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Sample records for isotope-resolved metabolomic analysis

  1. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells.

    PubMed

    Fan, Teresa W-M; Tan, Jinlian; McKinney, Martin M; Lane, Andrew N

    2012-06-01

    We have developed a simple NMR-based method to determine the turnover of nucleotides and incorporation into RNA by stable isotope resolved metabolomics (SIRM) in A549 lung cancer cells. This method requires no chemical degradation of the nucleotides or chromatography. During cell growth, the free ribonucleotide pool is rapidly replaced by de novo synthesized nucleotides. Using [U-(13)C]-glucose and [U-(13)C,(15)N]-glutamine as tracers, we showed that virtually all of the carbons in the nucleotide riboses were derived from glucose, whereas glutamine was preferentially utilized over glucose for pyrimidine ring biosynthesis, via the synthesis of Asp through the Krebs cycle. Incorporation of the glutamine amido nitrogen into the N3 and N9 positions of the purine rings was also demonstrated by proton-detected (15)N NMR. The incorporation of (13)C from glucose into total RNA was measured and shown to be a major sink for the nucleotides during cell proliferation. This method was applied to determine the metabolic action of an anti-cancer selenium agent (methylseleninic acid or MSA) on A549 cells. We found that MSA inhibited nucleotide turnover and incorporation into RNA, implicating an important role of nucleotide metabolism in the toxic action of MSA on cancer cells.

  2. 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

  3. Stable Isotope Resolved Metabolomics Studies in Ex Vivo TIssue Slices

    PubMed Central

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

    2016-01-01

    An important component of this methodology is to assess the role of the tumor microenvironment on tumor growth and survival. To tackle this problem, we have adapted the original approach of Warburg 1, by combining thin tissue slices with Stable Isotope Resolved Metabolomics (SIRM) to determine detailed metabolic activity of human tissues. SIRM enables the tracing of metabolic transformations of source molecules such as glucose or glutamine over defined time periods, and is a requirement for detailed pathway tracing and flux analysis. In our approach, we maintain freshly resected tissue slices (both cancerous and non- cancerous from the same organ of the same subject) in cell culture media, and treat with appropriate stable isotope-enriched nutrients, e.g. 13C6-glucose or 13C5, 15N2 -glutamine. These slices are viable for at least 24 h, and make it possible to eliminate systemic influence on the target tissue metabolism while maintaining the original 3D cellular architecture. It is therefore an excellent pre-clinical platform for assessing the effect of therapeutic agents on target tissue metabolism and their therapeutic efficacy on individual patients 2,3. PMID:27158639

  4. NMR-based Stable Isotope Resolved Metabolomics in systems biochemistry.

    PubMed

    Lane, Andrew N; Fan, Teresa W-M

    2017-08-15

    Metabolism is the basic activity of live cells, and monitoring the metabolic state provides a dynamic picture of the cells or tissues, and how they respond to external changes, for in disease or treatment with drugs. NMR is an extremely versatile analytical tool that can be applied to a wide range of biochemical problems. Despite its modest sensitivity its versatility make it an ideal tool for analyzing biochemical dynamics both in vitro and in vivo, especially when coupled with its isotope editing capabilities, from which isotope distributions can be readily determined. These are critical for any analyses of flux in live organisms. This review focuses on the utility of NMR spectroscopy in metabolomics, with an emphasis on NMR applications in stable isotope-enriched tracer research for elucidating biochemical pathways and networks with examples from nucleotide biochemistry. The knowledge gained from this area of research provides a ready link to genomic, epigenomic, transcriptomic, and proteomic information to achieve systems biochemical understanding of living cells and organisms. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model.

    PubMed

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

    2011-06-01

    We have determined the time course of [U-(13)C]-glucose utilization and transformations in SCID mice via bolus injection of the tracer in the tail vein. Incorporation of (13)C into metabolites extracted from mouse blood plasma and several tissues (lung, heart, brain, liver, kidney, and skeletal muscle) were profiled by NMR and GC-MS, which helped ascertain optimal sampling times for different target tissues. We found that the time for overall optimal (13)C incorporation into tissue was 15-20 min but with substantial differences in (13)C labeling patterns of various organs that reflected their specific metabolism. Using this stable isotope resolved metabolomics (SIRM) approach, we have compared the (13)C metabolite profile of the lungs in the same mouse with or without an orthotopic lung tumor xenograft established from human PC14PE6 lung adenocarcinoma cells. The (13)C metabolite profile shows considerable differences in [U-(13)C]-glucose transformations between the two lung tissues, demonstrating the feasibility of applying SIRM to investigate metabolic networks of human cancer xenograft in the mouse model.

  6. Probing the metabolic phenotype of breast cancer cells by multiple tracer stable isotope resolved metabolomics.

    PubMed

    Lane, Andrew N; Tan, Julie; Wang, Yali; Yan, Jun; Higashi, Richard M; Fan, Teresa W-M

    2017-02-02

    Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using (13)C6-glucose, (13)C-1+2-glucose, (13)C5,(15)N2-Gln, (13)C3-glycerol, and (13)C8-octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment.

  7. Stable isotope resolved metabolomics revealed 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 ...

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

    PubMed Central

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

    2016-01-01

    Aims 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. Background 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

  9. Melatonin Decreases Glucose Metabolism in Prostate Cancer Cells: A (13)C 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.

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

    PubMed Central

    Hevia, David; Gonzalez-Menendez, Pedro; Fernandez-Fernandez, Mario; Cueto, Sergio; Mayo, Juan C.

    2017-01-01

    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, 13C stable isotope-resolved metabolomics in androgen sensitive LNCaP and insensitive PC-3 prostate cancer cells were employed. In addition to metabolite 13C-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 13C-labeling of tricarboxylic acid cycle metabolites and ATP production. In addition, melatonin reduces lactate 13C-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. PMID:28933733

  11. 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.

  12. 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

  13. High resolution TOF MS coupled to CE for the analysis of isotopically resolved intact proteins.

    PubMed

    Taichrib, Angelina; Pelzing, Matthias; Pellegrino, Cristoforo; Rossi, Mara; Neusüss, Christian

    2011-06-10

    Intact protein analysis by mass spectrometry is of great interest for the characterisation of biotechnological products. Exact mass measurement in combination with isotopic resolution allows the detection of modifications leading to small mass changes like deamidation or reduction of disulfide bonds directly on the level of the intact protein. Here, a concept is presented based on time-of-flight mass spectrometry. A bench top TOF MS and a high resolution TOF MS were used to resolve the isotopes of intact recombinant human growth hormone and intact human erythropoietin, respectively. Thus, these 22 and around 30kDa large proteins can be characterised sensitively in great detail and along with capillary electrophoretic separation unambiguous identification of minor protein modifications like deamidation is possible. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Error Analysis and Propagation in Metabolomics Data Analysis.

    PubMed

    Moseley, Hunter N B

    2013-01-01

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

  15. [Metabolomics analysis of taxadiene producing yeasts].

    PubMed

    Yan, Huifang; Ding, Mingzhu; Yuan, Yingjin

    2014-02-01

    In order to study the inherent difference among terpenes producing yeasts from the point of metabolomics, we selected taxadiene producing yeasts as the model system. The changes of cellular metabolites during fermentation log phase of artificial functional yeasts were determined using metabolomics methods. The results represented that compared to W303-1A as a blank control, the metabolites in glycolysis, tricarboxylic acid cycle (TCA) cycle and several amino acids were influenced. And due to the changes of metabolites, the growth of cells was inhibited to a certain extent. Among the metabolites identified, citric acid content in taxadiene producing yeasts changed the most, the decreasing amplitude reached 90% or more. Therefore, citric acid can be a marker metabolite for the future study of artificial functional yeasts. The metabolomics analysis of taxadiene producing yeasts can provide more information in further studies on optimization of terpenes production in heterologous chassis.

  16. Metabolomic analysis of sun exposed skin.

    PubMed

    Randhawa, Manpreet; Southall, Michael; Samaras, Samantha Tucker

    2013-08-01

    It is very well known that exposure of skin to sun chronically accelerates the mechanism of aging as well as making it more susceptible toward skin cancer. This aspect of aging has been studied very well through genomics and proteomics tools. In this study we have used a metabolomic approach for the first time to determine the differences in the metabolome from full thickness skin biopsies from sun exposed and sun protected sites. We have primarily investigated the energy metabolism and the oxidative pathway in sun exposed skin. Biochemical pathway analysis revealed that energy metabolism in photoexposed skin is predominantly anaerobic. The study also validated the increased oxidative stress in skin.

  17. (13)C NMR Metabolomics: INADEQUATE Network Analysis.

    PubMed

    Clendinen, Chaevien S; Pasquel, Christian; Ajredini, Ramadan; Edison, Arthur S

    2015-06-02

    The many advantages of (13)C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, (13)C NMR offers a straightforward measurement of these compounds. Two-dimensional (13)C-(13)C correlation experiments like INADEQUATE (incredible natural abundance double quantum transfer experiment) are ideal for the structural elucidation of natural products and have great but untapped potential for metabolomics analysis. We demonstrate a new and semiautomated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE data sets using an in silico INADEQUATE database. We demonstrate this approach using isotopically labeled Caenorhabditis elegans mixtures.

  18. Error Analysis and Propagation in Metabolomics Data Analysis

    PubMed Central

    Moseley, Hunter N.B.

    2013-01-01

    Error analysis plays a fundamental role in describing the uncertainty in experimental results. It has several fundamental uses in metabolomics including experimental design, quality control of experiments, the selection of appropriate statistical methods, and the determination of uncertainty in results. Furthermore, the importance of error analysis has grown with the increasing number, complexity, and heterogeneity of measurements characteristic of ‘omics research. The increase in data complexity is particularly problematic for metabolomics, which has more heterogeneity than other omics technologies due to the much wider range of molecular entities detected and measured. This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis. These methodologies include analytical derivation and approximation techniques, Monte Carlo error analysis, and error analysis in metabolic inverse problems. Current limitations of each methodology with respect to metabolomics data analysis are also discussed. PMID:23667718

  19. Integrated sampling procedure for metabolome analysis.

    PubMed

    Schaub, Jochen; Schiesling, Carola; Reuss, Matthias; Dauner, Michael

    2006-01-01

    Metabolome analysis, the analysis of large sets of intracellular metabolites, has become an important systems analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures < or =95 degrees C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s(-)(1) and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS analysis of metabolites was examined as well. The integrated sampling procedure was validated

  20. 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.

  1. NMR Metabolomics Analysis of Parkinson's Disease

    PubMed Central

    Lei, Shulei; Powers, Robert

    2015-01-01

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

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. Analysis of bacterial biofilms using NMR-based metabolomics.

    PubMed

    Zhang, Bo; Powers, Robert

    2012-06-01

    Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this 'social structure' of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms.

  7. Analysis of bacterial biofilms using NMR-based metabolomics

    PubMed Central

    Zhang, Bo; Powers, Robert

    2013-01-01

    Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this ‘social structure’ of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms. PMID:22800371

  8. Urine metabolomics analysis for kidney cancer detection and biomarker discovery.

    PubMed

    Kim, Kyoungmi; Aronov, Pavel; Zakharkin, Stanislav O; Anderson, Danielle; Perroud, Bertrand; Thompson, Ian M; Weiss, Robert H

    2009-03-01

    Renal cell carcinoma (RCC) accounts for 11,000 deaths per year in the United States. When detected early, generally serendipitously by imaging conducted for other reasons, long term survival is generally excellent. When detected with symptoms, prognosis is poor. Under these circumstances, a screening biomarker has the potential for substantial public health benefit. The purpose of this study was to evaluate the utility of urine metabolomics analysis for metabolomic profiling, identification of biomarkers, and ultimately for devising a urine screening test for RCC. Fifty urine samples were obtained from RCC and control patients from two institutions, and in a separate study, urine samples were taken from 13 normal individuals. Hydrophilic interaction chromatography-mass spectrometry was performed to identify small molecule metabolites present in each sample. Cluster analysis, principal components analysis, linear discriminant analysis, differential analysis, and variance component analysis were used to analyze the data. Previous work is extended to confirm the effectiveness of urine metabolomics analysis using a larger and more diverse patient cohort. It is now shown that the utility of this technique is dependent on the site of urine collection and that there exist substantial sources of variation of the urinary metabolomic profile, although group variation is sufficient to yield viable biomarkers. Surprisingly there is a small degree of variation in the urinary metabolomic profile in normal patients due to time since the last meal, and there is little difference in the urinary metabolomic profile in a cohort of pre- and postnephrectomy (partial or radical) renal cell carcinoma patients, suggesting that metabolic changes associated with RCC persist after removal of the primary tumor. After further investigations relating to the discovery and identity of individual biomarkers and attenuation of residual sources of variation, our work shows that urine metabolomics

  9. 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.

  10. Metabolomic Analysis of Three Mollicute Species

    PubMed Central

    Vanyushkina, Anna A.; Fisunov, Gleb Y.; Gorbachev, Alexey Y.; Kamashev, Dmitri E.; Govorun, Vadim M.

    2014-01-01

    We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer. PMID:24595068

  11. Computational Tools for the Secondary Analysis of Metabolomics Experiments

    PubMed Central

    Booth, Sean C.; Weljie, Aalim M.; Turner, Raymond J.

    2013-01-01

    Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before. PMID:24688685

  12. 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...

  13. 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

  14. Microbial Metabolomics

    PubMed Central

    Tang, Jane

    2011-01-01

    Microbial metabolomics constitutes an integrated component of systems biology. By studying the complete set of metabolites within a microorganism and monitoring the global outcome of interactions between its development processes and the environment, metabolomics can potentially provide a more accurate snap shot of the actual physiological state of the cell. Recent advancement of technologies and post-genomic developments enable the study and analysis of metabolome. This unique contribution resulted in many scientific disciplines incorporating metabolomics as one of their “omics” platforms. This review focuses on metabolomics in microorganisms and utilizes selected topics to illustrate its impact on the understanding of systems microbiology. PMID:22379393

  15. Kidney tumor biomarkers revealed by simultaneous multiple matrix metabolomics analysis.

    PubMed

    Ganti, Sheila; Taylor, Sandra L; Abu Aboud, Omran; Yang, Joy; Evans, Christopher; Osier, Michael V; Alexander, Danny C; Kim, Kyoungmi; Weiss, Robert H

    2012-07-15

    Metabolomics is increasingly being used in cancer biology for biomarker discovery and identification of potential novel therapeutic targets. However, a systematic metabolomics study of multiple biofluids to determine their interrelationships and to describe their use as tumor proxies is lacking. Using a mouse xenograft model of kidney cancer, characterized by subcapsular implantation of Caki-1 clear cell human kidney cancer cells, we examined tissue, serum, and urine all obtained simultaneously at baseline (urine) and at, or close to, animal sacrifice (urine, tissue, and plasma). Uniform metabolomics analysis of all three "matrices" was accomplished using gas chromatography- and liquid chromatography-mass spectrometry. Of all the metabolites identified (267 in tissue, 246 in serum, and 267 in urine), 89 were detected in all 3 matrices, and the majority was altered in the same direction. Heat maps of individual metabolites showed that alterations in serum were more closely related to tissue than was urine. Two metabolites, cinnamoylglycine and nicotinamide, were concordantly and significantly (when corrected for multiple testing) altered in tissue and serum, and cysteine-glutathione disulfide showed the highest change (232.4-fold in tissue) of any metabolite. On the basis of these and other considerations, three pathways were chosen for biologic validation of the metabolomic data, resulting in potential therapeutic target identification. These data show that serum metabolomics analysis is a more accurate proxy for tissue changes than urine and that tryptophan degradation (yielding anti-inflammatory metabolites) is highly represented in renal cell carcinoma, and support the concept that PPAR-α antagonism may be a potential therapeutic approach for this disease.

  16. 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

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

    PubMed

    Carneiro, Sónia; Pereira, Rui; Rocha, Isabel

    2014-01-01

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

  18. 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

  19. A Comprehensive Analysis of Metabolomics and Transcriptomics in Cervical Cancer

    PubMed Central

    Yang, Kai; Xia, Bairong; Wang, Wenjie; Cheng, Jinlong; Yin, Mingzhu; Xie, Hongyu; Li, Junnan; Ma, Libing; Yang, Chunyan; Li, Ang; Fan, Xin; Dhillon, Harman S.; Hou, Yan; Lou, Ge; Li, Kang

    2017-01-01

    Cervical cancer (CC) still remains a common and deadly malignancy among females in developing countries. More accurate and reliable diagnostic methods/biomarkers should be discovered. In this study, we performed a comprehensive analysis of metabolomics (285 samples) and transcriptomics (52 samples) on the potential diagnostic implication and metabolic characteristic description in cervical cancer. Sixty-two metabolites were different between CC and normal controls (NOR), in which 5 metabolites (bilirubin, LysoPC(17:0), n-oleoyl threonine, 12-hydroxydodecanoic acid and tetracosahexaenoic acid) were selected as candidate biomarkers for CC. The AUC value, sensitivity (SE), and specificity (SP) of these 5 biomarkers were 0.99, 0.98 and 0.99, respectively. We further analysed the genes in 7 significantly enriched pathways, of which 117 genes, that were expressed differentially, were mainly involved in catalytic activity. Finally, a fully connected network of metabolites and genes in these pathways was built, which can increase the credibility of our selected metabolites. In conclusion, our biomarkers from metabolomics could set a path for CC diagnosis and screening. Our results also showed that variables of both transcriptomics and metabolomics were associated with CC. PMID:28225065

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

    PubMed

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

    2013-11-01

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

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

    PubMed

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

    2017-07-16

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

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

    PubMed

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

    2013-12-17

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

  3. 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.

  4. Isotopic Ratio Outlier Analysis Global Metabolomics of Caenorhabditis elegans

    PubMed Central

    Szewc, Mark A.; Garrett, Timothy; Menger, Robert F.; Yost, Richard A.; Beecher, Chris; Edison, Arthur S.

    2014-01-01

    We demonstrate the global metabolic analysis of Caenorhabditis elegans stress responses using a mass spectrometry-based technique called Isotopic Ratio Outlier Analysis (IROA). In an IROA protocol, control and experimental samples are isotopically labeled with 95% and 5% 13C, and the two sample populations are mixed together for uniform extraction, sample preparation, and LC-MS analysis. This labeling strategy provides several advantages over conventional approaches: 1) compounds arising from biosynthesis are easily distinguished from artifacts, 2) errors from sample extraction and preparation are minimized because the control and experiment are combined into a single sample, 3) measurement of both the molecular weight and the exact number of carbon atoms in each molecule provides extremely accurate molecular formulae, and 4) relative concentrations of all metabolites are easily determined. A heat shock perturbation was conducted on C. elegans to demonstrate this approach. We identified many compounds that significantly changed upon heat shock, including several from the purine metabolism pathway, which we use to demonstrate the approach. The metabolomic response information by IROA may be interpreted in the context of a wealth of genetic and proteomic information available for C. elegans. Furthermore, the IROA protocol can be applied to any organism that can be isotopically labeled, making it a powerful new tool in a global metabolomics pipeline. PMID:24274725

  5. Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration

    PubMed Central

    Grapov, Dmitry; Barupal, Dinesh Kumar

    2017-01-01

    Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other ‘omic’ families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license. PMID:28141874

  6. Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration.

    PubMed

    Wanichthanarak, Kwanjeera; Fan, Sili; Grapov, Dmitry; Barupal, Dinesh Kumar; Fiehn, Oliver

    2017-01-01

    Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other 'omic' families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license.

  7. Analysis of urinary metabolites for metabolomic study by pressurized CEC.

    PubMed

    Xie, Guoxiang; Su, Mingming; Li, Peng; Gu, Xue; Yan, Chao; Qiu, Yunping; Li, Houkai; Jia, Wei

    2007-12-01

    A new approach for the metabolomic study of urinary samples using pressurized CEC (pCEC) with gradient elution is proposed as an alternative chromatographic separation tool with higher degree of resolution, selectivity, sensitivity, and efficiency. The pCEC separation of urinary samples was performed on a RP column packed with C(18), 5 microm particles with an ACN/water mobile phase containing TFA. The effects of the acid modifiers, applied voltage, mobile phase, and detection wavelength were systematically evaluated using eight spiked standards, as well as urine samples. A typical analytical trial of urine samples from Sprague Dawley (S.D.) rats exposed to high-energy diet was carried out following sample pretreatment. Significant differences in urinary metabolic profiles were observed between the high energy diet-induced obesity rats and the healthy control rats at the 6th wk postdose. Multivariate statistical analysis revealed the differential metabolites in response to the diet, which were partially validated with the putative standards. This work suggests that such a pCEC-based separation and analysis method may provide a new and cost-effective platform for metabolomic study uniquely positioned between the conventional chromatographic tools such as HPLC, and hyphenated analytical techniques such as LC-MS.

  8. Mass-based metabolomic analysis of soybean sprouts during germination.

    PubMed

    Gu, Eun-Ji; Kim, Dong Wook; Jang, Gwang-Ju; Song, Seong Hwa; Lee, Jae-In; Lee, Sang Bong; Kim, Bo-Min; Cho, Yeongrae; Lee, Hyeon-Jeong; Kim, Hyun-Jin

    2017-02-15

    We investigated the metabolite profile of soybean sprouts at 0, 1, 2, 3, and 4days after germination using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-MS (LC-MS) to understand the relationship between germination and nutritional quality. Data were analyzed by partial least squares-discriminant analysis (PLS-DA), and sprout samples were separated successfully using their PLS-DA scores. Fifty-eight metabolites, including macromolecular derivatives related to energy production, amino acids, myo-inositol metabolites, phytosterols, antioxidants, isoflavones, and soyasaponins, contributed to the separation. Amino acids, myo-inositol metabolites, isoflavone aglycones, B soyasaponins, antioxidants, and phytosterols, associated with health benefits and/or taste quality, increased with germination time while isoflavone glycosides and DDMP soyasaponins decreased. Based on these metabolites, the metabolomic pathway associated with energy production in soybean sprouts is suggested. Our data suggest that sprouting is a useful processing step to improve soybean nutritional quality, and metabolomic analysis is useful in understanding nutritional change during sprouting. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Phenotypic Characterization Analysis of Human Hepatocarcinoma by Urine Metabolomics Approach

    PubMed Central

    Liang, Qun; Liu, Han; Wang, Cong; Li, Binbing

    2016-01-01

    Hepatocarcinoma (HCC) is one of the deadliest cancers in the world and represents a significant disease burden. Better biomarkers are needed for early detection of HCC. Metabolomics was applied to urine samples obtained from HCC patients to discover noninvasive and reliable biomarkers for rapid diagnosis of HCC. Metabolic profiling was performed by LC-Q-TOF-MS in conjunction with multivariate data analysis, machine learning approaches, ingenuity pathway analysis and receiver-operating characteristic curves were used to select the metabolites which were used for the noninvasive diagnosis of HCC. Fifteen differential metabolites contributing to the complete separation of HCC patients from matched healthy controls were identified involving several key metabolic pathways. More importantly, five marker metabolites were effective for the diagnosis of human HCC, achieved a sensitivity of 96.5% and specificity of 83% respectively, could significantly increase the diagnostic performance of the metabolic biomarkers. Overall, these results illustrate the power of the metabolomics technology which has the potential as a non-invasive strategies and promising screening tool to evaluate the potential of the metabolites in the early diagnosis of HCC patients at high risk and provides new insight into pathophysiologic mechanisms. PMID:26805550

  10. A Web Service Framework for Interactive Analysis of Metabolomics Data.

    PubMed

    Lyutvinskiy, Yaroslav; Watrous, Jeramie D; Jain, Mohit; Nilsson, Roland

    2017-06-06

    Analyzing mass spectrometry-based metabolomics data presents a major challenge to metabolism researchers, as it requires downloading and processing large data volumes through complex "pipelines", even in cases where only a single metabolite or peak is of interest. This presents a significant hurdle for data sharing, reanalysis, or meta-analysis of existing data sets, whether locally stored or available from public repositories. Here we introduce mzAccess, a software system that provides interactive, online access to primary mass spectrometry data in real-time via a Web service protocol, circumventing the need for bulk data processing. mzAccess allows querying instrument data for spectra, chromatograms, or two-dimensional MZ-RT areas in either profile or centroid modes through a simple, uniform interface that is independent of vendor or instrument type. Using a cache mechanism, mzAccess achieves response times in the millisecond range for typical liquid chromatography-mass spectrometry (LC-MS) peaks, enabling real-time browsing of large data sets with hundreds or even thousands of samples. By simplifying access to metabolite data, we hope that this system will help enable data sharing and reanalysis in the metabolomics field.

  11. AN UNTARGETED METABOLOMICS ANALYSIS OF ANTIPSYCHOTIC USE IN BIPOLAR DISORDER

    PubMed Central

    Burghardt, Kyle J.; Evans, Simon J.; Wiese, Kristen M.; Ellingrod, Vicki L.

    2015-01-01

    Background Second generation antipsychotic (SGA) use in bipolar disorder is common and has proven effective in short-term trials. There continues to be a lack of understanding of the mechanisms underlying many of their positive and negative effects in bipolar disorder. This study aimed to describe the metabolite profiles of bipolar subjects treated with SGAs by comparing to metabolite profiles of bipolar subjects treated with lithium, and schizophrenia subjects treated with SGAs. Methods Cross-sectional, fasting untargeted serum metabolomic profiling was conducted in 82 subjects diagnosed with bipolar I disorder (n=30 on SGAs and n=32 on lithium) or schizophrenia (n=20). Metabolomic profiles of bipolar subjects treated with SGAs were compared to bipolar subjects treated with lithium and schizophrenia subjects treated with SGAs using multivariate methods. Results Partial lease square discriminant analysis (PLS-DA) plots showed separation between bipolar subjects treated with SGAs, bipolar subjects treated with lithium, or schizophrenia subjects treated with SGAs. Top influential metabolite features were associated with several pathways including that of polyunsaturated fatty acids, pyruvate, glucose and branched chain amino acids. Conclusions The findings from this study require further validation in pre and post treated bipolar and schizophrenia subjects, but suggest that the pharmacometabolome may be diagnosis specific. PMID:26314700

  12. Metabolomics analysis: Finding out metabolic building blocks

    PubMed Central

    2017-01-01

    In this paper we propose a new methodology for the analysis of metabolic networks. We use the notion of strongly connected components of a graph, called in this context metabolic building blocks. Every strongly connected component is contracted to a single node in such a way that the resulting graph is a directed acyclic graph, called a metabolic DAG, with a considerably reduced number of nodes. The property of being a directed acyclic graph brings out a background graph topology that reveals the connectivity of the metabolic network, as well as bridges, isolated nodes and cut nodes. Altogether, it becomes a key information for the discovery of functional metabolic relations. Our methodology has been applied to the glycolysis and the purine metabolic pathways for all organisms in the KEGG database, although it is general enough to work on any database. As expected, using the metabolic DAGs formalism, a considerable reduction on the size of the metabolic networks has been obtained, specially in the case of the purine pathway due to its relative larger size. As a proof of concept, from the information captured by a metabolic DAG and its corresponding metabolic building blocks, we obtain the core of the glycolysis pathway and the core of the purine metabolism pathway and detect some essential metabolic building blocks that reveal the key reactions in both pathways. Finally, the application of our methodology to the glycolysis pathway and the purine metabolism pathway reproduce the tree of life for the whole set of the organisms represented in the KEGG database which supports the utility of this research. PMID:28493998

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

    PubMed

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

    2010-09-01

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

  14. 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

  15. MetaboAnalyst: a web server for metabolomic data analysis and interpretation

    PubMed Central

    Xia, Jianguo; Psychogios, Nick; Young, Nelson; Wishart, David S.

    2009-01-01

    Metabolomics is a newly emerging field of ‘omics’ research that is concerned with characterizing large numbers of metabolites using NMR, chromatography and mass spectrometry. It is frequently used in biomarker identification and the metabolic profiling of cells, tissues or organisms. The data processing challenges in metabolomics are quite unique and often require specialized (or expensive) data analysis software and a detailed knowledge of cheminformatics, bioinformatics and statistics. In an effort to simplify metabolomic data analysis while at the same time improving user accessibility, we have developed a freely accessible, easy-to-use web server for metabolomic data analysis called MetaboAnalyst. Fundamentally, MetaboAnalyst is a web-based metabolomic data processing tool not unlike many of today's web-based microarray analysis packages. It accepts a variety of input data (NMR peak lists, binned spectra, MS peak lists, compound/concentration data) in a wide variety of formats. It also offers a number of options for metabolomic data processing, data normalization, multivariate statistical analysis, graphing, metabolite identification and pathway mapping. In particular, MetaboAnalyst supports such techniques as: fold change analysis, t-tests, PCA, PLS-DA, hierarchical clustering and a number of more sophisticated statistical or machine learning methods. It also employs a large library of reference spectra to facilitate compound identification from most kinds of input spectra. MetaboAnalyst guides users through a step-by-step analysis pipeline using a variety of menus, information hyperlinks and check boxes. Upon completion, the server generates a detailed report describing each method used, embedded with graphical and tabular outputs. MetaboAnalyst is capable of handling most kinds of metabolomic data and was designed to perform most of the common kinds of metabolomic data analyses. MetaboAnalyst is accessible at http://www.metaboanalyst.ca PMID:19429898

  16. 1H NMR Metabolomics Analysis of Glioblastoma Subtypes

    PubMed Central

    Cuperlovic-Culf, Miroslava; Ferguson, Dean; Culf, Adrian; Morin, Pier; Touaibia, Mohamed

    2012-01-01

    Glioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by unpredictable clinical behaviors that suggest distinct molecular subtypes. With the tumor metabolic phenotype being one of the hallmarks of cancer, we have set upon to investigate whether GBMs show differences in their metabolic profiles. 1H NMR analysis was performed on metabolite extracts from a selection of nine glioblastoma cell lines. Analysis was performed directly on spectral data and on relative concentrations of metabolites obtained from spectra using a multivariate regression method developed in this work. Both qualitative and quantitative sample clustering have shown that cell lines can be divided into four groups for which the most significantly different metabolites have been determined. Analysis shows that some of the major cancer metabolic markers (such as choline, lactate, and glutamine) have significantly dissimilar concentrations in different GBM groups. The obtained lists of metabolic markers for subgroups were correlated with gene expression data for the same cell lines. Metabolic analysis generally agrees with gene expression measurements, and in several cases, we have shown in detail how the metabolic results can be correlated with the analysis of gene expression. Combined gene expression and metabolomics analysis have shown differential expression of transporters of metabolic markers in these cells as well as some of the major metabolic pathways leading to accumulation of metabolites. Obtained lists of marker metabolites can be leveraged for subtype determination in glioblastomas. PMID:22528487

  17. Metabolomics integrated elementary flux mode analysis in large metabolic networks.

    PubMed

    Gerstl, Matthias P; Ruckerbauer, David E; Mattanovich, Diethard; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2015-03-10

    Elementary flux modes (EFMs) are non-decomposable steady-state pathways in metabolic networks. They characterize phenotypes, quantify robustness or identify engineering targets. An EFM analysis (EFMA) is currently restricted to medium-scale models, as the number of EFMs explodes with the network's size. However, many topologically feasible EFMs are biologically irrelevant. We present thermodynamic EFMA (tEFMA), which calculates only the small(er) subset of thermodynamically feasible EFMs. We integrate network embedded thermodynamics into EFMA and show that we can use the metabolome to identify and remove thermodynamically infeasible EFMs during an EFMA without losing biologically relevant EFMs. Calculating only the thermodynamically feasible EFMs strongly reduces memory consumption and program runtime, allowing the analysis of larger networks. We apply tEFMA to study the central carbon metabolism of E. coli and find that up to 80% of its EFMs are thermodynamically infeasible. Moreover, we identify glutamate dehydrogenase as a bottleneck, when E. coli is grown on glucose and explain its inactivity as a consequence of network embedded thermodynamics. We implemented tEFMA as a Java package which is available for download at https://github.com/mpgerstl/tEFMA.

  18. Metabolomics analysis in rats after administration of Datura stramonium.

    PubMed

    Zhang, Meiling; Bao, Shihui; Lin, Feiou; Lin, Yingying; Zhang, Lijing; Xu, Mengzhi; Huang, Xueli; Wen, Congcong; Hu, Lufeng; Lin, Guanyang

    2015-01-01

    This study aimed to evaluate the effect of Datura stramonium on rats by examining the differences in urine and serum metabolites between Datura stramonium groups and control group. SIMCA-P+12.0.1.0 software was used for partial least-squares discriminant analysis (PLS-DA) to screen for the differential metabolites. Fifteen metabolites in urine including malonic acid, pentanedioic acid, D-xylose, D-ribose, xylulose, azelaic acid, threitol, glycine, butanoic acid, D-mannose, D-gluconic acid, galactonic acid, myo-inositol, octadecanoic acid, pseudouridine and ten metabolites in serum including alanine, butanedioic acid, L-methionine, propanedioic acid, hexadecanoic acid, D-fructose, tetradecanoic acid, D-glucose, D-galactose, oleic acid were selected as the characteristic metabolites. The PLS-DA scores plot indicated that serum and urine metabolites have a variety of changes among low dose group, high dose group and control group. These metabolites were related with amino metabolism, lipid metabolism and energy metabolism. The result reflected the relationship between metabolites in rat fluid and Datura stramonium spectra. Potential differences in metabolites and metabolic pathway analysis showed that the establishment of urine and serum metabolomics methods for further evaluating drug has great significance.

  19. Metabolomics analysis in rats after administration of Datura stramonium

    PubMed Central

    Zhang, Meiling; Bao, Shihui; Lin, Feiou; Lin, Yingying; Zhang, Lijing; Xu, Mengzhi; Huang, Xueli; Wen, Congcong; Hu, Lufeng; Lin, Guanyang

    2015-01-01

    This study aimed to evaluate the effect of Datura stramonium on rats by examining the differences in urine and serum metabolites between Datura stramonium groups and control group. SIMCA-P+12.0.1.0 software was used for partial least-squares discriminant analysis (PLS-DA) to screen for the differential metabolites. Fifteen metabolites in urine including malonic acid, pentanedioic acid, D-xylose, D-ribose, xylulose, azelaic acid, threitol, glycine, butanoic acid, D-mannose, D-gluconic acid, galactonic acid, myo-inositol, octadecanoic acid, pseudouridine and ten metabolites in serum including alanine, butanedioic acid, L-methionine, propanedioic acid, hexadecanoic acid, D-fructose, tetradecanoic acid, D-glucose, D-galactose, oleic acid were selected as the characteristic metabolites. The PLS-DA scores plot indicated that serum and urine metabolites have a variety of changes among low dose group, high dose group and control group. These metabolites were related with amino metabolism, lipid metabolism and energy metabolism. The result reflected the relationship between metabolites in rat fluid and Datura stramonium spectra. Potential differences in metabolites and metabolic pathway analysis showed that the establishment of urine and serum metabolomics methods for further evaluating drug has great significance. PMID:26885052

  20. Metabolomics in food science.

    PubMed

    Cevallos-Cevallos, Juan Manuel; Reyes-De-Corcuera, José Ignacio

    2012-01-01

    Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. 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.

  2. Untargeted Metabolomic Analysis of Capsicum spp. by GC-MS.

    PubMed

    Aranha, Bianca Camargo; Hoffmann, Jessica Fernanda; Barbieri, Rosa Lia; Rombaldi, Cesar Valmor; Chaves, Fábio Clasen

    2017-09-01

    In order to conserve the biodiversity of Capsicum species and find genotypes with potential to be utilised commercially, Embrapa Clima Temperado maintains an active germplasm collection (AGC) that requires characterisation, enabling genotype selection and support for breeding programmes. The objective of this study was to characterise pepper accessions from the Embrapa Clima Temperado AGC and differentiate species based on their metabolic profile using an untargeted metabolomics approach. Cold (-20°C) methanol extraction residue of freeze-dried fruit samples was partitioned into water/methanol (A) and chloroform (B) fractions. The polar fraction (A) was derivatised and both fractions (A and B) were analysed by gas chromatography coupled to mass spectrometry (GC-MS). Data from each fraction was analysed using a multivariate principal component analysis (PCA) with XCMS software. Amino acids, sugars, organic acids, capsaicinoids, and hydrocarbons were identified. Outlying accessions including P116 (C. chinense), P46, and P76 (C. annuum) were observed in a PCA plot mainly due to their high sucrose and fructose contents. PCA also indicated a separation of P221 (C. annuum) and P200 (C. chinense), because of their high dihydrocapsaicin content. Although the metabolic profiling did not allow for grouping by species, it permitted the simultaneous identification and quantification of several compounds complementing and expanding the metabolic database of the studied Capsicum spp. in the AGC. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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

    PubMed

    Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

    2016-04-12

    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 (MetaCore(TM), 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.

  4. 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...

  5. 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...

  6. Metabolomic Analysis of Two Different Models of Delayed Preconditioning

    PubMed Central

    Bravo, Claudio; Kudej, Raymond K.; Yuan, Chujun; Yoon, Seonghun; Ge, Hui; Park, Ji Yeon; Tian, Bin; Stanley, William C.; Vatner, Stephen F.; Vatner, Dorothy E.; Yan, Lin

    2013-01-01

    Recently we described an ischemic preconditioning induced by repetitive coronary stenosis, which is induced by 6 episodes of non-lethal ischemia over 3 days, and which also resembles the hibernating myocardium phenotype. When compared with traditional second window of ischemic preconditioning using DNA microarrays, many genes which differed in the repetitive coronary stenosis appeared targeted to metabolism. Accordingly, the goal of this study was to provide a more in depth analysis of changes in metabolism in the different models of delayed preconditioning, i.e., second window and repetitive coronary stenosis. This was accomplished using a metabolomic approach based on liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) techniques. Myocardial samples from the ischemic section of porcine hearts subjected to both models of late preconditioning were compared against sham controls. Interestingly, although both models involve delayed preconditioning, their metabolic signatures were radically different; of the total number of metabolites that changed in both models (135 metabolites) only 7 changed in both models, and significantly more, p<0.01, were altered in the repetitive coronary stenosis (40%) than in the second window (8.1%). The most significant changes observed were in energy metabolism, e.g., phosphocreatine was increased 4 fold and creatine kinase activity increased by 27.2%, a pattern opposite from heart failure, suggesting that the repetitive coronary stenosis and potentially hibernating myocardium have enhanced stress resistance capabilities. The improved energy metabolism could also be a key mechanism contributing to the cardioprotection observed in the repetitive coronary stenosis and in hibernating myocardium. PMID:23127662

  7. Metabolomics analysis identifies different metabotypes of asthma severity.

    PubMed

    Reinke, Stacey N; Gallart-Ayala, Héctor; Gómez, Cristina; Checa, Antonio; Fauland, Alexander; Naz, Shama; Kamleh, Muhammad Anas; Djukanović, Ratko; Hinks, Timothy S C; Wheelock, Craig E

    2017-03-01

    In this study, we sought to determine whether asthma has a metabolic profile and whether this profile is related to disease severity.We characterised the serum from 22 healthy individuals and 54 asthmatics (12 mild, 20 moderate, 22 severe) using liquid chromatography-high-resolution mass spectrometry-based metabolomics. Selected metabolites were confirmed by targeted mass spectrometry assays of eicosanoids, sphingolipids and free fatty acids.We conclusively identified 66 metabolites; 15 were significantly altered with asthma (p≤0.05). Levels of dehydroepiandrosterone sulfate, cortisone, cortisol, prolylhydroxyproline, pipecolate and N-palmitoyltaurine correlated significantly (p<0.05) with inhaled corticosteroid dose, and were further shifted in individuals treated with oral corticosteroids. Oleoylethanolamide increased with asthma severity independently of steroid treatment (p<0.001). Multivariate analysis revealed two patterns: 1) a mean difference between controls and patients with mild asthma (p=0.025), and 2) a mean difference between patients with severe asthma and all other groups (p=1.7×10(-4)). Metabolic shifts in mild asthma, relative to controls, were associated with exogenous metabolites (e.g. dietary lipids), while those in moderate and severe asthma (e.g. oleoylethanolamide, sphingosine-1-phosphate, N-palmitoyltaurine) were postulated to be involved in activating the transient receptor potential vanilloid type 1 (TRPV1) receptor, driving TRPV1-dependent pathogenesis in asthma.Our findings suggest that asthma is characterised by a modest systemic metabolic shift in a disease severity-dependent manner, and that steroid treatment significantly affects metabolism.

  8. Metabolome analysis of gram-positive bacteria such as Staphylococcus aureus by GC-MS and LC-MS.

    PubMed

    Liebeke, Manuel; Dörries, Kirsten; Meyer, Hanna; Lalk, Michael

    2012-01-01

    The field of metabolomics has become increasingly important in the context of functional genomics. Together with other "omics" data, the investigation of the metabolome is an essential part of systems biology. Beside the analysis of human and animal biofluids, the investigation of the microbial physiology by methods of metabolomics has gained increased attention. For example, the analysis of metabolic processes during growth or virulence factor expression is crucially important to understand pathogenesis of bacteria. Common bioanalytical techniques for metabolome analysis include liquid and gas chromatographic methods coupled to mass spectrometry (LC-MS and GC-MS) and spectroscopic approaches such as NMR. In order to achieve metabolome data representing the physiological status of a microorganism, well-verified protocols for sampling and analysis are necessary. This chapter presents a detailed protocol for metabolome analysis of the Gram-positive bacterium Staphylococcus aureus. A detailed manual for cell sampling and metabolite extraction is given, followed by the description of the analytical procedures GC-MS and LC-MS. The advantages and limitations of each experimental setup are discussed. Here, a guideline specified for S. aureus metabolomics and information for important protocol steps are presented, to avoid common pitfalls in microbial metabolome analysis.

  9. Metabolomic mechanisms of gypenoside against liver fibrosis in rats: An integrative analysis of proteomics and metabolomics data

    PubMed Central

    Song, Ya-Nan; Dong, Shu; Wei, Bin; Liu, Ping; Zhang, Yong-Yu; Su, Shi-Bing

    2017-01-01

    Aims To investigate mechanisms and altered pathways of gypenoside against carbon tetrachloride (CCl4)-induced liver fibrosis based on integrative analysis of proteomics and metabolomics data. Methods CCl4-induced liver fibrosis rats were administrated gypenoside. The anti-fibrosis effects were evaluated by histomorphology and liver hydroxyproline (Hyp) content. Protein profiling and metabolite profiling of rats liver tissues were examined by isobaric tags for relative and absolute quantitation (iTRAQ) approach and gas chromatography-mass spectrometer (GC-MS) technology. Altered pathways and pivotal proteins and metabolites were searched by integrative analysis of proteomics and metabolomics data. The levels of some key proteins in altered pathways were determined by western blot. Results Histopathological changes and Hyp content in gypenoside group had significant improvements (P<0.05). Compared to liver fibrosis model group, we found 301 up-regulated and 296 down-regulated proteins, and 9 up-regulated and 8 down-regulated metabolites in gypenoside group. According to integrative analysis, some important pathways were found, including glycolysis or gluconeogenesis, fructose and mannose metabolism, glycine, serine and threonine metabolism, lysine degradation, arginine and proline metabolism, glutathione metabolism, and sulfur metabolism. Furthermore, the levels of ALDH1B1, ALDH2 and ALDH7A1 were found increased and restored to normal levels after gypenoside treated (P<0.05). Conclusions Gypenoside inhibited CCl4-induced liver fibrosis, which may be involved in the alteration of glycolysis metabolism and the protection against the damage of aldehydes and lipid peroxidation by up-regulating ALDH. PMID:28291813

  10. 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...

  11. Design and analysis of metabolomics studies in epidemiologic research: a primer on -omic technologies.

    PubMed

    Tzoulaki, Ioanna; Ebbels, Timothy M D; Valdes, Ana; Elliott, Paul; Ioannidis, John P A

    2014-07-15

    Metabolomics is the field of "-omics" research concerned with the comprehensive characterization of the small low-molecular-weight metabolites in biological samples. In epidemiology, it represents an emerging technology and an unprecedented opportunity to measure environmental and other exposures with improved precision and far less measurement error than with standard epidemiologic methods. Advances in the application of metabolomics in large-scale epidemiologic research are now being realized through a combination of improved sample preparation and handling, automated laboratory and processing methods, and reduction in costs. The number of epidemiologic studies that use metabolic profiling is still limited, but it is fast gaining popularity in this area. In the present article, we present a roadmap for metabolomic analyses in epidemiologic studies and discuss the various challenges these data pose to large-scale studies. We discuss the steps of data preprocessing, univariate and multivariate data analysis, correction for multiplicity of comparisons with correlated data, and finally the steps of cross-validation and external validation. As data from metabolomic studies accumulate in epidemiology, there is a need for large-scale replication and synthesis of findings, increased availability of raw data, and a focus on good study design, all of which will highlight the potential clinical impact of metabolomics in this field. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. 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.

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

    PubMed

    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.

  14. 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.

  15. Baseline correction for NMR spectroscopic metabolomics data analysis.

    PubMed

    Xi, Yuanxin; Rocke, David M

    2008-07-29

    We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically by using LOWESS (locally weighted scatterplot smoothing) regression to estimate the noise variance. We tested this method on 1D NMR spectra with different forms of baseline distortions, and demonstrated that it is effective for both regular 1D NMR spectra and metabolomics spectra with over-crowded peaks. Compared with the automatic baseline correction function in XWINNMR 3.5, the penalized smoothing method provides more accurate baseline correction for high-signal density metabolomics spectra.

  16. Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis

    PubMed Central

    Xi, Yuanxin; Rocke, David M

    2008-01-01

    Background We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically by using LOWESS (locally weighted scatterplot smoothing) regression to estimate the noise variance. Results We tested this method on 1D NMR spectra with different forms of baseline distortions, and demonstrated that it is effective for both regular 1D NMR spectra and metabolomics spectra with over-crowded peaks. Conclusion Compared with the automatic baseline correction function in XWINNMR 3.5, the penalized smoothing method provides more accurate baseline correction for high-signal density metabolomics spectra. PMID:18664284

  17. Metabolomic analysis of normal and sickle cell erythrocytes.

    PubMed

    Darghouth, D; Koehl, B; Junot, C; Roméo, P-H

    2010-09-01

    Metabolic signatures of specialized circulating hematopoietic cells in physiological or human hematological diseases start to be described. We use a simple and highly reproductive extraction method of erythrocytes metabolites coupled with a liquid chromatography-mass spectrometry based metabolites profiling method to determine metabolomes of normal and sickle cell erythrocytes. Sickle cell erythrocytes and normal erythrocytes metabolomes display major differences in glycolysis, in glutathione, in ascorbate metabolisms and in metabolites associated to membranes turnover. In addition, the amounts of metabolites derived from urea cycle and NO metabolism that partly take place within erythrocyte were different between normal and sickle cell erythrocytes. These results show that metabolic profiling of red blood cell diseases can now be determined and might indicate new biomarkers that can be used for the follow-up of sickle cell patients.

  18. 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...

  19. Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE).

    PubMed

    Kuligowski, Julia; Pérez-Guaita, David; Sánchez-Illana, Ángel; León-González, Zacarías; de la Guardia, Miguel; Vento, Máximo; Lock, Eric F; Quintás, Guillermo

    2015-07-07

    Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures across multiple sources is challenging due to the high variable to sample ratios and differences in intensity and noise range. In this work we apply a recent method, Joint and Individual Variation Explained (JIVE), for the integrated unsupervised analysis of metabolomic profiles from multiple data sources. This method separates the shared patterns among data sources (i.e. the joint structure) from the individual structure of each data source that is unrelated to the joint structure. Two examples are described to show the applicability of JIVE for the simultaneous analysis of multi-source data using: (i) plasma samples subjected to different analytical techniques, sample treatment and measurement conditions; and (ii) plasma and urine samples subjected to liquid chromatography-mass spectrometry measured using two ionization conditions.

  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. Metabolomic Analysis Using Liquid Chromatography/Mass Spectrometry for Gastric Cancer.

    PubMed

    Liang, Qun; Wang, Cong; Li, Binbing

    2015-08-01

    Metabolomics is a post-genomics research field for analysis of low molecular weight compounds in biological samples and has shown great potentials for elucidating complex mechanisms associated with diseases. However, metabolomics studies on gastric cancer (GC), which is the second leading cause of cancer death worldwide, remain scarce, and the molecular mechanisms to metabolomics phenotypes are also still not fully understood. This study reports that the metabolic pathways can be exploited as biomarkers for diagnosis and treatment of GC progression as a case study. Importantly, the urinary metabolites and metabolic patterns were analyzed by high-throughput liquid chromatography mass spectrometry (LC-MS) metabolomics strategy coupled with chemometric evaluation. Sixteen metabolites (nine upregulated and seven downregulated) were differentially expressed and may thus serve as potential urinary biomarkers for human GC. These metabolites were mainly involved in multiple metabolic pathways, including citrate cycle (malic acid, succinic acid, 2-oxoglutarate, citric acid), cyanoamino acid metabolism (glycine, alanine), primary bile acid biosynthesis (glycine, taurine, glycocholic acid), arginine and proline metabolism (urea, L-proline), and fatty acid metabolism (hexadecanoic acid), among others. Network analysis validated close association between these identified metabolites and altered metabolic pathways in a variety of biological processes. These results suggest that urine metabolic profiles have great potential in detecting GC and may aid in understanding its underlying mechanisms. It provides insight into disease pathophysiology and can serve as the basis for developing disease biomarkers and therapeutic interventions for GC diseases.

  2. 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

  3. Metabolomic Analysis of Mouse Embryonic Fibroblast Cells in Response to Autophagy Induced by Acute Starvation

    PubMed Central

    Shen, Sensen; Weng, Rui; Li, Linnan; Xu, Xinyuan; Bai, Yu; Liu, Huwei

    2016-01-01

    Autophagy-related protein 7 (Atg7) is essential in the formation of the autophagophore and is indispensable for autophagy induction. Autophagy will exist in lower level or even be blocked in cells without Atg7. Even though the possible signaling pathways of Atg7 have been proposed, the metabolomic responses under acute starvation in cells with and without Atg7 have not been elucidated. This study therefore was designed and aimed to reveal the metabolomics of Atg7-dependent autophagy through metabolomic analysis of Atg7−/− mouse embryonic fibroblast cells (MEFs) and wild-type MEFs along with the starvation time. 30 significantly altered metabolites were identified in response to nutrient stress, which were mainly associated with amino acid, energy, carbohydrate, and lipid metabolism. For the wild-type MEFs, the induction of autophagy protected cell survival with some up-regulated lipids during the first two hours’ starvation, while the subsequent apoptosis resulted in the decrease of cell viability after four hours’ starvation. For the Atg7−/− MEFs, apoptosis perhaps led to the deactivation of tricarboxylic acid (TCA) cycle due to the lack of autophagy, which resulted in the immediate drop of cellular viability under starvation. These results contributed to the metabolomic study and provided new insights into the mechanism associated with Atg7-dependent autophagy. PMID:27703171

  4. Circadian Variation of the Human Metabolome Captured by Real-Time Breath Analysis

    PubMed Central

    Martinez-Lozano Sinues, Pablo; Tarokh, Leila; Li, Xue; Kohler, Malcolm; Brown, Steven A.; Zenobi, Renato; Dallmann, Robert

    2014-01-01

    Circadian clocks play a significant role in the correct timing of physiological metabolism, and clock disruption might lead to pathological changes of metabolism. One interesting method to assess the current state of metabolism is metabolomics. Metabolomics tries to capture the entirety of small molecules, i.e. the building blocks of metabolism, in a given matrix, such as blood, saliva or urine. Using mass spectrometric approaches we and others have shown that a significant portion of the human metabolome in saliva and blood exhibits circadian modulation; independent of food intake or sleep/wake rhythms. Recent advances in mass spectrometry techniques have introduced completely non-invasive breathprinting; a method to instantaneously assess small metabolites in human breath. In this proof-of-principle study, we extend these findings about the impact of circadian clocks on metabolomics to exhaled breath. As previously established, our method allows for real-time analysis of a rich matrix during frequent non-invasive sampling. We sampled the breath of three healthy, non-smoking human volunteers in hourly intervals for 24 hours during total sleep deprivation, and found 111 features in the breath of all individuals, 36–49% of which showed significant circadian variation in at least one individual. Our data suggest that real-time mass spectrometric "breathprinting" has high potential to become a useful tool to understand circadian metabolism, and develop new biomarkers to easily and in real-time assess circadian clock phase and function in experimental and clinical settings. PMID:25545545

  5. Metagenomics, Metatranscriptomics, and Metabolomics Approaches for Microbiome Analysis

    PubMed Central

    Aguiar-Pulido, Vanessa; Huang, Wenrui; Suarez-Ulloa, Victoria; Cickovski, Trevor; Mathee, Kalai; Narasimhan, Giri

    2016-01-01

    Microbiomes are ubiquitous and are found in the ocean, the soil, and in/on other living organisms. Changes in the microbiome can impact the health of the environmental niche in which they reside. In order to learn more about these communities, different approaches based on data from multiple omics have been pursued. Metagenomics produces a taxonomical profile of the sample, metatranscriptomics helps us to obtain a functional profile, and metabolomics completes the picture by determining which byproducts are being released into the environment. Although each approach provides valuable information separately, we show that, when combined, they paint a more comprehensive picture. We conclude with a review of network-based approaches as applied to integrative studies, which we believe holds the key to in-depth understanding of microbiomes. PMID:27199545

  6. 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

  7. Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based Metabolomics

    PubMed Central

    2017-01-01

    As mass spectrometry-based metabolomics becomes more widely used in biomedical research, it is important to revisit existing data analysis paradigms. Existing data preprocessing efforts have largely focused on methods which start by extracting features separately from each sample, followed by a subsequent attempt to group features across samples to facilitate comparisons. We show that this preprocessing approach leads to unnecessary variability in peak quantifications that adversely impacts downstream analysis. We present a new method, bakedpi, for the preprocessing of both centroid and profile mode metabolomics data that relies on an intensity-weighted bivariate kernel density estimation on a pooling of all samples to detect peaks. This new method reduces this unnecessary quantification variability and increases power in downstream differential analysis. PMID:28221771

  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. MetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach

    PubMed Central

    2013-01-01

    Background Determining sample sizes for metabolomic experiments is important but due to the complexity of these experiments, there are currently no standard methods for sample size estimation in metabolomics. Since pilot studies are rarely done in metabolomics, currently existing sample size estimation approaches which rely on pilot data can not be applied. Results In this article, an analysis based approach called MetSizeR is developed to estimate sample size for metabolomic experiments even when experimental pilot data are not available. The key motivation for MetSizeR is that it considers the type of analysis the researcher intends to use for data analysis when estimating sample size. MetSizeR uses information about the data analysis technique and prior expert knowledge of the metabolomic experiment to simulate pilot data from a statistical model. Permutation based techniques are then applied to the simulated pilot data to estimate the required sample size. Conclusions The MetSizeR methodology, and a publicly available software package which implements the approach, are illustrated through real metabolomic applications. Sample size estimates, informed by the intended statistical analysis technique, and the associated uncertainty are provided. PMID:24261687

  10. Metabolomic and network analysis of astaxanthin-producing Haematococcus pluvialis under various stress conditions.

    PubMed

    Su, Yingxue; Wang, Jiangxin; Shi, Mengliang; Niu, Xiangfeng; Yu, Xinheng; Gao, Lianju; Zhang, Xiaoqing; Chen, Lei; Zhang, Weiwen

    2014-10-01

    Various combinations of acetate (Ac), Fe(2+) and high light (HL) stress conditions were evaluated to maximize astaxanthin accumulation and biomass production in Haematococcus pluvialis, and then GC-MS and LC-MS based metabolomics were applied to determine molecular mechanisms responsible for enhancing astaxanthin accumulation under the stress conditions. With the optimized analytical protocols, the GC-MS and LC-MS analyses allowed identification of 93 stable and 24 unstable intracellular metabolites from H. pluvialis, respectively. In addition, a metabolic network was constructed based on GC-MS metabolomic datasets using a weighted correlation network analysis (WGCNA) approach. The network analysis uncovered 2, 1 and 1 distinguished metabolic modules highly associated with HL, Fe(2+) & HL, and Ac & Fe(2+) & HL conditions, respectively. Finally, LC-MS analysis found that AKG, Glu and R5P may be metabolites associated with the Fe(2+) & HL condition. The study provided the first metabolomic view of cell growth and astaxanthin accumulation in H. pluvialis.

  11. Meta-analysis of global metabolomic data identifies metabolites associated with life-span extension.

    PubMed

    Patti, Gary J; Tautenhahn, Ralf; Johannsen, Darcy; Kalisiak, Ewa; Ravussin, Eric; Brüning, Jens C; Dillin, Andrew; Siuzdak, Gary

    2014-08-01

    The manipulation of distinct signaling pathways and transcription factors has been shown to influence life span in a cell-non-autonomous manner in multicellular model organisms such as Caenorhabditis elegans. These data suggest that coordination of whole-organism aging involves endocrine signaling, however, the molecular identities of such signals have not yet been determined and their potential relevance in humans is unknown. Here we describe a novel metabolomic approach to identify molecules directly associated with extended life span in C. elegans that represent candidate compounds for age-related endocrine signals. To identify metabolic perturbations directly linked to longevity, we developed metabolomic software for meta-analysis that enabled intelligent comparisons of multiple different mutants. Simple pairwise comparisons of long-lived glp-1, daf-2, and isp-1 mutants to their respective controls resulted in more than 11,000 dysregulated metabolite features of statistical significance. By using meta-analysis, we were able to reduce this number to six compounds most likely to be associated with life-span extension. Mass spectrometry-based imaging studies suggested that these metabolites might be localized to C. elegans muscle. We extended the metabolomic analysis to humans by comparing quadricep muscle tissue from young and old individuals and found that two of the same compounds associated with longevity in worms were also altered in human muscle with age. These findings provide candidate compounds that may serve as age-related endocrine signals and implicate muscle as a potential tissue regulating their levels in humans.

  12. 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.

  13. Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

    PubMed Central

    Lutz, Norbert W.; Béraud, Evelyne; Cozzone, Patrick J.

    2014-01-01

    Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor

  14. 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.

  15. (1)H HR-MAS NMR-based metabolomics analysis for dry-fermented sausage characterization.

    PubMed

    García-García, Ana Belén; Lamichhane, Santosh; Castejón, David; Cambero, Mª Isabel; Bertram, Hanne Christine

    2018-02-01

    Proton high-resolution magic angle spinning ((1)H HR-MAS) nuclear magnetic resonance (NMR) spectroscopy in combination with principal component analysis (PCA) was employed to characterize dry-fermented sausages salchichón type throughout the manufacturing process. (1)H HR-MAS NMR metabolite profiling was achieved from a small sample of intact sausage after 0, 2, 4, 7, 11 and 14days of drying. Intriguingly, the obtained results enabled the identification of the three main stages in the traditional production of salchichón. Formulation, fermentation and drying-ripening periods showed distinct and characteristic metabolomic profiles. Compositional changes related to microbial activity, as well as proteolytic and lipolytic phenomena, decisive steps in such a ripening process, could be monitored through the NMR spectra. This study shows the potential of (1)H HR-MAS as a rapid method for probing metabolomic profiles and compositional changes during sausages processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. 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

    2017-07-12

    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.

  17. Comparative analysis of the volatile metabolomes of Pseudomonas aeruginosa clinical isolates.

    PubMed

    Bean, Heather D; Rees, Christiaan A; Hill, Jane E

    2016-11-21

    Pseudomonas aeruginosa is a nearly ubiquitous Gram-negative organism, well known to occupy a multitude of environmental niches and cause human infections at a variety of bodily sites, due to its metabolic flexibility, secondary to extensive genetic heterogeneity at the species level. Because of its dynamic metabolism and clinical importance, we sought to perform a comparative analysis on the volatile metabolome (the 'volatilome') produced by P. aeruginosa clinical isolates. In this study, we analyzed the headspace volatile molecules of 24 P. aeruginosa clinical isolates grown in vitro, using 2D gas chromatography time-of-flight mass spectrometry (GC  ×  GC-TOFMS). We identified 391 non-redundant compounds that we associate with the growth and metabolism of P. aeruginosa (the 'pan-volatilome'). Of these, 70 were produced by all 24 isolates (the 'core volatilome'), 52 by only a single isolate, and the remaining 269 volatile molecules by a subset. Sixty-five of the detected compounds could be assigned putative compound identifications, of which 43 had not previously been associated with P. aeruginosa. Using the accessory volatile molecules, we determined the inter-strain variation in the metabolomes of these isolates, clustering strains by their metabotypes. Assessing the extent of metabolomic diversity in P. aeruginosa through an analysis of the volatile molecules that it produces is a critical next step in the identification of novel diagnostic or prognostic biomarkers.

  18. Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells

    PubMed Central

    Peterson, Amanda L.; Walker, Adam K.; Sloan, Erica K.; Creek, Darren J.

    2016-01-01

    Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions. PMID:27669323

  19. Targeted metabolomic analysis of plasma samples for the diagnosis of inherited metabolic disorders.

    PubMed

    Janečková, Hana; Hron, Karel; Wojtowicz, Petr; Hlídková, Eva; Barešová, Anna; Friedecký, David; Zídková, Lenka; Hornik, Petr; Behúlová, Darina; Procházková, Dagmar; Vinohradská, Hana; Pešková, Karolína; Bruheim, Per; Smolka, Vratislav; Sťastná, Sylvie; Adam, Tomáš

    2012-02-24

    Metabolomics has become an important tool in clinical research and diagnosis of human diseases. In this work we focused on the diagnosis of inherited metabolic disorders (IMDs) in plasma samples using a targeted metabolomic approach. The plasma samples were analyzed with the flow injection analysis method. All the experiments were performed on a QTRAP 5500 tandem mass spectrometer (AB SCIEX, U.S.A.) with electrospray ionization. The compounds were measured in a multiple reaction monitoring mode. We analyzed 50 control samples and 34 samples with defects in amino acid metabolism (phenylketonuria, maple syrup urine disease, tyrosinemia I, argininemia, homocystinuria, carbamoyl phosphate synthetase deficiency, ornithine transcarbamylase deficiency, nonketotic hyperglycinemia), organic acidurias (methylmalonic aciduria, propionic aciduria, glutaric aciduria I, 3-hydroxy-3-methylglutaric aciduria, isovaleric aciduria), and mitochondrial defects (medium-chain acyl-coenzyme A dehydrogenase deficiency, carnitine palmitoyltransferase II deficiency). The controls were distinguished from the patient samples by principal component analysis and hierarchical clustering. Approximately 80% of patients were clearly detected by absolute metabolite concentrations, the sum of variance for first two principle components was in the range of 44-55%. Other patient samples were assigned due to the characteristic ratio of metabolites (the sum of variance for first two principle components 77 and 83%). This study has revealed that targeted metabolomic tools with automated and unsupervised processing can be applied for the diagnosis of various IMDs. Copyright © 2011 Elsevier B.V. All rights reserved.

  20. Plasma metabolome analysis by integrated ionization rapid-resolution liquid chromatography/tandem mass spectrometry.

    PubMed

    Tian, He; Bai, Jinfa; An, Zhuoling; Chen, Yanhua; Zhang, Ruiping; He, Jiuming; Bi, Xiaofeng; Song, Yongmei; Abliz, Zeper

    2013-09-30

    Acquiring global information on plasma-endogenous metabolites challenges metabolomics. This study has been designed to investigate the suitability of integrated ionization rapid-resolution liquid chromatography/tandem mass spectrometry (RRLC/MS/MS) for different kinds of metabolites in complex plasma, and provides an approach for plasma metabolomics in acquiring more comprehensive data of metabolites. Integrated ionization of electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) combined with RRLC/MS/MS has been carried out to perform analysis on the global plasma metabolome of healthy volunteers. The contributions to the total numbers of ion features by RRLC/MS with ESI, APCI, and APPI in positive and negative ion modes were calculated. Representative unique and identical ions were identified. The intensities of identical ions were compared. Each of ESI, APCI, and APPI coupled with RRLC/MS has its own advantage over the other two techniques for certain types of metabolites in plasma. LC/ESI-MS is very sensitive for detecting glycerophosphocholines, glycerophosphoethanolamines, acyl carnitines, bile acids, sulfate, etc. LC/APCI-MS is suitable for analyzing cyclic alcohols, fatty acids, and linoleic acids. LC/APPI-MS proves to be appropriate in detecting steroids, sphingolipids, some amino acids, nucleosides, and purines in plasma. It is suggested that the integrated ionization LC/MS approach should be applied for global plasma metabolomics. Moreover, the results obtained demonstrate that it is preferable to choose certain techniques from LC/ESI-MS, LC/APCI-MS, and LC/APPI-MS for metabolite target analysis. Copyright © 2013 John Wiley & Sons, Ltd.

  1. Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources.

    PubMed

    van der Werf, Mariët J; Overkamp, Karin M; Muilwijk, Bas; Koek, Maud M; van der Werff-van der Vat, Bianca J C; Jellema, Renger H; Coulier, Leon; Hankemeier, Thomas

    2008-04-01

    Metabolomics is an emerging, powerful, functional genomics technology that involves the comparative non-targeted analysis of the complete set of metabolites in an organism. We have set-up a robust quantitative metabolomics platform that allows the analysis of 'snapshot' metabolomes. In this study, we have applied this platform for the comprehensive analysis of the metabolite composition of Pseudomonas putida S12 grown on four different carbon sources, i.e. fructose, glucose, gluconate and succinate. This paper focuses on the microbial aspects of analyzing comprehensive metabolomes, and demonstrates that metabolomes can be analyzed reliably. The technical (i.e. sample work-up and analytical) reproducibility was on average 10%, while the biological reproducibility was approximately 40%. Moreover, the energy charge values of the microbial samples generated were determined, and indicated that no biotic or abiotic changes had occurred during sample work-up and analysis. In general, the metabolites present and their concentrations were very similar after growth on the different carbon sources. However, specific metabolites showed large differences in concentration, especially the intermediates involved in the degradation of the carbon sources studied. Principal component discriminant analysis was applied to identify metabolites that are specific for, i.e. not necessarily the metabolites that show those largest differences in concentration, cells grown on either of these four carbon sources. For selected enzymatic reactions, i.e. the glucose-6-phosphate isomerase, triosephosphate isomerase and phosphoglyceromutase reactions, the apparent equilibrium constants (K(app)) were calculated. In several instances a carbon source-dependent deviation between the apparent equilibrium constant (K(app)) and the thermodynamic equilibrium constant (K(eq)) was observed, hinting towards a potential point of metabolic regulation or towards bottlenecks in biosynthesis routes. For glucose-6

  2. Metabolomic Analysis of Pressure-overloaded and Infarcted Mouse Hearts

    PubMed Central

    Sansbury, Brian E.; De Martino, Angelica M.; Xie, Zhengzhi; Brooks, Alan C.; Brainard, Robert E.; Watson, Lewis J.; DeFilippis, Andrew P.; Cummins, Timothy D.; Harbeson, Matthew A.; Brittian, Kenneth R.; Prabhu, Sumanth D.; Bhatnagar, Aruni; Jones, Steven P.; Hill, Bradford G.

    2014-01-01

    Background Cardiac hypertrophy and heart failure are associated with metabolic dysregulation and a state of chronic energy deficiency. Although several disparate changes in individual metabolic pathways have been described, there has been no global assessment of metabolomic changes in hypertrophic and failing hearts in vivo. Here, we investigated the impact of pressure overload and infarction on myocardial metabolism. Methods and Results Male C57BL/6J mice were subjected to transverse aortic constriction (TAC) or permanent coronary occlusion (myocardial infarction; MI). A combination of LC/MS/MS and GC/MS techniques was used to measure 288 metabolites in these hearts. Both TAC and MI were associated with profound changes in myocardial metabolism affecting up to 40% of all metabolites measured. Prominent changes in branched amino acids acids (BCAAs) were observed after 1 week of TAC and 5 days after MI. Changes in BCAAs after MI were associated with myocardial insulin resistance. Longer duration of TAC and MI led to a decrease in purines, acylcarnitines, fatty acids and several lysolipid and sphingolipid species, but a marked increase in pyrimidines as well as ascorbate, heme and other indices of oxidative stress. Cardiac remodeling and contractile dysfunction in hypertrophied hearts were associated also with large increases in myocardial, but not plasma, levels of the polyamines putrescine and spermidine as well as the collagen breakdown product prolylhydroxyproline. Conclusions These findings reveal extensive metabolic remodeling common to both hypertrophic and failing hearts that are indicative of extensive extracellular matrix remodeling, insulin resistance and perturbations in amino acid, lipid and nucleotide metabolism. PMID:24762972

  3. 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

  4. 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

  5. Metabolomics analysis of metabolic effects of nicotinamide phosphoribosyltransferase (NAMPT) inhibition on human cancer cells.

    PubMed

    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.

  6. Metabolomics analysis of collagen-induced arthritis in rats and interventional effects of oral tolerance.

    PubMed

    Ding, Xinghong; Hu, Jinbo; Li, Jinfeng; Zhang, Yan; Shui, Bingjie; Ding, Zhishan; Yao, Li; Fan, Yongsheng

    2014-08-01

    A serum metabolomics method based on rapid resolution liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RRLC-Q-TOF-MS) was performed for a holistic evaluation of the metabolic changes of collagen-induced arthritis (CIA) in rats and to assess the interventional effects of type II collagen (CII) in this model. Partial least-squares-discriminant analysis (PLS-DA) was employed to study the metabolic profiling of CIA rats and control rats. Ten metabolites, namely, 12(S)-HHTrE, 12(S)-HEPE, PGE2, TXB2, 12(S)-HETE, LysoPE(16:0), PE(O-18:0/0:0), Lyso-PE(18:2), Lyso-PE(20:4), and Lyso-PC(22:5) were identified as differential metabolites associated with the pathogenesis of CIA. These results suggested that dysregulation of the arachidonic acid (AA) and phospholipid metabolic networks is involved in the pathomechanism of CIA. Differential metabolomics and histopathological analyses demonstrated that CII inhibits the progress of arthritis. Furthermore, the therapeutic effects of CII on CIA may involve regulation of the disordered AA and phospholipid metabolic networks. This metabolomics study provides new insights into the pathogenesis of arthritis and, furthermore, indicates the potential mechanism underlying the significantly increased prevalence of metabolic syndrome, defined as a clustering of cardiovascular disease (CVD) risk factors, in arthritis patients. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Metabolomic patterns associated to QTc interval in shiftworkers: an explorative analysis

    PubMed Central

    Campagna, Marcello; Locci, Emanuela; Piras, Roberto; Noto, Antonio; Lecca, Luigi Isaia; Pilia, Ilaria; Cocco, Pierluigi; d’Aloja, Ernesto; Scano, Paola

    2016-01-01

    Abstract Objectives: 1H NMR-metabolomic approach was used to investigate QTc interval correlation with plasma metabolic profiles in shiftworkers. Methods: Socio-demographic data, electrocardiographic QTc interval and plasma metabolic profiles from 32 male shiftworkers, were correlated by multivariate regression analysis. Results: We found a positive correlation between QTc interval values, body mass index, glycemia and lactate level and a negative correlation between QTc interval and both pyroglutamate and 3-hydroxybutyrate plasma level. Conclusions: Our analysis provides evidence of the association between clinical, metabolic profiles and QTc interval values. This could be used to identify markers of early effects and/or susceptibility in shiftworkers. PMID:27121294

  8. 1H-NMR analysis provides a metabolomic profile of patients with multiple sclerosis

    PubMed Central

    Cocco, Eleonora; Murgia, Federica; Lorefice, Lorena; Barberini, Luigi; Poddighe, Simone; Frau, Jessica; Fenu, Giuseppe; Coghe, Giancarlo; Murru, Maria Rita; Murru, Raffaele; Del Carratore, Francesco; Atzori, Luigi

    2015-01-01

    Objective: To investigate the metabolomic profiles of patients with multiple sclerosis (MS) and to define the metabolic pathways potentially related to MS pathogenesis. Methods: Plasma samples from 73 patients with MS (therapy-free for at least 90 days) and 88 healthy controls (HC) were analyzed by 1H-NMR spectroscopy. Data analysis was conducted with principal components analysis followed by a supervised analysis (orthogonal partial least squares discriminant analysis [OPLS-DA]). The metabolites were identified and quantified using Chenomx software, and the receiver operating characteristic (ROC) curves were calculated. Results: The model obtained with the OPLS-DA identified predictive metabolic differences between the patients with MS and HC (R2X = 0.615, R2Y = 0.619, Q2 = 0.476; p < 0.001). The differential metabolites included glucose, 5-OH-tryptophan, and tryptophan, which were lower in the MS group, and 3-OH-butyrate, acetoacetate, acetone, alanine, and choline, which were higher in the MS group. The suitability of the model was evaluated using an external set of samples. The values returned by the model were used to build the corresponding ROC curve (area under the curve of 0.98). Conclusion: NMR metabolomic analysis was able to discriminate different metabolic profiles in patients with MS compared with HC. With the exception of choline, the main metabolic changes could be connected to 2 different metabolic pathways: tryptophan metabolism and energy metabolism. Metabolomics appears to represent a promising noninvasive approach for the study of MS. PMID:26740964

  9. High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

    PubMed

    Da Silva, Laeticia; Godejohann, Markus; Martin, François-Pierre J; Collino, Sebastiano; Bürkle, Alexander; Moreno-Villanueva, María; Bernhardt, Jürgen; Toussaint, Olivier; Grubeck-Loebenstein, Beatrix; Gonos, Efstathios S; Sikora, Ewa; Grune, Tilman; Breusing, Nicolle; Franceschi, Claudio; Hervonen, Antti; Spraul, Manfred; Moco, Sofia

    2013-06-18

    Metabolism is essential to understand human health. To characterize human metabolism, a high-resolution read-out of the metabolic status under various physiological conditions, either in health or disease, is needed. Metabolomics offers an unprecedented approach for generating system-specific biochemical definitions of a human phenotype through the capture of a variety of metabolites in a single measurement. The emergence of large cohorts in clinical studies increases the demand of technologies able to analyze a large number of measurements, in an automated fashion, in the most robust way. NMR is an established metabolomics tool for obtaining metabolic phenotypes. Here, we describe the analysis of NMR-based urinary profiles for metabolic studies, challenged to a large human study (3007 samples). This method includes the acquisition of nuclear Overhauser effect spectroscopy one-dimensional and J-resolved two-dimensional (J-Res-2D) (1)H NMR spectra obtained on a 600 MHz spectrometer, equipped with a 120 μL flow probe, coupled to a flow-injection analysis system, in full automation under the control of a sampler manager. Samples were acquired at a throughput of ~20 (or 40 when J-Res-2D is included) min/sample. The associated technical analysis error over the full series of analysis is 12%, which demonstrates the robustness of the method. With the aim to describe an overall metabolomics workflow, the quantification of 36 metabolites, mainly related to central carbon metabolism and gut microbial host cometabolism, was obtained, as well as multivariate data analysis of the full spectral profiles. The metabolic read-outs generated using our analytical workflow can therefore be considered for further pathway modeling and/or biological interpretation.

  10. High-Resolution Quantitative Metabolome Analysis of Urine by Automated Flow Injection NMR

    PubMed Central

    2013-01-01

    Metabolism is essential to understand human health. To characterize human metabolism, a high-resolution read-out of the metabolic status under various physiological conditions, either in health or disease, is needed. Metabolomics offers an unprecedented approach for generating system-specific biochemical definitions of a human phenotype through the capture of a variety of metabolites in a single measurement. The emergence of large cohorts in clinical studies increases the demand of technologies able to analyze a large number of measurements, in an automated fashion, in the most robust way. NMR is an established metabolomics tool for obtaining metabolic phenotypes. Here, we describe the analysis of NMR-based urinary profiles for metabolic studies, challenged to a large human study (3007 samples). This method includes the acquisition of nuclear Overhauser effect spectroscopy one-dimensional and J-resolved two-dimensional (J-Res-2D) 1H NMR spectra obtained on a 600 MHz spectrometer, equipped with a 120 μL flow probe, coupled to a flow-injection analysis system, in full automation under the control of a sampler manager. Samples were acquired at a throughput of ∼20 (or 40 when J-Res-2D is included) min/sample. The associated technical analysis error over the full series of analysis is 12%, which demonstrates the robustness of the method. With the aim to describe an overall metabolomics workflow, the quantification of 36 metabolites, mainly related to central carbon metabolism and gut microbial host cometabolism, was obtained, as well as multivariate data analysis of the full spectral profiles. The metabolic read-outs generated using our analytical workflow can therefore be considered for further pathway modeling and/or biological interpretation. PMID:23718684

  11. Untargeted Metabolomic Analysis of Amniotic Fluid in the Prediction of Preterm Delivery and Bronchopulmonary Dysplasia

    PubMed Central

    Baraldi, Eugenio; Giordano, Giuseppe; Stocchero, Matteo; Moschino, Laura; Zaramella, Patrizia; Tran, Maria Rosa; Carraro, Silvia; Romero, Roberto; Gervasi, Maria Teresa

    2016-01-01

    Objective Bronchopulmonary dysplasia (BPD) is a serious complication associated with preterm birth. A growing body of evidence suggests a role for prenatal factors in its pathogenesis. Metabolomics allows simultaneous characterization of low molecular weight compounds and may provide a picture of such a complex condition. The aim of this study was to evaluate whether an unbiased metabolomic analysis of amniotic fluid (AF) can be used to investigate the risk of spontaneous preterm delivery (PTD) and BPD development in the offspring. Study design We conducted an exploratory study on 32 infants born from mothers who had undergone an amniocentesis between 21 and 28 gestational weeks because of spontaneous preterm labor with intact membranes. The AF samples underwent untargeted metabolomic analysis using mass spectrometry combined with ultra-performance liquid chromatography. The data obtained were analyzed using multivariate and univariate statistical data analysis tools. Results Orthogonally Constrained Projection to Latent Structures-Discriminant Analysis (oCPLS2-DA) excluded effects on data modelling of crucial clinical variables. oCPLS2-DA was able to find unique differences in select metabolites between term (n = 11) and preterm (n = 13) deliveries (negative ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.65; positive ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.70), and between PTD followed by the development of BPD (n = 10), and PTD without BPD (n = 11) (negative data set: R2 = 0.48, mean AUC ROC in prediction = 0.73; positive data set: R2 = 0.55, mean AUC ROC in prediction = 0.71). Conclusions This study suggests that amniotic fluid metabolic profiling may be promising for identifying spontaneous preterm birth and fetuses at risk for developing BPD. These findings support the hypothesis that some prenatal metabolic dysregulations may play a key role in the pathogenesis of PTD and the development of BPD. PMID:27755564

  12. Human urinary biomarkers of dioxin exposure: analysis by metabolomics and biologically driven data dimensionality reduction.

    PubMed

    Jeanneret, Fabienne; Boccard, Julien; Badoud, Flavia; Sorg, Olivier; Tonoli, David; Pelclova, Daniela; Vlckova, Stepanka; Rutledge, Douglas N; Samer, Caroline F; Hochstrasser, Denis; Saurat, Jean-Hilaire; Rudaz, Serge

    2014-10-15

    Untargeted metabolomic approaches offer new opportunities for a deeper understanding of the molecular events related to toxic exposure. This study proposes a metabolomic investigation of biochemical alterations occurring in urine as a result of dioxin toxicity. Urine samples were collected from Czech chemical workers submitted to severe dioxin occupational exposure in a herbicide production plant in the late 1960s. Experiments were carried out with ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution quadrupole time-of-flight (QTOF) mass spectrometry. A chemistry-driven feature selection was applied to focus on steroid-related metabolites. Supervised multivariate data analysis allowed biomarkers, mainly related to bile acids, to be highlighted. These results supported the hypothesis of liver damage and oxidative stress for long-term dioxin toxicity. As a second step of data analysis, the information gained from the urine analysis of Victor Yushchenko after his poisoning was examined. A subset of relevant urinary markers of acute dioxin toxicity from this extreme phenotype, including glucuro- and sulfo-conjugated endogenous steroid metabolites and bile acids, was assessed for its ability to detect long-term effects of exposure. The metabolomic strategy presented in this work allowed the determination of metabolic patterns related to dioxin effects in human and the discovery of highly predictive subsets of biologically meaningful and clinically relevant compounds. These results are expected to provide valuable information for a deeper understanding of the molecular events related to dioxin toxicity. Furthermore, it presents an original methodology of data dimensionality reduction by using extreme phenotype as a guide to select relevant features prior to data modeling (biologically driven data reduction). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Metabolomic analysis of wild and transgenic Nicotiana langsdorffii plants exposed to abiotic stresses: unraveling metabolic responses.

    PubMed

    Scalabrin, Elisa; Radaelli, Marta; Rizzato, Giovanni; Bogani, Patrizia; Buiatti, Marcello; Gambaro, Andrea; Capodaglio, Gabriele

    2015-08-01

    Nicotiana langsdorffii plants, wild and transgenic for the Agrobacterium rhizogenes rol C gene and the rat glucocorticoid receptor (GR) gene, were exposed to different abiotic stresses (high temperature, water deficit, and high chromium concentrations). An untargeted metabolomic analysis was carried out in order to investigate the metabolic effects of the inserted genes in response to the applied stresses and to obtain a comprehensive profiling of metabolites induced during abiotic stresses. High-performance liquid chromatography separation (HPLC) coupled to high-resolution mass spectrometry (HRMS) enabled the identification of more than 200 metabolites, and statistical analysis highlighted the most relevant compounds for each plant treatment. The plants exposed to heat stress showed a unique set of induced secondary metabolites, some of which were known while others were not previously reported for this kind of stress; significant changes were observed especially in lipid composition. The role of trichome, as a protection against heat stress, is here suggested by the induction of both acylsugars and glykoalkaloids. Water deficit and Cr(VI) stresses resulted mainly in enhanced antioxidant (HCAs, polyamine) levels and in the damage of lipids, probably as a consequence of reactive oxygen species (ROS) production. Moreover, the ability of rol C expression to prevent oxidative burst was confirmed. The results highlighted a clear influence of GR modification on plant stress response, especially to water deficiency-a phenomenon whose applications should be further investigated. This study provides new insights into the field of system biology and demonstrates the importance of metabolomics in the study of plant functioning. Graphical Abstract Untargeted metabolomic analysis was applied to wild type, GR and RolC modified Nicotiana Langsdorffii plants exposed to heat, water and Cr(VI) stresses. The key metabolites, highly affected by stress application, were identified

  14. A Benchtop Fractionation Procedure for Subcellular Analysis of the Plant Metabolome

    PubMed Central

    Fürtauer, Lisa; Weckwerth, Wolfram; Nägele, Thomas

    2016-01-01

    Although compartmentation is a key feature of eukaryotic cells, biological research is frequently limited by methods allowing for the comprehensive subcellular resolution of the metabolome. It has been widely accepted that such a resolution would be necessary in order to approximate cellular biochemistry and metabolic regulation, yet technical challenges still limit both the reproducible subcellular fractionation and the sample throughput being necessary for a statistically robust analysis. Here, we present a method and a detailed protocol which is based on the non-aqueous fractionation technique enabling the assignment of metabolites to their subcellular localization. The presented benchtop method aims at unraveling subcellular metabolome dynamics in a precise and statistically robust manner using a relatively small amount of tissue material. The method is based on the separation of cellular fractions via density gradients consisting of organic, non-aqueous solvents. By determining the relative distribution of compartment-specific marker enzymes together with metabolite profiles over the density gradient it is possible to estimate compartment-specific metabolite concentrations by correlation. To support this correlation analysis, a spreadsheet is provided executing a calculation algorithm to determine the distribution of metabolites over subcellular compartments. The calculation algorithm performs correlation of marker enzyme activity and metabolite abundance accounting for technical errors, reproducibility and the resulting error propagation. The method was developed, tested and validated in three natural accessions of Arabidopsis thaliana showing different ability to acclimate to low temperature. Particularly, amino acids were strongly shuffled between subcellular compartments in a cold-sensitive accession while a cold-tolerant accession was characterized by a stable subcellular metabolic homeostasis. Finally, we conclude that subcellular metabolome analysis is

  15. 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.

  16. 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.

  17. NMR metabolomic analysis of exhaled breath condensate of asthmatic patients at two different temperatures.

    PubMed

    Motta, Andrea; Paris, Debora; D'Amato, Maria; Melck, Dominique; Calabrese, Cecilia; Vitale, Carolina; Stanziola, Anna A; Corso, Gaetano; Sofia, Matteo; Maniscalco, Mauro

    2014-12-05

    Exhaled breath condensate (EBC) collection is a noninvasive method to investigate lung diseases. EBC is usually collected with commercial/custom-made condensers, but the optimal condensing temperature is often unknown. As such, the physical and chemical properties of exhaled metabolites should be considered when setting the temperature, therefore requiring validation and standardization of the collecting procedure. EBC is frequently used in nuclear magnetic resonance (NMR)-based metabolomics, which unambiguously recognizes different pulmonary pathological states. Here we applied NMR-based metabolomics to asthmatic and healthy EBC samples collected with two commercial condensers operating at -27.3 and -4.8 °C. Thirty-five mild asthmatic patients and 35 healthy subjects were included in the study, while blind validation was obtained from 20 asthmatic and 20 healthy different subjects not included in the primary analysis. We initially analyzed the samples separately and assessed the within-day, between-day, and technical repeatabilities. Next, samples were interchanged, and, finally, all samples were analyzed together, disregarding the condensing temperature. Partial least-squares discriminant analysis of NMR spectra correctly classified samples, without any influence from the temperature. Input variables were either integral bucket areas (spectral bucketing) or metabolite concentrations (targeted profiling). We always obtained strong regression models (95%), with high average-quality parameters for spectral profiling (R(2) = 0.84 and Q(2) = 0.78) and targeted profiling (R(2) = 0.91 and Q(2) = 0.87). In particular, although targeted profiling clustering is better than spectral profiling, all models reproduced the relative metabolite variations responsible for class differentiation. This warrants that cross comparisons are reliable and that NMR-based metabolomics could attenuate some specific problems linked to standardization of EBC collection.

  18. Biomarker identification and pathway analysis by serum metabolomics of childhood acute lymphoblastic leukemia.

    PubMed

    Bai, Yunnuo; Zhang, Haitao; Sun, Xiaohan; Sun, Changhao; Ren, Lihong

    2014-09-25

    Acute lymphoblastic leukemia (ALL) is a common hematological malignant neoplasm that typically affects children. Although intense chemotherapeutic regimens have been useful to combat the disease, approximately 20% of patients will relapse despite treatment. Diagnosing ALL requires bone marrow puncture procedure, which many parents do not consent to for it is invasive. Additionally, metabolic alterations associated with the disease are unclear. Metabolic alterations associated with ALL were investigated by performing serum metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. Ingenuity Pathways Analysis (IPA) was also performed. Thirty metabolites (17 detected in positive mode and 13 in negative mode) were differentially expressed between patients with ALL and control patients; these metabolites were selected as potential biomarkers. Based on IPA analysis, glycerophospholipid metabolism is deregulated in patients with ALL and may represent an underlying metabolic pathway associated with disease progression. Metabolomics can be used to analyze the metabolic activity of ALL patients compared to healthy controls. The data we provide here suggest that glycerophospholipid metabolism may be a key mechanism underlying disease progression and development. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Meta-Analysis of Untargeted Metabolomic Data: Combining Results from Multiple Profiling Experiments

    PubMed Central

    Patti, Gary J.; Tautenhahn, Ralf; Siuzdak, Gary

    2013-01-01

    metaXCMS is a software program for the analysis of liquid chromatography/mass spectrometry-based untargeted metabolomic data that is designed to identify differences in metabolic profiles across multiple sample groups (e.g., “healthy” versus “active disease” versus “inactive disease”). By performing second-order (“meta”) analysis, the software facilitates prioritization of interesting metabolite features from large untargeted metabolomic datasets prior to the rate-limiting step of structural identification. Here we provide a detailed step-by-step protocol for going from raw mass spectrometry data to metaXCMS results visualized as Venn diagrams and exported Microsoft Excel spreadsheets. There is no upper limit to the number of sample groups or individual samples that can be compared by the software, and data from most commercial mass spectrometers is supported. The speed of the analysis depends on computational resources and data volume, but will generally be less than one day for most users. metaXCMS is freely available at http://metlin.scripps.edu/metaXCMS/. PMID:22343432

  20. 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.

  1. The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity.

    PubMed

    Chen, H-H; Tseng, Y J; Wang, S-Y; Tsai, Y-S; Chang, C-S; Kuo, T-C; Yao, W-J; Shieh, C-C; Wu, C-H; Kuo, P-H

    2015-08-01

    Mechanisms of the development of abnormal metabolic phenotypes among obese population are not yet clear. In this study, we aimed to screen metabolomes of both healthy and subjects with abnormal obesity to identify potential metabolic pathways that may regulate the different metabolic characteristics of obesity. We recruited subjects with body mass index (BMI) over 25 from the weight-loss clinic of a central hospital in Taiwan. Metabolic healthy obesity (MHO) is defined as without having any form of hyperglycemia, hypertension and dyslipidemia, while metabolic abnormal obesity (MAO) is defined as having one or more abnormal metabolic indexes. Serum-based metabolomic profiling using both liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry of 34 MHO and MAO individuals with matching age, sex and BMI was performed. Conditional logistic regression and partial least squares discriminant analysis were applied to identify significant metabolites between the two groups. Pathway enrichment and topology analyses were conducted to evaluate the regulated pathways. A differential metabolite panel was identified to be significantly differed in MHO and MAO groups, including L-kynurenine, glycerophosphocholine (GPC), glycerol 1-phosphate, glycolic acid, tagatose, methyl palmitate and uric acid. Moreover, several metabolic pathways were relevant in distinguishing MHO from MAO groups, including fatty acid biosynthesis, phenylalanine metabolism, propanoate metabolism, and valine, leucine and isoleucine degradation. Different metabolomic profiles and metabolic pathways are important for distinguishing between MHO and MAO groups. We have identified and discussed the key metabolites and pathways that may prove important in the regulation of metabolic traits among the obese, which could provide useful clues to study the underlying mechanisms of the development of abnormal metabolic phenotypes.

  2. Untargeted metabolomic analysis in naturally occurring canine diabetes mellitus identifies similarities to human Type 1 Diabetes.

    PubMed

    O'Kell, Allison L; Garrett, Timothy J; Wasserfall, Clive; Atkinson, Mark A

    2017-08-25

    While predominant as a disease entity, knowledge voids exist regarding the pathogenesis of canine diabetes. To test the hypothesis that diabetic dogs have similar metabolomic perturbations to humans with type 1 diabetes (T1D), we analyzed serum metabolomic profiles of breed- and body weight-matched, diabetic (n = 6) and healthy (n = 6) dogs by liquid chromatography-mass spectrometry (LC-MS) profiling. We report distinct clustering of diabetic and control groups based on heat map analysis of known and unknown metabolites. Random forest classification identified 5/6 dogs per group correctly with overall out of bag error rate = 16.7%. Diabetic dogs demonstrated significant upregulation of glycolysis/gluconeogenesis intermediates (e.g., glucose/fructose, C6H12O6, keto-hexose, deoxy-hexose, (P < 0.01)), with significant downregulation of tryptophan metabolism metabolites (e.g., picolinic acid, indoxyl sulfate, anthranilate, (P < 0.01)). Multiple amino acids (AA), AA metabolites, and bile acids were also significantly lower in diabetic versus healthy dogs (P < 0.05) with the exception of the branched chain AA valine, which was elevated in diabetic animals (P < 0.05). Metabolomic profiles in diabetic versus healthy dogs shared similarities with those reported in human T1D (e.g., alterations in glycolysis/gluconeogensis metabolites, bile acids, and elevated branched chain AA). Further studies are warranted to evaluate the utility of canine diabetes to provide novel mechanistic insights to the human disorder.

  3. 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.

  4. Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

    PubMed

    Choi, Young Hae; Sertic, Sarah; Kim, Hye Kyong; Wilson, Erica G; Michopoulos, Filippos; Lefeber, Alfons W M; Erkelens, Cornelis; Prat Kricun, Sergio D; Verpoorte, Robert

    2005-02-23

    The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

  5. Metabolomic analysis of human cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis diseases.

    PubMed

    Safaei, Akram; Arefi Oskouie, Afsaneh; Mohebbi, Seyed Reza; Rezaei-Tavirani, Mostafa; Mahboubi, Mohammad; Peyvandi, Maryam; Okhovatian, Farshad; Zamanian-Azodi, Mona

    2016-01-01

    Metabolome analysis is used to evaluate the characteristics and interactions of low molecular weight metabolites under a specific set of conditions. In cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatotic hepatitis (NASH) the liver does not function thoroughly due to long-term damage. Unfortunately the early detection of cirrhosis, HCC, NAFLD and NASH is a clinical problem and determining a sensitive, specific and predictive novel method based on biomarker discovery is an important task. On the other hand, metabolomics has been reported as a new and powerful technology in biomarker discovery and dynamic field that cause global comprehension of system biology. In this review, it has been collected a heterogeneous set of metabolomics published studies to discovery of biomarkers in researches to introduce diagnostic biomarkers for early detection and the choice of patient-specific therapies.

  6. Metabolomic analysis of human cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis diseases

    PubMed Central

    Safaei, Akram; Arefi Oskouie, Afsaneh; Mohebbi, Seyed Reza; Rezaei-Tavirani, Mostafa; Mahboubi, Mohammad; Peyvandi, Maryam; Okhovatian, Farshad; Zamanian-Azodi, Mona

    2016-01-01

    Metabolome analysis is used to evaluate the characteristics and interactions of low molecular weight metabolites under a specific set of conditions. In cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatotic hepatitis (NASH) the liver does not function thoroughly due to long-term damage. Unfortunately the early detection of cirrhosis, HCC, NAFLD and NASH is a clinical problem and determining a sensitive, specific and predictive novel method based on biomarker discovery is an important task. On the other hand, metabolomics has been reported as a new and powerful technology in biomarker discovery and dynamic field that cause global comprehension of system biology. In this review, it has been collected a heterogeneous set of metabolomics published studies to discovery of biomarkers in researches to introduce diagnostic biomarkers for early detection and the choice of patient-specific therapies. PMID:27458508

  7. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis.

    PubMed

    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

    2015-06-15

    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 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, 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. Together, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC.

  8. Analysis of the Compartmentalized Metabolome – A Validation of the Non-Aqueous Fractionation Technique

    PubMed Central

    Klie, Sebastian; Krueger, Stephan; Krall, Leonard; Giavalisco, Patrick; Flügge, Ulf-Ingo; Willmitzer, Lothar; Steinhauser, Dirk

    2011-01-01

    With the development of high-throughput metabolic technologies, a plethora of primary and secondary compounds have been detected in the plant cell. However, there are still major gaps in our understanding of the plant metabolome. This is especially true with regards to the compartmental localization of these identified metabolites. Non-aqueous fractionation (NAF) is a powerful technique for the determination of subcellular metabolite distributions in eukaryotic cells, and it has become the method of choice to analyze the distribution of a large number of metabolites concurrently. However, the NAF technique produces a continuous gradient of metabolite distributions, not discrete assignments. Resolution of these distributions requires computational analyses based on marker molecules to resolve compartmental localizations. In this article we focus on expanding the computational analysis of data derived from NAF. Along with an experimental workflow, we describe the critical steps in NAF experiments and how computational approaches can aid in assessing the quality and robustness of the derived data. For this, we have developed and provide a new version (v1.2) of the BestFit command line tool for calculation and evaluation of subcellular metabolite distributions. Furthermore, using both simulated and experimental data we show the influence on estimated subcellular distributions by modulating important parameters, such as the number of fractions taken or which marker molecule is selected. Finally, we discuss caveats and benefits of NAF analysis in the context of the compartmentalized metabolome. PMID:22645541

  9. Metabolomic analysis of isonitrosoacetophenone-induced perturbations in phenolic metabolism of Nicotiana tabacum cells.

    PubMed

    Madala, Ntakadzeni E; Steenkamp, Paul A; Piater, Lizelle A; Dubery, Ian A

    2013-10-01

    Plants have developed biochemical and molecular responses to adapt to different stress environments. One of the characteristics of the multi-component defence response is the production of defence-related metabolites. Plant defences can be triggered by various stimuli, including synthetic or naturally occurring molecules, especially those derived from pathogens. In the current study, Nicotiana tabacum cell suspensions were treated with isonitrosoacetophenone (INAP), a subcomponent of a plant-derived stress metabolite with anti-fungal and anti-oxidant properties, in order to investigate the effect thereof on cellular metabolism. Subsequent metabolomic-based analyses were employed to evaluate changes in the metabolome. UPLC-MS in conjunction with multivariate data analyses was found to be an appropriate approach to study the effect of chemical inducers like INAP on plant metabolism in this model system. Principal component analysis (PCA) indicated that INAP is capable of inducing time-dependent metabolic perturbations in the cultured cells. Orthogonal projection to latent structures discriminant analysis (OPLS-DA) revealed metabolites of which the levels are affected by INAP, and eight of these were tentatively annotated from the mass spectral data and online databases. These metabolites are known in the context of plant stress- and defence responses and include benzoic- or cinnamic acid derivatives that are either glycosylated or quinilated as well as flavonoid derivatives. The results indicate that INAP affects the shikimate-, phenylpropanoid- and flavonoid pathways, the products of which may subsequently lead to an anti-oxidant environment in vivo.

  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. Metabolomics Analysis of the Larval Head of the Silkworm, Bombyx mori.

    PubMed

    Li, Yi; Wang, Xin; Chen, Quanmei; Hou, Yong; Xia, Qingyou; Zhao, Ping

    2016-09-20

    The head, which performs many biological functions, is the most complicated structure of an insect. Development, locomotor behavior, food intake, environmental sensing, and signal transduction are all controlled by the insect's head. As a well-studied insect in Lepidoptera, the silkworm head has an additional function of spinning silk fibers. To understand which molecules are involved in these physiological activities, we performed a metabolomics analysis of silkworm heads. By integrating GC-MS and LC-MS/MS, 90 metabolites were identified in the larval heads of silkworms. These were classified into 13 categories, including amino acids, sugars, organic acids, nucleotides, alcohols, and fatty acids. Informatics analysis revealed that these metabolites are involved in cellular processes, environmental information processing, genetic information processing, human diseases, metabolism, organismal systems, and other pathways. The identified metabolites and pathways are involved in biological processes such as signal transduction, carbohydrate metabolism, endocrine activities, and sensory activities; reflecting the functions of various organs in silkworm heads. Thus, our findings provide references which elucidate the potential functions of the silkworm head and will be of great value for the metabolomics research of silkworms and other insects.

  12. Plasma metabolomic analysis of human hepatocellular carcinoma: Diagnostic and therapeutic study

    PubMed Central

    Li, Jinquan; Feng, Jianghua; Chen, Zhong; Wang, Xiaomin

    2016-01-01

    Many hepatocellular carcinoma (HCC) patients suffer from late stages when diagnosed, leading to dismal prospects for cure. Improving the diagnosis and treatment of HCC remains a challenge. In this work, NMR-based metabolomic techniques were used to investigate the metabolic alterations of HCC patients from different pathological backgrounds. Metabolic improvement of clinical surgical treatments or transcatheter arterial chemoembolization (TACE) for recurrent or metastatic HCC was also evaluated. HCC was characterized by enhanced lipid metabolism and high consumption in response to liver injury. Expectedly, higher consumption of glucose and lactate production in TACE group confirmed that recurrent or metastatic HCC is more active in citric acid cycle and oxidative phosphorylation. However, TACE or surgical treatments did not immediately improve the metabolic profiles of HCC patients. Combining multivariate statistical analyses with univariate t-test, a series of characteristic metabolites were identified and served as biomarkers for discrimination of HCC patients in different pathological backgrounds. The relative metabolic pathway analyses help to get insight into the underlying biochemical mechanism and extend clinical relevance. Furthermore, algorithm of support vector classification was used to identify HCC and control subjects, and diagnostic sensitivity and specificity reached to 100% and 81.08% respectively by receiver operating characteristic analysis. It is concluded that NMR-based metabolomic analysis of plasma can provide a powerful approach to discover diagnostic and therapeutic biomarkers, and subsequently contribute to clinical disease management. PMID:27322079

  13. Metabolomics Analysis of the Larval Head of the Silkworm, Bombyx mori

    PubMed Central

    Li, Yi; Wang, Xin; Chen, Quanmei; Hou, Yong; Xia, Qingyou; Zhao, Ping

    2016-01-01

    The head, which performs many biological functions, is the most complicated structure of an insect. Development, locomotor behavior, food intake, environmental sensing, and signal transduction are all controlled by the insect’s head. As a well-studied insect in Lepidoptera, the silkworm head has an additional function of spinning silk fibers. To understand which molecules are involved in these physiological activities, we performed a metabolomics analysis of silkworm heads. By integrating GC-MS and LC-MS/MS, 90 metabolites were identified in the larval heads of silkworms. These were classified into 13 categories, including amino acids, sugars, organic acids, nucleotides, alcohols, and fatty acids. Informatics analysis revealed that these metabolites are involved in cellular processes, environmental information processing, genetic information processing, human diseases, metabolism, organismal systems, and other pathways. The identified metabolites and pathways are involved in biological processes such as signal transduction, carbohydrate metabolism, endocrine activities, and sensory activities; reflecting the functions of various organs in silkworm heads. Thus, our findings provide references which elucidate the potential functions of the silkworm head and will be of great value for the metabolomics research of silkworms and other insects. PMID:27657048

  14. MetaboAnalyst 2.0--a comprehensive server for metabolomic data analysis.

    PubMed

    Xia, Jianguo; Mandal, Rupasri; Sinelnikov, Igor V; Broadhurst, David; Wishart, David S

    2012-07-01

    First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server's multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.

  15. MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

    PubMed Central

    Xia, Jianguo; Mandal, Rupasri; Sinelnikov, Igor V.; Broadhurst, David; Wishart, David S.

    2012-01-01

    First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well. PMID:22553367

  16. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites.

    PubMed

    Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C

    2016-09-30

    Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

  17. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

    PubMed Central

    Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C.

    2016-01-01

    Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions. PMID:27706030

  18. Metabolomics in dyslipidemia.

    PubMed

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

    2014-01-01

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

  19. Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer.

    PubMed

    Kim, Kyoungmi; Taylor, Sandra L; Ganti, Sheila; Guo, Lining; Osier, Michael V; Weiss, Robert H

    2011-05-01

    Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy.

  20. Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis

    PubMed Central

    Kind, Tobias; Cho, Eunho; Park, Taeeun D.; Deng, Nan; Liu, Zhenqiu; Lee, Tack; Fiehn, Oliver; Kim, Jayoung

    2016-01-01

    This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms. PMID:27976711

  1. 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.

  2. Serum Metabolomics Analysis of Quercetin against Acrylamide-Induced Toxicity in Rats.

    PubMed

    Yang, Shuang; Cao, Can; Chen, Shuai; Hu, Liyan; Bao, Wei; Shi, Haidan; Zhao, Xiujuan; Sun, Changhao

    2016-12-07

    The current study aimed to investigate whether quercetin plays a protective role in acrylamide (AA)-induced toxicity using a metabolomics approach. Rats were randomly divided into groups as follows: control, treated with AA [5 mg/kg body weight (bw)], treated with different dosages of quercetin (10 and 50 mg/kg bw, respectively), and treated with two dosages of quercetin plus AA. After a 16 week treatment, rat serum was collected for metabolomics analysis. Biochemical tests and examination of liver histopathology were further conducted to verify metabolic alterations. Twelve metabolites were identified for which intensities were significantly changed (increased or reduced) as a result of the treatment. These metabolites included isorhamnetin, citric acid, pantothenic acid, isobutyryl-l-carnitine, eicosapentaenoic acid, docosahexaenoic acid, sphingosine 1-phosphate, lysoPC(20:4), lysoPC(22:6), lysoPE(20:3), undecanedioic acid, and dodecanedioic acid. The results indicate that quercetin (50 mg/kg bw) exerts partial protective effects on AA-induced toxicity by reducing oxidative stress, protecting the mitochondria, and regulating lipid metabolism.

  3. 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.

  4. Integrated proteomics and metabolomics analysis of rat testis: Mechanism of arsenic-induced male reproductive toxicity

    PubMed Central

    Huang, Qingyu; Luo, Lianzhong; Alamdar, Ambreen; Zhang, Jie; Liu, Liangpo; Tian, Meiping; Eqani, Syed Ali Musstjab Akber Shah; Shen, Heqing

    2016-01-01

    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. PMID:27585557

  5. 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

  6. 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., 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.

  7. Metabolomics in food analysis: application to the control of forbidden substances.

    PubMed

    Dervilly-Pinel, Gaud; Courant, Frédérique; Chéreau, Sylvain; Royer, Anne-Lise; Boyard-Kieken, Fanny; Antignac, Jean-Philippe; Monteau, Fabrice; Le Bizec, Bruno

    2012-08-01

    Metabolomics is a science of interest in food analysis to describe and predict properties of food products and processes. It includes the development of analytical methods with the ultimate goal being the identification of so-called 'quality markers', (i.e. sets of metabolites that correlate with, for example, quality, safety, taste, or fragrance of foodstuffs). In turn, these metabolites are influenced by factors as genetic differences of the raw food ingredients (such as animal breed or crop species differences), growth conditions (such as climate, irrigation strategy, or feeding) or production conditions (such as temperature, acidity, or pressure). In cases where the routine-based measurement of a food property faces some limitations such as the lack of knowledge regarding the target compounds to monitor, monitoring based on a limited set of crucial biomarkers is a good alternative, which is of great interest for food safety purposes regarding growth promoting practices. Such an approach may be more efficient than using a classic approach based on a limited set of known metabolites of anabolic compounds. In this context, screening strategies allowing detection of the physiological response resulting from anabolic compound administration are promising approaches to detect their misuse. The global metabolomics workflow implemented for such studies is presented and illustrated through various examples of biological matrices profiling (tissue, blood, urine) and for different classes of anabolic compounds (steroids, β-agonists and somatotropin).

  8. 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.

  9. Mechanism of Xinfeng Capsule on Adjuvant-Induced Arthritis via Analysis of Urinary Metabolomic Profiles

    PubMed Central

    Jiang, Hui; Liu, Jian; Wang, Ting; Gao, Jia-rong; Sun, Yue; Huang, Chuan-bing; Meng, Mei; Qin, Xiu-juan

    2016-01-01

    We aimed to explore the potential effects of Xinfeng capsule (XFC) on urine metabolic profiling in adjuvant-induced arthritis (AA) rats by using gas chromatography time-of-flight mass spectrometry (GC-TOF/MS). GC-TOF/MS technology was combined with multivariate statistical approaches, such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). These methods were used to distinguish the healthy group, untreated group, and XFC treated group and elucidate potential biomarkers. Nine potential biomarkers such as hippuric acid, adenine, and L-dopa were identified as potential biomarkers, indicating that purine metabolism, fat metabolism, amino acid metabolism, and energy metabolism were disturbed in AA rats. This study demonstrated that XFC is efficacious for RA and explained its potential metabolomics mechanism. PMID:26989506

  10. (1)H nuclear magnetic resonance-based extracellular metabolomic analysis of multidrug resistant Tca8113 oral squamous carcinoma cells.

    PubMed

    Wang, Hui; Chen, Jiao; Feng, Yun; Zhou, Wenjie; Zhang, Jihua; Yu, Y U; Wang, Xiaoqian; Zhang, Ping

    2015-06-01

    A major obstacle of successful chemotherapy is the development of multidrug resistance (MDR) in the cancer cells, which is difficult to reverse. Metabolomic analysis, an emerging approach that has been increasingly applied in various fields, is able to reflect the unique chemical fingerprints of specific cellular processes in an organism. The assessment of such metabolite changes can be used to identify novel therapeutic biomarkers. In the present study, (1)H nuclear magnetic resonance (NMR) spectroscopy was used to analyze the extracellular metabolomic spectrum of the Tca8113 oral squamous carcinoma cell line, in which MDR was induced using the carboplatin (CBP) and pingyangmycin (PYM) chemotherapy drugs in vitro. The data were analyzed using the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods. The results demonstrated that the extracellular metabolomic spectrum of metabolites such as glutamate, glycerophosphoethanol amine, α-Glucose and β-Glucose for the drug-induced Tca8113 cells was significantly different from the parental Tca8113 cell line. A number of biochemicals were also significantly different between the groups based on their NMR spectra, with drug-resistant cells presenting relatively higher levels of acetate and lower levels of lactate. In addition, a significantly higher peak was observed at δ 3.35 ppm in the spectrum of the PYM-induced Tca8113 cells. Therefore, (1)H NMR-based metabolomic analysis has a high potential for monitoring the formation of MDR during clinical tumor chemotherapy in the future.

  11. Metabolomics in melon: A new opportunity for aroma analysis

    PubMed Central

    Allwood, J. William; Cheung, William; Xu, Yun; Mumm, Roland; De Vos, Ric C.H.; Deborde, Catherine; Biais, Benoit; Maucourt, Mickael; Berger, Yosef; Schaffer, Arthur A.; Rolin, Dominique; Moing, Annick; Hall, Robert D.; Goodacre, Royston

    2014-01-01

    Cucumis melo fruit is highly valued for its sweet and refreshing flesh, however the flavour and value are also highly influenced by aroma as dictated by volatile organic compounds (VOCs). A simple and robust method of sampling VOCs on polydimethylsiloxane (PDMS) has been developed. Contrasting cultivars of C. melo subspecies melo were investigated at commercial maturity: three cultivars of var. Cantalupensis group Charentais (cv. Cézanne, Escrito, and Dalton) known to exhibit differences in ripening behaviour and shelf-life, as well as one cultivar of var. Cantalupensis group Ha’Ogan (cv. Noy Yisre’el) and one non-climacteric cultivar of var. Inodorus (cv. Tam Dew). The melon cultivar selection was based upon fruits exhibiting clear differences (cv. Noy Yisre’el and Tam Dew) and similarities (cv. Cézanne, Escrito, and Dalton) in flavour. In total, 58 VOCs were detected by thermal desorption (TD)-GC–MS which permitted the discrimination of each cultivar via Principal component analysis (PCA). PCA indicated a reduction in VOCs in the non-climacteric cv. Tam Dew compared to the four Cantalupensis cultivars. Within the group Charentais melons, the differences between the short, mid and long shelf-life cultivars were considerable. 1H NMR analysis led to the quantification of 12 core amino acids, their levels were 3–10-fold greater in the Charentais melons, although they were reduced in the highly fragrant cv. Cézanne, indicating their role as VOC precursors. This study along with comparisons to more traditional labour intensive solid phase micro-extraction (SPME) GC–MS VOC profiling data has indicated that the high-throughput PDMS method is of great potential for the assessment of melon aroma and quality. PMID:24417788

  12. Metabolomics in melon: a new opportunity for aroma analysis.

    PubMed

    Allwood, J William; Cheung, William; Xu, Yun; Mumm, Roland; De Vos, Ric C H; Deborde, Catherine; Biais, Benoit; Maucourt, Mickael; Berger, Yosef; Schaffer, Arthur A; Rolin, Dominique; Moing, Annick; Hall, Robert D; Goodacre, Royston

    2014-03-01

    Cucumis melo fruit is highly valued for its sweet and refreshing flesh, however the flavour and value are also highly influenced by aroma as dictated by volatile organic compounds (VOCs). A simple and robust method of sampling VOCs on polydimethylsiloxane (PDMS) has been developed. Contrasting cultivars of C. melo subspecies melo were investigated at commercial maturity: three cultivars of var. Cantalupensis group Charentais (cv. Cézanne, Escrito, and Dalton) known to exhibit differences in ripening behaviour and shelf-life, as well as one cultivar of var. Cantalupensis group Ha'Ogan (cv. Noy Yisre'el) and one non-climacteric cultivar of var. Inodorus (cv. Tam Dew). The melon cultivar selection was based upon fruits exhibiting clear differences (cv. Noy Yisre'el and Tam Dew) and similarities (cv. Cézanne, Escrito, and Dalton) in flavour. In total, 58 VOCs were detected by thermal desorption (TD)-GC-MS which permitted the discrimination of each cultivar via Principal component analysis (PCA). PCA indicated a reduction in VOCs in the non-climacteric cv. Tam Dew compared to the four Cantalupensis cultivars. Within the group Charentais melons, the differences between the short, mid and long shelf-life cultivars were considerable. ¹H NMR analysis led to the quantification of 12 core amino acids, their levels were 3-10-fold greater in the Charentais melons, although they were reduced in the highly fragrant cv. Cézanne, indicating their role as VOC precursors. This study along with comparisons to more traditional labour intensive solid phase micro-extraction (SPME) GC-MS VOC profiling data has indicated that the high-throughput PDMS method is of great potential for the assessment of melon aroma and quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    PubMed

    Kotze, Helen L; Armitage, Emily G; Sharkey, Kieran J; Allwood, James W; Dunn, Warwick B; Williams, Kaye J; Goodacre, Royston

    2013-10-23

    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. 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 before. Lactate

  14. Metabolome analysis of effect of aspirin on Drosophila lifespan extension.

    PubMed

    Song, Chaochun; Zhu, Chenxing; Wu, Qi; Qi, Jiancheng; Gao, Yue; Zhang, Zhichao; Gaur, Uma; Yang, Deying; Fan, Xiaolan; Yang, Mingyao

    2017-09-01

    Effective approaches for drug development involve the repurposing of existing drugs which are already approved by the FDA. Aspirin has been shown to have many health benefits since its discovery as a nonsteroidal anti-inflammatory drug (NSAID) to treat pain and inflammation. Recent experiments demonstrated the longevity effects of aspirin in Drosophila, but its mechanism remains to be explored. In order to elucidate the effects of drug on metabolism, we carried out the metabolic analysis of aspirin-treated flies. The results identified 404 active metabolites in addition to the extended lifespan and improved healthspan in fly. There were 28 metabolites having significant changes between aspirin-treated group and the control group, out of which 22 compounds were found to have detailed information. These compounds are reported to have important functions in energy metabolism, amino sugar metabolism, and urea metabolism, indicating that aspirin might be playing positive roles in the fly's lifespan and healthspan improvement. Because of the conservation of major longevity pathways and mechanisms in different species, the health benefits of aspirin administration could be extended to other animals and humans as well. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Exercise-Induced Alterations in Skeletal Muscle, Heart, Liver, and Serum Metabolome Identified by Non-Targeted Metabolomics Analysis.

    PubMed

    Starnes, Joseph W; Parry, Traci L; O'Neal, Sara K; Bain, James R; Muehlbauer, Michael J; Honcoop, Aubree; Ilaiwy, Amro; Christopher, Peter M; Patterson, Cam; Willis, Monte S

    2017-08-08

    The metabolic and physiologic responses to exercise are increasingly interesting, given that regular physical activity enhances antioxidant capacity, improves cardiac function, and protects against type 2 diabetes. The metabolic interactions between tissues and the heart illustrate a critical cross-talk we know little about. To better understand the metabolic changes induced by exercise, we investigated skeletal muscle (plantaris, soleus), liver, serum, and heart from exercise trained (or sedentary control) animals in an established rat model of exercise-induced aerobic training via non-targeted GC-MS metabolomics. Exercise-induced alterations in metabolites varied across tissues, with the soleus and serum affected the least. The alterations in the plantaris muscle and liver were most alike, with two metabolites increased in each (citric acid/isocitric acid and linoleic acid). Exercise training additionally altered nine other metabolites in the plantaris (C13 hydrocarbon, inosine/adenosine, fructose-6-phosphate, glucose-6-phosphate, 2-aminoadipic acid, heptadecanoic acid, stearic acid, alpha-tocopherol, and oleic acid). In the serum, we identified significantly decreased alpha-tocopherol levels, paralleling the increases identified in plantaris muscle. Eleven unique metabolites were increased in the heart, which were not affected in the other compartments (malic acid, serine, aspartic acid, myoinositol, glutamine, gluconic acid-6-phosphate, glutamic acid, pyrophosphate, campesterol, phosphoric acid, creatinine). These findings complement prior studies using targeted metabolomics approaches to determine the metabolic changes in exercise-trained human skeletal muscle. Specifically, exercise trained vastus lateralus biopsies had significantly increased linoleic acid, oleic acid, and stearic acid compared to the inactive groups, which were significantly increased in plantaris muscle in the present study. While increases in alpha-tocopherol have not been identified in

  16. Global metabolomic and network analysis of Escherichia coli responses to exogenous biofuels.

    PubMed

    Wang, Jiangxin; Chen, Lei; Tian, Xiaoxu; Gao, Lianju; Niu, Xiangfeng; Shi, Mengliang; Zhang, Weiwen

    2013-11-01

    Although synthetic biology progress has made it possible to produce various biofuels in more user-friendly hosts, such as Escherichia coli, the large-scale biofuel production in these non-native systems is still challenging, mostly due to the very low tolerance of these non-native hosts to the biofuel toxicity. To address the issues, in this study we determined the metabolic responses of E. coli induced by three major biofuel products, ethanol, butanol, and isobutanol, using a gas chromatography-mass spectrometry (GC-MS) approach. A metabolomic data set of 65 metabolites identified in all samples was then subjected to principal component analysis (PCA) to compare their effects and a weighted correlation network analysis (WGCNA) to identify the metabolic modules specifically responsive to each of the biofuel stresses, respectively. The PCA analysis showed that cellular responses caused by the biofuel stress were in general similar to aging cells at stationary phase, inconsistent with early studies showing a high degree of dissimilarity between metabolite responses during growth cessation as induced through stationary phases or through various environmental stress applications. The WGCNA analysis allowed identification of 2, 4, and 2 metabolic modules specifically associated with ethanol, butanol, and isobutanol treatments, respectively. The biofuel-associated modules included amino acids and osmoprotectants, such as isoleucine, valine, glycine, glutamate, and trehalose, suggesting amino acid metabolism and osmoregulation are among the key protection mechanisms against biofuel stresses in E. coli. Interestingly, no module was found associated with all three biofuel products, suggesting differential effects of each biofuel on E. coli. The findings enhanced our understanding of E. coli responses to exogenous biofuels and also demonstrated the effectiveness of the metabolomic and network analysis in identifying key targets for biofuel tolerance.

  17. Metabolomic analysis of key regulatory metabolites in hepatitis C virus-infected tree shrews.

    PubMed

    Sun, Hui; Zhang, Aihua; Yan, Guangli; Piao, Chengyu; Li, Weiyun; Sun, Chang; Wu, Xiuhong; Li, Xinghua; Chen, Yun; Wang, Xijun

    2013-03-01

    Metabolomics is a powerful new technology that allows the assessment of global low-molecular-weight metabolites in a biological system and which shows great potential in biomarker discovery. Analysis of the key metabolites in body fluids has become an important part of improving the diagnosis, prognosis, and therapy of diseases. Hepatitis C virus (HCV) is a major leading cause of liver disease worldwide and a serious burden on public health. However, the lack of a small-animal model has hampered the analysis of HCV pathogenesis. We hypothesize that an animal model (Tupaia belangeri chinensis) of HCV would produce a unique characterization of metabolic phenotypes. Ultra-performance liquid-chromatography/electrospray ionization-SYNAPT-high-definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) coupled with pattern recognition methods and system analysis was carried out to obtain comprehensive metabolomics profiling and pathways of large biological data sets. Taurine, hypotaurine, ether lipid, glycerophospholipid, arachidonic acid, tryptophan, and primary bile acid metabolism pathways were acutely perturbed, and 38 differential metabolites were identified. More important, five metabolite markers were selected via the "significance analysis for microarrays" method as the most discriminant and interesting biomarkers that were effective for the diagnosis of HCV. Network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Integrated network analysis of the key metabolites yields highly related signaling pathways associated with the differentially expressed proteins, which suggests that the creation of new treatment paradigms targeting and activating these networks in their entirety, rather than single proteins, might be necessary for controlling and treating HCV efficiently.

  18. Metabolomic Analysis of Key Regulatory Metabolites in Hepatitis C Virus–infected Tree Shrews*

    PubMed Central

    Sun, Hui; Zhang, Aihua; Yan, Guangli; Piao, Chengyu; Li, Weiyun; Sun, Chang; Wu, Xiuhong; Li, Xinghua; Chen, Yun; Wang, Xijun

    2013-01-01

    Metabolomics is a powerful new technology that allows the assessment of global low-molecular-weight metabolites in a biological system and which shows great potential in biomarker discovery. Analysis of the key metabolites in body fluids has become an important part of improving the diagnosis, prognosis, and therapy of diseases. Hepatitis C virus (HCV) is a major leading cause of liver disease worldwide and a serious burden on public health. However, the lack of a small-animal model has hampered the analysis of HCV pathogenesis. We hypothesize that an animal model (Tupaia belangeri chinensis) of HCV would produce a unique characterization of metabolic phenotypes. Ultra-performance liquid-chromatography/electrospray ionization-SYNAPT-high-definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) coupled with pattern recognition methods and system analysis was carried out to obtain comprehensive metabolomics profiling and pathways of large biological data sets. Taurine, hypotaurine, ether lipid, glycerophospholipid, arachidonic acid, tryptophan, and primary bile acid metabolism pathways were acutely perturbed, and 38 differential metabolites were identified. More important, five metabolite markers were selected via the “significance analysis for microarrays” method as the most discriminant and interesting biomarkers that were effective for the diagnosis of HCV. Network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Integrated network analysis of the key metabolites yields highly related signaling pathways associated with the differentially expressed proteins, which suggests that the creation of new treatment paradigms targeting and activating these networks in their entirety, rather than single proteins, might be necessary for controlling and treating HCV efficiently. PMID:23264353

  19. Metabolomic analysis of Ranunculus spp. as potential agents involved in the etiology of equine grass sickness.

    PubMed

    Michl, Johanna; Modarai, Maryam; Edwards, Sarah; Heinrich, Michael

    2011-09-28

    Identification of toxic or harmful agents continues to be a key goal in agricultural chemistry. This paper reports a metabolomic analysis of Ranunculus repens and related species, which were recently postulated to be cocausative agents in the etiology of equine grass sickness (EGS). Specifically, samples collected at EGS sites were compared with those from non-EGS sites. Furthermore, interspecific and seasonal variations and the species' response to edaphic and climatic factors were investigated. (1)H NMR spectroscopy in combination with multivariate data analysis was applied to the crude methanol extracts of the Ranunculus samples, as well as their chloroform fractions. Samples from EGS sites were significantly different from control samples. The metabolite composition varied greatly between different Ranunculus species. No significant changes could be observed between samples collected in different seasons. This work provides strong evidence that Ranunculus is involved in the etiology of EGS and has implications for agricultural management of pastures.

  20. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data.

    PubMed

    Tsai, I-Lin; Kuo, Tien-Chueh; Ho, Tsung-Jung; Harn, Yeu-Chern; Wang, San-Yuan; Fu, Wen-Mei; Kuo, Ching-Hua; Tseng, Yufeng Jane

    2013-05-03

    Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  1. Potential Biomarkers of Fatigue Identified by Plasma Metabolome Analysis in Rats

    PubMed Central

    Kume, Satoshi; Yamato, Masanori; Tamura, Yasuhisa; Jin, Guanghua; Nakano, Masayuki; Miyashige, Yukiharu; Eguchi, Asami; Ogata, Yoshiyuki; Goda, Nobuhito; Iwai, Kazuhiro; Yamano, Emi; Watanabe, Yasuyoshi; Soga, Tomoyoshi; Kataoka, Yosky

    2015-01-01

    In the present study, prior to the establishment of a method for the clinical diagnosis of chronic fatigue in humans, we validated the utility of plasma metabolomic analysis in a rat model of fatigue using capillary electrophoresis-mass spectrometry (CE-MS). In order to obtain a fatigued animal group, rats were placed in a cage filled with water to a height of 2.2 cm for 5 days. A food-restricted group, in which rats were limited to 10 g/d of food (around 50% of the control group), was also assessed. The food-restricted group exhibited weight reduction similar to that of the fatigued group. CE-MS measurements were performed to evaluate the profile of food intake-dependent metabolic changes, as well as the profile in fatigue loading, resulting in the identification of 48 metabolites in plasma. Multivariate analyses using hierarchical clustering and principal component analysis revealed that the plasma metabolome in the fatigued group showed clear differences from those in the control and food-restricted groups. In the fatigued group, we found distinctive changes in metabolites related to branched-chain amino acid metabolism, urea cycle, and proline metabolism. Specifically, the fatigued group exhibited significant increases in valine, leucine, isoleucine, and 2-oxoisopentanoate, and significant decreases in citrulline and hydroxyproline compared with the control and food-restricted groups. Plasma levels of total nitric oxide were increased in the fatigued group, indicating systemic oxidative stress. Further, plasma metabolites involved in the citrate cycle, such as cis-aconitate and isocitrate, were reduced in the fatigued group. The levels of ATP were significantly decreased in the liver and skeletal muscle, indicative of a deterioration in energy metabolism in these organs. Thus, this comprehensive metabolic analysis furthered our understanding of the pathophysiology of fatigue, and identified potential diagnostic biomarkers based on fatigue pathophysiology. PMID

  2. 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

  3. 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.

  4. Metabolomic analysis of NAD kinase-deficient mutants of the cyanobacterium Synechocystis sp. PCC 6803.

    PubMed

    Ishikawa, Yuuma; Miyagi, Atsuko; Haishima, Yuto; Ishikawa, Toshiki; Nagano, Minoru; Yamaguchi, Masatoshi; Hihara, Yukako; Kawai-Yamada, Maki

    2016-10-20

    NAD kinase (NADK) phosphorylates NAD(H) to NADP(H). The enzyme has a crucial role in the regulation of the NADP(H)/NAD(H) ratio in various organisms. The unicellular cyanobacterium Synechocystis sp. PCC 6803 possesses two NADK-encoding genes, sll1415 and slr0400. To elucidate the metabolic change in NADK-deficient mutants growing under photoautotrophic conditions, we conducted metabolomic analysis using capillary electrophoresis mass spectrometry (CE-MS). The growth curves of the wild-type parent (WT) and NADK-deficient mutants (Δ1415 and Δ0400) did not show any differences under photoautotrophic conditions. The NAD(P)(H) balance showed abnormality in both mutants. However, only the metabolite pattern of Δ0400 showed differences compared to WT. These results indicated that the two NADK isoforms have distinct functions in cyanobacterial metabolism. Copyright © 2016 Elsevier GmbH. All rights reserved.

  5. 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

  6. 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

  7. 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.

  8. Urine metabolomic analysis to detect metabolites associated with the development of contrast induced nephropathy

    PubMed Central

    Diercks, Deborah B.; Owen, Kelly P.; Kline, Jeffrey A.; Sutter, Mark E.

    2016-01-01

    Objective Contrast induced nephropathy (CIN) is a result of injury to the proximal tubules. The incidence of CIN is around 11% for imaging done in the acute care setting. We aim to analyze the metabolic patterns in the urine, before and after dosing with intravenous contrast for computed tomography (CT) imaging of the chest, to determine if metabolomic changes exist in patients who develop CIN. Methods A convenience sample of high risk patients undergoing a chest CT with intravenous contrast were eligible for enrollment. Urine samples were collected prior to imaging and 4 to 6 hours post imaging. Samples underwent gas chromatography/mass spectrometry profiling. Peak metabolite values were measured and data was log transformed. Significance analysis of microarrays and partial least squares was used to determine the most significant metabolites prior to CT imaging and within subject. Analysis of variance was used to rank metabolites associated with temporal change and CIN. CIN was defined as an increase in serum creatinine level of ≥ 0.5 mg/dL or ≥ 25% above baseline within 48 hours after contrast administration. Results We sampled paired urine samples from 63 subjects. The incidence of CIN was 6/63 (9.5%). Patients without CIN had elevated urinary citric acid and taurine concentrations in the pre-CT urine. Xylulose increased in the post CT sample in patients who developed CIN. Conclusion Differences in metabolomics patterns in patients who do and do not develop CIN exist. Metabolites may be potential early identifiers of CIN and identify patients at high-risk for developing this condition prior to imaging. PMID:28168227

  9. Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples.

    PubMed

    Beckmann, Manfred; Lloyd, Amanda J; Haldar, Sumanto; Favé, Gaëlle; Seal, Chris J; Brandt, Kirsten; Mathers, John C; Draper, John

    2013-08-01

    Although robust associations between dietary intake and population health are evident from conventional observational epidemiology, the outcomes of large-scale intervention studies testing the causality of those links have often proved inconclusive or have failed to demonstrate causality. This apparent conflict may be due to the well-recognised difficulty in measuring habitual food intake which may lead to confounding in observational epidemiology. Urine biomarkers indicative of exposure to specific foods offer information supplementary to the reliance on dietary intake self-assessment tools, such as FFQ, which are subject to individual bias. Biomarker discovery strategies using non-targeted metabolomics have been used recently to analyse urine from either short-term food intervention studies or from cohort studies in which participants consumed a freely-chosen diet. In the latter, the analysis of diet diary or FFQ information allowed classification of individuals in terms of the frequency of consumption of specific diet constituents. We review these approaches for biomarker discovery and illustrate both with particular reference to two studies carried out by the authors using approaches combining metabolite fingerprinting by MS with supervised multivariate data analysis. In both approaches, urine signals responsible for distinguishing between specific foods were identified and could be related to the chemical composition of the original foods. When using dietary data, both food distinctiveness and consumption frequency influenced whether differential dietary exposure could be discriminated adequately. We conclude that metabolomics methods for fingerprinting or profiling of overnight void urine, in particular, provide a robust strategy for dietary exposure biomarker-lead discovery.

  10. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    PubMed

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Physiological and Metabolomic Analysis of Issatchenkia orientalis MTY1 With Multiple Tolerance for Cellulosic Bioethanol Production.

    PubMed

    Seong, Yeong-Je; Lee, Hye-Jin; Lee, Jung-Eun; Kim, Sooah; Lee, Do Yup; Kim, Kyoung Heon; Park, Yong-Cheol

    2017-08-26

    Yeast with multiple tolerance onto harsh conditions has a number of advantages for bioethanol production. In this study, an alcohol yeast of Issatchenkia orientalis MTY1 is isolated in a Korean winery and its multiple tolerance against high temperature and acidic conditions is characterized in microaerobic batch cultures and by metabolomic analysis. In a series of batch cultures using 100 g L(-1) glucose, I. orientalis MTY1 possesses wider growth ranges at pH 2-8 and 30-45 °C than a conventional yeast of Saccharomyces cerevisiae D452-2. Moreover, I. orientalis MTY1 showes higher cell growth and ethanol productivity in the presence of acetic acid or furfural than S. cerevisiae D452-2. I. orientalis MTY1 produces 41.4 g L(-1) ethanol with 1.5 g L(-1)  h(-1) productivity at 42 °C and pH 4.2 in the presence of 4 g L(-1) acetic acid, whereas a thermo-tolerant yeast of Kluyvermyces marxianus ATCC36907 does not grow. By metabolomics by GC-TOF MS and statistical analysis of 125 metabolite peaks, it is revealed that the thermo-tolerance of I. orientalis MTY1 might be ascribed to higher contents of unsaturated fatty acids, purines and pyrimidines than S. cerevisiae D452-2. Conclusively, I. orientalis MTY1 could be a potent workhorse with multiple tolerance against harsh conditions considered in cellulosic bioethanol production. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Primary HCMV infection in pregnancy from classic data towards metabolomics: An exploratory analysis.

    PubMed

    Fattuoni, Claudia; Palmas, Francesco; Noto, Antonio; Barberini, Luigi; Mussap, Michele; Grapov, Dmitry; Dessì, Angelica; Casu, Mariano; Casanova, Andrea; Furione, Milena; Arossa, Alessia; Spinillo, Arsenio; Baldanti, Fausto; Fanos, Vassilios; Zavattoni, Maurizio

    2016-09-01

    Human cytomegalovirus (HCMV) is one of the most frequent risk of viral infections during pregnancy. The aim of this study was to evaluate the metabolic profile in amniotic fluid (AF) samples obtained from HCMV-infected, and uninfected fetuses in order to elucidate changes in metabolic pathways during congenital HCMV infection and to recognize new potential diagnostic and/or prognostic biomarkers. A retrospective cohort study was conducted on 63 pregnant women: 20 contracted primary HCMV infection during pregnancy and, subsequently, transmitted the virus to the fetus (transmitters); 20 contracted the infection without transmitting the virus to the fetus (non-transmitters); 23 who underwent amniocentesis for cytogenetic-based diagnosis were considered controls. Metabolomics analysis was performed by using the hyphenated technique Gas chromatography-mass spectrometry (GC-MS) followed by a multivariate statistical approach. Four PLS-DA models were generated: controls vs. transmitters; controls vs. non-transmitters; transmitters vs. non-transmitters; and asymptomatic infected vs. symptomatic infected newborns. Subsequently, these models were exploited for network mapping. Compared with controls, HCMV transmitters showed significantly increased levels in glutamine, glycine, serine, pyruvic acid, threonine, threonic acid, and cystine; conversely, unknown U1715 and U1804, glutamic acid, U1437, fructose, sugar-like A203003 and A203005, and tyrosine levels were found decreased. In non-transmitters, glutamine, serine, glycine, threonic acid, threonine, 1-monostearin, urea, and cystine were found increased, while sorbitol, unknown U1804, sugar-like A203003, U1751, xylitol, leucine and fructose were decreased. The comparison between transmitters and non-transmitters did not produce a statistically significant model. Unlike controls' profile, a common feature of HCMV infected subjects (transmitters and non-transmitters) was the activation of glutamine-glutamate and pyrimidine

  13. 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

  14. 3-hydroxykynurenine and other Parkinson's disease biomarkers discovered by metabolomic analysis.

    PubMed

    Lewitt, Peter A; Li, Jia; Lu, Mei; Beach, Thomas G; Adler, Charles H; Guo, Lining

    2013-10-01

    Parkinson's disease (PD) biomarkers are needed to enhance therapeutics research and to understand PD pathogenesis. Methods that simultaneously measure hundreds of small molecular-weight compounds-metabolomic analysis-"fingerprint" disease-specific alterations in individual compounds or metabolic pathways. Beyond a nontargeted search for PD biomarkers, we hypothesized that PD cerebrospinal fluid would show increased formation of the excitotoxin 3-hydroxykynurenine and diminished concentration of the antioxidant glutathione. Cerebrospinal fluid was collected at <4 hours postmortem from 48 pathologically-verified PD subjects and 57 comparably-aged controls. Assays involved ultra-high-performance liquid and gas chromatography linked to mass spectrometry. We used univariate techniques to determine fold-changes in concentrations of biochemicals; false-discovery rates were calculated to exclude spurious findings. Data was modeled using a Support Vector Machine for analyzing compounds selected by Welch's t test. Classification accuracy was determined by cross-validation. Of 243 structurally-identified biochemicals,19 compounds differentiated PD from controls at a 20% false-discovery level. In PD, mean 3-hydroxykynurenine concentration was increased by one-third, and mean oxidized glutathione was decreased by 40% (for each, P < .01). Four of the 19 compounds differentiating PD from controls were N-acetylated amino acids, suggesting a generalized alteration in N-acetylation activity. The Support Vector Machine classification model distinguished between groups at 83% sensitivity and 91% specificity for the learning data, and at 65% and 79% from cross-validation. In this study, the first for metabolomic profiling of PD cerebrospinal fluid, we found several novel biomarkers and offer new directions for recognizing disease-specific biochemical indicators. The findings support involvement of excitotoxicity and oxidative stress in the pathogenesis of PD.

  15. A Metabolomic Analysis of Two Intravenous Lipid Emulsions in a Murine Model

    PubMed Central

    Kalish, Brian T.; Le, Hau D.; Gura, Kathleen M.; Bistrian, Bruce R.; Puder, Mark

    2013-01-01

    Background Parenteral nutrition (PN), including intravenous lipid administration, is a life-saving therapy but can be complicated by cholestasis and liver disease. The administration of intravenous soy bean oil (SO) has been associated with the development of liver disease, while the administration of intravenous fish oil (FO) has been associated with the resolution of liver disease. The biochemical mechanism of this differential effect is unclear. This study compares SO and FO lipid emulsions in a murine model of hepatic steatosis, one of the first hits in PN-associated liver disease. Methods We established a murine model of hepatic steatosis in which liver injury is induced by orally feeding mice a PN solution. C57BL/6J mice were randomized to receive PN alone (a high carbohydrate diet (HCD)), PN plus intravenous FO (Omegaven®; Fresenius Kabi AG, Bad Homburg VDH, Germany), PN plus intravenous SO (Intralipid®; Fresenius Kabi AG, Bad Homburg v.d.H., Germany, for Baxter Healthcare, Deerfield, IL), or a chow diet. After 19 days, liver tissue was harvested from all animals and subjected to metabolomic profiling. Results The administration of an oral HCD without lipid induced profound hepatic steatosis. SO was associated with macro- and microvesicular hepatic steatosis, while FO largely prevented the development of steatosis. 321 detectable compounds were identified in the metabolomic analysis. HCD induced de novo fatty acid synthesis and oxidative stress. Both FO and SO relieved some of the metabolic shift towards de novo lipogenesis, but FO offered additional advantages in terms of lipid peroxidation and the generation of inflammatory precursors. Conclusions Improved lipid metabolism combined with reduced oxidative stress may explain the protective effect offered by intravenous FO in vivo. PMID:23565157

  16. Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses.

    PubMed

    Thévenot, Etienne A; Roux, Aurélie; Xu, Ying; Ezan, Eric; Junot, Christophe

    2015-08-07

    Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.

  17. Metabolomics in childhood diabetes

    PubMed Central

    Frohnert, Brigitte I; Rewers, Marian J

    2015-01-01

    Recent increases in the incidence of both type 1 (T1D) and type 2 diabetes (T2D) in children and adolescents point to the importance of environmental factors in the development of these diseases. Metabolomic analysis explores the integrated response of the organism to environmental changes. Metabolic profiling can identify biomarkers that are predictive of disease incidence and development, potentially providing insight into disease pathogenesis. This review provides an overview of the role of metabolomic analysis in diabetes research and summarizes recent research relating to the development of T1D and T2D in children. PMID:26420304

  18. 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.

  19. A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles1[w

    PubMed Central

    Tikunov, Yury; Lommen, Arjen; de Vos, C.H. Ric; Verhoeven, Harrie A.; Bino, Raoul J.; Hall, Robert D.; Bovy, Arnaud G.

    2005-01-01

    To take full advantage of the power of functional genomics technologies and in particular those for metabolomics, both the analytical approach and the strategy chosen for data analysis need to be as unbiased and comprehensive as possible. Existing approaches to analyze metabolomic data still do not allow a fast and unbiased comparative analysis of the metabolic composition of the hundreds of genotypes that are often the target of modern investigations. We have now developed a novel strategy to analyze such metabolomic data. This approach consists of (1) full mass spectral alignment of gas chromatography (GC)-mass spectrometry (MS) metabolic profiles using the MetAlign software package, (2) followed by multivariate comparative analysis of metabolic phenotypes at the level of individual molecular fragments, and (3) multivariate mass spectral reconstruction, a method allowing metabolite discrimination, recognition, and identification. This approach has allowed a fast and unbiased comparative multivariate analysis of the volatile metabolite composition of ripe fruits of 94 tomato (Lycopersicon esculentum Mill.) genotypes, based on intensity patterns of >20,000 individual molecular fragments throughout 198 GC-MS datasets. Variation in metabolite composition, both between- and within-fruit types, was found and the discriminative metabolites were revealed. In the entire genotype set, a total of 322 different compounds could be distinguished using multivariate mass spectral reconstruction. A hierarchical cluster analysis of these metabolites resulted in clustering of structurally related metabolites derived from the same biochemical precursors. The approach chosen will further enhance the comprehensiveness of GC-MS-based metabolomics approaches and will therefore prove a useful addition to nontargeted functional genomics research. PMID:16286451

  20. Metabolomic Analysis of the Effect of Postnatal Hypoxia on the Retina in a Newly Born Piglet Model

    PubMed Central

    Solberg, Rønnaug; Escobar, Javier; Arduini, Alessandro; Torres-Cuevas, Isabel; Lahoz, Agustín; Sastre, Juan; Saugstad, Ola Didrik; Vento, Máximo; Kuligowski, Julia; Quintás, Guillermo

    2013-01-01

    The availability of reliable biomarkers of brain injury secondary to birth asphyxia could substantially improve clinical grading, therapeutic intervention strategies, and prognosis. In this study, changes in the metabolome of retinal tissue caused by profound hypoxia in an established neonatal piglet model were investigated using an ultra performance liquid chromatography – quadrupole time of flight mass spectrometry (UPLC-QTOFMS) untargeted metabolomic approach, which included Partial Least Squares – Discriminant Analysis (PLSDA) multivariate data analysis. The initial identification of a set of discriminant metabolites from UPLC-QTOFMS data was confirmed by target UPLC-MS/MS and allowed the selection of endogenous CDP-choline as a promising candidate biomarker for hypoxia-derived brain damage assessing intensity of retinal hypoxia. Results from this study will foster further research on CDP-choline changes occurring during resuscitation. PMID:23823578

  1. Metabolomic analysis of human oral cancer cells with adenylate kinase 2 or phosphorylate glycerol kinase 1 inhibition

    PubMed Central

    Ji, Eoon Hye; Cui, Li; Yuan, Xiaoqing; Cheng, Siliangyu; Messadi, Diana; Yan, Xinmin; Hu, Shen

    2017-01-01

    The purpose of this study was to use liquid chromatography-mass spectrometry (LC-MS) with XCMS for a quantitative metabolomic analysis of UM1 and UM2 oral cancer cells after knockdown of metabolic enzyme adenylate kinase 2 (AK2) or phosphorylate glycerol kinase 1 (PGK1). UM1 and UM2 cells were initially transfected with AK2 siRNA, PGK1 siRNA or scrambled control siRNA, and then analyzed with LC-MS for metabolic profiles. XCMS analysis of the untargeted metabolomics data revealed a total of 3200-4700 metabolite features from the transfected UM1 or UM2 cancer cells and 369-585 significantly changed metabolites due to AK2 or PGK1 suppression. In addition, cluster analysis showed that a common group of metabolites were altered by AK2 knockdown or by PGK1 knockdown between the UM1 and UM2 cells. However, the set of significantly changed metabolites due to AK2 knockdown was found to be distinct from those significantly changed by PGK1 knockdown. Our study has demonstrated that LC-MS with XCMS is an efficient tool for metabolomic analysis of oral cancer cells, and knockdown of different genes results in distinct changes in metabolic phenotypes in oral cancer cells. PMID:28243334

  2. NextGen Brain Microdialysis: Applying Modern Metabolomics Technology to the Analysis of Extracellular Fluid in the Central Nervous System

    PubMed Central

    Kao, Chi-Ya; Anderzhanova, Elmira; Asara, John M.; Wotjak, Carsten T.; Turck, Christoph W.

    2015-01-01

    Microdialysis is a powerful method for in vivo neurochemical analyses. It allows fluid sampling in a dynamic manner in specific brain regions over an extended period of time. A particular focus has been the neurochemical analysis of extracellular fluids to explore central nervous system functions. Brain microdialysis recovers neurotransmitters, low-molecular-weight neuromodulators and neuropeptides of special interest when studying behavior and drug effects. Other small molecules, such as central metabolites, are typically not assessed despite their potential to yield important information related to brain metabolism and activity in selected brain regions. We have implemented a liquid chromatography online mass spectrometry metabolomics platform for an expanded analysis of mouse brain microdialysates. The method is sensitive and delivers information for a far greater number of analytes than commonly used electrochemical and fluorescent detection or biochemical assays. The metabolomics platform was applied to the analysis of microdialysates in a foot shock-induced mouse model of posttraumatic stress disorder (PTSD). The rich metabolite data information was then used to delineate affected prefrontal molecular pathways that reflect individual susceptibility for developing PTSD-like symptoms. We demonstrate that hypothesis-free metabolomics can be adapted to the analysis of microdialysates for the discovery of small molecules with functional significance. PMID:27602357

  3. Assessment of (1)H NMR-based metabolomics analysis for normalization of urinary metals against creatinine.

    PubMed

    Cassiède, Marc; Nair, Sindhu; Dueck, Meghan; Mino, James; McKay, Ryan; Mercier, Pascal; Quémerais, Bernadette; Lacy, Paige

    2017-01-01

    Proton nuclear magnetic resonance ((1)H NMR, or NMR) spectroscopy and inductively coupled plasma-mass spectrometry (ICP-MS) are commonly used for metabolomics and metal analysis in urine samples. However, creatinine quantification by NMR for the purpose of normalization of urinary metals has not been validated. We assessed the validity of using NMR analysis for creatinine quantification in human urine samples in order to allow normalization of urinary metal concentrations. NMR and ICP-MS techniques were used to measure metabolite and metal concentrations in urine samples from 10 healthy subjects. For metabolite analysis, two magnetic field strengths (600 and 700MHz) were utilized. In addition, creatinine concentrations were determined by using the Jaffe method. Creatinine levels were strongly correlated (R(2)=0.99) between NMR and Jaffe methods. The NMR spectra were deconvoluted with a target database containing 151 metabolites that are present in urine. A total of 50 metabolites showed good correlation (R(2)=0.7-1.0) at 600 and 700MHz. Metal concentrations determined after NMR-measured creatinine normalization were comparable to previous reports. NMR analysis provided robust urinary creatinine quantification, and was sufficient for normalization of urinary metal concentrations. We found that NMR-measured creatinine-normalized urinary metal concentrations in our control subjects were similar to general population levels in Canada and the United Kingdom. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes.

    PubMed

    Montenegro-Burke, J Rafael; Aisporna, Aries E; Benton, H Paul; Rinehart, Duane; Fang, Mingliang; Huan, Tao; Warth, Benedikt; Forsberg, Erica; Abe, Brian T; Ivanisevic, Julijana; Wolan, Dennis W; Teyton, Luc; Lairson, Luke; Siuzdak, Gary

    2017-01-17

    The speed and throughput of analytical platforms has been a driving force in recent years in the "omics" technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition.

  5. (1)H NMR metabolomics analysis of renal cell carcinoma cells: Effect of VHL inactivation on metabolism.

    PubMed

    Cuperlovic-Culf, Miroslava; Cormier, Kevin; Touaibia, Mohamed; Reyjal, Julie; Robichaud, Sarah; Belbraouet, Mehdi; Turcotte, Sandra

    2016-05-15

    Von Hippel-Lindau (VHL) is an onco-suppressor involved in oxygen and energy-dependent promotion of protein ubiquitination and proteosomal degradation. Loss of function mutations of VHL (VHL-cells) result in organ specific cancers with the best studied example in renal cell carcinomas. VHL has a well-established role in deactivation of hypoxia-inducible factor (HIF-1) and in regulation of PI3K/AKT/mTOR activity. Cell culture metabolomics analysis was utilized to determined effect of VHL and HIF-1α or HIF-2α on metabolism of renal cell carcinomas (RCC). RCC cells were stably transfected with VHL or shRNA designed to silence HIF-1α or HIF-2α genes. Obtained metabolic data was analysed qualitatively, searching for overall effects on metabolism as well as quantitatively, using methods developed in our group in order to determine specific metabolic changes. Analysis of the effect of VHL and HIF silencing on cellular metabolic footprints and fingerprints provided information about the metabolic pathways affected by VHL through HIF function as well as independently of HIF. Through correlation network analysis as well as statistical analysis of significant metabolic changes we have determined effects of VHL and HIF on energy production, amino acid metabolism, choline metabolism as well as cell regulation and signaling. VHL was shown to influence cellular metabolism through its effect on HIF proteins as well as by affecting activity of other factors. © 2015 UICC.

  6. Metabolomic analysis reveals the composition differences in 13 Chinese tea cultivars of different manufacturing suitabilities.

    PubMed

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

    2017-07-22

    Green tea and black tea are manufactured using appropriate tea cultivars in China. However, the metabolite differences relating to the manufacturing suitability of tea cultivars are unclear. In the present study, we performed a non-targeted metabolomic analysis on 13 Chinese tea cultivars using ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry to investigate comprehensively the metabolite differences between cultivars suitable for manufacturing green tea (GT cultivars) and cultivars suitable for manufacturing both green tea and black tea (G&BT cultivars). Multivariate statistical analysis and cluster analysis divided the 13 cultivars into two groups, namely GT cultivars and G&BT cultivars, which correlated with their manufacturing suitability. The GT cultivars contained higher levels of flavonoid glycosides, whereas the G&BT cultivars contained higher levels of catechins, dimeric catechins, phenolic acids and alkaloids. Metabolic pathway analysis revealed that the flavonoid pathway inclined toward the synthesis of flavonoid glycosides in GT cultivars, whereas it inclined toward the synthesis of catechins and phenolic acids in G&BT cultivars. The results of the present study will be helpful for discriminating the manufacturing suitability of tea cultivars and investigating their breeding. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  7. Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes

    PubMed Central

    2016-01-01

    The speed and throughput of analytical platforms has been a driving force in recent years in the “omics” technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition. PMID:27983788

  8. Data streaming for metabolomics: Accelerating data processing and analysis from days to minutes

    DOE PAGES

    Montenegro-Burke, J. Rafael; Aisporna, Aries E.; Benton, H. Paul; ...

    2016-12-16

    The speed and throughput of analytical platforms has been a driving force in recent years in the “omics” technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, whichmore » capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Here, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition.« less

  9. Genome-enabled plant metabolomics.

    PubMed

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

    2014-09-01

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

  10. Identification of N-acetyltaurine as a novel metabolite of ethanol through metabolomics-guided biochemical analysis.

    PubMed

    Shi, Xiaolei; Yao, Dan; Chen, Chi

    2012-02-24

    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.

  11. 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

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

    PubMed

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

    2014-01-01

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

  13. 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.

  14. Metabolomic analysis of soil communities can be used for pollution assessment.

    PubMed

    Jones, Oliver A H; Sdepanian, Stephanie; Lofts, Steven; Svendsen, Claus; Spurgeon, David J; Maguire, Mahon L; Griffin, Julian L

    2014-01-01

    Metabolic profiling can be used to assess the changes in biochemical profiles of soil communities living in contaminated sites. The term "community metabolomics" is proposed for the application of metabolomics techniques to the study of the entire community of a soil sample. The authors anticipate the present study to be a starting point for the use of this technique to assess how communities respond to factors such as pollution and climate change.

  15. Metabolomic Analysis of the Skeletal Muscle of Mice Overexpressing PGC-1α

    PubMed Central

    Tadaishi, Miki; Ogawa, Yoshihiro; Ezaki, Osamu; Kamei, Yasutomi; Miura, Shinji

    2015-01-01

    Peroxisome proliferator-activated receptor (PPAR) γ coactivator 1α (PGC-1α) is a coactivator of various nuclear receptors and other transcription factors whose expression increases in the skeletal muscle during exercise. We have previously made transgenic mice overexpressing PGC-1α in the skeletal muscle (PGC-1α-Tg mice). PGC-1α upregulates the expression of genes associated with red fibers, mitochondrial function, fatty acid oxidation, and branched chain amino acid (BCAA) degradation. However, global analyses of the actual metabolic products have not been investigated. In this study, we conducted metabolomic analysis of the skeletal muscle in PGC-1α-Tg mice by capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry. Principal component analysis and hierarchical cluster analysis showed clearly distinguishable changes in the metabolites between PGC-1α-Tg and wild-type control mice. Changes were observed in metabolite levels of various metabolic pathways such as the TCA cycle, pentose phosphate pathway, nucleotide synthesis, purine nucleotide cycle, and amino acid metabolism, including BCAA and β-alanine. Namely, metabolic products of the TCA cycle increased in PGC-1α-Tg mice, with increased levels of citrate (2.3-fold), succinate (2.2-fold), fumarate (2.8-fold), and malate (2.3-fold) observed. Metabolic products associated with the pentose phosphate pathway and nucleotide biosynthesis also increased in PGC-1α-Tg mice. Meanwhile, BCAA levels decreased (Val, 0.7-fold; Leu, 0.8-fold; and Ile, 0.7-fold), and Glu (3.1-fold) and Asp (2.2-fold) levels increased. Levels of β-alanine and related metabolites were markedly decreased in PGC-1α-Tg mice. Coordinated regulation of the TCA cycle and amino acid metabolism, including BCAA, suggests that PGC-1α plays important roles in energy metabolism. Moreover, our metabolomics data showing the activation of the purine nucleotide pathway, malate–aspartate shuttle, as well as creatine

  16. NMR metabolomic analysis of fecal water from subjects on a vegetarian diet.

    PubMed

    Pettersson, Jenny; Karlsson, Pernilla Christina; Choi, Young Hae; Verpoorte, Robert; Rafter, Joseph James; Bohlin, Lars

    2008-06-01

    A vegetarian diet rich in phytochemicals may prevent colon carcinogenesis by affecting biochemical processes in the colonic mucosa. Compounds passing the digestive system reaching the colon could potentially be detected in fecal water. We previously reported that intact fecal water samples from human volunteers significantly decreased prostaglandin production and COX-2 protein expression in colonic cells. The aim with the present study was to further study the composition of the fecal waters, using NMR spectroscopy and multivariate data analysis, and to trace the COX-2 inhibiting activity. Intact fecal water samples and fractions thereof were analyzed for their ability to inhibit prostaglandin E2 production in the human colon cell line HT-29. The majority of the tested aqueous phases derived from intact fecal water showed ability to inhibit prostaglandin production in cells (13.8+/-1.34% inhibition, p=0.01). NMR analysis indicated the presence of significant quantities of amino acids and fatty acids. Major metabolites included; acetic acid, butanoic acid, propanoic acid, glutamic acid and alanine. Smaller amounts of glycine and fumaric acid, which are known to have anti-inflammatory and anti-tumorigenic properties, were also detected. This study describes for the first time NMR metabolomic analysis of fecal water from subjects on a vegetarian diet.

  17. Analysis of stable isotope assisted metabolomics data acquired by GC-MS.

    PubMed

    Wei, Xiaoli; Shi, Biyun; Koo, Imhoi; Yin, Xinmin; Lorkiewicz, Pawel; Suhail, Hamid; Rattan, Ramandeep; Giri, Shailendra; McClain, Craig J; Zhang, Xiang

    2017-08-08

    Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., (13)C, (18)O and/or (15)N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 (13)C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform (13)C-glucose and (13)C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Metabolome analysis via comprehensive two-dimensional liquid chromatography: identification of modified nucleosides from RNA metabolism.

    PubMed

    Willmann, Lucas; Erbes, Thalia; Krieger, Sonja; Trafkowski, Jens; Rodamer, Michael; Kammerer, Bernd

    2015-05-01

    Modified nucleosides derived from the RNA metabolism constitute an important chemical class, which are discussed as potential biomarkers in the detection of mammalian breast cancer. Not only the variability of modifications, but also the complexity of biological matrices such as urinary samples poses challenges in the analysis of modified nucleosides. In the present work, a comprehensive two-dimensional liquid chromatography mass spectrometry (2D-LC-MS) approach for the analysis of modified nucleosides in biological samples was established. For prepurification of urinary samples and cell culture supernatants, we performed a cis-diol specific affinity chromatography using boronate-derivatized polyacrylamide gel. In order to establish a 2D-LC method, we tested numerous column combinations and chromatographic conditions. In order to determine the target compounds, we coupled the 2D-LC setup to a triple quadrupole mass spectrometer performing full scans, neutral loss scans, and multiple reaction monitoring (MRM). The combination of a Zorbax Eclipse Plus C18 column with a Zorbax Bonus-RP column was found to deliver a high degree of orthogonality and adequate separation. By application of 2D-LC-MS approaches, we were able to detect 28 target compounds from RNA metabolism and crosslinked pathways in urinary samples and 26 target compounds in cell culture supernatants, respectively. This is the first demonstration of the applicability and benefit of 2D-LC-MS for the targeted metabolome analysis of modified nucleosides and compounds from crosslinked pathways in different biological matrices.

  19. A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding.

    PubMed

    Gromski, Piotr S; Muhamadali, Howbeer; Ellis, David I; Xu, Yun; Correa, Elon; Turner, Michael L; Goodacre, Royston

    2015-06-16

    The predominance of partial least squares-discriminant analysis (PLS-DA) used to analyze metabolomics datasets (indeed, it is the most well-known tool to perform classification and regression in metabolomics), can be said to have led to the point that not all researchers are fully aware of alternative multivariate classification algorithms. This may in part be due to the widespread availability of PLS-DA in most of the well-known statistical software packages, where its implementation is very easy if the default settings are used. In addition, one of the perceived advantages of PLS-DA is that it has the ability to analyze highly collinear and noisy data. Furthermore, the calibration model is known to provide a variety of useful statistics, such as prediction accuracy as well as scores and loadings plots. However, this method may provide misleading results, largely due to a lack of suitable statistical validation, when used by non-experts who are not aware of its potential limitations when used in conjunction with metabolomics. This tutorial review aims to provide an introductory overview to several straightforward statistical methods such as principal component-discriminant function analysis (PC-DFA), support vector machines (SVM) and random forests (RF), which could very easily be used either to augment PLS or as alternative supervised learning methods to PLS-DA. These methods can be said to be particularly appropriate for the analysis of large, highly-complex data sets which are common output(s) in metabolomics studies where the numbers of variables often far exceed the number of samples. In addition, these alternative techniques may be useful tools for generating parsimonious models through feature selection and data reduction, as well as providing more propitious results. We sincerely hope that the general reader is left with little doubt that there are several promising and readily available alternatives to PLS-DA, to analyze large and highly complex data sets.

  20. Single-Cell Metabolomics.

    PubMed

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

    2017-01-01

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

  1. Microbial metabolomics: toward a platform with full metabolome coverage.

    PubMed

    van der Werf, Mariët J; Overkamp, Karin M; Muilwijk, Bas; Coulier, Leon; Hankemeier, Thomas

    2007-11-01

    Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three microorganisms-Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae-and resulted in a list of 905 different metabolites. Subsequently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metabolites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or annotated in existing E. coli databases.

  2. 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.

  3. Metabolomic analysis of phenolic compounds in buckwheat (Fagopyrum esculentum M.) sprouts treated with methyl jasmonate.

    PubMed

    Kim, Hyun-Jin; Park, Kee-Jai; Lim, Jeong-Ho

    2011-05-25

    The effects of exogenous methyl jasmonate (MeJA) on phytochemical production in buckwheat sprouts cultivated under dark conditions (0, 1, 3, 5, and 7 d) were investigated by metabolomic analysis, using ultra performance liquid chromatography-quadrupole-time-of-flight (UPLC-Q-TOF) mass spectroscopy (MS) and partial least-squares-discriminant analysis (PLS-DA). MeJA-treated and control groups showed no differences in growth but were clearly discriminated from each other on PLS-DA score plots. The metabolites contributing to the discrimination were assigned as chlorogenic acid, catechin, isoorientin, orientin, rutin, vitexin, and quercitrin, which have various health effects. Moreover, isoorientin, orientin, rutin, and vitexin were assigned as the main phytochemicals of sprouts cultivated under dark conditions. The accumulation of these metabolites caused the phenolic compound content and antioxidant activity of the sprouts to increase. Further, this study revealed that their accumulation resulted from the stimulation of the phenylpropanoid pathway by MeJA treatment. Therefore, these metabolites may be useful for better understanding the effects of MeJA on buckwheat sprout phytochemicals and contribute to improving the functional quality of the sprouts.

  4. Network analysis of the metabolome and transcriptome reveals novel regulation of potato pigmentation.

    PubMed

    Cho, Kyoungwon; Cho, Kwang-Soo; Sohn, Hwang-Bae; Ha, In Jin; Hong, Su-Young; Lee, Hyerim; Kim, Young-Mi; Nam, Myung Hee

    2016-03-01

    To gain insights into the regulatory networks related to anthocyanin biosynthesis and identify key regulatory genes, we performed an integrated analysis of the transcriptome and metabolome in sprouts germinated from three colored potato cultivars: light-red Hongyoung, dark-purple Jayoung, and white Atlantic. We investigated transcriptional and metabolic changes using statistical analyses and gene-metabolite correlation networks. Transcript and metabolite profiles were generated through high-throughput RNA-sequencing data analysis and ultraperformance liquid chromatography quadrupole time-of-flight tandem mass spectrometry, respectively. The identification and quantification of changes in anthocyanin were performed using molecular formula-based mass accuracy and specific features of their MS(2) spectra. Correlation tests of anthocyanin contents and transcriptional changes showed 823 strong correlations (correlation coefficient, R (2)>0.9) between 22 compounds and 119 transcripts categorized into flavonoid metabolism, hormones, transcriptional regulation, and signaling. The connection network of anthocyanins and genes showed a regulatory system involved in the pigmentation of light-red Hongyoung and dark-purple Jayoung potatoes, suggesting that this systemic approach is powerful for investigations into novel genes that are potential targets for the breeding of new valuable potato cultivars. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  5. Analysis of urinary metabolomic profiling for unstable angina pectoris disease based on nuclear magnetic resonance spectroscopy.

    PubMed

    Li, Zhongfeng; Liu, Xinfeng; Wang, Juan; Gao, Jian; Guo, Shuzhen; Gao, Kuo; Man, Hongxue; Wang, Yingfeng; Chen, Jianxin; Wang, Wei

    2015-12-01

    (1)H NMR-based urinary metabolic profiling is used for investigating the unstable angina pectoris (UAP) metabolic signatures, in order to find out candidate biomarkers to facilitate medical diagnosis. In this work, 27 urine samples from UAP patients and 20 healthy controls were used. The metabolic profiles of the samples were analyzed by multivariate statistics analysis, including PCA, PLS-DA and OPLS-DA. The PCA analysis exhibited slight separation with R(2)X of 0.681 and Q2 of 0.251, while the PLS-DA (R(2)X = 0.121, R(2)Y = 0.931, and Q(2) = 0.661) and the OPLS-DA (R(2)X = 0.121, R(2)Y = 0.931, Q(2) = 0.653) demonstrated that the model showed good performance. By OPLS-DA, 20 metabolites were identified. A diagnostic model was further constructed using the receiver-operator characteristic (ROC) curves (AUC = 0.953), which exhibited a satisfying sensitivity of 92.6%, specificity of 90% and accuracy of 89.1%. The results demonstrated that the NMR-based metabolomics approach showed good performance in identifying diagnostic urinary biomarkers, providing new insights into the metabolic process related to UAP.

  6. Metabolomics analysis of fungal biofilm development and of arachidonic acid-based quorum sensing mechanism.

    PubMed

    Ząbek, Adam; Junka, Adam; Szymczyk, Patrycja; Wojtowicz, Wojciech; Klimek-Ochab, Magdalena; Młynarz, Piotr

    2017-04-03

    The infections caused by filamentous fungi are becoming worldwide problem of healthcare systems due to increasing drug-resistance of this microorganism and increasing number of immunocompromised nosocomial patients. These infections are related with Aspergillus ability to form sessile communities referred to as the biofilms. The small compounds known as quorum sensing (QS) molecules allow this microorganism to coordinate all processes taking place during biofilm formation and maturation. In the study presented, the HRMAS (1) H NMR metabolomic approach was applied to define composition of extra and intracellular metabolites produced by biofilmic and planktonic (aka free-swimming) cultures of this microorganism and to evaluate impact of quorum sensing molecule, arachidonic acid (AA) on biofilm formation. The Scanning Electron Microscopy was used to confirm Aspergillus ability to form biofilm in vitro, while multivariate and univariate data analysis was applied to analyze data obtained. The Aspergillus strain was able to form strong biofilm structures in vitro. The statistical analysis revealed significant changes of metabolite production depending on Aspergillus culture type (biofilm vs. plankton), time and presence of QS molecules. The data obtained, if developed, might be used in future NMR diagnostics as markers of Aspergillus biofilm-related infections and lead to shorten time between pathogen identification and introduction of treatment.

  7. Network analysis of the metabolome and transcriptome reveals novel regulation of potato pigmentation

    PubMed Central

    Cho, Kyoungwon; Cho, Kwang-Soo; Sohn, Hwang-Bae; Ha, In Jin; Hong, Su-Young; Lee, Hyerim; Kim, Young-Mi; Nam, Myung Hee

    2016-01-01

    To gain insights into the regulatory networks related to anthocyanin biosynthesis and identify key regulatory genes, we performed an integrated analysis of the transcriptome and metabolome in sprouts germinated from three colored potato cultivars: light-red Hongyoung, dark-purple Jayoung, and white Atlantic. We investigated transcriptional and metabolic changes using statistical analyses and gene–metabolite correlation networks. Transcript and metabolite profiles were generated through high-throughput RNA-sequencing data analysis and ultraperformance liquid chromatography quadrupole time-of-flight tandem mass spectrometry, respectively. The identification and quantification of changes in anthocyanin were performed using molecular formula-based mass accuracy and specific features of their MS2 spectra. Correlation tests of anthocyanin contents and transcriptional changes showed 823 strong correlations (correlation coefficient, R 2>0.9) between 22 compounds and 119 transcripts categorized into flavonoid metabolism, hormones, transcriptional regulation, and signaling. The connection network of anthocyanins and genes showed a regulatory system involved in the pigmentation of light-red Hongyoung and dark-purple Jayoung potatoes, suggesting that this systemic approach is powerful for investigations into novel genes that are potential targets for the breeding of new valuable potato cultivars. PMID:26733692

  8. Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis

    PubMed Central

    Gu, Jinping; Hu, Xiaomin; Shao, Wei; Ji, Tianhai; Yang, Wensheng; Zhuo, Huiqin; Jin, Zeyu; Huang, Huiying; Chen, Jiacheng; Huang, Caihua; Lin, Donghai

    2016-01-01

    Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression. PMID:27527852

  9. Metabolomic Analysis of Exercise Effects in the POLG Mitochondrial DNA Mutator Mouse Brain

    PubMed Central

    Clark-Matott, Joanne; Saleem, Ayesha; Dai, Ying; Shurubor, Yevgeniya; Ma, Xiaoxing; Safdar, Adeel; Beal, M. Flint; Tarnopolsky, Mark; Simon, David K.

    2015-01-01

    Mitochondrial DNA (mtDNA) mutator mice express a mutated form of mtDNA polymerase gamma (PolgA) that results an accelerated accumulation of somatic mtDNA mutations in association with a premature aging phenotype. An exploratory metabolomic analysis of cortical metabolites in sedentary and exercised mtDNA mutator mice and wild-type (WT) littermate controls at 9–10 months of age was performed. Pathway analysis revealed deficits in the neurotransmitters acetylcholine, glutamate and aspartate that were ameliorated by exercise. Nicotinamide adenine dinucleotide (NAD+) depletion and evidence of increased Poly [ADP-ribose] polymerase 1 (PARP-1) activity were apparent in sedentary mtDNA mutator mouse cortex, along with deficits in carnitine metabolites and an upregulated antioxidant response that largely normalized with exercise. These data highlight specific pathways that are altered in the brain in association with an accelerated age-related accumulation of somatic mtDNA mutations. These results may have relevance to age-related neurodegenerative diseases associated with mitochondrial dysfunction, such as Alzheimer’s disease and Parkinson’s disease, and provide insights into potential mechanisms of beneficial effects of exercise on brain function. PMID:26294258

  10. 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.

  11. Elemental metabolomics.

    PubMed

    Zhang, Ping; Georgiou, Constantinos A; Brusic, Vladimir

    2017-01-10

    Elemental metabolomics is quantification and characterization of total concentration of chemical elements in biological samples and monitoring of their changes. Recent advances in inductively coupled plasma mass spectrometry have enabled simultaneous measurement of concentrations of > 70 elements in biological samples. In living organisms, elements interact and compete with each other for absorption and molecular interactions. They also interact with proteins and nucleotide sequences. These interactions modulate enzymatic activities and are critical for many molecular and cellular functions. Testing for concentration of > 40 elements in blood, other bodily fluids and tissues is now in routine use in advanced medical laboratories. In this article, we define the basic concepts of elemental metabolomics, summarize standards and workflows, and propose minimum information for reporting the results of an elemental metabolomics experiment. Major statistical and informatics tools for elemental metabolomics are reviewed, and examples of applications are discussed. Elemental metabolomics is emerging as an important new technology with applications in medical diagnostics, nutrition, agriculture, food science, environmental science and multiplicity of other areas. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. Combining metabolomic analysis and microarray gene expression analysis in the characterization of the medicinal plant Chelidonium majus L.

    PubMed

    Orland, A; Knapp, K; König, G M; Ulrich-Merzenich, G; Knöß, W

    2014-10-15

    Even though herbal medicines have played an important role in disease management and health for many centuries, their present frequent use is challenged by the necessity to determine their complex composition and their multitarget mode of action. In the present study, modern methods were investigated towards their potential in the characterization of herbal substances. As a model the herbal substance Chelidonii herba was used, for which several reports on liver toxicities exist. Extracts of Chelidonii herba with different solvents were characterized phytochemically and functionally by experiments with HepG2 liver cells. Chelidonii herba was extracted with four solvents of different polarity (dichloromethane, water, ethanol, and ethanol 50% (V/V); four replicates each). The different extracts were characterized metabolomically by (1)H-NMR fingerprinting analysis and principal component analysis (PCA). The content of alkaloids was additionally determined by RP-HPLC. Functional characterization was achieved by the determination of cell proliferation and by transcriptomics techniques (Whole Genome Gene Expression Microarrays v2, Agilent Technologies) in HepG2 cells after exposure to the different extracts (four experimental replicates each). Based on data from (1)H-NMR fingerprints and RP-HPLC analyses the different extracts showed a divergent composition of constituents depending on the solvent used. HepG2 liver cells responded differentially to the four extracts. Microarray analysis revealed a significant regulation of genes and signal cascades related to biotransformation. Also liver-toxic signal cascades were activated. Neither the activated genes nor the proliferation response could be clearly related to the differing alkaloid content of the extracts. Different manufacturing processes lead to different herbal preparations. A systems biology approach combining a metabolomic plant analysis with a functional characterization by gene expression profiling in HepG2

  13. Extraction protocol for nontargeted NMR and LC-MS metabolomics-based analysis of hard coral and their algal symbionts.

    PubMed

    Gordon, Benjamin R; Leggat, William; Motti, Cherie A

    2013-01-01

    Metabolomics and in particular, nontargeted metabolomics, has become a popular technique for the study of biological samples as it provides considerable amounts of information on extractable metabolites and is ideal for studying the metabolic response of an organism to stressors in its environment. One such organism, the symbiotic hard coral, presents its own complexity when considering a metabolomics approach in that it forms intricate associations with an array of symbiotic macro- and microbiota. While not discounting the importance of these many associations to the function of the coral holobiont, the coral-Symbiodinium relationship has been the most studied to date and as such, is the primary focus of this extraction protocol. This protocol provides details for the sample collection, extraction, and measurement of hard coral holobiont metabolites using both (1)H nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography coupled with mass spectrometry (LC-MS). Using this nontargeted metabolomics approach, the holobiont metabolism can be investigated for perturbations resulting from either (1) natural or anthropogenic environmental challenges, (2) the controlled application of stressors, and (3) differences between phenotypes or species. Consequently, this protocol will benefit both environmental and natural products based research of hard coral and their algal symbionts. Every effort has been made to provide the reader with all the details required to perform this protocol, including many of the costly and time consuming "pitfalls" or "traps" that were discovered during its development. As a result, this protocol can be confidently accomplished by those with less experience in the extraction and analysis of symbiotic hard coral, requiring minimal user input whilst ensuring reproducible and reliable results using readily available lab ware and reagents.

  14. Sparsity as cellular objective to infer directed metabolic networks from steady-state metabolome data: a theoretical analysis.

    PubMed

    Öksüz, Melik; Sadıkoğlu, Hasan; Çakır, Tunahan

    2013-01-01

    Since metabolome data are derived from the underlying metabolic network, reverse engineering of such data to recover the network topology is of wide interest. Lyapunov equation puts a constraint to the link between data and network by coupling the covariance of data with the strength of interactions (Jacobian matrix). This equation, when expressed as a linear set of equations at steady state, constitutes a basis to infer the network structure given the covariance matrix of data. The sparse structure of metabolic networks points to reactions which are active based on minimal enzyme production, hinting at sparsity as a cellular objective. Therefore, for a given covariance matrix, we solved Lyapunov equation to calculate Jacobian matrix by a simultaneous use of minimization of Euclidean norm of residuals and maximization of sparsity (the number of zeros in Jacobian matrix) as objective functions to infer directed small-scale networks from three kingdoms of life (bacteria, fungi, mammalian). The inference performance of the approach was found to be promising, with zero False Positive Rate, and almost one True positive Rate. The effect of missing data on results was additionally analyzed, revealing superiority over similarity-based approaches which infer undirected networks. Our findings suggest that the covariance of metabolome data implies an underlying network with sparsest pattern. The theoretical analysis forms a framework for further investigation of sparsity-based inference of metabolic networks from real metabolome data.

  15. 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

  16. 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.

  17. Metabolomics analysis reveals the metabolic and functional roles of flavonoids in light-sensitive tea leaves.

    PubMed

    Zhang, Qunfeng; Liu, Meiya; Ruan, Jianyun

    2017-03-20

    As the predominant secondary metabolic pathway in tea plants, flavonoid biosynthesis increases with increasing temperature and illumination. However, the concentration of most flavonoids decreases greatly in light-sensitive tea leaves when they are exposed to light, which further improves tea quality. To reveal the metabolism and potential functions of flavonoids in tea leaves, a natural light-sensitive tea mutant (Huangjinya) cultivated under different light conditions was subjected to metabolomics analysis. The results showed that chlorotic tea leaves accumulated large amounts of flavonoids with ortho-dihydroxylated B-rings (e.g., catechin gallate, quercetin and its glycosides etc.), whereas total flavonoids (e.g., myricetrin glycoside, epigallocatechin gallate etc.) were considerably reduced, suggesting that the flavonoid components generated from different metabolic branches played different roles in tea leaves. Furthermore, the intracellular localization of flavonoids and the expression pattern of genes involved in secondary metabolic pathways indicate a potential photoprotective function of dihydroxylated flavonoids in light-sensitive tea leaves. Our results suggest that reactive oxygen species (ROS) scavenging and the antioxidation effects of flavonoids help chlorotic tea plants survive under high light stress, providing new evidence to clarify the functional roles of flavonoids, which accumulate to high levels in tea plants. Moreover, flavonoids with ortho-dihydroxylated B-rings played a greater role in photo-protection to improve the acclimatization of tea plants.

  18. Metabolome Analysis of Arabidopsis thaliana Roots Identifies a Key Metabolic Pathway for Iron Acquisition

    PubMed Central

    Schmidt, Holger; Günther, Carmen; Weber, Michael; Spörlein, Cornelia; Loscher, Sebastian; Böttcher, Christoph; Schobert, Rainer; Clemens, Stephan

    2014-01-01

    Fe deficiency compromises both human health and plant productivity. Thus, it is important to understand plant Fe acquisition strategies for the development of crop plants which are more Fe-efficient under Fe-limited conditions, such as alkaline soils, and have higher Fe density in their edible tissues. Root secretion of phenolic compounds has long been hypothesized to be a component of the reduction strategy of Fe acquisition in non-graminaceous plants. We therefore subjected roots of Arabidopsis thaliana plants grown under Fe-replete and Fe-deplete conditions to comprehensive metabolome analysis by gas chromatography-mass spectrometry and ultra-pressure liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry. Scopoletin and other coumarins were found among the metabolites showing the strongest response to two different Fe-limited conditions, the cultivation in Fe-free medium and in medium with an alkaline pH. A coumarin biosynthesis mutant defective in ortho-hydroxylation of cinnamic acids was unable to grow on alkaline soil in the absence of Fe fertilization. Co-cultivation with wild-type plants partially rescued the Fe deficiency phenotype indicating a contribution of extracellular coumarins to Fe solubilization. Indeed, coumarins were detected in root exudates of wild-type plants. Direct infusion mass spectrometry as well as UV/vis spectroscopy indicated that coumarins are acting both as reductants of Fe(III) and as ligands of Fe(II). PMID:25058345

  19. Metabolomic analysis of antimicrobial mechanisms of ε-poly-L-lysine on Saccharomyces cerevisiae.

    PubMed

    Bo, Tao; Liu, Miao; Zhong, Cheng; Zhang, Qian; Su, Qin-Zhi; Tan, Zhi-Lei; Han, Pei-Pei; Jia, Shi-Ru

    2014-05-14

    ε-Poly-L-lysine (ε-PL), a naturally occurring amino acid homopolymer, has been widely used as a food preservative. However, its antimicrobial mechanism has not been fully understood. This study investigated the antimicrobial mode of action of ε-PL on a yeast, Saccharomyces cerevisiae. When treated with ε-PL at the concentration of 500 μg/mL, cell mortality was close to 100% and the phospholipid bilayer curvature, pores, and micelles on the surface of S. cerevisiae were clearly observed by scanning electron microscopy (SEM). At the level of 200 μg/mL, ε-PL significantly inhibited the cell growth of S. cerevisiae. When treated with 50 μg/mL ε-PL, the yeast cell was able to grow but the cell cycle was prolonged. A significant increase in cell membrane permeability was induced by ε-PL at higher concentrations. Metabolomics analysis revealed that the ε-PL stress led to the inhibition of primary metabolic pathways through the suppression of the tricarboxylic acid cycle and glycolysis. It is therefore proposed that the microbiostatic effect of ε-PL at lower levels on S. cerevisiae is achieved by inducing intracellular metabolic imbalance via disruption of cell membrane functions. Moreover, the results suggested that the antimicrobial mechanism of ε-PL on S. cerevisiae can in fact change from microbiostatic to microbicidal when the concentration of ε-PL increased, and the mechanisms of these two modes of action were completely different.

  20. Effect of Major Royal Jelly Proteins on Spatial Memory in Aged Rats: Metabolomics Analysis in Urine.

    PubMed

    Chen, Di; Liu, Fang; Wan, Jian-Bo; Lai, Chao-Qiang; Shen, Li-Rong

    2017-04-10

    Royal jelly (RJ) produced by worker honeybees is the sole food for the queen bee throughout her life as well as the larvae of worker bees for the first 3 days after hatching. Supplementation of RJ in the diet has been shown to increase spatial memory in rodents. However, the key constituents in RJ responsible for improvement of cognitive function are unknown. Our objective was to determine if the major royal jelly proteins (MRJPs) extracted from RJ can improve the spatial memory of aged rats. The spatial memory assay using the Morris water maze test was administered once to rats after a 14-week feeding. Metabolomics analysis based on quadrupole time-of-flight mass spectrometry was conducted to examine the differences in compounds from urine. Aged male rats fed MRJPs showed improved spatial memory up to 48.5% when compared to the control male aged rats fed distilled water. The metabolite pattern of the MRJPs-fed aged rats was regressed to that of the young rats. Compounds altered by MRJPs were mapped to nicotinate and nicotinamide metabolism, cysteine taurine metabolism, and energy metabolism pathways. In summary, MRJPs may improve spatial memory and possess the potential for prevention of cognitive impairment via the cysteine and taurine metabolism and energy metabolism pathways in aged rats.

  1. Metabolomics analysis of exhaled breath condensate for discrimination between lung cancer patients and risk factor individuals.

    PubMed

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

    2016-02-11

    The search for new clinical tests aimed at diagnosing chronic respiratory diseases is a current research line motivated by the lack of efficient screening tools and the severity of some of these pathologies. Alternative biological samples can open the door to new screening tools. A promising biofluid that is rarely used for diagnostic purposes is exhaled breath condensate (EBC), the composition of which has been inadequately studied. In this research, untargeted analysis of EBC using gas chromatography time-of-flight mass spectrometry has been applied to a cohort of patients with lung cancer (n  =  48), risk factor individuals (active smokers and ex-smokers, n  =  130) and control healthy individuals (non-smokers without respiratory diseases, n  =  61). An identical protocol was applied to the two EBC fractions provided by the sampling device (upper and central airways and distal airway) from each individual, which allowed the compositional differences between the two EBC fractions to be detected. Tentative compounds that contribute to discrimination between the three groups were identified, and a relevant role for lipids such as monoacylglycerols and squalene was found. These results could support the ability of metabolomics to go inside the study of lung cancer.

  2. Metabolome analysis of Arabidopsis thaliana roots identifies a key metabolic pathway for iron acquisition.

    PubMed

    Schmidt, Holger; Günther, Carmen; Weber, Michael; Spörlein, Cornelia; Loscher, Sebastian; Böttcher, Christoph; Schobert, Rainer; Clemens, Stephan

    2014-01-01

    Fe deficiency compromises both human health and plant productivity. Thus, it is important to understand plant Fe acquisition strategies for the development of crop plants which are more Fe-efficient under Fe-limited conditions, such as alkaline soils, and have higher Fe density in their edible tissues. Root secretion of phenolic compounds has long been hypothesized to be a component of the reduction strategy of Fe acquisition in non-graminaceous plants. We therefore subjected roots of Arabidopsis thaliana plants grown under Fe-replete and Fe-deplete conditions to comprehensive metabolome analysis by gas chromatography-mass spectrometry and ultra-pressure liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry. Scopoletin and other coumarins were found among the metabolites showing the strongest response to two different Fe-limited conditions, the cultivation in Fe-free medium and in medium with an alkaline pH. A coumarin biosynthesis mutant defective in ortho-hydroxylation of cinnamic acids was unable to grow on alkaline soil in the absence of Fe fertilization. Co-cultivation with wild-type plants partially rescued the Fe deficiency phenotype indicating a contribution of extracellular coumarins to Fe solubilization. Indeed, coumarins were detected in root exudates of wild-type plants. Direct infusion mass spectrometry as well as UV/vis spectroscopy indicated that coumarins are acting both as reductants of Fe(III) and as ligands of Fe(II).

  3. Metabolomic analysis reveals that carnitines are key regulatory metabolites in phase transition of the locusts.

    PubMed

    Wu, Rui; Wu, Zeming; Wang, Xianhui; Yang, Pengcheng; Yu, Dan; Zhao, Chunxia; Xu, Guowang; Kang, Le

    2012-02-28

    Phenotypic plasticity occurs prevalently and plays a vital role in adaptive evolution. However, the underlying molecular mechanisms responsible for the expression of alternate phenotypes remain unknown. Here, a density-dependent phase polyphenism of Locusta migratoria was used as the study model to identify key signaling molecules regulating the expression of phenotypic plasticity. Metabolomic analysis, using high-performance liquid chromatography and gas chromatography-mass spectrometry, showed that solitarious and gregarious locusts have distinct metabolic profiles in hemolymph. A total of 319 metabolites, many of which are involved in lipid metabolism, differed significantly in concentration between the phases. In addition, the time course of changes in the metabolic profiles of locust hemolymph that accompany phase transition was analyzed. Carnitine and its acyl derivatives, which are involved in the lipid β-oxidation process, were identified as key differential metabolites that display robust correlation with the time courses of phase transition. RNAi silencing of two key enzymes from the carnitine system, carnitine acetyltransferase and palmitoyltransferase, resulted in a behavioral transition from the gregarious to solitarious phase and the corresponding changes of metabolic profiles. In contrast, the injection of exogenous acetylcarnitine promoted the acquisition of gregarious behavior in solitarious locusts. These results suggest that carnitines mediate locust phase transition possibly through modulating lipid metabolism and influencing the nervous system of the locusts.

  4. Metabolomics and in-silico analysis reveal critical energy deregulations in animal models of Parkinson's disease.

    PubMed

    Poliquin, Pierre O; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

    2013-01-01

    Parkinson's disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a mitochondrial uncoupler [corrected]. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level.

  5. Metabolomics-driven quantitative analysis of ammonia assimilation in E. coli

    PubMed Central

    Yuan, Jie; Doucette, Christopher D; Fowler, William U; Feng, Xiao-Jiang; Piazza, Matthew; Rabitz, Herschel A; Wingreen, Ned S; Rabinowitz, Joshua D

    2009-01-01

    Despite extensive study of individual enzymes and their organization into pathways, the means by which enzyme networks control metabolite concentrations and fluxes in cells remains incompletely understood. Here, we examine the integrated regulation of central nitrogen metabolism in Escherichia coli through metabolomics and ordinary-differential-equation-based modeling. Metabolome changes triggered by modulating extracellular ammonium centered around two key intermediates in nitrogen assimilation, α-ketoglutarate and glutamine. Many other compounds retained concentration homeostasis, indicating isolation of concentration changes within a subset of the metabolome closely linked to the nutrient perturbation. In contrast to the view that saturated enzymes are insensitive to substrate concentration, competition for the active sites of saturated enzymes was found to be a key determinant of enzyme fluxes. Combined with covalent modification reactions controlling glutamine synthetase activity, such active-site competition was sufficient to explain and predict the complex dynamic response patterns of central nitrogen metabolites. PMID:19690571

  6. Consolidating metabolite identifiers to enable contextual and multi-platform metabolomics data analysis.

    PubMed

    Redestig, Henning; Kusano, Miyako; Fukushima, Atsushi; Matsuda, Fumio; Saito, Kazuki; Arita, Masanori

    2010-04-29

    Analysis of data from high-throughput experiments depends on the availability of well-structured data that describe the assayed biomolecules. Procedures for obtaining and organizing such meta-data on genes, transcripts and proteins have been streamlined in many data analysis packages, but are still lacking for metabolites. Chemical identifiers are notoriously incoherent, encompassing a wide range of different referencing schemes with varying scope and coverage. Online chemical databases use multiple types of identifiers in parallel but lack a common primary key for reliable database consolidation. Connecting identifiers of analytes found in experimental data with the identifiers of their parent metabolites in public databases can therefore be very laborious. Here we present a strategy and a software tool for integrating metabolite identifiers from local reference libraries and public databases that do not depend on a single common primary identifier. The program constructs groups of interconnected identifiers of analytes and metabolites to obtain a local metabolite-centric SQLite database. The created database can be used to map in-house identifiers and synonyms to external resources such as the KEGG database. New identifiers can be imported and directly integrated with existing data. Queries can be performed in a flexible way, both from the command line and from the statistical programming environment R, to obtain data set tailored identifier mappings. Efficient cross-referencing of metabolite identifiers is a key technology for metabolomics data analysis. We provide a practical and flexible solution to this task and an open-source program, the metabolite masking tool (MetMask), available at http://metmask.sourceforge.net, that implements our ideas.

  7. Consolidating metabolite identifiers to enable contextual and multi-platform metabolomics data analysis

    PubMed Central

    2010-01-01

    Background Analysis of data from high-throughput experiments depends on the availability of well-structured data that describe the assayed biomolecules. Procedures for obtaining and organizing such meta-data on genes, transcripts and proteins have been streamlined in many data analysis packages, but are still lacking for metabolites. Chemical identifiers are notoriously incoherent, encompassing a wide range of different referencing schemes with varying scope and coverage. Online chemical databases use multiple types of identifiers in parallel but lack a common primary key for reliable database consolidation. Connecting identifiers of analytes found in experimental data with the identifiers of their parent metabolites in public databases can therefore be very laborious. Results Here we present a strategy and a software tool for integrating metabolite identifiers from local reference libraries and public databases that do not depend on a single common primary identifier. The program constructs groups of interconnected identifiers of analytes and metabolites to obtain a local metabolite-centric SQLite database. The created database can be used to map in-house identifiers and synonyms to external resources such as the KEGG database. New identifiers can be imported and directly integrated with existing data. Queries can be performed in a flexible way, both from the command line and from the statistical programming environment R, to obtain data set tailored identifier mappings. Conclusions Efficient cross-referencing of metabolite identifiers is a key technology for metabolomics data analysis. We provide a practical and flexible solution to this task and an open-source program, the metabolite masking tool (MetMask), available at http://metmask.sourceforge.net, that implements our ideas. PMID:20426876

  8. Transcriptional and metabolomic analysis of Ascophyllum nodosum mediated freezing tolerance in Arabidopsis thaliana

    PubMed Central

    2012-01-01

    Background We have previously shown that lipophilic components (LPC) of the brown seaweed Ascophyllum nodosum (ANE) improved freezing tolerance in Arabidopsis thaliana. However, the mechanism(s) of this induced freezing stress tolerance is largely unknown. Here, we investigated LPC induced changes in the transcriptome and metabolome of A. thaliana undergoing freezing stress. Results Gene expression studies revealed that the accumulation of proline was mediated by an increase in the expression of the proline synthesis genes P5CS1 and P5CS2 and a marginal reduction in the expression of the proline dehydrogenase (ProDH) gene. Moreover, LPC application significantly increased the concentration of total soluble sugars in the cytosol in response to freezing stress. Arabidopsis sfr4 mutant plants, defective in the accumulation of free sugars, treated with LPC, exhibited freezing sensitivity similar to that of untreated controls. The 1H NMR metabolite profile of LPC-treated Arabidopsis plants exposed to freezing stress revealed a spectrum dominated by chemical shifts (δ) representing soluble sugars, sugar alcohols, organic acids and lipophilic components like fatty acids, as compared to control plants. Additionally, 2D NMR spectra suggested an increase in the degree of unsaturation of fatty acids in LPC treated plants under freezing stress. These results were supported by global transcriptome analysis. Transcriptome analysis revealed that LPC treatment altered the expression of 1113 genes (5%) in comparison with untreated plants. A total of 463 genes (2%) were up regulated while 650 genes (3%) were down regulated. Conclusion Taken together, the results of the experiments presented in this paper provide evidence to support LPC mediated freezing tolerance enhancement through a combination of the priming of plants for the increased accumulation of osmoprotectants and alteration of cellular fatty acid composition. PMID:23171218

  9. Metabolome analysis of milk fermented by γ-aminobutyric acid-producing Lactococcus lactis.

    PubMed

    Hagi, Tatsuro; Kobayashi, Miho; Nomura, Masaru

    2016-02-01

    γ-Aminobutyric acid (GABA) is one of the most important functional components in fermented foods because of its physiological functions, such as neurotransmission and antihypertensive activities. However, little is known about components other than GABA in GABA-rich fermented foods. A metabolomic approach offers an opportunity to discover bioactive and flavor components in fermented food. To find specific components in milk fermented with GABA-producing Lactococcus lactis 01-7, we compared the components found in GABA-rich fermented milk with those found in control milk fermented without GABA production using capillary electrophoresis time-of-flight mass spectrometry. A principal component analysis score plot showed a clear differentiation between the control milk fermented with L. lactis 01-1, which does not produce GABA, and GABA-rich milk fermented with a combination of L. lactis strains 01-1 and 01-7. As expected, the amount of GABA in GABA-rich fermented milk was much higher (1,216-fold) than that of the control milk. Interestingly, the amount of Orn was also much higher (27-fold) than that of the control milk. Peptide analysis showed that levels of 6 putative angiotensin-I-converting enzyme (ACE)-inhibitory peptides were also higher in the GABA-rich fermented milk. Furthermore, ACE-inhibitory activity of GABA-rich fermented milk tended to be higher than that of the control milk. These results indicate that the GABA-producing strain 01-7 provides fermented milk with other functional components in addition to GABA. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  10. Liquid chromatography time of flight mass spectrometry based environmental metabolomics for the analysis of Pseudomonas putida Bacteria in potable water.

    PubMed

    Kouremenos, Konstantinos A; Beale, David J; Antti, Henrik; Palombo, Enzo A

    2014-09-01

    Water supply biofilms have the potential to harbour waterborne diseases, accelerate corrosion, and contribute to the formation of tuberculation in metallic pipes. One particular species of bacteria known to be found in the water supply networks is Pseudomonas sp., with the presence of Pseudomonas putida being isolated to iron pipe tubercles. Current methods for detecting and analysis pipe biofilms are time consuming and expensive. The application of metabolomics techniques could provide an alternative method for assessing biofilm risk more efficiently based on bacterial activity. As such, this paper investigates the application of metabolomic techniques and provides a proof-of-concept application using liquid chromatography coupled with time-of-flight mass spectrometry (LC-ToF-MS) to three biologically independent P. putida samples, across five different growth conditions exposed to solid and soluble iron (Fe). Analysis of the samples in +ESI and -ESI mode yielded 887 and 1789 metabolite features, respectively. Chemometric analysis of the +ESI and -ESI data identified 34 and 39 significant metabolite features, respectively, where features were considered significant if the fold change was greater than 2 and obtained a p-value less than 0.05. Metabolite features were subsequently identified according to the Metabolomics Standard Initiative (MSI) Chemical Analysis Workgroup using analytical standards and standard online LC-MS databases. Possible markers for P. putida growth, with and without being exposed to solid and soluble Fe, were identified from a diverse range of different chemical classes of metabolites including nucleobases, nucleosides, dipeptides, tripeptides, amino acids, fatty acids, sugars, and phospholipids. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. An optimized method for NMR-based plant seed metabolomic analysis with maximized polar metabolite extraction efficiency, signal-to-noise ratio, and chemical shift consistency.

    PubMed

    Wu, Xiangyu; Li, Ning; Li, Hongde; Tang, Huiru

    2014-04-07

    Plant metabolomic analysis has become an essential part of functional genomics and systems biology and requires effective extraction of both primary and secondary metabolites from plant cells. To establish an optimized extraction method for the NMR-based analysis, we used the seeds of mungbean (Vigna radiata cv. Elü no. 1) as a model and systematically investigated the dependence of the metabolite composition in plant extracts on various extraction parameters including cell-breaking methods, extraction solvents, number of extraction repeats, tissue-to-solvent ratio, and extract-to-buffer ratio (for final NMR analysis). We also compared two NMR approaches for quantitative metabolomic analysis from completely relaxed spectra directly and from partially relaxed spectra calculated with T1. By maximizing the extraction efficiency and signal-to-noise ratio but minimizing inter-sample chemical-shift variations and metabolite degradations, we established a parameter-optimized protocol for NMR-based plant seed metabolomic analysis. We concluded that aqueous methanol was the best extraction solvent with an optimal tissue-to-solvent ratio of about 1 : 10-1 : 15 (mg per μL). The combination of tissuelyser homogenization with ultrasonication was the choice of cell-breaking method with three repeated extractions being necessary. For NMR analysis, the optimal extract-to-solvent was around 5-8 mg mL(-1) and completely relaxed spectra were ideal for intrinsically quantitative metabolomic analysis although partially relaxed spectra were employable for comparative metabolomics. This optimized method will offer ensured data quality for high-throughput and reliable plant metabolomics studies.

  12. 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.

  13. Renal cell carcinoma: a critical analysis of metabolomic biomarkers emerging from current model systems.

    PubMed

    Rodrigues, Daniela; Monteiro, Márcia; Jerónimo, Carmen; Henrique, Rui; Belo, Luís; Bastos, Maria de Lourdes; Guedes de Pinho, Paula; Carvalho, Márcia

    2017-02-01

    Metabolomics, an emerging field of "omics" sciences, has caught wide scientific attention in the area of biomarker research for cancers in which early diagnostic biomarkers have the potential to greatly improve patient outcome, such as renal cell carcinoma (RCC). Metabolomic approaches have been successfully applied to various human RCC model systems, mostly ex vivo neoplastic renal tissues and biofluids (urine and serum) from patients with RCC. Importantly, in contrast to other cancers, only a few studies have addressed the RCC metabolome using cancer cell culture-based in vitro models. Herein, we first carried out a comprehensive review of current metabolomic data in RCC, with emphasis on metabolite disturbances and dysregulated metabolic pathways identified in each of these experimental models. We then critically analyzed the consistency of evidence in this field and whether metabolites found altered in tumor cell and tissue microenvironment are reflected in biofluids, which constitute the rationale underlying the translation of discovered metabolic biomarkers into noninvasive diagnostic tools. Finally, dominant metabolic pathways and promising metabolites as biomarkers for diagnosis and prognosis of RCC are outlined.

  14. 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...

  15. 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...

  16. Metabolomic Analysis of the Effects of Polychlorinated Biphenyls in Non-alcoholic Fatty Liver Disease

    PubMed Central

    Shi, Xue; Wahlang, Banrida; Wei, Xiaoli; Yin, Xinmin; Falkner, K. Cameron; Prough, Russell A.; Kim, Seong Ho; Mueller, Eugene G.; McClain, Craig J.; Cave, Matthew; Zhang, Xiang

    2012-01-01

    Polychlorinated Biphenyls (PCBs) are persistent organic pollutants and have been associated with abnormal liver enzymes and suspected non-alcoholic fatty liver disease (NAFLD), obesity, and the metabolic syndrome in epidemiological studies. In epidemiological surveys of human PCB exposure, PCB 153 has the highest serum levels among PCB congeners. To determine the hepatic effects of PCB 153 in mice, C57BL/6J mice were fed either a control diet (CD) or a high fat diet (HFD) for 12 weeks, with or without PCB 153 co-exposure. The metabolite extracts from mouse livers were analyzed using linear trap quadruple - Fourier transform ion cyclotron resonance mass spectrometer (LTQ-FTICR MS) via direct infusion nano-electrospray ionization (DI-nESI) mass spectrometry. The metabolomics analysis indicated no difference in the metabolic profile between mice fed the control diet with PCB 153 exposure (CD+PCB 153) and mice fed the control diet (CD) without PCB 153 exposure. However, compared with CD group, levels of 10 metabolites were increased and 15 metabolites were reduced in mice fed HFD. Moreover, compared to CD+PCB 153 group, the abundances of 6 metabolites were increased and 18 metabolites were decreased in the mice fed high fat diet with PCB 153 exposure (HFD+PCB 153). Compared with HFD group, the abundances of 2 metabolites were increased and of 12 metabolites were reduced in HFD+PCB 153 group. These observations agree with the histological results and indicate that the metabolic effects of PCB 153 were highly dependent on macronutrient interactions with HFD. Antioxidant depletion is likely to be an important consequence of this interaction, as this metabolic disturbance has previously been implicated in obesity and NAFLD. PMID:22686559

  17. Proteomic and metabolomic analysis reveals rapid and extensive nicotine detoxification ability in honey bee larvae.

    PubMed

    du Rand, Esther E; Human, Hannelie; Smit, Salome; Beukes, Mervyn; Apostolides, Zeno; Nicolson, Susan W; Pirk, Christian W W

    2017-03-01

    Despite potential links between pesticides and bee declines, toxicology information on honey bee larvae (Apis mellifera) is scarce and detoxification mechanisms in this development stage are virtually unknown. Larvae are exposed to natural and synthetic toxins present in pollen and nectar through consumption of brood food. Due to the characteristic intensive brood care displayed by honey bees, which includes progressive feeding throughout larval development, it is generally assumed that larvae rely on adults to detoxify for them and exhibit a diminished detoxification ability. We found the opposite. We examined the proteomic and metabolomic responses of in vitro reared larvae fed nicotine (an alkaloid found in nectar and pollen) to understand how larvae cope on a metabolic level with dietary toxins. Larvae were able to effectively detoxify nicotine through an inducible detoxification mechanism. A coordinated stress response complemented the detoxification processes, and we detected significant enrichment of proteins functioning in energy and carbohydrate metabolism, as well as in development pathways, suggesting that nicotine may promote larval growth. Further exploration of the metabolic fate of nicotine using targeted mass spectrometry analysis demonstrated that, as in adult bees, formation of 4-hydroxy-4-(3-pyridyl) butanoic acid, the result of 2'C-oxidation of nicotine, is quantitatively the most significant pathway of nicotine metabolism. We provide conclusive evidence that larvae are capable of effectively catabolising a dietary toxin, suggesting that increased larval sensitivity to specific toxins is not due to diminished detoxification abilities. These findings broaden the current understanding of detoxification biochemistry at different organizational levels in the colony, bringing us closer to understanding the capacity of the colony as a superorganism to tolerate and resist toxic compounds, including pesticides, in the environment. Copyright © 2017

  18. Nontargeted metabolome analysis by use of Fourier Transform Ion Cyclotron Mass Spectrometry.

    PubMed

    Aharoni, Asaph; Ric de Vos, C H; Verhoeven, Harrie A; Maliepaard, Chris A; Kruppa, Gary; Bino, Raoul; Goodenowe, Dayan B

    2002-01-01

    Advanced functional genomic tools now allow the parallel and high-throughput analyses of gene and protein expression. Although this information is crucial to our understanding of gene function, it offers insufficient insight into phenotypic changes associated with metabolism. Here we introduce a high-capacity Fourier Transform Ion Cyclotron Mass Spectrometry (FTMS)-based method, capable of nontargeted metabolic analysis and suitable for rapid screening of similarities and dissimilarities in large collections of biological samples (e.g., plant mutant populations). Separation of the metabolites was achieved solely by ultra-high mass resolution; Identification of the putative metabolite or class of metabolites to which it belongs was achieved by determining the elemental composition of the metabolite based upon the accurate mass determination; and relative quantitation was achieved by comparing the absolute intensities of each mass using internal calibration. Crude plant extracts were introduced via direct (continuous flow) injection and ionized by either electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) in both positive or negative ionization modes. We first analyzed four consecutive stages of strawberry fruit development and identified changes in the levels of a large range of masses corresponding to known fruit metabolites. The data also revealed novel information on the metabolic transition from immature to ripe fruit. In another set of experiments, the method was used to track changes in metabolic profiles of tobacco flowers overexpressing a strawberry MYB transcription factor and altered in petal color. Only nine masses appeared different between transgenic and control plants, among which was the mass corresponding to cyanidin-3-rhamnoglucoside, the main flower pigment. The results demonstrate the feasibility and utility of the FTMS approach for a nontargeted and rapid metabolic "fingerprinting," which will greatly speed up current

  19. Comparative proteomic and metabolomic analysis reveal the antiosteoporotic molecular mechanism of icariin from Epimedium brevicornu maxim.

    PubMed

    Xue, Liming; Jiang, Yiping; Han, Ting; Zhang, Naidan; Qin, Luping; Xin, Hailiang; Zhang, Qiaoyan

    2016-11-04

    Icariin, a principal flavonoid glycoside of Epimedium brevicornu Maxim, has been widely proved to possess antiosteoporotic activity with promoting bone formation and decreasing bone resorption. However, the involving mechanisms remain unclear. To clear a global insight of signal pathways involved in anti-osteoporotic mechanism of icariin at proteins and metabolites level by integrating the proteomics and NMR metabonomics, in a systems biology approach. Mice were divided into sham, OVX model and icariin-treated OVX group, after 90 days treatment, difference gel electrophoresis combined with MALDI-TOF/TOF proteomics analysis on bone femur and serum metabolomics were carried out for monitor intracellular processes and elucidate anti-osteoporotic mechanism of icariin. Osteoblast and osteoclast were applied to evaluate the potential signal pathways. Twenty three proteins in bone femur, and 8 metabolites in serum, were significantly altered and identified, involving in bone remodeling, energy metabolism, cytoskeleton, lipid metabolism, MAPK signaling, Ca(2+) signaling et, al. Furthermore, animal experiment show icariin could enhance the BMD and BMC, decrease CTX-I level in ovariectomized mice. The mitochondrial membrane potential and the intracellular ATP levels were increased significantly, and the cytoskeleton were improved in icariin-treatment osteoblast and osteoclast. Icariin also increased mRNA expression of Runx2 and osterix of OB, decreased CTR and CAII mRNA expression and protein expression of P38 and JNK. However, icariin did not reveal any inhibition of the collagenolytic activity of cathepsin K, mRNA expression of MMP-9 and protein expression of ERK in osteoclast. we consider icariin as multi-targeting compounds for treating with osteoporosis, involve initiating osteoblastogenesis, inhibiting adipogenesis, and preventing osteoclast differentiation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  20. Metabolomics-Based Analysis of Banana and Pear Ingestion on Exercise Performance and Recovery.

    PubMed

    Nieman, David C; Gillitt, Nicholas D; Sha, Wei; Meaney, Mary Pat; John, Casey; Pappan, Kirk L; Kinchen, Jason M

    2015-12-04

    Bananas and pears vary in sugar and phenolic profiles, and metabolomics was utilized to measure their influence on exercise performance and recovery. Male athletes (N = 20) cycled for 75 km while consuming water (WATER), bananas (BAN), or pears (PEAR) (0.6 g carbohydrate/kg each hour) in randomized order. UPLC-MS/MS and the library of purified standards maintained by Metabolon (Durham, NC) were used to analyze metabolite shifts in pre- and postexercise (0-h, 1.5-h, 21-h) blood samples. Performance times were 5.0% and 3.3% faster during BAN and PEAR versus WATER (P = 0.018 and P = 0.091, respectively), with reductions in cortisol, IL-10, and total leukocytes, and increases in blood glucose, insulin, and FRAP. Partial Least Square Discriminant Analysis (PLS-DA) showed a distinct separation between trials immediately (R(2)Y = 0.877, Q(2)Y = 0.457) and 1.5-h postexercise (R(2)Y = 0.773, Q(2)Y = 0.441). A total of 107 metabolites (primarily lipid-related) increased more than 2-fold during WATER, with a 48% and 52% reduction in magnitude during BAN and PEAR recovery (P < 0.001). Increases in metabolites unique to BAN and PEAR included fructose and fruit constituents, and sulfated phenolics that were related to elevated FRAP. These data indicate that BAN and PEAR ingestion improves 75-km cycling performance, attenuates fatty acid utilization and oxidation, and contributes unique phenolics that augment antioxidant capacity.

  1. Quantitative metabolomics analysis of amino acid metabolism in recombinant Pichia pastoris under different oxygen availability conditions

    PubMed Central

    2012-01-01

    Background Environmental and intrinsic stress factors can result in the global alteration of yeast physiology, as evidenced by several transcriptional studies. Hypoxia has been shown to have a beneficial effect on the expression of recombinant proteins in Pichia pastoris growing on glucose. Furthermore, transcriptional profiling analyses revealed that oxygen availability was strongly affecting ergosterol biosynthesis, central carbon metabolism and stress responses, in particular the unfolded protein response. To contribute to the better understanding of the effect and interplay of oxygen availability and foreign protein secretion on central metabolism, a first quantitative metabolomic analysis of free amino acids pools in a recombinant P. pastoris strain growing under different oxygen availability conditions has been performed. Results The values obtained indicate significant variations in the intracellular amino acid pools due to different oxygen availability conditions, showing an overall increase of their size under oxygen limitation. Notably, even while foreign protein productivities were relatively low (about 40–80 μg Fab/gDCW·h), recombinant protein production was found to have a limited but significant impact on the intracellular amino acid pools, which were generally decreased in the producing strain compared with the reference strain. However, observed changes in individual amino acids pools were not correlated with their corresponding relative abundance in the recombinant protein sequence, but to the overall cell protein amino acid compositional variations. Conclusions Overall, the results obtained, combined with previous transcriptomic and proteomic analyses provide a systematic metabolic fingerprint of the oxygen availability impact on recombinant protein production in P. pastoris. PMID:22704468

  2. High-throughput discovery metabolomics.

    PubMed

    Fuhrer, Tobias; Zamboni, Nicola

    2015-02-01

    Non-targeted metabolomics by mass spectrometry has established as the method of choice for investigating metabolic phenotypes in basic and applied research. Compared to other omics, metabolomics provides broad scope and yet direct information on the integrated cellular response with low demand in material and sample preparation. These features render non-targeted metabolomics ideally suited for large scale screens and discovery. Here we review the achievements and potential in high-throughput, non-targeted metabolomics. We found that routine and precise analysis of thousands of small molecular features in thousands of complex samples per day and instrument is already reality, and ongoing developments in microfluidics and integrated interfaces will likely further boost throughput in the next few years. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. 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.

  4. Benzyl butyl phthalate promotes adipogenesis in 3T3-L1 preadipocytes: A High Content Cellomics and metabolomic analysis.

    PubMed

    Yin, Lei; Yu, Kevin Shengyang; Lu, Kun; Yu, Xiaozhong

    2016-04-01

    Benzyl butyl phthalate (BBP) has been known to induce developmental and reproductive toxicity. However, its association with dysregulation of adipogenesis has been poorly investigated. The present study aimed to examine the effect of BBP on the adipogenesis, and to elucidate the underlying mechanisms using the 3T3-L1 cells. The capacity of BBP to promote adipogenesis was evaluated by multiple staining approaches combined with a High Content Cellomics analysis. The dynamic changes of adipogenic regulatory genes and proteins were examined, and the metabolite profile was identified using GC/MC based metabolomic analysis. The High Content analysis showed BBP in contrast with Bisphenol A (BPA), a known environmental obesogen, increased lipid droplet accumulation in a similar dose-dependent manner. However, the size of the lipid droplets in BBP-treated cells was significantly larger than those in cells treated with BPA. BBP significantly induced mRNA expression of transcriptional factors C/EBPα and PPARγ, their downstream genes, and numerous adipogenic proteins in a dose and time-dependent manner. Furthermore, GC/MC metabolomic analysis revealed that BBP exposure perturbed the metabolic profiles that are associated with glyceroneogenesis and fatty acid synthesis. Altogether, our current study clearly demonstrates that BBP promoted the differentiation of 3T3-L1 through the activation of the adipogenic pathway and metabolic disturbance. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. 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.

  6. 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.

  7. Metabolomic analysis of rat serum in streptozotocin-induced diabetes and after treatment with oral triethylenetetramine (TETA)

    PubMed Central

    2012-01-01

    Background The prevalence, and associated healthcare burden, of diabetes mellitus is increasing worldwide. Mortality and morbidity are associated with diabetic complications in multiple organs and tissues, including the eye, kidney and cardiovascular system, and new therapeutics to treat these complications are required urgently. Triethylenetetramine (TETA) is one such experimental therapeutic that acts to chelate excess copper (II) in diabetic tissues and reduce oxidative stress and cellular damage. Methods Here we have performed two independent metabolomic studies of serum to assess the suitability of the streptozotocin (STZ)-induced rat model for studying diabetes and to define metabolite-related changes associated with TETA treatment. Ultraperformance liquid chromatography-mass spectrometry studies of serum from non-diabetic/untreated, non-diabetic/TETA-treated, STZ-induced diabetic/untreated and STZ-induced diabetic/TETA-treated rats were performed followed by univariate and multivariate analysis of data. Results Multiple metabolic changes related to STZ-induced diabetes, some of which have been reported previously in other animal and human studies, were observed, including changes in amino acid, fatty acid, glycerophospholipid and bile acid metabolism. Correlation analysis suggested that treatment with TETA led to a reversal of diabetes-associated changes in bile acid, fatty acid, steroid, sphingolipid and glycerophospholipid metabolism and proteolysis. Conclusions Metabolomic studies have shown that the STZ-induced rat model of diabetes is an appropriate model system to undertake research into diabetes and potential therapies as several metabolic changes observed in humans and other animal models were also observed in this study. Metabolomics has also identified several biological processes and metabolic pathways implicated in diabetic complications and reversed following treatment with the experimental therapeutic TETA. PMID:22546713

  8. 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

  9. Recent advances of metabolomics in plant biotechnology.

    PubMed

    Okazaki, Yozo; Saito, Kazuki

    2012-01-01

    Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants.

  10. 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.

  11. Quality evaluation and prediction of Citrullus lanatus by 1H NMR-based metabolomics and multivariate analysis.

    PubMed

    Tarachiwin, Lucksanaporn; Masako, Osawa; Fukusaki, Eiichiro

    2008-07-23

    (1)H NMR spectrometry in combination with multivariate analysis was considered to provide greater information on quality assessment over an ordinary sensory testing method due to its high reliability and high accuracy. The sensory quality evaluation of watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) was carried out by means of (1)H NMR-based metabolomics. Multivariate analyses by partial least-squares projections to latent structures-discrimination analysis (PLS-DA) and PLS-regression offered extensive information for quality differentiation and quality evaluation, respectively. The impact of watermelon and rootstock cultivars on the sensory qualities of watermelon was determined on the basis of (1)H NMR metabolic fingerprinting and profiling. The significant metabolites contributing to the discrimination were also identified. A multivariate calibration model was successfully constructed by PLS-regression with extremely high reliability and accuracy. Thus, (1)H NMR-based metabolomics with multivariate analysis was considered to be one of the most suitable complementary techniques that could be applied to assess and predict the sensory quality of watermelons and other horticultural plants.

  12. Pathway Analysis and Metabolites Identification by Metabolomics of Etiolation Substrate from Fresh-Cut Chinese Water Chestnut (Eleocharis tuberosa).

    PubMed

    Li, Yi-Xiao; Pan, Yong-Gui; He, Feng-Ping; Yuan, Meng-Qi; Li, Shang-Bin

    2016-12-01

    Fresh-cut Chinese water chestnuts (CWC) turn yellow after being peeled, reducing their shelf life and commercial value. Metabolomics, the systematic study of the full complement of small molecular metabolites, was useful for clarifying the mechanism of fresh-cut CWC etiolation and developing methods to inhibit yellowing. In this study, metabolic alterations associated with etiolation at different growth stages (0 day, 2 days, 3 days, 4 days, 5 days) from fresh-cut CWC were investigated using LC-MS and analyzed by pattern recognition methods (principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structures-discriminant analysis (OPLS-DA)). The metabolic pathways of the etiolation molecules were elucidated. The main metabolic pathway appears to be the conversion of phenylalanine to p-coumaroyl-CoA, followed by conversion to naringenin chalcone, to naringenin, and naringenin then following different pathways. Firstly, it can transform into apigenin and its derivatives; secondly, it can produce eriodictyol and its derivatives; and thirdly it can produce dihydrokaempferol, quercetin, and myricetin. The eriodictyol can be further transformed to luteolin, cyanidin, dihydroquercetin, dihydrotricetin, and others. This is the first reported use of metabolomics to study the metabolic pathways of the etiolation of fresh-cut CWC.

  13. 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.

  14. Arsenic Exposure Perturbs the Gut Microbiome and Its Metabolic Profile in Mice: An Integrated Metagenomics and Metabolomics Analysis

    PubMed Central

    Abo, Ryan Phillip; Schlieper, Katherine Ann; Graffam, Michelle E.; Levine, Stuart; Wishnok, John S.; Swenberg, James A.; Tannenbaum, Steven R.; Fox, James G.

    2014-01-01

    Background: The human intestine is host to an enormously complex, diverse, and vast microbial community—the gut microbiota. The gut microbiome plays a profound role in metabolic processing, energy production, immune and cognitive development, epithelial homeostasis, and so forth. However, the composition and diversity of the gut microbiome can be readily affected by external factors, which raises the possibility that exposure to toxic environmental chemicals leads to gut microbiome alteration, or dysbiosis. Arsenic exposure affects large human populations worldwide and has been linked to a number of diseases, including cancer, diabetes, and cardiovascular disorders. Objectives: We investigated the impact of arsenic exposure on the gut microbiome composition and its metabolic profiles. Methods: We used an integrated approach combining 16S rRNA gene sequencing and mass spectrometry–based metabolomics profiling to examine the functional impact of arsenic exposure on the gut microbiome. Results: 16S rRNA gene sequencing revealed that arsenic significantly perturbed the gut microbiome composition in C57BL/6 mice after exposure to 10 ppm arsenic for 4 weeks in drinking water. Moreover, metabolomics profiling revealed a concurrent effect, with a number of gut microflora–related metabolites being perturbed in multiple biological matrices. Conclusions: Arsenic exposure not only alters the gut microbiome community at the abundance level but also substantially disturbs its metabolic profiles at the function level. These findings may provide novel insights regarding perturbations of the gut microbiome and its functions as a potential new mechanism by which arsenic exposure leads to or exacerbates human diseases. Citation: Lu K, Abo RP, Schlieper KA, Graffam ME, Levine S, Wishnok JS, Swenberg JA, Tannenbaum SR, Fox JG. 2014. Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis. Environ Health

  15. Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis.

    PubMed

    Lu, Kun; Abo, Ryan Phillip; Schlieper, Katherine Ann; Graffam, Michelle E; Levine, Stuart; Wishnok, John S; Swenberg, James A; Tannenbaum, Steven R; Fox, James G

    2014-03-01

    The human intestine is host to an enormously complex, diverse, and vast microbial community-the gut microbiota. The gut microbiome plays a profound role in metabolic processing, energy production, immune and cognitive development, epithelial homeostasis, and so forth. However, the composition and diversity of the gut microbiome can be readily affected by external factors, which raises the possibility that exposure to toxic environmental chemicals leads to gut microbiome alteration, or dysbiosis. Arsenic exposure affects large human populations worldwide and has been linked to a number of diseases, including cancer, diabetes, and cardiovascular disorders. We investigated the impact of arsenic exposure on the gut microbiome composition and its metabolic profiles. We used an integrated approach combining 16S rRNA gene sequencing and mass spectrometry-based metabolomics profiling to examine the functional impact of arsenic exposure on the gut microbiome. 16S rRNA gene sequencing revealed that arsenic significantly perturbed the gut microbiome composition in C57BL/6 mice after exposure to 10 ppm arsenic for 4 weeks in drinking water. Moreover, metabolomics profiling revealed a concurrent effect, with a number of gut microflora-related metabolites being perturbed in multiple biological matrices. Arsenic exposure not only alters the gut microbiome community at the abundance level but also substantially disturbs its metabolic profiles at the function level. These findings may provide novel insights regarding perturbations of the gut microbiome and its functions as a potential new mechanism by which arsenic exposure leads to or exacerbates human diseases. Lu K, Abo RP, Schlieper KA, Graffam ME, Levine S, Wishnok JS, Swenberg JA, Tannenbaum SR, Fox JG. 2014. Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis. Environ Health Perspect 122:284-291; http://dx.doi.org/10.1289/ehp.1307429.

  16. Metabolomics in agriculture.

    PubMed

    Nadella, K D; Marla, Soma S; Kumar, P Ananda

    2012-04-01

    Metabolome refers to the complete set of metabolites synthesized through a series of multiple enzymatic steps from various biochemical pathways processing the information encrypted in the plant genome. Knowledge about synthesis and regulation of various plant metabolic substances has improved substantially with availability of Omics data originating from sequencing of plant genomes. Metabolic profiling of crops is increasingly becoming popular in assessing plant phenotypes and genetic diversity. Metabolic compositional changes vividly reflect the changes occurring during plant growth, development, and in response to stress. Hence, study of plant metabolic pathways, the interconnections between them in context of systems biology is increasingly becoming popular in identification of candidate genes. The present article reviews recent developments in analysis of plant metabolomics, available bioinformatics techniques and databases employed for comparative pathway analysis, metabolic QTLs, and their application in plants.

  17. Analysis of the hibernation cycle using LC-MS-based metabolomics in ground squirrel liver.

    PubMed

    Nelson, Clark J; Otis, Jessica P; Martin, Sandra L; Carey, Hannah V

    2009-03-03

    A hallmark of hibernation in mammals is metabolic flexibility, which is typified by reversible bouts of metabolic depression (torpor) and the seasonal shift from predominantly carbohydrate to lipid metabolism from summer to winter. To provide new insight into the control and consequences of hibernation, we used LC/MS-based metabolomics to measure differences in small molecules in ground squirrel liver in five activity states: summer, entering torpor, late torpor, arousing from torpor, and interbout arousal. There were significant alterations both seasonally and within torpor-arousal cycles in enzyme cofactor metabolism, amino acid catabolism, and purine and pyrimidine metabolism, with observed metabolites reduced during torpor and increased upon arousal. Multiple lipids also changed, including 1-oleoyllysophosphatidylcholine, cholesterol sulfate, and sphingosine, which tended to be lowest during torpor, and hexadecanedioic acid, which accumulated during a torpor bout. The results reveal the dramatic alterations that occur in several classes of metabolites, highlighting the value of metabolomic analyses in deciphering the hibernation phenotype.

  18. 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.

  19. Metabolomic analysis of Arabidopsis reveals hemiterpenoid glycosides as products of a nitrate ion-regulated, carbon flux overflow.

    PubMed

    Ward, Jane L; Baker, John M; Llewellyn, Aimee M; Hawkins, Nathaniel D; Beale, Michael H

    2011-06-28

    An understanding of the balance between carbon and nitrogen assimilation in plants is key to future bioengineering for a range of applications. Metabolomic analysis of the model plant, Arabidopsis thaliana, using combined NMR-MS revealed the presence of two hemiterpenoid glycosides that accumulated in leaf tissue, to ~1% dry weight under repeated nitrate-deficient conditions. The formation of these isoprenoids was correlated with leaf nitrate concentrations that could also be assayed in the metabolomic data using a unique flavonoid-nitrate mass spectral adduct. Analysis of leaf and root tissue from plants grown in hydroponics with a variety of root stressors identified the conditions under which the isoprenoid pathway in leaves was diverted to the hemiterpenoids. These compounds were strongly induced by root wounding or oxidative stress and weakly induced by potassium deficiency. Other stresses such as cold, saline, and osmotic stress did not induce the compounds. Replacement of nitrate with ammonia failed to suppress the formation of the hemiterpenoids, indicating that nitrate sensing was a key factor. Feeding of intermediates was used to study aspects of 2-C-methyl-d-erythritol-4-phosphate pathway regulation leading to hemiterpenoid formation. The formation of the hemiterpenoids in leaves was strongly correlated with the induction of the phenylpropanoids scopolin and coniferin in roots of the same plants. These shunts of photosynthetic carbon flow are discussed in terms of overflow mechanisms that have some parallels with isoprene production in tree species.

  20. Metabolomic analysis of Arabidopsis reveals hemiterpenoid glycosides as products of a nitrate ion-regulated, carbon flux overflow

    PubMed Central

    Ward, Jane L.; Baker, John M.; Llewellyn, Aimee M.; Hawkins, Nathaniel D.; Beale, Michael H.

    2011-01-01

    An understanding of the balance between carbon and nitrogen assimilation in plants is key to future bioengineering for a range of applications. Metabolomic analysis of the model plant, Arabidopsis thaliana, using combined NMR-MS revealed the presence of two hemiterpenoid glycosides that accumulated in leaf tissue, to ~1% dry weight under repeated nitrate-deficient conditions. The formation of these isoprenoids was correlated with leaf nitrate concentrations that could also be assayed in the metabolomic data using a unique flavonoid–nitrate mass spectral adduct. Analysis of leaf and root tissue from plants grown in hydroponics with a variety of root stressors identified the conditions under which the isoprenoid pathway in leaves was diverted to the hemiterpenoids. These compounds were strongly induced by root wounding or oxidative stress and weakly induced by potassium deficiency. Other stresses such as cold, saline, and osmotic stress did not induce the compounds. Replacement of nitrate with ammonia failed to suppress the formation of the hemiterpenoids, indicating that nitrate sensing was a key factor. Feeding of intermediates was used to study aspects of 2-C-methyl-d-erythritol-4-phosphate pathway regulation leading to hemiterpenoid formation. The formation of the hemiterpenoids in leaves was strongly correlated with the induction of the phenylpropanoids scopolin and coniferin in roots of the same plants. These shunts of photosynthetic carbon flow are discussed in terms of overflow mechanisms that have some parallels with isoprene production in tree species. PMID:21670294

  1. 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.

  2. Altered post-mortem metabolism identified in very fast chilled lamb M. longissimus thoracis et lumborum using metabolomic analysis.

    PubMed

    Warner, Robyn D; Jacob, Robin H; Rosenvold, Katja; Rochfort, Simone; Trenerry, Craige; Plozza, Tim; McDonagh, Matthew B

    2015-10-01

    The aim of this experiment was to use metabolomic techniques to investigate the energy metabolism in lamb M. longissimus thoracis et lumborum subjected to very fast chilling (VFC) post-mortem. The tissue was prepared by 2 different operators and subjected to very fast chilling (less than 0°C within 1.5h of slaughter) or typical chilling regimes (Control; 0°C within 22h of slaughter). Non-targeted metabolomic analysis ((1)H NMR) and targeted analysis ((31)P NMR, HPLC-PDA and HPLC-MS/MS) were used to examine the change in muscle metabolites post-mortem. One VFC treatment, which resulted in a colder core temperature and more tender meat, had higher levels of glycolytic intermediate metabolites pre-rigor as well as more of the end-products of adenosine and nicotine nucleotide metabolism pre-rigor, relative to conventionally chilled treatments. In conclusion, VFC to less than 0°C within 1.5h of slaughter causes considerable changes in metabolism and rigor onset, which are associated with tender meat.

  3. Metabolomic analysis to define and compare the effects of PAHs and oxygenated PAHs in developing zebrafish

    PubMed Central

    Elie, Marc R.; Choi, Jaewoo; Nkrumah-Elie, Yasmeen M.; Gonnerman, Gregory D.; Stevens, Jan F.; Tanguay, Robert L.

    2015-01-01

    Polycyclic aromatic hydrocarbons (PAHs) and their oxygenated derivatives are ubiquitously present in diesel exhaust, atmospheric particulate matter and soils sampled in urban areas. Therefore, inhalation or non-dietary ingestion of both PAHs and oxy-PAHs are major routes of exposure for people; especially young children living in these localities. While there has been extensive research on the parent PAHs, limited studies exist on the biological effects of oxy-PAHs which have been shown to be more soluble and more mobile in the environment. Additionally, investigations comparing the metabolic responses resulting from parent PAHs and oxy-PAHs exposures have not been reported. To address these current gaps, an untargeted metabolomics approach was conducted to examine the in vivo metabolomic profiles of developing zebrafish (Danio rerio) exposed to 4 µM of benz[a]anthracene (BAA) or benz[a]anthracene-7, 12-dione (BAQ). By integrating multivariate, univariate and pathway analyses, a total of 62 metabolites were significantly altered after 5 days of exposure. The marked perturbations revealed that both BAA and BAQ affect protein biosynthesis, mitochondrial function, neural development, vascular development and cardiac function. Our previous transcriptomic and genomic data were incorporated in this metabolomics study to provide a more comprehensive view of the relationship between PAH and oxy-PAH exposures on vertebrate development. PMID:26001975

  4. Metabolomic and Metagenomic Analysis of Two Crude Oil Production Pipelines Experiencing Differential Rates of Corrosion

    PubMed Central

    Bonifay, Vincent; Wawrik, Boris; Sunner, Jan; Snodgrass, Emily C.; Aydin, Egemen; Duncan, Kathleen E.; Callaghan, Amy V.; Oldham, Athenia; Liengen, Turid; Beech, Iwona

    2017-01-01

    Corrosion processes in two North Sea oil production pipelines were studied by analyzing pig envelope samples via metagenomic and metabolomic techniques. Both production systems have similar physico-chemical properties and injection waters are treated with nitrate, but one pipeline experiences severe corrosion and the other does not. Early and late pigging material was collected to gain insight into the potential causes for differential corrosion rates. Metabolites were extracted and analyzed via ultra-high performance liquid chromatography/high-resolution mass spectrometry with electrospray ionization (ESI) in both positive and negative ion modes. Metabolites were analyzed by comparison with standards indicative of aerobic and anaerobic hydrocarbon metabolism and by comparison to predicted masses for KEGG metabolites. Microbial community structure was analyzed via 16S rRNA gene qPCR, sequencing of 16S PCR products, and MySeq Illumina shotgun sequencing of community DNA. Metagenomic data were used to reconstruct the full length 16S rRNA genes and genomes of dominant microorganisms. Sequence data were also interrogated via KEGG annotation and for the presence of genes related to terminal electron accepting (TEA) processes as well as aerobic and anaerobic hydrocarbon degradation. Significant and distinct differences were observed when comparing the ‘high corrosion’ (HC) and the ‘low corrosion’ (LC) pipeline systems, especially with respect to the TEA utilization potential. The HC samples were dominated by sulfate-reducing bacteria (SRB) and archaea known for their ability to utilize simple carbon substrates, whereas LC samples were dominated by pseudomonads with the genetic potential for denitrification and aerobic hydrocarbon degradation. The frequency of aerobic hydrocarbon degradation genes was low in the HC system, and anaerobic hydrocarbon degradation genes were not detected in either pipeline. This is in contrast with metabolite analysis, which

  5. Metabolomic and Metagenomic Analysis of Two Crude Oil Production Pipelines Experiencing Differential Rates of Corrosion.

    PubMed

    Bonifay, Vincent; Wawrik, Boris; Sunner, Jan; Snodgrass, Emily C; Aydin, Egemen; Duncan, Kathleen E; Callaghan, Amy V; Oldham, Athenia; Liengen, Turid; Beech, Iwona

    2017-01-01

    Corrosion processes in two North Sea oil production pipelines were studied by analyzing pig envelope samples via metagenomic and metabolomic techniques. Both production systems have similar physico-chemical properties and injection waters are treated with nitrate, but one pipeline experiences severe corrosion and the other does not. Early and late pigging material was collected to gain insight into the potential causes for differential corrosion rates. Metabolites were extracted and analyzed via ultra-high performance liquid chromatography/high-resolution mass spectrometry with electrospray ionization (ESI) in both positive and negative ion modes. Metabolites were analyzed by comparison with standards indicative of aerobic and anaerobic hydrocarbon metabolism and by comparison to predicted masses for KEGG metabolites. Microbial community structure was analyzed via 16S rRNA gene qPCR, sequencing of 16S PCR products, and MySeq Illumina shotgun sequencing of community DNA. Metagenomic data were used to reconstruct the full length 16S rRNA genes and genomes of dominant microorganisms. Sequence data were also interrogated via KEGG annotation and for the presence of genes related to terminal electron accepting (TEA) processes as well as aerobic and anaerobic hydrocarbon degradation. Significant and distinct differences were observed when comparing the 'high corrosion' (HC) and the 'low corrosion' (LC) pipeline systems, especially with respect to the TEA utilization potential. The HC samples were dominated by sulfate-reducing bacteria (SRB) and archaea known for their ability to utilize simple carbon substrates, whereas LC samples were dominated by pseudomonads with the genetic potential for denitrification and aerobic hydrocarbon degradation. The frequency of aerobic hydrocarbon degradation genes was low in the HC system, and anaerobic hydrocarbon degradation genes were not detected in either pipeline. This is in contrast with metabolite analysis, which demonstrated the

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

    PubMed

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

    2015-04-07

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

  7. An integrative analysis of tissue-specific transcriptomic and metabolomic responses to short-term dietary methionine restriction in mice

    PubMed Central

    Ghosh, Sujoy; Forney, Laura A.; Wanders, Desiree; Stone, Kirsten P.

    2017-01-01

    Dietary methionine restriction (MR) produces a coordinated series of transcriptional responses in peripheral tissues that limit fat accretion, remodel lipid metabolism in liver and adipose tissue, and improve overall insulin sensitivity. Hepatic sensing of reduced methionine leads to induction and release of fibroblast growth factor 21 (FGF21), which acts centrally to increase sympathetic tone and activate thermogenesis in adipose tissue. FGF21 also has direct effects in adipose to enhance glucose uptake and oxidation. However, an understanding of how the liver senses and translates reduced dietary methionine into these transcriptional programs remains elusive. A comprehensive systems biology approach integrating transcriptomic and metabolomic readouts in MR-treated mice confirmed that three interconnected mechanisms (fatty acid transport and oxidation, tricarboxylic acid cycle, and oxidative phosphorylation) were activated in MR-treated inguinal adipose tissue. In contrast, the effects of MR in liver involved up-regulation of anti-oxidant responses driven by the nuclear factor, erythroid 2 like 2 transcription factor, NFE2L2. Metabolomic analysis provided evidence for redox imbalance, stemming from large reductions in the master anti-oxidant molecule glutathione coupled with disproportionate increases in ophthalmate and its precursors, glutamate and 2-aminobutyrate. Thus, cysteine and its downstream product, glutathione, emerge as key early hepatic signaling molecules linking dietary MR to its metabolic phenotype. PMID:28520765

  8. 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

  9. 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.

  10. An integrative analysis of tissue-specific transcriptomic and metabolomic responses to short-term dietary methionine restriction in mice.

    PubMed

    Ghosh, Sujoy; Forney, Laura A; Wanders, Desiree; Stone, Kirsten P; Gettys, Thomas W

    2017-01-01

    Dietary methionine restriction (MR) produces a coordinated series of transcriptional responses in peripheral tissues that limit fat accretion, remodel lipid metabolism in liver and adipose tissue, and improve overall insulin sensitivity. Hepatic sensing of reduced methionine leads to induction and release of fibroblast growth factor 21 (FGF21), which acts centrally to increase sympathetic tone and activate thermogenesis in adipose tissue. FGF21 also has direct effects in adipose to enhance glucose uptake and oxidation. However, an understanding of how the liver senses and translates reduced dietary methionine into these transcriptional programs remains elusive. A comprehensive systems biology approach integrating transcriptomic and metabolomic readouts in MR-treated mice confirmed that three interconnected mechanisms (fatty acid transport and oxidation, tricarboxylic acid cycle, and oxidative phosphorylation) were activated in MR-treated inguinal adipose tissue. In contrast, the effects of MR in liver involved up-regulation of anti-oxidant responses driven by the nuclear factor, erythroid 2 like 2 transcription factor, NFE2L2. Metabolomic analysis provided evidence for redox imbalance, stemming from large reductions in the master anti-oxidant molecule glutathione coupled with disproportionate increases in ophthalmate and its precursors, glutamate and 2-aminobutyrate. Thus, cysteine and its downstream product, glutathione, emerge as key early hepatic signaling molecules linking dietary MR to its metabolic phenotype.

  11. Cordyceps sinensis protects against liver and heart injuries in a rat model of chronic kidney disease: a metabolomic analysis

    PubMed Central

    Liu, Xia; Zhong, Fang; Tang, Xu-long; Lian, Fu-lin; Zhou, Qiao; Guo, Shan-mai; Liu, Jia-fu; Sun, Peng; Hao, Xu; Lu, Ying; Wang, Wei-ming; Chen, Nan; Zhang, Nai-xia

    2014-01-01

    Aim: To test the hypothesis that the traditional Chinese medicine Cordyceps sinensis could improve the metabolic function of extrarenal organs to achieve its anti-chronic kidney disease (CKD) effects. Methods: Male SD rats were divided into CKD rats (with 5/6-nephrectomy), CKD rats treated with Cordyceps sinensis (4 mg•kg-1•d-1, po), and sham-operated rats. After an 8-week treatment, metabolites were extracted from the hearts and livers of the rats, and then subjected to 1H-NMR-based metabolomic analysis. Results: Oxidative stress, energy metabolism, amino acid and protein metabolism and choline metabolism were considered as links between CKD and extrarenal organ dysfunction. Within the experimental period of 8 weeks, the metabolic disorders in the liver were more pronounced than in the heart, suggesting that CKD-related extrarenal organ dysfunctions occurred sequentially rather than simultaneously. Oral administration of Cordyceps sinensis exerted statistically significant rescue effects on the liver and heart by reversely regulating levels of those metabolites that are typically perturbed in CKD. Conclusion: Oral administration of Cordyceps sinensis significantly attenuates the liver and heart injuries in CKD rats. The 1H NMR-based metabolomic approach has provided a systematic view for understanding of CKD and the drug treatment, which can also be used to elucidate the mechanisms of action of other traditional Chinese medicines. PMID:24632844

  12. Metabolomic analysis of patient plasma yields evidence of plant-like α-linolenic acid metabolism in Plasmodium falciparum.

    PubMed

    Lakshmanan, Viswanathan; Rhee, Kyu Y; Wang, Wei; Yu, Yiting; Khafizov, Kamil; Fiser, Andras; Wu, Peng; Ndir, Omar; Mboup, Souleymane; Ndiaye, Daouda; Daily, Johanna P

    2012-07-15

    Metabolomics offers a powerful means to investigate human malaria parasite biology and host-parasite interactions at the biochemical level, and to discover novel therapeutic targets and biomarkers of infection. Here, we used an approach based on liquid chromatography and mass spectrometry to perform an untargeted metabolomic analysis of metabolite extracts from Plasmodium falciparum-infected and uninfected patient plasma samples, and from an enriched population of in vitro cultured P. falciparum-infected and uninfected erythrocytes. Statistical modeling robustly segregated infected and uninfected samples based on metabolite species with significantly different abundances. Metabolites of the α-linolenic acid (ALA) pathway, known to exist in plants but not known to exist in P. falciparum until now, were enriched in infected plasma and erythrocyte samples. In vitro labeling with (13)C-ALA showed evidence of plant-like ALA pathway intermediates in P. falciparum. Ortholog searches using ALA pathway enzyme sequences from 8 available plant genomes identified several genes in the P. falciparum genome that were predicted to potentially encode the corresponding enzymes in the hitherto unannotated P. falciparum pathway. These data suggest that our approach can be used to discover novel facets of host/malaria parasite biology in a high-throughput manner.

  13. Metabolomic analysis of methyl jasmonate-induced triterpenoid production in the medicinal herb Centella asiatica (L.) urban.

    PubMed

    James, Jacinda T; Tugizimana, Fidele; Steenkamp, Paul A; Dubery, Ian A

    2013-04-11

    Centella asiatica is an important source of biologically active pentacyclic triterpenoids. The enhancement of the biosynthesis of the centellosides by manipulation of associated metabolic pathways is receiving much attention. Jasmonates play critical roles in plant metabolism by up-regulating the expression of genes related to secondary metabolites. Here, we investigated the effect of methyl jasmonate (MeJa) in C. asiatica through targeted metabolomic profiling of asiaticoside and madecassoside as well as their aglycones, asiatic acid and madecassic acid. Cell suspensions were treated with 0.2 mM MeJa for 2, 4 and 6 days. Liquid chromatography coupled to mass spectrometry (LC-MS) was used to explore induced changes in metabolite profiles, both qualitatively and quantitatively. Principal component analysis (PCA)-derived scores plots revealed clusters of sample replicates for control and treated samples at 2, 4 and 6 days while loading plots aided in identifying signatory biomarkers (asiatic acid and madecassic acid, as well as asiaticoside and madecassoside) that clearly demonstrate the variability between samples. In addition to increased biosynthesis of the targeted centelloids, other differential changes in the intracellular metabolite profiles reflected the response of the C. asiatica cells to the MeJa-treatment as a reprogramming of the metabolome.

  14. Metabolomic analysis of plasma metabolites that may mediate effects of rye bread on satiety and weight maintenance in postmenopausal women.

    PubMed

    Lankinen, Maria; Schwab, Ursula; Seppänen-Laakso, Tuulikki; Mattila, Ismo; Juntunen, Katri; Mykkänen, Hannu; Poutanen, Kaisa; Gylling, Helena; Oresic, Matej

    2011-01-01

    The evidence of the beneficial health effects of dietary fiber and whole grain consumption is strong, but the underlying mechanisms are not completely understood. Here, we investigate how the consumption of high-fiber rye bread (RB) or white-wheat bread (WB) modifies the plasma metabolomic profiles in postmenopausal women. The study was a randomized crossover trial consisting of 8-wk intervention periods and an 8-wk washout period. The study included 39 postmenopausal women with elevated serum total cholesterol (5.0-8.5 mmol/L) and BMI 20-33 kg/m(2). During the intervention periods, the study breads contributed to least 20% of total energy intake. Two analytical platforms for metabolomics were applied. Lipidomic analysis was performed using ultra performance liquid chromatography coupled to electrospray ionization MS and the other metabolites, including sterols, organic acids, and alcohols, were analyzed by 2-dimensional GC coupled to time-of-flight MS. Altogether, 540 metabolites were profiled. Ribitol (P < 0.001), ribonic acid (P < 0.001), and indoleacetic acid (P < 0.001) increased during the RB consumption period. Ribonic acid correlated positively with tryptophan (r = 0.40; P = 0.003), which is a precursor for the biosynthesis of hunger-depressing serotonin. There were no changes in plasma lipidomic profiles during the RB or WB intervention periods. The results suggest that 8-wk consumption of high-fiber rye bread increases metabolites that might mediate positive effects of rye bread on satiety and weight maintenance.

  15. Cordyceps sinensis protects against liver and heart injuries in a rat model of chronic kidney disease: a metabolomic analysis.

    PubMed

    Liu, Xia; Zhong, Fang; Tang, Xu-long; Lian, Fu-lin; Zhou, Qiao; Guo, Shan-mai; Liu, Jia-fu; Sun, Peng; Hao, Xu; Lu, Ying; Wang, Wei-ming; Chen, Nan; Zhang, Nai-xia

    2014-05-01

    To test the hypothesis that the traditional Chinese medicine Cordyceps sinensis could improve the metabolic function of extrarenal organs to achieve its anti-chronic kidney disease (CKD) effects. Male SD rats were divided into CKD rats (with 5/6-nephrectomy), CKD rats treated with Cordyceps sinensis (4 mg•kg-1•d-1, po), and sham-operated rats. After an 8-week treatment, metabolites were extracted from the hearts and livers of the rats, and then subjected to (1)H-NMR-based metabolomic analysis. Oxidative stress, energy metabolism, amino acid and protein metabolism and choline metabolism were considered as links between CKD and extrarenal organ dysfunction. Within the experimental period of 8 weeks, the metabolic disorders in the liver were more pronounced than in the heart, suggesting that CKD-related extrarenal organ dysfunctions occurred sequentially rather than simultaneously. Oral administration of Cordyceps sinensis exerted statistically significant rescue effects on the liver and heart by reversely regulating levels of those metabolites that are typically perturbed in CKD. Oral administration of Cordyceps sinensis significantly attenuates the liver and heart injuries in CKD rats. The (1)H NMR-based metabolomic approach has provided a systematic view for understanding of CKD and the drug treatment, which can also be used to elucidate the mechanisms of action of other traditional Chinese medicines.

  16. Metabolomic changes during cellular transformation monitored by metabolite-metabolite correlation analysis and correlated with gene expression.

    PubMed

    Madhu, Basetti; Narita, Masako; Jauhiainen, Alexandra; Menon, Suraj; Stubbs, Marion; Tavaré, Simon; Narita, Masashi; Griffiths, John R

    To investigate metabolic changes during cellular transformation, we used a (1)H NMR based metabolite-metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite-metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome.

  17. Getting the right answers: understanding metabolomics challenges.

    PubMed

    Beisken, Stephan; Eiden, Michael; Salek, Reza M

    2015-01-01

    Small molecules within biological systems provide powerful insights into the biological roles, processes and states of organisms. Metabolomics is the study of the concentrations, structures and interactions of these thousands of small molecules, collectively known as the metabolome. Metabolomics is at the interface between chemistry, biology, statistics and computer science, requiring multidisciplinary skillsets. This presents unique challenges for researchers to fully utilize the information produced and to capture its potential diagnostic power. A good understanding of study design, sample preparation, analysis methods and data analysis is essential to get the right answers for the right questions. We outline the current state of the art, benefits and challenges of metabolomics to create an understanding of metabolomics studies from the experimental design to data analysis.

  18. Metabolomic analysis of avocado fruits by GC-APCI-TOF MS: effects of ripening degrees and fruit varieties.

    PubMed

    Hurtado-Fernández, E; Pacchiarotta, T; Mayboroda, O A; Fernández-Gutiérrez, A; Carrasco-Pancorbo, A

    2015-01-01

    In order to investigate avocado fruit ripening, nontargeted GC-APCI-TOF MS metabolic profiling analyses were carried out. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to explore the metabolic profiles from fruit samples of 13 varieties at two different ripening degrees. Mannoheptulose; pentadecylfuran; aspartic, malic, stearic, citric and pantothenic acids; mannitol; and β-sitosterol were some of the metabolites found as more influential for the PLS-DA model. The similarities among genetically related samples (putative mutants of "Hass") and their metabolic differences from the rest of the varieties under study have also been evaluated. The achieved results reveal new insights into avocado fruit composition and metabolite changes, demonstrating therefore the value of metabolomics as a functional genomics tool in characterizing the mechanism of fruit ripening development, a key developmental stage in most economically important fruit crops.

  19. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure

    PubMed Central

    Adkins, Daniel E.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Beardsley, Patrick M.; van den Oord, Edwin J. C. G.

    2012-01-01

    Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10−5, q = 0.013), tryptophan (p = 7.0 × 10−4, q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10−4, q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10−7). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10−4, q = 0.087) and ergothioneine (p = 3.0 × 10−4, q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects. PMID:23554582

  20. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure.

    PubMed

    McClay, Joseph L; Adkins, Daniel E; Vunck, Sarah A; Batman, Angela M; Vann, Robert E; Clark, Shaunna L; Beardsley, Patrick M; van den Oord, Edwin J C G

    2013-04-01

    Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10(-5), q = 0.013), tryptophan (p = 7.0 × 10(-4), q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10(-4), q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10(-7)). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10(-4), q = 0.087) and ergothioneine (p = 3.0 × 10(-4), q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects.

  1. Metabolomics in pneumonia and sepsis: an analysis of the GenIMS cohort study

    PubMed Central

    Yende, Sachin; Scott, Melanie J.; Pribis, John; Mohney, Robert P.; Bell, Lauren N.; Chen, Yi-Fan; Zuckerbraun, Brian S.; Bigbee, William L.; Yealy, Donald M.; Weissfeld, Lisa; Kellum, John A.; Angus, Derek C.

    2014-01-01

    Purpose To determine the global metabolomic profile as measured in circulating plasma from surviving and non-surviving patients with community-acquired pneumonia (CAP) and sepsis. Methods Random, outcome-stratified case–control sample from a prospective study of 1,895 patients hospitalized with CAP and sepsis. Cases (n = 15) were adults who died before 90 days, and controls (n = 15) were adults who survived, matched on demographics, infection type, and procalcitonin. We determined the global metabolomic profile in the first emergency department blood sample using non-targeted mass-spectrometry. We derived metabolite-based prognostic models for 90-day mortality. We determined if metabolites stimulated cytokine production by differentiated Thp1 monocytes in vitro, and validated metabolite profiles in mouse liver and kidney homogenates at 8 h in cecal ligation and puncture (CLP) sepsis. Results We identified 423 small molecules, of which the relative levels of 70 (17 %) were different between survivors and non-survivors (p ≤ 0.05). Broad differences were present in pathways of oxidative stress, bile acid metabolism, and stress response. Metabolite-based prognostic models for 90-day survival performed modestly (AUC = 0.67, 95 % CI 0.48, 0.81). Five nucleic acid metabolites were greater in non-survivors (p ≤ 0.05). Of these, pseudouridine increased monocyte expression of TNFα and IL1β versus control (p < 0.05). Pseudouridine was also increased in liver and kidney homogenates from CLP mice versus sham (p < 0.05 for both). Conclusions Although replication is required, we show the global metabolomic profile in plasma broadly differs between survivors and non-survivors of CAP and sepsis. Metabolite-based prognostic models had modest performance, though metabolites of oxidative stress may act as putative damage-associated molecular patterns. PMID:23673400

  2. Metabolomics in asthma.

    PubMed

    Luxon, Bruce A

    2014-01-01

    Asthma and airway inflammation are responses to infectious stimuli and the mechanisms of how they are mediated, whether by the innate or adaptive immune response systems, are complex and results in a broad spectrum of possible metabolic products. In principle, a syndrome such as asthma should have a characteristic temporal-spatial metabolic signature indicative of its current state and the constituents that caused it. Generally, the term metabolomics refers to the quantitative analysis of sets of small compounds from biological samples with molecular masses less than 1 kDa so unambiguous identification can be difficult and usually requires sophisticated instrumentation. The practical success of clinical metabolomics will largely hinge on a few key issues such as the ability to capture a readily available biofluid that can be analyzed to identify metabolite biomarkers with the required sensitivity and specificity in a cost-effective manner in a clinical setting. In this chapter, we review the current state of the metabolomics of asthma and airway inflammation with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and their future translation into the clinic as diagnostic aids for the choice of patient-specific therapies.

  3. Metabolomic analysis revealed that female mussel Mytilus galloprovincialis was sensitive to bisphenol A exposures.

    PubMed

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

    2014-03-01

    Bisphenol A (BPA) is a synthetic compound used in numerous chemicals, such as polycarbonate plastics and epoxy resins, and it can be released into aquatic environment and poses risk on aquatic organisms. In this work, metabolomics was applied to characterize the metabolic responses in mussel Mytilus galloprovincialis exposed to BPA. Our results indicated that the gonad of female mussel was sensitive to BPA exposures (1 and 10 μg/L) for one month. However, no significant metabolic responses were observed in male mussel gonads exposed to these two concentrations of BPA. Overall, this limited study suggested that the gender differences should be considered in marine ecotoxicology.

  4. How Large Is the Metabolome? A Critical Analysis of Data Exchange Practices in Chemistry

    PubMed Central

    Kind, Tobias; Scholz, Martin; Fiehn, Oliver

    2009-01-01

    Background Calculating the metabolome size of species by genome-guided reconstruction of metabolic pathways misses all products from orphan genes and from enzymes lacking annotated genes. Hence, metabolomes need to be determined experimentally. Annotations by mass spectrometry would greatly benefit if peer-reviewed public databases could be queried to compile target lists of structures that already have been reported for a given species. We detail current obstacles to compile such a knowledge base of metabolites. Results As an example, results are presented for rice. Two rice (oryza sativa) subspecies have been fully sequenced, oryza japonica and oryza indica. Several major small molecule databases were compared for listing known rice metabolites comprising PubChem, Chemical Abstracts, Beilstein, Patent databases, Dictionary of Natural Products, SetupX/BinBase, KNApSAcK DB, and finally those databases which were obtained by computational approaches, i.e. RiceCyc, KEGG, and Reactome. More than 5,000 small molecules were retrieved when searching these databases. Unfortunately, most often, genuine rice metabolites were retrieved together with non-metabolite database entries such as pesticides. Overlaps from database compound lists were very difficult to compare because structures were either not encoded in machine-readable format or because compound identifiers were not cross-referenced between databases. Conclusions We conclude that present databases are not capable of comprehensively retrieving all known metabolites. Metabolome lists are yet mostly restricted to genome-reconstructed pathways. We suggest that providers of (bio)chemical databases enrich their database identifiers to PubChem IDs and InChIKeys to enable cross-database queries. In addition, peer-reviewed journal repositories need to mandate submission of structures and spectra in machine readable format to allow automated semantic annotation of articles containing chemical structures. Such changes in

  5. Integrative analysis of transcriptomic and metabolomic profiling of ascites syndrome in broiler chickens induced by low temperature.

    PubMed

    Shi, Shourong; Shen, Yiru; Zhao, Zhenhua; Hou, Zhuocheng; Yang, Ying; Zhou, Huaijun; Zou, Jianmin; Guo, Yuming

    2014-11-01

    Ascites syndrome (AS) still has an unacceptably high incidence rate in both humans and animals although there have been many studies on AS. To continue our previous pathological and biochemical investigation on the underlying mechanisms of AS incidence in broiler chickens, cutting-edge technologies including RNA-seq and metabolimics were used by directly comparing AS chickens and healthy controls. The RNA-seq analysis in the liver identified 390 differentially expressed genes (DEGs), among which 212 genes were up-regulated and 178 genes were down-regulated in the AS group compared to the control. For the down-regulated DEGs, further gene ontology (GO) analysis suggested that lipid metabolism, cell differentiation, enzyme linked receptor protein signaling pathway and steroid biosynthesis pathway were significantly enriched. For up-regulated DEGs, the cholesterol metabolic process has the lowest p value (0.000966) of fold enrichment while the cholesterol biosynthetic process has the highest fold enrichment (46.67). The metabolomic analysis of serum revealed statistically significant changes in the concentrations of LysoPC(20 : 4), LysoPC(16 : 0), LysoPC(18 : 0), LysoPC(18 : 1), LysoPC(18 : 2), PC(14 : 1/20 : 1), PC(20 : 4/18 : 0), PC(14 : 1/22 : 1), dihydroxyacetone, indoleacrylic acid, ursodeoxycholic acid, l-valine, and l-tryptophan. The integrative analysis of transcriptome and metabolome indicated that two biological pathways of tryptophan biosynthesis and metabolism, and glycerophospholipid metabolism may contribute to the induction of AS in broilers. These findings have provided novel insights into our understanding of molecular mechanisms of AS incidence in broilers.

  6. Metabolomics in plant environmental physiology.

    PubMed

    Brunetti, Cecilia; George, Rachel M; Tattini, Massimiliano; Field, Katie; Davey, Matthew P

    2013-10-01

    Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants. When study is in reference to analysing samples that are relevant to environmental or ecologically based hypotheses, it is termed 'environmental metabolomics'. The emergence of environmental metabolomics as one of the latest of the omics technologies has been one of the most critically important recent developments in plant physiology. Its applications broach the entire landscape of plant ecology, from the understanding of plant plasticity and adaptation through to community composition and even genetic modification in crops. The multitude of novel studies published utilizing metabolomics methods employ a variety of techniques, from the initial stages of tissue sampling, through to sample preservation, transportation, and analysis. This review introduces the concept and applications of plant environmental metabolomics as an ecologically important investigative tool. It examines the main techniques used in situ within field sites, with particular reference to sampling and processing, and those more appropriate for use in laboratory-based settings with emphasis on secondary metabolite analysis.

  7. In-source fragmentation and correlation analysis as tools for metabolite identification exemplified with CE-TOF untargeted metabolomics.

    PubMed

    Godzien, Joanna; Armitage, Emily G; Angulo, Santiago; Martinez-Alcazar, Mari Paz; Alonso-Herranz, Vanesa; Otero, Abraham; Lopez-Gonzalvez, Angeles; Barbas, Coral

    2015-03-09

    The role of non-targeted metabolomics with its discovery power is constantly growing in many different fields of science. However, its biggest advantage of uncovering the unexpected is turning into one of its biggest bottlenecks, particularly in metabolite identification. Among different methods for metabolite identification or ID confirmation, tandem MS analysis plays a very important role. However, this method is limited to only certain types of MS analysers, making for example TOF-MS inaccessible for this type of metabolite identification. To overcome this, in-source fragmentation has been used to fragment molecules and obtain product ions. Since the molecule of interest is not isolated prior to its fragmentation, the acquired spectrum contains many different signals arising from the fragmentation of all compounds present in the sample. Therefore, to assign product ions to their precursors, a novel use of correlation analysis was tested with r ≥0.9 as an assignation of a product ion belonging to the precursor. This method and chosen cut-off was tested on three different sample complexity levels: conducting the analysis on a single standard, mix of co-eluting standards and on a plasma sample. Obtained results clearly proved the effectiveness of the proposed methodology for metabolite ID confirmation. Moreover, the proposed strategy can be successfully applied for semi-quantification of co-eluting molecules with the same monoisotopic mass but that differ in fragmentation pattern. The proposed methodology can greatly improve the robustness and throughput of identification in metabolomics studies by use of TOF-MS, which is crucial to obtain meaningful and trustful results. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Cholestasis and Intervention Effect of Paeonia lactiflora Pall.

    PubMed Central

    Ma, Xiao; Chi, Yong-Hui; Niu, Ming; Zhu, Yun; Zhao, Yan-Ling; Chen, Zhe; Wang, Jia-Bo; Zhang, Cong-En; Li, Jian-Yu; Wang, Li-Fu; Gong, Man; Wei, Shi-Zhang; Chen, Chang; Zhang, Lu; Wu, Ming-Quan; Xiao, Xiao-He

    2016-01-01

    Background: The dried root of Paeonia lactiflora Pall. (PLP) is a classical Chinese herbal medicine that has been used to treat hepatic disease for 1000s of years. Our previous work suggested that PLP can be used to treat hepatitis with severe cholestasis. This study explored the mechanism by which PLP affects ANIT-induced cholestasis in rats using a metabolomics approach. Methods: The effects of PLP on serum indices (TBIL, DBIL, AST, ALT, ALP, and TBA) and the histopathology of the liver were analyzed. Moreover, UHPLC-Q-TOF was performed to identify the possible effect of PLP on metabolites. The pathway analysis was conducted to illustrate the pathways and network by which PLP treats cholestasis. Result: High-dose PLP remarkably down-regulated the serum indices and alleviated histological damage to the liver. Metabolomics analyses showed that the therapeutic effect of high-dose PLP is mainly associated with the regulation of several metabolites, such as glycocholic acid, taurocholic acid, glycochenodeoxycholic acid, L(D)-arginine, and L-tryptophan. A pathway analysis showed that the metabolites were related to bile acid secretion and amino acid metabolism. In addition, the significant changes in bile acid transporters also indicated that bile acid metabolism might be involved in the therapeutic effect of PLP on cholestasis. Moreover, a principal component analysis indicated that the metabolites in the high-dose PLP group were closer to those of the control, whereas those of the moderate dose or low-dose PLP group were closer to those of the ANIT group. This finding indicated that metabolites may be responsible for the differences between the effects of low-dose and moderate-dose PLP. Conclusion: The therapeutic effect of high-dose PLP on cholestasis is possibly related to regulation of bile acid secretion and amino acid metabolism. Moreover, these findings may help better understand the mechanisms of disease and provide a potential therapy for cholestasis. PMID

  9. Normalization to specific gravity prior to analysis improves information recovery from high resolution mass spectrometry metabolomic profiles of human urine.

    PubMed

    Edmands, William M B; Ferrari, Pietro; Scalbert, Augustin

    2014-11-04

    Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets.

  10. A longitudinal analysis of the effects of age on the blood plasma metabolome in the common marmoset, Callithrix jacchus.

    PubMed

    Hoffman, Jessica M; Tran, ViLinh; Wachtman, Lynn M; Green, Cara L; Jones, Dean P; Promislow, Daniel E L

    2016-04-01

    Primates tend to be long-lived for their size with humans being the longest lived of all primates. There are compelling reasons to understand the underlying age-related processes that shape human lifespan. But the very fact of our long lifespan that makes it so compelling, also makes it especially difficult to study. Thus, in studies of aging, researchers have turned to non-human primate models, including chimpanzees, baboons, and rhesus macaques. More recently, the common marmoset, Callithrix jacchus, has been recognized as a particularly valuable model in studies of aging, given its small size, ease of housing in captivity, and relatively short lifespan. However, little is known about the physiological changes that occur as marmosets age. To begin to fill in this gap, we utilized high sensitivity metabolomics to define the longitudinal biochemical changes associated with age in the common marmoset. We measured 2104 metabolites from blood plasma at three separate time points over a 17-month period, and we completed both a cross-sectional and longitudinal analysis of the metabolome. We discovered hundreds of metabolites associated with age and body weight in both male and female animals. Our longitudinal analysis identified age-associated metabolic pathways that were not found in our cross-sectional analysis. Pathways enriched for age-associated metabolites included tryptophan, nucleotide, and xenobiotic metabolism, suggesting these biochemical pathways might play an important role in the basic mechanisms of aging in primates. Moreover, we found that many metabolic pathways associated with age were sex specific. Our work illustrates the power of longitudinal approaches, even in a short time frame, to discover novel biochemical changes that occur with age.

  11. Exploring the mode of action of dithranol therapy for psoriasis: a metabolomic analysis using HaCaT cells.

    PubMed

    Hollywood, Katherine A; Winder, Catherine L; Dunn, Warwick B; Xu, Yun; Broadhurst, David; Griffiths, Christopher E M; Goodacre, Royston

    2015-08-01

    Psoriasis is a common, immune-mediated inflammatory skin disease characterized by red, heavily scaled plaques. The disease affects over one million people in the UK and causes significant physical, psychological and societal impact. There is limited understanding regarding the exact pathogenesis of the disease although it is believed to be a consequence of genetic predisposition and environmental triggers. Treatments vary from topical therapies, such as dithranol, for disease of limited extent (<5% body surface area) to the new immune-targeted biologic therapies for severe psoriasis. Dithranol (also known as anthralin) is a topical therapy for psoriasis believed to work by inhibiting keratinocyte proliferation. To date there have been no metabolomic-based investigations into psoriasis. The HaCaT cell line is a model system for the epidermal keratinocyte proliferation characteristic of psoriasis and was thus chosen for study. Dithranol was applied at therapeutically relevant doses to HaCaT cells. Following the optimisation of enzyme inactivation and metabolite extraction, gas chromatography-mass spectrometry was employed for metabolomics as this addresses central metabolism. Cells were challenged with 0-0.5 μg mL(-1) in 0.1 μg mL(-1) steps and this quantitative perturbation generated data that were highly amenable to correlation analysis. Thus, we used a combination of traditional principal components analysis, hierarchical cluster analysis, along with correlation networks. All methods highlighted distinct metabolite groups, which had different metabolite trajectories with respect to drug concentration and the interpretation of these data established that cellular metabolism had been altered significantly and provided further clarification of the proposed mechanism of action of the drug.

  12. Integrated analysis of transcriptome and metabolome of Arabidopsis albino or pale green mutants with disrupted nuclear-encoded chloroplast proteins.

    PubMed

    Satou, Masakazu; Enoki, Harumi; Oikawa, Akira; Ohta, Daisaku; Saito, Kazunori; Hachiya, Takushi; Sakakibara, Hitoshi; Kusano, Miyako; Fukushima, Atsushi; Saito, Kazuki; Kobayashi, Masatomo; Nagata, Noriko; Myouga, Fumiyoshi; Shinozaki, Kazuo; Motohashi, Reiko

    2014-07-01

    We used four mutants having albino or pale green phenotypes with disrupted nuclear-encoded chloroplast proteins to analyze the regulatory system of metabolites in chloroplast. We performed an integrated analyses of transcriptomes and metabolomes of the four mutants. Transcriptome analysis was carried out using the Agilent Arabidopsis 2 Oligo Microarray, and metabolome analysis with two mass spectrometers; a direct-infusion Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR/MS) and a gas chromatograph-time of flight mass spectrometer. Among approximately 200 known metabolites detected by the FT-ICR/MS, 71 metabolites showed significant changes in the mutants when compared with controls (Ds donor plants). Significant accumulation of several amino acids (glutamine, glutamate and asparagine) was observed in the albino and pale green mutants. Transcriptome analysis revealed altered expressions of genes in several metabolic pathways. For example, genes involved in the tricarboxylic acid cycle, the oxidative pentose phosphate pathway, and the de novo purine nucleotide biosynthetic pathway were up-regulated. These results suggest that nitrogen assimilation is constitutively promoted in the albino and pale green mutants. The accumulation of ammonium ions in the albino and pale green mutants was consistently higher than in Ds donor lines. Furthermore, genes related to pyridoxin accumulation and the de novo purine nucleotide biosynthetic pathway were up-regulated, which may have occurred as a result of the accumulation of glutamine in the albino and pale green mutants. The difference in metabolic profiles seems to be correlated with the disruption of chloroplast internal membrane structures in the mutants. In albino mutants, the alteration of metabolites accumulation and genes expression is stronger than pale green mutants.

  13. Analysis of metabolomics datasets with high-performance computing and metabolite atlases

    SciTech Connect

    Yao, Yushu; Sun, Terence; Wang, Tony; Ruebel, Oliver; Northen, Trent; Bowen, Benjamin P.

    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 for 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.

  14. Metabolomics: a second-generation platform for crop and food analysis.

    PubMed

    Shepherd, Louise Vt; Fraser, Paul; Stewart, Derek

    2011-05-01

    The combined factors of financial and food security, a rapidly increasing population and the associated requirement for food generated sustainably in a changing environment have brought food swiftly to the top of most government agendas. The consequence of this is that we need to produce more food at an equivalent or higher quality with lower inputs. These aims are achievable using conventional breeding, but not in the required timelines, and thus state-of-the-art genetic and analytical technologies are coming to the forefront. The concept of metabolomics, underpinned by mainstream (GC-MS, LC-MS, NMR) and specialist (MALDI-TOF-MS) analytical technologies addressing broad chemical (class) targets and dynamic ranges, offers significant potential to add significant value to crop and food science and deliver on future food demands. Metabolomics has now found a home in the food analytical toolbox with raw material quality and safety the major quality areas, although, as we will show, it is translating beyond this into food storage, shelf-life and post-harvest processing.

  15. 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

  16. Metabolomic analysis and signatures in motor neuron disease†,††

    PubMed Central

    Rozen, Steve; Cudkowicz, Merit E.; Bogdanov, Mikhail; Matson, Wayne R.; Kristal, Bruce S.; Beecher, Chris; Harrison, Scott; Vouros, Paul; Flarakos, Jimmy; Vigneau-Callahan, Karen; Matson, Theodore D.; Newhall, Kristyn M.; Beal, M. Flint; Brown, Robert H.; Kaddurah-Daouk, Rima

    2008-01-01

    Motor neuron diseases (MND) are a heterogeneous group of disorders that includes amyotrophic lateral sclerosis (ALS) and result in death of motor neurons. These diseases may produce characteristic perturbations of the metabolome, the collection of small-molecules (metabolites) present in a cell, tissue, or organism. To test this hypothesis, we used high performance liquid chromatography followed by electrochemical detection to profile blood plasma from 28 patients with MND and 30 healthy controls. Of 317 metabolites, 50 were elevated in MNDpatients and more than 70 were decreased (p < 0.05). Among the compounds elevated, 12 were associated with the drug Riluzole. In a subsequent study of 19 subjects with MND who were not taking Riluzole and 33 healthy control subjects, six compounds were significantly elevated in MND, while the number of compounds with decreased concentration was similar to study 1. Our data also revealed a distinctive signature of highly correlated metabolites in a set of four patients, three of whom had lower motor neuron (LMN) disease. In both datasets we were able to separate MND patients from controls using multivariate regression techniques. These results suggest that metabolomic studies can be used to ascertain metabolic signatures of disease in a non-invasive fashion. Elucidation of the structures of signature molecules in ALS and other forms of MND should provide insight into aberrant biochemical pathways and may provide diagnostic markers and targets for drug design. PMID:18820733

  17. Analysis of the metabolome of Anopheles gambiae mosquito after exposure to Mycobacterium ulcerans

    PubMed Central

    Hoxmeier, J. Charles; Thompson, Brice D.; Broeckling, Corey D.; Small, Pamela; Foy, Brian D.; Prenni, Jessica; Dobos, Karen M.

    2015-01-01

    Infection with Mycobacterium ulcerans causes Buruli Ulcer, a neglected tropical disease. Mosquito vectors are suspected to participate in the transmission and environmental maintenance of the bacterium. However, mechanisms and consequences of mosquito contamination by M. ulcerans are not well understood. We evaluated the metabolome of the Anopheles gambiae mosquito to profile the metabolic changes associated with bacterial colonization. Contamination of mosquitoes with live M. ulcerans bacilli results in disruptions to lipid metabolic pathways of the mosquito, specifically the utilization of glycerolipid molecules, an affect that was not observed in mosquitoes exposed to dead M. ulcerans. These results are consistent with aberrations of lipid metabolism described in other mycobacterial infections, implying global host-pathogen interactions shared across diverse saprophytic and pathogenic mycobacterial species. This study implicates features of the bacterium, such as the putative M. ulcerans encoded phospholipase enzyme, which promote virulence, survival, and active adaptation in concert with mosquito development, and provides significant groundwork for enhanced studies of the vector-pathogen interactions using metabolomics profiling. Lastly, metabolic and survival data suggest an interaction which is unlikely to contribute to transmission of M. ulcerans by A. gambiae and more likely to contribute to persistence of M. ulcerans in waters cohabitated by both organisms. PMID:25784490

  18. Systematic analysis of the polyphenol metabolome using the Phenol‐Explorer database

    PubMed Central

    Rothwell, Joseph A.; Urpi‐Sarda, Mireia; Boto‐Ordoñez, Maria; Llorach, Rafael; Farran‐Codina, Andreu; Barupal, Dinesh Kumar; Neveu, Vanessa; Manach, Claudine; Andres‐Lacueva, Cristina

    2016-01-01

    Scope The Phenol‐Explorer web database details 383 polyphenol metabolites identified in human and animal biofluids from 221 publications. Here, we exploit these data to characterize and visualize the polyphenol metabolome, the set of all metabolites derived from phenolic food components. Methods and results Qualitative and quantitative data on 383 polyphenol metabolites as described in 424 human and animal intervention studies were systematically analyzed. Of these metabolites, 301 were identified without prior enzymatic hydrolysis of biofluids, and included glucuronide and sulfate esters, glycosides, aglycones, and O‐methyl ethers. Around one‐third of these compounds are also known as food constituents and corresponded to polyphenols absorbed without further metabolism. Many ring‐cleavage metabolites formed by gut microbiota were noted, mostly derived from hydroxycinnamates, flavanols, and flavonols. Median maximum plasma concentrations (C max) of all human metabolites were 0.09 and 0.32 μM when consumed from foods or dietary supplements, respectively. Median time to reach maximum plasma concentration in humans (T max) was 2.18 h. Conclusion These data show the complexity of the polyphenol metabolome and the need to take into account biotransformations to understand in vivo bioactivities and the role of dietary polyphenols in health and disease. PMID:26310602

  19. Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum

    PubMed Central

    Faijes, Magda; Mars, Astrid E; Smid, Eddy J

    2007-01-01

    Background A reliable quenching and metabolite extraction method has been developed for Lactobacillus plantarum. The energy charge value was used as a critical indicator for fixation of metabolism. Results Four different aqueous quenching solutions, all containing 60% of methanol, were compared for their efficiency. Only the solutions containing either 70 mM HEPES or 0.85% (w/v) ammonium carbonate (pH 5.5) caused less than 10% cell leakage and the energy charge of the quenched cells was high, indicating rapid inactivation of the metabolism. The efficiency of extraction of intracellular metabolites from cell cultures depends on the extraction methods, and is expected to vary between micro-organisms. For L. plantarum, we have compared five different extraction methodologies based on (i) cold methanol, (ii) perchloric acid, (iii) boiling ethanol, (iv) chloroform/methanol (1:1) and (v) chloroform/water (1:1). Quantification of representative intracellular metabolites showed that the best extraction efficiencies were achieved with cold methanol, boiling ethanol and perchloric acid. Conclusion The ammonium carbonate solution was selected as the most suitable quenching buffer for metabolomics studies in L. plantarum because (i) leakage is minimal, (ii) the energy charge indicates good fixation of metabolism, and (iii) all components are easily removed during freeze-drying. A modified procedure based on cold methanol extraction combined good extractability with mild extraction conditions and high enzymatic inactivation. These features make the combination of these quenching and extraction protocols very suitable for metabolomics studies with L. plantarum. PMID:17708760

  20. Analysis of Metabolomics Datasets with High-Performance Computing and Metabolite Atlases

    PubMed Central

    Yao, Yushu; Sun, Terence; Wang, Tony; Ruebel, Oliver; Northen, Trent; Bowen, Benjamin P.

    2015-01-01

    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 for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. 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. PMID:26287255

  1. Comparative Analysis of Compatibility Effects on Invigorating Blood Circulation for Cyperi Rhizoma Series of Herb Pairs Using Untargeted Metabolomics

    PubMed Central

    Liu, Pei; Shang, Er-Xin; Zhu, Yue; Yu, Jin-Gao; Qian, Da-Wei; Duan, Jin-Ao

    2017-01-01

    The mutual-assistance compatibility of Cyperi Rhizoma (Xiangfu, XF) and Angelicae Sinensis Radix (Danggui, DG), Chuanxiong Rhizoma (Chuanxiong, CX), Paeoniae Radix Alba (Baishao, BS), or Corydalis Rhizoma (Yanhusuo, YH), found in a traditional Chinese medicine (TCM) named Xiang-Fu-Si-Wu Decoction (XFSWD), can produce synergistic and promoting blood effects. Nowadays, XFSWD has been proved to be effective in activating blood circulation and dissipating blood stasis. However, the role of the herb pairs synergistic effects in the formula were poorly understood. In order to quantitatively assess the compatibility effects of herb pairs, mass spectrometry-based untargeted metabolomics studies were performed. The plasma and urine metabolic profiles of acute blood stasis rats induced by adrenaline hydrochloride and ice water and administered with Cyperi Rhizoma—Angelicae Sinensis Radix (XD), Cyperi Rhizoma—Chuanxiong Rhizoma (XC), Cyperi Rhizoma—Paeoniae Radix Alba (XB), Cyperi Rhizoma—Corydalis Rhizoma (XY) were compared. Relative peak area of identified metabolites was calculated and principal component analysis (PCA) score plot from the potential markers was used to visualize the overall differences. Then, the metabolites results were used with biochemistry indicators and genes expression values as parameters to quantitatively evaluate the compatibility effects of XF series of herb pairs by PCA and correlation analysis. The collective results indicated that the four XF herb pairs regulated glycerophospholipid metabolism, steroid hormone biosynthesis and arachidonic acid metabolism pathway. XD was more prominent in regulating the blood stasis during the four XF herb pairs. This study demonstrated that metabolomics was a useful tool to efficacy evaluation and compatibility effects of TCM elucidation. PMID:29018346

  2. Dietary intake and plasma metabolomic analysis of polyunsaturated fatty acids in bipolar subjects reveal dysregulation of linoleic acid metabolism.

    PubMed

    Evans, Simon J; Ringrose, Rachel N; Harrington, Gloria J; Mancuso, Peter; Burant, Charles F; McInnis, Melvin G

    2014-10-01

    Polyunsaturated fatty acids (PUFA) profiles associate with risk for mood disorders. This poses the hypothesis of metabolic differences between patients and unaffected healthy controls that relate to the primary illness or are secondary to medication use or dietary intake. However, dietary manipulation or supplementation studies show equivocal results improving mental health outcomes. This study investigates dietary patterns and metabolic profiles relevant to PUFA metabolism, in bipolar I individuals compared to non-psychiatric controls. We collected seven-day diet records and performed metabolomic analysis of fasted plasma collected immediately after diet recording. Regression analyses adjusted for age, gender and energy intake found that bipolar individuals had significantly lower intake of selenium and PUFAs, including eicosapentaenoic acid (EPA) (n-3), docosahexaenoic acid (DHA) (n-3), arachidonic acid (AA) (n-6) and docosapentaenoic acid (DPA) (n-3/n-6 mix); and significantly increased intake of the saturated fats, eicosanoic and docosanoic acid. Regression analysis of metabolomic data derived from plasma samples, correcting for age, gender, BMI, psychiatric medication use and dietary PUFA intake, revealed that bipolar individuals had reduced 13S-HpODE, a major peroxidation product of the n-6, linoleic acid (LA), reduced eicosadienoic acid (EDA), an elongation product of LA; reduced prostaglandins G2, F2 alpha and E1, synthesized from n-6 PUFA; and reduced EPA. These observations remained significant or near significant after Bonferroni correction and are consistent with metabolic variances between bipolar and control individuals with regard to PUFA metabolism. These findings suggest that specific dietary interventions aimed towards correcting these metabolic disparities may impact health outcomes for individuals with bipolar disorder.

  3. 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

  4. 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

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

    PubMed

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

    2014-11-01

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

  6. 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

  7. Metabolomics Analysis To Evaluate the Anti-Inflammatory Effects of Polyphenols: Glabridin Reversed Metabolism Change Caused by LPS in RAW 264.7 Cells.

    PubMed

    Liu, Kaiqin; Pi, Fuwei; Zhang, Hongxia; Ji, Jian; Xia, Shuang; Cui, Fangchao; Sun, Jiadi; Sun, Xiulan

    2017-07-26

    Inflammation has been shown to play a critical role in the development of many diseases. In this study, we used metabolomics to evaluate the inflammatory effect of lipopolysaccharide (LPS) and the anti-inflammatory effect of glabridin (GB, a polyphenol from Glycurrhiza glabra L. roots) in RAW 264.7 cells. Multivariate statistical analysis showed that in comparison with the LPS group, the metabolic profile of the GB group was more similar to that of the control group. LPS impacted the amino acid, energy, and lipid metabolisms in RAW 264.7 cells, and metabolic pathway analysis showed that GB reversed some of those LPS impacts. Metabolomics analysis provided us with a new perspective to better understand the inflammatory response and the anti-inflammatory effects of GB. Metabolic pathway analysis can be an effective tool to elucidate the mechanism of inflammation and to potentially find new anti-inflammatory agents.

  8. Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms

    SciTech Connect

    Kim, Young-Mo; Nowack, Shane; Olsen, Millie; Becraft, Eric; Wood, Jason M.; Thiel, Vera; Klapper, Isaac; Kuhl, Michael; Fredrickson, Jim K.; Bryant, Donald A.; Ward, David M.; Metz, Thomas O.

    2015-04-17

    Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptative and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabiting this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g. glycolate) and fermentation (e.g. acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gases (e.g. H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: 1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; 2) Synechococcus spp. produce CH4 via metabolism of phosphonates, and photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; 3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and 4) fluctuations in many metabolite pools (e.g. wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their

  9. Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms

    DOE PAGES

    Kim, Young-Mo; Nowack, Shane; Olsen, Millie; ...

    2015-04-17

    Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptative and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number ofmore » predominant taxa inhabiting this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g. glycolate) and fermentation (e.g. acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gases (e.g. H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: 1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; 2) Synechococcus spp. produce CH4 via metabolism of phosphonates, and photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; 3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and 4) fluctuations in many metabolite pools (e.g. wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences

  10. Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships.

    PubMed

    McHardy, Ian H; Goudarzi, Maryam; Tong, Maomeng; Ruegger, Paul M; Schwager, Emma; Weger, John R; Graeber, Thomas G; Sonnenburg, Justin L; Horvath, Steve; Huttenhower, Curtis; McGovern, Dermot Pb; Fornace, Albert J; Borneman, James; Braun, Jonathan

    2013-06-05

    Consistent compositional shifts in the gut microbiota are observed in IBD and other chronic intestinal disorders and may contribute to pathogenesis. The identities of microbial biomolecular mechanisms and metabolic products responsible for disease phenotypes remain to be determined, as do the means by which such microbial functions may be therapeutically modified. The composition of the microbiota and metabolites in gut microbiome samples in 47 subjects were determined. Samples were obtained by endoscopic mucosal lavage from the cecum and sigmoid colon regions, and each sample was sequenced using the 16S rRNA gene V4 region (Illumina-HiSeq 2000 platform) and assessed by UPLC mass spectroscopy. Spearman correlations were used to identify widespread, statistically significant microbial-metabolite relationships. Metagenomes for identified microbial OTUs were imputed using PICRUSt, and KEGG metabolic pathway modules for imputed genes were assigned using HUMAnN. The resulting metabolic pathway abundances were mostly concordant with metabolite data. Analysis of the metabolome-driven distribution of OTU phylogeny and function revealed clusters of clades that were both metabolically and metagenomically similar. The results suggest that microbes are syntropic with mucosal metabolome composition and therefore may be the source of and/or dependent upon gut epithelial metabolites. The consistent relationship between inferred metagenomic function and assayed metabolites suggests that metagenomic composition is predictive to a reasonable degree of microbial community metabolite pools. The finding that certain metabolites strongly correlate with microbial community structure raises the possibility of targeting metabolites for monitoring and/or therapeutically manipulating microbial community function in IBD and other chronic diseases.

  11. An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection

    PubMed Central

    Antharam, Vijay C.; McEwen, Daniel C.; Garrett, Timothy J.; Dossey, Aaron T.; Li, Eric C.; Kozlov, Andrew N.; Mesbah, Zhubene; Wang, Gary P.

    2016-01-01

    Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism. PMID:26871580

  12. Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships

    PubMed Central

    2013-01-01

    Background Consistent compositional shifts in the gut microbiota are observed in IBD and other chronic intestinal disorders and may contribute to pathogenesis. The identities of microbial biomolecular mechanisms and metabolic products responsible for disease phenotypes remain to be determined, as do the means by which such microbial functions may be therapeutically modified. Results The composition of the microbiota and metabolites in gut microbiome samples in 47 subjects were determined. Samples were obtained by endoscopic mucosal lavage from the cecum and sigmoid colon regions, and each sample was sequenced using the 16S rRNA gene V4 region (Illumina-HiSeq 2000 platform) and assessed by UPLC mass spectroscopy. Spearman correlations were used to identify widespread, statistically significant microbial-metabolite relationships. Metagenomes for identified microbial OTUs were imputed using PICRUSt, and KEGG metabolic pathway modules for imputed genes were assigned using HUMAnN. The resulting metabolic pathway abundances were mostly concordant with metabolite data. Analysis of the metabolome-driven distribution of OTU phylogeny and function revealed clusters of clades that were both metabolically and metagenomically similar. Conclusions The results suggest that microbes are syntropic with mucosal metabolome composition and therefore may be the source of and/or dependent upon gut epithelial metabolites. The consistent relationship between inferred metagenomic function and assayed metabolites suggests that metagenomic composition is predictive to a reasonable degree of microbial community metabolite pools. The finding that certain metabolites strongly correlate with microbial community structure raises the possibility of targeting metabolites for monitoring and/or therapeutically manipulating microbial community function in IBD and other chronic diseases. PMID:24450808

  13. Quantitative Metabolomic Analysis of Urinary Citrulline and Calcitroic Acid in Mice after Exposure to Various Types of Ionizing Radiation

    PubMed Central

    Goudarzi, Maryam; Chauthe, Siddheshwar; Strawn, Steven J.; Weber, Waylon M.; Brenner, David J.; Fornace, Albert J.

    2016-01-01

    With the safety of existing nuclear power plants being brought into question after the Fukushima disaster and the increased level of concern over terrorism-sponsored use of improvised nuclear devices, it is more crucial to develop well-defined radiation injury markers in easily accessible biofluids to help emergency-responders with injury assessment during patient triage. Here, we focused on utilizing ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to identify and quantitate the unique changes in the urinary excretion of two metabolite markers, calcitroic acid and citrulline, in mice induced by different forms of irradiation; X-ray irradiation at a low dose rate (LDR) of 3.0 mGy/min and a high dose rate (HDR) of 1.1 Gy/min, and internal exposure to Cesium-137 (137Cs) and Strontium-90 (90Sr). The multiple reaction monitoring analysis showed that, while exposure to 137Cs and 90Sr induced a statistically significant and persistent decrease, similar doses of X-ray beam at the HDR had the opposite effect, and the LDR had no effect on the urinary levels of these two metabolites. This suggests that the source of exposure and the dose rate strongly modulate the in vivo metabolomic injury responses, which may have utility in clinical biodosimetry assays for the assessment of exposure in an affected population. This study complements our previous investigations into the metabolomic profile of urine from mice internally exposed to 90Sr and 137Cs and to X-ray beam radiation. PMID:27213362

  14. Current breathomics--a review on data pre-processing techniques and machine learning in metabolomics breath analysis.

    PubMed

    Smolinska, A; Hauschild, A-Ch; Fijten, R R R; Dallinga, J W; Baumbach, J; van Schooten, F J

    2014-06-01

    We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.

  15. Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms.

    PubMed

    Kim, Young-Mo; Nowack, Shane; Olsen, Millie T; Becraft, Eric D; Wood, Jason M; Thiel, Vera; Klapper, Isaac; Kühl, Michael; Fredrickson, James K; Bryant, Donald A; Ward, David M; Metz, Thomas O

    2015-01-01

    Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptive and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabit this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms, and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g., glycolate) and fermentation (e.g., acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gasses (e.g., H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: (1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; (2) photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; (3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and (4) fluctuations in many metabolite pools (e.g., wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.

  16. An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection.

    PubMed

    Antharam, Vijay C; McEwen, Daniel C; Garrett, Timothy J; Dossey, Aaron T; Li, Eric C; Kozlov, Andrew N; Mesbah, Zhubene; Wang, Gary P

    2016-01-01

    Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.

  17. Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms

    PubMed Central

    Kim, Young-Mo; Nowack, Shane; Olsen, Millie T.; Becraft, Eric D.; Wood, Jason M.; Thiel, Vera; Klapper, Isaac; Kühl, Michael; Fredrickson, James K.; Bryant, Donald A.; Ward, David M.; Metz, Thomas O.

    2015-01-01

    Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptive and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabit this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms, and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g., glycolate) and fermentation (e.g., acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gasses (e.g., H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: (1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; (2) photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; (3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and (4) fluctuations in many metabolite pools (e.g., wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches. PMID:25941514

  18. NMR-Based Metabolomic Analysis of Huanglongbing-Asymptomatic and -Symptomatic Citrus Trees.

    PubMed

    Freitas, Deisy dos Santos; Carlos, Eduardo Fermino; Gil, Márcia Cristina Soares de Souza; Vieira, Luiz Gonzaga Esteves; Alcantara, Glaucia Braz

    2015-09-02

    Huanglongbing (HLB) is one of the most severe diseases that affects citrus trees worldwide and is associated with the yet uncultured bacteria Candidatus Liberibacter spp. To assess the metabolomic differences between HLB-asymptomatic and -symptomatic tissues, extracts from leaf and root samples taken from a uniform 6-year-old commercial orchard of Valencia trees were subjected to nuclear magnetic resonance (NMR) and chemometrics. The results show that the symptomatic trees had higher sucrose content in their leaves and no variation in their roots. In addition, proline betaine and malate were detected in smaller amounts in the HLB-affected symptomatic leaves. The changes in metabolic processes of the plant in response to HLB are corroborated by the relationship between the bacterial levels and the metabolic profiles.

  19. Metabolomics analysis reveals insights into biochemical mechanisms of mental stress-induced left ventricular dysfunction

    PubMed Central

    Boyle, Stephen H.; Matson, Wayne R.; Velazquez, Eric J.; Samad, Zainab; Williams, Redford B.; Sharma, Swati; Thomas, Beena; Wilson, Jennifer L.; O'Connor, Christopher

    2014-01-01

    Mental stress induced left ventricular dysfunction (LVD) has been associated with a greater risk of adverse events in coronary heart disease (CHD) patients independent of conventional risk indicators. The underlying biochemical mechanisms of this cardiovascular condition are poorly understood. Our objective was to use metabolomics technology to identify biochemical changes that co-occur with mental stress-induced LVD in patients with clinically stable CHD. Participants were adult CHD patients who were recruited for mental stress-induced myocardial ischemia screening. For this study, we randomly selected 30 patients representing the extremes of the mental stress-induced left ventricular ejection fraction (LVEF) change distribution; 15 who showed LVD (i.e. LVEF reduction ≥5) and 15 who showed a normal left ventricular response (NLVR; i.e. a LVEF increase of ≥5) to three mental stressors. An electrochemistry based metabolomics platform was used to profile pre- and post-stress serum samples yielding data for 22 known compounds, primarily within the tyrosine, tryptophan, purine and methionine pathways. There were significant stress-induced changes in several compounds. A comparison between the NLVR and LVD groups showed significant effects for kynurenine (p = .036, N-acetylserotonin (p = .054), uric acid (p = .015), tyrosine (p = .019) and a trend for methionine (p = .065); the NLVR group showed a significantly greater stress-induced reduction in all of those compounds compared to the LVD group. Many of these biochemicals have been implicated in other stress-related phenomena and are plausible candidates for mechanisms underlying LVD in response to mental stress. PMID:25983674

  20. Mass-spectrometry-based microbial metabolomics: recent developments and applications.

    PubMed

    Gao, Peng; Xu, Guowang

    2015-01-01

    Metabolomics is an omics technique aiming at qualitatively and quantitatively describing a metabolome by various analytical platforms. It is an indispensable component of modern systems biology. Microbial metabolomics can be roughly classified as metabolic footprint analysis and metabolic fingerprint analysis depending on the analyte origins. Both of them have been beneficial to microbiological research for different reasons. Mass spectrometry and nuclear magnetic resonance spectroscopy techniques are popular analytical strategies prevailing in the metabolomics field. In this review, chromatography-mass-spectrometry-based microbial metabolomic analysis steps are summarized, including sample collection, metabolite extraction, instrument analysis, and data analysis. Moreover, their applications in some representative fields are discussed as examples. The aim of this review is to present briefly recent technical advances in mass-spectrometry-based analysis, and to highlight the value of modern applications of microbial metabolomics.

  1. Metabolomics for salinity research.

    PubMed

    Roessner, Ute; Beckles, Diane M

    2012-01-01

    Soil salinity devastates agriculture. It reduces crop yields and makes arable land unsuitable for later use. Many species have evolved highly efficient strategies to sense, transduce, and build up tolerance to high salinity and even sensitive species have endogenous mechanism for coping with this stress. These underlying physiological and metabolic mechanisms can be unraveled using metabolomics. Here we describe detailed protocols of how to extract polar metabolites for analysis using GC-MS and LC-MS. We also touch briefly on considerations that should be taken into account when designing the experiment and how the resulting data may be analyzed and visualized in a biological context.

  2. Glucose-methanol co-utilization in Pichia pastoris studied by metabolomics and instationary ¹³C flux analysis.

    PubMed

    Jordà, Joel; Suarez, Camilo; Carnicer, Marc; ten Pierick, Angela; Heijnen, Joseph J; van Gulik, Walter; Ferrer, Pau; Albiol, Joan; Wahl, Aljoscha

    2013-02-28

    Several studies have shown that the utilization of mixed carbon feeds instead of methanol as sole carbon source is beneficial for protein production with the methylotrophic yeast Pichia pastoris. In particular, growth under mixed feed conditions appears to alleviate the metabolic burden related to stress responses triggered by protein overproduction and secretion. Yet, detailed analysis of the metabolome and fluxome under mixed carbon source metabolizing conditions are missing. To obtain a detailed flux distribution of central carbon metabolism, including the pentose phosphate pathway under methanol-glucose conditions, we have applied metabolomics and instationary ¹³C flux analysis in chemostat cultivations. Instationary ¹³C-based metabolic flux analysis using GC-MS and LC-MS measurements in time allowed for an accurate mapping of metabolic fluxes of glycolysis, pentose phosphate and methanol assimilation pathways. Compared to previous results from NMR-derived stationary state labelling data (proteinogenic amino acids, METAFoR) more fluxes could be determined with higher accuracy. Furthermore, using a thermodynamic metabolic network analysis the metabolite measurements and metabolic flux directions were validated. Notably, the concentration of several metabolites of the upper glycolysis and pentose phosphate pathway increased under glucose-methanol feeding compared to the reference glucose conditions, indicating a shift in the thermodynamic driving forces. Conversely, the extracellular concentrations of all measured metabolites were lower compared with the corresponding exometabolome of glucose-grown P. pastoris cells.The instationary ¹³C flux analysis resulted in fluxes comparable to previously obtained from NMR datasets of proteinogenic amino acids, but allowed several additional insights. Specifically, i) in vivo metabolic flux estimations were expanded to a larger metabolic network e.g. by including trehalose recycling, which accounted for about 1.5% of

  3. 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...

  4. 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...

  5. NMR metabolomics for soil analysis provide complementary, orthogonal data to MIR and traditional soil chemistry approaches--a land use study.

    PubMed

    Rochfort, Simone; Ezernieks, Vilnis; Mele, Pauline; Kitching, Matt

    2015-09-01

    The present study was designed to analyse soils by different methodologies to determine the range of traits that could be investigated for the study of environmental soil samples. Proton nuclear magnetic resonance spectroscopy ((1) H NMR) was employed for metametabolomic analysis of soils from agricultural systems (managed) or from soils in a native state (remnant). The metabolomic methodologies employed (grinding and extraction with sonication) are capable of breaking up cell walls and so enabled characterisation of both extracellular and intracellular components of soil. Diffuse mid-infrared spectroscopy (MIR) data was obtained for the same sample sets, and in addition, elemental composition was determined by conventional laboratory chemical testing methods. Also investigated was the antibiotic activity of the soil extracts. Resilient or suppressive soils are valued in the agricultural setting as they convey disease resistance (against bacterial and fungal pathogens) to crop plants. In order to test if any such biological activity could be detected in the soils, the extracts were tested against the bacteria Bacillus subtilis. Several extracts showed strong growth inhibition against the bacteria with the most active clustered together in principle component analysis (PCA) of the metabolomic data. The study showed that the NMR metabolomic approach corresponds more accurately to land use and biochemical properties potentially associated with suppression, while MIR data correlated well to inorganic chemical analysis. Thus, the study demonstrates the utility in combining these spectroscopic methods for soil analysis. Copyright © 2015 John Wiley & Sons, Ltd.

  6. 1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil.

    PubMed

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

    2013-08-27

    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.

  7. 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

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

    PubMed

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

    2015-07-31

    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.

  9. 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

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

    PubMed

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

    2013-08-06

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

  11. Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

    PubMed Central

    Hruby, Adela; Toledo, Estefanía; Clish, Clary B.; Martínez-González, Miguel A.

    2016-01-01

    OBJECTIVE To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24–1.48]; I2 = 9.5%), 36% for leucine (1.36 [1.17–1.58]; I2 = 37.4%), 35% for valine (1.35 [1.19–1.53]; I2 = 45.8%), 36% for tyrosine (1.36 [1.19–1.55]; I2 = 51.6%), and 26% for phenylalanine (1.26 [1.10–1.44]; I2 = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81–0.96] and 0

  12. Quantitative Clinical Diagnostic Analysis of Acetone in Human Blood by HPLC: A Metabolomic Search for Acetone as Indicator

    PubMed Central

    Akgul Kalkan, Esin; Sahiner, Mehtap; Ulker Cakir, Dilek; Alpaslan, Duygu; Yilmaz, Selehattin

    2016-01-01

    Using high-performance liquid chromatography (HPLC) and 2,4-dinitrophenylhydrazine (2,4-DNPH) as a derivatizing reagent, an analytical method was developed for the quantitative determination of acetone in human blood. The determination was carried out at 365 nm using an ultraviolet-visible (UV-Vis) diode array detector (DAD). For acetone as its 2,4-dinitrophenylhydrazone derivative, a good separation was achieved with a ThermoAcclaim C18 column (15 cm × 4.6 mm × 3 μm) at retention time (tR) 12.10 min and flowrate of 1 mL min−1 using a (methanol/acetonitrile) water elution gradient. The methodology is simple, rapid, sensitive, and of low cost, exhibits good reproducibility, and allows the analysis of acetone in biological fluids. A calibration curve was obtained for acetone using its standard solutions in acetonitrile. Quantitative analysis of acetone in human blood was successfully carried out using this calibration graph. The applied method was validated in parameters of linearity, limit of detection and quantification, accuracy, and precision. We also present acetone as a useful tool for the HPLC-based metabolomic investigation of endogenous metabolism and quantitative clinical diagnostic analysis. PMID:27298750

  13. 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

  14. Identification and metabolomic analysis of chemical modulators for lipid accumulation in Crypthecodinium cohnii.

    PubMed

    Li, Jinghan; Niu, Xiangfeng; Pei, Guangsheng; Sui, Xiao; Zhang, Xiaoqing; Chen, Lei; Zhang, Weiwen

    2015-09-01

    In the study, fourteen chemical modulators from five groups (i.e., auxin, gibberellin, cytokinin, signal transducer and amine) were evaluated for their effects on lipid accumulation in Crypthecodinium cohnii. The results showed that naphthoxyacetic acid (BNOA), 2-chlorodracylicacid, salicylic acid (SA), abscisic acid (ABA) and ethanolamine (ETA), increased lipid accumulation in C. cohnii by 10.00-18.78%. In addition, the combined uses of the above chemicals showed that two combinations, 1.0mg/L SA & 152.7 mg/L ETA and 4.0mg/L BNOA & 152.7 mg/L ETA, increased lipid accumulation by 22.45% and 20.54%, respectively. Moreover, a targeted metabolomic approach was employed to decipher the possible mechanisms responsible for the increased lipid accumulation, and the results showed that the enhanced metabolism in glycolysis and TCA cycle as well as the decreased metabolism in PPP pathway could be important for the stimulatory roles of BNOA & ETA and SA & ETA on lipid accumulation in C. cohnii.

  15. H-1 Nuclear Magnetic Resonance Metabolomics Analysis Identifies Novel Urinary Biomarkers for Lung Function

    SciTech Connect

    MCClay, Joseph L.; Adkins, Daniel E.; Isern, Nancy G.; O'Connell, Thomas M.; Wooten, Jan B.; Zedler, Barbara K.; Dasika, Madhukar S.; Webb, B. T.; Webb-Robertson, Bobbie-Jo M.; Pounds, Joel G.; Murrelle, Edward L.; Leppert, Mark F.; van den Oord, Edwin J.

    2010-06-04

    Chronic obstructive pulmonary disease (COPD), characterized by chronic airflow limitation, is a serious and growing public health concern. The major environmental risk factor for COPD is tobacco smoking, but the biological mechanisms underlying COPD are not well understood. In this study, we used proton nuclear magnetic resonance (1H-NMR) spectroscopy to identify and quantify metabolites associated with lung function in COPD. Plasma and urine were collected from 197 adults with COPD and from 195 adults without COPD. Samples were assayed using a 600 MHz NMR spectrometer, and the resulting spectra were analyzed against quantitative spirometric measures of lung function. After correcting for false discoveries and adjusting for covariates (sex, age, smoking) several spectral regions in urine were found to be significantly associated with baseline lung function. These regions correspond to the metabolites trigonelline, hippurate and formate. Concentrations of each metabolite, standardized to urinary creatinine, were associated with baseline lung function (minimum p-value = 0.0002 for trigonelline). No significant associations were found with plasma metabolites. Two of the three urinary metabolites positively associated with baseline lung function, i.e. hippurate and formate, are often related to gut microflora. This suggests that the microbiome composition is variable between individuals with different lung function. Alternatively, the nature and origins of all three associated metabolites may reflect lifestyle differences affecting overall health. Our results will require replication and validation, but demonstrate the utility of NMR metabolomics as a screening tool for identifying novel biomarkers of lung disease or disease risk.

  16. Metabolomic analysis of citrus infection by 'Candidatus Liberibacter' reveals insight into pathogenicity.

    PubMed

    Slisz, Anne M; Breksa, Andrew P; Mishchuk, Darya O; McCollum, Greg; Slupsky, Carolyn M

    2012-08-03

    Huanglongbing (HLB), considered the most serious citrus disease in the world, is associated with the nonculturable bacterium 'Candidatus Liberibacter asiaticus' (Las). Infection of citrus by this pathogen leads to reduced plant vigor and productivity, ultimately resulting in death of the infected tree. It can take up to two years following initial infection before outward symptoms become apparent, making detection difficult. The existing knowledge gap in our understanding of Las and its pathogenesis leading to HLB has stymied development of treatments and methods to mitigate the pathogen's influence. To evaluate the influence of Las on fruit quality in both symptomatic and asymptomatic fruit, and gain further insight into the pathogenesis of the disease, a 1H NMR metabolomics investigation, complemented with physicochemical and analyte-specific analyses, was undertaken. Comparison of the juice obtained from oranges gathered from Las+ (symptomatic and asymptomatic) and Las- (healthy) trees revealed significant differences in the concentrations of sugars, amino and organic acids, limonin glucoside, and limonin. This study demonstrates differing metabolic profiles in the juice of oranges from Las+ and Las- and proposes how Las may be able to evade citrus defense responses.

  17. Metabolomics Analysis Reveals Specific Novel Tetrapeptide and Potential Anti-Inflammatory Metabolites in Pathogenic Aspergillus species

    PubMed Central

    Lee, Kim-Chung; Tam, Emily W. T.; Lo, Ka-Ching; Tsang, Alan K. L.; Lau, Candy C. Y.; To, Kelvin K. W.; Chan, Jasper F. W.; Lam, Ching-Wan; Yuen, Kwok-Yung; Lau, Susanna K. P.; Woo, Patrick C. Y.

    2015-01-01

    Infections related to Aspergillus species have emerged to become an important focus in infectious diseases, as a result of the increasing use of immunosuppressive agents and high fatality associated with invasive aspergillosis. However, laboratory diagnosis of Aspergillus infections remains difficult. In this study, by comparing the metabolomic profiles of the culture supernatants of 30 strains of six pathogenic Aspergillus species (A. fumigatus, A. flavus, A. niger, A. terreus, A. nomius and A. tamarii) and 31 strains of 10 non-Aspergillus fungi, eight compounds present in all strains of the six Aspergillus species but not in any strain of the non-Aspergillus fungi were observed. One of the eight compounds, Leu–Glu–Leu–Glu, is a novel tetrapeptide and represents the first linear tetrapeptide observed in Aspergillus species, which we propose to be named aspergitide. Two other closely related Aspergillus-specific compounds, hydroxy-(sulfooxy)benzoic acid and (sulfooxy)benzoic acid, may possess anti-inflammatory properties, as 2-(sulfooxy)benzoic acid possesses a structure similar to those of aspirin [2-(acetoxy)benzoic acid] and salicylic acid (2-hydroxybenzoic acid). Further studies to examine the potentials of these Aspergillus-specific compounds for laboratory diagnosis of aspergillosis are warranted and further experiments will reveal whether Leu–Glu–Leu–Glu, hydroxy-(sulfooxy)benzoic acid and (sulfooxy)benzoic acid are virulent factors of the pathogenic Aspergillus species. PMID:26090713

  18. Desiccation tolerance in resurrection plants: new insights from transcriptome, proteome and metabolome analysis.

    PubMed

    Dinakar, Challabathula; Bartels, Dorothea

    2013-01-01

    Most higher plants are unable to survive desiccation to an air-dried state. An exception is a small group of vascular angiosperm plants, termed resurrection plants. They have evolved unique mechanisms of desiccation tolerance and thus can tolerate severe water loss, and mostly adjust their water content with the relative humidity in the environment. Desiccation tolerance is a complex phenomenon and depends on the regulated expression of numerous genes during dehydration and subsequent rehydration. Most of the resurrection plants have a large genome and are difficult to transform which makes them unsuitable for genetic approaches. However, technical advances have made it possible to analyze changes in gene expression on a large-scale. These approaches together with comparative studies with non-desiccation tolerant plants provide novel insights into the molecular processes required for desiccation tolerance and will shed light on identification of orphan genes with unknown functions. Here, we review large-scale recent transcriptomic, proteomic, and metabolomic studies that have been performed in desiccation tolerant plants and discuss how these studies contribute to understanding the molecular basis of desiccation tolerance.

  19. Desiccation tolerance in resurrection plants: new insights from transcriptome, proteome and metabolome analysis

    PubMed Central

    Dinakar, Challabathula; Bartels, Dorothea

    2013-01-01

    Most higher plants are unable to survive desiccation to an air-dried state. An exception is a small group of vascular angiosperm plants, termed resurrection plants. They have evolved unique mechanisms of desiccation tolerance and thus can tolerate severe water loss, and mostly adjust their water content with the relative humidity in the environment. Desiccation tolerance is a complex phenomenon and depends on the regulated expression of numerous genes during dehydration and subsequent rehydration. Most of the resurrection plants have a large genome and are difficult to transform which makes them unsuitable for genetic approaches. However, technical advances have made it possible to analyze changes in gene expression on a large-scale. These approaches together with comparative studies with non-desiccation tolerant plants provide novel insights into the molecular processes required for desiccation tolerance and will shed light on identification of orphan genes with unknown functions. Here, we review large-scale recent transcriptomic, proteomic, and metabolomic studies that have been performed in desiccation tolerant plants and discuss how these studies contribute to understanding the molecular basis of desiccation tolerance. PMID:24348488

  20. Integrated metabolomic and proteomic analysis reveals systemic responses of Rubrivivax benzoatilyticus JA2 to aniline stress.

    PubMed

    Mujahid, Md; Prasuna, M Lakshmi; Sasikala, Ch; Ramana, Ch Venkata

    2015-02-06

    Aromatic amines are widely distributed in the environment and are major environmental pollutants. Although degradation of aromatic amines is well studied in bacteria, physiological adaptations and stress response to these toxic compounds is not yet fully understood. In the present study, systemic responses of Rubrivivax benzoatilyticus JA2 to aniline stress were deciphered using metabolite and iTRAQ-labeled protein profiling. Strain JA2 tolerated high concentrations of aniline (30 mM) with trace amounts of aniline being transformed to acetanilide. GC-MS metabolite profiling revealed aniline stress phenotype wherein amino acid, carbohydrate, fatty acid, nitrogen metabolisms, and TCA (tricarboxylic acid cycle) were modulated. Strain JA2 responded to aniline by remodeling the proteome, and cellular functions, such as signaling, transcription, translation, stress tolerance, transport and carbohydrate metabolism, were highly modulated. Key adaptive responses, such as transcription/translational changes, molecular chaperones to control protein folding, and efflux pumps implicated in solvent extrusion, were induced in response to aniline stress. Proteo-metabolomics indicated extensive rewiring of metabolism to aniline. TCA cycle and amino acid catabolism were down-regulated while gluconeogenesis and pentose phosphate pathways were up-regulated, leading to the synthesis of extracellular polymeric substances. Furthermore, increased saturated fatty acid ratios in membranes due to aniline stress suggest membrane adaptation. The present study thus indicates that strain JA2 employs multilayered responses: stress response, toxic compound tolerance, energy conservation, and metabolic rearrangements to aniline.

  1. Metabolomics analysis of TiO2 nanoparticles induced toxicological effects on rice (Oryza sativa L.).

    PubMed

    Wu, Biying; Zhu, Lizhong; Le, X Chris

    2017-11-01

    The wide occurrence and high environmental concentration of titanium dioxide nanoparticles (nano-TiO2) have raised concerns about their potential toxic effects on crops. In this study, we employed a GC-MS-based metabolomic approach to investigate the potential toxicity of nano-TiO2 on hydroponically-cultured rice (Oryza sativa L.) after exposed to 0, 100, 250 or 500 mg/L of nano-TiO2 for fourteen days. Results showed that the biomass of rice was significantly decreased and the antioxidant defense system was significantly disturbed after exposure to nano-TiO2. One hundred and five identified metabolites showed significant difference compared to the control, among which the concentrations of glucose-6-phosphate, glucose-1-phosphate, succinic and isocitric acid were increased most, while the concentrations of sucrose, isomaltulose, and glyoxylic acid were decreased most. Basic energy-generating ways including tricarboxylic acid cycle and the pentose phosphate pathway, were elevated significantly while the carbohydrate synthesis metabolism including starch and sucrose metabolism, and glyoxylate and dicarboxylate metabolism were inhibited. However, the biosynthetic formation of most of the identified fatty acids, amino acids and secondary metabolites which correlated to crop quality, were increased. The results suggest that the metabolism of rice plants is distinctly disturbed after exposure to nano-TiO2, and nano-TiO2 would have a mixed effect on the yield and quality of rice. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Metabolomic analysis indicates a pivotal role of the hepatotoxin microcystin in high light adaptation of Microcystis.

    PubMed

    Meissner, Sven; Steinhauser, Dirk; Dittmann, Elke

    2015-05-01

    Microcystis is a freshwater cyanobacterium frequently forming nuisance blooms in the summer months. The genus belongs to the predominant producers of the potent hepatotoxin microcystin. The success of Microcystis and its remarkable resistance to high light conditions are not well understood. Here, we have compared the metabolic response of Microcystis aeruginosa PCC7806, its microcystin-deficient ΔmcyB mutant (Mut) and the cyanobacterial model organism Synechocystis PCC6803 to high light exposure of 250 μmol photons m(-2)  s(-1) using GC/MS-based metabolomics. Microcystis wild type and Mut show pronounced differences in their metabolic reprogramming upon high light. Seventeen per cent of the detected metabolites showed significant differences between the two genotypes after high light exposure. Whereas the microcystin-producing wild type shows a faster accumulation of glycolate upon high light illumination, loss of microcystin leads to an accumulation of general stress markers such as trehalose and sucrose. The study further uncovers differences in the high light adaptation of the bloom-forming cyanobacterium Microcystis and the model cyanobacterium Synechocystis. Most notably, Microcystis invests more into carbon reserves such as glycogen after high light exposure. Our data shed new light on the lifestyle of bloom-forming cyanobacteria, the role of the widespread toxin microcystin and the metabolic diversity of cyanobacteria.

  3. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites

    PubMed Central

    Wikoff, William R.; Anfora, Andrew T.; Liu, Jun; Schultz, Peter G.; Lesley, Scott A.; Peters, Eric C.; Siuzdak, Gary

    2009-01-01

    Although it has long been recognized that the enteric community of bacteria that inhabit the human distal intestinal track broadly impacts human health, the biochemical details that underlie these effects remain largely undefined. Here, we report a broad MS-based metabolomics study that demonstrates a surprisingly large effect of the gut “microbiome” on mammalian blood metabolites. Plasma extracts from germ-free mice were compared with samples from conventional (conv) animals by using various MS-based methods. Hundreds of features were detected in only 1 sample set, with the majority of these being unique to the conv animals, whereas ≈10% of all features observed in both sample sets showed significant changes in their relative signal intensity. Amino acid metabolites were particularly affected. For example, the bacterial-mediated production of bioactive indole-containing metabolites derived from tryptophan such as indoxyl sulfate and the antioxidant indole-3-propionic acid (IPA) was impacted. Production of IPA was shown to be completely dependent on the presence of gut microflora and could be established by colonization with the bacterium Clostridium sporogenes. Multiple organic acids containing phenyl groups were also greatly increased in the presence of gut microbes. A broad, drug-like phase II metabolic response of the host to metabolites generated by the microbiome was observed, suggesting that the gut microflora has a direct impact on the drug metabolism capacity of the host. Together, these results suggest a significant interplay between bacterial and mammalian metabolism. PMID:19234110

  4. Integrated plasma and urine metabolomics coupled with HPLC/QTOF-MS and chemometric analysis on potential biomarkers in liver injury and hepatoprotective effects of Er-Zhi-Wan.

    PubMed

    Yao, Weifeng; Gu, Haiwei; Zhu, Jiangjiang; Barding, Gregory; Cheng, Haibo; Bao, Beihua; Zhang, Li; Ding, Anwei; Li, Wei

    2014-11-01

    Metabolomics techniques are the comprehensive assessment of endogenous metabolites in a biological system and may provide additional insight into the molecular mechanisms. Er-Zhi-Wan (EZW) is a traditional Chinese medicine formula, which contains Fructus Ligustri Lucidi (FLL) and Herba Ecliptae (HE). EZW is widely used to prevent and treat various liver injuries through the nourishment of the liver. However, the precise molecular mechanism of hepatoprotective effects has not been comprehensively explored. Here, an integrated metabolomics strategy was designed to assess the effects and possible mechanisms of EZW against carbon tetrachloride-induced liver injury, a commonly used model of both acute and chronic liver intoxication. High-performance chromatography/quadrupole time-of-flight mass spectrometry (HPLC/QTOF-MS) combined with chemometric approaches including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to discover differentiating metabolites in metabolomics data of rat plasma and urine. Results indicate six differentiating metabolites, tryptophan, sphinganine, tetrahydrocorticosterone, pipecolic acid, L-2-amino-3-oxobutanoic acid and phosphoribosyl pyrophosphate, in the positive mode. Functional pathway analysis revealed that the alterations in these metabolites were associated with tryptophan metabolism, sphingolipid metabolism, steroid hormone biosynthesis, lysine degradation, glycine, serine and threonine metabolism, and pentose phosphate pathway. Of note, EZW has a potential pharmacological effect, which might be through regulating multiple perturbed pathways to the normal state. Our findings also showed that the robust integrated metabolomics techniques are promising for identifying more biomarkers and pathways and helping to clarify the function mechanisms of traditional Chinese medicine.

  5. 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.

  6. 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.

  7. 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

  8. Optimization of Huang-Lian-Jie-Du-Decoction for Ischemic Stroke Treatment and Mechanistic Study by Metabolomic Profiling and Network Analysis

    PubMed Central

    Zhang, Qian; Wang, Junsong; Liao, Shanting; Li, Pei; Xu, Dingqiao; Lv, Yan; Yang, Minghua; Kong, Lingyi

    2017-01-01

    Optimal drug proportions and mechanism deciphering of multicomponent drugs are critical for developing novel therapies to cope with complex diseases, such as stroke. In the present study, orthogonal experimental design was applied to explore the optimal proportion of the four component herbs in Huang-Lian-Jie-Du-Decoction (HLJDD) on the treatment of ischemic stroke. The treatment efficacies and mechanisms were assessed using global and amino acids (AAs) targeted metabolomics, as well as correlation network analysis. The global NMR metabolomics results revealed that AAs metabolism was significantly perturbed in middle cerebral artery occlusion rats. The levels of 23 endogenous AAs were then subjected to HPLC-QTOF-MS/MS analysis. These results complemented with neurobehavioral evaluations, cerebral infarct assessments, biochemical evaluations, histological inspections and immunohistochemistry observations strongly demonstrated that HLJDD with optimal proportion of 6 (Rhizoma coptidis): 4 (Radix scutellariae): 1 (Cortex phellodendr): 3 (Fructus Gardeniae) had the best efficacy on ischemic stroke, which could be ascribed to its modulation on AA metabolism. This integrated metabolomics approach showed the potential and applicable in deciphering the complex mechanisms of traditional Chinese medicine formulae on the treatment of complicated diseases, which provided new means to assess the treatment effects of herb combinations and to further development of drugs or therapies based on these formulae. PMID:28400733

  9. Microbiome-metabolome analysis reveals unhealthy alterations in the composition and metabolism of ruminal microbiota with increasing dietary grain in a goat model.

    PubMed

    Mao, Sheng-Yong; Huo, Wen-Jie; Zhu, Wei-Yun

    2016-02-01

    Currently, knowledge about the impact of high-grain (HG) feeding on rumen microbiota and metabolome is limited. In this study, a combination of the 454 pyrosequencing strategy and the mass spectrometry-based metabolomics technique was applied to investigate the effects of increased dietary grain (0%, 25% and 50% maize grain) on changes in whole ruminal microbiota and their metabolites using goat as a ruminant model. We observed a significant influence of HG feeding in shaping the ruminal bacterial community structure, diversity and composition, with an overall dominance of bacteria of the phylum Firmicutes along with a low abundance of Bacteriodetes in the HG group. High-grain feeding increased the number of ciliate and methanogens, and decreased the density of anaerobic fungi and the richness of the archaeal community. The metabolomics analysis revealed that HG feeding increased the levels of several toxic, inflammatory and unnatural compounds, including endotoxin, tryptamine, tyramine, histamine and phenylacetate. Correlation analysis on the combined datasets revealed some potential relationships between ruminal metabolites and certain microbial species. Information about these relationships may prove useful in either direct (therapeutic) or indirect (dietary) interventions for ruminal disorders due to microbial compositional shifts, such as ruminal acidosis.

  10. 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.

  11. Chemical features of Pericarpium Citri Reticulatae and Pericarpium Citri Reticulatae Viride revealed by GC-MS metabolomics analysis.

    PubMed

    Yi, Lunzhao; Dong, Naiping; Liu, Shao; Yi, Zhibiao; Zhang, Yi

    2015-11-01

    This paper introduces a detailed method to apply metabolic profiles conducting on tangerine peels (Citrus reticulata 'Dahongpao') at three maturity stages from July to December. Principal component analysis not only demonstrated the metabolic footprints of tangerine peels during ripening but also revealed the compounds (D-limonene and linalool) that mostly contributed to it. Furthermore, some other characteristic compounds were screened to further reveal the chemical features of Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV). In particular, compounds such as 4-carene (r = -0.94), 3-carene (r = -0.91), β-pinene (r = -0.85) and γ-terpinene (r = -0.87) were screened as major components for the pungent smell of PCRV. Geranyl acetate (r = 0.81), farnesyl acetate (r = 0.87) and three alcohols (6-hepten-1-ol, 3-methyl-1-hexanol, 1-octanol) may lead to the pleasant odour of PCR. We therefore propose that the metabolomics analysis focusing on ripening process will be an effective strategy for quality control of closely related herbal medicines. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Integrated Physiological, Proteomic, and Metabolomic Analysis of Ultra Violet (UV) Stress Responses and Adaptation Mechanisms in Pinus radiata.

    PubMed

    Pascual, Jesús; Cañal, María Jesús; Escandón, Mónica; Meijón, Mónica; Weckwerth, Wolfram; Valledor, Luis

    2017-03-01

    Globally expected changes in environmental conditions, especially the increase of UV irradiation, necessitate extending our knowledge of the mechanisms mediating tree species adaptation to this stress. This is crucial for designing new strategies to maintain future forest productivity. Studies focused on environmentally realistic dosages of UV irradiation in forest species are scarce. Pinus spp. are commercially relevant trees and not much is known about their adaptation to UV. In this work, UV treatment and recovery of Pinus radiata plants with dosages mimicking future scenarios, based on current models of UV radiation, were performed in a time-dependent manner. The combined metabolome and proteome analysis were complemented with measurements of + physiological parameters and gene expression. Sparse PLS analysis revealed complex molecular interaction networks of molecular and physiological data. Early responses prevented phototoxicity by reducing photosystem activity and the electron transfer chain together with the accumulation of photoprotectors and photorespiration. Apart from the reduction in photosynthesis as consequence of the direct UV damage on the photosystems, the primary metabolism was rearranged to deal with the oxidative stress while minimizing ROS production. New protein kinases and proteases related to signaling, coordination, and regulation of UV stress responses were revealed. All these processes demonstrate a complex molecular interaction network extending the current knowledge on UV-stress adaptation in pine. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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

    PubMed

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

    2014-03-14

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

  14. Shotgun Metabolomics Approach for the Analysis of Negatively Charged Water-Soluble Cellular Metabolites from Mouse Heart Tissue

    PubMed Central

    Sun, Gang; Yang, Kui; Zhao, Zhongdan; Guan, Shaoping; Han, Xianlin; Gross, Richard W.

    2010-01-01

    A shotgun metabolomics approach using MALDI-TOF/TOF mass spectrometry was developed for the rapid analysis of negatively charged water-soluble cellular metabolites. Through the use of neutral organic solvents to inactivate endogenous enzyme activities (i.e., methanol/chloroform/H2O extraction), in conjunction with a matrix having minimal background noise (9-amnioacridine), a set of multiplexed conditions was developed that allowed identification of 285 peaks corresponding to negatively charged metabolites from mouse heart extracts. Identification of metabolite peaks was based on mass accuracy and was confirmed by tandem mass spectrometry for 90 of the identified metabolite peaks. Through multiplexing ionization conditions, new suites of metabolites could be ionized and “spectrometric isolation” of closely neighboring peaks for subsequent tandem mass spectrometric interrogation could be achieved. Moreover, assignments of ions from isomeric metabolites and quantitation of their relative abundance was achieved in many cases through tandem mass spectrometry by identification of diagnostic fragmentation ions (e.g., discrimination of ATP from dGTP). The high sensitivity of this approach facilitated the detection of extremely low abundance metabolites including important signaling metabolites such as IP3, cAMP, and cGMP. Collectively, these results identify a multiplexed MALDI-TOF/TOF MS approach for analysis of negatively charged metabolites in mammalian tissues. PMID:17665876

  15. Characterization of metabolic states of Arabidopsis thaliana under diverse carbon and nitrogen nutrient conditions via targeted metabolomic analysis.

    PubMed

    Sato, Shigeru; Yanagisawa, Shuichi

    2014-02-01

    Plant growth and metabolism are regulated in response to various environmental factors. To investigate modulations in plant metabolism by the combined action of elevated atmospheric CO2 concentration and other nutritional factors, we performed targeted metabolomic analysis using Arabidopsis thaliana plants grown under 24 different conditions where the CO2 concentration, amounts and species of nitrogen source, and light intensity were modified. Our results indicate that both the biosynthesis of diverse metabolites and growth are promoted in proportion to the CO2 concentration at a wide range of CO2 levels, from ambient concentrations to an extremely high concentration (3,600 p.p.m.) of CO2. This suggests that A. thaliana has the potential to utilize effectively very high concentrations of CO2. On the other hand, ammonium (but not nitrate) supplied as an additional nitrogen source induced drastic alterations in metabolite composition, including increases in the contents of glucose, starch and several amino acids, and reductions in the tricarboxylic acid (TCA) cycle-related organic acid content under any CO2 conditions. Hierarchical clustering analysis using the metabolite profiles revealed that ammonium is a prominent factor determining metabolic status, while the CO2 concentration is not. However, ammonium-induced metabolic alterations were differently modified by high concentrations of CO2. Hence, our results imply that increases in CO2 concentration may differently influence plant metabolism depending on the nitrogen nutrient conditions.

  16. Development of bottom-fermenting saccharomyces strains that produce high SO2 levels, using integrated metabolome and transcriptome analysis.

    PubMed

    Yoshida, Satoshi; Imoto, Jun; Minato, Toshiko; Oouchi, Rie; Sugihara, Mao; Imai, Takeo; Ishiguro, Tatsuji; Mizutani, Satoru; Tomita, Masaru; Soga, Tomoyoshi; Yoshimoto, Hiroyuki

    2008-05-01

    Sulfite plays an important role in beer flavor stability. Although breeding of bottom-fermenting Saccharomyces strains that produce high levels of SO(2) is desirable, it is complicated by the fact that undesirable H(2)S is produced as an intermediate in the same pathway. Here, we report the development of a high-level SO(2)-producing bottom-fermenting yeast strain by integrated metabolome and transcriptome analysis. This analysis revealed that O-acetylhomoserine (OAH) is the rate-limiting factor for the production of SO(2) and H(2)S. Appropriate genetic modifications were then introduced into a prototype strain to increase metabolic fluxes from aspartate to OAH and from sulfate to SO(2), resulting in high SO(2) and low H(2)S production. Spontaneous mutants of an industrial strain that were resistant to both methionine and threonine analogs were then analyzed for similar metabolic fluxes. One promising mutant produced much higher levels of SO(2) than the parent but produced parental levels of H(2)S.

  17. Integrated proteomic and metabolomic analysis of larval brain associated with diapause induction and preparation in the cotton bollworm, Helicoverpa armigera.

    PubMed

    Zhang, Qi; Lu, Yu-Xuan; Xu, Wei-Hua

    2012-02-03

    Diapause is a developmental arrest that allows an organism to survive unfavorable environmental conditions and is induced by environmental signals at a certain sensitive developmental stage. In Helicoverpa armigera, the larval brain receives the environmental signals for diapause induction and then regulates diapause entry at the pupal stage. Here, combined proteomic and metabolomic differential display analysis was performed on the H. armigera larval brain. Using two-dimensional electrophoresis, it was found that 22 proteins were increased and 27 proteins were decreased in the diapause-destined larval brain, 37 of which were successfully identified by MALDI-TOF/TOF mass spectrometry. RT-PCR and Western blot analyses showed that the expression levels of the differentially expressed proteins were consistent with the 2-DE results. Furthermore, a total of 49 metabolites were identified in the larval brain by GC-MS analysis, including 4 metabolites at high concentrations and 14 metabolites at low concentrations. The results gave us a clue to understand the governing molecular events of the prediapause phase. Those differences that exist in the induction phase of diapause-destined individuals are probably relevant to a special memory mechanism for photoperiodic information storage, and those differences that exist in the preparation phase are likely to regulate accumulation of specific energy reserves in diapause-destined individuals.

  18. Metabolomic Analysis Reveals Cyanidins in Black Raspberry as Candidates for Suppression of Lipopolysaccharide-Induced Inflammation in Murine Macrophages.

    PubMed

    Jo, Young-Hee; Park, Hyun-Chang; Choi, Seulgi; Kim, Sugyeong; Bao, Cheng; Kim, Hyung Woo; Choi, Hyung-Kyoon; Lee, Hong Jin; Auh, Joong-Hyuck

    2015-06-10

    The extracts produced by multisolvent extraction and subfractionation with preparative liquid chromatography of black raspberry (Rubus coreanus Miquel) cultivated in Gochang, South Korea, were tested for their anti-inflammatory effects. The metabolomic profiling and analysis by orthogonal partial least-squares discriminant analysis (OLPS-DA) suggested that cyanidin, cyanidin-3-glucoside (C3G), and cyanidin-3-rutinoside (C3R) were key components for the anti-inflammatory responses in the most active fraction BF3-1, where they were present at 0.44, 1.26, and 0.56 μg/mg of BF3-1, respectively. Both BF3-1 and mixture of these cyanidins at the same ratio reduced lipopolysaccharide (LPS)-induced protein level of iNOS expression and suppressed mRNA and protein expressions of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β through inhibiting the phosphorylation of mitogen-activated protein kinases (MAPKs) and STAT3 in murine macrophage RAW264.7 cells. Overall, the results suggested that co-administration of cyanidin, C3G, and C3R is more effective than that of cyanidin alone and that the coexistence of these anthocyanin components in black raspberry plays a vital role in regulating LPS-induced inflammation even at submicromolar concentrations, making it possible to explain the health beneficial activity of its extracts.

  19. Metabolomics Analysis Reveals that AICAR Affects Glycerolipid, Ceramide and Nucleotide Synthesis Pathways in INS-1 Cells.

    PubMed

    ElAzzouny, Mahmoud A; Evans, Charles R; Burant, Charles F; Kennedy, Robert T

    2015-01-01

    AMPK regulates many metabolic pathways including fatty acid and glucose metabolism, both of which are closely associated with insulin secretion in pancreatic β-cells. Insulin secretion is regulated by metabolic coupling factors such as ATP/ADP ratio and other metabolites generated by the metabolism of nutrients such as glucose, fatty acid and amino acids. However, the connection between AMPK activation and insulin secretion in β-cells has not yet been fully elucidated at a metabolic level. To study the effect of AMPK activation on glucose stimulated insulin secretion, we applied the pharmacological activator 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) to an INS-1 (832/13) β-cell line. We measured the change in 66 metabolites in the presence or absence of AICAR using different stable isotopic labeled nutrients to probe selected pathways. AMPK activation by AICAR increased basal insulin secretion and reduced the glucose stimulation index. Although ATP/ADP ratios were not strongly affected by AICAR, several other metabolites and pathways important for insulin secretion were affected by AICAR treatment including long-chain CoAs, malonyl-CoA, 3-hydroxy-3 methylglutaryl CoA, diacylglycerol, and farnesyl pyrophosphate. Tracer studies using 13C-glucose revealed lower glucose flux in the purine and pyrimidine pathway and in the glycerolipid synthesis pathway. Untargeted metabolomics revealed reduction in ceramides caused by AICAR that may explain the beneficial role of AMPK in protecting β-cells from lipotoxicity. Taken together, the results provide an overall picture of the metabolic changes associated with AICAR treatment and how it modulates insulin secretion and β-cell survival.

  20. Metabolomics Analysis Reveals that AICAR Affects Glycerolipid, Ceramide and Nucleotide Synthesis Pathways in INS-1 Cells

    PubMed Central

    ElAzzouny, Mahmoud A.; Evans, Charles R.; Burant, Charles F; Kennedy, Robert T.

    2015-01-01

    AMPK regulates many metabolic pathways including fatty acid and glucose metabolism, both of which are closely associated with insulin secretion in pancreatic β-cells. Insulin secretion is regulated by metabolic coupling factors such as ATP/ADP ratio and other metabolites generated by the metabolism of nutrients such as glucose, fatty acid and amino acids. However, the connection between AMPK activation and insulin secretion in β-cells has not yet been fully elucidated at a metabolic level. To study the effect of AMPK activation on glucose stimulated insulin secretion, we applied the pharmacological activator 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) to an INS-1 (832/13) β-cell line. We measured the change in 66 metabolites in the presence or absence of AICAR using different stable isotopic labeled nutrients to probe selected pathways. AMPK activation by AICAR increased basal insulin secretion and reduced the glucose stimulation index. Although ATP/ADP ratios were not strongly affected by AICAR, several other metabolites and pathways important for insulin secretion were affected by AICAR treatment including long-chain CoAs, malonyl-CoA, 3-hydroxy-3 methylglutaryl CoA, diacylglycerol, and farnesyl pyrophosphate. Tracer studies using 13C-glucose revealed lower glucose flux in the purine and pyrimidine pathway and in the glycerolipid synthesis pathway. Untargeted metabolomics revealed reduction in ceramides caused by AICAR that may explain the beneficial role of AMPK in protecting β-cells from lipotoxicity. Taken together, the results provide an overall picture of the metabolic changes associated with AICAR treatment and how it modulates insulin secretion and β-cell survival. PMID:26107620

  1. Antiadhesive Activity and Metabolomics Analysis of Rat Urine after Cranberry (Vaccinium macrocarpon Aiton) Administration.

    PubMed

    Peron, Gregorio; Pellizzaro, Anna; Brun, Paola; Schievano, Elisabetta; Mammi, Stefano; Sut, Stefania; Castagliuolo, Ignazio; Dall'Acqua, Stefano

    2017-07-19

    Cranberry (Vaccinium macrocarpon Aiton) is used to treat noncomplicated urinary tract infections (UTIs). A-type procyanidins (PAC-A) are considered the active constituents able to inhibit bacterial adhesion to the urinary epithelium. However, the role of PAC-A in UTIs is debated, because of their poor bioavailability, extensive metabolism, limited knowledge about urinary excretion, and contradictory clinical trials. The effects of 35-day cranberry supplementation (11 mg/kg PAC-A, 4 mg/kg PAC-B) were studied in healthy rats using a ultra performance liquid chromatography-mass spectrometry (UPLC-MS)-based metabolomics approach. Microbial PAC metabolites, such as valeric acid and valerolactone derivatives, were related to cranberry consumption. An increased urinary excretion of glucuronidated metabolites was also observed. In a further experiment, urine samples were collected at 2, 4, 8, and 24 h after cranberry intake and their antiadhesive properties were tested against uropathogenic Escherichia coli. The 8 h samples showed the highest activity. Changes in urinary composition were studied by ultra performance liquid chromatography-time-of-flight (UPLC-QTOF), observing the presence of PAC metabolites. The PAC-A2 levels were measured in all collected samples, and the highest amounts, on the order of ng/mL, were found in the samples collected after 4 h. Results indicate that the antiadhesive activity against uropathogenic bacteria observed after cranberry consumption is ascribable to PAC-A metabolites rather than to a direct PAC-A effect, as the measured PAC-A levels in urine was lower than those reported as active in the literature.

  2. Partial least squares model and design of experiments toward the analysis of the metabolome of Jatropha gossypifolia leaves: Extraction and chromatographic fingerprint optimization.

    PubMed

    Pilon, Alan Cesar; Carnevale Neto, Fausto; Freire, Rafael Teixeira; Cardoso, Patrícia; Carneiro, Renato Lajarim; Da Silva Bolzani, Vanderlan; Castro-Gamboa, Ian

    2016-03-01

    A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols.

  3. A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography–mass spectrometry

    SciTech Connect

    Webb-Robertson, Bobbie-Jo; Kim, Young -Mo; Zink, Erika M.; Hallaian, Katherine A.; Zhang, Qibin; Madupu, Ramana; Waters, Katrina M.; Metz, Thomas O.

    2014-02-27

    Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentified metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.

  4. A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography–mass spectrometry

    DOE PAGES

    Webb-Robertson, Bobbie-Jo; Kim, Young -Mo; Zink, Erika M.; ...

    2014-02-27

    Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentifiedmore » metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.« less

  5. A Sister Group Contrast Using Untargeted Global Metabolomic Analysis Delineates the Biochemical Regulation Underlying Desiccation Tolerance in Sporobolus stapfianus[C][W][OA

    PubMed Central

    Oliver, Melvin J.; Guo, Lining; Alexander, Danny C.; Ryals, John A.; Wone, Bernard W.M.; Cushman, John C.

    2011-01-01

    Understanding how plants tolerate dehydration is a prerequisite for developing novel strategies for improving drought tolerance. The desiccation-tolerant (DT) Sporobolus stapfianus and the desiccation-sensitive (DS) Sporobolus pyramidalis formed a sister group contrast to reveal adaptive metabolic responses to dehydration using untargeted global metabolomic analysis. Young leaves from both grasses at full hydration or at 60% relative water content (RWC) and from S. stapfianus at lower RWCs were analyzed using liquid and gas chromatography linked to mass spectrometry or tandem mass spectrometry. Comparison of the two species in the fully hydrated state revealed intrinsic differences between the two metabolomes. S. stapfianus had higher concentrations of osmolytes, lower concentrations of metabolites associated with energy metabolism, and higher concentrations of nitrogen metabolites, suggesting that it is primed metabolically for dehydration stress. Further reduction of the leaf RWC to 60% instigated a metabolic shift in S. stapfianus toward the production of protective compounds, whereas S. pyramidalis responded differently. The metabolomes of S. stapfianus leaves below 40% RWC were strongly directed toward antioxidant production, nitrogen remobilization, ammonia detoxification, and soluble sugar production. Collectively, the metabolic profiles obtained uncovered a cascade of biochemical regulation strategies critical to the survival of S. stapfianus under desiccation. PMID:21467579

  6. LC-MS- and (1)H NMR-Based Metabolomic Analysis and in Vitro Toxicological Assessment of 43 Aristolochia Species.

    PubMed

    Michl, Johanna; Kite, Geoffrey C; Wanke, Stefan; Zierau, Oliver; Vollmer, Guenter; Neinhuis, Christoph; Simmonds, Monique S J; Heinrich, Michael

    2016-01-22

    Species of Aristolochia are used as herbal medicines worldwide. They cause aristolochic acid nephropathy (AAN), a devastating disease associated with kidney failure and renal cancer. Aristolochic acids I and II (1 and 2) are considered to be responsible for these nephrotoxic and carcinogenic effects. A wide range of other aristolochic acid analogues (AAAs) exist, and their implication in AAN may have been overlooked. An LC-MS- and (1)H NMR-based metabolomic analysis was carried out on 43 medicinally used Aristolochia species. The cytotoxicity and genotoxicity of 28 Aristolochia extracts were measured in human kidney (HK-2) cells. Compounds 1 and 2 were found to be the most common AAAs. However, AA IV (3), aristolactam I (4), and aristolactam BI (5) were also widespread. No correlation was found between the amounts of 1 or 2 and extract cytotoxicity against HK-2 cells. The genotoxicity and cytotoxicity of the extracts could be linked to their contents of 5, AA D (8), and AA IIIa (10). These results undermine the assumption that 1 and 2 are exclusively responsible for the toxicity of Aristolochia species. Other analogues are likely to contribute to their toxicity and need to be considered as nephrotoxic agents. These findings facilitate understanding of the nephrotoxic mechanisms of Aristolochia and have significance for the regulation of herbal medicines.

  7. Amniotic fluid metabolomics and biochemistry analysis provides novel insights into the diet-regulated foetal growth in a pig model

    PubMed Central

    Wan, Jin; Jiang, Fei; Zhang, Jiao; Xu, Qingsong; Chen, Daiwen; Yu, Bing; Mao, Xiangbing; Yu, Jie; Luo, Yuheng; He, Jun

    2017-01-01

    Foetal loss and intrauterine growth restriction are major problems in mammals, but there are few effective ways in preventing it. Intriguingly, chitosan oligosaccharide (COS), a biomaterial derived from chitosan, can promote foetal survival and growth. Therefore, we have investigated how COS affects foetal survival and growth in a pig model. Fifty-two sows were divided into two treatment groups (n = 26) and fed either solely a control diet or a control diet that includes 100 mg/kg COS. Amniotic fluid and foetus samples from six sows that were of average body weight in each group were collected on gestation day 35. We applied a 1H NMR-based metabolomics approach combined with biochemistry analysis to track the changes that occurred in the amniotic fluid of pregnant sows after COS intervention. Maternal COS inclusion had enhanced (P < 0.05) the foetal survival rate and size at 35 days. COS supplementation had both increased (P < 0.05) SOD, CAT and T-AOC activities and elevated (P < 0.05) IL-10, IgG and IgM concentrations in the amniotic fluid. Moreover, COS had affected (P < 0.05) the amniotic fluid’s lysine, citrate, glucose and hypoxanthine levels. Overall, COS inclusion induced amniotic fluid antioxidant status and metabolic profiles modifications characterising improvements in foetal survival and growth in a pig model. PMID:28300194

  8. Comparative analysis of volatile oils in the stems and roots of Ephedra sinica via GC-MS-based plant metabolomics.

    PubMed

    Lv, Meng-Ying; Sun, Jian-Bo; Wang, Min; Fan, Hong-Yan; Zhang, Zun-Jian; Xu, Feng-Guo

    2016-02-01

    With a great difference in therapeutic effects of Mahuang (MH, the stems of Ephedra sinica) and Mahuanggen (MHG, the roots of Ephedra sinica), chemical differences between MH and MHG should be investigated. In the present study, gas chromatography-mass spectrometry (GC-MS)-based plant metabolomics was employed to compare volatile oil profiles of MH and MHG. The antioxidant activities of volatile oils from MH and MHG were also compared. 32 differential chemical markers were identified according to the variable importance in the projection (VIP) value of orthogonal partial least squares discriminant analysis (OPLS-DA) and P value of Mann-Whitney test. Among them, chemical markers of tetramethylpyrazine (TMP) and α-terpineol were quantified. Their contents were much higher in most MH samples compared with MHG. The antioxidant assay demonstrated that MH had significantly higher free radical-scavenging activity than MHG. Although MH and MHG derived from the same medicinal plant, there was much difference in their volatile oil profiles. MH samples had significantly higher content of two reported pharmacologically important chemical markers of TMP and α-terpineol, which may account for their different antioxidant activities. Copyright © 2016 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

  9. A comprehensive analysis of myocardial substrate preference emphasizes the need for a synchronized fluxomic/metabolomic research design.

    PubMed

    Ragavan, Mukundan; Kirpich, Alexander; Fu, Xiaorong; Burgess, Shawn C; McIntyre, Lauren M; Merritt, Matthew E

    2017-06-01

    The heart oxidizes fatty acids, carbohydrates, and ketone bodies inside the tricarboxylic acid (TCA) cycle to generate the reducing equivalents needed for ATP production. Competition between these substrates makes it difficult to estimate the extent of pyruvate oxidation. Previously, hyperpolarized pyruvate detected propionate-mediated activation of carbohydrate oxidation, even in the presence of acetate. In this report, the optimal concentration of propionate for the activation of glucose oxidation was measured in mouse hearts perfused in Langendorff mode. This study was performed with a more physiologically relevant perfusate than the previous work. Increasing concentrations of propionate did not cause adverse effects on myocardial metabolism, as evidenced by unchanged O2 consumption, TCA cycle flux, and developed pressures. Propionate at 1 mM was sufficient to achieve significant increases in pyruvate dehydrogenase flux (3×), and anaplerosis (6×), as measured by isotopomer analysis. These results further demonstrate the potential of propionate as an aid for the correct estimation of total carbohydrate oxidative capacity in the heart. However, liquid chromotography/mass spectroscopy-based metabolomics detected large changes (~30-fold) in malate and fumarate pool sizes. This observation leads to a key observation regarding mass balance in the TCA cycle; flux through a portion of the cycle can be drastically elevated without changing the O2 consumption. Copyright © 2017 the American Physiological Society.

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

    PubMed

    Arbulu, M; Sampedro, M C; Gómez-Caballero, A; Goicolea, M A; Barrio, R J

    2015-02-09

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

  11. Metabolomic analysis and differential expression of anthocyanin biosynthetic genes in white- and red-flowered buckwheat cultivars (Fagopyrum esculentum).

    PubMed

    Kim, Yeon Bok; Park, Soo-Yun; Thwe, Aye Aye; Seo, Jeong Min; Suzuki, Tastsuro; Kim, Sun-Ju; Kim, Jae Kwang; Park, Sang Un

    2013-11-06

    Red-flowered buckwheat ( Fagopyrum esculentum ) is used in the production of tea, juice, and alcohols after the detoxification of fagopyrin. In order to investigate the metabolomics and regulatory of anthocyanin production in red-flowered (Gan-Chao) and white-flowered (Tanno) buckwheat cultivars, quantitative real-time RT-PCR (qRT-PCR), gas chromatography time-of-flight mass spectrometry (GC-TOFMS), and high performance liquid chromatography (HPLC) were conducted. The transcriptions of FePAL, FeC4H, Fe4CL1, FeF3H, FeANS, and FeDFR increased gradually from flowering stage 1 and reached their highest peaks at flowering stage 3 in Gan-Chao flower. In total 44 metabolites, 18 amino acids, 15 organic acids, 7 sugars, 3 sugar alcohols, and 1 amine were detected in Gan-Chao flowers. Two anthocyanins, cyanidin 3-O-glucoside and cyanidin 3-O-rutinoside, were identified in Gan-Chao cultivar. The first component of the partial least-squares to latent structures-discriminate analysis (PLS-DA) indicated that high amounts of phenolic, shikimic, and pyruvic acids were present in Gan-Chao. We suggest that transcriptions of genes involved in anthocyanin biosynthesis, anthocyanin contents, and metabolites have correlation in the red-flowered buckwheat Gan-Chao flowers. Our results may be helpful to understand anthocyanin biosynthesis in red-flowered buckwheat.

  12. Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease

    PubMed Central

    Poliquin, Pierre O.; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

    2013-01-01

    Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level. PMID:23935941

  13. Metabolomic analysis of serum from obese adults with hyperlipemia by UHPLC-Q-TOF MS/MS.

    PubMed

    Wang, Yang; Liu, Desheng; Li, Yue; Guo, Lei; Cui, Yinghua; Zhang, Xin; Li, Enyou

    2016-01-01

    The prevalence of obesity has dramatically increased and poses a major threat to human health. Obesity often accompanies hyperlipemia, which is strongly related to the occurrence and development of obesity-related chronic diseases. Differences in metabolomic profiling of serum between obese (with hyperlipemia) and normal-weight men (n = 30 in each group) were investigated using ultrahigh-pressure liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF MS/MS) and partial least-squares-discriminant analysis (PLS-DA). Obese men showed higher levels of weight, body mass index, fat mass, systolic blood pressure, fasting plasma glucose, triglyeride, total cholesterol, insulin, HOMA-IR and high-sensitivity CRP. Obese and normal-weight groups were clearly discriminated from each other on a PLS-DA score plot and nine major metabolites contributing to the discrimination were assigned, including increased 2-octenoylcarnitine, eicosadienoic acid, 12-hydroperoxyeicosatetraenoic acid, 4-hydroxyestrone sulfate, lysoPE[18:1(11Z)/0:0], thromboxane B2 and pyridinoline and decreased vitamin D3 glucosiduronate and 9,10-DHOME. These metabolites were associated with lipid metabolism and obesity-related diseases, and reflected the metabolic differences between normal and obese men, which may be important for future clinical diagnosis, treatment and assessment of the therapeutic effect on obesity-related chronic disease.

  14. 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.

  15. Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

    PubMed

    Basu, Sumanta; Duren, William; Evans, Charles R; Burant, Charles F; Michailidis, George; Karnovsky, Alla

    2017-05-15

    Recent technological advances in mass spectrometry, development of richer mass spectral libraries and data processing tools have enabled large scale metabolic profiling. Biological interpretation of metabolomics studies heavily relies on knowledge-based tools that contain information about metabolic pathways. Incomplete coverage of different areas of metabolism and lack of information about non-canonical connections between metabolites limits the scope of applications of such tools. Furthermore, the presence of a large number of unknown features, which cannot be readily identified, but nonetheless can represent bona fide compounds, also considerably complicates biological interpretation of the data. Leveraging recent developments in the statistical analysis of high-dimensional data, we developed a new Debiased Sparse Partial Correlation algorithm (DSPC) for estimating partial correlation networks and implemented it as a Java-based CorrelationCalculator program. We also introduce a new version of our previously developed tool Metscape that enables building and visualization of correlation networks. We demonstrate the utility of these tools by constructing biologically relevant networks and in aiding identification of unknown compounds. http://metscape.med.umich.edu. Supplementary data are available at Bioinformatics online.

  16. Supervised Semi-Automated Data Analysis Software for Gas Chromatography / Differential Mobility Spectrometry (GC/DMS) Metabolomics Applications.

    PubMed

    Peirano, Daniel J; Pasamontes, Alberto; Davis, Cristina E

    2016-09-01

    Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

  17. Study of exhaled breath condensate sample preparation for metabolomics analysis by LC-MS/MS in high resolution mode.

    PubMed

    Fernández-Peralbo, M A; Calderón Santiago, M; Priego-Capote, F; Luque de Castro, M D

    2015-11-01

    Metabolomic analysis of exhaled breath condensate (EBC) requires an unavoidable sample preparation step because of the low concentration of its components, and potential cleanup for possible interferents. Sample preparation based on protein precipitation (PP), solid-phase extraction (SPE) by hydrophilic and lipophilic sorbents or lyophilization has demonstrated that the analytical sample from the last is largely the best because lyophilization allows reconstitution in a volume as small as required (preconcentration factors up to 80-times with respect to the original sample), thus doubling the number of detected compounds as compared with the other alternatives (47 versus 25). In addition, PP and/or SPE cleanup are unnecessary as no effect from the EBC components removed by these steps appears in the chromatograms. The total 49 EBC compounds tentatively identified and confirmed by MS/MS in this research include amino acids, fatty acids, fatty amides, fatty aldehydes, sphingoid bases, oxoanionic compounds, imidazoles, hydroxy acids and aliphatic acyclic acids. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. GC-MS metabolomic analysis reveals significant alterations in cerebellar metabolic physiology in a mouse model of adult onset hypothyroidism.

    PubMed

    Constantinou, Caterina; Chrysanthopoulos, Panagiotis K; Margarity, Marigoula; Klapa, Maria I

    2011-02-04

    Although adult-onset hypothyroidism (AOH) has been connected to neural activity alterations, including movement, behavioral, and mental dysfunctions, the underlying changes in brain metabolic physiology have not been investigated in a systemic and systematic way. The current knowledge remains fragmented, referring to different experimental setups and recovered from various brain regions. In this study, we developed and applied a gas chromatography-mass spectrometry (GC-MS) metabolomics protocol to obtain a holistic view of the cerebellar metabolic physiology in a Balb/cJ mouse model of prolonged adult-onset hypothyroidism induced by a 64-day treatment with 1% potassium perchlorate in the drinking water of the animals. The high-throughput analysis enabled the correlation between multiple parallel-occurring metabolic phenomena; some have been previously related to AOH, while others implicated new pathways, designating new directions for further research. Specifically, an overall decline in the metabolic activity of the hypothyroid compared to the euthyroid cerebellum was observed, characteristically manifested in energy metabolism, glutamate/glutamine metabolism, osmolytic/antioxidant capacity, and protein/lipid synthesis. These alterations provide strong evidence that the mammalian cerebellum is metabolically responsive to AOH. In light of the cerebellum core functions and its increasingly recognized role in neurocognition, these findings further support the known phenotypic manifestations of AOH into movement and cognitive dysfunctions.

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

    PubMed Central

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

    2016-01-01

    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. PMID:27578275

  20. Integrated metabolomics and metagenomics analysis of plasma and urine identified microbial metabolites associated with coronary heart disease

    PubMed Central

    Feng, Qiang; Liu, Zhipeng; Zhong, Shilong; Li, Ruijun; Xia, Huihua; Jie, Zhuye; Wen, Bo; Chen, Xiaomin; Yan, Wei; Fan, Yanqun; Guo, Zhenyu; Meng, Nan; Chen, Jiyan; Yu, Xiyong; Zhang, Zhiwei; Kristiansen, Karsten; Wang, Jun; Xu, Xun; He, Kunlun; Li, Guanglei

    2016-01-01

    Coronary heart disease (CHD) is top risk factor for health in modern society, causing high mortality rate each year. However, there is no reliable way for early diagnosis and prevention of CHD so far. So study the mechanism of CHD and development of novel biomarkers is urgently needed. In this study, metabolomics and metagenomics technology are applied to discover new biomarkers from plasma and urine of 59 CHD patients and 43 healthy controls and trace their origin. We identify GlcNAc-6-P which has good diagnostic capability and can be used as potential biomarkers for CHD, together with mannitol and 15 plasma cholines. These identified metabolites show significant correlations with clinical biochemical indexes. Meanwhile, GlcNAc-6-P and mannitol are potential metabolites originated from intestinal microbiota. Association analysis on species and function levels between intestinal microbes and metabolites suggest a close correlation between Clostridium sp. HGF2 and GlcNAc-6-P, Clostridium sp. HGF2, Streptococcus sp. M143, Streptococcus sp. M334 and mannitol. These suggest the metabolic abnormality is significant and gut microbiota dysbiosis happens in CHD patients. PMID:26932197

  1. Cancer Metabolomics and the Human Metabolome Database

    PubMed Central

    Wishart, David S.; Mandal, Rupasri; Stanislaus, Avalyn; Ramirez-Gaona, Miguel

    2016-01-01

    The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world’s largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer. PMID:26950159

  2. Cancer Metabolomics and the Human Metabolome Database.

    PubMed

    Wishart, David S; Mandal, Rupasri; Stanislaus, Avalyn; Ramirez-Gaona, Miguel

    2016-03-02

    The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world's largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer.

  3. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors.

    PubMed

    Vázquez-Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez, Miguel Ángel; Vinaixa, Maria; Chiva-Blanch, Gemma; Estruch, Ramon; Correig, Xavier; Andrés-Lacueva, Cristina

    2012-08-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100mL/day, alcohol control). After each period, 24-h urine samples were collected and analyzed by (1) H-NMR. According to the results of a one-way ANOVA, significant markers were grouped in four categories: alcohol-related markers (ethanol); gin-related markers; wine-related markers; and gut microbiota markers (hippurate and 4-hydroxphenylacetic acid). Wine metabolites were classified into two groups; first, metabolites of food metabolome: tartrate (RWA and RWD), ethanol, and mannitol (RWA); and second, biomarkers that relates to endogenous modifications after wine consumption, comprising branched-chain amino acid (BCAA) metabolite (3-methyl-oxovalerate). Additionally, a possible interaction between alcohol and gut-related biomarkers has been identified. To our knowledge, this is the first time that this approach has been applied in a nutritional intervention with red wine. The results show the capacity of this approach to obtain a comprehensive metabolome picture including food metabolome and endogenous biomarkers of moderate wine intake.

  4. [Gastroenterological Cancer Diagnosis by Metabolomics-Discovery of Pancreatic Cancer Biomarker].

    PubMed

    Yoshida, Masaru; Nishiumi, Shin; Azuma, Takeshi

    2015-04-01

    The field of omics involves comprehensive investigations based on genomics, transcriptomics, proteomics, and metabolomics, and omics studies have developed rapidly. Metabolomics, metabolome analysis, involves technology to analyze the concentrations of low-molecular-weight metabolites comprehensively, and has recently rapidly developed along with improvements in analytical technology. Therefore, metabolome analysis is just beginning to be applied to not only food science and environmental research fields but also medical research. In the medical research field, especially, metabolome analysis plays an important role in novel disease biomarker discovery. The metabolome represents the endpoint of the omics cascade and, therefore, is considered to be closer to the phenotype. In addition, there is also a possibility that the metabolome is affected by exogenous factors such as environmental and food factors, as well as endogenous factors such as DNA/mRNA/protein. Therefore, metabolome analysis can be a useful approach for discovering effective biomarkers. Here, we explain the characteristics of metabolome analysis, and also outline metabolome analysis using a liquid chromatograph mass spectrometer (LC-MS), gas chromatograph mass spectrometer (GC-MS), capillary electrophoresis mass spectrometer (CE-MS), and matrix-assisted laser desorption ionization mass spectrometer (MALDI-MS). Then, we describe the findings of studies that used metabolome analysis in an attempt to discover biomarker candidates for pancreatic cancer, and discuss metabolome analysis-based disease diagnosis.

  5. Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli.

    PubMed

    Taymaz-Nikerel, Hilal; De Mey, Marjan; Baart, Gino J E; Maertens, Jo; Foulquié-Moreno, Maria Remedios; Charlier, Daniel; Heijnen, Joseph J; van Gulik, Walter M

    2016-04-01

    An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain. Unexpectedly the mutant had a higher energy efficiency, indicated by a much lower rate of oxygen consumption, under glucose-limited conditions, caused by the deletion of the transcription factors IclR and ArcA. Furthermore the mutant had a much lower uptake capacity for succinate (26-fold) and oxygen (17-fold under succinate excess) compared to the wild-type strain. The mutant strain produced 7.9 mmol.CmolX(-1).h(-1) succinate during chemostat cultivation, showing that the choice of the applied genetic modifications was a successful strategy. Furthermore, the applied genetic modifications resulted in multiple large changes in metabolite levels (FBP, pyruvate, 6PG, NAD(+) /NADH ratio, α-ketogluarate) corresponding to large changes in fluxes. Compared to the wild-type a considerable flux shift occurred from the tricarboxylic acid (TCA) cycle to the oxidative part of the pentose phosphate pathway, including an inversion of the pyruvate kinase flux. The mutant responded very differently to excess of succinate, with a remarkable possible reversal of the TCA cycle. The mutant and the wild-type both showed homeostatic behaviour with respect

  6. 3Omics: a web-based systems biology tool for analysis, integration and visualization of human transcriptomic, proteomic and metabolomic data.

    PubMed

    Kuo, Tien-Chueh; Tian, Tze-Feng; Tseng, Yufeng Jane

    2013-07-23

    Integrative and comparative analyses of multiple transcriptomics, proteomics and metabolomics datasets require an intensive knowledge of tools and background concepts. Thus, it is challenging for users to perform such analyses, highlighting the need for a single tool for such purposes. The 3Omics one-click web tool was developed to visualize and rapidly integrate multiple human inter- or intra-transcriptomic, proteomic, and metabolomic data by combining five commonly used analyses: correlation networking, coexpression, phenotyping, pathway enrichment, and GO (Gene Ontology) enrichment. 3Omics generates inter-omic correlation networks to visualize relationships in data with respect to time or experimental conditions for all transcripts, proteins and metabolites. If only two of three omics datasets are input, then 3Omics supplements the missing transcript, protein or metabolite information related to the input data by text-mining the PubMed database. 3Omics' coexpression analysis assists in revealing functions shared among different omics datasets. 3Omics' phenotype analysis integrates Online Mendelian Inheritance in Man with available transcript or protein data. Pathway enrichment analysis on metabolomics data by 3Omics reveals enriched pathways in the KEGG/HumanCyc database. 3Omics performs statistical Gene Ontology-based functional enrichment analyses to display significantly overrepresented GO terms in transcriptomic experiments. Although the principal application of 3Omics is the integration of multiple omics datasets, it is also capable of analyzing individual omics datasets. The information obtained from the analyses of 3Omics in Case Studies 1 and 2 are also in accordance with comprehensive findings in the literature. 3Omics incorporates the advantages and functionality of existing software into a single platform, thereby simplifying data analysis and enabling the user to perform a one-click integrated analysis. Visualization and analysis results are

  7. Metabolomic analysis for the study of maturation in pediatrics: Effect of confounding factors in a pilot study.

    PubMed

    Blanco, María Encarnación; González, Oskar; Albóniga, Oihane Elena; Alonso, María Luz; Alonso, Rosa María

    2017-09-01

    A pilot study for the investigation of the maturation grade of children has been carried out using plasma samples already analyzed in a previous pharmacokinetic study. By using a meticulous data treatment, possible confounding factors that may hinder the obtained results were identified. By doing so, it was possible to obtain enough evidence to support the feasibility of performing a larger study eluding some unwanted variability and minimizing not only the number of subjects involved but also the time and money spent on the study. In the pilot study the metabolic profiles obtained using UHPLC-TOF-MS technique of plasma samples from 14 newborn piglets (<5 days) were compared with the plasma profiles of 16 infant piglets (8 weeks). The type of anaesthesia administered, gender, vein or artery of blood extraction and time of sampling were studied as possible confounding factors. Unsupervised analysis by principal component analysis (PCA) clearly differentiated between neonates and children. During the data treatment and the statistical analysis, the effect of confounding factors such as the anaesthetic regimen was identified and removed, while the effect of the rest of studied factors was not considered relevant, and the discrimination between the two groups based on the age was maintained. This allowed extracting relevant conclusions for a future study design while avoiding the unnecessary sacrifice of animals. Furthermore, the results obtained demonstrate the utility of metabolomics in the discovery of novel putative plasma biomarkers such as carnitines that can be correlated with the maturation state of paediatric patients. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Integrated proteomic and metabolomic analysis of an artificial microbial community for two-step production of vitamin C.

    PubMed

    Ma, Qian; Zhou, Jian; Zhang, Weiwen; Meng, Xinxin; Sun, Junwei; Yuan, Ying-Jin

    2011-01-01

    An artificial microbial community consisted of Ketogulonicigenium vulgare and Bacillus megaterium has been used in industry to produce 2-keto-gulonic acid (2-KGA), the precursor of vitamin C. During the mix culture fermentation process, sporulation and cell lysis of B. megaterium can be observed. In order to investigate how these phenomena correlate with 2-KGA production, and to explore how two species interact with each other during the fermentation process, an integrated time-series proteomic and metabolomic analysis was applied to the system. The study quantitatively identified approximate 100 metabolites and 258 proteins. Principal Component Analysis of all the metabolites identified showed that glutamic acid, 5-oxo-proline, L-sorbose, 2-KGA, 2, 6-dipicolinic acid and tyrosine were potential biomarkers to distinguish the different time-series samples. Interestingly, most of these metabolites were closely correlated with the sporulation process of B. megaterium. Together with several sporulation-relevant proteins identified, the results pointed to the possibility that Bacillus sporulation process might be important part of the microbial interaction. After sporulation, cell lysis of B. megaterium was observed in the co-culture system. The proteomic results showed that proteins combating against intracellular reactive oxygen stress (ROS), and proteins involved in pentose phosphate pathway, L-sorbose pathway, tricarboxylic acid cycle and amino acids metabolism were up-regulated when the cell lysis of B. megaterium occurred. The cell lysis might supply purine substrates needed for K. vulgare growth. These discoveries showed B. megaterium provided key elements necessary for K. vulgare to grow better and produce more 2-KGA. The study represents the first attempt to decipher 2-KGA-producing microbial communities using quantitative systems biology analysis.

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

    PubMed Central

    Chen, Der-Yuan; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting

    2016-01-01

    Objective 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. Methods 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. Results 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). Conclusion 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. PMID

  10. 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.

  11. 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

  12. Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: Investigation of nicotinic acid receptor agonists

    SciTech Connect

    Zgoda-Pols, Joanna R.; Chowdhury, Swapan; Wirth, Mark; Milburn, Michael V.; Alexander, Danny C.; Alton, Kevin B.

    2011-08-15

    An investigative renal toxicity study using metabolomics was conducted with a potent nicotinic acid receptor (NAR) agonist, SCH 900424. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) techniques were used to identify small molecule biomarkers of acute kidney injury (AKI) that could aid in a better mechanistic understanding of SCH 900424-induced AKI in mice. The metabolomics study revealed 3-indoxyl sulfate (3IS) as a more sensitive marker of SCH 900424-induced renal toxicity than creatinine or urea. An LC-MS assay for quantitative determination of 3IS in mouse matrices was also developed. Following treatment with SCH 900424, 3IS levels were markedly increased in murine plasma and brain, thereby potentially contributing to renal- and central nervous system (CNS)-related rapid onset of toxicities. Furthermore, significant decrease in urinary excretion of 3IS in those animals due to compromised renal function may be associated with the elevation of 3IS in plasma and brain. These data suggest that 3IS has a potential to be a marker of renal and CNS toxicities during chemically-induced AKI in mice. In addition, based on the metabolomic analysis other statistically significant plasma markers including p-cresol-sulfate and tryptophan catabolites (kynurenate, kynurenine, 3-indole-lactate) might be of toxicological importance but have not been studied in detail. This comprehensive approach that includes untargeted metabolomic and targeted bioanalytical sample analyses could be used to investigate toxicity of other compounds that pose preclinical or clinical development challenges in a pharmaceutical discovery and development. - Research Highlights: > Nicotinic acid receptor agonist, SCH 900424, caused acute kidney injury in mice. > MS-based metabolomics was conducted to identify potential small molecule markers of renal toxicity. > 3-indoxyl-sulfate was found to be as a more sensitive marker of renal toxicity than creatinine

  13. Metabolomics for plant stress response.

    PubMed

    Shulaev, Vladimir; Cortes, Diego; Miller, Gad; Mittler, Ron

    2008-02-01

    Stress in plants could be defined as any change in growth condition(s) that disrupts metabolic homeostasis and requires an adjustment of metabolic pathways in a process that is usually referred to as acclimation. Metabolomics could contribute significantly to the study of stress biology in plants and other organisms by identifying different compounds, such as by-products of stress metabolism, stress signal transduction molecules or molecules that are part of the acclimation response of plants. These could be further tested by direct measurements, correlated with changes in transcriptome and proteome expression and confirmed by mutant analysis. In this review, we will discuss recent application of metabolomics and system biology to the area of plant stress response. We will describe approaches such as metabolic profiling and metabolic fingerprinting as well as combination of different 'omics' platforms to achieve a holistic view of the plant response stress and conduct detailed pathway analysis.

  14. Identification of novel toxicity-associated metabolites by metabolomics and mass isotopomer analysis of acetaminophen metabolism in wild-type and Cyp2e1-null mice.

    PubMed

    Chen, Chi; Krausz, Kristopher W; Idle, Jeffrey R; Gonzalez, Frank J

    2008-02-22

    CYP2E1 is recognized as the most important enzyme for initiation of acetaminophen (APAP)-induced toxicity. In this study, the resistance of Cyp2e1-null mice to APAP treatment was confirmed by comparing serum aminotransferase activities and blood urea nitrogen levels in wild-type and Cyp2e1-null mice. However, unexpectedly, profiling of major known APAP metabolites in urine and serum revealed that the contribution of CYP2E1 to APAP metabolism decreased with increasing APAP doses administered. Measurement of hepatic glutathione and hydrogen peroxide levels exposed the importance of oxidative stress in determining the consequence of APAP overdose. Subsequent metabolomic analysis was capable of constructing a principal components analysis (PCA) model that delineated a relationship between urinary metabolomes and the responses to APAP treatment. Urinary ions high in wild-type mice treated with 400 mg/kg APAP were elucidated as 3-methoxy-APAP glucuronide (VII) and three novel APAP metabolites, including S-(5-acetylamino-2-hydroxyphenyl)mercaptopyruvic acid (VI, formed by a Cys-APAP transamination reaction in kidney), 3,3'-biacetaminophen (VIII, an APAP dimer), and a benzothiazine compound (IX, originated from deacetylated APAP), through mass isotopomer analysis, accurate mass measurement, tandem mass spectrometry fragmentation, in vitro reactions, and chemical treatments. Dose-, time-, and genotype-dependent appearance of these minor APAP metabolites implied their association with the APAP-induced toxicity and potential biomarker application. Overall, the oxidative stress elicited by CYP2E1-mediated APAP metabolism might significantly contribute to APAP-induced toxicity. The combination of genetically modified animal models, mass isotopomer analysis, and metabolomics provides a powerful and efficient technical platform to characterize APAP-induced toxicity through identifying novel biomarkers and unraveling novel mechanisms.

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

    PubMed

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

    2014-08-30

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

  16. Application of a novel metabolomic approach based on atmospheric pressure photoionization mass spectrometry using flow injection analysis for the study of Alzheimer's disease.

    PubMed

    González-Domínguez, Raúl; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2015-01-01

    The use of atmospheric pressure photoionization is not widespread in metabolomics, despite its considerable potential for the simultaneous analysis of compounds with diverse polarities. This work considers the development of a novel analytical approach based on flow injection analysis and atmospheric pressure photoionization mass spectrometry for rapid metabolic screening of serum samples. Several experimental parameters were optimized, such as type of dopant, flow injection solvent, and their flows, given that a careful selection of these variables is mandatory for a comprehensive analysis of metabolites. Toluene and methanol were the most suitable dopant and flow injection solvent, respectively. Moreover, analysis in negative mode required higher solvent and dopant flows (100 µl min(-1) and 40 µl min(-1), respectively) compared to positive mode (50 µl min(-1) and 20 µl min(-1)). Then, the optimized approach was used to elucidate metabolic alterations associated with Alzheimer's disease. Thereby, results confirm the increase of diacylglycerols, ceramides, ceramide-1-phosphate and free fatty acids, indicating membrane destabilization processes, and reduction of fatty acid amides and several neurotransmitters related to impairments in neuronal transmission, among others. Therefore, it could be concluded that this metabolomic tool presents a great potential for analysis of biological samples, considering its high-throughput screening capability, fast analysis and comprehensive metabolite coverage.

  17. 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.

  18. Metabolomics in hypertension.

    PubMed

    Nikolic, Sonja B; Sharman, James E; Adams, Murray J; Edwards, Lindsay M

    2014-06-01

    Hypertension is the most prevalent chronic medical condition and a major risk factor for cardiovascular morbidity and mortality. In the majority of hypertensive cases, the underlying cause of hypertension cannot be easily identified because of the heterogeneous, polygenic and multi-factorial nature of hypertension. Metabolomics is a relatively new field of research that has been used to evaluate metabolic perturbations associated with disease, identify disease biomarkers and to both assess and predict drug safety and efficacy. Metabolomics has been increasingly used to characterize risk factors for cardiovascular disease, including hypertension, and it appears to have significant potential for uncovering mechanisms of this complex disease. This review details the analytical techniques, pre-analytical steps and study designs used in metabolomics studies, as well as the emerging role for metabolomics in gaining mechanistic insights into the development of hypertension. Suggestions as to the future direction for metabolomics research in the field of hypertension are also proposed.

  19. Optimization of harvesting, extraction, and analytical protocols for UPLC-ESI-MS-based metabolomic analysis of adherent mammalian cancer cells

    PubMed Central

    Krausz, Kristopher W.; Manna, Soumen K.; Li, Fei; Johnson, Caroline H.; Gonzalez, Frank J.

    2013-01-01

    In this study, a liquid chromatography mass spectrometry (LC/MS)-based metabolomics protocol was optimized for quenching, harvesting, and extraction of metabolites from the human pancreatic cancer cell line Panc-1. Trypsin/ethylenediaminetetraacetic acid (EDTA) treatment and cell scraping in water were compared for sample harvesting. Four different extraction methods were compared to investigate the efficiency of intracellular metabolite extraction, including pure acetonitrile, methanol, methanol/chloroform/H2O, and methanol/chloroform/acetonitrile. The separation efficiencies of hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) with UPLC-QTOF-MS were also evaluated. Global metabolomics profiles were compared; the number of total detected features and the recovery and relative extraction efficiencies of target metabolites were assessed. Trypsin/EDTA treatment caused substantial metabolite leakage proving it inadequate for metabolomics studies. Direct scraping after flash quenching with liquid nitrogen was chosen to harvest Panc-1 cells which allowed for samples to be stored before extraction. Methanol/chloroform/H2O was chosen as the optimal extraction solvent to recover the highest number of intracellular features with the best reproducibility. HILIC had better resolution for intracellular metabolites of Panc-1 cells. This optimized method therefore provides high sensitivity and reproducibility for a variety of cellular metabolites and can be applicable to further LC/MS-based global metabolomics study on Panc-1 cell lines and possibly other cancer cell lines with similar chemical and physical properties. PMID:23604415

  20. Metabolomics analysis of soy hydrolysates for the identification of productivity markers of mammalian cells for manufacturing therapeutic proteins.

    PubMed

    Richardson, Jason; Shah, Bhavana; Bondarenko, Pavel V; Bhebe, Prince; Zhang, Zhongqi; Nicklaus, Michele; Kombe, Maua C

    2015-01-01

    Soy hydrolysates are widely used as a nutrient supplement in mammalian cell culture for the production of recombinant proteins. The batch-to-batch variability of a soy hydrolysate often leads to productivity differences. This report describes our metabolomics platform, which includes a battery of LC-MS/MS modes of operation, and advanced data analysis software for automated data processing. The platform was successfully used for screening productivity markers in soy hydrolysates during the production of two therapeutic antibodies in two Chinese hamster ovary cell lines. A total of 123 soy hydrolysate batches were analyzed, from which 62 batches were used in the production runs of cell line #1 and 12 batches were used in the production runs of cell line #2. For cell line #1, out of 19 amino acids, 106 other metabolites and 4,131 peptides identified in the soy hydrolysate batches being used, several nucleosides and short hydrophobic peptides showed negative correlation with antibody titer, while ornithine, citrulline and several amino acids and organic acids correlated positively with titer. For cell line #2, only ornithine and citrulline showed strong positive correlation. When ornithine was spiked into the culture media, both cell lines demonstrated accelerated cell growth, indicating ornithine as a root cause of the performance difference. It is proposed that better soy hydrolysate performance resulted from better bacterial fermentation during the hydrolysate production. A few selected markers were used to predict the performance of other soy hydrolysate batches for cell line #1. The predicted titers agreed with the experimental values with good accuracy. © 2015 American Institute of Chemical Engineers.

  1. Metabolomic Analysis of Anti-Hypoxia and Anti-anxiety Effects of Fu Fang Jin Jing Oral Liquid

    PubMed Central

    Guan, Shuhong; Feng, Ruihong; Zhang, Hui; Liu, Qiuhong; Sun, Peng; Lin, Donghai; Zhang, Naixia; Shen, Jun

    2013-01-01

    Background Herba Rhodiolae is a traditional Chinese medicine used by the Tibetan people for treating hypoxia related diseases such as anxiety. Based on the previous work, we developed and patented an anti-anxiety herbal formula Fu Fang Jin Jing Oral Liquid (FJJOL) with Herba Rhodiolae as a chief ingredient. In this study, the anti-hypoxia and anti-anxiety effects of FJJOL in a high altitude forced-swimming mouse model with anxiety symptoms will be elucidated by NMR-based metabolomics. Methods In our experiments, the mice were divided randomly into four groups as flatland group, high altitude saline-treated group, high altitude FJJOL-treated group, and high altitude diazepam-treated group. To cause anxiety effects and hypoxic defects, a combination use of oxygen level decreasing (hypobaric cabin) and oxygen consumption increasing (exhaustive swimming) were applied to mice. After a three-day experimental handling, aqueous metabolites of mouse brain tissues were extracted and then subjected to NMR analysis. The therapeutic effects of FJJOL on the hypobaric hypoxia mice with anxiety symptoms were verified. Results Upon hypoxic exposure, both energy metabolism defects and disorders of functional metabolites in brain tissues of mice were observed. PCA, PLS-DA and OPLS-DA scatter plots revealed a clear group clustering for metabolic profiles in the hypoxia versus normoxia samples. After a three-day treatment with FJJOL, significant rescue effects on energy metabolism were detected, and levels of ATP, fumarate, malate and lactate in brain tissues of hypoxic mice recovered. Meanwhile, FJJOL also up-regulated the neurotransmitter GABA, and the improvement of anxiety symptoms was highly related to this effect. Conclusions FJJOL ameliorated hypobaric hypoxia effects by regulating energy metabolism, choline metabolism, and improving the symptoms of anxiety. The anti-anxiety therapeutic effects of FJJOL were comparable to the conventional anti-anxiety drug diazepam on the

  2. Blood-based diagnosis of Alzheimer's disease using fingerprinting metabolomics based on hydrophilic interaction liquid chromatography with mass spectrometry and multivariate statistical analysis.

    PubMed

    Inoue, Koichi; Tsuchiya, Hirofumi; Takayama, Takahiro; Akatsu, Hiroyasu; Hashizume, Yoshio; Yamamoto, Takayuki; Matsukawa, Noriyuki; Toyo'oka, Toshimasa

    2015-01-01

    Early and definitive diagnosis of Alzheimer's disease (AD) can lead to a better and more-targeted treatment and/or prevention for patients. In the diagnostic biomarkers of AD, the blood sample represents a more non-invasive, inexpensive and acceptable sources for repeated measurements than the cerebrospinal fluid. In this study, the fingerprinting metabolomics was proposed for the challenge of the blood-based diagnosis of defined AD by hydrophilic interaction liquid chromatography mass spectrometry (HILIC/MS). These plasma samples were selected from postmortem specimens based on these pathological examinations. Firstly, we compared these HILIC columns for the non-targeted metabolic assay using pooled plasma. The principal component analysis plot of these seven columns was performed using the repeatability of these chromatograms, and can be used to visualize trends in data sets by three-dimensional dispersion, contributory standard deviation and the number of detections. Based on these results, TSK-Amide 80 and TSKgel-NH₂ columns are used as a reliable HILIC/MS assay of blood-based AD metabolomics that showed metabolic profiling of the AD pathology in MS chromatograms that ranged from 1182 to 2284 compounds. A total of 54 peaks were evaluated in order to identify useful ion signal candidates using an orthogonal partial least-squares-discriminant analysis. These peaks were then specifically analyzed using the HILIC-tandem MS assay by a receiver operating characteristic curve and linear discriminant analysis for the diagnosis of the defined AD. The fingerprinting metabolomics can overcome the limitations of previous challenging blood-based diagnosis of AD, and directly evaluates the specific comparative statistical values from the raw data. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2015-04-01

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

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

    PubMed Central

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

    2017-01-01

    The muscle-specific ubiquitin ligases MuRF1, MuRF2, MuRF3 have been reported to have overlapping substrate specificities, interacting with each other as well as proteins involved in metabolism and cardiac function. In the heart, all three MuRF family proteins have proven critical to cardiac responses to ischemia and heart failure. The non-targeted metabolomics analysis of MuRF1-/-, MuRF2-/-, and MuRF3-/- hearts was initiated to investigate the hypothesis that MuRF1, MuRF2, and MuRF3 have a similarly altered metabolome, representing alterations in overlapping metabolic processes. Ventricular tissue was flash frozen and quantitatively analyzed by GC/MS using a library built upon the Fiehn GC/MS Metabolomics RTL Library. Non-targeted metabolomic analysis identified significant differences (via VIP statistical analysis) in taurine, myoinositol, and stearic acid for the three MuRF-/- phenotypes relative to their matched controls. Moreover, pathway enrichment analysis demonstrated that MuRF1-/- had significant changes in metabolite(s) involved in taurine metabolism and primary acid biosynthesis while MuRF2-/- had changes associated with ascorbic acid/aldarate metabolism (via VIP and t-test analysis vs. sibling-matched wildtype controls). By identifying the functional metabolic consequences of MuRF1, MuRF2, and MuRF3 in the intact heart, non-targeted metabolomics analysis discovered common pathways functionally affected by cardiac MuRF family proteins in vivo. These novel metabolomics findings will aid in guiding the molecular studies delineating the mechanisms that MuRF family proteins regulate metabolic pathways. Understanding these mechanism is an important key to understanding MuRF family proteins' protective effects on the heart during cardiac disease. PMID:28325996

  5. Combined stable isotope, proteomic, metabolomics, and spatial specific analysis to track carbon flow through a hypersaline phototrophic microbial mat

    NASA Astrophysics Data System (ADS)

    Moran, J.; Cory, A.; Riha, K. M.; Huang, E. L.; Gritsenko, M. A.; Kim, Y. M.; Metz, T. O.; Lipton, M. S.

    2014-12-01

    Tracking labeled substrates through microbial mat systems can help elucidate carbon dynamics, species interactions, and niche partitioning, but the inherent microbial complexity of these systems makes them difficult to probe with single analytical techniques. Here we use a combination of different tools to track three labeled substrates through a benthic phototrophic mat from Hot Lake. Hot Lake is a hypersaline, meromictic lake located in an endorheic basin in north-central Washington which, despite extreme salinity and seasonal water temperatures (> 55 ˚C), hosts dense, phototrophic benthic microbial mats. Cyanobacteria are the dominant CO2-fixing organisms in the system and we seek to understand the spatial and metabolic controls on how the carbon initially fixed by mat cyanobacteria is transferred to associated heterotrophic populations spread throughout the mat strata. We performed ex situ incubations over a complete diel cycle with 13C labeled bicarbonate, acetate, and glucose. Traditional elemental analysis IRMS provided an estimate of bulk label uptake to total biomass and showed that both bicarbonate and acetate were incorporated only during daylight while glucose uptake was nearly constant through the cycle. Spatially resolved isotope analysis using laser ablation IRMS showed distinctive patterns between the different substrates with bicarbonate having highest uptake in the top third of the mat, acetate uptake focused near the mat's center, and glucose showing similar uptake at all mat depths. Proteomic analysis showed a longer lag in substrate conversion to protein than to biomass and a distinct spike in the number of labeled peptides in the bicarbonate incubation near the end of the diel cycle. Proteomic analysis confirmed that photosynthetic organisms showed the highest rates of label conversion to protein but heterotrophic organisms also incorporated label into their peptides. Metabolomic analysis demonstrated the high conversion of organic substrates

  6. Metabolomics-guided analysis of isocoumarin production by Streptomyces species MBT76 and biotransformation of flavonoids and phenylpropanoids.

    PubMed

    Wu, Changsheng; Zhu, Hua; van Wezel, Gilles P; Choi, Young Hae

    2016-01-01

    Actinomycetes produce the majority of the antibiotics currently in clinical use. The efficiency of antibiotic production is affected by multiple factors such as nutrients, pH, temperature and growth phase. Finding the optimal harvesting time is crucial for successful isolation of the desired bioactive metabolites from actinomycetes, but for this conventional chemical analysis has limitations due to the metabolic complexity. This study explores the utility of NMR-based metabolomics for (1) optimizing fermentation time for the production of known and/or unknown bioactive compounds produced by actinomycetes; (2) elucidating the biosynthetic pathway for microbial natural products; and (3) facilitating the biotransformation of nature-abundant chemicals. The aqueous culture broth of actinomycete Streptomyces sp. MBT76 was harvested every 24 h for 5 days and each broth was extracted by ethyl acetate. The extracts were analyzed by (1)H NMR spectroscopy and the data were compared with principal component analysis (PCA) and orthogonal projection to latent structures (OPLS) analysis. Antimicrobial test were performed by agar diffusion assay. The secondary metabolites production by Streptomyces sp. MBT76 was growth phase-dependent. Isocoumarins (1-9), undecylprodiginine (10), streptorubin B (11), 1H-pyrrole-2-carboxamide (12), acetyltryptamine (13), and fervenulin (14) were identified, and their optimal production time was determined in crude extracts without tedious chromatographic fractionation. Of these compounds, 5,6,7,8-tetramethoxyl-3-methyl-isocoumarin (9) is as a novel compound, which was most likely synthesized by a type I iterative polyketide synthase (PKS) encoded by the icm gene cluster. Multivariate data analysis of the (1)H NMR spectra showed that acetyltryptamine (13) and tri-methoxylated isocoumarins (7 and 8) were the major determinants of antibiotic activity during later time points. The methoxylation was exploited to allow bioconversion of exogenously

  7. 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.

  8. 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

  9. Analysis of Sub-Lethal Toxicity of Perfluorooctane Sulfonate (PFOS) to Daphnia magna Using 1H Nuclear Magnetic Resonance-Based Metabolomics

    PubMed Central

    Kariuki, Martha N.; Nagato, Edward G.; Lankadurai, Brian P.; Simpson, André J.; Simpson, Myrna J.

    2017-01-01

    1H nuclear magnetic resonance (NMR)-based metabolomics was used to characterize the response of Daphnia magna after sub-lethal exposure to perfluorooctane sulfonate (PFOS), a commonly found environmental pollutant in freshwater ecosystems. Principal component analysis (PCA) scores plots showed significant separation in the exposed samples relative to the controls. Partial least squares (PLS) regression analysis revealed a strong linear correlation between the overall metabolic response and PFOS exposure concentration. More detailed analysis showed that the toxic mode of action is metabolite-specific with some metabolites exhibiting a non-monotonic response with higher PFOS exposure concentrations. Our study indicates that PFOS exposure disrupts various energy metabolism pathways and also enhances protein degradation. Overall, we identified several metabolites that are sensitive to PFOS exposure and may be used as bioindicators of D. magna health. In addition, this study also highlights the important utility of environmental metabolomic methods when attempting to elucidate acute and sub-lethal pollutant stressors on keystone organisms such as D. magna. PMID:28420092

  10. Plasma metabolic profiling analysis of cyclophosphamide-induced cardiotoxicity using metabolomics coupled with UPLC/Q-TOF-MS and ROC curve.

    PubMed

    Yin, Jia; Xie, Jiabin; Guo, Xuejun; Ju, Liang; Li, Yubo; Zhang, Yanjun

    2016-10-15

    Cyclophosphamide (CY) is a commonly-used nitrogen mustard alkylating agent, but its clinical application is severely limited by its cardiotoxicity. Since the development of metabolomics, the change of metabolite profiles caused by cyclophosphamide has been studied by metabolomics and has gained much attention. In this study, we analyzed rat plasma samples collected one, three and five days after cyclophosphamide administration using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS). Multiple statistical analyses, such as principal component analysis (PCA) and partial least squares - discriminant analysis (PLS-DA), were used to examine metabolite profile changes in plasma samples in order to screen for potential cardiotoxicity biomarkers and metabolic pathways. Levels of a dozen of metabolites changed significantly in plasma from the CY-treated group after one, three, and five days compared with the control group treated with normal saline (NS). Receiver operator characteristic (ROC) curve analysis suggested that the total 16 metabolites play important roles in different times of CY-induced cardiotoxicity respectively. Our results suggest that these metabolites in linoleic acid metabolism and glycerol phospholipid metabolism may be related to CY-induced cardiotoxicity. These metabolites could act as sensitive biomarkers for CY-induced cardiotoxicity and be useful for investigating toxic mechanisms. They may also lay a foundation for clinical use of cyclophosphamide. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Detection of inborn errors of metabolism utilizing GC-MS urinary metabolomics coupled with a modified orthogonal partial least squares discriminant analysis.

    PubMed

    Yang, Qin; Lin, Shan-Shan; Yang, Jiang-Tao; Tang, Li-Juan; Yu, Ru-Qin

    2017-04-01

    GC-MS urinary metabolomic analysis coupled with chemometrics is used to detect inborn errors of metabolism (IEMs), which are genetic disorders causing severe mental and physical debility and even sudden infant death. Orthogonal partial least squares discriminant analysis (OPLS-DA) is an efficient multivariate statistical method that conducts data analysis of metabolite profiling. However, performance degradation is often observed for OPLS-DA due to increasing size and complexity of metabolomic datasets. In this study, hybrid particle swarm optimization (HPSO) is employed to modify OPLS-DA by simultaneously selecting the optimal variable subset, associated weights and the appropriate number of orthogonal components, constructing a new algorithm called HPSO-OPLSDA. Investigating two IEMs, methylmalonic acidemia (MMA) and isovaleric acidemia (IVA), results suggest that HPSO-OPLSDA can significantly outperform OPLS-DA in terms of the discrimination between disease samples and healthy controls. Moreover, main discriminative metabolites are identified by HPSO-OPLSDA to aid the clinical diagnosis of IEMs, including methylmalonic-2, methylcitric-4(1) and 3-OH-propionic-2 for MMA and isovalerylglycine-1 for IVA.

  12. 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

  13. Metabolomics and dereplication strategies in natural products.

    PubMed

    Tawfike, Ahmed Fares; Viegelmann, Christina; Edrada-Ebel, Ruangelie

    2013-01-01

    Metabolomic methods can be utilized to screen diverse biological sources of potentially novel and sustainable sources of antibiotics and pharmacologically-active drugs. Dereplication studies by high resolution Fourier transform mass spectrometry coupled to liquid chromatography (LC-HRFTMS) and nuclear magnetic resonance (NMR) spectroscopy can establish the chemical profile of endophytic and/or endozoic microbial extracts and their plant or animal sources. Identifying the compounds of interest at an early stage will aid in the isolation of the bioactive components. Therefore metabolite profiling is important for functional genomics and in the search for new pharmacologically active compounds. Using the tools of metabolomics through the employment of LC-HRFTMS as well as high resolution NMR will be a very efficient approach. Metabolomic profiling has found its application in screening extracts of macroorganisms as well as in the isolation and cultivation of suspected microbial producers of bioactive natural products.Metabolomics is being applied to identify and biotechnologically optimize the production of pharmacologically active secondary metabolites. The links between metabolome evolution during optimization and processing factors can be identified through metabolomics. Information obtained from a metabolomics dataset can efficiently establish cultivation and production processes at a small scale which will be finally scaled up to a fermenter system, while maintaining or enhancing synthesis of the desired compounds. MZmine (BMC Bioinformatics 11:395-399, 2010; http://mzmine.sourceforge.net/download.shtml ) and SIEVE ( http://www.vastscientific.com/resources/index.html ; Rapid Commun Mass Spectrom 22:1912-1918, 2008) softwares are utilized to perform differential analysis of sample populations to find significant expressed features of complex biomarkers between parameter variables. Metabolomes are identified with the aid of existing high resolution MS and NMR

  14. Quantitative analysis of amino acids and acylcarnitines combined with untargeted metabolomics using ultra-high performance liquid chromatography and quadrupole time-of-flight mass spectrometry.

    PubMed

    Roy, Cynthia; Tremblay, Pierre-Yves; Bienvenu, Jean-François; Ayotte, Pierre

    2016-08-01

    Metabolomics is an "omic" technique being increasingly used in epidemiological and clinical studies. We developed a method combining untargeted metabolomics with the quantitative determination of eight amino acids (AA) and eight acylcarnitines (AC) in plasma using ultra-high pressure liquid chromatography (UHPLC), electrospray ionization (ESI) and quadrupole time-of-flight mass spectrometry (QTOFMS). Separation of metabolites is performed by ion-pair reverse phase UHPLC using a HSS T3 column (2.1×100mm, 100Å, 1.8μm particle size) and formic acid-ammonium acetate-heptafluorobutyric acid in water and formic acid-ammonium acetate in methanol as mobile phases. Metabolite identification and quantification are achieved using a QTOFMS operating in ESI-positive and full-scan mode along with MS(E) acquisition of fragmentation patterns. Targeted metabolites are quantified using the appropriate labeled standards and include branched-chain AA (leucine, isoleucine, valine), aromatic AA (phenylalanine, tyrosine) as well as acetylcarnitine and propionylcarnitine, which have been identified as biomarkers of future cardiometabolic disease risk. The inter-day precision (relative standard deviation) for the targeted method was <15% for all but one metabolite and accuracy (bias) of amino acids ranged from 0.5% to 13.9% using SRM 1950 as the external standard. Untargeted metabolomics in 30 plasma samples from the general Canadian population revealed 5018 features, of which 48 metabolites were identified using the MZmine 2.19 software including 23 by our in-house library that comprises 671 annotated metabolites. SRM 1950 analysis revealed 11,684 features, among which 154 metabolites were identified. Our method is currently applied in several epidemiological studies to better characterize cardiometabolic diseases and identify new biomarkers for disease prevention. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Proof of concept of microbiome-metabolome analysis and delayed gluten exposure on celiac disease autoimmunity in genetically at-risk infants.

    PubMed

    Sellitto, Maria; Bai, Guoyun; Serena, Gloria; Fricke, W Florian; Sturgeon, Craig; Gajer, Pawel; White, James R; Koenig, Sara S K; Sakamoto, Joyce; Boothe, Dustin; Gicquelais, Rachel; Kryszak, Deborah; Puppa, Elaine; Catassi, Carlo; Ravel, Jacques; Fasano, Alessio

    2012-01-01

    Celiac disease (CD) is a unique autoimmune disorder in which the genetic factors (DQ2/DQ8) and the environmental trigger (gluten) are known and necessary but not sufficient for its development. Other environmental components contributing to CD are poorly understood. Studies suggest that aspects of gluten intake might influence the risk of CD occurrence and timing of its onset, i.e., the amount and quality of ingested gluten, together with the pattern of infant feeding and the age at which gluten is introduced in the diet. In this study, we hypothesize that the intestinal microbiota as a whole rather than specific infections dictates the switch from tolerance to immune response in genetically susceptible individuals. Using a sample of infants genetically at risk of CD, we characterized the longitudinal changes in the microbial communities that colonize infants from birth to 24 months and the impact of two patterns of gluten introduction (early vs. late) on the gut microbiota and metabolome, and the switch from gluten tolerance to immune response, including onset of CD autoimmunity. We show that infants genetically susceptible to CD who are exposed to gluten early mount an immune response against gluten and develop CD autoimmunity more frequently than at-risk infants in which gluten exposure is delayed until 12 months of age. The data, while derived from a relatively small number of subjects, suggest differences between the developing microbiota of infants with genetic predisposition for CD and the microbiota from infants with a non-selected genetic background, with an overall lack of bacteria of the phylum Bacteriodetes along with a high abundance of Firmicutes and microbiota that do not resemble that of adults even at 2 years of age. Furthermore, metabolomics analysis reveals potential biomarkers for the prediction of CD. This study constitutes a definite proof-of-principle that these combined genomic and metabolomic approaches will be key to deciphering the role

  16. Technical Challenges in Mass Spectrometry-Based Metabolomics

    PubMed Central

    Matsuda, Fumio

    2016-01-01

    Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10–100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism. PMID:27900235

  17. Evaluation of automated sample preparation, retention time locked gas chromatography-mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species.

    PubMed

    Gu, Qun; David, Frank; Lynen, Frédéric; Rumpel, Klaus; Dugardeyn, Jasper; Van Der Straeten, Dominique; Xu, Guowang; Sandra, Pat

    2011-05-27

    In this paper, automated sample preparation, retention time locked gas chromatography-mass spectrometry (GC-MS) and data analysis methods for the metabolomics study were evaluated. A miniaturized and automated derivatisation method using sequential oximation and silylation was applied to a polar extract of 4 types (2 types×2 ages) of Arabidopsis thaliana, a popular model organism often used in plant sciences and genetics. Automation of the derivatisation process offers excellent repeatability, and the time between sample preparation and analysis was short and constant, reducing artifact formation. Retention time locked (RTL) gas chromatography-mass spectrometry was used, resulting in reproducible retention times and GC-MS profiles. Two approaches were used for data analysis. XCMS followed by principal component analysis (approach 1) and AMDIS deconvolution combined with a commercially available program (Mass Profiler Professional) followed by principal component analysis (approach 2) were compared. Several features that were up- or down-regulated in the different types were detected.

  18. Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

    PubMed

    Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

    2016-09-30

    The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by (1)H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity

  19. Transcriptomic and Metabolomic Analysis Revealed Multifaceted Effects of Phage Protein Gp70.1 on Pseudomonas aeruginosa

    PubMed Central

    Zhao, Xia; Chen, Canhuang; Jiang, Xingyu; Shen, Wei; Huang, Guangtao; Le, Shuai; Lu, Shuguang; Zou, Lingyun; Ni, Qingshan; Li, Ming; Zhao, Yan; Wang, Jing; Rao, Xiancai; Hu, Fuquan; Tan, Yinling

    2016-01-01

    The impact of phage infection on the host cell is severe. In order to take over the cellular machinery, some phage proteins were produced to shut off the host biosynthesis early in the phage infection. The discovery and identification of these phage-derived inhibitors have a significant prospect of application in antibacterial treatment. This work presented a phage protein, gp70.1, with non-specific inhibitory effects on Pseudomonas aeruginosa and Escherichia coli. Gp70.1 was encoded by early gene – orf 70.1 from P. aeruginosa phage PaP3. The P. aeruginosa with a plasmid encoding gp70.1 showed with delayed growth and had the appearance of a small colony. The combination of multifaceted analysis including microarray-based transcriptomic analysis, RT-qPCR, nuclear magnetic resonance (NMR) spectroscopy-based metabolomics and phenotype experiments were performed to investigate the effects of gp70.1 on P. aeruginosa. A total of 178 genes of P. aeruginosa mainly involved in extracellular function and metabolism were differentially expressed in the presence of gp70.1 at three examined time points. Furthermore, our results indicated that gp70.1 had an extensive impact on the extracellular phenotype of P. aeruginosa, such as motility, pyocyanin, extracellular protease, polysaccharide, and cellulase. For the metabolism of P. aeruginosa, the main effect of gp70.1 was the reduction of amino acid consumption. Finally, the RNA polymerase sigma factor RpoS was identified as a potential cellular target of gp70.1. Gp70.1 was the first bacterial inhibitor identified from Pseudomonas aeruginosa phage PaP3. It was also the first phage protein that interacted with the global regulator RpoS of bacteria. Our results indicated the potential value of gp70.1 in antibacterial applications. This study preliminarily revealed the biological function of gp70.1 and provided a reference for the study of other phage genes sharing similarities with orf70.1. PMID:27725812

  20. 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.

  1. Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis

    PubMed Central

    Bielecka, Monika; Watanabe, Mutsumi; Morcuende, Rosa; Scheible, Wolf-Rüdiger; Hawkesford, Malcolm J.; Hesse, Holger; Hoefgen, Rainer

    2015-01-01

    Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using ‘omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes. PMID:25674096

  2. Metabolome Analysis of Oryza sativa (Rice) Using Liquid Chromatography-Mass Spectrometry for Characterizing Organ Specificity of Flavonoids with Anti-inflammatory and Anti-oxidant Activity.

    PubMed

    Yang, Zhigang; Nakabayashi, Ryo; Mori, Tetsuya; Takamatsu, Satoshi; Kitanaka, Susumu; Saito, Kazuki

    2016-01-01

    Oryza sativa L. (rice) is an important staple crop across the world. In the previous study, we identified 36 specialized (secondary) metabolites including 28 flavonoids. In the present study, a metabolome analysis using liquid chromatography-mass spectrometry was conducted on the leaf, bran, and brown and polished rice grains to better understand the distribution of these metabolites. Principal component analysis using the metabolome data clearly characterized the accumulation patterns of the metabolites. Flavonoids, e.g., tricin, tricin 7-O-rutinoside, and tricin 7-O-β-D-glucopyranoside, were mainly present in the leaf and bran but not in the polished grain. In addition, anti-inflammatory and anti-oxidant activity of the metabolites were assayed in vitro. Tricin 4'-O-(erythro-β-guaiacylglyceryl)ether and isoscoparin 2″-O-(6‴-(E)-feruloyl)-glucopyranoside showed the strongest activity for inhibiting nitric oxide (NO) production and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging, respectively.

  3. Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis.

    PubMed

    Bielecka, Monika; Watanabe, Mutsumi; Morcuende, Rosa; Scheible, Wolf-Rüdiger; Hawkesford, Malcolm J; Hesse, Holger; Hoefgen, Rainer

    2014-01-01

    Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using 'omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes.

  4. Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis

    PubMed Central

    Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

    2016-01-01

    In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as “responding biomarkers” by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress. PMID:27171077

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

    PubMed

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

    2017-03-03

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

  6. Live-cell high resolution magic angle spinning magnetic resonance spectroscopy for in vivo analysis of Pseudomonas aeruginosa metabolomics

    PubMed Central

    RIGHI, VALERIA; CONSTANTINOU, CATERINA; KESARWANI, MEENU; RAHME, LAURENCE G.; TZIKA, ARIA A.

    2013-01-01

    Pseudomonas aeruginosa (PA) is a pathogenic gram-negative bacterium that is widespread in nature, inhabiting soil, water, plants and animals. PA is a prevalent cause of deleterious human infections, particularly in patients whose host defense mechanisms have been compromised. Metabolomics is an important tool used to study host-pathogen interactions and to identify novel therapeutic targets and corresponding compounds. The aim of the present study was to report the metabolic profile of live PA bacteria using in vivo high-resolution magic angle spinning (HRMAS) nuclear magnetic resonance spectroscopy (NMR), in combination with 1- and 2-dimensional HRMAS NMR. This methodology provides a new and powerful technique to rapidly interrogate the metabolome of intact bacterial cells and has several advantages over traditional techniques that identify metabolome components from disrupted cells. Furthermore, application of multidimensional HRMAS NMR, in combination with the novel technique total through-Bond correlation Spectroscopy (TOBSY), is a promising approach that may be used to obtain in vivo metabolomics information from intact live bacterial cells and can mediate such analyses in a short period of time. Moreover, HRMAS 1H NMR enables the investigation of the associations between metabolites and cell processes. In the present study, we detected and quantified several informative metabolic molecules in live PA cells, including N-acetyl, betaine, citrulline, alanine and glycine, which are important in peptidoglycan synthesis. The results provided a complete metabolic profile of PA for future studies of PA clinical isolates and mutants. In addition, this in vivo NMR biomedical approach might have clinical utility and should prove useful in gene function validation, the study of pathogenetic mechanisms, the classification of microbial strains into functional/clinical groups, the testing of anti-bacterial agents and the determination of metabolic profiles of bacterial

  7. Accelerating analysis for metabolomics, drugs and their metabolites in biological samples using multidimensional gas chromatography.

    PubMed

    Mitrevski, Blagoj S; Kouremenos, Konstantinos A; Marriott, Philip J

    2009-05-01

    Gas chromatography (GC) with mass spectrometry (MS) is one of the great enablin