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29 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 2015/04/22PubMed 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.

T-cell metabolism in autoimmune disease. Arthritis Res Ther. 2015;17(1):29 Authors: Yang Z, Matteson EL, Goronzy JJ, Weyand CM Abstract Cancer cells have long been known to fuel their pathogenic growth habits by sustaining a high glycolytic flux, first described almost 90 years ago as the so-called Warburg effect. Immune cells utilize a similar strategy to generate the energy carriers and metabolic intermediates they need to produce biomass and inflammatory mediators. Resting lymphocytes generate energy through oxidative phosphorylation and breakdown of fatty acids, and upon activation rapidly switch to aerobic glycolysis and low tricarboxylic acid flux. T cells in patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) have a disease-specific metabolic signature that may explain, at least in part, why they are dysfunctional. RA T cells are characterized by low adenosine triphosphate and lactate levels and increased availability of the cellular reductant NADPH. This anti-Warburg effect results from insufficient activity of the glycolytic enzyme phosphofructokinase and differentiates the metabolic status in RA T cells from those in cancer cells. Excess production of reactive oxygen species and a defect in lipid metabolism characterizes metabolic conditions in SLE T cells. Owing to increased production of the glycosphingolipids lactosylceramide, globotriaosylceramide and monosialotetrahexosylganglioside, SLE T cells change membrane raft formation and fail to phosphorylate pERK, yet hyperproliferate. Borrowing from cancer metabolomics, the metabolic modifications occurring in autoimmune disease are probably heterogeneous and context dependent. Variations of glucose, amino acid and lipid metabolism in different disease states may provide opportunities to develop biomarkers and exploit metabolic pathways as therapeutic targets. PMID: 25890351 [PubMed - as supplied by publisher]

Increased levels of choline metabolites are an early marker of docetaxel treatment response in BRCA1-mutated mouse mammary tumors: an assessment by ex vivo proton magnetic resonance spectroscopy. J Transl Med. 2015;13(1):114 Authors: van Asten JJ, Vettukattil R, Buckle T, Rottenberg S, van Leeuwen F, Bathen TF, Heerschap A Abstract BACKGROUND: Docetaxel is one of the most frequently used drugs to treat breast cancer. However, resistance or incomplete response to docetaxel is a major challenge. The aim of this study was to utilize MR metabolomics to identify potential biomarkers of docetaxel resistance in a mouse model for BRCA1-mutated breast cancer. METHODOLOGY: High resolution magic angle spinning (HRMAS) (1)H MR spectroscopy was performed on tissue samples obtained from docetaxel-sensitive or -resistant BRCA1-mutated mammary tumors in mice. Measurements were performed on samples obtained before treatment and at 1-2, 3-5 and 6-7 days after a 25 mg/kg dose of docetaxel. The MR spectra were analyzed by multivariate analysis, followed by analysis of the signals of individual compounds by peak fitting and integration with normalization to the integral of the creatine signal and of all signals between 2.9 and 3.6 ppm. RESULTS: The HRMAS spectra revealed significant metabolic differences between sensitive and resistant tissue samples. In particular choline metabolites were higher in resistant tumors by more than 50% with respect to creatine and by more than 30% with respect to all signals between 2.9 and 3.6 ppm. Shortly after treatment (1-2 days) the normalized choline metabolite levels were significantly increased by more than 30% in the sensitive group coinciding with the time of highest apoptotic activity induced by docetaxel. Thereafter, choline metabolites in these tumors returned towards pre-treatment levels. No change in choline compounds was observed in the resistant tumors over the whole time of investigation. CONCLUSIONS: Relative tissue concentrations of choline compounds are higher in docetaxel resistant than in sensitive BRCA1-mutated mouse mammary tumors, but in the first days after docetaxel treatment only in the sensitive tumors an increase of these compounds is observed. Thus both pre- and post-treatment tissue levels of choline compounds have potential to predict response to docetaxel treatment. PMID: 25890200 [PubMed - as supplied by publisher]

Fluxome study of Pseudomonas fluorescens reveals major reorganisation of carbon flux through central metabolic pathways in response to inactivation of the anti-sigma factor MucA. BMC Syst Biol. 2015;9(1):6 Authors: Lien SK, Niedenführ S, Sletta H, Nöh K, Bruheim P Abstract BACKGROUND: The bacterium Pseudomonas fluorescens switches to an alginate-producing phenotype when the pleiotropic anti-sigma factor MucA is inactivated. The inactivation is accompanied by an increased biomass yield on carbon sources when grown under nitrogen-limited chemostat conditions. A previous metabolome study showed significant changes in the intracellular metabolite concentrations, especially of the nucleotides, in mucA deletion mutants compared to the wild-type. In this study, the P. fluorescens SBW25 wild-type and an alginate non-producing mucA- ΔalgC double-knockout mutant are investigated through model-based (13)C-metabolic flux analysis ((13)C-MFA) to explore the physiological consequences of MucA inactivation at the metabolic flux level. Intracellular metabolite extracts from three carbon labelling experiments using fructose as the sole carbon source are analysed for (13)C-label incorporation in primary metabolites by gas and liquid chromatography tandem mass spectrometry. RESULTS: From mass isotopomer distribution datasets, absolute intracellular metabolic reaction rates for the wild type and the mutant are determined, revealing extensive reorganisation of carbon flux through central metabolic pathways in response to MucA inactivation. The carbon flux through the Entner-Doudoroff pathway was reduced in the mucA- ΔalgC mutant, while flux through the pentose phosphate pathway was increased. Our findings also indicated flexibility of the anaplerotic reactions through down-regulation of the pyruvate shunt in the mucA- ΔalgC mutant and up-regulation of the glyoxylate shunt. CONCLUSIONS: Absolute metabolic fluxes and metabolite levels give detailed, integrated insight into the physiology of this industrially, medically and agriculturally important bacterial species and suggest that the most efficient way of using a mucA- mutant as a cell factory for alginate production would be to use non-growing conditions and nitrogen deprivation. PMID: 25889900 [PubMed - as supplied by publisher]

EGFR/ERBB receptors differentially modulate sebaceous lipogenesis. FEBS Lett. 2015 Apr 15; Authors: Dahlhoff M, Camera E, Ludovici M, Picardo M, Müller U, Leonhardt H, Zouboulis CC, Schneider MR Abstract The roles of the epidermal growth factor receptor (EGFR) in sebaceous glands remain poorly explored. We show that human sebocytes express EGFR and lower levels of ERBB2 and ERBB3, all receptors being downregulated after the induction of lipid synthesis. Nile red staining showed that siRNA-mediated downregulation of EGFR or ERBB3 increases lipid accumulation, whereas ERBB2 downregulation has no effect. Spectrometry confirmed induction of triglycerides after EGFR or ERBB3 downregulation and revealed induction of cholesteryl esters after downregulation of EGFR, ERBB2 or ERBB3. Thus, EGFR/ERBB receptors differentially modulate sebaceous lipogenesis, a key feature of sebaceous gland physiology and of several skin diseases. PMID: 25889637 [PubMed - as supplied by publisher]

High-resolution metabolomics to discover potential parasite-specific biomarkers in a Plasmodium falciparum erythrocytic stage culture system. Malar J. 2015;14(1):122 Authors: Park YH, Shi YP, Liang B, Medriano CA, Jeon YH, Torres E, Uppal K, Slutsker L, Jones DP Abstract BACKGROUND: Current available malaria diagnostic methods each have some limitations to meet the need for real-time and large-scale screening of asymptomatic and low density malaria infection at community level. It was proposed that malaria parasite-specific low molecular-weight metabolites could be used as biomarkers for the development of a malaria diagnostic tool aimed to address this diagnostic challenge. In this study, high resolution metabolomics (HRM) was employed to identify malaria parasite-specific metabolites in Plasmodium falciparum in vitro culture samples. METHODS: Supernatants were collected at 12 hours interval from 3% haematocrit in vitro 48-hour time-course asynchronized culture system of P. falciparum. Liquid chromatography coupled with high resolution mass spectrometry was applied to discover potential parasite-specific metabolites in the cell culture supernatant. A metabolome-wide association study was performed to extract metabolites using Manhattan plot with false discovery rate (FDR) and hierarchical cluster analysis. The significant metabolites based on FDR cutoff were annotated using Metlin database. Standard curves were created using corresponding chemical compounds to accurately quantify potential Plasmodium-specific metabolites in culture supernatants. RESULTS: The number of significant metabolite features was 1025 in the supernatant of the Plasmodium infected culture based on Manhattan plot with FDR q=0.05. A two way hierarchical cluster analysis showed a clear segregation of the metabolic profile of parasite infected supernatant from non-infected supernatant at four time points during the 48 hour culture. Among the 1025 annotated metabolites, the intensities of four molecules were significantly increased with culture time suggesting a positive association between the quantity of these molecules and level of parasitaemia: i) 3-methylindole, a mosquito attractant, ii) succinylacetone, a haem biosynthesis inhibitor, iii) S-methyl-L-thiocitrulline, a nitric oxide synthase inhibitor, and iv) O-arachidonoyl glycidol, a fatty acid amide hydrolase inhibitor, The highest concentrations of 3-methylindole and succinylacetone were 178 ± 18.7 pmoles at 36 hours and 157±30.5 pmoles at 48 hours respectively in parasite infected supernatant. CONCLUSION: HRM with bioinformatics identified four potential parasite-specific metabolite biomarkers using in vitro culture supernatants. Further study in malaria infected human is needed to determine presence of the molecules and its relationship with parasite densities. PMID: 25889340 [PubMed - as supplied by publisher]

Helminth infections and type 2 diabetes: a cluster-randomized placebo controlled SUGARSPIN trial in Nangapanda, Flores, Indonesia. BMC Infect Dis. 2015;15(1):133 Authors: Tahapary DL, de Ruiter K, Martin I, van Lieshout L, Guigas B, Soewondo P, Djuardi Y, Wiria AE, Mayboroda OA, Houwing-Duistermaat JJ, Tasman H, Sartono E, Yazdanbakhsh M, Smit JW, Supali T Abstract BACKGROUND: Insulin resistance is a strong predictor of the development of type 2 diabetes mellitus. Chronic helminth infections might protect against insulin resistance via a caloric restriction state and indirectly via T-helper-2 polarization of the immune system. Therefore the elimination of helminths might remove this beneficial effect on insulin resistance. METHODS/DESIGN: To determine whether soil-transmitted helminth infections are associated with a better whole-body insulin sensitivity and whether this protection is reversible by anthelmintic treatment, a household-based cluster-randomized, double blind, placebo-controlled trial was conducted in the area of Nangapanda on Flores Island, Indonesia, an area endemic for soil-transmitted helminth infections. The trial incorporates three monthly treatment with albendazole or matching placebo for one year, whereby each treatment round consists of three consecutive days of supervised drug intake. The presence of soil-transmitted helminths will be evaluated in faeces using microscopy and/or PCR. The primary outcome of the study will be changes in insulin resistance as assessed by HOMA-IR, while the secondary outcomes will be changes in body mass index, waist circumference, fasting blood glucose, 2 h-glucose levels after oral glucose tolerance test, HbA1c, serum lipid levels, immunological parameters, and efficacy of anthelmintic treatment. DISCUSSION: The study will provide data on the effect of helminth infections on insulin resistance. It will assess the relationship between helminth infection status and immune responses as well as metabolic parameters, allowing the establishment of a link between inflammation and whole-body metabolic homeostasis. In addition, it will give information on anthelmintic treatment efficacy and effectiveness. TRIAL REGISTRATION: This study has been approved by the ethical committee of Faculty of Medicine Universitas Indonesia (ref: 549/H2.F1/ETIK/2013), and has been filed by the ethics committee of Leiden University Medical Center, clinical trial number: ISRCTN75636394 . The study is reported in accordance with the CONSORT guidelines for cluster-randomised trials. PMID: 25888525 [PubMed - as supplied by publisher]

IPO: a tool for automated optimization of XCMS parameters. BMC Bioinformatics. 2015 Apr 16;16(1):118 Authors: Libiseller G, Dvorzak M, Kleb U, Gander E, Eisenberg T, Madeo F, Neumann S, Trausinger G, Sinner F, Pieber T, Magnes C Abstract BACKGROUND: Untargeted metabolomics generates a huge amount of data. Software packages for automated data processing are crucial to successfully process these data. A variety of such software packages exist, but the outcome of data processing strongly depends on algorithm parameter settings. If they are not carefully chosen, suboptimal parameter settings can easily lead to biased results. Therefore, parameter settings also require optimization. Several parameter optimization approaches have already been proposed, but a software package for parameter optimization which is free of intricate experimental labeling steps, fast and widely applicable is still missing. RESULTS: We implemented the software package IPO ('Isotopologue Parameter Optimization') which is fast and free of labeling steps, and applicable to data from different kinds of samples and data from different methods of liquid chromatography - high resolution mass spectrometry and data from different instruments. IPO optimizes XCMS peak picking parameters by using natural, stable (13)C isotopic peaks to calculate a peak picking score. Retention time correction is optimized by minimizing relative retention time differences within peak groups. Grouping parameters are optimized by maximizing the number of peak groups that show one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiments, and the resulting scores are evaluated using response surface models. IPO was tested on three different data sets, each consisting of a training set and test set. IPO resulted in an increase of reliable groups (146% - 361%), a decrease of non-reliable groups (3% - 8%) and a decrease of the retention time deviation to one third. CONCLUSIONS: IPO was successfully applied to data derived from liquid chromatography coupled to high resolution mass spectrometry from three studies with different sample types and different chromatographic methods and devices. We were also able to show the potential of IPO to increase the reliability of metabolomics data. The source code is implemented in R, tested on Linux and Windows and it is freely available for download at https://github.com/glibiseller/IPO . The training sets and test sets can be downloaded from https://health.joanneum.at/IPO . PMID: 25888443 [PubMed - as supplied by publisher]

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction. BMC Bioinformatics. 2015;16(1):62 Authors: Dhanasekaran AR, Pearson JL, Ganesan B, Weimer BC Abstract BACKGROUND: Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism's genome as a database restricts metabolite identification to only those compounds that the organism can produce. RESULTS: To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment's MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis. CONCLUSIONS: Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome. PMID: 25887958 [PubMed - as supplied by publisher]

Human metabolic response to systemic inflammation: assessment of the concordance between experimental endotoxemia and clinical cases of sepsis/SIRS. Crit Care. 2015;19(1):71 Authors: Kamisoglu K, Haimovich B, Calvano SE, Coyle SM, Corbett SA, Langley RJ, Kingsmore SF, Androulakis IP Abstract INTRODUCTION: Two recent, independent, studies conducted novel metabolomics analyses relevant to human sepsis progression; one was a human model of endotoxin (lipopolysaccharide (LPS)) challenge (experimental endotoxemia) and the other was community acquired pneumonia and sepsis outcome diagnostic study (CAPSOD). The purpose of the present study was to assess the concordance of metabolic responses to LPS and community-acquired sepsis. METHODS: We tested the hypothesis that the patterns of metabolic response elicited by endotoxin would agree with those in clinical sepsis. Alterations in the plasma metabolome of the subjects challenged with LPS were compared with those of sepsis patients who had been stratified into two groups: sepsis patients with confirmed infection and non-infected patients who exhibited systemic inflammatory response syndrome (SIRS) criteria. Common metabolites between endotoxemia and both these groups were individually identified, together with their direction of change and functional classifications. RESULTS: Response to endotoxemia at the metabolome level elicited characteristics that agree well with those observed in sepsis patients despite the high degree of variability in the response of these patients. Moreover, some distinct features of SIRS have been identified. Upon stratification of sepsis patients based on 28-day survival, the direction of change in 21 of 23 metabolites was the same in endotoxemia and sepsis survival groups. CONCLUSIONS: The observed concordance in plasma metabolomes of LPS-treated subjects and sepsis survivors strengthens the relevance of endotoxemia to clinical research as a physiological model of community-acquired sepsis, and gives valuable insights into the metabolic changes that constitute a homeostatic response. Furthermore, recapitulation of metabolic differences between sepsis non-survivors and survivors in LPS-treated subjects can enable further research on the development and assessment of rational clinical therapies to prevent sepsis mortality. Compared with earlier studies which focused exclusively on comparing transcriptional dynamics, the distinct metabolomic responses to systemic inflammation with or without confirmed infection, suggest that the metabolome is much better at differentiating these pathophysiologies. Finally, the metabolic changes in the recovering patients shift towards the LPS-induced response pattern strengthening the notion that the metabolic, as well as transcriptional responses, characteristic to the endotoxemia model represent necessary and "healthy" responses to infectious stimuli. PMID: 25887472 [PubMed - as supplied by publisher]

Dysbiotic gut microbiota causes transmissible Crohn's disease-like ileitis independent of failure in antimicrobial defence. Gut. 2015 Apr 17; Authors: Schaubeck M, Clavel T, Calasan J, Lagkouvardos I, Haange SB, Jehmlich N, Basic M, Dupont A, Hornef M, Bergen MV, Bleich A, Haller D Abstract OBJECTIVES: Dysbiosis of the intestinal microbiota is associated with Crohn's disease (CD). Functional evidence for a causal role of bacteria in the development of chronic small intestinal inflammation is lacking. Similar to human pathology, TNF(deltaARE) mice develop a tumour necrosis factor (TNF)-driven CD-like transmural inflammation with predominant ileal involvement. DESIGN: Heterozygous TNF(deltaARE) mice and wildtype (WT) littermates were housed under conventional (CONV), specific pathogen-free (SPF) and germ-free (GF) conditions. Microbial communities were analysed by high-throughput 16S ribosomal RNA gene sequencing. Metaproteomes were measured using LC-MS. Temporal and spatial resolution of disease development was followed after antibiotic treatment and transfer of microbial communities into GF mice. Granulocyte infiltration and Paneth cell function was assessed by immunofluorescence and gene expression analysis. RESULTS: GF-TNF(deltaARE) mice were free of inflammation in the gut and antibiotic treatment of CONV-TNF(deltaARE) mice attenuated ileitis but not colitis, demonstrating that disease severity and location are microbiota-dependent. SPF-TNF(deltaARE) mice developed distinct ileitis-phenotypes associated with gradual loss of antimicrobial defence. 16S analysis and metaproteomics revealed specific compositional and functional alterations of bacterial communities in inflamed mice. Transplantation of disease-associated but not healthy microbiota transmitted CD-like ileitis to GF-TNF(deltaARE) recipients and triggered loss of lysozyme and cryptdin-2 expression. Monoassociation of GF-TNF(deltaARE) mice with the human CD-related Escherichia coli LF82 did not induce ileitis. CONCLUSIONS: We provide clear experimental evidence for the causal role of gut bacterial dysbiosis in the development of chronic ileal inflammation with subsequent failure of Paneth cell function. PMID: 25887379 [PubMed - as supplied by publisher]

Kernel approaches for differential expression analysis of mass spectrometry-based metabolomics data. BMC Bioinformatics. 2015;16(1):77 Authors: Zhan X, Patterson AD, Ghosh D Abstract BACKGROUND: Data generated from metabolomics experiments are different from other types of "-omics" data. For example, a common phenomenon in mass spectrometry (MS)-based metabolomics data is that the data matrix frequently contains missing values, which complicates some quantitative analyses. One way to tackle this problem is to treat them as absent. Hence there are two types of information that are available in metabolomics data: presence/absence of a metabolite and a quantitative value of the abundance level of a metabolite if it is present. Combining these two layers of information poses challenges to the application of traditional statistical approaches in differential expression analysis. RESULTS: In this article, we propose a novel kernel-based score test for the metabolomics differential expression analysis. In order to simultaneously capture both the continuous pattern and discrete pattern in metabolomics data, two new kinds of kernels are designed. One is the distance-based kernel and the other is the stratified kernel. While we initially describe the procedures in the case of single-metabolite analysis, we extend the methods to handle metabolite sets as well. CONCLUSIONS: Evaluation based on both simulated data and real data from a liver cancer metabolomics study indicates that our kernel method has a better performance than some existing alternatives. An implementation of the proposed kernel method in the R statistical computing environment is available at http://works.bepress.com/debashis_ghosh/60/ . PMID: 25887233 [PubMed - as supplied by publisher]

Proteomic and metabolomic analysis of the carotenogenic yeast Xanthophyllomyces dendrorhous using different carbon sources. BMC Genomics. 2015 Apr 12;16(1):289 Authors: Martinez-Moya P, Niehaus K, Alcaíno J, Baeza M, Cifuentes V Abstract BACKGROUND: Astaxanthin is a potent antioxidant with increasing biotechnological interest. In Xanthophyllomyces dendrorhous, a natural source of this pigment, carotenogenesis is a complex process regulated through several mechanisms, including the carbon source. X. dendrorhous produces more astaxanthin when grown on a non-fermentable carbon source, while decreased astaxanthin production is observed in the presence of high glucose concentrations. In the present study, we used a comparative proteomic and metabolomic analysis to characterize the yeast response when cultured in minimal medium supplemented with glucose (fermentable) or succinate (non-fermentable). RESULTS: A total of 329 proteins were identified from the proteomic profiles, and most of these proteins were associated with carotenogenesis, lipid and carbohydrate metabolism, and redox and stress responses. The metabolite profiles revealed 92 metabolites primarily associated with glycolysis, the tricarboxylic acid cycle, amino acids, organic acids, sugars and phosphates. We determined the abundance of proteins and metabolites of the central pathways of yeast metabolism and examined the influence of these molecules on carotenogenesis. Similar to previous proteomic-stress response studies, we observed modulation of abundance from several redox, stress response, carbohydrate and lipid enzymes. Additionally, the accumulation of trehalose, absence of key ROS response enzymes, an increased abundance of the metabolites of the pentose phosphate pathway and tricarboxylic acid cycle suggested an association between the accumulation of astaxanthin and oxidative stress in the yeast. Moreover, we observed the increased abundance of late carotenogenesis enzymes during astaxanthin accumulation under succinate growth conditions. CONCLUSIONS: The use of succinate as a carbon source in X. dendrorhous cultures increases the availability of acetyl-CoA for the astaxanthin production compared with glucose, likely reflecting the positive regulation of metabolic enzymes of the tricarboxylic acid and glyoxylate cycles. The high metabolite level generated in this pathway could increase the cellular respiration rate, producing reactive oxygen species, which induces carotenogenesis. PMID: 25887121 [PubMed - as supplied by publisher]

Related Articles Quorum-Sensing Dysbiotic Shifts in the HIV-Infected Oral Metabiome. PLoS One. 2015;10(4):e0123880 Authors: Brown RE, Ghannoum MA, Mukherjee PK, Gillevet PM, Sikaroodi M Abstract We implemented a Systems Biology approach using Correlation Difference Probability Network (CDPN) analysis to provide insights into the statistically significant functional differences between HIV-infected patients and uninfected individuals. The analysis correlates bacterial microbiome ("bacteriome"), fungal microbiome ("mycobiome"), and metabolome data to model the underlying biological processes comprising the Human Oral Metabiome. CDPN highlights the taxa-metabolite-taxa differences between the cohorts that frequently capture quorum-sensing modifications that reflect communication disruptions in the dysbiotic HIV cohort. The results also highlight the significant role of cyclic mono and dipeptides as quorum-sensing (QS) mediators between oral bacteria and fungal genus. The developed CDPN approach allowed us to model the interactions of taxa and key metabolites, and hypothesize their possible contribution to the etiology of Oral Candidiasis (OC). PMID: 25886290 [PubMed - as supplied by publisher]

Related Articles Population pharmacokinetic modeling of the Qishe pill in three major traditional Chinese medicine-defined constitutional types of healthy Chinese subjects: study protocol for a randomized controlled trial. Trials. 2015;16(1):64 Authors: Sun YL, Hou T, Liu SF, Zhang ZL, Zhang N, Yao M, Yang L, Shi Q, Cui XJ, Wang YJ Abstract BACKGROUND: High incidences of neck pain morbidity are challenging in various situations for populations based on their demographic, physiological and pathological characteristics. Chinese proprietary herbal medicines, as Complementary and Alternative Medicine (CAM) products, are usually developed from well-established and long-standing recipes formulated as tablets or capsules. However, good quantification and strict standardization are still needed for implementation of individualized therapies. The Qishe pill was developed and has been used clinically since 2009. The Qishe pill's personalized medicine should be documented and administered to various patients according to the ancient TCM system, a classification of personalized constitution types, established to determine predisposition and prognosis to diseases as well as therapy and life-style administration. Therefore, we describe the population pharmacokinetic profile of the Qishe pill and compare its metabolic rate in the three major constitution types (Qi-Deficiency, Yin-Deficiency and Blood-Stasis) to address major challenges to individualized standardized TCM. METHODS/DESIGN: Healthy subjects (N = 108) selected based on constitutional types will be assessed, and standardized pharmacokinetic protocol will be used for assessing demographic, physiological, and pathological data. Laboratory biomarkers will be evaluated and blood samples collected for pharmacokinetics(PK) analysis and second-generation gene sequencing. In single-dose administrations, subjects in each constitutional type cohort (N = 36) will be randomly divided into three groups to receive different Qishe pill doses (3.75, 7.5 and 15 grams). Multiomics, including next generation sequencing, metabolomics, and proteomics, will complement the Qishe pill's multilevel assessment, with cytochrome P450 genes as targets. In a comparison with the general population, a systematic population pharmacokinetic (PopPK) model for the Qishe pill will be established and verified. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov, NCT02294448 .15 November 2014. PMID: 25885543 [PubMed - as supplied by publisher]

Related Articles MRM-Ion Pair Finder: a systematic approach to transform non-targeted mode to pseudo-targeted mode for metabolomics study based on liquid chromatography-mass spectrometry. Anal Chem. 2015 Apr 17; Authors: Luo P, Dai W, Yin P, Zeng Z, Kong H, Zhou L, Wang X, Chen S, Lu X, Xu G Abstract Pseudo-targeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from Q-TOF MS by information-dependent acquisition (IDA), then picks targeted ion-pair and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of pseudo-targeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS2 spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was firstly analyzed and the representative ion pairs were correctly picked out, then pooled serum samples were further studied and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer, 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudo-targeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries. PMID: 25884293 [PubMed - as supplied by publisher]

Related Articles Oxidized phosphatidylcholines suggest oxidative stress in patients with medium-chain acyl-CoA dehydrogenase deficiency. Talanta. 2015 Jul 1;139:62-6 Authors: Najdekr L, Gardlo A, Mádrová L, Friedecký D, Janečková H, Correa ES, Goodacre R, Adam T Abstract Inborn errors of metabolism encompass a large group of diseases caused by enzyme deficiencies and are therefore amenable to metabolomics investigations. Medium chain acyl-CoA dehydrogenase deficiency (MCADD) is a defect in β-oxidation of fatty acids, and is one of the most well understood disorders. We report here the use of liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics and targeted flow injection analysis-tandem mass spectrometry (FIA-TMS) that lead to discovery of novel compounds of oxidative stress. Dry blood spots of controls (n=25) and patient samples (n=25) were extracted by methanol/water (1/1, v/v) and these supernatants were analyzed by LC-MS method with detection by an Orbitrap Elite MS. Data were processed by XCMS and CAMERA followed by dimension reduction methods. Patients were clearly distinguished from controls in PCA. S-plot derived from OPLS-DA indicated that medium-chain acylcarnitines (octanoyl, decenoyl and decanoyl carnitines) as well as three phosphatidylcholines (PC(16:0,9:0(COOH))), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were important metabolites for differentiation between patients and healthy controls. In order to biologically validate these discriminatory molecules as indicators for oxidative stress, a second cohort of individuals were analyzed, including MCADD (n=25) and control (n=250) samples. These were measured by a modified newborn screening method using FIA-TMS (API 4000) in MRM mode. Calculated p-values for PC(16:0,9:0(COOH)), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were 1.927×10(-14), 2.391×10(-15) and 3.354×10(-15) respectively. These elevated oxidized phospholipids indeed show an increased presence of oxidative stress in MCADD patients as one of the pathophysiological mechanisms of the disease. PMID: 25882409 [PubMed - in process]

Related Articles A gas chromatography-mass spectrometry based study on serum metabolomics in rats chronically poisoned with hydrogen sulfide. J Forensic Leg Med. 2015 May;32:59-63 Authors: Deng M, Zhang M, Huang X, Ma J, Hu L, Lin G, Wang X Abstract Hydrogen sulfide poisoning is a common occupational hazard, whose mortality and incidence rates are first and second, respectively, among occupational poisoning incidents in China. The main target organs of its toxicity are in the central nervous system and respiratory system. However, there are currently no specific direct tests that can be used to diagnose poisoned patients. In this study, we developed a serum metabonomic method using orthogonal partial least squares-discriminate analysis (OPLS-DA), based on gas chromatography-mass spectrometry (GC/MS) to evaluate the effect of chronic poisoning by hydrogen sulfide in rats. The OPLS-DA data demonstrated that the model group (n = 60) differed significantly from the control group (n = 30), suggesting that the metabolic profiles of the two groups are markedly different. Alterations in the levels of some metabolites such as citrate, galactose, lactate, mannose, inositol, urea, phosphate, alanine and valine were detected by OPLS-DA analysis. We observed changes in metabolic pathways including lipid metabolism, energy metabolism and amino metabolism in the model group. Our results indicate that GC/MS-based metabonomic methods may provide novel detection means for chronic hydrogen sulfide poisoning. PMID: 25882152 [PubMed - in process]

Related Articles Cardiomyopathy and Worsened Ischemic Heart Failure in SM22-α Cre-Mediated Neuropilin-1 Null Mice: Dysregulation of PGC1α and Mitochondrial Homeostasis. Arterioscler Thromb Vasc Biol. 2015 Apr 16; Authors: Wang Y, Cao Y, Yamada S, Thirunavukkarasu M, Nin V, Joshi M, Rishi MT, Bhattacharya S, Camacho-Pereira J, Sharma AK, Shameer K, Kocher JP, Sanchez JA, Wang E, Hoeppner LH, Dutta SK, Leof EB, Shah V, Claffey KP, Chini E, Simons M, Terzic A, Maulik N, Mukhopadhyay D Abstract OBJECTIVE: Neuropilin-1 (NRP-1) is a multidomain membrane receptor involved in angiogenesis and development of neuronal circuits, however, the role of NRP-1 in cardiovascular pathophysiology remains elusive. APPROACH AND RESULTS: In this study, we first observed that deletion of NRP-1 induced peroxisome proliferator-activated receptor γ coactivator 1α in cardiomyocytes and vascular smooth muscle cells, which was accompanied by dysregulated cardiac mitochondrial accumulation and induction of cardiac hypertrophy- and stress-related markers. To investigate the role of NRP-1 in vivo, we generated mice lacking Nrp-1 in cardiomyocytes and vascular smooth muscle cells (SM22-α-Nrp-1 KO), which exhibited decreased survival rates, developed cardiomyopathy, and aggravated ischemia-induced heart failure. Mechanistically, we found that NRP-1 specifically controls peroxisome proliferator-activated receptor γ coactivator 1 α and peroxisome proliferator-activated receptor γ in cardiomyocytes through crosstalk with Notch1 and Smad2 signaling pathways, respectively. Moreover, SM22-α-Nrp-1 KO mice exhibited impaired physical activities and altered metabolite levels in serum, liver, and adipose tissues, as demonstrated by global metabolic profiling analysis. CONCLUSIONS: Our findings provide new insights into the cardioprotective role of NRP-1 and its influence on global metabolism. PMID: 25882068 [PubMed - as supplied by publisher]

Related Articles Metabolite profiles in heart failure: looking for unique signatures in a heterogeneous syndrome. J Am Coll Cardiol. 2015 Apr 21;65(15):1521-4 Authors: Wang TJ, Gupta DK PMID: 25881933 [PubMed - in process]