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Related Articles Increased Dynamics of Tricarboxylic Acid Cycle and Glutamate Synthesis in Obese Adipose Tissue: In vivo Metabolic Turnover Analysis. J Biol Chem. 2017 Jan 24;: Authors: Nagao H, Nishizawa H, Bamba T, Nakayama Y, Isozumi N, Nagamori S, Kanai Y, Tanaka Y, Kita S, Fukuda S, Funahashi T, Maeda N, Fukusaki E, Shimomura I Abstract Obesity locates upstream of various metabolic disorders. However, little is known about abnormalities in metabolic change of obese adipose tissue. Here, we use static metabolic analysis and in vivo metabolic turn over analysis to assess metabolic dynamics in obese mice. The static metabolic analyses showed that glutamate and constitutive metabolites of tricarboxylic acid (TCA) cycle were increased in white adipose tissue (WAT) of ob/ob and diet-induced obesity (DIO) mice, but not in liver or skeletal muscle of these obese mice. Moreover, in vivo metabolic turnover analyses demonstrated that glucose-derived these metabolites were dynamically and specifically produced in obese WAT, compared to lean WAT. Glutamate rise in obese WAT was associated with downregulation of GLAST, a major glutamate transporter for adipocytes, and low uptake of glutamate into adipose tissue. In adipocytes, glutamate treatment reduced adiponectin secretion and insulin-mediated glucose uptake and phosphorylation of Akt. These data suggest that high intra-adipocytes glutamate level potentially relates to adipocyte dysfunction in obesity. The study provides novel insight of metabolic dysfunction in obesity through comprehensive application of in vivo metabolic turnover analysis in two obese animal models. PMID: 28119455 [PubMed - as supplied by publisher]

Related Articles METabolic Syndrome In Men (METSIM) Study: a resource for studies of metabolic and cardiovascular diseases. J Lipid Res. 2017 Jan 24;: Authors: Laakso M, Kuusisto J, Stancakova A, Kuulasmaa T, Pajukanta P, Lusis AJ, Collins FS, Mohlke K, Boehnke M Abstract METabolic Syndrome In Men (METSIM) study is a population-based study including 10,197 Finnish men examined in 2005-2010. The aim of the study is to investigate non-genetic and genetic factors associated with the risk of type 2 diabetes and cardiovascular disease, and with cardiovascular risk factors. The protocol includes a detailed phenotyping of the participants, an oral glucose tolerance test, fasting laboratory measurements including proton nuclear magnetic resonance measurements, mass spectometry metabolomics, adipose tissue biopsies from 1,400 participants, and a stool sample. In our ongoing follow-up study, we have to date re-examined 6,496 participants. Extensive genotyping and exome sequencing have been performed for essentially all METSIM participants, and >2,000 METSIM participants have been whole genome sequenced. We have identified several non-genetic markers associated with the development of diabetes and cardiovascular events, and participated in several genetic association studies to identify gene variants associated with diabetes, hyperglycemia and cardiovascular risk factors. The generation of a phenotype and genotype resource in the METSIM study allows us to proceed towards "systems genetics" approach which includes statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels to provide a global view of the molecular architecture of complex traits. PMID: 28119442 [PubMed - as supplied by publisher]

Related Articles Feasibility of ultra-performance liquid chromatography-ion mobility-time-of-flight mass spectrometry in analyzing oxysterols. J Chromatogr A. 2017 Jan 18;: Authors: Kylli P, Hankemeier T, Kostiainen R Abstract Oxysterols are oxygenated cholesterols that are important in many cell functions and they may also be indicative of certain diseases. The purpose of this work was to study the feasibility of ultra-performance liquid chromatography-ion mobility-time-of-flight mass spectrometry (UPLC-IM-TOFMS) using traveling wave cell in analyzing oxysterols and especially their isomers in biological samples. Oxysterols were analyzed as their p-toluenesulfonyl isocyanate derivatives, which improved the separation of isomeric oxysterols by ion mobility and ionization efficiency in the electrospray ionization step. The UPLC-IM-TOFMS method was shown to be fast and to provide good quantitative performance. The feasibility of the method was demonstrated in the analyses of oxysterols in fibroblast cell samples. PMID: 28118975 [PubMed - as supplied by publisher]

Related Articles Chronic unpredictive mild stress leads to altered hepatic metabolic profile and gene expression. Sci Rep. 2016 Mar 23;6:23441 Authors: Jia HM, Li Q, Zhou C, Yu M, Yang Y, Zhang HW, Ding G, Shang H, Zou ZM Abstract Depression is a complex disease characterized by a series of pathological changes. Research on depression is mainly focused on the changes in brain, but not on liver. Therefore, we initially explored the metabolic profiles of hepatic extracts from rats treated with chronic unpredictive mild stress (CUMS) by UPLC-Q-TOF/MS. Using multivariate statistical analysis, a total of 26 altered metabolites distinguishing CUMS-induced depression from normal control were identified. Using two-stage receiver operating characteristic (ROC) analysis, 18 metabolites were recognized as potential biomarkers related to CUMS-induced depression via 12 metabolic pathways. Subsequently, we detected the mRNA expressions levels of apoptosis-associated genes such as Bax and Bcl-2 and four key enzymes including Pla2g15, Pnpla6, Baat and Gad1 involved in phospholipid and primary bile acid biosynthesis in liver tissues of CUMS rats by real-time qRT-PCR assay. The expression levels of Bax, Bcl-2, Pla2g15, Pnpla6 and Gad1 mRNA were 1.43,1.68, 1.74, 1.67 and 1.42-fold higher, and those of Baat, Bax/Bcl-2 ratio mRNA were 0.83, 0.85-fold lower in CUMS rats compared with normal control. Results of liver-targeted metabonomics and mRNA expression demonstrated that CUMS-induced depression leads to variations in hepatic metabolic profile and gene expression, and ultimately results in liver injury. PMID: 27006086 [PubMed - indexed for MEDLINE]

17 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/01/25PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

How close are we to complete annotation of metabolomes? Curr Opin Chem Biol. 2017 Jan 20;36:64-69 Authors: Viant MR, Kurland IJ, Jones MR, Dunn WB Abstract The metabolome describes the full complement of the tens to hundreds of thousands of low molecular weight metabolites present within a biological system. Identification of the metabolome is critical for discovering the maximum amount of biochemical knowledge from metabolomics datasets. Yet no exhaustive experimental characterisation of any organismal metabolome has been reported to date, dramatically contrasting with the genome sequencing of thousands of plants, animals and microbes. Here, we review the status of metabolome annotation and describe advances in the analytical methodologies being applied. In part through new international coordination, we conclude that we are now entering a new era of metabolome annotation. PMID: 28113135 [PubMed - as supplied by publisher]

Inference of cancer mechanisms through computational systems analysis. Mol Biosyst. 2017 Jan 23;: Authors: Qi Z, Voit EO Abstract Large amounts of metabolomics data have been accumulated to study metabolic alterations in cancer that allow cancer cells to synthesize molecular materials necessary for cell growth and proliferation. Although metabolic reprogramming in cancer was discovered almost a century ago, the underlying biochemical mechanisms are still unclear. We show that metabolomics data can be used to infer likely biochemical mechanisms associated with cancer. The proposed inference method is data-driven and quite generic; its efficacy is demonstrated by the analysis of changes in purine metabolism of human renal cell carcinoma. The method and results are essentially unbiased and tolerate noise in the data well. The proposed method correctly identified and accurately quantified primary enzymatic alterations in cancer, and these account for over 80% of the metabolic alterations in the investigated carcinoma. Interestingly, the two primary action sites are not the most sensitive reaction steps in purine metabolism, which implies that sensitivity analysis is not a valid approach for identifying cancer targets. The proposed method exhibits statistically high precision and robustness even for analyses of moderately incomplete metabolomics data. By permitting analyses of individual metabolic profiles, the method may become a tool of personalized precision medicine. PMID: 28112324 [PubMed - as supplied by publisher]

Multi-omics analyses reveal metabolic alterations regulated by hepatitis B virus core protein in hepatocellular carcinoma cells. Sci Rep. 2017 Jan 23;7:41089 Authors: Xie Q, Fan F, Wei W, Liu Y, Xu Z, Zhai L, Qi Y, Ye B, Zhang Y, Basu S, Zhao Z, Wu J, Xu P Abstract Chronic hepatitis B virus (HBV) infection is partly responsible for hepatitis, fatty liver disease and hepatocellular carcinoma (HCC). HBV core protein (HBc), encoded by the HBV genome, may play a significant role in HBV life cycle. However, the function of HBc in the occurrence and development of liver disease is still unclear. To investigate the underlying mechanisms, HBc-transfected HCC cells were characterized by multi-omics analyses. Combining proteomics and metabolomics analyses, our results showed that HBc promoted the expression of metabolic enzymes and the secretion of metabolites in HCC cells. In addition, glycolysis and amino acid metabolism were significantly up-regulated by HBc. Moreover, Max-like protein X (MLX) might be recruited and enriched by HBc in the nucleus to regulate glycolysis pathways. This study provides further insights into the function of HBc in the molecular pathogenesis of HBV-induced diseases and indicates that metabolic reprogramming appears to be a hallmark of HBc transfection. PMID: 28112229 [PubMed - in process]

Loss of Merlin induces metabolomic adaptation that engages dependence on Hedgehog signaling. Sci Rep. 2017 Jan 23;7:40773 Authors: Das S, Jackson WP, Prasain JK, Hanna A, Bailey SK, Tucker JA, Bae S, Wilson LS, Samant RS, Barnes S, Shevde LA Abstract The tumor suppressor protein Merlin is proteasomally degraded in breast cancer. We undertook an untargeted metabolomics approach to discern the global metabolomics profile impacted by Merlin in breast cancer cells. We discerned specific changes in glutathione metabolites that uncovered novel facets of Merlin in impacting the cancer cell metabolome. Concordantly, Merlin loss increased oxidative stress causing aberrant activation of Hedgehog signaling. Abrogation of GLI-mediated transcription activity compromised the aggressive phenotype of Merlin-deficient cells indicating a clear dependence of cells on Hedgehog signaling. In breast tumor tissues, GLI1 expression enhanced tissue identification and discriminatory power of Merlin, cumulatively presenting a powerful substantiation of the relationship between these two proteins. We have uncovered, for the first time, details of the tumor cell metabolomic portrait modulated by Merlin, leading to activation of Hedgehog signaling. Importantly, inhibition of Hedgehog signaling offers an avenue to target the vulnerability of tumor cells with loss of Merlin. PMID: 28112165 [PubMed - in process]

Genetics of schizophrenia: A consensus paper of the WFSBP Task Force on Genetics. World J Biol Psychiatry. 2017 Jan 23;:1-14 Authors: Giegling I, Hosak L, Mössner R, Serretti A, Bellivier F, Claes S, Collier DA, Corrales A, DeLisi LE, Gallo C, Gill M, Kennedy JL, Leboyer M, Maier W, Marquez M, Massat I, Mors O, Muglia P, Nöthen MM, Ospina-Duque J, Owen MJ, Propping P, Shi Y, St Clair D, Thibaut F, Cichon S, Mendlewicz J, O'Donovan MC, Rujescu D Abstract OBJECTIVES: Schizophrenia is a severe psychiatric disease affecting about 1% of the general population. The relative contribution of genetic factors has been estimated to be up to 80%. The mode of inheritance is complex, non-Mendelian, and in most cases involving the combined action of large numbers of genes. METHODS: This review summarises recent efforts to identify genetic variants associated with schizophrenia detected, e.g., through genome-wide association studies, studies on copy-number variants or next-generation sequencing. RESULTS: A large, new body of evidence on genetics of schizophrenia has accumulated over recent years. Many new robustly associated genetic loci have been detected. Furthermore, there is consensus that at least a dozen microdeletions and microduplications contribute to the disease. Genetic overlap between schizophrenia, other psychiatric disorders, and neurodevelopmental syndromes raised new questions regarding the current classification of psychiatric and neurodevelopmental diseases. CONCLUSIONS: Future studies will address especially the functional characterisation of genetic variants. This will hopefully open the doors to our understanding of the pathophysiology of schizophrenia and other related diseases. Complementary, integrated systems biology approaches to genomics, transcriptomics, proteomics and metabolomics may also play crucial roles in enabling a precision medicine approach to the treatment of individual patients. PMID: 28112043 [PubMed - as supplied by publisher]

Systematic evaluation of serum and plasma collection on the endogenous metabolome. Bioanalysis. 2017 Jan 23;: Authors: Zhou Z, Chen Y, He J, Xu J, Zhang R, Mao Y, Abliz Z Abstract AIM: In metabolomics research, the use of different blood collection methods may influence endogenous metabolites. MATERIALS & METHODS: Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants. RESULTS: Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma. PMID: 28111959 [PubMed - as supplied by publisher]

Related Articles Ultra high performance liquid chromatography-high resolution mass spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets. Metabolomics. 2017;13(2):15 Authors: Lloyd AJ, Beckmann M, Wilson T, Tailliart K, Allaway D, Draper J Abstract INTRODUCTION AND OBJECTIVES: The purpose of this study was to use high accurate mass metabolomic profiling to investigate differences within a phenotypically diverse canine population, with breed-related morphological, physiological and behavioural differences. Previously, using a broad metabolite fingerprinting approach, lipids appear to dominate inter- and intra- breed discrimination. The purpose here was to use Ultra High Performance Liquid Chromatography-High Resolution Mass Spectrometry (UHPLC-HRMS) to identify in more detail, inter-breed signatures in plasma lipidomic profiles of home-based, client-owned dogs maintained on different diets and fed according to their owners' feeding regimens. METHODS: Nine dog breeds were recruited in this study (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese: 7-12 dogs per breed). Metabolite profiling on a MTBE lipid extract of fasted plasma was performed using UHPLC-HRMS. RESULTS: Multivariate modelling and classification indicated that the main source of lipidome variance was between the three breeds Chihuahua, Dachshund and Greyhound and the other six breeds, however some intra-breed variance was evident in Labrador Retrievers. Metabolites associated with dietary intake impacted on breed-associated variance and following filtering of these signals out of the data-set unique inter-breed lipidome differences for Chihuahua, Golden Retriever and Greyhound were identified. CONCLUSION: By using a phenotypically diverse home-based canine population, we were able to show that high accurate mass lipidomics can enable identification of metabolites in the first pass plasma profile, capturing distinct metabolomic variability associated with genetic differences, despite environmental and dietary variability. PMID: 28111530 [PubMed - in process]

Related Articles NMR Techniques in Metabolomic Studies: A Quick Overview on Examples of Utilization. Appl Magn Reson. 2017;48(1):1-21 Authors: Kruk J, Doskocz M, Jodłowska E, Zacharzewska A, Łakomiec J, Czaja K, Kujawski J Abstract Metabolomics is a rapidly developing branch of science that concentrates on identifying biologically active molecules with potential biomarker properties. To define the best biomarkers for diseases, metabolomics uses both models (in vitro, animals) and human, as well as, various techniques such as mass spectroscopy, gas chromatography, liquid chromatography, infrared and UV-VIS spectroscopy and nuclear magnetic resonance. The last one takes advantage of the magnetic properties of certain nuclei, such as (1)H, (13)C, (31)P, (19)F, especially their ability to absorb and emit energy, what is crucial for analyzing samples. Among many spectroscopic NMR techniques not only one-dimensional (1D) techniques are known, but for many years two-dimensional (2D, for example, COSY, DOSY, JRES, HETCORE, HMQS), three-dimensional (3D, DART-MS, HRMAS, HSQC, HMBC) and solid-state NMR have been used. In this paper, authors taking apart fundamental division of nuclear magnetic resonance techniques intend to shown their wide application in metabolomic studies, especially in identifying biomarkers. PMID: 28111499 [PubMed - in process]

Related Articles GC-MS-based Metabolomics Identifies an Amino Acid Signature of Acute Ischemic Stroke. Neurosci Lett. 2017 Jan 19;: Authors: Wang D, Kong J, Wu J, Wang X, Lai M Abstract Ischemic stroke is a serious public health problem worldwide. Here, we characterized the metabolite features of acute ischemic stroke (AIS) using a gas chromatography-mass spectrometry-based metabolomics. Forty AIS patients and 29 sex and age-matched controls were recruited. The serum metabolic profiles were significantly different between the two groups. Compared to the controls, the patients had elevated levels of lactate, carbonate and glutamate (P<0.01), and lowered levels of alanine, citrate, glycine, isoleucine, leucine, serine, tyrosine, methionine, tryptophan, erythronic acid, urea, purine, hypoxanthine, and proline in the serum (P<0.05). Amino acids are the most important disturbed metabolites. Most dysregulated metabolites are closely correlated with each other and with several biochemical indices. The differential metabolites reflect pathophysiological processes of inflammation, energy deficit, oxidative stress, neurotoxicity, neuro excitation and injury. Tyrosine, lactate, and tryptophan were screened as a panel of potential biomarkers of AIS, jointly enabling a high precision (91.7%) to diagnose AIS by classification and regression tree (CRT). Collectively, we discovered a marked perturbation of metabolome of AIS in the serum, mainly associated with amino acid-related metabolism. Tyrosine, lactate, and tryptophan may be considered as potential biomarkers of AIS. PMID: 28111353 [PubMed - as supplied by publisher]

Related Articles The Application of Principal Component Analysis to Drug Discovery and Biomedical Data. Drug Discov Today. 2017 Jan 19;: Authors: Giuliani A Abstract There is a neat distinction between general purpose statistical techniques and quantitative models developed for specific problems .Principal Component Analysis (PCA) blurs this distinction: while being a general purpose statistical technique, it implies a peculiar style of reasoning. PCA is a 'hypothesis generating' tool creating a statistical mechanics frame for biological systems modeling without the need for strong a priori theoretical assumptions. This makes PCA of utmost importance for approaching drug discovery by a systemic perspective overcoming too narrow reductionist approaches. PMID: 28111329 [PubMed - as supplied by publisher]

Related Articles Metabolomic profiling of brain tissues of mice chronically exposed to heroin. Drug Metab Pharmacokinet. 2016 Oct 27;: Authors: Li RS, Takeda T, Ohshima T, Yamada H, Ishii Y Abstract The chronic neurotoxicity of heroin on the nervous system is poorly understood. To address this issue, we comprehensively assessed the alteration of brain metabolomics caused by chronic heroin exposure and the withdrawal of heroin. Male C57BL/6J mice (n = 10) were given heroin (15 μmol/kg, i.p., twice a day) for 12 days while the withdrawal group received saline-treatment instead of heroin for the last two days. The control group received saline. We developed an UPLC-TOF/MS-based metabolomic approach to analyze the metabolites and carry out a metabolic pathway analysis in the brain. The major metabolites contributing to the discrimination were identified as amino acids, tricarboxylic-acid cycle intermediates, neurotransmitters, nucleotides and other compounds. A marked reduction in histidine and a slight but significant increase in phenylalanine and tryptophan were observed after heroin was withdrawn while the increased level of catecholamines was restored to baseline. Interestingly, N-acetylserotonin - a precursor of melatonin - was increased with the withdrawal of heroin while melatonin was markedly reduced along with the sub-chronic exposure to heroin. This shows that heroin disrupts not only the energy metabolism but also the biosynthesis of both catecholamines and melatonin in the mouse brain. Therefore, these substances are candidate biomarkers for chronic heroin-abuse. PMID: 28111102 [PubMed - as supplied by publisher]

Related Articles Carbon Sources Tune Antibiotic Susceptibility in Pseudomonas aeruginosa via Tricarboxylic Acid Cycle Control. Cell Chem Biol. 2017 Jan 16;: Authors: Meylan S, Porter CB, Yang JH, Belenky P, Gutierrez A, Lobritz MA, Park J, Kim SH, Moskowitz SM, Collins JJ Abstract Metabolically dormant bacteria present a critical challenge to effective antimicrobial therapy because these bacteria are genetically susceptible to antibiotic treatment but phenotypically tolerant. Such tolerance has been attributed to impaired drug uptake, which can be reversed by metabolic stimulation. Here, we evaluate the effects of central carbon metabolite stimulations on aminoglycoside sensitivity in the pathogen Pseudomonas aeruginosa. We identify fumarate as a tobramycin potentiator that activates cellular respiration and generates a proton motive force by stimulating the tricarboxylic acid (TCA) cycle. In contrast, we find that glyoxylate induces phenotypic tolerance by inhibiting cellular respiration with acetyl-coenzyme A diversion through the glyoxylate shunt, despite drug import. Collectively, this work demonstrates that TCA cycle activity is important for both aminoglycoside uptake and downstream lethality and identifies a potential strategy for potentiating aminoglycoside treatment of P. aeruginosa infections. PMID: 28111098 [PubMed - as supplied by publisher]

Related Articles In Situ Metabolomics in Cancer by Mass Spectrometry Imaging. Adv Cancer Res. 2017;134:117-132 Authors: Buck A, Aichler M, Huber K, Walch A Abstract Metabolomics is a rapidly evolving and a promising research field with the expectation to improve diagnosis, therapeutic treatment prediction, and prognosis of particular diseases. Among all techniques used to assess the metabolome in biological systems, mass spectrometry imaging is the method of choice to qualitatively and quantitatively analyze metabolite distribution in tissues with a high spatial resolution, thus providing molecular data in relation to cancer histopathology. The technique is ideally suited to study tissues molecular content and is able to provide molecular biomarkers or specific mass signatures which can be used in classification or the prognostic evaluation of tumors. Recently, it was shown that FFPE tissue samples are also suitable for metabolic analyses. This progress in methodology allows access to a highly valuable resource of tissues believed to widen and strengthen metabolic discovery-driven studies. PMID: 28110648 [PubMed - in process]

Related Articles Insomnia does not mediate or modify the association between MTNR1B risk variant rs10830963 and glucose levels. Diabetologia. 2016 May;59(5):1070-2 Authors: Ollila HM, Kronholm E, Kettunen J, Silander K, Perola M, Porkka-Heiskanen T, Salomaa V, Paunio T PMID: 26912228 [PubMed - indexed for MEDLINE]

Related Articles Acute-on-chronic liver failure: recent update. J Biomed Res. 2017 Jan 19;: Authors: Azeem A, Ka CS, Daqing M Abstract Acute on chronic liver failure (ACLF) was first described in 1995 as a clinical syndrome distinct to classic acute decompensation. Characterized by complications of decompensation, ACLF occurs on a background of chronic liver dysfunction and is associated with high rates of organ failure and significant short-term mortality estimated between 45% and 90%. Despite the clinical relevance of the condition, it still remains largely undefined with continued disagreement regarding its precise etiological factors, clinical course, prognostic criteria and management pathways. It is concerning that, despite our relative lack of understanding of the condition, the burden of ACLF among cirrhotic patients remains significant with an estimated prevalence of 30.9%. This paper highlights our current understanding of ACLF, including its etiology, diagnostic and prognostic criteria and pathophysiology. It is evident that further refinement of the ACLF classification system is required in order to detect high-risk patients and improve short-term mortality rates. The field of metabolomics certainly warrants investigation to enhance diagnostic and prognostic parameters, while the use of granulocyte-colony stimulating factor is a promising future therapeutic intervention for patients with ACLF. PMID: 28110320 [PubMed - as supplied by publisher]