Sample records for isotope-resolved metabolomic analysis

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

    PubMed Central

    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

  2. Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

    PubMed

    Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

    2014-01-01

    Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

  3. Application of Stable Isotope-Assisted Metabolomics for Cell Metabolism Studies

    PubMed Central

    You, Le; Zhang, Baichen; Tang, Yinjie J.

    2014-01-01

    The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other “omics” analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research. PMID:24957020

  4. Stable isotope resolved metabolomics reveals the role of anabolic and catabolic processes in glyphosate-induced amino acid accumulation in Amaranthus palmeri biotypes

    USDA-ARS?s Scientific Manuscript database

    Using stable isotope resolved metabolomics (SIRM), we characterized the role of anabolic (de novo synthesis) vs catabolic (protein catalysis) processes contributing to free amino acid pools in glyphosate susceptible (S) and resistant (R) Amaranthus palmeri biotypes. Following exposure to glyphosate ...

  5. Natural isotope correction of MS/MS measurements for metabolomics and (13)C fluxomics.

    PubMed

    Niedenführ, Sebastian; ten Pierick, Angela; van Dam, Patricia T N; Suarez-Mendez, Camilo A; Nöh, Katharina; Wahl, S Aljoscha

    2016-05-01

    Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. © 2015 Wiley Periodicals, Inc.

  6. Metabolomics of Early Stage Plant Cell–Microbe Interaction Using Stable Isotope Labeling

    PubMed Central

    Pang, Qiuying; Zhang, Tong; Wang, Yang; Kong, Wenwen; Guan, Qijie; Yan, Xiufeng; Chen, Sixue

    2018-01-01

    Metabolomics has been used in unraveling metabolites that play essential roles in plant–microbe (including pathogen) interactions. However, the problem of profiling a plant metabolome with potential contaminating metabolites from the coexisting microbes has been largely ignored. To address this problem, we implemented an effective stable isotope labeling approach, where the metabolome of a plant bacterial pathogen Pseudomonas syringae pv. tomato (Pst) DC3000 was labeled with heavy isotopes. The labeled bacterial cells were incubated with Arabidopsis thaliana epidermal peels (EPs) with guard cells, and excessive bacterial cells were subsequently removed from the plant tissues by washing. The plant metabolites were characterized by liquid chromatography mass spectrometry using multiple reactions monitoring, which can differentiate plant and bacterial metabolites. Targeted metabolomic analysis suggested that Pst DC3000 infection may modulate stomatal movement by reprograming plant signaling and primary metabolic pathways. This proof-of-concept study demonstrates the utility of this strategy in differentiation of the plant and microbe metabolomes, and it has broad applications in studying metabolic interactions between microbes and other organisms. PMID:29922325

  7. Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM).

    PubMed

    Yang, Ye; Fan, Teresa W-M; Lane, Andrew N; Higashi, Richard M

    2017-07-11

    Amino acids have crucial roles in central metabolism, both anabolic and catabolic. To elucidate these roles, steady-state concentrations of amino acids alone are insufficient, as each amino acid participates in multiple pathways and functions in a complex network, which can also be compartmentalized. Stable Isotope-Resolved Metabolomics (SIRM) is an approach that uses atom-resolved tracking of metabolites through biochemical transformations in cells, tissues, or whole organisms. Using different elemental stable isotopes to label multiple metabolite precursors makes it possible to resolve simultaneously the utilization of these precursors in a single experiment. Conversely, a single precursor labeled with two (or more) different elemental isotopes can trace the allocation of e.g. C and N atoms through the network. Such dual-label experiments however challenge the resolution of conventional mass spectrometers, which must distinguish the neutron mass differences among different elemental isotopes. This requires ultrahigh resolution Fourier transform mass spectrometry (UHR-FTMS). When combined with direct infusion nano-electrospray ion source (nano-ESI), UHR-FTMS can provide rapid, global, and quantitative analysis of all possible mass isotopologues of metabolites. Unfortunately, very low mass polar metabolites such as amino acids can be difficult to analyze by current models of UHR-FTMS, plus the high salt content present in typical cell or tissue polar extracts may cause unacceptable ion suppression for sources such as nano-ESI. Here we describe a modified method of ethyl chloroformate (ECF) derivatization of amino acids to enable rapid quantitative analysis of stable isotope labeled amino acids using nano-ESI UHR-FTMS. This method showed excellent linearity with quantifiable limits in the low nanomolar range represented in microgram quantities of biological specimens, which results in extracts with total analyte abundances in the low to sub-femtomole range. We have

  8. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2017-01-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. PMID:28239968

  9. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future.

    PubMed

    Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

    2016-08-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  10. Melatonin Decreases Glucose Metabolism in Prostate Cancer Cells: A 13C Stable Isotope-Resolved Metabolomic Study.

    PubMed

    Hevia, David; Gonzalez-Menendez, Pedro; Fernandez-Fernandez, Mario; Cueto, Sergio; Rodriguez-Gonzalez, Pablo; Garcia-Alonso, Jose I; Mayo, Juan C; Sainz, Rosa M

    2017-07-26

    The pineal neuroindole melatonin exerts an exceptional variety of systemic functions. Some of them are exerted through its specific membrane receptors type 1 and type 2 (MT1 and MT2) while others are mediated by receptor-independent mechanisms. A potential transport of melatonin through facilitative glucose transporters (GLUT/ SLC2A ) was proposed in prostate cancer cells. The prostate cells have a particular metabolism that changes during tumor progression. During the first steps of carcinogenesis, oxidative phosphorylation is reactivated while the switch to the "Warburg effect" only occurs in advanced tumors and in the metastatic stage. Here, we investigated whether melatonin might change prostate cancer cell metabolism. To do so, 13 C stable isotope-resolved metabolomics in androgen sensitive LNCaP and insensitive PC-3 prostate cancer cells were employed. In addition to metabolite 13 C-labeling, ATP/AMP levels, and lactate dehydrogenase or pentose phosphate pathway activity were measured. Melatonin reduces lactate labeling in androgen-sensitive cells and it also lowers 13 C-labeling of tricarboxylic acid cycle metabolites and ATP production. In addition, melatonin reduces lactate 13 C-labeling in androgen insensitive prostate cancer cells. Results demonstrated that melatonin limits glycolysis as well as the tricarboxylic acid cycle and pentose phosphate pathway in prostate cancer cells, suggesting that the reduction of glucose uptake is a major target of the indole in this tumor type.

  11. Preclinical models for interrogating drug action in human cancers using Stable Isotope Resolved Metabolomics (SIRM).

    PubMed

    Lane, Andrew N; Higashi, Richard M; Fan, Teresa W-M

    2016-07-01

    In this review we compare the advantages and disadvantages of different model biological systems for determining the metabolic functions of cells in complex environments, how they may change in different disease states, and respond to therapeutic interventions. All preclinical drug-testing models have advantages and drawbacks. We compare and contrast established cell, organoid and animal models with ex vivo organ or tissue culture and in vivo human experiments in the context of metabolic readout of drug efficacy. As metabolism reports directly on the biochemical state of cells and tissues, it can be very sensitive to drugs and/or other environmental changes. This is especially so when metabolic activities are probed by stable isotope tracing methods, which can also provide detailed mechanistic information on drug action. We have developed and been applying Stable Isotope-Resolved Metabolomics (SIRM) to examine metabolic reprogramming of human lung cancer cells in monoculture, in mouse xenograft/explant models, and in lung cancer patients in situ (Lane et al. 2011; T. W. Fan et al. 2011; T. W-M. Fan et al. 2012; T. W. Fan et al. 2012; Xie et al. 2014b; Ren et al. 2014a; Sellers et al. 2015b). We are able to determine the influence of the tumor microenvironment using these models. We have now extended the range of models to fresh human tissue slices, similar to those originally described by O. Warburg (Warburg 1923), which retain the native tissue architecture and heterogeneity with a paired benign versus cancer design under defined cell culture conditions. This platform offers an unprecedented human tissue model for preclinical studies on metabolic reprogramming of human cancer cells in their tissue context, and response to drug treatment (Xie et al. 2014a). As the microenvironment of the target human tissue is retained and individual patient's response to drugs is obtained, this platform promises to transcend current limitations of drug selection for clinical

  12. Metabolomic Analysis and Visualization Engine for LC–MS Data

    PubMed Central

    Melamud, Eugene; Vastag, Livia; Rabinowitz, Joshua D.

    2017-01-01

    Metabolomic analysis by liquid chromatography–high-resolution mass spectrometry results in data sets with thousands of features arising from metabolites, fragments, isotopes, and adducts. Here we describe a software package, Metabolomic Analysis and Visualization ENgine (MAVEN), designed for efficient interactive analysis of LC–MS data, including in the presence of isotope labeling. The software contains tools for all aspects of the data analysis process, from feature extraction to pathway-based graphical data display. To facilitate data validation, a machine learning algorithm automatically assesses peak quality. Users interact with raw data primarily in the form of extracted ion chromatograms, which are displayed with overlaid circles indicating peak quality, and bar graphs of peak intensities for both unlabeled and isotope-labeled metabolite forms. Click-based navigation leads to additional information, such as raw data for specific isotopic forms or for metabolites changing significantly between conditions. Fast data processing algorithms result in nearly delay-free browsing. Drop-down menus provide tools for the overlay of data onto pathway maps. These tools enable animating series of pathway graphs, e.g., to show propagation of labeled forms through a metabolic network. MAVEN is released under an open source license at http://maven.princeton.edu. PMID:21049934

  13. Quantitative Metabolome Analysis Based on Chromatographic Peak Reconstruction in Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.

    PubMed

    Huan, Tao; Li, Liang

    2015-07-21

    Generating precise and accurate quantitative information on metabolomic changes in comparative samples is important for metabolomics research where technical variations in the metabolomic data should be minimized in order to reveal biological changes. We report a method and software program, IsoMS-Quant, for extracting quantitative information from a metabolomic data set generated by chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). Unlike previous work of relying on mass spectral peak ratio of the highest intensity peak pair to measure relative quantity difference of a differentially labeled metabolite, this new program reconstructs the chromatographic peaks of the light- and heavy-labeled metabolite pair and then calculates the ratio of their peak areas to represent the relative concentration difference in two comparative samples. Using chromatographic peaks to perform relative quantification is shown to be more precise and accurate. IsoMS-Quant is integrated with IsoMS for picking peak pairs and Zero-fill for retrieving missing peak pairs in the initial peak pairs table generated by IsoMS to form a complete tool for processing CIL LC-MS data. This program can be freely downloaded from the www.MyCompoundID.org web site for noncommercial use.

  14. Development of high-performance chemical isotope labeling LC-MS for profiling the human fecal metabolome.

    PubMed

    Xu, Wei; Chen, Deying; Wang, Nan; Zhang, Ting; Zhou, Ruokun; Huan, Tao; Lu, Yingfeng; Su, Xiaoling; Xie, Qing; Li, Liang; Li, Lanjuan

    2015-01-20

    Human fecal samples contain endogenous human metabolites, gut microbiota metabolites, and other compounds. Profiling the fecal metabolome can produce metabolic information that may be used not only for disease biomarker discovery, but also for providing an insight about the relationship of the gut microbiome and human health. In this work, we report a chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS) method for comprehensive and quantitative analysis of the amine- and phenol-containing metabolites in fecal samples. Differential (13)C2/(12)C2-dansyl labeling of the amines and phenols was used to improve LC separation efficiency and MS detection sensitivity. Water, methanol, and acetonitrile were examined as an extraction solvent, and a sequential water-acetonitrile extraction method was found to be optimal. A step-gradient LC-UV setup and a fast LC-MS method were evaluated for measuring the total concentration of dansyl labeled metabolites that could be used for normalizing the sample amounts of individual samples for quantitative metabolomics. Knowing the total concentration was also useful for optimizing the sample injection amount into LC-MS to maximize the number of metabolites detectable while avoiding sample overloading. For the first time, dansylation isotope labeling LC-MS was performed in a simple time-of-flight mass spectrometer, instead of high-end equipment, demonstrating the feasibility of using a low-cost instrument for chemical isotope labeling metabolomics. The developed method was applied for profiling the amine/phenol submetabolome of fecal samples collected from three families. An average of 1785 peak pairs or putative metabolites were found from a 30 min LC-MS run. From 243 LC-MS runs of all the fecal samples, a total of 6200 peak pairs were detected. Among them, 67 could be positively identified based on the mass and retention time match to a dansyl standard library, while 581 and 3197 peak pairs could be putatively

  15. IsoMS: automated processing of LC-MS data generated by a chemical isotope labeling metabolomics platform.

    PubMed

    Zhou, Ruokun; Tseng, Chiao-Li; Huan, Tao; Li, Liang

    2014-05-20

    A chemical isotope labeling or isotope coded derivatization (ICD) metabolomics platform uses a chemical derivatization method to introduce a mass tag to all of the metabolites having a common functional group (e.g., amine), followed by LC-MS analysis of the labeled metabolites. To apply this platform to metabolomics studies involving quantitative analysis of different groups of samples, automated data processing is required. Herein, we report a data processing method based on the use of a mass spectral feature unique to the chemical labeling approach, i.e., any differential-isotope-labeled metabolites are detected as peak pairs with a fixed mass difference in a mass spectrum. A software tool, IsoMS, has been developed to process the raw data generated from one or multiple LC-MS runs by peak picking, peak pairing, peak-pair filtering, and peak-pair intensity ratio calculation. The same peak pairs detected from multiple samples are then aligned to produce a CSV file that contains the metabolite information and peak ratios relative to a control (e.g., a pooled sample). This file can be readily exported for further data and statistical analysis, which is illustrated in an example of comparing the metabolomes of human urine samples collected before and after drinking coffee. To demonstrate that this method is reliable for data processing, five (13)C2-/(12)C2-dansyl labeled metabolite standards were analyzed by LC-MS. IsoMS was able to detect these metabolites correctly. In addition, in the analysis of a (13)C2-/(12)C2-dansyl labeled human urine, IsoMS detected 2044 peak pairs, and manual inspection of these peak pairs found 90 false peak pairs, representing a false positive rate of 4.4%. IsoMS for Windows running R is freely available for noncommercial use from www.mycompoundid.org/IsoMS.

  16. Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

    PubMed Central

    Kümmel, Anne; Panke, Sven; Heinemann, Matthias

    2006-01-01

    As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data. PMID:16788595

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

    PubMed

    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

  18. Global isotope metabolomics reveals adaptive strategies for nitrogen assimilation

    DOE PAGES

    Kurczy, Michael E.; Forsberg, Erica M.; Thorgersen, Michael P.; ...

    2016-04-05

    Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using 15NO 3 as a nitrogen source. In contrast to a control ( Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee ( Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2more » strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. In conclusion, the use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.« less

  19. Global isotope metabolomics reveals adaptive strategies for nitrogen assimilation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kurczy, Michael E.; Forsberg, Erica M.; Thorgersen, Michael P.

    Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using 15NO 3 as a nitrogen source. In contrast to a control ( Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee ( Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2more » strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. In conclusion, the use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.« less

  20. Metabolomics relative quantitation with mass spectrometry using chemical derivatization and isotope labeling

    DOE PAGES

    O'Maille, Grace; Go, Eden P.; Hoang, Linh; ...

    2008-01-01

    Comprehensive detection and quantitation of metabolites from a biological source constitute the major challenges of current metabolomics research. Two chemical derivatization methodologies, butylation and amination, were applied to human serum for ionization enhancement of a broad spectrum of metabolite classes, including steroids and amino acids. LC-ESI-MS analysis of the derivatized serum samples provided a significant signal elevation across the total ion chromatogram to over a 100-fold increase in ionization efficiency. It was also demonstrated that derivatization combined with isotopically labeled reagents facilitated the relative quantitation of derivatized metabolites from individual as well as pooled samples.

  1. Spatially resolved δ13C analysis using laser ablation isotope ratio mass spectrometry

    NASA Astrophysics Data System (ADS)

    Moran, J.; Riha, K. M.; Nims, M. K.; Linley, T. J.; Hess, N. J.; Nico, P. S.

    2014-12-01

    Inherent geochemical, organic matter, and microbial heterogeneity over small spatial scales can complicate studies of carbon dynamics through soils. Stable isotope analysis has a strong history of helping track substrate turnover, delineate rhizosphere activity zones, and identifying transitions in vegetation cover, but most traditional isotope approaches are limited in spatial resolution by a combination of physical separation techniques (manual dissection) and IRMS instrument sensitivity. We coupled laser ablation sampling with isotope measurement via IRMS to enable spatially resolved analysis over solid surfaces. Once a targeted sample region is ablated the resulting particulates are entrained in a helium carrier gas and passed through a combustion reactor where carbon is converted to CO2. Cyrotrapping of the resulting CO2 enables a reduction in carrier gas flow which improves overall measurement sensitivity versus traditional, high flow sample introduction. Currently we are performing sample analysis at 50 μm resolution, require 65 ng C per analysis, and achieve measurement precision consistent with other continuous flow techniques. We will discuss applications of the laser ablation IRMS (LA-IRMS) system to microbial communities and fish ecology studies to demonstrate the merits of this technique and how similar analytical approaches can be transitioned to soil systems. Preliminary efforts at analyzing soil samples will be used to highlight strengths and limitations of the LA-IRMS approach, paying particular attention to sample preparation requirements, spatial resolution, sample analysis time, and the types of questions most conducive to analysis via LA-IRMS.

  2. Identification of N-Acetyltaurine as a Novel Metabolite of Ethanol through Metabolomics-guided Biochemical Analysis*

    PubMed Central

    Shi, Xiaolei; Yao, Dan; Chen, Chi

    2012-01-01

    The influence of ethanol on the small molecule metabolome and the role of CYP2E1 in ethanol-induced hepatotoxicity were investigated using liquid chromatography-mass spectrometry (LC-MS)-based metabolomics platform and Cyp2e1-null mouse model. Histological and biochemical examinations of ethanol-exposed mice indicated that the Cyp2e1-null mice were more resistant to ethanol-induced hepatic steatosis and transaminase leakage than the wild-type mice, suggesting CYP2E1 contributes to ethanol-induced toxicity. Metabolomic analysis of urinary metabolites revealed time- and dose-dependent changes in the chemical composition of urine. Along with ethyl glucuronide and ethyl sulfate, N-acetyltaurine (NAT) was identified as a urinary metabolite that is highly responsive to ethanol exposure and is correlated with the presence of CYP2E1. Subsequent stable isotope labeling analysis using deuterated ethanol determined that NAT is a novel metabolite of ethanol. Among three possible substrates of NAT biosynthesis (taurine, acetyl-CoA, and acetate), the level of taurine was significantly reduced, whereas the levels of acetyl-CoA and acetate were dramatically increased after ethanol exposure. In vitro incubation assays suggested that acetate is the main precursor of NAT, which was further confirmed by the stable isotope labeling analysis using deuterated acetate. The incubations of tissues and cellular fractions with taurine and acetate indicated that the kidney has the highest NAT synthase activity among the tested organs, whereas the cytosol is the main site of NAT biosynthesis inside the cell. Overall, the combination of biochemical and metabolomic analysis revealed NAT is a novel metabolite of ethanol and a potential biomarker of hyperacetatemia. PMID:22228769

  3. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

    PubMed

    Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

    2014-07-01

    Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

  4. Metabolome analysis for discovering biomarkers of gastroenterological cancer.

    PubMed

    Suzuki, Makoto; Nishiumi, Shin; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-09-01

    Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Qualitative metabolome analysis of human cerebrospinal fluid by 13C-/12C-isotope dansylation labeling combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry.

    PubMed

    Guo, Kevin; Bamforth, Fiona; Li, Liang

    2011-02-01

    Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by (13)C-dansyl and (12)C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner. © American Society for Mass Spectrometry, 2011

  6. Qualitative Metabolome Analysis of Human Cerebrospinal Fluid by 13C-/12C-Isotope Dansylation Labeling Combined with Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

    NASA Astrophysics Data System (ADS)

    Guo, Kevin; Bamforth, Fiona; Li, Liang

    2011-02-01

    Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by 13C-dansyl and 12C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner.

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

    PubMed

    Mung, Dorothea; Li, Liang

    2017-04-18

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

  8. Development of isotope labeling LC-MS for human salivary metabolomics and application to profiling metabolome changes associated with mild cognitive impairment.

    PubMed

    Zheng, Jiamin; Dixon, Roger A; Li, Liang

    2012-12-18

    Saliva is a readily available biofluid that may contain metabolites of interest for diagnosis and prognosis of diseases. In this work, a differential (13)C/(12)C isotope dansylation labeling method, combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR-MS), is described for quantitative profiling of the human salivary metabolome. New strategies are presented to optimize the sample preparation and LC-MS detection processes. The strategies allow the use of as little of 5 μL of saliva sample as a starting material to determine the concentration changes of an average of 1058 ion pairs or putative metabolites in comparative saliva samples. The overall workflow consists of several steps including acetone-induced protein precipitation, (12)C-dansylation labeling of the metabolites, and LC-UV measurement of the total concentration of the labeled metabolites in individual saliva samples. A pooled sample was prepared from all the individual samples and labeled with (13)C-dansylation to serve as a reference. Using this metabolome profiling method, it was found that compatible metabolome results could be obtained after saliva samples were stored in tubes normally used for genetic material collection at room temperature, -20 °C freezer, and -80 °C freezer over a period of 1 month, suggesting that many saliva samples already collected in genomic studies could become a valuable resource for metabolomics studies, although the effect of much longer term of storage remains to be determined. Finally, the developed method was applied for analyzing the metabolome changes of two different groups: normal healthy older adults and comparable older adults with mild cognitive impairment (MCI). Top-ranked 18 metabolites successfully distinguished the two groups, among which seven metabolites were putatively identified while one metabolite, taurine, was definitively identified.

  9. Time-resolved comparative metabolomes for Koji fermentation with brown-, white-, and giant embryo-rice.

    PubMed

    Lee, Da Eun; Lee, Sunmin; Singh, Digar; Jang, Eun Seok; Shin, Hye Won; Moon, Byoung Seok; Lee, Choong Hwan

    2017-09-15

    A time-resolved non-targeted metabolomic study towards evaluating the effects of three rice substrate types viz., white rice (WR), giant embryo rice (GER), and brown rice (BR), on Koji fermentation was performed. Notwithstanding the relatively higher proportions of metabolites in unfermented BR (BR 0>WR 0, GER 0), the relative levels of metabolic repertoire in BR Koji were marginally enhanced during 36h fermentation except those for phenolic acids, fatty acids, and vitamins. The WR Koji showed higher levels of lysophospholipids (LysoPC's) and protease-released amino acids (WR 36>GER 36>BR 36). The higher β-glucosidase activity in GER Koji effected the increased levels of sugars and flavonoid aglycons complementing its higher antioxidant activity (GER Koji>BR Koji∼WR Koji). The present study holistically underpins the dynamic metabolomes and enzymatic states during rice Koji fermentation with varying substrate types. The present study finds applications in optimization of commercial Koji production. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    PubMed

    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

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

    PubMed

    Luo, Xian; Li, Liang

    2017-11-07

    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.

  12. Development of an Integrated Metabolomic Profiling Approach for Infectious Diseases Research

    PubMed Central

    Lv, Haitao; Hung, Chia S.; Chaturvedi, Kaveri S.; Hooton, Thomas M.; Henderson, Jeffrey P.

    2013-01-01

    Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ∼2300 molecular features. Principal components analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts. PMID:21922104

  13. Effects of sample injection amount and time-of-flight mass spectrometric detection dynamic range on metabolome analysis by high-performance chemical isotope labeling LC-MS.

    PubMed

    Zhou, Ruokun; Li, Liang

    2015-04-06

    The effect of sample injection amount on metabolome analysis in a chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) platform was investigated. The performance of time-of-flight (TOF) mass spectrometers with and without a high-dynamic-range (HD) detection system was compared in the analysis of (12)C2/(13)C2-dansyl labeled human urine samples. An average of 1635 ± 21 (n = 3) peak pairs or putative metabolites was detected using the HD-TOF-MS, compared to 1429 ± 37 peak pairs from a conventional or non-HD TOF-MS. In both instruments, signal saturation was observed. However, in the HD-TOF-MS, signal saturation was mainly caused by the ionization process, while in the non-HD TOF-MS, it was caused by the detection process. To extend the MS detection range in the non-HD TOF-MS, an automated switching from using (12)C to (13)C-natural abundance peaks for peak ratio calculation when the (12)C peaks are saturated has been implemented in IsoMS, a software tool for processing CIL LC-MS data. This work illustrates that injecting an optimal sample amount is important to maximize the metabolome coverage while avoiding the sample carryover problem often associated with over-injection. A TOF mass spectrometer with an enhanced detection dynamic range can also significantly increase the number of peak pairs detected. In chemical isotope labeling (CIL) LC-MS, relative metabolite quantification is done by measuring the peak ratio of a (13)C2-/(12)C2-labeled peak pair for a given metabolite present in two comparative samples. The dynamic range of peak ratio measurement does not need to be very large, as only subtle changes of metabolite concentrations are encountered in most metabolomic studies where relative metabolome quantification of different groups of samples is performed. However, the absolute concentrations of different metabolites can be very different, requiring a technique to provide a wide detection dynamic range to allow the detection of as

  14. Present and foreseeable future of metabolomics in forensic analysis.

    PubMed

    Castillo-Peinado, L S; Luque de Castro, M D

    2016-06-21

    The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

    PubMed

    Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

    2012-03-01

    MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

  16. Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara J.; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2016-01-01

    The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program’s goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. PMID:27434804

  17. Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

    PubMed

    Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

    2018-01-01

    Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

  18. SECIMTools: a suite of metabolomics data analysis tools.

    PubMed

    Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

    2018-04-20

    Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

  19. LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

    PubMed Central

    Clasquin, Michelle F.; Melamud, Eugene; Rabinowitz, Joshua D.

    2014-01-01

    MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. PMID:22389014

  20. Top-down MALDI-in-source decay-FTICR mass spectrometry of isotopically resolved proteins.

    PubMed

    Nicolardi, Simone; Switzar, Linda; Deelder, André M; Palmblad, Magnus; van der Burgt, Yuri E M

    2015-03-17

    An accurate mass measurement of a known protein provides information on potential amino acid deletions and post-translational modifications. Although this field is dominated by strategies based on electrospray ionization, mass spectrometry (MS) methods using matrix-assisted laser desorption/ionization (MALDI) have the advantage of yielding predominantly singly charged precursor ions, thus avoiding peak overlap from different charge states of multiple species. Such MALDI-MS methods require mass measurement at ultrahigh resolution, which is provided by Fourier transform ion cyclotron resonance (FTICR) mass analyzers. Recently, using a MALDI-FTICR-MS platform equipped with a 15 T magnet, we reported on the mass analysis of intact human serum peptides and small proteins with isotopic resolution up to ∼15 kDa and identified new proteoforms from an accurate measurement of mass distances. In the current study, we have used this FTICR system after an upgrade with a novel dynamically harmonized ICR cell, i.e., ParaCell, for mapping isotopically resolved intact proteins up to about 17 kDa and performed top-down MALDI in-source decay (ISD) analysis. Standard proteins myoglobin (m/z-value 16,950) and ribonuclease B (m/z-value 14,900) were measured with resolving powers of 62,000 and 61,000, respectively. Furthermore, it will be shown that (singly charged) MALDI-ISD fragment ions can be measured at isotopic resolution up to m/z-value 12,000 (e.g., resolving power 39,000 at m/z-value 12,000) providing more reliable identifications. Moreover, examples are presented of pseudo-MS(3) experiments on ISD fragment ions from RNase B by collisional-induced dissociation (CID).

  1. Automated LC-HRMS(/MS) Approach for the Annotation of Fragment Ions Derived from Stable Isotope Labeling-Assisted Untargeted Metabolomics

    PubMed Central

    2014-01-01

    Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native 12C- and uniformly 13C (U-13C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-13C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research. PMID:24965664

  2. Metabolites associated with adaptation of microorganisms to an acidophilic, metal-rich environment identified by stable-isotope-enabled metabolomics.

    PubMed

    Mosier, Annika C; Justice, Nicholas B; Bowen, Benjamin P; Baran, Richard; Thomas, Brian C; Northen, Trent R; Banfield, Jillian F

    2013-03-12

    Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities. Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly

  3. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

    PubMed Central

    Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K. Sreekumaran; Sumner, Susan; Subramaniam, Shankar

    2016-01-01

    The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. PMID:26467476

  4. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    PubMed

    Xia, Jianguo; Wishart, David S

    2016-09-07

    MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

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

    PubMed

    Shen, Weifeng; Han, Wei; Li, Yunong; Meng, Zhiqi; Cai, Leiming; Li, Liang

    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 12 C-/ 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

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

    PubMed

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

    2017-01-01

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

  7. Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data.

    PubMed

    Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

    2016-07-01

    The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program's goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. The complete set of training materials including slide sets and videos can be viewed at http://www.uab.edu/proteomics/metabolomics/workshop/workshop_june_2015.php. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  8. Metabolomic Analysis in Heart Failure.

    PubMed

    Ikegami, Ryutaro; Shimizu, Ippei; Yoshida, Yohko; Minamino, Tohru

    2017-12-25

    It is thought that at least 6,500 low-molecular-weight metabolites exist in humans, and these metabolites have various important roles in biological systems in addition to proteins and genes. Comprehensive assessment of endogenous metabolites is called metabolomics, and recent advances in this field have enabled us to understand the critical role of previously unknown metabolites or metabolic pathways in the cardiovascular system. In this review, we will focus on heart failure and how metabolomic analysis has contributed to improving our understanding of the pathogenesis of this critical condition.

  9. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools.

    PubMed

    Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K Sreekumaran; Sumner, Susan; Subramaniam, Shankar

    2016-01-04

    The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Influential Parameters for the Analysis of Intracellular Parasite Metabolomics.

    PubMed

    Carey, Maureen A; Covelli, Vincent; Brown, Audrey; Medlock, Gregory L; Haaren, Mareike; Cooper, Jessica G; Papin, Jason A; Guler, Jennifer L

    2018-04-25

    Metabolomics is increasingly popular for the study of pathogens. For the malaria parasite Plasmodium falciparum , both targeted and untargeted metabolomics have improved our understanding of pathogenesis, host-parasite interactions, and antimalarial drug treatment and resistance. However, purification and analysis procedures for performing metabolomics on intracellular pathogens have not been explored. Here, we purified in vitro -grown ring-stage intraerythrocytic P. falciparum parasites for untargeted metabolomics studies; the small size of this developmental stage amplifies the challenges associated with metabolomics studies as the ratio between host and parasite biomass is maximized. Following metabolite identification and data preprocessing, we explored multiple confounding factors that influence data interpretation, including host contamination and normalization approaches (including double-stranded DNA, total protein, and parasite numbers). We conclude that normalization parameters have large effects on differential abundance analysis and recommend the thoughtful selection of these parameters. However, normalization does not remove the contribution from the parasite's extracellular environment (culture media and host erythrocyte). In fact, we found that extraparasite material is as influential on the metabolome as treatment with a potent antimalarial drug with known metabolic effects (artemisinin). Because of this influence, we could not detect significant changes associated with drug treatment. Instead, we identified metabolites predictive of host and medium contamination that could be used to assess sample purification. Our analysis provides the first quantitative exploration of the effects of these factors on metabolomics data analysis; these findings provide a basis for development of improved experimental and analytical methods for future metabolomics studies of intracellular organisms. IMPORTANCE Molecular characterization of pathogens such as the

  11. Time-resolved metabolomics analysis of individual differences during the early stage of lipopolysaccharide-treated rats.

    PubMed

    Dai, Die; Gao, Yiqiao; Chen, Jiaqing; Huang, Yin; Zhang, Zunjian; Xu, Fengguo

    2016-10-03

    Lipopolysaccharide (LPS) can lead to uncontrollable cytokine production and eventually cause fatal sepsis syndrome. Individual toxicity difference of LPS has been widely reported. In our study we observed that two thirds of the rats (24/36) died at a given dose of LPS, while the rest (12/36) survived. Tracking the dynamic metabolic change in survival and non-survival rats in the early stage may reveal new system information to understand the inter-individual variation in response to LPS. As the time-resolved datasets are very complex and no single method can elucidate the problem clearly and comprehensively, the static and dynamic metabolomics methods were employed in combination as cross-validation. Intriguingly, some common results have been observed. Lipids were the main different metabolites between survival and non-survival rats in pre-dose serum and in the early stage of infection with LPS. The LPS treatment led to S-adenosly-methionine and total cysteine individual difference in early stage, and subsequent significant perturbations in energy metabolism and oxidative stress. Furthermore, cytokine profiles were analyzed to identify potential biological associations between cytokines and specific metabolites. Our collective findings may provide some heuristic guidance for elucidating the underlying mechanism of individual difference in LPS-mediated disease.

  12. Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing*

    PubMed Central

    Welle, Kevin A.; Zhang, Tian; Hryhorenko, Jennifer R.; Shen, Shichen; Qu, Jun; Ghaemmaghami, Sina

    2016-01-01

    Recent advances in mass spectrometry have enabled system-wide analyses of protein turnover. By globally quantifying the kinetics of protein clearance and synthesis, these methodologies can provide important insights into the regulation of the proteome under varying cellular and environmental conditions. To facilitate such analyses, we have employed a methodology that combines metabolic isotopic labeling (Stable Isotope Labeling in Cell Culture - SILAC) with isobaric tagging (Tandem Mass Tags - TMT) for analysis of multiplexed samples. The fractional labeling of multiple time-points can be measured in a single mass spectrometry run, providing temporally resolved measurements of protein turnover kinetics. To demonstrate the feasibility of the approach, we simultaneously measured the kinetics of protein clearance and accumulation for more than 3000 proteins in dividing and quiescent human fibroblasts and verified the accuracy of the measurements by comparison to established non-multiplexed approaches. The results indicate that upon reaching quiescence, fibroblasts compensate for lack of cellular growth by globally downregulating protein synthesis and upregulating protein degradation. The described methodology significantly reduces the cost and complexity of temporally-resolved dynamic proteomic experiments and improves the precision of proteome-wide turnover data. PMID:27765818

  13. Time-resolved metabolomics reveals metabolic modulation in rice foliage

    PubMed Central

    Sato, Shigeru; Arita, Masanori; Soga, Tomoyoshi; Nishioka, Takaaki; Tomita, Masaru

    2008-01-01

    Background To elucidate the interaction of dynamics among modules that constitute biological systems, comprehensive datasets obtained from "omics" technologies have been used. In recent plant metabolomics approaches, the reconstruction of metabolic correlation networks has been attempted using statistical techniques. However, the results were unsatisfactory and effective data-mining techniques that apply appropriate comprehensive datasets are needed. Results Using capillary electrophoresis mass spectrometry (CE-MS) and capillary electrophoresis diode-array detection (CE-DAD), we analyzed the dynamic changes in the level of 56 basic metabolites in plant foliage (Oryza sativa L. ssp. japonica) at hourly intervals over a 24-hr period. Unsupervised clustering of comprehensive metabolic profiles using Kohonen's self-organizing map (SOM) allowed classification of the biochemical pathways activated by the light and dark cycle. The carbon and nitrogen (C/N) metabolism in both periods was also visualized as a phenotypic linkage map that connects network modules on the basis of traditional metabolic pathways rather than pairwise correlations among metabolites. The regulatory networks of C/N assimilation/dissimilation at each time point were consistent with previous works on plant metabolism. In response to environmental stress, glutathione and spermidine fluctuated synchronously with their regulatory targets. Adenine nucleosides and nicotinamide coenzymes were regulated by phosphorylation and dephosphorylation. We also demonstrated that SOM analysis was applicable to the estimation of unidentifiable metabolites in metabolome analysis. Hierarchical clustering of a correlation coefficient matrix could help identify the bottleneck enzymes that regulate metabolic networks. Conclusion Our results showed that our SOM analysis with appropriate metabolic time-courses effectively revealed the synchronous dynamics among metabolic modules and elucidated the underlying biochemical

  14. Spatially resolved analysis of plutonium isotopic signatures in environmental particle samples by laser ablation-MC-ICP-MS.

    PubMed

    Konegger-Kappel, Stefanie; Prohaska, Thomas

    2016-01-01

    Laser ablation-multi-collector-inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) was optimized and investigated with respect to its performance for determining spatially resolved Pu isotopic signatures within radioactive fuel particle clusters. Fuel particles had been emitted from the Chernobyl nuclear power plant (ChNPP) where the 1986 accident occurred and were deposited in the surrounding soil, where weathering processes caused their transformation into radioactive clusters, so-called micro-samples. The size of the investigated micro-samples, which showed surface alpha activities below 40 mBq, ranged from about 200 to 1000 μm. Direct single static point ablations allowed to identify variations of Pu isotopic signatures not only between distinct fuel particle clusters but also within individual clusters. The resolution was limited to 100 to 120 μm as a result of the applied laser ablation spot sizes and the resolving power of the nuclear track radiography methodology that was applied for particle pre-selection. The determined (242)Pu/(239)Pu and (240)Pu/(239)Pu isotope ratios showed a variation from low to high Pu isotope ratios, ranging from 0.007(2) to 0.047(8) for (242)Pu/(239)Pu and from 0.183(13) to 0.577(40) for (240)Pu/(239)Pu. In contrast to other studies, the applied methodology allowed for the first time to display the Pu isotopic distribution in the Chernobyl fallout, which reflects the differences in the spent fuel composition over the reactor core. The measured Pu isotopic signatures are in good agreement with the expected Pu isotopic composition distribution that is typical for a RBMK-1000 reactor, indicating that the analyzed samples are originating from the ill-fated Chernobyl reactor. The average Pu isotope ratios [(240)Pu/(239)Pu = 0.388(86), (242)Pu/(239)Pu = 0.028(11)] that were calculated from all investigated samples (n = 48) correspond well to previously published results of Pu analyses in contaminated samples from

  15. A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets

    PubMed Central

    Carreer, William J.; Flight, Robert M.; Moseley, Hunter N. B.

    2013-01-01

    New metabolomics applications of ultra-high resolution and accuracy mass spectrometry can provide thousands of detectable isotopologues, with the number of potentially detectable isotopologues increasing exponentially with the number of stable isotopes used in newer isotope tracing methods like stable isotope-resolved metabolomics (SIRM) experiments. This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both 13C and 15N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a 13C/15N-tracing experiment. Finally, we demonstrate the algorithm on a full omics-level dataset. PMID:24404440

  16. Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry.

    PubMed

    Yoshida, Masaru; Hatano, Naoya; Nishiumi, Shin; Irino, Yasuhiro; Izumi, Yoshihiro; Takenawa, Tadaomi; Azuma, Takeshi

    2012-01-01

    Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry, and matrix assisted laser desorption ionization-mass spectrometry. Then, the findings of studies about GC-MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.

  17. Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics.

    PubMed

    Marchand, Jérémy; Martineau, Estelle; Guitton, Yann; Dervilly-Pinel, Gaud; Giraudeau, Patrick

    2017-02-01

    Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

    PubMed

    Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

    2016-02-01

    Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  19. Calcium isotope analysis by mass spectrometry.

    PubMed

    Boulyga, Sergei F

    2010-01-01

    The variations in the isotopic composition of calcium caused by fractionation in heterogeneous systems and by nuclear reactions can provide insight into numerous biological, geological, and cosmic processes, and therefore isotopic analysis finds a wide spectrum of applications in cosmo- and geochemistry, paleoclimatic, nutritional, and biomedical studies. The measurement of calcium isotopic abundances in natural samples has challenged the analysts for more than three decades. Practically all Ca isotopes suffer from significant isobaric interferences, whereas low-abundant isotopes can be particularly affected by neighboring major isotopes. The extent of natural variations of stable isotopes appears to be relatively limited, and highly precise techniques are required to resolve isotopic effects. Isotope fractionation during sample preparation and measurements and instrumental mass bias can significantly exceed small isotope abundance variations in samples, which have to be investigated. Not surprisingly, a TIMS procedure developed by Russell et al. (Russell et al., 1978. Geochim Cosmochim Acta 42: 1075-1090) for Ca isotope measurements was considered as revolutionary for isotopic measurements in general, and that approach is used nowadays (with small modifications) for practically all isotopic systems and with different mass spectrometric techniques. Nevertheless, despite several decades of calcium research and corresponding development of mass spectrometers, the available precision and accuracy is still not always sufficient to achieve the challenging goals. The present article discusses figures of merits of presently used analytical methods and instrumentation, and attempts to critically assess their limitations. In Sections 2 and 3, mass spectrometric methods applied to precise stable isotope analysis and to the determination of (41)Ca are described. Section 4 contains a short summary of selected applications, and includes tracer experiments and the potential use

  20. Metabolome analysis of Drosophila melanogaster during embryogenesis.

    PubMed

    An, Phan Nguyen Thuy; Yamaguchi, Masamitsu; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-01-01

    The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos' metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo.

  1. Metabolome Analysis of Drosophila melanogaster during Embryogenesis

    PubMed Central

    An, Phan Nguyen Thuy; Yamaguchi, Masamitsu; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-01-01

    The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos’ metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo. PMID:25121768

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

    NASA Astrophysics Data System (ADS)

    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.

  3. Informatics for Metabolomics.

    PubMed

    Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

    2016-01-01

    Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

  4. Chemical Isotope Labeling LC-MS for High Coverage and Quantitative Profiling of the Hydroxyl Submetabolome in Metabolomics.

    PubMed

    Zhao, Shuang; Luo, Xian; Li, Liang

    2016-11-01

    A key step in metabolomics is to perform accurate relative quantification of the metabolomes in comparative samples with high coverage. Hydroxyl-containing metabolites are an important class of the metabolome with diverse structures and physical/chemical properties; however, many of them are difficult to detect with high sensitivity. We present a high-performance chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) technique for in-depth profiling of the hydroxyl submetabolome, which involves the use of acidic liquid-liquid extraction to enrich hydroxyl metabolites into ethyl acetate from an aqueous sample. After drying and then redissolving in acetonitrile, the metabolite extract is labeled using a base-activated 12 C- or 13 C-dansylation reaction. A fast step-gradient LC-UV method is used to determine the total concentration of labeled metabolites. On the basis of the concentration information, a 12 C-labeled individual sample is mixed with an equal mole amount of a 13 C-labeled pool or control for relative metabolite quantification. The 12 C-/ 13 C-labeled mixtures are individually analyzed by LC-MS, and the resultant peak pairs of labeled metabolites in MS are measured for relative quantification and metabolite identification. A standard library of 85 hydroxyl compounds containing MS, retention time, and MS/MS information was constructed for positive metabolite identification based on matches of two or all three of these parameters with those of an unknown. Using human urine as an example, we analyzed samples of 1:1 12 C-/ 13 C-labeled urine in triplicate with triplicate runs per sample and detected an average of 3759 ± 45 peak pairs or metabolites per run and 3538 ± 71 pairs per sample with 3093 pairs in common (n = 9). Out of the 3093 peak pairs, 2304 pairs (75%) could be positively or putatively identified based on metabolome database searches, including 20 pairs positively identified using the dansylated hydroxyl standards library

  5. Synthesis of l-cysteine derivatives containing stable sulfur isotopes and application of this synthesis to reactive sulfur metabolome.

    PubMed

    Ono, Katsuhiko; Jung, Minkyung; Zhang, Tianli; Tsutsuki, Hiroyasu; Sezaki, Hiroshi; Ihara, Hideshi; Wei, Fan-Yan; Tomizawa, Kazuhito; Akaike, Takaaki; Sawa, Tomohiro

    2017-05-01

    Cysteine persulfide is an L-cysteine derivative having one additional sulfur atom bound to a cysteinyl thiol group, and it serves as a reactive sulfur species that regulates redox homeostasis in cells. Here, we describe a rapid and efficient method of synthesis of L-cysteine derivatives containing isotopic sulfur atoms and application of this method to a reactive sulfur metabolome. We used bacterial cysteine syntheses to incorporate isotopic sulfur atoms into the sulfhydryl moiety of L-cysteine. We cloned three cysteine synthases-CysE, CysK, and CysM-from the Gram-negative bacterium Salmonella enterica serovar Typhimurium LT2, and we generated their recombinant enzymes. We synthesized 34 S-labeled L-cysteine from O-acetyl-L-serine and 34 S-labeled sodium sulfide as substrates for the CysK or CysM reactions. Isotopic labeling of L-cysteine at both sulfur ( 34 S) and nitrogen ( 15 N) atoms was also achieved by performing enzyme reactions with 15 N-labeled L-serine, acetyl-CoA, and 34 S-labeled sodium sulfide in the presence of CysE and CysK. The present enzyme systems can be applied to syntheses of a series of L-cysteine derivatives including L-cystine, L-cystine persulfide, S-sulfo-L-cysteine, L-cysteine sulfonate, and L-selenocystine. We also prepared 34 S-labeled N-acetyl-L-cysteine (NAC) by incubating 34 S-labeled L-cysteine with acetyl coenzyme A in test tubes. Tandem mass spectrometric identification of low-molecular-weight thiols after monobromobimane derivatization revealed the endogenous occurrence of NAC in the cultured mammalian cells such as HeLa cells and J774.1 cells. Furthermore, we successfully demonstrated, by using 34 S-labeled NAC, metabolic conversion of NAC to glutathione and its persulfide, via intermediate formation of L-cysteine, in the cells. The approach using isotopic sulfur labeling combined with mass spectrometry may thus contribute to greater understanding of reactive sulfur metabolome and redox biology. Copyright © 2017 Elsevier Inc

  6. Calcium Isotope Analysis by Mass Spectrometry

    NASA Astrophysics Data System (ADS)

    Boulyga, S.; Richter, S.

    2010-12-01

    The variations in the isotopic composition of calcium caused by fractionation in heterogeneous systems and by nuclear reactions can provide insight into numerous biological, geological, and cosmic processes, and therefore isotopic analysis finds a wide spectrum of applications in cosmo- and geochemistry, paleoclimatic, nutritional, and biomedical studies. The measurement of calcium isotopic abundances in natural samples has challenged the analysts for more than three decades. Practically all Ca isotopes suffer from significant isobaric interferences, whereas low-abundant isotopes can be particularly affected by neighboring major isotopes. The extent of natural variations of stable isotopes appears to be relatively limited, and highly precise techniques are required to resolve isotopic effects. Isotope fractionation during sample preparation and measurements and instrumental mass bias can significantly exceed small isotope abundance variations in samples, which have to be investigated. Not surprisingly, a TIMS procedure developed by Russell et al. (Russell et al., 1978. Geochim Cosmochim Acta 42: 1075-1090) for Ca isotope measurements was considered as revolutionary for isotopic measurements in general, and that approach is used nowadays (with small modifications) for practically all isotopic systems and with different mass spectrometric techniques. Nevertheless, despite several decades of calcium research and corresponding development of mass spectrometers, the available precision and accuracy is still not always sufficient to achieve the challenging goals. This presentation discusses figures of merits of presently used analytical methods and instrumentation, and attempts to critically assess their limitations. Additionally, the availability of Ca isotope reference materials will be discussed.

  7. Spatially Resolved, In Situ Carbon Isotope Analysis of Archean Organic Matter

    NASA Technical Reports Server (NTRS)

    Williford, Kenneth H.; Ushikubo, Takayuki; Lepot, Kevin; Hallmann, Christian; Spicuzza, Michael J.; Eigenbrode, Jennifer L.; Summons, Roger E.; Valley, John W.

    2011-01-01

    Spatiotemporal variability in the carbon isotope composition of sedimentary organic matter (OM) preserves information about the evolution of the biosphere and of the exogenic carbon cycle as a whole. Primary compositions, and imprints of the post-depositional processes that obscure them, exist at the scale of individual sedimentary grains (mm to micron). Secondary ion mass spectrometry (SIMS) (1) enables analysis at these scales and in petrographic context, (2) permits morphological and compositional characterization of the analyte and associated minerals prior to isotopic analysis, and (3) reveals patterns of variability homogenized by bulk techniques. Here we present new methods for in situ organic carbon isotope analysis with sub-permil precision and spatial resolution to 1 micron using SIMS, as well as new data acquired from a suite of Archean rocks. Three analytical protocols were developed for the CAMECA ims1280 at WiscSIMS to analyze domains of varying size and carbon concentration. Average reproducibility (at 2SD) using a 6 micron spot size with two Faraday cup detectors was 0.4 %, and 0.8 % for analyses using 1 micron and 3 micron spot sizes with a Faraday cup (for C-12) and an electron multiplier (for C-13). Eight coals, two ambers, a shungite, and a graphite were evaluated for micron-scale isotopic heterogeneity, and LCNN anthracite (delta C-13 = -23.56 +/- 0.1 %, 2SD) was chosen as the working standard. Correlation between instrumental bias and H/C was observed and calibrated for each analytical session using organic materials with H/C between 0.1 and 1.5 (atomic), allowing a correction based upon a C-13H/C-13 measurement included in every analysis. Matrix effects of variable C/SiO2 were evaluated by measuring mm to sub-micron graphite domains in quartzite from Bogala mine, Sri Lanka. Apparent instrumental bias and C-12 count rate are correlated in this case, but this may be related to a crystal orientation effect in graphite. Analyses of amorphous

  8. Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

    DOE PAGES

    Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe; ...

    2017-04-07

    In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

  9. Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe

    In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

  10. Metabolomic Analysis in Brain Research: Opportunities and Challenges

    PubMed Central

    Vasilopoulou, Catherine G.; Margarity, Marigoula; Klapa, Maria I.

    2016-01-01

    Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results. PMID:27252656

  11. Environmental metabolomics: a SWOT analysis (strengths, weaknesses, opportunities, and threats).

    PubMed

    Miller, Marion G

    2007-02-01

    Metabolomic approaches have the potential to make an exceptional contribution to understanding how chemicals and other environmental stressors can affect both human and environmental health. However, the application of metabolomics to environmental exposures, although getting underway, has not yet been extensively explored. This review will use a SWOT analysis model to discuss some of the strengths, weaknesses, opportunities, and threats that are apparent to an investigator venturing into this relatively new field. SWOT has been used extensively in business settings to uncover new outlooks and identify problems that would impede progress. The field of environmental metabolomics provides great opportunities for discovery, and this is recognized by a high level of interest in potential applications. However, understanding the biological consequence of environmental exposures can be confounded by inter- and intra-individual differences. Metabolomic profiles can yield a plethora of data, the interpretation of which is complex and still being evaluated and researched. The development of the field will depend on the availability of technologies for data handling and that permit ready access metabolomic databases. Understanding the relevance of metabolomic endpoints to organism health vs adaptation vs variation is an important step in understanding what constitutes a substantive environmental threat. Metabolomic applications in reproductive research are discussed. Overall, the development of a comprehensive mechanistic-based interpretation of metabolomic changes offers the possibility of providing information that will significantly contribute to the protection of human health and the environment.

  12. Metabolomics-Based Elucidation of Active Metabolic Pathways in Erythrocytes and HSC-Derived Reticulocytes.

    PubMed

    Srivastava, Anubhav; Evans, Krystal J; Sexton, Anna E; Schofield, Louis; Creek, Darren J

    2017-04-07

    A detailed analysis of the metabolic state of human-stem-cell-derived erythrocytes allowed us to characterize the existence of active metabolic pathways in younger reticulocytes and compare them to mature erythrocytes. Using high-resolution LC-MS-based untargeted metabolomics, we found that reticulocytes had a comparatively much richer repertoire of metabolites, which spanned a range of metabolite classes. An untargeted metabolomics analysis using stable-isotope-labeled glucose showed that only glycolysis and the pentose phosphate pathway actively contributed to the biosynthesis of metabolites in erythrocytes, and these pathways were upregulated in reticulocytes. Most metabolite species found to be enriched in reticulocytes were residual pools of metabolites produced by earlier erythropoietic processes, and their systematic depletion in mature erythrocytes aligns with the simplification process, which is also seen at the cellular and the structural level. Our work shows that high-resolution LC-MS-based untargeted metabolomics provides a global coverage of the biochemical species that are present in erythrocytes. However, the incorporation of stable isotope labeling provides a more accurate description of the active metabolic processes that occur in each developmental stage. To our knowledge, this is the first detailed characterization of the active metabolic pathways of the erythroid lineage, and it provides a rich database for understanding the physiology of the maturation of reticulocytes into mature erythrocytes.

  13. Capillary electrophoresis - Mass spectrometry metabolomics analysis revealed enrichment of hypotaurine in rat glioma tissues.

    PubMed

    Gao, Peng; Ji, Min; Fang, Xueyan; Liu, Yingyang; Yu, Zhigang; Cao, Yunfeng; Sun, Aijun; Zhao, Liang; Zhang, Yong

    2017-11-15

    Glioma is one of the most lethal brain malignancies with unknown etiologies. Many metabolomics analysis aiming at diverse kinds of samples had been performed. Due to the varied adopted analytical platforms, the reported disease-related metabolites were not consistent across different studies. Comparable metabolomics results are more likely to be acquired by analyzing the same sample types with identical analytical platform. For tumor researches, tissue samples metabolomics analysis own the unique advantage that it can gain more direct insight into disease-specific pathological molecules. In this light, a previous reported capillary electrophoresis - mass spectrometry human tissues metabolomics analysis method was employed to profile the metabolome of rat C6 cell implantation gliomas and the corresponding precancerous tissues. It was found that 9 metabolites increased in the glioma tissues. Of them, hypotaurine was the only metabolite that enriched in the malignant tissues as what had been reported in the relevant human tissues metabolomics analysis. Furthermore, hypotaurine was also proved to inhibit α-ketoglutarate-dependent dioxygenases (2-KDDs) through immunocytochemistry staining and in vitro enzymatic activity assays by using C6 cell cultures. This study reinforced the previous conclusion that hypotaurine acted as a competitive inhibitor of 2-KDDs and proved the value of metabolomics in oncology studies. Copyright © 2017. Published by Elsevier Inc.

  14. Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

    PubMed Central

    Beatty, Perrin H.; Klein, Matthias S.; Fischer, Jeffrey J.; Lewis, Ian A.; Muench, Douglas G.; Good, Allen G.

    2016-01-01

    A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields. PMID:27735856

  15. Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)

    PubMed Central

    Amberg, Alexander; Barrett, Dave; Beale, Michael H.; Beger, Richard; Daykin, Clare A.; Fan, Teresa W.-M.; Fiehn, Oliver; Goodacre, Royston; Griffin, Julian L.; Hankemeier, Thomas; Hardy, Nigel; Harnly, James; Higashi, Richard; Kopka, Joachim; Lane, Andrew N.; Lindon, John C.; Marriott, Philip; Nicholls, Andrew W.; Reily, Michael D.; Thaden, John J.; Viant, Mark R.

    2013-01-01

    There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum. PMID:24039616

  16. Stable Isotope-Assisted Evaluation of Different Extraction Solvents for Untargeted Metabolomics of Plants

    PubMed Central

    Doppler, Maria; Kluger, Bernhard; Bueschl, Christoph; Schneider, Christina; Krska, Rudolf; Delcambre, Sylvie; Hiller, Karsten; Lemmens, Marc; Schuhmacher, Rainer

    2016-01-01

    The evaluation of extraction protocols for untargeted metabolomics approaches is still difficult. We have applied a novel stable isotope-assisted workflow for untargeted LC-HRMS-based plant metabolomics , which allows for the first time every detected feature to be considered for method evaluation. The efficiency and complementarity of commonly used extraction solvents, namely 1 + 3 (v/v) mixtures of water and selected organic solvents (methanol, acetonitrile or methanol/acetonitrile 1 + 1 (v/v)), with and without the addition of 0.1% (v/v) formic acid were compared. Four different wheat organs were sampled, extracted and analysed by LC-HRMS. Data evaluation was performed with the in-house-developed MetExtract II software and R. With all tested solvents a total of 871 metabolites were extracted in ear, 785 in stem, 733 in leaf and 517 in root samples, respectively. Between 48% (stem) and 57% (ear) of the metabolites detected in a particular organ were found with all extraction mixtures, and 127 of 996 metabolites were consistently shared between all extraction agent/organ combinations. In aqueous methanol, acidification with formic acid led to pronounced pH dependency regarding the precision of metabolite abundance and the number of detectable metabolites, whereas extracts of acetonitrile-containing mixtures were less affected. Moreover, methanol and acetonitrile have been found to be complementary with respect to extraction efficiency. Interestingly, the beneficial properties of both solvents can be combined by the use of a water-methanol-acetonitrile mixture for global metabolite extraction instead of aqueous methanol or aqueous acetonitrile alone. PMID:27367667

  17. Applying quantitative metabolomics based on chemical isotope labeling LC-MS for detecting potential milk adulterant in human milk.

    PubMed

    Mung, Dorothea; Li, Liang

    2018-02-25

    There is an increasing demand for donor human milk to feed infants for various reasons including that a mother may be unable to provide sufficient amounts of milk for their child or the milk is considered unsafe for the baby. Selling and buying human milk via the Internet has gained popularity. However, there is a risk of human milk sold containing other adulterants such as animal or plant milk. Analytical tools for rapid detection of adulterants in human milk are needed. We report a quantitative metabolomics method for detecting potential milk adulterants (soy, almond, cow, goat and infant formula milk) in human milk. It is based on the use of a high-performance chemical isotope labeling (CIL) LC-MS platform to profile the metabolome of an unknown milk sample, followed by multivariate or univariate comparison of the resultant metabolomic profile with that of human milk to determine the differences. Using dansylation LC-MS to profile the amine/phenol submetabolome, we could detect an average of 4129 ± 297 (n = 9) soy metabolites, 3080 ± 470 (n = 9) almond metabolites, 4256 ± 136 (n = 18) cow metabolites, 4318 ± 198 (n = 9) goat metabolites, 4444 ± 563 (n = 9) infant formula metabolites, and 4020 ± 375 (n = 30) human metabolites. This high level of coverage allowed us to readily differentiate the six different types of samples. From the analysis of binary mixtures of human milk containing 5, 10, 25, 50 and 75% other type of milk, we demonstrated that this method could be used to detect the presence of as low as 5% adulterant in human milk. We envisage that this method could be applied to detect contaminant or adulterant in other types of food or drinks. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Can NMR solve some significant challenges in metabolomics?

    PubMed Central

    Gowda, G.A. Nagana; Raftery, Daniel

    2015-01-01

    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 biospecimens 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. PMID:26476597

  19. Can NMR solve some significant challenges in metabolomics?

    PubMed

    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. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Can NMR solve some significant challenges in metabolomics?

    NASA Astrophysics Data System (ADS)

    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.

  1. Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

    PubMed

    Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

    2017-03-01

    Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing

  2. Functional Analysis of Metabolomics Data.

    PubMed

    Chagoyen, Mónica; López-Ibáñez, Javier; Pazos, Florencio

    2016-01-01

    Metabolomics aims at characterizing the repertory of small chemical compounds in a biological sample. As it becomes more massive and larger sets of compounds are detected, a functional analysis is required to convert these raw lists of compounds into biological knowledge. The most common way of performing such analysis is "annotation enrichment analysis," also used in transcriptomics and proteomics. This approach extracts the annotations overrepresented in the set of chemical compounds arisen in a given experiment. Here, we describe the protocols for performing such analysis as well as for visualizing a set of compounds in different representations of the metabolic networks, in both cases using free accessible web tools.

  3. Rapid two-dimensional ALSOFAST-HSQC experiment for metabolomics and fluxomics studies: application to a 13C-enriched cancer cell model treated with gold nanoparticles.

    PubMed

    Schätzlein, Martina Palomino; Becker, Johanna; Schulze-Sünninghausen, David; Pineda-Lucena, Antonio; Herance, José Raul; Luy, Burkhard

    2018-04-01

    Isotope labeling enables the use of 13 C-based metabolomics techniques with strongly improved resolution for a better identification of relevant metabolites and tracing of metabolic fluxes in cell and animal models, as required in fluxomics studies. However, even at high NMR-active isotope abundance, the acquisition of one-dimensional 13 C and classical two-dimensional 1 H, 13 C-HSQC experiments remains time consuming. With the aim to provide a shorter, more efficient alternative, herein we explored the ALSOFAST-HSQC experiment with its rapid acquisition scheme for the analysis of 13 C-labeled metabolites in complex biological mixtures. As an initial step, the parameters of the pulse sequence were optimized to take into account the specific characteristics of the complex samples. We then applied the fast two-dimensional experiment to study the effect of different kinds of antioxidant gold nanoparticles on a HeLa cancer cell model grown on 13 C glucose-enriched medium. As a result, 1 H, 13 C-2D correlations could be obtained in a couple of seconds to few minutes, allowing a simple and reliable identification of various 13 C-enriched metabolites and the determination of specific variations between the different sample groups. Thus, it was possible to monitor glucose metabolism in the cell model and study the antioxidant effect of the coated gold nanoparticles in detail. Finally, with an experiment time of only half an hour, highly resolved 1 H, 13 C-HSQC spectra using the ALSOFAST-HSQC pulse sequence were acquired, revealing the isotope-position-patterns of the corresponding 13 C-nuclei from carbon multiplets. Graphical abstract Fast NMR applied to metabolomics and fluxomics studies with gold nanoparticles.

  4. MASS SPECTROMETRY-BASED METABOLOMICS

    PubMed Central

    Dettmer, Katja; Aronov, Pavel A.; Hammock, Bruce D.

    2007-01-01

    This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed. PMID:16921475

  5. An R package for the integrated analysis of metabolomics and spectral data.

    PubMed

    Costa, Christopher; Maraschin, Marcelo; Rocha, Miguel

    2016-06-01

    Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as nuclear magnetic resonance, gas or liquid chromatography, mass spectrometry, infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  6. Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics

    PubMed Central

    Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A.; Caron, Christophe

    2015-01-01

    Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. Availability and implementation: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). Contact: contact@workflow4metabolomics.org PMID:25527831

  7. Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

    PubMed

    Sridharan, Gautham Vivek; Bruinsma, Bote Gosse; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

    2017-11-13

    Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.

  8. Enhanced spatially-resolved trace analysis using combined SIMS-single-stage AMS

    NASA Astrophysics Data System (ADS)

    Grabowski, K. S.; Groopman, E. E.; Fahey, A. J.

    2017-11-01

    Secondary ion mass spectrometry (SIMS) provides spatially resolved trace analysis of solid materials, but can be complicated by unresolved abundant molecular isobars. By adding a 300-kV single-stage accelerator mass spectrometer (SSAMS) as a detector for a Cameca ims 4f SIMS, one can measure more abundant positive ions from the SIMS while removing molecular isobars, thus improving very low abundance trace element and isotope analysis. This paper describes important features and capabilities of such an integrated system at the Naval Research Laboratory using charge state +1 ions. Transmission loss is compared to molecule destruction as gas flow to the molecule-destruction cell increases. As most measurements tolerate more modest abundance sensitivities than for 14C analysis, a lower gas flow is acceptable, so good transmission of 20-50% for ions of interest can be maintained for a broad range of ion masses. This new instrument has measured isotope ratios for uranium, lead, rare earths, and other elements from particulates and localized regions, with molecule destruction enabling the measurement at low SIMS mass resolving power and thus high transmission, as examples will show. This new and world-unique instrument provides improved capabilities for applications in nuclear and other forensics, geochemistry, cosmochemistry, and the development of optical, electronic, multifunctional, and structural materials.

  9. Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

    PubMed

    Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

    2017-12-01

    Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Metabolomic Studies in Drosophila.

    PubMed

    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.

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

    PubMed

    Vaniya, Arpana; Fiehn, Oliver

    2015-06-01

    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.

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

    PubMed

    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 10 6 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.

  13. Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

    PubMed

    Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

    2015-05-01

    The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

  14. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    PubMed Central

    Nishiumi, Shin; Suzuki, Makoto; Kobayashi, Takashi; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-01-01

    The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis. PMID:25003943

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

    PubMed

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

    2015-02-01

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

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

    PubMed

    Ibarra-González, Isabel; Rodríguez-Valentín, Rocío; Lazcano-Ponce, Eduardo; Vela-Amieva, Marcela

    2017-01-01

    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. 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. Identification of new metabolomic profiles associated with IDD 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.

  17. Introducing Undergraduate Students to Metabolomics Using a NMR-Based Analysis of Coffee Beans

    ERIC Educational Resources Information Center

    Sandusky, Peter Olaf

    2017-01-01

    Metabolomics applies multivariate statistical analysis to sets of high-resolution spectra taken over a population of biologically derived samples. The objective is to distinguish subpopulations within the overall sample population, and possibly also to identify biomarkers. While metabolomics has become part of the standard analytical toolbox in…

  18. Metabolomics for laboratory diagnostics.

    PubMed

    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.

  19. Haystack, a web-based tool for metabolomics research.

    PubMed

    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

  20. Modelling short time series in metabolomics: a functional data analysis approach.

    PubMed

    Montana, Giovanni; Berk, Maurice; Ebbels, Tim

    2011-01-01

    Metabolomics is the study of the complement of small molecule metabolites in cells, biofluids and tissues. Many metabolomic experiments are designed to compare changes observed over time under two or more experimental conditions (e.g. a control and drug-treated group), thus producing time course data. Models from traditional time series analysis are often unsuitable because, by design, only very few time points are available and there are a high number of missing values. We propose a functional data analysis approach for modelling short time series arising in metabolomic studies which overcomes these obstacles. Our model assumes that each observed time series is a smooth random curve, and we propose a statistical approach for inferring this curve from repeated measurements taken on the experimental units. A test statistic for detecting differences between temporal profiles associated with two experimental conditions is then presented. The methodology has been applied to NMR spectroscopy data collected in a pre-clinical toxicology study.

  1. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    PubMed Central

    Hajduk, Joanna; Klupczynska, Agnieszka; Dereziński, Paweł; Matysiak, Jan; Kokot, Piotr; Nowak, Dorota M.; Gajęcka, Marzena; Nowak-Markwitz, Ewa; Kokot, Zenon J.

    2015-01-01

    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. PMID:26694367

  2. METABOLOMICS IN MEDICAL SCIENCES--TRENDS, CHALLENGES AND PERSPECTIVES.

    PubMed

    Klupczyńska, Agnieszka; Dereziński, Paweł; Kokot, Zenon J

    2015-01-01

    Metabolomics is the latest of the "omic" technologies that involves comprehensive analysis of small molecule metabolites of an organism or a specific biological sample. Metabolomics provides an insight into the cell status and describes an actual health condition of organisms. Analysis of metabolome offers a unique opportunity to study the influence of genetic variation, disease, applied treatment or diet on endogenous metabolic state of organisms. There are many areas that might benefit from metabolomic research. In the article some applications of this novel "omic" technology in the field of medical sciences are presented. One of the most popular aims of metabolomic studies is biomarker discovery. Despite using the state-of-art analytical techniques along with advanced bioinformatic tools, metabolomic experiments encounter numerous difficulties and pitfalls. Challenges that researchers in the field of analysis of metabolome have to face include i.a., technical limitations, bioinformatic challenges and integration with other "omic" sciences. One of the grand challenges for studies in the field of metabolomics is to tackle the problem of data analysis, which is probably the most time consuming stage of metabolomic workflow and requires close collaboration between analysts, clinicians and experts in chemometric analysis. Implementation of metabolomics into clinical practice will be dependent on establishment of standardized protocols in analytical performance and data analysis and development of fit-for-purpose biomarker method validation. Metabolomics allows to achieve a sophisticated level of information about biological systems and opens up new perspectives in many fields of medicine, especially in oncology. Apart from its extensive cognitive significance, metabolomics manifests also a practical importance as it may lead to design of new non-invasive, sensitive and specific diagnostic techniques and development of new therapies.

  3. Simulation of multi-photon emission isotopes using time-resolved SimSET multiple photon history generator

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chiang, Chih-Chieh; Lin, Hsin-Hon; Lin, Chang-Shiun

    Abstract-Multiple-photon emitters, such as In-111 or Se-75, have enormous potential in the field of nuclear medicine imaging. For example, Se-75 can be used to investigate the bile acid malabsorption and measure the bile acid pool loss. The simulation system for emission tomography (SimSET) is a well-known Monte Carlo simulation (MCS) code in nuclear medicine for its high computational efficiency. However, current SimSET cannot simulate these isotopes due to the lack of modeling of complex decay scheme and the time-dependent decay process. To extend the versatility of SimSET for simulation of those multi-photon emission isotopes, a time-resolved multiple photon history generatormore » based on SimSET codes is developed in present study. For developing the time-resolved SimSET (trSimSET) with radionuclide decay process, the new MCS model introduce new features, including decay time information and photon time-of-flight information, into this new code. The half-life of energy states were tabulated from the Evaluated Nuclear Structure Data File (ENSDF) database. The MCS results indicate that the overall percent difference is less than 8.5% for all simulation trials as compared to GATE. To sum up, we demonstrated that time-resolved SimSET multiple photon history generator can have comparable accuracy with GATE and keeping better computational efficiency. The new MCS code is very useful to study the multi-photon imaging of novel isotopes that needs the simulation of lifetime and the time-of-fight measurements. (authors)« less

  4. Seasonally Resolved Oxygen Isotope Paleoclimate Proxy in Tree-Ring Cellulose from the Southeastern U.S.

    NASA Astrophysics Data System (ADS)

    Miller, D. L.; Mora, C. I.; Grissino-Mayer, H. D.; Mock, C. J.

    2004-12-01

    Stable isotopes in precipitation reflect changes in climate, moisture source, and extreme events such as tropical cyclones, and an oxygen isotope proxy record of these changes through time and space is preserved in tree-ring cellulose. Extreme climate events such as droughts and hurricanes are formidable natural disasters in the southeastern United States, and considerable efforts have been made to understand factors controlling their frequency, whether natural or anthropogenic. Tree rings offer an unusually well-resolved, dateable record of climate events extending beyond modern or historical (documentary) records. Oxygen isotopes in alpha-cellulose of shallowly-rooted conifers predominately reflect the composition of precipitation. Tropical storm convection results in marked 18O depletion in storm precipitation, to -15‰ relative to source seawater (~0‰ ). The depletion increases towards the eyewall of the cyclone, however, isotopically depleted precipitation may extend outward many 100's of km. Storm water 18O depletion translates to soil water 18O depletion that may persist for many weeks until ameliorated by soil water evaporation. Tree growth during that time will take up the anomalous isotopic compositions. Distinctive earlywood (EW ~March-June) versus latewood (LW ~July-October) growth allows the rings to be resolved at an intra-annual (seasonal) scale. By comparison to average soil water, droughts result in 18O-enriched soil water compositions. Seasonal drought or years of continued drought will be similarly captured in the isotope compositions of tree-ring cellulose. A 227-year (1770-1997) seasonally-resolved record of tropical cyclone and drought activity was obtained from cross-sections of felled slash pines (Pinus elliottii Engelm.) and remnant longleaf pines (Pinus palustris Mill.) from southern Georgia. Interpretations of drought or hurricane events were tested by comparison with recent, detailed meteorological records. The 227-year record reveals

  5. Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration.

    PubMed

    Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

    2017-05-01

    Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCoreTM, MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Metabolomics in Toxicology and Preclinical Research

    PubMed Central

    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

  7. Liver metabolomics analysis associated with feed efficiency on steers

    USDA-ARS?s Scientific Manuscript database

    The liver represents a metabolic crossroad regulating and modulating nutrients available from digestive tract absorption to the peripheral tissues. To identify potential differences in liver function that lead to differences in feed efficiency, liver metabolomic analysis was conducted using ultra-pe...

  8. Vibrationally-Resolved Kinetic Isotope Effects in the Proton-Transfer Dynamics of Ground-State Tropolone

    NASA Astrophysics Data System (ADS)

    Chew, Kathryn; Vealey, Zachary; Vaccaro, Patrick

    2015-06-01

    The vibrational and isotopic dependence of the hindered (tunneling-mediated) proton-transfer reaction taking place in the ground electronic state ( X1{A}1) of monodeuterated tropolone (TrOD) has been explored under ambient (bulk-gas) conditions by applying two-color variants of resonant four-wave mixing (RFWM) spectroscopy in conjunction with polarization-resolved detection schemes designed to alleviate spectral complexity and facilitate rovibrational assignments. Full rotation-tunneling analyses of high-resolution spectral profiles acquired for the fundamental and first-overtone bands of a reaction-promoting O-D\\cdotsO deformation/ring-breathing mode, νb{36}(a1), were performed, thereby extracting refined structural and dynamical information that affords benchmarks for the quantitative interpretation of tunneling-induced signatures found in long-range scans of X1{A}1 vibrational levels residing below Etilde{X}vib = 1700 wn}. Observed kinetic isotope effects, which reflect changes in both reaction kinematics and vibrational displacements, will be discussed, with high-level quantum-chemical calculations serving to elucidate state-resolved propensities for proton transfer in TrOH and TrOD.

  9. Metabolomic analysis using porcine skin: a pilot study of analytical techniques.

    PubMed

    Wu, Julie; Fiehn, Oliver; Armstrong, April W

    2014-06-15

    Metabolic byproducts serve as indicators of the chemical processes and can provide valuable information on pathogenesis by measuring the amplified output. Standardized techniques for metabolome extraction of skin samples serve as a critical foundation to this field but have not been developed. We sought to determine the optimal cell lysage techniques for skin sample preparation and to compare GC-TOF-MS and UHPLC-QTOF-MS for metabolomic analysis. Using porcine skin samples, we pulverized the skin via various combinations of mechanical techniques for cell lysage. After extraction, the samples were subjected to GC-TOF-MS and/or UHPLC-QTOF-MS. Signal intensities from GC-TOF-MS analysis showed that ultrasonication (2.7x107) was most effective for cell lysage when compared to mortar-and-pestle (2.6x107), ball mill followed by ultrasonication (1.6x107), mortar-and-pestle followed by ultrasonication (1.4x107), and homogenization (trial 1: 8.4x106; trial 2: 1.6x107). Due to the similar signal intensities, ultrasonication and mortar-and-pestle were applied to additional samples and subjected to GC-TOF-MS and UHPLC-QTOF-MS. Ultrasonication yielded greater signal intensities than mortar-and-pestle for 92% of detected metabolites following GC-TOF-MS and for 68% of detected metabolites following UHPLC-QTOF-MS. Overall, ultrasonication is the preferred method for efficient cell lysage of skin tissue for both metabolomic platforms. With standardized sample preparation, metabolomic analysis of skin can serve as a powerful tool in elucidating underlying biological processes in dermatological conditions.

  10. The food metabolome: a window over dietary exposure.

    PubMed

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine; Andres-Lacueva, Cristina; Dragsted, Lars O; Draper, John; Rappaport, Stephen M; van der Hooft, Justin J J; Wishart, David S

    2014-06-01

    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 compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown 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 face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health. © 2014 American Society for Nutrition.

  11. Metagenomic and metabolomic analysis of the toxic effects of trichloroacetamide-induced gut microbiome and urine metabolome perturbations in mice.

    PubMed

    Zhang, Yan; Zhao, Fuzheng; Deng, Yongfeng; Zhao, Yanping; Ren, Hongqiang

    2015-04-03

    Disinfection byproducts (DBPs) in drinking water have been linked to various diseases, including colon, colorectal, rectal, and bladder cancer. Trichloroacetamide (TCAcAm) is an emerging nitrogenous DBP, and our previous study found that TCAcAm could induce some changes associated with host-gut microbiota co-metabolism. In this study, we used an integrated approach combining metagenomics, based on high-throughput sequencing, and metabolomics, based on nuclear magnetic resonance (NMR), to evaluate the toxic effects of TCAcAm exposure on the gut microbiome and urine metabolome. High-throughput sequencing revealed that the gut microbiome's composition and function were significantly altered after TCAcAm exposure for 90 days in Mus musculus mice. In addition, metabolomic analysis showed that a number of gut microbiota-related metabolites were dramatically perturbed in the urine of the mice. These results may provide novel insight into evaluating the health risk of environmental pollutants as well as revealing the potential mechanism of TCAcAm's toxic effects.

  12. Role of metabolomics in TBI research

    PubMed Central

    Wolahan, Stephanie M.; Hirt, Daniel; Braas, Daniel; Glenn, Thomas C.

    2016-01-01

    Synopsis Metabolomics is an important member of the omics community in that it defines which small molecules may be responsible for disease states. This article reviews the essential principles of metabolomics from specimen preparation, chemical analysis, and advanced statistical methods. Metabolomics in TBI has so far been underutilized. Future metabolomics based studies focused on the diagnoses, prognoses, and treatment effects, need to be conducted across all types of TBI. PMID:27637396

  13. Reprint Of: Enhanced spatially-resolved trace analysis using combined SIMS-single-stage AMS

    NASA Astrophysics Data System (ADS)

    Grabowski, K. S.; Groopman, E. E.; Fahey, A. J.

    2018-01-01

    Secondary ion mass spectrometry (SIMS) provides spatially resolved trace analysis of solid materials, but can be complicated by unresolved abundant molecular isobars. By adding a 300-kV single-stage accelerator mass spectrometer (SSAMS) as a detector for a Cameca ims 4f SIMS, one can measure more abundant positive ions from the SIMS while removing molecular isobars, thus improving very low abundance trace element and isotope analysis. This paper describes important features and capabilities of such an integrated system at the Naval Research Laboratory using charge state +1 ions. Transmission loss is compared to molecule destruction as gas flow to the molecule-destruction cell increases. As most measurements tolerate more modest abundance sensitivities than for 14C analysis, a lower gas flow is acceptable, so good transmission of 20-50% for ions of interest can be maintained for a broad range of ion masses. This new instrument has measured isotope ratios for uranium, lead, rare earths, and other elements from particulates and localized regions, with molecule destruction enabling the measurement at low SIMS mass resolving power and thus high transmission, as examples will show. This new and world-unique instrument provides improved capabilities for applications in nuclear and other forensics, geochemistry, cosmochemistry, and the development of optical, electronic, multifunctional, and structural materials.

  14. Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype

    DOE PAGES

    Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; ...

    2011-01-01

    Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiplemore » pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.« less

  15. Best-Matched Internal Standard Normalization in Liquid Chromatography-Mass Spectrometry Metabolomics Applied to Environmental Samples.

    PubMed

    Boysen, Angela K; Heal, Katherine R; Carlson, Laura T; Ingalls, Anitra E

    2018-01-16

    The goal of metabolomics is to measure the entire range of small organic molecules in biological samples. In liquid chromatography-mass spectrometry-based metabolomics, formidable analytical challenges remain in removing the nonbiological factors that affect chromatographic peak areas. These factors include sample matrix-induced ion suppression, chromatographic quality, and analytical drift. The combination of these factors is referred to as obscuring variation. Some metabolomics samples can exhibit intense obscuring variation due to matrix-induced ion suppression, rendering large amounts of data unreliable and difficult to interpret. Existing normalization techniques have limited applicability to these sample types. Here we present a data normalization method to minimize the effects of obscuring variation. We normalize peak areas using a batch-specific normalization process, which matches measured metabolites with isotope-labeled internal standards that behave similarly during the analysis. This method, called best-matched internal standard (B-MIS) normalization, can be applied to targeted or untargeted metabolomics data sets and yields relative concentrations. We evaluate and demonstrate the utility of B-MIS normalization using marine environmental samples and laboratory grown cultures of phytoplankton. In untargeted analyses, B-MIS normalization allowed for inclusion of mass features in downstream analyses that would have been considered unreliable without normalization due to obscuring variation. B-MIS normalization for targeted or untargeted metabolomics is freely available at https://github.com/IngallsLabUW/B-MIS-normalization .

  16. RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

    PubMed Central

    Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

    2018-01-01

    The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be

  17. RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

    PubMed

    Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

    2018-02-22

    The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be

  18. Haystack, a web-based tool for metabolomics research

    PubMed Central

    2014-01-01

    Background 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. Results 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. Conclusion 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

  19. Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation

    PubMed Central

    Parsons, Helen M; Ludwig, Christian; Günther, Ulrich L; Viant, Mark R

    2007-01-01

    Background Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend upon the variance of the data, it is important to first minimise any contribution from unwanted technical variance arising from sample preparation and analytical measurements, and thereby maximise any contribution from wanted biological variance between different classes. The generalised logarithm (glog) transform was developed to stabilise the variance in DNA microarray datasets, but has rarely been applied to metabolomics data. In particular, it has not been rigorously evaluated against other scaling techniques used in metabolomics, nor tested on all forms of NMR spectra including 1-dimensional (1D) 1H, projections of 2D 1H, 1H J-resolved (pJRES), and intact 2D J-resolved (JRES). Results Here, the effects of the glog transform are compared against two commonly used variance stabilising techniques, autoscaling and Pareto scaling, as well as unscaled data. The four methods are evaluated in terms of the effects on the variance of NMR metabolomics data and on the classification accuracy following multivariate analysis, the latter achieved using principal component analysis followed by linear discriminant analysis. For two of three datasets analysed, classification accuracies were highest following glog transformation: 100% accuracy for discriminating 1D NMR spectra of hypoxic and normoxic invertebrate muscle, and 100% accuracy for discriminating 2D JRES spectra of fish livers sampled from two rivers. For the third dataset, pJRES spectra of urine from two breeds of dog, the glog transform and autoscaling achieved equal highest accuracies. Additionally we extended the glog algorithm to effectively suppress noise, which proved critical for the analysis of 2D JRES spectra. Conclusion We have demonstrated that the glog and extended glog transforms stabilise the technical variance in NMR metabolomics

  20. Neuronal metabolomics by ion mobility mass spectrometry: cocaine effects on glucose and selected biogenic amine metabolites in the frontal cortex, striatum, and thalamus of the rat.

    PubMed

    Kaplan, Kimberly A; Chiu, Veronica M; Lukus, Peter A; Zhang, Xing; Siems, William F; Schenk, James O; Hill, Herbert H

    2013-02-01

    We report results of studies of global and targeted neuronal metabolomes by ambient pressure ion mobility mass spectrometry. The rat frontal cortex, striatum, and thalamus were sampled from control nontreated rats and those treated with acute cocaine or pargyline. Quantitative evaluations were made by standard additions or isotopic dilution. The mass detection limit was ~100 pmol varying with the analyte. Targeted metabolites of dopamine, serotonin, and glucose followed the rank order of distribution expected between the anatomical areas. Data was evaluated by principal component analysis on 764 common metabolites (identified by m/z and reduced mobility). Differences between anatomical areas and treatment groups were observed for 53 % of these metabolites using principal component analysis. Global and targeted metabolic differences were observed between the three anatomical areas with contralateral differences between some areas. Following drug treatments, global and targeted metabolomes were found to shift relative to controls and still maintained anatomical differences. Pargyline reduced 3,4-dihydroxyphenylacetic acid below detection limits, and 5-HIAA varied between anatomical regions. Notable findings were: (1) global metabolomes were different between anatomical areas and were altered by acute cocaine providing a broad but targeted window of discovery for metabolic changes produced by drugs of abuse; (2) quantitative analysis was demonstrated using isotope dilution and standard addition; (3) cocaine changed glucose and biogenic amine metabolism in the anatomical areas tested; and (4) the largest effect of cocaine was on the glycolysis metabolome in the thalamus confirming inferences from previous positron emission tomography studies using 2-deoxyglucose.

  1. Further analysis of the IRIS iron isotope experiment

    NASA Technical Reports Server (NTRS)

    Tarle, G.; Ahlen, S. P.; Cartwright, B. G.; Solarz, M.

    1980-01-01

    The IRIS Fe isotope experiment was extended to atomic charges of Z = 19, with isotopic distributions for 500 events ranging from 18 to 28. Normalization of the detector response functions at Fe-56 produced a single well resolved peak at Sc-45, establishing the resolution and mass scale of the device over the entire charge region. The abundance distributions for the predominantly primary isotopes Ca-40, Fe-54, Fe-56, Ni-58, and Ni-60 do not indicate a large admixture of material with distinctly nonsolar abundances.

  2. The future of metabolomics in ELIXIR

    PubMed Central

    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. PMID:29043062

  3. The future of metabolomics in ELIXIR.

    PubMed

    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.

  4. Validation of metabolomics analysis of human perilymph fluid using liquid chromatography-mass spectroscopy.

    PubMed

    Mavel, Sylvie; Lefèvre, Antoine; Bakhos, David; Dufour-Rainfray, Diane; Blasco, Hélène; Emond, Patrick

    2018-05-22

    Although there is some data from animal studies, the metabolome of inner ear fluid in humans remains unknown. Characterization of the metabolome of the perilymph would allow for better understanding of its role in auditory function and for identification of biomarkers that might allow prediction of response to therapeutics. There is a major technical challenge due to the small sample of perilymph fluid available for analysis (sub-microliter). The objectives of this study were to develop and validate a methodology for analysis of perilymph metabolome using liquid chromatography-high resolution mass spectrometry (LC-HRMS). Due to the low availability of perilymph fluid; a methodological study was first performed using low volumes (0.8 μL) of cerebrospinal fluid (CSF) and optimized the LC-HRMS parameters using targeted and non-targeted metabolomics approaches. We obtained excellent parameters of reproducibility for about 100 metabolites. This methodology was then used to analyze perilymph fluid using two complementary chromatographic supports: reverse phase (RP-C18) and hydrophilic interaction liquid chromatography (HILIC). Both methods were highly robust and showed their complementarity, thus reinforcing the interest to combine these chromatographic supports. A fingerprinting was obtained from 98 robust metabolites (analytical variability <30%), where amino acids (e.g., asparagine, valine, glutamine, alanine, etc.), carboxylic acids and derivatives (e.g., lactate, carnitine, trigonelline, creatinine, etc.) were observed as first-order signals. This work lays the foundations of a robust analytical workflow for the exploration of the perilymph metabolome dedicated to the research of biomarkers for the diagnosis/prognosis of auditory pathologies. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

    USDA-ARS?s Scientific Manuscript database

    The rumen has a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in feed efficiency, rumen fluid metabolomic analysis by LC-MS and multivariate/univariate statistical analysis were used to identify differences in r...

  6. Real-time isotope monitoring network at the Biosphere 2 Landscape Evolution Observatory resolves meter-to-catchment scale flow dynamics

    NASA Astrophysics Data System (ADS)

    Volkmann, T. H. M.; Van Haren, J. L. M.; Kim, M.; Harman, C. J.; Pangle, L.; Meredith, L. K.; Troch, P. A.

    2017-12-01

    Stable isotope analysis is a powerful tool for tracking flow pathways, residence times, and the partitioning of water resources through catchments. However, the capacity of stable isotopes to characterize catchment hydrological dynamics has not been fully exploited as commonly used methodologies constrain the frequency and extent at which isotopic data is available across hydrologically-relevant compartments (e.g. soil, plants, atmosphere, streams). Here, building upon significant recent developments in laser spectroscopy and sampling techniques, we present a fully automated monitoring network for tracing water isotopes through the three model catchments of the Landscape Evolution Observatory (LEO) at the Biosphere 2, University of Arizona. The network implements state-of-the-art techniques for monitoring in great spatiotemporal detail the stable isotope composition of water in the subsurface soil, the discharge outflow, and the atmosphere above the bare soil surface of each of the 330-m2 catchments. The extensive valving and probing systems facilitate repeated isotope measurements from a total of more than five-hundred locations across the LEO domain, complementing an already dense array of hydrometric and other sensors installed on, within, and above each catchment. The isotope monitoring network is operational and was leveraged during several months of experimentation with deuterium-labelled rain pulse applications. Data obtained during the experiments demonstrate the capacity of the monitoring network to resolve sub-meter to whole-catchment scale flow and transport dynamics in continuous time. Over the years to come, the isotope monitoring network is expected to serve as an essential tool for collaborative interdisciplinary Earth science at LEO, allowing us to disentangle changes in hydrological behavior as the model catchments evolve in time through weathering and colonization by plant communities.

  7. Meteoritic Sulfur Isotopic Analysis

    NASA Technical Reports Server (NTRS)

    Thiemens, Mark H.

    1996-01-01

    Funds were requested to continue our program in meteoritic sulfur isotopic analysis. We have recently detected a potential nucleosynthetic sulfur isotopic anomaly. We will search for potential carriers. The documentation of bulk systematics and the possible relation to nebular chemistry and oxygen isotopes will be explored. Analytical techniques for delta(sup 33), delta(sup 34)S, delta(sup 36)S isotopic analysis were improved. Analysis of sub milligram samples is now possible. A possible relation between sulfur isotopes and oxygen was detected, with similar group systematics noted, particularly in the case of aubrites, ureilites and entstatite chondrites. A possible nucleosynthetic excess S-33 has been noted in bulk ureilites and an oldhamite separate from Norton County. High energy proton (approximately 1 GeV) bombardments of iron foils were done to experimentally determine S-33, S-36 spallogenic yields for quantitation of isotopic measurements in iron meteorites. Techniques for measurement of mineral separates were perfected and an analysis program initiated. The systematic behavior of bulk sulfur isotopes will continue to be explored.

  8. Applied metabolomics in drug discovery.

    PubMed

    Cuperlovic-Culf, M; Culf, A S

    2016-08-01

    The metabolic profile is a direct signature of phenotype and biochemical activity following any perturbation. Metabolites are small molecules present in a biological system including natural products as well as drugs and their metabolism by-products depending on the biological system studied. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs. This review focuses primarily on the application of metabolomics in the discovery of active drugs from natural products and the analysis of chemical libraries and the computational analysis of metabolic networks. Metabolomics methodology, both experimental and analytical is fast developing. At the same time, databases of compounds are ever growing with the inclusion of more molecular and spectral information. An increasing number of systems are being represented by very detailed metabolic network models. Combining these experimental and computational tools with high throughput drug testing and drug discovery techniques can provide new promising compounds and leads.

  9. Stable Isotope Analysis of Chlorate

    NASA Astrophysics Data System (ADS)

    Brundrett, M.; Jackson, W. A.; Sturchio, N. C.; Bohlke, J. K.; Hatzinger, P.

    2016-12-01

    Studies have confirmed the presence of chlorate (ClO3-) throughout terrestrial and extraterrestrial systems generally in excess of perchlorate (ClO4-) [1, 2]. ClO3- occurrence, production, and post depositional transformation has significant implications to our understanding of atmospheric Cl cycling and potential biogeochemical reactions on Earth and Mars. The isotopic composition of oxyanions can be used to evaluate their production mechanisms and post-depositional alteration [3, 4]. However, no information is available on the natural isotopic composition of ClO3-. The objective of this study was to develop a method to measure the stable isotope composition (δ18O, δ17O and δ37Cl) of ClO3- and to determine the isotopic composition of ClO3- in natural desert salt accumulations that have been studied previously for NO3- and ClO4- isotopic composition. The process of ClO3- purification and analysis of δ18O, δ 17O and δ37Cl is problematic but has recently been resolved by adapting previously published methods for ClO4-. Competitive anions (e.g. NO3-, Cl-, ClO4-, and SO4-2) are removed through a series of processes including biological reduction, solid phase extraction, and anion or cation exchange. Initial results for control samples treated with the above method have a maximum variation of ± 2 ‰. These methods are being applied to representative samples to determine if various sources of natural and synthetic ClO3- have distinctive isotopic compositions, as reported previously for ClO4- [3, 4]. Establishing the range of isotopic composition of natural ClO3- also could provide information about atmospheric ClO3- production mechanisms and post-depositional processing, with implications for the atmospheric chemistry of oxychlorine compounds and the global biogeochemical cycling of Cl. [1] Jackson et al. (2015) EPSL 430, 470-476. [2] Rao et al. (2010) ES&T 44, 8429-8434. [3] Jackson et al. (2010) ES&T 44, 4869-4876. [4] Bao and Gu (2004) ES&T 38, 5073-5077.

  10. Applications of Metabolomics in Cancer Studies.

    PubMed

    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.

  11. Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

    PubMed

    Puchades-Carrasco, Leonor; Palomino-Schätzlein, Martina; Pérez-Rambla, Clara; Pineda-Lucena, Antonio

    2016-05-01

    Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  12. A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

    PubMed Central

    Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J.; Yanes, Oscar

    2012-01-01

    Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples. PMID:24957762

  13. A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data.

    PubMed

    Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J; Yanes, Oscar

    2012-10-18

    Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples.

  14. Cerebrospinal Fluid Metabolomics After Natural Product Treatment in an Experimental Model of Cerebral Ischemia.

    PubMed

    Huan, Tao; Xian, Jia Wen; Leung, Wing Nang; Li, Liang; Chan, Chun Wai

    2016-11-01

    Cerebrospinal fluid (CSF) is an important biofluid for diagnosis of and research on neurological diseases. However, in-depth metabolomic profiling of CSF remains an analytical challenge due to the small volume of samples, particularly in small animal models. In this work, we report the application of a high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) workflow for CSF metabolomics in Gastrodia elata and Uncaria rhynchophylla water extract (GUW)-treated experimental cerebral ischemia model of rat. The GUW is a commonly used Traditional Chinese Medicine (TCM) for hypertension and brain disease. This study investigated the amine- and phenol-containing biomarkers in the CSF metabolome. After GUW treatment for 7 days, the neurological deficit score was significantly improved with infarct volume reduction, while the integrity of brain histological structure was preserved. Over 1957 metabolites were quantified in CSF by dansylation LC-MS. The analysis of this comprehensive list of metabolites suggests that metabolites associated with oxidative stress, inflammatory response, and excitotoxicity change during GUW-induced alleviation of ischemic injury. This work is significant in that (1) it shows CIL LC-MS can be used for in-depth profiling of the CSF metabolome in experimental ischemic stroke and (2) identifies several potential molecular targets (that might mediate the central nervous system) and associate with pharmacodynamic effects of some frequently used TCMs.

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

    PubMed

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2018-05-01

    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.

  16. Using stable isotopes to resolve eco-hydrological dynamics of soil-plant-atmosphere feedbacks

    NASA Astrophysics Data System (ADS)

    Dubbert, M.; Piayda, A.; Kübert, A.; Cuntz, M.; Werner, C.

    2016-12-01

    , M. et al. (2014a): Oxygen isotope signatures of transpired water vapor: the role of isotopic non-steady-state transpiration under natural conditions. New Phytologist. Werner, C. and Dubbert, M. (2016): Resolving rapid dynamics of soil-plant-atmosphere interactions. New Phytologist.

  17. Flux analysis and metabolomics for systematic metabolic engineering of microorganisms.

    PubMed

    Toya, Yoshihiro; Shimizu, Hiroshi

    2013-11-01

    Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and (13)C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Stable isotope analysis of Dacryoconarid carbonate microfossils: a new tool for Devonian oxygen and carbon isotope stratigraphy.

    PubMed

    Frappier, Amy Benoit; Lindemann, Richard H; Frappier, Brian R

    2015-04-30

    Dacryoconarids are extinct marine zooplankton known from abundant, globally distributed calcite microfossils in the Devonian, but their shell stable isotope composition has not been previously explored. Devonian stable isotope stratigraphy is currently limited to less common invertebrates or bulk rock analyses of uncertain provenance. As with Cenozoic planktonic foraminifera, isotopic analysis of dacryoconarid shells could facilitate higher-resolution, geographically widespread stable isotope records of paleoenvironmental change, including marine hypoxia events, climate changes, and biocrises. We explored the use of Dacryoconarid isotope stratigraphy as a viable method in interpreting paleoenvironments. We applied an established method for determining stable isotope ratios (δ(13) C, δ(18) O values) of small carbonate microfossils to very well-preserved dacryoconarid shells. We analyzed individual calcite shells representing five common genera using a Kiel carbonate device coupled to a MAT 253 isotope ratio mass spectrometer. Calcite shell δ(13) C and δ(18) O values were compared by taxonomic group, rock unit, and locality. Single dacryoconarid calcite shells are suitable for stable isotope analysis using a Kiel-IRMS setup. The dacryoconarid shell δ(13) C values (-4.7 to 2.3‰) and δ(18) O values (-10.3 to -4.8‰) were consistent across taxa, independent of shell size or part, but varied systematically through time. Lower fossil δ(18) O values were associated with warmer water temperature and more variable δ(13) C values were associated with major bioevents. Dacryoconarid δ(13) C and δ(18) O values differed from bulk rock carbonate values. Dacryoconarid individual microfossil δ(13) C and δ(18) O values are highly sensitive to paleoenvironmental changes, thus providing a promising avenue for stable isotope chemostratigraphy to better resolve regional to global paleoceanographic changes throughout the upper Silurian to the upper Devonian. Our results

  19. Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

    NASA Astrophysics Data System (ADS)

    Chen, Deying; Su, Xiaoling; Wang, Nan; Li, Yunong; Yin, Hua; Li, Liang; Li, Lanjuan

    2017-01-01

    We report a chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the amine/phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with sham operation, OA control group, and OA rats with treatment, separately, using glucosamine/Celecoxib and three traditional Chinese medicines (Epimedii folium, Chuanxiong Rhizoma and Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including 2-aminoadipic acid, saccharopine and GABA were selected as potential biomarkers of OA progression and OA treatment. This study illustrates that CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying disease progression and treatment in animal models.

  20. Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

    PubMed Central

    Chen, Deying; Su, Xiaoling; Wang, Nan; Li, Yunong; Yin, Hua; Li, Liang; Li, Lanjuan

    2017-01-01

    We report a chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the amine/phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with sham operation, OA control group, and OA rats with treatment, separately, using glucosamine/Celecoxib and three traditional Chinese medicines (Epimedii folium, Chuanxiong Rhizoma and Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including 2-aminoadipic acid, saccharopine and GABA were selected as potential biomarkers of OA progression and OA treatment. This study illustrates that CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying disease progression and treatment in animal models. PMID:28091618

  1. Sample normalization methods in quantitative metabolomics.

    PubMed

    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.

  2. Jasmonate-mediated stomatal closure under elevated CO2 revealed by time-resolved metabolomics

    USDA-ARS?s Scientific Manuscript database

    Foliar stomatal movements are critical for regulating plant water status and gas exchange. Elevated carbon dioxide (CO2) concentrations are known to induce stomatal closure. However, current knowledge on CO2 signal transduction in stomatal guard cells is limited. Here we report the metabolomic respo...

  3. Metabolome analysis of esophageal cancer tissues using capillary electrophoresis-time-of-flight mass spectrometry.

    PubMed

    Tokunaga, Masanori; Kami, Kenjiro; Ozawa, Soji; Oguma, Junya; Kazuno, Akihito; Miyachi, Hayato; Ohashi, Yoshiaki; Kusuhara, Masatoshi; Terashima, Masanori

    2018-06-01

    Reports of the metabolomic characteristics of esophageal cancer are limited. In the present study, we thus conducted metabolome analysis of paired tumor tissues (Ts) and non-tumor esophageal tissues (NTs) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). The Ts and surrounding NTs were surgically excised pair-wise from 35 patients with esophageal cancer. Following tissue homogenization and metabolite extraction, a total of 110 compounds were absolutely quantified by CE-TOFMS. We compared the concentrations of the metabolites between Ts and NTs, between pT1 or pT2 (pT1-2) and pT3 or pT4 (pT3-4) stage, and between node-negative (pN-) and node-positive (pN+) samples. Principal component analysis and hierarchical clustering analysis revealed clear metabolomic differences between Ts and NTs. Lactate and citrate levels in Ts were significantly higher (P=0.001) and lower (P<0.001), respectively, than those in NTs, which corroborated with the Warburg effect in Ts. The concentrations of most amino acids apart from glutamine were higher in Ts than in NTs, presumably due to hyperactive glutaminolysis in Ts. The concentrations of malic acid (P=0.015) and citric acid (P=0.008) were significantly lower in pT3-4 than in pT1-2, suggesting the downregulation of tricarboxylic acid (TCA) cycle activity in pT3-4. On the whole, in this study, we demonstrate significantly different metabolomic characteristics between tumor and non-tumor tissues and identified a novel set of metabolites that were strongly associated with the degree of tumor progression. A further understanding of cancer metabolomics may enable the selection of more appropriate treatment strategies, thereby contributing to individualized medicine.

  4. Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

    PubMed

    Thonusin, Chanisa; IglayReger, Heidi B; Soni, Tanu; Rothberg, Amy E; Burant, Charles F; Evans, Charles R

    2017-11-10

    In recent years, mass spectrometry-based metabolomics has increasingly been applied to large-scale epidemiological studies of human subjects. However, the successful use of metabolomics in this context is subject to the challenge of detecting biologically significant effects despite substantial intensity drift that often occurs when data are acquired over a long period or in multiple batches. Numerous computational strategies and software tools have been developed to aid in correcting for intensity drift in metabolomics data, but most of these techniques are implemented using command-line driven software and custom scripts which are not accessible to all end users of metabolomics data. Further, it has not yet become routine practice to assess the quantitative accuracy of drift correction against techniques which enable true absolute quantitation such as isotope dilution mass spectrometry. We developed an Excel-based tool, MetaboDrift, to visually evaluate and correct for intensity drift in a multi-batch liquid chromatography - mass spectrometry (LC-MS) metabolomics dataset. The tool enables drift correction based on either quality control (QC) samples analyzed throughout the batches or using QC-sample independent methods. We applied MetaboDrift to an original set of clinical metabolomics data from a mixed-meal tolerance test (MMTT). The performance of the method was evaluated for multiple classes of metabolites by comparison with normalization using isotope-labeled internal standards. QC sample-based intensity drift correction significantly improved correlation with IS-normalized data, and resulted in detection of additional metabolites with significant physiological response to the MMTT. The relative merits of different QC-sample curve fitting strategies are discussed in the context of batch size and drift pattern complexity. Our drift correction tool offers a practical, simplified approach to drift correction and batch combination in large metabolomics studies

  5. Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata.

    PubMed

    Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

    2018-01-01

    The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata , identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata , with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata , as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

  6. Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

    PubMed Central

    Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

    2018-01-01

    The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature. PMID:29719546

  7. A Metabolomic Perspective on Coeliac Disease

    PubMed Central

    Calabrò, Antonio

    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 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. PMID:24665364

  8. Working Up a Good Sweat – The Challenges of Standardising Sweat Collection for Metabolomics Analysis

    PubMed Central

    Hussain, Joy N; Mantri, Nitin; Cohen, Marc M

    2017-01-01

    Introduction Human sweat is a complex biofluid of interest to diverse scientific fields. Metabolomics analysis of sweat promises to improve screening, diagnosis and self-monitoring of numerous conditions through new applications and greater personalisation of medical interventions. Before these applications can be fully developed, existing methods for the collection, handling, processing and storage of human sweat need to be revised. This review presents a cross-disciplinary overview of the origins, composition, physical characteristics and functional roles of human sweat, and explores the factors involved in standardising sweat collection for metabolomics analysis. Methods A literature review of human sweat analysis over the past 10 years (2006–2016) was performed to identify studies with metabolomics or similarly applicable ‘omics’ analysis. These studies were reviewed with attention to sweat induction and sampling techniques, timing of sweat collection, sweat storage conditions, laboratory derivation, processing and analytical platforms. Results Comparative analysis of 20 studies revealed numerous factors that can significantly impact the validity, reliability and reproducibility of sweat analysis including: anatomical site of sweat sampling, skin integrity and preparation; temperature and humidity at the sweat collection sites; timing and nature of sweat collection; metabolic quenching; transport and storage; qualitative and quantitative measurements of the skin microbiota at sweat collection sites; and individual variables such as diet, emotional state, metabolic conditions, pharmaceutical, recreational drug and supplement use. Conclusion Further development of standard operating protocols for human sweat collection can open the way for sweat metabolomics to significantly add to our understanding of human physiology in health and disease. PMID:28798503

  9. Tools for the functional interpretation of metabolomic experiments.

    PubMed

    Chagoyen, Monica; Pazos, Florencio

    2013-11-01

    The so-called 'omics' approaches used in modern biology aim at massively characterizing the molecular repertories of living systems at different levels. Metabolomics is one of the last additions to the 'omics' family and it deals with the characterization of the set of metabolites in a given biological system. As metabolomic techniques become more massive and allow characterizing larger sets of metabolites, automatic methods for analyzing these sets in order to obtain meaningful biological information are required. Only recently the first tools specifically designed for this task in metabolomics appeared. They are based on approaches previously used in transcriptomics and other 'omics', such as annotation enrichment analysis. These, together with generic tools for metabolic analysis and visualization not specifically designed for metabolomics will for sure be in the toolbox of the researches doing metabolomic experiments in the near future.

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

    PubMed Central

    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. PMID:28531195

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

    PubMed

    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.

  12. Establishing Substantial Equivalence: Metabolomics

    NASA Astrophysics Data System (ADS)

    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.

  13. Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

    USDA-ARS?s Scientific Manuscript database

    The rumen plays a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in feed efficiency, rumen metabolomic analysis by ultra-performance liquid chromatography/ time-of-flight mass spectrometry (MS) and multivariate/u...

  14. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    NASA Astrophysics Data System (ADS)

    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.

  15. COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access.

    PubMed

    Salek, Reza M; Neumann, Steffen; Schober, Daniel; Hummel, Jan; Billiau, Kenny; Kopka, Joachim; Correa, Elon; Reijmers, Theo; Rosato, Antonio; Tenori, Leonardo; Turano, Paola; Marin, Silvia; Deborde, Catherine; Jacob, Daniel; Rolin, Dominique; Dartigues, Benjamin; Conesa, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; O'Hagan, Steve; Hao, Jie; van Vliet, Michael; Sysi-Aho, Marko; Ludwig, Christian; Bouwman, Jildau; Cascante, Marta; Ebbels, Timothy; Griffin, Julian L; Moing, Annick; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Viant, Mark R; Goodacre, Royston; Günther, Ulrich L; Hankemeier, Thomas; Luchinat, Claudio; Walther, Dirk; Steinbeck, Christoph

    Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative 'coordination of standards in metabolomics' (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities' participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

  16. Compliance with minimum information guidelines in public metabolomics repositories

    PubMed Central

    Spicer, Rachel A.; Salek, Reza; Steinbeck, Christoph

    2017-01-01

    The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards. PMID:28949328

  17. Compliance with minimum information guidelines in public metabolomics repositories.

    PubMed

    Spicer, Rachel A; Salek, Reza; Steinbeck, Christoph

    2017-09-26

    The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

  18. Urine metabolomics.

    PubMed

    Zhang, Aihua; Sun, Hui; Wu, Xiuhong; Wang, Xijun

    2012-12-24

    Metabolomics is a powerful technique for the discovery of novel biomarkers and elucidation of biochemical pathways to improve diagnosis, prognosis and therapy. An advantage of this approach is its ability to assess global metabolic profiles to enhance pathologic characterization. Urine is an ideal bio-medium for disease study because it is readily available, easily obtained and less complex than other body fluids. Ease of collection allows for serial sampling to monitor disease and therapeutic response. Because of this potential, this paper will review urine metabolomic analysis, discuss its significance in the post-genomic era and highlight the specific roles of endogenous small molecule metabolites in this emerging field. Copyright © 2012 Elsevier B.V. All rights reserved.

  19. Mathematical Modeling Approaches in Plant Metabolomics.

    PubMed

    Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas

    2018-01-01

    The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.

  20. Metabolomic Analysis in Severe Childhood Pneumonia in The Gambia, West Africa: Findings from a Pilot Study

    PubMed Central

    Laiakis, Evagelia C.; Morris, Gerard A. J.; Fornace, Albert J.; Howie, Stephen R. C.

    2010-01-01

    Background Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. Methodology/Principal Findings Eleven children with World Health Organization (WHO)-defined severe pneumonia of non-homogeneous aetiology were selected in The Gambia, West Africa, along with community controls. Metabolomic analysis of matched plasma and urine samples was undertaken using Ultra Performance Liquid Chromatography (UPLC) coupled to Time-of-Flight Mass Spectrometry (TOFMS). Biomarker extraction was done using SIMCA-P+ and Random Forests (RF). ‘Unsupervised’ (blinded) data were analyzed by Principal Component Analysis (PCA), while ‘supervised’ (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5′-diphosphate (ADP) were lower

  1. Metabolomic analysis in severe childhood pneumonia in the Gambia, West Africa: findings from a pilot study.

    PubMed

    Laiakis, Evagelia C; Morris, Gerard A J; Fornace, Albert J; Howie, Stephen R C

    2010-09-09

    Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. Eleven children with World Health Organization (WHO)-defined severe pneumonia of non-homogeneous aetiology were selected in The Gambia, West Africa, along with community controls. Metabolomic analysis of matched plasma and urine samples was undertaken using Ultra Performance Liquid Chromatography (UPLC) coupled to Time-of-Flight Mass Spectrometry (TOFMS). Biomarker extraction was done using SIMCA-P+ and Random Forests (RF). 'Unsupervised' (blinded) data were analyzed by Principal Component Analysis (PCA), while 'supervised' (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5'-diphosphate (ADP) were lower; uric acid and L-histidine were lower in urine from

  2. NMR and MS Methods for Metabolomics.

    PubMed

    Amberg, Alexander; Riefke, Björn; Schlotterbeck, Götz; Ross, Alfred; Senn, Hans; Dieterle, Frank; Keck, Matthias

    2017-01-01

    Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.

  3. Metabolomic analysis of insulin resistance across different mouse strains and diets.

    PubMed

    Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E

    2017-11-24

    Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  4. Spatially-resolved isotopic study of carbon trapped in ∼3.43 Ga Strelley Pool Formation stromatolites

    NASA Astrophysics Data System (ADS)

    Flannery, David T.; Allwood, Abigail C.; Summons, Roger E.; Williford, Kenneth H.; Abbey, William; Matys, Emily D.; Ferralis, Nicola

    2018-02-01

    The large isotopic fractionation of carbon associated with enzymatic carbon assimilation allows evidence for life's antiquity, and potentially the early operation of several extant metabolic pathways, to be derived from the stable carbon isotope record of sedimentary rocks. Earth's organic carbon isotope record extends to the Late Eoarchean-Early Paleoarchean: the age of the oldest known sedimentary rocks. However, complementary inorganic carbon reservoirs are poorly represented in the oldest units, and commonly reported bulk organic carbon isotope measurements do not capture the micro-scale isotopic heterogeneities that are increasingly reported from younger rocks. Here, we investigated the isotopic composition of the oldest paired occurrences of sedimentary carbonate and organic matter, which are preserved as dolomite and kerogen within textural biosignatures of the ∼3.43 Ga Strelley Pool Formation. We targeted least-altered carbonate phases in situ using microsampling techniques guided by non-destructive elemental mapping. Organic carbon isotope values were measured by spatially-resolved bulk analyses, and in situ using secondary ion mass spectrometry to target microscale domains of organic material trapped within inorganic carbon matrixes. Total observed fractionation of 13C ranges from -29 to -45‰. Our data are consistent with studies of younger Archean rocks that host biogenic stromatolites and organic-inorganic carbon pairs showing greater fractionation than expected for Rubisco fixation alone. We conclude that organic matter was fixed and/or remobilized by at least one metabolism in addition to the CBB cycle, possibly by the Wood-Ljungdahl pathway or methanogenesis-methanotrophy, in a shallow-water marine environment during the Paleoarchean.

  5. Metabolomics in Newborns.

    PubMed

    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.

  6. Spatially Resolved Analysis of Amines Using a Fluorescence Molecular Probe: Molecular Analysis of IDPs

    NASA Technical Reports Server (NTRS)

    Clemett, S. J.; Messenger, S.; Thomas-Keprta, K. L.; Wentworth, S. J.; Robinson, G. A.; McKay, D. S.

    2002-01-01

    Some Interplanetary Dust Particles (IDPs) have large isotope anomalies in H and N. To address the nature of the carrier phase, we are developing a procedure to spatially resolve the distribution of organic species on IDP thin sections utilizing fluorescent molecular probes. Additional information is contained in the original extended abstract.

  7. MetaboAnalystR: an R package for flexible and reproducible analysis of metabolomics data.

    PubMed

    Chong, Jasmine; Xia, Jianguo

    2018-06-28

    The MetaboAnalyst web application has been widely used for metabolomics data analysis and interpretation. Despite its user-friendliness, the web interface has presented its inherent limitations (especially for advanced users) with regard to flexibility in creating customized workflow, support for reproducible analysis, and capacity in dealing with large data. To address these limitations, we have developed a companion R package (MetaboAnalystR) based on the R code base of the web server. The package has been thoroughly tested to ensure that the same R commands will produce identical results from both interfaces. MetaboAnalystR complements the MetaboAnalyst web server to facilitate transparent, flexible and reproducible analysis of metabolomics data. MetaboAnalystR is freely available from https://github.com/xia-lab/MetaboAnalystR. Supplementary data are available at Bioinformatics online.

  8. Normalization of oxygen and hydrogen isotope data

    USGS Publications Warehouse

    Coplen, T.B.

    1988-01-01

    To resolve confusion due to expression of isotopic data from different laboratories on non-corresponding scales, oxygen isotope analyses of all substances can be expressed relative to VSMOW or VPDB (Vienna Peedee belemnite) on scales normalized such that the ??18O of SLAP is -55.5% relative to VSMOW. H3+ contribution in hydrogen isotope ratio analysis can be easily determined using two gaseous reference samples that differ greatly in deuterium content. ?? 1988.

  9. A pilot study of the effect of human breast milk on urinary metabolome analysis in infants.

    PubMed

    Shoji, Hiromichi; Taka, Hikari; Kaga, Naoko; Ikeda, Naho; Kitamura, Tomohiro; Miura, Yoshiki; Shimizu, Toshiaki

    2017-08-28

    This study aimed to examine the nutritional effect of breast feeding on healthy term infants by using urinary metabolome analysis. Urine samples were collected from 19 and 14 infants at 1 and 6 months, respectively. Infants were separated into two groups: the breast-fed group receiving <540 mL/week of their intake from formula (n=13 at 1 month; n=9 at 6 months); and the formula-fed group receiving no breast milk (BM) (n=6 at 1 month; n=5 at 6 months). Urinary metabolome analysis was performed using capillary electrophoresis-time-of-flight mass spectrometry (CE-TOF/MS). A total of 29 metabolites were detected by CE-TOF/MS metabolome analysis in all samples. Urinary excretion of choline metabolites (choline base solution, N,N-dimethylglycine, sarcosine, and betaine) at 1 month were significantly (p<0.05) higher in breast-fed infants than in formula-fed infants. However, choline metabolites were not significantly different between the groups at 6 months. Urinary excretion of lactic acid in breast-fed infants at 1 and 6 months was significantly lower than that in formula-fed infants. Urinary l(-)-threonine and l-carnosine excretion at 1 month was significantly lower in breast-fed infants than in formula-fed infants, but it was not significantly different between the groups at 6 months. The type of feeding in early infancy affects choline metabolism, as well as lactate, threonine, and carnosine levels, in healthy term infants. Urinary metabolome analysis by the CE-TOF/MS method is useful for assessing nutritional metabolism in infants.

  10. Light Stable Isotopic Compositions of Enriched Mantle Sources: Resolving the Dehydration Paradox

    NASA Astrophysics Data System (ADS)

    Dixon, J. E.; Bindeman, I. N.; Kingsley, R. H.

    2017-12-01

    An outstanding puzzle in mantle geochemistry has been the origin and evolution of Earth's volatile components. The "dehydration paradox" refers to the following conundrum. Mantle compositions for some enriched mid-ocean ridge (MORB) and ocean island (OIB) basalts basalts require involvement of a mostly dehydrated slab component to explain the trace element ratios and radiogenic isotopic compositions, but a fully hydrated slab component to explain the stable isotopic compositions. Volatile and stable isotopic data on enriched MORB show a diversity of enriched components. Pacific PREMA-type basalts (H2O/Ce = 215 ± 30, δDSMOW = -45 ± 5 ‰) are similar to those in the north Atlantic (H2O/Ce = 220 ± 30; δDSMOW = -30 to -40 ‰). Basalts with EM-type signatures have regionally variable volatile compositions. North Atlantic EM-type basalts are wetter (H2O/Ce = 330 ± 30) and have isotopically heavier hydrogen (δDSMOW = -57 ± 5 ‰) than north Atlantic MORB. South Atlantic EM-type basalts are damp (H2O/Ce = 120 ± 10) with intermediate δDSMOW (-68 ± 2 ‰), similar to dDSMOW for Pacific MORB. North EPR EM-type basalts are dry (H2O/Ce = 110 ± 20) and isotopically light (δDSMOW = -94 ± 3 ‰). Boron and lithium isotopic ratios parallel the trends observed for dDSMOW. A multi-stage metasomatic and melting model accounts for the origin of the enriched components by extending the subduction factory concept down through the mantle transition zone, with slab temperature a key variable. The dehydration paradox is resolved by decoupling of volatiles from lithophile elements, reflecting primary dehydration of the slab followed by secondary rehydration and re-equilibration by fluids derived from subcrustal hydrous phases (e.g., antigorite) in cooler, deeper parts of the slab. The "expanded subduction factory" model includes melting at several key depths, including 1) 180 to 280 km, where EM-type mantle compositions are generated above slabs with average to hot thermal

  11. An overview of methods using (13)C for improved compound identification in metabolomics and natural products.

    PubMed

    Clendinen, Chaevien S; Stupp, Gregory S; Ajredini, Ramadan; Lee-McMullen, Brittany; Beecher, Chris; Edison, Arthur S

    2015-01-01

    Compound identification is a major bottleneck in metabolomics studies. In nuclear magnetic resonance (NMR) investigations, resonance overlap often hinders unambiguous database matching or de novo compound identification. In liquid chromatography-mass spectrometry (LC-MS), discriminating between biological signals and background artifacts and reliable determination of molecular formulae are not always straightforward. We have designed and implemented several NMR and LC-MS approaches that utilize (13)C, either enriched or at natural abundance, in metabolomics applications. For LC-MS applications, we describe a technique called isotopic ratio outlier analysis (IROA), which utilizes samples that are isotopically labeled with 5% (test) and 95% (control) (13)C. This labeling strategy leads to characteristic isotopic patterns that allow the differentiation of biological signals from artifacts and yield the exact number of carbons, significantly reducing possible molecular formulae. The relative abundance between the test and control samples for every IROA feature can be determined simply by integrating the peaks that arise from the 5 and 95% channels. For NMR applications, we describe two (13)C-based approaches. For samples at natural abundance, we have developed a workflow to obtain (13)C-(13)C and (13)C-(1)H statistical correlations using 1D (13)C and (1)H NMR spectra. For samples that can be isotopically labeled, we describe another NMR approach to obtain direct (13)C-(13)C spectroscopic correlations. These methods both provide extensive information about the carbon framework of compounds in the mixture for either database matching or de novo compound identification. We also discuss strategies in which (13)C NMR can be used to identify unknown compounds from IROA experiments. By combining technologies with the same samples, we can identify important biomarkers and corresponding metabolites of interest.

  12. Combined Metabolomic Analysis of Plasma and Urine Reveals AHBA, Tryptophan and Serotonin Metabolism as Potential Risk Factors in Gestational Diabetes Mellitus (GDM)

    PubMed Central

    Leitner, Miriam; Fragner, Lena; Danner, Sarah; Holeschofsky, Nastassja; Leitner, Karoline; Tischler, Sonja; Doerfler, Hannes; Bachmann, Gert; Sun, Xiaoliang; Jaeger, Walter; Kautzky-Willer, Alexandra; Weckwerth, Wolfram

    2017-01-01

    Gestational diabetes mellitus during pregnancy has severe implications for the health of the mother and the fetus. Therefore, early prediction and an understanding of the physiology are an important part of prenatal care. Metabolite profiling is a long established method for the analysis and prediction of metabolic diseases. Here, we applied untargeted and targeted metabolomic protocols to analyze plasma and urine samples of pregnant women with and without GDM. Univariate and multivariate statistical analyses of metabolomic profiles revealed markers such as 2-hydroxybutanoic acid (AHBA), 3-hydroxybutanoic acid (BHBA), amino acids valine and alanine, the glucose-alanine-cycle, but also plant-derived compounds like sitosterin as different between control and GDM patients. PLS-DA and VIP analysis revealed tryptophan as a strong variable separating control and GDM. As tryptophan is biotransformed to serotonin we hypothesized whether serotonin metabolism might also be altered in GDM. To test this hypothesis we applied a method for the analysis of serotonin, metabolic intermediates and dopamine in urine by stable isotope dilution direct infusion electrospray ionization mass spectrometry (SID-MS). Indeed, serotonin and related metabolites differ significantly between control and GDM patients confirming the involvement of serotonin metabolism in GDM. Clustered correlation coefficient visualization of metabolite correlation networks revealed the different metabolic signatures between control and GDM patients. Eventually, the combination of selected blood plasma and urine sample metabolites improved the AUC prediction accuracy to 0.99. The detected GDM candidate biomarkers and the related systemic metabolic signatures are discussed in their pathophysiological context. Further studies with larger cohorts are necessary to underpin these observations. PMID:29312952

  13. Biodiversity in targeted metabolomics analysis of filamentous fungal pathogens by 1H NMR-based studies.

    PubMed

    Ząbek, Adam; Klimek-Ochab, Magdalena; Jawień, Ewa; Młynarz, Piotr

    2017-07-01

    The taxonomical classification among fungi kingdom in the last decades was evolved. In this work the targeted metabolomics study based on 1 H NMR spectroscopy combined with chemometrics tools was reported to be useful for differentiation of three model of fungal strains, which represent various genus of Ascomycota (Aspergillus pallidofulvus, Fusarium oxysporum, Geotrichum candidum) were selected in order to perform metabolomics studies. Each tested species, revealed specific metabolic profile of primary endo-metabolites. The species of A. pallidofulvus is represented by the highest concentration of glycerol, glucitol and Unk5. While, F. oxysporum species is characterised by increased level of propylene glycol, ethanol, 4-aminobutyrate, succinate, xylose, Unk1 and Unk4. In G. candidum, 3-methyl-2-oxovalerate, glutamate, pyruvate, glutamine and citrate were elevated. Additionally, a detailed analysis of metabolic changes among A. pallidofulvus, F. oxysporum and G. candidum showed that A. pallidofulvus seems to be the most pathogenic fungi. The obtained results demonstrated that targeted metabolomics analysis could be utilized in the future as a supporting taxonomical tool for currently methods.

  14. Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

    PubMed Central

    2014-01-01

    Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

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

    PubMed Central

    Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2014-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544

  16. Mass Spectrometry Strategies for Clinical Metabolomics and Lipidomics in Psychiatry, Neurology, and Neuro-Oncology

    PubMed Central

    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. PMID:23842599

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

    PubMed

    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.

  18. Urine Metabolomics Analysis for Biomarker Discovery and Detection of Jaundice Syndrome in Patients With Liver Disease*

    PubMed Central

    Wang, Xijun; Zhang, Aihua; Han, Ying; Wang, Ping; Sun, Hui; Song, Gaochen; Dong, Tianwei; Yuan, Ye; Yuan, Xiaoxia; Zhang, Miao; Xie, Ning; Zhang, He; Dong, Hui; Dong, Wei

    2012-01-01

    Metabolomics is a powerful new technology that allows for the assessment of global metabolic profiles in easily accessible biofluids and biomarker discovery in order to distinguish between diseased and nondiseased status information. Deciphering the molecular networks that distinguish diseases may lead to the identification of critical biomarkers for disease aggressiveness. However, current diagnostic methods cannot predict typical Jaundice syndrome (JS) in patients with liver disease and little is known about the global metabolomic alterations that characterize JS progression. Emerging metabolomics provides a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication, and therapy. Therefore, the aim of this study is to find the potential biomarkers from JS disease by using a nontarget metabolomics method, and test their usefulness in human JS diagnosis. Multivariate data analysis methods were utilized to identify the potential biomarkers. Interestingly, 44 marker metabolites contributing to the complete separation of JS from matched healthy controls were identified. Metabolic pathways (Impact-value≥0.10) including alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies were found to be disturbed in JS patients. This study demonstrates the possibilities of metabolomics as a diagnostic tool in diseases and provides new insight into pathophysiologic mechanisms. PMID:22505723

  19. A strategy for selecting data mining techniques in metabolomics.

    PubMed

    Banimustafa, Ahmed Hmaidan; Hardy, Nigel W

    2012-01-01

    There is a general agreement that the development of metabolomics depends not only on advances in chemical analysis techniques but also on advances in computing and data analysis methods. Metabolomics data usually requires intensive pre-processing, analysis, and mining procedures. Selecting and applying such procedures requires attention to issues including justification, traceability, and reproducibility. We describe a strategy for selecting data mining techniques which takes into consideration the goals of data mining techniques on the one hand, and the goals of metabolomics investigations and the nature of the data on the other. The strategy aims to ensure the validity and soundness of results and promote the achievement of the investigation goals.

  20. Differential metabolome analysis of field-grown maize kernels in response to drought stress

    USDA-ARS?s Scientific Manuscript database

    Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

  1. MetaMapR: pathway independent metabolomic network analysis incorporating unknowns.

    PubMed

    Grapov, Dmitry; Wanichthanarak, Kwanjeera; Fiehn, Oliver

    2015-08-15

    Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between >200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools. Freely available at http://dgrapov.github.io/MetaMapR/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http://dgrapov.github.io/MetaMapR/. ofiehn@ucdavis.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Basics of mass spectrometry based metabolomics.

    PubMed

    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.

  3. Metabolomics and Its Application to Acute Lung Diseases

    PubMed Central

    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

  4. Metabolomics: A Primer.

    PubMed

    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.

  5. Metabolomic Fingerprinting of Romaneschi Globe Artichokes by NMR Spectroscopy and Multivariate Data Analysis.

    PubMed

    de Falco, Bruna; Incerti, Guido; Pepe, Rosa; Amato, Mariana; Lanzotti, Virginia

    2016-09-01

    Globe artichoke (Cynara cardunculus L. var. scolymus L. Fiori) and cardoon (Cynara cardunculus L. var. altilis DC) are sources of nutraceuticals and bioactive compounds. To apply a NMR metabolomic fingerprinting approach to Cynara cardunculus heads to obtain simultaneous identification and quantitation of the major classes of organic compounds. The edible part of 14 Globe artichoke populations, belonging to the Romaneschi varietal group, were extracted to obtain apolar and polar organic extracts. The analysis was also extended to one species of cultivated cardoon for comparison. The (1) H-NMR of the extracts allowed simultaneous identification of the bioactive metabolites whose quantitation have been obtained by spectral integration followed by principal component analysis (PCA). Apolar organic extracts were mainly based on highly unsaturated long chain lipids. Polar organic extracts contained organic acids, amino acids, sugars (mainly inulin), caffeoyl derivatives (mainly cynarin), flavonoids, and terpenes. The level of nutraceuticals was found to be highest in the Italian landraces Bianco di Pertosa zia E and Natalina while cardoon showed the lowest content of all metabolites thus confirming the genetic distance between artichokes and cardoon. Metabolomic approach coupling NMR spectroscopy with multivariate data analysis allowed for a detailed metabolite profile of artichoke and cardoon varieties to be obtained. Relevant differences in the relative content of the metabolites were observed for the species analysed. This work is the first application of (1) H-NMR with multivariate statistics to provide a metabolomic fingerprinting of Cynara scolymus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Isotope analysis in the transmission electron microscope.

    PubMed

    Susi, Toma; Hofer, Christoph; Argentero, Giacomo; Leuthner, Gregor T; Pennycook, Timothy J; Mangler, Clemens; Meyer, Jannik C; Kotakoski, Jani

    2016-10-10

    The Ångström-sized probe of the scanning transmission electron microscope can visualize and collect spectra from single atoms. This can unambiguously resolve the chemical structure of materials, but not their isotopic composition. Here we differentiate between two isotopes of the same element by quantifying how likely the energetic imaging electrons are to eject atoms. First, we measure the displacement probability in graphene grown from either 12 C or 13 C and describe the process using a quantum mechanical model of lattice vibrations coupled with density functional theory simulations. We then test our spatial resolution in a mixed sample by ejecting individual atoms from nanoscale areas spanning an interface region that is far from atomically sharp, mapping the isotope concentration with a precision better than 20%. Although we use a scanning instrument, our method may be applicable to any atomic resolution transmission electron microscope and to other low-dimensional materials.

  7. An overview of renal metabolomics.

    PubMed

    Kalim, Sahir; Rhee, Eugene P

    2017-01-01

    The high-throughput, high-resolution phenotyping enabled by metabolomics has been applied increasingly to a variety of questions in nephrology research. This article provides an overview of current metabolomics methodologies and nomenclature, citing specific considerations in sample preparation, metabolite measurement, and data analysis that investigators should understand when examining the literature or designing a study. Furthermore, we review several notable findings that have emerged in the literature that both highlight some of the limitations of current profiling approaches, as well as outline specific strengths unique to metabolomics. More specifically, we review data on the following: (i) tryptophan metabolites and chronic kidney disease onset, illustrating the interpretation of metabolite data in the context of established biochemical pathways; (ii) trimethylamine-N-oxide and cardiovascular disease in chronic kidney disease, illustrating the integration of exogenous and endogenous inputs to the blood metabolome; and (iii) renal mitochondrial function in diabetic kidney disease and acute kidney injury, illustrating the potential for rapid translation of metabolite data for diagnostic or therapeutic aims. Finally, we review future directions, including the need to better characterize interperson and intraperson variation in the metabolome, pool existing data sets to identify the most robust signals, and capitalize on the discovery potential of emerging nontargeted methods. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

  8. Combined use of isotopic fingerprint and metabolomics analysis for the authentication of saw palmetto (Serenoa repens) extracts.

    PubMed

    Perini, Matteo; Paolini, Mauro; Camin, Federica; Appendino, Giovanni; Vitulo, Francesca; De Combarieu, Eric; Sardone, Nicola; Martinelli, Ernesto Marco; Pace, Roberto

    2018-04-22

    Saw palmetto (Serenoa repens, SP) is the most expensive oil source of the pharmaceutical and healthfood market, and its high cost and recurrent shortages have spurred the development of designer blends of fatty acids to mimic its phytochemical profile and fraudulently comply with the current authentication assays. To detect this adulteration, the combined use of isotopic fingerprint and omic analysis has been investigated, using Principal Component Analysis (PCA) to handle the complex databases generated by these techniques and to identify the possible source of the adulterants. Surprisingly, the presence of fatty acids of animal origin turned out to be widespread in commercial samples of saw palmetto oil. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Metabolomics in Toxicology and Preclinical Research, a t4 Workshop Report

    EPA Science Inventory

    Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological condition of the test system, and of changes affected by anthropogenic chemicals. Metabolomic analysis is used in many fields, ranging...

  10. Tissue Multiplatform-Based Metabolomics/Metabonomics for Enhanced Metabolome Coverage.

    PubMed

    Vorkas, Panagiotis A; Abellona U, M R; Li, Jia V

    2018-01-01

    The use of tissue as a matrix to elucidate disease pathology or explore intervention comes with several advantages. It allows investigation of the target alteration directly at the focal location and facilitates the detection of molecules that could become elusive after secretion into biofluids. However, tissue metabolomics/metabonomics comes with challenges not encountered in biofluid analyses. Furthermore, tissue heterogeneity does not allow for tissue aliquoting. Here we describe a multiplatform, multi-method workflow which enables metabolic profiling analysis of tissue samples, while it can deliver enhanced metabolome coverage. After applying a dual consecutive extraction (organic followed by aqueous), tissue extracts are analyzed by reversed-phase (RP-) and hydrophilic interaction liquid chromatography (HILIC-) ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) and nuclear magnetic resonance (NMR) spectroscopy. This pipeline incorporates the required quality control features, enhances versatility, allows provisional aliquoting of tissue extracts for future guided analyses, expands the range of metabolites robustly detected, and supports data integration. It has been successfully employed for the analysis of a wide range of tissue types.

  11. Systematic Applications of Metabolomics in Metabolic Engineering

    PubMed Central

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

    The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering. PMID:24957776

  12. MetaboLights: towards a new COSMOS of metabolomics data management.

    PubMed

    Steinbeck, Christoph; Conesa, Pablo; Haug, Kenneth; Mahendraker, Tejasvi; Williams, Mark; Maguire, Eamonn; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Salek, Reza M; Griffin, Julian L

    2012-10-01

    Exciting funding initiatives are emerging in Europe and the US for metabolomics data production, storage, dissemination and analysis. This is based on a rich ecosystem of resources around the world, which has been build during the past ten years, including but not limited to resources such as MassBank in Japan and the Human Metabolome Database in Canada. Now, the European Bioinformatics Institute has launched MetaboLights, a database for metabolomics experiments and the associated metadata (http://www.ebi.ac.uk/metabolights). It is the first comprehensive, cross-species, cross-platform metabolomics database maintained by one of the major open access data providers in molecular biology. In October, the European COSMOS consortium will start its work on Metabolomics data standardization, publication and dissemination workflows. The NIH in the US is establishing 6-8 metabolomics services cores as well as a national metabolomics repository. This communication reports about MetaboLights as a new resource for Metabolomics research, summarises the related developments and outlines how they may consolidate the knowledge management in this third large omics field next to proteomics and genomics.

  13. LC-MS based metabolomics and chemometrics study of the toxic effects of copper on Saccharomyces cerevisiae.

    PubMed

    Farrés, Mireia; Piña, Benjamí; Tauler, Romà

    2016-08-01

    Copper containing fungicides are used to protect vineyards from fungal infections. Higher residues of copper in grapes at toxic concentrations are potentially toxic and affect the microorganisms living in vineyards, such as Saccharomyces cerevisiae. In this study, the response of the metabolic profiles of S. cerevisiae at different concentrations of copper sulphate (control, 1 mM, 3 mM and 6 mM) was analysed by liquid chromatography coupled to mass spectrometry (LC-MS) and multivariate curve resolution-alternating least squares (MCR-ALS) using an untargeted metabolomics approach. Peak areas of the MCR-ALS resolved elution profiles in control and in Cu(ii)-treated samples were compared using partial least squares regression (PLSR) and PLS-discriminant analysis (PLS-DA), and the intracellular metabolites best contributing to sample discrimination were selected and identified. Fourteen metabolites showed significant concentration changes upon Cu(ii) exposure, following a dose-response effect. The observed changes were consistent with the expected effects of Cu(ii) toxicity, including oxidative stress and DNA damage. This research confirmed that LC-MS based metabolomics coupled to chemometric methods are a powerful approach for discerning metabolomics changes in S. cerevisiae and for elucidating modes of toxicity of environmental stressors, including heavy metals like Cu(ii).

  14. Updates in metabolomics tools and resources: 2014-2015.

    PubMed

    Misra, Biswapriya B; van der Hooft, Justin J J

    2016-01-01

    Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Associations of Nasopharyngeal Metabolome and Microbiome with Severity among Infants with Bronchiolitis. A Multiomic Analysis.

    PubMed

    Stewart, Christopher J; Mansbach, Jonathan M; Wong, Matthew C; Ajami, Nadim J; Petrosino, Joseph F; Camargo, Carlos A; Hasegawa, Kohei

    2017-10-01

    Bronchiolitis is the most common lower respiratory infection in infants; however, it remains unclear which infants with bronchiolitis will develop severe illness. In addition, although emerging evidence indicates associations of the upper-airway microbiome with bronchiolitis severity, little is known about the mechanisms linking airway microbes and host response to disease severity. To determine the relations among the nasopharyngeal airway metabolome profiles, microbiome profiles, and severity in infants with bronchiolitis. We conducted a multicenter prospective cohort study of infants (age <1 yr) hospitalized with bronchiolitis. By applying metabolomic and metagenomic (16S ribosomal RNA gene and whole-genome shotgun sequencing) approaches to 144 nasopharyngeal airway samples collected within 24 hours of hospitalization, we determined metabolome and microbiome profiles and their association with higher severity, defined by the use of positive pressure ventilation (i.e., continuous positive airway pressure and/or intubation). Nasopharyngeal airway metabolome profiles significantly differed by bronchiolitis severity (P < 0.001). Among 254 metabolites identified, a panel of 25 metabolites showed high sensitivity (84%) and specificity (86%) in predicting the use of positive pressure ventilation. The intensity of these metabolites was correlated with relative abundance of Streptococcus pneumoniae. In the pathway analysis, sphingolipid metabolism was the most significantly enriched subpathway in infants with positive pressure ventilation use compared with those without (P < 0.001). Enrichment of sphingolipid metabolites was positively correlated with the relative abundance of S. pneumoniae. Although further validation is needed, our multiomic analyses demonstrate the potential of metabolomics to predict bronchiolitis severity and better understand microbe-host interaction.

  16. Oxygen isotopes in nitrite: Analysis, calibration, and equilibration

    USGS Publications Warehouse

    Casciotti, K.L.; Böhlke, J.K.; McIlvin, M.R.; Mroczkowski, S.J.; Hannon, J.E.

    2007-01-01

    Nitrite is a central intermediate in the nitrogen cycle and can persist in significant concentrations in ocean waters, sediment pore waters, and terrestrial groundwaters. To fully interpret the effect of microbial processes on nitrate (NO3-), nitrite (NO2-), and nitrous oxide (N2O) cycling in these systems, the nitrite pool must be accessible to isotopic analysis. Furthermore, because nitrite interferes with most methods of nitrate isotopic analysis, accurate isotopic analysis of nitrite is essential for correct measurement of nitrate isotopes in a sample that contains nitrite. In this study, nitrite salts with varying oxygen isotopic compositions were prepared and calibrated and then used to test the denitrifier method for nitrite oxygen isotopic analysis. The oxygen isotopic fractionation during nitrite reduction to N2O by Pseudomonas aureofaciens was lower than for nitrate conversion to N2O, while oxygen isotopic exchange between nitrite and water during the reaction was similar. These results enable the extension of the denitrifier method to oxygen isotopic analysis of nitrite (in the absence of nitrate) and correction of nitrate isotopes for the presence of nitrite in “mixed” samples. We tested storage conditions for seawater and freshwater samples that contain nitrite and provide recommendations for accurate oxygen isotopic analysis of nitrite by any method. Finally, we report preliminary results on the equilibrium isotope effect between nitrite and water, which can play an important role in determining the oxygen isotopic value of nitrite where equilibration with water is significant.

  17. Isotopic Analysis and Evolved Gases

    NASA Technical Reports Server (NTRS)

    Swindle, Timothy D.; Boynton, William V.; Chutjian, Ara; Hoffman, John H.; Jordan, Jim L.; Kargel, Jeffrey S.; McEntire, Richard W.; Nyquist, Larry

    1996-01-01

    Precise measurements of the chemical, elemental, and isotopic composition of planetary surface material and gases, and observed variations in these compositions, can contribute significantly to our knowledge of the source(s), ages, and evolution of solar system materials. The analyses discussed in this paper are mostly made by mass spectrometers or some other type of mass analyzer, and address three broad areas of interest: (1) atmospheric composition - isotopic, elemental, and molecular, (2) gases evolved from solids, and (3) solids. Current isotopic data on nine elements, mostly from in situ analysis, but also from meteorites and telescopic observations are summarized. Potential instruments for isotopic analysis of lunar, Martian, Venusian, Mercury, and Pluto surfaces, along with asteroid, cometary and icy satellites, surfaces are discussed.

  18. Clinical application of metabolomics in neonatology.

    PubMed

    Fanos, Vassilios; Antonucci, Roberto; Barberini, Luigi; Noto, Antonio; Atzori, Luigi

    2012-04-01

    The youngest and more rapidly increasing "omic" discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a "snapshot" of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine ("a window on the organism") is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.

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

    PubMed

    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.

  20. High Resolution Separations and Improved Ion Production and Transmission in Metabolomics

    PubMed Central

    Metz, Thomas O.; Page, Jason S.; Baker, Erin S.; Tang, Keqi; Ding, Jie; Shen, Yufeng; Smith, Richard D.

    2008-01-01

    The goal of metabolomics analyses is the detection and quantitation of as many sample components as reasonably possible in order to identify compounds or “features” that can be used to characterize the samples under study. When utilizing electrospray ionization to produce ions for analysis by mass spectrometry (MS), it is important that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize ionization suppression and thereby extend the dynamic range of the measurement, as well as the coverage of the metabolome. Similarly, optimization of the MS inlet and interface can lead to increased measurement sensitivity. This perspective review will focus on the role of high resolution liquid chromatography (LC) separations in conjunction with improved ion production and transmission for LC-MS-based metabolomics. Additional emphasis will be placed on the compromise between metabolome coverage and sample analysis throughput. PMID:19255623

  1. Spent culture medium analysis from individually cultured bovine embryos demonstrates metabolomic differences.

    PubMed

    Perkel, Kayla J; Madan, Pavneesh

    2017-12-01

    Spent culture medium can provide valuable information regarding the physiological state of a bovine preimplantation embryos through non-invasive analysis of the sum/depleted metabolite constituents. Metabolomics has become of great interest as an adjunct technique to morphological and cleavage-rate assessment, but more importantly, in improving our understanding of metabolism. In this study, in vitro produced bovine embryos developing at different rates were evaluated using proton nuclear magnetic resonance (1H NMR). Spent culture medium from individually cultured embryos (2-cell to blastocyst stage) were divided into two groups based on their cleavage rate fast growing (FG) and slow growing (SG; developmentally delayed by 12-24 h), then analyzed by a 600 MHz NMR spectrometer. Sixteen metabolites were detected and investigated for sum/depletion throughout development. Data indicate distinct differences between the 4-cell SG and FG embryos for pyruvate (P < 0.05, n = 9) and at the 16-cell stage for acetate, tryptophan, leucine/isoleucine, valine and histidine. Overall sum/depletion levels of metabolites demonstrated that embryos produced glutamate, but consumed histidine, tyrosine, glycine, methionine, tryptophan, phenylalanine, lysine, arginine, acetate, threonine, alanine, pyruvate, valine, isoleucine/leucine, and lactate with an overall trend of higher consumption of these metabolites by FG groups. Principal component analysis revealed distinct clustering of the plain medium, SG, and FG group, signifying the uniqueness of the metabolomic signatures of each of these groups. This study is the first of its kind to characterize the metabolomic profiles of SG and FG bovine embryos produced in vitro using 1H NMR. Elucidating differences between embryos of varying developmental rates could contribute to a better understanding of embryonic health and physiology.

  2. The Human Serum Metabolome

    PubMed Central

    Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

    2011-01-01

    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. PMID:21359215

  3. Metabolomics in chemical ecology.

    PubMed

    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.

  4. Metabolomic Analysis of Key Central Carbon Metabolism Carboxylic Acids as Their 3-Nitrophenylhydrazones by UPLC/ESI-MS

    PubMed Central

    Han, Jun; Gagnon, Susannah; Eckle, Tobias; Borchers, Christoph H.

    2014-01-01

    Multiple hydroxy-, keto-, di-, and tri-carboxylic acids are among the cellular metabolites of central carbon metabolism (CCM). Sensitive and reliable analysis of these carboxylates is important for many biological and cell engineering studies. In this work, we examined 3-nitrophenylhydrazine as a derivatizing reagent and optimized the reaction conditions for the measurement of ten CCM related carboxylic compounds, including glycolate, lactate, malate, fumarate, succinate, citrate, isocitrate, pyruvate, oxaloacetate, and α-ketoglutarate as their 3-nitrophenylhydrazones using LC/MS with electrospray ionization. With the derivatization protocol which we have developed, and using negative-ion multiple reaction monitoring on a triple-quadrupole instrument, all of the carboxylates showed good linearity within a dynamic range of ca. 200 to more than 2000. The on-column limits of detection and quantitation were from high femtomoles to low picomoles. The analytical accuracies for eight of the ten analytes were determined to be between 89.5 to 114.8% (CV≤7.4%, n=6). Using a quadrupole time-of-flight instrument, the isotopic distribution patterns of these carboxylates, extracted from a 13C-labeled mouse heart, were successfully determined by UPLC/MS with full-mass detection, indicating the possible utility of this analytical method for metabolic flux analysis. In summary, this work demonstrates an efficient chemical derivatization LC/MS method for metabolomic analysis of these key CCM intermediates in a biological matrix. PMID:23580203

  5. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter

    Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

  6. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

    DOE PAGES

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; ...

    2015-05-07

    Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

  7. Metabolomic markers of fertility in bull seminal plasma

    PubMed Central

    Dinh, Thu; Kaya, Abdullah; Topper, Einko; Moura, Arlindo Alencar

    2018-01-01

    Metabolites play essential roles in biological systems, but detailed identities and significance of the seminal plasma metabolome related to bull fertility are still unknown. The objectives of this study were to determine the comprehensive metabolome of seminal plasma from Holstein bulls and to ascertain the potential of metabolites as biomarkers of bull fertility. The seminal plasma metabolome from 16 Holstein bulls with two fertility rates were determined by gas chromatography-mass spectrometry (GC-MS). Multivariate and univariate analyses of the data were performed, and the pathways associated with the seminal plasma metabolome were identified using bioinformatics approaches. Sixty-three metabolites were identified in the seminal plasma of all bulls. Fructose was the most abundant metabolite in the seminal fluid, followed for citric acid, lactic acid, urea and phosphoric acid. Androstenedione, 4-ketoglucose, D-xylofuranose, 2-oxoglutaric acid and erythronic acid represented the least predominant metabolites. Partial-Least Squares Discriminant Analysis (PLSDA) revealed a distinct separation between high and low fertility bulls. The metabolites with the greatest Variable Importance in Projection score (VIP > 2) were 2-oxoglutaric acid and fructose. Heat-map analysis, based on VIP score, and univariate analysis indicated that 2-oxoglutaric acid was less (P = 0.02); whereas fructose was greater (P = 0.02) in high fertility than in low fertility bulls. The current study is the first to describe the metabolome of bull seminal plasma using GC-MS and presented metabolites such as 2-oxoglutaric acid and fructose as potential biomarkers of bull fertility. PMID:29634739

  8. A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions

    PubMed Central

    2013-01-01

    Background Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Results Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia

  9. Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

    PubMed Central

    Zordoky, Beshay N.; Sung, Miranda M.; Ezekowitz, Justin; Mandal, Rupasri; Han, Beomsoo; Bjorndahl, Trent C.; Bouatra, Souhaila; Anderson, Todd; Oudit, Gavin Y.; Wishart, David S.; Dyck, Jason R. B.

    2015-01-01

    Background Heart failure (HF) with preserved ejection fraction (HFpEF) is increasingly recognized as an important clinical entity. Preclinical studies have shown differences in the pathophysiology between HFpEF and HF with reduced ejection fraction (HFrEF). Therefore, we hypothesized that a systematic metabolomic analysis would reveal a novel metabolomic fingerprint of HFpEF that will help understand its pathophysiology and assist in establishing new biomarkers for its diagnosis. Methods and Results Ambulatory patients with clinical diagnosis of HFpEF (n = 24), HFrEF (n = 20), and age-matched non-HF controls (n = 38) were selected for metabolomic analysis as part of the Alberta HEART (Heart Failure Etiology and Analysis Research Team) project. 181 serum metabolites were quantified by LC-MS/MS and 1H-NMR spectroscopy. Compared to non-HF control, HFpEF patients demonstrated higher serum concentrations of acylcarnitines, carnitine, creatinine, betaine, and amino acids; and lower levels of phosphatidylcholines, lysophosphatidylcholines, and sphingomyelins. Medium and long-chain acylcarnitines and ketone bodies were higher in HFpEF than HFrEF patients. Using logistic regression, two panels of metabolites were identified that can separate HFpEF patients from both non-HF controls and HFrEF patients with area under the receiver operating characteristic (ROC) curves of 0.942 and 0.981, respectively. Conclusions The metabolomics approach employed in this study identified a unique metabolomic fingerprint of HFpEF that is distinct from that of HFrEF. This metabolomic fingerprint has been utilized to identify two novel panels of metabolites that can separate HFpEF patients from both non-HF controls and HFrEF patients. Clinical Trial Registration ClinicalTrials.gov NCT02052804 PMID:26010610

  10. Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

    PubMed Central

    Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

    2013-01-01

    The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

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

    PubMed

    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 <0.05) that cannot be discovered by other machine 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.

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

    PubMed Central

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-01-01

    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. PMID:27271597

  13. Untargeted metabolomic analysis of tomato pollen development and heat stress response.

    PubMed

    Paupière, Marine J; Müller, Florian; Li, Hanjing; Rieu, Ivo; Tikunov, Yury M; Visser, Richard G F; Bovy, Arnaud G

    2017-06-01

    Pollen development metabolomics. Developing pollen is among the plant structures most sensitive to high temperatures, and a decrease in pollen viability is often associated with an alteration of metabolite content. Most of the metabolic studies of pollen have focused on a specific group of compounds, which limits the identification of physiologically important metabolites. To get a better insight into pollen development and the pollen heat stress response, we used a liquid chromatography-mass spectrometry platform to detect secondary metabolites in pollen of tomato (Solanum lycopersicum L.) at three developmental stages under control conditions and after a short heat stress at 38 °C. Under control conditions, the young microspores accumulated a large amount of alkaloids and polyamines, whereas the mature pollen strongly accumulated flavonoids. The heat stress treatment led to accumulation of flavonoids in the microspore. The biological role of the detected metabolites is discussed. This study provides the first untargeted metabolomic analysis of developing pollen under a changing environment that can serve as reference for further studies.

  14. Metabolomics and Epidemiology Working Group

    Cancer.gov

    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.

  15. UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research.

    PubMed

    Nassar, Ala F; Wu, Terence; Nassar, Samuel F; Wisnewski, Adam V

    2017-02-01

    Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

    PubMed Central

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide–consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry–based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level. PMID:25486521

  17. MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles

    PubMed Central

    2011-01-01

    Background Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments. Description MeRy-B, the first platform for plant 1H-NMR metabolomic profiles, is designed (i) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (ii) for queries and visualization of the data, (iii) to discriminate between profiles with spectrum visualization tools and statistical analysis, (iv) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues. Conclusion MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from http://www.cbib.u-bordeaux2.fr/MERYB/index.php. PMID:21668943

  18. Lipidome and metabolome analysis of fresh tobacco leaves in different geographical regions using liquid chromatography-mass spectrometry.

    PubMed

    Li, Lili; Lu, Xin; Zhao, Jieyu; Zhang, Junjie; Zhao, Yanni; Zhao, Chunxia; Xu, Guowang

    2015-07-01

    The combination of the lipidome and the metabolome can provide much more information in plant metabolomics studies. A method for the simultaneous extraction of the lipidome and the metabolome of fresh tobacco leaves was developed. Method validation was performed on the basis of the optimal ratio of methanol to methyl tert-butyl ether to water (37:45:68) from the design of experiments. Good repeatability was obtained. We found that 92.2% and 91.6% of the peaks for the lipidome and the metabolome were within a relative standard deviation of 20%, accounting for 94.6% and 94.6% of the total abundance, respectively. The intraday and interday precisions were also satisfactory. A total of 230 metabolites, including 129 lipids, were identified. Significant differences were found in lipidomic and metabolomic profiles of fresh tobacco leaves in different geographical regions. Highly unsaturated galactolipids, phosphatidylethanolamines, predominant phosphatidylcholines, most of the polyphenols, amino acids, and polyamines had a higher content in Yunnan province, and low-unsaturation-degree galactolipids, triacylglycerols, glucosylceramides with trihydroxy long-chain bases, acylated sterol glucosides, and some organic acids were more abundant in Henan province. Correlation analysis between differential metabolites and climatic factors indicated the vital importance of temperature. The fatty acid unsaturation degree of galactolipids could be influenced by temperature. Accumulation of polyphenols and decreases in the ratios of stigmasterols to sitosterols and glucosylstigmasterols to glucosylsitosterols were also correlated with lower temperature in Yunnan province. Furthermore, lipids were more sensitive to climatic variations than other metabolites.

  19. Comparison of peak-picking workflows for untargeted liquid chromatography/high-resolution mass spectrometry metabolomics data analysis.

    PubMed

    Rafiei, Atefeh; Sleno, Lekha

    2015-01-15

    Data analysis is a key step in mass spectrometry based untargeted metabolomics, starting with the generation of generic peak lists from raw liquid chromatography/mass spectrometry (LC/MS) data. Due to the use of various algorithms by different workflows, the results of different peak-picking strategies often differ widely. Raw LC/HRMS data from two types of biological samples (bile and urine), as well as a standard mixture of 84 metabolites, were processed with four peak-picking softwares: Peakview®, Markerview™, MetabolitePilot™ and XCMS Online. The overlaps between the results of each peak-generating method were then investigated. To gauge the relevance of peak lists, a database search using the METLIN online database was performed to determine which features had accurate masses matching known metabolites as well as a secondary filtering based on MS/MS spectral matching. In this study, only a small proportion of all peaks (less than 10%) were common to all four software programs. Comparison of database searching results showed peaks found uniquely by one workflow have less chance of being found in the METLIN metabolomics database and are even less likely to be confirmed by MS/MS. It was shown that the performance of peak-generating workflows has a direct impact on untargeted metabolomics results. As it was demonstrated that the peaks found in more than one peak detection workflow have higher potential to be identified by accurate mass as well as MS/MS spectrum matching, it is suggested to use the overlap of different peak-picking workflows as preliminary peak lists for more rugged statistical analysis in global metabolomics investigations. Copyright © 2014 John Wiley & Sons, Ltd.

  20. Preparation of Authigenic Pyrite from Methane-bearing Sediments for In Situ Sulfur Isotope Analysis Using SIMS.

    PubMed

    Lin, Zhiyong; Sun, Xiaoming; Peckmann, Jörn; Lu, Yang; Strauss, Harald; Xu, Li; Lu, Hongfeng; Teichert, Barbara M A

    2017-08-31

    Different sulfur isotope compositions of authigenic pyrite typically result from the sulfate-driven anaerobic oxidation of methane (SO4-AOM) and organiclastic sulfate reduction (OSR) in marine sediments. However, unravelling the complex pyritization sequence is a challenge because of the coexistence of different sequentially formed pyrite phases. This manuscript describes a sample preparation procedure that enables the use of secondary ion mass spectroscopy (SIMS) to obtain in situ δ 34 S values of various pyrite generations. This allows researchers to constrain how SO4-AOM affects pyritization in methane-bearing sediments. SIMS analysis revealed an extreme range in δ 34 S values, spanning from -41.6 to +114.8‰, which is much wider than the range of δ 34 S values obtained by the traditional bulk sulfur isotope analysis of the same samples. Pyrite in the shallow sediment mainly consists of 34 S-depleted framboids, suggesting early diagenetic formation by OSR. Deeper in the sediment, more pyrite occurs as overgrowths and euhedral crystals, which display much higher SIMS δ 34 S values than the framboids. Such 34 S-enriched pyrite is related to enhanced SO4-AOM at the sulfate-methane transition zone, postdating OSR. High-resolution in situ SIMS sulfur isotope analyses allow for the reconstruction of the pyritization processes, which cannot be resolved by bulk sulfur isotope analysis.

  1. The 1H-NMR-based metabolite profile of acute alcohol consumption: A metabolomics intervention study

    PubMed Central

    Mason, Shayne; Mienie, Lodewyk J.; Wevers, Ron A.; Westerhuis, Johan A.

    2018-01-01

    Metabolomics studies of disease conditions related to chronic alcohol consumption provide compelling evidence of several perturbed metabolic pathways underlying the pathophysiology of alcoholism. The objective of the present study was to utilize proton nuclear magnetic resonance (1H-NMR) spectroscopy metabolomics to study the holistic metabolic consequences of acute alcohol consumption in humans. The experimental design was a cross-over intervention study which included a number of substances to be consumed—alcohol, a nicotinamide adenine dinucleotide (NAD) supplement, and a benzoic acid-containing flavoured water vehicle. The experimental subjects—24 healthy, moderate-drinking young men—each provided six hourly-collected urine samples for analysis. Complete data sets were obtained from 20 of the subjects and used for data generation, analysis and interpretation. The results from the NMR approach produced complex spectral data, which could be resolved sufficiently through the application of a combination of univariate and multivariate methods of statistical analysis. The metabolite profiles resulting from acute alcohol consumption indicated that alcohol-induced NAD+ depletion, and the production of an excessive amount of reducing equivalents, greatly perturbed the hepatocyte redox homeostasis, resulting in essentially three major metabolic disturbances—up-regulated lactic acid metabolism, down-regulated purine catabolism and osmoregulation. Of these, the urinary excretion of the osmolyte sorbitol proved to be novel, and suggests hepatocyte swelling due to ethanol influx following acute alcohol consumption. Time-dependent metabolomics investigations, using designed interventions, provide a way of interpreting the variation induced by the different factors of a designed experiment, thereby also giving methodological significance to this study. The outcomes of this approach have the potential to significantly advance our understanding of the serious impact of

  2. Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data.

    PubMed

    Marco-Ramell, Anna; Palau-Rodriguez, Magali; Alay, Ania; Tulipani, Sara; Urpi-Sarda, Mireia; Sanchez-Pla, Alex; Andres-Lacueva, Cristina

    2018-01-02

    Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses

  3. The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments.

    PubMed

    Martins, Marina C M; Caldana, Camila; Wolf, Lucia Daniela; de Abreu, Luis Guilherme Furlan

    2018-01-01

    The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

  4. Resolving the trophic relations of cryptic species: an example using stable isotope analysis of dolphin teeth.

    PubMed

    Owen, Kylie; Charlton-Robb, Kate; Thompson, Ross

    2011-02-18

    Understanding the foraging ecology and diet of animals can play a crucial role in conservation of a species. This is particularly true where species are cryptic and coexist in environments where observing feeding behaviour directly is difficult. Here we present the first information on the foraging ecology of a recently identified species of dolphin (Southern Australian bottlenose dolphin (SABD)) and comparisons to the common bottlenose dolphin (CBD) in Victoria, Australia, using stable isotope analysis of teeth. Stable isotope signatures differed significantly between SABD and CBD for both δ(13)C (-14.4‰ vs. -15.5‰ respectively) and δ(15)N (15.9‰ vs. 15.0‰ respectively), suggesting that the two species forage in different areas and consume different prey. This finding supports genetic and morphological data indicating that SABD are distinct from CBD. In Victoria, the SABD is divided into two distinct populations, one in the large drowned river system of Port Phillip Bay and the other in a series of coastal lakes and lagoons called the Gippsland Lakes. Within the SABD species, population differences were apparent. The Port Phillip Bay population displayed a significantly higher δ(15)N than the Gippsland Lakes population (17.0‰ vs. 15.5‰), suggesting that the Port Phillip Bay population may feed at a higher trophic level--a result which is supported by analysis of local food chains. Important future work is required to further understand the foraging ecology and diet of this newly described, endemic, and potentially endangered species of dolphin.

  5. Resolving the Trophic Relations of Cryptic Species: An Example Using Stable Isotope Analysis of Dolphin Teeth

    PubMed Central

    Owen, Kylie; Charlton-Robb, Kate; Thompson, Ross

    2011-01-01

    Understanding the foraging ecology and diet of animals can play a crucial role in conservation of a species. This is particularly true where species are cryptic and coexist in environments where observing feeding behaviour directly is difficult. Here we present the first information on the foraging ecology of a recently identified species of dolphin (Southern Australian bottlenose dolphin (SABD)) and comparisons to the common bottlenose dolphin (CBD) in Victoria, Australia, using stable isotope analysis of teeth. Stable isotope signatures differed significantly between SABD and CBD for both δ13C (−14.4‰ vs. −15.5‰ respectively) and δ15N (15.9‰ vs. 15.0‰ respectively), suggesting that the two species forage in different areas and consume different prey. This finding supports genetic and morphological data indicating that SABD are distinct from CBD. In Victoria, the SABD is divided into two distinct populations, one in the large drowned river system of Port Phillip Bay and the other in a series of coastal lakes and lagoons called the Gippsland Lakes. Within the SABD species, population differences were apparent. The Port Phillip Bay population displayed a significantly higher δ15N than the Gippsland Lakes population (17.0‰ vs. 15.5‰), suggesting that the Port Phillip Bay population may feed at a higher trophic level - a result which is supported by analysis of local food chains. Important future work is required to further understand the foraging ecology and diet of this newly described, endemic, and potentially endangered species of dolphin. PMID:21364748

  6. Metabolomic Strategies Involving Mass Spectrometry Combined with Liquid and Gas Chromatography.

    PubMed

    Lopes, Aline Soriano; Cruz, Elisa Castañeda Santa; Sussulini, Alessandra; Klassen, Aline

    2017-01-01

    Amongst all omics sciences, there is no doubt that metabolomics is undergoing the most important growth in the last decade. The advances in analytical techniques and data analysis tools are the main factors that make possible the development and establishment of metabolomics as a significant research field in systems biology. As metabolomic analysis demands high sensitivity for detecting metabolites present in low concentrations in biological samples, high-resolution power for identifying the metabolites and wide dynamic range to detect metabolites with variable concentrations in complex matrices, mass spectrometry is being the most extensively used analytical technique for fulfilling these requirements. Mass spectrometry alone can be used in a metabolomic analysis; however, some issues such as ion suppression may difficultate the quantification/identification of metabolites with lower concentrations or some metabolite classes that do not ionise as well as others. The best choice is coupling separation techniques, such as gas or liquid chromatography, to mass spectrometry, in order to improve the sensitivity and resolution power of the analysis, besides obtaining extra information (retention time) that facilitates the identification of the metabolites, especially when considering untargeted metabolomic strategies. In this chapter, the main aspects of mass spectrometry (MS), liquid chromatography (LC) and gas chromatography (GC) are discussed, and recent clinical applications of LC-MS and GC-MS are also presented.

  7. SHRIMP-SI Multiple Sulfur Isotope Analysis of Sulfides from Brazilian Deposits: Analytical Capability to Resolve Single Grain Textural Complexities and Distinct Sulfur Sources

    NASA Astrophysics Data System (ADS)

    Ireland, T. R.; Teles, G. D. S.; Chemale, F., Jr.; Avila, J.

    2016-12-01

    The Archean atmosphere is thought to be several times more reducing than the present day atmosphere, and the occurrence of Mass Independent Fractionation of Sulfur isotopes (MIF-S) in sulfides of sedimentary and volcanogenic rocks older than 2.45 Ga reinforces it. The most accepted mechanism to generate MIF-S requires photochemical reactions with volcanogenic SO2 in an anoxic atmosphere (O2 levels <10-5 PAL). The identification of MIF-S, noted as Δ33S and Δ36S, requires precise measurements of less abundant 33S and 36S isotopes, which were first attained by bulk isotope analyses. However, in-situ analysis has become essential, as many of ancient sulfide samples have suffered post-depositional processes, and their primary isotopic signature from the atmosphere are now overprinted by mass-dependent fractionation processes. High-precision and resolution in situ measurements of 32S, 33S, 34S and 36S in sulfides can be achieved by SHRIMP-SI, which allows isotopic determinations with internal errors better than 0.05‰ for Δ33S and 0.2‰ for Δ36S (2SE), and reproducibility about 0.1‰ for Δ33S and better than 0.5‰ for Δ36S (2SD). Examples of the SHRIMP-SI capability are provided by multiple sulfur isotope analysis of samples from Brazil, the Au-(U) and pyrite deposits of Jacobina Basin and the massive sulfide deposits of the 3.3 Ga Mundo Novo Greenstone Belt. The level of precision and spatial resolution achievable with SHRIMP-SI allowed the isotopic distinction between sedimentary and post-depositional pyrites in Jacobina Basin, as well as the identification of different sulfur sources in the Mundo Novo Greenstone Belt VMS deposits.

  8. Distinct urine metabolome after Asian ginseng and American ginseng intervention based on GC-MS metabolomics approach

    PubMed Central

    Yang, Liu; Yu, Qing-Tao; Ge, Ya-Zhong; Zhang, Wen-Song; Fan, Yong; Ma, Chung-Wah; Liu, Qun; Qi, Lian-Wen

    2016-01-01

    Ginseng occupies a prominent position in the list of best-selling natural products worldwide. Asian ginseng (Panax ginseng) and American ginseng (Panax quinquefolius) show different properties and medicinal applications in pharmacology, even though the main active constituents of them are both thought to be ginsenosides. Metabolomics is a promising method to profile entire endogenous metabolites and monitor their fluctuations related to exogenous stimulus. Herein, an untargeted metabolomics approach was applied to study the overall urine metabolic differences between Asian ginseng and American ginseng in mice. Metabolomics analyses were performed using gas chromatography-mass spectrometry (GC-MS) together with multivariate statistical data analysis. A total of 21 metabolites related to D-glutamine and D-glutamate metabolism, glutathione metabolism, TCA cycle and glyoxylate and dicarboxylate metabolism, differed significantly under the Asian ginseng treatment; 34 metabolites mainly associated with glyoxylate and dicarboxylate metabolism, TCA cycle and taurine and hypotaurine metabolism, were significantly altered after American ginseng treatment. Urinary metabolomics reveal that Asian ginseng and American ginseng can benefit organism physiological and biological functions via regulating multiple metabolic pathways. The important pathways identified from Asian ginseng and American ginseng can also help to explore new therapeutic effects or action targets so as to broad application of these two ginsengs. PMID:27991533

  9. Analysis of salivary phenotypes of generalized aggressive and chronic periodontitis through nuclear magnetic resonance-based metabolomics.

    PubMed

    Romano, Federica; Meoni, Gaia; Manavella, Valeria; Baima, Giacomo; Tenori, Leonardo; Cacciatore, Stefano; Aimetti, Mario

    2018-06-07

    Recent findings about the differential gene expression signature of periodontal lesions have raised the hypothesis of distinctive biological phenotypes expressed by generalized chronic periodontitis (GCP) and generalized aggressive periodontitis (GAgP) patients. Therefore, this cross-sectional investigation was planned, primarily, to determine the ability of nuclear magnetic resonance (NMR) spectroscopic analysis of unstimulated whole saliva to discriminate GCP and GAgP disease-specific metabolomic fingerprint and, secondarily, to assess potential metabolites discriminating periodontitis patients from periodontally healthy individuals (HI). NMR-metabolomics spectra were acquired from salivary samples of patients with a clinical diagnosis of GCP (n = 33) or GAgP (n = 28) and from HI (n = 39). The clustering of HI, GCP and GAgP patients was achieved by using a combination of the Principal Component Analysis and Canonical Correlation Analysis on the NMR profiles. These analyses revealed a significant predictive accuracy discriminating HI from GCP, and discriminating HI from GAgP patients (both 81%). In contrast, the GAgP and GCP saliva samples seem to belong to the same metabolic space (60% predictive accuracy). Significantly lower levels (P < 0.05) of pyruvate, N-acetyl groups and lactate and higher levels (P < 0.05) of proline, phenylalanine, and tyrosine were found in GCP and GAgP patients compared with HI. Within the limitations of this study, CGP and GAgP metabolomic profiles were not unequivocally discriminated through a NMR-based spectroscopic analysis of saliva. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  10. iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination

    PubMed Central

    Chang, Hui-Yin; Chen, Ching-Tai; Lih, T. Mamie; Lynn, Ke-Shiuan; Juo, Chiun-Gung; Hsu, Wen-Lian; Sung, Ting-Yi

    2016-01-01

    Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤0.19) when quantifying the two internal standards and had higher abundance correlation (≥0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html. PMID:26784691

  11. Metabolomic Assessment of Embryo Viability

    PubMed Central

    Uyar, Asli; Seli, Emre

    2014-01-01

    Preimplantation embryo metabolism demonstrates distinctive characteristics associated with the developmental potential of embryos. On this basis, metabolite content of culture media was hypothesized to reflect the implantation potential of individual embryos. This hypothesis was tested in consecutive studies reporting a significant association between culture media metabolites and embryo development or clinical pregnancy. The need for a noninvasive, reliable, and rapid embryo assessment strategy promoted metabolomics studies in vitro fertilization (IVF) in an effort to increase success rates of single embryo transfers. With the advance of analytical techniques and bioinformatics, commercial instruments were developed to predict embryo viability using spectroscopic analysis of surplus culture media. However, despite the initial promising results from proof-of-principal studies, recent randomized controlled trials using commercial instruments failed to show a consistent benefit in improving pregnancy rates when metabolomics is used as an adjunct to morphology. At present, the application of metabolomics technology in clinical IVF laboratory requires the elimination of factors underlying inconsistent findings, when possible, and development of reliable predictive models accounting for all possible sources of bias throughout the embryo selection process. PMID:24515909

  12. The Human Urine Metabolome

    PubMed Central

    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

    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 containing

  13. Plasma Metabolomic Changes following PI3K Inhibition as Pharmacodynamic Biomarkers: Preclinical Discovery to Phase I Trial Evaluation.

    PubMed

    Ang, Joo Ern; Pandher, Rupinder; Ang, Joo Chew; Asad, Yasmin J; Henley, Alan T; Valenti, Melanie; Box, Gary; de Haven Brandon, Alexis; Baird, Richard D; Friedman, Lori; Derynck, Mika; Vanhaesebroeck, Bart; Eccles, Suzanne A; Kaye, Stan B; Workman, Paul; de Bono, Johann S; Raynaud, Florence I

    2016-06-01

    PI3K plays a key role in cellular metabolism and cancer. Using a mass spectrometry-based metabolomics platform, we discovered that plasma concentrations of 26 metabolites, including amino acids, acylcarnitines, and phosphatidylcholines, were decreased in mice bearing PTEN-deficient tumors compared with non-tumor-bearing controls and in addition were increased following dosing with class I PI3K inhibitor pictilisib (GDC-0941). These candidate metabolomics biomarkers were evaluated in a phase I dose-escalation clinical trial of pictilisib. Time- and dose-dependent effects were observed in patients for 22 plasma metabolites. The changes exceeded baseline variability, resolved after drug washout, and were recapitulated on continuous dosing. Our study provides a link between modulation of the PI3K pathway and changes in the plasma metabolome and demonstrates that plasma metabolomics is a feasible and promising strategy for biomarker evaluation. Also, our findings provide additional support for an association between insulin resistance, branched-chain amino acids, and related metabolites following PI3K inhibition. Mol Cancer Ther; 15(6); 1412-24. ©2016 AACR. ©2016 American Association for Cancer Research.

  14. Integrated redox proteomics and metabolomics of mitochondria to identify mechanisms of cd toxicity.

    PubMed

    Go, Young-Mi; Roede, James R; Orr, Michael; Liang, Yongliang; Jones, Dean P

    2014-05-01

    Cadmium (Cd) exposure contributes to human diseases affecting liver, kidney, lung, and other organ systems, but mechanisms underlying the pleotropic nature of these toxicities are poorly understood. Cd accumulates in humans from dietary, environmental (including cigarette smoke), and occupational sources, and has a twenty-year biologic half-life. Our previous mouse and cell studies showed that environmental low-dose Cd exposure altered protein redox states resulting in stimulation of inflammatory signaling and disruption of the actin cytoskeleton system, suggesting that Cd could impact multiple mechanisms of disease. In the current study, we investigated the effects of acute Cd exposure on the redox proteome and metabolome of mouse liver mitochondria to gain insight into associated toxicological mechanisms and functions. We analyzed redox states of liver mitochondrial proteins by redox proteomics using isotope coded affinity tag (ICAT) combined mass spectrometry. Redox ICAT identified 2687 cysteine-containing peptides (peptidyl Cys) of which 1667 peptidyl Cys (657 proteins) were detected in both control and Cd-exposed samples. Of these, 46% (1247 peptidyl Cys, 547 proteins) were oxidized by Cd more than 1.5-fold relative to controls. Bioinformatics analysis using MetaCore software showed that Cd affected 86 pathways, including 24 Cys in proteins functioning in branched chain amino acid (BCAA) and 14 Cys in proteins functioning in fatty acid (acylcarnitine/carnitine) metabolism. Consistently, high-resolution metabolomics data showed that Cd treatment altered levels of BCAA and carnitine metabolites. Together, these results show that mitochondrial protein redox and metabolites are targets in Cd-induced hepatotoxicity. The results further indicate that redox proteomics and metabolomics can be used in an integrated systems approach to investigate complex disease mechanisms.

  15. 1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil

    PubMed Central

    Lankadurai, Brian P.; Furdui, Vasile I.; Reiner, Eric J.; Simpson, André J.; Simpson, Myrna J.

    2013-01-01

    1H NMR-based metabolomics was used to measure the response of Eisenia fetida earthworms after exposure to sub-lethal concentrations of perfluorooctane sulfonate (PFOS) in soil. Earthworms were exposed to a range of PFOS concentrations (five, 10, 25, 50, 100 or 150 mg/kg) for two, seven and fourteen days. Earthworm tissues were extracted and analyzed by 1H NMR. Multivariate statistical analysis of the metabolic response of E. fetida to PFOS exposure identified time-dependent responses that were comprised of two separate modes of action: a non-polar narcosis type mechanism after two days of exposure and increased fatty acid oxidation after seven and fourteen days of exposure. Univariate statistical analysis revealed that 2-hexyl-5-ethyl-3-furansulfonate (HEFS), betaine, leucine, arginine, glutamate, maltose and ATP are potential indicators of PFOS exposure, as the concentrations of these metabolites fluctuated significantly. Overall, NMR-based metabolomic analysis suggests elevated fatty acid oxidation, disruption in energy metabolism and biological membrane structure and a possible interruption of ATP synthesis. These conclusions obtained from analysis of the metabolic profile in response to sub-lethal PFOS exposure indicates that NMR-based metabolomics is an excellent discovery tool when the mode of action (MOA) of contaminants is not clearly defined. PMID:24958147

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

    PubMed Central

    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 cell line, RPTEC/TERT1, treated with 10 and 35 μmol·liter−1 of chloroacetaldehyde, a metabolite of the anti-cancer drug ifosfamide. Our study outlines the establishment of an automated and easy to use untargeted metabolomics workflow for HPLC-high resolution mass spectrometry data. Automated data analysis workflows based on open source software (OpenMS, KNIME) enabled a comprehensive and reproducible analysis of the complex and voluminous metabolomics data produced by the profiling approach. Time- and concentration-dependent responses were clearly evident in the metabolomic profiles. To obtain a more comprehensive picture of the mode of action, transcriptomics and proteomics data were also integrated. For toxicity profiling of chloroacetaldehyde, 428 and 317 metabolite features were detectable in positive and negative modes, respectively, after stringent removal of chemical noise and unstable signals. Changes upon treatment were explored using principal component analysis, and statistically significant differences were identified using linear models for microarray assays. The analysis revealed toxic effects only for the treatment with 35 μmol·liter−1 for 3 and 14 days. The most regulated metabolites were glutathione and metabolites related to the oxidative stress response of the cells. These findings are corroborated by proteomics and transcriptomics data, which show, among other things, an activation of the Nrf2 and ATF4 pathways. PMID:26055719

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

    PubMed

    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.

  18. Metabolomic analysis of pancreatic β-cell insulin release in response to glucose.

    PubMed

    Huang, Mei; Joseph, Jamie W

    2012-01-01

    Defining the key metabolic pathways that are important for fuel-regulated insulin secretion is critical to providing a complete picture of how nutrients regulate insulin secretion. We have performed a detailed metabolomics study of the clonal β-cell line 832/13 using a gas chromatography-mass spectrometer (GC-MS) to investigate potential coupling factors that link metabolic pathways to insulin secretion. Mid-polar and polar metabolites, extracted from the 832/13 β-cells, were derivatized and then run on a GC/MS to identify and quantify metabolite concentrations. Three hundred fifty-five out of 527 chromatographic peaks could be identified as metabolites by our metabolomic platform. These identified metabolites allowed us to perform a systematic analysis of key pathways involved in glucose-stimulated insulin secretion (GSIS). Of these metabolites, 41 were consistently identified as biomarker for GSIS by orthogonal partial least-squares (OPLS). Most of the identified metabolites are from common metabolic pathways including glycolytic, sorbitol-aldose reductase pathway, pentose phosphate pathway, and the TCA cycle suggesting these pathways play an important role in GSIS. Lipids and related products were also shown to contribute to the clustering of high glucose sample groups. Amino acids lysine, tyrosine, alanine and serine were upregulated by glucose whereas aspartic acid was downregulated by glucose suggesting these amino acids might play a key role in GSIS. In summary, a coordinated signaling cascade elicited by glucose metabolism in pancreatic β-cells is revealed by our metabolomics platform providing a new conceptual framework for future research and/or drug discovery.

  19. Metabolomic and elemental analysis of camel and bovine urine by GC-MS and ICP-MS.

    PubMed

    Ahamad, Syed Rizwan; Alhaider, Abdul Qader; Raish, Mohammad; Shakeel, Faiyaz

    2017-01-01

    Recent studies from the author's laboratory indicated that camel urine possesses antiplatelet activity and anti-cancer activity which is not present in bovine urine. The objective of this study is to compare the volatile and elemental components of bovine and camel urine using GC-MS and ICP-MS analysis. We are interested to know the component that performs these biological activities. The freeze dried urine was dissolved in dichloromethane and then derivatization process followed by using BSTFA for GC-MS analysis. Thirty different compounds were analyzed by the derivatization process in full scan mode. For ICP-MS analysis twenty eight important elements were analyzed in both bovine and camel urine. The results of GC-MS and ICP-MS analysis showed marked difference in the urinary metabolites. GC-MS evaluation of camel urine finds a lot of products of metabolism like benzene propanoic acid derivatives, fatty acid derivatives, amino acid derivatives, sugars, prostaglandins and canavanine. Several research reports reveal the metabolomics studies on camel urine but none of them completely reported the pharmacology related metabolomics. The present data of GC-MS suggest and support the previous studies and activities related to camel urine.

  20. Probing the metabolic network in bloodstream-form Trypanosoma brucei using untargeted metabolomics with stable isotope labelled glucose.

    PubMed

    Creek, Darren J; Mazet, Muriel; Achcar, Fiona; Anderson, Jana; Kim, Dong-Hyun; Kamour, Ruwida; Morand, Pauline; Millerioux, Yoann; Biran, Marc; Kerkhoven, Eduard J; Chokkathukalam, Achuthanunni; Weidt, Stefan K; Burgess, Karl E V; Breitling, Rainer; Watson, David G; Bringaud, Frédéric; Barrett, Michael P

    2015-03-01

    Metabolomics coupled with heavy-atom isotope-labelled glucose has been used to probe the metabolic pathways active in cultured bloodstream form trypomastigotes of Trypanosoma brucei, a parasite responsible for human African trypanosomiasis. Glucose enters many branches of metabolism beyond glycolysis, which has been widely held to be the sole route of glucose metabolism. Whilst pyruvate is the major end-product of glucose catabolism, its transamination product, alanine, is also produced in significant quantities. The oxidative branch of the pentose phosphate pathway is operative, although the non-oxidative branch is not. Ribose 5-phosphate generated through this pathway distributes widely into nucleotide synthesis and other branches of metabolism. Acetate, derived from glucose, is found associated with a range of acetylated amino acids and, to a lesser extent, fatty acids; while labelled glycerol is found in many glycerophospholipids. Glucose also enters inositol and several sugar nucleotides that serve as precursors to macromolecule biosynthesis. Although a Krebs cycle is not operative, malate, fumarate and succinate, primarily labelled in three carbons, were present, indicating an origin from phosphoenolpyruvate via oxaloacetate. Interestingly, the enzyme responsible for conversion of phosphoenolpyruvate to oxaloacetate, phosphoenolpyruvate carboxykinase, was shown to be essential to the bloodstream form trypanosomes, as demonstrated by the lethal phenotype induced by RNAi-mediated downregulation of its expression. In addition, glucose derivatives enter pyrimidine biosynthesis via oxaloacetate as a precursor to aspartate and orotate.

  1. Dendrobium huoshanense polysaccharide prevents ethanol-induced liver injury in mice by metabolomic analysis.

    PubMed

    Wang, Xiao-Yu; Luo, Jian-Ping; Chen, Rui; Zha, Xue-Qiang; Pan, Li-Hua

    2015-01-01

    The prevalence of alcohol consumption has increased in modern dietary life and alcoholic liver injury can follow. Dendrobium huoshanense polysaccharide (DHP) is a homogeneous polysaccharide isolated from Dendrobium huoshanense, which possesses hepatoprotection function. In this study, we investigated the metabolic profiles of serum and liver tissues extracts from control, ethanol-treated and DHP\\ethanol-treated mice using a UHPLC/LTQ Orbitrap XL MS-based metabolomics approach. Our results indicated that DHP alleviated early steatosis and inflammation in liver histology and the metabolomic analysis of serum and hepatic tissue revealed that first, ethanol treatment mainly altered phosphatidylcholines (PCs) including PC (13:0) and phosphocholine, arachidonic acid metabolites including 20-ethyl PGF2α and amino acids including L-Proline; Second, DHP supplementation ameliorated the altered metabolic levels particularly involved in phosphocholine and L-Proline. These data suggested that DHP might restore the perturbed metabolism pathways by ethanol exposure to prevent the progression of alcoholic liver injury. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants.

    PubMed

    Hagel, Jillian M; Mandal, Rupasri; Han, Beomsoo; Han, Jun; Dinsmore, Donald R; Borchers, Christoph H; Wishart, David S; Facchini, Peter J

    2015-09-15

    Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional (1)H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were

  3. Growth of Malignant Non-CNS Tumors Alters Brain Metabolome

    PubMed Central

    Kovalchuk, Anna; Nersisyan, Lilit; Mandal, Rupasri; Wishart, David; Mancini, Maria; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

    2018-01-01

    Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon. PMID:29515623

  4. Second Class Resolver: a retrospective analysis.

    PubMed

    D'Attilio, M; Rodolfino, D; Filippakos, A; Saccucci, M; Festa, F; Tripodi, D

    2014-03-01

    To evaluate the use of Second Class Resolver (SCR), a new fixed orthopaedic appliance, for the treatment of skeletal Class II malocclusion in growing subjects. Design Retrospective analysis. Forty subjects were treated with Second Class Resolver (SCR). The mean age was 8 years at the beginning of treatment and 10 years at the end of treatment. Digital cephalometric superimpositions on lateral radiographs taken at start and end of treatment were assessed. The cephalometric values were statistically analysed. Cephalometric analysis of changes during treatment shows reduction of ANB angle (mean 2°); reduction of Witts Index (mean 3 mm); reduction of Maxillo-Mandibular angle (MM) (mean 1°); reduction of SNA (angle mean 3°); reduction of gonial angle (mean 1.8°); increase of the mandibular branch length (mean 5 mm); increase of mandibular body (mean 2.9°). The Second Class Resolver can be beneficially used for the treatment of Class II malocclusion.

  5. Metabolic Disturbances in Adult-Onset Still's Disease Evaluated Using Liquid Chromatography/Mass Spectrometry-Based Metabolomic Analysis.

    PubMed

    Chen, Der-Yuan; Chen, Yi-Ming; Chien, Han-Ju; Lin, Chi-Chen; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting; Lai, Chien-Chen

    2016-01-01

    Liquid chromatography/mass spectrometry (LC/MS)-based comprehensive analysis of metabolic profiles with metabolomics approach has potential diagnostic and predictive implications. However, no metabolomics data have been reported in adult-onset Still's disease (AOSD). This study investigated the metabolomic profiles in AOSD patients and examined their association with clinical characteristics and disease outcome. Serum metabolite profiles were determined on 32 AOSD patients and 30 healthy controls (HC) using ultra-performance liquid chromatography (UPLC)/MS analysis, and the differentially expressed metabolites were quantified using multiple reactions monitoring (MRM)/MS analysis in 44 patients and 42 HC. Pure standards were utilized to confirm the presence of the differentially expressed metabolites. Eighteen differentially expressed metabolites were identified in AOSD patents using LC/MS-based analysis, of which 13 metabolites were validated by MRM/MS analysis. Among them, serum levels of lysoPC(18:2), urocanic acid and indole were significantly lower, and L-phenylalanine levels were significantly higher in AOSD patients compared with HC. Moreover, serum levels of lysoPC(18:2), PhePhe, uridine, taurine, L-threonine, and (R)-3-Hydroxy-hexadecanoic acid were significantly correlated with disease activity scores (all p<0.05) in AOSD patients. A different clustering of metabolites was associated with a different disease outcome, with significantly lower levels of isovalerylsarcosine observed in patients with chronic articular pattern (median, 77.0AU/ml) compared with monocyclic (341.5AU/ml, p<0.01) or polycyclic systemic pattern (168.0AU/ml, p<0.05). Thirteen differentially expressed metabolites identified and validated in AOSD patients were shown to be involved in five metabolic pathways. Significant associations of metabolic profiles with disease activity and outcome of AOSD suggest their involvement in AOSD pathogenesis.

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

    PubMed Central

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

    2017-01-01

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

  7. Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis.

    PubMed

    Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

    2016-12-13

    In untargeted metabolomics analysis, several factors (e.g., unwanted experimental &biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data.

  8. Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis

    PubMed Central

    Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

    2016-01-01

    In untargeted metabolomics analysis, several factors (e.g., unwanted experimental & biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data. PMID:27958387

  9. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods

    PubMed Central

    Boaz, Segal M.; Champagne, Cory D.; Fowler, Melinda A.; Houser, Dorian H.; Crocker, Daniel E.

    2011-01-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to seven weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. PMID:21983145

  10. Resolving mass spectral overlaps in atom probe tomography by isotopic substitutions - case of TiSi15N.

    PubMed

    Engberg, David L J; Johnson, Lars J S; Jensen, Jens; Thuvander, Mattias; Hultman, Lars

    2018-01-01

    Mass spectral overlaps in atom probe tomography (APT) analyses of complex compounds typically limit the identification of elements and microstructural analysis of a material. This study concerns the TiSiN system, chosen because of severe mass-to-charge-state ratio overlaps of the 14 N + and 28 Si 2+ peaks as well as the 14 N 2 + and 28 Si + peaks. By substituting 14 N with 15 N, mass spectrum peaks generated by ions composed of one or more N atoms will be shifted toward higher mass-to-charge-state ratios, thereby enabling the separation of N from the predominant Si isotope. We thus resolve thermodynamically driven Si segregation on the nanometer scale in cubic phase Ti 1- x Si x 15 N thin films for Si contents 0.08 ≤ x ≤ 0.19 by APT, as corroborated by transmission electron microscopy. The APT analysis yields a composition determination that is in good agreement with energy dispersive X-ray spectroscopy and elastic recoil detection analyses. Additionally, a method for determining good voxel sizes for visualizing small-scale fluctuations is presented and demonstrated for the TiSiN system. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2016-04-01

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

  12. Full-Spectrum-Analysis Isotope ID

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mitchell, Dean J.; Harding, Lee; Thoreson, Gregory G.

    2017-06-28

    FSAIsotopeID analyzes gamma ray spectra to identify radioactive isotopes (radionuclides). The algorithm fits the entire spectrum with combinations of pre-computed templates for a comprehensive set of radionuclides with varying thicknesses and compositions of shielding materials. The isotope identification algorithm is suitable for the analysis of spectra collected by gamma-ray sensors ranging from medium-resolution detectors, such a NaI, to high-resolution detectors, such as HPGe. In addition to analyzing static measurements, the isotope identification algorithm is applied for the radiation search applications. The search subroutine maintains a running background spectrum that is passed to the isotope identification algorithm, and it also selectsmore » temporal integration periods that optimize the responsiveness and sensitivity. Gain stabilization is supported for both types of applications.« less

  13. Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.

    PubMed

    Wei, Runmin; Wang, Jingye; Su, Mingming; Jia, Erik; Chen, Shaoqiu; Chen, Tianlu; Ni, Yan

    2018-01-12

    Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).

  14. Mass spectrometry as a quantitative tool in plant metabolomics

    PubMed Central

    Jorge, Tiago F.; Mata, Ana T.

    2016-01-01

    Metabolomics is a research field used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physico-chemical properties, and therefore powerful analytical tools are required for the separation, characterization and quantification of this vast compound diversity present in plant matrices. In this review, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and important criteria for the development and validation of MS-based analytical methods provided. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644967

  15. ENVIRONMENTAL ISOTOPES FOR RESOLUTION OF HYDROLOGY PROBLEMS

    EPA Science Inventory

    The use of environmental isotopes as tracers in the hydrosphere is increasing as analytical instrumentation improves and more applications are discovered. There exists still misconceptions on the role of isotopes in resolving hydrology problems. Naturally occurring isotopes in th...

  16. Blood transcriptomics and metabolomics for personalized medicine.

    PubMed

    Li, Shuzhao; Todor, Andrei; Luo, Ruiyan

    2016-01-01

    Molecular analysis of blood samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology. Recent developments have opened new opportunities to utilize transcriptomics and metabolomics for personalized and precision medicine. Efforts from human immunology have infused into this area exquisite characterizations of subpopulations of blood cells. It is now possible to infer from blood transcriptomics, with fine accuracy, the contribution of immune activation and of cell subpopulations. In parallel, high-resolution mass spectrometry has brought revolutionary analytical capability, detecting > 10,000 metabolites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus, the re-examination of blood chemicals by metabolomics is in order. Transcriptomics and metabolomics can be integrated to provide a more comprehensive understanding of the human biological states. We will review these new data and methods and discuss how they can contribute to personalized medicine.

  17. [Metabolomics research of medicinal plants].

    PubMed

    Duan, Li-Xin; Dai, Yun-Tao; Sun, Chao; Chen, Shi-Lin

    2016-11-01

    Metabolomics is the comprehensively study of chemical processes involving small molecule metabolites. It is an important part of systems biology, and is widely applied in complex traditional Chinese medicine(TCM)system. Metabolites biosynthesized by medicinal plants are the effective basis for TCM. Metabolomics studies of medicinal plants will usher in a new period of vigorous development with the implementation of Herb Genome Program and the development of TCM synthetic biology. This manuscript introduces the recent research progresses of metabolomics technology and the main research contents of metabolomics studies for medicinal plants, including identification and quality evaluation for medicinal plants, cultivars breeding, stress resistance, metabolic pathways, metabolic network, metabolic engineering and synthetic biology researches. The integration of genomics, transcriptomics and metabolomics approaches will finally lay foundation for breeding of medicinal plants, R&D, quality and safety evaluation of innovative drug. Copyright© by the Chinese Pharmaceutical Association.

  18. Applications of stable isotope analysis in mammalian ecology.

    PubMed

    Walter, W David; Kurle, Carolyn M; Hopkins, John B

    2014-01-01

    In this editorial, we provide a brief introduction and summarize the 10 research articles included in this Special Issue on Applications of stable isotope analysis in mammalian ecology. The first three articles report correction and discrimination factors that can be used to more accurately estimate the diets of extinct and extant mammals using stable isotope analysis. The remaining seven applied research articles use stable isotope analysis to address a variety of wildlife conservation and management questions from the oceans to the mountains.

  19. Metabolomics and malaria biology

    PubMed Central

    Lakshmanan, Viswanathan; Rhee, Kyu Y.; Daily, Johanna P.

    2010-01-01

    Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research. PMID:20970461

  20. Global open data management in metabolomics.

    PubMed

    Haug, Kenneth; Salek, Reza M; Steinbeck, Christoph

    2017-02-01

    Chemical Biology employs chemical synthesis, analytical chemistry and other tools to study biological systems. Recent advances in both molecular biology such as next generation sequencing (NGS) have led to unprecedented insights towards the evolution of organisms' biochemical repertoires. Because of the specific data sharing culture in Genomics, genomes from all kingdoms of life become readily available for further analysis by other researchers. While the genome expresses the potential of an organism to adapt to external influences, the Metabolome presents a molecular phenotype that allows us to asses the external influences under which an organism exists and develops in a dynamic way. Steady advancements in instrumentation towards high-throughput and highresolution methods have led to a revival of analytical chemistry methods for the measurement and analysis of the metabolome of organisms. This steady growth of metabolomics as a field is leading to a similar accumulation of big data across laboratories worldwide as can be observed in all of the other omics areas. This calls for the development of methods and technologies for handling and dealing with such large datasets, for efficiently distributing them and for enabling re-analysis. Here we describe the recently emerging ecosystem of global open-access databases and data exchange efforts between them, as well as the foundations and obstacles that enable or prevent the data sharing and reanalysis of this data. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Metabolomic analysis for the protective effects of mangiferin on sepsis-induced lung injury in mice.

    PubMed

    Wang, Yilin; Liu, Yang; Cao, Qiqi; Shi, Xuan; Lu, Hongtao; Gao, Songyan; Yang, Rui

    2018-06-01

    This study aimed to investigate the efficacy of mangiferin, including its known antioxidant and anti-inflammatory effects on sepsis-induced lung injury induced by a classical cecal ligation and puncture (CLP) models in mouse using a metabolomics approach. A total of 24 mice were randomly divided into four groups: the sham group was given saline before sham operation. The CLP group received the CLP operation only. HMF and LMF groups were given mangiferin treatment of high dose and low dose of mangiferin, respectively, before the CLP operation. One week after treatment, the mice were sacrificed and their lungs were collected for metabolomics analysis. We developed ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry to perform lung metabolic profiling analysis. With the methods of principal component analysis and partial least squares discriminant analysis, 58 potential metabolites associated with amino acid metabolism, purine metabolism, lipid metabolism and energy regulation were observed to be increased or reduced in HMF and LMF groups compared with the CLP group. Conclusively, our results suggest that mangiferin plays a protective role in the moderation of sepsis-induced lung injury through reducing oxidative stress, regulating lipid metabolism and energy biosynthesis. Copyright © 2018 John Wiley & Sons, Ltd.

  2. Application of a Smartphone Metabolomics Platform to the Authentication of Schisandra sinensis.

    PubMed

    Kwon, Hyuk Nam; Phan, Hong-Duc; Xu, Wen Jun; Ko, Yoon-Joo; Park, Sunghyouk

    2016-05-01

    Herbal medicines have been used for a long time all around the world. Since the quality of herbal preparations depends on the source of herbal materials, there has been a strong need to develop methods to correctly identify the origin of materials. To develop a smartphone metabolomics platform as a simpler and low-cost alternative for the identification of herbal material source. Schisandra sinensis extracts from Korea and China were prepared. The visible spectra of all samples were measured by a smartphone spectrometer platform. This platform included all the necessary measures built-in for the metabolomics research: data acquisition, processing, chemometric analysis and visualisation of the results. The result of the smartphone metabolomics platform was compared to that of NMR-based metabolomics, suggesting the feasibility of smartphone platform in metabolomics research. The smartphone metabolomics platform gave similar results to the NMR method, showing good separation between Korean and Chinese materials and correct predictability for all test samples. With its accuracy and advantages of affordability, user-friendliness, and portability, the smartphone metabolomics platform could be applied to the authentication of other medicinal plants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  3. Amniotic Fluid Metabolomic Analysis in Spontaneous Preterm Birth

    PubMed Central

    Jones, Janice; Gunst, Phillip R.; Kacerovsky, Marian; Fortunato, Stephen J.; Saade, George R.; Basraon, Sanmaan

    2014-01-01

    Objective: To identify metabolic changes associated with early spontaneous preterm birth (PTB; <34 weeks) and term births, using high-throughput metabolomics of amniotic fluid (AF) in African American population. Method: In this study, AF samples retrieved from spontaneous PTB (<34 weeks [n = 25]) and normal term birth (n = 25) by transvaginal amniocentesis at the time of labor prior to delivery were subjected to metabolomics analysis. Equal volumes of samples were subjected to a standard solvent extraction method and analyzed using gas chromatography/mass spectrometry (MS) and liquid chromatography/MS/MS. Biochemicals were identified through matching of ion features to a library of biochemical standards. After log transformation and imputation of minimum observed values for each compound, t test, correlation tests, and false discovery rate corrections were used to identify differentially regulated metabolites. Data were controlled for clinical/demographic variables and medication during pregnancy. Results: Of 348 metabolites measured in AF samples, 121 metabolites had a gestational age effect and 116 differed significantly between PTB and term births. A majority of significantly altered metabolites could be classified into 3 categories, namely, (1) liver function, (2) fatty acid and coenzyme A (CoA) metabolism, and (3) histidine metabolism. The signature of altered liver function was apparent in many cytochrome P450-related pathways including bile acids, steroids, xanthines, heme, and phase II detoxification of xenobiotics with the largest fold change seen with pantothenol, a CoA synthesis inhibitor that was 8-fold more abundant in PTB. Conclusion: Global metabolic profiling of AF revealed alteration in hepatic metabolites involving xenobiotic detoxification and CoA metabolism in PTB. Maternal and/or fetal hepatic function differences may be developmentally related and its contribution PTB as a cause or effect of PTB is still unclear. PMID:24440995

  4. Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

    PubMed

    Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

    2016-10-28

    Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

  5. Food metabolomics: from farm to human.

    PubMed

    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.

  6. An introduction to metabolomics and its potential application in veterinary science.

    PubMed

    Jones, Oliver A H; Cheung, Victoria L

    2007-10-01

    Metabolomics has been found to be applicable to a wide range of fields, including the study of gene function, toxicology, plant sciences, environmental analysis, clinical diagnostics, nutrition, and the discrimination of organism genotypes. This approach combines high-throughput sample analysis with computer-assisted multivariate pattern-recognition techniques. It is increasingly being deployed in toxico- and pharmacokinetic studies in the pharmaceutical industry, especially during the safety assessment of candidate drugs in human medicine. However, despite the potential of this technique to reduce both costs and the numbers of animals used for research, examples of the application of metabolomics in veterinary research are, thus far, rare. Here we give an introduction to metabolomics and discuss its potential in the field of veterinary science.

  7. Metabolomics analysis reveals 6-benzylaminopurine as a stimulator for improving lipid and DHA accumulation of Aurantiochytriumsp.

    PubMed

    Yu, Xin-Jun; Sun, Jie; Zheng, Jian-Yong; Sun, Ya-Qi; Wang, Zhao

    2016-04-01

    Phytohormones are chemical messengers that have a positive effect on biodiesel production of microalgae at low concentrations. However, the effect of phytohormone 6-benzylaminopurine on lipid and docosahexaenoic acid (DHA) production in marine DHA-producer Aurantiochytrium has never been reported. In this study, a GC-MS-based metabolomics method combined with a multivariate analysis is applied to reveal the metabolic mechanism of 6-benzylaminopurine enhancing production of lipid and DHA in Aurantiochytrium sp.YLH70. In total, 71 metabolites were identified by GC-MS. The PCA model revealed that 76.9% of metabolite variation was related to 6-benzylaminopurine treatment, and overall metabolomics profiles between the 6-benzylaminopurine and control groups were clearly discriminated. Forty-six metabolites identified by the PLS-DA model were responsible for responding to 6-benzylaminopurine. Metabolic analysis showed that 6-benzylaminopurine could accelerate the rate of utilization of glucose in Aurantiochytrium sp. YLH70, and the metabolic flux from glycolysis, TCA cycle and mevalonate pathway to fatty acids biosynthesis was promoted. Moreover, the anti-stress mechanism in Aurantiochytrium sp.YLH70 might be induced by 6-benzylaminopurine. Metabolomics is a suitable tool to discover the metabolic mechanism for improving lipid and DHA accumulation in a microorganism. 6-benzylaminopurine has the potential to stimulate lipid and DHA production of Aurantiochytrium sp.YLH70 for industrial purposes. © 2015 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

  8. Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

    PubMed Central

    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

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

    EPA Science Inventory

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

  10. Metabolomic analysis can detect the composition of pasta enriched with fibre after cooking.

    PubMed

    Beleggia, Romina; Menga, Valeria; Platani, Cristiano; Nigro, Franca; Fragasso, Mariagiovanna; Fares, Clara

    2016-07-01

    Several studies have demonstrated that metabolomics has a definite place in food quality, nutritional value, and safety issues. The aim of the present study was to determine and compare the metabolites in different pasta samples with fibre, and to investigate the modifications induced in these different kinds of pasta during cooking, using a gas chromatography-mass spectrometry-based metabolomics approach. Differences were seen for some of the amino acids, which were absent in control pasta, while were present both in the commercially available high-fibre pasta (samples A-C) and the enriched pasta (samples D-F). The highest content in reducing sugars was observed in enriched samples in comparison with high-fibre pasta. The presence of stigmasterol in samples enriched with wheat bran was relevant. Cooking decreased all of the metabolites: the high-fibre pasta (A-C) and Control showed losses of amino acids and tocopherols, while for sugars and organic acids, the decrease depended on the pasta sample. The enriched pasta samples (D-F) showed the same decreases with the exception of phytosterols, and in pasta with barley the decrease of saturated fatty acids was not significant as for tocopherols in pasta with oat. Principal component analysis of the metabolites and the pasta discrimination was effective in differentiating the enriched pasta from the commercial pasta, both uncooked and cooked. The study has established that such metabolomic analyses provide useful tools in the evaluation of the changes in nutritional compounds in high-fibre and enriched pasta, both before and after cooking. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  11. Measurement of isotope abundance variations in nature by gravimetric spiking isotope dilution analysis (GS-IDA).

    PubMed

    Chew, Gina; Walczyk, Thomas

    2013-04-02

    Subtle variations in the isotopic composition of elements carry unique information about physical and chemical processes in nature and are now exploited widely in diverse areas of research. Reliable measurement of natural isotope abundance variations is among the biggest challenges in inorganic mass spectrometry as they are highly sensitive to methodological bias. For decades, double spiking of the sample with a mix of two stable isotopes has been considered the reference technique for measuring such variations both by multicollector-inductively coupled plasma mass spectrometry (MC-ICPMS) and multicollector-thermal ionization mass spectrometry (MC-TIMS). However, this technique can only be applied to elements having at least four stable isotopes. Here we present a novel approach that requires measurement of three isotope signals only and which is more robust than the conventional double spiking technique. This became possible by gravimetric mixing of the sample with an isotopic spike in different proportions and by applying principles of isotope dilution for data analysis (GS-IDA). The potential and principle use of the technique is demonstrated for Mg in human urine using MC-TIMS for isotopic analysis. Mg is an element inaccessible to double spiking methods as it consists of three stable isotopes only and shows great potential for metabolically induced isotope effects waiting to be explored.

  12. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

    DOE PAGES

    Benton, H. Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G.; ...

    2014-12-12

    An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometrymore » data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.« less

  13. Advances in high-resolution mass spectrometry based on metabolomics studies for food--a review.

    PubMed

    Rubert, Josep; Zachariasova, Milena; Hajslova, Jana

    2015-01-01

    Food authenticity becomes a necessity for global food policies, since food placed in the market without fail has to be authentic. It has always been a challenge, since in the past minor components, called also markers, have been mainly monitored by chromatographic methods in order to authenticate the food. Nevertheless, nowadays, advanced analytical methods have allowed food fingerprints to be achieved. At the same time they have been also combined with chemometrics, which uses statistical methods in order to verify food and to provide maximum information by analysing chemical data. These sophisticated methods based on different separation techniques or stand alone have been recently coupled to high-resolution mass spectrometry (HRMS) in order to verify the authenticity of food. The new generation of HRMS detectors have experienced significant advances in resolving power, sensitivity, robustness, extended dynamic range, easier mass calibration and tandem mass capabilities, making HRMS more attractive and useful to the food metabolomics community, therefore becoming a reliable tool for food authenticity. The purpose of this review is to summarise and describe the most recent metabolomics approaches in the area of food metabolomics, and to discuss the strengths and drawbacks of the HRMS analytical platforms combined with chemometrics.

  14. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

    Metabolomics is becoming a well-established tool for studying how organisms, such as fish, respond to various stressors. For example, the literature is rich with laboratory studies involving analysis of samples from organisms exposed to individual chemical toxicants. These studie...

  15. Metabolomics study of human urinary metabolome modifications after intake of almond (Prunus dulcis (Mill.) D.A. Webb) skin polyphenols.

    PubMed

    Llorach, Rafael; Garrido, Ignacio; Monagas, Maria; Urpi-Sarda, Mireia; Tulipani, Sara; Bartolome, Begona; Andres-Lacueva, Cristina

    2010-11-05

    Almond, as a part of the nut family, is an important source of biological compounds, and specifically, almond skins have been considered an important source of polyphenols, including flavan-3-ols and flavonols. Polyphenol metabolism may produce several classes of metabolites that could often be more biologically active than their dietary precursor and could also become a robust new biomarker of almond polyphenol intake. In order to study urinary metabolome modifications during the 24 h after a single dose of almond skin extract, 24 volunteers (n = 24), who followed a polyphenol-free diet for 48 h before and during the study, ingested a dietary supplement of almond skin phenolic compounds (n = 12) or a placebo (n = 12). Urine samples were collected before ((-2)-0 h) and after (0-2 h, 2-6 h, 6-10 h, and 10-24 h) the intake and were analyzed by liquid chromatography-mass spectrometry (LC-q-TOF) and multivariate statistical analysis (principal component analysis (PCA) and orthogonal projection to latent structures (OPLS)). Putative identification of relevant biomarkers revealed a total of 34 metabolites associated with the single dose of almond extract, including host and, in particular, microbiota metabolites. As far as we know, this is the first time that conjugates of hydroxyphenylvaleric, hydroxyphenylpropionic, and hydroxyphenylacetic acids have been identified in human samples after the consumption of flavan-3-ols through a metabolomic approach. The results showed that this non-targeted approach could provide new intake biomarkers, contributing to the development of the food metabolome as an important part of the human urinary metabolome.

  16. Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

    PubMed

    Caesar, Lindsay K; Kvalheim, Olav M; Cech, Nadja B

    2018-08-27

    Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA failed to cluster replicates in the data sets. To identify contaminant peaks, we developed a filtering process that evaluated the relative peak area variance of each variable within triplicate injections. These interferent peaks were found across all samples, but did not show consistent peak area from injection to injection, even when evaluating the same chemical sample. This filtering process identified 128 ions that appear to originate from the UPLC-MS system. Data sets collected for a high number of pools with comparatively simple chemical composition were highly influenced by these chemical interferents, as were samples that were analyzed at a low concentration. When chemical interferent masses were removed, technical replicates clustered in

  17. Clinical Metabolomics and Glaucoma.

    PubMed

    Barbosa-Breda, João; Himmelreich, Uwe; Ghesquière, Bart; Rocha-Sousa, Amândio; Stalmans, Ingeborg

    2018-01-01

    Glaucoma is one of the leading causes of irreversible blindness worldwide. However, there are no biomarkers that accurately help clinicians perform an early diagnosis or detect patients with a high risk of progression. Metabolomics is the study of all metabolites in an organism, and it has the potential to provide a biomarker. This review summarizes the findings of metabolomics in glaucoma patients and explains why this field is promising for new research. We identified published studies that focused on metabolomics and ophthalmology. After providing an overview of metabolomics in ophthalmology, we focused on human glaucoma studies. Five studies have been conducted in glaucoma patients and all compared patients to healthy controls. Using mass spectrometry, significant differences were found in blood plasma in the metabolic pathways that involve palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors. For nuclear magnetic resonance spectroscopy, a high glutamine-glutamate/creatine ratio was found in the vitreous and lateral geniculate body; no differences were detected in the optic radiations, and a lower N-acetylaspartate/choline ratio was observed in the geniculocalcarine and striate areas. Metabolomics can move glaucoma care towards a personalized approach and provide new knowledge concerning the pathophysiology of glaucoma, which can lead to new therapeutic options. © 2017 S. Karger AG, Basel.

  18. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods.

    PubMed

    Boaz, Segal M; Champagne, Cory D; Fowler, Melinda A; Houser, Dorian H; Crocker, Daniel E

    2012-02-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to 7 weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. Copyright © 2011 Elsevier Inc. All rights reserved.

  19. Review of mass spectrometry-based metabolomics in cancer research

    PubMed Central

    Liesenfeld, David B.; Habermann, Nina; Owen, Robert W.; Scalbert, Augustin; Ulrich, Cornelia M.

    2014-01-01

    Metabolomics, the systematic investigation of all metabolites present within a biological system, is used in biomarker development for many human diseases, including cancer. In this review we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including <100 patients. Standardization is required especially concerning sample preparation and data analysis. In a second part of this review, we reconstructed a metabolic network of cancer patients by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed. PMID:24096148

  20. Metabolomic profiling in perinatal asphyxia: a promising new field.

    PubMed

    Denihan, Niamh M; Boylan, Geraldine B; Murray, Deirdre M

    2015-01-01

    Metabolomics, the latest "omic" technology, is defined as the comprehensive study of all low molecular weight biochemicals, "metabolites" present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field.

  1. Metabolomic Profiling in Perinatal Asphyxia: A Promising New Field

    PubMed Central

    Denihan, Niamh M.; Boylan, Geraldine B.; Murray, Deirdre M.

    2015-01-01

    Metabolomics, the latest “omic” technology, is defined as the comprehensive study of all low molecular weight biochemicals, “metabolites” present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field. PMID:25802843

  2. Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

    PubMed

    Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

    2016-06-01

    Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

  3. Metabolomic Analysis of Overactive Bladder in Male Patients: Identification of Potential Metabolite Biomarkers.

    PubMed

    Shimura, Hiroshi; Mitsui, Takahiko; Kira, Satoru; Ihara, Tatsuya; Sawada, Norifumi; Nakagomi, Hiroshi; Miyamoto, Tatsuya; Tsuchiya, Sachiko; Kanda, Mie; Takeda, Masayuki

    2018-05-09

    To identify metabolites that are associated with an overactive bladder (OAB) using metabolomics. A total of 58 male patients without apparent neurologic disease completed 24-hour bladder diaries of their micturition behavior and International Prostate Symptom Score (IPSS) for the assessment of micturition behavior and lower urinary tract symptoms. Urgency was defined as an IPSS urgency score of ≥2 (OAB group), and patients with IPSS urgency scores of ≤1 belonged to the control group. A comprehensive study of plasma metabolites was also conducted using capillary electrophoresis time-of-flight mass spectrometry. Metabolite levels were compared between the control and OAB groups using the Mann-Whitney U test. Potential metabolite biomarkers were selected using multivariate logistic regression analysis. Of the 58 subjects, the control and OAB groups consisted of 32 and 26 male patients, respectively. Nocturnal urinary volume, 24-hour micturition frequency, nocturnal micturition frequency, and the nocturia index were significantly higher in the OAB group. Metabolomic analysis revealed 60 metabolites in the subjects' plasma. The levels of 11 metabolites differed between the control and OAB groups. Multivariate analysis showed that an increased glutamate level and reduced arginine, glutamine, and inosine monophosphate levels are significantly associated with OAB in male patients. Reduced levels of asparagine and hydroxyproline could also be associated with OAB. Urgency is associated with abnormal metabolism. Analyses of amino acid profiles might aid the search for new treatment targets for OAB. Copyright © 2018 Elsevier Inc. All rights reserved.

  4. MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

    PubMed Central

    Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

    2014-01-01

    Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a

  5. Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data

    PubMed Central

    Treutler, Hendrik; Neumann, Steffen

    2016-01-01

    Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92% of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0. PMID:27775610

  6. Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers.

    PubMed

    Carlson, Alyssa K; Rawle, Rachel A; Adams, Erik; Greenwood, Mark C; Bothner, Brian; June, Ronald K

    2018-05-05

    Osteoarthritis affects over 250 million individuals worldwide. Currently, there are no options for early diagnosis of osteoarthritis, demonstrating the need for biomarker discovery. To find biomarkers of osteoarthritis in human synovial fluid, we used high performance liquid-chromatography mass spectrometry for global metabolomic profiling. Metabolites were extracted from human osteoarthritic (n = 5), rheumatoid arthritic (n = 3), and healthy (n = 5) synovial fluid, and a total of 1233 metabolites were detected. Principal components analysis clearly distinguished the metabolomic profiles of diseased from healthy synovial fluid. Synovial fluid from rheumatoid arthritis patients contained expected metabolites consistent with the inflammatory nature of the disease. Similarly, unsupervised clustering analysis found that each disease state was associated with distinct metabolomic profiles and clusters of co-regulated metabolites. For osteoarthritis, co-regulated metabolites that were upregulated compared to healthy synovial fluid mapped to known disease processes including chondroitin sulfate degradation, arginine and proline metabolism, and nitric oxide metabolism. We utilized receiver operating characteristic analysis to determine the diagnostic value of each metabolite and identified 35 metabolites as potential biomarkers of osteoarthritis, with an area under the receiver operating characteristic curve >0.9. These metabolites included phosphatidylcholine, lysophosphatidylcholine, ceramides, myristate derivatives, and carnitine derivatives. This pilot study provides strong justification for a larger cohort-based study of human osteoarthritic synovial fluid using global metabolomics. The significance of these data is the demonstration that metabolomic profiling of synovial fluid can identify relevant biomarkers of joint disease. Copyright © 2018 Elsevier Inc. All rights reserved.

  7. Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

    PubMed

    Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

    2016-08-12

    Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. COnsortium of METabolomics Studies (COMETS)

    Cancer.gov

    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.

  9. Combined metabolome and proteome analysis of the mantle tissue from Pacific oyster Crassostrea gigas exposed to elevated pCO2.

    PubMed

    Wei, Lei; Wang, Qing; Ning, Xuanxuan; Mu, Changkao; Wang, Chunlin; Cao, Ruiwen; Wu, Huifeng; Cong, Ming; Li, Fei; Ji, Chenglong; Zhao, Jianmin

    2015-03-01

    Ocean acidification (OA) has been found to affect an array of normal physiological processes in mollusks, especially posing a significant threat to the fabrication process of mollusk shell. In the current study, the impact of exposure to elevated pCO2 condition was investigated in mantle tissue of Crassostrea gigas by an integrated metabolomic and proteomic approach. Analysis of metabolome and proteome revealed that elevated pCO2 could affect energy metabolism in oyster C. gigas, marked by differentially altered ATP, succinate, MDH, PEPCK and ALDH levels. Moreover, the up-regulated calponin-2, tropomyosins and myosin light chains indicated that elevated pCO2 probably caused disturbances in cytoskeleton structure in mantle tissue of oyster C. gigas. This work demonstrated that a combination of proteomics and metabolomics could provide important insights into the effects of OA at molecular levels. Copyright © 2014 Elsevier Inc. All rights reserved.

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

    PubMed Central

    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

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

    PubMed

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

    2017-04-01

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

  12. Targeted metabolomic profiling in rat tissues reveals sex differences.

    PubMed

    Ruoppolo, Margherita; Caterino, Marianna; Albano, Lucia; Pecce, Rita; Di Girolamo, Maria Grazia; Crisci, Daniela; Costanzo, Michele; Milella, Luigi; Franconi, Flavia; Campesi, Ilaria

    2018-03-16

    Sex differences affect several diseases and are organ-and parameter-specific. In humans and animals, sex differences also influence the metabolism and homeostasis of amino acids and fatty acids, which are linked to the onset of diseases. Thus, the use of targeted metabolite profiles in tissues represents a powerful approach to examine the intermediary metabolism and evidence for any sex differences. To clarify the sex-specific activities of liver, heart and kidney tissues, we used targeted metabolomics, linear discriminant analysis (LDA), principal component analysis (PCA), cluster analysis and linear correlation models to evaluate sex and organ-specific differences in amino acids, free carnitine and acylcarnitine levels in male and female Sprague-Dawley rats. Several intra-sex differences affect tissues, indicating that metabolite profiles in rat hearts, livers and kidneys are organ-dependent. Amino acids and carnitine levels in rat hearts, livers and kidneys are affected by sex: male and female hearts show the greatest sexual dimorphism, both qualitatively and quantitatively. Finally, multivariate analysis confirmed the influence of sex on the metabolomics profiling. Our data demonstrate that the metabolomics approach together with a multivariate approach can capture the dynamics of physiological and pathological states, which are essential for explaining the basis of the sex differences observed in physiological and pathological conditions.

  13. Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

    NASA Astrophysics Data System (ADS)

    Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

    2016-12-01

    The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34-80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics.

  14. Isotope Tales: Remaining Problems, Unsolvable Questions, and Gentle Successes

    NASA Astrophysics Data System (ADS)

    fogel, marilyn; bradley, christina; newsome, seth; filipp, fabian

    2014-05-01

    Earth's biomes function and adapt today as climate changes and ecosystems and the organisms within them adapt. Stable isotope biogeochemistry has had a major influence in understanding climate perturbations and continues to be an active area of research on many fronts. Banking on the success of compound specific stable isotope analyses of amino acids, nitrogen, carbon, and hydrogen isotopes continue to reveal subtle shifts in oceanic food webs and metabolic changes in microbes, plants, and animals. A biochemical understanding of exactly how organisms process and partition stable isotopes during metabolism remains unsolved, but is required if this field is to move beyond description to quantitation. Although the patterns of carbon and nitrogen isotopes are fairly well established in the common amino acids, we need to consider specifics: How do shifting metabolic pathways (metabolomics) influence the outcome of stable isotope partitioning? What influence does the gut microflora in animals have on isotopic labeling? What are the intramolecular isotope patterns of common amino acids and what do they tell us? What can be learned with other isotope systems, such as hydrogen? Results and ideas of how to move forward in this field will be presented starting at the molecular level and ending with ecosystems.

  15. Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of “Unknown Function”

    PubMed Central

    Quanbeck, Stephanie M.; Brachova, Libuse; Campbell, Alexis A.; Guan, Xin; Perera, Ann; He, Kun; Rhee, Seung Y.; Bais, Preeti; Dickerson, Julie A.; Dixon, Philip; Wohlgemuth, Gert; Fiehn, Oliver; Barkan, Lenore; Lange, Iris; Lange, B. Markus; Lee, Insuk; Cortes, Diego; Salazar, Carolina; Shuman, Joel; Shulaev, Vladimir; Huhman, David V.; Sumner, Lloyd W.; Roth, Mary R.; Welti, Ruth; Ilarslan, Hilal; Wurtele, Eve S.; Nikolau, Basil J.

    2012-01-01

    Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs. PMID:22645570

  16. Grade-dependent metabolic reprogramming in kidney cancer revealed by combined proteomics and metabolomics analysis

    PubMed Central

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; Bianchi, Cristina; Johnstone, Megan E.; Donohoe, Dallas R.; Trott, Josephine F.; Aboud, Omran Abu; Stirdivant, Steven; Neri, Bruce; Wolfert, Robert; Stewart, Benjamin; Perego, Roberto; Hsieh, James J.; Weiss, Robert H.

    2015-01-01

    Kidney cancer (or renal cell carcinoma [RCC]) is known as “the internist’s tumor” because it has protean systemic manifestations suggesting it utilizes complex, non-physiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the VHL tumor suppressor, in characterizing higher grade tumors we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, while the β-oxidation pathway is inhibited leading to increased fatty acyl-carnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared to other metabolic pathways. Together, our results offer a rationale to evaluate novel anti-metabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC. PMID:25952651

  17. Impact of a western diet on the ovarian and serum metabolome.

    PubMed

    Dhungana, Suraj; Carlson, James E; Pathmasiri, Wimal; McRitchie, Susan; Davis, Matt; Sumner, Susan; Appt, Susan E

    2016-10-01

    The objective of this investigation was to determine differences in the profiles of endogenous metabolites (metabolomics) among ovaries and serum derived from Old World nonhuman primates fed prudent or Western diets. A retrospective, observational study was done using archived ovarian tissue and serum from midlife cynomolgus monkeys (Macaca fasicularis). Targeted and broad spectrum metabolomics analysis was used to compare ovarian tissue and serum from monkeys that had been exposed to a prudent diet or a Western diet. Monkeys in the prudent diet group (n=13) were research naïve and had been exposed only to a commercial monkey chow diet (low in cholesterol and saturated fats, high in complex carbohydrates). Western diet monkeys (n=8) had consumed a diet that was high in cholesterol, saturated animal fats and soluble carbohydrates for 2 years prior to ovarian tissue and serum collection. Metabolomic analyses were done on extracts of homogenized ovary tissue samples, and extracts of serum. Targeted analysis was conducted using the Biocrates p180 kit and broad spectrum analysis was conducted using UPLC-TOF-MS, resulting in the detection of 3500 compound ions. Using metabolomics methods, which capture thousands of signals for metabolites, 64 metabolites were identified in serum and 47 metabolites were identified in ovarian tissue that differed by diet. Quantitative targeted analysis revealed 13 amino acids, 6 acrylcarnitines, and 2 biogenic amines that were significantly (p<0.05) different between the two diet groups for serum extracts, and similar results were observed for the ovary extracts. These data demonstrate that dietary exposure had a significant impact on the serum and ovarian metabolome, and demonstrated perturbation in carnitine, lipids/fatty acid, and amino acid metabolic pathways. Published by Elsevier Ireland Ltd.

  18. Biological variation of Vanilla planifolia leaf metabolome.

    PubMed

    Palama, Tony Lionel; Fock, Isabelle; Choi, Young Hae; Verpoorte, Robert; Kodja, Hippolyte

    2010-04-01

    The metabolomic analysis of Vanilla planifolia leaves collected at different developmental stages was carried out using (1)H-nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis in order to evaluate their variation. Ontogenic changes of the metabolome were considered since leaves of different ages were collected at two different times of the day and in two different seasons. Principal component analysis (PCA) and partial least square modeling discriminate analysis (PLS-DA) of (1)H NMR data provided a clear separation according to leaf age, time of the day and season of collection. Young leaves were found to have higher levels of glucose, bis[4-(beta-D-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A) and bis[4-(beta-D-glucopyranosyloxy)-benzyl]-2-(2-butyl)-tartrate (glucoside B), whereas older leaves had more sucrose, acetic acid, homocitric acid and malic acid. Results obtained from PLS-DA analysis showed that leaves collected in March 2008 had higher levels of glucosides A and B as compared to those collected in August 2007. However, the relative standard deviation (RSD) exhibited by the individual values of glucosides A and B showed that those compounds vary more according to their developmental stage (50%) than to the time of day or the season in which they were collected (19%). Although morphological variations of the V. planifolia accessions were observed, no clear separation of the accessions was determined from the analysis of the NMR spectra. The results obtained in this study, show that this method based on the use of (1)H NMR spectroscopy in combination with multivariate analysis has a great potential for further applications in the study of vanilla leaf metabolome. Copyright 2009 Elsevier Ltd. All rights reserved.

  19. Optimization of the quenching method for metabolomics analysis of Lactobacillus bulgaricus.

    PubMed

    Chen, Ming-ming; Li, Ai-li; Sun, Mao-cheng; Feng, Zhen; Meng, Xiang-chen; Wang, Ying

    2014-04-01

    This study proposed a quenching protocol for metabolite analysis of Lactobacillus delbrueckii subsp. bulgaricus. Microbial cells were quenched with 60% methanol/water, 80% methanol/glycerol, or 80% methanol/water. The effect of the quenching process was assessed by the optical density (OD)-based method, flow cytometry, and gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed for metabolite identification. The results indicated that quenching with 80% methanol/water solution led to less damage to the L. bulgaricus cells, characterized by the lower relative fraction of prodium iodide (PI)-labeled cells and the higher OD recovery ratio. Through GC-MS analysis, higher levels of intracellular metabolites (including focal glutamic acid, aspartic acid, alanine, and AMP) and a lower leakage rate were detected in the sample quenched with 80% methanol/water compared with the others. In conclusion, we suggested a higher concentration of cold methanol quenching for L. bulgaricus metabolomics due to its decreasing metabolite leakage.

  20. Metabolomics: a state-of-the-art technology for better understanding of male infertility.

    PubMed

    Minai-Tehrani, A; Jafarzadeh, N; Gilany, K

    2016-08-01

    Male factor infertility affects approximately half of the infertile couples, in spite of many years of research on male infertility treatment and diagnosis; several outstanding questions remain to be addressed. In this regard, metabolomics as a novel field of omics has been suggested to be applied for male infertility problems. A variety of terms associated with metabolite quantity and quality have been established to demonstrate mixtures of metabolites. Despite metabolomics and metabolite analyses have been around more than decades, a limited number of studies concerning male infertility have been carried out. In this review, we summarised the latest finding in metabolomics techniques and metabolomics biomarkers correlated with male infertility. The rapid progress of a variety of metabolomics platforms, such as nonoptical and optical spectroscopy, could ease separation, recognition, classification and quantification of several metabolites and their metabolic pathways. Here, we recommend that the novel biomarkers determined in the course of metabolomics analysis may stand for potential application of treatment and future clinical practice. © 2015 Blackwell Verlag GmbH.

  1. Recent advances in liquid-phase separations for clinical metabolomics.

    PubMed

    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.

  2. Nuclear magnetic resonance (NMR)-based metabolomics for cancer research.

    PubMed

    Ranjan, Renuka; Sinha, Neeraj

    2018-05-07

    Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research. Copyright © 2018 John Wiley & Sons, Ltd.

  3. Spatially Resolved Isotopic Source Signatures of Wetland Methane Emissions

    NASA Astrophysics Data System (ADS)

    Ganesan, A. L.; Stell, A. C.; Gedney, N.; Comyn-Platt, E.; Hayman, G.; Rigby, M.; Poulter, B.; Hornibrook, E. R. C.

    2018-04-01

    We present the first spatially resolved wetland δ13C(CH4) source signature map based on data characterizing wetland ecosystems and demonstrate good agreement with wetland signatures derived from atmospheric observations. The source signature map resolves a latitudinal difference of 10‰ between northern high-latitude (mean -67.8‰) and tropical (mean -56.7‰) wetlands and shows significant regional variations on top of the latitudinal gradient. We assess the errors in inverse modeling studies aiming to separate CH4 sources and sinks by comparing atmospheric δ13C(CH4) derived using our spatially resolved map against the common assumption of globally uniform wetland δ13C(CH4) signature. We find a larger interhemispheric gradient, a larger high-latitude seasonal cycle, and smaller trend over the period 2000-2012. The implication is that erroneous CH4 fluxes would be derived to compensate for the biases imposed by not utilizing spatially resolved signatures for the largest source of CH4 emissions. These biases are significant when compared to the size of observed signals.

  4. RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli.

    PubMed

    McCloskey, Douglas; Xu, Julia; Schrübbers, Lars; Christensen, Hanne B; Herrgård, Markus J

    2018-04-25

    Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics of biochemical reactions between strains that could have implications when choosing a host for bioprocessing. Copyright © 2018. Published by Elsevier Inc.

  5. Metabolomic approach for improving ethanol stress tolerance in Saccharomyces cerevisiae.

    PubMed

    Ohta, Erika; Nakayama, Yasumune; Mukai, Yukio; Bamba, Takeshi; Fukusaki, Eiichiro

    2016-04-01

    The budding yeast Saccharomyces cerevisiae is widely used for brewing and ethanol production. The ethanol sensitivity of yeast cells is still a serious problem during ethanol fermentation, and a variety of genetic approaches (e.g., random mutant screening under selective pressure of ethanol) have been developed to improve ethanol tolerance. In this study, we developed a strategy for improving ethanol tolerance of yeast cells based on metabolomics as a high-resolution quantitative phenotypic analysis. We performed gas chromatography-mass spectrometry analysis to identify and quantify 36 compounds on 14 mutant strains including knockout strains for transcription factor and metabolic enzyme genes. A strong relation between metabolome of these mutants and their ethanol tolerance was observed. Data mining of the metabolomic analysis showed that several compounds (such as trehalose, valine, inositol and proline) contributed highly to ethanol tolerance. Our approach successfully detected well-known ethanol stress related metabolites such as trehalose and proline thus, to further prove our strategy, we focused on valine and inositol as the most promising target metabolites in our study. Our results show that simultaneous deletion of LEU4 and LEU9 (leading to accumulation of valine) or INM1 and INM2 (leading to reduction of inositol) significantly enhanced ethanol tolerance. This study shows the potential of the metabolomic approach to identify target genes for strain improvement of S. cerevisiae with higher ethanol tolerance. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  6. Optimization of a direct analysis in real time/time-of-flight mass spectrometry method for rapid serum metabolomic fingerprinting.

    PubMed

    Zhou, Manshui; McDonald, John F; Fernández, Facundo M

    2010-01-01

    Metabolomic fingerprinting of bodily fluids can reveal the underlying causes of metabolic disorders associated with many diseases, and has thus been recognized as a potential tool for disease diagnosis and prognosis following therapy. Here we report a rapid approach in which direct analysis in real time (DART) coupled with time-of-flight (TOF) mass spectrometry (MS) and hybrid quadrupole TOF (Q-TOF) MS is used as a means for metabolomic fingerprinting of human serum. In this approach, serum samples are first treated to precipitate proteins, and the volatility of the remaining metabolites increased by derivatization, followed by DART MS analysis. Maximum DART MS performance was obtained by optimizing instrumental parameters such as ionizing gas temperature and flow rate for the analysis of identical aliquots of a healthy human serum samples. These variables were observed to have a significant effect on the overall mass range of the metabolites detected as well as the signal-to-noise ratios in DART mass spectra. Each DART run requires only 1.2 min, during which more than 1500 different spectral features are observed in a time-dependent fashion. A repeatability of 4.1% to 4.5% was obtained for the total ion signal using a manual sampling arm. With the appealing features of high-throughput, lack of memory effects, and simplicity, DART MS has shown potential to become an invaluable tool for metabolomic fingerprinting. 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

  7. Metabolomics of Genetically Modified Crops

    PubMed Central

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

    2014-01-01

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

  8. UPLC-QTOF analysis reveals metabolomic changes in the flag leaf of wheat (Triticum aestivum L.) under low-nitrogen stress.

    PubMed

    Zhang, Yang; Ma, Xin-Ming; Wang, Xiao-Chun; Liu, Ji-Hong; Huang, Bing-Yan; Guo, Xiao-Yang; Xiong, Shu-Ping; La, Gui-Xiao

    2017-02-01

    Wheat is one of the most important grain crop plants worldwide. Nitrogen (N) is an essential macronutrient for the growth and development of wheat and exerts a marked influence on its metabolites. To investigate the influence of low nitrogen stress on various metabolites of the flag leaf of wheat (Triticum aestivum L.), a metabolomic analysis of two wheat cultivars under different induced nitrogen levels was conducted during two important growth periods based on large-scale untargeted metabolomic analysis using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF). Multivariate analyses-such as principle components analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA)-were used for data analysis. PCA yielded distinctive clustering information among the samples, classifying the wheat flag samples into two categories: those under normal N treatment and low N treatment. By processing OPLS-DA, eleven secondary metabolites were shown to be responsible for classifying the two groups. The secondary metabolites may be considered potential biomarkers of low nitrogen stress. Chemical analyses showed that most of the identified secondary metabolites were flavonoids and their related derivatives, such as iso-vitexin, iso-orientin and methylisoorientin-2″-O-rhamnoside, etc. This study confirmed the effect of low nitrogen stress on the metabolism of wheat, and revealed that the accumulation of secondary metabolites is a response to abiotic stresses. Meanwhile, we aimed to identify markers which could be used to monitor the nitrogen status of wheat crops, presumably to guide appropriate fertilization regimens. Furthermore, the UPLC-QTOF metabolic platform technology can be used to study metabolomic variations of wheat under abiotic stresses. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  9. Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing.

    PubMed

    Ernst, Madeleine; Silva, Denise Brentan; Silva, Ricardo Roberto; Vêncio, Ricardo Z N; Lopes, Norberto Peporine

    2014-06-01

    Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

  10. A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops.

    PubMed

    Martínez Bueno, María Jesús; Díaz-Galiano, Francisco José; Rajski, Łukasz; Cutillas, Víctor; Fernández-Alba, Amadeo R

    2018-04-20

    In the last decade, the consumption trend of organic food has increased dramatically worldwide. However, the lack of reliable chemical markers to discriminate between organic and conventional products makes this market susceptible to food fraud in products labeled as "organic". Metabolomic fingerprinting approach has been demonstrated as the best option for a full characterization of metabolome occurring in plants, since their pattern may reflect the impact of both endogenous and exogenous factors. In the present study, advanced technologies based on high performance liquid chromatography-high-resolution accurate mass spectrometry (HPLC-HRAMS) has been used for marker search in organic and conventional tomatoes grown in greenhouse under controlled agronomic conditions. The screening of unknown compounds comprised the retrospective analysis of all tomato samples throughout the studied period and data processing using databases (mzCloud, ChemSpider and PubChem). In addition, stable nitrogen isotope analysis (δ 15 N) was assessed as a possible indicator to support discrimination between both production systems using crop/fertilizer correlations. Pesticide residue analyses were also applied as a well-established way to evaluate the organic production. Finally, the evaluation by combined chemometric analysis of high-resolution accurate mass spectrometry (HRAMS) and δ 15 N data provided a robust classification model in accordance with the agricultural practices. Principal component analysis (PCA) showed a sample clustering according to farming systems and significant differences in the sample profile was observed for six bioactive components (L-tyrosyl-L-isoleucyl-L-threonyl-L-threonine, trilobatin, phloridzin, tomatine, phloretin and echinenone). Copyright © 2018 Elsevier B.V. All rights reserved.

  11. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

    PubMed

    Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

    2018-03-20

    The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

  12. Analysis of metabolomic profile of fermented Orostachys japonicus A. Berger by capillary electrophoresis time of flight mass spectrometry

    PubMed Central

    Das, Gitishree; Patra, Jayanta Kumar; Lee, Sun-Young; Kim, Changgeon; Park, Jae Gyu

    2017-01-01

    Microbial cell performance in food biotechnological processes has become an important concern for improving human health worldwide. Lactobacillus plantarum, which is widely distributed in nature, is a lactic acid bacterium with many industrial applications for fermented foods or functional foods (e.g., probiotics). In the present study, using capillary electrophoresis time of flight mass spectrometry, the metabolomic profile of dried Orostachys japonicus A. Berger, a perennial medicinal herb with L. plantarum was compared with that of O. japonicus fermented with L. plantarum to elucidate the metabolomic changes induced by the fermentation process. The levels of several metabolites were changed by the fermentation process, indicating their involvement in microbial performance. For example, glycolysis, the pentose phosphate pathway, the TCA cycle, the urea cycle-related metabolism, nucleotide metabolism, and lipid and amino acid metabolism were altered significantly by the fermentation process. Although the fermented metabolites were not tested using in vivo studies to increase human health benefits, our findings provide an insight into the alteration of metabolites induced by fermentation, and indicated that the metabolomic analysis for the process should be accompanied by fermenting strains and conditions. PMID:28704842

  13. Analysis of metabolomic profile of fermented Orostachys japonicus A. Berger by capillary electrophoresis time of flight mass spectrometry.

    PubMed

    Das, Gitishree; Patra, Jayanta Kumar; Lee, Sun-Young; Kim, Changgeon; Park, Jae Gyu; Baek, Kwang-Hyun

    2017-01-01

    Microbial cell performance in food biotechnological processes has become an important concern for improving human health worldwide. Lactobacillus plantarum, which is widely distributed in nature, is a lactic acid bacterium with many industrial applications for fermented foods or functional foods (e.g., probiotics). In the present study, using capillary electrophoresis time of flight mass spectrometry, the metabolomic profile of dried Orostachys japonicus A. Berger, a perennial medicinal herb with L. plantarum was compared with that of O. japonicus fermented with L. plantarum to elucidate the metabolomic changes induced by the fermentation process. The levels of several metabolites were changed by the fermentation process, indicating their involvement in microbial performance. For example, glycolysis, the pentose phosphate pathway, the TCA cycle, the urea cycle-related metabolism, nucleotide metabolism, and lipid and amino acid metabolism were altered significantly by the fermentation process. Although the fermented metabolites were not tested using in vivo studies to increase human health benefits, our findings provide an insight into the alteration of metabolites induced by fermentation, and indicated that the metabolomic analysis for the process should be accompanied by fermenting strains and conditions.

  14. Intrauterine Growth Restriction Programs the Hypothalamus of Adult Male Rats: Integrated Analysis of Proteomic and Metabolomic Data.

    PubMed

    Pedroso, Amanda P; Souza, Adriana P; Dornellas, Ana P S; Oyama, Lila M; Nascimento, Cláudia M O; Santos, Gianni M S; Rosa, José C; Bertolla, Ricardo P; Klawitter, Jelena; Christians, Uwe; Tashima, Alexandre K; Ribeiro, Eliane B

    2017-04-07

    Programming of hypothalamic functions regulating energy homeostasis may play a role in intrauterine growth restriction (IUGR)-induced adulthood obesity. The present study investigated the effects of IUGR on the hypothalamus proteome and metabolome of adult rats submitted to 50% protein-energy restriction throughout pregnancy. Proteomic and metabolomic analyzes were performed by data independent acquisition mass spectrometry and multiple reaction monitoring, respectively. At age 4 months, the restricted rats showed elevated adiposity, increased leptin and signs of insulin resistance. 1356 proteins were identified and 348 quantified while 127 metabolites were quantified. The restricted hypothalamus showed down-regulation of 36 proteins and 5 metabolites and up-regulation of 21 proteins and 9 metabolites. Integrated pathway analysis of the proteomics and metabolomics data indicated impairment of hypothalamic glucose metabolism, increased flux through the hexosamine pathway, deregulation of TCA cycle and the respiratory chain, and alterations in glutathione metabolism. The data suggest IUGR modulation of energy metabolism and redox homeostasis in the hypothalamus of male adult rats. The present results indicated deleterious consequences of IUGR on hypothalamic pathways involved in pivotal physiological functions. These results provide guidance for future mechanistic studies assessing the role of intrauterine malnutrition in the development of metabolic diseases later in life.

  15. Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia

    PubMed Central

    Erogbogbo, Folarin; May, Jasmine; Swihart, Mark; Prasad, Paras N.; Smart, Katie; Jack, Seif El; Korcyk, Dariusz; Webster, Mark; Stewart, Ralph; Zeng, Irene; Jullig, Mia; Bakeev, Katherine; Jamieson, Michelle; Kasabov, Nikolas; Gopalan, Banu; Liang, Linda; Hu, Raphael; Schliebs, Stefan; Villas-Boas, Silas; Gladding, Patrick

    2013-01-01

    Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment. PMID:24019856

  16. Phytochemical diversity of cranberry (Vaccinium macrocarpon Aiton) cultivars by anthocyanin determination and metabolomic profiling with chemometric analysis.

    PubMed

    Brown, Paula N; Murch, Susan J; Shipley, Paul

    2012-01-11

    Originally native to the eastern United States, American cranberry ( Vaccinium macrocarpon Aiton, family Ericaceae) cultivation of native and hybrid varieties has spread across North America. Herein is reported the phytochemical diversity of five cranberry cultivars (Stevens, Ben Lear, Bergman, Pilgrim, and GH1) collected in the Greater Vancouver Regional District, by anthocyanin content and UPLC-TOF-MS metabolomic profiling. The anthocyanin content for biological replicates (n = 5) was determined as 7.98 ± 5.83, Ben Lear; 7.02 ± 1.75, Bergman; 6.05 ± 2.51, GH1; 3.28 ± 1.88, Pilgrim; and 2.81 ± 0.81, Stevens. Using subtractive metabonomic algorithms 6481 compounds were found conserved across all varietals, with 136 (Ben Lear), 84 (Bergman), 91 (GH1), 128 (Pilgrim), and 165 (Stevens) unique compounds observed. Principal component analysis (PCA) did not differentiate varieties, whereas partial least-squares discriminate analysis (PLS-DA) exhibited clustering patterns. Univariate statistical approaches were applied to the data set, establishing significance of values and assessing quality of the models. Metabolomic profiling with chemometric analysis proved to be useful for characterizing metabonomic changes across cranberry varieties.

  17. Metabolomics analysis reveals 6‐benzylaminopurine as a stimulator for improving lipid and DHA accumulation of Aurantiochytriumsp.

    PubMed Central

    Yu, Xin‐Jun; Sun, Jie; Zheng, Jian‐Yong; Sun, Ya‐Qi

    2016-01-01

    Abstract BACKGROUND Phytohormones are chemical messengers that have a positive effect on biodiesel production of microalgae at low concentrations. However, the effect of phytohormone 6‐benzylaminopurine on lipid and docosahexaenoic acid (DHA) production in marine DHA‐producer Aurantiochytrium has never been reported. In this study, a GC‐MS‐based metabolomics method combined with a multivariate analysis is applied to reveal the metabolic mechanism of 6‐benzylaminopurine enhancing production of lipid and DHA in Aurantiochytrium sp.YLH70. RESULTS In total, 71 metabolites were identified by GC‐MS. The PCA model revealed that 76.9% of metabolite variation was related to 6‐benzylaminopurine treatment, and overall metabolomics profiles between the 6‐benzylaminopurine and control groups were clearly discriminated. Forty‐six metabolites identified by the PLS‐DA model were responsible for responding to 6‐benzylaminopurine. Metabolic analysis showed that 6‐benzylaminopurine could accelerate the rate of utilization of glucose in Aurantiochytrium sp. YLH70, and the metabolic flux from glycolysis, TCA cycle and mevalonate pathway to fatty acids biosynthesis was promoted. Moreover, the anti‐stress mechanism in Aurantiochytrium sp.YLH70 might be induced by 6‐benzylaminopurine. CONCLUSION Metabolomics is a suitable tool to discover the metabolic mechanism for improving lipid and DHA accumulation in a microorganism. 6‐benzylaminopurine has the potential to stimulate lipid and DHA production of Aurantiochytrium sp.YLH70 for industrial purposes. © 2015 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:27065509

  18. Metabolic changes associated with papillary thyroid carcinoma: A nuclear magnetic resonance-based metabolomics study.

    PubMed

    Li, Yanyun; Chen, Minjian; Liu, Cuiping; Xia, Yankai; Xu, Bo; Hu, Yanhui; Chen, Ting; Shen, Meiping; Tang, Wei

    2018-05-01

    Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. Nuclear magnetic resonance (NMR)‑based metabolomic technique is the gold standard in metabolite structural elucidation, and can provide different coverage of information compared with other metabolomic techniques. Here, we firstly conducted NMR based metabolomics study regarding detailed metabolic changes especially metabolic pathway changes related to PTC pathogenesis. 1H NMR-based metabolomic technique was adopted in conju-nction with multivariate analysis to analyze matched tumor and normal thyroid tissues obtained from 16 patients. The results were further annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG), and Human Metabolome Database, and then were analyzed using modules of pathway analysis and enrichment analysis of MetaboAnalyst 3.0. Based on the analytical techniques, we established the models of principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least-squares discriminant analysis (OPLS‑DA) which could discriminate PTC from normal thyroid tissue, and found 15 robust differentiated metabolites from two OPLS-DA models. We identified 8 KEGG pathways and 3 pathways of small molecular pathway database which were significantly related to PTC by using pathway analysis and enrichment analysis, respectively, through which we identified metabolisms related to PTC including branched chain amino acid metabolism (leucine and valine), other amino acid metabolism (glycine and taurine), glycolysis (lactate), tricarboxylic acid cycle (citrate), choline metabolism (choline, ethanolamine and glycerolphosphocholine) and lipid metabolism (very-low‑density lipoprotein and low-density lipoprotein). In conclusion, the PTC was characterized with increased glycolysis and inhibited tricarboxylic acid cycle, increased oncogenic amino acids as well as abnormal choline and lipid metabolism. The findings in this study provide new

  19. Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics.

    PubMed

    Gika, Helen G; Theodoridis, Georgios A; Plumb, Robert S; Wilson, Ian D

    2014-01-01

    Based on publication and citation numbers liquid chromatography (LC-MS) has become the major analytical technology in the field of global metabolite profiling. This dominance reflects significant investments from both the research community and instrument manufacturers. Here an overview of the approaches taken for LC-MS-based metabolomics research is given, describing critical steps in the realisation of such studies: study design and its needs, specific technological problems to be addressed and major obstacles in data treatment and biomarker identification. The current state of the art for LC-MS-based analysis in metabonomics/metabolomics is described including recent developments in liquid chromatography, mass spectrometry and data treatment as these are applied in metabolomics underlining the challenges, limitations and prospects for metabolomics research. Examples of the application of metabolite profiling in the life sciences focusing on disease biomarker discovery are highlighted. In addition, new developments and future prospects are described. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

    PubMed Central

    Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

    2016-01-01

    The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34–80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics. PMID:28000704

  1. Metabolomic analysis reveals metabolic changes caused by bisphenol A in rats.

    PubMed

    Chen, Minjian; Zhou, Kun; Chen, Xiaojiao; Qiao, Shanlei; Hu, Yanhui; Xu, Bo; Xu, Bin; Han, Xiumei; Tang, Rong; Mao, Zhilei; Dong, Congcong; Wu, Di; Wang, Yubang; Wang, Shoulin; Zhou, Zuomin; Xia, Yankai; Wang, Xinru

    2014-04-01

    Bisphenol A (BPA) is a widely used material known to cause adverse effects in humans and other mammals. To date, little is known about the global metabolomic alterations caused by BPA using urinalysis. Sprague-Dawley rats were orally administrated BPA at the levels of 0, 0.5 μg/kg/day and 50 mg/kg/day covering a low dose and a reference dose for 8 weeks. We conducted a capillary electrophoresis in tandem with electrospray ionization time-of-flight mass spectrometry based nontargeted metabolomic analysis using rat urine. To verify the metabolic alteration at both low and high doses, reverse transcription-polymerase chain reaction (RT-PCR) and western blotting were further conducted to analyze hepatic expression of methionine adenosyltransferase Iα (Mat1a) and methionine adenosyltransferase IIα (Mat2a). Hepatic S-adenosylmethionine (SAMe) was also analyzed. A total of 199 metabolites were profiled. Statistical analysis and pathway mapping indicated that the most significant metabolic perturbations induced by BPA were the increased biotin and riboflavin excretion, increased synthesis of methylated products, elevated purine nucleotide catabolism, and increased flux through the choline metabolism pathway. We found significantly higher mRNA and protein levels of Mat1a and Mat2a, and significantly higher SAMe levels in rat liver at both low and high doses. These two genes encode critical isoenzymes that catalyze the formation of SAMe, the principal biological methyl donor involved in the choline metabolism. In conclusion, an elevated choline metabolism is underlying the mechanism of highly methylated environment and related metabolic alterations caused by BPA. The data of BPA-elevated accepted biomarkers of injury indicate that BPA induces DNA methylation damage and broad protein degradation, and the increased deleterious metabolites in choline pathway may also be involved in the toxicity of BPA.

  2. MWASTools: an R/bioconductor package for metabolome-wide association studies.

    PubMed

    Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel

    2018-03-01

    MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. The MWASTools R package is implemented in R (version  > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. m.dumas@imperial.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  3. Metabolomic Profiles of Current Cigarette Smokers

    PubMed Central

    Hsu, Ping-Ching; Lan, Renny S.; Brasky, Theodore M.; Marian, Catalin; Cheema, Amrita K.; Ressom, Habtom W.; Loffredo, Christopher A.; Pickworth, Wallace B.; Shields, Peter G.

    2017-01-01

    Smoking-related biomarkers for lung cancer and other diseases are needed to enhance early detection strategies and to provide a science base for tobacco product regulation. An untargeted metabolomics approach by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF MS) totaling 957 assays was used in a novel experimental design where 105 current smokers smoked 2 cigarettes one hour apart. Blood was collected immediately before and after each cigarette allowing for within-subject replication. Dynamic changes of the metabolomic profiles from smokers’ four blood samples were observed and biomarkers affected by cigarette smoking were identified. Thirty-one metabolites were definitively shown to be affected by acute effect of cigarette smoking, uniquely including menthol-glucuronide, the reduction of glutamate, oleamide, and 13 glycerophospholipids. This first time identification of a menthol metabolite in smokers’ blood serves as proof-of-principle for using metabolomics to identify new tobacco-exposure biomarkers, and also provides new opportunities in studying menthol-containing tobacco products in humans. Gender and race differences also were observed. Network analysis revealed 12 molecules involved in cancer, notably inhibition of cAMP. These novel tobacco-related biomarkers provide new insights to the effects of smoking which may be important in carcinogenesis but not previously linked with tobacco-related diseases. PMID:27341184

  4. Metabolomic biosignature differentiates melancholic depressive patients from healthy controls.

    PubMed

    Liu, Yashu; Yieh, Lynn; Yang, Tao; Drinkenburg, Wilhelmus; Peeters, Pieter; Steckler, Thomas; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

    2016-08-23

    Major depressive disorder (MDD) is a heterogeneous disease at the level of clinical symptoms, and this heterogeneity is likely reflected at the level of biology. Two clinical subtypes within MDD that have garnered interest are "melancholic depression" and "anxious depression". Metabolomics enables us to characterize hundreds of small molecules that comprise the metabolome, and recent work suggests the blood metabolome may be able to inform treatment decisions for MDD, however work is at an early stage. Here we examine a metabolomics data set to (1) test whether clinically homogenous MDD subtypes are also more biologically homogeneous, and hence more predictiable, (2) devise a robust machine learning framework that preserves biological meaning, and (3) describe the metabolomic biosignature for melancholic depression. With the proposed computational system we achieves around 80 % classification accuracy, sensitivity and specificity for melancholic depression, but only ~72 % for anxious depression or MDD, suggesting the blood metabolome contains more information about melancholic depression.. We develop an ensemble feature selection framework (EFSF) in which features are first clustered, and learning then takes place on the cluster centroids, retaining information about correlated features during the feature selection process rather than discarding them as most machine learning methods will do. Analysis of the most discriminative feature clusters revealed differences in metabolic classes such as amino acids and lipids as well as pathways studied extensively in MDD such as the activation of cortisol in chronic stress. We find the greater clinical homogeneity does indeed lead to better prediction based on biological measurements in the case of melancholic depression. Melancholic depression is shown to be associated with changes in amino acids, catecholamines, lipids, stress hormones, and immune-related metabolites. The proposed computational framework can be adapted

  5. Metabolomics as a Functional Tool in Screening Gastro Intestinal Diseases: Where are we in High Throughput Screening?

    PubMed

    Gundamaraju, Rohit; Vemuri, Ravichandra; Eri, Rajaraman; Ishiki, Hamilton M; Coy-Barrera, Ericsson; Yarla, Nagendra Sastry; Dos Santos, Sócrates Golzio; Alves, Mateus Feitosa; Barbosa Filho, José Maria; Diniz, Margareth F F M; Scotti, Marcus T; Scotti, Luciana

    2017-01-01

    Identifying novel bio markers in gastro intestinal disease is a promising method where a comprehensive analysis of the metabolome is performed. Metabolomics has evolved enormously in the past decade, paving a path in gastro intestinal disease research, especially diseases which lead to high morbidity and mortality. Metabolomics involves identifying metabolites such as anti-oxidants, and amino acids etc., which are screened in the urine, feces and tissue samples. Certain cases employ advanced tools like GC-MS, 1HNMR and GC-MS/SPME which reveal valuable information concerning disease severity and differentiation. In light of escalating health care costs and risky invasive procedures, metabolomics can be chosen as a safe yet precise method for screening diseases like ulcerative colitis, Crohns' disease, celiac disease, and gastro intestinal cancers. The present review focuses on major advancements in gastro intestinal metabolomics, giving attention to which parameters are assessed, and to recent changes in metabolite analysis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  6. Field-based Metabolomics for Assessing Contaminated Surface Waters

    EPA Science Inventory

    Metabolomics is becoming well-established for studying chemical contaminant-induced alterations to normal biological function. For example, the literature contains a wealth of laboratory-based studies involving analysis of samples from organisms exposed to individual chemical tox...

  7. Quantitative metabolomics of the thermophilic methylotroph Bacillus methanolicus.

    PubMed

    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.

  8. An initial non-targeted analysis of the peanut seed metabolome

    USDA-ARS?s Scientific Manuscript database

    There are likely a large number of compounds that constitute the peanut seed metabolome that have yet to be elucidated. Although the proximate composition and nutrients such as vitamins and minerals are well known, the composition of many other small molecule metabolites present have not been syste...

  9. Optical spectroscopy of laser-produced plasmas for standoff isotopic analysis

    NASA Astrophysics Data System (ADS)

    Harilal, S. S.; Brumfield, B. E.; LaHaye, N. L.; Hartig, K. C.; Phillips, M. C.

    2018-06-01

    Rapid, in-field, and non-contact isotopic analysis of solid materials is extremely important to a large number of applications, such as nuclear nonproliferation monitoring and forensics, geochemistry, archaeology, and biochemistry. Presently, isotopic measurements for these and many other fields are performed in laboratory settings. Rapid, in-field, and non-contact isotopic analysis of solid material is possible with optical spectroscopy tools when combined with laser ablation. Laser ablation generates a transient vapor of any solid material when a powerful laser interacts with a sample of interest. Analysis of atoms, ions, and molecules in a laser-produced plasma using optical spectroscopy tools can provide isotopic information with the advantages of real-time analysis, standoff capability, and no sample preparation requirement. Both emission and absorption spectroscopy methods can be used for isotopic analysis of solid materials. However, applying optical spectroscopy to the measurement of isotope ratios from solid materials presents numerous challenges. Isotope shifts arise primarily due to variation in nuclear charge distribution caused by different numbers of neutrons, but the small proportional nuclear mass differences between nuclei of various isotopes lead to correspondingly small differences in optical transition wavelengths. Along with this, various line broadening mechanisms in laser-produced plasmas and instrumental broadening generated by the detection system are technical challenges frequently encountered with emission-based optical diagnostics. These challenges can be overcome by measuring the isotope shifts associated with the vibronic emission bands from molecules or by using the techniques of laser-based absorption/fluorescence spectroscopy to marginalize the effect of instrumental broadening. Absorption and fluorescence spectroscopy probe the ground state atoms existing in the plasma when it is cooler, which inherently provides narrower

  10. Metabolomics for secondary metabolite research.

    PubMed

    Breitling, Rainer; Ceniceros, Ana; Jankevics, Andris; Takano, Eriko

    2013-11-11

    Metabolomics, the global characterization of metabolite profiles, is becoming an increasingly powerful tool for research on secondary metabolite discovery and production. In this review we discuss examples of recent technological advances and biological applications of metabolomics in the search for chemical novelty and the engineered production of bioactive secondary metabolites.

  11. Optimization of the quenching method for metabolomics analysis of Lactobacillus bulgaricus *

    PubMed Central

    Chen, Ming-ming; Li, Ai-li; Sun, Mao-cheng; Feng, Zhen; Meng, Xiang-chen; Wang, Ying

    2014-01-01

    This study proposed a quenching protocol for metabolite analysis of Lactobacillus delbrueckii subsp. bulgaricus. Microbial cells were quenched with 60% methanol/water, 80% methanol/glycerol, or 80% methanol/water. The effect of the quenching process was assessed by the optical density (OD)-based method, flow cytometry, and gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed for metabolite identification. The results indicated that quenching with 80% methanol/water solution led to less damage to the L. bulgaricus cells, characterized by the lower relative fraction of prodium iodide (PI)-labeled cells and the higher OD recovery ratio. Through GC-MS analysis, higher levels of intracellular metabolites (including focal glutamic acid, aspartic acid, alanine, and AMP) and a lower leakage rate were detected in the sample quenched with 80% methanol/water compared with the others. In conclusion, we suggested a higher concentration of cold methanol quenching for L. bulgaricus metabolomics due to its decreasing metabolite leakage. PMID:24711354

  12. Multiple sulfur isotope determination on SO2 gas

    NASA Astrophysics Data System (ADS)

    Halas, Stanislaw; Pienkos, Tomasz

    2017-04-01

    The principal motivation of this study is to apply SO2 gas in the multiple isotope analysis (i.e. simultaneous analysis of sulfur isotope ratios: 33S/32S , 34S/32S and 36S/32S) rather than SF6 gas. SO2 gas can be easily prepared from sulfides (Robinson and Kusakabe 1975) and from sulfates (Halas and Wolacewicz 1981), whilst the preparation of SF6 gas requires the use of a fluorination line (Ono et al. 2006) and a mass spectrometer with enhanced resolving power to resolve isotope peaks 33SF5- from 32SF5- (masses 128 and 127). In the patent application (Halas et al. 2016) we have described a new ion source which can be applied for analysis of gases. The new ion source significantly enhances generation, both positive and negative, ions in comparison to commonly used Nier type. The analyzed gas is admitted from a dual inlet system to the ion source through separate capillaries connected to the pneumatically operated changeover valve as described by Halas (1979). It is important to have SO2 samples well purified from volatiles which eliminates O2 interference at mass 32 peak. A great advantage of the isotope analysis on S+ instead on SO+ or SO2+spectra is that there is no need to keep constant oxygen isotopic composition in the SO2 gas. Usually sulfide and sulfate samples have different oxygen, but it doesn't matter in the case of analysis on S+. The achieved precision (1σ) on positive ion beams was better than 0.1‰ and 0.01‰ for δ36S and δ34S, respectively. Unfortunately δ33S cannot be measured in this way, because of formation of 32SH+ ions which interfere with 33S+. The details of the design of the ion source, vacuum system and electronic controllers are presented in the poster. We thank to Dr. Keith Hackley for donation of an old mass spectrometer to UMCS, on the basis of which we were able to develop the new instrument. This study was supported by NCN project 2013/11/B/ST10/00250. References Hałas S., Pieńkos T., Pelc A., Wójtowicz A. (2016) Patent

  13. Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer

    NASA Astrophysics Data System (ADS)

    Huan, Tao; Troyer, Dean A.; Li, Liang

    2016-08-01

    We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy.

  14. Unraveling Biochemical Pathways Affected by Mitochondrial Dysfunctions Using Metabolomic Approaches

    PubMed Central

    Demine, Stéphane; Reddy, Nagabushana; Renard, Patricia; Raes, Martine; Arnould, Thierry

    2014-01-01

    Mitochondrial dysfunction(s) (MDs) can be defined as alterations in the mitochondria, including mitochondrial uncoupling, mitochondrial depolarization, inhibition of the mitochondrial respiratory chain, mitochondrial network fragmentation, mitochondrial or nuclear DNA mutations and the mitochondrial accumulation of protein aggregates. All these MDs are known to alter the capacity of ATP production and are observed in several pathological states/diseases, including cancer, obesity, muscle and neurological disorders. The induction of MDs can also alter the secretion of several metabolites, reactive oxygen species production and modify several cell-signalling pathways to resolve the mitochondrial dysfunction or ultimately trigger cell death. Many metabolites, such as fatty acids and derived compounds, could be secreted into the blood stream by cells suffering from mitochondrial alterations. In this review, we summarize how a mitochondrial uncoupling can modify metabolites, the signalling pathways and transcription factors involved in this process. We describe how to identify the causes or consequences of mitochondrial dysfunction using metabolomics (liquid and gas chromatography associated with mass spectrometry analysis, NMR spectroscopy) in the obesity and insulin resistance thematic. PMID:25257998

  15. Metabolomic analysis of 92 pulmonary embolism patients from a nested case-control study identifies metabolites associated with adverse clinical outcomes.

    PubMed

    Zeleznik, O A; Poole, E M; Lindstrom, S; Kraft, P; Van Hylckama Vlieg, A; Lasky-Su, J A; Harrington, L B; Hagan, K; Kim, J; Parry, B A; Giordano, N; Kabrhel, C

    2018-03-01

    Essentials Risk-stratification often fails to predict clinical deterioration in pulmonary embolism (PE). First-ever high-throughput metabolomics analysis of risk-stratified PE patients. Changes in circulating metabolites reflect a compromised energy metabolism in PE. Metabolites play a key role in the pathophysiology and risk stratification of PE. Background Patients with acute pulmonary embolism (PE) exhibit wide variation in clinical presentation and outcomes. Our understanding of the pathophysiologic mechanisms differentiating low-risk and high-risk PE is limited, so current risk-stratification efforts often fail to predict clinical deterioration and are insufficient to guide management. Objectives To improve our understanding of the physiology differentiating low-risk from high-risk PE, we conducted the first-ever high-throughput metabolomics analysis (843 named metabolites) comparing PE patients across risk strata within a nested case-control study. Patients/methods We enrolled 92 patients diagnosed with acute PE and collected plasma within 24 h of PE diagnosis. We used linear regression and pathway analysis to identify metabolites and pathways associated with PE risk-strata. Results When we compared 46 low-risk with 46 intermediate/high-risk PEs, 50 metabolites were significantly different after multiple testing correction. These metabolites were enriched in the following pathways: tricarboxylic acid (TCA) cycle, fatty acid metabolism (acyl carnitine) and purine metabolism, (hypo)xanthine/inosine containing. Additionally, energy, nucleotide and amino acid pathways were downregulated in intermediate/high-risk PE patients. When we compared 28 intermediate-risk with 18 high-risk PE patients, 41 metabolites differed at a nominal P-value level. These metabolites were enriched in fatty acid metabolism (acyl cholines), and hemoglobin and porphyrin metabolism. Conclusion Our results suggest that high-throughput metabolomics can provide insight into the

  16. Metabolomics: beyond biomarkers and towards mechanisms

    PubMed Central

    Johnson, Caroline H.; Ivanisevic, Julijana; Siuzdak, Gary

    2017-01-01

    Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases. PMID:26979502

  17. Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges.

    PubMed

    Tokarz, Janina; Haid, Mark; Cecil, Alexander; Prehn, Cornelia; Artati, Anna; Möller, Gabriele; Adamski, Jerzy

    2017-10-01

    The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Conventional and Accelerated-Solvent Extractions of Green Tea (Camellia sinensis) for Metabolomics-based Chemometrics

    PubMed Central

    Kellogg, Joshua J.; Wallace, Emily D.; Graf, Tyler N.; Oberlies, Nicholas H.; Cech, Nadja B.

    2018-01-01

    Metabolomics has emerged as an important analytical technique for multiple applications. The value of information obtained from metabolomics analysis depends on the degree to which the entire metabolome is present and the reliability of sample treatment to ensure reproducibility across the study. The purpose of this study was to compare methods of preparing complex botanical extract samples prior to metabolomics profiling. Two extraction methodologies, accelerated solvent extraction and a conventional solvent maceration, were compared using commercial green tea [Camellia sinensis (L.) Kuntze (Theaceae)] products as a test case. The accelerated solvent protocol was first evaluated to ascertain critical factors influencing extraction using a D-optimal experimental design study. The accelerated solvent and conventional extraction methods yielded similar metabolite profiles for the green tea samples studied. The accelerated solvent extraction yielded higher total amounts of extracted catechins, was more reproducible, and required less active bench time to prepare the samples. This study demonstrates the effectiveness of accelerated solvent as an efficient methodology for metabolomics studies. PMID:28787673

  19. Time-Resolved DNA Stable Isotope Probing Links Desulfobacterales- and Coriobacteriaceae-Related Bacteria to Anaerobic Degradation of Benzene under Methanogenic Conditions

    PubMed Central

    Noguchi, Mana; Kurisu, Futoshi; Kasuga, Ikuro; Furumai, Hiroaki

    2014-01-01

    To identify the microorganisms involved in benzene degradation, DNA-stable isotope probing (SIP) with 13C-benzene was applied to a methanogenic benzene-degrading enrichment culture. Pyrosequencing of ribosomal RNA (rRNA) gene sequences revealed that the community structure was highly complex in spite of a 3-year incubation only with benzene. The culture degraded 98% of approximately 1 mM 13C-benzene and mineralized 72% of that within 63 d. The terminal restriction fragment length polymorphism (T-RFLP) profiles of the buoyant density fractions revealed the incorporation of 13C into two phylotypes after 64 d. These two phylotypes were determined to be Desulfobacterales- and Coriobacteriaceae-related bacteria by cloning and sequencing of the 16S rRNA gene in the 13C-labeled DNA abundant fraction. Comparative pyrosequencing analysis of the buoyant density fractions of 12C- and 13C-labeled samples indicated the incorporation of 13C into three bacterial and one archaeal OTUs related to Desulfobacterales, Coriobacteriales, Rhodocyclaceae, and Methanosarcinales. The first two OTUs included the bacteria detected by T-RFLP-cloning-sequencing analysis. Furthermore, time-resolved SIP analysis confirmed that the activity of all these microbes appeared at the earliest stage of degradation. In this methanogenic culture, Desulfobacterales- and Coriobacteriaceae-related bacteria were most likely to be the major benzene degraders. PMID:24909708

  20. Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia.

    PubMed

    Pérez-Rambla, Clara; Puchades-Carrasco, Leonor; García-Flores, María; Rubio-Briones, José; López-Guerrero, José Antonio; Pineda-Lucena, Antonio

    2017-01-01

    Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results. In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH. Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1 H nuclear magnetic resonance ( 1 H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches. The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH. PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

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

    PubMed

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

    2014-03-01

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

  2. On the resilience of nitrogen assimilation by intact roots under starvation, as revealed by isotopic and metabolomic techniques.

    PubMed

    Bathellier, Camille; Tcherkez, Guillaume; Mauve, Caroline; Bligny, Richard; Gout, Elizabeth; Ghashghaie, Jaleh

    2009-09-01

    The response of root metabolism to variations in carbon source availability is critical for whole-plant nitrogen (N) assimilation and growth. However, the effect of changes in the carbohydrate input to intact roots is currently not well understood and, for example, both smaller and larger values of root:shoot ratios or root N uptake have been observed so far under elevated CO(2). In addition, previous studies on sugar starvation mainly focused on senescent or excised organs while an increasing body of data suggests that intact roots may behave differently with, for example, little protein remobilization. Here, we investigated the carbon and nitrogen primary metabolism in intact roots of French bean (Phaseolus vulgaris L.) plants maintained under continuous darkness for 4 days. We combined natural isotopic (15)N/(14)N measurements, metabolomic and (13)C-labeling data and show that intact roots continued nitrate assimilation to glutamate for at least 3 days while the respiration rate decreased. The activity of the tricarboxylic acid cycle diminished so that glutamate synthesis was sustained by the anaplerotic phosphoenolpyruvate carboxylase fixation. Presumably, the pentose phosphate pathway contributed to provide reducing power for nitrate reduction. All the biosynthetic metabolic fluxes were nevertheless down-regulated and, consequently, the concentration of all amino acids decreased. This is the case of asparagine, strongly suggesting that, as opposed to excised root tips, protein remobilization in intact roots remained very low for 3 days in spite of the restriction of respiratory substrates. Copyright (c) 2009 John Wiley & Sons, Ltd.

  3. Metabolomics for Biomarker Discovery: Moving to the Clinic

    PubMed Central

    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

  4. Metabolomics discloses donor liver biomarkers associated with early allograft dysfunction.

    PubMed

    Cortes, Miriam; Pareja, Eugenia; García-Cañaveras, Juan C; Donato, M Teresa; Montero, Sandra; Mir, Jose; Castell, José V; Lahoz, Agustín

    2014-09-01

    Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD. A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients. A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4). A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  5. Integrating tracer-based metabolomics data and metabolic fluxes in a linear fashion via Elementary Carbon Modes.

    PubMed

    Pey, Jon; Rubio, Angel; Theodoropoulos, Constantinos; Cascante, Marta; Planes, Francisco J

    2012-07-01

    Constraints-based modeling is an emergent area in Systems Biology that includes an increasing set of methods for the analysis of metabolic networks. In order to refine its predictions, the development of novel methods integrating high-throughput experimental data is currently a key challenge in the field. In this paper, we present a novel set of constraints that integrate tracer-based metabolomics data from Isotope Labeling Experiments and metabolic fluxes in a linear fashion. These constraints are based on Elementary Carbon Modes (ECMs), a recently developed concept that generalizes Elementary Flux Modes at the carbon level. To illustrate the effect of our ECMs-based constraints, a Flux Variability Analysis approach was applied to a previously published metabolic network involving the main pathways in the metabolism of glucose. The addition of our ECMs-based constraints substantially reduced the under-determination resulting from a standard application of Flux Variability Analysis, which shows a clear progress over the state of the art. In addition, our approach is adjusted to deal with combinatorial explosion of ECMs in genome-scale metabolic networks. This extension was applied to infer the maximum biosynthetic capacity of non-essential amino acids in human metabolism. Finally, as linearity is the hallmark of our approach, its importance is discussed at a methodological, computational and theoretical level and illustrated with a practical application in the field of Isotope Labeling Experiments. Copyright © 2012 Elsevier Inc. All rights reserved.

  6. Menthol smokers: metabolomic profiling and smoking behavior

    PubMed Central

    Hsu, Ping-Ching; Lan, Renny S.; Brasky, Theodore M.; Marian, Catalin; Cheema, Amrita K.; Ressom, Habtom W.; Loffredo, Christopher A.; Pickworth, Wallace B.; Shields, Peter G.

    2016-01-01

    Background The use of menthol in cigarettes and marketing is under consideration for regulation by the FDA. However, the effects of menthol on smoking behavior and carcinogen exposure have been inconclusive. We previously reported metabolomic profiling for cigarette smokers, and novelly identified a menthol-glucuronide (MG) as the most significant metabolite directly related to smoking. Here, MG is studied in relation to smoking behavior and metabolomic profiles. Methods A cross-sectional study of 105 smokers who smoked two cigarettes in the laboratory one hour apart. Blood nicotine, MG and exhaled carbon monoxide (CO) boosts were determined (the difference before and after smoking). Spearman's correlation, Chi-Square and ANCOVA adjusted for gender, race and cotinine levels for menthol smokers assessed the relationship of MG boost, smoking behavior, and metabolic profiles. Multivariate metabolite characterization using supervised Partial Least Squares-Discriminant Analysis (PLS-DA) was carried out for the classification of metabolomics profiles. Results MG boost was positively correlated with CO boost, nicotine boost, average puff volume, puff duration, and total smoke exposure. Classification using PLS-DA, MG was the top metabolite discriminating metabolome of menthol vs. non-menthol smokers. Among menthol smokers, forty-two metabolites were significantly correlated with MG boost, which linked to cellular functions such as of cell death, survival, and movement. Conclusion Plasma MG boost is a new smoking behavior biomarker that may provides novel information over self-reported use of menthol cigarettes by integrating different smoking measures for understanding smoking behavior and harm of menthol cigarettes. Impacts These results provide insight into the biological effect of menthol smoking. PMID:27628308

  7. Translating Metabolomics to Cardiovascular Biomarkers

    PubMed Central

    Senn, Todd; Hazen, Stanley L.; Tang, W. H. Wilson

    2012-01-01

    Metabolomics is the systematic study of the unique chemical fingerprints of small-molecules, or metabolite profiles, that are related to a variety of cellular metabolic processes in a cell, organ, or organism. While mRNA gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell, metabolic profiling provides direct and indirect physiologic insights that can potentially be detectable in a wide range of biospecimens. Although not specific to cardiac conditions, translating metabolomics to cardiovascular biomarkers has followed the traditional path of biomarker discovery from identification and confirmation to clinical validation and bedside testing. With technological advances in metabolomic tools (such as nuclear magnetic resonance spectroscopy and mass spectrometry) and more sophisticated bioinformatics and analytical techniques, the ability to measure low-molecular-weight metabolites in biospecimens provides a unique insight into established and novel metabolic pathways. Systemic metabolomics may provide physiologic understanding of cardiovascular disease states beyond traditional profiling, and may involve descriptions of metabolic responses of an individual or population to therapeutic interventions or environmental exposures. PMID:22824112

  8. Metabolomic analysis of amino acid and energy metabolism in rats supplemented with chlorogenic acid

    PubMed Central

    Ruan, Zheng; Yang, Yuhui; Zhou, Yan; Wen, Yanmei; Ding, Sheng; Liu, Gang; Wu, Xin; Deng, Zeyuan; Assaad, Houssein; Wu, Guoyao

    2016-01-01

    This study was conducted to investigate effects of chlorogenic acid (CGA) supplementation on serum and hepatic metabolomes in rats. Rats received daily intragastric administration of either CGA (60 mg/kg body weight) or distilled water (control) for 4 weeks. Growth performance, serum biochemical profiles, and hepatic morphology were measured. Additionally, serum and liver tissue extracts were analyzed for metabolomes by high-resolution 1H nuclear magnetic resonance-based metabolomics and multivariate statistics. CGA did not affect rat growth performance, serum biochemical profiles, or hepatic morphology. However, supplementation with CGA decreased serum concentrations of lactate, pyruvate, succinate, citrate, β-hydroxybutyrate and acetoacetate, while increasing serum concentrations of glycine and hepatic concentrations of glutathione. These results suggest that CGA supplementation results in perturbation of energy and amino acid metabolism in rats. We suggest that glycine and glutathione in serum may be useful biomarkers for biological properties of CGA on nitrogen metabolism in vivo. PMID:24927697

  9. The molecular mechanism of Mo isotope fractionation during adsorption to birnessite

    USGS Publications Warehouse

    Wasylenki, L.E.; Weeks, C.L.; Bargar, J.R.; Spiro, T.G.; Hein, J.R.; Anbar, A.D.

    2011-01-01

    Fractionation of Mo isotopes during adsorption to manganese oxides is a primary control on the global ocean Mo isotope budget. Previous attempts to explain what drives the surprisingly large isotope effect ??97/95Modissolved-??97/95Moadsorbed=1.8??? have not successfully resolved the fractionation mechanism. New evidence from extended X-ray absorption fine structure analysis and density functional theory suggests that Mo forms a polymolybdate complex on the surfaces of experimental and natural samples. Mo in this polynuclear structure is in distorted octahedral coordination, while Mo remaining in solution is predominantly in tetrahedral coordination as MoO42- Our results indicate that the difference in coordination environment between dissolved Mo and adsorbed Mo is the cause of isotope fractionation. The molecular mechanism of metal isotope fractionation in this system should enable us to explain and possibly predict metal isotope effects in other systems where transition metals adsorb to mineral surfaces. ?? 2011 Elsevier Ltd.

  10. Metabolomic comparison between wild Ophiocordyceps sinensis and artificial cultured Cordyceps militaris.

    PubMed

    Chen, Lin; Liu, Yuetao; Guo, Qingfeng; Zheng, Qingxia; Zhang, Wancun

    2018-05-11

    A systematic study on the metabolome differences between wild Ophiocordyceps sinensis and artificial cultured Cordyceps militaris was conducted using liquid chromatography-mass spectrometry. Principal component analysis and orthogonal projection on latent structure-discriminant analysis results showed that C. militaris grown on solid rice medium (R-CM) and C. militaris grown on tussah pupa (T-CM) evidently separated and individually separated from wild O. sinensis, indicating metabolome difference among wild O. sinensis, R-CM and T-CM. The metabolome differences between R-CM and T-CM indicated that C. militaris could accommodate to culture medium by differential metabolic regulation. Hierarchical clustering analysis was further performed to cluster the differential metabolites and samples based on their metabolic similarity. The higher content of amino acids (pyroglutamic acid, glutamic acid, histidine, phenylalanine and arginine), unsaturated fatty acid (linolenic acid and linoleic acid), peptides, mannitol, adenosine and succinoadenosine in O. sinensis make it as an excellent choice as a traditional Chinese medicine for invigoration or nutritional supplementation. Similar compositions with O. sinensis and easy cultivation make artificially cultured C. militaris a possible alternative to O. sinensis. Copyright © 2018 John Wiley & Sons, Ltd.

  11. Dissemination of metabolomics results: role of MetaboLights and COSMOS.

    PubMed

    Salek, Reza M; Haug, Kenneth; Steinbeck, Christoph

    2013-05-17

    With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information.

  12. Dissemination of metabolomics results: role of MetaboLights and COSMOS

    PubMed Central

    2013-01-01

    With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information. PMID:23683662

  13. REVIEW ARTICLE: Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes

    NASA Astrophysics Data System (ADS)

    Dunn, Warwick B.

    2008-03-01

    The functional levels of biological cells or organisms can be separated into the genome, transcriptome, proteome and metabolome. Of these the metabolome offers specific advantages to the investigation of the phenotype of biological systems. The investigation of the metabolome (metabolomics) has only recently appeared as a mainstream scientific discipline and is currently developing rapidly for the study of microbial, plant and mammalian metabolomes. The metabolome pipeline or workflow encompasses the processes of sample collection and preparation, collection of analytical data, raw data pre-processing, data analysis and data storage. Of these processes the collection of analytical data will be discussed in this review with specific interest shown in the application of mass spectrometry in the metabolomics pipeline. The current developments in mass spectrometry platforms (GC-MS, LC-MS, DIMS and imaging MS) and applications of specific interest will be highlighted. The current limitations of these platforms and applications will be discussed with areas requiring further development also highlighted. These include the detectable coverage of the metabolome, the identification of metabolites and the process of converting raw data to biological knowledge.

  14. Trophic hierarchies revealed via amino acid isotopic analysis

    USDA-ARS?s Scientific Manuscript database

    Despite the potential of isotopic methods to illuminate trophic function, accurate estimates of lifetime feeding tendencies have remained elusive. A relatively new approach—referred to as compound-specific isotopic analysis (CSIA)—has emerged, centering on the measurement of 15N:14N ratios in amino ...

  15. Counting missing values in a metabolite-intensity data set for measuring the analytical performance of a metabolomics platform.

    PubMed

    Huan, Tao; Li, Liang

    2015-01-20

    Metabolomics requires quantitative comparison of individual metabolites present in an entire sample set. Unfortunately, missing intensity values in one or more samples are very common. Because missing values can have a profound influence on metabolomic results, the extent of missing values found in a metabolomic data set should be treated as an important parameter for measuring the analytical performance of a technique. In this work, we report a study on the scope of missing values and a robust method of filling the missing values in a chemical isotope labeling (CIL) LC-MS metabolomics platform. Unlike conventional LC-MS, CIL LC-MS quantifies the concentration differences of individual metabolites in two comparative samples based on the mass spectral peak intensity ratio of a peak pair from a mixture of differentially labeled samples. We show that this peak-pair feature can be explored as a unique means of extracting metabolite intensity information from raw mass spectra. In our approach, a peak-pair peaking algorithm, IsoMS, is initially used to process the LC-MS data set to generate a CSV file or table that contains metabolite ID and peak ratio information (i.e., metabolite-intensity table). A zero-fill program, freely available from MyCompoundID.org , is developed to automatically find a missing value in the CSV file and go back to the raw LC-MS data to find the peak pair and, then, calculate the intensity ratio and enter the ratio value into the table. Most of the missing values are found to be low abundance peak pairs. We demonstrate the performance of this method in analyzing an experimental and technical replicate data set of human urine metabolome. Furthermore, we propose a standardized approach of counting missing values in a replicate data set as a way of gauging the extent of missing values in a metabolomics platform. Finally, we illustrate that applying the zero-fill program, in conjunction with dansylation CIL LC-MS, can lead to a marked improvement in

  16. The effects of age and dietary restriction on the tissue-specific metabolome of Drosophila

    PubMed Central

    Laye, Matthew J; Tran, ViLinh; Jones, Dean P; Kapahi, Pankaj; Promislow, Daniel E L

    2015-01-01

    Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age-related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease-associated phenotypes. Here, we use high-resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient-rich ad libitum (AL) or nutrient-restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age-related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age. PMID:26085309

  17. Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

    PubMed Central

    Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

    2014-01-01

    Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

  18. Metabolomics and Personalized Medicine.

    PubMed

    Koen, Nadia; Du Preez, Ilse; Loots, Du Toit

    2016-01-01

    Current clinical practice strongly relies on the prognosis, diagnosis, and treatment of diseases using methods determined and averaged for the specific diseased cohort/population. Although this approach complies positively with most patients, misdiagnosis, treatment failure, relapse, and adverse drug effects are common occurrences in many individuals, which subsequently hamper the control and eradication of a number of diseases. These incidences can be explained by individual variation in the genome, transcriptome, proteome, and metabolome of a patient. Various "omics" approaches have investigated the influence of these factors on a molecular level, with the intention of developing personalized approaches to disease diagnosis and treatment. Metabolomics, the newest addition to the "omics" domain and the closest to the observed phenotype, reflects changes occurring at all molecular levels, as well as influences resulting from other internal and external factors. By comparing the metabolite profiles of two or more disease phenotypes, metabolomics can be applied to identify biomarkers related to the perturbation being investigated. These biomarkers can, in turn, be used to develop personalized prognostic, diagnostic, and treatment approaches, and can also be applied to the monitoring of disease progression, treatment efficacy, predisposition to drug-related side effects, and potential relapse. In this review, we discuss the contributions that metabolomics has made, and can potentially still make, towards the field of personalized medicine. © 2016 Elsevier Inc. All rights reserved.

  19. Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies.

    PubMed

    Zaitsu, Kei; Hayashi, Yumi; Kusano, Maiko; Tsuchihashi, Hitoshi; Ishii, Akira

    2016-02-01

    Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided. Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

  20. Advances in laser ablation MC-ICPMS isotopic analysis of rock materials

    NASA Astrophysics Data System (ADS)

    Young, E. D.

    2007-12-01

    Laser ablation multiple-collector inductively coupled plasma-source mass spectrometry (LA-MC-ICPMS) is a rapid method for obtaining high-precision isotope ratio measurements in geological samples. The method has been used with success for measuring isotope ratios of numerous elements, including Pb, Hf, Mg, Si, and Fe in terrestrial and extraterrestrial samples. It fills the gap between the highest precision obtainable with acid digestion together with MC-ICPMS and thermal ionization mass spectrometry (TIMS) and the maximum spatial resolution afforded by secondary ion mass spectrometry (SIMS). Matrix effects have been shown to be negligible for Pb isotopic analysis by LA-MC-ICPMS (Simon et al., 2007). Glass standards NBS 610, 612, and 614 have Pb/matrix ratios spanning two orders of magnitude. Our sample-standard bracketing laser ablation technique gives accurate and precise 208Pb/206Pb and 207Pb/206Pb for these glasses. The accuracy is superior to that obtained when using Tl to correct for mass fractionation. Accuracy and precision (± 0.2 ‰) for Pb in feldspars is comparable to that for double-spike TIMS. Data like these have been used to distinguish distinct sources of magmas in the Long Valley silicic magma system. LA-MC-ICPMS analyses of Mg isotope ratios in calcium-aluminum-rich inclusions (CAIs) from carbonaceous chondrite meteorites have revealed a wealth of new information about the history of these objects. A byproduct of this work has been recognition of the importance of different mass fractionation laws among three isotopes of a given element. Kinetic and equilibrium processes define distinct fractionation laws. Reservoir effects can further modify these laws. The result is that the linear coefficient β that relates the logarithms of the ratios n2/n1 and n3/n1 (ni refers to the number of atoms of isotope i) of isotopes with masses m3 > m2 > m1 is not unique. Rather, it is process dependent. In the case of Mg, this coefficient ranges from 0.521 for

  1. Metabolomics through the lens of precision cardiovascular medicine.

    PubMed

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

    2017-03-20

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

  2. Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis.

    PubMed

    Li, Zihui; Du, Boping; Li, Jing; Zhang, Jinli; Zheng, Xiaojing; Jia, Hongyan; Xing, Aiying; Sun, Qi; Liu, Fei; Zhang, Zongde

    2017-03-01

    Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM. We used 1 H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0. The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM. Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Metabolomics in diabetes, a review.

    PubMed

    Pallares-Méndez, Rigoberto; Aguilar-Salinas, Carlos A; Cruz-Bautista, Ivette; Del Bosque-Plata, Laura

    2016-01-01

    Metabolomics is a promising approach for the identification of chemical compounds that serve for early detection, diagnosis, prediction of therapeutic response and prognosis of disease. Moreover, metabolomics has shown to increase the diagnostic threshold and prediction of type 2 diabetes. Evidence suggests that branched-chain amino acids, acylcarnitines and aromatic amino acids may play an early role on insulin resistance, exposing defects on amino acid metabolism, β-oxidation, and tricarboxylic acid cycle. This review aims to provide a panoramic view of the metabolic shifts that antecede or follow type 2 diabetes. Key messages BCAAs, AAAs and acylcarnitines are strongly associated with early insulin resistance. Diabetes risk prediction has been improved when adding metabolomic markers of dysglycemia to standard clinical and biochemical factors.

  4. The great importance of normalization of LC-MS data for highly-accurate non-targeted metabolomics.

    PubMed

    Mizuno, Hajime; Ueda, Kazuki; Kobayashi, Yuta; Tsuyama, Naohiro; Todoroki, Kenichiro; Min, Jun Zhe; Toyo'oka, Toshimasa

    2017-01-01

    The non-targeted metabolomics analysis of biological samples is very important to understand biological functions and diseases. LC combined with electrospray ionization-based MS has been a powerful tool and widely used for metabolomic analyses. However, the ionization efficiency of electrospray ionization fluctuates for various unexpected reasons such as matrix effects and intraday variations of the instrument performances. To remove these fluctuations, normalization methods have been developed. Such techniques include increasing the sensitivity, separating co-eluting components and normalizing the ionization efficiencies. Normalization techniques allow simultaneously correcting of the ionization efficiencies of the detected metabolite peaks and achieving quantitative non-targeted metabolomics. In this review paper, we focused on these normalization methods for non-targeted metabolomics by LC-MS. Copyright © 2016 John Wiley & Sons, Ltd.

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

    PubMed

    Caldwell, Gary W; Leo, Gregory C

    2017-01-01

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

  6. Metabolomics applied to the pancreatic islet.

    PubMed

    Gooding, Jessica R; Jensen, Mette V; Newgard, Christopher B

    2016-01-01

    Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Applying Metabolomics to differentiate amphibian responses ...

    EPA Pesticide Factsheets

    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

  8. Metabolomic markers of fatigue: Association between circulating metabolome and fatigue in women with chronic widespread pain.

    PubMed

    Freidin, Maxim B; Wells, Helena R R; Potter, Tilly; Livshits, Gregory; Menni, Cristina; Williams, Frances M K

    2018-02-01

    Fatigue is a sensation of unbearable tiredness that frequently accompanies chronic widespread musculoskeletal pain (CWP) and inflammatory joint disease. Its mechanisms are poorly understood and there is a lack of effective biomarkers for diagnosis and onset prediction. We studied the circulating metabolome in a population sample characterised for CWP to identify biomarkers showing specificity for fatigue. Untargeted metabolomic profiling was conducted on fasting plasma and serum samples of 1106 females with and without CWP from the TwinsUK cohort. Linear mixed-effects models accounting for covariates were used to determine relationships between fatigue and metabolites. Receiver operating curve (ROC)-analysis was used to determine predictive value of metabolites for fatigue. While no association between fatigue and metabolites was identified in twins without CWP (n=711), in participants with CWP (n=395), levels of eicosapentaenoate (EPA) ω-3 fatty acid were significantly reduced in those with fatigue (β=-0.452±0.116; p=1.2×10 -4 ). A significant association between fatigue and two other metabolites also emerged when BMI was excluded from the model: 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF), and C-glycosyltryptophan (p=1.5×10 -4 and p=3.1×10 -4 , respectively). ROC analysis has identified a combination of 15 circulating metabolites with good predictive potential for fatigue in CWP (AUC=75%; 95% CI 69-80%). The results of this agnostic metabolomics screening show that fatigue is metabolically distinct from CWP, and is associated with a decrease in circulating levels of EPA. Our panel of circulating metabolites provides the starting point for a diagnostic test for fatigue in CWP. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  9. Women with preterm birth have a distinct cervicovaginal metabolome.

    PubMed

    Ghartey, Jeny; Bastek, Jamie A; Brown, Amy G; Anglim, Laura; Elovitz, Michal A

    2015-06-01

    Metabolomics has the potential to reveal novel pathways involved in the pathogenesis of preterm birth (PTB). The objective of this study was to investigate whether the cervicovaginal (CV) metabolome was different in asymptomatic women destined to have a PTB compared with term birth. A nested case-control study was performed using CV fluid collected from a larger prospective cohort. The CV fluid was collected between 20-24 weeks (V1) and 24-28 weeks (V2). The metabolome was compared between women with a spontaneous PTB (n = 10) to women who delivered at term (n = 10). Samples were extracted and prepared for analysis using a standard extraction solvent method. Global biochemical profiles were determined using gas chromatography/mass spectrometry and ultra-performance liquid chromatography/tandem mass spectrometry. An ANOVA was used to detect differences in biochemical compounds between the groups. A false discovery rate was estimated to account for multiple comparisons. A total of 313 biochemicals were identified in CV fluid. Eighty-two biochemicals were different in the CV fluid at V1 in those destined to have a PTB compared with term birth, whereas 48 were different at V2. Amino acid, carbohydrate, and peptide metabolites were distinct between women with and without PTB. These data suggest that the CV space is metabolically active during pregnancy. Changes in the CV metabolome may be observed weeks, if not months, prior to any clinical symptoms. Understanding the CV metabolome may hold promise for unraveling the pathogenesis of PTB and may provide novel biomarkers to identify women most at risk. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. PROM and Labour Effects on Urinary Metabolome: A Pilot Study

    PubMed Central

    Meloni, Alessandra; Palmas, Francesco; Mereu, Rossella; Deiana, Sara Francesca; Fais, Maria Francesca; Mussap, Michele; Ragusa, Antonio; Pintus, Roberta; Fanos, Vassilios; Melis, Gian Benedetto

    2018-01-01

    Since pathologies and complications occurring during pregnancy and/or during labour may cause adverse outcomes for both newborns and mothers, there is a growing interest in metabolomic applications on pregnancy investigation. In fact, metabolomics has proved to be an efficient strategy for the description of several perinatal conditions. In particular, this study focuses on premature rupture of membranes (PROM) in pregnancy at term. For this project, urine samples were collected at three different clinical conditions: out of labour before PROM occurrence (Ph1), out of labour with PROM (Ph2), and during labour with PROM (Ph3). GC-MS analysis, followed by univariate and multivariate statistical analysis, was able to discriminate among the different classes, highlighting the metabolites most involved in the discrimination. PMID:29511388

  11. Quantitative Metabolomics Reveals an Epigenetic Blueprint for Iron Acquisition in Uropathogenic Escherichia coli

    PubMed Central

    Henderson, Jeffrey P.; Crowley, Jan R.; Pinkner, Jerome S.; Walker, Jennifer N.; Tsukayama, Pablo; Stamm, Walter E.; Hooton, Thomas M.; Hultgren, Scott J.

    2009-01-01

    Bacterial pathogens are frequently distinguished by the presence of acquired genes associated with iron acquisition. The presence of specific siderophore receptor genes, however, does not reliably predict activity of the complex protein assemblies involved in synthesis and transport of these secondary metabolites. Here, we have developed a novel quantitative metabolomic approach based on stable isotope dilution to compare the complement of siderophores produced by Escherichia coli strains associated with intestinal colonization or urinary tract disease. Because uropathogenic E. coli are believed to reside in the gut microbiome prior to infection, we compared siderophore production between urinary and rectal isolates within individual patients with recurrent UTI. While all strains produced enterobactin, strong preferential expression of the siderophores yersiniabactin and salmochelin was observed among urinary strains. Conventional PCR genotyping of siderophore receptors was often insensitive to these differences. A linearized enterobactin siderophore was also identified as a product of strains with an active salmochelin gene cluster. These findings argue that qualitative and quantitative epi-genetic optimization occurs in the E. coli secondary metabolome among human uropathogens. Because the virulence-associated biosynthetic pathways are distinct from those associated with rectal colonization, these results suggest strategies for virulence-targeted therapies. PMID:19229321

  12. Metabolomic evaluation of ginsenosides distribution in Panax genus (Panax ginseng and Panax quinquefolius) using multivariate statistical analysis.

    PubMed

    Pace, Roberto; Martinelli, Ernesto Marco; Sardone, Nicola; D E Combarieu, Eric

    2015-03-01

    Ginseng is any one of the eleven species belonging to the genus Panax of the family Araliaceae and is found in North America and in eastern Asia. Ginseng is characterized by the presence of ginsenosides. Principally Panax ginseng and Panax quinquefolius are the adaptogenic herbs and are commonly distributed as health food markets. In the present study high performance liquid chromatography has been used to identify and quantify ginsenosides in the two subject species and the different parts of the plant (roots, neck, leaves, flowers, fruits). The power of this chromatographic technique to evaluate the identity of botanical material and to distinguishing different part of the plants has been investigated with metabolomic technique such as principal component analysis. Metabolomics provide a good opportunity for mining useful chemical information from the chromatographic data set resulting an important tool for quality evaluation of medicinal plants in the authenticity, consistency and efficacy. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Disruption of TCA Cycle and Glutamate Metabolism Identified by Metabolomics in an In Vitro Model of Amyotrophic Lateral Sclerosis.

    PubMed

    Veyrat-Durebex, Charlotte; Corcia, Philippe; Piver, Eric; Devos, David; Dangoumau, Audrey; Gouel, Flore; Vourc'h, Patrick; Emond, Patrick; Laumonnier, Frédéric; Nadal-Desbarats, Lydie; Gordon, Paul H; Andres, Christian R; Blasco, Hélène

    2016-12-01

    This study aims to develop a cellular metabolomics model that reproduces the pathophysiological conditions found in amyotrophic lateral sclerosis in order to improve knowledge of disease physiology. We used a co-culture model combining the motor neuron-like cell line NSC-34 and the astrocyte clone C8-D1A, with each over-expressing wild-type or G93C mutant human SOD1, to examine amyotrophic lateral sclerosis (ALS) physiology. We focused on the effects of mutant human SOD1 as well as oxidative stress induced by menadione on intracellular metabolism using a metabolomics approach through gas chromatography coupled with mass spectrometry (GC-MS) analysis. Preliminary non-supervised analysis by Principal Component Analysis (PCA) revealed that cell type, genetic environment, and time of culture influenced the metabolomics profiles. Supervised analysis using orthogonal partial least squares discriminant analysis (OPLS-DA) on data from intracellular metabolomics profiles of SOD1 G93C co-cultures produced metabolites involved in glutamate metabolism and the tricarboxylic acid cycle (TCA) cycle. This study revealed the feasibility of using a metabolomics approach in a cellular model of ALS. We identified potential disruption of the TCA cycle and glutamate metabolism under oxidative stress, which is consistent with prior research in the disease. Analysis of metabolic alterations in an in vitro model is a novel approach to investigation of disease physiology.

  14. Zinc stress affects ionome and metabolome in tea plants.

    PubMed

    Zhang, Yinfei; Wang, Yu; Ding, Zhaotang; Wang, Hui; Song, Lubin; Jia, Sisi; Ma, Dexin

    2017-02-01

    The research of physiological responses to Zn stress in plants has been extensively studied. However, the ionomics and metabolomics responses of plants to Zn stress remain largely unknown. In present study, the nutrient elements were identified involved in ion homeostasis and metabolomics changes related to Zn deficiency or excess in tea plants. Nutrient element analysis demonstrated that the concentrations of Zn affected the ion-uptake in roots and the nutrient element transportation to leaves, leading to the different distribution of P, S, Al, Ca, Fe and Cu in the tea leaves or roots. Metabolomics analysis revealed that Zn deficiency or excess differentially influenced the metabolic pathways in the tea leaves. More specifically, Zn deficiency affected the metabolism of carbohydrates, and Zn excess affected flavonoids metabolism. Additionally, the results showed that both Zn deficiency and Zn excess led to reduced nicotinamide levels, which speeded up NAD + degradation and thus reduced energy metabolism. Furthermore, element-metabolite correlation analysis illustrated that Zn contents in the tea leaves were positively correlated with organic acids, nitrogenous metabolites and some carbohydrate metabolites, and negatively correlated with the metabolites involved in secondary metabolism and some other carbohydrate metabolites. Meanwhile, metabolite-metabolite correlation analysis demonstrated that organic acids, sugars, amino acids and flavonoids played dominant roles in the regulation of the tea leaf metabolism under Zn stress. Therefore, the conclusion should be drawn that the tea plants responded to Zn stress by coordinating ion-uptake and regulation of metabolism of carbohydrates, nitrogenous metabolites, and flavonoids. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  15. Conventional and accelerated-solvent extractions of green tea (camellia sinensis) for metabolomics-based chemometrics.

    PubMed

    Kellogg, Joshua J; Wallace, Emily D; Graf, Tyler N; Oberlies, Nicholas H; Cech, Nadja B

    2017-10-25

    Metabolomics has emerged as an important analytical technique for multiple applications. The value of information obtained from metabolomics analysis depends on the degree to which the entire metabolome is present and the reliability of sample treatment to ensure reproducibility across the study. The purpose of this study was to compare methods of preparing complex botanical extract samples prior to metabolomics profiling. Two extraction methodologies, accelerated solvent extraction and a conventional solvent maceration, were compared using commercial green tea [Camellia sinensis (L.) Kuntze (Theaceae)] products as a test case. The accelerated solvent protocol was first evaluated to ascertain critical factors influencing extraction using a D-optimal experimental design study. The accelerated solvent and conventional extraction methods yielded similar metabolite profiles for the green tea samples studied. The accelerated solvent extraction yielded higher total amounts of extracted catechins, was more reproducible, and required less active bench time to prepare the samples. This study demonstrates the effectiveness of accelerated solvent as an efficient methodology for metabolomics studies. Copyright © 2017. Published by Elsevier B.V.

  16. Computational Metabolomics: A Framework for the Million Metabolome

    PubMed Central

    Uppal, Karan; Walker, Douglas I.; Liu, Ken; Li, Shuzhao; Go, Young-Mi; Jones, Dean P.

    2017-01-01

    “Sola dosis facit venenum.” These words of Paracelsus, “the dose makes the poison”, can lead to a cavalier attitude concerning potential toxicities of the vast array of low abundance environmental chemicals to which humans are exposed. Exposome research teaches that 80–85% of human disease is linked to environmental exposures. The human exposome is estimated to include >400,000 environmental chemicals, most of which are uncharacterized with regard to human health. In fact, mass spectrometry measures >200,000 m/z features (ions) in microliter volumes derived from human samples; most are unidentified. This crystallizes a grand challenge for chemical research in toxicology: to develop reliable and affordable analytical methods to understand health impacts of the extensive human chemical experience. To this end, there appears to be no choice but to abandon the limitations of measuring one chemical at a time. The present review looks at progress in computational metabolomics to provide probability based annotation linking ions to known chemicals and serve as a foundation for unambiguous designation of unidentified ions for toxicologic study. We review methods to characterize ions in terms of accurate mass m/z, chromatographic retention time, correlation of adduct, isotopic and fragment forms, association with metabolic pathways and measurement of collision-induced dissociation products, collision cross section, and chirality. Such information can support a largely unambiguous system for documenting unidentified ions in environmental surveillance and human biomonitoring. Assembly of this data would provide a resource to characterize and understand health risks of the array of low-abundance chemicals to which humans are exposed. PMID:27629808

  17. Method for isotopic analysis of chlorinated organic compounds

    DOEpatents

    Holt, Ben D.; Sturchio, Neil C.

    1999-01-01

    The present invention provides a method for preparing a VOC sample for carbon and chlorine isotope ratio analysis by mass spectrometer. A VOC sample is placed in a combustion tube and reacted with CuO to form CO.sub.2 and CuCl. The CO.sub.2 is then extracted and analyzed for the carbon isotope ratio. The CuCl is separated from the excess CuO and reacted with CH.sub.3 I to form CH.sub.3 Cl, extracted and analyzed for chlorine isotope ratio.

  18. Metabolomics of Clostridial Biofuel Production

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rabinowitz, Joshua D; Aristilde, Ludmilla; Amador-Noguez, Daniel

    2015-09-08

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

  19. Light stable isotope analysis of meteorites by ion microprobe

    NASA Technical Reports Server (NTRS)

    Mcsween, Harry Y., Jr.

    1994-01-01

    The main goal was to develop the necessary secondary ion mass spectrometer (SIMS) techniques to use a Cameca ims-4f ion microprobe to measure light stable isotope ratios (H, C, O and S) in situ and in non-conducting mineral phases. The intended application of these techniques was the analysis of meteorite samples, although the techniques that have been developed are equally applicable to the investigation of terrestrial samples. The first year established techniques for the analysis of O isotope ratios (delta O-18 and delta O-17) in conducting mineral phases and the measurement of S isotope ratios (delta S-34) in a variety of sulphide phases. In addition, a technique was developed to measure delta S-34 values in sulphates, which are insulators. Other research undertaken in the first year resulted in SIMS techniques for the measurement of wide variety of trace elements in carbonate minerals, with the aim of understanding the nature of alteration fluids in carbonaceous chondrites. In the second year we developed techniques for analyzing O isotope ratios in nonconducting mineral phases. These methods are potentially applicable to the measurement of other light stable isotopes such as H, C and S in insulators. Also, we have further explored the analytical techniques used for the analysis of S isotopes in sulphides by analyzing troilite in a number of L and H ordinary chondrites. This was done to see if there was any systematic differences with petrological type.

  20. Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis.

    PubMed

    Emwas, Abdul-Hamid; Roy, Raja; McKay, Ryan T; Ryan, Danielle; Brennan, Lorraine; Tenori, Leonardo; Luchinat, Claudio; Gao, Xin; Zeri, Ana Carolina; Gowda, G A Nagana; Raftery, Daniel; Steinbeck, Christoph; Salek, Reza M; Wishart, David S

    2016-02-05

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

  1. Fossil Fuel Combustion-Related Emissions Dominate Atmospheric Ammonia Sources during Severe Haze Episodes: Evidence from (15)N-Stable Isotope in Size-Resolved Aerosol Ammonium.

    PubMed

    Pan, Yuepeng; Tian, Shili; Liu, Dongwei; Fang, Yunting; Zhu, Xiaying; Zhang, Qiang; Zheng, Bo; Michalski, Greg; Wang, Yuesi

    2016-08-02

    The reduction of ammonia (NH3) emissions is urgently needed due to its role in aerosol nucleation and growth causing haze formation during its conversion into ammonium (NH4(+)). However, the relative contributions of individual NH3 sources are unclear, and debate remains over whether agricultural emissions dominate atmospheric NH3 in urban areas. Based on the chemical and isotopic measurements of size-resolved aerosols in urban Beijing, China, we find that the natural abundance of (15)N (expressed using δ(15)N values) of NH4(+) in fine particles varies with the development of haze episodes, ranging from -37.1‰ to -21.7‰ during clean/dusty days (relative humidity: ∼ 40%), to -13.1‰ to +5.8‰ during hazy days (relative humidity: 70-90%). After accounting for the isotope exchange between NH3 gas and aerosol NH4(+), the δ(15)N value of the initial NH3 during hazy days is found to be -14.5‰ to -1.6‰, which indicates fossil fuel-based emissions. These emissions contribute 90% of the total NH3 during hazy days in urban Beijing. This work demonstrates the analysis of δ(15)N values of aerosol NH4(+) to be a promising new tool for partitioning atmospheric NH3 sources, providing policy makers with insights into NH3 emissions and secondary aerosols for regulation in urban environments.

  2. Iron isotope composition of particles produced by UV-femtosecond laser ablation of natural oxides, sulfides, and carbonates.

    PubMed

    d'Abzac, Francois-Xavier; Beard, Brian L; Czaja, Andrew D; Konishi, Hiromi; Schauer, James J; Johnson, Clark M

    2013-12-17

    The need for femtosecond laser ablation (fs-LA) systems coupled to MC-ICP-MS to accurately perform in situ stable isotope analyses remains an open question, because of the lack of knowledge concerning ablation-related isotopic fractionation in this regime. We report the first iron isotope analysis of size-resolved, laser-induced particles of natural magnetite, siderite, pyrrhotite, and pyrite, collected through cascade impaction, followed by analysis by solution nebulization MC-ICP-MS, as well as imaging using electron microscopy. Iron mass distributions are independent of mineralogy, and particle morphology includes both spheres and agglomerates for all ablated phases. X-ray spectroscopy shows elemental fractionation in siderite (C-rich agglomerates) and pyrrhotite/pyrite (S-rich spheres). We find an increase in (56)Fe/(54)Fe ratios of +2‰, +1.2‰, and +0.8‰ with increasing particle size for magnetite, siderite, and pyrrhotite, respectively. Fe isotope differences in size-sorted aerosols from pyrite ablation are not analytically resolvable. Experimental data are discussed using models of particles generation by Hergenröder and elemental/isotopic fractionation by Richter. We interpret the isotopic fractionation to be related to the iron condensation time scale, dependent on its saturation in the gas phase, as a function of mineral composition. Despite the isotopic variations across aerosol size fractions, total aerosol composition, as calculated from mass balance, confirms that fs-LA produces a stoichiometric sampling in terms of isotopic composition. Specifically, both elemental and isotopic fractionation are produced by particle generation processes and not by femtosecond laser-matter interactions. These results provide critical insights into the analytical requirements for laser-ablation-based stable isotope measurements of high-precision and accuracy in geological samples, including the importance of quantitative aerosol transport to the ICP.

  3. ICC-CLASS: isotopically-coded cleavable crosslinking analysis software suite

    PubMed Central

    2010-01-01

    Background Successful application of crosslinking combined with mass spectrometry for studying proteins and protein complexes requires specifically-designed crosslinking reagents, experimental techniques, and data analysis software. Using isotopically-coded ("heavy and light") versions of the crosslinker and cleavable crosslinking reagents is analytically advantageous for mass spectrometric applications and provides a "handle" that can be used to distinguish crosslinked peptides of different types, and to increase the confidence of the identification of the crosslinks. Results Here, we describe a program suite designed for the analysis of mass spectrometric data obtained with isotopically-coded cleavable crosslinkers. The suite contains three programs called: DX, DXDX, and DXMSMS. DX searches the mass spectra for the presence of ion signal doublets resulting from the light and heavy isotopic forms of the isotopically-coded crosslinking reagent used. DXDX searches for possible mass matches between cleaved and uncleaved isotopically-coded crosslinks based on the established chemistry of the cleavage reaction for a given crosslinking reagent. DXMSMS assigns the crosslinks to the known protein sequences, based on the isotopically-coded and un-coded MS/MS fragmentation data of uncleaved and cleaved peptide crosslinks. Conclusion The combination of these three programs, which are tailored to the analytical features of the specific isotopically-coded cleavable crosslinking reagents used, represents a powerful software tool for automated high-accuracy peptide crosslink identification. See: http://www.creativemolecules.com/CM_Software.htm PMID:20109223

  4. Complete Metabolome and Lipidome Analysis Reveals Novel Biomarkers in the Human Diabetic Corneal Stroma

    PubMed Central

    Priyadarsini, Shrestha; McKay, Tina B; Sarker-Nag, Akhee; Allegood, Jeremy; Chalfant, Charles; Ma, Jian-Xing; Karamichos, Dimitrios

    2016-01-01

    Prolonged hyperglycemia during diabetes mellitus can cause severe ophthalmic complications affecting both the anterior and posterior ocular segments leading to impaired vision or blindness. Diabetes-induced corneal pathologies are associated with decreased wound healing capacity, corneal edema, and altered epithelial basement membrane. The mechanism by which diabetes modulates structure and function within the corneal stroma are unknown. In our study, we characterized the effects of diabetes on extracellular matrix, lipid transport, and cellular metabolism by defining the entire metabolome and lipidome of Type 1 and Type 2 human diabetic corneal stroma. Significant increases in Collagen I and III were found in diabetic corneas suggesting that diabetes promotes defects in matrix structure leading to scarring. Furthermore, increased lipid content, including sphingosine-1-phosphate and dihydrosphingosine, in diabetic corneas compared to healthy controls were measured suggesting altered lipid retention. Metabolomics analysis identified elevated tryptophan metabolites, independent of glucose metabolism, which correlated with upregulation of the Kynurenine pathway in diabetic corneas. We also found significant upregulation of novel biomarkers aminoadipic acid, D,L-pipecolic acid, and dihydroorotate. Our study links aberrant tryptophan metabolism to end-stage pathologies associated with diabetes indicating the potential of the Kynurenine pathway as a therapeutic target for inhibiting diabetes-associated defects in the eye. PMID:27742548

  5. The effects of age and dietary restriction on the tissue-specific metabolome of Drosophila.

    PubMed

    Laye, Matthew J; Tran, ViLinh; Jones, Dean P; Kapahi, Pankaj; Promislow, Daniel E L

    2015-10-01

    Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age-related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease-associated phenotypes. Here, we use high-resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient-rich ad libitum (AL) or nutrient-restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age-related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

  6. Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

    PubMed

    Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

    2008-01-01

    Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

  7. Spatially Resolved Genomic, Stable Isotopic, and Lipid Analyses of a Modern Freshwater Microbialite from Cuatro Ciénegas, Mexico

    PubMed Central

    Nitti, Anthony; Daniels, Camille A.; Siefert, Janet; Souza, Valeria; Hollander, David

    2012-01-01

    Abstract Microbialites are biologically mediated carbonate deposits found in diverse environments worldwide. To explore the organisms and processes involved in microbialite formation, this study integrated genomic, lipid, and both organic and inorganic stable isotopic analyses to examine five discrete depth horizons spanning the surface 25 mm of a modern freshwater microbialite from Cuatro Ciénegas, Mexico. Distinct bacterial communities and geochemical signatures were observed in each microbialite layer. Photoautotrophic organisms accounted for approximately 65% of the sequences in the surface community and produced biomass with distinctive lipid biomarker and isotopic (δ13C) signatures. This photoautotrophic biomass was efficiently degraded in the deeper layers by heterotrophic organisms, primarily sulfate-reducing proteobacteria. Two spatially distinct zones of carbonate precipitation were observed within the microbialite, with the first zone corresponding to the phototroph-dominated portion of the microbialite and the second zone associated with the presence of sulfate-reducing heterotrophs. The coupling of photoautotrophic production, heterotrophic decomposition, and remineralization of organic matter led to the incorporation of a characteristic biogenic signature into the inorganic CaCO3 matrix. Overall, spatially resolved multidisciplinary analyses of the microbialite enabled correlations to be made between the distribution of specific organisms, precipitation of carbonate, and preservation of unique lipid and isotopic geochemical signatures. These findings are critical for understanding the formation of modern microbialites and have implications for the interpretation of ancient microbialite records. Key Words: Microbial ecology—Microbe-mineral interactions—Microbial mats—Stromatolites—Genomics. Astrobiology 12, 685–698. PMID:22882001

  8. Metabolome progression during early gut microbial colonization of gnotobiotic mice

    PubMed Central

    Marcobal, Angela; Yusufaly, Tahir; Higginbottom, Steven; Snyder, Michael; Sonnenburg, Justin L.; Mias, George I.

    2015-01-01

    The microbiome has been implicated directly in host health, especially host metabolic processes and development of immune responses. These are particularly important in infants where the gut first begins being colonized, and such processes may be modeled in mice. In this investigation we follow longitudinally the urine metabolome of ex-germ-free mice, which are colonized with two bacterial species, Bacteroides thetaiotaomicron and Bifidobacterium longum. High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series analysis to urine metabolomics data. Results demonstrate both gradual and punctuated changes in metabolite production and that early colonization events profoundly impact the nature of small molecules circulating in the host. The identified small molecules are implicated in amino acid and carbohydrate metabolic processes, and offer insights into the dynamic changes occurring during the colonization process, using high-throughput longitudinal methodology. PMID:26118551

  9. Method for isotopic analysis of chlorinated organic compounds

    DOEpatents

    Holt, B.D.; Sturchio, N.C.

    1999-08-24

    The present invention provides a method for preparing a VOC sample for carbon and chlorine isotope ratio analysis by mass spectrometer. A VOC sample is placed in a combustion tube and reacted with CuO to form CO{sub 2} and CuCl. The CO{sub 2} is then extracted and analyzed for the carbon isotope ratio. The CuCl is separated from the excess CuO and reacted with CH{sub 3}I to form CH{sub 3}Cl, extracted and analyzed for chlorine isotope ratio. 9 figs.

  10. Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells.

    PubMed

    García-Cañaveras, Juan Carlos; López, Silvia; Castell, José Vicente; Donato, M Teresa; Lahoz, Agustín

    2016-02-01

    MS-based metabolite profiling of adherent mammalian cells comprises several challenging steps such as metabolism quenching, cell detachment, cell disruption, metabolome extraction, and metabolite measurement. In LC-MS, the final metabolome coverage is strongly determined by the separation technique and the MS conditions used. Human liver-derived cell line HepG2 was chosen as adherent mammalian cell model to evaluate the performance of several commonly used procedures in both sample processing and LC-MS analysis. In a first phase, metabolite extraction and sample analysis were optimized in a combined manner. To this end, the extraction abilities of five different solvents (or combinations) were assessed by comparing the number and the levels of the metabolites comprised in each extract. Three different chromatographic methods were selected for metabolites separation. A HILIC-based method which was set to specifically separate polar metabolites and two RP-based methods focused on lipidome and wide-ranging metabolite detection, respectively. With regard to metabolite measurement, a Q-ToF instrument operating in both ESI (+) and ESI (-) was used for unbiased extract analysis. Once metabolite extraction and analysis conditions were set up, the influence of cell harvesting on metabolome coverage was also evaluated. Therefore, different protocols for cell detachment (trypsinization or scraping) and metabolism quenching were compared. This study confirmed the inconvenience of trypsinization as a harvesting technique, and the importance of using complementary extraction solvents to extend metabolome coverage, minimizing interferences and maximizing detection, thanks to the use of dedicated analytical conditions through the combination of HILIC and RP separations. The proposed workflow allowed the detection of over 300 identified metabolites from highly polar compounds to a wide range of lipids.

  11. Relationships between digestive efficiency and metabolomic profiles of serum and intestinal contents in chickens.

    PubMed

    Beauclercq, Stéphane; Nadal-Desbarats, Lydie; Hennequet-Antier, Christelle; Gabriel, Irène; Tesseraud, Sophie; Calenge, Fanny; Le Bihan-Duval, Elisabeth; Mignon-Grasteau, Sandrine

    2018-04-27

    The increasing cost of conventional feedstuffs has bolstered interest in genetic selection for digestive efficiency (DE), a component of feed efficiency, assessed by apparent metabolisable energy corrected to zero nitrogen retention (AMEn). However, its measurement is time-consuming and constraining, and its relationship with metabolic efficiency poorly understood. To simplify selection for this trait, we searched for indirect metabolic biomarkers through an analysis of the serum metabolome using nuclear magnetic resonance ( 1 H NMR). A partial least squares (PLS) model including six amino acids and two derivatives from butyrate predicted 59% of AMEn variability. Moreover, to increase our knowledge of the molecular mechanisms controlling DE, we investigated 1 H NMR metabolomes of ileal, caecal, and serum contents by fitting canonical sparse PLS. This analysis revealed strong associations between metabolites and DE. Models based on the ileal, caecal, and serum metabolome respectively explained 77%, 78%, and 74% of the variability of AMEn and its constitutive components (utilisation of starch, lipids, and nitrogen). In our conditions, the metabolites presenting the strongest associations with AMEn were proline in the serum, fumarate in the ileum and glucose in caeca. This study shows that serum metabolomics offers new opportunities to predict chicken DE.

  12. Causal Genetic Variation Underlying Metabolome Differences.

    PubMed

    Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

    2017-08-01

    An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

  13. Counting individual sulfur atoms in a protein by ultrahighresolution Fourier transform ion cyclotron resonance mass spectrometry: Experimental resolution of isotopic fine structure in proteins

    PubMed Central

    Shi, Stone D.-H.; Hendrickson, Christopher L.; Marshall, Alan G.

    1998-01-01

    A typical molecular ion mass spectrum consists of a sum of signals from species of various possible isotopic compositions. Only the monoisotopic peak (e.g., all carbons are 12C; all nitrogens are 14N, etc.) has a unique elemental composition. Every other isotope peak at approximately integer multiples of ∼1 Da higher in nominal mass represents a sum of contributions from isotope combinations differing by a few mDa (e.g., two 13C vs. two 15N vs. one 13C and one 15N vs. 34S, vs. 18O, etc., at ∼2 Da higher in mass than the monoisotopic mass). At sufficiently high mass resolving power, each of these nominal-mass peaks resolves into its isotopic fine structure. Here, we report resolution of the isotopic fine structure of proteins up to 15.8 kDa (isotopic 13C,15N doubly depleted tumor suppressor protein, p16), made possible by electrospray ionization followed by ultrahigh-resolution Fourier transform ion cyclotron resonance mass analysis at 9.4 tesla. Further, a resolving power of m/Δm50% ≈8,000,000 has been achieved on bovine ubiquitin (8.6 kDa). These results represent a 10-fold increase in the highest mass at which isotopic fine structure previously had been observed. Finally, because isotopic fine structure reveals elemental composition directly, it can be used to confirm or determine molecular formula. For p16, for example, we were able to determine (5.1 ± 0.3) the correct number (five) of sulfur atoms solely from the abundance ratio of the resolved 34S peak to the monoisotopic peak. PMID:9751700

  14. New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report.

    PubMed

    Bowler, Russell P; Wendt, Chris H; Fessler, Michael B; Foster, Matthew W; Kelly, Rachel S; Lasky-Su, Jessica; Rogers, Angela J; Stringer, Kathleen A; Winston, Brent W

    2017-12-01

    This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

  15. Identification and Profiling of Specialized Pro-Resolving Mediators in Human Tears by Lipid Mediator Metabolomics.

    PubMed

    English, Justin T; Norris, Paul C; Hodges, Robin R; Dartt, Darlene A; Serhan, Charles N

    2017-02-01

    Specialized pro-resolving mediators (SPM), e.g. Resolvin D1, Protectin D1, Lipoxin A₄, and Resolvin E1 have each shown to be active in ocular models reducing inflammation. In general, SPMs have specific agonist functions that stimulate resolution of infection and inflammation in animal disease models. The presence and quantity of SPM in human emotional tears is of interest. Here, utilizing a targeted LC-MS-MS metabololipidomics based approach we document the identification of pro-inflammatory (Prostaglandins and Leukotriene B₄) and pro-resolving lipid mediators (D-series Resolvins, Protectin D1, and Lipoxin A₄) in human emotional tears from 12 healthy individuals. SPMs from the Maresin family (Maresin 1 and Maresin 2) were not present in these samples. Principal Component Analysis (PCA) revealed gender differences in the production of specific mediators within these tear samples as the SPMs were essentially absent in these female donors. These results indicate that specific SPM signatures are present in human emotional tears at concentrations known to be bioactive. Moreover, they will help to further appreciate the mechanisms of production and action of SPMs in the eye, as well as their physiologic roles in human ocular disease resolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Challenges of metabolomics in human gut microbiota research.

    PubMed

    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.

  17. Adjoint Sensitivity Analysis for Scale-Resolving Turbulent Flow Solvers

    NASA Astrophysics Data System (ADS)

    Blonigan, Patrick; Garai, Anirban; Diosady, Laslo; Murman, Scott

    2017-11-01

    Adjoint-based sensitivity analysis methods are powerful design tools for engineers who use computational fluid dynamics. In recent years, these engineers have started to use scale-resolving simulations like large-eddy simulations (LES) and direct numerical simulations (DNS), which resolve more scales in complex flows with unsteady separation and jets than the widely-used Reynolds-averaged Navier-Stokes (RANS) methods. However, the conventional adjoint method computes large, unusable sensitivities for scale-resolving simulations, which unlike RANS simulations exhibit the chaotic dynamics inherent in turbulent flows. Sensitivity analysis based on least-squares shadowing (LSS) avoids the issues encountered by conventional adjoint methods, but has a high computational cost even for relatively small simulations. The following talk discusses a more computationally efficient formulation of LSS, ``non-intrusive'' LSS, and its application to turbulent flows simulated with a discontinuous-Galkerin spectral-element-method LES/DNS solver. Results are presented for the minimal flow unit, a turbulent channel flow with a limited streamwise and spanwise domain.

  18. Comparison of subacute effects of two types of pyrethroid insecticides using metabolomics methods.

    PubMed

    Miao, Jiyan; Wang, Dezhen; Yan, Jin; Wang, Yao; Teng, Miaomiao; Zhou, Zhiqiang; Zhu, Wentao

    2017-11-01

    In this study, 1 H NMR based metabolomics analysis, LC-MS/MS based serum metabolomics and histopathology techniques were used to investigate the toxic effects of subacute exposure to two types of pyrethroid insecticides bifenthrin and lambda-cyhalothrin in mice. Metabolomic analysis of tissues extracts and serum showed that these two types of pyrethroid insecticides resulted in alterations of metabolites in the liver, kidney and serum of mice. Based on the altered metabolites, several significant pathways were identified, which are associated with gut microbial metabolism, lipid metabolism, nucleotide catabolism, tyrosine metabolism and energy metabolism. The results showed that bifenthrin and lambda-cyhalothrin have similarities in disruption of metabolic pathways in kidney, indicating that the toxicological mechanisms of these two types of insecticides have some likeness to each other. This study may provide novel insight into revealing differences of toxicological mechanisms between these two types of pyrethroid insecticides. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Brain Injury Alters Volatile Metabolome

    PubMed Central

    Cohen, Akiva S.; Gordon, Amy R.; Opiekun, Maryanne; Martin, Talia; Elkind, Jaclynn; Lundström, Johan N.; Beauchamp, Gary K.

    2016-01-01

    Chemical signals arising from body secretions and excretions communicate information about health status as have been reported in a range of animal models of disease. A potential common pathway for diseases to alter chemical signals is via activation of immune function—which is known to be intimately involved in modulation of chemical signals in several species. Based on our prior findings that both immunization and inflammation alter volatile body odors, we hypothesized that injury accompanied by inflammation might correspondingly modify the volatile metabolome to create a signature endophenotype. In particular, we investigated alteration of the volatile metabolome as a result of traumatic brain injury. Here, we demonstrate that mice could be trained in a behavioral assay to discriminate mouse models subjected to lateral fluid percussion injury from appropriate surgical sham controls on the basis of volatile urinary metabolites. Chemical analyses of the urine samples similarly demonstrated that brain injury altered urine volatile profiles. Behavioral and chemical analyses further indicated that alteration of the volatile metabolome induced by brain injury and alteration resulting from lipopolysaccharide-associated inflammation were not synonymous. Monitoring of alterations in the volatile metabolome may be a useful tool for rapid brain trauma diagnosis and for monitoring recovery. PMID:26926034

  20. Reprogramming the metabolome rescues retinal degeneration.

    PubMed

    Park, Karen Sophia; Xu, Christine L; Cui, Xuan; Tsang, Stephen H

    2018-05-01

    Metabolomics studies in the context of ophthalmology have largely focused on identifying metabolite concentrations that characterize specific retinal diseases. Studies involving mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have shown that individuals suffering from retinal diseases exhibit metabolic profiles that markedly differ from those of control individuals, supporting the notion that metabolites may serve as easily identifiable biomarkers for specific conditions. An emerging branch of metabolomics resulting from biomarker studies, however, involves the study of retinal metabolic dysfunction as causes of degeneration. Recent publications have identified a number of metabolic processes-including but not limited to glucose and oxygen metabolism-that, when perturbed, play a role in the degeneration of photoreceptor cells. As a result, such studies have led to further research elucidating methods for prolonging photoreceptor survival in an effort to halt degeneration in its early stages. This review will explore the ways in which metabolomics has deepened our understanding of the causes of retinal degeneration and discuss how metabolomics can be used to prevent retinal degeneration from progressing to its later disease stages.

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

    PubMed

    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.

  2. Metabolomic and proteomic analysis of D-lactate-producing Lactobacillus delbrueckii under various fermentation conditions.

    PubMed

    Liang, Shaoxiong; Gao, Dacheng; Liu, Huanhuan; Wang, Cheng; Wen, Jianping

    2018-05-28

    As an important feedstock monomer for the production of biodegradable stereo-complex poly-lactic acid polymer, D-lactate has attracted much attention. To improve D-lactate production by microorganisms such as Lactobacillus delbrueckii, various fermentation conditions were performed, such as the employment of anaerobic fermentation, the utilization of more suitable neutralizing agents, and exploitation of alternative nitrogen sources. The highest D-lactate titer could reach 133 g/L under the optimally combined fermentation condition, increased by 70.5% compared with the control. To decipher the potential mechanisms of D-lactate overproduction, the time-series response of intracellular metabolism to different fermentation conditions was investigated by GC-MS and LC-MS/MS-based metabolomic analysis. Then the metabolomic datasets were subjected to weighted correlation network analysis (WGCNA), and nine distinct metabolic modules and eight hub metabolites were identified to be specifically associated with D-lactate production. Moreover, a quantitative iTRAQ-LC-MS/MS proteomic approach was employed to further analyze the change of intracellular metabolism under the combined fermentation condition, identifying 97 up-regulated and 42 down-regulated proteins compared with the control. The in-depth analysis elucidated how the key factors exerted influence on D-lactate biosynthesis. The results revealed that glycolysis and pentose phosphate pathways, transport of glucose, amino acids and peptides, amino acid metabolism, peptide hydrolysis, synthesis of nucleotides and proteins, and cell division were all strengthened, while ATP consumption for exporting proton, cell damage, metabolic burden caused by stress response, and bypass of pyruvate were decreased under the combined condition. These might be the main reasons for significantly improved D-lactate production. These findings provide the first omics view of cell growth and D-lactate overproduction in L. delbrueckii, which

  3. The Human Blood Metabolome-Transcriptome Interface

    PubMed Central

    Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

    2015-01-01

    Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

  4. The longitudinal cerebrospinal fluid metabolomic profile of amyotrophic lateral sclerosis

    PubMed Central

    Gray, Elizabeth; Larkin, James R.; Claridge, Tim D. W.; Talbot, Kevin; Sibson, Nicola R.; Turner, Martin R.

    2015-01-01

    Neurochemical biomarkers are urgently sought in ALS. Metabolomic analysis of cerebrospinal fluid (CSF) using proton nuclear magnetic resonance (1H-NMR) spectroscopy is a highly sensitive method capable of revealing nervous system cellular pathology. The 1H-NMR CSF metabolomic signature of ALS was sought in a longitudinal cohort. Six-monthly serial collection was performed in ALS patients across a range of clinical sub-types (n = 41) for up to two years, and in healthy controls at a single time-point (n = 14). A multivariate statistical approach, partial least squares discriminant analysis, was used to determine differences between the NMR spectra from patients and controls. Significantly predictive models were found using those patients with at least one year's interval between recruitment and the second sample. Glucose, lactate, citric acid and, unexpectedly, ethanol were the discriminating metabolites elevated in ALS. It is concluded that 1H-NMR captured the CSF metabolomic signature associated with derangements in cellular energy utilization connected with ALS, and was most prominent in comparisons using patients with longer disease duration. The specific metabolites identified support the concept of a hypercatabolic state, possibly involving mitochondrial dysfunction specifically. Endogenous ethanol in the CSF may be an unrecognized novel marker of neuronal tissue injury in ALS. PMID:26121274

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

    PubMed

    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.

  6. Biometrics from the carbon isotope ratio analysis of amino acids in human hair.

    PubMed

    Jackson, Glen P; An, Yan; Konstantynova, Kateryna I; Rashaid, Ayat H B

    2015-01-01

    This study compares and contrasts the ability to classify individuals into different grouping factors through either bulk isotope ratio analysis or amino-acid-specific isotope ratio analysis of human hair. Using LC-IRMS, we measured the isotope ratios of 14 amino acids in hair proteins independently, and leucine/isoleucine as a co-eluting pair, to provide 15 variables for classification. Multivariate analysis confirmed that the essential amino acids and non-essential amino acids were mostly independent variables in the classification rules, thereby enabling the separation of dietary factors of isotope intake from intrinsic or phenotypic factors of isotope fractionation. Multivariate analysis revealed at least two potential sources of non-dietary factors influencing the carbon isotope ratio values of the amino acids in human hair: body mass index (BMI) and age. These results provide evidence that compound-specific isotope ratio analysis has the potential to go beyond region-of-origin or geospatial movements of individuals-obtainable through bulk isotope measurements-to the provision of physical and characteristic traits about the individuals, such as age and BMI. Further development and refinement, for example to genetic, metabolic, disease and hormonal factors could ultimately be of great assistance in forensic and clinical casework. Copyright © 2014 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

  7. Resolvent analysis of exact coherent solutions

    NASA Astrophysics Data System (ADS)

    Rosenberg, Kevin; McKeon, Beverley

    2017-11-01

    Exact coherent solutions have been hypothesized to constitute the state-space skeleton of turbulent trajectories and thus are of interest as a means to better understand the underlying dynamics of turbulent flows. An asymptotic description of how these types of solutions self-sustain was provided by Hall & Sherwin. Here we offer a fully-nonlinear perspective on the self-sustainment of these solutions in terms of triadic scale interactions and use the resolvent framework of McKeon & Sharma to interpret these results from an input/output point of view. We analyze traveling wave solutions and periodic orbits in channel flow, and demonstrate how resolvent analysis can be used to obtain low-dimensional representations of these flows. We gratefully acknowledge funding from the AFOSR (FA9550-16-1-0361) and J.S. Park, M.D. Graham, and J.F. Gibson for providing data for the ECS solutions.

  8. Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.

    PubMed

    Georgii, Elisabeth; Jin, Ming; Zhao, Jin; Kanawati, Basem; Schmitt-Kopplin, Philippe; Albert, Andreas; Winkler, J Barbro; Schäffner, Anton R

    2017-07-10

    Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response. In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways. Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome

  9. Metabolomics Analysis of the Toxic Effects of the Production of Lycopene and Its Precursors.

    PubMed

    Miguez, April M; McNerney, Monica P; Styczynski, Mark P

    2018-01-01

    Using cells as microbial factories enables highly specific production of chemicals with many advantages over chemical syntheses. A number of exciting new applications of this approach are in the area of precision metabolic engineering, which focuses on improving the specificity of target production. In recent work, we have used precision metabolic engineering to design lycopene-producing Escherichia coli for use as a low-cost diagnostic biosensor. To increase precursor availability and thus the rate of lycopene production, we heterologously expressed the mevalonate pathway. We found that simultaneous induction of these pathways increases lycopene production, but induction of the mevalonate pathway before induction of the lycopene pathway decreases both lycopene production and growth rate. Here, we aim to characterize the metabolic changes the cells may be undergoing during expression of either or both of these heterologous pathways. After establishing an improved method for quenching E. coli for metabolomics analysis, we used two-dimensional gas chromatography coupled to mass spectrometry (GCxGC-MS) to characterize the metabolomic profile of our lycopene-producing strains in growth conditions characteristic of our biosensor application. We found that the metabolic impacts of producing low, non-toxic levels of lycopene are of much smaller magnitude than the typical metabolic changes inherent to batch growth. We then used metabolomics to study differences in metabolism caused by the time of mevalonate pathway induction and the presence of the lycopene biosynthesis genes. We found that overnight induction of the mevalonate pathway was toxic to cells, but that the cells could recover if the lycopene pathway was not also heterologously expressed. The two pathways appeared to have an antagonistic metabolic effect that was clearly reflected in the cells' metabolic profiles. The metabolites homocysteine and homoserine exhibited particularly interesting behaviors and may be

  10. Metabolomics in transfusion medicine.

    PubMed

    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.

  11. Ultrasound: a subexploited tool for sample preparation in metabolomics.

    PubMed

    Luque de Castro, M D; Delgado-Povedano, M M

    2014-01-02

    Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Particular geoscientific perspectives on stable isotope analysis in the arboreal system

    NASA Astrophysics Data System (ADS)

    Helle, Gerhard; Balting, Daniel; Pauly, Maren; Slotta, Franziska

    2017-04-01

    parameters. However, millennial or multi-millennial high quality reconstructions from tree ring isotopes are still rare. This is because of i) methodological constraints related to mass spectrometric analyses and ii) the nature of tree-ring chronologies that are put together by many trees of various individual ages. In view of this: What is the state-of-the-art in high throughput tree ring stable isotope analyses? Is it necessary to advance existing methodologies further to conserve the annual time resolution provided by the tree-ring archive? Other terrestrial archives, like lake sediments and speleothems rarely provide annually resolved stable isotope data. Furthermore, certain tree species from tropical or sub-tropical regions cannot be dated properly by dendrochronology and hence demand specific stable isotope measuring strategies, etc.. Although the points raised here do specifically apply for the tree ring archive, some of them are important for all proxy archives of organic origin.

  13. Metabolomics enables precision medicine: "A White Paper, Community Perspective".

    PubMed

    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

    stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our

  14. Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

    PubMed Central

    He, Xiangyi; Zhong, Jie; Wang, Shuwei; Zhou, Yufen; Wang, Lei; Zhang, Yongping; Yuan, Yaozong

    2017-01-01

    To establish a screening strategy for pancreatic cancer (PC) based on new-onset diabetic mellitus (NO-DM), serum metabolomics analysis and a search for the metabolic pathways associated with PC related DM were performed. Serum samples from patients with NO-DM (n = 30) and patients with pancreatic cancer and NO-DM were examined by liquid chromatography-mass spectrometry. Data were analyzed using principal components analysis (PCA) and orthogonal projection to latent structures (OPLS) of the most significant metabolites. The diagnostic model was constructed using logistic regression analysis. Metabolic pathways were analyzed using the web-based tool MetPA. PC patients with NO-DM were older and had a lower BMI and shorter duration of DM than those with NO-DM. The metabolomic profiles of patients with PC and NO-DM were significantly different from those of patients with NO-DM in the PCA and OPLS models. Sixty two differential metabolites were identified by the OPLS model. The logistic regression model using a panel of two metabolites including N_Succinyl_L_diaminopimelic_acid and PE (18:2) had high sensitivity (93.3%) and specificity (93.1%) for PC. The top three metabolic pathways associated with PC related DM were valine, leucine and isoleucine biosynthesis and degradation, primary bile acid biosynthesis, and sphingolipid metabolism. In conclusion, screening for PC based on NO-DM using serum metabolomics in combination with clinic characteristics and CA19-9 is a potential useful strategy. Several metabolic pathways differed between PC related DM and type 2 DM. PMID:28418859

  15. Metabolomics and Trace Element Analysis of Camel Tear by GC-MS and ICP-MS.

    PubMed

    Ahamad, Syed Rizwan; Raish, Mohammad; Yaqoob, Syed Hilal; Khan, Altaf; Shakeel, Faiyaz

    2017-06-01

    Camel tear metabolomics and elemental analysis are useful in getting the information regarding the components responsible for maintaining the protective system that allows living in the desert and dry regions. The aim of this study was to correlate that the camel tears can be used as artificial tears for the evaluation of dryness in the eye. Eye biomarkers of camel tears were analyzed by gas chromatography-mass spectroscopy (GC-MS) and inductively coupled plasma mass spectroscopy (ICP-MS). The major compounds detected in camel tears by GC-MS were alanine, valine, leucine, norvaline, glycine, cadaverine, urea, ribitol, sugars, and higher fatty acids like octadecanoic acid and hexadecanoic acid. GC-MS analysis of camel tears also finds several products of metabolites and its associated metabolic participants. ICP-MS analysis showed the presence of different concentration of elemental composition in the camel tears.

  16. Metabolome analysis reveals the effect of carbon catabolite control on the poly(γ-glutamic acid) biosynthesis of Bacillus licheniformis ATCC 9945.

    PubMed

    Mitsunaga, Hitoshi; Meissner, Lena; Palmen, Thomas; Bamba, Takeshi; Büchs, Jochen; Fukusaki, Eiichiro

    2016-04-01

    Poly(γ-glutamic acid) (PGA) is a polymer composed of L- and/or D-glutamic acids that is produced by Bacillus sp. Because the polymer has various features as water soluble, edible, non-toxic and so on, it has attracted attention as a candidate for many applications such as foods, cosmetics and so on. However, although it is well known that the intracellular metabolism of Bacillus sp. is mainly regulated by catabolite control, the effect of the catabolite control on the PGA producing Bacillus sp. is largely unknown. This study is the first report of metabolome analysis on the PGA producing Bacillus sp. that reveals the effect of carbon catabolite control on the metabolism of PGA producing Bacillus licheniformis ATCC 9945. Results showed that the cells cultivated in glycerol-containing medium showed higher PGA production than the cells in glucose-containing medium. Furthermore, metabolome analysis revealed that the activators of CcpA and CodY, global regulatory proteins of the intracellular metabolism, accumulated in the cells cultivated in glycerol-containing and glucose-containing medium, respectively, with CodY apparently inhibiting PGA production. Moreover, the cells seemed to produce glutamate from citrate and ammonium using glutamine synthetase/glutamate synthase. Pulsed addition of di-ammonium hydrogen citrate, as suggested by the metabolome result, was able to achieve the highest value so far for PGA production in B. licheniformis. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  17. Serum Metabolomic Profiling in Acute Alcoholic Hepatitis Identifies Multiple Dysregulated Pathways

    PubMed Central

    Rachakonda, Vikrant; Gabbert, Charles; Raina, Amit; Bell, Lauren N.; Cooper, Sara; Malik, Shahid; Behari, Jaideep

    2014-01-01

    Background and Objectives While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH), the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. Methods This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. Results Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA) cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. Conclusion Severe AAH is

  18. Comparative proteomic and metabolomic analysis of Streptomyces tsukubaensis reveals the metabolic mechanism of FK506 overproduction by feeding soybean oil.

    PubMed

    Wang, Jun; Liu, Huanhuan; Huang, Di; Jin, Lina; Wang, Cheng; Wen, Jianping

    2017-03-01

    FK506 (tacrolimus) is a 23-membered polyketide macrolide that possesses powerful immunosuppressant activity. In this study, feeding soybean oil into the fermentation culture of Streptomyces tsukubaensis improved FK506 production by 88.8%. To decipher the overproduction mechanism, comparative proteomic and metabolomic analysis was carried out. A total of 72 protein spots with differential expression in the two-dimensional gel electrophoresis (2-DE) were identified by matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF-MS), and 66 intracellular metabolites were measured by gas chromatography-mass spectrometer (GC-MS). The analysis of proteome and metabolome indicated that feeding soybean oil as a supplementary carbon source could not only strengthen the FK506 precursor metabolism and energy metabolism but also tune the pathways related to transcriptional regulation, translation, and stress response, suggesting a better intracellular metabolic environment for the synthesis of FK506. Based on these analyses, 20 key metabolites and precursors of FK506 were supplemented into the soybean oil medium. Among them, lysine, citric acid, shikimic acid, and malonic acid performed excellently for promoting the FK506 production and biomass. Especially, the addition of malonic acid achieved the highest FK506 production, which was 1.56-fold of that in soybean oil medium and 3.05-fold of that in initial medium. This report represented the first comprehensive study on the comparative proteomics and metabolomics applied in S. tsukubaensis, and it would be a rational guidance to further strengthen the FK506 production.

  19. The Role of Mass Spectrometry-Based Metabolomics in Medical Countermeasures Against Radiation

    PubMed Central

    Patterson, Andrew D.; Lanz, Christian; Gonzalez, Frank J.; Idle, Jeffrey R.

    2013-01-01

    Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry (CMCR) was established to develop field-deployable biodosimeters based, in principle, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter. PMID:19890938

  20. Online stable isotope analysis of dissolved organic carbon size classes using size exclusion chromatography coupled to an isotope ratio mass spectrometer.

    PubMed

    Malik, Ashish; Scheibe, Andrea; LokaBharathi, P A; Gleixner, Gerd

    2012-09-18

    Stable isotopic content of dissolved organic carbon (δ(13)C-DOC) provides valuable information on its origin and fate. In an attempt to get additional insights into DOC cycling, we developed a method for δ(13)C measurement of DOC size classes by coupling high-performance liquid chromatography (HPLC)-size exclusion chromatography (SEC) to online isotope ratio mass spectrometry (IRMS). This represents a significant methodological contribution to DOC research. The interface was evaluated using various organic compounds, thoroughly tested with soil-water from a C3-C4 vegetation change experiment, and also applied to riverine and marine DOC. δ(13)C analysis of standard compounds resulted in excellent analytical precision (≤0.3‰). Chromatography resolved soil DOC into 3 fractions: high molecular weight (HMW; 0.4-10 kDa), low molecular weight (LMW; 50-400 Da), and retained (R) fraction. Sample reproducibility for measurement of δ(13)C-DOC size classes was ±0.25‰ for HMW fraction, ± 0.54‰ for LMW fraction, and ±1.3‰ for R fraction. The greater variance in δ(13)C values of the latter fractions was due to their lower concentrations. The limit of quantification (SD ≤0.6‰) for each size fraction measured as a peak is 200 ng C (2 mg C/L). δ(13)C-DOC values obtained in SEC mode correlated significantly with those obtained without column in the μEA mode (p < 0.001, intercept 0.17‰), which rules out SEC-associated isotopic effects or DOC loss. In the vegetation change experiment, fractions revealed a clear trend in plant contribution to DOC; those in deeper soils and smaller size fractions had less plant material. It was also demonstrated that the technique can be successfully applied to marine and riverine DOC without further sample pretreatment.

  1. The human plasma-metabolome: Reference values in 800 French healthy volunteers; impact of cholesterol, gender and age

    PubMed Central

    Al-Salameh, Abdallah; Croixmarie, Vincent; Masson, Perrine; Corruble, Emmanuelle; Fève, Bruno; Colle, Romain; Ripoll, Laurent; Walther, Bernard; Boursier-Neyret, Claire; Werner, Erwan; Becquemont, Laurent; Chanson, Philippe

    2017-01-01

    Metabolomic approaches are increasingly used to identify new disease biomarkers, yet normal values of many plasma metabolites remain poorly defined. The aim of this study was to define the “normal” metabolome in healthy volunteers. We included 800 French volunteers aged between 18 and 86, equally distributed according to sex, free of any medication and considered healthy on the basis of their medical history, clinical examination and standard laboratory tests. We quantified 185 plasma metabolites, including amino acids, biogenic amines, acylcarnitines, phosphatidylcholines, sphingomyelins and hexose, using tandem mass spectrometry with the Biocrates AbsoluteIDQ p180 kit. Principal components analysis was applied to identify the main factors responsible for metabolome variability and orthogonal projection to latent structures analysis was employed to confirm the observed patterns and identify pattern-related metabolites. We established a plasma metabolite reference dataset for 144/185 metabolites. Total blood cholesterol, gender and age were identified as the principal factors explaining metabolome variability. High total blood cholesterol levels were associated with higher plasma sphingomyelins and phosphatidylcholines concentrations. Compared to women, men had higher concentrations of creatinine, branched-chain amino acids and lysophosphatidylcholines, and lower concentrations of sphingomyelins and phosphatidylcholines. Elderly healthy subjects had higher sphingomyelins and phosphatidylcholines plasma levels than young subjects. We established reference human metabolome values in a large and well-defined population of French healthy volunteers. This study provides an essential baseline for defining the “normal” metabolome and its main sources of variation. PMID:28278231

  2. The human plasma-metabolome: Reference values in 800 French healthy volunteers; impact of cholesterol, gender and age.

    PubMed

    Trabado, Séverine; Al-Salameh, Abdallah; Croixmarie, Vincent; Masson, Perrine; Corruble, Emmanuelle; Fève, Bruno; Colle, Romain; Ripoll, Laurent; Walther, Bernard; Boursier-Neyret, Claire; Werner, Erwan; Becquemont, Laurent; Chanson, Philippe

    2017-01-01

    Metabolomic approaches are increasingly used to identify new disease biomarkers, yet normal values of many plasma metabolites remain poorly defined. The aim of this study was to define the "normal" metabolome in healthy volunteers. We included 800 French volunteers aged between 18 and 86, equally distributed according to sex, free of any medication and considered healthy on the basis of their medical history, clinical examination and standard laboratory tests. We quantified 185 plasma metabolites, including amino acids, biogenic amines, acylcarnitines, phosphatidylcholines, sphingomyelins and hexose, using tandem mass spectrometry with the Biocrates AbsoluteIDQ p180 kit. Principal components analysis was applied to identify the main factors responsible for metabolome variability and orthogonal projection to latent structures analysis was employed to confirm the observed patterns and identify pattern-related metabolites. We established a plasma metabolite reference dataset for 144/185 metabolites. Total blood cholesterol, gender and age were identified as the principal factors explaining metabolome variability. High total blood cholesterol levels were associated with higher plasma sphingomyelins and phosphatidylcholines concentrations. Compared to women, men had higher concentrations of creatinine, branched-chain amino acids and lysophosphatidylcholines, and lower concentrations of sphingomyelins and phosphatidylcholines. Elderly healthy subjects had higher sphingomyelins and phosphatidylcholines plasma levels than young subjects. We established reference human metabolome values in a large and well-defined population of French healthy volunteers. This study provides an essential baseline for defining the "normal" metabolome and its main sources of variation.

  3. Two-Phase Extraction for Comprehensive Analysis of the Plant Metabolome by NMR.

    PubMed

    Schripsema, Jan; Dagnino, Denise

    2018-01-01

    Metabolomics is the area of research, which strives to obtain complete metabolic fingerprints, to detect differences between them, and to provide hypothesis to explain those differences [1]. But obtaining complete metabolic fingerprints is not an easy task. Metabolite extraction is a key step during this process, and much research has been devoted to finding the best solvent mixture to extract as much metabolites as possible.Here a procedure is described for analysis of both polar and apolar metabolites using a two-phase extraction system. D 2 O and CDCl 3 are the solvents of choice, and their major advantage is that, for the identification of the compounds, standard databases can be used because D 2 O and CDCl 3 are the solvents most commonly used for pure compound NMR spectra. The procedure enables the absolute quantification of components via the addition of suitable internal standards. The extracts are also suitable for further analysis with other systems like LC-MS or GC-MS.

  4. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    PubMed

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Metabolomic analysis of urine samples by UHPLC-QTOF-MS: Impact of normalization strategies.

    PubMed

    Gagnebin, Yoric; Tonoli, David; Lescuyer, Pierre; Ponte, Belen; de Seigneux, Sophie; Martin, Pierre-Yves; Schappler, Julie; Boccard, Julien; Rudaz, Serge

    2017-02-22

    Among the various biological matrices used in metabolomics, urine is a biofluid of major interest because of its non-invasive collection and its availability in large quantities. However, significant sources of variability in urine metabolomics based on UHPLC-MS are related to the analytical drift and variation of the sample concentration, thus requiring normalization. A sequential normalization strategy was developed to remove these detrimental effects, including: (i) pre-acquisition sample normalization by individual dilution factors to narrow the concentration range and to standardize the analytical conditions, (ii) post-acquisition data normalization by quality control-based robust LOESS signal correction (QC-RLSC) to correct for potential analytical drift, and (iii) post-acquisition data normalization by MS total useful signal (MSTUS) or probabilistic quotient normalization (PQN) to prevent the impact of concentration variability. This generic strategy was performed with urine samples from healthy individuals and was further implemented in the context of a clinical study to detect alterations in urine metabolomic profiles due to kidney failure. In the case of kidney failure, the relation between creatinine/osmolality and the sample concentration is modified, and relying only on these measurements for normalization could be highly detrimental. The sequential normalization strategy was demonstrated to significantly improve patient stratification by decreasing the unwanted variability and thus enhancing data quality. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Metabolome Profiling of Partial and Fully Reprogrammed Induced Pluripotent Stem Cells.

    PubMed

    Park, Soon-Jung; Lee, Sang A; Prasain, Nutan; Bae, Daekyeong; Kang, Hyunsu; Ha, Taewon; Kim, Jong Soo; Hong, Ki-Sung; Mantel, Charlie; Moon, Sung-Hwan; Broxmeyer, Hal E; Lee, Man Ryul

    2017-05-15

    Acquisition of proper metabolomic fate is required to convert somatic cells toward fully reprogrammed pluripotent stem cells. The majority of induced pluripotent stem cells (iPSCs) are partially reprogrammed and have a transcriptome different from that of the pluripotent stem cells. The metabolomic profile and mitochondrial metabolic functions required to achieve full reprogramming of somatic cells to iPSC status have not yet been elucidated. Clarification of the metabolites underlying reprogramming mechanisms should enable further optimization to enhance the efficiency of obtaining fully reprogrammed iPSCs. In this study, we characterized the metabolites of human fully reprogrammed iPSCs, partially reprogrammed iPSCs, and embryonic stem cells (ESCs). Using capillary electrophoresis time-of-flight mass spectrometry-based metabolomics, we found that 89% of analyzed metabolites were similarly expressed in fully reprogrammed iPSCs and human ESCs (hESCs), whereas partially reprogrammed iPSCs shared only 74% similarly expressed metabolites with hESCs. Metabolomic profiling analysis suggested that converting mitochondrial respiration to glycolytic flux is critical for reprogramming of somatic cells into fully reprogrammed iPSCs. This characterization of metabolic reprogramming in iPSCs may enable the development of new reprogramming parameters for enhancing the generation of fully reprogrammed human iPSCs.

  7. Metabolomic characterization of laborers exposed to welding fumes.

    PubMed

    Wang, Kuo-Ching; Kuo, Ching-Hua; Tian, Tze-Feng; Tsai, Mong-Hsun; Chiung, Yin-Mei; Hsiech, Chun-Ming; Tsai, Sung-Jeng; Wang, San-Yuan; Tsai, Dong-Ming; Huang, Chiang-Ching; Tseng, Y Jane

    2012-03-19

    The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders. © 2012 American

  8. High-resolution isotope measurements resolve rapid ecohydrological dynamics at the soil-plant interface.

    PubMed

    Volkmann, Till H M; Haberer, Kristine; Gessler, Arthur; Weiler, Markus

    2016-05-01

    Plants rely primarily on rainfall infiltrating their root zones - a supply that is inherently variable, and fluctuations are predicted to increase on most of the Earth's surface. Yet, interrelationships between water availability and plant use on short timescales are difficult to quantify and remain poorly understood. To overcome previous methodological limitations, we coupled high-resolution in situ observations of stable isotopes in soil and transpiration water. We applied the approach along with Bayesian mixing modeling to track the fate of (2) H-labeled rain pulses following drought through soil and plants of deciduous tree ecosystems. We resolve how rainwater infiltrates the root zones in a nonequilibrium process and show that tree species differ in their ability to quickly acquire the newly available source. Sessile oak (Quercus petraea) adjusted root uptake to vertical water availability patterns under drought, but readjustment toward the rewetted topsoil was delayed. By contrast, European beech (Fagus sylvatica) readily utilized water from all soil depths independent of water depletion, enabling faster uptake of rainwater. Our results demonstrate that species-specific plasticity and responses to water supply fluctuations on short timescales can now be identified and must be considered to predict vegetation functional dynamics and water cycling under current and future climatic conditions. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  9. Metabolomics analysis of the effect of dissolved oxygen on spinosad production by Saccharopolyspora spinosa.

    PubMed

    Lu, Chunzhe; Yin, Jing; Zhao, Fanglong; Li, Feng; Lu, Wenyu

    2017-05-01

    Spinosad, a universal bio-pesticide, is obtained from the soil actinomycete Saccharopolyspora spinosa. Dissolved oxygen, an important contributing factor in aerobic microbial fermentation, however, is not always available in sufficient amounts. To alleviate oxygen limitation in spinosad production, three different oxygen vectors, namely oleic acid, toluene, and n-dodecane, were added into early fermentation. Results indicated that n-dodecane was the optimal oxygen vector. Spinosad yield was increased by 44.2% compared to that in the control group in the presence of 0.5% n-dodecane, added after 120 h of incubation. Yields of the test group reached 6.52 mg/g dry cell weight (DCW), while that of the control group was limited to 4.52 mg/g DCW. Metabolomics analysis by gas chromatography coupled to mass spectrometry was performed to demonstrate the metabolism mechanism in the presence and absence of oxygen vector. In total, 78 principal intracellular metabolites in S. spinosa were detected and quantified in the presence and absence of n-dodecane. Levels of some metabolites that were related to the tricarboxylic acid cycle and pentose phosphate pathway varied significantly. Aspartic acid and glucose-1-phosphate levels varied significantly and contributed most in the distinction of the fermentation conditions and phases. The above findings give new insights into the improvement and the metabolomic characteristics of industrial spinosad production.

  10. Integrated Analysis of the Transcriptome and Metabolome of Corynebacterium glutamicum during Penicillin-Induced Glutamic Acid Production.

    PubMed

    Hirasawa, Takashi; Saito, Masaki; Yoshikawa, Katsunori; Furusawa, Chikara; Shmizu, Hiroshi

    2018-05-01

    Corynebacterium glutamicum is known for its ability to produce glutamic acid and has been utilized for the fermentative production of various amino acids. Glutamic acid production in C. glutamicum is induced by penicillin. In this study, the transcriptome and metabolome of C. glutamicum is analyzed to understand the mechanism of penicillin-induced glutamic acid production. Transcriptomic analysis with DNA microarray revealed that expression of some glycolysis- and TCA cycle-related genes, which include those encoding the enzymes involved in conversion of glucose to 2-oxoglutaric acid, is upregulated after penicillin addition. Meanwhile, expression of some TCA cycle-related genes, encoding the enzymes for conversion of 2-oxoglutaric acid to oxaloacetic acid, and the anaplerotic reactions decreased. In addition, expression of NCgl1221 and odhI, encoding proteins involved in glutamic acid excretion and inhibition of the 2-oxoglutarate dehydrogenase, respectively, is upregulated. Functional category enrichment analysis of genes upregulated and downregulated after penicillin addition revealed that genes for signal transduction systems are enriched among upregulated genes, whereas those for energy production and carbohydrate and amino acid metabolisms are enriched among the downregulated genes. As for the metabolomic analysis using capillary electrophoresis time-of-flight mass spectrometry, the intracellular content of most metabolites of the glycolysis and the TCA cycle decreased dramatically after penicillin addition. Overall, these results indicate that the cellular metabolism and glutamic acid excretion are mainly optimized at the transcription level during penicillin-induced glutamic acid production by C. glutamicum. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context.

    PubMed

    Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens; Gobbo-Neto, Leonardo

    2018-01-01

    Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

  12. Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.

    PubMed

    Lee, Sang-Hyun; Kim, Sooah; Kwon, Min-A; Jung, Young Hoon; Shin, Yong-An; Kim, Kyoung Heon

    2014-12-01

    Well-established metabolome sample preparation is a prerequisite for reliable metabolomic data. For metabolome sampling of a Gram-positive strict anaerobe, Clostridium acetobutylicum, fast filtration and metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v) at -20°C under anaerobic conditions has been commonly used. This anaerobic metabolite processing method is laborious and time-consuming since it is conducted in an anaerobic chamber. Also, there have not been any systematic method evaluation and development of metabolome sample preparation for strict anaerobes and Gram-positive bacteria. In this study, metabolome sampling and extraction methods were rigorously evaluated and optimized for C. acetobutylicum by using gas chromatography/time-of-flight mass spectrometry-based metabolomics, in which a total of 116 metabolites were identified. When comparing the atmospheric (i.e., in air) and anaerobic (i.e., in an anaerobic chamber) processing of metabolome sample preparation, there was no significant difference in the quality and quantity of the metabolomic data. For metabolite extraction, pure methanol at -20°C was a better solvent than acetonitrile/methanol/water (2:2:1, v/v/v) at -20°C that is frequently used for C. acetobutylicum, and metabolite profiles were significantly different depending on extraction solvents. This is the first evaluation of metabolite sample preparation under aerobic processing conditions for an anaerobe. This method could be applied conveniently, efficiently, and reliably to metabolome analysis for strict anaerobes in air. © 2014 Wiley Periodicals, Inc.

  13. Analysis of metabolomics datasets with high-performance computing and metabolite atlases

    DOE PAGES

    Yao, Yushu; Sun, Terence; Wang, Tony; ...

    2015-07-20

    Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged formore » future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.« less

  14. Elemental and Isotopic Analysis of Uranium Oxide an NIST Glass Standards by FEMTOSECOND-LA-ICP-MIC-MS

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ebert, Chris; Zamzow, Daniel S.; McBay, Eddie H.

    2009-06-01

    The objective of this work was to test and demonstrate the analytical figures of merit of a femtosecond-laser ablation (fs-LA) system coupled with an inductively coupled plasma-multi-ion collector-mass spectrometer (ICP-MIC-MS). The mobile fs-LA sampling system was designed and assembled at Ames Laboratory and shipped to Oak Ridge National Laboratory (ORNL), where it was integrated with an ICP-MIC-MS. The test period of the integrated systems was February 2-6, 2009. Spatially-resolved analysis of particulate samples is accomplished by 100-shot laser ablation using a fs-pulsewidth laser and monitoring selected isotopes in the resulting ICP-MS transient signal. The capability of performing high sensitivity, spatiallymore » resolved, isotopic analyses with high accuracy and precision and with virtually no sample preparation makes fs-LA-ICP-MIC-MS valuable for the measurement of actinide isotopes at low concentrations in very small samples for nonproliferation purposes. Femtosecond-LA has been shown to generate particles from the sample that are more representative of the bulk composition, thereby minimizing weaknesses encountered in previous work using nanosecond-LA (ns-LA). The improvement of fs- over ns-LA sampling arises from the different mechanisms for transfer of energy into the sample in these two laser pulse-length regimes. The shorter duration fs-LA pulses induce less heating and cause less damage to the sample than the longer ns pulses. This results in better stoichiometric sampling (i.e., a closer correlation between the composition of the ablated particles and that of the original solid sample), which improves accuracy for both intra- and inter-elemental analysis. The primary samples analyzed in this work are (a) solid uranium oxide powdered samples having different {sup 235}U to {sup 238}U concentration ratios, and (b) glass reference materials (NIST 610, 612, 614, and 616). Solid uranium oxide samples containing {sup 235}U in depleted, natural, and

  15. Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

    PubMed

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

    2016-01-01

    Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

  16. Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

    PubMed Central

    2016-01-01

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment. PMID:26745651

  17. Integrated proteomics and metabolomics analysis of rat testis: Mechanism of arsenic-induced male reproductive toxicity

    NASA Astrophysics Data System (ADS)

    Huang, Qingyu; Luo, Lianzhong; Alamdar, Ambreen; Zhang, Jie; Liu, Liangpo; Tian, Meiping; Eqani, Syed Ali Musstjab Akber Shah; Shen, Heqing

    2016-09-01

    Arsenic is a widespread metalloid in environment, whose exposure has been associated with a broad spectrum of toxic effects. However, a global view of arsenic-induced male reproductive toxicity is still lack, and the underlying mechanisms remain largely unclear. Our results revealed that arsenic exposure decreased testosterone level and reduced sperm quality in rats. By conducting an integrated proteomics and metabolomics analysis, the present study aims to investigate the global influence of arsenic exposure on the proteome and metabolome in rat testis. The abundance of 70 proteins (36 up-regulated and 34 down-regulated) and 13 metabolites (8 increased and 5 decreased) were found to be significantly altered by arsenic treatment. Among these, 19 proteins and 2 metabolites were specifically related to male reproductive system development and function, including spermatogenesis, sperm function and fertilization, fertility, internal genitalia development, and mating behavior. It is further proposed that arsenic mainly impaired spermatogenesis and fertilization via aberrant modulation of these male reproduction-related proteins and metabolites, which may be mediated by the ERK/AKT/NF-κB-dependent signaling pathway. Overall, these findings will aid our understanding of the mechanisms responsible for arsenic-induced male reproductive toxicity, and from such studies useful biomarkers indicative of arsenic exposure could be discovered.

  18. Integrated proteomics and metabolomics analysis of rat testis: Mechanism of arsenic-induced male reproductive toxicity.

    PubMed

    Huang, Qingyu; Luo, Lianzhong; Alamdar, Ambreen; Zhang, Jie; Liu, Liangpo; Tian, Meiping; Eqani, Syed Ali Musstjab Akber Shah; Shen, Heqing

    2016-09-02

    Arsenic is a widespread metalloid in environment, whose exposure has been associated with a broad spectrum of toxic effects. However, a global view of arsenic-induced male reproductive toxicity is still lack, and the underlying mechanisms remain largely unclear. Our results revealed that arsenic exposure decreased testosterone level and reduced sperm quality in rats. By conducting an integrated proteomics and metabolomics analysis, the present study aims to investigate the global influence of arsenic exposure on the proteome and metabolome in rat testis. The abundance of 70 proteins (36 up-regulated and 34 down-regulated) and 13 metabolites (8 increased and 5 decreased) were found to be significantly altered by arsenic treatment. Among these, 19 proteins and 2 metabolites were specifically related to male reproductive system development and function, including spermatogenesis, sperm function and fertilization, fertility, internal genitalia development, and mating behavior. It is further proposed that arsenic mainly impaired spermatogenesis and fertilization via aberrant modulation of these male reproduction-related proteins and metabolites, which may be mediated by the ERK/AKT/NF-κB-dependent signaling pathway. Overall, these findings will aid our understanding of the mechanisms responsible for arsenic-induced male reproductive toxicity, and from such studies useful biomarkers indicative of arsenic exposure could be discovered.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Heyman, Heino M.; Zhang, Xing; Tang, Keqi

    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.

  20. The application of metabolomics in traditional Chinese medicine opens up a dialogue between Chinese and Western medicine.

    PubMed

    Cao, Hongxin; Zhang, Aihua; Zhang, Huamin; Sun, Hui; Wang, Xijun

    2015-02-01

    Metabolomics provides an opportunity to develop the systematic analysis of the metabolites and has been applied to discovering biomarkers and perturbed pathways which can clarify the action mechanism of traditional Chinese medicines (TCM). TCM is a comprehensive system of medical practice that has been used to diagnose, treat and prevent illnesses more than 3000 years. Metabolomics represents a powerful approach that provides a dynamic picture of the phenotype of biosystems through the study of endogenous metabolites, and its methods resemble those of TCM. Recently, metabolomics tools have been used for facilitating interactional effects of both Western medicine and TCM. We describe a protocol for investigating how metabolomics can be used to open up 'dialogue' between Chinese and Western medicine, and facilitate lead compound discovery and development from TCM. Metabolomics will bridge the cultural gap between TCM and Western medicine and improve development of integrative medicine, and maximally benefiting the human. Copyright © 2014 John Wiley & Sons, Ltd.

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

    PubMed

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

    2017-11-01

    Infertility is a complex disorder with significant medical, psychological and financial consequences for patients. With live-birth rates per cycle below 30% and a drive from the Human Fertilisation and Embryology Authority (HFEA) to encourage single embryo transfer, there is significant research in different areas aiming to improve success rates of fertility treatments. One such area is investigating the causes of infertility at a molecular level, and metabolomics techniques provide a platform for studying relevant biofluids in the reproductive tract. The aim of this systematic review is to examine the recent findings for the potential application of metabolomics to female reproduction, specifically to the metabolomics of follicular fluid (FF), embryo culture medium (ECM) and endometrial fluid. To our knowledge no other systematic review has investigated this topic. English peer-reviewed journals on PubMed, Science Direct, SciFinder, were systematically searched for studies investigating metabolomics and the female reproductive tract with no time restriction set for publications. Studies were assessed for quality using the risk of bias assessment and ROBIN-I. There were 21 studies that met the inclusion criteria and were included in the systematic review. Metabolomic studies have been employed for the compositional analysis of various biofluids in the female reproductive tract, including FF, ECM, blastocoele fluid and endometrial fluid. There is some weak evidence that metabolomics technologies studying ECM might be able to predict the viability of individual embryos and implantation rate better than standard embryo morphology, However these data were not supported by randomized the controlled trials (RCTs) which showed no evidence that using metabolomics is able to improve the most important reproductive outcomes, such as clinical pregnancy and live-birth rates. This systematic review provides guidance for future metabolomic studies on biofluids of the female

  2. A metabolomics guided exploration of marine natural product chemical space.

    PubMed

    Floros, Dimitrios J; Jensen, Paul R; Dorrestein, Pieter C; Koyama, Nobuhiro

    2016-09-01

    Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

  3. Effect of environment and genotype on commercial maize hybrids using LC/MS-based metabolomics.

    PubMed

    Baniasadi, Hamid; Vlahakis, Chris; Hazebroek, Jan; Zhong, Cathy; Asiago, Vincent

    2014-02-12

    We recently applied gas chromatography coupled to time-of-flight mass spectrometry (GC/TOF-MS) and multivariate statistical analysis to measure biological variation of many metabolites due to environment and genotype in forage and grain samples collected from 50 genetically diverse nongenetically modified (non-GM) DuPont Pioneer commercial maize hybrids grown at six North American locations. In the present study, the metabolome coverage was extended using a core subset of these grain and forage samples employing ultra high pressure liquid chromatography (uHPLC) mass spectrometry (LC/MS). A total of 286 and 857 metabolites were detected in grain and forage samples, respectively, using LC/MS. Multivariate statistical analysis was utilized to compare and correlate the metabolite profiles. Environment had a greater effect on the metabolome than genetic background. The results of this study support and extend previously published insights into the environmental and genetic associated perturbations to the metabolome that are not associated with transgenic modification.

  4. Fossil Fuel Combustion-Related Emissions Dominate Atmospheric Ammonia Sources during Severe Haze Episodes: Evidence from 15N-Stable Isotope in Size-Resolved Aerosol Ammonium

    NASA Astrophysics Data System (ADS)

    Pan, Y.; Tian, S.; Liu, D.; Fang, Y.; Zhu, X.; Zhang, Q.; Zheng, B.; Michalski, G. M.; Wang, Y.

    2016-12-01

    The reduction of ammonia (NH3) emissions is urgently needed due to its major contributions to nitrogen deposition and particle pollution. However, the relative contributions of individual NH3 sources are unclear, and debate remains over whether agricultural emissions dominate atmospheric NH3 in urban areas. Based on the chemical and isotopic measurements of size-resolved aerosols in urban Beijing, China, we find that the natural abundance of 15N (expressed using δ15N values) of ammonium (NH4+) in fine particles varies with the development of haze episodes, ranging from -37.1‰ to -21.7‰ during clean/dusty days (relative humidity: ˜ 40%), to -13.1‰ to +5.8‰ during hazy days (relative humidity: 70-90%). After factoring the isotope exchange between NH3 gas and aerosol NH4+, the δ15N value of the initial NH3 during hazy days is found to be -14.5‰ to -1.6‰, which indicates fossil fuel-based emissions. These emissions contribute 90% of the total NH3 during hazy days in urban Beijing. This work demonstrates the analysis of δ15N values of aerosol NH4+ to be a promising new tool for partitioning atmospheric NH3 sources, providing policy makers with insights into NH3 emissions and secondary aerosols for regulation in urban environments. This work also shed lights on the sources of nitrogen deposition in downwind ecosystems.

  5. Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure.

    PubMed

    García-Sevillano, M A; García-Barrera, T; Navarro, F; Montero-Lobato, Z; Gómez-Ariza, J L

    2015-04-01

    Mass spectrometry (MS)-based toxicometabolomics requires analytical approaches for obtaining unbiased metabolic profiles. The present work explores the general application of direct infusion MS using a high mass resolution analyzer (a hybrid systems triple quadrupole-time-of-flight) and a complementary gas chromatography-MS analysis to mitochondria extracts from mouse hepatic cells, emphasizing on mitochondria isolation from hepatic cells with a commercial kit, sample treatment after cell lysis, comprehensive metabolomic analysis and pattern recognition from metabolic profiles. Finally, the metabolomic platform was successfully checked on a case-study based on the exposure experiment of mice Mus musculus to inorganic arsenic during 12 days. Endogenous metabolites alterations were recognized by partial least squares-discriminant analysis. Subsequently, metabolites were identified by combining MS/MS analysis and metabolomics databases. This work reports for the first time the effects of As-exposure on hepatic mitochondria metabolic pathways based on MS, and reveals disturbances in Krebs cycle, β-oxidation pathway, amino acids degradation and perturbations in creatine levels. This non-target analysis provides extensive metabolic information from mitochondrial organelle, which could be applied to toxicology, pharmacology and clinical studies.

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

    PubMed

    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.

  7. MVAPACK: A Complete Data Handling Package for NMR Metabolomics

    PubMed Central

    2015-01-01

    Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set. PMID:24576144

  8. Blood metabolomics analysis identifies abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism in bipolar disorder.

    PubMed

    Yoshimi, Noriko; Futamura, Takashi; Kakumoto, Keiji; Salehi, Alireza M; Sellgren, Carl M; Holmén-Larsson, Jessica; Jakobsson, Joel; Pålsson, Erik; Landén, Mikael; Hashimoto, Kenji

    2016-06-01

    Bipolar disorder (BD) is a severe and debilitating psychiatric disorder. However, the precise biological basis remains unknown, hampering the search for novel biomarkers. We performed a metabolomics analysis to discover novel peripheral biomarkers for BD. We quantified serum levels of 116 metabolites in mood-stabilized male BD patients (n = 54) and age-matched male healthy controls (n = 39). After multivariate logistic regression, serum levels of pyruvate, N-acetylglutamic acid, α-ketoglutarate, and arginine were significantly higher in BD patients than in healthy controls. Conversely, serum levels of β-alanine, and serine were significantly lower in BD patients than in healthy controls. Chronic (4-weeks) administration of lithium or valproic acid to adult male rats did not alter serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, or arginine, but lithium administration significantly increased serum levels of α-ketoglutarate. The metabolomics analysis demonstrated altered serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, and arginine in BD patients. The present findings suggest that abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism play a role in the pathogenesis of BD.

  9. New approaches for metabolomics by mass spectrometry

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Vertes, Akos

    Small molecules constitute a large part of the world around us, including fossil and some renewable energy sources. Solar energy harvested by plants and bacteria is converted into energy rich small molecules on a massive scale. Some of the worst contaminants of the environment and compounds of interest for national security also fall in the category of small molecules. The development of large scale metabolomic analysis methods lags behind the state of the art established for genomics and proteomics. This is commonly attributed to the diversity of molecular classes included in a metabolome. Unlike nucleic acids and proteins, metabolites domore » not have standard building blocks, and, as a result, their molecular properties exhibit a wide spectrum. This impedes the development of dedicated separation and spectroscopic methods. Mass spectrometry (MS) is a strong contender in the quest for a quantitative analytical tool with extensive metabolite coverage. Although various MS-based techniques are emerging for metabolomics, many of these approaches include extensive sample preparation that make large scale studies resource intensive and slow. New ionization methods are redefining the range of analytical problems that can be solved using MS. This project developed new approaches for the direct analysis of small molecules in unprocessed samples, as well as pushed the limits of ultratrace analysis in volume limited complex samples. The projects resulted in techniques that enabled metabolomics investigations with enhanced molecular coverage, as well as the study of cellular response to stimuli on a single cell level. Effectively individual cells became reaction vessels, where we followed the response of a complex biological system to external perturbation. We established two new analytical platforms for the direct study of metabolic changes in cells and tissues following external perturbation. For this purpose we developed a novel technique, laser ablation electrospray

  10. Impact of storage conditions on the urinary metabolomics fingerprint.

    PubMed

    Laparre, Jérôme; Kaabia, Zied; Mooney, Mark; Buckley, Tom; Sherry, Mark; Le Bizec, Bruno; Dervilly-Pinel, Gaud

    2017-01-25

    Urine stability during storage is essential in metabolomics to avoid misleading conclusions or erroneous interpretations. Facing the lack of comprehensive studies on urine metabolome stability, the present work performed a follow-up of potential modifications in urinary chemical profile using LC-HRMS on the basis of two parameters: the storage temperature (+4 °C, -20 °C, -80 °C and freeze-dried stored at -80 °C) and the storage duration (5-144 days). Both HILIC and RP chromatographies have been implemented in order to globally monitor the urinary metabolome. Using an original data processing associated to univariate and multivariate data analysis, our study confirms that chemical profiles of urine samples stored at +4 °C are very rapidly modified, as observed for instance for compounds such as:N-acetyl Glycine, Adenosine, 4-Amino benzoic acid, N-Amino diglycine, creatine, glucuronic acid, 3-hydroxy-benzoic acid, pyridoxal, l-pyroglutamic acid, shikimic acid, succinic acid, thymidine, trigonelline and valeryl-carnitine, while it also demonstrates that urine samples stored at -20 °C exhibit a global stability over a long period with no major modifications compared to -80 °C condition. This study is the first to investigate long term stability of urine samples and report potential modifications in the urinary metabolome, using both targeted approach monitoring individually a large number (n > 200) of urinary metabolites and an untargeted strategy enabling assessing for global impact of storage conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Discovery of human urinary biomarkers of aronia-citrus juice intake by HPLC-q-TOF-based metabolomic approach.

    PubMed

    Llorach, Rafael; Medina, Sonia; García-Viguera, Cristina; Zafrilla, Pilar; Abellán, José; Jauregui, Olga; Tomás-Barberán, Francisco A; Gil-Izquierdo, Angel; Andrés-Lacueva, Cristina

    2014-06-01

    Metabolomics has emerged in the field of food and nutrition sciences as a powerful tool for doing profiling approaches. In this context, HPLC-q-TOF-based metabolomics approach was applied to unveil changes in the urinary metabolome in human subjects (n = 51, 23 men and 28 women) after regular aronia-citrus juice (AC-juice) intake (250 mL/day) during 16 weeks compared to individuals given a placebo beverage. Samples were analyzed by HPLC-q-TOF followed by multivariate data analysis (orthogonal signal filtering-partial least square discriminant analysis) that discriminated relevant mass features related to AC-juice intake. The results showed that biomarkers of AC-juice intake including metabolites coming from metabolism of food components as proline betaine, ferulic acid, and two unknown mercapturate derivatives were identified. Discovery of new biomarkers of food intake will help in the building up of the food metabolome and facilitate future insights into the mechanisms of action of dietary components in population health. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Molecular Isotopic Distribution Analysis (MIDAs) with Adjustable Mass Accuracy

    NASA Astrophysics Data System (ADS)

    Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo

    2014-01-01

    In this paper, we present Molecular Isotopic Distribution Analysis (MIDAs), a new software tool designed to compute molecular isotopic distributions with adjustable accuracies. MIDAs offers two algorithms, one polynomial-based and one Fourier-transform-based, both of which compute molecular isotopic distributions accurately and efficiently. The polynomial-based algorithm contains few novel aspects, whereas the Fourier-transform-based algorithm consists mainly of improvements to other existing Fourier-transform-based algorithms. We have benchmarked the performance of the two algorithms implemented in MIDAs with that of eight software packages (BRAIN, Emass, Mercury, Mercury5, NeutronCluster, Qmass, JFC, IC) using a consensus set of benchmark molecules. Under the proposed evaluation criteria, MIDAs's algorithms, JFC, and Emass compute with comparable accuracy the coarse-grained (low-resolution) isotopic distributions and are more accurate than the other software packages. For fine-grained isotopic distributions, we compared IC, MIDAs's polynomial algorithm, and MIDAs's Fourier transform algorithm. Among the three, IC and MIDAs's polynomial algorithm compute isotopic distributions that better resemble their corresponding exact fine-grained (high-resolution) isotopic distributions. MIDAs can be accessed freely through a user-friendly web-interface at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/midas/index.html.

  13. Molecular Isotopic Distribution Analysis (MIDAs) with adjustable mass accuracy.

    PubMed

    Alves, Gelio; Ogurtsov, Aleksey Y; Yu, Yi-Kuo

    2014-01-01

    In this paper, we present Molecular Isotopic Distribution Analysis (MIDAs), a new software tool designed to compute molecular isotopic distributions with adjustable accuracies. MIDAs offers two algorithms, one polynomial-based and one Fourier-transform-based, both of which compute molecular isotopic distributions accurately and efficiently. The polynomial-based algorithm contains few novel aspects, whereas the Fourier-transform-based algorithm consists mainly of improvements to other existing Fourier-transform-based algorithms. We have benchmarked the performance of the two algorithms implemented in MIDAs with that of eight software packages (BRAIN, Emass, Mercury, Mercury5, NeutronCluster, Qmass, JFC, IC) using a consensus set of benchmark molecules. Under the proposed evaluation criteria, MIDAs's algorithms, JFC, and Emass compute with comparable accuracy the coarse-grained (low-resolution) isotopic distributions and are more accurate than the other software packages. For fine-grained isotopic distributions, we compared IC, MIDAs's polynomial algorithm, and MIDAs's Fourier transform algorithm. Among the three, IC and MIDAs's polynomial algorithm compute isotopic distributions that better resemble their corresponding exact fine-grained (high-resolution) isotopic distributions. MIDAs can be accessed freely through a user-friendly web-interface at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/midas/index.html.

  14. Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery.

    PubMed

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2018-05-01

    This work reports the second part of a review intending to give the state of the art of major metabolic phenotyping strategies. It particularly deals with inherent advantages and limits regarding data analysis issues and biological information retrieval tools along with translational challenges. This Part starts with introducing the main data preprocessing strategies of the different metabolomics data. Then, it describes the main data analysis techniques including univariate and multivariate aspects. It also addresses the challenges related to metabolite annotation and characterization. Finally, functional analysis including pathway and network strategies are discussed. The last section of this review is devoted to practical considerations and current challenges and pathways to bring metabolomics into clinical environments.

  15. Compound-Specific Isotope Analysis of Diesel Fuels in a Forensic Investigation

    NASA Astrophysics Data System (ADS)

    Muhammad, Syahidah; Frew, Russell; Hayman, Alan

    2015-02-01

    Compound-specific isotope analysis (CSIA) offers great potential as a tool to provide chemical evidence in a forensic investigation. Many attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large data set is analyzed and the isotopic differences between samples are subtle. In the present study, discrimination of diesel oils involved in a diesel theft case was carried out to infer the relatedness of the samples to potential source samples. This discriminatory analysis used a suite of hydrocarbon diagnostic indices, alkanes, to generate carbon and hydrogen isotopic data of the compositions of the compounds which were then processed using multivariate statistical analyses to infer the relatedness of the data set. The results from this analysis were put into context by comparing the data with the δ13C and δ2H of alkanes in commercial diesel samples obtained from various locations in the South Island of New Zealand. Based on the isotopic character of the alkanes, it is suggested that diesel fuels involved in the diesel theft case were distinguishable. This manuscript shows that CSIA when used in tandem with multivariate statistical analysis provide a defensible means to differentiate and source-apportion qualitatively similar oils at the molecular level. This approach was able to overcome confounding challenges posed by the near single-point source of origin i.e. the very subtle differences in isotopic values between the samples.

  16. Compound-specific isotope analysis of diesel fuels in a forensic investigation

    PubMed Central

    Muhammad, Syahidah A.; Frew, Russell D.; Hayman, Alan R.

    2015-01-01

    Compound-specific isotope analysis (CSIA) offers great potential as a tool to provide chemical evidence in a forensic investigation. Many attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large data set is analyzed and the isotopic differences between samples are subtle. In the present study, discrimination of diesel oils involved in a diesel theft case was carried out to infer the relatedness of the samples to potential source samples. This discriminatory analysis used a suite of hydrocarbon diagnostic indices, alkanes, to generate carbon and hydrogen isotopic data of the compositions of the compounds which were then processed using multivariate statistical analyses to infer the relatedness of the data set. The results from this analysis were put into context by comparing the data with the δ13C and δ2H of alkanes in commercial diesel samples obtained from various locations in the South Island of New Zealand. Based on the isotopic character of the alkanes, it is suggested that diesel fuels involved in the diesel theft case were distinguishable. This manuscript shows that CSIA when used in tandem with multivariate statistical analysis provide a defensible means to differentiate and source-apportion qualitatively similar oils at the molecular level. This approach was able to overcome confounding challenges posed by the near single-point source of origin, i.e., the very subtle differences in isotopic values between the samples. PMID:25774366

  17. Untargeted metabolomics unravels functionalities of phosphorylation sites in Saccharomyces cerevisiae.

    PubMed

    Raguz Nakic, Zrinka; Seisenbacher, Gerhard; Posas, Francesc; Sauer, Uwe

    2016-11-15

    Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection. Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway. We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.

  18. Metabolomics in Sepsis and Its Impact on Public Health.

    PubMed

    Evangelatos, Nikolaos; Bauer, Pia; Reumann, Matthias; Satyamoorthy, Kapaettu; Lehrach, Hans; Brand, Angela

    2017-01-01

    Sepsis, with its often devastating consequences for patients and their families, remains a major public health concern that poses an increasing financial burden. Early resuscitation together with the elucidation of the biological pathways and pathophysiological mechanisms with the use of "-omics" technologies have started changing the clinical and research landscape in sepsis. Metabolomics (i.e., the study of the metabolome), an "-omics" technology further down in the "-omics" cascade between the genome and the phenome, could be particularly fruitful in sepsis research with the potential to alter the clinical practice. Apart from its benefit for the individual patient, metabolomics has an impact on public health that extends beyond its applications in medicine. In this review, we present recent developments in metabolomics research in sepsis, with a focus on pneumonia, and we discuss the impact of metabolomics on public health, with a focus on free/libre open source software. © 2018 S. Karger AG, Basel.

  19. Metabolomic Profiles Delineate Signature Metabolic Shifts during Estrogen Deficiency-Induced Bone Loss in Rat by GC-TOF/MS

    PubMed Central

    Zhang, Qi; Ying, Hanjie; A, Jiye; Sun, Jianguo; Wu, Di; Wang, Yonglu; Li, Jing; Liu, Yinhui

    2013-01-01

    Postmenopausal osteoporosis is a complicated and multi-factorial disease. To study the metabolic profiles and pathways activated in osteoporosis, Eight rats were oophorectomized (OVX group) to represent postmenopausal osteoporosis and the other eight rats were sham operated (Sham group) to be the control. The biochemical changes were assessed with metabolomics using a gas chromatography/time-of-flight mass spectrometry. Metabolomic profile using serial blood samples obtained prior to and at different time intervals after OVX were analyzed by principal component analysis (PCA) and Partial least squares-discriminant analysis (PLS-DA). The conventional indicators (bone mineral density, serum Bone alkaline phosphatase (B-ALP) and N-telopeptide of type I collagen (NTx) of osteoporosis in rats were also determined simultaneously. In OVX group, the metabolomics method could describe the endogenous changes of the disease more sensitively and systematically than the conventional criteria during the progression of osteoporosis. Significant metabolomic difference was also observed between the OVX and Sham groups. The metabolomic analyses of rat plasma showed that levels of arachidonic acid, octadecadienoic acid, branched-chain amino acids (valine, leucine and isoleucine), homocysteine, hydroxyproline and ketone bodies (3-Hydroxybutyric Acid) significantly elevated, while levels of docosahexaenoic acid, dodecanoic acid and lysine significantly decreased in OVX group compared with those in the homeochronous Sham group. Considering such metabolites are closely related to the pathology of the postmenopausal osteoporosis, the results suggest that potential biomarkers for the early diagnosis or the pathogenesis of osteoporosis might be identified via metabolomic study. PMID:23408954

  20. Use of stable isotope analysis in determining aquatic food webs

    EPA Science Inventory

    Stable isotope analysis is a useful tool for describing resource-consumer dynamics in ecosystems. In general, organisms of a given trophic level or functional feeding group will have a stable isotope ratio identifiable different than their prey because of preferential use of one ...

  1. A Direct Cell Quenching Method for Cell-Culture Based Metabolomics

    EPA Science Inventory

    A crucial step in metabolomic analysis of cellular extracts is the cell quenching process. The conventional method first uses trypsin to detach cells from their growth surface. This inevitably changes the profile of cellular metabolites since the detachment of cells from the extr...

  2. Vitamins, Metabolomics and Prostate Cancer

    PubMed Central

    Mondul, Alison M; Weinstein, Stephanie J; Albanes, Demetrius

    2016-01-01

    Purpose How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms by which vitamins influence prostate cancer risk. Methods Prostate cancer risk data related to vitamins E, A, and D and metabolomics profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Results Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomics profiling of fasting serum collected 1-20 years prior to clinical diagnoses found lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with risk of aggressive disease. Conclusions Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study. PMID:27339624

  3. Vitamins, metabolomics, and prostate cancer.

    PubMed

    Mondul, Alison M; Weinstein, Stephanie J; Albanes, Demetrius

    2017-06-01

    How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms through which vitamins influence prostate cancer risk. Prostate cancer risk data related to vitamins E, A, and D and metabolomic profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have had mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomic profiling of fasting serum collected 1-20 years prior to clinical diagnoses found reduced lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with lower risk of aggressive disease. Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study.

  4. Optical spectroscopy of laser-produced plasmas for standoff isotopic analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harilal, Sivanandan S.; Brumfield, Brian E.; LaHaye, Nicole L.

    2018-04-20

    This review article covers the present status of isotope detection through emission, absorption, and fluorescence spectroscopy of atoms and molecules in a laser-produced plasma formed from a solid sample. A description of the physics behind isotope shifts in atoms and molecules is presented, followed by the physics behind solid sampling of laser ablation plumes, optical methods for isotope measurements, the suitable physical conditions of laser-produced plasma plumes for isotopic analysis, and the current status. Finally, concluding remarks will be made on the existing gaps between previous works in the literature and suggestions for future work.

  5. Optical spectroscopy of laser-produced plasmas for standoff isotopic analysis

    DOE PAGES

    Harilal, S. S.; Brumfield, B. E.; LaHaye, N. L.; ...

    2018-04-20

    This review article covers the present status of isotope detection through emission, absorption, and fluorescence spectroscopy of atoms and molecules in a laser-produced plasma formed from a solid sample. A description of the physics behind isotope shifts in atoms and molecules is presented, followed by the physics behind solid sampling of laser ablation plumes, optical methods for isotope measurements, the suitable physical conditions of laser-produced plasma plumes for isotopic analysis, and the current status. Lastly, concluding remarks will be made on the existing gaps between previous works in the literature and suggestions for future work.

  6. Optical spectroscopy of laser-produced plasmas for standoff isotopic analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harilal, S. S.; Brumfield, B. E.; LaHaye, N. L.

    This review article covers the present status of isotope detection through emission, absorption, and fluorescence spectroscopy of atoms and molecules in a laser-produced plasma formed from a solid sample. A description of the physics behind isotope shifts in atoms and molecules is presented, followed by the physics behind solid sampling of laser ablation plumes, optical methods for isotope measurements, the suitable physical conditions of laser-produced plasma plumes for isotopic analysis, and the current status. Lastly, concluding remarks will be made on the existing gaps between previous works in the literature and suggestions for future work.

  7. Optical spectroscopy of laser-produced plasmas for standoff isotopic analysis

    DOE PAGES

    Harilal, S. S.; Brumfield, B. E.; LaHaye, N. L.; ...

    2018-06-01

    This review article covers the present status of isotope detection through emission, absorption, and fluorescence spectroscopy of atoms and molecules in a laser-produced plasma formed from a solid sample. A description of the physics behind isotope shifts in atoms and molecules is presented, followed by the physics behind solid sampling of laser ablation plumes, optical methods for isotope measurements, the suitable physical conditions of laser-produced plasma plumes for isotopic analysis, and the current status. Finally, concluding remarks will be made on the existing gaps between previous works in the literature and suggestions for future work.

  8. Optical spectroscopy of laser-produced plasmas for standoff isotopic analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harilal, S. S.; Brumfield, B. E.; LaHaye, N. L.

    This review article covers the present status of isotope detection through emission, absorption, and fluorescence spectroscopy of atoms and molecules in a laser-produced plasma formed from a solid sample. A description of the physics behind isotope shifts in atoms and molecules is presented, followed by the physics behind solid sampling of laser ablation plumes, optical methods for isotope measurements, the suitable physical conditions of laser-produced plasma plumes for isotopic analysis, and the current status. Finally, concluding remarks will be made on the existing gaps between previous works in the literature and suggestions for future work.

  9. Mass spectrometry-based plant metabolomics: Metabolite responses to abiotic stress.

    PubMed

    Jorge, Tiago F; Rodrigues, João A; Caldana, Camila; Schmidt, Romy; van Dongen, Joost T; Thomas-Oates, Jane; António, Carla

    2016-09-01

    Metabolomics is one omics approach that can be used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include analysis of a wide range of chemical species with diverse physical properties, from ionic inorganic compounds to biochemically derived hydrophilic carbohydrates, organic and amino acids, and a range of hydrophobic lipid-related compounds. This complexitiy brings huge challenges to the analytical technologies employed in current plant metabolomics programs, and powerful analytical tools are required for the separation and characterization of this extremely high compound diversity present in biological sample matrices. The use of mass spectrometry (MS)-based analytical platforms to profile stress-responsive metabolites that allow some plants to adapt to adverse environmental conditions is fundamental in current plant biotechnology research programs for the understanding and development of stress-tolerant plants. In this review, we describe recent applications of metabolomics and emphasize its increasing application to study plant responses to environmental (stress-) factors, including drought, salt, low oxygen caused by waterlogging or flooding of the soil, temperature, light and oxidative stress (or a combination of them). Advances in understanding the global changes occurring in plant metabolism under specific abiotic stress conditions are fundamental to enhance plant fitness and increase stress tolerance. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:620-649, 2016. © 2015 Wiley Periodicals, Inc.

  10. Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

    PubMed

    Blasco, H; Patin, F; Madji Hounoum, B; Gordon, P H; Vourc'h, P; Andres, C R; Corcia, P

    2016-03-01

    Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. © 2016 EAN.

  11. Untargeted metabolomics reveals specific withanolides and fatty acyl glycoside as tentative metabolites to differentiate organic and conventional Physalis peruviana fruits.

    PubMed

    Llano, Sandra M; Muñoz-Jiménez, Ana M; Jiménez-Cartagena, Claudio; Londoño-Londoño, Julián; Medina, Sonia

    2018-04-01

    The agronomic production systems may affect the levels of food metabolites. Metabolomics approaches have been applied as useful tool for the characterization of fruit metabolome. In this study, metabolomics techniques were used to assess the differences in phytochemical composition between goldenberry samples produced by organic and conventional systems. To verify that the organic samples were free of pesticides, individual pesticides were analyzed. Principal component analysis showed a clear separation of goldenberry samples from two different farming systems. Via targeted metabolomics assays, whereby carotenoids and ascorbic acid were analyzed, not statistical differences between both crops were found. Conversely, untargeted metabolomics allowed us to identify two withanolides and one fatty acyl glycoside as tentative metabolites to differentiate goldenberry fruits, recording organic fruits higher amounts of these compounds than conventional samples. Hence, untargeted metabolomics technology could be suitable to research differences on phytochemicals under different agricultural management practices and to authenticate organic products. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. System and method for high precision isotope ratio destructive analysis

    DOEpatents

    Bushaw, Bruce A; Anheier, Norman C; Phillips, Jon R

    2013-07-02

    A system and process are disclosed that provide high accuracy and high precision destructive analysis measurements for isotope ratio determination of relative isotope abundance distributions in liquids, solids, and particulate samples. The invention utilizes a collinear probe beam to interrogate a laser ablated plume. This invention provides enhanced single-shot detection sensitivity approaching the femtogram range, and isotope ratios that can be determined at approximately 1% or better precision and accuracy (relative standard deviation).

  13. Introduction to metabolomics and its applications in ophthalmology

    PubMed Central

    Tan, S Z; Begley, P; Mullard, G; Hollywood, K A; Bishop, P N

    2016-01-01

    Metabolomics is the study of endogenous and exogenous metabolites in biological systems, which aims to provide comparative semi-quantitative information about all metabolites in the system. Metabolomics is an emerging and potentially powerful tool in ophthalmology research. It is therefore important for health professionals and researchers involved in the speciality to understand the basic principles of metabolomics experiments. This article provides an overview of the experimental workflow and examples of its use in ophthalmology research from the study of disease metabolism and pathogenesis to identification of biomarkers. PMID:26987591

  14. Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile.

    PubMed

    Okuma, Nobuyuki; Saita, Makiko; Hoshi, Noriyuki; Soga, Tomoyoshi; Tomita, Masaru; Sugimoto, Masahiro; Kimoto, Katsuhiko

    2017-01-01

    This study characterized the changes in quality and quantity of saliva, and changes in the salivary metabolomic profile, to understand the effects of masticatory stimulation. Stimulated and unstimulated saliva samples were collected from 55 subjects and salivary hydrophilic metabolites were comprehensively quantified using capillary electrophoresis-time-of-flight mass spectrometry. In total, 137 metabolites were identified and quantified. The concentrations of 44 metabolites in stimulated saliva were significantly higher than those in unstimulated saliva. Pathway analysis identified the upregulation of the urea cycle and synthesis and degradation pathways of glycine, serine, cysteine and threonine in stimulated saliva. A principal component analysis revealed that the effect of masticatory stimulation on salivary metabolomic profiles was less dependent on sample population sex, age, and smoking. The concentrations of only 1 metabolite in unstimulated saliva, and of 3 metabolites stimulated saliva, showed significant correlation with salivary secretion volume, indicating that the salivary metabolomic profile and salivary secretion volume were independent factors. Masticatory stimulation affected not only salivary secretion volume, but also metabolite concentration patterns. A low correlation between the secretion volume and these patterns supports the conclusion that the salivary metabolomic profile may be a new indicator to characterize masticatory stimulation.

  15. Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD)

    PubMed Central

    Rhoades, Seth D.

    2017-01-01

    Introduction Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Objective Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). Methods We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. Results LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. Conclusions The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method. PMID:28348510

  16. Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD).

    PubMed

    Rhoades, Seth D; Weljie, Aalim M

    2016-12-01

    Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method.

  17. Enhanced sensitivity of DNA- and rRNA-based stable isotope probing by fractionation and quantitative analysis of isopycnic centrifugation gradients.

    PubMed

    Lueders, Tillmann; Manefield, Mike; Friedrich, Michael W

    2004-01-01

    Stable isotope probing (SIP) of nucleic acids allows the detection and identification of active members of natural microbial populations that are involved in the assimilation of an isotopically labelled compound into nucleic acids. SIP is based on the separation of isotopically labelled DNA or rRNA by isopycnic density gradient centrifugation. We have developed a highly sensitive protocol for the detection of 'light' and 'heavy' nucleic acids in fractions of centrifugation gradients. It involves the fluorometric quantification of total DNA or rRNA, and the quantification of either 16S rRNA genes or 16S rRNA in gradient fractions by real-time PCR with domain-specific primers. Using this approach, we found that fully 13C-labelled DNA or rRNA of Methylobacterium extorquens was quantitatively resolved from unlabelled DNA or rRNA of Methanosarcina barkeri by cesium chloride or cesium trifluoroacetate density gradient centrifugation respectively. However, a constant low background of unspecific nucleic acids was detected in all DNA or rRNA gradient fractions, which is important for the interpretation of environmental SIP results. Consequently, quantitative analysis of gradient fractions provides a higher precision and finer resolution for retrieval of isotopically enriched nucleic acids than possible using ethidium bromide or gradient fractionation combined with fingerprinting analyses. This is a prerequisite for the fine-scale tracing of microbial populations metabolizing 13C-labelled compounds in natural ecosystems.

  18. Metabolomic analysis of urine with Nuclear Magnetic Resonance spectroscopy in patients with idiopathic sudden sensorineural hearing loss: A preliminary study.

    PubMed

    Carta, Filippo; Lussu, Milena; Bandino, Fabrizio; Noto, Antonio; Peppi, Marcello; Chuchueva, Natalia; Atzori, Luigi; Fanos, Vassilios; Puxeddu, Roberto

    2017-08-01

    Idiopathic sudden sensorineural hearing loss is a frequent emergency, with unknown aetiology and usually treated with empiric therapy. Steroids represent the only validated treatment but prognosis is unpredictable and the possibility to select the patients who will not respond to steroids could avoid unnecessary treatments. Metabolomic profiling of the biofluids target the analysis of the final product of genic expression and enzymatic activity, defining the biochemical phenotype of a whole biologic system. We studied the metabolomics of the urine of a cohort of patients with idiopathic sudden sensorineural hearing loss, correlating the metabolic profiles with the clinical outcomes. Metabolomic profiling of urine samples was performed by 1 H Nuclear Magnetic Resonance spectroscopy in combination with multivariate statistical approaches. 26 patients were included in the study: 5 healthy controls, 13 patients who did not recover after treatment at 6 months while the remaining 8 patients recovered from the hearing loss. The orthogonal partial least square-discriminant analysis score plot showed a significant separation between the two groups, responders and non-responders after steroid therapy, R 2 Y of 0.83, Q 2 of 0.38 and p value <0.05. The resulting metabolic profiles were characterized by higher levels of urinary B-Alanine, 3-hydroxybutyrate and Trimethylamine N-oxide, and lower levels of Citrate and Creatinine in patients with worst outcome. Idiopathic sudden sensorineural hearing loss is a specific disease with unclear systemic changes, but our data suggest that there are different types of this disorder or patients predisposed to effective action of steroids allowing the recover after treatment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. Genomic and Metabolomic Profile Associated to Microalbuminuria

    PubMed Central

    Marrachelli, Vannina G.; Monleon, Daniel; Rentero, Pilar; Mansego, María L.; Morales, Jose Manuel; Galan, Inma; Segura, Remedios; Martinez, Fernando; Martin-Escudero, Juan Carlos; Briongos, Laisa; Marin, Pablo; Lliso, Gloria; Chaves, Felipe Javier; Redon, Josep

    2014-01-01

    To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE) were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men, ACR>30 mg/g in 81 subjects) with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of RPH3A gene and the rs4359_CC of ACE gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria. PMID:24918908

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

    PubMed

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

    2016-03-24

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

  1. Prospects and Challenges in tropical isotope dendroclimatology

    NASA Astrophysics Data System (ADS)

    Evans, M. N.; Anchukaitis, K. J.; White, S. R.; Ektvedt, T. M.; Penniston, R. C.; Rheaume, M. M.; Bowman, D. M.

    2008-12-01

    We review a stable isotope-based approach to the development, modeling, interpretation, and analysis of hydrometeorological estimates from tropical trees. The strategy overcomes the common problem of missing, intermittent or non-annual ring structure in tropical trees by relying instead on the observation of the annual wet-dry seasonality typical to tropical environments as mirrored in the oxygen isotopic composition of wood-derived α-cellulose. We explore regions for which forward modeling of the proxy system would expect us to resolve hydrometeorological variations associated with the El Niño-Southern Oscillation (ENSO) phenomenon, rather than being limited to regions with tree species or environments producing verifiable annual ring chronologies. A modified protocol allows for rapid, simple and non-toxic micro-extraction of pure α-cellulose, which is isotopically indistinguishable from that produced by more classical means. We describe a new reactor for the pyrolysis of α-cellulose in an induction heater, which permits isotopic analysis of α-cellulose samples as small as 30μg, and as many as 100 automated sample analyses per day. A forward model adapted for tropical environments can be used to test and refine the interpretation of the isotopic data, and to predict locales for which we should be able to maximize the paleoclimatic potential of future sample collections. We have found the modeled isotopic chronometer and raingage in agreement with independent chronological controls in a variety of environments and tree species in Costa Rica, Indonesia, Brazil, Peru and Australia. Development of long hydrometeorological records from the terrestrial tropics is underway not only by our group, but by a growing number of collaborators and colleagues. Together we should be able to build a network of paleoprecipitation records and better understand the linkages between tropical surface ocean temperatures and large-scale drought.

  2. Single-cell metabolomics: analytical and biological perspectives.

    PubMed

    Zenobi, R

    2013-12-06

    There is currently much interest in broad molecular profiling of single cells; a cell's metabolome-its full complement of small-molecule metabolites-is a direct indicator of phenotypic diversity of single cells and a nearly immediate readout of how cells react to environmental influences. However, the metabolome is very difficult to measure at the single-cell level because of rapid metabolic dynamics, the structural diversity of the molecules, and the inability to amplify or tag small-molecule metabolites. Measurement techniques including mass spectrometry, capillary electrophoresis, and, to a lesser extent, optical spectroscopy and fluorescence detection have led to impressive advances in single-cell metabolomics. Even though none of these methodologies can currently measure the metabolome of a single cell completely, rapidly, and nondestructively, progress has been sufficient such that the field is witnessing a shift from feasibility studies to investigations that yield new biological insight. Particularly interesting fields of application are cancer biology, stem cell research, and monitoring of xenobiotics and drugs in tissue sections at the single-cell level.

  3. Metabolic Mechanism for l-Leucine-Induced Metabolome To Eliminate Streptococcus iniae.

    PubMed

    Du, Chao-Chao; Yang, Man-Jun; Li, Min-Yi; Yang, Jun; Peng, Bo; Li, Hui; Peng, Xuan-Xian

    2017-05-05

    Crucial metabolites that modulate hosts' metabolome to eliminate bacterial pathogens have been documented, but the metabolic mechanisms are largely unknown. The present study explores the metabolic mechanism for l-leucine-induced metabolome to eliminate Streptococcus iniae in tilapia. GC-MS-based metabolomics was used to investigate the tilapia liver metabolic profile in the presence of exogenous l-leucine. Thirty-seven metabolites of differential abundance were determined, and 11 metabolic pathways were enriched. Pattern recognition analysis identified serine and proline as crucial metabolites, which are the two metabolites identified in survived tilapias during S. iniae infection, suggesting that the two metabolites play crucial roles in l-leucine-induced elimination of the pathogen by the host. Exogenous l-serine reduces the mortality of tilapias infected by S. iniae, providing a robust proof supporting the conclusion. Furthermore, exogenous l-serine elevates expression of genes IL-1β and IL-8 in tilapia spleen, but not TNFα, CXCR4 and Mx, suggesting that the metabolite promotes a phagocytosis role of macrophages, which is consistent with the finding that l-leucine promotes macrophages to kill both Gram-positive and Gram-negative bacterial pathogens. Therefore, the ability of phagocytosis enhanced by exogenous l-leucine is partly attributed to elevation of l-serine. These results demonstrate a metabolic mechanism by which exogenous l-leucine modulates tilapias' metabolome to enhance innate immunity and eliminate pathogens.

  4. GC-TOF/MS-based metabolomic profiling of estrogen deficiency-induced obesity in ovariectomized rats

    PubMed Central

    Ma, Bo; Zhang, Qi; Wang, Guang-ji; A, Ji-ye; Wu, Di; Liu, Ying; Cao, Bei; Liu, Lin-sheng; Hu, Ying-ying; Wang, Yong-lu; Zheng, Ya-ya

    2011-01-01

    Aim: To explore the alteration of endogenous metabolites and identify potential biomarkers using metabolomic profiling with gas chromatography coupled a time-of-flight mass analyzer (GC/TOF-MS) in a rat model of estrogen-deficiency-induced obesity. Methods: Twelve female Sprague-Dawley rats six month of age were either sham-operated or ovariectomized (OVX). Rat blood was collected, and serum was analyzed for biomarkers using standard colorimetric methods with commercial assay kits and a metabolomic approach with GC/TOF-MS. The data were analyzed using multivariate statistical techniques. Results: A high body weight and body mass index inversely correlated with serum estradiol (E2) in the OVX rats compared to the sham rats. Estrogen deficiency also significantly increased serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol. Utilizing GC/TOF-MS-based metabolomic analysis and the partial least-squares discriminant analysis, the OVX samples were discriminated from the shams. Elevated levels of cholesterol, glycerol, glucose, arachidonic acid, glutamic acid, glycine, and cystine and reduced alanine levels were observed. Serum glucose metabolism, energy metabolism, lipid metabolism, and amino acid metabolism were involved in estrogen-deficiency-induced obesity in OVX rats. Conclusion: The series of potential biomarkers identified in the present study provided fingerprints of rat metabolomic changes during obesity and an overview of multiple metabolic pathways during the progression of obesity involving glucose metabolism, lipid metabolism, and amino acid metabolism. PMID:21293480

  5. Impact of a cafeteria diet and daily physical training on the rat serum metabolome

    PubMed Central

    Suárez-García, Susana; del Bas, Josep M.; Caimari, Antoni; Escorihuela, Rosa M.; Arola, Lluís; Suárez, Manuel

    2017-01-01

    Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS), which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST) or cafeteria diet (CAF) and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which moderate

  6. Impact of a cafeteria diet and daily physical training on the rat serum metabolome.

    PubMed

    Suárez-García, Susana; Del Bas, Josep M; Caimari, Antoni; Escorihuela, Rosa M; Arola, Lluís; Suárez, Manuel

    2017-01-01

    Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS), which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST) or cafeteria diet (CAF) and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which moderate

  7. Metabolomic responses to lumacaftor/ivacaftor in cystic fibrosis.

    PubMed

    Kopp, Benjamin T; McCulloch, Scott; Shrestha, Chandra L; Zhang, Shuzhong; Sarzynski, Lisa; Woodley, Frederick W; Hayes, Don

    2018-05-01

    Cystic fibrosis (CF) is a life-limiting disease caused by a defect in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Lumacaftor/Ivacaftor is a novel CFTR modulator approved for patients that are homozygous for Phe508del CFTR, but its clinical effectiveness varies amongst patients, making it difficult to determine clinical responders. Therefore, identifying biochemical biomarkers associated with drug response are clinically important for follow-up studies. Serum metabolomics was performed on twenty patients with CF pre- and 6-month post-Lumacaftor/Ivacaftor response via Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Correlation with clinical variables was performed. Metabolomics analysis demonstrated 188 differentially regulated metabolites between patients pre- and post-Lumacaftor/Ivacaftor initiation, with a predominance of lipid and amino acid alterations. The top 30 metabolites were able to differentiate pre- and post-Lumacaftor/Ivacaftor status in greater than 90% of patients via a random-forest confusion matrix. Alterations in bile acids, phospholipids, and bacteria-associated metabolites were the predominant changes associated with drug response. Importantly, changes in metabolic patterns were associated with clinical responders. Selected key lipid and amino acid metabolic pathways were significantly affected by Lumacaftor/Ivacaftor initiation and similar pathways were affected in clinical responders. Targeted metabolomics may provide useful and relevant biomarkers of CFTR modulator responses. © 2018 Wiley Periodicals, Inc.

  8. Metabolomic and proteomic analysis of a clonal insulin-producing beta-cell line (INS-1 832/13).

    PubMed

    Fernandez, Céline; Fransson, Ulrika; Hallgard, Elna; Spégel, Peter; Holm, Cecilia; Krogh, Morten; Wårell, Kristofer; James, Peter; Mulder, Hindrik

    2008-01-01

    Metabolites generated from fuel metabolism in pancreatic beta-cells control exocytosis of insulin, a process which fails in type 2 diabetes. To identify and quantify these metabolites, global and unbiased analysis of cellular metabolism is required. To this end, polar metabolites, extracted from the clonal 832/13 beta-cell line cultured at 2.8 and 16.7 mM glucose for 48 h, were derivatized followed by identification and quantification, using gas chromatography (GC) and mass spectrometry (MS). After culture at 16.7 mM glucose for 48 h, 832/13 beta-cells exhibited a phenotype reminiscent of glucotoxicity with decreased content and secretion of insulin. The metabolomic analysis revealed alterations in the levels of 7 metabolites derived from glycolysis, the TCA cycle and pentose phosphate shunt, and 4 amino acids. Principal component analysis of the metabolite data showed two clusters, corresponding to the cells cultured at 2.8 and 16.7 mM glucose, respectively. Concurrent changes in protein expression were analyzed by 2-D gel electrophoresis followed by LC-MS/MS. The identities of 86 spots corresponding to 75 unique proteins that were significantly different in 832/13 beta-cells cultured at 16.7 mM glucose were established. Only 5 of these were found to be metabolic enzymes that could be involved in the metabolomic alterations observed. Anticipated changes in metabolite levels in cells exposed to increased glucose were observed, while changes in enzyme levels were much less profound. This suggests that substrate availability, allosteric regulation, and/or post-translational modifications are more important determinants of metabolite levels than enzyme expression at the protein level.

  9. Isotopic disproportionation during hydrogen isotopic analysis of nitrogen-bearing organic compounds

    USGS Publications Warehouse

    Nair, Sreejesh; Geilmann, Heike; Coplen, Tyler B.; Qi, Haiping; Gehre, Matthias; Schimmelmann, Arndt; Brand, Willi A.

    2015-01-01

    Rationale High-precision hydrogen isotope ratio analysis of nitrogen-bearing organic materials using high-temperature conversion (HTC) techniques has proven troublesome in the past. Formation of reaction products other than molecular hydrogen (H2) has been suspected as a possible cause of incomplete H2 yield and hydrogen isotopic fractionation. Methods The classical HTC reactor setup and a modified version including elemental chromium, both operated at temperatures in excess of 1400 °C, have been compared using a selection of nitrogen-bearing organic compounds, including caffeine. A focus of the experiments was to avoid or suppress hydrogen cyanide (HCN) formation and to reach quantitative H2 yields. The technique also was optimized to provide acceptable sample throughput. Results The classical HTC reaction of a number of selected compounds exhibited H2 yields from 60 to 90 %. Yields close to 100 % were measured for the experiments with the chromium-enhanced reactor. The δ2H values also were substantially different between the two types of experiments. For the majority of the compounds studied, a highly significant relationship was observed between the amount of missing H2and the number of nitrogen atoms in the molecules, suggesting the pyrolytic formation of HCN as a byproduct. A similar linear relationship was found between the amount of missing H2 and the observed hydrogen isotopic result, reflecting isotopic fractionation. Conclusions The classical HTC technique to produce H2 from organic materials using high temperatures in the presence of glassy carbon is not suitable for nitrogen-bearing compounds. Adding chromium to the reaction zone improves the yield to 100 % in most cases. The initial formation of HCN is accompanied by a strong hydrogen isotope effect, with the observed hydrogen isotope results on H2 being substantially shifted to more negative δ2H values. The reaction can be understood as an initial disproportionation leading to H2 and HCN

  10. Fecal metabolome of the Hadza hunter-gatherers: a host-microbiome integrative view

    PubMed Central

    Turroni, Silvia; Fiori, Jessica; Rampelli, Simone; Schnorr, Stephanie L.; Consolandi, Clarissa; Barone, Monica; Biagi, Elena; Fanelli, Flaminia; Mezzullo, Marco; Crittenden, Alyssa N.; Henry, Amanda G.; Brigidi, Patrizia; Candela, Marco

    2016-01-01

    The recent characterization of the gut microbiome of traditional rural and foraging societies allowed us to appreciate the essential co-adaptive role of the microbiome in complementing our physiology, opening up significant questions on how the microbiota changes that have occurred in industrialized urban populations may have altered the microbiota-host co-metabolic network, contributing to the growing list of Western diseases. Here, we applied a targeted metabolomics approach to profile the fecal metabolome of the Hadza of Tanzania, one of the world’s few remaining foraging populations, and compared them to the profiles of urban living Italians, as representative of people in the post-industrialized West. Data analysis shows that during the rainy season, when the diet is primarily plant-based, Hadza are characterized by a distinctive enrichment in hexoses, glycerophospholipids, sphingolipids, and acylcarnitines, while deplete in the most common natural amino acids and derivatives. Complementary to the documented unique metagenomic features of their gut microbiome, our findings on the Hadza metabolome lend support to the notion of an alternate microbiome configuration befitting of a nomadic forager lifestyle, which helps maintain metabolic homeostasis through an overall scarcity of inflammatory factors, which are instead highly represented in the Italian metabolome. PMID:27624970

  11. Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context

    PubMed Central

    Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens

    2018-01-01

    Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group. PMID:29324799

  12. A novel approach to the simultaneous extraction and non-targeted analysis of the small molecules metabolome and lipidome using 96-well solid phase extraction plates with column-switching technology.

    PubMed

    Li, Yubo; Zhang, Zhenzhu; Liu, Xinyu; Li, Aizhu; Hou, Zhiguo; Wang, Yuming; Zhang, Yanjun

    2015-08-28

    This study combines solid phase extraction (SPE) using 96-well plates with column-switching technology to construct a rapid and high-throughput method for the simultaneous extraction and non-targeted analysis of small molecules metabolome and lipidome based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry. This study first investigated the columns and analytical conditions for small molecules metabolome and lipidome, separated by an HSS T3 and BEH C18 columns, respectively. Next, the loading capacity and actuation duration of SPE were further optimized. Subsequently, SPE and column switching were used together to rapidly and comprehensively analyze the biological samples. The experimental results showed that the new analytical procedure had good precision and maintained sample stability (RSD<15%). The method was then satisfactorily applied to more widely analyze the small molecules metabolome and lipidome to test the throughput. The resulting method represents a new analytical approach for biological samples, and a highly useful tool for researches in metabolomics and lipidomics. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Stable-carbon isotope ratios for sourcing the nerve-agent precursor methylphosphonic dichloride and its products

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Moran, James J.; Fraga, Carlos G.; Nims, Megan K.

    The ability to connect a chemical threat agent to a specific batch of a synthetic precursor can provide a fingerprint to contribute to effective forensic investigations. Stable isotope analysis can leverage intrinsic, natural isotopic variability within the molecules of a threat agent to unlock embedded chemical fingerprints in the material. Methylphosphonic dichloride (DC) is a chemical precursor to the nerve agent sarin. It is converted to methylphosphonic difluoride (DF) as part of the sarin synthesis process. We used a suite of commercially available DC stocks to both evaluate the potential for δ13C analysis to be used as a fingerprinting toolmore » in sarin-related investigations and to develop sample preparation techniques (using chemical hydrolysis) that can simplify isotopic analysis of DC and its synthetic products. We demonstrate that natural isotopic variability in DC results in at least three distinct, isotope-resolved clusters within the thirteen stocks we analyzed. Isotopic variability in the carbon feedstock (i.e., methanol) used for DC synthesis is likely inherited by the DC samples we measured. We demonstrate that the hydrolysis of DC and DF to methylphosphonic acid (MPA) can be used as a preparative step for isotopic analysis because the reaction does not impart a measureable isotopic fractionation. MPA is more chemically stable, less toxic, and easier to handle than DC or DF. Further, the hydrolysis method we demonstrated can be applied to a suite of other precursors or to sarin itself, thereby providing a potentially valuable forensic tool.« less

  14. Stable-Carbon Isotope Ratios for Sourcing the Nerve-Agent Precursor Methylphosphonic Dichloride and Its Products

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Moran, James J.; Fraga, Carlos G.; Nims, Megan K.

    The ability to connect a chemical threat agent to a specific batch of a synthetic precursor can provide a fingerprint to contribute to effective forensic investigations. Stable isotope analysis can leverage intrinsic, natural isotopic variability within the molecules of a threat agent to unlock embedded chemical fingerprints in the material. Methylphosphonic dichloride (DC) is a chemical precursor to the nerve agent sarin. DC is converted to methylphosphonic difluoride (DF) as part of the sarin synthesis process. We used a suite of commercially available DC stocks to both evaluate the potential for δ 13C analysis to be used as a fingerprintingmore » tool in sarin-related investigations and to develop sample preparation techniques (using chemical hydrolysis) that can simplify isotopic analysis of DC and its synthetic products. We demonstrate that natural isotopic variability in DC results in at least three distinct, isotope-resolved clusters within the thirteen stocks we analyzed. Isotopic variability in the carbon feedstock (i.e., methanol) used for DC synthesis is likely inherited by the DC samples we measured. Here, we demonstrate that the hydrolysis of DC and DF to methylphosphonic acid (MPA) can be used as a preparative step for isotopic analysis because the reaction does not impart a significant isotopic fractionation. MPA is more chemically stable, less toxic, and easier to handle than DC or DF. Further, the hydrolysis method we demonstrated can be applied to a suite of other precursors or to sarin itself, thereby providing a potentially valuable forensic tool.« less

  15. Stable-Carbon Isotope Ratios for Sourcing the Nerve-Agent Precursor Methylphosphonic Dichloride and Its Products

    DOE PAGES

    Moran, James J.; Fraga, Carlos G.; Nims, Megan K.

    2018-04-01

    The ability to connect a chemical threat agent to a specific batch of a synthetic precursor can provide a fingerprint to contribute to effective forensic investigations. Stable isotope analysis can leverage intrinsic, natural isotopic variability within the molecules of a threat agent to unlock embedded chemical fingerprints in the material. Methylphosphonic dichloride (DC) is a chemical precursor to the nerve agent sarin. DC is converted to methylphosphonic difluoride (DF) as part of the sarin synthesis process. We used a suite of commercially available DC stocks to both evaluate the potential for δ 13C analysis to be used as a fingerprintingmore » tool in sarin-related investigations and to develop sample preparation techniques (using chemical hydrolysis) that can simplify isotopic analysis of DC and its synthetic products. We demonstrate that natural isotopic variability in DC results in at least three distinct, isotope-resolved clusters within the thirteen stocks we analyzed. Isotopic variability in the carbon feedstock (i.e., methanol) used for DC synthesis is likely inherited by the DC samples we measured. Here, we demonstrate that the hydrolysis of DC and DF to methylphosphonic acid (MPA) can be used as a preparative step for isotopic analysis because the reaction does not impart a significant isotopic fractionation. MPA is more chemically stable, less toxic, and easier to handle than DC or DF. Further, the hydrolysis method we demonstrated can be applied to a suite of other precursors or to sarin itself, thereby providing a potentially valuable forensic tool.« less

  16. Stable-carbon isotope ratios for sourcing the nerve-agent precursor methylphosphonic dichloride and its products.

    PubMed

    Moran, James J; Fraga, Carlos G; Nims, Megan K

    2018-08-15

    The ability to connect a chemical threat agent to a specific batch of a synthetic precursor can provide a fingerprint to contribute to effective forensic investigations. Stable isotope analysis can leverage intrinsic, natural isotopic variability within the molecules of a threat agent to unlock embedded chemical fingerprints in the material. Methylphosphonic dichloride (DC) is a chemical precursor to the nerve agent sarin. DC is converted to methylphosphonic difluoride (DF) as part of the sarin synthesis process. We used a suite of commercially available DC stocks to both evaluate the potential for δ 13 C analysis to be used as a fingerprinting tool in sarin-related investigations and to develop sample preparation techniques (using chemical hydrolysis) that can simplify isotopic analysis of DC and its synthetic products. We demonstrate that natural isotopic variability in DC results in at least three distinct, isotope-resolved clusters within the thirteen stocks we analyzed. Isotopic variability in the carbon feedstock (i.e., methanol) used for DC synthesis is likely inherited by the DC samples we measured. We demonstrate that the hydrolysis of DC and DF to methylphosphonic acid (MPA) can be used as a preparative step for isotopic analysis because the reaction does not impart a significant isotopic fractionation. MPA is more chemically stable, less toxic, and easier to handle than DC or DF. Further, the hydrolysis method we demonstrated can be applied to a suite of other precursors or to sarin itself, thereby providing a potentially valuable forensic tool. Copyright © 2018. Published by Elsevier B.V.

  17. Metabolomic Analysis of Alfalfa (Medicago sativa L.) Root-Symbiotic Rhizobia Responses under Alkali Stress.

    PubMed

    Song, Tingting; Xu, Huihui; Sun, Na; Jiang, Liu; Tian, Pu; Yong, Yueyuan; Yang, Weiwei; Cai, Hua; Cui, Guowen

    2017-01-01

    Alkaline salts (e.g., NaHCO 3 and Na 2 CO 3 ) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na 2 SO 4 ) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa ( Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO 3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance.

  18. Metabolomic Analysis of Alfalfa (Medicago sativa L.) Root-Symbiotic Rhizobia Responses under Alkali Stress

    PubMed Central

    Song, Tingting; Xu, Huihui; Sun, Na; Jiang, Liu; Tian, Pu; Yong, Yueyuan; Yang, Weiwei; Cai, Hua; Cui, Guowen

    2017-01-01

    Alkaline salts (e.g., NaHCO3 and Na2CO3) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na2SO4) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa (Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance. PMID:28744296

  19. Whole grains beyond fibre: what can metabolomics tell us about mechanisms?

    PubMed

    Ross, Alastair B

    2015-08-01

    Dietary fibre alone does not fully explain the frequent association between greater intake of whole grains and reduced risk of disease in observational studies, and other phytochemicals or food structure may also play an important role. For all the observational evidence for the benefits of a whole-grain-rich diet, we have only limited knowledge of the mechanisms behind this reduction in disease risk, aside from the action of specific cereal fibres on reduction of blood cholesterol and the post-prandial glucose peak. Nutritional metabolomics, the global measurement and interpretation of metabolic profiles, assesses the interaction of food with the endogenous gene-protein cascade and the gut microbiome. This approach allows the generation of new hypotheses which account for systemic effects, rather than just focusing on one or two mechanisms or metabolic pathways. To date, animal and human trials using metabolomics to investigate mechanistic changes to metabolism on eating whole grains and cereal fractions have led to new hypotheses around mechanistic effects of whole grains. These include the role of cereals as a major source of dietary glycine betaine, a possible effect on phospholipid synthesis or metabolism, the role of branched-chain amino acids and improvements in insulin sensitivity, and the possibility that whole grains may have an effect on protein metabolism. These hypotheses help explain some of the observed effects of whole grains, although mechanistic studies using stable isotopes and fully quantitative measures are required to confirm these potential mechanisms.

  20. 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.

    PubMed

    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.