WorldWideScience

Sample records for metabolome

  1. Metabolomics

    DEFF Research Database (Denmark)

    Pedersen, Hans

    is a presentation of a core consistency diagnostic aiding in determining the number of components in a PARAFAC2 model. It is of great importance to validate especially PLS-DA models and if not done properly, the developed models might reveal spurious groupings. Furthermore, data from metabolomics studies contain...... and the results indicate that GC-MS-based metabolomics in combination with PARAFAC2 modelling is applicable for extracting relevant biological information from the plasma samples. Overall, the work in this thesis shows that suitable and properly validated chemometrics models used in metabolomics are very useful...

  2. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    how to properly handle complex metabolomics data, in order to achieve reliable and valid multivariate models. This has been illustrated by three case studies with examples of forecasting breast cancer and early detection of colorectal cancer based on data from nuclear magnetic resonance (NMR...... based on NMR data with RRV and known risk markers. The sensitivity and specificity values are 0.80 and 0.79, respectively, for a test set validated model. The second case study is based on plasma samples with verified colorectal cancer and three types of control samples analysed by fluorescence...... spectroscopy a potential tool in early detection of colorectal cancer. Finally, plasma samples have been analysed using GC-MS. The method requires extensive sample preparation and therefore the study can only be considered a feasibility study with room for optimization. However, 14 plasma samples were analysed...

  3. Nutritional Metabolomics

    DEFF Research Database (Denmark)

    Gürdeniz, Gözde

    Metabolomics provides a holistic approach to investigate the perturbations in human metabolism with respect to a specific exposure. In nutritional metabolomics, the research question is generally related to the effect of a specific food intake on metabolic profiles commonly of plasma or urine...... strategy influences the patterns identified as important for the nutritional question under study. Therefore, in depth understanding of the study design and the specific effects of the analytical technology on the produced data is extremely important to achieve high quality data handling. Besides data...... handling, this thesis also deals with biological interpretation of postprandial metabolism and trans fatty acid (TFA) intake. Two nutritional issues were objects of investigation: 1) metabolic states as a function of time since the last meal and 2) markers related to intakes of cis- and trans-fat. Plasma...

  4. Metabolomics and Epidemiology Working Group

    Science.gov (United States)

    The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

  5. Metabolomic Studies in Drosophila.

    Science.gov (United States)

    Cox, James E; Thummel, Carl S; Tennessen, Jason M

    2017-07-01

    Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila , often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research. Copyright © 2017 by the Genetics Society of America.

  6. Metabolomics in chemical ecology.

    Science.gov (United States)

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  7. Metabolomic studies in pulmonology

    Directory of Open Access Journals (Sweden)

    R. R. Furina

    2015-01-01

    Full Text Available The review shows the results of metabolomic studies in pulmonology. The key idea of metabolomics is to detect specific biomarkers in a biological sample for the diagnosis of diseases of the bronchi and lung. Main methods for the separation and identification of volatile organic substances as biomarkers (gas chromatography, mass spectrometry, and nuclear magnetic resonance spectrometry used in metabolomics are given. A solid-phase microextraction method used to pre-prepare a sample is also covered. The results of laboratory tests for biomarkers for lung cancer, acute respiratory distress syndrome, chronic obstructive pulmonary disease, cystic fibrosis, chronic infections, and pulmonary tuberculosis are presented. In addition, emphasis is placed on the possibilities of metabolomics used in experimental medicine, including to the study of asthma. The information is of interest to both theorists and practitioners.

  8. The food metabolome

    DEFF Research Database (Denmark)

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine

    2014-01-01

    The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according...... to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food...... by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still...

  9. Quality assurance of metabolomics.

    Science.gov (United States)

    Bouhifd, Mounir; Beger, Richard; Flynn, Thomas; Guo, Lining; Harris, Georgina; Hogberg, Helena; Kaddurah-Daouk, Rima; Kamp, Hennicke; Kleensang, Andre; Maertens, Alexandra; Odwin-DaCosta, Shelly; Pamies, David; Robertson, Donald; Smirnova, Lena; Sun, Jinchun; Zhao, Liang; Hartung, Thomas

    2015-01-01

    Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.

  10. COnsortium of METabolomics Studies (COMETS)

    Science.gov (United States)

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

  11. Clinical Metabolomics and Glaucoma.

    Science.gov (United States)

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

    2018-01-01

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

  12. Nanoparticle-Assisted Metabolomics

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2018-03-01

    Full Text Available Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics.

  13. Metabolomics in Immunology Research.

    Science.gov (United States)

    Everts, Bart

    2018-01-01

    There is a growing appreciation that metabolic processes and individual metabolites can shape the function of immune cells and thereby play important roles in the outcome of immune responses. In this respect, the use of MS- and NMR spectroscopy-based platforms to characterize and quantify metabolites in biological samples has recently yielded important novel insights into how our immune system functions and has contributed to the identification of biomarkers for immune-mediated diseases. Here, these recent immunological studies in which metabolomics has been used and made significant contributions to these fields will be discussed. In particular the role of metabolomics to the rapidly advancing field of cellular immunometabolism will be highlighted as well as the future prospects of such metabolomic tools in immunology.

  14. Microbial metabolomics : Toward a platform with full metabolome coverage

    NARCIS (Netherlands)

    Werf, M.J.v.d.; Overkamp, K.M.; Muilwijk, B.; Coulier, L.; Hankemeier, T.

    2007-01-01

    Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial

  15. Metabolomics of Genetically Modified Crops

    Directory of Open Access Journals (Sweden)

    Carolina Simó

    2014-10-01

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

  16. Metabolomics of genetically modified crops.

    Science.gov (United States)

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

    2014-10-20

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

  17. Metabolomics of Genetically Modified Crops

    Science.gov (United States)

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

    2014-01-01

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

  18. NMR-based metabolomics applications

    DEFF Research Database (Denmark)

    Iaccarino, Nunzia

    juice from ancient Danish apple cultivars. Both studies revealed variety-related peculiarities that would have been difficult to detect by means of traditional analysis. The second part of the project includes four metabolomics studies performed on samples of biological origin. In particular, the first......Metabolomics is the scientific discipline that identifies and quantifies endogenous and exogenous metabolites in different biological samples. Metabolites are crucial components of a biological system and they are highly informative about its functional state, due to their closeness to the organism...... focused on the analysis of various samples covering a wide range of fields, namely, food and nutraceutical sciences, cell metabolomics and medicine using a metabolomics approach. Indeed, the first part of the thesis describes two exploratory studies performed on Algerian extra virgin olive oil and apple...

  19. NMR-based milk metabolomics

    DEFF Research Database (Denmark)

    Sundekilde, Ulrik; Larsen, Lotte Bach; Bertram, Hanne Christine S.

    2013-01-01

    and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking...... the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive...... compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining...

  20. Metabolomics Workbench (MetWB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Metabolomics Program's Data Repository and Coordinating Center (DRCC), housed at the San Diego Supercomputer Center (SDSC), University of California, San Diego,...

  1. Metabolomics Society’s International Affiliations

    NARCIS (Netherlands)

    Roessner, U.; Rolin, D.; Rijswijk, van M.E.C.; Hall, R.D.; Hankemeier, T.

    2015-01-01

    In 2012 the Metabolomics Society established a more formal system for national and regional metabolomics initiatives, interest groups, societies and networks to become an International Affiliate of the Society. A number of groups (http://metabolomicssociety.org/international-affilia

  2. ECMDB: The E. coli Metabolome Database

    OpenAIRE

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

    2012-01-01

    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. E...

  3. Metabolomics: the chemistry between ecology and genetics

    NARCIS (Netherlands)

    Macel, M.; Dam, van N.M.; Keurentjes, J.J.B.

    2010-01-01

    Metabolomics is a fast developing field of comprehensive untargeted chemical analyses. It has many applications and can in principle be used on any organism without prior knowledge of the metabolome or genome. The amount of functional information that is acquired with metabolomics largely depends on

  4. Vitamins, metabolomics, and prostate cancer.

    Science.gov (United States)

    Mondul, Alison M; Weinstein, Stephanie J; Albanes, Demetrius

    2017-06-01

    How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms through which vitamins influence prostate cancer risk. Prostate cancer risk data related to vitamins E, A, and D and metabolomic profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have had mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomic profiling of fasting serum collected 1-20 years prior to clinical diagnoses found reduced lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with lower risk of aggressive disease. Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study.

  5. YMDB: the Yeast Metabolome Database

    Science.gov (United States)

    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

  6. Metabolomics Application in Maternal-Fetal Medicine

    OpenAIRE

    Fanos, Vassilios; Atzori, Luigi; Makarenko, Karina; Melis, Gian Benedetto; Ferrazzi, Enrico

    2013-01-01

    Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, prete...

  7. Functional metabolomics reveals novel active products in the DHA metabolome

    Directory of Open Access Journals (Sweden)

    Masakazu eShinohara

    2012-04-01

    Full Text Available Endogenous mechanisms for successful resolution of an acute inflammatory response and the local return to homeostasis are of interest because excessive inflammation underlies many human diseases. In this review, we provide an update and overview of functional metabolomics that identified a new bioactive metabolome of docosahexaenoic acid (DHA. Systematic studies revealed that DHA was converted to DHEA-derived novel bioactive products as well as aspirin-triggered (AT forms of protectins. The new oxygenated DHEA derived products blocked PMN chemotaxis, reduced P-selectin expression and platelet-leukocyte adhesion, and showed organ protection in ischemia/reperfusion injury. These products activated cannabinoid receptor (CB2 receptor and not CB1 receptors. The AT-PD1 reduced neutrophil (PMN recruitment in murine peritonitis. With human cells, AT-PD1 decreased transendothelial PMN migration as well as enhanced efferocytosis of apoptotic human PMN by macrophages. The recent findings reviewed here indicate that DHEA oxidative metabolism and aspirin-triggered conversion of DHA produce potent novel molecules with anti-inflammatory and organ-protective properties, opening the DHA metabolome functional roles.

  8. Metabolomics in Toxicology and Preclinical Research

    Science.gov (United States)

    Ramirez, Tzutzuy; Daneshian, Mardas; Kamp, Hennicke; Bois, Frederic Y.; Clench, Malcolm R.; Coen, Muireann; Donley, Beth; Fischer, Steven M.; Ekman, Drew R.; Fabian, Eric; Guillou, Claude; Heuer, Joachim; Hogberg, Helena T.; Jungnickel, Harald; Keun, Hector C.; Krennrich, Gerhard; Krupp, Eckart; Luch, Andreas; Noor, Fozia; Peter, Erik; Riefke, Bjoern; Seymour, Mark; Skinner, Nigel; Smirnova, Lena; Verheij, Elwin; Wagner, Silvia; Hartung, Thomas; van Ravenzwaay, Bennard; Leist, Marcel

    2013-01-01

    Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context. PMID:23665807

  9. Metabolomics techniques for nanotoxicity investigations.

    Science.gov (United States)

    Lv, Mengying; Huang, Wanqiu; Chen, Zhipeng; Jiang, Hulin; Chen, Jiaqing; Tian, Yuan; Zhang, Zunjian; Xu, Fengguo

    2015-01-01

    Nanomaterials are commonly defined as engineered structures with at least one dimension of 100 nm or less. Investigations of their potential toxicological impact on biological systems and the environment have yet to catch up with the rapid development of nanotechnology and extensive production of nanoparticles. High-throughput methods are necessary to assess the potential toxicity of nanoparticles. The omics techniques are well suited to evaluate toxicity in both in vitro and in vivo systems. Besides genomic, transcriptomic and proteomic profiling, metabolomics holds great promises for globally evaluating and understanding the molecular mechanism of nanoparticle-organism interaction. This manuscript presents a general overview of metabolomics techniques, summarizes its early application in nanotoxicology and finally discusses opportunities and challenges faced in nanotoxicology.

  10. Metabolomics and ischaemic heart disease.

    Science.gov (United States)

    Rasmiena, Aliki A; Ng, Theodore W; Meikle, Peter J

    2013-03-01

    Ischaemic heart disease accounts for nearly half of the global cardiovascular disease burden. Aetiologies relating to heart disease are complex, but dyslipidaemia, oxidative stress and inflammation are cardinal features. Despite preventative measures and advancements in treatment regimens with lipid-lowering agents, the high prevalence of heart disease and the residual risk of recurrent events continue to be a significant burden to the health sector and to the affected individuals and their families. The development of improved risk models for the early detection and prevention of cardiovascular events in addition to new therapeutic strategies to address this residual risk are required if we are to continue to make inroads into this most prevalent of diseases. Metabolomics and lipidomics are modern disciplines that characterize the metabolite and lipid complement respectively, of a given system. Their application to ischaemic heart disease has demonstrated utilities in population profiling, identification of multivariate biomarkers and in monitoring of therapeutic response, as well as in basic mechanistic studies. Although advances in magnetic resonance and mass spectrometry technologies have given rise to the fields of metabolomics and lipidomics, the plethora of data generated presents challenges requiring specific statistical and bioinformatics applications, together with appropriate study designs. Nonetheless, the predictive and re-classification capacity of individuals with various degrees of risk by the plasma lipidome has recently been demonstrated. In the present review, we summarize evidence derived exclusively by metabolomic and lipidomic studies in the context of ischaemic heart disease. We consider the potential role of plasma lipid profiling in assessing heart disease risk and therapeutic responses, and explore the potential mechanisms. Finally, we highlight where metabolomic studies together with complementary -omic disciplines may make further

  11. The future of metabolomics in ELIXIR.

    Science.gov (United States)

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B; Ebbels, Timothy M D; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L; Jimenez, Rafael C; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K; Neumann, Steffen; O'Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A; Spjuth, Ola; Thévenot, Etienne A; Viant, Mark R; Weber, Ralf J M; Willighagen, Egon L; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

  12. Symbiosis of chemometrics and metabolomics: past, present, and future

    NARCIS (Netherlands)

    van der Greef, J.; Smilde, A. K.

    2005-01-01

    Metabolomics is a growing area in the field of systems biology. Metabolomics has already a long history and also the connection of metabolomics with chemometrics goes back some time. This review discusses the symbiosis of metabolomics and chemometrics with emphasis on the medical domain, puts the

  13. A Metabolomic Perspective on Coeliac Disease

    Science.gov (United States)

    Calabrò, Antonio

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD) revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism. PMID:24665364

  14. Metabolomics and bioactive substances in plants

    DEFF Research Database (Denmark)

    Khakimov, Bekzod

    Metabolomic analysis of plants broadens understanding of how plants may benefit humans, animals and the environment, provide sustainable food and energy, and improve current agricultural, pharmacological and medicinal practices in order to bring about healthier and longer life. The quality...... and amount of the extractible biological information is largely determined by data acquisition, data processing and analysis methodologies of the plant metabolomics studies. This PhD study focused mainly on the development and implementation of new metabolomics methodologies for improved data acquisition...... and data processing. The study mainly concerned the three most commonly applied analytical techniques in plant metabolomics, GC-MS, LC-MS and NMR. In addition, advanced chemometrics methods e.g. PARAFAC2 and ASCA have been extensively used for development of complex metabolomics data processing...

  15. Functional Analysis of Metabolomics Data.

    Science.gov (United States)

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

    2016-01-01

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

  16. Elucidation of cellular metabolism via metabolomics and stable-isotope assisted metabolomics.

    Science.gov (United States)

    Hiller, Karsten; Metallo, Christian; Stephanopoulos, Gregory

    2011-07-01

    Metabolomics and metabolic flux analysis (MFA) are powerful tools in the arsenal of methodologies of systems biology. Currently, metabolomics techniques are applied routinely for biomarker determination. However, standard metabolomics techniques only provide static information about absolute or relative metabolite amounts. The application of stable-isotope tracers has opened up a new dimension to metabolomics by providing dynamic information of intracellular fluxes and, by extension, enzyme activities. In the first part of the manuscript we review experimental and computational technologies applicable for metabolomics analyses. In the second part we present current technologies based on the use of stable isotopes and their applications to the analysis of cellular metabolism. Beginning with the determination of mass isotopomer distributions (MIDs), we review technologies for metabolic flux analysis (MFA) and conclude with the presentation of a new methodology for the non-targeted analysis of stable-isotope labeled metabolomics data.

  17. Probabilistic Principal Component Analysis for Metabolomic Data.

    LENUS (Irish Health Repository)

    Nyamundanda, Gift

    2010-11-23

    Abstract Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field.

  18. Metabolomics Application in Maternal-Fetal Medicine

    Directory of Open Access Journals (Sweden)

    Vassilios Fanos

    2013-01-01

    Full Text Available Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, preterm delivery, premature rupture of membranes, gestational diabetes mellitus, preeclampsia, neonatal asphyxia, and hypoxic-ischemic encephalopathy. The aim of this review is to summarize and comment on original data available in relevant published works in order to emphasize the clinical potential of metabolomics in obstetrics in the immediate future.

  19. [Metabolomics in research of phytotherapeutics].

    Science.gov (United States)

    Kráfová, Katarina; Jampílek, Josef; Ostrovský, Ivan

    2012-02-01

    Pharmaceutical and food industries are increasingly focused on the great potential of plant secondary metabolites or natural substances which can be used as therapeutics or model compounds for development of new drugs. The paper is devoted to the use of metabolomics, metabolic profiling and metabolic "fingerprint" for the identification of individual active phyto-substances in plant extracts, in profiling of unique groups of plant secondary metabolites that can be used to improve the classification of several species of medicinal plants as well as for a better characterization and quality control of medicinal extracts, tinctures and phytotherapeutic products prepared from these plants. Combined analytical methods and multivariate statistical analysis are used for metabolite identification. Using this approach, medicinal plants are evaluated not only on the basis of a limited number of pharmacologically important metabolites but also based on the fingerprints of minor metabolites and bioactive molecules.

  20. Comprehensive metabolomic profiling and incident cardiovascular disease: a systematic review

    Science.gov (United States)

    Background: Metabolomics is a promising tool of cardiovascular biomarker discovery. We systematically reviewed the literature on comprehensive metabolomic profiling in association with incident cardiovascular disease (CVD). Methods and Results: We searched MEDLINE and EMBASE from inception to Janua...

  1. Plant Metabolomics : the missiong link in functional genomics strategies

    NARCIS (Netherlands)

    Hall, R.D.; Beale, M.; Fiehn, O.; Hardy, N.; Summer, L.; Bino, R.

    2002-01-01

    After the establishment of technologies for high-throughput DNA sequencing (genomics), gene expression analysis (transcriptomics), and protein analysis (proteomics), the remaining functional genomics challenge is that of metabolomics. Metabolomics is the term coined for essentially comprehensive,

  2. Metabolomics data normalization with EigenMS.

    Directory of Open Access Journals (Sweden)

    Yuliya V Karpievitch

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

  3. Metabolomics: towards understanding traditional Chinese medicine.

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Wang, Zhigang; Sun, Wenjun; Wang, Ping; Wang, Xijun

    2010-12-01

    Metabolomics represent a global understanding of metabolite complement of integrated living systems and dynamic responses to the changes of both endogenous and exogenous factors and has many potential applications and advantages for the research of complex systems. As a systemic approach, metabolomics adopts a "top-down" strategy to reflect the function of organisms from the end products of the metabolic network and to understand metabolic changes of a complete system caused by interventions in a holistic context. This property agrees with the holistic thinking of Traditional Chinese Medicine (TCM), a complex medical science, suggesting that metabolomics has the potential to impact our understanding of the theory behind the evidence-based Chinese medicine. Consequently, the development of robust metabolomic platforms will greatly facilitate, for example, the understanding of the action mechanisms of TCM formulae and the analysis of Chinese herbal (CHM) and mineral medicine, acupuncture, and Chinese medicine syndromes. This review summarizes some of the applications of metabolomics in special TCM issues with an emphasis on metabolic biomarker discovery. © Georg Thieme Verlag KG Stuttgart · New York.

  4. Basics of mass spectrometry based metabolomics.

    Science.gov (United States)

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

    2014-11-01

    The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Metabolomics to Explore Impact of Dairy Intake

    Directory of Open Access Journals (Sweden)

    Hong Zheng

    2015-06-01

    Full Text Available 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.

  6. Metabolomic heterogeneity of pulmonary arterial hypertension.

    Directory of Open Access Journals (Sweden)

    Yidan Zhao

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

  7. Microbiome, Metabolome and Inflammatory Bowel Disease

    Directory of Open Access Journals (Sweden)

    Ishfaq Ahmed

    2016-06-01

    Full Text Available Inflammatory Bowel Disease (IBD is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD or Ulcerative Colitis (UC, two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis.

  8. Metabolomics in pediatric nephrology: Emerging concepts

    Science.gov (United States)

    Hanna, Mina H; Brophy, Patrick D

    2014-01-01

    Metabolomics, the latest of the “omics” sciences, refers to the systematic study of metabolites and their changes in biological samples due to physiological stimuli and/or genetic modification. Because metabolites represent the downstream expression of genome, transcriptome and proteome, they can closely reflect the phenotype of an organism at a specific time. As an emerging field in analytical biochemistry; metabolomics has the potential to play a major role for monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights for novel biomarkers of kidney diseases, given the limitations of the current traditional markers. The clinical utility of metabolomics in the field of pediatric nephrology includes biomarker discovery, defining as yet unrecognized biologic therapeutic targets, linking of metabolites to relevant standard indices and clinical outcomes, and providing a window of opportunity to investigate the intricacies of environment/genetic interplay in specific disease states. PMID:25027575

  9. Linking metabolomics data to underlying metabolic regulation

    Directory of Open Access Journals (Sweden)

    Thomas eNägele

    2014-11-01

    Full Text Available 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

  10. MBRole: enrichment analysis of metabolomic data.

    Science.gov (United States)

    Chagoyen, Monica; Pazos, Florencio

    2011-03-01

    While many tools exist for performing enrichment analysis of transcriptomic and proteomic data in order to interpret them in biological terms, almost no equivalent tools exist for metabolomic data. We present Metabolite Biological Role (MBRole), a web server for carrying out over-representation analysis of biological and chemical annotations in arbitrary sets of metabolites (small chemical compounds) coming from metabolomic data of any organism or sample. The web server is freely available at http://csbg.cnb.csic.es/mbrole. It was tested in the main web browsers.

  11. Metabolomics of forage plants: a review.

    Science.gov (United States)

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

    2012-11-01

    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. 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. 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 of studies using metabolomics

  12. Microbial metabolomics in open microscale platforms

    Science.gov (United States)

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

    2016-01-01

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

  13. Chemometrics Methods and Strategies in Metabolomics.

    Science.gov (United States)

    Pinto, Rui Climaco

    2017-01-01

    Chemometrics has been a fundamental discipline for the development of metabolomics, while symbiotically growing with it. From design of experiments, through data processing, to data analysis, chemometrics tools are used to design, process, visualize, explore and analyse metabolomics data.In this chapter, the most commonly used chemometrics methods for data analysis and interpretation of metabolomics experiments will be presented, with focus on multivariate analysis. These are projection-based linear methods, like principal component analysis (PCA) and orthogonal projection to latent structures (OPLS), which facilitate interpretation of the causes behind the observed sample trends, correlation with outcomes or group discrimination analysis. Validation procedures for multivariate methods will be presented and discussed.Univariate analysis is briefly discussed in the context of correlation-based linear regression methods to find associations to outcomes or in analysis of variance-based and logistic regression methods for class discrimination. These methods rely on frequentist statistics, with the determination of p-values and corresponding multiple correction procedures.Several strategies of design-analysis of metabolomics experiments will be discussed, in order to guide the reader through different setups, adopted to better address some experimental issues and to better test the scientific hypotheses.

  14. Analyzing metabolomics-based challenge test

    NARCIS (Netherlands)

    Vis, D.J.; Westerhuis, J.A.; Jacobs, D.M.; van Duynhoven, J.P.M.; Wopereis, S.; van Ommen, B.; Hendriks, M.M.W.B.; Smilde, A.K.

    2015-01-01

    Challenge tests are used to assess the resilience of human beings to perturbations by analyzing responses to detect functional abnormalities. Well known examples are allergy tests and glucose tolerance tests. Increasingly, metabolomics analysis of blood or serum samples is used to analyze the

  15. Data-processing strategies for metabolomics studies

    NARCIS (Netherlands)

    Hendriks, M.M.W.B.; Eeuwijk, van F.A.; Jellema, R.H.; Westerhuis, J.A.; Reijmers, T.H.; Hoefsloot, H.C.J.; Smilde, A.K.

    2011-01-01

    Metabolomics studies aim at a better understanding of biochemical processes by studying relations between metabolites and between metabolites and other types of information (e.g., sensory and phenotypic features). The objectives of these studies are diverse, but the types of data generated and the

  16. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

    Science.gov (United States)

    Alonso, Cristina; Fernández-Ramos, David; Varela-Rey, Marta; Martínez-Arranz, Ibon; Navasa, Nicolás; Van Liempd, Sebastiaan M; Lavín Trueba, José L; Mayo, Rebeca; Ilisso, Concetta P; de Juan, Virginia G; Iruarrizaga-Lejarreta, Marta; delaCruz-Villar, Laura; Mincholé, Itziar; Robinson, Aaron; Crespo, Javier; Martín-Duce, Antonio; Romero-Gómez, Manuel; Sann, Holger; Platon, Julian; Van Eyk, Jennifer; Aspichueta, Patricia; Noureddin, Mazen; Falcón-Pérez, Juan M; Anguita, Juan; Aransay, Ana M; Martínez-Chantar, María Luz; Lu, Shelly C; Mato, José M

    2017-05-01

    Nonalcoholic fatty liver disease (NAFLD) is a consequence of defects in diverse metabolic pathways that involve hepatic accumulation of triglycerides. Features of these aberrations might determine whether NAFLD progresses to nonalcoholic steatohepatitis (NASH). We investigated whether the diverse defects observed in patients with NAFLD are caused by different NAFLD subtypes with specific serum metabolomic profiles, and whether these can distinguish patients with NASH from patients with simple steatosis. We collected liver and serum from methionine adenosyltransferase 1a knockout (MAT1A-KO) mice, which have chronically low levels of hepatic S-adenosylmethionine (SAMe) and spontaneously develop steatohepatitis, as well as C57Bl/6 mice (controls); the metabolomes of all samples were determined. We also analyzed serum metabolomes of 535 patients with biopsy-proven NAFLD (353 with simple steatosis and 182 with NASH) and compared them with serum metabolomes of mice. MAT1A-KO mice were also given SAMe (30 mg/kg/day for 8 weeks); liver samples were collected and analyzed histologically for steatohepatitis. Livers of MAT1A-KO mice were characterized by high levels of triglycerides, diglycerides, fatty acids, ceramides, and oxidized fatty acids, as well as low levels of SAMe and downstream metabolites. There was a correlation between liver and serum metabolomes. We identified a serum metabolomic signature associated with MAT1A-KO mice that also was present in 49% of the patients; based on this signature, we identified 2 NAFLD subtypes. We identified specific panels of markers that could distinguish patients with NASH from patients with simple steatosis for each subtype of NAFLD. Administration of SAMe reduced features of steatohepatitis in MAT1A-KO mice. In an analysis of serum metabolomes of patients with NAFLD and MAT1A-KO mice with steatohepatitis, we identified 2 major subtypes of NAFLD and markers that differentiate steatosis from NASH in each subtype. These might be

  17. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites

  18. Metabolomics of Clostridial Biofuel Production

    Energy Technology Data Exchange (ETDEWEB)

    Rabinowitz, Joshua D [Princeton Univ., NJ (United States); Aristilde, Ludmilla [Cornell Univ., Ithaca, NY (United States); Amador-Noguez, Daniel [Univ. of Wisconsin, Madison, WI (United States)

    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

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

    Science.gov (United States)

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

    2018-01-01

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

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

    OpenAIRE

    Fujimura, Yoshinori; Kurihara, Kana; Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

    2011-01-01

    BACKGROUND: Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. MET...

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

    Science.gov (United States)

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2017-08-24

    Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

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

    DEFF Research Database (Denmark)

    Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Nielsen, Henrik Bjørn

    2016-01-01

    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 individ......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...

  3. Metabolomic analysis of three Mollicute species.

    Directory of Open Access Journals (Sweden)

    Anna A Vanyushkina

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

  4. Data fusion in metabolomic cancer diagnostics

    DEFF Research Database (Denmark)

    Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco

    2013-01-01

    We have recently shown that fluorescence spectroscopy of plasma samples has promising abilities regarding early detection of colorectal cancer. In the present paper, these results were further developed by combining fluorescence with the biomarkers, CEA and TIMP-1 and traditional metabolomic...... measurements in the form of (1)H NMR spectroscopy. The results indicate that using an extensive profile established by combining such measurements together with the biomarkers is better than using single markers....

  5. Metabolomics for assessment of nutritional status.

    Science.gov (United States)

    Zivkovic, Angela M; German, J Bruce

    2009-09-01

    The current rise in diet-related diseases continues to be one of the most significant health problems facing both the developed and the developing world. The use of metabolomics - the accurate and comprehensive measurement of a significant fraction of important metabolites in accessible biological fluids - for the assessment of nutritional status is a promising way forward. The basic toolset, targets and knowledge are all being developed in the emerging field of metabolomics, yet important knowledge and technology gaps will need to be addressed in order to bring such assessment to practice. Dysregulation within the principal metabolic organs (e.g. intestine, adipose, skeletal muscle and liver) are at the center of a diet-disease paradigm that includes metabolic syndrome, type 2 diabetes and obesity. The assessment of both essential nutrient status and the more comprehensive systemic metabolic response to dietary, lifestyle and environmental influences (e.g. metabolic phenotype) are necessary for the evaluation of status in individuals that can identify the multiple targets of intervention needed to address metabolic disease. The first proofs of principle building the knowledge to bring actionable metabolic diagnostics to practice through metabolomics are now appearing.

  6. Global open data management in metabolomics.

    Science.gov (United States)

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

    2017-02-01

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

  7. The metabolome 18 years on: a concept comes of age.

    Science.gov (United States)

    Kell, Douglas B; Oliver, Stephen G

    2016-01-01

    The term 'metabolome' was introduced to the scientific literature in September 1998. To mark its 18-year-old 'coming of age', two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

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

    Science.gov (United States)

    Miller, Marion G

    2007-02-01

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

  9. A metabolomics study on human dietary intervention with apples

    DEFF Research Database (Denmark)

    Dragsted, L. O.; Kristensen, M.; Ravn-Haren, Gitte

    2009-01-01

    Metabolomics is a promising tool for searching out new biomarkers and the development of hypotheses in nutrition research. This chapter will describe the design of human dietary intervention studies where samples are collected for metabolomics analyses as well as the analytical issues and data...

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

    Science.gov (United States)

    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…

  11. Metabolomic Profiling of Prostate Cancer Progression During Active Surveillance

    Science.gov (United States)

    2012-10-01

    cancer or a history of transurethral resection of the prostate (TURP) for benign prostatic hypertrophy are excluded. Somewhat surprisingly...AD_________________ Award Number: W81XWH-11-1-0451 TITLE: Metabolomic Profiling of Prostate Cancer...29 September 2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Metabolomic Profiling of Prostate Cancer Progression During Active Surveillance 5b

  12. Plant metabolomics and its potential application for human nutrition

    NARCIS (Netherlands)

    Hall, R.D.; Brouwer, I.D.; Fitzgerald, M.A.

    2008-01-01

    With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental

  13. Gas chromatography mass spectrometry : key technology in metabolomics

    NARCIS (Netherlands)

    Koek, Maud Marijtje

    2009-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues. Gas chromatography coupled to mass spectrometry (GC-MS) is very suitable for metabolomics analysis, as it combines high separation power with

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

    Science.gov (United States)

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

    2017-09-26

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

  15. Tools for the functional interpretation of metabolomic experiments.

    Science.gov (United States)

    Chagoyen, Monica; Pazos, Florencio

    2013-11-01

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

  16. Error Analysis and Propagation in Metabolomics Data Analysis.

    Science.gov (United States)

    Moseley, Hunter N B

    2013-01-01

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

  17. Biological variation of Vanilla planifolia leaf metabolome.

    Science.gov (United States)

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

    2010-04-01

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

  18. A Metabolomic Signature of Acute Caloric Restriction.

    Science.gov (United States)

    Collet, Tinh-Hai; Sonoyama, Takuhiro; Henning, Elana; Keogh, Julia M; Ingram, Brian; Kelway, Sarah; Guo, Lining; Farooqi, I Sadaf

    2017-12-01

    The experimental paradigm of acute caloric restriction (CR) followed by refeeding (RF) can be used to study the homeostatic mechanisms that regulate energy homeostasis, which are relevant to understanding the adaptive response to weight loss. Metabolomics, the measurement of hundreds of small molecule metabolites, their precursors, derivatives, and degradation products, has emerged as a useful tool for the study of physiology and disease and was used here to study the metabolic response to acute CR. We used four ultra high-performance liquid chromatography-tandem mass spectrometry methods to characterize changes in carbohydrates, lipids, amino acids, and steroids in eight normal weight men at baseline, after 48 hours of CR (10% of energy requirements) and after 48 hours of ad libitum RF in a tightly controlled environment. We identified a distinct metabolomic signature associated with acute CR characterized by the expected switch from carbohydrate to fat utilization with increased lipolysis and β-fatty acid oxidation. We found an increase in ω-fatty acid oxidation and levels of endocannabinoids, which are known to promote food intake. These changes were reversed with RF. Several plasmalogen phosphatidylethanolamines (endogenous antioxidants) significantly decreased with CR (all P ≤ 0.0007). Additionally, acute CR was associated with an increase in the branched chain amino acids (all P ≤ 1.4 × 10-7) and dehydroepiandrosterone sulfate (P = 0.0006). We identified a distinct metabolomic signature associated with acute CR. Further studies are needed to characterize the mechanisms that mediate these changes and their potential contribution to the adaptive response to dietary restriction. Copyright © 2017 Endocrine Society

  19. Challenges of metabolomics in human gut microbiota research.

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-06-02

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

  1. Radiation Metabolomics: Current Status and Future Directions

    Directory of Open Access Journals (Sweden)

    Smrithi eSugumaran Menon

    2016-02-01

    Full Text Available Human exposure to ionizing radiation 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 ionizing radiation. 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.

  2. Integrated sampling procedure for metabolome analysis.

    Science.gov (United States)

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

    2006-01-01

    Metabolome analysis, the analysis of large sets of intracellular metabolites, has become an important systems analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s(-)(1) and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady-state metabolite analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h(-)(1).

  3. Serum Metabolomics of Burkitt Lymphoma Mouse Models.

    Directory of Open Access Journals (Sweden)

    Fengmin Yang

    Full Text Available Burkitt lymphoma (BL is a rare and highly aggressive type of non-Hodgkin lymphoma. The mortality rate of BL patients is very high due to the rapid growth rate and frequent systemic spread of the disease. A better understanding of the pathogenesis, more sensitive diagnostic tools and effective treatment methods for BL are essential. Metabolomics, an important aspect of systems biology, allows the comprehensive analysis of global, dynamic and endogenous biological metabolites based on their nuclear magnetic resonance (NMR and mass spectrometry (MS. It has already been used to investigate the pathogenesis and discover new biomarkers for disease diagnosis and prognosis. In this study, we analyzed differences of serum metabolites in BL mice and normal mice by NMR-based metabolomics. We found that metabolites associated with energy metabolism, amino acid metabolism, fatty acid metabolism and choline phospholipid metabolism were altered in BL mice. The diagnostic potential of the metabolite differences was investigated in this study. Glutamate, glycerol and choline had a high diagnostic accuracy; in contrast, isoleucine, leucine, pyruvate, lysine, α-ketoglutarate, betaine, glycine, creatine, serine, lactate, tyrosine, phenylalanine, histidine and formate enabled the accurate differentiation of BL mice from normal mice. The discovery of abnormal metabolism and relevant differential metabolites may provide useful clues for developing novel, noninvasive approaches for the diagnosis and prognosis of BL based on these potential biomarkers.

  4. Metabolomics, a promising approach to translational research in cardiology

    Directory of Open Access Journals (Sweden)

    Martino Deidda

    2015-12-01

    In this article, we will provide a description of metabolomics in comparison with other, better known “omics” disciplines such as genomics and proteomics. In addition, we will review the current rationale for the implementation of metabolomics in cardiology, its basic methodology and the available data from human studies in this discipline. The topics covered will delineate the importance of being able to use the metabolomic information to understand the mechanisms of diseases from the perspective of systems biology, and as a non-invasive approach to the diagnosis, grading and treatment of cardiovascular diseases.

  5. New approaches for metabolomics by mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Vertes, Akos [George Washington Univ., Washington, DC (United States)

    2017-07-10

    Small molecules constitute a large part of the world around us, including fossil and some renewable energy sources. Solar energy harvested by plants and bacteria is converted into energy rich small molecules on a massive scale. Some of the worst contaminants of the environment and compounds of interest for national security also fall in the category of small molecules. The development of large scale metabolomic analysis methods lags behind the state of the art established for genomics and proteomics. This is commonly attributed to the diversity of molecular classes included in a metabolome. Unlike nucleic acids and proteins, metabolites do not have standard building blocks, and, as a result, their molecular properties exhibit a wide spectrum. This impedes the development of dedicated separation and spectroscopic methods. Mass spectrometry (MS) is a strong contender in the quest for a quantitative analytical tool with extensive metabolite coverage. Although various MS-based techniques are emerging for metabolomics, many of these approaches include extensive sample preparation that make large scale studies resource intensive and slow. New ionization methods are redefining the range of analytical problems that can be solved using MS. This project developed new approaches for the direct analysis of small molecules in unprocessed samples, as well as pushed the limits of ultratrace analysis in volume limited complex samples. The projects resulted in techniques that enabled metabolomics investigations with enhanced molecular coverage, as well as the study of cellular response to stimuli on a single cell level. Effectively individual cells became reaction vessels, where we followed the response of a complex biological system to external perturbation. We established two new analytical platforms for the direct study of metabolic changes in cells and tissues following external perturbation. For this purpose we developed a novel technique, laser ablation electrospray

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

    Directory of Open Access Journals (Sweden)

    Carroll Adam J

    2010-07-01

    Full Text Available Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Description Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.. Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP their own data to the server for online processing via a novel raw data processing pipeline. Conclusions MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to

  7. Molecular identification in metabolomics using infrared ion spectroscopy

    NARCIS (Netherlands)

    Martens, J.; Berden, G.; van Outersterp, R.E.; Kluijtmans, L.A.J.; Engelke, U.F.; van Karnebeek, C.D.M.; Wevers, R.A.; Oomens, J.

    2017-01-01

    Small molecule identification is a continually expanding field of research and represents the core challenge in various areas of (bio) analytical science, including metabolomics. Here, we unequivocally differentiate enantiomeric N-acetylhexosamines in body fluids using infrared ion spectroscopy,

  8. Plant single-cell and single-cell-type metabolomics.

    Science.gov (United States)

    Misra, Biswapriya B; Assmann, Sarah M; Chen, Sixue

    2014-10-01

    In conjunction with genomics, transcriptomics, and proteomics, plant metabolomics is providing large data sets that are paving the way towards a comprehensive and holistic understanding of plant growth, development, defense, and productivity. However, dilution effects from organ- and tissue-based sampling of metabolomes have limited our understanding of the intricate regulation of metabolic pathways and networks at the cellular level. Recent advances in metabolomics methodologies, along with the post-genomic expansion of bioinformatics knowledge and functional genomics tools, have allowed the gathering of enriched information on individual cells and single cell types. Here we review progress, current status, opportunities, and challenges presented by single cell-based metabolomics research in plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    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...

  10. Microbial metabolomics with gas chromatography/mass spectrometry

    NARCIS (Netherlands)

    Koek, M.M.; Muilwijk, B.; Werf, M.J. van der; Hankemeier, T.

    2006-01-01

    An analytical method was set up suitable for the analysis of microbial metabolomes, consisting of an oximation and silylation derivatization reaction and subsequent analysis by gas chromatography coupled to mass spectrometry. Microbial matrixes contain many compounds that potentially interfere with

  11. A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it.

    Science.gov (United States)

    Spicer, Rachel A; Steinbeck, Christoph

    2018-01-01

    Data sharing is being increasingly required by journals and has been heralded as a solution to the 'replication crisis'. (i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals' policies to those that publish the most metabolomics papers. A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications. Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data. Further efforts are required to improve data sharing in metabolomics.

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

    Science.gov (United States)

    Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

    2012-01-01

    Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

  13. Metabolomic NMR fingerprinting: an exploratory and predictive tool

    OpenAIRE

    Lauri, Ilaria

    2014-01-01

    Metabolomics is the comprehensive assessment of low molecular weight organic metabolites within biological system. The identification and characterization of several chemical species, or metabolic fingerprinting, is an emergent approach in metabolomics field that provides a valuable “snapshot” of metabolic profiles. This approach is finding an increasing number of applications in many areas including cancer research, drug discovery and food science. The combined use of NMR spectroscopy, data ...

  14. Statistical methods for handling unwanted variation in metabolomics data

    OpenAIRE

    De Livera, Alysha M.; 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...

  15. Integrative metabolomics as emerging tool to study autophagy regulation

    Directory of Open Access Journals (Sweden)

    Sarah Stryeck

    2017-07-01

    Full Text Available Recent technological developments in metabolomics research have enabled in-depth characterization of complex metabolite mixtures in a wide range of biological, biomedical, environmental, agricultural, and nutritional research fields. Nuclear magnetic resonance spectroscopy and mass spectrometry are the two main platforms for performing metabolomics studies. Given their broad applicability and the systemic insight into metabolism that can be ob-tained it is not surprising that metabolomics becomes increasingly popular in basic biological research. In this review, we provide an overview on key me-tabolites, recent studies, and future opportunities for metabolomics in stud-ying autophagy regulation. Metabolites play a pivotal role in autophagy regulation and are therefore key targets for autophagy research. Given the recent success of metabolomics, it can be expected that metabolomics ap-proaches will contribute significantly to deciphering the complex regulatory mechanisms involved in autophagy in the near future and promote under-standing of autophagy and autophagy-related diseases in living cells and or-ganisms.

  16. Quality assurance procedures for mass spectrometry untargeted metabolomics. a review.

    Science.gov (United States)

    Dudzik, Danuta; Barbas-Bernardos, Cecilia; García, Antonia; Barbas, Coral

    2018-01-05

    Untargeted metabolomics, as a global approach, has already proven its great potential and capabilities for the investigation of health and disease, as well as the wide applicability for other research areas. Although great progress has been made on the feasibility of metabolomics experiments, there are still some challenges that should be faced and that includes all sources of fluctuations and bias affecting every step involved in multiplatform untargeted metabolomics studies. The identification and reduction of the main sources of unwanted variation regarding the pre-analytical, analytical and post-analytical phase of metabolomics experiments is essential to ensure high data quality. Nowadays, there is still a lack of information regarding harmonized guidelines for quality assurance as those available for targeted analysis. In this review, sources of variations to be considered and minimized along with methodologies and strategies for monitoring and improvement the quality of the results are discussed. The given information is based on evidences from different groups among our own experiences and recommendations for each stage of the metabolomics workflow. The comprehensive overview with tools presented here might serve other researchers interested in monitoring, controlling and improving the reliability of their findings by implementation of good experimental quality practices in the untargeted metabolomics study. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Impact of dietary polydextrose fiber on the human gut metabolome.

    Science.gov (United States)

    Lamichhane, Santosh; Yde, Christian C; Forssten, Sofia; Ouwehand, Arthur C; Saarinen, Markku; Jensen, Henrik Max; Gibson, Glenn R; Rastall, Robert; Fava, Francesca; Bertram, Hanne Christine

    2014-10-08

    The aim of the present study was to elucidate the impact of polydextrose PDX an soluble fiber, on the human fecal metabolome by high-resolution nuclear magnetic resonance (NMR) spectroscopy-based metabolomics in a dietary intervention study (n = 12). Principal component analysis (PCA) revealed a strong effect of PDX consumption on the fecal metabolome, which could be mainly ascribed to the presence of undigested fiber and oligosaccharides formed from partial degradation of PDX. Our results demonstrate that NMR-based metabolomics is a useful technique for metabolite profiling of feces and for testing compliance to dietary fiber intake in such trials. In addition, novel associations between PDX and the levels of the fecal metabolites acetate and propionate could be identified. The establishment of a correlation between the fecal metabolome and levels of Bifidobacterium (R(2) = 0.66) and Bacteroides (R(2) = 0.46) demonstrates the potential of NMR-based metabolomics to elucidate metabolic activity of bacteria in the gut.

  18. Mass spectrometry-based metabolomics for tuberculosis meningitis.

    Science.gov (United States)

    Zhang, Peixu; Zhang, Weiguanliu; Lang, Yue; Qu, Yan; Chu, Fengna; Chen, Jiafeng; Cui, Li

    2018-04-18

    Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described. Copyright © 2018. Published by Elsevier B.V.

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

    Science.gov (United States)

    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 .

  20. Metabolomics study of Populus type propolis.

    Science.gov (United States)

    Anđelković, Boban; Vujisić, Ljubodrag; Vučković, Ivan; Tešević, Vele; Vajs, Vlatka; Gođevac, Dejan

    2017-02-20

    Herein, we propose rapid and simple spectroscopic methods to determine the chemical composition of propolis derived from various Populus species using a metabolomics approach. In order to correlate variability in Populus type propolis composition with the altitude of its collection, NMR, IR, and UV spectroscopy followed by OPLS was conducted. The botanical origin of propolis was established by comparing propolis spectral data to those of buds of various Populus species. An O2PLS method was utilized to integrate two blocks of data. According to OPLS and O2PLS, the major compounds in propolis samples, collected from temperate continental climate above 500m, were phenolic glycerides originating from P. tremula buds. Flavonoids were predominant in propolis samples collected below 400m, originating from P. nigra and P. x euramericana buds. Samples collected at 400-500m were of mixed origin, with variable amounts of all detected metabolites. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Analyses of tropistic responses using metabolomics.

    Science.gov (United States)

    Millar, Katherine D L; Kiss, John Z

    2013-01-01

    Characterization of phototropism and gravitropism has been through gene expression studies, assessment of curvature response, and protein expression experiments. To our knowledge, the current study is the first to determine how the metabolome, the complete set of small-molecule metabolites within a plant, is impacted during these tropisms. We have determined the metabolic profile of plants during gravitropism and phototropism. Seedlings of Arabidopsis thaliana wild type (WT) and phyB mutant were exposed to unidirectional light (red or blue) or reoriented to induce a tropistic response, and small-molecule metabolites were assayed and quantified. A subset of the WT was analyzed using microarray experiments to obtain gene profiling data. Analyses of the metabolomic data using principal component analysis showed a common profile in the WT during the different tropistic curvatures, but phyB mutants produced a distinctive profile for each tropism. Interestingly, the gravity treatment elicited the greatest changes in gene expression of the WT, followed by blue light, then by red light treatments. For all tropisms, we identified genes that were downregulated by a large magnitude in carbohydrate metabolism and secondary metabolism. These included ATCSLA15, CELLULOSE SYNTHASE-LIKE, and ATCHS/SHS/TT4, CHALCONE SYNTHASE. In addition, genes involved in amino acid biosynthesis were strongly upregulated, and these included THA1 (THREONINE ALDOLASE 1) and ASN1 (DARK INDUCIBLE asparagine synthase). We have established the first metabolic profile of tropisms in conjunction with transcriptomic analyses. This approach has been useful in characterizing the similarities and differences in the molecular mechanisms involved with phototropism and gravitropism.

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

    NARCIS (Netherlands)

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

    2006-01-01

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

  3. Can NMR solve some significant challenges in metabolomics?

    Science.gov (United States)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

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

  4. Metabolomics for functional genomics, systems biology, and biotechnology.

    Science.gov (United States)

    Saito, Kazuki; Matsuda, Fumio

    2010-01-01

    Metabolomics now plays a significant role in fundamental plant biology and applied biotechnology. Plants collectively produce a huge array of chemicals, far more than are produced by most other organisms; hence, metabolomics is of great importance in plant biology. Although substantial improvements have been made in the field of metabolomics, the uniform annotation of metabolite signals in databases and informatics through international standardization efforts remains a challenge, as does the development of new fields such as fluxome analysis and single cell analysis. The principle of transcript and metabolite cooccurrence, particularly transcriptome coexpression network analysis, is a powerful tool for decoding the function of genes in Arabidopsis thaliana. This strategy can now be used for the identification of genes involved in specific pathways in crops and medicinal plants. Metabolomics has gained importance in biotechnology applications, as exemplified by quantitative loci analysis, prediction of food quality, and evaluation of genetically modified crops. Systems biology driven by metabolome data will aid in deciphering the secrets of plant cell systems and their application to biotechnology.

  5. [Development of Plant Metabolomics and Medicinal Plant Genomics].

    Science.gov (United States)

    Saito, Kazuki

    2018-01-01

     A variety of chemicals produced by plants, often referred to as 'phytochemicals', have been used as medicines, food, fuels and industrial raw materials. Recent advances in the study of genomics and metabolomics in plant science have accelerated our understanding of the mechanisms, regulation and evolution of the biosynthesis of specialized plant products. We can now address such questions as how the metabolomic diversity of plants is originated at the levels of genome, and how we should apply this knowledge to drug discovery, industry and agriculture. Our research group has focused on metabolomics-based functional genomics over the last 15 years and we have developed a new research area called 'Phytochemical Genomics'. In this review, the development of a research platform for plant metabolomics is discussed first, to provide a better understanding of the chemical diversity of plants. Then, representative applications of metabolomics to functional genomics in a model plant, Arabidopsis thaliana, are described. The extension of integrated multi-omics analyses to non-model specialized plants, e.g., medicinal plants, is presented, including the identification of novel genes, metabolites and networks for the biosynthesis of flavonoids, alkaloids, sulfur-containing metabolites and terpenoids. Further, functional genomics studies on a variety of medicinal plants is presented. I also discuss future trends in pharmacognosy and related sciences.

  6. LC-MS-BASED METABOLOMICS OF XENOBIOTIC-INDUCED TOXICITIES

    Directory of Open Access Journals (Sweden)

    Chi Chen

    2013-01-01

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

  7. Mixing omics: combining genetics and metabolomics to study rheumatic diseases.

    Science.gov (United States)

    Menni, Cristina; Zierer, Jonas; Valdes, Ana M; Spector, Tim D

    2017-03-01

    Metabolomics is an exciting field in systems biology that provides a direct readout of the biochemical activities taking place within an individual at a particular point in time. Metabolite levels are influenced by many factors, including disease status, environment, medications, diet and, importantly, genetics. Thanks to their dynamic nature, metabolites are useful for diagnosis and prognosis, as well as for predicting and monitoring the efficacy of treatments. At the same time, the strong links between an individual's metabolic and genetic profiles enable the investigation of pathways that underlie changes in metabolite levels. Thus, for the field of metabolomics to yield its full potential, researchers need to take into account the genetic factors underlying the production of metabolites, and the potential role of these metabolites in disease processes. In this Review, the methodological aspects related to metabolomic profiling and any potential links between metabolomics and the genetics of some of the most common rheumatic diseases are described. Links between metabolomics, genetics and emerging fields such as the gut microbiome and proteomics are also discussed.

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

    Science.gov (United States)

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

    2015-01-01

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

  9. Genetic basis of metabolome variation in yeast.

    Directory of Open Access Journals (Sweden)

    Jeffrey S Breunig

    2014-03-01

    Full Text Available 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.

  10. Deconstructing the pig sex metabolome: Targeted metabolomics in heavy pigs revealed sexual dimorphisms in plasma biomarkers and metabolic pathways.

    Science.gov (United States)

    Bovo, S; Mazzoni, G; Calò, D G; Galimberti, G; Fanelli, F; Mezzullo, M; Schiavo, G; Scotti, E; Manisi, A; Samoré, A B; Bertolini, F; Trevisi, P; Bosi, P; Dall'Olio, S; Pagotto, U; Fontanesi, L

    2015-12-01

    Metabolomics has opened new possibilities to investigate metabolic differences among animals. In this study, we applied a targeted metabolomic approach to deconstruct the pig sex metabolome as defined by castrated males and entire gilts. Plasma from 545 performance-tested Italian Large White pigs (172 castrated males and 373 females) sampled at about 160 kg live weight were analyzed for 186 metabolites using the Biocrates AbsoluteIDQ p180 Kit. After filtering, 132 metabolites (20 AA, 11 biogenic amines, 1 hexose, 13 acylcarnitines, 11 sphingomyelins, 67 phosphatidylcholines, and 9 lysophosphatidylcholines) were retained for further analyses. The multivariate approach of the sparse partial least squares discriminant analysis was applied, together with a specifically designed statistical pipeline, that included a permutation test and a 10 cross-fold validation procedure that produced stability and effect size statistics for each metabolite. Using this approach, we identified 85 biomarkers (with metabolites from all analyzed chemical families) that contributed to the differences between the 2 groups of pigs ( metabolic shift in castrated males toward energy storage and lipid production. Similar general patterns were observed for most sphingomyelins, phosphatidylcholines, and lysophosphatidylcholines. Metabolomic pathway analysis and pathway enrichment identified several differences between the 2 sexes. This metabolomic overview opened new clues on the biochemical mechanisms underlying sexual dimorphism that, on one hand, might explain differences in terms of economic traits between castrated male pigs and entire gilts and, on the other hand, could strengthen the pig as a model to define metabolic mechanisms related to fat deposition.

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

    Directory of Open Access Journals (Sweden)

    Jun Hong

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    DEFF Research Database (Denmark)

    Gonzalez-Franquesa, Alba; Burkart, Alison M; Isganaitis, Elvira

    2016-01-01

    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......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....... 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...

  14. Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks.

    Science.gov (United States)

    Fearnley, Liam G; Inouye, Michael

    2016-10-01

    Metabolomics is becoming feasible for population-scale studies of human disease. In this review, we survey epidemiological studies that leverage metabolomics and multi-omics to gain insight into disease mechanisms. We outline key practical, technological and analytical limitations while also highlighting recent successes in integrating these data. The use of multi-omics to infer reaction rates is discussed as a potential future direction for metabolomics research, as a means of identifying biomarkers as well as inferring causality. Furthermore, we highlight established analysis approaches as well as simulation-based methods currently used in single- and multi-cell levels in systems biology. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

  15. Serum Metabolomics in Rats after Acute Paraquat Poisoning.

    Science.gov (United States)

    Wang, Zhiyi; Ma, Jianshe; Zhang, Meiling; Wen, Congcong; Huang, Xueli; Sun, Fa; Wang, Shuanghu; Hu, Lufeng; Lin, Guanyang; Wang, Xianqin

    2015-01-01

    Paraquat is one of the most widely used herbicides in the world and is highly toxic to humans and animals. In this study, we developed a serum metabolomic method based on GC/MS to evaluate the effects of acute paraquat poisoning on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the level of octadecanoic acid, L-serine, L-threonine, L-valine, and glycerol in the acute paraquat poisoning group (36 mg/kg) increased, while the levels of hexadecanoic acid, D-galactose, and decanoic acid decreased. These findings provide an overview of systematic responses to paraquat exposure and metabolomic insight into the toxicological mechanism of paraquat. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate the mechanism of acute paraquat poisoning through the exploration of biomarkers.

  16. Metabolomic-based identification of clusters that reflect dietary patterns.

    Science.gov (United States)

    Gibbons, Helena; Carr, Eibhlin; McNulty, Breige A; Nugent, Anne P; Walton, Janette; Flynn, Albert; Gibney, Michael J; Brennan, Lorraine

    2017-10-01

    Classification of subjects into dietary patterns generally relies on self-reporting dietary data which are prone to error. The aim of the present study was to develop a model for objective classification of people into dietary patterns based on metabolomic data. Dietary and urinary metabolomic data from the National Adult Nutrition Survey (NANS) was used in the analysis (n = 567). Two-step cluster analysis was applied to the urinary data to identify clusters. The subsequent model was used in an independent cohort to classify people into dietary patterns. Two distinct dietary patterns were identified. Cluster 1 was characterized by significantly higher intakes of breakfast cereals, low fat and skimmed milks, potatoes, fruit, fish and fish dishes (p patterns based on metabolomics data. Future applications of this approach could be developed for rapid and objective assignment of subjects into dietary patterns. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

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

    2016-06-01

    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.

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

    Science.gov (United States)

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

    2017-01-01

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

  19. Medicinal Plants: A Public Resource for Metabolomics and Hypothesis Development

    Directory of Open Access Journals (Sweden)

    Eve Syrkin Wurtele

    2012-11-01

    Full Text Available 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

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

    Science.gov (United States)

    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

    2012-11-21

    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

  1. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    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.

  3. Metabolome analysis - mass spectrometry and microbial primary metabolites

    DEFF Research Database (Denmark)

    Højer-Pedersen, Jesper Juul

    2008-01-01

    increased amounts of data generated in high resolution. One major limitation though is the digestion of data coverting the information into a format that can be interpreted in a biological context and take metabolomics beyond the principle of guilt-byassociation. To analyze the data there is a general need....... Statistical analysis of the footprinting data revealed discriminating ions, which could be assigned using the in silico metabolome. By this approach metabolic footprinting can advance from a classification method that is used to derive biological information based on guilt-by-association, to a tool...

  4. Metabolomic Biomarkers in the Progression to Type 1 Diabetes

    DEFF Research Database (Denmark)

    Overgaard, Anne Julie; Kaur, Simranjeet; Pociot, Flemming

    2016-01-01

    Metabolomics is the snapshot of all detectable metabolites and lipids in biological materials and has potential in reflecting genetic and environmental factors contributing to the development of complex diseases, such as type 1 diabetes. The progression to seroconversion to development of type 1...... diabetes has been studied using this technique, although in relatively small cohorts and at limited time points. Overall, three observations have been consistently reported; phospholipids at birth are lower in children developing type 1 diabetes early in childhood, methionine levels are lower in children...... at seroconversion, and triglycerides are increased at seroconversion and associated to microbiome diversity, indicating an association between the metabolome and microbiome in type 1 diabetes progression....

  5. [Application and research advances of metabolomics in the field of orthopedics].

    Science.gov (United States)

    Sun, Zhijian; Qiu, Guixing; Zhao, Yu

    2015-06-01

    Metabolomics is a subject of systematic, qualitative and quantitative analysis of all metabolites in all organisms, which is applied to finding biomarkers and studying pathogenesis of diseases. Study procedures of metabolomics include data acquisition by spectroscopic/spectrometric techniques, multivariate statistical analysis and projection of the acquired metabolomic information. In recent years, metabolomics have gained popularity in orthopedic field. Metabolomic study of osteoarthritis was firstly conducted and widely developed. Metabolite profiles of different samples, including serum/plasma, urine, synovial fluid and synovial tissue, were studied and dozens of differential metabolites and several disturbed metabolic pathways were found. In addition, metabolomic studies of osteoporosis, ankylosing spondylitis and bone tumors were also conducted, which identified many potential biomarkers and made further understanding of pathogenesis of corresponding disease. However, metabolomic studies in orthopedic field just begin. More orthopedic diseases will be researched thank to the satisfactory results of previous reports.

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

    Science.gov (United States)

    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

  7. Bagged K-means clustering of metabolome data

    NARCIS (Netherlands)

    Hageman, J. A.; van den Berg, R. A.; Westerhuis, J. A.; Hoefsloot, H. C. J.; Smilde, A. K.

    2006-01-01

    Clustering of metabolomics data can be hampered by noise originating from biological variation, physical sampling error and analytical error. Using data analysis methods which are not specially suited for dealing with noisy data will yield sub optimal solutions. Bootstrap aggregating (bagging) is a

  8. Advances in Ginkgo biloba research: Genomics and metabolomics ...

    African Journals Online (AJOL)

    The maiden hair tree, Ginkgo biloba is very much resistant to a wide spectrum of biotic and abiotic stress conditions. It hardly seems to be attacked by any herbivore or microbe. In spite of its strong resistant nature to wide stress conditions, only little research has been carried out at genomics and metabolomics level to ...

  9. Effect of sleep deprivation on the human metabolome

    NARCIS (Netherlands)

    S.K. Davies (Sarah); J.E. Ang (Joo Ern); V.L. Revell (Victoria); B. Holmes (Ben); A. Mann (Anuska); F.P. Robertson (Francesca); N. Cui (Nanyi); B. Middleton (Benita); K. Ackermann (Katrin); M.H. Kayser (Manfred); A.E. Thumser (Alfred); P. Raynaud (Philippe); D.J. Skene (Debra)

    2014-01-01

    textabstractSleep restriction and circadian clock disruption are associated with metabolic disorders such as obesity, insulin resistance, and diabetes. The metabolic pathways involved in human sleep, however, have yet to be investigatedwith the use of a metabolomics approach. Here we have used

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

    Science.gov (United States)

    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...

  11. Reflections on univariate and multivariate analysis of metabolomics data

    NARCIS (Netherlands)

    Saccenti, E.; Hoefsloot, H.C.J.; Smilde, A.K.; Westerhuis, J.A.; Hendriks, M.M.W.B.

    2014-01-01

    Metabolomics experiments usually result in a large quantity of data. Univariate and multivariate analysis techniques are routinely used to extract relevant information from the data with the aim of providing biological knowledge on the problem studied. Despite the fact that statistical tools like

  12. Metabolomics and food processing: From semolina to pasta

    CSIR Research Space (South Africa)

    Beleggia, R

    2011-09-01

    Full Text Available Agric Food Chem. 2011 Sep 14;59(17):9366-77. Epub 2011 Aug 16. Metabolomics and food processing: from semolina to pasta. Beleggia R, Platani C, Papa R, Di Chio A, Barros E, Mashaba C, Wirth J, Fammartino A, Sautter C, Conner S, Rauscher J, Stewart D...

  13. Genetic algorithm based two-mode clustering of metabolomics data

    NARCIS (Netherlands)

    Hageman, J.A.; van den Berg, R.A.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2008-01-01

    Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering

  14. Sample preparation procedures utilized in microbial metabolomics: An overview.

    Science.gov (United States)

    Patejko, Małgorzata; Jacyna, Julia; Markuszewski, Michał J

    2017-02-01

    Bacteria are remarkably diverse in terms of their size, structure and biochemical properties. Due to this fact, it is hard to develop a universal method for handling bacteria cultures during metabolomic analysis. The choice of suitable processing methods constitutes a key element in any analysis, because only appropriate selection of procedures may provide accurate results, leading to reliable conclusions. Because of that, every analytical experiment concerning bacteria requires individually and very carefully planned research methodology. Although every study varies in terms of sample preparation, there are few general steps to follow while planning experiment, like sampling, separation of cells from growth medium, stopping their metabolism and extraction. As a result of extraction, all intracellular metabolites should be washed out from cell environment. What is more, extraction method utilized cannot cause any chemical decomposition or degradation of the metabolome. Furthermore, chosen extraction method should correlate with analytical technique, so it will not disturb or prolong following sample preparation steps. For those reasons, we observe a need to summarize sample preparation procedures currently utilized in microbial metabolomic studies. In the presented overview, papers concerning analysis of extra- and intracellular metabolites, published over the last decade, have been discussed. Presented work gives some basic guidelines that might be useful while planning experiments in microbial metabolomics. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Application of Metabolomics to Study Effects of Bariatric Surgery

    Directory of Open Access Journals (Sweden)

    Paulina Samczuk

    2018-01-01

    Full Text Available Bariatric surgery was born in the 1950s at the University of Minnesota. From this time, it continues to evolve and, by the same token, gives new or better possibilities to treat not only obesity but also associated comorbidities. Metabolomics is also a relatively young science discipline, and similarly, it shows great potential for the comprehensive study of the dynamic alterations of the metabolome. It has been widely used in medicine, biology studies, biomarker discovery, and prognostic evaluations. Currently, several dozen metabolomics studies were performed to study the effects of bariatric surgery. LC-MS and NMR are the most frequently used techniques to study main effects of RYGB or SG. Research has yield many interesting results involving not only clinical parameters but also molecular modulations. Detected changes pertain to amino acid, lipids, carbohydrates, or gut microbiota alterations. It proves that including bariatric surgery to metabolic surgery is warranted. However, many molecular modulations after those procedures remain unexplained. Therefore, application of metabolomics to study this field seems to be a proper solution. New findings can suggest new directions of surgery technics modifications, contribute to broadening knowledge about obesity and diseases related to it, and perhaps develop nonsurgical methods of treatment in the future.

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

    Science.gov (United States)

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

    2017-11-13

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

  17. Metabolomic changes of Brassica rapa under biotic stress

    NARCIS (Netherlands)

    Abdel-Farid Ali, Ibrahim Bayoumi

    2009-01-01

    It has been shown by this thesis that plant metabolomics is a promising tool for studying the interaction between B. rapa and pathogenic fungi. It gives a picture of the plant metabolites during the interaction. Brassica rapa has many defense related compounds such as glucosinolates, IAA,

  18. Metabolomics: Insulin Resistance and Type 2 Diabetes Mellitus

    Science.gov (United States)

    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...

  19. Alterations of red blood cell metabolome in overhydrated hereditary stomatocytosis.

    NARCIS (Netherlands)

    Darghouth, D.; Koehl, B.; Heilier, J.F.; Madalinski, G.; Bovee, P.H.; Bosman, G.J.C.G.M.; Delaunay, J.; Junot, C.; Romeo, P.H.

    2011-01-01

    Overhydrated hereditary stomatocytosis, clinically characterized by hemolytic anemia, is a rare disorder of the erythrocyte membrane permeability to monovalent cations, associated with mutations in the Rh-associated glycoprotein gene. We assessed the red blood cell metabolome of 4 patients with this

  20. Preliminary metabolomics analysis of placenta in maternal obesity.

    Science.gov (United States)

    Fattuoni, Claudia; Mandò, Chiara; Palmas, Francesco; Anelli, Gaia Maria; Novielli, Chiara; Parejo Laudicina, Estefanìa; Savasi, Valeria Maria; Barberini, Luigi; Dessì, Angelica; Pintus, Roberta; Fanos, Vassilios; Noto, Antonio; Cetin, Irene

    2018-01-01

    Metabolomics identifies phenotypical groups with specific metabolic profiles, being increasingly applied to several pregnancy conditions. This is the first preliminary study analyzing placental metabolomics in normal weight (NW) and obese (OB) pregnancies. Twenty NW (18.5 ≤ BMI< 25 kg/m 2 ) and eighteen OB (BMI≥ 30 kg/m 2 ) pregnancies were studied. Placental biopsies were collected at elective caesarean section. Metabolites extraction method was optimized for hydrophilic and lipophilic phases, then analyzed with GC-MS. Univariate and PLS-DA multivariate analysis were applied. Univariate analysis showed increased uracil levels while multivariate PLS-DA analysis revealed lower levels of LC-PUFA derivatives in the lipophilic phase and several metabolites with significantly different levels in the hydrophilic phase of OB vs NW. Placental metabolome analysis of obese pregnancies showed differences in metabolites involved in antioxidant defenses, nucleotide production, as well as lipid synthesis and energy production, supporting a shift towards higher placental metabolism. OB placentas also showed a specific fatty acids profile suggesting a disruption of LC-PUFA biomagnification. This study can lay the foundation to further metabolomic placental characterization in maternal obesity. Metabolic signatures in obese placentas may reflect changes occurring in the intrauterine metabolic environment, which may affect the development of adult diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2018-01-01

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

  2. Metabolomic characteristics of Catharanthus roseus plants in time and space

    NARCIS (Netherlands)

    Qifang, Pan; Qifang, Pan

    2014-01-01

    The thesis aims at combining metabolomics with other methods to investigate the regulation of the TIA biosynthesis and how this is connected with other pathways and the plant’s physiology and development. It reviews the biosynthesis studies of Catharanthus roseus. An HPLC method is described for

  3. The effects of gliadin on urine metabolome in mice

    DEFF Research Database (Denmark)

    Roager, Henrik Munch; Zhang, Li; Frandsen, Henrik Lauritz

    in the gliadin mice. Also, Maillard reaction products and β-oxidized tocopherols were observed in higher levels in the urine of gliadin mice, suggesting increased oxidative stress in the gliadin mice. Indisputably, gliadin affected the urine metabolome. However, the mechanisms behind the observed metabolite...

  4. Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars.

    Directory of Open Access Journals (Sweden)

    Yoshinori Fujimura

    Full Text Available BACKGROUND: Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity of diverse Japanese green tea cultivars. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC in human umbilical vein endothelial cells (HUVECs. This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6 and Sunrouge (SR strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS. Multivariate statistical analyses, principal component analysis (PCA and orthogonal partial least-squares-discriminant analysis (OPLS-DA, revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive

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

    Science.gov (United States)

    Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

    2011-01-01

    Background Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. Methodology/Principal Findings We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract

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

    Science.gov (United States)

    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. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Arnald eAlonso

    2015-03-01

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

  8. Proteomics and Metabolomics: two emerging areas for legume improvement

    Directory of Open Access Journals (Sweden)

    Abirami eRamalingam

    2015-12-01

    Full Text Available The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important source 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 signalling 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 signalling in legumes. In

  9. Metabolomics and its integration with systems biology: PSI 2014 conference panel discussion report.

    Science.gov (United States)

    More, Tushar; RoyChoudhury, Sourav; Gollapalli, Kishore; Patel, Sandip K; Gowda, Harsha; Chaudhury, Koel; Rapole, Srikanth

    2015-09-08

    Metabolomics, being a relatively new field, is facing multiple challenges related to data acquisition and interpretation, reproducibility across analytical platforms, integration with other omics approaches and translation into theragnostic biomarkers. There is an immediate need to overcome these challenges in order to make metabolomics more useful and reliable in terms of improving our current understanding of disease biology and help in developing predictive biomarkers. Researchers interested in metabolomics gathered for a panel discussion on 'Metabolomics and its integration with systems biology' during the 6th Annual Meeting of Proteomics Society-India and International Conference on "Proteomics from Discovery to Function" held at the Indian Institute of Technology, Bombay from December 7-9, 2014. The panel discussed various challenges related to metabolomics and also proposed several effective solutions for optimum implementation of metabolomics in clinical practice. The key areas of panel discussion were improvement in metabolite databases with comprehensive spectral libraries, need for extensive bioinformatics tools for integrative approaches and serious considerations for clinical validation of the biomarkers for the successful implementation of metabolomics in clinics. Information drafted in this report is significant for researchers working in metabolomics field to overcome the challenges and successful implementation of metabolomics in clinical practice. This article is part of a special issue titled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2017-07-04

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

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

    International Nuclear Information System (INIS)

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

  12. PROM and Labour Effects on Urinary Metabolome: A Pilot Study

    Directory of Open Access Journals (Sweden)

    Alessandra Meloni

    2018-01-01

    Full Text Available Since pathologies and complications occurring during pregnancy and/or during labour may cause adverse outcomes for both newborns and mothers, there is a growing interest in metabolomic applications on pregnancy investigation. In fact, metabolomics has proved to be an efficient strategy for the description of several perinatal conditions. In particular, this study focuses on premature rupture of membranes (PROM in pregnancy at term. For this project, urine samples were collected at three different clinical conditions: out of labour before PROM occurrence (Ph1, out of labour with PROM (Ph2, and during labour with PROM (Ph3. GC-MS analysis, followed by univariate and multivariate statistical analysis, was able to discriminate among the different classes, highlighting the metabolites most involved in the discrimination.

  13. Polyphenol metabolomics of twenty Italian red grape varieties

    Directory of Open Access Journals (Sweden)

    Bavaresco Luigi

    2016-01-01

    Full Text Available “Suspect screening analysis”method to study grape metabolomics, was performed. This method is a middle-way “targeted” and “untargeted”approach aiming at identifying the largest number of metabolites in grape samples. A new database of putative grape and wine metabolites (GrapeMetabolomics, which currently contains around 1,100 compounds, was constructed by CREA at Conegliano. By performing high-resolution mass spectrometry analysis of the grape extract in both positive and negative ionization mode, averaging 320-450 putative compounds are identified. Most of them are grape polyphenols, such as anthocyanins, flavonols and stilbene derivatives. By performing PCA and Cluster Analysis the composition in anthocyanins and flavonols of 20 Italian red grape varieties, was studied.

  14. Metabolomics of Δ9-tetrahydrocannabinol: implications in toxicity.

    Science.gov (United States)

    Dinis-Oliveira, Ricardo Jorge

    2016-01-01

    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.

  15. Metabolome Consistency: Additional Parazoanthines from the Mediterranean Zoanthid Parazoanthus Axinellae

    Directory of Open Access Journals (Sweden)

    Coralie Audoin

    2014-05-01

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

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

    Science.gov (United States)

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

    2014-05-30

    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.

  17. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    Metabolomics is part of systems biology and a rapidly evolving field. It is a tool to analyze multiple metabolic changes in biofluids and tissues and aims at determining biomarkers in the metabolism. LC-MS (liquid chromatography – mass spectrometry), GC-MS (gas chromatography – mass spectrometry...... the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were......, potential biomarkers from LC-MS and NMR data could be detected and the relationships among the measurement variables of both analytical methods could be studied. Detection of potential biomarkers is followed up by an identification process through online metabolite and pathway databases. This process...

  18. Metabolomics Insights Into Pathophysiological Mechanisms of Interstitial Cystitis

    Science.gov (United States)

    Fiehn, Oliver

    2014-01-01

    Interstitial cystitis (IC), also known as painful bladder syndrome or bladder pain syndrome, is a chronic lower urinary tract syndrome characterized by pelvic pain, urinary urgency, and increased urinary frequency in the absence of bacterial infection or identifiable clinicopathology. IC can lead to long-term adverse effects on the patient's quality of life. Therefore, early diagnosis and better understanding of the mechanisms underlying IC are needed. Metabolomic studies of biofluids have become a powerful method for assessing disease mechanisms and biomarker discovery, which potentially address these important clinical needs. However, limited intensive metabolic profiles have been elucidated in IC. The article is a short review on metabolomic analyses that provide a unique fingerprint of IC with a focus on its use in determining a potential diagnostic biomarker associated with symptoms, a response predictor of therapy, and a prognostic marker. PMID:25279237

  19. The MetaboLights repository: curation challenges in metabolomics

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  1. The role of metabolomics in tuberculosis treatment research.

    Science.gov (United States)

    Luies, Laneke; du Preez, Ilse; Loots, Du Toit

    2017-11-01

    Despite the fact that tuberculosis (TB) is a curable disease, it still results in approximately 1.8 million deaths annually. Various inadequacies in the current TB treatment strategies are major contributors to this high disease prevalence, including the long duration of therapy, the severe side effects associated with TB drugs, treatment failure due to drug resistance, post-treatment disease relapse, and HIV co-infection. In this review, we describe how metabolomics has contributed toward better explaining/elucidating the mechanisms of drug action/metabolism, drug toxicity and microbial drug resistance, and how metabolite biomarkers may serve as prognostic indicators for predicting treatment outcome as well as for the development of new TB drugs. We also discuss possible future contributions that metabolomics can make toward more efficient, less toxic TB treatment strategies.

  2. An untargeted metabolomic assessment of cocoa beans during fermentation

    OpenAIRE

    Mayorga Gross, Ana Lucía; Quirós Guerrero, Luis Manuel; Fourny, G.; Vaillant Barka, Fabrice

    2016-01-01

    Fermentation is a critical step in the processing of high quality cocoa; however, the biochemistry behind is still not well understood at a molecular level. In this research, using a non-targeted approach, the main metabolomic changes that occur throughout the fermentation process were explored. Genetically undefined cocoa varieties from Trinidad and Tobago (n = 3), Costa Rica (n = 1) and one clone IMC-67 (n = 3) were subjected to spontaneous fermentation using farm-based and pilot plant cont...

  3. Metabolome Consistency: Additional Parazoanthines from the Mediterranean Zoanthid Parazoanthus Axinellae

    OpenAIRE

    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 absolu...

  4. Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress

    Science.gov (United States)

    2017-10-01

    continuing work on the role of stress in ovarian cancer development indicates that chronic stress may increase risk of developing ovarian cancer. 15...advice. Dr. Poole was also a peer mentor to three post-doctoral fellows working in the CDNM. Results from the ongoing research in the role of stress in...AWARD NUMBER: W81XWH-13-1-0493 TITLE: Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress PRINCIPAL INVESTIGATOR

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

    Directory of Open Access Journals (Sweden)

    Cseke Leland J

    2011-05-01

    Full Text Available Abstract 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.

  6. Metabolomics to unveil and understand phenotypic diversity between pathogen populations.

    Directory of Open Access Journals (Sweden)

    Ruben t'Kindt

    Full Text Available Leishmaniasis is a debilitating disease caused by the parasite Leishmania. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study Leishmania donovani parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for L. donovani to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant L. donovani isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured in vitro and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of Leishmania and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical Leishmania isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.

  7. A metabolomics approach to thrips resistance in tomato

    OpenAIRE

    Romero González, Roman Rodolfo

    2011-01-01

    Western flower thrips is one of the most serious crop pests worldwide. Its control relies mainly on pesticides whose excessive use leads to resistance development and environmental contamination. As an alternative, in this thesis host-plant resistance in wild and domesticated tomatoes was studied using metabolomics. Different resistance mechanisms in which mechanical and chemical defenses work coordinately to fend thrips off were observed and contrasted. In all cases resistance was associated...

  8. NMR-based metabolomics of mammalian cell and tissue cultures

    International Nuclear Information System (INIS)

    Aranibar, Nelly; Borys, Michael; Mackin, Nancy A.; Ly, Van; Abu-Absi, Nicholas; Abu-Absi, Susan; Niemitz, Matthias; Schilling, Bernhard; Li, Zheng Jian; Brock, Barry; Russell, Reb J.; Tymiak, Adrienne; Reily, Michael D.

    2011-01-01

    NMR spectroscopy was used to evaluate growth media and the cellular metabolome in two systems of interest to biomedical research. The first of these was a Chinese hamster ovary cell line engineered to express a recombinant protein. Here, NMR spectroscopy and a quantum mechanical total line shape analysis were utilized to quantify 30 metabolites such as amino acids, Krebs cycle intermediates, activated sugars, cofactors, and others in both media and cell extracts. The impact of bioreactor scale and addition of anti-apoptotic agents to the media on the extracellular and intracellular metabolome indicated changes in metabolic pathways of energy utilization. These results shed light into culture parameters that can be manipulated to optimize growth and protein production. Second, metabolomic analysis was performed on the superfusion media in a common model used for drug metabolism and toxicology studies, in vitro liver slices. In this study, it is demonstrated that two of the 48 standard media components, choline and histidine are depleted at a faster rate than many other nutrients. Augmenting the starting media with extra choline and histidine improves the long-term liver slice viability as measured by higher tissues levels of lactate dehydrogenase (LDH), glutathione and ATP, as well as lower LDH levels in the media at time points out to 94 h after initiation of incubation. In both models, media components and cellular metabolites are measured over time and correlated with currently accepted endpoint measures.

  9. Computational Metabolomics Operations at BioCyc.org

    Directory of Open Access Journals (Sweden)

    Peter D. Karp

    2015-05-01

    Full Text Available 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.

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

    Directory of Open Access Journals (Sweden)

    Joanna Hajduk

    2015-12-01

    Full Text Available The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18 and a matched control group (n = 13. The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44% and specificity (84.62%, as well as the total group membership classification value (90.32% calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

  11. Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows.

    Science.gov (United States)

    Imhasly, Sandro; Naegeli, Hanspeter; Baumann, Sven; von Bergen, Martin; Luch, Andreas; Jungnickel, Harald; Potratz, Sarah; Gerspach, Christian

    2014-06-02

    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. 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. 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.

  12. A metabolomics guided exploration of marine natural product chemical space.

    Science.gov (United States)

    Floros, Dimitrios J; Jensen, Paul R; Dorrestein, Pieter C; Koyama, Nobuhiro

    2016-09-01

    Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

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

    Science.gov (United States)

    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. © 2013 Elsevier B.V. All rights reserved.

  14. NMR metabolomics of thrips (Frankliniella occidentalis) resistance in Senecio hybrids.

    Science.gov (United States)

    Leiss, Kirsten A; Choi, Young H; Abdel-Farid, Ibrahim B; Verpoorte, Robert; Klinkhamer, Peter G L

    2009-02-01

    Western flower thrips (Frankliniella occidentalis) has become a key insect pest of agricultural and horticultural crops worldwide. Little is known about host plant resistance to thrips. In this study, we investigated thrips resistance in F (2) hybrids of Senecio jacobaea and Senecio aquaticus. We identified thrips-resistant hybrids applying three different bioassays. Subsequently, we compared the metabolomic profiles of these hybrids applying nuclear magnetic resonance spectroscopy (NMR). The new developments of NMR facilitate a wide range coverage of the metabolome. This makes NMR especially suitable if there is no a priori knowledge of the compounds related to herbivore resistance and allows a holistic approach analyzing different chemical compounds simultaneously. We show that the metabolomes of thrips-resistant and -susceptible hybrids differed considerably. Thrips-resistant hybrids contained higher amounts of the pyrrolizidine alkaloids (PA), jacobine, and jaconine, especially in younger leaves. Also, a flavanoid, kaempferol glucoside, accumulated in the resistant plants. Both PAs and kaempferol are known for their inhibitory effect on herbivores. In resistant and susceptible F (2) hybrids, young leaves showed less thrips damage than old leaves. Consistent with the optimal plant defense theory, young leaves contained increased levels of primary metabolites such as sucrose, raffinose, and stachyose, but also accumulated jacaranone as a secondary plant defense compound. Our results prove NMR as a promising tool to identify different metabolites involved in herbivore resistance. It constitutes a significant advance in the study of plant-insect relationships, providing key information on the implementation of herbivore resistance breeding strategies in plants.

  15. Solid-phase microextraction and the human fecal VOC metabolome.

    Directory of Open Access Journals (Sweden)

    Emma Dixon

    2011-04-01

    Full Text Available The diagnostic potential and health implications of volatile organic compounds (VOCs present in human feces has begun to receive considerable attention. Headspace solid-phase microextraction (SPME has greatly facilitated the isolation and analysis of VOCs from human feces. Pioneering human fecal VOC metabolomic investigations have utilized a single SPME fiber type for analyte extraction and analysis. However, we hypothesized that the multifarious nature of metabolites present in human feces dictates the use of several diverse SPME fiber coatings for more comprehensive metabolomic coverage. We report here an evaluation of eight different commercially available SPME fibers, in combination with both GC-MS and GC-FID, and identify the 50/30 µm CAR-DVB-PDMS, 85 µm CAR-PDMS, 65 µm DVB-PDMS, 7 µm PDMS, and 60 µm PEG SPME fibers as a minimal set of fibers appropriate for human fecal VOC metabolomics, collectively isolating approximately 90% of the total metabolites obtained when using all eight fibers. We also evaluate the effect of extraction duration on metabolite isolation and illustrate that ex vivo enteric microbial fermentation has no effect on metabolite composition during prolonged extractions if the SPME is performed as described herein.

  16. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary

    2009-12-01

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

  17. Chitosan and grape secondary metabolites: A proteomics and metabolomics approach

    Directory of Open Access Journals (Sweden)

    Bavaresco Luigi

    2017-01-01

    Full Text Available Chitosan is a polysaccharide obtained by deacetylation of chitin, and it is involved in defence mechanisms of plants toward diseases. In the present work, V. vinifera L. cv. Ortrugo, grafted on 420A rootstock was grown in pot and treated, at veraison, by 0.03% chitosan solution at cluster level. Just before the treatment (T0 and 24 hours (T1, 48 hours (T2, 72 hours (T3 and 10 days (T4 later, the concentration of stilbenic compounds was detected, and at T1 proteomics and metabolomics analyses were done. Proteomics relies on the analysis of the complete set of proteins existing in a given substrate, while metabolomics relies on the analyses of the complete set of metabolites in a given substrate. The treatment improved the stilbene concentration over the control at T1. Proteomic analysis showed that superoxide dismutase (SOD and phenylalanine ammonia-lyase (PAL were overexpressed in the treated grapes. SOD is known to be an enzyme active against reactive oxygen species (ROS while PAL is a key enzyme in the phenylpropanoids pathway. Metabolomics analysis highlighted the positive role of the treatment in improving the triperpenoid concentration (betulin, erythrodiol, uvaol, oleanolate; these compounds are known to be effective against microbes, insects and fungi.

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

    Science.gov (United States)

    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

    2016-02-15

    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.

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

    Directory of Open Access Journals (Sweden)

    Arthur S. Edison

    2016-02-01

    Full Text Available 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.

  20. Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

    Directory of Open Access Journals (Sweden)

    Perrin H. Beatty

    2016-10-01

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

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

    Science.gov (United States)

    Sridharan, Gokul; Ramani, Pratibha; Patankar, Sangeeta

    2017-01-01

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

  2. Nutritional impact on the plasma metabolome of rats.

    Science.gov (United States)

    Mellert, W; Kapp, M; Strauss, V; Wiemer, J; Kamp, H; Walk, T; Looser, R; Prokoudine, A; Fabian, E; Krennrich, G; Herold, M; van Ravenzwaay, B

    2011-11-30

    Metabolite profiling (metabolomics) elucidates changes in biochemical pathways under various conditions, e.g., different nutrition scenarios or compound administration. BASF and metanomics have obtained plasma metabolic profiles of approximately 500 compounds (agrochemicals, chemicals and pharmaceuticals) from 28-day rat studies. With these profiles the establishment of a database (MetaMap(®)Tox) containing specific metabolic patterns associated with many toxicological modes of action was achieved. To evaluate confounding factors influencing metabolome patterns, the effect of fasting vs. non-fasting prior to blood sampling, the influence of high caloric diet and caloric restriction as well as the administration of corn oil and olive oil was studied for its influence on the metabolome. All mentioned treatments had distinct effects: triacylglycerol, phospholipids and their degradation product levels (fatty acids, glycerol, lysophosphatidylcholine) were often altered depending on the nutritional status. Also some amino acid and related compounds were changed. Some metabolites derived from food (e.g. alpha-tocopherol, ascorbic acid, beta-sitosterol, campesterol) were biomarkers related to food consumption, whereas others indicated a changed energy metabolism (e.g. hydroxybutyrate, pyruvate). Strikingly, there was a profound difference in the metabolite responses to diet restriction in male and female rats. Consequently, when evaluating the metabolic profile of a compound, the effect of nutritional status should be taken into account. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2014-01-01

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

  4. Metabolomics as a promising tool for early osteoarthritis diagnosis

    Directory of Open Access Journals (Sweden)

    E.B. de Sousa

    2017-09-01

    Full Text Available Osteoarthritis (OA is the main cause of disability worldwide, due to progressive articular cartilage loss and degeneration. According to recent research, OA is more than just a degenerative disease due to some metabolic components associated to its pathogenesis. However, no biomarker has been identified to detect this disease at early stages or to track its development. Metabolomics is an emerging field and has the potential to detect many metabolites in a single spectrum using high resolution nuclear magnetic resonance (NMR techniques or mass spectrometry (MS. NMR is a reproducible and reliable non-destructive analytical method. On the other hand, MS has a lower detection limit and is more destructive, but it is more sensitive. NMR and MS are useful for biological fluids, such as urine, blood plasma, serum, or synovial fluid, and have been used for metabolic profiling in dogs, mice, sheep, and humans. Thus, many metabolites have been listed as possibly associated to OA pathogenesis. The goal of this review is to provide an overview of the studies in animal models and humans, regarding the use of metabolomics as a tool for early osteoarthritis diagnosis. The concept of osteoarthritis as a metabolic disease and the importance of detecting a biomarker for its early diagnosis are highlighted. Then, some studies in plasma and synovial tissues are shown, and finally the application of metabolomics in the evaluation of synovial fluid is described.

  5. Maternal Plasma Metabolomic Profiles in Spontaneous Preterm Birth: Preliminary Results

    Directory of Open Access Journals (Sweden)

    Barbara Lizewska

    2018-01-01

    Full Text Available Objective. To profile maternal plasma metabolome in spontaneous preterm birth. Method. In this retrospective case-control study, we have examined plasma of patient with preterm birth (between 22 and 36 weeks of pregnancy (n=57, with threatened preterm labor (between 23 and 36 weeks of pregnancy (n=49, and with term delivery (n=25. Plasma samples were analysed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS in positive and negative polarity modes. Results. We found 168 differentially expressed metabolites that were significantly distinct between study groups. We determined 51 metabolites using publicly available databases that could be subdivided into one of the five groups: amino acids, fatty acids, lipids, hormones, and bile acids. PLS-DA models, verified by SVM classification accuracy, differentiated preterm birth and term delivery groups. Conclusions. Maternal plasma metabolites are different between term and preterm parturitions. Part of them may be related with preterm labor, while others may be affected by gestational age or the beginning of labor. Metabolite profile can classify preterm or term delivery groups raising the potential of metabolome as a biomarker to identify high-risk pregnancies. Metabolomic studies are also a tool to detect individual compounds that may be further tested in targeted researches.

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

    Energy Technology Data Exchange (ETDEWEB)

    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. However, 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.

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

    Science.gov (United States)

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

    2010-11-05

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

  8. UHPLC-Q-Orbitrap-HRMS-based global metabolomics reveal metabolome modifications in plasma of young women after cranberry juice consumption.

    Science.gov (United States)

    Liu, Haiyan; Garrett, Timothy J; Su, Zhihua; Khoo, Christina; Gu, Liwei

    2017-07-01

    Plasma metabolome in young women following cranberry juice consumption were investigated using a global UHPLC-Q-Orbitrap-HRMS approach. Seventeen female college students, between 21 and 29 years old, were given either cranberry juice or apple juice for three days using a cross-over design. Plasma samples were collected before and after juice consumption. Plasma metabolomes were analyzed using UHPLC-Q-Orbitrap-HRMS followed by orthogonal partial least squares-discriminant analyses (OPLS-DA). S-plot was used to identify discriminant metabolites. Validated OPLS-DA analyses showed that the plasma metabolome in young women, including both exogenous and endogenous metabolites, were altered following cranberry juice consumption. Cranberry juice caused increases of exogenous metabolites including quinic acid, vanilloloside, catechol sulfate, 3,4-dihydroxyphenyl ethanol sulfate, coumaric acid sulfate, ferulic acid sulfate, 5-(trihydroxphenyl)-gamma-valerolactone, 3-(hydroxyphenyl)proponic acid, hydroxyphenylacetic acid and trihydroxybenzoic acid. In addition, the plasma levels of endogenous metabolites including citramalic acid, aconitic acid, hydroxyoctadecanoic acid, hippuric acid, 2-hydroxyhippuric acid, vanilloylglycine, 4-acetamido-2-aminobutanoic acid, dihydroxyquinoline, and glycerol 3-phosphate were increased in women following cranberry juice consumption. The metabolic differences and discriminant metabolites observed in this study may serve as biomarkers of cranberry juice consumption and explain its health promoting properties in human. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Exploring the inflammatory metabolomic profile to predict response to TNF-α inhibitors in rheumatoid arthritis

    NARCIS (Netherlands)

    Cuppen, B.V.J.; Fu, J.; Wietmarschen, H.A. van; Harms, A.C.; Koval, S.; Marijnissen, A.C.A.; Peeters, J.J.W.; Bijlsma, J.W.J.; Tekstra, J.; Laar, J.M. van; Hankemeier, T.; Lafeber, F.P.J.G.; Greef, J. van der

    2016-01-01

    In clinical practice, approximately one-Third of patients with rheumatoid arthritis(RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in

  10. Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping

    NARCIS (Netherlands)

    Kloet, F.M. van der; Bobeldijk, I.; Verheij, E.R.; Jellema, R.H.

    2009-01-01

    Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the

  11. Standard reporting requirements for biological samples in metabolomics experiments: Microbial and in vitro biology experiments

    NARCIS (Netherlands)

    Werf, M.J. van der; Takors, R.; Smedsgaard, J.; Nielsen, J.; Ferenci, T.; Portais, J.C.; Wittmann, C.; Hooks, M.; Tomassini, A.; Oldiges, M.; Fostel, J.; Sauer, U.

    2007-01-01

    With the increasing use of metabolomics as a means to study a large number of different biological research questions, there is a need for a minimal set of reporting standards that allow the scientific community to evaluate, understand, repeat, compare and re-investigate metabolomics studies. Here

  12. A proposed framework for the description of plant metabolomics experiments and their results

    NARCIS (Netherlands)

    Jenkens, H.; Hardy, N.; Beckmann, M.; Draper, J.; Smith, A.R.; Taylor, J.; Fiehn, O.; Goodacre, R.; Bino, R.J.; Hall, R.D.; Kopka, J.; Lane, G.A.; Lange, B.M.; Liu, J.R.; Mendes, P.; Nikolau, B.J.; Oliver, S.G.; Paton, I.R.; Roessner-Tunali, U.; Saito, K.; Smedsgaard, J.; Sumner, L.W.; Wang, T.; Walsh, S.; Wurtele, E.S.; Kell, D.B.

    2004-01-01

    The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known

  13. A proposed framework for the description of plant metabolomics experiments and their results

    DEFF Research Database (Denmark)

    Jenkins, H.; Hardy, N.; Beckmann, M-

    2004-01-01

    The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known...

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

    Science.gov (United States)

    Sandusky, Peter Olaf

    2017-01-01

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

  15. The future of metabolomics in ELIXIR [version 2; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Merlijn van Rijswijk

    2017-10-01

    Full Text Available Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

  16. The future of metabolomics in ELIXIR [version 1; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Merlijn van Rijswijk

    2017-09-01

    Full Text Available Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

  17. Metabolomic profiling of rapid cold hardening and cold shock in Drosophila melanogaster

    DEFF Research Database (Denmark)

    Overgaard, Johannes; Malmendal, Anders; Sørensen, Jesper

    2007-01-01

    study used untargeted (1)H NMR metabolomic profiling to examine the metabolomic response in Drosophila melanogaster during the 72 h following RCH and cold shock treatment. These findings are discussed in relation to the costs and benefits of RCH that are measured in terms of survival and reproductive...

  18. Vitamin D prenatal programming of childhood metabolomics profiles at age 3 y

    DEFF Research Database (Denmark)

    Blighe, Kevin; Chawes, Bo L; Kelly, Rachel S

    2017-01-01

    was to analyze the programming role of in utero vitamin D exposure on children's metabolomics profiles.Design:First, unsupervised clustering was done with plasma metabolomics profiles from a case-control subset of 245 children aged 3 y with and without asthma from the Vitamin D Antenatal Asthma Reduction Trial...

  19. A new strategy of exploring metabolomics data using Monte Carlo tree.

    Science.gov (United States)

    Cao, Dong-Sheng; Wang, Bing; Zeng, Mao-Mao; Liang, Yi-Zeng; Xu, Qing-Song; Zhang, Liang-Xiao; Li, Hong-Dong; Hu, Qian-Nan

    2011-03-07

    Large amounts of data from high-throughput metabolomics experiments have become commonly more and more complex, which brings a number of challenges to existing statistical modeling. Thus there is a need to develop a statistically efficient approach for mining the underlying metabolite information contained by metabolomics data under investigation. In this work, we provide a new strategy based on Monte Carlo cross validation coupled with the classification tree algorithm, which is termed as the MCTree approach. The MCTree approach inherently provides a feasible way to uncover the predictive structure of metabolomics data by the establishment of many cross-predictive models. With the help of the sample proximity matrix such obtained, it seems to be able to give some interesting insights into metabolomics data. Simultaneously, informative metabolites or potential biomarkers can be successfully discovered by means of variable importance ranking in the MCTree approach. Two real metabolomics datasets are finally used to demonstrate the performance of the proposed approach.

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

    Science.gov (United States)

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

    2015-11-01

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

  1. Profiling the Metabolome Changes Caused by Cranberry Procyanidins in Plasma of Female Rats using 1H NMR and UHPLC-Q-Orbitrap-HRMS Global Metabolomics Approaches

    Science.gov (United States)

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

    2015-01-01

    Scope The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using 1H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Methods and results Twenty four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for 3 times using a 250 mg extracts/kg body weight dose. Plasma were collected six hours after the last gavage and analyzed using 1H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using 1H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulfate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4′-O-methyl-(−)-epicatechin-3′-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(−)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-γ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. Conclusion The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. PMID:26264887

  2. Fish mucus metabolome reveals fish life-history traits

    Science.gov (United States)

    Reverter, M.; Sasal, P.; Banaigs, B.; Lecchini, D.; Lecellier, G.; Tapissier-Bontemps, N.

    2017-06-01

    Fish mucus has important biological and ecological roles such as defense against fish pathogens and chemical mediation among several species. A non-targeted liquid chromatography-mass spectrometry metabolomic approach was developed to study gill mucus of eight butterflyfish species in Moorea (French Polynesia), and the influence of several fish traits (geographic site and reef habitat, species taxonomy, phylogeny, diet and parasitism levels) on the metabolic variability was investigated. A biphasic extraction yielding two fractions (polar and apolar) was used. Fish diet (obligate corallivorous, facultative corallivorous or omnivorous) arose as the main driver of the metabolic differences in the gill mucus in both fractions, accounting for 23% of the observed metabolic variability in the apolar fraction and 13% in the polar fraction. A partial least squares discriminant analysis allowed us to identify the metabolites (variable important in projection, VIP) driving the differences between fish with different diets (obligate corallivores, facultative corallivores and omnivorous). Using accurate mass data and fragmentation data, we identified some of these VIP as glycerophosphocholines, ceramides and fatty acids. Level of monogenean gill parasites was the second most important factor shaping the gill mucus metabolome, and it explained 10% of the metabolic variability in the polar fraction and 5% in the apolar fraction. A multiple regression tree revealed that the metabolic variability due to parasitism in the polar fraction was mainly due to differences between non-parasitized and parasitized fish. Phylogeny and butterflyfish species were factors contributing significantly to the metabolic variability of the apolar fraction (10 and 3%, respectively) but had a less pronounced effect in the polar fraction. Finally, geographic site and reef habitat of butterflyfish species did not influence the gill mucus metabolome of butterflyfishes.

  3. Metabolomics Based Profiling of Dexamethasone Side Effects in Rats

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    Abeer K. Malkawi

    2018-02-01

    Full Text Available Dexamethasone (Dex is a synthetic glucocorticoid that has anti-inflammatory and immunosuppressant effects and is used in several conditions such as asthma and severe allergy. Patients receiving Dex, either at a high dose or for a long time, might develop several side effects such as hyperglycemia, weight change, or osteoporosis due to its in vivo non-selectivity. Herein, we used liquid chromatography-tandem mass spectrometry-based comprehensive targeted metabolomic profiling as well as radiographic imaging techniques to study the side effects of Dex treatment in rats. The Dex-treated rats suffered from a ∼20% reduction in weight gain, hyperglycemia (145 mg/dL, changes in serum lipids, and reduction in total serum alkaline phosphatase (ALP (∼600 IU/L. Also, compared to controls, Dex-treated rats showed a distinctive metabolomics profile. In particular, serum amino acids metabolism showed six-fold reduction in phenylalanine, lysine, and arginine levels and upregulation of tyrosine and hydroxyproline reflecting perturbations in gluconeogenesis and protein catabolism which together lead to weight loss and abnormal bone metabolism. Sorbitol level was markedly elevated secondary to hyperglycemia and reflecting activation of the polyol metabolism pathway causing a decrease in the availability of reducing molecules (glutathione, NADPH, NAD+. Overexpression of succinylacetone (4,6-dioxoheptanoic acid suggests a novel inhibitory effect of Dex on hepatic fumarylacetoacetate hydrolase. The acylcarnitines, mainly the very long chain species (C12, C14:1, C18:1 were significantly increased after Dex treatment which reflects degradation of the adipose tissue. In conclusion, long-term Dex therapy in rats is associated with a distinctive metabolic profile which correlates with its side effects. Therefore, metabolomics based profiling may predict Dex treatment-related side effects and may offer possible novel therapeutic interventions.

  4. Mass spectrometry data of metabolomics analysis of Nepenthes pitchers.

    Science.gov (United States)

    Rosli, Muhammad Aqil Fitri; Azizan, Kamalrul Azlan; Baharum, Syarul Nataqain; Goh, Hoe-Han

    2017-10-01

    Hybridisation plays a significant role in the evolution and diversification of plants. Hybridisation among Nepenthes species is extensive, either naturally or man-made. To investigate the effects of hybridisation on the chemical compositions, we carried out metabolomics study on pitcher tissue of Nepenthes ampullaria, Nepenthes rafflesiana and their hybrid, Nepenthes × hookeriana . Pitcher samples were harvested and extracted in methanol:chloroform:water via sonication-assisted extraction before analysed using LC-TOF-MS. MS data were analysed using XCMS online version 2.2.5. This is the first MS data report towards the profiling, identification and comprehensive comparison of metabolites present in Nepenthes species.

  5. Mass spectrometry data of metabolomics analysis of Nepenthes pitchers

    Directory of Open Access Journals (Sweden)

    Muhammad Aqil Fitri Rosli

    2017-10-01

    Full Text Available Hybridisation plays a significant role in the evolution and diversification of plants. Hybridisation among Nepenthes species is extensive, either naturally or man-made. To investigate the effects of hybridisation on the chemical compositions, we carried out metabolomics study on pitcher tissue of Nepenthes ampullaria, Nepenthes rafflesiana and their hybrid, Nepenthes × hookeriana. Pitcher samples were harvested and extracted in methanol:chloroform:water via sonication-assisted extraction before analysed using LC-TOF-MS. MS data were analysed using XCMS online version 2.2.5. This is the first MS data report towards the profiling, identification and comprehensive comparison of metabolites present in Nepenthes species.

  6. Could exercise metabolomics pave the way for gymnomimetics?

    Science.gov (United States)

    Burke, Megan F; Dunbar, Richard L; Rader, Daniel J

    2010-07-21

    Regular physical activity and especially aerobic exercise are associated with reduced risk of disease and enhanced longevity, but the molecular mechanisms of these health benefits remain obscure. A comprehensive metabolomic approach was used to characterize the changes in blood levels of >200 metabolites upon vigorous exercise and identified two dozen that changed substantially. One, niacinamide, is intimately related to the metabolism of nicotinamide adenine dinucleotide (NAD(+)) and its reduced form NADH, which is in turn linked with exercise capacity as well as health status. Intensive investigation of metabolic changes with exercise could lead to pharmacological attempts to mimic the beneficial effects of exercise, an approach we term "gymnomimetics."

  7. Exploring cancer metabolism using stable isotope-resolved metabolomics (SIRM).

    Science.gov (United States)

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

    2017-07-14

    Metabolic reprogramming is a hallmark of cancer. The changes in metabolism are adaptive to permit proliferation, survival, and eventually metastasis in a harsh environment. Stable isotope-resolved metabolomics (SIRM) is an approach that uses advanced approaches of NMR and mass spectrometry to analyze the fate of individual atoms from stable isotope-enriched precursors to products to deduce metabolic pathways and networks. The approach can be applied to a wide range of biological systems, including human subjects. This review focuses on the applications of SIRM to cancer metabolism and its use in understanding drug actions. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  8. Mass spectrometry-based metabolomics of single yeast cells.

    Science.gov (United States)

    Ibáñez, Alfredo J; Fagerer, Stephan R; Schmidt, Anna Mareike; Urban, Pawel L; Jefimovs, Konstantins; Geiger, Philipp; Dechant, Reinhard; Heinemann, Matthias; Zenobi, Renato

    2013-05-28

    Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.

  9. A primer to nutritional metabolomics by NMR spectroscopy and chemometrics

    DEFF Research Database (Denmark)

    Savorani, Francesco; Rasmussen, Morten Arendt; Mikkelsen, Mette Skau

    2013-01-01

    structures for multivariate pattern recognition methods and (3) NMR for providing a unique fingerprint of the lipoprotein status of the subject. For the first time in history, by combining NMR spectroscopy and chemometrics we are able to perform inductive nutritional research as a complement to the deductive......This paper outlines the advantages and disadvantages of using high throughput NMR metabolomics for nutritional studies with emphasis on the workflow and data analytical methods for generation of new knowledge. The paper describes one-by-one the major research activities in the interdisciplinary...

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2016-05-25

    Natural product plays a vital role in disease prevention and treatment since the appearance of civilization, but the toxicity severely hinders its wide use. In order to avoid toxic effect as far as possible and use natural product safely, more comprehensive understandings of toxicity are urgently required. Since the metabolome represents the physiological or pathological status of organisms, metabolomics-based toxicology is of significance to observe potential injury before toxins have caused physiological or pathological damages. Metabolomics-based toxicology can evaluate toxicity and identify toxicological biomarker of natural product, which is helpful to guide clinical medication and reduce adverse drug reactions. In the past decades, dozens of metabolomic researches have been implemented on toxicity evaluation, toxicological biomarker identification and potential mechanism exploration of nephrotoxicity, hepatotoxicity, cardiotoxicity and central nervous system toxicity induced by pure compounds, extracts and compound prescriptions. In this paper, metabolomic technology, sample preparation, data process and analysis, and metabolomics-based toxicological research of natural product are reviewed, and finally, the potential problems and further perspectives in toxicological metabolomic investigations of natural product are discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  12. Metabolomics and detection of colorectal cancer in humans: a systematic review.

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    Wang, Haili; Tso, Victor K; Slupsky, Carolyn M; Fedorak, Richard N

    2010-09-01

    Metabolomics represents one of the new omics sciences and capitalizes on the unique presence and concentration of small molecules in tissues and body fluids to construct a 'fingerprint' that can be unique to the individual and, within that individual, unique to environmental influences, including health and disease states. As such, metabolomics has the potential to serve an important role in diagnosis and management of human conditions. Colorectal cancer is a major public health concern. Current population-based screening methods are suboptimal and whether metabolomics could represent a new tool of screening is under investigation. The purpose of this systematic review is to summarize existing literature on metabolomics and colorectal cancer, in terms of diagnostic accuracies and distinguishing metabolites. Eight studies are included. A total of 12 metabolites (taurine, lactate, choline, inositol, glycine, phosphocholine, proline, phenylalanine, alanine, threonine, valine and leucine) were found to be more prevalent in colorectal cancer and glucose was found to be in higher proportion in control specimens using tissue metabolomics. Serum and urine metabolomics identified several other differential metabolites between controls and colorectal cancer patients. This article highlights the novelty of the field of metabolomics in colorectal oncology.

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

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    Matthias S. Klein

    2016-01-01

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

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

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    Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

    2018-01-05

    Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

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

    Science.gov (United States)

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

    2016-05-01

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

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

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    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Gouveia-Figueira, Sandra [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå (Sweden); Pinto, Rui [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Bioinformatics Infrastructure for Life Sciences (Sweden); Trygg, Johan [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Zivkovic, Angela M. [Department of Nutrition, University of California, Davis, One Shields Ave, CA 95616 (United States); Nording, Malin L., E-mail: malin.nording@umu.se [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden)

    2016-02-18

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Robin D Couch

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

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

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    Ana Jiménez-Girón

    2014-12-01

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

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

    Science.gov (United States)

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

    2017-06-06

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

  1. MetaboAnalyst 3.0--making metabolomics more meaningful.

    Science.gov (United States)

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

    2015-07-01

    MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

    Directory of Open Access Journals (Sweden)

    Laura Righetti

    2016-07-01

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

  3. Structured plant metabolomics for the simultaneous exploration of multiple factors

    Science.gov (United States)

    Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

    2016-01-01

    Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor–metabolite crosstalk. However, unravelling all factor–metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset. PMID:27853298

  4. Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

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    Takao Itoi

    2017-04-01

    Full Text Available This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC from malignant diseases, such as biliary tract cancer (BTC, intraductal papillary mucinous carcinoma (IPMC, and various benign pancreaticobiliary diseases. Capillary electrophoresismass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41 of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140. Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test. Four multiple logistic regression models (MLR were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC of 0.970 (95% confidential interval (CI, 0.946–0.994, p < 0.0001. Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020 with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA, carbohydrate antigen 19-9 (CA19-9, pancreatic cancer-associated antigen (DUPAN2 and s-pancreas-1 antigen (SPAN1. Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.

  5. Integration of metabolomics and transcriptomics in nanotoxicity studies.

    Science.gov (United States)

    Shin, Tae Hwan; Lee, Da Yeon; Lee, Hyeon-Seong; Park, Hyung Jin; Jin, Moon Suk; Paik, Man-Jeong; Manavalan, Balachandran; Mo, Jung-Soon; Lee, Gwang

    2018-01-01

    Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics". [BMB Reports 2018; 51(1): 14-20].

  6. Obesity and psychotic disorders: uncovering common mechanisms through metabolomics

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    Matej Orešič

    2012-09-01

    Full Text Available Primary obesity and psychotic disorders are similar with respect to the associated changes in energy balance and co-morbidities, including metabolic syndrome. Such similarities do not necessarily demonstrate causal links, but instead suggest that specific causes of and metabolic disturbances associated with obesity play a pathogenic role in the development of co-morbid disorders, potentially even before obesity develops. Metabolomics – the systematic study of metabolites, which are small molecules generated by the process of metabolism – has been important in elucidating the pathways underlying obesity-associated co-morbidities. This review covers how recent metabolomic studies have advanced biomarker discovery and the elucidation of mechanisms underlying obesity and its co-morbidities, with a specific focus on metabolic syndrome and psychotic disorders. The importance of identifying metabolic markers of disease-associated intermediate phenotypes – traits modulated but not encoded by the DNA sequence – is emphasized. Such markers would be applicable as diagnostic tools in a personalized healthcare setting and might also open up novel therapeutic avenues.

  7. Perinatal asphyxia: a review from a metabolomics perspective.

    Science.gov (United States)

    Fattuoni, Claudia; Palmas, Francesco; Noto, Antonio; Fanos, Vassilios; Barberini, Luigi

    2015-04-17

    Perinatal asphyxia is defined as an oxygen deprivation that occurs around the time of birth, and may be caused by several perinatal events. This medical condition affects some four million neonates worldwide per year, causing the death of one million subjects. In most cases, infants successfully recover from hypoxia episodes; however, some patients may develop HIE, leading to permanent neurological conditions or impairment of different organs and systems. Given its multifactor dependency, the timing, severity and outcome of this disease, mainly assessed through Sarnat staging, are of difficult evaluation. Moreover, although the latest newborn resuscitation guideline suggests the use of a 21% oxygen concentration or room air, such an approach is still under debate. Therefore, the pathological mechanism is still not clear and a golden standard treatment has yet to be defined. In this context, metabolomics, a new discipline that has described important perinatal issues over the last years, proved to be a useful tool for the monitoring, the assessment, and the identification of potential biomarkers associated with asphyxia events. This review covers metabolomics research on perinatal asphyxia condition, examining in detail the studies reported both on animal and human models.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  10. New frontiers in metabolomics: from measurement to insight [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Eli Riekeberg

    2017-07-01

    Full Text Available Metabolomics is the newest addition to the “omics” disciplines and has shown rapid growth in its application to human health research because of fundamental advancements in measurement and analysis techniques. Metabolomics has unique and proven advantages in systems biology and biomarker discovery. The next generation of analysis techniques promises even richer and more complete analysis capabilities that will enable earlier clinical diagnosis, drug refinement, and personalized medicine. A review of current advancements in methodologies and statistical analysis that are enhancing and improving the performance of metabolomics is presented along with highlights of some recent successful applications.

  11. Automated assembly of species metabolomes through data submission into a public repository.

    Science.gov (United States)

    Salek, Reza M; Conesa, Pablo; Cochrane, Keeva; Haug, Kenneth; Williams, Mark; Kale, Namrata; Moreno, Pablo; Jayaseelan, Kalai Vanii; Macias, Jose Ramon; Nainala, Venkata Chandrasekhar; Hall, Robert D; Reed, Laura K; Viant, Mark R; O'Donovan, Claire; Steinbeck, Christoph

    2017-08-01

    Following similar global efforts to exchange genomic and other biomedical data, global databases in metabolomics have now been established. MetaboLights, the first general purpose, publically available, cross-species, cross-application database in metabolomics, has become the fastest growing data repository at the European Bioinformatics Institute in terms of data volume. Here we present the automated assembly of species metabolomes in MetaboLights, a crucial reference for chemical biology, which is growing through user submissions. © The Authors 2017. Published by Oxford University Press.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-03-31

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

  13. Metabolomic Profiling for Identification of Novel Potential Biomarkers in Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Maria G. Barderas

    2011-01-01

    Full Text Available Metabolomics involves the identification and quantification of metabolites present in a biological system. Three different approaches can be used: metabolomic fingerprinting, metabolic profiling, and metabolic footprinting, in order to evaluate the clinical course of a disease, patient recovery, changes in response to surgical intervention or pharmacological treatment, as well as other associated features. Characteristic patterns of metabolites can be revealed that broaden our understanding of a particular disorder. In the present paper, common strategies and analytical techniques used in metabolomic studies are reviewed, particularly with reference to the cardiovascular field.

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

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    Isabel Ibarra-González

    2017-07-01

    Full Text Available Objective. Inborn errors of metabolism (IEM are genetic conditions that are sometimes associated with intellectual  developmental disorders (IDD. The aim of this study is to contribute to the metabolic characterization of IDD of unknown etiology in Mexico. Materials and methods. Metabolic screening using tandem mass spectrometry and fluorometry will be performed to rule out IEM. In addition,target metabolomic analysis will be done to characterize the metabolomic profile of patients with IDD. Conclusion. Identification of new metabolomic profiles associated withIDD of unknown etiology and comorbidities will contribute to the development of novel diagnostic and therapeutic schemes for the prevention and treatment of IDD in Mexico.

  15. Metabolomics in critical care medicine: a new approach to biomarker discovery.

    Science.gov (United States)

    Banoei, Mohammad M; Donnelly, Sarah J; Mickiewicz, Beata; Weljie, Aalim; Vogel, Hans J; Winston, Brent W

    2014-12-01

    To present an overview and comparison of the main metabolomics techniques (1H NMR, GC-MS, and LC-MS) and their current and potential use in critical care medicine. This is a focused review, not a systematic review, using the PubMed database as the predominant source of references to compare metabolomics techniques. 1H NMR, GC-MS, and LC-MS are complementary techniques that can be used on a variety of biofluids for metabolomics analysis of patients in the Intensive Care Unit (ICU). These techniques have been successfully used for diagnosis and prognosis in the ICU and other clinical settings; for example, in patients with septic shock and community-acquired pneumonia. Metabolomics is a powerful tool that has strong potential to impact diagnosis and prognosis and to examine responses to treatment in critical care medicine through diagnostic and prognostic biomarker and biopattern identification.

  16. The potential of metabolomics for Leishmania research in the post-genomics era.

    Science.gov (United States)

    Scheltema, Richard A; Decuypere, Saskia; T'kindt, Ruben; Dujardin, Jean-Claude; Coombs, Graham H; Breitling, Rainer

    2010-08-01

    The post-genomics era has provided researchers with access to a new generation of tools for the global characterization and understanding of pathogen diversity. This review provides a critical summary of published Leishmania post-genomic research efforts to date, and discusses the potential impact of the addition of metabolomics to the post-genomic toolbox. Metabolomics aims at understanding biology by comprehensive metabolite profiling. We present an overview of the design and interpretation of metabolomics experiments in the context of Leishmania research. Sample preparation, measurement techniques, and bioinformatics analysis of the generated complex datasets are discussed in detail. To illustrate the concepts and the expected results of metabolomics analyses, we also present an overview of comparative metabolic profiles of drug-sensitive and drug-resistant Leishmania donovani clinical isolates.

  17. Metabolomics as an emerging strategy for the investigation of yogurt components

    NARCIS (Netherlands)

    Settachaimongkon, S.; Valenberg, van H.J.F.; Smid, E.J.

    2017-01-01

    The advanced development in metabolomics allows discovery of a wide range of metabolites in complex biological systems including food matrices. This analytical approach provides opportunities to attain a global metabolite profile and discover potential biomarkers and various chemical contaminants

  18. The photographer and the greenhouse: how to analyse plant metabolomics data

    NARCIS (Netherlands)

    Jansen, J.J.; Smit, S.; Hoefsloot, H.C.J.; Smilde, A.K.

    2010-01-01

    ntroduction - Plant metabolomics experiments yield large amounts of data, too much to be interpretable by eye. Multivariate data analyses are therefore essential to extract and visualise the information of interest. Objective - Because multivariate statistical methods may be remote from the

  19. Highlights of the 2012 Research Workshop: Using nutrigenomics and metabolomics in clinical nutrition research.

    Science.gov (United States)

    Zeisel, Steven H; Waterland, Robert A; Ordovás, José M; Muoio, Deborah M; Jia, Wei; Fodor, Anthony

    2013-03-01

    The American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Research Workshop, "Using Nutrigenomics and Metabolomics in Clinical Nutrition Research," was held on January 21, 2012, in Orlando, Florida. The conference brought together experts in human nutrition who use nutrigenomic and metabolomic methods to better understand metabolic individuality and nutrition effects on health. We are beginning to understand how genetic variation and epigenetic events alter requirements for and responses to foods in our diet (the field of nutrigenetics/nutrigenomics and epigenetics). At the same time, methods for profiling almost all of the products of metabolism in plasma, urine, and tissues (metabolomics) are being refined. The relationships between diet and nutrigenomic-metabolomic profiles, as well as between these profiles and health, are being elucidated, and this will dramatically alter clinical practice in nutrition.

  20. Rapid volatile metabolomics and genomics in large strawberry populations segregating for aroma

    Science.gov (United States)

    Volatile organic compounds (VOCs) in strawberry (Fragaria spp.) represent a large portion of the fruit secondary metabolome, and contribute significantly to aroma, flavor, disease resistance, pest resistance and overall fruit quality. Understanding the basis for volatile compound biosynthesis and it...

  1. Statistical methods for the analysis of high-throughput metabolomics data

    Directory of Open Access Journals (Sweden)

    Fabian J. Theis

    2013-01-01

    Full Text Available Metabolomics is a relatively new high-throughput technology that aims at measuring all endogenous metabolites within a biological sample in an unbiased fashion. The resulting metabolic profiles may be regarded as functional signatures of the physiological state, and have been shown to comprise effects of genetic regulation as well as environmental factors. This potential to connect genotypic to phenotypic information promises new insights and biomarkers for different research fields, including biomedical and pharmaceutical research. In the statistical analysis of metabolomics data, many techniques from other omics fields can be reused. However recently, a number of tools specific for metabolomics data have been developed as well. The focus of this mini review will be on recent advancements in the analysis of metabolomics data especially by utilizing Gaussian graphical models and independent component analysis.

  2. Drought enhances folivory by shifting foliar metabolomes in Quercus ilex trees

    Czech Academy of Sciences Publication Activity Database

    Rivas-Ubach, A.; Gargallo-Garriga, A.; Sardans, J.; Oravec, Michal; Mateu-Castell, L.; Pérez-Trujillo, M.; Parella, T.; Ogaya, R.; Urban, Otmar; Penuelas, J.

    2014-01-01

    Roč. 202, č. 3 (2014), s. 874-885 ISSN 1469-8137 Institutional support: RVO:67179843 Keywords : drought * ecology * ecometabolomics * folivory * metabolomics * stoichiometry Subject RIV: EF - Botanics Impact factor: 6.545, year: 2013

  3. A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

    Science.gov (United States)

    Merino, Jordi; Leong, Aaron; Meigs, James B.

    2018-01-01

    Purpose of Review The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction. Recent Findings In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bio-informatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Summary Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for “multi-omic” prediction to improve health. PMID:29103096

  4. IDEOM : an Excel interface for analysis of LC-MS-based metabolomics data

    NARCIS (Netherlands)

    Creek, Darren J.; Jankevics, Andris; Burgess, Karl E. V.; Breitling, Rainer; Barrett, Michael P.; Wren, Jonathan

    2012-01-01

    The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates

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

    Science.gov (United States)

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

  6. Metabolomics reveals distinct neurochemical profiles associated with stress resilience

    Directory of Open Access Journals (Sweden)

    Brooke N. Dulka

    2017-12-01

    Full Text Available Acute social defeat represents a naturalistic form of conditioned fear and is an excellent model in which to investigate the biological basis of stress resilience. While there is growing interest in identifying biomarkers of stress resilience, until recently, it has not been feasible to associate levels of large numbers of neurochemicals and metabolites to stress-related phenotypes. The objective of the present study was to use an untargeted metabolomics approach to identify known and unknown neurochemicals in select brain regions that distinguish susceptible and resistant individuals in two rodent models of acute social defeat. In the first experiment, male mice were first phenotyped as resistant or susceptible. Then, mice were subjected to acute social defeat, and tissues were immediately collected from the ventromedial prefrontal cortex (vmPFC, basolateral/central amygdala (BLA/CeA, nucleus accumbens (NAc, and dorsal hippocampus (dHPC. Ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS was used for the detection of water-soluble neurochemicals. In the second experiment, male Syrian hamsters were paired in daily agonistic encounters for 2 weeks, during which they formed stable dominant-subordinate relationships. Then, 24 h after the last dominance encounter, animals were exposed to acute social defeat stress. Immediately after social defeat, tissue was collected from the vmPFC, BLA/CeA, NAc, and dHPC for analysis using UPLC-HRMS. Although no single biomarker characterized stress-related phenotypes in both species, commonalities were found. For instance, in both model systems, animals resistant to social defeat stress also show increased concentration of molecules to protect against oxidative stress in the NAc and vmPFC. Additionally, in both mice and hamsters, unidentified spectral features were preliminarily annotated as potential targets for future experiments. Overall, these findings

  7. Dietary and metabolomic determinants of relapse in ulcerative colitis patients: A pilot prospective cohort study

    OpenAIRE

    Keshteli, Ammar Hassanzadeh; van den Brand, Floris F; Madsen, Karen L; Mandal, Rupasri; Valcheva, Rosica; Kroeker, Karen I; Han, Beomsoo; Bell, Rhonda C; Cole, Janis; Hoevers, Thomas; Wishart, David S; Fedorak, Richard N; Dieleman, Levinus A

    2017-01-01

    AIM To identify demographic, clinical, metabolomic, and lifestyle related predictors of relapse in adult ulcerative colitis (UC) patients. METHODS In this prospective pilot study, UC patients in clinical remission were recruited and followed-up at 12 mo to assess a clinical relapse, or not. At baseline information on demographic and clinical parameters was collected. Serum and urine samples were collected for analysis of metabolomic assays using a combined direct infusion/liquid chromatograph...

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

    OpenAIRE

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

    2017-01-01

    While predominant as a disease entity, knowledge voids exist regarding the pathogenesis of canine diabetes. To test the hypothesis that diabetic dogs have similar metabolomic perturbations to humans with type 1 diabetes (T1D), we analyzed serum metabolomic profiles of breed- and body weight-matched, diabetic (n?=?6) and healthy (n?=?6) dogs by liquid chromatography-mass spectrometry (LC-MS) profiling. We report distinct clustering of diabetic and control groups based on heat map analysis of k...

  9. Topsoil depth substantially influences the responses to drought of the foliar metabolomes of Mediterranean forests

    Energy Technology Data Exchange (ETDEWEB)

    Rivas-Ubach, Albert; Barbeta, Adrià; Sardans, Jordi; Guenther, Alex; Ogaya, Romà; Oravec, Michal; Urban, Otmar; Peñuelas, Josep

    2016-08-01

    Soils provide physical support, water, and nutrients to terrestrial plants. Upper soil layers are crucial for forest dynamics, especially under drought conditions, because many biological processes occur there and provide support, water and nutrients to terrestrial plants. We postulated that tree size and overall plant function manifested in the metabolome composition, the total set of metabolites, were dependent on the depth of upper soil layers and on water availability. We sampled leaves for stoichiometric and metabolomic analyses once per season from differently sized Quercus ilex trees under natural and experimental drought conditions as projected for the coming decades. Different sized trees had different metabolomes and plots with shallower soils had smaller trees. Soil moisture of the upper soil did not explain the tree size and smaller trees did not show higher concentrations of biomarker metabolites related to drought stress. However, the impact of drought treatment on metabolomes was higher in smaller trees in shallower soils. Our results suggested that tree size was more dependent on the depth of the upper soil layers, which indirectly affect the metabolomes of the trees, than on the moisture content of the upper soil layers. Metabolomic profiling of Q. ilex supported the premise that water availability in the upper soil layers was not necessarily correlated with tree size. The higher impact of drought on trees growing in shallower soils nevertheless indicates a higher vulnerability of small trees to the future increase in frequency, intensity, and duration of drought projected for the Mediterranean Basin and other areas. Metabolomics has proven to be an excellent tool detecting significant metabolic changes among differently sized individuals of the same species and it improves our understanding of the connection between plant metabolomes and environmental variables such as soil depth and moisture content.

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

    OpenAIRE

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

    2014-01-01

    Background: Metabolic byproducts serve as indicators of the chemical processes and can provide valuable information on pathogenesis by measuring the amplified output. Standardized techniques for metabolome extraction of skin samples serve as a critical foundation to this field but have not been developed. Objectives: We sought to determine the optimal cell lysage techniques for skin sample preparation and to compare GC-TOF-MS and UHPLC-QTOF-MS for metabolomic analysis. ...

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

    OpenAIRE

    Arvonio, Raffaele

    2011-01-01

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

  12. Software and Database Usage on Metabolomic Studies: Using XCMS on LC-MS Data Analysis

    Directory of Open Access Journals (Sweden)

    Mustafa Celebier

    2014-04-01

    Full Text Available Metabolome is the complete set of small-molecule metabolites to be found in a cell or a single organism. Metabolomics is the scientific study to determine and identify the chemicals in metabolome with advanced analytical techniques. Nowadays, the elucidation of the molecular mechanism of any disease with genome analysis and proteome analysis is not sufficient. Instead of these, a holistic assessment including metabolomic studies provides rational and accurate results. Metabolite levels in an organism are associated with the cellular functions. Thus, determination of the metabolite amounts identifies the phenotype of a cell or tissue related with the genetic and some other variations. Even though, the analysis of metabolites for medical diagnosis and therapy have been performed for a long time, the studies to improve the analysis methods for metabolite profiling are recently increased. The application of metabolomics includes the identification of biomarkers, enzyme-substract interactions, drug-activity studies, metabolic pathway analysis and some other studies related with the system biology. The preprocessing and computing of the data obtained from LC-MS, GC-MS, CE-MS and NMR for metabolite profiling are helpful for preventing from time consuming manual data analysis processes and possible random errors on profiling period. In addition, such preprocesses allow us to identify low amount of metabolites which are not possible to be analyzed by manual processing. Therefore, the usage of software and databases for this purpose could not be ignored. In this study, it is briefly presented the software and database used on metabolomics and it is evaluated the capability of these software on metabolite profiling. Particularly, the performance of one of the most popular software called XCMS on the evaluation of LC-MS results for metabolomics was overviewed. In the near future, metabolomics with software and database support is estimated to be a routine

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

    Science.gov (United States)

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

    2016-03-24

    MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

  14. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    International Nuclear Information System (INIS)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M.C.; Wijmenga, Sybren S.

    2012-01-01

    Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

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

    Science.gov (United States)

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

    2016-01-01

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

  16. Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia.

    Science.gov (United States)

    Banoei, Mohammad M; Vogel, Hans J; Weljie, Aalim M; Kumar, Anand; Yende, Sachin; Angus, Derek C; Winston, Brent W

    2017-04-19

    Metabolomics is a tool that has been used for the diagnosis and prognosis of specific diseases. The purpose of this study was to examine if metabolomics could be used as a potential diagnostic and prognostic tool for H1N1 pneumonia. Our hypothesis was that metabolomics can potentially be used early for the diagnosis and prognosis of H1N1 influenza pneumonia. 1 H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to profile the metabolome in 42 patients with H1N1 pneumonia, 31 ventilated control subjects in the intensive care unit (ICU), and 30 culture-positive plasma samples from patients with bacterial community-acquired pneumonia drawn within the first 24 h of hospital admission for diagnosis and prognosis of disease. We found that plasma-based metabolomics from samples taken within 24 h of hospital admission can be used to discriminate H1N1 pneumonia from bacterial pneumonia and nonsurvivors from survivors of H1N1 pneumonia. Moreover, metabolomics is a highly sensitive and specific tool for the 90-day prognosis of mortality in H1N1 pneumonia. This study demonstrates that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU on the basis of plasma samples taken within 24 h of hospital/ICU admission, early in the course of disease.

  17. Enteric Helminths Promote Salmonella Coinfection by Altering the Intestinal Metabolome.

    Science.gov (United States)

    Reynolds, Lisa A; Redpath, Stephen A; Yurist-Doutsch, Sophie; Gill, Navkiran; Brown, Eric M; van der Heijden, Joris; Brosschot, Tara P; Han, Jun; Marshall, Natalie C; Woodward, Sarah E; Valdez, Yanet; Borchers, Christoph H; Perona-Wright, Georgia; Finlay, B Brett

    2017-04-15

    Intestinal helminth infections occur predominantly in regions where exposure to enteric bacterial pathogens is also common. Helminth infections inhibit host immunity against microbial pathogens, which has largely been attributed to the induction of regulatory or type 2 (Th2) immune responses. Here we demonstrate an additional 3-way interaction in which helminth infection alters the metabolic environment of the host intestine to enhance bacterial pathogenicity. We show that an ongoing helminth infection increased colonization by Salmonella independently of T regulatory or Th2 cells. Instead, helminth infection altered the metabolic profile of the intestine, which directly enhanced bacterial expression of Salmonella pathogenicity island 1 (SPI-1) genes and increased intracellular invasion. These data reveal a novel mechanism by which a helminth-modified metabolome promotes susceptibility to bacterial coinfection. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

  18. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen

    2006-01-01

    network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from......Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

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

    Science.gov (United States)

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

    2016-07-01

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

  20. Metabolomics tools for the synthetic biology of natural products.

    Science.gov (United States)

    Hollywood, Katherine A; Schmidt, Kamila; Takano, Eriko; Breitling, Rainer

    2018-03-19

    Metabolomics plays an increasingly central role within the Design-Build-Test cycle of synthetic biology, in particular in applications targeting the discovery, diversification and optimised production of a wide range of natural products. For example, improved methods for the online monitoring of chemical reactions accelerate data generation to be compatible with the rapid iterations and increasing library sizes of automated synthetic biology pipelines. Combinations of label-free metabolic profiling and 13 C-based flux analysis lead to increased resolution in the identification of metabolic bottlenecks affecting product yield in engineered microbes. And molecular networking strategies drastically increase our ability to identify and characterise novel chemically complex biomolecules of interest in a diverse range of samples. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Independent component analysis in non-hypothesis driven metabolomics

    DEFF Research Database (Denmark)

    Li, Xiang; Hansen, Jakob; Zhao, Xinjie

    2012-01-01

    components were involved in fuel metabolism, representing one of the most affected metabolic changes occurring in exercising humans. Conclusive time dependent physiological changes of the metabolic pattern under exercise conditions were detected. We conclude that after optimization ICA can successfully......In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori...... information on the investigated process and moreover can separate statistically independent source signals with non-Gaussian distribution, we aimed to elucidate the analytical power of ICA for the metabolic pattern analysis and the identification of key metabolites in this exercise study. A novel approach...

  2. The dental calculus metabolome in modern and historic samples

    DEFF Research Database (Denmark)

    Velsko, Irina M.; Overmyer, Katherine A.; Speller, Camilla

    2017-01-01

    Introduction: Dental calculus is a mineralized microbial dental plaque biofilm that forms throughout life by precipitation of salivary calcium salts. Successive cycles of dental plaque growth and calcification make it an unusually well-preserved, long-term record of host-microbial interaction...... in the archaeological record. Recent studies have confirmed the survival of authentic ancient DNA and proteins within historic and prehistoric dental calculus, making it a promising substrate for investigating oral microbiome evolution via direct measurement and comparison of modern and ancient specimens. Objective: We...... present the first comprehensive characterization of the human dental calculus metabolome using a multi-platform approach. Methods: Ultra performance liquid chromatography-tandem mass spectrometry (UPLC–MS/MS) quantified 285 metabolites in modern and historic (200 years old) dental calculus, including...

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

    Directory of Open Access Journals (Sweden)

    Arita Masanori

    2008-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Siamak Ravanbakhsh

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

  5. Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data

    Directory of Open Access Journals (Sweden)

    Kevin Schwahn

    2017-12-01

    Full Text Available Recent advances in metabolomics technologies have resulted in high-quality (time-resolved metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derived from it. Unlike the existing approaches which establish a relation between pairs of metabolites, SCA facilitates the discovery of higher-order dependence between more than two metabolites. By using a paradigmatic model of the tricarboxylic acid cycle we show that the higher-order dependence reflects the coupling of concentration of reactant complexes, capturing the subtle difference between the employed enzyme kinetics. Using time-resolved metabolic profiles from Arabidopsis thaliana and Escherichia coli, we show that SCA can be used to quantify the difference in coupling of reactant complexes, and hence, reaction rates, underlying the stringent response in these model organisms. By using SCA with data from natural variation of wild and domesticated wheat and tomato accession, we demonstrate that the domestication is accompanied by loss of such couplings, in these species. Therefore, application of SCA to metabolomics data from natural variation in wild and domesticated populations provides a mechanistic way to understanding domestication and its relation to metabolic networks.

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

    Science.gov (United States)

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-04-14

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

  7. Characterizing Dissolved Organic Matter and Metabolites in an Actively Serpentinizing Ophiolite Using Global Metabolomics Techniques

    Science.gov (United States)

    Seyler, L. M.; Rempfert, K. R.; Kraus, E. A.; Spear, J. R.; Templeton, A. S.; Schrenk, M. O.

    2017-12-01

    Environmental metabolomics is an emerging approach used to study ecosystem properties. Through bioinformatic comparisons to metagenomic data sets, metabolomics can be used to study microbial adaptations and responses to varying environmental conditions. Since the techniques are highly parallel to organic geochemistry approaches, metabolomics can also provide insight into biogeochemical processes. These analyses are a reflection of metabolic potential and intersection with other organisms and environmental components. Here, we used an untargeted metabolomics approach to characterize dissolved organic carbon and aqueous metabolites from groundwater obtained from an actively serpentinizing habitat. Serpentinites are known to support microbial communities that feed off of the products of serpentinization (such as methane and H2 gas), while adapted to harsh environmental conditions such as high pH and low DIC availability. However, the biochemistry of microbial populations that inhabit these environments are understudied and are complicated by overlapping biotic and abiotic processes. The aim of this study was to identify potential sources of carbon in an environment that is depleted of soluble inorganic carbon, and to characterize the flow of metabolites and describe overlapping biogenic and abiogenic processes impacting carbon cycling in serpentinizing rocks. We applied untargeted metabolomics techniques to groundwater taken from a series of wells drilled into the Semail Ophiolite in Oman.. Samples were analyzed via quadrupole time-of-flight liquid chromatography tandem mass spectrometry (QToF-LC/MS/MS). Metabolomes and metagenomic data were imported into Progenesis QI software for statistical analysis and correlation, and metabolic networks constructed using the Genome-Linked Application for Metabolic Maps (GLAMM), a web interface tool. Further multivariate statistical analyses and quality control was performed using EZinfo. Pools of dissolved organic carbon could

  8. Perplexing Metabolomes in Fungal-Insect Trophic Interactions: A Terra Incognita of Mycobiocontrol Mechanisms

    Science.gov (United States)

    Singh, Digar; Son, Su Y.; Lee, Choong H.

    2016-01-01

    The trophic interactions of entomopathogenic fungi in different ecological niches viz., soil, plants, or insect themselves are effectively regulated by their maneuvered metabolomes and the plethora of metabotypes. In this article, we discuss a holistic framework of co-evolutionary metabolomes and metabotypes to model the interactions of biocontrol fungi especially with mycosed insects. Conventionally, the studies involving fungal biocontrol mechanisms are reported in the context of much aggrandized fungal entomotoxins while the adaptive response mechanisms of host insects are relatively overlooked. The present review asserts that the selective pressure exerted among the competing or interacting species drives alterations in their overall metabolomes which ultimately implicates in corresponding metabotypes. Quintessentially, metabolomics offers a most generic and tractable model to assess the fungal-insect antagonism in terms of interaction biomarkers, biosynthetic pathway plasticity, and their co-evolutionary defense. The fungi chiefly rely on a battery of entomotoxins viz., secondary metabolites falling in the categories of NRP’s (non-ribosomal peptides), PK’s (polyketides), lysine derive alkaloids, and terpenoids. On the contrary, insects overcome mycosis through employing different layers of immunity manifested as altered metabotypes (phenoloxidase activity) and overall metabolomes viz., carbohydrates, lipids, fatty acids, amino acids, and eicosanoids. Here, we discuss the recent findings within conventional premise of fungal entomotoxicity and the evolution of truculent immune response among host insect. The metabolomic frameworks for fungal–insect interaction can potentially transmogrify our current comprehensions of biocontrol mechanisms to develop the hypervirulent biocontrol strains with least environmental concerns. Moreover, the interaction metabolomics (interactome) in complementation with other -omics cascades could further be applied to address

  9. Linking diet to acne metabolomics, inflammation, and comedogenesis: an update

    Directory of Open Access Journals (Sweden)

    Melnik BC

    2015-07-01

    proliferation. Oleate stimulates P. acnes adhesion, keratinocyte proliferation, and comedogenesis via interleukin-1α release. Thus, diet-induced metabolomic alterations promote the visible sebofollicular inflammasomopathy acne vulgaris. Nutrition therapy of acne has to increase FoxO1 and to attenuate mTORC1/SREBP-1c signaling. Patients should balance total calorie uptake and restrict refined carbohydrates, milk, dairy protein supplements, saturated fats, and trans-fats. A paleolithic-like diet enriched in vegetables and fish is recommended. Plant-derived mTORC1 inhibitors and ω-3-PUFAs are promising dietary supplements supporting nutrition therapy of acne vulgaris. Keywords: acne, comedogenesis, diet, inflammasome, metabolomics, quorum sensing

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

    Science.gov (United States)

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

    2013-12-01

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

  11. Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery.

    Science.gov (United States)

    Patel, Seema; Ahmed, Shadab

    2015-03-25

    Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2011-11-04

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

  13. Cardiac resynchronization therapy induces adaptive metabolic transitions in the metabolomic profile of heart failure.

    Science.gov (United States)

    Nemutlu, Emirhan; Zhang, Song; Xu, Yi-Zhou; Terzic, Andre; Zhong, Li; Dzeja, Petras D; Cha, Yong-Mei

    2015-06-01

    Heart failure (HF) is associated with ventricular dyssynchrony and energetic inefficiency, which can be alleviated by cardiac resynchronization therapy (CRT). The aim of this study was to determine the metabolomic signature in HF and its prognostic value regarding the response to CRT. This prospective study consisted of 24 patients undergoing CRT for advanced HF and 10 control patients who underwent catheter ablation for supraventricular arrhythmia but not CRT. Blood samples were collected before and 3 months after CRT. Metabolomic profiling of plasma samples was performed with the use of gas chromatography-mass spectrometry and nuclear magnetic resonance. The plasma metabolomic profile was altered in the HF patients, with a distinct panel of metabolites, including Krebs cycle and lipid, amino acid, and nucleotide metabolism. CRT improved the metabolomic profile. The succinate-glutamate ratio, an index of Krebs cycle activity, improved from 0.58 ± 0.13 to 2.84 ± 0.60 (P HF patients, indicating harmonization of myocardial energy substrate metabolism. CRT responders may have a favorable metabolomic profile as a potential biomarker for predicting CRT outcome. Published by Elsevier Inc.

  14. Strategies for Extending Metabolomics Studies with Stable Isotope Labelling and Fluxomics

    Directory of Open Access Journals (Sweden)

    Anubhav Srivastava

    2016-10-01

    Full Text Available This is a perspective from the peer session on stable isotope labelling and fluxomics at the Australian & New Zealand Metabolomics Conference (ANZMET held from 30 March to 1 April 2016 at La Trobe University, Melbourne, Australia. This report summarizes the key points raised in the peer session which focused on the advantages of using stable isotopes in modern metabolomics and the challenges in conducting flux analyses. The session highlighted the utility of stable isotope labelling in generating reference standards for metabolite identification, absolute quantification, and in the measurement of the dynamic activity of metabolic pathways. The advantages and disadvantages of different approaches of fluxomics analyses including flux balance analysis, metabolic flux analysis and kinetic flux profiling were also discussed along with the use of stable isotope labelling in in vivo dynamic metabolomics. A number of crucial technical considerations for designing experiments and analyzing data with stable isotope labelling were discussed which included replication, instrumentation, methods of labelling, tracer dilution and data analysis. This report reflects the current viewpoint on the use of stable isotope labelling in metabolomics experiments, identifying it as a great tool with the potential to improve biological interpretation of metabolomics data in a number of ways.

  15. An Integrated Outlook on the Metagenome and Metabolome of Intestinal Diseases

    Directory of Open Access Journals (Sweden)

    Wanping Aw

    2015-11-01

    Full Text Available Recently, metagenomics and metabolomics are the two most rapidly advancing “omics” technologies. Metagenomics seeks to characterize the composition of microbial communities, their operations, and their dynamically co-evolving relationships with the habitats they occupy, whereas metabolomics studies unique chemical endpoints (metabolites that specific cellular processes leave behind. Remarkable progress in DNA sequencing and mass spectrometry technologies has enabled the comprehensive collection of information on the gut microbiome and its metabolome in order to assess the influence of the gut microbiota on host physiology on a whole-systems level. Our gut microbiota, which consists of prokaryotic cells together with its metabolites, creates a unique gut ecosystem together with the host eukaryotic cells. In this review, we will highlight the detailed relationships between gut microbiota and its metabolites on host health and the pathogenesis of various intestinal diseases such as inflammatory bowel disease and colorectal cancer. Therapeutic interventions such as probiotic and prebiotic administrations and fecal microbiota transplantations will also be discussed. We would like to promote this unique biology-wide approach of incorporating metagenome and metabolome information as we believe that this can help us understand the intricate interplay between gut microbiota and host metabolism to a greater extent. This novel integration of microbiome, metatranscriptome, and metabolome information will help us have an improved holistic understanding of the complex mammalian superorganism, thereby allowing us to gain new and unprecedented insights to providing exciting novel therapeutic approaches for optimal intestinal health.

  16. Identification of drug targets by chemogenomic and metabolomic profiling in yeast

    KAUST Repository

    Wu, Manhong

    2012-12-01

    OBJECTIVE: To advance our understanding of disease biology, the characterization of the molecular target for clinically proven or new drugs is very important. Because of its simplicity and the availability of strains with individual deletions in all of its genes, chemogenomic profiling in yeast has been used to identify drug targets. As measurement of drug-induced changes in cellular metabolites can yield considerable information about the effects of a drug, we investigated whether combining chemogenomic and metabolomic profiling in yeast could improve the characterization of drug targets. BASIC METHODS: We used chemogenomic and metabolomic profiling in yeast to characterize the target for five drugs acting on two biologically important pathways. A novel computational method that uses a curated metabolic network was also developed, and it was used to identify the genes that are likely to be responsible for the metabolomic differences found. RESULTS AND CONCLUSION: The combination of metabolomic and chemogenomic profiling, along with data analyses carried out using a novel computational method, could robustly identify the enzymes targeted by five drugs. Moreover, this novel computational method has the potential to identify genes that are causative of metabolomic differences or drug targets. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.

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

    Science.gov (United States)

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

    2014-01-01

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

  18. Metabolomics-assisted biotechnological interventions for developing plant-based functional foods and nutraceuticals.

    Science.gov (United States)

    Kumar, Arun; Mosa, Kareem A; Ji, Liyao; Kage, Udaykumar; Dhokane, Dhananjay; Karre, Shailesh; Madalageri, Deepa; Pathania, Neemisha

    2017-03-08

    Today, the dramatic changes in types of food consumed have led to an increased burden of chronic diseases. Therefore, the emphasis of food research is not only to ensure quality food that can supply adequate nutrients to prevent nutrition related diseases, but also to ensure overall physical and mental-health. This has led to the concept of functional foods and nutraceuticals (FFNs), which can be ideally produced and delivered through plants. Metabolomics can help in getting the most relevant functional information, and thus has been considered the greatest -OMICS technology to date. However, metabolomics has not been exploited to the best potential in plant sciences. The technology can be leveraged to identify the health promoting compounds and metabolites that can be used for the development of FFNs. This article reviews (i) plant-based FFNs-related metabolites and their health benefits; (ii) use of different analytic platforms for targeted and non-targeted metabolite profiling along with experimental considerations; (iii) exploitation of metabolomics to develop FFNs in plants using various biotechnological tools; and (iv) potential use of metabolomics in plant breeding. We have also provided some insights into integration of metabolomics with latest genome editing tools for metabolic pathway regulation in plants.

  19. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    Science.gov (United States)

    Xia, Jianguo; Wishart, David S

    2016-09-07

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

  20. Short overview on metabolomic approach and redox changes in psychiatric disorders

    Directory of Open Access Journals (Sweden)

    Gordana Nedic Erjavec

    2018-04-01

    Full Text Available Schizophrenia, depression and posttraumatic stress disorder (PTSD are severe mental disorders and complicated diagnostic entities, due to their phenotypic, biological and genetic heterogeneity, unknown etiology, and poorly understood alterations in biological pathways and biological mechanisms. Disturbed homeostasis between overproduction of oxidant species, overcoming redox regulation and a lack of cellular antioxidant defenses, resulting in free radical-mediated pathology and subsequent neurotoxicity contributes to development of depression, schizophrenia and PTSD, their heterogeneous clinical presentation and resistance to treatment. Metabolomics is a discipline that combines different strategies with the aim to extract, detect, identify and quantify all metabolites that are present in a biological sample and might provide mechanistic insights into the etiology of various psychiatric disorders. Therefore, oxidative stress research combined with metabolomics might offer a novel approach in dissecting psychiatric disorders, since these data-driven but not necessarily hypothesis-driven methods might identify new targets, molecules and pathways responsible for development of schizophrenia, depression or PTSD. Findings from the oxidative research in psychiatry together with metabolomics data might facilitate development of specific and validated prognostic, therapeutic and clinical biomarkers. These methods might reveal bio-signatures of individual patients, leading to individualized treatment approach. In reviewing findings related to oxidative stress and metabolomics in selected psychiatric disorders, we have highlighted how these novel approaches might make a unique contribution to deeper understanding of psychopathological alterations underlying schizophrenia, depression and PTSD. Keywords: Schizophrenia, Depression, Posttraumatic stress disorder, Oxidative stress, Lipid peroxidation, Metabolomics, Biomarkers

  1. Untargeted Metabolomics Approach in Halophiles: Understanding the Biodeterioration Process of Building Materials

    Directory of Open Access Journals (Sweden)

    Justyna Adamiak

    2017-12-01

    Full Text Available The aim of the study was to explore the halophile metabolome in building materials using untargeted metabolomics which allows for broad metabolome coverage. For this reason, we used high-performance liquid chromatography interfaced to high-resolution mass spectrometry (HPLC/HRMS. As an alternative to standard microscopy techniques, we introduced pioneering Coherent Anti-stokes Raman Scattering Microscopy (CARS to non-invasively visualize microbial cells. Brick samples saturated with salt solution (KCl, NaCl (two salinity levels, MgSO4, Mg(NO32, were inoculated with the mixture of preselected halophilic microorganisms, i.e., bacteria: Halobacillus styriensis, Halobacillus naozhouensis, Halobacillus hunanensis, Staphylococcus succinus, Marinococcus halophilus, Virgibacillus halodenitryficans, and yeast: Sterigmatomyces halophilus and stored at 28°C and 80% relative humidity for a year. Metabolites were extracted directly from the brick samples and measured via HPLC/HRMS in both positive and negative ion modes. Overall, untargeted metabolomics allowed for discovering the interactions of halophilic microorganisms with buildings materials which together with CARS microscopy enabled us to elucidate the biodeterioration process caused by halophiles. We observed that halophile metabolome was differently affected by different salt solutions. Furthermore, we found indications for haloadaptive strategies and degradation of brick samples due to microbial pigment production as a salt stress response. Finally, we detected changes in lipid content related to changes in the structure of phospholipid bilayers and membrane fluidity.

  2. Mono-colonization with Lactobacillus acidophilus NCFM affects the intestinal metabolome as compared to germ-free mice

    DEFF Research Database (Denmark)

    Roager, Henrik Munch; Sulek, Karolina; Skov, Kasper

    of colonizing bacteria. In this study the effect of the Lactobacillus acidophilus NCFM strain was investigated by comparing the metabolome of mono-colonized and germ-free mice in several compartments. By liquid-chromatography coupled to mass spectrometry, we were able to show that the metabolome differed...

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

    Energy Technology Data Exchange (ETDEWEB)

    Rivas-Ubach, Albert [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland Washington 99354 USA; CREAF, Cerdanyola del Vallès 08913 Catalonia Spain; Hódar, José A. [Grupo de Ecología Terrestre, Departamento de Biología Animal y Ecología, Facultad de Ciencias, Universidad de Granada, 18071 Granada Spain; Sardans, Jordi [CREAF, Cerdanyola del Vallès 08913 Catalonia Spain; CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB, Cerdanyola del Vallès 08913 Catalonia Spain; Kyle, Jennifer E. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington 99354 USA; Kim, Young-Mo [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington 99354 USA; Oravec, Michal [Global Change Research Centre, Academy of Sciences of the Czech Republic, Bĕlidla 4a CZ-603 00 Brno Czech Republic; Urban, Otmar [Global Change Research Centre, Academy of Sciences of the Czech Republic, Bĕlidla 4a CZ-603 00 Brno Czech Republic; Guenther, Alex [Department of Earth System Science, University of California, Irvine California 92697 USA; Peñuelas, Josep [CREAF, Cerdanyola del Vallès 08913 Catalonia Spain; CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB, Cerdanyola del Vallès 08913 Catalonia Spain

    2016-06-02

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

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

    Directory of Open Access Journals (Sweden)

    Stéphane Demine

    2014-09-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  7. Frontiers in nutrigenomics, proteomics, metabolomics and cancer prevention.

    Science.gov (United States)

    Davis, Cindy D; Milner, John

    2004-07-13

    While dietary habits continue to surface as a significant factor that may influence cancer incidence and tumor behavior, there is considerable scientific uncertainty about who will benefit most. Adequate [corrected] knowledge about how the responses depend on an individual's genetic background (nutrigenetic effects), the cumulative effects of food components on genetic expression profiles (nutritional transcriptomics and nutritional epigenomics effects), the occurrence and activity of proteins (proteomic effects) and/or the dose and temporal changes in cellular small molecular weight compounds (metabolomics effects) will [corrected] assist in identifying responders and non-responders. Expanding the information about similarities and differences in the "omic" responses across tissues will not only provide clues about specificity in response to bioactive food components but assist in the identification of surrogate tissues and biomarkers that can be used for predicting a response. Deciphering the importance of each of these potential sites of regulation will be particularly challenging but does hold promise in explaining many of the inconsistencies in the literature.

  8. Association genetics of the loblolly pine (Pinus taeda, Pinaceae) metabolome.

    Science.gov (United States)

    Eckert, Andrew J; Wegrzyn, Jill L; Cumbie, W Patrick; Goldfarb, Barry; Huber, Dudley A; Tolstikov, Vladimir; Fiehn, Oliver; Neale, David B

    2012-03-01

    The metabolome of a plant comprises all small molecule metabolites, which are produced during cellular processes. The genetic basis for metabolites in nonmodel plants is unknown, despite frequently observed correlations between metabolite concentrations and stress responses. A quantitative genetic analysis of metabolites in a nonmodel plant species is thus warranted. Here, we use standard association genetic methods to correlate 3563 single nucleotide polymorphisms (SNPs) to concentrations of 292 metabolites measured in a single loblolly pine (Pinus taeda) association population. A total of 28 single locus associations were detected, representing 24 and 20 unique SNPs and metabolites, respectively. Multilocus Bayesian mixed linear models identified 2998 additional associations for a total of 1617 unique SNPs associated to 255 metabolites. These SNPs explained sizeable fractions of metabolite heritabilities when considered jointly (56.6% on average) and had lower minor allele frequencies and magnitudes of population structure as compared with random SNPs. Modest sets of SNPs (n = 1-23) explained sizeable portions of genetic effects for many metabolites, thus highlighting the importance of multi-SNP models to association mapping, and exhibited patterns of polymorphism consistent with being linked to targets of natural selection. The implications for association mapping in forest trees are discussed. © 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.

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

    Science.gov (United States)

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

    2017-09-01

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

  10. Environmental metabolomics with data science for investigating ecosystem homeostasis.

    Science.gov (United States)

    Kikuchi, Jun; Ito, Kengo; Date, Yasuhiro

    2018-02-01

    A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches. Copyright © 2017. Published by Elsevier B.V.

  11. Nontargeted Metabolomics Reveals the Multilevel Response to Antibiotic Perturbations.

    Science.gov (United States)

    Zampieri, Mattia; Zimmermann, Michael; Claassen, Manfred; Sauer, Uwe

    2017-05-09

    Microbes have shown a remarkable ability in evading the killing actions of antimicrobial agents, such that treatment of bacterial infections represents once more an urgent global challenge. Understanding the initial bacterial response to antimicrobials may reveal intrinsic tolerance mechanisms to antibiotics and suggest alternative and less conventional therapeutic strategies. Here, we used mass spectrometry-based metabolomics to monitor the immediate metabolic response of Escherichia coli to a variety of antibiotic perturbations. We show that rapid metabolic changes can reflect drug mechanisms of action and reveal the active role of metabolism in mediating the first stress response to antimicrobials. We uncovered a role for ammonium imbalance in aggravating chloramphenicol toxicity and the essential function of deoxythymidine 5'-diphosphate (dTDP)-rhamnose synthesis for the immediate transcriptional upregulation of GyrA in response to quinolone antibiotics. Our results suggest bacterial metabolism as an attractive target to interfere with the early bacterial response to antibiotic treatments and reduce the probability for survival and eventual evolution of antibiotic resistance. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  12. Metabolomics Approach Reveals Integrated Metabolic Network Associated with Serotonin Deficiency

    Science.gov (United States)

    Weng, Rui; Shen, Sensen; Tian, Yonglu; Burton, Casey; Xu, Xinyuan; Liu, Yi; Chang, Cuilan; Bai, Yu; Liu, Huwei

    2015-07-01

    Serotonin is an important neurotransmitter that broadly participates in various biological processes. While serotonin deficiency has been associated with multiple pathological conditions such as depression, schizophrenia, Alzheimer’s disease and Parkinson’s disease, the serotonin-dependent mechanisms remain poorly understood. This study therefore aimed to identify novel biomarkers and metabolic pathways perturbed by serotonin deficiency using metabolomics approach in order to gain new metabolic insights into the serotonin deficiency-related molecular mechanisms. Serotonin deficiency was achieved through pharmacological inhibition of tryptophan hydroxylase (Tph) using p-chlorophenylalanine (pCPA) or genetic knockout of the neuronal specific Tph2 isoform. This dual approach improved specificity for the serotonin deficiency-associated biomarkers while minimizing nonspecific effects of pCPA treatment or Tph2 knockout (Tph2-/-). Non-targeted metabolic profiling and a targeted pCPA dose-response study identified 21 biomarkers in the pCPA-treated mice while 17 metabolites in the Tph2-/- mice were found to be significantly altered compared with the control mice. These newly identified biomarkers were associated with amino acid, energy, purine, lipid and gut microflora metabolisms. Oxidative stress was also found to be significantly increased in the serotonin deficient mice. These new biomarkers and the overall metabolic pathways may provide new understanding for the serotonin deficiency-associated mechanisms under multiple pathological states.

  13. Chemical Structure Identification in Metabolomics: Computational Modeling of Experimental Features

    Directory of Open Access Journals (Sweden)

    Lochana C Menikarachchi

    2013-02-01

    Full Text Available The identification of compounds in complex mixtures remains challenging despite recent advances in analytical techniques. At present, no single method can detect and quantify the vast array of compounds that might be of potential interest in metabolomics studies. High performance liquid chromatography/mass spectrometry (HPLC/MS is often considered the analytical method of choice for analysis of biofluids. The positive identification of an unknown involves matching at least two orthogonal HPLC/MS measurements (exact mass, retention index, drift time etc. against an authentic standard. However, due to the limited availability of authentic standards, an alternative approach involves matching known and measured features of the unknown compound with computationally predicted features for a set of candidate compounds downloaded from a chemical database. Computationally predicted features include retention index, ECOM50 (energy required to decompose 50% of a selected precursor ion in a collision induced dissociation cell, drift time, whether the unknown compound is biological or synthetic and a collision induced dissociation (CID spectrum. Computational predictions are used to filter the initial “bin” of candidate compounds. The final output is a ranked list of candidates that best match the known and measured features. In this mini review, we discuss cheminformatics methods underlying this database search-filter identification approach.

  14. Metabolomic profiling of doxycycline treatment in chronic obstructive pulmonary disease.

    Science.gov (United States)

    Singh, Brajesh; Jana, Saikat K; Ghosh, Nilanjana; Das, Soumen K; Joshi, Mamata; Bhattacharyya, Parthasarathi; Chaudhury, Koel

    2017-01-05

    Serum metabolic profiling can identify the metabolites responsible for discrimination between doxycycline treated and untreated chronic obstructive pulmonary disease (COPD) and explain the possible effect of doxycycline in improving the disease conditions. 1 H nuclear magnetic resonance (NMR)-based metabolomics was used to obtain serum metabolic profiles of 60 add-on doxycycline treated COPD patients and 40 patients receiving standard therapy. The acquired data were analyzed using multivariate principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). A clear metabolic differentiation was apparent between the pre and post doxycycline treated group. The distinguishing metabolites lactate and fatty acids were significantly down-regulated and formate, citrate, imidazole and l-arginine upregulated. Lactate and folate are further validated biochemically. Metabolic changes, such as decreased lactate level, inhibited arginase activity and lowered fatty acid level observed in COPD patients in response to add-on doxycycline treatment, reflect the anti-inflammatory action of the drug. Doxycycline as a possible therapeutic option for COPD seems promising. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. The Guard Cell Metabolome: Functions in Stomatal Movement and Global Food Security

    Directory of Open Access Journals (Sweden)

    Biswapriya eMisra

    2015-05-01

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

  16. Plasma metabolomic profiles in breast cancer patients and healthy controls: by race and tumor receptor subtypes.

    Science.gov (United States)

    Shen, Jie; Yan, Li; Liu, Song; Ambrosone, Christine B; Zhao, Hua

    2013-12-01

    A few studies in the last several years have shown that metabolomics, the study of metabolites and small intermediate molecules, may help better understand the breast carcinogenesis. However, breast cancer is a heterogeneous disease with different subtypes. Additionally, there is a significant racial difference in terms of breast cancer incidence and mortality. Few, if any, metabolomics studies in breast cancer have considered race and tumor subtypes in the study design. We performed a global metabolomic profiling using mass spectrometry and samples from 60 breast cancer cases and 60 matched controls. A total of 375 named metabolites were observed, with 117 metabolites whose levels were significantly different between African American and Caucasian American women (P racial difference.

  17. Variable selection in the explorative analysis of several data blocks in metabolomics

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Nørskov, Natalja; Yde, Christian Clement

    for biological validation. The data set used in this study is metabolomics data from an animal intervention study. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using NMR and LC-MS based...... associated with these effects are far from fully understood. This is due to the diversity of active constituents in whole grain and the complexity in the response to each of them. Metabolomic approaches being capable of describing the effects of diet on metabolism are ideally suited to address this issue....... For the present study three experimental diets were formulated containing whole grain, wheat aleurone, and an aleurone enriched rye fraction, respectively. The diets were fed to six pigs in a repeated 3 x 3 latin square design and a standard wheat flour diet was used as wash-out diet between the experimental...

  18. Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness.

    Directory of Open Access Journals (Sweden)

    Katarzyna Bozek

    2014-05-01

    Full Text Available Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys.

  19. Impacts of endophyte infection of ryegrass on rhizosphere metabolome and microbial community

    DEFF Research Database (Denmark)

    Wakelin, S.; Harrison, Scott James; Mander, C.

    2015-01-01

    of these interactions on rhizosphere microbiology are not well characterised. This is important, because there may be opportunities or risks associated with selective disruption of the rhizosphere microbiota. We explored the interaction of two commercially used endophyte fungi, E. festucae var. lolii strains AR1 and AR......37, within a genetically uniform breeding line of perennial ryegrass (Lolium perenne cv. Samson 11104) on the rhizosphere metabolome and the composition of the fungal, bacterial, and Pseudomonas communities. There were strong differences in the rhizosphere metabolomes between infested and non......-infested ryegrass strains (P=0.06). These were attributed to shifts in various n-alkane hydrocarbon compounds. The endophyte-associated alteration in rhizosphere metabolome was linked to changes in the total bacterial (Pcommunities. Furthermore, there was varying levels...

  20. Local false discovery rate estimation using feature reliability in LC/MS metabolomics data.

    Science.gov (United States)

    Chong, Elizabeth Y; Huang, Yijian; Wu, Hao; Ghasemzadeh, Nima; Uppal, Karan; Quyyumi, Arshed A; Jones, Dean P; Yu, Tianwei

    2015-11-24

    False discovery rate (FDR) control is an important tool of statistical inference in feature selection. In mass spectrometry-based metabolomics data, features can be measured at different levels of reliability and false features are often detected in untargeted metabolite profiling as chemical and/or bioinformatics noise. The traditional false discovery rate methods treat all features equally, which can cause substantial loss of statistical power to detect differentially expressed features. We propose a reliability index for mass spectrometry-based metabolomics data with repeated measurements, which is quantified using a composite measure. We then present a new method to estimate the local false discovery rate (lfdr) that incorporates feature reliability. In simulations, our proposed method achieved better balance between sensitivity and controlling false discovery, as compared to traditional lfdr estimation. We applied our method to a real metabolomics dataset and were able to detect more differentially expressed metabolites that were biologically meaningful.

  1. Impact of exercise on fecal and cecal metabolome over aging: a longitudinal study in rats.

    Science.gov (United States)

    Deda, Olga; Gika, Helen; Panagoulis, Theodoros; Taitzoglou, Ioannis; Raikos, Nikolaos; Theodoridis, Georgios

    2017-01-01

    Physical exercise can reduce adverse conditions during aging, while both exercise and aging act as metabolism modifiers. The present study investigates rat fecal and cecal metabolome alterations derived from exercise during rats' lifespan. Groups of rats trained life-long or for a specific period of time were under study. The training protocol consisted of swimming, 15-18 min per day, 3-5 days per week, with load of 4-0% of rat's weight. Fecal samples and cecal extracts were analyzed by targeted and untargeted metabolic profiling methods (GC-MS and LC-MS/MS). Effects of exercise and aging on the rats' fecal and cecal metabolome were observed. Fecal and cecal metabolomics are a promising field to investigate exercise biochemistry and age-related alterations.

  2. Three-Dimensional Microbiome and Metabolome Cartography of a Diseased Human Lung.

    Science.gov (United States)

    Garg, Neha; Wang, Mingxun; Hyde, Embriette; da Silva, Ricardo R; Melnik, Alexey V; Protsyuk, Ivan; Bouslimani, Amina; Lim, Yan Wei; Wong, Richard; Humphrey, Greg; Ackermann, Gail; Spivey, Timothy; Brouha, Sharon S; Bandeira, Nuno; Lin, Grace Y; Rohwer, Forest; Conrad, Douglas J; Alexandrov, Theodore; Knight, Rob; Dorrestein, Pieter C

    2017-11-08

    Our understanding of the spatial variation in the chemical and microbial makeup of an entire human organ remains limited, in part due to the size and heterogeneity of human organs and the complexity of the associated metabolome and microbiome. To address this challenge, we developed a workflow to enable the cartography of metabolomic and microbiome data onto a three-dimensional (3D) organ reconstruction built off radiological images. This enabled the direct visualization of the microbial and chemical makeup of a human lung from a cystic fibrosis patient. We detected host-derived molecules, microbial metabolites, medications, and region-specific metabolism of medications and placed it in the context of microbial distributions in the lung. Our tool further created browsable maps of a 3D microbiome/metabolome reconstruction map on a radiological image of a human lung and forms an interactive resource for the scientific community. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods

    Energy Technology Data Exchange (ETDEWEB)

    Bingol, Ahmet K.

    2018-04-18

    Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome manual absolute quantitation step of metabolites in 1D 1H NMR spectra. This provides more consistency between inter-laboratory comparisons. Integration of 2D NMR metabolomics databases under a unified web server allowed very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry. These hybrid NMR/MS approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing to profile ever larger number of metabolites in application studies.

  4. Biomarkers for predicting type 2 diabetes development — Can metabolomics improve on existing biomarkers?

    DEFF Research Database (Denmark)

    Savolainen, Otto; Fagerberg, Björn; Lind, Mads Vendelbo

    2017-01-01

    Aim The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Methods Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based...... on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years followup. The metabolomics results were used as a standalone prediction...... model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Results Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin...

  5. Preanalytical aspects and sample quality assessment in metabolomics studies of human blood.

    Science.gov (United States)

    Yin, Peiyuan; Peter, Andreas; Franken, Holger; Zhao, Xinjie; Neukamm, Sabine S; Rosenbaum, Lars; Lucio, Marianna; Zell, Andreas; Häring, Hans-Ulrich; Xu, Guowang; Lehmann, Rainer

    2013-05-01

    Metabolomics is a powerful tool that is increasingly used in clinical research. Although excellent sample quality is essential, it can easily be compromised by undetected preanalytical errors. We set out to identify critical preanalytical steps and biomarkers that reflect preanalytical inaccuracies. We systematically investigated the effects of preanalytical variables (blood collection tubes, hemolysis, temperature and time before further processing, and number of freeze-thaw cycles) on metabolomics studies of clinical blood and plasma samples using a nontargeted LC-MS approach. Serum and heparinate blood collection tubes led to chemical noise in the mass spectra. Distinct, significant changes of 64 features in the EDTA-plasma metabolome were detected when blood was exposed to room temperature for 2, 4, 8, and 24 h. The resulting pattern was characterized by increases in hypoxanthine and sphingosine 1-phosphate (800% and 380%, respectively, at 2 h). In contrast, the plasma metabolome was stable for up to 4 h when EDTA blood samples were immediately placed in iced water. Hemolysis also caused numerous changes in the metabolic profile. Unexpectedly, up to 4 freeze-thaw cycles only slightly changed the EDTA-plasma metabolome, but increased the individual variability. Nontargeted metabolomics investigations led to the following recommendations for the preanalytical phase: test the blood collection tubes, avoid hemolysis, place whole blood immediately in ice water, use EDTA plasma, and preferably use nonrefrozen biobank samples. To exclude outliers due to preanalytical errors, inspect the biomarker signal intensities reflecting systematic as well as accidental and preanalytical inaccuracies before processing the bioinformatics data. © 2013 American Association for Clinical Chemistry.

  6. A Nontargeted UHPLC-HRMS Metabolomics Pipeline for Metabolite Identification: Application to Cardiac Remote Ischemic Preconditioning.

    Science.gov (United States)

    Kouassi Nzoughet, Judith; Bocca, Cinzia; Simard, Gilles; Prunier-Mirebeau, Delphine; Chao de la Barca, Juan Manuel; Bonneau, Dominique; Procaccio, Vincent; Prunier, Fabrice; Lenaers, Guy; Reynier, Pascal

    2017-02-07

    In recent years, the number of investigations based on nontargeted metabolomics has increased, although often without a thorough assessment of analytical strategies applied to acquire data. Following published guidelines for metabolomics experiments, we report a validated nontargeted metabolomics strategy with pipeline for unequivocal identification of metabolites using the MSMLS molecule library. We achieved an in-house database containing accurate m/z values, retention times, isotopic patterns, full MS, and MS/MS spectra. A UHPLC-HRMS Q-Exactive method was developed, and experimental variations were determined within and between 3 experimental days. The extraction efficiency as well as the accuracy, precision, repeatability, and linearity of the method were assessed, the method demonstrating good performances. The methodology was further blindly applied to plasma from remote ischemic pre-conditioning (RIPC) rats. Samples, previously analyzed by targeted metabolomics using completely different protocol, analytical strategy, and platform, were submitted to our analytical pipeline. A combination of multivariate and univariate statistical analyses was employed. Selection of putative biomarkers from OPLS-DA model and S-plot was combined to jack-knife confidence intervals, metabolites' VIP values, and univariate statistics. Only variables with strong model contribution and highly statistical reliability were selected as discriminated metabolites. Three biomarkers identified by the previous targeted metabolomics study were found in the current work, in addition to three novel metabolites, emphasizing the efficiency of the current methodology and its ability to identify new biomarkers of clinical interest, in a single sequence. The biomarkers were identified to level 1 according to the metabolomics standard initiative and confirmed by both RPLC and HILIC-HRMS.

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

    Science.gov (United States)

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

    2016-04-01

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

  8. Metabolomic derangements are associated with mortality in critically ill adult patients.

    Science.gov (United States)

    Rogers, Angela J; McGeachie, Michael; Baron, Rebecca M; Gazourian, Lee; Haspel, Jeffrey A; Nakahira, Kiichi; Fredenburgh, Laura E; Hunninghake, Gary M; Raby, Benjamin A; Matthay, Michael A; Otero, Ronny M; Fowler, Vance G; Rivers, Emanuel P; Woods, Christopher W; Kingsmore, Stephen; Langley, Ray J; Choi, Augustine M K

    2014-01-01

    To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults. Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible. We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study. We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations). Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill

  9. Metabolomic derangements are associated with mortality in critically ill adult patients.

    Directory of Open Access Journals (Sweden)

    Angela J Rogers

    Full Text Available To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU mortality in adults.Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible.We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI. We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD study.We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05. Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05 in the CAPSOD population. Replicating metabolites included lipids (N = 14, amino acids or amino acid breakdown products (N = 12, carbohydrates (N = 1, nucleotides (N = 3, and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4, taurochenodeoxycholate, 3-(4-hydroxyphenyl lactate, sucrose, kynurenine. This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations.Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill

  10. MetabR: an R script for linear model analysis of quantitative metabolomic data

    Directory of Open Access Journals (Sweden)

    Ernest Ben

    2012-10-01

    Full Text Available Abstract Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

  11. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    Energy Technology Data Exchange (ETDEWEB)

    Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

    2012-10-31

    Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  12. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis.

    Science.gov (United States)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan E; Jia, Wei; Xie, Guoxiang; Garmire, Lana X

    2016-03-31

    More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies. We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis.

  13. Data standards can boost metabolomics research, and if there is a will, there is a way.

    Science.gov (United States)

    Rocca-Serra, Philippe; Salek, Reza M; Arita, Masanori; Correa, Elon; Dayalan, Saravanan; Gonzalez-Beltran, Alejandra; Ebbels, Tim; Goodacre, Royston; Hastings, Janna; Haug, Kenneth; Koulman, Albert; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Schober, Daniel; Smith, James; Steinbeck, Christoph; Viant, Mark R; Neumann, Steffen

    2016-01-01

    Thousands of articles using metabolomics approaches are published every year. With the increasing amounts of data being produced, mere description of investigations as text in manuscripts is not sufficient to enable re-use anymore: the underlying data needs to be published together with the findings in the literature to maximise the benefit from public and private expenditure and to take advantage of an enormous opportunity to improve scientific reproducibility in metabolomics and cognate disciplines. Reporting recommendations in metabolomics started to emerge about a decade ago and were mostly concerned with inventories of the information that had to be reported in the literature for consistency. In recent years, metabolomics data standards have developed extensively, to include the primary research data, derived results and the experimental description and importantly the metadata in a machine-readable way. This includes vendor independent data standards such as mzML for mass spectrometry and nmrML for NMR raw data that have both enabled the development of advanced data processing algorithms by the scientific community. Standards such as ISA-Tab cover essential metadata, including the experimental design, the applied protocols, association between samples, data files and the experimental factors for further statistical analysis. Altogether, they pave the way for both reproducible research and data reuse, including meta-analyses. Further incentives to prepare standards compliant data sets include new opportunities to publish data sets, but also require a little "arm twisting" in the author guidelines of scientific journals to submit the data sets to public repositories such as the NIH Metabolomics Workbench or MetaboLights at EMBL-EBI. In the present article, we look at standards for data sharing, investigate their impact in metabolomics and give suggestions to improve their adoption.

  14. Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease

    Directory of Open Access Journals (Sweden)

    Robert A. Quinn

    2016-08-01

    Full Text Available Background. Cystic fibrosis (CF is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS. The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable. Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset.

  15. Integrated work-flow for quantitative metabolome profiling of plants, Peucedani Radix as a case.

    Science.gov (United States)

    Song, Yuelin; Song, Qingqing; Liu, Yao; Li, Jun; Wan, Jian-Bo; Wang, Yitao; Jiang, Yong; Tu, Pengfei

    2017-02-08

    Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only

  16. Linalool is a PPARα ligand that reduces plasma TG levels and rewires the hepatic transcriptome and plasma metabolome[S

    Science.gov (United States)

    Jun, Hee-jin; Lee, Ji Hae; Kim, Jiyoung; Jia, Yaoyao; Kim, Kyoung Heon; Hwang, Kwang Yeon; Yun, Eun Ju; Do, Kyoung-Rok; Lee, Sung-Joon

    2014-01-01

    We investigated the hypotriglyceridemic mechanism of action of linalool, an aromatic monoterpene present in teas and fragrant herbs. Reporter gene and time-resolved fluorescence resonance energy transfer assays demonstrated that linalool is a direct ligand of PPARα. Linalool stimulation reduced cellular lipid accumulation regulating PPARα-responsive genes and significantly induced FA oxidation, and its effects were markedly attenuated by silencing PPARα expression. In mice, the oral administration of linalool for 3 weeks reduced plasma TG concentrations in Western-diet-fed C57BL/6J mice (31%, P linalool stimulation rewired global gene expression in lipid-loaded hepatocytes and that the effects of 1 mM linalool were comparable to those of 0.1 mM fenofibrate. Metabolomic analysis of the mouse plasma revealed that the global metabolite profiles were significantly distinguishable between linalool-fed mice and controls. Notably, the concentrations of saturated FAs were significantly reduced in linalool-fed mice. These findings suggest that the appropriate intake of a natural aromatic compound could exert beneficial metabolic effects by regulating a cellular nutrient sensor. PMID:24752549

  17. Metabolomic approach to human brain spectroscopy identifies associations between clinical features and the frontal lobe metabolome in multiple sclerosis

    Science.gov (United States)

    Vingara, Lisa K.; Yu, Hui Jing; Wagshul, Mark E.; Serafin, Dana; Christodoulou, Christopher; Pelczer, István; Krupp, Lauren B.; Maletić-Savatić, Mirjana

    2013-01-01

    Proton magnetic resonance spectroscopy (1H-MRS) is capable of noninvasively detecting metabolic changes that occur in the brain tissue in vivo. Its clinical utility has been limited so far, however, by analytic methods that focus on independently evaluated metabolites and require prior knowledge about which metabolites to examine. Here, we applied advanced computational methodologies from the field of metabolomics, specifically partial least squares discriminant analysis and orthogonal partial least squares, to in vivo 1H-MRS from frontal lobe white matter of 27 patients with relapsing–remitting multiple sclerosis (RRMS) and 14 healthy controls. We chose RRMS, a chronic demyelinating disorder of the central nervous system, because its complex pathology and variable disease course make the need for reliable biomarkers of disease progression more pressing. We show that in vivo MRS data, when analyzed by multivariate statistical methods, can provide reliable, distinct profiles of MRS-detectable metabolites in different patient populations. Specifically, we find that brain tissue in RRMS patients deviates significantly in its metabolic profile from that of healthy controls, even though it appears normal by standard MRI techniques. We also identify, using statistical means, the metabolic signatures of certain clinical features common in RRMS, such as disability score, cognitive impairments, and response to stress. This approach to human in vivo MRS data should promote understanding of the specific metabolic changes accompanying disease pathogenesis, and could provide biomarkers of disease progression that would be useful in clinical trials. PMID:23751863

  18. Metabolomics: a bird’s eye view of infertile men: review article

    Directory of Open Access Journals (Sweden)

    Niloofar Agharezaee

    2018-03-01

    Full Text Available Infertility influences an estimated 20% of couples worldwide. The factors that can affect the fertility potential are equally distributed between men and women. Despite extensive research in male infertility, the etiology in majority of infertile men is unknown. In 2010, there was an opinion published in Nature asking a selection of leading researchers and policy-makers about what their future focuses will be in 2020. Metabolomics was mentioned as the leading omics technology by them. The word metabolomics has been defined almost 20 years ago. However, the clinical metabolomics history goes back to more than 1,000 years ago. The great Persian physician and philosopher Avicenna observed an individual urine changes during illness. Today, the color or smell changes are known to be caused by metabolites deregulation indicating metabolic diseases. Metabolomics approach is a systematic analysis of the unique pattern followed by a specific biochemical pathway that uses a biological material, e.g. spermatozoa or human seminal plasma. For the diagnosis of infertile men, the typical parameters of semen analysis are: sperm motility, sperm morphology, concentration and count. Human seminal plasma is a valuable biological source which was not used in the diagnosis of infertile men, unfortunately. To the best of our knowledge, there is no parameter for analysis of the human seminal plasma. Thus, the need for a novel parameter to diagnose infertile men is urgently needed. We recommend the use of seminal plasma in order to diagnose infertile men according to our previous research. Only a handful studies have used metabolomics approaches in the male infertility. In this study, we summarize the current research and our contribution to the field of male infertility and metabolomics. One of our main contributions has been to use metabolic profiling of seminal plasma from non-obstructive azoospermia to find 36 potentials biomarkers for detection of spermatogenesis

  19. Navigating the human metabolome for biomarker identification and design of pharmaceutical molecules

    DEFF Research Database (Denmark)

    Kouskoumvekaki, Irene; Panagiotou, Gianni

    2010-01-01

    Metabolome Database (HMDB) and the Chinese Natural Product Database (CNPD), we demonstrate the close relatedness of the two data sets of compounds, and we further illustrate how structural similarity with human metabolites could assist in the design of novel pharmaceuticals and the elucidation......, neurological and other diseases, we demonstrate how these tools can facilitate diagnosis and identification of potential biomarkers for use within disease diagnosis. Additionally, we discuss the increasing importance of the integration of metabolomics data in drug discovery. On a case-study based on the Human...

  20. LC-MS-Based Metabolomic Investigation of Chemopreventive Phytochemical-Elicited Metabolic Events.

    Science.gov (United States)

    Wang, Lei; Yao, Dan; Chen, Chi

    2016-01-01

    Phytochemicals are under intensive investigation for their potential use as chemopreventive agents in blocking or suppressing carcinogenesis. Metabolic interactions between phytochemical and biological system play an important role in determining the efficacy and toxicity of chemopreventive phytochemicals. However, complexities of phytochemical biotransformation and intermediary metabolism pose challenges for studying phytochemical-elicited metabolic events. Metabolomics has become a highly effective technical platform to detect subtle changes in a complex metabolic system. Here, using green tea polyphenols as an example, we describe a workflow of LC-MS-based metabolomics study, covering the procedures and techniques in sample collection, preparation, LC-MS analysis, data analysis, and interpretation.

  1. Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data.

    Science.gov (United States)

    Forssen, Henrietta; Patel, Riyaz; Fitzpatrick, Natalie; Hingorani, Aroon; Timmis, Adam; Hemingway, Harry; Denaxas, Spiros

    2017-01-01

    Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a priori selected input features and thus might suffer from poorer accuracy. Supervised machine learning methods can potentially be used in order to fully exploit the dimensionality and richness of the data. In this paper, we systematically implement and evaluate a set of supervised learning methods (L1 regression, random forest classifier) and compare them to traditional regression-based approaches for disease prediction using metabolomic data.

  2. Coping with iron limitation: a metabolomic study of Synechocystis sp PCC 6803

    Czech Academy of Sciences Publication Activity Database

    Rivas-Ubach, A.; Poret-Peterson, A. T.; Penuelas, J.; Sardans, J.; Pérez-Trujillo, M.; Legido-Quigley, C.; Oravec, Michal; Urban, Otmar; Elser, J. J.

    2018-01-01

    Roč. 40, č. 2 (2018), č. článku 28. ISSN 0137-5881 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk(CZ) LM2015061 Institutional support: RVO:86652079 Keywords : sp strain pcc-6803 * ocean acidification * unicellular cyanobacterium * marine-phytoplankton * foliar metabolomes * nitrogen-fixation * metal homeostasis * oxidative stress * pacific-ocean * responses * Metabolomics * Metallomics * Iron limitation * Cyanobacteria * Ecological stoichiometry Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 1.364, year: 2016

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

    Science.gov (United States)

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

    2017-12-01

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

  4. Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

    Energy Technology Data Exchange (ETDEWEB)

    Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J., E-mail: myrna.simpson@utoronto.ca

    2016-01-15

    Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: {sup 1}H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of {sup 1}H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by

  5. Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

    International Nuclear Information System (INIS)

    Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J.

    2016-01-01

    Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: 1 H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of 1 H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by changes in the

  6. Understanding Aquatic Rhizosphere Processes Through Metabolomics and Metagenomics Approach

    Science.gov (United States)

    Lee, Yong Jian; Mynampati, Kalyan; Drautz, Daniela; Arumugam, Krithika; Williams, Rohan; Schuster, Stephan; Kjelleberg, Staffan; Swarup, Sanjay

    2013-04-01

    The aquatic rhizosphere is a region around the roots of aquatic plants. Many studies focusing on terrestrial rhizosphere have led to a good understanding of the interactions between the roots, its exudates and its associated rhizobacteria. The rhizosphere of free-floating roots, however, is a different habitat that poses several additional challenges, including rapid diffusion rates of signals and nutrient molecules, which are further influenced by the hydrodynamic forces. These can lead to rapid diffusion and complicates the studying of diffusible factors from both plant and/or rhizobacterial origins. These plant systems are being increasingly used for self purification of water bodies to provide sustainable solution. A better understanding of these processes will help in improving their performance for ecological engineering of freshwater systems. The same principles can also be used to improve the yield of hydroponic cultures. Novel toolsets and approaches are needed to investigate the processes occurring in the aquatic rhizosphere. We are interested in understanding the interaction between root exudates and the complex microbial communities that are associated with the roots, using a systems biology approach involving metabolomics and metagenomics. With this aim, we have developed a RhizoFlowCell (RFC) system that provides a controlled study of aquatic plants, observed the root biofilms, collect root exudates and subject the rhizosphere system to changes in various chemical or physical perturbations. As proof of concept, we have used RFC to test the response of root exudation patterns of Pandanus amaryllifolius after exposure to the pollutant naphthalene. Complexity of root exudates in the aquatic rhizosphere was captured using this device and analysed using LC-qTOF-MS. The highly complex metabolomic profile allowed us to study the dynamics of the response of roots to varying levels of naphthalene. The metabolic profile changed within 5mins after spiking with

  7. Metabolome and proteome changes with aging in Caenorhabditis elegans

    Science.gov (United States)

    Copes, Neil; Edwards, Clare; Chaput, Dale; Saifee, Mariam; Barjuca, Iosif; Nelson, Daniel; Paraggio, Alyssa; Saad, Patrick; Lipps, David; Stevens, Stanley M.; Bradshaw, Patrick C.

    2015-01-01

    To expand the understanding of aging in the model organism Caenorhabditis elegans, global quantification of metabolite and protein levels in young and aged nematodes was performed using mass spectrometry. With age there was a decreased abundance of proteins functioning in transcription termination, mRNA degradation, mRNA stability, protein synthesis, and proteasomal function. Furthermore there was altered S-adenosyl methionine metabolism as well as a decreased abundance of the S-adenosyl methionine synthetase (SAMS-1) protein. Other aging-related changes included alterations in free fatty acid levels and composition, decreased levels of ribosomal proteins, decreased levels of NADP-dependent isocitrate dehydrogenase (IDH1), a shift in the cellular redox state, an increase in sorbitol content, alterations in free amino acid levels, and indications of altered muscle function and sarcoplasmic reticulum Ca2+ homeostasis. There were also decreases in pyrimidine and purine metabolite levels, most markedly nitrogenous bases. Supplementing the culture medium with cytidine (a pyrimidine nucleoside) or hypoxanthine (a purine base) increased lifespan slightly, suggesting that aging-induced alterations in ribonucleotide metabolism affect lifespan. An age-related increase in body size, lipotoxicity from ectopic yolk lipoprotein accumulation, a decline in NAD+ levels, and mitochondrial electron transport chain dysfunction may explain many of these changes. In addition, dietary restriction in aged worms resulting from sarcopenia of the pharyngeal pump likely decreases the abundance of SAMS-1, possibly leading to decreased phosphatidylcholine levels, larger lipid droplets, and ER and mitochondrial stress. The complementary use of proteomics and metabolomics yielded unique insights into the molecular processes altered with age in C. elegans. PMID:26390854

  8. Reconstruction of food webs in biological soil crusts using metabolomics.

    Science.gov (United States)

    Baran, Richard; Brodie, Eoin L.; Mayberry-Lewis, Jazmine; Nunes Da Rocha, Ulisses; Bowen, Benjamin P.; Karaoz, Ulas; Cadillo-Quiroz, Hinsby; Garcia-Pichel, Ferran; Northen, Trent R.

    2015-04-01

    Biological soil crusts (BSCs) are communities of organisms inhabiting the upper layer of soil in arid environments. BSCs persist in a dessicated dormant state for extended periods of time and experience pulsed periods of activity facilitated by infrequent rainfall. Microcoleus vaginatus, a non-diazotrophic filamentous cyanobacterium, is the key primary producer in BSCs in the Colorado Plateau and is an early pioneer in colonizing arid environments. Over decades, BSCs proceed through developmental stages with increasing complexity of constituent microorganisms and macroscopic properties. Metabolic interactions among BSC microorganisms probably play a key role in determining the community dynamics and cycling of carbon and nitrogen. However, these metabolic interactions have not been studied systematically. Towards this goal, exometabolomic analysis was performed using liquid chromatography coupled to tandem mass spectrometry on biological soil crust pore water and spent media of key soil bacterial isolates. Comparison of spent vs. fresh media was used to determine uptake or release of metabolites by specific microbes. To link pore water experiments with isolate studies, metabolite extracts of authentic soil were used as supplements for isolate exometabolomic profiling. Our soil metabolomics methods detected hundreds of metabolites from soils including many novel compounds. Overall, Microcoleus vaginatus was found to release and utilize a broad range of metabolites. Many of these metabolites were also taken up by heterotrophs but there were surprisingly few metabolites uptaken by all isolates. This points to a competition for a small set of central metabolites and specialization of individual heterotrophs towards a diverse pool of available organic nutrients. Overall, these data suggest that understanding the substrate specialization of biological soil crust bacteria can help link community structure to nutrient cycling.

  9. Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers.

    LENUS (Irish Health Repository)

    Kenny, Louise C

    2012-01-31

    Preeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery\\/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15+\\/-1 weeks\\' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15+\\/-1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.

  10. Proteomics, metabolomics and ionomics perspectives of salinity tolerance in halophytes

    Directory of Open Access Journals (Sweden)

    ASHA KUMARI YADAV

    2015-07-01

    Full Text Available Halophytes are plants which naturally survive in saline environment. They account for approximately 1% of the total flora of the world. They include both dicots and monocots and are distributed mainly in arid, semi-arid inlands and saline wet lands along the tropical and sub-tropical coasts. Salinity tolerance in halophytes depends on a set of ecological and physiological characteristics that allow them to grow and flourish in high saline conditions. The ability of halophytes to tolerate high salt is determined by the effective coordination between various physiological processes, metabolic pathways and protein or gene networks responsible for delivering salinity tolerance. The salinity responsive proteins belong to diverse functional classes such as photosynthesis, redox homeostasis, stress/defence, carbohydrate and energy metabolism, protein metabolism, signal transduction and membrane transport. The important metabolites which are involved in salt tolerance of halophytes are proline and proline analogue (4-hydroxy-N-methyl proline, glycine betaine, pinitol, myo-inositol, mannitol, sorbitol, O-methylmucoinositol and polyamines. In halophytes, the synthesis of specific proteins and osmotically active metabolites control ion and water flux and support scavenging of oxygen radicals under salt stress condition. The present review summarizes the salt tolerance mechanisms of halophytes by elucidating the recent studies that have focused on proteomic, metabolomic and ionomic aspects of various halophytes in response to salinity. By integrating the information from halophytes and its comparison with glycophytes could give an overview of salt tolerance mechanisms in halophytes, thus laying down the pavement for development of salt tolerant crop plants through genetic modification and effective breeding strategies.

  11. Robust Early Pregnancy Prediction of Later Preeclampsia Using Metabolomic Biomarkers.

    LENUS (Irish Health Repository)

    Kenny, Louise C

    2010-09-13

    Preeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery\\/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15±1 weeks\\' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15±1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.

  12. Metabolome and proteome changes with aging in Caenorhabditis elegans.

    Science.gov (United States)

    Copes, Neil; Edwards, Clare; Chaput, Dale; Saifee, Mariam; Barjuca, Iosif; Nelson, Daniel; Paraggio, Alyssa; Saad, Patrick; Lipps, David; Stevens, Stanley M; Bradshaw, Patrick C

    2015-12-01

    To expand the understanding of aging in the model organism Caenorhabditis elegans, global quantification of metabolite and protein levels in young and aged nematodes was performed using mass spectrometry. With age, there was a decreased abundance of proteins functioning in transcription termination, mRNA degradation, mRNA stability, protein synthesis, and proteasomal function. Furthermore, there was altered S-adenosyl methionine metabolism as well as a decreased abundance of the S-adenosyl methionine synthetase (SAMS-1) protein. Other aging-related changes included alterations in free fatty acid levels and composition, decreased levels of ribosomal proteins, decreased levels of NADP-dependent isocitrate dehydrogenase (IDH1), a shift in the cellular redox state, an increase in sorbitol content, alterations in free amino acid levels, and indications of altered muscle function and sarcoplasmic reticulum Ca(2+) homeostasis. There were also decreases in pyrimidine and purine metabolite levels, most markedly nitrogenous bases. Supplementing the culture medium with cytidine (a pyrimidine nucleoside) or hypoxanthine (a purine base) increased lifespan slightly, suggesting that aging-induced alterations in ribonucleotide metabolism affect lifespan. An age-related increase in body size, lipotoxicity from ectopic yolk lipoprotein accumulation, a decline in NAD(+) levels, and mitochondrial electron transport chain dysfunction may explain many of these changes. In addition, dietary restriction in aged worms resulting from sarcopenia of the pharyngeal pump likely decreases the abundance of SAMS-1, possibly leading to decreased phosphatidylcholine levels, larger lipid droplets, and ER and mitochondrial stress. The complementary use of proteomics and metabolomics yielded unique insights into the molecular processes altered with age in C. elegans. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics: the not-so-simple process of method performance evaluation.

    Science.gov (United States)

    Tulipani, Sara; Mora-Cubillos, Ximena; Jáuregui, Olga; Llorach, Rafael; García-Fuentes, Eduardo; Tinahones, Francisco J; Andres-Lacueva, Cristina

    2015-03-03

    Although LC-MS untargeted metabolomics continues to expand into exiting research domains, methodological issues have not been solved yet by the definition of unbiased, standardized and globally accepted analytical protocols. In the present study, the response of the plasma metabolome coverage to specific methodological choices of the sample preparation (two SPE technologies, three sample-to-solvent dilution ratios) and the LC-ESI-MS data acquisition steps of the metabolomics workflow (four RP columns, four elution solvent combinations, two solvent quality grades, postcolumn modification of the mobile phase) was investigated in a pragmatic and decision tree-like performance evaluation strategy. Quality control samples, reference plasma and human plasma from a real nutrimetabolomic study were used for intermethod comparisons. Uni- and multivariate data analysis approaches were independently applied. The highest method performance was obtained by combining the plasma hybrid extraction with the highest solvent proportion during sample preparation, the use of a RP column compatible with 100% aqueous polar phase (Atlantis T3), and the ESI enhancement by using UHPLC-MS purity grade methanol as both organic phase and postcolumn modifier. Results led to the following considerations: submit plasma samples to hybrid extraction for removal of interfering components to minimize the major sample-dependent matrix effects; avoid solvent evaporation following sample extraction if loss in detection and peak shape distortion of early eluting metabolites are not noticed; opt for a RP column for superior retention of highly polar species when analysis fractionation is not feasible; use ultrahigh quality grade solvents and "vintage" analytical tricks such as postcolumn organic enrichment of the mobile phase to enhance ESI efficiency. The final proposed protocol offers an example of how novel and old-fashioned analytical solutions may fruitfully cohabit in untargeted metabolomics

  14. An Ultrahigh-Performance Liquid Chromatography-Time-of-Flight Mass Spectrometry Metabolomic Approach to Studying the Impact of Moderate Red-Wine Consumption on Urinary Metabolome.

    Science.gov (United States)

    Esteban-Fernández, Adelaida; Ibañez, Clara; Simó, Carolina; Bartolomé, Begoña; Moreno-Arribas, M Victoria

    2018-04-06

    Moderate red-wine consumption has been widely described to exert several benefits in human health. This is mainly due to its unique content of bioactive polyphenols, which suffer several modifications along their pass through the digestive system, including microbial transformation in the colon and phase-II metabolism, until they are finally excreted in urine and feces. To determine the impact of moderate wine consumption in the overall urinary metabolome of healthy volunteers ( n = 41), samples from a red-wine interventional study (250 mL/day, 28 days) were investigated. Urine (24 h) was collected before and after intervention and analyzed by an untargeted ultrahigh-performance liquid chromatography-time-of-flight mass spectrometry metabolomics approach. 94 compounds linked to wine consumption, including specific wine components (tartaric acid), microbial-derived phenolic metabolites (5-(dihydroxyphenyl)-γ-valerolactones and 4-hydroxyl-5-(phenyl)-valeric acids), and endogenous compounds were identified. Also, some relationships between parallel fecal and urinary metabolomes are discussed.

  15. Metabolomic Pathways to Osteoporosis in Middle-Aged Women: A Genome-Metabolome-Wide Mendelian Randomization Study.

    Science.gov (United States)

    Moayyeri, Alireza; Cheung, Ching-Lung; Tan, Kathryn Cb; Morris, John A; Cerani, Agustin; Mohney, Robert P; Richards, J Brent; Hammond, Christopher; Spector, Tim D; Menni, Cristina

    2017-12-12

    The metabolic state of the body can be a major determinant of bone health. We used a Mendelian randomization approach to identify metabolites causally associated with bone mass to better understand the biological mechanisms of osteoporosis. We tested bone phenotypes (femoral neck, total hip, and lumbar spine bone mineral density [BMD]) for association with 280 fasting blood metabolites in 6055 women from TwinsUK cohort with genomewide genotyping scans. Causal associations between metabolites and bone phenotypes were further assessed in a bidirectional Mendelian randomization study using genetic markers/scores as instrumental variables. Significant associations were replicated in 624 participants from the Hong Kong Osteoporosis Study (HKOS). Fifteen metabolites showed direct associations with bone phenotypes after adjusting for covariates and multiple testing. Using genetic instruments, four of these metabolites were found to be causally associated with hip or spine BMD. These included androsterone sulfate, epiandrosterone sulfate, 5alpha-androstan-3beta17beta-diol disulfate (encoded by CYP3A5), and 4-androsten-3beta17beta-diol disulfate (encoded by SULT2A1). In the HKOS population, all four metabolites showed significant associations with hip and spine BMD in the expected directions. No causal reverse association between BMD and any of the metabolites were found. In the first metabolome-genomewide Mendelian randomization study of human bone mineral density, we identified four novel biomarkers causally associated with BMD. Our findings reveal novel biological pathways involved in the pathogenesis of osteoporosis. © 2017 American Society for Bone and Mineral Research. © 2017 American Society for Bone and Mineral Research.

  16. A 'Foodomic' Approach for the Evaluation of Food Quality and its Impact on the Human Metabolome

    DEFF Research Database (Denmark)

    Trimigno, Alessia

    In recent years, omic sciences have been increasingly employed in a multitude of research fields thanks to their high-throughput capabilities and holistic approach. Among the omic sciences, metabolomics and foodomics have recently emerged in the investigation of food and nutrition and their relat......In recent years, omic sciences have been increasingly employed in a multitude of research fields thanks to their high-throughput capabilities and holistic approach. Among the omic sciences, metabolomics and foodomics have recently emerged in the investigation of food and nutrition...... carried out both in Italy and in Denmark, outlines the analytical pipeline of the foodomic approach and highlights the current challenges in the field (Chapter 2.3). The thesis traces the path of modern foodomics and metabolomics from the definition and description of food quality (Chapters 3 to 6......), to the profiling of the metabolome (Chapters 7 to 8.5), and finally the investigation of the impact of food on the human health, the prevention of diseases, and the identification of biomarkers of health status (Chapters 8.6 and 8.7). The impact of factors such as genetic modification or farming method...

  17. Highlights of the 2012 research workshop: Using nutrigenomics and metabolomics in clinical nutrition research

    Science.gov (United States)

    The American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Research Workshop, "Using Nutrigenomics and Metabolomics in Clinical Nutrition Research," was held on January 21, 2012, in Orlando, Florida. The conference brought together experts in human nutrition who use nutrigenomic and meta...

  18. Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice

    NARCIS (Netherlands)

    Lu, Y.; Boekschoten, M.V.; Wopereis, S.; Müller, M.; Kersten, S.

    2011-01-01

    Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice. Physiol Genomics 43: 1307-1318, 2011. First published September 27, 2011; doi:10.1152/physiolgenomics.00100.2011. Elevated circulating triglycerides, which are considered a risk factor for

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

    Science.gov (United States)

    Costa, Christopher; Maraschin, Marcelo; Rocha, Miguel

    2016-06-01

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

  20. Accurate mass error correction in liquid chromatography time-of-flight mass spectrometry based metabolomics

    NARCIS (Netherlands)

    Mihaleva, V.V.; Vorst, O.F.J.; Maliepaard, C.A.; Verhoeven, H.A.; Vos, de C.H.; Hall, R.D.; Ham, van R.C.H.J.

    2008-01-01

    Compound identification and annotation in (untargeted) metabolomics experiments based on accurate mass require the highest possible accuracy of the mass determination. Experimental LC/TOF-MS platforms equipped with a time-to-digital converter (TDC) give the best mass estimate for those mass signals

  1. Novel chemistry of invasive plants: exotic species have more unique metabolomic profiles than native congeners

    NARCIS (Netherlands)

    Macel, M.; de Vos, R.C.H.; Jansen, J.J.; Van der Putten, W.H.; Van Dam, N.M.

    2014-01-01

    t is often assumed that exotic plants can become invasive when they possess novel secondary chemistry compared with native plants in the introduced range. Using untargeted metabolomic fingerprinting, we compared a broad range of metabolites of six successful exotic plant species and their native

  2. Plant Metabolomics and Its Potential for Systems Biology Research: Background Concepts, Technology, and Methodology

    NARCIS (Netherlands)

    Allwood, J.W.; Vos, de C.H.; Moing, A.; Deborde, C.; Erban, A.; Kopka, J.; Goodacre, R.; Hall, R.D.

    2011-01-01

    The "metabolome" comprises the entire complement of small molecules in a plant or any other organism. It represents the ultimate phenotype of cells, deduced from the perturbation of gene expression and the modulation of protein function, as well as environmental cues. Extensive advances over the

  3. Towards a scientific interpretation of the terroir concept: plasticity of the grape berry metabolome.

    Science.gov (United States)

    Anesi, Andrea; Stocchero, Matteo; Dal Santo, Silvia; Commisso, Mauro; Zenoni, Sara; Ceoldo, Stefania; Tornielli, Giovanni Battista; Siebert, Tracey E; Herderich, Markus; Pezzotti, Mario; Guzzo, Flavia

    2015-08-07

    The definition of the terroir concept is one of the most debated issues in oenology and viticulture. The dynamic interaction among diverse factors including the environment, the grapevine plant and the imposed viticultural techniques means that the wine produced in a given terroir is unique. However, there is an increasing interest to define and quantify the contribution of individual factors to a specific terroir objectively. Here, we characterized the metabolome and transcriptome of berries from a single clone of the Corvina variety cultivated in seven different vineyards, located in three macrozones, over a 3-year trial period. To overcome the anticipated strong vintage effect, we developed statistical tools that allowed us to identify distinct terroir signatures in the metabolic composition of berries from each macrozone, and from different vineyards within each macrozone. We also identified non-volatile and volatile components of the metabolome which are more plastic and therefore respond differently to terroir diversity. We observed some relationships between the plasticity of the metabolome and transcriptome, allowing a multifaceted scientific interpretation of the terroir concept. Our experiments with a single Corvina clone in different vineyards have revealed the existence of a clear terroir-specific effect on the transcriptome and metabolome which persists over several vintages and allows each vineyard to be characterized by the unique profile of specific metabolites.

  4. Alteration of metabolomic markers of amino-acid metabolism in piglets with in-feed antibiotics.

    Science.gov (United States)

    Mu, Chunlong; Yang, Yuxiang; Yu, Kaifan; Yu, Miao; Zhang, Chuanjian; Su, Yong; Zhu, Weiyun

    2017-04-01

    In-feed antibiotics have been used to promote growth in piglets, but its impact on metabolomics profiles associated with host metabolism is largely unknown. In this study, to test the hypothesis that antibiotic treatment may affect metabolite composition both in the gut and host biofluids, metabolomics profiles were analyzed in antibiotic-treated piglets. Piglets were fed a corn-soy basal diet with or without in-feed antibiotics from postnatal day 7 to day 42. The serum biochemical parameters, metabolomics profiles of the serum, urine, and jejunal digesta, and indicators of microbial metabolism (short-chain fatty acids and biogenic amines) were analyzed. Compared to the control group, antibiotics treatment did not have significant effects on serum biochemical parameters except that it increased (P Antibiotics treatment increased the relative concentrations of metabolites involved in amino-acid metabolism in the serum, while decreased the relative concentrations of most amino acids in the jejunal content. Antibiotics reduced urinary 2-ketoisocaproate and hippurate. Furthermore, antibiotics decreased (P Antibiotics significantly affected the concentrations of biogenic amines, which are derived from microbial amino-acid metabolism. The three major amines, putrescine, cadaverine, and spermidine, were all increased (P antibiotics-treated piglets. These results identified the phenomena that in-feed antibiotics may have significant impact on the metabolomic markers of amino-acid metabolism in piglets.

  5. Metabolic Mechanism for l-Leucine-Induced Metabolome To Eliminate Streptococcus iniae.

    Science.gov (United States)

    Du, Chao-Chao; Yang, Man-Jun; Li, Min-Yi; Yang, Jun; Peng, Bo; Li, Hui; Peng, Xuan-Xian

    2017-05-05

    Crucial metabolites that modulate hosts' metabolome to eliminate bacterial pathogens have been documented, but the metabolic mechanisms are largely unknown. The present study explores the metabolic mechanism for l-leucine-induced metabolome to eliminate Streptococcus iniae in tilapia. GC-MS-based metabolomics was used to investigate the tilapia liver metabolic profile in the presence of exogenous l-leucine. Thirty-seven metabolites of differential abundance were determined, and 11 metabolic pathways were enriched. Pattern recognition analysis identified serine and proline as crucial metabolites, which are the two metabolites identified in survived tilapias during S. iniae infection, suggesting that the two metabolites play crucial roles in l-leucine-induced elimination of the pathogen by the host. Exogenous l-serine reduces the mortality of tilapias infected by S. iniae, providing a robust proof supporting the conclusion. Furthermore, exogenous l-serine elevates expression of genes IL-1β and IL-8 in tilapia spleen, but not TNFα, CXCR4 and Mx, suggesting that the metabolite promotes a phagocytosis role of macrophages, which is consistent with the finding that l-leucine promotes macrophages to kill both Gram-positive and Gram-negative bacterial pathogens. Therefore, the ability of phagocytosis enhanced by exogenous l-leucine is partly attributed to elevation of l-serine. These results demonstrate a metabolic mechanism by which exogenous l-leucine modulates tilapias' metabolome to enhance innate immunity and eliminate pathogens.

  6. Metabolome strategy against Edwardsiella tarda infection through glucose-enhanced metabolic modulation in tilapias.

    Science.gov (United States)

    Peng, Bo; Ma, Yan-Mei; Zhang, Jian-Ying; Li, Hui

    2015-08-01

    Edwardsiella tarda causes fish disease and great economic loss. However, metabolic strategy against the pathogen remains unexplored. In the present study, GC-MS based metabolomics was used to investigate the metabolic profile from tilapias infected by sublethal dose of E. tarda. The metabolic differences between the dying group and survival group allow the identification of key pathways and crucial metabolites during infections. More importantly, those metabolites may modulate the survival-related metabolome to enhance the anti-infective ability. Our data showed that tilapias generated two different strategies, survival-metabolome and death-metabolome, to encounter EIB202 infection, leading to differential outputs of the survival and dying. Glucose was the most crucial biomarker, which was upregulated and downregulated in the survival and dying groups, respectively. Exogenous glucose by injection or oral administration enhanced hosts' ability against EIB202 infection and increased the chances of survival. These findings highlight that host mounts the metabolic strategy to cope with bacterial infection, from which crucial biomarkers may be identified to enhance the metabolic strategy. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    CSIR Research Space (South Africa)

    Madala, NE

    2012-08-01

    Full Text Available systems, and results differ with the mode of data acquisition and output generation. LC–MS is one of many techniques that has been used to study the metabolomes of different organisms but, although used extensively, it does not provide a complete metabolic...

  8. The effects of liraglutide in mice with diet-induced obesity studied by metabolomics

    Czech Academy of Sciences Publication Activity Database

    Bugáňová, M.; Pelantová, H.; Holubová, M.; Šedivá, B.; Maletínská, L.; Železná, B.; Kuneš, Jaroslav; Kačer, P.; Kuzma, M.; Haluzík, M.

    2017-01-01

    Roč. 233, č. 1 (2017), s. 93-104 ISSN 0022-0795 Institutional support: RVO:67985823 Keywords : NMR metabolomics * obesity type 2 * diabetes mellitus * liraglutide * mouse urine Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition OBOR OECD: Endocrinology and metabolism (including diabetes , hormones) Impact factor: 4.706, year: 2016

  9. Use of metabolomics for the identification and validation of clinical biomarkers for preterm birth: Preterm SAMBA

    OpenAIRE

    Cecatti, Jose G.; Souza, Renato T.; Sulek, Karolina; Costa, Maria L.; Kenny, Louise C.; McCowan, Lesley M. E.; Pacagnella, Rodolfo C.; Villas-Boas, Silas G.; Mayrink, Jussara; Passini, Renato; Franchini, Kleber G.; Baker, Philip N.

    2016-01-01

    Background: Spontaneous preterm birth is a complex syndrome with multiple pathways interactions determining its occurrence, including genetic, immunological, physiologic, biochemical and environmental factors. Despite great worldwide efforts in preterm birth prevention, there are no recent effective therapeutic strategies able to decrease spontaneous preterm birth rates or their consequent neonatal morbidity/mortality. The Preterm SAMBA study will associate metabolomics technologies to identi...

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

    NARCIS (Netherlands)

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

    2017-01-01

    Key message: Pollen development metabolomics.Abstract: Developing pollen is among the plant structures most sensitive to high temperatures, and a decrease in pollen viability is often associated with an alteration of metabolite content. Most of the metabolic studies of pollen have focused on a

  11. Large-scale human metabolomics studies: A strategy for data (pre-) processing and validation

    NARCIS (Netherlands)

    Bijlsma, S.; Bobeldijk, I.; Verheij, E.R.; Ramaker, R.; Kochhar, S.; Macdonald, I.A.; Ommen, B. van; Smilde, A.K.

    2006-01-01

    A large metabolomics study was performed on 600 plasma samples taken at four time points before and after a single intake of a high fat test meal by obese and lean subjects. All samples were analyzed by a liquid chromatography-mass spectrometry (LC-MS) lipidomic method for metabolic profiling. A

  12. Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation

    NARCIS (Netherlands)

    Bijlsma, Sabina; Bobeldijk, Ivana; Verheij, Elwin R.; Ramaker, Raymond; Kochhar, Sunil; Macdonald, Ian A.; van Ommen, Ben; Smilde, Age K.

    2006-01-01

    A large metabolomics study was performed on 600 plasma samples taken at four time points before and after a single intake of a high fat test meal by obese and lean subjects. All samples were analyzed by a liquid chromatography-mass spectrometry (LC-MS) lipidomic method for metabolic profiling. A

  13. 1H NMR metabolomics of earthworm exposure to sub-lethal concentrations of phenanthrene in soil

    International Nuclear Information System (INIS)

    Brown, Sarah A.E.; McKelvie, Jennifer R.; Simpson, Andre J.; Simpson, Myrna J.

    2010-01-01

    1 H NMR metabolomics was used to monitor earthworm responses to sub-lethal (50-1500 mg/kg) phenanthrene exposure in soil. Total phenanthrene was analyzed via soxhlet extraction, bioavailable phenanthrene was estimated by hydroxypropyl-β-cyclodextrin (HPCD) and 1-butanol extractions and sorption to soil was assessed by batch equilibration. Bioavailable phenanthrene (HPCD-extracted) comprised ∼65-97% of total phenanthrene added to the soil. Principal component analysis (PCA) showed differences in responses between exposed earthworms and controls after 48 h exposure. The metabolites that varied with exposure included amino acids (isoleucine, alanine and glutamine) and maltose. PLS models indicated that earthworm response is positively correlated to both total phenanthrene concentration and bioavailable (HPCD-extracted) phenanthrene in a freshly spiked, unaged soil. These results show that metabolomics is a powerful, direct technique that may be used to monitor contaminant bioavailability and toxicity of sub-lethal concentrations of contaminants in the environment. These initial findings warrant further metabolomic studies with aged contaminated soils. - 1 H NMR metabolomics is used to directly monitor metabolic responses of Eisenia fetida after 48 h of exposure to sub-lethal concentrations of phenanthrene in soil.

  14. A functional genomics approach using metabolomics and in silico pathway analysis

    DEFF Research Database (Denmark)

    Förster, Jochen; Gombert, Andreas Karoly; Nielsen, Jens

    2002-01-01

    analysis techniques and changes in the genotype will in many cases lead to different metabolite profiles. Here, a theoretical framework that may be applied to identify the function of orphan genes is presented. The approach is based on a combination of metabolome analysis combined with in silico pathway...

  15. Tools and Databases of the KOMICS Web Portal for Preprocessing, Mining, and Dissemination of Metabolomics Data

    Directory of Open Access Journals (Sweden)

    Nozomu Sakurai

    2014-01-01

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

  16. Metabolomics investigation to shed light on cheese as a possible piece in the French paradox puzzle

    DEFF Research Database (Denmark)

    Zheng, Hong; Yde, Christian C; Clausen, Morten R

    2015-01-01

    An NMR-based metabolomics approach was used to investigate the differentiation between subjects consuming cheese or milk and to elucidate the potential link to an effect on the blood cholesterol level. Fifteen healthy young men participated in a full cross-over study where they consumed three iso-caloric...

  17. A Distinctive Urinary Metabolomic Fingerprint Is Linked With Endoscopic Postoperative Disease Recurrence in Crohn's Disease Patients.

    Science.gov (United States)

    Keshteli, Ammar Hassanzadeh; Tso, Robert; Dieleman, Levinus A; Park, Heekuk; Kroeker, Karen I; Jovel, Juan; Gillevet, Patrick M; Sikaroodi, Masoumeh; Mandal, Rupasri; Fedorak, Richard N; Madsen, Karen L

    2018-03-19

    Crohn's disease (CD) patients who undergo ileocolonic resection frequently have disease recurrence. The aim of this preliminary study was to identify urinary metabolomic profiles associated with disease recurrence in order to identify underlying mechanisms of recurrence and possible disease biomarkers. Biopsies from the neoterminal ileum were collected from CD patients (n = 38) after ileocolonic resection in order to assess mucosa-associated microbiota using 16S rRNA multitag pyrosequencing. Urine samples were collected, and metabolomic profiling was done using high-resolution nuclear magnetic resolution spectroscopy and a combined direct infusion liquid chromatography tandem mass spectrometry. The Rutgeerts scoring system was used to assess endoscopic postoperative recurrence of CD. There were 28 (73.7%) patients with endoscopic CD recurrence. CD patients who were in endoscopic remission had a higher abundance of Bacteroidetes and lower abundance of Fusobacteria and Proteobacteria in comparison with CD patients who had endoscopic recurrence. In addition, metabolomic profiling could also discriminate between these 2 groups of patients. Endoscopic recurrence was associated with increased concentration of urinary levoglucosan. Rutgeerts score was positively correlated with levoglucosan and propylene glycol levels. CD patients who present with endoscopic disease recurrence after surgery have a unique urinary metabolomic fingerprint that can differentiate them from CD patients who are in endoscopic remission after ileocolonic resection. In addition, mucosal-associated microbiota in CD patients with or without disease recurrence after surgery differs and correlates with some urinary metabolites.

  18. Metabolomic assessment reveals a stimulatory effect of calcium treatment on glucosinolates contents in broccoli microgreen

    Science.gov (United States)

    Preharvest calcium application has been shown to increase broccoli microgreen yield and extend shelf life. Here we investigated the effect of calcium application on its metabolome using ultra high-performance liquid chromatography (UHPLC) tandem with mass spectrometry (HRMS). The data collected were...

  19. Metabolomic differences in early and late lactation first-parity gilts

    Science.gov (United States)

    Investigating the metabolome provides the evaluation of all cellular processes occuring while accounting for environmental influence and may provide additional information for selection criteria to fully evolve. Blood samples and body condition measurements were acquired from 68, first-parity gilts ...

  20. Circadian variation of the human metabolome captured by real-time breath analysis.

    Directory of Open Access Journals (Sweden)

    Pablo Martinez-Lozano Sinues

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

  1. Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules.

    Science.gov (United States)

    Pannkuk, Evan L; Fornace, Albert J; Laiakis, Evagelia C

    2017-10-01

    Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease. Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research.

  2. Diurnal effects of anoxia on the metabolome of the seagrass Zostera marina

    DEFF Research Database (Denmark)

    Hasler-Sheetal, Harald; Fragner, Lena; Holmer, Marianne

    2015-01-01

    We investigated the response, adaptation and tolerance mechanisms of the temperate seagrass Zostera marina to water column anoxia. We exposed Z. marina to a diurnal light/dark cycle under anoxia and assessed the metabolic response by measuring the metabolome with gas chromatography coupled to mass...

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

    NARCIS (Netherlands)

    Kümmel, Anne; Panke, Sven; Heinemann, Matthias

    2006-01-01

    As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic

  4. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    Science.gov (United States)

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Urinary metabolomic fingerprinting after consumption of a probiotic strain in women with mastitis.

    Science.gov (United States)

    Vázquez-Fresno, Rosa; Llorach, Rafael; Marinic, Jelena; Tulipani, Sara; Garcia-Aloy, Mar; Espinosa-Martos, Irene; Jiménez, Esther; Rodríguez, Juan Miguel; Andres-Lacueva, Cristina

    2014-09-01

    Infectious mastitis is a common condition among lactating women, with staphylococci and streptococci being the main aetiological agents. In this context, some lactobacilli strains isolated from breast milk appear to be particularly effective for treating mastitis and, therefore, constitute an attractive alternative to antibiotherapy. A (1)H NMR-based metabolomic approach was applied to detect metabolomic differences after consuming a probiotic strain (Lactobacillus salivarius PS2) in women with mastitis. 24h urine of women with lactational mastitis was collected at baseline and after 21 days of probiotic (PB) administration. Multivariate analysis (OSC-PLS-DA and hierarchical clustering) showed metabolome differences after PB treatment. The discriminant metabolites detected at baseline were lactose, and ibuprofen and acetaminophen (two pharmacological drugs commonly used for mastitis pain), while, after PB intake, creatine and the gut microbial co-metabolites hippurate and TMAO were detected. In addition, a voluntary desertion of the pharmacological drugs ibuprofen and acetaminophen was observed after probiotic administration. The application of NMR-based metabolomics enabled the identification of the overall effects of probiotic consumption among women suffering from mastitis and highlighted the potential of this approach in evaluating the outcomes of probiotics consumption. To our knowledge, this is the first time that this approach has been applied in women with mastitis during lactation. Copyright © 2014. Published by Elsevier Ltd.

  6. Novel chemistry of invasive plants: exotic species have more unique metabolomic profiles than native congeners

    NARCIS (Netherlands)

    Macel, M.; Vos, de R.C.H.; Jansen, J.J.; Putten, van der W.H.; Dam, van N.M.

    2014-01-01

    It is often assumed that exotic plants can become invasive when they possess novel secondary chemistry compared with native plants in the introduced range. Using untargeted metabolomic fingerprinting, we compared a broad range of metabolites of six successful exotic plant species and their native

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

    NARCIS (Netherlands)

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

    2015-01-01

    The effects of conventional industrial processing steps on global phytochemical composition of broccoli, tomato and carrot purees were investigated by using a range of complementary targeted and untargeted metabolomics approaches including LC–PDA for vitamins, 1H NMR for polar metabolites, accurate

  8. Non-target effects of GM potato : an eco-metabolomics approach

    NARCIS (Netherlands)

    Plischke, Andreas

    2013-01-01

    In this thesis, patterns of variation in plant metabolomes and insect communities were described in GM and non-GM potato plants in both laboratory and field experiments. Differences between plant genotypes in insect abundances were small when compared to year-to-year differences, location effects

  9. Regulation of floral scent production in petunia revealed by targeted metabolomics

    NARCIS (Netherlands)

    Verdonk, J.C.; Vos, de C.H.; Verhoeven, H.A.; Haring, M.A.; Tunen, van A.J.; Schuurink, R.C.

    2003-01-01

    Petunia hybrida line W115 (Mitchell) has large white flowers that produce a pleasant fragrance. By applying solid phase micro extraction (SPME) techniques coupled to GC-MS analysis, volatile emission was monitored in vivo using a targeted metabolomics approach. Mature flowers released predominantly

  10. Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

    NARCIS (Netherlands)

    Graham, S.F.; Ruiz Aracama, A.; Lommen, A.; Cannizzo, F.T.; Biolatti, B.; Elliott, C.T.; Mooney, M.H.

    2012-01-01

    Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with

  11. Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice

    NARCIS (Netherlands)

    Lu, Y.; Boekschoten, M.V.; Wopereis, S.; Muller, M.R.; Kersten, A.H.

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 wk

  12. Comparative transcriptomics and metabolomic analysis of fenofibrate and fish oil treatments in mice

    NARCIS (Netherlands)

    Lu Yingchang (Kevin), Y.; Boekschoten, Mark; Wopereis, Suzan; Muller, Michael; Kersten, Sander

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 week

  13. Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness

    DEFF Research Database (Denmark)

    Bozek, Katarzyna; Wei, Yuning; Yan, Zheng

    2014-01-01

    Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees...

  14. New figures of merit for comprehensive functional genomics data: the metabolomics case

    NARCIS (Netherlands)

    van Batenburg, M.F.; Coulier, L.; van Eeuwijk, F.; Smilde, A.K.; Westerhuis, J.A.

    2011-01-01

    In the field of metabolomics, hundreds of metabolites are measured simultaneously by analytical platforms such as gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and NMR to obtain their concentration levels in a reliable way. Analytical repeatability

  15. New figures of merit for comprehensive functional genomics data: The metabolomics case

    NARCIS (Netherlands)

    Batenburg, M.F. van; Coulier, L.; Eeuwijk, F. van; Smilde, A.K.; Westerhuis, J.A.

    2011-01-01

    In the field of metabolomics, hundreds of metabolites are measured simultaneously by analytical platforms such as gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and NMR to obtain their concentration levels in a reliable way. Analytical repeatability

  16. High Aerobic Capacity Mitigates Changes in the Plasma Metabolomic Profile Associated with Aging.

    Science.gov (United States)

    Falegan, Oluyemi S; Vogel, Hans J; Hittel, Dustin S; Koch, Lauren G; Britton, Steven L; Hepple, Russ T; Shearer, Jane

    2017-02-03

    Advancing age is associated with declines in maximal oxygen consumption. Declines in aerobic capacity not only contribute to the aging process but also are an independent risk factor for morbidity, cardiovascular disease, and all-cause mortality. Although statistically convincing, the relationships between aerobic capacity, aging, and disease risk remain largely unresolved. To this end, we employed sensitive, system-based metabolomics approach to determine whether enhanced aerobic capacity could mitigate some of the changes seen in the plasma metabolomic profile associated with aging. Metabolomic profiles of plasma samples obtained from young (13 month) and old (26 month) rats bred for low (LCR) or high (HCR) running capacity using proton nuclear magnetic resonance spectroscopy ( 1 H NMR) were examined. Results demonstrated strong profile separation in old and low aerobic capacity rats, whereas young and high aerobic capacity rat models were less predictive. Significantly differential metabolites between the groups include taurine, acetone, valine, and trimethylamine-N-oxide among other metabolites, specifically citrate, succinate, isovalerate, and proline, were differentially increased in older HCR animals compared with their younger counterparts. When interactions between age and aerobic capacity were examined, results demonstrated that enhanced aerobic capacity could mitigate some but not all age-associated alterations in the metabolomic profile.

  17. Impact of Soil Warming on the Plant Metabolome of Icelandic Grasslands

    Science.gov (United States)

    Gargallo-Garriga, Albert; Ayala-Roque, Marta; Granda, Victor; Sigurdsson, Bjarni D.; Leblans, Niki I. W.; Oravec, Michal; Urban, Otmar; Janssens, Ivan A.

    2017-01-01

    Climate change is stronger at high than at temperate and tropical latitudes. The natural geothermal conditions in southern Iceland provide an opportunity to study the impact of warming on plants, because of the geothermal bedrock channels that induce stable gradients of soil temperature. We studied two valleys, one where such gradients have been present for centuries (long-term treatment), and another where new gradients were created in 2008 after a shallow crustal earthquake (short-term treatment). We studied the impact of soil warming (0 to +15 °C) on the foliar metabolomes of two common plant species of high northern latitudes: Agrostis capillaris, a monocotyledon grass; and Ranunculus acris, a dicotyledonous herb, and evaluated the dependence of shifts in their metabolomes on the length of the warming treatment. The two species responded differently to warming, depending on the length of exposure. The grass metabolome clearly shifted at the site of long-term warming, but the herb metabolome did not. The main up-regulated compounds at the highest temperatures at the long-term site were saccharides and amino acids, both involved in heat-shock metabolic pathways. Moreover, some secondary metabolites, such as phenolic acids and terpenes, associated with a wide array of stresses, were also up-regulated. Most current climatic models predict an increase in annual average temperature between 2–8 °C over land masses in the Arctic towards the end of this century. The metabolomes of A. capillaris and R. acris shifted abruptly and nonlinearly to soil warming >5 °C above the control temperature for the coming decades. These results thus suggest that a slight warming increase may not imply substantial changes in plant function, but if the temperature rises more than 5 °C, warming may end up triggering metabolic pathways associated with heat stress in some plant species currently dominant in this region. PMID:28832555

  18. E-Cigarette Affects the Metabolome of Primary Normal Human Bronchial Epithelial Cells.

    Directory of Open Access Journals (Sweden)

    Argo Aug

    Full Text Available E-cigarettes are widely believed to be safer than conventional cigarettes and have been even suggested as aids for smoking cessation. However, while reasonable with some regards, this judgment is not yet supported by adequate biomedical research data. Since bronchial epithelial cells are the immediate target of inhaled toxicants, we hypothesized that exposure to e-cigarettes may affect the metabolome of human bronchial epithelial cells (HBEC and that the changes are, at least in part, induced by oxidant-driven mechanisms. Therefore, we evaluated the effect of e-cigarette liquid (ECL on the metabolome of HBEC and examined the potency of antioxidants to protect the cells. We assessed the changes of the intracellular metabolome upon treatment with ECL in comparison of the effect of cigarette smoke condensate (CSC with mass spectrometry and principal component analysis on air-liquid interface model of normal HBEC. Thereafter, we evaluated the capability of the novel antioxidant tetrapeptide O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1 to attenuate the effect of ECL. ECL caused a significant shift in the metabolome that gradually gained its maximum by the 5th hour and receded by the 7th hour. A second alteration followed at the 13th hour. Treatment with CSC caused a significant initial shift already by the 1st hour. ECL, but not CSC, significantly increased the concentrations of arginine, histidine, and xanthine. ECL, in parallel with CSC, increased the content of adenosine diphosphate and decreased that of three lipid species from the phosphatidylcholine family. UPF1 partially counteracted the ECL-induced deviations, UPF1's maximum effect occurred at the 5th hour. The data support our hypothesis that ECL profoundly alters the metabolome of HBEC in a manner, which is comparable and partially overlapping with the effect of CSC. Hence, our results do not support the concept of harmlessness of e-cigarettes.

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

    Science.gov (United States)

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

    2018-05-01

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

  20. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production.

    Science.gov (United States)

    Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

    2016-01-01

    The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a 'Westernised' lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  1. Infrared biospectroscopy for a fast qualitative evaluation of sample preparation in metabolomics.

    Science.gov (United States)

    Kuligowski, Julia; Pérez-Guaita, David; Escobar, Javier; Lliso, Isabel; de la Guardia, Miguel; Lendl, Bernhard; Vento, Máximo; Quintás, Guillermo

    2014-09-01

    Liquid chromatography-mass spectrometry (LC-MS) has been increasingly used in biomedicine to study the dynamic metabolomic responses of biological systems under different physiological or pathological conditions. To obtain an integrated snapshot of the system, metabolomic methods in biomedicine typically analyze biofluids (e.g. plasma) that require clean-up before being injected into LC-MS systems. However, high resolution LC-MS is costly in terms of resources required for sample and data analysis and care must be taken to prevent chemical (e.g. ion suppression) or statistical artifacts. Because of that, the effect of sample preparation on the metabolomic profile during metabolomic method development is often overlooked. This work combines an Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) and a multivariate exploratory data analysis for a cost-effective qualitative evaluation of major changes in sample composition during sample preparation. ATR-FTIR and LC-time of flight mass spectrometry (TOFMS) data from the analysis of a set of plasma samples precipitated using acetonitrile, methanol and acetone performed in parallel were used as a model example. Biochemical information obtained from the analysis of the ATR-FTIR and LC-TOFMS data was thoroughly compared to evaluate the strengths and shortcomings of FTIR biospectroscopy for assessing sample preparation in metabolomics studies. Results obtained show the feasibility of ATR-FTIR for the evaluation of major trends in the plasma composition changes among different sample pretreatments, providing information in terms of e.g., amino acids, proteins, lipids and carbohydrates overall contents comparable to those found by LC-TOFMS. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics

    Directory of Open Access Journals (Sweden)

    Hardy Nigel

    2006-06-01

    Full Text Available Abstract Background The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. Description MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. Conclusion The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion.

  3. Use of metabolomics for the identification and validation of clinical biomarkers for preterm birth: Preterm SAMBA.

    Science.gov (United States)

    Cecatti, Jose G; Souza, Renato T; Sulek, Karolina; Costa, Maria L; Kenny, Louise C; McCowan, Lesley M; Pacagnella, Rodolfo C; Villas-Boas, Silas G; Mayrink, Jussara; Passini, Renato; Franchini, Kleber G; Baker, Philip N

    2016-08-08

    Spontaneous preterm birth is a complex syndrome with multiple pathways interactions determining its occurrence, including genetic, immunological, physiologic, biochemical and environmental factors. Despite great worldwide efforts in preterm birth prevention, there are no recent effective therapeutic strategies able to decrease spontaneous preterm birth rates or their consequent neonatal morbidity/mortality. The Preterm SAMBA study will associate metabolomics technologies to identify clinical and metabolite predictors for preterm birth. These innovative and unbiased techniques might be a strategic key to advance spontaneous preterm birth prediction. Preterm SAMBA study consists of a discovery phase to identify biophysical and untargeted metabolomics from blood and hair samples associated with preterm birth, plus a validation phase to evaluate the performance of the predictive modelling. The first phase, a case-control study, will randomly select 100 women who had a spontaneous preterm birth (before 37 weeks) and 100 women who had term birth in the Cork Ireland and Auckland New Zealand cohorts within the SCOPE study, an international consortium aimed to identify potential metabolomic predictors using biophysical data and blood samples collected at 20 weeks of gestation. The validation phase will recruit 1150 Brazilian pregnant women from five participant centres and will collect blood and hair samples at 20 weeks of gestation to evaluate the performance of the algorithm model (sensitivity, specificity, predictive values and likelihood ratios) in predicting spontaneous preterm birth (before 34 weeks, with a secondary analysis of delivery before 37 weeks). The Preterm SAMBA study intends to step forward on preterm birth prediction using metabolomics techniques, and accurate protocols for sample collection among multi-ethnic populations. The use of metabolomics in medical science research is innovative and promises to provide solutions for disorders with multiple

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

    Directory of Open Access Journals (Sweden)

    Daisuke Saigusa

    Full Text Available Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met using mass spectrometry (MS, largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

  5. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production

    Science.gov (United States)

    Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

    2015-01-01

    Objective The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a ‘Westernised’ lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Design and results Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Conclusions Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. PMID:25431456

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

    Science.gov (United States)

    Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

    2017-05-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

  8. NMR-based metabolomics in human disease diagnosis: Applications, limitations, and recommendations

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2013-04-03

    Metabolomics is a dynamic and emerging research field, similar to proteomics, transcriptomics and genomics in affording global understanding of biological systems. It is particularly useful in functional genomic studies in which metabolism is thought to be perturbed. Metabolomics provides a snapshot of the metabolic dynamics that reflect the response of living systems to both pathophysiological stimuli and/or genetic modification. Because this approach makes possible the examination of interactions between an organism and its diet or environment, it is particularly useful for identifying biomarkers of disease processes that involve the environment. For example, the interaction of a high fat diet with cardiovascular disease can be studied via such a metabolomics approach by modeling the interaction between genes and diet. The high reproducibility of NMR-based techniques gives this method a number of advantages over other analytical techniques in large-scale and long-term metabolomic studies, such as epidemiological studies. This approach has been used to study a wide range of diseases, through the examination of biofluids, including blood plasma/serum, urine, blister fluid, saliva and semen, as well as tissue extracts and intact tissue biopsies. However, complicating the use of NMR spectroscopy in biomarker discovery is the fact that numerous variables can effect metabolic composition including, fasting, stress, drug administration, diet, gender, age, physical activity, life style and the subject\\'s health condition. To minimize the influence of these variations in the datasets, all experimental conditions including sample collection, storage, preparation as well as NMR spectroscopic parameters and data analysis should be optimized carefully and conducted in an identical manner as described by the local standard operating protocol. This review highlights the potential applications of NMR-based metabolomics studies and gives some recommendations to improve sample

  9. Linking diet to acne metabolomics, inflammation, and comedogenesis: an update.

    Science.gov (United States)

    Melnik, Bodo C

    2015-01-01

    -induced metabolomic alterations promote the visible sebofollicular inflammasomopathy acne vulgaris. Nutrition therapy of acne has to increase FoxO1 and to attenuate mTORC1/SREBP-1c signaling. Patients should balance total calorie uptake and restrict refined carbohydrates, milk, dairy protein supplements, saturated fats, and trans-fats. A paleolithic-like diet enriched in vegetables and fish is recommended. Plant-derived mTORC1 inhibitors and ω-3-PUFAs are promising dietary supplements supporting nutrition therapy of acne vulgaris.

  10. Linking diet to acne metabolomics, inflammation, and comedogenesis: an update

    Science.gov (United States)

    Melnik, Bodo C

    2015-01-01

    -induced metabolomic alterations promote the visible sebofollicular inflammasomopathy acne vulgaris. Nutrition therapy of acne has to increase FoxO1 and to attenuate mTORC1/SREBP-1c signaling. Patients should balance total calorie uptake and restrict refined carbohydrates, milk, dairy protein supplements, saturated fats, and trans-fats. A paleolithic-like diet enriched in vegetables and fish is recommended. Plant-derived mTORC1 inhibitors and ω-3-PUFAs are promising dietary supplements supporting nutrition therapy of acne vulgaris. PMID:26203267

  11. Noninvasive metabolomic profiling as an adjunct to morphology for noninvasive embryo assessment in women undergoing single embryo transfer

    NARCIS (Netherlands)

    Seli, E.; Vergouw, C.G.; Morita, H.; Botros, L.; Roos, P.; Lambalk, C.B.; Yamashita, N.; Kato, O.; Sakkas, D.

    2010-01-01

    Objective: To determine whether metabolomic profiling of spent embryo culture media correlates with reproductive potential of human embryos. Design: Retrospective study. Setting: Academic and a private assisted reproductive technology (ART) programs. Patient(s): Women undergoing single embryo

  12. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors

    OpenAIRE

    Vázquez Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez Martínez, Miguel Ángel; Vinaixa Crevillent, Maria; Chiva Blanch, Gemma; Estruch Riba, Ramon; Correig Blanchar, Xavier; Andrés Lacueva, Ma. Cristina

    2012-01-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100m...

  13. Metabolomic profiles delineate signature metabolic shifts during estrogen deficiency-induced bone loss in rat by GC-TOF/MS.

    Directory of Open Access Journals (Sweden)

    Bo Ma

    Full Text Available Postmenopausal osteoporosis is a complicated and multi-factorial disease. To study the metabolic profiles and pathways activated in osteoporosis, Eight rats were oophorectomized (OVX group to represent postmenopausal osteoporosis and the other eight rats were sham operated (Sham group to be the control. The biochemical changes were assessed with metabolomics using a gas chromatography/time-of-flight mass spectrometry. Metabolomic profile using serial blood samples obtained prior to and at different time intervals after OVX were analyzed by principal component analysis (PCA and Partial least squares-discriminant analysis (PLS-DA. The conventional indicators (bone mineral density, serum Bone alkaline phosphatase (B-ALP and N-telopeptide of type I collagen (NTx of osteoporosis in rats were also determined simultaneously. In OVX group, the metabolomics method could describe the endogenous changes of the disease more sensitively and systematically than the conventional criteria during the progression of osteoporosis. Significant metabolomic difference was also observed between the OVX and Sham groups. The metabolomic analyses of rat plasma showed that levels of arachidonic acid, octadecadienoic acid, branched-chain amino acids (valine, leucine and isoleucine, homocysteine, hydroxyproline and ketone bodies (3-Hydroxybutyric Acid significantly elevated, while levels of docosahexaenoic acid, dodecanoic acid and lysine significantly decreased in OVX group compared with those in the homeochronous Sham group. Considering such metabolites are closely related to the pathology of the postmenopausal osteoporosis, the results suggest that potential biomarkers for the early diagnosis or the pathogenesis of osteoporosis might be identified via metabolomic study.

  14. The green tea modulates large intestinal microbiome and exo/endogenous metabolome altered through chronic UVB-exposure.

    Directory of Open Access Journals (Sweden)

    Eun Sung Jung

    Full Text Available The attenuating effects of green tea supplements (GTS against the ultraviolet (UV radiation induced skin damages are distinguished. However, the concomitant effects of GTS on the large intestinal microbiomes and associated metabolomes are largely unclear. Herein, we performed an integrated microbiome-metabolome analysis to uncover the esoteric links between gut microbiome and exo/endogenous metabolome maneuvered in the large intestine of UVB-exposed mice subjected to dietary GTS. In UVB-exposed mice groups (UVB, class Bacilli and order Bifidobacteriales were observed as discriminant taxa with decreased lysophospholipid levels compared to the unexposed mice groups subjected to normal diet (NOR. Conversely, in GTS fed UVB-exposed mice (U+GTS, the gut-microbiome diversity was greatly enhanced with enrichment in the classes, Clostridia and Erysipelotrichia, as well as genera, Allobaculum and Lachnoclostridium. Additionally, the gut endogenous metabolomes changed with an increase in amino acids, fatty acids, lipids, and bile acids contents coupled with a decrease in nucleobases and carbohydrate levels. The altered metabolomes exhibited high correlations with GTS enriched intestinal microflora. Intriguingly, the various conjugates of green tea catechins viz., sulfated, glucuronided, and methylated ones including their exogenous derivatives were detected from large intestinal contents and liver samples. Hence, we conjecture that the metabolic conversions for the molecular components in GTS strongly influenced the gut micro-environment in UVB-exposed mice groups, ergo modulate their gut-microbiome as well as exo/endogenous metabolomes.

  15. Serial Metabolome Changes in a Prospective Cohort of Subjects with Influenza Viral Infection and Comparison with Dengue Fever.

    Science.gov (United States)

    Cui, Liang; Fang, Jinling; Ooi, Eng Eong; Lee, Yie Hou

    2017-07-07

    Influenza virus infection (IVI) and dengue virus infection (DVI) are major public health threats. Between IVI and DVI, clinical symptoms can be overlapping yet infection-specific, but host metabolome changes are not well-described. Untargeted metabolomics and targeted oxylipinomic analyses were performed on sera serially collected at three phases of infection from a prospective cohort study of adult subjects with either H3N2 influenza infection or dengue fever. Untargeted metabolomics identified 26 differential metabolites, and major perturbed pathways included purine metabolism, fatty acid biosynthesis and β-oxidation, tryptophan metabolism, phospholipid catabolism, and steroid hormone pathway. Alterations in eight oxylipins were associated with the early symptomatic phase of H3N2 flu infection, were mostly arachidonic acid-derived, and were enriched in the lipoxygenase pathway. There was significant overlap in metabolome profiles in both infections. However, differences specific to IVI and DVI were observed. DVI specifically attenuated metabolites including serotonin, bile acids and biliverdin. Additionally, metabolome changes were more persistent in IVI in which metabolites such as hypoxanthine, inosine, and xanthine of the purine metabolism pathway remained significantly elevated at 21-27 days after fever onset. This study revealed the dynamic metabolome changes in IVI subjects and provided biochemical insights on host physiological similarities and differences between IVI and DVI.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  17. Impact of a cafeteria diet and daily physical training on the rat serum metabolome.

    Directory of Open Access Journals (Sweden)

    Susana Suárez-García

    Full Text Available Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS, which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST or cafeteria diet (CAF and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which

  18. NMR metabolomics of ripened and developing oilseed rape (Brassica napus) and turnip rape (Brassica rapa).

    Science.gov (United States)

    Kortesniemi, Maaria; Vuorinen, Anssi L; Sinkkonen, Jari; Yang, Baoru; Rajala, Ari; Kallio, Heikki

    2015-04-01

    The oilseeds of the commercially important oilseed rape (Brassica napus) and turnip rape (Brassica rapa) were investigated with (1)H NMR metabolomics. The compositions of ripened (cultivated in field trials) and developing seeds (cultivated in controlled conditions) were compared in multivariate models using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Differences in the major lipids and the minor metabolites between the two species were found. A higher content of polyunsaturated fatty acids and sucrose were observed in turnip rape, while the overall oil content and sinapine levels were higher in oilseed rape. The genotype traits were negligible compared to the effect of the growing site and concomitant conditions on the oilseed metabolome. This study demonstrates the applicability of NMR-based analysis in determining the species, geographical origin, developmental stage, and quality of oilseed Brassicas. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Metabolomics Reveals that Dietary Xenoestrogens Alter Cellular Metabolism Induced by Palbociclib/Letrozole Combination Cancer Therapy.

    Science.gov (United States)

    Warth, Benedikt; Raffeiner, Philipp; Granados, Ana; Huan, Tao; Fang, Mingliang; Forsberg, Erica M; Benton, H Paul; Goetz, Laura; Johnson, Caroline H; Siuzdak, Gary

    2018-03-15

    Recently, the palbociclib/letrozole combination therapy was granted accelerated US FDA approval for the treatment of estrogen receptor (ER)-positive breast cancer. Since the underlying metabolic effects of these drugs are yet unknown, we investigated their synergism at the metabolome level in MCF-7 cells. As xenoestrogens interact with the ER, we additionally aimed at deciphering the impact of the phytoestrogen genistein and the estrogenic mycotoxin zearalenone. A global metabolomics approach was applied to unravel metabolite and pathway modifications. The results clearly showed that the combined effects of palbociclib and letrozole on cellular metabolism were far more pronounced than that of each agent alone and potently influenced by xenoestrogens. This behavior was confirmed in proliferation experiments and functional assays. Specifically, amino acids and central carbon metabolites were attenuated, while higher abundances were observed for fatty acids and most nucleic acid-related metabolites. Interestingly, exposure to model xenoestrogens appeared to counteract these effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. (1)H NMR metabolomics to study the effects of diazepam on anisatin induced convulsive seizures.

    Science.gov (United States)

    Li, Pei; Wei, Dan-Dan; Wang, Jun-Song; Yang, Ming-Hua; Kong, Ling-Yi

    2016-01-05

    The anticonvulsive properties of diazepam have been extensively studied, mainly focusing on the γ-amino butyrate (GABA) system. The aim of this investigation was to integrally analyze the metabolic events related to neuroprotection of diazepam on anisatin-induced convulsive seizures by a NMR-based metabolomic approach combined with histopathological examination and behavior examination. Multivariate analysis on metabolic profiles of the piriform cortex and cerebellum of mice revealed that diazepam could relieve mice suffering from the convulsive seizures by recovering destructed neurotransmitter and neuromodulator metabolism, ameliorating oxidative stress, alleviating the disturbance in energy, amino acid and nucleic acid metabolism in anisatin intoxicated mice. This integrated metabolomics study provided a powerful and highly effective approach to elucidate therapeutic effects and assessed the safety of diazepam. This study should be helpful for our understanding of convulsive seizures, and provide a holistic view of the treatment effects of benzodiazepine on convulsive seizures. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Fumio eMatsuda

    2011-08-01

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

  2. Mono-colonization with Lactobacillus acidophilus NCFM affects the intestinal metabolome in mice

    DEFF Research Database (Denmark)

    Roager, Henrik Munch; Sulek, Karolina; Skov, Kasper

    -tocopherol acetate) in higher levels in the intestine of GF mice compared to MC mice, suggesting that NCFM either metabolizes the compound or indirectly affects the absorption by changing the metabolome in the intestine. The use of NCFM to increase the uptake of vitamin E supplements in humans and animals...... (NCFM) on the intestinal metabolome (jejunum, caecum, and colon) in mice by comparing NCFM mono-colonized (MC) mice with GF mice using liquid chromatography coupled to mass-spectrometry (LC-MS). The study adds to existing evidence that NCFM in vivo affects the bile acid signature of mice...... by deconjugation and dehydroxylation of bile acids. Furthermore, we confirmed that carbohydrate metabolism is affected by NCFM in the mouse intestine. Especially, the digestion of larger carbohydrates (penta- and tetrasaccharides) was increased in MC mice. Interestingly, we also found vitamin E (α...

  3. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

  4. Metabolomics investigation to shed light on cheese as a possible piece in the French paradox puzzle.

    Science.gov (United States)

    Zheng, Hong; Yde, Christian C; Clausen, Morten R; Kristensen, Mette; Lorenzen, Janne; Astrup, Arne; Bertram, Hanne C

    2015-03-18

    An NMR-based metabolomics approach was used to investigate the differentiation between subjects consuming cheese or milk and to elucidate the potential link to an effect on blood cholesterol level. Fifteen healthy young men participated in a full crossover study during which they consumed three isocaloric diets with similar fat contents that were either (i) high in milk, (ii) high in cheese with equal amounts of dairy calcium, or (iii) a control diet for 14 days. Urine and feces samples were collected and analyzed by NMR-based metabolomics. Cheese and milk consumption decreased urinary choline and TMAO levels and increased fecal excretion of acetate, propionate, and lipid. Compared with milk intake, cheese consumption significantly reduced urinary citrate, creatine, and creatinine levels and significantly increased the microbiota-related metabolites butyrate, hippurate, and malonate. Correlation analyses indicated that microbial and lipid metabolism could be involved in the dairy-induced effects on blood cholesterol level.

  5. Mapping the variation of the carrot metabolome using 1H NMR spectroscopy and consensus PCA.

    Science.gov (United States)

    Clausen, Morten Rahr; Edelenbos, Merete; Bertram, Hanne Christine

    2014-05-14

    Genetic variation is the most influential factor for carrot (Daucus carota L.) composition. However, difference in metabolite content between carrot varieties has not been described by NMR, although primary metabolites are important for human health and sensory properties. The aim of the present study was to investigate the effect of genotype on carrot metabolite composition using a (1)H NMR-based metabolomics approach. After extraction using aqueous and organic solvents, 25 hydrophilic metabolites, β-carotene, sterols, triacylglycerols, and phospholipids were detected. Multiblock PCA showed that three principal components could be identified for classification of the five carrot varieties using different spectroscopic regions and the results of the two solvent extraction methods as blocks. The varieties were characterized by differences in carbohydrate, amino acid, nucleotide, fatty acid, sterol, and β-carotene contents. (1)H NMR spectroscopy coupled with multiblock data analysis was an efficient and useful tool to map the carrot metabolome and identify genetic differences between varieties.

  6. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  7. Transmissible microbial and metabolomic remodeling by soluble dietary fiber improves metabolic homeostasis.

    Science.gov (United States)

    He, Baokun; Nohara, Kazunari; Ajami, Nadim J; Michalek, Ryan D; Tian, Xiangjun; Wong, Matthew; Losee-Olson, Susan H; Petrosino, Joseph F; Yoo, Seung-Hee; Shimomura, Kazuhiro; Chen, Zheng

    2015-06-04

    Dietary fibers are increasingly appreciated as beneficial nutritional components. However, a requisite role of gut microbiota in fiber function and the overall impact of fibers on metabolomic flux remain unclear. We herein showed enhancing effects of a soluble resistant maltodextrin (RM) on glucose homeostasis in mouse metabolic disease models. Remarkably, fecal microbiota transplantation (FMT) caused pronounced and time-dependent improvement in glucose tolerance in RM recipient mice, indicating a causal relationship between microbial remodeling and metabolic efficacy. Microbial 16S sequencing revealed transmissible taxonomic changes correlated with improved metabolism, notably enrichment of probiotics and reduction of Alistipes and Bacteroides known to associate with high fat/protein diets. Metabolomic profiling further illustrated broad changes, including enrichment of phenylpropionates and decreases in key intermediates of glucose utilization, cholesterol biosynthesis and amino acid fermentation. These studies elucidate beneficial roles of RM-dependent microbial remodeling in metabolic homeostasis, and showcase prevalent health-promoting potentials of dietary fibers.

  8. Proteomic and metabolomic analysis of atrial profibrillatory remodelling in congestive heart failure.

    Science.gov (United States)

    De Souza, Ayesha I; Cardin, Sophie; Wait, Robin; Chung, Yuen-Li; Vijayakumar, Meeraa; Maguy, Ange; Camm, A John; Nattel, Stanley

    2010-11-01

    Congestive heart failure (CHF) leads to atrial structural remodelling and increased susceptibility to atrial fibrillation. The underlying molecular mechanisms are poorly understood. We applied high-throughput proteomic and metabolomic analysis to left-atrial cardiomyocytes and tissues obtained from sham and ventricular-tachypaced (VTP, 240 bpm × 24 h and × 2 weeks) CHF dogs. Protein-extracts were subjected to two-dimensional gel electrophoresis using differential in-gel electrophoresis technology. Differentially expressed (Pglycolysis to alpha-ketoacid metabolism. We conclude that VTP-induced CHF causes time-dependent changes in the atrial proteome and metabolome, providing insights into molecular mechanisms contributing to arrhythmogenic atrial remodelling. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. The Da Vinci European BioBank: A Metabolomics-Driven Infrastructure

    Directory of Open Access Journals (Sweden)

    Dario Carotenuto

    2015-04-01

    Full Text Available We present here the organization of the recently-constituted da Vinci European BioBank (daVEB, https://www.davincieuropeanbiobank.org/it. The biobank was created as an infrastructure to support the activities of the Fiorgen Foundation (http://www.fiorgen.net/, a nonprofit organization that promotes research in the field of pharmacogenomics and personalized medicine. The way operating procedures concerning samples and data have been developed at daVEB largely stems from the strong metabolomics connotation of Fiorgen and from the involvement of the scientific collaborators of the foundation in international/European projects aimed to tackle the standardization of pre-analytical procedures and the promotion of data standards in metabolomics.

  10. The Da Vinci European BioBank: A Metabolomics-Driven Infrastructure

    Science.gov (United States)

    Carotenuto, Dario; Luchinat, Claudio; Marcon, Giordana; Rosato, Antonio; Turano, Paola

    2015-01-01

    We present here the organization of the recently-constituted da Vinci European BioBank (daVEB, https://www.davincieuropeanbiobank.org/it). The biobank was created as an infrastructure to support the activities of the Fiorgen Foundation (http://www.fiorgen.net/), a nonprofit organization that promotes research in the field of pharmacogenomics and personalized medicine. The way operating procedures concerning samples and data have been developed at daVEB largely stems from the strong metabolomics connotation of Fiorgen and from the involvement of the scientific collaborators of the foundation in international/European projects aimed to tackle the standardization of pre-analytical procedures and the promotion of data standards in metabolomics. PMID:25913579

  11. Arginine: New Insights into Growth Performance and Urinary Metabolomic Profiles of Rats

    Directory of Open Access Journals (Sweden)

    Guangmang Liu

    2016-08-01

    Full Text Available Arginine regulates growth performance, nutrient metabolism and health effects, but the underlying mechanism remains unknown. This study aims to investigate the effect of dietary arginine supplementation on rat growth performance and urinary metabolome through 1H-NMR spectroscopy. Twenty rats were randomly assigned to two groups supplemented with 0% or 1.0% l-arginine for 4 weeks. Urine samples were analyzed through NMR-based metabolomics. Arginine supplementation significantly increased the urine levels of 4-aminohippurate, acetate, creatine, creatinine, ethanolamine, formate, hippurate, homogentisate, indoxyl sulfate, and phenylacetyglycine. Conversely, arginine decreased the urine levels of acetamide, β-glucose, cirtulline, ethanol, glycine, isobutyrate, lactate, malonate, methymalonate, N-acetylglutamate, N-methylnicotinamide, and propionate. Results suggested that arginine can alter common systemic metabolic processes, including energy metabolism, amino acid metabolism, and gut microbiota metabolism. Moreover, the results also imply a possible physiological role of the metabolism in mediating the arginine supplementation-supported growth of rats.

  12. Metabolomics Approach To Evaluate a Baltic Sea Sourced Diet for Cultured Arctic Char (Salvelinus alpinus L.).

    Science.gov (United States)

    Cheng, Ken; Müllner, Elisabeth; Moazzami, Ali A; Carlberg, Hanna; Brännäs, Eva; Pickova, Jana

    2017-06-21

    Aqua feeds traditionally rely on fishmeal as a protein source, which is costly and unsustainable. A new feed was formulated in the study with Baltic Sea sourced decontaminated fishmeal, Mytilus edulis and Saccharomyces cerevisiae, and given to Arctic char (Salvelinus alpinus) for ten months. The diet-induced changes on metabolic profile in fish plasma, liver, and muscle were studied relative to a fishmeal-based standard diet by using a 1 H NMR-based metabolomics approach. Fish fed the test diet had higher content of betaine and lower levels of trimethylamine-N-oxide and aromatic amino acids in plasma or tissues, which were mainly caused by the diet. The metabolomics results are useful to understand the mechanism of lower body mass, smaller Fulton's condition factor, and a tendency of less lipid content observed in fish fed the test diet. Thus, modifications on the dietary levels of these compounds in the feed are needed to achieve better growth performance.

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

    Science.gov (United States)

    2014-01-01

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

  14. Chemometrics applied to quality control and metabolomics for traditional Chinese medicines.

    Science.gov (United States)

    Liu, Shao; Liang, Yi-Zeng; Liu, Hai-Tao

    2016-03-15

    Traditional Chinese medicines (TCMs) bring a great challenge in quality control and evaluating the efficacy because of their complexity of chemical composition. Chemometric techniques provide a good opportunity for mining more useful chemical information from TCMs. Then, the application of chemometrics in the field of TCMs is spontaneous and necessary. This review focuses on the recent various important chemometrics tools for chromatographic fingerprinting, including peak alignment information features, baseline correction and applications of chemometrics in metabolomics and modernization of TCMs, including authentication and evaluation of the quality of TCMs, evaluating the efficacy of TCMs and essence of TCM syndrome. In the conclusions, the general trends and some recommendations for improving chromatographic metabolomics data analysis are provided. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Untargeted metabolomics: an emerging approach to determine the composition of herbal products

    Directory of Open Access Journals (Sweden)

    Flavia Guzzo

    2013-01-01

    Full Text Available Natural remedies, such as those based on traditional Chinese medicines, have become more popular also in western countries over the last 10 years. The composition of these herbal products is largely unknown and difficult to determine. Moreover, since plants respond to their environment changing the metabolome, the composition of plant material can vary depending on the plant growth conditions.However, there is a growing need of a deeper knowledge on such natural remedies also in view of the growing number of reports of toxicity following the consumption of herbal supplements. Untargeted metabolomics is a useful approach for the simultaneous analysis of many compounds in herbal products. In particular, liquid chromatography/mass spectrometry (LC-MS can determine presence, amount and sometime structures of plant metabolites in complex herbal mixtures, with significant advantages over techniques such as nuclear magnetic resonance (NMR spectroscopy and gas chromatography/mass spectrometry (GC-MS.

  16. Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery.

    Science.gov (United States)

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2017-08-25

    This work reports the second part of a review intending to give the state of the art of major metabolic phenotyping strategies. It particularly deals with inherent advantages and limits regarding data analysis issues and biological information retrieval tools along with translational challenges. This Part starts with introducing the main data preprocessing strategies of the different metabolomics data. Then, it describes the main data analysis techniques including univariate and multivariate aspects. It also addresses the challenges related to metabolite annotation and characterization. Finally, functional analysis including pathway and network strategies are discussed. The last section of this review is devoted to practical considerations and current challenges and pathways to bring metabolomics into clinical environments.

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

    Directory of Open Access Journals (Sweden)

    Vladimir Tolstikov

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

  18. Topsoil depth substantially influences the responses to drought of the foliar metabolomes of Mediterranean forests

    Czech Academy of Sciences Publication Activity Database

    Rivas-Ubach, A.; Barbeta, A.; Sardans, J.; Guenther, A.; Ogaya, R.; Oravec, Michal; Urban, Otmar; Peňuelas, J.

    2016-01-01

    Roč. 21, aug (2016), s. 41-54 ISSN 1433-8319 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk(CZ) LM2015061; GA MŠk EE2.3.20.0246 Institutional support: RVO:67179843 Keywords : vegetation structure * soil depth * soil moisture * metabolomics * Quercus ilex Subject RIV: ED - Physiology Impact factor: 3.123, year: 2016

  19. Targeted metabolomic profiling of cardioprotective effect of Ginkgo biloba L. extract on myocardial ischemia in rats.

    Science.gov (United States)

    Wang, Zhe; Zhang, Jinlan; Ren, Tiankun; Dong, Zhen

    2016-06-01

    Myocardial ischemia (MI) is one of the highest mortality diseases in the world. It is closely associated with metabolism disorders of endogenous substances. Ginkgo biloba L. extract (GBE) is a popular herbal medicine used for prevention and therapy of MI. But its regulation effect on the metabolism disorders caused by MI remains currently unknown. Our metabolomic profiling study provided insight into endogenous metabolic disorders of MI and cardioprotective mechanisms of GBE. The rats were preventive administrated of GBE (200mg/kg, i.g.) for 4 weeks and then subcutaneous injected of isoproterenol to establish MI model. Heart marker enzymes and histopathological examination were adopted to evaluate MI model and effect of GBE. On this base, endogenous metabolites in rat plasma and heart were well profiled using the developed targeted metabolomic profiling platform to comprehensively analyze metabolic pathways and find biomarkers. A targeted metabolomic profiling platform was developed and only 100μl biological sample was used to quantify 808 metabolites covering the core network of lipid, energy, amino acid and nucleotide metabolism. Then using this platform, endogenous metabolites of rats undergoing MI model and GBE pre-treatment were well profiled. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to discriminate between groups and find biomarkers. The metabolomic profiles of MI model rats pre-protected by GBE were significantly different from those of unprotected. 47 metabolites were found as potential biomarkers and indicated MI would lead to disturbed metabolism due to inflammation, oxidative stress and structural damage; while GBE could effectively restore fatty acid, sphingolipid, phosphoglyceride, glyceride, amino acid and energy metabolism, closely related to its antioxidant, PAF antagonist and hypolipidemic properties. The cardioprotective effect of GBE can be achieved through the comprehensive regulation of multiple metabolic

  20. The effects of liraglutide in mice with diet-induced obesity studied by metabolomics

    Czech Academy of Sciences Publication Activity Database

    Bugáňová, Martina; Pelantová, Helena; Holubová, Martina; Šedivá, B.; Maletínská, Lenka; Železná, Blanka; Kuneš, Jaroslav; Kačer, Petr; Kuzma, Marek; Haluzík, M.

    2017-01-01

    Roč. 233, č. 1 (2017), s. 93-104 ISSN 0022-0795 R&D Projects: GA ČR GA13-14105S; GA MŠk(CZ) LO1509 Institutional support: RVO:61388971 ; RVO:61388963 Keywords : NMR metabolomics * obesity * type 2 diabetes mellitus Subject RIV: EE - Microbiology, Virology OBOR OECD: Microbiology; Physiology (including cytology) (UOCHB-X) Impact factor: 4.706, year: 2016

  1. Effects of menstrual cycle phase on metabolomic profiles in premenopausal women.

    Science.gov (United States)

    Wallace, M; Hashim, Y Z H-Y; Wingfield, M; Culliton, M; McAuliffe, F; Gibney, M J; Brennan, L

    2010-04-01

    Characterization of the normal degree of physiological variation in the metabolomic profiles of healthy humans is a necessary step in the development of metabolomics as both a clinical research and diagnostic tool. This study investigated the effects of the menstrual cycle on (1)H nuclear magnetic resonance (NMR) derived metabolomic profiles of urine and plasma from healthy women. In this study, 34 healthy women were recruited and a first void urine and fasting blood sample were collected from each woman at four different time points during one menstrual cycle. Serum hormone levels were used in combination with the menstrual calendar to classify the urine and plasma samples into five different phases i.e. menstrual, follicular, periovulatory, luteal and premenstrual. The urine and plasma samples were analysed using (1)H NMR spectroscopy and subsequent data were analysed using principal component analysis (PCA) and partial least squares discriminant analysis. PCA of the urine spectra showed no separation of samples based on the phases of the menstrual cycle. Multivariate analysis of the plasma spectra showed a separation of the menstrual phase and the luteal phase samples (R(2) = 0.61, Q(2) = 0.41). Subsequent analysis revealed a significant decrease in levels of glutamine, glycine, alanine, lysine, serine and creatinine and a significant increase in levels of acetoacetate and very low density lipoprotein (VLDL CH(2)) during the luteal phase. These results establish a need to control for metabolic changes that occur in plasma due to the menstrual cycle in the design of future metabolomic studies involving premenopausal women.

  2. Assessing the impact of transcriptomics, proteomics and metabolomics on fungal phytopathology.

    Science.gov (United States)

    Tan, Kar-Chun; Ipcho, Simon V S; Trengove, Robert D; Oliver, Richard P; Solomon, Peter S

    2009-09-01

    SUMMARY Peer-reviewed literature is today littered with exciting new tools and techniques that are being used in all areas of biology and medicine. Transcriptomics, proteomics and, more recently, metabolomics are three of these techniques that have impacted on fungal plant pathology. Used individually, each of these techniques can generate a plethora of data that could occupy a laboratory for years. When used in combination, they have the potential to comprehensively dissect a system at the transcriptional and translational level. Transcriptomics, or quantitative gene expression profiling, is arguably the most familiar to researchers in the field of fungal plant pathology. Microarrays have been the primary technique for the last decade, but others are now emerging. Proteomics has also been exploited by the fungal phytopathogen community, but perhaps not to its potential. A lack of genome sequence information has frustrated proteomics researchers and has largely contributed to this technique not fulfilling its potential. The coming of the genome sequencing era has partially alleviated this problem. Metabolomics is the most recent of these techniques to emerge and is concerned with the non-targeted profiling of all metabolites in a given system. Metabolomics studies on fungal plant pathogens are only just beginning to appear, although its potential to dissect many facets of the pathogen and disease will see its popularity increase quickly. This review assesses the impact of transcriptomics, proteomics and metabolomics on fungal plant pathology over the last decade and discusses their futures. Each of the techniques is described briefly with further reading recommended. Key examples highlighting the application of these technologies to fungal plant pathogens are also reviewed.

  3. Mass spectrometry-based metabolomic fingerprinting for screening cold tolerance in Arabidopsis thaliana accessions

    Czech Academy of Sciences Publication Activity Database

    Václavík, L.; Mishra, Anamika; Mishra, Kumud; Hajslova, J.

    2013-01-01

    Roč. 405, č. 8 (2013), s. 2671-2683 ISSN 1618-2642 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA MŠk OC08055 Institutional support: RVO:67179843 Keywords : cold tolerance * Arabidopsis thaliana * metabolomic fingerprinting * LC-MS * DART-MS * chemometric analysis Subject RIV: EH - Ecology, Behaviour Impact factor: 3.578, year: 2013

  4. Metabolomic characteristics of arsenic-associated diabetes in a prospective cohort in Chihuahua, Mexico.

    Science.gov (United States)

    Martin, Elizabeth; González-Horta, Carmen; Rager, Julia; Bailey, Kathryn A; Sánchez-Ramírez, Blanca; Ballinas-Casarrubias, Lourdes; Ishida, María C; Gutiérrez-Torres, Daniela S; Hernández Cerón, Roberto; Viniegra Morales, Damián; Baeza Terrazas, Francisco A; Saunders, R Jesse; Drobná, Zuzana; Mendez, Michelle A; Buse, John B; Loomis, Dana; Jia, Wei; García-Vargas, Gonzalo G; Del Razo, Luz M; Stýblo, Miroslav; Fry, Rebecca

    2015-04-01

    Chronic exposure to inorganic arsenic (iAs) has been linked to an increased risk of diabetes, yet the specific disease phenotype and underlying mechanisms are poorly understood. In the present study we set out to identify iAs exposure-associated metabolites with altered abundance in nondiabetic and diabetic individuals in an effort to understand the relationship between exposure, metabolomic response, and disease status. A nested study design was used to profile metabolomic shifts in urine and plasma collected from 90 diabetic and 86 nondiabetic individuals matched for varying iAs concentrations in drinking water, body mass index, age, and sex. Diabetes diagnosis was based on measures of fasting plasma glucose and 2-h blood glucose. Multivariable models were used to identify metabolites with altered abundance associated with iAs exposure among diabetic and nondiabetic individuals. A total of 132 metabolites were identified to shift in urine or plasma in response to iAs exposure characterized by the sum of iAs metabolites in urine (U-tAs). Although many metabolites were altered in both diabetic and nondiabetic 35 subjects, diabetic individuals displayed a unique response to iAs exposure with 59 altered metabolites including those that play a role in tricarboxylic acid cycle and amino acid metabolism. Taken together, these data highlight the broad impact of iAs exposure on the human metabolome, and demonstrate some specificity of the metabolomic response between diabetic and nondiabetic individuals. These data may provide novel insights into the mechanisms and phenotype of diabetes associated with iAs exposure. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer

    DEFF Research Database (Denmark)

    Bertini, Ivano; Cacciatore, Stefano; Jensen, Benny V

    2012-01-01

    survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P = 1.33 × 10(-6)). A number of metabolites concurred with the (1)H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that (1)H-NMR profiling of patient serum can provide a strong metabolomic signature of m...

  6. MSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data.

    Science.gov (United States)

    Hughes, Grant; Cruickshank-Quinn, Charmion; Reisdorph, Richard; Lutz, Sharon; Petrache, Irina; Reisdorph, Nichole; Bowler, Russell; Kechris, Katerina

    2014-01-01

    Although R packages exist for the pre-processing of metabolomic data, they currently do not incorporate additional analysis steps of summarization, filtering and normalization of aligned data. We developed the MSPrep R package to complement other packages by providing these additional steps, implementing a selection of popular normalization algorithms and generating diagnostics to help guide investigators in their analyses. http://www.sourceforge.net/projects/msprep

  7. Long-term differential changes in mouse intestinal metabolomics after γ and heavy ion radiation exposure.

    Directory of Open Access Journals (Sweden)

    Amrita K Cheema

    Full Text Available Tissue consequences of radiation exposure are dependent on radiation quality and high linear energy transfer (high-LET radiation, such as heavy ions in space is known to deposit higher energy in tissues and cause greater damage than low-LET γ radiation. While radiation exposure has been linked to intestinal pathologies, there are very few studies on long-term effects of radiation, fewer involved a therapeutically relevant γ radiation dose, and none explored persistent tissue metabolomic alterations after heavy ion space radiation exposure. Using a metabolomics approach, we report long-term metabolomic markers of radiation injury and perturbation of signaling pathways linked to metabolic alterations in mice after heavy ion or γ radiation exposure. Intestinal tissues (C57BL/6J, female, 6 to 8 wks were analyzed using ultra performance liquid chromatography coupled with electrospray quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS two months after 2 Gy γ radiation and results were compared to an equitoxic ⁵⁶Fe (1.6 Gy radiation dose. The biological relevance of the metabolites was determined using Ingenuity Pathway Analysis, immunoblots, and immunohistochemistry. Metabolic profile analysis showed radiation-type-dependent spatial separation of the groups. Decreased adenine and guanosine and increased inosine and uridine suggested perturbed nucleotide metabolism. While both the radiation types affected amino acid metabolism, the ⁵⁶Fe radiation preferentially altered dipeptide metabolism. Furthermore, ⁵⁶Fe radiation caused upregulation of 'prostanoid biosynthesis' and 'eicosanoid signaling', which are interlinked events related to cellular inflammation and have implications for nutrient absorption and inflammatory bowel disease during space missions and after radiotherapy. In conclusion, our data showed for the first time that metabolomics can not only be used to distinguish between heavy ion and γ radiation exposures, but

  8. Natural variation of root exudates in Arabidopsis thaliana-linking metabolomic and genomic data

    OpenAIRE

    Susann Mönchgesang; Nadine Strehmel; Stephan Schmidt; Lore Westphal; Franziska Taruttis; Erik Müller; Siska Herklotz; Steffen Neumann; Dierk Scheel

    2016-01-01

    Many metabolomics studies focus on aboveground parts of the plant, while metabolism within roots and the chemical composition of the rhizosphere, as influenced by exudation, are not deeply investigated. In this study, we analysed exudate metabolic patterns of Arabidopsis thaliana and their variation in genetically diverse accessions. For this project, we used the 19 parental accessions of the Arabidopsis MAGIC collection. Plants were grown in a hydroponic system, their exudates were harvested...

  9. Dietary and metabolomic determinants of relapse in ulcerative colitis patients: A pilot prospective cohort study.

    Science.gov (United States)

    Keshteli, Ammar Hassanzadeh; van den Brand, Floris F; Madsen, Karen L; Mandal, Rupasri; Valcheva, Rosica; Kroeker, Karen I; Han, Beomsoo; Bell, Rhonda C; Cole, Janis; Hoevers, Thomas; Wishart, David S; Fedorak, Richard N; Dieleman, Levinus A

    2017-06-07

    To identify demographic, clinical, metabolomic, and lifestyle related predictors of relapse in adult ulcerative colitis (UC) patients. In this prospective pilot study, UC patients in clinical remission were recruited and followed-up at 12 mo to assess a clinical relapse, or not. At baseline information on demographic and clinical parameters was collected. Serum and urine samples were collected for analysis of metabolomic assays using a combined direct infusion/liquid chromatography tandem mass spectrometry and nuclear magnetic resolution spectroscopy. Stool samples were also collected to measure fecal calprotectin (FCP). Dietary assessment was performed using a validated self-administered food frequency questionnaire. Twenty patients were included (mean age: 42.7 ± 14.8 years, females: 55%). Seven patients (35%) experienced a clinical relapse during the follow-up period. While 6 patients (66.7%) with normal body weight developed a clinical relapse, 1 UC patient (9.1%) who was overweight/obese relapsed during the follow-up ( P = 0.02). At baseline, poultry intake was significantly higher in patients who were still in remission during follow-up (0.9 oz vs 0.2 oz, P = 0.002). Five patients (71.4%) with FCP > 150 μg/g and 2 patients (15.4%) with normal FCP (≤ 150 μg/g) at baseline relapsed during the follow-up ( P = 0.02). Interestingly, baseline urinary and serum metabolomic profiling of UC patients with or without clinical relapse within 12 mo showed a significant difference. The most important metabolites that were responsible for this discrimination were trans-aconitate, cystine and acetamide in urine, and 3-hydroxybutyrate, acetoacetate and acetone in serum. A combination of baseline dietary intake, fecal calprotectin, and metabolomic factors are associated with risk of UC clinical relapse within 12 mo.

  10. Dietary and metabolomic determinants of relapse in ulcerative colitis patients: A pilot prospective cohort study

    Science.gov (United States)

    Keshteli, Ammar Hassanzadeh; van den Brand, Floris F; Madsen, Karen L; Mandal, Rupasri; Valcheva, Rosica; Kroeker, Karen I; Han, Beomsoo; Bell, Rhonda C; Cole, Janis; Hoevers, Thomas; Wishart, David S; Fedorak, Richard N; Dieleman, Levinus A

    2017-01-01

    AIM To identify demographic, clinical, metabolomic, and lifestyle related predictors of relapse in adult ulcerative colitis (UC) patients. METHODS In this prospective pilot study, UC patients in clinical remission were recruited and followed-up at 12 mo to assess a clinical relapse, or not. At baseline information on demographic and clinical parameters was collected. Serum and urine samples were collected for analysis of metabolomic assays using a combined direct infusion/liquid chromatography tandem mass spectrometry and nuclear magnetic resolution spectroscopy. Stool samples were also collected to measure fecal calprotectin (FCP). Dietary assessment was performed using a validated self-administered food frequency questionnaire. RESULTS Twenty patients were included (mean age: 42.7 ± 14.8 years, females: 55%). Seven patients (35%) experienced a clinical relapse during the follow-up period. While 6 patients (66.7%) with normal body weight developed a clinical relapse, 1 UC patient (9.1%) who was overweight/obese relapsed during the follow-up (P = 0.02). At baseline, poultry intake was significantly higher in patients who were still in remission during follow-up (0.9 oz vs 0.2 oz, P = 0.002). Five patients (71.4%) with FCP > 150 μg/g and 2 patients (15.4%) with normal FCP (≤ 150 μg/g) at baseline relapsed during the follow-up (P = 0.02). Interestingly, baseline urinary and serum metabolomic profiling of UC patients with or without clinical relapse within 12 mo showed a significant difference. The most important metabolites that were responsible for this discrimination were trans-aconitate, cystine and acetamide in urine, and 3-hydroxybutyrate, acetoacetate and acetone in serum. CONCLUSION A combination of baseline dietary intake, fecal calprotectin, and metabolomic factors are associated with risk of UC clinical relapse within 12 mo. PMID:28638229

  11. Evaluation of extracts of Piper sarmentosum for accelerated stability by metabolomic fingerprint profiling

    OpenAIRE

    K Hussain; Z Ismail; A Sadikun; P Ibrahim

    2009-01-01

    Unlike pharmaceuticals, precise stability assessment of herbal products is challenging because of their complex nature. A new trend in natural products is that the extract is considered active as a whole whether active constituents are known or not. Hence, the stability of all the constituents must be taken into account, which is possible by analyzing metabolomic fingerprint profiles. Therefore, present study aimed to evaluate ethanol extracts of fruit of Piper sarmentosum, an important medic...

  12. Gut microbiota, metabolome and immune signatures in patients with uncomplicated diverticular disease.

    Science.gov (United States)

    Barbara, Giovanni; Scaioli, Eleonora; Barbaro, Maria Raffaella; Biagi, Elena; Laghi, Luca; Cremon, Cesare; Marasco, Giovanni; Colecchia, Antonio; Picone, Gianfranco; Salfi, Nunzio; Capozzi, Francesco; Brigidi, Patrizia; Festi, Davide

    2017-07-01

    The engagement of the gut microbiota in the development of symptoms and complications of diverticular disease has been frequently hypothesised. Our aim was to explore colonic immunocytes, gut microbiota and the metabolome in patients with diverticular disease in a descriptive, cross-sectional, pilot study. Following colonoscopy with biopsy and questionnaire phenotyping, patients were classified into diverticulosis or symptomatic uncomplicated diverticular disease; asymptomatic subjects served as controls. Mucosal immunocytes, in the diverticular region and in unaffected sites, were quantified with immunohistochemistry. Mucosa and faecal microbiota were analysed by the phylogenetic platform high taxonomic fingerprint (HTF)-Microbi.Array, while the metabolome was assessed by 1 H nuclear magnetic resonance. Compared with controls, patients with diverticula, regardless of symptoms, had a >70% increase in colonic macrophages. Their faecal microbiota showed depletion of Clostridium cluster IV. Clostridium cluster IX, Fusobacterium and Lactobacillaceae were reduced in symptomatic versus asymptomatic patients. A negative correlation was found between macrophages and mucosal Clostridium cluster IV and Akkermansia . Urinary and faecal metabolome changes in diverticular disease involved the hippurate and kynurenine pathways. Six urinary molecules allowed to discriminate diverticular disease and control groups with >95% accuracy. Patients with colonic diverticular disease show depletion of microbiota members with anti-inflammatory activity associated with mucosal macrophage infiltration. Metabolome profiles were linked to inflammatory pathways and gut neuromotor dysfunction and showed the ability to discriminate diverticular subgroups and controls. These data pave the way for further large-scale studies specifically aimed at identifying microbiota signatures with a potential diagnostic value in patients with diverticular disease. Published by the BMJ Publishing Group Limited

  13. Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis.

    Directory of Open Access Journals (Sweden)

    Joong Kyong Ahn

    Full Text Available Rheumatoid arthritis (RA is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3, which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin. Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA.

  14. Facilitating the development of controlled vocabularies for metabolomics technologies with text mining

    Directory of Open Access Journals (Sweden)

    Rebholz-Schuhmann Dietrich

    2008-04-01

    Full Text Available Abstract Background Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public resources. Experimental data sets from metabolomics studies need to be integrated with one another, but also with data produced by other types of omics studies in the spirit of systems biology, hence the pressing need for vocabularies and ontologies in metabolomics. However, it is time-consuming and non trivial to construct these resources manually. Results We describe a methodology for rapid development of controlled vocabularies, a study originally motivated by the needs for vocabularies describing metabolomics technologies. We present case studies involving two controlled vocabularies (for nuclear magnetic resonance spectroscopy and gas chromatography whose development is currently underway as part of the Metabolomics Standards Initiative. The initial vocabularies were compiled manually, providing a total of 243 and 152 terms. A total of 5,699 and 2,612 new terms were acquired automatically from the literature. The analysis of the results showed that full-text articles (especially the Materials and Methods sections are the major source of technology-specific terms as opposed to paper abstracts. Conclusions We suggest a text mining method for efficient corpus-based term acquisition as a way of rapidly expanding a set of controlled vocabularies with the terms used in the scientific literature. We adopted an integrative approach, combining relatively generic software and data resources for time- and cost-effective development of a text mining tool for expansion of controlled vocabularies across various domains, as a practical alternative to both manual term collection and tailor-made named entity recognition methods.

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

    Science.gov (United States)

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

    2014-01-01

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

  16. Metabolomic Profiling of 13 Diatom Cultures and Their Adaptation to Nitrate-Limited Growth Conditions.

    Directory of Open Access Journals (Sweden)

    Mariusz A Bromke

    Full Text Available Diatoms are very efficient in their use of available nutrients. Changes in nutrient availability influence the metabolism and the composition of the cell constituents. Since diatoms are valuable candidates to search for oil producing algae, measurements of diatom-produced compounds can be very useful for biotechnology. In order to explore the diversity of lipophilic compounds produced by diatoms, we describe the results from an analysis of 13 diatom strains. With the help of a lipidomics platform, which combines an UPLC separation with a high resolution/high mass accuracy mass spectrometer, we were able to measure and annotate 142 lipid species. Out of these, 32 were present in all 13 cultures. The annotated lipid features belong to six classes of glycerolipids. The data obtained from the measurements were used to create lipidomic profiles. The metabolomic overview of analysed cultures is amended by the measurement of 96 polar compounds. To further increase the lipid diversity and gain insight into metabolomic adaptation to nitrogen limitation, diatoms were cultured in media with high and low concentrations of nitrate. The growth in nitrogen-deplete or nitrogen-replete conditions affects metabolite accumulation but has no major influence on the species-specific metabolomic profile. Thus, the genetic component is stronger in determining metabolic patterns than nitrogen levels. Therefore, lipid profiling is powerful enough to be used as a molecular fingerprint for diatom cultures. Furthermore, an increase of triacylglycerol (TAG accumulation was observed in low nitrogen samples, although this trend was not consistent across all 13 diatom strains. Overall, our results expand the current understanding of metabolomics diversity in diatoms and confirm their potential value for producing lipids for either bioenergy or as feed stock.

  17. MET-XAlign: a metabolite cross-alignment tool for LC/MS-based comparative metabolomics.

    Science.gov (United States)

    Zhang, Wenchao; Lei, Zhentian; Huhman, David; Sumner, Lloyd W; Zhao, Patrick X

    2015-09-15

    Liquid chromatography/mass spectrometry (LC/MS) metabolite profiling has been widely used in comparative metabolomics studies; however, LC/MS-based comparative metabolomics currently faces several critical challenges. One of the greatest challenges is how to effectively align metabolites across different LC/MS profiles; a single metabolite can give rise to multiple peak features, and the grouped peak features that can be used to construct a spectrum pattern of single metabolite can vary greatly between biochemical experiments and even between instrument runs. Another major challenge is that the observed retention time for a single metabolite can also be significantly affected by experimental conditions. To overcome these two key challenges, we present a novel metabolite-based alignment approach entitled MET-XAlign to align metabolites across LC/MS metabolomics profiles. MET-XAlign takes the deduced molecular mass and estimated compound retention time information that can be extracted by our previously published tool, MET-COFEA, and aligns metabolites based on this information. We demonstrate that MET-XAlign is able to cross-align metabolite compounds, either known or unknown, in LC/MS profiles not only across different samples but also across different biological experiments and different electrospray ionization modes. Therefore, our proposed metabolite-based cross-alignment approach is a great step forward and its implementation, MET-XAlign, is a very useful tool in LC/MS-based comparative metabolomics. MET-XAlign has been successfully implemented with core algorithm coding in C++, making it very efficient, and visualization interface coding in the Microsoft.NET Framework. The MET-XAlign software along with demonstrative data is freely available at http://bioinfo.noble.org/manuscript-support/met-xalign/ .

  18. MASTR-MS: a web-based collaborative laboratory information management system (LIMS) for metabolomics.

    Science.gov (United States)

    Hunter, Adam; Dayalan, Saravanan; De Souza, David; Power, Brad; Lorrimar, Rodney; Szabo, Tamas; Nguyen, Thu; O'Callaghan, Sean; Hack, Jeremy; Pyke, James; Nahid, Amsha; Barrero, Roberto; Roessner, Ute; Likic, Vladimir; Tull, Dedreia; Bacic, Antony; McConville, Malcolm; Bellgard, Matthew

    2017-01-01

    An increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no Laboratory Information Management Systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments. Here we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a Node Management System that can be used to link and manage projects across one or multiple collaborating laboratories; a User Management System which defines different user groups and privileges of users; a Quote Management System where client quotes are managed; a Project Management System in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined, and a Data Management System that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS. MASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research

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

    Science.gov (United States)

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

    2014-06-15

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

  20. Impact of soil warming on the plant metabolome of Icelandic grasslands

    Czech Academy of Sciences Publication Activity Database

    Gargallo-Garriga, A.; Ayala-Roque, M.; Sardans, J.; Bartrons, M.; Granda, V.; Sigurdsson, B. D.; Leblans, N. I.W.; Oravec, Michal; Urban, Otmar; Janssens, I. A.; Peñuelas, J.

    2017-01-01

    Roč. 7, č. 3 (2017), č. článku 44. E-ISSN 2218-1989 R&D Projects: GA MŠk(CZ) LM2015061; GA MŠk(CZ) LO1415 Institutional support: RVO:86652079 Keywords : Climate change * Geothermal bedrock channels * Grassland * Iceland * Metabolome * Warming Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7)

  1. Metabolomic Profiling of 13 Diatom Cultures and Their Adaptation to Nitrate-Limited Growth Conditions

    Science.gov (United States)

    Bromke, Mariusz A.; Sabir, Jamal S.; Alfassi, Fahad A.; Hajarah, Nahid H.; Kabli, Saleh A.; Al-Malki, Abdulrahman L.; Ashworth, Matt P.; Méret, Michaël; Jansen, Robert K.; Willmitzer, Lothar

    2015-01-01

    Diatoms are very efficient in their use of available nutrients. Changes in nutrient availability influence the metabolism and the composition of the cell constituents. Since diatoms are valuable candidates to search for oil producing algae, measurements of diatom-produced compounds can be very useful for biotechnology. In order to explore the diversity of lipophilic compounds produced by diatoms, we describe the results from an analysis of 13 diatom strains. With the help of a lipidomics platform, which combines an UPLC separation with a high resolution/high mass accuracy mass spectrometer, we were able to measure and annotate 142 lipid species. Out of these, 32 were present in all 13 cultures. The annotated lipid features belong to six classes of glycerolipids. The data obtained from the measurements were used to create lipidomic profiles. The metabolomic overview of analysed cultures is amended by the measurement of 96 polar compounds. To further increase the lipid diversity and gain insight into metabolomic adaptation to nitrogen limitation, diatoms were cultured in media with high and low concentrations of nitrate. The growth in nitrogen-deplete or nitrogen-replete conditions affects metabolite accumulation but has no major influence on the species-specific metabolomic profile. Thus, the genetic component is stronger in determining metabolic patterns than nitrogen levels. Therefore, lipid profiling is powerful enough to be used as a molecular fingerprint for diatom cultures. Furthermore, an increase of triacylglycerol (TAG) accumulation was observed in low nitrogen samples, although this trend was not consistent across all 13 diatom strains. Overall, our results expand the current understanding of metabolomics diversity in diatoms and confirm their potential value for producing lipids for either bioenergy or as feed stock. PMID:26440112

  2. Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics

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    Margaux Marie-Hélène, Olivia Luck

    2015-07-01

    Full Text Available Long-term endurance exercise severely affects metabolism in both human and animal athletes resulting in serious risk of metabolic disorders during or after competition. Young horses (up to 6 years old can compete in races up to 90 km despite limited scientific knowledge of energetic metabolism responses to long distance exercise in these animals. The hypothesis of this study was that there would be a strong effect of endurance exercise on the metabolomic profiles of young horses and that the energetic metabolism response in young horses would be different from that of more experienced horses. Metabolomic profiling is a powerful method that combines Nuclear magnetic resonance (NMR spectrometry with supervised orthogonal projection on latent structure (OPLS statistical analysis. 1H-NMR spectra were obtained from plasma samples drawn from young horses (before and after competition. The spectra obtained before and after the race from the same horse (92 samples were compared using OPLS. The statistical parameters showed the robustness of the model (R2Y=0.947, Q2Y=0.856 and CV-ANOVA p-value < 0.001. For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1. The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism. An OPLS model was calculated to compare spectra obtained on plasma taken after the race from 6-year-old horses and from experienced horses (cross-validated ANOVA p-value < 0.001. The comparison of metabolomic profiles in young horses to those from experienced horses showed that experienced horses maintained their glycemia with higher levels of lactate and a decrease of plasma lipids after the race.

  3. Non-target effects of GM potato: an eco-metabolomics approach

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    Plischke, Andreas

    2013-01-01

    In this thesis, patterns of variation in plant metabolomes and insect communities were described in GM and non-GM potato plants in both laboratory and field experiments. Differences between plant genotypes in insect abundances were small when compared to year-to-year differences, location effects and differences between developmental stages of plants. Standardized effect sizes are discussed as an alternative scale for measuring effects. Leaf age, aphid infestation and virus infection were fou...

  4. "Omics" of High Altitude Biology: A Urinary Metabolomics Biomarker Study of Rats Under Hypobaric Hypoxia.

    Science.gov (United States)

    Koundal, Sunil; Gandhi, Sonia; Kaur, Tanzeer; Mazumder, Avik; Khushu, Subash

    2015-12-01

    High altitude medicine is an emerging subspecialty that has crosscutting relevance for 21(st) century science and society: from sports medicine and aerospace industry to urban and rural communities living in high altitude. Recreational travel to high altitude has also become increasingly popular. Rarely has the biology of high altitude biology been studied using systems sciences and omics high-throughput technologies. In the present study, 1H-NMR-based metabolomics, along with multivariate analyses, were employed in a preclinical rat model to characterize the urinary metabolome under hypobaric hypoxia stress. Rats were exposed to simulated altitude of 6700 m above the sea level. The urine samples were collected from pre- and post-exposure (1, 3, 7, and 14 days) of hypobaric hypoxia. Metabolomics urinalysis showed alterations in TCA cycle metabolites (citrate, α-ketoglutarate), cell membrane metabolism (choline), gut micro-flora metabolism (hippurate, phenylacetylglycine), and others (N-acetyl glutamate, creatine, taurine) in response to hypobaric hypoxia. Taurine, a potential biomarker of hepatic function, was elevated after 3 days of hypobaric hypoxia, which indicates altered liver functioning. Liver histopathology confirmed the damage to tissue architecture due to hypobaric hypoxia. The metabolic pathway analysis identified taurine metabolism and TCA as important pathways that might have contributed to hypobaric hypoxia-induced pathophysiology. This study demonstrates the use of metabolomics as a promising tool for discovery and understanding of novel biochemical responses to hypobaric hypoxia exposure, providing new insight in the field of high altitude medicine and the attendant health problems that occur in response to high altitude. The findings reported here also have potential relevance for sports medicine and aviation sciences.

  5. Serum metabolomic profiling in acute alcoholic hepatitis identifies multiple dysregulated pathways.

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    Rachakonda, Vikrant; Gabbert, Charles; Raina, Amit; Bell, Lauren N; Cooper, Sara; Malik, Shahid; Behari, Jaideep

    2014-01-01

    While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH), the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA) cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. Severe AAH is characterized by a distinct metabolic phenotype spanning

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

    International Nuclear Information System (INIS)

    Ibáñez, Clara; Simó, Carolina; García-Cañas, Virginia; Cifuentes, Alejandro; Castro-Puyana, María

    2013-01-01

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

  7. Clinical Metabolomics and Nutrition: The New Frontier in Neonatology and Pediatrics

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    Angelica Dessì

    2014-01-01

    Full Text Available In the pediatric clinic, nutritional research is focusing more and more on preventing the development of long-term diseases as well as supporting the repair processes important in the therapy of already fully developed diseases. Most children who are hospitalized or affected by chronic diseases could benefit from specific and careful attention to nutrition. Indeed, the state of nutrition modulates all body functions, including the different metabolic processes which, all together, have a profound effect on the development of the health and future of all individuals. Inappropriate food, even in the first periods of life, can accelerate the development of chronic metabolic diseases, especially in the pediatric age. To gain further insights into metabolic cycles and how they are connected with diet and health, nutrition and metabolomics interact to develop and apply modern technologies for metabolic assessment. In particular, nutritionists are evaluating the metabolomic approach to establish the single nutritional phenotypes, that is, the way in which diet interacts with individuals’ metabolisms. This strategy offers the possibility of providing a complete definition of the individual’s nutritional and health status, predict the risk of disease, and create metabolomic databases supporting the development of “personalized nutrition,” in which diet is attuned to the nutritional needs of individual patients.

  8. Metabolomic profiling in blood from umbilical cords of low birth weight newborns

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    Ivorra Carmen

    2012-07-01

    Full Text Available Abstract Background Low birth weight has been linked to an increased risk to develop obesity, type 2 diabetes, and hypertension in adult life, although the mechanisms underlying the association are not well understood. The objective was to determine whether the metabolomic profile of plasma from umbilical cord differs between low and normal birth weight newborns. Methods Fifty healthy pregnant women and their infants were selected. The eligibility criteria were being born at term and having a normal pregnancy. Pairs were grouped according to their birth weight: low birth weight (LBW, birth weight th percentile, n = 20 and control (control, birth weight between the 75th-90th percentiles, n = 30. Nuclear Magnetic Resonance (NMR was used to generate metabolic fingerprints of umbilical cord plasma samples. Simultaneously, the metabolomic profiles of the mothers were analysed. The resulting data were subjected to chemometric, principal component and partial least squares discriminant analyses. Results Umbilical cord plasma from LBW and control newborns displayed a clearly differentiated metabolic profile. Seven metabolites were identified that discriminate the LBW from the control group. LBW newborns had lower levels of choline, proline, glutamine, alanine and glucose than did the control newborns, while plasma levels of phenylalanine and citrulline were higher in LBW newborns (p Conclusions Low birth weight newborns display a differential metabolomic profile than those of normal birth weight, a finding not present in the mothers. The meaning and the potential utility of the findings as biomarkers of risk need to be addressed in future studies.

  9. Characterization of the Wheat Leaf Metabolome during Grain Filling and under Varied N-Supply

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    Elmien Heyneke

    2017-11-01

    Full Text Available Progress in improving crop growth is an absolute goal despite the influence multifactorial components have on crop yield and quality. An Avalon × Cadenza doubled-haploid wheat mapping population was used to study the leaf metabolome of field grown wheat at weekly intervals during the time in which the canopy contributes to grain filling, i.e., from anthesis to 5 weeks post-anthesis. Wheat was grown under four different nitrogen supplies reaching from residual soil N to a luxury over-fertilization (0, 100, 200, and 350 kg N ha−1. Four lines from a segregating doubled haploid population derived of a cross of the wheat elite cvs. Avalon and Cadenza were chosen as they showed pairwise differences in either N utilization efficiency (NUtE or senescence timing. 108 annotated metabolites of primary metabolism and ions were determined. The analysis did not provide genotype specific markers because of a remarkable stability of the metabolome between lines. We speculate that the reason for failing to identify genotypic markers might be due to insufficient genetic diversity of the wheat parents and/or the known tendency of plants to keep metabolome homeostasis even under adverse conditions through multiple adaptations and rescue mechanism. The data, however, provided a consistent catalogue of metabolites and their respective responses to environmental and developmental factors and may bode well for future systems biology approaches, and support plant breeding and crop improvement.

  10. Liver functional metabolomics discloses an action of L-leucine against Streptococcus iniae infection in tilapias.

    Science.gov (United States)

    Ma, Yan-Mei; Yang, Man-Jun; Wang, Sanying; Li, Hui; Peng, Xuan-Xian

    2015-08-01

    Streptococcus iniae seriously affects the intensive farming of tilapias. Much work has been conducted on prevention and control of S. iniae infection, but little published information on the metabolic response is available in tilapias against the bacterial infection, and no metabolic modulation way may be adopted to control this disease. The present study used GC/MS based metabolomics to characterize the metabolic profiling of tilapias infected by a lethal dose (LD50) of S. iniae and determined two characteristic metabolomes separately responsible for the survival and dying fishes. A reversal changed metabolite, decreased and increased l-leucine in the dying and survival groups, respectively, was identified as a biomarker which featured the difference between the two metabolomes. More importantly, exogenous l-leucine could be used as a metabolic modulator to elevate survival ability of tilapias infected by S. iniae. These results indicate that tilapias mount metabolic strategies to deal with bacterial infection, which can be regulated by exogenous metabolites such as l-leucine. The present study establishes an alternative way, metabolic modulation, to cope with bacterial infections. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Covering Chemical Diversity of Genetically-Modified Tomatoes Using Metabolomics for Objective Substantial Equivalence Assessment

    Science.gov (United States)

    Hirai, Tadayoshi; Oikawa, Akira; Matsuda, Fumio; Fukushima, Atsushi; Arita, Masanori; Watanabe, Shin; Yano, Megumu; Hiwasa-Tanase, Kyoko; Ezura, Hiroshi; Saito, Kazuki

    2011-01-01

    As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms. PMID:21359231

  12. Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.

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    Neeraj Sinha

    Full Text Available Despite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical disease settings. In our study patients diagnosed with mild and moderate/severe ARDS clinically governed by hypoxemic P/F ratio between 100-300 but with indistinct molecular phenotype were discriminated employing nuclear magnetic resonance (NMR based metabolomics of mini bronchoalveolar lavage fluid (mBALF. Resulting biomarker prototype comprising six metabolites was substantiated highlighting ARDS susceptibility/recovery. Both the groups (mild and moderate/severe ARDS showed distinct biochemical profile based on 83.3% classification by discriminant function analysis and cross validated accuracy of 91% using partial least squares discriminant analysis as major classifier. The predictive performance of narrowed down six metabolites were found analogous with chemometrics. The proposed biomarker model consisting of six metabolites proline, lysine/arginine, taurine, threonine and glutamate were found characteristic of ARDS sub-stages with aberrant metabolism observed mainly in arginine, proline metabolism, lysine synthesis and so forth correlating to diseased metabotype. Thus NMR based metabolomics has provided new insight into ARDS sub-stages and conclusively a precise biomarker model proposed, reflecting underlying metabolic dysfunction aiding prior clinical decision making.

  13. Integration of datasets from different analytical techniques to assess the impact of nutrition on human metabolome

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    Pamela eVernocchi

    2012-12-01

    Full Text Available Bacteria colonizing the human intestinal tract exhibit a high phylogenetic diversity that reflects their immense metabolic potentials. The catalytic activity of gut microbes has an important impact on gastrointestinal (GI functions and host health. The microbial conversion of carbohydrates and other food components leads to the formation of a large number of compounds that affect the host metabolome and have beneficial or adverse effects on human health. Meabolomics is a metabolic-biology system approach focused on the metabolic responses understanding of living systems to physio-pathological stimuli by using multivariate statistical data on human body fluids obtained by different instrumental techniques. A metabolomic approach based on an analytical platform could be able to separate, detect, characterize and quantify a wide range of metabolites and its metabolic pathways. This approach has been recently applied to study the metabolic changes triggered in the gut microbiota by specific diet components and diet variations, specific diseases, probiotic and synbiotic food intake.This review describes the metabolomic data obtained by analyzing human fluids by using different techniques and particularly Gas Chromatography Mass Spectrometry Solid-phase Micro Extraction (GC-MS/SPME, Proton Nuclear Magnetic Resonance (1H-NMR Spectroscopy and Fourier Transform Infrared (FTIR Spectroscopy. This instrumental approach have a good potential in the identification and detection of specific food intake and diseases biomarkers.

  14. Urine metabolite analysis as a function of deoxynivalenol exposure: an NMR-based metabolomics investigation.

    Science.gov (United States)

    Hopton, R P; Turner, E; Burley, V J; Turner, P C; Fisher, J

    2010-02-01

    Deoxynivalenol (DON) is a toxic fungal metabolite that frequently contaminates cereal crops including wheat, maize and barley. Despite knowledge of frequent exposure through diet, our understanding of the potential consequences of human exposure remains limited, in part due to the lack of validated exposure biomarkers. In this study, we interrogated the urinary metabolome using nuclear magnetic resonance (NMR) spectroscopy to compare individuals with known low and high DON exposure through consumption of their normal diet. Urine samples from 22 adults from the UK (seven males, 15 females; age range = 21-59 years) had previously determined urinary DON levels using an established liquid chromatography-mass spectrometry (LC-MS) assay. Urine samples were subsequently analysed using an NMR-based metabolomics approach coupled with multivariate statistical analysis. Metabolic profiling suggested that hippurate levels could be used to distinguish between groups with low (3.6 ng DON mg(-1) creatinine: 95% CI = 2.6, 5.0 ng mg(-1)) and high (11.1 ng mg(-1): 95% CI = 8.1, 15.5 ng mg(-1)) DON exposure, with the concentration of hippurate being significantly (1.5 times) higher for people with high DON exposure than for those with low DON exposure (p = 0.047). This, to our knowledge, is the first report of a metabolomics-derived biomarker of DON exposure in humans.

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

    Science.gov (United States)

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

    2017-04-07

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

  16. The food-gut human axis: the effects of diet on gut microbiota and metabolome.

    Science.gov (United States)

    De Angelis, Maria; Garruti, Gabriella; Minervini, Fabio; Bonfrate, Leonilde; Portincasa, Piero; Gobbetti, Marco

    2017-04-27

    Gut microbiota, the largest symbiont community hosted in human organism, is emerging as a pivotal player in the relationship between dietary habits and health. Oral and, especially, intestinal microbes metabolize dietary components, affecting human health by producing harmful or beneficial metabolites, which are involved in the incidence and progression of several intestinal related and non-related diseases. Habitual diet (Western, Agrarian and Mediterranean omnivore diets, vegetarian, vegan and gluten-free diets) drives the composition of the gut microbiota and metabolome. Within the dietary components, polymers (mainly fibers, proteins, fat and polyphenols) that are not hydrolyzed by human enzymes seem to be the main leads of the metabolic pathways of gut microbiota, which in turn directly influences the human metabolome. Specific relationships between diet and microbes, microbes and metabolites, microbes and immune functions and microbes and/or their metabolites and some human diseases are being established. Dietary treatments with fibers are the most effective to benefit the metabolome profile, by improving the synthesis of short chain fatty acids and decreasing the level of molecules, such as p-cresyl sulfate, indoxyl sulfate and trimethylamine N-oxide, involved in disease state. Based on the axis diet-microbiota-health, this review aims at describing the most recent knowledge oriented towards a profitable use of diet to provide benefits to human health, both directly and indirectly, through the activity of gut microbiota. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  17. Metabolomics reveals significant variations in metabolites and correlations regarding the maturation of walnuts (Juglans regia L.

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    Guodong Rao

    2016-06-01

    Full Text Available The content of walnut metabolites is related to its nutritive value and physiological characteristics, however, comprehensive information concerning the metabolome of walnut kernels is limited. In this study we analyzed the metabolites of walnut kernels at five developmental stages from filling to ripening using GC-MS-based untargeted metabolomics; of a total 252 peaks identified, 85 metabolites were positively identified. Further statistical analysis revealed that these 85 metabolites covered different types of metabolism pathways. PCA scores revealed that the metabolic compositions of the embryo are different at each stage, while the metabolic composition of the endotesta could not be significantly separated into distinct groups. Additionally, 7225 metabolite-metabolite correlations were detected in walnut kernel by a Pearson correlation coefficient approach; during screening of the calculated correlations, 463 and 1047 were determined to be significant with r2≥0.49 and had a false discovery rate (FDR ≤0.05 in endotesta and embryo, respectively. This work provides the first comprehensive metabolomic study of walnut kernels and reveals that most of the carbohydrate and protein-derived carbon was transferred into other compounds, such as fatty acids, during the maturation of walnuts, which may potentially provide the basis for further studies on walnut kernel metabolism.

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

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    Le You

    2014-03-01

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

  19. Studying the Differences of Bacterial Metabolome and Microbiome in the Colon between Landrace and Meihua Piglets

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    Shijuan Yan

    2017-09-01

    Full Text Available This study was conducted to compare the microbiome and metabolome differences in the colon lumen from two pig breeds with different genetic backgrounds. Fourteen weaned piglets at 30 days of age, including seven Landrace piglets (a lean-type pig breed with a fast growth rate and seven Meihua piglets (a fatty-type Chinese local pig breed with a slow growth rate, were fed the same diets for 35 days. Untargeted metabolomics analyses showed that a total of 401 metabolites differed between Landrace and Meihua. Seventy of these 401 metabolites were conclusively identified. Landrace accumulated more short-chain fatty acids (SCFAs and secondary bile acids in the colon lumen. Moreover, expression of the SCFAs transporter (solute carrier family 5 member 8, SLC5A8 and receptor (G protein-coupled receptor 41, GPR41 in the colon mucosa was higher, while the bile acids receptor (farnesoid X receptor, FXR had lower expression in Landrace compared to Meihua. The relative abundances of 8 genera and 16 species of bacteria differed significantly between Landrace and Meihua, and were closely related to the colonic concentrations of bile acids or SCFAs based on Pearson's correlation analysis. Collectively, our results demonstrate for the first time that there were differences in the colonic microbiome and metabolome between Meihua and Landrace piglets, with the most profound disparity in production of SCFAs and secondary bile acids.

  20. Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

    Science.gov (United States)

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

    2016-01-01

    Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

  1. Profiles of microbial fatty acids in the human metabolome are disease-specific

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    Zhanna A Ktsoyan

    2011-01-01

    Full Text Available The human gastrointestinal tract is inhabited by a diverse and dense symbiotic microbiota, the composition of which is the result of host-microbe co-evolution and co-adaptation. This tight integration creates intense crosstalk and signalling between the host and microbiota at the cellular and metabolic levels. In many genetic or infectious diseases the balance between host and microbiota may be compromised resulting in erroneous communication. Consequently, the composition of the human metabolome, which includes the gut metabolome, may be different in health and disease states in terms of microbial products and metabolites entering systemic circulation. To test this hypothesis, we measured the level of hydroxy, branched, cyclopropyl and unsaturated fatty acids, aldehydes, and phenyl derivatives in blood of patients with a hereditary autoinflammatory disorder, familial Mediterranean fever (FMF, and in patients with peptic ulceration (PU resulting from Helicobacter pylori infection. Discriminant function analysis of a data matrix consisting of 94 cases as statistical units (37 FMF patients, 14 PU patients, and 43 healthy controls and the concentration of 35 microbial products in the blood as statistical variables revealed a high accuracy of the proposed model (all cases were correctly classified. This suggests that the profile of microbial products and metabolites in the human metabolome is specific for a given disease and may potentially serve as a biomarker for disease.

  2. Metabolomic profiles of myocardial ischemia under treatment with salvianolic acid B

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    Lu Yonghai

    2012-03-01

    Full Text Available Abstract Background Radix Salvia miltiorrhiza (Danshen has been used as a principal herb in treating cardiovascular diseases in Chinese medicine. Salvianolic acid B (SA-B, a water-soluble active component of Danshen, was found to have anti-myocardial ischemia (anti-MI effect. This study aims to investigate mechanisms of SA-B on MI. Methods Five conventional Western medicines (isosorbide dinitrate, verapamil, propranolol, captopril and trimethazine with different mechanisms for treating cardiovascular diseases were selected as positive references to compare with SA-B in changing of the metabolomic profiles in MI rats under treatment. Potential mechanisms of SA-B were further investigated in H9C2 cell line. Results The metabolomic profiles between SA-B- and propranolol-treated MI rats were similar, since there was a big overlap between the two groups in the PLS-DA score plot. Finally, it was demonstrated that SA-B exhibited a protective effect on MI mainly by decreasing the concentration of cyclic adenosine monophosphate (cAMP and Ca2+ and inhibiting protein kinase A (PKA. Conclusion SA-B and propanolol exhibited similar metabolomic profiles, indicating that the two drugs might have a similar mechanism.

  3. From models to crop species: caveats and solutions for translational metabolomics

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    Takayuki eTohge

    2011-10-01

    Full Text Available Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa that illustrate how such dangers can be detected and circumvented.

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

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    Amanda L. Peterson

    2016-09-01

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

  5. Metabolomics: An Essential Tool to Understand the Function of Peroxisome Proliferator–Activated Receptor Alpha

    Science.gov (United States)

    Montanez, Jessica E.; Peters, Jeffrey M.; Correll, Jared B.; Gonzalez, Frank J.; Patterson, Andrew D.

    2013-01-01

    The peroxisome proliferator–activated receptor (PPAR) family of nuclear hormone transcription factors (PPARα, PPARβ/δ, and PPARγ) is regulated by a wide array of ligands including natural and synthetic chemicals. PPARs have important roles in control of energy metabolism and are known to influence inflammation, differentiation, carcinogenesis, and chemical toxicity. As such, PPARs have been targeted as therapy for common disorders such as cancer, metabolic syndrome, obesity, and diabetes. The recent application of metabolomics, or the global, unbiased measurement of small molecules found in biofluids, or extracts from cells, tissues, or organisms, has advanced our understanding of the varied and important roles that the PPARs have in normal physiology as well as in pathophysiological processes. Continued development and refinement of analytical platforms, and the application of new bioinformatics strategies, have accelerated the widespread use of metabolomics and have allowed further integration of small molecules into systems biology. Recent studies using metabolomics to understand PPARα function, as well as to identify PPARα biomarkers associated with drug efficacy/toxicity and drug-induced liver injury, will be discussed. PMID:23197196

  6. Metabolomics reveals variation and correlation among different tissues of olive (Olea europaea L.).

    Science.gov (United States)

    Guodong, Rao; Xiaoxia, Liu; Weiwei, Zha; Wenjun, Wu; Jianguo, Zhang

    2017-09-15

    Metabolites in olives are associated with nutritional value and physiological properties. However, comprehensive information regarding the olive metabolome is limited. In this study, we identified 226 metabolites from three different tissues of olive using a non-targeted metabolomic profiling approach, of which 76 named metabolites were confirmed. Further statistical analysis revealed that these 76 metabolites covered different types of primary metabolism and some of the secondary metabolism pathways. One-way analysis of variance (ANOVA) statistical assay was performed to calculate the variations within the detected metabolites, and levels of 65 metabolites were differentially expressed in different samples. Hierarchical cluster analysis (HCA) dendrograms showed variations among different tissues that were similar to the metabolite profiles observed in new leaves and fruit. Additionally, 5776 metabolite-metabolite correlations were detected by a Pearson correlation coefficient approach. Screening of the calculated correlations revealed 3136, 3025, and 5184 were determined to metabolites and had significant correlations in three different combinations, respectively. This work provides the first comprehensive metabolomic of olive, which will provide new insights into understanding the olive metabolism, and potentially help advance studies in olive metabolic engineering. © 2017. Published by The Company of Biologists Ltd.

  7. Experimental Chagas disease-induced perturbations of the fecal microbiome and metabolome.

    Science.gov (United States)

    McCall, Laura-Isobel; Tripathi, Anupriya; Vargas, Fernando; Knight, Rob; Dorrestein, Pieter C; Siqueira-Neto, Jair L

    2018-03-12

    Trypanosoma cruzi parasites are the causative agents of Chagas disease. These parasites infect cardiac and gastrointestinal tissues, leading to local inflammation and tissue damage. Digestive Chagas disease is associated with perturbations in food absorption, intestinal traffic and defecation. However, the impact of T. cruzi infection on the gut microbiota and metabolome have yet to be characterized. In this study, we applied mass spectrometry-based metabolomics and 16S rRNA sequencing to profile infection-associated alterations in fecal bacterial composition and fecal metabolome through the acute-stage and into the chronic stage of infection, in a murine model of Chagas disease. We observed joint microbial and chemical perturbations associated with T. cruzi infection. These included alterations in conjugated linoleic acid (CLA) derivatives and in specific members of families Ruminococcaceae and Lachnospiraceae, as well as alterations in secondary bile acids and members of order Clostridiales. These results highlight the importance of multi-'omics' and poly-microbial studies in understanding parasitic diseases in general, and Chagas disease in particular.

  8. First-Trimester Serum Acylcarnitine Levels to Predict Preeclampsia: A Metabolomics Approach

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    Maria P. H. Koster

    2015-01-01

    Full Text Available Objective. To expand the search for preeclampsia (PE metabolomics biomarkers through the analysis of acylcarnitines in first-trimester maternal serum. Methods. This was a nested case-control study using serum from pregnant women, drawn between 8 and 14 weeks of gestational age. Metabolites were measured using an UPLC-MS/MS based method. Concentrations were compared between controls (n=500 and early-onset- (EO- PE (n=68 or late-onset- (LO- PE (n=99 women. Metabolites with a false discovery rate <10% for both EO-PE and LO-PE were selected and added to prediction models based on maternal characteristics (MC, mean arterial pressure (MAP, and previously established biomarkers (PAPPA, PLGF, and taurine. Results. Twelve metabolites were significantly different between EO-PE women and controls, with effect levels between −18% and 29%. For LO-PE, 11 metabolites were significantly different with effect sizes between −8% and 24%. Nine metabolites were significantly different for both comparisons. The best prediction model for EO-PE consisted of MC, MAP, PAPPA, PLGF, taurine, and stearoylcarnitine (AUC = 0.784. The best prediction model for LO-PE consisted of MC, MAP, PAPPA, PLGF, and stearoylcarnitine (AUC = 0.700. Conclusion. This study identified stearoylcarnitine as a novel metabolomics biomarker for EO-PE and LO-PE. Nevertheless, metabolomics-based assays for predicting PE are not yet suitable for clinical implementation.

  9. Enzymatically Modified Starch Ameliorates Postprandial Serum Triglycerides and Lipid Metabolome in Growing Pigs.

    Science.gov (United States)

    Metzler-Zebeli, Barbara U; Eberspächer, Eva; Grüll, Dietmar; Kowalczyk, Lidia; Molnar, Timea; Zebeli, Qendrim

    2015-01-01

    Developing host digestion-resistant starches to promote human health is of great research interest. Chemically modified starches (CMS) are widely used in processed foods and although the modification of the starch molecule allows specific reduction in digestibility, the metabolic effects of CMS have been less well described. This short-term study evaluated the impact of enzymatically modified starch (EMS) on fasting and postprandial profiles of blood glucose, insulin and lipids, and serum metabolome in growing pigs. Eight jugular-vein catheterized pigs (initial body weight, 37.4 kg; 4 months of age) were fed 2 diets containing 72% purified starch (EMS or waxy corn starch (control)) in a cross-over design for 7 days. On day 8, an 8-hour meal tolerance test (MTT) was performed with serial blood samplings. Besides biochemical analysis, serum was analysed for 201 metabolites through targeted mass spectrometry-based metabolomic approaches. Pigs fed the EMS diet showed increased (Ppostprandial serum triglycerides with EMS versus control diet (Ppostprandial raise in serum lipids and suggested constant alteration in the synthesis or breakdown of sphingolipids and phospholipids which might be a health benefit of EMS consumption. Because serum insulin was not lowered, more research is warranted to reveal possible underlying mechanisms behind the observed changes in the profile of serum lipid metabolome in response to EMS consumption.

  10. Biogeography shaped the metabolome of the genus Espeletia: a phytochemical perspective on an Andean adaptive radiation.

    Science.gov (United States)

    Padilla-González, Guillermo F; Diazgranados, Mauricio; Da Costa, Fernando B

    2017-08-18

    The páramo ecosystem has the highest rate of diversification across plant lineages on earth, of which the genus Espeletia (Asteraceae) is a prime example. The current distribution and molecular phylogeny of Espeletia suggest the influence of Andean geography and past climatic fluctuations on the diversification of this genus. However, molecular markers have failed to reveal subtle biogeographical trends in Espeletia diversification, and metabolomic evidence for allopatric segregation in plants has never been reported. Here, we present for the first time a metabolomics approach based on liquid chromatography-mass spectrometry for revealing subtle biogeographical trends in Espeletia diversification. We demonstrate that Espeletia lineages can be distinguished by means of different metabolic fingerprints correlated to the country of origin on a global scale and to the páramo massif on a regional scale. Distinctive patterns in the accumulation of secondary metabolites according to the main diversification centers of Espeletia are also identified and a comprehensive phytochemical characterization is reported. These findings demonstrate that a variation in the metabolic fingerprints of Espeletia lineages followed the biogeography of this genus, suggesting that our untargeted metabolomics approach can be potentially used as a model to understand the biogeographic history of additional plant groups in the páramo ecosystem.

  11. Mapping an atlas of tissue-specific Drosophila melanogaster metabolomes by high resolution mass spectrometry.

    Directory of Open Access Journals (Sweden)

    Venkateswara R Chintapalli

    Full Text Available Metabolomics can provide exciting insights into organismal function, but most work on simple models has focussed on the whole organism metabolome, so missing the contributions of individual tissues. Comprehensive metabolite profiles for ten tissues from adult Drosophila melanogaster were obtained here by two chromatographic methods, a hydrophilic interaction (HILIC method for polar metabolites and a lipid profiling method also based on HILIC, in combination with an Orbitrap Exactive instrument. Two hundred and forty two polar metabolites were putatively identified in the various tissues, and 251 lipids were observed in positive ion mode and 61 in negative ion mode. Although many metabolites were detected in all tissues, every tissue showed characteristically abundant metabolites which could be rationalised against specific tissue functions. For example, the cuticle contained high levels of glutathione, reflecting a role in oxidative defence; the alimentary canal (like vertebrate gut had high levels of acylcarnitines for fatty acid metabolism, and the head contained high levels of ether lipids. The male accessory gland uniquely contained decarboxylated S-adenosylmethionine. These data thus both provide valuable insights into tissue function, and a reference baseline, compatible with the FlyAtlas.org transcriptomic resource, for further metabolomic analysis of this important model organism, for example in the modelling of human inborn errors of metabolism, aging or metabolic imbalances such as diabetes.

  12. Metabolomics reveals variation and correlation among different tissues of olive (Olea europaea L.

    Directory of Open Access Journals (Sweden)

    Rao Guodong

    2017-09-01

    Full Text Available Metabolites in olives are associated with nutritional value and physiological properties. However, comprehensive information regarding the olive metabolome is limited. In this study, we identified 226 metabolites from three different tissues of olive using a non-targeted metabolomic profiling approach, of which 76 named metabolites were confirmed. Further statistical analysis revealed that these 76 metabolites covered different types of primary metabolism and some of the secondary metabolism pathways. One-way analysis of variance (ANOVA statistical assay was performed to calculate the variations within the detected metabolites, and levels of 65 metabolites were differentially expressed in different samples. Hierarchical cluster analysis (HCA dendrograms showed variations among different tissues that were similar to the metabolite profiles observed in new leaves and fruit. Additionally, 5776 metabolite-metabolite correlations were detected by a Pearson correlation coefficient approach. Screening of the calculated correlations revealed 3136, 3025, and 5184 were determined to metabolites and had significant correlations in three different combinations, respectively. This work provides the first comprehensive metabolomic of olive, which will provide new insights into understanding the olive metabolism, and potentially help advance studies in olive metabolic engineering.

  13. Metabolomics guided pathway analysis reveals link between cancer metastasis, cholesterol sulfate, and phospholipids

    Directory of Open Access Journals (Sweden)

    Caroline H. Johnson

    2017-10-01

    Full Text Available Abstract Background Cancer cells that enter the metastatic cascade require traits that allow them to survive within the circulation and colonize distant organ sites. As disseminating cancer cells adapt to their changing microenvironments, they also modify their metabolism and metabolite production. Methods A mouse xenograft model of spontaneous tumor metastasis was used to determine the metabolic rewiring that occurs between primary cancers and their metastases. An “autonomous” mass spectrometry-based untargeted metabolomic workflow with integrative metabolic pathway analysis revealed a number of differentially regulated metabolites in primary mammary fat pad (MFP tumors compared to microdissected paired lung metastases. The study was further extended to analyze metabolites in paired normal tissues which determined the potential influence of metabolites from the microenvironment. Results Metabolomic analysis revealed that multiple metabolites were increased in metastases, including cholesterol sulfate and phospholipids (phosphatidylglycerols and phosphatidylethanolamine. Metabolite analysis of normal lung tissue in the mouse model also revealed increased levels of these metabolites compared to tissues from normal MFP and primary MFP tumors, indicating potential extracellular uptake by cancer cells in lung metastases. These results indicate a potential functional importance of cholesterol sulfate and phospholipids in propagating metastasis. In addition, metabolites involved in DNA/RNA synthesis and the TCA cycle were decreased in lung metastases compared to primary MFP tumors. Conclusions Using an integrated metabolomic workflow, this study identified a link between cholesterol sulfate and phospholipids, metabolic characteristics of the metastatic niche, and the capacity of tumor cells to colonize distant sites.

  14. Integration of Metabolomics and Transcriptomics Reveals Major Metabolic Pathways and Potential Biomarker Involved in Prostate Cancer.

    Science.gov (United States)

    Ren, Shancheng; Shao, Yaping; Zhao, Xinjie; Hong, Christopher S; Wang, Fubo; Lu, Xin; Li, Jia; Ye, Guozhu; Yan, Min; Zhuang, Zhengping; Xu, Chuanliang; Xu, Guowang; Sun, Yinghao

    2016-01-01

    Prostate cancer is a highly prevalent tumor affecting millions of men worldwide, but poor understanding of its pathogenesis has limited effective clinical management of patients. In addition to transcriptional profiling or transcriptomics, metabolomics is being increasingly utilized to discover key molecular changes underlying tumorigenesis. In this study, we integrated transcriptomics and metabolomics to analyze 25 paired human prostate cancer tissues and adjacent noncancerous tissues, followed by further validation of our findings in an additional cohort of 51 prostate cancer patients and 16 benign prostatic hyperplasia patients. We found several altered pathways aberrantly expressed at both metabolic and transcriptional levels, including cysteine and methionine metabolism, nicotinamide adenine dinucleotide metabolism, and hexosamine biosynthesis. Additionally, the metabolite sphingosine demonstrated high specificity and sensitivity for distinguishing prostate cancer from benign prostatic hyperplasia, particularly for patients with low prostate specific antigen level (0-10 ng/ml). We also found impaired sphingosine-1-phosphate receptor 2 signaling, downstream of sphingosine, representing a loss of tumor suppressor gene and a potential key oncogenic pathway for therapeutic targeting. By integrating metabolomics and transcriptomics, we have provided both a broad picture of the molecular perturbations underlying prostate cancer and a preliminary study of a novel metabolic signature, which may help to discriminate prostate cancer from normal tissue and benign prostatic hyperplasia. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  15. Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

    Science.gov (United States)

    Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota

    2016-01-01

    The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

  16. Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

    Science.gov (United States)

    Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

    2016-01-01

    Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

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

    Science.gov (United States)

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

    2014-01-01

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

  18. Metabolomics of cancer cell cultures to assess the effects of dietary phytochemicals.

    Science.gov (United States)

    Brasili, Elisa; Filho, Valdir Cechinel

    2017-05-03

    Cancer is a multi-factorial disease and is a major cause of morbidity and mortality worldwide. Dietary phytochemicals have been used for the treatment of cancer throughout history due to their safety, low toxicity, and general availability. Several studies have been performed to elucidate the effects of dietary phytochemicals on cancer metabolism, and many molecular targets of phytochemicals have been discovered. In spite of remarkable progress, their effects on cancer metabolism have not yet been fully clarified. Recent developments in metabolomics allowed to probe much further the metabolism of cancer, highlighting altered metabolic pathways and offering a new powerful tool to investigate cancer disease. In this review, we discuss the main metabolic alterations of cancer cells and the potentiality of phytochemicals as promising modulators of cancer metabolism. We will focus on the application of nuclear magnetic resonance-based metabolomics on breast and hepatocellular cancer cell lines to evaluate the impact of curcumin and resveratrol on cancer metabolome with the aim to demonstrate the premise of this approach to provide useful information for a better understanding of impact of diet components on cancer disease.

  19. Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

    Science.gov (United States)

    Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

    2018-04-01

    Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

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

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

    2013-11-13

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

  1. Metabolomic Effects of Xylitol and Fluoride on Plaque Biofilm in Vivo

    Science.gov (United States)

    Takahashi, N.; Washio, J.

    2011-01-01

    Dental caries is initiated by demineralization of the tooth surface through acid production from sugar by plaque biofilm. Fluoride and xylitol have been used worldwide as caries-preventive reagents, based on in vitro-proven inhibitory mechanisms on bacterial acid production. We attempted to confirm the inhibitory mechanisms of fluoride and xylitol in vivo by performing metabolome analysis on the central carbon metabolism in supragingival plaque using the combination of capillary electrophoresis and a time-of-flight mass spectrometer. Fluoride (225 and 900 ppm F−) inhibited lactate production from 10% glucose by 34% and 46%, respectively, along with the increase in 3-phosphoglycerate and the decrease in phosphoenolpyruvate in the EMP pathway in supragingival plaque. These results confirmed that fluoride inhibited bacterial enolase in the EMP pathway and subsequently repressed acid production in vivo. In contrast, 10% xylitol had no effect on acid production and the metabolome profile in supragingival plaque, although xylitol 5-phosphate was produced. These results suggest that xylitol is not an inhibitor of plaque acid production but rather a non-fermentative sugar alcohol. Metabolome analyses of plaque biofilm can be applied for monitoring the efficacy of dietary components and medicines for plaque biofilm, leading to the development of effective plaque control. PMID:21940519

  2. Metabolomic Profiles of a Midge (Procladius villosimanus, Kieffer Are Associated with Sediment Contamination in Urban Wetlands

    Directory of Open Access Journals (Sweden)

    Katherine J. Jeppe

    2017-12-01

    Full Text Available Metabolomic techniques are powerful tools for investigating organism-environment interactions. Metabolite profiles have the potential to identify exposure or toxicity before populations are disrupted and can provide useful information for environmental assessment. However, under complex environmental scenarios, metabolomic responses to exposure can be distorted by background and/or organismal variation. In the current study, we use LC-MS (liquid chromatography-mass spectrometry and GC-MS (gas chromatography-mass spectrometry to measure metabolites of the midge Procladius villosimanus inhabiting 21 urban wetlands. These metabolites were tested against common sediment contaminants using random forest models and metabolite enrichment analysis. Sediment contaminant concentrations in the field correlated with several P. villosimanus metabolites despite natural environmental and organismal variation. Furthermore, enrichment analysis indicated that metabolite sets implicated in stress responses were enriched, pointing to specific cellular functions affected by exposure. Methionine metabolism, sugar metabolism and glycerolipid metabolism associated with total petroleum hydrocarbon and metal concentrations, while mitochondrial electron transport and urea cycle sets associated only with bifenthrin. These results demonstrate the potential for metabolomics approaches to provide useful information in field-based environmental assessments.

  3. Salivary and fecal microbiota and metabolome of celiac children under gluten-free diet.

    Science.gov (United States)

    De Angelis, Maria; Vannini, Lucia; Di Cagno, Raffaella; Cavallo, Noemi; Minervini, Fabio; Francavilla, Ruggiero; Ercolini, Danilo; Gobbetti, Marco

    2016-12-19

    Celiac disease (CD) is an inflammatory autoimmune disorder resulting from the combination of genetic predisposition and gluten ingestion. A life-long gluten free diet (GFD) is the only therapeutic approach. Dysbiosis, which can precede the CD pathogenesis and/or persist when subjects are on GFD, is reviewed and discussed. Salivary microbiota and metabolome differed between healthy and celiac children treated under GFD (T-CD) for at least two years. The type of GFD (African- vs Italian-style) modified the microbiota and metabolome of Saharawi T-CD children. Different studies showed bacterial dysbiosis at duodenal and/or fecal level of patients with active untreated CD (U-CD) and T-CD compared to healthy subjects. The ratio of protective anti-inflammatory bacteria such as Lactobacillus-Bifidobacterium to potentially harmful Bacteroides-Enterobacteriaceae was the lowest in U-CD and T-CD children. In agreement with dysbiosis, serum, fecal and urinary metabolome from U-CD and T-CD patients showed altered levels of free amino acids and volatile organic compounds. However, consensus across studies defining specific bacteria and metabolites in U-CD or T-CD patients is still lacking. Future research efforts are required to determine the relationships between CD and oral and intestinal microbiotas to improve the composition of GFD for restoring the gut dysbiosis as a preventative or therapeutic approach for CD. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Application of Metabolomics to Quality Control of Natural Product Derived Medicines.

    Science.gov (United States)

    Lee, Kyung-Min; Jeon, Jun-Yeong; Lee, Byeong-Ju; Lee, Hwanhui; Choi, Hyung-Kyoon

    2017-11-01

    Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. Veregen ® (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

  5. Optimal preprocessing of serum and urine metabolomic data fusion for staging prostate cancer through design of experiment.

    Science.gov (United States)

    Zheng, Hong; Cai, Aimin; Zhou, Qi; Xu, Pengtao; Zhao, Liangcai; Li, Chen; Dong, Baijun; Gao, Hongchang

    2017-10-23

    Accurate classification of cancer stages will achieve precision treatment for cancer. Metabolomics presents biological phenotypes at the metabolite level and holds a great potential for cancer classification. Since metabolomic data can be obtained from different samples or analytical techniques, data fusion has been applied to improve classification accuracy. Data preprocessing is an essential step during metabolomic data analysis. Therefore, we developed an innovative optimization method to select a proper data preprocessing strategy for metabolomic data fusion using a design of experiment approach for improving the classification of prostate cancer (PCa) stages. In this study, urine and serum samples were collected from participants at five phases of PCa and analyzed using a 1 H NMR-based metabolomic approach. Partial least squares-discriminant analysis (PLS-DA) was used as a classification model and its performance was assessed by goodness of fit (R 2 ) and predictive ability (Q 2 ). Results show that data preprocessing significantly affect classification performance and depends on data properties. Using the fused metabolomic data from urine and serum, PLS-DA model with the optimal data preprocessing (R 2  = 0.729, Q 2  = 0.504, P < 0.0001) can effectively improve model performance and achieve a better classification result for PCa stages as compared with that without data preprocessing (R 2  = 0.139, Q 2  = 0.006, P = 0.450). Therefore, we propose that metabolomic data fusion integrated with an optimal data preprocessing strategy can significantly improve the classification of cancer stages for precision treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2018-03-02

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

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

    Science.gov (United States)

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

    2018-02-22

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

  8. mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data.

    Science.gov (United States)

    Doerfler, Hannes; Sun, Xiaoliang; Wang, Lei; Engelmeier, Doris; Lyon, David; Weckwerth, Wolfram

    2014-01-01

    The metabolome is a highly dynamic entity and the final readout of the genotype x environment x phenotype (GxExP) relationship of an organism. Monitoring metabolite dynamics over time thus theoretically encrypts the whole range of possible chemical and biochemical transformations of small molecules involved in metabolism. The bottleneck is, however, the sheer number of unidentified structures in these samples. This represents the next challenge for metabolomics technology and is comparable with genome sequencing 30 years ago. At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated m/z feature extraction and subsequent structure or pathway assignment. Here we provide an automated pathway inference strategy comprising measurements of metabolome time series using LC- MS with high resolution and high mass accuracy. An algorithm was developed, called mzGroupAnalyzer, to automatically explore the metabolome for the detection of metabolite transformations caused by biochemical or chemical modifications. Pathways are extracted directly from the data and putative novel structures can be identified. The detected m/z features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. This method was applied to Arabidopsis thaliana treated simultaneously with cold and high light. Due to a protective antioxidant response the plants turn from green to purple color via the accumulation of flavonoid structures. The detection of potential biochemical pathways resulted in 15 putatively new compounds involved in the flavonoid-pathway. These compounds were further validated by product ion spectra from the same data. The mzGroupAnalyzer is implemented in the graphical user interface (GUI) of the metabolomics toolbox COVAIN (Sun & Weckwerth, 2012, Metabolomics 8: 81

  9. mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data.

    Directory of Open Access Journals (Sweden)

    Hannes Doerfler

    Full Text Available The metabolome is a highly dynamic entity and the final readout of the genotype x environment x phenotype (GxExP relationship of an organism. Monitoring metabolite dynamics over time thus theoretically encrypts the whole range of possible chemical and biochemical transformations of small molecules involved in metabolism. The bottleneck is, however, the sheer number of unidentified structures in these samples. This represents the next challenge for metabolomics technology and is comparable with genome sequencing 30 years ago. At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated m/z feature extraction and subsequent structure or pathway assignment. Here we provide an automated pathway inference strategy comprising measurements of metabolome time series using LC- MS with high resolution and high mass accuracy. An algorithm was developed, called mzGroupAnalyzer, to automatically explore the metabolome for the detection of metabolite transformations caused by biochemical or chemical modifications. Pathways are extracted directly from the data and putative novel structures can be identified. The detected m/z features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. This method was applied to Arabidopsis thaliana treated simultaneously with cold and high light. Due to a protective antioxidant response the plants turn from green to purple color via the accumulation of flavonoid structures. The detection of potential biochemical pathways resulted in 15 putatively new compounds involved in the flavonoid-pathway. These compounds were further validated by product ion spectra from the same data. The mzGroupAnalyzer is implemented in the graphical user interface (GUI of the metabolomics toolbox COVAIN (Sun & Weckwerth, 2012

  10. The hepatic and skeletal muscle ovine metabolomes as affected by weight loss: a study in three sheep breeds using NMR-metabolomics

    Science.gov (United States)

    Palma, Mariana; Scanlon, Tim; Kilminster, Tanya; Milton, John; Oldham, Chris; Greeff, Johan; Matzapetakis, Manolis; Almeida, André M.

    2016-01-01

    Sheep are a valuable resource for meat and wool production. During the dry summer, pastures are scarce and animals face Seasonal Weight Loss (SWL), which decreases production yields. The study of breeds tolerant to SWL is important to understand the physiological mechanisms of tolerance to nutritional scarcity, and define breeding strategies. Merino, Damara and Dorper sheep breeds have been described as having different levels of tolerance to SWL. In this work, we assess their liver and muscle metabolomes, and compare the responses to feed restriction. Ram lambs from each breed were divided into growth and feed restricted groups, over 42 days. Tissue metabolomes were assessed by 1H-NMR. The Dorper restricted group showed few changes in both tissues, suggesting higher tolerance to nutritional scarcity. The Merinos exhibited more differences between treatment groups. Major differences were related to fat and protein mobilization, and antioxidant activity. Between the Damara groups, the main differences were observed in amino acid composition in muscle and in energy-related pathways in the liver. Integration of present results and previous data on the same animals support the hypothesis that, Dorper and Damara breeds are more tolerant to SWL conditions and thus, more suitable breeds for harsh environmental conditions. PMID:27966615

  11. Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

    Science.gov (United States)

    Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

    2017-06-21

    Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction

  12. Metabolomic analysis of the saliva of Japanese patients with oral squamous cell carcinoma.

    Science.gov (United States)

    Ohshima, Mitsuyoshi; Sugahara, Keisuke; Kasahara, Kiyohiro; Katakura, Akira

    2017-05-01

    The aim of the present study was to characterize the metabolic systems in Japanese patients with oral squamous cell carcinoma (OSCC) using capillary electrophoresis-mass spectrometry (CE-MS) metabolome analysis of saliva samples. A previous study showed variations among ethnicities and tumor sites in the saliva metabolome of patients with OSCC using CE-MS. In the present study, saliva was obtained from 22 Japanese patients with OSCC and from 21 healthy controls who visited the Department of Dentistry, Oral and Maxillofacial Surgery, Tokyo Dental Collage Ichikawa General Hospital, Tokyo, Japan, and all samples were subject to comprehensive quantitative metabolome analysis using CE-MS. A total of 499 metabolites were detected as CE-MS peaks in the saliva tested from the two groups. A total of 25 metabolites were revealed as potential markers to discriminate between patients with OSCC and healthy controls: Choline, p-hydroxyphenylacetic acid, and 2-hydroxy-4-methylvaleric acid (P<0.001); valine, 3-phenyllactic acid, leucine, hexanoic acid, octanoic acid, terephthalic acid, γ-butyrobetaine, and 3-(4-hydroxyphenyl)propionic acid (P<0.01); and isoleucine, tryptophan, 3-phenylpropionic acid, 2-hydroxyvaleric acid, butyric acid, cadaverine, 2-oxoisovaleric acid, N6,N6,N6-trimethyllysine, taurine, glycolic acid, 3-hydroxybutyric acid, heptanoic acid, alanine, and urea (P<0.05, according to the Wilcoxon rank sum test). A previous study by Sugimoto and co-workers detected 24 discriminatory metabolites, 7 of which (taurine, valine, leucine, isoleucine, choline, cadaverine, and tryptophan) were also detected in the present study. In the present study, however, choline, metabolites in the branched chain amino acids (BCAA) cycle, urea, and 3-hydroxybutyric acid were also characterized. Choline and metabolites of the BCAA cycle have previously been reported in OSCC using metabolome analysis. To the best of our knowledge, no previous reports have identified urea and 3

  13. Implications of genotypic differences in the generation of a urinary metabolomics radiation signature

    Energy Technology Data Exchange (ETDEWEB)

    Laiakis, Evagelia C., E-mail: ecl28@georgetown.edu [Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington DC (United States); Pannkuk, Evan L. [Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington DC (United States); Diaz-Rubio, Maria Elena [Pediatrics, Division of Developmental Nutrition, University of Arkansas for Medical Sciences, Little Rock, AR (United States); Wang, Yi-Wen [Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington DC (United States); Mak, Tytus D. [Mass Spectrometry Data Center, National Institute of Standards and Technology (NIST), Gaithersburg MD (United States); Simbulan-Rosenthal, Cynthia M. [Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington DC (United States); Brenner, David J. [Columbia University, New York, NY (United States); Fornace, Albert J. [Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington DC (United States); Lombardi Comprehensive Cancer Center, Georgetown University, Washington DC (United States); Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 22254 (Saudi Arabia)

    2016-06-15

    Highlights: • Metabolomics can rapidly assess the collective small molecule content in biofluids. • Previous studies focused on urine of wild type mice and now extending to radiosensitive mice. • The Parp1{sup −/−} mice were utilized as a model radiosensitive mouse line. • Time-dependent perturbations are evident in different metabolic pathways. • Metabolomics can be used to dissect the effects of genotoxic agents on metabolism. - Abstract: The increased threat of radiological terrorism and accidental nuclear exposures, together with increased usage of radiation-based medical procedures, has made necessary the development of minimally invasive methods for rapid identification of exposed individuals. Genetically predisposed radiosensitive individuals comprise a significant number of the population and require specialized attention and treatments after such events. Metabolomics, the assessment of the collective small molecule content in a given biofluid or tissue, has proven effective in the rapid identification of radiation biomarkers and metabolic perturbations. To investigate how the genotypic background may alter the ionizing radiation (IR) signature, we analyzed urine from Parp1{sup −/−} mice, as a model radiosensitive genotype, exposed to IR by utilizing the analytical power of liquid chromatography coupled with mass spectrometry (LC–MS), as urine has been thoroughly investigated in wild type (WT) mice in previous studies from our laboratory. Samples were collected at days one and three after irradiation, time points that are important for the early and efficient triage of exposed individuals. Time-dependent perturbations in metabolites were observed in the tricarboxylic acid pathway (TCA). Other differentially excreted metabolites included amino acids and metabolites associated with dysregulation of energy metabolism pathways. Time-dependent apoptotic pathway activation between WT and mutant mice following IR exposure may explain the

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

    Directory of Open Access Journals (Sweden)

    Evagelia C Laiakis

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

  15. Impact of anesthesia and euthanasia on metabolomics of mammalian tissues: studies in a C57BL/6J mouse model.

    Science.gov (United States)

    Overmyer, Katherine A; Thonusin, Chanisa; Qi, Nathan R; Burant, Charles F; Evans, Charles R

    2015-01-01

    A critical application of metabolomics is the evaluation of tissues, which are often the primary sites of metabolic dysregulation in disease. Laboratory rodents have been widely used for metabolomics studies involving tissues due to their facile handing, genetic manipulability and similarity to most aspects of human metabolism. However, the necessary step of administration of anesthesia in preparation for tissue sampling is not often given careful consideration, in spite of its potential for causing alterations in the metabolome. We examined, for the first time using untargeted and targeted metabolomics, the effect of several commonly used methods of anesthesia and euthanasia for collection of skeletal muscle, liver, heart, adipose and serum of C57BL/6J mice. The data revealed dramatic, tissue-specific impacts of tissue collection strategy. Among many differences observed, post-euthanasia samples showed elevated levels of glucose 6-phosphate and other glycolytic intermediates in skeletal muscle. In heart and liver, multiple nucleotide and purine degradation metabolites accumulated in tissues of euthanized compared to anesthetized animals. Adipose tissue was comparatively less affected by collection strategy, although accumulation of lactate and succinate in euthanized animals was observed in all tissues. Among methods of tissue collection performed pre-euthanasia, ketamine showed more variability compared to isoflurane and pentobarbital. Isoflurane induced elevated liver aspartate but allowed more rapid initiation of tissue collection. Based on these findings, we present a more optimal collection strategy mammalian tissues and recommend that rodent tissues intended for metabolomics studies be collected under anesthesia rather than post-euthanasia.

  16. Impact of Anesthesia and Euthanasia on Metabolomics of Mammalian Tissues: Studies in a C57BL/6J Mouse Model

    Science.gov (United States)

    Overmyer, Katherine A.; Thonusin, Chanisa; Qi, Nathan R.; Burant, Charles F.; Evans, Charles R.

    2015-01-01

    A critical application of metabolomics is the evaluation of tissues, which are often the primary sites of metabolic dysregulation in disease. Laboratory rodents have been widely used for metabolomics studies involving tissues due to their facile handing, genetic manipulability and similarity to most aspects of human metabolism. However, the necessary step of administration of anesthesia in preparation for tissue sampling is not often given careful consideration, in spite of its potential for causing alterations in the metabolome. We examined, for the first time using untargeted and targeted metabolomics, the effect of several commonly used methods of anesthesia and euthanasia for collection of skeletal muscle, liver, heart, adipose and serum of C57BL/6J mice. The data revealed dramatic, tissue-specific impacts of tissue collection strategy. Among many differences observed, post-euthanasia samples showed elevated levels of glucose 6-phosphate and other glycolytic intermediates in skeletal muscle. In heart and liver, multiple nucleotide and purine degradation metabolites accumulated in tissues of euthanized compared to anesthetized animals. Adipose tissue was comparatively less affected by collection strategy, although accumulation of lactate and succinate in euthanized animals was observed in all tissues. Among methods of tissue collection performed pre-euthanasia, ketamine showed more variability compared to isoflurane and pentobarbital. Isoflurane induced elevated liver aspartate but allowed more rapid initiation of tissue collection. Based on these findings, we present a more optimal collection strategy mammalian tissues and recommend that rodent tissues intended for metabolomics studies be collected under anesthesia rather than post-euthanasia. PMID:25658945

  17. Disruption of TCA Cycle and Glutamate Metabolism Identified by Metabolomics in an In Vitro Model of Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Veyrat-Durebex, Charlotte; Corcia, Philippe; Piver, Eric; Devos, David; Dangoumau, Audrey; Gouel, Flore; Vourc'h, Patrick; Emond, Patrick; Laumonnier, Frédéric; Nadal-Desbarats, Lydie; Gordon, Paul H; Andres, Christian R; Blasco, Hélène

    2016-12-01

    This study aims to develop a cellular metabolomics model that reproduces the pathophysiological conditions found in amyotrophic lateral sclerosis in order to improve knowledge of disease physiology. We used a co-culture model combining the motor neuron-like cell line NSC-34 and the astrocyte clone C8-D1A, with each over-expressing wild-type or G93C mutant human SOD1, to examine amyotrophic lateral sclerosis (ALS) physiology. We focused on the effects of mutant human SOD1 as well as oxidative stress induced by menadione on intracellular metabolism using a metabolomics approach through gas chromatography coupled with mass spectrometry (GC-MS) analysis. Preliminary non-supervised analysis by Principal Component Analysis (PCA) revealed that cell type, genetic environment, and time of culture influenced the metabolomics profiles. Supervised analysis using orthogonal partial least squares discriminant analysis (OPLS-DA) on data from intracellular metabolomics profiles of SOD1 G93C co-cultures produced metabolites involved in glutamate metabolism and the tricarboxylic acid cycle (TCA) cycle. This study revealed the feasibility of using a metabolomics approach in a cellular model of ALS. We identified potential disruption of the TCA cycle and glutamate metabolism under oxidative stress, which is consistent with prior research in the disease. Analysis of metabolic alterations in an in vitro model is a novel approach to investigation of disease physiology.

  18. Day-3 embryo metabolomics in the spent culture media is altered in obese women undergoing in vitro fertilization.

    Science.gov (United States)

    Bellver, José; De Los Santos, María J; Alamá, Pilar; Castelló, Damià; Privitera, Laura; Galliano, Daniela; Labarta, Elena; Vidal, Carmen; Pellicer, Antonio; Domínguez, Francisco

    2015-06-01

    To determine whether the global metabolomic profile of the spent culture media (SCM) of day-3 embryos is different in obese and normoweight women undergoing in vitro fertilization (IVF). Prospective cohort analysis. IVF clinic. Twenty-eight young, nonsmoking women with normoweight, nonsmoking male partners with mild/normal sperm factors undergoing a first IVF attempt for idiopathic infertility, tubal factor infertility, or failed ovulation induction: obese ovulatory women (n = 12); obese women with polycystic ovary syndrome (PCOS; n = 4); normoweight ovulatory women (n = 12). Fifty μl of SCM collected from two day-3 embryos of each cohort. Metabolomic profiling via ultrahigh performance liquid chromatography coupled to mass spectrometry of SCM from a total of 56 embryos. The untargeted metabolomic profile was different in obese and normoweight women. Partial least squares discriminant analysis resulted in a clear separation of samples when a total of 551 differential metabolites were considered. A prediction model was generated using the most consistent metabolites. Most of the metabolites identified were saturated fatty acids, which were detected in lower concentrations in the SCM of embryos from obese women. The metabolomic profile was similar in obese women with or without PCOS. The metabolomic profile in the SCM of day-3 embryos is different in normoweight and obese women. Saturated fatty acids seem to be reduced when embryos from obese patients are present. NCT01448863. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  19. Comparison of earthworm responses to petroleum hydrocarbon exposure in aged field contaminated soil using traditional ecotoxicity endpoints and 1H NMR-based metabolomics

    International Nuclear Information System (INIS)

    Whitfield Åslund, Melissa; Stephenson, Gladys L.; Simpson, André J.; Simpson, Myrna J.

    2013-01-01

    1 H NMR metabolomics and conventional ecotoxicity endpoints were used to examine the response of earthworms exposed to petroleum hydrocarbons (PHCs) in soil samples collected from a site that was contaminated with crude oil from a pipeline failure in the mid-1990s. The conventional ecotoxicity tests showed that the soils were not acutely toxic to earthworms (average survival ≥90%), but some soil samples impaired reproduction endpoints by >50% compared to the field control soil. Additionally, metabolomics revealed significant relationships between earthworm metabolic profiles (collected after 2 or 14 days of exposure) and soil properties including soil PHC concentration. Further comparisons by partial least squares regression revealed a significant relationship between the earthworm metabolomic data (collected after only 2 or 14 days) and the reproduction endpoints (measured after 63 days). Therefore, metabolomic responses measured after short exposure periods may be predictive of chronic, ecologically relevant toxicity endpoints for earthworms exposed to soil contaminants. -- Highlights: •Earthworm response to petroleum hydrocarbon exposure in soil is examined. •Metabolomics shows significant changes to metabolic profile after 2 days. •Significant relationships observed between metabolomic and reproduction endpoints. •Metabolomics may have value as a rapid screening tool for chronic toxicity. -- Earthworm metabolomic responses measured after 2 and 14 days are compared to traditional earthworm ecotoxicity endpoints (survival and reproduction) in petroleum hydrocarbon contaminated soil

  20. Fatty acid and metabolomic profiling approaches differentiate heterotrophic and mixotrophic culture conditions in a microalgal food supplement 'Euglena'.

    Science.gov (United States)

    Zeng, Min; Hao, Wenlong; Zou, Yongdong; Shi, Mengliang; Jiang, Yongguang; Xiao, Peng; Lei, Anping; Hu, Zhangli; Zhang, Weiwen; Zhao, Liqing; Wang, Jiangxin

    2016-06-02

    Microalgae have been recognized as a good food source of natural biologically active ingredients. Among them, the green microalga Euglena is a very promising food and nutritional supplements, providing high value-added poly-unsaturated fatty acids, paramylon and proteins. Different culture conditions could affect the chemical composition and food quality of microalgal cells. However, little information is available for distinguishing the different cellular changes especially the active ingredients including poly-saturated fatty acids and other metabolites under different culture conditions, such as light and dark. In this study, together with fatty acid profiling, we applied a gas chromatography-mass spectrometry (GC-MS)-based metabolomics to differentiate hetrotrophic and mixotrophic culture conditions. This study suggests metabolomics can shed light on understanding metabolomic changes under different culture conditions and provides a theoretical basis for industrial applications of microalgae, as food with better high-quality active ingredients.