Science.gov

Sample records for metabolomics

  1. Microbial Metabolomics

    PubMed Central

    Tang, Jane

    2011-01-01

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

  2. Elemental metabolomics.

    PubMed

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

    2017-01-10

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

  3. Metabolomics in food science.

    PubMed

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

    2012-01-01

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

  4. Metabolomics for laboratory diagnostics.

    PubMed

    Bujak, Renata; Struck-Lewicka, Wiktoria; Markuszewski, Michał J; Kaliszan, Roman

    2015-09-10

    Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Metabolomics and Epidemiology Working Group

    Cancer.gov

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

  6. Cancer Metabolomics and the Human Metabolome Database

    PubMed Central

    Wishart, David S.; Mandal, Rupasri; Stanislaus, Avalyn; Ramirez-Gaona, Miguel

    2016-01-01

    The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world’s largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer. PMID:26950159

  7. Cancer Metabolomics and the Human Metabolome Database.

    PubMed

    Wishart, David S; Mandal, Rupasri; Stanislaus, Avalyn; Ramirez-Gaona, Miguel

    2016-03-02

    The application of metabolomics towards cancer research has led to a renewed appreciation of metabolism in cancer development and progression. It has also led to the discovery of metabolite cancer biomarkers and the identification of a number of novel cancer causing metabolites. The rapid growth of metabolomics in cancer research is also leading to challenges. In particular, with so many cancer-associate metabolites being identified, it is often difficult to keep track of which compounds are associated with which cancers. It is also challenging to track down information on the specific pathways that particular metabolites, drugs or drug metabolites may be affecting. Even more frustrating are the difficulties associated with identifying metabolites from NMR or MS spectra. Fortunately, a number of metabolomics databases are emerging that are designed to address these challenges. One such database is the Human Metabolome Database (HMDB). The HMDB is currently the world's largest and most comprehensive, organism-specific metabolomics database. It contains more than 40,000 metabolite entries, thousands of metabolite concentrations, >700 metabolic and disease-associated pathways, as well as information on dozens of cancer biomarkers. This review is intended to provide a brief summary of the HMDB and to offer some guidance on how it can be used in metabolomic studies of cancer.

  8. Metabolomics: A Primer.

    PubMed

    Liu, Xiaojing; Locasale, Jason W

    2017-04-01

    Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future.

  9. Metabolomics in hypertension.

    PubMed

    Nikolic, Sonja B; Sharman, James E; Adams, Murray J; Edwards, Lindsay M

    2014-06-01

    Hypertension is the most prevalent chronic medical condition and a major risk factor for cardiovascular morbidity and mortality. In the majority of hypertensive cases, the underlying cause of hypertension cannot be easily identified because of the heterogeneous, polygenic and multi-factorial nature of hypertension. Metabolomics is a relatively new field of research that has been used to evaluate metabolic perturbations associated with disease, identify disease biomarkers and to both assess and predict drug safety and efficacy. Metabolomics has been increasingly used to characterize risk factors for cardiovascular disease, including hypertension, and it appears to have significant potential for uncovering mechanisms of this complex disease. This review details the analytical techniques, pre-analytical steps and study designs used in metabolomics studies, as well as the emerging role for metabolomics in gaining mechanistic insights into the development of hypertension. Suggestions as to the future direction for metabolomics research in the field of hypertension are also proposed.

  10. Metabolomics in chemical ecology.

    PubMed

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

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

  11. The Human Serum Metabolome

    PubMed Central

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

    2011-01-01

    Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

  12. Metabolomics and malaria biology

    PubMed Central

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

    2010-01-01

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

  13. Metabolomics and protozoan parasites.

    PubMed

    Paget, Timothy; Haroune, Nicolas; Bagchi, Sushmita; Jarroll, Edward

    2013-06-01

    In this review, we examine the state-of-the-art technologies (gas and liquid chromatography, mass spectroscopy and nuclear magnetic resonance, etc.) in the well-established area of metabolomics especially as they relate to protozoan parasites.

  14. Metabolomics in dyslipidemia.

    PubMed

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

    2014-01-01

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

  15. The human serum metabolome

    USDA-ARS?s Scientific Manuscript database

    Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically i...

  16. Quality assurance of metabolomics.

    PubMed

    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.

  17. COnsortium of METabolomics Studies (COMETS)

    Cancer.gov

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

  18. Metabolomics of temperature stress.

    PubMed

    Guy, Charles; Kaplan, Fatma; Kopka, Joachim; Selbig, Joachim; Hincha, Dirk K

    2008-02-01

    Plants possess inducible tolerance mechanisms that extend the temperature range for survival during acute temperature stress. The inducible mechanisms of cold acclimation and acquired thermotolerance involve highly complex processes. These include perception and signal transduction of non-optimal temperatures or their physical consequences on cellular components that program extensive modification of the transcriptome, proteome, metabolome and composition and physical structure of the cytoplasm, membranes and cell walls. Therefore, a systems biology approach will be necessary to advance the understanding of plant stress responses and tolerance mechanisms. One promise of systems biology is that it will greatly enhance our understanding of individual and collective functions and thereby provide a more holistic view of plant stress responses. Past studies have found that several metabolites that could functionally contribute to induced stress tolerance have been associated with stress responses. Recent metabolite-profiling studies have refocused attention on these and other potentially important components found in the 'temperature-stress metabolome'. These metabolomic studies have demonstrated that active reconfiguration of the metabolome is regulated in part by changes in gene expression initiated by temperature-stress-activated signaling and stress-related transcription factors. One aspect of metabolism that is consistent across all of the temperature-stress metabolomic studies to date is the prominent role of central carbohydrate metabolism, which seems to be a major feature of the reprogramming of the metabolome during temperature stress. Future metabolomic studies of plant temperature-stress responses should reveal additional metabolic pathways that have important functions in temperature-stress tolerance mechanisms.

  19. Clinical Metabolomics and Glaucoma.

    PubMed

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

    2017-09-01

    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.

  20. Single-Cell Metabolomics.

    PubMed

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

    2017-01-01

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

  1. Establishing Substantial Equivalence: Metabolomics

    NASA Astrophysics Data System (ADS)

    Beale, Michael H.; Ward, Jane L.; Baker, John M.

    Modern ‘metabolomic’ methods allow us to compare levels of many structurally diverse compounds in an automated fashion across a large number of samples. This technology is ideally suited to screening of populations of plants, including trials where the aim is the determination of unintended effects introduced by GM. A number of metabolomic methods have been devised for the determination of substantial equivalence. We have developed a methodology, using [1H]-NMR fingerprinting, for metabolomic screening of plants and have applied it to the study of substantial equivalence of field-grown GM wheat. We describe here the principles and detail of that protocol as applied to the analysis of flour generated from field plots of wheat. Particular emphasis is given to the downstream data processing and comparison of spectra by multivariate analysis, from which conclusions regarding metabolome changes due to the GM can be assessed against the background of natural variation due to environment.

  2. Metabolomics of Diabetic Retinopathy.

    PubMed

    Liew, Gerald; Lei, Zhou; Tan, Gavin; Joachim, Nichole; Ho, I-Van; Wong, Tien Y; Mitchell, Paul; Gopinath, Bamini; Crossett, Ben

    2017-09-23

    Metabolomics is the study of dysregulated metabolites in biological materials. We reviewed the use of the technique to elucidate the genetic and environmental factors that contribute to the development of diabetic retinopathy. With regard to metabolomic studies of diabetic retinopathy, the field remains in its infancy with few studies published to date and little replication of results. Vitreous and serum samples are the main tissues examined, and dysregulation in pathways such as the pentose phosphate pathway, arginine to proline pathway, polyol pathway, and ascorbic acidic pathways have been reported. Few studies have examined the metabolomic underpinnings of diabetic retinopathy. Further research is required to replicate findings to date and determine longitudinal associations with disease.

  3. Metabolomics in childhood diabetes

    PubMed Central

    Frohnert, Brigitte I; Rewers, Marian J

    2015-01-01

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

  4. Metabolomics in agriculture.

    PubMed

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

    2012-04-01

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

  5. Metabolomics in asthma.

    PubMed

    Luxon, Bruce A

    2014-01-01

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

  6. Metabolomics and human nutrition.

    PubMed

    Primrose, Sandy; Draper, John; Elsom, Rachel; Kirkpatrick, Verity; Mathers, John C; Seal, Chris; Beckmann, Manfred; Haldar, Sumanto; Beattie, John H; Lodge, John K; Jenab, Mazda; Keun, Hector; Scalbert, Augustin

    2011-04-01

    The present report summarises a workshop convened by the UK Food Standards Agency (Agency) on 25 March 2010 to discuss the current Agency's funded research on the use of metabolomics technologies in human nutrition research. The objectives of this workshop were to review progress to date, to identify technical challenges and ways of overcoming them, and to discuss future research priorities and the application of metabolomics in public health nutrition research and surveys. Results from studies nearing completion showed that by using carefully designed dietary and sampling regimens, it is possible to identify novel biomarkers of food intake that could not have been predicted from current knowledge of food composition. These findings provide proof-of-principle that the metabolomics approach can be used to develop new putative biomarkers of dietary intake. The next steps will be to validate these putative biomarkers, to develop rapid and inexpensive assays for biomarkers of food intake of high public health relevance, and to test their utility in population cohort studies and dietary surveys.

  7. The Human Urine Metabolome

    PubMed Central

    Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

    2013-01-01

    Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing

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

    PubMed Central

    Guo, An Chi; Sajed, Tanvir; Steele, Michael A.; Plastow, Graham S.; Wishart, David S.

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed. PMID:28531195

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

    PubMed

    Goldansaz, Seyed Ali; Guo, An Chi; Sajed, Tanvir; Steele, Michael A; Plastow, Graham S; Wishart, David S

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

  10. Metabolomics protocols for filamentous fungi.

    PubMed

    Gummer, Joel P A; Krill, Christian; Du Fall, Lauren; Waters, Ormonde D C; Trengove, Robert D; Oliver, Richard P; Solomon, Peter S

    2012-01-01

    Proteomics and transcriptomics are established functional genomics tools commonly used to study filamentous fungi. Metabolomics has recently emerged as another option to complement existing techniques and provide detailed information on metabolic regulation and secondary metabolism. Here, we describe broad generic protocols that can be used to undertake metabolomics studies in filamentous fungi.

  11. Biological insights through nontargeted metabolomics.

    PubMed

    Sévin, Daniel C; Kuehne, Andreas; Zamboni, Nicola; Sauer, Uwe

    2015-08-01

    Metabolomics is increasingly employed to investigate metabolism and its reciprocal crosstalk with cellular signaling and regulation. In recent years, several nontargeted metabolomics methods providing substantial metabolome coverage have been developed. Here, we review and compare the contributions of traditional targeted and nontargeted metabolomics in advancing different research areas ranging from biotechnology to human health. Although some studies demonstrated the power of nontargeted profiling in generating unexpected and yet highly important insights, we found that most mechanistic links were still revealed by hypothesis-driven targeted methods. Novel computational approaches for formal interpretation of complex metabolic patterns and integration of complementary molecular layers are required to tap the full potential of nontargeted metabolomics for data-driven, discovery-oriented research and rapidly nucleating novel biological insights. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Genome-enabled plant metabolomics.

    PubMed

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

    2014-09-01

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

  13. MASS SPECTROMETRY-BASED METABOLOMICS

    PubMed Central

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

    2007-01-01

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

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

    PubMed

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

    2007-11-01

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

  15. Metabolomics for salinity research.

    PubMed

    Roessner, Ute; Beckles, Diane M

    2012-01-01

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

  16. Metabolomics of genetically modified crops.

    PubMed

    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

    PubMed Central

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

    2014-01-01

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

  18. Metabolomics in diabetes.

    PubMed

    Zhang, Ai-hua; Qiu, Shi; Xu, Hong-ying; Sun, Hui; Wang, Xi-jun

    2014-02-15

    Characterization of metabolic changes is key to early detection, treatment, and understanding molecular mechanisms of diabetes. Diabetes represents one of the most important global health problems. Approximately 90% of diabetics have type 2 diabetes. Identification of effective screening markers is critical for early treatment and intervention that can delay and/or prevent complications associated with this chronic disease. Fortunately, metabolomics has introduced new insights into the pathology of diabetes as well as to predict disease onset and revealed new biomarkers to improve diagnostics in a range of diseases. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand T2D phenotypes. Characteristic patterns of metabolites can be revealed that broaden our understanding of T2D disorder. This technique-driven review aims to demystify the mechanisms of T2D, to provide updates on the applications of metabolomics in addressing T2D with a focus on metabolites based biomarker discovery. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. Metabolomics in diabetic complications.

    PubMed

    Filla, Laura A; Edwards, James L

    2016-04-01

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

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

    PubMed

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

    2015-05-01

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

  1. High-throughput discovery metabolomics.

    PubMed

    Fuhrer, Tobias; Zamboni, Nicola

    2015-02-01

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

  2. Metabolomics in plant environmental physiology.

    PubMed

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

    2013-10-01

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

  3. Food metabolomics: from farm to human.

    PubMed

    Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

    2016-02-01

    Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Metabolomics in diabetes, a review.

    PubMed

    Pallares-Méndez, Rigoberto; Aguilar-Salinas, Carlos A; Cruz-Bautista, Ivette; Del Bosque-Plata, Laura

    2016-01-01

    Metabolomics is a promising approach for the identification of chemical compounds that serve for early detection, diagnosis, prediction of therapeutic response and prognosis of disease. Moreover, metabolomics has shown to increase the diagnostic threshold and prediction of type 2 diabetes. Evidence suggests that branched-chain amino acids, acylcarnitines and aromatic amino acids may play an early role on insulin resistance, exposing defects on amino acid metabolism, β-oxidation, and tricarboxylic acid cycle. This review aims to provide a panoramic view of the metabolic shifts that antecede or follow type 2 diabetes. Key messages BCAAs, AAAs and acylcarnitines are strongly associated with early insulin resistance. Diabetes risk prediction has been improved when adding metabolomic markers of dysglycemia to standard clinical and biochemical factors.

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

    PubMed

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

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

  6. Vitamins, metabolomics, and prostate cancer.

    PubMed

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

    2017-06-01

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

  7. Brain Injury Alters Volatile Metabolome.

    PubMed

    Kimball, Bruce A; Cohen, Akiva S; Gordon, Amy R; Opiekun, Maryanne; Martin, Talia; Elkind, Jaclynn; Lundström, Johan N; Beauchamp, Gary K

    2016-06-01

    Chemical signals arising from body secretions and excretions communicate information about health status as have been reported in a range of animal models of disease. A potential common pathway for diseases to alter chemical signals is via activation of immune function-which is known to be intimately involved in modulation of chemical signals in several species. Based on our prior findings that both immunization and inflammation alter volatile body odors, we hypothesized that injury accompanied by inflammation might correspondingly modify the volatile metabolome to create a signature endophenotype. In particular, we investigated alteration of the volatile metabolome as a result of traumatic brain injury. Here, we demonstrate that mice could be trained in a behavioral assay to discriminate mouse models subjected to lateral fluid percussion injury from appropriate surgical sham controls on the basis of volatile urinary metabolites. Chemical analyses of the urine samples similarly demonstrated that brain injury altered urine volatile profiles. Behavioral and chemical analyses further indicated that alteration of the volatile metabolome induced by brain injury and alteration resulting from lipopolysaccharide-associated inflammation were not synonymous. Monitoring of alterations in the volatile metabolome may be a useful tool for rapid brain trauma diagnosis and for monitoring recovery. Published by Oxford University Press on behalf of US Government 2016.

  8. Brain Injury Alters Volatile Metabolome

    PubMed Central

    Cohen, Akiva S.; Gordon, Amy R.; Opiekun, Maryanne; Martin, Talia; Elkind, Jaclynn; Lundström, Johan N.; Beauchamp, Gary K.

    2016-01-01

    Chemical signals arising from body secretions and excretions communicate information about health status as have been reported in a range of animal models of disease. A potential common pathway for diseases to alter chemical signals is via activation of immune function—which is known to be intimately involved in modulation of chemical signals in several species. Based on our prior findings that both immunization and inflammation alter volatile body odors, we hypothesized that injury accompanied by inflammation might correspondingly modify the volatile metabolome to create a signature endophenotype. In particular, we investigated alteration of the volatile metabolome as a result of traumatic brain injury. Here, we demonstrate that mice could be trained in a behavioral assay to discriminate mouse models subjected to lateral fluid percussion injury from appropriate surgical sham controls on the basis of volatile urinary metabolites. Chemical analyses of the urine samples similarly demonstrated that brain injury altered urine volatile profiles. Behavioral and chemical analyses further indicated that alteration of the volatile metabolome induced by brain injury and alteration resulting from lipopolysaccharide-associated inflammation were not synonymous. Monitoring of alterations in the volatile metabolome may be a useful tool for rapid brain trauma diagnosis and for monitoring recovery. PMID:26926034

  9. YMDB: the Yeast Metabolome Database

    PubMed Central

    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

  10. LC-MS-based metabolomics: an update.

    PubMed

    Fang, Zhong-Ze; Gonzalez, Frank J

    2014-08-01

    Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics can have a major impact in multiple research fields, especially when combined with other technologies, such as stable isotope tracers and genetically modified mice. This review highlights recent applications of metabolomic technology in the study of xenobiotic metabolism and toxicity, and the understanding of disease pathogenesis and therapeutics. Metabolomics has been employed to study metabolism of noscapine, an aryl hydrocarbon receptor antagonist, and to determine the mechanisms of liver toxicities of rifampicin and isoniazid, trichloroethylene, and gemfibrozil. Metabolomics-based insights into the pathogenesis of inflammatory bowel disease, alcohol-induced liver diseases, non-alcoholic steatohepatitis, and farnesoid X receptor signaling pathway-based therapeutic target discovery will also be discussed. Limitations in metabolomics technology such as sample preparation and lack of LC-MS databases and metabolite standards, need to be resolved in order to improve and broaden the application of metabolomic studies.

  11. Recent advances of metabolomics in plant biotechnology.

    PubMed

    Okazaki, Yozo; Saito, Kazuki

    2012-01-01

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

  12. Metabolomics in Toxicology and Preclinical Research

    PubMed Central

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

    2013-01-01

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

  13. Metabolome-ionome-biomass interactions

    PubMed Central

    Sanchez, Diego H; Redestig, Henning; Krämer, Ute; Udvardi, Michael K

    2008-01-01

    Long-term exposure of plants to saline soil results in mineral ion imbalance, altered metabolism and reduced growth. Currently, the interaction between ion content and plant metabolism under salt-stress is poorly understood. Here we present a multivariate correlation study on the metabolome, ionome and biomass changes of Lotus japonicus challenged by salt stress. Using latent variable models, we show that increasing salinity leads to reproducible changes of metabolite, ion and nutrient pools. Strong correlations between the metabolome and the ionome or biomass may allow one to estimate the degree of salt stress experienced by a plant based on metabolite profiles. Despite the apparently high predictive power of the models, it remains to be investigated whether such metabolite profiles of non- or moderately-stressed plants can be used by breeding programs as ideal ideotypes for the selection of enhanced salt-tolerant genotypes. PMID:19704810

  14. Metabolomics for plant stress response.

    PubMed

    Shulaev, Vladimir; Cortes, Diego; Miller, Gad; Mittler, Ron

    2008-02-01

    Stress in plants could be defined as any change in growth condition(s) that disrupts metabolic homeostasis and requires an adjustment of metabolic pathways in a process that is usually referred to as acclimation. Metabolomics could contribute significantly to the study of stress biology in plants and other organisms by identifying different compounds, such as by-products of stress metabolism, stress signal transduction molecules or molecules that are part of the acclimation response of plants. These could be further tested by direct measurements, correlated with changes in transcriptome and proteome expression and confirmed by mutant analysis. In this review, we will discuss recent application of metabolomics and system biology to the area of plant stress response. We will describe approaches such as metabolic profiling and metabolic fingerprinting as well as combination of different 'omics' platforms to achieve a holistic view of the plant response stress and conduct detailed pathway analysis.

  15. Progress toward single cell metabolomics

    PubMed Central

    Rubakhin, Stanislav S.; Lanni, Eric J.; Sweedler, Jonathan V.

    2012-01-01

    The metabolome refers to the entire set of small molecules, or metabolites, within a biological sample. These molecules are involved in many fundamental intracellular functions and reflect the cell’s physiological condition. The ability to detect and identify metabolites and determine and monitor their amounts at the single cell level enables an exciting range of studies of biological variation and functional heterogeneity between cells, even within a presumably homogenous cell population. Significant progress has been made in the development and application of bioanalytical tools for single cell metabolomics based on mass spectrometry, microfluidics, and capillary separations. Remarkable improvements in the sensitivity, specificity, and throughput of these approaches enable investigation of multiple metabolites simultaneously in a range of individual cell samples. PMID:23246232

  16. Metabolomic signature of brain cancer.

    PubMed

    Pandey, Renu; Caflisch, Laura; Lodi, Alessia; Brenner, Andrew J; Tiziani, Stefano

    2017-06-15

    Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed. © 2017 Wiley Periodicals, Inc.

  17. Applications of metabolomics in agriculture.

    PubMed

    Dixon, Richard A; Gang, David R; Charlton, Adrian J; Fiehn, Oliver; Kuiper, Harry A; Reynolds, Tracey L; Tjeerdema, Ronald S; Jeffery, Elizabeth H; German, J Bruce; Ridley, William P; Seiber, James N

    2006-11-29

    Biological systems are exceedingly complex. The unraveling of the genome in plants and humans revealed fewer than the anticipated number of genes. Therefore, other processes such as the regulation of gene expression, the action of gene products, and the metabolic networks resulting from catalytic proteins must make fundamental contributions to the remarkable diversity inherent in living systems. Metabolomics is a relatively new approach aimed at improved understanding of these metabolic networks and the subsequent biochemical composition of plants and other biological organisms. Analytical tools within metabolomics including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy can profile the impact of time, stress, nutritional status, and environmental perturbation on hundreds of metabolites simultaneously resulting in massive, complex data sets. This information, in combination with transcriptomics and proteomics, has the potential to generate a more complete picture of the composition of food and feed products, to optimize crop trait development, and to enhance diet and health. Selected presentations from an American Chemical Society symposium held in March 2005 have been assembled to highlight the emerging application of metabolomics in agriculture.

  18. Disease monitoring of hepatocellular carcinoma through metabolomics

    PubMed Central

    Fitian, Asem I; Cabrera, Roniel

    2017-01-01

    We elucidate major pathways of hepatocarcinogenesis and accurate diagnostic metabolomic biomarkers of hepatocellular carcinoma (HCC) identified by contemporary HCC metabolomics studies, and delineate a model HCC metabolomics study design. A literature search was carried out on Pubmed for HCC metabolomics articles published in English. All relevant articles were accessed in full text. Major search terms included “HCC”, “metabolomics”, “metabolomics”, “metabonomic” and “biomarkers”. We extracted clinical and demographic data on all patients and consolidated the lead candidate biomarkers, pathways, and diagnostic performance of metabolomic expression patterns reported by all studies in tables. Where reported, we also extracted and summarized the metabolites and pathways most highly associated with the development of cirrhosis in table format. Pathways of lysophospholipid, sphingolipid, bile acid, amino acid, and reactive oxygen species metabolism were most consistently associated with HCC in the cited works. Several studies also elucidate metabolic alterations strongly associated with cirrhosis, with γ-glutamyl peptides, bile acids, and dicarboxylic acids exhibiting the highest capacity for stratifying cirrhosis patients from appropriately matched controls. Collectively, global metabolomic profiles of the referenced works exhibit a promising diagnostic capacity for HCC at a capacity greater than that of conventional diagnostic biomarker alpha-fetoprotein. Metabolomics is a powerful strategy for identifying global metabolic signatures that exhibit potential to be leveraged toward the screening, diagnosis, and management of HCC. A streamlined study design and patient matching methodology may improve concordance among metabolomic datasets in future works. PMID:28105254

  19. A Metabolomic Perspective on Coeliac Disease

    PubMed Central

    Calabrò, Antonio

    2014-01-01

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

  20. NMR Metabolomics Analysis of Parkinson's Disease

    PubMed Central

    Lei, Shulei; Powers, Robert

    2015-01-01

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

  1. Getting the right answers: understanding metabolomics challenges.

    PubMed

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

    2015-01-01

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

  2. Plant tissue extraction for metabolomics.

    PubMed

    Roessner, Ute; Dias, Daniel Anthony

    2013-01-01

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

  3. Environmental metabolomics: Biological markers for metal toxicity.

    PubMed

    García-Sevillano, Miguel Ángel; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2015-07-14

    Environmental metabolomics is an emerging field referred to the application of metabolomics to characterize the interactions of living organisms with their environment. In this sense, the importance of monitoring the effects of toxic metals on living organisms has increased as a consequence of natural changes and anthropogenic activities that have led to an increase of toxic metals levels in terrestrial and aquatic ecosystems. For this purpose, the use of metabolomics based on mass spectrometry to study metal toxicity is gaining importance in recent years. Environmental metabolomics can be used to: discover the mode of action (MOA) of toxic metals through controlled laboratory experiments; evaluate toxicity (biological adverse response to a substance), that may be useful in risk assessment; and develop new biomarkers (based in metabolome shifts discovered through controlled laboratory experiments) that may be applied in environmental biomonitoring (environmental realistic scenario). In this review, it is discussed how metabolomics based on mass spectrometry can be applied to study metal toxicity, considering the most important hallmarks related to metabolomic experiments. This article is protected by copyright. All rights reserved.

  4. Metabolomics in neonatology: fact or fiction?

    PubMed

    Fanos, V; Van den Anker, J; Noto, A; Mussap, M; Atzori, L

    2013-02-01

    The newest 'omics' science is metabolomics, the latest offspring of genomics, considered the most innovative of the 'omics' sciences. Metabolomics, also called the 'new clinical biochemistry', is an approach based on the systematic study of the complete set of metabolites in a biological sample. The metabolome is considered the most predictive phenotype and is capable of considering epigenetic differences. It is so close to the phenotype that it can be considered the phenotype itself. In the last three years about 5000 papers have been listed in PubMed on this topic, but few data are available in the newborn. The aim of this review, after a description of background and technical procedures, is to analyse the clinical applications of metabolomics in neonatology, covering the following points: gestational age, postnatal age, type of delivery, zygosity, perinatal asphyxia, intrauterine growth restriction, prenatal inflammation and brain injury, respiratory, cardiovascular renal, metabolic diseases; sepsis, necrotizing enterocolitis and antibiotic treatment; nutritional studies on maternal milk and formula, pharma-metabolomics, long-term diseases. Pros and cons of metabolomics are also discussed. All this comes about with the non-invasive collection of a few drops of urine (exceptionally important for the neonate, especially those of low birth weight). Only time and large-scale studies to validate initial results will place metabolomics within neonatology. In any case, it is important for perinatologists to learn and understand this new technology to offer their patients the utmost in diagnostic and therapeutic opportunities.

  5. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    PubMed Central

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

    2014-01-01

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

  6. Metabolomics applied to the pancreatic islet

    PubMed Central

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

    2016-01-01

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

  7. Metabolomics in Population-Based Research

    Cancer.gov

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

  8. Metabolomics Standards Workshop and the development of international standards for reporting metabolomics experimental results.

    PubMed

    Castle, Arthur L; Fiehn, Oliver; Kaddurah-Daouk, Rima; Lindon, John C

    2006-06-01

    Informatics standards and controlled vocabularies are essential for allowing information technology to help exchange, manage, interpret and compare large data collections. In a rapidly evolving field, the challenge is to work out how best to describe, but not prescribe, the use of these technologies and methods. A Metabolomics Standards Workshop was held by the US National Institutes of Health (NIH) to bring together multiple ongoing standards efforts in metabolomics with the NIH research community. The goals were to discuss metabolomics workflows (methods, technologies and data treatments) and the needs, challenges and potential approaches to developing a Metabolomics Standards Initiative that will help facilitate this rapidly growing field which has been a focus of the NIH roadmap effort. This report highlights specific aspects of what was presented and discussed at the 1st and 2nd August 2005 Metabolomics Standards Workshop.

  9. Metabolomics and dereplication strategies in natural products.

    PubMed

    Tawfike, Ahmed Fares; Viegelmann, Christina; Edrada-Ebel, Ruangelie

    2013-01-01

    Metabolomic methods can be utilized to screen diverse biological sources of potentially novel and sustainable sources of antibiotics and pharmacologically-active drugs. Dereplication studies by high resolution Fourier transform mass spectrometry coupled to liquid chromatography (LC-HRFTMS) and nuclear magnetic resonance (NMR) spectroscopy can establish the chemical profile of endophytic and/or endozoic microbial extracts and their plant or animal sources. Identifying the compounds of interest at an early stage will aid in the isolation of the bioactive components. Therefore metabolite profiling is important for functional genomics and in the search for new pharmacologically active compounds. Using the tools of metabolomics through the employment of LC-HRFTMS as well as high resolution NMR will be a very efficient approach. Metabolomic profiling has found its application in screening extracts of macroorganisms as well as in the isolation and cultivation of suspected microbial producers of bioactive natural products.Metabolomics is being applied to identify and biotechnologically optimize the production of pharmacologically active secondary metabolites. The links between metabolome evolution during optimization and processing factors can be identified through metabolomics. Information obtained from a metabolomics dataset can efficiently establish cultivation and production processes at a small scale which will be finally scaled up to a fermenter system, while maintaining or enhancing synthesis of the desired compounds. MZmine (BMC Bioinformatics 11:395-399, 2010; http://mzmine.sourceforge.net/download.shtml ) and SIEVE ( http://www.vastscientific.com/resources/index.html ; Rapid Commun Mass Spectrom 22:1912-1918, 2008) softwares are utilized to perform differential analysis of sample populations to find significant expressed features of complex biomarkers between parameter variables. Metabolomes are identified with the aid of existing high resolution MS and NMR

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

    PubMed

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

    2015-04-07

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

  11. METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  14. METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

    EPA Science Inventory

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

  15. Metabolomics data normalization with EigenMS.

    PubMed

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

    2014-01-01

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

  16. THE METABOLOMIC WINDOW INTO HEPATOBILIARY DISEASE

    PubMed Central

    Beyoğlu, Diren; Idle, Jeffrey R.

    2014-01-01

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

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

    DTIC Science & Technology

    2014-10-01

    AWARD NUMBER: W81XWH-13-1-0493 TITLE: Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and...SUBTITLE Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress 5a. CONTRACT NUMBER Perceived Stress...SUBJECT TERMS ovarian cancer, psychosocial stress, depression, anxiety, social support, metabolomics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

  18. Metabolomics: a new era in cardiology?

    PubMed

    Mercuro, Giuseppe; Bassareo, Pier P; Deidda, Martino; Cadeddu, Christian; Barberini, Luigi; Atzori, Luigi

    2011-11-01

    The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end-products of cellular processes. Metabolomics is the systematic study of small-molecule metabolite profiles that specific cellular processes leave behind. RNA messenger gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell. Metabolic profiling, in turn, amplifies changes both in the proteome and the genome, and represents a more accurate approximation to the phenotype of an organism in health and disease. In this article, we have provided a description of metabolomics, in the presence of other, more familiar 'omics' disciplines, such as genomics and proteomics. In addition, we have reviewed the current rationale for metabolomics in cardiology, its basic methodology and the data actually available in human studies in this discipline. The discussed topics highlight the importance of being able to use the metabolomics information in order to understand disease mechanisms from a systems biology perspective as a noninvasive approach to diagnose, grade and treat cardiovascular diseases.

  19. Systematic Applications of Metabolomics in Metabolic Engineering

    PubMed Central

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

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

  20. Metabolomics: Applications and Promise in Mycobacterial Disease

    PubMed Central

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

    2015-01-01

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

  1. Applying Metabolomics to differentiate amphibian responses ...

    EPA Pesticide Factsheets

    Introduction/Objectives/Methods One of the biggest challenges in ecological risk assessment is determining the impact of multiple stressors on individual organisms and populations in ‘real world’ scenarios. Emerging ‘omic technologies, notably, metabolomics, provides an opportunity to address the uncertainties surrounding ecological risk assessment of multiple stressors. The objective of this study was to use a metabolomics biomarker approach to investigate the effect of multiple stressors on amphibian metamorphs. To this end, metamorphs of Rana pipiens (northern leopard frogs) were exposed to the insecticide Carbaryl (0.32 μg/L), a conspecific predator alarm call (Lithobates catesbeianus), Carbaryl and the predator alarm call, and a control with no stressor. In addition to metabolomic fingerprinting, we measured corticosterone levels in each treatment to assess general stress response. We analyzed relative abundances of endogenous metabolites collected in liver tissue with gas chromatography coupled with mass spectrometry. Support vector machine (SVM) methods with recursive feature elimination (RFE) were applied to rank the metabolomic profiles produced. Results/Conclusions SVM-RFE of the acquired metabolomic spectra demonstrated 85-96% classification accuracy among control and all treatment groups when using the top 75 ranked retention time bins. Biochemical fluxes observed in the groups exposed to carbaryl, predation threat, and the combined treatmen

  2. Metabolomics: Developing a chemical specific fingerprint

    USGS Publications Warehouse

    Putnam, Joel G.

    2016-01-01

    We combine cell assays and metabolomics to create a powerful tool, which emerges to elevate the identification of new control chemicals. We combined the use of bigheaded carp fry cell line with metabolite profiling to describe the dose response to thiram. Thiram is a registered pesticide commonly used as a fungicide in the field or as a seed protectant and is known to be toxic to fish. Seven concentrations of thiram were used to dose bighead carp fry cells and silver carp fry cells. We identified 700 metabolomic markers and 41 of those markers exhibited a dose response to thiram in the bighead carp fry cells. We identified 1590 metabolomic markers with 205 of those markers exhibited a dose response to thiram in the silver carp fry cells. When the metabolites of both cell lines are compared using volcano plots, 16 metabolomic markers were identified as significant. A smaller subset of metabolites indicate that a thiram specific metabolomic fingerprint exists that is not species specific, but instead toxin specific. Application of toxin fingerprints (toxin specific but species independent metabolites) can be used to address the cause of ecological significant events, such as mass fish kills.

  3. Clinical application of metabolomics in neonatology.

    PubMed

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

    2012-04-01

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

  4. Metabolomics: towards understanding traditional Chinese medicine.

    PubMed

    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.

  5. Basics of mass spectrometry based metabolomics.

    PubMed

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

    2014-11-01

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

  6. Sulfites and the wine metabolome.

    PubMed

    Roullier-Gall, Chloé; Hemmler, Daniel; Gonsior, Michael; Li, Yan; Nikolantonaki, Maria; Aron, Alissa; Coelho, Christian; Gougeon, Régis D; Schmitt-Kopplin, Philippe

    2017-12-15

    In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Metabolomic profiling of plant tissues.

    PubMed

    Rambla, José L; López-Gresa, M P; Bellés, J M; Granell, Antonio

    2015-01-01

    Metabolomics is a powerful discipline aimed at a comprehensive and global analysis of the metabolites present in a cell, tissue, or organism, and to which increasing attention has been paid in the last few years. Given the high diversity in physical and chemical properties of plant metabolites, not a single method is able to analyze them all.Here we describe two techniques for the profiling of two quite different groups of metabolites: polar and semi-polar secondary metabolites, including many of those involved in plant response to biotic and abiotic stress, and volatile compounds, which include those responsible of most of our perception of food flavor. According to these techniques, polar and semi-polar metabolites are extracted in methanol, separated by liquid chromatography (UPLC), and detected by a UV-VIS detector (PDA) and a time-of-flight (ToF) mass spectrometer. Volatile compounds, on the other hand, are extracted by headspace solid phase microextraction (HS-SPME), and separated and detected by gas chromatography coupled to mass spectrometry (GC-MS).

  8. The metabolomics of oxidative stress.

    PubMed

    Noctor, Graham; Lelarge-Trouverie, Caroline; Mhamdi, Amna

    2015-04-01

    Oxidative stress resulting from increased availability of reactive oxygen species (ROS) is a key component of many responses of plants to challenging environmental conditions. The consequences for plant metabolism are complex and manifold. We review data on small compounds involved in oxidative stress, including ROS themselves and antioxidants and redox buffers in the membrane and soluble phases, and we discuss the wider consequences for plant primary and secondary metabolism. While metabolomics has been exploited in many studies on stress, there have been relatively few non-targeted studies focused on how metabolite signatures respond specifically to oxidative stress. As part of the discussion, we present results and reanalyze published datasets on metabolite profiles in catalase-deficient plants, which can be considered to be model oxidative stress systems. We emphasize the roles of ROS-triggered changes in metabolites as potential oxidative signals, and discuss responses that might be useful as markers for oxidative stress. Particular attention is paid to lipid-derived compounds, the status of antioxidants and antioxidant breakdown products, altered metabolism of amino acids, and the roles of phytohormone pathways.

  9. Metabolomics in pediatric nephrology: Emerging concepts

    PubMed Central

    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

  10. Metabolomics in pediatric nephrology: emerging concepts.

    PubMed

    Hanna, Mina H; Brophy, Patrick D

    2015-06-01

    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 in monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights into 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 biological 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.

  11. Metabolomics in rheumatic diseases: desperately seeking biomarkers.

    PubMed

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

    2016-05-01

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

  12. Metabolomics: Definitions and Significance in Systems Biology.

    PubMed

    Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

    2017-01-01

    Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

  13. Metabolomics to Explore Impact of Dairy Intake.

    PubMed

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

    2015-06-17

    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.

  14. Metabolomics, a Powerful Tool for Agricultural Research.

    PubMed

    Tian, He; Lam, Sin Man; Shui, Guanghou

    2016-11-17

    Metabolomics, which is based mainly on nuclear magnetic resonance (NMR), gas-chromatography (GC) or liquid-chromatography (LC) coupled to mass spectrometry (MS) analytical technologies to systematically acquire the qualitative and quantitative information of low-molecular-mass endogenous metabolites, provides a direct snapshot of the physiological condition in biological samples. As complements to transcriptomics and proteomics, it has played pivotal roles in agricultural and food science research. In this review, we discuss the capacities of NMR, GC/LC-MS in the acquisition of plant metabolome, and address the potential promise and diverse applications of metabolomics, particularly lipidomics, to investigate the responses of Arabidopsis thaliana, a primary plant model for agricultural research, to environmental stressors including heat, freezing, drought, and salinity.

  15. Metabolomics, a Powerful Tool for Agricultural Research

    PubMed Central

    Tian, He; Lam, Sin Man; Shui, Guanghou

    2016-01-01

    Metabolomics, which is based mainly on nuclear magnetic resonance (NMR), gas-chromatography (GC) or liquid-chromatography (LC) coupled to mass spectrometry (MS) analytical technologies to systematically acquire the qualitative and quantitative information of low-molecular-mass endogenous metabolites, provides a direct snapshot of the physiological condition in biological samples. As complements to transcriptomics and proteomics, it has played pivotal roles in agricultural and food science research. In this review, we discuss the capacities of NMR, GC/LC-MS in the acquisition of plant metabolome, and address the potential promise and diverse applications of metabolomics, particularly lipidomics, to investigate the responses of Arabidopsis thaliana, a primary plant model for agricultural research, to environmental stressors including heat, freezing, drought, and salinity. PMID:27869667

  16. Microbiome, Metabolome and Inflammatory Bowel Disease

    PubMed Central

    Ahmed, Ishfaq; Roy, Badal C.; Khan, Salman A.; Septer, Seth; Umar, Shahid

    2016-01-01

    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. PMID:27681914

  17. Metabolomic change precedes apple superficial scald symptoms.

    PubMed

    Rudell, David R; Mattheis, James P; Hertog, Maarten L A T M

    2009-09-23

    Untargeted metabolic profiling was employed to characterize metabolomic changes associated with 'Granny Smith' apple superficial scald development following 1-MCP or DPA treatment. Partial least-squares discriminant analyses were used to link metabolites with scald, postharvest treatments, and storage duration. Models revealed metabolomic differentiation between untreated controls and fruit treated with DPA or 1-MCP within 1 week following storage initiation. Metabolic divergence between controls and DPA-treated fruit after 4 weeks of storage preceded scald symptom development by 2 months. alpha-Farnesene oxidation products with known associations to scald, including conjugated trienols, 6-methyl-5-hepten-2-one, and 6-methyl-5-hepten-2-ol, were associated with presymptomatic as well as scalded control fruit. Likewise, a large group of putative triterpenoids with mass spectral features similar to those of ursolic acid and beta-sitosterol were associated with control fruit and scald. Results demonstrate that extensive metabolomic changes associated with scald precede actual symptom development.

  18. [Metabolomics analysis of taxadiene producing yeasts].

    PubMed

    Yan, Huifang; Ding, Mingzhu; Yuan, Yingjin

    2014-02-01

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

  19. Proteomics and metabolomics in inflammatory bowel disease.

    PubMed

    Yau, Yunki; Leong, Rupert W; Zeng, Ming; Wasinger, Valerie C

    2013-07-01

    Genome-wide studies in inflammatory bowel disease (IBD) have allowed us to understand Crohn's disease and ulcerative colitis as forms of related autoinflammatory disorders that arise from a multitude of pathogenic origins. Proteomics and metabolomics are the offspring of genomics that possess unprecedented possibilities to characterize unknown pathogenic pathways. It has been about a decade since proteomics was first applied to IBD, and 5 years for metabolomics. These techniques have yielded novel and potentially important findings, but turning these results into beneficial patient outcomes remains challenging. This review recounts the history and context of clinical IBD developments before and after proteomics and metabolomics IBD in this field, discusses the challenges in consolidating high complexity data with physiological understanding, and provides an outlook on the emerging principles that will help interface the bioanalytical laboratory with IBD prognosis.

  20. Metabolomics to Explore Impact of Dairy Intake

    PubMed Central

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

    2015-01-01

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

  1. Metabolomics in rheumatic diseases: desperately seeking biomarkers

    PubMed Central

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

    2016-01-01

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

  2. Genomic and Metabolomic Profile Associated to Microalbuminuria

    PubMed Central

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

    2014-01-01

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

  3. Linking metabolomics data to underlying metabolic regulation

    PubMed Central

    Nägele, Thomas

    2014-01-01

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

  4. Computational Metabolomics: A Framework for the Million Metabolome

    PubMed Central

    Uppal, Karan; Walker, Douglas I.; Liu, Ken; Li, Shuzhao; Go, Young-Mi; Jones, Dean P.

    2017-01-01

    “Sola dosis facit venenum.” These words of Paracelsus, “the dose makes the poison”, can lead to a cavalier attitude concerning potential toxicities of the vast array of low abundance environmental chemicals to which humans are exposed. Exposome research teaches that 80–85% of human disease is linked to environmental exposures. The human exposome is estimated to include >400,000 environmental chemicals, most of which are uncharacterized with regard to human health. In fact, mass spectrometry measures >200,000 m/z features (ions) in microliter volumes derived from human samples; most are unidentified. This crystallizes a grand challenge for chemical research in toxicology: to develop reliable and affordable analytical methods to understand health impacts of the extensive human chemical experience. To this end, there appears to be no choice but to abandon the limitations of measuring one chemical at a time. The present review looks at progress in computational metabolomics to provide probability based annotation linking ions to known chemicals and serve as a foundation for unambiguous designation of unidentified ions for toxicologic study. We review methods to characterize ions in terms of accurate mass m/z, chromatographic retention time, correlation of adduct, isotopic and fragment forms, association with metabolic pathways and measurement of collision-induced dissociation products, collision cross section, and chirality. Such information can support a largely unambiguous system for documenting unidentified ions in environmental surveillance and human biomonitoring. Assembly of this data would provide a resource to characterize and understand health risks of the array of low-abundance chemicals to which humans are exposed. PMID:27629808

  5. Metabolomics in bladder cancer: a systematic review

    PubMed Central

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

    2015-01-01

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

  6. Metabolomic analysis of sun exposed skin.

    PubMed

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

    2013-08-01

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

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

    PubMed Central

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

    2016-01-01

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

  8. Metabolomics in the study of kidney diseases.

    PubMed

    Weiss, Robert H; Kim, Kyoungmi

    2011-10-25

    Metabolomics--the nontargeted measurement of all metabolites produced by the body--is beginning to show promise in both biomarker discovery and, in the form of pharmacometabolomics, in aiding the choice of therapy for patients with specific diseases. In its two basic forms (pattern recognition and metabolite identification), this developing field has been used to discover potential biomarkers in several renal diseases, including acute kidney injury (attributable to a variety of causes), autosomal dominant polycystic kidney disease and kidney cancer. NMR and gas chromatography or liquid chromatography, together with mass spectrometry, are generally used to separate and identify metabolites. Many hurdles need to be overcome in this field, such as achieving consistency in collection of biofluid samples, controlling for batch effects during the analysis and applying the most appropriate statistical analysis to extract the maximum amount of biological information from the data obtained. Pathway and network analyses have both been applied to metabolomic analysis, which vastly extends its clinical relevance and effects. In addition, pharmacometabolomics analyses, in which a metabolomic signature can be associated with a given therapeutic effect, are beginning to appear in the literature, which will lead to personalized therapies. Thus, metabolomics holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in kidney disease.

  9. Cellular Metabolomics for Exposure and Toxicity Assessment

    EPA Science Inventory

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

  10. Microbial metabolomics in open microscale platforms

    PubMed Central

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

    2016-01-01

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

  11. Lessons learned from metabolomics in cystic fibrosis.

    PubMed

    Muhlebach, Marianne S; Sha, Wei

    2015-12-01

    Cystic fibrosis is a mono-genetic multi-system disease; however, respiratory manifestations cause the main morbidity and mortality where chronic bacterial infections lead to bronchiectasis and ultimately respiratory failure. Metabolomics allows a relatively complete snapshot of metabolic processes in a sample using different mass spectrometry methods. Sample types used for discovery of biomarkers or pathomechanisms in cystic fibrosis (CF) have included blood, respiratory secretions, and exhaled breath to date. Metabolomics has shown distinction of CF vs. non-CF for matrices of blood, exhaled breath, and respiratory epithelial cultures, each showing different pathways. Severity of lung disease has been addressed by studies in bronchoalveolar lavage and exhaled breath condensate showing separation by metabolites that the authors of each study related to inflammation; e.g., ethanol, acetone, purines. Lipidomics has been applied to blood and sputum samples showing associations with lung function and Pseudomonas aeruginosa infection status. Finally, studies of bacteria grown in vitro showed differences of bacterial metabolites to be associated with clinical parameters. Metabolomics, in the sense of global metabolomic profiling, is a powerful technique that has allowed discovery of pathways that had not previously been implicated in CF. These may include purines, mitochondrial pathways, and different aspects of glucose metabolism besides the known differences in lipid metabolism in CF. However, targeted studies to validate such potential metabolites and pathways of interest are necessary. Studies evaluating metabolites of bacterial origin are in their early stages. Thus further well-designed studies could be envisioned.

  12. Apple storage management using postharvest metabolomics

    USDA-ARS?s Scientific Manuscript database

    Using broad metabolic profiling of over 600 metabolites, we have previously demonstrated that diphenylamine treatment, 1-methylcyclopropene treatment, and storage duration all alter the apple peel metabolome during cold storage. Because these changes precede and/or are potentially indicative of pos...

  13. Metabolomics in the fight against malaria

    PubMed Central

    Salinas, Jorge L; Kissinger, Jessica C; Jones, Dean P; Galinski, Mary R

    2014-01-01

    Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC), a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP) malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource. PMID:25185001

  14. NMR-based Metabolomics for Cancer Research

    EPA Science Inventory

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

  15. Cellular Metabolomics for Exposure and Toxicity Assessment

    EPA Science Inventory

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

  16. NMR-based Metabolomics for Cancer Research

    EPA Science Inventory

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

  17. Metabolomics for Plant Improvement: Status and Prospects

    PubMed Central

    Kumar, Rakesh; Bohra, Abhishek; Pandey, Arun K.; Pandey, Manish K.; Kumar, Anirudh

    2017-01-01

    Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s) and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement. PMID:28824660

  18. Metabolomic profiling of neoplastic lesions in mice.

    PubMed

    Lu, Xiaojie; Ji, Li-Juan; Chen, Jin-Lian

    2014-01-01

    Most cancers develop upon the accumulation of genetic alterations that provoke and sustain the transformed phenotype. Several metabolomic approaches now allow for the global assessment of intermediate metabolites, generating profound insights into the metabolic rewiring associated with malignant transformation. The metabolomic profiling of neoplastic lesions growing in mice, irrespective of their origin, can provide invaluable information on the mechanisms underlying oncogenesis, tumor progression, and response to therapy. Moreover, the metabolomic profiling of tumors growing in mice may result in the identification of novel diagnostic or prognostic biomarkers, which is of great clinical significance. Several methods can be applied to the metabolomic profiling of neoplastic lesions in mice, including mass spectrometry-based techniques (e.g., gas chromatography-, capillary electrophoresis-, or liquid chromatography-coupled mass spectrometry) as well as nuclear magnetic resonance. Here, we compare and discuss the advantages and disadvantages of all these techniques to provide a concise and reliable guide for readers interested in this active area of investigation. © 2014 Elsevier Inc. All rights reserved.

  19. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

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

  20. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

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

  1. Metabolomic Change Precedes Apple Superficial Scald Symptoms

    USDA-ARS?s Scientific Manuscript database

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

  2. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

    PubMed

    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

  3. Metabolomics of Clostridial Biofuel Production

    SciTech Connect

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

    2015-09-08

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

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

    PubMed

    Gao, Peng; Xu, Guowang

    2015-01-01

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

  5. An LC-MS-based metabolomics approach for exploring urinary metabolome modifications after cocoa consumption.

    PubMed

    Llorach, Rafael; Urpi-Sarda, Mireia; Jauregui, Olga; Monagas, Maria; Andres-Lacueva, Cristina

    2009-11-01

    Cocoa-phytochemicals have been related to the health-benefits of cocoa consumption. Metabolomics has been proposed as a powerful tool to characterize both the intake and the effects on the metabolism of dietary components. Human urine metabolome modifications after single cocoa intake were explored in a randomized, crossed, and controlled trial. After overnight fasting, 10 subjects consumed randomly either a single dose of cocoa powder with milk or water, or milk without cocoa. Urine samples were collected before the ingestion and at 0-6, 6-12, and 12-24-h after test-meals consumption. Samples were analyzed by HPLC-q-ToF, followed by multivariate data analysis. Results revealed an important effect on urinary metabolome during the 24 h after cocoa powder intake. These changes were not influenced by matrix as no global differences were found between cocoa powder consumption with milk or with water. Overall, 27 metabolites related to cocoa-phytochemicals, including alkaloid derivatives, polyphenol metabolites (both host and microbial metabolites) and processing-derived products such as diketopiperazines, were identified as the main contributors to the urinary modifications after cocoa powder intake. These results confirm that metabolomics will contribute to better characterization of the urinary metabolome in order to further explore the metabolism of phytochemicals and its relation with human health.

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

    PubMed

    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.

  7. MVAPACK: a complete data handling package for NMR metabolomics.

    PubMed

    Worley, Bradley; Powers, Robert

    2014-05-16

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

  8. Application of metabolomics technology in the research of Chinese medicine.

    PubMed

    Liu, Ping; Wang, Ping

    2014-04-01

    In recent years, a novel analytical technology, metabolomics is widely used in the modern research of Chinese medicine (CM). Metabolomics adopts a "top-down" strategy to reflect the function of organisms from terminal symptoms of metabolic network and understand metabolic changes of a complete system caused by interventions. As a holistic approach, metabolomics technology, including nuclear magnetic resonance, gas chromatography-mass spectrometry, and liquid chromatography-mass spectrometry, favorable to express the meaning of basic theories of CM, CM syndrome and Chinese herb. Therefore, we believe that metabolomics technology will greatly benefit to development for the research of CM in the light of modern sciences.

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

    PubMed

    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.

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

    PubMed Central

    2015-01-01

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

  11. Dissecting Bottromycin Biosynthesis Using Comparative Untargeted Metabolomics.

    PubMed

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

    2016-08-08

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

  12. Dissecting Bottromycin Biosynthesis Using Comparative Untargeted Metabolomics

    PubMed Central

    Crone, William J. K.; Vior, Natalia M.; Santos‐Aberturas, Javier; Schmitz, Lukas G.; Leeper, Finian J.

    2016-01-01

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

  13. A new exploration of licorice metabolome.

    PubMed

    Rizzato, Giovanni; Scalabrin, Elisa; Radaelli, Marta; Capodaglio, Gabriele; Piccolo, Oreste

    2017-04-15

    The roots and rhizomes of licorice plants (genus Glycyrrhiza L.) are commercially employed, after processing, in confectionery production or as sweetening and flavouring agents in the food, tobacco and beer industries. G. glabra, G. inflata and G. uralensis are the most significant licorice species, often indistinctly used for different productions. Licorice properties are directly related to its chemical composition, which determines the commercial values and the quality of the derived products. In order to better understand the characteristics and properties of each species, a chemical characterization of three species of licorice (G. glabra, G. inflata, G. uralensis) is proposed, through an untargeted metabolomic approach and using high-resolution mass spectrometry. The statistical analysis reveals new possible markers for the analyzed species, and provides a reliable identification of a high number of metabolites, contributing to the characterization of Glycyrrhiza metabolome.

  14. Metabolomic Analysis of Three Mollicute Species

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2016-01-04

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

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

    PubMed Central

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

    2016-01-01

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

  17. Blood Transcriptomics and Metabolomics for Personalized Medicine

    DTIC Science & Technology

    2015-10-31

    66] Roberts LD, Koulman A, Griffin JL. Towards metabolic biomarkers of insulin resis- tance and type 2 diabetes : progress from the metabolome. Lancet...cancer pa- tients, its therapeutic efficiency varies depending on the patient’s breast cancer subtype. This is because trastuzumab targets HER2 (human...largely dependent on mass spectrometry. 3S. Li et al. / Computational and Structural Biotechnology Journal 14 (2016) 1–7Database [29,30], METLIN [31

  18. Data fusion in metabolomic cancer diagnostics.

    PubMed

    Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco; Kjeldahl, Karin; Christensen, Ib Jarle; Brünner, Nils; Lawaetz, Anders Juul

    2013-02-01

    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.

  19. The Metabolomic Strategy in Tuberculosis Therapy.

    PubMed

    Kumar, Nitendra; Shreshtha, Ashwinee Kumar; Patra, Sanjukta

    2017-01-01

    Tuberculosis causes around 1.4 million deaths every year remaining to be a major cause of morbidity and mortality. Mycobacterium tuberculosis is adept at surviving the assault of our immune system, which has perplexed many researchers. Not only are they difficult to treat, but also difficult to detect accurately. The current reservoir of drugs and method to diagnose them is depleting faster than we are able to replace them with newer one. The advances made in the field of metabolomic have opened up a window of opportunities such as identification of new drug and druggable site, prediction of drug toxicity and detection of new biomarkers to accurately diagnose the disease. With its short history of less than two decades, metabolomics has shown very promising future to tackle this concern. Equally important developments in analytical techniques and application of data interpretation have further facilitated the scope of this field. The present review discusses the advances in metabolomic research with an emphasis on tuberculosis diagnosis and therapeutics. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. Metabolomics for Assessment of Nutritional Status

    PubMed Central

    Zivkovic, Angela M.; German, J. Bruce

    2010-01-01

    Purpose of review 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. Recent findings Dysregulation within the principal metabolic organs (e.g. intestine, adipose, skeletal muscle, 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. Summary The first proofs of principle building the knowledge to bring actionable metabolic diagnostics to practice through metabolomics are now appearing. PMID:19584717

  1. Global open data management in metabolomics.

    PubMed

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

    2017-02-01

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

  2. Innovation in Metabolomics to Improve Personalized Healthcare

    PubMed Central

    Cacciatore, Stefano; Loda, Massimo

    2016-01-01

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

  3. Metabolomic profiles of current cigarette smokers.

    PubMed

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

    2017-02-01

    Smoking-related biomarkers for lung cancer and other diseases are needed to enhance early detection strategies and to provide a science base for tobacco product regulation. An untargeted metabolomics approach by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF MS) totaling 957 assays was used in a novel experimental design where 105 current smokers smoked two cigarettes 1 h apart. Blood was collected immediately before and after each cigarette allowing for within-subject replication. Dynamic changes of the metabolomic profiles from smokers' four blood samples were observed and biomarkers affected by cigarette smoking were identified. Thirty-one metabolites were definitively shown to be affected by acute effect of cigarette smoking, uniquely including menthol-glucuronide, the reduction of glutamate, oleamide, and 13 glycerophospholipids. This first time identification of a menthol metabolite in smokers' blood serves as proof-of-principle for using metabolomics to identify new tobacco-exposure biomarkers, and also provides new opportunities in studying menthol-containing tobacco products in humans. Gender and race differences also were observed. Network analysis revealed 12 molecules involved in cancer, notably inhibition of cAMP. These novel tobacco-related biomarkers provide new insights to the effects of smoking which may be important in carcinogenesis but not previously linked with tobacco-related diseases. © 2016 Wiley Periodicals, Inc.

  4. Tracer-based Metabolomics: Concepts and Practices

    PubMed Central

    Lee, W-N. Paul; Wahjudi, Paulin N.; Xu, Jun; Go, Vay Liang

    2010-01-01

    Tracer-based metabolomics is a systems biology tool that combines advances in tracer methodology for physiological studies, high throughput “-omics” technologies and constraint based modeling of metabolic networks. It is different from the commonly known metabolomics or metabonomics in that it is a targeted approach based on a metabolic network model in cells. Because of its complexity, it is the least understood among the various “-omics”. In this review, the development of concepts and practices of tracer-based metabolomics is traced from the early application of radioactive isotopes in metabolic studies to the recent application of stable isotopes and isotopomer analysis using mass spectrometry; and from the modeling of biochemical reactions using flux analysis to the recent theoretical formulation of the constraint based modeling. How these newer experimental methods and concepts of constraint-based modeling approaches can be applied to metabolic studies is illustrated by examples of studies in determining metabolic responses of cells to pharmacological agents and nutrient environment changes. PMID:20713038

  5. Biomarker Discovery and Translation in Metabolomics

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Miller, Marion G

    2007-02-01

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

  7. Tissue and Metabolomic Biomarkers of Recurrent Renal Cell Carcinoma

    DTIC Science & Technology

    2013-04-01

    project. The cumulative data is currently being analyzed with the clinical data in the partnering PIs facility. 15. SUBJECT TERMS Kidney cancer ...American Association of Cancer Research Annual Meeting, Washington, DC, April 2013. Conclusions: We have developed a combined proteomics, metabolomics ...1 AD_________________ Award Number: W81XWH-10-1-0173 TITLE: Tissue and Metabolomic Biomarkers of

  8. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    NASA Astrophysics Data System (ADS)

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    2016-12-01

    Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

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

    ERIC Educational Resources Information Center

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

    2016-01-01

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

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

    ERIC Educational Resources Information Center

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

    2016-01-01

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

  11. Recent developments in liquid-phase separation techniques for metabolomics.

    PubMed

    Ramautar, Rawi; de Jong, Gerhardus J

    2014-04-01

    Metabolomics is the comprehensive analysis of low molecular weight compounds in biological samples such as cells, body fluids and tissues. Comprehensive profiling of metabolites in complex sample matrices with the current analytical toolbox remains a huge challenge. Over the past few years, liquid chromatography-mass spectrometry (LC-MS) and capillary electrophoresis-mass spectrometry (CE-MS) have emerged as powerful complementary analytical techniques in the field of metabolomics. This Review provides an update of the most recent developments in LC-MS and CE-MS for metabolomics. Concerning LC-MS, attention is paid to developments in column technology and miniaturized systems, while strategies are discussed to improve the reproducibility and the concentration sensitivity of CE-MS for metabolomics studies. Novel interfacing techniques for coupling CE to MS are also considered. Representative examples illustrate the potential of the recent developments in LC-MS and CE-MS for metabolomics. Finally, some conclusions and perspectives are provided.

  12. Error Analysis and Propagation in Metabolomics Data Analysis.

    PubMed

    Moseley, Hunter N B

    2013-01-01

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

  13. Data in support of enhancing metabolomics research through data mining.

    PubMed

    Martínez-Arranz, Ibon; Mayo, Rebeca; Pérez-Cormenzana, Miriam; Mincholé, Itziar; Salazar, Lorena; Alonso, Cristina; Mato, José M

    2015-06-01

    Metabolomics research has evolved considerably, particularly during the last decade. Over the course of this evolution, the interest in this 'omic' discipline is now more evident than ever. However, the future of metabolomics will depend on its capability to find biomarkers. For that reason, data mining constitutes a challenging task in metabolomics workflow. This work has been designed in support of the research article entitled "Enhancing metabolomics research through data mining", which proposed a methodological data handling guideline. An aging research in healthy population was used as a guiding thread to illustrate this process. Here we provide a further interpretation of the obtained statistical results. We also focused on the importance of graphical visualization tools as a clue to understand the most common univariate and multivariate data analyses applied in metabolomics.

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

    PubMed

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

    2017-09-26

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

  15. Applying metabolomics to uncover novel biology in ARDS.

    PubMed

    Rogers, Angela J; Matthay, Michael A

    2014-06-01

    A better understanding of the pathogenesis and the resolution of the acute respiratory distress syndrome (ARDS) is needed. Although some progress has been made with the use of protein biomarkers and candidate gene studies in understanding the pathobiology of ARDS, we propose that new studies that measure the chemical breakdown products of cellular metabolism (metabolomics) may provide new insights into ARDS, in part because metabolomics targets a later point in the genomics cascade than is possible with studies of DNA, RNA, and protein biomarkers. Technological advances have made large-scale metabolomic profiling increasingly feasible. Metabolomic approaches have already achieved novel insights in nonpulmonary diseases such as diabetes mellitus and malignancy, as well as in sepsis, a major risk factor for developing ARDS. Metabolomic profiling is a promising approach to identify novel pathways in both patients at risk for developing ARDS as well as in the early phase of established ARDS.

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

    PubMed Central

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

    2017-01-01

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

  17. Development of quantitative metabolomics for Pichia pastoris.

    PubMed

    Carnicer, Marc; Canelas, André B; Ten Pierick, Angela; Zeng, Zhen; van Dam, Jan; Albiol, Joan; Ferrer, Pau; Heijnen, Joseph J; van Gulik, Walter

    2012-04-01

    Accurate, reliable and reproducible measurement of intracellular metabolite levels has become important for metabolic studies of microbial cell factories. A first critical step for metabolomic studies is the establishment of an adequate quenching and washing protocol, which ensures effective arrest of all metabolic activity and removal of extracellular metabolites, without causing leakage of metabolites from the cells. Five different procedures based on cold methanol quenching and cell separation by filtration were tested for metabolomics of Pichia pastoris regarding methanol content and temperature of the quenching solution as key parameters. Quantitative evaluation of these protocols was carried out through mass balance analysis, based on metabolite measurements in all sample fractions, those are whole broth, quenched and washed cells, culture filtrate and quenching and washing solution. Finally, the optimal method was used to study the time profiles of free amino acid and central carbon metabolism intermediates in glucose-limited chemostat cultures. Acceptable recoveries (>90%) were obtained for all quenching procedures tested. However, quenching at -27°C in 60% v/v methanol performed slightly better in terms of leakage minimization. We could demonstrate that five residence times under glucose limitation are enough to reach stable intracellular metabolite pools. Moreover, when comparing P. pastoris and S. cerevisiae metabolomes, under the same cultivation conditions, similar metabolite fingerprints were found in both yeasts, except for the lower glycolysis, where the levels of these metabolites in P. pastoris suggested an enzymatic capacity limitation in that part of the metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0308-1) contains supplementary material, which is available to authorized users.

  18. Metabolomic signatures of aggressive prostate cancer.

    PubMed

    McDunn, Jonathan E; Li, Zhen; Adam, Klaus-Peter; Neri, Bruce P; Wolfert, Robert L; Milburn, Michael V; Lotan, Yair; Wheeler, Thomas M

    2013-10-01

    Current diagnostic techniques have increased the detection of prostate cancer; however, these tools inadequately stratify patients to minimize mortality. Recent studies have identified a biochemical signature of prostate cancer metastasis, including increased sarcosine abundance. This study examined the association of tissue metabolites with other clinically significant findings. A state of the art metabolomics platform analyzed prostatectomy tissues (331 prostate tumor, 178 cancer-free prostate tissues) from two independent sites. Biochemicals were analyzed by gas chromatography-mass spectrometry and ultrahigh performance liquid chromatography-tandem mass spectrometry. Statistical analyses identified metabolites associated with cancer aggressiveness: Gleason score, extracapsular extension, and seminal vesicle and lymph node involvement. Prostate tumors had significantly altered metabolite profiles compared to cancer-free prostate tissues, including biochemicals associated with cell growth, energetics, stress, and loss of prostate-specific biochemistry. Many metabolites were further associated with clinical findings of aggressive disease. Aggressiveness-associated metabolites stratified prostate tumor tissues with high abundances of compounds associated with normal prostate function (e.g., citrate and polyamines) from more clinically advanced prostate tumors. These aggressive prostate tumors were further subdivided by abundance profiles of metabolites including NAD+ and kynurenine. When added to multiparametric nomograms, metabolites improved prediction of organ confinement (AUROC from 0.53 to 0.62) and 5-year recurrence (AUROC from 0.53 to 0.64). These findings support and extend earlier metabolomic studies in prostate cancer and studies where metabolic enzymes have been associated with carcinogenesis and/or outcome. Furthermore, these data suggest that panels of analytes may be valuable to translate metabolomic findings to clinically useful diagnostic tests

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

    PubMed

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

    2015-06-02

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

  20. Metabolomics of cocaine: implications in toxicity.

    PubMed

    Dinis-Oliveira, Ricardo Jorge

    2015-01-01

    Cocaine is the most commonly used illicit drug among those seeking care in Emergency Departments or drug detoxification centers. Cocaine, chemically known as benzoylmethylecgonine, is a naturally occurring substance found in the leaves of the Erythroxylum coca plant. The pharmacokinetics of cocaine 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 cocaine, namely by presenting all known metabolites of cocaine and their roles in the cocaine-mediated toxic effects.

  1. The use of metabolomics in population-based research.

    PubMed

    Su, L Joseph; Fiehn, Oliver; Maruvada, Padma; Moore, Steven C; O'Keefe, Stephen J; Wishart, David S; Zanetti, Krista A

    2014-11-01

    The NIH has made a significant commitment through the NIH Common Fund's Metabolomics Program to build infrastructure and capacity for metabolomics research, which should accelerate the field. Given this investment, it is the ideal time to start planning strategies to capitalize on the infrastructure being established. An obvious gap in the literature relates to the effective use of metabolomics in large-population studies. Although published reports from population-based studies are beginning to emerge, the number to date remains relatively small. Yet, there is great potential for using metabolomics in population-based studies to evaluate the effects of nutritional, pharmaceutical, and environmental exposures (the "exposome"); conduct risk assessments; predict disease development; and diagnose diseases. Currently, the majority of the metabolomics studies in human populations are in nutrition or nutrition-related fields. This symposium provided a timely venue to highlight the current state-of-science on the use of metabolomics in population-based research. This session provided a forum at which investigators with extensive experience in performing research within large initiatives, multi-investigator grants, and epidemiology consortia could stimulate discussion and ideas for population-based metabolomics research and, in turn, improve knowledge to help devise effective methods of health research. © 2014 American Society for Nutrition.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-06-02

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

  4. Metabolomics: the "new clinical chemistry" for personalized neonatal medicine.

    PubMed

    Antonucci, R; Atzori, L; Barberini, L; Fanos, V

    2010-06-01

    Metabolomics is a new approach based on the systematic study of the full complement of metabolites in a biological sample. This technology consists of two sequential steps: (1) an experimental technique, based on mass spectrometry or nuclear magnetic resonance (NMR) spectroscopy, designed to profile low molecular weight compounds, and (2) multivariate data analysis. Metabolomic analysis of biofluids or tissues has been successfully used in the fields of physiology, diagnostics, functional genomics, pharmacology, toxicology and nutrition. Recent studies have evaluated how physiological variables or pathological conditions can affect metabolomic profiles of different biofluids in pediatric populations. Little is known about the overall metabolic status of the term and preterm neonate. On the other hand, the management of sick or preterm newborns might be improved if more information on perinatal/neonatal maturational processes and their metabolic background were available. At present, the use of metabolomics in Neonatology is still in the pioneering phase. Meaningful diagnostic information and simple, non-invasive collection techniques make urine a particularly suitable biofluid for metabolomic approach in neonatal medicine. Using NMR-based metabolomic analysis of urine, distinct metabolic patterns have been shown to be associated with different classes of gestational age in a population of preterm and term infants. Together with genomics and proteomics, metabolomics appears to be a promising tool in Neonatology for the monitoring of postnatal metabolic maturation, the identification of biomarkers as early predictors of outcome, the diagnosis and monitoring of various diseases and the "tailored" management of neonatal disorders.

  5. Challenges of metabolomics in human gut microbiota research.

    PubMed

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

    2016-08-01

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

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

    PubMed Central

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-01-01

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

  7. Glucose enhances tilapia against Edwardsiella tarda infection through metabolome reprogramming.

    PubMed

    Zeng, Zhao-Hai; Du, Chao-Chao; Liu, Shi-Rao; Li, Hui; Peng, Xuan-Xian; Peng, Bo

    2017-02-01

    We have recently reported that the survival of tilapia, Oreochromis niloticus, during Edwardsiella tarda infection is tightly associated with their metabolome, where the survived O. niloticus has distinct metabolomic profile to dying O. niloticus. Glucose is the key metabolite to distinguish the survival- and dying-metabolome. More importantly, exogenous administration of glucose to the fish greatly enhances their survival for the infection, indicating the functional roles of glucose in metabolome repurposing, known as reprogramming metabolomics. However, the underlying information for the reprogramming is not yet available. Here, GC/MS based metabolomics is used to understand the mechanisms by which how exogenous glucose elevates O. niloticus, anti-infectious ability to E. tarda. Results showed that exogenous glucose promotes stearic acid and palmitic acid biosynthesis but attenuates TCA cycle to potentiate O. niloticus against bacterial infection, which is confirmed by the fact that exogenous stearic acid increases immune protection in O. niloticus against E. tarda infection in a manner of Mx protein. These results indicate that exogenous glucose reprograms O. niloticus anti-infective metabolome that characterizes elevation of stearic acid and palmitic acid and attenuation of the TCA cycle. Therefore, our results proposed a novel mechanism that glucose promotes unsaturated fatty acid biosynthesis to cope with infection, thereby highlighting a potential way of enhancing fish immunity in aquaculture. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    PubMed Central

    Fearnley, Liam G; Inouye, Michael

    2016-01-01

    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. PMID:27118561

  9. Technical Challenges in Mass Spectrometry-Based Metabolomics

    PubMed Central

    Matsuda, Fumio

    2016-01-01

    Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10–100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism. PMID:27900235

  10. The Human Blood Metabolome-Transcriptome Interface

    PubMed Central

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

    2015-01-01

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

  11. Serum Metabolomics of Burkitt Lymphoma Mouse Models

    PubMed Central

    Yang, Fengmin; Du, Jie; Zhang, Hong; Ruan, Guorui; Xiang, Junfeng; Wang, Lixia; Sun, Hongxia; Guan, Aijiao; Shen, Gang; Liu, Yan; Guo, Xiaomeng; Li, Qian; Tang, Yalin

    2017-01-01

    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. PMID:28129369

  12. Metabolomic analyses for atherosclerosis, diabetes, and obesity

    PubMed Central

    2013-01-01

    Insulin resistance associated with type 2 diabetes mellitus (T2DM), obesity, and atherosclerosis is a global health problem. A portfolio of abnormalities of metabolic and vascular homeostasis accompanies T2DM and obesity, which are believed to conspire to lead to accelerated atherosclerosis and premature death. The complexity of metabolic changes in the diseases presents challenges for a full understanding of the molecular pathways contributing to the development of these diseases. The recent advent of new technologies in this area termed “Metabolomics” may aid in comprehensive metabolic analysis of these diseases. Therefore, metabolomics has been extensively applied to the metabolites of T2DM, obesity, and atherosclerosis not only for the assessment of disease development and prognosis, but also for the biomarker discovery of disease diagnosis. Herein, we summarize the recent applications of metabolomics technology and the generated datasets in the metabolic profiling of these diseases, in particular, the applications of these technologies to these diseases at the cellular, animal models, and human disease levels. In addition, we also extensively discuss the mechanisms linking the metabolic profiling in insulin resistance, T2DM, obesity, and atherosclerosis, with a particular emphasis on potential roles of increased production of reactive oxygen species (ROS) and mitochondria dysfunctions. PMID:24252331

  13. Radiation Metabolomics: Current Status and Future Directions

    PubMed Central

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

    2016-01-01

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

  14. Monolithic columns in plant proteomics and metabolomics.

    PubMed

    Rigobello-Masini, Marilda; Penteado, José Carlos Pires; Masini, Jorge Cesar

    2013-03-01

    Since "omics" techniques emerged, plant studies, from biochemistry to ecology, have become more comprehensive. Plant proteomics and metabolomics enable the construction of databases that, with the help of genomics and informatics, show the data obtained as a system. Thus, all the constituents of the system can be seen with their interactions in both space and time. For instance, perturbations in a plant ecosystem as a consequence of application of herbicides or exposure to pollutants can be predicted by using information gathered from these databases. Analytical chemistry has been involved in this scientific evolution. Proteomics and metabolomics are emerging fields that require separation, identification, and quantification of proteins, peptides, and small molecules of metabolites in complex biological samples. The success of this work relies on efficient chromatographic and electrophoretic techniques, and on mass spectrometric detection. This paper reviews recent developments in the use of monolithic columns, focusing on their applications in "top-down" and "bottom-up" approaches, including their use as supports for immobilization of proteolytic enzymes and their use in two-dimensional and multidimensional chromatography. Whereas polymeric columns have been predominantly used for separation of proteins and polypeptides, silica-based monoliths have been more extensively used for separation of small molecules of metabolites. Representative applications in proteomics and in analysis of plant metabolites are given and summarized in tables.

  15. Metabolomics reveals the perturbations in the metabolome of Caenorhabditis elegans exposed to titanium dioxide nanoparticles.

    PubMed

    Ratnasekhar, Ch; Sonane, Madhavi; Satish, Aruna; Mudiam, Mohana Krishna Reddy

    2015-01-01

    The increasing use of nanotechnology in our daily life can have many unintended effects and pose adverse impact on human health, environment and ecosystems. Wider application of engineered nanoparticles, especially TiO2 nanoparticles (TiO2 NP) necessitates the understanding of toxicity and mechanism of action. Metabolomics provides a unique opportunity to find out biomarkers of nanoparticles exposure, which leads to the identification of cellular pathways and their biological mechanisms. Gas chromatography mass spectrometry (GC-MS)-based metabolomics approach was used in the present study to understand the toxicity of sub-lethal concentrations (7.7 and 38.5 µg/ml) of TiO2 NP (<25 nm) in well-known, soil nematode Caenorhabditis elegans (C. elegans). Multivariate pattern recognition analysis reflected the perturbations in the metabolism (amino acids, organic acids, sugars) of C. elegans on exposure to TiO2 NP. The biological pathways affected due to the exposure of TiO2 NP were identified, among them mainly affected pathways are tricarboxylic acid (TCA) cycle, arachidonic acid metabolism and glyoxalate dicarobxylate metabolism. The manifestation of differential metabolic profile in organism exposed to TiO2 (NP or bulk particle) was witnessed as an effect on reproduction. The present study demonstrates that metabolomics can be employed as a tool to understand the potential toxicity of nanoparticles in terms of organism-environment interactions as well as in assessing the organism function at the molecular level.

  16. Determination of antiprotozoal drug mechanisms by metabolomics approaches.

    PubMed

    Creek, Darren J; Barrett, Michael P

    2014-01-01

    The discovery, development and optimal utilization of pharmaceuticals can be greatly enhanced by knowledge of their modes of action. However, many drugs currently on the market act by unknown mechanisms. Untargeted metabolomics offers the potential to discover modes of action for drugs that perturb cellular metabolism. Development of high resolution LC-MS methods and improved data analysis software now allows rapid detection of drug-induced changes to cellular metabolism in an untargeted manner. Several studies have demonstrated the ability of untargeted metabolomics to provide unbiased target discovery for antimicrobial drugs, in particular for antiprotozoal agents. Furthermore, the utilization of targeted metabolomics techniques has enabled validation of existing hypotheses regarding antiprotozoal drug mechanisms. Metabolomics approaches are likely to assist with optimization of new drug candidates by identification of drug targets, and by allowing detailed characterization of modes of action and resistance of existing and novel antiprotozoal drugs.

  17. NMR metabolomics of human blood and urine in disease research.

    PubMed

    Duarte, Iola F; Diaz, Sílvia O; Gil, Ana M

    2014-05-01

    This paper reviews the main applications of NMR metabolomics of blood and urine in disease research, over the last 5 years. The broad range of disease types addressed attests the increasing interest within the academic and medical communities to explore the recognised potential of metabolomics to (1) provide insight into underlying disease pathogenesis and (2) unveil new metabolic markers for disease diagnosis and follow up. Importantly, most recent studies reveal an increasing awareness of possible limitations and pitfalls of the metabolomics approach, together with efforts for improved study design and statistical validation, which are crucial requisites for the sound development of NMR metabolomics and its progress into the clinical setting. Copyright © 2013 Elsevier B.V. All rights reserved.

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

    NASA Image and Video Library

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

  19. Metabolomic determinants of necrotizing enterocolitis in preterm piglets

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

    Zhang, Bo; Powers, Robert

    2012-06-01

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

  1. The Role of Metabolomics in Brain Metabolism Research.

    PubMed

    Ivanisevic, Julijana; Siuzdak, Gary

    2015-09-01

    This special edition of the Journal of Neuroimmune Pharmacology focuses on the leading edge of metabolomics in brain metabolism research. The topics covered include a metabolomic field overview and the challenges in neuroscience metabolomics. The workflow and utility of different analytical platforms to profile complex biological matrices that include biofluids, brain tissue and cells, are shown in several case studies. These studies demonstrate how global and targeted metabolite profiling can be applied to distinguish disease stages and to understand the effects of drug action on the central nervous system (CNS). Finally, we discuss the importance of metabolomics to advance the understanding of brain function that includes ligand-receptor interactions and new insights into the mechanisms of CNS disorders.

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

    EPA Science Inventory

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

  3. Analysis of bacterial biofilms using NMR-based metabolomics

    PubMed Central

    Zhang, Bo; Powers, Robert

    2013-01-01

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

  4. METABOLOMICS IN SMALL FISH TOXICOLOGY AND ECOLOGICAL RISK ASSESSMENTS

    EPA Science Inventory

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

  5. Applying Metabolomics to differentiate amphibian responses to multiple stressors

    EPA Science Inventory

    Introduction/Objectives/Methods One of the biggest challenges in ecological risk assessment is determining the impact of multiple stressors on individual organisms and populations in ‘real world’ scenarios. Emerging ‘omic technologies, notably, metabolomics, pr...

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

    USDA-ARS?s Scientific Manuscript database

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

  7. International NMR-based Environmental Metabolomics Intercomparison Exercise

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  9. Applying Metabolomics to differentiate amphibian responses to multiple stressors

    EPA Science Inventory

    Introduction/Objectives/Methods One of the biggest challenges in ecological risk assessment is determining the impact of multiple stressors on individual organisms and populations in ‘real world’ scenarios. Emerging ‘omic technologies, notably, metabolomics, pr...

  10. Field-based Metabolomics for Assessing Contaminated Surface Waters

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  12. Field-based Metabolomics for Assessing Contaminated Surface Waters

    EPA Science Inventory

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

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

    PubMed Central

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

    2014-01-01

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

  14. International NMR-based Environmental Metabolomics Intercomparison Exercise

    EPA Science Inventory

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

  15. METABOLOMICS IN SMALL FISH TOXICOLOGY AND ECOLOGICAL RISK ASSESSMENTS

    EPA Science Inventory

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

  16. Dissemination of metabolomics results: role of MetaboLights and COSMOS.

    PubMed

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

    2013-05-17

    With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information.

  17. Plant metabolomics is not ripe for environmental risk assessment.

    PubMed

    Hall, Robert D; de Maagd, Ruud A

    2014-08-01

    Metabolomics separates and detects small molecules and helps determine the composition of plant materials. This makes it appear to be a possible contributor to environmental risk assessment (ERA) of transgenic plants. Here we argue that, despite important advances in the technology, limited annotation and our limited knowledge of the role of metabolites in plant-environment interactions means that metabolomics is not yet ripe for ERA. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2014-06-01

    The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health. © 2014 American Society for Nutrition.

  19. Metabolomics and Its Application to Acute Lung Diseases

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2012-01-01

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

  1. Metabolomics as a Driver in Advancing Precision Medicine in Sepsis.

    PubMed

    Eckerle, Michelle; Ambroggio, Lilliam; Puskarich, Michael A; Winston, Brent; Jones, Alan E; Standiford, Theodore J; Stringer, Kathleen A

    2017-09-01

    The objective of this review is to explain the science of metabolomics-a science of systems biology that measures and studies endogenous small molecules (metabolites) that are present in a single biological sample-and its application to the diagnosis and treatment of sepsis. In addition, we discuss how discovery through metabolomics can contribute to the development of precision medicine targets for this complex disease state and the potential avenues for those new discoveries to be applied in the clinical environment. A nonsystematic literature review was performed focusing on metabolomics, pharmacometabolomics, and sepsis. Human (adult and pediatric) and animal studies were included. Metabolomics has been investigated in the diagnosis, prognosis, and risk stratification of sepsis, as well as for the identification of drug target opportunities. Metabolomics elucidates a new level of detail when compared with other systems biology sciences, with regard to the metabolites that are most relevant in the pathophysiology of sepsis, as well as highlighting specific biochemical pathways at work in sepsis. Metabolomics also highlights biochemical differences between sepsis survivors and nonsurvivors at a level of detail greater than that demonstrated by genomics, transcriptomics, or proteomics, potentially leading to actionable targets for new therapies. The application of pharmacometabolomics and its integration with other systems pharmacology to sepsis therapeutics could be particularly helpful in differentiating drug responders and nonresponders and furthering knowledge of mechanisms of drug action and response. The accumulated literature on metabolomics suggests it is a viable tool for continued discovery around the pathophysiology, diagnosis and prognosis, and treatment of sepsis in both adults and children, and it provides a greater level of biochemical detail and insight than other systems biology approaches. However, the clinical application of metabolomics in

  2. Solving the differential biochemical Jacobian from metabolomics covariance data.

    PubMed

    Nägele, Thomas; Mair, Andrea; Sun, Xiaoliang; Fragner, Lena; Teige, Markus; Weckwerth, Wolfram

    2014-01-01

    High-throughput molecular analysis has become an integral part in organismal systems biology. In contrast, due to a missing systematic linkage of the data with functional and predictive theoretical models of the underlying metabolic network the understanding of the resulting complex data sets is lacking far behind. Here, we present a biomathematical method addressing this problem by using metabolomics data for the inverse calculation of a biochemical Jacobian matrix, thereby linking computer-based genome-scale metabolic reconstruction and in vivo metabolic dynamics. The incongruity of metabolome coverage by typical metabolite profiling approaches and genome-scale metabolic reconstruction was solved by the design of superpathways to define a metabolic interaction matrix. A differential biochemical Jacobian was calculated using an approach which links this metabolic interaction matrix and the covariance of metabolomics data satisfying a Lyapunov equation. The predictions of the differential Jacobian from real metabolomic data were found to be correct by testing the corresponding enzymatic activities. Moreover it is demonstrated that the predictions of the biochemical Jacobian matrix allow for the design of parameter optimization strategies for ODE-based kinetic models of the system. The presented concept combines dynamic modelling strategies with large-scale steady state profiling approaches without the explicit knowledge of individual kinetic parameters. In summary, the presented strategy allows for the identification of regulatory key processes in the biochemical network directly from metabolomics data and is a fundamental achievement for the functional interpretation of metabolomics data.

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

    PubMed

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

    2014-01-02

    Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

  4. Solving the Differential Biochemical Jacobian from Metabolomics Covariance Data

    PubMed Central

    Nägele, Thomas; Mair, Andrea; Sun, Xiaoliang; Fragner, Lena; Teige, Markus; Weckwerth, Wolfram

    2014-01-01

    High-throughput molecular analysis has become an integral part in organismal systems biology. In contrast, due to a missing systematic linkage of the data with functional and predictive theoretical models of the underlying metabolic network the understanding of the resulting complex data sets is lacking far behind. Here, we present a biomathematical method addressing this problem by using metabolomics data for the inverse calculation of a biochemical Jacobian matrix, thereby linking computer-based genome-scale metabolic reconstruction and in vivo metabolic dynamics. The incongruity of metabolome coverage by typical metabolite profiling approaches and genome-scale metabolic reconstruction was solved by the design of superpathways to define a metabolic interaction matrix. A differential biochemical Jacobian was calculated using an approach which links this metabolic interaction matrix and the covariance of metabolomics data satisfying a Lyapunov equation. The predictions of the differential Jacobian from real metabolomic data were found to be correct by testing the corresponding enzymatic activities. Moreover it is demonstrated that the predictions of the biochemical Jacobian matrix allow for the design of parameter optimization strategies for ODE-based kinetic models of the system. The presented concept combines dynamic modelling strategies with large-scale steady state profiling approaches without the explicit knowledge of individual kinetic parameters. In summary, the presented strategy allows for the identification of regulatory key processes in the biochemical network directly from metabolomics data and is a fundamental achievement for the functional interpretation of metabolomics data. PMID:24695071

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

    PubMed

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

    2016-06-21

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

  6. The metabolomics of carotenoids in engineered cell factory.

    PubMed

    Liu, Guan-Nan; Zhu, Yue-Hui; Jiang, Jian-Guo

    2009-07-01

    Carotenoids such as beta-carotene, lycopene, and antheraxanthin have plenty of scientific and commercial value. The comprehensive investigation of carotenoids drives people to improve and develop all kinds of analytical techniques to approach or even achieve "versatile" analysis. The metabolic engineering efforts in plants and algae have progressed rapidly, aiming to enable the use of plants and algae as "cell factories" for producing specific or novel carotenoids, such as beta-carotene (provitamin A) in Gold rice, while the emerging technologies of metabolomics support it by providing comprehensive analysis of carotenoids biochemical characterizations. This review describes metabolomics as a high-throughput platform to study carotenoids, including the engineering methods in the plants or algae, the bioinformatics for metabolomics, and the metabolomics of carotenoids in engineered cell factory. Modern systems biology tools, together with the development of genomics and metabolomics databases, will dramatically facilitate the advancement of our knowledge in gene-to-metabolite networks in plants. Metabolomics accompanying genomics, transcriptomics, and proteomics as well as bioinformatics facilitate metabolic engineering efforts towards designing superior biocatalysts in cell factories. Ongoing advances in biological techniques coupled with crucial metabolic networks will further promote plants and algae as attractive platforms for the production of numerous high-value compounds such as carotenoids.

  7. Metabolomics of Head and Neck Cancer: A Mini-Review

    PubMed Central

    Shin, Jae M.; Kamarajan, Pachiyappan; Fenno, J. Christopher; Rickard, Alexander H.; Kapila, Yvonne L.

    2016-01-01

    Metabolomics is used in systems biology to enhance the understanding of complex disease processes, such as cancer. Head and neck cancer (HNC) is an epithelial malignancy that arises in the upper aerodigestive tract and affects more than half a million people worldwide each year. Recently, significant effort has focused on integrating multiple “omics” technologies for oncological research. In particular, research has been focused on identifying tumor-specific metabolite profiles using different sample types (biological fluids, cells and tissues) and a variety of metabolomic platforms and technologies. With our current understanding of molecular abnormalities of HNC, the addition of metabolomic studies will enhance our knowledge of the pathogenesis of this disease and potentially aid in the development of novel strategies to prevent and treat HNC. In this review, we summarize the proposed hypotheses and conclusions from publications that reported findings on the metabolomics of HNC. In addition, we address the potential influence of host-microbe metabolomics in cancer. From a systems biology perspective, the integrative use of genomics, transcriptomics and proteomics will be extremely important for future translational metabolomic-based research discoveries. PMID:27877135

  8. Recent advances in metabolomics in neurological disease, and future perspectives.

    PubMed

    Zhang, Ai-hua; Sun, Hui; Wang, Xi-jun

    2013-10-01

    Discovery of clinically relevant biomarkers for diseases has revealed metabolomics has potential advantages that classical diagnostic approaches do not. The great asset of metabolomics is that it enables assessment of global metabolic profiles of biofluids and discovery of biomarkers distinguishing disease status, with the possibility of enhancing clinical diagnostics. Most current clinical chemistry tests rely on old technology, and are neither sensitive nor specific for a particular disease. Clinical diagnosis of major neurological disorders, for example Alzheimer's disease and Parkinson's disease, on the basis of current clinical criteria is unsatisfactory. Emerging metabolomics is a powerful technique for discovering novel biomarkers and biochemical pathways to improve diagnosis, and for determination of prognosis and therapy. Identifying multiple novel biomarkers for neurological diseases has been greatly enhanced with recent advances in metabolomics that are more accurate than routine clinical practice. Cerebrospinal fluid (CSF), which is known to be a rich source of small-molecule biomarkers for neurological and neurodegenerative diseases, and is in close contact with diseased areas in neurological disorders, could potentially be used for disease diagnosis. Metabolomics will drive CSF analysis, facilitate and improve the development of disease treatment, and result in great benefits to public health in the long-term. This review covers different aspects of CSF metabolomics and discusses their significance in the postgenomic era, emphasizing the potential importance of endogenous small-molecule metabolites in this emerging field.

  9. Metabolomics: current state and evolving methodologies and tools.

    PubMed

    Oldiges, Marco; Lütz, Stephan; Pflug, Simon; Schroer, Kirsten; Stein, Nadine; Wiendahl, Christiane

    2007-09-01

    In recent years, metabolomics developed to an accepted and valuable tool in life sciences. Substantial improvements of analytical hardware allow metabolomics to run routinely now. Data are successfully used to investigate genotype-phenotype relations of strains and mutants. Metabolomics facilitates metabolic engineering to optimise mircoorganisms for white biotechnology and spreads to the investigation of biotransformations and cell culture. Metabolomics serves not only as a source of qualitative but also quantitative data of intra-cellular metabolites essential for the model-based description of the metabolic network operating under in vivo conditions. To collect reliable metabolome data sets, culture and sampling conditions, as well as the cells' metabolic state, are crucial. Hence, application of biochemical engineering principles and method standardisation efforts become important. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical and regulatory networks and, even more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This knowledge will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells.

  10. Brain Region Mapping using Global Metabolomics

    PubMed Central

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

    2014-01-01

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

  11. Brain region mapping using global metabolomics.

    PubMed

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

    2014-11-20

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

  12. Metabolomics study of Populus type propolis.

    PubMed

    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.

  13. Integrated sampling procedure for metabolome analysis.

    PubMed

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

    2006-01-01

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

  14. Secondary Metabolic Pathway-Targeted Metabolomics

    PubMed Central

    Vizcaino, Maria I.; Crawford, Jason M.

    2016-01-01

    This chapter provides step-by-step methods for building secondary metabolic pathway-targeted molecular networks to assess microbial natural product biosynthesis at a systems level and to aid in downstream natural product discovery efforts. Methods described include high-resolution mass spectrometry (HRMS)-based comparative metabolomics, pathway-targeted tandem MS (MS/MS) molecular networking, and isotopic labeling for the elucidation of natural products encoded by orphan biosynthetic pathways. The metabolomics network workflow covers the following six points: (1) method development, (2) bacterial culture growth and organic extraction, (3) HRMS data acquisition and analysis, (4) pathway-targeted MS/MS data acquisition, (5) mass spectral network building, and (6) network enhancement. This chapter opens with a discussion on the practical considerations of natural product extraction, chromatographic processing, and enhanced detection of the analytes of interest within complex organic mixtures using liquid chromatography (LC)-HRMS. Next, we discuss the utilization of a chemometric platform, focusing on Agilent Mass Profiler Professional software, to run MS-based differential analysis between sample groups and controls to acquire a unique set of molecular features that are dependent on the presence of a secondary metabolic pathway. Using this unique list of molecular features, the chapter then details targeted MS/MS acquisition for subsequent pathway-dependent network clustering through the online Global Natural Products Social Molecular Networking (GnPS) platform. Genetic information, ionization intensities, isotopic labeling, and additional experimental data can be mapped onto the pathway-dependent network, facilitating systems biosynthesis analyses. The finished product will provide a working molecular network to assess experimental perturbations and guide novel natural product discoveries. PMID:26831709

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    PubMed

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

    2009-03-01

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

  3. Metabolomic Profiling in LRRK2-Related Parkinson's Disease

    PubMed Central

    Aasly, Jan O.; White, Linda R.; Matson, Wayne R.; Henchcliffe, Claire; Beal, M. Flint; Bogdanov, Mikhail

    2009-01-01

    Background Mutations in LRRK2 gene represent the most common known genetic cause of Parkinson's disease (PD). Methodology/Principal Findings We used metabolomic profiling to identify biomarkers that are associated with idiopathic and LRRK2 PD. We compared plasma metabolomic profiles of patients with PD due to the G2019S LRRK2 mutation, to asymptomatic family members of these patients either with or without G2019S LRRK2 mutations, and to patients with idiopathic PD, as well as non-related control subjects. We found that metabolomic profiles of both idiopathic PD and LRRK2 PD subjects were clearly separated from controls. LRRK2 PD patients had metabolomic profiles distinguishable from those with idiopathic PD, and the profiles could predict whether the PD was secondary to LRRK2 mutations or idiopathic. Metabolomic profiles of LRRK2 PD patients were well separated from their family members, but there was a slight overlap between family members with and without LRRK2 mutations. Both LRRK2 and idiopathic PD patients showed significantly reduced uric acid levels. We also found a significant decrease in levels of hypoxanthine and in the ratios of major metabolites of the purine pathway in plasma of PD patients. Conclusions/Significance These findings show that LRRK2 patients with the G2019S mutation have unique metabolomic profiles that distinguish them from patients with idiopathic PD. Furthermore, asymptomatic LRRK2 carriers can be separated from gene negative family members, which raises the possibility that metabolomic profiles could be useful in predicting which LRRK2 carriers will eventually develop PD. The results also suggest that there are aberrations in the purine pathway in PD which may occur upstream from uric acid. PMID:19847307

  4. [Gastroenterological Cancer Diagnosis by Metabolomics-Discovery of Pancreatic Cancer Biomarker].

    PubMed

    Yoshida, Masaru; Nishiumi, Shin; Azuma, Takeshi

    2015-04-01

    The field of omics involves comprehensive investigations based on genomics, transcriptomics, proteomics, and metabolomics, and omics studies have developed rapidly. Metabolomics, metabolome analysis, involves technology to analyze the concentrations of low-molecular-weight metabolites comprehensively, and has recently rapidly developed along with improvements in analytical technology. Therefore, metabolome analysis is just beginning to be applied to not only food science and environmental research fields but also medical research. In the medical research field, especially, metabolome analysis plays an important role in novel disease biomarker discovery. The metabolome represents the endpoint of the omics cascade and, therefore, is considered to be closer to the phenotype. In addition, there is also a possibility that the metabolome is affected by exogenous factors such as environmental and food factors, as well as endogenous factors such as DNA/mRNA/protein. Therefore, metabolome analysis can be a useful approach for discovering effective biomarkers. Here, we explain the characteristics of metabolome analysis, and also outline metabolome analysis using a liquid chromatograph mass spectrometer (LC-MS), gas chromatograph mass spectrometer (GC-MS), capillary electrophoresis mass spectrometer (CE-MS), and matrix-assisted laser desorption ionization mass spectrometer (MALDI-MS). Then, we describe the findings of studies that used metabolome analysis in an attempt to discover biomarker candidates for pancreatic cancer, and discuss metabolome analysis-based disease diagnosis.

  5. Metabolomics for clinical use and research in chronic kidney disease.

    PubMed

    Hocher, Berthold; Adamski, Jerzy

    2017-03-06

    Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.

  6. A plasma metabolomic signature discloses human breast cancer

    PubMed Central

    Quiles, José Luís; Ramírez-Tortosa, Mari-Carmen; Sol, Joaquim; Ruiz-Sanjuan, Maria; Fernandez, Mónica; de la Torre Cabrera, Capilla; Ramírez-Tortosa, Cesar; Granados-Principal, Sergio; Sánchez-Rovira, Pedro; Pamplona, Reinald

    2017-01-01

    Purpose Metabolomics is the comprehensive global study of metabolites in biological samples. In this retrospective pilot study we explored whether serum metabolomic profile can discriminate the presence of human breast cancer irrespective of the cancer subtype. Methods Plasma samples were analyzed from healthy women (n = 20) and patients with breast cancer after diagnosis (n = 91) using a liquid chromatography-mass spectrometry platform. Multivariate statistics and a Random Forest (RF) classifier were used to create a metabolomics panel for the diagnosis of human breast cancer. Results Metabolomics correctly distinguished between breast cancer patients and healthy control subjects. In the RF supervised class prediction analysis comparing breast cancer and healthy control groups, RF accurately classified 100% both samples of the breast cancer patients and healthy controls. So, the class error for both group in and the out-of-bag error were 0. We also found 1269 metabolites with different concentration in plasma from healthy controls and cancer patients; and basing on exact mass, retention time and isotopic distribution we identified 35 metabolites. These metabolites mostly support cell growth by providing energy and building stones for the synthesis of essential biomolecules, and function as signal transduction molecules. The collective results of RF, significance testing, and false discovery rate analysis identified several metabolites that were strongly associated with breast cancer. Conclusions In breast cancer a metabolomics signature of cancer exists and can be detected in patient plasma irrespectively of the breast cancer type. PMID:28076849

  7. Developing urinary metabolomic signatures as early bladder cancer diagnostic markers.

    PubMed

    Shen, Chong; Sun, Zeyu; Chen, Deying; Su, Xiaoling; Jiang, Jing; Li, Gonghui; Lin, Biaoyang; Yan, Jiajun

    2015-01-01

    Early detection is vital to improve the overall survival rate of bladder cancer (BCa) patients, yet there is a lack of a reliable urine-based assay for early detection of BCa. Urine metabolites represented a potential rich source of biomarkers for BCa. This study aimed to develop a metabolomics approach for high coverage discovery and identification of metabolites in urine samples. Urine samples from 23 early stage BCa patients and 21 healthy volunteers with minimum sample preparations were analyzed by a short 30 min UPLC-HRMS method. We detected and quantified over 9000 unique UPLC-HRMS features, which is more than four times than about 2000 features detected in previous urine metabolomic studies. Furthermore, multivariate OPLS-DA classification models were established to differentiate urine samples from bladder cancer cohort and normal health cohort. We identified three BCa-upregulated metabolites: nicotinuric acid, trehalose, AspAspGlyTrp, and three BCa-downregulated metabolites: inosinic acid, ureidosuccinic acid, GlyCysAlaLys. Finally, analysis of six post-surgery BCa urine samples showed that these BCa-metabolomic features reverted to normal state after tumor removal, suggesting that they reflected metabolomic features associated with BCa. ROC analyses using two linear regression models to combine the identified markers showed a high diagnostic performance for detecting BCa with AUC (area under the ROC curve) values of 0.919 to 0.934. In summary, we developed a high coverage metabolomic approach that has potential for biomarker discovery in cancers.

  8. Recent advances in the application of metabolomics to Alzheimer's Disease.

    PubMed

    Trushina, Eugenia; Mielke, Michelle M

    2014-08-01

    The pathophysiological changes associated with Alzheimer's Disease (AD) begin decades before the emergence of clinical symptoms. Understanding the early mechanisms associated with AD pathology is, therefore, especially important for identifying disease-modifying therapeutic targets. While the majority of AD clinical trials to date have focused on anti-amyloid-beta (Aβ) treatments, other therapeutic approaches may be necessary. The ability to monitor changes in cellular networks that include both Aβ and non-Aβ pathways is essential to advance our understanding of the etiopathogenesis of AD and subsequent development of cognitive symptoms and dementia. Metabolomics is a powerful tool that detects perturbations in the metabolome, a pool of metabolites that reflects changes downstream of genomic, transcriptomic and proteomic fluctuations, and represents an accurate biochemical profile of the organism in health and disease. The application of metabolomics could help to identify biomarkers for early AD diagnosis, to discover novel therapeutic targets, and to monitor therapeutic response and disease progression. Moreover, given the considerable parallel between mouse and human metabolism, the use of metabolomics provides ready translation of animal research into human studies for accelerated drug design. In this review, we will summarize current progress in the application of metabolomics in both animal models and in humans to further understanding of the mechanisms involved in AD pathogenesis. © 2013.

  9. Can NMR solve some significant challenges in metabolomics?

    NASA Astrophysics Data System (ADS)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

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

  10. Can NMR solve some significant challenges in metabolomics?

    PubMed Central

    Gowda, G.A. Nagana; Raftery, Daniel

    2015-01-01

    The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact biospecimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. PMID:26476597

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    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.

  13. A plasma metabolomic signature discloses human breast cancer.

    PubMed

    Jové, Mariona; Collado, Ricardo; Quiles, José Luís; Ramírez-Tortosa, Mari-Carmen; Sol, Joaquim; Ruiz-Sanjuan, Maria; Fernandez, Mónica; de la Torre Cabrera, Capilla; Ramírez-Tortosa, Cesar; Granados-Principal, Sergio; Sánchez-Rovira, Pedro; Pamplona, Reinald

    2017-03-21

    Metabolomics is the comprehensive global study of metabolites in biological samples. In this retrospective pilot study we explored whether serum metabolomic profile can discriminate the presence of human breast cancer irrespective of the cancer subtype. Plasma samples were analyzed from healthy women (n = 20) and patients with breast cancer after diagnosis (n = 91) using a liquid chromatography-mass spectrometry platform. Multivariate statistics and a Random Forest (RF) classifier were used to create a metabolomics panel for the diagnosis of human breast cancer. Metabolomics correctly distinguished between breast cancer patients and healthy control subjects. In the RF supervised class prediction analysis comparing breast cancer and healthy control groups, RF accurately classified 100% both samples of the breast cancer patients and healthy controls. So, the class error for both group in and the out-of-bag error were 0. We also found 1269 metabolites with different concentration in plasma from healthy controls and cancer patients; and basing on exact mass, retention time and isotopic distribution we identified 35 metabolites. These metabolites mostly support cell growth by providing energy and building stones for the synthesis of essential biomolecules, and function as signal transduction molecules. The collective results of RF, significance testing, and false discovery rate analysis identified several metabolites that were strongly associated with breast cancer. In breast cancer a metabolomics signature of cancer exists and can be detected in patient plasma irrespectively of the breast cancer type.

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

    PubMed Central

    Chen, Chi; Kim, Sangyub

    2013-01-01

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

  15. The Progress of Metabolomics Study in Traditional Chinese Medicine Research.

    PubMed

    Wang, Pengcheng; Wang, Qiuhong; Yang, Bingyou; Zhao, Shan; Kuang, Haixue

    2015-01-01

    Traditional Chinese medicine (TCM) has played important roles in health protection and disease treatment for thousands of years in China and has gained the gradual acceptance of the international community. However, many intricate issues, which cannot be explained by traditional methods, still remain, thus, new ideas and technologies are needed. As an emerging system biology technology, the holistic view adopted by metabolomics is similar to that of TCM, which allows us to investigate TCM with complicated conditions and multiple factors in depth. In this paper, we tried to give a timely and comprehensive update about the methodology progression of metabolomics, as well as its applications, in different fields of TCM studies including quality control, processing, safety and efficacy evaluation. The herbs investigated by metabolomics were selected for detailed examination, including Anemarrhena asphodeloides Bunge, Atractylodes macrocephala Kidd, Pinellia ternate, etc.; furthermore, some valuable results have been obtained and summarized. In conclusion, although the study of metabolomics is at the early phase and requires further scrutiny and validation, it still provides bright prospects to dissect the synergistic action of multiple components from TCM. Overall, with the further development of analytical techniques, especially multi-analysis techniques, we expect that metabolomics will greatly promote TCM research and the establishment of international standards, which is beneficial to TCM modernization.

  16. Spectral relative standard deviation: a practical benchmark in metabolomics.

    PubMed

    Parsons, Helen M; Ekman, Drew R; Collette, Timothy W; Viant, Mark R

    2009-03-01

    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 assess the reproducibility of metabolomics datasets that are derived from all the detected metabolites. Here we calculate spectrum-wide relative standard deviations (RSDs; also termed coefficient of variation, CV) for ten metabolomics datasets, spanning a variety of sample types from mammals, fish, invertebrates and a cell line, and display them succinctly as boxplots. We demonstrate multiple applications of spectral RSDs for characterising technical as well as inter-individual biological variation: for optimising metabolite extractions, comparing analytical techniques, investigating matrix effects, and comparing biofluids and tissue extracts from single and multiple species for optimising experimental design. Technical variation within metabolomics datasets, recorded using one- and two-dimensional NMR and mass spectrometry, ranges from 1.6 to 20.6% (reported as the median spectral RSD). Inter-individual biological variation is typically larger, ranging from as low as 7.2% for tissue extracts from laboratory-housed rats to 58.4% for fish plasma. In addition, for some of the datasets we confirm that the spectral RSD values are largely invariant across different spectral processing methods, such as baseline correction, normalisation and binning resolution. In conclusion, we propose spectral RSDs and their median values contained herein as practical benchmarks for metabolomics studies.

  17. Error Analysis and Propagation in Metabolomics Data Analysis

    PubMed Central

    Moseley, Hunter N.B.

    2013-01-01

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

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

    PubMed

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

    2014-09-01

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

  19. The Siderophore Metabolome of Azotobacter vinelandii

    PubMed Central

    Baars, Oliver; Zhang, Xinning

    2015-01-01

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

  20. The Siderophore Metabolome of Azotobacter vinelandii.

    PubMed

    Baars, Oliver; Zhang, Xinning; Morel, François M M; Seyedsayamdost, Mohammad R

    2015-10-09

    In this study, we performed a detailed characterization of the siderophore metabolome, or "chelome," of the agriculturally important and widely studied model organism Azotobacter vinelandii. Using a new high-resolution liquid chromatography-mass spectrometry (LC-MS) approach, we found over 35 metal-binding secondary metabolites, indicative of a vast chelome in A. vinelandii. These include vibrioferrin, a siderophore previously observed only in marine bacteria. Quantitative analyses of siderophore production during diazotrophic growth with different sources and availabilities of Fe showed that, under all tested conditions, vibrioferrin was present at the highest concentration of all siderophores and suggested new roles for vibrioferrin in the soil environment. Bioinformatic searches confirmed the capacity for vibrioferrin production in Azotobacter spp. and other bacteria spanning multiple phyla, habitats, and lifestyles. Moreover, our studies revealed a large number of previously unreported derivatives of all known A. vinelandii siderophores and rationalized their origins based on genomic analyses, with implications for siderophore diversity and evolution. Together, these insights provide clues as to why A. vinelandii harbors multiple siderophore biosynthesis gene clusters. Coupled with the growing evidence for alternative functions of siderophores, the vast chelome in A. vinelandii may be explained by multiple, disparate evolutionary pressures that act on siderophore production. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  1. A Latitudinal Metabolome of the Atlantic Ocean

    NASA Astrophysics Data System (ADS)

    Johnson, W.; Kido Soule, M. C.; Longnecker, K.; Kujawinski, E. B.

    2016-02-01

    Microbial consortia function via the exchange and transformation of small organic molecules or metabolites. These metabolites make up a pool of rapidly cycling organic matter in the ocean that is challenging to characterize due to its low concentrations. We seek to determine the distribution of these molecules and the factors that shape their abundance and flux. Through measurements of the abundance of a core set of metabolites, including nucleic acids, amino acids, sugars, vitamins, and signaling molecules, we gain a real-time snapshot of microbial activity. We used a targeted metabolomics technique to profile metabolite abundance in particulate and dissolved organic matter extracts collected from a 14,000 km transect running from 38˚S to 55˚N in the Western Atlantic Ocean. This extensive dataset is the first of its kind in the Atlantic Ocean and allows us to explore connections among metabolites as well as latitudinal trends in metabolite abundance. We found changes in the intracellular abundance of certain metabolites between low and high nutrient regions and a wide distribution of certain dissolved vitamins in the surface ocean. These measurements give us baseline data on the distribution of these metabolites and allow us to extend our understanding of microbial community activity in different regions of the ocean.

  2. Obesity and Asthma: Microbiome-Metabolome Interactions.

    PubMed

    Shore, Stephanie A; Cho, Youngji

    2016-05-01

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

  3. Extraction parameters for metabolomics from cell extracts

    PubMed Central

    Ser, Zheng; Liu, Xiaojing; Tang, Ngoc Nu; Locasale, Jason W

    2015-01-01

    The successful extraction of metabolites is a critical step in metabolite profiling. By optimizing metabolite extraction, the range and quantitative capacity of metabolomics studies can be improved. We considered eight separate extraction protocols for the preparation of a metabolite extract from cultured mammalian cells. Parameters considered included temperature, pH, and cell washing before extraction. The effects on metabolite recovery were studied using a high resolution liquid chromatography mass spectrometry (LC-HRMS) platform that measures metabolites of diverse chemical classes including among others amino acids, lipids, and sugar derivatives. The temperature considered during the extraction or the presence of formic acid, a commonly used additive, was shown to have minimal effects on the measured ion intensities of metabolites. However, washing of samples before metabolite extraction whether with water or PBS (both commonly considered practices) exhibited dramatic effects on measured intensities of both intra- and extra-cellular metabolites. Together these findings present a systematic assessment of extraction conditions for metabolite profiling. PMID:25613493

  4. Metabolomic phenotyping of a cloned pig model

    PubMed Central

    2011-01-01

    Background Pigs are widely used as models for human physiological changes in intervention studies, because of the close resemblance between human and porcine physiology and the high degree of experimental control when using an animal model. Cloned animals have, in principle, identical genotypes and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5) was for the first time elucidated by nuclear magnetic resonance (NMR)-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6) by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could not be established. Conclusions From the present study we conclude that cloned and normal outbred pigs are phenotypically different. However, it cannot be concluded that the use of cloned animals will reduce the inter-individual variation in intervention studies, though this is based on a limited number of animals. PMID:21859467

  5. Genetic basis of metabolome variation in yeast.

    PubMed

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

    2014-03-01

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

  6. Genetic Basis of Metabolome Variation in Yeast

    PubMed Central

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

    2014-01-01

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

  7. Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases.

    PubMed

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

    2013-01-01

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

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

    PubMed

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

    2011-11-09

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

  9. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

    PubMed Central

    2015-01-01

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

  10. Direct infusion mass spectrometry for metabolomic phenotyping of diseases.

    PubMed

    González-Domínguez, Raúl; Sayago, Ana; Fernández-Recamales, Ángeles

    2017-01-01

    Metabolomics based on direct mass spectrometry (MS) analysis, either by direct infusion or flow injection of crude sample extracts, shows a great potential for metabolic fingerprinting because of its high-throughput screening capability, wide metabolite coverage and reduced time of analysis. Considering that numerous metabolic pathways are significantly perturbed during the initiation and progression of diseases, these metabolomic tools can be used to get a deeper understanding about disease pathogenesis and discover potential biomarkers for early diagnosis. In this work, we describe the most common metabolomic platforms used in biomedical research, with special focus on strategies based on direct MS analysis. Then, a comprehensive review on the application of direct MS fingerprinting in clinical issues is provided.

  11. The promise of metabolomics in cancer molecular therapeutics.

    PubMed

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

    2004-12-01

    A systematic elucidation of cancer cell dysfunction and therapeutic mechanisms seems within reach with modern functional genomics and proteomics tools. However, for this potential to be realized, the metabolic consequences of gene expression and protein activity must be understood. 'Metabolomics' is currently a major missing component. It differs from classical metabolic studies by its greater breadth, depth and speed, enabled by the huge advances in analytical instrumentation (especially nuclear magnetic resonance and mass spectrometry) over the past two decades. Multiple metabolic pathways and networks can now be traced by the flow of atoms through metabolites, known as isotopomer analyses. Thus, metabolomics demands both high-throughput and high-information content analyses, and interpretation: the latter is currently a bottleneck. There are currently very few metabolomic studies in cancer therapeutics, despite this great need and potential.

  12. Challenges and developments in tandem mass spectrometry based clinical metabolomics.

    PubMed

    Ceglarek, Uta; Leichtle, Alexander; Brügel, Mathias; Kortz, Linda; Brauer, Romy; Bresler, Kristin; Thiery, Joachim; Fiedler, Georg Martin

    2009-03-25

    'Clinical metabolomics' aims at evaluating and predicting health and disease risk in an individual by investigating metabolic signatures in body fluids or tissues, which are influenced by genetics, epigenetics, environmental exposures, diet, and behaviour. Powerful analytical techniques like liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) offers a rapid, effective and economical way to analyze metabolic alterations of pre-defined target metabolites in biological samples. Novel hyphenated technical approaches like the combination of tandem mass spectrometry combined with linear ion trap (QTrap mass spectrometry) combines both identification and quantification of known and unknown metabolic targets. We describe new concepts and developments of mass spectrometry based multi-target metabolome profiling in the field of clinical diagnostics and research. Particularly, the experiences from newborn screening provided important insights about the diagnostic potential of metabolite profiling arrays and directs to the clinical aim of predictive, preventive and personalized medicine by metabolomics.

  13. Metabolomics biomarkers for tuberculosis diagnostics: current status and future objectives.

    PubMed

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

    2017-02-01

    Numerous studies have contributed to our current understanding of the complex biology of pulmonary tuberculosis and subsequently provided solutions to its control or eradication. Metabolomics, a newcomer to the Omics research domain, has significantly contributed to this understanding by identifying biomarkers originating from the disease-associated metabolome adaptations of both the microbe and host. These biomarkers have shed light on previously unknown disease mechanisms, many of which have been implemented toward the development of improved diagnostic strategies. In this review, we will discuss the role that metabolomics has played in tuberculosis research to date, with a specific focus on new biomarker identification, and how these have contributed to improved disease characterization and diagnostics, and their potential clinical applications.

  14. Considerations when choosing a genetic model organism for metabolomics studies.

    PubMed

    Reed, Laura K; Baer, Charles F; Edison, Arthur S

    2017-02-01

    Model organisms are important in many areas of chemical biology. In metabolomics, model organisms can provide excellent samples for methods development as well as the foundation of comparative phylometabolomics, which will become possible as metabolomics applications expand. Comparative studies of conserved and unique metabolic pathways will help in the annotation of metabolites as well as provide important new targets of investigation in biology and biomedicine. However, most chemical biologists are not familiar with genetics, which needs to be considered when choosing a model organism. In this review we summarize the strengths and weaknesses of several genetic systems, including natural isolates, recombinant inbred lines, and genetic mutations. We also discuss methods to detect targets of selection on the metabolome.

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

    PubMed Central

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

    2013-01-01

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

  16. Serum Metabolomics in Rats after Acute Paraquat Poisoning.

    PubMed

    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.

  17. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

    SciTech Connect

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

    2014-12-12

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

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

    PubMed

    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.

  19. The Metabolomic Signature of Malignant Glioma Reflects Accelerated Anabolic Metabolism

    PubMed Central

    Chinnaiyan, Prakash; Kensicki, Elizabeth; Bloom, Gregory; Prabhu, Antony; Sarcar, Bhaswati; Kahali, Soumen; Eschrich, Steven; Qu, Xiaotao; Forsyth, Peter; Gillies, Robert

    2015-01-01

    Although considerable progress has been made toward understanding glioblastoma biology through large-scale genetic and protein expression analyses, little is known about the underlying metabolic alterations promoting their aggressive phenotype. We conducted global metabolomic profiling on patient-derived glioma specimens and identified specific metabolic programs differentiating low- and high-grade tumors, with the metabolic signature of glioblastoma reflecting accelerated anabolic metabolism. When coupled with transcriptional profiles, we identified the metabolic phenotype of the mesenchymal subtype to consist of accumulation of the glycolytic intermediate phosphoenolpyruvate and decreased pyruvate kinase activity. Unbiased hierarchical clustering of metabolomic profiles identified three subclasses, which we term energetic, anabolic, and phospholipid catabolism with prognostic relevance. These studies represent the first global metabolomic profiling of glioma, offering a previously undescribed window into their metabolic heterogeneity, and provide the requisite framework for strategies designed to target metabolism in this rapidly fatal malignancy. PMID:23026133

  20. Unintended effects in genetically modified crops: revealed by metabolomics?

    PubMed

    Rischer, Heiko; Oksman-Caldentey, Kirsi-Marja

    2006-03-01

    In Europe the commercialization of food derived from genetically modified plants has been slow because of the complex regulatory process and the concerns of consumers. Risk assessment is focused on potential adverse effects on humans and the environment, which could result from unintended effects of genetic modifications: unintended effects are connected to changes in metabolite levels in the plants. One of the major challenges is how to analyze the overall metabolite composition of GM plants in comparison to conventional cultivars, and one possible solution is offered by metabolomics. The ultimate aim of metabolomics is the identification and quantification of all small molecules in an organism; however, a single method enabling complete metabolome analysis does not exist. Given a comprehensive extraction method, a hierarchical strategy--starting with global fingerprinting and followed by complementary profiling attempts--is the most logical and economic approach to detect unintended effects in GM crops.

  1. Integrated metabolomics and phytochemical genomics approaches for studies on rice.

    PubMed

    Okazaki, Yozo; Saito, Kazuki

    2016-01-01

    Metabolomics is widely employed to monitor the cellular metabolic state and assess the quality of plant-derived foodstuffs because it can be used to manage datasets that include a wide range of metabolites in their analytical samples. In this review, we discuss metabolomics research on rice in order to elucidate the overall regulation of the metabolism as it is related to the growth and mechanisms of adaptation to genetic modifications and environmental stresses such as fungal infections, submergence, and oxidative stress. We also focus on phytochemical genomics studies based on a combination of metabolomics and quantitative trait locus (QTL) mapping techniques. In addition to starch, rice produces many metabolites that also serve as nutrients for human consumers. The outcomes of recent phytochemical genomics studies of diverse natural rice resources suggest there is potential for using further effective breeding strategies to improve the quality of ingredients in rice grains.

  2. Overview of mass spectrometry-based metabolomics: opportunities and challenges.

    PubMed

    Gowda, G A Nagana; Djukovic, Danijel

    2014-01-01

    The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges.

  3. Overview of Mass Spectrometry-Based Metabolomics: Opportunities and Challenges

    PubMed Central

    Gowda, G.A. Nagana; Djukovic, Danijel

    2015-01-01

    The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges. PMID:25270919

  4. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action

    PubMed Central

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

    2016-01-01

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

  5. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action.

    PubMed

    Vincent, Isabel M; Ehmann, David E; Mills, Scott D; Perros, Manos; Barrett, Michael P

    2016-04-01

    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 cyanidem-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.

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed Central

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

    2012-01-01

    Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq) for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range ofantioxidant, 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

  8. Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2017-01-01

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

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

    PubMed

    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.

  11. Recent applications of metabolomics to advance microbial biofuel production.

    PubMed

    Martien, Julia I; Amador-Noguez, Daniel

    2017-02-01

    Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers.

  12. The potential biomarkers of drug addiction: proteomic and metabolomics challenges.

    PubMed

    Wang, Lv; Wu, Ning; Zhao, Tai-Yun; Li, Jin

    2016-07-28

    Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

  13. An emerging role for metabolomics in nutrition science.

    PubMed

    Astarita, Giuseppe; Langridge, James

    2013-01-01

    Nutritional research is undergoing a remarkable transformation driven by new technological tools. Because of the complexity of the components present in food and how they may interact with the biochemical networks of living organisms, nutrition cannot be considered a reductionist discipline. More holistic approaches, which are capable of gathering comprehensive, high-throughput amounts of data, appear to best enhance our understanding of the role of food in health and disease. In this context, global metabolite analysis, or 'metabolomics', is becoming an appealing research tool for nutrigenomics and nutrigenetics scientists. The purpose of the present review is to highlight some potential applications of metabolomics in nutrition research.

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

    PubMed

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

    2016-02-01

    Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided. Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  17. Metabolomics in diagnosis and biomarker discovery of colorectal cancer.

    PubMed

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

    2014-04-01

    Colorectal cancer (CRC), a major public health concern, is the second leading cause of cancer death in developed countries. There is a need for better preventive strategies to improve the patient outcome that is substantially influenced by cancer stage at the time of diagnosis. Patients with early stage colorectal have a significant higher 5-year survival rates compared to patients diagnosed at late stage. Although traditional colonoscopy remains the effective means to diagnose CRC, this approach generally suffers from poor patient compliance. Thus, it is important to develop more effective methods for early diagnosis of this disease process, also there is an urgent need for biomarkers to diagnose CRC, assess disease severity, and prognosticate course. Increasing availability of high-throughput methodologies open up new possibilities for screening new potential candidates for identifying biomarkers. Fortunately, metabolomics, the study of all metabolites produced in the body, considered most closely related to a patient's phenotype, can provide clinically useful biomarkers applied in CRC, and may now open new avenues for diagnostics. It has a largely untapped potential in the field of oncology, through the analysis of the cancer metabolome to identify marker metabolites defined here as surrogate indicators of physiological or pathophysiological states. In this review we take a closer look at the metabolomics used within the field of colorectal cancer. Further, we highlight the most interesting metabolomics publications and discuss these in detail; additional studies are mentioned as a reference for the interested reader. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  18. Method validation strategies involved in non-targeted metabolomics.

    PubMed

    Naz, Shama; Vallejo, Maria; García, Antonia; Barbas, Coral

    2014-08-01

    Non-targeted metabolomics is the hypothesis generating, global unbiased analysis of all the small-molecule metabolites present within a biological system, under a given set of conditions. It includes several common steps such as selection of biological samples, sample pre-treatment, analytical conditions set-up, acquiring data, data analysis by chemometrics, database search and biological interpretation. Non-targeted metabolomics offers the potential for a holistic approach in the area of biomedical research in order to improve disease diagnosis and to understand its pathological mechanisms. Various analytical methods have been developed based on nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) coupled with different separation techniques. The key points in any analytical method development are the validation of every step to get a reliable and reproducible result and non-targeted metabolomics is not beyond this criteria, although analytical challenges are completely new and different to target methods. This review paper will describe the available validation strategies that are being used and as well will recommend some steps to consider during a non-targeted metabolomics analytical method development. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Advances in metabolomic applications in plant genetics and breeding

    USDA-ARS?s Scientific Manuscript database

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

  20. Metabolomics approaches and applications in prostate cancer research.

    PubMed

    Zhang, Aihua; Yan, Guangli; Han, Ying; Wang, Xijun

    2014-09-01

    Prostate cancer is a leading cause of cancer deaths in men worldwide. Although prostate-specific antigen (PSA) has been extensively used as a serum biomarker to detect prostate cancer, this screening method has suffered from a lack of specificities and sensitivities. The successful prevention and treatment of prostate cancer relies on the early and accurate detection of the disease; therefore, more sensitive biomarkers are urgently needed. Prostate has long been known to exhibit unique metabolite profiles, fortunately, metabolomics, the study of all metabolites produced in the body, can be considered most closely related to a patient's phenotype. It may provide clinically useful biomarkers applied toward identifying metabolic alterations in prostate cancer and has introduced new insights into the pathology of prostate cancer. This advanced bioanalytic method may now open door for diagnostics. Metabolomics has a great and largely potential in the field of disease, and the analysis of the cancer metabolome to identify novel biomarkers and targets can now be undertaken in many research laboratories. In this review, we take a closer look at the metabolomics in the field of prostate cancer and highlight the interesting publications as references for the interested reader.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  2. Recent Highlights of Metabolomics in Chinese Medicine Syndrome Research

    PubMed Central

    Zhang, Ai-hua; Sun, Hui; Qiu, Shi; Wang, Xi-jun

    2013-01-01

    Chinese medicine syndrome (CMS, “ZHENG” in Chinese) is an understanding of the regularity of disease occurrence and development as well as a certain stage of a comprehensive response of patients with body condition. However, because of the complexity of CMS and the limitation of present investigation method, the research for deciphering the scientific basis and systematic features of CMS is difficult to go further. Metabolomics enables mapping of early biochemical changes in disease and hence provides an opportunity to develop predictive biomarkers. Moreover, its method and design resemble those of traditional Chinese medicine (TCM) which focuses on human disease via the integrity of close relationship between body and syndromes. In the systemic context, metabolomics has a convergence with TCM syndrome; therefore it could provide useful tools for exploring essence of CMS disease, facilitating personalized TCM, and will help to in-depth understand CMS. The integration of the metabolomics and CMS aspects will give promise to bridge the gap between Chinese and Western medicine and help catch the traditional features of CMS. In this paper, particular attention will be paid to the past successes in applications of robust metabolomic approaches to contribute to low-molecular-weight metabolites (biomarkers) discovery in CMS research and development. PMID:24302964

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

    DTIC Science & Technology

    2015-10-01

    respectively). Depression was significantly associated with increased ovarian cancer risk (hazard ratio: 1.26), as was being widowed (hazard ratio: 1.38...TERMS ovarian cancer, psychosocial stress, depression , anxiety, social support, metabolomics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...examine whether self-reported stress exposures ( depressive symptoms, phobic anxiety, social support, job strain, care-giving stress) are associated with

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

    EPA Science Inventory

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

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

    PubMed Central

    2014-01-01

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  9. Computational Tools for the Secondary Analysis of Metabolomics Experiments

    PubMed Central

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

    2013-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    EPA Science Inventory

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

  12. [Metabolomics in ischaemic stroke, new diagnostic and prognostic biomarkers].

    PubMed

    Mauri-Capdevila, Gerard; Jove, Mariona; Suarez-Luis, Idalmis; Portero-Otin, Manuel; Purroy, Francisco

    2013-07-01

    The study of biomarkers related with ischaemic stroke is becoming increasingly more important as a way to further our knowledge of the pathophysiological changes that occur in cerebrovascular disease and to make it easier to reach an early diagnosis. Within this field, metabolomics offers a novel approach. The field is defined as the study of the small-molecule metabolites derived from cell metabolism. Its interest lies in the fact that, using a biological sample, it offers a snapshot of the cellular changes that are taking place. Today, the application of metabolomics requires a complex methodology that includes the application of laboratory separation techniques, multivariant statistical analyses and the use of bioinformatic tools. A number of studies conducted within the field of cardiovascular disease have focused on the application of this approach. In recent years there has been a steady growth in the number of publications referring to the metabolic changes related with ischaemic stroke, both in animal models and in patients. Metabolomics makes it possible to obtain the profiles of metabolites that identify patients who have suffered an ischaemic stroke. Furthermore, since studies have been carried out that relate certain metabolites with the most common causations of ischaemic stroke, metabolomics may eventually play a significant role in the study of cryptogenic stroke. The most exhaustive knowledge of the changes in the metabolic pathways involved in cerebrovascular disease could lay the foundations for the development of new neuroprotector strategies.

  13. METABOLOMIC STUDIES OF ENDOCRINE DISRUPTION IN SMALL FISH MODELS

    EPA Science Inventory

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

  14. Liver metabolomics analysis associated with feed efficiency on steers

    USDA-ARS?s Scientific Manuscript database

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

  15. Metabolomics: Insulin Resistance and Type 2 Diabetes Mellitus

    USDA-ARS?s Scientific Manuscript database

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

  16. Impact of Intestinal Microbiota on Intestinal Luminal Metabolome

    PubMed Central

    Matsumoto, Mitsuharu; Kibe, Ryoko; Ooga, Takushi; Aiba, Yuji; Kurihara, Shin; Sawaki, Emiko; Koga, Yasuhiro; Benno, Yoshimi

    2012-01-01

    Low–molecular-weight metabolites produced by intestinal microbiota play a direct role in health and disease. In this study, we analyzed the colonic luminal metabolome using capillary electrophoresis mass spectrometry with time-of-flight (CE-TOFMS) —a novel technique for analyzing and differentially displaying metabolic profiles— in order to clarify the metabolite profiles in the intestinal lumen. CE-TOFMS identified 179 metabolites from the colonic luminal metabolome and 48 metabolites were present in significantly higher concentrations and/or incidence in the germ-free (GF) mice than in the Ex-GF mice (p < 0.05), 77 metabolites were present in significantly lower concentrations and/or incidence in the GF mice than in the Ex-GF mice (p < 0.05), and 56 metabolites showed no differences in the concentration or incidence between GF and Ex-GF mice. These indicate that intestinal microbiota highly influenced the colonic luminal metabolome and a comprehensive understanding of intestinal luminal metabolome is critical for clarifying host-intestinal bacterial interactions. PMID:22724057

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

    PubMed

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

    2016-06-21

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

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

    EPA Science Inventory

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

  19. Metabolomic Analysis in Brain Research: Opportunities and Challenges

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-04-01

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

  1. Ion mobility derived collision cross sections to support metabolomics applications.

    PubMed

    Paglia, Giuseppe; Williams, Jonathan P; Menikarachchi, Lochana; Thompson, J Will; Tyldesley-Worster, Richard; Halldórsson, Skarphédinn; Rolfsson, Ottar; Moseley, Arthur; Grant, David; Langridge, James; Palsson, Bernhard O; Astarita, Giuseppe

    2014-04-15

    Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC-TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches.

  2. Faecal and Serum Metabolomics in Paediatric Inflammatory Bowel Disease.

    PubMed

    Kolho, Kaija-Leena; Pessia, Alberto; Jaakkola, Tytti; de Vos, Willem M; Velagapudi, Vidya

    2017-03-01

    Inflammatory bowel disease [IBD] is considered to result from the interplay between host and intestinal microbiota but its pathogenesis is incompletely understood. While IBD in adults has shown to be associated with marked changes in body fluid metabolomics, there are only few studies in children. Hence, this prospective study addressed the faecal and serum metabolomics in newly diagnosed paediatric IBD. Paediatric patients with IBD undergoing diagnostic endoscopies and controls also with endoscopy but no signs of inflammation provided blood and stool samples in a tertiary care hospital. Blood inflammatory markers and faecal calprotectin levels were determined. The serum and faecal metabolomics were determined using ultra-high pressure liquid chromatography coupled to a mass spectrometer. Serum and faecal metabolite profiles in newly diagnosed paediatric IBD patients were different from healthy controls and categorized Crohn's disease and ulcerative colitis [UC] patients into separate groups. In serum, amino acid metabolism, folate biosynthesis and signalling pathways were perturbed in Crohn's disease; in UC also sphingolipid metabolic pathways were perturbed when compared to controls. In faecal samples, there was an increased level of several metabolites in UC in contrast to low or intermediate levels in Crohn's disease. There was a clear correlation with the level of inflammation, i.e. faecal calprotectin levels and the profile of various biologically important metabolites [carnosine, ribose and, most significantly, choline]. Characterization of inflammatory pattern using metabolomics analysis is a promising tool for better understanding disease pathogenesis of paediatric IBD.

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

    PubMed

    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.

  4. Metabolomic Biomarker Identification in Presence of Outliers and Missing Values

    PubMed Central

    Hoque, Md. Aminul; Shahjaman, Md.; Islam, S. M. Shahinul; Mollah, Md. Nurul Haque

    2017-01-01

    Metabolomics is the sophisticated and high-throughput technology based on the entire set of metabolites which is known as the connector between genotypes and phenotypes. For any phenotypic changes, potential metabolite (biomarker) identification is very important because it provides diagnostic as well as prognostic markers and can help to develop new biomolecular therapy. Biomarker identification from metabolomics data analysis is hampered by the use of high-throughput technology that provides high dimensional data matrix which contains missing values as well as outliers. However, missing value imputation and outliers handling techniques play important role in identifying biomarker correctly. Although several missing value imputation techniques are available, outliers deteriorate the accuracy of imputation as well as the accuracy of biomarker identification. Therefore, in this paper we have proposed a new biomarker identification technique combining the groupwise robust singular value decomposition, t-test, and fold-change approach that can identify biomarkers more correctly from metabolomics dataset. We have also compared the performance of the proposed technique with those of other traditional techniques for biomarker identification using both simulated and real data analysis in absence and presence of outliers. Using our proposed method in hepatocellular carcinoma (HCC) dataset, we have also identified the four upregulated and two downregulated metabolites as potential metabolomic biomarkers for HCC disease. PMID:28293630

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    Sethi, Sumit

    2016-01-01

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

  7. Metabolomics of aging assessed in individual parasitoid wasps

    PubMed Central

    Kapranas, Apostolos; Snart, Charles J. P.; Williams, Huw; Hardy, Ian C. W.; Barrett, David A.

    2016-01-01

    Metabolomics studies of low-biomass organisms, such as small insects, have previously relied on the pooling of biological samples to overcome detection limits, particularly using NMR. We show that the differentiation of metabolite profiles of individual 1 mg parasitoid wasps of different ages is possible when using a modified sample preparation and a combination of untargeted NMR and LC-MS based metabolomics. Changes were observed between newly emerged and older wasps in glycerolipids, amino acids and circulatory sugars. This advance in chemical profiling has important implications for the study of the behaviour and ecology of parasitoids and many other species of small organisms because predictions and observations are typically made at the level of the individual. Thus, the metabolomic state of low-biomass individuals can now be related to their behaviour and ecological performance. We discuss specifically the utility of age-related metabolomic profiling but our new approach can be applied to a wide range of biological research. PMID:27713504

  8. Metabolomics biomarkers of frailty in elderly breast cancer patients.

    PubMed

    Corona, Giuseppe; Polesel, Jerry; Fratino, Lucia; Miolo, Gianmaria; Rizzolio, Flavio; Crivellari, Diana; Addobbati, Riccardo; Cervo, Silvia; Toffoli, Giuseppe

    2014-07-01

    Metabolome analysis has emerged as a powerful technique for detecting and define specific physio-pathological phenotypes. In this investigation the diagnostic potential of metabolomics has been applied to better characterize the multiple biochemical alterations that concur in the definition of the frailty phenotype observed in elderly breast cancer patients. The study included 89 women with breast cancer (range 70-97 years) classified as Fit (n = 49), Unfit (n = 23), or Frail (n = 17) according to comprehensive geriatric assessment. The serum metabolomic profile was performed by tandem mass spectrometry and included different classes of metabolites such as amino acids, acylcarnitines, sphingo-, and glycerol-phospolipids. ANOVA was applied to identify the metabolites differing significantly among Fit, Unfit, and Frail patients. In patients carrying the frail phenotype, the amino acid perturbations involve serine, tryptophan, hydroxyproline, histidine, its derivate 3-methyl-hystidine, cystine, and β-aminoisobutyric acid. With regard to lipid metabolism, the frailty phenotype was characterized by a decrease of a wide number of glycerol- and sphingo-phospholipid metabolites. These metabolomics biomarkers may give a further insight into the biochemical processes involved in the development of frailty in breast cancer patients. Moreover, they might be useful to refine the comprehensive geriatric assessment model.

  9. Metabolomic signatures associated with disease severity in multiple sclerosis

    PubMed Central

    Alonso, Cristina; Agirrezabal, Ion; Kotelnikova, Ekaterina; Zubizarreta, Irati; Pulido-Valdeolivas, Irene; Saiz, Albert; Comabella, Manuel; Montalban, Xavier; Villar, Luisa; Alvarez-Cermeño, Jose Carlos; Fernández, Oscar; Alvarez-Lafuente, Roberto; Arroyo, Rafael; Castro, Azucena

    2017-01-01

    Objective: To identify differences in the metabolomic profile in the serum of patients with multiple sclerosis (MS) compared to controls and to identify biomarkers of disease severity. Methods: We studied 2 cohorts of patients with MS: a retrospective longitudinal cohort of 238 patients and 74 controls and a prospective cohort of 61 patients and 41 controls with serial serum samples. Patients were stratified into active or stable disease based on 2 years of prospective assessment accounting for presence of clinical relapses or changes in disability measured with the Expanded Disability Status Scale (EDSS). Metabolomic profiling (lipids and amino acids) was performed by ultra-high-performance liquid chromatography coupled to mass spectrometry in serum samples. Data analysis was performed using parametric methods, principal component analysis, and partial least square discriminant analysis for assessing the differences between cases and controls and for subgroups based on disease severity. Results: We identified metabolomics signatures with high accuracy for classifying patients vs controls as well as for classifying patients with medium to high disability (EDSS >3.0). Among them, sphingomyelin and lysophosphatidylethanolamine were the metabolites that showed a more robust pattern in the time series analysis for discriminating between patients and controls. Moreover, levels of hydrocortisone, glutamic acid, tryptophan, eicosapentaenoic acid, 13S-hydroxyoctadecadienoic acid, lysophosphatidylcholines, and lysophosphatidylethanolamines were associated with more severe disease (non-relapse-free or increase in EDSS). Conclusions: We identified metabolomic signatures composed of hormones, lipids, and amino acids associated with MS and with a more severe course. PMID:28180139

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

    PubMed

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

    2012-07-15

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

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

    PubMed Central

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

    2011-01-01

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

  12. Metabolomics of Apc Min/+ mice genetically susceptible to intestinal cancer

    PubMed Central

    2014-01-01

    Background To determine how diets high in saturated fat could increase polyp formation in the mouse model of intestinal neoplasia, Apc Min/+ , we conducted large-scale metabolome analysis and association study of colon and small intestine polyp formation from plasma and liver samples of Apc Min/+ vs. wild-type littermates, kept on low vs. high-fat diet. Label-free mass spectrometry was used to quantify untargeted plasma and acyl-CoA liver compounds, respectively. Differences in contrasts of interest were analyzed statistically by unsupervised and supervised modeling approaches, namely Principal Component Analysis and Linear Model of analysis of variance. Correlation between plasma metabolite concentrations and polyp numbers was analyzed with a zero-inflated Generalized Linear Model. Results Plasma metabolome in parallel to promotion of tumor development comprises a clearly distinct profile in Apc Min/+ mice vs. wild type littermates, which is further altered by high-fat diet. Further, functional metabolomics pathway and network analyses in Apc Min/+ mice on high-fat diet revealed associations between polyp formation and plasma metabolic compounds including those involved in amino-acids metabolism as well as nicotinamide and hippuric acid metabolic pathways. Finally, we also show changes in liver acyl-CoA profiles, which may result from a combination of Apc Min/+ -mediated tumor progression and high fat diet. The biological significance of these findings is discussed in the context of intestinal cancer progression. Conclusions These studies show that high-throughput metabolomics combined with appropriate statistical modeling and large scale functional approaches can be used to monitor and infer changes and interactions in the metabolome and genome of the host under controlled experimental conditions. Further these studies demonstrate the impact of diet on metabolic pathways and its relation to intestinal cancer progression. Based on our results, metabolic signatures

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Carneiro, Sónia; Pereira, Rui; Rocha, Isabel

    2014-01-01

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

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

    PubMed Central

    Alonso, Arnald; Marsal, Sara; Julià, Antonio

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  18. Navigating the road ahead: addressing challenges for use of metabolomics in epidemiology studies.

    PubMed

    Haznadar, Majda; Maruvada, Padma; Mette, Eliza; Milner, John; Moore, Steven C; Nicastro, Holly L; Sampson, Joshua N; Su, L Joseph; Verma, Mukesh; Zanetti, Krista A

    2014-04-01

    Metabolomics platforms allow for the measurement of hundreds to thousands of unique small chemical entities, as well as offer extensive coverage of metabolic markers related to obesity, diet, smoking, and other exposures of high interest to health scientists. Nevertheless, its potential use as a tool in population-based study design has not been fully explored. As the field of metabolomics continues to mature, and in part, accelerate through the National Institutes of Health (NIH) investment of ≤65 million in the Common Fund's Metabolomics Program (https://common fund.nih.gov/metabolomics/index), it is time to consider those challenges most pertinent to epidemiologic studies.

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

    PubMed

    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.

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

    PubMed

    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.

  1. Integrated Metabolomics and Genomics: Systems Approaches to Biomarkers and Mechanisms of Cardiovascular Disease

    PubMed Central

    Shah, Svati H.; Newgard, Christopher B.

    2015-01-01

    The genetic architecture underlying the heritability of cardiovascular disease (CVD) is incompletely understood. Metabolomics is an emerging technology platform that has shown early success in identifying biomarkers and mechanisms of common, chronic diseases. Integration of metabolomics, genetics and other ‘omics’ platforms in a systems biology approach holds potential for elucidating novel genetic markers and mechanisms for CVD. We review important studies that have utilized metabolomic profiling in cardiometabolic diseases, approaches for integrating metabolomics with genetics and other molecular profiling platforms, and key studies showing the potential for such studies in deciphering CVD genetics, biomarkers and mechanisms. PMID:25901039

  2. Metabolomics enables precision medicine: "A White Paper, Community Perspective".

    PubMed

    Beger, Richard D; Dunn, Warwick; Schmidt, Michael A; Gross, Steven S; Kirwan, Jennifer A; Cascante, Marta; Brennan, Lorraine; Wishart, David S; Oresic, Matej; Hankemeier, Thomas; Broadhurst, David I; Lane, Andrew N; Suhre, Karsten; Kastenmüller, Gabi; Sumner, Susan J; Thiele, Ines; Fiehn, Oliver; Kaddurah-Daouk, Rima

    Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and

  3. Ultrahigh resolution metabolomics for S-containing metabolites.

    PubMed

    Nakabayashi, Ryo; Saito, Kazuki

    2017-02-01

    The advent of the genome-editing era greatly increases the opportunities for synthetic biology research that aims to enhance production of potentially useful bioactive metabolites in heterologous hosts. A wide variety of sulfur (S)-containing metabolites (S-metabolites) are known to possess bioactivities and health-promoting properties, but finding them and their chemical assignment using mass spectrometry-based metabolomics has been difficult. In this review, we highlight recent advances on the targeted metabolomic analysis of S-metabolites (S-omics) in plants using ultrahigh resolution mass spectrometry. The use of exact mass and signal intensity differences between (32)S-containing monoisotopic ions and counterpart (34)S isotopic ions exploits an entirely new method to characterize S-metabolites. Finally, we discuss the availability of S-omics for synthetic biology.

  4. The MetaboLights repository: curation challenges in metabolomics.

    PubMed

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

    2013-01-01

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

  5. The MetaboLights repository: curation challenges in metabolomics

    PubMed Central

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

    2013-01-01

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

  6. Genomics and metabolomics of post-weaning return to estrus.

    PubMed

    Rempel, Lea A; Rohrer, Gary A; Nonneman, Danny J

    2017-09-01

    The weaning-to-estrus interval is a multifaceted trait that has the potential to substantially improve production efficiency in today's global swine industry, if variation in this measure can be reduced. Systems-biology approaches should help close the knowledge gap and increase selection tools and management strategies-such as gilt development programs, farrowing, and lactation feeding programs-to decrease the weaning-to-estrus interval. Metabolomics, the study of small compounds within biofluids and tissues, provides links between genotype and phenotype. Given the complexity and influence of the environment on the weaning-to-estrus interval, incorporating metabolomics data will provide valuable insight and guidance for future physiological as well as genetic and genomic strategies to reduce this interval, thereby improving sow productivity. This article is a U.S. Government work and is in the public domain in the USA.

  7. Metabolomics Insights Into Pathophysiological Mechanisms of Interstitial Cystitis

    PubMed Central

    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

  8. Postgenomics Diagnostics: Metabolomics Approaches to Human Blood Profiling

    PubMed Central

    Lokhov, Petr; Archakov, Alexander

    2013-01-01

    Abstract We live in exciting times with the prospects of postgenomics diagnostics. Metabolomics is a novel “omics” data-intensive science that is accelerating the development of postgenomics diagnostics, particularly with use of accessible peripheral tissue compartments. Metabolomics involves the study of a comprehensive set of low molecular weight substances (metabolites) present in biological systems. The metabolite profiles represent the molecular phenotype of biological systems and reflect the information encoded at the genomic level and implemented at the transcriptomic and proteomic levels. Analysis of the human blood metabolite profile is a universal and highly promising tool for clinical postgenomics applications because it reflects both the endogenous and exogenous (environmental) factors influencing an individual organism. This article presents a critical synthesis and original analysis of both the technical implementation of metabolic profiling of blood and statistical analysis of metabolite profiles for effective disease diagnostics and risk assessment in the present postgenomics era. PMID:24044364

  9. Baseline correction for NMR spectroscopic metabolomics data analysis.

    PubMed

    Xi, Yuanxin; Rocke, David M

    2008-07-29

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

  10. Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis

    PubMed Central

    Xi, Yuanxin; Rocke, David M

    2008-01-01

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

  11. Plant metabolomics: from experimental design to knowledge extraction.

    PubMed

    Rai, Amit; Umashankar, Shivshankar; Swarup, Sanjay

    2013-01-01

    Metabolomics is one of the most recent additions to the functional genomics approaches. It involves the use of analytical chemistry techniques to provide high-density data of metabolic profiles. Data is then analyzed using advanced statistics and databases to extract biological information, thus providing the metabolic phenotype of an organism. Large variety of metabolites produced by plants through the complex metabolic networks and their dynamic changes in response to various perturbations can be studied using metabolomics. Here, we describe the basic features of plant metabolic diversity and analytical methods to describe this diversity, which includes experimental workflows starting from experimental design, sample preparation, hardware and software choices, combined with knowledge extraction methods. Finally, we describe a scenario for using these workflows to identify differential metabolites and their pathways from complex biological samples.

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

    PubMed

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

    2014-05-30

    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.

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

    PubMed

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

    2016-07-21

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

  14. Metabolomic analysis of normal and sickle cell erythrocytes.

    PubMed

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

    2010-09-01

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

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

    PubMed Central

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

    2014-01-01

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

  16. Probabilistic assignment of formulas to mass peaks in metabolomics experiments.

    PubMed

    Rogers, Simon; Scheltema, Richard A; Girolami, Mark; Breitling, Rainer

    2009-02-15

    High-accuracy mass spectrometry is a popular technology for high-throughput measurements of cellular metabolites (metabolomics). One of the major challenges is the correct identification of the observed mass peaks, including the assignment of their empirical formula, based on the measured mass. We propose a novel probabilistic method for the assignment of empirical formulas to mass peaks in high-throughput metabolomics mass spectrometry measurements. The method incorporates information about possible biochemical transformations between the empirical formulas to assign higher probability to formulas that could be created from other metabolites in the sample. In a series of experiments, we show that the method performs well and provides greater insight than assignments based on mass alone. In addition, we extend the model to incorporate isotope information to achieve even more reliable formula identification. A supplementary document, Matlab code, data and further information are available from http://www.dcs.gla.ac.uk/inference/metsamp.

  17. Metabolomics to Unveil and Understand Phenotypic Diversity between Pathogen Populations

    PubMed Central

    t'Kindt, Ruben; Scheltema, Richard A.; Jankevics, Andris; Brunker, Kirstyn; Rijal, Suman; Dujardin, Jean-Claude; Breitling, Rainer; Watson, David G.; Coombs, Graham H.; Decuypere, Saskia

    2010-01-01

    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. PMID:21152055

  18. Metabolomic approaches to phenotype characterization and applications to complex diseases.

    PubMed

    Oresic, Matej; Vidal-Puig, Antonio; Hänninen, Virve

    2006-07-01

    Metabolites are the key regulators of systems homeostasis. As such, concentration changes of specific groups of metabolites may reflect systemic responses to environmental, therapeutic or genetic interventions. Thus, the study of metabolites is a powerful tool for the characterization of complex phenotypes as well as for the development of biomarkers for specific physiological responses. Therefore, metabolomics is a valuable platform for studies of complex diseases and the development of new therapies, both in nonclinical disease model characterization and clinical settings.

  19. Comprehensive Metabolomic Profiling and Incident Cardiovascular Disease: A Systematic Review.

    PubMed

    Ruiz-Canela, Miguel; Hruby, Adela; Clish, Clary B; Liang, Liming; Martínez-González, Miguel A; Hu, Frank B

    2017-09-28

    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). We searched MEDLINE and EMBASE from inception to January 2016. Studies were eligible if they pertained to adult humans; followed an agnostic and/or comprehensive approach; used serum or plasma (not urine or other biospecimens); conducted metabolite profiling at baseline in the context of examining prospective disease; and included myocardial infarction, stroke, and/or CVD death in the CVD outcome definition. We identified 12 original articles (9 cohort and 3 nested case-control studies); participant numbers ranged from 67 to 7256. Mass spectrometry was the predominant analytical method. The number and chemical diversity of metabolites were very heterogeneous, ranging from 31 to >10 000 features. Four studies used untargeted profiling. Different types of metabolites were associated with CVD risk: acylcarnitines, dicarboxylacylcarnitines, and several amino acids and lipid classes. Only tiny improvements in CVD prediction beyond traditional risk factors were observed using these metabolites (C index improvement ranged from 0.006 to 0.05). There are a limited number of longitudinal studies assessing associations between comprehensive metabolomic profiles and CVD risk. Quantitatively synthesizing the literature is challenging because of the widely varying analytical tools and the diversity of methodological and statistical approaches. Although some results are promising, more research is needed, notably standardization of metabolomic techniques and statistical approaches. Replication and combinations of novel and holistic methodological approaches would move the field toward the realization of its promise. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

  20. Impact of storage conditions on the urinary metabolomics fingerprint.

    PubMed

    Laparre, Jérôme; Kaabia, Zied; Mooney, Mark; Buckley, Tom; Sherry, Mark; Le Bizec, Bruno; Dervilly-Pinel, Gaud

    2017-01-25

    Urine stability during storage is essential in metabolomics to avoid misleading conclusions or erroneous interpretations. Facing the lack of comprehensive studies on urine metabolome stability, the present work performed a follow-up of potential modifications in urinary chemical profile using LC-HRMS on the basis of two parameters: the storage temperature (+4 °C, -20 °C, -80 °C and freeze-dried stored at -80 °C) and the storage duration (5-144 days). Both HILIC and RP chromatographies have been implemented in order to globally monitor the urinary metabolome. Using an original data processing associated to univariate and multivariate data analysis, our study confirms that chemical profiles of urine samples stored at +4 °C are very rapidly modified, as observed for instance for compounds such as:N-acetyl Glycine, Adenosine, 4-Amino benzoic acid, N-Amino diglycine, creatine, glucuronic acid, 3-hydroxy-benzoic acid, pyridoxal, l-pyroglutamic acid, shikimic acid, succinic acid, thymidine, trigonelline and valeryl-carnitine, while it also demonstrates that urine samples stored at -20 °C exhibit a global stability over a long period with no major modifications compared to -80 °C condition. This study is the first to investigate long term stability of urine samples and report potential modifications in the urinary metabolome, using both targeted approach monitoring individually a large number (n > 200) of urinary metabolites and an untargeted strategy enabling assessing for global impact of storage conditions.

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

    PubMed Central

    2011-01-01

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

  2. [Optimized sample preparation for metabolome studies on Streptomyces coelicolor].

    PubMed

    Li, Yihong; Li, Shanshan; Ai, Guomin; Wang, Weishan; Zhang, Buchang; Yang, Keqian

    2014-04-01

    Streptomycetes produce many antibiotics and are important model microorgansims for scientific research and antibiotic production. Metabolomics is an emerging technological platform to analyze low molecular weight metabolites in a given organism qualitatively and quantitatively. Compared to other Omics platform, metabolomics has greater advantage in monitoring metabolic flux distribution and thus identifying key metabolites related to target metabolic pathway. The present work aims at establishing a rapid, accurate sample preparation protocol for metabolomics analysis in streptomycetes. In the present work, several sample preparation steps, including cell quenching time, cell separation method, conditions for metabolite extraction and metabolite derivatization were optimized. Then, the metabolic profiles of Streptomyces coelicolor during different growth stages were analyzed by GC-MS. The optimal sample preparation conditions were as follows: time of low-temperature quenching 4 min, cell separation by fast filtration, time of freeze-thaw 45 s/3 min and the conditions of metabolite derivatization at 40 degrees C for 90 min. By using this optimized protocol, 103 metabolites were finally identified from a sample of S. coelicolor, which distribute in central metabolic pathways (glycolysis, pentose phosphate pathway and citrate cycle), amino acid, fatty acid, nucleotide metabolic pathways, etc. By comparing the temporal profiles of these metabolites, the amino acid and fatty acid metabolic pathways were found to stay at a high level during stationary phase, therefore, these pathways may play an important role during the transition between the primary and secondary metabolism. An optimized protocol of sample preparation was established and applied for metabolomics analysis of S. coelicolor, 103 metabolites were identified. The temporal profiles of metabolites reveal amino acid and fatty acid metabolic pathways may play an important role in the transition from primary to

  3. Tuning Metabolome Coverage in Reversed Phase LC-MS Metabolomics of MeOH Extracted Samples Using the Reconstitution Solvent Composition.

    PubMed

    Lindahl, Anna; Sääf, Siv; Lehtiö, Janne; Nordström, Anders

    2017-07-18

    Considering the physicochemical diversity of the metabolome, untargeted metabolomics will inevitably discriminate against certain compound classes. Efforts are nevertheless made to maximize the metabolome coverage. Contrary to the main steps of a typical liquid chromatography-mass spectrometry (LC-MS) metabolomics workflow, such as metabolite extraction, the sample reconstitution step has not been optimized for maximal metabolome coverage. This sample concentration step typically occurs after metabolite extraction, when dried samples are reconstituted in a solvent for injection on column. The aim of this study was to evaluate the impact of the sample reconstitution solvent composition on metabolome coverage in untargeted LC-MS metabolomics. Lysogeny Broth medium samples reconstituted in MeOH/H2O ratios ranging from 0 to 100% MeOH and analyzed with untargeted reversed phase LC-MS showed that the highest number of metabolite features (n = 1500) was detected in samples reconstituted in 100% H2O. As compared to a commonly used reconstitution solvent mixture of 50/50 MeOH/H2O, our results indicate that the small fraction of compounds increasing in peak area response by the addition of MeOH to H2O, 5%, is outweighed by the fraction of compounds with decreased response, 57%. We evaluated our results on human serum samples from lymphoma patients and healthy control subjects. Reconstitution in 100% H2O resulted in a higher number of significant metabolites discriminating between these two groups than both 50% and 100% MeOH. These findings show that the sample reconstitution step has a clear impact on the metabolome coverage of MeOH extracted biological samples, highlighting the importance of the reconstitution solvent composition for untargeted discovery metabolomics.

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

    PubMed Central

    Floros, Dimitrios J.

    2017-01-01

    Introduction 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. Objective 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. Method In this work we utilize untargeted LC–MS/MS based metabolomics together with molecular networking to Result 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. Conclusion 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. PMID:28819353

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

    PubMed

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

    2014-12-01

    Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development. Copyright © 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  6. Metabolomics in cancer biomarker discovery: current trends and future perspectives.

    PubMed

    Armitage, Emily G; Barbas, Coral

    2014-01-01

    Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels. Following this, cancer central carbon metabolism has been researched extensively and beyond respiration, cancer has been found to involve a wide range of metabolic processes, and many more are still to be unveiled. Studying cancer through metabolomics could reveal new biomarkers for cancer that could be useful for its future prognosis, diagnosis and therapy. Metabolomics is becoming an increasingly popular tool in the life sciences since it is a relatively fast and accurate technique that can be applied with either a particular focus or in a global manner to reveal new knowledge about biological systems. There have been many examples of its application to reveal potential biomarkers in different cancers that have employed a range of different analytical platforms. In this review, approaches in metabolomics that have been employed in cancer biomarker discovery are discussed and some of the most noteworthy research in the field is highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Current Advances in the Metabolomics Study on Lotus Seeds

    PubMed Central

    Zhu, Mingzhi; Liu, Ting; Guo, Mingquan

    2016-01-01

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

  8. Analytical approaches to metabolomics and applications to systems biology.

    PubMed

    Wang, Jeffrey H; Byun, Jaeman; Pennathur, Subramaniam

    2010-09-01

    Phenotypic expression of renal diseases encompasses a complex interaction between genetic, environmental, and local tissue factors. The level of complexity requires integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate metabolites from biological samples. The small molecules represent the end result of complexity of biological processes in a given cell, tissue, or organ, and thus form attractive candidates to understand disease phenotypes. Metabolites represent a diverse group of low-molecular-weight structures including lipids, amino acids, peptides, nucleic acids, and organic acids, which makes comprehensive analysis a difficult analytical challenge. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled separation, characterization, detection, and quantification of such chemically diverse structures. Continued development of bioinformatics and analytical strategies will accelerate widespread use and integration of metabolomics into systems biology. Here, we will discuss analytical and bioinformatic techniques and highlight recent studies that use metabolomics in understanding pathophysiology of disease processes.

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

    PubMed

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

    2013-11-15

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

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

    PubMed

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

    2016-02-15

    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.

  11. Metabolomics as a promising tool for early osteoarthritis diagnosis.

    PubMed

    de Sousa, E B; Dos Santos, G C; Duarte, M E L; Moura, V; Aguiar, D P

    2017-09-21

    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.

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

    DOE PAGES

    Larsen, Peter E.; Dai, Yang

    2015-09-14

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

  13. An exome array study of the plasma metabolome

    PubMed Central

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

    2016-01-01

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

  14. Multivariate classification of urine metabolome profiles for breast cancer diagnosis.

    PubMed

    Kim, Younghoon; Koo, Imhoi; Jung, Byung Hwa; Chung, Bong Chul; Lee, Doheon

    2010-04-16

    Diagnosis techniques using urine are non-invasive, inexpensive, and easy to perform in clinical settings. The metabolites in urine, as the end products of cellular processes, are closely linked to phenotypes. Therefore, urine metabolome is very useful in marker discoveries and clinical applications. However, only univariate methods have been used in classification studies using urine metabolome. Since multiple genes or proteins would be involved in developments of complex diseases such as breast cancer, multiple compounds including metabolites would be related with the complex diseases, and multivariate methods would be needed to identify those multiple metabolite markers. Moreover, because combinatorial effects among the markers can seriously affect disease developments and there also exist individual differences in genetic makeup or heterogeneity in cancer progressions, single marker is not enough to identify cancers. We proposed classification models using multivariate classification techniques and developed an analysis procedure for classification studies using metabolome data. Through this strategy, we identified five potential urinary biomarkers for breast cancer with high accuracy, among which the four biomarker candidates were not identifiable by only univariate methods. We also proposed potential diagnosis rules to help in clinical decision making. Besides, we showed that combinatorial effects among multiple biomarkers can enhance discriminative power for breast cancer. In this study, we successfully showed that multivariate classifications are needed to precisely diagnose breast cancer. After further validation with independent cohorts and experimental confirmation, these marker candidates will likely lead to clinically applicable assays for earlier diagnoses of breast cancer.

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

    PubMed

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

    2015-06-01

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

  16. Solid-Phase Microextraction and the Human Fecal VOC Metabolome

    PubMed Central

    Dixon, Emma; Clubb, Cynthia; Pittman, Sara; Ammann, Larry; Rasheed, Zeehasham; Kazmi, Nazia; Keshavarzian, Ali; Gillevet, Pat; Rangwala, Huzefa; Couch, Robin D.

    2011-01-01

    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. PMID:21494609

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

    SciTech Connect

    Larsen, Peter E.; Dai, Yang

    2015-09-14

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

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

    PubMed Central

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

    2014-01-01

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

  19. Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

    PubMed Central

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

    2016-01-01

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

  20. Impact of red meat consumption on the metabolome of rats.

    PubMed

    Jakobsen, Louise M A; Yde, Christian C; Van Hecke, Thomas; Jessen, Randi; Young, Jette F; De Smet, Stefaan; Bertram, Hanne Christine

    2017-03-01

    The scope of the present study was to investigate the effects of red versus white meat intake on the metabolome of rats. Twenty-four male Sprague-Dawley rats were randomly assigned to 15 days of ad libitum feeding of one of four experimental diets: (i) lean chicken, (ii) chicken with lard, (iii) lean beef, and (iv) beef with lard. Urine, feces, plasma, and colon tissue samples were analyzed using (1) H NMR-based metabolomics and real-time PCR was performed on colon tissue to examine the expression of specific genes. Urinary excretion of acetate and anserine was higher after chicken intake, while carnosine, fumarate, and trimethylamine N-oxide excretion were higher after beef intake. In colon tissue, higher choline levels and lower lipid levels were found after intake of chicken compared to beef. Expression of the apc gene was higher in response to the lean chicken and beef with lard diets. Correlation analysis revealed that intestinal apc gene expression was correlated with fecal lactate content (R(2) = 0.65). This study is the first to identify specific differences in the metabolome related to the intake of red and white meat. These differences may reflect perturbations in endogenous metabolism that can be linked to the proposed harmful effects associated with intake of red meat. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    PubMed Central

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

    2016-01-01

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

  2. Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows

    PubMed Central

    2014-01-01

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

  3. Structure-revealing data fusion model with applications in metabolomics.

    PubMed

    Acar, Evrim; Lawaetz, Anders J; Rasmussen, Morten A; Bro, Rasmus

    2013-01-01

    In many disciplines, data from multiple sources are acquired and jointly analyzed for enhanced knowledge discovery. For instance, in metabolomics, different analytical techniques are used to measure biological fluids in order to identify the chemicals related to certain diseases. It is widely-known that, some of these analytical methods, e.g., LC-MS (Liquid Chromatography - Mass Spectrometry) and NMR (Nuclear Magnetic Resonance) spectroscopy, provide complementary data sets and their joint analysis may enable us to capture a larger proportion of the complete metabolome belonging to a specific biological system. Fusing data from multiple sources has proved useful in many fields including bioinformatics, signal processing and social network analysis. However, identification of common (shared) and individual (unshared) structures across multiple data sets remains a major challenge in data fusion studies. With a goal of addressing this challenge, we propose a novel unsupervised data fusion model. Our contributions are two-fold: (i) We formulate a data fusion model based on joint factorization of matrices and higher-order tensors, which can automatically reveal common and individual components. (ii) We demonstrate that the proposed approach provides promising results in joint analysis of metabolomics data sets consisting of fluorescence and NMR measurements of plasma samples in terms of separation of colorectal cancer patients from controls.

  4. Volatile metabolomic signature of human breast cancer cell lines.

    PubMed

    Silva, Catarina L; Perestrelo, Rosa; Silva, Pedro; Tomás, Helena; Câmara, José S

    2017-03-03

    Breast cancer (BC) remains the most prevalent oncologic pathology in women, causing huge psychological, economic and social impacts on our society. Currently, the available diagnostic tools have limited sensitivity and specificity. Metabolome analysis has emerged as a powerful tool for obtaining information about the biological processes that occur in organisms, and is a useful platform for discovering new biomarkers or make disease diagnosis using different biofluids. Volatile organic compounds (VOCs) from the headspace of cultured BC cells and normal human mammary epithelial cells, were collected by headspace solid-phase microextraction (HS-SPME) and analyzed by gas chromatography combined with mass spectrometry (GC-MS), thus defining a volatile metabolomic signature. 2-Pentanone, 2-heptanone, 3-methyl-3-buten-1-ol, ethyl acetate, ethyl propanoate and 2-methyl butanoate were detected only in cultured BC cell lines. Multivariate statistical methods were used to verify the volatomic differences between BC cell lines and normal cells in order to find a set of specific VOCs that could be associated with BC, providing comprehensive insight into VOCs as potential cancer biomarkers. The establishment of the volatile fingerprint of BC cell lines presents a powerful approach to find endogenous VOCs that could be used to improve the BC diagnostic tools and explore the associated metabolomic pathways.

  5. Zinc stress affects ionome and metabolome in tea plants.

    PubMed

    Zhang, Yinfei; Wang, Yu; Ding, Zhaotang; Wang, Hui; Song, Lubin; Jia, Sisi; Ma, Dexin

    2017-02-01

    The research of physiological responses to Zn stress in plants has been extensively studied. However, the ionomics and metabolomics responses of plants to Zn stress remain largely unknown. In present study, the nutrient elements were identified involved in ion homeostasis and metabolomics changes related to Zn deficiency or excess in tea plants. Nutrient element analysis demonstrated that the concentrations of Zn affected the ion-uptake in roots and the nutrient element transportation to leaves, leading to the different distribution of P, S, Al, Ca, Fe and Cu in the tea leaves or roots. Metabolomics analysis revealed that Zn deficiency or excess differentially influenced the metabolic pathways in the tea leaves. More specifically, Zn deficiency affected the metabolism of carbohydrates, and Zn excess affected flavonoids metabolism. Additionally, the results showed that both Zn deficiency and Zn excess led to reduced nicotinamide levels, which speeded up NAD(+) degradation and thus reduced energy metabolism. Furthermore, element-metabolite correlation analysis illustrated that Zn contents in the tea leaves were positively correlated with organic acids, nitrogenous metabolites and some carbohydrate metabolites, and negatively correlated with the metabolites involved in secondary metabolism and some other carbohydrate metabolites. Meanwhile, metabolite-metabolite correlation analysis demonstrated that organic acids, sugars, amino acids and flavonoids played dominant roles in the regulation of the tea leaf metabolism under Zn stress. Therefore, the conclusion should be drawn that the tea plants responded to Zn stress by coordinating ion-uptake and regulation of metabolism of carbohydrates, nitrogenous metabolites, and flavonoids.

  6. Neonatal Metabolomic Profiles Related to Prenatal Arsenic Exposure.

    PubMed

    Laine, Jessica E; Bailey, Kathryn A; Olshan, Andrew F; Smeester, Lisa; Drobná, Zuzana; Stýblo, Miroslav; Douillet, Christelle; García-Vargas, Gonzalo; Rubio-Andrade, Marisela; Pathmasiri, Wimal; McRitchie, Susan; Sumner, Susan J; Fry, Rebecca C

    2017-01-03

    Prenatal inorganic arsenic (iAs) exposure is associated with health effects evident at birth and later in life. An understanding of the relationship between prenatal iAs exposure and alterations in the neonatal metabolome could reveal critical molecular modifications, potentially underpinning disease etiologies. In this study, nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis was used to identify metabolites in neonate cord serum associated with prenatal iAs exposure in participants from the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort, in Gómez Palacio, Mexico. Through multivariable linear regression, ten cord serum metabolites were identified as significantly associated with total urinary iAs and/or iAs metabolites, measured as %iAs, %monomethylated arsenicals (MMAs), and %dimethylated arsenicals (DMAs). A total of 17 metabolites were identified as significantly associated with total iAs and/or iAs metabolites in cord serum. These metabolites are indicative of changes in important biochemical pathways such as vitamin metabolism, the citric acid (TCA) cycle, and amino acid metabolism. These data highlight that maternal biotransformation of iAs and neonatal levels of iAs and its metabolites are associated with differences in neonate cord metabolomic profiles. The results demonstrate the potential utility of metabolites as biomarkers/indicators of in utero environmental exposure.

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

    PubMed Central

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

    2015-01-01

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

  8. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

    DOE PAGES

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

    2014-12-12

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

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

    PubMed

    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 < 0.05) representing a "healthy" cluster. Cluster 2 had significantly higher intakes of chips/processed potatoes, meat products, savory snacks and high-energy beverages (p < 0.05) representing an "unhealthy cluster". Classification was supported by significant differences in nutrient status (p < 0.05). Validation in an independent group revealed that 94% of subjects were correctly classified. The model developed was capable of classifying individuals into dietary 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.

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

    PubMed

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

    2016-09-01

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

  11. Volatile metabolomic signature of human breast cancer cell lines

    PubMed Central

    Silva, Catarina L.; Perestrelo, Rosa; Silva, Pedro; Tomás, Helena; Câmara, José S.

    2017-01-01

    Breast cancer (BC) remains the most prevalent oncologic pathology in women, causing huge psychological, economic and social impacts on our society. Currently, the available diagnostic tools have limited sensitivity and specificity. Metabolome analysis has emerged as a powerful tool for obtaining information about the biological processes that occur in organisms, and is a useful platform for discovering new biomarkers or make disease diagnosis using different biofluids. Volatile organic compounds (VOCs) from the headspace of cultured BC cells and normal human mammary epithelial cells, were collected by headspace solid-phase microextraction (HS-SPME) and analyzed by gas chromatography combined with mass spectrometry (GC–MS), thus defining a volatile metabolomic signature. 2-Pentanone, 2-heptanone, 3-methyl-3-buten-1-ol, ethyl acetate, ethyl propanoate and 2-methyl butanoate were detected only in cultured BC cell lines. Multivariate statistical methods were used to verify the volatomic differences between BC cell lines and normal cells in order to find a set of specific VOCs that could be associated with BC, providing comprehensive insight into VOCs as potential cancer biomarkers. The establishment of the volatile fingerprint of BC cell lines presents a powerful approach to find endogenous VOCs that could be used to improve the BC diagnostic tools and explore the associated metabolomic pathways. PMID:28256598

  12. Non-targeted metabolomics in sport and exercise science.

    PubMed

    Heaney, Liam M; Deighton, Kevin; Suzuki, Toru

    2017-03-27

    Metabolomics incorporates the study of metabolites that are produced and released through physiological processes at both the systemic and cellular levels. Biological compounds at the metabolite level are of paramount interest in the sport and exercise sciences, although research in this field has rarely been referred to with the global 'omics terminology. Commonly studied metabolites in exercise science are notably within cellular pathways for adenosine triphosphate production such as glycolysis (e.g., pyruvate and lactate), β-oxidation of free fatty acids (e.g., palmitate) and ketone bodies (e.g., β-hydroxybutyrate). Non-targeted metabolomic technologies are able to simultaneously analyse the large numbers of metabolites present in human biological samples such as plasma, urine and saliva. These analytical technologies predominately employ nuclear magnetic resonance spectroscopy and chromatography coupled to mass spectrometry. Performing experiments based on non-targeted methods allows for systemic metabolite changes to be analysed and compared to a particular physiological state (e.g., pre-/post-exercise) and provides an opportunity to prospect for metabolite signatures that offer beneficial information for translation into an exercise science context, for both elite performance and public health monitoring. This narrative review provides an introduction to non-targeted metabolomic technologies and discusses current and potential applications in sport and exercise science.

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

    PubMed Central

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

    2015-01-01

    The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases. PMID:26694367

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

    PubMed Central

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

    2016-01-01

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

  15. Metabolomic biomarkers in diabetic kidney diseases--A systematic review.

    PubMed

    Zhang, Yumin; Zhang, Siwen; Wang, Guixia

    2015-01-01

    Diabetic kidney disease (DKD) is generally characterized by increasing albuminuria in diabetic patients; however, few biomarkers are available to facilitate early diagnosis of this disease. The application of metabolomics has shown promises addressing this need. In this review, we conducted a search about metabolomic biomarkers in DKD patients through MEDLINE, EMBASE, and Cochrane Database up to the end of March, 2015. 12 eligible studies were selected and evaluated subsequently through the use of QUADOMICS, a quality assessment tool. 7 of the 12 included studies were classified as 'high quality'. We also recorded specific study characteristics including participants' characteristics, metabolomic techniques, sample types, and significantly altered metabolites between DKD and control groups. Products of lipid metabolisms including esterified and non-esterified fatty acids, carnitines, phospholipids and metabolites involved in branch-chained amino acids and aromatic amino acids metabolisms were frequently affected biomarkers of DKD. Other differential metabolites were also found, while some of their associations with DKD were unclear. Further more studies are required to test these findings in larger, diverse ethnic populations with elaborate study designs, and finally we could translate them into the benefits of DKD patients.

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2013-11-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In this study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine (MA)-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate, FDR <0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent MA levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

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

    SciTech Connect

    Larsen, Peter E.; Dai, Yang

    2015-09-14

    Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. 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.

  19. THE ATHENS LAB'S ROLE IN EPA'S COMPUTATIONAL TOXICOLOGY PROGRAM WITH AN EMPHASIS ON METABOLOMICS AS A DIAGNOSTIC TOOL FOR TOXICOLOGY

    EPA Science Inventory

    This presentation gives a brief introduction to EPA's computational toxicology program and the Athens Lab's role in it. The talk also covered a brief introduction to metabolomics; advantages/disadvanage of metabolomics for toxicity assessment; goals of the EPA Athens metabolomics...

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

    PubMed

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

    2010-11-05

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

  1. Radiation Metabolomics. 5. Identification of Urinary Biomarkers of Ionizing Radiation Exposure in Nonhuman Primates by Mass Spectrometry-Based Metabolomics

    PubMed Central

    Johnson, Caroline H.; Patterson, Andrew D.; Krausz, Kristopher W.; Kalinich, John F.; Tyburski, John B.; Kang, Dong Wook; Luecke, Hans; Gonzalez, Frank J.; Blakely, William F.; Idle, Jeffrey R.

    2012-01-01

    Mass spectrometry-based metabolomics has previously demonstrated utility for identifying biomarkers of ionizing radiation exposure in cellular, mouse and rat in vivo radiation models. To provide a valuable link from small laboratory rodents to humans, γ-radiation-induced urinary biomarkers were investigated using a nonhuman primate total-body-irradiation model. Mass spectrometry-based metabolomics approaches were applied to determine whether biomarkers could be identified, as well as the previously discovered rodent biomarkers of γ radiation. Ultra-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry analysis was carried out on a time course of clean-catch urine samples collected from nonhuman primates (n = 6 per cohort) exposed to sham, 1.0, 3.5, 6.5 or 8.5 Gy doses of 60Co γ ray (~0.55 Gy/min) ionizing radiation. By multivariate data analysis, 13 biomarkers of radiation were discovered: N-acetyltaurine, isethionic acid, taurine, xanthine, hypoxanthine, uric acid, creatine, creatinine, tyrosol sulfate, 3-hydroxytyrosol sulfate, tyramine sulfate, N-acetylserotonin sulfate, and adipic acid. N-Acetyltaurine, isethionic acid, and taurine had previously been identified in rats, and taurine and xanthine in mice after ionizing radiation exposure. Mass spectrometry-based metabolomics has thus successfully revealed and verified urinary biomarkers of ionizing radiation exposure in the nonhuman primate for the first time, which indicates possible mechanisms for ionizing radiation injury. PMID:22954391

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

    PubMed

    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.

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

    PubMed

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

    2016-01-12

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

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

    PubMed

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

    2014-05-16

    The identification of the no observed adverse effect level (NOAEL) is the key regulatory outcome of toxicity studies. With the introduction of "omics" technologies into toxicological research, the question arises as to how sensitive these technologies are relative to classical regulatory toxicity parameters. BASF SE and metanomics developed the in vivo metabolome database MetaMap®Tox containing metabolome data for more than 500 reference compounds. For several years metabolome analysis has been routinely performed in regulatory toxicity studies (REACH mandated testing or new compound development), mostly in the context of 28 day studies in rats (OECD 407 guideline). For those chemicals for which a toxicological NOAEL level was obtained at either high or mid-dose level, we evaluated the associated metabolome to investigate the sensitivity of metabolomics versus classical toxicology with respect to the NOAEL. For the definition of a metabolomics NOAEL the ECETOC criteria (ECETOC, 2007) were used. In this context we evaluated 104 cases. Comparable sensitivity was noted in 75% of the cases, increased sensitivity of metabolomics in 8%, and decreased sensitivity in 18% of the cases. In conclusion, these data suggest that metabolomics profiling has a similar sensitivity to the classical toxicological study (e.g. OECD 407) design. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

    EPA Science Inventory

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

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

    Cancer.gov

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

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

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

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

    2012-10-01

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

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

    EPA Science Inventory

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

  10. Comparison of fully wettable RPLC stationary phases for LC-MS-based cellular metabolomics.

    PubMed

    Si-Hung, Le; Causon, Tim J; Hann, Stephan

    2017-07-10

    Reversed-phase LC combined with high-resolution mass spectrometry (HRMS) is one of the most popular methods for cellular metabolomics studies. Due to the difficulties in analyzing a wide range of polarities encountered in the metabolome, 100%-wettable reversed-phase materials are frequently used to maximize metabolome coverage within a single analysis. Packed with silica-based sub-3 μm diameter particles, these columns allow high separation efficiency and offer a reasonable compromise for metabolome coverage within a single analysis. While direct performance comparison can be made using classical chromatographic characterization approaches, a comprehensive assessment of the column's performance for cellular metabolomics requires use of a full LC-HRMS workflow in order to reflect realistic study conditions used for cellular metabolomics. In this study, a comparison of several reversed-phase LC columns for metabolome analysis using such a dedicated workflow is presented. All columns were tested under the same analytical conditions on an LC-TOF-MS platform using a variety of authentic metabolite standards and biotechnologically relevant yeast cell extracts. Data on total workflow performance including retention behavior, peak capacity, coverage, and molecular feature extraction repeatability from these columns are presented with consideration for both nontargeted screening and differential metabolomics workflows using authentic standards and Pichia pastoris cell extract samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  13. Monitoring Ecological Impacts of Environmental Surface Waters using Cell-based Metabolomics

    EPA Science Inventory

    Optimized cell-based metabolomics has been used to study the impacts of contaminants in surface waters on human and fish metabolomes. This method has proven to be resource- and time-effective, as well as sustainable for long term and large scale studies. In the current study, cel...

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

    PubMed Central

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

    2013-01-01

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

  15. Metabolomics for measuring phytochemicals, and assessing human and animal responses to phytochemicals, in food science.

    PubMed

    McGhie, Tony K; Rowan, Daryl D

    2012-01-01

    Metabolomics, comprehensive metabolite analysis, is finding increasing application as a tool to measure and enable the manipulation of the phytochemical content of foods, to identify the measures of dietary intake, and to understand human and animal responses to phytochemicals in the diet. Recent applications of metabolomics directed toward understanding the role of phytochemicals in food and nutrition are reviewed.

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

    PubMed Central

    2012-01-01

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

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

    PubMed

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

    2008-02-01

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

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

    PubMed

    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 ( < 0.05 at the stability statistic test). All acylcarnitines and almost all biogenic amines were higher in castrated males than in gilts. Metabolites involved in tryptophan catabolism had the largest differences (i.e., delta = 20% for serotonin) between castrated males (higher) and gilts (lower). The level of several AA (Ala, Arg, Gly, His, Lys, Ser, Thr, and Trp) was higher in gilts (delta was from approximately 1.0 to approximately 4.8%) whereas products of AA catabolism (taurine, 2-aminoadipic acid, and methionine sulfoxide) were higher in castrated males (delta was approximately 5.0-6.0%), suggesting a 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

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

    PubMed

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

    2014-02-01

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

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

    PubMed Central

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

    2014-01-01

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

  1. NMR-based metabolomics: from sample preparation to applications in nutrition research.

    PubMed

    Brennan, Lorraine

    2014-11-01

    Metabolomics is the study of metabolites present in biological samples such as biofluids, tissue/cellular extracts and culture media. Measurement of these metabolites is achieved through use of analytical techniques such as NMR and mass spectrometry coupled to liquid chromatography. Combining metabolomic data with multivariate data analysis tools allows the elucidation of alterations in metabolic pathways under different physiological conditions. Applications of NMR-based metabolomics have grown in recent years and it is now widely used across a number of disciplines. The present review gives an overview of the developments in the key steps involved in an NMR-based metabolomics study. Furthermore, there will be a particular emphasis on the use of NMR-based metabolomics in nutrition research. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2016-06-01

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

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

    PubMed

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

    2017-04-01

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

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed

    Hamzeiy, Hamid; Cox, Jürgen

    2017-02-01

    Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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

    PubMed

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

    2015-11-01

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

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

    PubMed

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

    2014-10-01

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

  8. Metabolomic profile of children with recurrent respiratory infections.

    PubMed

    Bozzetto, Sara; Pirillo, Paola; Carraro, Silvia; Berardi, Mariangela; Cesca, Laura; Stocchero, Matteo; Giordano, Giuseppe; Zanconato, Stefania; Baraldi, Eugenio

    2017-01-01

    Recurrent respiratory infections (RRI) represent a widespread condition which has a severe social and economic impact. Immunostimulants are used for their prevention. It is crucial to better characterize children with RRI to refine their diagnosis and identify effective personalized prevention strategies. Metabolomics is a high-dimensional biological method that can be used for hypothesis-free biomarker profiling, examining a large number of metabolites in a given sample using spectroscopic techniques. Multivariate statistical data analysis then enables us to infer which metabolic information is relevant to the biological characterization of a given physiological or pathological condition. This can lead to the emergence of new, sometimes unexpected metabolites, and hitherto unknown metabolic pathways, enabling the formulation of new pathogenetic hypotheses, and the identification of new therapeutic targets. The aim of our pilot study was to apply mass-spectrometry-based metabolomics to the analysis of urine samples from children with RRI, comparing these children's biochemical metabolic profiles with those of healthy peers. We also compared the RRI children's and healthy controls' metabolomic urinary profiles after the former had received pidotimod treatment for 3 months to see whether this immunostimulant was associated with biochemical changes in the RRI children's metabolic profile. 13 children (age range 3-6 yeas) with RRI and 15 matched per age healthy peers with no history of respiratory diseases or allergies were enrolled. Their metabolomic urine samples were compared before and after the RRI children had been treated with pidotimod for a period of 3 months. Metabolomic analyses on the urine samples were done using mass spectrometry combined with ultra-performance liquid chromatography (UPLC-MS). The resulting spectroscopic data then underwent multivariate statistical analysis and the most relevant variables characterizing the two groups were identified

  9. Network Marker Selection for Untargeted LC-MS Metabolomics Data.

    PubMed

    Cai, Qingpo; Alvarez, Jessica A; Kang, Jian; Yu, Tianwei

    2017-02-17

    Untargeted metabolomics using high-resolution liquid chromatography-mass spectrometry (LC-MS) is becoming one of the major areas of high-throughput biology. Functional analysis, that is, analyzing the data based on metabolic pathways or the genome-scale metabolic network, is critical in feature selection and interpretation of metabolomics data. One of the main challenges in the functional analyses is the lack of the feature identity in the LC-MS data itself. By matching mass-to-charge ratio (m/z) values of the features to theoretical values derived from known metabolites, some features can be matched to one or more known metabolites. When multiple matchings occur, in most cases only one of the matchings can be true. At the same time, some known metabolites are missing in the measurements. Current network/pathway analysis methods ignore the uncertainty in metabolite identification and the missing observations, which could lead to errors in the selection of significant subnetworks/pathways. In this paper, we propose a flexible network feature selection framework that combines metabolomics data with the genome-scale metabolic network. The method adopts a sequential feature screening procedure and machine learning-based criteria to select important subnetworks and identify the optimal feature matching simultaneously. Simulation studies show that the proposed method has a much higher sensitivity than the commonly used maximal matching approach. For demonstration, we apply the method on a cohort of healthy subjects to detect subnetworks associated with the body mass index (BMI). The method identifies several subnetworks that are supported by the current literature, as well as detects some subnetworks with plausible new functional implications. The R code is available at http://web1.sph.emory.edu/users/tyu8/MSS.

  10. Vaginal microbiome and metabolome highlight specific signatures of bacterial vaginosis.

    PubMed

    Vitali, B; Cruciani, F; Picone, G; Parolin, C; Donders, G; Laghi, L

    2015-12-01

    In this study, we sought to find novel bacterial and metabolic hallmarks for bacterial vaginosis (BV). We studied the vaginal microbiome and metabolome of vaginal fluids from BV-affected patients (n = 43) and healthy controls (n = 37) by means of an integrated approach based on quantitative polymerase chain reaction (qPCR) and proton nuclear magnetic resonance ((1)H-NMR). The correlations between the clinical condition and vaginal bacterial communities were investigated by principal component analysis (PCA). To define the metabolomics signatures of BV, 100 discriminant analysis by projection on latent structure (PLS-DA) models were calculated. Bacterial signatures distinguishing the health condition and BV were identified by qPCR. Lactobacillus crispatus strongly featured the healthy vagina, while increased concentrations of Prevotella, Atopobium and Mycoplasma hominis specifically marked the infection. (1)H-NMR analysis has led to the identification and quantification of 17 previously unreported molecules. BV was associated with changes in the concentration of metabolites belonging to the families of amines, organic acids, short chain fatty acids, amino acids, nitrogenous bases and monosaccharides. In particular, maltose, kynurenine and NAD(+) primarily characterised the healthy status, while nicotinate, malonate and acetate were the best metabolic hallmarks of BV. This study helps to better understand the role of the vaginal microbiota and metabolome in the development of BV infection. We propose a molecular approach for the diagnosis of BV based on quantitative detection in the vaginal fluids of Atopobium, Prevotella and M. hominis, and nicotinate, malonate and acetate by combining qPCR and (1)H-NMR.

  11. Metabolomics in angiotensin II-induced cardiac hypertrophy.

    PubMed

    Mervaala, Eero; Biala, Agnieszka; Merasto, Saara; Lempiäinen, Juha; Mattila, Ismo; Martonen, Essi; Eriksson, Ove; Louhelainen, Marjut; Finckenberg, Piet; Kaheinen, Petri; Muller, Dominik N; Luft, Friedrich C; Lapatto, Risto; Oresic, Matej

    2010-02-01

    Angiotensin II (Ang II) induces mitochondrial dysfunction. We tested whether Ang II alters the "metabolomic" profile. We harvested hearts from 8-week-old double transgenic rats harboring human renin and angiotensinogen genes (dTGRs) and controls (Sprague-Dawley), all with or without Ang II type 1 receptor (valsartan) blockade. We used gas chromatography coupled with time-of-flight mass spectrometry to detect 247 intermediary metabolites. We used a partial least-squares discriminate analysis and identified 112 metabolites that differed significantly after corrections (false discovery rate q <0.05). We found great differences in the use of fatty acids as an energy source, namely, decreased levels of octanoic, oleic, and linoleic acids in dTGR (all P<0.01). The increase in cardiac hypoxanthine levels in dTGRs suggested an increase in purine degradation, whereas other changes supported an increased ketogenic amino acid tyrosine level, causing energy production failure. The metabolomic profile of valsartan-treated dTGRs more closely resembled Sprague-Dawley rats than untreated dTGRs. Mitochondrial respiratory chain activity of cytochrome C oxidase was decreased in dTGRs, whereas complex I and complex II were unaltered. Mitochondria from dTGR hearts showed morphological alterations suggesting increased mitochondrial fusion. Cardiac expression of the redox-sensitive and the cardioprotective metabolic sensor sirtuin 1 was increased in dTGRs. Interestingly, valsartan changed the level of 33 metabolites and induced mitochondrial biogenesis in Sprague-Dawley rats. Thus, distinct patterns of cardiac substrate use in Ang II-induced cardiac hypertrophy are associated with mitochondrial dysfunction. The finding underscores the importance of Ang II in the regulation of mitochondrial biogenesis and cardiac metabolomics, even in healthy hearts.

  12. Plasma Metabolomics in Human Pulmonary Tuberculosis Disease: A Pilot Study

    PubMed Central

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

    2014-01-01

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

  13. Fish mucus metabolome reveals fish life-history traits

    NASA Astrophysics Data System (ADS)

    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.

  14. Characterization of differences between blood sample matrices in untargeted metabolomics.

    PubMed

    Denery, Judith R; Nunes, Ashlee A K; Dickerson, Tobin J

    2011-02-01

    Large-scale proteomic and metabolomic technologies are increasingly gaining attention for their use in the diagnosis of human disease. In order to ensure the statistical power of relevant markers, such analyses must incorporate a large number of representative samples. While in a best-case scenario these samples are collected through a study design that is specifically tailored for the desired analysis, often studies must rely upon the analysis of large numbers of previously banked samples that may or may not have complete and accurate documentation of their associated collection and storage methods. In this study, several human blood matrices were analyzed and compared for the quality of metabolomic output. The sample types that were tested include plasma prepared with a variety of anticoagulants and serum collected by venipuncture and capillary blood collection protocols. Analysis with liquid chromatography-mass spectrometry (LC-MS) revealed only subtle differences between the various plasma preparation methods. Differences between the serum and plasma samples appear to be largely peptide/protein-based and are consistent with the biological distinction of the two matrices. Interestingly, the small molecule lysophosphatidylinositol was found to be in higher abundance in plasma, as a possible consequence of the effect of the intrinsic clotting cascade on adjacent metabolic pathways. Comparison of the small-molecule profiles of the capillary- and venipuncture-collected samples revealed 23 statistically significant compound differences between these sample types. Most of these features can be attributed to surfactants and detergents used to pretreat the skin in order to maintain the sterility of sample collection. However, several have identical mass and molecular formulas as endogenous human metabolites and could be erroneously attributed to actual metabolic perturbations. Understanding the extent of these matrix effects is important for control of systematic bias

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

    2014-01-01

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

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

    PubMed

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

    2017-07-16

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

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

    PubMed

    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 < 0.05), and intergroup comparison was done using Student's t-test (P < 0.05). Significant upregulation of estradiol-17-beta-3-sulfate, L-carnitine, 5-methylthioadenosine (MTA), 8-hydroxyadenine, 2-methylcitric acid, putrescine, and estrone-3-sulfate was seen in 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.

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

    PubMed Central

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

    2011-01-01

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

  20. Challenges of Inversely Estimating Jacobian from Metabolomics Data

    PubMed Central

    Sun, Xiaoliang; Länger, Bettina; Weckwerth, Wolfram

    2015-01-01

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

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

    PubMed Central

    2014-01-01

    Background Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species. Results To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins. Conclusion Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization

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

    PubMed

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

    2014-01-01

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

  3. Metabolomics of urinary tract infection: a new uroscope in town.

    PubMed

    Gupta, Ashish; Bansal, Navneeta; Houston, Brian

    2012-05-01

    Urinary tract infection (UTI) is a potentially life-threatening infectious disease. For rapid directed therapy of UTIs, it is essential to determine the causative microorganism. To date, there is no single test that has been proven to reliably, rapidly and accurately identify the etiologic organism in UTI. The molecular methods for diagnosing the cause of UTI and prognostic development of clinically important metabolomic evaluations and their limitations for use in the diagnosis and monitoring of infections are discussed in this review article. The application of the emerging investigative device NMR spectroscopy as a surrogate method for the diagnosis of UTI is also addressed.

  4. Metabolomics in the Studies of Islet Autoimmunity and Type 1 Diabetes

    PubMed Central

    Oresic, Matej

    2012-01-01

    The metabolome is sensitive to genetic and environmental factors contributing to complex diseases such as type 1 diabetes (T1D). Metabolomics is the study of biochemical and physiological processes involving metabolites. It is therefore one of the key platforms for the discovery and study of pathophysiological phenomena leading to T1D and the development of T1D-associated complications. Although the application of metabolomics in T1D research is still rare, metabolomic research has already advanced across the full spectrum, from disease progression to the development of diabetic complications. Metabolomic studies in T1D have contributed to an improved etiopathogenic understanding and demonstrated their potential in the clinic. For example, metabolomic data from recent T1D studies suggest that a specific metabolic profile, or metabotype, precedes islet autoimmunity and the development of overt T1D. These early metabolic changes are attributed to many biochemical pathways, thus suggesting a systemic change in metabolism which may be inborn. Based on this evidence, the role of the metabolome in the progression to T1D is therefore to facilitate specific biochemical processes associated with T1D, and to contribute to the development of a vulnerable state in which disease is more likely to be triggered. This may have important implications for the understanding of T1D pathophysiology and early disease detection and prevention. PMID:23804263

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

    PubMed

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

    2016-01-07

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

  6. A systems-level "misunderstanding": the plasma metabolome in Huntington's disease.

    PubMed

    Rosas, Herminia D; Doros, Gheorghe; Bhasin, Swati; Thomas, Beena; Gevorkian, Sona; Malarick, Keith; Matson, Wayne; Hersch, Steven M

    2015-07-01

    Huntington's disease (HD) is a rare neurodegenerative disease caused by the expansion of an N-terminal repeat in the huntingtin protein. The protein is expressed in all cells in the body; hence, peripheral tissues, such as blood, may recapitulate processes in the brain. The plasma metabolome may provide a window into active processes that influence brain health and a unique opportunity to noninvasively identify processes that may contribute to neurodegeneration. Alterations in metabolic pathways in brain have been shown to profoundly impact HD. Therefore, identification and quantification of critical metabolomic perturbations could provide novel biomarkers for disease onset and disease progression. We analyzed the plasma metabolomic profiles from 52 premanifest (PHD), 102 early symptomatic HD, and 140 healthy controls (NC) using liquid chromatography coupled with a highly sensitive electrochemical detection platform. Alterations in tryptophan, tyrosine, purine, and antioxidant pathways were identified, including many related to energetic and oxidative stress and derived from the gut microbiome. Multivariate statistical modeling demonstrated mutually distinct metabolomic profiles, suggesting that the processes that determine onset were likely distinct from those that determine progression. Gut microbiome-derived metabolites particularly differentiated the PHD metabolome, while the symptomatic HD metabolome was increasingly influenced by metabolites that may reflect mutant huntingtin toxicity and neurodegeneration. Understanding the complex changes in the delicate balance of the metabolome and the gut microbiome in HD, and how they relate to disease onset, progression, and phenotypic variability in HD are critical questions for future research.

  7. Pharma-metabolomics in neonatology: is it a dream or a fact?

    PubMed

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

    2012-01-01

    The 'omics' technologies represent analytical approaches that have a holistic view on molecules such as genes, transcripts, proteins and metabolites constituting a cell, tissue or organism. The profiling of genes, transcripts and proteins has been referred to as genomics, transcriptomics and proteomics. Finally, there is the youngest and most rapidly increasing of the "omics" disciplines: metabolomics. Metabolomics appears to be a new, very useful tool in neonatology, especially in the fields of pharma-metabolomics and nutri- metabolomics. Since it appears to be predictive and preventive, it can be considered the 'new clinical chemistry' for personalized neonatal medicine. At present, the use of metabolomics in neonatology is still in the pioneering phase. In clinical practice, only a limited number of metabolites are routinely measured in the biofluids of newborns by conventional analytical methods to study the metabolic status of the organism. However, the management of sick or preterm newborns might be improved if more information on perinatal/ neonatal maturational processes and their metabolic background were available. The aim of this review, after a general introduction on pharma-metabolomics, is to present the potential of NMR-based metabolomic analysis of newbom urine in neonatology in the field of pharmacology.

  8. Novel quantitative metabolomic approach for the study of stress responses of plant root metabolism.

    PubMed

    Li, Kefeng; Wang, Xu; Pidatala, Venkataramana R; Chang, Chi-Peng; Cao, Xiaohong

    2014-12-05

    Quantitative metabolomics (qMetabolomics) is a powerful tool for understanding the intricate metabolic processes involved in plant abiotic stress responses. qMetabolomics is hindered by the limited coverage and high cost of isotopically labeled standards. In this study, we first selected 271 metabolites which might play important roles in abiotic stress responses as the targets and established a comprehensive LC-MS/MS based qMetabolomic method. We then developed a novel metabolic labeling method using E. coli-Saccharomyces cerevisiae two-step cultivation for the production of uniformly (13)C-labeled metabolites as internal standards. Finally, we applied the developed qMetabolomic method to investigate the influence of Pb stress on maize root metabolism. The absolute concentration of 226 metabolites in maize roots was accurately quantified in a single run within 30 min. Our study also revealed that glycolysis, purine, pyrimidine, and phospholipids were the main metabolic pathways in maize roots involved in Pb stress response. To our knowledge, this is the most comprehensive qMetabolomic method for plant metabolomics thus far. We developed a simple and inexpensive metabolic labeling method which dramatically expanded the availability of uniformly (13)C labeled metabolites. Our findings also provided new insights of maize metabolic responses to Pb stress.

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

    PubMed

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

    2016-05-25

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

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

    PubMed Central

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

    2016-01-01

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

  11. A systems-level “misunderstanding”: the plasma metabolome in Huntington’s disease

    PubMed Central

    Rosas, Herminia D; Doros, Gheorghe; Bhasin, Swati; Thomas, Beena; Gevorkian, Sona; Malarick, Keith; Matson, Wayne; Hersch, Steven M

    2015-01-01

    Objective Huntington’s disease (HD) is a rare neurodegenerative disease caused by the expansion of an N-terminal repeat in the huntingtin protein. The protein is expressed in all cells in the body; hence, peripheral tissues, such as blood, may recapitulate processes in the brain. The plasma metabolome may provide a window into active processes that influence brain health and a unique opportunity to noninvasively identify processes that may contribute to neurodegeneration. Alterations in metabolic pathways in brain have been shown to profoundly impact HD. Therefore, identification and quantification of critical metabolomic perturbations could provide novel biomarkers for disease onset and disease progression. Methods We analyzed the plasma metabolomic profiles from 52 premanifest (PHD), 102 early symptomatic HD, and 140 healthy controls (NC) using liquid chromatography coupled with a highly sensitive electrochemical detection platform. Results Alterations in tryptophan, tyrosine, purine, and antioxidant pathways were identified, including many related to energetic and oxidative stress and derived from the gut microbiome. Multivariate statistical modeling demonstrated mutually distinct metabolomic profiles, suggesting that the processes that determine onset were likely distinct from those that determine progression. Gut microbiome-derived metabolites particularly differentiated the PHD metabolome, while the symptomatic HD metabolome was increasingly influenced by metabolites that may reflect mutant huntingtin toxicity and neurodegeneration. Interpretation Understanding the complex changes in the delicate balance of the metabolome and the gut microbiome in HD, and how they relate to disease onset, progression, and phenotypic variability in HD are critical questions for future research. PMID:26273688

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

    PubMed

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

    2016-05-01

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

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

    PubMed

    Klein, Matthias S; Shearer, Jane

    2016-01-01

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

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

    PubMed Central

    Klein, Matthias S.; Shearer, Jane

    2016-01-01

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

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

    PubMed

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

    2015-07-01

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

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

    PubMed Central

    Grapov, Dmitry; Barupal, Dinesh Kumar

    2017-01-01

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

  17. [The method for early diagnosis of the gastric cancer based metabolomics research].

    PubMed

    Furina, R R; Ryzhkov, V L; Mitrakova, N N; Koptina, A V; Safiullin, I K; Lychagin, K A; Eroshkin, P R

    2014-01-01

    This paper deals with the questions of the usage of metabolomics research results in the diagnosis of gastric cancer. The central idea metabolomics is to identify the specific biomarkers in a biological sample used in a diagnostics this disease. The volatile organic compounds--metabolites isolated from the urine samples from patients are considered as biomarkers. The paper also describes main methods of separation and identification of volatile organic compounds (gas chromatography, mass spectrometry) applied in metabolomics. The paper presents some results of laboratory research aimed at the detection of biomarkers of gastric cancer. The presented material will be of some help in solving the problems of early diagnosis of this disease.

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

    PubMed

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

    2017-01-01

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

  19. Eating at the Table of Another: Metabolomics of Host/Parasite Interactions

    PubMed Central

    Kafsack, Björn F.C.; Llinás, Manuel

    2010-01-01

    The application of metabolomics, the global analysis of metabolite levels, to the study of protozoan parasites has become an important tool for understanding the host/parasite relationship and holds promise for the development of direly needed therapeutics and improved diagnostics. Research advances over the past decade have opened the door for a systems biology approach to protozoan parasites with metabolomics providing a crucial readout of metabolic activity. In this review we highlight recent metabolomic approaches to protozoan parasites, including metabolite profiling, integration with genomics, transcription, and proteomic analysis, as well as the use of metabolic fingerprints for the diagnosis of parasitic infections. PMID:20159614

  20. Eating at the table of another: metabolomics of host-parasite interactions.

    PubMed

    Kafsack, Björn F C; Llinás, Manuel

    2010-02-18

    The application of metabolomics, the global analysis of metabolite levels, to the study of protozoan parasites has become an important tool for understanding the host-parasite relationship and holds promise for the development of direly needed therapeutics and improved diagnostics. Research advances over the past decade have opened the door for a systems biology approach to protozoan parasites with metabolomics, providing a crucial readout of metabolic activity. In this review, we highlight recent metabolomic approaches to protozoan parasites, including metabolite profiling, integration with genomics, transcription, and proteomic analysis, and the use of metabolic fingerprints for the diagnosis of parasitic infections.

  1. Systematic evaluation of serum and plasma collection on the endogenous metabolome.

    PubMed

    Zhou, Zhi; Chen, Yanhua; He, Jiuming; Xu, Jing; Zhang, Ruiping; Mao, Yan; Abliz, Zeper

    2017-02-01

    In metabolomics research, the use of different blood collection methods may influence endogenous metabolites. Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants. Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma.

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

    PubMed

    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.

  3. Metabolomics: a valuable tool for stem cell monitoring in regenerative medicine

    PubMed Central

    McNamara, Laura E.; Sjöström, Terje; Meek, R. M. Dominic; Oreffo, Richard O. C.; Su, Bo; Dalby, Matthew J.; Burgess, Karl E. V.

    2012-01-01

    Metabolomics is a method for investigation of changes in the global metabolite profile of cells. This paper discusses the technical application of the approach, considering metabolite extraction, separation, mass spectrometry and data interpretation. A particular focus is on the application of metabolomics to the study of stem cell physiology in the context of biomaterials and regenerative medicine. Case studies are used to illustrate key points, focusing on the use of metabolomics in the examination of mesenchymal stem cell responses to titania-nanopillared substrata designed for orthopaedic applications. PMID:22628210

  4. Multi-platform characterization of the human cerebrospinal fluid metabolome: a comprehensive and quantitative update

    PubMed Central

    2012-01-01

    Background Human cerebral spinal fluid (CSF) is known to be a rich source of small molecule biomarkers for neurological and neurodegenerative diseases. In 2007, we conducted a comprehensive metabolomic study and performed a detailed literature review on metabolites that could be detected (via metabolomics or other techniques) in CSF. A total of 308 detectable metabolites were identified, of which only 23% were shown to be routinely identifiable or quantifiable with the metabolomics technologies available at that time. The continuing advancement in analytical technologies along with the growing interest in CSF metabolomics has led us to re-visit the human CSF metabolome and to re-assess both its size and the level of coverage than can be achieved with today's technologies. Methods We used five analytical platforms, including nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), direct flow injection-mass spectrometry (DFI-MS/MS) and inductively coupled plasma-mass spectrometry (ICP-MS) to perform quantitative metabolomics on multiple human CSF samples. This experimental work was complemented with an extensive literature review to acquire additional information on reported CSF compounds, their concentrations and their disease associations. Results NMR, GC-MS and LC-MS methods allowed the identification and quantification of 70 CSF metabolites (as previously reported). DFI-MS/MS allowed the quantification of 78 metabolites (6 acylcarnitines, 13 amino acids, hexose, 42 phosphatidylcholines, 2 lyso-phosphatidylcholines and 14 sphingolipids), while ICP-MS provided quantitative results for 33 metal ions in CSF. Literature analysis led to the identification of 57 more metabolites. In total, 476 compounds have now been confirmed to exist in human CSF. Conclusions The use of improved metabolomic and other analytical techniques has led to a 54% increase in the known size of the human CSF metabolome

  5. Prediction of intracellular metabolic states from extracellular metabolomic data.

    PubMed

    Aurich, Maike K; Paglia, Giuseppe; Rolfsson, Óttar; Hrafnsdóttir, Sigrún; Magnúsdóttir, Manuela; Stefaniak, Magdalena M; Palsson, Bernhard Ø; Fleming, Ronan M T; Thiele, Ines

    Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well-suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context.

  6. Urine metabolomics for kidney cancer detection and biomarker discovery.

    PubMed

    Ganti, Sheila; Weiss, Robert H

    2011-01-01

    Renal cell carcinoma (RCC) is one of the few human cancers whose incidence is increasing. The disease regularly progresses asymptomatically and is frequently metastatic upon presentation, thereby necessitating the development of an early method of detection. A metabolomic approach for biomarker detection using urine as a biofluid is appropriate since the tumor is located in close proximity to the urinary space. By comparing the composition of urine from individuals with RCC to control individuals, differences in metabolite composition of this biofluid can be identified, and these data can be utilized to create a clinically applicable and, possibly, bedside assay. Recent studies have shown that sample handling and processing greatly influences the variability seen in the urinary metabolome of both cancer and control patients. Once a standard method of collection is developed, identifying metabolic derangements associated with RCC will also lead to the investigation of novel targets for therapeutic intervention. The objective of this review is to discuss existing methods for sample collection, processing, data analysis, and recent findings in this emerging field.

  7. Toward Supportive Data Collection Tools for Plant Metabolomics[w

    PubMed Central

    Jenkins, Helen; Johnson, Helen; Kular, Baldeep; Wang, Trevor; Hardy, Nigel

    2005-01-01

    Over recent years, a number of initiatives have proposed standard reporting guidelines for functional genomics experiments. Associated with these are data models that may be used as the basis of the design of software tools that store and transmit experiment data in standard formats. Central to the success of such data handling tools is their usability. Successful data handling tools are expected to yield benefits in time saving and in quality assurance. Here, we describe the collection of datasets that conform to the recently proposed data model for plant metabolomics known as ArMet (architecture for metabolomics) and illustrate a number of approaches to robust data collection that have been developed in collaboration between software engineers and biologists. These examples also serve to validate ArMet from the data collection perspective by demonstrating that a range of software tools, supporting data recording and data upload to central databases, can be built using the data model as the basis of their design. PMID:15888680

  8. MetaboAnalyst 3.0--making metabolomics more meaningful.

    PubMed

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

    2015-07-01

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

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

    PubMed Central

    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

  10. Metabolomics Profiling for Obstructive Sleep Apnea and Simple Snorers

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2017-06-06

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2007-12-01

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

  14. Global isotope metabolomics reveals adaptive strategies for nitrogen assimilation

    DOE PAGES

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

    2016-04-05

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

  15. Metabolomic insight into soy sauce through (1)H NMR spectroscopy.

    PubMed

    Ko, Bong-Kuk; Ahn, Hyuk-Jin; van den Berg, Frans; Lee, Cherl-Ho; Hong, Young-Shick

    2009-08-12

    Soy sauce, a well-known seasoning in Asia and throughout the world, consists of many metabolites that are produced during fermentation or aging and that have various health benefits. However, their comprehensive assessment has been limited due to targeted or instrumentally specific analysis. This paper presents for the first time a metabolic characterization of soy sauce, especially that aged up to 12 years, to obtain a global understanding of the metabolic variations through (1)H NMR spectroscopy coupled with multivariate pattern recognition techniques. Elevated amino acids and organic acids and the consumption of carbohydrate were associated with continuous involvement of microflora in aging for 12 years. In particular, continuous increases in the levels of betaine were found during aging for up to 12 years, demonstrating that microbial- or enzyme-related metabolites were also coupled with osmotolerant or halophilic bacteria present during aging. This work provides global insights into soy sauce through a (1)H NMR-based metabolomic approach that enhances the current understanding of the holistic metabolome and allows assessment of soy sauce quality.

  16. ¹³C NMR metabolomics: applications at natural abundance.

    PubMed

    Clendinen, Chaevien S; Lee-McMullen, Brittany; Williams, Caroline M; Stupp, Gregory S; Vandenborne, Krista; Hahn, Daniel A; Walter, Glenn A; Edison, Arthur S

    2014-09-16

    (13)C NMR has many advantages for a metabolomics study, including a large spectral dispersion, narrow singlets at natural abundance, and a direct measure of the backbone structures of metabolites. However, it has not had widespread use because of its relatively low sensitivity compounded by low natural abundance. Here we demonstrate the utility of high-quality (13)C NMR spectra obtained using a custom (13)C-optimized probe on metabolomic mixtures. A workflow was developed to use statistical correlations between replicate 1D (13)C and (1)H spectra, leading to composite spin systems that can be used to search publicly available databases for compound identification. This was developed using synthetic mixtures and then applied to two biological samples, Drosophila melanogaster extracts and mouse serum. Using the synthetic mixtures we were able to obtain useful (13)C-(13)C statistical correlations from metabolites with as little as 60 nmol of material. The lower limit of (13)C NMR detection under our experimental conditions is approximately 40 nmol, slightly lower than the requirement for statistical analysis. The (13)C and (1)H data together led to 15 matches in the database compared to just 7 using (1)H alone, and the (13)C correlated peak lists had far fewer false positives than the (1)H generated lists. In addition, the (13)C 1D data provided improved metabolite identification and separation of biologically distinct groups using multivariate statistical analysis in the D. melanogaster extracts and mouse serum.

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

    PubMed

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

    2013-12-17

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

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

    PubMed

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

    2015-06-01

    Vitamin D is linked to a number of adverse pregnancy outcomes through largely unknown mechanisms. This study was conducted to examine the role of vitamin D status in metabolomic profiles in a group of 30 pregnant, African American adolescents (17.1 ± 1.1 years) at midgestation (26.8 ± 2.8 weeks), in 15 adolescents with 25-hydroxy vitamin D (25(OH)D) ≥20 ng/mL, and in 15 teens with 25(OH)D <20 ng/mL. Serum metabolomic profiles were examined using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry. A novel hierarchical mixture model was used to evaluate differences in metabolite profiles between low and high groups. A total of 326 compounds were identified and included in subsequent statistical analyses. Eleven metabolites had significantly different means between the 2 vitamin D groups, after correcting for multiple hypothesis testing: pyridoxate, bilirubin, xylose, and cholate were higher, and leukotrienes, 1,2-propanediol, azelate, undecanedioate, sebacate, inflammation associated complement component 3 peptide (HWESASXX), and piperine were lower in serum from adolescents with 25(OH)D ≥20 ng/mL. Lower maternal vitamin D status at midgestation impacted serum metabolic profiles in pregnant adolescents. © The Author(s) 2014.

  19. Identification of salivary metabolomic biomarkers for oral cancer screening

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Toya, Yoshihiro; Shimizu, Hiroshi

    2013-11-01

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

  1. Global isotope metabolomics reveals adaptive strategies for nitrogen assimilation

    SciTech Connect

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

    2016-04-05

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

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

    PubMed

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

    2012-01-01

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

  3. Biomarkers of Whale Shark Health: A Metabolomic Approach

    PubMed Central

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

    2012-01-01

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

  4. Effect of sleep deprivation on the human metabolome.

    PubMed

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

    2014-07-22

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

  5. Comparative metabolomics of drought acclimation in model and forage legumes.

    PubMed

    Sanchez, Diego H; Schwabe, Franziska; Erban, Alexander; Udvardi, Michael K; Kopka, Joachim

    2012-01-01

    Water limitation has become a major concern for agriculture. Such constraints reinforce the urgent need to understand mechanisms by which plants cope with water deprivation. We used a non-targeted metabolomic approach to explore plastic systems responses to non-lethal drought in model and forage legume species of the Lotus genus. In the model legume Lotus. japonicus, increased water stress caused gradual increases of most of the soluble small molecules profiled, reflecting a global and progressive reprogramming of metabolic pathways. The comparative metabolomic approach between Lotus species revealed conserved and unique metabolic responses to drought stress. Importantly, only few drought-responsive metabolites were conserved among all species. Thus we highlight a potential impediment to translational approaches that aim to engineer traits linked to the accumulation of compatible solutes. Finally, a broad comparison of the metabolic changes elicited by drought and salt acclimation revealed partial conservation of these metabolic stress responses within each of the Lotus species, but only few salt- and drought-responsive metabolites were shared between all. The implications of these results are discussed with regard to the current insights into legume water stress physiology.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2015-01-01

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

  8. Discovery of metabolomics biomarkers for early detection of nephrotoxicity.

    PubMed

    Boudonck, Kurt J; Mitchell, Matthew W; Német, László; Keresztes, Lilla; Nyska, Abraham; Shinar, Doron; Rosenstock, Moti

    2009-04-01

    Drug-induced nephrotoxicity is a major concern, since many pharmacological compounds are filtered through the kidneys for excretion into urine. To discover biochemical biomarkers useful for early identification of nephrotoxicity, metabolomic experiments were performed on Sprague-Dawley Crl:CD (SD) rats treated with the nephrotoxins gentamicin, cisplatin, or tobramycin. Using a combination of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS), a global, nontargeted metabolomics analysis was performed on urine and kidney samples collected after one, five, and twenty-eight dosing days. Increases in polyamines and amino acids were observed in urine from drug-treated rats after a single dose, and prior to observable histological kidney damage and conventional clinical chemistry indications of nephrotoxicity. Thus, these metabolites are potential biomarkers for the early detection of drug-induced nephrotoxicity. Upon prolonged dosing, nephrotoxin-induced changes included a progressive loss of amino acids in urine, concomitant with a decrease in amino acids and nucleosides in kidney tissue. A nephrotoxicity prediction model, based on the levels of branched-chain amino acids in urine, distinguished nephrotoxin-treated samples from vehicle-control samples, with 100%, 93%, and 70% accuracy at day 28, day 5, and day 1, respectively. Thus, this panel of biomarkers may provide a noninvasive method to detect kidney injury long before the onset of histopathological kidney damage.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2016-07-27

    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.

  11. Metabolomic tools for secondary metabolite discovery from marine microbial symbionts.

    PubMed

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

    2014-06-05

    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.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

    Finkelstein, Julia L.; Pressman, Eva K.; Cooper, Elizabeth M.; Kent, Tera R.; Bar, Haim Y.

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  15. Alcohol Induced Alterations to the Human Fecal VOC Metabolome

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2017-02-15

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

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

    PubMed

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

    2016-06-17

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

  18. 13C NMR Metabolomics: Applications at Natural Abundance

    PubMed Central

    2015-01-01

    13C NMR has many advantages for a metabolomics study, including a large spectral dispersion, narrow singlets at natural abundance, and a direct measure of the backbone structures of metabolites. However, it has not had widespread use because of its relatively low sensitivity compounded by low natural abundance. Here we demonstrate the utility of high-quality 13C NMR spectra obtained using a custom 13C-optimized probe on metabolomic mixtures. A workflow was developed to use statistical correlations between replicate 1D 13C and 1H spectra, leading to composite spin systems that can be used to search publicly available databases for compound identification. This was developed using synthetic mixtures and then applied to two biological samples, Drosophila melanogaster extracts and mouse serum. Using the synthetic mixtures we were able to obtain useful 13C–13C statistical correlations from metabolites with as little as 60 nmol of material. The lower limit of 13C NMR detection under our experimental conditions is approximately 40 nmol, slightly lower than the requirement for statistical analysis. The 13C and 1H data together led to 15 matches in the database compared to just 7 using 1H alone, and the 13C correlated peak lists had far fewer false positives than the 1H generated lists. In addition, the 13C 1D data provided improved metabolite identification and separation of biologically distinct groups using multivariate statistical analysis in the D. melanogaster extracts and mouse serum. PMID:25140385

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

    PubMed Central

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

    2016-01-01

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

  20. Isotopic Ratio Outlier Analysis Global Metabolomics of Caenorhabditis elegans

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-10-03

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

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

    PubMed

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

    2014-07-01

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

  3. Impact of Exercise and Aging on Rat Urine and Blood Metabolome. An LC-MS Based Metabolomics Longitudinal Study

    PubMed Central

    Deda, Olga; Gika, Helen G.; Taitzoglou, Ioannis; Raikos, Νikolaos; Theodoridis, Georgios

    2017-01-01

    Aging is an inevitable condition leading to health deterioration and death. Regular physical exercise can moderate the metabolic phenotype changes of aging. However, only a small number of metabolomics-based studies provide data on the effect of exercise along with aging. Here, urine and whole blood samples from Wistar rats were analyzed in a longitudinal study to explore metabolic alterations due to exercise and aging. The study comprised three different programs of exercises, including a life-long protocol which started at the age of 5 months and ended at the age of 21 months. An acute exercise session was also evaluated. Urine and whole blood samples were collected at different time points and were analyzed by LC-MS/MS (Liquid Chromatography–tandem Mass Spectrometry). Based on their metabolic profiles, samples from trained and sedentary rats were differentiated. The impact on the metabolome was found to depend on the length of exercise period with acute exercise also showing significant changes. Metabolic alterations due to aging were equally pronounced in sedentary and trained rats in both urine and blood analyzed samples. PMID:28241477

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-06-01

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

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

    PubMed

    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.

  8. Webinar Presentation: Using Metabolomics with Neonatal Blood Spots to Discover Causes of Childhood Leukemia

    EPA Pesticide Factsheets

    This presentation, Using Metabolomics with Neonatal Blood Spots to Discover Causes of Childhood Leukemia, was given at the NIEHS/EPA Children's Centers 2016 Webinar Series: Exposome held on May 11, 2016.

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

    PubMed

    Wettersten, Hiromi I; Weiss, Robert H

    2013-01-01

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

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

    PubMed Central

    Aretz, Ina; Meierhofer, David

    2016-01-01

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

  11. Loss of Merlin induces metabolomic adaptation that engages dependence on Hedgehog signaling

    PubMed Central

    Das, Shamik; Jackson, William P.; Prasain, Jeevan K.; Hanna, Ann; Bailey, Sarah K.; Tucker, J. Allan; Bae, Sejong; Wilson, Landon S.; Samant, Rajeev S.; Barnes, Stephen; Shevde, Lalita A.

    2017-01-01

    The tumor suppressor protein Merlin is proteasomally degraded in breast cancer. We undertook an untargeted metabolomics approach to discern the global metabolomics profile impacted by Merlin in breast cancer cells. We discerned specific changes in glutathione metabolites that uncovered novel facets of Merlin in impacting the cancer cell metabolome. Concordantly, Merlin loss increased oxidative stress causing aberrant activation of Hedgehog signaling. Abrogation of GLI-mediated transcription activity compromised the aggressive phenotype of Merlin-deficient cells indicating a clear dependence of cells on Hedgehog signaling. In breast tumor tissues, GLI1 expression enhanced tissue identification and discriminatory power of Merlin, cumulatively presenting a powerful substantiation of the relationship between these two proteins. We have uncovered, for the first time, details of the tumor cell metabolomic portrait modulated by Merlin, leading to activation of Hedgehog signaling. Importantly, inhibition of Hedgehog signaling offers an avenue to target the vulnerability of tumor cells with loss of Merlin. PMID:28112165