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Sample records for isotope-resolved metabolomic analysis

  1. Stable Isotope Resolved Metabolomics Analysis of Ribonucleotide and RNA Metabolism in Human Lung Cancer Cells.

    PubMed

    Fan, Teresa W-M; Tan, Jinlian; McKinney, Martin M; Lane, Andrew N

    2012-06-01

    We have developed a simple NMR-based method to determine the turnover of nucleotides and incorporation into RNA by stable isotope resolved metabolomics (SIRM) in A549 lung cancer cells. This method requires no chemical degradation of the nucleotides or chromatography. During cell growth, the free ribonucleotide pool is rapidly replaced by de novo synthesized nucleotides. Using [U-(13)C]-glucose and [U-(13)C,(15)N]-glutamine as tracers, we showed that virtually all of the carbons in the nucleotide riboses were derived from glucose, whereas glutamine was preferentially utilized over glucose for pyrimidine ring biosynthesis, via the synthesis of Asp through the Krebs cycle. Incorporation of the glutamine amido nitrogen into the N3 and N9 positions of the purine rings was also demonstrated by proton-detected (15)N NMR. The incorporation of (13)C from glucose into total RNA was measured and shown to be a major sink for the nucleotides during cell proliferation. This method was applied to determine the metabolic action of an anti-cancer selenium agent (methylseleninic acid or MSA) on A549 cells. We found that MSA inhibited nucleotide turnover and incorporation into RNA, implicating an important role of nucleotide metabolism in the toxic action of MSA on cancer cells.

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

    PubMed Central

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

    2012-01-01

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

  3. 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

  4. Probing the metabolic phenotype of breast cancer cells by multiple tracer stable isotope resolved metabolomics.

    PubMed

    Lane, Andrew N; Tan, Julie; Wang, Yali; Yan, Jun; Higashi, Richard M; Fan, Teresa W-M

    2017-02-02

    Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using (13)C6-glucose, (13)C-1+2-glucose, (13)C5,(15)N2-Gln, (13)C3-glycerol, and (13)C8-octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment.

  5. Stable isotope resolved metabolomics of lung cancer in a SCID mouse model.

    PubMed

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

    2011-06-01

    We have determined the time course of [U-(13)C]-glucose utilization and transformations in SCID mice via bolus injection of the tracer in the tail vein. Incorporation of (13)C into metabolites extracted from mouse blood plasma and several tissues (lung, heart, brain, liver, kidney, and skeletal muscle) were profiled by NMR and GC-MS, which helped ascertain optimal sampling times for different target tissues. We found that the time for overall optimal (13)C incorporation into tissue was 15-20 min but with substantial differences in (13)C labeling patterns of various organs that reflected their specific metabolism. Using this stable isotope resolved metabolomics (SIRM) approach, we have compared the (13)C metabolite profile of the lungs in the same mouse with or without an orthotopic lung tumor xenograft established from human PC14PE6 lung adenocarcinoma cells. The (13)C metabolite profile shows considerable differences in [U-(13)C]-glucose transformations between the two lung tissues, demonstrating the feasibility of applying SIRM to investigate metabolic networks of human cancer xenograft in the mouse model.

  6. Stable isotope resolved metabolomics revealed the role of anabolic and catabolic processes in glyphosate-induced amino acid accumulation in Amaranthus palmeri biotypes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using stable isotope resolved metabolomics (SIRM), we characterized the role of anabolic (de novo synthesis) vs catabolic (protein catalysis) processes contributing to free amino acid pools in glyphosate susceptible (S) and resistant (R) Amaranthus palmeri biotypes. Following exposure to glyphosate ...

  7. 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

  8. Error Analysis and Propagation in Metabolomics Data Analysis.

    PubMed

    Moseley, Hunter N B

    2013-01-01

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

  9. [Metabolomics analysis of taxadiene producing yeasts].

    PubMed

    Yan, Huifang; Ding, Mingzhu; Yuan, Yingjin

    2014-02-01

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

  10. Metabolomic analysis of sun exposed skin.

    PubMed

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

    2013-08-01

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

  11. 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.

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

    PubMed

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

    2015-06-02

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

  13. Integrated sampling procedure for metabolome analysis.

    PubMed

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

    2006-01-01

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

  14. NMR Metabolomics Analysis of Parkinson's Disease

    PubMed Central

    Lei, Shulei; Powers, Robert

    2015-01-01

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

  15. 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

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

    PubMed

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

    2016-01-04

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

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

    PubMed

    Zhang, Bo; Powers, Robert

    2012-06-01

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

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

    PubMed

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

    2009-03-01

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

  19. 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

  20. 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

  1. Microbial Metabolomics

    PubMed Central

    Tang, Jane

    2011-01-01

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

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

    PubMed

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

    2012-07-15

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    Carneiro, Sónia; Pereira, Rui; Rocha, Isabel

    2014-01-01

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

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

    PubMed

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

    2013-11-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2017-01-01

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

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

    PubMed Central

    Grapov, Dmitry; Barupal, Dinesh Kumar

    2017-01-01

    Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other ‘omic’ families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license. PMID:28141874

  9. Flux analysis and metabolomics for systematic metabolic engineering of microorganisms.

    PubMed

    Toya, Yoshihiro; Shimizu, Hiroshi

    2013-11-01

    Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and (13)C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.

  10. Isotopic ratio outlier analysis global metabolomics of Caenorhabditis elegans.

    PubMed

    Stupp, Gregory S; Clendinen, Chaevien S; Ajredini, Ramadan; Szewc, Mark A; Garrett, Timothy; Menger, Robert F; Yost, Richard A; Beecher, Chris; Edison, Arthur S

    2013-12-17

    We demonstrate the global metabolic analysis of Caenorhabditis elegans stress responses using a mass-spectrometry-based technique called isotopic ratio outlier analysis (IROA). In an IROA protocol, control and experimental samples are isotopically labeled with 95 and 5% (13)C, and the two sample populations are mixed together for uniform extraction, sample preparation, and LC-MS analysis. This labeling strategy provides several advantages over conventional approaches: (1) compounds arising from biosynthesis are easily distinguished from artifacts, (2) errors from sample extraction and preparation are minimized because the control and experiment are combined into a single sample, (3) measurement of both the molecular weight and the exact number of carbon atoms in each molecule provides extremely accurate molecular formulas, and (4) relative concentrations of all metabolites are easily determined. A heat-shock perturbation was conducted on C. elegans to demonstrate this approach. We identified many compounds that significantly changed upon heat shock, including several from the purine metabolism pathway. The metabolomic response information by IROA may be interpreted in the context of a wealth of genetic and proteomic information available for C. elegans . Furthermore, the IROA protocol can be applied to any organism that can be isotopically labeled, making it a powerful new tool in a global metabolomics pipeline.

  11. 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

  12. 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

  13. Analysis of urinary metabolites for metabolomic study by pressurized CEC.

    PubMed

    Xie, Guoxiang; Su, Mingming; Li, Peng; Gu, Xue; Yan, Chao; Qiu, Yunping; Li, Houkai; Jia, Wei

    2007-12-01

    A new approach for the metabolomic study of urinary samples using pressurized CEC (pCEC) with gradient elution is proposed as an alternative chromatographic separation tool with higher degree of resolution, selectivity, sensitivity, and efficiency. The pCEC separation of urinary samples was performed on a RP column packed with C(18), 5 microm particles with an ACN/water mobile phase containing TFA. The effects of the acid modifiers, applied voltage, mobile phase, and detection wavelength were systematically evaluated using eight spiked standards, as well as urine samples. A typical analytical trial of urine samples from Sprague Dawley (S.D.) rats exposed to high-energy diet was carried out following sample pretreatment. Significant differences in urinary metabolic profiles were observed between the high energy diet-induced obesity rats and the healthy control rats at the 6th wk postdose. Multivariate statistical analysis revealed the differential metabolites in response to the diet, which were partially validated with the putative standards. This work suggests that such a pCEC-based separation and analysis method may provide a new and cost-effective platform for metabolomic study uniquely positioned between the conventional chromatographic tools such as HPLC, and hyphenated analytical techniques such as LC-MS.

  14. Mass-based metabolomic analysis of soybean sprouts during germination.

    PubMed

    Gu, Eun-Ji; Kim, Dong Wook; Jang, Gwang-Ju; Song, Seong Hwa; Lee, Jae-In; Lee, Sang Bong; Kim, Bo-Min; Cho, Yeongrae; Lee, Hyeon-Jeong; Kim, Hyun-Jin

    2017-02-15

    We investigated the metabolite profile of soybean sprouts at 0, 1, 2, 3, and 4days after germination using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-MS (LC-MS) to understand the relationship between germination and nutritional quality. Data were analyzed by partial least squares-discriminant analysis (PLS-DA), and sprout samples were separated successfully using their PLS-DA scores. Fifty-eight metabolites, including macromolecular derivatives related to energy production, amino acids, myo-inositol metabolites, phytosterols, antioxidants, isoflavones, and soyasaponins, contributed to the separation. Amino acids, myo-inositol metabolites, isoflavone aglycones, B soyasaponins, antioxidants, and phytosterols, associated with health benefits and/or taste quality, increased with germination time while isoflavone glycosides and DDMP soyasaponins decreased. Based on these metabolites, the metabolomic pathway associated with energy production in soybean sprouts is suggested. Our data suggest that sprouting is a useful processing step to improve soybean nutritional quality, and metabolomic analysis is useful in understanding nutritional change during sprouting.

  15. AN UNTARGETED METABOLOMICS ANALYSIS OF ANTIPSYCHOTIC USE IN BIPOLAR DISORDER

    PubMed Central

    Burghardt, Kyle J.; Evans, Simon J.; Wiese, Kristen M.; Ellingrod, Vicki L.

    2015-01-01

    Background Second generation antipsychotic (SGA) use in bipolar disorder is common and has proven effective in short-term trials. There continues to be a lack of understanding of the mechanisms underlying many of their positive and negative effects in bipolar disorder. This study aimed to describe the metabolite profiles of bipolar subjects treated with SGAs by comparing to metabolite profiles of bipolar subjects treated with lithium, and schizophrenia subjects treated with SGAs. Methods Cross-sectional, fasting untargeted serum metabolomic profiling was conducted in 82 subjects diagnosed with bipolar I disorder (n=30 on SGAs and n=32 on lithium) or schizophrenia (n=20). Metabolomic profiles of bipolar subjects treated with SGAs were compared to bipolar subjects treated with lithium and schizophrenia subjects treated with SGAs using multivariate methods. Results Partial lease square discriminant analysis (PLS-DA) plots showed separation between bipolar subjects treated with SGAs, bipolar subjects treated with lithium, or schizophrenia subjects treated with SGAs. Top influential metabolite features were associated with several pathways including that of polyunsaturated fatty acids, pyruvate, glucose and branched chain amino acids. Conclusions The findings from this study require further validation in pre and post treated bipolar and schizophrenia subjects, but suggest that the pharmacometabolome may be diagnosis specific. PMID:26314700

  16. Amniotic Fluid Metabolomic Analysis in Spontaneous Preterm Birth

    PubMed Central

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

    2014-01-01

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

  17. MetaboAnalyst: a web server for metabolomic data analysis and interpretation

    PubMed Central

    Xia, Jianguo; Psychogios, Nick; Young, Nelson; Wishart, David S.

    2009-01-01

    Metabolomics is a newly emerging field of ‘omics’ research that is concerned with characterizing large numbers of metabolites using NMR, chromatography and mass spectrometry. It is frequently used in biomarker identification and the metabolic profiling of cells, tissues or organisms. The data processing challenges in metabolomics are quite unique and often require specialized (or expensive) data analysis software and a detailed knowledge of cheminformatics, bioinformatics and statistics. In an effort to simplify metabolomic data analysis while at the same time improving user accessibility, we have developed a freely accessible, easy-to-use web server for metabolomic data analysis called MetaboAnalyst. Fundamentally, MetaboAnalyst is a web-based metabolomic data processing tool not unlike many of today's web-based microarray analysis packages. It accepts a variety of input data (NMR peak lists, binned spectra, MS peak lists, compound/concentration data) in a wide variety of formats. It also offers a number of options for metabolomic data processing, data normalization, multivariate statistical analysis, graphing, metabolite identification and pathway mapping. In particular, MetaboAnalyst supports such techniques as: fold change analysis, t-tests, PCA, PLS-DA, hierarchical clustering and a number of more sophisticated statistical or machine learning methods. It also employs a large library of reference spectra to facilitate compound identification from most kinds of input spectra. MetaboAnalyst guides users through a step-by-step analysis pipeline using a variety of menus, information hyperlinks and check boxes. Upon completion, the server generates a detailed report describing each method used, embedded with graphical and tabular outputs. MetaboAnalyst is capable of handling most kinds of metabolomic data and was designed to perform most of the common kinds of metabolomic data analyses. MetaboAnalyst is accessible at http://www.metaboanalyst.ca PMID:19429898

  18. 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

  19. Metabolomics in food science.

    PubMed

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

    2012-01-01

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

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

    PubMed

    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.

  1. 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

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

    PubMed

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

    2015-03-10

    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.

  3. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    PubMed

    Xia, Jianguo; Wishart, David S

    2016-09-07

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

  4. Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration.

    PubMed

    Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

    2016-04-12

    Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCore(TM), MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration.

  5. 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...

  6. Metabolomics analysis identifies different metabotypes of asthma severity.

    PubMed

    Reinke, Stacey N; Gallart-Ayala, Héctor; Gómez, Cristina; Checa, Antonio; Fauland, Alexander; Naz, Shama; Kamleh, Muhammad Anas; Djukanović, Ratko; Hinks, Timothy S C; Wheelock, Craig E

    2017-03-01

    In this study, we sought to determine whether asthma has a metabolic profile and whether this profile is related to disease severity.We characterised the serum from 22 healthy individuals and 54 asthmatics (12 mild, 20 moderate, 22 severe) using liquid chromatography-high-resolution mass spectrometry-based metabolomics. Selected metabolites were confirmed by targeted mass spectrometry assays of eicosanoids, sphingolipids and free fatty acids.We conclusively identified 66 metabolites; 15 were significantly altered with asthma (p≤0.05). Levels of dehydroepiandrosterone sulfate, cortisone, cortisol, prolylhydroxyproline, pipecolate and N-palmitoyltaurine correlated significantly (p<0.05) with inhaled corticosteroid dose, and were further shifted in individuals treated with oral corticosteroids. Oleoylethanolamide increased with asthma severity independently of steroid treatment (p<0.001). Multivariate analysis revealed two patterns: 1) a mean difference between controls and patients with mild asthma (p=0.025), and 2) a mean difference between patients with severe asthma and all other groups (p=1.7×10(-4)). Metabolic shifts in mild asthma, relative to controls, were associated with exogenous metabolites (e.g. dietary lipids), while those in moderate and severe asthma (e.g. oleoylethanolamide, sphingosine-1-phosphate, N-palmitoyltaurine) were postulated to be involved in activating the transient receptor potential vanilloid type 1 (TRPV1) receptor, driving TRPV1-dependent pathogenesis in asthma.Our findings suggest that asthma is characterised by a modest systemic metabolic shift in a disease severity-dependent manner, and that steroid treatment significantly affects metabolism.

  7. Metabolome analysis of gram-positive bacteria such as Staphylococcus aureus by GC-MS and LC-MS.

    PubMed

    Liebeke, Manuel; Dörries, Kirsten; Meyer, Hanna; Lalk, Michael

    2012-01-01

    The field of metabolomics has become increasingly important in the context of functional genomics. Together with other "omics" data, the investigation of the metabolome is an essential part of systems biology. Beside the analysis of human and animal biofluids, the investigation of the microbial physiology by methods of metabolomics has gained increased attention. For example, the analysis of metabolic processes during growth or virulence factor expression is crucially important to understand pathogenesis of bacteria. Common bioanalytical techniques for metabolome analysis include liquid and gas chromatographic methods coupled to mass spectrometry (LC-MS and GC-MS) and spectroscopic approaches such as NMR. In order to achieve metabolome data representing the physiological status of a microorganism, well-verified protocols for sampling and analysis are necessary. This chapter presents a detailed protocol for metabolome analysis of the Gram-positive bacterium Staphylococcus aureus. A detailed manual for cell sampling and metabolite extraction is given, followed by the description of the analytical procedures GC-MS and LC-MS. The advantages and limitations of each experimental setup are discussed. Here, a guideline specified for S. aureus metabolomics and information for important protocol steps are presented, to avoid common pitfalls in microbial metabolome analysis.

  8. Metabolomic mechanisms of gypenoside against liver fibrosis in rats: An integrative analysis of proteomics and metabolomics data

    PubMed Central

    Song, Ya-Nan; Dong, Shu; Wei, Bin; Liu, Ping; Zhang, Yong-Yu; Su, Shi-Bing

    2017-01-01

    Aims To investigate mechanisms and altered pathways of gypenoside against carbon tetrachloride (CCl4)-induced liver fibrosis based on integrative analysis of proteomics and metabolomics data. Methods CCl4-induced liver fibrosis rats were administrated gypenoside. The anti-fibrosis effects were evaluated by histomorphology and liver hydroxyproline (Hyp) content. Protein profiling and metabolite profiling of rats liver tissues were examined by isobaric tags for relative and absolute quantitation (iTRAQ) approach and gas chromatography-mass spectrometer (GC-MS) technology. Altered pathways and pivotal proteins and metabolites were searched by integrative analysis of proteomics and metabolomics data. The levels of some key proteins in altered pathways were determined by western blot. Results Histopathological changes and Hyp content in gypenoside group had significant improvements (P<0.05). Compared to liver fibrosis model group, we found 301 up-regulated and 296 down-regulated proteins, and 9 up-regulated and 8 down-regulated metabolites in gypenoside group. According to integrative analysis, some important pathways were found, including glycolysis or gluconeogenesis, fructose and mannose metabolism, glycine, serine and threonine metabolism, lysine degradation, arginine and proline metabolism, glutathione metabolism, and sulfur metabolism. Furthermore, the levels of ALDH1B1, ALDH2 and ALDH7A1 were found increased and restored to normal levels after gypenoside treated (P<0.05). Conclusions Gypenoside inhibited CCl4-induced liver fibrosis, which may be involved in the alteration of glycolysis metabolism and the protection against the damage of aldehydes and lipid peroxidation by up-regulating ALDH. PMID:28291813

  9. 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.

  10. Metabolomic analysis of normal and sickle cell erythrocytes.

    PubMed

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

    2010-09-01

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

  11. 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...

  12. Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE).

    PubMed

    Kuligowski, Julia; Pérez-Guaita, David; Sánchez-Illana, Ángel; León-González, Zacarías; de la Guardia, Miguel; Vento, Máximo; Lock, Eric F; Quintás, Guillermo

    2015-07-07

    Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures across multiple sources is challenging due to the high variable to sample ratios and differences in intensity and noise range. In this work we apply a recent method, Joint and Individual Variation Explained (JIVE), for the integrated unsupervised analysis of metabolomic profiles from multiple data sources. This method separates the shared patterns among data sources (i.e. the joint structure) from the individual structure of each data source that is unrelated to the joint structure. Two examples are described to show the applicability of JIVE for the simultaneous analysis of multi-source data using: (i) plasma samples subjected to different analytical techniques, sample treatment and measurement conditions; and (ii) plasma and urine samples subjected to liquid chromatography-mass spectrometry measured using two ionization conditions.

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

    DOE PAGES

    Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; ...

    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

  14. Metabolomic Analysis of Mouse Embryonic Fibroblast Cells in Response to Autophagy Induced by Acute Starvation

    PubMed Central

    Shen, Sensen; Weng, Rui; Li, Linnan; Xu, Xinyuan; Bai, Yu; Liu, Huwei

    2016-01-01

    Autophagy-related protein 7 (Atg7) is essential in the formation of the autophagophore and is indispensable for autophagy induction. Autophagy will exist in lower level or even be blocked in cells without Atg7. Even though the possible signaling pathways of Atg7 have been proposed, the metabolomic responses under acute starvation in cells with and without Atg7 have not been elucidated. This study therefore was designed and aimed to reveal the metabolomics of Atg7-dependent autophagy through metabolomic analysis of Atg7−/− mouse embryonic fibroblast cells (MEFs) and wild-type MEFs along with the starvation time. 30 significantly altered metabolites were identified in response to nutrient stress, which were mainly associated with amino acid, energy, carbohydrate, and lipid metabolism. For the wild-type MEFs, the induction of autophagy protected cell survival with some up-regulated lipids during the first two hours’ starvation, while the subsequent apoptosis resulted in the decrease of cell viability after four hours’ starvation. For the Atg7−/− MEFs, apoptosis perhaps led to the deactivation of tricarboxylic acid (TCA) cycle due to the lack of autophagy, which resulted in the immediate drop of cellular viability under starvation. These results contributed to the metabolomic study and provided new insights into the mechanism associated with Atg7-dependent autophagy. PMID:27703171

  15. 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

  16. 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

  17. Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based Metabolomics

    PubMed Central

    2017-01-01

    As mass spectrometry-based metabolomics becomes more widely used in biomedical research, it is important to revisit existing data analysis paradigms. Existing data preprocessing efforts have largely focused on methods which start by extracting features separately from each sample, followed by a subsequent attempt to group features across samples to facilitate comparisons. We show that this preprocessing approach leads to unnecessary variability in peak quantifications that adversely impacts downstream analysis. We present a new method, bakedpi, for the preprocessing of both centroid and profile mode metabolomics data that relies on an intensity-weighted bivariate kernel density estimation on a pooling of all samples to detect peaks. This new method reduces this unnecessary quantification variability and increases power in downstream differential analysis. PMID:28221771

  18. 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.

  19. Meta-analysis of global metabolomic data identifies metabolites associated with life-span extension.

    PubMed

    Patti, Gary J; Tautenhahn, Ralf; Johannsen, Darcy; Kalisiak, Ewa; Ravussin, Eric; Brüning, Jens C; Dillin, Andrew; Siuzdak, Gary

    2014-08-01

    The manipulation of distinct signaling pathways and transcription factors has been shown to influence life span in a cell-non-autonomous manner in multicellular model organisms such as Caenorhabditis elegans. These data suggest that coordination of whole-organism aging involves endocrine signaling, however, the molecular identities of such signals have not yet been determined and their potential relevance in humans is unknown. Here we describe a novel metabolomic approach to identify molecules directly associated with extended life span in C. elegans that represent candidate compounds for age-related endocrine signals. To identify metabolic perturbations directly linked to longevity, we developed metabolomic software for meta-analysis that enabled intelligent comparisons of multiple different mutants. Simple pairwise comparisons of long-lived glp-1, daf-2, and isp-1 mutants to their respective controls resulted in more than 11,000 dysregulated metabolite features of statistical significance. By using meta-analysis, we were able to reduce this number to six compounds most likely to be associated with life-span extension. Mass spectrometry-based imaging studies suggested that these metabolites might be localized to C. elegans muscle. We extended the metabolomic analysis to humans by comparing quadricep muscle tissue from young and old individuals and found that two of the same compounds associated with longevity in worms were also altered in human muscle with age. These findings provide candidate compounds that may serve as age-related endocrine signals and implicate muscle as a potential tissue regulating their levels in humans.

  20. Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

    PubMed Central

    Lutz, Norbert W.; Béraud, Evelyne; Cozzone, Patrick J.

    2014-01-01

    Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor

  1. Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells

    PubMed Central

    Peterson, Amanda L.; Walker, Adam K.; Sloan, Erica K.; Creek, Darren J.

    2016-01-01

    Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions. PMID:27669323

  2. Comparative analysis of the volatile metabolomes of Pseudomonas aeruginosa clinical isolates.

    PubMed

    Bean, Heather D; Rees, Christiaan A; Hill, Jane E

    2016-11-21

    Pseudomonas aeruginosa is a nearly ubiquitous Gram-negative organism, well known to occupy a multitude of environmental niches and cause human infections at a variety of bodily sites, due to its metabolic flexibility, secondary to extensive genetic heterogeneity at the species level. Because of its dynamic metabolism and clinical importance, we sought to perform a comparative analysis on the volatile metabolome (the 'volatilome') produced by P. aeruginosa clinical isolates. In this study, we analyzed the headspace volatile molecules of 24 P. aeruginosa clinical isolates grown in vitro, using 2D gas chromatography time-of-flight mass spectrometry (GC  ×  GC-TOFMS). We identified 391 non-redundant compounds that we associate with the growth and metabolism of P. aeruginosa (the 'pan-volatilome'). Of these, 70 were produced by all 24 isolates (the 'core volatilome'), 52 by only a single isolate, and the remaining 269 volatile molecules by a subset. Sixty-five of the detected compounds could be assigned putative compound identifications, of which 43 had not previously been associated with P. aeruginosa. Using the accessory volatile molecules, we determined the inter-strain variation in the metabolomes of these isolates, clustering strains by their metabotypes. Assessing the extent of metabolomic diversity in P. aeruginosa through an analysis of the volatile molecules that it produces is a critical next step in the identification of novel diagnostic or prognostic biomarkers.

  3. 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

  4. 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.

  5. 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

  6. Metabolomic patterns associated to QTc interval in shiftworkers: an explorative analysis

    PubMed Central

    Campagna, Marcello; Locci, Emanuela; Piras, Roberto; Noto, Antonio; Lecca, Luigi Isaia; Pilia, Ilaria; Cocco, Pierluigi; d’Aloja, Ernesto; Scano, Paola

    2016-01-01

    Abstract Objectives: 1H NMR-metabolomic approach was used to investigate QTc interval correlation with plasma metabolic profiles in shiftworkers. Methods: Socio-demographic data, electrocardiographic QTc interval and plasma metabolic profiles from 32 male shiftworkers, were correlated by multivariate regression analysis. Results: We found a positive correlation between QTc interval values, body mass index, glycemia and lactate level and a negative correlation between QTc interval and both pyroglutamate and 3-hydroxybutyrate plasma level. Conclusions: Our analysis provides evidence of the association between clinical, metabolic profiles and QTc interval values. This could be used to identify markers of early effects and/or susceptibility in shiftworkers. PMID:27121294

  7. High-resolution quantitative metabolome analysis of urine by automated flow injection NMR.

    PubMed

    Da Silva, Laeticia; Godejohann, Markus; Martin, François-Pierre J; Collino, Sebastiano; Bürkle, Alexander; Moreno-Villanueva, María; Bernhardt, Jürgen; Toussaint, Olivier; Grubeck-Loebenstein, Beatrix; Gonos, Efstathios S; Sikora, Ewa; Grune, Tilman; Breusing, Nicolle; Franceschi, Claudio; Hervonen, Antti; Spraul, Manfred; Moco, Sofia

    2013-06-18

    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) (1)H 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.

  8. 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

  9. 1H-NMR analysis provides a metabolomic profile of patients with multiple sclerosis

    PubMed Central

    Cocco, Eleonora; Murgia, Federica; Lorefice, Lorena; Barberini, Luigi; Poddighe, Simone; Frau, Jessica; Fenu, Giuseppe; Coghe, Giancarlo; Murru, Maria Rita; Murru, Raffaele; Del Carratore, Francesco; Atzori, Luigi

    2015-01-01

    Objective: To investigate the metabolomic profiles of patients with multiple sclerosis (MS) and to define the metabolic pathways potentially related to MS pathogenesis. Methods: Plasma samples from 73 patients with MS (therapy-free for at least 90 days) and 88 healthy controls (HC) were analyzed by 1H-NMR spectroscopy. Data analysis was conducted with principal components analysis followed by a supervised analysis (orthogonal partial least squares discriminant analysis [OPLS-DA]). The metabolites were identified and quantified using Chenomx software, and the receiver operating characteristic (ROC) curves were calculated. Results: The model obtained with the OPLS-DA identified predictive metabolic differences between the patients with MS and HC (R2X = 0.615, R2Y = 0.619, Q2 = 0.476; p < 0.001). The differential metabolites included glucose, 5-OH-tryptophan, and tryptophan, which were lower in the MS group, and 3-OH-butyrate, acetoacetate, acetone, alanine, and choline, which were higher in the MS group. The suitability of the model was evaluated using an external set of samples. The values returned by the model were used to build the corresponding ROC curve (area under the curve of 0.98). Conclusion: NMR metabolomic analysis was able to discriminate different metabolic profiles in patients with MS compared with HC. With the exception of choline, the main metabolic changes could be connected to 2 different metabolic pathways: tryptophan metabolism and energy metabolism. Metabolomics appears to represent a promising noninvasive approach for the study of MS. PMID:26740964

  10. Untargeted Metabolomic Analysis of Amniotic Fluid in the Prediction of Preterm Delivery and Bronchopulmonary Dysplasia

    PubMed Central

    Baraldi, Eugenio; Giordano, Giuseppe; Stocchero, Matteo; Moschino, Laura; Zaramella, Patrizia; Tran, Maria Rosa; Carraro, Silvia; Romero, Roberto; Gervasi, Maria Teresa

    2016-01-01

    Objective Bronchopulmonary dysplasia (BPD) is a serious complication associated with preterm birth. A growing body of evidence suggests a role for prenatal factors in its pathogenesis. Metabolomics allows simultaneous characterization of low molecular weight compounds and may provide a picture of such a complex condition. The aim of this study was to evaluate whether an unbiased metabolomic analysis of amniotic fluid (AF) can be used to investigate the risk of spontaneous preterm delivery (PTD) and BPD development in the offspring. Study design We conducted an exploratory study on 32 infants born from mothers who had undergone an amniocentesis between 21 and 28 gestational weeks because of spontaneous preterm labor with intact membranes. The AF samples underwent untargeted metabolomic analysis using mass spectrometry combined with ultra-performance liquid chromatography. The data obtained were analyzed using multivariate and univariate statistical data analysis tools. Results Orthogonally Constrained Projection to Latent Structures-Discriminant Analysis (oCPLS2-DA) excluded effects on data modelling of crucial clinical variables. oCPLS2-DA was able to find unique differences in select metabolites between term (n = 11) and preterm (n = 13) deliveries (negative ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.65; positive ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.70), and between PTD followed by the development of BPD (n = 10), and PTD without BPD (n = 11) (negative data set: R2 = 0.48, mean AUC ROC in prediction = 0.73; positive data set: R2 = 0.55, mean AUC ROC in prediction = 0.71). Conclusions This study suggests that amniotic fluid metabolic profiling may be promising for identifying spontaneous preterm birth and fetuses at risk for developing BPD. These findings support the hypothesis that some prenatal metabolic dysregulations may play a key role in the pathogenesis of PTD and the development of BPD. PMID:27755564

  11. Human urinary biomarkers of dioxin exposure: analysis by metabolomics and biologically driven data dimensionality reduction.

    PubMed

    Jeanneret, Fabienne; Boccard, Julien; Badoud, Flavia; Sorg, Olivier; Tonoli, David; Pelclova, Daniela; Vlckova, Stepanka; Rutledge, Douglas N; Samer, Caroline F; Hochstrasser, Denis; Saurat, Jean-Hilaire; Rudaz, Serge

    2014-10-15

    Untargeted metabolomic approaches offer new opportunities for a deeper understanding of the molecular events related to toxic exposure. This study proposes a metabolomic investigation of biochemical alterations occurring in urine as a result of dioxin toxicity. Urine samples were collected from Czech chemical workers submitted to severe dioxin occupational exposure in a herbicide production plant in the late 1960s. Experiments were carried out with ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution quadrupole time-of-flight (QTOF) mass spectrometry. A chemistry-driven feature selection was applied to focus on steroid-related metabolites. Supervised multivariate data analysis allowed biomarkers, mainly related to bile acids, to be highlighted. These results supported the hypothesis of liver damage and oxidative stress for long-term dioxin toxicity. As a second step of data analysis, the information gained from the urine analysis of Victor Yushchenko after his poisoning was examined. A subset of relevant urinary markers of acute dioxin toxicity from this extreme phenotype, including glucuro- and sulfo-conjugated endogenous steroid metabolites and bile acids, was assessed for its ability to detect long-term effects of exposure. The metabolomic strategy presented in this work allowed the determination of metabolic patterns related to dioxin effects in human and the discovery of highly predictive subsets of biologically meaningful and clinically relevant compounds. These results are expected to provide valuable information for a deeper understanding of the molecular events related to dioxin toxicity. Furthermore, it presents an original methodology of data dimensionality reduction by using extreme phenotype as a guide to select relevant features prior to data modeling (biologically driven data reduction).

  12. 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

  13. A Benchtop Fractionation Procedure for Subcellular Analysis of the Plant Metabolome

    PubMed Central

    Fürtauer, Lisa; Weckwerth, Wolfram; Nägele, Thomas

    2016-01-01

    Although compartmentation is a key feature of eukaryotic cells, biological research is frequently limited by methods allowing for the comprehensive subcellular resolution of the metabolome. It has been widely accepted that such a resolution would be necessary in order to approximate cellular biochemistry and metabolic regulation, yet technical challenges still limit both the reproducible subcellular fractionation and the sample throughput being necessary for a statistically robust analysis. Here, we present a method and a detailed protocol which is based on the non-aqueous fractionation technique enabling the assignment of metabolites to their subcellular localization. The presented benchtop method aims at unraveling subcellular metabolome dynamics in a precise and statistically robust manner using a relatively small amount of tissue material. The method is based on the separation of cellular fractions via density gradients consisting of organic, non-aqueous solvents. By determining the relative distribution of compartment-specific marker enzymes together with metabolite profiles over the density gradient it is possible to estimate compartment-specific metabolite concentrations by correlation. To support this correlation analysis, a spreadsheet is provided executing a calculation algorithm to determine the distribution of metabolites over subcellular compartments. The calculation algorithm performs correlation of marker enzyme activity and metabolite abundance accounting for technical errors, reproducibility and the resulting error propagation. The method was developed, tested and validated in three natural accessions of Arabidopsis thaliana showing different ability to acclimate to low temperature. Particularly, amino acids were strongly shuffled between subcellular compartments in a cold-sensitive accession while a cold-tolerant accession was characterized by a stable subcellular metabolic homeostasis. Finally, we conclude that subcellular metabolome analysis is

  14. 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.

  15. 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.

  16. NMR metabolomic analysis of exhaled breath condensate of asthmatic patients at two different temperatures.

    PubMed

    Motta, Andrea; Paris, Debora; D'Amato, Maria; Melck, Dominique; Calabrese, Cecilia; Vitale, Carolina; Stanziola, Anna A; Corso, Gaetano; Sofia, Matteo; Maniscalco, Mauro

    2014-12-05

    Exhaled breath condensate (EBC) collection is a noninvasive method to investigate lung diseases. EBC is usually collected with commercial/custom-made condensers, but the optimal condensing temperature is often unknown. As such, the physical and chemical properties of exhaled metabolites should be considered when setting the temperature, therefore requiring validation and standardization of the collecting procedure. EBC is frequently used in nuclear magnetic resonance (NMR)-based metabolomics, which unambiguously recognizes different pulmonary pathological states. Here we applied NMR-based metabolomics to asthmatic and healthy EBC samples collected with two commercial condensers operating at -27.3 and -4.8 °C. Thirty-five mild asthmatic patients and 35 healthy subjects were included in the study, while blind validation was obtained from 20 asthmatic and 20 healthy different subjects not included in the primary analysis. We initially analyzed the samples separately and assessed the within-day, between-day, and technical repeatabilities. Next, samples were interchanged, and, finally, all samples were analyzed together, disregarding the condensing temperature. Partial least-squares discriminant analysis of NMR spectra correctly classified samples, without any influence from the temperature. Input variables were either integral bucket areas (spectral bucketing) or metabolite concentrations (targeted profiling). We always obtained strong regression models (95%), with high average-quality parameters for spectral profiling (R(2) = 0.84 and Q(2) = 0.78) and targeted profiling (R(2) = 0.91 and Q(2) = 0.87). In particular, although targeted profiling clustering is better than spectral profiling, all models reproduced the relative metabolite variations responsible for class differentiation. This warrants that cross comparisons are reliable and that NMR-based metabolomics could attenuate some specific problems linked to standardization of EBC collection.

  17. Lipidome and metabolome analysis of fresh tobacco leaves in different geographical regions using liquid chromatography-mass spectrometry.

    PubMed

    Li, Lili; Lu, Xin; Zhao, Jieyu; Zhang, Junjie; Zhao, Yanni; Zhao, Chunxia; Xu, Guowang

    2015-07-01

    The combination of the lipidome and the metabolome can provide much more information in plant metabolomics studies. A method for the simultaneous extraction of the lipidome and the metabolome of fresh tobacco leaves was developed. Method validation was performed on the basis of the optimal ratio of methanol to methyl tert-butyl ether to water (37:45:68) from the design of experiments. Good repeatability was obtained. We found that 92.2% and 91.6% of the peaks for the lipidome and the metabolome were within a relative standard deviation of 20%, accounting for 94.6% and 94.6% of the total abundance, respectively. The intraday and interday precisions were also satisfactory. A total of 230 metabolites, including 129 lipids, were identified. Significant differences were found in lipidomic and metabolomic profiles of fresh tobacco leaves in different geographical regions. Highly unsaturated galactolipids, phosphatidylethanolamines, predominant phosphatidylcholines, most of the polyphenols, amino acids, and polyamines had a higher content in Yunnan province, and low-unsaturation-degree galactolipids, triacylglycerols, glucosylceramides with trihydroxy long-chain bases, acylated sterol glucosides, and some organic acids were more abundant in Henan province. Correlation analysis between differential metabolites and climatic factors indicated the vital importance of temperature. The fatty acid unsaturation degree of galactolipids could be influenced by temperature. Accumulation of polyphenols and decreases in the ratios of stigmasterols to sitosterols and glucosylstigmasterols to glucosylsitosterols were also correlated with lower temperature in Yunnan province. Furthermore, lipids were more sensitive to climatic variations than other metabolites.

  18. 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

  19. Metabolomics Analysis of the Larval Head of the Silkworm, Bombyx mori

    PubMed Central

    Li, Yi; Wang, Xin; Chen, Quanmei; Hou, Yong; Xia, Qingyou; Zhao, Ping

    2016-01-01

    The head, which performs many biological functions, is the most complicated structure of an insect. Development, locomotor behavior, food intake, environmental sensing, and signal transduction are all controlled by the insect’s head. As a well-studied insect in Lepidoptera, the silkworm head has an additional function of spinning silk fibers. To understand which molecules are involved in these physiological activities, we performed a metabolomics analysis of silkworm heads. By integrating GC-MS and LC-MS/MS, 90 metabolites were identified in the larval heads of silkworms. These were classified into 13 categories, including amino acids, sugars, organic acids, nucleotides, alcohols, and fatty acids. Informatics analysis revealed that these metabolites are involved in cellular processes, environmental information processing, genetic information processing, human diseases, metabolism, organismal systems, and other pathways. The identified metabolites and pathways are involved in biological processes such as signal transduction, carbohydrate metabolism, endocrine activities, and sensory activities; reflecting the functions of various organs in silkworm heads. Thus, our findings provide references which elucidate the potential functions of the silkworm head and will be of great value for the metabolomics research of silkworms and other insects. PMID:27657048

  20. Plasma metabolomic analysis of human hepatocellular carcinoma: Diagnostic and therapeutic study

    PubMed Central

    Li, Jinquan; Feng, Jianghua; Chen, Zhong; Wang, Xiaomin

    2016-01-01

    Many hepatocellular carcinoma (HCC) patients suffer from late stages when diagnosed, leading to dismal prospects for cure. Improving the diagnosis and treatment of HCC remains a challenge. In this work, NMR-based metabolomic techniques were used to investigate the metabolic alterations of HCC patients from different pathological backgrounds. Metabolic improvement of clinical surgical treatments or transcatheter arterial chemoembolization (TACE) for recurrent or metastatic HCC was also evaluated. HCC was characterized by enhanced lipid metabolism and high consumption in response to liver injury. Expectedly, higher consumption of glucose and lactate production in TACE group confirmed that recurrent or metastatic HCC is more active in citric acid cycle and oxidative phosphorylation. However, TACE or surgical treatments did not immediately improve the metabolic profiles of HCC patients. Combining multivariate statistical analyses with univariate t-test, a series of characteristic metabolites were identified and served as biomarkers for discrimination of HCC patients in different pathological backgrounds. The relative metabolic pathway analyses help to get insight into the underlying biochemical mechanism and extend clinical relevance. Furthermore, algorithm of support vector classification was used to identify HCC and control subjects, and diagnostic sensitivity and specificity reached to 100% and 81.08% respectively by receiver operating characteristic analysis. It is concluded that NMR-based metabolomic analysis of plasma can provide a powerful approach to discover diagnostic and therapeutic biomarkers, and subsequently contribute to clinical disease management. PMID:27322079

  1. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    PubMed

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable.

  2. Metabolomic analysis of isonitrosoacetophenone-induced perturbations in phenolic metabolism of Nicotiana tabacum cells.

    PubMed

    Madala, Ntakadzeni E; Steenkamp, Paul A; Piater, Lizelle A; Dubery, Ian A

    2013-10-01

    Plants have developed biochemical and molecular responses to adapt to different stress environments. One of the characteristics of the multi-component defence response is the production of defence-related metabolites. Plant defences can be triggered by various stimuli, including synthetic or naturally occurring molecules, especially those derived from pathogens. In the current study, Nicotiana tabacum cell suspensions were treated with isonitrosoacetophenone (INAP), a subcomponent of a plant-derived stress metabolite with anti-fungal and anti-oxidant properties, in order to investigate the effect thereof on cellular metabolism. Subsequent metabolomic-based analyses were employed to evaluate changes in the metabolome. UPLC-MS in conjunction with multivariate data analyses was found to be an appropriate approach to study the effect of chemical inducers like INAP on plant metabolism in this model system. Principal component analysis (PCA) indicated that INAP is capable of inducing time-dependent metabolic perturbations in the cultured cells. Orthogonal projection to latent structures discriminant analysis (OPLS-DA) revealed metabolites of which the levels are affected by INAP, and eight of these were tentatively annotated from the mass spectral data and online databases. These metabolites are known in the context of plant stress- and defence responses and include benzoic- or cinnamic acid derivatives that are either glycosylated or quinilated as well as flavonoid derivatives. The results indicate that INAP affects the shikimate-, phenylpropanoid- and flavonoid pathways, the products of which may subsequently lead to an anti-oxidant environment in vivo.

  3. 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

  4. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis.

    PubMed

    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

    2015-06-15

    Kidney cancer [or renal cell carcinoma (RCC)] is known as "the internist's tumor" because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic 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 Von Hippel-Lindau 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, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. 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 with other metabolic pathways. Together, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC.

  5. MetaboAnalyst 2.0--a comprehensive server for metabolomic data analysis.

    PubMed

    Xia, Jianguo; Mandal, Rupasri; Sinelnikov, Igor V; Broadhurst, David; Wishart, David S

    2012-07-01

    First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server's multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.

  6. MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

    PubMed Central

    Xia, Jianguo; Mandal, Rupasri; Sinelnikov, Igor V.; Broadhurst, David; Wishart, David S.

    2012-01-01

    First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well. PMID:22553367

  7. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

    PubMed Central

    Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C.

    2016-01-01

    Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions. PMID:27706030

  8. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites.

    PubMed

    Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C

    2016-09-30

    Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

  9. 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

  10. Metabolomics analysis of the effect of dissolved oxygen on spinosad production by Saccharopolyspora spinosa.

    PubMed

    Lu, Chunzhe; Yin, Jing; Zhao, Fanglong; Li, Feng; Lu, Wenyu

    2017-02-02

    Spinosad, a universal bio-pesticide, is obtained from the soil actinomycete Saccharopolyspora spinosa. Dissolved oxygen, an important contributing factor in aerobic microbial fermentation, however, is not always available in sufficient amounts. To alleviate oxygen limitation in spinosad production, three different oxygen vectors, namely oleic acid, toluene, and n-dodecane, were added into early fermentation. Results indicated that n-dodecane was the optimal oxygen vector. Spinosad yield was increased by 44.2% compared to that in the control group in the presence of 0.5% n-dodecane, added after 120 h of incubation. Yields of the test group reached 6.52 mg/g dry cell weight (DCW), while that of the control group was limited to 4.52 mg/g DCW. Metabolomics analysis by gas chromatography coupled to mass spectrometry was performed to demonstrate the metabolism mechanism in the presence and absence of oxygen vector. In total, 78 principal intracellular metabolites in S. spinosa were detected and quantified in the presence and absence of n-dodecane. Levels of some metabolites that were related to the tricarboxylic acid cycle and pentose phosphate pathway varied significantly. Aspartic acid and glucose-1-phosphate levels varied significantly and contributed most in the distinction of the fermentation conditions and phases. The above findings give new insights into the improvement and the metabolomic characteristics of industrial spinosad production.

  11. Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis

    PubMed Central

    Kind, Tobias; Cho, Eunho; Park, Taeeun D.; Deng, Nan; Liu, Zhenqiu; Lee, Tack; Fiehn, Oliver; Kim, Jayoung

    2016-01-01

    This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms. PMID:27976711

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    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.

  13. 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.

  14. Metabolomics in food analysis: application to the control of forbidden substances.

    PubMed

    Dervilly-Pinel, Gaud; Courant, Frédérique; Chéreau, Sylvain; Royer, Anne-Lise; Boyard-Kieken, Fanny; Antignac, Jean-Philippe; Monteau, Fabrice; Le Bizec, Bruno

    2012-08-01

    Metabolomics is a science of interest in food analysis to describe and predict properties of food products and processes. It includes the development of analytical methods with the ultimate goal being the identification of so-called 'quality markers', (i.e. sets of metabolites that correlate with, for example, quality, safety, taste, or fragrance of foodstuffs). In turn, these metabolites are influenced by factors as genetic differences of the raw food ingredients (such as animal breed or crop species differences), growth conditions (such as climate, irrigation strategy, or feeding) or production conditions (such as temperature, acidity, or pressure). In cases where the routine-based measurement of a food property faces some limitations such as the lack of knowledge regarding the target compounds to monitor, monitoring based on a limited set of crucial biomarkers is a good alternative, which is of great interest for food safety purposes regarding growth promoting practices. Such an approach may be more efficient than using a classic approach based on a limited set of known metabolites of anabolic compounds. In this context, screening strategies allowing detection of the physiological response resulting from anabolic compound administration are promising approaches to detect their misuse. The global metabolomics workflow implemented for such studies is presented and illustrated through various examples of biological matrices profiling (tissue, blood, urine) and for different classes of anabolic compounds (steroids, β-agonists and somatotropin).

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

    PubMed

    Wang, Hui; Chen, Jiao; Feng, Yun; Zhou, Wenjie; Zhang, Jihua; Yu, Y U; Wang, Xiaoqian; Zhang, Ping

    2015-06-01

    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, (1)H 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, (1)H NMR-based metabolomic analysis has a high potential for monitoring the formation of MDR during clinical tumor chemotherapy in the future.

  16. 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

  17. 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

  18. Metabolomic analysis of key regulatory metabolites in hepatitis C virus-infected tree shrews.

    PubMed

    Sun, Hui; Zhang, Aihua; Yan, Guangli; Piao, Chengyu; Li, Weiyun; Sun, Chang; Wu, Xiuhong; Li, Xinghua; Chen, Yun; Wang, Xijun

    2013-03-01

    Metabolomics is a powerful new technology that allows the assessment of global low-molecular-weight metabolites in a biological system and which shows great potential in biomarker discovery. Analysis of the key metabolites in body fluids has become an important part of improving the diagnosis, prognosis, and therapy of diseases. Hepatitis C virus (HCV) is a major leading cause of liver disease worldwide and a serious burden on public health. However, the lack of a small-animal model has hampered the analysis of HCV pathogenesis. We hypothesize that an animal model (Tupaia belangeri chinensis) of HCV would produce a unique characterization of metabolic phenotypes. Ultra-performance liquid-chromatography/electrospray ionization-SYNAPT-high-definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) coupled with pattern recognition methods and system analysis was carried out to obtain comprehensive metabolomics profiling and pathways of large biological data sets. Taurine, hypotaurine, ether lipid, glycerophospholipid, arachidonic acid, tryptophan, and primary bile acid metabolism pathways were acutely perturbed, and 38 differential metabolites were identified. More important, five metabolite markers were selected via the "significance analysis for microarrays" method as the most discriminant and interesting biomarkers that were effective for the diagnosis of HCV. Network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Integrated network analysis of the key metabolites yields highly related signaling pathways associated with the differentially expressed proteins, which suggests that the creation of new treatment paradigms targeting and activating these networks in their entirety, rather than single proteins, might be necessary for controlling and treating HCV efficiently.

  19. Metabolomic Analysis of Key Regulatory Metabolites in Hepatitis C Virus–infected Tree Shrews*

    PubMed Central

    Sun, Hui; Zhang, Aihua; Yan, Guangli; Piao, Chengyu; Li, Weiyun; Sun, Chang; Wu, Xiuhong; Li, Xinghua; Chen, Yun; Wang, Xijun

    2013-01-01

    Metabolomics is a powerful new technology that allows the assessment of global low-molecular-weight metabolites in a biological system and which shows great potential in biomarker discovery. Analysis of the key metabolites in body fluids has become an important part of improving the diagnosis, prognosis, and therapy of diseases. Hepatitis C virus (HCV) is a major leading cause of liver disease worldwide and a serious burden on public health. However, the lack of a small-animal model has hampered the analysis of HCV pathogenesis. We hypothesize that an animal model (Tupaia belangeri chinensis) of HCV would produce a unique characterization of metabolic phenotypes. Ultra-performance liquid-chromatography/electrospray ionization-SYNAPT-high-definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) coupled with pattern recognition methods and system analysis was carried out to obtain comprehensive metabolomics profiling and pathways of large biological data sets. Taurine, hypotaurine, ether lipid, glycerophospholipid, arachidonic acid, tryptophan, and primary bile acid metabolism pathways were acutely perturbed, and 38 differential metabolites were identified. More important, five metabolite markers were selected via the “significance analysis for microarrays” method as the most discriminant and interesting biomarkers that were effective for the diagnosis of HCV. Network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Integrated network analysis of the key metabolites yields highly related signaling pathways associated with the differentially expressed proteins, which suggests that the creation of new treatment paradigms targeting and activating these networks in their entirety, rather than single proteins, might be necessary for controlling and treating HCV efficiently. PMID:23264353

  20. 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.

  1. Metabolomic analysis of Ranunculus spp. as potential agents involved in the etiology of equine grass sickness.

    PubMed

    Michl, Johanna; Modarai, Maryam; Edwards, Sarah; Heinrich, Michael

    2011-09-28

    Identification of toxic or harmful agents continues to be a key goal in agricultural chemistry. This paper reports a metabolomic analysis of Ranunculus repens and related species, which were recently postulated to be cocausative agents in the etiology of equine grass sickness (EGS). Specifically, samples collected at EGS sites were compared with those from non-EGS sites. Furthermore, interspecific and seasonal variations and the species' response to edaphic and climatic factors were investigated. (1)H NMR spectroscopy in combination with multivariate data analysis was applied to the crude methanol extracts of the Ranunculus samples, as well as their chloroform fractions. Samples from EGS sites were significantly different from control samples. The metabolite composition varied greatly between different Ranunculus species. No significant changes could be observed between samples collected in different seasons. This work provides strong evidence that Ranunculus is involved in the etiology of EGS and has implications for agricultural management of pastures.

  2. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data.

    PubMed

    Tsai, I-Lin; Kuo, Tien-Chueh; Ho, Tsung-Jung; Harn, Yeu-Chern; Wang, San-Yuan; Fu, Wen-Mei; Kuo, Ching-Hua; Tseng, Yufeng Jane

    2013-05-03

    Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  3. 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

  4. LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

    PubMed

    Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

    2012-03-01

    MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

  5. 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

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

    PubMed

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

    2012-02-01

    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 7 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.

  7. Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis

    PubMed Central

    Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

    2016-01-01

    In untargeted metabolomics analysis, several factors (e.g., unwanted experimental & biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data. PMID:27958387

  8. 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

  9. Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples.

    PubMed

    Beckmann, Manfred; Lloyd, Amanda J; Haldar, Sumanto; Favé, Gaëlle; Seal, Chris J; Brandt, Kirsten; Mathers, John C; Draper, John

    2013-08-01

    Although robust associations between dietary intake and population health are evident from conventional observational epidemiology, the outcomes of large-scale intervention studies testing the causality of those links have often proved inconclusive or have failed to demonstrate causality. This apparent conflict may be due to the well-recognised difficulty in measuring habitual food intake which may lead to confounding in observational epidemiology. Urine biomarkers indicative of exposure to specific foods offer information supplementary to the reliance on dietary intake self-assessment tools, such as FFQ, which are subject to individual bias. Biomarker discovery strategies using non-targeted metabolomics have been used recently to analyse urine from either short-term food intervention studies or from cohort studies in which participants consumed a freely-chosen diet. In the latter, the analysis of diet diary or FFQ information allowed classification of individuals in terms of the frequency of consumption of specific diet constituents. We review these approaches for biomarker discovery and illustrate both with particular reference to two studies carried out by the authors using approaches combining metabolite fingerprinting by MS with supervised multivariate data analysis. In both approaches, urine signals responsible for distinguishing between specific foods were identified and could be related to the chemical composition of the original foods. When using dietary data, both food distinctiveness and consumption frequency influenced whether differential dietary exposure could be discriminated adequately. We conclude that metabolomics methods for fingerprinting or profiling of overnight void urine, in particular, provide a robust strategy for dietary exposure biomarker-lead discovery.

  10. Urine metabolomic analysis to detect metabolites associated with the development of contrast induced nephropathy

    PubMed Central

    Diercks, Deborah B.; Owen, Kelly P.; Kline, Jeffrey A.; Sutter, Mark E.

    2016-01-01

    Objective Contrast induced nephropathy (CIN) is a result of injury to the proximal tubules. The incidence of CIN is around 11% for imaging done in the acute care setting. We aim to analyze the metabolic patterns in the urine, before and after dosing with intravenous contrast for computed tomography (CT) imaging of the chest, to determine if metabolomic changes exist in patients who develop CIN. Methods A convenience sample of high risk patients undergoing a chest CT with intravenous contrast were eligible for enrollment. Urine samples were collected prior to imaging and 4 to 6 hours post imaging. Samples underwent gas chromatography/mass spectrometry profiling. Peak metabolite values were measured and data was log transformed. Significance analysis of microarrays and partial least squares was used to determine the most significant metabolites prior to CT imaging and within subject. Analysis of variance was used to rank metabolites associated with temporal change and CIN. CIN was defined as an increase in serum creatinine level of ≥ 0.5 mg/dL or ≥ 25% above baseline within 48 hours after contrast administration. Results We sampled paired urine samples from 63 subjects. The incidence of CIN was 6/63 (9.5%). Patients without CIN had elevated urinary citric acid and taurine concentrations in the pre-CT urine. Xylulose increased in the post CT sample in patients who developed CIN. Conclusion Differences in metabolomics patterns in patients who do and do not develop CIN exist. Metabolites may be potential early identifiers of CIN and identify patients at high-risk for developing this condition prior to imaging. PMID:28168227

  11. 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

  12. 3-hydroxykynurenine and other Parkinson's disease biomarkers discovered by metabolomic analysis.

    PubMed

    Lewitt, Peter A; Li, Jia; Lu, Mei; Beach, Thomas G; Adler, Charles H; Guo, Lining

    2013-10-01

    Parkinson's disease (PD) biomarkers are needed to enhance therapeutics research and to understand PD pathogenesis. Methods that simultaneously measure hundreds of small molecular-weight compounds-metabolomic analysis-"fingerprint" disease-specific alterations in individual compounds or metabolic pathways. Beyond a nontargeted search for PD biomarkers, we hypothesized that PD cerebrospinal fluid would show increased formation of the excitotoxin 3-hydroxykynurenine and diminished concentration of the antioxidant glutathione. Cerebrospinal fluid was collected at <4 hours postmortem from 48 pathologically-verified PD subjects and 57 comparably-aged controls. Assays involved ultra-high-performance liquid and gas chromatography linked to mass spectrometry. We used univariate techniques to determine fold-changes in concentrations of biochemicals; false-discovery rates were calculated to exclude spurious findings. Data was modeled using a Support Vector Machine for analyzing compounds selected by Welch's t test. Classification accuracy was determined by cross-validation. Of 243 structurally-identified biochemicals,19 compounds differentiated PD from controls at a 20% false-discovery level. In PD, mean 3-hydroxykynurenine concentration was increased by one-third, and mean oxidized glutathione was decreased by 40% (for each, P < .01). Four of the 19 compounds differentiating PD from controls were N-acetylated amino acids, suggesting a generalized alteration in N-acetylation activity. The Support Vector Machine classification model distinguished between groups at 83% sensitivity and 91% specificity for the learning data, and at 65% and 79% from cross-validation. In this study, the first for metabolomic profiling of PD cerebrospinal fluid, we found several novel biomarkers and offer new directions for recognizing disease-specific biochemical indicators. The findings support involvement of excitotoxicity and oxidative stress in the pathogenesis of PD.

  13. Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses.

    PubMed

    Thévenot, Etienne A; Roux, Aurélie; Xu, Ying; Ezan, Eric; Junot, Christophe

    2015-08-07

    Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.

  14. Metabolomics in childhood diabetes

    PubMed Central

    Frohnert, Brigitte I; Rewers, Marian J

    2015-01-01

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

  15. 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.

  16. Metabolomic Analysis of the Effect of Postnatal Hypoxia on the Retina in a Newly Born Piglet Model

    PubMed Central

    Solberg, Rønnaug; Escobar, Javier; Arduini, Alessandro; Torres-Cuevas, Isabel; Lahoz, Agustín; Sastre, Juan; Saugstad, Ola Didrik; Vento, Máximo; Kuligowski, Julia; Quintás, Guillermo

    2013-01-01

    The availability of reliable biomarkers of brain injury secondary to birth asphyxia could substantially improve clinical grading, therapeutic intervention strategies, and prognosis. In this study, changes in the metabolome of retinal tissue caused by profound hypoxia in an established neonatal piglet model were investigated using an ultra performance liquid chromatography – quadrupole time of flight mass spectrometry (UPLC-QTOFMS) untargeted metabolomic approach, which included Partial Least Squares – Discriminant Analysis (PLSDA) multivariate data analysis. The initial identification of a set of discriminant metabolites from UPLC-QTOFMS data was confirmed by target UPLC-MS/MS and allowed the selection of endogenous CDP-choline as a promising candidate biomarker for hypoxia-derived brain damage assessing intensity of retinal hypoxia. Results from this study will foster further research on CDP-choline changes occurring during resuscitation. PMID:23823578

  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. PMID:27602357

  18. Metabolomic analysis of human oral cancer cells with adenylate kinase 2 or phosphorylate glycerol kinase 1 inhibition

    PubMed Central

    Ji, Eoon Hye; Cui, Li; Yuan, Xiaoqing; Cheng, Siliangyu; Messadi, Diana; Yan, Xinmin; Hu, Shen

    2017-01-01

    The purpose of this study was to use liquid chromatography-mass spectrometry (LC-MS) with XCMS for a quantitative metabolomic analysis of UM1 and UM2 oral cancer cells after knockdown of metabolic enzyme adenylate kinase 2 (AK2) or phosphorylate glycerol kinase 1 (PGK1). UM1 and UM2 cells were initially transfected with AK2 siRNA, PGK1 siRNA or scrambled control siRNA, and then analyzed with LC-MS for metabolic profiles. XCMS analysis of the untargeted metabolomics data revealed a total of 3200-4700 metabolite features from the transfected UM1 or UM2 cancer cells and 369-585 significantly changed metabolites due to AK2 or PGK1 suppression. In addition, cluster analysis showed that a common group of metabolites were altered by AK2 knockdown or by PGK1 knockdown between the UM1 and UM2 cells. However, the set of significantly changed metabolites due to AK2 knockdown was found to be distinct from those significantly changed by PGK1 knockdown. Our study has demonstrated that LC-MS with XCMS is an efficient tool for metabolomic analysis of oral cancer cells, and knockdown of different genes results in distinct changes in metabolic phenotypes in oral cancer cells. PMID:28243334

  19. (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.

  20. Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes

    PubMed Central

    2016-01-01

    The speed and throughput of analytical platforms has been a driving force in recent years in the “omics” technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition. PMID:27983788

  1. Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes.

    PubMed

    Montenegro-Burke, J Rafael; Aisporna, Aries E; Benton, H Paul; Rinehart, Duane; Fang, Mingliang; Huan, Tao; Warth, Benedikt; Forsberg, Erica; Abe, Brian T; Ivanisevic, Julijana; Wolan, Dennis W; Teyton, Luc; Lairson, Luke; Siuzdak, Gary

    2017-01-17

    The speed and throughput of analytical platforms has been a driving force in recent years in the "omics" technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition.

  2. Single-Cell Metabolomics.

    PubMed

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

    2017-01-01

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

  3. 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

  4. NMR metabolomic analysis of fecal water from subjects on a vegetarian diet.

    PubMed

    Pettersson, Jenny; Karlsson, Pernilla Christina; Choi, Young Hae; Verpoorte, Robert; Rafter, Joseph James; Bohlin, Lars

    2008-06-01

    A vegetarian diet rich in phytochemicals may prevent colon carcinogenesis by affecting biochemical processes in the colonic mucosa. Compounds passing the digestive system reaching the colon could potentially be detected in fecal water. We previously reported that intact fecal water samples from human volunteers significantly decreased prostaglandin production and COX-2 protein expression in colonic cells. The aim with the present study was to further study the composition of the fecal waters, using NMR spectroscopy and multivariate data analysis, and to trace the COX-2 inhibiting activity. Intact fecal water samples and fractions thereof were analyzed for their ability to inhibit prostaglandin E2 production in the human colon cell line HT-29. The majority of the tested aqueous phases derived from intact fecal water showed ability to inhibit prostaglandin production in cells (13.8+/-1.34% inhibition, p=0.01). NMR analysis indicated the presence of significant quantities of amino acids and fatty acids. Major metabolites included; acetic acid, butanoic acid, propanoic acid, glutamic acid and alanine. Smaller amounts of glycine and fumaric acid, which are known to have anti-inflammatory and anti-tumorigenic properties, were also detected. This study describes for the first time NMR metabolomic analysis of fecal water from subjects on a vegetarian diet.

  5. Metabolomic analysis of soil communities can be used for pollution assessment.

    PubMed

    Jones, Oliver A H; Sdepanian, Stephanie; Lofts, Steven; Svendsen, Claus; Spurgeon, David J; Maguire, Mahon L; Griffin, Julian L

    2014-01-01

    Metabolic profiling can be used to assess the changes in biochemical profiles of soil communities living in contaminated sites. The term "community metabolomics" is proposed for the application of metabolomics techniques to the study of the entire community of a soil sample. The authors anticipate the present study to be a starting point for the use of this technique to assess how communities respond to factors such as pollution and climate change.

  6. A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding.

    PubMed

    Gromski, Piotr S; Muhamadali, Howbeer; Ellis, David I; Xu, Yun; Correa, Elon; Turner, Michael L; Goodacre, Royston

    2015-06-16

    The predominance of partial least squares-discriminant analysis (PLS-DA) used to analyze metabolomics datasets (indeed, it is the most well-known tool to perform classification and regression in metabolomics), can be said to have led to the point that not all researchers are fully aware of alternative multivariate classification algorithms. This may in part be due to the widespread availability of PLS-DA in most of the well-known statistical software packages, where its implementation is very easy if the default settings are used. In addition, one of the perceived advantages of PLS-DA is that it has the ability to analyze highly collinear and noisy data. Furthermore, the calibration model is known to provide a variety of useful statistics, such as prediction accuracy as well as scores and loadings plots. However, this method may provide misleading results, largely due to a lack of suitable statistical validation, when used by non-experts who are not aware of its potential limitations when used in conjunction with metabolomics. This tutorial review aims to provide an introductory overview to several straightforward statistical methods such as principal component-discriminant function analysis (PC-DFA), support vector machines (SVM) and random forests (RF), which could very easily be used either to augment PLS or as alternative supervised learning methods to PLS-DA. These methods can be said to be particularly appropriate for the analysis of large, highly-complex data sets which are common output(s) in metabolomics studies where the numbers of variables often far exceed the number of samples. In addition, these alternative techniques may be useful tools for generating parsimonious models through feature selection and data reduction, as well as providing more propitious results. We sincerely hope that the general reader is left with little doubt that there are several promising and readily available alternatives to PLS-DA, to analyze large and highly complex data sets.

  7. Metabolomic evaluation of ginsenosides distribution in Panax genus (Panax ginseng and Panax quinquefolius) using multivariate statistical analysis.

    PubMed

    Pace, Roberto; Martinelli, Ernesto Marco; Sardone, Nicola; D E Combarieu, Eric

    2015-03-01

    Ginseng is any one of the eleven species belonging to the genus Panax of the family Araliaceae and is found in North America and in eastern Asia. Ginseng is characterized by the presence of ginsenosides. Principally Panax ginseng and Panax quinquefolius are the adaptogenic herbs and are commonly distributed as health food markets. In the present study high performance liquid chromatography has been used to identify and quantify ginsenosides in the two subject species and the different parts of the plant (roots, neck, leaves, flowers, fruits). The power of this chromatographic technique to evaluate the identity of botanical material and to distinguishing different part of the plants has been investigated with metabolomic technique such as principal component analysis. Metabolomics provide a good opportunity for mining useful chemical information from the chromatographic data set resulting an important tool for quality evaluation of medicinal plants in the authenticity, consistency and efficacy.

  8. Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis

    PubMed Central

    Gu, Jinping; Hu, Xiaomin; Shao, Wei; Ji, Tianhai; Yang, Wensheng; Zhuo, Huiqin; Jin, Zeyu; Huang, Huiying; Chen, Jiacheng; Huang, Caihua; Lin, Donghai

    2016-01-01

    Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression. PMID:27527852

  9. Metabolomic analysis of phenolic compounds in buckwheat (Fagopyrum esculentum M.) sprouts treated with methyl jasmonate.

    PubMed

    Kim, Hyun-Jin; Park, Kee-Jai; Lim, Jeong-Ho

    2011-05-25

    The effects of exogenous methyl jasmonate (MeJA) on phytochemical production in buckwheat sprouts cultivated under dark conditions (0, 1, 3, 5, and 7 d) were investigated by metabolomic analysis, using ultra performance liquid chromatography-quadrupole-time-of-flight (UPLC-Q-TOF) mass spectroscopy (MS) and partial least-squares-discriminant analysis (PLS-DA). MeJA-treated and control groups showed no differences in growth but were clearly discriminated from each other on PLS-DA score plots. The metabolites contributing to the discrimination were assigned as chlorogenic acid, catechin, isoorientin, orientin, rutin, vitexin, and quercitrin, which have various health effects. Moreover, isoorientin, orientin, rutin, and vitexin were assigned as the main phytochemicals of sprouts cultivated under dark conditions. The accumulation of these metabolites caused the phenolic compound content and antioxidant activity of the sprouts to increase. Further, this study revealed that their accumulation resulted from the stimulation of the phenylpropanoid pathway by MeJA treatment. Therefore, these metabolites may be useful for better understanding the effects of MeJA on buckwheat sprout phytochemicals and contribute to improving the functional quality of the sprouts.

  10. Metabolomics analysis of fungal biofilm development and of arachidonic acid-based quorum sensing mechanism.

    PubMed

    Ząbek, Adam; Junka, Adam; Szymczyk, Patrycja; Wojtowicz, Wojciech; Klimek-Ochab, Magdalena; Młynarz, Piotr

    2017-04-03

    The infections caused by filamentous fungi are becoming worldwide problem of healthcare systems due to increasing drug-resistance of this microorganism and increasing number of immunocompromised nosocomial patients. These infections are related with Aspergillus ability to form sessile communities referred to as the biofilms. The small compounds known as quorum sensing (QS) molecules allow this microorganism to coordinate all processes taking place during biofilm formation and maturation. In the study presented, the HRMAS (1) H NMR metabolomic approach was applied to define composition of extra and intracellular metabolites produced by biofilmic and planktonic (aka free-swimming) cultures of this microorganism and to evaluate impact of quorum sensing molecule, arachidonic acid (AA) on biofilm formation. The Scanning Electron Microscopy was used to confirm Aspergillus ability to form biofilm in vitro, while multivariate and univariate data analysis was applied to analyze data obtained. The Aspergillus strain was able to form strong biofilm structures in vitro. The statistical analysis revealed significant changes of metabolite production depending on Aspergillus culture type (biofilm vs. plankton), time and presence of QS molecules. The data obtained, if developed, might be used in future NMR diagnostics as markers of Aspergillus biofilm-related infections and lead to shorten time between pathogen identification and introduction of treatment.

  11. Metabolomic Analysis of Exercise Effects in the POLG Mitochondrial DNA Mutator Mouse Brain

    PubMed Central

    Clark-Matott, Joanne; Saleem, Ayesha; Dai, Ying; Shurubor, Yevgeniya; Ma, Xiaoxing; Safdar, Adeel; Beal, M. Flint; Tarnopolsky, Mark; Simon, David K.

    2015-01-01

    Mitochondrial DNA (mtDNA) mutator mice express a mutated form of mtDNA polymerase gamma (PolgA) that results an accelerated accumulation of somatic mtDNA mutations in association with a premature aging phenotype. An exploratory metabolomic analysis of cortical metabolites in sedentary and exercised mtDNA mutator mice and wild-type (WT) littermate controls at 9–10 months of age was performed. Pathway analysis revealed deficits in the neurotransmitters acetylcholine, glutamate and aspartate that were ameliorated by exercise. Nicotinamide adenine dinucleotide (NAD+) depletion and evidence of increased Poly [ADP-ribose] polymerase 1 (PARP-1) activity were apparent in sedentary mtDNA mutator mouse cortex, along with deficits in carnitine metabolites and an upregulated antioxidant response that largely normalized with exercise. These data highlight specific pathways that are altered in the brain in association with an accelerated age-related accumulation of somatic mtDNA mutations. These results may have relevance to age-related neurodegenerative diseases associated with mitochondrial dysfunction, such as Alzheimer’s disease and Parkinson’s disease, and provide insights into potential mechanisms of beneficial effects of exercise on brain function. PMID:26294258

  12. 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

  13. Analysis of urinary metabolomic profiling for unstable angina pectoris disease based on nuclear magnetic resonance spectroscopy.

    PubMed

    Li, Zhongfeng; Liu, Xinfeng; Wang, Juan; Gao, Jian; Guo, Shuzhen; Gao, Kuo; Man, Hongxue; Wang, Yingfeng; Chen, Jianxin; Wang, Wei

    2015-12-01

    (1)H NMR-based urinary metabolic profiling is used for investigating the unstable angina pectoris (UAP) metabolic signatures, in order to find out candidate biomarkers to facilitate medical diagnosis. In this work, 27 urine samples from UAP patients and 20 healthy controls were used. The metabolic profiles of the samples were analyzed by multivariate statistics analysis, including PCA, PLS-DA and OPLS-DA. The PCA analysis exhibited slight separation with R(2)X of 0.681 and Q2 of 0.251, while the PLS-DA (R(2)X = 0.121, R(2)Y = 0.931, and Q(2) = 0.661) and the OPLS-DA (R(2)X = 0.121, R(2)Y = 0.931, Q(2) = 0.653) demonstrated that the model showed good performance. By OPLS-DA, 20 metabolites were identified. A diagnostic model was further constructed using the receiver-operator characteristic (ROC) curves (AUC = 0.953), which exhibited a satisfying sensitivity of 92.6%, specificity of 90% and accuracy of 89.1%. The results demonstrated that the NMR-based metabolomics approach showed good performance in identifying diagnostic urinary biomarkers, providing new insights into the metabolic process related to UAP.

  14. 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

  15. 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).

  16. Effect of Major Royal Jelly Proteins on Spatial Memory in Aged Rats: Metabolomics Analysis in Urine.

    PubMed

    Chen, Di; Liu, Fang; Wan, Jian-Bo; Lai, Chao-Qiang; Shen, Li-Rong

    2017-04-10

    Royal jelly (RJ) produced by worker honeybees is the sole food for the queen bee throughout her life as well as the larvae of worker bees for the first 3 days after hatching. Supplementation of RJ in the diet has been shown to increase spatial memory in rodents. However, the key constituents in RJ responsible for improvement of cognitive function are unknown. Our objective was to determine if the major royal jelly proteins (MRJPs) extracted from RJ can improve the spatial memory of aged rats. The spatial memory assay using the Morris water maze test was administered once to rats after a 14-week feeding. Metabolomics analysis based on quadrupole time-of-flight mass spectrometry was conducted to examine the differences in compounds from urine. Aged male rats fed MRJPs showed improved spatial memory up to 48.5% when compared to the control male aged rats fed distilled water. The metabolite pattern of the MRJPs-fed aged rats was regressed to that of the young rats. Compounds altered by MRJPs were mapped to nicotinate and nicotinamide metabolism, cysteine taurine metabolism, and energy metabolism pathways. In summary, MRJPs may improve spatial memory and possess the potential for prevention of cognitive impairment via the cysteine and taurine metabolism and energy metabolism pathways in aged rats.

  17. Metabolomic analysis of antimicrobial mechanisms of ε-poly-L-lysine on Saccharomyces cerevisiae.

    PubMed

    Bo, Tao; Liu, Miao; Zhong, Cheng; Zhang, Qian; Su, Qin-Zhi; Tan, Zhi-Lei; Han, Pei-Pei; Jia, Shi-Ru

    2014-05-14

    ε-Poly-L-lysine (ε-PL), a naturally occurring amino acid homopolymer, has been widely used as a food preservative. However, its antimicrobial mechanism has not been fully understood. This study investigated the antimicrobial mode of action of ε-PL on a yeast, Saccharomyces cerevisiae. When treated with ε-PL at the concentration of 500 μg/mL, cell mortality was close to 100% and the phospholipid bilayer curvature, pores, and micelles on the surface of S. cerevisiae were clearly observed by scanning electron microscopy (SEM). At the level of 200 μg/mL, ε-PL significantly inhibited the cell growth of S. cerevisiae. When treated with 50 μg/mL ε-PL, the yeast cell was able to grow but the cell cycle was prolonged. A significant increase in cell membrane permeability was induced by ε-PL at higher concentrations. Metabolomics analysis revealed that the ε-PL stress led to the inhibition of primary metabolic pathways through the suppression of the tricarboxylic acid cycle and glycolysis. It is therefore proposed that the microbiostatic effect of ε-PL at lower levels on S. cerevisiae is achieved by inducing intracellular metabolic imbalance via disruption of cell membrane functions. Moreover, the results suggested that the antimicrobial mechanism of ε-PL on S. cerevisiae can in fact change from microbiostatic to microbicidal when the concentration of ε-PL increased, and the mechanisms of these two modes of action were completely different.

  18. 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

  19. 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

  20. 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.

  1. An optimized method for NMR-based plant seed metabolomic analysis with maximized polar metabolite extraction efficiency, signal-to-noise ratio, and chemical shift consistency.

    PubMed

    Wu, Xiangyu; Li, Ning; Li, Hongde; Tang, Huiru

    2014-04-07

    Plant metabolomic analysis has become an essential part of functional genomics and systems biology and requires effective extraction of both primary and secondary metabolites from plant cells. To establish an optimized extraction method for the NMR-based analysis, we used the seeds of mungbean (Vigna radiata cv. Elü no. 1) as a model and systematically investigated the dependence of the metabolite composition in plant extracts on various extraction parameters including cell-breaking methods, extraction solvents, number of extraction repeats, tissue-to-solvent ratio, and extract-to-buffer ratio (for final NMR analysis). We also compared two NMR approaches for quantitative metabolomic analysis from completely relaxed spectra directly and from partially relaxed spectra calculated with T1. By maximizing the extraction efficiency and signal-to-noise ratio but minimizing inter-sample chemical-shift variations and metabolite degradations, we established a parameter-optimized protocol for NMR-based plant seed metabolomic analysis. We concluded that aqueous methanol was the best extraction solvent with an optimal tissue-to-solvent ratio of about 1 : 10-1 : 15 (mg per μL). The combination of tissuelyser homogenization with ultrasonication was the choice of cell-breaking method with three repeated extractions being necessary. For NMR analysis, the optimal extract-to-solvent was around 5-8 mg mL(-1) and completely relaxed spectra were ideal for intrinsically quantitative metabolomic analysis although partially relaxed spectra were employable for comparative metabolomics. This optimized method will offer ensured data quality for high-throughput and reliable plant metabolomics studies.

  2. 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...

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

    PubMed

    Huan, Tao; Li, Liang

    2015-07-21

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

  4. Renal cell carcinoma: a critical analysis of metabolomic biomarkers emerging from current model systems.

    PubMed

    Rodrigues, Daniela; Monteiro, Márcia; Jerónimo, Carmen; Henrique, Rui; Belo, Luís; Bastos, Maria de Lourdes; Guedes de Pinho, Paula; Carvalho, Márcia

    2017-02-01

    Metabolomics, an emerging field of "omics" sciences, has caught wide scientific attention in the area of biomarker research for cancers in which early diagnostic biomarkers have the potential to greatly improve patient outcome, such as renal cell carcinoma (RCC). Metabolomic approaches have been successfully applied to various human RCC model systems, mostly ex vivo neoplastic renal tissues and biofluids (urine and serum) from patients with RCC. Importantly, in contrast to other cancers, only a few studies have addressed the RCC metabolome using cancer cell culture-based in vitro models. Herein, we first carried out a comprehensive review of current metabolomic data in RCC, with emphasis on metabolite disturbances and dysregulated metabolic pathways identified in each of these experimental models. We then critically analyzed the consistency of evidence in this field and whether metabolites found altered in tumor cell and tissue microenvironment are reflected in biofluids, which constitute the rationale underlying the translation of discovered metabolic biomarkers into noninvasive diagnostic tools. Finally, dominant metabolic pathways and promising metabolites as biomarkers for diagnosis and prognosis of RCC are outlined.

  5. Proteomic and metabolomic analysis reveals rapid and extensive nicotine detoxification ability in honey bee larvae.

    PubMed

    du Rand, Esther E; Human, Hannelie; Smit, Salome; Beukes, Mervyn; Apostolides, Zeno; Nicolson, Susan W; Pirk, Christian W W

    2017-03-01

    Despite potential links between pesticides and bee declines, toxicology information on honey bee larvae (Apis mellifera) is scarce and detoxification mechanisms in this development stage are virtually unknown. Larvae are exposed to natural and synthetic toxins present in pollen and nectar through consumption of brood food. Due to the characteristic intensive brood care displayed by honey bees, which includes progressive feeding throughout larval development, it is generally assumed that larvae rely on adults to detoxify for them and exhibit a diminished detoxification ability. We found the opposite. We examined the proteomic and metabolomic responses of in vitro reared larvae fed nicotine (an alkaloid found in nectar and pollen) to understand how larvae cope on a metabolic level with dietary toxins. Larvae were able to effectively detoxify nicotine through an inducible detoxification mechanism. A coordinated stress response complemented the detoxification processes, and we detected significant enrichment of proteins functioning in energy and carbohydrate metabolism, as well as in development pathways, suggesting that nicotine may promote larval growth. Further exploration of the metabolic fate of nicotine using targeted mass spectrometry analysis demonstrated that, as in adult bees, formation of 4-hydroxy-4-(3-pyridyl) butanoic acid, the result of 2'C-oxidation of nicotine, is quantitatively the most significant pathway of nicotine metabolism. We provide conclusive evidence that larvae are capable of effectively catabolising a dietary toxin, suggesting that increased larval sensitivity to specific toxins is not due to diminished detoxification abilities. These findings broaden the current understanding of detoxification biochemistry at different organizational levels in the colony, bringing us closer to understanding the capacity of the colony as a superorganism to tolerate and resist toxic compounds, including pesticides, in the environment.

  6. Metabolomics-Based Analysis of Banana and Pear Ingestion on Exercise Performance and Recovery.

    PubMed

    Nieman, David C; Gillitt, Nicholas D; Sha, Wei; Meaney, Mary Pat; John, Casey; Pappan, Kirk L; Kinchen, Jason M

    2015-12-04

    Bananas and pears vary in sugar and phenolic profiles, and metabolomics was utilized to measure their influence on exercise performance and recovery. Male athletes (N = 20) cycled for 75 km while consuming water (WATER), bananas (BAN), or pears (PEAR) (0.6 g carbohydrate/kg each hour) in randomized order. UPLC-MS/MS and the library of purified standards maintained by Metabolon (Durham, NC) were used to analyze metabolite shifts in pre- and postexercise (0-h, 1.5-h, 21-h) blood samples. Performance times were 5.0% and 3.3% faster during BAN and PEAR versus WATER (P = 0.018 and P = 0.091, respectively), with reductions in cortisol, IL-10, and total leukocytes, and increases in blood glucose, insulin, and FRAP. Partial Least Square Discriminant Analysis (PLS-DA) showed a distinct separation between trials immediately (R(2)Y = 0.877, Q(2)Y = 0.457) and 1.5-h postexercise (R(2)Y = 0.773, Q(2)Y = 0.441). A total of 107 metabolites (primarily lipid-related) increased more than 2-fold during WATER, with a 48% and 52% reduction in magnitude during BAN and PEAR recovery (P < 0.001). Increases in metabolites unique to BAN and PEAR included fructose and fruit constituents, and sulfated phenolics that were related to elevated FRAP. These data indicate that BAN and PEAR ingestion improves 75-km cycling performance, attenuates fatty acid utilization and oxidation, and contributes unique phenolics that augment antioxidant capacity.

  7. Metabolomic Analysis of the Effects of Polychlorinated Biphenyls in Non-alcoholic Fatty Liver Disease

    PubMed Central

    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

    2012-01-01

    Polychlorinated Biphenyls (PCBs) are persistent organic pollutants and have been associated with abnormal liver enzymes and suspected non-alcoholic 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 co-exposure. The metabolite extracts from mouse livers were analyzed using linear trap quadruple - Fourier transform ion cyclotron resonance mass spectrometer (LTQ-FTICR MS) via direct infusion nano-electrospray 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

  8. Quantitative metabolomics analysis of amino acid metabolism in recombinant Pichia pastoris under different oxygen availability conditions

    PubMed Central

    2012-01-01

    Background Environmental and intrinsic stress factors can result in the global alteration of yeast physiology, as evidenced by several transcriptional studies. Hypoxia has been shown to have a beneficial effect on the expression of recombinant proteins in Pichia pastoris growing on glucose. Furthermore, transcriptional profiling analyses revealed that oxygen availability was strongly affecting ergosterol biosynthesis, central carbon metabolism and stress responses, in particular the unfolded protein response. To contribute to the better understanding of the effect and interplay of oxygen availability and foreign protein secretion on central metabolism, a first quantitative metabolomic analysis of free amino acids pools in a recombinant P. pastoris strain growing under different oxygen availability conditions has been performed. Results The values obtained indicate significant variations in the intracellular amino acid pools due to different oxygen availability conditions, showing an overall increase of their size under oxygen limitation. Notably, even while foreign protein productivities were relatively low (about 40–80 μg Fab/gDCW·h), recombinant protein production was found to have a limited but significant impact on the intracellular amino acid pools, which were generally decreased in the producing strain compared with the reference strain. However, observed changes in individual amino acids pools were not correlated with their corresponding relative abundance in the recombinant protein sequence, but to the overall cell protein amino acid compositional variations. Conclusions Overall, the results obtained, combined with previous transcriptomic and proteomic analyses provide a systematic metabolic fingerprint of the oxygen availability impact on recombinant protein production in P. pastoris. PMID:22704468

  9. Recent advances of metabolomics in plant biotechnology.

    PubMed

    Okazaki, Yozo; Saito, Kazuki

    2012-01-01

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

  10. Metabolomic and elemental analysis of camel and bovine urine by GC-MS and ICP-MS.

    PubMed

    Ahamad, Syed Rizwan; Alhaider, Abdul Qader; Raish, Mohammad; Shakeel, Faiyaz

    2017-01-01

    Recent studies from the author's laboratory indicated that camel urine possesses antiplatelet activity and anti-cancer activity which is not present in bovine urine. The objective of this study is to compare the volatile and elemental components of bovine and camel urine using GC-MS and ICP-MS analysis. We are interested to know the component that performs these biological activities. The freeze dried urine was dissolved in dichloromethane and then derivatization process followed by using BSTFA for GC-MS analysis. Thirty different compounds were analyzed by the derivatization process in full scan mode. For ICP-MS analysis twenty eight important elements were analyzed in both bovine and camel urine. The results of GC-MS and ICP-MS analysis showed marked difference in the urinary metabolites. GC-MS evaluation of camel urine finds a lot of products of metabolism like benzene propanoic acid derivatives, fatty acid derivatives, amino acid derivatives, sugars, prostaglandins and canavanine. Several research reports reveal the metabolomics studies on camel urine but none of them completely reported the pharmacology related metabolomics. The present data of GC-MS suggest and support the previous studies and activities related to camel urine.

  11. Benzyl butyl phthalate promotes adipogenesis in 3T3-L1 preadipocytes: A High Content Cellomics and metabolomic analysis.

    PubMed

    Yin, Lei; Yu, Kevin Shengyang; Lu, Kun; Yu, Xiaozhong

    2016-04-01

    Benzyl butyl phthalate (BBP) has been known to induce developmental and reproductive toxicity. However, its association with dysregulation of adipogenesis has been poorly investigated. The present study aimed to examine the effect of BBP on the adipogenesis, and to elucidate the underlying mechanisms using the 3T3-L1 cells. The capacity of BBP to promote adipogenesis was evaluated by multiple staining approaches combined with a High Content Cellomics analysis. The dynamic changes of adipogenic regulatory genes and proteins were examined, and the metabolite profile was identified using GC/MC based metabolomic analysis. The High Content analysis showed BBP in contrast with Bisphenol A (BPA), a known environmental obesogen, increased lipid droplet accumulation in a similar dose-dependent manner. However, the size of the lipid droplets in BBP-treated cells was significantly larger than those in cells treated with BPA. BBP significantly induced mRNA expression of transcriptional factors C/EBPα and PPARγ, their downstream genes, and numerous adipogenic proteins in a dose and time-dependent manner. Furthermore, GC/MC metabolomic analysis revealed that BBP exposure perturbed the metabolic profiles that are associated with glyceroneogenesis and fatty acid synthesis. Altogether, our current study clearly demonstrates that BBP promoted the differentiation of 3T3-L1 through the activation of the adipogenic pathway and metabolic disturbance.

  12. Comparative proteomic and metabolomic analysis of Streptomyces tsukubaensis reveals the metabolic mechanism of FK506 overproduction by feeding soybean oil.

    PubMed

    Wang, Jun; Liu, Huanhuan; Huang, Di; Jin, Lina; Wang, Cheng; Wen, Jianping

    2017-03-01

    FK506 (tacrolimus) is a 23-membered polyketide macrolide that possesses powerful immunosuppressant activity. In this study, feeding soybean oil into the fermentation culture of Streptomyces tsukubaensis improved FK506 production by 88.8%. To decipher the overproduction mechanism, comparative proteomic and metabolomic analysis was carried out. A total of 72 protein spots with differential expression in the two-dimensional gel electrophoresis (2-DE) were identified by matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF-MS), and 66 intracellular metabolites were measured by gas chromatography-mass spectrometer (GC-MS). The analysis of proteome and metabolome indicated that feeding soybean oil as a supplementary carbon source could not only strengthen the FK506 precursor metabolism and energy metabolism but also tune the pathways related to transcriptional regulation, translation, and stress response, suggesting a better intracellular metabolic environment for the synthesis of FK506. Based on these analyses, 20 key metabolites and precursors of FK506 were supplemented into the soybean oil medium. Among them, lysine, citric acid, shikimic acid, and malonic acid performed excellently for promoting the FK506 production and biomass. Especially, the addition of malonic acid achieved the highest FK506 production, which was 1.56-fold of that in soybean oil medium and 3.05-fold of that in initial medium. This report represented the first comprehensive study on the comparative proteomics and metabolomics applied in S. tsukubaensis, and it would be a rational guidance to further strengthen the FK506 production.

  13. Metabolomic analysis of rat serum in streptozotocin-induced diabetes and after treatment with oral triethylenetetramine (TETA)

    PubMed Central

    2012-01-01

    Background The prevalence, and associated healthcare burden, of diabetes mellitus is increasing worldwide. Mortality and morbidity are associated with diabetic complications in multiple organs and tissues, including the eye, kidney and cardiovascular system, and new therapeutics to treat these complications are required urgently. Triethylenetetramine (TETA) is one such experimental therapeutic that acts to chelate excess copper (II) in diabetic tissues and reduce oxidative stress and cellular damage. Methods Here we have performed two independent metabolomic studies of serum to assess the suitability of the streptozotocin (STZ)-induced rat model for studying diabetes and to define metabolite-related changes associated with TETA treatment. Ultraperformance liquid chromatography-mass spectrometry studies of serum from non-diabetic/untreated, non-diabetic/TETA-treated, STZ-induced diabetic/untreated and STZ-induced diabetic/TETA-treated rats were performed followed by univariate and multivariate analysis of data. Results Multiple metabolic changes related to STZ-induced diabetes, some of which have been reported previously in other animal and human studies, were observed, including changes in amino acid, fatty acid, glycerophospholipid and bile acid metabolism. Correlation analysis suggested that treatment with TETA led to a reversal of diabetes-associated changes in bile acid, fatty acid, steroid, sphingolipid and glycerophospholipid metabolism and proteolysis. Conclusions Metabolomic studies have shown that the STZ-induced rat model of diabetes is an appropriate model system to undertake research into diabetes and potential therapies as several metabolic changes observed in humans and other animal models were also observed in this study. Metabolomics has also identified several biological processes and metabolic pathways implicated in diabetic complications and reversed following treatment with the experimental therapeutic TETA. PMID:22546713

  14. Phytochemical diversity of cranberry (Vaccinium macrocarpon Aiton) cultivars by anthocyanin determination and metabolomic profiling with chemometric analysis.

    PubMed

    Brown, Paula N; Murch, Susan J; Shipley, Paul

    2012-01-11

    Originally native to the eastern United States, American cranberry ( Vaccinium macrocarpon Aiton, family Ericaceae) cultivation of native and hybrid varieties has spread across North America. Herein is reported the phytochemical diversity of five cranberry cultivars (Stevens, Ben Lear, Bergman, Pilgrim, and GH1) collected in the Greater Vancouver Regional District, by anthocyanin content and UPLC-TOF-MS metabolomic profiling. The anthocyanin content for biological replicates (n = 5) was determined as 7.98 ± 5.83, Ben Lear; 7.02 ± 1.75, Bergman; 6.05 ± 2.51, GH1; 3.28 ± 1.88, Pilgrim; and 2.81 ± 0.81, Stevens. Using subtractive metabonomic algorithms 6481 compounds were found conserved across all varietals, with 136 (Ben Lear), 84 (Bergman), 91 (GH1), 128 (Pilgrim), and 165 (Stevens) unique compounds observed. Principal component analysis (PCA) did not differentiate varieties, whereas partial least-squares discriminate analysis (PLS-DA) exhibited clustering patterns. Univariate statistical approaches were applied to the data set, establishing significance of values and assessing quality of the models. Metabolomic profiling with chemometric analysis proved to be useful for characterizing metabonomic changes across cranberry varieties.

  15. Development of a capillary electrophoresis-mass spectrometry method using polymer capillaries for metabolomic analysis of yeast.

    PubMed

    Tanaka, Yoshihide; Higashi, Tetsuji; Rakwal, Randeep; Wakida, Shin-ichi; Iwahashi, Hitoshi

    2008-05-01

    Metabolomics is an emerging field in analytical biochemistry, and the development of such a method for comprehensive and quantitative analysis of organic acids, carbohydrates, and nucleotides is a necessity in the era of functional genomics. When a concentrated yeast extract was analyzed by CE-MS using a successive multiple ionic-polymer layer (SMIL)-coated capillary, the adsorption of the contaminants on the capillary wall caused severe problems such as no elution, band-broadening, and asymmetric peaks. Therefore, an analytical method for the analysis of anionic metabolites in yeast was developed by pressure-assisted CE using an inert polymer capillary made from poly(ether etherketone) (PEEK) and PTFE. We preferred to use the PEEK over the PTFE capillary in CE-MS due to the easy-to-use PEEK capillary and its high durability. The separation of anionic metabolites was successfully achieved with ammonium hydrogencarbonate/formate buffer (pH 6.0) as the electrolyte solution. The use of 2-propanol washing after every electrophoresis run not only eliminated wall-adsorption phenomena, but allowed for good repeatability to be obtained for migration times in the metabolomic analysis.

  16. Quality evaluation and prediction of Citrullus lanatus by 1H NMR-based metabolomics and multivariate analysis.

    PubMed

    Tarachiwin, Lucksanaporn; Masako, Osawa; Fukusaki, Eiichiro

    2008-07-23

    (1)H NMR spectrometry in combination with multivariate analysis was considered to provide greater information on quality assessment over an ordinary sensory testing method due to its high reliability and high accuracy. The sensory quality evaluation of watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) was carried out by means of (1)H NMR-based metabolomics. Multivariate analyses by partial least-squares projections to latent structures-discrimination analysis (PLS-DA) and PLS-regression offered extensive information for quality differentiation and quality evaluation, respectively. The impact of watermelon and rootstock cultivars on the sensory qualities of watermelon was determined on the basis of (1)H NMR metabolic fingerprinting and profiling. The significant metabolites contributing to the discrimination were also identified. A multivariate calibration model was successfully constructed by PLS-regression with extremely high reliability and accuracy. Thus, (1)H NMR-based metabolomics with multivariate analysis was considered to be one of the most suitable complementary techniques that could be applied to assess and predict the sensory quality of watermelons and other horticultural plants.

  17. Pathway Analysis and Metabolites Identification by Metabolomics of Etiolation Substrate from Fresh-Cut Chinese Water Chestnut (Eleocharis tuberosa).

    PubMed

    Li, Yi-Xiao; Pan, Yong-Gui; He, Feng-Ping; Yuan, Meng-Qi; Li, Shang-Bin

    2016-12-01

    Fresh-cut Chinese water chestnuts (CWC) turn yellow after being peeled, reducing their shelf life and commercial value. Metabolomics, the systematic study of the full complement of small molecular metabolites, was useful for clarifying the mechanism of fresh-cut CWC etiolation and developing methods to inhibit yellowing. In this study, metabolic alterations associated with etiolation at different growth stages (0 day, 2 days, 3 days, 4 days, 5 days) from fresh-cut CWC were investigated using LC-MS and analyzed by pattern recognition methods (principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structures-discriminant analysis (OPLS-DA)). The metabolic pathways of the etiolation molecules were elucidated. The main metabolic pathway appears to be the conversion of phenylalanine to p-coumaroyl-CoA, followed by conversion to naringenin chalcone, to naringenin, and naringenin then following different pathways. Firstly, it can transform into apigenin and its derivatives; secondly, it can produce eriodictyol and its derivatives; and thirdly it can produce dihydrokaempferol, quercetin, and myricetin. The eriodictyol can be further transformed to luteolin, cyanidin, dihydroquercetin, dihydrotricetin, and others. This is the first reported use of metabolomics to study the metabolic pathways of the etiolation of fresh-cut CWC.

  18. Metabolomics in agriculture.

    PubMed

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

    2012-04-01

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

  19. 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.

  20. Analysis of the hibernation cycle using LC-MS-based metabolomics in ground squirrel liver.

    PubMed

    Nelson, Clark J; Otis, Jessica P; Martin, Sandra L; Carey, Hannah V

    2009-03-03

    A hallmark of hibernation in mammals is metabolic flexibility, which is typified by reversible bouts of metabolic depression (torpor) and the seasonal shift from predominantly carbohydrate to lipid metabolism from summer to winter. To provide new insight into the control and consequences of hibernation, we used LC/MS-based metabolomics to measure differences in small molecules in ground squirrel liver in five activity states: summer, entering torpor, late torpor, arousing from torpor, and interbout arousal. There were significant alterations both seasonally and within torpor-arousal cycles in enzyme cofactor metabolism, amino acid catabolism, and purine and pyrimidine metabolism, with observed metabolites reduced during torpor and increased upon arousal. Multiple lipids also changed, including 1-oleoyllysophosphatidylcholine, cholesterol sulfate, and sphingosine, which tended to be lowest during torpor, and hexadecanedioic acid, which accumulated during a torpor bout. The results reveal the dramatic alterations that occur in several classes of metabolites, highlighting the value of metabolomic analyses in deciphering the hibernation phenotype.

  1. 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.

  2. 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

  3. Metabolomic and Metagenomic Analysis of Two Crude Oil Production Pipelines Experiencing Differential Rates of Corrosion

    PubMed Central

    Bonifay, Vincent; Wawrik, Boris; Sunner, Jan; Snodgrass, Emily C.; Aydin, Egemen; Duncan, Kathleen E.; Callaghan, Amy V.; Oldham, Athenia; Liengen, Turid; Beech, Iwona

    2017-01-01

    Corrosion processes in two North Sea oil production pipelines were studied by analyzing pig envelope samples via metagenomic and metabolomic techniques. Both production systems have similar physico-chemical properties and injection waters are treated with nitrate, but one pipeline experiences severe corrosion and the other does not. Early and late pigging material was collected to gain insight into the potential causes for differential corrosion rates. Metabolites were extracted and analyzed via ultra-high performance liquid chromatography/high-resolution mass spectrometry with electrospray ionization (ESI) in both positive and negative ion modes. Metabolites were analyzed by comparison with standards indicative of aerobic and anaerobic hydrocarbon metabolism and by comparison to predicted masses for KEGG metabolites. Microbial community structure was analyzed via 16S rRNA gene qPCR, sequencing of 16S PCR products, and MySeq Illumina shotgun sequencing of community DNA. Metagenomic data were used to reconstruct the full length 16S rRNA genes and genomes of dominant microorganisms. Sequence data were also interrogated via KEGG annotation and for the presence of genes related to terminal electron accepting (TEA) processes as well as aerobic and anaerobic hydrocarbon degradation. Significant and distinct differences were observed when comparing the ‘high corrosion’ (HC) and the ‘low corrosion’ (LC) pipeline systems, especially with respect to the TEA utilization potential. The HC samples were dominated by sulfate-reducing bacteria (SRB) and archaea known for their ability to utilize simple carbon substrates, whereas LC samples were dominated by pseudomonads with the genetic potential for denitrification and aerobic hydrocarbon degradation. The frequency of aerobic hydrocarbon degradation genes was low in the HC system, and anaerobic hydrocarbon degradation genes were not detected in either pipeline. This is in contrast with metabolite analysis, which

  4. 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

    2016-02-05

    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.

  5. Metabolomic analysis of patient plasma yields evidence of plant-like α-linolenic acid metabolism in Plasmodium falciparum.

    PubMed

    Lakshmanan, Viswanathan; Rhee, Kyu Y; Wang, Wei; Yu, Yiting; Khafizov, Kamil; Fiser, Andras; Wu, Peng; Ndir, Omar; Mboup, Souleymane; Ndiaye, Daouda; Daily, Johanna P

    2012-07-15

    Metabolomics offers a powerful means to investigate human malaria parasite biology and host-parasite interactions at the biochemical level, and to discover novel therapeutic targets and biomarkers of infection. Here, we used an approach based on liquid chromatography and mass spectrometry to perform an untargeted metabolomic analysis of metabolite extracts from Plasmodium falciparum-infected and uninfected patient plasma samples, and from an enriched population of in vitro cultured P. falciparum-infected and uninfected erythrocytes. Statistical modeling robustly segregated infected and uninfected samples based on metabolite species with significantly different abundances. Metabolites of the α-linolenic acid (ALA) pathway, known to exist in plants but not known to exist in P. falciparum until now, were enriched in infected plasma and erythrocyte samples. In vitro labeling with (13)C-ALA showed evidence of plant-like ALA pathway intermediates in P. falciparum. Ortholog searches using ALA pathway enzyme sequences from 8 available plant genomes identified several genes in the P. falciparum genome that were predicted to potentially encode the corresponding enzymes in the hitherto unannotated P. falciparum pathway. These data suggest that our approach can be used to discover novel facets of host/malaria parasite biology in a high-throughput manner.

  6. 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

  7. 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

  8. Metabolomic changes during cellular transformation monitored by metabolite-metabolite correlation analysis and correlated with gene expression.

    PubMed

    Madhu, Basetti; Narita, Masako; Jauhiainen, Alexandra; Menon, Suraj; Stubbs, Marion; Tavaré, Simon; Narita, Masashi; Griffiths, John R

    To investigate metabolic changes during cellular transformation, we used a (1)H NMR based metabolite-metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite-metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome.

  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.

  10. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure

    PubMed Central

    Adkins, Daniel E.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Beardsley, Patrick M.; van den Oord, Edwin J. C. G.

    2012-01-01

    Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10−5, q = 0.013), tryptophan (p = 7.0 × 10−4, q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10−4, q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10−7). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10−4, q = 0.087) and ergothioneine (p = 3.0 × 10−4, q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects. PMID:23554582

  11. 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.

  12. Metabolomic analysis revealed that female mussel Mytilus galloprovincialis was sensitive to bisphenol A exposures.

    PubMed

    Ji, Chenglong; Wei, Lei; Zhao, Jianmin; Wu, Huifeng

    2014-03-01

    Bisphenol A (BPA) is a synthetic compound used in numerous chemicals, such as polycarbonate plastics and epoxy resins, and it can be released into aquatic environment and poses risk on aquatic organisms. In this work, metabolomics was applied to characterize the metabolic responses in mussel Mytilus galloprovincialis exposed to BPA. Our results indicated that the gonad of female mussel was sensitive to BPA exposures (1 and 10 μg/L) for one month. However, no significant metabolic responses were observed in male mussel gonads exposed to these two concentrations of BPA. Overall, this limited study suggested that the gender differences should be considered in marine ecotoxicology.

  13. 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.

  14. 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

  15. Normalization to specific gravity prior to analysis improves information recovery from high resolution mass spectrometry metabolomic profiles of human urine.

    PubMed

    Edmands, William M B; Ferrari, Pietro; Scalbert, Augustin

    2014-11-04

    Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets.

  16. 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.

  17. Integrated analysis of transcriptome and metabolome of Arabidopsis albino or pale green mutants with disrupted nuclear-encoded chloroplast proteins.

    PubMed

    Satou, Masakazu; Enoki, Harumi; Oikawa, Akira; Ohta, Daisaku; Saito, Kazunori; Hachiya, Takushi; Sakakibara, Hitoshi; Kusano, Miyako; Fukushima, Atsushi; Saito, Kazuki; Kobayashi, Masatomo; Nagata, Noriko; Myouga, Fumiyoshi; Shinozaki, Kazuo; Motohashi, Reiko

    2014-07-01

    We used four mutants having albino or pale green phenotypes with disrupted nuclear-encoded chloroplast proteins to analyze the regulatory system of metabolites in chloroplast. We performed an integrated analyses of transcriptomes and metabolomes of the four mutants. Transcriptome analysis was carried out using the Agilent Arabidopsis 2 Oligo Microarray, and metabolome analysis with two mass spectrometers; a direct-infusion Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR/MS) and a gas chromatograph-time of flight mass spectrometer. Among approximately 200 known metabolites detected by the FT-ICR/MS, 71 metabolites showed significant changes in the mutants when compared with controls (Ds donor plants). Significant accumulation of several amino acids (glutamine, glutamate and asparagine) was observed in the albino and pale green mutants. Transcriptome analysis revealed altered expressions of genes in several metabolic pathways. For example, genes involved in the tricarboxylic acid cycle, the oxidative pentose phosphate pathway, and the de novo purine nucleotide biosynthetic pathway were up-regulated. These results suggest that nitrogen assimilation is constitutively promoted in the albino and pale green mutants. The accumulation of ammonium ions in the albino and pale green mutants was consistently higher than in Ds donor lines. Furthermore, genes related to pyridoxin accumulation and the de novo purine nucleotide biosynthetic pathway were up-regulated, which may have occurred as a result of the accumulation of glutamine in the albino and pale green mutants. The difference in metabolic profiles seems to be correlated with the disruption of chloroplast internal membrane structures in the mutants. In albino mutants, the alteration of metabolites accumulation and genes expression is stronger than pale green mutants.

  18. Systematic analysis of the polyphenol metabolome using the Phenol‐Explorer database

    PubMed Central

    Rothwell, Joseph A.; Urpi‐Sarda, Mireia; Boto‐Ordoñez, Maria; Llorach, Rafael; Farran‐Codina, Andreu; Barupal, Dinesh Kumar; Neveu, Vanessa; Manach, Claudine; Andres‐Lacueva, Cristina

    2016-01-01

    Scope The Phenol‐Explorer web database details 383 polyphenol metabolites identified in human and animal biofluids from 221 publications. Here, we exploit these data to characterize and visualize the polyphenol metabolome, the set of all metabolites derived from phenolic food components. Methods and results Qualitative and quantitative data on 383 polyphenol metabolites as described in 424 human and animal intervention studies were systematically analyzed. Of these metabolites, 301 were identified without prior enzymatic hydrolysis of biofluids, and included glucuronide and sulfate esters, glycosides, aglycones, and O‐methyl ethers. Around one‐third of these compounds are also known as food constituents and corresponded to polyphenols absorbed without further metabolism. Many ring‐cleavage metabolites formed by gut microbiota were noted, mostly derived from hydroxycinnamates, flavanols, and flavonols. Median maximum plasma concentrations (C max) of all human metabolites were 0.09 and 0.32 μM when consumed from foods or dietary supplements, respectively. Median time to reach maximum plasma concentration in humans (T max) was 2.18 h. Conclusion These data show the complexity of the polyphenol metabolome and the need to take into account biotransformations to understand in vivo bioactivities and the role of dietary polyphenols in health and disease. PMID:26310602

  19. Analysis of metabolomics datasets with high-performance computing and metabolite atlases

    DOE PAGES

    Yao, Yushu; Sun, Terence; Wang, Tony; ...

    2015-07-20

    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 formore » future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, 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.« less

  20. Analysis of metabolomics datasets with high-performance computing and metabolite atlases

    SciTech Connect

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

    2015-07-20

    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. Furthermore, 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.

  1. Metabolomics: a second-generation platform for crop and food analysis.

    PubMed

    Shepherd, Louise Vt; Fraser, Paul; Stewart, Derek

    2011-05-01

    The combined factors of financial and food security, a rapidly increasing population and the associated requirement for food generated sustainably in a changing environment have brought food swiftly to the top of most government agendas. The consequence of this is that we need to produce more food at an equivalent or higher quality with lower inputs. These aims are achievable using conventional breeding, but not in the required timelines, and thus state-of-the-art genetic and analytical technologies are coming to the forefront. The concept of metabolomics, underpinned by mainstream (GC-MS, LC-MS, NMR) and specialist (MALDI-TOF-MS) analytical technologies addressing broad chemical (class) targets and dynamic ranges, offers significant potential to add significant value to crop and food science and deliver on future food demands. Metabolomics has now found a home in the food analytical toolbox with raw material quality and safety the major quality areas, although, as we will show, it is translating beyond this into food storage, shelf-life and post-harvest processing.

  2. 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

  3. 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

  4. Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum

    PubMed Central

    Faijes, Magda; Mars, Astrid E; Smid, Eddy J

    2007-01-01

    Background A reliable quenching and metabolite extraction method has been developed for Lactobacillus plantarum. The energy charge value was used as a critical indicator for fixation of metabolism. Results Four different aqueous quenching solutions, all containing 60% of methanol, were compared for their efficiency. Only the solutions containing either 70 mM HEPES or 0.85% (w/v) ammonium carbonate (pH 5.5) caused less than 10% cell leakage and the energy charge of the quenched cells was high, indicating rapid inactivation of the metabolism. The efficiency of extraction of intracellular metabolites from cell cultures depends on the extraction methods, and is expected to vary between micro-organisms. For L. plantarum, we have compared five different extraction methodologies based on (i) cold methanol, (ii) perchloric acid, (iii) boiling ethanol, (iv) chloroform/methanol (1:1) and (v) chloroform/water (1:1). Quantification of representative intracellular metabolites showed that the best extraction efficiencies were achieved with cold methanol, boiling ethanol and perchloric acid. Conclusion The ammonium carbonate solution was selected as the most suitable quenching buffer for metabolomics studies in L. plantarum because (i) leakage is minimal, (ii) the energy charge indicates good fixation of metabolism, and (iii) all components are easily removed during freeze-drying. A modified procedure based on cold methanol extraction combined good extractability with mild extraction conditions and high enzymatic inactivation. These features make the combination of these quenching and extraction protocols very suitable for metabolomics studies with L. plantarum. PMID:17708760

  5. A Metabolomic Perspective on Coeliac Disease

    PubMed Central

    Calabrò, Antonio

    2014-01-01

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

  6. Study of exhaled breath condensate sample preparation for metabolomics analysis by LC-MS/MS in high resolution mode.

    PubMed

    Fernández-Peralbo, M A; Calderón Santiago, M; Priego-Capote, F; Luque de Castro, M D

    2015-11-01

    Metabolomic analysis of exhaled breath condensate (EBC) requires an unavoidable sample preparation step because of the low concentration of its components, and potential cleanup for possible interferents. Sample preparation based on protein precipitation (PP), solid-phase extraction (SPE) by hydrophilic and lipophilic sorbents or lyophilization has demonstrated that the analytical sample from the last is largely the best because lyophilization allows reconstitution in a volume as small as required (preconcentration factors up to 80-times with respect to the original sample), thus doubling the number of detected compounds as compared with the other alternatives (47 versus 25). In addition, PP and/or SPE cleanup are unnecessary as no effect from the EBC components removed by these steps appears in the chromatograms. The total 49 EBC compounds tentatively identified and confirmed by MS/MS in this research include amino acids, fatty acids, fatty amides, fatty aldehydes, sphingoid bases, oxoanionic compounds, imidazoles, hydroxy acids and aliphatic acyclic acids.

  7. The Human Urine Metabolome

    PubMed Central

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

    2013-01-01

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

  8. Dietary intake and plasma metabolomic analysis of polyunsaturated fatty acids in bipolar subjects reveal dysregulation of linoleic acid metabolism.

    PubMed

    Evans, Simon J; Ringrose, Rachel N; Harrington, Gloria J; Mancuso, Peter; Burant, Charles F; McInnis, Melvin G

    2014-10-01

    Polyunsaturated fatty acids (PUFA) profiles associate with risk for mood disorders. This poses the hypothesis of metabolic differences between patients and unaffected healthy controls that relate to the primary illness or are secondary to medication use or dietary intake. However, dietary manipulation or supplementation studies show equivocal results improving mental health outcomes. This study investigates dietary patterns and metabolic profiles relevant to PUFA metabolism, in bipolar I individuals compared to non-psychiatric controls. We collected seven-day diet records and performed metabolomic analysis of fasted plasma collected immediately after diet recording. Regression analyses adjusted for age, gender and energy intake found that bipolar individuals had significantly lower intake of selenium and PUFAs, including eicosapentaenoic acid (EPA) (n-3), docosahexaenoic acid (DHA) (n-3), arachidonic acid (AA) (n-6) and docosapentaenoic acid (DPA) (n-3/n-6 mix); and significantly increased intake of the saturated fats, eicosanoic and docosanoic acid. Regression analysis of metabolomic data derived from plasma samples, correcting for age, gender, BMI, psychiatric medication use and dietary PUFA intake, revealed that bipolar individuals had reduced 13S-HpODE, a major peroxidation product of the n-6, linoleic acid (LA), reduced eicosadienoic acid (EDA), an elongation product of LA; reduced prostaglandins G2, F2 alpha and E1, synthesized from n-6 PUFA; and reduced EPA. These observations remained significant or near significant after Bonferroni correction and are consistent with metabolic variances between bipolar and control individuals with regard to PUFA metabolism. These findings suggest that specific dietary interventions aimed towards correcting these metabolic disparities may impact health outcomes for individuals with bipolar disorder.

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

    DOE PAGES

    Kim, Young-Mo; Nowack, Shane; Olsen, Millie; ...

    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

  10. Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships

    PubMed Central

    2013-01-01

    Background Consistent compositional shifts in the gut microbiota are observed in IBD and other chronic intestinal disorders and may contribute to pathogenesis. The identities of microbial biomolecular mechanisms and metabolic products responsible for disease phenotypes remain to be determined, as do the means by which such microbial functions may be therapeutically modified. Results The composition of the microbiota and metabolites in gut microbiome samples in 47 subjects were determined. Samples were obtained by endoscopic mucosal lavage from the cecum and sigmoid colon regions, and each sample was sequenced using the 16S rRNA gene V4 region (Illumina-HiSeq 2000 platform) and assessed by UPLC mass spectroscopy. Spearman correlations were used to identify widespread, statistically significant microbial-metabolite relationships. Metagenomes for identified microbial OTUs were imputed using PICRUSt, and KEGG metabolic pathway modules for imputed genes were assigned using HUMAnN. The resulting metabolic pathway abundances were mostly concordant with metabolite data. Analysis of the metabolome-driven distribution of OTU phylogeny and function revealed clusters of clades that were both metabolically and metagenomically similar. Conclusions The results suggest that microbes are syntropic with mucosal metabolome composition and therefore may be the source of and/or dependent upon gut epithelial metabolites. The consistent relationship between inferred metagenomic function and assayed metabolites suggests that metagenomic composition is predictive to a reasonable degree of microbial community metabolite pools. The finding that certain metabolites strongly correlate with microbial community structure raises the possibility of targeting metabolites for monitoring and/or therapeutically manipulating microbial community function in IBD and other chronic diseases. PMID:24450808

  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. 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

  13. 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

  14. 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

  15. 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.

  16. 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

    2015-09-02

    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.

  17. Metabolomics for salinity research.

    PubMed

    Roessner, Ute; Beckles, Diane M

    2012-01-01

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

  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

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

    2013-08-27

    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.

  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.

  1. 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

  2. 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

  3. Ultraperformance liquid chromatography-mass spectrometry based comprehensive metabolomics combined with pattern recognition and network analysis methods for characterization of metabolites and metabolic pathways from biological data sets.

    PubMed

    Zhang, Ai-hua; Sun, Hui; Han, Ying; Yan, Guang-li; Yuan, Ye; Song, Gao-chen; Yuan, Xiao-xia; Xie, Ning; Wang, Xi-jun

    2013-08-06

    Metabolomics is the study of metabolic changes in biological systems and provides the small molecule fingerprints related to the disease. Extracting biomedical information from large metabolomics data sets by multivariate data analysis is of considerable complexity. Therefore, more efficient and optimizing metabolomics data processing technologies are needed to improve mass spectrometry applications in biomarker discovery. Here, we report the findings of urine metabolomic investigation of hepatitis C virus (HCV) patients by high-throughput ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) coupled with pattern recognition methods (principal component analysis, partial least-squares, and OPLS-DA) and network pharmacology. A total of 20 urinary differential metabolites (13 upregulated and 7 downregulated) were identified and contributed to HCV progress, involve several key metabolic pathways such as taurine and hypotaurine metabolism, glycine, serine and threonine metabolism, histidine metabolism, arginine and proline metabolism, and so forth. Metabolites identified through metabolic profiling may facilitate the development of more accurate marker algorithms to better monitor disease progression. Network analysis validated close contact between these metabolites and implied the importance of the metabolic pathways. Mapping altered metabolites to KEGG pathways identified alterations in a variety of biological processes mediated through complex networks. These findings may be promising to yield a valuable and noninvasive tool that insights into the pathophysiology of HCV and to advance the early diagnosis and monitor the progression of disease. Overall, this investigation illustrates the power of the UPLC-MS platform combined with the pattern recognition and network analysis methods that can engender new insights into HCV pathobiology.

  4. 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.

  5. 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

  6. 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

  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.

  8. 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.

  9. Metabolomic analysis indicates a pivotal role of the hepatotoxin microcystin in high light adaptation of Microcystis.

    PubMed

    Meissner, Sven; Steinhauser, Dirk; Dittmann, Elke

    2015-05-01

    Microcystis is a freshwater cyanobacterium frequently forming nuisance blooms in the summer months. The genus belongs to the predominant producers of the potent hepatotoxin microcystin. The success of Microcystis and its remarkable resistance to high light conditions are not well understood. Here, we have compared the metabolic response of Microcystis aeruginosa PCC7806, its microcystin-deficient ΔmcyB mutant (Mut) and the cyanobacterial model organism Synechocystis PCC6803 to high light exposure of 250 μmol photons m(-2)  s(-1) using GC/MS-based metabolomics. Microcystis wild type and Mut show pronounced differences in their metabolic reprogramming upon high light. Seventeen per cent of the detected metabolites showed significant differences between the two genotypes after high light exposure. Whereas the microcystin-producing wild type shows a faster accumulation of glycolate upon high light illumination, loss of microcystin leads to an accumulation of general stress markers such as trehalose and sucrose. The study further uncovers differences in the high light adaptation of the bloom-forming cyanobacterium Microcystis and the model cyanobacterium Synechocystis. Most notably, Microcystis invests more into carbon reserves such as glycogen after high light exposure. Our data shed new light on the lifestyle of bloom-forming cyanobacteria, the role of the widespread toxin microcystin and the metabolic diversity of cyanobacteria.

  10. 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

    2015-02-06

    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.

  11. Metabolomic analysis of citrus infection by 'Candidatus Liberibacter' reveals insight into pathogenicity.

    PubMed

    Slisz, Anne M; Breksa, Andrew P; Mishchuk, Darya O; McCollum, Greg; Slupsky, Carolyn M

    2012-08-03

    Huanglongbing (HLB), considered the most serious citrus disease in the world, is associated with the nonculturable bacterium 'Candidatus Liberibacter asiaticus' (Las). Infection of citrus by this pathogen leads to reduced plant vigor and productivity, ultimately resulting in death of the infected tree. It can take up to two years following initial infection before outward symptoms become apparent, making detection difficult. The existing knowledge gap in our understanding of Las and its pathogenesis leading to HLB has stymied development of treatments and methods to mitigate the pathogen's influence. To evaluate the influence of Las on fruit quality in both symptomatic and asymptomatic fruit, and gain further insight into the pathogenesis of the disease, a 1H NMR metabolomics investigation, complemented with physicochemical and analyte-specific analyses, was undertaken. Comparison of the juice obtained from oranges gathered from Las+ (symptomatic and asymptomatic) and Las- (healthy) trees revealed significant differences in the concentrations of sugars, amino and organic acids, limonin glucoside, and limonin. This study demonstrates differing metabolic profiles in the juice of oranges from Las+ and Las- and proposes how Las may be able to evade citrus defense responses.

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

    PubMed

    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.

  13. 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

  14. 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.

  15. 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.

  16. Metabolome analysis reveals the effect of carbon catabolite control on the poly(γ-glutamic acid) biosynthesis of Bacillus licheniformis ATCC 9945.

    PubMed

    Mitsunaga, Hitoshi; Meissner, Lena; Palmen, Thomas; Bamba, Takeshi; Büchs, Jochen; Fukusaki, Eiichiro

    2016-04-01

    Poly(γ-glutamic acid) (PGA) is a polymer composed of L- and/or D-glutamic acids that is produced by Bacillus sp. Because the polymer has various features as water soluble, edible, non-toxic and so on, it has attracted attention as a candidate for many applications such as foods, cosmetics and so on. However, although it is well known that the intracellular metabolism of Bacillus sp. is mainly regulated by catabolite control, the effect of the catabolite control on the PGA producing Bacillus sp. is largely unknown. This study is the first report of metabolome analysis on the PGA producing Bacillus sp. that reveals the effect of carbon catabolite control on the metabolism of PGA producing Bacillus licheniformis ATCC 9945. Results showed that the cells cultivated in glycerol-containing medium showed higher PGA production than the cells in glucose-containing medium. Furthermore, metabolome analysis revealed that the activators of CcpA and CodY, global regulatory proteins of the intracellular metabolism, accumulated in the cells cultivated in glycerol-containing and glucose-containing medium, respectively, with CodY apparently inhibiting PGA production. Moreover, the cells seemed to produce glutamate from citrate and ammonium using glutamine synthetase/glutamate synthase. Pulsed addition of di-ammonium hydrogen citrate, as suggested by the metabolome result, was able to achieve the highest value so far for PGA production in B. licheniformis.

  17. Optimization of Huang-Lian-Jie-Du-Decoction for Ischemic Stroke Treatment and Mechanistic Study by Metabolomic Profiling and Network Analysis

    PubMed Central

    Zhang, Qian; Wang, Junsong; Liao, Shanting; Li, Pei; Xu, Dingqiao; Lv, Yan; Yang, Minghua; Kong, Lingyi

    2017-01-01

    Optimal drug proportions and mechanism deciphering of multicomponent drugs are critical for developing novel therapies to cope with complex diseases, such as stroke. In the present study, orthogonal experimental design was applied to explore the optimal proportion of the four component herbs in Huang-Lian-Jie-Du-Decoction (HLJDD) on the treatment of ischemic stroke. The treatment efficacies and mechanisms were assessed using global and amino acids (AAs) targeted metabolomics, as well as correlation network analysis. The global NMR metabolomics results revealed that AAs metabolism was significantly perturbed in middle cerebral artery occlusion rats. The levels of 23 endogenous AAs were then subjected to HPLC-QTOF-MS/MS analysis. These results complemented with neurobehavioral evaluations, cerebral infarct assessments, biochemical evaluations, histological inspections and immunohistochemistry observations strongly demonstrated that HLJDD with optimal proportion of 6 (Rhizoma coptidis): 4 (Radix scutellariae): 1 (Cortex phellodendr): 3 (Fructus Gardeniae) had the best efficacy on ischemic stroke, which could be ascribed to its modulation on AA metabolism. This integrated metabolomics approach showed the potential and applicable in deciphering the complex mechanisms of traditional Chinese medicine formulae on the treatment of complicated diseases, which provided new means to assess the treatment effects of herb combinations and to further development of drugs or therapies based on these formulae.

  18. Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

    PubMed Central

    Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

    2016-01-01

    The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34–80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics. PMID:28000704

  19. Microbiome-metabolome analysis reveals unhealthy alterations in the composition and metabolism of ruminal microbiota with increasing dietary grain in a goat model.

    PubMed

    Mao, Sheng-Yong; Huo, Wen-Jie; Zhu, Wei-Yun

    2016-02-01

    Currently, knowledge about the impact of high-grain (HG) feeding on rumen microbiota and metabolome is limited. In this study, a combination of the 454 pyrosequencing strategy and the mass spectrometry-based metabolomics technique was applied to investigate the effects of increased dietary grain (0%, 25% and 50% maize grain) on changes in whole ruminal microbiota and their metabolites using goat as a ruminant model. We observed a significant influence of HG feeding in shaping the ruminal bacterial community structure, diversity and composition, with an overall dominance of bacteria of the phylum Firmicutes along with a low abundance of Bacteriodetes in the HG group. High-grain feeding increased the number of ciliate and methanogens, and decreased the density of anaerobic fungi and the richness of the archaeal community. The metabolomics analysis revealed that HG feeding increased the levels of several toxic, inflammatory and unnatural compounds, including endotoxin, tryptamine, tyramine, histamine and phenylacetate. Correlation analysis on the combined datasets revealed some potential relationships between ruminal metabolites and certain microbial species. Information about these relationships may prove useful in either direct (therapeutic) or indirect (dietary) interventions for ruminal disorders due to microbial compositional shifts, such as ruminal acidosis.

  20. Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

    NASA Astrophysics Data System (ADS)

    Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

    2016-12-01

    The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34–80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics.

  1. Optimization study for metabolomics analysis of human sweat by liquid chromatography-tandem mass spectrometry in high resolution mode.

    PubMed

    Calderón-Santiago, M; Priego-Capote, F; Jurado-Gámez, B; Luque de Castro, M D

    2014-03-14

    Sweat has recently gained popularity as a potential tool for diagnostics and biomarker monitoring as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis, which increases chloride levels in sweat. The aim of the present study was to develop an analytical method for analysis of human sweat by liquid chromatography-mass spectrometry (LC-Q-TOF MS/MS) in high resolution mode. Thus, different sample preparation strategies and different chromatographic modes (HILIC and C18 reverse modes) were compared to check their effect on the profile of sweat metabolites. Forty-one compounds were identified by the MS/MS information obtained with a mass tolerance window below 4 ppm. Amino acids, dicarboxylic acids and other interesting metabolites such as inosine, choline, uric acid and tyramine were identified. Among the tested protocols, direct analysis after dilution was a suited option to obtain a representative snapshot of sweat metabolome. In addition, sample clean up by C18 SpinColumn SPE cartridges improved the sensitivity of most identified compounds and reduced the number of interferents. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders.

  2. Integrated Physiological, Proteomic, and Metabolomic Analysis of Ultra Violet (UV) Stress Responses and Adaptation Mechanisms in Pinus radiata.

    PubMed

    Pascual, Jesús; Cañal, María Jesús; Escandón, Mónica; Meijón, Mónica; Weckwerth, Wolfram; Valledor, Luis

    2017-03-01

    Globally expected changes in environmental conditions, especially the increase of UV irradiation, necessitate extending our knowledge of the mechanisms mediating tree species adaptation to this stress. This is crucial for designing new strategies to maintain future forest productivity. Studies focused on environmentally realistic dosages of UV irradiation in forest species are scarce. Pinus spp. are commercially relevant trees and not much is known about their adaptation to UV. In this work, UV treatment and recovery of Pinus radiata plants with dosages mimicking future scenarios, based on current models of UV radiation, were performed in a time-dependent manner. The combined metabolome and proteome analysis were complemented with measurements of + physiological parameters and gene expression. Sparse PLS analysis revealed complex molecular interaction networks of molecular and physiological data. Early responses prevented phototoxicity by reducing photosystem activity and the electron transfer chain together with the accumulation of photoprotectors and photorespiration. Apart from the reduction in photosynthesis as consequence of the direct UV damage on the photosystems, the primary metabolism was rearranged to deal with the oxidative stress while minimizing ROS production. New protein kinases and proteases related to signaling, coordination, and regulation of UV stress responses were revealed. All these processes demonstrate a complex molecular interaction network extending the current knowledge on UV-stress adaptation in pine.

  3. Integrated proteomic and metabolomic analysis of larval brain associated with diapause induction and preparation in the cotton bollworm, Helicoverpa armigera.

    PubMed

    Zhang, Qi; Lu, Yu-Xuan; Xu, Wei-Hua

    2012-02-03

    Diapause is a developmental arrest that allows an organism to survive unfavorable environmental conditions and is induced by environmental signals at a certain sensitive developmental stage. In Helicoverpa armigera, the larval brain receives the environmental signals for diapause induction and then regulates diapause entry at the pupal stage. Here, combined proteomic and metabolomic differential display analysis was performed on the H. armigera larval brain. Using two-dimensional electrophoresis, it was found that 22 proteins were increased and 27 proteins were decreased in the diapause-destined larval brain, 37 of which were successfully identified by MALDI-TOF/TOF mass spectrometry. RT-PCR and Western blot analyses showed that the expression levels of the differentially expressed proteins were consistent with the 2-DE results. Furthermore, a total of 49 metabolites were identified in the larval brain by GC-MS analysis, including 4 metabolites at high concentrations and 14 metabolites at low concentrations. The results gave us a clue to understand the governing molecular events of the prediapause phase. Those differences that exist in the induction phase of diapause-destined individuals are probably relevant to a special memory mechanism for photoperiodic information storage, and those differences that exist in the preparation phase are likely to regulate accumulation of specific energy reserves in diapause-destined individuals.

  4. Development of bottom-fermenting saccharomyces strains that produce high SO2 levels, using integrated metabolome and transcriptome analysis.

    PubMed

    Yoshida, Satoshi; Imoto, Jun; Minato, Toshiko; Oouchi, Rie; Sugihara, Mao; Imai, Takeo; Ishiguro, Tatsuji; Mizutani, Satoru; Tomita, Masaru; Soga, Tomoyoshi; Yoshimoto, Hiroyuki

    2008-05-01

    Sulfite plays an important role in beer flavor stability. Although breeding of bottom-fermenting Saccharomyces strains that produce high levels of SO(2) is desirable, it is complicated by the fact that undesirable H(2)S is produced as an intermediate in the same pathway. Here, we report the development of a high-level SO(2)-producing bottom-fermenting yeast strain by integrated metabolome and transcriptome analysis. This analysis revealed that O-acetylhomoserine (OAH) is the rate-limiting factor for the production of SO(2) and H(2)S. Appropriate genetic modifications were then introduced into a prototype strain to increase metabolic fluxes from aspartate to OAH and from sulfate to SO(2), resulting in high SO(2) and low H(2)S production. Spontaneous mutants of an industrial strain that were resistant to both methionine and threonine analogs were then analyzed for similar metabolic fluxes. One promising mutant produced much higher levels of SO(2) than the parent but produced parental levels of H(2)S.

  5. Metabolomic Analysis Reveals Cyanidins in Black Raspberry as Candidates for Suppression of Lipopolysaccharide-Induced Inflammation in Murine Macrophages.

    PubMed

    Jo, Young-Hee; Park, Hyun-Chang; Choi, Seulgi; Kim, Sugyeong; Bao, Cheng; Kim, Hyung Woo; Choi, Hyung-Kyoon; Lee, Hong Jin; Auh, Joong-Hyuck

    2015-06-10

    The extracts produced by multisolvent extraction and subfractionation with preparative liquid chromatography of black raspberry (Rubus coreanus Miquel) cultivated in Gochang, South Korea, were tested for their anti-inflammatory effects. The metabolomic profiling and analysis by orthogonal partial least-squares discriminant analysis (OLPS-DA) suggested that cyanidin, cyanidin-3-glucoside (C3G), and cyanidin-3-rutinoside (C3R) were key components for the anti-inflammatory responses in the most active fraction BF3-1, where they were present at 0.44, 1.26, and 0.56 μg/mg of BF3-1, respectively. Both BF3-1 and mixture of these cyanidins at the same ratio reduced lipopolysaccharide (LPS)-induced protein level of iNOS expression and suppressed mRNA and protein expressions of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β through inhibiting the phosphorylation of mitogen-activated protein kinases (MAPKs) and STAT3 in murine macrophage RAW264.7 cells. Overall, the results suggested that co-administration of cyanidin, C3G, and C3R is more effective than that of cyanidin alone and that the coexistence of these anthocyanin components in black raspberry plays a vital role in regulating LPS-induced inflammation even at submicromolar concentrations, making it possible to explain the health beneficial activity of its extracts.

  6. Metabolomics Analysis Reveals that AICAR Affects Glycerolipid, Ceramide and Nucleotide Synthesis Pathways in INS-1 Cells.

    PubMed

    ElAzzouny, Mahmoud A; Evans, Charles R; Burant, Charles F; Kennedy, Robert T

    2015-01-01

    AMPK regulates many metabolic pathways including fatty acid and glucose metabolism, both of which are closely associated with insulin secretion in pancreatic β-cells. Insulin secretion is regulated by metabolic coupling factors such as ATP/ADP ratio and other metabolites generated by the metabolism of nutrients such as glucose, fatty acid and amino acids. However, the connection between AMPK activation and insulin secretion in β-cells has not yet been fully elucidated at a metabolic level. To study the effect of AMPK activation on glucose stimulated insulin secretion, we applied the pharmacological activator 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) to an INS-1 (832/13) β-cell line. We measured the change in 66 metabolites in the presence or absence of AICAR using different stable isotopic labeled nutrients to probe selected pathways. AMPK activation by AICAR increased basal insulin secretion and reduced the glucose stimulation index. Although ATP/ADP ratios were not strongly affected by AICAR, several other metabolites and pathways important for insulin secretion were affected by AICAR treatment including long-chain CoAs, malonyl-CoA, 3-hydroxy-3 methylglutaryl CoA, diacylglycerol, and farnesyl pyrophosphate. Tracer studies using 13C-glucose revealed lower glucose flux in the purine and pyrimidine pathway and in the glycerolipid synthesis pathway. Untargeted metabolomics revealed reduction in ceramides caused by AICAR that may explain the beneficial role of AMPK in protecting β-cells from lipotoxicity. Taken together, the results provide an overall picture of the metabolic changes associated with AICAR treatment and how it modulates insulin secretion and β-cell survival.

  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. Cancer Metabolomics and the Human Metabolome Database.

    PubMed

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

    2016-03-02

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

  9. 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.

  10. 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.

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

    DOE PAGES

    Webb-Robertson, Bobbie-Jo; Kim, Young -Mo; Zink, Erika M.; ...

    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

  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. Supervised Semi-Automated Data Analysis Software for Gas Chromatography / Differential Mobility Spectrometry (GC/DMS) Metabolomics Applications.

    PubMed

    Peirano, Daniel J; Pasamontes, Alberto; Davis, Cristina E

    2016-09-01

    Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

  14. 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

  15. 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

    2013-11-06

    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.

  16. GC-MS metabolomic analysis reveals significant alterations in cerebellar metabolic physiology in a mouse model of adult onset hypothyroidism.

    PubMed

    Constantinou, Caterina; Chrysanthopoulos, Panagiotis K; Margarity, Marigoula; Klapa, Maria I

    2011-02-04

    Although adult-onset hypothyroidism (AOH) has been connected to neural activity alterations, including movement, behavioral, and mental dysfunctions, the underlying changes in brain metabolic physiology have not been investigated in a systemic and systematic way. The current knowledge remains fragmented, referring to different experimental setups and recovered from various brain regions. In this study, we developed and applied a gas chromatography-mass spectrometry (GC-MS) metabolomics protocol to obtain a holistic view of the cerebellar metabolic physiology in a Balb/cJ mouse model of prolonged adult-onset hypothyroidism induced by a 64-day treatment with 1% potassium perchlorate in the drinking water of the animals. The high-throughput analysis enabled the correlation between multiple parallel-occurring metabolic phenomena; some have been previously related to AOH, while others implicated new pathways, designating new directions for further research. Specifically, an overall decline in the metabolic activity of the hypothyroid compared to the euthyroid cerebellum was observed, characteristically manifested in energy metabolism, glutamate/glutamine metabolism, osmolytic/antioxidant capacity, and protein/lipid synthesis. These alterations provide strong evidence that the mammalian cerebellum is metabolically responsive to AOH. In light of the cerebellum core functions and its increasingly recognized role in neurocognition, these findings further support the known phenotypic manifestations of AOH into movement and cognitive dysfunctions.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

    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.

  18. Amniotic fluid metabolomics and biochemistry analysis provides novel insights into the diet-regulated foetal growth in a pig model

    PubMed Central

    Wan, Jin; Jiang, Fei; Zhang, Jiao; Xu, Qingsong; Chen, Daiwen; Yu, Bing; Mao, Xiangbing; Yu, Jie; Luo, Yuheng; He, Jun

    2017-01-01

    Foetal loss and intrauterine growth restriction are major problems in mammals, but there are few effective ways in preventing it. Intriguingly, chitosan oligosaccharide (COS), a biomaterial derived from chitosan, can promote foetal survival and growth. Therefore, we have investigated how COS affects foetal survival and growth in a pig model. Fifty-two sows were divided into two treatment groups (n = 26) and fed either solely a control diet or a control diet that includes 100 mg/kg COS. Amniotic fluid and foetus samples from six sows that were of average body weight in each group were collected on gestation day 35. We applied a 1H NMR-based metabolomics approach combined with biochemistry analysis to track the changes that occurred in the amniotic fluid of pregnant sows after COS intervention. Maternal COS inclusion had enhanced (P < 0.05) the foetal survival rate and size at 35 days. COS supplementation had both increased (P < 0.05) SOD, CAT and T-AOC activities and elevated (P < 0.05) IL-10, IgG and IgM concentrations in the amniotic fluid. Moreover, COS had affected (P < 0.05) the amniotic fluid’s lysine, citrate, glucose and hypoxanthine levels. Overall, COS inclusion induced amniotic fluid antioxidant status and metabolic profiles modifications characterising improvements in foetal survival and growth in a pig model. PMID:28300194

  19. Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease

    PubMed Central

    Poliquin, Pierre O.; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

    2013-01-01

    Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level. PMID:23935941

  20. 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.

  1. 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

    2015-02-09

    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.

  2. 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.

  3. 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

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

    PubMed

    Yoshida, Masaru; Nishiumi, Shin; Azuma, Takeshi

    2015-04-01

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

  5. Cultivar Determination of Ricinus communis via the Metabolome: a Proof of Concept Investigation

    DTIC Science & Technology

    2009-08-01

    enforcement agencies. Given the above information, strategies that are able to determine cultivar and provenance of an extract from R. communis...consideration was metabolomics. Metabolomics is the study of the metabolome of an organism. The metabolome can be defined as the pool of extractable chemistry...these analyses were then further analysed using Principal Component Analysis (PCA). For HPLC-UV analysis, the seed extract from seven R. communis

  6. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors.

    PubMed

    Vázquez-Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez, Miguel Ángel; Vinaixa, Maria; Chiva-Blanch, Gemma; Estruch, Ramon; Correig, Xavier; Andrés-Lacueva, Cristina

    2012-08-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100mL/day, alcohol control). After each period, 24-h urine samples were collected and analyzed by (1) H-NMR. According to the results of a one-way ANOVA, significant markers were grouped in four categories: alcohol-related markers (ethanol); gin-related markers; wine-related markers; and gut microbiota markers (hippurate and 4-hydroxphenylacetic acid). Wine metabolites were classified into two groups; first, metabolites of food metabolome: tartrate (RWA and RWD), ethanol, and mannitol (RWA); and second, biomarkers that relates to endogenous modifications after wine consumption, comprising branched-chain amino acid (BCAA) metabolite (3-methyl-oxovalerate). Additionally, a possible interaction between alcohol and gut-related biomarkers has been identified. To our knowledge, this is the first time that this approach has been applied in a nutritional intervention with red wine. The results show the capacity of this approach to obtain a comprehensive metabolome picture including food metabolome and endogenous biomarkers of moderate wine intake.

  7. Integrated proteomic and metabolomic analysis of an artificial microbial community for two-step production of vitamin C.

    PubMed

    Ma, Qian; Zhou, Jian; Zhang, Weiwen; Meng, Xinxin; Sun, Junwei; Yuan, Ying-Jin

    2011-01-01

    An artificial microbial community consisted of Ketogulonicigenium vulgare and Bacillus megaterium has been used in industry to produce 2-keto-gulonic acid (2-KGA), the precursor of vitamin C. During the mix culture fermentation process, sporulation and cell lysis of B. megaterium can be observed. In order to investigate how these phenomena correlate with 2-KGA production, and to explore how two species interact with each other during the fermentation process, an integrated time-series proteomic and metabolomic analysis was applied to the system. The study quantitatively identified approximate 100 metabolites and 258 proteins. Principal Component Analysis of all the metabolites identified showed that glutamic acid, 5-oxo-proline, L-sorbose, 2-KGA, 2, 6-dipicolinic acid and tyrosine were potential biomarkers to distinguish the different time-series samples. Interestingly, most of these metabolites were closely correlated with the sporulation process of B. megaterium. Together with several sporulation-relevant proteins identified, the results pointed to the possibility that Bacillus sporulation process might be important part of the microbial interaction. After sporulation, cell lysis of B. megaterium was observed in the co-culture system. The proteomic results showed that proteins combating against intracellular reactive oxygen stress (ROS), and proteins involved in pentose phosphate pathway, L-sorbose pathway, tricarboxylic acid cycle and amino acids metabolism were up-regulated when the cell lysis of B. megaterium occurred. The cell lysis might supply purine substrates needed for K. vulgare growth. These discoveries showed B. megaterium provided key elements necessary for K. vulgare to grow better and produce more 2-KGA. The study represents the first attempt to decipher 2-KGA-producing microbial communities using quantitative systems biology analysis.

  8. UPLC-QTOF analysis reveals metabolomic changes in the flag leaf of wheat (Triticum aestivum L.) under low-nitrogen stress.

    PubMed

    Zhang, Yang; Ma, Xin-Ming; Wang, Xiao-Chun; Liu, Ji-Hong; Huang, Bing-Yan; Guo, Xiao-Yang; Xiong, Shu-Ping; La, Gui-Xiao

    2017-02-01

    Wheat is one of the most important grain crop plants worldwide. Nitrogen (N) is an essential macronutrient for the growth and development of wheat and exerts a marked influence on its metabolites. To investigate the influence of low nitrogen stress on various metabolites of the flag leaf of wheat (Triticum aestivum L.), a metabolomic analysis of two wheat cultivars under different induced nitrogen levels was conducted during two important growth periods based on large-scale untargeted metabolomic analysis using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF). Multivariate analyses-such as principle components analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA)-were used for data analysis. PCA yielded distinctive clustering information among the samples, classifying the wheat flag samples into two categories: those under normal N treatment and low N treatment. By processing OPLS-DA, eleven secondary metabolites were shown to be responsible for classifying the two groups. The secondary metabolites may be considered potential biomarkers of low nitrogen stress. Chemical analyses showed that most of the identified secondary metabolites were flavonoids and their related derivatives, such as iso-vitexin, iso-orientin and methylisoorientin-2″-O-rhamnoside, etc. This study confirmed the effect of low nitrogen stress on the metabolism of wheat, and revealed that the accumulation of secondary metabolites is a response to abiotic stresses. Meanwhile, we aimed to identify markers which could be used to monitor the nitrogen status of wheat crops, presumably to guide appropriate fertilization regimens. Furthermore, the UPLC-QTOF metabolic platform technology can be used to study metabolomic variations of wheat under abiotic stresses.

  9. Metabolic Disturbances in Adult-Onset Still’s Disease Evaluated Using Liquid Chromatography/Mass Spectrometry-Based Metabolomic Analysis

    PubMed Central

    Chen, Der-Yuan; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting

    2016-01-01

    Objective Liquid chromatography/mass spectrometry (LC/MS)-based comprehensive analysis of metabolic profiles with metabolomics approach has potential diagnostic and predictive implications. However, no metabolomics data have been reported in adult-onset Still’s disease (AOSD). This study investigated the metabolomic profiles in AOSD patients and examined their association with clinical characteristics and disease outcome. Methods Serum metabolite profiles were determined on 32 AOSD patients and 30 healthy controls (HC) using ultra-performance liquid chromatography (UPLC)/MS analysis, and the differentially expressed metabolites were quantified using multiple reactions monitoring (MRM)/MS analysis in 44 patients and 42 HC. Pure standards were utilized to confirm the presence of the differentially expressed metabolites. Results Eighteen differentially expressed metabolites were identified in AOSD patents using LC/MS-based analysis, of which 13 metabolites were validated by MRM/MS analysis. Among them, serum levels of lysoPC(18:2), urocanic acid and indole were significantly lower, and L-phenylalanine levels were significantly higher in AOSD patients compared with HC. Moreover, serum levels of lysoPC(18:2), PhePhe, uridine, taurine, L-threonine, and (R)-3-Hydroxy-hexadecanoic acid were significantly correlated with disease activity scores (all p<0.05) in AOSD patients. A different clustering of metabolites was associated with a different disease outcome, with significantly lower levels of isovalerylsarcosine observed in patients with chronic articular pattern (median, 77.0AU/ml) compared with monocyclic (341.5AU/ml, p<0.01) or polycyclic systemic pattern (168.0AU/ml, p<0.05). Conclusion Thirteen differentially expressed metabolites identified and validated in AOSD patients were shown to be involved in five metabolic pathways. Significant associations of metabolic profiles with disease activity and outcome of AOSD suggest their involvement in AOSD pathogenesis. PMID

  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 for plant stress response.

    PubMed

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

    2008-02-01

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

  12. 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

  13. Metabolomics: A Primer.

    PubMed

    Liu, Xiaojing; Locasale, Jason W

    2017-04-01

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

  14. Identification of novel toxicity-associated metabolites by metabolomics and mass isotopomer analysis of acetaminophen metabolism in wild-type and Cyp2e1-null mice.

    PubMed

    Chen, Chi; Krausz, Kristopher W; Idle, Jeffrey R; Gonzalez, Frank J

    2008-02-22

    CYP2E1 is recognized as the most important enzyme for initiation of acetaminophen (APAP)-induced toxicity. In this study, the resistance of Cyp2e1-null mice to APAP treatment was confirmed by comparing serum aminotransferase activities and blood urea nitrogen levels in wild-type and Cyp2e1-null mice. However, unexpectedly, profiling of major known APAP metabolites in urine and serum revealed that the contribution of CYP2E1 to APAP metabolism decreased with increasing APAP doses administered. Measurement of hepatic glutathione and hydrogen peroxide levels exposed the importance of oxidative stress in determining the consequence of APAP overdose. Subsequent metabolomic analysis was capable of constructing a principal components analysis (PCA) model that delineated a relationship between urinary metabolomes and the responses to APAP treatment. Urinary ions high in wild-type mice treated with 400 mg/kg APAP were elucidated as 3-methoxy-APAP glucuronide (VII) and three novel APAP metabolites, including S-(5-acetylamino-2-hydroxyphenyl)mercaptopyruvic acid (VI, formed by a Cys-APAP transamination reaction in kidney), 3,3'-biacetaminophen (VIII, an APAP dimer), and a benzothiazine compound (IX, originated from deacetylated APAP), through mass isotopomer analysis, accurate mass measurement, tandem mass spectrometry fragmentation, in vitro reactions, and chemical treatments. Dose-, time-, and genotype-dependent appearance of these minor APAP metabolites implied their association with the APAP-induced toxicity and potential biomarker application. Overall, the oxidative stress elicited by CYP2E1-mediated APAP metabolism might significantly contribute to APAP-induced toxicity. The combination of genetically modified animal models, mass isotopomer analysis, and metabolomics provides a powerful and efficient technical platform to characterize APAP-induced toxicity through identifying novel biomarkers and unraveling novel mechanisms.

  15. Application of a novel metabolomic approach based on atmospheric pressure photoionization mass spectrometry using flow injection analysis for the study of Alzheimer's disease.

    PubMed

    González-Domínguez, Raúl; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2015-01-01

    The use of atmospheric pressure photoionization is not widespread in metabolomics, despite its considerable potential for the simultaneous analysis of compounds with diverse polarities. This work considers the development of a novel analytical approach based on flow injection analysis and atmospheric pressure photoionization mass spectrometry for rapid metabolic screening of serum samples. Several experimental parameters were optimized, such as type of dopant, flow injection solvent, and their flows, given that a careful selection of these variables is mandatory for a comprehensive analysis of metabolites. Toluene and methanol were the most suitable dopant and flow injection solvent, respectively. Moreover, analysis in negative mode required higher solvent and dopant flows (100 µl min(-1) and 40 µl min(-1), respectively) compared to positive mode (50 µl min(-1) and 20 µl min(-1)). Then, the optimized approach was used to elucidate metabolic alterations associated with Alzheimer's disease. Thereby, results confirm the increase of diacylglycerols, ceramides, ceramide-1-phosphate and free fatty acids, indicating membrane destabilization processes, and reduction of fatty acid amides and several neurotransmitters related to impairments in neuronal transmission, among others. Therefore, it could be concluded that this metabolomic tool presents a great potential for analysis of biological samples, considering its high-throughput screening capability, fast analysis and comprehensive metabolite coverage.

  16. Blood-based diagnosis of Alzheimer's disease using fingerprinting metabolomics based on hydrophilic interaction liquid chromatography with mass spectrometry and multivariate statistical analysis.

    PubMed

    Inoue, Koichi; Tsuchiya, Hirofumi; Takayama, Takahiro; Akatsu, Hiroyasu; Hashizume, Yoshio; Yamamoto, Takayuki; Matsukawa, Noriyuki; Toyo'oka, Toshimasa

    2015-01-01

    Early and definitive diagnosis of Alzheimer's disease (AD) can lead to a better and more-targeted treatment and/or prevention for patients. In the diagnostic biomarkers of AD, the blood sample represents a more non-invasive, inexpensive and acceptable sources for repeated measurements than the cerebrospinal fluid. In this study, the fingerprinting metabolomics was proposed for the challenge of the blood-based diagnosis of defined AD by hydrophilic interaction liquid chromatography mass spectrometry (HILIC/MS). These plasma samples were selected from postmortem specimens based on these pathological examinations. Firstly, we compared these HILIC columns for the non-targeted metabolic assay using pooled plasma. The principal component analysis plot of these seven columns was performed using the repeatability of these chromatograms, and can be used to visualize trends in data sets by three-dimensional dispersion, contributory standard deviation and the number of detections. Based on these results, TSK-Amide 80 and TSKgel-NH₂ columns are used as a reliable HILIC/MS assay of blood-based AD metabolomics that showed metabolic profiling of the AD pathology in MS chromatograms that ranged from 1182 to 2284 compounds. A total of 54 peaks were evaluated in order to identify useful ion signal candidates using an orthogonal partial least-squares-discriminant analysis. These peaks were then specifically analyzed using the HILIC-tandem MS assay by a receiver operating characteristic curve and linear discriminant analysis for the diagnosis of the defined AD. The fingerprinting metabolomics can overcome the limitations of previous challenging blood-based diagnosis of AD, and directly evaluates the specific comparative statistical values from the raw data.

  17. Non-targeted metabolomics analysis of cardiac Muscle Ring Finger-1 (MuRF1), MuRF2, and MuRF3 in vivo reveals novel and redundant metabolic changes

    PubMed Central

    Banerjee, Ranjan; He, Jun; Spaniel, Carolyn; Quintana, Megan T.; Wang, Zhongjing; Bain, James; Newgard, Christopher B.; Muehlbauer, Michael J.; Willis, Monte S.

    2017-01-01

    The muscle-specific ubiquitin ligases MuRF1, MuRF2, MuRF3 have been reported to have overlapping substrate specificities, interacting with each other as well as proteins involved in metabolism and cardiac function. In the heart, all three MuRF family proteins have proven critical to cardiac responses to ischemia and heart failure. The non-targeted metabolomics analysis of MuRF1-/-, MuRF2-/-, and MuRF3-/- hearts was initiated to investigate the hypothesis that MuRF1, MuRF2, and MuRF3 have a similarly altered metabolome, representing alterations in overlapping metabolic processes. Ventricular tissue was flash frozen and quantitatively analyzed by GC/MS using a library built upon the Fiehn GC/MS Metabolomics RTL Library. Non-targeted metabolomic analysis identified significant differences (via VIP statistical analysis) in taurine, myoinositol, and stearic acid for the three MuRF-/- phenotypes relative to their matched controls. Moreover, pathway enrichment analysis demonstrated that MuRF1-/- had significant changes in metabolite(s) involved in taurine metabolism and primary acid biosynthesis while MuRF2-/- had changes associated with ascorbic acid/aldarate metabolism (via VIP and t-test analysis vs. sibling-matched wildtype controls). By identifying the functional metabolic consequences of MuRF1, MuRF2, and MuRF3 in the intact heart, non-targeted metabolomics analysis discovered common pathways functionally affected by cardiac MuRF family proteins in vivo. These novel metabolomics findings will aid in guiding the molecular studies delineating the mechanisms that MuRF family proteins regulate metabolic pathways. Understanding these mechanism is an important key to understanding MuRF family proteins' protective effects on the heart during cardiac disease.

  18. 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

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

    DTIC Science & Technology

    2014-10-01

    AWARD NUMBER: W81XWH-13-1-0493 TITLE: Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and...SUBTITLE Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress 5a. CONTRACT NUMBER Perceived Stress...relationship between stress and ovarian cancer has never been evaluated in humans. In our analysis of self-reported stress and risk of ovarian cancer , we

  20. Metabolomics in chemical ecology.

    PubMed

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

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

  1. 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

  2. Metabolomics and malaria biology

    PubMed Central

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

    2010-01-01

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

  3. Metabolomics and dereplication strategies in natural products.

    PubMed

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

    2013-01-01

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

  4. Technical Challenges in Mass Spectrometry-Based Metabolomics

    PubMed Central

    Matsuda, Fumio

    2016-01-01

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

  5. Detection of inborn errors of metabolism utilizing GC-MS urinary metabolomics coupled with a modified orthogonal partial least squares discriminant analysis.

    PubMed

    Yang, Qin; Lin, Shan-Shan; Yang, Jiang-Tao; Tang, Li-Juan; Yu, Ru-Qin

    2017-04-01

    GC-MS urinary metabolomic analysis coupled with chemometrics is used to detect inborn errors of metabolism (IEMs), which are genetic disorders causing severe mental and physical debility and even sudden infant death. Orthogonal partial least squares discriminant analysis (OPLS-DA) is an efficient multivariate statistical method that conducts data analysis of metabolite profiling. However, performance degradation is often observed for OPLS-DA due to increasing size and complexity of metabolomic datasets. In this study, hybrid particle swarm optimization (HPSO) is employed to modify OPLS-DA by simultaneously selecting the optimal variable subset, associated weights and the appropriate number of orthogonal components, constructing a new algorithm called HPSO-OPLSDA. Investigating two IEMs, methylmalonic acidemia (MMA) and isovaleric acidemia (IVA), results suggest that HPSO-OPLSDA can significantly outperform OPLS-DA in terms of the discrimination between disease samples and healthy controls. Moreover, main discriminative metabolites are identified by HPSO-OPLSDA to aid the clinical diagnosis of IEMs, including methylmalonic-2, methylcitric-4(1) and 3-OH-propionic-2 for MMA and isovalerylglycine-1 for IVA.

  6. Proof of concept of microbiome-metabolome analysis and delayed gluten exposure on celiac disease autoimmunity in genetically at-risk infants.

    PubMed

    Sellitto, Maria; Bai, Guoyun; Serena, Gloria; Fricke, W Florian; Sturgeon, Craig; Gajer, Pawel; White, James R; Koenig, Sara S K; Sakamoto, Joyce; Boothe, Dustin; Gicquelais, Rachel; Kryszak, Deborah; Puppa, Elaine; Catassi, Carlo; Ravel, Jacques; Fasano, Alessio

    2012-01-01

    Celiac disease (CD) is a unique autoimmune disorder in which the genetic factors (DQ2/DQ8) and the environmental trigger (gluten) are known and necessary but not sufficient for its development. Other environmental components contributing to CD are poorly understood. Studies suggest that aspects of gluten intake might influence the risk of CD occurrence and timing of its onset, i.e., the amount and quality of ingested gluten, together with the pattern of infant feeding and the age at which gluten is introduced in the diet. In this study, we hypothesize that the intestinal microbiota as a whole rather than specific infections dictates the switch from tolerance to immune response in genetically susceptible individuals. Using a sample of infants genetically at risk of CD, we characterized the longitudinal changes in the microbial communities that colonize infants from birth to 24 months and the impact of two patterns of gluten introduction (early vs. late) on the gut microbiota and metabolome, and the switch from gluten tolerance to immune response, including onset of CD autoimmunity. We show that infants genetically susceptible to CD who are exposed to gluten early mount an immune response against gluten and develop CD autoimmunity more frequently than at-risk infants in which gluten exposure is delayed until 12 months of age. The data, while derived from a relatively small number of subjects, suggest differences between the developing microbiota of infants with genetic predisposition for CD and the microbiota from infants with a non-selected genetic background, with an overall lack of bacteria of the phylum Bacteriodetes along with a high abundance of Firmicutes and microbiota that do not resemble that of adults even at 2 years of age. Furthermore, metabolomics analysis reveals potential biomarkers for the prediction of CD. This study constitutes a definite proof-of-principle that these combined genomic and metabolomic approaches will be key to deciphering the role

  7. 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.

  8. Evaluation of automated sample preparation, retention time locked gas chromatography-mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species.

    PubMed

    Gu, Qun; David, Frank; Lynen, Frédéric; Rumpel, Klaus; Dugardeyn, Jasper; Van Der Straeten, Dominique; Xu, Guowang; Sandra, Pat

    2011-05-27

    In this paper, automated sample preparation, retention time locked gas chromatography-mass spectrometry (GC-MS) and data analysis methods for the metabolomics study were evaluated. A miniaturized and automated derivatisation method using sequential oximation and silylation was applied to a polar extract of 4 types (2 types×2 ages) of Arabidopsis thaliana, a popular model organism often used in plant sciences and genetics. Automation of the derivatisation process offers excellent repeatability, and the time between sample preparation and analysis was short and constant, reducing artifact formation. Retention time locked (RTL) gas chromatography-mass spectrometry was used, resulting in reproducible retention times and GC-MS profiles. Two approaches were used for data analysis. XCMS followed by principal component analysis (approach 1) and AMDIS deconvolution combined with a commercially available program (Mass Profiler Professional) followed by principal component analysis (approach 2) were compared. Several features that were up- or down-regulated in the different types were detected.

  9. Transcriptomic and Metabolomic Analysis Revealed Multifaceted Effects of Phage Protein Gp70.1 on Pseudomonas aeruginosa

    PubMed Central

    Zhao, Xia; Chen, Canhuang; Jiang, Xingyu; Shen, Wei; Huang, Guangtao; Le, Shuai; Lu, Shuguang; Zou, Lingyun; Ni, Qingshan; Li, Ming; Zhao, Yan; Wang, Jing; Rao, Xiancai; Hu, Fuquan; Tan, Yinling

    2016-01-01

    The impact of phage infection on the host cell is severe. In order to take over the cellular machinery, some phage proteins were produced to shut off the host biosynthesis early in the phage infection. The discovery and identification of these phage-derived inhibitors have a significant prospect of application in antibacterial treatment. This work presented a phage protein, gp70.1, with non-specific inhibitory effects on Pseudomonas aeruginosa and Escherichia coli. Gp70.1 was encoded by early gene – orf 70.1 from P. aeruginosa phage PaP3. The P. aeruginosa with a plasmid encoding gp70.1 showed with delayed growth and had the appearance of a small colony. The combination of multifaceted analysis including microarray-based transcriptomic analysis, RT-qPCR, nuclear magnetic resonance (NMR) spectroscopy-based metabolomics and phenotype experiments were performed to investigate the effects of gp70.1 on P. aeruginosa. A total of 178 genes of P. aeruginosa mainly involved in extracellular function and metabolism were differentially expressed in the presence of gp70.1 at three examined time points. Furthermore, our results indicated that gp70.1 had an extensive impact on the extracellular phenotype of P. aeruginosa, such as motility, pyocyanin, extracellular protease, polysaccharide, and cellulase. For the metabolism of P. aeruginosa, the main effect of gp70.1 was the reduction of amino acid consumption. Finally, the RNA polymerase sigma factor RpoS was identified as a potential cellular target of gp70.1. Gp70.1 was the first bacterial inhibitor identified from Pseudomonas aeruginosa phage PaP3. It was also the first phage protein that interacted with the global regulator RpoS of bacteria. Our results indicated the potential value of gp70.1 in antibacterial applications. This study preliminarily revealed the biological function of gp70.1 and provided a reference for the study of other phage genes sharing similarities with orf70.1. PMID:27725812

  10. Metabolomics and protozoan parasites.

    PubMed

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

    2013-06-01

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

  11. The human serum metabolome

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. 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

  13. 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

  14. Metabolome Analysis of Oryza sativa (Rice) Using Liquid Chromatography-Mass Spectrometry for Characterizing Organ Specificity of Flavonoids with Anti-inflammatory and Anti-oxidant Activity.

    PubMed

    Yang, Zhigang; Nakabayashi, Ryo; Mori, Tetsuya; Takamatsu, Satoshi; Kitanaka, Susumu; Saito, Kazuki

    2016-01-01

    Oryza sativa L. (rice) is an important staple crop across the world. In the previous study, we identified 36 specialized (secondary) metabolites including 28 flavonoids. In the present study, a metabolome analysis using liquid chromatography-mass spectrometry was conducted on the leaf, bran, and brown and polished rice grains to better understand the distribution of these metabolites. Principal component analysis using the metabolome data clearly characterized the accumulation patterns of the metabolites. Flavonoids, e.g., tricin, tricin 7-O-rutinoside, and tricin 7-O-β-D-glucopyranoside, were mainly present in the leaf and bran but not in the polished grain. In addition, anti-inflammatory and anti-oxidant activity of the metabolites were assayed in vitro. Tricin 4'-O-(erythro-β-guaiacylglyceryl)ether and isoscoparin 2″-O-(6‴-(E)-feruloyl)-glucopyranoside showed the strongest activity for inhibiting nitric oxide (NO) production and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging, respectively.

  15. Tailored liquid chromatography-mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells.

    PubMed

    Cuykx, Matthias; Negreira, Noelia; Beirnaert, Charlie; Van den Eede, Nele; Rodrigues, Robim; Vanhaecke, Tamara; Laukens, Kris; Covaci, Adrian

    2017-03-03

    Metabolomics protocols are often combined with Liquid Chromatography-Mass Spectrometry (LC-MS) using mostly reversed phase chromatography coupled to accurate mass spectrometry, e.g. quadrupole time-of-flight (QTOF) mass spectrometers to measure as many metabolites as possible. In this study, we optimised the LC-MS separation of cell extracts after fractionation in polar and non-polar fractions. Both phases were analysed separately in a tailored approach in four different runs (two for the non-polar and two for the polar-fraction), each of them specifically adapted to improve the separation of the metabolites present in the extract. This approach improves the coverage of a broad range of the metabolome of the HepaRG cells and the separation of intra-class metabolites. The non-polar fraction was analysed using a C18-column with end-capping, mobile phase compositions were specifically adapted for each ionisation mode using different co-solvents and buffers. The polar extracts were analysed with a mixed mode Hydrophilic Interaction Liquid Chromatography (HILIC) system. Acidic metabolites from glycolysis and the Krebs cycle, together with phosphorylated compounds, were best detected with a method using ion pairing (IP) with tributylamine and separation on a phenyl-hexyl column. Accurate mass detection was performed with the QTOF in MS-mode only using an extended dynamic range to improve the quality of the dataset. Parameters with the greatest impact on the detection were the balance between mass accuracy and linear range, the fragmentor voltage, the capillary voltage, the nozzle voltage, and the nebuliser pressure. By using a tailored approach for the intracellular HepaRG metabolome, consisting of three different LC techniques, over 2200 metabolites can be measured with a high precision and acceptable linear range. The developed method is suited for qualitative untargeted LC-MS metabolomics studies.

  16. Accelerating analysis for metabolomics, drugs and their metabolites in biological samples using multidimensional gas chromatography.

    PubMed

    Mitrevski, Blagoj S; Kouremenos, Konstantinos A; Marriott, Philip J

    2009-05-01

    Gas chromatography (GC) with mass spectrometry (MS) is one of the great enabling analytical tools available to the chemical and biochemical analyst for the measurement of volatile and semi-volatile compounds. From the analysis result, it is possible to assess progress in chemical reactions, to monitor environmental pollutants in a wide range of soil, water or air samples, to determine if an athlete or horse trainer has contravened doping laws, or if crude oil has migrated through subsurface rock to a reservoir. Each of these scenarios and samples has an associated implementation method for GC-MS. However, few samples and the associated interpretation of data is as complex or important as biochemical sample analysis for trace drugs or metabolites. Improving the analysis in both the GC and MS domains is a continual search for better separation, selectivity and sensitivity. Multidimensional methods are playing important roles in providing quality data to address the needs of analysts.

  17. Metabolomic differentiation of maca (Lepidium meyenii) accessions cultivated under different conditions using NMR and chemometric analysis.

    PubMed

    Zhao, Jianping; Avula, Bharathi; Chan, Michael; Clément, Céline; Kreuzer, Michael; Khan, Ikhlas A

    2012-01-01

    To gain insights on the effects of color type, cultivation history, and growing site on the composition alterations of maca (Lepidium meyenii Walpers) hypocotyls, NMR profiling combined with chemometric analysis was applied to investigate the metabolite variability in different maca accessions. Maca hypocotyls with different colors (yellow, pink, violet, and lead-colored) cultivated at different geographic sites and different areas were examined for differences in metabolite expression. Differentiations of the maca accessions grown under the different cultivation conditions were determined by principle component analyses (PCAs) which were performed on the datasets derived from their ¹H NMR spectra. A total of 16 metabolites were identified by NMR analysis, and the changes in metabolite levels in relation to the color types and growing conditions of maca hypocotyls were evaluated using univariate statistical analysis. In addition, the changes of the correlation pattern among the metabolites identified in the maca accessions planted at the two different sites were examined. The results from both multivariate and univariate analysis indicated that the planting site was the major determining factor with regards to metabolite variations in maca hypocotyls, while the color of maca accession seems to be of minor importance in this respect.

  18. Quality assurance of metabolomics.

    PubMed

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

    2015-01-01

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

  19. NMR-Based Metabolomic Analysis of Spatial Variation in Soft Corals

    PubMed Central

    He, Qing; Sun, Ruiqi; Liu, Huijuan; Geng, Zhufeng; Chen, Dawei; Li, Yinping; Han, Jiao; Lin, Wenhan; Du, Shushan; Deng, Zhiwei

    2014-01-01

    Soft corals are common marine organisms that inhabit tropical and subtropical oceans. They are shown to be rich source of secondary metabolites with biological activities. In this work, soft corals from two geographical locations were investigated using 1H-NMR spectroscopy coupled with multivariate statistical analysis at the metabolic level. A partial least-squares discriminant analysis showed clear separation among extracts of soft corals grown in Sanya Bay and Weizhou Island. The specific markers that contributed to discrimination between soft corals in two origins belonged to terpenes, sterols and N-containing compounds. The satisfied precision of classification obtained indicates this approach using combined 1H-NMR and chemometrics is effective to discriminate soft corals collected in different geographical locations. The results revealed that metabolites of soft corals evidently depended on living environmental condition, which would provide valuable information for further relevant coastal marine environment evaluation. PMID:24686560

  20. Tandem LC columns for the simultaneous retention of polar and nonpolar molecules in comprehensive metabolomics analysis.

    PubMed

    Chalcraft, Kenneth R; McCarry, Brian E

    2013-11-01

    The tandem use of hydrophilic interaction LC columns with RP columns in series configuration has resulted in the retention of both polar and nonpolar components in complex biological samples (mouse serum) in a single analysis. This approach successfully coupled various columns with orthogonal separation characteristics, employed a single solvent gradient program compatible with the two columns and used ESI coupled to a TOF mass spectrometer for detection. Ion suppression, a common problem in ESI, was virtually eliminated for components eluting with apparent capacity factors >0.7. Retention time reproducibility with the tandem columns performed over three days with over 100 injections was comparable to that observed for single columns alone. This method was applied to the analysis of a pooled mouse serum sample and afforded highly reproducible data for up to 3000 mass spectral features. This approach was implemented with a conventional LC-MS system and should find broad applicability in the comprehensive analysis of complex mixtures containing a wide range of compound polarities.

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

    PubMed Central

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

    2016-01-01

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

  2. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  3. Clinical application of metabolomics in neonatology.

    PubMed

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

    2012-04-01

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

  4. Metabolomics: towards understanding traditional Chinese medicine.

    PubMed

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

    2010-12-01

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

  5. Metabolomics: Applications and Promise in Mycobacterial Disease

    PubMed Central

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

    2015-01-01

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

  6. Systematic Applications of Metabolomics in Metabolic Engineering

    PubMed Central

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

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

  7. Basics of mass spectrometry based metabolomics.

    PubMed

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

    2014-11-01

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

  8. MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis.

    PubMed

    Tsugawa, Hiroshi; Cajka, Tomas; Kind, Tobias; Ma, Yan; Higgins, Brendan; Ikeda, Kazutaka; Kanazawa, Mitsuhiro; VanderGheynst, Jean; Fiehn, Oliver; Arita, Masanori

    2015-06-01

    Data-independent acquisition (DIA) in liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) provides comprehensive untargeted acquisition of molecular data. We provide an open-source software pipeline, which we call MS-DIAL, for DIA-based identification and quantification of small molecules by mass spectral deconvolution. For a reversed-phase LC-MS/MS analysis of nine algal strains, MS-DIAL using an enriched LipidBlast library identified 1,023 lipid compounds, highlighting the chemotaxonomic relationships between the algal strains.

  9. Evaluation and identification of dioxin exposure biomarkers in human urine by high-resolution metabolomics, multivariate analysis and in vitro synthesis.

    PubMed

    Jeanneret, Fabienne; Tonoli, David; Hochstrasser, Denis; Saurat, Jean-Hilaire; Sorg, Olivier; Boccard, Julien; Rudaz, Serge

    2016-01-05

    A previous high-resolution metabolomic study pointed out a dysregulation of urinary steroids and bile acids in human cases of acute dioxin exposure. A subset of 24 compounds was highlighted as putative biomarkers. The aim of the current study was (i) to evaluate the 24 biomarkers in an independent human cohort exposed to dioxins released from the incineration fumes of a municipal waste incinerator and; (ii) to identify them by comparison with authentic chemical standards and biosynthesised products obtained with in vitro metabolic reactions. An orthogonal projection to latent structures discriminant analysis built on biomarker profiles measured in the intoxicated cohort and the controls separated both groups with reported values of 93.8%; 100% and 87.5% for global accuracy; sensitivity and specificity; respectively. These results corroborated the 24 compounds as exposure biomarkers; but a definite identification was necessary for a better understanding of dioxin toxicity. Dehydroepiandrosterone 3β-sulfate, androsterone 3α-glucuronide, androsterone 3α-sulfate, pregnanediol 3α-glucuronide and 11-ketoetiocholanolone 3α-glucuronide were identified by authentic standards. Metabolic reactions characterised four biomarkers: glucuronide conjugates of 11β-hydroxyandrosterone; glycochenodeoxycholic acid and glycocholic acid produced in human liver microsomes and glycoursodeoxycholic acid sulfate generated in cytosol fraction. The combination of metabolomics by high-resolution mass spectrometry with in vitro metabolic syntheses confirmed a perturbed profile of steroids and bile acids in human cases of dioxin exposure.

  10. A powerful methodological approach combining headspace solid phase microextraction, mass spectrometry and multivariate analysis for profiling the volatile metabolomic pattern of beer starting raw materials.

    PubMed

    Gonçalves, João L; Figueira, José A; Rodrigues, Fátima P; Ornelas, Laura P; Branco, Ricardo N; Silva, Catarina L; Câmara, José S

    2014-10-01

    The volatile metabolomic patterns from different raw materials commonly used in beer production, namely barley, corn and hop-derived products - such as hop pellets, hop essential oil from Saaz variety and tetra-hydro isomerized hop extract (tetra hop), were established using a suitable analytical procedure based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography-quadrupole mass spectrometry detection (GC-qMS). Some SPME extraction parameters were optimized. The best results, in terms of maximum signal recorded and number of isolated metabolites, were obtained with a 50/30 μm DVB/CAR/PDMS coating fiber at 40 °C for 30 min. A set of 152 volatile metabolites comprising ketones (27), sesquiterpenes (26), monoterpenes (19), aliphatic esters (19), higher alcohols (15), aldehydes (11), furan compounds (11), aliphatic fatty acids (9), aliphatic hydrocarbons (8), sulphur compounds (5) and nitrogen compounds (2) were positively identified. Each raw material showed a specific volatile metabolomic profile. Monoterpenes in hop essential oil and corn, sesquiterpenes in hop pellets, ketones in tetra hop and aldehydes and sulphur compounds in barley were the predominant chemical families in the targeted beer raw materials. β-Myrcene was the most dominant volatile metabolite in hop essential oil, hop pellets and corn samples while, in barley, the predominant volatile metabolites were dimethyl sulphide and 3-methylbutanal and, in tetra hop, 6-methyl-2-pentanone and 4-methyl-2-pentanone. Principal component analysis (PCA) showed natural sample grouping among beer raw materials.

  11. Metabolome, transcriptome and metabolic flux analysis of arabinose fermentation by engineered Saccharomyces cerevisiae.

    PubMed

    Wisselink, H Wouter; Cipollina, Chiara; Oud, Bart; Crimi, Barbara; Heijnen, Joseph J; Pronk, Jack T; van Maris, Antonius J A

    2010-11-01

    One of the challenges in strain improvement by evolutionary engineering is to subsequently determine the molecular basis of the improved properties that were enriched from the natural genetic variation during the selective conditions. This study focuses on Saccharomyces cerevisiae IMS0002 which, after metabolic and evolutionary engineering, ferments the pentose sugar arabinose. Glucose- and arabinose-limited anaerobic chemostat cultures of IMS0002 and its non-evolved ancestor were subjected to transcriptome analysis, intracellular metabolite measurements and metabolic flux analysis. Increased expression of the GAL-regulon and deletion of GAL2 in IMS0002 confirmed that the galactose transporter is essential for growth on arabinose. Elevated intracellular concentrations of pentose-phosphate-pathway intermediates and upregulation of TKL2 and YGR043c (encoding transketolase and transaldolase isoenzymes) suggested an involvement of these genes in flux-controlling reactions in arabinose fermentation. Indeed, deletion of these genes in IMS0002 caused a 21% reduction of the maximum specific growth rate on arabinose.

  12. COnsortium of METabolomics Studies (COMETS)

    Cancer.gov

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

  13. Linking metabolomics data to underlying metabolic regulation

    PubMed Central

    Nägele, Thomas

    2014-01-01

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

  14. Metabolomic analysis and phenylpropanoid biosynthesis in hairy root culture of tartary buckwheat cultivars.

    PubMed

    Thwe, Aye Aye; Kim, Jae Kwang; Li, Xiaohua; Kim, Yeon Bok; Uddin, Md Romij; Kim, Sun Ju; Suzuki, Tatsuro; Park, Nam Il; Park, Sang Un

    2013-01-01

    Buckwheat, Fagopyrum tataricum Gaertn., is an important medicinal plant, which contains several phenolic compounds, including one of the highest content of rutin, a phenolic compound with anti-inflammatory properties. An experiment was conducted to investigate the level of expression of various genes in the phenylpropanoid biosynthetic pathway to analyze in vitro production of anthocyanin and phenolic compounds from hairy root cultures derived from 2 cultivars of tartary buckwheat (Hokkai T8 and T10). A total of 47 metabolites were identified by gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) and subjected to principal component analysis (PCA) in order to fully distinguish between Hokkai T8 and T10 hairy roots. The expression levels of phenylpropanoid biosynthetic pathway genes, through qRT-PCR, showed higher expression for almost all the genes in T10 than T8 hairy root except for FtF3'H-2 and FtFLS-2. Rutin, quercetin, gallic acid, caffeic acid, ferulic acid, 4-hydroxybenzoic acid, and 2 anthocyanin compounds were identified in Hokkai T8 and T10 hairy roots. The concentration of rutin and anthocyanin in Hokkai T10 hairy roots of tartary buckwheat was several-fold higher compared with that obtained from Hokkai T8 hairy root. This study provides useful information on the molecular and physiological dynamic processes that are correlated with phenylpropanoid biosynthetic gene expression and phenolic compound content in F. tataricum species.

  15. [Serum metabolomics analysis on benign prostate hyperplasia in mice based on liquid chromatography-mass spectrometry].

    PubMed

    Geng, Yue; Sun, Fengxia; Ma, Yu; Deng, Ligang; Lü, Jianyun; Li, Teng; Wang, Congcong

    2014-12-01

    Benign prostatic hyperplasia (BPH) increasingly becomes a common factor affecting the quality of life of aging men. Its pathogenesis has not yet been fully elucidated. Ultra-high pressure liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was employed to detect the changes of serum metabolites in normal mice, benign prostatic hyperplasia model mice and BPH model mice with finasteride intervention. The serum metabolite profiles of the three groups of mice were analyzed. Partial least squares-discriminant analysis (PLS-DA) was used for group differentiation and biomarker selection. The results showed good distinction among the three groups of mice serum metabolite spectra. Three potential biomarkers, 1-hexadecanoyl-SN-glycero-3-phosphocholine, 1-O-hexadecyl-2-O-acetyl-sn-glyceryl-3-phosphorylcholine and (Z)-13-docosenamide, were discovered and identified. They all indicated the occurrence of benign prostatic hypertrophy is closely related to the disorders of lipid metabolism. Coinpared with the control group, the contents of the first two substances were significantly increased in the serum of BPH model mice, and significantly decreased after intervened by finasteride. The contents of (Z)-13-docosenamide decreased significantly in the serum of model group, and increased after intervened by finasteride. Compared with the control group, the contents of three biomarkers in finasteride group did not recover completely and had significant differences. This study is conductive to open new avenues of diagnosis and medical treatment for BPH.

  16. Use of the Analysis of the Volatile Faecal Metabolome in Screening for Colorectal Cancer

    PubMed Central

    2015-01-01

    Diagnosis of colorectal cancer is an invasive and expensive colonoscopy, which is usually carried out after a positive screening test. Unfortunately, existing screening tests lack specificity and sensitivity, hence many unnecessary colonoscopies are performed. Here we report on a potential new screening test for colorectal cancer based on the analysis of volatile organic compounds (VOCs) in the headspace of faecal samples. Faecal samples were obtained from subjects who had a positive faecal occult blood sample (FOBT). Subjects subsequently had colonoscopies performed to classify them into low risk (non-cancer) and high risk (colorectal cancer) groups. Volatile organic compounds were analysed by selected ion flow tube mass spectrometry (SIFT-MS) and then data were analysed using both univariate and multivariate statistical methods. Ions most likely from hydrogen sulphide, dimethyl sulphide and dimethyl disulphide are statistically significantly higher in samples from high risk rather than low risk subjects. Results using multivariate methods show that the test gives a correct classification of 75% with 78% specificity and 72% sensitivity on FOBT positive samples, offering a potentially effective alternative to FOBT. PMID:26086914

  17. Targeted Metabolomic Analysis of Polyphenols with Antioxidant Activity in Sour Guava (Psidium friedrichsthalianum Nied.) Fruit.

    PubMed

    Cuadrado-Silva, Carmen Tatiana; Pozo-Bayón, Maria Ángeles; Osorio, Coralia

    2016-12-23

    Psidium is a genus of tropical bushes belonging to the Myrtaceae family distributed in Central and South America. The polar extract of Psidium friedrichsthalianum Nied. was partitioned with ethyl ether, ethyl acetate, and n-butanol, and the total phenolic content and antioxidant activity were measured by Folin-Ciocalteu and ABTS assays, respectively. The ethyl acetate fraction exhibited both the highest phenolic content and antioxidant activity. Due to the complexity of this fraction, an analytical method for the comprehensive profiling of phenolic compounds was done by UPLC-ESI/QqQ in MRM (multiple reaction monitoring) mode. In this targeted analysis, 22 phenolic compounds were identified, among which several hydroxybenzoic, phenylacetic, and hydroxycinnamic acid derivatives were found. This is the first time that (+)-catechin, procyanidin B1, procyanidin B2, and (-)-epicatechin have been reported as constituents of sour guava. A fractionation by exclusion size, C18-column chromatography, and preparative RRLC (rapid resolution liquid chromatography) allowed us to confirm the presence of ellagic acid and isomeric procyanidins B, well-known bioactive compounds. The content of phenolic compounds in this fruit shows its potential for the development of functional foods.

  18. Metabolomics of temperature stress.

    PubMed

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

    2008-02-01

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

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

    PubMed Central

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

    2014-01-01

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

  20. Metabolomics Analysis and Biosynthesis of Rosmarinic Acid in Agastache rugosa Kuntze Treated with Methyl Jasmonate

    PubMed Central

    Uddin, Md. Romij; Xu, Hui; Park, Woo Tae; Tuan, Pham Anh; Li, Xiaohua; Chung, Eunsook; Lee, Jai-Heon; Park, Sang Un

    2013-01-01

    This study investigated the effect of methyl jasmonate (MeJA) on metabolic profiles and rosmarinic acid (RA) biosynthesis in cell cultures of Agastache rugosa Kuntze. Transcript levels of phenylpropanoid biosynthetic genes, i.e., ArPAL, Ar4CL, and ArC4H, maximally increased 4.5-fold, 3.4-fold, and 3.5-fold, respectively, compared with the untreated controls, and the culture contained relatively high amounts of RA after exposure of cells to 50 µM MeJA. RA levels were 2.1-, 4.7-, and 3.9-fold higher after exposure to 10, 50, and 100 µM MeJA, respectively, than those in untreated controls. In addition, the transcript levels of genes attained maximum levels at different time points after the initial exposure. The transcript levels of ArC4H and Ar4CL were transiently induced by MeJA, and reached a maximum of up to 8-fold at 3 hr and 6 hr, respectively. The relationships between primary metabolites and phenolic acids in cell cultures of A. rugosa treated with MeJA were analyzed by gas chromatography coupled with time-of-flight mass spectrometry. In total, 45 metabolites, including 41 primary metabolites and 4 phenolic acids, were identified from A. rugosa. Metabolite profiles were subjected to partial least square-discriminate analysis to evaluate the effects of MeJA. The results indicate that both phenolic acids and precursors for the phenylpropanoid biosynthetic pathway, such as aromatic amino acids and shikimate, were induced as a response to MeJA treatment. Therefore, MeJA appears to have an important impact on RA accumulation, and the increased RA accumulation in the treated cells might be due to activation of the phenylpropanoid genes ArPAL, ArC4H, and Ar4CL. PMID:23724034

  1. Metabolomics and molecular marker analysis to explore pepper (Capsicum sp.) biodiversity.

    PubMed

    Wahyuni, Yuni; Ballester, Ana-Rosa; Tikunov, Yury; de Vos, Ric C H; Pelgrom, Koen T B; Maharijaya, Awang; Sudarmonowati, Enny; Bino, Raoul J; Bovy, Arnaud G

    2013-02-01

    An overview of the metabolic diversity in ripe fruits of a collection of 32 diverse pepper (Capsicum sp.) accessions was obtained by measuring the composition of both semi-polar and volatile metabolites in fruit pericarp, using untargeted LC-MS and headspace GC-MS platforms, respectively. Accessions represented C. annuum, C. chinense, C. frutescens and C. baccatum species, which were selected based on variation in morphological characters, pungency and geographic origin. Genotypic analysis using AFLP markers confirmed the phylogenetic clustering of accessions according to Capsicum species and separated C. baccatum from the C. annuum-C. chinense-C. frutescens complex. Species-specific clustering was also observed when accessions were grouped based on their semi-polar metabolite profiles. In total 88 semi-polar metabolites could be putatively identified. A large proportion of these metabolites represented conjugates of the main pepper flavonoids (quercetin, apigenin and luteolin) decorated with different sugar groups at different positions along the aglycone. In addition, a large group of acyclic diterpenoid glycosides, called capsianosides, was found to be highly abundant in all C. annuum genotypes. In contrast to the variation in semi-polar metabolites, the variation in volatiles corresponded well to the differences in pungency between the accessions. This was particularly true for branched fatty acid esters present in pungent accessions, which may reflect the activity through the acyl branch of the metabolic pathway leading to capsaicinoids. In addition, large genetic variation was observed for many well-established pepper aroma compounds. These profiling data can be used in breeding programs aimed at improving metabolite-based quality traits such as flavour and health-related metabolites in pepper fruits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-012-0432-6) contains supplementary material, which is available to

  2. Differential metabolomic analysis of the potential antiproliferative mechanism of olive leaf extract on the JIMT-1 breast cancer cell line.

    PubMed

    Barrajón-Catalán, Enrique; Taamalli, Amani; Quirantes-Piné, Rosa; Roldan-Segura, Cristina; Arráez-Román, David; Segura-Carretero, Antonio; Micol, Vicente; Zarrouk, Mokhtar

    2015-02-01

    A new differential metabolomic approach has been developed to identify the phenolic cellular metabolites derived from breast cancer cells treated with a supercritical fluid extracted (SFE) olive leaf extract. The SFE extract was previously shown to have significant antiproliferative activity relative to several other olive leaf extracts examined in the same model. Upon SFE extract incubation of JIMT-1 human breast cancer cells, major metabolites were identified by using HPLC coupled to electrospray ionization quadrupole-time-of-flight mass spectrometry (ESI-Q-TOF-MS). After treatment, diosmetin was the most abundant intracellular metabolite, and it was accompanied by minor quantities of apigenin and luteolin. To identify the putative antiproliferative mechanism, the major metabolites and the complete extract were assayed for cell cycle, MAPK and PI3K proliferation pathways modulation. Incubation with only luteolin showed a significant effect in cell survival. Luteolin induced apoptosis, whereas the whole olive leaf extract incubation led to a significant cell cycle arrest at the G1 phase. The antiproliferative activity of both pure luteolin and olive leaf extract was mediated by the inactivation of the MAPK-proliferation pathway at the extracellular signal-related kinase (ERK1/2). However, the flavone concentration of the olive leaf extract did not fully explain the strong antiproliferative activity of the extract. Therefore, the effects of other compounds in the extract, probably at the membrane level, must be considered. The potential synergistic effects of the extract also deserve further attention. Our differential metabolomics approach identified the putative intracellular metabolites from a botanical extract that have antiproliferative effects, and this metabolomics approach can be expanded to other herbal extracts or pharmacological complex mixtures.

  3. Untargeted metabolomics analysis revealed changes in the composition of glycerolipids and phospholipids in Bacillus subtilis under 1-butanol stress.

    PubMed

    Vinayavekhin, Nawaporn; Mahipant, Gumpanat; Vangnai, Alisa S; Sangvanich, Polkit

    2015-07-01

    1-Butanol has been utilized widely in industry and can be produced or transformed by microbes. However, current knowledge about the mechanisms of 1-butanol tolerance in bacteria remains quite limited. Here, we applied untargeted metabolomics to study Bacillus subtilis cells under 1-butanol stress and identified 55 and 37 ions with significantly increased and decreased levels, respectively. Using accurate mass determination, tandem mass spectra, and synthetic standards, 86 % of these ions were characterized. The levels of phosphatidylethanolamine, diglucosyldiacylglycerol, and phosphatidylserine were found to be upregulated upon 1-butanol treatment, whereas those of diacylglycerol and lysyl phosphatidylglycerol were downregulated. Most lipids contained 15:0/15:0, 16:0/15:0, and 17:0/15:0 acyl chains, and all were mapped to membrane lipid biosynthetic pathways. Subsequent two-stage quantitative real-time reverse transcriptase PCR analyses of genes in the two principal membrane lipid biosynthesis pathways revealed elevated levels of ywiE transcripts in the presence of 1-butanol and reduced expression levels of cdsA, pgsA, mprF, clsA, and yfnI transcripts. Thus, the gene transcript levels showed agreement with the metabolomics data. Lastly, the cell morphology was investigated by scanning electron microscopy, which indicated that cells became almost twofold longer after 1.4 % (v/v) 1-butanol stress for 12 h. Overall, the studies uncovered changes in the composition of glycerolipids and phospholipids in B. subtilis under 1-butanol stress, emphasizing the power of untargeted metabolomics in the discovery of new biological insights.

  4. Neuropsychiatric Symptoms in Inborn Errors of Metabolism: Incorporation of Genomic and Metabolomic Analysis into Therapeutics and Prevention

    PubMed Central

    Pan, Lisa

    2013-01-01

    Inborn errors of metabolism may present as a spectrum ranging from neonatal lethality to non-specific symptoms. Neuropsychiatric manifestations have been identified in three groups: those presenting as emergencies, those with chronic fluctuating symptoms, and those associated with mental retardation. Milder central nervous system specific inborn errors of metabolism may also present later in life with isolated psychiatric symptoms. Inborn errors of metabolism presenting with neuropsychiatric symptoms are described with illustrative case examples. Metabolomic and genomic approaches to identification and treatment are described. PMID:23525354

  5. Metabolomic Approaches for Characterizing Aquatic Ecosystems

    EPA Science Inventory

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

  6. Field-based Metabolomics for Assessing Contaminated Surface Waters

    EPA Science Inventory

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

  7. Integrated transcriptomic and metabolomic analysis of the central metabolism of Synechocystis sp. PCC 6803 under different trophic conditions.

    PubMed

    Yoshikawa, Katsunori; Hirasawa, Takashi; Ogawa, Kenichi; Hidaka, Yuki; Nakajima, Tsubasa; Furusawa, Chikara; Shimizu, Hiroshi

    2013-05-01

    Cyanobacteria have received considerable attention as a sustainable energy resource because of their organic material production capacity using light energy and CO2 as a carbon source. Therefore, it is important to understand the cellular metabolism of cyanobacteria for metabolic engineering. In this study, to shed light on the central metabolism of cyanobacteria, we performed transcriptomic and metabolomic analyses of a glucose-tolerant strain of the cyanobacterium Synechocystis sp. PCC 6803, which was cultured under auto- and mixotrophic conditions. Our results indicate that the oxidative pentose phosphate pathway and glycolysis are activated under mixotrophic conditions rather than autotrophic conditions. Moreover, we examined the effect of atrazine, a photosynthesis inhibitor, on the metabolism of PCC 6803 under mixotrophic conditions, which was defined as photoheterotrophic conditions, by transcriptomics and metabolomics. We demonstrated that the activity of the glycolytic pathway decreased due to the indirect effect of atrazine. In addition, the difference in transcriptional and metabolic changes between auto- and photoheterotrophic conditions could also be captured. The omics dataset reported herein provides clues for understanding the metabolism of cyanobacteria.

  8. Metabolomic Analysis of Diet-Induced Type 2 Diabetes Using UPLC/MS Integrated with Pattern Recognition Approach

    PubMed Central

    Sun, Hui; Zhang, Shuxiang; Zhang, Aihua; Yan, Guangli; Wu, Xiuhong; Han, Ying; Wang, Xijun

    2014-01-01

    Metabolomics represents an emerging discipline concerned with comprehensive assessment of small molecule endogenous metabolites in biological systems and provides a powerful approach insight into the mechanisms of diseases. Type 2 diabetes (T2D), called the burden of the 21st century, is growing with an epidemic rate. However, its precise molecular mechanism has not been comprehensively explored. In this study, we applied urinary metabolomics based on the UPLC/MS integrated with pattern recognition approaches to discover differentiating metabolites, to characterize and explore metabolic pathway disruption in an experimental model for high-fat-diet induced T2D. Six differentiating urinary metabolites were found in the negative mode, and two (2-(4-hydroxy-3-methoxy-phenyl) acetaldehyde sulfate, 2-phenylethanol glucuronide) of which were identified involving the key metabolic pathways linked to pentose and glucuronate interconversions, starch, sucrose metabolism and tyrosine metabolism. Our study provides new insight into pathophysiologic mechanisms and may enhance the understanding of T2D pathogenesis. PMID:24671089

  9. Proteomic and metabolomic analysis on the toxicological effects of As (III) and As (V) in juvenile mussel Mytilus galloprovincialis.

    PubMed

    Yu, Deliang; Ji, Chenglong; Zhao, Jianmin; Wu, Huifeng

    2016-05-01

    Inorganic arsenic (As) is a known pollutant including two chemical forms (arsenite (As III) and arsenate (As V)), in marine and coastal environment. Marine mussel Mytilus galloprovincialis is an important environmental monitoring species around the world. In this study, we focused on valence-specific responses of As in juvenile mussel M. galloprovincialis using a combined proteomic and metabolomic approach. Metabolic responses indicated that As (III) mainly caused disturbance in osmotic regulation in juvenile mussels. As (V) caused disturbances in both osmotic regulation and energy metabolism marked by different metabolic responses, including betaine, taurine, glucose and glycogen. Proteomic responses exhibited that As (III) had a significant negative effect on cytoskeleton and cell structure (actin and collagen alpha-6(VI) chain). As (V) affected some key enzymes involved in energy metabolism (cytosolic malate dehydrogenase, cMDH) and cell development (ornithine aminotransferase and astacin). Overall, all these results confirmed the valence-specific responses in juvenile mussels to As exposures. These findings demonstrate that a combined metabolomic and proteomic approach could provide an important insight into the toxicological effects of environmental pollutants in organisms.

  10. Metabolomic analysis of the effects of chronic arsenic exposure in a mouse model of diet-induced fatty liver disease

    PubMed Central

    Shi, Xue; Wei, Xiaoli; Koo, Imhoi; Schmidt, Robin H.; Yin, Xinmin; Kim, Seong Ho; Vaughn, Andrew; McClain, Craig J.; Arteel, Gavin E.

    2014-01-01

    Arsenic is a widely-distributed environmental component that is associated with a variety of cancer and non-cancer adverse health effects. Additional lifestyle factors, such as diet, contribute to the manifestation of disease. Recently, arsenic was found to increase inflammation and liver injury in a dietary model of fatty liver disease. The purpose of the present study was to investigate potential mechanisms of this diet-environment interaction via a high throughput metabolomics approach. GC×GC-TOF MS was used to identify metabolites that were significantly increased or decreased in the livers of mice fed a Western diet (a diet high in fat and cholesterol) and co-exposed to arsenic-contaminated drinking water. The results showed that there are distinct hepatic metabolomic profiles associated with eating a high fat diet, drinking arsenic-contaminated water, and the combination of the two. Among the metabolites that were decreased when arsenic exposure was combined with a high fat diet were short-chain and medium-chain fatty acid metabolites and the anti-inflammatory amino acid, glycine. These results are consistent with the observed increase in inflammation and cell death in the livers of these mice, and they point to potentially novel mechanisms by which these metabolic pathways could be altered by arsenic in the context of diet-induced fatty liver disease. PMID:24328084

  11. Metabolomic and flux-balance analysis of age-related decline of hypoxia tolerance in Drosophila muscle tissue

    PubMed Central

    Coquin, Laurence; Feala, Jacob D; McCulloch, Andrew D; Paternostro, Giovanni

    2008-01-01

    The fruitfly Drosophila melanogaster is increasingly used as a model organism for studying acute hypoxia tolerance and for studying aging, but the interactions between these two factors are not well known. Here we show that hypoxia tolerance degrades with age in post-hypoxic recovery of whole-body movement, heart rate and ATP content. We previously used 1H NMR metabolomics and a constraint-based model of ATP-generating metabolism to discover the end products of hypoxic metabolism in flies and generate hypotheses for the biological mechanisms. We expand the reactions in the model using tissue- and age-specific microarray data from the literature, and then examine metabolomic profiles of thoraxes after 4 h at 0.5% O2 and after 5 min of recovery in 40- versus 3-day-old flies. Model simulations were constrained to fluxes calculated from these data. Simulations suggest that the decreased ATP production during reoxygenation seen in aging flies can be attributed to reduced recovery of mitochondrial respiration pathways and concomitant overdependence on the acetate production pathway as an energy source. PMID:19096360

  12. Metabolomics in the study of kidney diseases.

    PubMed

    Weiss, Robert H; Kim, Kyoungmi

    2011-10-25

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

  13. Bile acid signaling in lipid metabolism: metabolomic and lipidomic analysis of lipid and bile acid markers linked to anti-obesity and anti-diabetes in mice.

    PubMed

    Qi, Yunpeng; Jiang, Changtao; Cheng, Jie; Krausz, Kristopher W; Li, Tiangang; Ferrell, Jessica M; Gonzalez, Frank J; Chiang, John Y L

    2015-01-01

    Bile acid synthesis is the major pathway for catabolism of cholesterol. Cholesterol 7α-hydroxylase (CYP7A1) is the rate-limiting enzyme in the bile acid biosynthetic pathway in the liver and plays an important role in regulating lipid, glucose and energy metabolism. Transgenic mice overexpressing CYP7A1 (CYP7A1-tg mice) were resistant to high-fat diet (HFD)-induced obesity, fatty liver, and diabetes. However the mechanism of resistance to HFD-induced obesity of CYP7A1-tg mice has not been determined. In this study, metabolomic and lipidomic profiles of CYP7A1-tg mice were analyzed to explore the metabolic alterations in CYP7A1-tg mice that govern the protection against obesity and insulin resistance by using ultra-performance liquid chromatography-coupled with electrospray ionization quadrupole time-of-flight mass spectrometry combined with multivariate analyses. Lipidomics analysis identified seven lipid markers including lysophosphatidylcholines, phosphatidylcholines, sphingomyelins and ceramides that were significantly decreased in serum of HFD-fed CYP7A1-tg mice. Metabolomics analysis identified 13 metabolites in bile acid synthesis including taurochenodeoxycholic acid, taurodeoxycholic acid, tauroursodeoxycholic acid, taurocholic acid, and tauro-β-muricholic acid (T-β-MCA) that differed between CYP7A1-tg and wild-type mice. Notably, T-β-MCA, an antagonist of the farnesoid X receptor (FXR) was significantly increased in intestine of CYP7A1-tg mice. This study suggests that reducing 12α-hydroxylated bile acids and increasing intestinal T-β-MCA may reduce high fat diet-induced increase of phospholipids, sphingomyelins and ceramides, and ameliorate diabetes and obesity. This article is part of a Special Issue entitled Linking transcription to physiology in lipodomics.

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

    PubMed Central

    Fearnley, Liam G; Inouye, Michael

    2016-01-01

    Metabolomics is becoming feasible for population-scale studies of human disease. In this review, we survey epidemiological studies that leverage metabolomics and multi-omics to gain insight into disease mechanisms. We outline key practical, technological and analytical limitations while also highlighting recent successes in integrating these data. The use of multi-omics to infer reaction rates is discussed as a potential future direction for metabolomics research, as a means of identifying biomarkers as well as inferring causality. Furthermore, we highlight established analysis approaches as well as simulation-based methods currently used in single- and multi-cell levels in systems biology. PMID:27118561

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

    PubMed

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-06-02

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

  16. Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats

    PubMed Central

    Tranchida, Fabrice; Shintu, Laetitia; Rakotoniaina, Zo; Tchiakpe, Léopold; Deyris, Valérie; Hiol, Abel; Caldarelli, Stefano

    2015-01-01

    We explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and glycoproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR. PMID:26288372

  17. UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: effect of experimental artefacts and anticoagulant.

    PubMed

    Barri, Thaer; Dragsted, Lars Ove

    2013-03-20

    Clotting and anticoagulation of blood samples may give rise to different metabolic profiles of serum and plasma samples, respectively. The anticoagulant used for blood plasma preparation may affect the resulting metabolic profile due to different mechanisms involved in anticoagulation by various agents, e.g. heparin, EDTA and citrate. In the present study, we looked into metabolite and other differences in matched serum and plasma samples and different plasma preparations by using untargeted UPLC-ESI-QTOF/MS profiling and multivariate data analysis (PCA and OPLS-DA). Metabolite differences between serum and plasma samples were mainly related to small peptides reflecting presence or absence of coagulation. Only subtle metabolite differences between the different plasma preparations were noticed, which were primarily related to ion suppression or enhancement caused by citrate and EDTA anticoagulants. For the first time, we also report that anticoagulant counter cation (Na+ or K+) in Na-citrate and K-EDTA plasma can make some metabolites more dominant in ESI-MS. Polymeric material residues originating from blood collection tubes for serum preparation were observed only in serum samples. Hypoxanthine and xanthine were found at higher levels in serum than in plasma samples, possibly due to release from the clot. Mass spectral features of sodium formate and potassium formate ion clusters were detected in citrate and EDTA plasma samples, respectively, originating from formate in mobile phase and Na(+) (in Na-citrate tubes) and K(+) (in K-EDTA tubes). Among the anticoagulants, heparin is recommended for plasma samples used for LC-ESI/MS-based metabolomics of hydrophilic compounds because no plasma interferences or matrix effects were noticed for this polarity range. Citrate and EDTA should be avoided since interferences and serious matrix effects were encountered on some co-eluting polar metabolites. Serum is recommended as a second choice and an alternative to plasma. In

  18. Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats.

    PubMed

    Tranchida, Fabrice; Shintu, Laetitia; Rakotoniaina, Zo; Tchiakpe, Léopold; Deyris, Valérie; Hiol, Abel; Caldarelli, Stefano

    2015-01-01

    We explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and glycoproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR.

  19. Isotopic Ratio Outlier Analysis of the S. cerevisiae Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery.

    PubMed

    Qiu, Yunping; Moir, Robyn; Willis, Ian; Beecher, Chris; Tsai, Yu-Hsuan; Garrett, Timothy J; Yost, Richard A; Kurland, Irwin J

    2016-03-01

    Isotopic ratio outlier analysis (IROA) is a (13)C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the S. cerevisiae metabolome. S. cerevisiae was grown in YNB media, containing randomized 95% (13)C, or 5%(13)C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%(13)C extracts, or light isotopologues in the 95%(13)C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the (12)C monoisotopic and the (13)C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate "clean" EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study.

  20. A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer

    NASA Astrophysics Data System (ADS)

    Auslander, Noam; Yizhak, Keren; Weinstock, Adam; Budhu, Anuradha; Tang, Wei; Wang, Xin Wei; Ambs, Stefan; Ruppin, Eytan

    2016-07-01

    Disrupted regulation of cellular processes is considered one of the hallmarks of cancer. We analyze metabolomic and transcriptomic profiles jointly collected from breast cancer and hepatocellular carcinoma patients to explore the associations between the expression of metabolic enzymes and the levels of the metabolites participating in the reactions they catalyze. Surprisingly, both breast cancer and hepatocellular tumors exhibit an increase in their gene-metabolites associations compared to noncancerous adjacent tissues. Following, we build predictors of metabolite levels from the expression of the enzyme genes catalyzing them. Applying these predictors to a large cohort of breast cancer samples we find that depleted levels of key cancer-related metabolites including glucose, glycine, serine and acetate are significantly associated with improved patient survival. Thus, we show that the levels of a wide range of metabolites in breast cancer can be successfully predicted from the transcriptome, going beyond the limited set of those measured.

  1. Transcriptomic, proteomic and metabolomic analysis of maize responses to UV-B: comparison of greenhouse and field growth conditions.

    PubMed

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

    2011-08-01

    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 hour 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.

  2. Microbial metabolomics in open microscale platforms

    PubMed Central

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

    2016-01-01

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

  3. Non-targeted metabolomics study for the analysis of chemical compositions in three types of tea by using gas chromatograph-mass spectrometry and liquid chromatography-mass spectrometry.

    PubMed

    Zhang, Lei; Zeng, Zhongda; Ye, Guozhu; Zhao, Chunxia; Lu, Xin; Xu, Guowang

    2014-08-01

    Tea is one of the most widely consumed beverages in the world for its benefits to daily life and health. To discover the difference and correlation of chemical compositions in the three typical types of tea, a non-targeted metabolomics method was developed. After the optimization of extraction methods, gas chromatography-time-of-flight mass spectrometry and liquid chromatography-quadrupole time-of-flight mass spectrometry were applied for metabolomics analysis, 1,812 and 2,608 features were obtained, respectively. By comparing with the known compounds in public and/or commercial databases, 173 compounds were tentatively identified, and 109 of them were experimentally confirmed by standards. Totally, 33 tea samples including 12, 12 and 9 samples of green, oolong and black tea, respectively, were analyzed by using the above two methods. Multivatiate analysis, Mann-Whitney U test and hierarchical cluster analysis were used to find and visualize the differential components in the three types of tea. Finally, 90 compounds, which contain catechins, amino acids, organic acids, flavonol glycosides, alkaloids, carbohydrates, lipids, etc, were found with a significant difference among them. This study demonstrates the potentials and power of metabolomics methods to understand the chemical secrets of tea. This should help a lot to optimize the processes of agriculture, storage, preparation and consumption.

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

    PubMed Central

    Alonso, Arnald; Marsal, Sara; Julià, Antonio

    2015-01-01

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

  5. Metabolomics and Its Application to Acute Lung Diseases

    PubMed Central

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

    2016-01-01

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

  6. Metabolomics and human nutrition.

    PubMed

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

    2011-04-01

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

  7. Metabolomic Analysis Reveals Increased Aerobic Glycolysis and Amino Acid Deficit in a Cellular Model of Amyotrophic Lateral Sclerosis.

    PubMed

    Valbuena, Gabriel N; Rizzardini, Milena; Cimini, Sara; Siskos, Alexandros P; Bendotti, Caterina; Cantoni, Lavinia; Keun, Hector C

    2016-05-01

    Defects in energy metabolism are potential pathogenic mechanisms in amyotrophic lateral sclerosis (ALS), a rapidly fatal disease with no cure. The mechanisms through which this occurs remain elusive and their understanding may prove therapeutically useful. We used metabolomics and stable isotope tracers to examine metabolic changes in a well-characterized cell model of familial ALS, the motor neuronal NSC-34 line stably expressing human wild-type Cu/Zn superoxide dismutase (wtSOD1) or mutant G93A (G93ASOD1). Our findings indicate that wt and G93ASOD1 expression both enhanced glucose metabolism under serum deprivation. However, in wtSOD1 cells, this phenotype increased supply of amino acids for protein and glutathione synthesis, while in G93ASOD1 cells it was associated with death, aerobic glycolysis, and a broad dysregulation of amino acid homeostasis. Aerobic glycolysis was mainly due to induction of pyruvate dehydrogenase kinase 1. Our study thus provides novel insight into the role of deranged energy metabolism as a cause of poor adaptation to stress and a promoter of neural cell damage in the presence of mutant SOD1. Furthermore, the metabolic alterations we report may help explain why mitochondrial dysfunction and impairment of the endoplasmic reticulum stress response are frequently seen in ALS.

  8. Comprehensive analysis of mitochondria in roots and hypocotyls of soybean under flooding stress using proteomics and metabolomics techniques.

    PubMed

    Komatsu, Setsuko; Yamamoto, Akifumi; Nakamura, Takuji; Nouri, Mohammad-Zaman; Nanjo, Yohei; Nishizawa, Keito; Furukawa, Kiyoshi

    2011-09-02

    Flooding is a serious problem for soybeans because it reduces growth and grain yield. Proteomic and metabolomic techniques were used to examine whether mitochondrial function is altered in soybeans by flooding stress. Mitochondrial fractions were purified from the roots and hypocotyls of 4-day-old soybean seedlings that had been flooded for 2 days. Mitochondrial matrix and membrane proteins were separated by two-dimensional polyacrylamide gel electrophoresis and blue-native polyacrylamide gel electrophoresis, respectively. Differentially expressed proteins and metabolites were identified using mass spectrometry. Proteins and metabolites related to the tricarboxylic acid cycle and γ-amino butyrate shunt were up-regulated by flooding stress, while inner membrane carrier proteins and proteins related to complexes III, IV, and V of the electron transport chains were down-regulated. The amounts of NADH and NAD were increased; however, ATP was significantly decreased by flooding stress. These results suggest that flooding directly impairs electron transport chains, although NADH production increases in the mitochondria through the tricarboxylic acid cycle.

  9. Untargeted metabolomics analysis reveals key pathways responsible for the synergistic killing of colistin and doripenem combination against Acinetobacter baumannii

    PubMed Central

    Maifiah, Mohd Hafidz Mahamad; Creek, Darren J.; Nation, Roger L.; Forrest, Alan; Tsuji, Brian T.; Velkov, Tony; Li, Jian

    2017-01-01

    Combination therapy is deployed for the treatment of multidrug-resistant Acinetobacter baumannii, as it can rapidly develop resistance to current antibiotics. This is the first study to investigate the synergistic effect of colistin/doripenem combination on the metabolome of A. baumannii. The metabolite levels were measured using LC-MS following treatment with colistin (2 mg/L) or doripenem (25 mg/L) alone, and their combination at 15 min, 1 hr and 4 hr (n = 4). Colistin caused early (15 min and 1 hr) disruption of the bacterial outer membrane and cell wall, as demonstrated by perturbation of glycerophospholipids and fatty acids. Concentrations of peptidoglycan biosynthesis metabolites decreased at 4 hr by doripenem alone, reflecting its mechanism of action. The combination induced significant changes to more key metabolic pathways relative to either monotherapy. Down-regulation of cell wall biosynthesis (via D-sedoheptulose 7-phosphate) and nucleotide metabolism (via D-ribose 5-phosphate) was associated with perturbations in the pentose phosphate pathway induced initially by colistin (15 min and 1 hr) and later by doripenem (4 hr). We discovered that the combination synergistically killed A. baumannii via time-dependent inhibition of different key metabolic pathways. Our study highlights the significant potential of systems pharmacology in elucidating the mechanism of synergy and optimizing antibiotic pharmacokinetics/pharmacodynamics. PMID:28358014

  10. Metabolomic analysis revealed the differential responses in two pedigrees of clam Ruditapes philippinarum towards Vibrio harveyi challenge.

    PubMed

    Liu, Xiaoli; Zhao, Jianmin; Wu, Huifeng; Wang, Qing

    2013-12-01

    Manila clam Ruditapes philippinarum is an important marine aquaculture shellfish. This species has several pedigrees including White, Zebra, Liangdao Red and Marine Red distributing in the coastal areas in North China. In this work, we studied the metabolic differences induced by Vibrio harveyi in hepatopancreas from White and Zebra clams using NMR-based metabolomics. Metabolic responses (e.g., amino acids, glucose, glycogen, ATP and succinate) and altered mRNA expression levels of related genes (ATP synthase, heat shock protein 90, defensin and lysozyme) suggested that V. harveyi induced clear disruption in energy metabolism and immune stresses in both White and Zebra clam hepatopancreas. However, V. harveyi caused obvious osmotic stress in Zebra clam hepatopancreas, which was not observed in V. harveyi-challenged White clams samples. In addition, V. harveyi challenge induced more severe disruption in energy metabolism and immune stress in White clams than in Zebra clams. Overall, our results indicated that the biological differences between different pedigrees of R. philippinarum should be considered in immunity studies.

  11. Metabolic alterations in the sera of Chinese patients with mild persistent asthma: a GC-MS-based metabolomics analysis

    PubMed Central

    Chang, Chun; Guo, Zhi-guo; He, Bei; Yao, Wan-zhen

    2015-01-01

    Aim: To character the specific metabolomics profiles in the sera of Chinese patients with mild persistent asthma and to explore potential metabolic biomarkers. Methods: Seventeen Chinese patients with mild persistent asthma and age- and sex-matched healthy controls were enrolled. Serum samples were collected, and serum metabolites were analyzed using GC-MS coupled with a series of multivariate statistical analyses. Results: Clear intergroup separations existed between the asthmatic patients and control subjects. A list of differential metabolites and several top altered metabolic pathways were identified. The levels of succinate (an intermediate in tricarboxylic acid cycle) and inosine were highly upregulated in the asthmatic patients, suggesting a greater effort to breathe during exacerbation and hypoxic stress due to asthma. Other differential metabolites, such as 3,4-dihydroxybenzoic acid and phenylalanine, were also identified. Furthermore, the differential metabolites possessed higher values of area under the ROC curve (AUC), suggesting an excellent clinical ability for the prediction of asthma. Conclusion: Metabolic activity is significantly altered in the sera of Chinese patients with mild persistent asthma. The data might be helpful for identifying novel biomarkers and therapeutic targets for asthma. PMID:26526201

  12. Time-resolved metabolomics analysis of individual differences during the early stage of lipopolysaccharide-treated rats

    PubMed Central

    Dai, Die; Gao, Yiqiao; Chen, Jiaqing; Huang, Yin; Zhang, Zunjian; Xu, Fengguo

    2016-01-01

    Lipopolysaccharide (LPS) can lead to uncontrollable cytokine production and eventually cause fatal sepsis syndrome. Individual toxicity difference of LPS has been widely reported. In our study we observed that two thirds of the rats (24/36) died at a given dose of LPS, while the rest (12/36) survived. Tracking the dynamic metabolic change in survival and non-survival rats in the early stage may reveal new system information to understand the inter-individual variation in response to LPS. As the time-resolved datasets are very complex and no single method can elucidate the problem clearly and comprehensively, the static and dynamic metabolomics methods were employed in combination as cross-validation. Intriguingly, some common results have been observed. Lipids were the main different metabolites between survival and non-survival rats in pre-dose serum and in the early stage of infection with LPS. The LPS treatment led to S-adenosly-methionine and total cysteine individual difference in early stage, and subsequent significant perturbations in energy metabolism and oxidative stress. Furthermore, cytokine profiles were analyzed to identify potential biological associations between cytokines and specific metabolites. Our collective findings may provide some heuristic guidance for elucidating the underlying mechanism of individual difference in LPS-mediated disease. PMID:27695004

  13. Comparisons of large (Vaccinium macrocarpon Ait.) and small (Vaccinium oxycoccos L., Vaccinium vitis-idaea L.) cranberry in British Columbia by phytochemical determination, antioxidant potential, and metabolomic profiling with chemometric analysis.

    PubMed

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

    2012-04-01

    There is a long history of use and modern commercial importance of large and small cranberries in North America. The central objective of the current research was to characterize and compare the chemical composition of 2 west coast small cranberry species traditionally used (Vaccinium oxycoccos L. and Vaccinium vitis-idaea L.) with the commercially cultivated large cranberry (Vaccinium macrocarpon Ait.) indigenous to the east coast of North America. V. oxycoccos and V. macrocarpon contained the 5 major anthocyanins known in cranberry; however, the ratio of glycosylated peonidins to cyanidins varied, and V. vitis-idaea did not contain measurable amounts of glycosylated peonidins. Extracts of all three berries were found to contain serotonin, melatonin, and ascorbic acid. Antioxidant activity was not found to correlate with indolamine levels while anthocyanin content showed a negative correlation, and vitamin C content positively correlated. From the metabolomics profiles, 4624 compounds were found conserved across V. macrocarpon, V. oxycoccoS, and V. vitis-idaea with a total of approximately 8000-10 000 phytochemicals detected in each species. From significance analysis, it was found that 2 compounds in V. macrocarpoN, 3 in V. oxycoccos, and 5 in V. vitis-idaea were key to the characterization and differentiation of these cranberry metabolomes. Through multivariate modeling, differentiation of the species was observed, and univariate statistical analysis was employed to provide a quality assessment of the models developed for the metabolomics data.

  14. A strategy for rapid analysis of xenobiotic metabolome of Sini decoction in vivo using ultra-performance liquid chromatography-electrospray ionization quadrupole-time-of-flight mass spectrometry combined with pattern recognition approach.

    PubMed

    Tan, Guangguo; Liu, Min; Dong, Xin; Wu, Si; Fan, Li; Qiao, Youbei; Chai, Yifeng; Wu, Hong

    2014-08-05

    Xenobiotic metabolome identificatioqn of Chinese herbal prescription in biological systems is a very challenging task. In the present work, a reliable strategy based on the combination of ultra-performance liquid chromatography-electrospray ionization quadrupole-time-of-flight mass spectrometry (UHPLC-ESI-Q-TOFMS) and pattern recognition approach such as principal component analysis (PCA) and partial least squared discriminant analysis (PLS-DA) was proposed to rapidly discover and analyze the xenobiotic metabolome from Sini decoction (SND). Using the S- and VIP-plots of PLS-DA, 96 and 112 interest ions from positive and negative ion datasets were extracted as SND metabolome in rat urine following oral administration of SND. Among them, 53 absorbed prototype components of SND and 49 metabolites were identified, which provided essential data for further studying the relationship between the chemical components and pharmacological activity of SND. Our results indicated that hydrolysis and demethylation were the major metabolic pathways of diterpenoid alkaloids, while glucuronidation, sulfation, hydrolysis, reduction, demethylation, and hydroxylation were the main metabolic pathways of flavonoids, and hydrolysis was the metabolic pathway of gingerol-related compounds. No saponin-related metabolites were detected.

  15. Prostate Cancer Patients–Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics

    NASA Astrophysics Data System (ADS)

    Fernández-Peralbo, M. A.; Gómez-Gómez, E.; Calderón-Santiago, M.; Carrasco-Valiente, J.; Ruiz-García, J.; Requena-Tapia, M. J.; Luque de Castro, M. D.; Priego-Capote, F.

    2016-12-01

    The existing clinical biomarkers for prostate cancer (PCa) diagnosis are far from ideal (e.g., the prostate specific antigen (PSA) serum level suffers from lack of specificity, providing frequent false positives leading to over-diagnosis). A key step in the search for minimum invasive tests to complement or replace PSA should be supported on the changes experienced by the biochemical pathways in PCa patients as compared to negative biopsy control individuals. In this research a comprehensive global analysis by LC–QTOF was applied to urine from 62 patients with a clinically significant PCa and 42 healthy individuals, both groups confirmed by biopsy. An unpaired t-test (p-value < 0.05) provided 28 significant metabolites tentatively identified in urine, used to develop a partial least squares discriminant analysis (PLS-DA) model characterized by 88.4 and 92.9% of sensitivity and specificity, respectively. Among the 28 significant metabolites 27 were present at lower concentrations in PCa patients than in control individuals, while only one reported higher concentrations in PCa patients. The connection among the biochemical pathways in which they are involved (DNA methylation, epigenetic marks on histones and RNA cap methylation) could explain the concentration changes with PCa and supports, once again, the role of metabolomics in upstream processes.

  16. Analysis of the Enantioselective Effects of PCB95 in Zebrafish (Danio rerio) Embryos through Targeted Metabolomics by UPLC-MS/MS

    PubMed Central

    Xu, Nana; Mu, Pengqian; Yin, Zhiqiang; Jia, Qi; Yang, Shuming; Qian, Yongzhong; Qiu, Jing

    2016-01-01

    As persistent organic pollutants, polychlorinated biphenyls (PCBs) accumulate in the bodies of animals and humans, resulting in toxic effects on the reproductive, immune, nervous, and endocrine systems. The biological and toxicological characteristics of enantiomers of chiral PCBs may differ, but these enantioselective effects of PCBs have not been fully characterized. In this study, we performed metabolomics analysis, using ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) to investigate the enantioselective toxic effects of PCB95 in zebrafish (Danio rerio) embryos after exposure to three dose levels of 0.1, 1, and 10 μg/L for 72 h. Multivariate analysis directly reflected the metabolic perturbations caused by PCB95. The effects of (-)-PCB95 and (+)-PCB95 were more prominent than those of the racemate in zebrafish embryos. A total of 26 endogenous metabolites were selected as potential marker metabolites with variable importance at projection values larger than 1 and significant differences (p<0.05). These metabolites included amino acids, organic acids, nucleosides, betaine, and choline. The changes in these biomarkers were dependent on the enantiomer-specific structures of PCB95. Fifteen metabolic pathways were significantly affected, and several nervous and immune system-related metabolites were significantly validated after exposure. These metabolic changes indicated that the toxic effects of PCB95 may be associated with the interaction of PCB95 with the nervous and immune systems, thus resulting in disruption of energy metabolism and liver function. PMID:27500732

  17. Metabolomics of Ulva lactuca Linnaeus (Chlorophyta) exposed to oil fuels: Fourier transform infrared spectroscopy and multivariate analysis as tools for metabolic fingerprint.

    PubMed

    Pilatti, Fernanda Kokowicz; Ramlov, Fernanda; Schmidt, Eder Carlos; Costa, Christopher; Oliveira, Eva Regina de; Bauer, Claudia M; Rocha, Miguel; Bouzon, Zenilda Laurita; Maraschin, Marcelo

    2017-01-30

    Fossil fuels, e.g. gasoline and diesel oil, account for substantial share of the pollution that affects marine ecosystems. Environmental metabolomics is an emerging field that may help unravel the effect of these xenobiotics on seaweeds and provide methodologies for biomonitoring coastal ecosystems. In the present study, FTIR and multivariate analysis were used to discriminate metabolic profiles of Ulva lactuca after in vitro exposure to diesel oil and gasoline, in combinations of concentrations (0.001%, 0.01%, 0.1%, and 1.0% - v/v) and times of exposure (30min, 1h, 12h, and 24h). PCA and HCA performed on entire mid-infrared spectral window were able to discriminate diesel oil-exposed thalli from the gasoline-exposed ones. HCA performed on spectral window related to the protein absorbance (1700-1500cm(-1)) enabled the best discrimination between gasoline-exposed samples regarding the time of exposure, and between diesel oil-exposed samples according to the concentration. The results indicate that the combination of FTIR with multivariate analysis is a simple and efficient methodology for metabolic profiling with potential use for biomonitoring strategies.

  18. 1H NMR metabolomic study of auxotrophic starvation in yeast using Multivariate Curve Resolution-Alternating Least Squares for Pathway Analysis

    PubMed Central

    Puig-Castellví, Francesc; Alfonso, Ignacio; Piña, Benjamin; Tauler, Romà

    2016-01-01

    Disruption of specific metabolic pathways constitutes the mode of action of many known toxicants and it is responsible for the adverse phenotypes associated to human genetic defects. Conversely, many industrial applications rely on metabolic alterations of diverse microorganisms, whereas many therapeutic drugs aim to selectively disrupt pathogens’ metabolism. In this work we analyzed metabolic changes induced by auxotrophic starvation conditions in yeast in a non-targeted approach, using one-dimensional proton Nuclear Magnetic Resonance spectroscopy (1H NMR) and chemometric analyses. Analysis of the raw spectral datasets showed specific changes linked to the different stages during unrestricted yeast growth, as well as specific changes linked to each of the four tested starvation conditions (L-methionine, L-histidine, L-leucine and uracil). Analysis of changes in concentrations of more than 40 metabolites by Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) showed the normal progression of key metabolites during lag, exponential and stationary unrestricted growth phases, while reflecting the metabolic blockage induced by the starvation conditions. In this case, different metabolic intermediates accumulated over time, allowing identification of the different metabolic pathways specifically affected by each gene disruption. This synergy between NMR metabolomics and molecular biology may have clear implications for both genetic diagnostics and drug development. PMID:27485935

  19. Prostate Cancer Patients–Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics

    PubMed Central

    Fernández-Peralbo, M. A.; Gómez-Gómez, E.; Calderón-Santiago, M.; Carrasco-Valiente, J.; Ruiz-García, J.; Requena-Tapia, M. J.; Luque de Castro, M. D.; Priego-Capote, F.

    2016-01-01

    The existing clinical biomarkers for prostate cancer (PCa) diagnosis are far from ideal (e.g., the prostate specific antigen (PSA) serum level suffers from lack of specificity, providing frequent false positives leading to over-diagnosis). A key step in the search for minimum invasive tests to complement or replace PSA should be supported on the changes experienced by the biochemical pathways in PCa patients as compared to negative biopsy control individuals. In this research a comprehensive global analysis by LC–QTOF was applied to urine from 62 patients with a clinically significant PCa and 42 healthy individuals, both groups confirmed by biopsy. An unpaired t-test (p-value < 0.05) provided 28 significant metabolites tentatively identified in urine, used to develop a partial least squares discriminant analysis (PLS-DA) model characterized by 88.4 and 92.9% of sensitivity and specificity, respectively. Among the 28 significant metabolites 27 were present at lower concentrations in PCa patients than in control individuals, while only one reported higher concentrations in PCa patients. The connection among the biochemical pathways in which they are involved (DNA methylation, epigenetic marks on histones and RNA cap methylation) could explain the concentration changes with PCa and supports, once again, the role of metabolomics in upstream processes. PMID:27910903

  20. Metabolomics analysis of the toxicity pathways of triphenyl phosphate in HepaRG cells and comparison to oxidative stress mechanisms caused by acetaminophen.

    PubMed

    Van den Eede, Nele; Cuykx, Matthias; Rodrigues, Robim M; Laukens, Kris; Neels, Hugo; Covaci, Adrian; Vanhaecke, Tamara

    2015-12-01

    Since the publication of REACH guidelines, the need for in vitro tools for toxicity testing has increased. We present here the development of a hepatotoxicity testing tool using human HepaRG cell cultures and metabolomics. HepaRG cells were exposed to either 4mM acetaminophen (APAP) as reference toxicant for oxidative stress or 50 μM triphenyl phosphate (TPHP) as toxicant with unknown toxicity pathways (TPs). After 72 h exposure, cells were subjected to quenching and liquid-liquid extraction which resulted in a polar and an apolar fraction. Analysis of fractions was performed by ultrahigh performance liquid chromatography-high resolution tandem mass spectrometry (UHPLC-QTOF-MS). Significantly up or down regulated metabolites were selected by univariate statistics prior to identification. In order to obtain robust and specific TP biomarkers, the experiment was also repeated using a different culture medium composition to assess which metabolites show consistent changes. Potential biomarkers belonging to different TPs were found for APAP and TPHP. For APAP, the biomarkers were related to a decrease in unsaturated phospholipids, and for TPHP to an accumulation of phosphoglycerolipids and increase of palmitoyl lysophosphatidylcholine. This first proof-of-concept opens new perspectives for the analysis of other (reference) toxicants with different TPs and it can be used to expand the in vitro tool for hepatotoxicity screening of various compounds.

  1. Metabolomics protocols for filamentous fungi.

    PubMed

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

    2012-01-01

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

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

    PubMed

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

    2014-01-01

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

  3. Solving the Differential Biochemical Jacobian from Metabolomics Covariance Data

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2013-10-01

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

  5. Blood Transcriptomics and Metabolomics for Personalized Medicine

    DTIC Science & Technology

    2015-10-31

    online 31 October 2015 Keywords: Transcriptomics Metabolomics Blood systems biology Personalized medicine Data integrationMolecular analysis of blood...samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology . Recent developments have opened new...article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Contents1. An overdue review of “blood systems biology

  6. A Metabolomic Analysis of Omega-3 Fatty Acid-Mediated Attenuation of Western Diet-Induced Nonalcoholic Steatohepatitis in LDLR-/- Mice

    PubMed Central

    Depner, Christopher M.; Traber, Maret G.; Bobe, Gerd; Kensicki, Elizabeth; Bohren, Kurt M.; Milne, Ginger; Jump, Donald B.

    2013-01-01

    Background Nonalcoholic steatohepatitis (NASH) is a progressive form of nonalcoholic fatty liver disease and a risk factor for cirrhosis, hepatocellular carcinoma and liver failure. Previously, we reported that dietary docosahexaenoic acid (DHA, 22:6,n-3) was more effective than eicosapentaenoic acid (EPA, 20:5,n-3) at reversing western diet (WD) induced NASH in LDLR-/- mice. Methods Using livers from our previous study, we carried out a global non-targeted metabolomic approach to quantify diet-induced changes in hepatic metabolism. Results Livers from WD + olive oil (WD + O)-fed mice displayed histological and gene expression features consistent with NASH. The metabolomic analysis of 320 metabolites established that the WD and n-3 polyunsaturated fatty acid (PUFA) supplementation had broad effects on all major metabolic pathways. Livers from WD + O-fed mice were enriched in saturated (SFA) and monounsaturated fatty acids (MUFA), palmitoyl-sphingomyelin, cholesterol, n-6 PUFA, n-6 PUFA-containing phosphoglycerolipids, n-6 PUFA-derived oxidized lipids (12-HETE) and depleted of C20-22 n-3 PUFA-containing phosphoglycerolipids, C20-22 n-3 PUFA-derived oxidized lipids (18-HEPE, 17,18-DiHETE) and S-lactoylglutathione, a methylglyoxal detoxification product. WD + DHA was more effective than WD + EPA at attenuating WD + O-induced changes in NASH gene expression markers, n-6 PUFA and oxidized lipids, citrate and S-lactosyl glutathione. Diet-induced changes in hepatic MUFA and sphingolipid content were associated with changes in expression of enzymes involved in MUFA and sphingolipid synthesis. Changes in hepatic oxidized fatty acids and S-lactoylglutathione, however, correlated with hepatic n-3 and n-6 C20-22 PUFA content. Hepatic C20-22 n-3 PUFA content was inversely associated with hepatic α-tocopherol and ascorbate content and positively associated with urinary F2- and F3-isoprostanes, revealing diet effects on whole body oxidative stress. Conclusion DHA regulation of

  7. Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha‐tocopherol, beta‐carotene cancer prevention (ATBC) study

    PubMed Central

    Mondul, Alison M.; Moore, Steven C.; Weinstein, Stephanie J.; Karoly, Edward D.; Sampson, Joshua N.

    2015-01-01

    Despite decades of concerted epidemiological research, relatively little is known about the etiology of prostate cancer. As genome‐wide association studies have identified numerous genetic variants, so metabolomic profiling of blood and other tissues represents an agnostic, “broad‐spectrum” approach for examining potential metabolic biomarkers of prostate cancer risk. To this end, we conducted a prospective analysis of prostate cancer within the Alpha‐Tocopherol, Beta‐Carotene Cancer Prevention Study cohort based on 200 cases (100 aggressive) and 200 controls (age‐ and blood collection date‐matched) with fasting serum collected up to 20 years prior to case diagnoses. Ultrahigh performance liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy identified 626 compounds detected in >95% of the men and the odds ratio per 1‐standard deviation increase in log‐metabolite levels and risk were estimated using conditional logistic regression. We observed strong inverse associations between energy and lipid metabolites and aggressive cancer (p = 0.018 and p = 0.041, respectively, for chemical class over‐representation). Inositol‐1‐phosphate showed the strongest association (OR = 0.56, 95% CI = 0.39–0.81, p = 0.002) and glycerophospholipids and fatty acids were heavily represented; e.g., oleoyl‐linoleoyl‐glycerophosphoinositol (OR = 0.64, p = 0.004), 1‐stearoylglycerophosphoglycerol (OR=0.65, p = 0.025), stearate (OR=0.65, p = 0.010) and docosadienoate (OR = 0.66, p = 0.014). Both alpha‐ketoglutarate and citrate were associated with aggressive disease risk (OR = 0.69, 95% CI = 0.51–0.94, p = 0.02; OR = 0.69, 95% CI = 0.50–0.95, p = 0.02), as were elevated thyroxine and trimethylamine oxide (OR = 1.65, 95% CI = 1.08–2.54, p = 0.021; and OR = 1.36, 95% CI = 1.02–1.81, p = 0.039). Serum PSA adjustment did not alter the

  8. Transcriptomic and metabolomic analysis of copper stress acclimation in Ectocarpus siliculosus highlights signaling and tolerance mechanisms in brown algae

    PubMed Central

    2014-01-01

    Background Brown algae are sessile macro-organisms of great ecological relevance in coastal ecosystems. They evolved independently from land plants and other multicellular lineages, and therefore hold several original ontogenic and metabolic features. Most brown algae grow along the coastal zone where they face frequent environmental changes, including exposure to toxic levels of heavy metals such as copper (Cu). Results We carried out large-scale transcriptomic and metabolomic analyses to decipher the short-term acclimation of the brown algal model E. siliculosus to Cu stress, and compared these data to results known for other abiotic stressors. This comparison demonstrates that Cu induces oxidative stress in E. siliculosus as illustrated by the transcriptomic overlap between Cu and H2O2 treatments. The common response to Cu and H2O2 consisted in the activation of the oxylipin and the repression of inositol signaling pathways, together with the regulation of genes coding for several transcription-associated proteins. Concomitantly, Cu stress specifically activated a set of genes coding for orthologs of ABC transporters, a P1B-type ATPase, ROS detoxification systems such as a vanadium-dependent bromoperoxidase, and induced an increase of free fatty acid contents. Finally we observed, as a common abiotic stress mechanism, the activation of autophagic processes on one hand and the repression of genes involved in nitrogen assimilation on the other hand. Conclusions Comparisons with data from green plants indicate that some processes involved in Cu and oxidative stress response are conserved across these two distant lineages. At the same time the high number of yet uncharacterized brown alga-specific genes induced in response to copper stress underlines the potential to discover new components and molecular interactions unique to these organisms. Of particular interest for future research is the potential cross-talk between reactive oxygen species (ROS)-, myo

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

    PubMed

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

    2014-01-01

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

  10. (1)H-NMR analysis of the human urinary metabolome in response to an 18-month multi-component exercise program and calcium-vitamin-D3 supplementation in older men.

    PubMed

    Sheedy, John R; Gooley, Paul R; Nahid, Amsha; Tull, Dedreia L; McConville, Malcolm J; Kukuljan, Sonja; Nowson, Caryl A; Daly, Robin M; Ebeling, Peter R

    2014-11-01

    The musculoskeletal benefits of calcium and vitamin-D3 supplementation and exercise have been extensively studied, but the effect on metabolism remains contentious. Urine samples were analyzed by (1)H-NMR spectroscopy from participants recruited for an 18-month, randomized controlled trial of a multi-component exercise program and calcium and vitamin-D3 fortified milk consumption. It was shown previously that no increase in musculoskeletal composition was observed for participants assigned to the calcium and vitamin-D3 intervention, but exercise resulted in increased bone mineral density, total lean body mass, and muscle strength. Retrospective metabolomics analysis of urine samples from patients involved in this study revealed no distinct changes in the urinary metabolome in response to the calcium and vitamin-D3 intervention, but significant changes followed the exercise intervention, notably a reduction in creatinine and an increase in choline, guanidinoacetate, and hypoxanthine (p < 0.001, fold change > 1.5). These metabolites are intrinsically involved in anaerobic ATP synthesis, intracellular buffering, and methyl-balance regulation. The exercise intervention had a marked effect on the urine metabolome and markers of muscle turnover but none of these metabolites were obvious markers of bone turnover. Measurement of specific urinary exercise biomarkers may provide a basis for monitoring performance and metabolic response to exercise regimes.

  11. Investigation on the antidepressant effect of sea buckthorn seed oil through the GC-MS-based metabolomics approach coupled with multivariate analysis.

    PubMed

    Tian, Jun-sheng; Liu, Cai-chun; Xiang, Huan; Zheng, Xiao-fen; Peng, Guo-jiang; Zhang, Xiang; Du, Guan-hua; Qin, Xue-mei

    2015-11-01

    Depression is one of the prevalent and serious mental disorders and the number of depressed patients has been on the rise globally during the recent decades. Sea buckthorn seed oil from traditional Chinese medicine (TCM) is edible and has been widely used for treatment of different diseases for a long time. However, there are few published reports on the antidepressant effect of sea buckthorn seed oil. With the objective of finding potential biomarkers of the therapeutic response of sea buckthorn seed oil in chronic unpredictable mild stress (CUMS) rats, urine metabolomics based on gas chromatography-mass spectrometry (GC-MS) coupled with multivariate analysis was applied. In this study, we discovered a higher level of pimelic acid as well as palmitic acid and a lower level of suberic acid, citrate, phthalic acid, cinnamic acid and Sumiki's acid in urine of rats exposed to CUMS procedures after sea buckthorn seed oil was administered. These changes of metabolites are involved in energy metabolism, fatty acid metabolism and other metabolic pathways as well as in the synthesis of neurotransmitters and it is helpful to facilitate the efficacy evaluation and mechanism elucidating the effect of sea buckthorn seed oil for depression management.

  12. Metabolomic and mass isotopomer analysis of liver gluconeogenesis and citric acid cycle. I. Interrelation between gluconeogenesis and cataplerosis; formation of methoxamates from aminooxyacetate and ketoacids.

    PubMed

    Yang, Lili; Kombu, Rajan S; Kasumov, Takhar; Zhu, Shu-Han; Cendrowski, Andrea V; David, France; Anderson, Vernon E; Kelleher, Joanne K; Brunengraber, Henri

    2008-08-08

    We conducted a study coupling metabolomics and mass isotopomer analysis of liver gluconeogenesis and citric acid cycle. Rat livers were perfused with lactate or pyruvate +/- aminooxyacetate or mercaptopicolinate in the presence of 40% enriched NaH(13)CO(3). Other livers were perfused with dimethyl [1,4-(13)C(2)]succinate +/- mercaptopicolinate. In this first of two companion articles, we show that a substantial fraction of gluconeogenic carbon leaves the liver as citric acid cycle intermediates, mostly alpha-ketoglutarate. The efflux of gluconeogenic carbon ranges from 10 to 200% of the rate of liver gluconeogenesis. This cataplerotic efflux of gluconeogenic carbon may contribute to renal gluconeogenesis in vivo. Multiple crossover analyses of concentrations of gluconeogenic intermediates and redox measurements expand previous reports on the regulation of gluconeogenesis and the effects of inhibitors. We also demonstrate the formation of adducts from the condensation, in the liver, of (i) aminooxyacetate with pyruvate, alpha-ketoglutarate, and oxaloacetate and (ii) mercaptopicolinate and pyruvate. These adducts may exert metabolic effects unrelated to their effect on gluconeogenesis.

  13. Learning to Classify Organic and Conventional Wheat - A Machine Learning Driven Approach Using the MeltDB 2.0 Metabolomics Analysis Platform.

    PubMed

    Kessler, Nikolas; Bonte, Anja; Albaum, Stefan P; Mäder, Paul; Messmer, Monika; Goesmann, Alexander; Niehaus, Karsten; Langenkämper, Georg; Nattkemper, Tim W

    2015-01-01

    We present results of our machine learning approach to the problem of classifying GC-MS data originating from wheat grains of different farming systems. The aim is to investigate the potential of learning algorithms to classify GC-MS data to be either from conventionally grown or from organically grown samples and considering different cultivars. The motivation of our work is rather obvious nowadays: increased demand for organic food in post-industrialized societies and the necessity to prove organic food authenticity. The background of our data set is given by up to 11 wheat cultivars that have been cultivated in both farming systems, organic and conventional, throughout 3 years. More than 300 GC-MS measurements were recorded and subsequently processed and analyzed in the MeltDB 2.0 metabolomics analysis platform, being briefly outlined in this paper. We further describe how unsupervised (t-SNE, PCA) and supervised (SVM) methods can be applied for sample visualization and classification. Our results clearly show that years have most and wheat cultivars have second-most influence on the metabolic composition of a sample. We can also show that for a given year and cultivar, organic and conventional cultivation can be distinguished by machine-learning algorithms.

  14. RNA-Seq-based transcriptomic and metabolomic analysis reveal stress responses and programmed cell death induced by acetic acid in Saccharomyces cerevisiae.

    PubMed

    Dong, Yachen; Hu, Jingjin; Fan, Linlin; Chen, Qihe

    2017-02-17

    As a typical harmful inhibitor in cellulosic hydrolyzates, acetic acid not only hinders bioethanol production, but also induces cell death in Saccharomyces cerevisiae. Herein, we conducted both transcriptomic and metabolomic analyses to investigate the global responses under acetic acid stress at different stages. There were 295 up-regulated and 427 down-regulated genes identified at more than two time points during acetic acid treatment (150 mM, pH 3.0). These differentially expressed genes (DEGs) were mainly involved in intracellular homeostasis, central metabolic pathway, transcription regulation, protein folding and stabilization, ubiquitin-dependent protein catabolic process, vesicle-mediated transport, protein synthesis, MAPK signaling pathways, cell cycle, programmed cell death, etc. The interaction network of all identified DEGs was constructed to speculate the potential regulatory genes and dominant pathways in response to acetic acid. The transcriptional changes were confirmed by metabolic profiles and phenotypic analysis. Acetic acid resulted in severe acidification in both cytosol and mitochondria, which was different from the effect of extracellular pH. Additionally, the imbalance of intracellular acetylation was shown to aggravate cell death under this stress. Overall, this work provides a novel and comprehensive understanding of stress responses and programmed cell death induced by acetic acid in yeast.

  15. Untargeted metabolomic analysis of human serum samples associated with different levels of red meat consumption: A possible indicator of type 2 diabetes?

    PubMed

    Carrizo, Daniel; Chevallier, Olivier P; Woodside, Jayne V; Brennan, Sarah F; Cantwell, Marie M; Cuskelly, Geraldine; Elliott, Christopher T

    2017-04-15

    Red meat consumption has been associated with negative health effects. A study to identify biomarkers of meat consumption was undertaken using serum samples collected from combining high resolution mass spectrometry (UPLC-QTof-MS) and chemometrics. Using orthogonal partial last-squares discriminant analysis (OPLS-DA), multivariate models were created for both modes of acquisition (ESI-/ESI+) and red meat intake classes (YES/NO). In the serum samples, a total 3280 and 3225 ions of interest were detected in positive and negative modes, respectively. Of these, 62 were found to be significantly different (p<0.05) between the two groups. Glycerophospholipids as well as other family lipids, such as lysophospholipids or sphingomyelin, were found significantly (p<0.05) different between yes and no red meat intake groups. This study has shown metabolomics fingerprints have the capability to identify potential biomarkers of red meat consumption, as well as possible health risk factors (e.g., key metabolic families related to the risk of development type 2 diabetes).

  16. RNA-Seq-based transcriptomic and metabolomic analysis reveal stress responses and programmed cell death induced by acetic acid in Saccharomyces cerevisiae

    PubMed Central

    Dong, Yachen; Hu, Jingjin; Fan, Linlin; Chen, Qihe

    2017-01-01

    As a typical harmful inhibitor in cellulosic hydrolyzates, acetic acid not only hinders bioethanol production, but also induces cell death in Saccharomyces cerevisiae. Herein, we conducted both transcriptomic and metabolomic analyses to investigate the global responses under acetic acid stress at different stages. There were 295 up-regulated and 427 down-regulated genes identified at more than two time points during acetic acid treatment (150 mM, pH 3.0). These differentially expressed genes (DEGs) were mainly involved in intracellular homeostasis, central metabolic pathway, transcription regulation, protein folding and stabilization, ubiquitin-dependent protein catabolic process, vesicle-mediated transport, protein synthesis, MAPK signaling pathways, cell cycle, programmed cell death, etc. The interaction network of all identified DEGs was constructed to speculate the potential regulatory genes and dominant pathways in response to acetic acid. The transcriptional changes were confirmed by metabolic profiles and phenotypic analysis. Acetic acid resulted in severe acidification in both cytosol and mitochondria, which was different from the effect of extracellular pH. Additionally, the imbalance of intracellular acetylation was shown to aggravate cell death under this stress. Overall, this work provides a novel and comprehensive understanding of stress responses and programmed cell death induced by acetic acid in yeast. PMID:28209995

  17. Metabolomic analysis reveals key metabolites related to the rapid adaptation of Saccharomyce cerevisiae to multiple inhibitors of furfural, acetic acid, and phenol.

    PubMed

    Wang, Xin; Li, Bing-Zhi; Ding, Ming-Zhu; Zhang, Wei-Wen; Yuan, Ying-Jin

    2013-03-01

    During hydrolysis of lignocellulosic biomass, a broad range of inhibitors are generated, which interfere with yeast growth and bioethanol production. In order to improve the strain tolerance to multiple inhibitors--acetic acid, furfural, and phenol (three representative lignocellulose-derived inhibitors) and uncover the underlying tolerant mechanism, an adaptation experiment was performed in which the industrial Saccharomyces cerevisiae was cultivated repeatedly in a medium containing multiple inhibitors. The adaptation occurred quickly, accompanied with distinct increase in growth rate, glucose utilization rate, furfural metabolism rate, and ethanol yield, only after the first transfer. A similar rapid adaptation was also observed for the lab strains of BY4742 and BY4743. The metabolomic analysis was employed to investigate the responses of the industrial S. cereviaise to three inhibitors during the adaptation. The results showed that higher levels of 2-furoic acid, 2, 3-butanediol, intermediates in glycolytic pathway, and amino acids derived from glycolysis, were discovered in the adapted strains, suggesting that enhanced metabolic activity in these pathways may relate to resistance against inhibitors. Additionally, through single-gene knockouts, several genes related to alanine metabolism, GABA shunt, and glycerol metabolism were verified to be crucial for the resistance to multiple inhibitors. This study provides new insights into the tolerance mechanism against multiple inhibitors, and guides for the improvement of tolerant ethanologenic yeast strains for lignocellulose-bioethanol fermentation.

  18. Comparative metabolomic analysis highlights the involvement of sugars and glycerol in melatonin-mediated innate immunity against bacterial pathogen in Arabidopsis.

    PubMed

    Qian, Yongqiang; Tan, Dun-Xian; Reiter, Russel J; Shi, Haitao

    2015-10-28

    Melatonin is an important secondary messenger in plant innate immunity against the bacterial pathogen Pseudomonas syringe pv. tomato (Pst) DC3000 in the salicylic acid (SA)- and nitric oxide (NO)-dependent pathway. However, the metabolic homeostasis in melatonin-mediated innate immunity is unknown. In this study, comparative metabolomic analysis found that the endogenous levels of both soluble sugars (fructose, glucose, melibose, sucrose, maltose, galatose, tagatofuranose and turanose) and glycerol were commonly increased after both melatonin treatment and Pst DC3000 infection in Arabidopsis. Further studies showed that exogenous pre-treatment with fructose, glucose, sucrose, or glycerol increased innate immunity against Pst DC3000 infection in wild type (Col-0) Arabidopsis plants, but largely alleviated their effects on the innate immunity in SA-deficient NahG plants and NO-deficient mutants. This indicated that SA and NO are also essential for sugars and glycerol-mediated disease resistance. Moreover, exogenous fructose, glucose, sucrose and glycerol pre-treatments remarkably increased endogenous NO level, but had no significant effect on the endogenous melatonin level. Taken together, this study highlights the involvement of sugars and glycerol in melatonin-mediated innate immunity against bacterial pathogen in SA and NO-dependent pathway in Arabidopsis.

  19. Dissecting Bottromycin Biosynthesis Using Comparative Untargeted Metabolomics

    PubMed Central

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

    2016-01-01

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

  20. A new exploration of licorice metabolome.

    PubMed

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

    2017-04-15

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

  1. Dissecting Bottromycin Biosynthesis Using Comparative Untargeted Metabolomics.

    PubMed

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

    2016-08-08

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

  2. Tracer-based Metabolomics: Concepts and Practices

    PubMed Central

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

    2010-01-01

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

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

    PubMed

    McGhie, Tony K; Rowan, Daryl D

    2012-01-01

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

  4. Metabolomics of genetically modified crops.

    PubMed

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

    2014-10-20

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

  5. Metabolomics of Genetically Modified Crops

    PubMed Central

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

    2014-01-01

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

  6. Metabolomics in diabetic complications.

    PubMed

    Filla, Laura A; Edwards, James L

    2016-04-01

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

  7. Serum Metabolomics in Rats after Acute Paraquat Poisoning.

    PubMed

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

    2015-01-01

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

  8. Metabolomic profiles of current cigarette smokers.

    PubMed

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

    2017-02-01

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

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

    PubMed Central

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

    2008-01-01

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

  10. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

    SciTech Connect

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

    2014-12-12

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

  11. Metabolomic Study on Idiosyncratic Liver Injury Induced by Different Extracts of Polygonum multiflorum in Rats Integrated with Pattern Recognition and Enriched Pathways Analysis

    PubMed Central

    Li, Chun-Yu; Tu, Can; Gao, Dan; Wang, Rui-Lin; Zhang, Hai-Zhu; Niu, Ming; Li, Rui-Yu; Zhang, Cong-En; Li, Rui-Sheng; Xiao, Xiao-He; Yang, Mei-Hua; Wang, Jia-Bo

    2016-01-01

    Currently, numerous liver injury cases related to a famous Chinese herb- Polygonum Multiflorum (Heshouwu in Chinese) have attracted great attention in many countries. Our previous work showed that Heshouwu-induced hepatotoxicity belonged to idiosyncratic drug-induced liver injury (IDILI). Unfortunately, the components and mechanisms attributed to IDILI of Heshouwu are difficult to determine and thus remain unknown. Attempts to explore puzzles, we prepared the chloroform (CH)-, ethyl acetate (EA)-, and residue (RE) extracts of Heshouwu to investigate IDILI constituents and underlying mechanisms, using biochemistry, histopathology, and metabolomics examinations. The results showed that co-treatment with non-toxic dose of lipopolysaccharide (LPS) and EA extract could result in evident liver injury, indicated by the significant elevation of plasma alanine aminotransferase and aspartate aminotransferase activities, as well as obvious liver histologic damage; whereas other two separated fractions, CH and RE extracts, failed to induce observable liver injury. Furthermore, 21 potential metabolomic biomarkers that differentially expressed in LPS/EA group compared with other groups without liver injury were identified by untargeted metabolomics, mainly involved two pathways: tricarboxylic acid cycle and sphingolipid metabolism. This work illustrated EA extract had close association with the idiosyncratic hepatotoxicity of Heshouwu and provided a metabolomic insight into IDILI of different extracts from Heshouwu. PMID:28018221

  12. FTIR analysis of the metabolomic stress response induced by N-alkyltropinium bromide surfactants in the yeasts Saccharomyces cerevisiae and Candida albicans.

    PubMed

    Corte, Laura; Tiecco, Matteo; Roscini, Luca; Germani, Raimondo; Cardinali, Gianluigi

    2014-04-01

    The activity of surfactants against fungal cells has been studied less than against bacteria, although the medical and industrial importance of the former is of paramount importance. In this paper the surfactant biocidal effect was measured in the yeasts Saccharomyces cerevisiae and Candida albicans with a previously described FTIR bioassay which estimates the stress level as function of the FTIR spectra variation of the cells upon exposition to the chemicals. N-tetradecyltropinium bromide was chosen as stressing agent on the basis of previous preliminary study demonstrating its ability to kill prokaryotic and especially eukaryotic cells at concentration around or over the critical micellar concentration (c.m.c.). Here we show that this surfactant is able to inactivate S. cerevisiae cells at 0.4mM and C. albicans cells at 0.6mM after 1h exposition. FTIR analysis revealed that the surfactant induced metabolomics reactions of S. cerevisiae cells in the regions of amides (W2) and fatty acids (W1). In the same way C. albicans cells showed the maximum stress response in amides (W2) and mixed (W3) regions. Variations of the hydrophobic tail of this surfactant produced a reduced level of cell stress with both the 12C and 16C variants; although these two compounds were more effective in inducing cell mortality in S. cerevisiae but not in C. albicans. In conclusion, this paper has shown that, for this surfactant, the n-alkyl chain must vary between 12C and 16C and that the hydrophilic head size is not as critical as the tail length.

  13. Nontargeted metabolomic analysis and "commercial-homophyletic" comparison-induced biomarkers verification for the systematic chemical differentiation of five different parts of Panax ginseng.

    PubMed

    Qiu, Shi; Yang, Wen-Zhi; Yao, Chang-Liang; Qiu, Zhi-Dong; Shi, Xiao-Jian; Zhang, Jing-Xian; Hou, Jin-Jun; Wang, Qiu-Rong; Wu, Wan-Ying; Guo, De-An

    2016-07-01

    A key segment in authentication of herbal medicines is the establishment of robust biomarkers that embody the intrinsic metabolites difference independent of the growing environment or processing technics. We present a strategy by nontargeted metabolomics and "Commercial-homophyletic" comparison-induced biomarkers verification with new bioinformatic vehicles, to improve the efficiency and reliability in authentication of herbal medicines. The chemical differentiation of five different parts (root, leaf, flower bud, berry, and seed) of Panax ginseng was illustrated as a case study. First, an optimized ultra-performance liquid chromatography/quadrupole time-of-flight-MS(E) (UPLC/QTOF-MS(E)) approach was established for global metabolites profiling. Second, UNIFI™ combined with search of an in-house library was employed to automatically characterize the metabolites. Third, pattern recognition multivariate statistical analysis of the MS(E) data of different parts of commercial and homophyletic samples were separately performed to explore potential biomarkers. Fourth, potential biomarkers deduced from commercial and homophyletic root and leaf samples were cross-compared to infer robust biomarkers. Fifth, discriminating models by artificial neutral network (ANN) were established to identify different parts of P. ginseng. Consequently, 164 compounds were characterized, and 11 robust biomarkers enabling the differentiation among root, leaf, flower bud, and berry, were discovered by removing those structurally unstable and possibly processing-related ones. The ANN models using the robust biomarkers managed to exactly discriminate four different parts and root adulterant with leaf as well. Conclusively, biomarkers verification using homophyletic samples conduces to the discovery of robust biomarkers. The integrated strategy facilitates authentication of herbal medicines in a more efficient and more intelligent manner.

  14. The application of skin metabolomics in the context of transdermal drug delivery.

    PubMed

    Li, Jinling; Xu, Weitong; Liang, Yibiao; Wang, Hui

    2017-04-01

    Metabolomics is a powerful emerging tool for the identification of biomarkers and the exploration of metabolic pathways in a high-throughput manner. As an administration site for percutaneous absorption, the skin has a variety of metabolic enzymes, except other than hepar. However, technologies to fully detect dermal metabolites remain lacking. Skin metabolomics studies have mainly focused on the regulation of dermal metabolites by drugs or on the metabolism of drugs themselves. Skin metabolomics techniques include collection and preparation of skin samples, data collection, data processing and analysis. Furthermore, studying dermal metabolic effects via metabolomics can provide novel explanations for the pathogenesis of some dermatoses and unique insights for designing targeted prodrugs, promoting drug absorption and controlling drug concentration. This paper reviews current progress in the field of skin metabolomics, with a specific focus on dermal drug delivery systems and dermatosis.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2016-06-01

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

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

    PubMed

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

    2012-10-01

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

  18. Can NMR solve some significant challenges in metabolomics?

    NASA Astrophysics Data System (ADS)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

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

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

    PubMed

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

    2015-01-01

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

  20. Can NMR solve some significant challenges in metabolomics?

    PubMed Central

    Gowda, G.A. Nagana; Raftery, Daniel

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  2. Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    Rischer, Heiko; Oksman-Caldentey, Kirsi-Marja

    2006-03-01

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

  4. An emerging role for metabolomics in nutrition science.

    PubMed

    Astarita, Giuseppe; Langridge, James

    2013-01-01

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

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

    PubMed

    Martien, Julia I; Amador-Noguez, Daniel

    2017-02-01

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

  6. An in-source multiple collision-neutral loss filtering based nontargeted metabolomics approach for the comprehensive analysis of malonyl-ginsenosides from Panax ginseng, P. quinquefolius, and P. notoginseng.

    PubMed

    Shi, Xiao-Jian; Yang, Wen-Zhi; Qiu, Shi; Yao, Chang-Liang; Shen, Yao; Pan, Hui-Qin; Bi, Qi-Rui; Yang, Min; Wu, Wan-Ying; Guo, De-An

    2017-02-01

    The simultaneous identification and quantification of target metabolites from herbal medicines are difficult to implement by the full-scan MS based nontargeted metabolomics approaches. Here an in-source multiple collision-neutral loss filtering (IMC-NLF) based nontargeted metabolomics approach is developed and applied to identify and quantify the variations of malonyl-ginsenosides, a common group of acyl saponins with potential anti-diabetic activity, among Panax ginseng, P. quinquefolius, and P. notoginseng. The key steps of the IMC-NLF strategy are the acquisition of specific high-resolution neutral loss data and the efficient filtering of target precursor ions from the full-scan spectra. Using a hybrid LTQ-Orbitrap mass spectrometer after UHPLC separation, abundant in-source product ions, [M-H-CO2](-) (due to the vulnerability of the carboxyl group) and [M-H-Mal.](-), were generated at the energies of 70 V and 90 V, respectively. After spectral deconvolution, the generated peak list was screened by dual NLF using a Neutral Loss MS Finder software (NL of 43.9898 Da for CO2 and 86.0004 Da for the malonyl substituent). By combining the precursor ions list-triggered HCD-MS/MS and basic hydrolysis, a total of 101 malonyl-ginsenosides (including 69 from P. ginseng, 52 from P. quinquefolius, and 44 from P. notoginseng) were identified or tentatively characterized. The variations of 81 characterized malonyl-ginsenosides among 45 batches of Ginseng samples were statistically analyzed disclosing ten potential markers. It is the first systematic analysis of malonyl-ginsenosides. The IMC-NLF approach by a single analytical platform is promising in targeted analyses of modification-specific metabolites in metabolomics and drug metabolism.

  7. Metabolomic profiling of plant tissues.

    PubMed

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

    2015-01-01

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

  8. Eating at the table of another: metabolomics of host-parasite interactions.

    PubMed

    Kafsack, Björn F C; Llinás, Manuel

    2010-02-18

    The application of metabolomics, the global analysis of metabolite levels, to the study of protozoan parasites has become an important tool for understanding the host-parasite relationship and holds promise for the development of direly needed therapeutics and improved diagnostics. Research advances over the past decade have opened the door for a systems biology approach to protozoan parasites with metabolomics, providing a crucial readout of metabolic activity. In this review, we highlight recent metabolomic approaches to protozoan parasites, including metabolite profiling, integration with genomics, transcription, and proteomic analysis, and the use of metabolic fingerprints for the diagnosis of parasitic infections.

  9. Eating at the Table of Another: Metabolomics of Host/Parasite Interactions

    PubMed Central

    Kafsack, Björn F.C.; Llinás, Manuel

    2010-01-01

    The application of metabolomics, the global analysis of metabolite levels, to the study of protozoan parasites has become an important tool for understanding the host/parasite relationship and holds promise for the development of direly needed therapeutics and improved diagnostics. Research advances over the past decade have opened the door for a systems biology approach to protozoan parasites with metabolomics providing a crucial readout of metabolic activity. In this review we highlight recent metabolomic approaches to protozoan parasites, including metabolite profiling, integration with genomics, transcription, and proteomic analysis, as well as the use of metabolic fingerprints for the diagnosis of parasitic infections. PMID:20159614

  10. Positional Enrichment by Proton Analysis (PEPA): A One-Dimensional (1) H-NMR Approach for (13) C Stable Isotope Tracer Studies in Metabolomics.

    PubMed

    Vinaixa, Maria; Rodríguez, Miguel A; Aivio, Suvi; Capellades, Jordi; Gómez, Josep; Canyellas, Nicolau; Stracker, Travis H; Yanes, Oscar

    2017-03-20

    A novel metabolomics approach for NMR-based stable isotope tracer studies called PEPA is presented, and its performance validated using human cancer cells. PEPA detects the position of carbon label in isotopically enriched metabolites and quantifies fractional enrichment by indirect determination of (13) C-satellite peaks using 1D-(1) H-NMR spectra. In comparison with (13) C-NMR, TOCSY and HSQC, PEPA improves sensitivity, accelerates the elucidation of (13) C positions in labeled metabolites and the quantification of the percentage of stable isotope enrichment. Altogether, PEPA provides a novel framework for extending the high-throughput of (1) H-NMR metabolic profiling to stable isotope tracing in metabolomics, facilitating and complementing the information derived from 2D-NMR experiments and expanding the range of isotopically enriched metabolites detected in cellular extracts.

  11. Positional Enrichment by Proton Analysis (PEPA): A One‐Dimensional 1H‐NMR Approach for 13C Stable Isotope Tracer Studies in Metabolomics

    PubMed Central

    Rodríguez, Miguel A.; Aivio, Suvi; Capellades, Jordi; Gómez, Josep; Canyellas, Nicolau; Stracker, Travis H.

    2017-01-01

    Abstract A novel metabolomics approach for NMR‐based stable isotope tracer studies called PEPA is presented, and its performance validated using human cancer cells. PEPA detects the position of carbon label in isotopically enriched metabolites and quantifies fractional enrichment by indirect determination of 13C‐satellite peaks using 1D‐1H‐NMR spectra. In comparison with 13C‐NMR, TOCSY and HSQC, PEPA improves sensitivity, accelerates the elucidation of 13C positions in labeled metabolites and the quantification of the percentage of stable isotope enrichment. Altogether, PEPA provides a novel framework for extending the high‐throughput of 1H‐NMR metabolic profiling to stable isotope tracing in metabolomics, facilitating and complementing the information derived from 2D‐NMR experiments and expanding the range of isotopically enriched metabolites detected in cellular extracts. PMID:28220994

  12. Application of metabolomics based on direct mass spectrometry analysis for the elucidation of altered metabolic pathways in serum from the APP/PS1 transgenic model of Alzheimer's disease.

    PubMed

    González-Domínguez, Raúl; García-Barrera, Tamara; Vitorica, Javier; Gómez-Ariza, José Luis

    2015-03-25

    Metabolomic analysis of brain tissue from transgenic mouse models of Alzheimer's disease has demonstrated a great potential for the study of pathological mechanisms and the development of new therapies and biomarkers for diagnosis. However, in order to translate these investigations to the clinical practice it is necessary to corroborate these findings in peripheral samples. To this end, this work considers the application of a novel metabolomic platform based on the combination of a two-steps extraction procedure with complementary analysis by direct infusion electrospray mass spectrometry and flow infusion atmospheric pressure photoionization mass spectrometry for a holistic investigation of metabolic abnormalities in serum samples from APP/PS1 mice. A number of metabolites were found to be perturbed in this mouse model, including increased levels of di- and tri-acylglycerols, eicosanoids, inosine, choline and glycerophosphoethanolamine; reduced content of cholesteryl esters, free fatty acids, lysophosphocholines, amino acids, energy-related metabolites, phosphoethanolamine and urea, as well as abnormal distribution of phosphocholines depending on the fatty acid linked to the molecular moiety. This allowed the elucidation of possible pathways disturbed underlying to disease (abnormal homeostasis of phospholipids leading to membrane breakdown, energy-related failures, hyperammonemia and hyperlipidemia, among others), thus demonstrating the utility of peripheral samples to investigate pathology in the APP/PS1 model.

  13. Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography-mass spectrometry.

    PubMed

    Smart, Kathleen F; Aggio, Raphael B M; Van Houtte, Jeremy R; Villas-Bôas, Silas G

    2010-09-01

    This protocol describes an analytical platform for the analysis of intra- and extracellular metabolites of microbial cells (yeast, filamentous fungi and bacteria) using gas chromatography-mass spectrometry (GC-MS). The protocol is subdivided into sampling, sample preparation, chemical derivatization of metabolites, GC-MS analysis and data processing and analysis. This protocol uses two robust quenching methods for microbial cultures, the first of which, cold glycerol-saline quenching, causes reduced leakage of intracellular metabolites, thus allowing a more reliable separation of intra- and extracellular metabolites with simultaneous stopping of cell metabolism. The second, fast filtration, is specifically designed for quenching filamentous micro-organisms. These sampling techniques are combined with an easy sample-preparation procedure and a fast chemical derivatization reaction using methyl chloroformate. This reaction takes place at room temperature, in aqueous medium, and is less prone to matrix effect compared with other derivatizations. This protocol takes an average of 10 d to complete and enables the simultaneous analysis of hundreds of metabolites from the central carbon metabolism (amino and nonamino organic acids, phosphorylated organic acids and fatty acid intermediates) using an in-house MS library and a data analysis pipeline consisting of two free software programs (Automated Mass Deconvolution and Identification System (AMDIS) and R).

  14. Metabolomic signatures associated with disease severity in multiple sclerosis

    PubMed Central

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

    2017-01-01

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

  15. Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

    NASA Astrophysics Data System (ADS)

    Malmendal, Anders; Sørensen, Jesper Givskov; Overgaard, Johannes; Holmstrup, Martin; Nielsen, Niels Chr.; Loeschcke, Volker

    2013-05-01

    We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic 1H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.

  16. Combined Metabolomics and Proteomics Analysis of Major Depression in an Animal Model: Perturbed Energy Metabolism in the Chronic Mild Stressed Rat Cerebellum

    PubMed Central

    Shao, Wei-hua; Chen, Jian-jun; Fan, Song-hua; Lei, Yang; Xu, Hong-bo; Zhou, Jian; Cheng, Peng-fei; Yang, Yong-tao; Rao, Cheng-long; Wu, Bo; Liu, Hai-peng

    2015-01-01

    Abstract Major depressive disorder (MDD) is a highly prevalent, debilitating mental illness of importance for global health. However, its molecular pathophysiology remains poorly understood. Combined proteomics and metabolomics approaches should provide a comprehensive understanding of MDD's etiology. The present study reports novel “-omics” insights from a rodent model of MDD. Cerebellar samples from chronic mild stressed (CMS)-treated depressed rats and controls were compared with a focus on the differentially expressed proteins and metabolites using isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics and gas chromotography/mass spectrometry (GC-MS) metabolomics techniques, respectively. The combined analyses found significant alterations associated with cerebellar energy metabolism, as indicated by (1) abnormal amino acid metabolism accompanied by corresponding metabolic enzymatic alterations and disturbed protein turnover, (2) increased glycolytic and tricarboxylic acid (TCA) cycle enzyme levels paralleled by changes in the concentrations of associated metabolites, and (3) perturbation of ATP biosynthesis through adenosine accompanied by perturbation of the mitochondrial respiratory chain. To the best of our knowledge, this study is the first to integrate proteomics and metabolomics analyses to examine the pathophysiological mechanism(s) underlying MDD in a CMS rodent model of depression. These results can offer important insights into the pathogenesis of MDD. PMID:26134254

  17. Combined Metabolomics and Proteomics Analysis of Major Depression in an Animal Model: Perturbed Energy Metabolism in the Chronic Mild Stressed Rat Cerebellum.

    PubMed

    Shao, Wei-hua; Chen, Jian-jun; Fan, Song-hua; Lei, Yang; Xu, Hong-bo; Zhou, Jian; Cheng, Peng-fei; Yang, Yong-tao; Rao, Cheng-long; Wu, Bo; Liu, Hai-peng; Xie, Peng

    2015-07-01

    Major depressive disorder (MDD) is a highly prevalent, debilitating mental illness of importance for global health. However, its molecular pathophysiology remains poorly understood. Combined proteomics and metabolomics approaches should provide a comprehensive understanding of MDD's etiology. The present study reports novel "-omics" insights from a rodent model of MDD. Cerebellar samples from chronic mild stressed (CMS)-treated depressed rats and controls were compared with a focus on the differentially expressed proteins and metabolites using isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics and gas chromotography/mass spectrometry (GC-MS) metabolomics techniques, respectively. The combined analyses found significant alterations associated with cerebellar energy metabolism, as indicated by (1) abnormal amino acid metabolism accompanied by corresponding metabolic enzymatic alterations and disturbed protein turnover, (2) increased glycolytic and tricarboxylic acid (TCA) cycle enzyme levels paralleled by changes in the concentrations of associated metabolites, and (3) perturbation of ATP biosynthesis through adenosine accompanied by perturbation of the mitochondrial respiratory chain. To the best of our knowledge, this study is the first to integrate proteomics and metabolomics analyses to examine the pathophysiological mechanism(s) underlying MDD in a CMS rodent model of depression. These results can offer important insights into the pathogenesis of MDD.

  18. Food metabolomics: from farm to human.

    PubMed

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

    2016-02-01

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

  19. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action

    PubMed Central

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

    2016-01-01

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

  20. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action.

    PubMed

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

    2016-04-01

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

  1. Integrated metabolomic analysis of the nano-sized copper particle-induced hepatotoxicity and nephrotoxicity in rats: A rapid invivo screening method for nanotoxicity

    SciTech Connect

    Lei Ronghui; Wu Chunqi; Yang Baohua; Ma Huazhai; Shi Chang; Wang Quanjun; Wang Qingxiu; Yuan Ye; Liao Mingyang

    2008-10-15

    Despite an increasing application of copper nanoparticles, there is a serious lack of information concerning their impact on human health and the environment. In this study, the biochemical compositions of urine, serum, and extracts of liver and kidney tissues of rats treated with nano-copper at the different doses (50, 100, and 200 mg/kg/d for 5 d) were investigated using {sup 1}H NMR techniques with the pattern recognition methods. Serum biochemical analysis and histopathological examinations of the liver and kidney of all the rats were simultaneously performed. All the results indicated that the effects produced by nano-copper at a dose of 100 or 50 mg/kg/d were less than those induced at a higher dose of 200 mg/kg/d. Nano-copper induced overt hepatotoxicity and nephrotoxicity at 200 mg/kg/d for 5 d, which mainly involved scattered dot hepatocytic necrosis and widespread renal proximal tubule necrosis. Increased citrate, succinate, trimethylamine-N-oxide, glucose, and amino acids, accompanied by decreased creatinine levels were observed in the urine; furthermore, elevated levels of lactate, 3-hydroxybutyrate, acetate, creatine, triglycerides, and phosphatide and reduced glucose levels were observed in the serum. The predominant changes identified in the liver tissue aqueous extracts included increased lactate and creatine levels together with reduced glutamine and taurine levels, and the metabolic profile of the kidney tissue aqueous extracts showed an increase in lactate and a drop in glucose. In the chloroform/methanol extracts of the liver and kidney tissues, elevated triglyceride species were identified. These changes suggested that mitochondrial failure, enhanced ketogenesis, fatty acid {beta}-oxidation, and glycolysis contributed to the hepatotoxicity and nephrotoxicity induced by nano-copper at 200 mg/kg/d for 5 d. An increase in triglycerides in the serum, liver and kidney tissues could serve as a potential sensitive biomarker reflecting the lipidosis

  2. Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.

    PubMed

    Lee, Sang-Hyun; Kim, Sooah; Kwon, Min-A; Jung, Young Hoon; Shin, Yong-An; Kim, Kyoung Heon

    2014-12-01

    Well-established metabolome sample preparation is a prerequisite for reliable metabolomic data. For metabolome sampling of a Gram-positive strict anaerobe, Clostridium acetobutylicum, fast filtration and metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v) at -20°C under anaerobic conditions has been commonly used. This anaerobic metabolite processing method is laborious and time-consuming since it is conducted in an anaerobic chamber. Also, there have not been any systematic method evaluation and development of metabolome sample preparation for strict anaerobes and Gram-positive bacteria. In this study, metabolome sampling and extraction methods were rigorously evaluated and optimized for C. acetobutylicum by using gas chromatography/time-of-flight mass spectrometry-based metabolomics, in which a total of 116 metabolites were identified. When comparing the atmospheric (i.e., in air) and anaerobic (i.e., in an anaerobic chamber) processing of metabolome sample preparation, there was no significant difference in the quality and quantity of the metabolomic data. For metabolite extraction, pure methanol at -20°C was a better solvent than acetonitrile/methanol/water (2:2:1, v/v/v) at -20°C that is frequently used for C. acetobutylicum, and metabolite profiles were significantly different depending on extraction solvents. This is the first evaluation of metabolite sample preparation under aerobic processing conditions for an anaerobe. This method could be applied conveniently, efficiently, and reliably to metabolome analysis for strict anaerobes in air.

  3. Metabolomics driven analysis of artichoke leaf and its commercial products via UHPLC-q-TOF-MS and chemometrics.

    PubMed

    Farag, Mohamed A; El-Ahmady, Sherweit H; Elian, Fatma S; Wessjohann, Ludger A

    2013-11-01

    The demand to develop efficient and reliable analytical methods for the quality control of herbal medicines and nutraceuticals is on the rise, together with an increase in the legal requirements for safe and consistent levels of active principles. Here, we describe an ultra-high performance liquid chromatography method (UHPLC) coupled with quadrupole high resolution time of flight mass spectrometry (qTOF-MS) analysis for the comprehensive measurement of metabolites from three Cynara scolymus (artichoke) cultivars: American Green Globe, French Hyrious, and Egyptian Baladi. Under optimized conditions, 50 metabolites were simultaneously quantified and identified including: eight caffeic acid derivatives, six saponins, 12 flavonoids and 10 fatty acids. Principal component analysis (PCA) was used to define both similarities and differences among the three artichoke leaf cultivars. In addition, batches from seven commercially available artichoke market products were analysed and showed variable quality, particularly in caffeic acid derivatives, flavonoid and fatty acid contents. PCA analysis was able to discriminate between various preparations, including differentiation between various batches from the same supplier. To the best of our knowledge, this study provides the first approach utilizing UHPLC-MS based metabolite fingerprinting to reveal secondary metabolite compositional differences in artichoke leaf extracts.

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

    PubMed

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

    2016-04-01

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

  5. Early Effect of Amyloid β-Peptide on Hippocampal and Serum Metabolism in Rats Studied by an Integrated Method of NMR-Based Metabolomics and ANOVA-Simultaneous Component Analysis.

    PubMed

    Du, Yao; Zheng, Hong; Xia, Huanhuan; Zhao, Liangcai; Hu, Wenyi; Bai, Guanghui; Yan, Zhihan; Gao, Hongchang

    2017-01-01

    Amyloid β (Aβ) deposition has been implicated in the pathogenesis of Alzheimer's disease. However, the early effect of Aβ deposition on metabolism remains unclear. In the present study, thus, we explored the metabolic changes in the hippocampus and serum during first 2 weeks of Aβ25-35 injection in rats by using an integrated method of NMR-based metabolomics and ANOVA-simultaneous component analysis (ASCA). Our results show that Aβ25-35 injection, time, and their interaction had statistically significant effects on the hippocampus and serum metabolome. Furthermore, we identified key metabolites that mainly contributed to these effects. After Aβ25-35 injection from 1 to 2 weeks, the levels of lactate, N-acetylaspartate, creatine, and taurine were decreased in rat hippocampus, while an increase in lactate and decreases in LDL/VLDL and glucose were observed in rat serum. Therefore, we suggest that the reduction in energy and lipid metabolism as well as an increase in anaerobic glycolysis may occur at the early stage of Aβ25-35 deposition.

  6. Early Effect of Amyloid β-Peptide on Hippocampal and Serum Metabolism in Rats Studied by an Integrated Method of NMR-Based Metabolomics and ANOVA-Simultaneous Component Analysis

    PubMed Central

    Du, Yao; Xia, Huanhuan; Zhao, Liangcai; Hu, Wenyi; Bai, Guanghui

    2017-01-01

    Amyloid β (Aβ) deposition has been implicated in the pathogenesis of Alzheimer's disease. However, the early effect of Aβ deposition on metabolism remains unclear. In the present study, thus, we explored the metabolic changes in the hippocampus and serum during first 2 weeks of Aβ25–35 injection in rats by using an integrated method of NMR-based metabolomics and ANOVA-simultaneous component analysis (ASCA). Our results show that Aβ25–35 injection, time, and their interaction had statistically significant effects on the hippocampus and serum metabolome. Furthermore, we identified key metabolites that mainly contributed to these effects. After Aβ25–35 injection from 1 to 2 weeks, the levels of lactate, N-acetylaspartate, creatine, and taurine were decreased in rat hippocampus, while an increase in lactate and decreases in LDL/VLDL and glucose were observed in rat serum. Therefore, we suggest that the reduction in energy and lipid metabolism as well as an increase in anaerobic glycolysis may occur at the early stage of Aβ25–35 deposition. PMID:28243597

  7. Comprehensive Metabolomic Analysis in Blood, Urine, Fat, and Muscle in Men with Metabolic Syndrome: A Randomized, Placebo-Controlled Clinical Trial on the Effects of Resveratrol after Four Months’ Treatment

    PubMed Central

    Korsholm, Anne Sofie; Kjær, Thomas Nordstrøm; Ornstrup, Marie Juul; Pedersen, Steen Bønløkke

    2017-01-01

    Resveratrol possesses several beneficial metabolic effects in rodents, while the effects of resveratrol in humans remain unclear. Therefore, we performed a non-targeted comprehensive metabolomic analysis on blood, urine, adipose tissue, and skeletal muscle tissue in middle-aged men with metabolic syndrome randomized to either resveratrol or placebo treatment for four months. Changes in steroid hormones across all four matrices were the most pronounced changes observed. Resveratrol treatment reduced sulfated androgen precursors in blood, adipose tissue, and muscle tissue, and increased these metabolites in urine. Furthermore, markers of muscle turnover were increased and lipid metabolism was affected, with increased intracellular glycerol and accumulation of long-chain saturated, monounsaturated, and polyunsaturated (n3 and n6) free fatty acids in resveratrol-treated men. Finally, urinary derivatives of aromatic amino acids, which mainly reflect the composition of the gut microbiota, were altered upon resveratrol treatment. In conclusion, the non-targeted metabolomics approach applied to four different matrices provided evidence of subtle but robust effects on several metabolic pathways following resveratrol treatment for four months in men with metabolic syndrome—effects that, for the most part, would not have been detected by routine analyses. The affected pathways should be the focus of future clinical trials on resveratrol’s effects, and perhaps particularly the areas of steroid metabolism and the gut microbiome. PMID:28273841

  8. Development of quantitative metabolomics for Pichia pastoris.

    PubMed

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

    2012-04-01

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

  9. Analysis of liposoluble carboxylic acids metabolome in human serum by stable isotope labeling coupled with liquid chromatography-mass spectrometry.

    PubMed

    Zhu, Quan-Fei; Zhang, Zheng; Liu, Ping; Zheng, Shu-Jian; Peng, Ke; Deng, Qian-Yun; Zheng, Fang; Yuan, Bi-Feng; Feng, Yu-Qi

    2016-08-19

    Fatty acids (FAs) are groups of liposoluble carboxylic acids (LCAs) and play important roles in various physiological processes. Abnormal contents or changes of FAs are associated with a series of diseases. Here we developed a strategy with stable isotope labeling combined with liquid chromatography-tandem mass spectrometry (IL-LC-MS) analysis for comprehensive profiling and relative quantitation of LCAs in human serum. In this strategy, a pair of isotope labeling reagents (2-dimethylaminoethylamine (DMED)) and d4-2-dimethylaminoethylamine (d4-DMED) were employed to selectively label carboxyl groups of LCAs. The DMED and d4-DMED labeled products can lose four characteristic neutral fragments of 45 and 49Da or 63 and 67Da in collision-induced dissociation. Therefore, quadruple neutral loss scan (QNLS) mode was established and used for non-targeted profiling of LCAs. The peak pairs of DMED and d4-DMED labeling with the same retention time, intensity and characteristic mass differences were extracted from the two NLS spectra respectively, and assigned as potential LCA candidates. Using this strategy, 241 LCA candidates were discovered in the human serum; 156 carboxylic acid compounds could be determined by searching HMDB and METLIN databases (FAs are over 90%) and 21 of these LCAs were successfully identified by standards. Subsequently, a modified pseudo-targeted method with multiple reaction monitoring (MRM) detection mode was developed and used for relative quantification of LCAs in human serum from type 2 diabetes mellitus (T2DM) patients and healthy controls. As a result, 81 LCAs were found to have significant difference between T2DM patients and healthy controls. Taken together, the isotope labeling combined with tandem mass spectrometry analysis demonstrated to be a powerful strategy for identification and quantification of LCA compounds in serum samples.

  10. Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

    PubMed Central

    Welzenbach, Julia; Neuhoff, Christiane; Heidt, Hanna; Cinar, Mehmet Ulas; Looft, Christian; Schellander, Karl; Tholen, Ernst; Große-Brinkhaus, Christine

    2016-01-01

    The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein “phosphoglycerate mutase 2” and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes. PMID:27589727

  11. Metabolomic and (13)C-metabolic flux analysis of a xylose-consuming Saccharomyces cerevisiae strain expressing xylose isomerase.

    PubMed

    Wasylenko, Thomas M; Stephanopoulos, Gregory

    2015-03-01

    Over the past two decades, significant progress has been made in the engineering of xylose-consuming Saccharomyces cerevisiae strains for production of lignocellulosic biofuels. However, the ethanol productivities achieved on xylose are still significantly lower than those observed on glucose for reasons that are not well understood. We have undertaken an analysis of central carbon metabolite pool sizes and metabolic fluxes on glucose and on xylose under aerobic and anaerobic conditions in a strain capable of rapid xylose assimilation via xylose isomerase in order to investigate factors that may limit the rate of xylose fermentation. We find that during xylose utilization the flux through the non-oxidative Pentose Phosphate Pathway (PPP) is high but the flux through the oxidative PPP is low, highlighting an advantage of the strain employed in this study. Furthermore, xylose fails to elicit the full carbon catabolite repression response that is characteristic of glucose fermentation in S. cerevisiae. We present indirect evidence that the incomplete activation of the fermentation program on xylose results in a bottleneck in lower glycolysis, leading to inefficient re-oxidation of NADH produced in glycolysis.

  12. Shooting control by brassinosteroids: metabolomic analysis and effect of brassinazole on Malus prunifolia, the Marubakaido apple rootstock.

    PubMed

    Pereira-Netto, Adaucto B; Roessner, Ute; Fujioka, Shozo; Bacic, Antony; Asami, Tadao; Yoshida, Shigeo; Clouse, Steven D

    2009-04-01

    To help unravel the role of brassinosteroids (BRs) in the control of shooting, we treated the shoots of Marubakaido apple rootstock (Malus prunifolia (Willd.) Borkh cv. Marubakaido) with brassinolide and Brz 220, an inhibitor of BR biosynthesis. Brassinolide differentially affected elongation and formation of main and primary lateral shoots, which resulted in reduced apical dominance. Treatment of shoots with increasing doses of Brz 220 led to a progressive inhibition of main shoot elongation. Eight different BRs were also identified in the shoots of M. prunifolia. Progressive decline in 6-deoxocathasterone, 6-deoxotyphasterol and castasterone was related to increased doses of Brz 220. Analysis of the metabolic profiles between a fluoro-containing derivative of 28-homocastasterone (5F-HCS) using treated and untreated shoots demonstrated that no 5F-HCS-specific metabolite was identified. However, 4 weeks after the treatment, fructose, glucose and the putatively identified gulonic acid were higher in 5F-HCS-treated shoots, compared to untreated shoots. These results indicate that the previously reported 5F-HCS-induced stimulation of shoot elongation and formation of new shoots in the Marubakaido shoots is under the control of changes in the endogenous BR pool. In addition, the results presented in this report also indicate that the 5F-HCS-induced shooting likely involves a variety of different mechanisms and consequently does not result from changes in the endogenous levels of any single metabolite.

  13. Pharma-metabolomics in neonatology: is it a dream or a fact?

    PubMed

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

    2012-01-01

    The 'omics' technologies represent analytical approaches that have a holistic view on molecules such as genes, transcripts, proteins and metabolites constituting a cell, tissue or organism. The profiling of genes, transcripts and proteins has been referred to as genomics, transcriptomics and proteomics. Finally, there is the youngest and most rapidly increasing of the "omics" disciplines: metabolomics. Metabolomics appears to be a new, very useful tool in neonatology, especially in the fields of pharma-metabolomics and nutri- metabolomics. Since it appears to be predictive and preventive, it can be considered the 'new clinical chemistry' for personalized neonatal medicine. At present, the use of metabolomics in neonatology is still in the pioneering phase. In clinical practice, only a limited number of metabolites are routinely measured in the biofluids of newborns by conventional analytical methods to study the metabolic status of the organism. However, the management of sick or preterm newborns might be improved if more information on perinatal/ neonatal maturational processes and their metabolic background were available. The aim of this review, after a general introduction on pharma-metabolomics, is to present the potential of NMR-based metabolomic analysis of newbom urine in neonatology in the field of pharmacology.

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

    PubMed

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

    2016-05-25

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2014-08-01

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

  17. K-targeted metabolomic analysis extends chemical subtraction to DESIGNER extracts: selective depletion of extracts of hops (Humulus lupulus).

    PubMed

    Ramos Alvarenga, René F; Friesen, J Brent; Nikolić, Dejan; Simmler, Charlotte; Napolitano, José G; van Breemen, Richard; Lankin, David C; McAlpine, James B; Pauli, Guido F; Chen, Shao-Nong

    2014-12-26

    This study introduces a flexible and compound targeted approach to Deplete and Enrich Select Ingredients to Generate Normalized Extract Resources, generating DESIGNER extracts, by means of chemical subtraction or augmentation of metabolites. Targeting metabolites based on their liquid-liquid partition coefficients (K values), K targeting uses countercurrent separation methodology to remove single or multiple compounds from a chemically complex mixture, according to the following equation: DESIGNER extract = total extract ± target compound(s). Expanding the scope of the recently reported depletion of extracts by immunoaffinity or solid phase liquid chromatography, the present approach allows a more flexible, single- or multi-targeted removal of constituents from complex extracts such as botanicals. Chemical subtraction enables both chemical and biological characterization, including detection of synergism/antagonism by both the subtracted targets and the remaining metabolite mixture, as well as definition of the residual complexity of all fractions. The feasibility of the DESIGNER concept is shown by K-targeted subtraction of four bioactive prenylated phenols, isoxanthohumol (1), 8-prenylnaringenin (2), 6-prenylnaringenin (3), and xanthohumol (4), from a standardized hops (Humulus lupulus L.) extract using specific solvent systems. Conversely, adding K-targeted isolates allows enrichment of the original extract and hence provides an augmented DESIGNER material. Multiple countercurrent separation steps were used to purify each of the four compounds, and four DESIGNER extracts with varying depletions were prepared. The DESIGNER approach innovates the characterization of chemically complex extracts through integration of enabling technologies such as countercurrent separation, K-by-bioactivity, the residual complexity concepts, as well as quantitative analysis by (1)H NMR, LC-MS, and HiFSA-based NMR fingerprinting.

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

    PubMed

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

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

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

    PubMed Central

    2014-01-01

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

  20. YMDB: the Yeast Metabolome Database

    PubMed Central

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

    2012-01-01

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

  1. Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing.

    PubMed

    Ernst, Madeleine; Silva, Denise Brentan; Silva, Ricardo Roberto; Vêncio, Ricardo Z N; Lopes, Norberto Peporine

    2014-06-01

    Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

  2. Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of “Unknown Function”

    PubMed Central

    Quanbeck, Stephanie M.; Brachova, Libuse; Campbell, Alexis A.; Guan, Xin; Perera, Ann; He, Kun; Rhee, Seung Y.; Bais, Preeti; Dickerson, Julie A.; Dixon, Philip; Wohlgemuth, Gert; Fiehn, Oliver; Barkan, Lenore; Lange, Iris; Lange, B. Markus; Lee, Insuk; Cortes, Diego; Salazar, Carolina; Shuman, Joel; Shulaev, Vladimir; Huhman, David V.; Sumner, Lloyd W.; Roth, Mary R.; Welti, Ruth; Ilarslan, Hilal; Wurtele, Eve S.; Nikolau, Basil J.

    2012-01-01

    Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs. PMID:22645570

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

    PubMed

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

    2014-10-01

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

  4. Serum Metabolomics of Burkitt Lymphoma Mouse Models

    PubMed Central

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

    2017-01-01

    Burkitt lymphoma (BL) is a rare and highly aggressive type of non-Hodgkin lymphoma. The mortality rate of BL patients is very high due to the rapid growth rate and frequent systemic spread of the disease. A better understanding of the pathogenesis, more sensitive diagnostic tools and effective treatment methods for BL are essential. Metabolomics, an important aspect of systems biology, allows the comprehensive analysis of global, dynamic and endogenous biological metabolites based on their nuclear magnetic resonance (NMR) and mass spectrometry (MS). It has already been used to investigate the pathogenesis and discover new biomarkers for disease diagnosis and prognosis. In this study, we analyzed differences of serum metabolites in BL mice and normal mice by NMR-based metabolomics. We found that metabolites associated with energy metabolism, amino acid metabolism, fatty acid metabolism and choline phospholipid metabolism were altered in BL mice. The diagnostic potential of the metabolite differences was investigated in this study. Glutamate, glycerol and choline had a high diagnostic accuracy; in contrast, isoleucine, leucine, pyruvate, lysine, α-ketoglutarate, betaine, glycine, creatine, serine, lactate, tyrosine, phenylalanine, histidine and formate enabled the accurate differentiation of BL mice from normal mice. The discovery of abnormal metabolism and relevant differential metabolites may provide useful clues for developing novel, noninvasive approaches for the diagnosis and prognosis of BL based on these potential biomarkers. PMID:28129369

  5. Monolithic columns in plant proteomics and metabolomics.

    PubMed

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

    2013-03-01

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

  6. Metabolomic analyses for atherosclerosis, diabetes, and obesity

    PubMed Central

    2013-01-01

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

  7. Radiation Metabolomics: Current Status and Future Directions

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2014-07-01

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

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

    PubMed

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

    2016-04-01

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

  10. Serum metabolomics analysis of patients with chikungunya and dengue mono/co-infections reveals distinct metabolite signatures in the three disease conditions

    PubMed Central

    Shrinet, Jatin; Shastri, Jayanthi S.; Gaind, Rajni; Bhavesh, Neel Sarovar; Sunil, Sujatha

    2016-01-01

    Chikungunya and dengue are arboviral infections with overlapping clinical symptoms. A subset of chikungunya infection occurs also as co-infections with dengue, resulting in complications during diagnosis and patient management. The present study was undertaken to identify the global metabolome of patient sera infected with chikungunya as mono infections and with dengue as co-infections. Using nuclear magnetic resonance (NMR) spectroscopy, the metabolome of sera of three disease conditions, namely, chikungunya and dengue as mono-infections and when co-infected were ascertained and compared with healthy individuals. Further, the cohorts were analyzed on the basis of age, onset of fever and joint involvement. Here we show that many metabolites in the serum are significantly differentially regulated during chikungunya mono-infection as well as during chikungunya co-infection with dengue. We observed that glycine, serine, threonine, galactose and pyrimidine metabolisms are the most perturbed pathways in both mono and co-infection conditions. The affected pathways in our study correlate well with the clinical manifestation like fever, inflammation, energy deprivation and joint pain during the infections. These results may serve as a starting point for validations and identification of distinct biomolecules that could be exploited as biomarker candidates thereby helping in better patient management. PMID:27845374

  11. Serum metabolomics analysis of patients with chikungunya and dengue mono/co-infections reveals distinct metabolite signatures in the three disease conditions

    NASA Astrophysics Data System (ADS)

    Shrinet, Jatin; Shastri, Jayanthi S.; Gaind, Rajni; Bhavesh, Neel Sarovar; Sunil, Sujatha

    2016-11-01

    Chikungunya and dengue are arboviral infections with overlapping clinical symptoms. A subset of chikungunya infection occurs also as co-infections with dengue, resulting in complications during diagnosis and patient management. The present study was undertaken to identify the global metabolome of patient sera infected with chikungunya as mono infections and with dengue as co-infections. Using nuclear magnetic resonance (NMR) spectroscopy, the metabolome of sera of three disease conditions, namely, chikungunya and dengue as mono-infections and when co-infected were ascertained and compared with healthy individuals. Further, the cohorts were analyzed on the basis of age, onset of fever and joint involvement. Here we show that many metabolites in the serum are significantly differentially regulated during chikungunya mono-infection as well as during chikungunya co-infection with dengue. We observed that glycine, serine, threonine, galactose and pyrimidine metabolisms are the most perturbed pathways in both mono and co-infection conditions. The affected pathways in our study correlate well with the clinical manifestation like fever, inflammation, energy deprivation and joint pain during the infections. These results may serve as a starting point for validations and identification of distinct biomolecules that could be exploited as biomarker candidates thereby helping in better patient management.

  12. Multi-platform characterization of the human cerebrospinal fluid metabolome: a comprehensive and quantitative update

    PubMed Central

    2012-01-01

    Background Human cerebral spinal fluid (CSF) is known to be a rich source of small molecule biomarkers for neurological and neurodegenerative diseases. In 2007, we conducted a comprehensive metabolomic study and performed a detailed literature review on metabolites that could be detected (via metabolomics or other techniques) in CSF. A total of 308 detectable metabolites were identified, of which only 23% were shown to be routinely identifiable or quantifiable with the metabolomics technologies available at that time. The continuing advancement in analytical technologies along with the growing interest in CSF metabolomics has led us to re-visit the human CSF metabolome and to re-assess both its size and the level of coverage than can be achieved with today's technologies. Methods We used five analytical platforms, including nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), direct flow injection-mass spectrometry (DFI-MS/MS) and inductively coupled plasma-mass spectrometry (ICP-MS) to perform quantitative metabolomics on multiple human CSF samples. This experimental work was complemented with an extensive literature review to acquire additional information on reported CSF compounds, their concentrations and their disease associations. Results NMR, GC-MS and LC-MS methods allowed the identification and quantification of 70 CSF metabolites (as previously reported). DFI-MS/MS allowed the quantification of 78 metabolites (6 acylcarnitines, 13 amino acids, hexose, 42 phosphatidylcholines, 2 lyso-phosphatidylcholines and 14 sphingolipids), while ICP-MS provided quantitative results for 33 metal ions in CSF. Literature analysis led to the identification of 57 more metabolites. In total, 476 compounds have now been confirmed to exist in human CSF. Conclusions The use of improved metabolomic and other analytical techniques has led to a 54% increase in the known size of the human CSF metabolome

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  15. The application of metabolomics in traditional Chinese medicine opens up a dialogue between Chinese and Western medicine.

    PubMed

    Cao, Hongxin; Zhang, Aihua; Zhang, Huamin; Sun, Hui; Wang, Xijun

    2015-02-01

    Metabolomics provides an opportunity to develop the systematic analysis of the metabolites and has been applied to discovering biomarkers and perturbed pathways which can clarify the action mechanism of traditional Chinese medicines (TCM). TCM is a comprehensive system of medical practice that has been used to diagnose, treat and prevent illnesses more than 3000 years. Metabolomics represents a powerful approach that provides a dynamic picture of the phenotype of biosystems through the study of endogenous metabolites, and its methods resemble those of TCM. Recently, metabolomics tools have been used for facilitating interactional effects of both Western medicine and TCM. We describe a protocol for investigating how metabolomics can be used to open up 'dialogue' between Chinese and Western medicine, and facilitate lead compound discovery and development from TCM. Metabolomics will bridge the cultural gap between TCM and Western medicine and improve development of integrative medicine, and maximally benefiting the human.

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

    PubMed Central

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

    2014-01-01

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

  17. Postgenomics Diagnostics: Metabolomics Approaches to Human Blood Profiling

    PubMed Central

    Lokhov, Petr; Archakov, Alexander

    2013-01-01

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

  18. Progress toward single cell metabolomics

    PubMed Central

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

    2012-01-01

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

  19. Applications of metabolomics in agriculture.

    PubMed

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

    2006-11-29

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