PubMed

Related Articles Metabolic profiles of dioscin in rats revealed by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry. Biomed Chromatogr. 2015 Sep;29(9):1415-21 Authors: Zhu H, Xu JD, Mao Q, Shen H, Kong M, Chen JP, Li SL Abstract Dioscin (DIS), one of the most abundant bioactive steroidal saponins in Dioscorea sp., is used as a complementary medicine to treat coronary disease and angina pectoris in China. Although the pharmacological activities and pharmacokinetics of DIS have been well demonstrated, information regarding the final metabolic fates is very limited. This study investigated the in vivo metabolic profiles of DIS after oral administration by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry method. The structures of the metabolites were identified and tentatively characterized by means of comparing the molecular mass, retention time and fragmentation pattern of the analytes with those of the parent compound. A total of eight metabolites, including seven phase I and one phase II metabolites, were detected and tentatively identified for the first time. Oxidation, deglycosylation and glucuronidation were found to be the major metabolic processes of the compound in rats. In addition, a possible metabolic pathway on the biotransformation of DIS in vivo was proposed. This study provides valuable and new information on the metabolism of DIS, which will be helpful for further understanding its mechanism of action. PMID: 25678372 [PubMed - indexed for MEDLINE]

Related Articles Short communication: Use of genomic and metabolic information as well as milk performance records for prediction of subclinical ketosis risk via artificial neural networks. J Dairy Sci. 2015 Jan;98(1):322-9 Authors: Ehret A, Hochstuhl D, Krattenmacher N, Tetens J, Klein MS, Gronwald W, Thaller G Abstract Subclinical ketosis is one of the most prevalent metabolic disorders in high-producing dairy cows during early lactation. This renders its early detection and prevention important for both economical and animal-welfare reasons. Construction of reliable predictive models is challenging, because traits like ketosis are commonly affected by multiple factors. In this context, machine learning methods offer great advantages because of their universal learning ability and flexibility in integrating various sorts of data. Here, an artificial-neural-network approach was applied to investigate the utility of metabolic, genetic, and milk performance data for the prediction of milk levels of β-hydroxybutyrate within and across consecutive weeks postpartum. Data were collected from 218 dairy cows during their first 5wk in milk. All animals were genotyped with a 50,000 SNP panel, and weekly information on the concentrations of the milk metabolites glycerophosphocholine and phosphocholine as well as milk composition data (milk yield, fat and protein percentage) was available. The concentration of β-hydroxybutyric acid in milk was used as target variable in all prediction models. Average correlations between observed and predicted target values up to 0.643 could be obtained, if milk metabolite and routine milk recording data were combined for prediction at the same day within weeks. Predictive performance of metabolic as well as milk performance-based models was higher than that of models based on genetic information. PMID: 25465566 [PubMed - indexed for MEDLINE]

23 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 2016/02/18PubMed comprises more than 24 million 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.

Glucose metabolism in gastric cancer: The cutting-edge. World J Gastroenterol. 2016 Feb 14;22(6):2046-59 Authors: Yuan LW, Yamashita H, Seto Y Abstract Glucose metabolism in gastric cancer cells differs from that of normal epithelial cells. Upregulated aerobic glycolysis (Warburg effect) in gastric cancer meeting the demands of cell proliferation is associated with genetic mutations, epigenetic modification and proteomic alteration. Understanding the mechanisms of aerobic glycolysis may contribute to our knowledge of gastric carcinogenesis. Metabolomic studies offer novel, convenient and practical tools in the search for new biomarkers for early detection, diagnosis, prognosis, and chemosensitivity prediction of gastric cancer. Interfering with the process of glycolysis in cancer cells may provide a new and promising therapeutic strategy for gastric cancer. In this article, we present a brief review of recent studies of glucose metabolism in gastric cancer, with primary focus on the clinical applications of new biomarkers and their potential therapeutic role in gastric cancer. PMID: 26877609 [PubMed - in process]

Optimization of large-scale pseudotargeted metabolomics method based on liquid chromatography-mass spectrometry. J Chromatogr A. 2016 Feb 4; Authors: Luo P, Yin P, Zhang W, Zhou L, Lu X, Lin X, Xu G Abstract Liquid chromatography-mass spectrometry (LC-MS) is now a main stream technique for large-scale metabolic phenotyping to obtain a better understanding of genomic functions. However, repeatability is still an essential issue for the LC-MS based methods, and convincing strategies for long time analysis are urgently required. Our former reported pseudotargeted method which combines nontargeted and targeted analyses, is proved to be a practical approach with high-quality and information-rich data. In this study, we developed a comprehensive strategy based on the pseudotargeted analysis by integrating blank-wash, pooled quality control (QC) sample, and post-calibration for the large-scale metabolomics study. The performance of strategy was optimized from both pre- and post-acquisition sections including the selection of QC samples, insertion frequency of QC samples, and post-calibration methods. These results imply that the pseudotargeted method is rather stable and suitable for large-scale study of metabolic profiling. As a proof of concept, the proposed strategy was applied to the combination of 3 independent batches within a time span of 5 weeks, and generated about 54% of the features with coefficient of variations (CV) below 15%. Moreover, the stability and maximal capability of a single analytical batch could be extended to at least 282 injections (about 110h) while still providing excellent stability, the CV of 63% metabolic features was less than 15%. Taken together, the improved repeatability of our strategy provides a reliable protocol for large-scale metabolomics studies. PMID: 26877181 [PubMed - as supplied by publisher]

The TCA cycle transferase DLST is important for MYC-mediated leukemogenesis. Leukemia. 2016 Feb 15; Authors: Anderson NM, Li D, Peng HL, Laroche FJ, Mansour MR, Gjini E, Aioub M, Helman DJ, Roderick JE, Cheng T, Harrold I, Samaha Y, Meng L, Amsterdam A, Neuberg DS, Denton TT, Sanda T, Kelliher MA, Singh A, Look AT, Feng H Abstract Despite the pivotal role of MYC in the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL) and many other cancers, the mechanisms underlying MYC-mediated tumorigenesis remain inadequately understood. Here we utilized a well-characterized zebrafish model of Myc-induced T-ALL for genetic studies to identify novel genes contributing to disease onset. We found that heterozygous inactivation of a tricarboxylic acid (TCA) cycle enzyme, dihydrolipoamide S-succinyltransferase (Dlst), significantly delayed tumor onset in zebrafish without detectable effects on fish development. DLST is the E2 transferase of the α-ketoglutarate dehydrogenase complex (KGDHC), which converts α-ketoglutarate (α-KG) to succinyl-CoA in the TCA cycle. RNAi knockdown of DLST led to decreased cell viability and induction of apoptosis in human T-ALL cell lines. Polar metabolomics profiling revealed that the TCA cycle was disrupted by DLST knockdown in human T-ALL cells, as demonstrated by an accumulation of α-KG and a decrease of succinyl-CoA. Addition of succinate, the downstream TCA cycle intermediate, to human T-ALL cells was sufficient to rescue defects in cell viability caused by DLST inactivation. Together, our studies uncovered an important role for DLST in MYC-mediated leukemogenesis and demonstrated the metabolic dependence of T-lymphoblasts on the TCA cycle, thus providing implications for targeted therapy.Leukemia accepted article preview online, 15 February 2016. doi:10.1038/leu.2016.26. PMID: 26876595 [PubMed - as supplied by publisher]

MCT1 Modulates Cancer Cell Pyruvate Export and Growth of Tumors that Co-express MCT1 and MCT4. Cell Rep. 2016 Feb 10; Authors: Hong CS, Graham NA, Gu W, Espindola Camacho C, Mah V, Maresh EL, Alavi M, Bagryanova L, Krotee PA, Gardner BK, Behbahan IS, Horvath S, Chia D, Mellinghoff IK, Hurvitz SA, Dubinett SM, Critchlow SE, Kurdistani SK, Goodglick L, Braas D, Graeber TG, Christofk HR Abstract Monocarboxylate transporter 1 (MCT1) inhibition is thought to block tumor growth through disruption of lactate transport and glycolysis. Here, we show MCT1 inhibition impairs proliferation of glycolytic breast cancer cells co-expressing MCT1 and MCT4 via disruption of pyruvate rather than lactate export. MCT1 expression is elevated in glycolytic breast tumors, and high MCT1 expression predicts poor prognosis in breast and lung cancer patients. Acute MCT1 inhibition reduces pyruvate export but does not consistently alter lactate transport or glycolytic flux in breast cancer cells that co-express MCT1 and MCT4. Despite the lack of glycolysis impairment, MCT1 loss-of-function decreases breast cancer cell proliferation and blocks growth of mammary fat pad xenograft tumors. Our data suggest MCT1 expression is elevated in glycolytic cancers to promote pyruvate export that when inhibited, enhances oxidative metabolism and reduces proliferation. This study presents an alternative molecular consequence of MCT1 inhibitors, further supporting their use as anti-cancer therapeutics. PMID: 26876179 [PubMed - as supplied by publisher]

A combined non-targeted and targeted metabolomics approach to study the stereoselective metabolism of benalaxyl enantiomers in mouse hepatic microsomes. Environ Pollut. 2016 Feb 10;212:358-365 Authors: Wang X, Wang D, Wang Y, Zhang P, Zhou Z, Zhu W Abstract Understanding of xenobiotic metabolism is necessary for risk assessment as well as toxicological research. In the present study, nanoLC/LTQ-Orbitrap mass based non-targeted metabolomics method coupled with ultra-performance liquid chromatography (UPLC)/triple quadrupole mass based targeted metabolomics method was carried out to investigate the stereoselective metabolism of benalaxyl in mouse hepatic microsomes. As a result, 7 metabolites of benalaxyl were identified, including 5 previously reported and 2 newly identified metabolites in present work. Hydroxylation, oxidation and esterolysis were major biotransformation reactions of benalaxyl in mouse hepatic microsomes. For stereoselective metabolism study, (-)-R-benalaxyl degraded much faster than its antipode with the t1/2 of 81.24 and 190.38 min for (-)-R- and (+)-S-benalaxyl, respectively. More importantly, stereoselectivity was also observed in the formation of the identified metabolites. In conclusion, the combined use of the mass spectrometry based targeted and non-targeted metabolomics provided a new approach to investigate stereoselective metabolism and identify novel metabolites of chiral pesticides. This study highlights the stereoselective metabolic profile of benalaxyl enantiomers and provides reliable data for benalaxyl toxicological risk assessment in mammal. PMID: 26874317 [PubMed - as supplied by publisher]

Lean-seafood intake decreases urinary markers of mitochondrial lipid and energy metabolism in healthy subjects: metabolomics results from a randomized crossover intervention study. Mol Nutr Food Res. 2016 Feb 13; Authors: Schmedes M, Aadland EK, Sundekilde UK, Jacques H, Lavigne C, Graff IE, Eng Ø, Holthe A, Mellgren G, Young JF, Bertram HC, Liaset B, Clausen MR Abstract SCOPE: Proteins constitute an important part of the human diet, but understanding of the effects of different dietary protein sources on human metabolism is sparse. We aimed to elucidate diet-induced metabolic changes through untargeted urinary metabolomics after 4 wks of intervention with lean-seafood or non-seafood diets. METHODS: In a randomized controlled trial with crossover design 20 healthy subjects consumed 2 balanced diets that varied in main protein sources for 4 wks. Morning spot urine samples were collected before and after each intervention period. Untargeted metabolomics based on (1) H NMR spectroscopy and LC-MS analyses were applied to characterize the urinary metabolic response to the interventions. RESULTS: The lean-seafood diet period reduced the urinary level of L-carnitine, 2,6-dimethylheptanoylcarnitine and N-2-pyridone-5-carboxamide (2PY), relative to the non-seafood period. The dietary analysis revealed that the higher urinary level of trimethylamine-N-oxide (TMAO) after the lean-seafood diet period and guanidinoacetate and 3-methylhistidine (3MH) after the non-seafood diet period was related to the endogenous content of these compounds in the diets. CONCLUSIONS: Our data reveal that 4 wks of lean-seafood intake reduces urinary excretion of metabolites involved in mitochondrial lipid and energy metabolism possibly facilitating a higher lipid catabolism in healthy subjects after the lean-seafood intake. This article is protected by copyright. All rights reserved. PMID: 26873789 [PubMed - as supplied by publisher]

The study on serum and urine of renal interstitial fibrosis rats induced by unilateral ureteral obstruction based on metabonomics and network analysis methods. Anal Bioanal Chem. 2016 Feb 12; Authors: Xiang Z, Sun H, Cai X, Chen D Abstract Transmission of biological information is a biochemical process of multistep cascade from genes/proteins to metabolites. However, because most metabolites reflect the terminal information of the biochemical process, it is difficult to describe the transmission process of disease information in terms of the metabolomics strategy. In this paper, by incorporating network and metabolomics methods, an integrated approach was proposed to systematically investigate and explain the molecular mechanism of renal interstitial fibrosis. Through analysis of the network, the cascade transmission process of disease information starting from genes/proteins to metabolites was putatively identified and uncovered. The results indicated that renal fibrosis was involved in metabolic pathways of glycerophospholipid metabolism, biosynthesis of unsaturated fatty acids and arachidonic acid metabolism, riboflavin metabolism, tyrosine metabolism, and sphingolipid metabolism. These pathways involve kidney disease genes such as TGF-β1 and P2RX7. Our results showed that combining metabolomics and network analysis can provide new strategies and ideas for the interpretation of pathogenesis of disease with full consideration of "gene-protein-metabolite." Graphical Abstract ᅟ. PMID: 26873208 [PubMed - as supplied by publisher]

Target-based metabolomics for the quantitative measurement of 37 pathway metabolites in rat brain and serum using hydrophilic interaction ultra-high-performance liquid chromatography-tandem mass spectrometry. Anal Bioanal Chem. 2016 Feb 12; Authors: Chen J, Hou W, Han B, Liu G, Gong J, Li Y, Zhong D, Liao Q, Xie Z Abstract Amino acids, neurotransmitters, purines, and pyrimidines are bioactive molecules that play fundamental roles in maintaining various physiological functions. Their metabolism is closely related to the health, growth, development, reproduction, and homeostasis of organisms. Most recently, comprehensive measurements of these metabolites have shown their potential as innovative approaches in disease surveillance or drug intervention. However, simultaneous measurement of these metabolites presents great difficulties. Here, we report a novel quantitative method that uses hydrophilic interaction ultra-high-performance liquid chromatography-tandem mass spectrometry (HILIC-UPLC-MS/MS), which is highly selective, high throughput, and exhibits better chromatographic behavior than existing methods. The developed method enabled the rapid quantification of 37 metabolites, spanning amino acids, neurotransmitters, purines, and pyrimidines pathways, within 6.5 min. The compounds were separated on an ACQUITY UPLC® BEH Amide column. Serum and brain homogenate were extracted by protein precipitation. The intra- and interday precision of all of the analytes was less than 11.34 %, and the accuracy was between -11.74 and 11.51 % for all quality control (QC) levels. The extraction recoveries of serum ranged from 84.58 % to 116.43 % and those of brain samples from 80.80 % to 119.39 %, while the RSD was 14.61 % or less for all recoveries. This method was used to successfully characterize alterations in the rat brain and, in particular, their dynamics in serum. The following study was performed to simultaneously test global changes of these metabolites in a serotonin antagonist p-chlorophenylalanine (PCPA)-induced anxiety and insomnia rat model to understand the effect and mechanism of PCPA. Taken together, these results show that the method is able to simultaneously monitor a large panel of metabolites and that this protocol may represent a metabolomic method to diagnose toxicological and pathophysiological states. Graphical Abstract Overview of experimental workflow. PMID: 26873199 [PubMed - as supplied by publisher]

18 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 2016/02/13PubMed comprises more than 24 million 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.

Related Articles Metabolomic and Transcriptomic Comparison of Solid-State and Submerged Fermentation of Penicillium expansum KACC 40815. PLoS One. 2016;11(2):e0149012 Authors: Kim HY, Heo DY, Park HM, Singh D, Lee CH Abstract Penicillium spp. are known to harbor a wide array of secondary metabolites with cryptic bioactivities. However, the metabolomics of these species is not well-understood in terms of different fermentation models and conditions. The present study involved metabolomics profiling and transcriptomic analysis of Penicillium expansum 40815 under solid-state fermentation (SSF) and submerged fermentation (SmF). Metabolite profiling was carried out using ultra-performance liquid chromatography quadruple time-of-flight mass spectrometry with multivariate analysis, followed by transcriptomic analyses of differentially expressed genes. In principal component analysis, the metabolite profiling data was studied under different experimental sets, including SSF and SmF. The significantly different metabolites such as polyketide metabolites (agonodepside B, rotiorin, verrucosidin, and ochrephilone) and corresponding gene transcripts (polyketide synthase, aromatic prenyltransferase, and terpenoid synthase) were primarily detected under SmF conditions. In contrast, the meroterpenoid compounds (andrastin A and C) and their genes transcripts were exclusively detected under SSF conditions. We demonstrated that the metabolite production and its corresponding gene expression levels in P. expansum 40815 were significantly influenced by the varying growth parameters and the immediate environment. This study further provides a foundation to produce specific metabolites by regulating fermentation conditions. PMID: 26863302 [PubMed - as supplied by publisher]

Related Articles Plasma First Resuscitation Reduces Lactate Acidosis, Enhances Redox Homeostasis, Amino Acid and Purine Catabolism in a Rat Model of Profound Hemorrhagic Shock. Shock. 2016 Feb 6; Authors: D'Alessandro A, Moore HB, Moore EE, Wither MJ, Nemkov T, Morton AP, Gonzalez E, Chapman MP, Fragoso M, Slaughter A, Sauaia A, Silliman CC, Hansen KC, Banerjee A Abstract The use of aggressive crystalloid resuscitation to treat hypoxemia, hypovolemia and nutrient deprivation promoted by massive blood loss may lead to the development of the blood vicious cycle of acidosis, hypothermia, and coagulopathy and, utterly, death. Metabolic acidosis is one of the many metabolic derangements triggered by severe trauma/hemorrhagic shock, also including enhanced proteolysis, lipid mobilization, as well as traumatic diabetes. Appreciation of the metabolic benefit of plasma first resuscitation is an important concept. Plasma resuscitation has been shown to correct hyperfibrinolysis secondary to severe hemorrhage better than normal saline. Here we hypothesize that plasma first resuscitation corrects metabolic derangements promoted by severe hemorrhage better than resuscitation with normal saline. Ultra-high-performance liquid chromatography-mass spectrometry-based metabolomics analyses were performed to screen plasma metabolic profiles upon shock and resuscitation with either platelet-free plasma or normal saline in a rat model of severe hemorrhage. Of the 251 metabolites that were monitored, 101 were significantly different in plasma vs normal saline resuscitated rats. Plasma resuscitation corrected lactate acidosis by promoting glutamine/amino acid catabolism and purine salvage reactions. Plasma first resuscitation may benefit critically injured trauma patients by relieving the lactate burden and promoting other non-clinically measured metabolic changes. In the light of our results, we propose that plasma resuscitation may promote fueling of mitochondrial metabolism, through the enhancement of glutaminolysis/amino acid catabolism and purine salvage reactions. The treatment of trauma patients in hemorrhagic shock with plasma first resuscitation is likely not only to improve coagulation, but also to promote substrate-specific metabolic corrections. PMID: 26863033 [PubMed - as supplied by publisher]

Related Articles Adjustments to the preanalytical phase of quantitative cell-free DNA analysis. Data Brief. 2016 Mar;6:326-9 Authors: Bronkhorst AJ, Aucamp J, Pretorius PJ Abstract Evaluating the kinetics of cell-free DNA (cfDNA) in the blood of cancer patients could be a strong auxiliary component to the molecular characterization of cfDNA, but its potential clinical significance is obscured by the absence of an analytical consensus. To utilize quantitative cfDNA assessment with confidence, it is crucial that the preanalytical phase is standardized. In a previous publication, several preanalytical variables that may affect quantitative measurements of cfDNA were identified, and the most confounding variables were assessed further using the growth medium of cultured cancer cells as a source of cfDNA ("Cell-free DNA: Preanalytical variables" [1]). The data accompanying this report relates to these experiments, which includes numerous changes to the sample handling and isolation protocols, and can be used for the interpretation of these results and other similar experiments by different researchers. PMID: 26862578 [PubMed]

Related Articles Short and long term prognosis in perinatal asphyxia: An update. World J Clin Pediatr. 2016 Feb 8;5(1):67-74 Authors: Ahearne CE, Boylan GB, Murray DM Abstract Interruption of blood flow and gas exchange to the fetus in the perinatal period, known as perinatal asphyxia, can, if significant, trigger a cascade of neuronal injury, leading on to neonatal encephalopathy (NE) and resultant long-term damage. While the majority of infants who are exposed to perinatal hypoxia-ischaemia will recover quickly and go on to have a completely normal survival, a proportion will suffer from an evolving clinical encephalopathy termed hypoxic-ischaemic encephalopathy (HIE) or NE if the diagnosis is unclear. Resultant complications of HIE/NE are wide-ranging and may affect the motor, sensory, cognitive and behavioural outcome of the child. The advent of therapeutic hypothermia as a neuroprotective treatment for those with moderate and severe encephalopathy has improved prognosis. Outcome prediction in these infants has changed, but is more important than ever, as hypothermia is a time sensitive intervention, with a very narrow therapeutic window. To identify those who will benefit from current and emerging neuroprotective therapies we must be able to establish the severity of their injury soon after birth. Currently available indicators such as blood biochemistry, clinical examination and electrophysiology are limited. Emerging biological and physiological markers have the potential to improve our ability to select those infants who will benefit most from intervention. Biomarkers identified from work in proteomics, metabolomics and transcriptomics as well as physiological markers such as heart rate variability, EEG analysis and radiological imaging when combined with neuroprotective measures have the potential to improve outcome in HIE/NE. The aim of this review is to give an overview of the literature in regards to short and long-term outcome following perinatal asphyxia, and to discuss the prediction of this outcome in the early hours after birth when intervention is most crucial; looking at both currently available tools and introducing novel markers. PMID: 26862504 [PubMed]

Related Articles Integrating candidate metabolites and biochemical factors to elucidate the action mechanism of Xue-sai-tong injection based on (1)H NMR metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci. 2016 Feb 4; Authors: Jiang M, Zhao X, Wang L, Xu L, Zhang Y, Li Z Abstract A strategy of integrating candidate metabolites with crucial biochemical factors was proposed in this study to discover relevant biological functions for interpreting the action mechanism of Traditional Chinese Medicines (TCM). This approach was applied to Xue-Sai-Tong injection (XST) to reveal the action mechanism based on the metabolic response in an ischemia/reperfusion (I/R) rat model by analyzing NMR profile. Partial least squares discriminate analysis (PLS-DA) was used to compare metabolic profiles of serum samples and revealed nine metabolites altered by I/R injury could be restored to normal status (sham-operated group) under the therapy of XST. The pathway enrichment analysis suggested the metabolic changes were mainly involved in pyruvate metabolism, glycolysis, and citrate cycle. The functional roles of the candidate metabolites were further identified by Pearson correlation analysis with the key biochemical factors in serum. The results indicated pyruvate, succinate, acetate and lysine showed significant associations with the oxidative stress factors. Elevated level of pyruvate was found as an essential metabolic response for the major effect of XST against I/R injury by enhancing glycolysis and overcoming the induced reactive oxygen species (ROS). This metabolomics approach provides a better understanding of the mechanisms of TCM and helps to develop a holistic view of TCM efficacy. PMID: 26862062 [PubMed - as supplied by publisher]

Related Articles Metabolite profiles of diabetes incidence and intervention response in the Diabetes Prevention Program. Diabetes. 2016 Feb 9; Authors: Walford GA, Ma Y, Clish C, Florez JC, Wang TJ, Gerszten RE, Diabetes Prevention Program Research Group Abstract Identifying novel biomarkers of type 2 diabetes risk may improve prediction and prevention among individuals at high risk of the disease and elucidate new biological pathways relevant to diabetes development. We performed plasma metabolite profiling in the Diabetes Prevention Program (DPP), a completed trial that randomized high-risk individuals to lifestyle, metformin, or placebo interventions. Previously reported markers, branched chain and aromatic amino acids and glutamine/glutamate, were associated with incident diabetes (P<0.05 for all), but these associations were attenuated upon adjustment for clinical and biochemical measures. By contrast, baseline levels of betaine (also known as glycine betaine, HR 0.84 per SD log metabolite level, P=0.02) and three other metabolites were associated with incident diabetes even after adjustment. Moreover, betaine was increased by the lifestyle intervention, which was the most effective approach to preventing diabetes, and increases in betaine at 2 years were also associated with lower diabetes incidence (P=0.01). Our findings indicate betaine is a marker of diabetes risk among high-risk individuals both at baseline and during preventive interventions, and complement animal models demonstrating a direct role for betaine in modulating metabolic health. PMID: 26861782 [PubMed - as supplied by publisher]

Related Articles Random Sample Consensus combined with Partial Least Squares regression (RANSAC-PLS) for microbial metabolomics data mining and phenotype improvement. J Biosci Bioeng. 2016 Feb 6; Authors: Teoh ST, Kitamura M, Nakayama Y, Putri S, Mukai Y, Fukusaki E Abstract In recent years, the advent of high-throughput omics technology has made possible a new class of strain engineering approaches, based on identification of possible gene targets for phenotype improvement from omic-level comparison of different strains or growth conditions. Metabolomics, with its focus on the omic level closest to the phenotype, lends itself naturally to this semi-rational methodology. When a quantitative phenotype such as growth rate under stress is considered, regression modeling using multivariate techniques such as partial least squares (PLS) is often used to identify metabolites correlated with the target phenotype. However, linear modeling techniques such as PLS require a consistent metabolite-phenotype trend across the samples, which may not be the case when outliers or multiple conflicting trends are present in the data. To address this, we proposed a data-mining strategy that utilizes random sample consensus (RANSAC) to select subsets of samples with consistent trends for construction of better regression models. By applying a combination of RANSAC and PLS (RANSAC-PLS) to a dataset from a previous study (gas chromatography/mass spectrometry metabolomics data and 1-butanol tolerance of 19 yeast mutant strains), new metabolites were indicated to be correlated with tolerance within certain subsets of the samples. The relevance of these metabolites to 1-butanol tolerance were then validated from single-deletion strains of corresponding metabolic genes. The results showed that RANSAC-PLS is a promising strategy to identify unique metabolites that provide additional hints for phenotype improvement, which could not be detected by traditional PLS modeling using the entire dataset. PMID: 26861498 [PubMed - as supplied by publisher]

Related Articles Identification of Conserved and Diverse Metabolic Shifts during Rice Grain Development. Sci Rep. 2016;6:20942 Authors: Hu C, Tohge T, Chan SA, Song Y, Rao J, Cui B, Lin H, Wang L, Fernie AR, Zhang D, Shi J Abstract Seed development dedicates to reserve synthesis and accumulation and uncovering its genetic and biochemical mechanisms has been a major research focus. Although proteomic and transcriptomic analyses revealed dynamic changes of genes and enzymes involved, the information regarding concomitant metabolic changes is missing. Here we investigated the dynamic metabolic changes along the rice grain development of two japonica and two indica cultivars using non-targeted metabolomics approach, in which we successfully identified 214 metabolites. Statistical analyses revealed both cultivar and developmental stage dependent metabolic changes in rice grains. Generally, the stage specific metabolic kinetics corresponded well to the physiological status of the developing grains, and metabolic changes in developing rice grain are similar to those of dicot Arabidopsis and tomato at reserve accumulation stage but are different from those of dicots at seed desiccation stage. The remarkable difference in metabolite abundances between japonica and indica rice grain was observed at the reserve accumulation stage. Metabolite-metabolite correlation analysis uncovered potential new pathways for several metabolites. Taken together, this study uncovered both conserved and diverse development associated metabolic kinetics of rice grains, which facilitates further study to explore fundamental questions regarding the evolution of seed metabolic capabilities as well as their potential applications in crop improvement. PMID: 26860358 [PubMed - in process]