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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 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

  6. 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

  7. 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

  8. 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...

  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

    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 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

  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. 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

  7. 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

  8. 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

  9. 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

  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. 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

  18. 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

  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. 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

  2. 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

  3. 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

  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. 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

  7. 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

  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. 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

  12. 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

  13. 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

  14. 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

  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 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

  19. 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

  20. 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

  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. 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

  5. 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

  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. 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...

  9. 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

  10. 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

  11. 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...

  12. 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, ...

  13. 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...

  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. 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

  2. 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

  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. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  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. 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

  14. 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…

  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. 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

  19. 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

  20. 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

  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. 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

  11. 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

  12. 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...

  13. 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...

  14. 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...

  15. (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...

  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. 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...

  19. 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...

  20. 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

  1. 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...

  2. 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

  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. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  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. 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

  20. 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

  1. 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

  2. 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.

  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. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. [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

  11. 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

  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. 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...

  14. 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

  15. 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...

  16. 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...

  17. 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

  18. 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...

  19. 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...

  20. 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...

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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 ...

  9. 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

  10. 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...

  11. 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

  12. 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...

  13. 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

  14. 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

  15. 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

  16. 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

  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. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  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. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  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. 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.

  17. 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...

  18. 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

  19. 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

  20. 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

  1. 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...

  2. 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...

  3. 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 ...

  4. 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

  5. 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

  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. 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