PubMed

Chemical Assignment of Structural Isomers of Sulfur-Containing Metabolites in Garlic by Liquid Chromatography-Fourier Transform Ion Cyclotron Resonance-Mass Spectrometry. J Nutr. 2016 Jan 13; Authors: Nakabayashi R, Sawada Y, Aoyagi M, Yamada Y, Hirai MY, Sakurai T, Kamoi T, Rowan DD, Saito K Abstract BACKGROUND: The chemical assignment of metabolites is crucial to understanding the relation between food composition and biological activity. OBJECTIVE: This study was designed to detect and chemically assign sulfur-containing metabolites by using LC-Fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) in Allium plants. METHODS: Ultrahigh resolution (>250,000 full width at half-maximum) and mass accuracy (<1 mDa) by FTICR-MS allowed us to distinguish ions containing sulfur isotopes ((32)S and (34)S). RESULTS: Putative 69 S-containing monoisotopic ions (S-ions) were extracted from the metabolome data of onion (Allium cepa), green onion (Allium fistulosum), and garlic (Allium sativum) on the basis of theoretical mass differences between (32)S-ions and their (34)S-substituted counterparts and on the natural abundance of (34)S. Eight S-ions were chemically assigned by using the reference data according to the guidelines of the Metabolomics Standards Initiative. Three ions detected in garlic were assigned as derived from the isomers γ-glutamyl-S-1-propenylcysteine and γ-glutamyl-S-2-propenylcysteine and as S-2-propenylmercaptoglutathione on the basis of differences in key product ions identified in reference tandem MS spectra. CONCLUSION: The ability to discriminate between such geometric isomers will be extremely useful for the chemical assignment of unknown metabolites in MS-based metabolomics. PMID: 26764333 [PubMed - as supplied by publisher]

Rapid comparison of metabolites in humans and rats of different sexes using untargeted UPLC-TOFMS and an in-house software platform. Eur J Mass Spectrom (Chichester, Eng). 2015;21(6):801-21 Authors: Liang Q, Xu W, Hong Q, Xiao C, Yang L, Ma Z, Wang Y, Tan H, Tang X, Gao Y Abstract Metabolite differences between sexes have rarely been observed in a global manner, but it has recently been made possible by the advancement in metabolomics techniques. In this study, untargeted ultraperformance liquid chromatography coupled to time-of-flight mass spectrometry and an in-house software platform were used for a rapid comparison of sex differences in urinary metabolites in humans and in urinary and serum metabolites in Sprague Dawley (SD) rats. In addition, the species differences of urinary metabolites between humans and SD rats were also observed. Principle component analysis showed that all the observed metabolite sex differences were more distinct in SD rats than in humans, indicating that the sex differences of human urinary metabolites is small compared with that of SD rats. In SD rats, the observed metabolite sex differences were more distinct in urine than in serum, indicating the importance of urine analysis for metabolomics studies. The species differences in the urinary metabolites of humans and SD rats were much more distinct than any of the observed sex differences. Many sex- and species-related markers were discovered and putatively identified. In both humans and SD rats, steroid metabolites appeared to constitute a major sex difference in urinary metabolites. This provides new proof of the special importance of steroid metabolites in sex differences from an untargeted metabolomics investigation, which is rare for sex differences. Contrary patterns involving adrenocortical activity appeared to exist between rodents and humans, which agrees with previous reports. In the serum metabolites of SD rats, sex differences in ascorbic acid or its isomer and pantothenic acid or its isomer, but not in steroid metabolites, were prominent. Human-specific α-N- phenylacetyl-l-glutamine and androsterone glucuronide were among the putative identities of the markers discriminating humans and SD rats. This study demonstrated the feasibility of an in-house software platform and provides metabolite-related information on sex and species differences. PMID: 26764310 [PubMed - in process]

Variable selection for binary classification using error rate p-values applied to metabolomics data. BMC Bioinformatics. 2016;17(1):33 Authors: van Reenen M, Reinecke CJ, Westerhuis JA, Venter JH Abstract BACKGROUND: Metabolomics datasets are often high-dimensional though only a limited number of variables are expected to be informative given a specific research question. The important task of selecting informative variables can therefore become complex. In this paper we look at discriminating between two groups. Two tasks need to be performed: (i) finding variables which differ between the two groups; and (ii) determining how the selected variables can be used to classify new subjects. We introduce an approach using minimum classification error rates as test statistics to find discriminatory and therefore informative variables. The thresholds resulting in the minimum error rates can be used to classify new subjects. This approach transforms error rates into p-values and is referred to as ERp. RESULTS: We show that non-parametric hypothesis testing, based on minimum classification error rates as test statistics, can find statistically significantly shifted variables. The discriminatory ability of variables becomes more apparent when error rates are evaluated based on their corresponding p-values, as relatively high error rates can still be statistically significant. ERp can handle unequal and small group sizes, as well as account for the cost of misclassification. ERp retains (if known) or reveals (if unknown) the shift direction, aiding in biological interpretation. The threshold resulting in the minimum error rate can immediately be used to classify new subjects. We use NMR generated metabolomics data to illustrate how ERp is able to discriminate subjects diagnosed with Mycobacterium tuberculosis infected meningitis from a control group. The list of discriminatory variables produced by ERp contains all biologically relevant variables with appropriate shift directions discussed in the original paper from which this data is taken. CONCLUSIONS: ERp performs variable selection and classification, is non-parametric and aids biological interpretation while handling unequal group sizes and misclassification costs. All this is achieved by a single approach which is easy to perform and interpret. ERp has the potential to address many other characteristics of metabolomics data. Future research aims to extend ERp to account for a large proportion of observations below the detection limit, as well as expand on interactions between variables. PMID: 26763892 [PubMed - in process]

Potential of monitoring isotopologues by quantitative gas chromatography with time-of-flight mass spectrometry for metabolomic assay. J Sep Sci. 2016 Jan 13; Authors: Wang Y, Hu H, Su Y, Zhang F, Guo Y Abstract Because of the extreme complexity of metabolomic samples, the effectiveness of quantitative gas chromatography with time-of-flight mass spectrometry depends substantially on the expanding of the linear dynamic range. Facing the existent of numerous saturated detector signals, a data processing method based on monitoring isotopologues has been developed. The monoisotopic ion kept the high mass spectrometry sensitivity and the less abundant isotopologue ions extended the linear dynamic range. The alternative method was proved to extend the linear dynamic range to five orders of magnitude successfully and overcome the quantitative problems induced by the ion detector saturation. Finally, to validate the applicability, the method was applied to a metabolomic assay of Alzheimer's disease. Comparing with the traditional monoisotopic method, the use of monitoring isotopologues helped to discover additional eight metabolites with significant difference and conducted a more reliable principal component analysis as well. The results demonstrated that monitoring isotopologues in quantitative gas chromatography with time-of-flight mass spectrometry could improve the authenticity of metabolomic analysis. This article is protected by copyright. All rights reserved. PMID: 26763370 [PubMed - as supplied by publisher]

Sample normalization methods in quantitative metabolomics. J Chromatogr A. 2015 Dec 10; Authors: Wu Y, Li L Abstract To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. PMID: 26763302 [PubMed - as supplied by publisher]

Related Articles Comprehensive Metabolomic, Lipidomic and Microscopic Profiling of Yarrowia lipolytica during Lipid Accumulation Identifies Targets for Increased Lipogenesis. PLoS One. 2015;10(4):e0123188 Authors: Pomraning KR, Wei S, Karagiosis SA, Kim YM, Dohnalkova AC, Arey BW, Bredeweg EL, Orr G, Metz TO, Baker SE Abstract Yarrowia lipolytica is an oleaginous ascomycete yeast that accumulates large amounts of lipids and has potential as a biofuel producing organism. Despite a growing scientific literature focused on lipid production by Y. lipolytica, there remain significant knowledge gaps regarding the key biological processes involved. We applied a combination of metabolomic and lipidomic profiling approaches as well as microscopic techniques to identify and characterize the key pathways involved in de novo lipid accumulation from glucose in batch cultured, wild-type Y. lipolytica. We found that lipids accumulated rapidly and peaked at 48 hours during the five day experiment, concurrent with a shift in amino acid metabolism. We also report that exhaustion of extracellular sugars coincided with thickening of the cell wall, suggesting that genes involved in cell wall biogenesis may be a useful target for improving the efficiency of lipid producing yeast strains. PMID: 25905710 [PubMed - indexed for MEDLINE]

Related Articles Metabolic profiling analysis of berberine, palmatine, jatrorrhizine, coptisine and epiberberine in zebrafish by ultra-high performance liquid chromatography coupled with LTQ Orbitrap mass spectrometer. Xenobiotica. 2015 Apr;45(4):302-11 Authors: Li Y, Wang H, Si N, Ren W, Han L, Xin S, Zuo R, Wei X, Yang J, Zhao H, Bian B Abstract 1. Zebrafish has been used in metabolic study of drugs as a powerful tool in recent years. In this study, we make a feasible metabolism investigation of five protoberberine alkaloids (PBAs) applied in zebrafish model for the first time, including berberine (BBR), palmatine (PAL), jatrorrhizine (JAT), coptisine (COP) and epiberberine (EBBR). 2. After exposure for 24 hours, 19 metabolites were identified by LTQ Orbitrap mass spectrometer, including 9 phase I metabolites and 10 phase II metabolites. Demethylation, hydroxylation, sulfation and glucuronidation were the major metabolic transformation of PBAs in zebrafish, which were similar to mammals. Compared with reported literatures, BBR and JAT showed high consistency between human and zebrafish in metabolic pathways. 3. To our knowledge, this is the first time to study in vivo metabolism of COP, which provides useful information to other researchers. 4. This study indicated that zebrafish model is feasible and reasonable to predict the metabolism of PBAs. It showed great potential for developing a novel and rapid method for predicting the metabolism of trace compounds of botanical drugs, with the advantages of lower cost, higher performance and easier set up. PMID: 25369727 [PubMed - indexed for MEDLINE]

Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A. Oncotarget. 2015 Dec 29; Authors: Rohwer N, Bindel F, Grimm C, Lin SJ, Wappler J, Klinger B, Blüthgen N, Du Bois I, Schmeck B, Lehrach H, de Graauw M, Goncalves E, Saez-Rodriguez J, Tan P, Grabsch HI, Prigione A, Kempa S, Cramer T Abstract Despite the approval of numerous molecular targeted drugs, long-term antiproliferative efficacy is rarely achieved and therapy resistance remains a central obstacle of cancer care. Combined inhibition of multiple cancer-driving pathways promises to improve antiproliferative efficacy. HIF-1 is a driver of gastric cancer and considered to be an attractive target for therapy. We noted that gastric cancer cells are able to functionally compensate the stable loss of HIF-1α. Via transcriptomics we identified a group of upregulated genes in HIF-1α-deficient cells and hypothesized that these genes confer survival upon HIF-1α loss. Strikingly, simultaneous knock-down of HIF-1α and Annexin A1 (ANXA1), one of the identified genes, resulted in complete cessation of proliferation. Using stable isotope-resolved metabolomics, oxidative and reductive glutamine metabolism was found to be significantly impaired in HIF-1α/ANXA1-deficient cells, potentially explaining the proliferation defect. In summary, we present a conceptually novel application of stable gene inactivation enabling in-depth deconstruction of resistance mechanisms. In theory, this experimental approach is applicable to any cancer-driving gene or pathway and promises to identify various new targets for combination therapies. PMID: 26760764 [PubMed - as supplied by publisher]

The choice of amniotic fluid in metabolomics for the monitoring of fetus health. Expert Rev Mol Diagn. 2016 Jan 13; Authors: Palmas F, Fattuoni C, Noto A, Barberini L, Dessì A, Fanos V Abstract Amniotic fluid (AF) is a biological fluid in which metabolite transport is regulated by the placenta, the permeable skin, fetal lung egress and gastric fluid. During pregnancy, the composition of AF changes from similar to the interstitial fluid of the mother, to a more complex system, influenced by the fetus's urine. Since AF reflects the mother's and the fetus's health status at the same time, it may be an important diagnostic tool for a wider spectrum of clinical conditions. Indeed, the metabolic characterization of AF in relation to pathological occurrences may lead to the discovery of new biomarkers for a better clinical practice. For this reason, metabolomics may be the most suitable strategy for this task. In this review, research works on metabolomic AF analysis are discussed according to the morbidity of interest, being preterm birth/labor, gestational age and diabetes and fetal malformations, along with a number of other important studies. PMID: 26760526 [PubMed - as supplied by publisher]

LC-MS based metabolomics discovers purine endogenous associations with low dose salbutamol in urine collected for anti-doping tests. Anal Chem. 2016 Jan 13; Authors: Wang Y, Caldwell RT, Cowan DA, Legido-Quigley C Abstract Current anti-doping analytical methods are tailored mainly to the targeting of known drugs and endogenous molecules. This causes difficulties in rapidly reacting to emerging threats such as designer drugs, biological therapeutic agents and technologies. Biomarkers are considered as a promising approach for the fight against these threats to sport. The main purpose of this study was to find surrogate biomarkers induced by the intake of small amounts of the model compound salbutamol and explore a sensitive approach to help screen for possible drug misuse. Urine samples (91) from athletes with detectable salbutamol (30) and negative samples (61) were analyzed using a UHPLC-MS. A third group (30) was created by spiking salbutamol into negative samples to eliminate confounding effects. Data were then analysed in XCMS to extract metabolic features. Orthogonal Partial Least Squares - Discriminant Analysis was performed to select features correlated with detectable salbutamol (pcorr >0.5) and ROC analysis was performed to measure the predictive potential of the markers. Univariate analysis including Mann-Whitney U test and Spearman's correlation was conducted on selected markers. A total of 7,000 metabolic features were parsed, one feature identified as hypoxanthine increased with salbutamol (p <0.001). The ROC curve of hypoxanthine returned an AUC of 0.79 (p <0.001). Correlation with salbutamol (r=0.415, p <0.01, Spearman's correlation) showed hypoxanthine and purine metabolism have association to salbutamol administration. This surrogate discovery approach needs further PK studies but in the meantime can be used as an intelligence-based complementary approach for targeting of athletes to be further tested. PMID: 26760048 [PubMed - as supplied by publisher]

Related Articles CD47 Receptor Globally Regulates Metabolic Pathways That Control Resistance to Ionizing Radiation. J Biol Chem. 2015 Oct 9;290(41):24858-74 Authors: Miller TW, Soto-Pantoja DR, Schwartz AL, Sipes JM, DeGraff WG, Ridnour LA, Wink DA, Roberts DD Abstract Modulating tissue responses to stress is an important therapeutic objective. Oxidative and genotoxic stresses caused by ionizing radiation are detrimental to healthy tissues but beneficial for treatment of cancer. CD47 is a signaling receptor for thrombospondin-1 and an attractive therapeutic target because blocking CD47 signaling protects normal tissues while sensitizing tumors to ionizing radiation. Here we utilized a metabolomic approach to define molecular mechanisms underlying this radioprotective activity. CD47-deficient cells and cd47-null mice exhibited global advantages in preserving metabolite levels after irradiation. Metabolic pathways required for controlling oxidative stress and mediating DNA repair were enhanced. Some cellular energetics pathways differed basally in CD47-deficient cells, and the global declines in the glycolytic and tricarboxylic acid cycle metabolites characteristic of normal cell and tissue responses to irradiation were prevented in the absence of CD47. Thus, CD47 mediates signaling from the extracellular matrix that coordinately regulates basal metabolism and cytoprotective responses to radiation injury. PMID: 26311851 [PubMed - indexed for MEDLINE]

Related Articles Application of GC/MS-based metabonomic profiling in studying the therapeutic effects of Huangbai-Zhimu herb-pair (HZ) extract on streptozotocin-induced type 2 diabetes in mice. J Chromatogr B Analyt Technol Biomed Life Sci. 2015 Aug 1;997:96-104 Authors: Song L, Liu H, Wang Y, Wang Y, Liu J, Zhou Z, Chu H, Zhuang P, Zhang Y Abstract A protocol for metabolic profiling of mice urine was developed based on gas chromatograph-mass spectrometer (GC-MS) to explore metabolic state directly. The intra-day, inter-day, repeatability, and stability RSD for most endogenous compounds were less than 3%. Type 2 diabetic mellitus (T2DM) mice model was induced by high calorie diet combined with streptozocin. Urine from the control, T2DM and Huangbai-Zhimu herb-pair (HZ) treatment mice were enrolled in the subsequent study to show the usefulness of the method. OPLS-DA scores plots demonstrate that the cluster of T2DM mice is separated from that of control mice, while HZ-T2DM mice are located close to control mice, indicating that metabolic profiles of these HZ-T2DM mice are placed toward those of control group. The results illustrate that HZ treatment could lower the level of d-glucose, hexadecanoic acid, octadecanoic acid, propanoic acid, 3-hydroxybutyric acid, and 2,3-dihydroxybutanoic acid in urine of DM mice, meanwhile the results show that HZ treatment could ameliorate T2DM symptoms by intervening the fatty acid metabolism, starch and sucrose metabolism, and glyoxylate and dicarboxylate metabolism. This preliminary application indicated that the method is suitable and reliable for urine metabolic profiling. This study might explain the metabolic effects of T2DM and the mechanisms of action of HZ against T2DM. PMID: 26094210 [PubMed - indexed for MEDLINE]

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Related Articles Volatile Organic Compounds (VOC) as new biomarkers for colorectal cancer: a review. Colorectal Dis. 2016 Jan 11; Authors: Di Lena M, Porcelli F, Altomare DF Abstract AIM: The analysis of the volatile part of the metabolome (Volatile Organic Compounds (VOC)) present in the gas phase of excreted materials is a promising new research field for the identification of screening tools for several cancers, including colorectal cancer (CRC). The VOC signature can reflect the health status as a 'fingerprint', which can be modified in several diseases. Technical difficulties still limit the widespread use of VOC analysis in the clinical setting, but this approach has already been applied successfully in the diagnosis of CRC. The present study reviews the available data on VOC present in DEAR AUITHOR THE WORD 'HEADSPACE' IS NOT ENGLISH AS FAR AS I KNOW. IF YOU WANT TO INCLUDE A WORD THAT IS RECOGNISED THEN PLEASE LET ME KNOW. OTHERWISE I WILL REMOVE IT FROM THE TEXT. Headspace is the word used to identify "the gaseous constituents of a closed space above liquids or solid emitting and vapors measured using headspace gas chromatography" the headspace (the gaseous constituents of a closed space above a liquid or solid) of blood, urine, faeces and breath as a potential screening tool for CRC. METHOD: A systematic electronic literature search was conducted in PubMed, Scirus and Google using the keywords Metabolomic, Volatile Organic Compounds (VOC), Electronic-nose and Colorectal Cancer. Only articles published in English between 2000-2015 were selected and independently checked by two of the authors. RESULTS: Ten papers describing the reliability of VOC analysis in breath and faeces, blood and urine were selected, all indicating good reliability in detecting colorectal cancer. The use of different substrates and different analytical platforms has led to the identification of different patterns of VOC. CONCLUSION: The reliability of a metabolomic approach in CRC screening as a non-invasive biomarker is supported by this review despite several limitation due to the number of patients included in each study, the different analytical platforms and the biological material used and different VOCs identified This article is protected by copyright. All rights reserved. PMID: 26752703 [PubMed - as supplied by publisher]

Related Articles Metabolic Analysis of Medicinal Dendrobium officinale and Dendrobium huoshanense during Different Growth Years. PLoS One. 2016;11(1):e0146607 Authors: Jin Q, Jiao C, Sun S, Song C, Cai Y, Lin Y, Fan H, Zhu Y Abstract Metabolomics technology has enabled an important method for the identification and quality control of Traditional Chinese Medical materials. In this study, we isolated metabolites from cultivated Dendrobium officinale and Dendrobium huoshanense stems of different growth years in the methanol/water phase and identified them using gas chromatography coupled with mass spectrometry (GC-MS). First, a metabolomics technology platform for Dendrobium was constructed. The metabolites in the Dendrobium methanol/water phase were mainly sugars and glycosides, amino acids, organic acids, alcohols. D. officinale and D. huoshanense and their growth years were distinguished by cluster analysis in combination with multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Eleven metabolites that contributed significantly to this differentiation were subjected to t-tests (P<0.05) to identify biomarkers that discriminate between D. officinale and D. huoshanense, including sucrose, glucose, galactose, succinate, fructose, hexadecanoate, oleanitrile, myo-inositol, and glycerol. Metabolic profiling of the chemical compositions of Dendrobium species revealed that the polysaccharide content of D. huoshanense was higher than that of D. officinale, indicating that the D. huoshanense was of higher quality. Based on the accumulation of Dendrobium metabolites, the optimal harvest time for Dendrobium was in the third year. This initial metabolic profiling platform for Dendrobium provides an important foundation for the further study of secondary metabolites (pharmaceutical active ingredients) and metabolic pathways. PMID: 26752292 [PubMed - as supplied by publisher]

Related Articles Urinary Biomarkers of Brain Diseases. Genomics Proteomics Bioinformatics. 2016 Jan 2; Authors: An M, Gao Y Abstract Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome. PMID: 26751805 [PubMed - as supplied by publisher]

Related Articles Influence of weight reduction on blood levels of C-reactive protein, tumor necrosis factor-α, interleukin-6, and oxylipins in obese subjects. Prostaglandins Leukot Essent Fatty Acids. 2015 Dec 17; Authors: Möller K, Ostermann AI, Rund K, Thoms S, Blume C, Stahl F, Hahn A, Schebb NH, Schuchardt JP Abstract INTRODUCTION: Obesity is associated with inflammation and weight reduction has been shown to influence the inflammatory process. Besides classic inflammatory markers, oxidized polyunsaturated fatty acid (PUFA) metabolites (oxylipins) are potent mediators of inflammation. Little is known about endogenous levels of oxylipins, e.g. hydroxy, epoxy and dihydroxy FA in obese subjects with persistent low-grade inflammation. We aimed to evaluate levels of inflammatory markers and blood oxylipins in obese subjects before and after weight reduction. SUBJECTS AND METHODS: In the present study, 42 obese (BMI 32.7±0.22kg/m(2)) men and women were classified in groups according to high-sensitivity C-reactive protein (hsCRP) levels (no inflammation<1mg/L; low-grade inflammation≥3mg/L). Subjects underwent an intervention for eight weeks, which consisted of two phases: (1) week 1 and 2: total replacement of three meals by a formula diet and (2) six week partial formula diet (replacement of 1-2 meals). Blood samples were taken prior and post intervention for analysis of plasma protein levels of hsCRP, tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). Plasma Levels of free (unesterified) hydroxy, epoxy, and dihydroxy FAs as well as several prostanoids were analyzed in plasma by means of LC-MS-based targeted metabolomics. RESULTS: At baseline subjects with low-grade inflammation (hsCRP 8.95±1.39mg/L) showed significant higher levels of IL-6 (22.7±1.15ng/L) and TNF-α (17.4±0.75ng/L) compared to subjects with no inflammation (hsCRP: 0.69±0.05mg/L; IL-6: 15.9±1.18ng/L; TNF-α: 14.6±0.80ng/L). In both group's body weight was significantly reduced (p<0.001) after intervention (no inflammation group: -7.19±0.86kg, -7.3±0.89%, p<0.001; low-grade inflammation group: -6.78±0.87kg, -6.7±0.81%, p<0.001). Moreover, we observed significant decreases in levels of hsCRP (4.66±0.64mg/L; p=0.006), IL-6 (6.81±1.15ng/L; p<0.001) and TNF-α (6.09±0.47ng/L; p<0.001) in subjects with low-grade inflammation. Of 60 quantified oxylipins, 11 linoleic acid (LA)-, 1 dihomo-γ-linolenic acid (DGLA)-, 7 alpha linolenic acid (ALA)-, 15 arachidonic acid (AA)-, 8 eicosapentaenoic acid (EPA)- and 18 docosahexaenoic acid (DHA)-metabolites could be detected in plasma. For most oxylipins no differences were found between the low and high hsCRP groups before and after weight reduction. Interestingly, in subjects with low- grade inflammation several AA-derived oxylipins (5-, 8-, 12-hydroxyeicosatetraenoic acids (HETE)) were significantly higher compared to subjects with no inflammation before weight reduction and significantly reduced after weight reduction. CONCLUSION: Even moderate weight loss in obese subjects correlates to a significant improvement in the inflammatory state, by reducing hsCRP, IL-6, TNF-α and few oxylipins. The biological consequences of these changes remain to be further investigated. PMID: 26751601 [PubMed - as supplied by publisher]

Related Articles Advances in mass spectrometry-based clinical biomarker discovery. Clin Proteomics. 2016;13:1 Authors: Crutchfield CA, Thomas SN, Sokoll LJ, Chan DW Abstract The greatest unmet needs in biomarker discovery are those discoveries that lead to the development of clinical diagnostic tests. These clinical diagnostic tests can provide early intervention when a patient would present otherwise healthy (e.g., cancer or cardiovascular disease) and aid clinical decision making with improved clinical outcomes. The past two decades have seen significant technological improvements in the analytical capabilities of mass spectrometers. Mass spectrometers are unique in that they can directly analyze any biological molecule susceptible to ionization. The biological studies of human metabolites and proteins using contemporary mass spectrometry technology (metabolomics and proteomics, respectively) has been ongoing for over a decade. Some of these studies have resulted in exciting insights into human biology. However, relatively few biomarkers have been translated into clinical tests. This review will discuss some key technological developments that have occurred over this time with an emphasis on technologies that will create new avenues for biomarker discovery. PMID: 26751220 [PubMed - as supplied by publisher]

Related Articles 1H NMR and GC-MS based metabolomics reveal defense and detoxification mechanism of cucumber plant under nano-Cu stress. Environ Sci Technol. 2016 Jan 11; Authors: Zhao L, Huang Y, Hu J, Zhou H, Adeleye AS, Keller AA Abstract Since copper nanoparticles are being increasingly used in agriculture as pesticides, it is important to assess their potential implications for agriculture. Concerns have been raised about the bioaccumulation of nano-Cu and their toxicity to crop plants. Here, the response of cucumber plants in hydroponic culture at early development stages to two concentrations of nano-Cu (10 and 20 mg/L) was evaluated by proton nuclear magnetic resonance spectroscopy (1H NMR) and Gas Chromatography-Mass Spectrometry (GC-MS) based metabolomics. Changes in mineral nutrient metabolism induced by nano-Cu were determined by ICP-OES. Results showed that nano-Cu at both concentrations interfere with the uptake of a number of micro- and macro-nutrients, such as Na, P, S, Mo, Zn, and Fe. Metabolomics data revealed that nano-Cu at both levels triggered significant metabolic changes in cucumber leaves and root exudates. The root exudate metabolic changes revealed an active defense mechanism against nano-Cu stress: up-regulation of amino acids to sequester/exclude Cu/nano-Cu; down-regulation of citric acids to reduce the mobilization of Cu ions; ascorbic acid up-regulation to combat reactive oxygen species; up-regulation of phenolic compounds to improve antioxidant system. Thus, we demonstrate that non-targeted 1H NMR and GC-MS based metabolomics can successfully identify physiological responses induced by nanoparticles. Root exudates metabolomics revealed important detoxification mechanisms. PMID: 26751164 [PubMed - as supplied by publisher]

Related Articles Serum Trimethylamine-N-Oxide Is Strongly Related to Renal Function and Predicts Outcome in Chronic Kidney Disease. PLoS One. 2016;11(1):e0141738 Authors: Missailidis C, Hällqvist J, Qureshi AR, Barany P, Heimbürger O, Lindholm B, Stenvinkel P, Bergman P Abstract BACKGROUND: The microbial metabolite Trimethylamine-N-oxide (TMAO) has been linked to adverse cardiovascular outcome and mortality in the general population. OBJECTIVE: To assess the contribution of TMAO to inflammation and mortality in chronic kidney disease (CKD) patients ranging from mild-moderate to end-stage disease and 1) associations with glomerular filtration rate (GFR) 2) effect of dialysis and renal transplantation (Rtx) 3) association with inflammatory biomarkers and 4) its predictive value for all-cause mortality. METHODS: Levels of metabolites were quantified by a novel liquid chromatography/tandem mass spectrometry-based method in fasting plasma samples from 80 controls and 179 CKD 3-5 patients. Comorbidities, nutritional status, biomarkers of inflammation and GFR were assessed. RESULTS: GFR was the dominant variable affecting TMAO (β = -0.41; p<0.001), choline (β = -0.38; p<0.001), and betaine (β = 0.45; p<0.001) levels. A longitudinal study of 74 CKD 5 patients starting renal replacement therapy demonstrated that whereas dialysis treatment did not affect TMAO, Rtx reduced levels of TMAO to that of controls (p<0.001). Following Rtx choline and betaine levels continued to increase. In CKD 3-5, TMAO levels were associated with IL-6 (Rho = 0.42; p<0.0001), fibrinogen (Rho = 0.43; p<0.0001) and hsCRP (Rho = 0.17; p = 0.022). Higher TMAO levels were associated with an increased risk for all-cause mortality that remained significant after multivariate adjustment (HR 4.32, 95% CI 1.32-14.2; p = 0.016). CONCLUSION: Elevated TMAO levels are strongly associated with degree of renal function in CKD and normalize after renal transplantation. TMAO levels correlates with increased systemic inflammation and is an independent predictor of mortality in CKD 3-5 patients. PMID: 26751065 [PubMed - as supplied by publisher]