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Sample records for metabolome

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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. PMID:25344987

  6. Metabolomics in multiple sclerosis.

    PubMed

    Bhargava, Pavan; Calabresi, Peter A

    2016-04-01

    Multiple sclerosis (MS) is a chronic demyelinating disorder of the central nervous system with inflammatory and degenerative components. The cause of MS remains unknown although genetic and environmental factors appear to play a role in its etiopathogenesis. Metabolomics is a new "omics" technology that aims at measuring small molecules in various biological matrices and can provide information that is not readily obtained from genomics, transcriptomics, or proteomics. Currently, several different analytical platforms exist for metabolomics, and both untargeted and targeted approaches are being employed. Methods of analysis of metabolomics data are also being developed and no consensus currently exists on the optimal approach to analysis and interpretation of these data. Metabolomics has the potential to provide putative biomarkers, insights into the pathophysiology of the disease, and to aid in precision medicine for patients with MS. PMID:26754801

  7. The human serum metabolome

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 i...

  8. Multivariate Analysis in Metabolomics

    PubMed Central

    Worley, Bradley; Powers, Robert

    2015-01-01

    Metabolomics aims to provide a global snapshot of all small-molecule metabolites in cells and biological fluids, free of observational biases inherent to more focused studies of metabolism. However, the staggeringly high information content of such global analyses introduces a challenge of its own; efficiently forming biologically relevant conclusions from any given metabolomics dataset indeed requires specialized forms of data analysis. One approach to finding meaning in metabolomics datasets involves multivariate analysis (MVA) methods such as principal component analysis (PCA) and partial least squares projection to latent structures (PLS), where spectral features contributing most to variation or separation are identified for further analysis. However, as with any mathematical treatment, these methods are not a panacea; this review discusses the use of multivariate analysis for metabolomics, as well as common pitfalls and misconceptions. PMID:26078916

  9. COnsortium of METabolomics Studies (COMETS)

    Cancer.gov

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

  10. Metabolomics in Newborns.

    PubMed

    Noto, Antonio; Fanos, Vassilios; Dessì, Angelica

    2016-01-01

    Metabolomics is the quantitative analysis of a large number of low molecular weight metabolites that are intermediate or final products of all the metabolic pathways in a living organism. Any metabolic profiles detectable in a human biological fluid are caused by the interaction between gene expression and the environment. The metabolomics approach offers the possibility to identify variations in metabolite profile that can be used to discriminate disease. This is particularly important for neonatal and pediatric studies especially for severe ill patient diagnosis and early identification. This property is of a great clinical importance in view of the newer definitions of health and disease. This review emphasizes the workflow of a typical metabolomics study and summarizes the latest results obtained in neonatal studies with particular interest in prematurity, intrauterine growth retardation, inborn errors of metabolism, perinatal asphyxia, sepsis, necrotizing enterocolitis, kidney disease, bronchopulmonary dysplasia, and cardiac malformation and dysfunction. PMID:27117660

  11. 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.

  12. Metabolomics and Renal Disease

    PubMed Central

    Rhee, Eugene P.

    2015-01-01

    Purpose of review This review summarizes recent metabolomics studies of renal disease, outlining some of the limitations of the literature to date. Recent findings The application of metabolomics in nephrology research has expanded from initial analyses of uremia to include both cross-sectional and longitudinal studies of earlier stages of kidney disease. Although these studies have nominated several potential markers of incident CKD and CKD progression, lack of overlap in metabolite coverage has limited the ability to synthesize results across groups. Further, direct examination of renal metabolite handling has underscored the substantial impact kidney function has on these potential markers (and many other circulating metabolites). In experimental studies, metabolomics has been used to identify a signature of decreased mitochondrial function in diabetic nephropathy and a preference for aerobic glucose metabolism in PKD; in each case, these studies have outlined novel therapeutic opportunities. Finally, as a complement to the longstanding interest in renal metabolite clearance, the microbiome has been increasingly recognized as the source of many plasma metabolites, including some with potential functional relevance to CKD and its complications. Summary The high-throughput, high-resolution phenotyping enabled by metabolomics technologies has begun to provide insight on renal disease in clinical, physiologic, and experimental contexts. PMID:26050125

  13. Metabolomics in transfusion medicine.

    PubMed

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

    2016-04-01

    Biochemical investigations on the regulatory mechanisms of red blood cell (RBC) and platelet (PLT) metabolism have fostered a century of advances in the field of transfusion medicine. Owing to these advances, storage of RBCs and PLT concentrates has become a lifesaving practice in clinical and military settings. There, however, remains room for improvement, especially with regard to the introduction of novel storage and/or rejuvenation solutions, alternative cell processing strategies (e.g., pathogen inactivation technologies), and quality testing (e.g., evaluation of novel containers with alternative plasticizers). Recent advancements in mass spectrometry-based metabolomics and systems biology, the bioinformatics integration of omics data, promise to speed up the design and testing of innovative storage strategies developed to improve the quality, safety, and effectiveness of blood products. Here we review the currently available metabolomics technologies and briefly describe the routine workflow for transfusion medicine-relevant studies. The goal is to provide transfusion medicine experts with adequate tools to navigate through the otherwise overwhelming amount of metabolomics data burgeoning in the field during the past few years. Descriptive metabolomics data have represented the first step omics researchers have taken into the field of transfusion medicine. However, to up the ante, clinical and omics experts will need to merge their expertise to investigate correlative and mechanistic relationships among metabolic variables and transfusion-relevant variables, such as 24-hour in vivo recovery for transfused RBCs. Integration with systems biology models will potentially allow for in silico prediction of metabolic phenotypes, thus streamlining the design and testing of alternative storage strategies and/or solutions. PMID:26662506

  14. 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

  15. 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

  16. LC-MS-based metabolomics

    PubMed Central

    Zhou, Bin; Xiao, Jun Feng; Tuli, Leepika

    2013-01-01

    Metabolomics aims at identification and quantitation of small molecules involved in metabolic reactions. LC-MS has enjoyed a growing popularity as the platform for metabolomic studies due to its high throughput, soft ionization, and good coverage of metabolites. The success of LC-MS-based metabolomic study often depends on multiple experimental, analytical, and computational steps. This review presents a workflow of a typical LC-MS-based metabolomic analysis for identification and quantitation of metabolites indicative of biological/environmental perturbations. Challenges and current solutions in each step of the workflow are reviewed. The review intends to help investigators understand the challenges in metabolomic studies and to determine appropriate experimental, analytical, and computational methods to address these challenges. PMID:22041788

  17. Metabolomics of Genetically Modified Crops

    PubMed Central

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

    2014-01-01

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

  18. Metabolomics of genetically modified crops.

    PubMed

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

    2014-01-01

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

  19. Metabolomics in diabetic complications.

    PubMed

    Filla, Laura A; Edwards, James L

    2016-04-22

    With a global prevalence of 9%, diabetes is the direct cause of millions of deaths each year and is quickly becoming a health crisis. Major long-term complications of diabetes arise from persistent oxidative stress and dysfunction in multiple metabolic pathways. The most serious complications involve vascular damage and include cardiovascular disease as well as microvascular disorders such as nephropathy, neuropathy, and retinopathy. Current clinical analyses like glycated hemoglobin and plasma glucose measurements hold some value as prognostic indicators of the severity of complications, but investigations into the underlying pathophysiology are still lacking. Advancements in biotechnology hold the key to uncovering new pathways and establishing therapeutic targets. Metabolomics, the study of small endogenous molecules, is a powerful toolset for studying pathophysiological processes and has been used to elucidate metabolic signatures of diabetes in various biological systems. Current challenges in the field involve correlating these biomarkers to specific complications to provide a better prediction of future risk and disease progression. This review will highlight the progress that has been made in the field of metabolomics including technological advancements, the identification of potential biomarkers, and metabolic pathways relevant to macro- and microvascular diabetic complications. PMID:26891794

  20. Computational approaches for systems metabolomics.

    PubMed

    Krumsiek, Jan; Bartel, Jörg; Theis, Fabian J

    2016-06-01

    Systems genetics is defined as the simultaneous assessment and analysis of multi-omics datasets. In the past few years, metabolomics has been established as a robust tool describing an important functional layer in this approach. The metabolome of a biological system represents an integrated state of genetic and environmental factors and has been referred to as a 'link between genotype and phenotype'. In this review, we summarize recent progresses in statistical analysis methods for metabolomics data in combination with other omics layers. We put a special focus on complex, multivariate statistical approaches as well as pathway-based and network-based analysis methods. Moreover, we outline current challenges and pitfalls of metabolomics-focused multi-omics analyses and discuss future steps for the field. PMID:27135552

  1. Understanding Metabolomics in Biomedical Research

    PubMed Central

    Kim, Su Jung; Kim, Su Hee; Kim, Ji Hyun; Hwang, Shin

    2016-01-01

    The term "omics" refers to any type of specific study that provides collective information on a biological system. Representative omics includes genomics, proteomics, and metabolomics, and new omics is constantly being added, such as lipidomics or glycomics. Each omics technique is crucial to the understanding of various biological systems and complements the information provided by the other approaches. The main strengths of metabolomics are that metabolites are closely related to the phenotypes of living organisms and provide information on biochemical activities by reflecting the substrates and products of cellular metabolism. The transcriptome does not always correlate with the proteome, and the translated proteome might not be functionally active. Therefore, their changes do not always result in phenotypic alterations. Unlike the genome or proteome, the metabolome is often called the molecular phenotype of living organisms and is easily translated into biological conditions and disease states. Here, we review the general strategies of mass spectrometry-based metabolomics. Targeted metabolome or lipidome analysis is discussed, as well as nontargeted approaches, with a brief explanation of the advantages and disadvantages of each platform. Biomedical applications that use mass spectrometry-based metabolomics are briefly introduced. PMID:26676338

  2. Metabolomics: moving towards personalized medicine

    PubMed Central

    Baraldi, Eugenio; Carraro, Silvia; Giordano, Giuseppe; Reniero, Fabiano; Perilongo, Giorgio; Zacchello, Franco

    2009-01-01

    In many fields of medicine there is a growing interest in characterizing diseases at molecular level with a view to developing an individually tailored therapeutic approach. Metabolomics is a novel area that promises to contribute significantly to the characterization of various disease phenotypes and to the identification of personal metabolic features that can predict response to therapies. Based on analytical platforms such as mass spectrometry or NMR-based spectroscopy, the metabolomic approach enables a comprehensive overview of the metabolites, leading to the characterization of the metabolic fingerprint of a given sample. These metabolic fingerprints can then be used to distinguish between different disease phenotypes and to predict a drug's effectiveness and/or toxicity. Several studies published in the last few years applied the metabolomic approach in the field of pediatric medicine. Being a highly informative technique that can be used on samples collected non-invasively (e.g. urine or exhaled breath condensate), metabolomics has appeal for the study of pediatric diseases. Here we present and discuss the pediatric clinical studies that have taken the metabolomic approach. PMID:19852788

  3. Metabolomics techniques in nanotoxicology studies.

    PubMed

    Schnackenberg, Laura K; Sun, Jinchun; Beger, Richard D

    2012-01-01

    The rapid growth in the development of nanoparticles for uses in a variety of applications including targeted drug delivery, cancer therapy, imaging, and as biological sensors has led to questions about potential toxicity of such particles to humans. High-throughput methods are necessary to evaluate the potential toxicity of nanoparticles. The omics technologies are particularly well suited to evaluate toxicity in both in vitro and in vivo systems. Metabolomics, specifically, can rapidly screen for biomarkers related to predefined pathways or processes in biofluids and tissues. Specifically, oxidative stress has been implicated as a potential mechanism of toxicity in nanoparticles and is generally difficult to measure by conventional methods. Furthermore, metabolomics can provide mechanistic insight into nanotoxicity. This chapter focuses on the application of both LC/MS and NMR-based metabolomics approaches to study the potential toxicity of nanoparticles. PMID:22975962

  4. YMDB: the Yeast Metabolome Database.

    PubMed

    Jewison, Timothy; Knox, Craig; Neveu, Vanessa; Djoumbou, Yannick; Guo, An Chi; Lee, Jacqueline; Liu, Philip; Mandal, Rupasri; Krishnamurthy, Ram; Sinelnikov, Igor; Wilson, Michael; Wishart, David S

    2012-01-01

    The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated 'metabolomic' database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry. PMID:22064855

  5. Contributions from metabolomics to fish research.

    PubMed

    Samuelsson, Linda M; Larsson, D G Joakim

    2008-10-01

    Metabolomics is a systems approach to studying the small, endogenous metabolites in an organ, biofluid or whole organism. It can be used as a screening tool for metabolite profiling, or to detect changes in the metabolome brought on by external or internal stressors. The purpose of this review is to summarize and evaluate the information obtained from the application of metabolomics in fish research and to discuss its future potential. It is already clear that metabolomics has contributed new knowledge about fish in areas such as basic physiology and development, disease, water pollution and aspects concerning fish as foodstuffs. PMID:19082135

  6. Metabolomic assessment of embryo viability.

    PubMed

    Uyar, Asli; Seli, Emre

    2014-03-01

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

  7. HMDB: the Human Metabolome Database

    PubMed Central

    Wishart, David S.; Tzur, Dan; Knox, Craig; Eisner, Roman; Guo, An Chi; Young, Nelson; Cheng, Dean; Jewell, Kevin; Arndt, David; Sawhney, Summit; Fung, Chris; Nikolai, Lisa; Lewis, Mike; Coutouly, Marie-Aude; Forsythe, Ian; Tang, Peter; Shrivastava, Savita; Jeroncic, Kevin; Stothard, Paul; Amegbey, Godwin; Block, David; Hau, David. D.; Wagner, James; Miniaci, Jessica; Clements, Melisa; Gebremedhin, Mulu; Guo, Natalie; Zhang, Ying; Duggan, Gavin E.; MacInnis, Glen D.; Weljie, Alim M.; Dowlatabadi, Reza; Bamforth, Fiona; Clive, Derrick; Greiner, Russ; Li, Liang; Marrie, Tom; Sykes, Brian D.; Vogel, Hans J.; Querengesser, Lori

    2007-01-01

    The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at: PMID:17202168

  8. HMDB: the Human Metabolome Database.

    PubMed

    Wishart, David S; Tzur, Dan; Knox, Craig; Eisner, Roman; Guo, An Chi; Young, Nelson; Cheng, Dean; Jewell, Kevin; Arndt, David; Sawhney, Summit; Fung, Chris; Nikolai, Lisa; Lewis, Mike; Coutouly, Marie-Aude; Forsythe, Ian; Tang, Peter; Shrivastava, Savita; Jeroncic, Kevin; Stothard, Paul; Amegbey, Godwin; Block, David; Hau, David D; Wagner, James; Miniaci, Jessica; Clements, Melisa; Gebremedhin, Mulu; Guo, Natalie; Zhang, Ying; Duggan, Gavin E; Macinnis, Glen D; Weljie, Alim M; Dowlatabadi, Reza; Bamforth, Fiona; Clive, Derrick; Greiner, Russ; Li, Liang; Marrie, Tom; Sykes, Brian D; Vogel, Hans J; Querengesser, Lori

    2007-01-01

    The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at: www.hmdb.ca. PMID:17202168

  9. Metabolomic Fingerprinting: Challenges and Opportunities

    PubMed Central

    Kosmides, Alyssa K.; Kamisoglu, Kubra; Calvano, Steve E.; Corbett, Siobhan A.; Androulakis, Ioannis P.

    2014-01-01

    Systems biology has primarily focused on studying genomics, transcriptomics, and proteomics and their dynamic interactions. These, however, represent only the potential for a biological outcome since the ultimate phenotype at the level of the eventually produced metabolites is not taken into consideration. The emerging field of metabolomics provides complementary guidance toward an integrated approach to this problem: It allows global profiling of the metabolites of a cell, tissue, or host and presents information on the actual end points of a response. A wide range of data collection methods are currently used and allow the extraction of global or tissue-specific metabolic profiles. The great amount and complexity of data that are collected require multivariate analysis techniques, but the increasing amount of work in this field has made easy-to-use analysis programs readily available. Metabolomics has already shown great potential in drug toxicity studies, disease modeling, and diagnostics and may be integrated with genomic and proteomic data in the future to provide in-depth understanding of systems, pathways, and their functionally dynamic interactions. In this review we discuss the current state of the art of metabolomics, its applications, and future potential. PMID:24579644

  10. Tissue-Based Metabolomics to Analyze the Breast Cancer Metabolome.

    PubMed

    Budczies, Jan; Denkert, Carsten

    2016-01-01

    Mass spectrometry and nuclear magnetic resonance-based metabolomics have been developed into mature technologies that can be utilized to analyze hundreds of biological samples in a high-throughput manner. Over the past few years, both technologies were utilized to analyze large cohorts of fresh frozen breast cancer tissues. Metabolite biomarkers were shown to separate breast cancer tissues from normal breast tissues with high sensitivity and specificity. Furthermore, the metabolome differed between hormone receptor positive (HR+) and hormone receptor negative (HR-) breast cancer, but was unchanged in HER2+ tumors compared to HER2- tumors. New metabolism-related biomarkers were discovered including the 4-aminobutyrate aminotransferase ABAT, where low mRNA expression led to an accumulation of beta-alanine and shortened relapse-free survival. The glutamate-to-glutamine ratio (GGR) represents another new biomarker that was increased in 88 % of HR- tumors and 56 % of HR+ tumors compared to normal breast tissues. The GGR might help to stratify patients for the treatment with specific glutaminase inhibitors that were recently developed and are currently being tested in phase I clinical studies. Surprisingly, 2-hydroxyglutarate (2-HG), initially found to accumulate in isocitrate dehydrogenase (IDH) mutated gliomas and leukemias and described as an oncometabolite, was detected to be drastically increased in several breast carcinomas in the absence of IDH mutations. In summary, metabolomics analysis of breast cancer tissues is a reliable method and has produced many new biological insights that may impact breast cancer diagnostics and treatment over the coming years. PMID:27557538

  11. Plant tissue extraction for metabolomics.

    PubMed

    Roessner, Ute; Dias, Daniel Anthony

    2013-01-01

    Plants are not only important producers of foods and energy storages (e.g., sugars, carbohydrates, proteins, and fats) in the form of grains, fruits, and vegetables, they also provide many valuable products to human existence including wood, fibers, oils, resins, pigments, antioxidants, and sources of medicine. Most importantly in light of this book, plants have been a source of therapeutic and health promoting compounds throughout history. This chapter describes several essential considerations for the extraction process when aiming to study plant metabolism or to characterize the chemical composition of plant originated samples using metabolomics technologies. PMID:23963900

  12. 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

  13. Metabolomics applied to the pancreatic islet

    PubMed Central

    Gooding, Jessica R.; Jensen, Mette V.; Newgard, Christopher B.

    2016-01-01

    Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. PMID:26116790

  14. Metabolomics applied to the pancreatic islet.

    PubMed

    Gooding, Jessica R; Jensen, Mette V; Newgard, Christopher B

    2016-01-01

    Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. PMID:26116790

  15. Revisiting Protocols for the NMR Analysis of Bacterial Metabolomes

    PubMed Central

    Halouska, Steven; Zhang, Bo; Gaupp, Rosmarie; Lei, Shulei; Snell, Emily; Fenton, Robert J.; Barletta, Raul G.; Somerville, Greg A.; Powers, Robert

    2015-01-01

    Over the past decade, metabolomics has emerged as an important technique for systems biology. Measuring all the metabolites in a biological system provides an invaluable source of information to explore various cellular processes, and to investigate the impact of environmental factors and genetic modifications. Nuclear magnetic resonance (NMR) spectroscopy is an important method routinely employed in metabolomics. NMR provides comprehensive structural and quantitative information useful for metabolomics fingerprinting, chemometric analysis, metabolite identification and metabolic pathway construction. A successful metabolomics study relies on proper experimental protocols for the collection, handling, processing and analysis of metabolomics data. Critically, these protocols should eliminate or avoid biologically-irrelevant changes to the metabolome. We provide a comprehensive description of our NMR-based metabolomics procedures optimized for the analysis of bacterial metabolomes. The technical details described within this manuscript should provide a useful guide to reliably apply our NMR-based metabolomics methodology to systems biology studies. PMID:26078915

  16. Emerging applications of metabolomics in drug discovery and precision medicine.

    PubMed

    Wishart, David S

    2016-07-01

    Metabolomics is an emerging 'omics' science involving the comprehensive characterization of metabolites and metabolism in biological systems. Recent advances in metabolomics technologies are leading to a growing number of mainstream biomedical applications. In particular, metabolomics is increasingly being used to diagnose disease, understand disease mechanisms, identify novel drug targets, customize drug treatments and monitor therapeutic outcomes. This Review discusses some of the latest technological advances in metabolomics, focusing on the application of metabolomics towards uncovering the underlying causes of complex diseases (such as atherosclerosis, cancer and diabetes), the growing role of metabolomics in drug discovery and its potential effect on precision medicine. PMID:26965202

  17. Applications of Metabolomics for Kidney Disease Research

    PubMed Central

    Wettersten, Hiromi I.; Weiss, Robert H.

    2013-01-01

    Metabolomics is one of the relative newcomers of the omics techniques and is likely the one most closely related to actual real-time disease pathophysiology. Hence, it has the power to yield not only specific biomarkers but also insight into the pathophysiology of disease. Despite this power, metabolomics as applied to kidney disease is still in its early adolescence and has not yet reached the mature stage of clinical application, i.e., specific biomarker and therapeutic target discovery. On the other hand, the insight gained from hints into what makes these diseases tick, as is evident from the metabolomics pathways which have been found to be altered in kidney cancer, are now beginning to bear fruit in leading to potential therapeutic targets. It is quite likely that, with greater numbers of clinical materials and with more investigators jumping into the field, metabolomics may well change the course of kidney disease research. PMID:23538740

  18. Metabolomic studies of human gastric cancer: review.

    PubMed

    Jayavelu, Naresh Doni; Bar, Nadav S

    2014-07-01

    Metabolomics is a field of study in systems biology that involves the identification and quantification of metabolites present in a biological system. Analyzing metabolic differences between unperturbed and perturbed networks, such as cancerous and non-cancerous samples, can provide insight into underlying disease pathology, disease prognosis and diagnosis. Despite the large number of review articles concerning metabolomics and its application in cancer research, biomarker and drug discovery, these reviews do not focus on a specific type of cancer. Metabolomics may provide biomarkers useful for identification of early stage gastric cancer, potentially addressing an important clinical need. Here, we present a short review on metabolomics as a tool for biomarker discovery in human gastric cancer, with a primary focus on its use as a predictor of anticancer drug chemosensitivity, diagnosis, prognosis, and metastasis. PMID:25009381

  19. Metabolomic profiling of tumor-bearing mice.

    PubMed

    Wettersten, Hiromi I; Ganti, Sheila; Weiss, Robert H

    2014-01-01

    Metabolomics is one of the newcomers among the "omics" techniques, perhaps also constituting the most relevant for the study of pathophysiological conditions. Metabolomics may indeed yield not only disease-specific biomarkers but also profound insights into the etiology and progression of a variety of human disorders. Various metabolomic approaches are currently available to study oncogenesis and tumor progression in vivo, in murine tumor models. Many of these models rely on the xenograft of human cancer cells into immunocompromised mice. Understanding how the metabolism of these cells evolves in vivo is critical to evaluate the actual pertinence of xenograft models to human pathology. Here, we discuss various tumor xenograft models and methods for their metabolomic profiling to provide a short guide to investigators interested in this field of research. PMID:24924138

  20. Metabolomics in Population-Based Research

    Cancer.gov

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

  1. Sample normalization methods in quantitative metabolomics.

    PubMed

    Wu, Yiman; Li, Liang

    2016-01-22

    To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. PMID:26763302

  2. ECMDB: the E. coli Metabolome Database.

    PubMed

    Guo, An Chi; Jewison, Timothy; Wilson, Michael; Liu, Yifeng; Knox, Craig; Djoumbou, Yannick; Lo, Patrick; Mandal, Rupasri; Krishnamurthy, Ram; Wishart, David S

    2013-01-01

    The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ∼1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. Each metabolite entry in the ECMDB contains an average of 75 separate data fields, including comprehensive compound descriptions, names and synonyms, chemical taxonomy, compound structural and physicochemical data, bacterial growth conditions and substrates, reactions, pathway information, enzyme data, gene/protein sequence data and numerous hyperlinks to images, references and other public databases. The ECMDB also includes an extensive collection of intracellular metabolite concentration data compiled from our own work as well as other published metabolomic studies. This information is further supplemented with thousands of fully assigned reference nuclear magnetic resonance and mass spectrometry spectra obtained from pure E. coli metabolites that we (and others) have collected. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of E. coli's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers but also to molecular biologists, systems biologists and individuals in the biotechnology industry. PMID:23109553

  3. Clinical impact of human breast milk metabolomics.

    PubMed

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

    2015-12-01

    Metabolomics is a research field concerned with the analysis of metabolome, the complete set of metabolites in a given cell, tissue, or biological sample. Being able to provide a molecular snapshot of biological systems, metabolomics has emerged as a functional methodology in a wide range of research areas such as toxicology, pharmacology, food technology, nutrition, microbial biotechnology, systems biology, and plant biotechnology. In this review, we emphasize the applications of metabolomics in investigating the human breast milk (HBM) metabolome. HBM is the recommended source of nutrition for infants since it contains the optimal balance of nutrients for developing babies, and it provides a range of benefits for growth, immunity, and development. The molecular mechanisms beyond the inter- and intra-variability of HBM that make its composition unique are yet to be well-characterized. Although still in its infancy, the study of HBM metabolome has already proven itself to be of great value in providing insights into this biochemical variability in relation to mother phenotype, diet, disease, and lifestyle. The results of these investigations lay the foundation for further developments useful to identify normal and aberrant biochemical changes as well as to develop strategies to promote healthy infant feeding practices. PMID:25689794

  4. METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

    EPA Science Inventory

    Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other 'omic techniques) may be more tangible in ecotoxicology because...

  5. NMR-based Metabolomics Applications in Biological and Environmental Science

    EPA Science Inventory

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

  6. THE METABOLOMIC WINDOW INTO HEPATOBILIARY DISEASE

    PubMed Central

    Beyoğlu, Diren; Idle, Jeffrey R.

    2014-01-01

    Summary The emergent discipline of metabolomics has attracted considerable research effort in hepatology. Here we review the metabolomic data for nonalcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH), cirrhosis, hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), alcoholic liver disease (ALD), hepatitis B and C, cholecystitis, cholestasis, liver transplantation and acute hepatotoxicity in animal models. A metabolomic window has permitted a view into the changing biochemistry occurring in the transitional phases between a healthy liver and hepatocellular carcinoma or cholangiocarcinoma. Whether provoked by obesity and diabetes, alcohol use or oncogenic viruses, the liver develops a core metabolomic phenotype (CMP) that involves dysregulation of bile acid and phospholipid homeostasis. The CMP commences at the transition between the healthy liver (Phase 0) and NAFLD/NASH, ALD or viral hepatitis (Phase 1). This CMP is maintained in the presence or absence of cirrhosis (Phase 2) and whether or not either HCC or CCA (Phase 3) develop. Inflammatory signalling in the liver triggers the appearance of the CMP. Many other metabolomic markers distinguish between Phases 0, 1, 2 and 3. A metabolic remodelling in HCC has been described but metabolomic data from all four Phases demonstrate that the Warburg shift from mitochondrial respiration to cytosolic glycolysis foreshadows HCC and may occur as early as Phase 1. The metabolic remodelling also involves an upregulation of fatty acid β-oxidation, also beginning in Phase 1. The storage of triglycerides in fatty liver provides high energy-yielding substrates for Phases 2 and 3 of liver pathology. The metabolomic window into hepatobiliary disease sheds new light on the systems pathology of the liver. PMID:23714158

  7. Metabolomics Data Normalization with EigenMS

    PubMed Central

    Karpievitch, Yuliya V.; Nikolic, Sonja B.; Wilson, Richard; Sharman, James E.; Edwards, Lindsay M.

    2014-01-01

    Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated). Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05) as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data. PMID:25549083

  8. Metabolomics data normalization with EigenMS.

    PubMed

    Karpievitch, Yuliya V; Nikolic, Sonja B; Wilson, Richard; Sharman, James E; Edwards, Lindsay M

    2014-01-01

    Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated). Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05) as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data. PMID:25549083

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

    PubMed

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

    2016-07-01

    The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program's goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. The complete set of training materials including slide sets and videos can be viewed at http://www.uab.edu/proteomics/metabolomics/workshop/workshop_june_2015.php. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27434804

  10. Systematic Applications of Metabolomics in Metabolic Engineering

    PubMed Central

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

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

  11. Recent Applications of Metabolomics Toward Cyanobacteria

    PubMed Central

    Schwarz, Doreen; Orf, Isabel; Kopka, Joachim; Hagemann, Martin

    2013-01-01

    Our knowledge on cyanobacterial molecular biology increased tremendously by the application of the “omics” techniques. Only recently, metabolomics was applied systematically to model cyanobacteria. Metabolomics, the quantitative estimation of ideally the complete set of cellular metabolites, is particularly well suited to mirror cellular metabolism and its flexibility under diverse conditions. Traditionally, small sets of metabolites are quantified in targeted metabolome approaches. The development of separation technologies coupled to mass-spectroscopy- or nuclear-magnetic-resonance-based identification of low molecular mass molecules presently allows the profiling of hundreds of metabolites of diverse chemical nature. Metabolome analysis was applied to characterize changes in the cyanobacterial primary metabolism under diverse environmental conditions or in defined mutants. The resulting lists of metabolites and their steady state concentrations in combination with transcriptomics can be used in system biology approaches. The application of stable isotopes in fluxomics, i.e. the quantitative estimation of carbon and nitrogen fluxes through the biochemical network, has only rarely been applied to cyanobacteria, but particularly this technique will allow the making of kinetic models of cyanobacterial systems. The further application of metabolomics in the concert of other “omics” technologies will not only broaden our knowledge, but will also certainly strengthen the base for the biotechnological application of cyanobacteria. PMID:24957891

  12. Metabolomics: Applications and Promise in Mycobacterial Disease.

    PubMed

    Mirsaeidi, Mehdi; Banoei, Mohammad Mehdi; Winston, Brent W; Schraufnagel, Dean E

    2015-09-01

    Until recently, the study of mycobacterial diseases was trapped in culture-based technology that is more than a century old. The use of nucleic acid amplification is changing this, and powerful new technologies are on the horizon. Metabolomics, which is the study of sets of metabolites of both the bacteria and host, is being used to clarify mechanisms of disease, and can identify changes leading to better diagnosis, treatment, and prognostication of mycobacterial diseases. Metabolomic profiles are arrays of biochemical products of genes in their environment. These complex patterns are biomarkers that can allow a more complete understanding of cell function, dysfunction, and perturbation than genomics or proteomics. Metabolomics could herald sweeping advances in personalized medicine and clinical trial design, but the challenges in metabolomics are also great. Measured metabolite concentrations vary with the timing within a condition, the intrinsic biology, the instruments, and the sample preparation. Metabolism profoundly changes with age, sex, variations in gut microbial flora, and lifestyle. Validation of biomarkers is complicated by measurement accuracy, selectivity, linearity, reproducibility, robustness, and limits of detection. The statistical challenges include analysis, interpretation, and description of the vast amount of data generated. Despite these drawbacks, metabolomics provides great opportunity and the potential to understand and manage mycobacterial diseases. PMID:26196272

  13. Basics of mass spectrometry based metabolomics.

    PubMed

    Courant, Frédérique; Antignac, Jean-Philippe; Dervilly-Pinel, Gaud; Le Bizec, Bruno

    2014-11-01

    The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18). PMID:25168716

  14. Application of Metabolomics in Thyroid Cancer Research

    PubMed Central

    Wojakowska, Anna; Chekan, Mykola; Widlak, Piotr; Pietrowska, Monika

    2015-01-01

    Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis. PMID:25972898

  15. Metabolomics in rheumatic diseases: desperately seeking biomarkers

    PubMed Central

    Guma, Monica; Tiziani, Stefano; Firestein, Gary S.

    2016-01-01

    Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases. PMID:26935283

  16. Metabolomics to Explore Impact of Dairy Intake.

    PubMed

    Zheng, Hong; Clausen, Morten R; Dalsgaard, Trine K; Bertram, Hanne C

    2015-06-01

    Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health. PMID:26091233

  17. Metabolomics to Explore Impact of Dairy Intake

    PubMed Central

    Zheng, Hong; Clausen, Morten R.; Dalsgaard, Trine K.; Bertram, Hanne C.

    2015-01-01

    Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health. PMID:26091233

  18. Metabolomics and Diabetes: Analytical and Computational Approaches

    PubMed Central

    Sas, Kelli M.; Karnovsky, Alla; Michailidis, George

    2015-01-01

    Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field. PMID:25713200

  19. Metabolomic Heterogeneity of Pulmonary Arterial Hypertension

    PubMed Central

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

    2014-01-01

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

  20. Metabolomics in rheumatic diseases: desperately seeking biomarkers.

    PubMed

    Guma, Monica; Tiziani, Stefano; Firestein, Gary S

    2016-05-01

    Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases. PMID:26935283

  1. Metabolomic fingerprinting of plant extracts.

    PubMed

    Mattoli, L; Cangi, F; Maidecchi, A; Ghiara, C; Ragazzi, E; Tubaro, M; Stella, L; Tisato, F; Traldi, P

    2006-12-01

    The standardization and quality control of plant extracts is an important topic, in particular, when such extracts are used for medicinal purposes. Consequently, the development of fast and effective analytical methods for metabolomic fingerprinting of plant extracts is of high interest. In this investigation, electrospray mass spectrometry (ESI-MS) and (1)H NMR techniques were employed with further statistical analyses of the acquired data. The results showed that negative ion mode ESI-MS is particularly effective for characterization of plant extracts. Different samples of the same species appear well-clustered and separated from the other species. To verify the effectiveness of the method, two other batches of extracts from a species, in which the principal components were already identified (Cynara scolymus), were analyzed, and the components that were verified by the principal component analysis (PCA) were found to be within the region identified as characteristic of Cynara Scolymus extracts. The data from extracts of the other species were well separated from those pertaining to the species previously characterized. Only the case of a species that was strictly correlated from a botanical point of view, with extracts that were previously analyzed, showed overlapping. PMID:17051519

  2. Genomic and Metabolomic Profile Associated to Microalbuminuria

    PubMed Central

    Marrachelli, Vannina G.; Monleon, Daniel; Rentero, Pilar; Mansego, María L.; Morales, Jose Manuel; Galan, Inma; Segura, Remedios; Martinez, Fernando; Martin-Escudero, Juan Carlos; Briongos, Laisa; Marin, Pablo; Lliso, Gloria; Chaves, Felipe Javier; Redon, Josep

    2014-01-01

    To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE) were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men, ACR>30 mg/g in 81 subjects) with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of RPH3A gene and the rs4359_CC of ACE gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria. PMID:24918908

  3. Linking metabolomics data to underlying metabolic regulation

    PubMed Central

    Nägele, Thomas

    2014-01-01

    The comprehensive experimental analysis of a metabolic constitution plays a central role in approaches of organismal systems biology. Quantifying the impact of a changing environment on the homeostasis of cellular metabolism has been the focus of numerous studies applying various metabolomics techniques. It has been proven that approaches which integrate different analytical techniques, e.g., LC-MS, GC-MS, CE-MS and H-NMR, can provide a comprehensive picture of a certain metabolic homeostasis. Identification of metabolic compounds and quantification of metabolite levels represent the groundwork for the analysis of regulatory strategies in cellular metabolism. This significantly promotes our current understanding of the molecular organization and regulation of cells, tissues and whole organisms. Nevertheless, it is demanding to elicit the pertinent information which is contained in metabolomics data sets. Based on the central dogma of molecular biology, metabolite levels and their fluctuations are the result of a directed flux of information from gene activation over transcription to translation and posttranslational modification. Hence, metabolomics data represent the summed output of a metabolic system comprising various levels of molecular organization. As a consequence, the inverse assignment of metabolomics data to underlying regulatory processes should yield information which—if deciphered correctly—provides comprehensive insight into a metabolic system. Yet, the deduction of regulatory principles is complex not only due to the high number of metabolic compounds, but also because of a high level of cellular compartmentalization and differentiation. Motivated by the question how metabolomics approaches can provide a representative view on regulatory biochemical processes, this article intends to present and discuss current metabolomics applications, strategies of data analysis and their limitations with respect to the interpretability in context of

  4. Metabolomics of forage plants: a review

    PubMed Central

    Rasmussen, Susanne; Parsons, Anthony J.; Jones, Christopher S.

    2012-01-01

    Background Forage plant breeding is under increasing pressure to deliver new cultivars with improved yield, quality and persistence to the pastoral industry. New innovations in DNA sequencing technologies mean that quantitative trait loci analysis and marker-assisted selection approaches are becoming faster and cheaper, and are increasingly used in the breeding process with the aim to speed it up and improve its precision. High-throughput phenotyping is currently a major bottle neck and emerging technologies such as metabolomics are being developed to bridge the gap between genotype and phenotype; metabolomics studies on forages are reviewed in this article. Scope Major challenges for pasture production arise from the reduced availability of resources, mainly water, nitrogen and phosphorus, and metabolomics studies on metabolic responses to these abiotic stresses in Lolium perenne and Lotus species will be discussed here. Many forage plants can be associated with symbiotic microorganisms such as legumes with nitrogen fixing rhizobia, grasses and legumes with phosphorus-solubilizing arbuscular mycorrhizal fungi, and cool temperate grasses with fungal anti-herbivorous alkaloid-producing Neotyphodium endophytes and metabolomics studies have shown that these associations can significantly affect the metabolic composition of forage plants. The combination of genetics and metabolomics, also known as genetical metabolomics can be a powerful tool to identify genetic regions related to specific metabolites or metabolic profiles, but this approach has not been widely adopted for forages yet, and we argue here that more studies are needed to improve our chances of success in forage breeding. Conclusions Metabolomics combined with other ‘-omics’ technologies and genome sequencing can be invaluable tools for large-scale geno- and phenotyping of breeding populations, although the implementation of these approaches in forage breeding programmes still lags behind. The majority

  5. Metabolomic applications in nutritional research: a perspective.

    PubMed

    O'Gorman, Aoife; Brennan, Lorraine

    2015-10-01

    Metabolomics focuses on the global study of metabolites in cells, tissues and biofluids. Analytical technologies such as nuclear magnetic resonance (NMR) spectroscopy and hyphenated mass spectrometry (MS) combined with advanced multivariate statistical methods allow us to study perturbations in metabolism. The close link between metabolism and nutrition has seen the application of metabolomics in nutritional research increase in recent times. Such applications can be divided into three main categories, namely (1) the area of dietary biomarker identification, (2) diet-related diseases and (3) nutritional interventions. The present perspective gives an overview of these applications and an outlook to the future. PMID:25640072

  6. Metabolomics in bladder cancer: a systematic review

    PubMed Central

    Cheng, Yidong; Yang, Xiao; Deng, Xiaheng; Zhang, Xiaolei; Li, Pengchao; Tao, Jun; Qin, Chao; Wei, Jifu; Lu, Qiang

    2015-01-01

    Bladder cancer (BC) is the most common urological malignancy. Early diagnosis of BC is crucial to improve patient outcomes. Currently, metabolomics is a potential technique that can be used to detect BC. We reviewed current publications and synthesised the findings on BC and metabolomics, i.e. metabolite upregulation and downregulation. Fourteen metabolites (lactic acid, leucine, valine, phenylalanine, glutamate, histidine, aspartic acid, tyrosine, serine, uracil, hypoxanthine, carnitine, pyruvic acid and citric acid) were identified as potential biomarkers for BC. In conclusion, this systematic review presents new opportunities for the diagnosis of BC. PMID:26379905

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

    PubMed Central

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

    2016-01-01

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

  8. Microbial metabolomics in open microscale platforms

    PubMed Central

    Barkal, Layla J.; Theberge, Ashleigh B.; Guo, Chun-Jun; Spraker, Joe; Rappert, Lucas; Berthier, Jean; Brakke, Kenneth A.; Wang, Clay C. C.; Beebe, David J.; Keller, Nancy P.; Berthier, Erwin

    2016-01-01

    The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid–liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria. PMID:26842393

  9. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

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

  10. NMR-based Metabolomics for Cancer Research

    EPA Science Inventory

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

  11. Cellular Metabolomics for Exposure and Toxicity Assessment

    EPA Science Inventory

    We have developed NMR automation and cell quench methods for cell culture-based metabolomics to study chemical exposure and toxicity. Our flow automation method is robust and free of cross contamination. The direct cell quench method is rapid and effective. Cell culture-based met...

  12. Microbial metabolomics in open microscale platforms.

    PubMed

    Barkal, Layla J; Theberge, Ashleigh B; Guo, Chun-Jun; Spraker, Joe; Rappert, Lucas; Berthier, Jean; Brakke, Kenneth A; Wang, Clay C C; Beebe, David J; Keller, Nancy P; Berthier, Erwin

    2016-01-01

    The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid-liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria. PMID:26842393

  13. Metabolomic Change Precedes Apple Superficial Scald Symptoms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metabolic profiling of 621 metabolites was employed to characterize metabolomic changes associated with ‘Granny Smith’ apple superficial scald development following 1-MCP or DPA treatment. Partial least squares-discriminant analyses were used to link metabolites with scald, postharvest treatments, ...

  14. Metabolomics of Clostridial Biofuel Production

    SciTech Connect

    Rabinowitz, Joshua D; Aristilde, Ludmilla; Amador-Noguez, Daniel

    2015-09-08

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

  15. Metabolomics and its application to studying metal toxicity.

    PubMed

    Booth, Sean C; Workentine, Matthew L; Weljie, Aalim M; Turner, Raymond J

    2011-11-01

    Here we explain the omics approach of metabolomics and how it can be applied to study a physiological response to toxic metal exposure. This review aims to educate the metallomics field to the tool of metabolomics. Metabolomics is becoming an increasingly used tool to compare natural and challenged states of various organisms, from disease states in humans to toxin exposure to environmental systems. This approach is key to understanding and identifying the cellular or biochemical targets of metals and the underlying physiological response. Metabolomics steps are described and overviews of its application to metal toxicity to organisms are given. As this approach is very new there are yet only a small number of total studies and therefore only a brief overview of some metal metabolomics studies is described. A frank critical evaluation of the approach is given to provide newcomers to the method a clear idea of the challenges and the rewards of applying metabolomics to their research. PMID:21922109

  16. 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. PMID:27188312

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

    PubMed

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

    2015-01-01

    Metabolomics is the latest of the "omic" technologies that involves comprehensive analysis of small molecule metabolites of an organism or a specific biological sample. Metabolomics provides an insight into the cell status and describes an actual health condition of organisms. Analysis of metabolome offers a unique opportunity to study the influence of genetic variation, disease, applied treatment or diet on endogenous metabolic state of organisms. There are many areas that might benefit from metabolomic research. In the article some applications of this novel "omic" technology in the field of medical sciences are presented. One of the most popular aims of metabolomic studies is biomarker discovery. Despite using the state-of-art analytical techniques along with advanced bioinformatic tools, metabolomic experiments encounter numerous difficulties and pitfalls. Challenges that researchers in the field of analysis of metabolome have to face include i.a., technical limitations, bioinformatic challenges and integration with other "omic" sciences. One of the grand challenges for studies in the field of metabolomics is to tackle the problem of data analysis, which is probably the most time consuming stage of metabolomic workflow and requires close collaboration between analysts, clinicians and experts in chemometric analysis. Implementation of metabolomics into clinical practice will be dependent on establishment of standardized protocols in analytical performance and data analysis and development of fit-for-purpose biomarker method validation. Metabolomics allows to achieve a sophisticated level of information about biological systems and opens up new perspectives in many fields of medicine, especially in oncology. Apart from its extensive cognitive significance, metabolomics manifests also a practical importance as it may lead to design of new non-invasive, sensitive and specific diagnostic techniques and development of new therapies. PMID:26647618

  18. MVAPACK: A Complete Data Handling Package for NMR Metabolomics

    PubMed Central

    2015-01-01

    Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set. PMID:24576144

  19. 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

  20. 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

    2016-01-01

    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

  1. Metabolomics analysis of shucked mussels' freshness.

    PubMed

    Aru, Violetta; Pisano, Maria Barbara; Savorani, Francesco; Engelsen, Søren Balling; Cosentino, Sofia; Cesare Marincola, Flaminia

    2016-08-15

    In this work a NMR metabolomics approach was applied to analyze changes in the metabolic profile of the bivalve mollusk Mytilus galloprovincialis upon storage at 0°C and 4°C for 10 and 6 days, respectively. The most significant microbial groups involved in spoilage of mussels were also investigated. The time-related metabolic signature of mussels was analysed by Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) which revealed a clear discrimination between the fresh samples and those stored at 0°C and 4°C. The results evidenced a noticeable increase in acetate, lactate, succinate, alanine, branched chain amino acids, trimethylamine and a progressive decline of osmolytes like betaine, homarine and taurine during storage. Exploration of the correlations of these metabolites with microbial counts suggested their use as potential biomarkers of spoilage. The results support the use of NMR metabolomics as a valuable tool to provide information on seafood freshness. PMID:27006214

  2. Metabolomic analysis of three Mollicute species.

    PubMed

    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

  3. Dissecting Bottromycin Biosynthesis Using Comparative Untargeted Metabolomics.

    PubMed

    Crone, William J K; Vior, Natalia M; Santos-Aberturas, Javier; Schmitz, Lukas G; Leeper, Finian J; Truman, Andrew W

    2016-08-01

    Bottromycin A2 is a structurally unique ribosomally synthesized and post-translationally modified peptide (RiPP) that possesses potent antibacterial activity towards multidrug-resistant bacteria. The structural novelty of bottromycin stems from its unprecedented macrocyclic amidine and rare β-methylated amino acid residues. The N-terminus of a precursor peptide (BtmD) is converted into bottromycin A2 by tailoring enzymes encoded in the btm gene cluster. However, little was known about key transformations in this pathway, including the unprecedented macrocyclization. To understand the pathway in detail, an untargeted metabolomic approach that harnesses mass spectral networking was used to assess the metabolomes of a series of pathway mutants. This analysis has yielded key information on the function of a variety of previously uncharacterized biosynthetic enzymes, including a YcaO domain protein and a partner protein that together catalyze the macrocyclization. PMID:27374993

  4. Metabolomic Imaging for Human Prostate Cancer Detection

    PubMed Central

    Wu, Chin-Lee; Jordan, Kate W.; Ratai, Eva M.; Sheng, Jinhua; Adkins, Christen B.; DeFeo, Elita M; Jenkins, Bruce G.; Ying, Leslie; McDougal, W. Scott; Cheng, Leo L.

    2010-01-01

    As current radiological approaches cannot accurately localize prostate cancer in vivo, biopsies are conducted at random within prostates for at-risk patients, leading to high false-negative rates. Metabolomic imaging can map cancer-specific biomolecular profile values onto anatomical structures to direct biopsy. In this preliminary study, we evaluated five prostatectomy-removed whole prostates from biopsy-proven cancer patients on a 7 Tesla human, whole-body magnetic resonance scanner. Localized, multi-cross-sectional, multi-voxel magnetic resonance spectra were used to construct a malignancy index based on prostate cancer metabolomic profiles obtained from previous, intact tissue analyses by a 14 Tesla spectrometer. This calculated Malignancy Index shows linear correlation with lesion size (p<0.013) and demonstrates a 93–97% overall accuracy for detecting the presence of prostate cancer lesions. PMID:20371475

  5. Innovation in Metabolomics to Improve Personalized Healthcare

    PubMed Central

    Cacciatore, Stefano; Loda, Massimo

    2016-01-01

    Metabolomics is the systemic study of all small molecules (metabolites) and their concentration as affected by pathological and physiological alterations or environmental or other factors. Metabolic alterations represent a “window” on the complex interactions between genetic expression, enzyme activity, and metabolic reactions. Techniques, including nuclear magnetic resonance spectroscopy, mass spectrometry, Fourier-transform infrared, and Raman spectroscopy, have led to significant advances in metabolomics. The field is shifting from feasibility studies to biological and clinical applications. Fields of application range from cancer biology to stem cell research and assessment of xenobiotics and drugs in tissues and single cells. Cross-validation across high-throughput platforms has allowed findings from expression profiling to be confirmed with metabolomics. Specific genetic alterations appear to drive unique metabolic programs. These, in turn, can be used as biomarkers of genetic subtypes of prostate cancer or as discovery tools for therapeutic targeting of metabolic enzymes. Thus, metabolites in blood may serve as biomarkers of tumor state, including inferring driving oncogenes. Novel applications such as these suggest that metabolic profiling may be utilized in refining personalized medicine. PMID:26014591

  6. HMDB: a knowledgebase for the human metabolome

    PubMed Central

    Wishart, David S.; Knox, Craig; Guo, An Chi; Eisner, Roman; Young, Nelson; Gautam, Bijaya; Hau, David D.; Psychogios, Nick; Dong, Edison; Bouatra, Souhaila; Mandal, Rupasri; Sinelnikov, Igor; Xia, Jianguo; Jia, Leslie; Cruz, Joseph A.; Lim, Emilia; Sobsey, Constance A.; Shrivastava, Savita; Huang, Paul; Liu, Philip; Fang, Lydia; Peng, Jun; Fradette, Ryan; Cheng, Dean; Tzur, Dan; Clements, Melisa; Lewis, Avalyn; De Souza, Andrea; Zuniga, Azaret; Dawe, Margot; Xiong, Yeping; Clive, Derrick; Greiner, Russ; Nazyrova, Alsu; Shaykhutdinov, Rustem; Li, Liang; Vogel, Hans J.; Forsythe, Ian

    2009-01-01

    The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users. PMID:18953024

  7. HMDB: a knowledgebase for the human metabolome.

    PubMed

    Wishart, David S; Knox, Craig; Guo, An Chi; Eisner, Roman; Young, Nelson; Gautam, Bijaya; Hau, David D; Psychogios, Nick; Dong, Edison; Bouatra, Souhaila; Mandal, Rupasri; Sinelnikov, Igor; Xia, Jianguo; Jia, Leslie; Cruz, Joseph A; Lim, Emilia; Sobsey, Constance A; Shrivastava, Savita; Huang, Paul; Liu, Philip; Fang, Lydia; Peng, Jun; Fradette, Ryan; Cheng, Dean; Tzur, Dan; Clements, Melisa; Lewis, Avalyn; De Souza, Andrea; Zuniga, Azaret; Dawe, Margot; Xiong, Yeping; Clive, Derrick; Greiner, Russ; Nazyrova, Alsu; Shaykhutdinov, Rustem; Li, Liang; Vogel, Hans J; Forsythe, Ian

    2009-01-01

    The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users. PMID:18953024

  8. Integration of metabolomics data into metabolic networks

    PubMed Central

    Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

    2015-01-01

    Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data. PMID:25741348

  9. Metabolomics as a diagnostic tool in gastroenterology.

    PubMed

    De Preter, Vicky; Verbeke, Kristin

    2013-11-01

    Metabolomics has increasingly been applied in addition to other "omic" approaches in the study of the pathophysiology of different gastrointestinal diseases. Metabolites represent molecular readouts of the cell status reflecting a physiological phenotype. In addition, changes in metabolite concentrations induced by exogenous factors such as environmental and dietary factors which do not affect the genome, are taken into account. Metabolic reactions initiated by the host or gut microbiota can lead to "marker" metabolites present in different biological fluids that allow differentiation between health and disease. Several lines of evidence implicated the involvement of intestinal microbiota in the pathogenesis of inflammatory bowel disease (IBD). Also in irritable bowel syndrome (IBS), a role of an abnormal microbiota composition, so-called dysbiosis, is supported by experimental data. These compositional alterations could play a role in the aetiology of both diseases by altering the metabolic activities of the gut bacteria. Several studies have applied a metabolomic approach to identify these metabolite signatures. However, before translating a potential metabolite biomarker into clinical use, additional validation studies are required. This review summarizes contributions that metabolomics has made in IBD and IBS and presents potential future directions within the field. PMID:24199025

  10. Metabolomics as a diagnostic tool in gastroenterology

    PubMed Central

    De Preter, Vicky; Verbeke, Kristin

    2013-01-01

    Metabolomics has increasingly been applied in addition to other “omic” approaches in the study of the pathophysiology of different gastrointestinal diseases. Metabolites represent molecular readouts of the cell status reflecting a physiological phenotype. In addition, changes in metabolite concentrations induced by exogenous factors such as environmental and dietary factors which do not affect the genome, are taken into account. Metabolic reactions initiated by the host or gut microbiota can lead to “marker” metabolites present in different biological fluids that allow differentiation between health and disease. Several lines of evidence implicated the involvement of intestinal microbiota in the pathogenesis of inflammatory bowel disease (IBD). Also in irritable bowel syndrome (IBS), a role of an abnormal microbiota composition, so-called dysbiosis, is supported by experimental data. These compositional alterations could play a role in the aetiology of both diseases by altering the metabolic activities of the gut bacteria. Several studies have applied a metabolomic approach to identify these metabolite signatures. However, before translating a potential metabolite biomarker into clinical use, additional validation studies are required. This review summarizes contributions that metabolomics has made in IBD and IBS and presents potential future directions within the field. PMID:24199025

  11. Biomarker Discovery and Translation in Metabolomics

    PubMed Central

    Nagana Gowda, G.A.; Raftery, D.

    2016-01-01

    The multifaceted field of metabolomics has witnessed exponential growth in both methods development and applications. Owing to the urgent need, a significant fraction of research investigations in the field is focused on understanding, diagnosing and preventing human diseases; hence, the field of biomedicine has been the major beneficiary of metabolomics research. A large body of literature now documents the discovery of numerous potential biomarkers and provides greater insights into pathogeneses of numerous human diseases. A sizable number of findings have been tested for translational applications focusing on disease diagnostics ranging from early detection, to therapy prediction and prognosis, monitoring treatment and recurrence detection, as well as the important area of therapeutic target discovery. Current advances in analytical technologies promise quantitation of biomarkers from even small amounts of bio-specimens using non-invasive or minimally invasive approaches, and facilitate high-throughput analysis required for real time applications in clinical settings. Nevertheless, a number of challenges exist that have thus far delayed the translation of a majority of promising biomarker discoveries to the clinic. This article presents advances in the field of metabolomics with emphasis on biomarker discovery and translational efforts, highlighting the current status, challenges and future directions. PMID:27134822

  12. Application of Metabolomics for High Resolution Phenotype Analysis

    PubMed Central

    Fukusaki, Eiichiro

    2014-01-01

    Metabolome, a total profile of whole metabolites, is placed on downstream of proteome. Metabolome is thought to be results of implementation of genomic information. In other words, metabolome can be called as high resolution phenotype. The easiest operation of metabolomics is the integration to the upstream ome information including transcriptome and/or proteome. Those trials have been reported at a certain scientific level. In addition, metabolomics can be operated in stand-alone mode without any other ome information. Among metabolomics tactics, the author’s group is particularly focusing on metabolic fingerprinting, in which metabolome information is employed as explanatory variant to evaluate response variant. Metabolic fingerprinting technique is expected not only for analyzing slight difference depending on genotype difference but also for expressing dynamic variation of living organisms. The author introduces several good examples which he performed. Those are useful for easy understanding of the power of metabolomics. In addition, the author mentions the latest technology for analysis of metabolic dynamism. The author’s group developed a facile analytical method for semi-quantitative metabolic dynamism. The author introduces the novel method that uses time dependent variation of isotope distribution based on stable isotope dilution. PMID:26819889

  13. Metabolomics for Undergraduates: Identification and Pathway Assignment of Mitochondrial Metabolites

    ERIC Educational Resources Information Center

    Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E. N.; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa

    2016-01-01

    Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening…

  14. Statistical methods for handling unwanted variation in metabolomics data

    PubMed Central

    Sysi-Aho, Marko; Jacob, Laurent; Gagnon-Bartsch, Johann A.; Castillo, Sandra; Simpson, Julie A; Speed, Terence P.

    2015-01-01

    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 recognised 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 online. PMID:25692814

  15. Review: Microfluidic Applications in Metabolomics and Metabolic Profiling

    PubMed Central

    Kraly, James R.; Holcomb, Ryan E.; Guan, Qian; Henry, Charles S.

    2009-01-01

    Metabolomics is an emerging area of research focused on measuring small molecules in biological samples. There are a number of different types of metabolomics, ranging from global profiling of all metabolites in a single sample to measurement of a selected group of analytes. Microfluidics and related technologies have been used in this research area with good success. The aim of this review article is to summarize the use of microfluidics in metabolomics. Direct application of microfluidics to the determination of small molecules is covered first. Next, important sample preparation methods developed for microfluidics and applicable to metabolomics are covered. Finally, a summary of metabolomic work as it relates to analysis of cellular events using microfluidics is covered. PMID:19800473

  16. 13C NMR Metabolomics: INADEQUATE Network Analysis

    PubMed Central

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

    2015-01-01

    The many advantages of 13C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, 13C NMR offers a straightforward measurement of these compounds. Two-dimensional 13C-13C 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 semi-automated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE datasets using an in silico INADEQUATE database. We demonstrate this approach using isotopically labeled Caenorhabditis elegans mixtures. PMID:25932900

  17. Genomic, Proteomic, and Metabolomic Data Integration Strategies

    PubMed Central

    Wanichthanarak, Kwanjeera; Fahrmann, Johannes F; Grapov, Dmitry

    2015-01-01

    Robust interpretation of experimental results measuring discreet biological domains remains a significant challenge in the face of complex biochemical regulation processes such as organismal versus tissue versus cellular metabolism, epigenetics, and protein post-translational modification. Integration of analyses carried out across multiple measurement or omic platforms is an emerging approach to help address these challenges. This review focuses on select methods and tools for the integration of metabolomic with genomic and proteomic data using a variety of approaches including biochemical pathway-, ontology-, network-, and empirical-correlation-based methods. PMID:26396492

  18. The Utility of Metabolomics in Natural Product and Biomarker Characterization

    PubMed Central

    Cox, Daniel G.; Oh, Joonseok; Keasling, Adam; Colson, Kim

    2014-01-01

    Background Metabolomics is a well-established rapidly developing research field involving quantitative and qualitative metabolite assessment within biological systems. Recent improvements in metabolomics technologies reveal the unequivocal value of metabolomics tools in natural products discovery, gene-function analysis, systems biology and diagnostic platforms. Scope of review We review of some of the prominent metabolomics methodologies employed in data acquisition and analysis of natural products and disease-related biomarkers. Major conclusions This review demonstrates that metabolomics represents a highly adaptable technology with diverse applications ranging from environmental toxicology to disease diagnosis. Metabolomic analysis is shown to provide a unique snapshot of the functional genetic status of an organism by examining its biochemical profile, with relevance toward resolving phylogenetic associations involving horizontal gene transfer and distinguishing subgroups of genera possessing high genetic homology, as well as an increasing role in both elucidating biosynthetic transformations of natural products and detecting preclinical biomarkers of numerous disease states. General significance This review expands the interest in multiplatform combinatorial metabolomic analysis. The applications reviewed range from phylogenetic assignment, biosynthetic transformations of natural products, and the detection of preclinical biomarkers. PMID:25151044

  19. Challenges of metabolomics in human gut microbiota research.

    PubMed

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

    2016-08-01

    The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine. PMID:27012595

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

    PubMed Central

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-01-01

    Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases. PMID:27271597

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

    PubMed

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-01-01

    Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the 'Warburg effect'. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases. PMID:27271597

  2. Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies.

    PubMed

    Zaitsu, Kei; Hayashi, Yumi; Kusano, Maiko; Tsuchihashi, Hitoshi; Ishii, Akira

    2016-02-01

    Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided. PMID:26613805

  3. Introduction to metabolomics and its applications in ophthalmology.

    PubMed

    Tan, S Z; Begley, P; Mullard, G; Hollywood, K A; Bishop, P N

    2016-06-01

    Metabolomics is the study of endogenous and exogenous metabolites in biological systems, which aims to provide comparative semi-quantitative information about all metabolites in the system. Metabolomics is an emerging and potentially powerful tool in ophthalmology research. It is therefore important for health professionals and researchers involved in the speciality to understand the basic principles of metabolomics experiments. This article provides an overview of the experimental workflow and examples of its use in ophthalmology research from the study of disease metabolism and pathogenesis to identification of biomarkers. PMID:26987591

  4. Metabolomics in the identification of biomarkers of dietary intake

    PubMed Central

    O'Gorman, Aoife; Gibbons, Helena; Brennan, Lorraine

    2013-01-01

    Traditional methods for assessing dietary exposure can be unreliable, with under reporting one of the main problems. In an attempt to overcome such problems there is increasing interest in identifying biomarkers of dietary intake to provide a more accurate measurement. Metabolomics is an analytical technique that aims to identify and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics coupled with statistical analysis for the identification of dietary biomarkers, with a number of putative biomarkers identified. This minireview focuses on metabolomics based approaches and highlights some of the key successes. PMID:24688686

  5. Error Propagation Analysis for Quantitative Intracellular Metabolomics

    PubMed Central

    Tillack, Jana; Paczia, Nicole; Nöh, Katharina; Wiechert, Wolfgang; Noack, Stephan

    2012-01-01

    Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The total measurement error of any analytical protocol is the result of an accumulation of single errors introduced by several processing steps. Here, we present a framework for the quantification of intracellular metabolites, including error propagation during metabolome sample processing. Focusing on one specific protocol, we comprehensively investigate all currently known and accessible factors that ultimately impact the accuracy of intracellular metabolite concentration data. All intermediate steps are modeled, and their uncertainty with respect to the final concentration data is rigorously quantified. Finally, on the basis of a comprehensive metabolome dataset of Corynebacterium glutamicum, an integrated error propagation analysis for all parts of the model is conducted, and the most critical steps for intracellular metabolite quantification are detected. PMID:24957773

  6. Targeting of the hydrophobic metabolome by pathogens.

    PubMed

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

    2015-05-01

    The hydrophobic molecules of the metabolome - also named the lipidome - constitute a major part of the entire metabolome. Novel technologies show the existence of a staggering number of individual lipid species, the biological functions of which are, with the exception of only a few lipid species, unknown. Much can be learned from pathogens that have evolved to take advantage of the complexity of the lipidome to escape the immune system of the host organism and to allow their survival and replication. Different types of pathogens target different lipids as shown in interaction maps, allowing visualization of differences between different types of pathogens. Bacterial and viral pathogens target predominantly structural and signaling lipids to alter the cellular phenotype of the host cell. Fungal and parasitic pathogens have complex lipidomes themselves and target predominantly the release of polyunsaturated fatty acids from the host cell lipidome, resulting in the generation of eicosanoids by either the host cell or the pathogen. Thus, whereas viruses and bacteria induce predominantly alterations in lipid metabolites at the host cell level, eukaryotic pathogens focus on interference with lipid metabolites affecting systemic inflammatory reactions that are part of the immune system. A better understanding of the interplay between host-pathogen interactions will not only help elucidate the fundamental role of lipid species in cellular physiology, but will also aid in the generation of novel therapeutic drugs. PMID:25754025

  7. Radiation Metabolomics: Current Status and Future Directions

    PubMed Central

    Menon, Smrithi S.; Uppal, Medha; Randhawa, Subeena; Cheema, Mehar S.; Aghdam, Nima; Usala, Rachel L.; Ghosh, Sanchita P.; Cheema, Amrita K.; Dritschilo, Anatoly

    2016-01-01

    Human exposure to ionizing radiation (IR) disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as organ- and tissue-specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high-resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic IR. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure. PMID:26870697

  8. The Human Blood Metabolome-Transcriptome Interface

    PubMed Central

    Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

    2015-01-01

    Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

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

    PubMed

    Barnes, S; Benton, H P; Casazza, K; Cooper, S J; Cui, X; Du, X; Engler, J A; Kabarowski, J H; Li, S; Pathmasiri, W; Prasain, J K; Renfrow, M B; Tiwari, H K

    2016-07-01

    Metabolomics is perhaps the most challenging of the -omics fields, given the complexity of an organism's metabolome and the rapid rate at which it changes. When one sets out to study metabolism there are numerous dynamic variables that can influence metabolism that must be considered. Recognizing the experimental challenges confronting researchers who undertake metabolism studies, workshops like the one at University of Alabama at Birmingham have been established to offer instructional guidance. A summary of the UAB course training materials is being published as a two-part Special Feature Tutorial. In this month's Part I the authors discuss details of good experimental design and sample collection and handling. In an upcoming Part II, the authors discuss in detail the various aspects of data analysis. PMID:27434812

  10. METABOLOMICS AS A DIAGNOSTIC TOOL FOR SMALL FISH TOXICOLOGY RESEARCH

    EPA Science Inventory

    Metabolomics involves the application of advanced analytical and statistical tools to profile changes in levels of endogenous metabolites in tissues and biofluids resulting from disease onset or stress. While certain metabolites are being specifically targeted in these studies, w...

  11. METABOLOMICS IN SMALL FISH TOXICOLOGY AND ECOLOGICAL RISK ASSESSMENTS

    EPA Science Inventory

    The US EPA is tasked with protecting not only humans, but also ecosystems from potentially harmful effects of chemical pollutants. Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in ecotoxicology. Indeed, the advantages of met...

  12. International NMR-based Environmental Metabolomics Intercomparison Exercise

    EPA Science Inventory

    Several fundamental requirements must be met so that NMR-based metabolomics and the related technique of metabonomics can be formally adopted into environmental monitoring and chemical risk assessment. Here we report an intercomparison exercise which has evaluated the effectivene...

  13. (Video 6 of 8) Metabolomics: You Are What You Eat

    NASA Video Gallery

    NASA’s Human Research Program releases “Metabolomics: You Are What You Eat” video to highlight its Twins Study which uses omics to study Mark and Scott Kelly’s metabolites. Omics is an evolving fie...

  14. Spectral Relative Standard Deviation: A Practical Benchmark in Metabolomics

    EPA Science Inventory

    Metabolomics datasets, by definition, comprise of measurements of large numbers of metabolites. Both technical (analytical) and biological factors will induce variation within these measurements that is not consistent across all metabolites. Consequently, criteria are required to...

  15. Is there a role for stool metabolomics in cystic fibrosis?

    PubMed

    Kaakoush, Nadeem O; Pickford, Russell; Jaffe, Adam; Ooi, Chee Y

    2016-08-01

    A number of studies utilizing metabolomics have focused on the pathophysiology of cystic fibrosis (CF) lung disease. Here, we performed fecal metabolomics on pancreatic insufficient (PI) and sufficient (PS) children with CF and compared them with healthy controls (HC). Fecal metabolomics can differentiate between PS-CF and PI-CF. We identified a potential biomarker of disease severity or cystic fibrosis transmembrane conductance regulator function (m/z, 463.247; retention time, 0.570717 min) that discriminates between HC versus PS-CF versus PI-CF. We also identified lipoyl-GMP as a potential novel inflammatory biomarker, and elevation in fecal glycerol 1,2-didodecanoate 3-tetradecanoate may provide clues to the pathogenesis of intestinal inflammation. For the first time, we demonstrate the potential applications of fecal metabolomics in CF. PMID:27553892

  16. Field-based Metabolomics for Assessing Contaminated Surface Waters

    EPA Science Inventory

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

  17. Global metabolomic profiling targeting childhood obesity in the Hispanic population

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metabolomics may unravel important biological pathways involved in the pathophysiology of childhood obesity. We aimed to 1) identify metabolites that differ significantly between nonobese and obese Hispanic children; 2) collapse metabolites into principal components (PCs) associated with obesity and...

  18. Interpreting Metabolomics Data to Mode of Action of Chemicals

    EPA Science Inventory

    Metabolomics approach utilizes high-throughput identification, quantification, and characterization of low molecular weight endogenous metabolites from numerous metabolic pathways. Exposure to environmental chemicals, which act through multiple mechanisms, cause perturbation of...

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

    PubMed Central

    Heuberger, Adam L.; Robison, Faith M.; Lyons, Sarah Marie A.; Broeckling, Corey D.; Prenni, Jessica E.

    2014-01-01

    Metabolic processes in plants are key components of physiological and biochemical disease resistance. Metabolomics, the analysis of a broad range of small molecule compounds in a biological system, has been used to provide a systems-wide overview of plant metabolism associated with defense responses. Plant immunity has been examined using multiple metabolomics workflows that vary in methods of detection, annotation, and interpretation, and the choice of workflow can significantly impact the conclusions inferred from a metabolomics investigation. The broad range of metabolites involved in plant defense often requires multiple chemical detection platforms and implementation of a non-targeted approach. A review of the current literature reveals a wide range of workflows that are currently used in plant metabolomics, and new methods for analyzing and reporting mass spectrometry (MS) data can improve the ability to translate investigative findings among different plant-pathogen systems. PMID:25009545

  20. 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

  1. Metabolomic determinants of necrotizing enterocolitis in preterm piglets

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Studies in premature infants and animals show that carbohydrate malabsorption and gut microbiota colonisation are key elements for triggering necrotizing enterocolitis (NEC). Our aim was to determine how dietary carbohydrate composition affects the metabolomic profile and whether unique metabolite s...

  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. Metabolomics and Its Application to Acute Lung Diseases

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2014-06-01

    The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health. PMID:24760973

  5. Metabolomics and Its Application to Acute Lung Diseases.

    PubMed

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

    2016-01-01

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

  6. Unique plasma metabolomic signature of osteonecrosis of the femoral head.

    PubMed

    Liu, Xiaolin; Li, Qing; Sheng, Jiagen; Hu, Bin; Zhu, Zhenzhong; Zhou, Shumin; Yin, Junhui; Gong, Qiang; Wang, Yang; Zhang, Changqing

    2016-07-01

    Metabolomic analysis was performed to determine the metabolomic signature of osteonecrosis of the femoral head (ONFH), and to investigate the underlying relationship between the metabolomic signature and the pathogenesis of ONFH. Plasma samples were collected from 30 ONFH patients and 30 normal subjects. The global metabolomic profile was obtained through a combination of high-throughput liquid- and gas-chromatography-based mass spectrometry analyses. All statistical analyses were conducted using the R software. The results showed clear differences in the metabolomic signature between the plasma of ONFH patients compared with normal subjects. Among the 354 identified metabolites, the expression of 123 metabolites were significantly changed in ONFH patients compared with normal subjects (p < 0.05, q < 0.10). Bioinformatics analysis revealed that these abnormal metabolites were mainly involved in lipid-, glutathione-, nucleotide-, and energy-associated pathways, which might be related to enhanced inflammation, oxidative stress, and energy deficiency due to ONFH. This study provides the first metabolomic analysis of ONFH, and identifies a previously unrecognized metabolic signature in ONFH plasma. The results offer new insights into the pathological mechanisms of ONFH through its influence on metabolic pathways, providing the requisite framework for identifying biomarkers or novel targets for therapeutic intervention. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1158-1167, 2016. PMID:26662932

  7. SMART: Statistical Metabolomics Analysis-An R Tool.

    PubMed

    Liang, Yu-Jen; Lin, Yu-Ting; Chen, Chia-Wei; Lin, Chien-Wei; Chao, Kun-Mao; Pan, Wen-Harn; Yang, Hsin-Chou

    2016-06-21

    Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis. This study developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data preprocessing to downstream association analysis. We developed Statistical Metabolomics Analysis-An R Tool (SMART), which can analyze input files with different formats, visually represent various types of data features, implement peak alignment and annotation, conduct quality control for samples and peaks, explore batch effects, and perform association analysis. A pharmacometabolomics study of antihypertensive medication was conducted and data were analyzed using SMART. Neuromedin N was identified as a metabolite significantly associated with angiotensin-converting-enzyme inhibitors in our metabolome-wide association analysis (p = 1.56 × 10(-4) in an analysis of covariance (ANCOVA) with an adjustment for unknown latent groups and p = 1.02 × 10(-4) in an ANCOVA with an adjustment for hidden substructures). This endogenous neuropeptide is highly related to neurotensin and neuromedin U, which are involved in blood pressure regulation and smooth muscle contraction. The SMART software, a user guide, and example data can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/metabolomics/SMART.htm . PMID:27248514

  8. The Brain Metabolome of Male Rats across the Lifespan

    PubMed Central

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

    2016-01-01

    Comprehensive and accurate characterization of brain metabolome is fundamental to brain science, but has been hindered by technical limitations. We profiled the brain metabolome in male Wistar rats at different ages (day 1 to week 111) using high-sensitivity and high-resolution mass spectrometry. Totally 380 metabolites were identified and 232 of them were quantitated. Compared with anatomical regions, age had a greater effect on variations in the brain metabolome. Lipids, fatty acids and amino acids accounted for the largest proportions of the brain metabolome, and their concentrations varied across the lifespan. The levels of polyunsaturated fatty acids were higher in infancy (week 1 to week 3) compared with later ages, and the ratio of omega-6 to omega-3 fatty acids increased in the aged brain (week 56 to week 111). Importantly, a panel of 20 bile acids were quantitatively measured, most of which have not previously been documented in the brain metabolome. This study extends the breadth of the mammalian brain metabolome as well as our knowledge of functional brain development, both of which are critically important to move the brain science forward. PMID:27063670

  9. Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites.

    PubMed

    Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E N; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa

    2016-01-01

    Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening approach to identify all the metabolites in a given biological system is called metabolic fingerprinting. Using high-resolution and high-mass accuracy mass spectrometry, large metabolome coverage, sensitivity, and specificity can be attained. Although the theoretical concepts of this methodology are usually provided in life-science programs, hands-on laboratory experiments are not usually accessible to undergraduate students. Even if the instruments are available, there are not simple laboratory protocols created specifically for teaching metabolomics. We designed a straightforward hands-on laboratory experiment to introduce students to this methodology, relating it to biochemical knowledge through metabolic pathway mapping of the identified metabolites. This study focuses on mitochondrial metabolomics since mitochondria have a well-known, medium-sized cellular sub-metabolome. These features facilitate both data processing and pathway mapping. In this experiment, students isolate mitochondria from potatoes, extract the metabolites, and analyze them by high-resolution mass spectrometry (using an FT-ICR mass spectrometer). The resulting mass list is submitted to an online program for metabolite identification, and compounds associated with mitochondrial pathways can be highlighted in a metabolic network map. PMID:26537432

  10. Metabolomics predicts stroke recurrence after transient ischemic attack

    PubMed Central

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

    2015-01-01

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

  11. Clinical Applications of Metabolomics in Oncology: A Review

    PubMed Central

    Spratlin, Jennifer L.; Serkova, Natalie J.; Gail Eckhardt, S.

    2009-01-01

    Metabolomics, an omic science in systems biology, is the global quantitative assessment of endogenous metabolites within a biological system. Either individually or grouped as a metabolomic profile, detection of metabolites is carried out in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry. There is potential for the metabolome to have a multitude of uses in oncology, including the early detection and diagnosis of cancer and as both a predictive and pharmacodynamic marker of drug effect. Despite this, there is lack of knowledge in the oncology community regarding metabolomics and confusion about its methodologic processes, technical challenges, and clinical applications. Metabolomics, when used as a translational research tool, can provide a link between the laboratory and clinic, particularly because metabolic and molecular imaging technologies, such as positron emission tomography and magnetic resonance spectroscopic imaging, enable the discrimination of metabolic markers noninvasively in vivo. Here, we review the current and potential applications of metabolomics, focusing on its use as a biomarker for cancer diagnosis, prognosis, and therapeutic evaluation. PMID:19147747

  12. Ultrasound: a subexploited tool for sample preparation in metabolomics.

    PubMed

    Luque de Castro, M D; Delgado-Povedano, M M

    2014-01-01

    Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. PMID:24331041

  13. Brain Region Mapping using Global Metabolomics

    PubMed Central

    Ivanisevic, Julijana; Epstein, Adrian; Kurczy, Michael E.; Benton, H. Paul; Uritboonthai, Winnie; Fox, Howard S.; Boska, Michael D.; Gendelman, Howard E.; Siuzdak, Gary

    2014-01-01

    SUMMARY Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present a novel untargeted mass spectrometry-based metabolomics approach that has successfully uncovered differences in broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed unique water-soluble and lipid metabolite patterns between brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric and sialic acid whose physiological roles in brain metabolism are poorly understood. This study lays important groundwork by defining regional homeostasis for the normal mouse brain to give context to the reaction to pathological events. PMID:25457182

  14. Analyzing Complex Metabolomic Networks: Experiments and Simulation

    NASA Astrophysics Data System (ADS)

    Steuer, R.; Kurths, J.; Fiehn, O.; Weckwerth, W.

    2002-03-01

    In the recent years, remarkable advances in molecular biology have enabled us to measure the behavior of complex regularity networks underlying biological systems. In particular, high throughput techniques, such as gene expression arrays, allow a fast acquisition of a large number of simultaneously measured variables. Similar to gene expression, the analysis of metabolomic datasets results in a huge number of metabolite co-regulations: Metabolites are the end products of cellular regulatory processes, their level can be regarded as the ultimate response to genetic or environmental changes. In this presentation we focus on the topological description of such networks, using both, experimental data and simulations. In particular, we discuss the possibility to deduce novel links between metabolites, using concepts from (nonlinear) time series analysis and information theory.

  15. Metabolomics in Small Fish Toxicology: Assessing the Impacts of Model EDCs

    EPA Science Inventory

    Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other ‘omic techniques) may be more tangible in ecotoxicology because...

  16. Applications of NMR-based metabolomics in biological and environmental research

    EPA Science Inventory

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used by biologists to study the dynamic response of biological systems (cells, tissues, or whole organisms) under diverse physiological or pathological conditions. Metabolomics deals with the qu...

  17. Standard Reporting Requirements for Biological Samples in Metabolomics Experiments: Environmental Context

    EPA Science Inventory

    Metabolomic technologies are increasingly being applied to study biological questions in a range of different settings from clinical through to environmental. As with other high-throughput technologies, such as those used in transcriptomics and proteomics, metabolomics continues...

  18. 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...

  19. Can NMR solve some significant challenges in metabolomics?

    NASA Astrophysics Data System (ADS)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

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

  20. Application of Metabolomics to Multiple Chemical Sensitivity Research.

    PubMed

    Katoh, Takahiko; Fujiwara, Yuki; Nakashita, Chihiro; Lu, Xi; Hisada, Aya; Miyazaki, Wataru; Azuma, Kenichi; Tanigawa, Mari; Uchiyama, Iwao; Kunugita, Naoki

    2016-01-01

    Multiple chemical sensitivity (MCS) is an acquired chronic disorder characterized by nonspecific symptoms in multiple organ systems associated with exposure to low-level chemicals. Diagnosis of MCS can be difficult because of the inability to assess the causal relationship between exposure and symptoms. No standardized objective measures for the identification of MCS and no precise definition of this disorder have been established. Recent technological advances in mass spectrometry have significantly improved our capacity to obtain more data from each biological sample. Metabolomics comprises the methods and techniques that are used to determine the small-level molecules in biofluids and tissues. The metabolomic profile-the metabolome-has multiple applications in many biological sciences, including the development of new diagnostic tools for medicine. We performed metabolomics to detect the difference between 9 patients with MCS and 9 controls. We identified 183 substances whose levels were beyond the normal detection limit. The most prominent differences included significant increases in the levels of both hexanoic acid and pelargonic acid, and also a significant decrease in the level of acetylcarnitine in patients with MCS. In conclusion, using metabolomics analysis, we uncovered a hitherto unrecognized alteration in the levels of metabolites in MCS. These changes may have important biological implications and may have a significant potential for use as biomarkers. PMID:26832623

  1. Metabolomics: Bridging the Gap between Pharmaceutical Development and Population Health.

    PubMed

    Tolstikov, Vladimir

    2016-01-01

    Metabolomics has emerged as an essential tool for studying metabolic processes, stratification of patients, as well as illuminating the fundamental metabolic alterations in disease onset, progression, or response to therapeutic intervention. Metabolomics materialized within the pharmaceutical industry as a standalone assay in toxicology and disease pathology and eventually evolved towards aiding in drug discovery and pre-clinical studies via supporting pharmacokinetic and pharmacodynamic characterization of a drug or a candidate. Recent progress in the field is illustrated by coining of the new term-Pharmacometabolomics. Integration of data from metabolomics with large-scale omics along with clinical, molecular, environmental and behavioral analysis has demonstrated the enhanced utility of deconstructing the complexity of health, disease, and pharmaceutical intervention(s), which further highlight it as an essential component of systems medicine. This review presents the current state and trend of metabolomics applications in pharmaceutical development, and highlights the importance and potential of clinical metabolomics as an essential part of multi-omics protocols that are directed towards shaping precision medicine and population health. PMID:27399792

  2. LC-MS-based Metabolomics of Xenobiotic-induced Toxicities

    PubMed Central

    Chen, Chi; Kim, Sangyub

    2013-01-01

    Xenobiotic exposure, especially high-dose or repeated exposure of xenobiotics, can elicit detrimental effects on biological systems through diverse mechanisms. Changes in metabolic systems, including formation of reactive metabolites and disruption of endogenous metabolism, are not only the common consequences of toxic xenobiotic exposure, but in many cases are the major causes behind development of xenobiotic-induced toxicities (XIT). Therefore, examining the metabolic events associated with XIT generates mechanistic insights into the initiation and progression of XIT, and provides guidance for prevention and treatment. Traditional bioanalytical platforms that target only a few suspected metabolites are capable of validating the expected outcomes of xenobiotic exposure. However, these approaches lack the capacity to define global changes and to identify unexpected events in the metabolic system. Recent developments in high-throughput metabolomics have dramatically expanded the scope and potential of metabolite analysis. Among all analytical techniques adopted for metabolomics, liquid chromatography-mass spectrometry (LC-MS) has been most widely used for metabolomic investigations of XIT due to its versatility and sensitivity in metabolite analysis. In this review, technical platform of LC-MS-based metabolomics, including experimental model, sample preparation, instrumentation, and data analysis, are discussed. Applications of LC-MS-based metabolomics in exploratory and hypothesis-driven investigations of XIT are illustrated by case studies of xenobiotic metabolism and endogenous metabolism associated with xenobiotic exposure. PMID:24688689

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

    PubMed Central

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

    2013-01-01

    In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health. PMID:23986911

  4. Effect of acute stresses on zebra fish (Danio rerio) metabolome measured by NMR-based metabolomics.

    PubMed

    Mushtaq, Mian Yahya; Marçal, Rosilene Moretti; Champagne, Danielle L; van der Kooy, Frank; Verpoorte, Robert; Choi, Young Hae

    2014-09-01

    We applied an acute stress model to zebra fish in order to measure the changes in the metabolome due to biological stress. This was done by submitting the fish to fifteen minutes of acute confinement (netting) stress, and then five minutes for the open field and light/dark field tests. A polar extract of the zebra fish was then subjected to (1)H nuclear magnetic spectroscopy. Multivariate data analysis of the spectra showed a clear separation associated to a wide range of metabolites between zebra fish that were submitted to open field and light/dark field tests. Alanine, taurine, adenosine, creatine, lactate, and histidine were high in zebra fish to which the light/dark field test was applied, regardless of stress, while acetate and isoleucine/lipids appeared to be higher in zebra fish exposed to the open field test. These results show that any change in the environment, even for a small period of time, has a noticeable physiological impact. This research provides an insight of how different mechanisms are activated under different environments to maintain the homeostasis of the body. It should also contribute to establish zebra fish as a model for metabolomics studies. PMID:25098933

  5. Metabolomics in the Rhizosphere: Tapping into Belowground Chemical Communication.

    PubMed

    van Dam, Nicole M; Bouwmeester, Harro J

    2016-03-01

    The rhizosphere is densely populated with a variety of organisms. Interactions between roots and rhizosphere community members are mostly achieved via chemical communication. Root exudates contain an array of primary and secondary plant metabolites that can attract, deter, or kill belowground insect herbivores, nematodes, and microbes, and inhibit competing plants. Metabolomics of root exudates can potentially help us to better understand this chemical dialogue. The main limitations are the proper sampling of the exudate, the sensitivity of the metabolomics platforms, and the multivariate data analysis to identify causal relations. Novel technologies may help to generate a spatially explicit metabolome of the root and its exudates at a scale that is relevant for the rhizosphere community. PMID:26832948

  6. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

    PubMed Central

    Hong, Jun; Yang, Litao; Zhang, Dabing; Shi, Jianxin

    2016-01-01

    As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality. PMID:27258266

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

    PubMed Central

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

    2013-01-01

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

  8. Clinical metabolomics paves the way towards future healthcare strategies

    PubMed Central

    Collino, Sebastiano; Martin, François‐Pierre J.; Rezzi, Serge

    2013-01-01

    Metabolomics is recognized as a powerful top‐down system biological approach to understand genetic‐environment‐health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation. PMID:22348240

  9. A metabolomic approach differentiates between conventional and organic ketchups.

    PubMed

    Vallverdú-Queralt, Anna; Medina-Remón, Alexander; Casals-Ribes, Isidre; Amat, Mercedes; Lamuela-Raventós, Rosa Maria

    2011-11-01

    The agronomic environments in which tomatoes are cultivated potentially affect the levels of antioxidants and other metabolites in commercial products. In this study, biochemical and metabolomic techniques were used to assess the differences between ketchups produced by organic and conventional systems. An untargeted metabolomic approach using QToF-MS was used to identify those nutrients that have the greatest impact on the overall metabolomic profile of organic ketchups as compared to conventional ones. Individual polyphenols were quantified using LC-ESI-QqQ. This multifaceted approach revealed that the agronomic environment in which tomatoes are grown induces alterations in the content of antioxidant capacity, phenolics, and other metabolites in ketchups. Organic cultivation was found to provide tomatoes and tomato-derived products with a significantly higher content of antioxidant microconstituents, whereas glutamylphenylalanine and N-malonyltryptophan were detected only in conventional ketchups. PMID:21958116

  10. Metabolome progression during early gut microbial colonization of gnotobiotic mice.

    PubMed

    Marcobal, Angela; Yusufaly, Tahir; Higginbottom, Steven; Snyder, Michael; Sonnenburg, Justin L; Mias, George I

    2015-01-01

    The microbiome has been implicated directly in host health, especially host metabolic processes and development of immune responses. These are particularly important in infants where the gut first begins being colonized, and such processes may be modeled in mice. In this investigation we follow longitudinally the urine metabolome of ex-germ-free mice, which are colonized with two bacterial species, Bacteroides thetaiotaomicron and Bifidobacterium longum. High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series analysis to urine metabolomics data. Results demonstrate both gradual and punctuated changes in metabolite production and that early colonization events profoundly impact the nature of small molecules circulating in the host. The identified small molecules are implicated in amino acid and carbohydrate metabolic processes, and offer insights into the dynamic changes occurring during the colonization process, using high-throughput longitudinal methodology. PMID:26118551

  11. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

    PubMed Central

    2015-01-01

    An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. As a result of this unique integration, we can analyze large profiling datasets and simultaneously obtain structural identifications. Validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometry data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level. PMID:25496351

  12. Autonomous metabolomics for rapid metabolite identification in global profiling.

    PubMed

    Benton, H Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G; Kurczy, Michael E; Johnson, Caroline H; Franco, Lauren; Rinehart, Duane; Valentine, Elizabeth; Gowda, Harsha; Ubhi, Baljit K; Tautenhahn, Ralf; Gieschen, Andrew; Fields, Matthew W; Patti, Gary J; Siuzdak, Gary

    2015-01-20

    An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. As a result of this unique integration, we can analyze large profiling datasets and simultaneously obtain structural identifications. Validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometry data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level. PMID:25496351

  13. Metabolomics of AS-5 RBC supernatants following routine storage

    PubMed Central

    D’Alessandro, A.; Hansen, K. C.; Silliman, C. C.; Moore, E. E.; Kelher, M.; Banerjee, A.

    2015-01-01

    Background and Objectives The safety and efficacy of stored red blood cells (RBCs) transfusion has been long debated due to retrospective clinical evidence and laboratory results, indicating a potential correlation between increased morbidity and mortality following transfusion of RBC units stored longer than 14 days. We hypothesize that storage in Optisol additive solution-5 leads to a unique metabolomics profile in the supernatant of stored RBCs. Materials and Methods Whole blood was drawn from five healthy donors, RBC units were manufactured, and prestorage leucoreduced by filtration. Samples were taken on days 1 and 42, the cells removed, and mass spectrometry-based metabolomics was performed. Results The results confirmed the progressive impairment of RBC energy metabolism by day 42 with indirect markers of a parallel alteration of glutathione and NADPH homeostasis. Moreover, oxidized pro-inflammatory lipids accumulated by the end of storage. Conclusion The supernatants from stored RBCs may represent a burden to the transfused recipients from a metabolomics standpoint. PMID:25200932

  14. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science.

    PubMed

    Hong, Jun; Yang, Litao; Zhang, Dabing; Shi, Jianxin

    2016-01-01

    As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality. PMID:27258266

  15. Metabolome progression during early gut microbial colonization of gnotobiotic mice

    PubMed Central

    Marcobal, Angela; Yusufaly, Tahir; Higginbottom, Steven; Snyder, Michael; Sonnenburg, Justin L.; Mias, George I.

    2015-01-01

    The microbiome has been implicated directly in host health, especially host metabolic processes and development of immune responses. These are particularly important in infants where the gut first begins being colonized, and such processes may be modeled in mice. In this investigation we follow longitudinally the urine metabolome of ex-germ-free mice, which are colonized with two bacterial species, Bacteroides thetaiotaomicron and Bifidobacterium longum. High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series analysis to urine metabolomics data. Results demonstrate both gradual and punctuated changes in metabolite production and that early colonization events profoundly impact the nature of small molecules circulating in the host. The identified small molecules are implicated in amino acid and carbohydrate metabolic processes, and offer insights into the dynamic changes occurring during the colonization process, using high-throughput longitudinal methodology. PMID:26118551

  16. Analyzing methods for path mining with applications in metabolomics.

    PubMed

    Tagore, Somnath; Chowdhury, Nirmalya; De, Rajat K

    2014-01-25

    Metabolomics is one of the key approaches of systems biology that consists of studying biochemical networks having a set of metabolites, enzymes, reactions and their interactions. As biological networks are very complex in nature, proper techniques and models need to be chosen for their better understanding and interpretation. One of the useful strategies in this regard is using path mining strategies and graph-theoretical approaches that help in building hypothetical models and perform quantitative analysis. Furthermore, they also contribute to analyzing topological parameters in metabolome networks. Path mining techniques can be based on grammars, keys, patterns and indexing. Moreover, they can also be used for modeling metabolome networks, finding structural similarities between metabolites, in-silico metabolic engineering, shortest path estimation and for various graph-based analysis. In this manuscript, we have highlighted some core and applied areas of path-mining for modeling and analysis of metabolic networks. PMID:24230973

  17. What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

    PubMed

    Gonzalez-Franquesa, Alba; Burkart, Alison M; Isganaitis, Elvira; Patti, Mary-Elizabeth

    2016-08-01

    Type 2 diabetes (T2D) is increasing worldwide, making identification of biomarkers for detection, staging, and effective prevention strategies an especially critical scientific and medical goal. Fortunately, advances in metabolomics techniques, together with improvements in bioinformatics and mathematical modeling approaches, have provided the scientific community with new tools to describe the T2D metabolome. The metabolomics signatures associated with T2D and obesity include increased levels of lactate, glycolytic intermediates, branched-chain and aromatic amino acids, and long-chain fatty acids. Conversely, tricarboxylic acid cycle intermediates, betaine, and other metabolites decrease. Future studies will be required to fully integrate these and other findings into our understanding of diabetes pathophysiology and to identify biomarkers of disease risk, stage, and responsiveness to specific treatments. PMID:27319324

  18. Biochemical mechanisms of nephrotoxicity: application for metabolomics.

    PubMed

    Niemann, Claus U; Serkova, Natalie J

    2007-08-01

    This review describes biochemical pathways of nephrotoxicity and the application of metabolic biomarkers as they relate to nephrotoxicity. Specific and sensitive biomarkers constitute the missing link in the continuum of exposure to toxins and susceptibility, disease development and possible therapeutic intervention. Important requirements for biomarker development are a detailed understanding of biochemical pathways involved in nephrotoxicity, minimal invasiveness and capacity to screen large at-risk populations. Lastly, possible biomarker candidates should be organ specific and equally applicable in preclinical drug testing as well as in clinical care of patients. This review discusses four major metabolic pathways associated with disturbed renal homeostasis: i) direct metabolic evidence of abnormal excretion of endogenous metabolites; ii) disturbances in kidney osmolarity and renal osmolyte homeostasis; iii) impaired energy state followed by dysregulation of glucose, fatty acid and ketone body metabolism; and iv) oxidative stress in renal tissues. Each of these pathways can be monitored by specific surrogate markers in urine and blood using modern metabolomics technologies. PMID:17696804

  19. Genetic Basis of Metabolome Variation in Yeast

    PubMed Central

    Breunig, Jeffrey S.; Hackett, Sean R.; Rabinowitz, Joshua D.; Kruglyak, Leonid

    2014-01-01

    Metabolism, the conversion of nutrients into usable energy and biochemical building blocks, is an essential feature of all cells. The genetic factors responsible for inter-individual metabolic variability remain poorly understood. To investigate genetic causes of metabolome variation, we measured the concentrations of 74 metabolites across 100 segregants from a Saccharomyces cerevisiae cross by liquid chromatography-tandem mass spectrometry. We found 52 quantitative trait loci for 34 metabolites. These included linkages due to overt changes in metabolic genes, e.g., linking pyrimidine intermediates to the deletion of ura3. They also included linkages not directly related to metabolic enzymes, such as those for five central carbon metabolites to ira2, a Ras/PKA pathway regulator, and for the metabolites, S-adenosyl-methionine and S-adenosyl-homocysteine to slt2, a MAP kinase involved in cell wall integrity. The variant of ira2 that elevates metabolite levels also increases glucose uptake and ethanol secretion. These results highlight specific examples of genetic variability, including in genes without prior known metabolic regulatory function, that impact yeast metabolism. PMID:24603560

  20. Obesity and Asthma: Microbiome-Metabolome Interactions.

    PubMed

    Shore, Stephanie A; Cho, Youngji

    2016-05-01

    Obesity is a risk factor for asthma, but obese subjects with asthma respond poorly to standard asthma drugs. Obesity also alters gut bacterial community structure. Obesity-related changes in gut bacteria contribute to weight gain and other obesity-related conditions, including insulin resistance and systemic inflammation. Here, we review the rationale for the hypothesis that obesity-related changes in gut bacteria may also play a role in obesity-related asthma. The metabolomes of the liver, serum, urine, and adipose tissue are altered in obesity. Gut bacteria produce a large number of metabolites, which can reach the blood and circulate to other organs, and gut bacteria-derived metabolites have been shown to contribute to disease processes outside the gastrointestinal tract, including cardiovascular disease. Here, we describe the potential roles for two such classes of metabolites in obesity-related asthma: short-chain fatty acids and bile acids. Greater understanding of the role of microbiota in obesity-related asthma could lead to novel microbiota-based treatments for these hard-to-treat patients. PMID:26949916

  1. The Siderophore Metabolome of Azotobacter vinelandii

    PubMed Central

    Baars, Oliver; Zhang, Xinning

    2015-01-01

    In this study, we performed a detailed characterization of the siderophore metabolome, or “chelome,” of the agriculturally important and widely studied model organism Azotobacter vinelandii. Using a new high-resolution liquid chromatography-mass spectrometry (LC-MS) approach, we found over 35 metal-binding secondary metabolites, indicative of a vast chelome in A. vinelandii. These include vibrioferrin, a siderophore previously observed only in marine bacteria. Quantitative analyses of siderophore production during diazotrophic growth with different sources and availabilities of Fe showed that, under all tested conditions, vibrioferrin was present at the highest concentration of all siderophores and suggested new roles for vibrioferrin in the soil environment. Bioinformatic searches confirmed the capacity for vibrioferrin production in Azotobacter spp. and other bacteria spanning multiple phyla, habitats, and lifestyles. Moreover, our studies revealed a large number of previously unreported derivatives of all known A. vinelandii siderophores and rationalized their origins based on genomic analyses, with implications for siderophore diversity and evolution. Together, these insights provide clues as to why A. vinelandii harbors multiple siderophore biosynthesis gene clusters. Coupled with the growing evidence for alternative functions of siderophores, the vast chelome in A. vinelandii may be explained by multiple, disparate evolutionary pressures that act on siderophore production. PMID:26452553

  2. Alcohol-induced metabolomic differences in humans.

    PubMed

    Jaremek, M; Yu, Z; Mangino, M; Mittelstrass, K; Prehn, C; Singmann, P; Xu, T; Dahmen, N; Weinberger, K M; Suhre, K; Peters, A; Döring, A; Hauner, H; Adamski, J; Illig, T; Spector, T D; Wang-Sattler, R

    2013-01-01

    Alcohol consumption is one of the world's major risk factors for disease development. But underlying mechanisms by which moderate-to-heavy alcohol intake causes damage are poorly understood and biomarkers are sub-optimal. Here, we investigated metabolite concentration differences in relation to alcohol intake in 2090 individuals of the KORA F4 and replicated results in 261 KORA F3 and up to 629 females of the TwinsUK adult bioresource. Using logistic regression analysis adjusted for age, body mass index, smoking, high-density lipoproteins and triglycerides, we identified 40/18 significant metabolites in males/females with P-values <3.8E-04 (Bonferroni corrected) that differed in concentrations between moderate-to-heavy drinkers (MHD) and light drinkers (LD) in the KORA F4 study. We further identified specific profiles of the 10/5 metabolites in males/females that clearly separated LD from MHD in the KORA F4 cohort. For those metabolites, the respective area under the receiver operating characteristic curves were 0.812/0.679, respectively, thus providing moderate-to-high sensitivity and specificity for the discrimination of LD to MHD. A number of alcohol-related metabolites could be replicated in the KORA F3 and TwinsUK studies. Our data suggests that metabolomic profiles based on diacylphosphatidylcholines, lysophosphatidylcholines, ether lipids and sphingolipids form a new class of biomarkers for excess alcohol intake and have potential for future epidemiological and clinical studies. PMID:23820610

  3. Radiation metabolomics and its potential in biodosimetry

    PubMed Central

    Coy, Stephen L.; Cheema, Amrita K.; Tyburski, John B.; Laiakis, Evagelia C.; Collins, Sean P.; Fornace, Albert J.

    2013-01-01

    Purpose Radiation exposure triggers a complex network of molecular and cellular responses that impacts metabolic processes and alters the levels of metabolites. Such metabolites have potential as biomarkers for radiation dosimetry. This review provides an overview of radiation signalling and metabolism, of metabolomic approaches used in the discovery phase, and of instrumentation with the potential to assess radiation injury in the field. Approach Recent developments in fast, high-resolution chromatography and mass spectrometry and new data analysis methods allow the quantitative assessment of thousands of metabolites based on biofluids obtained non-invasively. This complex analysis leads to the discovery-phase identification of groups of metabolites useful for screening and biodosimetry by targeted quantitative measurement. Instrumentation for target analysis can be simpler than that used for discovery, so we examine current technologies based on ion mobility. Conclusions Recent published results and ongoing studies examine the complex changes in the levels of many metabolites caused by radiation exposure, and identify groups of small-molecule biomarkers for radiation biodosimetry. Based on results showing separation orthogonal to mass, chemical noise suppression, and high sensitivity, differential mobility mass spectrometry (DMS-MS) ion mobility spectrometry appears highly promising for the development of deployable instrumentation. PMID:21692691

  4. Genetic Influences on Metabolite Levels: A Comparison across Metabolomic Platforms.

    PubMed

    Yet, Idil; Menni, Cristina; Shin, So-Youn; Mangino, Massimo; Soranzo, Nicole; Adamski, Jerzy; Suhre, Karsten; Spector, Tim D; Kastenmüller, Gabi; Bell, Jordana T

    2016-01-01

    Metabolomic profiling is a powerful approach to characterize human metabolism and help understand common disease risk. Although multiple high-throughput technologies have been developed to assay the human metabolome, no technique is capable of capturing the entire human metabolism. Large-scale metabolomics data are being generated in multiple cohorts, but the datasets are typically profiled using different metabolomics platforms. Here, we compared analyses across two of the most frequently used metabolomic platforms, Biocrates and Metabolon, with the aim of assessing how complimentary metabolite profiles are across platforms. We profiled serum samples from 1,001 twins using both targeted (Biocrates, n = 160 metabolites) and non-targeted (Metabolon, n = 488 metabolites) mass spectrometry platforms. We compared metabolite distributions and performed genome-wide association analyses to identify shared genetic influences on metabolites across platforms. Comparison of 43 metabolites named for the same compound on both platforms indicated strong positive correlations, with few exceptions. Genome-wide association scans with high-throughput metabolic profiles were performed for each dataset and identified genetic variants at 7 loci associated with 16 unique metabolites on both platforms. The 16 metabolites showed consistent genetic associations and appear to be robustly measured across platforms. These included both metabolites named for the same compound across platforms as well as unique metabolites, of which 2 (nonanoylcarnitine (C9) [Biocrates]/Unknown metabolite X-13431 [Metabolon] and PC aa C28:1 [Biocrates]/1-stearoylglycerol [Metabolon]) are likely to represent the same or related biochemical entities. The results demonstrate the complementary nature of both platforms, and can be informative for future studies of comparative and integrative metabolomics analyses in samples profiled on different platforms. PMID:27073872

  5. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action

    PubMed Central

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

    2016-01-01

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

  6. Discovering Oxysterols in Plasma: A Window on the Metabolome

    PubMed Central

    Griffiths, William J.; Hornshaw, Martin; Woffendin, Gary; Baker, Sharon F.; Lockhart, Andrew; Heidelberger, Sibylle; Gustafsson, Magnus; Sjövall, Jan; Wang, Yuqin

    2008-01-01

    While the proteome defines the expressed gene products, the metabolome results from reactions controlled by such gene products. Plasma represents an accessible “window” to the metabolome both in regard of availability and content. The wide range of the plasma metabolome, in terms of molecular diversity and abundance, makes its comprehensive analysis challenging. Here we demonstrate an analytical method designed to target one region of the metabolome i.e. oxysterols. Since the discovery of their biological activity as ligands to nuclear receptors there has been a reawakening of interest in oxysterols and their analysis. In addition, the oxysterols, 24S- and 27-hydroxycholesterol, are currently under investigation as potential biomarkers associated with neurodegenerative disorders such as Alzheimer's disease and multiple sclerosis; widespread analysis of these lipids in clinical studies will require the development of robust, sensitive and rapid analytical techniques. In this communication we present results of an investigation of the oxysterols content of human plasma using a newly developed high-performance liquid chromatography – mass spectrometry (HPLC-MS) method incorporating charge-tagging and high-resolution MS. The method has allowed the identification in plasma of monohydroxylated cholesterol molecules, 7α-, 24S- and 27-hydroxycholesterol; the cholestenetriol 7α,27-dihydroxycholesterol; and 3β-hydroxycholest-5-en-27-oic acid and its metabolite and 3β,7α-dihydroxycholest-5-en-27-oic acid. The methodology described is also applicable for the analysis of other sterols in plasma i.e. cholesterol, 7-dehydrocholesterol, and desmosterol, as well as cholesterol 5,6-seco-sterols and steroid hormones. Although involving derivatisation, sample preparation is straight forward and chromatographic analysis rapid (17 min), while the MS method offers high sensitivity (ng/mL of sterol in plasma, or pg on-column) and specificity. The methodology is suitable for

  7. Genetic Influences on Metabolite Levels: A Comparison across Metabolomic Platforms

    PubMed Central

    Yet, Idil; Menni, Cristina; Shin, So-Youn; Mangino, Massimo; Soranzo, Nicole; Adamski, Jerzy; Suhre, Karsten; Spector, Tim D.

    2016-01-01

    Metabolomic profiling is a powerful approach to characterize human metabolism and help understand common disease risk. Although multiple high-throughput technologies have been developed to assay the human metabolome, no technique is capable of capturing the entire human metabolism. Large-scale metabolomics data are being generated in multiple cohorts, but the datasets are typically profiled using different metabolomics platforms. Here, we compared analyses across two of the most frequently used metabolomic platforms, Biocrates and Metabolon, with the aim of assessing how complimentary metabolite profiles are across platforms. We profiled serum samples from 1,001 twins using both targeted (Biocrates, n = 160 metabolites) and non-targeted (Metabolon, n = 488 metabolites) mass spectrometry platforms. We compared metabolite distributions and performed genome-wide association analyses to identify shared genetic influences on metabolites across platforms. Comparison of 43 metabolites named for the same compound on both platforms indicated strong positive correlations, with few exceptions. Genome-wide association scans with high-throughput metabolic profiles were performed for each dataset and identified genetic variants at 7 loci associated with 16 unique metabolites on both platforms. The 16 metabolites showed consistent genetic associations and appear to be robustly measured across platforms. These included both metabolites named for the same compound across platforms as well as unique metabolites, of which 2 (nonanoylcarnitine (C9) [Biocrates]/Unknown metabolite X-13431 [Metabolon] and PC aa C28:1 [Biocrates]/1-stearoylglycerol [Metabolon]) are likely to represent the same or related biochemical entities. The results demonstrate the complementary nature of both platforms, and can be informative for future studies of comparative and integrative metabolomics analyses in samples profiled on different platforms. PMID:27073872

  8. Medicinal plants: a public resource for metabolomics and hypothesis development.

    PubMed

    Wurtele, Eve Syrkin; Chappell, Joe; Jones, A Daniel; Celiz, Mary Dawn; Ransom, Nick; Hur, Manhoi; Rizshsky, Ludmila; Crispin, Matthew; Dixon, Philip; Liu, Jia; P Widrlechner, Mark; Nikolau, Basil J

    2012-01-01

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

  9. Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

    PubMed Central

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

    2015-01-01

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

  10. Mitochondrial responses to extreme environments: insights from metabolomics.

    PubMed

    O'Brien, Katie A; Griffin, Julian L; Murray, Andrew J; Edwards, Lindsay M

    2015-01-01

    Humans are capable of survival in a remarkable range of environments, including the extremes of temperature and altitude as well as zero gravity. Investigation into physiological function in response to such environmental stresses may help further our understanding of human (patho-) physiology both at a systems level and in certain disease states, making it a highly relevant field of study. This review focuses on the application of metabolomics in assessing acclimatisation to these states, particularly the insights this approach can provide into mitochondrial function. It includes an overview of metabolomics and the associated analytical tools and also suggests future avenues of research. PMID:25949809

  11. [Metabolomics has the potential to improve drug therapy.

    PubMed

    Stage, Claus; Jürgens, Gesche; Dalhoff, Kim Peder; Rasmussen, Henrik Berg

    2014-03-17

    Until now drug therapy has primarily been controlled by dose titration on the basis of effects and side effects. However, a lot of people being treated with a drug experience too little effect or too many side effects. Therefore it will be advantageous to improve drug therapy and make it even more "individualized". In this chase metabolomics is a hot topic. The aim of this paper is to review the concepts of metabolomics and the possible applications in regard to drug development, drug therapy and diagnosis, prognosis and monitoring of diseases. PMID:25096206

  12. Metabolomic Profiling of Arginine Metabolome Links Altered Methylation to Chronic Kidney Disease Accelerated Atherosclerosis

    PubMed Central

    Mathew, Anna V; Zeng, Lixia; Byun, Jaeman; Pennathur, Subramaniam

    2015-01-01

    Atherosclerotic cardiovascular disease is the leading cause of death in patients with chronic kidney disease (CKD), but the mechanisms underlying vascular disease has not been fully understood. As the nitrogen donor in nitric oxide (NO·) synthesis, arginine and its metabolic products are integrally linked to vascular health and information. We hypothesized that derangements in this pathway could explain, in part, increased atherosclerotic risk in CKD. We developed a targeted metabolomic platform to profile quantitatively arginine metabolites in plasma by liquid chromatography tandem mass spectrometry (LC/MS). Male low-density lipoprotein receptor defcient (LDLr−/−) mice at age 6 weeks were subjected to sham or 5/6 nephrectomy surgery to induce CKD. Subsequently, the animals were maintained on high fat diet for 24 weeks. Targeted metabolomic analysis of arginine metabolites in plasma was performed by isotope dilution LC/MS including asymmetric dimethyl arginine (ADMA), symmetric dimethyl arginine (SDMA), N-mono-methylarginine (NMMA), arginine and citrulline. Although elevated plasma levels of ADMA and SDMA were found in the CKD mice, only higher ADMA level correlated with degree of atherosclerosis. No significant differences were noted in levels of NMMA between the groups. CKD mice had high levels of citrulline and arginine, but ADMA levels had no correlation with either of these metabolites. These fndings strongly implicate altered arginine methylation and accumulation of ADMA, may in part contribute to CKD accelerated atherosclerosis. It raises the possibility that interrupting pathways that generate ADMA or enhance its metabolism may have therapeutic potential in mitigating atherosclerosis. PMID:26778898

  13. Omics-Based Biomarkers: Application of Metabolomics in Neuropsychiatric Disorders

    PubMed Central

    Sethi, Sumit

    2016-01-01

    One of the major concerns of modern society is to identify putative biomarkers that serve as a valuable early diagnostic tool to identify a subset of patients with increased risk to develop neuropsychiatric disorders. Biomarker identification in neuropsychiatric disorders is proposed to offer a number of important benefits to patient well-being, including prediction of forthcoming disease, diagnostic precision, and a level of disease description that would guide treatment choice. Nowadays, the metabolomics approach has unlocked new possibilities in diagnostics of devastating disorders like neuropsychiatric disorders. Metabolomics-based technologies have the potential to map early biochemical changes in disease and hence provide an opportunity to develop predictive biomarkers that can be used as indicators of pathological abnormalities prior to development of clinical symptoms of neuropsychiatric disorders. This review highlights different -omics strategies for biomarker discovery in neuropsychiatric disorders. We also highlight initial outcomes from metabolomics studies in psychiatric disorders such as schizophrenia, bipolar disorder, and addictive disorders. This review will also present issues and challenges regarding the implementation of the metabolomics approach as a routine diagnostic tool in the clinical laboratory in context with neuropsychiatric disorders. PMID:26453695

  14. APPLICATION OF METABOLOMICS FOR IMPROVING ECOLOGICAL EXPOSURE AND RISK ASSESSMENTS

    EPA Science Inventory

    We have developed a research program in metabolomics that involves numerous partners across EPA, other federal labs, academia, and the private sector. A primary goal is to develop metabolite-based markers that can be used by EPA in ecological exposure and risk assessments. We are...

  15. A METABOLOMIC APPROACH TO UNDERSTANDING ENDOCRINE DISRUPTION IN FATHEAD MINNOW

    EPA Science Inventory

    Although widely used in the study of rodent toxicity responses to assess human risk, metabolomics is now finding utility in toxicity assessments in a wide variety of other organisms including environmentally relevant small fish species such as fathead minnow (FHM) and medaka. To...

  16. METABOLOMIC STUDIES OF ENDOCRINE DISRUPTION IN SMALL FISH MODELS

    EPA Science Inventory

    Metabolomics is now being widely used to obtain complementary information to genomic and proteomic studies. To better understand temporal, compensatory and dose responses to endocrine-disrupting chemicals (EDCs) within the hypothalamic-pituitary¬gonadal (HPG) axis, we have carrie...

  17. Metabolome-Wide Association Study of Primary Open Angle Glaucoma

    PubMed Central

    Burgess, L. Goodwin; Uppal, Karan; Walker, Douglas I.; Roberson, Rachel M.; Tran, ViLinh; Parks, Megan B.; Wade, Emily A.; May, Alexandra T.; Umfress, Allison C.; Jarrell, Kelli L.; Stanley, Brooklyn O. C.; Kuchtey, John; Kuchtey, Rachel W.; Jones, Dean P.; Brantley, Milam A.

    2015-01-01

    Purpose To determine if primary open-angle glaucoma (POAG) patients can be differentiated from controls based on metabolic characteristics. Methods We used ultra-high resolution mass spectrometry with C18 liquid chromatography for metabolomic analysis on frozen plasma samples from 72 POAG patients and 72 controls. Metabolome-wide Spearman correlation was performed to select differentially expressed metabolites (DEM) correlated with POAG. We corrected P values for multiple testing using Benjamini and Hochberg false discovery rate (FDR). Hierarchical cluster analysis (HCA) was used to depict the relationship between participants and DEM. Differentially expressed metabolites were matched to the METLIN metabolomics database; both DEM and metabolites significantly correlating with DEM were analyzed using MetaboAnalyst to identify metabolic pathways altered in POAG. Results Of the 2440 m/z (mass/charge) features recovered after filtering, 41 differed between POAG cases and controls at FDR = 0.05. Hierarchical cluster analysis revealed these DEM to associate into eight clusters; three of these clusters contained the majority of the DEM and included palmitoylcarnitine, hydroxyergocalciferol, and high-resolution METLIN matches to sphingolipids, other vitamin D-related metabolites, and terpenes. MetaboAnalyst also indicated likely alteration in steroid biosynthesis pathways. Conclusions Global ultrahigh resolution metabolomics emphasized the importance of altered lipid metabolism in POAG. The results suggest specific metabolic processes, such as those involving palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors, may contribute to POAG status and merit more detailed study with targeted methods. PMID:26230767

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

    PubMed

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

    2016-07-01

    The advancement of omics technology has vigorously promoted the development of the life sciences; metabolomics in particular has emerged as a powerful tool that has a promising future in scientific research and clinical practice. As terminal products of complex biochemical networks, endogenous low-molecular-weight metabolites contain rich information about the physiological status of an individual or group of people. Also, this information has more practical significance in that we know "what happened" instead of "what might happen" to some degree. Rapid and accurate screening of metabolites on a large scale was beyond imagining in the past; however, benefiting from high-throughput technical means, the overall disturbance of metabolites induced by environmental stimulus or treatments can now be well analyzed. After appropriate bioinformatic analysis, clinically relevant biomarkers of a disease can be found, and an accurate and dynamic picture of metabolic disturbance that contributes to a phenotype of a certain organism can be constructed. Biomarkers can also reveal the general metabolic condition by pathways that correlate with disease progression, or even with the risk of certain diseases. Thus, as an indispensable part of the framework of systems biology, metabolomics has been widely used in, but not limited to, the fields of medical science, pharmaceuticals, botany, and microbiology. In this article, we focus on metabolomics' mainstream research content and technical innovations such as determination methods for biologically active compounds; further, we pay more attention to the future trends and various possibilities for metabolomics study. PMID:26337255

  19. 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

  20. Discovering Regulated Metabolite Families in Untargeted Metabolomics Studies.

    PubMed

    Treutler, Hendrik; Tsugawa, Hiroshi; Porzel, Andrea; Gorzolka, Karin; Tissier, Alain; Neumann, Steffen; Balcke, Gerd Ulrich

    2016-08-16

    The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS(1) abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application "MetFamily", which is freely available at http://msbi.ipb-halle.de/MetFamily/ . MetFamily provides a dynamic link between the patterns based on MS(1)-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS(1) patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato Solanum habrochaites LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR. PMID:27452369

  1. Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate.

    PubMed

    Misra, Biswapriya B; de Armas, Evaldo; Tong, Zhaohui; Chen, Sixue

    2015-01-01

    Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs) are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs) represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus) to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3-). Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3- responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3-. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids), and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids) as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage. PMID:26641455

  2. Plant metabolomics: from holistic hope, to hype, to hot topic.

    PubMed

    Hall, Robert D

    2006-01-01

    In a short time, plant metabolomics has gone from being just an ambitious concept to being a rapidly growing, valuable technology applied in the stride to gain a more global picture of the molecular organization of multicellular organisms. The combination of improved analytical capabilities with newly designed, dedicated statistical, bioinformatics and data mining strategies, is beginning to broaden the horizons of our understanding of how plants are organized and how metabolism is both controlled but highly flexible. Metabolomics is predicted to play a significant, if not indispensable role in bridging the phenotype-genotype gap and thus in assisting us in our desire for full genome sequence annotation as part of the quest to link gene to function. Plants are a fabulously rich source of diverse functional biochemicals and metabolomics is also already proving valuable in an applied context. By creating unique opportunities for us to interrogate plant systems and characterize their biochemical composition, metabolomics will greatly assist in identifying and defining much of the still unexploited biodiversity available today. PMID:16411949

  3. Highly Repeatable Dissolution Dynamic Nuclear Polarization for Heteronuclear NMR Metabolomics.

    PubMed

    Bornet, Aurélien; Maucourt, Mickaël; Deborde, Catherine; Jacob, Daniel; Milani, Jonas; Vuichoud, Basile; Ji, Xiao; Dumez, Jean-Nicolas; Moing, Annick; Bodenhausen, Geoffrey; Jannin, Sami; Giraudeau, Patrick

    2016-06-21

    At natural (13)C abundance, metabolomics based on heteronuclear NMR is limited by sensitivity. We have recently demonstrated how hyperpolarization by dissolution dynamic nuclear polarization (D-DNP) assisted by cross-polarization (CP) provides a reliable way of enhancing the sensitivity of heteronuclear NMR in dilute mixtures of metabolites. In this Technical Note, we evaluate the precision of this experimental approach, a critical point for applications to metabolomics. The higher the repeatability, the greater the likelihood that one can detect small biologically relevant differences between samples. The average repeatability of our state-of-the-art D-DNP NMR equipment for samples of metabolomic relevance (20 mg dry weight tomato extracts) is 3.6% for signals above the limit of quantification (LOQ) and 6.4% when all the signals above the limit of detection (LOD) are taken into account. This first report on the repeatability of D-DNP highlights the compatibility of the technique with the requirements of metabolomics and confirms its potential as an analytical tool for such applications. PMID:27253320

  4. Metabolomics: Insulin Resistance and Type 2 Diabetes Mellitus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Type 2 diabetes mellitus (T2DM) develops over many years, providing an opportunity to consider early prognostic tools that guide interventions to thwart disease. Advancements in analytical chemistry enable quantitation of hundreds of metabolites in biofluids and tissues (metabolomics), providing in...

  5. Advances in metabolomic applications in plant genetics and breeding

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metabolomics is a systems biology discipline wherein abundances of endogenous metabolites from biological samples are identified and quantitatively measured across a large range of metabolites and/or a large number of samples. Since all developmental, physiological and response to the environment ph...

  6. Nuclear magnetic resonance metabolomics of iron deficiency in soybean leaves

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Iron (Fe) deficiency is an important agricultural concern leading to lower yields and crop quality. A better understanding of the condition, at the metabolome level, could contribute to the design of strategies to ameliorate Fe deficiency problems. Fe-sufficient and Fe-deficient soybean leaf extract...

  7. Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate

    PubMed Central

    Misra, Biswapriya B.; de Armas, Evaldo; Tong, Zhaohui; Chen, Sixue

    2015-01-01

    Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs) are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs) represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus) to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3-). Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3- responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3-. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids), and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids) as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage. PMID:26641455

  8. Lipid metabolome-wide effects of the PPARgamma agonist rosiglitazone.

    PubMed

    Watkins, Steven M; Reifsnyder, Peter R; Pan, Huei-ju; German, J Bruce; Leiter, Edward H

    2002-11-01

    Successful therapy for chronic diseases must normalize a targeted aspect of metabolism without disrupting the regulation of other metabolic pathways essential for maintaining health. Use of a limited number of single molecule surrogates for disease, or biomarkers, to monitor the efficacy of a therapy may fail to predict undesirable side effects. In this study, a comprehensive metabolomic assessment of lipid metabolites was employed to determine the specific effects of the peroxisome proliferator-activated receptor gamma (PPARgamma) agonist rosiglitazone on structural lipid metabolism in a new mouse model of Type 2 diabetes. Dietary supplementation with rosiglitazone (200 mg/kg diet) suppressed Type 2 diabetes in obese (NZO x NON)F1 male mice, but chronic treatment markedly exacerbated hepatic steatosis. The metabolomic data revealed that rosiglitazone i) induced hypolipidemia (by dysregulating liver-plasma lipid exchange), ii) induced de novo fatty acid synthesis, iii) decreased the biosynthesis of lipids within the peroxisome, iv) substantially altered free fatty acid and cardiolipin metabolism in heart, and v) elicited an unusual accumulation of polyunsaturated fatty acids within adipose tissue. These observations suggest that the phenotypes induced by rosiglitazone are mediated by multiple tissue-specific metabolic variables. Because many of the effects of rosiglitazone on tissue metabolism were reflected in the plasma lipid metabolome, metabolomics has excellent potential for developing clinical assessments of metabolic response to drug therapy. PMID:12401879

  9. Improved drug therapy: triangulating phenomics with genomics and metabolomics

    PubMed Central

    2014-01-01

    Embracing the complexity of biological systems has a greater likelihood to improve prediction of clinical drug response. Here we discuss limitations of a singular focus on genomics, epigenomics, proteomics, transcriptomics, metabolomics, or phenomics—highlighting the strengths and weaknesses of each individual technique. In contrast, ‘systems biology’ is proposed to allow clinicians and scientists to extract benefits from each technique, while limiting associated weaknesses by supplementing with other techniques when appropriate. Perfect predictive modeling is not possible, whereas modeling of intertwined phenomic responses using genomic stratification with metabolomic modifications may greatly improve predictive values for drug therapy. We thus propose a novel-integrated approach to personalized medicine that begins with phenomic data, is stratified by genomics, and ultimately refined by metabolomic pathway data. Whereas perfect prediction of efficacy and safety of drug therapy is not possible, improvements can be achieved by embracing the complexity of the biological system. Starting with phenomics, the combination of linking metabolomics to identify common biologic pathways and then stratifying by genomic architecture, might increase predictive values. This systems biology approach has the potential, in specific subsets of patients, to avoid drug therapy that will be either ineffective or unsafe. PMID:25181945

  10. Xenobiotics Produce Distinct Metabolomic Responses in Zebrafish Larvae (Danio rerio).

    PubMed

    Huang, Susie S Y; Benskin, Jonathan P; Chandramouli, Bharat; Butler, Heather; Helbing, Caren C; Cosgrove, John R

    2016-06-21

    Sensitive and quantitative protocols for characterizing low-dose effects are needed to meet the demands of 21st century chemical hazard assessment. To test the hypothesis that xenobiotic exposure at environmentally relevant concentrations produces specific biochemical fingerprints in organisms, metabolomic perturbations in zebrafish (Danio rerio) embryo/larvae were measured following 24 h exposures to 13 individual chemicals covering a wide range of contaminant classes. Measured metabolites (208 in total) included amino acids, biogenic amines, fatty acids, bile acids, sugars, and lipids. The 96-120 h post-fertilization developmental stage was the most appropriate model for detecting xenobiotic-induced metabolomic perturbations. Metabolomic fingerprints were largely chemical- and dose-specific and were reproducible in multiple exposures over a 16-month period. Furthermore, chemical-specific responses were detected in the presence of an effluent matrix; importantly, in the absence of morphological response. In addition to improving sensitivity for detecting biological responses to low-level xenobiotic exposures, these data can aid the classification of novel contaminants based on the similarity of metabolomic responses to well-characterized "model" compounds. This approach is clearly of use for rapid, sensitive, and specific analyses of chemical effect on organisms, and can supplement existing methods, such as the Zebrafish Embryo Toxicity assay (OECD TG236), with molecular-level information. PMID:27232715

  11. 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...

  12. GENETICAL METABOLOMICS OF FLAVONOID BIOSYNTHESIS IN POPULUS: A CASE STUDY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetical metabolomics (metabolite profiling combined with quantitative trait locus [QTL] analysis) is proposed as a new tool to identify loci that control metabolite abundances. This concept was evaluated in a case study with the model tree Populus. By using HPLC, the peak abundances were analyzed ...

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

    PubMed

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

    2016-04-01

    The budding yeast Saccharomyces cerevisiae is widely used for brewing and ethanol production. The ethanol sensitivity of yeast cells is still a serious problem during ethanol fermentation, and a variety of genetic approaches (e.g., random mutant screening under selective pressure of ethanol) have been developed to improve ethanol tolerance. In this study, we developed a strategy for improving ethanol tolerance of yeast cells based on metabolomics as a high-resolution quantitative phenotypic analysis. We performed gas chromatography-mass spectrometry analysis to identify and quantify 36 compounds on 14 mutant strains including knockout strains for transcription factor and metabolic enzyme genes. A strong relation between metabolome of these mutants and their ethanol tolerance was observed. Data mining of the metabolomic analysis showed that several compounds (such as trehalose, valine, inositol and proline) contributed highly to ethanol tolerance. Our approach successfully detected well-known ethanol stress related metabolites such as trehalose and proline thus, to further prove our strategy, we focused on valine and inositol as the most promising target metabolites in our study. Our results show that simultaneous deletion of LEU4 and LEU9 (leading to accumulation of valine) or INM1 and INM2 (leading to reduction of inositol) significantly enhanced ethanol tolerance. This study shows the potential of the metabolomic approach to identify target genes for strain improvement of S. cerevisiae with higher ethanol tolerance. PMID:26344121

  14. The nutritional phenotype in the age of metabolomics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The concept of the nutritional phenotype is proposed as a defined and integrated set of genetic, proteomic, metabolomic, functional, and behavioral factors that, when measured, form the basis for assessment of human nutritional status. The nutritional phenotype integrates the effects of diet on dise...

  15. Metabolomic Analysis in Brain Research: Opportunities and Challenges.

    PubMed

    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

  16. 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

  17. The Role of Metabolomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools.

    PubMed

    Trezzi, Jean-Pierre; Vlassis, Nikos; Hiller, Karsten

    2015-01-01

    This chapter introduces the emerging field of metabolomics and its application in the context of cancer biomarker research. Taking advantage of modern high-throughput technologies, and enhanced computational power, metabolomics has a high potential for cancer biomarker identification and the development of diagnostic tools. This chapter describes current metabolomics technologies used in cancer research, starting with metabolomics sample preparation, elaborating on current analytical methodologies for metabolomics measurement and introducing existing software for data analysis. The last part of this chapter deals with the statistical analysis of very large metabolomics datasets and their relevance for cancer biomarker identification. PMID:26530359

  18. NMR-based metabolomics reveals urinary metabolome modifications in female Sprague-Dawley rats by cranberry procyanidins.

    PubMed

    Liu, Haiyan; Tayyari, Fariba; Edison, Arthur S; Su, Zhihua; Gu, Liwei

    2016-08-01

    A (1)H NMR global metabolomics approach was used to investigate the urinary metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) or partially purified apple procyanidins (PPAP). After collecting 24-h baseline urine, 24 female Sprague-Dawley rats were randomly separated into two groups and gavaged with PPCP or PPAP twice using a dose of 250 mg extracts per kilogram body weight. The 24-h urine samples were collected after the gavage. Urine samples were analyzed using (1)H NMR. Multivariate analyses showed that the urinary metabolome in rats was modified after administering PPCP or PPAP compared to baseline urine metabolic profiles. 2D (1)H-(13)C HSQC NMR was conducted to assist identification of discriminant metabolites. An increase of hippurate, lactate and succinate and a decrease of citrate and α-ketoglutarate were observed in rat urine after administering PPCP. Urinary levels of d-glucose, d-maltose, 3-(3'-hydroxyphenyl)-3-hydroxypropanoic acid, p-hydroxyphenylacetic acid, formate and phenol increased but citrate, α-ketoglutarate and creatinine decreased in rats after administering PPAP. Furthermore, the NMR analysis showed that the metabolome in the urine of rats administered with PPCP differed from those gavaged with PPAP. Compared to PPAP, PPCP caused an increase of urinary excretion of hippurate but a decrease of 3-(3'-hydroxyphenyl)-3-hydroxypropanoic acid, p-hydroxyphenylacetic acid and phenol. These metabolome changes caused by cranberry procyanidins may help to explain its reported health benefits and identify biomarkers of cranberry procyanidin intake. PMID:27309592

  19. Analytical Methods in Untargeted Metabolomics: State of the Art in 2015

    PubMed Central

    Alonso, Arnald; Marsal, Sara; Julià, Antonio

    2015-01-01

    Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile – the metabolome – has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance and mass spectrometry are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review, we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high-throughput biotechnologies is also reviewed. PMID:25798438

  20. Separating the inseparable: the metabolomic analysis of plant-pathogen interactions.

    PubMed

    Allwood, J William; Heald, Jim; Lloyd, Amanda J; Goodacre, Royston; Mur, Luis A J

    2012-01-01

    Plant-microbe interactions-whether pathogenic or symbiotic-exert major influences on plant physiology and productivity. Analysis of such interactions represents a particular challenge to metabolomic approaches due to the intimate association between the interacting partners coupled with a general commonality of metabolites. We here describe an approach based on co-cultivation of Arabidopsis cell cultures and bacterial plant pathogens to assess the metabolomes of both interacting partners, which we refer to as dual metabolomics. PMID:22351169

  1. Proteomics and Metabolomics: Two Emerging Areas for Legume Improvement

    PubMed Central

    Ramalingam, Abirami; Kudapa, Himabindu; Pazhamala, Lekha T.; Weckwerth, Wolfram; Varshney, Rajeev K.

    2015-01-01

    The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen) in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species, Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signaling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signaling in legumes. In this review, several

  2. Nuclear magnetic resonance: a key metabolomics platform in the drug discovery process.

    PubMed

    Leenders, Justine; Frédérich, Michel; de Tullio, Pascal

    2015-06-01

    Metabolomics is an innovative tool that is now emerging in the drug discovery process. Indeed, its ability to follow the dynamic perturbations in the metabolome resulting from pathologies but also from drug treatment and or/toxicity is of value for the development of new therapeutic approaches. Nuclear magnetic resonance (NMR) spectroscopy, which is an important analytical technique for several steps of the lead discovery, validation and optimization processes, has been described, together with mass spectrometry (MS) as one of the major platform that could be used for metabolomics studies. This review highlights why NMR could be considered a key tool for the application of metabolomics in drug discovery. PMID:26190682

  3. Metabolomic Imaging of Prostate Cancer with Magnetic Resonance Spectroscopy and Mass Spectrometry

    PubMed Central

    Spur, Eva-Margarete; Decelle, Emily A.; Cheng, Leo L.

    2013-01-01

    Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized non-invasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth for newly biopsy-diagnosed, asymptomatic PCa patients. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, the study of PCa metabolomics is mainly accomplished utilizing magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness non-invasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be possible not only with PCa, but applied to different tissues and organs to evaluate other human malignancies or metabolic diseases. PMID:23549758

  4. Metabolome consistency: additional parazoanthines from the mediterranean zoanthid parazoanthus axinellae.

    PubMed

    Audoin, Coralie; Cocandeau, Vincent; Thomas, Olivier P; Bruschini, Adrien; Holderith, Serge; Genta-Jouve, Grégory

    2014-01-01

    Ultra-high pressure liquid chromatography coupled to high resolution mass spectrometry (UHPLC-MS/MS) analysis of the organic extract obtained from the Mediterranean zoanthid Parazoanthus axinellae yielded to the identification of five new parazoanthines F-J. The structures were fully determined by comparison of fragmentation patterns with those of previously isolated parazoathines and MS/MS spectra simulation of in silico predicted compounds according to the metabolome consistency. The absolute configuration of the new compounds has been assigned using on-line electronic circular dichroism (UHPLC-ECD). We thus demonstrated the potential of highly sensitive hyphenated techniques to characterize the structures of a whole family of natural products within the metabolome of a marine species. Minor compounds can be characterized using these techniques thus avoiding long isolation processes that may alter the structure of the natural products. These results are also of interest to identify putative bioactive compounds present at low concentration in a complex mixture. PMID:24957034

  5. The MetaboLights repository: curation challenges in metabolomics

    PubMed Central

    Salek, Reza M.; Haug, Kenneth; Conesa, Pablo; Hastings, Janna; Williams, Mark; Mahendraker, Tejasvi; Maguire, Eamonn; González-Beltrán, Alejandra N.; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Steinbeck, Christoph

    2013-01-01

    MetaboLights is the first general-purpose open-access curated repository for metabolomic studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Increases in the number of depositions, number of samples per study and the file size of data submitted to MetaboLights present a challenge for the objective of ensuring high-quality and standardized data in the context of diverse metabolomic workflows and data representations. Here, we describe the MetaboLights curation pipeline, its challenges and its practical application in quality control of complex data depositions. Database URL: http://www.ebi.ac.uk/metabolights PMID:23630246

  6. Leveraging metabolomics for functional investigations in sequenced marine diatoms.

    PubMed

    Fernie, Alisdair R; Obata, Toshihiro; Allen, Andrew E; Araújo, Wagner L; Bowler, Chris

    2012-07-01

    Recent years have witnessed the genomic decoding of a wide range of photosynthetic organisms from the model plant Arabidopsis thaliana and the complex genomes of important crop species to single-celled marine phytoplankton. The comparative sequencing of green, red and brown algae has provided considerable insight into a number of important questions concerning their evolution, physiology and metabolism. The combinatorial application of metabolomics has further deepened our understanding both of the function of individual genes and of metabolic processes. Here we discuss the power of utilising metabolomics in conjunction with sequencing data to gain greater insight into the metabolic hierarchies underpinning the function of individual organisms, using unicellular marine diatoms as a case study to exemplify the advantages of this approach. PMID:22465020

  7. The MetaboLights repository: curation challenges in metabolomics.

    PubMed

    Salek, Reza M; Haug, Kenneth; Conesa, Pablo; Hastings, Janna; Williams, Mark; Mahendraker, Tejasvi; Maguire, Eamonn; González-Beltrán, Alejandra N; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Steinbeck, Christoph

    2013-01-01

    MetaboLights is the first general-purpose open-access curated repository for metabolomic studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Increases in the number of depositions, number of samples per study and the file size of data submitted to MetaboLights present a challenge for the objective of ensuring high-quality and standardized data in the context of diverse metabolomic workflows and data representations. Here, we describe the MetaboLights curation pipeline, its challenges and its practical application in quality control of complex data depositions. Database URL: http://www.ebi.ac.uk/metabolights. PMID:23630246

  8. Metabolomics of Δ(9)-tetrahydrocannabinol: implications in toxicity.

    PubMed

    Dinis-Oliveira, Ricardo Jorge

    2016-02-01

    Cannabis sativa is the most commonly used recreational drug, Δ(9)-tetrahydrocannabinol (Δ(9)-THC) being the main addictive compound. Biotransformation of cannabinoids is an important field of xenobiochemistry and toxicology and the study of the metabolism can lead to the discovery of new compounds, unknown metabolites with unique structures and new therapeutic effects. The pharmacokinetics of Δ(9)-THC is dependent on multiple factors such as physical/chemical form, route of administration, genetics, and concurrent consumption of alcohol. This review aims to discuss metabolomics of Δ(9)-THC, namely by presenting all known metabolites of Δ(9)-THC described both in vitro and in vivo, and their roles in the Δ(9)-THC-mediated toxic effects. Since medicinal use is increasing, metabolomics of Δ(9)-THC will also be discussed in order to uncover potential active metabolites that can be made available for this purpose. PMID:26828228

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

    PubMed

    Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Nielsen, Henrik Bjørn; Hyotylainen, Tuulia; Nielsen, Trine; Jensen, Benjamin A H; Forslund, Kristoffer; Hildebrand, Falk; Prifti, Edi; Falony, Gwen; Le Chatelier, Emmanuelle; Levenez, Florence; Doré, Joel; Mattila, Ismo; Plichta, Damian R; Pöhö, Päivi; Hellgren, Lars I; Arumugam, Manimozhiyan; Sunagawa, Shinichi; Vieira-Silva, Sara; Jørgensen, Torben; Holm, Jacob Bak; Trošt, Kajetan; Kristiansen, Karsten; Brix, Susanne; Raes, Jeroen; Wang, Jun; Hansen, Torben; Bork, Peer; Brunak, Søren; Oresic, Matej; Ehrlich, S Dusko; Pedersen, Oluf

    2016-07-21

    Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin-resistant individuals is characterized by increased levels of branched-chain amino acids (BCAAs), which correlate with a gut microbiome that has an enriched biosynthetic potential for BCAAs and is deprived of genes encoding bacterial inward transporters for these amino acids. Prevotella copri and Bacteroides vulgatus are identified as the main species driving the association between biosynthesis of BCAAs and insulin resistance, and in mice we demonstrate that P. copri can induce insulin resistance, aggravate glucose intolerance and augment circulating levels of BCAAs. Our findings suggest that microbial targets may have the potential to diminish insulin resistance and reduce the incidence of common metabolic and cardiovascular disorders. PMID:27409811

  10. Using next generation transcriptome sequencing to predict an ectomycorrhizal metabolome

    PubMed Central

    2011-01-01

    Background Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. Results We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models using a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. Conclusions The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems. PMID:21569493

  11. Metabolomic characterization of laborers exposed to welding fumes.

    PubMed

    Wang, Kuo-Ching; Kuo, Ching-Hua; Tian, Tze-Feng; Tsai, Mong-Hsun; Chiung, Yin-Mei; Hsiech, Chun-Ming; Tsai, Sung-Jeng; Wang, San-Yuan; Tsai, Dong-Ming; Huang, Chiang-Ching; Tseng, Y Jane

    2012-03-19

    The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders. PMID:22292500

  12. The Time Is Right to Focus on Model Organism Metabolomes.

    PubMed

    Edison, Arthur S; Hall, Robert D; Junot, Christophe; Karp, Peter D; Kurland, Irwin J; Mistrik, Robert; Reed, Laura K; Saito, Kazuki; Salek, Reza M; Steinbeck, Christoph; Sumner, Lloyd W; Viant, Mark R

    2016-01-01

    Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research. PMID:26891337

  13. Computational Metabolomics Operations at BioCyc.org

    PubMed Central

    Karp, Peter D.; Billington, Richard; Holland, Timothy A.; Kothari, Anamika; Krummenacker, Markus; Weaver, Daniel; Latendresse, Mario; Paley, Suzanne

    2015-01-01

    BioCyc.org is a genome and metabolic pathway web portal covering 5500 organisms, including Homo sapiens, Arabidopsis thaliana, Saccharomyces cerevisiae and Escherichia coli. These organism-specific databases have undergone variable degrees of curation. The EcoCyc (Escherichia coli Encyclopedia) database is the most highly curated; its contents have been derived from 27,000 publications. The MetaCyc (Metabolic Encyclopedia) database within BioCyc is a “universal” metabolic database that describes pathways, reactions, enzymes and metabolites from all domains of life. Metabolic pathways provide an organizing framework for analyzing metabolomics data, and the BioCyc website provides computational operations for metabolomics data that include metabolite search and translation of metabolite identifiers across multiple metabolite databases. The site allows researchers to store and manipulate metabolite lists using a facility called SmartTables, which supports metabolite enrichment analysis. That analysis operation identifies metabolite sets that are statistically over-represented for the substrates of specific metabolic pathways. BioCyc also enables visualization of metabolomics data on individual pathway diagrams and on the organism-specific metabolic map diagrams that are available for every BioCyc organism. Most of these operations are available both interactively and as programmatic web services. PMID:26011592

  14. Preterm gut microbiota and metabolome following discharge from intensive care.

    PubMed

    Stewart, Christopher J; Skeath, Tom; Nelson, Andrew; Fernstad, Sara J; Marrs, Emma C L; Perry, John D; Cummings, Stephen P; Berrington, Janet E; Embleton, Nicholas D

    2015-01-01

    The development of the preterm gut microbiome is important for immediate and longer-term health following birth. We aimed to determine if modifications to the preterm gut on the neonatal intensive care unit (NICU) impacted the gut microbiota and metabolome long-term. Stool samples were collected from 29 infants ages 1-3 years post discharge (PD) from a single NICU. Additional NICU samples were included from 14/29 infants. Being diagnosed with disease or receiving increased antibiotics while on the NICU did not significantly impact the microbiome PD. Significant decreases in common NICU organisms including K. oxytoca and E. faecalis and increases in common adult organisms including Akkermansia sp., Blautia sp., and Bacteroides sp. and significantly different Shannon diversity was shown between NICU and PD samples. The metabolome increased in complexity, but while PD samples had unique bacterial profiles we observed comparable metabolomic profiles. The preterm gut microbiome is able to develop complexity comparable to healthy term infants despite limited environmental exposures, high levels of antibiotic administration, and of the presence of serious disease. Further work is needed to establish the direct effect of weaning as a key event in promoting future gut health. PMID:26598071

  15. Preterm gut microbiota and metabolome following discharge from intensive care

    PubMed Central

    Stewart, Christopher J.; Skeath, Tom; Nelson, Andrew; Fernstad, Sara J.; Marrs, Emma C. L.; Perry, John D.; Cummings, Stephen P.; Berrington, Janet E.; Embleton, Nicholas D.

    2015-01-01

    The development of the preterm gut microbiome is important for immediate and longer-term health following birth. We aimed to determine if modifications to the preterm gut on the neonatal intensive care unit (NICU) impacted the gut microbiota and metabolome long-term. Stool samples were collected from 29 infants ages 1–3 years post discharge (PD) from a single NICU. Additional NICU samples were included from 14/29 infants. Being diagnosed with disease or receiving increased antibiotics while on the NICU did not significantly impact the microbiome PD. Significant decreases in common NICU organisms including K. oxytoca and E. faecalis and increases in common adult organisms including Akkermansia sp., Blautia sp., and Bacteroides sp. and significantly different Shannon diversity was shown between NICU and PD samples. The metabolome increased in complexity, but while PD samples had unique bacterial profiles we observed comparable metabolomic profiles. The preterm gut microbiome is able to develop complexity comparable to healthy term infants despite limited environmental exposures, high levels of antibiotic administration, and of the presence of serious disease. Further work is needed to establish the direct effect of weaning as a key event in promoting future gut health. PMID:26598071

  16. Alterations in Human Liver Metabolome during Prolonged Cryostorage.

    PubMed

    Abuja, Peter M; Ehrhart, Friederike; Schoen, Uwe; Schmidt, Tomm; Stracke, Frank; Dallmann, Guido; Friedrich, Torben; Zimmermann, Heiko; Zatloukal, Kurt

    2015-07-01

    Tissue metabolomics requires high sample quality that crucially depends on the biobanking storage protocol. Hence, we systematically analyzed the influence of realistic storage scenarios on the liver metabolome with different storage temperatures and repeated transfer of samples between storage and retrieval environments, simulating the repeated temperature changes affecting unrelated samples stored in the same container as the sample that is to be retrieved. By cycling between storage (-80 °C freezer, liquid nitrogen, cold nitrogen gas) and retrieval (room temperature, -80 °C), assuming three cycles per day and sample, we simulated biobank storage between 3 months and 10 years. Liver tissue metabolome was analyzed by liquid chromatography/mass spectrometry. Most metabolite concentrations changed <5% for the first "year" of time-compressed biobanking simulation, predominantly due to hydrolysis of peptides and lipids. Interestingly, storage temperature affected metabolite concentrations only little, while there was a linear dependence on the number of temperature change cycles. Elevated sample temperature during (prolonged) retrieval time led to a distinctly different signature of metabolite changes that were induced by cycling. Our findings allow giving recommendations for optimized storage protocols and provide signatures that allow detection of deviations from protocol. PMID:26036795

  17. Cold acclimation wholly reorganizes the Drosophila melanogaster transcriptome and metabolome.

    PubMed

    MacMillan, Heath A; Knee, Jose M; Dennis, Alice B; Udaka, Hiroko; Marshall, Katie E; Merritt, Thomas J S; Sinclair, Brent J

    2016-01-01

    Cold tolerance is a key determinant of insect distribution and abundance, and thermal acclimation can strongly influence organismal stress tolerance phenotypes, particularly in small ectotherms like Drosophila. However, there is limited understanding of the molecular and biochemical mechanisms that confer such impressive plasticity. Here, we use high-throughput mRNA sequencing (RNA-seq) and liquid chromatography - mass spectrometry (LC-MS) to compare the transcriptomes and metabolomes of D. melanogaster acclimated as adults to warm (rearing) (21.5 °C) or cold conditions (6 °C). Cold acclimation improved cold tolerance and led to extensive biological reorganization: almost one third of the transcriptome and nearly half of the metabolome were differentially regulated. There was overlap in the metabolic pathways identified via transcriptomics and metabolomics, with proline and glutathione metabolism being the most strongly-supported metabolic pathways associated with increased cold tolerance. We discuss several new targets in the study of insect cold tolerance (e.g. dopamine signaling and Na(+)-driven transport), but many previously identified candidate genes and pathways (e.g. heat shock proteins, Ca(2+) signaling, and ROS detoxification) were also identified in the present study, and our results are thus consistent with and extend the current understanding of the mechanisms of insect chilling tolerance. PMID:27357258

  18. Current Advances in the Metabolomics Study on Lotus Seeds

    PubMed Central

    Zhu, Mingzhi; Liu, Ting; Guo, Mingquan

    2016-01-01

    Lotus (Nelumbo nucifera), which is distributed widely throughout Asia, Australia and North America, is an aquatic perennial that has been cultivated for over 2,000 years. It is very stimulating that almost all parts of lotus have been consumed as vegetable as well as food, especially the seeds. Except for the nutritive values of lotus, there has been increasing interest in its potential as functional food due to its rich secondary metabolites, such as flavonoids and alkaloids. Not only have these metabolites greatly contributed to the biological process of lotus seeds, but also have been reported to possess multiple health-promoting effects, including antioxidant, anti-amnesic, anti-inflammatory, and anti-tumor activities. Thus, comprehensive metabolomic profiling of these metabolites is of key importance to help understand their biological activities, and other chemical biology features. In this context, this review will provide an update on the current technological platforms, and workflow associated with metabolomic studies on lotus seeds, as well as insights into the application of metabolomics for the improvement of food safety and quality, assisting breeding, and promotion of the study of metabolism and pharmacokinetics of lotus seeds; meanwhile it will also help explore new perspectives and outline future challenges in this fast-growing research subject. PMID:27379154

  19. Potential of metabolomics in preclinical and clinical drug development.

    PubMed

    Kumar, Baldeep; Prakash, Ajay; Ruhela, Rakesh Kumar; Medhi, Bikash

    2014-12-01

    Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development. PMID:25443721

  20. The longitudinal cerebrospinal fluid metabolomic profile of amyotrophic lateral sclerosis

    PubMed Central

    Gray, Elizabeth; Larkin, James R.; Claridge, Tim D. W.; Talbot, Kevin; Sibson, Nicola R.; Turner, Martin R.

    2015-01-01

    Neurochemical biomarkers are urgently sought in ALS. Metabolomic analysis of cerebrospinal fluid (CSF) using proton nuclear magnetic resonance (1H-NMR) spectroscopy is a highly sensitive method capable of revealing nervous system cellular pathology. The 1H-NMR CSF metabolomic signature of ALS was sought in a longitudinal cohort. Six-monthly serial collection was performed in ALS patients across a range of clinical sub-types (n = 41) for up to two years, and in healthy controls at a single time-point (n = 14). A multivariate statistical approach, partial least squares discriminant analysis, was used to determine differences between the NMR spectra from patients and controls. Significantly predictive models were found using those patients with at least one year's interval between recruitment and the second sample. Glucose, lactate, citric acid and, unexpectedly, ethanol were the discriminating metabolites elevated in ALS. It is concluded that 1H-NMR captured the CSF metabolomic signature associated with derangements in cellular energy utilization connected with ALS, and was most prominent in comparisons using patients with longer disease duration. The specific metabolites identified support the concept of a hypercatabolic state, possibly involving mitochondrial dysfunction specifically. Endogenous ethanol in the CSF may be an unrecognized novel marker of neuronal tissue injury in ALS. PMID:26121274

  1. The longitudinal cerebrospinal fluid metabolomic profile of amyotrophic lateral sclerosis.

    PubMed

    Gray, Elizabeth; Larkin, James R; Claridge, Tim D W; Talbot, Kevin; Sibson, Nicola R; Turner, Martin R

    2015-01-01

    Neurochemical biomarkers are urgently sought in ALS. Metabolomic analysis of cerebrospinal fluid (CSF) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy is a highly sensitive method capable of revealing nervous system cellular pathology. The (1)H-NMR CSF metabolomic signature of ALS was sought in a longitudinal cohort. Six-monthly serial collection was performed in ALS patients across a range of clinical sub-types (n = 41) for up to two years, and in healthy controls at a single time-point (n = 14). A multivariate statistical approach, partial least squares discriminant analysis, was used to determine differences between the NMR spectra from patients and controls. Significantly predictive models were found using those patients with at least one year's interval between recruitment and the second sample. Glucose, lactate, citric acid and, unexpectedly, ethanol were the discriminating metabolites elevated in ALS. It is concluded that (1)H-NMR captured the CSF metabolomic signature associated with derangements in cellular energy utilization connected with ALS, and was most prominent in comparisons using patients with longer disease duration. The specific metabolites identified support the concept of a hypercatabolic state, possibly involving mitochondrial dysfunction specifically. Endogenous ethanol in the CSF may be an unrecognized novel marker of neuronal tissue injury in ALS. PMID:26121274

  2. Mapping Microbial Response Metabolomes for Induced Natural Product Discovery.

    PubMed

    Derewacz, Dagmara K; Covington, Brett C; McLean, John A; Bachmann, Brian O

    2015-09-18

    Intergeneric microbial interactions may originate a significant fraction of secondary metabolic gene regulation in nature. Herein, we expose a genomically characterized Nocardiopsis strain, with untapped polyketide biosynthetic potential, to intergeneric interactions via coculture with low inoculum exposure to Escherichia, Bacillus, Tsukamurella, and Rhodococcus. The challenge-induced responses of extracted metabolites were characterized via multivariate statistical and self-organizing map (SOM) analyses, revealing the magnitude and selectivity engendered by the limiting case of low inoculum exposure. The collected inventory of cocultures revealed substantial metabolomic expansion in comparison to monocultures with nearly 14% of metabolomic features in cocultures undetectable in monoculture conditions and many features unique to coculture genera. One set of SOM-identified responding features was isolated, structurally characterized by multidimensional NMR, and revealed to comprise previously unreported polyketides containing an unusual pyrrolidinol substructure and moderate and selective cytotoxicity. Designated ciromicin A and B, they are detected across mixed cultures with intergeneric preferences under coculture conditions. The structural novelty of ciromicin A is highlighted by its ability to undergo a diastereoselective photochemical 12-π electron rearrangement to ciromicin B at visible wavelengths. This study shows how organizing trends in metabolomic responses under coculture conditions can be harnessed to characterize multipartite cultures and identify previously silent secondary metabolism. PMID:26039241

  3. 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

  4. Metabolomics for Biomarker Discovery: Moving to the Clinic

    PubMed Central

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

    2015-01-01

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

  5. An exome array study of the plasma metabolome

    PubMed Central

    Rhee, Eugene P.; Yang, Qiong; Yu, Bing; Liu, Xuan; Cheng, Susan; Deik, Amy; Pierce, Kerry A.; Bullock, Kevin; Ho, Jennifer E.; Levy, Daniel; Florez, Jose C.; Kathiresan, Sek; Larson, Martin G.; Vasan, Ramachandran S.; Clish, Clary B.; Wang, Thomas J.; Boerwinkle, Eric; O'Donnell, Christopher J.; Gerszten, Robert E.

    2016-01-01

    The study of rare variants may enhance our understanding of the genetic determinants of the metabolome. Here, we analyze the association between 217 plasma metabolites and exome variants on the Illumina HumanExome Beadchip in 2,076 participants in the Framingham Heart Study, with replication in 1,528 participants of the Atherosclerosis Risk in Communities Study. We identify an association between GMPS and xanthosine using single variant analysis and associations between HAL and histidine, PAH and phenylalanine, and UPB1 and ureidopropionate using gene-based tests (P<5 × 10−8 in meta-analysis), highlighting novel coding variants that may underlie inborn errors of metabolism. Further, we show how an examination of variants across the spectrum of allele frequency highlights independent association signals at select loci and generates a more integrated view of metabolite heritability. These studies build on prior metabolomics genome wide association studies to provide a more complete picture of the genetic architecture of the plasma metabolome. PMID:27453504

  6. Metabolome of human gut microbiome is predictive of host dysbiosis

    DOE PAGESBeta

    Larsen, Peter E.; Dai, Yang

    2015-09-14

    Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. The community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent onmore » its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

  7. Metabolome of human gut microbiome is predictive of host dysbiosis

    SciTech Connect

    Larsen, Peter E.; Dai, Yang

    2015-09-14

    Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. The community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

  8. Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows

    PubMed Central

    2014-01-01

    Background Hepatic lipidosis or fatty liver disease is a major metabolic disorder of high-producing dairy cows that compromises animal performance and, hence, causes heavy economic losses worldwide. This syndrome, occurring during the critical transition from gestation to early lactation, leads to an impaired health status, decreased milk yield, reduced fertility and shortened lifetime. Because the prevailing clinical chemistry parameters indicate advanced liver damage independently of the underlying disease, currently, hepatic lipidosis can only be ascertained by liver biopsy. We hypothesized that the condition of fatty liver disease may be accompanied by an altered profile of endogenous metabolites in the blood of affected animals. Results To identify potential small-molecule biomarkers as a novel diagnostic alternative, the serum samples of diseased dairy cows were subjected to a targeted metabolomics screen by triple quadrupole mass spectrometry. A subsequent multivariate test involving principal component and linear discriminant analyses yielded 29 metabolites (amino acids, phosphatidylcholines and sphingomyelines) that, in conjunction, were able to distinguish between dairy cows with no hepatic lipidosis and those displaying different stages of the disorder. Conclusions This proof-of-concept study indicates that metabolomic profiles, including both amino acids and lipids, distinguish hepatic lipidosis from other peripartal disorders and, hence, provide a promising new tool for the diagnosis of hepatic lipidosis. By generating insights into the molecular pathogenesis of hepatic lipidosis, metabolomics studies may also facilitate the prevention of this syndrome. PMID:24888604

  9. The role of metabolomics in neonatal and pediatric laboratory medicine.

    PubMed

    Mussap, Michele; Antonucci, Roberto; Noto, Antonio; Fanos, Vassilios

    2013-11-15

    Metabolomics consists of the quantitative analysis of a large number of low molecular mass metabolites involving substrates or products in metabolic pathways existing in all living systems. The analysis of the metabolic profile detectable in a human biological fluid allows to instantly identify changes in the composition of endogenous and exogenous metabolites caused by the interaction between specific physiopathological states, gene expression, and environment. In pediatrics and neonatology, metabolomics offers new encouraging perspectives for the improvement of critically ill patient outcome, for the early recognition of metabolic profiles associated with the development of diseases in the adult life, and for delivery of individualized medicine. In this view, nutrimetabolomics, based on the recognition of specific cluster of metabolites associated with nutrition and pharmacometabolomics, based on the capacity to personalize drug therapy by analyzing metabolic modifications due to therapeutic treatment may open new frontiers in the prevention and in the treatment of pediatric and neonatal diseases. This review summarizes the most relevant results published in the literature on the application of metabolomics in pediatric and neonatal clinical settings. However, there is the urgent need to standardize physiological and preanalytical variables, analytical methods, data processing, and result presentation, before establishing the definitive clinical value of results. PMID:24035970

  10. The Time Is Right to Focus on Model Organism Metabolomes

    PubMed Central

    Edison, Arthur S.; Hall, Robert D.; Junot, Christophe; Karp, Peter D.; Kurland, Irwin J.; Mistrik, Robert; Reed, Laura K.; Saito, Kazuki; Salek, Reza M.; Steinbeck, Christoph; Sumner, Lloyd W.; Viant, Mark R.

    2016-01-01

    Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research. PMID:26891337

  11. Cold acclimation wholly reorganizes the Drosophila melanogaster transcriptome and metabolome

    PubMed Central

    MacMillan, Heath A.; Knee, Jose M.; Dennis, Alice B.; Udaka, Hiroko; Marshall, Katie E.; Merritt, Thomas J. S.; Sinclair, Brent J.

    2016-01-01

    Cold tolerance is a key determinant of insect distribution and abundance, and thermal acclimation can strongly influence organismal stress tolerance phenotypes, particularly in small ectotherms like Drosophila. However, there is limited understanding of the molecular and biochemical mechanisms that confer such impressive plasticity. Here, we use high-throughput mRNA sequencing (RNA-seq) and liquid chromatography – mass spectrometry (LC-MS) to compare the transcriptomes and metabolomes of D. melanogaster acclimated as adults to warm (rearing) (21.5 °C) or cold conditions (6 °C). Cold acclimation improved cold tolerance and led to extensive biological reorganization: almost one third of the transcriptome and nearly half of the metabolome were differentially regulated. There was overlap in the metabolic pathways identified via transcriptomics and metabolomics, with proline and glutathione metabolism being the most strongly-supported metabolic pathways associated with increased cold tolerance. We discuss several new targets in the study of insect cold tolerance (e.g. dopamine signaling and Na+-driven transport), but many previously identified candidate genes and pathways (e.g. heat shock proteins, Ca2+ signaling, and ROS detoxification) were also identified in the present study, and our results are thus consistent with and extend the current understanding of the mechanisms of insect chilling tolerance. PMID:27357258

  12. Current Advances in the Metabolomics Study on Lotus Seeds.

    PubMed

    Zhu, Mingzhi; Liu, Ting; Guo, Mingquan

    2016-01-01

    Lotus (Nelumbo nucifera), which is distributed widely throughout Asia, Australia and North America, is an aquatic perennial that has been cultivated for over 2,000 years. It is very stimulating that almost all parts of lotus have been consumed as vegetable as well as food, especially the seeds. Except for the nutritive values of lotus, there has been increasing interest in its potential as functional food due to its rich secondary metabolites, such as flavonoids and alkaloids. Not only have these metabolites greatly contributed to the biological process of lotus seeds, but also have been reported to possess multiple health-promoting effects, including antioxidant, anti-amnesic, anti-inflammatory, and anti-tumor activities. Thus, comprehensive metabolomic profiling of these metabolites is of key importance to help understand their biological activities, and other chemical biology features. In this context, this review will provide an update on the current technological platforms, and workflow associated with metabolomic studies on lotus seeds, as well as insights into the application of metabolomics for the improvement of food safety and quality, assisting breeding, and promotion of the study of metabolism and pharmacokinetics of lotus seeds; meanwhile it will also help explore new perspectives and outline future challenges in this fast-growing research subject. PMID:27379154

  13. Metabolomics reveals insect metabolic responses associated with fungal infection.

    PubMed

    Xu, Yong-Jiang; Luo, Feifei; Gao, Qiang; Shang, Yanfang; Wang, Chengshu

    2015-06-01

    The interactions between insects and pathogenic fungi are complex. We employed metabolomic techniques to profile insect metabolic dynamics upon infection by the pathogenic fungus Beauveria bassiana. Silkworm larvae were infected with fungal spores and microscopic observations demonstrated that the exhaustion of insect hemocytes was coupled with fungal propagation in the insect body cavity. Metabolomic analyses revealed that fungal infection could significantly alter insect energy and nutrient metabolisms as well as the immune defense responses, including the upregulation of carbohydrates, amino acids, fatty acids, and lipids, but the downregulation of eicosanoids and amines. The insect antifeedant effect of the fungal infection was evident with the reduced level of maclurin (a component of mulberry leaves) in infected insects but elevated accumulations in control insects. Insecticidal and cytotoxic mycotoxins like oosporein and beauveriolides were also detected in insects at the later stages of infection. Taken together, the metabolomics data suggest that insect immune responses are energy-cost reactions and the strategies of nutrient deprivation, inhibition of host immune responses, and toxin production would be jointly employed by the fungus to kill insects. The data obtained in this study will facilitate future functional studies of genes and pathways associated with insect-fungus interactions. PMID:25895944

  14. An exome array study of the plasma metabolome.

    PubMed

    Rhee, Eugene P; Yang, Qiong; Yu, Bing; Liu, Xuan; Cheng, Susan; Deik, Amy; Pierce, Kerry A; Bullock, Kevin; Ho, Jennifer E; Levy, Daniel; Florez, Jose C; Kathiresan, Sek; Larson, Martin G; Vasan, Ramachandran S; Clish, Clary B; Wang, Thomas J; Boerwinkle, Eric; O'Donnell, Christopher J; Gerszten, Robert E

    2016-01-01

    The study of rare variants may enhance our understanding of the genetic determinants of the metabolome. Here, we analyze the association between 217 plasma metabolites and exome variants on the Illumina HumanExome Beadchip in 2,076 participants in the Framingham Heart Study, with replication in 1,528 participants of the Atherosclerosis Risk in Communities Study. We identify an association between GMPS and xanthosine using single variant analysis and associations between HAL and histidine, PAH and phenylalanine, and UPB1 and ureidopropionate using gene-based tests (P<5 × 10(-8) in meta-analysis), highlighting novel coding variants that may underlie inborn errors of metabolism. Further, we show how an examination of variants across the spectrum of allele frequency highlights independent association signals at select loci and generates a more integrated view of metabolite heritability. These studies build on prior metabolomics genome wide association studies to provide a more complete picture of the genetic architecture of the plasma metabolome. PMID:27453504

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

    PubMed Central

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

    2016-01-01

    Integrated analysis of metabolomics, transcriptomics and immunohistochemistry can contribute to a deeper understanding of biological processes altered in cancer and possibly enable improved diagnostic or prognostic tests. In this study, a set of 254 metabolites was determined by gas-chromatography/liquid chromatography-mass spectrometry in matched malignant and non-malignant prostatectomy samples of 106 prostate cancer (PCa) patients. Transcription analysis of matched samples was performed on a set of 15 PCa patients using Affymetrix U133 Plus 2.0 arrays. Expression of several proteins was immunohistochemically determined in 41 matched patient samples and the association with clinico-pathological parameters was analyzed by an integrated data analysis. These results further outline the highly deregulated metabolism of fatty acids, sphingolipids and polyamines in PCa. For the first time, the impact of the ERG translocation on the metabolome was demonstrated, highlighting an altered fatty acid oxidation in TMPRSS2-ERG translocation positive PCa specimens. Furthermore, alterations in cholesterol metabolism were found preferentially in high grade tumors, enabling the cells to create energy storage. With this integrated analysis we could not only confirm several findings from previous metabolomic studies, but also contradict others and finally expand our concepts of deregulated biological pathways in PCa. PMID:26623558

  16. NMR-BASED METABOLOMIC STUDIES OF ENDOCRINE DISRUPTION IN SMALL FISH MODELS

    EPA Science Inventory

    Metabolomics is now being widely used to obtain complementary information to genomic and proteomic studies. Among the various approaches used in metabolomics, NMR spectroscopy is particularly powerful, in part because it is relatively non-selective, and is amenable to the study o...

  17. Metabolite Profiling in the Pursuit of Biomarkers for IVF Outcome: The Case for Metabolomics Studies

    PubMed Central

    McRae, C.; Sharma, V.; Fisher, J.

    2013-01-01

    Background. This paper presents the literature on biomarkers of in vitro fertilisation (IVF) outcome, demonstrating the progression of these studies towards metabolite profiling, specifically metabolomics. The need for more, and improved, metabolomics studies in the field of assisted conception is discussed. Methods. Searches were performed on ISI Web of Knowledge SM for literature associated with biomarkers of oocyte and embryo quality, and biomarkers of IVF outcome in embryo culture medium, follicular fluid (FF), and blood plasma in female mammals. Results. Metabolomics in the field of female reproduction is still in its infancy. Metabolomics investigations of embryo culture medium for embryo selection have been the most common, but only within the last five years. Only in 2012 has the first metabolomics investigation of FF for biomarkers of oocyte quality been reported. The only metabolomics studies of human blood plasma in this context have been aimed at identifying women with polycystic ovary syndrome (PCOS). Conclusions. Metabolomics is becoming more established in the field of assisted conception, but the studies performed so far have been preliminary and not all potential applications have yet been explored. With further improved metabolomics studies, the possibility of identifying a method for predicting IVF outcome may become a reality. PMID:25763388

  18. The sensitivity of metabolomics versus classical regulatory toxicology from a NOAEL perspective.

    PubMed

    van Ravenzwaay, B; Montoya, G A; Fabian, E; Herold, M; Krennrich, G; Looser, R; Mellert, W; Peter, E; Strauss, V; Walk, T; Kamp, H

    2014-05-16

    The identification of the no observed adverse effect level (NOAEL) is the key regulatory outcome of toxicity studies. With the introduction of "omics" technologies into toxicological research, the question arises as to how sensitive these technologies are relative to classical regulatory toxicity parameters. BASF SE and metanomics developed the in vivo metabolome database MetaMap®Tox containing metabolome data for more than 500 reference compounds. For several years metabolome analysis has been routinely performed in regulatory toxicity studies (REACH mandated testing or new compound development), mostly in the context of 28 day studies in rats (OECD 407 guideline). For those chemicals for which a toxicological NOAEL level was obtained at either high or mid-dose level, we evaluated the associated metabolome to investigate the sensitivity of metabolomics versus classical toxicology with respect to the NOAEL. For the definition of a metabolomics NOAEL the ECETOC criteria (ECETOC, 2007) were used. In this context we evaluated 104 cases. Comparable sensitivity was noted in 75% of the cases, increased sensitivity of metabolomics in 8%, and decreased sensitivity in 18% of the cases. In conclusion, these data suggest that metabolomics profiling has a similar sensitivity to the classical toxicological study (e.g. OECD 407) design. PMID:24657160

  19. Think Tank on Metabolomics and Prospective Cohorts: How to Leverage Resources

    Cancer.gov

    This Think Tank identified resources that can be used collaboratively across prospective cohorts; developed strategies to leverage resources for advancing the use of metabolomics in prospective cohort studies; identified the best strategies for performing analyses using metabolomics data across multiple studies; and, established a collaborative group that will identify and tackle research projects that cannot be effectively investigated by one independent group.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Taking Metabolomics to the Field: A Pilot Study in a Great Lakes Area of Concern (AOC)

    EPA Science Inventory

    Measurement of changes in endogenous metabolites via 1H-NMR-based metabolomics has shown great potential for assessing organisms exposed to environmental pollutants, and thus could aid the efforts of risk assessors. However, to date, the application of metabolomics to ecologi...

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

    PubMed

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

    2015-04-24

    Metabolomics is the qualitative and quantitative analysis of all of the small molecules in a biological sample at a specific time and influence. Technologies for metabolomics analysis have developed rapidly as new analytical tools for chemical separations, mass spectrometry, and NMR spectroscopy have emerged. Plants have one of the largest metabolomes, and it is estimated that the average plant leaf can contain upward of 30 000 phytochemicals. In the past decade, over 1200 papers on plant metabolomics have been published. A standard metabolomics data set contains vast amounts of information and can either investigate or generate hypotheses. The key factors in using plant metabolomics data most effectively are the experimental design, authentic standard availability, extract standardization, and statistical analysis. Using cranberry (Vaccinium macrocarpon) as a model system, this review will discuss and demonstrate strategies and tools for analysis and interpretation of metabolomics data sets including eliminating false discoveries and determining significance, metabolite clustering, and logical algorithms for discovery of new metabolites and pathways. Together these metabolomics tools represent an entirely new pipeline for phytochemical discovery. PMID:25751407

  3. Ethylene insensitivity alters ripening-associated metabolomic changes in apple peel

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metabolomic changes were compared in untreated, diphenylamine treated, and 1-methylcyclopropene treated ‘Granny Smith’ apples stored for up to 6 months at 1 oC in air. Metabolomic evaluation, including 600+ metabolites, was employed to characterize ripening-related metabolism. Partial Least Square...

  4. Teaching (and learning from) metabolomics: the 2006 PlantMetaNet ETNA Metabolomics Research School.

    PubMed

    Böttcher, Christoph; Centeno, Danilo; Freitag, Jens; Höfgen, Rainer; Köhl, Karin; Kopka, Joachim; Kroymann, Juergen; Matros, Andrea; Mock, Hans-Peter; Neumann, Stefan; Pfalz, Marina; von Roepenack-Lahaye, Edda; Schauer, Nicolas; Trenkamp, Sandra; Zurbriggen, Matias; Fernie, Alisdair R

    2008-02-01

    Under the auspices of the European Training and Networking Activity programme of the European Union, a 'Metabolic Profiling and Data Analysis' Plant Genomics and Bioinformatics Summer School was hosted in Potsdam, Germany between 20 and 29 September 2006. Sixteen early career researchers were invited from the European Union partner nations and the so-called developing nations (Appendix). Lectures from invited leading European researchers provided an overview of the state of the art of these fields and seeded discussion regarding major challenges for their future advancement. Hands-on experience was provided by an example experiment - that of defining the metabolic response of Arabidopsis to treatment of a commercial herbicide of defined mode of action. This experiment was performed throughout the duration of the course in order to teach the concepts underlying extraction and machine handling as well as to provide a rich data set with which the required computation and statistical skills could be illustrated. Here we review the state of the field by describing both key lectures given at and practical aspects taught at the summer school. In addition, we disclose results that were obtained using the four distinct technical platforms at the different participating institutes. While the effects of the chosen herbicide are well documented, this study looks at a broader number of metabolites than in previous investigations. This allowed, on the one hand, not only to characterise further effects of the herbicide than previously observed but also to detect molecules other than the herbicide that were obviously present in the commercial formulation. These data and the workshop in general are all discussed in the context of the teaching of metabolomics. PMID:18251856

  5. Single-Cell Metabolomics: Changes in the Metabolome of Freshly Isolated and Cultured Neurons

    PubMed Central

    2012-01-01

    Metabolites are involved in a diverse range of intracellular processes, including a cell’s response to a changing extracellular environment. Using single-cell capillary electrophoresis coupled to electrospray ionization mass spectrometry, we investigated how placing individual identified neurons in culture affects their metabolic profile. First, glycerol-based cell stabilization was evaluated using metacerebral neurons from Aplysia californica; the measurement error was reduced from ∼24% relative standard deviation to ∼6% for glycerol-stabilized cells compared to those isolated without glycerol stabilization. In order to determine the changes induced by culturing, 14 freshly isolated and 11 overnight-cultured neurons of two metabolically distinct cell types from A. californica, the B1 and B2 buccal neurons, were characterized. Of the more than 300 distinctive cell-related signals detected, 35 compounds were selected for their known biological roles and compared among each measured cell. Unsupervised multivariate and statistical analysis revealed robust metabolic differences between these two identified neuron types. We then compared the changes induced by overnight culturing; metabolite concentrations were distinct for 26 compounds in the cultured B1 cells. In contrast, culturing had less influence on the metabolic profile of the B2 neurons, with only five compounds changing significantly. As a result of these culturing-induced changes, the metabolic composition of the B1 neurons became indistinguishable from the cultured B2 cells. This observation suggests that the two cell types differentially regulate their in vivo or in vitro metabolomes in response to a changing environment. PMID:23077722

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

    PubMed

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

    2016-06-01

    Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells. PMID:27074779

  7. Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks

    PubMed Central

    Chokkathukalam, Achuthanunni; Kim, Dong-Hyun; Barrett, Michael P; Breitling, Rainer; Creek, Darren J

    2014-01-01

    The rapid emergence of metabolomics has enabled system-wide measurements of metabolites in various organisms. However, advances in the mechanistic understanding of metabolic networks remain limited, as most metabolomics studies cannot routinely provide accurate metabolite identification, absolute quantification and flux measurement. Stable isotope labeling offers opportunities to overcome these limitations. Here we describe some current approaches to stable isotope-labeled metabolomics and provide examples of the significant impact that these studies have had on our understanding of cellular metabolism. Furthermore, we discuss recently developed software solutions for the analysis of stable isotope-labeled metabolomics data and propose the bioinformatics solutions that will pave the way for the broader application and optimal interpretation of system-scale labeling studies in metabolomics. PMID:24568354

  8. Aqueous and lipid nuclear magnetic resonance metabolomic profiles of the earthworm Aporrectodea caliginosa show potential as an indicator species for environmental metabolomics.

    PubMed

    Brown, Jeffrey N; Samuelsson, Linda; Bernardi, Giuliana; Gooneratne, Ravi; Larsson, D G Joakim

    2014-10-01

    The common pasture earthworm Aporrectodea caliginosa has often been neglected in environmental metabolomics in favor of species easily bred in the laboratory. The present study assigns aqueous metabolites in A. caliginosa using high-resolution 1- and 2-dimensional nuclear magnetic resonance (NMR) spectroscopy. In total, 51 aqueous metabolites were identified, including typical amino acids (alanine, leucine, asparagine, phenylalanine), sugars (maltose, glucose), the dominant earthworm-specific 2-hexyl-5-ethyl-furansulfonate, and several previously unreported metabolites (oxoglutarate, putrescine). Examining the lesser-known earthworm lipid metabolome showed various lipid fatty acyl chains, cholesterol, and phosphatidylcholine. To briefly test if the NMR metabolomic techniques could differentiate A. caliginosa from different sites, earthworms were collected from 2 adjacent farms. Orthogonal partial least squares discriminant analysis detected metabolomic differences, suggesting the worms from the 2 sites differed in their energy metabolism, as indicated by altered levels of alanine, glutamine, glutamate, malate, fumarate, and lipids. Evidence of greater utilization of lipid energy reserves and onset of protein catabolism was also present. While the precise cause of the metabolomic differences could not be determined, the results show the potential of this species for further environmental metabolomic studies. PMID:24995628

  9. Mealtime, temporal, and daily variability of the human urinary and plasma metabolomes in a tightly controlled environment.

    PubMed

    Kim, Kyoungmi; Mall, Christine; Taylor, Sandra L; Hitchcock, Stacie; Zhang, Chen; Wettersten, Hiromi I; Jones, A Daniel; Chapman, Arlene; Weiss, Robert H

    2014-01-01

    While metabolomics has tremendous potential for diagnostic biomarker and therapeutic target discovery, its utility may be diminished by the variability that occurs due to environmental exposures including diet and the influences of the human circadian rhythm. For successful translation of metabolomics findings into the clinical setting, it is necessary to exhaustively define the sources of metabolome variation. To address these issues and to measure the variability of urinary and plasma metabolomes throughout the day, we have undertaken a comprehensive inpatient study in which we have performed non-targeted metabolomics analysis of blood and urine in 26 volunteers (13 healthy subjects with no known disease and 13 healthy subjects with autosomal dominant polycystic kidney disease not taking medication). These individuals were evaluated in a clinical research facility on two separate occasions, over three days, while on a standardized, weight-based diet. Subjects provided pre- and post-prandial blood and urine samples at the same time of day, and all samples were analyzed by "fast lane" LC-MS-based global metabolomics. The largest source of variability in blood and urine metabolomes was attributable to technical issues such as sample preparation and analysis, and less variability was due to biological variables, meals, and time of day. Higher metabolome variability was observed after the morning as compared to the evening meal, yet day-to-day variability was minimal and urine metabolome variability was greater than that of blood. Thus we suggest that blood and urine are suitable biofluids for metabolomics studies, though nontargeted mass spectrometry alone may not offer sufficient precision to reveal subtle changes in the metabolome. Additional targeted analyses may be needed to support the data from nontargeted mass spectrometric analyses. In light of these findings, future metabolomics studies should consider these sources of variability to allow for appropriate

  10. Salivary Microbiota and Metabolome Associated with Celiac Disease

    PubMed Central

    Francavilla, Ruggiero; Ercolini, Danilo; Piccolo, Maria; Vannini, Lucia; Siragusa, Sonya; De Filippis, Francesca; De Pasquale, Ilaria; Di Cagno, Raffaella; Di Toma, Michele; Gozzi, Giorgia; Serrazanetti, Diana I.; Gobbetti, Marco

    2014-01-01

    This study aimed to investigate the salivary microbiota and metabolome of 13 children with celiac disease (CD) under a gluten-free diet (treated celiac disease [T-CD]). The same number of healthy children (HC) was used as controls. The salivary microbiota was analyzed by an integrated approach using culture-dependent and -independent methods. Metabolome analysis was carried out by gas chromatography-mass spectrometry–solid-phase microextraction. Compared to HC, the number of some cultivable bacterial groups (e.g., total anaerobes) significantly (P < 0.05) differed in the saliva samples of the T-CD children. As shown by community-level catabolic profiles, the highest Shannon's diversity and substrate richness were found in HC. Pyrosequencing data showed the highest richness estimator and diversity index values for HC. Levels of Lachnospiraceae, Gemellaceae, and Streptococcus sanguinis were highest for the T-CD children. Streptococcus thermophilus levels were markedly decreased in T-CD children. The saliva of T-CD children showed the largest amount of Bacteroidetes (e.g., Porphyromonas sp., Porphyromonas endodontalis, and Prevotella nanceiensis), together with the smallest amount of Actinobacteria. T-CD children were also characterized by decreased levels of some Actinomyces species, Atopobium species, and Corynebacterium durum. Rothia mucilaginosa was the only Actinobacteria species found at the highest level in T-CD children. As shown by multivariate statistical analyses, the levels of organic volatile compounds markedly differentiated T-CD children. Some compounds (e.g., ethyl-acetate, nonanal, and 2-hexanone) were found to be associated with T-CD children. Correlations (false discovery rate [FDR], <0.05) were found between the relative abundances of bacteria and some volatile organic compounds (VOCs). The findings of this study indicated that CD is associated with oral dysbiosis that could affect the oral metabolome. PMID:24657864

  11. Metabolomic insights into system-wide coordination of vertebrate metamorphosis

    PubMed Central

    2014-01-01

    Background After completion of embryogenesis, many organisms experience an additional obligatory developmental transition to attain a substantially different juvenile or adult form. During anuran metamorphosis, the aquatic tadpole undergoes drastic morphological changes and remodelling of tissues and organs to become a froglet. Thyroid hormones are required to initiate the process, but the mechanism whereby the many requisite changes are coordinated between organs and tissues is poorly understood. Metabolites are often highly conserved biomolecules between species and are the closest reflection of phenotype. Due to the extensive distribution of blood throughout the organism, examination of the metabolites contained therein provides a system-wide overview of the coordinated changes experienced during metamorphosis. We performed an untargeted metabolomic analysis on serum samples from naturally-metamorphosing Rana catesbeiana from tadpoles to froglets using ultraperformance liquid chromatography coupled to a mass spectrometer. Total and aqueous metabolite extracts were obtained from each serum sample to select for nonpolar and polar metabolites, respectively, and selected metabolites were validated by running authentic compounds. Results The majority of the detected metabolites (74%) showed statistically significant abundance changes (padj < 0.001) between metamorphic stages. We observed extensive remodelling of five core metabolic pathways: arginine and purine/pyrimidine, cysteine/methionine, sphingolipid, and eicosanoid metabolism and the urea cycle, and found evidence for a major role for lipids during this postembryonic process. Metabolites traditionally linked to human disease states were found to have biological linkages to the system-wide changes occuring during the events leading up to overt morphological change. Conclusions To our knowledge, this is the first wide-scale metabolomic study of vertebrate metamorphosis identifying fundamental pathways

  12. Plasma metabolomics in human pulmonary tuberculosis disease: a pilot study.

    PubMed

    Frediani, Jennifer K; Jones, Dean P; Tukvadze, Nestan; Uppal, Karan; Sanikidze, Eka; Kipiani, Maia; Tran, ViLinh T; Hebbar, Gautam; Walker, Douglas I; Kempker, Russell R; Kurani, Shaheen S; Colas, Romain A; Dalli, Jesmond; Tangpricha, Vin; Serhan, Charles N; Blumberg, Henry M; Ziegler, Thomas R

    2014-01-01

    We aimed to characterize metabolites during tuberculosis (TB) disease and identify new pathophysiologic pathways involved in infection as well as biomarkers of TB onset, progression and resolution. Such data may inform development of new anti-tuberculosis drugs. Plasma samples from adults with newly diagnosed pulmonary TB disease and their matched, asymptomatic, sputum culture-negative household contacts were analyzed using liquid chromatography high-resolution mass spectrometry (LC-MS) to identify metabolites. Statistical and bioinformatics methods were used to select accurate mass/charge (m/z) ions that were significantly different between the two groups at a false discovery rate (FDR) of q<0.05. Two-way hierarchical cluster analysis (HCA) was used to identify clusters of ions contributing to separation of cases and controls, and metabolomics databases were used to match these ions to known metabolites. Identity of specific D-series resolvins, glutamate and Mycobacterium tuberculosis (Mtb)-derived trehalose-6-mycolate was confirmed using LC-MS/MS analysis. Over 23,000 metabolites were detected in untargeted metabolomic analysis and 61 metabolites were significantly different between the two groups. HCA revealed 8 metabolite clusters containing metabolites largely upregulated in patients with TB disease, including anti-TB drugs, glutamate, choline derivatives, Mycobacterium tuberculosis-derived cell wall glycolipids (trehalose-6-mycolate and phosphatidylinositol) and pro-resolving lipid mediators of inflammation, known to stimulate resolution, efferocytosis and microbial killing. The resolvins were confirmed to be RvD1, aspirin-triggered RvD1, and RvD2. This study shows that high-resolution metabolomic analysis can differentiate patients with active TB disease from their asymptomatic household contacts. Specific metabolites upregulated in the plasma of patients with active TB disease, including Mtb-derived glycolipids and resolvins, have potential as biomarkers

  13. Plant metabolomics: from holistic data to relevant biomarkers.

    PubMed

    Wolfender, Jean-Luc; Rudaz, Serge; Choi, Young Hae; Kim, Hye Kyong

    2013-01-01

    Metabolomics is playing an increasingly important role in plant science. It aims at the comprehensive analysis of the plant metabolome which consists both of primary and secondary metabolites. The goal of metabolomics is ultimately to identify and quantify this wide array of small molecules in biological samples. This new science is included in several systems biology approaches and is based primarily on the unbiased acquisition of mass spectrometric (MS) or nuclear magnetic resonance (NMR) data from carefully selected samples. This approach provides the most ''functional'' information of the 'omics' technologies of a given organism since metabolites are the end products of the cellular regulatory processes. The application of state-of-the-art data mining, that includes various untargeted and targeted multivariate data analysis methods, to the vast amount of data generated by this data-driven approach leads to sample classification and the identification of relevant biomarkers. The biological areas that have been successfully studied by this holistic approach include global metabolite composition assessment, mutant and phenotype characterisation, taxonomy, developmental processes, stress response, interaction with the environment, quality control assessment, lead finding and mode of action of botanicals. This review summarises the main MS- and NMR-based approaches that are used to perform these studies and discusses the potential and current limitations of the various methods. The intent is not to provide an exhaustive overview of the field, which has grown considerably over the past decade, but to summarise the main strategies that are used and to discuss the potential and limitations of the different approaches as well as future trends. PMID:23210790

  14. Toxicogenomics and Metabolomics of Pentamethylchromanol (PMCol)-Induced Hepatotoxicity

    PubMed Central

    Parman, Toufan; Bunin, Deborah I.; Ng, Hanna H.; McDunn, Jonathan E.; Wulff, Jacob E.; Wang, Abraham; Swezey, Robert; Rasay, Laura; Fairchild, David G.; Kapetanovic, Izet M.; Green, Carol E.

    2011-01-01

    Pentamethyl-6-chromanol (PMCol), a chromanol-type compound related to vitamin E, was proposed as an anticancer agent with activity against androgen-dependent cancers. In repeat dose-toxicity studies in rats and dogs, PMCol caused hepatotoxicity, nephrotoxicity, and hematological effects. The objectives of this study were to determine the mechanisms of the observed toxicity and identify sensitive early markers of target organ injury by integrating classical toxicology, toxicogenomics, and metabolomic approaches. PMCol was administered orally to male Sprague-Dawley rats at 200 and 2000 mg/kg daily for 7 or 28 days. Changes in clinical chemistry included elevated alanine aminotransferase, total bilirubin, cholesterol and triglycerides—indicative of liver toxicity that was confirmed by microscopic findings (periportal hepatocellular hydropic degeneration and cytomegaly) in treated rats. Metabolomic evaluations of liver revealed time- and dose-dependent changes, including depletion of total glutathione and glutathione conjugates, decreased methionine, and increased S-adenosylhomocysteine, cysteine, and cystine. PMCol treatment also decreased cofactor levels, namely, FAD and increased NAD(P)+. Microarray analysis of liver found that differentially expressed genes were enriched in the glutathione and cytochrome P450 pathways by PMCol treatment. Reverse transcription-polymerase chain reaction of six upregulated genes and one downregulated gene confirmed the microarray results. In conclusion, the use of metabolomics and toxicogenomics demonstrates that chronic exposure to high doses of PMCol induces liver damage and dysfunction, probably due to both direct inhibition of glutathione synthesis and modification of drug metabolism pathways. Depletion of glutathione due to PMCol exposure ultimately results in a maladaptive response, increasing the consumption of hepatic dietary antioxidants and resulting in elevated reactive oxygen species levels associated with hepatocellular

  15. Challenges of Inversely Estimating Jacobian from Metabolomics Data

    PubMed Central

    Sun, Xiaoliang; Länger, Bettina; Weckwerth, Wolfram

    2015-01-01

    Inferring dynamics of metabolic networks directly from metabolomics data provides a promising way to elucidate the underlying mechanisms of biological systems, as reported in our previous studies (Weckwerth, 2011; Sun and Weckwerth, 2012; Nägele et al., 2014) by a differential Jacobian approach. The Jacobian is solved from an overdetermined system of equations as JC + CJT = −2D, called Lyapunov Equation in its generic form,1 where J is the Jacobian, C is the covariance matrix of metabolomics data, and D is the fluctuation matrix. Lyapunov Equation can be further simplified as the linear form Ax = b. Frequently, this linear equation system is ill-conditioned, i.e., a small variation in the right side b results in a big change in the solution x, thus making the solution unstable and error-prone. At the same time, inaccurate estimation of covariance matrix and uncertainties in the fluctuation matrix bring biases to the solution x. Here, we first reviewed common approaches to circumvent the ill-conditioned problems, including total least squares, Tikhonov regularization, and truncated singular value decomposition. Then, we benchmarked these methods on several in silico kinetic models with small to large perturbations on the covariance and fluctuation matrices. The results identified that the accuracy of the reverse Jacobian is mainly dependent on the condition number of A, the perturbation amplitude of C, and the stiffness of the kinetic models. Our research contributes a systematical comparison of methods to inversely solve Jacobian from metabolomics data. PMID:26636075

  16. Metabolome-Proteome Differentiation Coupled to Microbial Divergence

    SciTech Connect

    Wilmes, P; Bowen, Benjamin P.; Thomas, Brian; Mueller, Ryan; Denef, Vincent; Verberkmoes, Nathan C; Hettich, Robert {Bob} L; Northen, Trent R.; Banfield, Jillian F.

    2010-01-01

    Tandem high-throughput proteomics and metabolomics were employed to functionally characterize natural microbial biofilm communities. Distinct molecular signatures exist for each analyzed sample. Deconvolution of the high-resolution molecular data demonstrates that identified proteins and detected metabolites exhibit organism-specific correlation patterns. These patterns are reflective of the functional differentiation of two bacterial species that share the same genus and that co-occur in the sampled microbial communities. Our analyses indicate that the two species have similar niche breadths and are not in strong competition with one another.

  17. The nonvolatile metabolome of sunflower linear glandular trichomes.

    PubMed

    Spring, Otmar; Pfannstiel, Jens; Klaiber, Iris; Conrad, Jürgen; Beifuß, Uwe; Apel, Lysanne; Aschenbrenner, Anna-Katharina; Zipper, Reinhard

    2015-11-01

    Uniseriate linear glandular trichomes occur on stems, leaves and flowering parts of Helianthus species and related taxa. Their metabolic activity and biological function are still poorly understood. A phytochemical study documented the accumulation of bisabolene type sesquiterpenes and flavonoids as the major constituents of the non-volatile metabolome of linear glandular trichomes in the common sunflower, Helianthus annuus. Besides known sesquiterpenes of the glandulone, helibisabonol and heliannuol type, four previously undescribed sesquiterpenes named glandulone D, E, F and helibisabonol C were identified by spectroscopic analysis. In addition, four known nevadensin type flavonoids varying in O-methoxy substitutions were found. None of them has previously been reported from Helianthus annuus. PMID:26412774

  18. TOCCATA: a customized carbon total correlation spectroscopy NMR metabolomics database.

    PubMed

    Bingol, Kerem; Zhang, Fengli; Bruschweiler-Li, Lei; Brüschweiler, Rafael

    2012-11-01

    A customized metabolomics NMR database, TOCCATA, is introduced, which uses (13)C chemical shift information for the reliable identification of metabolites, their spin systems, and isomeric states. TOCCATA, whose information was derived from the BMRB and HMDB databases and the literature, currently contains 463 compounds and 801 spin systems, and it can be used through a publicly accessible web server. TOCCATA allows the identification of metabolites in the submillimolar concentration range from (13)C-(13)C total correlation spectroscopy experiments of complex mixtures, which is demonstrated for an Escherichia coli cell lysate, a carbohydrate mixture, and an amino acid mixture, all of which were uniformly (13)C-labeled. PMID:23016498

  19. Serum Metabolomic Profiling of Rats by Intervention of Aconitum soongaricum.

    PubMed

    Zhang, Fan; Liu, Jiao; Lei, Jun; He, Wenjing; Sun, Yun

    2015-12-01

    To understand the toxic mechanism and to find the changes in the endogenous metabolites of Aconitum soongaricum Stapf for clinical detection, a combination of 1H NMR spectroscopy and multivariate statistical analysis was applied to examine the metabolic profiles of the blood serum samples collected from the rat model. In total, thirteen biomarkers of A. soongaricum were found and identified. It turned out that A. soongaricum treatment may partially disorder the metabolism. The study has shown the potential application of NMR-based metabolomic analysis in providing further insights into the toxicity caused by A. soongaricum. PMID:26882691

  20. Metabolomics - the complementary field in systems biology: a review on obesity and type 2 diabetes.

    PubMed

    Abu Bakar, Mohamad Hafizi; Sarmidi, Mohamad Roji; Cheng, Kian-Kai; Ali Khan, Abid; Suan, Chua Lee; Zaman Huri, Hasniza; Yaakob, Harisun

    2015-07-01

    Metabolomic studies on obesity and type 2 diabetes mellitus have led to a number of mechanistic insights into biomarker discovery and comprehension of disease progression at metabolic levels. This article reviews a series of metabolomic studies carried out in previous and recent years on obesity and type 2 diabetes, which have shown potential metabolic biomarkers for further evaluation of the diseases. Literature including journals and books from Web of Science, Pubmed and related databases reporting on the metabolomics in these particular disorders are reviewed. We herein discuss the potential of reported metabolic biomarkers for a novel understanding of disease processes. These biomarkers include fatty acids, TCA cycle intermediates, carbohydrates, amino acids, choline and bile acids. The biological activities and aetiological pathways of metabolites of interest in driving these intricate processes are explained. The data from various publications supported metabolomics as an effective strategy in the identification of novel biomarkers for obesity and type 2 diabetes. Accelerating interest in the perspective of metabolomics to complement other fields in systems biology towards the in-depth understanding of the molecular mechanisms underlying the diseases is also well appreciated. In conclusion, metabolomics can be used as one of the alternative approaches in biomarker discovery and the novel understanding of pathophysiological mechanisms in obesity and type 2 diabetes. It can be foreseen that there will be an increasing research interest to combine metabolomics with other omics platforms towards the establishment of detailed mechanistic evidence associated with the disease processes. PMID:25919044

  1. Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

    PubMed

    Blasco, H; Patin, F; Madji Hounoum, B; Gordon, P H; Vourc'h, P; Andres, C R; Corcia, P

    2016-03-01

    Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. PMID:26822316

  2. Nuclear magnetic resonance based metabolomics and liver diseases: Recent advances and future clinical applications

    PubMed Central

    Amathieu, Roland; Triba, Mohamed Nawfal; Goossens, Corentine; Bouchemal, Nadia; Nahon, Pierre; Savarin, Philippe; Le Moyec, Laurence

    2016-01-01

    Metabolomics is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. It is an “omics” technique that is situated downstream of genomics, transcriptomics and proteomics. Metabolomics is recognized as a promising technique in the field of systems biology for the evaluation of global metabolic changes. During the last decade, metabolomics approaches have become widely used in the study of liver diseases for the detection of early biomarkers and altered metabolic pathways. It is a powerful technique to improve our pathophysiological knowledge of various liver diseases. It can be a useful tool to help clinicians in the diagnostic process especially to distinguish malignant and non-malignant liver disease as well as to determine the etiology or severity of the liver disease. It can also assess therapeutic response or predict drug induced liver injury. Nevertheless, the usefulness of metabolomics is often not understood by clinicians, especially the concept of metabolomics profiling or fingerprinting. In the present work, after a concise description of the different techniques and processes used in metabolomics, we will review the main research on this subject by focusing specifically on in vitro proton nuclear magnetic resonance spectroscopy based metabolomics approaches in human studies. We will first consider the clinical point of view enlighten physicians on this new approach and emphasis its future use in clinical “routine”. PMID:26755887

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

    PubMed

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

    2016-05-25

    Natural product plays a vital role in disease prevention and treatment since the appearance of civilization, but the toxicity severely hinders its wide use. In order to avoid toxic effect as far as possible and use natural product safely, more comprehensive understandings of toxicity are urgently required. Since the metabolome represents the physiological or pathological status of organisms, metabolomics-based toxicology is of significance to observe potential injury before toxins have caused physiological or pathological damages. Metabolomics-based toxicology can evaluate toxicity and identify toxicological biomarker of natural product, which is helpful to guide clinical medication and reduce adverse drug reactions. In the past decades, dozens of metabolomic researches have been implemented on toxicity evaluation, toxicological biomarker identification and potential mechanism exploration of nephrotoxicity, hepatotoxicity, cardiotoxicity and central nervous system toxicity induced by pure compounds, extracts and compound prescriptions. In this paper, metabolomic technology, sample preparation, data process and analysis, and metabolomics-based toxicological research of natural product are reviewed, and finally, the potential problems and further perspectives in toxicological metabolomic investigations of natural product are discussed. PMID:27041073

  4. Metabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application

    PubMed Central

    Klein, Matthias S.; Shearer, Jane

    2016-01-01

    Type 2 diabetes (T2D) and its comorbidities have reached epidemic proportions, with more than half a billion cases expected by 2030. Metabolomics is a fairly new approach for studying metabolic changes connected to disease development and progression and for finding predictive biomarkers to enable early interventions, which are most effective against T2D and its comorbidities. In metabolomics, the abundance of a comprehensive set of small biomolecules (metabolites) is measured, thus giving insight into disease-related metabolic alterations. This review shall give an overview of basic metabolomics methods and will highlight current metabolomics research successes in the prediction and diagnosis of T2D. We summarized key metabolites changing in response to T2D. Despite large variations in predictive biomarkers, many studies have replicated elevated plasma levels of branched-chain amino acids and their derivatives, aromatic amino acids and α-hydroxybutyrate ahead of T2D manifestation. In contrast, glycine levels and lysophosphatidylcholine C18:2 are depressed in both predictive studies and with overt disease. The use of metabolomics for predicting T2D comorbidities is gaining momentum, as are our approaches for translating basic metabolomics research into clinical applications. As a result, metabolomics has the potential to enable informed decision-making in the realm of personalized medicine. PMID:26636104

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

    SciTech Connect

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

    2008-03-31

    The goal of metabolomics experiments is the detection and quantitation of as many sample components as reasonably possible in order to identify “features” that can be used to characterize the samples under study. When utilizing electrospray ionization to produce ions for analysis by mass spectrometry (MS), it is imperative that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize the phenomenon of ionization suppression. Similarly, optimization of the MS inlet can lead to increased measurement sensitivity. This review will focus on the role of high resolution liquid chromatography (LC) separations in conjunction with improved ion production and transmission for LC-MS-based metabolomics.

  6. Metabolomics Profiling for Obstructive Sleep Apnea and Simple Snorers.

    PubMed

    Xu, Huajun; Zheng, Xiaojiao; Qian, Yingjun; Guan, Jian; Yi, Hongliang; Zou, Jianyin; Wang, Yuyu; Meng, Lili; Zhao, Aihua; Yin, Shankai; Jia, Wei

    2016-01-01

    Few clinical studies have explored altered urinary metabolite levels in patients with obstructive sleep apnea (OSA). Thus, we applied a metabolomics approach to analyze urinary metabolites in three groups of participants: patients with polysomnography (PSG)-confirmed OSA, simple snorers (SS), and normal subjects. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry were used. A total of 21 and 31 metabolites were differentially expressed in the SS and OSA groups, respectively. Patients with OSA had 18 metabolites different from those with SS. Of the 56 metabolites detected among the 3 groups, 24 were consistently higher or lower. A receiver operator curve analysis revealed that the combination of 4-hydroxypentenoic acid, arabinose, glycochenodeoxycholate-3-sulfate, isoleucine, serine, and xanthine produced a moderate diagnostic score with a sensitivity (specificity) of 75% (78%) for distinguishing OSA from those without OSA. The combination of 4-hydroxypentenoic acid, 5-dihydrotestosterone sulfate, serine, spermine, and xanthine distinguished OSA from SS with a sensitivity of 85% and specificity of 80%. Multiple metabolites and metabolic pathways associated with SS and OSA were identified using the metabolomics approach, and the altered metabolite signatures could potentially serve as an alternative diagnostic method to PSG. PMID:27480913

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

    PubMed Central

    Jiménez-Girón, Ana; Muñoz-González, Irene; Martín-Álvarez, Pedro J.; Moreno-Arribas, María Victoria; Bartolomé, Begoña

    2014-01-01

    Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others) seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33). It assembles data from two analytical approaches: (1) UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis); and (2) UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis). Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota. PMID:25532710

  8. Arteriovenous Blood Metabolomics: A Readout of Intra-Tissue Metabostasis

    PubMed Central

    Ivanisevic, Julijana; Elias, Darlene; Deguchi, Hiroshi; Averell, Patricia M.; Kurczy, Michael; Johnson, Caroline H.; Tautenhahn, Ralf; Zhu, Zhengjiang; Watrous, Jeramie; Jain, Mohit; Griffin, John; Patti, Gary J.; Siuzdak, Gary

    2015-01-01

    The human circulatory system consists of arterial blood that delivers nutrients to tissues, and venous blood that removes the metabolic by-products. Although it is well established that arterial blood generally has higher concentrations of glucose and oxygen relative to venous blood, a comprehensive biochemical characterization of arteriovenous differences has not yet been reported. Here we apply cutting-edge, mass spectrometry-based metabolomic technologies to provide a global characterization of metabolites that vary in concentration between the arterial and venous blood of human patients. Global profiling of paired arterial and venous plasma from 20 healthy individuals, followed up by targeted analysis made it possible to measure subtle (<2 fold), yet highly statistically significant and physiologically important differences in water soluble human plasma metabolome. While we detected changes in lactic acid, alanine, glutamine, and glutamate as expected from skeletal muscle activity, a number of unanticipated metabolites were also determined to be significantly altered including Krebs cycle intermediates, amino acids that have not been previously implicated in transport, and a few oxidized fatty acids. This study provides the most comprehensive assessment of metabolic changes in the blood during circulation to date and suggests that such profiling approach may offer new insights into organ homeostasis and organ specific pathology. PMID:26244428

  9. Characterization and Discrimination of Ancient Grains: A Metabolomics Approach

    PubMed Central

    Righetti, Laura; Rubert, Josep; Galaverna, Gianni; Folloni, Silvia; Ranieri, Roberto; Stranska-Zachariasova, Milena; Hajslova, Jana; Dall’Asta, Chiara

    2016-01-01

    Hulled, or ancient, wheats were the earliest domesticated wheats by mankind and the ancestors of current wheats. Their cultivation drastically decreased during the 1960s; however, the increasing demand for a healthy and equilibrated diet led to rediscovering these grains. Our aim was to use a non-targeted metabolomic approach to discriminate and characterize similarities and differences between ancient Triticum varieties. For this purpose, 77 hulled wheat samples from three different varieties were collected: Garfagnana T. turgidum var. dicoccum L. (emmer), ID331 T. monococcum L. (einkorn) and Rouquin T. spelta L. (spelt). The ultra high performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-QTOF) metabolomics approach highlighted a pronounced sample clustering according to the wheat variety, with an excellent predictability (Q2), for all the models built. Fifteen metabolites were tentatively identified based on accurate masses, isotopic pattern, and product ion spectra. Among these, alkylresorcinols (ARs) were found to be significantly higher in spelt and emmer, showing different homologue composition. Furthermore, phosphatidylcholines (PC) and lysophosphatidylcholines (lysoPC) levels were higher in einkorn variety. The results obtained in this study confirmed the importance of ARs as markers to distinguish between Triticum species and revealed their values as cultivar markers, being not affected by the environmental influences. PMID:27472322

  10. Global Isotope Metabolomics Reveals Adaptive Strategies for Nitrogen Assimilation.

    PubMed

    Kurczy, Michael E; Forsberg, Erica M; Thorgersen, Michael P; Poole, Farris L; Benton, H Paul; Ivanisevic, Julijana; Tran, Minerva L; Wall, Judy D; Elias, Dwayne A; Adams, Michael W W; Siuzdak, Gary

    2016-06-17

    Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using (15)NO3 as a nitrogen source. In contrast to a control (Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee (Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2 strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. The use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher. PMID:27045776

  11. Metabolomics Profiling for Obstructive Sleep Apnea and Simple Snorers

    PubMed Central

    Xu, Huajun; Zheng, Xiaojiao; Qian, Yingjun; Guan, Jian; Yi, Hongliang; Zou, Jianyin; Wang, Yuyu; Meng, Lili; Zhao, Aihua; Yin, Shankai; Jia, Wei

    2016-01-01

    Few clinical studies have explored altered urinary metabolite levels in patients with obstructive sleep apnea (OSA). Thus, we applied a metabolomics approach to analyze urinary metabolites in three groups of participants: patients with polysomnography (PSG)-confirmed OSA, simple snorers (SS), and normal subjects. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry were used. A total of 21 and 31 metabolites were differentially expressed in the SS and OSA groups, respectively. Patients with OSA had 18 metabolites different from those with SS. Of the 56 metabolites detected among the 3 groups, 24 were consistently higher or lower. A receiver operator curve analysis revealed that the combination of 4-hydroxypentenoic acid, arabinose, glycochenodeoxycholate-3-sulfate, isoleucine, serine, and xanthine produced a moderate diagnostic score with a sensitivity (specificity) of 75% (78%) for distinguishing OSA from those without OSA. The combination of 4-hydroxypentenoic acid, 5-dihydrotestosterone sulfate, serine, spermine, and xanthine distinguished OSA from SS with a sensitivity of 85% and specificity of 80%. Multiple metabolites and metabolic pathways associated with SS and OSA were identified using the metabolomics approach, and the altered metabolite signatures could potentially serve as an alternative diagnostic method to PSG. PMID:27480913

  12. Regularized MANOVA (rMANOVA) in untargeted metabolomics.

    PubMed

    Engel, J; Blanchet, L; Bloemen, B; van den Heuvel, L P; Engelke, U H F; Wevers, R A; Buydens, L M C

    2015-10-29

    Many advanced metabolomics experiments currently lead to data where a large number of response variables were measured while one or several factors were changed. Often the number of response variables vastly exceeds the sample size and well-established techniques such as multivariate analysis of variance (MANOVA) cannot be used to analyze the data. ANOVA simultaneous component analysis (ASCA) is an alternative to MANOVA for analysis of metabolomics data from an experimental design. In this paper, we show that ASCA assumes that none of the metabolites are correlated and that they all have the same variance. Because of these assumptions, ASCA may relate the wrong variables to a factor. This reduces the power of the method and hampers interpretation. We propose an improved model that is essentially a weighted average of the ASCA and MANOVA models. The optimal weight is determined in a data-driven fashion. Compared to ASCA, this method assumes that variables can correlate, leading to a more realistic view of the data. Compared to MANOVA, the model is also applicable when the number of samples is (much) smaller than the number of variables. These advantages are demonstrated by means of simulated and real data examples. The source code of the method is available from the first author upon request, and at the following github repository: https://github.com/JasperE/regularized-MANOVA. PMID:26547490

  13. Vitamin D Status Affects Serum Metabolomic Profiles in Pregnant Adolescents.

    PubMed

    Finkelstein, Julia L; Pressman, Eva K; Cooper, Elizabeth M; Kent, Tera R; Bar, Haim Y; O'Brien, Kimberly O

    2015-06-01

    Vitamin D is linked to a number of adverse pregnancy outcomes through largely unknown mechanisms. This study was conducted to examine the role of vitamin D status in metabolomic profiles in a group of 30 pregnant, African American adolescents (17.1 ± 1.1 years) at midgestation (26.8 ± 2.8 weeks), in 15 adolescents with 25-hydroxy vitamin D (25(OH)D) ≥20 ng/mL, and in 15 teens with 25(OH)D <20 ng/mL. Serum metabolomic profiles were examined using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry. A novel hierarchical mixture model was used to evaluate differences in metabolite profiles between low and high groups. A total of 326 compounds were identified and included in subsequent statistical analyses. Eleven metabolites had significantly different means between the 2 vitamin D groups, after correcting for multiple hypothesis testing: pyridoxate, bilirubin, xylose, and cholate were higher, and leukotrienes, 1,2-propanediol, azelate, undecanedioate, sebacate, inflammation associated complement component 3 peptide (HWESASXX), and piperine were lower in serum from adolescents with 25(OH)D ≥20 ng/mL. Lower maternal vitamin D status at midgestation impacted serum metabolic profiles in pregnant adolescents. PMID:25367051

  14. Alcohol induced alterations to the human fecal VOC metabolome.

    PubMed

    Couch, Robin D; Dailey, Allyson; Zaidi, Fatima; Navarro, Karl; Forsyth, Christopher B; Mutlu, Ece; Engen, Phillip A; Keshavarzian, Ali

    2015-01-01

    Studies have shown that excessive alcohol consumption impacts the intestinal microbiota composition, causing disruption of homeostasis (dysbiosis). However, this observed change is not indicative of the dysbiotic intestinal microbiota function that could result in the production of injurious and toxic products. Thus, knowledge of the effects of alcohol on the intestinal microbiota function and their metabolites is warranted, in order to better understand the role of the intestinal microbiota in alcohol associated organ failure. Here, we report the results of a differential metabolomic analysis comparing volatile organic compounds (VOC) detected in the stool of alcoholics and non-alcoholic healthy controls. We performed the analysis with fecal samples collected after passage as well as with samples collected directly from the sigmoid lumen. Regardless of the approach to fecal collection, we found a stool VOC metabolomic signature in alcoholics that is different from healthy controls. The most notable metabolite alterations in the alcoholic samples include: (1) an elevation in the oxidative stress biomarker tetradecane; (2) a decrease in five fatty alcohols with anti-oxidant property; (3) a decrease in the short chain fatty acids propionate and isobutyrate, important in maintaining intestinal epithelial cell health and barrier integrity; (4) a decrease in alcohol consumption natural suppressant caryophyllene; (5) a decrease in natural product and hepatic steatosis attenuator camphene; and (6) decreased dimethyl disulfide and dimethyl trisulfide, microbial products of decomposition. Our results showed that intestinal microbiota function is altered in alcoholics which might promote alcohol associated pathologies. PMID:25751150

  15. Identification of salivary metabolomic biomarkers for oral cancer screening.

    PubMed

    Ishikawa, Shigeo; Sugimoto, Masahiro; Kitabatake, Kenichiro; Sugano, Ayako; Nakamura, Marina; Kaneko, Miku; Ota, Sana; Hiwatari, Kana; Enomoto, Ayame; Soga, Tomoyoshi; Tomita, Masaru; Iino, Mitsuyoshi

    2016-01-01

    The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples, and between salivary samples from oral cancer and controls, respectively (P < 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726-0.928, P < 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. PMID:27539254

  16. A Strategy for Sensitive, Large Scale Quantitative Metabolomics

    PubMed Central

    Liu, Xiaojing; Ser, Zheng; Cluntun, Ahmad A.; Mentch, Samantha J.; Locasale, Jason W.

    2014-01-01

    Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases. PMID:24894601

  17. 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

  18. Metabolomic profiles delineate mycolactone signature in Buruli ulcer disease

    PubMed Central

    Niang, Fatoumata; Sarfo, Fred S.; Frimpong, Michael; Guenin-Macé, Laure; Wansbrough-Jones, Mark; Stinear, Timothy; Phillips, Richard O.; Demangel, Caroline

    2015-01-01

    Infection of human skin with Mycobacterium ulcerans, the causative agent of Buruli ulcer, is associated with the systemic diffusion of a bacterial macrolide named mycolactone. Patients with progressive disease show alterations in their serum proteome, likely reflecting the inhibition of secreted protein production by mycolactone at the cellular level. Here, we used semi-quantitative metabolomics to characterize metabolic perturbations in serum samples of infected individuals, and human cells exposed to mycolactone. Among the 430 metabolites profiled across 20 patients and 20 healthy endemic controls, there were significant differences in the serum levels of hexoses, steroid hormones, acylcarnitines, purine, heme, bile acids, riboflavin and lysolipids. In parallel, analysis of 292 metabolites in human T cells treated or not with mycolactone showed alterations in hexoses, lysolipids and purine catabolites. Together, these data demonstrate that M. ulcerans infection causes systemic perturbations in the serum metabolome that can be ascribed to mycolactone. Of particular importance to Buruli ulcer pathogenesis is that changes in blood sugar homeostasis in infected patients are mirrored by alterations in hexose metabolism in mycolactone-exposed cells. PMID:26634444

  19. Metabolomic Tools for Secondary Metabolite Discovery from Marine Microbial Symbionts

    PubMed Central

    Macintyre, Lynsey; Zhang, Tong; Viegelmann, Christina; Juarez Martinez, Ignacio; Cheng, Cheng; Dowdells, Catherine; Abdelmohsen, Usama Ramadan; Gernert, Christine; Hentschel, Ute; Edrada-Ebel, RuAngelie

    2014-01-01

    Marine invertebrate-associated symbiotic bacteria produce a plethora of novel secondary metabolites which may be structurally unique with interesting pharmacological properties. Selection of strains usually relies on literature searching, genetic screening and bioactivity results, often without considering the chemical novelty and abundance of secondary metabolites being produced by the microorganism until the time-consuming bioassay-guided isolation stages. To fast track the selection process, metabolomic tools were used to aid strain selection by investigating differences in the chemical profiles of 77 bacterial extracts isolated from cold water marine invertebrates from Orkney, Scotland using liquid chromatography-high resolution mass spectrometry (LC-HRMS) and nuclear magnetic resonance (NMR) spectroscopy. Following mass spectrometric analysis and dereplication using an Excel macro developed in-house, principal component analysis (PCA) was employed to differentiate the bacterial strains based on their chemical profiles. NMR 1H and correlation spectroscopy (COSY) were also employed to obtain a chemical fingerprint of each bacterial strain and to confirm the presence of functional groups and spin systems. These results were then combined with taxonomic identification and bioassay screening data to identify three bacterial strains, namely Bacillus sp. 4117, Rhodococcus sp. ZS402 and Vibrio splendidus strain LGP32, to prioritize for scale-up based on their chemically interesting secondary metabolomes, established through dereplication and interesting bioactivities, determined from bioassay screening. PMID:24905482

  20. Alcohol Induced Alterations to the Human Fecal VOC Metabolome

    PubMed Central

    Couch, Robin D.; Dailey, Allyson; Zaidi, Fatima; Navarro, Karl; Forsyth, Christopher B.; Mutlu, Ece; Engen, Phillip A.; Keshavarzian, Ali

    2015-01-01

    Studies have shown that excessive alcohol consumption impacts the intestinal microbiota composition, causing disruption of homeostasis (dysbiosis). However, this observed change is not indicative of the dysbiotic intestinal microbiota function that could result in the production of injurious and toxic products. Thus, knowledge of the effects of alcohol on the intestinal microbiota function and their metabolites is warranted, in order to better understand the role of the intestinal microbiota in alcohol associated organ failure. Here, we report the results of a differential metabolomic analysis comparing volatile organic compounds (VOC) detected in the stool of alcoholics and non-alcoholic healthy controls. We performed the analysis with fecal samples collected after passage as well as with samples collected directly from the sigmoid lumen. Regardless of the approach to fecal collection, we found a stool VOC metabolomic signature in alcoholics that is different from healthy controls. The most notable metabolite alterations in the alcoholic samples include: (1) an elevation in the oxidative stress biomarker tetradecane; (2) a decrease in five fatty alcohols with anti-oxidant property; (3) a decrease in the short chain fatty acids propionate and isobutyrate, important in maintaining intestinal epithelial cell health and barrier integrity; (4) a decrease in alcohol consumption natural suppressant caryophyllene; (5) a decrease in natural product and hepatic steatosis attenuator camphene; and (6) decreased dimethyl disulfide and dimethyl trisulfide, microbial products of decomposition. Our results showed that intestinal microbiota function is altered in alcoholics which might promote alcohol associated pathologies. PMID:25751150

  1. 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

  2. Identification of salivary metabolomic biomarkers for oral cancer screening

    PubMed Central

    Ishikawa, Shigeo; Sugimoto, Masahiro; Kitabatake, Kenichiro; Sugano, Ayako; Nakamura, Marina; Kaneko, Miku; Ota, Sana; Hiwatari, Kana; Enomoto, Ayame; Soga, Tomoyoshi; Tomita, Masaru; Iino, Mitsuyoshi

    2016-01-01

    The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples, and between salivary samples from oral cancer and controls, respectively (P < 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726–0.928, P < 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. PMID:27539254

  3. Effect of sleep deprivation on the human metabolome.

    PubMed

    Davies, Sarah K; Ang, Joo Ern; Revell, Victoria L; Holmes, Ben; Mann, Anuska; Robertson, Francesca P; Cui, Nanyi; Middleton, Benita; Ackermann, Katrin; Kayser, Manfred; Thumser, Alfred E; Raynaud, Florence I; Skene, Debra J

    2014-07-22

    Sleep restriction and circadian clock disruption are associated with metabolic disorders such as obesity, insulin resistance, and diabetes. The metabolic pathways involved in human sleep, however, have yet to be investigated with the use of a metabolomics approach. Here we have used untargeted and targeted liquid chromatography (LC)/MS metabolomics to examine the effect of acute sleep deprivation on plasma metabolite rhythms. Twelve healthy young male subjects remained in controlled laboratory conditions with respect to environmental light, sleep, meals, and posture during a 24-h wake/sleep cycle, followed by 24 h of wakefulness. Two-hourly plasma samples collected over the 48 h period were analyzed by LC/MS. Principal component analysis revealed a clear time of day variation with a significant cosine fit during the wake/sleep cycle and during 24 h of wakefulness in untargeted and targeted analysis. Of 171 metabolites quantified, daily rhythms were observed in the majority (n = 109), with 78 of these maintaining their rhythmicity during 24 h of wakefulness, most with reduced amplitude (n = 66). During sleep deprivation, 27 metabolites (tryptophan, serotonin, taurine, 8 acylcarnitines, 13 glycerophospholipids, and 3 sphingolipids) exhibited significantly increased levels compared with during sleep. The increased levels of serotonin, tryptophan, and taurine may explain the antidepressive effect of acute sleep deprivation and deserve further study. This report, to our knowledge the first of metabolic profiling during sleep and sleep deprivation and characterization of 24 h rhythms under these conditions, offers a novel view of human sleep/wake regulation. PMID:25002497

  4. MetaboAnalyst 3.0--making metabolomics more meaningful.

    PubMed

    Xia, Jianguo; Sinelnikov, Igor V; Han, Beomsoo; Wishart, David S

    2015-07-01

    MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms. PMID:25897128

  5. Arteriovenous Blood Metabolomics: A Readout of Intra-Tissue Metabostasis.

    PubMed

    Ivanisevic, Julijana; Elias, Darlene; Deguchi, Hiroshi; Averell, Patricia M; Kurczy, Michael; Johnson, Caroline H; Tautenhahn, Ralf; Zhu, Zhengjiang; Watrous, Jeramie; Jain, Mohit; Griffin, John; Patti, Gary J; Siuzdak, Gary

    2015-01-01

    The human circulatory system consists of arterial blood that delivers nutrients to tissues, and venous blood that removes the metabolic by-products. Although it is well established that arterial blood generally has higher concentrations of glucose and oxygen relative to venous blood, a comprehensive biochemical characterization of arteriovenous differences has not yet been reported. Here we apply cutting-edge, mass spectrometry-based metabolomic technologies to provide a global characterization of metabolites that vary in concentration between the arterial and venous blood of human patients. Global profiling of paired arterial and venous plasma from 20 healthy individuals, followed up by targeted analysis made it possible to measure subtle (<2 fold), yet highly statistically significant and physiologically important differences in water soluble human plasma metabolome. While we detected changes in lactic acid, alanine, glutamine, and glutamate as expected from skeletal muscle activity, a number of unanticipated metabolites were also determined to be significantly altered including Krebs cycle intermediates, amino acids that have not been previously implicated in transport, and a few oxidized fatty acids. This study provides the most comprehensive assessment of metabolic changes in the blood during circulation to date and suggests that such profiling approach may offer new insights into organ homeostasis and organ specific pathology. PMID:26244428

  6. Analysis of metabolomic data using support vector machines.

    PubMed

    Mahadevan, Sankar; Shah, Sirish L; Marrie, Thomas J; Slupsky, Carolyn M

    2008-10-01

    Metabolomics is an emerging field providing insight into physiological processes. It is an effective tool to investigate disease diagnosis or conduct toxicological studies by observing changes in metabolite concentrations in various biofluids. Multivariate statistical analysis is generally employed with nuclear magnetic resonance (NMR) or mass spectrometry (MS) data to determine differences between groups (for instance diseased vs healthy). Characteristic predictive models may be built based on a set of training data, and these models are subsequently used to predict whether new test data falls under a specific class. In this study, metabolomic data is obtained by doing a (1)H NMR spectroscopy on urine samples obtained from healthy subjects (male and female) and patients suffering from Streptococcus pneumoniae. We compare the performance of traditional PLS-DA multivariate analysis to support vector machines (SVMs), a technique widely used in genome studies on two case studies: (1) a case where nearly complete distinction may be seen (healthy versus pneumonia) and (2) a case where distinction is more ambiguous (male versus female). We show that SVMs are superior to PLS-DA in both cases in terms of predictive accuracy with the least number of features. With fewer number of features, SVMs are able to give better predictive model when compared to that of PLS-DA. PMID:18767870

  7. Biomarkers of whale shark health: a metabolomic approach.

    PubMed

    Dove, Alistair D M; Leisen, Johannes; Zhou, Manshui; Byrne, Jonathan J; Lim-Hing, Krista; Webb, Harry D; Gelbaum, Leslie; Viant, Mark R; Kubanek, Julia; Fernández, Facundo M

    2012-01-01

    In a search for biomarkers of health in whale sharks and as exploration of metabolomics as a modern tool for understanding animal physiology, the metabolite composition of serum in six whale sharks (Rhincodon typus) from an aquarium collection was explored using (1)H nuclear magnetic resonance (NMR) spectroscopy and direct analysis in real time (DART) mass spectrometry (MS). Principal components analysis (PCA) of spectral data showed that individual animals could be resolved based on the metabolite composition of their serum and that two unhealthy individuals could be discriminated from the remaining healthy animals. The major difference between healthy and unhealthy individuals was the concentration of homarine, here reported for the first time in an elasmobranch, which was present at substantially lower concentrations in unhealthy whale sharks, suggesting that this metabolite may be a useful biomarker of health status in this species. The function(s) of homarine in sharks remain uncertain but it likely plays a significant role as an osmolyte. The presence of trimethylamine oxide (TMAO), another well-known protective osmolyte of elasmobranchs, at 0.1-0.3 mol L(-1) was also confirmed using both NMR and MS. Twenty-three additional potential biomarkers were identified based on significant differences in the frequency of their occurrence between samples from healthy and unhealthy animals, as detected by DART MS. Overall, NMR and MS provided complementary data that showed that metabolomics is a useful approach for biomarker prospecting in poorly studied species like elasmobranchs. PMID:23166652

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

    PubMed

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

    2014-07-01

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

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

    PubMed

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

    2014-10-01

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

  10. The glycerophospho-metabolome and its influence on amino acid homeostasis revealed by brain metabolomics of GDE1(-/-) mice

    PubMed Central

    Kopp, Florian; Komatsu, Toru; Nomura, Daniel K.; Trauger, Sunia A.; Thomas, Jason R.; Siuzdak, Gary; Simon, Gabriel M.; Cravatt, Benjamin F.

    2010-01-01

    GDE1 is a mammalian glycerophosphodiesterase (GDE) implicated by in vitro studies in the regulation of glycerophopho-inositol (GroPIns) and possibly other glycerophospho (GroP) metabolites. Here, we show using untargeted metabolomics that GroPIns is profoundly (> 20-fold) elevated in brain tissue from GDE1(-/-) mice. Furthermore, two additional GroP-metabolites not previously identified in eukaryotic cells, glycerophospho-serine (GroPSer) and glycerophospho-glycerate (GroPGate), were also highly elevated in GDE1(-/-) brains. Enzyme assays with synthetic GroP-metabolites confirmed that GroPSer and GroPGate are direct substrates of GDE1. Interestingly, our metabolomic profiles also revealed that serine (both L-and D-) levels were significantly reduced in brains of GDE1 (-/-) mice. These findings designate GroPSer as a previously unappreciated reservoir for free serine in the nervous system and suggest that GDE1, through recycling serine from GroPSer, may impact D-serine-dependent neural signaling processes in vivo. PMID:20797612

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

    PubMed

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

    2015-02-01

    Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This review covers the approximate period of 2000 to 2014, and highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR for metabolite identifications, and X-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine. PMID:25342293

  12. Metabolomic strategies for the identification of new enzyme functions and metabolic pathways.

    PubMed

    Prosser, Gareth A; Larrouy-Maumus, Gerald; de Carvalho, Luiz Pedro S

    2014-06-01

    Recent technological advances in accurate mass spectrometry and data analysis have revolutionized metabolomics experimentation. Activity-based and global metabolomic profiling methods allow simultaneous and rapid screening of hundreds of metabolites from a variety of chemical classes, making them useful tools for the discovery of novel enzymatic activities and metabolic pathways. By using the metabolome of the relevant organism or close species, these methods capitalize on biological relevance, avoiding the assignment of artificial and non-physiological functions. This review discusses state-of-the-art metabolomic approaches and highlights recent examples of their use for enzyme annotation, discovery of new metabolic pathways, and gene assignment of orphan metabolic activities across diverse biological sources. PMID:24829223

  13. RAMAN SPECTROSCOPY-BASED METABOLOMICS FOR DIFFERENTIATING EXPOSURES TO TRIAZOLE FUNGICIDES USING RAT URINE

    EPA Science Inventory

    Normal Raman spectroscopy was evaluated as a metabolomic tool for assessing the impacts of exposure to environmental contaminants, using rat urine collected during the course of a toxicological study. Specifically, one of three triazole fungicides, myclobutanil, propiconazole or ...

  14. Modern plant metabolomics: Advanced natural product gene discoveries, improved technologies, and future prospects

    SciTech Connect

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

    2014-10-24

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

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

    PubMed Central

    Aretz, Ina; Meierhofer, David

    2016-01-01

    Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology. PMID:27128910

  16. Establishment of local searching methods for orbitrap-based high throughput metabolomics analysis.

    PubMed

    Tang, Haiping; Wang, Xueying; Xu, Lina; Ran, Xiaorong; Li, Xiangjun; Chen, Ligong; Zhao, Xinbin; Deng, Haiteng; Liu, Xiaohui

    2016-08-15

    Our method aims to establish local endogenous metabolite databases economically without purchasing chemical standards, giving strong bases for following orbitrap based high throughput untargeted metabolomics analysis. A new approach here is introduced to construct metabolite databases on the base of biological sample analysis and mathematic extrapolation. Building local metabolite databases traditionally requires expensive chemical standards, which is barely affordable for most research labs. As a result, most labs working on metabolomics analysis have to refer public libraries, which is time consuming and limited for high throughput analysis. Using this strategy, a high throughput orbitrap based metabolomics platform can be established at almost no cost within a couple of months. It enables to facilitate the application of high throughput metabolomics analysis to identify disease-related biomarkers or investigate biological functions using orbitrap. PMID:27260449

  17. Metabolomic Technologies for Improving the Quality of Food: Practice and Promise.

    PubMed

    Johanningsmeier, Suzanne D; Harris, G Keith; Klevorn, Claire M

    2016-01-01

    It is now well documented that the diet has a significant impact on human health and well-being. However, the complete set of small molecule metabolites present in foods that make up the human diet and the role of food production systems in altering this food metabolome are still largely unknown. Metabolomic platforms that rely on nuclear magnetic resonance (NMR) and mass spectrometry (MS) analytical technologies are being employed to study the impact of agricultural practices, processing, and storage on the global chemical composition of food; to identify novel bioactive compounds; and for authentication and region-of-origin classifications. This review provides an overview of the current terminology, analytical methods, and compounds associated with metabolomic studies, and provides insight into the application of metabolomics to generate new knowledge that enables us to produce, preserve, and distribute high-quality foods for health promotion. PMID:26772413

  18. USING PHARMACOKINETIC DATA TO INTERPRET METABOLOMIC CHANGES IN CD-1 MICE TREATED WITH TRIAZOLE FUNGICIDES

    EPA Science Inventory

    Triazoles are a class of fungicides widely used in both pharmaceutical and agricultural applications. These compounds elicit a variety of toxic effects including disruption of normal metabolic processes such as steroidogenesis. Metabolomics is used to measure dynamic changes in e...

  19. Linkage of exposure and effects using genomics, proteomics and metabolomics in small fish models (presentation)

    EPA Science Inventory

    This research project combines the use of whole organism endpoints, genomic, proteomic and metabolomic approaches, and computational modeling in a systems biology approach to 1) identify molecular indicators of exposure and biomarkers of effect to EDCs representing several modes/...

  20. Methods used to increase the comprehensive coverage of urinary and plasma metabolomes by MS.

    PubMed

    Chen, Yanhua; Xu, Jing; Zhang, Ruiping; Abliz, Zeper

    2016-05-01

    Metabolomics, focusing on comprehensive analysis of all the metabolites in a biological system, provides a direct signature of biochemical activity. Using emerging technologies in MS, it is possible to simultaneously and rapidly analyze thousands of metabolites. However, due to the chemical and physical diversity of metabolites, it is difficult to acquire a comprehensive and reliable profiling of the whole metabolome. Here, we summarize the state of the art in metabolomics research, focusing on efforts to provide a more comprehensive metabolome coverage via improvements in two fundamental processes: sample preparation and MS analysis. Additionally, the reliable analysis is also highlighted via the combinations of multiple methods (e.g., targeted and untargeted approaches), and analytical quality control and calibration methods. PMID:27079429

  1. INVESTIGATING THE ENANTIOSELECTIVE TOXICITY OF CONAZOLE FUNGICIDES IN RAINBOW TROUT THROUGH NMR BASED METABOLOMICS

    EPA Science Inventory

    Recently, metabolomics, or the quantitative measurement of a broad spectrum of metabolic responses of living systems in response to disease onset or genetic modification, has been employed to enable rapid identification of the mechanisms of toxicity for compounds of environmental...

  2. Metabolomics and its potential in diagnosis, prognosis and treatment of rheumatic diseases

    PubMed Central

    Zdrojewski, Zbigniew

    2015-01-01

    The main aim of metabolomics is to make a comprehensive study of metabolites, the intermediates of biochemical processes in living organisms. Any pathophysiological mechanism caused by disease will inevitably lead to related changes in the concentrations of specific metabolites. In line with this, metabolomics offers a promising laboratory tool for the analysis of potential diagnostic biomarkers that may be used to assess susceptibility to a disease and to evaluate the prognosis and therapeutic response to treatment. Recent data have shown that metabolomics analysis in rheumatoid arthritis has made possible more efficient diagnosis, discrimination between patients with regard to disease activity, prediction of the response to a particular treatment approach, differentiation between rheumatic disease subtypes and greater understanding of the pathophysiology of this disease. Here we characterize metabolomics as a comprehensive laboratory tool and review its potential in the diagnosis, prognosis and treatment of rheumatic diseases such as rheumatoid arthritis.

  3. Applications of metabolomics for kidney disease research: from biomarkers to therapeutic targets.

    PubMed

    Wettersten, Hiromi I; Weiss, Robert H

    2013-01-01

    Metabolomics is one of the relative newcomers of the omics techniques and is likely the one most closely related to actual real-time disease pathophysiology. Hence, it has the power to yield not only specific biomarkers but also insight into the pathophysiology of disease. Despite this power, metabolomics as applied to kidney disease is still in its early adolescence and has not yet reached the mature stage of clinical application, i.e., specific biomarker and therapeutic target discovery. On the other hand, the insight gained from hints into what makes these diseases tick, as is evident from the metabolomics pathways which have been found to be altered in kidney cancer, are now beginning to bear fruit in leading to potential therapeutic targets. It is quite likely that, with greater numbers of clinical materials and with more investigators jumping into the field, metabolomics may well change the course of kidney disease research. PMID:23538740

  4. Metabolomics from the Lab to the Field: Lessons Learned Along the Way

    EPA Science Inventory

    Use of metabolomics in laboratory studies for chemical toxicity evaluation is fast becoming an established technique in environmental science, displaying excellent sensitivity, physiological relevance, and providing valuable information regarding toxic mode(s)-of-action. These qu...

  5. Assessment of Genetically Modified Soybean in Relation to Natural Variation in the Soybean Seed Metabolome

    PubMed Central

    Clarke, Joseph D.; Alexander, Danny C.; Ward, Dennis P.; Ryals, John A.; Mitchell, Matthew W.; Wulff, Jacob E.; Guo, Lining

    2013-01-01

    Genetically modified (GM) crops currently constitute a significant and growing part of agriculture. An important aspect of GM crop adoption is to demonstrate safety and equivalence with respect to conventional crops. Untargeted metabolomics has the ability to profile diverse classes of metabolites and thus could be an adjunct for GM crop substantial equivalence assessment. To account for environmental effects and introgression of GM traits into diverse genetic backgrounds, we propose that the assessment for GM crop metabolic composition should be understood within the context of the natural variation for the crop. Using a non-targeted metabolomics platform, we profiled 169 metabolites and established their dynamic ranges from the seeds of 49 conventional soybean lines representing the current commercial genetic diversity. We further demonstrated that the metabolome of a GM line had no significant deviation from natural variation within the soybean metabolome, with the exception of changes in the targeted engineered pathway. PMID:24170158

  6. Urinary metabolomic profiling of asthmatics can be related to clinical characteristics.

    PubMed

    Loureiro, C C; Oliveira, A S; Santos, M; Rudnitskaya, A; Todo-Bom, A; Bousquet, J; Rocha, S M

    2016-09-01

    Metabolomics has been increasingly explored to achieve an improved understanding of asthma. In the current observational and exploratory study, the first to have examined the relationship between oxidative stress extension, eosinophilic inflammation, and disease severity in asthmatic patients, metabolomics (using target aliphatic aldehydes and alkanes) was carried out using solid-phase microextraction (SPME) followed by a comprehensive two-dimensional gas chromatography coupled to mass spectrometry with a high-resolution time-of-flight analyzer (GC×GC-ToFMS). We were able to demonstrate that metabolomics can give valuable insights into asthma mechanisms once lipidic peroxidation assessed by urinary metabolomics is related to the clinical characteristics of nonobese asthmatics, such as disease severity, lung function, and eosinophilic inflammation. Nevertheless, considering our sample size, the obtained results require further validation using a much larger sample cohort. PMID:27188766

  7. Modern plant metabolomics: Advanced natural product gene discoveries, improved technologies, and future prospects

    DOE PAGESBeta

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

    2014-10-24

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

  8. METABOLOMICS FOR DEVELOPING MARKERS OF CHEMICAL EXPOSURE AND DISTINGUISHING TOXICITY PATHWAYS

    EPA Science Inventory

    Metabolomics involves the application of advanced analytical and statistical tools to profile changes in levels of endogenous metabolites in tissues and biofluids resulting from disease onset, stress, or chemical exposure. Nuclear Magnetic Resonance (NMR) spectroscopy-based meta...

  9. Metabolomic strategies for the identification of new enzyme functions and metabolic pathways

    PubMed Central

    Prosser, Gareth A; Larrouy-Maumus, Gerald; de Carvalho, Luiz Pedro S

    2014-01-01

    Recent technological advances in accurate mass spectrometry and data analysis have revolutionized metabolomics experimentation. Activity-based and global metabolomic profiling methods allow simultaneous and rapid screening of hundreds of metabolites from a variety of chemical classes, making them useful tools for the discovery of novel enzymatic activities and metabolic pathways. By using the metabolome of the relevant organism or close species, these methods capitalize on biological relevance, avoiding the assignment of artificial and non-physiological functions. This review discusses state-of-the-art metabolomic approaches and highlights recent examples of their use for enzyme annotation, discovery of new metabolic pathways, and gene assignment of orphan metabolic activities across diverse biological sources. PMID:24829223

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

    SciTech Connect

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

    2011-08-15

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

  11. Metabolomics approaches for discovering biomarkers of drug-induced hepatotoxicity and nephrotoxicity

    SciTech Connect

    Beger, Richard D.; Sun, Jinchun; Schnackenberg, Laura K.

    2010-03-01

    Hepatotoxicity and nephrotoxicity are two major reasons that drugs are withdrawn post-market, and hence it is of major concern to both the FDA and pharmaceutical companies. The number of cases of serious adverse effects (SAEs) in marketed drugs has climbed faster than the number of total drug prescriptions issued. In some cases, preclinical animal studies fail to identify the potential toxicity of a new chemical entity (NCE) under development. The current clinical chemistry biomarkers of liver and kidney injury are inadequate in terms of sensitivity and/or specificity, prompting the need to discover new translational specific biomarkers of organ injury. Metabolomics along with genomics and proteomics technologies have the capability of providing translational diagnostic and prognostic biomarkers specific for early stages of liver and kidney injury. Metabolomics has several advantages over the other omics platforms such as ease of sample preparation, data acquisition and use of biofluids collected through minimally invasive procedures in preclinical and clinical studies. The metabolomics platform is reviewed with particular emphasis on applications involving drug-induced hepatotoxicity and nephrotoxicity. Analytical platforms for metabolomics, chemometrics for mining metabolomics data and the applications of the metabolomics technologies are covered in detail with emphasis on recent work in the field.

  12. Plasma metabolomic profiles enhance precision medicine for volunteers of normal health.

    PubMed

    Guo, Lining; Milburn, Michael V; Ryals, John A; Lonergan, Shaun C; Mitchell, Matthew W; Wulff, Jacob E; Alexander, Danny C; Evans, Anne M; Bridgewater, Brandi; Miller, Luke; Gonzalez-Garay, Manuel L; Caskey, C Thomas

    2015-09-01

    Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care. PMID:26283345

  13. Metabolomic profiling can predict which humans will develop liver dysfunction when deprived of dietary choline

    PubMed Central

    Sha, Wei; da Costa, Kerry-Ann; Fischer, Leslie M.; Milburn, Michael V.; Lawton, Kay A.; Berger, Alvin; Jia, Wei; Zeisel, Steven H.

    2010-01-01

    Choline is an essential nutrient, and deficiency causes liver and muscle dysfunction. Common genetic variations alter the risk of developing organ dysfunction when choline deficient, probably by causing metabolic inefficiencies that should be detectable even while ingesting a normal choline-adequate diet. We determined whether metabolomic profiling of plasma at baseline could predict whether humans will develop liver dysfunction when deprived of dietary choline. Fifty-three participants were fed a diet containing 550 mg choline/70 kg/d for 10 d and then fed <50 mg choline/70 kg/d for up to 42 d. Participants who developed organ dysfunction on this diet were repleted with a choline-adequate diet for ≥3 d. Plasma samples, obtained at baseline, end of depletion, and end of repletion, were used for targeted and nontargeted metabolomic profiling. Liver fat was assessed using magnetic resonance spectroscopy. Metabolomic profiling and targeted biochemical analyses were highly correlated for the analytes assessed by both procedures. In addition, we report relative concentration changes of other small molecules detected by the nontargeted metabolomic analysis after choline depletion. Finally, we show that metabolomic profiles of participants when they were consuming a control baseline diet could predict whether they would develop liver dysfunction when deprived of dietary choline.—Sha, W., da Costa, K., Fischer, L. M., Milburn, M. V., Lawton, K. A., Berger, A., Jia, W., Zeisel, S. H. Metabolomic profiling can predict which humans will develop liver dysfunction when deprived of dietary choline. PMID:20371621

  14. Plasma metabolomic profiles enhance precision medicine for volunteers of normal health

    PubMed Central

    Guo, Lining; Milburn, Michael V.; Ryals, John A.; Lonergan, Shaun C.; Mitchell, Matthew W.; Wulff, Jacob E.; Alexander, Danny C.; Evans, Anne M.; Bridgewater, Brandi; Miller, Luke; Gonzalez-Garay, Manuel L.; Caskey, C. Thomas

    2015-01-01

    Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care. PMID:26283345

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

    PubMed

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

    2016-08-01

    Male factor infertility affects approximately half of the infertile couples, in spite of many years of research on male infertility treatment and diagnosis; several outstanding questions remain to be addressed. In this regard, metabolomics as a novel field of omics has been suggested to be applied for male infertility problems. A variety of terms associated with metabolite quantity and quality have been established to demonstrate mixtures of metabolites. Despite metabolomics and metabolite analyses have been around more than decades, a limited number of studies concerning male infertility have been carried out. In this review, we summarised the latest finding in metabolomics techniques and metabolomics biomarkers correlated with male infertility. The rapid progress of a variety of metabolomics platforms, such as nonoptical and optical spectroscopy, could ease separation, recognition, classification and quantification of several metabolites and their metabolic pathways. Here, we recommend that the novel biomarkers determined in the course of metabolomics analysis may stand for potential application of treatment and future clinical practice. PMID:26608970

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

    PubMed

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

    2016-01-01

    MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. PMID:27010336

  17. Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health.

    PubMed

    Vernocchi, Pamela; Del Chierico, Federica; Putignani, Lorenza

    2016-01-01

    The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies. PMID:27507964

  18. Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

    PubMed Central

    Vernocchi, Pamela; Del Chierico, Federica; Putignani, Lorenza

    2016-01-01

    The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies. PMID:27507964

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

    PubMed

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-01-01

    Uropathogenic Escherichia coli (UPEC) growth in women's bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the "interactive metabolome", which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI. PMID:27076285

  20. Data Fusion in Metabolomics and Proteomics for Biomarker Discovery.

    PubMed

    Blanchet, Lionel; Smolinska, Agnieszka

    2016-01-01

    Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry. Each method has inherent advantages and drawbacks, but they are complementary in terms of biological information.The fusion of different measurements is a complex topic. We describe here a framework allowing combining multiple data sets, provided by different analytical platforms. For each platform, the relevant information is extracted in the first step. The obtained latent variables are then fused and further analyzed. The influence of the original variables is then calculated back and interpreted. PMID:26519180

  1. Symbiodinium—Invertebrate Symbioses and the Role of Metabolomics

    PubMed Central

    Gordon, Benjamin R.; Leggat, William

    2010-01-01

    Symbioses play an important role within the marine environment. Among the most well known of these symbioses is that between coral and the photosynthetic dinoflagellate, Symbiodinium spp. Understanding the metabolic relationships between the host and the symbiont is of the utmost importance in order to gain insight into how this symbiosis may be disrupted due to environmental stressors. Here we summarize the metabolites related to nutritional roles, diel cycles and the common metabolites associated with the invertebrate-Symbiodinium relationship. We also review the more obscure metabolites and toxins that have been identified through natural products and biomarker research. Finally, we discuss the key role that metabolomics and functional genomics will play in understanding these important symbioses. PMID:21116405

  2. Using metabolomics to dissect host-parasite interactions.

    PubMed

    Kloehn, J; Blume, M; Cobbold, S A; Saunders, E C; Dagley, M J; McConville, M J

    2016-08-01

    Protozoan parasites have evolved diverse growth and metabolic strategies for surviving and proliferating within different extracellular and intracellular niches in their mammalian hosts. Metabolomic approaches, including high coverage metabolite profiling and (13)C/(2)H-stable isotope labeling, are increasingly being used to identify parasite metabolic pathways that are important for survival and replication in vivo. These approaches are highlighting new links between parasite carbon metabolism and the ability of different parasite stages to colonize specific niches or host cell types. They have also revealed novel metabolic regulatory mechanisms that are important for homeostasis and survival in potentially nutrient variable environments. These studies highlight the importance of parasite and host metabolism as determinants of host-parasite interactions. PMID:27200489

  3. Metabolomics Analyses of Cancer Cells in Controlled Microenvironments.

    PubMed

    Gravel, Simon-Pierre; Avizonis, Daina; St-Pierre, Julie

    2016-01-01

    The tumor microenvironment is a complex and heterogeneous milieu in which cancer cells undergo metabolic reprogramming to fuel their growth. Cancer cell lines grown in vitro using traditional culture methods represent key experimental models to gain a mechanistic understanding of tumor biology. This protocol describes the use of gas chromatography-mass spectrometry (GC-MS) to assess metabolic changes in cancer cells grown under varied levels of oxygen and nutrients that may better mimic the tumor microenvironment. Intracellular metabolite changes, metabolite uptake and release, as well as stable isotope ((13)C) tracer analyses are done in a single experimental setup to provide an integrated understanding of metabolic adaptation. Overall, this chapter describes some essential tools and methods to perform comprehensive metabolomics analyses. PMID:27581029

  4. The human NAD metabolome: Functions, metabolism and compartmentalization

    PubMed Central

    Nikiforov, Andrey; Kulikova, Veronika; Ziegler, Mathias

    2015-01-01

    Abstract The metabolism of NAD has emerged as a key regulator of cellular and organismal homeostasis. Being a major component of both bioenergetic and signaling pathways, the molecule is ideally suited to regulate metabolism and major cellular events. In humans, NAD is synthesized from vitamin B3 precursors, most prominently from nicotinamide, which is the degradation product of all NAD-dependent signaling reactions. The scope of NAD-mediated regulatory processes is wide including enzyme regulation, control of gene expression and health span, DNA repair, cell cycle regulation and calcium signaling. In these processes, nicotinamide is cleaved from NAD+ and the remaining ADP-ribosyl moiety used to modify proteins (deacetylation by sirtuins or ADP-ribosylation) or to generate calcium-mobilizing agents such as cyclic ADP-ribose. This review will also emphasize the role of the intermediates in the NAD metabolome, their intra- and extra-cellular conversions and potential contributions to subcellular compartmentalization of NAD pools. PMID:25837229

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

    PubMed

    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. Discovery of biomarkers for oxidative stress based on cellular metabolomics.

    PubMed

    Wang, Ningli; Wei, Jianteng; Liu, Yewei; Pei, Dong; Hu, Qingping; Wang, Yu; Di, Duolong

    2016-07-01

    Oxidative stress has a close relationship with various pathologic physiology phenomena and the potential biomarkers of oxidative stress may provide evidence for clinical diagnosis or disease prevention. Metabolomics was employed to identify the potential biomarkers of oxidative stress. High-performance liquid chromatography-diode array detector, mass spectrometry and partial least squares discriminate analysis were used in this study. The 10, 15 and 13 metabolites were considered to discriminate the model group, vitamin E-treated group and l-glutathione-treated group, respectively. Some of them have been identified, namely, malic acid, vitamin C, reduced glutathione and tryptophan. Identification of other potential biomarkers should be conducted and their physiological significance also needs to be elaborated. PMID:27168482

  7. Metabolomics reveals elevated macromolecular degradation in periodontal disease.

    PubMed

    Barnes, V M; Ciancio, S G; Shibly, O; Xu, T; Devizio, W; Trivedi, H M; Guo, L; Jönsson, T J

    2011-11-01

    Periodontitis is a chronic inflammatory disease characterized by tissue destruction. In the diseased oral environment, saliva has primarily been considered to act as a protectant by lubricating the tissue, mineralizing the bones, neutralizing the pH, and combating microbes. To understand the metabolic role that saliva plays in the diseased state, we performed untargeted metabolomic profiling of saliva from healthy and periodontitic individuals. Several classes of biochemicals, including dipeptide, amino acid, carbohydrate, lipids, and nucleotide metabolites, were altered, consistent with increased macromolecular degradation of proteins, triacylglycerol, glycerolphospholipids, polysaccharides, and polynucleotides in the individuals with periodontal disease. These changes partially reflected the enhanced host-bacterial interactions in the diseased state as supported by increased levels of bacterially modified amino acids and creatine metabolite. More importantly, the increased lipase, protease, and glycosidase activities associated with periodontitis generated a more favorable energy environment for oral bacteria, potentially exacerbating the disease state. PMID:21856966

  8. Circadian Metabolism: From Mechanisms to Metabolomics and Medicine.

    PubMed

    Brown, Steven A

    2016-06-01

    The circadian clock directs nearly all aspects of diurnal physiology, including metabolism. Current research identifies several major axes by which it exerts these effects, including systemic signals as well as direct control of cellular processes by local clocks. This redundant network can transmit metabolic and timing information bidirectionally for optimal synchrony of metabolic processes. Recent advances in cellular profiling and metabolomics technologies have yielded unprecedented insights into the mechanisms behind this control. They have also helped to illuminate individual variation in these mechanisms that could prove important in personalized therapy for metabolic disease. Finally, these technologies have provided platforms with which to screen for the first potential drugs affecting clock-modulated metabolic function. PMID:27113082

  9. Carbon backbone topology of the metabolome of a cell.

    PubMed

    Bingol, Kerem; Zhang, Fengli; Bruschweiler-Li, Lei; Brüschweiler, Rafael

    2012-05-30

    The complex metabolic makeup of a biological system, such as a cell, is a key determinant of its biological state providing unique insights into its function. Here we characterize the metabolome of a cell by a novel homonuclear (13)C 2D NMR approach applied to a nonfractionated uniformly (13)C-enriched lysate of E. coli cells and determine de novo their carbon backbone topologies that constitute the "topolome". A protocol was developed, which first identifies traces in a constant-time (13)C-(13)C TOCSY NMR spectrum that are unique for individual mixture components and then assembles for each trace the corresponding carbon-bond topology network by consensus clustering. This led to the determination of 112 topologies of unique metabolites from a single sample. The topolome is dominated by carbon topologies of carbohydrates (34.8%) and amino acids (45.5%) that can constitute building blocks of more complex structures. PMID:22540339

  10. Amyotrophic Lateral Sclerosis and Metabolomics: Clinical Implication and Therapeutic Approach

    PubMed Central

    Kumar, Alok; Ghosh, Devlina; Singh, R. L.

    2013-01-01

    Amyotrophic lateral sclerosis (ALS) is one of the most common motor neurodegenerative disorders, primarily affecting upper and lower motor neurons in the brain, brainstem, and spinal cord, resulting in paralysis due to muscle weakness and atrophy. The majority of patients die within 3–5 years of symptom onset as a consequence of respiratory failure. Due to relatively fast progression of the disease, early diagnosis is essential. Metabolomics offer a unique opportunity to understand the spatiotemporal metabolic crosstalks through the assessment of body fluids and tissue. So far, one of the most challenging issues related to ALS is to understand the variation of metabolites in body fluids and CNS with the progression of disease. In this paper we will review the changes in metabolic profile in response to disease progression condition and also see the therapeutic implication of various drugs in ALS patients. PMID:26317018

  11. Metabolomic and lipidomic analyses of chronologically aging yeast.

    PubMed

    Richard, Vincent R; Bourque, Simon D; Titorenko, Vladimir I

    2014-01-01

    Metabolomic and lipidomic analyses of yeast cells provide comprehensive empirical datasets for unveiling mechanisms underlying complex biological processes. In this chapter, we describe detailed protocols for using such analyses to study the age-related dynamics of changes in intracellular and extracellular levels of various metabolites and membrane lipids in chronologically aging yeast. The protocols for the following high-throughput analyses are described: (1) microanalytic biochemical assays for monitoring intracellular concentrations of trehalose and glycogen; (2) gas chromatographic quantitative assessment of extracellular concentrations of ethanol and acetic acid; and (3) mass spectrometric identification and quantitation of the entire complement of cellular lipids. These protocols are applicable to the exploration of the metabolic patterns associated not only with aging but also with many other vital processes in yeast. The described here methodology complements the powerful genetic approaches available for mechanistic studies of fundamental aspects of yeast biology. PMID:25213255

  12. Symbiodinium-invertebrate symbioses and the role of metabolomics.

    PubMed

    Gordon, Benjamin R; Leggat, William

    2010-01-01

    Symbioses play an important role within the marine environment. Among the most well known of these symbioses is that between coral and the photosynthetic dinoflagellate, Symbiodinium spp. Understanding the metabolic relationships between the host and the symbiont is of the utmost importance in order to gain insight into how this symbiosis may be disrupted due to environmental stressors. Here we summarize the metabolites related to nutritional roles, diel cycles and the common metabolites associated with the invertebrate-Symbiodinium relationship. We also review the more obscure metabolites and toxins that have been identified through natural products and biomarker research. Finally, we discuss the key role that metabolomics and functional genomics will play in understanding these important symbioses. PMID:21116405

  13. 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

  14. Evaluating effects of penicillin treatment on the metabolome of rats.

    PubMed

    Sun, Jinchun; Schnackenberg, Laura K; Khare, Sangeeta; Yang, Xi; Greenhaw, James; Salminen, William; Mendrick, Donna L; Beger, Richard D

    2013-08-01

    Penicillin (PEN) V, a well-known antibiotic widely used in the treatment of Gram-positive bacterial infections, was evaluated in this study. LC/MS- and NMR-based metabolic profiling were employed to examine the effects of PEN on the host's metabolic phenotype. Male Sprague Dawley rats were randomly divided into groups that were orally administered either 0.5% methylcellulose vehicle, 100 or 2400mg PEN/kg body weight once daily for up to 14 consecutive days. Urine, plasma and tissue were collected from groups sacrificed at 6h, 24h or 14d. The body fluids were subjected to clinical chemistry and metabolomics analysis; the tissue samples were processed for histopathology. The only notable clinical chemistry observation was that gamma glutamyltransferase (GGT) significantly decreased at 24h for both dose groups, and significantly decreased at 14d for the high-dose groups. Partial least squares discriminant analysis scores plots of the metabolomics data from urine and plasma samples showed dose- and time-dependent grouping patterns. Time- and dose-dependent decreases in urinary metabolites including indole-containing metabolites (such as 3-methyldioxyindole sulfate generated from bacterial metabolism of tryptophan), organic acids containing phenyl groups (such as hippuric acid, phenyllactic acid and 3-hydroxyanthranilic acid), and metabolites conjugated with sulfate or glucuronide (such as cresol sulfate and aminophenol sulfate) indicated that the gut microflora population was suppressed. Decreases in many host-gut microbiota urinary co-metabolites (indole- and phenyl-containing metabolites, amino acids, vitamins, nucleotides and bile acids) suggested gut microbiota play important roles in the regulation of host metabolism, including dietary nutrient absorption and reprocessing the absorbed nutrients. Decreases in urinary conjugated metabolites (sulfate, glucuronide and glycine conjugates) implied that gut microbiota might have an impact on chemical detoxification

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

    PubMed

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

    2015-01-01

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

  16. 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

  17. Potential serum biomarkers from a metabolomics study of autism

    PubMed Central

    Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie

    2016-01-01

    Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811

  18. Early hepatic insulin resistance in mice: a metabolomics analysis.

    PubMed

    Li, Lei O; Hu, Yun-Fu; Wang, Lily; Mitchell, Matthew; Berger, Alvin; Coleman, Rosalind A

    2010-03-01

    When fed with a high-fat safflower oil diet for 3 wk, wild-type mice develop hepatic insulin resistance, whereas mice lacking glycerol-3-phosphate acyltransferase-1 retain insulin sensitivity. We examined early changes in the development of insulin resistance via liver and plasma metabolome analyses that compared wild-type and glycerol-3-phosphate acyltransferase-deficient mice fed with either a low-fat or the safflower oil diet for 3 wk. We reasoned that diet-induced changes in metabolites that occurred only in the wild-type mice would reflect those metabolites that were specifically related to hepatic insulin resistance. Of the identifiable metabolites (from 322 metabolites) in liver, wild-type mice fed with the high-fat diet had increases in urea cycle intermediates, consistent with increased deamination of amino acids used for gluconeogenesis. Also increased were stearoylglycerol, gluconate, glucarate, 2-deoxyuridine, and pantothenate. Decreases were observed in S-adenosylhomocysteine, lactate, the bile acid taurocholate, and 1,5-anhydroglucitol, a previously identified marker of short-term glycemic control. Of the identifiable metabolites (from 258 metabolites) in plasma, wild-type mice fed with the high-fat diet had increases in plasma stearate and two pyrimidine-related metabolites, whereas decreases were found in plasma bradykinin, alpha-ketoglutarate, taurocholate, and the tryptophan metabolite, kynurenine. This study identified metabolites previously not known to be associated with insulin resistance and points to the utility of metabolomics analysis in identifying unrecognized biochemical pathways that may be important in understanding the pathophysiology of diabetes. PMID:20150186

  19. The use of metabolomics for the discovery of new biomarkers of effect.

    PubMed

    van Ravenzwaay, B; Cunha, G Coelho-Palermo; Leibold, E; Looser, R; Mellert, W; Prokoudine, A; Walk, T; Wiemer, J

    2007-07-30

    Will metabolomics have a greater chance of success in toxicology and biomarker assessment than genomics and proteomics? Metabolomics has the advantage that (1) it analyses the last step in a series of changes following a toxic insult, (2) many of the metabolites have a known function and (3) changes are detectable in blood. If the analysis of a great number of individual organs can be replaced by one matrix then this will provide significant advantages (less invasive method, no need to kill animals, time course analysis possible). We have chosen to perform the analysis of blood metabolites in such a way as to minimize the risk of artifacts and to have a high number of known metabolites. We have also reduced the amount of variation in the biological system as well as during analysis. In a series of proof of concept studies it could be demonstrated that (1) the metabolome of control animals was stable of a period of nearly 1 year, with a remarkable differentiation between males and females, (2) a dose response relationship in metabolome changes was induced by phenobarbital and that (3) different modes of action could be distinguished by blood metabolome analysis. To investigate the potential of metabolomics to find biomarkers or specific patterns of change we have analyzed the blood metabolome of rats treated with HPPD inhibitors, a novel class of herbicides. The results demonstrated that a single metabolite, tyrosine, can be used as a biomarker. In addition to tyrosine we also found a specific pattern of change that involved nine metabolites. Though the extent of change was less than for tyrosine the consistent change of these metabolites is diagnostic for this (toxicological) mode of action. PMID:17614222

  20. A novel approach for LC-MS/MS-based chiral metabolomics fingerprinting and chiral metabolomics extraction using a pair of enantiomers of chiral derivatization reagents.

    PubMed

    Takayama, Takahiro; Mochizuki, Toshiki; Todoroki, Kenichiro; Min, Jun Zhe; Mizuno, Hajime; Inoue, Koichi; Akatsu, Hiroyasu; Noge, Ichiro; Toyo'oka, Toshimasa

    2015-10-22

    Chiral metabolites are found in a wide variety of living organisms and some of them are understood to be physiologically active compounds and biomarkers. However, the overall analysis of chiral metabolomics is quite difficult due to the high number of metabolites, the significant diversity in their physicochemical properties, and concentration range from metabolite-to-metabolite. To solve this difficulty, we developed a novel approach for chiral metabolomics fingerprinting and chiral metabolomics extraction, which is based on the labeling of a pair of enantiomers of chiral derivatization reagents (i.e., DMT-(S,R)-Pro-OSu and DMT-3(S,R)-Apy) and precursor ion scan chromatography of the derivatives. The multivariate statistics is also required for this strategy. The proposed procedures were evaluated by the detection of a diagnostic marker (i.e., d-lactic acid) using the saliva of diabetic patients. This method was used for the determination of biomarker candidates of chiral amines and carboxyls in Alzheimer's disease (AD) brain homogenates. As the results, l-phenylalanine (L-Phe) and l-lactic acid (L-LA) were identified as the decreased and increased biomarker candidates in the AD brain, respectively. Therefore, the proposed approach seems to be helpful for the determination of non-target chiral metabolomics possessing amines and carboxyls. PMID:26526912

  1. Are the metabolomic responses to folivory of closely related plant species linked to macroevolutionary and plant-folivore coevolutionary processes?

    PubMed

    Rivas-Ubach, Albert; Hódar, José A; Sardans, Jordi; Kyle, Jennifer E; Kim, Young-Mo; Oravec, Michal; Urban, Otmar; Guenther, Alex; Peñuelas, Josep

    2016-07-01

    The debate whether the coevolution of plants and insects or macroevolutionary processes (phylogeny) is the main driver determining the arsenal of molecular defensive compounds of plants remains unresolved. Attacks by herbivorous insects affect not only the composition of defensive compounds in plants but also the entire metabolome. Metabolomes are the final products of genotypes and are constrained by macroevolutionary processes, so closely related species should have similar metabolomic compositions and may respond in similar ways to attacks by folivores. We analyzed the elemental compositions and metabolomes of needles from three closely related Pinus species with distant coevolutionary histories with the caterpillar of the processionary moth respond similarly to its attack. All pines had different metabolomes and metabolic responses to herbivorous attack. The metabolomic variation among the species and the responses to folivory reflected their macroevolutionary relationships, with P. pinaster having the most divergent metabolome. The concentrations of terpenes were in the attacked trees supporting the hypothesis that herbivores avoid plant individuals with higher concentrations. Our results suggest that macroevolutionary history plays important roles in the metabolomic responses of these pine species to folivory, but plant-insect coevolution probably constrains those responses. Combinations of different evolutionary factors and trade-offs are likely responsible for the different responses of each species to folivory, which is not necessarily exclusively linked to plant-insect coevolution. PMID:27386082

  2. Identification of endogenous substrates of orphan cytochrome P450 enzymes through the use of untargeted metabolomics approaches

    PubMed Central

    Cheng, Qian; Guengerich, F. Peter.

    2013-01-01

    Summary Metabolomics provides an invaluable means to interrogate the function of “orphan” enzymes, i.e., those whose endogenous substrates are not known. Here we describe a high performance liquid chromatography-coupled mass spectrometry (HPLC-MS)-based metabolomics approach to identify an endogenous substrate of an orphan cytochrome P450. PMID:23475668

  3. REVIEW ARTICLE: Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes

    NASA Astrophysics Data System (ADS)

    Dunn, Warwick B.

    2008-03-01

    The functional levels of biological cells or organisms can be separated into the genome, transcriptome, proteome and metabolome. Of these the metabolome offers specific advantages to the investigation of the phenotype of biological systems. The investigation of the metabolome (metabolomics) has only recently appeared as a mainstream scientific discipline and is currently developing rapidly for the study of microbial, plant and mammalian metabolomes. The metabolome pipeline or workflow encompasses the processes of sample collection and preparation, collection of analytical data, raw data pre-processing, data analysis and data storage. Of these processes the collection of analytical data will be discussed in this review with specific interest shown in the application of mass spectrometry in the metabolomics pipeline. The current developments in mass spectrometry platforms (GC-MS, LC-MS, DIMS and imaging MS) and applications of specific interest will be highlighted. The current limitations of these platforms and applications will be discussed with areas requiring further development also highlighted. These include the detectable coverage of the metabolome, the identification of metabolites and the process of converting raw data to biological knowledge.

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

    PubMed Central

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-01-01

    Uropathogenic Escherichia coli (UPEC) growth in women’s bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the “interactive metabolome”, which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI. PMID:27076285

  5. Nutri-metabolomics: subtle serum metabolic differences in healthy subjects by NMR-based metabolomics after a short-term nutritional intervention with two tomato sauces.

    PubMed

    Bondia-Pons, Isabel; Cañellas, Nicolau; Abete, Itziar; Rodríguez, Miguel Ángel; Perez-Cornago, Aurora; Navas-Carretero, Santiago; Zulet, M Ángeles; Correig, Xavier; Martínez, J Alfredo

    2013-12-01

    Postgenomics research and development is witnessing novel intersections of omics data intensive technology and applications in health and personalized nutrition. Chief among these is the nascent field of nutri-metabolomics that harnesses metabolomics platforms to discern person-to-person variations in nutritional responses. To this end, differences in the origin and ripening stage of fruits might have a strong impact on their phytochemical composition, and consequently, on their potential nutri-metabolomics effects on health. The objective of the present study was to evaluate the effects of a 4-week cross-over nutritional intervention on the metabolic status of 24 young healthy subjects. The intervention was carried out with two tomato sauces differing in their natural lycopene content, which was achieved by using tomatoes harvested at different times. Blood samples were drawn from each subject before and after each intervention period. Aqueous and lipid extracts from serum samples were analyzed by 1H-NMR metabolic profiling combined with analysis of variance simultaneous component analysis (ASCA) and multilevel simultaneous component analysis (MSCA). These methods allowed the interpretation of the variation induced by the main factors of the study design (sauce treatment and time). The levels of creatine, creatinine, leucine, choline, methionine, and acetate in aqueous extracts were increased after the intervention with the high-lycopene content sauce, while those of ascorbic acid, lactate, pyruvate, isoleucine, alanine were increased after the normal-lycopene content sauce. In conclusion, NMR-based metabolomics of aqueous and lipid extracts allowed the detection of different metabolic changes after the nutritional intervention. This outcome might partly be due to the different ripening state of the fruits used in production of the tomato sauces. The findings presented herein collectively attest to the emergence of the field of nutri-metabolomics as a novel

  6. Complementing reversed-phase selectivity with porous graphitized carbon to increase the metabolome coverage in an on-line two-dimensional LC-MS setup for metabolomics

    PubMed Central

    Ortmayr, Karin; Hann, Stephan

    2015-01-01

    Efficient and robust separation methods are indispensable in modern LC-MS based metabolomics, where high-resolution mass spectrometers are challenged by isomeric and isobaric metabolites. The optimization of chromatographic separation hence remains an invaluable tool in the comprehensive analysis of the chemically diverse intracellular metabolome. While it is widely accepted that a single method with comprehensive metabolome coverage does not exist, the potential of combining different chromatographic selectivities in two-dimensional liquid chromatography is underestimated in the field. Here, we introduce a novel separation system combining reversed-phase and porous graphitized carbon liquid chromatography in a heart-cut on-line two-dimensional setup for mass spectrometry. The proposed experimental setup can be readily implemented using standard HPLC equipment with only one additional HPLC pump and a two-position six-port valve. The method proved to be robust with excellent retention time stability (average 0.4%) even in the presence of biological matrix. Testing the presented approach on a test mixture of 82 relevant intracellular metabolites, the number of metabolites that are retained could be doubled as compared to reversed-phase liquid chromatography alone. The presented work further demonstrates how the distinct selectivity of porous graphitized carbon complements reversed-phase liquid chromatography and extends the metabolome coverage of conventional LC-MS based methods in metabolomics to biologically important, but analytically challenging compound groups such as sugar phosphates. Both metabolic profiling and metabolic fingerprinting benefit from this method's increased separation capabilities that enhance sample throughput and the biological information content of LC-MS data. An inter-platform comparison with GC- and LC-tandem MS analyses confirmed the validity of the presented two-dimensional approach in the analysis of yeast cell extracts from P

  7. Effects of pre-analytical processes on blood samples used in metabolomics studies.

    PubMed

    Yin, Peiyuan; Lehmann, Rainer; Xu, Guowang

    2015-07-01

    Every day, analytical and bio-analytical chemists make sustained efforts to improve the sensitivity, specificity, robustness, and reproducibility of their methods. Especially in targeted and non-targeted profiling approaches, including metabolomics analysis, these objectives are not easy to achieve; however, robust and reproducible measurements and low coefficients of variation (CV) are crucial for successful metabolomics approaches. Nevertheless, all efforts from the analysts are in vain if the sample quality is poor, i.e. if preanalytical errors are made by the partner during sample collection. Preanalytical risks and errors are more common than expected, even when standard operating procedures (SOP) are used. This risk is particularly high in clinical studies, and poor sample quality may heavily bias the CV of the final analytical results, leading to disappointing outcomes of the study and consequently, although unjustified, to critical questions about the analytical performance of the approach from the partner who provided the samples. This review focuses on the preanalytical phase of liquid chromatography-mass spectrometry-driven metabolomics analysis of body fluids. Several important preanalytical factors that may seriously affect the profile of the investigated metabolome in body fluids, including factors before sample collection, blood drawing, subsequent handling of the whole blood (transportation), processing of plasma and serum, and inadequate conditions for sample storage, will be discussed. In addition, a detailed description of latent effects on the stability of the blood metabolome and a suggestion for a practical procedure to circumvent risks in the preanalytical phase will be given. PMID:25736245

  8. Dansylation metabolite assay: a simple and rapid method for sample amount normalization in metabolomics.

    PubMed

    Wu, Yiman; Li, Liang

    2014-10-01

    Metabolomics involves the comparison of the metabolomes of individual samples from two or more groups to reveal the metabolic differences. In order to measure the metabolite concentration differences accurately, using the same amount of starting materials is essential. In this work, we describe a simple and rapid method for sample amount normalization. It is based on dansylation labeling of the amine and phenol submetabolome of an individual sample, followed by solvent extraction of the labeled metabolites and ultraviolet (UV) absorbance measurement using a microplate reader. A calibration curve of a mixture of 17 dansyl-labeled amino acid standards is used to determine the total concentration of the labeled metabolites in a sample. According to the measured concentrations of individual samples, the volume of an aliquot taken from each sample is adjusted so that the same sample amount is taken for subsequent metabolome comparison. As an example of applications, this dansylation metabolite assay method is shown to be useful in comparative metabolome analysis of two different E. coli strains using a differential chemical isotope labeling LC-MS platform. Because of the low cost of equipment and reagents and the simple procedure used in the assay, this method can be readily implemented. We envisage that, this assay, which is analogous to the bicinchoninic acid (BCA) protein assay widely used in proteomics, will be applicable to many types of samples for quantitative metabolomics. PMID:25215550

  9. Recent advances in the application of metabolomics to Alzheimer’s Disease

    PubMed Central

    Trushina, Eugenia; Mielke, Michelle M.

    2013-01-01

    The pathophysiological changes associated with Alzheimer’s Disease (AD) begin decades before the emergence of clinical symptoms. Understanding the early mechanisms associated with AD pathology is, therefore, especially important for identifying disease-modifying therapeutic targets. While the majority of AD clinical trials to date have focused on anti-amyloid-beta (Aβ) treatments, other therapeutic approaches may be necessary. The ability to monitor changes in cellular networks that include both Aβ and non-Aβ pathways is essential to advance our understanding of the etiopathogenesis of AD and subsequent development of cognitive symptoms and dementia. Metabolomics is a powerful tool that detects perturbations in the metabolome, a pool of metabolites that reflects changes downstream of genomic, transcriptomic and proteomic fluctuations, and represents an accurate biochemical profile of the organism in health and disease. The application of metabolomics could help to identify biomarkers for early AD diagnosis, to discover novel therapeutic targets, and to monitor therapeutic response and disease progression. Moreover, given the considerable parallel between mouse and human metabolism, the use of metabolomics provides ready translation of animal research into human studies for accelerated drug design. In this review, we will summarize current progress in the application of metabolomics in both animal models and in humans to further understanding of the mechanisms involved in AD pathogenesis. PMID:23816564

  10. 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. PMID:24966222

  11. Tools and databases of the KOMICS web portal for preprocessing, mining, and dissemination of metabolomics data.

    PubMed

    Sakurai, Nozomu; Ara, Takeshi; Enomoto, Mitsuo; Motegi, Takeshi; Morishita, Yoshihiko; Kurabayashi, Atsushi; Iijima, Yoko; Ogata, Yoshiyuki; Nakajima, Daisuke; Suzuki, Hideyuki; Shibata, Daisuke

    2014-01-01

    A metabolome--the collection of comprehensive quantitative data on metabolites in an organism--has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data. PMID:24949426

  12. A Metabolomic Approach to Understanding the Metabolic Link between Obesity and Diabetes

    PubMed Central

    Park, Seokjae; Sadanala, Krishna Chaitanya; Kim, Eun-Kyoung

    2015-01-01

    Obesity and diabetes arise from an intricate interplay between both genetic and environmental factors. It is well recognized that obesity plays an important role in the development of insulin resistance and diabetes. Yet, the exact mechanism of the connection between obesity and diabetes is still not completely understood. Metabolomics is an analytical approach that aims to detect and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics to the identification of disease biomarkers, with a number of well-known biomarkers identified. Metabolomics is a potent approach to unravel the intricate relationships between metabolism, obesity and progression to diabetes and, at the same time, has potential as a clinical tool for risk evaluation and monitoring of disease. Moreover, metabolomics applications have revealed alterations in the levels of metabolites related to obesity-associated diabetes. This review focuses on the part that metabolomics has played in elucidating the roles of metabolites in the regulation of systemic metabolism relevant to obesity and diabetes. It also explains the possible metabolic relation and association between the two diseases. The metabolites with altered profiles in individual disorders and those that are specifically and similarly altered in both disorders are classified, categorized and summarized. PMID:26072981

  13. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    PubMed

    Xia, Jianguo; Wishart, David S

    2016-01-01

    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. PMID:27603023

  14. Metabolomics Guides Rational Development of a Simplified Cell Culture Medium for Drug Screening against Trypanosoma brucei

    PubMed Central

    Creek, Darren J.; Nijagal, Brunda; Kim, Dong-Hyun; Rojas, Federico; Matthews, Keith R.

    2013-01-01

    In vitro culture methods underpin many experimental approaches to biology and drug discovery. The modification of established cell culture methods to make them more biologically relevant or to optimize growth is traditionally a laborious task. Emerging metabolomic technology enables the rapid evaluation of intra- and extracellular metabolites and can be applied to the rational development of cell culture media. In this study, untargeted semiquantitative and targeted quantitative metabolomic analyses of fresh and spent media revealed the major nutritional requirements for the growth of bloodstream form Trypanosoma brucei. The standard culture medium (HMI11) contained unnecessarily high concentrations of 32 nutrients that were subsequently removed to make the concentrations more closely resemble those normally found in blood. Our new medium, Creek's minimal medium (CMM), supports in vitro growth equivalent to that in HMI11 and causes no significant perturbation of metabolite levels for 94% of the detected metabolome (<3-fold change; α = 0.05). Importantly, improved sensitivity was observed for drug activity studies in whole-cell phenotypic screenings and in the metabolomic mode of action assays. Four-hundred-fold 50% inhibitory concentration decreases were observed for pentamidine and methotrexate, suggesting inhibition of activity by nutrients present in HMI11. CMM is suitable for routine cell culture and offers important advantages for metabolomic studies and drug activity screening. PMID:23571546

  15. The metabolomic study on atherosclerosis mice and its application in a traditional Chinese medicine Sishen granule.

    PubMed

    Tian, Feng; Gu, Lei; Si, Aiyong; Yao, Quanbao; Zhang, Xianwei; Zhao, Jihui; Hu, Daode

    2016-06-01

    Although an atherosclerosis (AS) model using low-density lipoprotein receptor deletion mice has been widely applied, its pathological pathway in metabolite level is still not clear. To further reveal the metabolite profile and identify the potential biomarkers in AS development, a serum metabolomic approach was developed based on reversed-phase liquid chromatography/quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). The established metabolomic platform was also used for elucidating the therapeutic mechanism of a traditional Chinese medicine named Sishen granule (SSKL). Twenty-one potential biomarkers in AS mouse serum were identified. Through functional analysis of these biomarkers, inflammation, proliferation, dysfunction of energy metabolism and amino acid metabolism were considered the most relevant pathological changes in AS. DNA damage products were found for the first time in the metabolomic study of AS. The network established by 20 biomarkers revealed that pyruvate metabolism, citrate cycle, fatty acid metabolism and urea metabolism were seriously disturbed. This metabolomic study not only supplied a systematic view of the progression of AS but also provided a theoretical basis for the treatment of AS. This metabolomic study also demonstrated that SSKL had therapeutic effectiveness for AS through partly reversing the inflammation reaction and amino acid metabolism dysfunction. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26488619

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

    PubMed

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

    2015-01-01

    Metabolomics is a new field of medicine focused on examining and analyzing metabolites produced in biological cells. Biological fluids primarily used in this method include: plasma, cerebrospinal fluid, saliva and urine. The most common methods of evaluating the composition involve nuclear magnetic resonance (NMR) and magnetic resonance (MR) with addition of gas chromatography (GC-MS) or liquid chromatography (LC-MS). Metabolomics is used in a wide variety of medicine disciplines. The variability of biochemical processes in tumor cells in comparison to normal cells is the starting point of such studies. The metabolomic changes are observed not only in solid tumors, like the mammary tumor, ovarian cancer, prostate cancer but also in tumors of the hematopoietic and lymphoid tissues. Nowadays, the aim of studies is to find biomarkers which would help to diagnose a disease quickly, assess its progression, and implement effective treatment. Metabolomics is also widely applied in metabolic diseases, mainly the diabetes. The list of examined metabolites gives promising chances for a successful prognosis, diagnosis and comprehensive monitoring of the progression of this civilization disease. The development of metabolomics will also contribute to the individualization of treatment, proper drugs adjustment, which will make a therapy more successful, cause less side effects and improve the quality of patient's life. PMID:26615014

  17. Post-acquisition filtering of salt cluster artefacts for LC-MS based human metabolomic studies.

    PubMed

    McMillan, A; Renaud, J B; Gloor, G B; Reid, G; Sumarah, M W

    2016-01-01

    Liquid chromatography-high resolution mass spectrometry (LC-MS) has emerged as one of the most widely used platforms for untargeted metabolomics due to its unparalleled sensitivity and metabolite coverage. Despite its prevalence of use, the proportion of true metabolites identified in a given experiment compared to background contaminants and ionization-generated artefacts remains poorly understood. Salt clusters are well documented artefacts of electrospray ionization MS, recognized by their characteristically high mass defects (for this work simply generalized as the decimal numbers after the nominal mass). Exploiting this property, we developed a method to identify and remove salt clusters from LC-MS-based human metabolomics data using mass defect filtering. By comparing the complete set of endogenous metabolites in the human metabolome database to actual plasma, urine and stool samples, we demonstrate that up to 28.5 % of detected features are likely salt clusters. These clusters occur irrespective of ionization mode, column type, sweep gas and sample type, but can be easily removed post-acquisition using a set of R functions presented here. Our mass defect filter removes unwanted noise from LC-MS metabolomics datasets, while retaining true metabolites, and requires only a list of m/z and retention time values. Reducing the number of features prior to statistical analyses will result in more accurate multivariate modeling and differential feature selection, as well as decreased reporting of unknowns that often constitute the largest proportion of human metabolomics data. PMID:27606010

  18. Unexpected similarities between the Schizosaccharomyces and human blood metabolomes, and novel human metabolites.

    PubMed

    Chaleckis, Romanas; Ebe, Masahiro; Pluskal, Tomáš; Murakami, Itsuo; Kondoh, Hiroshi; Yanagida, Mitsuhiro

    2014-10-01

    Metabolomics, a modern branch of chemical biology, provides qualitative and quantitative information about the metabolic states of organisms or cells at the molecular level. Here we report non-targeted, metabolomic analyses of human blood, using liquid chromatography-mass spectrometry (LC-MS). We compared the blood metabolome to the previously reported metabolome of the fission yeast, Schizosaccharomyces pombe. The two metabolomic datasets were highly similar: 101 of 133 compounds identified in human blood (75%) were also present in S. pombe, and 45 of 57 compounds enriched in red blood cells (RBCs) (78%) were also present in yeast. The most abundant metabolites were ATP, glutathione, and glutamine. Apart from these three, the next most abundant metabolites were also involved in energy metabolism, anti-oxidation, and amino acid metabolism. We identified fourteen new blood compounds, eight of which were enriched in RBCs: citramalate, GDP-glucose, trimethyl-histidine, trimethyl-phenylalanine, trimethyl-tryptophan, trimethyl-tyrosine, UDP-acetyl-glucosamine, UDP-glucuronate, dimethyl-lysine, glutamate methyl ester, N-acetyl-(iso)leucine, N-acetyl-glutamate, N2-acetyl-lysine, and N6-acetyl-lysine. Ten of the newly identified blood metabolites were also detected in S. pombe, and ten of the 14 newly identified blood metabolites were methylated or acetylated amino acids. Trimethylated or acetylated free amino acids were also abundant in white blood cells. It may be possible to investigate their physiological roles using yeast genetics. PMID:25010571

  19. Two birds with one stone: Doing metabolomics with your proteomics kit

    PubMed Central

    Fischer, Roman; Bowness, Paul; Kessler, Benedikt M

    2013-01-01

    Proteomic research facilities and laboratories are facing increasing demands for the integration of biological data from multiple ‘-OMICS’ approaches. The aim to fully understand biological processes requires the integrated study of genomes, proteomes and metabolomes. While genomic and proteomic workflows are different, the study of the metabolome overlaps significantly with the latter, both in instrumentation and methodology. However, chemical diversity complicates an easy and direct access to the metabolome by mass spectrometry (MS). The present review provides an introduction into metabolomics workflows from the viewpoint of proteomic researchers. We compare the physicochemical properties of proteins and peptides with metabolites/small molecules to establish principle differences between these analyte classes based on human data. We highlight the implications this may have on sample preparation, separation, ionisation, detection and data analysis. We argue that a typical proteomic workflow (nLC-MS) can be exploited for the detection of a number of aliphatic and aromatic metabolites, including fatty acids, lipids, prostaglandins, di/tripeptides, steroids and vitamins, thereby providing a straightforward entry point for metabolomics-based studies. Limitations and requirements are discussed as well as extensions to the LC-MS workflow to expand the range of detectable molecular classes without investing in dedicated instrumentation such as GC-MS, CE-MS or NMR. PMID:24155035

  20. Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery

    PubMed Central

    2012-01-01

    Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development. PMID:22546809

  1. Metabolomics unveils urinary changes in subjects with metabolic syndrome following 12-week nut consumption.

    PubMed

    Tulipani, Sara; Llorach, Rafael; Jáuregui, Olga; López-Uriarte, Patricia; Garcia-Aloy, Mar; Bullo, Mònica; Salas-Salvadó, Jordi; Andrés-Lacueva, Cristina

    2011-11-01

    Through an HPLC-Q-TOF-MS-driven nontargeted metabolomics approach, we aimed to discriminate changes in the urinary metabolome of subjects with metabolic syndrome (MetS), following 12 weeks of mixed nuts consumption (30 g/day), compared to sex- and age-matched individuals given a control diet. The urinary metabolome corresponding to the nut-enriched diet clearly clustered in a distinct group, and the multivariate data analysis discriminated relevant mass features in this separation. Metabolites corresponding to the discriminating ions (MS features) were then subjected to multiple tandem mass spectrometry experiments using LC-ITD-FT-MS, to confirm their putative identification. The metabolomics approach revealed 20 potential markers of nut intake, including fatty acid conjugated metabolites, phase II and microbial-derived phenolic metabolites, and serotonin metabolites. An increased excretion of serotonin metabolites was associated for the first time with nut consumption. Additionally, the detection of urinary markers of gut microbial and phase II metabolism of nut polyphenols confirmed the understanding of their bioavailability and bioactivity as a priority area of research in the determination of the health effects derived from nut consumption. The results confirmed how a nontargeted metabolomics strategy may help to access unexplored metabolic pathways impacted by diet, thereby raising prospects for new intervention targets. PMID:21905751

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

    PubMed Central

    Wood, Paul L

    2014-01-01

    Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed. PMID:23842599

  3. MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks.

    PubMed

    Cottret, Ludovic; Wildridge, David; Vinson, Florence; Barrett, Michael P; Charles, Hubert; Sagot, Marie-France; Jourdan, Fabien

    2010-07-01

    High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr. PMID:20444866

  4. Metabolomic analysis of rat plasma following chronic low-dose exposure to dichlorvos.

    PubMed

    Yang, J; Wang, H; Xu, W; Hao, D; Du, L; Zhao, X; Sun, C

    2013-02-01

    This study aims to assess the metabolomic profile and related histopathological outcomes of rat plasma after chronic low-dose exposure to dichlorvos (DDVP). A total of 120 male Wistar rats were treated with 0, 2.4, 7.2, and 21.6 mg/kg of body weight/day DDVP continuously for 24 weeks by drinking water. Rat plasma samples were collected at different time-points to measure the metabolomic profiles by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Liver tissue analysis was performed to correlate histopathological outcome status to plasma metabolomics. Significant changes in some of the metabolites were found in all the treated groups compared with the control group. LysoPC (15:0/0:0), LysoPC (16:0/0:0), LysoPC (17:0/0:0), LysoPC (0:0/18:0), sphingosine, sphinganine, C16 sphinganine, C17 sphinganine, and arachidonic acid were decreased in the treated groups. LysoPE (16:0/0:0) was increased after dosing with DDVP. Histopathological test outcomes coincided with the plasma metabolomic-profile analysis results obtained by UPLC-MS. The livers were damaged following chronic exposure to DDVP. Abnormal changes in some lipids in the plasma, such as LysoPC (0:0/18:0), were closely related to liver dysfunction. Therefore, metabolomic analysis provides the unique advantages of unveiling the mechanisms of DDVP. PMID:23060408

  5. Metabolomic Analysis of Diapausing and Noni-diapausing Larvae of the European Corn Borer Ostrinia nubilalis (Hbn.) (Lepidoptera: Crambidae).

    PubMed

    Purać, Jelena; Kojić, Danijela; Popović, Željko D; Vukašinović, Elvira; Tiziani, Stefano; Günther, Ulrich L; Grubor-Lajšić, Gordana

    2015-01-01

    In this study, an (1)H-NMR -based metabolomic approach was used to investigate the biochemical mechanisms of diapause and cold hardiness in diapausing larvae of the European corn borer Ostrinia nubilalis. Metabolomic patterns in polar hemolymph extracts from non-diapausing and diapausing larvae of O. nubilalis were compared. Analysis indicated 13 metabolites: 7 amino acids, glycerol, acetate, citrate, succinate, lactate and putrescine. Results show that diapausing larvae display different metabolomic patterns compared to active non-diapausing larvae, with predominant metabolites identified as glycerol, proline and alanine. In specific diapausing larvae initially kept at 5 °C then gradually chilled to –3 °C and –16 °C, alanine , glycerol and acetate were predominant metabolites. (1)H-NMR spectroscopy provides new insight into the metabolomic patterns associated with cold resistance and diapause in O. nubilalis larvae, suggesting distinct metabolomes function in actively developing and diapausing larvae. PMID:26680702

  6. Chemometric methods in data processing of mass spectrometry-based metabolomics: A review.

    PubMed

    Yi, Lunzhao; Dong, Naiping; Yun, Yonghuan; Deng, Baichuan; Ren, Dabing; Liu, Shao; Liang, Yizeng

    2016-03-31

    This review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets. PMID:26965324

  7. Metabolite identification and quantitation in LC-MS/MS-based metabolomics

    PubMed Central

    Xiao, Jun Feng; Zhou, Bin; Ressom, Habtom W.

    2011-01-01

    Metabolomics aims at detection and quantitation of all metabolites in biological samples. The presence of metabolites with a wide variety of physicochemical properties and different levels of abundance challenges existing analytical platforms used for identification and quantitation of metabolites. Significant efforts have been made to improve analytical and computational methods for metabolomics studies. This review focuses on the use of liquid chromatography with tandem mass spectrometry (LC-MS/MS) for quantitative and qualitative metabolomics studies. It illustrates recent developments in computational methods for metabolite identification, including ion annotation, spectral interpretation and spectral matching. We also review selected reaction monitoring and high-resolution MS for metabolite quantitation. We discuss current challenges in metabolite identification and quantitation as well as potential solutions. PMID:22345829

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

    PubMed Central

    Vaniya, Arpana

    2015-01-01

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

  9. Review: Metabolomics in the developmental origins of obesity and its cardiometabolic consequences

    PubMed Central

    Hivert, MF; Perng, W; Watkins, S; Newgard, CB; Kenny, LC; Kristal, BS; Patti, ME; Isganaitis, E; DeMeo, DL; Oken, E; Gillman, MW

    2015-01-01

    In this review, we discuss the potential role of metabolomics to enhance understanding of obesity-related developmental origins of health and disease (DOHaD). We first provide an overview of common techniques and analytical approaches to help interested investigators dive into this relatively novel field. Next, we describe how metabolomics may capture exposures that are notoriously difficult to quantify, and help to further refine phenotypes associated with excess adiposity and related metabolic sequelae over the life course. Together, these data can ultimately help to elucidate mechanisms that underlie fetal metabolic programming. Finally, we review current gaps in knowledge and identify areas where the field of metabolomics is likely to provide insights into mechanisms linked to DOHaD in human populations. PMID:25631626

  10. Agronomic, metabolomic and lipidomic characterisation of Sicilian Origanum vulgare (L.) ecotypes.

    PubMed

    Tuttolomondo, Teresa; Martinelli, Federico; Mariotti, Lorenzo; Leto, Claudio; Maggio, Antonella; La Bella, Salvatore

    2016-01-01

    Although Origanum vulgare (L.) has been deeply analysed at phytochemical level, poor knowledge is available regarding non-volatile compounds such as lipids. The aim of this work was to characterise five wild Sicilian Origanum ecotypes from an agronomic, metabolomic and lipidomic perspective. Serradifalco presented higher dry weight and inflorescences/plant than the others while Favara had a significantly higher number of branches per plant and more extensive flowered stratum. Metabolomic analysis, performed with LC-MS-TOF, allowed a preliminary characterisation of the non-volatile metabolome of the five oregano ecotypes Origanum vulgare ssp. hirtum. Twenty-five metabolites were identified belonging to organic acids, amino acids, lysophosphatidylcholines, carnithines, nucleic bases and lysophosphatidylethanolamines. Lipidomic analysis identified 115 polar plant membrane glycerolipid species. Thirteen of them were differentially present in the two chosen ecotypes. The role of these metabolites in plant physiology from a qualitative and pharmacological point of view was discussed. PMID:26540480

  11. Assessment of fruit juice authenticity using UPLC-QToF MS: a metabolomics approach.

    PubMed

    Jandrić, Z; Roberts, D; Rathor, M N; Abrahim, A; Islam, M; Cannavan, A

    2014-04-01

    In recent years, with the growing complexity of global food supply chains and trade, food fraud, including adulteration of high value foods with cheaper substitutes, has become an increasingly important issue. A metabolomics approach can be applied to discover biomarkers that can be used to trace food adulteration. A study was undertaken to discover novel, potential biomarkers for the rapid detection of the adulteration of fruit juices with cheaper alternatives. Pineapple, orange, grapefruit, apple, clementine, and pomelo were investigated. Untargeted metabolite fingerprinting was performed by UPLC-QToF MS with multivariate data analysis. Twenty-one differential metabolites were selected, contributing to the separation between pineapple, orange and grapefruit juices, and their admixtures down to 1% adulteration level. A targeted metabolomics method was then optimised and adulteration could be detected at 1%. The results demonstrate that metabolomics has potential as a screening tool for the rapid detection of food adulteration. PMID:24262519

  12. Dual metabolomics: a novel approach to understanding plant-pathogen interactions.

    PubMed

    Allwood, J William; Clarke, Andrew; Goodacre, Royston; Mur, Luis A J

    2010-04-01

    One of the most well-characterised plant pathogenic interactions involves Arabidopsis thaliana and the bacteria Pseudomonas syringae pathovar tomato (Pst). The standard Pst inoculation procedure involves infiltration of large populations of bacteria into plant leaves which means that metabolite changes cannot be readily assigned to the host or pathogen. A plant cell-pathogen co-culture based approach has been developed where the plant and pathogen cells are separated after 12h of co-culture via differential filtering and centrifugation. Fourier transform infrared (FT-IR) spectroscopy was employed to assess the intracellular metabolomes (metabolic fingerprints) of both host and pathogen and their extruded (extracellular) metabolites (metabolic footprints) under conditions relevant to disease and resistance. We propose that this system will enable the metabolomic profiling of the separated host and pathogen (i.e. 'dual metabolomics') and will facilitate the modelling of reciprocal responses. PMID:20138320

  13. 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

  14. The guard cell metabolome: functions in stomatal movement and global food security

    PubMed Central

    Misra, Biswapriya B.; Acharya, Biswa R.; Granot, David; Assmann, Sarah M.; Chen, Sixue

    2015-01-01

    Guard cells represent a unique single cell-type system for the study of cellular responses to abiotic and biotic perturbations that affect stomatal movement. Decades of effort through both classical physiological and functional genomics approaches have generated an enormous amount of information on the roles of individual metabolites in stomatal guard cell function and physiology. Recent application of metabolomics methods has produced a substantial amount of new information on metabolome control of stomatal movement. In conjunction with other “omics” approaches, the knowledge-base is growing to reach a systems-level description of this single cell-type. Here we summarize current knowledge of the guard cell metabolome and highlight critical metabolites that bear significant impact on future engineering and breeding efforts to generate plants/crops that are resistant to environmental challenges and produce high yield and quality products for food and energy security. PMID:26042131

  15. Omic Relief for the Biotically Stressed: Metabolomics of Plant Biotic Interactions.

    PubMed

    Tenenboim, Hezi; Brotman, Yariv

    2016-09-01

    Many aspects of the way plants protect themselves against pathogen attack, or react upon such an attack, are realized by metabolites. The ambitious aim of metabolomics, namely the identification and annotation of the entire cellular metabolome, still poses a considerable challenge due to the high diversity of the metabolites in the cell. Recent advances in analytical methods and data analysis have resulted in improved sensitivity, accuracy, and capacity, allowing the analysis of several hundreds or even thousands of compounds within one sample. Investigators have only recently begun to acknowledge and harness the power of metabolomics to elucidate key questions in the study of plant biotic interactions; we review trends and developments in the field. PMID:27185334

  16. The Role of Mass Spectrometry-Based Metabolomics in Medical Countermeasures Against Radiation

    PubMed Central

    Patterson, Andrew D.; Lanz, Christian; Gonzalez, Frank J.; Idle, Jeffrey R.

    2013-01-01

    Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry (CMCR) was established to develop field-deployable biodosimeters based, in principle, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter. PMID:19890938

  17. The impact of blood on liver metabolite profiling - a combined metabolomic and proteomic approach.

    PubMed

    Ly-Verdú, Saray; Schaefer, Alexander; Kahle, Melanie; Groeger, Thomas; Neschen, Susanne; Arteaga-Salas, Jose M; Ueffing, Marius; de Angelis, Martin Hrabe; Zimmermann, Ralf

    2014-02-01

    Metabolomics has entered the well-established omic sciences as it is an indispensable information resource to achieve a global picture of biological systems. The aim of the present study was to estimate the influence of blood removal from mice liver as part of sample preparation for metabolomic and proteomic studies. For this purpose, perfused mice liver tissue (i.e. with blood removed) and unperfused mice liver tissue (i.e. containing blood) were compared by two-dimensional gas chromatography time of flight mass spectrometry (GC × GC-TOFMS) for the metabolomic part, and by liquid chromatography tandem mass spectrometry (LC-MS/MS) for the proteomic part. Our data showed significant differences between the unperfused and perfused liver tissue samples. Furthermore, we also observed an overlap of blood and tissue metabolite profiles in our data, suggesting that the perfusion of liver tissue prior to analysis is beneficial for an accurate metabolic profile of this organ. PMID:23934789

  18. Metabolomic profiling for the identification of novel diagnostic markers in prostate cancer.

    PubMed

    Lucarelli, Giuseppe; Rutigliano, Monica; Galleggiante, Vanessa; Giglio, Andrea; Palazzo, Silvano; Ferro, Matteo; Simone, Cristiano; Bettocchi, Carlo; Battaglia, Michele; Ditonno, Pasquale

    2015-01-01

    Metabolomic profiling offers a powerful methodology for understanding the perturbations of biochemical systems occurring during a disease process. During neoplastic transformation, prostate cells undergo metabolic reprogramming to satisfy the demands of growth and proliferation. An early event in prostate cell transformation is the loss of capacity to accumulate zinc. This change is associated with a higher energy efficiency and increased lipid biosynthesis for cellular proliferation, membrane formation and cell signaling. Moreover, recent studies have shown that sarcosine, an N-methyl derivative of glycine, was significantly increased during disease progression from normal to localized to metastatic prostate cancer. Mapping the metabolomic profiles to their respective biochemical pathways showed an upregulation of androgen-induced protein synthesis, an increased amino acid metabolism and a perturbation of nitrogen breakdown pathways, along with high total choline-containing compounds and phosphocholine levels. In this review, the role of emerging biomarkers is summarized, based on the current understanding of the prostate cancer metabolome. PMID:26174441

  19. Cytoplasmic genetic variation and extensive cytonuclear interactions influence natural variation in the metabolome

    PubMed Central

    Joseph, Bindu; Corwin, Jason A; Li, Baohua; Atwell, Suzi; Kliebenstein, Daniel J

    2013-01-01

    Understanding genome to phenotype linkages has been greatly enabled by genomic sequencing. However, most genome analysis is typically confined to the nuclear genome. We conducted a metabolomic QTL analysis on a reciprocal RIL population structured to examine how variation in the organelle genomes affects phenotypic variation. This showed that the cytoplasmic variation had effects similar to, if not larger than, the largest individual nuclear locus. Inclusion of cytoplasmic variation into the genetic model greatly increased the explained phenotypic variation. Cytoplasmic genetic variation was a central hub in the epistatic network controlling the plant metabolome. This epistatic influence manifested such that the cytoplasmic background could alter or hide pairwise epistasis between nuclear loci. Thus, cytoplasmic genetic variation plays a central role in controlling natural variation in metabolomic networks. This suggests that cytoplasmic genomes must be included in any future analysis of natural variation. DOI: http://dx.doi.org/10.7554/eLife.00776.001 PMID:24150750

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

    PubMed Central

    Bingol, Kerem; Brüschweiler, Rafael

    2015-01-01

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

  1. Exceptional Evolutionary Divergence of Human Muscle and Brain Metabolomes Parallels Human Cognitive and Physical Uniqueness

    PubMed Central

    Bozek, Katarzyna; Wei, Yuning; Yan, Zheng; Liu, Xiling; Xiong, Jieyi; Sugimoto, Masahiro; Tomita, Masaru; Pääbo, Svante; Pieszek, Raik; Sherwood, Chet C.; Hof, Patrick R.; Ely, John J.; Steinhauser, Dirk; Willmitzer, Lothar; Bangsbo, Jens; Hansson, Ola; Call, Josep; Giavalisco, Patrick; Khaitovich, Philipp

    2014-01-01

    Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys. PMID:24866127

  2. Metabolomic analysis of amino acid and energy metabolism in rats supplemented with chlorogenic acid

    PubMed Central

    Ruan, Zheng; Yang, Yuhui; Zhou, Yan; Wen, Yanmei; Ding, Sheng; Liu, Gang; Wu, Xin; Deng, Zeyuan; Assaad, Houssein; Wu, Guoyao

    2016-01-01

    This study was conducted to investigate effects of chlorogenic acid (CGA) supplementation on serum and hepatic metabolomes in rats. Rats received daily intragastric administration of either CGA (60 mg/kg body weight) or distilled water (control) for 4 weeks. Growth performance, serum biochemical profiles, and hepatic morphology were measured. Additionally, serum and liver tissue extracts were analyzed for metabolomes by high-resolution 1H nuclear magnetic resonance-based metabolomics and multivariate statistics. CGA did not affect rat growth performance, serum biochemical profiles, or hepatic morphology. However, supplementation with CGA decreased serum concentrations of lactate, pyruvate, succinate, citrate, β-hydroxybutyrate and acetoacetate, while increasing serum concentrations of glycine and hepatic concentrations of glutathione. These results suggest that CGA supplementation results in perturbation of energy and amino acid metabolism in rats. We suggest that glycine and glutathione in serum may be useful biomarkers for biological properties of CGA on nitrogen metabolism in vivo. PMID:24927697

  3. 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

  4. 1H NMR metabolomics study of age profiling in children

    PubMed Central

    Gu, Haiwei; Pan, Zhengzheng; Xi, Bowei; Hainline, Bryan E.; Shanaiah, Narasimhamurthy; Asiago, Vincent; Nagana Gowda, G. A.; Raftery, Daniel

    2014-01-01

    Metabolic profiling of urine provides a fingerprint of personalized endogenous metabolite markers that correlate to a number of factors such as gender, disease, diet, toxicity, medication, and age. It is important to study these factors individually, if possible to unravel their unique contributions. In this study, age-related metabolic changes in children of age 12 years and below were analyzed by 1H NMR spectroscopy of urine. The effect of age on the urinary metabolite profile was observed as a distinct age-dependent clustering even from the unsupervised principal component analysis. Further analysis, using partial least squares with orthogonal signal correction regression with respect to age, resulted in the identification of an age-related metabolic profile. Metabolites that correlated with age included creatinine, creatine, glycine, betaine/TMAO, citrate, succinate, and acetone. Although creatinine increased with age, all the other metabolites decreased. These results may be potentially useful in assessing the biological age (as opposed to chronological) of young humans as well as in providing a deeper understanding of the confounding factors in the application of metabolomics. PMID:19441074

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

    PubMed Central

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

    2014-01-01

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

  6. Comparative Metabolomic and Lipidomic Analysis of Phenotype Stratified Prostate Cells

    PubMed Central

    Booher, Christiana L.; Rhim, Johng S.; Rainville, Paul; Langridge, James; Baker, Andrew; Nyalwidhe, Julius O.

    2015-01-01

    Prostate cancer (PCa) is the most prevalent cancer amongst men and the second most common cause of cancer related-deaths in the USA. Prostate cancer is a heterogeneous disease ranging from indolent asymptomatic cases to very aggressive life threatening forms. The goal of this study was to identify differentially expressed metabolites and lipids in prostate cells with different tumorigenic phenotypes. We have used mass spectrometry metabolomic profiling, lipidomic profiling, bioinformatic and statistical methods to identify, quantify and characterize differentially regulated molecules in five prostate derived cell lines. We have identified potentially interesting species of different lipid subclasses including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), glycerophosphoinositols (PIs) and other metabolites that are significantly upregulated in prostate cancer cells derived from distant metastatic sites. Transcriptomic and biochemical analysis of key enzymes that are involved in lipid metabolism demonstrate the significant upregulation of choline kinase alpha in the metastatic cells compared to the non-malignant and non-metastatic cells. This suggests that different de novo lipogenesis and other specific signal transduction pathways are activated in aggressive metastatic cells as compared to normal and non-metastatic cells. PMID:26244785

  7. Atmospheric pressure infrared MALDI imaging mass spectrometry for plant metabolomics.

    PubMed

    Li, Yue; Shrestha, Bindesh; Vertes, Akos

    2008-01-15

    The utility of atmospheric pressure infrared MALDI mass spectrometry (AP IR-MALDI) was assessed for plant metabolomics studies. Tissue sections from plant organs, including flowers, ovaries, aggregate fruits, fruits, leaves, tubers, bulbs, and seeds were studied in both positive and negative ion modes. For leaves, single laser pulses sampled the cuticle and upper epidermal cells, whereas multiple pulses were demonstrated to ablate some mesophyll layers. Tandem mass spectra were obtained with collision-activated dissociation to aid with the identification of some observed ions. In the positive mode, most ions were produced as potassium, proton, or sometimes sodium ion adducts, whereas proton loss was dominant in the negative ion mode. Over 50 small metabolites and various lipids were detected in the spectra including, for example, 7 of the 10 intermediates in the citric acid cycle. Key components of the glycolysis pathway occurring in the plant cytosol were found along with intermediates of phospholipid biosynthesis and reactants or products of amino acid, nucleotide, oligosaccharide, and flavonoid biosynthesis. AP IR-MALDI mass spectrometry was used to follow the fluid transport driven by transpiration and image the spatial distributions of several metabolites in a white lily (Lilium candidum) flower petal. PMID:18088102

  8. Association genetics of the loblolly pine (Pinus taeda, Pinaceae) metabolome.

    PubMed

    Eckert, Andrew J; Wegrzyn, Jill L; Cumbie, W Patrick; Goldfarb, Barry; Huber, Dudley A; Tolstikov, Vladimir; Fiehn, Oliver; Neale, David B

    2012-03-01

    The metabolome of a plant comprises all small molecule metabolites, which are produced during cellular processes. The genetic basis for metabolites in nonmodel plants is unknown, despite frequently observed correlations between metabolite concentrations and stress responses. A quantitative genetic analysis of metabolites in a nonmodel plant species is thus warranted. Here, we use standard association genetic methods to correlate 3563 single nucleotide polymorphisms (SNPs) to concentrations of 292 metabolites measured in a single loblolly pine (Pinus taeda) association population. A total of 28 single locus associations were detected, representing 24 and 20 unique SNPs and metabolites, respectively. Multilocus Bayesian mixed linear models identified 2998 additional associations for a total of 1617 unique SNPs associated to 255 metabolites. These SNPs explained sizeable fractions of metabolite heritabilities when considered jointly (56.6% on average) and had lower minor allele frequencies and magnitudes of population structure as compared with random SNPs. Modest sets of SNPs (n = 1-23) explained sizeable portions of genetic effects for many metabolites, thus highlighting the importance of multi-SNP models to association mapping, and exhibited patterns of polymorphism consistent with being linked to targets of natural selection. The implications for association mapping in forest trees are discussed. PMID:22129444

  9. Proteomics and Metabolomics for In Situ Monitoring of Wound Healing

    PubMed Central

    Kalkhof, Stefan; Förster, Yvonne; Schmidt, Johannes; Schulz, Matthias C.; Baumann, Sven; Weißflog, Anne; Gao, Wenling; Hempel, Ute; Eckelt, Uwe; Rammelt, Stefan; von Bergen, Martin

    2014-01-01

    Wound healing of soft tissue and bone defects is a complex process in which cellular differentiation and adaption are regulated by internal and external factors, among them are many different proteins. In contrast to insights into the significance of various single proteins based on model systems, the knowledge about the processes at the actual site of wound healing is still limited. This is caused by a general lack of methods that allow sampling of extracellular factors, metabolites, and proteins in situ. Sampling of wound fluids in combination with proteomics and metabolomics is one of the promising approaches to gain comprehensive and time resolved data on effector molecules. Here, we describe an approach to sample metabolites by microdialysis and to extract proteins simultaneously by adsorption. With this approach it is possible (i) to collect, enrich, and purify proteins for a comprehensive proteome analysis; (ii) to detect more than 600 proteins in different defects including more than 100 secreted proteins, of which many proteins have previously been demonstrated to have diagnostic or predictive power for the wound healing state; and (iii) to combine continuous sampling of cytokines and metabolites and discontinuous sampling of larger proteins to gain complementary information of the same defect. PMID:25162036

  10. Metabolomics Approach Reveals Integrated Metabolic Network Associated with Serotonin Deficiency

    PubMed Central

    Weng, Rui; Shen, Sensen; Tian, Yonglu; Burton, Casey; Xu, Xinyuan; Liu, Yi; Chang, Cuilan; Bai, Yu; Liu, Huwei

    2015-01-01

    Serotonin is an important neurotransmitter that broadly participates in various biological processes. While serotonin deficiency has been associated with multiple pathological conditions such as depression, schizophrenia, Alzheimer’s disease and Parkinson’s disease, the serotonin-dependent mechanisms remain poorly understood. This study therefore aimed to identify novel biomarkers and metabolic pathways perturbed by serotonin deficiency using metabolomics approach in order to gain new metabolic insights into the serotonin deficiency-related molecular mechanisms. Serotonin deficiency was achieved through pharmacological inhibition of tryptophan hydroxylase (Tph) using p-chlorophenylalanine (pCPA) or genetic knockout of the neuronal specific Tph2 isoform. This dual approach improved specificity for the serotonin deficiency-associated biomarkers while minimizing nonspecific effects of pCPA treatment or Tph2 knockout (Tph2-/-). Non-targeted metabolic profiling and a targeted pCPA dose-response study identified 21 biomarkers in the pCPA-treated mice while 17 metabolites in the Tph2-/- mice were found to be significantly altered compared with the control mice. These newly identified biomarkers were associated with amino acid, energy, purine, lipid and gut microflora metabolisms. Oxidative stress was also found to be significantly increased in the serotonin deficient mice. These new biomarkers and the overall metabolic pathways may provide new understanding for the serotonin deficiency-associated mechanisms under multiple pathological states. PMID:26154191

  11. Metabolomic profiling and antioxidant activity of some Acacia species

    PubMed Central

    Abdel-Farid, I.B.; Sheded, M.G.; Mohamed, E.A.

    2014-01-01

    Metabolomic profiling of different parts (leaves, flowers and pods) of Acacia species (Acacia nilotica, Acacia seyal and Acacia laeta) was evaluated. The multivariate data analyses such as principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were used to differentiate the distribution of plant metabolites among different species or different organs of the same species. A.nilotica was characterized with a high content of saponins and A.seyal was characterized with high contents of proteins, phenolics, flavonoids and anthocyanins. A.laeta had a higher content of carbohydrates than A. nilotica and A. seyal. On the basis of these results, total antioxidant capacity, DPPH free radical scavenging activity and reducing power of the methanolic extracts of studied parts were evaluated. A.nilotica and A.seyal extracts showed less inhibitory concentration 50 (IC50) compared to A.laeta extracts which means that these two species have the strongest radical scavenging activity whereas A. laeta extracts have the lowest radical scavenging activity. A positive correlation between saponins and flavonoids with total antioxidant capacity and DPPH radical scavenging activity was observed. Based on these results, the potentiality of these plants as antioxidants was discussed. PMID:25313274

  12. Metabolomics profiling reveals novel markers for leukocyte telomere length.

    PubMed

    Zierer, Jonas; Kastenmüller, Gabi; Suhre, Karsten; Gieger, Christian; Codd, Veryan; Tsai, Pei-Chien; Bell, Jordana; Peters, Annette; Strauch, Konstantin; Schulz, Holger; Weidinger, Stephan; Mohney, Robert P; Samani, Nilesh J; Spector, Tim; Mangino, Massimo; Menni, Cristina

    2016-01-01

    Leukocyte telomere length (LTL) is considered one of the most predictive markers of biological aging. The aim of this study was to identify novel pathways regulating LTL using a metabolomics approach. To this end, we tested associations between 280 blood metabolites and LTL in 3511 females from TwinsUK and replicated our results in the KORA cohort. We furthermore tested significant metabolites for associations with several aging-related phenotypes, gene expression markers and epigenetic markers to investigate potential underlying pathways. Five metabolites were associated with LTL: Two lysolipids, 1-stearoylglycerophosphoinositol (P=1.6×10(-5)) and 1-palmitoylglycerophosphoinositol (P=1.6×10(-5)), were found to be negatively associated with LTL and positively associated with phospholipase A2 expression levels suggesting an involvement of fatty acid metabolism and particularly membrane composition in biological aging. Moreover, two gamma-glutamyl amino acids, gamma-glutamyltyrosine (P=2.5×10(-6)) and gamma-glutamylphenylalanine (P=1.7×10(-5)), were negatively correlated with LTL. Both are products of the glutathione cycle and markers for increased oxidative stress. Metabolites were also correlated with functional measures of aging, i.e. higher blood pressure and HDL cholesterol levels and poorer lung, liver and kidney function. Our results suggest an involvement of altered fatty acid metabolism and increased oxidative stress in human biological aging, reflected by LTL and age-related phenotypes of vital organ systems. PMID:26797767

  13. Metabolomics profiling reveals novel markers for leukocyte telomere length

    PubMed Central

    Zierer, Jonas; Kastenmüller, Gabi; Suhre, Karsten; Gieger, Christian; Codd, Veryan; Tsai, Pei-Chien; Bell, Jordana; Peters, Annette; Strauch, Konstantin; Schulz, Holger; Weidinger, Stephan; Mohney, Robert P.; Samani, Nilesh J.; Spector, Tim; Mangino, Massimo; Menni, Cristina

    2016-01-01

    Leukocyte telomere length (LTL) is considered one of the most predictive markers of biological aging. The aim of this study was to identify novel pathways regulating LTL using a metabolomics approach. To this end, we tested associations between 280 blood metabolites and LTL in 3511 females from TwinsUK and replicated our results in the KORA cohort. We furthermore tested significant metabolites for associations with several aging-related phenotypes, gene expression markers and epigenetic markers to investigate potential underlying pathways. Five metabolites were associated with LTL: Two lysolipids, 1-stearoylglycerophosphoinositol (P=1.6×10−5) and 1-palmitoylglycerophosphoinositol (P=1.6×10−5), were found to be negatively associated with LTL and positively associated with phospholipase A2 expression levels suggesting an involvement of fatty acid metabolism and particularly membrane composition in biological aging. Moreover, two gamma-glutamyl amino acids, gamma-glutamyltyrosine (P=2.5×10−6) and gamma-glutamylphenylalanine (P=1.7×10−5), were negatively correlated with LTL. Both are products of the glutathione cycle and markers for increased oxidative stress. Metabolites were also correlated with functional measures of aging, i.e. higher blood pressure and HDL cholesterol levels and poorer lung, liver and kidney function. Our results suggest an involvement of altered fatty acid metabolism and increased oxidative stress in human biological aging, reflected by LTL and age-related phenotypes of vital organ systems. PMID:26797767

  14. Metabolomic differentiation of nutritional stress in an aquatic invertebrate.

    PubMed

    Wagner, Nicole D; Lankadurai, Brian P; Simpson, Myrna J; Simpson, Andre J; Frost, Paul C

    2015-01-01

    Poor diet quality frequently constrains the growth and reproduction of primary consumers, altering their population dynamics, interactions in food webs, and contributions to ecosystem services such as nutrient cycling. The identification and measurement of an animal's nutritional state are thus central to studying the connections between diet and animal ecology. Here we show how the nutritional state of a freshwater invertebrate, Daphnia magna, can be determined by analyzing its endogenous metabolites using hydrogen nuclear magnetic resonance-based metabolomics. With a multivariate analysis, we observed the differentiation of the metabolite composition of animals grown under control conditions (good food and no environmental stress), raised on different diets (low quantity, nitrogen limited, and phosphorus limited), and exposed to two common environmental stressors (bacterial infection and salt stress). We identified 18 metabolites that were significantly different between control animals and at least one limiting food type or environmental stressor. The unique metabolite responses of animals caused by inadequate nutrition and environmental stress are reflective of dramatic and distinctive effects that each stressor has on animal metabolism. Our results suggest that dietary-specific induced changes in metabolite composition of animal consumers hold considerable promise as indicators of nutritional stress and will be invaluable to future studies of animal nutrition. PMID:25590592

  15. Analytical strategies to assess the functional metabolome of vitamin E.

    PubMed

    Torquato, Pierangelo; Ripa, Orsola; Giusepponi, Danilo; Galarini, Roberta; Bartolini, Desirée; Wallert, Maria; Pellegrino, Roberto; Cruciani, Gabriele; Lorkowski, Stefan; Birringer, Marc; Mazzini, Francesco; Galli, Francesco

    2016-05-30

    After more than 90 years from its discovery and thousands of papers published, the physiological roles of vitamin E (tocopherols and tocotrienols) are still not fully clarified. In the last few decades, the enzymatic metabolism of this vitamin has represented a stimulating subject of research. Its elucidation has opened up new horizons to the interpretation of the biological function of that class of molecules. The identification of specific properties for some of the physiological metabolites and the definition of advanced analytical techniques to assess the human metabolome of this vitamin in vivo, have paved the way to a series of hypotheses on the functional implications that this metabolism may have far beyond its catabolic role. The present review collects the available information on the most relevant analytical strategies employed to assess the status and metabolism of vitamin E in humans as well as in other model systems. A particular focus is dedicated to the analytical methods used to measure vitamin E metabolites, and particularly long-chain metabolites, in biological fluids and tissues. Preliminary information on a new LC-APCI-MS/MS method to measure these metabolites in human serum is reported. PMID:26947319

  16. Loss-of-function variants influence the human serum metabolome.

    PubMed

    Yu, Bing; Li, Alexander H; Metcalf, Ginger A; Muzny, Donna M; Morrison, Alanna C; White, Simon; Mosley, Thomas H; Gibbs, Richard A; Boerwinkle, Eric

    2016-08-01

    The metabolome is a collection of small molecules resulting from multiple cellular and biological processes that can act as biomarkers of disease, and African-Americans exhibit high levels of genetic diversity. Exome sequencing of a sample of deeply phenotyped African-Americans allowed us to analyze the effects of annotated loss-of-function (LoF) mutations on 308 serum metabolites measured by untargeted liquid and gas chromatography coupled with mass spectrometry. In an independent sample, we identified and replicated four genes harboring six LoF mutations that significantly affected five metabolites. These sites were related to a 19 to 45% difference in geometric mean metabolite levels, with an average effect size of 25%. We show that some of the affected metabolites are risk predictors or diagnostic biomarkers of disease and, using the principle of Mendelian randomization, are in the causal pathway of disease. For example, LoF mutations in SLCO1B1 elevate the levels of hexadecanedioate, a fatty acid significantly associated with increased blood pressure levels and risk of incident heart failure in both African-Americans and an independent sample of European-Americans. We show that SLCO1B1 LoF mutations significantly increase the risk of incident heart failure, thus implicating the metabolite in the causal pathway of disease. These results reveal new avenues into gene function and the understanding of disease etiology by integrating -omic technologies into a deeply phenotyped population study. PMID:27602404

  17. Loss-of-function variants influence the human serum metabolome

    PubMed Central

    Yu, Bing; Li, Alexander H.; Metcalf, Ginger A.; Muzny, Donna M.; Morrison, Alanna C.; White, Simon; Mosley, Thomas H.; Gibbs, Richard A.; Boerwinkle, Eric

    2016-01-01

    The metabolome is a collection of small molecules resulting from multiple cellular and biological processes that can act as biomarkers of disease, and African-Americans exhibit high levels of genetic diversity. Exome sequencing of a sample of deeply phenotyped African-Americans allowed us to analyze the effects of annotated loss-of-function (LoF) mutations on 308 serum metabolites measured by untargeted liquid and gas chromatography coupled with mass spectrometry. In an independent sample, we identified and replicated four genes harboring six LoF mutations that significantly affected five metabolites. These sites were related to a 19 to 45% difference in geometric mean metabolite levels, with an average effect size of 25%. We show that some of the affected metabolites are risk predictors or diagnostic biomarkers of disease and, using the principle of Mendelian randomization, are in the causal pathway of disease. For example, LoF mutations in SLCO1B1 elevate the levels of hexadecanedioate, a fatty acid significantly associated with increased blood pressure levels and risk of incident heart failure in both African-Americans and an independent sample of European-Americans. We show that SLCO1B1 LoF mutations significantly increase the risk of incident heart failure, thus implicating the metabolite in the causal pathway of disease. These results reveal new avenues into gene function and the understanding of disease etiology by integrating -omic technologies into a deeply phenotyped population study. PMID:27602404

  18. Sum of the Parts: Mass Spectrometry-Based Metabolomics

    PubMed Central

    Milne, Stephen B.; Mathews, Thomas P.; Myers, David S.; Ivanova, Pavlina T.; Brown, H. Alex

    2013-01-01

    Metabolomics is a rapidly growing field of research used in the identification and quantification of the small molecule metabolites within an organism, thereby providing insights into cell metabolism and bioenergetics as well as processes important in clinical medicine, such as disposition of pharmaceutical compounds. It offers comprehensive information on thousands of low molecular weight compounds (<1500 Da) that represent a wide range of pathways and intermediary metabolism. Due to its vast expansion in the last two decades mass spectrometry has become an indispensable tool in “omic” analyses. The use of different ionization techniques such as the more traditional electrospray (ESI) and matrix-assisted laser desorption (MALDI), as well as recently popular desorption electrospray ionization (DESI), has allowed the analysis of a wide range of biomolecules (e.g. peptides, proteins, lipids and sugars), and their imaging and analysis in the original sample environment in a workup free fashion. An overview of the current state of the methodology is given, as well as examples of application. PMID:23442130

  19. Novel biomarkers for pre-diabetes identified by metabolomics

    PubMed Central

    Wang-Sattler, Rui; Yu, Zhonghao; Herder, Christian; Messias, Ana C; Floegel, Anna; He, Ying; Heim, Katharina; Campillos, Monica; Holzapfel, Christina; Thorand, Barbara; Grallert, Harald; Xu, Tao; Bader, Erik; Huth, Cornelia; Mittelstrass, Kirstin; Döring, Angela; Meisinger, Christa; Gieger, Christian; Prehn, Cornelia; Roemisch-Margl, Werner; Carstensen, Maren; Xie, Lu; Yamanaka-Okumura, Hisami; Xing, Guihong; Ceglarek, Uta; Thiery, Joachim; Giani, Guido; Lickert, Heiko; Lin, Xu; Li, Yixue; Boeing, Heiner; Joost, Hans-Georg; de Angelis, Martin Hrabé; Rathmann, Wolfgang; Suhre, Karsten; Prokisch, Holger; Peters, Annette; Meitinger, Thomas; Roden, Michael; Wichmann, H-Erich; Pischon, Tobias; Adamski, Jerzy; Illig, Thomas

    2012-01-01

    Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4 × 10−4 to 2.1 × 10−13. Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite–protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D. PMID:23010998

  20. 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

  1. Metabolomic screening and identification of bioactivation pathways of ritonavir

    PubMed Central

    Li, Feng; Lu, Jie; Ma, Xiaochao

    2011-01-01

    Ritonavir-boosted protease inhibitor regimens are widely used for HIV chemotherapy. However, ritonavir causes multiple side effects, and the mechanisms are not fully understood. The current study was designed to explore the metabolic pathways of ritonavir that may be related to its toxicity. Metabolomic analysis screened out 26 ritonavir metabolites in mice, and half of them are novel. These novel ritonavir metabolites include two glycine conjugated, two N-acetylcysteine conjugated and three ring-open products. Accompanied with the generation of ritonavir ring-open metabolites, the formation of methanethioamide and 2-methylpropanethioamide were expected. Based upon the structures of these novel metabolites, five bioactivation pathways are proposed, which may be associated with sulfation and epoxidation. By using Cyp3a-null mice, we confirmed that CYP3A is involved in four pathways of RTV bioactivation. In addition, all these five bioactivation pathways were recapitulated in the incubation of ritonavir in human liver microsomes. Further studies are suggested to determine the role of CYP3A and these bioactivation pathways in ritonavir toxicity. PMID:22040299

  2. An investigation of boron toxicity in barley using metabolomics.

    PubMed

    Roessner, Ute; Patterson, John H; Forbes, Megan G; Fincher, Geoffrey B; Langridge, Peter; Bacic, Anthony

    2006-11-01

    Boron (B) is an essential micronutrient that affects plant growth at either deficient or toxic concentrations in soil. The aim of this work was to investigate the adaptation of barley (Hordeum vulgare) plants to toxic B levels and to increase our understanding of B toxicity tolerance mechanisms. We used a metabolomics approach to compare metabolite profiles in root and leaf tissues of an intolerant, commercial cultivar (cv Clipper) and a B-tolerant Algerian landrace (cv Sahara). After exposure to elevated B (200 and 1,000 microM), the number and amplitude of metabolite changes in roots was greater in Clipper than in Sahara. In contrast, leaf metabolites of both cultivars only responded following 1,000 microM treatment, at which B toxicity symptoms (necrosis) were visible. In addition, metabolite levels were dramatically altered in the tips of leaves of the sensitive cultivar Clipper after growth in 1,000 microM B compared to those of Sahara. This correlates with a gradual accumulation of B from leaf base to tip in B-intolerant cultivars. Overall, there were always greater differences between tissue types (roots and leaves) than between the two cultivars. This work has provided insights into metabolic differences of two genetically distinct barley cultivars and information about how they respond metabolically to increasing B levels. PMID:16998089

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

    PubMed Central

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

    2015-01-01

    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. PMID:25754258

  4. Metabolomics connects aberrant bioenergetic, transmethylation, and gut microbiota in sarcoidosis

    PubMed Central

    Geamanu, Andreea; Gupta, Smiti V.; Bauerfeld, Christian

    2016-01-01

    Sarcoidosis is a systemic granulomatous disease of unknown etiology. Granulomatous inflammation in sarcoidosis may affect multiple organs, including the lungs, skin, CNS, and the eyes, leading to severe morbidity and mortality. The underlying mechanisms for sustained inflammation in sarcoidosis are unknown. We hypothesized that metabolic changes play a critical role in perpetuation of inflammation in sarcoidosis. 1H nuclear magnetic resonance (NMR)-based untargeted metabolomic analysis was used to identify circulating molecules in serum to discriminate sarcoidosis patients from healthy controls. Principal component analyses (PCA) were performed to identify different metabolic markers and explore the changes of associated biochemical pathways. Using Chenomx 7.6 NMR Suite software, we identified and quantified metabolites responsible for such separation in the PCA models. Quantitative analysis showed that the levels of metabolites, such as 3-hydroxybutyrate, acetoacetate, carnitine, cystine, homocysteine, pyruvate, and trimethylamine N-oxide were significantly increased in sarcoidosis patients. Interestingly, succinate, a major intermediate metabolite involved in the tricyclic acid cycle was significantly decreased in sarcoidosis patients. Application of integrative pathway analyses identified deregulation of butanoate, ketone bodies, citric cycle metabolisms, and transmethylation. This may be used for development of new drugs or nutritional modification. PMID:27489531

  5. 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

  6. Gas chromatography-mass spectrometry (GC-MS)-based metabolomics.

    PubMed

    Garcia, Antonia; Barbas, Coral

    2011-01-01

    Metabolic fingerprinting, the main tool in metabolomics, is a non-targeted methodology where all detectable peaks (or signals), including those from unknown analytes, are considered to establish sample classification. After pattern comparison, those signals changing in response to a specific situation under investigation are identified to gain biological insight. For this purpose, gas chromatographymass spectrometry (GC-MS) has a drawback in that only volatile compounds or compounds that can be made volatile after derivatization can be analysed, and derivatization often requires extensive sample treatment. However, once the analysis is focused on low molecular weight metabolites, GC-MS is highly efficient, sensitive, and reproducible. Moreover, it is quantitative, and its compound identification capabilities are superior to other separation techniques because GC-MS instruments obtain mass spectra with reproducible fragmentation patterns, which allow for the creation of public databases. This chapter describes well-established protocols for metabolic fingerprinting (i.e. the comprehensive analysis of small molecules) in plasma and urine using GC-MS. Guidelines will also be provided regarding subsequent data pre-treatment, pattern recognition, and marker identification. PMID:21207291

  7. A metabolomics approach to characterise and identify various Mycobacterium species.

    PubMed

    Olivier, Ilse; Loots, Du Toit

    2012-03-01

    We investigated the potential use of gas chromatography mass spectrometry (GC-MS), in combination with multivariate statistical data processing, to build a model for the classification of various tuberculosis (TB) causing, and non-TB Mycobacterium species, on the basis of their characteristic metabolite profiles. A modified Bligh-Dyer extraction procedure was used to extract lipid components from Mycobacterium tuberculosis, Mycobacterium avium, Mycobacterium bovis, and Mycobacterium kansasii cultures. Principle component analyses (PCA) of the GC-MS generated data showed a clear differentiation between all the Mycobacterium species tested. Subsequently, the 12 compounds best describing the variation between the sample groups were identified as potential metabolite markers, using PCA and partial least-squares discriminant analysis (PLS-DA). These metabolite markers were then used to build a discriminant classification model based on Bayes' theorem, in conjunction with multivariate kernel density estimation. This model subsequently correctly classified 2 "unknown" samples for each of the Mycobacterium species analysed, with probabilities ranging from 72 to 100%. Furthermore, Mycobacterium species classification could be achieved in less than 16 h, and the detection limit for this approach was 1×10(3)bacteriamL(-1). This study proves the capacity of a GC-MS, metabolomics pattern recognition approach for its possible use in TB diagnostics and disease characterisation. PMID:22301369

  8. Metabolomics – A novel window into inflammatory disease

    PubMed Central

    Fitzpatrick, Martin; Young, Stephen P

    2015-01-01

    Inflammation is an important component of normal responses to infection and injury. However, chronic activation of the immune system, perhaps due to aberrant responses to normal stimuli, can lead to the establishment of a chronic inflammatory state. Such inflammatory conditions are often debilitating, and are associated with a number of important co-morbidities including cardiovascular disease. Resting non-proliferative tissues have distinctive metabolic activities and requirements, which differ considerably from those in infiltrating immune cells, which are undergoing proliferation and differentiation. Immune responses in tissues may therefore be modulated by the relative abundance of substrates in the inflamed site. In turn immune cell activity can feed back and affect metabolic behaviour of the tissues, as most clearly demonstrated in cachexia - the loss of cellular mass driven by tumour necrosis factor-alpha (TNF-α) a key mediator of the inflammatory response. Here we discuss the potential for metabolomic analysis to clarify the interactions between inflammation and metabolic changes underlying many diseases. We suggest that an increased understanding of the interaction between inflammation and cellular metabolism, energy substrate use, tissue breakdown markers, the microbiome and drug metabolites, may provide novel insight into the regulation of inflammatory diseases. PMID:23348753

  9. Metabolomics Approach Reveals Integrated Metabolic Network Associated with Serotonin Deficiency

    NASA Astrophysics Data System (ADS)

    Weng, Rui; Shen, Sensen; Tian, Yonglu; Burton, Casey; Xu, Xinyuan; Liu, Yi; Chang, Cuilan; Bai, Yu; Liu, Huwei

    2015-07-01

    Serotonin is an important neurotransmitter that broadly participates in various biological processes. While serotonin deficiency has been associated with multiple pathological conditions such as depression, schizophrenia, Alzheimer’s disease and Parkinson’s disease, the serotonin-dependent mechanisms remain poorly understood. This study therefore aimed to identify novel biomarkers and metabolic pathways perturbed by serotonin deficiency using metabolomics approach in order to gain new metabolic insights into the serotonin deficiency-related molecular mechanisms. Serotonin deficiency was achieved through pharmacological inhibition of tryptophan hydroxylase (Tph) using p-chlorophenylalanine (pCPA) or genetic knockout of the neuronal specific Tph2 isoform. This dual approach improved specificity for the serotonin deficiency-associated biomarkers while minimizing nonspecific effects of pCPA treatment or Tph2 knockout (Tph2-/-). Non-targeted metabolic profiling and a targeted pCPA dose-response study identified 21 biomarkers in the pCPA-treated mice while 17 metabolites in the Tph2-/- mice were found to be significantly altered compared with the control mice. These newly identified biomarkers were associated with amino acid, energy, purine, lipid and gut microflora metabolisms. Oxidative stress was also found to be significantly increased in the serotonin deficient mice. These new biomarkers and the overall metabolic pathways may provide new understanding for the serotonin deficiency-associated mechanisms under multiple pathological states.

  10. Low-Level Environmental Phthalate Exposure Associates with Urine Metabolome Alteration in a Chinese Male Cohort.

    PubMed

    Zhang, Jie; Liu, Liangpo; Wang, Xiaofei; Huang, Qingyu; Tian, Meiping; Shen, Heqing

    2016-06-01

    The general population is exposed to phthalates through various sources and routes. Integration of omics data and epidemiological data is a key step toward directly linking phthalate biomonitoring data with biological response. Urine metabolomics is a powerful tool to identify exposure biomarkers and delineate the modes of action of environmental stressors. The objectives of this study are to investigate the association between low-level environmental phthalate exposure and urine metabolome alteration in male population, and to unveil the metabolic pathways involved in the mechanisms of phthalate toxicity. In this retrospective cross-sectional study, we studied the urine metabolomic profiles of 364 male subjects exposed to low-level environmental phthalates. Di(2-ethylhexyl) phthalate (DEHP) and dibutyl phthalate (DBP) are the most widely used phthalates. ∑DEHP and MBP (the major metabolite of DBP) were associated with significant alteration of global urine metabolome in the male population. We observed significant increase in the levels of acetylneuraminic acid, carnitine C8:1, carnitine C18:0, cystine, phenylglycine, phenylpyruvic acid and glutamylphenylalanine; and meanwhile, decrease in the levels of carnitine C16:2, diacetylspermine, alanine, taurine, tryptophan, ornithine, methylglutaconic acid, hydroxyl-PEG2 and keto-PGE2 in high exposure group. The observations indicated that low-level environmental phthalate exposure associated with increased oxidative stress and fatty acid oxidation and decreased prostaglandin metabolism. Urea cycle, tryptophan and phenylalanine metabolism disruption was also observed. The urine metabolome disruption effects associated with ∑DEHP and MBP were similar, but not identical. The multibiomarker models presented AUC values of 0.845 and 0.834 for ∑DEHP and MBP, respectively. The predictive accuracy rates of established models were 81% for ΣDEHP and 73% for MBP. Our results suggest that low-level environmental phthalate

  11. The effects of age and dietary restriction on the tissue-specific metabolome of Drosophila

    PubMed Central

    Laye, Matthew J; Tran, ViLinh; Jones, Dean P; Kapahi, Pankaj; Promislow, Daniel E L

    2015-01-01

    Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age-related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease-associated phenotypes. Here, we use high-resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient-rich ad libitum (AL) or nutrient-restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age-related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age. PMID:26085309

  12. TISSUE METABOLOMICS OF HEPATOCELLULAR CARCINOMA: TUMOR ENERGY METABOLISM AND THE ROLE OF TRANSCRIPTOMIC CLASSIFICATION

    PubMed Central

    Beyoğlu, Diren; Imbeaud, Sandrine; Maurhofer, Olivier; Bioulac-Sage, Paulette; Zucman-Rossi, Jessica; Dufour, Jean-François; Idle, Jeffrey R.

    2013-01-01

    Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up- and downregulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding non-tumor liver tissues from the same patients was investigated by gas chromatography-mass spectrometry (GCMS) based metabolomics. HCC was characterized by approximately two-fold depletion of glucose, glycerol 3- and 2-phosphate, malate, alanine, myo-inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a four-fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3-phosphate, malate, myo-inositol or stearic acid tissue concentrations were found, suggesting that the Wnt/β-catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid, suggesting that the high serum α-fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism. Conclusion Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process. PMID:23463346

  13. Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease.

    PubMed

    Quinn, Robert A; Lim, Yan Wei; Mak, Tytus D; Whiteson, Katrine; Furlan, Mike; Conrad, Douglas; Rohwer, Forest; Dorrestein, Pieter

    2016-01-01

    Background. Cystic fibrosis (CF) is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE) that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples) to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable). Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF) and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events) as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset. PMID:27602256

  14. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies.

    PubMed

    Lima, Ana Rita; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, Paula

    2016-08-01

    Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection. PMID:27567960

  15. Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease

    PubMed Central

    Lim, Yan Wei; Mak, Tytus D.; Whiteson, Katrine; Conrad, Douglas; Rohwer, Forest; Dorrestein, Pieter

    2016-01-01

    Background. Cystic fibrosis (CF) is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE) that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples) to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable). Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF) and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events) as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset. PMID:27602256

  16. LC-MS-Based Metabolomic Investigation of Chemopreventive Phytochemical-Elicited Metabolic Events.

    PubMed

    Wang, Lei; Yao, Dan; Chen, Chi

    2016-01-01

    Phytochemicals are under intensive investigation for their potential use as chemopreventive agents in blocking or suppressing carcinogenesis. Metabolic interactions between phytochemical and biological system play an important role in determining the efficacy and toxicity of chemopreventive phytochemicals. However, complexities of phytochemical biotransformation and intermediary metabolism pose challenges for studying phytochemical-elicited metabolic events. Metabolomics has become a highly effective technical platform to detect subtle changes in a complex metabolic system. Here, using green tea polyphenols as an example, we describe a workflow of LC-MS-based metabolomics study, covering the procedures and techniques in sample collection, preparation, LC-MS analysis, data analysis, and interpretation. PMID:26608291

  17. What Have Mass Spectrometry-Based Proteomics and Metabolomics (Not) Taught Us about Psychiatric Disorders?

    PubMed Central

    Turck, Christoph W.; Filiou, Michaela D.

    2015-01-01

    Understanding the molecular causes and finding appropriate therapies for psychiatric disorders are challenging tasks for research; -omics technologies are used to elucidate the molecular mechanisms underlying brain dysfunction in a hypothesis-free manner. In this review, we will focus on mass spectrometry-based proteomics and metabolomics and address how these approaches have contributed to our understanding of psychiatric disorders. Specifically, we will discuss what we have learned from mass spectrometry-based proteomics and metabolomics studies in rodent models and human cohorts, outline current limitations and discuss the potential of these methods for future applications in psychiatry.

  18. AB145. Comparative metabolomic analyses in term and preterm Malaysian infants

    PubMed Central

    Muthukanoo, Renuga Devi; Loke, Mun-Fai; Choo, Yao-Mun; Kamar, Azanna Ahmad; Ishak, Mohd Taufik; Vadivelu, Jamuna; Thong, Meow-Keong

    2015-01-01

    Background Metabolomics, which involves profiling and comprehensive analysis of cellular metabolites, is a promising new tool for clinical diagnostic in neonatology. Urine is considered to be the most predictive of phenotypic outcome in neonatal conditions. Management of sick neonates could be improved with the availability of information on perinatal/neonatal maturational processes and their metabolic background. This study was carried out to compare metabolites identified in the urine sample obtained from term and preterm infants from the postnatal and neonatal intensive care unit (NICU) of University of Malaya Medical Centre. Methods Experiments were carried out to compare the metabolomic profiles between (I) collection of urine using urine bag and cotton ball from preterm infants, (II) urine collection at different time-points from preterm infants, (III) preterm and term infants, (IV) different birth weights of preterm infants and (V) between preterms with and without respiratory distress syndrome (RDS). Urine samples were stored at -40 °C freezer until analysis. Metabolites were extracted using cold methanol extraction. The extracted samples were analyzed on an Agilent 6540 Accurate-Mass LC/QTOF mass spectrometer. Qualitative analysis was done using MassHunter Professional Profiler. Results In relation to principle component analysis (PCA) plot, there were no observable differences between collection of urine using urine bag and cotton ball. Thus, urine samples were collected using cotton ball for all subsequent experiments. There were also no significant differences between the metabolomic profiles of week 1 and week 2 preterm infants. It was found that 47 metabolites and two biological pathways were found to differ significantly between preterm and term infants (P value <0.01). On the other hand, metabolomic profiles between preterm infants <1 kg and those >1 kg differed in 17 metabolites (P value <0.01). Importantly, 110 metabolites and 39 biological

  19. Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops

    PubMed Central

    Catchpole, Gareth S.; Beckmann, Manfred; Enot, David P.; Mondhe, Madhav; Zywicki, Britta; Taylor, Janet; Hardy, Nigel; Smith, Aileen; King, Ross D.; Kell, Douglas B.; Fiehn, Oliver; Draper, John

    2005-01-01

    There is current debate whether genetically modified (GM) plants might contain unexpected, potentially undesirable changes in overall metabolite composition. However, appropriate analytical technology and acceptable metrics of compositional similarity require development. We describe a comprehensive comparison of total metabolites in field-grown GM and conventional potato tubers using a hierarchical approach initiating with rapid metabolome “fingerprinting” to guide more detailed profiling of metabolites where significant differences are suspected. Central to this strategy are data analysis procedures able to generate validated, reproducible metrics of comparison from complex metabolome data. We show that, apart from targeted changes, these GM potatoes in this study appear substantially equivalent to traditional cultivars. PMID:16186495

  20. NMR-based metabolomics of prostate cancer: a protagonist in clinical diagnostics.

    PubMed

    Kumar, Deepak; Gupta, Ashish; Nath, Kavindra

    2016-06-01

    Advances in the application of NMR spectroscopy-based metabolomic profiling of prostate cancer comprises a potential tactic for understanding the impaired biochemical pathways arising due to a disease evolvement and progression. This technique involves qualitative and quantitative estimation of plethora of small molecular weight metabolites of body fluids or tissues using state-of-the-art chemometric methods delivering an important platform for translational research from basic to clinical, to reveal the pathophysiological snapshot in a single step. This review summarizes the present arrays and recent advancements in NMR-based metabolomics and a glimpse of currently used medical imaging tactics, with their role in clinical diagnosis of prostate cancer. PMID:26959614

  1. Linalool is a PPARα ligand that reduces plasma TG levels and rewires the hepatic transcriptome and plasma metabolome[S

    PubMed Central

    Jun, Hee-jin; Lee, Ji Hae; Kim, Jiyoung; Jia, Yaoyao; Kim, Kyoung Heon; Hwang, Kwang Yeon; Yun, Eun Ju; Do, Kyoung-Rok; Lee, Sung-Joon

    2014-01-01

    We investigated the hypotriglyceridemic mechanism of action of linalool, an aromatic monoterpene present in teas and fragrant herbs. Reporter gene and time-resolved fluorescence resonance energy transfer assays demonstrated that linalool is a direct ligand of PPARα. Linalool stimulation reduced cellular lipid accumulation regulating PPARα-responsive genes and significantly induced FA oxidation, and its effects were markedly attenuated by silencing PPARα expression. In mice, the oral administration of linalool for 3 weeks reduced plasma TG concentrations in Western-diet-fed C57BL/6J mice (31%, P < 0.05) and human apo E2 mice (50%, P < 0.05) and regulated hepatic PPARα target genes. However, no such effects were seen in PPARα-deficient mice. Transcriptome profiling revealed that linalool stimulation rewired global gene expression in lipid-loaded hepatocytes and that the effects of 1 mM linalool were comparable to those of 0.1 mM fenofibrate. Metabolomic analysis of the mouse plasma revealed that the global metabolite profiles were significantly distinguishable between linalool-fed mice and controls. Notably, the concentrations of saturated FAs were significantly reduced in linalool-fed mice. These findings suggest that the appropriate intake of a natural aromatic compound could exert beneficial metabolic effects by regulating a cellular nutrient sensor. PMID:24752549

  2. Understanding Aquatic Rhizosphere Processes Through Metabolomics and Metagenomics Approach

    NASA Astrophysics Data System (ADS)

    Lee, Yong Jian; Mynampati, Kalyan; Drautz, Daniela; Arumugam, Krithika; Williams, Rohan; Schuster, Stephan; Kjelleberg, Staffan; Swarup, Sanjay

    2013-04-01

    The aquatic rhizosphere is a region around the roots of aquatic plants. Many studies focusing on terrestrial rhizosphere have led to a good understanding of the interactions between the roots, its exudates and its associated rhizobacteria. The rhizosphere of free-floating roots, however, is a different habitat that poses several additional challenges, including rapid diffusion rates of signals and nutrient molecules, which are further influenced by the hydrodynamic forces. These can lead to rapid diffusion and complicates the studying of diffusible factors from both plant and/or rhizobacterial origins. These plant systems are being increasingly used for self purification of water bodies to provide sustainable solution. A better understanding of these processes will help in improving their performance for ecological engineering of freshwater systems. The same principles can also be used to improve the yield of hydroponic cultures. Novel toolsets and approaches are needed to investigate the processes occurring in the aquatic rhizosphere. We are interested in understanding the interaction between root exudates and the complex microbial communities that are associated with the roots, using a systems biology approach involving metabolomics and metagenomics. With this aim, we have developed a RhizoFlowCell (RFC) system that provides a controlled study of aquatic plants, observed the root biofilms, collect root exudates and subject the rhizosphere system to changes in various chemical or physical perturbations. As proof of concept, we have used RFC to test the response of root exudation patterns of Pandanus amaryllifolius after exposure to the pollutant naphthalene. Complexity of root exudates in the aquatic rhizosphere was captured using this device and analysed using LC-qTOF-MS. The highly complex metabolomic profile allowed us to study the dynamics of the response of roots to varying levels of naphthalene. The metabolic profile changed within 5mins after spiking with

  3. The Human Milk Metabolome Reveals Diverse Oligosaccharide Profiles123

    PubMed Central

    Smilowitz, Jennifer T.; O’Sullivan, Aifric; Barile, Daniela; German, J. Bruce; Lönnerdal, Bo; Slupsky, Carolyn M.

    2013-01-01

    Breast milk delivers nutrition and protection to the developing infant. There has been considerable research on the high-molecular-weight milk components; however, low-molecular-weight metabolites have received less attention. To determine the effect of maternal phenotype and diet on the human milk metabolome, milk collected at day 90 postpartum from 52 healthy women was analyzed by using proton nuclear magnetic resonance spectroscopy. Sixty-five milk metabolites were quantified (mono-, di-, and oligosaccharides; amino acids and derivatives; energy metabolites; fatty acids and associated metabolites; vitamins, nucleotides, and derivatives; and others). The biological variation, represented as the percentage CV of each metabolite, varied widely (4–120%), with several metabolites having low variation (<20%), including lactose, urea, glutamate, myo-inositol, and creatinine. Principal components analysis identified 2 clear groups of participants who were differentiable on the basis of milk oligosaccharide concentration and who were classified as secretors or nonsecretors of fucosyltransferase 2 (FUT2) gene products according to the concentration of 2′-fucosyllactose, lactodifucotetraose, and lacto-N-fucopentaose I. Exploration of the interrelations between the milk sugars by using Spearman rank correlations revealed significant positive and negative associations, including positive correlations between fucose and products of the FUT2 gene and negative correlations between fucose and products of the fucosyltransferase 3 (FUT3) gene. The total concentration of milk oligosaccharides was conserved among participants (%CV = 18%), suggesting tight regulation of total oligosaccharide production; however, concentrations of specific oligosaccharides varied widely between participants (%CV = 30.4–84.3%). The variability in certain milk metabolites suggests possible roles in infant or infant gut microbial development. This trial was registered at clinicaltrials.gov as NCT

  4. Reconstruction of food webs in biological soil crusts using metabolomics.

    NASA Astrophysics Data System (ADS)

    Baran, Richard; Brodie, Eoin L.; Mayberry-Lewis, Jazmine; Nunes Da Rocha, Ulisses; Bowen, Benjamin P.; Karaoz, Ulas; Cadillo-Quiroz, Hinsby; Garcia-Pichel, Ferran; Northen, Trent R.

    2015-04-01

    Biological soil crusts (BSCs) are communities of organisms inhabiting the upper layer of soil in arid environments. BSCs persist in a dessicated dormant state for extended periods of time and experience pulsed periods of activity facilitated by infrequent rainfall. Microcoleus vaginatus, a non-diazotrophic filamentous cyanobacterium, is the key primary producer in BSCs in the Colorado Plateau and is an early pioneer in colonizing arid environments. Over decades, BSCs proceed through developmental stages with increasing complexity of constituent microorganisms and macroscopic properties. Metabolic interactions among BSC microorganisms probably play a key role in determining the community dynamics and cycling of carbon and nitrogen. However, these metabolic interactions have not been studied systematically. Towards this goal, exometabolomic analysis was performed using liquid chromatography coupled to tandem mass spectrometry on biological soil crust pore water and spent media of key soil bacterial isolates. Comparison of spent vs. fresh media was used to determine uptake or release of metabolites by specific microbes. To link pore water experiments with isolate studies, metabolite extracts of authentic soil were used as supplements for isolate exometabolomic profiling. Our soil metabolomics methods detected hundreds of metabolites from soils including many novel compounds. Overall, Microcoleus vaginatus was found to release and utilize a broad range of metabolites. Many of these metabolites were also taken up by heterotrophs but there were surprisingly few metabolites uptaken by all isolates. This points to a competition for a small set of central metabolites and specialization of individual heterotrophs towards a diverse pool of available organic nutrients. Overall, these data suggest that understanding the substrate specialization of biological soil crust bacteria can help link community structure to nutrient cycling.

  5. Thermal Degradation of Small Molecules: A Global Metabolomic Investigation

    PubMed Central

    2015-01-01

    Thermal processes are widely used in small molecule chemical analysis and metabolomics for derivatization, vaporization, chromatography, and ionization, especially in gas chromatography mass spectrometry (GC/MS). In this study the effect of heating was examined on a set of 64 small molecule standards and, separately, on human plasma metabolite extracts. The samples, either derivatized or underivatized, were heated at three different temperatures (60, 100, and 250 °C) at different exposure times (30 s, 60 s, and 300 s). All the samples were analyzed by liquid chromatography coupled to electrospray ionization mass spectrometry (LC/MS) and the data processed by XCMS Online (xcmsonline.scripps.edu). The results showed that heating at an elevated temperature of 100 °C had an appreciable effect on both the underivatized and derivatized molecules, and heating at 250 °C created substantial changes in the profile. For example, over 40% of the molecular peaks were altered in the plasma metabolite analysis after heating (250 °C, 300s) with a significant formation of degradation and transformation products. The analysis of 64 small molecule standards validated the temperature-induced changes observed on the plasma metabolites, where most of the small molecules degraded at elevated temperatures even after minimal exposure times (30 s). For example, tri- and diorganophosphates (e.g., adenosine triphosphate and adenosine diphosphate) were readily degraded into a mono-organophosphate (e.g., adenosine monophosphate) during heating. Nucleosides and nucleotides (e.g., inosine and inosine monophosphate) were also found to be transformed into purine derivatives (e.g., hypoxanthine). A newly formed transformation product, oleoyl ethyl amide, was identified in both the underivatized and derivatized forms of the plasma extracts and small molecule standard mixture, and was likely generated from oleic acid. Overall these analyses show that small molecules and metabolites undergo

  6. Proteomics, metabolomics, and ionomics perspectives of salinity tolerance in halophytes.

    PubMed

    Kumari, Asha; Das, Paromita; Parida, Asish Kumar; Agarwal, Pradeep K

    2015-01-01

    Halophytes are plants which naturally survive in saline environment. They account for ∼1% of the total flora of the world. They include both dicots and monocots and are distributed mainly in arid, semi-arid inlands and saline wet lands along the tropical and sub-tropical coasts. Salinity tolerance in halophytes depends on a set of ecological and physiological characteristics that allow them to grow and flourish in high saline conditions. The ability of halophytes to tolerate high salt is determined by the effective coordination between various physiological processes, metabolic pathways and protein or gene networks responsible for delivering salinity tolerance. The salinity responsive proteins belong to diverse functional classes such as photosynthesis, redox homeostasis; stress/defense, carbohydrate and energy metabolism, protein metabolism, signal transduction and membrane transport. The important metabolites which are involved in salt tolerance of halophytes are proline and proline analog (4-hydroxy-N-methyl proline), glycine betaine, pinitol, myo-inositol, mannitol, sorbitol, O-methylmucoinositol, and polyamines. In halophytes, the synthesis of specific proteins and osmotically active metabolites control ion and water flux and support scavenging of oxygen radicals under salt stress condition. The present review summarizes the salt tolerance mechanisms of halophytes by elucidating the recent studies that have focused on proteomic, metabolomic, and ionomic aspects of various halophytes in response to salinity. By integrating the information from halophytes and its comparison with glycophytes could give an overview of salt tolerance mechanisms in halophytes, thus laying down the pavement for development of salt tolerant crop plants through genetic modification and effective breeding strategies. PMID:26284080

  7. Metabolomic markers for intestinal ischemia in a mouse model

    PubMed Central

    Fahrner, René; Beyoğlu, Diren; Beldi, Guido; Idle, Jeffrey R.

    2013-01-01

    Background Diagnosis of intestinal ischemia remains a clinical challenge. The aim of the present study was to use a metabolomic protocol to identify upregulated and downregulated small molecules (Mr < 500) in the serum of mice with intestinal ischemia. Such molecules could have clinical utility when evaluated as biomarkers in human studies. Methods A mouse model for intestinal ischemia was established and validated using histology and serum tumor necrosis factor α concentrations. A second mouse model of peritoneal sepsis was used as a positive control. Serial serum samples were collected from these and from sham-operated animals. Sera were analyzed by gas chromatography–mass spectrometry for 40 small molecules as their trimethylsilyl and O-methyloxime derivatives. Peak areas were normalized against an internal standard and resultant peak area ratios subjected to multivariate data analysis using unsupervised principal components analysis and supervised orthogonal projection to latent structures–discriminant analysis. Upregulated and downregulated serum molecules were identified from their correlation to the orthogonal projection to latent structures–discriminant analysis model. Results Three highly significantly upregulated (fold-change) serum molecules in intestinal ischemia were inorganic phosphate (2.4), urea (4.3), and threonic acid (2.9). Five highly significantly downregulated (fold-change) serum molecules were stearic acid (1.7), arabinose (2.7), xylose (1.6), glucose (1.4), and ribose (2.2). Lactic acid remained unchanged in intestinal ischemia. Conclusions Distinct molecular changes are reported here for the first time in intestinal ischemia. They reveal impairments of gut microbiota metabolism, intestinal absorption, and renal function, together with increased oxidative stress. In contrast to other reports, lactic acid was not significantly changed. These molecular signatures may now be evaluated in clinical studies. PMID:22947700

  8. Proteomics, metabolomics, and ionomics perspectives of salinity tolerance in halophytes

    PubMed Central

    Kumari, Asha; Das, Paromita; Parida, Asish Kumar; Agarwal, Pradeep K.

    2015-01-01

    Halophytes are plants which naturally survive in saline environment. They account for ∼1% of the total flora of the world. They include both dicots and monocots and are distributed mainly in arid, semi-arid inlands and saline wet lands along the tropical and sub-tropical coasts. Salinity tolerance in halophytes depends on a set of ecological and physiological characteristics that allow them to grow and flourish in high saline conditions. The ability of halophytes to tolerate high salt is determined by the effective coordination between various physiological processes, metabolic pathways and protein or gene networks responsible for delivering salinity tolerance. The salinity responsive proteins belong to diverse functional classes such as photosynthesis, redox homeostasis; stress/defense, carbohydrate and energy metabolism, protein metabolism, signal transduction and membrane transport. The important metabolites which are involved in salt tolerance of halophytes are proline and proline analog (4-hydroxy-N-methyl proline), glycine betaine, pinitol, myo-inositol, mannitol, sorbitol, O-methylmucoinositol, and polyamines. In halophytes, the synthesis of specific proteins and osmotically active metabolites control ion and water flux and support scavenging of oxygen radicals under salt stress condition. The present review summarizes the salt tolerance mechanisms of halophytes by elucidating the recent studies that have focused on proteomic, metabolomic, and ionomic aspects of various halophytes in response to salinity. By integrating the information from halophytes and its comparison with glycophytes could give an overview of salt tolerance mechanisms in halophytes, thus laying down the pavement for development of salt tolerant crop plants through genetic modification and effective breeding strategies. PMID:26284080

  9. BioSpider: a web server for automating metabolome annotations.

    PubMed

    Knox, Craig; Shrivastava, Savita; Stothard, Paul; Eisner, Roman; Wishart, David S

    2007-01-01

    One of the growing challenges in life science research lies in finding useful, descriptive or quantitative data about newly reported biomolecules (genes, proteins, metabolites and drugs). An even greater challenge is finding information that connects these genes, proteins, drugs or metabolites to each other. Much of this information is scattered through hundreds of different databases, abstracts or books and almost none of it is particularly well integrated. While some efforts are being undertaken at the NCBI and EBI to integrate many different databases together, this still falls short of the goal of having some kind of human-readable synopsis that summarizes the state of knowledge about a given biomolecule - especially small molecules. To address this shortfall, we have developed BioSpider. BioSpider is essentially an automated report generator designed specifically to tabulate and summarize data on biomolecules - both large and small. Specifically, BioSpider allows users to type in almost any kind of biological or chemical identifier (protein/gene name, sequence, accession number, chemical name, brand name, SMILES string, InCHI string, CAS number, etc.) and it returns an in-depth synoptic report (approximately 3-30 pages in length) about that biomolecule and any other biomolecule it may target. This summary includes physico-chemical parameters, images, models, data files, descriptions and predictions concerning the query molecule. BioSpider uses a web-crawler to scan through dozens of public databases and employs a variety of specially developed text mining tools and locally developed prediction tools to find, extract and assemble data for its reports. Because of its breadth, depth and comprehensiveness, we believe BioSpider will prove to be a particularly valuable tool for researchers in metabolomics. BioSpider is available at: www.biospider.ca PMID:17990488

  10. Thermal Degradation of Small Molecules: A Global Metabolomic Investigation.

    PubMed

    Fang, Mingliang; Ivanisevic, Julijana; Benton, H Paul; Johnson, Caroline H; Patti, Gary J; Hoang, Linh T; Uritboonthai, Winnie; Kurczy, Michael E; Siuzdak, Gary

    2015-11-01

    Thermal processes are widely used in small molecule chemical analysis and metabolomics for derivatization, vaporization, chromatography, and ionization, especially in gas chromatography mass spectrometry (GC/MS). In this study the effect of heating was examined on a set of 64 small molecule standards and, separately, on human plasma metabolite extracts. The samples, either derivatized or underivatized, were heated at three different temperatures (60, 100, and 250 °C) at different exposure times (30 s, 60 s, and 300 s). All the samples were analyzed by liquid chromatography coupled to electrospray ionization mass spectrometry (LC/MS) and the data processed by XCMS Online ( xcmsonline.scripps.edu ). The results showed that heating at an elevated temperature of 100 °C had an appreciable effect on both the underivatized and derivatized molecules, and heating at 250 °C created substantial changes in the profile. For example, over 40% of the molecular peaks were altered in the plasma metabolite analysis after heating (250 °C, 300s) with a significant formation of degradation and transformation products. The analysis of 64 small molecule standards validated the temperature-induced changes observed on the plasma metabolites, where most of the small molecules degraded at elevated temperatures even after minimal exposure times (30 s). For example, tri- and diorganophosphates (e.g., adenosine triphosphate and adenosine diphosphate) were readily degraded into a mono-organophosphate (e.g., adenosine monophosphate) during heating. Nucleosides and nucleotides (e.g., inosine and inosine monophosphate) were also found to be transformed into purine derivatives (e.g., hypoxanthine). A newly formed transformation product, oleoyl ethyl amide, was identified in both the underivatized and derivatized forms of the plasma extracts and small molecule standard mixture, and was likely generated from oleic acid. Overall these analyses show that small molecules and metabolites undergo

  11. Metabolic versatility in Haemophilus influenzae: a metabolomic and genomic analysis.

    PubMed

    Othman, Dk Seti Maimonah Pg; Schirra, Horst; McEwan, Alastair G; Kappler, Ulrike

    2014-01-01

    Haemophilus influenzae is a host adapted human pathogen known to contribute to a variety of acute and chronic diseases of the upper and lower respiratory tract as well as the middle ear. At the sites of infection as well as during growth as a commensal the environmental conditions encountered by H. influenzae will vary significantly, especially in terms of oxygen availability, however, the mechanisms by which the bacteria can adapt their metabolism to cope with such changes have not been studied in detail. Using targeted metabolomics the spectrum of metabolites produced during growth of H. influenzae on glucose in RPMI-based medium was found to change from acetate as the main product during aerobic growth to formate as the major product during anaerobic growth. This change in end-product is likely caused by a switch in the major route of pyruvate degradation. Neither lactate nor succinate or fumarate were major products of H. influenzae growth under any condition studied. Gene expression studies and enzyme activity data revealed that despite an identical genetic makeup and very similar metabolite production profiles, H. influenzae strain Rd appeared to favor glucose degradation via the pentose phosphate pathway, while strain 2019, a clinical isolate, showed higher expression of enzymes involved in glycolysis. Components of the respiratory chain were most highly expressed during microaerophilic and anaerobic growth in both strains, but again clear differences existed in the expression of genes associated e.g., with NADH oxidation, nitrate and nitrite reduction in the two strains studied. Together our results indicate that H. influenzae uses a specialized type of metabolism that could be termed "respiration assisted fermentation" where the respiratory chain likely serves to alleviate redox imbalances caused by incomplete glucose oxidation, and at the same time provides a means of converting a variety of compounds including nitrite and nitrate that arise as part of

  12. Fecal metabolomics: assay performance and association with colorectal cancer

    PubMed Central

    Goedert, James J.; Sampson, Joshua N.; Moore, Steven C.; Xiao, Qian; Xiong, Xiaoqin; Hayes, Richard B.; Ahn, Jiyoung; Shi, Jianxin; Sinha, Rashmi

    2014-01-01

    Metabolomic analysis of feces may provide insights on colorectal cancer (CRC) if assay performance is satisfactory. In lyophilized feces from 48 CRC cases, 102 matched controls, and 48 masked quality control specimens, 1043 small molecules were detected with a commercial platform. Assay reproducibility was good for 527 metabolites [technical intraclass correlation coefficient (ICC) >0.7 in quality control specimens], but reproducibility in 6-month paired specimens was lower for the majority of metabolites (within-subject ICC ≤0.5). In the CRC cases and controls, significant differences (false discovery rate ≤0.10) were found for 41 of 1043 fecal metabolites. Direct cancer association was found with three fecal heme-related molecules [covariate-adjusted 90th versus 10th percentile odds ratio (OR) = 17–345], 18 peptides/amino acids (OR = 3–14), palmitoyl-sphingomyelin (OR = 14), mandelate (OR = 3) and p-hydroxy-benzaldehyde (OR = 4). Conversely, cancer association was inverse with acetaminophen metabolites (OR <0.1), tocopherols (OR = 0.3), sitostanol (OR = 0.2), 3-dehydrocarnitine (OR = 0.4), pterin (OR = 0.3), conjugated-linoleate-18-2N7 (OR = 0.2), N-2-furoyl-glycine (OR = 0.3) and p-aminobenzoate (PABA, OR = 0.2). Correlations suggested an independent role for palmitoyl-sphingomyelin and a central role for PABA (which was stable over 6 months, within-subject ICC 0.67) modulated by p-hydroxy-benzaldehyde. Power calculations based on ICCs indicate that only 45% of metabolites with a true relative risk 5.0 would be found in prospectively collected, prediagnostic specimens from 500 cases and 500 controls. Thus, because fecal metabolites vary over time, very large studies will be needed to reliably detect associations of many metabolites that potentially contribute to CRC. PMID:25037050

  13. Fecal metabolomics: assay performance and association with colorectal cancer.

    PubMed

    Goedert, James J; Sampson, Joshua N; Moore, Steven C; Xiao, Qian; Xiong, Xiaoqin; Hayes, Richard B; Ahn, Jiyoung; Shi, Jianxin; Sinha, Rashmi

    2014-09-01

    Metabolomic analysis of feces may provide insights on colorectal cancer (CRC) if assay performance is satisfactory. In lyophilized feces from 48 CRC cases, 102 matched controls, and 48 masked quality control specimens, 1043 small molecules were detected with a commercial platform. Assay reproducibility was good for 527 metabolites [technical intraclass correlation coefficient (ICC) >0.7 in quality control specimens], but reproducibility in 6-month paired specimens was lower for the majority of metabolites (within-subject ICC ≤0.5). In the CRC cases and controls, significant differences (false discovery rate ≤0.10) were found for 41 of 1043 fecal metabolites. Direct cancer association was found with three fecal heme-related molecules [covariate-adjusted 90th versus 10th percentile odds ratio (OR) = 17-345], 18 peptides/amino acids (OR = 3-14), palmitoyl-sphingomyelin (OR = 14), mandelate (OR = 3) and p-hydroxy-benzaldehyde (OR = 4). Conversely, cancer association was inverse with acetaminophen metabolites (OR <0.1), tocopherols (OR = 0.3), sitostanol (OR = 0.2), 3-dehydrocarnitine (OR = 0.4), pterin (OR = 0.3), conjugated-linoleate-18-2N7 (OR = 0.2), N-2-furoyl-glycine (OR = 0.3) and p-aminobenzoate (PABA, OR = 0.2). Correlations suggested an independent role for palmitoyl-sphingomyelin and a central role for PABA (which was stable over 6 months, within-subject ICC 0.67) modulated by p-hydroxy-benzaldehyde. Power calculations based on ICCs indicate that only 45% of metabolites with a true relative risk 5.0 would be found in prospectively collected, prediagnostic specimens from 500 cases and 500 controls. Thus, because fecal metabolites vary over time, very large studies will be needed to reliably detect associations of many metabolites that potentially contribute to CRC. PMID:25037050

  14. Fecal Microbiota, Fecal Metabolome, and Colorectal Cancer Interrelations

    PubMed Central

    Sinha, Rashmi; Ahn, Jiyoung; Sampson, Joshua N.; Shi, Jianxin; Yu, Guoqin; Xiong, Xiaoqin; Hayes, Richard B.; Goedert, James J.

    2016-01-01

    Background and Aims Investigation of microbe-metabolite relationships in the gut is needed to understand and potentially reduce colorectal cancer (CRC) risk. Methods Microbiota and metabolomics profiling were performed on lyophilized feces from 42 CRC cases and 89 matched controls. Multivariable logistic regression was used to identify statistically independent associations with CRC. First principal coordinate-component pair (PCo1-PC1) and false discovery rate (0.05)-corrected P-values were calculated for 116,000 Pearson correlations between 530 metabolites and 220 microbes in a sex*case/control meta-analysis. Results Overall microbe-metabolite PCo1-PC1 was more strongly correlated in cases than in controls (Rho 0.606 vs 0.201, P = 0.01). CRC was independently associated with lower levels of Clostridia, Lachnospiraceae, p-aminobenzoate and conjugated linoleate, and with higher levels of Fusobacterium, Porphyromonas, p-hydroxy-benzaldehyde, and palmitoyl-sphingomyelin. Through postulated effects on cell shedding (palmitoyl-sphingomyelin), inflammation (conjugated linoleate), and innate immunity (p-aminobenzoate), metabolites mediated the CRC association with Fusobacterium and Porphyromonas by 29% and 34%, respectively. Overall, palmitoyl-sphingomyelin correlated directly with abundances of Enterobacteriaceae (Gammaproteobacteria), three Actinobacteria and five Firmicutes. Only Parabacteroides correlated inversely with palmitoyl-sphingomyelin. Other lipids correlated inversely with Alcaligenaceae (Betaproteobacteria). Six Bonferroni-significant correlations were found, including low indolepropionate and threnoylvaline with Actinobacteria and high erythronate and an uncharacterized metabolite with Enterobacteriaceae. Conclusions Feces from CRC cases had very strong microbe-metabolite correlations that were predominated by Enterobacteriaceae and Actinobacteria. Metabolites mediated a direct CRC association with Fusobacterium and Porphyromonas, but not an inverse

  15. A metabolomics investigation of non genotoxic carcinogenicity in the rat

    PubMed Central

    Ament, Zsuzsanna; Waterman, Claire L; West, James A; Waterfield, Catherine; Currie, Richard A; Wright, Jayne; Griffin, Julian L

    2014-01-01

    Non-genotoxic carcinogens (NGCs) promote tumour growth by altering gene expression which ultimately leads to cancer without directly causing a change in DNA sequence. As a result NGCs are not detected in mutagenesis assays. Whilst there are proposed biomarkers of carcinogenic potential, the definitive identification of non-genotoxic carcinogens still rests with the rat and mouse long term bioassay. Such assays are expensive, time consuming, require a large number of animals and their relevance to human health risk assessments is debatable. Metabolomics and lipidomics in combination with pathology and clinical chemistry were used to profile perturbations produced by 10 compounds which represented a range of rat non-genotoxic hepatocarcinogens (NGC), non-genotoxic non-hepatocarcinogens (non-NGC) and a genotoxic hepatocarcinogen. Each compound was administered at its maximum tolerated dose level for 7, 28 and 91 days to male Fisher 344 rats. Changes in liver metabolite concentration differentiated the treated groups across different time points. The most significant differences were driven by pharmacological mode of action, specifically by the peroxisome proliferator activated receptor alpha (PPAR-α) agonists. Despite these dominant effects, good predictions could be made when differentiating NGCs from non-NGCs. Predictive ability measured by leave one out cross validation was 87% and 77% after 28 days of dosing for NGCs and non-NGCs, respectively. Amongst the discriminatory metabolites we identified free fatty acids, phospholipids, triacylglycerols, as well as precursors of eicosanoid and the products of reactive oxygen species linked to processes of inflammation, proliferation and oxidative stress. Thus, metabolic profiling is able to identify changes due to the pharmacological mode of action of xenobiotics and contribute to early screening for non-genotoxic potential. PMID:24161236

  16. Metabolic versatility in Haemophilus influenzae: a metabolomic and genomic analysis

    PubMed Central

    Othman, Dk Seti Maimonah Pg; Schirra, Horst; McEwan, Alastair G.; Kappler, Ulrike

    2014-01-01

    Haemophilus influenzae is a host adapted human pathogen known to contribute to a variety of acute and chronic diseases of the upper and lower respiratory tract as well as the middle ear. At the sites of infection as well as during growth as a commensal the environmental conditions encountered by H. influenzae will vary significantly, especially in terms of oxygen availability, however, the mechanisms by which the bacteria can adapt their metabolism to cope with such changes have not been studied in detail. Using targeted metabolomics the spectrum of metabolites produced during growth of H. influenzae on glucose in RPMI-based medium was found to change from acetate as the main product during aerobic growth to formate as the major product during anaerobic growth. This change in end-product is likely caused by a switch in the major route of pyruvate degradation. Neither lactate nor succinate or fumarate were major products of H. influenzae growth under any condition studied. Gene expression studies and enzyme activity data revealed that despite an identical genetic makeup and very similar metabolite production profiles, H. influenzae strain Rd appeared to favor glucose degradation via the pentose phosphate pathway, while strain 2019, a clinical isolate, showed higher expression of enzymes involved in glycolysis. Components of the respiratory chain were most highly expressed during microaerophilic and anaerobic growth in both strains, but again clear differences existed in the expression of genes associated e.g., with NADH oxidation, nitrate and nitrite reduction in the two strains studied. Together our results indicate that H. influenzae uses a specialized type of metabolism that could be termed “respiration assisted fermentation” where the respiratory chain likely serves to alleviate redox imbalances caused by incomplete glucose oxidation, and at the same time provides a means of converting a variety of compounds including nitrite and nitrate that arise as part

  17. Metabolomics confirms that dissolved organic carbon mitigates copper toxicity.

    PubMed

    Taylor, Nadine S; Kirwan, Jennifer A; Yan, Norman D; Viant, Mark R; Gunn, John M; McGeer, James C

    2016-03-01

    Reductions in atmospheric emissions from the metal smelters in Sudbury, Canada, produced major improvements in acid and metal contamination of local lakes and indirectly increased dissolved organic carbon (DOC) concentrations. Metal toxicity, however, has remained a persistent problem for aquatic biota. Integrating high-throughput, nontargeted mass spectrometry metabolomics with conventional toxicological measures elucidated the mediating effects of dissolved organic matter (DOM) on the toxicity of Cu to Daphnia pulex-pulicaria, a hybrid isolated from these soft water lakes. Two generations of daphniids were exposed to Cu (0-20 μg/L) at increasing levels of natural DOM (0-4 mg DOC/L). Added DOM reduced Cu toxicity monotonically with median lethal concentration values increasing from 2.3 μg/L Cu without DOM to 22.7 μg/L Cu at 4 mg DOC/L. Reproductive output similarly benefited, increasing with DOM, yet falling with increases in Cu. Second generation reproduction was more impaired than the first generation. Dissolved organic matter had a greater influence than Cu on the metabolic status of the daphniids. Putative identification of metabolite peaks indicated that DOM elevation increased the metabolic energy status of the first generation animals, but this benefit was reduced in the second generation, although evidence of increased oxidative stress was detected. These results indicate that Sudbury's terrestrial ecosystems should be managed to increase aquatic DOM supply to enable daphniid colonists to both survive and foster stable populations. Environ Toxicol Chem 2016;35:635-644. © 2015 SETAC. PMID:26274843

  18. Exploring the Saccharomyces cerevisiae Volatile Metabolome: Indigenous versus Commercial Strains

    PubMed Central

    Alves, Zélia; Melo, André; Figueiredo, Ana Raquel; Coimbra, Manuel A.; Gomes, Ana C.; Rocha, Sílvia M.

    2015-01-01

    Winemaking is a highly industrialized process and a number of commercial Saccharomyces cerevisiae strains are used around the world, neglecting the diversity of native yeast strains that are responsible for the production of wines peculiar flavours. The aim of this study was to in-depth establish the S. cerevisiae volatile metabolome and to assess inter-strains variability. To fulfill this objective, two indigenous strains (BT2652 and BT2453 isolated from spontaneous fermentation of grapes collected in Bairrada Appellation, Portugal) and two commercial strains (CSc1 and CSc2) S. cerevisiae were analysed using a methodology based on advanced multidimensional gas chromatography (HS-SPME/GC×GC-ToFMS) tandem with multivariate analysis. A total of 257 volatile metabolites were identified, distributed over the chemical families of acetals, acids, alcohols, aldehydes, ketones, terpenic compounds, esters, ethers, furan-type compounds, hydrocarbons, pyrans, pyrazines and S-compounds. Some of these families are related with metabolic pathways of amino acid, carbohydrate and fatty acid metabolism as well as mono and sesquiterpenic biosynthesis. Principal Component Analysis (PCA) was used with a dataset comprising all variables (257 volatile components), and a distinction was observed between commercial and indigenous strains, which suggests inter-strains variability. In a second step, a subset containing esters and terpenic compounds (C10 and C15), metabolites of particular relevance to wine aroma, was also analysed using PCA. The terpenic and ester profiles express the strains variability and their potential contribution to the wine aromas, specially the BT2453, which produced the higher terpenic content. This research contributes to understand the metabolic diversity of indigenous wine microflora versus commercial strains and achieved knowledge that may be further exploited to produce wines with peculiar aroma properties. PMID:26600152

  19. 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

  20. New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics: the not-so-simple process of method performance evaluation.

    PubMed

    Tulipani, Sara; Mora-Cubillos, Ximena; Jáuregui, Olga; Llorach, Rafael; García-Fuentes, Eduardo; Tinahones, Francisco J; Andres-Lacueva, Cristina

    2015-03-01

    Although LC-MS untargeted metabolomics continues to expand into exiting research domains, methodological issues have not been solved yet by the definition of unbiased, standardized and globally accepted analytical protocols. In the present study, the response of the plasma metabolome coverage to specific methodological choices of the sample preparation (two SPE technologies, three sample-to-solvent dilution ratios) and the LC-ESI-MS data acquisition steps of the metabolomics workflow (four RP columns, four elution solvent combinations, two solvent quality grades, postcolumn modification of the mobile phase) was investigated in a pragmatic and decision tree-like performance evaluation strategy. Quality control samples, reference plasma and human plasma from a real nutrimetabolomic study were used for intermethod comparisons. Uni- and multivariate data analysis approaches were independently applied. The highest method performance was obtained by combining the plasma hybrid extraction with the highest solvent proportion during sample preparation, the use of a RP column compatible with 100% aqueous polar phase (Atlantis T3), and the ESI enhancement by using UHPLC-MS purity grade methanol as both organic phase and postcolumn modifier. Results led to the following considerations: submit plasma samples to hybrid extraction for removal of interfering components to minimize the major sample-dependent matrix effects; avoid solvent evaporation following sample extraction if loss in detection and peak shape distortion of early eluting metabolites are not noticed; opt for a RP column for superior retention of highly polar species when analysis fractionation is not feasible; use ultrahigh quality grade solvents and "vintage" analytical tricks such as postcolumn organic enrichment of the mobile phase to enhance ESI efficiency. The final proposed protocol offers an example of how novel and old-fashioned analytical solutions may fruitfully cohabit in untargeted metabolomics

  1. Symposium: innovative techniques in human embryo viability assessment. Non-invasive assessment of embryo viability by metabolomic profiling of culture media ('metabolomics').

    PubMed

    Nagy, Zsolt Peter; Sakkas, Denny; Behr, Barry

    2008-10-01

    Increasing the efficiency of the IVF procedure by improving pregnancy/implantation rates and at the same time lowering (or avoiding) the risks of multiple gestations are the primary goals of the current assisted reproductive technology. These aims require a much improved gamete/embryo testing and selection procedure, which, using the current approach of microscopy-based morphology evaluation is unlikely to be achieved. Therefore, alternative or additional, non-invasive techniques have been proposed which may be able to detect alterations of the culture environment surrounding gametes/embryos reflective of the (patho-)physiological processes. One of the most recently applied approaches is to measure metabolomic changes in the culture medium of embryos and oocytes ('exometabolomics'). Initial studies have demonstrated that different types of spectrophotometric tests, including Raman and near-infrared (NIR) techniques, are similarly well capable of detecting specific changes of the 'secretome' (exometabolome). These studies have also demonstrated that metabolomic measurements correlate well with embryo development and morphology assessment. Furthermore, viability index on oocytes/embryos established by metabolomic tests may be a stronger predictor for implantation potential than traditional morphological assessment. Although the results of these initial investigations are promising, further prospective studies are required to define clearly the potential benefits and most relevant applications of this novel non-invasive technology in the field of assisted reproduction. PMID:18854103

  2. Potential for Metabolomics-Based Markers of Exposure:Encouraging Evidence from Studies using Model Organisms

    EPA Science Inventory

    Genomic techniques (transcriptomics, proteomics, and metabolomics) have the potential to significantly improve the way chemical risk is managed in the 21st century. Indeed, a significant amount of research has been devoted to the use of these techniques to screen chemicals for h...

  3. Global Metabolomic Analysis of a Mammalian Host Infected with Bacillus anthracis

    PubMed Central

    Nguyen, Chinh T. Q.; Shetty, Vivekananda

    2015-01-01

    Whereas DNA provides the information to design life and proteins provide the materials to construct it, the metabolome can be viewed as the physiology that powers it. As such, metabolomics, the field charged with the study of the dynamic small-molecule fluctuations that occur in response to changing biology, is now being used to study the basis of disease. Here, we describe a comprehensive metabolomic analysis of a systemic bacterial infection using Bacillus anthracis, the etiological agent of anthrax disease, as the model pathogen. An organ and blood analysis identified approximately 400 metabolites, including several key classes of lipids involved in inflammation, as being suppressed by B. anthracis. Metabolite changes were detected as early as 1 day postinfection, well before the onset of disease or the spread of bacteria to organs, which testifies to the sensitivity of this methodology. Functional studies using pharmacologic inhibition of host phospholipases support the idea of a role of these key enzymes and lipid mediators in host survival during anthrax disease. Finally, the results are integrated to provide a comprehensive picture of how B. anthracis alters host physiology. Collectively, the results of this study provide a blueprint for using metabolomics as a platform to identify and study novel host-pathogen interactions that shape the outcome of an infection. PMID:26438791

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

    PubMed

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

    2016-05-01

    Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13) C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full useof LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13) C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. Biotechnol. Bioeng. 2016;113: 1137-1147. © 2015 Wiley Periodicals, Inc. PMID:26479486

  5. Efficacy of Fluidized Bed Bioartificial Liver in Treating Fulminant Hepatic Failure in Pigs: A Metabolomics Study.

    PubMed

    Zhou, Pengcheng; Shao, Li; Zhao, Lifu; Lv, Guoliang; Pan, Xiaoping; Zhang, Anye; Li, Jianzhou; Zhou, Ning; Chen, Deying; Li, Lanjuan

    2016-01-01

    Bioartificial livers may act as a promising therapy for fulminant hepatic failure (FHF) with better accessibility and less injury compared to orthotopic liver transplantation. This study aims to evaluate the efficacy and safety of a fluidized bed bioartificial liver (FBBAL) and to explore its therapeutic mechanisms based on metabolomics. FHF was induced by D-galactosamine. Eighteen hours later, pigs were treated with an FBBAL containing encapsulated primary porcine hepatocytes (B group), with a sham FBBAL (containing cell-free capsules, S group) or with only intensive care (C group) for 6 h. Serum samples were assayed using ultra-performance liquid chromatography-mass spectrometry. The difference in survival time (51.6 ± 7.9 h vs. 49.3 ± 6.6 h) and serum metabolome was negligible between the S and C groups, whereas FBBAL treatment significantly prolonged survival time (70.4 ± 11.5h, P < 0.01) and perturbed the serum metabolome, resulting in a marked decrease in phosphatidylcholines, lysophosphatidylcholines, sphingomyelinase, and fatty acids and an increase in conjugated bile acids. The FBBAL exhibits some liver functions and may exert its therapeutic effect by altering the serum metabolome of FHF pigs. Moreover, alginate-chitosan capsules have less influence on serum metabolites. Nevertheless, the alterations were not universally beneficial, revealing that much should be done to improve the FBBAL. PMID:27194381

  6. Efficacy of Fluidized Bed Bioartificial Liver in Treating Fulminant Hepatic Failure in Pigs: A Metabolomics Study

    PubMed Central

    Zhou, Pengcheng; Shao, Li; Zhao, Lifu; Lv, Guoliang; Pan, Xiaoping; Zhang, Anye; Li, Jianzhou; Zhou, Ning; Chen, Deying; Li, Lanjuan

    2016-01-01

    Bioartificial livers may act as a promising therapy for fulminant hepatic failure (FHF) with better accessibility and less injury compared to orthotopic liver transplantation. This study aims to evaluate the efficacy and safety of a fluidized bed bioartificial liver (FBBAL) and to explore its therapeutic mechanisms based on metabolomics. FHF was induced by D-galactosamine. Eighteen hours later, pigs were treated with an FBBAL containing encapsulated primary porcine hepatocytes (B group), with a sham FBBAL (containing cell-free capsules, S group) or with only intensive care (C group) for 6 h. Serum samples were assayed using ultra-performance liquid chromatography-mass spectrometry. The difference in survival time (51.6 ± 7.9 h vs. 49.3 ± 6.6 h) and serum metabolome was negligible between the S and C groups, whereas FBBAL treatment significantly prolonged survival time (70.4 ± 11.5h, P < 0.01) and perturbed the serum metabolome, resulting in a marked decrease in phosphatidylcholines, lysophosphatidylcholines, sphingomyelinase, and fatty acids and an increase in conjugated bile acids. The FBBAL exhibits some liver functions and may exert its therapeutic effect by altering the serum metabolome of FHF pigs. Moreover, alginate–chitosan capsules have less influence on serum metabolites. Nevertheless, the alterations were not universally beneficial, revealing that much should be done to improve the FBBAL. PMID:27194381

  7. Global metabolomic analysis of a mammalian host infected with Bacillus anthracis.

    PubMed

    Nguyen, Chinh T Q; Shetty, Vivekananda; Maresso, Anthony W

    2015-12-01

    Whereas DNA provides the information to design life and proteins provide the materials to construct it, the metabolome can be viewed as the physiology that powers it. As such, metabolomics, the field charged with the study of the dynamic small-molecule fluctuations that occur in response to changing biology, is now being used to study the basis of disease. Here, we describe a comprehensive metabolomic analysis of a systemic bacterial infection using Bacillus anthracis, the etiological agent of anthrax disease, as the model pathogen. An organ and blood analysis identified approximately 400 metabolites, including several key classes of lipids involved in inflammation, as being suppressed by B. anthracis. Metabolite changes were detected as early as 1 day postinfection, well before the onset of disease or the spread of bacteria to organs, which testifies to the sensitivity of this methodology. Functional studies using pharmacologic inhibition of host phospholipases support the idea of a role of these key enzymes and lipid mediators in host survival during anthrax disease. Finally, the results are integrated to provide a comprehensive picture of how B. anthracis alters host physiology. Collectively, the results of this study provide a blueprint for using metabolomics as a platform to identify and study novel host-pathogen interactions that shape the outcome of an infection. PMID:26438791

  8. Rifaximin Modulates the Vaginal Microbiome and Metabolome in Women Affected by Bacterial Vaginosis

    PubMed Central

    Picone, Gianfranco; Cruciani, Federica; Brigidi, Patrizia; Calanni, Fiorella; Donders, Gilbert; Capozzi, Francesco; Vitali, Beatrice

    2014-01-01

    Bacterial vaginosis (BV) is a common vaginal disorder characterized by the decrease of lactobacilli and overgrowth of Gardnerella vaginalis and resident anaerobic vaginal bacteria. In the present work, the effects of rifaximin vaginal tablets on vaginal microbiota and metabolome of women affected by BV were investigated by combining quantitative PCR and a metabolomic approach based on 1H nuclear magnetic resonance. To highlight the general trends of the bacterial communities and metabolomic profiles in response to the antibiotic/placebo therapy, a multivariate statistical strategy was set up based on the trajectories traced by vaginal samples in a principal component analysis space. Our data demonstrated the efficacy of rifaximin in restoring a health-like condition in terms of both bacterial communities and metabolomic features. In particular, rifaximin treatment was significantly associated with an increase in the lactobacillus/BV-related bacteria ratio, as well as with an increase in lactic acid concentration and a decrease of a pool of metabolites typically produced by BV-related bacteria (acetic acid, succinate, short-chain fatty acids, and biogenic amines). Among the tested dosages of rifaximin (100 and 25 mg for 5 days and 100 mg for 2 days), 25 mg for 5 days was found to be the most effective. PMID:24709255

  9. Rifaximin modulates the vaginal microbiome and metabolome in women affected by bacterial vaginosis.

    PubMed

    Laghi, Luca; Picone, Gianfranco; Cruciani, Federica; Brigidi, Patrizia; Calanni, Fiorella; Donders, Gilbert; Capozzi, Francesco; Vitali, Beatrice

    2014-06-01

    Bacterial vaginosis (BV) is a common vaginal disorder characterized by the decrease of lactobacilli and overgrowth of Gardnerella vaginalis and resident anaerobic vaginal bacteria. In the present work, the effects of rifaximin vaginal tablets on vaginal microbiota and metabolome of women affected by BV were investigated by combining quantitative PCR and a metabolomic approach based on (1)H nuclear magnetic resonance. To highlight the general trends of the bacterial communities and metabolomic profiles in response to the antibiotic/placebo therapy, a multivariate statistical strategy was set up based on the trajectories traced by vaginal samples in a principal component analysis space. Our data demonstrated the efficacy of rifaximin in restoring a health-like condition in terms of both bacterial communities and metabolomic features. In particular, rifaximin treatment was significantly associated with an increase in the lactobacillus/BV-related bacteria ratio, as well as with an increase in lactic acid concentration and a decrease of a pool of metabolites typically produced by BV-related bacteria (acetic acid, succinate, short-chain fatty acids, and biogenic amines). Among the tested dosages of rifaximin (100 and 25 mg for 5 days and 100 mg for 2 days), 25 mg for 5 days was found to be the most effective. PMID:24709255

  10. Metabolomic Applications to Decipher Gut Microbial Metabolic Influence in Health and Disease

    PubMed Central

    Martin, François-Pierre J.; Collino, Sebastiano; Rezzi, Serge; Kochhar, Sunil

    2012-01-01

    Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial–mammalian cross talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids, and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease etiology, diagnostic stratification, and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR) spectroscopy and mass spectrometry provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation. PMID:22557976

  11. Integration of datasets from different analytical techniques to assess the impact of nutrition on human metabolome

    PubMed Central

    Vernocchi, Pamela; Vannini, Lucia; Gottardi, Davide; Del Chierico, Federica; Serrazanetti, Diana I.; Ndagijimana, Maurice; Guerzoni, Maria E.

    2012-01-01

    Bacteria colonizing the human intestinal tract exhibit a high phylogenetic diversity that reflects their immense metabolic potentials. The catalytic activity of gut microbes has an important impact on gastrointestinal (GI) functions and host health. The microbial conversion of carbohydrates and other food components leads to the formation of a large number of compounds that affect the host metabolome and have beneficial or adverse effects on human health. Metabolomics is a metabolic-biology system approach focused on the metabolic responses understanding of living systems to physio-pathological stimuli by using multivariate statistical data on human body fluids obtained by different instrumental techniques. A metabolomic approach based on an analytical platform could be able to separate, detect, characterize and quantify a wide range of metabolites and its metabolic pathways. This approach has been recently applied to study the metabolic changes triggered in the gut microbiota by specific diet components and diet variations, specific diseases, probiotic and synbiotic food intake. This review describes the metabolomic data obtained by analyzing human fluids by using different techniques and particularly Gas Chromatography Mass Spectrometry Solid-phase Micro Extraction (GC-MS/SPME), Proton Nuclear Magnetic Resonance (1H-NMR) Spectroscopy and Fourier Transform Infrared (FTIR) Spectroscopy. This instrumental approach has a good potential in the identification and detection of specific food intake and diseases biomarkers. PMID:23248777

  12. Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases.

    PubMed

    Mikkonen, J J W; Singh, S P; Herrala, M; Lappalainen, R; Myllymaa, S; Kullaa, A M

    2016-08-01

    Metabolomics is a systemic study of metabolites, which are small molecules generated by the process of metabolism. The metabolic profile of saliva can provide an early outlook of the changes associated with a wide range of diseases, including oral cancer and periodontal diseases. It is possible to measure levels of disease-specific metabolites using different methods as presented in this study. However, many challenges exist including incomplete understanding of the complicated metabolic pathways of different oral diseases. The review concludes with the discussion on future perspectives of salivary metabolomics from a clinician point of view. Salivary metabolomics may afford a new research avenue to identify local and systemic disorders but also to aid in the design and modification of therapies. A MEDLINE search using keywords "salivary metabolomics" returned 23 results in total, of which seven were omitted for being reviews or letters to the editor. The rest of the articles were used for preparation of the review, 13 of these were published in the last 5 years. PMID:26446036

  13. Urinary metabolomic fingerprinting after consumption of a probiotic strain in women with mastitis.

    PubMed

    Vázquez-Fresno, Rosa; Llorach, Rafael; Marinic, Jelena; Tulipani, Sara; Garcia-Aloy, Mar; Espinosa-Martos, Irene; Jiménez, Esther; Rodríguez, Juan Miguel; Andres-Lacueva, Cristina

    2014-09-01

    Infectious mastitis is a common condition among lactating women, with staphylococci and streptococci being the main aetiological agents. In this context, some lactobacilli strains isolated from breast milk appear to be particularly effective for treating mastitis and, therefore, constitute an attractive alternative to antibiotherapy. A (1)H NMR-based metabolomic approach was applied to detect metabolomic differences after consuming a probiotic strain (Lactobacillus salivarius PS2) in women with mastitis. 24h urine of women with lactational mastitis was collected at baseline and after 21 days of probiotic (PB) administration. Multivariate analysis (OSC-PLS-DA and hierarchical clustering) showed metabolome differences after PB treatment. The discriminant metabolites detected at baseline were lactose, and ibuprofen and acetaminophen (two pharmacological drugs commonly used for mastitis pain), while, after PB intake, creatine and the gut microbial co-metabolites hippurate and TMAO were detected. In addition, a voluntary desertion of the pharmacological drugs ibuprofen and acetaminophen was observed after probiotic administration. The application of NMR-based metabolomics enabled the identification of the overall effects of probiotic consumption among women suffering from mastitis and highlighted the potential of this approach in evaluating the outcomes of probiotics consumption. To our knowledge, this is the first time that this approach has been applied in women with mastitis during lactation. PMID:24880136

  14. Using the matrix-induced ion suppression method for concentration normalization in cellular metabolomics studies.

    PubMed

    Chen, Guan-Yuan; Liao, Hsiao-Wei; Tsai, I-Lin; Tseng, Yufeng Jane; Kuo, Ching-Hua

    2015-10-01

    Studies of the cell metabolome greatly improve our understanding of cell biology. Currently, most cellular metabolomics studies control only cell numbers or protein content without adjusting the total metabolite concentration, mainly because of the lack of an effective concentration normalization method for cell metabolites. This study proposed a matrix-induced ion suppression (MIIS) method to measure the total amount of cellular metabolites by utilizing flow injection analysis coupled with electrospray ionization mass spectrometry (FIA-ESI-MS).We used series dilutions of HL-60 cell extracts to establish the relationship between cellular metabolite concentration and the degree of ion suppression of the ion suppression indicator, and a good correlation was obtained between 2- and 12-fold dilutions of cell extracts (R(2) = 0.999). Two lung cancer cells, CL1-0 and CL1-5, were selected as the model cell lines to evaluate the efficacy of the MIIS method and the importance of metabolite concentration normalization. Through MIIS analysis, CL1-0 cells were found to contain metabolites at a concentration 2.1 times higher than in CL1-5, and the metastatic properties of CL1-5 could only be observed after 2.1-fold dilution of CL1-0 before metabolomic analysis. Our results demonstrated that the MIIS method is an effective approach for metabolite concentration normalization and that controlling metabolite concentrations can improve data integrity in cellular metabolomics studies. PMID:26359637

  15. Integration of metabolomics and proteomics in multiple sclerosis: From biomarkers discovery to personalized medicine.

    PubMed

    Del Boccio, Piero; Rossi, Claudia; di Ioia, Maria; Cicalini, Ilaria; Sacchetta, Paolo; Pieragostino, Damiana

    2016-04-01

    Personalized medicine is the science of individualized prevention and therapy. In the last decade, advances in high-throughput approaches allowed the development of proteomic and metabolomic studies in evaluating the association of genetic and phenotypic variability with disease sensitivity and analgesic response. These considerations have more value in case of multiple sclerosis (MuS), a multifactorial disease with high heterogeneity in clinical course and treatment response. In this review, we reported and updated about proteomic and metabolomic studies for the research of new candidate biomarkers in MuS, and difficulties in their clinical applications. We focused especially on the description of both "omics" approaches that, once integrated, may synergically describe pathophysiology conditions. To prove this assumption, we rebuilt interaction between proteins and metabolites described in the literature as potential biomarkers for MuS, and a pathway analysis of these molecules was performed. The result of such speculation demonstrated a strong convergence of proteomic and metabolomic results in this field, showing also a poorness of available tools for incorporating "omics" approaches. In conclusion, the integration of Metabolomics and Proteomics may allow a more complete characterization of such a heterogeneous disease, providing further insights into personalized healthcare. PMID:27061322

  16. Variation at range margins across multiple spatial scales: environmental temperature, population genetics and metabolomic phenotype

    PubMed Central

    Kunin, William E.; Vergeer, Philippine; Kenta, Tanaka; Davey, Matthew P.; Burke, Terry; Ian Woodward, F.; Quick, Paul; Mannarelli, Maria-Elena; Watson-Haigh, Nathan S.; Butlin, Roger

    2009-01-01

    Range margins are spatially complex, with environmental, genetic and phenotypic variations occurring across a range of spatial scales. We examine variation in temperature, genes and metabolomic profiles within and between populations of the subalpine perennial plant Arabidopsis lyrata ssp. petraea from across its northwest European range. Our surveys cover a gradient of fragmentation from largely continuous populations in Iceland, through more fragmented Scandinavian populations, to increasingly widely scattered populations at the range margin in Scotland, Wales and Ireland. Temperature regimes vary substantially within some populations, but within-population variation represents a larger fraction of genetic and especially metabolomic variances. Both physical distance and temperature differences between sites are found to be associated with genetic profiles, but not metabolomic profiles, and no relationship was found between genetic and metabolomic population structures in any region. Genetic similarity between plants within populations is the highest in the fragmented populations at the range margin, but differentiation across space is the highest there as well, suggesting that regional patterns of genetic diversity may be scale dependent. PMID:19324821

  17. Open-Access Metabolomics Databases for Natural Product Research: Present Capabilities and Future Potential

    PubMed Central

    Johnson, Sean R.; Lange, Bernd Markus

    2015-01-01

    Various databases have been developed to aid in assigning structures to spectral peaks observed in metabolomics experiments. In this review article, we discuss the utility of currently available open-access spectral and chemical databases for natural products discovery. We also provide recommendations on how the research community can contribute to further improvements. PMID:25789275

  18. Two dimensional NMR spectroscopic approaches for exploring plant metabolome: A review

    PubMed Central

    Mahrous, Engy A.; Farag, Mohamed A.

    2014-01-01

    Today, most investigations of the plant metabolome tend to be based on either nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), with or without hyphenation with chromatography. Although less sensitive than MS, NMR provides a powerful complementary technique for the identification and quantification of metabolites in plant extracts. NMR spectroscopy, well appreciated by phytochemists as a particularly information-rich method, showed recent paradigm shift for the improving of metabolome(s) structural and functional characterization and for advancing the understanding of many biological processes. Furthermore, two dimensional NMR (2D NMR) experiments and the use of chemometric data analysis of NMR spectra have proven highly effective at identifying novel and known metabolites that correlate with changes in genotype or phenotype. In this review, we provide an overview of the development of NMR in the field of metabolomics with special focus on 2D NMR spectroscopic techniques and their applications in phytomedicines quality control analysis and drug discovery from natural sources, raising more attention at its potential to reduce the gap between the pace of natural products research and modern drug discovery demand. PMID:25685540

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  20. Potential impact of soil microbiomes on the leaf metabolome and on herbivore feeding behavior

    Technology Transfer Automated Retrieval System (TEKTRAN)

    : It is known that environmental factors can affect the biosynthesis of leaf metabolites. Similarly, specific pairwise plant-microbe interactions modulate specifically the plant’s metabolome by stimulating production of phytoalexins and other defense-related compounds. However, there is no informati...

  1. Alzheimer's disease-like pathology has transient effects on the brain and blood metabolome.

    PubMed

    Pan, Xiaobei; Nasaruddin, Muhammad Bin; Elliott, Christopher T; McGuinness, Bernadette; Passmore, Anthony P; Kehoe, Patrick G; Hölscher, Christian; McClean, Paula L; Graham, Stewart F; Green, Brian D

    2016-02-01

    The pathogenesis of Alzheimer's disease (AD) is complex involving multiple contributing factors. The extent to which AD pathology affects the metabolome is still not understood nor is it known how disturbances change as the disease progresses. For the first time, we have profiled longitudinally (6, 8, 10, 12, and 18 months) both the brain and plasma metabolome of APPswe/PS1deltaE9 double transgenic and wild-type mice. A total of 187 metabolites were quantified using a targeted metabolomic methodology. Multivariate statistical analysis produced models that distinguished APPswe/PS1deltaE9 from wild-type mice at 8, 10, and 12 months. Metabolic pathway analysis found perturbed polyamine metabolism in both brain and blood plasma. There were other disturbances in essential amino acids, branched-chain amino acids, and also in the neurotransmitter serotonin. Pronounced imbalances in phospholipid and acylcarnitine homeostasis were evident in 2 age groups. AD-like pathology, therefore, affects greatly on both the brain and blood metabolomes, although there appears to be a clear temporal sequence whereby changes to brain metabolites precede those in blood. PMID:26827653

  2. A Direct Cell Quenching Method for Cell-Culture Based Metabolomics

    EPA Science Inventory

    A crucial step in metabolomic analysis of cellular extracts is the cell quenching process. The conventional method first uses trypsin to detach cells from their growth surface. This inevitably changes the profile of cellular metabolites since the detachment of cells from the extr...

  3. 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. PMID:26086729

  4. Fecal metabolome of the Hadza hunter-gatherers: a host-microbiome integrative view.

    PubMed

    Turroni, Silvia; Fiori, Jessica; Rampelli, Simone; Schnorr, Stephanie L; Consolandi, Clarissa; Barone, Monica; Biagi, Elena; Fanelli, Flaminia; Mezzullo, Marco; Crittenden, Alyssa N; Henry, Amanda G; Brigidi, Patrizia; Candela, Marco

    2016-01-01

    The recent characterization of the gut microbiome of traditional rural and foraging societies allowed us to appreciate the essential co-adaptive role of the microbiome in complementing our physiology, opening up significant questions on how the microbiota changes that have occurred in industrialized urban populations may have altered the microbiota-host co-metabolic network, contributing to the growing list of Western diseases. Here, we applied a targeted metabolomics approach to profile the fecal metabolome of the Hadza of Tanzania, one of the world's few remaining foraging populations, and compared them to the profiles of urban living Italians, as representative of people in the post-industrialized West. Data analysis shows that during the rainy season, when the diet is primarily plant-based, Hadza are characterized by a distinctive enrichment in hexoses, glycerophospholipids, sphingolipids, and acylcarnitines, while deplete in the most common natural amino acids and derivatives. Complementary to the documented unique metagenomic features of their gut microbiome, our findings on the Hadza metabolome lend support to the notion of an alternate microbiome configuration befitting of a nomadic forager lifestyle, which helps maintain metabolic homeostasis through an overall scarcity of inflammatory factors, which are instead highly represented in the Italian metabolome. PMID:27624970

  5. Blood metabolome profiles of cattle colonized with Escherichia coli O157

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metabolomics is being increasingly used for diagnosis of asymptomatic/difficult-to-diagnose diseases in humans including parasitic (i.e. protozoan, schistosomal), viral (i.e. cytomegalovirus), bacterial (i.e. cystic fibrosis caused by Pseudomonas), genetic (i.e. autism) and cancer (i.e. gastric canc...

  6. Propiconazole induces alterations in the hepatic metabolome of mice: relevance to propiconazole-induced hepatocarcinogenesis

    EPA Science Inventory

    Propiconazole is a mouse hepatotumorigenic fungicide and has been the subject of recent mechanistic investigations on its carcinogenic mechanism of action. The goals of this study were: 1. To identify metabolomic changes induced in the liver by increasing doses of propiconazole i...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. Propiconazole induces alterations in the hepatic metabolome of mice: relevance to propiconazole-induced hepatocarcinogenesis

    EPA Science Inventory

    Propiconazole is a mouse hepatotumorigenic fungicide and has been the subject of recent investigations into its carcinogenic mechanism of action. The goals of this study were: 1. To identify metabolomic changes induced in the liver by increasing doses of propiconazole in mice; 2...

  9. Metabolomic technologies for improving the quality of food: Practice and promise

    Technology Transfer Automated Retrieval System (TEKTRAN)

    It is now well documented that the diet has a significant impact on human health and well-being. However, the complete set of small molecule metabolites present in foods that make up the human diet and the role of food production systems in altering this food metabolome are still largely unknown. Me...

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

    DOE PAGESBeta

    Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; Cho, Yonghoon; Deutschbauer, Adam; Arkin, Adam; Northen, Trent; Siuzdak, Gary

    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

  11. Metabolomic assessment reveals a stimulatory effect of calcium treatment on glucosinolates contents in broccoli microgreen

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Preharvest calcium application has been shown to increase broccoli microgreen yield and extend shelf life. Here we investigated the effect of calcium application on its metabolome using ultra high-performance liquid chromatography (UHPLC) tandem with mass spectrometry (HRMS). The data collected were...

  12. Metabolomic differences in early and late lactation first-parity gilts

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Investigating the metabolome provides the evaluation of all cellular processes occuring while accounting for environmental influence and may provide additional information for selection criteria to fully evolve. Blood samples and body condition measurements were acquired from 68, first-parity gilts ...

  13. RAMAN SPECTROSCOPY-BASED METABOLOMICS: EVALUATION OF SAMPLE PREPARATION AND OPTICAL ACCESSORIES

    EPA Science Inventory

    The field of metabonomics/metabolomics involves observing endogenous metabolites from organisms that change in response to exposure to a stressor or chemical of interest. Methods are being developed for measuring the Raman spectra of low-concentration metabolites in urine. The ...

  14. Mass spectrometry-based plant metabolomics: Metabolite responses to abiotic stress.

    PubMed

    Jorge, Tiago F; Rodrigues, João A; Caldana, Camila; Schmidt, Romy; van Dongen, Joost T; Thomas-Oates, Jane; António, Carla

    2016-09-01

    Metabolomics is one omics approach that can be used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include analysis of a wide range of chemical species with diverse physical properties, from ionic inorganic compounds to biochemically derived hydrophilic carbohydrates, organic and amino acids, and a range of hydrophobic lipid-related compounds. This complexitiy brings huge challenges to the analytical technologies employed in current plant metabolomics programs, and powerful analytical tools are required for the separation and characterization of this extremely high compound diversity present in biological sample matrices. The use of mass spectrometry (MS)-based analytical platforms to profile stress-responsive metabolites that allow some plants to adapt to adverse environmental conditions is fundamental in current plant biotechnology research programs for the understanding and development of stress-tolerant plants. In this review, we describe recent applications of metabolomics and emphasize its increasing application to study plant responses to environmental (stress-) factors, including drought, salt, low oxygen caused by waterlogging or flooding of the soil, temperature, light and oxidative stress (or a combination of them). Advances in understanding the global changes occurring in plant metabolism under specific abiotic stress conditions are fundamental to enhance plant fitness and increase stress tolerance. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:620-649, 2016. PMID:25589422

  15. Assessing metabolomic and chemical diversity of a soybean lineage representing 35 years of breeding

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information on crop genotype- and phenotype-metabolite associations can be of value to trait development as well as to food security and safety. The unique study presented here assessed seed metabolomic and ionomic diversity in a soybean lineage representing ~35 years of breeding (launch years 1972-...

  16. GIM3E: Condition-specific Models of Cellular Metabolism Developed from Metabolomics and Expression Data

    SciTech Connect

    Schmidt, Brian; Ebrahim, Ali; Metz, Thomas O.; Adkins, Joshua N.; Palsson, Bernard O.; Hyduke, Daniel R.

    2013-11-15

    Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been reported. Results: GIMMME (Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics, and intracellular metabolomics data. GIMMME establishes metabolite utilization requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions, and also provides calculations of the turnover (production / consumption) flux of metabolites. GIMMME was employed to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIMMME has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/

  17. 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

  18. UV-B mediated metabolic rearrangements in poplar revealed by non-targeted metabolomics.

    PubMed

    Kaling, Moritz; Kanawati, Basem; Ghirardo, Andrea; Albert, Andreas; Winkler, Jana Barbro; Heller, Werner; Barta, Csengele; Loreto, Francesco; Schmitt-Kopplin, Philippe; Schnitzler, Jörg-Peter

    2015-05-01

    Plants have to cope with various abiotic stresses including UV-B radiation (280-315 nm). UV-B radiation is perceived by a photoreceptor, triggers morphological responses and primes plant defence mechanisms such as antioxidant levels, photoreapir or accumulation of UV-B screening pigments. As poplar is an important model system for trees, we elucidated the influence of UV-B on overall metabolite patterns in poplar leaves grown under high UV-B radiation. Combining non-targeted metabolomics with gas exchange analysis and confocal microscopy, we aimed understanding how UV-B radiation triggers metabolome-wide changes, affects isoprene emission, photosynthetic performance, epidermal light attenuation and finally how isoprene-free poplars adjust their metabolome under UV-B radiation. Exposure to UV-B radiation caused a comprehensive rearrangement of the leaf metabolome. Several hundreds of metabolites were up- and down-regulated over various pathways. Our analysis, revealed the up-regulation of flavonoids, anthocyanins and polyphenols and the down-regulation of phenolic precursors in the first 36 h of UV-B treatment. We also observed a down-regulation of steroids after 12 h. The accumulation of phenolic compounds leads to a reduced light transmission in UV-B-exposed plants. However, the accumulation of phenolic compounds was reduced in non-isoprene-emitting plants suggesting a metabolic- or signalling-based interaction between isoprenoid and phenolic pathways. PMID:24738572

  19. Pre-storage UV-White Light Irradiation Alters Apple Peel Metabolome

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Global metabolic profiling of ‘Granny Smith’ apple peel was employed for evaluating metabolomic alterations resulting from pre-storage UV-white light irradiation. Apples were bagged mid-season to restrict sunlight, harvested at the pre-climacteric stage prior to bag removal, treated with fluorescen...

  20. Radiation Metabolomics: Identification of Minimally Invasive Urine Biomarkers for Gamma-Radiation Exposure in Mice

    PubMed Central

    Tyburski, John B.; Patterson, Andrew D.; Krausz, Kristopher W.; Slavík, Josef; Fornace, Albert J.; Gonzalez, Frank J.; Idle, Jeffrey R.

    2008-01-01

    Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for γ-radiation biodosimetry in a mouse model. Mice were γ-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography–time-of-flight mass spectrometry (UPLC–TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and β-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose–response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to γ radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans. PMID:18582157

  1. Toward the comprehensive understanding of the gut ecosystem via metabolomics-based integrated omics approach.

    PubMed

    Aw, Wanping; Fukuda, Shinji

    2015-01-01

    Recent advances in DNA sequencing and mass spectrometry technologies have allowed us to collect more data on microbiome and metabolome to assess the influence of the gut microbiota on human health at a whole-systems level. Major advances in metagenomics and metabolomics technologies have shown that the gut microbiota contributes to host overall health status to a large extent. As such, the gut microbiota is often likened to a measurable and functional organ consisting of prokaryotic cells, which creates the unique gut ecosystem together with the host eukaryotic cells. In this review, we discuss in detail the relationship between gut microbiota and its metabolites like choline, bile acids, phenols, and short-chain fatty acids in the host health and etiopathogenesis of various pathological states such as multiple sclerosis, autism, obesity, diabetes, and chronic kidney disease. By integrating metagenomic and metabolomic information on a systems biology-wide approach, we would be better able to understand this interplay between gut microbiome and host metabolism. Integration of the microbiome, metatranscriptome, and metabolome information will pave the way toward an improved holistic understanding of the complex mammalian superorganism. Through the modeling of metabolic interactions between lifestyle, diet, and microbiota, integrated omics-based understanding of the gut ecosystem is the new avenue, providing exciting novel therapeutic approaches for optimal host health. PMID:25338280

  2. A Metabolomics-driven Elucidation of the Anti-obesity Mechanisms of Xanthohumol*

    PubMed Central

    Kirkwood, Jay S.; Legette, LeeCole L.; Miranda, Cristobal L.; Jiang, Yuan; Stevens, Jan F.

    2013-01-01

    Mild, mitochondrial uncoupling increases energy expenditure and can reduce the generation of reactive oxygen species (ROS). Activation of cellular, adaptive stress response pathways can result in an enhanced capacity to reduce oxidative damage. Together, these strategies target energy imbalance and oxidative stress, both underlying factors of obesity and related conditions such as type 2 diabetes. Here we describe a metabolomics-driven effort to uncover the anti-obesity mechanism(s) of xanthohumol (XN), a prenylated flavonoid from hops. Metabolomics analysis of fasting plasma from obese, Zucker rats treated with XN revealed decreases in products of dysfunctional fatty acid oxidation and ROS, prompting us to explore the effects of XN on muscle cell bioenergetics. At low micromolar concentrations, XN acutely increased uncoupled respiration in several different cell types, including myocytes. Tetrahydroxanthohumol also increased respiration, suggesting electrophilicity did not play a role. At higher concentrations, XN inhibited respiration in a ROS-dependent manner. In myocytes, time course metabolomics revealed acute activation of glutathione recycling and long term induction of glutathione synthesis as well as several other changes indicative of short term elevated cellular stress and a concerted adaptive response. Based on these findings, we hypothesize that XN may ameliorate metabolic syndrome, at least in part, through mitochondrial uncoupling and stress response induction. In addition, time course metabolomics appears to be an effective strategy for uncovering metabolic events that occur during a stress response. PMID:23673658

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems.

    PubMed

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

    2016-07-15

    Metabolomics has recently proved to be useful in the area of biomarker discovery for cancers in which early diagnostic and prognostic biomarkers are urgently needed, as is the case of bladder cancer (BC). This article presents a comprehensive review of the literature on the metabolomic studies on BC, highlighting metabolic pathways perturbed in this disease and the altered metabolites as potential biomarkers for BC detection. Current disease model systems used in the study of BC metabolome include in vitro-cultured cancer cells, ex vivo neoplastic bladder tissues and biological fluids, mainly urine but also blood serum/plasma, from BC patients. The major advantages and drawbacks of each model system are discussed. Based on available data, it seems that BC metabolic signature is mainly characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid metabolism, known to be crucial for cell proliferation, as well as glutathione metabolism, known to be determinant in maintaining cellular redox balance. In addition, purine and pyrimidine metabolism as well as carnitine species were found to be altered in BC. Finally, it is emphasized that, despite the progress made in respect to novel biomarkers for BC diagnosis, there are still some challenges and limitations that should be addressed in future metabolomic studies to ensure their translatability to clinical practice. PMID:26804544

  5. Highlights of the 2012 research workshop: Using nutrigenomics and metabolomics in clinical nutrition research

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Research Workshop, "Using Nutrigenomics and Metabolomics in Clinical Nutrition Research," was held on January 21, 2012, in Orlando, Florida. The conference brought together experts in human nutrition who use nutrigenomic and meta...

  6. Establishment of quantitative severity evaluation model for spinal cord injury by metabolomic fingerprinting.

    PubMed

    Peng, Jin; Zeng, Jun; Cai, Bin; Yang, Hao; Cohen, Mitchell Jay; Chen, Wei; Sun, Ming-Wei; Lu, Charles Damien; Jiang, Hua

    2014-01-01

    Spinal cord injury (SCI) is a devastating event with a limited hope for recovery and represents an enormous public health issue. It is crucial to understand the disturbances in the metabolic network after SCI to identify injury mechanisms and opportunities for treatment intervention. Through plasma 1H-nuclear magnetic resonance (NMR) screening, we identified 15 metabolites that made up an "Eigen-metabolome" capable of distinguishing rats with severe SCI from healthy control rats. Forty enzymes regulated these 15 metabolites in the metabolic network. We also found that 16 metabolites regulated by 130 enzymes in the metabolic network impacted neurobehavioral recovery. Using the Eigen-metabolome, we established a linear discrimination model to cluster rats with severe and mild SCI and control rats into separate groups and identify the interactive relationships between metabolic biomarkers in the global metabolic network. We identified 10 clusters in the global metabolic network and defined them as distinct metabolic disturbance domains of SCI. Metabolic paths such as retinal, glycerophospholipid, arachidonic acid metabolism; NAD-NADPH conversion process, tyrosine metabolism, and cadaverine and putrescine metabolism were included. In summary, we presented a novel interdisciplinary method that integrates metabolomics and global metabolic network analysis to visualize metabolic network disturbances after SCI. Our study demonstrated the systems biological study paradigm that integration of 1H-NMR, metabolomics, and global metabolic network analysis is useful to visualize complex metabolic disturbances after severe SCI. Furthermore, our findings may provide a new quantitative injury severity evaluation model for clinical use. PMID:24727691

  7. 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. PMID:26853041

  8. Push-through direct injection NMR: an optimized automation method applied to metabolomics

    EPA Science Inventory

    There is a pressing need to increase the throughput of NMR analysis in fields such as metabolomics and drug discovery. Direct injection (DI) NMR automation is recognized to have the potential to meet this need due to its suitability for integration with the 96-well plate format. ...

  9. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    PubMed

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. PMID:25529705

  10. Environmental metabolomics reveal geographic variation in aerobic metabolism and metabolic substrates in Mongolian gerbils (Meriones unguiculatus).

    PubMed

    Shi, Yao-Long; Chi, Qing-Sheng; Liu, Wei; Fu, He-Ping; Wang, De-Hua

    2015-06-01

    Mongolian gerbils (Meriones unguiculatus) have a large-scale distribution in northern China. Geographic physiological variations which related to energy and water metabolism are critical to animals' local adaptation and distribution. However, the underlying biochemical mechanism of such variation and its role in adaptation remains largely unknown. We used GC-MS metabolomics approach to investigate the biochemical adaptation of Mongolian gerbils from xeric (desert), transition (desert steppe) and mesic (typical steppe) environments. Gerbils in desert population had lower resting metabolic rate (RMR) and total evaporative water loss (TEWL) than mesic population. Serum metabolomics revealed that concentrations of five tricarboxylic acid cycle intermediates (citrate, cis-aconitate, α-ketoglutarate, fumarate and malate) were lower in desert population than mesic population. Gastrocnemius metabolomics and citrate synthase activity analysis showed a lower concentration of citrate and lower citrate synthase activity in desert population. These findings suggest that desert dwelling gerbils decrease RMR and TEWL via down-regulation of aerobic respiration. Gastrocnemius metabolomics also revealed that there were higher concentrations of glucose and glycolytic intermediates, but lower concentrations of lipids, amino acids and urea in desert population than mesic population. This geographic variation in metabolic substrates may enhance metabolic water production per oxygen molecule for desert population while constraining aerobic respiration to reduce RMR and TEWL. PMID:25817427

  11. Mass spectrometric signatures of the blood plasma metabolome for disease diagnostics

    PubMed Central

    LOKHOV, PETR G.; BALASHOVA, ELENA E.; VOSKRESENSKAYA, ANNA A.; TRIFONOVA, OXANA P.; MASLOV, DMITRY L.; ARCHAKOV, ALEXANDER I.

    2016-01-01

    In metabolomics, a large number of small molecules can be detected in a single run. However, metabolomic data do not include the absolute concentrations of each metabolite. Generally, mass spectrometry analyses provide metabolite concentrations that are derived from mass peak intensities, and the peak intensities are strictly dependent on the type of mass spectrometer used, as well as the technical characteristics, options and protocols applied. To convert mass peak intensities to actual concentrations, calibration curves have to be generated for each metabolite, and this represents a significant challenge depending on the number of metabolites that are detected and involved in metabolome-based diagnostics. To overcome this limitation, and to facilitate the development of diagnostic tests based on metabolomics, mass peak intensities may be expressed in quintiles. The present study demonstrates the advantage of this approach. The examples of diagnostic signatures, which were designed in accordance to this approach, are provided for lung and prostate cancer (leading causes of mortality due to cancer in developed countries) and impaired glucose tolerance (which precedes type 2 diabetes, the most common endocrinology disease worldwide). PMID:26870348

  12. Tools and Databases of the KOMICS Web Portal for Preprocessing, Mining, and Dissemination of Metabolomics Data

    PubMed Central

    Enomoto, Mitsuo; Morishita, Yoshihiko; Kurabayashi, Atsushi; Iijima, Yoko; Ogata, Yoshiyuki; Nakajima, Daisuke; Suzuki, Hideyuki; Shibata, Daisuke

    2014-01-01

    A metabolome—the collection of comprehensive quantitative data on metabolites in an organism—has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study on Jatropha curcas is presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data. PMID:24949426

  13. Non-invasive metabolomic analysis using a commercial NIR instrument for embryo selection

    PubMed Central

    Sfontouris, Ioannis A; Lainas, George T; Sakkas, Denny; Zorzovilis, Ioannis Z; Petsas, George K; Lainas, Trifon G

    2013-01-01

    CONTEXT: Metabolomics was introduced in human in vitro fertilization (IVF) for noninvasive identification of viable embryos with the highest developmental competence. AIMS: To determine whether embryo selection using a commercial version of metabolomic analysis leads to increased implantation rates (IRs) with fetal cardiac activity (FCA) compared with morphology evaluation alone. SETTING AND DESIGN: Randomized controlled trial from April to December 2010 at a private IVF unit. The study was terminated prematurely due to the market withdrawal of the instrument. MATERIALS AND METHODS: IVF patients ≥18 and ≤43 years with ≥4 × 2PN were randomly allocated to metabolomic analysis combined with embryo morphology (ViaMetrics-E; metabolomics + morphology group) or embryo morphology alone (morphology group). Cycles with frozen embryos, oocyte donations, or testicular biopsy were excluded. STATISTICAL ANALYSIS: Categorical and continuous data were analyzed for statistical significance using 2-tailed Fisher's exact test and t-test, respectively. Statistical significance was accepted when P > 0.05. RESULTS: A total of 125 patients were included in the study; 39 patients were allocated to metabolomics + morphology group and 86 patients to morphology group. Patients were stratified according to the day of embryo transfer (Days 2, 3, or 5). IRs with FCA were similar for Days 2 and 3 transfers in both groups. For Day 5 transfers, IRs with FCA were significantly higher in the metabolomics + morphology group (46.8% vs. 28.9%; P = 0.041; 95% confidence intervalp [CI]: 1.09-34.18). Pregnancy and live births rates were similar for Days 2, 3, and 5 in both groups. The study was terminated early following the voluntary market withdrawal of ViaMetrics-E in December 2010. CONCLUSIONS: Metabolomic analysis using the commercial near-infrared (NIR) instrument does not appear to have a beneficial effect on pregnancy and live births, with improvement in IR with FCA for Day 5 transfers

  14. Metabolomic profile in pancreatic cancer patients: a consensus-based approach to identify highly discriminating metabolites

    PubMed Central

    Di Gangi, Iole Maria; Mazza, Tommaso; Fontana, Andrea; Copetti, Massimiliano; Fusilli, Caterina; Ippolito, Antonio; Mattivi, Fulvio; Latiano, Anna; Andriulli, Angelo

    2016-01-01

    Purpose pancreatic adenocarcinoma is the fourth leading cause of cancer related deaths due to its aggressive behavior and poor clinical outcome. There is a considerable variability in the frequency of serum tumor markers in cancer' patients. We performed a metabolomics screening in patients diagnosed with pancreatic cancer. Experimental Design Two targeted metabolomic assays were conducted on 40 serum samples of patients diagnosed with pancreatic cancer and 40 healthy controls. Multivariate methods and classification trees were performed. Materials and Methods Sparse partial least squares discriminant analysis (SPLS-DA) was used to reduce the high dimensionality of a pancreatic cancer metabolomic dataset, differentiating between pancreatic cancer (PC) patients and healthy subjects. Using Random Forest analysis palmitic acid, 1,2-dioleoyl-sn-glycero-3-phospho-rac-glycerol, lanosterol, lignoceric acid, 1-monooleoyl-rac-glycerol, cholesterol 5α,6α epoxide, erucic acid and taurolithocholic acid (T-LCA), oleoyl-L-carnitine, oleanolic acid were identified among 206 metabolites as highly discriminating between disease states. Comparison between Receiver Operating Characteristic (ROC) curves for palmitic acid and CA 19-9 showed that the area under the ROC curve (AUC) of palmitic acid (AUC=1.000; 95% confidence interval) is significantly higher than CA 19-9 (AUC=0.963; 95% confidence interval: 0.896-1.000). Conclusion Mass spectrometry-based metabolomic profiling of sera from pancreatic cancer patients and normal subjects showed significant alterations in the profiles of the metabolome of PC patients as compared to controls. These findings offer an information-rich matrix for discovering novel candidate biomarkers with diagnostic or prognostic potentials. PMID:26735340

  15. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production

    PubMed Central

    Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

    2015-01-01

    Objective The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a ‘Westernised’ lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Design and results Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Conclusions Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. PMID:25431456

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

    PubMed Central

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

    2015-01-01

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

  17. Development of a Metabolomic Radiation Signature in Urine from Patients Undergoing Total Body Irradiation

    PubMed Central

    Laiakis, Evagelia C.; Mak, Tytus D.; Anizan, Sebastien; Amundson, Sally A.; Barker, Christopher A.; Wolden, Suzanne L.; Brenner, David J.; Fornace, Albert J.

    2014-01-01

    The emergence of the threat of radiological terrorism and other radiological incidents has led to the need for development of fast, accurate and noninvasive methods for detection of radiation exposure. The purpose of this study was to extend radiation metabolomic biomarker discovery to humans, as previous studies have focused on mice. Urine was collected from patients undergoing total body irradiation at Memorial Sloan-Kettering Cancer Center prior to hematopoietic stem cell transplantation at 4–6 h postirradiation (a single dose of 1.25 Gy) and 24 h (three fractions of 1.25 Gy each). Global metabolomic profiling was obtained through analysis with ultra performance liquid chromatography coupled to time-of-flight mass spectrometry (TOFMS). Prior to further analyses, each sample was normalized to its respective creatinine level. Statistical analysis was conducted by the nonparametric Kolmogorov-Smirnov test and the Fisher’s exact test and markers were validated against pure standards. Seven markers showed distinct differences between pre- and post-exposure samples. Of those, trimethyl-l-lysine and the carnitine conjugates acetylcarnitine, decanoylcarnitine and octanoylcarnitine play an important role in the transportation of fatty acids across mitochondria for subsequent fatty acid β-oxidation. The remaining metabolites, hypoxanthine, xanthine and uric acid are the final products of the purine catabolism pathway, and high levels of excretion have been associated with increased oxidative stress and radiation induced DNA damage. Further analysis revealed sex differences in the patterns of excretion of the markers, demonstrating that generation of a sex-specific metabolomic signature will be informative and can provide a quick and reliable assessment of individuals in a radiological scenario. This is the first radiation metabolomics study in human urine laying the foundation for the use of metabolomics in biodosimetry and providing confidence in biomarker

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

    PubMed Central

    Aug, Argo; Altraja, Siiri; Kilk, Kalle; Porosk, Rando; Soomets, Ursel; Altraja, Alan

    2015-01-01

    E-cigarettes are widely believed to be safer than conventional cigarettes and have been even suggested as aids for smoking cessation. However, while reasonable with some regards, this judgment is not yet supported by adequate biomedical research data. Since bronchial epithelial cells are the immediate target of inhaled toxicants, we hypothesized that exposure to e-cigarettes may affect the metabolome of human bronchial epithelial cells (HBEC) and that the changes are, at least in part, induced by oxidant-driven mechanisms. Therefore, we evaluated the effect of e-cigarette liquid (ECL) on the metabolome of HBEC and examined the potency of antioxidants to protect the cells. We assessed the changes of the intracellular metabolome upon treatment with ECL in comparison of the effect of cigarette smoke condensate (CSC) with mass spectrometry and principal component analysis on air-liquid interface model of normal HBEC. Thereafter, we evaluated the capability of the novel antioxidant tetrapeptide O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1) to attenuate the effect of ECL. ECL caused a significant shift in the metabolome that gradually gained its maximum by the 5th hour and receded by the 7th hour. A second alteration followed at the 13th hour. Treatment with CSC caused a significant initial shift already by the 1st hour. ECL, but not CSC, significantly increased the concentrations of arginine, histidine, and xanthine. ECL, in parallel with CSC, increased the content of adenosine diphosphate and decreased that of three lipid species from the phosphatidylcholine family. UPF1 partially counteracted the ECL-induced deviations, UPF1’s maximum effect occurred at the 5th hour. The data support our hypothesis that ECL profoundly alters the metabolome of HBEC in a manner, which is comparable and partially overlapping with the effect of CSC. Hence, our results do not support the concept of harmlessness of e-cigarettes. PMID:26536230

  19. Application of 1H-NMR metabolomic profiling for reef-building corals.

    PubMed

    Sogin, Emilia M; Anderson, Paul; Williams, Philip; Chen, Chii-Shiarng; Gates, Ruth D

    2014-01-01

    In light of global reef decline new methods to accurately, cheaply, and quickly evaluate coral metabolic states are needed to assess reef health. Metabolomic profiling can describe the response of individuals to disturbance (i.e., shifts in environmental conditions) across biological models and is a powerful approach for characterizing and comparing coral metabolism. For the first time, we assess the utility of a proton-nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomics approach in characterizing coral metabolite profiles by 1) investigating technical, intra-, and inter-sample variation, 2) evaluating the ability to recover targeted metabolite spikes, and 3) assessing the potential for this method to differentiate among coral species. Our results indicate 1H-NMR profiling of Porites compressa corals is highly reproducible and exhibits low levels of variability within and among colonies. The spiking experiments validate the sensitivity of our methods and showcase the capacity of orthogonal partial least squares discriminate analysis (OPLS-DA) to distinguish between profiles spiked with varying metabolite concentrations (0 mM, 0.1 mM, and 10 mM). Finally, 1H-NMR metabolomics coupled with OPLS-DA, revealed species-specific patterns in metabolite profiles among four reef-building corals (Pocillopora damicornis, Porites lobata, Montipora aequituberculata, and Seriatopora hystrix). Collectively, these data indicate that 1H-NMR metabolomic techniques can profile reef-building coral metabolomes and have the potential to provide an integrated picture of the coral phenotype in response to environmental change. PMID:25354140

  20. Application of 1H-NMR Metabolomic Profiling for Reef-Building Corals

    PubMed Central

    Sogin, Emilia M.; Anderson, Paul; Williams, Philip; Chen, Chii-Shiarng; Gates, Ruth D.

    2014-01-01

    In light of global reef decline new methods to accurately, cheaply, and quickly evaluate coral metabolic states are needed to assess reef health.