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Sample records for isotope-resolved metabolomic analysis

  1. 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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

    Aims In this review we compare the advantages and disadvantages of different model biological systems for determining the metabolic functions of cells in complex environments, how they may change in different disease states, and respond to therapeutic interventions. Background All preclinical drug-testing models have advantages and drawbacks. We compare and contrast established cell, organoid and animal models with ex vivo organ or tissue culture and in vivo human experiments in the context of metabolic readout of drug efficacy. As metabolism reports directly on the biochemical state of cells and tissues, it can be very sensitive to drugs and/or other environmental changes. This is especially so when metabolic activities are probed by stable isotope tracing methods, which can also provide detailed mechanistic information on drug action. We have developed and been applying Stable Isotope-Resolved Metabolomics (SIRM) to examine metabolic reprogramming of human lung cancer cells in monoculture, in mouse xenograft/explant models, and in lung cancer patients in situ (Lane et al. 2011; T. W. Fan et al. 2011; T. W-M. Fan et al. 2012; T. W. Fan et al. 2012; Xie et al. 2014b; Ren et al. 2014a; Sellers et al. 2015b). We are able to determine the influence of the tumor microenvironment using these models. We have now extended the range of models to fresh human tissue slices, similar to those originally described by O. Warburg (Warburg 1923), which retain the native tissue architecture and heterogeneity with a paired benign versus cancer design under defined cell culture conditions. This platform offers an unprecedented human tissue model for preclinical studies on metabolic reprogramming of human cancer cells in their tissue context, and response to drug treatment (Xie et al. 2014a). As the microenvironment of the target human tissue is retained and individual patient's response to drugs is obtained, this platform promises to transcend current limitations of drug selection

  4. Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics

    PubMed Central

    2014-01-01

    Background Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Results Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. Conclusions By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade. PMID:25035808

  5. Multivariate Analysis in Metabolomics

    PubMed Central

    Worley, Bradley; Powers, Robert

    2015-01-01

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

  6. Revisiting Protocols for the NMR Analysis of Bacterial Metabolomes

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2016-06-21

    The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed. PMID:27188312

  8. Metabolomics analysis of shucked mussels' freshness.

    PubMed

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

    2016-08-15

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

  9. 13C NMR Metabolomics: INADEQUATE Network Analysis

    PubMed Central

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

    2015-01-01

    The many advantages of 13C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, 13C NMR offers a straightforward measurement of these compounds. Two-dimensional 13C-13C correlation experiments like INADEQUATE (incredible natural abundance double quantum transfer experiment) are ideal for the structural elucidation of natural products and have great but untapped potential for metabolomics analysis. We demonstrate a new and semi-automated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE datasets using an in silico INADEQUATE database. We demonstrate this approach using isotopically labeled Caenorhabditis elegans mixtures. PMID:25932900

  10. Error Propagation Analysis for Quantitative Intracellular Metabolomics

    PubMed Central

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

    2012-01-01

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

  11. Application of Metabolomics for High Resolution Phenotype Analysis

    PubMed Central

    Fukusaki, Eiichiro

    2014-01-01

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

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

    PubMed

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

    2016-06-21

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

  13. 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

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

    PubMed

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

    2016-01-01

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

  15. 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

  16. Metabolomic analysis of three Mollicute species.

    PubMed

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

    2014-01-01

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

  17. 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

  18. 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

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

    PubMed

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

    2016-01-01

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

  20. 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

  1. 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

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

    PubMed

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

    2012-01-01

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

  3. 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

  4. 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

  5. Analysis of metabolomic data using support vector machines.

    PubMed

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

    2008-10-01

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

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

    PubMed

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

    2016-08-15

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

  7. Amniotic Fluid Metabolomic Analysis in Spontaneous Preterm Birth

    PubMed Central

    Jones, Janice; Gunst, Phillip R.; Kacerovsky, Marian; Fortunato, Stephen J.; Saade, George R.; Basraon, Sanmaan

    2014-01-01

    Objective: To identify metabolic changes associated with early spontaneous preterm birth (PTB; <34 weeks) and term births, using high-throughput metabolomics of amniotic fluid (AF) in African American population. Method: In this study, AF samples retrieved from spontaneous PTB (<34 weeks [n = 25]) and normal term birth (n = 25) by transvaginal amniocentesis at the time of labor prior to delivery were subjected to metabolomics analysis. Equal volumes of samples were subjected to a standard solvent extraction method and analyzed using gas chromatography/mass spectrometry (MS) and liquid chromatography/MS/MS. Biochemicals were identified through matching of ion features to a library of biochemical standards. After log transformation and imputation of minimum observed values for each compound, t test, correlation tests, and false discovery rate corrections were used to identify differentially regulated metabolites. Data were controlled for clinical/demographic variables and medication during pregnancy. Results: Of 348 metabolites measured in AF samples, 121 metabolites had a gestational age effect and 116 differed significantly between PTB and term births. A majority of significantly altered metabolites could be classified into 3 categories, namely, (1) liver function, (2) fatty acid and coenzyme A (CoA) metabolism, and (3) histidine metabolism. The signature of altered liver function was apparent in many cytochrome P450-related pathways including bile acids, steroids, xanthines, heme, and phase II detoxification of xenobiotics with the largest fold change seen with pantothenol, a CoA synthesis inhibitor that was 8-fold more abundant in PTB. Conclusion: Global metabolic profiling of AF revealed alteration in hepatic metabolites involving xenobiotic detoxification and CoA metabolism in PTB. Maternal and/or fetal hepatic function differences may be developmentally related and its contribution PTB as a cause or effect of PTB is still unclear. PMID:24440995

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

    PubMed

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

    2010-03-01

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

  9. 1H NMR Metabolomics Analysis of Glioblastoma Subtypes

    PubMed Central

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

    2012-01-01

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

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

    PubMed Central

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

    2015-01-01

    Elementary flux modes (EFMs) are non-decomposable steady-state pathways in metabolic networks. They characterize phenotypes, quantify robustness or identify engineering targets. An EFM analysis (EFMA) is currently restricted to medium-scale models, as the number of EFMs explodes with the network's size. However, many topologically feasible EFMs are biologically irrelevant. We present thermodynamic EFMA (tEFMA), which calculates only the small(er) subset of thermodynamically feasible EFMs. We integrate network embedded thermodynamics into EFMA and show that we can use the metabolome to identify and remove thermodynamically infeasible EFMs during an EFMA without losing biologically relevant EFMs. Calculating only the thermodynamically feasible EFMs strongly reduces memory consumption and program runtime, allowing the analysis of larger networks. We apply tEFMA to study the central carbon metabolism of E. coli and find that up to 80% of its EFMs are thermodynamically infeasible. Moreover, we identify glutamate dehydrogenase as a bottleneck, when E. coli is grown on glucose and explain its inactivity as a consequence of network embedded thermodynamics. We implemented tEFMA as a Java package which is available for download at https://github.com/mpgerstl/tEFMA. PMID:25754258

  11. Metabolomics analysis in rats after administration of Datura stramonium

    PubMed Central

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

    2015-01-01

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

  12. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    PubMed

    Xia, Jianguo; Wishart, David S

    2016-01-01

    MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc. PMID:27603023

  13. Comparative Metabolomic and Lipidomic Analysis of Phenotype Stratified Prostate Cells

    PubMed Central

    Booher, Christiana L.; Rhim, Johng S.; Rainville, Paul; Langridge, James; Baker, Andrew; Nyalwidhe, Julius O.

    2015-01-01

    Prostate cancer (PCa) is the most prevalent cancer amongst men and the second most common cause of cancer related-deaths in the USA. Prostate cancer is a heterogeneous disease ranging from indolent asymptomatic cases to very aggressive life threatening forms. The goal of this study was to identify differentially expressed metabolites and lipids in prostate cells with different tumorigenic phenotypes. We have used mass spectrometry metabolomic profiling, lipidomic profiling, bioinformatic and statistical methods to identify, quantify and characterize differentially regulated molecules in five prostate derived cell lines. We have identified potentially interesting species of different lipid subclasses including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), glycerophosphoinositols (PIs) and other metabolites that are significantly upregulated in prostate cancer cells derived from distant metastatic sites. Transcriptomic and biochemical analysis of key enzymes that are involved in lipid metabolism demonstrate the significant upregulation of choline kinase alpha in the metastatic cells compared to the non-malignant and non-metastatic cells. This suggests that different de novo lipogenesis and other specific signal transduction pathways are activated in aggressive metastatic cells as compared to normal and non-metastatic cells. PMID:26244785

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

    PubMed

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

    2013-02-01

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

  15. 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...

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

    PubMed

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

    2014-07-15

    Metabolomics is the field of "-omics" research concerned with the comprehensive characterization of the small low-molecular-weight metabolites in biological samples. In epidemiology, it represents an emerging technology and an unprecedented opportunity to measure environmental and other exposures with improved precision and far less measurement error than with standard epidemiologic methods. Advances in the application of metabolomics in large-scale epidemiologic research are now being realized through a combination of improved sample preparation and handling, automated laboratory and processing methods, and reduction in costs. The number of epidemiologic studies that use metabolic profiling is still limited, but it is fast gaining popularity in this area. In the present article, we present a roadmap for metabolomic analyses in epidemiologic studies and discuss the various challenges these data pose to large-scale studies. We discuss the steps of data preprocessing, univariate and multivariate data analysis, correction for multiplicity of comparisons with correlated data, and finally the steps of cross-validation and external validation. As data from metabolomic studies accumulate in epidemiology, there is a need for large-scale replication and synthesis of findings, increased availability of raw data, and a focus on good study design, all of which will highlight the potential clinical impact of metabolomics in this field. PMID:24966222

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

    PubMed

    Costa, Christopher; Maraschin, Marcelo; Rocha, Miguel

    2016-06-01

    Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as nuclear magnetic resonance, gas or liquid chromatography, mass spectrometry, infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines. PMID:26853041

  18. Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The rumen plays a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in feed efficiency, rumen metabolomic analysis by ultra-performance liquid chromatography/ time-of-flight mass spectrometry (MS) and multivariate/u...

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

    PubMed

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

    2015-01-01

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

  20. Global Metabolomic Analysis of a Mammalian Host Infected with Bacillus anthracis

    PubMed Central

    Nguyen, Chinh T. Q.; Shetty, Vivekananda

    2015-01-01

    Whereas DNA provides the information to design life and proteins provide the materials to construct it, the metabolome can be viewed as the physiology that powers it. As such, metabolomics, the field charged with the study of the dynamic small-molecule fluctuations that occur in response to changing biology, is now being used to study the basis of disease. Here, we describe a comprehensive metabolomic analysis of a systemic bacterial infection using Bacillus anthracis, the etiological agent of anthrax disease, as the model pathogen. An organ and blood analysis identified approximately 400 metabolites, including several key classes of lipids involved in inflammation, as being suppressed by B. anthracis. Metabolite changes were detected as early as 1 day postinfection, well before the onset of disease or the spread of bacteria to organs, which testifies to the sensitivity of this methodology. Functional studies using pharmacologic inhibition of host phospholipases support the idea of a role of these key enzymes and lipid mediators in host survival during anthrax disease. Finally, the results are integrated to provide a comprehensive picture of how B. anthracis alters host physiology. Collectively, the results of this study provide a blueprint for using metabolomics as a platform to identify and study novel host-pathogen interactions that shape the outcome of an infection. PMID:26438791

  1. Global metabolomic analysis of a mammalian host infected with Bacillus anthracis.

    PubMed

    Nguyen, Chinh T Q; Shetty, Vivekananda; Maresso, Anthony W

    2015-12-01

    Whereas DNA provides the information to design life and proteins provide the materials to construct it, the metabolome can be viewed as the physiology that powers it. As such, metabolomics, the field charged with the study of the dynamic small-molecule fluctuations that occur in response to changing biology, is now being used to study the basis of disease. Here, we describe a comprehensive metabolomic analysis of a systemic bacterial infection using Bacillus anthracis, the etiological agent of anthrax disease, as the model pathogen. An organ and blood analysis identified approximately 400 metabolites, including several key classes of lipids involved in inflammation, as being suppressed by B. anthracis. Metabolite changes were detected as early as 1 day postinfection, well before the onset of disease or the spread of bacteria to organs, which testifies to the sensitivity of this methodology. Functional studies using pharmacologic inhibition of host phospholipases support the idea of a role of these key enzymes and lipid mediators in host survival during anthrax disease. Finally, the results are integrated to provide a comprehensive picture of how B. anthracis alters host physiology. Collectively, the results of this study provide a blueprint for using metabolomics as a platform to identify and study novel host-pathogen interactions that shape the outcome of an infection. PMID:26438791

  2. Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype

    DOE PAGESBeta

    Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; Cho, Yonghoon; Deutschbauer, Adam; Arkin, Adam; Northen, Trent; Siuzdak, Gary

    2011-01-01

    Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiplemore » pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.« less

  3. Non-invasive metabolomic analysis using a commercial NIR instrument for embryo selection

    PubMed Central

    Sfontouris, Ioannis A; Lainas, George T; Sakkas, Denny; Zorzovilis, Ioannis Z; Petsas, George K; Lainas, Trifon G

    2013-01-01

    CONTEXT: Metabolomics was introduced in human in vitro fertilization (IVF) for noninvasive identification of viable embryos with the highest developmental competence. AIMS: To determine whether embryo selection using a commercial version of metabolomic analysis leads to increased implantation rates (IRs) with fetal cardiac activity (FCA) compared with morphology evaluation alone. SETTING AND DESIGN: Randomized controlled trial from April to December 2010 at a private IVF unit. The study was terminated prematurely due to the market withdrawal of the instrument. MATERIALS AND METHODS: IVF patients ≥18 and ≤43 years with ≥4 × 2PN were randomly allocated to metabolomic analysis combined with embryo morphology (ViaMetrics-E; metabolomics + morphology group) or embryo morphology alone (morphology group). Cycles with frozen embryos, oocyte donations, or testicular biopsy were excluded. STATISTICAL ANALYSIS: Categorical and continuous data were analyzed for statistical significance using 2-tailed Fisher's exact test and t-test, respectively. Statistical significance was accepted when P > 0.05. RESULTS: A total of 125 patients were included in the study; 39 patients were allocated to metabolomics + morphology group and 86 patients to morphology group. Patients were stratified according to the day of embryo transfer (Days 2, 3, or 5). IRs with FCA were similar for Days 2 and 3 transfers in both groups. For Day 5 transfers, IRs with FCA were significantly higher in the metabolomics + morphology group (46.8% vs. 28.9%; P = 0.041; 95% confidence intervalp [CI]: 1.09-34.18). Pregnancy and live births rates were similar for Days 2, 3, and 5 in both groups. The study was terminated early following the voluntary market withdrawal of ViaMetrics-E in December 2010. CONCLUSIONS: Metabolomic analysis using the commercial near-infrared (NIR) instrument does not appear to have a beneficial effect on pregnancy and live births, with improvement in IR with FCA for Day 5 transfers

  4. Comprehensive analysis of transcriptome and metabolome analysis in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma

    PubMed Central

    Murakami, Yoshiki; Kubo, Shoji; Tamori, Akihiro; Itami, Saori; Kawamura, Etsushi; Iwaisako, Keiko; Ikeda, Kazuo; Kawada, Norifumi; Ochiya, Takahiro; Taguchi, Y-h

    2015-01-01

    Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are liver originated malignant tumors. Of the two, ICC has the worse prognosis because it has no reliable diagnostic markers and its carcinogenic mechanism is not fully understood. The aim of this study was to integrate metabolomics and transcriptomics datasets to identify variances if any in the carcinogenic mechanism of ICC and HCC. Ten ICC and 6 HCC who were resected surgically, were enrolled. miRNA and mRNA expression analysis were performed by microarray on ICC and HCC and their corresponding non-tumor tissues (ICC_NT and HCC_NT). Compound analysis was performed using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Principle component analysis (PCA) revealed that among the four sample groups (ICC, ICC_NT, HCC, and HCC_NT) there were 14 compounds, 62 mRNAs and 17 miRNAs with two distinct patterns: tumor and non-tumor, and ICC and non-ICC. We accurately (84.38%) distinguished ICC by the distinct pattern of its compounds. Pathway analysis using transcriptome and metabolome showed that several pathways varied between tumor and non-tumor samples. Based on the results of the PCA, we believe that ICC and HCC have different carcinogenic mechanism therefore knowing the specific profile of genes and compounds can be useful in diagnosing ICC. PMID:26538415

  5. Comprehensive analysis of transcriptome and metabolome analysis in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma.

    PubMed

    Murakami, Yoshiki; Kubo, Shoji; Tamori, Akihiro; Itami, Saori; Kawamura, Etsushi; Iwaisako, Keiko; Ikeda, Kazuo; Kawada, Norifumi; Ochiya, Takahiro; Taguchi, Y-h

    2015-01-01

    Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are liver originated malignant tumors. Of the two, ICC has the worse prognosis because it has no reliable diagnostic markers and its carcinogenic mechanism is not fully understood. The aim of this study was to integrate metabolomics and transcriptomics datasets to identify variances if any in the carcinogenic mechanism of ICC and HCC. Ten ICC and 6 HCC who were resected surgically, were enrolled. miRNA and mRNA expression analysis were performed by microarray on ICC and HCC and their corresponding non-tumor tissues (ICC_NT and HCC_NT). Compound analysis was performed using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Principle component analysis (PCA) revealed that among the four sample groups (ICC, ICC_NT, HCC, and HCC_NT) there were 14 compounds, 62 mRNAs and 17 miRNAs with two distinct patterns: tumor and non-tumor, and ICC and non-ICC. We accurately (84.38%) distinguished ICC by the distinct pattern of its compounds. Pathway analysis using transcriptome and metabolome showed that several pathways varied between tumor and non-tumor samples. Based on the results of the PCA, we believe that ICC and HCC have different carcinogenic mechanism therefore knowing the specific profile of genes and compounds can be useful in diagnosing ICC. PMID:26538415

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  9. Extending the isotopically resolved mass range of Orbitrap mass spectrometers.

    PubMed

    Shaw, Jared B; Brodbelt, Jennifer S

    2013-09-01

    The routine analysis of large biomolecules (greater than 30 kDa) has been a challenge for Orbitrap mass spectrometers due to the relatively high kinetic energy of ions entering and within the Orbitrap mass analyzer. This characteristic results in rapid signal decay for large biomolecules due to energetic collisions with background gas molecules. Here, we report a method to significantly enhance the analysis of large biomolecules in an Orbitrap mass spectrometer. The combination of reduced C-trap and higher energy collisional dissociation (HCD) cell bath gas pressures, using helium as the bath gas and trapping ions in the HCD cell prior to mass analysis, greatly increased sensitivity and reduced signal decay for large protein ions. As a result, isotopic resolution of monoclonal immunoglobulin G was achieved, and we have established a new high-mass record for which accurate mass measurement and isotopic resolution have been achieved. PMID:23909473

  10. Metabolomics Analysis of Seminal Plasma in Infertile Males with Kidney-Yang Deficiency: A Preliminary Study

    PubMed Central

    Chen, Xiang; Hu, Chao; Dai, Jican; Chen, Lei

    2015-01-01

    Traditional Chinese medicine (TCM) is an important treatment for male infertility, and its application to therapy is dependent on differentiation of TCM syndromes. This study aims to investigate the changes in metabolites and metabolic pathways in infertile males with Kidney-Yang Deficiency syndrome (KYDS) via metabolomics approaches. Seminal plasma samples were collected from 18 infertile males with KYDS and 18 fertile males. Liquid chromatography and mass spectrometry were used to characterize metabolomics profiles. Principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and pathway analysis were used for pattern recognition and metabolite identification. PCA and PLS-DA results differentiated the two groups of patients. Forty-one discriminating metabolites (18 in positive mode and 23 in negative mode) were identified. Seven metabolites were related to five potential metabolic pathways associated with biosynthesis and metabolism of aromatic amino acids, tricarboxylic acid cycle, and sphingolipid metabolism. The changes in metabolic pathways may play an important role in the origin of KYDS-associated male infertility. Metabolomics analysis of seminal plasma may be used to differentiate TCM syndromes of infertile males, but further research must be conducted. PMID:25945117

  11. Metabolomic analysis reveals mechanism of antioxidant butylated hydroxyanisole on lipid accumulation in Crypthecodinium cohnii.

    PubMed

    Sui, Xiao; Niu, Xiangfeng; Shi, Mengliang; Pei, Guangsheng; Li, Jinghan; Chen, Lei; Wang, Jiangxin; Zhang, Weiwen

    2014-12-24

    The heterotrophic dinoflagellate alga Crypthecodinium cohnii is known to accumulate lipids with a high fraction of docosahexaenoic acid (DHA). In this study, we first evaluated two antioxidant compounds, butylated hydroxyanisole (BHA) and propyl gallate (PG), for their effects on lipid accumulation in C. cohnii. The results showed that antioxidant BHA could increase lipid accumulation in C. cohnii by 8.80% at a final concentration of 30 μM, while PG had no obvious effect on lipid accumulation at the tested concentrations. To decipher the molecular mechanism responsible for the increased lipid accumulation by BHA, we employed an integrated GC-MS and LC-MS metabolomic approach to determine the time-series metabolic profiles with or without BHA, and then subjected the metabolomic data to a principal component analysis (PCA) and a weighted gene coexpression network analysis (WGCNA) network analyses to identify the key metabolic modules and metabolites possibly relevant to the increased lipid accumulation. LC-MS analysis showed that several metabolites, including NADPH, could be important for the stimulation role of BHA on lipid accumulation. Meanwhile GC-MS and network analyses allowed identification of eight metabolic modules and nine hub metabolites possibly relevant to the stimulation role of BHA in C. cohnii. The study provided a metabolomics view of the BHA mode of action on lipid accumulation in C. cohnii, and the information could be valuable for a better understanding of antioxidant effects on lipid accumulation in other microalgae as well. PMID:25436856

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

    PubMed

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

    2014-10-01

    Various combinations of acetate (Ac), Fe(2+) and high light (HL) stress conditions were evaluated to maximize astaxanthin accumulation and biomass production in Haematococcus pluvialis, and then GC-MS and LC-MS based metabolomics were applied to determine molecular mechanisms responsible for enhancing astaxanthin accumulation under the stress conditions. With the optimized analytical protocols, the GC-MS and LC-MS analyses allowed identification of 93 stable and 24 unstable intracellular metabolites from H. pluvialis, respectively. In addition, a metabolic network was constructed based on GC-MS metabolomic datasets using a weighted correlation network analysis (WGCNA) approach. The network analysis uncovered 2, 1 and 1 distinguished metabolic modules highly associated with HL, Fe(2+) & HL, and Ac & Fe(2+) & HL conditions, respectively. Finally, LC-MS analysis found that AKG, Glu and R5P may be metabolites associated with the Fe(2+) & HL condition. The study provided the first metabolomic view of cell growth and astaxanthin accumulation in H. pluvialis. PMID:25164345

  13. LC-MS analysis of the plasma metabolome--a novel sample preparation strategy.

    PubMed

    Skov, Kasper; Hadrup, Niels; Smedsgaard, Jørn; Frandsen, Henrik

    2015-01-26

    Blood plasma is a well-known body fluid often analyzed in studies on the effects of toxic compounds as physiological or chemical induced changes in the mammalian body are reflected in the plasma metabolome. Sample preparation prior to LC-MS based analysis of the plasma metabolome is a challenge as plasma contains compounds with very different properties. Besides, proteins, which usually are precipitated with organic solvent, phospholipids, are known to cause ion suppression in electrospray mass spectrometry. We have compared two different sample preparation techniques prior to LC-qTOF analysis of plasma samples: the first is protein precipitation; the second is protein precipitation followed by solid phase extraction with sub-fractionation into three sub-samples: a phospholipid, a lipid and a polar sub-fraction. Molecular feature extraction of the data files from LC-qTOF analysis of the samples revealed 1792 molecular features from the protein precipitation procedure. The protein precipitation followed by solid phase extraction procedure with three sub-samples gave a total of 4234 molecular features. This suggests that sub-sampling into polar, lipid and phospholipid fractions enables extraction of more metabolomic information as compared to protein precipitation alone. Chromatography showed good separation of the metabolites with little retention time drift (<1s) and a mass accuracy below 3 ppm was observed. The performance of the method was investigated using plasma samples from rats administered the environmental pollutant perfluorononanoic acid. PMID:25531874

  14. Individualized therapy of HHT driven by network analysis of metabolomic profiles

    PubMed Central

    2011-01-01

    Background Hereditary Hemorrhagic Telangiectasia (HHT) is an autosomal dominant disease with a varying range of phenotypes involving abnormal vasculature primarily manifested as arteriovenous malformations in various organs, including the nose, brain, liver, and lungs. The varied presentation and involvement of different organ systems makes the choice of potential treatment medications difficult. Results A patient with a mixed-clinical presentation and presumed diagnosis of HHT, severe exertional dyspnea, and diffuse pulmonary shunting at the microscopic level presented for treatment. We sought to analyze her metabolomic plasma profile to assist with pharmacologic treatment selection. Fasting serum samples from 5 individuals (4 healthy and 1 with HHT) were metabolomically profiled. A global metabolic network reconstruction, Recon 1, was used to help guide the choice of medication via analysis of the differential metabolism between the patient and healthy controls using metabolomic data. Flux Balance Analysis highlighted changes in metabolic pathway activity, notably in nitric oxide synthase (NOS), which suggested a potential link between changes in vascular endothelial function and metabolism. This finding supported the use of an already approved medication, bevacizumab (Avastin). Following 2 months of treatment, the patient's metabolic profile shifted, becoming more similar to the control subject profiles, suggesting that the treatment was addressing at least part of the pathophysiological state. Conclusions In this 'individualized case study' of personalized medicine, we carry out untargeted metabolomic profiling of a patient and healthy controls. Rather than filtering the data down to a single value, these data are analyzed in the context of a network model of metabolism, in order to simulate the biochemical phenotypic differences between healthy and disease states; the results then guide the therapy. This presents one approach to achieving the goals of

  15. Metabolic versatility in Haemophilus influenzae: a metabolomic and genomic analysis

    PubMed Central

    Othman, Dk Seti Maimonah Pg; Schirra, Horst; McEwan, Alastair G.; Kappler, Ulrike

    2014-01-01

    Haemophilus influenzae is a host adapted human pathogen known to contribute to a variety of acute and chronic diseases of the upper and lower respiratory tract as well as the middle ear. At the sites of infection as well as during growth as a commensal the environmental conditions encountered by H. influenzae will vary significantly, especially in terms of oxygen availability, however, the mechanisms by which the bacteria can adapt their metabolism to cope with such changes have not been studied in detail. Using targeted metabolomics the spectrum of metabolites produced during growth of H. influenzae on glucose in RPMI-based medium was found to change from acetate as the main product during aerobic growth to formate as the major product during anaerobic growth. This change in end-product is likely caused by a switch in the major route of pyruvate degradation. Neither lactate nor succinate or fumarate were major products of H. influenzae growth under any condition studied. Gene expression studies and enzyme activity data revealed that despite an identical genetic makeup and very similar metabolite production profiles, H. influenzae strain Rd appeared to favor glucose degradation via the pentose phosphate pathway, while strain 2019, a clinical isolate, showed higher expression of enzymes involved in glycolysis. Components of the respiratory chain were most highly expressed during microaerophilic and anaerobic growth in both strains, but again clear differences existed in the expression of genes associated e.g., with NADH oxidation, nitrate and nitrite reduction in the two strains studied. Together our results indicate that H. influenzae uses a specialized type of metabolism that could be termed “respiration assisted fermentation” where the respiratory chain likely serves to alleviate redox imbalances caused by incomplete glucose oxidation, and at the same time provides a means of converting a variety of compounds including nitrite and nitrate that arise as part

  16. Metabolic versatility in Haemophilus influenzae: a metabolomic and genomic analysis.

    PubMed

    Othman, Dk Seti Maimonah Pg; Schirra, Horst; McEwan, Alastair G; Kappler, Ulrike

    2014-01-01

    Haemophilus influenzae is a host adapted human pathogen known to contribute to a variety of acute and chronic diseases of the upper and lower respiratory tract as well as the middle ear. At the sites of infection as well as during growth as a commensal the environmental conditions encountered by H. influenzae will vary significantly, especially in terms of oxygen availability, however, the mechanisms by which the bacteria can adapt their metabolism to cope with such changes have not been studied in detail. Using targeted metabolomics the spectrum of metabolites produced during growth of H. influenzae on glucose in RPMI-based medium was found to change from acetate as the main product during aerobic growth to formate as the major product during anaerobic growth. This change in end-product is likely caused by a switch in the major route of pyruvate degradation. Neither lactate nor succinate or fumarate were major products of H. influenzae growth under any condition studied. Gene expression studies and enzyme activity data revealed that despite an identical genetic makeup and very similar metabolite production profiles, H. influenzae strain Rd appeared to favor glucose degradation via the pentose phosphate pathway, while strain 2019, a clinical isolate, showed higher expression of enzymes involved in glycolysis. Components of the respiratory chain were most highly expressed during microaerophilic and anaerobic growth in both strains, but again clear differences existed in the expression of genes associated e.g., with NADH oxidation, nitrate and nitrite reduction in the two strains studied. Together our results indicate that H. influenzae uses a specialized type of metabolism that could be termed "respiration assisted fermentation" where the respiratory chain likely serves to alleviate redox imbalances caused by incomplete glucose oxidation, and at the same time provides a means of converting a variety of compounds including nitrite and nitrate that arise as part of

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

    PubMed Central

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

    2014-01-01

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

  18. Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

    PubMed Central

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide–consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry–based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level. PMID:25486521

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

    PubMed

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide-consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry-based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level. PMID:25486521

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

    PubMed

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

    2014-08-01

    A serum metabolomics method based on rapid resolution liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RRLC-Q-TOF-MS) was performed for a holistic evaluation of the metabolic changes of collagen-induced arthritis (CIA) in rats and to assess the interventional effects of type II collagen (CII) in this model. Partial least-squares-discriminant analysis (PLS-DA) was employed to study the metabolic profiling of CIA rats and control rats. Ten metabolites, namely, 12(S)-HHTrE, 12(S)-HEPE, PGE2, TXB2, 12(S)-HETE, LysoPE(16:0), PE(O-18:0/0:0), Lyso-PE(18:2), Lyso-PE(20:4), and Lyso-PC(22:5) were identified as differential metabolites associated with the pathogenesis of CIA. These results suggested that dysregulation of the arachidonic acid (AA) and phospholipid metabolic networks is involved in the pathomechanism of CIA. Differential metabolomics and histopathological analyses demonstrated that CII inhibits the progress of arthritis. Furthermore, the therapeutic effects of CII on CIA may involve regulation of the disordered AA and phospholipid metabolic networks. This metabolomics study provides new insights into the pathogenesis of arthritis and, furthermore, indicates the potential mechanism underlying the significantly increased prevalence of metabolic syndrome, defined as a clustering of cardiovascular disease (CVD) risk factors, in arthritis patients. PMID:24814225

  1. Influence of Missing Values Substitutes on Multivariate Analysis of Metabolomics Data

    PubMed Central

    Gromski, Piotr S.; Xu, Yun; Kotze, Helen L.; Correa, Elon; Ellis, David I.; Armitage, Emily Grace; Turner, Michael L.; Goodacre, Royston

    2014-01-01

    Missing values are known to be problematic for the analysis of gas chromatography-mass spectrometry (GC-MS) metabolomics data. Typically these values cover about 10%–20% of all data and can originate from various backgrounds, including analytical, computational, as well as biological. Currently, the most well known substitute for missing values is a mean imputation. In fact, some researchers consider this aspect of data analysis in their metabolomics pipeline as so routine that they do not even mention using this replacement approach. However, this may have a significant influence on the data analysis output(s) and might be highly sensitive to the distribution of samples between different classes. Therefore, in this study we have analysed different substitutes of missing values namely: zero, mean, median, k-nearest neighbours (kNN) and random forest (RF) imputation, in terms of their influence on unsupervised and supervised learning and, thus, their impact on the final output(s) in terms of biological interpretation. These comparisons have been demonstrated both visually and computationally (classification rate) to support our findings. The results show that the selection of the replacement methods to impute missing values may have a considerable effect on the classification accuracy, if performed incorrectly this may negatively influence the biomarkers selected for an early disease diagnosis or identification of cancer related metabolites. In the case of GC-MS metabolomics data studied here our findings recommend that RF should be favored as an imputation of missing value over the other tested methods. This approach displayed excellent results in terms of classification rate for both supervised methods namely: principal components-linear discriminant analysis (PC-LDA) (98.02%) and partial least squares-discriminant analysis (PLS-DA) (97.96%) outperforming other imputation methods. PMID:24957035

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

    PubMed Central

    2013-01-01

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

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

    PubMed

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

    2015-08-01

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

  4. Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

    PubMed

    Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

    2016-02-01

    Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. PMID:26032167

  5. Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

    PubMed

    Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

    2016-08-12

    Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified. PMID:27393630

  6. Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

    PubMed Central

    Chen, Yingrong; Ma, Zhihong; Min, Lishan; Li, Hongwei; Wang, Bin; Zhong, Jing; Dai, Licheng

    2015-01-01

    Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC) curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that glycerophospho-N-arachidonoyl ethanolamine (GpAEA) and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer. PMID:25961003

  7. Metabolomics in multiple sclerosis.

    PubMed

    Bhargava, Pavan; Calabresi, Peter A

    2016-04-01

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

  8. LC-MS metabolomics from study design to data-analysis – using a versatile pathogen as a test case

    PubMed Central

    Berg, Maya; Vanaerschot, Manu; Jankevics, Andris; Cuypers, Bart; Breitling, Rainer; Dujardin, Jean-Claude

    2013-01-01

    Thanks to significant improvements in LC-MS technology, metabolomics is increasingly used as a tool to discriminate the responses of organisms to various stimuli or drugs. In this minireview we discuss all aspects of the LC-MS metabolomics pipeline, using a complex and versatile model organism, Leishmania donovani, as an illustrative example. The benefits of a hyphenated mass spectrometry platform and a detailed overview of the entire experimental pipeline from sampling, sample storage and sample list set-up to LC-MS measurements and the generation of meaningful results with state-of-the-art data-analysis software will be thoroughly discussed. Finally, we also highlight important pitfalls in the processing of LC-MS data and comment on the benefits of implementing metabolomics in a systems biology approach. PMID:24688684

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  11. Grade-dependent metabolic reprogramming in kidney cancer revealed by combined proteomics and metabolomics analysis

    PubMed Central

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; Bianchi, Cristina; Johnstone, Megan E.; Donohoe, Dallas R.; Trott, Josephine F.; Aboud, Omran Abu; Stirdivant, Steven; Neri, Bruce; Wolfert, Robert; Stewart, Benjamin; Perego, Roberto; Hsieh, James J.; Weiss, Robert H.

    2015-01-01

    Kidney cancer (or renal cell carcinoma [RCC]) is known as “the internist’s tumor” because it has protean systemic manifestations suggesting it utilizes complex, non-physiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the VHL tumor suppressor, in characterizing higher grade tumors we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, while the β-oxidation pathway is inhibited leading to increased fatty acyl-carnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared to other metabolic pathways. Together, our results offer a rationale to evaluate novel anti-metabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC. PMID:25952651

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

    PubMed Central

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

    2011-01-01

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

  13. Use of a pre-analysis osmolality normalisation method to correct for variable urine concentrations and for improved metabolomic analyses.

    PubMed

    Chetwynd, Andrew J; Abdul-Sada, Alaa; Holt, Stephen G; Hill, Elizabeth M

    2016-01-29

    Metabolomics analyses of urine have the potential to provide new information on the detection and progression of many disease processes. However, urine samples can vary significantly in total solute concentration and this presents a challenge to achieve high quality metabolomic datasets and the detection of biomarkers of disease or environmental exposures. This study investigated the efficacy of pre- and post-analysis normalisation methods to analyse metabolomic datasets obtained from neat and diluted urine samples from five individuals. Urine samples were extracted by solid phase extraction (SPE) prior to metabolomic analyses using a sensitive nanoflow/nanospray LC-MS technique and the data analysed by principal component analyses (PCA). Post-analysis normalisation of the datasets to either creatinine or osmolality concentration, or to mass spectrum total signal (MSTS), revealed that sample discrimination was driven by the dilution factor of urine rather than the individual providing the sample. Normalisation of urine samples to equal osmolality concentration prior to LC-MS analysis resulted in clustering of the PCA scores plot according to sample source and significant improvements in the number of peaks common to samples of all three dilutions from each individual. In addition, the ability to identify discriminating markers, using orthogonal partial least squared-discriminant analysis (OPLS-DA), was greatly improved when pre-analysis normalisation to osmolality was compared with post-analysis normalisation to osmolality and non-normalised datasets. Further improvements for peak area repeatability were observed in some samples when the pre-analysis normalisation to osmolality was combined with a post-analysis mass spectrum total useful signal (MSTUS) or MSTS normalisation. Future adoption of such normalisation methods may reduce the variability in metabolomics analyses due to differing urine concentrations and improve the discovery of discriminating metabolites

  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. PMID:25344987

  15. Automated charge state determination of complex isotope-resolved mass spectra by peak-target Fourier transform.

    PubMed

    Chen, Li; Yap, Yee Leng

    2008-01-01

    This study describes a new algorithm for charge state determination of complex isotope-resolved mass spectra. This algorithm is based on peak-target Fourier transform (PTFT) of isotope packets. It is modified from the widely used Fourier transform method because Fourier transform may give ambiguous charge state assignment for low signal-to-noise ratio (S/N) or overlapping isotopic clusters. The PTFT algorithm applies a novel "folding" strategy to enhance peaks that are symmetrically spaced about the targeted peak before applying the FT. The "folding" strategy multiplies each point to the high-m/z side of the targeted peak by its counterpart on the low-m/z side. A Fourier transform of this "folded" spectrum is thus simplified, emphasizing the charge state of the "chosen" ion, whereas ions of other charge states contribute less to the transformed data. An intensity-dependent technique is also proposed for charge state determination from frequency signals. The performance of PTFT is demonstrated using experimental electrospray ionization Fourier transform ion cyclotron resonance mass spectra. The results show that PTFT is robust for charge state determination of low S/N and overlapping isotopic clusters, and also useful for manual verification of potential hidden isotopic clusters that may be missed by the current analysis algorithms, i.e., AID-MS or THRASH. PMID:18293485

  16. 1H nuclear magnetic resonance-based extracellular metabolomic analysis of multidrug resistant Tca8113 oral squamous carcinoma cells

    PubMed Central

    WANG, HUI; CHEN, JIAO; FENG, YUN; ZHOU, WENJIE; ZHANG, JIHUA; YU, YU; WANG, XIAOQIAN; ZHANG, PING

    2015-01-01

    A major obstacle of successful chemotherapy is the development of multidrug resistance (MDR) in the cancer cells, which is difficult to reverse. Metabolomic analysis, an emerging approach that has been increasingly applied in various fields, is able to reflect the unique chemical fingerprints of specific cellular processes in an organism. The assessment of such metabolite changes can be used to identify novel therapeutic biomarkers. In the present study, 1H nuclear magnetic resonance (NMR) spectroscopy was used to analyze the extracellular metabolomic spectrum of the Tca8113 oral squamous carcinoma cell line, in which MDR was induced using the carboplatin (CBP) and pingyangmycin (PYM) chemotherapy drugs in vitro. The data were analyzed using the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods. The results demonstrated that the extracellular metabolomic spectrum of metabolites such as glutamate, glycerophosphoethanol amine, α-Glucose and β-Glucose for the drug-induced Tca8113 cells was significantly different from the parental Tca8113 cell line. A number of biochemicals were also significantly different between the groups based on their NMR spectra, with drug-resistant cells presenting relatively higher levels of acetate and lower levels of lactate. In addition, a significantly higher peak was observed at δ 3.35 ppm in the spectrum of the PYM-induced Tca8113 cells. Therefore, 1H NMR-based metabolomic analysis has a high potential for monitoring the formation of MDR during clinical tumor chemotherapy in the future. PMID:26137105

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

    PubMed Central

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

    2016-01-01

    Arsenic is a widespread metalloid in environment, whose exposure has been associated with a broad spectrum of toxic effects. However, a global view of arsenic-induced male reproductive toxicity is still lack, and the underlying mechanisms remain largely unclear. Our results revealed that arsenic exposure decreased testosterone level and reduced sperm quality in rats. By conducting an integrated proteomics and metabolomics analysis, the present study aims to investigate the global influence of arsenic exposure on the proteome and metabolome in rat testis. The abundance of 70 proteins (36 up-regulated and 34 down-regulated) and 13 metabolites (8 increased and 5 decreased) were found to be significantly altered by arsenic treatment. Among these, 19 proteins and 2 metabolites were specifically related to male reproductive system development and function, including spermatogenesis, sperm function and fertilization, fertility, internal genitalia development, and mating behavior. It is further proposed that arsenic mainly impaired spermatogenesis and fertilization via aberrant modulation of these male reproduction-related proteins and metabolites, which may be mediated by the ERK/AKT/NF-κB-dependent signaling pathway. Overall, these findings will aid our understanding of the mechanisms responsible for arsenic-induced male reproductive toxicity, and from such studies useful biomarkers indicative of arsenic exposure could be discovered. PMID:27585557

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

    PubMed

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

    2011-05-01

    Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy. PMID:21348635

  19. In vitro nematicidal activity of aryl hydrazones and comparative GC-MS metabolomics analysis.

    PubMed

    Eloh, Kodjo; Demurtas, Monica; Deplano, Alessandro; Ngoutane Mfopa, Alvine; Murgia, Antonio; Maxia, Andrea; Onnis, Valentina; Caboni, Pierluigi

    2015-11-18

    A series of aryl hydrazones were synthesized and in vitro assayed for their activity on the root-knot nematode Meloidogyne incognita. The phenylhydrazones of thiophene-2-carboxyaldehyde 5, 3-methyl-2-thiophenecarboxyaldehyde, 6, and salicylaldehyde, 2, were the most potent with EC50/48h values of 16.6 ± 2.2, 23.2 ± 2.7, and 24.3 ± 1.4 mg/L, respectively. A GC-MS metabolomics analysis, after in vitro nematode treatment with hydrazone 6 at 100 mg/L for 12 h, revealed elevated levels of fatty acids such as lauric acid, stearic acid, 2-octenoic acid, and palmitic acid. Whereas control samples showed the highest levels of monoacylglycerols such as monostearin and 2-monostearin, surprisingly, 2 h after treatment with hydrazone 6, nematodes excreted 3 times the levels of ammonia eliminated in the same conditions by controls. Thus, phenylhydrazones may represent a good scaffold in the discovery and synthesis of new nematicidal compounds, and a metabolomics approach may be helpful in understanding their mechanisms of toxicity and mode of action. PMID:26528945

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

    PubMed

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

    2016-01-01

    Arsenic is a widespread metalloid in environment, whose exposure has been associated with a broad spectrum of toxic effects. However, a global view of arsenic-induced male reproductive toxicity is still lack, and the underlying mechanisms remain largely unclear. Our results revealed that arsenic exposure decreased testosterone level and reduced sperm quality in rats. By conducting an integrated proteomics and metabolomics analysis, the present study aims to investigate the global influence of arsenic exposure on the proteome and metabolome in rat testis. The abundance of 70 proteins (36 up-regulated and 34 down-regulated) and 13 metabolites (8 increased and 5 decreased) were found to be significantly altered by arsenic treatment. Among these, 19 proteins and 2 metabolites were specifically related to male reproductive system development and function, including spermatogenesis, sperm function and fertilization, fertility, internal genitalia development, and mating behavior. It is further proposed that arsenic mainly impaired spermatogenesis and fertilization via aberrant modulation of these male reproduction-related proteins and metabolites, which may be mediated by the ERK/AKT/NF-κB-dependent signaling pathway. Overall, these findings will aid our understanding of the mechanisms responsible for arsenic-induced male reproductive toxicity, and from such studies useful biomarkers indicative of arsenic exposure could be discovered. PMID:27585557

  1. Metabolomic differentiation of Cannabis sativa cultivars using 1H NMR spectroscopy and principal component analysis.

    PubMed

    Choi, Young Hae; Kim, Hye Kyong; Hazekamp, Arno; Erkelens, Cornelis; Lefeber, Alfons W M; Verpoorte, Robert

    2004-06-01

    The metabolomic analysis of 12 Cannabis sativa cultivars was carried out by 1H NMR spectroscopy and multivariate analysis techniques. Principal component analysis (PCA) of the 1H NMR spectra showed a clear discrimination between those samples by principal component 1 (PC1) and principal component 3 (PC3) in cannabinoid fraction. The loading plot of PC value obtained from all 1)H NMR signals shows that Delta9-tetrahydrocannabinolic acid (THCA) and cannabidiolic acid (CBDA) are important metabolites to differentiate the cultivars from each other. The discrimination of the cultivars could also be obtained from a water extract containing carbohydrates and amino acids. The level of sucrose, glucose, asparagine, and glutamic acid are found to be major discriminating metabolites of these cultivars. This method allows an efficient differentiation between cannabis cultivars without any prepurification steps. PMID:15217272

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

    PubMed Central

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

    2016-01-01

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

  3. MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles

    PubMed Central

    2011-01-01

    Background Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments. Description MeRy-B, the first platform for plant 1H-NMR metabolomic profiles, is designed (i) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (ii) for queries and visualization of the data, (iii) to discriminate between profiles with spectrum visualization tools and statistical analysis, (iv) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues. Conclusion MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from http://www.cbib.u-bordeaux2.fr/MERYB/index.php. PMID:21668943

  4. Selective paired ion contrast analysis: a novel algorithm for analyzing postprocessed LC-MS metabolomics data possessing high experimental noise.

    PubMed

    Mak, Tytus D; Laiakis, Evagelia C; Goudarzi, Maryam; Fornace, Albert J

    2015-03-17

    One of the consequences in analyzing biological data from noisy sources, such as human subjects, is the sheer variability of experimentally irrelevant factors that cannot be controlled for. This holds true especially in metabolomics, the global study of small molecules in a particular system. While metabolomics can offer deep quantitative insight into the metabolome via easy-to-acquire biofluid samples such as urine and blood, the aforementioned confounding factors can easily overwhelm attempts to extract relevant information. This can mar potentially crucial applications such as biomarker discovery. As such, a new algorithm, called Selective Paired Ion Contrast (SPICA), has been developed with the intent of extracting potentially biologically relevant information from the noisiest of metabolomic data sets. The basic idea of SPICA is built upon redefining the fundamental unit of statistical analysis. Whereas the vast majority of algorithms analyze metabolomics data on a single-ion basis, SPICA relies on analyzing ion-pairs. A standard metabolomic data set is reinterpreted by exhaustively considering all possible ion-pair combinations. Statistical comparisons between sample groups are made only by analyzing the differences in these pairs, which may be crucial in situations where no single metabolite can be used for normalization. With SPICA, human urine data sets from patients undergoing total body irradiation (TBI) and from a colorectal cancer (CRC) relapse study were analyzed in a statistically rigorous manner not possible with conventional methods. In the TBI study, 3530 statistically significant ion-pairs were identified, from which numerous putative radiation specific metabolite-pair biomarkers that mapped to potentially perturbed metabolic pathways were elucidated. In the CRC study, SPICA identified 6461 statistically significant ion-pairs, several of which putatively mapped to folic acid biosynthesis, a key pathway in colorectal cancer. Utilizing support

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-03-01

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

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

    PubMed

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

    2013-11-01

    Although synthetic biology progress has made it possible to produce various biofuels in more user-friendly hosts, such as Escherichia coli, the large-scale biofuel production in these non-native systems is still challenging, mostly due to the very low tolerance of these non-native hosts to the biofuel toxicity. To address the issues, in this study we determined the metabolic responses of E. coli induced by three major biofuel products, ethanol, butanol, and isobutanol, using a gas chromatography-mass spectrometry (GC-MS) approach. A metabolomic data set of 65 metabolites identified in all samples was then subjected to principal component analysis (PCA) to compare their effects and a weighted correlation network analysis (WGCNA) to identify the metabolic modules specifically responsive to each of the biofuel stresses, respectively. The PCA analysis showed that cellular responses caused by the biofuel stress were in general similar to aging cells at stationary phase, inconsistent with early studies showing a high degree of dissimilarity between metabolite responses during growth cessation as induced through stationary phases or through various environmental stress applications. The WGCNA analysis allowed identification of 2, 4, and 2 metabolic modules specifically associated with ethanol, butanol, and isobutanol treatments, respectively. The biofuel-associated modules included amino acids and osmoprotectants, such as isoleucine, valine, glycine, glutamate, and trehalose, suggesting amino acid metabolism and osmoregulation are among the key protection mechanisms against biofuel stresses in E. coli. Interestingly, no module was found associated with all three biofuel products, suggesting differential effects of each biofuel on E. coli. The findings enhanced our understanding of E. coli responses to exogenous biofuels and also demonstrated the effectiveness of the metabolomic and network analysis in identifying key targets for biofuel tolerance. PMID:24016299

  8. Targeted deuteration of polyphenolics for their qualitative and quantitative metabolomic analysis in plant-derived extracts.

    PubMed

    Roe, Mikel R; Cohen, Jerry D; Hegeman, Adrian D

    2014-01-01

    Polyphenolics are a chemically diverse class of plant specialized metabolites with strong antioxidant properties, and their consumption has been associated with improved human health. Metabolomic analysis of these compounds in both plant and mammalian samples has relied predominantly on liquid chromatography coupled to electrospray ionization mass spectrometry (LC-ESI-MS). Due to variable matrix effects across samples during ionization, the accuracy of this approach for quantifying compounds is greatly improved by incorporating stable isotope-labeled standards into the sample prior to analysis. However, commercially available, stable isotope-labeled, polyphenolic standards are both limited and costly. Here we present a protocol for generating stable isotope-labeled polyphenolics based on their deuteration by mild acid-catalyzed, electrophilic aromatic substitution. Importantly, this protocol is effective for generating stable isotope-labeled standards of many biologically relevant polyphenolics, both aglycones and the various conjugated forms alike. PMID:24218207

  9. NMR analysis of the human saliva metabolome distinguishes dementia patients from matched controls.

    PubMed

    Figueira, João; Jonsson, Pär; Nordin Adolfsson, Annelie; Adolfsson, Rolf; Nyberg, Lars; Öhman, Anders

    2016-07-19

    Saliva is a biofluid that is sensitive to metabolic changes and is straightforward to collect in a non-invasive manner, but it is seldom used for metabolite analysis when studying neurodegenerative disorders. We present a procedure for both an untargeted and targeted analysis of the saliva metabolome in which nuclear magnetic resonance (NMR) spectroscopy is used in combination with multivariate data analysis. The applicability of this approach is demonstrated on saliva samples selected from the 25 year prospective Betula study, including samples from dementia subjects with either Alzheimer's disease (AD) or vascular dementia at the time of sampling or who developed it by the next sampling/assessment occasion five years later, and age-, gender-, and education-matched control individuals without dementia. Statistically significant multivariate models were obtained that separated patients with dementia from controls and revealed seven discriminatory metabolites. Dementia patients showed significantly increased concentrations of acetic acid (fold change (fc) = 1.25, p = 2 × 10(-5)), histamine (fc = 1.26, p = 0.019), and propionate (fc = 1.35, p = 0.002), while significantly decreased levels were observed for dimethyl sulfone (fc = 0.81, p = 0.005), glycerol (fc = 0.79, p = 0.04), taurine (fc = 0.70, p = 0.007), and succinate (fc = 0.62, p = 0.008). Histamine, succinate, and taurine are known to be important in AD, and acetic acid and glycerol are involved in related pathways. Dimethyl sulfone and propionate originate from the diet and bacterial flora and might reflect poorer periodontal status in the dementia patients. For these seven metabolites, a weak but statistically significant pre-diagnostic value was observed. Taken together, we present a robust and general NMR analysis approach for studying the saliva metabolome that has potential use for screening and early detection of dementia. PMID:27265744

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

    PubMed Central

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

    2015-01-01

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

  11. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods

    PubMed Central

    Boaz, Segal M.; Champagne, Cory D.; Fowler, Melinda A.; Houser, Dorian H.; Crocker, Daniel E.

    2011-01-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to seven weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. PMID:21983145

  12. 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

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

    PubMed Central

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

    2013-01-01

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

  14. High coverage metabolomics analysis reveals phage-specific alterations to Pseudomonas aeruginosa physiology during infection.

    PubMed

    De Smet, Jeroen; Zimmermann, Michael; Kogadeeva, Maria; Ceyssens, Pieter-Jan; Vermaelen, Wesley; Blasdel, Bob; Bin Jang, Ho; Sauer, Uwe; Lavigne, Rob

    2016-08-01

    Phage-mediated metabolic changes in bacteria are hypothesized to markedly alter global nutrient and biogeochemical cycles. Despite their theoretic importance, experimental data on the net metabolic impact of phage infection on the bacterial metabolism remains scarce. In this study, we tracked the dynamics of intracellular metabolites using untargeted high coverage metabolomics in Pseudomonas aeruginosa cells infected with lytic bacteriophages from six distinct phage genera. Analysis of the metabolomics data indicates an active interference in the host metabolism. In general, phages elicit an increase in pyrimidine and nucleotide sugar metabolism. Furthermore, clear phage-specific and infection stage-specific responses are observed, ranging from extreme metabolite depletion (for example, phage YuA) to complete reorganization of the metabolism (for example, phage phiKZ). As expected, pathways targeted by the phage-encoded auxiliary metabolic genes (AMGs) were enriched among the metabolites changing during infection. The effect on pyrimidine metabolism of phages encoding AMGs capable of host genome degradation (for example, YuA and LUZ19) was distinct from those lacking nuclease-encoding genes (for example, phiKZ), which demonstrates the link between the encoded set of AMGs of a phage and its impact on host physiology. However, a large fraction of the profound effect on host metabolism could not be attributed to the phage-encoded AMGs. We suggest a potentially crucial role for small, 'non-enzymatic' peptides in metabolism take-over and hypothesize on potential biotechnical applications for such peptides. The highly phage-specific nature of the metabolic impact emphasizes the potential importance of the 'phage diversity' parameter when studying metabolic interactions in complex communities. PMID:26882266

  15. Metabolome analysis of Saccharomyces cerevisiae and optimization of culture medium for S-adenosyl-L-methionine production.

    PubMed

    Hayakawa, Kenshi; Matsuda, Fumio; Shimizu, Hiroshi

    2016-12-01

    S-Adenosyl-L-methionine (SAM) is a fine chemical used as a nutritional supplement and a prescription drug. It is industrially produced using Saccharomyces cerevisiae owing to its high SAM content. To investigate the optimization of culture medium components for higher SAM production, metabolome analysis was conducted to compare the intracellular metabolite concentrations between Kyokai no. 6 (high SAM-producing) and laboratory yeast S288C (control) under different SAM production conditions. Metabolome analysis and the result of principal component analysis showed that the rate-limiting step for SAM production was ATP supply and the levels of degradation products of adenosine nucleotides were higher in Kyokai 6 strain than in the S288C strain under the L-methionine supplemented condition. Analysis of ATP accumulation showed that the levels of intracellular ATP in the Kyokai 6 strain were also higher compared to those in the S288C strain. Furthermore, as expected from metabolome analysis, the SAM content of Kyokai 6 strain cultivated in the medium without yeast extract increased by 2.5-fold compared to that in the additional condition, by increasing intracellular ATP level with inhibited cell growth. These results suggest that high SAM production is attributed to the enhanced ATP supply with L-methionine condition and high efficiency of intracellular ATP consumption. PMID:27277079

  16. 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.

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

    PubMed Central

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

    2015-01-01

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

  18. LC-MS-based metabolomics

    PubMed Central

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

    2013-01-01

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

  19. Optimization of the quenching method for metabolomics analysis of Lactobacillus bulgaricus.

    PubMed

    Chen, Ming-ming; Li, Ai-li; Sun, Mao-cheng; Feng, Zhen; Meng, Xiang-chen; Wang, Ying

    2014-04-01

    This study proposed a quenching protocol for metabolite analysis of Lactobacillus delbrueckii subsp. bulgaricus. Microbial cells were quenched with 60% methanol/water, 80% methanol/glycerol, or 80% methanol/water. The effect of the quenching process was assessed by the optical density (OD)-based method, flow cytometry, and gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed for metabolite identification. The results indicated that quenching with 80% methanol/water solution led to less damage to the L. bulgaricus cells, characterized by the lower relative fraction of prodium iodide (PI)-labeled cells and the higher OD recovery ratio. Through GC-MS analysis, higher levels of intracellular metabolites (including focal glutamic acid, aspartic acid, alanine, and AMP) and a lower leakage rate were detected in the sample quenched with 80% methanol/water compared with the others. In conclusion, we suggested a higher concentration of cold methanol quenching for L. bulgaricus metabolomics due to its decreasing metabolite leakage. PMID:24711354

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

    PubMed

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

    2016-05-15

    Von Hippel-Lindau (VHL) is an onco-suppressor involved in oxygen and energy-dependent promotion of protein ubiquitination and proteosomal degradation. Loss of function mutations of VHL (VHL-cells) result in organ specific cancers with the best studied example in renal cell carcinomas. VHL has a well-established role in deactivation of hypoxia-inducible factor (HIF-1) and in regulation of PI3K/AKT/mTOR activity. Cell culture metabolomics analysis was utilized to determined effect of VHL and HIF-1α or HIF-2α on metabolism of renal cell carcinomas (RCC). RCC cells were stably transfected with VHL or shRNA designed to silence HIF-1α or HIF-2α genes. Obtained metabolic data was analysed qualitatively, searching for overall effects on metabolism as well as quantitatively, using methods developed in our group in order to determine specific metabolic changes. Analysis of the effect of VHL and HIF silencing on cellular metabolic footprints and fingerprints provided information about the metabolic pathways affected by VHL through HIF function as well as independently of HIF. Through correlation network analysis as well as statistical analysis of significant metabolic changes we have determined effects of VHL and HIF on energy production, amino acid metabolism, choline metabolism as well as cell regulation and signaling. VHL was shown to influence cellular metabolism through its effect on HIF proteins as well as by affecting activity of other factors. PMID:26620126

  1. Novel Strategy for Non-Targeted Isotope-Assisted Metabolomics by Means of Metabolic Turnover and Multivariate Analysis

    PubMed Central

    Nakayama, Yasumune; Tamada, Yoshihiro; Tsugawa, Hiroshi; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-01-01

    Isotope-labeling is a useful technique for understanding cellular metabolism. Recent advances in metabolomics have extended the capability of isotope-assisted studies to reveal global metabolism. For instance, isotope-assisted metabolomics technology has enabled the mapping of a global metabolic network, estimation of flux at branch points of metabolic pathways, and assignment of elemental formulas to unknown metabolites. Furthermore, some data processing tools have been developed to apply these techniques to a non-targeted approach, which plays an important role in revealing unknown or unexpected metabolism. However, data collection and integration strategies for non-targeted isotope-assisted metabolomics have not been established. Therefore, a systematic approach is proposed to elucidate metabolic dynamics without targeting pathways by means of time-resolved isotope tracking, i.e., “metabolic turnover analysis”, as well as multivariate analysis. We applied this approach to study the metabolic dynamics in amino acid perturbation of Saccharomyces cerevisiae. In metabolic turnover analysis, 69 peaks including 35 unidentified peaks were investigated. Multivariate analysis of metabolic turnover successfully detected a pathway known to be inhibited by amino acid perturbation. In addition, our strategy enabled identification of unknown peaks putatively related to the perturbation. PMID:25257997

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

    PubMed Central

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

    2015-01-01

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

  3. Metabolomics in Newborns.

    PubMed

    Noto, Antonio; Fanos, Vassilios; Dessì, Angelica

    2016-01-01

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

  4. Metabolomic and proteomic analysis of serum from preterm infants with necrotising entercolitis and late-onset sepsis

    PubMed Central

    Stewart, Christopher J; Nelson, Andrew; Treumann, Achim; Skeath, Tom; Cummings, Stephen P; Embleton, Nicholas D; Berrington, Janet E

    2016-01-01

    Background: Necrotising enterocolitis (NEC) and late-onset sepsis (LOS) are the leading causes of death among preterm infants in the developed world. This study aimed to explore the serum proteome and metabolome longitudinally in preterm infants with NEC or LOS, matched to controls. Methods: Nineteen patients (10 cases, 9 controls) were included. A sample 14 d prior to and following, as well as at disease diagnosis, was included for cases. Controls had serum matched at diagnosis for corresponding case. All samples (n = 39) underwent shotgun proteomic analysis, and 37 samples also underwent metabolomics analysis using ultra performance liquid chromatography–tandem mass spectrometry. Results: The proteomic and metabolomic profiles of serum were comparable between all infants. Eight proteins were associated with NEC and four proteins were associated with LOS. C-reactive protein was increased in all NEC patients at diagnosis. Conclusion: No single protein or metabolite was detected in all NEC or LOS cases which was absent from controls; however, several proteins were identified which were associated with disease status. The differing expression of these proteins between diseased infants potentially relates to differing pathophysiology of disease. Thus, it is unlikely a single biomarker exists for NEC and/or LOS. PMID:26571220

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

    PubMed Central

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

    2016-01-01

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

  6. Metabolomic analysis of clinical plasma from cerebral infarction patients presenting with blood stasis.

    PubMed

    Cha, Min Ho; Kim, Min Jung; Jung, Jeeyoun; Kim, Jin Hee; Lee, Myeong Soo; Kim, Myung-Sunny

    2015-01-01

    Blood stasis (BS) is characterized as a disorder of blood circulation. In traditional Korean medicine (TKM), it is viewed as a cause factor of diseases such as multiple sclerosis and stroke. This study investigated differences in the plasma metabolites profiles of subjects displaying BS or non-BS patterns. Thirty-one patients with cerebral infarction diagnosed with BS and an equal number of sex- and age-matched non-BS patients were enrolled. Metabolic profiling was performed using UPLC-MS. The ratio of subjects with a rough pulse and purple coloration of the tongue was higher in patients presenting with BS pattern. Through metabolomics analysis, 82 metabolites that differed significantly between the BS and non-BS pattern were identified, and the two groups were significantly separated using an orthogonal partial least square-discriminant analysis model (P < 0.001). Of these 82 metabolites, acetyl carnitine, leucine, kynurenine, phosphocholine, hexanoyl carnitine, and decanoyl carnitine were present in significantly higher levels in patients with a BS pattern than those with a non-BS pattern. Our results also demonstrated that seven plasma metabolites, including acyl-carnitines and kynurenine, were associated with a BS pattern, suggesting that variant plasma metabolic profiles may serve as a biomarker for diagnosis of BS in patients with cerebral infarction. PMID:25834622

  7. Metabolomic analysis revealed glycylglycine accumulation in astrocytes after methionine enkephalin administration exhibiting neuron protective effects.

    PubMed

    Zhao, Chungang; Du, Huijie; Xu, Li; Wang, Jiao; Tang, Ling; Cao, Yunfeng; Li, Chen; Wang, Qingjun; Liu, Yang; Shan, Fengping; Feng, Juan; Xu, Fang; Gao, Peng

    2015-11-10

    Owing to its unrevealed etiology, multiple sclerosis lacks specific therapies up to now. Experiential administration of methionine enkephalin (MENK) on mouse model improved disease manifestations to some extent. In order to gain more insight on the significance of MENK application, a capillary electrophoresis-mass spectrometry (CE-MS) technique was employed to profile intracellular metabolite fluctuation in 5 astrocytoma cell lines challenged by MENK. The processed data were first evaluated through a bioinformatic process to ensure their compatibility with the study aims and then subjected to multivariate analysis. The results indicated that MENK administration increased intracellular tyrosine, phenylalanine, methionine and glycylglycine. Exemplified by U87 cells, glycylglycine inhibited cell proliferation as well as MENK but it also decreased cell nitric oxide excretion which could not be evoked by MENK. The neuron protective effects were also mirrored by the increased expression of some genes related to remyelination. This study demonstrated CE-MS to be a promising tool for cell metabolomic analysis and benefited the therapeutic exploring of multiple sclerosis with respect to metabolism intervention. PMID:26163404

  8. Comparative metabolomics analysis of docosahexaenoic acid fermentation processes by Schizochytrium sp. under different oxygen availability conditions.

    PubMed

    Li, Juan; Ren, Lu-Jing; Sun, Guan-Nan; Qu, Liang; Huang, He

    2013-05-01

    The intracellular metabolic profile characterization of Schizochytrium sp. throughout docosahexaenoic acid fermentation was investigated using gas chromatography-mass spectrometry (GC-MS). Metabolite profiles originating from Schizochytrium sp. under normal and limited oxygen supply conditions were distinctive and distinguished by principal components analysis (PCA). A total of more than 60 intracellular metabolites were detected and quantified with the levels of some metabolites involved in central carbon metabolism varying throughout both processes. Both fermentation processes were differentiated into three main phases by principal components analysis. Potential biomarkers responsible for distinguishing the different fermentation phases were identified as glutamic acid, proline, glycine, alanine, and glucose. In addition, alanine, glutamic acid, glucose, inositol, ornithine, and galactose were found to make great contribution for dry cell weight and fatty acid composition during normal and limited oxygen supply fermentations. Furthermore, significantly higher levels of succinate and several amino acids in cells of limited oxygen supply fermentation revealed that they might play important roles in resisting oxygen deficiency and increasing DHA synthesis during the lipid accumulation. These findings provide novel insights into the metabolomic characteristics during docosahexaenoic acid fermentation processes by Schizochytrium sp. PMID:23586678

  9. Metabolomic analysis of the green microalga Chlamydomonas reinhardtii cultivated under day/night conditions.

    PubMed

    Willamme, Rémi; Alsafra, Zouheir; Arumugam, Rameshkumar; Eppe, Gauthier; Remacle, Françoise; Levine, R D; Remacle, Claire

    2015-12-10

    Biomass composition of Chlamydomonas reinhardtii was studied during two consecutive cycles of 12h light/12h dark. As in our experimental conditions the two synchronized divisions were separated by 20h, it was possible to show that accumulation of dry weight, proteins, chlorophyll and fatty acids mainly depends on cell division, whereas starch accumulation depends on a circadian rhythm as reported previously. Our metabolomics analyses also revealed that accumulation of five (Ser, Val, Leu, Ile and Thr) of the nine free amino acids detected displayed rhythmicity, depending on cell division while Glu was 20-50 times more abundant than the other ones probably because this free amino acid serves not only for protein synthesis but also for biosynthesis of nitrogen compounds. In addition, we performed a thermodynamic-motivated theoretical approach known as 'surprisal analysis'. The results from this analysis showed that cells were close to a steady state all along the 48h of the experiment. In addition, calculation of free energy of cellular metabolites showed that the transition point, i.e. the state which immediately precedes cell division, corresponds to the most unstable stage of the cell cycle and that division is identified as the greatest drop in the free energy of metabolites. PMID:25941156

  10. A GC-MS urinary quantitative metabolomics analysis in depressed patients treated with TCM formula of Xiaoyaosan.

    PubMed

    Tian, Jun-Sheng; Peng, Guo-Jiang; Wu, Yan-Fei; Zhou, Jian-Jun; Xiang, Huan; Gao, Xiao-Xia; Zhou, Yu-Zhi; Qin, Xue-Mei; Du, Guan-Hua

    2016-07-15

    Xiaoyaosan, one of the best-known traditional Chinese medicine prescriptions, has been widely used in China for the treatment of mental disorders such as depression. Although both clinical application and animal experiments indicate that Xiaoyaosan has an obvious antidepressant effect, the mechanism still remains unclarified, and there are few studies quantitatively measured the biomarkers of Xiaoyaosan treatment by metabolomics to determination. In this study, 25 depressed patients and 33 healthy volunteers were recruited. A GC-MS based metabolomics approach and the multivariate statistical methods were used for analyzing the urine metabolites of depressed patients before and after treatment compared with healthy controls. Then the biomakers through metabolomics determination were carried out the quantitative analysis. In total, 5 metabolites were identified as the potential diseased and therapeutic biomarkers of depression and Xiaoyaosan. Alanine, citrate and hippurate levels were significantly increased in the urine samples from depressed patients compared with healthy controls, while phenylalanie and tyrosine levels were significantly decreased. However, after Xiaoyaosan treatment for 6 weeks, phenylalanie and tyrosine levels were significantly increased (p<0.05) and alanine, citrate and hippurate levels significantly decreased (p<0.05). Xiaoyaosan has a good priority on the treatment of depression and the ability to adjust the neurotransmitters to obtain the best treated response and also could regulate the metabolism of amino acids and promote to produce energy meet the needs of the body. PMID:26733091

  11. New frontiers in pharmaceutical analysis: A metabolomic approach to check batch compliance of complex products based on natural substances.

    PubMed

    Mattoli, L; Burico, M; Fodaroni, G; Tamimi, S; Bedont, S; Traldi, P; Stocchero, M

    2016-07-15

    Natural substances, particularly medicinal plants and their extracts, are still today intended as source for new Active Pharmaceutical Ingredients (APIs). Alternatively they can be validly employed to prepare medicines, food supplements or medical devices. The most adopted analytical approach used to verify quality of natural substances like medicinal plants is based still today on the traditional quantitative determination of marker compounds and/or active ingredients, besides the acquisition of a fingerprint by TLC, NIR, HPLC, GC. Here a new analytical approach based on untargeted metabolomic fingerprinting by means of Mass Spectrometry (MS) to verify the quality of grinTuss adulti syrup, a complex products based on medicinal plants, is proposed. Recently, untargeted metabolomic has been successfully applied to assess quality of natural substances, plant extracts, as well as corresponding formulated products, being the complexity a resource but not necessarily a limit. The untargeted metabolomic fingerprinting includes the monitoring of the main constituents, giving weighted relevance to the most abundant ones, but also considering minor components, that might be notable in view of an integrated - often synergistic - effect on the biological system. Two different years of production were investigated. The collected samples were analyzed by Flow Injection ElectroSpray Ionization Mass Spectrometry Analysis (FIA-ESI-MS) and a suitable data processing procedure was developed to transform the MS spectra into robust fingerprints. Multivariate Statistical Process Control (MSPC) was applied in order to obtain multivariate control charts that were validated to prove the effectiveness of the proposed method. PMID:27155737

  12. [Anti-depressive mechanism of Fufang Chaigui prescription based on neuroendocrine hormone and metabolomic correlation analysis].

    PubMed

    Chen, Lei; Liu, Huan; Chen, Jian-li; Gao, Xiao-xia; Zhou, Yu-zhi; Tian, Jun-sheng; Qin, Xue-mei

    2015-10-01

    To elucidate the anti-depressive effect of Fufang Chaigui prescription and its mechanism and investigate its effect on neuroendocrine hormone, rats were included into a chronic unpredictable mild stress (CUMS) model for 28 d, and drugs were administered at the same time. During the period, rats' behaviors were observed and the blood was collected by using ELISA to determine representative hormone concentrations of HPAA, HPTA and HPGA. The changes in endogenous metabolites were analyzed by using H NMR metabolomics to seek the potential biomarkers. Results showed Fufang Chaigui prescription could improve the behaviors of CUMS rats obviously, increase contents of ACTH, CORT, T₃and decrease contents of TSH and TESTO and regulate the levels of lactate, α-glucose, choline, N-acetylglycoprotein, trimethylamine oxide and leucine to get closer to the contents of control group. The results of correlation analysis indicated that HPTA was associated with glycometabolism, amino acid metabolism and choline metabolism. And HPAA was related to glycometabolism and amino acid metabolism. However, HPGA was only correlated with glycometabolism. In conclusion, Fufang Chaigui prescription could show an obvious anti-depressive effect and its underlying mechanism might involve regulations of neuroendocrine function and pathways of glycometabolism, amino acid metabolism and choline metabolism. PMID:27062831

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2012-02-28

    Phenotypic plasticity occurs prevalently and plays a vital role in adaptive evolution. However, the underlying molecular mechanisms responsible for the expression of alternate phenotypes remain unknown. Here, a density-dependent phase polyphenism of Locusta migratoria was used as the study model to identify key signaling molecules regulating the expression of phenotypic plasticity. Metabolomic analysis, using high-performance liquid chromatography and gas chromatography-mass spectrometry, showed that solitarious and gregarious locusts have distinct metabolic profiles in hemolymph. A total of 319 metabolites, many of which are involved in lipid metabolism, differed significantly in concentration between the phases. In addition, the time course of changes in the metabolic profiles of locust hemolymph that accompany phase transition was analyzed. Carnitine and its acyl derivatives, which are involved in the lipid β-oxidation process, were identified as key differential metabolites that display robust correlation with the time courses of phase transition. RNAi silencing of two key enzymes from the carnitine system, carnitine acetyltransferase and palmitoyltransferase, resulted in a behavioral transition from the gregarious to solitarious phase and the corresponding changes of metabolic profiles. In contrast, the injection of exogenous acetylcarnitine promoted the acquisition of gregarious behavior in solitarious locusts. These results suggest that carnitines mediate locust phase transition possibly through modulating lipid metabolism and influencing the nervous system of the locusts. PMID:22328148

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

    PubMed Central

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

    2012-01-01

    Phenotypic plasticity occurs prevalently and plays a vital role in adaptive evolution. However, the underlying molecular mechanisms responsible for the expression of alternate phenotypes remain unknown. Here, a density-dependent phase polyphenism of Locusta migratoria was used as the study model to identify key signaling molecules regulating the expression of phenotypic plasticity. Metabolomic analysis, using high-performance liquid chromatography and gas chromatography–mass spectrometry, showed that solitarious and gregarious locusts have distinct metabolic profiles in hemolymph. A total of 319 metabolites, many of which are involved in lipid metabolism, differed significantly in concentration between the phases. In addition, the time course of changes in the metabolic profiles of locust hemolymph that accompany phase transition was analyzed. Carnitine and its acyl derivatives, which are involved in the lipid β-oxidation process, were identified as key differential metabolites that display robust correlation with the time courses of phase transition. RNAi silencing of two key enzymes from the carnitine system, carnitine acetyltransferase and palmitoyltransferase, resulted in a behavioral transition from the gregarious to solitarious phase and the corresponding changes of metabolic profiles. In contrast, the injection of exogenous acetylcarnitine promoted the acquisition of gregarious behavior in solitarious locusts. These results suggest that carnitines mediate locust phase transition possibly through modulating lipid metabolism and influencing the nervous system of the locusts. PMID:22328148

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

    PubMed

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

    2014-01-01

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

  17. Comparative mass spectrometry & nuclear magnetic resonance metabolomic approaches for nutraceuticals quality control analysis: a brief review.

    PubMed

    Farag, Mohamed A

    2014-01-01

    The number of botanical dietary supplements in the market has recently increased primarily due to increased health awareness. Standardization and quality control of the constituents of these plant extracts is an important topic, particularly when such ingredients are used long term as dietary supplements, or in cases where higher doses are marketed as drugs. The development of fast, comprehensive, and effective untargeted analytical methods for plant extracts is of high interest. Nuclear magnetic resonance spectroscopy and mass spectrometry are the most informative tools, each of which enables high-throughput and global analysis of hundreds of metabolites in a single step. Although only one of the two techniques is utilized in the majority of plant metabolomics applications, there is a growing interest in combining the data from both platforms to effectively unravel the complexity of plant samples. The application of combined MS and NMR in the quality control of nutraceuticals forms the major part of this review. Finally I will look at the future developments and perspectives of these two technologies for the quality control of herbal materials. PMID:24354527

  18. Metabolomics driven analysis of Erythrina lysistemon cell suspension culture in response to methyl jasmonate elicitation.

    PubMed

    Farag, Mohamed A; Mekky, Hattem; El-Masry, Sawsan

    2016-09-01

    An MS-based metabolomic approach was used to profile the secondary metabolite of the ornamental plant Erythrina lysistemon via ultra-performance liquid chromatography coupled to photodiode array detection and high resolution q-TOF mass spectrometry (UPLC-PDA-MS). Cultures maintained the capacity to produce E. lysistemon flavonoid subclasses with pterocarpans amounting for the most abundant ones suggesting that it could provide a resource of such flavonoid subclass. In contrast, alkaloids, major constituents of Erythrina genus, were detected at trace levels in suspension cultures. Methyl jasmonate (MeJA), phytohormone, was further supplied to culture with the aim of increasing secondary metabolites production and with metabolite profiles subjected to multivariate data analysis to evaluate its effect. Results revealed that triterpene i.e. oleanolic acid and fatty acid i.e. hydroxy-octadecadienoic acid were elicited in response to methyl jasmonate, whereas pterocarpans i.e., isoneorautenol showed a decline in response to elicitation suggesting for the induction of terpenoid biosynthetic pathway and concurrent with a down regulation of pterocarpans. In conclusion, a total of 53 secondary metabolites including 3 flavones, 12 isoflavones, 4 isoflavanones, 4 alkaloids, 11 pterocarpans, and 5 phenolic acids were identified. PMID:27504198

  19. Computational approaches for systems metabolomics.

    PubMed

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

    2016-06-01

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

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

    PubMed Central

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

    2009-01-01

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

  1. Metabolomic analysis of amino acid and energy metabolism in rats supplemented with chlorogenic acid

    PubMed Central

    Ruan, Zheng; Yang, Yuhui; Zhou, Yan; Wen, Yanmei; Ding, Sheng; Liu, Gang; Wu, Xin; Deng, Zeyuan; Assaad, Houssein; Wu, Guoyao

    2016-01-01

    This study was conducted to investigate effects of chlorogenic acid (CGA) supplementation on serum and hepatic metabolomes in rats. Rats received daily intragastric administration of either CGA (60 mg/kg body weight) or distilled water (control) for 4 weeks. Growth performance, serum biochemical profiles, and hepatic morphology were measured. Additionally, serum and liver tissue extracts were analyzed for metabolomes by high-resolution 1H nuclear magnetic resonance-based metabolomics and multivariate statistics. CGA did not affect rat growth performance, serum biochemical profiles, or hepatic morphology. However, supplementation with CGA decreased serum concentrations of lactate, pyruvate, succinate, citrate, β-hydroxybutyrate and acetoacetate, while increasing serum concentrations of glycine and hepatic concentrations of glutathione. These results suggest that CGA supplementation results in perturbation of energy and amino acid metabolism in rats. We suggest that glycine and glutathione in serum may be useful biomarkers for biological properties of CGA on nitrogen metabolism in vivo. PMID:24927697

  2. Metabolomic Analysis of Gingival Crevicular Fluid Using Gas Chromatography/Mass Spectrometry.

    PubMed

    Ozeki, Miho; Nozaki, Takenori; Aoki, Jun; Bamba, Takeshi; Jensen, Kirk R; Murakami, Shinya; Toyoda, Michisato

    2016-01-01

    Periodontitis is one of the most prevalent threats to oral health as the most common cause of tooth loss. In order to perform effective treatment, a clinical test that detect sites where disease activity is high and predicts periodontal tissue destruction is strongly desired, however, it is still difficult to prognose the periodontal tissue breakdown on the basis of conventional methods. The aim of this study is to examine the usefulness of gas chromatography/mass spectrometry (GC/MS), which could eventually be used for on-site analysis of metabolites in gingival crevicular fluid (GCF) in order to objectively diagnose periodontitis at a molecular level. GCF samples were collected from two diseased sites (one site with a moderate pocket and another site with a deep pocket) from each patient and from clinically healthy sites of volunteers. Nineteen metabolites were identified using GC/MS. Total ion current chromatograms showed broad differences in metabolite peak patterns between GCF samples obtained from healthy sites, moderate-pocket sites, and deep-pocket sites. The intensity difference of some metabolites was significant at sites with deep pockets compared to healthy sites. Additionally, metabolite intensities at moderate-pocket sites showed an intermediate profile between the severely diseased sites and healthy sites, which suggested that periodontitis progression could be observed with a changing metabolite profile. Principal component analysis confirmed these observations by clearly delineating healthy sites and sites with deep pockets. These results suggest that metabolomic analysis of GCF could be useful for prediction and diagnosis of periodontal disease in a single visit from a patient and provides the groundwork for establishing a new, on-site diagnostic method for periodontitis. PMID:27446770

  3. Metabolomic Analysis of Gingival Crevicular Fluid Using Gas Chromatography/Mass Spectrometry

    PubMed Central

    Ozeki, Miho; Nozaki, Takenori; Aoki, Jun; Bamba, Takeshi; Jensen, Kirk R.; Murakami, Shinya; Toyoda, Michisato

    2016-01-01

    Periodontitis is one of the most prevalent threats to oral health as the most common cause of tooth loss. In order to perform effective treatment, a clinical test that detect sites where disease activity is high and predicts periodontal tissue destruction is strongly desired, however, it is still difficult to prognose the periodontal tissue breakdown on the basis of conventional methods. The aim of this study is to examine the usefulness of gas chromatography/mass spectrometry (GC/MS), which could eventually be used for on-site analysis of metabolites in gingival crevicular fluid (GCF) in order to objectively diagnose periodontitis at a molecular level. GCF samples were collected from two diseased sites (one site with a moderate pocket and another site with a deep pocket) from each patient and from clinically healthy sites of volunteers. Nineteen metabolites were identified using GC/MS. Total ion current chromatograms showed broad differences in metabolite peak patterns between GCF samples obtained from healthy sites, moderate-pocket sites, and deep-pocket sites. The intensity difference of some metabolites was significant at sites with deep pockets compared to healthy sites. Additionally, metabolite intensities at moderate-pocket sites showed an intermediate profile between the severely diseased sites and healthy sites, which suggested that periodontitis progression could be observed with a changing metabolite profile. Principal component analysis confirmed these observations by clearly delineating healthy sites and sites with deep pockets. These results suggest that metabolomic analysis of GCF could be useful for prediction and diagnosis of periodontal disease in a single visit from a patient and provides the groundwork for establishing a new, on-site diagnostic method for periodontitis. PMID:27446770

  4. Metabolomic analysis of cerebral spinal fluid from patients with severe brain injury.

    PubMed

    Glenn, Thomas C; Hirt, Daniel; Mendez, Gustavo; McArthur, David L; Sturtevant, Rachael; Wolahan, Stephanie; Fazlollahi, Farbod; Ordon, Matthew; Bilgin-Freiert, Arzu; Ellingson, Ben; Vespa, Paul; Hovda, David A; Martin, Neil A

    2013-01-01

    Proton nuclear magnetic resonance (H-NMR) spectroscopic analysis of cerebral spinal fluid provides a quick, non-invasive modality for evaluating the metabolic activity of brain-injured patients. In a prospective study, we compared the CSF of 44 TBI patients and 13 non-injured control subjects. CSF was screened for ten parameters: β-glucose (Glu), lactate (Lac), propylene glycol (PG), glutamine (Gln), alanine (Ala), α-glucose (A-Glu), pyruvate (PYR), creatine (Cr), creatinine (Crt), and acetate (Ace). Using mixed effects measures, we discovered statistically significant differences between control and trauma concentrations (mM). TBI patients had significantly higher concentrations of PG, while statistical trends existed for lactate, glutamine, and creatine. TBI patients had a significantly decreased concentration of total creatinine. There were no significant differences between TBI patients and non-injured controls regarding β- or α-glucose, alanine, pyruvate or acetate. Correlational analysis between metabolites revealed that the strongest significant correlations in non-injured subjects were between β- and α-glucose (r = 0.74), creatinine and pyruvate (r = 0.74), alanine and creatine (r = 0.62), and glutamine and α-glucose (r = 0.60). For TBI patients, the strongest significant correlations were between lactate and α-glucose (r = 0.54), lactate and alanine (r = 0.53), and α-glucose and alanine (r = 0.48). The GLM and multimodel inference indicated that the combined metabolites of PG, glutamine, α-glucose, and creatinine were the strongest predictors for CMRO2, ICP, and GOSe. By analyzing the CSF of patients with TBI, our goal was to create a metabolomic fingerprint for brain injury. PMID:23564115

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

    PubMed Central

    2012-01-01

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

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

    PubMed

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

    2014-09-01

    Water supply biofilms have the potential to harbour waterborne diseases, accelerate corrosion, and contribute to the formation of tuberculation in metallic pipes. One particular species of bacteria known to be found in the water supply networks is Pseudomonas sp., with the presence of Pseudomonas putida being isolated to iron pipe tubercles. Current methods for detecting and analysis pipe biofilms are time consuming and expensive. The application of metabolomics techniques could provide an alternative method for assessing biofilm risk more efficiently based on bacterial activity. As such, this paper investigates the application of metabolomic techniques and provides a proof-of-concept application using liquid chromatography coupled with time-of-flight mass spectrometry (LC-ToF-MS) to three biologically independent P. putida samples, across five different growth conditions exposed to solid and soluble iron (Fe). Analysis of the samples in +ESI and -ESI mode yielded 887 and 1789 metabolite features, respectively. Chemometric analysis of the +ESI and -ESI data identified 34 and 39 significant metabolite features, respectively, where features were considered significant if the fold change was greater than 2 and obtained a p-value less than 0.05. Metabolite features were subsequently identified according to the Metabolomics Standard Initiative (MSI) Chemical Analysis Workgroup using analytical standards and standard online LC-MS databases. Possible markers for P. putida growth, with and without being exposed to solid and soluble Fe, were identified from a diverse range of different chemical classes of metabolites including nucleobases, nucleosides, dipeptides, tripeptides, amino acids, fatty acids, sugars, and phospholipids. PMID:24674937

  7. Quantitative Metabolome Analysis Based on Chromatographic Peak Reconstruction in Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.

    PubMed

    Huan, Tao; Li, Liang

    2015-07-21

    Generating precise and accurate quantitative information on metabolomic changes in comparative samples is important for metabolomics research where technical variations in the metabolomic data should be minimized in order to reveal biological changes. We report a method and software program, IsoMS-Quant, for extracting quantitative information from a metabolomic data set generated by chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). Unlike previous work of relying on mass spectral peak ratio of the highest intensity peak pair to measure relative quantity difference of a differentially labeled metabolite, this new program reconstructs the chromatographic peaks of the light- and heavy-labeled metabolite pair and then calculates the ratio of their peak areas to represent the relative concentration difference in two comparative samples. Using chromatographic peaks to perform relative quantification is shown to be more precise and accurate. IsoMS-Quant is integrated with IsoMS for picking peak pairs and Zero-fill for retrieving missing peak pairs in the initial peak pairs table generated by IsoMS to form a complete tool for processing CIL LC-MS data. This program can be freely downloaded from the www.MyCompoundID.org web site for noncommercial use. PMID:26086729

  8. An initial non-targeted analysis of the peanut seed metabolome

    Technology Transfer Automated Retrieval System (TEKTRAN)

    There are likely a large number of compounds that constitute the peanut seed metabolome that have yet to be elucidated. Although the proximate composition and nutrients such as vitamins and minerals are well known, the composition of many other small molecule metabolites present have not been syste...

  9. Metabolomic analysis of the effects of polychlorinated biphenyls in nonalcoholic fatty liver disease.

    PubMed

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

    2012-07-01

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

  10. Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls.

    PubMed

    Deng, Lingli; Gu, Haiwei; Zhu, Jiangjiang; Nagana Gowda, G A; Djukovic, Danijel; Chiorean, E Gabriela; Raftery, Daniel

    2016-08-16

    Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical

  11. Metabolomics analysis reveals 6‐benzylaminopurine as a stimulator for improving lipid and DHA accumulation of Aurantiochytriumsp.

    PubMed Central

    Yu, Xin‐Jun; Sun, Jie; Zheng, Jian‐Yong; Sun, Ya‐Qi

    2016-01-01

    Abstract BACKGROUND Phytohormones are chemical messengers that have a positive effect on biodiesel production of microalgae at low concentrations. However, the effect of phytohormone 6‐benzylaminopurine on lipid and docosahexaenoic acid (DHA) production in marine DHA‐producer Aurantiochytrium has never been reported. In this study, a GC‐MS‐based metabolomics method combined with a multivariate analysis is applied to reveal the metabolic mechanism of 6‐benzylaminopurine enhancing production of lipid and DHA in Aurantiochytrium sp.YLH70. RESULTS In total, 71 metabolites were identified by GC‐MS. The PCA model revealed that 76.9% of metabolite variation was related to 6‐benzylaminopurine treatment, and overall metabolomics profiles between the 6‐benzylaminopurine and control groups were clearly discriminated. Forty‐six metabolites identified by the PLS‐DA model were responsible for responding to 6‐benzylaminopurine. Metabolic analysis showed that 6‐benzylaminopurine could accelerate the rate of utilization of glucose in Aurantiochytrium sp. YLH70, and the metabolic flux from glycolysis, TCA cycle and mevalonate pathway to fatty acids biosynthesis was promoted. Moreover, the anti‐stress mechanism in Aurantiochytrium sp.YLH70 might be induced by 6‐benzylaminopurine. CONCLUSION Metabolomics is a suitable tool to discover the metabolic mechanism for improving lipid and DHA accumulation in a microorganism. 6‐benzylaminopurine has the potential to stimulate lipid and DHA production of Aurantiochytrium sp.YLH70 for industrial purposes. © 2015 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:27065509

  12. Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis

    PubMed Central

    Cruickshank-Quinn, Charmion; Quinn, Kevin D.; Powell, Roger; Yang, Yanhui; Armstrong, Michael; Mahaffey, Spencer; Reisdorph, Richard; Reisdorph, Nichole

    2014-01-01

    Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl.  Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists. PMID:25045913

  13. Detection of batch effects in liquid chromatography-mass spectrometry metabolomic data using guided principal component analysis.

    PubMed

    Kuligowski, J; Pérez-Guaita, D; Lliso, I; Escobar, J; León, Z; Gombau, L; Solberg, R; Saugstad, O D; Vento, M; Quintás, G

    2014-12-01

    Metabolomics based on liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for studying dynamic responses of biological systems to different physiological or pathological conditions. Differences in the instrumental response within and between batches introduce unwanted and uncontrolled data variation that should be removed to extract useful information. This work exploits a recently developed method for the identification of batch effects in high throughput genomic data based on the calculation of a δ statistic through principal component analysis (PCA) and guided PCA. Its applicability to LC-MS metabolomic data was tested on two real examples. The first example involved the repeated analysis of 42 plasma samples and 6 blanks in three independent batches, and the second data set involved the analysis of 101 plasma and 18 blank samples in a single batch with a total runtime of 50h. The first and second data set were used to evaluate between and within-batch effects using the δ statistic, respectively. Results obtained showed the usefulness of using the δ statistic together with other approaches such as summary statistics of peak intensity distributions, PCA scores plots or the monitoring of IS peak intensities, to detect and identify instrumental instabilities in LC-MS. PMID:25159433

  14. Metabolomic and high-throughput sequencing analysis-modern approach for the assessment of biodeterioration of materials from historic buildings.

    PubMed

    Gutarowska, Beata; Celikkol-Aydin, Sukriye; Bonifay, Vincent; Otlewska, Anna; Aydin, Egemen; Oldham, Athenia L; Brauer, Jonathan I; Duncan, Kathleen E; Adamiak, Justyna; Sunner, Jan A; Beech, Iwona B

    2015-01-01

    Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar, and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II-Birkenau concentration and extermination camp in Oświecim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM), metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and nine fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus, and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of microbial communities

  15. Understanding Metabolomics in Biomedical Research

    PubMed Central

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

    2016-01-01

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

  16. Combined metabolome and proteome analysis of the mantle tissue from Pacific oyster Crassostrea gigas exposed to elevated pCO2.

    PubMed

    Wei, Lei; Wang, Qing; Ning, Xuanxuan; Mu, Changkao; Wang, Chunlin; Cao, Ruiwen; Wu, Huifeng; Cong, Ming; Li, Fei; Ji, Chenglong; Zhao, Jianmin

    2015-03-01

    Ocean acidification (OA) has been found to affect an array of normal physiological processes in mollusks, especially posing a significant threat to the fabrication process of mollusk shell. In the current study, the impact of exposure to elevated pCO2 condition was investigated in mantle tissue of Crassostrea gigas by an integrated metabolomic and proteomic approach. Analysis of metabolome and proteome revealed that elevated pCO2 could affect energy metabolism in oyster C. gigas, marked by differentially altered ATP, succinate, MDH, PEPCK and ALDH levels. Moreover, the up-regulated calponin-2, tropomyosins and myosin light chains indicated that elevated pCO2 probably caused disturbances in cytoskeleton structure in mantle tissue of oyster C. gigas. This work demonstrated that a combination of proteomics and metabolomics could provide important insights into the effects of OA at molecular levels. PMID:25559488

  17. Unified and isomer-specific NMR metabolomics database for the accurate analysis of (13)C-(1)H HSQC spectra.

    PubMed

    Bingol, Kerem; Li, Da-Wei; Bruschweiler-Li, Lei; Cabrera, Oscar A; Megraw, Timothy; Zhang, Fengli; Brüschweiler, Rafael

    2015-02-20

    A new metabolomics database and query algorithm for the analysis of (13)C-(1)H HSQC spectra is introduced, which unifies NMR spectroscopic information on 555 metabolites from both the Biological Magnetic Resonance Data Bank (BMRB) and Human Metabolome Database (HMDB). The new database, termed Complex Mixture Analysis by NMR (COLMAR) (13)C-(1)H HSQC database, can be queried via an interactive, easy to use web interface at http://spin.ccic.ohio-state.edu/index.php/hsqc/index . Our new HSQC database separately treats slowly exchanging isomers that belong to the same metabolite, which permits improved query in cases where lowly populated isomers are below the HSQC detection limit. The performance of our new database and query web server compares favorably with the one of existing web servers, especially for spectra of samples of high complexity, including metabolite mixtures from the model organisms Drosophila melanogaster and Escherichia coli. For such samples, our web server has on average a 37% higher accuracy (true positive rate) and a 82% lower false positive rate, which makes it a useful tool for the rapid and accurate identification of metabolites from (13)C-(1)H HSQC spectra at natural abundance. This information can be combined and validated with NMR data from 2D TOCSY-type spectra that provide connectivity information not present in HSQC spectra. PMID:25333826

  18. Unified and Isomer-Specific NMR Metabolomics Database for the Accurate Analysis of 13C–1H HSQC Spectra

    PubMed Central

    2015-01-01

    A new metabolomics database and query algorithm for the analysis of 13C–1H HSQC spectra is introduced, which unifies NMR spectroscopic information on 555 metabolites from both the Biological Magnetic Resonance Data Bank (BMRB) and Human Metabolome Database (HMDB). The new database, termed Complex Mixture Analysis by NMR (COLMAR) 13C–1H HSQC database, can be queried via an interactive, easy to use web interface at http://spin.ccic.ohio-state.edu/index.php/hsqc/index. Our new HSQC database separately treats slowly exchanging isomers that belong to the same metabolite, which permits improved query in cases where lowly populated isomers are below the HSQC detection limit. The performance of our new database and query web server compares favorably with the one of existing web servers, especially for spectra of samples of high complexity, including metabolite mixtures from the model organisms Drosophila melanogaster and Escherichia coli. For such samples, our web server has on average a 37% higher accuracy (true positive rate) and a 82% lower false positive rate, which makes it a useful tool for the rapid and accurate identification of metabolites from 13C–1H HSQC spectra at natural abundance. This information can be combined and validated with NMR data from 2D TOCSY-type spectra that provide connectivity information not present in HSQC spectra. PMID:25333826

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

    PubMed

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

    2015-10-01

    The aim of this experiment was to use metabolomic techniques to investigate the energy metabolism in lamb M. longissimus thoracis et lumborum subjected to very fast chilling (VFC) post-mortem. The tissue was prepared by 2 different operators and subjected to very fast chilling (less than 0°C within 1.5h of slaughter) or typical chilling regimes (Control; 0°C within 22h of slaughter). Non-targeted metabolomic analysis ((1)H NMR) and targeted analysis ((31)P NMR, HPLC-PDA and HPLC-MS/MS) were used to examine the change in muscle metabolites post-mortem. One VFC treatment, which resulted in a colder core temperature and more tender meat, had higher levels of glycolytic intermediate metabolites pre-rigor as well as more of the end-products of adenosine and nicotine nucleotide metabolism pre-rigor, relative to conventionally chilled treatments. In conclusion, VFC to less than 0°C within 1.5h of slaughter causes considerable changes in metabolism and rigor onset, which are associated with tender meat. PMID:26163181

  20. Blood metabolomics analysis identifies abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism in bipolar disorder

    PubMed Central

    Yoshimi, Noriko; Futamura, Takashi; Kakumoto, Keiji; Salehi, Alireza M.; Sellgren, Carl M.; Holmén-Larsson, Jessica; Jakobsson, Joel; Pålsson, Erik; Landén, Mikael; Hashimoto, Kenji

    2016-01-01

    Background Bipolar disorder (BD) is a severe and debilitating psychiatric disorder. However, the precise biological basis remains unknown, hampering the search for novel biomarkers. We performed a metabolomics analysis to discover novel peripheral biomarkers for BD. Methods We quantified serum levels of 116 metabolites in mood-stabilized male BD patients (n = 54) and age-matched male healthy controls (n = 39). Results After multivariate logistic regression, serum levels of pyruvate, N-acetylglutamic acid, α-ketoglutarate, and arginine were significantly higher in BD patients than in healthy controls. Conversely, serum levels of β-alanine, and serine were significantly lower in BD patients than in healthy controls. Chronic (4-weeks) administration of lithium or valproic acid to adult male rats did not alter serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, or arginine, but lithium administration significantly increased serum levels of α-ketoglutarate. Conclusions The metabolomics analysis demonstrated altered serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, and arginine in BD patients. General significance The present findings suggest that abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism play a role in the pathogenesis of BD. PMID:27114925

  1. Capillary electrophoresis-mass spectrometry-based metabolome analysis of serum and saliva from neurodegenerative dementia patients.

    PubMed

    Tsuruoka, Mayuko; Hara, Junko; Hirayama, Akiyoshi; Sugimoto, Masahiro; Soga, Tomoyoshi; Shankle, William R; Tomita, Masaru

    2013-10-01

    Despite increasing global prevalence, the precise pathogenesis and terms for objective diagnosis of neurodegenerative dementias remain controversial, and comprehensive understanding of the disease remains lacking. Here, we conducted metabolomic analysis of serum and saliva obtained from patients with neurodegenerative dementias (n = 10), including Alzheimer's disease, frontotemporal lobe dementia, and Lewy body disease, as well as from age-matched healthy controls (n = 9). Using CE-TOF-MS, six metabolites in serum (β-alanine, creatinine, hydroxyproline, glutamine, iso-citrate, and cytidine) and two in saliva (arginine and tyrosine) were significantly different between dementias and controls. Using multivariate analysis, serum was confirmed as a more efficient biological fluid for diagnosis compared to saliva; additionally, 45 metabolites in total were identified as candidate markers that could discriminate at least one pair of diagnostic groups from the healthy control group. These metabolites possibly provide an objective method for diagnosing dementia-type by multiphase screening. Moreover, diagnostic-type-dependent differences were observed in several tricarboxylic acid cycle compounds detected in serum, indicating that some pathways in glucose metabolism may be altered in dementia patients. This pilot study revealed novel alterations in metabolomic profiles between various neurodegenerative dementias, which would contribute to etiological investigations. PMID:23857558

  2. Metabolome analysis and pathway abundance profiling of Yarrowia lipolytica cultivated on different carbon sources.

    PubMed

    Zhao, Chen; Gu, Deqing; Nambou, Komi; Wei, Liujing; Chen, Jun; Imanaka, Tadayuki; Hua, Qiang

    2015-07-20

    Yarrowia lipolytica, a model microorganism of oleaginous yeasts with developed sophisticated genetic tools, is able to metabolize a wide range of substrates and accumulate large amounts of lipids. However, there is a lack of literature reporting the metabolic characteristics of Y. lipolytica metabolizing these substrates in a systematic view. In this study, Y. lipolytica was cultivated on a variety of carbon sources, among which cell growth and production characteristics on two representative substrates (glucose and oleic acid) were investigated in detail at metabolomic level. Metabolic pathway abundance was computed to interpret the metabolome data in a straightforward way. The results showed that most pathway abundances decreased in the shift from growth to production phase. Specifically, when cultivated on glucose, abundances of twelve pathways decreased markedly between the growth and lipid production phases, while thirteen pathways reduced and only three pathways increased significantly in abundances on oleic acid. In comparison, for the same cultivation phase only a few pathways exhibited significant changes between glucose-grown and oleic acid-grown cells. This study revealed that the pathway abundance could be used to effectively show the activity changes of pathways, providing a new perspective to employ metabolomics data for understanding cell metabolism and enhancing the production of target metabolites. PMID:25912211

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-07-01

    Polycyclic aromatic hydrocarbons (PAHs) and their oxygenated derivatives are ubiquitously present in diesel exhaust, atmospheric particulate matter and soils sampled in urban areas. Therefore, inhalation or non-dietary ingestion of both PAHs and oxy-PAHs are major routes of exposure for people; especially young children living in these localities. While there has been extensive research on the parent PAHs, limited studies exist on the biological effects of oxy-PAHs which have been shown to be more soluble and more mobile in the environment. Additionally, investigations comparing the metabolic responses resulting from parent PAHs and oxy-PAHs exposures have not been reported. To address these current gaps, an untargeted metabolomics approach was conducted to examine the in vivo metabolomic profiles of developing zebrafish (Danio rerio) exposed to 4 µM of benz[a]anthracene (BAA) or benz[a]anthracene-7,12-dione (BAQ). By integrating multivariate, univariate and pathway analyses, a total of 63 metabolites were significantly altered after 5 days of exposure. The marked perturbations revealed that both BAA and BAQ affect protein biosynthesis, mitochondrial function, neural development, vascular development and cardiac function. Our previous transcriptomic and genomic data were incorporated in this metabolomics study to provide a more comprehensive view of the relationship between PAH and oxy-PAH exposures on vertebrate development. PMID:26001975

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

    PubMed Central

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

    2014-01-01

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

  6. Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

    PubMed Central

    2016-01-01

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment. PMID:26745651

  7. Metabolomics analysis reveals that bile acids and phospholipids contribute to variable responses to low-temperature-induced ascites syndrome.

    PubMed

    Shen, Yiru; Shi, Shourong; Tong, Haibing; Guo, Yuming; Zou, Jianmin

    2014-06-01

    Ascites is a major problem for both human health and animal production, due to its association with high rates of morbidity and mortality, low efficiency of nutrient utilization, and permanent adverse effects on performance. Although it is one of the three major metabolic diseases in poultry production, the underlying mechanisms are largely unknown. In this study, six ascites syndrome (AS) chickens and six normal chickens were obtained from each group (108 chickens) at 21 and 35 days. A liver metabolomics method based on ultra-performance liquid chromatography/quadruple time-of-flight mass spectrometry (UPLC/Q-TOF/MS) was used to explore the metabolic pattern of low molecular mass metabolites in chickens with low-temperature-induced AS. Coupled with blood biochemistry and histopathology results, the significant difference in metabolic profiling between the AS group and the control group, as determined through pattern recognition analysis, indicated changes in global tissue metabolites. The results showed that a primary bile acid synthesis disorder and inflammation had occurred by 21 days and that lysophospholipid metabolism was disrupted by 35 days with the continuation of low temperatures. Several metabolites, including taurodeoxycholic acid, cholic acid glucuronide, glycocholic acid, LysoPC(15 : 0) and taurocholic acid, were identified as the potential and proper biomarkers of AS. These biochemical changes in tissue metabolites are related to perturbations of lipid metabolism, which may be helpful to further understand the AS mechanisms. This work shows that the metabolomics is a valuable tool for studying metabolic diseases. PMID:24700147

  8. Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis.

    PubMed

    Emwas, Abdul-Hamid; Roy, Raja; McKay, Ryan T; Ryan, Danielle; Brennan, Lorraine; Tenori, Leonardo; Luchinat, Claudio; Gao, Xin; Zeri, Ana Carolina; Gowda, G A Nagana; Raftery, Daniel; Steinbeck, Christoph; Salek, Reza M; Wishart, David S

    2016-02-01

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment. PMID:26745651

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

    PubMed

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

    2015-01-01

    In order to investigate avocado fruit ripening, nontargeted GC-APCI-TOF MS metabolic profiling analyses were carried out. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to explore the metabolic profiles from fruit samples of 13 varieties at two different ripening degrees. Mannoheptulose; pentadecylfuran; aspartic, malic, stearic, citric and pantothenic acids; mannitol; and β-sitosterol were some of the metabolites found as more influential for the PLS-DA model. The similarities among genetically related samples (putative mutants of "Hass") and their metabolic differences from the rest of the varieties under study have also been evaluated. The achieved results reveal new insights into avocado fruit composition and metabolite changes, demonstrating therefore the value of metabolomics as a functional genomics tool in characterizing the mechanism of fruit ripening development, a key developmental stage in most economically important fruit crops. PMID:25381615

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

    PubMed

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

    2014-11-01

    Ascites syndrome (AS) still has an unacceptably high incidence rate in both humans and animals although there have been many studies on AS. To continue our previous pathological and biochemical investigation on the underlying mechanisms of AS incidence in broiler chickens, cutting-edge technologies including RNA-seq and metabolimics were used by directly comparing AS chickens and healthy controls. The RNA-seq analysis in the liver identified 390 differentially expressed genes (DEGs), among which 212 genes were up-regulated and 178 genes were down-regulated in the AS group compared to the control. For the down-regulated DEGs, further gene ontology (GO) analysis suggested that lipid metabolism, cell differentiation, enzyme linked receptor protein signaling pathway and steroid biosynthesis pathway were significantly enriched. For up-regulated DEGs, the cholesterol metabolic process has the lowest p value (0.000966) of fold enrichment while the cholesterol biosynthetic process has the highest fold enrichment (46.67). The metabolomic analysis of serum revealed statistically significant changes in the concentrations of LysoPC(20 : 4), LysoPC(16 : 0), LysoPC(18 : 0), LysoPC(18 : 1), LysoPC(18 : 2), PC(14 : 1/20 : 1), PC(20 : 4/18 : 0), PC(14 : 1/22 : 1), dihydroxyacetone, indoleacrylic acid, ursodeoxycholic acid, l-valine, and l-tryptophan. The integrative analysis of transcriptome and metabolome indicated that two biological pathways of tryptophan biosynthesis and metabolism, and glycerophospholipid metabolism may contribute to the induction of AS in broilers. These findings have provided novel insights into our understanding of molecular mechanisms of AS incidence in broilers. PMID:25178933

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

    PubMed Central

    Kind, Tobias; Scholz, Martin; Fiehn, Oliver

    2009-01-01

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

  12. Extraction of Hydrophilic Metabolites from Plasmodium falciparum-Infected Erythrocytes for Metabolomic Analysis

    PubMed Central

    Olszewski, Kellen L.; Llinás, Manuel

    2012-01-01

    Metabolomics is an increasingly common analytical approach for investigating metabolic networks of pathogenic organisms. This may be of particular use in the study of parasitic infections due to the intrinsic metabolic connection between the parasite and its host. In vitro cultures of the malaria parasite Plasmodium falciparum present a valuable platform to elucidate the structure and dynamics of the parasite’s metabolic network and to determine the mechanisms of action of antimalarial drugs and drug resistance mutations. Accurately measuring metabolite levels requires a reproducible method for quantifying intracellular metabolites. Here we present a simple protocol for extracting hydrophilic metabolites from P. falciparum-infected erythrocyte cultures. PMID:22990783

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

    PubMed

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

    2016-04-01

    Primates tend to be long-lived for their size with humans being the longest lived of all primates. There are compelling reasons to understand the underlying age-related processes that shape human lifespan. But the very fact of our long lifespan that makes it so compelling, also makes it especially difficult to study. Thus, in studies of aging, researchers have turned to non-human primate models, including chimpanzees, baboons, and rhesus macaques. More recently, the common marmoset, Callithrix jacchus, has been recognized as a particularly valuable model in studies of aging, given its small size, ease of housing in captivity, and relatively short lifespan. However, little is known about the physiological changes that occur as marmosets age. To begin to fill in this gap, we utilized high sensitivity metabolomics to define the longitudinal biochemical changes associated with age in the common marmoset. We measured 2104 metabolites from blood plasma at three separate time points over a 17-month period, and we completed both a cross-sectional and longitudinal analysis of the metabolome. We discovered hundreds of metabolites associated with age and body weight in both male and female animals. Our longitudinal analysis identified age-associated metabolic pathways that were not found in our cross-sectional analysis. Pathways enriched for age-associated metabolites included tryptophan, nucleotide, and xenobiotic metabolism, suggesting these biochemical pathways might play an important role in the basic mechanisms of aging in primates. Moreover, we found that many metabolic pathways associated with age were sex specific. Our work illustrates the power of longitudinal approaches, even in a short time frame, to discover novel biochemical changes that occur with age. PMID:26805607

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

    PubMed

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

    2015-08-01

    Psoriasis is a common, immune-mediated inflammatory skin disease characterized by red, heavily scaled plaques. The disease affects over one million people in the UK and causes significant physical, psychological and societal impact. There is limited understanding regarding the exact pathogenesis of the disease although it is believed to be a consequence of genetic predisposition and environmental triggers. Treatments vary from topical therapies, such as dithranol, for disease of limited extent (<5% body surface area) to the new immune-targeted biologic therapies for severe psoriasis. Dithranol (also known as anthralin) is a topical therapy for psoriasis believed to work by inhibiting keratinocyte proliferation. To date there have been no metabolomic-based investigations into psoriasis. The HaCaT cell line is a model system for the epidermal keratinocyte proliferation characteristic of psoriasis and was thus chosen for study. Dithranol was applied at therapeutically relevant doses to HaCaT cells. Following the optimisation of enzyme inactivation and metabolite extraction, gas chromatography-mass spectrometry was employed for metabolomics as this addresses central metabolism. Cells were challenged with 0-0.5 μg mL(-1) in 0.1 μg mL(-1) steps and this quantitative perturbation generated data that were highly amenable to correlation analysis. Thus, we used a combination of traditional principal components analysis, hierarchical cluster analysis, along with correlation networks. All methods highlighted distinct metabolite groups, which had different metabolite trajectories with respect to drug concentration and the interpretation of these data established that cellular metabolism had been altered significantly and provided further clarification of the proposed mechanism of action of the drug. PMID:26018604

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2015-01-01

    Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. By using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models. PMID:26287255

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

    PubMed Central

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

    2015-01-01

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

  18. Metabolomic analysis of sex specific metabolites in gonads of the mussel, Mytilus edulis.

    PubMed

    Cubero-Leon, Elena; Minier, Christophe; Rotchell, Jeanette M; Hill, Elizabeth M

    2012-06-01

    Marine mussels have been used as sentinel organisms to monitor exposure to a variety of chemical contaminants, including endocrine disrupting chemicals, in the aquatic environment. Although they are an important species for use in ecotoxicology investigations, information on their reproductive physiology and biochemistry is fragmentary. Mass spectrometry-based profiling techniques are increasingly being used to study how the metabolome of an organism changes as a result of tissue differentiation, disease or in response to environmental stressors. In this study, ultraperformance liquid chromatography-time-of-flight-mass spectrometry (UPLC-TOFMS) was used to investigate sex specific differences in the mussel metabolome in order to further investigate the reproductive physiology of this species. Using this method, a comparison of female and male mantle tissues containing mature gonad, revealed significant differences in glycerophosphatidylcholine (PC) and lysophosphatidylcholine (LPC) metabolites. A number of other unidentified metabolites, including those putatively identified as conjugated sterols, were also differentially expressed between male and female mantle/gonadal tissue. PMID:22475636

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

    PubMed

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

    2015-01-01

    Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. By using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models. PMID:26287255

  20. The potential of metabolomic analysis techniques for the characterisation of α1-adrenergic receptors in cultured N1E-115 mouse neuroblastoma cells.

    PubMed

    Wenner, Maria I; Maker, Garth L; Dawson, Linda F; Drummond, Peter D; Mullaney, Ian

    2016-08-01

    Several studies of neuropathic pain have linked abnormal adrenergic signalling to the development and maintenance of pain, although the mechanisms underlying this are not yet fully understood. Metabolomic analysis is a technique that can be used to give a snapshot of biochemical status, and can aid in the identification of the mechanisms behind pathological changes identified in cells, tissues and biological fluids. This study aimed to use gas chromatography-mass spectrometry-based metabolomic profiling in combination with reverse transcriptase-polymerase chain reaction and immunocytochemistry to identify functional α1-adrenergic receptors on cultured N1E-115 mouse neuroblastoma cells. The study was able to confirm the presence of mRNA for the α1D subtype, as well as protein expression of the α1-adrenergic receptor. Furthermore, metabolomic data revealed changes to the metabolite profile of cells when exposed to adrenergic pharmacological intervention. Agonist treatment with phenylephrine hydrochloride (10 µM) resulted in altered levels of several metabolites including myo-inositol, glucose, fructose, alanine, leucine, phenylalanine, valine, and n-acetylglutamic acid. Many of the changes observed in N1E-115 cells by agonist treatment were modulated by additional antagonist treatment (prazosin hydrochloride, 100 µM). A number of these changes reflected what is known about the biochemistry of α1-adrenergic receptor activation. This preliminary study therefore demonstrates the potential of metabolomic profiling to confirm the presence of functional receptors on cultured cells. PMID:26408527

  1. 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

  2. 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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2014-06-01

    We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics. PMID:24713999

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

    DOE PAGESBeta

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

    2015-04-17

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

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

    SciTech Connect

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

    2015-04-17

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

  12. Metabolomic pattern analysis after mediterranean diet intervention in a nondiabetic population: a 1- and 3-year follow-up in the PREDIMED study.

    PubMed

    Vázquez-Fresno, Rosa; Llorach, Rafael; Urpi-Sarda, Mireia; Lupianez-Barbero, Ascension; Estruch, Ramón; Corella, Dolores; Fitó, Montserrat; Arós, Fernando; Ruiz-Canela, Miguel; Salas-Salvadó, Jordi; Andres-Lacueva, Cristina

    2015-01-01

    The Mediterranean diet (MD) is considered a dietary pattern with beneficial effects on human health. The aim of this study was to assess the effect of an MD on urinary metabolome by comparing subjects at 1 and 3 years of follow-up, after an MD supplemented with either extra-virgin olive oil (MD + EVOO) or nuts (MD + Nuts), to those on advice to follow a control low-fat diet (LFD). Ninety-eight nondiabetic volunteers were evaluated, using metabolomic approaches, corresponding to MD + EVOO (n = 41), MD + Nuts (n = 27), or LFD (n = 30) groups. The (1)H NMR urinary profiles were examined at baseline and after 1 and 3 years of follow-up. Multivariate data analysis (OSC-PLS-DA and HCA) methods were used to identify the potential biomarker discriminating groups, exhibiting a urinary metabolome separation between MD groups against baseline and LFD. Results revealed that the most prominent hallmarks concerning MD groups were related to the metabolism of carbohydrates (3-hydroxybutyrate, citrate, and cis-aconitate), creatine, creatinine, amino acids (proline, N-acetylglutamine, glycine, branched-chain amino acids, and derived metabolites), lipids (oleic and suberic acids), and microbial cometabolites (phenylacetylglutamine and p-cresol). Otherwise, hippurate, trimethylamine-N-oxide, histidine and derivates (methylhistidines, carnosine, and anserine), and xanthosine were predominant after LFD. The application of NMR-based metabolomics enabled the classification of individuals regarding their dietary pattern and highlights the potential of this approach for evaluating changes in the urinary metabolome at different time points of follow-up in response to specific dietary interventions. PMID:25353684

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

    PubMed

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

    2015-09-01

    Huanglongbing (HLB) is one of the most severe diseases that affects citrus trees worldwide and is associated with the yet uncultured bacteria Candidatus Liberibacter spp. To assess the metabolomic differences between HLB-asymptomatic and -symptomatic tissues, extracts from leaf and root samples taken from a uniform 6-year-old commercial orchard of Valencia trees were subjected to nuclear magnetic resonance (NMR) and chemometrics. The results show that the symptomatic trees had higher sucrose content in their leaves and no variation in their roots. In addition, proline betaine and malate were detected in smaller amounts in the HLB-affected symptomatic leaves. The changes in metabolic processes of the plant in response to HLB are corroborated by the relationship between the bacterial levels and the metabolic profiles. PMID:26285838

  14. Transcriptomic, proteomic and metabolomic analysis of maize responses to UV-B

    PubMed Central

    Campi, Mabel; Morrow, Darren J; Fernandes, John; Walbot, Virginia

    2011-01-01

    UV-B radiation from normal solar fluence elicits physiological and developmental changes in plants under fluctuating environmental conditions. Most UV photobiology studies in plants utilize controlled greenhouse and growth chamber environments in which few conditions vary except the brief presence of UV-B radiation. Our purpose was to compare responses to UV-B in irradiated and shielded maize organs in field (natural solar plus 2x solar supplementation for defined periods) and greenhouse (2x solar supplementation only) conditions during a 4 h exposure. Three parameters were assessed—transcripts, proteins and metabolites—to determine the degree of overlap in maize responses in field and greenhouse conditions. We assessed irradiated leaves, and both shielded leaves and immature ears. After comparing transcriptome, proteome and metabolome profiles, we find there are more differences than similarities between field and greenhouse responses. PMID:21758019

  15. [Metabolome Analysis of Human Serum: Implications for Early Detection of Colorectal Cancer].

    PubMed

    Yamazaki, Yasuyo

    2015-03-01

    With the recent development of novel technologies capable of comprehensively detecting and accurately identifying small molecules within biological samples--the field of metabolomics--new information about disease biology is emerging. A comprehensive metabolomics strategy was used to discover novel small molecules which were significantly decreased in the serum of colorectal cancer (CRC) patients relative to normal individuals. The metabolite markers, hydroxylated polyunsaturated ultra long-chain fatty acids (hPULCFAs), were characterized using HPLC-coupled tandem mass spectrometry, and a high-throughput screening (HTS) method compatible with conventional triple-quadrupole mass spectrometers in clinical labs. around the world was developed. The HTS method was used to determine serum levels of the 28 carbon-containing hPULCFA C28H46O4 (named GTA-446) in independent clinical validation studies to investigate the effect of tumor removal after surgery, chemo- or radiation therapy and the correlation with age. We have also obtained results from a two-year prospective trial. Serum samples from a representative cohort of physician-referred colonoscopy subjects (n = 4,923) were collected between July 2008 and August 2010. Ninety-eight new CRC cases were detected in the colonoscopy cohort. Overall sensitivity in this cohort was 85.7%, with 86.5% in the early stage (0-II) and 84.8% in the late-stage (III-IV). This trial represents the first prospective study of this magnitude investigating a metabolic biomarker for CRC. The results indicate that pre-colonoscopy screening using serum GTA-446 levels is a viable approach to detecting early-stage CRC. PMID:26524856

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

    2013-01-01

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

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

    EPA Science Inventory

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

  19. 1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil

    PubMed Central

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

    2013-01-01

    1H NMR-based metabolomics was used to measure the response of Eisenia fetida earthworms after exposure to sub-lethal concentrations of perfluorooctane sulfonate (PFOS) in soil. Earthworms were exposed to a range of PFOS concentrations (five, 10, 25, 50, 100 or 150 mg/kg) for two, seven and fourteen days. Earthworm tissues were extracted and analyzed by 1H NMR. Multivariate statistical analysis of the metabolic response of E. fetida to PFOS exposure identified time-dependent responses that were comprised of two separate modes of action: a non-polar narcosis type mechanism after two days of exposure and increased fatty acid oxidation after seven and fourteen days of exposure. Univariate statistical analysis revealed that 2-hexyl-5-ethyl-3-furansulfonate (HEFS), betaine, leucine, arginine, glutamate, maltose and ATP are potential indicators of PFOS exposure, as the concentrations of these metabolites fluctuated significantly. Overall, NMR-based metabolomic analysis suggests elevated fatty acid oxidation, disruption in energy metabolism and biological membrane structure and a possible interruption of ATP synthesis. These conclusions obtained from analysis of the metabolic profile in response to sub-lethal PFOS exposure indicates that NMR-based metabolomics is an excellent discovery tool when the mode of action (MOA) of contaminants is not clearly defined. PMID:24958147

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

    PubMed

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

    2015-09-01

    The present study was designed to analyse soils by different methodologies to determine the range of traits that could be investigated for the study of environmental soil samples. Proton nuclear magnetic resonance spectroscopy ((1) H NMR) was employed for metametabolomic analysis of soils from agricultural systems (managed) or from soils in a native state (remnant). The metabolomic methodologies employed (grinding and extraction with sonication) are capable of breaking up cell walls and so enabled characterisation of both extracellular and intracellular components of soil. Diffuse mid-infrared spectroscopy (MIR) data was obtained for the same sample sets, and in addition, elemental composition was determined by conventional laboratory chemical testing methods. Also investigated was the antibiotic activity of the soil extracts. Resilient or suppressive soils are valued in the agricultural setting as they convey disease resistance (against bacterial and fungal pathogens) to crop plants. In order to test if any such biological activity could be detected in the soils, the extracts were tested against the bacteria Bacillus subtilis. Several extracts showed strong growth inhibition against the bacteria with the most active clustered together in principle component analysis (PCA) of the metabolomic data. The study showed that the NMR metabolomic approach corresponds more accurately to land use and biochemical properties potentially associated with suppression, while MIR data correlated well to inorganic chemical analysis. Thus, the study demonstrates the utility in combining these spectroscopic methods for soil analysis. PMID:25640917

  1. Metabolomic analysis of percutaneous fine-needle aspiration specimens of thyroid nodules: Potential application for the preoperative diagnosis of thyroid cancer

    PubMed Central

    Ryoo, Inseon; Kwon, Hyuknam; Kim, Soo Chin; Jung, Seung Chai; Yeom, Jeong A; Shin, Hwa Seon; Cho, Hye Rim; Yun, Tae Jin; Choi, Seung Hong; Sohn, Chul-Ho; Park, Sunghyouk; Kim, Ji-hoon

    2016-01-01

    Thyroid nodules are a very common problem. Since malignant thyroid nodules should be treated surgically, preoperative diagnosis of thyroid cancer is very crucial. Cytopathologic analysis of percutaneous fine-needle aspiration (FNA) specimens is the current gold standard for diagnosing thyroid nodules. However, this method has led to high rates of inconclusive results. Metabolomics has emerged as a useful tool in medical fields and shown great potential in diagnosing various cancers. Here, we evaluated the potential of nuclear magnetic resonance (NMR) analysis of percutaneous FNA specimens for preoperative diagnosis of thyroid cancer. We analyzed metabolome of FNA samples of papillary thyroid carcinoma (n = 35) and benign follicular nodule (n = 69) using a proton NMR spectrometer. The metabolomic profiles showed a considerable discrimination between benign and malignant nodules. Receiver operating characteristic (ROC) curve analysis indicated that seven metabolites could serve as discriminators (area under ROC curve value, 0.64–0.85). These findings demonstrated that NMR analysis of percutaneous FNA specimens of thyroid nodules can be potentially useful in the accurate and rapid preoperative diagnosis of thyroid cancer. PMID:27440433

  2. 1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil.

    PubMed

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

    2013-01-01

    1H NMR-based metabolomics was used to measure the response of Eisenia fetida earthworms after exposure to sub-lethal concentrations of perfluorooctane sulfonate (PFOS) in soil. Earthworms were exposed to a range of PFOS concentrations (five, 10, 25, 50, 100 or 150 mg/kg) for two, seven and fourteen days. Earthworm tissues were extracted and analyzed by 1H NMR. Multivariate statistical analysis of the metabolic response of E. fetida to PFOS exposure identified time-dependent responses that were comprised of two separate modes of action: a non-polar narcosis type mechanism after two days of exposure and increased fatty acid oxidation after seven and fourteen days of exposure. Univariate statistical analysis revealed that 2-hexyl-5-ethyl-3-furansulfonate (HEFS), betaine, leucine, arginine, glutamate, maltose and ATP are potential indicators of PFOS exposure, as the concentrations of these metabolites fluctuated significantly. Overall, NMR-based metabolomic analysis suggests elevated fatty acid oxidation, disruption in energy metabolism and biological membrane structure and a possible interruption of ATP synthesis. These conclusions obtained from analysis of the metabolic profile in response to sub-lethal PFOS exposure indicates that NMR-based metabolomics is an excellent discovery tool when the mode of action (MOA) of contaminants is not clearly defined. PMID:24958147

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

    PubMed

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

    2015-07-31

    Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial cell line, RPTEC/TERT1, treated with 10 and 35 μmol·liter(-1) of chloroacetaldehyde, a metabolite of the anti-cancer drug ifosfamide. Our study outlines the establishment of an automated and easy to use untargeted metabolomics workflow for HPLC-high resolution mass spectrometry data. Automated data analysis workflows based on open source software (OpenMS, KNIME) enabled a comprehensive and reproducible analysis of the complex and voluminous metabolomics data produced by the profiling approach. Time- and concentration-dependent responses were clearly evident in the metabolomic profiles. To obtain a more comprehensive picture of the mode of action, transcriptomics and proteomics data were also integrated. For toxicity profiling of chloroacetaldehyde, 428 and 317 metabolite features were detectable in positive and negative modes, respectively, after stringent removal of chemical noise and unstable signals. Changes upon treatment were explored using principal component analysis, and statistically significant differences were identified using linear models for microarray assays. The analysis revealed toxic effects only for the treatment with 35 μmol·liter(-1) for 3 and 14 days. The most regulated metabolites were glutathione and metabolites related to the oxidative stress response of the cells. These findings are corroborated by proteomics and transcriptomics data, which show, among other things, an activation of the Nrf2 and ATF4 pathways. PMID:26055719

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

    PubMed Central

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

    2015-01-01

    Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial cell line, RPTEC/TERT1, treated with 10 and 35 μmol·liter−1 of chloroacetaldehyde, a metabolite of the anti-cancer drug ifosfamide. Our study outlines the establishment of an automated and easy to use untargeted metabolomics workflow for HPLC-high resolution mass spectrometry data. Automated data analysis workflows based on open source software (OpenMS, KNIME) enabled a comprehensive and reproducible analysis of the complex and voluminous metabolomics data produced by the profiling approach. Time- and concentration-dependent responses were clearly evident in the metabolomic profiles. To obtain a more comprehensive picture of the mode of action, transcriptomics and proteomics data were also integrated. For toxicity profiling of chloroacetaldehyde, 428 and 317 metabolite features were detectable in positive and negative modes, respectively, after stringent removal of chemical noise and unstable signals. Changes upon treatment were explored using principal component analysis, and statistically significant differences were identified using linear models for microarray assays. The analysis revealed toxic effects only for the treatment with 35 μmol·liter−1 for 3 and 14 days. The most regulated metabolites were glutathione and metabolites related to the oxidative stress response of the cells. These findings are corroborated by proteomics and transcriptomics data, which show, among other things, an activation of the Nrf2 and ATF4 pathways. PMID:26055719

  5. A model-driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K-12 MG1655 that is biochemically and thermodynamically consistent.

    PubMed

    McCloskey, Douglas; Gangoiti, Jon A; King, Zachary A; Naviaux, Robert K; Barshop, Bruce A; Palsson, Bernhard O; Feist, Adam M

    2014-04-01

    The advent of model-enabled workflows in systems biology allows for the integration of experimental data types with genome-scale models to discover new features of biology. This work demonstrates such a workflow, aimed at establishing a metabolomics platform applied to study the differences in metabolomes between anaerobic and aerobic growth of Escherichia coli. Constraint-based modeling was utilized to deduce a target list of compounds for downstream method development. An analytical and experimental methodology was developed and tailored to the compound chemistry and growth conditions of interest. This included the construction of a rapid sampling apparatus for use with anaerobic cultures. The resulting genome-scale data sets for anaerobic and aerobic growth were validated by comparison to previous small-scale studies comparing growth of E. coli under the same conditions. The metabolomics data were then integrated with the E. coli genome-scale metabolic model (GEM) via a sensitivity analysis that utilized reaction thermodynamics to reconcile simulated growth rates and reaction directionalities. This analysis highlighted several optimal network usage inconsistencies, including the incorrect use of the beta-oxidation pathway for synthesis of fatty acids. This analysis also identified enzyme promiscuity for the pykA gene, that is critical for anaerobic growth, and which has not been previously incorporated into metabolic models of E coli. PMID:24249002

  6. A NEW METABOLOMICS ANALYSIS TECHNIQUE: STEADY-STATE METABOLIC NETWORK DYNAMICS ANALYSIS

    PubMed Central

    CAKMAK, ALI; QI, XINJIAN; CICEK, A. ERCUMENT; BEDERMAN, ILYA; HENDERSON, LEIGH; DRUMM, MITCHELL; OZSOYOGLU, GULTEKIN

    2014-01-01

    With the recent advances in experimental technologies, such as gas chromatography and mass spectrometry, the number of metabolites that can be measured in biofluids of individuals has markedly increased. Given a set of such measurements, a very common task encountered by biologists is to identify the metabolic mechanisms that lead to changes in the concentrations of given metabolites and interpret the metabolic consequences of the observed changes in terms of physiological problems, nutritional deficiencies, or diseases. In this paper, we present the steady-state metabolic network dynamics analysis (SMDA) approach in detail, together with its application in a cystic fibrosis study. We also present a computational performance evaluation of the SMDA tool against a mammalian metabolic network database. The query output space of the SMDA tool is exponentially large in the number of reactions of the network. However, (i) larger numbers of observations exponentially reduce the output size, and (ii) exploratory search and browsing of the query output space is provided to allow users to search for what they are looking for. PMID:22809304

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

    PubMed

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

    2014-11-01

    Metabolomics techniques are the comprehensive assessment of endogenous metabolites in a biological system and may provide additional insight into the molecular mechanisms. Er-Zhi-Wan (EZW) is a traditional Chinese medicine formula, which contains Fructus Ligustri Lucidi (FLL) and Herba Ecliptae (HE). EZW is widely used to prevent and treat various liver injuries through the nourishment of the liver. However, the precise molecular mechanism of hepatoprotective effects has not been comprehensively explored. Here, an integrated metabolomics strategy was designed to assess the effects and possible mechanisms of EZW against carbon tetrachloride-induced liver injury, a commonly used model of both acute and chronic liver intoxication. High-performance chromatography/quadrupole time-of-flight mass spectrometry (HPLC/QTOF-MS) combined with chemometric approaches including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to discover differentiating metabolites in metabolomics data of rat plasma and urine. Results indicate six differentiating metabolites, tryptophan, sphinganine, tetrahydrocorticosterone, pipecolic acid, L-2-amino-3-oxobutanoic acid and phosphoribosyl pyrophosphate, in the positive mode. Functional pathway analysis revealed that the alterations in these metabolites were associated with tryptophan metabolism, sphingolipid metabolism, steroid hormone biosynthesis, lysine degradation, glycine, serine and threonine metabolism, and pentose phosphate pathway. Of note, EZW has a potential pharmacological effect, which might be through regulating multiple perturbed pathways to the normal state. Our findings also showed that the robust integrated metabolomics techniques are promising for identifying more biomarkers and pathways and helping to clarify the function mechanisms of traditional Chinese medicine. PMID:25245419

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

    PubMed Central

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

    2016-01-01

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

  9. Serum metabolomics study and eicosanoid analysis of childhood atopic dermatitis based on liquid chromatography-mass spectrometry.

    PubMed

    Huang, Yan; Chen, Guoyou; Liu, Xinyu; Shao, Yaping; Gao, Peng; Xin, Chenchen; Cui, Zhenze; Zhao, Xinjie; Xu, Guowang

    2014-12-01

    Atopic dermatitis (AD) is the most common inflammatory skin disease in children. In the study, ultra high performance liquid chromatography-mass spectrometry was used to investigate serum metabolic abnormalities of AD children. Two batch fasting sera were collected from AD children and healthy control; one of them was for nontargeted metabolomics analysis, the other for targeted eicosanoids analysis. AD children were divided into high immunoglobulin E (IgE) group and normal IgE group. On the basis of the two analysis approaches, it was found that the differential metabolites of AD, leukotriene B4, prostaglandins, conjugated bile acids, etc., were associated with inflammatory response and bile acids metabolism. Carnitines, free fatty acids, lactic acid, etc., increased in the AD group with high IgE, which revealed energy metabolism disorder. Amino acid metabolic abnormalities and increased levels of Cytochrome P450 epoxygenase metabolites were found in the AD group with normal IgE. The results provided a new perspective to understand the mechanism and find potential biomarkers of AD and may provide a new reference for personalized treatment. PMID:25316199

  10. Metabolomic Analysis of Key Central Carbon Metabolism Carboxylic Acids as Their 3-Nitrophenylhydrazones by UPLC/ESI-MS

    PubMed Central

    Han, Jun; Gagnon, Susannah; Eckle, Tobias; Borchers, Christoph H.

    2014-01-01

    Multiple hydroxy-, keto-, di-, and tri-carboxylic acids are among the cellular metabolites of central carbon metabolism (CCM). Sensitive and reliable analysis of these carboxylates is important for many biological and cell engineering studies. In this work, we examined 3-nitrophenylhydrazine as a derivatizing reagent and optimized the reaction conditions for the measurement of ten CCM related carboxylic compounds, including glycolate, lactate, malate, fumarate, succinate, citrate, isocitrate, pyruvate, oxaloacetate, and α-ketoglutarate as their 3-nitrophenylhydrazones using LC/MS with electrospray ionization. With the derivatization protocol which we have developed, and using negative-ion multiple reaction monitoring on a triple-quadrupole instrument, all of the carboxylates showed good linearity within a dynamic range of ca. 200 to more than 2000. The on-column limits of detection and quantitation were from high femtomoles to low picomoles. The analytical accuracies for eight of the ten analytes were determined to be between 89.5 to 114.8% (CV≤7.4%, n=6). Using a quadrupole time-of-flight instrument, the isotopic distribution patterns of these carboxylates, extracted from a 13C-labeled mouse heart, were successfully determined by UPLC/MS with full-mass detection, indicating the possible utility of this analytical method for metabolic flux analysis. In summary, this work demonstrates an efficient chemical derivatization LC/MS method for metabolomic analysis of these key CCM intermediates in a biological matrix. PMID:23580203

  11. Quantitative Analysis of Cancer Metabolism: From pSIRM to MFA.

    PubMed

    Zasada, Christin; Kempa, Stefan

    2016-01-01

    Metabolic reprogramming is a required step during oncogenesis and essential for cellular proliferation. It is triggered by activation of oncogenes and loss of tumor suppressor genes. Beside the combinatorial events leading to cancer, common changes within the central metabolism are reported. Increase of glycolysis and subsequent lactic acid formation has been a focus of cancer metabolism research for almost a century. With the improvements of bioanalytical techniques within the last decades, a more detailed analysis of metabolism is possible and recent studies demonstrate a wide range of metabolic rearrangements in various cancer types. However, a systematic and mechanistic understanding is missing thus far. Therefore, analytical and computational tools have to be developed allowing for a dynamic and quantitative analysis of cancer metabolism. In this chapter, we outline the application of pulsed stable isotope resolved metabolomics (pSIRM) and describe the interface toward computational analysis of metabolism. PMID:27557540

  12. Untargeted metabolomic analysis of miltefosine action in Leishmania infantum reveals changes to the internal lipid metabolism☆

    PubMed Central

    Vincent, Isabel M.; Weidt, Stefan; Rivas, Luis; Burgess, Karl; Smith, Terry K.; Ouellette, Marc

    2013-01-01

    There are many theories as to the mode of action of miltefosine against Leishmania including alterations to the membrane lipid content, induction of apoptosis and modulation of macrophage responses. Here we perform untargeted metabolomics to elucidate the metabolic changes involved in miltefosine action. Over 800 metabolites were detected, 10% of which were significantly altered after 3.75 h. Many of the changes related to an increase in alkane fragment and sugar release. Fragment release is synchronised with reactive oxygen species production, but native membrane phospholipids remain intact. Signs of DNA damage were also detected as were changes to the levels of some thiols and polyamines. After 5 h of miltefosine treatment the cells showed depleted levels of most metabolites, indicating that the cells’ outer membrane integrity had become compromised and internal metabolites were escaping upon cell death. In miltefosine resistant cells, the drug was not internalised and the changes to the internal metabolite levels were not seen. In contrast, cells resistant to antimony (SbIII) had similar corresponding alterations to the levels of internal metabolites as wild-type cells. A detailed knowledge of the mode of action of miltefosine will be important to inform the design of combination therapies to combat leishmaniasis, something that the research community should be prioritising in the coming years. PMID:24596665

  13. Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower.

    PubMed

    Moschen, Sebastián; Bengoa Luoni, Sofía; Di Rienzo, Julio A; Caro, María Del Pilar; Tohge, Takayuki; Watanabe, Mutsumi; Hollmann, Julien; González, Sergio; Rivarola, Máximo; García-García, Francisco; Dopazo, Joaquin; Hopp, Horacio Esteban; Hoefgen, Rainer; Fernie, Alisdair R; Paniego, Norma; Fernández, Paula; Heinz, Ruth A

    2016-02-01

    Leaf senescence is a complex process, which has dramatic consequences on crop yield. In sunflower, gap between potential and actual yields reveals the economic impact of senescence. Indeed, sunflower plants are incapable of maintaining their green leaf area over sustained periods. This study characterizes the leaf senescence process in sunflower through a systems biology approach integrating transcriptomic and metabolomic analyses: plants being grown under both glasshouse and field conditions. Our results revealed a correspondence between profile changes detected at the molecular, biochemical and physiological level throughout the progression of leaf senescence measured at different plant developmental stages. Early metabolic changes were detected prior to anthesis and before the onset of the first senescence symptoms, with more pronounced changes observed when physiological and molecular variables were assessed under field conditions. During leaf development, photosynthetic activity and cell growth processes decreased, whereas sucrose, fatty acid, nucleotide and amino acid metabolisms increased. Pathways related to nutrient recycling processes were also up-regulated. Members of the NAC, AP2-EREBP, HB, bZIP and MYB transcription factor families showed high expression levels, and their expression level was highly correlated, suggesting their involvement in sunflower senescence. The results of this study thus contribute to the elucidation of the molecular mechanisms involved in the onset and progression of leaf senescence in sunflower leaves as well as to the identification of candidate genes involved in this process. PMID:26132509

  14. Integrative analysis of proteomics and metabolomics of anaphylactoid reaction induced by Xuesaitong injection.

    PubMed

    Xu, Yubin; Dou, Deqiang; Ran, Xiaoku; Liu, Chunyan; Chen, Jing

    2015-10-16

    Injection with natural compounds is an important method in the application of natural medicine, but its adverse drug reactions (ADRs) occur frequently, particularly the anaphylactoid reaction, which accounts for more than 77% of all reactions and has become a serious threat to public health. Here, the Xuesaitong injection (XSTI) was employed as an example to elucidate its anaphylactoid mechanism and look for potential biomarkers to assay the anaphylactoid reaction of herbal medicine injection by proteomics and metabolomics. These results disclosed that 13 differential proteins and 28 metabolites, which were further approved using the ELISA method and reference standards, respectively, were suggested as potential biomarkers to examine the anaphylactoid mechanism. The up-regulated expression of Gpx1, Sc5b9, C4d and down-regulated expression of F12, Kng1, C2 and C6 revealed that the XSTI-induced anaphylactoid reaction occurs via direct stimulation, complement and the kallikrein-kinin pathway. In addition, substances that induce an anaphylactoid effect include histamine, LTB4, uric acid and other drugs, which have been confirmed to be involved in arginine and proline metabolism, histidine metabolism, arachidonic acid metabolism purine metabolism and the TCA cycle. Furthermore, separation experiments have indicated that 10-kDa molecules of XSTI are the main allergenic factor inducing an anaphylactoid reaction. PMID:26372445

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2015-09-01

    In the study, fourteen chemical modulators from five groups (i.e., auxin, gibberellin, cytokinin, signal transducer and amine) were evaluated for their effects on lipid accumulation in Crypthecodinium cohnii. The results showed that naphthoxyacetic acid (BNOA), 2-chlorodracylicacid, salicylic acid (SA), abscisic acid (ABA) and ethanolamine (ETA), increased lipid accumulation in C. cohnii by 10.00-18.78%. In addition, the combined uses of the above chemicals showed that two combinations, 1.0mg/L SA & 152.7 mg/L ETA and 4.0mg/L BNOA & 152.7 mg/L ETA, increased lipid accumulation by 22.45% and 20.54%, respectively. Moreover, a targeted metabolomic approach was employed to decipher the possible mechanisms responsible for the increased lipid accumulation, and the results showed that the enhanced metabolism in glycolysis and TCA cycle as well as the decreased metabolism in PPP pathway could be important for the stimulatory roles of BNOA & ETA and SA & ETA on lipid accumulation in C. cohnii. PMID:25818259

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

    SciTech Connect

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

    2010-06-04

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    Dinakar, Challabathula; Bartels, Dorothea

    2013-01-01

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

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

    PubMed

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

    2015-02-01

    Aromatic amines are widely distributed in the environment and are major environmental pollutants. Although degradation of aromatic amines is well studied in bacteria, physiological adaptations and stress response to these toxic compounds is not yet fully understood. In the present study, systemic responses of Rubrivivax benzoatilyticus JA2 to aniline stress were deciphered using metabolite and iTRAQ-labeled protein profiling. Strain JA2 tolerated high concentrations of aniline (30 mM) with trace amounts of aniline being transformed to acetanilide. GC-MS metabolite profiling revealed aniline stress phenotype wherein amino acid, carbohydrate, fatty acid, nitrogen metabolisms, and TCA (tricarboxylic acid cycle) were modulated. Strain JA2 responded to aniline by remodeling the proteome, and cellular functions, such as signaling, transcription, translation, stress tolerance, transport and carbohydrate metabolism, were highly modulated. Key adaptive responses, such as transcription/translational changes, molecular chaperones to control protein folding, and efflux pumps implicated in solvent extrusion, were induced in response to aniline stress. Proteo-metabolomics indicated extensive rewiring of metabolism to aniline. TCA cycle and amino acid catabolism were down-regulated while gluconeogenesis and pentose phosphate pathways were up-regulated, leading to the synthesis of extracellular polymeric substances. Furthermore, increased saturated fatty acid ratios in membranes due to aniline stress suggest membrane adaptation. The present study thus indicates that strain JA2 employs multilayered responses: stress response, toxic compound tolerance, energy conservation, and metabolic rearrangements to aniline. PMID:25388363

  1. Analysis of Eisenia fetida earthworm responses to sub-lethal C60 nanoparticle exposure using (1)H-NMR based metabolomics.

    PubMed

    Lankadurai, Brian P; Nagato, Edward G; Simpson, André J; Simpson, Myrna J

    2015-10-01

    The enhanced production and environmental release of Buckminsterfullerene (C60) nanoparticles will likely increase the exposure and risk to soil dwelling organisms. We used (1)H NMR-based metabolomics to investigate the response of Eisenia fetida earthworms to sub-lethal C60 nanoparticle exposure in both contact and soil tests. Principal component analysis of (1)H NMR data showed clear separation between controls and exposed earthworms after just 2 days of exposure, however as exposure time increased the separation decreased in soil but increased in contact tests suggesting potential adaptation during soil exposure. The amino acids leucine, valine, isoleucine and phenylalanine, the nucleoside inosine, and the sugars glucose and maltose emerged as potential bioindicators of exposure to C60 nanoparticles. The significant responses observed in earthworms using NMR-based metabolomics after exposure to very low concentrations of C60 nanoparticles suggests the need for further investigations to better understand and predict their sub-lethal toxicity. PMID:26024814

  2. Metabolomics and Epidemiology Working Group

    Cancer.gov

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

  3. Qualitative Metabolome Analysis of Human Cerebrospinal Fluid by 13C-/12C-Isotope Dansylation Labeling Combined with Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

    NASA Astrophysics Data System (ADS)

    Guo, Kevin; Bamforth, Fiona; Li, Liang

    2011-02-01

    Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by 13C-dansyl and 12C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner.

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2015-11-01

    This paper introduces a detailed method to apply metabolic profiles conducting on tangerine peels (Citrus reticulata 'Dahongpao') at three maturity stages from July to December. Principal component analysis not only demonstrated the metabolic footprints of tangerine peels during ripening but also revealed the compounds (D-limonene and linalool) that mostly contributed to it. Furthermore, some other characteristic compounds were screened to further reveal the chemical features of Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV). In particular, compounds such as 4-carene (r = -0.94), 3-carene (r = -0.91), β-pinene (r = -0.85) and γ-terpinene (r = -0.87) were screened as major components for the pungent smell of PCRV. Geranyl acetate (r = 0.81), farnesyl acetate (r = 0.87) and three alcohols (6-hepten-1-ol, 3-methyl-1-hexanol, 1-octanol) may lead to the pleasant odour of PCR. We therefore propose that the metabolomics analysis focusing on ripening process will be an effective strategy for quality control of closely related herbal medicines. PMID:25976810

  6. Metabolomic analysis of saponins in crude extracts of Quillaja saponaria by liquid chromatography/mass spectrometry for product authentication.

    PubMed

    Kite, Geoffrey C; Howes, Melanie-Jayne R; Simmonds, Monique S J

    2004-01-01

    Analysis of 50% aqueous methanolic extracts of bark of Quillaja saponaria Molina (quillaja) by liquid chromatography/mass spectrometry (LC/MS), using negative ion electrospray, revealed over 100 saponins. The majority could be assigned to known structures or generalised variations of these from the product ion spectra obtained by serial mass spectrometry in a quadrupole ion trap mass spectrometer. Ten saponins contained a fatty acid domain terminated with both a pentose and deoxyhexose unit, a feature thus far only reported in QS-III. Twenty saponins were based on a hydroxylated derivative of quillaic acid, whereas only six 22beta-hydroxyquillaic acid saponins have been described. The occurrence of pairs of saponins differing only by the presence of a rhamnose or xylose unit in the C-3-substituted saccharide was readily observed in two-dimensional mass maps, and these showed the presence of the unreported 'rhamnose partner' of QS-III. However, one sample labelled as Q. saponaria appeared to lack all saponins containing rhamnose in the C-3 saccharide. Methods to authenticate saponin extracts of quillaja by LC/MS are suggested based on the general metabolomic profile, the occurrence of specific major saponins covering known structural variations, or the presence of saponins containing the unusual fatty acid domain, revealed by neutral loss analysis. PMID:15517552

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

    PubMed Central

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

    2010-01-01

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

  8. Increased serum bile acid concentration following low-dose chronic administration of thioacetamide in rats, as evidenced by metabolomic analysis.

    PubMed

    Jeong, Eun Sook; Kim, Gabin; Shin, Ho Jung; Park, Se-Myo; Oh, Jung-Hwa; Kim, Yong-Bum; Moon, Kyoung-Sik; Choi, Hyung-Kyoon; Jeong, Jayoung; Shin, Jae-Gook; Kim, Dong Hyun

    2015-10-15

    A liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS)-based metabolomics approach was employed to identify endogenous metabolites as potential biomarkers for thioacetamide (TAA)-induced liver injury. TAA (10 and 30mg/kg), a well-known hepatotoxic agent, was administered daily to male Sprague-Dawley (SD) rats for 28days. We then conducted untargeted analyses of endogenous serum and liver metabolites. Partial least squares discriminant analysis (PLS-DA) was performed on serum and liver samples to evaluate metabolites associated with TAA-induced perturbation. TAA administration resulted in altered levels of bile acids, acyl carnitines, and phospholipids in serum and in the liver. We subsequently demonstrated and confirmed the occurrence of compromised bile acid homeostasis. TAA treatment significantly increased serum levels of conjugated bile acids in a dose-dependent manner, which correlated well with toxicity. However, hepatic levels of these metabolites were not substantially changed. Gene expression profiling showed that the hepatic mRNA levels of Ntcp, Bsep, and Oatp1b2 were significantly suppressed, whereas those of basolateral Mrp3 and Mrp4 were increased. Decreased levels of Ntcp, Oatp1b2, and Ostα proteins in the liver were confirmed by western blot analysis. These results suggest that serum bile acids might be increased due to the inhibition of bile acid enterohepatic circulation rather than increased endogenous bile acid synthesis. Moreover, serum bile acids are a good indicator of TAA-induced hepatotoxicity. PMID:26222700

  9. Targeted metabolomics of the arachidonic acid cascade: current state and challenges of LC-MS analysis of oxylipins.

    PubMed

    Willenberg, Ina; Ostermann, Annika I; Schebb, Nils Helge

    2015-04-01

    Quantification of eicosanoids and oxylipins derived from other polyunsaturated fatty acids in biological samples is crucial for a better understanding of the biology of these lipid mediators. Moreover, a robust and reliable quantification is necessary to monitor the effects of pharmaceutical intervention and diet on the arachidonic acid (AA) cascade, one of today's most relevant drug targets. Low (sub-nanomolar) concentrations and a large number of structurally similar analytes, including regioisomers, require high chromatographic resolution and selective and sensitive mass spectrometry analysis. Currently, reversed-phase liquid chromatography in combination with detection on sensitive triple-quadrupole instruments, operating in selected reaction monitoring mode, is the main method of quantitative oxylipin analysis. A lack of standardized sample collection, handling, and preparation procedures, degradation of the analytes during sample preparation, and purity and availability of standards (internal standards) are the major problems of targeted metabolomics approaches for the AA cascade. Major challenges for instrumental analytical methods are the detection of esterified oxylipins, and separation and individual detection of oxylipin isomers. Solving these problems would help to further knowledge of the biology of lipid mediators, and is an important task for bio-analytical research. PMID:25577350

  10. Metabolomic analysis of amino acid and fat metabolism in rats with L-tryptophan supplementation.

    PubMed

    Ruan, Zheng; Yang, Yuhui; Wen, Yanmei; Zhou, Yan; Fu, Xiaofang; Ding, Sheng; Liu, Gang; Yao, Kang; Wu, Xin; Deng, Zeyuan; Wu, Guoyao; Yin, Yulong

    2014-12-01

    Tryptophan (TRP) is an important precursor for several neurotransmitters and metabolic regulators, which play a vital role in regulating nutrient metabolism. The purpose of this study was to investigate the effects of tryptophan supplementation on the biochemical profiles, intestinal structure, liver structure and serum metabolome in rats. Rats received daily intragastric administration of either tryptophan at doses of 200 mg/kg body weight per day or saline (control group) for 7 days. TRP supplementation had a tendency to decrease the body weight of rats (P > 0.05). The levels of urea and CHO in serum were decreased in the TRP-supplemented group rats compared with control group rats (P < 0.05). TRP supplementation increased the villus height and the ratio of villus height to crypt depth in the jejunum compared to control group rats (P < 0.05). Metabolic effects of tryptophan supplementation include: (1) increases in the serum concentrations of lysine, glycine, alanine, glutamate, glutamine, citrulline, methionine, tyrosine, 1-methylhistidine, and albumin, and decreases in the concentrations of serum branched-chain amino acid (isoleucine, valine and leucine); (2) decreases in the serum concentrations of formate and nitrogenous products (trimethylamine, TMAO, methylamine and dimethylamine), and in the contraction of trimethylamine in feces; (3) decreases in serum levels of lipids, low density lipoprotein, very low density lipoprotein, together with the elevated ratio of acetoacetate to β-hydroxybutyrate. The results indicate that tryptophan supplementation reduced the catabolism of dietary amino acids and promoted protein synthesis in rats, promoted the oxidation of fatty acid and reduced fat deposition in the body of rats. PMID:25139634

  11. Transcriptomic, proteomic and metabolomic analysis of UV-B signaling in maize

    PubMed Central

    2011-01-01

    Background Under normal solar fluence, UV-B damages macromolecules, but it also elicits physiological acclimation and developmental changes in plants. Excess UV-B decreases crop yield. Using a treatment twice solar fluence, we focus on discovering signals produced in UV-B-irradiated maize leaves that translate to systemic changes in shielded leaves and immature ears. Results Using transcriptome and proteomic profiling, we tracked the kinetics of transcript and protein alterations in exposed and shielded organs over 6 h. In parallel, metabolic profiling identified candidate signaling molecules based on rapid increase in irradiated leaves and increased levels in shielded organs; pathways associated with the synthesis, sequestration, or degradation of some of these potential signal molecules were UV-B-responsive. Exposure of just the top leaf substantially alters the transcriptomes of both irradiated and shielded organs, with greater changes as additional leaves are irradiated. Some phenylpropanoid pathway genes are expressed only in irradiated leaves, reflected in accumulation of pathway sunscreen molecules. Most protein changes detected occur quickly: approximately 92% of the proteins in leaves and 73% in immature ears changed after 4 h UV-B were altered by a 1 h UV-B treatment. Conclusions There were significant transcriptome, proteomic, and metabolomic changes under all conditions studied in both shielded and irradiated organs. A dramatic decrease in transcript diversity in irradiated and shielded leaves occurs between 0 h and 1 h, demonstrating the susceptibility of plants to short term UV-B spikes as during ozone depletion. Immature maize ears are highly responsive to canopy leaf exposure to UV-B. PMID:21679461

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2016-03-01

    A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols. PMID:26757030

  14. A Statistical Analysis of the Effects of Urease Pre-treatment on the Measurement of the Urinary Metabolome by Gas Chromatography-Mass Spectrometry

    PubMed Central

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

    2014-01-01

    Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentified metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Overall, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses. PMID:25254001

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

    DOE PAGESBeta

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

    2014-02-27

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

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

    SciTech Connect

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

    2014-02-27

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

  17. Sample normalization methods in quantitative metabolomics.

    PubMed

    Wu, Yiman; Li, Liang

    2016-01-22

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

  18. Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer.

    PubMed

    Huan, Tao; Troyer, Dean A; Li, Liang

    2016-01-01

    We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy. PMID:27578275

  19. Integrated metabolomics and metagenomics analysis of plasma and urine identified microbial metabolites associated with coronary heart disease.

    PubMed

    Feng, Qiang; Liu, Zhipeng; Zhong, Shilong; Li, Ruijun; Xia, Huihua; Jie, Zhuye; Wen, Bo; Chen, Xiaomin; Yan, Wei; Fan, Yanqun; Guo, Zhenyu; Meng, Nan; Chen, Jiyan; Yu, Xiyong; Zhang, Zhiwei; Kristiansen, Karsten; Wang, Jun; Xu, Xun; He, Kunlun; Li, Guanglei

    2016-01-01

    Coronary heart disease (CHD) is top risk factor for health in modern society, causing high mortality rate each year. However, there is no reliable way for early diagnosis and prevention of CHD so far. So study the mechanism of CHD and development of novel biomarkers is urgently needed. In this study, metabolomics and metagenomics technology are applied to discover new biomarkers from plasma and urine of 59 CHD patients and 43 healthy controls and trace their origin. We identify GlcNAc-6-P which has good diagnostic capability and can be used as potential biomarkers for CHD, together with mannitol and 15 plasma cholines. These identified metabolites show significant correlations with clinical biochemical indexes. Meanwhile, GlcNAc-6-P and mannitol are potential metabolites originated from intestinal microbiota. Association analysis on species and function levels between intestinal microbes and metabolites suggest a close correlation between Clostridium sp. HGF2 and GlcNAc-6-P, Clostridium sp. HGF2, Streptococcus sp. M143, Streptococcus sp. M334 and mannitol. These suggest the metabolic abnormality is significant and gut microbiota dysbiosis happens in CHD patients. PMID:26932197

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

    PubMed

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

    2013-11-01

    Red-flowered buckwheat ( Fagopyrum esculentum ) is used in the production of tea, juice, and alcohols after the detoxification of fagopyrin. In order to investigate the metabolomics and regulatory of anthocyanin production in red-flowered (Gan-Chao) and white-flowered (Tanno) buckwheat cultivars, quantitative real-time RT-PCR (qRT-PCR), gas chromatography time-of-flight mass spectrometry (GC-TOFMS), and high performance liquid chromatography (HPLC) were conducted. The transcriptions of FePAL, FeC4H, Fe4CL1, FeF3H, FeANS, and FeDFR increased gradually from flowering stage 1 and reached their highest peaks at flowering stage 3 in Gan-Chao flower. In total 44 metabolites, 18 amino acids, 15 organic acids, 7 sugars, 3 sugar alcohols, and 1 amine were detected in Gan-Chao flowers. Two anthocyanins, cyanidin 3-O-glucoside and cyanidin 3-O-rutinoside, were identified in Gan-Chao cultivar. The first component of the partial least-squares to latent structures-discriminate analysis (PLS-DA) indicated that high amounts of phenolic, shikimic, and pyruvic acids were present in Gan-Chao. We suggest that transcriptions of genes involved in anthocyanin biosynthesis, anthocyanin contents, and metabolites have correlation in the red-flowered buckwheat Gan-Chao flowers. Our results may be helpful to understand anthocyanin biosynthesis in red-flowered buckwheat. PMID:24083509

  1. Integrated metabolomics and metagenomics analysis of plasma and urine identified microbial metabolites associated with coronary heart disease

    PubMed Central

    Feng, Qiang; Liu, Zhipeng; Zhong, Shilong; Li, Ruijun; Xia, Huihua; Jie, Zhuye; Wen, Bo; Chen, Xiaomin; Yan, Wei; Fan, Yanqun; Guo, Zhenyu; Meng, Nan; Chen, Jiyan; Yu, Xiyong; Zhang, Zhiwei; Kristiansen, Karsten; Wang, Jun; Xu, Xun; He, Kunlun; Li, Guanglei

    2016-01-01

    Coronary heart disease (CHD) is top risk factor for health in modern society, causing high mortality rate each year. However, there is no reliable way for early diagnosis and prevention of CHD so far. So study the mechanism of CHD and development of novel biomarkers is urgently needed. In this study, metabolomics and metagenomics technology are applied to discover new biomarkers from plasma and urine of 59 CHD patients and 43 healthy controls and trace their origin. We identify GlcNAc-6-P which has good diagnostic capability and can be used as potential biomarkers for CHD, together with mannitol and 15 plasma cholines. These identified metabolites show significant correlations with clinical biochemical indexes. Meanwhile, GlcNAc-6-P and mannitol are potential metabolites originated from intestinal microbiota. Association analysis on species and function levels between intestinal microbes and metabolites suggest a close correlation between Clostridium sp. HGF2 and GlcNAc-6-P, Clostridium sp. HGF2, Streptococcus sp. M143, Streptococcus sp. M334 and mannitol. These suggest the metabolic abnormality is significant and gut microbiota dysbiosis happens in CHD patients. PMID:26932197

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

    PubMed

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

    2016-01-01

    The prevalence of obesity has dramatically increased and poses a major threat to human health. Obesity often accompanies hyperlipemia, which is strongly related to the occurrence and development of obesity-related chronic diseases. Differences in metabolomic profiling of serum between obese (with hyperlipemia) and normal-weight men (n = 30 in each group) were investigated using ultrahigh-pressure liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF MS/MS) and partial least-squares-discriminant analysis (PLS-DA). Obese men showed higher levels of weight, body mass index, fat mass, systolic blood pressure, fasting plasma glucose, triglyeride, total cholesterol, insulin, HOMA-IR and high-sensitivity CRP. Obese and normal-weight groups were clearly discriminated from each other on a PLS-DA score plot and nine major metabolites contributing to the discrimination were assigned, including increased 2-octenoylcarnitine, eicosadienoic acid, 12-hydroperoxyeicosatetraenoic acid, 4-hydroxyestrone sulfate, lysoPE[18:1(11Z)/0:0], thromboxane B2 and pyridinoline and decreased vitamin D3 glucosiduronate and 9,10-DHOME. These metabolites were associated with lipid metabolism and obesity-related diseases, and reflected the metabolic differences between normal and obese men, which may be important for future clinical diagnosis, treatment and assessment of the therapeutic effect on obesity-related chronic disease. PMID:26043712

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

    PubMed

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

    2016-01-22

    Species of Aristolochia are used as herbal medicines worldwide. They cause aristolochic acid nephropathy (AAN), a devastating disease associated with kidney failure and renal cancer. Aristolochic acids I and II (1 and 2) are considered to be responsible for these nephrotoxic and carcinogenic effects. A wide range of other aristolochic acid analogues (AAAs) exist, and their implication in AAN may have been overlooked. An LC-MS- and (1)H NMR-based metabolomic analysis was carried out on 43 medicinally used Aristolochia species. The cytotoxicity and genotoxicity of 28 Aristolochia extracts were measured in human kidney (HK-2) cells. Compounds 1 and 2 were found to be the most common AAAs. However, AA IV (3), aristolactam I (4), and aristolactam BI (5) were also widespread. No correlation was found between the amounts of 1 or 2 and extract cytotoxicity against HK-2 cells. The genotoxicity and cytotoxicity of the extracts could be linked to their contents of 5, AA D (8), and AA IIIa (10). These results undermine the assumption that 1 and 2 are exclusively responsible for the toxicity of Aristolochia species. Other analogues are likely to contribute to their toxicity and need to be considered as nephrotoxic agents. These findings facilitate understanding of the nephrotoxic mechanisms of Aristolochia and have significance for the regulation of herbal medicines. PMID:26706944

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

    PubMed

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

    2016-02-01

    With a great difference in therapeutic effects of Mahuang (MH, the stems of Ephedra sinica) and Mahuanggen (MHG, the roots of Ephedra sinica), chemical differences between MH and MHG should be investigated. In the present study, gas chromatography-mass spectrometry (GC-MS)-based plant metabolomics was employed to compare volatile oil profiles of MH and MHG. The antioxidant activities of volatile oils from MH and MHG were also compared. 32 differential chemical markers were identified according to the variable importance in the projection (VIP) value of orthogonal partial least squares discriminant analysis (OPLS-DA) and P value of Mann-Whitney test. Among them, chemical markers of tetramethylpyrazine (TMP) and α-terpineol were quantified. Their contents were much higher in most MH samples compared with MHG. The antioxidant assay demonstrated that MH had significantly higher free radical-scavenging activity than MHG. Although MH and MHG derived from the same medicinal plant, there was much difference in their volatile oil profiles. MH samples had significantly higher content of two reported pharmacologically important chemical markers of TMP and α-terpineol, which may account for their different antioxidant activities. PMID:26968679

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

    PubMed

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

    2015-02-01

    The current study presents a method for comprehensive untargeted metabolomic fingerprinting of the non-volatile profile of the Graciano Vitis vinifera wine variety, using liquid chromatography/electrospray ionization time of flight mass spectrometry (LC-ESI-QTOF). Pre-treatment of samples, chromatographic columns, mobile phases, elution gradients and ionization sources, were evaluated for the extraction of the maximum number of metabolites in red wine. Putative compounds were extracted from the raw data using the extraction algorithm, molecular feature extractor (MFE). For the metabolite identification the WinMet database was designed based on electronic databases and literature research and includes only the putative metabolites reported to be present in oenological matrices. The results from WinMet were compared with those in the METLIN database to evaluate how much the databases overlap for performing identifications. The reproducibility of the analysis was assessed using manual processing following replicate injections of Vitis vinifera cv. Graciano wine spiked with external standards. In the present work, 411 different metabolites in Graciano Vitis vinifera red wine were identified, including primary wine metabolites such as sugars (4%), amino acids (23%), biogenic amines (4%), fatty acids (2%), and organic acids (32%) and secondary metabolites such as phenols (27%) and esters (8%). Significant differences between varieties Tempranillo and Graciano were related to the presence of fifteen specific compounds. PMID:25597799

  6. Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer

    PubMed Central

    Huan, Tao; Troyer, Dean A.; Li, Liang

    2016-01-01

    We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy. PMID:27578275

  7. 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

  8. Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli.

    PubMed

    Taymaz-Nikerel, Hilal; De Mey, Marjan; Baart, Gino J E; Maertens, Jo; Foulquié-Moreno, Maria Remedios; Charlier, Daniel; Heijnen, Joseph J; van Gulik, Walter M

    2016-04-01

    An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain. Unexpectedly the mutant had a higher energy efficiency, indicated by a much lower rate of oxygen consumption, under glucose-limited conditions, caused by the deletion of the transcription factors IclR and ArcA. Furthermore the mutant had a much lower uptake capacity for succinate (26-fold) and oxygen (17-fold under succinate excess) compared to the wild-type strain. The mutant strain produced 7.9 mmol.CmolX(-1) .h(-1) succinate during chemostat cultivation, showing that the choice of the applied genetic modifications was a successful strategy. Furthermore, the applied genetic modifications resulted in multiple large changes in metabolite levels (FBP, pyruvate, 6PG, NAD(+) /NADH ratio, α-ketogluarate) corresponding to large changes in fluxes. Compared to the wild-type a considerable flux shift occurred from the tricarboxylic acid (TCA) cycle to the oxidative part of the pentose phosphate pathway, including an inversion of the pyruvate kinase flux. The mutant responded very differently to excess of succinate, with a remarkable possible reversal of the TCA cycle. The mutant and the wild-type both showed homeostatic behaviour with respect

  9. Metabolomic analysis of breath volatile organic compounds reveals unique breathprints in children with inflammatory bowel disease: A pilot study

    PubMed Central

    Patel, Nisha; Alkhouri, Naim; Eng, Katharine; Cikach, Frank; Mahajan, Lori; Yan, Chen; Grove, David; Rome, Ellen S.; Lopez, Rocio; Dweik, Raed A.

    2014-01-01

    Background Breath testing is becoming an important diagnostic method to evaluate many disease states. In light of rising healthcare costs, is important to develop a simple non-invasive tool to potentially identify pediatric patients who need endoscopy for suspected inflammatory bowel disease (IBD). Aim The primary aim of this study was to analyze exhaled volatile organic compounds (VOCs) to evaluate for the presence of a unique breath pattern to differentiate pediatric patients with (IBD) from healthy controls. Methods A cross-sectional, single-center study included pediatric IBD patients and healthy controls (age range, 5-21 years). The diagnosis of IBD was confirmed by endoscopic, histologic, and radiographic data. Exhaled breath was collected and analyzed using a selective ion flow tube mass spectroscopy (SIFT-MS) to identify new markers or patterns of IBD. Results 117 patients (62 with IBD and 55 healthy controls) were included in the study. Linear discriminant analysis and principle component analysis of mass scanning ion peak data demonstrated 21 pre-selected VOCs correctly classify patients with IBD or as healthy controls; p < 0.0001. Multivariable logistic regression analysis further showed 3 specific VOCs (1-octene, 1-decene, (E)-2-nonene) had excellent accuracy for predicting the presence of IBD with an area under the curve (AUC) of 0.96 (95% CI: 0.93, 0.99). No significant difference in VOCs was found between patients with Crohn's disease or ulcerative colitis and no significant correlation was seen with disease activity. Conclusion This pilot data supports the hypothesis that a unique breathprint potentially exists for pediatric IBD in the exhaled metabolome. PMID:25041596

  10. Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

    PubMed Central

    Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

    2014-01-01

    Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

  11. Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: Investigation of nicotinic acid receptor agonists

    SciTech Connect

    Zgoda-Pols, Joanna R.; Chowdhury, Swapan; Wirth, Mark; Milburn, Michael V.; Alexander, Danny C.; Alton, Kevin B.

    2011-08-15

    An investigative renal toxicity study using metabolomics was conducted with a potent nicotinic acid receptor (NAR) agonist, SCH 900424. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) techniques were used to identify small molecule biomarkers of acute kidney injury (AKI) that could aid in a better mechanistic understanding of SCH 900424-induced AKI in mice. The metabolomics study revealed 3-indoxyl sulfate (3IS) as a more sensitive marker of SCH 900424-induced renal toxicity than creatinine or urea. An LC-MS assay for quantitative determination of 3IS in mouse matrices was also developed. Following treatment with SCH 900424, 3IS levels were markedly increased in murine plasma and brain, thereby potentially contributing to renal- and central nervous system (CNS)-related rapid onset of toxicities. Furthermore, significant decrease in urinary excretion of 3IS in those animals due to compromised renal function may be associated with the elevation of 3IS in plasma and brain. These data suggest that 3IS has a potential to be a marker of renal and CNS toxicities during chemically-induced AKI in mice. In addition, based on the metabolomic analysis other statistically significant plasma markers including p-cresol-sulfate and tryptophan catabolites (kynurenate, kynurenine, 3-indole-lactate) might be of toxicological importance but have not been studied in detail. This comprehensive approach that includes untargeted metabolomic and targeted bioanalytical sample analyses could be used to investigate toxicity of other compounds that pose preclinical or clinical development challenges in a pharmaceutical discovery and development. - Research Highlights: > Nicotinic acid receptor agonist, SCH 900424, caused acute kidney injury in mice. > MS-based metabolomics was conducted to identify potential small molecule markers of renal toxicity. > 3-indoxyl-sulfate was found to be as a more sensitive marker of renal toxicity than creatinine

  12. Clinical impact of human breast milk metabolomics.

    PubMed

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

    2015-12-01

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

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

    PubMed

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

    2016-07-01

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

  14. Metabolomics analysis of soy hydrolysates for the identification of productivity markers of mammalian cells for manufacturing therapeutic proteins.

    PubMed

    Richardson, Jason; Shah, Bhavana; Bondarenko, Pavel V; Bhebe, Prince; Zhang, Zhongqi; Nicklaus, Michele; Kombe, Maua C

    2015-01-01

    Soy hydrolysates are widely used as a nutrient supplement in mammalian cell culture for the production of recombinant proteins. The batch-to-batch variability of a soy hydrolysate often leads to productivity differences. This report describes our metabolomics platform, which includes a battery of LC-MS/MS modes of operation, and advanced data analysis software for automated data processing. The platform was successfully used for screening productivity markers in soy hydrolysates during the production of two therapeutic antibodies in two Chinese hamster ovary cell lines. A total of 123 soy hydrolysate batches were analyzed, from which 62 batches were used in the production runs of cell line #1 and 12 batches were used in the production runs of cell line #2. For cell line #1, out of 19 amino acids, 106 other metabolites and 4,131 peptides identified in the soy hydrolysate batches being used, several nucleosides and short hydrophobic peptides showed negative correlation with antibody titer, while ornithine, citrulline and several amino acids and organic acids correlated positively with titer. For cell line #2, only ornithine and citrulline showed strong positive correlation. When ornithine was spiked into the culture media, both cell lines demonstrated accelerated cell growth, indicating ornithine as a root cause of the performance difference. It is proposed that better soy hydrolysate performance resulted from better bacterial fermentation during the hydrolysate production. A few selected markers were used to predict the performance of other soy hydrolysate batches for cell line #1. The predicted titers agreed with the experimental values with good accuracy. PMID:25583076

  15. Metabolomic Analysis of Anti-Hypoxia and Anti-anxiety Effects of Fu Fang Jin Jing Oral Liquid

    PubMed Central

    Guan, Shuhong; Feng, Ruihong; Zhang, Hui; Liu, Qiuhong; Sun, Peng; Lin, Donghai; Zhang, Naixia; Shen, Jun

    2013-01-01

    Background Herba Rhodiolae is a traditional Chinese medicine used by the Tibetan people for treating hypoxia related diseases such as anxiety. Based on the previous work, we developed and patented an anti-anxiety herbal formula Fu Fang Jin Jing Oral Liquid (FJJOL) with Herba Rhodiolae as a chief ingredient. In this study, the anti-hypoxia and anti-anxiety effects of FJJOL in a high altitude forced-swimming mouse model with anxiety symptoms will be elucidated by NMR-based metabolomics. Methods In our experiments, the mice were divided randomly into four groups as flatland group, high altitude saline-treated group, high altitude FJJOL-treated group, and high altitude diazepam-treated group. To cause anxiety effects and hypoxic defects, a combination use of oxygen level decreasing (hypobaric cabin) and oxygen consumption increasing (exhaustive swimming) were applied to mice. After a three-day experimental handling, aqueous metabolites of mouse brain tissues were extracted and then subjected to NMR analysis. The therapeutic effects of FJJOL on the hypobaric hypoxia mice with anxiety symptoms were verified. Results Upon hypoxic exposure, both energy metabolism defects and disorders of functional metabolites in brain tissues of mice were observed. PCA, PLS-DA and OPLS-DA scatter plots revealed a clear group clustering for metabolic profiles in the hypoxia versus normoxia samples. After a three-day treatment with FJJOL, significant rescue effects on energy metabolism were detected, and levels of ATP, fumarate, malate and lactate in brain tissues of hypoxic mice recovered. Meanwhile, FJJOL also up-regulated the neurotransmitter GABA, and the improvement of anxiety symptoms was highly related to this effect. Conclusions FJJOL ameliorated hypobaric hypoxia effects by regulating energy metabolism, choline metabolism, and improving the symptoms of anxiety. The anti-anxiety therapeutic effects of FJJOL were comparable to the conventional anti-anxiety drug diazepam on the

  16. Response to weaning and dietary L-glutamine supplementation: metabolomic analysis in piglets by gas chromatography/mass spectrometry*

    PubMed Central

    Xiao, Ying-ping; Wu, Tian-xing; Hong, Qi-hua; Sun, Jiang-ming; Chen, An-guo; Yang, Cai-mei; Li, Xiao-yan

    2012-01-01

    A novel metabolomic method based on gas chromatography/mass spectrometry (GC-MS) was applied to determine the metabolites in the serum of piglets in response to weaning and dietary L-glutamine (Gln) supplementation. Thirty-six 21-d-old piglets were randomly assigned into three groups. One group continued to suckle from the sows (suckling group), whereas the other two groups were weaned and their diets were supplemented with 1% (w/w) Gln or isonitrogenous L-alanine, respectively, representing Gln group or control group. Serum samples were collected to characterize metabolites after a 7-d treatment. Results showed that twenty metabolites were down-regulated significantly (P<0.05) in control piglets compared with suckling ones. These data demonstrated that early weaning causes a wide range of metabolic changes across arginine and proline metabolism, aminosugar and nucleotide metabolism, galactose metabolism, glycerophospholipid metabolism, biosynthesis of unsaturated fatty acid, and fatty acid metabolism. Dietary Gln supplementation increased the levels of creatinine,D-xylose, 2-hydroxybutyric acid, palmitelaidic acid, and α-L-galactofuranose (P<0.05) in early weaned piglets, and were involved in the arginine and proline metabolism, carbohydrate metabolism, and fatty acid metabolism. A leave-one-out cross-validation of random forest analysis indicated that creatinine was the most important metabolite among the three groups. Notably, the concentration of creatinine in control piglets was decreased (P=0.00001) compared to the suckling piglets, and increased (P=0.0003) in Gln-supplemented piglets. A correlation network for weaned and suckling piglets revealed that early weaning changed the metabolic pathways, leading to the abnormality of carbohydrate metabolism, amino acid metabolism, and lipid metabolism, which could be partially improved by dietary Gln supplementation. These findings provide fresh insight into the complex metabolic changes in response to early

  17. Comparative metabolomic analysis reveals a reactive oxygen species-dominated dynamic model underlying chilling environment adaptation and tolerance in rice.

    PubMed

    Zhang, Jingyu; Luo, Wei; Zhao, Yuan; Xu, Yunyuan; Song, Shuhui; Chong, Kang

    2016-09-01

    Cold, a major environmental stress for plants, has been studied intensively for decades. Its response system has been revealed, especially at the transcriptional level. The mechanisms underlying recovery growth and environmental adaptation, however, remain unknown. Taking advantage of a naturally existing system, two subspecies of Asian cultivated rice (Oryza sativa) with significant divergence in chilling tolerance, we analyzed representative japonica and indica varieties, Nipponbare and 93-11, using comparative metabolomic analysis at six time points covering chilling treatment and recovery. In total, 223 known metabolites were detected. During chilling treatment, significant biochemical changes were centered on antioxidation. During recovery, a wide-ranging chilling response was observed. Large-scale amino acid accumulation occurred, consistent with the appearance of chilling injury. At the mid-treatment stage, the accumulation of antioxidation-related compounds appeared earlier in Nipponbare than in 93-11, consistent with the higher reactive oxygen species (ROS) levels in japonica vs indica varieties. A significant contribution of ROS-mediated gene regulation, rather than the C-repeat binding factor/dehydration-responsive-element binding factor (CBF/DREB) regulon, to the more vigorous transcriptional stress response in Nipponbare was revealed by RNA-seq. Accordingly, during recovery, the induction of stress-tolerant-related metabolites was more active in the chilling-tolerant variety Nipponbare. Senescence-related compounds accumulated only in the chilling-sensitive variety 93-11. Our study uncovers the dynamic metabolic models underlying chilling response and recovery, and reveals a ROS-dominated rice adaptation mechanism to low-temperature environments. PMID:27198693

  18. Of Monkeys and Men: A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

    PubMed Central

    Saccenti, Edoardo; Tenori, Leonardo; Verbruggen, Paul; Timmerman, Marieke E.; Bouwman, Jildau; van der Greef, Jan; Luchinat, Claudio; Smilde, Age K.

    2014-01-01

    Background Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the variation of intrinsic (such as (epi)genetic variation, gut microbiota, etc.) and extrinsic factors (such as dietary habits, life-style and environmental conditions). Understanding the relative contributions of these factors is essential to establish the robustness of the healthy individual metabolic phenotype. Methods To assess the relative contribution of intrinsic and extrinsic factors we compared multilevel analysis results obtained from subjects of Homo sapiens and Macaca mulatta, the latter kept in a controlled environment with a standardized diet by making use of previously published data and results. Results We observed similarities for the two species and found the diversity of urinary metabolic phenotypes as identified by nuclear magnetic resonance (NMR) spectroscopy could be ascribed to the complex interplay of intrinsic factors and, to a lesser extent, of extrinsic factors in particular minimizing the role played by diet in shaping the metabolic phenotype. Moreover, we show that despite the standardization of diet as the most relevant extrinsic factor, a clear individual and discriminative metabolic fingerprint also exists for monkeys. We investigate the metabolic phenotype both at the static (i.e., at the level of the average metabolite concentration) and at the dynamic level (i.e., concerning their variation over time), and we show that these two components sum up to the overall phenotype with different relative contributions of about 1/4 and 3/4, respectively, for both species. Finally, we show that the great degree diversity observed in the urinary metabolic phenotype of both species can be attributed to differences in both the static and dynamic part of

  19. Combined stable isotope, proteomic, metabolomics, and spatial specific analysis to track carbon flow through a hypersaline phototrophic microbial mat

    NASA Astrophysics Data System (ADS)

    Moran, J.; Cory, A.; Riha, K. M.; Huang, E. L.; Gritsenko, M. A.; Kim, Y. M.; Metz, T. O.; Lipton, M. S.

    2014-12-01

    Tracking labeled substrates through microbial mat systems can help elucidate carbon dynamics, species interactions, and niche partitioning, but the inherent microbial complexity of these systems makes them difficult to probe with single analytical techniques. Here we use a combination of different tools to track three labeled substrates through a benthic phototrophic mat from Hot Lake. Hot Lake is a hypersaline, meromictic lake located in an endorheic basin in north-central Washington which, despite extreme salinity and seasonal water temperatures (> 55 ˚C), hosts dense, phototrophic benthic microbial mats. Cyanobacteria are the dominant CO2-fixing organisms in the system and we seek to understand the spatial and metabolic controls on how the carbon initially fixed by mat cyanobacteria is transferred to associated heterotrophic populations spread throughout the mat strata. We performed ex situ incubations over a complete diel cycle with 13C labeled bicarbonate, acetate, and glucose. Traditional elemental analysis IRMS provided an estimate of bulk label uptake to total biomass and showed that both bicarbonate and acetate were incorporated only during daylight while glucose uptake was nearly constant through the cycle. Spatially resolved isotope analysis using laser ablation IRMS showed distinctive patterns between the different substrates with bicarbonate having highest uptake in the top third of the mat, acetate uptake focused near the mat's center, and glucose showing similar uptake at all mat depths. Proteomic analysis showed a longer lag in substrate conversion to protein than to biomass and a distinct spike in the number of labeled peptides in the bicarbonate incubation near the end of the diel cycle. Proteomic analysis confirmed that photosynthetic organisms showed the highest rates of label conversion to protein but heterotrophic organisms also incorporated label into their peptides. Metabolomic analysis demonstrated the high conversion of organic substrates

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

    PubMed

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

    2015-01-01

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

  1. Metabolomic Fingerprinting: Challenges and Opportunities

    PubMed Central

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

    2014-01-01

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

  2. 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

  3. Quantitative analysis of amino acids and acylcarnitines combined with untargeted metabolomics using ultra-high performance liquid chromatography and quadrupole time-of-flight mass spectrometry.

    PubMed

    Roy, Cynthia; Tremblay, Pierre-Yves; Bienvenu, Jean-François; Ayotte, Pierre

    2016-08-01

    Metabolomics is an "omic" technique being increasingly used in epidemiological and clinical studies. We developed a method combining untargeted metabolomics with the quantitative determination of eight amino acids (AA) and eight acylcarnitines (AC) in plasma using ultra-high pressure liquid chromatography (UHPLC), electrospray ionization (ESI) and quadrupole time-of-flight mass spectrometry (QTOFMS). Separation of metabolites is performed by ion-pair reverse phase UHPLC using a HSS T3 column (2.1×100mm, 100Å, 1.8μm particle size) and formic acid-ammonium acetate-heptafluorobutyric acid in water and formic acid-ammonium acetate in methanol as mobile phases. Metabolite identification and quantification are achieved using a QTOFMS operating in ESI-positive and full-scan mode along with MS(E) acquisition of fragmentation patterns. Targeted metabolites are quantified using the appropriate labeled standards and include branched-chain AA (leucine, isoleucine, valine), aromatic AA (phenylalanine, tyrosine) as well as acetylcarnitine and propionylcarnitine, which have been identified as biomarkers of future cardiometabolic disease risk. The inter-day precision (relative standard deviation) for the targeted method was <15% for all but one metabolite and accuracy (bias) of amino acids ranged from 0.5% to 13.9% using SRM 1950 as the external standard. Untargeted metabolomics in 30 plasma samples from the general Canadian population revealed 5018 features, of which 48 metabolites were identified using the MZmine 2.19 software including 23 by our in-house library that comprises 671 annotated metabolites. SRM 1950 analysis revealed 11,684 features, among which 154 metabolites were identified. Our method is currently applied in several epidemiological studies to better characterize cardiometabolic diseases and identify new biomarkers for disease prevention. PMID:27240302

  4. Weighted correlation network analysis (WGCNA) applied to the tomato fruit metabolome

    Technology Transfer Automated Retrieval System (TEKTRAN)

    One of the challenges for systems biology approaches is that hundreds to thousands of variables are often measured for treatments with low replication, thus creating a multiple testing problem. Principal component analysis (PCA) and weighted correlation network analysis (WGCNA) are two complementary...

  5. Metabolomic assessment of embryo viability.

    PubMed

    Uyar, Asli; Seli, Emre

    2014-03-01

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

  6. Metabolome Analysis of Biosynthetic Mutants Reveals a Diversity of Metabolic Changes and Allows Identification of a Large Number of New Compounds in Arabidopsis1[W][OA

    PubMed Central

    Böttcher, Christoph; von Roepenack-Lahaye, Edda; Schmidt, Jürgen; Schmotz, Constanze; Neumann, Steffen; Scheel, Dierk; Clemens, Stephan

    2008-01-01

    Metabolomics is facing a major challenge: the lack of knowledge about metabolites present in a given biological system. Thus, large-scale discovery of metabolites is considered an essential step toward a better understanding of plant metabolism. We show here that the application of a metabolomics approach generating structural information for the analysis of Arabidopsis (Arabidopsis thaliana) mutants allows the efficient cataloging of metabolites. Fifty-six percent of the features that showed significant differences in abundance between seeds of wild-type, transparent testa4, and transparent testa5 plants could be annotated. Seventy-five compounds were structurally characterized, 21 of which could be identified. About 40 compounds had not been known from Arabidopsis before. Also, the high-resolution analysis revealed an unanticipated expansion of metabolic conversions upstream of biosynthetic blocks. Deficiency in chalcone synthase results in the increased seed-specific biosynthesis of a range of phenolic choline esters. Similarly, a lack of chalcone isomerase activity leads to the accumulation of various naringenin chalcone derivatives. Furthermore, our data provide insight into the connection between p-coumaroyl-coenzyme A-dependent pathways. Lack of flavonoid biosynthesis results in elevated synthesis not only of p-coumarate-derived choline esters but also of sinapate-derived metabolites. However, sinapoylcholine is not the only accumulating end product. Instead, we observed specific and sophisticated changes in the complex pattern of sinapate derivatives. PMID:18552234

  7. Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis

    PubMed Central

    Bielecka, Monika; Watanabe, Mutsumi; Morcuende, Rosa; Scheible, Wolf-Rüdiger; Hawkesford, Malcolm J.; Hesse, Holger; Hoefgen, Rainer

    2015-01-01

    Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using ‘omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes. PMID:25674096

  8. Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis

    PubMed Central

    Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

    2016-01-01

    In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as “responding biomarkers” by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress. PMID:27171077

  9. Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

    PubMed

    Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

    2016-01-01

    In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress. PMID:27171077

  10. Metabolomics Data Normalization with EigenMS

    PubMed Central

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

    2014-01-01

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