in high-efficiency LC separations and sensitive electrospray ionization approaches and the benefits to incorporating both in LC-MS-based approaches. The advantages and disadvantages of various quantitative approaches are reviewed, followed by the current LC-MS-based tools available for candidate biomarker characterization and identification. Finally, a brief prediction on the future path of LC-MS-based methods in metabolic profiling and metabolomic studies is given.

  17. How accurate is ultrasound in evaluating palpable breast masses ...

    African Journals Online (AJOL)

    Introduction: Breast masses have become common in women. Such masses pose a potential threat to women especially in the era of increased cases of breast cancer worldwide. Breast carcinoma ranks first among the malignant tumors affecting females in many parts of the world with the rate of breast cancer being 1 in 8 in ...

  18. MassCascade: Visual Programming for LC-MS Data Processing in Metabolomics.

    Science.gov (United States)

    Beisken, Stephan; Earll, Mark; Portwood, David; Seymour, Mark; Steinbeck, Christoph

    2014-04-01

    Liquid chromatography coupled to mass spectrometry (LC-MS) is commonly applied to investigate the small molecule complement of organisms. Several software tools are typically joined in custom pipelines to semi-automatically process and analyse the resulting data. General workflow environments like the Konstanz Information Miner (KNIME) offer the potential of an all-in-one solution to process LC-MS data by allowing easy integration of different tools and scripts. We describe MassCascade and its workflow plug-in for processing LC-MS data. The Java library integrates frequently used algorithms in a modular fashion, thus enabling it to serve as back-end for graphical front-ends. The functions available in MassCascade have been encapsulated in a plug-in for the workflow environment KNIME, allowing combined use with e.g. statistical workflow nodes from other providers and making the tool intuitive to use without knowledge of programming. The design of the software guarantees a high level of modularity where processing functions can be quickly replaced or concatenated. MassCascade is an open-source library for LC-MS data processing in metabolomics. It embraces the concept of visual programming through its KNIME plug-in, simplifying the process of building complex workflows. The library was validated using open data.

  19. Metabolomic approach for identifying and visualizing molecular tissue markers in tadpoles of Xenopus tropicalis by mass spectrometry imaging

    Directory of Open Access Journals (Sweden)

    Naoko Goto-Inoue

    2016-09-01

    Full Text Available In developmental and cell biology it is crucial to evaluate the dynamic profiles of metabolites. An emerging frog model system using Xenopus tropicalis, whose genome sequence and inbred strains are available, is now ready for metabolomics investigation in amphibians. In this study we applied matrix-assisted laser desorption/ionization (MALDI-mass spectrometry imaging (MSI analysis to identify and visualize metabolomic molecular markers in tadpoles of Xenopus tropicalis. We detected tissue-specific peaks and visualized their distribution in tissues, and distinguished 19 tissues and their specific peaks. We identified, for the first time, some of their molecular localizations via tandem mass spectrometric analysis: hydrocortisone in artery, L-DOPA in rhombencephalon, taurine in eye, corticosterone in gill, heme in heart, inosine monophosphate and carnosine in muscle, dopamine in nerves, and phosphatidylethanolamine (16:0/20:4 in pharynx. This is the first MALDI-MSI study of X. tropicalis tadpoles, as in small tadpoles it is hard to distinguish and dissect the various organs. Furthermore, until now there has been no data about the metabolomic profile of each organ. Our results suggest that MALDI-MSI is potentially a powerful tool for examining the dynamics of metabolomics in metamorphosis as well as conformational changes due to metabolic changes.

  20. 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.

  1. Solid-phase analytical derivatization for gas-chromatography-mass-spectrometry-based metabolomics.

    Science.gov (United States)

    Takeo, Emi; Sasano, Ryoichi; Shimma, Shuichi; Bamba, Takeshi; Fukusaki, Eiichiro

    2017-08-08

    A novel derivatization method for gas chromatography/mass spectrometry (GC/MS)-based metabolomics was developed, based on solid-phase analytical derivatization (SPAD) with methoximation followed by trimethylsilylation. This SPAD method realized derivatization on solid phases combining strong anion exchange with strong cation exchange. To omit a sample condensation process, GC/MS injection was performed using a large-volume injection mode. This mode uses a stomach-shaped insert, and enables a large quantity of sample to be vaporized and introduced into the GC/MS system. In the present study, several parameters were investigated for each SPAD step. The optimal derivatization conditions were determined to be 3-min-methoximation with 5 μL of >5% methoxyamine solution, and 10-min-trimethylsilylation with 25 μL of N-methyl-N-trimethylsilyl-trifluoroacetamide (MSTFA). Derivatized analytes were effectively eluted with 25 μL of n-hexane. The influences of coexisting substances were also investigated. Coexisting saccharides did not significantly affect the derivatization of analytes. Moreover, saccharides were efficiently washed out using 80% (v/v) acetonitrile in water. The influences of coexisting sodium chloride were negated by dilution of the sample solution with water. The developed method enables the derivatization of both anionic and cationic metabolites, and high-throughput sample preparation. The coverage of detectable metabolites for the developed method was similar to that of the conventional method. This is the first report of a SPAD-based human plasma metabolome analysis protocol. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  2. Optimization of large-scale pseudotargeted metabolomics method based on liquid chromatography-mass spectrometry.

    Science.gov (United States)

    Luo, Ping; Yin, Peiyuan; Zhang, Weijian; Zhou, Lina; Lu, Xin; Lin, Xiaohui; Xu, Guowang

    2016-03-11

    Liquid chromatography-mass spectrometry (LC-MS) is now a main stream technique for large-scale metabolic phenotyping to obtain a better understanding of genomic functions. However, repeatability is still an essential issue for the LC-MS based methods, and convincing strategies for long time analysis are urgently required. Our former reported pseudotargeted method which combines nontargeted and targeted analyses, is proved to be a practical approach with high-quality and information-rich data. In this study, we developed a comprehensive strategy based on the pseudotargeted analysis by integrating blank-wash, pooled quality control (QC) sample, and post-calibration for the large-scale metabolomics study. The performance of strategy was optimized from both pre- and post-acquisition sections including the selection of QC samples, insertion frequency of QC samples, and post-calibration methods. These results imply that the pseudotargeted method is rather stable and suitable for large-scale study of metabolic profiling. As a proof of concept, the proposed strategy was applied to the combination of 3 independent batches within a time span of 5 weeks, and generated about 54% of the features with coefficient of variations (CV) below 15%. Moreover, the stability and maximal capability of a single analytical batch could be extended to at least 282 injections (about 110h) while still providing excellent stability, the CV of 63% metabolic features was less than 15%. Taken together, the improved repeatability of our strategy provides a reliable protocol for large-scale metabolomics studies. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Metabolic Profiling of Human Benign and Malignant Pulmonary Nodules Using Mass Spectrometry-Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Choon Nam Ong

    2013-07-01

    Full Text Available Solitary pulmonary nodule (SPN or coin lesion is a mass in the lung and can be commonly found in chest X-rays or computerized tomography (CT scans. However, despite the advancement of imaging technologies, it is still difficult to distinguish malignant cancer from benign SPNs. Here we investigated the metabolic profiling of patients with benign and malignant pulmonary nodules. A combination of gas chromatography/mass spectrometry (GC/MS and liquid chromatography/mass spectrometry (LC/MS was used to profile the plasma metabolites in 17 patients with malignant SPNs, 15 patients with benign SPNs and 20 healthy controls. The metabolic profiles were assayed using OPLS-DA, and further analyzed to identify marker metabolites related to diseases. Both GC/MS- and LC/MS-derived models showed clear discriminations in metabolic profiles among three groups. It was found that 63 metabolites (12 from GC/MS, 51 from LC/MS contributed to the differences. Of these, 48 metabolites showed same change trend in both malignant and benign SPNs as compared with healthy controls, indicating some common pathways including inflammation and oxidative injury shared by two diseases. In contrast, 14 metabolites constituted distinct profiles that differentiated malignant from benign SPNs, which might be a unique biochemical feature associated with lung cancer. Overall, our data suggested that integration of two highly sensitive and complementary metabolomics platforms could enable a comprehensive metabolic profiling and assist in discrimination malignant from benign SPNs.

  4. Quantitative proteomics using the high resolution accurate mass capabilities of the quadrupole-orbitrap mass spectrometer.

    Science.gov (United States)

    Gallien, Sebastien; Domon, Bruno

    2014-08-01

    High resolution/accurate mass hybrid mass spectrometers have considerably advanced shotgun proteomics and the recent introduction of fast sequencing capabilities has expanded its use for targeted approaches. More specifically, the quadrupole-orbitrap instrument has a unique configuration and its new features enable a wide range of experiments. An overview of the analytical capabilities of this instrument is presented, with a focus on its application to quantitative analyses. The high resolution, the trapping capability and the versatility of the instrument have allowed quantitative proteomic workflows to be redefined and new data acquisition schemes to be developed. The initial proteomic applications have shown an improvement of the analytical performance. However, as quantification relies on ion trapping, instead of ion beam, further refinement of the technique can be expected.

  5. Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry

    NARCIS (Netherlands)

    Vos, de C.H.; Moco, S.I.A.; Lommen, A.; Keurentjes, J.J.B.; Bino, R.J.; Hall, R.D.

    2007-01-01

    Untargeted metabolomics aims to gather information on as many metabolites as possible in biological systems by taking into account all information present in the data sets. Here we describe a detailed protocol for large-scale untargeted metabolomics of plant tissues, based on reversed phase liquid

  6. Alteration in the liver metabolome of rats with metabolic syndrome after treatment with Hydroxytyrosol. A Mass Spectrometry And Nuclear Magnetic Resonance - based metabolomics study.

    Science.gov (United States)

    Dagla, Ioanna; Benaki, Dimitra; Baira, Eirini; Lemonakis, Nikolaos; Poudyal, Hemant; Brown, Lindsay; Tsarbopoulos, Anthony; Skaltsounis, Alexios-Leandros; Mikros, Emmanouel; Gikas, Evagelos

    2018-02-01

    Metabolic syndrome (MetS) represents a group of abnormalities that enhances the risk for cardiovascular disease, diabetes and stroke. The Mediterranean diet seems to be an important dietary pattern, which reduces the incidence of MetS. Hydroxytyrosol (HT) - a simple phenol found in olive oil - has received increased attention for its antioxidant activity. Recently, the European Foods Safety Authority (EFSA) claimed that dietary consumption of HT exhibits a protective role against cardiovascular disease. In this study, an experimental protocol has been setup, including isolated HT administration in a diet induced model of MetS in young Wistar rats, in order to find out whether HT has a protective effect against MetS. Rats were randomly divided into two groups nurtured by high-carbohydrate high-fat (H) (MetS inducing diet) and high-carbohydrate high-fat + HT (HHT). HT (20mg/kg/d oral gavage, water vehicle) was administered for 8 weeks on the basal diet. Previous pharmacological evaluation of HT showed that hepatic steatosis was reduced and the inflammatory cells into the liver were infiltrated. These indicate that HT shows bioactivity against metabolic syndrome. Therefore, the metabolomics evaluation of liver extracts would indicate the putative biochemical mechanisms of HT activity. Thus, the extracts of liver tissues were analyzed using Ultra Performance Liquid Chromatography - High Resolution Mass Spectrometry (UPLC-HRMS, Orbitrap Discovery) and Nuclear Magnetic Resonance (NMR) spectroscopy (Bruker Avance III 600MHz). Multivariate analysis was performed in order to gain insight on the metabolic effects of HT administration on the liver metabolome. Normalization employing multiple internal standards and Quality Control-based Robust LOESS (LOcally Estimated Scatterplot Smoothing) Signal Correction algorithm (QC-RLSC) was added in the processing pipeline to enhance the reliability of metabolomic analysis by reducing unwanted information. Experimentally, HHT rats were

  7. A Rough Guide to Metabolite Identification Using High Resolution Liquid Chromatography Mass Spectrometry in Metabolomic Profiling in Metazoans

    Directory of Open Access Journals (Sweden)

    David G Watson

    2013-01-01

    Full Text Available Compound identification in mass spectrometry based metabolomics can be a problem but sometimes the problem seems to be presented in an over complicated way. The current review focuses on metazoans where the range of metabolites is more restricted than for example in plants. The focus is on liquid chromatography with high resolution mass spectrometry where it is proposed that most of the problems in compound identification relate to structural isomers rather than to isobaric compounds. Thus many of the problems faced relate to separation of isomers, which is usually required even if fragmentation is used to support structural identification. Many papers report the use of MS/MS or MS2 as an adjunct to the identification of known metabolites but there a few examples in metabolomics studies of metazoans of complete structure elucidation of novel metabolites or metabolites where no authentic standards are available for comparison.

  8. A matrix-induced ion suppression method to normalize concentration in urinary metabolomics studies using flow injection analysis electrospray ionization mass spectrometry.

    Science.gov (United States)

    Chen, Guan-yuan; Liao, Hsiao-wei; Tseng, Yufeng Jane; Tsai, I-lin; Kuo, Ching-hua

    2015-03-15

    Normalizing the total urine concentration is important for minimizing bias in urinary metabolomics analysis comparisons. In this study, we report a matrix-induced ion suppression (MIIS)-based method to normalize concentration using flow injection analysis coupled with electrospray ionization mass spectrometry (FIA-ESI-MS). An ion suppression indicator (ISI) was spiked into urine samples, and the intensity of the extracted ion chromatogram (EIC) for ISI in a urine matrix was subtracted by the EIC for a blank solution and used to calculate the extent to which the signal was reduced by the urine matrix. A series dilution of pooled urine samples was used to correlate the urine concentration and level of ion suppression for ISI. A regression equation was used to estimate the relative concentration of unknown urine samples. The MIIS method was validated for linearity, precision and accuracy. We obtained a good correlation using a quadratic regression model for 1- to 32-fold urine dilutions (R(2)=0.998). The reproducibility (n=4) and intermediate precision (n=3) were below 5% RSD, and the accuracy ranged from 97.15% to 102.10%. The established method was used to estimate the relative concentrations of 16 urine samples, and the results were compared with commonly used normalization methods. Pearson's correlation test was used to demonstrate that the MIIS method correlated highly with the creatinine and osmolarity methods; the correlation coefficients were 0.93 and 0.99, respectively. We successfully applied this method to a urinary metabolomics study on breast cancer. This study demonstrated the MIIS method is simple, accurate and can contribute to data integrity in urinary metabolomics studies. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Determination of total concentration of chemically labeled metabolites as a means of metabolome sample normalization and sample loading optimization in mass spectrometry-based metabolomics.

    Science.gov (United States)

    Wu, Yiman; Li, Liang

    2012-12-18

    For mass spectrometry (MS)-based metabolomics, it is important to use the same amount of starting materials from each sample to compare the metabolome changes in two or more comparative samples. Unfortunately, for biological samples, the total amount or concentration of metabolites is difficult to determine. In this work, we report a general approach of determining the total concentration of metabolites based on the use of chemical labeling to attach a UV absorbent to the metabolites to be analyzed, followed by rapid step-gradient liquid chromatography (LC) UV detection of the labeled metabolites. It is shown that quantification of the total labeled analytes in a biological sample facilitates the preparation of an appropriate amount of starting materials for MS analysis as well as the optimization of the sample loading amount to a mass spectrometer for achieving optimal detectability. As an example, dansylation chemistry was used to label the amine- and phenol-containing metabolites in human urine samples. LC-UV quantification of the labeled metabolites could be optimally performed at the detection wavelength of 338 nm. A calibration curve established from the analysis of a mixture of 17 labeled amino acid standards was found to have the same slope as that from the analysis of the labeled urinary metabolites, suggesting that the labeled amino acid standard calibration curve could be used to determine the total concentration of the labeled urinary metabolites. A workflow incorporating this LC-UV metabolite quantification strategy was then developed in which all individual urine samples were first labeled with (12)C-dansylation and the concentration of each sample was determined by LC-UV. The volumes of urine samples taken for producing the pooled urine standard were adjusted to ensure an equal amount of labeled urine metabolites from each sample was used for the pooling. The pooled urine standard was then labeled with (13)C-dansylation. Equal amounts of the (12)C

  10. Mass Spectrometry-Based Quantitative Metabolomics Revealed a Distinct Lipid Profile in Breast Cancer Patients

    Directory of Open Access Journals (Sweden)

    Yun Yen

    2013-04-01

    Full Text Available Breast cancer accounts for the largest number of newly diagnosed cases in female cancer patients. Although mammography is a powerful screening tool, about 20% of breast cancer cases cannot be detected by this method. New diagnostic biomarkers for breast cancer are necessary. Here, we used a mass spectrometry-based quantitative metabolomics method to analyze plasma samples from 55 breast cancer patients and 25 healthy controls. A number of 30 patients and 20 age-matched healthy controls were used as a training dataset to establish a diagnostic model and to identify potential biomarkers. The remaining samples were used as a validation dataset to evaluate the predictive accuracy for the established model. Distinct separation was obtained from an orthogonal partial least squares-discriminant analysis (OPLS-DA model with good prediction accuracy. Based on this analysis, 39 differentiating metabolites were identified, including significantly lower levels of lysophosphatidylcholines and higher levels of sphingomyelins in the plasma samples obtained from breast cancer patients compared with healthy controls. Using logical regression, a diagnostic equation based on three metabolites (lysoPC a C16:0, PC ae C42:5 and PC aa C34:2 successfully differentiated breast cancer patients from healthy controls, with a sensitivity of 98.1% and a specificity of 96.0%.

  11. Gas chromatography/mass spectrometry-based urine metabolome study in children for inborn errors of metabolism: An Indian experience.

    Science.gov (United States)

    Hampe, Mahesh H; Panaskar, Shrimant N; Yadav, Ashwini A; Ingale, Pramod W

    2017-02-01

    The present study highlights the feasibility of gas chromatography/mass spectrometry (GC/MS)-based analysis for simultaneous detection of >200 marker metabolites in urine found in characteristic pattern in inborn errors of metabolism (IEM) in India. During this retrospective study conducted from July 2013 to January 2016, we collected urine specimens on filter papers from Indian children across the country along with relevant demographic and clinical data. The laboratory technique involved urease pretreatment followed by deproteinization, derivatization, and subsequent computer-aided analysis of organic acids, amino acids, fatty acids, and sugars by GC/MS, which enable chemical diagnosis of IEM. Totally 23,140 patients were investigated for IEM with an estimated frequency of about 1.40%, that is, 323 positive cases. Most frequent disorders observed were of primary lactic acidemia (27.2%) and organic acidemia (methylmalonic aciduria, glutaric acidemia type I, propionic aciduria, etc.) followed by aminoacidopathies (maple syrup urine disease, phenylketonuria, tyrosinemia, etc.). Furthermore, alkaptonuria, canavan disease, and 4-hydroxybutyric aciduria were also diagnosed. Prompt treatment following diagnosis led to a better outcome in a considerable number of patients. GC/MS with one-step metabolomics enables quick detection, accurate identification, and precise quantification of a wide range of urinary markers that may not be discovered using existing newborn screening programs. The technique is effective as a second-tier test to other established screening technologies, as well as one-step primary screening tool for a wide spectrum of IEM. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  12. Twins labeling-liquid chromatography/mass spectrometry based metabolomics for absolute quantification of tryptophan and its key metabolites.

    Science.gov (United States)

    Guo, Huimin; Jiao, Yu; Wang, Xu; Lu, Tao; Zhang, Zunjian; Xu, Fengguo

    2017-06-30

    Tryptophan metabolism plays a crucial role in mediating gastrointestinal function. Here, in order to absolutely quantify tryptophan and its metabolites, a liquid chromatography-mass spectrometry (LC-MS) based targeted metabolomics approach was developed using N-dimethyl-/N-diethyl-amino naphthalene-1-sulfonyl chloride (Dns/Dens-Cl) as twins labeling (TL) reagents. Dns-Cl is famous in amine and phenol derivations, and structure is similar with Dens-Cl. The introduction of easily protonated moiety of tertiary ammonium-containing part in the derivatives from Dns to tryptophan and its metabolites not only improved the LC separation but also enhanced their MS response. In addition, the Dens labeled standards were used as internal standards to compensate for matrix effects and ensure accurate quantifications. With the proposed method, twelve metabolites in tryptophan pathway could be detected at sub-ng/mL levels using only 20μL rat serum (the limit of detection could reach 3pg/mL for tryptamine, N-acetyl-serotonin and 6-hydroxymelatonin). The sensitivity was enhanced about 1-2 orders of magnitude compared with non-derivatization method. Focusing on tryptophan pathway, the method was successfully applied to determine the absolute serum concentrations of twelve tryptophan metabolites in a vincristine-induced ileus rat model. A significant down-regulation of the tryptophan metabolism along the kynurenine pathway and up-regulation of serotonin pathway were uncovered. Our findings provide a deeper insight into the mechanism of gastrointestinal dysfunction. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry.

    Science.gov (United States)

    Zhang, Hongyou; Wu, Ling; Xu, Chuang; Xia, Cheng; Sun, Lingwei; Shu, Shi

    2013-09-26

    Ketosis is an important problem for dairy cows` production performance. However, it is still little known about plasma metabolomics details of dairy ketosis. A gas chromatography/mass spectrometry (GC/MS) technique was used to investigate plasma metabolic differences in cows that had clinical ketosis (CK, n=22), subclinical ketosis (SK, n=32), or were clinically normal controls (NC, n=22). The endogenous plasma metabolome was measured by chemical derivatization followed by GC/MS, which led to the detection of 267 variables. A two-sample t-test of 30, 32, and 13 metabolites showed statistically significant differences between SK and NC, CK and NC, and CK and SK, respectively. Orthogonal signal correction-partial least-square discriminant analysis (OPLS-DA) revealed that the metabolic patterns of both CK and SK were mostly similar, with the exception of a few differences. The development of CK and SK involved disturbances in many metabolic pathways, mainly including fatty acid metabolism, amino acid metabolism, glycolysis, gluconeogenesis, and the pentose phosphate pathway. A diagnostic model arbitrary two groups was constructed using OPLS-DA and receiver-operator characteristic curves (ROC). Multivariate statistical diagnostics yielded the 19 potential biomarkers for SK and NC, 31 for CK and NC, and 8 for CK and SK with area under the curve (AUC) values. Our results showed the potential biomarkers from CK, SK, and NC, including carbohydrates, fatty acids, amino acids, even sitosterol and vitamin E isomers, etc. 2-piperidinecarboxylic acid and cis-9-hexadecenoic acid were closely associated with metabolic perturbations in ketosis as Glc, BHBA and NEFA for dealing with metabolic disturbances of ketosis in clinical practice. However, further research is needed to explain changes of 2,3,4-trihydroxybutyric acid, 3,4-dihydroxybutyric acid, α-aminobutyric acid, methylmalonic acid, sitosterol and α-tocopherol in CK and SK, and to reveal differences between CK and SK. Our

  14. Collision energy alteration during mass spectrometric acquisition is essential to ensure unbiased metabolomic analysis

    CSIR Research Space (South Africa)

    Madala, NE

    2012-08-01

    Full Text Available Metabolomics entails identification and quantification of all metabolites within a biological system with a given physiological status; as such, it should be unbiased. A variety of techniques are used to measure the metabolite content of living...

  15. Metabolomics of adherent mammalian cells by capillary electrophoresis-mass spectrometry: HT-29 cells as case study.

    Science.gov (United States)

    Ibáñez, Clara; Simó, Carolina; Valdés, Alberto; Campone, Luca; Piccinelli, Anna Lisa; García-Cañas, Virginia; Cifuentes, Alejandro

    2015-06-10

    In this work, the optimization of an effective protocol for cell metabolomics is described with special emphasis in the sample preparation and subsequent analysis of intracellular metabolites from adherent mammalian cells by capillary electrophoresis-mass spectrometry. As case study, colon cancer HT-29 cells, a human cell model to investigate colon cancer, are employed. The feasibility of the whole method for cell metabolomics is demonstrated via a fast and sensitive profiling of the intracellular metabolites HT-29 cells by capillary electrophoresis-time-of-flight mass spectrometry (CE-TOF MS). The suitability of this methodology is further corroborated through the examination of the metabolic changes in the polyamines pathway produced in colon cancer HT-29 cells by difluoromethylornithine (DFMO), a known potent ornithine decarboxylase inhibitor. The selection of the optimum extraction conditions allowed a higher sample volume injection that led to an increase in CE-TOF MS sensitivity. Following a non-targeted metabolomics approach, 10 metabolites (namely, putrescine, ornithine, gamma-aminobutyric acid (GABA), oxidized and reduced glutathione, 5'-deoxy-5'-(methylthio)adenosine, N-acetylputrescine, cysteinyl-glycine, spermidine and an unknown compound) were found to be significantly altered by DFMO (p<0.05) in HT-29 cells. In addition to the effect of DFMO on polyamine metabolism, minor modifications of other metabolic pathways (e.g., related to intracellular thiol redox state) were observed. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Metabolomic Profiles of Body Mass Index in the Framingham Heart Study Reveal Distinct Cardiometabolic Phenotypes.

    Directory of Open Access Journals (Sweden)

    Jennifer E Ho

    Full Text Available Although obesity and cardiometabolic traits commonly overlap, underlying pathways remain incompletely defined. The association of metabolite profiles across multiple cardiometabolic traits may lend insights into the interaction of obesity and metabolic health. We sought to investigate metabolic signatures of obesity and related cardiometabolic traits in the community using broad-based metabolomic profiling.We evaluated the association of 217 assayed metabolites and cross-sectional as well as longitudinal changes in cardiometabolic traits among 2,383 Framingham Offspring cohort participants. Body mass index (BMI was associated with 69 of 217 metabolites (P<0.00023 for all, including aromatic (tyrosine, phenylalanine and branched chain amino acids (valine, isoleucine, leucine. Additional metabolic pathways associated with BMI included the citric acid cycle (isocitrate, alpha-ketoglutarate, aconitate, the tryptophan pathway (kynurenine, kynurenic acid, and the urea cycle. There was considerable overlap in metabolite profiles between BMI, abdominal adiposity, insulin resistance [IR] and dyslipidemia, modest overlap of metabolite profiles between BMI and hyperglycemia, and little overlap with fasting glucose or elevated blood pressure. Metabolite profiles were associated with longitudinal changes in fasting glucose, but the involved metabolites (ornithine, 5-HIAA, aminoadipic acid, isoleucine, cotinine were distinct from those associated with baseline glucose or other traits. Obesity status appeared to "modify" the association of 9 metabolites with IR. For example, bile acid metabolites were strongly associated with IR among obese but not lean individuals, whereas isoleucine had a stronger association with IR in lean individuals.In this large-scale metabolite profiling study, body mass index was associated with a broad range of metabolic alterations. Metabolite profiling highlighted considerable overlap with abdominal adiposity, insulin resistance

  17. Reference Standardization for Mass Spectrometry and High-resolution Metabolomics Applications to Exposome Research.

    Science.gov (United States)

    Go, Young-Mi; Walker, Douglas I; Liang, Yongliang; Uppal, Karan; Soltow, Quinlyn A; Tran, ViLinh; Strobel, Frederick; Quyyumi, Arshed A; Ziegler, Thomas R; Pennell, Kurt D; Miller, Gary W; Jones, Dean P

    2015-12-01

    The exposome is the cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes. A major challenge for exposome research lies in the development of robust and affordable analytic procedures to measure the broad range of exposures and associated biologic impacts occurring over a lifetime. Biomonitoring is an established approach to evaluate internal body burden of environmental exposures, but use of biomonitoring for exposome research is often limited by the high costs associated with quantification of individual chemicals. High-resolution metabolomics (HRM) uses ultra-high resolution mass spectrometry with minimal sample preparation to support high-throughput relative quantification of thousands of environmental, dietary, and microbial chemicals. HRM also measures metabolites in most endogenous metabolic pathways, thereby providing simultaneous measurement of biologic responses to environmental exposures. The present research examined quantification strategies to enhance the usefulness of HRM data for cumulative exposome research. The results provide a simple reference standardization protocol in which individual chemical concentrations in unknown samples are estimated by comparison to a concurrently analyzed, pooled reference sample with known chemical concentrations. The approach was tested using blinded analyses of amino acids in human samples and was found to be comparable to independent laboratory results based on surrogate standardization or internal standardization. Quantification was reproducible over a 13-month period and extrapolated to thousands of chemicals. The results show that reference standardization protocol provides an effective strategy that will enhance data collection for cumulative exposome research. In principle, the approach can be extended to other types of mass spectrometry and other analytical methods. © The

  18. Urinary metabolomic analysis of intrahepatic cholestasis of pregnancy based on high performance liquid chromatography/mass spectrometry.

    Science.gov (United States)

    Ma, Li; Zhang, Xiaoqing; Pan, Feng; Cui, Yue; Yang, Ting; Deng, Linlin; Shao, Yong; Ding, Min

    2017-08-01

    Intrahepatic cholestasis of pregnancy (ICP), a pregnancy-related liver disease, leads to complications for both mothers and fetuses. Metabolomic approach has been applied to maternal-fetal medicine. The global metabolomic alterations that are specific in ICP as yet have not been investigated. Based on high performance liquid chromatography/hybrid quadrupole time-of-flight (HPLC/Q-TOF) mass spectrometry, the untargeted metabolomics was used to analyze the changes of urinary metabolites between ICP group and the control group. One hundred nine variables in positive model and 119 variables in negative model were significantly different (pimportance in the project) score>1 by the orthogonal partial least squares discriminant analysis (OPLS-DA). 14 metabolites in positive model and 18 metabolites in negative model were selected and identified based on HMDB (human metabolome database). Most of these metabolites were involved in bile acids biosynthesis and metabolism, hormone metabolism and lipid metabolism. A metabolite panel (MG (22:5), LysoPE (22:5), l-homocysteine sulfonic acid, glycocholic acid and chenodeoxycholic acid 3-sulfate) was contrusted by the binary logistic regression analysis with high diagnostic accuracy for ICP. The area under the receiver operating characteristic curve was 0.988 with the sensitivity of 90.0% and specificity of 93.3%. Urinary metabolites allow for the discrimination of ICP from the controls by orthogonal partial least squares discriminant analysis. Therefore, these findings may provide deep insights for the etiopathogenesis of ICP. Moreover, the maternal urinary metabolite panel has the potential to be used as non-invasive biomarkers for the diagnosis of ICP. Copyright © 2017. Published by Elsevier B.V.

  19. 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.

  20. Analytical methods in untargeted metabolomics: state of the art in 2015

    Directory of Open Access Journals (Sweden)

    Arnald eAlonso

    2015-03-01

    Full Text Available Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile –the metabolome- has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance (NMR and mass spectrometry (MS are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high throughput biotechnologies is also reviewed.

  1. 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

  2. Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: Application to the detection of breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Gu Haiwei [Department of Physics, Purdue University, West Lafayette, IN 47907 (United States); Pan Zhengzheng [Department of Chemistry, Purdue University, West Lafayette, IN 47907 (United States); Xi Bowei [Department of Statistics, Purdue University, West Lafayette, IN 47907 (United States); Asiago, Vincent [Department of Chemistry, Purdue University, West Lafayette, IN 47907 (United States); Musselman, Brian [IonSense Inc., 999 Broadway, Suite 404, Saugus, MA 01906 (United States); Raftery, Daniel, E-mail: raftery@purdue.edu [Department of Chemistry, Purdue University, West Lafayette, IN 47907 (United States)

    2011-02-07

    Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, {sup 1}H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology.

  3. An Accurate Census of the Stellar Masses of Massive Central Galaxies

    Science.gov (United States)

    Moustakas, John; Lang, Dustin; Napier, Kevin; Stillman, Coley Michael; Poremba, Megan R.; Dey, Arjun; Rozo, Eduardo; Rykoff, Eli; Schlegel, David; Wechsler, Risa

    2018-01-01

    A significant fraction of the stellar mass in brightest cluster galaxies--as much as 50% or more--lies in the low surface brightness and hard-to-detect outer envelope of the galaxy. An accurate census of the integrated stellar masses of central galaxies critically impacts many outstanding problems in galaxy evolution, including measurements of the star formation efficiency in massive halos, the relative importance of supernova and black hole feedback, and the cosmic baryon fraction. We use deep optical and mid-infrared imaging of a sample of more than 35,000 central galaxies obtained as part of the Legacy Survey (http://legacysurvey.org) to measure their azimuthally averaged stellar mass profiles and integrated stellar masses. We compare our results with previous measurements of the massive end of the stellar mass function and the stellar mass-halo mass relation, and discuss the implications of our results for numerical simulations of star formation and feedback in massive galaxies.

  4. Identification of imidacloprid metabolites in onion (Allium cepa L.) using high-resolution mass spectrometry and accurate mass tools.

    Science.gov (United States)

    Thurman, E Michael; Ferrer, Imma; Zavitsanos, Paul; Zweigenbaum, Jerry A

    2013-09-15

    Imidacloprid is a potent and widely used insecticide on vegetable crops, such as onion (Allium cepa L.). Because of possible toxicity to beneficial insects, imidacloprid and several metabolites have raised safety concerns for pollenating insects, such as honey bees. Thus, imidacloprid metabolites continue to be an important subject for new methods that better understand its dissipation and fate in plants, such as onions. One month after a single addition of imidacloprid to soil containing onion plants, imidacloprid and its metabolites were extracted from pulverized onion with a methanol/water-buffer mixture and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/QTOF-MS) using a labeled imidacloprid internal standard and tandem mass spectrometric (MS/MS) analysis. Accurate mass tools were developed and applied to detect seven new metabolites of imidacloprid with the goal to better understand its fate in onion. The accurate mass tools include: database searching, diagnostic ions, chlorine mass filters, Mass Profiler software, and manual use of metabolic analogy. The new metabolites discovered included an amine reduction product (m/z 226.0854), and its methylated analogue (m/z 240.1010), and five other metabolites, all of unknown toxicity to insects. The accurate mass tools were combined with LC/QTOF-MS and were able to detect both known and new metabolites of imidacloprid using fragmentation studies of both parent and labeled standards. New metabolites and their structures were inferred from these MS/MS studies with accurate mass, which makes it possible to better understand imidacloprid metabolism in onion as well as new metabolite targets for toxicity studies. Copyright © 2013 John Wiley & Sons, Ltd.

  5. Accurate mass determination of short-lived isotopes by a tandem Penning-trap mass spectrometer

    Science.gov (United States)

    Stolzenberg, H.; Becker, St.; Bollen, G.; Kern, F.; Kluge, H.-J.; Otto, Th.; Savard, G.; Schweikhard, L.; Audi, G.; Moore, R. B.

    1990-12-01

    A mass spectrometer consisting of two Penning traps has been set up for short-lived isotopes at the on-line mass separator ISOLDE at CERN. The ion beam is collected and cooled in the first trap. After delivery to the second trap, high-accuracy direct mass measurements are made by determining the cyclotron frequency of the stored ions. Measurements have been performed for 118-137Cs. A resolving power of over 106 and an accuracy of 1.4×10-7 have been achieved, corresponding to about 20 keV.

  6. Accurate mass determination of short-lived isotopes by a tandem Penning-trap mass spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    Stolzenberg, H.; Becker, S.; Bollen, G.; Kern, F.; Kluge, H.; Otto, T.; Savard, G.; Schweikhard, L. (Institut fuer Physik, Universitaet Mainz, D-6500 Mainz (Federal Republic of Germany)); Audi, G. (Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, Laboratoire Rene Bernas, Batiment 108, F-91405 Orsay (France)); Moore, R.B. (Foster Radiation Laboratory, McGill University, Montreal (Canada)); The ISOLDE Collaboration

    1990-12-17

    A mass spectrometer consisting of two Penning traps has been set up for short-lived isotopes at the on-line mass separator ISOLDE at CERN. The ion beam is collected and cooled in the first trap. After delivery to the second trap, high-accuracy direct mass measurements are made by determining the cyclotron frequency of the stored ions. Measurements have been performed for {sup 118}Cs--{sup 137}Cs. A resolving power of over 10{sup 6} and an accuracy of 1.4{times}10{sup {minus}7} have been achieved, corresponding to about 20 keV.

  7. Capillary electrophoresis-mass spectrometry using a flow-through microvial interface for cationic metabolome analysis.

    Science.gov (United States)

    Lindenburg, Petrus W; Ramautar, Rawi; Jayo, Roxana G; Chen, David D Y; Hankemeier, Thomas

    2014-05-01

    The application of CE-MS in the field of metabolomics is underrepresented, even though it is in principle highly suited for the analysis of small charged compounds, as many metabolites are. Moreover, a robust coupling, using the sheath liquid (SL)-assisted interface was already presented more than a decade ago. A lack of concentration sensitivity is often mentioned as a reason for the underrepresentation of CE-MS in metabolomics. This is caused by postcolumn dilution of the sample with SL, which is typically delivered at a flow rate of 1-10 μL/min. In this study, we investigated the performance of the flow-through microvial (MV) assisted CE-MS interface for cationic metabolomics. With this interface, only a little liquid is added postcolumn, that is, typically 100-500 nL/min. For the evaluation, we used a metabolite mix comprising 45 important cationic metabolites and compared the sensitivity and LOD of both devices. The performance of the CE-MS system was significantly improved by using the MV-assisted interface; the sensitivity was increased more than three times and the LOD decreased more than five times. Then, we analyzed single zebrafish embryos to demonstrate the method on a volume-limited biological sample. In comparison with SL-assisted CE-MS, twice as many molecular features were found, of which several could be identified. These results demonstrate the good potential of the MV interface for enhancing the coverage of the metabolome. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. The yeast metabolome addressed by electrospray ionization mass spectrometry: Initiation of a mass spectral library and its applications for metabolic footprinting by direct infusion mass spectrometry

    DEFF Research Database (Denmark)

    Højer-Pedersen, Jesper Juul; Smedsgaard, Jørn; Nielsen, Jens

    2008-01-01

    for ionization of microbial metabolites without any previous derivatization needed. To address the capabilities of ESI-MS in detecting the metabolome of Saccharomyces cerevisiae, the in silico metabolome of this organism was used as a template to present a theoretical metabolome. This showed that in combination...... into the ionization and fragmentation characteristics of the different metabolites. With this insight, a small study of metabolic footprinting with ESI-MS demonstrated that biological information can be extracted from footprinting spectra. Statistical analysis of the footprinting data revealed discriminating ions...

  9. Urinary Metabolomic Study of Chlorogenic Acid in a Rat Model of Chronic Sleep Deprivation Using Gas Chromatography-Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Wei-ni Ma

    2018-01-01

    Full Text Available The urinary metabolomic study based on gas chromatography-mass spectrometry (GC-MS had been developed to investigate the possible antidepressant mechanism of chlorogenic acid (CGA in a rat model of sleep deprivation (SD. According to pattern recognition analysis, there was a clear separation among big platform group (BP, sleep deprivation group (SD, and the CGA (model + CGA, and CGA group was much closer to the BP group by showing a tendency of recovering towards BP group. Thirty-six significantly changed metabolites related to antidepressant by CGA were identified and used to explore the potential mechanism. Combined with the result of the classic behavioral tests and biochemical indices, CGA has significant antidepressant effects in a rat model of SD, suggesting that the mechanism of action of CGA might be involved in regulating the abnormal pathway of nicotinate and nicotinamide metabolism; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and arginine and proline metabolism. Our results also show that metabolomics analysis based on GC-MS is a useful tool for exploring biomarkers involved in depression and elucidating the potential therapeutic mechanisms of Chinese medicine.

  10. Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Suzanne Miyamoto

    2015-04-01

    Full Text Available Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05. Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection.

  11. Comparative metabolomic analysis of Saccharomyces cerevisiae during the degradation of patulin using gas chromatography-mass spectrometry.

    Science.gov (United States)

    Shao, Suqin; Zhou, Ting; McGarvey, Brian D

    2012-05-01

    A comparative metabolomic analysis was conducted on Saccharomyces cerevisiae cells with and without patulin treatment using gas chromatography-mass spectrometry-based approach. A total of 72 metabolites were detected and compared, including 16 amino acids, 29 organic acids and alcohols, 19 sugars and sugar alcohols, 2 nucleotides, and 6 miscellaneous compounds. Principle component analysis showed a clear separation of metabolome between the cells with and without patulin treatment, and most of the identified metabolites contributed to the separation. A close examination of the identified metabolites showed an increased level of most of the free amino acids, an increased level of the intermediates in the tricarboxylic acid cycle, a higher amount of glycerol, a changed fatty acid composition, and a decreased level of cysteine and glutathione in the cells with patulin treatment. This finding indicated a slower protein synthesis rate and induced oxidative stress in the cells with patulin treatment, and provided new insights into the effect of toxic chemicals on the metabolism of organisms.

  12. Fluoroacetylation/fluoroethylesterification as a derivatization approach for gas chromatography-mass spectrometry in metabolomics: preliminary study of lymphohyperplastic diseases.

    Science.gov (United States)

    Karamani, Anna A; Fiamegos, Yiannis Ch; Vartholomatos, George; Stalikas, Constantine D

    2013-08-09

    Metabolic fingerprinting in combination with gas chromatography and multivariate analysis is being extensively employed for the improved understanding of biological changes induced by endogenous or exogenous factors. Chemical derivatization increases the sensitivity and specificity of gas chromatography-mass spectrometry (GC-MS) for polar or thermally labile biological compounds, which bear derivatizable groups. Thus, there is a constant demand for simple methods of derivatization and separation that satisfy the need for metabolite analysis, identifying as many chemical classes of compounds as possible. In this study, an optimized protocol of extraction and derivatization is established as a generally applicable method for the analysis of a wide range of classes of metabolites in urine, whole blood and saliva. Compounds of biological relevance bearing hydroxyl- carboxyl- and amino-groups are derivatized using single-step fluoroacetylation/fluoroethylesterification after proper optimization of the protocol. Subsequently, the developed derivatization procedure is engaged in finding blood metabolic biomarkers, induced by lymphohyperplastic disease, through the metabolomic fingerprinting approach, the multivariate modeling (hierarchical cluster analysis) and GC-MS. Our preliminary, GC-MS-based metabolomic fingerprinting study underlines the contribution of certain metabolites to the discrimination of patients with lymphohyperplastic diseases. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Inter-laboratory reproducibility of fast gas chromatography-electron impact-time of flight mass spectrometry (GC-EI-TOF/MS) based plant metabolomics

    NARCIS (Netherlands)

    Allwood, J.W.; Erban, A.; Koning, S.; Dun, W.B.; Luedemann, A.; Lommen, A.; Kay, L.; Löscher, R.; Kopka, J.; Goodacre, R.

    2009-01-01

    The application of gas chromatography¿mass spectrometry (GC¿MS) to the `global¿ analysis of metabolites in complex samples (i.e. metabolomics) has now become routine. The generation of these data-rich profiles demands new strategies in data mining and standardisation of experimental and reporting

  14. Intra- and inter-metabolite correlation spectroscopy of tomato metabolomics data obtained by liquid chromatography-mass spectrometry and nuclear magnetic resonance

    NARCIS (Netherlands)

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

    2008-01-01

    Nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LCMS) are frequently used as technological platforms for metabolomics applications. In this study, the metabolic profiles of ripe fruits from 50 different tomato cultivars, including beef, cherry and round types, were

  15. A real time metabolomic profiling approach to detecting fish fraud using rapid evaporative ionisation mass spectrometry.

    Science.gov (United States)

    Black, Connor; Chevallier, Olivier P; Haughey, Simon A; Balog, Julia; Stead, Sara; Pringle, Steven D; Riina, Maria V; Martucci, Francesca; Acutis, Pier L; Morris, Mike; Nikolopoulos, Dimitrios S; Takats, Zoltan; Elliott, Christopher T

    2017-01-01

    Fish fraud detection is mainly carried out using a genomic profiling approach requiring long and complex sample preparations and assay running times. Rapid evaporative ionisation mass spectrometry (REIMS) can circumvent these issues without sacrificing a loss in the quality of results. To demonstrate that REIMS can be used as a fast profiling technique capable of achieving accurate species identification without the need for any sample preparation. Additionally, we wanted to demonstrate that other aspects of fish fraud other than speciation are detectable using REIMS. 478 samples of five different white fish species were subjected to REIMS analysis using an electrosurgical knife. Each sample was cut 8-12 times with each one lasting 3-5 s and chemometric models were generated based on the mass range m/z 600-950 of each sample. The identification of 99 validation samples provided a 98.99% correct classification in which species identification was obtained near-instantaneously (≈ 2 s) unlike any other form of food fraud analysis. Significant time comparisons between REIMS and polymerase chain reaction (PCR) were observed when analysing 6 mislabelled samples demonstrating how REIMS can be used as a complimentary technique to detect fish fraud. Additionally, we have demonstrated that the catch method of fish products is capable of detection using REIMS, a concept never previously reported. REIMS has been proven to be an innovative technique to help aid the detection of fish fraud and has the potential to be utilised by fisheries to conduct their own quality control (QC) checks for fast accurate results.

  16. 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.

  17. Analysis of hydraulic fracturing flowback and produced waters using accurate mass: identification of ethoxylated surfactants.

    Science.gov (United States)

    Thurman, E Michael; Ferrer, Imma; Blotevogel, Jens; Borch, Thomas

    2014-10-07

    Two series of ethylene oxide (EO) surfactants, polyethylene glycols (PEGs from EO3 to EO33) and linear alkyl ethoxylates (LAEs C-9 to C-15 with EO3-EO28), were identified in hydraulic fracturing flowback and produced water using a new application of the Kendrick mass defect and liquid chromatography/quadrupole-time-of-flight mass spectrometry. The Kendrick mass defect differentiates the proton, ammonium, and sodium adducts in both singly and doubly charged forms. A structural model of adduct formation is presented, and binding constants are calculated, which is based on a spherical cagelike conformation, where the central cation (NH4(+) or Na(+)) is coordinated with ether oxygens. A major purpose of the study was the identification of the ethylene oxide (EO) surfactants and the construction of a database with accurate masses and retention times in order to unravel the mass spectral complexity of surfactant mixtures used in hydraulic fracturing fluids. For example, over 500 accurate mass assignments are made in a few seconds of computer time, which then is used as a fingerprint chromatogram of the water samples. This technique is applied to a series of flowback and produced water samples to illustrate the usefulness of ethoxylate "fingerprinting", in a first application to monitor water quality that results from fluids used in hydraulic fracturing.

  18. Pattern Recognition and Pathway Analysis with Genetic Algorithms in Mass Spectrometry Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Wei Zou

    2009-04-01

    Full Text Available A robust and complete workflow for metabolic profiling and data mining was described in detail. Three independent and complementary analytical techniques for metabolic profiling were applied: hydrophilic interaction chromatography (HILIC–LC–ESI–MS, reversed-phase liquid chromatography (RP–LC–ESI–MS, and gas chromatography (GC–TOF–MS all coupled to mass spectrometry (MS. Unsupervised methods, such as principle component analysis (PCA and clustering, and supervised methods, such as classification and PCA-DA (discriminatory analysis were used for data mining. Genetic Algorithms (GA, a multivariate approach, was probed for selection of the smallest subsets of potentially discriminative predictors. From thousands of peaks found in total, small subsets selected by GA were considered as highly potential predictors allowing discrimination among groups. It was found that small groups of potential top predictors selected with PCA-DA and GA are different and unique. Annotated GC–TOF–MS data generated identified feature metabolites. Metabolites putatively detected with LC–ESI–MS profiling require further elemental composition assignment with accurate mass measurement by Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS and structure elucidation by nuclear magnetic resonance spectroscopy (NMR. GA was also used to generate correlated networks for pathway analysis. Several case studies, comprising groups of plant samples bearing different genotypes and groups of samples of human origin, namely patients and healthy volunteers’ urine samples, demonstrated that such a workflow combining comprehensive metabolic profiling and advanced data mining techniques provides a powerful approach for pattern recognition and biomarker discovery

  19. Vitroprocines, new antibiotics against Acinetobacter baumannii, discovered from marine Vibrio sp. QWI-06 using mass-spectrometry-based metabolomics approach

    Science.gov (United States)

    Liaw, Chih-Chuang; Chen, Pei-Chin; Shih, Chao-Jen; Tseng, Sung-Pin; Lai, Ying-Mi; Hsu, Chi-Hsin; Dorrestein, Pieter C.; Yang, Yu-Liang

    2015-08-01

    A robust and convenient research strategy integrating state-of-the-art analytical techniques is needed to efficiently discover novel compounds from marine microbial resources. In this study, we identified a series of amino-polyketide derivatives, vitroprocines A-J, from the marine bacterium Vibrio sp. QWI-06 by an integrated approach using imaging mass spectroscopy and molecular networking, as well as conventional bioactivity-guided fractionation and isolation. The structure-activity relationship of vitroprocines against Acinetobacter baumannii is proposed. In addition, feeding experiments with 13C-labeled precursors indicated that a pyridoxal 5‧-phosphate-dependent mechanism is involved in the biosynthesis of vitroprocines. Elucidation of amino-polyketide derivatives from a species of marine bacteria for the first time demonstrates the potential of this integrated metabolomics approach to uncover marine bacterial biodiversity.

  20. Mass spectrometric metabolomic imaging of biofilms on corroding steel surfaces using laser ablation and solvent capture by aspiration.

    Science.gov (United States)

    Brauer, Jonathan I; Makama, Zakari; Bonifay, Vincent; Aydin, Egemen; Kaufman, Eric D; Beech, Iwona B; Sunner, Jan

    2015-03-02

    Ambient laser ablation and solvent capture by aspiration (LASCA) mass spectrometric imaging was combined with metabolomics high-performance liquid chromatography (HPLC) mass spectrometry analysis and light profilometry to investigate the correlation between chemical composition of marine bacterial biofilms on surfaces of 1018 carbon steel and corrosion damage of steel underneath the biofilms. Pure cultures of Marinobacter sp. or a wild population of bacteria present in coastal seawater served as sources of biofilms. Profilometry data of biofilm-free surfaces demonstrated heterogeneous distributions of corrosion damage. LASCA data were correlated with areas on the coupons varying in the level of corrosion attack, to reveal differences in chemical composition within biofilm regions associated with corroding and corrosion-free zones. Putative identification of selected compounds was carried out based on HPLC results and subsequent database searches. This is the first report of successful ambient chemical and metabolomic imaging of marine biofilms on corroding metallic materials. The metabolic analysis of such biofilms is challenging due to the presence in the biofilm of large amounts of corrosion products. However, by using the LASCA imaging interface, images of more than 1000 ions (potential metabolites) are generated, revealing striking heterogeneities within the biofilm. In the two model systems studied here, it is found that some of the patterns observed in selected ion images closely correlate with the occurrence and extent of corrosion in the carbon steel substrate as revealed by profilometry, while others do not. This approach toward the study of microbially influenced corrosion (MIC) holds great promise for approaching a fundamental understanding of the mechanisms involved in MIC.

  1. Accurate label-free protein quantitation with high- and low-resolution mass spectrometers.

    Science.gov (United States)

    Krey, Jocelyn F; Wilmarth, Phillip A; Shin, Jung-Bum; Klimek, John; Sherman, Nicholas E; Jeffery, Erin D; Choi, Dongseok; David, Larry L; Barr-Gillespie, Peter G

    2014-02-07

    Label-free quantitation of proteins analyzed by tandem mass spectrometry uses either integrated peak intensity from the parent-ion mass analysis (MS1) or features from fragment-ion analysis (MS2), such as spectral counts or summed fragment-ion intensity. We directly compared MS1 and MS2 quantitation by analyzing human protein standards diluted into Escherichia coli extracts on an Orbitrap mass spectrometer. We found that summed MS2 intensities were nearly as accurate as integrated MS1 intensities, and both outperformed MS2 spectral counting in accuracy and linearity. We compared these results to those obtained from two low-resolution ion-trap mass spectrometers; summed MS2 intensities from LTQ and LTQ Velos instruments were similar in accuracy to those from the Orbitrap. Data from all three instruments are available via ProteomeXchange with identifier PXD000602. Abundance measurements using MS1 or MS2 intensities had limitations, however. While measured protein concentration was on average well-correlated with the known concentration, there was considerable protein-to-protein variation. Moreover, not all human proteins diluted to a mole fraction of 10(-3) or lower were detected, with a strong falloff below 10(-4) mole fraction. These results show that MS1 and MS2 intensities are simple measures of protein abundance that are on average accurate but should be limited to quantitation of proteins of intermediate to higher fractional abundance.

  2. Untargeted metabolomic analysis using liquid chromatography quadrupole time-of-flight mass spectrometry for non-volatile profiling of wines

    Energy Technology Data Exchange (ETDEWEB)

    Arbulu, M. [Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain); Sampedro, M.C. [Central Service of Analysis, SGIker, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain); Gómez-Caballero, A.; Goicolea, M.A. [Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain); Barrio, R.J., E-mail: r.barrio@ehu.es [Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain)

    2015-02-09

    Highlights: • An untargeted metabolomic method for the non-volatile profile of the Graciano wine was developed. • 411 different metabolites in Graciano Vitis vinifera red wine were identified. • 15 compounds could serve to differentiate Graciano and Tempranillo wines. • An enological database (WinMet) with 2080 compounds was constructed. - Abstract: The current study presents a method for comprehensive untargeted metabolomic fingerprinting of the non-volatile profile of the Graciano Vitis vinifera wine variety, using liquid chromatography/electrospray ionization time of flight mass spectrometry (LC–ESI-QTOF). Pre-treatment of samples, chromatographic columns, mobile phases, elution gradients and ionization sources, were evaluated for the extraction of the maximum number of metabolites in red wine. Putative compounds were extracted from the raw data using the extraction algorithm, molecular feature extractor (MFE). For the metabolite identification the WinMet database was designed based on electronic databases and literature research and includes only the putative metabolites reported to be present in oenological matrices. The results from WinMet were compared with those in the METLIN database to evaluate how much the databases overlap for performing identifications. The reproducibility of the analysis was assessed using manual processing following replicate injections of Vitis vinifera cv. Graciano wine spiked with external standards. In the present work, 411 different metabolites in Graciano Vitis vinifera red wine were identified, including primary wine metabolites such as sugars (4%), amino acids (23%), biogenic amines (4%), fatty acids (2%), and organic acids (32%) and secondary metabolites such as phenols (27%) and esters (8%). Significant differences between varieties Tempranillo and Graciano were related to the presence of fifteen specific compounds.

  3. Semiquantitative dynamic contrast-enhanced MRI for accurate classification of complex adnexal masses.

    Science.gov (United States)

    Kazerooni, Anahita Fathi; Malek, Mahrooz; Haghighatkhah, Hamidreza; Parviz, Sara; Nabil, Mahnaz; Torbati, Leila; Assili, Sanam; Saligheh Rad, Hamidreza; Gity, Masoumeh

    2017-02-01

    To identify the best dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) descriptive parameters in predicting malignancy of complex ovarian masses, and develop an optimal decision tree for accurate classification of benign and malignant complex ovarian masses. Preoperative DCE-MR images of 55 sonographically indeterminate ovarian masses (27 benign and 28 malignant) were analyzed prospectively. Four descriptive parameters of the dynamic curve, namely, time-to-peak (TTP), wash-in-rate (WIR), relative signal intensity (SIrel ), and the initial area under the curve (IAUC60 ) were calculated on the normalized curves of specified regions-of-interest (ROIs). A two-tailed Student's t-test and two automated classifiers, linear discriminant analysis (LDA) and support vector machines (SVMs), were used to compare the performance of the mentioned parameters individually and in combination with each other. TTP (P = 6.15E-8) and WIR (P = 5.65E-5) parameters induced the highest sensitivity (89% for LDA, and 97% for SVM) and specificity (93% for LDA, and 100% for SVM), respectively. Regarding the high sensitivity of TTP and high specificity of WIR and through their combination, an accurate and simple decision-tree classifier was designed using the line equation obtained by LDA classification model. The proposed classifier achieved an accuracy of 89% and area under the ROC curve of 93%. In this study an accurate decision-tree classifier based on a combination of TTP and WIR parameters was proposed, which provides a clinically flexible framework to aid radiologists/clinicians to reach a conclusive preoperative diagnosis and patient-specific therapy plan for distinguishing malignant from benign complex ovarian masses. 2 J. Magn. Reson. Imaging 2017;45:418-427. © 2016 International Society for Magnetic Resonance in Medicine.

  4. Anthropometric measures are not accurate predictors of fat mass in ALS.

    Science.gov (United States)

    Ioannides, Zara A; Steyn, Frederik J; Henderson, Robert D; Mccombe, Pamela A; Ngo, Shyuan T

    2017-11-01

    Anthropometric measurements including body mass index (BMI) and body adiposity index (BAI) are widely employed as indicators of fat mass (FM). Metabolic abnormalities in amyotrophic lateral sclerosis (ALS) impact disease progression, therefore assessment of FM informs care. The aim of this study was to determine whether BMI and BAI are accurate predictors of FM in ALS. Methodology and main findings: BMI, BAI and percentage FM (determined by air displacement plethysmography; FM-ADP) were measured in control (n = 35) and ALS (n = 44) participants. While BMI and BAI correlated significantly with FM-ADP, neither index provided an accurate estimate of FM. In longitudinally assessed ALS participants (n = 29; ∼six-month repeat assessment interval), although a change in BMI (r 2  = 0.62 r = 0.79 p FM-ADP, the anthropometric measures did not consistently reflect increases or decreases observed in FM-ADP. Using FM-ADP as the standard, this study suggests that BMI and BAI are not accurate measures of FM in ALS. Furthermore, longitudinal assessments indicate that changes in BMI and BAI do not consistently reflect true changes of FM in ALS.

  5. The Brain Metabolome of Male Rats across the Lifespan.

    Science.gov (United States)

    Zheng, Xiaojiao; Chen, Tianlu; Zhao, Aihua; Wang, Xiaoyan; Xie, Guoxiang; Huang, Fengjie; Liu, Jiajian; Zhao, Qing; Wang, Shouli; Wang, Chongchong; Zhou, Mingmei; Panee, Jun; He, Zhigang; Jia, Wei

    2016-04-11

    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 amino acids accounted for the largest proportions of the brain metabolome, and their concentrations varied across the lifespan. The levels of polyunsaturated fatty acids were higher in infancy (week 1 to week 3) compared with later ages, and the ratio of omega-6 to omega-3 fatty acids increased in the aged brain (week 56 to week 111). Importantly, a panel of 20 bile acids were quantitatively measured, most of which have not previously been documented in the brain metabolome. This study extends the breadth of the mammalian brain metabolome as well as our knowledge of functional brain development, both of which are critically important to move the brain science forward.

  6. Development and Validation of a High-Throughput Mass Spectrometry Based Urine Metabolomic Test for the Detection of Colonic Adenomatous Polyps

    Directory of Open Access Journals (Sweden)

    Lu Deng

    2017-06-01

    Full Text Available Background: Colorectal cancer is one of the leading causes of cancer deaths worldwide. The detection and removal of the precursors to colorectal cancer, adenomatous polyps, is the key for screening. The aim of this study was to develop a clinically scalable (high throughput, low cost, and high sensitivity mass spectrometry (MS-based urine metabolomic test for the detection of adenomatous polyps. Methods: Prospective urine and stool samples were collected from 685 participants enrolled in a colorectal cancer screening program to undergo colonoscopy examination. Statistical analysis was performed on 69 urine metabolites measured by one-dimensional nuclear magnetic resonance spectroscopy to identify key metabolites. A targeted MS assay was then developed to quantify the key metabolites in urine. A MS-based urine metabolomic diagnostic test for adenomatous polyps was established using 67% samples (un-blinded training set and validated using the remaining 33% samples (blinded testing set. Results: The MS-based urine metabolomic test identifies patients with colonic adenomatous polyps with an AUC of 0.692, outperforming the NMR based predictor with an AUC of 0.670. Conclusion: Here we describe a clinically scalable MS-based urine metabolomic test that identifies patients with adenomatous polyps at a higher level of sensitivity (86% over current fecal-based tests (<18%.

  7. Optimization study for metabolomics analysis of human sweat by liquid chromatography-tandem mass spectrometry in high resolution mode.

    Science.gov (United States)

    Calderón-Santiago, M; Priego-Capote, F; Jurado-Gámez, B; Luque de Castro, M D

    2014-03-14

    Sweat has recently gained popularity as a potential tool for diagnostics and biomarker monitoring as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis, which increases chloride levels in sweat. The aim of the present study was to develop an analytical method for analysis of human sweat by liquid chromatography-mass spectrometry (LC-Q-TOF MS/MS) in high resolution mode. Thus, different sample preparation strategies and different chromatographic modes (HILIC and C18 reverse modes) were compared to check their effect on the profile of sweat metabolites. Forty-one compounds were identified by the MS/MS information obtained with a mass tolerance window below 4 ppm. Amino acids, dicarboxylic acids and other interesting metabolites such as inosine, choline, uric acid and tyramine were identified. Among the tested protocols, direct analysis after dilution was a suited option to obtain a representative snapshot of sweat metabolome. In addition, sample clean up by C18 SpinColumn SPE cartridges improved the sensitivity of most identified compounds and reduced the number of interferents. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Body mass index continues to accurately predict percent body fat as women age despite changes in muscle mass and height.

    Science.gov (United States)

    Ablove, Tova; Binkley, Neil; Leadley, Sarah; Shelton, James; Ablove, Robert

    2015-07-01

    Body mass index (BMI) is commonly used to predict obesity in clinical practice because it is suggested to closely correlate with percent body fat (%BF). With aging, women lose both lean mass and height. Because of this, many clinicians question whether BMI is an accurate predictor of obesity in aging women. In evaluating the equation for BMI (weight/height(2)), it is clear that both variables can have a dramatic effect on BMI calculation. We evaluated the relationship between BMI and %BF, as measured by dual-energy x-ray absorptiometry, in the setting of age-related changes in height loss and body composition in women. Our objective is to determine whether BMI continues to correlate with %BF as women age. Study participants were identified using data from five osteoporosis clinical trials, where healthy participants had full-body dual-energy x-ray absorptiometry scans. Deidentified data from 274 women aged between 35 and 95 years were evaluated. %BF, weight, age, tallest height, actual height, and appendicular lean mass were collected from all participants. BMI was calculated using the actual height and the tallest height of each study participant. %BF was compared with BMI and stratified for age. BMI calculated using the tallest height and BMI calculated using actual height both had strong correlations with %BF. Surprisingly, the effects of changes in height and lean body mass balance each other out in BMI calculation. There continues to be a strong correlation between BMI and %BF in adult women as they age.

  9. 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.

  10. Chemical Derivatization and Ultrahigh Resolution and Accurate Mass Spectrometry Strategies for "Shotgun" Lipidome Analysis.

    Science.gov (United States)

    Ryan, Eileen; Reid, Gavin E

    2016-09-20

    Lipids play critical structural and functional roles in the regulation of cellular homeostasis, and it is increasingly recognized that the disruption of lipid metabolism or signaling or both is associated with the onset and progression of certain metabolically linked diseases. As a result, the field of lipidomics has emerged to comprehensively identify and structurally characterize the diverse range of lipid species within a sample of interest and to quantitatively monitor their abundances under different physiological or pathological conditions. Mass spectrometry (MS) has become a critical enabling platform technology for lipidomic researchers. However, the presence of isobaric (i.e., same nominal mass) and isomeric (i.e., same exact mass) lipids within complex lipid extracts means that MS-based identification and quantification of individual lipid species remains a significant analytical challenge. Ultrahigh resolution and accurate mass spectrometry (UHRAMS) offers a convenient solution to the isobaric mass overlap problem, while a range of chromatographic separation, differential extraction, intrasource separation and selective ionization methods, or tandem mass spectrometry (MS/MS) strategies may be used to address some types of isomeric mass lipid overlaps. Alternatively, chemical derivatization strategies represent a more recent approach for the separation of lipids within complex mixtures, including for isomeric lipids. In this Account, we highlight the key components of a lipidomics workflow developed in our laboratory, whereby certain lipid classes or subclasses, namely, aminophospholipids and O-alk-1'-enyl (i.e., plasmalogen) ether-containing lipids, are shifted in mass following sequential functional group selective chemical derivatization reactions prior to "shotgun" nano-ESI-UHRAMS analysis, "targeted" MS/MS, and automated database searching. This combined derivatization and UHRAMS approach resolves both isobaric mass lipids and certain categories of

  11. Cluster abundance in chameleon f(R) gravity I: toward an accurate halo mass function prediction

    Science.gov (United States)

    Cataneo, Matteo; Rapetti, David; Lombriser, Lucas; Li, Baojiu

    2016-12-01

    We refine the mass and environment dependent spherical collapse model of chameleon f(R) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f(R) halo abundance with respect to that of General Relativity (GR) within a precision of lesssim 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f(R) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.

  12. Oxidized fatty acid analysis by charge-switch derivatization, selected reaction monitoring, and accurate mass quantitation.

    Science.gov (United States)

    Liu, Xinping; Moon, Sung Ho; Mancuso, David J; Jenkins, Christopher M; Guan, Shaoping; Sims, Harold F; Gross, Richard W

    2013-11-01

    A highly sensitive, specific, and robust method for the analysis of oxidized metabolites of linoleic acid (LA), arachidonic acid (AA), and docosahexaenoic acid (DHA) was developed using charge-switch derivatization, liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI MS/MS) with selected reaction monitoring (SRM) and quantitation by high mass accuracy analysis of product ions, thereby minimizing interferences from contaminating ions. Charge-switch derivatization of LA, AA, and DHA metabolites with N-(4-aminomethylphenyl)-pyridinium resulted in a 10- to 30-fold increase in ionization efficiency. Improved quantitation was accompanied by decreased false positive interferences through accurate mass measurements of diagnostic product ions during SRM transitions by ratiometric comparisons with stable isotope internal standards. The limits of quantitation were between 0.05 and 6.0pg, with a dynamic range of 3 to 4 orders of magnitude (correlation coefficient r(2)>0.99). This approach was used to quantitate the levels of representative fatty acid metabolites from wild-type (WT) and iPLA2γ(-/-) mouse liver identifying the role of iPLA2γ in hepatic lipid second messenger production. Collectively, these results demonstrate the utility of high mass accuracy product ion analysis in conjunction with charge-switch derivatization for the highly specific quantitation of diminutive amounts of LA, AA, and DHA metabolites in biologic systems. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. 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

  14. Compound identification in gas chromatography/mass spectrometry-based metabolomics by blind source separation.

    Science.gov (United States)

    Domingo-Almenara, Xavier; Perera, Alexandre; Ramírez, Noelia; Cañellas, Nicolau; Correig, Xavier; Brezmes, Jesus

    2015-08-28

    Metabolomics GC-MS samples involve high complexity data that must be effectively resolved to produce chemically meaningful results. Multivariate curve resolution-alternating least squares (MCR-ALS) is the most frequently reported technique for that purpose. More recently, independent component analysis (ICA) has been reported as an alternative to MCR. Those algorithms attempt to infer a model describing the observed data and, therefore, the least squares regression used in MCR assumes that the data is a linear combination of that model. However, due to the high complexity of real data, the construction of a model to describe optimally the observed data is a critical step and these algorithms should prevent the influence from outlier data. This study proves independent component regression (ICR) as an alternative for GC-MS compound identification. Both ICR and MCR though require least squares regression to correctly resolve the mixtures. In this paper, a novel orthogonal signal deconvolution (OSD) approach is introduced, which uses principal component analysis to determine the compound spectra. The study includes a compound identification comparison between the results by ICA-OSD, MCR-OSD, ICR and MCR-ALS using pure standards and human serum samples. Results shows that ICR may be used as an alternative to multivariate curve methods, as ICR efficiency is comparable to MCR-ALS. Also, the study demonstrates that the proposed OSD approach achieves greater spectral resolution accuracy than the traditional least squares approach when compounds elute under undue interference of biological matrices. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. 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.

  16. Comparison of Ambient and Atmospheric Pressure Ion Sources for Cystic Fibrosis Exhaled Breath Condensate Ion Mobility-Mass Spectrometry Metabolomics

    Science.gov (United States)

    Zang, Xiaoling; Pérez, José J.; Jones, Christina M.; Monge, María Eugenia; McCarty, Nael A.; Stecenko, Arlene A.; Fernández, Facundo M.

    2017-08-01

    Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the gene that encodes the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The vast majority of the mortality is due to progressive lung disease. Targeted and untargeted CF breath metabolomics investigations via exhaled breath condensate (EBC) analyses have the potential to expose metabolic alterations associated with CF pathology and aid in assessing the effectiveness of CF therapies. Here, transmission-mode direct analysis in real time traveling wave ion mobility spectrometry time-of-flight mass spectrometry (TM-DART-TWIMS-TOF MS) was tested as a high-throughput alternative to conventional direct infusion (DI) electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) methods, and a critical comparison of the three ionization methods was conducted. EBC was chosen as the noninvasive surrogate for airway sampling over expectorated sputum as EBC can be collected in all CF subjects regardless of age and lung disease severity. When using pooled EBC collected from a healthy control, ESI detected the most metabolites, APCI a log order less, and TM-DART the least. TM-DART-TWIMS-TOF MS was used to profile metabolites in EBC samples from five healthy controls and four CF patients, finding that a panel of three discriminant EBC metabolites, some of which had been previously detected by other methods, differentiated these two classes with excellent cross-validated accuracy.

  17. Model-based peak alignment of metabolomic profiling from comprehensive two-dimensional gas chromatography mass spectrometry.

    Science.gov (United States)

    Jeong, Jaesik; Shi, Xue; Zhang, Xiang; Kim, Seongho; Shen, Changyu

    2012-02-08

    Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS) has been used for metabolite profiling in metabolomics. However, there is still much experimental variation to be controlled including both within-experiment and between-experiment variation. For efficient analysis, an ideal peak alignment method to deal with such variations is in great need. Using experimental data of a mixture of metabolite standards, we demonstrated that our method has better performance than other existing method which is not model-based. We then applied our method to the data generated from the plasma of a rat, which also demonstrates good performance of our model. We developed a model-based peak alignment method to process both homogeneous and heterogeneous experimental data. The unique feature of our method is the only model-based peak alignment method coupled with metabolite identification in an unified framework. Through the comparison with other existing method, we demonstrated that our method has better performance. Data are available at http://stage.louisville.edu/faculty/x0zhan17/software/software-development/mspa. The R source codes are available at http://www.biostat.iupui.edu/~ChangyuShen/CodesPeakAlignment.zip. 2136949528613691.

  18. Model-based peak alignment of metabolomic profiling from comprehensive two-dimensional gas chromatography mass spectrometry

    Directory of Open Access Journals (Sweden)

    Jeong Jaesik

    2012-02-01

    Full Text Available Abstract Background Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS has been used for metabolite profiling in metabolomics. However, there is still much experimental variation to be controlled including both within-experiment and between-experiment variation. For efficient analysis, an ideal peak alignment method to deal with such variations is in great need. Results Using experimental data of a mixture of metabolite standards, we demonstrated that our method has better performance than other existing method which is not model-based. We then applied our method to the data generated from the plasma of a rat, which also demonstrates good performance of our model. Conclusions We developed a model-based peak alignment method to process both homogeneous and heterogeneous experimental data. The unique feature of our method is the only model-based peak alignment method coupled with metabolite identification in an unified framework. Through the comparison with other existing method, we demonstrated that our method has better performance. Data are available at http://stage.louisville.edu/faculty/x0zhan17/software/software-development/mspa. The R source codes are available at http://www.biostat.iupui.edu/~ChangyuShen/CodesPeakAlignment.zip. Trial Registration 2136949528613691

  19. Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery.

    Science.gov (United States)

    Zhang, Tong; Watson, David G; Wang, Lijie; Abbas, Muhammad; Murdoch, Laura; Bashford, Lisa; Ahmad, Imran; Lam, Nga-Yee; Ng, Anthony C F; Leung, Hing Y

    2013-01-01

    Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (Pprotocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.

  20. Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Tong Zhang

    Full Text Available Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS in combination with orthogonal Hydrophilic Interaction (HILIC and Reversed Phase (RP liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition. The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC test, the area under curve (AUC for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (P<0.05 between an independent patient cohort and controls. This is the first time such a rigorous test has been applied to this type of model. If validated, the established protocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.

  1. A plasma metabolomic signature discloses human breast cancer.

    Science.gov (United States)

    Jové, Mariona; Collado, Ricardo; Quiles, José Luís; Ramírez-Tortosa, Mari-Carmen; Sol, Joaquim; Ruiz-Sanjuan, Maria; Fernandez, Mónica; de la Torre Cabrera, Capilla; Ramírez-Tortosa, Cesar; Granados-Principal, Sergio; Sánchez-Rovira, Pedro; Pamplona, Reinald

    2017-03-21

    Metabolomics is the comprehensive global study of metabolites in biological samples. In this retrospective pilot study we explored whether serum metabolomic profile can discriminate the presence of human breast cancer irrespective of the cancer subtype. Plasma samples were analyzed from healthy women (n = 20) and patients with breast cancer after diagnosis (n = 91) using a liquid chromatography-mass spectrometry platform. Multivariate statistics and a Random Forest (RF) classifier were used to create a metabolomics panel for the diagnosis of human breast cancer. Metabolomics correctly distinguished between breast cancer patients and healthy control subjects. In the RF supervised class prediction analysis comparing breast cancer and healthy control groups, RF accurately classified 100% both samples of the breast cancer patients and healthy controls. So, the class error for both group in and the out-of-bag error were 0. We also found 1269 metabolites with different concentration in plasma from healthy controls and cancer patients; and basing on exact mass, retention time and isotopic distribution we identified 35 metabolites. These metabolites mostly support cell growth by providing energy and building stones for the synthesis of essential biomolecules, and function as signal transduction molecules. The collective results of RF, significance testing, and false discovery rate analysis identified several metabolites that were strongly associated with breast cancer. In breast cancer a metabolomics signature of cancer exists and can be detected in patient plasma irrespectively of the breast cancer type.

  2. 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.

  3. Liquid Chromatography–Mass Spectrometry Based Metabolomics Study of Cloned versus Normal Pigs Fed Either Restricted or Ad Libitum High-Energy Diets

    DEFF Research Database (Denmark)

    Christensen, Kirstine Lykke; Hedemann, Mette Skou; Jørgensen, Henry

    2012-01-01

    manner (60% of ad libitum) for 6 months, and plasma was subjected to liquid chromatography–mass spectrometry nontargeted metabolomics and biochemical analyses. Low systemic levels of IGF-1 could indicate altered growth conditions and energy metabolism in cloned pigs. In response to ad libitum feeding...... of the metabolome of cloned pigs compared to normal control pigs was performed to elucidate the variation and possible differences in the metabolic phenotypes during a dietary intervention. A total of 19 control pigs and 17 cloned pigs were given the same high-energy dense diet either ad libitum or in a restricted......, clones had a decreased energy intake and lower weight gain compared to controls, and plasma lipid profiles were changed accordingly. Elevated lactate and decreased creatine levels implied an increased anaerobic metabolism in ad libitum fed clones. Less interindividual variation between cloned pigs...

  4. Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

    Science.gov (United States)

    Bean, Heather D.; Hill, Jane E.; Dimandja, Jean-Marie D.

    2015-01-01

    The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly- resolved peaks, especially those at the extremes of the detector linear range, and no influence on well- chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. PMID:25857541

  5. In-depth glycoproteomic characterization of γ-conglutin by high-resolution accurate mass spectrometry.

    Directory of Open Access Journals (Sweden)

    Silvia Schiarea

    Full Text Available The molecular characterization of bioactive food components is necessary for understanding the mechanisms of their beneficial or detrimental effects on human health. This study focused on γ-conglutin, a well-known lupin seed N-glycoprotein with health-promoting properties and controversial allergenic potential. Given the importance of N-glycosylation for the functional and structural characteristics of proteins, we studied the purified protein by a mass spectrometry-based glycoproteomic approach able to identify the structure, micro-heterogeneity and attachment site of the bound N-glycan(s, and to provide extensive coverage of the protein sequence. The peptide/N-glycopeptide mixtures generated by enzymatic digestion (with or without N-deglycosylation were analyzed by high-resolution accurate mass liquid chromatography-multi-stage mass spectrometry. The four main micro-heterogeneous variants of the single N-glycan bound to γ-conglutin were identified as Man2(Xyl (Fuc GlcNAc2, Man3(Xyl (Fuc GlcNAc2, GlcNAcMan3(Xyl (Fuc GlcNAc2 and GlcNAc 2Man3(Xyl (Fuc GlcNAc2. These carry both core β1,2-xylose and core α1-3-fucose (well known Cross-Reactive Carbohydrate Determinants, but corresponding fucose-free variants were also identified as minor components. The N-glycan was proven to reside on Asn131, one of the two potential N-glycosylation sites. The extensive coverage of the γ-conglutin amino acid sequence suggested three alternative N-termini of the small subunit, that were later confirmed by direct-infusion Orbitrap mass spectrometry analysis of the intact subunit.

  6. Empirical Accurate Masses and Radii of Single Stars with TESS and Gaia

    Science.gov (United States)

    Stassun, Keivan G.; Corsaro, Enrico; Pepper, Joshua A.; Gaudi, B. Scott

    2018-01-01

    We present a methodology for the determination of empirical masses of single stars through the combination of three direct observables with Gaia and Transiting Exoplanet Survey Satellite (TESS): (i) the surface gravity via granulation-driven variations in the TESS light curve, (ii) the bolometric flux at Earth via the broadband spectral energy distribution, and (iii) the distance via the Gaia parallax. We demonstrate the method using 525 Kepler stars for which these measures are available in the literature, and show that the stellar masses can be measured with this method to a precision of ∼25%, limited by the surface-gravity precision of the granulation “flicker” method (∼0.1 dex) and by the parallax uncertainties (∼10% for the Kepler sample). We explore the impact of expected improvements in the surface gravity determinations—through the application of granulation background fitting and the use of recently published granulation-metallicity relations—and improvements in the parallaxes with the arrival of the Gaia second data release. We show that the application of this methodology to stars that will be observed by TESS should yield radii good to a few percent and masses good to ≈10%. Importantly, the method does not require the presence of an orbiting, eclipsing, or transiting body, nor does it require spatial resolution of the stellar surface. Thus, we can anticipate the determination of fundamental, accurate stellar radii and masses for hundreds of thousands of bright single stars—across the entire sky and spanning the Hertzsprung–Russell diagram—including those that will ultimately be found to host planets.

  7. 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.

  8. SPARC: MASS MODELS FOR 175 DISK GALAXIES WITH SPITZER PHOTOMETRY AND ACCURATE ROTATION CURVES

    Energy Technology Data Exchange (ETDEWEB)

    Lelli, Federico; McGaugh, Stacy S. [Department of Astronomy, Case Western Reserve University, Cleveland, OH 44106 (United States); Schombert, James M., E-mail: federico.lelli@case.edu [Department of Physics, University of Oregon, Eugene, OR 97403 (United States)

    2016-12-01

    We introduce SPARC ( Spitzer Photometry and Accurate Rotation Curves): a sample of 175 nearby galaxies with new surface photometry at 3.6  μ m and high-quality rotation curves from previous H i/H α studies. SPARC spans a broad range of morphologies (S0 to Irr), luminosities (∼5 dex), and surface brightnesses (∼4 dex). We derive [3.6] surface photometry and study structural relations of stellar and gas disks. We find that both the stellar mass–H i mass relation and the stellar radius–H i radius relation have significant intrinsic scatter, while the H i   mass–radius relation is extremely tight. We build detailed mass models and quantify the ratio of baryonic to observed velocity ( V {sub bar}/ V {sub obs}) for different characteristic radii and values of the stellar mass-to-light ratio (ϒ{sub ⋆}) at [3.6]. Assuming ϒ{sub ⋆} ≃ 0.5 M {sub ⊙}/ L {sub ⊙} (as suggested by stellar population models), we find that (i) the gas fraction linearly correlates with total luminosity; (ii) the transition from star-dominated to gas-dominated galaxies roughly corresponds to the transition from spiral galaxies to dwarf irregulars, in line with density wave theory; and (iii)  V {sub bar}/ V {sub obs} varies with luminosity and surface brightness: high-mass, high-surface-brightness galaxies are nearly maximal, while low-mass, low-surface-brightness galaxies are submaximal. These basic properties are lost for low values of ϒ{sub ⋆} ≃ 0.2 M {sub ⊙}/ L {sub ⊙} as suggested by the DiskMass survey. The mean maximum-disk limit in bright galaxies is ϒ{sub ⋆} ≃ 0.7 M {sub ⊙}/ L {sub ⊙} at [3.6]. The SPARC data are publicly available and represent an ideal test bed for models of galaxy formation.

  9. Exo-metabolome of Pseudovibrio sp. FO-BEG1 analyzed by ultra-high resolution mass spectrometry and the effect of phosphate limitation.

    Directory of Open Access Journals (Sweden)

    Stefano Romano

    Full Text Available Oceanic dissolved organic matter (DOM is an assemblage of reduced carbon compounds, which results from biotic and abiotic processes. The biotic processes consist in either release or uptake of specific molecules by marine organisms. Heterotrophic bacteria have been mostly considered to influence the DOM composition by preferential uptake of certain compounds. However, they also secrete a variety of molecules depending on physiological state, environmental and growth conditions, but so far the full set of compounds secreted by these bacteria has never been investigated. In this study, we analyzed the exo-metabolome, metabolites secreted into the environment, of the heterotrophic marine bacterium Pseudovibrio sp. FO-BEG1 via ultra-high resolution mass spectrometry, comparing phosphate limited with phosphate surplus growth conditions. Bacteria belonging to the Pseudovibrio genus have been isolated worldwide, mainly from marine invertebrates and were described as metabolically versatile Alphaproteobacteria. We show that the exo-metabolome is unexpectedly large and diverse, consisting of hundreds of compounds that differ by their molecular formulae. It is characterized by a dynamic recycling of molecules, and it is drastically affected by the physiological state of the strain. Moreover, we show that phosphate limitation greatly influences both the amount and the composition of the secreted molecules. By assigning the detected masses to general chemical categories, we observed that under phosphate surplus conditions the secreted molecules were mainly peptides and highly unsaturated compounds. In contrast, under phosphate limitation the composition of the exo-metabolome changed during bacterial growth, showing an increase in highly unsaturated, phenolic, and polyphenolic compounds. Finally, we annotated the detected masses using multiple metabolite databases. These analyses suggested the presence of several masses analogue to masses of known bioactive

  10. Proteomics, lipidomics, metabolomics: a mass spectrometry tutorial from a computer scientist's point of view

    Science.gov (United States)

    2014-01-01

    Background For decades, mass spectrometry data has been analyzed to investigate a wide array of research interests, including disease diagnostics, biological and chemical theory, genomics, and drug development. Progress towards solving any of these disparate problems depends upon overcoming the common challenge of interpreting the large data sets generated. Despite interim successes, many data interpretation problems in mass spectrometry are still challenging. Further, though these challenges are inherently interdisciplinary in nature, the significant domain-specific knowledge gap between disciplines makes interdisciplinary contributions difficult. Results This paper provides an introduction to the burgeoning field of computational mass spectrometry. We illustrate key concepts, vocabulary, and open problems in MS-omics, as well as provide invaluable resources such as open data sets and key search terms and references. Conclusions This paper will facilitate contributions from mathematicians, computer scientists, and statisticians to MS-omics that will fundamentally improve results over existing approaches and inform novel algorithmic solutions to open problems. PMID:25078324

  11. ISOLTRAP: a tandem Penning trap system for accurate on-line mass determination of short-lived isotopes

    Science.gov (United States)

    Bollen, G.; Becker, S.; Kluge, H.-J.; König, M.; Moore, R. B.; Otto, T.; Raimbault-Hartmann, H.; Savard, G.; Schweikhard, L.; Stolzenberg, H.; Isolde Collaboration

    1996-02-01

    The tandem Penning trap mass spectrometer ISOLTRAP has been set up at the on-line mass separator ISOLDE at CERN/Geneva for accurate mass measurements of short-lived nuclei with T {1}/{2} ≥ 1 s. The mass measurement is performed via the determination of the cyclotron frequency of an ion in a magnetic field. The design of the spectrometer matches the particular requirements for on-line mass measurements on short-lived isotopes. With the ISOLTRAP spectrometer masses of more than 70 radioactive nuclei have so far been determined with resolving powers exceeding one million and an accuracy of typically 10 -7.

  12. ISOLTRAP: a tandem Penning trap system for accurate on-line mass determination of short-lived isotopes

    Energy Technology Data Exchange (ETDEWEB)

    Bollen, G. [Gesellschaft fuer Schwerionenforschung mbH, Darmstadt (Germany); Becker, S. [Mainz Univ. (Germany). Inst. fuer Physik; Kluge, H.J. [Gesellschaft fuer Schwerionenforschung mbH, Darmstadt (Germany); Koenig, M. [Gesellschaft fuer Schwerionenforschung mbH, Darmstadt (Germany); Moore, R.B. [McGill Univ., Montreal, PQ (Canada). Foster Radiation Lab.; Otto, T. [Mainz Univ. (Germany). Inst. fuer Physik; Raimbault-Hartmann, H. [Mainz Univ. (Germany). Inst. fuer Physik; Savard, G. [Mainz Univ. (Germany). Inst. fuer Physik; Schweikhard, L. [Mainz Univ. (Germany). Inst. fuer Physik; Stolzenberg, H. [Mainz Univ. (Germany). Inst. fuer Physik; ISOLDE Collaboration

    1996-01-11

    The tandem Penning trap mass spectrometer ISOLTRAP has been set up at the on-line mass separator ISOLDE at CERN/Geneva for accurate mass measurements of short-lived nuclei with T{sub 1/2} {>=}1 s. The mass measurement is performed via the determination of the cyclotron frequency of an ion in a magnetic field. The design of the spectrometer matches the particular requirements for on-line mass measurements on short-lived isotopes. With the ISOLTRAP spectrometer masses of more than 70 radioactive nuclei have so far been determined with resolving powers exceeding one million and an accuracy of typically 10{sup -7}. (orig.).

  13. Development of a method for enhancing metabolomics coverage of human sweat by gas chromatography-mass spectrometry in high resolution mode.

    Science.gov (United States)

    Delgado-Povedano, M M; Calderón-Santiago, M; Priego-Capote, F; Luque de Castro, M D

    2016-01-28

    Sweat has recently gained popularity as clinical sample in metabolomics analysis as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis that increases chloride levels in sweat. However, the whole composition of sweat is still unknown and there is a lack of analytical strategies for sweat analysis. The aim of the present study was to develop and validate a method for metabolomic analysis of human sweat by gas chromatography-time of flight/mass spectrometry (GC-TOF/MS) in high resolution mode. Thus, different sample preparation strategies were compared to check their effect on the profile of sweat metabolites. Sixty-six compounds were tentatively identified by the obtained MS information. Amino acids, dicarboxylic acids and other interesting metabolites such as myo-inositol and urocanic acid were identified. Among the tested protocols, methyoxiamination plus silylation after deproteinization was the most suited option to obtain a representative snapshot of sweat metabolome. The intra-day repeatability of the method ranged from 0.60 to 16.99% and the inter-day repeatability from 2.75 to 31.25%. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Enhancing the power of liquid chromatography-mass spectrometry-based urine metabolomics in negative ion mode by optimization of the additive.

    Science.gov (United States)

    Zhang, Xumin; Clausen, Morten Rahr; Zhao, Xiaolu; Zheng, Hong; Bertram, Hanne Christine

    2012-09-18

    Untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics studies are usually carried out in both positive and negative ion modes; however, it is frequently ignored that the optimal conditions in positive ion mode and negative ion mode are often not the same. We carried out a systematic investigation on urine samples to evaluate the additive effects in negative ion mode. It was found that the widely used conditions, 0.1% formic acid (FA) and NH(4)Ac at different pH, are far from the optimum for untargeted urine metabolomics studies. Compared to 0.1% FA, the use of 1 mM acetic acid (HAc) resulted in almost three times as many detected peaks (401 vs 148) and around five times the size of the peak area (33.55 × 10(6) vs 6.47 × 10(6)). The remarkable improvement can be explained by two factors: (i) a significantly enhanced ionization efficiency due to the combination of an appropriate pH at around 4.0-4.5, the reducibility of H(+), and the high gas-phase basicity of Ac(-) and (ii) a reproducible LC separation due to an acceptable buffering capacity. Our study revealed the importance and necessity of additive optimization, which can be of benefit in related metabolomics studies.

  15. Ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry MSE-based untargeted milk metabolomics in dairy cows with subclinical or clinical mastitis.

    Science.gov (United States)

    Xi, Xiaomin; Kwok, Lai-Yu; Wang, Yuenan; Ma, Chen; Mi, Zhihui; Zhang, Heping

    2017-06-01

    In this study, a novel metabolomics technique based on ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry in the MS E mode was used to investigate the milk metabolomics of healthy, subclinical, and clinical mastitis cows, which were classified based on somatic cell count and presentation of clinical symptoms. Meanwhile, univariate and multivariate statistical analyses were performed to identify the significant differences across the 3 groups. Compared with healthy milk samples, less glucose, d-glycerol-1-phosphate, 4-hydroxyphenyllactate, l-carnitine, sn-glycero-3-phosphocholine, citrate, and hippurate were detected in the clinical mastitic milk samples, whereas less d-glycerol-1-phosphate, benzoic acid, l-carnitine, and cis-aconitate were found in the subclinical mastitic milk samples. Meanwhile, the milk concentration of arginine and Leu-Leu increased in both the clinical and subclinical mastitis groups. Besides, less 4-hydroxyphenyllactate, cis-aconitate, lactose, and oxoglutarate were detected in the clinical than the subclinical mastitic milk samples, whereas the abundance of some oligopeptides (Leu-Ala, Phe-Pro-Ile, Asn-Arg-Ala-Ile, and Val-Phe-Val-Tyr) increased by over 7.95-fold. Our results suggest that significant variations exist across healthy and mastitis cows. The current metabolomics approach will help in better understanding the pathobiology of mastitis, although clinical validation will be required before field application. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  16. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics for comparison of caffeinated and decaffeinated coffee and its implications for Alzheimer's disease.

    Science.gov (United States)

    Chang, Kai Lun; Ho, Paul C

    2014-01-01

    Findings from epidemiology, preclinical and clinical studies indicate that consumption of coffee could have beneficial effects against dementia and Alzheimer's disease (AD). The benefits appear to come from caffeinated coffee, but not decaffeinated coffee or pure caffeine itself. Therefore, the objective of this study was to use metabolomics approach to delineate the discriminant metabolites between caffeinated and decaffeinated coffee, which could have contributed to the observed therapeutic benefits. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics approach was employed to characterize the metabolic differences between caffeinated and decaffeinated coffee. Orthogonal partial least squares discriminant analysis (OPLS-DA) showed distinct separation between the two types of coffee (cumulative Q(2) = 0.998). A total of 69 discriminant metabolites were identified based on the OPLS-DA model, with 37 and 32 metabolites detected to be higher in caffeinated and decaffeinated coffee, respectively. These metabolites include several benzoate and cinnamate-derived phenolic compounds, organic acids, sugar, fatty acids, and amino acids. Our study successfully established GC-TOF-MS based metabolomics approach as a highly robust tool in discriminant analysis between caffeinated and decaffeinated coffee samples. Discriminant metabolites identified in this study are biologically relevant and provide valuable insights into therapeutic research of coffee against AD. Our data also hint at possible involvement of gut microbial metabolism to enhance therapeutic potential of coffee components, which represents an interesting area for future research.

  17. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS-based metabolomics for comparison of caffeinated and decaffeinated coffee and its implications for Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Kai Lun Chang

    Full Text Available Findings from epidemiology, preclinical and clinical studies indicate that consumption of coffee could have beneficial effects against dementia and Alzheimer's disease (AD. The benefits appear to come from caffeinated coffee, but not decaffeinated coffee or pure caffeine itself. Therefore, the objective of this study was to use metabolomics approach to delineate the discriminant metabolites between caffeinated and decaffeinated coffee, which could have contributed to the observed therapeutic benefits. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS-based metabolomics approach was employed to characterize the metabolic differences between caffeinated and decaffeinated coffee. Orthogonal partial least squares discriminant analysis (OPLS-DA showed distinct separation between the two types of coffee (cumulative Q(2 = 0.998. A total of 69 discriminant metabolites were identified based on the OPLS-DA model, with 37 and 32 metabolites detected to be higher in caffeinated and decaffeinated coffee, respectively. These metabolites include several benzoate and cinnamate-derived phenolic compounds, organic acids, sugar, fatty acids, and amino acids. Our study successfully established GC-TOF-MS based metabolomics approach as a highly robust tool in discriminant analysis between caffeinated and decaffeinated coffee samples. Discriminant metabolites identified in this study are biologically relevant and provide valuable insights into therapeutic research of coffee against AD. Our data also hint at possible involvement of gut microbial metabolism to enhance therapeutic potential of coffee components, which represents an interesting area for future research.

  18. Gas chromatography-mass spectrometry based metabolomic approach for optimization and toxicity evaluation of earthworm sub-lethal responses to carbofuran.

    Directory of Open Access Journals (Sweden)

    Mohana Krishna Reddy Mudiam

    Full Text Available Despite recent advances in understanding mechanism of toxicity, the development of biomarkers (biochemicals that vary significantly with exposure to chemicals for pesticides and environmental contaminants exposure is still a challenging task. Carbofuran is one of the most commonly used pesticides in agriculture and said to be most toxic carbamate pesticide. It is necessary to identify the biochemicals that can vary significantly after carbofuran exposure on earthworms which will help to assess the soil ecotoxicity. Initially, we have optimized the extraction conditions which are suitable for high-throughput gas chromatography mass spectrometry (GC-MS based metabolomics for the tissue of earthworm, Metaphire posthuma. Upon evaluation of five different extraction solvent systems, 80% methanol was found to have good extraction efficiency based on the yields of metabolites, multivariate analysis, total number of peaks and reproducibility of metabolites. Later the toxicity evaluation was performed to characterize the tissue specific metabolomic perturbation of earthworm, Metaphire posthuma after exposure to carbofuran at three different concentration levels (0.15, 0.3 and 0.6 mg/kg of soil. Seventeen metabolites, contributing to the best classification performance of highest dose dependent carbofuran exposed earthworms from healthy controls were identified. This study suggests that GC-MS based metabolomic approach was precise and sensitive to measure the earthworm responses to carbofuran exposure in soil, and can be used as a promising tool for environmental eco-toxicological studies.

  19. Response to weaning and dietary L-glutamine supplementation: metabolomic analysis in piglets by gas chromatography/mass spectrometry*

    Science.gov (United States)

    Xiao, Ying-ping; Wu, Tian-xing; Hong, Qi-hua; Sun, Jiang-ming; Chen, An-guo; Yang, Cai-mei; Li, Xiao-yan

    2012-01-01

    A novel metabolomic method based on gas chromatography/mass spectrometry (GC-MS) was applied to determine the metabolites in the serum of piglets in response to weaning and dietary L-glutamine (Gln) supplementation. Thirty-six 21-d-old piglets were randomly assigned into three groups. One group continued to suckle from the sows (suckling group), whereas the other two groups were weaned and their diets were supplemented with 1% (w/w) Gln or isonitrogenous L-alanine, respectively, representing Gln group or control group. Serum samples were collected to characterize metabolites after a 7-d treatment. Results showed that twenty metabolites were down-regulated significantly (Ppiglets compared with suckling ones. These data demonstrated that early weaning causes a wide range of metabolic changes across arginine and proline metabolism, aminosugar and nucleotide metabolism, galactose metabolism, glycerophospholipid metabolism, biosynthesis of unsaturated fatty acid, and fatty acid metabolism. Dietary Gln supplementation increased the levels of creatinine,D-xylose, 2-hydroxybutyric acid, palmitelaidic acid, and α-L-galactofuranose (Pearly weaned piglets, and were involved in the arginine and proline metabolism, carbohydrate metabolism, and fatty acid metabolism. A leave-one-out cross-validation of random forest analysis indicated that creatinine was the most important metabolite among the three groups. Notably, the concentration of creatinine in control piglets was decreased (P=0.00001) compared to the suckling piglets, and increased (P=0.0003) in Gln-supplemented piglets. A correlation network for weaned and suckling piglets revealed that early weaning changed the metabolic pathways, leading to the abnormality of carbohydrate metabolism, amino acid metabolism, and lipid metabolism, which could be partially improved by dietary Gln supplementation. These findings provide fresh insight into the complex metabolic changes in response to early weaning and dietary Gln

  20. MPINet: Metabolite Pathway Identification via Coupling of Global Metabolite Network Structure and Metabolomic Profile

    Directory of Open Access Journals (Sweden)

    Feng Li

    2014-01-01

    Full Text Available High-throughput metabolomics technology, such as gas chromatography mass spectrometry, allows the analysis of hundreds of metabolites. Understanding that these metabolites dominate the study condition from biological pathway perspective is still a significant challenge. Pathway identification is an invaluable aid to address this issue and, thus, is urgently needed. In this study, we developed a network-based metabolite pathway identification method, MPINet, which considers the global importance of metabolites and the unique character of metabolomic profile. Through integrating the global metabolite functional network structure and the character of metabolomic profile, MPINet provides a more accurate metabolomic pathway analysis. This integrative strategy simultaneously captures the global nonequivalence of metabolites in a pathway and the bias from metabolomic experimental technology. We then applied MPINet to four different types of metabolite datasets. In the analysis of metastatic prostate cancer dataset, we demonstrated the effectiveness of MPINet. With the analysis of the two type 2 diabetes datasets, we show that MPINet has the potentiality for identifying novel pathways related with disease and is reliable for analyzing metabolomic data. Finally, we extensively applied MPINet to identify drug sensitivity related pathways. These results suggest MPINet’s effectiveness and reliability for analyzing metabolomic data across multiple different application fields.

  1. Skinfold anthropometry--the accurate method for fat free mass measurement in COPD.

    Science.gov (United States)

    Hronek, Miloslav; Kovarik, Miroslav; Aimova, Petra; Koblizek, Vladimir; Pavlikova, Ladislava; Salajka, Frantisek; Zadak, Zdenek

    2013-10-01

    Fat free mass index (FFMI) is an independent predictor of metabolic and functional consequences in COPD. For its measurement dual energy X-ray absorptiometry (DEXA), skin-fold anthropometry (SFA), bioelectrical impedance analysis (BIA) and bioimpedance spectroscopy (BIS) are used in clinical practice. The aim of our pilot study was to analyse precisely and critically which method is most accurate and available for common use in clinical practice for measurement of FFM by assessment against relevant DEXA in patients with COPD. This was an observational cross-sectional study of consecutive COPD subjects. FFM by methods of SFA, two versions of BIA, and BIS was compared with that from clinically relevant DEXA in 41 outpatients (mean age 66.5 ± 7.7 yrs) with stable COPD, 34 men and 7 women, with mean BMI 28.2 ± 6.1 kg.m(-2). All methods underestimate FFM in comparison with DEXA. In the general evaluation non-significant differences with the smallest mean bias were demonstrated for SFA (1.2 kg) and BIA (3.8 kg), but there was a difference of more than 9 kg using BIS and BIA COPD methods (p DEXA and SFA was demonstrated via Lin's concordance coefficient and Bland-Altman test. SFA has been demonstrated as an accurate, available and cheap method for determination of FFM and FM with application of the Durnin Womersley equation for body density and with the Siri equation for FM in patients with COPD. SFA can be easily applied in routine clinical practice.

  2. Screening in veterinary drug analysis and sports doping control based on full-scan, accurate-mass spectrometry

    NARCIS (Netherlands)

    Peters, R.J.B.; Stolker, A.A.M.; Mol, J.G.J.; Lommen, A.; Lyris, E.; Angelis, Y.S.; Vonaparti, A.; Stamou, M.; Georgakopoulos, C.G.; Nielen, M.W.F.

    2010-01-01

    A common trend in food contaminants and sports doping control is towards a limited number of targeted, full-scan, accurate-mass spectrometry (MS) methods based on time-of-flight (TOF) or Fourier-transform orbital trap (Orbitrap) mass analyzers. Retrospective analysis of the full-scan datasets of

  3. The New Panacea in Metabolomics, Proteomics and Genomics - Electrochemistry/Mass Spectrometry

    Science.gov (United States)

    Kraj, A.; Chervet, J.P.; Purkerson, J.; Eysberg, M.

    2010-01-01

    RP-65 Combining Electrochemistry (EC) with Mass Spectrometry (MS) has shown great potential for the investigation of drug metabolism1,2,3. Recently, the use of EC/MS has been extended towards new applications such as: 1. Fast synthesis of metabolites in micro preparative mode to generate sufficient amounts for the characterization by NMR and/or use as reference material. A specially designed μ-preparative electrochemical flow cell will be presented. 2. Rapid risk assessments of drug-protein binding. Investigation of drug-protein adducts by conventionally used techniques (microsomal incubation, in-vivo studies) are very laborious and have often low efficiency. With the application of EC, it is possible to activate proteins and drugs within seconds to undergo covalent drug-protein binding. 3. Signal enhancement in MS Proteomics. EC/LC/MS can enhance the signal intensity in MS by using electroactive derivatizing agent (e.g. N-(2-Ferroceneethyl)maleimide (FEM) for stabilizing thiol groups in proteins) or directly improving ionization efficiency. 4. Oxidative damage of DNA. On-line EC/ESI-MS is novel tool to study oxidative processes of nucleic acids, as well as to create covalent drug adducts with nucleic acids. All these applications illustrate the tremendous power and broad applicability of electrochemistry as a promising tool to mimic nature's Redox reactions, including oxidative damage of DNA, protein stress, lipid oxidation, etc. [1] Jurva U., Wikstrom H. V., Weidolf L., Bruins A.P., Comparison between electrochemistry/mass spectrometry and cytochrome P450 catalyzed oxidation reactions, Rapid Commun. Mass Spectrom. 17 (2003) 800–810. [2] Baumann A., Lohmann W., Schubert B., Oberacher H., Karst U., Metabolic studies of tetrazepam based on electrochemical simulation incomparison to in vivo and in vitro methods, J. Chromatogr. A 1216 (2009) 3192–3198. [3] Lohmann W., Hayen H., Karst U.,Covalent Protein Modification by Reactive Drug Metabolites Using Online

  4. 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.

  5. 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.

  6. 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

  7. One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks.

    Science.gov (United States)

    Myers, Owen D; Sumner, Susan J; Li, Shuzhao; Barnes, Stephen; Du, Xiuxia

    2017-09-05

    False positive and false negative peaks detected from extracted ion chromatograms (EIC) are an urgent problem with existing software packages that preprocess untargeted liquid or gas chromatography-mass spectrometry metabolomics data because they can translate downstream into spurious or missing compound identifications. We have developed new algorithms that carry out the sequential construction of EICs and detection of EIC peaks. We compare the new algorithms to two popular software packages XCMS and MZmine 2 and present evidence that these new algorithms detect significantly fewer false positives. Regarding the detection of compounds known to be present in the data, the new algorithms perform at least as well as XCMS and MZmine 2. Furthermore, we present evidence that mass tolerance in m/z should be favored rather than mass tolerance in ppm in the process of constructing EICs. The mass tolerance parameter plays a critical role in the EIC construction process and can have immense impact on the detection of EIC peaks.

  8. 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.

  9. Screening and confirmation criteria for hormone residue analysis using liquid chromatography accurate mass time-of-flight, Fourier transform ion cyclotron resonance and orbitrap mass spectrometry techniques

    NARCIS (Netherlands)

    Nielen, M.W.F.; Engelen, M.C. van; Zuiderent, R.; Ramaker, R.

    2007-01-01

    An emerging trend is recognised in hormone and veterinary drug residue analysis from liquid chromatography tandem mass spectrometry (LC/MS/MS) based screening and confirmation towards accurate mass alternatives such as LC coupled with time-of-flight (TOF), Fourier transform ion cyclotron resonance

  10. [Serum metabolomics analysis on benign prostate hyperplasia in mice based on liquid chromatography-mass spectrometry].

    Science.gov (United States)

    Geng, Yue; Sun, Fengxia; Ma, Yu; Deng, Ligang; Lü, Jianyun; Li, Teng; Wang, Congcong

    2014-12-01

    Benign prostatic hyperplasia (BPH) increasingly becomes a common factor affecting the quality of life of aging men. Its pathogenesis has not yet been fully elucidated. Ultra-high pressure liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was employed to detect the changes of serum metabolites in normal mice, benign prostatic hyperplasia model mice and BPH model mice with finasteride intervention. The serum metabolite profiles of the three groups of mice were analyzed. Partial least squares-discriminant analysis (PLS-DA) was used for group differentiation and biomarker selection. The results showed good distinction among the three groups of mice serum metabolite spectra. Three potential biomarkers, 1-hexadecanoyl-SN-glycero-3-phosphocholine, 1-O-hexadecyl-2-O-acetyl-sn-glyceryl-3-phosphorylcholine and (Z)-13-docosenamide, were discovered and identified. They all indicated the occurrence of benign prostatic hypertrophy is closely related to the disorders of lipid metabolism. Coinpared with the control group, the contents of the first two substances were significantly increased in the serum of BPH model mice, and significantly decreased after intervened by finasteride. The contents of (Z)-13-docosenamide decreased significantly in the serum of model group, and increased after intervened by finasteride. Compared with the control group, the contents of three biomarkers in finasteride group did not recover completely and had significant differences. This study is conductive to open new avenues of diagnosis and medical treatment for BPH.

  11. Comprehensive and Comparative Metabolomic Profiling of Wheat, Barley, Oat and Rye Using Gas Chromatography-Mass Spectrometry and Advanced Chemometrics.

    Science.gov (United States)

    Khakimov, Bekzod; Jespersen, Birthe Møller; Engelsen, Søren Balling

    2014-10-31

    Beyond the main bulk components of cereals such as the polysaccharides and proteins, lower concentration secondary metabolites largely contribute to the nutritional value. This paper outlines a comprehensive protocol for GC-MS metabolomic profiling of phenolics and organic acids in grains, the performance of which is demonstrated through a comparison of the metabolite profiles of the main northern European cereal crops: wheat, barley, oat and rye. Phenolics and organic acids were extracted using acidic hydrolysis, trimethylsilylated using a new method based on trimethylsilyl cyanide and analyzed by GC-MS. In order to extract pure metabolite peaks, the raw chromatographic data were processed by a multi-way decomposition method, Parallel Factor Analysis 2. This approach lead to the semi-quantitative detection of a total of 247 analytes, out of which 89 were identified based on RI and EI-MS library match. The cereal metabolome included 32 phenolics, 30 organic acids, 10 fatty acids, 11 carbohydrates and 6 sterols. The metabolome of the four cereals were compared in detail, including low concentration phenolics and organic acids. Rye and oat displayed higher total concentration of phenolic acids, but ferulic, caffeic and sinapinic acids and their esters were found to be the main phenolics in all four cereals. Compared to the previously reported methods, the outlined protocol provided an efficient and high throughput analysis of the cereal metabolome and the acidic hydrolysis improved the detection of conjugated phenolics.

  12. Comprehensive and Comparative Metabolomic Profiling of Wheat, Barley, Oat and Rye Using Gas Chromatography-Mass Spectrometry and Advanced Chemometrics

    Directory of Open Access Journals (Sweden)

    Bekzod Khakimov

    2014-10-01

    Full Text Available Beyond the main bulk components of cereals such as the polysaccharides and proteins, lower concentration secondary metabolites largely contribute to the nutritional value. This paper outlines a comprehensive protocol for GC-MS metabolomic profiling of phenolics and organic acids in grains, the performance of which is demonstrated through a comparison of the metabolite profiles of the main northern European cereal crops: wheat, barley, oat and rye. Phenolics and organic acids were extracted using acidic hydrolysis, trimethylsilylated using a new method based on trimethylsilyl cyanide and analyzed by GC-MS. In order to extract pure metabolite peaks, the raw chromatographic data were processed by a multi-way decomposition method, Parallel Factor Analysis 2. This approach lead to the semi-quantitative detection of a total of 247 analytes, out of which 89 were identified based on RI and EI-MS library match. The cereal metabolome included 32 phenolics, 30 organic acids, 10 fatty acids, 11 carbohydrates and 6 sterols. The metabolome of the four cereals were compared in detail, including low concentration phenolics and organic acids. Rye and oat displayed higher total concentration of phenolic acids, but ferulic, caffeic and sinapinic acids and their esters were found to be the main phenolics in all four cereals. Compared to the previously reported methods, the outlined protocol provided an efficient and high throughput analysis of the cereal metabolome and the acidic hydrolysis improved the detection of conjugated phenolics.

  13. A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

    Directory of Open Access Journals (Sweden)

    Jianwen She

    2013-09-01

    Full Text Available Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC, reversed-phase liquid chromatography (RP–LC, and gas chromatography (GC. All three techniques are coupled to a mass spectrometer (MS in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

  14. Histamine quantification in human plasma using high resolution accurate mass LC-MS technology.

    Science.gov (United States)

    Laurichesse, Mathieu; Gicquel, Thomas; Moreau, Caroline; Tribut, Olivier; Tarte, Karin; Morel, Isabelle; Bendavid, Claude; Amé-Thomas, Patricia

    2016-01-01

    Histamine (HA) is a small amine playing an important role in anaphylactic reactions. In order to identify and quantify HA in plasma matrix, different methods have been developed but present several disadvantages. Here, we developed an alternative method using liquid chromatography coupled with an ultra-high resolution and accurate mass instrument, Q Exactive™ (Thermo Fisher) (LCHRMS). The method includes a protein precipitation of plasma samples spiked with HA-d4 as internal standard (IS). LC separation was performed on a C18 Accucore column (100∗2.1mm, 2.6μm) using a mobile phase containing nonafluoropentanoic acid (3nM) and acetonitrile with 0.1% (v/v) formic acid on gradient mode. Separation of analytes was obtained within 10min. Analysis was performed from full scan mode and targeted MS2 mode using a 5ppm mass window. Ion transitions monitored for targeted MS2 mode were 112.0869>95.0607m/z for HA and 116.1120>99.0855m/z for HA-d4. Calibration curves were obtained by adding standard calibration dilution at 1 to 180nM in TrisBSA. Elution of HA and IS occurred at 4.1min. The method was validated over a range of concentrations from 1nM to 100nM. The intra- and inter-run precisions were <15% for quality controls. Human plasma samples from 30 patients were analyzed by LCHRMS, and the results were highly correlated with those obtained using the gold standard radioimmunoassay (RIA) method. Overall, we demonstrate here that LCHRMS is a sensitive method for histamine quantification in biological human plasmas, suitable for routine use in medical laboratories. In addition, LCHRMS is less time-consuming than RIA, avoids the use of radioactivity, and could then be considered as an alternative quantitative method. Copyright © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  15. Strategy for comparative untargeted metabolomics reveals honey markers of different floral and geographic origins using ultrahigh-performance liquid chromatography-hybrid quadrupole-orbitrap mass spectrometry.

    Science.gov (United States)

    Li, Yi; Jin, Yue; Yang, Shupeng; Zhang, Wenwen; Zhang, Jinzhen; Zhao, Wen; Chen, Lanzhen; Wen, Yaqin; Zhang, Yongxin; Lu, Kaizhi; Zhang, Yaping; Zhou, Jinhui; Yang, Shuming

    2017-05-26

    Honey discrimination based on floral and geographic origins is limited by the ability to determine reliable markers because developing hypothetical substances in advance considerably limits the throughput of metabolomics studies. Here, we present a novel approach to screen and elucidate honey markers based on comparative untargeted metabolomics using ultrahigh-performance liquid chromatography-hybrid quadrupole-orbitrap mass spectrometry (UHPLC-Q-Orbitrap). To reduce metabolite information losses during sample preparation, the honey samples were dissolved in water and centrifuged to remove insoluble particles prior to UHPLC-Q-Orbitrap analysis in positive and negative electrospray ionization modes. The data were pretreated using background subtraction, chromatographic peak extraction, normalization, transformation and scaling to remove interferences from unwanted biases and variance in the experimental data. The pretreated data were further processed using principal component analysis (PCA) and a three-stage approach (t-test, volcano plot and variable importance in projection (VIP) plot) to ensure marker authenticity. A correlation between the molecular and fragment ions with a mass accuracy of less than 1.0ppm was used to annotate and elucidate the marker structures, and the marker responses in real samples were used to confirm the effectiveness of the honey discrimination. Moreover, we evaluated the data quality using blank and quality control (QC) samples based on PCA clustering, retention times, normalized levels and peak areas. This strategy will help guide standardized, comparative untargeted metabolomics studies of honey and other agro-products from different floral and geographic origins. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. 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...

  17. Development of a metabolomic approach based on liquid chromatography-high resolution mass spectrometry to screen for clenbuterol abuse in calves.

    Science.gov (United States)

    Courant, Frédérique; Pinel, Gaud; Bichon, Emmanuelle; Monteau, Fabrice; Antignac, Jean-Philippe; Le Bizec, Bruno

    2009-08-01

    Beta-agonist compounds can be misused in food-producing animals for growth promoting purposes. Efficient methods based on mass spectrometry detection have been developed to ensure the control of such veterinary drug residues. Nevertheless, the use of "cocktails" composed of mixtures of low amounts of several substances as well as the synthesis of new compounds of unknown structure prevent efficient prevention. To circumvent those problems, new analytical tools able to detect such abuse are today mandatory. In this context, metabolomics may represent a new emerging strategy for investigating the global physiological effects associated to a family of substances and therefore, to suspect the administration of beta-agonists (either "cocktails" or unknown compounds). As a first demonstration of feasibility, an untargeted metabolomic approach based on liquid chromatography coupled to high resolution mass spectrometry measurements was developed and made it possible to highlight metabolic modifications in urine consecutively to a clenbuterol administration. By the means of chemometrics, those metabolic differences were used to build predictive models able to suspect clenbuterol administration in calves. This new approach may be considered of valuable interest to overcome current limitations in the control of growth promoters' abuse, with promising perspectives in terms of screening.

  18. Assessment of two complementary liquid chromatography coupled to high resolution mass spectrometry metabolomics strategies for the screening of anabolic steroid treatment in calves

    Energy Technology Data Exchange (ETDEWEB)

    Dervilly-Pinel, Gaud, E-mail: laberca@oniris-nantes.fr [ONIRIS, Ecole nationale veterinaire, agroalimentaire et de l' alimentation Nantes-Atlantique, Laboratoire d' Etude des Residus et Contaminants dans les Aliments (LABERCA), Atlanpole - La Chantrerie, BP 40706, Nantes F-44307 (France); Weigel, Stefan; Lommen, Arjen [RIKILT - Institute of Food Safety, Wageningen UR, P.O. Box 230, 6700 AE Wageningen (Netherlands); Chereau, Sylvain; Rambaud, Lauriane [ONIRIS, Ecole nationale veterinaire, agroalimentaire et de l' alimentation Nantes-Atlantique, Laboratoire d' Etude des Residus et Contaminants dans les Aliments (LABERCA), Atlanpole - La Chantrerie, BP 40706, Nantes F-44307 (France); Essers, Martien [RIKILT - Institute of Food Safety, Wageningen UR, P.O. Box 230, 6700 AE Wageningen (Netherlands); Antignac, Jean-Philippe [ONIRIS, Ecole nationale veterinaire, agroalimentaire et de l' alimentation Nantes-Atlantique, Laboratoire d' Etude des Residus et Contaminants dans les Aliments (LABERCA), Atlanpole - La Chantrerie, BP 40706, Nantes F-44307 (France); Nielen, Michel W.F. [RIKILT - Institute of Food Safety, Wageningen UR, P.O. Box 230, 6700 AE Wageningen (Netherlands); Wageningen University, Laboratory of Organic Chemistry, Wageningen (Netherlands); Le Bizec, Bruno [ONIRIS, Ecole nationale veterinaire, agroalimentaire et de l' alimentation Nantes-Atlantique, Laboratoire d' Etude des Residus et Contaminants dans les Aliments (LABERCA), Atlanpole - La Chantrerie, BP 40706, Nantes F-44307 (France)

    2011-08-26

    Anabolic steroids are banned in food producing livestock in Europe. Efficient methods based on mass spectrometry detection have been developed to ensure the control of such veterinary drug residues. Nevertheless, the use of 'cocktails' composed of mixtures of low amounts of several substances as well as the synthesis of new compounds of unknown structure prevent efficient prevention. New analytical tools able to detect such abuse are today mandatory. In this context, metabolomics may represent new emerging strategies for investigating the global physiological effects associated to a family of substances and therefore, to suspect the administration of steroids. The purpose of the present study was to set up, assess and compare two complementary mass spectrometry-based metabolomic strategies as new tools to screen for steroid abuse in cattle and demonstrate the feasibility of such approaches. The protocols were developed in two European laboratories in charge of residues analysis in the field of food safety. Apart from sample preparation, the global process was different in both laboratories from LC-HRMS fingerprinting to multivariate data analysis through data processing and involved both LC-Orbitrap-XCMS and UPLC-ToF-MS-MetAlign strategies. The reproducibility of both sample preparation and MS measurements were assessed in order to guarantee that any differences in the acquired fingerprints were not caused by analytical variability but reflect metabolome modifications upon steroids administration. The protocols were then applied to urine samples collected on a large group of animals consisting of 12 control calves and 12 calves administrated with a mixture of 17{beta}-estradiol 3-benzoate and 17{beta}-nandrolone laureate esters according to a protocol reflecting likely illegal practices. The modifications in urine profiles as indicators of steroid administration have been evaluated in this context and proved the suitability of the approach for

  19. Accurate screening for synthetic preservatives in beverage using high performance liquid chromatography with time-of-flight mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Li Xiuqin; Zhang Feng; Sun Yanyan; Yong Wei [Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Jia 3, Gaobeidian North Road, Beijing 100025 (China); Chu Xiaogang [Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Jia 3, Gaobeidian North Road, Beijing 100025 (China)], E-mail: lixq_sypu@yahoo.com; Fang Yanyan; Zweigenbaum, Jerry [Agilent Technologies, Inc., 2850 Centerville Road, Wilmington, Delaware (United States)

    2008-02-11

    In this study, liquid chromatography time-of-flight mass spectrometry (HPLC/TOF-MS) is applied to qualitation and quantitation of 18 synthetic preservatives in beverage. The identification by HPLC/TOF-MS is accomplished with the accurate mass (the subsequent generated empirical formula) of the protonated molecules [M + H]+ or the deprotonated molecules [M - H]-, along with the accurate mass of their main fragment ions. In order to obtain sufficient sensitivity for quantitation purposes (using the protonated or deprotonated molecule) and additional qualitative mass spectrum information provided by the fragments ions, segment program of fragmentor voltages is designed in positive and negative ion mode, respectively. Accurate mass measurements are highly useful in the complex sample analyses since they allow us to achieve a high degree of specificity, often needed when other interferents are present in the matrix. The mass accuracy typically obtained is routinely better than 3 ppm. The 18 compounds behave linearly in the 0.005-5.0 mg.kg{sup -1} concentration range, with correlation coefficient >0.996. The recoveries at the tested concentrations of 1.0 mg.kg{sup -1}-100 mg.kg{sup -1} are 81-106%, with coefficients of variation <7.5%. Limits of detection (LODs) range from 0.0005 to 0.05 mg.kg{sup -1}, which are far below the required maximum residue level (MRL) for these preservatives in foodstuff. The method is suitable for routine quantitative and qualitative analyses of synthetic preservatives in foodstuff.

  20. Ion mobility derived collision cross sections to support metabolomics applications.

    Science.gov (United States)

    Paglia, Giuseppe; Williams, Jonathan P; Menikarachchi, Lochana; Thompson, J Will; Tyldesley-Worster, Richard; Halldórsson, Skarphédinn; Rolfsson, Ottar; Moseley, Arthur; Grant, David; Langridge, James; Palsson, Bernhard O; Astarita, Giuseppe

    2014-04-15

    Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD proof of concept, we used UPLC-TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches.

  1. An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yang; Liu, Fang; Li, Peng; He, Chengwei; Wang, Ruibing; Su, Huanxing; Wan, Jian-Bo, E-mail: jbwan@umac.mo

    2016-07-13

    Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies. - Highlights: • An UHPLC/Q-TOF tsMIM MS-based pseudotargeted metabolomics was proposed. • Compared to full scan, the improved method exhibits better repeatability and a wider linear range. • The proposed method could achieve pseudotargeted analysis on one UHPLC/Q-TOF/MS instrument. • The developed method was successfully used to discover biomarkers for alcohol-induced liver injury.

  2. Profiling the metabolome changes caused by cranberry procyanidins in plasma of female rats using (1) H NMR and UHPLC-Q-Orbitrap-HRMS global metabolomics approaches.

    Science.gov (United States)

    Liu, Haiyan; Garrett, Timothy J; Tayyari, Fariba; Gu, Liwei

    2015-11-01

    The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using (1) H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Twenty-four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for three times using a 250 mg extracts/kg body weight dose. Plasma was collected 6 h after the last gavage and analyzed using (1) H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using (1) H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in the plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulphate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4'-O-methyl-(-)-epicatechin-3'-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(-)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-ϒ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. 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.

  4. Use of high-resolution accurate mass spectrometry to detect reported and previously unreported cannabinomimetics in "herbal high" products.

    Science.gov (United States)

    Hudson, Simon; Ramsey, John; King, Les; Timbers, Sarah; Maynard, Steve; Dargan, Paul I; Wood, David M

    2010-06-01

    A range of "Herbal High" products were tested for synthetic cannabinoids (cannabinomimetics) to qualitatively determine and compare their individual and relative content. Liquid chromatography-high resolution accurate mass spectrometry was used to rapidly screen samples for a range of cannabinomimetics using mono-isotopic masses derived from the elemental composition of target analytes. A screening database of over 140 compounds was rapidly created. This approach, combined with further tandem mass spectrometric experiments, also facilitated the detection and identification of compounds for which reference materials were not available. Previously reported cannabinomimetics, including JWH-018 and CP47,497 and its homologues, were detected in varying relative proportions along with several tentatively identified unreported cannabinomimetics. In some countries, the decision has been made to include these substances within their drug control legislation, and other countries are considering similar action. The currently applied drug screening techniques are unlikely to be effective in providing scientific evidence to support their identification in seized products. The application of high-resolution accurate mass spectrometry offers a solution. In addition, the technology provides a relatively simple and quick method for screening products, building substance databases, and even identifying novel substances using a combination of accurate mass derived elemental composition and fragment ions combined with fragmentation prediction software.

  5. Polyphenol Identification Based on Systematic and Robust High-Resolution Accurate Mass Spectroscopy Fragmentation

    NARCIS (Netherlands)

    Hooft, van der J.J.J.; Vervoort, J.J.M.; Bino, R.J.; Beekwilder, M.J.; Vos, de R.C.H.

    2011-01-01

    High-mass resolution multi-stage mass spectrometry (MSn) fragmentation was tested for differentiation and identification of metabolites, using a series of 121 polyphenolic molecules. The MSn fragmentation approach is based on the systematic breakdown of compounds, forming a so-called spectral tree.

  6. Dose-response characteristics of Clematis triterpenoid saponins and clematichinenoside AR in rheumatoid arthritis rats by liquid chromatography/mass spectrometry-based serum and urine metabolomics.

    Science.gov (United States)

    Li, Rui; Guo, Lin-Xiu; Li, Yi; Chang, Wen-Qi; Liu, Jian-Qun; Liu, Li-Fang; Xin, Gui-Zhong

    2017-03-20

    Clematidis Radix et Rhizoma is a traditional Chinese medicine widely used for treating arthritic disease. Clematis triterpenoid saponins (TS) and clematichinenoside AR (C-AR) have been considered to be responsible for its antiarthritic effects. However, the underling mechanism is still unclear because of their low bioavailability. To address of this issue, metabolomics tools were performed to determine metabolic variations associated with rheumatoid arthritis (RA) and responses to Clematis TS, C-AR and positive drug (Triptolide, TP) treatments. This metabolomics investigation of RA was conducted in collagen-induced arthritis (CIA) rats. Liquid chromatography/mass spectrometry and multivariate statistical tools were used to identify the alteration of serum and urine metabolites associated with RA and responses to drug treatment. As a result, 45 potential metabolites associated with RA were identified. After treatment, a total of 24 biomarkers were regulated to normal like levels. Among these, PC(18:0/20:4), 9,11-octadecadienoic acid, arachidonic acid, 1-methyladenosine, valine, hippuric acid and pantothenic acid etc, were reversed in Clematis TS and C-AR groups. Tetrahydrocortisol was regulated to normal levels in Clematis TS and TP groups, while 3,7,12-trihydroxycholan-24-oic acid was regulated in C-AR and TP groups. Biomarkers like citric acid, p-cresol glucuronide, creatinine, cortolone were reversed in TP group. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Liquid chromatography - high resolution mass spectrometry-based metabolomic approach for the detection of Continuous Erythropoiesis Receptor Activator effects in horse doping control.

    Science.gov (United States)

    Joré, Céline; Loup, Benoît; Garcia, Patrice; Paris, Anne-Christelle; Popot, Marie-Agnès; Audran, Michel; Bonnaire, Yves; Varlet-Marie, Emmanuelle; Bailly-Chouriberry, Ludovic

    2017-10-27

    Erythropoiesis Stimulating Agents (ESAs) were developed for therapeutic purposes to stimulate red blood cell (RBC) production. Consequently, tissue oxygenation is enhanced as athlete's endurance and ESAs misuse now benefits doping. Our hypothesis is that most of ESAs should have similar mechanisms and thus have the same effects on metabolism. Studying the metabolome variations could allow suspecting the use of any ESAs with a single method by targeting their effects. In this objective, a metabolomic study was carried out on 3 thoroughbred horses with a single administration of 4.2μg/kg of Mircera(®), also called Continuous Erythropoiesis Receptor Activator (CERA). Blood and urine samples were collected from D-17 to D+74 and haematological parameters were followed throughout the study as plasmatic CERA concentration (ELISA). Urine and plasma metabolic fingerprints were recorded by Liquid Chromatography coupled to High Resolution Mass Spectrometry (LC-HRMS) in positive and negative mode. After preprocessing steps, normalized data were analyzed by multivariate statistics to build OPLS models. Hemoglobin concentration and hematocrit showed a significant increase after CERA administration unlike reticulocytes. CERA concentration showed a high intensity peak and then a slow decrease until becoming undetectable after D+31. Models built with multivariate statistics allow a discrimination between pre and post-administration plasma and urine samples until 74days after administration, i.e. 43days longer than ELISA method. By reducing and studying variables (ions), some potential candidate biomarkers were found. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Metabolomics study on primary dysmenorrhea patients during the luteal regression stage based on ultra performance liquid chromatography coupled with quadrupole‑time‑of‑flight mass spectrometry.

    Science.gov (United States)

    Fang, Ling; Gu, Caiyun; Liu, Xinyu; Xie, Jiabin; Hou, Zhiguo; Tian, Meng; Yin, Jia; Li, Aizhu; Li, Yubo

    2017-03-01

    Primary dysmenorrhea (PD) is a common gynecological disorder which, while not life‑threatening, severely affects the quality of life of women. Most patients with PD suffer ovarian hormone imbalances caused by uterine contraction, which results in dysmenorrhea. PD patients may also suffer from increases in estrogen levels caused by increased levels of prostaglandin synthesis and release during luteal regression and early menstruation. Although PD pathogenesis has been previously reported on, these studies only examined the menstrual period and neglected the importance of the luteal regression stage. Therefore, the present study used urine metabolomics to examine changes in endogenous substances and detect urine biomarkers for PD during luteal regression. Ultra performance liquid chromatography coupled with quadrupole‑time‑of‑flight mass spectrometry was used to create metabolomic profiles for 36 patients with PD and 27 healthy controls. Principal component analysis and partial least squares discriminate analysis were used to investigate the metabolic alterations associated with PD. Ten biomarkers for PD were identified, including ornithine, dihydrocortisol, histidine, citrulline, sphinganine, phytosphingosine, progesterone, 17‑hydroxyprogesterone, androstenedione, and 15‑keto‑prostaglandin F2α. The specificity and sensitivity of these biomarkers was assessed based on the area under the curve of receiver operator characteristic curves, which can be used to distinguish patients with PD from healthy controls. These results provide novel targets for the treatment of PD.

  9. Accurate Empirical Radii and Masses of Planets and Their Host Stars with Gaia Parallaxes

    Science.gov (United States)

    Stassun, Keivan G.; Collins, Karen A.; Gaudi, B. Scott

    2017-03-01

    We present empirical measurements of the radii of 116 stars that host transiting planets. These radii are determined using only direct observables—the bolometric flux at Earth, the effective temperature, and the parallax provided by the Gaia first data release—and thus are virtually model independent, with extinction being the only free parameter. We also determine each star’s mass using our newly determined radius and the stellar density, a virtually model independent quantity itself from previously published transit analyses. These stellar radii and masses are in turn used to redetermine the transiting-planet radii and masses, again using only direct observables. The median uncertainties on the stellar radii and masses are 8% and 30%, respectively, and the resulting uncertainties on the planet radii and masses are 9% and 22%, respectively. These accuracies are generally larger than previously published model-dependent precisions of 5% and 6% on the planet radii and masses, respectively, but the newly determined values are purely empirical. We additionally report radii for 242 stars hosting radial-velocity (non-transiting) planets, with a median achieved accuracy of ≈2%. Using our empirical stellar masses we verify that the majority of putative “retired A stars” in the sample are indeed more massive than ˜1.2 {M}⊙ . Most importantly, the bolometric fluxes and angular radii reported here for a total of 498 planet host stars—with median accuracies of 1.7% and 1.8%, respectively—serve as a fundamental data set to permit the re-determination of transiting-planet radii and masses with the Gaia second data release to ≈3% and ≈5% accuracy, better than currently published precisions, and determined in an entirely empirical fashion.

  10. 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

  11. Disruption of the Prostaglandin Metabolome and Characterization of the Pharmaceutical Exposome in Fish Exposed to Wastewater Treatment Works Effluent As Revealed by Nanoflow-Nanospray Mass Spectrometry-Based Metabolomics.

    Science.gov (United States)

    David, Arthur; Lange, Anke; Abdul-Sada, Alaa; Tyler, Charles R; Hill, Elizabeth M

    2017-01-03

    Fish can be exposed to a complex mixture of chemical contaminants, including pharmaceuticals, present in discharges of wastewater treatment works (WwTWs) effluents. There is little information on the effects of effluent exposure on fish metabolism, especially the small molecule signaling compounds which are the biological target of many pharmaceuticals. We applied a newly developed sensitive nanoflow-nanospray mass spectrometry nontargeted profiling technique to identify changes in the exposome and metabolome of roach (Rutilus rutilus) exposed to a final WwTWs effluent for 15 days. Effluent exposure resulted in widespread reduction (between 50% and 90%) in prostaglandin (PG) profiles in fish tissues and plasma with disruptions also in tryptophan/serotonin, bile acid and lipid metabolism. Metabolite disruptions were not explained by altered expression of genes associated with the PG or tryptophan metabolism. Of the 31 pharmaceutical metabolites that were detected in the effluent exposome of fish, 6 were nonsteroidal anti-inflammatory drugs but with plasma concentrations too low to disrupt PG biosynthesis. PGs, bile acids, and tryptophan metabolites are important mediators regulating a diverse array of physiological systems in fish and the identity of wastewater contaminants disrupting their metabolism warrants further investigation on their exposure effects on fish health.

  12. An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system

    OpenAIRE

    Krause, Douglas J.; Hinke, Jefferson T.; Perryman, Wayne L.; Goebel, Michael E.; LeRoi, Donald J.

    2017-01-01

    Measurements of body size and mass are fundamental to pinniped population management and research. Manual measurements tend to be accurate but are invasive and logistically challenging to obtain. Ground-based photogrammetric techniques are less invasive, but inherent limitations make them impractical for many field applications. The recent proliferation of unmanned aerial systems (UAS) in wildlife monitoring has provided a promising new platform for the photogrammetry of free-ranging pinniped...

  13. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) Provides Accurate Direct from Culture Species Identification within the Genus Candida.

    Science.gov (United States)

    Cameron, Simon J S; Bolt, Frances; Perdones-Montero, Alvaro; Rickards, Tony; Hardiman, Kate; Abdolrasouli, Alireza; Burke, Adam; Bodai, Zsolt; Karancsi, Tamas; Simon, Daniel; Schaffer, Richard; Rebec, Monica; Balog, Julia; Takáts, Zoltan

    2016-11-14

    Members of the genus Candida, such as C. albicans and C. parapsilosis, are important human pathogens. Other members of this genus, previously believed to carry minimal disease risk, are increasingly recognised as important human pathogens, particularly because of variations in susceptibilities to widely used anti-fungal agents. Thus, rapid and accurate identification of clinical Candida isolates is fundamental in ensuring timely and effective treatments are delivered. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has previously been shown to provide a high-throughput platform for the rapid and accurate identification of bacterial and fungal isolates. In comparison to commercially available matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI-ToF), REIMS based methods require no preparative steps nor time-consuming cell extractions. Here, we report on the ability of REIMS-based analysis to rapidly and accurately identify 153 clinical Candida isolates to species level. Both handheld bipolar REIMS and high-throughput REIMS platforms showed high levels of species classification accuracy, with 96% and 100% of isolates classified correctly to species level respectively. In addition, significantly different (FDR corrected P value < 0.05) lipids within the 600 to 1000 m/z mass range were identified, which could act as species-specific biomarkers in complex microbial communities.

  14. Capillary electrophoresis-mass spectrometry-based metabolome analysis of serum and saliva from neurodegenerative dementia patients.

    Science.gov (United States)

    Tsuruoka, Mayuko; Hara, Junko; Hirayama, Akiyoshi; Sugimoto, Masahiro; Soga, Tomoyoshi; Shankle, William R; Tomita, Masaru

    2013-10-01

    Despite increasing global prevalence, the precise pathogenesis and terms for objective diagnosis of neurodegenerative dementias remain controversial, and comprehensive understanding of the disease remains lacking. Here, we conducted metabolomic analysis of serum and saliva obtained from patients with neurodegenerative dementias (n = 10), including Alzheimer's disease, frontotemporal lobe dementia, and Lewy body disease, as well as from age-matched healthy controls (n = 9). Using CE-TOF-MS, six metabolites in serum (β-alanine, creatinine, hydroxyproline, glutamine, iso-citrate, and cytidine) and two in saliva (arginine and tyrosine) were significantly different between dementias and controls. Using multivariate analysis, serum was confirmed as a more efficient biological fluid for diagnosis compared to saliva; additionally, 45 metabolites in total were identified as candidate markers that could discriminate at least one pair of diagnostic groups from the healthy control group. These metabolites possibly provide an objective method for diagnosing dementia-type by multiphase screening. Moreover, diagnostic-type-dependent differences were observed in several tricarboxylic acid cycle compounds detected in serum, indicating that some pathways in glucose metabolism may be altered in dementia patients. This pilot study revealed novel alterations in metabolomic profiles between various neurodegenerative dementias, which would contribute to etiological investigations. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Development of high throughput 96-blade solid phase microextraction-liquid chromatrography-mass spectrometry protocol for metabolomics.

    Science.gov (United States)

    Mousavi, Fatemeh; Bojko, Barbara; Pawliszyn, Janusz

    2015-09-10

    In metabolomics, the workflow for quantitative and comprehensive metabolic mapping of cellular metabolites can be a very challenging undertaking. Sampling and sample preparation play a significant role in untargeted analysis, as they may affect the composition of the analyzed metabolome. In the current work, different solid phase microextraction (SPME) coating chemistries were developed and applied to provide simultaneous extraction of a wide range of both hydrophobic and hydrophilic cellular metabolites produced by a model organism, Escherichia coli. Three different LC-MS methods were also evaluated for analysis of extracted metabolites. Finally, over 200 cellular metabolites were separated and detected with widely varying hydrophobicities ranging within -7 < log P < 15, including amino acids, peptides, nucleotides, carbohydrates, polycarboxylic acids, vitamins, phosphorylated compounds, and lipids such as hydrophobic phospholipids, prenol lipids, and fatty acids at the stationary phase of the E. coli life cycle using the developed 96-blade SPME-LC-MS method. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Does body mass index accurately reflect body fat? A comparison of anthropometric measures in the longitudinal assessment of fat mass.

    Science.gov (United States)

    Phan, Thao-Ly T; Maresca, Michelle M; Hossain, Jobayer; Datto, George A

    2012-07-01

    To determine which anthropometric measure best correlates with change in fat mass (FM) over time. The authors performed a retrospective cohort study of 76 obese patients (mean body mass index [BMI] 38 kg/m(2) and mean age 13 years) presenting to an obesity clinic between 2005 and 2010. For each patient, during 2 visits, FM was measured by bioelectrical impedance analysis and the following measures obtained: BMI, waist circumference, hip circumference, and neck circumference. Correlation coefficients and linear regression analyses were calculated to examine the relationship between each measure and FM. Change in BMI correlated better with change in FM than any other measure and had the strongest effect on change in FM (P FM.

  17. Collision-induced fragmentation accurate mass spectrometric analysis methods to rapidly characterize plant extracts

    Science.gov (United States)

    The rapid advances in analytical chromatography equipment have made the reliable and reproducible measurement of a wide range of plant chemical components possible. Full chemical characterization of a given plant material is possible with the new mass spectrometers currently available. For phytochem...

  18. Collision-induced fragmentation accurate mass spectrometric analysis methods to rapidly characterize phytochemicals in plant extracts

    Science.gov (United States)

    The rapid advances in analytical chromatography equipment have made the reliable and reproducible measurement of a wide range of plant chemical components possible. Full chemical characterization of a given plant material is possible with the new mass spectrometers currently available. New methods a...

  19. An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system.

    Science.gov (United States)

    Krause, Douglas J; Hinke, Jefferson T; Perryman, Wayne L; Goebel, Michael E; LeRoi, Donald J

    2017-01-01

    Measurements of body size and mass are fundamental to pinniped population management and research. Manual measurements tend to be accurate but are invasive and logistically challenging to obtain. Ground-based photogrammetric techniques are less invasive, but inherent limitations make them impractical for many field applications. The recent proliferation of unmanned aerial systems (UAS) in wildlife monitoring has provided a promising new platform for the photogrammetry of free-ranging pinnipeds. Leopard seals (Hydrurga leptonyx) are an apex predator in coastal Antarctica whose body condition could be a valuable indicator of ecosystem health. We aerially surveyed leopard seals of known body size and mass to test the precision and accuracy of photogrammetry from a small UAS. Flights were conducted in January and February of 2013 and 2014 and 50 photogrammetric samples were obtained from 15 unrestrained seals. UAS-derived measurements of standard length were accurate to within 2.01 ± 1.06%, and paired comparisons with ground measurements were statistically indistinguishable. An allometric linear mixed effects model predicted leopard seal mass within 19.40 kg (4.4% error for a 440 kg seal). Photogrammetric measurements from a single, vertical image obtained using UAS provide a noninvasive approach for estimating the mass and body condition of pinnipeds that may be widely applicable.

  20. An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system.

    Directory of Open Access Journals (Sweden)

    Douglas J Krause

    Full Text Available Measurements of body size and mass are fundamental to pinniped population management and research. Manual measurements tend to be accurate but are invasive and logistically challenging to obtain. Ground-based photogrammetric techniques are less invasive, but inherent limitations make them impractical for many field applications. The recent proliferation of unmanned aerial systems (UAS in wildlife monitoring has provided a promising new platform for the photogrammetry of free-ranging pinnipeds. Leopard seals (Hydrurga leptonyx are an apex predator in coastal Antarctica whose body condition could be a valuable indicator of ecosystem health. We aerially surveyed leopard seals of known body size and mass to test the precision and accuracy of photogrammetry from a small UAS. Flights were conducted in January and February of 2013 and 2014 and 50 photogrammetric samples were obtained from 15 unrestrained seals. UAS-derived measurements of standard length were accurate to within 2.01 ± 1.06%, and paired comparisons with ground measurements were statistically indistinguishable. An allometric linear mixed effects model predicted leopard seal mass within 19.40 kg (4.4% error for a 440 kg seal. Photogrammetric measurements from a single, vertical image obtained using UAS provide a noninvasive approach for estimating the mass and body condition of pinnipeds that may be widely applicable.

  1. Rapid yet accurate measurement of mass diffusion coefficients by phase shifting interferometer

    CERN Document Server

    Guo Zhi Xiong; Komiya, A

    1999-01-01

    The technique of using a phase-shifting interferometer is applied to the study of diffusion in transparent liquid mixtures. A quick method is proposed for determining the diffusion coefficient from the measurements of the location of fringes on a grey level picture. The measurement time is very short (within 100 s) and a very small transient diffusion field can be observed and recorded accurately with a rate of 30 frames per second. The measurement can be completed using less than 0.12 cc of solutions. The influence of gravity on the measurement of the diffusion coefficient is eliminated in the present method. Results on NaCl-water diffusion systems are presented and compared with the reference data. (author)

  2. 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.

  3. Discrimination of Citrus reticulata Blanco and Citrus reticulata 'Chachi' by gas chromatograph-mass spectrometry based metabolomics approach.

    Science.gov (United States)

    Duan, Li; Guo, Long; Dou, Li-Li; Zhou, Chang-Lin; Xu, Feng-Guo; Zheng, Guo-Dong; Li, Ping; Liu, E-Hu

    2016-12-01

    Citri Reticulatae Pericarpium, mainly including the pericarp of Citrus reticulata Blanco and the pericarp of Citrus reticulata 'Chachi', has been consumed daily as food and dietary supplement for centuries. In this study, GC-MS based metabolomics was employed to compare comprehensively the volatile constituents in Citrus reticulata Blanco and Citrus reticulata 'Chachi'. Principal component analysis and orthogonal partial least squares discrimination analysis indicated that samples could be distinguished effectively from one another. Fifteen metabolites were finally identified for use as chemical markers in discrimination of Citri Reticulatae Pericarpium samples. The antimicrobial activity against Gram-negative and Gram-positive bacteria of the volatile oil from Citrus reticulata Blanco and Citrus reticulata 'Chachi' was investigated preliminarily. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. A powerful methodological approach combining headspace solid phase microextraction, mass spectrometry and multivariate analysis for profiling the volatile metabolomic pattern of beer starting raw materials.

    Science.gov (United States)

    Gonçalves, João L; Figueira, José A; Rodrigues, Fátima P; Ornelas, Laura P; Branco, Ricardo N; Silva, Catarina L; Câmara, José S

    2014-10-01

    The volatile metabolomic patterns from different raw materials commonly used in beer production, namely barley, corn and hop-derived products - such as hop pellets, hop essential oil from Saaz variety and tetra-hydro isomerized hop extract (tetra hop), were established using a suitable analytical procedure based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography-quadrupole mass spectrometry detection (GC-qMS). Some SPME extraction parameters were optimized. The best results, in terms of maximum signal recorded and number of isolated metabolites, were obtained with a 50/30 μm DVB/CAR/PDMS coating fiber at 40 °C for 30 min. A set of 152 volatile metabolites comprising ketones (27), sesquiterpenes (26), monoterpenes (19), aliphatic esters (19), higher alcohols (15), aldehydes (11), furan compounds (11), aliphatic fatty acids (9), aliphatic hydrocarbons (8), sulphur compounds (5) and nitrogen compounds (2) were positively identified. Each raw material showed a specific volatile metabolomic profile. Monoterpenes in hop essential oil and corn, sesquiterpenes in hop pellets, ketones in tetra hop and aldehydes and sulphur compounds in barley were the predominant chemical families in the targeted beer raw materials. β-Myrcene was the most dominant volatile metabolite in hop essential oil, hop pellets and corn samples while, in barley, the predominant volatile metabolites were dimethyl sulphide and 3-methylbutanal and, in tetra hop, 6-methyl-2-pentanone and 4-methyl-2-pentanone. Principal component analysis (PCA) showed natural sample grouping among beer raw materials. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

    Science.gov (United States)

    Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

    2017-05-02

    Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

  6. Accurate determination of silver nanoparticles in animal tissues by inductively coupled plasma mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Veverková, Lenka [Regional Centre of Advanced Technologies and Materials, Department of Analytical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); Hradilová, Šárka [Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); Milde, David, E-mail: david.mlde@upol.cz [Regional Centre of Advanced Technologies and Materials, Department of Analytical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); Panáček, Aleš [Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); Skopalová, Jana [Regional Centre of Advanced Technologies and Materials, Department of Analytical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); Kvítek, Libor [Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); Petrželová, Kamila [Regional Centre of Advanced Technologies and Materials, Department of Analytical Chemistry, Faculty of Science, Palacky University, 17.listopadu 12, CZ 771 46 Olomouc (Czech Republic); National Reference Laboratory for Chemical Elements, Department of Residues in Kroměříž, State Veterinary Institute Olomouc, Hulínská 2286, CZ 767 60 Kroměříž (Czech Republic); and others

    2014-12-01

    This study examined recoveries of silver determination in animal tissues after wet digestion by inductively coupled plasma mass spectrometry. The composition of the mineralization mixture for microwave assisted digestion was optimized and the best recoveries were obtained for mineralization with HNO{sub 3} and addition of HCl promptly after digestion. The optimization was performed on model samples of chicken meat spiked with silver nanoparticles and a solution of ionic silver. Basic calculations of theoretical distribution of Ag among various silver-containing species were implemented and the results showed that most of the silver is in the form of soluble complexes AgCl{sub 2}{sup −} and AgCl{sub 3}{sup 2−} for the optimized composition of the mineralization mixture. Three animal tissue certified reference materials were then analyzed to verify the trueness and precision of the results. - Highlights: • We performed detailed optimization of microwave assisted digestion procedure of animal tissue used prior to Ag determination by ICP-MS. • We provide basic equilibrium calculations to give theoretical explanation of results from optimization of tested mineralization mixtures. • Results from method validation that was done by analysis of several matrix CRMs are presented.

  7. 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

  8. Accurate modeling of intermediate-mass-ratio inspirals: exploring the form of the self-force in the intermediate-mass-ratio regime

    CERN Document Server

    Huerta, E A; Brown, Duncan A

    2012-01-01

    The LIGO detector is undergoing a major upgrade that will increase its sensitivity by a factor of 10, and extend its bandwidth from 40 Hz to 10 Hz on the lower frequency end, while also allowing for high-frequency operation due to its tunability. This advanced LIGO (aLIGO) detector will extend the mass range at which compact mass binaries may be detected by a factor of four or more at a fixed signal-to-noise ratio [1]. The inspirals of stellar-mass compact objects into intermediate-mass black holes (IMBHs) of 50-350 solar masses will lie in the frequency band of aLIGO [2]. GW searches for these type of events will provide conclusive evidence for the existence of IMBHs and explore the dynamics of cluster environments. To realize this science we need to develop waveform templates that accurately capture the dynamical evolution of these type of events before aLIGO begins observations. Implementing gravitational self-force (SF) corrections in templates for compact binaries with mass-ratios 1:10-1:1000 will be ess...

  9. Accurate Mass Fragment Library for Rapid Analysis of Pesticides on Produce Using Ambient Pressure Desorption Ionization with High-Resolution Mass Spectrometry

    Science.gov (United States)

    Kern, Sara E.; Lin, Lora A.; Fricke, Frederick L.

    2014-08-01

    U.S. food imports have been increasing steadily for decades, intensifying the need for a rapid and sensitive screening technique. A method has been developed that uses foam disks to sample the surface of incoming produce. This work provides complimentary information to the extensive amount of published pesticide fragmentation data collected using LCMS systems (Sack et al. Journal of Agricultural and Food Chemistry, 59, 6383-6411, 2011; Mol et al. Analytical and Bioanalytical Chemistry, 403, 2891-2908, 2012). The disks are directly analyzed using transmission-mode direct analysis in real time (DART) ambient pressure desorption ionization coupled to a high resolution accurate mass-mass spectrometer (HRAM-MS). In order to provide more certainty in the identification of the pesticides detected, a library of accurate mass fragments and isotopes of the protonated parent molecular ion (the [M+H]+) has been developed. The HRAM-MS is equipped with a quadrupole mass filter, providing the capability of "data-dependent" fragmentation, as opposed to "all -ion" fragmentation (where all of the ions enter a collision chamber and are fragmented at once). A temperature gradient for the DART helium stream and multiple collision energies were employed to detect and fragment 164 pesticides of varying chemical classes, sizes, and polarities. The accurate mass information of precursor ([M+H]+ ion) and fragment ions is essential in correctly identifying chemical contaminants on the surface of imported produce. Additionally, the inclusion of isotopes of the [M+H]+ in the database adds another metric to the confirmation process. The fragmentation data were collected using a Q-Exactive mass spectrometer and were added to a database used to process data collected with an Exactive mass spectrometer, an instrument that is more readily available for this screening application. The commodities investigated range from smooth-skinned produce such as apples to rougher surfaces like broccoli. The

  10. UC2 search: Using unique connectivity of uncharged compounds for metabolite annotation by database searching in mass spectrometry-based metabolomics.

    Science.gov (United States)

    Sakurai, Nozomu; Narise, Takafumi; Sim, Joon-Soo; Lee, Chang-Muk; Ikeda, Chiaki; Akimoto, Nayumi; Kanaya, Shigehiko

    2017-10-12

    For metabolite annotation in metabolomics, variations in the registered states of compounds (charged and multiple components such as salts) and their redundancy among compound databases could be the cause of misannotations and hamper immediate recognition of the uniqueness of metabolites while searching by mass values measured using mass spectrometry. We developed a search system named UC2 (Unique Connectivity of Uncharged Compounds) where compounds are tentatively neutralized into uncharged states and stored on the basis of their unique connectivity of atoms after removing their stereochemical information using the first block in the hash of the IUPAC International Chemical Identifier, by which false-positive hits are remarkably reduced, both charged and uncharged compounds are properly searched in a single query and records having a unique connectivity are compiled in a single search result. The UC2 search tool is available free of charge as a REST web service (http://webs2.kazusa.or.jp/mfsearcher) and a Java-based GUI tool. sakurai@kazusa.or.jp. Supplementary data are available at Bioinformatics online.

  11. 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.

  12. Fourier Transform Mass Spectrometry and Nuclear Magnetic Resonance Analysis for the Rapid and Accurate Characterization of Hexacosanoylceramide.

    Science.gov (United States)

    Ross, Charles W; Simonsick, William J; Bogusky, Michael J; Celikay, Recep W; Guare, James P; Newton, Randall C

    2016-06-28

    Ceramides are a central unit of all sphingolipids which have been identified as sites of biological recognition on cellular membranes mediating cell growth and differentiation. Several glycosphingolipids have been isolated, displaying immunomodulatory and anti-tumor activities. These molecules have generated considerable interest as potential vaccine adjuvants in humans. Accurate analyses of these and related sphingosine analogues are important for the characterization of structure, biological function, and metabolism. We report the complementary use of direct laser desorption ionization (DLDI), sheath flow electrospray ionization (ESI) Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) and high-field nuclear magnetic resonance (NMR) analysis for the rapid, accurate identification of hexacosanoylceramide and starting materials. DLDI does not require stringent sample preparation and yields representative ions. Sheath-flow ESI yields ions of the product and byproducts and was significantly better than monospray ESI due to improved compound solubility. Negative ion sheath flow ESI provided data of starting materials and products all in one acquisition as hexacosanoic acid does not ionize efficiently when ceramides are present. NMR provided characterization of these lipid molecules complementing the results obtained from MS analyses. NMR data was able to differentiate straight chain versus branched chain alkyl groups not easily obtained from mass spectrometry.

  13. Fourier Transform Mass Spectrometry and Nuclear Magnetic Resonance Analysis for the Rapid and Accurate Characterization of Hexacosanoylceramide

    Directory of Open Access Journals (Sweden)

    Charles W. Ross

    2016-06-01

    Full Text Available Ceramides are a central unit of all sphingolipids which have been identified as sites of biological recognition on cellular membranes mediating cell growth and differentiation. Several glycosphingolipids have been isolated, displaying immunomodulatory and anti-tumor activities. These molecules have generated considerable interest as potential vaccine adjuvants in humans. Accurate analyses of these and related sphingosine analogues are important for the characterization of structure, biological function, and metabolism. We report the complementary use of direct laser desorption ionization (DLDI, sheath flow electrospray ionization (ESI Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS and high-field nuclear magnetic resonance (NMR analysis for the rapid, accurate identification of hexacosanoylceramide and starting materials. DLDI does not require stringent sample preparation and yields representative ions. Sheath-flow ESI yields ions of the product and byproducts and was significantly better than monospray ESI due to improved compound solubility. Negative ion sheath flow ESI provided data of starting materials and products all in one acquisition as hexacosanoic acid does not ionize efficiently when ceramides are present. NMR provided characterization of these lipid molecules complementing the results obtained from MS analyses. NMR data was able to differentiate straight chain versus branched chain alkyl groups not easily obtained from mass spectrometry.

  14. High-throughput tissue extraction protocol for NMR- and MS-based metabolomics.

    Science.gov (United States)

    Wu, Huifeng; Southam, Andrew D; Hines, Adam; Viant, Mark R

    2008-01-15

    In metabolomics, tissues typically are extracted by grinding in liquid nitrogen followed by the stepwise addition of solvents. This is time-consuming and difficult to automate, and the multiple steps can introduce variability. Here we optimize tissue extraction methods compatible with high-throughput, reproducible nuclear magnetic resonance (NMR) spectroscopy- and mass spectrometry (MS)-based metabolomics. Previously, we concluded that methanol/chloroform/water extraction is preferable for metabolomics, and we further optimized this here using fish liver and an automated Precellys 24 bead-based homogenizer, allowing rapid extraction of multiple samples without carryover. We compared three solvent addition strategies: stepwise, two-step, and all solvents simultaneously. Then we evaluated strategies for improved partitioning of metabolites between solvent phases, including the addition of extra water and different partition times. Polar extracts were analyzed by NMR and principal components analysis, and the two-step approach was preferable based on lipid partitioning, reproducibility, yield, and throughput. Longer partitioning or extra water increased yield and decreased lipids in the polar phase but caused metabolic decay in these extracts. Overall, we conclude that the two-step method with extra water provides good quality data but that the two-step method with 10 min partitioning provides a more accurate snapshot of the metabolome. Finally, when validating the two-step strategy using NMR and MS metabolomics, we showed that technical variability was considerably smaller than biological variability.

  15. Metabolomics as a Potential Chemotaxonomical Tool: Application in the Genus Vernonia Schreb

    OpenAIRE

    Maria Elvira Poleti Martucci; Ric C H De Vos; Carlos Alexandre Carollo; Leonardo Gobbo-Neto

    2014-01-01

    The taxonomic classification of the genus Vernonia Schreb is complex and, as yet, unclear. We here report the use of untargeted metabolomics approaches, followed by multivariate analyses methods and a phytochemical characterization of ten Vernonia species. Metabolic fingerprints were obtained by accurate mass measurements and used to determine the phytochemical similarities and differences between species through multivariate analyses approaches. Principal component analysis based on the rela...

  16. A new approach for plasma (xeno)metabolomics based on solid-phase extraction and nanoflow liquid chromatography-nanoelectrospray ionisation mass spectrometry.

    Science.gov (United States)

    David, Arthur; Abdul-Sada, Alaa; Lange, Anke; Tyler, Charles R; Hill, Elizabeth M

    2014-10-24

    Current metabolite profiling methods based on liquid chromatography-mass spectrometry (LC-MS) platforms do not detect many of the components present at trace concentrations in extracts of plasma due to their low ionisation efficiency or to interference from highly abundant compounds. Nanoflow LC-nanospray MS platforms, which are commonly used in proteomics, could overcome these limitations and significantly increase analytical sensitivity and coverage of the plasma (xeno)metabolome (i.e., metabolites and xenobiotics), but require small injection volumes (ionisation-time-of-flight mass spectrometry (nUHPLC-nESI-TOFMS). These methods use phospholipid filtration plates in combination with polymeric or mixed mode exchange solid-phase extraction (SPE). The phospholipid filtration plates removed >94% of the predominant phospholipid/lysophospholipid species from plasma, whilst absolute recoveries of 63 selected (xeno)metabolites from spiked plasma were generally between 60 and 104%. After a further SPE step, recoveries of test compounds were between 50 and 81%. Studies revealed that both the sample preparation methodology and nUHPLC-nESI-TOFMS analyses gave acceptable repeatability. A qualitative comparison of SPE methods revealed that sample concentration by either polymer or mixed mode ion-exchange SPE gave comprehensive metabolite coverage of plasma extracts, but the use of cation exchange SPE significantly increased detection of many cationic compounds in the sample extracts. Method detection limits for steroid, eicosanoid and bile metabolites were <1.0ng/mL plasma and for pharmaceutical contaminants were between 0.01 and 30ng/mL plasma. Comparison of the phospholipid removal/cation exchange SPE and the classical protein precipitation (PPT) sample preparation methodologies revealed that both methods detected the same range of (xeno)metabolites. However, unlike PPT extracts, the SPE preparations allowed direct injection of more concentrated plasma extracts onto the n

  17. Evolution of potent odorants within the volatile metabolome of high-quality hazelnuts (Corylus avellana L.): evaluation by comprehensive two-dimensional gas chromatography coupled with mass spectrometry.

    Science.gov (United States)

    Rosso, Marta Cialiè; Liberto, Erica; Spigolon, Nicola; Fontana, Mauro; Somenzi, Marco; Bicchi, Carlo; Cordero, Chiara

    2018-01-09

    Within the pattern of volatiles released by food products (volatilome), potent odorants are bio-active compounds that trigger aroma perception by activating a complex array of odor receptors (ORs) in the regio olfactoria. Their informative role is fundamental to select optimal post-harvest and storage conditions and preserve food sensory quality. This study addresses the volatile metabolome from high-quality hazelnuts (Corylus avellana L.) from the Ordu region (Turkey) and Tonda Romana from Italy, and investigates its evolution throughout the production chain (post-harvest, industrial storage, roasting) to find functional correlations between technological strategies and product quality. The volatile metabolome is analyzed by headspace solid-phase microextration combined with comprehensive two-dimensional gas chromatography and mass spectrometry. Dedicated pattern recognition, based on 2D data (targeted fingerprinting), is used to mine analytical outputs, while principal component analysis (PCA), Fisher ratio, hierarchical clustering, and analysis of variance are used to find decision makers among the most informative chemicals. Low-temperature drying (18-20 °C) has a decisive effect on quality; it correlates negatively with bacteria and mold metabolic activity, nut viability, and lipid oxidation products (2-methyl-1-propanol, 3-methyl-1-butanol, 2-ethyl-1-hexanol, 2-octanol, 1-octen-3-ol, hexanal, octanal and (E)-2-heptanal). Protective atmosphere storage (99% N2-1% O2) effectively limits lipid oxidation for 9-12 months after nut harvest. The combination of optimal drying and storage preserves the aroma potential; after roasting at different shelf-lives, key odorants responsible for malty and buttery (2- and 3-methylbutanal, 2,3-butanedione and 2,3-pentanedione), earthy (methylpyrazine, 2-ethyl-5-methyl pyrazine and 3-ethyl-2,5-dimethyl pyrazine) and caramel-like and musty notes (2,5-dimethyl-4-hydroxy-3(2H)-furanone - furaneol and acetyl pyrrole) show no

  18. Development of quantitative metabolomics for Pichia pastoris.

    Science.gov (United States)

    Carnicer, Marc; Canelas, André B; Ten Pierick, Angela; Zeng, Zhen; van Dam, Jan; Albiol, Joan; Ferrer, Pau; Heijnen, Joseph J; van Gulik, Walter

    2012-04-01

    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 of all metabolic activity and removal of extracellular metabolites, without causing leakage of metabolites from the cells. Five different procedures based on cold methanol quenching and cell separation by filtration were tested for metabolomics of Pichia pastoris regarding methanol content and temperature of the quenching solution as key parameters. Quantitative evaluation of these protocols was carried out through mass balance analysis, based on metabolite measurements in all sample fractions, those are whole broth, quenched and washed cells, culture filtrate and quenching and washing solution. Finally, the optimal method was used to study the time profiles of free amino acid and central carbon metabolism intermediates in glucose-limited chemostat cultures. Acceptable recoveries (>90%) were obtained for all quenching procedures tested. However, quenching at -27°C in 60% v/v methanol performed slightly better in terms of leakage minimization. We could demonstrate that five residence times under glucose limitation are enough to reach stable intracellular metabolite pools. Moreover, when comparing P. pastoris and S. cerevisiae metabolomes, under the same cultivation conditions, similar metabolite fingerprints were found in both yeasts, except for the lower glycolysis, where the levels of these metabolites in P. pastoris suggested an enzymatic capacity limitation in that part of the metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0308-1) contains supplementary material, which is available to authorized users.

  19. Development of an Isotope-Dilution Liquid Chromatography/Mass Spectrometric Method for the Accurate Determination of Acetaminophen in Tablets

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Hyun Ju; Kim, Byung Joo; Lee, Joon Hee; Hwang, Eui Jin [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)

    2010-12-15

    Acetaminophen (N-acetyl-p-aminophenol) is one of the most popular analgesic and antipyretic drugs. An isotope dilution mass spectrometric method based on LC/MS was developed as a candidate reference method for the accurate determination of acetaminophen in pharmaceutical product. After spiking an isotope labeled acetaminophen (acetyl-{sup 13}C{sub 2}, {sup 15}Nacetaminophen) as an internal standard, tablet extracts were analyzed by LC/MS in a selected reaction monitoring (SRM) mode to detect ions at m/z 152→110 and m/z 155→111 for acetaminophen and acetyl-{sup 13}C{sub 2}, {sup 15}N-acetaminophen, respectively. The repeatability and reproducibility of the developed ID/LC-MS method were tested for the validation and assessment of metrological quality of the method.

  20. Mass Spectrometry-Based Metabolomic and Lipidomic Analyses of the Effects of Dietary Platycodon grandiflorum on Liver and Serum of Obese Mice under a High-Fat Diet

    Directory of Open Access Journals (Sweden)

    Hye Min Park

    2017-01-01

    Full Text Available We aimed to identify metabolites involved in the anti-obesity effects of Platycodon grandiflorum (PG in high-fat diet (HFD-fed mice using mass spectrometry (MS-based metabolomic techniques. C57BL/6J mice were divided into four groups: normal diet (ND-fed mice, HFD-fed mice, HFD with 1% PG extract-fed mice (HPGL, and HFD with 5% PG extract-fed mice (HPGH. After 8 weeks, the HFD group gained more weight than the ND group, while dietary 5% PG extract attenuated this change. The partial least squares discriminant analysis (PLS-DA score plots showed a clear distinction between experimental groups in serum and liver markers. We also identified 10 and 32 metabolites in the serum and liver, respectively, as potential biomarkers that could explain the effect of high-dose PG added to HFD-fed mice, which were strongly involved in amino acid metabolism (glycine, serine, threonine, methionine, glutamate, phenylalanine, ornithine, lysine, and tyrosine, TCA cycle (fumarate and succinate, lipid metabolism (linoleic and oleic acid methyl esters, oleamide, and cholesterol, purine/pyrimidine metabolism (uracil and hypoxanthine, carbohydrate metabolism (maltose, and glycerophospholipid metabolism (phosphatidylcholines, phosphatidylethanolamines, lysophosphatidylcholines, and lysophosphatidylethanolamines. We suggest that further studies on these metabolites could help us gain a better understanding of both HFD-induced obesity and the effects of PG.

  1. Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet’s Disease by Gas Chromatography/Time-of-Flight−Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Joong Kyong Ahn

    2017-11-01

    Full Text Available Diagnosing Behcet’s disease (BD is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flight–mass spectrometry (GC/TOF−MS. Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC were assessed using GC/TOF−MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF−MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA model were R2X of 0.231, R2Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, l-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974. OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%. We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF−MS.

  2. Multiclass semi-volatile compounds determination in wine by gas chromatography accurate time-of-flight mass spectrometry.

    Science.gov (United States)

    Rodríguez-Cabo, T; Rodríguez, I; Ramil, M; Silva, A; Cela, R

    2016-04-15

    The performance of gas chromatography (GC) with accurate, high resolution mass spectrometry (HRMS) for the determination of a group of 39 semi-volatile compounds related to wine quality (pesticide residues, phenolic off-flavours, phenolic pollutants and bioactive stilbenes) is investigated. Solid-phase extraction (SPE) was used as extraction technique, previously to acetylation (phenolic compounds) and dispersive liquid-liquid microextraction (DLLME) concentration. Compounds were determined by GC coupled to a quadrupole time-of-flight (QTOF) MS system through an electron ionization (EI) source. The final method attained limits of quantification (LOQs) at the very low ng mL(-1) level, covering the range of expected concentrations for target compounds in red and white wines. For 38 out of 39 compounds, performance of sample preparation and determination steps were hardly affected by the wine matrix; thus, accurate recoveries were achieved by using pseudo-external calibration. Levels of target compounds in a set of 25 wine samples are reported. The capabilities of the described approach for the post-run identification of species not considered during method development, without retention time information, are illustrated and discussed with selected examples of compounds from different classes. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. 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

  4. Masses of the components of SB2 binaries observed with Gaia - IV. Accurate SB2 orbits for 14 binaries and masses of three binaries*

    Science.gov (United States)

    Kiefer, F.; Halbwachs, J.-L.; Lebreton, Y.; Soubiran, C.; Arenou, F.; Pourbaix, D.; Famaey, B.; Guillout, P.; Ibata, R.; Mazeh, T.

    2018-02-01

    The orbital motion of non-contact double-lined spectroscopic binaries (SB2s), with periods of a few tens of days to several years, holds unique, accurate information on individual stellar masses, which only long-term monitoring can unlock. The combination of radial velocity measurements from high-resolution spectrographs and astrometric measurements from high-precision interferometers allows the derivation of SB2 component masses down to the percent precision. Since 2010, we have observed a large sample of SB2s with the SOPHIE spectrograph at the Observatoire de Haute-Provence, aiming at the derivation of orbital elements with sufficient accuracy to obtain masses of components with relative errors as low as 1 per cent when the astrometric measurements of the Gaia satellite are taken into account. In this paper, we present the results from 6 yr of observations of 14 SB2 systems with periods ranging from 33 to 4185 days. Using the TODMOR algorithm, we computed radial velocities from the spectra and then derived the orbital elements of these binary systems. The minimum masses of the 28 stellar components are then obtained with an average sample accuracy of 1.0 ± 0.2 per cent. Combining the radial velocities with existing interferometric measurements, we derived the masses of the primary and secondary components of HIP 61100, HIP 95995 and HIP 101382 with relative errors for components (A,B) of, respectively, (2.0, 1.7) per cent, (3.7, 3.7) per cent and (0.2, 0.1) per cent. Using the CESAM2K stellar evolution code, we constrained the initial He abundance, age and metallicity for HIP 61100 and HIP 95995.

  5. 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.

  6. Forensic Analysis of Stains on Fabric Using Direct Analysis in Real-time Ionization with High-Resolution Accurate Mass-Mass Spectrometry.

    Science.gov (United States)

    Kern, Sara E; Crowe, John B; Litzau, Jonathan J; Heitkemper, Douglas T

    2017-06-12

    A rapid technique using direct analysis in real-time (DART) ambient ionization coupled to a high-resolution accurate mass-mass spectrometer (HRAM-MS) was employed to analyze stains on an individual's pants suspected to have been involved in a violent crime. The victim was consuming chocolate ice cream at the time of the attack, and investigators recovered the suspect's pants exhibiting splatter stains. Liquid chromatography with mass spectral detection (LC-MS) and stereoscopic light microscopy (SLM) were also utilized in this analysis. It was determined that the stains on the pants contained theobromine and caffeine, known components of chocolate. A shard from the ceramic bowl that contained the victim's ice cream and a control chocolate ice cream sample were also found to contain caffeine and theobromine. The use of DART-HRAM-MS was useful in this case due to its rapid analysis capability and because of the limited amount of sample present as a stain. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

  7. Accurate determination of selected pesticides in soya beans by liquid chromatography coupled to isotope dilution mass spectrometry.

    Science.gov (United States)

    Huertas Pérez, J F; Sejerøe-Olsen, B; Fernández Alba, A R; Schimmel, H; Dabrio, M

    2015-05-01

    A sensitive, accurate and simple liquid chromatography coupled with mass spectrometry method for the determination of 10 selected pesticides in soya beans has been developed and validated. The method is intended for use during the characterization of selected pesticides in a reference material. In this process, high accuracy and appropriate uncertainty levels associated to the analytical measurements are of utmost importance. The analytical procedure is based on sample extraction by the use of a modified QuEChERS (quick, easy, cheap, effective, rugged, safe) extraction and subsequent clean-up of the extract with C18, PSA and Florisil. Analytes were separated on a C18 column using gradient elution with water-methanol/2.5 mM ammonium acetate mobile phase, and finally identified and quantified by triple quadrupole mass spectrometry in the multiple reaction monitoring mode (MRM). Reliable and accurate quantification of the analytes was achieved by means of stable isotope-labelled analogues employed as internal standards (IS) and calibration with pure substance solutions containing both, the isotopically labelled and native compounds. Exceptions were made for thiodicarb and malaoxon where the isotopically labelled congeners were not commercially available at the time of analysis. For the quantification of those compounds methomyl-(13)C2(15)N and malathion-D10 were used respectively. The method was validated according to the general principles covered by DG SANCO guidelines. However, validation criteria were set more stringently. Mean recoveries were in the range of 86-103% with RSDs lower than 8.1%. Repeatability and intermediate precision were in the range of 3.9-7.6% and 1.9-8.7% respectively. LODs were theoretically estimated and experimentally confirmed to be in the range 0.001-0.005 mg kg(-1) in the matrix, while LOQs established as the lowest spiking mass fractionation level were in the range 0.01-0.05 mg kg(-1). The method reliably identifies and quantifies the

  8. A Gas Chromatography-Mass Spectrometry Based Study on Urine Metabolomics in Rats Chronically Poisoned with Hydrogen Sulfide

    National Research Council Canada - National Science Library

    Deng, Mingjie; Zhang, Meiling; Sun, Fa; Ma, Jianshe; Hu, Lufeng; Yang, Xuezhi; Lin, Guanyang; Wang, Xianqin

    2015-01-01

      Gas chromatography-mass spectrometry (GS-MS) in combination with multivariate statistical analysis was applied to explore the metabolic variability in urine of chronically hydrogen sulfide- (H2S...

  9. Bioprospecting of microalgae: Proper extraction followed by high performance liquid chromatographic-high resolution mass spectrometric fingerprinting as key tools for successful metabolom characterization.

    Science.gov (United States)

    Stranska-Zachariasova, Milena; Kastanek, Petr; Dzuman, Zbynek; Rubert, Josep; Godula, Michal; Hajslova, Jana

    2016-03-15

    Currently, the interest in microalgae as a source of biologically active components exploitable as supplementary ingredients to food/feed or in cosmetics continues to increase. Existing research mainly aims to focus on revealing and recovering the rare, cost competitive components of the algae metabolom. Because these components could be of very different physicochemical character, a universal approach for their isolation and characterization should be developed. This study demonstrates the systematic development of the extraction strategy that represents one of the key challenges in effective algae bioprospecting, which predefines their further industrial application. By using of Trachydiscus minutus as a model microalgae biomass, following procedures were tested and critically evaluated in order to develop the generic procedure for microalgae bioprospecting: (i) various ways of mechanical disintegration of algae cells enabling maximum extraction efficiency, (ii) the use of a wide range of extraction solvents/solvent mixtures suitable for optimal extraction yields of polar, medium-polar, and non-polar compounds, (iii) the use of consecutive extractions as a fractionation approach. Within the study, targeted screening of selected compounds representing broad range of polarities was realized by ultra-high performance liquid chromatography coupled with high resolution tandem mass spectrometric detection (UHPLC-HRMS/MS), to assess the effectiveness of undertaken isolation steps. As a result, simple and high-throughput extraction-fractionation strategy based on consecutive extraction with water-aqueous methanol-hexane/isopropanol was developed. Moreover, to demonstrate the potential of the UHPLC-HRMS/MS for the retrospective non-target screening and compounds identification, the collected mass spectra have been evaluated to characterize the pattern of extracted metabolites. Attention was focused on medium-/non-polar extracts and characterization of lipid species

  10. Accurate protein complex retrieval by affinity enrichment mass spectrometry (AE-MS) rather than affinity purification mass spectrometry (AP-MS).

    Science.gov (United States)

    Keilhauer, Eva C; Hein, Marco Y; Mann, Matthias

    2015-01-01

    Protein-protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein-protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  11. Innovations in Mass Spectrometry for Precise and Accurate Isotope Ratio Determination from Very Small Analyte Quantities (Invited)

    Science.gov (United States)

    Lloyd, N. S.; Bouman, C.; Horstwood, M. S.; Parrish, R. R.; Schwieters, J. B.

    2010-12-01

    This presentation describes progress in mass spectrometry for analysing very small analyte quantities, illustrated by example applications from nuclear forensics. In this challenging application, precise and accurate (‰) uranium isotope ratios are required from 1 - 2 µm diameter uranium oxide particles, which comprise less than 40 pg of uranium. Traditionally these are analysed using thermal ionisation mass spectrometry (TIMS), and more recently using secondary ionisation mass spectrometry (SIMS). Multicollector inductively-coupled plasma mass spectrometry (MC-ICP-MS) can offer higher productivity compared to these techniques, but is traditionally limited by low efficiency of analyte utilisation (sample through to ion detection). Samples can either be introduced as a solution, or sampled directly from solid using laser ablation. Large multi-isotope ratio datasets can help identify provenance and intended use of anthropogenic uranium and other nuclear materials [1]. The Thermo Scientific NEPTUNE Plus (Bremen, Germany) with ‘Jet Interface’ option offers unparalleled MC-ICP-MS sensitivity. An analyte utilisation of c. 4% has previously been reported for uranium [2]. This high-sensitivity configuration utilises a dry high-capacity (100 m3/h) interface pump, special skimmer and sampler cones and a desolvating nebuliser system. Coupled with new acquisition methodologies, this sensitivity enhancement makes possible the analysis of micro-particles and small sample volumes at higher precision levels than previously achieved. New, high-performance, full-size and compact discrete dynode secondary electron multipliers (SEM) exhibit excellent stability and linearity over a large dynamic range and can be configured to simultaneously measure all of the uranium isotopes. Options for high abundance-sensitivity filters on two ion beams are also available, e.g. for 236U and 234U. Additionally, amplifiers with high ohm (1012 - 1013) feedback resistors have been developed to

  12. Gas Chromatography Time-Of-Flight Mass Spectrometry (GC-TOF-MS)-Based Metabolomics for Comparison of Caffeinated and Decaffeinated Coffee and Its Implications for Alzheimer’s Disease

    Science.gov (United States)

    Chang, Kai Lun; Ho, Paul C.

    2014-01-01

    Findings from epidemiology, preclinical and clinical studies indicate that consumption of coffee could have beneficial effects against dementia and Alzheimer’s disease (AD). The benefits appear to come from caffeinated coffee, but not decaffeinated coffee or pure caffeine itself. Therefore, the objective of this study was to use metabolomics approach to delineate the discriminant metabolites between caffeinated and decaffeinated coffee, which could have contributed to the observed therapeutic benefits. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics approach was employed to characterize the metabolic differences between caffeinated and decaffeinated coffee. Orthogonal partial least squares discriminant analysis (OPLS-DA) showed distinct separation between the two types of coffee (cumulative Q2 = 0.998). A total of 69 discriminant metabolites were identified based on the OPLS-DA model, with 37 and 32 metabolites detected to be higher in caffeinated and decaffeinated coffee, respectively. These metabolites include several benzoate and cinnamate-derived phenolic compounds, organic acids, sugar, fatty acids, and amino acids. Our study successfully established GC-TOF-MS based metabolomics approach as a highly robust tool in discriminant analysis between caffeinated and decaffeinated coffee samples. Discriminant metabolites identified in this study are biologically relevant and provide valuable insights into therapeutic research of coffee against AD. Our data also hint at possible involvement of gut microbial metabolism to enhance therapeutic potential of coffee components, which represents an interesting area for future research. PMID:25098597

  13. Existing equations to estimate lean body mass are not accurate in the critically ill: Results of a multicenter observational study.

    Science.gov (United States)

    Moisey, Lesley L; Mourtzakis, Marina; Kozar, Rosemary A; Compher, Charlene; Heyland, Daren K

    2017-12-01

    Lean body mass (LBM), quantified using computed tomography (CT), is a significant predictor of clinical outcomes in the critically ill. While CT analysis is precise and accurate in measuring body composition, it may not be practical or readily accessible to all patients in the intensive care unit (ICU). Here, we assessed the agreement between LBM measured by CT and four previously developed equations that predict LBM using variables (i.e. age, sex, weight, height) commonly recorded in the ICU. LBM was calculated in 327 critically ill adults using CT scans, taken at ICU admission, and 4 predictive equations (E1-4) that were derived from non-critically adults since there are no ICU-specific equations. Agreement was assessed using paired t-tests, Pearson's correlation coefficients and Bland-Altman plots. Median LBM calculated by CT was 45 kg (IQR 37-53 kg) and was significantly different (p equations overestimated LBM (error ranged from 7.5 to 9.9 kg), compared with LBM calculated by CT, suggesting insufficient agreement. Our data indicates a large bias is present between the calculation of LBM by CT imaging and the predictive equations that have been compared here. This underscores the need for future research toward the development of ICU-specific equations that reliably estimate LBM in a practical and cost-effective manner. Copyright © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  14. Accurate quantification of PAHs in water in the presence of dissolved humic acids using isotope dilution mass spectrometry.

    Science.gov (United States)

    Bercaru, Ofelia; Ulberth, Franz; Emons, Hendrik; Vandecasteele, Carlo

    2006-03-01

    The effect of dissolved humic acids on the recovery of PAHs from water samples has been investigated using a commercially available humic acid preparation as colloid model and a mixture containing the 16 EPA PAHs. The presence of humic acid reduced the extraction efficiency down to between 10 and 75%. An analytical protocol was therefore developed for the accurate determination of PAHs in the presence of humic acids based on isotope dilution mass spectrometry. The procedure compensates for losses due to sorption of PAHs and can be used for the determination of the total PAH concentration in water, i.e. dissolved PAHs plus PAHs adsorbed on colloids. To obtain reliable estimates it is essential to allow a certain time for equilibration between the isotope spike and the aqueous matrix which may vary between 5 and 24 h, in correlation with the water solubility of PAHs. The protocol allows one to recover the 16 PAHs studied at 94 to 105%. The expanded uncertainty of the measurements was 5-7% for all PAHs. Liquid-liquid extraction and solid-phase extraction in combination with the developed isotope dilution protocol performed equally well for the quantification of PAHs from water samples rich in colloidal material.

  15. Accurate quantification of PAHs in water in the presence of dissolved humic acids using isotope dilution mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Bercaru, Ofelia; Ulberth, Franz; Emons, Hendrik [Institute for Reference Materials and Measurements (IRMM), European Commission, Joint Research Centre, Geel (Belgium); Vandecasteele, Carlo [Katholieke Universiteit Leuven, Department of Chemical Engineering, Heverlee (Belgium)

    2006-03-15

    The effect of dissolved humic acids on the recovery of PAHs from water samples has been investigated using a commercially available humic acid preparation as colloid model and a mixture containing the 16 EPA PAHs. The presence of humic acid reduced the extraction efficiency down to between 10 and 75%. An analytical protocol was therefore developed for the accurate determination of PAHs in the presence of humic acids based on isotope dilution mass spectrometry. The procedure compensates for losses due to sorption of PAHs and can be used for the determination of the total PAH concentration in water, i.e. dissolved PAHs plus PAHs adsorbed on colloids. To obtain reliable estimates it is essential to allow a certain time for equilibration between the isotope spike and the aqueous matrix which may vary between 5 and 24 h, in correlation with the water solubility of PAHs. The protocol allows one to recover the 16 PAHs studied at 94 to 105%. The expanded uncertainty of the measurements was 5-7% for all PAHs. Liquid-liquid extraction and solid-phase extraction in combination with the developed isotope dilution protocol performed equally well for the quantification of PAHs from water samples rich in colloidal material. (orig.)

  16. Mass Spectrometry-Based Metabolomics of Agave Sap (Agave salmiana after Its Inoculation with Microorganisms Isolated from Agave Sap Concentrate Selected to Enhance Anticancer Activity

    Directory of Open Access Journals (Sweden)

    Luis M. Figueroa

    2017-11-01

    Full Text Available Saponins have been correlated with the reduction of cancer cell growth and the apoptotic effect of agave sap concentrate. Empirical observations of this artisanal Mexican food have shown that fermentation occurs after agave sap is concentrated, but little is known about the microorganisms that survive after cooking, or their effects on saponins and other metabolites. The aim of this study was to evaluate the changes in metabolites found in agave (A. salmiana sap after its fermentation with microorganisms isolated from agave sap concentrate, and demonstrate its potential use to enhance anticancer activity. Microorganisms were isolated by dilution plating and identified by 16S rRNA analysis. Isolates were used to ferment agave sap, and their corresponding butanolic extracts were compared with those that enhanced the cytotoxic activity on colon (Caco-2 and liver (Hep-G2 cancer cells. Metabolite changes were investigated by mass spectrometry-based metabolomics. Among 69 isolated microorganisms, the actinomycetes Arthrobacter globiformis and Gordonia sp. were used to analyze the metabolites, along with bioactivity changes. From the 939 ions that were mainly responsible for variation among fermented samples at 48 h, 96 h, and 192 h, four were correlated to anticancer activity. It was shown that magueyoside B, a kammogenin glycoside, was found at higher intensities in the samples fermented with Gordonia sp. that reduced Hep-G2 viability better than controls. These findings showed that microorganisms from agave sap concentrate change agave sap metabolites such as saponins. Butanolic extracts obtained after agave sap fermentation with Arthrobacter globiformis or Gordonia sp. increased the cancer cell growth inhibitory effect on colon or liver cancer cells, respectively.

  17. Computational Mass Spectrometry (Dagstuhl Seminar 13491)

    OpenAIRE

    Aebersbold, Ruedi; Kohlbacher, Oliver; Vitek, Olga

    2014-01-01

    The last decade has brought tremendous technological advances in mass spectrometry, which in turn have enabled new applications of mass spectrometry in the life sciences. Proteomics, metabolomics, lipidomics, glycomics and related fields have gotten a massive boost, which also resulted in vastly increased amount of data produced and increased complexity of these data sets. An efficient and accurate analysis of these data sets has become the key bottleneck in the field. The seminar 'Com...

  18. Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography-mass spectrometry.

    Science.gov (United States)

    Smart, Kathleen F; Aggio, Raphael B M; Van Houtte, Jeremy R; Villas-Bôas, Silas G

    2010-09-01

    This protocol describes an analytical platform for the analysis of intra- and extracellular metabolites of microbial cells (yeast, filamentous fungi and bacteria) using gas chromatography-mass spectrometry (GC-MS). The protocol is subdivided into sampling, sample preparation, chemical derivatization of metabolites, GC-MS analysis and data processing and analysis. This protocol uses two robust quenching methods for microbial cultures, the first of which, cold glycerol-saline quenching, causes reduced leakage of intracellular metabolites, thus allowing a more reliable separation of intra- and extracellular metabolites with simultaneous stopping of cell metabolism. The second, fast filtration, is specifically designed for quenching filamentous micro-organisms. These sampling techniques are combined with an easy sample-preparation procedure and a fast chemical derivatization reaction using methyl chloroformate. This reaction takes place at room temperature, in aqueous medium, and is less prone to matrix effect compared with other derivatizations. This protocol takes an average of 10 d to complete and enables the simultaneous analysis of hundreds of metabolites from the central carbon metabolism (amino and nonamino organic acids, phosphorylated organic acids and fatty acid intermediates) using an in-house MS library and a data analysis pipeline consisting of two free software programs (Automated Mass Deconvolution and Identification System (AMDIS) and R).

  19. Retrospective screening of relevant pesticide metabolites in food using liquid chromatography high resolution mass spectrometry and accurate-mass databases of parent molecules and diagnostic fragment ions.

    Science.gov (United States)

    Polgár, László; García-Reyes, Juan F; Fodor, Péter; Gyepes, Attila; Dernovics, Mihály; Abrankó, László; Gilbert-López, Bienvenida; Molina-Díaz, Antonio

    2012-08-03

    In recent years, the detection and characterization of relevant pesticide metabolites in food is an important task in order to evaluate their formation, kinetics, stability, and toxicity. In this article, a methodology for the systematic screening of pesticides and their main metabolites in fruit and vegetable samples is described, using LC-HRMS and accurate-mass database search of parent compounds and their diagnostic fragment ions. The approach is based on (i) search for parent pesticide molecules; (ii) search for their metabolites in the positive samples, assuming common fragmentation pathways between the metabolites and parent pesticide molecules; and (iii) search for pesticide conjugates using the data from both parent species and diagnostic fragment ions. An accurate-mass database was constructed consisting of 1396 compounds (850 parent compounds, 447 fragment ions and 99 metabolites). The screening process was performed by the software in an automated fashion. The proposed methodology was evaluated with 29 incurred samples and the output obtained was compared to standard pesticide testing methods (targeted LC-MS/MS). Examples on the application of the proposed approach are shown, including the detection of several pesticide glycosides derivatives, which were found with significantly relevant intensities. Glucose-conjugated forms of parent compounds (e.g., fenhexamid-O-glucoside) and those of metabolites (e.g., despropyl-iprodione-N-glycoside) were detected. Facing the lack of standards for glycosylated pesticides, the study was completed with the synthesis of fenhexamid-O-glucoside for quantification purposes. In some cases the pesticide derivatives were found in a relatively high ratio, drawing the attention to these kinds of metabolites and showing that they should not be neglected in multi-residue methods. The global coverage obtained on the 29 analyzed samples showed the usefulness and benefits of the proposed approach and highlights the practical

  20. Quantitative profiling of bile acids in biofluids and tissues based on accurate mass high resolution LC-FT-MS: Compound class targeting in a metabolomics workflow

    NARCIS (Netherlands)

    Bobeldijk, I.; Hekman, M.; Vries de- Weij, J.van der; Coulier, L.; Ramaker, R.; Kleemann, R.; Kooistra, T.; Rubingh, C.; Freidig, A.; Verheij, E.

    2008-01-01

    We report a sensitive, generic method for quantitative profiling of bile acids and other endogenous metabolites in small quantities of various biological fluids and tissues. The method is based on a straightforward sample preparation, separation by reversed-phase high performance

  1. Broad screening of illicit ingredients in cosmetics using ultra-high-performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry with customized accurate-mass database and mass spectral library.

    Science.gov (United States)

    Meng, Xianshuang; Bai, Hua; Guo, Teng; Niu, Zengyuan; Ma, Qiang

    2017-12-15

    Comprehensive identification and quantitation of 100 multi-class regulated ingredients in cosmetics was achieved using ultra-high-performance liquid chromatography (UHPLC) coupled with hybrid quadrupole-Orbitrap high-resolution mass spectrometry (Q-Orbitrap HRMS). A simple, efficient, and inexpensive sample pretreatment protocol was developed using ultrasound-assisted extraction (UAE), followed by dispersive solid-phase extraction (dSPE). The cosmetic samples were analyzed by UHPLC-Q-Orbitrap HRMS under synchronous full-scan MS and data-dependent MS/MS (full-scan MS 1 /dd-MS 2 ) acquisition mode. The mass resolution was set to 70,000 FWHM (full width at half maximum) for full-scan MS 1 and 17,500 FWHM for dd-MS 2 stage with the experimentally measured mass deviations of less than 2ppm (parts per million) for quasi-molecular ions and 5ppm for characteristic fragment ions for each individual analyte. An accurate-mass database and a mass spectral library were built in house for searching the 100 target compounds. Broad screening was conducted by comparing the experimentally measured exact mass of precursor and fragment ions, retention time, isotopic pattern, and ionic ratio with the accurate-mass database and by matching the acquired MS/MS spectra against the mass spectral library. The developed methodology was evaluated and validated in terms of limits of detection (LODs), limits of quantitation (LOQs), linearity, stability, accuracy, and matrix effect. The UHPLC-Q-Orbitrap HRMS approach was applied for the analysis of 100 target illicit ingredients in 123 genuine cosmetic samples, and exhibited great potential for high-throughput, sensitive, and reliable screening of multi-class illicit compounds in cosmetics. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. 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.

  3. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery

    OpenAIRE

    Saigusa, Daisuke; Okamura, Yasunobu; Motoike, Ikuko N.; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well p...

  4. Ion Mobility Spectrometry-Mass Spectrometry Coupled with Gas-Phase Hydrogen/Deuterium Exchange for Metabolomics Analyses

    Science.gov (United States)

    Maleki, Hossein; Karanji, Ahmad K.; Majuta, Sandra; Maurer, Megan M.; Valentine, Stephen J.

    2017-09-01

    Ion mobility spectrometry-mass spectrometry (IMS-MS) in combination with gas-phase hydrogen/deuterium exchange (HDX) and collision-induced dissociation (CID) is evaluated as an analytical method for small-molecule standard and mixture characterization. Experiments show that compound ions exhibit unique HDX reactivities that can be used to distinguish different species. Additionally, it is shown that gas-phase HDX kinetics can be exploited to provide even further distinguishing capabilities by using different partial pressures of reagent gas. The relative HDX reactivity of a wide variety of molecules is discussed in light of the various molecular structures. Additionally, hydrogen accessibility scoring (HAS) and HDX kinetics modeling of candidate (in silico) ion structures is utilized to estimate the relative ion conformer populations giving rise to specific HDX behavior. These data interpretation methods are discussed with a focus on developing predictive tools for HDX behavior. Finally, an example is provided in which ion mobility information is supplemented with HDX reactivity data to aid identification efforts of compounds in a metabolite extract. [Figure not available: see fulltext.

  5. Untargeted metabolomics from biological sources using ultraperformance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS).

    Science.gov (United States)

    Snyder, Nathaniel W; Khezam, Maya; Mesaros, Clementina A; Worth, Andrew; Blair, Ian A

    2013-05-20

    Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.

  6. Metabolomics-based approach for ranking the candidate structures of unidentified peaks in capillary electrophoresis time-of-flight mass spectrometry.

    Science.gov (United States)

    Yamamoto, Hiroyuki; Sasaki, Kazunori

    2017-04-01

    One of the technical challenges encountered during metabolomics research is determining the chemical structures of unidentified peaks. We have developed a metabolomics-based chemoinformatics approach for ranking the candidate structures of unidentified peaks. Our approach uses information about the known metabolites detected in samples containing unidentified peaks and involves three discrete steps. The first step involves identifying "precursor/product metabolites" as potential reactants or products derived from the unidentified peaks. In the second step, candidate structures for the unidentified peak are searched against the PubChem database using a molecular formula. These structures are then ranked by structural similarity against precursor/product metabolites and candidate structures. In the third step, the migration time is predicted to refine the candidate structures. Two simulation studies were conducted to highlight the efficacy of our approach, including the use of 20 proteinogenic amino acids as pseudo-unidentified peaks, and leave-one-out experiments for all of the annotated metabolites with and without filtering against the Human Metabolome Database. We also applied our approach to two unidentified peaks in a urine sample, which were identified as glycocyamidine and N-acetylglycine. These results suggest that our approach could be used to identify unidentified peaks during metabolomics analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline

    NARCIS (Netherlands)

    Ranninger, Christina; Rurik, Marc; Limonciel, Alice; Ruzek, Silke; Reischl, Roland; Wilmes, Anja; Jennings, Paul; Hewitt, Philip; Dekant, Wolfgang; Kohlbacher, Oliver; Huber, Christian G

    2015-01-01

    Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial

  8. Diagnostic approach to breast cancer patients based on target metabolomics in saliva by liquid chromatography with tandem mass spectrometry.

    Science.gov (United States)

    Takayama, Takahiro; Tsutsui, Haruhito; Shimizu, Ippei; Toyama, Tatsuya; Yoshimoto, Nobuyasu; Endo, Yumi; Inoue, Koichi; Todoroki, Kenichiro; Min, Jun Zhe; Mizuno, Hajime; Toyo'oka, Toshimasa

    2016-01-15

    Breast cancer is one of the most fearful diseases due to its increasing worldwide prevalence. A number of screening tests has been employed including clinical examinations and mammography. However, another screening method, which is a simple, not embarrassing, and low cost, is highly desired. Based on these findings, we are currently investigating the determination of polyamines including their acetylated structures for the diagnosis of breast cancer patients. We established a diagnostic approach to breast cancer patients based on the ratios of polyamines in saliva by a UPLC-MS/MS analysis. Twelve polyamines including their acetylated form were labeled with DBD-F, separated by a reversed-phase chromatography and detected by a Xevo TQ-S tandem mass spectrometer. Eight polyamines (e.g., SPM, CAD, Ac-SPM, N1-Ac-SPD, N8-Ac-SPD) strongly correlated with the cancer patients. A simple 1-order equation was developed for the discrimination of the breast cancer patients and healthy persons (Y=0.5XSPM-3XAc-SPM-0.15XSPD-3.5XN8-Ac-SPD+0.5XN1-Ac-SPD+0.04XCAD). The concordance rate of the breast cancer patients and the healthy persons by the equation was 88% and 76% on the training set, respectively, whereas those on the validation set was both 88%. The score Y in the equation tended to correlate with the cancer stage of the patients and increased with the more serious conditions. The determination of polyamines in the saliva after the cancer patient operations was also performed to identify the concentration change before and after the surgical treatment. The discriminant analysis using 6 polyamines (i.e., N8-Ac-SPD, N1-Ac-SPD, CAD, DAc-SPD, PUT, and Ac-PUT), which were the most influenced molecules derived from the ROC analysis, was performed using the relative percentage. Both the sensitivity and specificity indicated nearly 80% from the ROC analysis result using the ratio of N8-Ac-SPD/(N1-Ac-SPD+N8-Ac-SPD). The discrimination equation appears to be useful for the diagnosis of

  9. 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.

  10. A composite score combining waist circumference and body mass index more accurately predicts body fat percentage in 6-to 13-year-old children

    NARCIS (Netherlands)

    Aeberli, I.; Gut-Knabenhans, M.; Kusche-Ammann, R.S.; Molinari, L.; Zimmermann, M.B.

    2013-01-01

    Body mass index (BMI) and waist circumference (WC) are widely used to predict % body fat (BF) and classify degrees of pediatric adiposity. However, both measures have limitations. The aim of this study was to evaluate whether a combination of WC and BMI would more accurately predict %BF than either

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Nanoflow-nanospray mass spectrometry metabolomics reveals disruption of the urinary metabolite profiles of HIV-positive patients on combination antiretroviral therapy

    OpenAIRE

    Chetwynd, Andrew J; Samarawickrama, Amanda; Vera, Jaime H.; Bremner, Stephen A; Abdul-Sada, Alaa; Gilleece, Yvonne; Holt, Stephen G.; Hill, Elizabeth M

    2016-01-01

    Background: The use of combination antiretroviral therapy (cART) has substantially improved the outlook for patients with HIV infection. However, lifelong exposure to cART is also associated with adverse metabolic changes and an enhanced risk of renal, hepatic and cardiovascular dysfunction. This study investigated disruptions of the urinary metabolome of cART-exposed patients, thereby furthering our understanding of some of the side effects of pharmaceutical intervention.\\ud \\ud Methods: HIV...

  16. 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.

  17. HEASARC Astronomical Archive: GLIESE2MAS - Gliese Catalog Stars with Accurate Coordinates and 2MASS Cross-Identifications

    Data.gov (United States)

    National Aeronautics and Space Administration — This table contains precise epoch 2000 coordinates and cross-identifications to sources in the 2MASS Point Source Catalog for nearly all stars in the Gliese,...

  18. 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.

  19. Metabolomics Study of Resina Draconis on Myocardial Ischemia Rats Using Ultraperformance Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry Combined with Pattern Recognition Methods and Metabolic Pathway Analysis.

    Science.gov (United States)

    Qi, Yunpeng; Gu, Haiwei; Song, Yunlong; Dong, Xin; Liu, Aijun; Lou, Ziyang; Fan, Guorong; Chai, Yifeng

    2013-01-01

    Resina draconis (bright red resin isolated from Dracaena cochinchinensis, RD) has been clinically used for treatment of myocardial ischemia (MI) for many years. However, the mechanisms of its pharmacological action on MI are still poorly understood. This study aimed to characterize the plasma metabolic profiles of MI and investigate the mechanisms of RD on MI using ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry-based metabolomics combined with pattern recognition methods and metabolic pathway analysis. Twenty metabolite markers characterizing metabolic profile of MI were revealed, which were mainly involved in aminoacyl-tRNA biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis, vascular smooth muscle contraction, sphingolipid metabolism, and so forth. After RD treatment, however, levels of seven MI metabolite markers, including phytosphingosine, sphinganine, acetylcarnitine, cGMP, cAMP, L-tyrosine, and L-valine, were turned over, indicating that RD is likely to alleviate MI through regulating the disturbed vascular smooth muscle contraction, sphingolipid metabolism, phenylalanine metabolism, and BCAA metabolism. To our best knowledge, this is the first comprehensive study to investigate the mechanisms of RD for treating MI, from a metabolomics point of view. Our findings are very valuable to gain a better understanding of MI metabolic profiles and provide novel insights for exploring the mechanisms of RD on MI.

  20. Metabolomics Study of Resina Draconis on Myocardial Ischemia Rats Using Ultraperformance Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry Combined with Pattern Recognition Methods and Metabolic Pathway Analysis

    Directory of Open Access Journals (Sweden)

    Yunpeng Qi

    2013-01-01

    Full Text Available Resina draconis (bright red resin isolated from Dracaena cochinchinensis, RD has been clinically used for treatment of myocardial ischemia (MI for many years. However, the mechanisms of its pharmacological action on MI are still poorly understood. This study aimed to characterize the plasma metabolic profiles of MI and investigate the mechanisms of RD on MI using ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry-based metabolomics combined with pattern recognition methods and metabolic pathway analysis. Twenty metabolite markers characterizing metabolic profile of MI were revealed, which were mainly involved in aminoacyl-tRNA biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis, vascular smooth muscle contraction, sphingolipid metabolism, and so forth. After RD treatment, however, levels of seven MI metabolite markers, including phytosphingosine, sphinganine, acetylcarnitine, cGMP, cAMP, L-tyrosine, and L-valine, were turned over, indicating that RD is likely to alleviate MI through regulating the disturbed vascular smooth muscle contraction, sphingolipid metabolism, phenylalanine metabolism, and BCAA metabolism. To our best knowledge, this is the first comprehensive study to investigate the mechanisms of RD for treating MI, from a metabolomics point of view. Our findings are very valuable to gain a better understanding of MI metabolic profiles and provide novel insights for exploring the mechanisms of RD on MI.

  1. 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.

  2. 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

  3. 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.

  4. Accurate measurements of experimental parameters in supercritical fluid chromatography. I. Extent of variations of the mass and volumetric flow rates.

    Science.gov (United States)

    Tarafder, Abhijit; Guiochon, Georges

    2013-04-12

    Previous reports have highlighted the influence of the properties of the mobile phase flow rate on the column performance achieved in supercritical fluid chromatography (SFC). In SFC both the mass and the volumetric flow rates have unique influences on the chromatographic performance and the determination of their exact values is critical. It is well understood that the mass flow rate stays constant along an SFC system whereas the volumetric flow rate may vary considerably, but the extent of these variations and the role of the individual operating parameters in influencing these variations have not been clearly reported yet. The factors that control the mass and the volumetric flow rates in an SFC system are discussed and the possible extent of variations of these flow rates under different operating pressures and temperatures are demonstrate quantitatively. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Negative electrospray ionisation of fluorotelomer alcohols (FTOH) and FTOH-derived acrylate surfactants by liquid chromatography coupled to accurate (tandem) mass spectrometry

    DEFF Research Database (Denmark)

    Trier, Xenia; Christensen, Jan H.; Niessen, Wilfried M. A.

    Fluorotelomer alcohols (FTOHs) are used to synthesize fluorinated surfactants, which form bioaccumulative perfluorinated degradation products, which are toxic to humans and the environment. To facilitate screening for FTOH-derived surfactants by LC-ESI–-MS, we identified product ions of FTOHs, an......, and propose FTOH fragmentation pathways on two MS instruments. By extraction of FTOH basepeak ions from accurate mass spectra, homologues series of peaks showed up in an industrial blend of FTOH-derived fluoroacrylates used in food paper packaging....

  6. Metabolomic analysis identifies altered metabolic pathways in Multiple Sclerosis.

    Science.gov (United States)

    Poddighe, Simone; Murgia, Federica; Lorefice, Lorena; Liggi, Sonia; Cocco, Eleonora; Marrosu, Maria Giovanna; Atzori, Luigi

    2017-12-01

    Multiple sclerosis (MS) is a chronic, demyelinating disease that affects the central nervous system and is characterized by a complex pathogenesis and difficult management. The identification of new biomarkers would be clinically useful for more accurate diagnoses and disease monitoring. Metabolomics, the identification of small endogenous molecules, offers an instantaneous molecular snapshot of the MS phenotype. Here the metabolomic profiles (utilizing plasma from patients with MS) were characterized with a Gas cromatography-mass spectrometry-based platform followed by a multivariate statistical analysis and comparison with a healthy control (HC) population. The obtained partial least square discriminant analysis (PLS-DA) model identified and validated significant metabolic differences between individuals with MS and HC (R2X=0.223, R2Y=0.82, Q2=0.562; p<0.001). Among discriminant metabolites phosphate, fructose, myo-inositol, pyroglutamate, threonate, l-leucine, l-asparagine, l-ornithine, l-glutamine, and l-glutamate were correctly identified, and some resulted as unknown. A receiver operating characteristic (ROC) curve with AUC 0.84 (p=0.01; CI: 0.75-1) generated with the concentrations of the discriminant metabolites, supported the strength of the model. Pathway analysis indicated asparagine and citrulline biosynthesis as the main canonical pathways involved in MS. Changes in the citrulline biosynthesis pathway suggests the involvement of oxidative stress during neuronal damage. The results confirmed metabolomics as a useful approach to better understand the pathogenesis of MS and to provide new biomarkers for the disease to be used together with clinical data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Accurate quantitation of pentaerythritol tetranitrate and its degradation products using liquid chromatography-atmospheric pressure chemical ionization-mass spectrometry

    NARCIS (Netherlands)

    Brust, H.; Asten, A. van; Koeberg, M.; Dalmolen, J.; Heijden, A.E.D.M. van der; Schoenmakers, P.

    2014-01-01

    After an explosion of pentaerythritol tetranitrate (PETN), its degradation products pentaerythritol trinitrate (PETriN), dinitrate (PEDiN) and mononitrate (PEMN) were detected using liquid chromatography-atmospheric-pressure chemical-ionization-mass spectrometry (LC-APCI-MS). Discrimination between

  8. Accurate and precise 40Ar/39Ar dating by high-resolution, multi-collection, mass spectrometry

    DEFF Research Database (Denmark)

    Storey, Michael; Rivera, Tiffany; Flude, Stephanie

    New generation, high resolution, multi-collector noble gas mass spectrometers equipped with ion-counting electron multipliers provide opportunities for improved accuracy and precision in 40Ar/39Ar dating. Here we report analytical protocols and age cross-calibration studies using a NU-Instruments......New generation, high resolution, multi-collector noble gas mass spectrometers equipped with ion-counting electron multipliers provide opportunities for improved accuracy and precision in 40Ar/39Ar dating. Here we report analytical protocols and age cross-calibration studies using a NU......-Instruments multi-collector Noblesse noble gas mass spectrometer configured with a faraday detector and three ion-counting electron multipliers. The instrument has the capability to measure several noble gas isotopes simultaneously and to change measurement configurations instantaneously by the use of QUAD lenses...... (zoom optics). The Noblesse offer several advantages over previous generation noble gas mass spectrometers and is particularly suited for single crystal 40Ar/39Ar dating because of: (i) improved source sensitivity (ii) ion-counting electron multipliers, which have much lower signal to noise ratios than...

  9. Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods

    Energy Technology Data Exchange (ETDEWEB)

    Bingol, Kerem; Brüschweiler, Rafael

    2017-02-01

    Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.

  10. Metabolomic approaches for orange origin discrimination by ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry.

    Science.gov (United States)

    Díaz, Ramon; Pozo, Oscar J; Sancho, Juan V; Hernández, Félix

    2014-08-15

    In this work, hybrid quadrupole time-of-flight mass spectrometer (QTOF MS) coupled to ultra high performance liquid chromatography (UHPLC) has been used for biomarkers identification for correct authentication of Valencia (Spain) oranges. Differentiation from foreign Argentinean, Brazilian and South African oranges has been carried out using XCMS application and multivariate analysis to UHPLC-(Q)TOF MS data acquired in both, positive and negative ionisation modes. Several markers have been found and corroborated by analysing two seasons samples. A seasonal independent marker was found and its structure elucidated using accurate mass data and MS(E) fragmentation spectrum information. Empirical formula was searched in Reaxys database applying sub-structure filtering from the fragments obtained. Three possible structures were found and citrusin D, a compound present in sweet oranges, has been identified as the most plausible as it fits better with the product ion scan performed for this compound. As a result of data obtained in this work, citrusin D is suggested as a potential marker to distinguish the geographic origin of oranges. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. Non-targeted determination of (13)C-labeling in the Methylobacterium extorquens AM1 metabolome using the two-dimensional mass cluster method and principal component analysis.

    Science.gov (United States)

    Reaser, Brooke C; Yang, Song; Fitz, Brian D; Parsons, Brendon A; Lidstrom, Mary E; Synovec, Robert E

    2016-02-05

    A novel analytical workflow is presented for the analysis of time-dependent (13)C-labeling of the metabolites in the methylotrophic bacterium Methylobacterium extorquens AM1 using gas chromatography time-of-flight mass spectrometry (GC-TOFMS). Using (13)C-methanol as the substrate in a time course experiment, the method provides an accurate determination of the number of carbons converted to the stable isotope. The method also extracts a quantitative isotopic dilution time course profile for (13)C uptake of each metabolite labeled that could in principle be used to obtain metabolic flux rates. The analytical challenges encountered require novel analytical platforms and chemometric techniques. GC-TOFMS offers advanced separation of mixtures, identification of individual components, and high data density for the application of advanced chemometrics. This workflow combines both novel and traditional chemometric techniques, including the recently reported two-dimensional mass cluster plot method (2D m/z cluster plot method) as well as principal component analysis (PCA). The 2D m/z cluster plot method effectively indexed all metabolites present in the sample and deconvoluted metabolites at ultra-low chromatographic resolution (RS≈0.04). Using the pure mass spectra extracted, two PCA models were created. Firstly, PCA was used on the first and last time points of the time course experiment to determine and quantify the extent of (13)C uptake. Secondly, PCA modeled the full time course in order to quantitatively extract the time course profile for each metabolite. The 2D m/z cluster plot method found 152 analytes (metabolites and reagent peaks), with 54 pure analytes, and 98 were convoluted, with 65 of the 98 requiring mathematical deconvolution. Of the 152 analytes surveyed, 83 were metabolites determined by the PCA model to have incorporated (13)C while 69 were determined to be either metabolites or reagent peaks that remained unlabeled. Copyright © 2015 Elsevier B

  17. Accurate Protein Complex Retrieval by Affinity Enrichment Mass Spectrometry (AE-MS) Rather than Affinity Purification Mass Spectrometry (AP-MS)

    OpenAIRE

    Keilhauer, E.; Hein, M; Mann, M

    2015-01-01

    Protein?protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from backgroun...

  18. Isotopic ratio outlier analysis global metabolomics of Caenorhabditis elegans.

    Science.gov (United States)

    Stupp, Gregory S; Clendinen, Chaevien S; Ajredini, Ramadan; Szewc, Mark A; Garrett, Timothy; Menger, Robert F; Yost, Richard A; Beecher, Chris; Edison, Arthur S

    2013-12-17

    We demonstrate the global metabolic analysis of Caenorhabditis elegans stress responses using a mass-spectrometry-based technique called isotopic ratio outlier analysis (IROA). In an IROA protocol, control and experimental samples are isotopically labeled with 95 and 5% (13)C, and the two sample populations are mixed together for uniform extraction, sample preparation, and LC-MS analysis. This labeling strategy provides several advantages over conventional approaches: (1) compounds arising from biosynthesis are easily distinguished from artifacts, (2) errors from sample extraction and preparation are minimized because the control and experiment are combined into a single sample, (3) measurement of both the molecular weight and the exact number of carbon atoms in each molecule provides extremely accurate molecular formulas, and (4) relative concentrations of all metabolites are easily determined. A heat-shock perturbation was conducted on C. elegans to demonstrate this approach. We identified many compounds that significantly changed upon heat shock, including several from the purine metabolism pathway. The metabolomic response information by IROA may be interpreted in the context of a wealth of genetic and proteomic information available for C. elegans . Furthermore, the IROA protocol can be applied to any organism that can be isotopically labeled, making it a powerful new tool in a global metabolomics pipeline.

  19. Rapid and Accurate Identification of Animal Species in Natural Leather Goods by Liquid Chromatography/Mass Spectrometry.

    Science.gov (United States)

    Izuchi, Yukari; Takashima, Tsuneo; Hatano, Naoya

    2016-01-01

    The demand for leather goods has grown globally in recent years. Industry revenue is forecast to reach $91.2 billion by 2018. There is an ongoing labelling problem in the leather items market, in that it is currently impossible to identify the species that a given piece of leather is derived from. To address this issue, we developed a rapid and simple method for the specific identification of leather derived from cattle, horses, pigs, sheep, goats, and deer by analysing peptides produced by the trypsin-digestion of proteins contained in leather goods using liquid chromatography/mass spectrometry. We determined species-specific amino acid sequences by liquid chromatography/tandem mass spectrometry analysis using the Mascot software program and demonstrated that collagen α-1(I), collagen α-2(I), and collagen α-1(III) from the dermal layer of the skin are particularly useful in species identification.

  20. CLASH-VLT: Constraints on the Dark Matter Equation of State from Accurate Measurements of Galaxy Cluster Mass Profiles

    Science.gov (United States)

    Sartoris, Barbara; Biviano, Andrea; Rosati, Piero; Borgani, Stefano; Umetsu, Keiichi; Bartelmann, Matthias; Girardi, Marisa; Grillo, Claudio; Lemze, Doron; Zitrin, Adi; Balestra, Italo; Mercurio, Amata; Nonino, Mario; Postman, Marc; Czakon, Nicole; Bradley, Larry; Broadhurst, Tom; Coe, Dan; Medezinski, Elinor; Melchior, Peter; Meneghetti, Massimo; Merten, Julian; Annunziatella, Marianna; Benitez, Narciso; Czoske, Oliver; Donahue, Megan; Ettori, Stefano; Ford, Holland; Fritz, Alexander; Kelson, Dan; Koekemoer, Anton; Kuchner, Ulrike; Lombardi, Marco; Maier, Christian; Moustakas, Leonidas A.; Munari, Emiliano; Presotto, Valentina; Scodeggio, Marco; Seitz, Stella; Tozzi, Paolo; Zheng, Wei; Ziegler, Bodo

    2014-03-01

    A pressureless scenario for the dark matter (DM) fluid is a widely adopted hypothesis, despite the absence of direct observational evidence. According to general relativity, the total mass-energy content of a system shapes the gravitational potential well, but different test particles perceive this potential in different ways depending on their properties. Cluster galaxy velocities, being Ltc, depend solely on the gravitational potential, whereas photon trajectories reflect the contributions from the gravitational potential plus a relativistic-pressure term that depends on the cluster mass. We exploit this phenomenon to constrain the equation of state (EoS) parameter of the fluid, primarily DM, contained in galaxy clusters. We use complementary information provided by the kinematic and lensing mass profiles of the galaxy cluster MACS 1206.2-0847 at z = 0.44, as obtained in an extensive imaging and spectroscopic campaign within the Cluster Lensing And Supernova survey with Hubble. The unprecedented high quality of our data set and the properties of this cluster are well suited to determine the EoS parameter of the cluster fluid. Since baryons contribute at most 15% to the total mass in clusters and their pressure is negligible, the EoS parameter we derive describes the behavior of the DM fluid. We obtain the most stringent constraint on the DM EoS parameter to date, w = (pr + 2 pt )/(3 c 2ρ) = 0.00 ± 0.15 (stat) ± 0.08 (syst), averaged over the radial range 0.5 Mpc pr and pt are the radial and tangential pressure, and ρ is the density. We plan to further improve our constraint by applying the same procedure to all clusters from the ongoing Cluster Lensing And Supernova Survey with Hubble-Very Large Telescope program.

  1. 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.

  2. 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.

  3. Non-targeted screening for contaminants in paper and board food-contact materials using effect-directed analysis and accurate mass spectrometry

    DEFF Research Database (Denmark)

    Bengtström, Linda; Rosenmai, Anna Kjerstine; Trier, Xenia

    2016-01-01

    Due to large knowledge gaps in chemical composition and toxicological data for substances involved, paper and board food-contact materials (P&B FCM) have been emerging as a FCM type of particular concern for consumer safety. This study describes the development of a step-by-step strategy, including......R) activity. These fractions were analysed by gas chromatography (GC) and ultra-HPLC (UHPLC) coupled to quadrupole time-of-flight mass spectrometers (QTOF MS) in order tentatively to identify substances. The elemental composition was determined for peaks above a threshold, and compared with entries...... in a commercial mass spectral library for GC-MS (GC-EI-QTOF MS) analysis and an in-house built library of accurate masses for substances known to be used in P&B packaging for UHPLC-QTOF analysis. Of 75 tentatively identified substances, 15 were initially selected for further testing in vitro; however, only seven...

  4. Accurate mass measurements of {sup 26}Ne, {sup 26-3}Na, {sup 29-33}Mg performed with the MISTRAL spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    Gaulard, C. [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France)]. E-mail: gaulard@csnsm.in2p3.fr; Audi, G. [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France); Bachelet, C. [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France); Lunney, D. [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France); Saint Simon, M. de [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France); Thibault, C. [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France); Vieira, N. [Centre de Spectrometrie Nucleaire et de Spectrometrie de Masse, CSNSM, IN2P3-CNRS and UPS, Batiment 108, F-91405 Orsay Campus (France)

    2006-02-20

    The minuteness of the nuclear binding energy requires that mass measurements be highly precise and accurate. Here we report on new measurements of {sup 29-33}Mg and {sup 26}Na performed with the MISTRAL mass spectrometer at CERN's ISOLDE facility. Since mass measurements are prone to systematic errors, considerable effort has been devoted to their evaluation and elimination in order to achieve accuracy and not only precision. We have therefore conducted a campaign of measurements for calibration and error evaluation. As a result, we now have a satisfactory description of the MISTRAL calibration laws and error budget. We have applied our new understanding to previous measurements of {sup 26}Ne, {sup 26-3}Na and {sup 29,32}Mg for which re-evaluated values are reported.

  5. Accurate calibration of a molecular beam time-of-flight mass spectrometer for on-line analysis of high molecular weight species.

    Science.gov (United States)

    Apicella, B; Wang, X; Passaro, M; Ciajolo, A; Russo, C

    2016-10-15

    Time-of-Flight (TOF) Mass Spectrometry is a powerful analytical technique, provided that an accurate calibration by standard molecules in the same m/z range of the analytes is performed. Calibration in a very large m/z range is a difficult task, particularly in studies focusing on the detection of high molecular weight clusters of different molecules or high molecular weight species. External calibration is the most common procedure used for TOF mass spectrometric analysis in the gas phase and, generally, the only available standards are made up of mixtures of noble gases, covering a small mass range for calibration, up to m/z 136 (higher mass isotope of xenon). In this work, an accurate calibration of a Molecular Beam Time-of Flight Mass Spectrometer (MB-TOFMS) is presented, based on the use of water clusters up to m/z 3000. The advantages of calibrating a MB-TOFMS with water clusters for the detection of analytes with masses above those of the traditional calibrants such as noble gases were quantitatively shown by statistical calculations. A comparison of the water cluster and noble gases calibration procedures in attributing the masses to a test mixture extending up to m/z 800 is also reported. In the case of the analysis of combustion products, another important feature of water cluster calibration was shown, that is the possibility of using them as "internal standard" directly formed from the combustion water, under suitable experimental conditions. The water clusters calibration of a MB-TOFMS gives rise to a ten-fold reduction in error compared to the traditional calibration with noble gases. The consequent improvement in mass accuracy in the calibration of a MB-TOFMS has important implications in various fields where detection of high molecular mass species is required. In combustion products analysis, it is also possible to obtain a new calibration spectrum before the acquisition of each spectrum, only modifying some operative conditions. Copyright © 2016

  6. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond.

    Science.gov (United States)

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-06-02

    Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the 'Warburg effect'. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

  7. Using MALDI-TOF mass spectrometry as a rapid and accurate diagnostic tool in infective endocarditis: a case report of a patient with mitral valve infective endocarditis caused by Abiotrophia defectiva

    DEFF Research Database (Denmark)

    Holler, Jon Gitz; Pedersen, Line; Calum, Henrik

    2011-01-01

    A case of infective endocarditis caused by Abiotrophia defectiva is presented. The use of MALDI-TOF mass spectrometry as a rapid and accurate diagnostic tool in infective endocarditis is discussed.......A case of infective endocarditis caused by Abiotrophia defectiva is presented. The use of MALDI-TOF mass spectrometry as a rapid and accurate diagnostic tool in infective endocarditis is discussed....

  8. 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...

  9. 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.

  10. 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...

  11. 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...

  12. Nontargeted Modification-Specific Metabolomics Investigation of Glycosylated Secondary Metabolites in Tea (Camellia sinensis L.) Based on Liquid Chromatography-High-Resolution Mass Spectrometry.

    Science.gov (United States)

    Dai, Weidong; Tan, Junfeng; Lu, Meiling; Xie, Dongchao; Li, Pengliang; Lv, Haipeng; Zhu, Yin; Guo, Li; Zhang, Yue; Peng, Qunhua; Lin, Zhi

    2016-09-07

    Glycosylation on small molecular metabolites modulates a series of biological events in plants. However, a large number of glycosides have not been discovered and investigated using -omics approaches. Here, a general strategy named "nontargeted modification-specific metabolomics" was applied to map the glycosylation of metabolites. The key aspect of this method is to adopt in-source collision-induced dissociation to dissociate the glycosylated metabolite, causing a characteristic neutral loss pattern, which acts as an indicator for the glycosylation identification. In an exemplary application in green teas, 120 glucosylated/galactosylated, 38 rhamnosylated, 21 rutinosylated, and 23 primeverosylated metabolites were detected simultaneously. Among them, 61 glycosylated metabolites were putatively identified according to current tea metabolite databases. Thanks to the annotations of glycosyl moieties in advance, the method aids metabolite identifications. An additional 40 novel glycosylated metabolites were tentatively elucidated. This work provides a feasible strategy to discover and identify novel glycosylated metabolites in plants.

  13. Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.

    Science.gov (United States)

    Abelin, Jennifer G; Keskin, Derin B; Sarkizova, Siranush; Hartigan, Christina R; Zhang, Wandi; Sidney, John; Stevens, Jonathan; Lane, William; Zhang, Guang Lan; Eisenhaure, Thomas M; Clauser, Karl R; Hacohen, Nir; Rooney, Michael S; Carr, Steven A; Wu, Catherine J

    2017-02-21

    Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. The link between quasar broad-line region and galaxy-scale outflows and accurate CIV-based black hole masses

    Science.gov (United States)

    Coatman, Liam; Hewett, Paul C.; Banerji, Manda; Richards, Gordon T.; Hennawi, Joseph F.; Prochaska, Jason X.

    2017-01-01

    Accurate black-hole (BH) mass estimates for high-redshift (z>2) quasars are essential for better understanding the relationship between super-massive BH accretion and star formation. Progress is currently limited by the large systematic errors in virial BH-masses derived from the CIV broad emission line, which is often significantly blueshifted relative to systemic, most likely due to outflowing gas in the quasar broad-line region. We have assembled Balmer-line based BH masses for a large sample of 230 high-luminosity (1045.5-1048 ergs-1), redshift 1.5CIV blueshifts seen in the quasar population. We find the CIV-based BH-masses to be larger than the corresponding Balmer line-based masses by almost an order of magnitude at the most extreme blueshifts (˜5000 kms-1). An empirical correction to the CIV BH-masses is derived, which depends only on the properties of the CIV line itself (i.e. blueshift and FWHM). We show that this new correction now enables the derivation of un-biased CIV-based virial BH masses for the majority of high-luminosity, high-redshift quasars.In the same high-luminosity quasar sample, we find the narrow [OIII] emission to be weaker and more asymmetric than is generally found in lower-luminosity AGN and that a significant fraction of our quasars have exceptionally broad (FWHM > 3000 kms-1), blueshifted [OIII] emission. We find a strong correlation between the CIV and [OIII] blueshifts. This correlation holds even for quasars at fixed luminosity and suggests that broad line region outflows in quasars are connected to galaxy-scale winds.

  15. 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.

  16. Accurate analysis of trace earthy-musty odorants in water by headspace solid phase microextraction gas chromatography-mass spectrometry.

    Science.gov (United States)

    Ma, Kang; Zhang, Jin Na; Zhao, Min; He, Ya Juan

    2012-06-01

    A simple and sensitive method was developed for the simultaneous separation and determination of trace earthy-musty compounds including geosmin, 2-methylisoborneol, 2-isobutyl-3-methoxypyrazine, 2-isopropyl-3-methoxypyrazine, 2,3,4-trichloroanisole, 2,4,6-trichloroanisole, and 2,3,6-trichloroanisole in water samples. This method combined headspace solid-phase microextraction (HS-SPME) with gas chromatography-mass spectrometry and used naphthalene-d(8) as internal standard. A divinylbenzene/carboxen/polydimethylsiloxane fiber exposing at 90°C for 30 min provided effective sample enrichment in HS-SPME. These compounds were separated by a DB-1701MS capillary column and detected in selected ion monitoring mode within 12 min. The method showed a good linearity from 1 to 100 ng L(-1) and detection limits within (0.25-0.61 ng L(-1)) for all compounds. Using naphthalene-d(8) as the internal standard, the intra-day relative standard deviation (RSD) was within (2.6-3.4%), while the inter-day RSD was (3.5-4.9%). Good recoveries were obtained for tap water (80.5-90.6%), river water (81.5-92.4%), and lake water (83.5-95.2%) spiked at 10 ng L(-1). Compared with other methods using HS-SPME for determination of odor compounds in water samples, this present method had more analytes, better precision, and recovery. This method was successfully applied for analysis of earthy-musty odors in water samples from different sources. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. A Metabolomic Approach Applied to a Liquid Chromatography Coupled to High-Resolution Tandem Mass Spectrometry Method (HPLC-ESI-HRMS/MS): Towards the Comprehensive Evaluation of the Chemical Composition of Cannabis Medicinal Extracts.

    Science.gov (United States)

    Citti, Cinzia; Battisti, Umberto Maria; Braghiroli, Daniela; Ciccarella, Giuseppe; Schmid, Martin; Vandelli, Maria Angela; Cannazza, Giuseppe

    2017-09-15

    Cannabis sativa L. is a powerful medicinal plant and its use has recently increased for the treatment of several pathologies. Nonetheless, side effects, like dizziness and hallucinations, and long-term effects concerning memory and cognition, can occur. Most alarming is the lack of a standardised procedure to extract medicinal cannabis. Indeed, each galenical preparation has an unknown chemical composition in terms of cannabinoids and other active principles that depends on the extraction procedure. This study aims to highlight the main differences in the chemical composition of Bediol® extracts when the extraction is carried out with either ethyl alcohol or olive oil for various times (0, 60, 120 and 180 min for ethyl alcohol, and 0, 60, 90 and 120 min for olive oil). Cannabis medicinal extracts (CMEs) were analysed by liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) using an untargeted metabolomics approach. The data sets were processed by unsupervised multivariate analysis. Our results suggested that the main difference lies in the ratio of acid to decarboxylated cannabinoids, which dramatically influences the pharmacological activity of CMEs. Minor cannabinoids, alkaloids, and amino acids contributing to this difference are also discussed. The main cannabinoids were quantified in each extract applying a recently validated LC-MS and LC-UV method. Notwithstanding the use of a standardised starting plant material, great changes are caused by different extraction procedures. The metabolomics approach is a useful tool for the evaluation of the chemical composition of cannabis extracts. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  18. Comparative metabolomics analysis on invigorating blood circulation for herb pair Gui-Hong by ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry and pattern recognition approach.

    Science.gov (United States)

    Li, Shujiao; Lin, Hang; Tang, Yuping; Li, Weixia; Shen, Juan; Kai, Jun; Yue, Shijun; Shang, Guanxiong; Zhu, Zhenhua; Shang, Erxin; Zhang, Changbin; Zhang, Li; Yan, Hui; Liu, Pei; Duan, Jin-ao

    2015-03-25

    The compatibility of Angelicae Sinensis Radix (Danggui, DG) and Flos Carthami (Honghua, HH), a famous herb pair Gui-Hong (GH), can produce synergistic and promoting blood effects. Although some physiological and pathological function parameters of the acute blood stasis have been investigated, little information about the changes of small metabolites in biofluids has been reported. In present study, global metabolic profiling with ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) combined with pattern recognition method was performed to discover the underlying blood-activating regulation mechanisms of DG, HH and GH on the acute blood stasis rats induced by subcutaneous injection of adrenaline hydrochloride and ice water bath. The total 14 metabolites (10 in urine and 4 in plasma), up regulated or down regulated (Pblood stasis progress. These promising identified biomarkers underpin the metabolic pathway including phenylalanine metabolism, sphingolipid metabolism, arachidonic acid metabolism and arginine and proline metabolism are disturbed in the acute blood stasis rats, which identified by using pathway analysis with MetPA. The altered metabolites and hemorheological indexes could be regulated closer to normal level after DG, HH and GH intervention. In term of activate blood circulation function, GH was the most effective as shown by the relative distance in PLS-DA score plots and relative intensity of metabolomics trategy, reflecting the synergic action between Danggui and Honghua. The results demonstrated that biofluids metabolomics was a powerful tool in clinical diagnosis and treatment of syndrome of blood stasis for providing information on changes in metabolites pathways. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. 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.

  20. Combined use of medium mass resolution and desolvation introduction system for accurate plutonium determination in the femtogram range by inductively coupled plasma-sector-field mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Pointurier, Fabien, E-mail: fabien.pointurier@cea.fr; Pottin, Anne-Claire; Hemet, Philippe; Hubert, Amelie

    2011-03-15

    Formation of a polyatomic species made of an atom of a heavy element like lead, mercury or iridium, and atoms abundant in plasma (argon, nitrogen, oxygen, and hydrogen) when using an inductively coupled plasma-sector-field mass spectrometer (ICP-SFMS) may lead to false detection of femtograms (fg) of plutonium or bias in the measured concentrations. Mathematical corrections, based on the measurement of heavy element concentrations in the sample solutions and determination of the extents of formation of the polyatomic interferences, are efficient but time-consuming and degrade detection limits. We describe and discuss a new method based on the combination of, on the one hand, medium mass resolution (MR) of the ICP-SFMS to separate plutonium isotopes physically from interfering polyatomic species, and, on the other, use of a desolvation introduction system (DIS) to enhance sensitivity, thus partly compensating for the loss of transmission due to use of a higher resolution. Plutonium peaks are perfectly separated from the major interfering species (PbO{sub 2}, HgAr, and IrO{sub 3}) with a mass resolution of {approx} 4000. The resulting nine-fold transmission loss is partly compensated by a five-fold increase in sensitivity obtained with the DIS and a lower background. The instrumental detection limits for plutonium isotopes, calculated for measurements of pure synthetic solutions, of the new method (known as MR-DIS method) and of the one currently used in the laboratory (LR method), based on a low mass resolution equal to 360, a microconcentric nebulizer and two in-line cooled spray chambers, are roughly equivalent, at around 0.2 fg ml{sup -1}. Regarding the measurement of real-life samples, the results obtained with both methods agree and the corresponding analytical detection limits for plutonium isotopes {sup 239}Pu, {sup 240}Pu and {sup 241}Pu are of a few fg.ml{sup -1} of sample solution, slightly lower with the MR-DIS method than with the current LR method

  1. 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

  2. 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

  3. 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.

  4. Disruption of the prostaglandin metabolome and characterization of the pharmaceutical exposome in fish exposed to wastewater treatment works effluent as revealed by nanoflow-nanospray mass spectrometry-based metabolomics

    OpenAIRE

    David, Arthur; Lange, Anke; Abdul-Sada, Alaa; Tyler, Charles R; Hill, Elizabeth M.

    2016-01-01

    Fish can be exposed to a complex mixture of chemical contaminants, including pharmaceuticals, present in discharges of wastewater treatment works (WwTWs) effluents. There is little information on the effects of effluent exposure on fish metabolism, especially the small molecule signaling compounds which are the biological target of many pharmaceuticals. We applied a newly developed sensitive nanoflow-nanospray mass spectrometry nontargeted profiling technique to identify changes in the exposo...

  5. Challenges of metabolomics in human gut microbiota research.

    Science.gov (United States)

    Smirnov, Kirill S; Maier, Tanja V; Walker, Alesia; Heinzmann, Silke S; Forcisi, Sara; Martinez, Inés; Walter, Jens; Schmitt-Kopplin, Philippe

    2016-08-01

    The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine. Copyright © 2016 Elsevier GmbH. All rights reserved.

  6. Metabolomics: the "new clinical chemistry" for personalized neonatal medicine.

    Science.gov (United States)

    Antonucci, R; Atzori, L; Barberini, L; Fanos, V

    2010-06-01

    Metabolomics is a new approach based on the systematic study of the full complement of metabolites in a biological sample. This technology consists of two sequential steps: (1) an experimental technique, based on mass spectrometry or nuclear magnetic resonance (NMR) spectroscopy, designed to profile low molecular weight compounds, and (2) multivariate data analysis. Metabolomic analysis of biofluids or tissues has been successfully used in the fields of physiology, diagnostics, functional genomics, pharmacology, toxicology and nutrition. Recent studies have evaluated how physiological variables or pathological conditions can affect metabolomic profiles of different biofluids in pediatric populations. Little is known about the overall metabolic status of the term and preterm neonate. On the other hand, the management of sick or preterm newborns might be improved if more information on perinatal/neonatal maturational processes and their metabolic background were available. At present, the use of metabolomics in Neonatology is still in the pioneering phase. Meaningful diagnostic information and simple, non-invasive collection techniques make urine a particularly suitable biofluid for metabolomic approach in neonatal medicine. Using NMR-based metabolomic analysis of urine, distinct metabolic patterns have been shown to be associated with different classes of gestational age in a population of preterm and term infants. Together with genomics and proteomics, metabolomics appears to be a promising tool in Neonatology for the monitoring of postnatal metabolic maturation, the identification of biomarkers as early predictors of outcome, the diagnosis and monitoring of various diseases and the "tailored" management of neonatal disorders.

  7. An accurate method for microanalysis of carbon monoxide in putrid postmortem blood by head-space gas chromatography-mass spectrometry (HS/GC/MS).

    Science.gov (United States)

    Hao, Hongxia; Zhou, Hong; Liu, Xiaopei; Zhang, Zhong; Yu, Zhongshan

    2013-06-10

    Carbon monoxide (CO) may be the cause of more than half the fatal poisonings reported in many countries, with some of these cases under-reported or misdiagnosed by medical professionals. Therefore, an accurate and reliable analytical method to measure blood carboxyhemoglobin level (COHb%), in the 1% to lethal range, is essential for correct diagnosis. Herein a method was established, i.e. head-space gas chromatography-mass spectrometry (HS/GC/MS) that has numerous advantages over other techniques, such as UV spectrometry, for determination of COHb%. There was a linear relationship (R(2)=0. 9995) between the peak area for CO and the COHb% in blood. Using a molecular sieve-packed column, CO levels in the air down to 0.01% and COHb% levels in small blood samples down to 0.2% could be quantitated rapidly and accurately. Furthermore, this method showed good reproducibility with a relative standard deviation for COHb% of <1%. Therefore, this technique provides an accurate and reliable method for determining CO and COHb% levels and may prove useful for investigation of deaths potentially related to CO exposure. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  8. Mass Spectrometry-based Workflow for Accurate Quantification of Escherichia coli Enzymes: How Proteomics Can Play a Key Role in Metabolic Engineering*

    Science.gov (United States)

    Trauchessec, Mathieu; Jaquinod, Michel; Bonvalot, Aline; Brun, Virginie; Bruley, Christophe; Ropers, Delphine; de Jong, Hidde; Garin, Jérôme; Bestel-Corre, Gwenaëlle; Ferro, Myriam

    2014-01-01

    Metabolic engineering aims to design high performance microbial strains producing compounds of interest. This requires systems-level understanding; genome-scale models have therefore been developed to predict metabolic fluxes. However, multi-omics data including genomics, transcriptomics, fluxomics, and proteomics may be required to model the metabolism of potential cell factories. Recent technological advances to quantitative proteomics have made mass spectrometry-based quantitative assays an interesting alternative to more traditional immuno-affinity based approaches. This has improved specificity and multiplexing capabilities. In this study, we developed a quantification workflow to analyze enzymes involved in central metabolism in Escherichia coli (E. coli). This workflow combined full-length isotopically labeled standards with selected reaction monitoring analysis. First, full-length 15N labeled standards were produced and calibrated to ensure accurate measurements. Liquid chromatography conditions were then optimized for reproducibility and multiplexing capabilities over a single 30-min liquid chromatography-MS analysis. This workflow was used to accurately quantify 22 enzymes involved in E. coli central metabolism in a wild-type reference strain and two derived strains, optimized for higher NADPH production. In combination with measurements of metabolic fluxes, proteomics data can be used to assess different levels of regulation, in particular enzyme abundance and catalytic rate. This provides information that can be used to design specific strains used in biotechnology. In addition, accurate measurement of absolute enzyme concentrations is key to the development of predictive kinetic models in the context of metabolic engineering. PMID:24482123

  9. Decision peptide-driven: a free software tool for accurate protein quantification using gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry.

    Science.gov (United States)

    Santos, Hugo M; Reboiro-Jato, Miguel; Glez-Peña, Daniel; Nunes-Miranda, J D; Fdez-Riverola, Florentino; Carvallo, R; Capelo, J L

    2010-09-15

    The decision peptide-driven tool implements a software application for assisting the user in a protocol for accurate protein quantification based on the following steps: (1) protein separation through gel electrophoresis; (2) in-gel protein digestion; (3) direct and inverse (18)O-labeling and (4) matrix assisted laser desorption ionization time of flight mass spectrometry, MALDI analysis. The DPD software compares the MALDI results of the direct and inverse (18)O-labeling experiments and quickly identifies those peptides with paralleled loses in different sets of a typical proteomic workflow. Those peptides are used for subsequent accurate protein quantification. The interpretation of the MALDI data from direct and inverse labeling experiments is time-consuming requiring a significant amount of time to do all comparisons manually. The DPD software shortens and simplifies the searching of the peptides that must be used for quantification from a week to just some minutes. To do so, it takes as input several MALDI spectra and aids the researcher in an automatic mode (i) to compare data from direct and inverse (18)O-labeling experiments, calculating the corresponding ratios to determine those peptides with paralleled losses throughout different sets of experiments; and (ii) allow to use those peptides as internal standards for subsequent accurate protein quantification using (18)O-labeling. In this work the DPD software is presented and explained with the quantification of protein carbonic anhydrase. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  10. RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data.

    Science.gov (United States)

    Broeckling, C D; Afsar, F A; Neumann, S; Ben-Hur, A; Prenni, J E

    2014-07-15

    Metabolomic data are frequently acquired using chromatographically coupled mass spectrometry (MS) platforms. For such datasets, the first step in data analysis relies on feature detection, where a feature is defined by a mass and retention time. While a feature typically is derived from a single compound, a spectrum of mass signals is more a more-accurate representation of the mass spectrometric signal for a given metabolite. Here, we report a novel feature grouping method that operates in an unsupervised manner to group signals from MS data into spectra without relying on predictability of the in-source phenomenon. We additionally address a fundamental bottleneck in metabolomics, annotation of MS level signals, by incorporating indiscriminant MS/MS (idMS/MS) data implicitly: feature detection is performed on both MS and idMS/MS data, and feature-feature relationships are determined simultaneously from the MS and idMS/MS data. This approach facilitates identification of metabolites using in-source MS and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation compared to single-feature measures, and decreases false positive annotations of unpredictable phenomenon as novel compounds. This tool is released as a freely available R package, called RAMClustR, and is sufficiently versatile to group features from any chromatographic-spectrometric platform or feature-finding software.

  11. Metabolite identification of triptolide by data-dependent accurate mass spectrometric analysis in combination with online hydrogen/deuterium exchange and multiple data-mining techniques.

    Science.gov (United States)

    Du, Fuying; Liu, Ting; Liu, Tian; Wang, Yongwei; Wan, Yakun; Xing, Jie

    2011-10-30

    Triptolide (TP), the primary active component of the herbal medicine Tripterygium wilfordii Hook F, has shown promising antileukemic and anti-inflammatory activity. The pharmacokinetic profile of TP indicates an extensive metabolic elimination in vivo; however, its metabolic data is rarely available partly because of the difficulty in identifying it due to the absence of appropriate ultraviolet chromophores in the structure and the presence of endogenous interferences in biological samples. In the present study, the biotransformation of TP was investigated by improved data-dependent accurate mass spectrometric analysis, using an LTQ/Orbitrap hybrid mass spectrometer in conjunction with the online hydrogen (H)/deuterium (D) exchange technique for rapid structural characterization. Accurate full-scan MS and MS/MS data were processed with multiple post-acquisition data-mining techniques, which were complementary and effective in detecting both common and uncommon metabolites from biological matrices. As a result, 38 phase I, 9 phase II and 8 N-acetylcysteine (NAC) metabolites of TP were found in rat urine. Accurate MS/MS data were used to support assignments of metabolite structures, and online H/D exchange experiments provided additional evidence for exchangeable hydrogen atoms in the structure. The results showed the main phase I metabolic pathways of TP are hydroxylation, hydrolysis and desaturation, and the resulting metabolites subsequently undergo phase II processes. The presence of NAC conjugates indicated the capability of TP to form reactive intermediate species. This study also demonstrated the effectiveness of LC/HR-MS(n) in combination with multiple post-acquisition data-mining methods and the online H/D exchange technique for the rapid identification of drug metabolites. Copyright © 2011 John Wiley & Sons, Ltd.

  12. 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.

  13. 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

  14. Chemicalome and metabolome profiling of polymethoxylated flavonoids in Citri Reticulatae Pericarpium based on an integrated strategy combining background subtraction and modified mass defect filter in a Microsoft Excel Platform.

    Science.gov (United States)

    Zeng, Su-Ling; Duan, Li; Chen, Bai-Zhong; Li, Ping; Liu, E-Hu

    2017-07-28

    Detection of metabolites in complex biological matrixes is a great challenge because of the background noise and endogenous components. Herein, we proposed an integrated strategy that combined background subtraction program and modified mass defect filter (MMDF) data mining in a Microsoft Excel platform for chemicalome and metabolome profiling of the polymethoxylated flavonoids (PMFs) in Citri Reticulatae Pericarpium (CRP). The exogenously-sourced ions were firstly filtered out by the developed Visual Basic for Applications (VBA) program incorporated in the Microsoft Office. The novel MMDF strategy was proposed for detecting both target and untarget constituents and metabolites based on narrow, well-defined mass defect ranges. The approach was validated to be powerful, and potentially useful for the metabolite identification of both single compound and homologous compound mixture. We successfully identified 30 and 31 metabolites from rat biosamples after oral administration of nobiletin and tangeretin, respectively. A total of 56 PMFs compounds were chemically characterized and 125 metabolites were captured. This work demonstrated the feasibility of the integrated approach for reliable characterization of the constituents and metabolites in herbal medicines. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. 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.

  16. 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.

  17. Time is ripe: maturation of metabolomics in chronobiology.

    Science.gov (United States)

    Rhoades, Seth D; Sengupta, Arjun; Weljie, Aalim M

    2017-02-01

    Sleep and circadian rhythms studies have recently benefited from metabolomics analyses, uncovering new connections between chronobiology and metabolism. From untargeted mass spectrometry to quantitative nuclear magnetic resonance spectroscopy, a diversity of analytical approaches has been applied for biomarker discovery in the field. In this review we consider advances in the application of metabolomics technologies which have uncovered significant effects of sleep and circadian cycles on several metabolites, namely phosphatidylcholine species, medium-chain carnitines, and aromatic amino acids. Study design and data processing measures essential for detecting rhythmicity in metabolomics data are also discussed. Future developments in these technologies are anticipated vis-à-vis validating early findings, given metabolomics has only recently entered the ring with other systems biology assessments in chronometabolism studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. 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.

  19. 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.

  20. 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.

  1. Simple and accurate measurement of carbamazepine in surface water by use of porous membrane-protected micro-solid-phase extraction coupled with isotope dilution mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Teo, Hui Ling [Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore 117528 (Singapore); Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543 (Singapore); Wong, Lingkai [Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore 117528 (Singapore); Liu, Qinde, E-mail: liu_qinde@hsa.gov.sg [Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore 117528 (Singapore); Teo, Tang Lin; Lee, Tong Kooi [Chemical Metrology Division, Applied Sciences Group, Health Sciences Authority, 1 Science Park Road, #01-05/06, The Capricorn, Singapore Science Park II, Singapore 117528 (Singapore); Lee, Hian Kee, E-mail: chmleehk@nus.edu.sg [Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543 (Singapore)

    2016-03-17

    To achieve fast and accurate analysis of carbamazepine in surface water, we developed a novel porous membrane-protected micro-solid-phase extraction (μ-SPE) method, followed by liquid chromatography-isotope dilution tandem mass spectrometry (LC-IDMS/MS) analysis. The μ-SPE device (∼0.8 × 1 cm) was fabricated by heat-sealing edges of a polypropylene membrane sheet to devise a bag enclosing the sorbent. The analytes (both carbamazepine and isotope-labelled carbamazepine) were first extracted by μ-SPE device in the sample (10 mL) via agitation, then desorbed in an organic solvent (1 mL) via ultrasonication. Several parameters such as organic solvent for pre-conditioning of μ-SPE device, amount of sorbent, adsorption time, and desorption solvent and time were investigated to optimize the μ-SPE efficiency. The optimized method has limits of detection and quantitation estimated to be 0.5 ng L{sup −1} and 1.6 ng L{sup −1}, respectively. Surface water samples spiked with different amounts of carbamazepine (close to 20, 500, and 1600 ng L{sup −1}, respectively) were analysed for the validation of method precision and accuracy. Good precision was obtained as demonstrated by relative standard deviations of 0.7% for the samples with concentrations of 500 and 1600 ng kg{sup −1}, and 5.8% for the sample with concentration of 20 ng kg{sup −1}. Good accuracy was also demonstrated by the relative recoveries in the range of 96.7%–103.5% for all samples with uncertainties of 1.1%–5.4%. Owing to the same chemical properties of carbamazepine and isotope-labelled carbamazepine, the isotope ratio in the μ-SPE procedure was accurately controlled. The use of μ-SPE coupled with IDMS analysis significantly facilitated the fast and accurate measurement of carbamazepine in surface water. - Highlights: • μ-SPE coupled with IDMS for the measurement of carbamazepine. • The method is the first report of coupling μ-SPE with IDMS. • μ-SPE is fast, time

  2. Yeast metabolomics: sample preparation for a GC/MS-based analysis.

    Science.gov (United States)

    Carneiro, Sónia; Pereira, Rui; Rocha, Isabel

    2014-01-01

    Metabolome sample preparation is one of the key factors in metabolomics analyses. The quality of the metabolome data will depend on the suitability of the experimental procedures to the cellular system (e.g., yeast cells) and the analytical performance. Here, we summarize a protocol for metabolome analysis of yeast cells using gas chromatography-mass spectrometry (GC-MS). First, the main phases of a metabolomics analysis are identified: sample preparation, metabolite extraction, and analysis. We also provide an overview on different methods used to quench samples and extract intracellular metabolites from yeast cells. This protocol provides a detailed description of a GC-MS-based analysis of yeast metabolome, in particular for metabolites containing amino and/or carboxyl groups, which represent most of the compounds participating in the central carbon metabolism.

  3. 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

  4. Recent advances in metabolomics in neurological disease, and future perspectives.

    Science.gov (United States)

    Zhang, Ai-hua; Sun, Hui; Wang, Xi-jun

    2013-10-01

    Discovery of clinically relevant biomarkers for diseases has revealed metabolomics has potential advantages that classical diagnostic approaches do not. The great asset of metabolomics is that it enables assessment of global metabolic profiles of biofluids and discovery of biomarkers distinguishing disease status, with the possibility of enhancing clinical diagnostics. Most current clinical chemistry tests rely on old technology, and are neither sensitive nor specific for a particular disease. Clinical diagnosis of major neurological disorders, for example Alzheimer's disease and Parkinson's disease, on the basis of current clinical criteria is unsatisfactory. Emerging metabolomics is a powerful technique for discovering novel biomarkers and biochemical pathways to improve diagnosis, and for determination of prognosis and therapy. Identifying multiple novel biomarkers for neurological diseases has been greatly enhanced with recent advances in metabolomics that are more accurate than routine clinical practice. Cerebrospinal fluid (CSF), which is known to be a rich source of small-molecule biomarkers for neurological and neurodegenerative diseases, and is in close contact with diseased areas in neurological disorders, could potentially be used for disease diagnosis. Metabolomics will drive CSF analysis, facilitate and improve the development of disease treatment, and result in great benefits to public health in the long-term. This review covers different aspects of CSF metabolomics and discusses their significance in the postgenomic era, emphasizing the potential importance of endogenous small-molecule metabolites in this emerging field.

  5. A validated high-resolution accurate mass LC-MS assay for quantitative determination of metoprolol and α-hydroxymetoprolol in human serum for application in pharmacokinetics

    Directory of Open Access Journals (Sweden)

    Sjoukje Postma-Kunnen

    2017-06-01

    Full Text Available To determine metoprolol and its metabolite α-hydroxymetoprolol in human serum we validated a method on an LC system with an Exactive® Orbitrap mass spectrometer (Thermo Scientific as detector and isotope-labelled metoprolol-d7 as internal standard. A simple sample preparation was used with water-acetonitrile (15:85, v/v as precipitation reagent. This method has a chromatographic run time of 15 min and linear calibration curves in the range of 5.0-250 μg/L for both metoprolol and α-hydroxymetoprolol. Validation showed the method to be accurate, with a good precision, selective and with a lower limit of quantitation of 2.0 μg/L for metoprolol and 1.0 μg/L for α-hydroxymetoprolol, respectively. This validated LC-Orbitrap MS analysis for metoprolol and α-hydroxymetoprolol can be used for application in human pharmacokinetics.

  6. Sectional power-law correction for the accurate determination of lutetium by isotope dilution multiple collector-inductively coupled plasma-mass spectrometry

    Science.gov (United States)

    Yuan, Hong-Lin; Gao, Shan; Zong, Chun-Lei; Dai, Meng-Ning

    2009-11-01

    In this study, we employ a sectional power-law (SPL) correction that provides accurate and precise measurements of 176Lu/ 175Lu ratios in geological samples using multiple collector-inductively coupled plasma-mass spectrometry (MC-ICP-MS). Three independent power laws were adopted based on the 176Lu/ 176Yb ratios of samples measured after chemical chromatography. Using isotope dilution (ID) techniques and the SPL correction method, the measured lutetium contents of United States Geological Survey rock standards (BHVO-1, BHVO-2, BCR-2, AGV-1, and G-2) agree well with the recommended values. Results obtained by conventional ICP-MS and INAA are generally higher than those obtained by ID-TIMS and ID-MC-ICP-MS; this discrepancy probably reflects oxide interference and inaccurate corrections.

  7. Determination of doping peptides via solid-phase microelution and accurate-mass quadrupole time-of-flight LC-MS.

    Science.gov (United States)

    Cuervo, Darío; Loli, Cynthia; Fernández-Álvarez, María; Muñoz, Gloria; Carreras, Daniel

    2017-10-15

    A complete analytical protocol for the determination of 25 doping-related peptidic drugs and 3 metabolites in urine was developed by means of accurate-mass quadrupole time-of-flight (Q-TOF) LC-MS analysis following solid-phase extraction (SPE) on microplates and conventional SPE pre-treatment for initial testing and confirmation, respectively. These substances included growth hormone releasing factors, gonadotropin releasing factors and anti-diuretic hormones, with molecular weights ranging from 540 to 1320Da. Optimal experimental conditions were stablished after investigation of different parameters concerning sample preparation and instrumental analysis. Weak cation exchange SPE followed by C18 HPLC chromatography and accurate mass detection provided the required sensitivity and selectivity for all the target peptides under study. 2mg SPE on 96-well microplates can be used in combination with full scan MS detection for the initial testing, thus providing a fast, cost-effective and high-throughput protocol for the processing of a large batch of samples simultaneously. On the other hand, extraction on 30mg SPE cartridges and subsequent target MS/MS determination was the protocol of choice for confirmatory purposes. The methodology was validated in terms of selectivity, recovery, matrix effect, precision, sensitivity (limit of detection, LOD), cross contamination, carryover, robustness and stability. Recoveries ranged from 6 to 70% (microplates) and 17-95% (cartridges), with LODs from 0.1 to 1ng/mL. The suitability of the method was assessed by analyzing different spiked or excreted urines containing some of the target substances. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. 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

  9. Impacts on the metabolome of down-regulating polyphenol oxidase in transgenic potato tubers

    Science.gov (United States)

    Tubers of potato (Solanum tuberosum L. cv. Estima) genetically modified (GM) to reduce polyphenol oxidase (PPO) activity and enzymatic discolouration were assessed for changes in the metabolome using Liquid Chromatography-Mass Spectrometry (LC-MS) and Gas Chromatography (GC)-MS. Metabolome changes ...

  10. Changes in the Metabolome of Picea balfouriana Embryogenic Tissues That Were Linked to Different Levels of 6-BAP by Gas Chromatography-Mass Spectrometry Approach.

    Directory of Open Access Journals (Sweden)

    Q F Li

    Full Text Available Embryogenic cultures of Picea balfouriana, which is an important commercial species for reforestation in Southern China, easily lose their embryogenic ability during long-term culture. Embryogenic tissue that proliferated at lower concentrations (3.6 μM and 2.5 μM of 6-benzylaminopurine (6-BAP were more productive, and generated 113 ± 6 and 89 ± 3 mature embryos per 100 mg embryogenic tissue, respectively. A metabolomic approach was used to study the changes in metabolites linked to embryogenic competence related to three different 6-BAP concentrations (2.5 μM, 3.6 μM, and 5 μM. A total of 309 compounds were obtained, among which 123 metabolites mapped to Kyoto Encyclopedia of Genes and genomes (KEGG pathways. The levels of 35 metabolites were significantly differentially regulated among the three 6-BAP treatments, and 32 metabolites differed between the 2.5 μM and 5 μM treatments. A total of 17 metabolites appeared only once among the three comparisons. The combination of a score plot and a loading plot showed that in the samples with higher embryogenic ability (3.6 μM and 2.5 μM, up-regulated metabolites were mostly amino acids and down-regulated metabolites were mostly primary carbohydrates (especially sugars. These results suggested that 6-BAP may influence embryogenic competence by nitrogen metabolism, which could cause an increase in amino acid levels and higher amounts of aspartate, isoleucine, and leucine in tissues with higher embryogenic ability. Furthermore, we speculated that 6-BAP may affect the amount of tryptophan in tissues, which would change the indole-3-acetic acid levels and influence the embryogenic ability.

  11. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    Metabolomics is part of systems biology and a rapidly evolving field. It is a tool to analyze multiple metabolic changes in biofluids and tissues and aims at determining biomarkers in the metabolism. LC-MS (liquid chromatography – mass spectrometry), GC-MS (gas chromatography – mass spectrometry...

  12. 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

  13. Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.; Bingol, Ahmet K.

    2018-01-17

    We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited for discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.

  14. The use of in vitro technologies and high-resolution/accurate-mass LC-MS to screen for metabolites of 'designer' steroids in the equine.

    Science.gov (United States)

    Clarke, Adam; Scarth, James; Teale, Phil; Pearce, Clive; Hillyer, Lynn

    2011-01-01

    Detection of androgenic-anabolic steroid abuse in equine sports requires knowledge of the drug's metabolism in order to target appropriate metabolites, especially where urine is the matrix of choice. Studying 'designer' steroid metabolism is problematic since it is difficult to obtain ethical approval for in vivo metabolism studies due to a lack of toxicological data. In this study, the equine in vitro metabolism of eight steroids available for purchase on the Internet is reported; including androsta-1,4,6-triene-3,17-dione, 4-chloro,17α-methyl-androsta-1,4-diene-3,17β-diol, estra-4,9-diene-3,17-dione, 4-hydroxyandrostenedione, 20-hydroxyecdysone, 11-keto-androstenedione, 17α-methyldrostanolone, and tetrahydrogestrinone. In order to allow for retrospective analysis of sample testing data, the use of a high-resolution (HR) accurate-mass Thermo LTQ-Orbitrap liquid chromatography-mass spectrometry (LC-MS) instrument was employed for metabolite identification of underivatized sample extracts. The full scan LC-HRMS Orbitrap data were complimented by LC-HRMS/MS and gas-chromatography-mass spectrometry (GC-MS) experiments in order to provide fragmentation information and to ascertain whether GC-MS was capable of detecting any metabolite not detected by LC-HRMS. With the exception of 20-hydroxyecdysone, all compounds were found to be metabolized by equine liver S9 and/or microsomes. With the exception of 17α-methyldrostanolone, which produced metabolites that could only be detected by GC-MS, the metabolites of all other compounds could be identified using LC-HRMS, thus allowing retrospective analysis of previously acquired full-scan data resulting from routine equine drug testing screens. In summary, while in vitro techniques do not serve as a replacement for more definitive in vivo studies in all situations, their use does offer an alternative in situations where it would not be ethical to administer untested drugs to animals.

  15. 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.

  16. Metabolomics predicts stroke recurrence after transient ischemic attack

    Science.gov (United States)

    Jové, Mariona; Mauri-Capdevila, Gerard; Suárez, Idalmis; Cambray, Serafi; Sanahuja, Jordi; Quílez, Alejandro; Farré, Joan; Benabdelhak, Ikram; Pamplona, Reinald; Portero-Otín, Manuel

    2015-01-01

    Objective: To discover, by using metabolomics, novel candidate biomarkers for stroke recurrence (SR) with a higher prediction power than present ones. Methods: Metabolomic analysis was performed by liquid chromatography coupled to mass spectrometry in plasma samples from an initial cohort of 131 TIA patients recruited <24 hours after the onset of symptoms. Pattern analysis and metabolomic profiling, performed by multivariate statistics, disclosed specific SR and large-artery atherosclerosis (LAA) biomarkers. The use of these methods in an independent cohort (162 subjects) confirmed the results obtained in the first cohort. Results: Metabolomics analyses could predict SR using pattern recognition methods. Low concentrations of a specific lysophosphatidylcholine (LysoPC[16:0]) were significantly associated with SR. Moreover, LysoPC(20:4) also arose as a potential SR biomarker, increasing the prediction power of age, blood pressure, clinical features, duration of symptoms, and diabetes scale (ABCD2) and LAA. Individuals who present early (<3 months) recurrence have a specific metabolomic pattern, differing from non-SR and late SR subjects. Finally, a potential LAA biomarker, LysoPC(22:6), was also described. Conclusions: The use of metabolomics in SR biomarker research improves the predictive power of conventional predictors such as ABCD2 and LAA. Moreover, pattern recognition methods allow us to discriminate not only SR patients but also early and late SR cases. PMID:25471397

  17. 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

  18. Metabolomics and its application to acute lung diseases

    Directory of Open Access Journals (Sweden)

    Kathleen A. Stringer

    2016-02-01

    Full Text Available Metabolomics is a rapidly expanding field of systems biology that is gaining significant attention in many areas of biomedical research. Also known as metabonomics, it comprises the analysis of all small molecules or metabolites that are present within an organism or a specific compartment of the body. Metabolite detection and quantification provide a valuable addition to genomics and proteomics, and give unique insights into metabolic changes that occur in tangent to alterations in gene and protein activity that are associated with disease. As a novel approach to understanding disease, metabolomics provides a snapshot in time of all metabolites present in a biological sample such as whole blood, plasma, serum, urine, and many other specimens that may be obtained from either patients or experimental models. In this article, we review the burgeoning field of metabolomics in its application to acute lung diseases, specifically pneumonia and acute respiratory disease syndrome (ARDS. We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized environmental toxins. Recent reports have suggested that metabolomics analysis using nuclear magnetic resonance (NMR and mass spectrometry (MS approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe disease, such as sepsis, which kills many patients each year. In addition, metabolomics may provide more detailed phenotyping of patient heterogeneity which is needed to achieve the goal of precision medicine. However, although several experimental and clinical metabolomics studies have been conducted assessing the application of the science to acute lung diseases, only incremental progress has been made. Specifically, little is known about the metabolic phenotypes of these illnesses. These data are needed to substantiate metabolomics biomarker credentials so that clinicians can employ them for clinical

  19. Metabolomics and Its Application to Acute Lung Diseases

    Science.gov (United States)

    Stringer, Kathleen A.; McKay, Ryan T.; Karnovsky, Alla; Quémerais, Bernadette; Lacy, Paige

    2016-01-01

    Metabolomics is a rapidly expanding field of systems biology that is gaining significant attention in many areas of biomedical research. Also known as metabonomics, it comprises the analysis of all small molecules or metabolites that are present within an organism or a specific compartment of the body. Metabolite detection and quantification provide a valuable addition to genomics and proteomics and give unique insights into metabolic changes that occur in tangent to alterations in gene and protein activity that are associated with disease. As a novel approach to understanding disease, metabolomics provides a “snapshot” in time of all metabolites present in a biological sample such as whole blood, plasma, serum, urine, and many other specimens that may be obtained from either patients or experimental models. In this article, we review the burgeoning field of metabolomics in its application to acute lung diseases, specifically pneumonia and acute respiratory disease syndrome (ARDS). We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized environmental toxins. Recent reports have suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe disease, such as sepsis, which kills many patients each year. In addition, metabolomics may provide more detailed phenotyping of patient heterogeneity, which is needed to achieve the goal of precision medicine. However, although several experimental and clinical metabolomics studies have been conducted assessing the application of the science to acute lung diseases, only incremental progress has been made. Specifically, little is known about the metabolic phenotypes of these illnesses. These data are needed to substantiate metabolomics biomarker credentials so that clinicians can employ them for clinical decision

  20. 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.

  1. An optimized method for the accurate determination of patulin in apple products by isotope dilution-liquid chromatography/mass spectrometry.

    Science.gov (United States)

    Seo, Miyeong; Kim, Byungjoo; Baek, Song-Yee

    2015-07-01

    Patulin, a mycotoxin produced by several molds in fruits, has been frequently detected in apple products. Therefore, regulatory bodies have established recommended maximum permitted patulin concentrations for each type of apple product. Although several analytical methods have been adopted to determine patulin in food, quality control of patulin analysis is not easy, as reliable certified reference materials (CRMs) are not available. In this study, as a part of a project for developing CRMs for patulin analysis, we developed isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC/MS/MS) as a higher-order reference method for the accurate value-assignment of CRMs. (13)C7-patulin was used as internal standard. Samples were extracted with ethyl acetate to improve recovery. For further sample cleanup with solid-phase extraction (SPE), the HLB SPE cartridge was chosen after comparing with several other types of SPE cartridges. High-performance liquid chromatography was performed on a multimode column for proper retention and separation of highly polar and water-soluble patulin from sample interferences. Sample extracts were analyzed by LC/MS/MS with electrospray ionization in negative ion mode with selected reaction monitoring of patulin and (13)C7-patulin at m/z 153→m/z 109 and m/z 160→m/z 115, respectively. The validity of the method was tested by measuring gravimetrically fortified samples of various apple products. In addition, the repeatability and the reproducibility of the method were tested to evaluate the performance of the method. The method was shown to provide accurate measurements in the 3-40 μg/kg range with a relative expanded uncertainty of around 1%.

  2. Effects of fluconazole on the metabolomic profile of Candida albicans.

    Science.gov (United States)

    Katragkou, Aspasia; Alexander, Elizabeth L; Eoh, Hyungjin; Raheem, Saki K; Roilides, Emmanuel; Walsh, Thomas J

    2016-03-01

    Little is known about the effects of fluconazole on the metabolism of Candida albicans. We performed LC/MS-based metabolomic profiling of the response of C. albicans cells to increasing doses of fluconazole. C. albicans cells were cultured to mid-logarithmic growth phase in liquid medium and then inoculated in replicate on to nitrocellulose filters under vacuum filtration. Organisms were cultured to mid-logarithmic growth phase and treated with 0-4 mg/L fluconazole. Following metabolic quenching at mid-logarithmic growth phase, intracellular metabolites were extracted and analysed by LC/MS. Changes in pool sizes of individual metabolites were verified by Student's t-test, adjusted for multiple hypothesis testing by Benjamini-Hochberg correction. Distribution of metabolites was analysed by the Kyoto Encyclopedia of Genes and Genomes metabolic pathways database. We reproducibly detected 64 metabolites whose identities were confirmed by comparison against a pure standard and a library of accurate mass-retention time pairs. These 64 metabolites were broadly representative of eukaryotic central metabolic pathways. Among them 12 had their mean abundance significantly altered in response to increasing fluconazole concentrations. Pool sizes of four intermediates of central carbon metabolism (α-ketoglutarate, glucose-6-phosphate, phenylpyruvate and ribose-5-phosphate) and mevalonate were increased by 0.5-1.5-fold (P ≤ 0.05). Five amino acids (glycine, proline, tryptophan, aminoisobutanoate and asparagine) and guanine were decreased by 0.5-0.75-fold (P ≤ 0.05). Fluconazole treatment of C. albicans resulted in increased central carbon and decreased amino acid synthesis intermediates, suggesting a rerouting of metabolic pathways. The function of these metabolomic changes remains to be elucidated; however, they may represent previously unrecognized mechanisms of metabolic injury induced by fluconazole against C. albicans. © The Author 2015. Published by Oxford

  3. Headspace solid-phase microextraction combined with mass spectrometry as a powerful analytical tool for profiling the terpenoid metabolomic pattern of hop-essential oil derived from Saaz variety.

    Science.gov (United States)

    Gonçalves, João; Figueira, José; Rodrigues, Fátima; Câmara, José S

    2012-09-01

    Hop (Humulus lupulus L., Cannabaceae family) is prized for its essential oil contents, used in beer production and, more recently, in biological and pharmacological applications. In this work, a method involving headspace solid-phase microextraction and gas chromatography-mass spectrometry was developed and optimized to establish the terpenoid (monoterpenes and sesquiterpenes) metabolomic pattern of hop-essential oil derived from Saaz variety as a mean to explore this matrix as a powerful biological source for newer, more selective, biodegradable and naturally produced antimicrobial and antioxidant compounds. Different parameters affecting terpenoid metabolites extraction by headspace solid-phase microextraction were considered and optimized: type of fiber coatings, extraction temperature, extraction time, ionic strength, and sample agitation. In the optimized method, analytes were extracted for 30 min at 40°C in the sample headspace with a 50/30 μm divinylbenzene/carboxen/polydimethylsiloxane coating fiber. The methodology allowed the identification of a total of 27 terpenoid metabolites, representing 92.5% of the total Saaz hop-essential oil volatile terpenoid composition. The headspace composition was dominated by monoterpenes (56.1%, 13 compounds), sesquiterpenes (34.9%, 10), oxygenated monoterpenes (1.41%, 3), and hemiterpenes (0.04%, 1) some of which can probably contribute to the hop of Saaz variety aroma. Mass spectrometry analysis revealed that the main metabolites are the monoterpene β-myrcene (53.0 ± 1.1% of the total volatile fraction), and the cyclic sesquiterpenes, α-humulene (16.6 ± 0.8%), and β-caryophyllene (14.7 ± 0.4%), which together represent about 80% of the total volatile fraction from the hop-essential oil. These findings suggest that this matrix can be explored as a powerful biosource of terpenoid metabolites. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

    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.

  5. Accurate Identification of Common Pathogenic Nocardia Species: Evaluation of a Multilocus Sequence Analysis Platform and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

    Science.gov (United States)

    Chen, Sharon C-A.; Fan, Xin; Zhang, Li; Li, Hai-Xia; Hou, Xin; Cheng, Jing-Wei; Kong, Fanrong; Zhao, Yu-Pei; Xu, Ying-Chun

    2016-01-01

    Species identification of Nocardia is not straightforward due to rapidly evolving taxonomy, insufficient discriminatory power of conventional phenotypic methods and also of single gene locus analysis including 16S rRNA gene sequencing. Here we evaluated the ability of a 5-locus (16S rRNA, gyrB, secA1, hsp65 and rpoB) multilocus sequence analysis (MLSA) approach as well as that of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in comparison with sequencing of the 5’-end 606 bp partial 16S rRNA gene to provide identification of 25 clinical isolates of Nocardia. The 5’-end 606 bp 16S rRNA gene sequencing successfully assigned 24 of 25 (96%) clinical isolates to species level, namely Nocardia cyriacigeorgica (n = 12, 48%), N. farcinica (n = 9, 36%), N. abscessus (n = 2, 8%) and N. otitidiscaviarum (n = 1, 4%). MLSA showed concordance with 16S rRNA gene sequencing results for the same 24 isolates. However, MLSA was able to identify the remaining isolate as N. wallacei, and clustered N. cyriacigeorgica into three subgroups. None of the clinical isolates were correctly identified to the species level by MALDI-TOF MS analysis using the manufacturer-provided database. A small “in-house” spectral database was established incorporating spectra of five clinical isolates representing the five species identified in this study. After complementation with the “in-house” database, of the remaining 20 isolates, 19 (95%) were correctly identified to species level (score ≥ 2.00) and one (an N. abscessus strain) to genus level (score ≥ 1.70 and Nocardia. MALDI-TOF MS can provide rapid and accurate identification but is reliant on a robust mass spectra database. PMID:26808813

  6. Accurate Identification of Common Pathogenic Nocardia Species: Evaluation of a Multilocus Sequence Analysis Platform and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

    Science.gov (United States)

    Xiao, Meng; Pang, Lu; Chen, Sharon C-A; Fan, Xin; Zhang, Li; Li, Hai-Xia; Hou, Xin; Cheng, Jing-Wei; Kong, Fanrong; Zhao, Yu-Pei; Xu, Ying-Chun

    2016-01-01

    Species identification of Nocardia is not straightforward due to rapidly evolving taxonomy, insufficient discriminatory power of conventional phenotypic methods and also of single gene locus analysis including 16S rRNA gene sequencing. Here we evaluated the ability of a 5-locus (16S rRNA, gyrB, secA1, hsp65 and rpoB) multilocus sequence analysis (MLSA) approach as well as that of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in comparison with sequencing of the 5'-end 606 bp partial 16S rRNA gene to provide identification of 25 clinical isolates of Nocardia. The 5'-end 606 bp 16S rRNA gene sequencing successfully assigned 24 of 25 (96%) clinical isolates to species level, namely Nocardia cyriacigeorgica (n = 12, 48%), N. farcinica (n = 9, 36%), N. abscessus (n = 2, 8%) and N. otitidiscaviarum (n = 1, 4%). MLSA showed concordance with 16S rRNA gene sequencing results for the same 24 isolates. However, MLSA was able to identify the remaining isolate as N. wallacei, and clustered N. cyriacigeorgica into three subgroups. None of the clinical isolates were correctly identified to the species level by MALDI-TOF MS analysis using the manufacturer-provided database. A small "in-house" spectral database was established incorporating spectra of five clinical isolates representing the five species identified in this study. After complementation with the "in-house" database, of the remaining 20 isolates, 19 (95%) were correctly identified to species level (score ≥ 2.00) and one (an N. abscessus strain) to genus level (score ≥ 1.70 and Nocardia. MALDI-TOF MS can provide rapid and accurate identification but is reliant on a robust mass spectra database.

  7. Targeted quantitative bioanalysis in plasma using liquid chromatography/high-resolution accurate mass spectrometry: an evaluation of global selectivity as a function of mass resolving power and extraction window, with comparison of centroid and profile modes.

    Science.gov (United States)

    Xia, Yuan-Qing; Lau, Jim; Olah, Timothy; Jemal, Mohammed

    2011-10-15

    There is a growing interest in exploring the use of liquid chromatography coupled with full-scan high resolution accurate mass spectrometry (LC/HRMS) in bioanalytical laboratories as an alternative to the current practice of using LC coupled with tandem mass spectrometry (LC/MS/MS). Therefore, we have investigated the theoretical and practical aspects of LC/HRMS as it relates to the quantitation of drugs in plasma, which is the most commonly used matrix in pharmacokinetics studies. In order to assess the overall selectivity of HRMS, we evaluated the potential interferences from endogenous plasma components by analyzing acetonitrile-precipitated blank human plasma extract using an LC/HRMS system under chromatographic conditions typically used for LC/MS/MS bioanalysis with the acquisition of total ion chromatograms (TICs) using 10 k and 20 k resolving power in both profile and centroid modes. From each TIC, we generated extracted ion chromatograms (EICs) of the exact masses of the [M + H](+) ions of 153 model drugs using different mass extraction windows (MEWs) and determined the number of plasma endogenous peaks detected in each EIC. Fewer endogenous peaks are detected using higher resolving power, narrower MEW, and centroid mode. A 20 k resolving power can be considered adequate for the selective determination of drugs in plasma. To achieve desired analyte EIC selectivity and simultaneously avoid missing data points in the analyte EIC peak, the MEW used should not be too wide or too narrow and should be a small fraction of the full width at half maximum (FWHM) of the profile mass peak. It is recommended that the optimum MEW be established during method development under the specified chromatographic and sample preparation conditions. In general, the optimum MEW, typically ≤ ±20 ppm for 20 k resolving power, is smaller for the profile mode when compared with the centroid mode. Copyright © 2011 John Wiley & Sons, Ltd.

  8. Accurate determination of Curium and Californium isotopic ratios by inductively coupled plasma quadrupole mass spectrometry (ICP-QMS) in 248Cm samples for transmutation studies

    Energy Technology Data Exchange (ETDEWEB)

    Gourgiotis, A.; Isnard, H.; Aubert, M.; Dupont, E.; AlMahamid, I.; Cassette, P.; Panebianco, S.; Letourneau, A.; Chartier, F.; Tian, G.; Rao, L.; Lukens, W.

    2011-02-01

    The French Atomic Energy Commission has carried out several experiments including the mini-INCA (INcineration of Actinides) project for the study of minor-actinide transmutation processes in high intensity thermal neutron fluxes, in view of proposing solutions to reduce the radiotoxicity of long-lived nuclear wastes. In this context, a Cm sample enriched in {sup 248}Cm ({approx}97 %) was irradiated in thermal neutron flux at the High Flux Reactor (HFR) of the Laue-Langevin Institute (ILL). This work describes a quadrupole ICP-MS (ICP-QMS) analytical procedure for precise and accurate isotopic composition determination of Cm before sample irradiation and of Cm and Cf after sample irradiation. The factors that affect the accuracy and reproducibility of isotopic ratio measurements by ICP-QMS, such as peak centre correction, detector dead time, mass bias, abundance sensitivity and hydrides formation, instrumental background, and memory blank were carefully evaluated and corrected. Uncertainties of the isotopic ratios, taking into account internal precision of isotope ratio measurements, peak tailing, and hydrides formations ranged from 0.3% to 1.3%. This uncertainties range is quite acceptable for the nuclear data to be used in transmutation studies.

  9. Assessment of two complementary liquid chromatography coupled to high resolution mass spectrometry metabolomics strategies for the screening of anabolic steroid treatment in calves

    NARCIS (Netherlands)

    Dervilly-Pinel, G.; Weigel, S.; Lommen, A.; Chereau, S.; Rambaud, L.; Essers, M.L.; Antignac, J.P.; Nielen, M.W.F.; Bizec, Le B.

    2011-01-01

    Anabolic steroids are banned in food producing livestock in Europe. Efficient methods based on mass spectrometry detection have been developed to ensure the control of such veterinary drug residues. Nevertheless, the use of “cocktails” composed of mixtures of low amounts of several substances as

  10. Metabolomics of Small Numbers of Cells: Metabolomic Profiling of 100, 1000, and 10000 Human Breast Cancer Cells.

    Science.gov (United States)

    Luo, Xian; Li, Liang

    2017-10-26

    In cellular metabolomics, it is desirable to carry out metabolomic profiling using a small number of cells in order to save time and cost. In some applications (e.g., working with circulating tumor cells in blood), only a limited number of cells are available for analysis. In this report, we describe a method based on high-performance chemical isotope labeling (CIL) nanoflow liquid chromatography mass spectrometry (nanoLC-MS) for high-coverage metabolomic analysis of small numbers of cells (i.e., ≤10000 cells). As an example, (12)C-/(13)C-dansyl labeling of the metabolites in lysates of 100, 1000, and 10000 MCF-7 breast cancer cells was carried out using a new labeling protocol tailored to handle small amounts of metabolites. Chemical-vapor-assisted ionization in a captivespray interface was optimized for improving metabolite ionization and increasing robustness of nanoLC-MS. Compared to microflow LC-MS, the nanoflow system provided much improved metabolite detectability with a significantly reduced sample amount required for analysis. Experimental duplicate analyses of biological triplicates resulted in the detection of 1620 ± 148, 2091 ± 89 and 2402 ± 80 (n = 6) peak pairs or metabolites in the amine/phenol submetabolome from the (12)C-/(13)C-dansyl labeled lysates of 100, 1000, and 10000 cells, respectively. About 63-69% of these peak pairs could be either identified using dansyl labeled standard library or mass-matched to chemical structures in human metabolome databases. We envisage the routine applications of this method for high-coverage quantitative cellular metabolomics using a starting material of 10000 cells. Even for analyzing 100 or 1000 cells, although the metabolomic coverage is reduced from the maximal coverage, this method can still detect thousands of metabolites, allowing the analysis of a large fraction of the metabolome and focused analysis of the detectable metabolites.

  11. 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

  12. A view from above: cloud plots to visualize global metabolomic data.

    Science.gov (United States)

    Patti, Gary J; Tautenhahn, Ralf; Rinehart, Duane; Cho, Kevin; Shriver, Leah P; Manchester, Marianne; Nikolskiy, Igor; Johnson, Caroline H; Mahieu, Nathaniel G; Siuzdak, Gary

    2013-01-15

    Global metabolomics describes the comprehensive analysis of small molecules in a biological system without bias. With mass spectrometry-based methods, global metabolomic data sets typically comprise thousands of peaks, each of which is associated with a mass-to-charge ratio, retention time, fold change, p-value, and relative intensity. Although several visualization schemes have been used for metabolomic data, most commonly used representations exclude important data dimensions and therefore limit interpretation of global data sets. Given that metabolite identification through tandem mass spectrometry data acquisition is a time-limiting step of the untargeted metabolomic workflow, simultaneous visualization of these parameters from large sets of data could facilitate compound identification and data interpretation. Here, we present such a visualization scheme of global metabolomic data using a so-called "cloud plot" to represent multidimensional data from septic mice. While much attention has been dedicated to lipid compounds as potential biomarkers for sepsis, the cloud plot shows that alterations in hydrophilic metabolites may provide an early signature of the disease prior to the onset of clinical symptoms. The cloud plot is an effective representation of global mass spectrometry-based metabolomic data, and we describe how to extract it as standard output from our XCMS metabolomic software.

  13. Metabolomic analysis of lung epithelial secretions in rats: an investigation of bronchoalveolar lavage fluid by GC-MS and FT-IR.

    Science.gov (United States)

    Qamar, Wajhul; Ahamad, Syed Rizwan; Ali, Raisuddin; Khan, Mohammad Rashid; Al-Ghadeer, Abdul Rahman

    2014-11-01

    Rat bronchoalveolar lavage fluid (BALF) metabolome can be used to obtain valuable, precise, and accurate information about underlying lung conditions in an experiment. The present study focuses on the evaluation of the lung epithelium metabolome in a rat model using techniques including bronchoalveolar lavage, gas chromatography-mass spectroscopy (GC-MS), and Fourier transform infrared spectroscopy (FT-IR). Untargeted metabolites in BALF were extracted in ethyl acetate and derivatized by standard methods for the analysis by GC-MS. FT-IR spectra of ethyl acetate extract of BALF were obtained and read for the characteristic fingerprint of rats under investigation. Analyses were done in individual animals to obtain consistent data. BALF cells were counted by flow cytometry to monitor any inflammatory condition in rats. FT-IR analysis finds two peaks which are characteristically different from the extract medium, which is ethyl acetate. FT-IR peaks correspond to that of amino acids and carbohydrates, including β-D-glucose, α-D-glucose, and β-D-galactose. GC-MS evaluation of the BALF finds several products of the metabolism or its participants. Main compounds in the BALF detected by GC-MS include succinate, fumarate, glycine, alanine, 2-methyl-3-oxovaleric acid, dodecanoic acid, tetradecanoic acid, hexadecanoic acid, octanoic acid, trans-9-octadecanoic acid, octadecanoic acid, and Prostaglandin F1α. Several research reports reveal metabolomic parameters in murine model lung tissue or BALF, but they rarely reported a complete metabolomics model profile, particularly in rats. The present data of GC-MS and FT-IR suggest that the set up can be exploited to study metabolomic alterations in several lung conditions including acute lung toxicity, inflammation, asthma, bronchitis, fibrosis, and emphysema.

  14. A metabolomic approach to the evaluation of the origin of extra virgin olive oil: a convenient statistical treatment of mass spectrometric analytical data.

    Science.gov (United States)

    Cavaliere, Brunella; De Nino, Antonio; Hayet, Fourati; Lazez, Aida; Macchione, Barbara; Moncef, Cossentini; Perri, Enzo; Sindona, Giovanni; Tagarelli, Antonio

    2007-02-21

    The selection of suitable markers from the secondary metabolism of lipoxygenase, in experimental olive oils produced from drupes harvested in different areas of the Italian Calabria region and of Tunisia, allows an easy discrimination between each cluster of samples. The origin of the foodstuff can be ascertained even when the distances between the production zones are very close to each other as in Calabria. Olive oils produced from irrigated and nonirrigated farms in Tunisia were also clearly distinguishable. The markers were detected by chemical ionization mass spectrometry with an ion trap gas chromatography-mass spectrometry apparatus. The quantitative data of Calabrian olive oil samples were subjected to linear discriminant analysis, whereas the Tunisian data were treated by means of other two statistical tools, i.e., the Kruskal-Wallis test and the Wald-Wolfowitz test.

  15. Selenium metabolomics in yeast using complementary reversed-phase/hydrophilic ion interaction (HILIC) liquid chromatography-electrospray hybrid quadrupole trap/Orbitrap mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Arnaudguilhem, C.; Bierla, K.; Ouerdane, L.; Preud' homme, H. [CNRS/UPPA, Laboratoire de Chimie Analytique Bio-inorganique et Environnement, UMR 5254, Helioparc, 2, Av. Pr. Angot, 64053 Pau (France); Yiannikouris, A. [Alltech Inc., 3031 Catnip Hill Pike, Nicholasville, KY (United States); Lobinski, R., E-mail: ryszard.lobinski@univ-pau.fr [CNRS/UPPA, Laboratoire de Chimie Analytique Bio-inorganique et Environnement, UMR 5254, Helioparc, 2, Av. Pr. Angot, 64053 Pau (France); Chair of Analytical Chemistry, Warsaw University of Technology, 00-664 Warszawa (Poland)

    2012-12-13

    Highlights: Black-Right-Pointing-Pointer The use of bimodal chromatographic separation enlarged amount of compounds identified. Black-Right-Pointing-Pointer The method allowed the largest scale ever (>60 compounds) speciation analysis of selenium metabolites in Se-rich yeast. Black-Right-Pointing-Pointer The estimated concentration of compounds was given. - Abstract: A high efficiency chromatographic separation on a porous graphitic carbon stationary phase was developed for a large-scale separation of selenium metabolites in Se-rich yeast prior to their identification by electrospray hybrid quadrupole trap/Orbitrap mass spectrometry (Orbitrap MS{sup n}). The reversed-phase (RP) separation mode offered distinctly higher separation efficiency than the hydrophilic ion interaction (HILIC) mode. The latter was nevertheless complementary and useful to validate the detection of several compounds. The method allowed the detection of 64 metabolites including 30 Se-Se or Se-S conjugates (3 triple S/Se/S ones) and 14 selenoethers. 21 previously unreported metabolites were detected on the basis of the selenium isotopic pattern usually matched with the sub-ppm mass accuracy. 9 of these metabolites were subsequently identified using the multi-stage high mass accuracy (<5 ppm) mass spectrometry. The identified metabolites (and their groups) were quantified on-line by ICP-MS fitted with a frequency-matching generator allowing a quasi-uniform response over the large (20-90%) acetonitrile mobile phase concentration range. The morphology of HPLC-ICP-MS chromatograms was remarkably similar to that of HPLC multi-ion extracted ESI-MS chromatograms. The detection limits obtained by ICP MS and ESI MS were 1 and 2 ppb, respectively.

  16. 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.

  17. 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.

  18. NMR/MS Translator for the Enhanced Simultaneous Analysis of Metabolomics Mixtures by NMR Spectroscopy and Mass Spectrometry: Application to Human Urine.

    Science.gov (United States)

    Bingol, Kerem; Brüschweiler, Rafael

    2015-06-05

    A novel metabolite identification strategy is presented for the combined NMR/MS analysis of complex metabolite mixtures. The approach first identifies metabolite candidates from 1D or 2D NMR spectra by NMR database query, which is followed by the determination of the masses (m/z) of their possible ions, adducts, fragments, and characteristic isotope distributions. The expected m/z ratios are then compared with the MS(1) spectrum for the direct assignment of those signals of the mass spectrum that contain information about the same metabolites as the NMR spectra. In this way, the mass spectrum can be assigned with very high confidence, and it provides at the same time validation of the NMR-derived metabolites. The method was first demonstrated on a model mixture, and it was then applied to human urine collected from a pool of healthy individuals. A number of metabolites could be detected that had not been reported previously, further extending the list of known urine metabolites. The new analysis approach, which is termed NMR/MS Translator, is fully automated and takes only a few seconds on a computer workstation. NMR/MS Translator synergistically uses the power of NMR and MS, enhancing the accuracy and efficiency of the identification of those metabolites compiled in databases.

  19. Metabolomic profiling of prostate cancer by matrix assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry imaging using Matrix Coating Assisted by an Electric Field (MCAEF).

    Science.gov (United States)

    Wang, Xiaodong; Han, Jun; Hardie, Darryl B; Yang, Juncong; Pan, Jingxi; Borchers, Christoph H

    2017-07-01

    In this work, we combined the use of two MALDI matrices (quercetin and 9-aminoacridine), a recently developed new matrix coating technique - matrix coating assisted by an electric field (MCAEF), and matrix-assisted laser desorption/ionization - Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICRMS) to detect and image endogenous compounds in the cancerous and non-cancerous regions of three human prostate cancer (stage II) tissue specimens. After three rounds of imaging data acquisitions (i.e., quercetin for positive and negative ion detection and 9-aminoacridine for negative ion detection), and metabolite identification, a total of 1091 metabolites including 1032 lipids and 59 other metabolites were routinely detected and successfully localized. Of these compounds, 250 and 217 were only detected in either the cancerous or the non-cancerous regions respectively, although we cannot rule out the presence of these metabolites at concentrations below the detection limit. In addition, 152 of the other 624 metabolites showed differential distributions (p<0.05, t-test) between the two regions of the tissues. Further studies on a larger number of clinical specimens will need to be carried out to confirm this large number of apparently cancer-related metabolites. The successful determination of the spatial locations and abundances of these endogenous biomolecules indicated significant metabolism abnormalities - e.g., increased energy charge and under-expression of neutral acyl glycerides, in the prostate cancer samples. To our knowledge, this work has resulted in MALDI-MS imaging of the largest group of metabolites in prostate cancer thus far and demonstrated the importance of using complementary matrices for comprehensive metabolomic imaging by MALDI-MS. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. 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

  1. Cosmological constraints from the CFHTLenS shear measurements using a new, accurate, and flexible way of predicting non-linear mass clustering

    Science.gov (United States)

    Angulo, Raul E.; Hilbert, Stefan

    2015-03-01

    We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.

  2. A High Resolution/Accurate Mass (HRAM) Data-Dependent MS3 Neutral Loss Screening, Classification, and Relative Quantitation Methodology for Carbonyl Compounds in Saliva

    Science.gov (United States)

    Dator, Romel; Carrà, Andrea; Maertens, Laura; Guidolin, Valeria; Villalta, Peter W.; Balbo, Silvia

    2017-04-01

    Reactive carbonyl compounds (RCCs) are ubiquitous in the environment and are generated endogenously as a result of various physiological and pathological processes. These compounds can react with biological molecules inducing deleterious processes believed to be at the basis of their toxic effects. Several of these compounds are implicated in neurotoxic processes, aging disorders, and cancer. Therefore, a method characterizing exposures to these chemicals will provide insights into how they may influence overall health and contribute to disease pathogenesis. Here, we have developed a high resolution accurate mass (HRAM) screening strategy allowing simultaneous identification and relative quantitation of DNPH-derivatized carbonyls in human biological fluids. The screening strategy involves the diagnostic neutral loss of hydroxyl radical triggering MS3 fragmentation, which is only observed in positive ionization mode of DNPH-derivatized carbonyls. Unique fragmentation pathways were used to develop a classification scheme for characterizing known and unanticipated/unknown carbonyl compounds present in saliva. Furthermore, a relative quantitation strategy was implemented to assess variations in the levels of carbonyl compounds before and after exposure using deuterated d 3 -DNPH. This relative quantitation method was tested on human samples before and after exposure to specific amounts of alcohol. The nano-electrospray ionization (nano-ESI) in positive mode afforded excellent sensitivity with detection limits on-column in the high-attomole levels. To the best of our knowledge, this is the first report of a method using HRAM neutral loss screening of carbonyl compounds. In addition, the method allows simultaneous characterization and relative quantitation of DNPH-derivatized compounds using nano-ESI in positive mode.

  3. 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.

  4. Recent applications of metabolomics to advance microbial biofuel production.

    Science.gov (United States)

    Martien, Julia I; Amador-Noguez, Daniel

    2017-02-01

    Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers. Copyright © 2016. Published by Elsevier Ltd.

  5. Obesity-Related Metabolomic Analysis of Human Subjects in Black Soybean Peptide Intervention Study by Ultraperformance Liquid Chromatography and Quadrupole-Time-of-Flight Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Min Jung Kim

    2013-01-01

    Full Text Available The present study aimed to identify key metabolites related to weight reduction in humans by studying the metabolic profiles of sera obtained from 34 participants who underwent dietary intervention with black soybean peptides (BSP for 12 weeks. This research is a sequel to our previous work in which the effects of BSP on BMI and blood composition of lipid were investigated. Sera of the study were subjected to ultra performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS, and the data were analyzed using partial least-squares discriminate analysis (PLS-DA score plots. Body mass index and percent body fat of the test group were reduced. Levels of betaine, benzoic acid, pyroglutamic acid, pipecolic acid, N-phenylacetamide, uric acid, l-aspartyl-l-phenylalanine, and lysophosphatidyl cholines (lysoPCs (C18:1, C18:2, C20:1, and C20:4 showed significant increases. Levels of l-proline, valine, l-leucine/isoleucine, hypoxanthine, glutamine, l-methionine, phenylpyruvic acid, several carnitine derivatives, and lysoPCs (C14:0, PC16:0, C15:0, C16:0, C17:1, C18:0, and C22:0 were significantly decreased. In particular, lysoPC 16:0 with a VIP value of 12.02 is esteemed to be the most important metabolite for evaluating the differences between the 2 serum samples. Our result confirmed weight-lowering effects of BSP, accompanied by favorable changes in metabolites in the subjects’ blood. Therefore, this research enables us to better understand obesity and increases the predictability of the obesity-related risk by studying metabolites present in the blood.

  6. Metabolomics for phytochemical discovery: development of statistical approaches using a cranberry model system.

    Science.gov (United States)

    Turi, Christina E; Finley, Jamie; Shipley, Paul R; Murch, Susan J; Brown, Paula N

    2015-04-24

    Metabolomics is the qualitative and quantitative analysis of all of the small molecules in a biological sample at a specific time and influence. Technologies for metabolomics analysis have developed rapidly as new analytical tools for chemical separations, mass spectrometry, and NMR spectroscopy have emerged. Plants have one of the largest metabolomes, and it is estimated that the average plant leaf can contain upward of 30 000 phytochemicals. In the past decade, over 1200 papers on plant metabolomics have been published. A standard metabolomics data set contains vast amounts of information and can either investigate or generate hypotheses. The key factors in using plant metabolomics data most effectively are the experimental design, authentic standard availability, extract standardization, and statistical analysis. Using cranberry (Vaccinium macrocarpon) as a model system, this review will discuss and demonstrate strategies and tools for analysis and interpretation of metabolomics data sets including eliminating false discoveries and determining significance, metabolite clustering, and logical algorithms for discovery of new metabolites and pathways. Together these metabolomics tools represent an entirely new pipeline for phytochemical discovery.

  7. 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.

  8. Quantitative metabolomics of the thermophilic methylotroph Bacillus methanolicus.

    Science.gov (United States)

    Carnicer, Marc; Vieira, Gilles; Brautaset, Trygve; Portais, Jean-Charles; Heux, Stephanie

    2016-06-01

    The gram-positive bacterium Bacillus methanolicus MGA3 is a promising candidate for methanol-based biotechnologies. Accurate determination of intracellular metabolites is crucial for engineering this bacteria into an efficient microbial cell factory. Due to the diversity of chemical and cell properties, an experimental protocol validated on B. methanolicus is needed. Here a systematic evaluation of different techniques for establishing a reliable basis for metabolome investigations is presented. Metabolome analysis was focused on metabolites closely linked with B. methanolicus central methanol metabolism. As an alternative to cold solvent based procedures, a solvent-free quenching strategy using stainless steel beads cooled to -20 °C was assessed. The precision, the consistency of the measurements, and the extent of metabolite leakage from quenched cells were evaluated in procedures with and without cell separation. The most accurate and reliable performance was provided by the method without cell separation, as significant metabolite leakage occurred in the procedures based on fast filtration. As a biological test case, the best protocol was used to assess the metabolome of B. methanolicus grown in chemostat on methanol at two different growth rates and its validity was demonstrated. The presented protocol is a first and helpful step towards developing reliable metabolomics data for thermophilic methylotroph B. methanolicus. This will definitely help for designing an efficient methylotrophic cell factory.

  9. Metabolomics for clinical use and research in chronic kidney disease.

    Science.gov (United States)

    Hocher, Berthold; Adamski, Jerzy

    2017-05-01

    Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.

  10. 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.

  11. Conversation on data mining strategies in LC-MS untargeted metabolomics: pre-processing and pre-treatment steps

    CSIR Research Space (South Africa)

    Tugizimana, F

    2016-11-01

    Full Text Available ” extraction of information from these metabolomic datasets is still a non-trivial undertaking. A conversation on data mining strategies for a maximal information extraction from metabolomic data is needed. Using a liquid chromatography-mass spectrometry (LC...

  12. Metabolomics and Its Application in the Development of Discovering Biomarkers for Osteoporosis Research

    Directory of Open Access Journals (Sweden)

    Huanhuan Lv

    2016-12-01

    Full Text Available Osteoporosis is a progressive skeletal disorder characterized by low bone mass and increased risk of fracture in later life. The incidence and costs associated with treating osteoporosis cause heavy socio-economic burden. Currently, the diagnosis of osteoporosis mainly depends on bone mineral density and bone turnover markers. However, these indexes are not sensitive and accurate enough to reflect the osteoporosis progression. Metabolomics offers the potential for a holistic approach for clinical diagnoses and treatment, as well as understanding of the pathological mechanism of osteoporosis. In this review, we firstly describe the study subjects of osteoporosis and bio-sample preparation procedures for different analytic purposes, followed by illustrating the biomarkers with potentially predictive, diagnosis and pharmaceutical values when applied in osteoporosis research. Then, we summarize the published metabolic pathways related to osteoporosis. Furthermore, we discuss the importance of chronological data and combination of multi-omics in fully understanding osteoporosis. The application of metabolomics in osteoporosis could provide researchers the opportunity to gain new insight into the metabolic profiling and pathophysiological mechanisms. However, there is still much to be done to validate the potential biomarkers responsible for the progression of osteoporosis and there are still many details needed to be further elucidated.

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

    Science.gov (United States)

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

    2015-02-01

    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, (1)H NMR for polar metabolites, accurate mass LC-QTOF MS for semi-polar metabolites, LC-MRM for oxylipins, and headspace GC-MS for volatile compounds. An initial exploratory experiment indicated that the order of blending and thermal treatments had the highest impact on the phytochemicals in the purees. This blending-heating order effect was investigated in more depth by performing alternate blending-heating sequences in triplicate on the same batches of broccoli, tomato and carrot. For each vegetable and particularly in broccoli, a large proportion of the metabolites detected in the purees was significantly influenced by the blending-heating order, amongst which were potential health-related phytochemicals and flavour compounds like vitamins C and E, carotenoids, flavonoids, glucosinolates and oxylipins. Our metabolomics data indicates that during processing the activity of a series of endogenous plant enzymes, such as lipoxygenases, peroxidases and glycosidases, including myrosinase in broccoli, is key to the final metabolite composition and related quality of the purees. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Metabolomics as a potential chemotaxonomical tool: application in the genus Vernonia schreb.

    Directory of Open Access Journals (Sweden)

    Maria Elvira Poleti Martucci

    Full Text Available The taxonomic classification of the genus Vernonia Schreb is complex and, as yet, unclear. We here report the use of untargeted metabolomics approaches, followed by multivariate analyses methods and a phytochemical characterization of ten Vernonia species. Metabolic fingerprints were obtained by accurate mass measurements and used to determine the phytochemical similarities and differences between species through multivariate analyses approaches. Principal component analysis based on the relative levels of 528 metabolites, indicated that the ten species could be clustered into four groups. Thereby, V. polyanthes was the only species with presence of flavones chrysoeriol-7-O-glycuronyl, acacetin-7-O-glycuronyl and sesquiterpenes lactones piptocarphin A and piptocarphin B, while glaucolide A was detected in both V. brasiliana and V. polyanthes, separating these species from the two other species of the Vernonanthura group. Species from the Lessingianthus group were unique in showing a positive response in the foam test, suggesting the presence of saponins, which could be confirmed by metabolite annotation. V. rufogrisea showed a great variety of sesquiterpene lactones, placing this species into a separate group. Species within the Chrysolaena group were unique in accumulating clovamide. Our results of LC-MS-based profiling combined with multivariate analyses suggest that metabolomics approaches, such as untargeted LC-MS, may be potentially used as a large-scale chemotaxonomical tool, in addition to classical morphological and cytotaxonomical approaches, in order to facilitate taxonomical classifications.

  15. Metabolomics as a potential chemotaxonomical tool: application in the genus Vernonia schreb.

    Science.gov (United States)

    Martucci, Maria Elvira Poleti; De Vos, Ric C H; Carollo, Carlos Alexandre; Gobbo-Neto, Leonardo

    2014-01-01

    The taxonomic classification of the genus Vernonia Schreb is complex and, as yet, unclear. We here report the use of untargeted metabolomics approaches, followed by multivariate analyses methods and a phytochemical characterization of ten Vernonia species. Metabolic fingerprints were obtained by accurate mass measurements and used to determine the phytochemical similarities and differences between species through multivariate analyses approaches. Principal component analysis based on the relative levels of 528 metabolites, indicated that the ten species could be clustered into four groups. Thereby, V. polyanthes was the only species with presence of flavones chrysoeriol-7-O-glycuronyl, acacetin-7-O-glycuronyl and sesquiterpenes lactones piptocarphin A and piptocarphin B, while glaucolide A was detected in both V. brasiliana and V. polyanthes, separating these species from the two other species of the Vernonanthura group. Species from the Lessingianthus group were unique in showing a positive response in the foam test, suggesting the presence of saponins, which could be confirmed by metabolite annotation. V. rufogrisea showed a great variety of sesquiterpene lactones, placing this species into a separate group. Species within the Chrysolaena group were unique in accumulating clovamide. Our results of LC-MS-based profiling combined with multivariate analyses suggest that metabolomics approaches, such as untargeted LC-MS, may be potentially used as a large-scale chemotaxonomical tool, in addition to classical morphological and cytotaxonomical approaches, in order to facilitate taxonomical classifications.

  16. Metabolomics study on the toxicity of Annona squamosa by ultraperformance liquid-chromatography high-definition mass spectrometry coupled with pattern recognition approach and metabolic pathways analysis.

    Science.gov (United States)

    Miao, Yun-Jie; Shi, Ye-Ye; Li, Fu-Qiang; Shan, Chen-Xiao; Chen, Yong; Chen, Jian-Wei; Li, Xiang

    2016-05-26

    Annona squamosa Linn (Annonaceae) is a commonly used and effective traditional Chinese medicine (TCM) especially in the South China. The seeds of Annona squamosa Linn (SAS) have been used as a folk remedy to treat "malignant sores" (cancer) in South of China, but they also have high toxicity on human body. To discover the potential biomarkers in the mice caused by SAS. We made metabonomics studies on the toxicity of SAS by ultraperformance liquid-chromatography high-definition mass spectrometry coupled with pattern recognition approach and metabolic pathways analysis. The significant difference in metabolic profiles and changes of metabolite biomarkers between the Control group and SAS group were well observed. 11 positive ions and 9 negative ions (Pmetabolic pathways of SAS group are discussed according to the identified endogenous metabolites, and eight metabolic pathways are identified using Kyoto Encyclopedia of Genes and Genomes (KEGG). The present study demonstrates that metabonomics analysis could greatly facilitate and provide useful information for the further comprehensive understanding of the pharmacological activity and potential toxicity of SAS in the progress of them being designed to a new anti-tumor medicine. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. Selection of Taste Markers Related to Lactic Acid Bacteria Microflora Metabolism for Chinese Traditional Paocai: A Gas Chromatography-Mass Spectrometry-Based Metabolomics Approach.

    Science.gov (United States)

    Zhao, Nan; Zhang, Chuchu; Yang, Qin; Guo, Zhuang; Yang, Bo; Lu, Wenwei; Li, Dongyao; Tian, Fengwei; Liu, Xiaoming; Zhang, Hao; Chen, Wei

    2016-03-23

    Traditional paocai brine (PB) is continuously propagated by back-slopping and contains numerous lactic acid bacteria (LAB) strains. Although PB is important for the quality of paocai (Chinese sauerkraut), the taste features, taste-related compounds of PB-paocai and the effects of LAB communities from PB on the taste compounds remain unclear. An electronic tongue was used to evaluate the taste features of 13 PB-paocai samples. Umami, saltiness, bitterness, sweetness, and aftertaste astringency were the main taste features of PB-paocai. A total of 14 compounds were identified as discriminant taste markers for PB-paocai via gas chromatography-mass spectrometry (GC-MS)-based multimarker profiling. A LAB co-culture (Lactobacillus plantarum, Lactobacillus buchneri, and Pediococcus ethanoliduran) from PB could significantly increase glutamic acid (umami), sucrose (sweetness), glycine (sweetness), lactic acid (sourness), and γ-aminobutyric acid in PB-paocai, which would endow it with important flavor features. Such features could then facilitate starter screening and fermentation optimization to produce paocai-related foods with better nutritional and sensory qualities.

  18. 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

  19. A high-performance liquid chromatography-tandem mass spectrometry-based targeted metabolomics kidney dysfunction marker panel in human urine.

    Science.gov (United States)

    Klepacki, Jacek; Klawitter, Jost; Klawitter, Jelena; Thurman, Joshua M; Christians, Uwe

    2015-06-15

    Previous studies have examined and documented fluctuations in urine metabolites in response to disease processes and drug toxicity affecting glomerular filtration, tubule cell metabolism, reabsorption, oxidative stress, purine degradation, active secretion and kidney amino acylase activity representative of diminished renal function. However, a high-throughput assay that incorporates metabolites that are surrogate markers for such changes into a kidney dysfunction panel has yet to be described. A high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) assay for the quantification of ten metabolites associated with the Krebs cycle, purine degradation, and oxidative stress in human urine was developed and validated. Normal values were assessed in healthy adult (n=120) and pediatric (n=36) individuals. In addition, 9 pediatric renal transplant recipients patients were evaluated before and after initial dosing of the immunosuppressant tacrolimus in a proof-of-concept study. The assay met all predefined acceptance criteria. The lower limit of quantification ranged from 0.1 to 1000 μmol/l. Inter-day trueness and imprecisions ranged from 91.4-112.9% and 1.5-12.4%, respectively. The total assay run time was 5.5 minutes. Concentrations of glucose, sorbitol, and trimethylamine oxide (TMAO) were elevated in pediatric renal transplant patients (n=9) prior to transplantation as well as before and immediately after initial dosing of tacrolimus. One month post-transplant urine metabolite patterns matched those of healthy children (n=36). The LC-MS/MS assay will provide the basis for further large-scale clinical studies to explore these analytes as molecular markers for the patients with renal insufficiency. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

    Science.gov (United States)

    Hayton, Sarah; Maker, Garth L; Mullaney, Ian; Trengove, Robert D

    2017-12-01

    Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

  5. 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,...

  6. 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

  7. Control of Strobilurin Fungicides in Wheat Using Direct Analysis in Real Time Accurate Time-of-Flight and Desorption Electrospray Ionization Linear Ion Trap Mass Spectrometry

    NARCIS (Netherlands)

    Schurek, J.; Vaclavik, L.; Hooijerink, H.; Lacina, O.; Poustka, J.; Sharman, M.; Caldow, M.; Nielen, M.W.F.; Hajslova, J.

    2008-01-01

    Ambient mass spectrometry has been used for the analysis of strobilurin residues in wheat. The use of this novel, challenging technique, employing a direct analysis in a real time (DART) ion-source coupled with a time-of-flight mass spectrometer (TOF MS) and a desorption electrospray ionization

  8. Development of accurate mass spectrometric routine and reference methods for the determination of trace amounts of iridium and rhodium in photographic emulsionsf

    NARCIS (Netherlands)

    Krystek, Petra; Heumann, Klaus G.

    1999-01-01

    For the determination of trace amounts of iridium and rhodium in photographic emulsions different sample treatment procedures were coupled with inductively coupled plasma mass spectrometry (ICP-MS) and, for iridium, also with negative thermal ionisation isotope dilution mass spectrometry (NTI-IDMS)

  9. 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

  10. Identification of Plasma Metabolomic Profiling for Diagnosis of Esophageal Squamous-Cell Carcinoma Using an UPLC/TOF/MS Platform

    Directory of Open Access Journals (Sweden)

    Lihong Yin

    2013-04-01

    Full Text Available Epidemiological studies indicated that esophageal squamous-cell carcinoma (ESCC is still one of the most common causes of cancer incidence in the world. Searching for valuable markers including circulating endogenous metabolites associated with the risk of esophageal cancer, is extremely important A comparative metabolomics study was performed by using ultraperformance liquid chromatography-electrospray ionization-accurate mass time-of-flight mass spectrometry to analyze 53 pairs of plasma samples from ESCC patients and healthy controls recruited in Huaian, China. The result identified a metabolomic profiling of plasma including 25 upregulated metabolites and five downregulated metabolites, for early diagnosis of ESCC. With a database-based verification protocol, 11 molecules were identified, and six upregulated molecules of interest in ESCC were found to belong to phospholipids as follows: phosphatidylserine, phosphatidic acid, phosphatidyl choline, phosphatidylinositol, phosphatidyl ethanolamine, and sphinganine 1-phosphate. Clinical estimation of metabolic biomarkers through hierarchical cluster analysis in plasma samples from 17 ESCC patients and 29 healthy volunteers indicated that the present metabolite profile could distinguish ESCC patients from healthy individuals. The cluster of aberrant expression of these metabolites in ESCC indicates the critical role of phospholipid metabolism in the oncogenesis of ESCC and suggests its potential ability to assess the risk of ESCC development in addition to currently used risk factors.

  11. DEVELOPMENT OF ANALYTICAL METHODS IN METABOLOMICS FOR THE STUDY OF HEREDITARY AND ACQUIRED GENETIC DISEASE

    OpenAIRE

    Arvonio, Raffaele

    2011-01-01

    METABOLOMICS AND MASS SPECTROMETRY The research project take place in the branch of metabolomics, which involves the systematic study of the metabolites present in a cell and in this area MS, thanks to its potential to carry out controlled experiments of fragmentation, plays a role as a key methodology for identification of various metabolites. The work of thesis project is focused on the analytical methods development for the diagnosis of metabolic diseases and is divided as follows: ...

  12. 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

  13. Potential of dynamically harmonized Fourier transform ion cyclotron resonance cell for high-throughput metabolomics fingerprinting: control of data quality.

    Science.gov (United States)

    Habchi, Baninia; Alves, Sandra; Jouan-Rimbaud Bouveresse, Delphine; Appenzeller, Brice; Paris, Alain; Rutledge, Douglas N; Rathahao-Paris, Estelle

    2018-01-01

    Due to the presence of pollutants in the environment and food, the assessment of human exposure is required. This necessitates high-throughput approaches enabling large-scale analysis and, as a consequence, the use of high-performance analytical instruments to obtain highly informative metabolomic profiles. In this study, direct introduction mass spectrometry (DIMS) was performed using a Fourier transform ion cyclotron resonance (FT-ICR) instrument equipped with a dynamically harmonized cell. Data quality was evaluated based on mass resolving power (RP), mass measurement accuracy, and ion intensity drifts from the repeated injections of quality control sample (QC) along the analytical process. The large DIMS data size entails the use of bioinformatic tools for the automatic selection of common ions found in all QC injections and for robustness assessment and correction of eventual technical drifts. RP values greater than 106 and mass measurement accuracy of lower than 1 ppm were obtained using broadband mode resulting in the detection of isotopic fine structure. Hence, a very accurate relative isotopic mass defect (RΔm) value was calculated. This reduces significantly the number of elemental composition (EC) candidates and greatly improves compound annotation. A very satisfactory estimate of repeatability of both peak intensity and mass measurement was demonstrated. Although, a non negligible ion intensity drift was observed for negative ion mode data, a normalization procedure was easily applied to correct this phenomenon. This study illustrates the performance and robustness of the dynamically harmonized FT-ICR cell to perform large-scale high-throughput metabolomic analyses in routine conditions. Graphical abstract Analytical performance of FT-ICR instrument equipped with a dynamically harmonized cell.

  14. 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

  15. Exploring the Role of Different Neonatal Nutrition Regimens during the First Week of Life by Urinary GC-MS Metabolomics

    National Research Council Canada - National Science Library

    Dessì, Angelica; Murgia, Antonio; Agostino, Rocco; Pattumelli, Maria Grazia; Schirru, Andrea; Scano, Paola; Fanos, Vassilios; Caboni, Pierluigi

    2016-01-01

    In this study, a gas-chromatography mass spectrometry (GC-MS) metabolomics study was applied to examine urine metabolite profiles of different classes of neonates under different nutrition regimens...

  16. 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

  17. 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

  18. A Comprehensive Review of School-Based Body Mass Index Screening Programs and Their Implications for School Health: Do the Controversies Accurately Reflect the Research?

    Science.gov (United States)

    Ruggieri, Dominique G.; Bass, Sarah B.

    2015-01-01

    Background: Whereas legislation for body mass index (BMI) surveillance and screening programs has passed in 25 states, the programs are often subject to ethical debates about confidentiality and privacy, school-to-parent communication, and safety and self-esteem issues for students. Despite this debate, no comprehensive analysis has been completed…

  19. Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects.

    Science.gov (United States)

    Sumner, Lloyd W; Lei, Zhentian; Nikolau, Basil J; Saito, Kazuki

    2015-02-01

    Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This review covers the approximate period of 2000 to 2014, and highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR for metabolite identifications, and X-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.

  20. Increasing rigor in NMR-based metabolomics through validated and open source tools.

    Science.gov (United States)

    Eghbalnia, Hamid R; Romero, Pedro R; Westler, William M; Baskaran, Kumaran; Ulrich, Eldon L; Markley, John L

    2017-02-01

    The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism's phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies. Copyright © 2016. Published by Elsevier Ltd.

  1. A protocol for the investigation of the intracellular Staphylococcus aureus metabolome.

    Science.gov (United States)

    Meyer, Hanna; Liebeke, Manuel; Lalk, Michael

    2010-06-15

    Systems biology studies assume the acquisition of reliable and reproducible data sets. Metabolomics, in particular, requires comprehensive evaluated workflows to enable the analysis of hundreds of different compounds. Therefore, a protocol to elucidate the metabolome of the gram-positive pathogen, Staphylococcus aureus COL strain, grown in a chemically defined medium is introduced here. Different standard operating procedures in the field of metabolome experiments were tested for common pitfalls. These included suitable and fast sampling processes, efficient metabolite extraction, quenching effectiveness (energy charge), and estimation of leakage and recovery of metabolites. Moreover, a cell disruption protocol for S. aureus was developed and optimized for metabolome analyses, for the express purpose of obtaining reproducible data. We used complementary methods (e.g., gas chromatography and/or liquid chromatography coupled with mass spectrometry) to detect the highly chemically diverse groups of metabolites for a global insight into the intracellular metabolism of S. aureus. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  2. 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.

  3. Key elements of metabolomics in the study of biomarkers of diabetes.

    Science.gov (United States)

    Adamski, Jerzy

    2016-12-01

    Metabolomics is instrumental in the analysis of disease mechanisms and biomarkers of disease. The human metabolome is influenced by genetics and environmental interactions and reveals characteristic signatures of disease. Population studies with metabolomics require special study designs and care needs to be taken with pre-analytics. Gas chromatography coupled to mass spectrometry, liquid chromatography coupled to mass spectrometry or NMR are popular techniques used for metabolomic analyses in human cohorts. Metabolomics has been successfully used in the biomarker search for disease prediction and progression, for analyses of drug action and for the development of companion diagnostics. Several metabolites or metabolite classes identified by metabolomics have gained much attention in the field of diabetes research in the search for early disease detection, differentiation of progressor types and compliance with medication. This review summarises a presentation given at the 'New approaches beyond genetics' symposium at the 2015 annual meeting of the EASD. It is accompanied by another review from this symposium by Bernd Mayer (DOI: 10.1007/s00125-016-4032-2 ) and an overview by the Session Chair, Leif Groop (DOI: 10.1007/s00125-016-4014-4 ).

  4. 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...

  5. 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.

  6. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2015-01-01

    To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases. PMID:26090402

  7. 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.

  8. A decade in prostate cancer: from NMR to metabolomics.

    Science.gov (United States)

    DeFeo, Elita M; Wu, Chin-Lee; McDougal, W Scott; Cheng, Leo L

    2011-05-17

    Over the past 30 years, continuous progress in the application of nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance spectroscopic imaging (MRSI) to the detection, diagnosis and characterization of human prostate cancer has turned what began as scientific curiosity into a useful clinical option. In vivo MRSI technology has been integrated into the daily care of prostate cancer patients, and innovations in ex vivo methods have helped to establish NMR-based prostate cancer metabolomics. Metabolomic and multimodality imaging could be the future of the prostate cancer clinic--particularly given the rationale that more accurate interrogation of a disease as complex as human prostate cancer is most likely to be achieved through paradigms involving multiple, instead of single and isolated, parameters. The research and clinical results achieved through in vivo MRSI and ex vivo NMR investigations during the first 11 years of the 21st century illustrate areas where these technologies can be best translated into clinical practice.

  9. Serum metabolomics in oral leukoplakia and oral squamous cell carcinoma.

    Science.gov (United States)

    Sridharan, Gokul; Ramani, Pratibha; Patankar, Sangeeta

    2017-01-01

    Metabolomics is a core discipline of system biology focusing on the study of low molecular weight compounds in biological system. Analysis of human metabolome, which is composed of diverse group of metabolites, can aid in diagnosis and prognosis of oral squamous cell carcinoma (OSCC). The aim of the present study is to analyze and identify serum metabolites in oral leukoplakia and OSCC as a potential diagnostic biomarker and a predictor for malignant transformation of oral leukoplakia. Serum metabolomic profile of patients diagnosed with oral leukoplakia (n = 21) and OSCC (n = 22) was compared with normal controls (n = 18) using quadrupole time of flight-liquid chromatography-mass spectrometry. MassHunter profile software was used for metabolite identification, and statistical analysis to assess the variation of the metabolites was performed using Mass Profiler Professional software. Statistical significance between the three groups was expressed using ANOVA (P oral leukoplakia and OSCC than in normal controls. Furthermore, significant upregulation of 5,6-dihydrouridine, 4-hydroxypenbutolol glucuronide, 8-hydroxyadenine, and putrescine was evident in OSCC group than in oral leukoplakia. Upregulation of L-carnitine, lysine, 2-methylcitric acid, putrescine; 8-hydroxyadenine; 17-estradiol; 5,6-dihydrouridine; and MTA suggests their diagnostic potential in oral leukoplakia and OSCC. Further, a significant upregulation of putrescine, 8-hydroxyadenine, and 5,6-dihydrouridine in OSCC than in oral leukoplakia indicates their potential role in predicting the malignant transformation of oral leukoplakia.

  10. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary

    2009-12-01

    Full Text Available Afaf El-Ansary, Nouf Al-Afaleg, Yousra Al-YafaeeBiochemistry Department, Science College, King Saud University, Riyadh, Saudi ArabiaAbstract: Biomarkers are pharmacological and physiological measurements or specific biochemicals in the body that have a particular molecular feature that makes them useful for measuring the progress of disease or the effects of treatment. Due to the complexity of neurological disorders, it is very difficult to have perfect markers. Brain diseases require plenty of markers to reflect the metabolic impairment of different brain cells. The recent introduction of the metabolomic approach helps the study of neurological diseases based on profiling a multitude of biochemical components related to brain metabolism. This review is a trial to elucidate the possibility to use this approach to identify plasma metabolic markers related to neurological disorders. Previous trials using different metabolomic analyses including nuclear magnetic resonance spectroscopy, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, and capillary electrophoresis will be traced.Keywords: metabolic biomarkers, neurological disorders. metabolome, nuclear magnetic resonance, mass spectrometry, chromatography

  11. 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...

  12. Integration of tissue metabolomics, transcriptomics and immunohistochemistry reveals ERG- and gleason score-specific metabolomic alterations in prostate cancer

    OpenAIRE

    Meller, Sebastian; Meyer, Hellmuth-A; Bethan, Bianca; Dietrich, Dimo; Maldonado, Sandra Gonz?lez; Lein, Michael; Montani, Matteo; Reszka, Regina; Schatz, Philipp; Peter, Erik; Stephan, Carsten; Jung, Klaus; Kamlage, Beate; Kristiansen, Glen

    2015-01-01

    Integrated analysis of metabolomics, transcriptomics and immunohistochemistry can contribute to a deeper understanding of biological processes altered in cancer and possibly enable improved diagnostic or prognostic tests. In this study, a set of 254 metabolites was determined by gas-chromatography/liquid chromatography-mass spectrometry in matched malignant and non-malignant prostatectomy samples of 106 prostate cancer (PCa) patients. Transcription analysis of matched samples was performed on...

  13. Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

    Science.gov (United States)

    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. Methodology/Principal Findings We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract

  14. Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars.

    Directory of Open Access Journals (Sweden)

    Yoshinori Fujimura

    Full Text Available 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. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC in human umbilical vein endothelial cells (HUVECs. This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6 and Sunrouge (SR strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS. Multivariate statistical analyses, principal component analysis (PCA and orthogonal partial least-squares-discriminant analysis (OPLS-DA, revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive

  15. Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars.

    Science.gov (United States)

    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

    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. We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract. Our findings suggest that metabolic profiling

  16. MetaFIND: A feature analysis tool for metabolomics data

    Directory of Open Access Journals (Sweden)

    Cunningham Pádraig

    2008-11-01

    Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

  17. New figures of merit for comprehensive functional genomics data: the metabolomics case

    NARCIS (Netherlands)

    Batenburg, van M.F.; Coulier, L.; Eeuwijk, van F.A.; Smilde, A.K.; Westerhuis, J.A.

    2011-01-01

    In the field of metabolomics, hundreds of metabolites are measured simultaneously by analytical platforms such as gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and NMR to obtain their concentration levels in a reliable way. Analytical repeatability

  18. The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases.

    Science.gov (United States)

    Gianazza, Erica; Tremoli, Elena; Banfi, Cristina

    2014-12-01

    Selected reaction monitoring, also known as multiple reaction monitoring, is a powerful targeted mass spectrometry approach for a confident quantitation of proteins/peptides in complex biological samples. In recent years, its optimization and application have become pivotal and of great interest in clinical research to derive useful outcomes for patient care. Thus, selected reaction monitoring/multiple reaction monitoring is now used as a highly sensitive and selective method for the evaluation of protein abundances and biomarker verification with potential applications in medical screening. This review describes technical aspects for the development of a robust multiplex assay and discussing its recent applications in cardiovascular proteomics: verification of promising disease candidates to select only the highest quality peptides/proteins for a preclinical validation, as well as quantitation of protein isoforms and post-translational modifications.

  19. Accurate determination of bromine and iodine in medicinal plants by inductively coupled plasma-mass spectrometry after microwave-induced combustion

    Science.gov (United States)

    Nascimento, Mariele S.; Mendes, Ana Luiza G.; Henn, Alessandra S.; Picoloto, Rochele S.; Mello, Paola A.; Flores, Erico M. M.

    2017-12-01

    In this work, a method for the determination of bromine and iodine in medicinal plants by inductively coupled plasma mass spectrometry (ICP-MS) after digestion by microwave-induced combustion (MIC) was developed. Medicinal plants were pressed as pellets and combusted at 20 bar of oxygen. The suitability of absorbing solution (water, 50 mmol L- 1 (NH4)2CO3, 10 mmol L- 1, 25 mmol L- 1, 50 mmol L- 1 or 100 mmol L- 1 NH4OH) was evaluated and a reflux step of 5 min was applied after combustion. The accuracy of the proposed method was evaluated by using certified reference materials (CRMs) of apple leaves and peach leaves and also by spiked samples. Using 50 mmol L- 1 NH4OH as absorbing solution, recoveries close to 100% for bromine and iodine were obtained as well as a low relative standard deviation (5%). No statistical difference (t-test, 95% of confidence level) was observed between the values obtained by ICP-MS after MIC digestion and the certified values. One of the important advantages of the proposed method is that it allowed the use of a relatively high sample mass (1000 mg) of medicinal plant resulting in low limits of quantification (0.033 μg g- 1 and 0.003 μg g- 1 for Br and I, respectively). Blanks were always negligible and only diluted solutions were used, in agreement with current recommendations for analytical methods. A high digestion efficiency was achieved (> 99%) assuring quantitative results. The concentration of analytes in medicinal plants was in the range of 0.17 μg g- 1 to 53.1 μg g- 1 for Br and medicinal plants (125 μg g- 1).

  20. A Metabolomic Strategy to Screen the Prototype Components and Metabolites of Shuang-Huang-Lian Injection in Human Serum by Ultra Performance Liquid Chromatography Coupled with Quadrupole Time-of-Flight Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Mingxing Guo

    2014-01-01

    Full Text Available Shuang-huang-lian injection (SHLI is a famous Chinese patent medicine, which has been wildly used in clinic to treat acute respiratory tract infection, pneumonia, influenza, and so forth. Despite the widespread clinical application, the prototype components and metabolites of SHLI have not been fully elucidated, especially in human body. To discover and screen the constituents or metabolites of Chinese medicine in biofluids tends to be more and more difficult due to the complexity of chemical compositions, metabolic reactions and matrix effects. In this work, a metabolomic strategy to comprehensively elucidate the prototype components and metabolites of SHLI in human serum conducted by UPLC-Q-TOF/MS was developed. Orthogonal partial least squared discriminant analysis (OPLS-DA was applied to distinguish the exogenous, namely, drug-induced constituents, from endogenous in human serum. In the S-plot, 35 drug-induced constituents were found, including 23 prototype compounds and 12 metabolites which indicated that SHLI in human body mainly caused phase II metabolite reactions. It was concluded that the metabolomic strategy for identification of herbal constituents and metabolites in biological samples was successfully developed. This identification and structural elucidation of the chemical compounds provided essential data for further pharmacological and pharmacokinetics study of SHLI.

  1. Development of a Rapid and Accurate Identification Method for Citrobacter Species Isolated from Pork Products Using a Matrix-Assisted Laser-Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS).

    Science.gov (United States)

    Kwak, Hye-Lim; Han, Sun-Kyung; Park, Sunghoon; Park, Si Hong; Shim, Jae-Yong; Oh, Mihwa; Ricke, Steven C; Kim, Hae-Yeong

    2015-09-01

    Previous detection methods for Citrobacter are considered time consuming and laborious. In this study, we have developed a rapid and accurate detection method for Citrobacter species in pork products, using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). A total of 35 Citrobacter strains were isolated from 30 pork products and identified by both MALDI-TOF MS and 16S rRNA gene sequencing approaches. All isolates were identified to the species level by the MALDI-TOF MS, while 16S rRNA gene sequencing results could not discriminate them clearly. These results confirmed that MALDI-TOF MS is a more accurate and rapid detection method for the identification of Citrobacter species.

  2. Metabolomic analysis of platelets during storage

    DEFF Research Database (Denmark)

    Paglia, Giuseppe; Sigurjónsson, Ólafur E; Rolfsson, Óttar

    2015-01-01

    BACKGROUND: Platelet concentrates (PCs) can be prepared using three methods: platelet (PLT)-rich plasma, apheresis, and buffy coat. The aim of this study was to obtain a comprehensive data set that describes metabolism of buffy coat-derived PLTs during storage and to compare it with a previously...... measurements. This data set was obtained by combining a series of standard quality control assays to monitor the quality of stored PLTs and a deep coverage metabolomics study using liquid chromatography coupled with mass spectrometry. RESULTS: Stored PLTs showed a distinct metabolic transition occurring 4 days...... after their collection. The transition was evident in PLT produced by both production methods. Apheresis-derived PLTs showed a clearer phenotype of PLT activation during early days of storage. The activated phenotype of apheresis PLTs was accompanied by a higher metabolic activity, especially related...

  3. 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.

  4. 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

  5. A comprehensive review of school-based body mass index screening programs and their implications for school health: do the controversies accurately reflect the research?

    Science.gov (United States)

    Ruggieri, Dominique G; Bass, Sarah B

    2015-01-01

    Whereas legislation for body mass index (BMI) surveillance and screening programs has passed in 25 states, the programs are often subject to ethical debates about confidentiality and privacy, school-to-parent communication, and safety and self-esteem issues for students. Despite this debate, no comprehensive analysis has been completed that compares and contrasts how these issues differentially affect schools, parents, and students. A keyword search from electronic databases and a review of state legislation related to BMI surveillance and screening were used to identify relevant literature and data focused on surveillance and screening policies, BMI report cards, and parental perceptions of BMI screenings and their child's weight status [corrected]. This article addresses the gap of previous literature by outlining the ethical considerations and implications that BMI screening programs and report cards have for schools, parents, and students, and links these with outcome studies to address whether these controversies are supported by research. Despite the controversies surrounding these programs, this review shows that they can be valuable for all parties and demonstrates BMI screening programs to be vital to the development of robust school-based obesity prevention programs and promotion of healthy lifestyles in schools. © 2014, American School Health Association.

  6. 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

  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. Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia.

    Science.gov (United States)

    Banoei, Mohammad M; Vogel, Hans J; Weljie, Aalim M; Kumar, Anand; Yende, Sachin; Angus, Derek C; Winston, Brent W

    2017-04-19

    Metabolomics is a tool that has been used for the diagnosis and prognosis of specific diseases. The purpose of this study was to examine if metabolomics could be used as a potential diagnostic and prognostic tool for H1N1 pneumonia. Our hypothesis was that metabolomics can potentially be used early for the diagnosis and prognosis of H1N1 influenza pneumonia. (1)H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to profile the metabolome in 42 patients with H1N1 pneumonia, 31 ventilated control subjects in the intensive care unit (ICU), and 30 culture-positive plasma samples from patients with bacterial community-acquired pneumonia drawn within the first 24 h of hospital admission for diagnosis and prognosis of disease. We found that plasma-based metabolomics from samples taken within 24 h of hospital admission can be used to discriminate H1N1 pneumonia from bacterial pneumonia and nonsurvivors from survivors of H1N1 pneumonia. Moreover, metabolomics is a highly sensitive and specific tool for the 90-day prognosis of mortality in H1N1 pneumonia. This study demonstrates that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU on the basis of plasma samples taken within 24 h of hospital/ICU admission, early in the course of disease.

  9. Metabolomic correlation-network modules in Arabidopsis based on a graph-clustering approach

    Directory of Open Access Journals (Sweden)

    Redestig Henning

    2011-01-01

    Full Text Available Abstract Background Deciphering the metabolome is essential for a better understanding of the cellular metabolism as a system. Typical metabolomics data show a few but significant correlations among metabolite levels when data sampling is repeated across individuals grown under strictly controlled conditions. Although several studies have assessed topologies in metabolomic correlation networks, it remains unclear whether highly connected metabolites in these networks have specific functions in known tissue- and/or genotype-dependent biochemical pathways. Results In our study of metabolite profiles we subjected root tissues to gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS and used published information on the aerial parts of 3 Arabidopsis genotypes, Col-0 wild-type, methionine over-accumulation 1 (mto1, and transparent testa4 (tt4 to compare systematically the metabolomic correlations in samples of roots and aerial parts. We then applied graph clustering to the constructed correlation networks to extract densely connected metabolites and evaluated the clusters by biochemical-pathway enrichment analysis. We found that the number of significant correlations varied by tissue and genotype and that the obtained clusters were significantly enriched for metabolites included in biochemical pathways. Conclusions We demonstrate that the graph-clustering approach identifies tissue- and/or genotype-dependent metabolomic clusters related to the biochemical pathway. Metabolomic correlations complement information about changes in mean metabolite levels and may help to elucidate the organization of metabolically functional modules.

  10. Recent advances in thermal desorption-gas chromatography-mass spectrometery method to eliminate the matrix effect between air and water samples: application to the accurate determination of Henry's law constant.

    Science.gov (United States)

    Kim, Yong-Hyun; Kim, Ki-Hyun

    2014-05-16

    Accurate values for the Henry's law constants are essential to describe the environmental dynamics of a solute, but substantial errors are recognized in many reported data due to practical difficulties in measuring solubility and/or vapor pressure. Despite such awareness, validation of experimental approaches has scarcely been made. An experimental approach based on thermal desorption-gas chromatography-mass spectrometery (TD-GC-MS) method was developed to concurrently allow the accurate determination of target compounds from the headspace and aqueous samples in closed equilibrated system. The analysis of six aromatics and eight non-aromatic oxygenates was then carried out in a static headspace mode. An estimation of the potential bias and mass balance (i.e., sum of mass measured individually from gas and liquid phases vs. the mass initially added to the system) demonstrates compound-specific phase dependency so that the best results are obtained by aqueous (less soluble aromatics) and headspace analysis (more soluble non-aromatics). Accordingly, we were able to point to the possible sources of biases in previous studies and provide the best estimates for the Henry's constants (Matm(-1)): benzene (0.17), toluene (0.15), p-xylene (0.13), m-xylene (0.13), o-xylene (0.19), styrene (0.27); propionaldehyde (9.26), butyraldehyde (6.19), isovaleraldehyde (2.14), n-valeraldehyde (3.98), methyl ethyl ketone (10.5), methyl isobutyl ketone (3.93), n-butyl acetate (2.41), and isobutyl alcohol (22.2). Copyright © 2014 Elsevier B.V. All rights reserved.

  11. 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.

  12. Metabolomic analysis of normal and sickle cell erythrocytes.

    Science.gov (United States)

    Darghouth, D; Koehl, B; Junot, C; Roméo, P-H

    2010-09-01

    Metabolic signatures of specialized circulating hematopoietic cells in physiological or human hematological diseases start to be described. We use a simple and highly reproductive extraction method of erythrocytes metabolites coupled with a liquid chromatography-mass spectrometry based metabolites profiling method to determine metabolomes of normal and sickle cell erythrocytes. Sickle cell erythrocytes and normal erythrocytes metabolomes display major differences in glycolysis, in glutathione, in ascorbate metabolisms and in metabolites associated to membranes turnover. In addition, the amounts of metabolites derived from urea cycle and NO metabolism that partly take place within erythrocyte were different between normal and sickle cell erythrocytes. These results show that metabolic profiling of red blood cell diseases can now be determined and might indicate new biomarkers that can be used for the follow-up of sickle cell patients. Copyright 2010. Published by Elsevier SAS.

  13. Metabolome Consistency: Additional Parazoanthines from the Mediterranean Zoanthid Parazoanthus Axinellae

    Directory of Open Access Journals (Sweden)

    Coralie Audoin

    2014-05-01

    Full Text Available Ultra-high pressure liquid chromatography coupled to high resolution mass spectrometry (UHPLC-MS/MS analysis of the organic extract obtained from the Mediterranean zoanthid Parazoanthus axinellae yielded to the identification of five new parazoanthines F-J. The structures were fully determined by comparison of fragmentation patterns with those of previously isolated parazoathines and MS/MS spectra simulation of in silico predicted compounds according to the metabolome consistency. The absolute configuration of the new compounds has been assigned using on-line electronic circular dichroism (UHPLC-ECD. We thus demonstrated the potential of highly sensitive hyphenated techniques to characterize the structures of a whole family of natural products within the metabolome of a marine species. Minor compounds can be characterized using these techniques thus avoiding long isolation processes that may alter the structure of the natural products. These results are also of interest to identify putative bioactive compounds present at low concentration in a complex mixture.

  14. Polyphenol metabolomics of twenty Italian red grape varieties

    Directory of Open Access Journals (Sweden)

    Bavaresco Luigi

    2016-01-01

    Full Text Available “Suspect screening analysis”method to study grape metabolomics, was performed. This method is a middle-way “targeted” and “untargeted”approach aiming at identifying the largest number of metabolites in grape samples. A new database of putative grape and wine metabolites (GrapeMetabolomics, which currently contains around 1,100 compounds, was constructed by CREA at Conegliano. By performing high-resolution mass spectrometry analysis of the grape extract in both positive and negative ionization mode, averaging 320-450 putative compounds are identified. Most of them are grape polyphenols, such as anthocyanins, flavonols and stilbene derivatives. By performing PCA and Cluster Analysis the composition in anthocyanins and flavonols of 20 Italian red grape varieties, was studied.

  15. An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis.

    Science.gov (United States)

    Cho, Hye Rim; Wen, He; Ryu, Young Jin; An, Yong Jin; Kim, Hyo Cheol; Moon, Woo Kyung; Han, Moon Hee; Park, Sunghyouk; Choi, Seung Hong

    2012-10-15

    Leptomeningeal carcinomatosis (LC) is the third most common metastatic complication of the central nervous system. However, the current modalities to reliably diagnose this condition are not satisfactory. Here, we report a preclinical proof of concept for a metabolomics-based diagnostic strategy using a rat LC model incorporating glioma cells that stably express green fluorescent protein. Cytologic diagnoses gave 66.7% sensitivity for the 7-day LC group and 0% for the 3-day LC group. MR imaging could not diagnose LC at these stages. In contrast, nuclear magnetic resonance-based metabolomics on cerebrospinal fluid detected marked differences between the normal and LC groups. Predictions based on the multivariate model provided sensitivity, specificity, and overall accuracy of 88% to 89% in both groups for LC diagnosis. Further statistical analyses identified lactate, acetate, and creatine as specific for the 7-day LC group, with glucose a specific marker of the normal group. Overall, we showed that the metabolomics approach provided both earlier and more accurate diagnostic results than cytology and MR imaging in current use.

  16. Accurate determination of 3-alkyl-2-methoxypyrazines in wines by gas chromatography quadrupole time-of-flight tandem mass spectrometry following solid-phase extraction and dispersive liquid-liquid microextraction.

    Science.gov (United States)

    Fontana, Ariel; Rodríguez, Isaac; Cela, Rafael

    2017-09-15

    A new reliable method for the determination 3-alkyl-2-methoxypyrazines (MPs) in wine samples based on the sequential combination of solid-phase extraction (SPE), dispersive liquid-liquid microextraction (DLLME) and gas chromatography (GC) quadrupole time-of-flight accurate tandem mass spectrometry (QTOF-MS/MS) is presented. Primary extraction of target analytes was carried out by using a reversed-phase Oasis HLB (200mg) SPE cartridge combined with acetonitrile as elution solvent. Afterwards, the SPE extract was submitted to DLLME concentration using 0.06mL carbon tetrachloride (CCl4) as extractant. Under final working conditions, sample concentration factors above 379 times and limits of quantification (LOQs) between 0.3 and 2.1ngL(-1) were achieved. Moreover, the overall extraction efficiency of the method was unaffected by the particular characteristics of each wine; thus, accurate results (relative recoveries from 84 to 108% for samples spiked at concentrations from 5 to 25ngL(-1)) were obtained using matrix-matched standards, without using standard additions over every sample. Highly selective chromatographic records were achieved considering a mass window of 5mDa, centered in the quantification product ion corresponding to each compound. Twelve commercial wines, elaborated with grapes from different varieties and geographical origins, were processed with the optimized method. The 2-isobutyl-3-methoxypyrazine (IBMP) was determined at levels above the LOQs of the method in half of the samples. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data.

    Science.gov (United States)

    Grissa, Dhouha; Pétéra, Mélanie; Brandolini, Marion; Napoli, Amedeo; Comte, Blandine; Pujos-Guillot, Estelle

    2016-01-01

    Untargeted metabolomics is a powerful phenotyping tool for better understanding biological mechanisms involved in human pathology development and identifying early predictive biomarkers. This approach, based on multiple analytical platforms, such as mass spectrometry (MS), chemometrics and bioinformatics, generates massive and complex data that need appropriate analyses to extract the biologically meaningful information. Despite various tools available, it is still a challenge to handle such large and noisy datasets with limited number of individuals without risking overfitting. Moreover, when the objective is focused on the identification of early predictive markers of clinical outcome, few years before occurrence, it becomes essential to use the appropriate algorithms and workflow to be able to discover subtle effects among this large amount of data. In this context, this work consists in studying a workflow describing the general feature selection process, using knowledge discovery and data mining methodologies to propose advanced solutions for predictive biomarker discovery. The strategy was focused on evaluating a combination of numeric-symbolic approaches for feature selection with the objective of obtaining the best combination of metabolites producing an effective and accurate predictive model. Relying first on numerical approaches, and especially on machine learning methods (SVM-RFE, RF, RF-RFE) and on univariate statistical analyses (ANOVA), a comparative study was performed on an original metabolomic dataset and reduced subsets. As resampling method, LOOCV was applied to minimize the risk of overfitting. The best k-features obtained with different scores of importance from the combination of these different approaches were compared and allowed determining the variable stabilities using Formal Concept Analysis. The results revealed the interest of RF-Gini combined with ANOVA for feature selection as these two complementary methods allowed selecting the 48

  18. Combinatory Evaluation of Transcriptome and Metabolome Profiles of Low Temperature-induced Resistant Ascites Syndrome in Broiler Chickens

    OpenAIRE

    Shourong Shi; Yiru Shen; Shan Zhang; Zhenhua Zhao; Zhuocheng Hou; Huaijun Zhou; Jianmin Zou; Yuming Guo

    2017-01-01

    To select metabolic biomarkers and differentially expressed genes (DEGs) associated with resistant-ascites syndrome (resistant-AS), we used innovative techniques such as metabolomics and transcriptomics to comparatively examine resistant-AS chickens and AS controls. Metabolomic evaluation of chicken serum using ultra-performance liquid chromatography-quadruple time-of-flight high-sensitivity mass spectrometry (UPLC-QTOF/HSMS) showed significantly altered lysoPC(18:1), PE(18:3/16:0), PC(20:1/1...

  19. 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...

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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...

  6. 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...

  7. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study......Background: More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies...

  8. Accurate identification and quantification of 11-nor-delta(9)-tetrahydrocannabinol-9-carboxylic acid in urine drug testing: evaluation of a direct high efficiency liquid chromatographic-mass spectrometric method.

    Science.gov (United States)

    Stephanson, Nikolai; Josefsson, Martin; Kronstrand, Robert; Beck, Olof

    2008-08-01

    A direct liquid chromatographic-tandem mass spectrometric (LC-MS/MS) method for measurement of urinary Delta(9)-tetrahydrocannabinol carboxylic acid (THCA) was developed. The method involved dilution of the urine sample with water containing (2)H(9)-deuterated analogue as internal standard, hydrolysis with ammonia, reversed phase chromatography using a Waters ultra-performance liquid chromatography (UPLC) equipment with gradient elution, negative electrospray ionization, and monitoring of two product ions in selected reaction monitoring mode. The measuring range was 2-1000 ng/mL for THCA, and the intra- and inter-assay imprecision, expressed as the coefficient of variation, was below 5%. Influence from urine matrix on ionization efficiency was noted in infusion experiments, but was compensated for by the internal standard. Comparison with established gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods in authentic patient samples demonstrated accuracy in both qualitative and quantitative results. A small difference in mean ratios (~15%) may be explained by the use of different hydrolysis procedures between methods. In conclusion, the high efficiency LC-MS/MS method was capable of accurately identify and quantify THCA in urine with a capacity of 14 samples per hour.

  9. Ways for accurate analysis of high purity materials using the glow discharge mass spectrometry (GD-MS); Wege zur genauen Charakterisierung hochreiner Materialien mit der Glimmentladungs-Massenspektrometrie (GD-MS)

    Energy Technology Data Exchange (ETDEWEB)

    Gusarova, Tamara

    2010-04-14

    The main aim of this work consists in the investigation, development and application of improved possibilities of accurate analysis of high purity materials using the solid sample technique of Glow Discharge Mass Spectrometry (GD-MS), as well as in the sensitivity enhancement of GD Optical Emission Spectrometry (GD-OES) by implicating the hollow cathode effect. The emphasis of the PhD thesis consists in the accurate quantification for GD-MS. As appropriate certified reference materials (CRMs) for calibration are lacking in most cases an accurate quantification especially for trace elements mass fractions at {mu}g kg{sup -1} level can often not be achieved. To overcome this problem and to expand the possibilities of modern GD-MS hereby, synthetic standards were applied for calibration of both high resolution GD-MS instruments ''VG 9000'' and ''Element GD''. The standards were prepared by doping of matrix powder with trace element standard solutions followed by drying and pressing the doped powder to compact pellets. With the quantification approach worked out and described here accurate analysis results with small uncertainties can be achieved for most elements of periodic table in almost every matrix composition. Furthermore direct traceability of the analytical results to the International System of Units (SI) is provided ensuring their higher metrological quality. Numerous additional systematic investigations concerning the preparation of the synthetic standards and their properties were carried out. The results of calibration of GD-MS instruments with synthetic standards for Co (Co-C), Cu, In, Fe and Zn matrices were checked by measuring CRMs. These results were also contrasted with those of other quantification approaches, as usually used in GD-MS routine. The results achieved with synthetic standards had the highest accuracy. The successful participation in the round robin test CCQM-P107 between international

  10. Lactation-related metabolic mechanism investigated based on mammary gland metabolomics and 4 biofluids' metabolomics relationships in dairy cows.

    Science.gov (United States)

    Sun, Hui-Zeng; Shi, Kai; Wu, Xue-Hui; Xue, Ming-Yuan; Wei, Zi-Hai; Liu, Jian-Xin; Liu, Hong-Yun

    2017-12-02

    Lactation is extremely important for dairy cows; however, the understanding of the underlying metabolic mechanisms is very limited. This study was conducted to investigate the inherent metabolic patterns during lactation using the overall biofluid metabolomics and the metabolic differences from non-lactation periods, as determined using partial tissue-metabolomics. We analyzed the metabolomic profiles of four biofluids (rumen fluid, serum, milk and urine) and their relationships in six mid-lactation Holstein cows and compared their mammary gland (MG) metabolomic profiles with those of six non-lactating cows by using gas chromatography-time of flight/mass spectrometry. In total, 33 metabolites were shared among the four biofluids, and 274 metabolites were identified in the MG tissues. The sub-clusters of the hierarchical clustering analysis revealed that the rumen fluid and serum metabolomics profiles were grouped together and highly correlated but were separate from those for milk. Urine had the most different profile compared to the other three biofluids. Creatine was identified as the most different metabolite among the four biofluids (VIP = 1.537). Five metabolic pathways, including gluconeogenesis, pyruvate metabolism, the tricarboxylic acid cycle (TCA cycle), glycerolipid metabolism, and aspartate metabolism, showed the most functional enrichment among the four biofluids (false discovery rate 2). Clear discriminations were observed in the MG metabolomics profiles between the lactating and non-lactating cows, with 54 metabolites having a significantly higher abundance (P  1) in the lactation group. Lactobionic acid, citric acid, orotic acid and oxamide were extracted by the S-plot as potential biomarkers of the metabolic difference between lactation and non-lactation. The TCA cycle, glyoxylate and dicarboxylate metabolism, glutamate metabolism and glycine metabolism were determined to be pathways that were significantly impacted (P 0.1) in the

  11. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    Directory of Open Access Journals (Sweden)

    Joanna Hajduk

    2015-12-01

    Full Text Available The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18 and a matched control group (n = 13. The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44% and specificity (84.62%, as well as the total group membership classification value (90.32% calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

  12. Recent advances in liquid-phase separations for clinical metabolomics.

    Science.gov (United States)

    Kohler, Isabelle; Giera, Martin

    2017-01-01

    Over the last decades, several technological improvements have been achieved in liquid-based separation techniques, notably, with the advent of fully porous sub-2 μm particles and superficially porous sub-3 μm particles, the comeback of supercritical fluid chromatography, and the development of alternative chromatographic modes such as hydrophilic interaction chromatography. Combined with mass spectrometry, these techniques have demonstrated their added value, substantially increasing separation efficiency, selectivity, and speed of analysis. These benefits are essential in modern clinical metabolomics typically involving the study of large-scale sample cohorts and the analysis of thousands of metabolites showing extensive differences in physicochemical properties. This review presents a brief overview of the recent developments in liquid-phase separation sciences in the context of clinical metabolomics, focusing on increased throughput as well as metabolite coverage. Relevant metabolomics applications highlighting the benefits of ultra-high performance liquid chromatography, core-shell technology, high-temperature liquid chromatography, capillary electrophoresis, supercritical fluid chromatography, and hydrophilic interaction chromatography are discussed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Metabolomics as a promising tool for early osteoarthritis diagnosis.

    Science.gov (United States)

    de Sousa, E B; Dos Santos, G C; Duarte, M E L; Moura, V; Aguiar, D P

    2017-09-21

    Osteoarthritis (OA) is the main cause of disability worldwide, due to progressive articular cartilage loss and degeneration. According to recent research, OA is more than just a degenerative disease due to some metabolic components associated to its pathogenesis. However, no biomarker has been identified to detect this disease at early stages or to track its development. Metabolomics is an emerging field and has the potential to detect many metabolites in a single spectrum using high resolution nuclear magnetic resonance (NMR) techniques or mass spectrometry (MS). NMR is a reproducible and reliable non-destructive analytical method. On the other hand, MS has a lower detection limit and is more destructive, but it is more sensitive. NMR and MS are useful for biological fluids, such as urine, blood plasma, serum, or synovial fluid, and have been used for metabolic profiling in dogs, mice, sheep, and humans. Thus, many metabolites have been listed as possibly associated to OA pathogenesis. The goal of this review is to provide an overview of the studies in animal models and humans, regarding the use of metabolomics as a tool for early osteoarthritis diagnosis. The concept of osteoarthritis as a metabolic disease and the importance of detecting a biomarker for its early diagnosis are highlighted. Then, some studies in plasma and synovial tissues are shown, and finally the application of metabolomics in the evaluation of synovial fluid is described.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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

  19. Metabolomics enables precision medicine: "A White Paper, Community Perspective".

    Science.gov (United States)

    Beger, Richard D; Dunn, Warwick; Schmidt, Michael A; Gross, Steven S; Kirwan, Jennifer A; Cascante, Marta; Brennan, Lorraine; Wishart, David S; Oresic, Matej; Hankemeier, Thomas; Broadhurst, David I; Lane, Andrew N; Suhre, Karsten; Kastenmüller, Gabi; Sumner, Susan J; Thiele, Ines; Fiehn, Oliver; Kaddurah-Daouk, Rima

    Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and

  20. 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

  1. 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.

  2. Integration of tissue metabolomics, transcriptomics and immunohistochemistry reveals ERG- and gleason score-specific metabolomic alterations in prostate cancer

    Science.gov (United States)

    Meller, Sebastian; Meyer, Hellmuth-A; Bethan, Bianca; Dietrich, Dimo; Maldonado, Sandra González; Lein, Michael; Montani, Matteo; Reszka, Regina; Schatz, Philipp; Peter, Erik; Stephan, Carsten; Jung, Klaus; Kamlage, Beate; Kristiansen, Glen

    2016-01-01

    Integrated analysis of metabolomics, transcriptomics and immunohistochemistry can contribute to a deeper understanding of biological processes altered in cancer and possibly enable improved diagnostic or prognostic tests. In this study, a set of 254 metabolites was determined by gas-chromatography/liquid chromatography-mass spectrometry in matched malignant and non-malignant prostatectomy samples of 106 prostate cancer (PCa) patients. Transcription analysis of matched samples was performed on a set of 15 PCa patients using Affymetrix U133 Plus 2.0 arrays. Expression of several proteins was immunohistochemically determined in 41 matched patient samples and the association with clinico-pathological parameters was analyzed by an integrated data analysis. These results further outline the highly deregulated metabolism of fatty acids, sphingolipids and polyamines in PCa. For the first time, the impact of the ERG translocation on the metabolome was demonstrated, highlighting an altered fatty acid oxidation in TMPRSS2-ERG translocation positive PCa specimens. Furthermore, alterations in cholesterol metabolism were found preferentially in high grade tumors, enabling the cells to create energy storage. With this integrated analysis we could not only confirm several findings from previous metabolomic studies, but also contradict others and finally expand our concepts of deregulated biological pathways in PCa. PMID:26623558

  3. Global metabolomic profiling of human serum from obese individuals by liquid chromatography-time-of-flight/mass spectrometry to evaluate the intake of breakfasts prepared with heated edible oils.

    Science.gov (United States)

    Ferreiro-Vera, Carlos; Priego-Capote, Feliciano; Calderón-Santiago, Mónica; Luque de Castro, María D

    2013-12-01

    The metabolic profile of human serum after intake of breakfasts prepared with different heated vegetable oils has been studied. Four oils (olive and sunflower oils, pure and enriched with natural and artificial oxidation inhibitors) were subjected to a simulated heated process prior to breakfast preparation. A metabolomics global profiling approach performed on post-basal serum samples revealed statistical differences among individuals based on breakfast intake, and identified compounds responsible for such differences. Serum samples obtained in basal state (control samples) and 2 and 4h after programmed intakes were analyzed by LC-TOF/MS. The resulting fingerprints were compared and differences between basal and post-basal states evaluated, observing that the intake of different breakfasts altered the metabolic signature of serum. Analysis models based on PLS algorithms were developed to discriminate individuals in post-basal state for each intervention breakfast. Then, Volcano tests enabled to detect significant molecular entities explaining the variability associated to each breakfast. It is worth emphasizing the importance of fatty acids, their derivatives and phospholipids for tentative identification. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. 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

  5. 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 net