PubMed

Food metabolomics: from farm to human. Curr Opin Biotechnol. 2015 Sep 28;37:16-23 Authors: Kim S, Kim J, Yun EJ, Kim KH Abstract Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. PMID: 26426959 [PubMed - as supplied by publisher]

Recent applications of ce- and hplc-ms in the analysis of human fluids. Electrophoresis. 2015 Oct 1; Authors: Iadarola P, Fumagalli M, Bardoni AM, Salvini R, Viglio S Abstract The present review intends to cover the literature on the use of CE-/LC-MS for the analysis of human fluids, from 2010 until present. It has been planned to provide an overview of the most recent practical applications of these techniques to less extensively used human body fluids, including, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate, tear fluid, breast fluid, amniotic fluid and cerumen. Potential pitfalls related to fluid collection and sample preparation, with particular attention to sample clean-up procedures, and methods of analysis, from the research laboratory to a clinical setting will also be addressed. While being apparent that proteomics/metabolomics represent the most prominent approaches for global identification/quantification of putative biomarkers for a variety of human diseases, evidence is also provided of the suitability of these sophisticated techniques for the detection of heterogeneous components carried by these fluids. This article is protected by copyright. All rights reserved. PMID: 26426542 [PubMed - as supplied by publisher]

Chenodeoxycholic Acid as a Potential Prognostic Marker for Roux-en-Y Gastric Bypass in Chinese Obese Patients. J Clin Endocrinol Metab. 2015 Oct 1;:jc20152884 Authors: Yu H, Ni Y, Bao Y, Zhang P, Zhao A, Chen T, Xie G, Tu Y, Zhang L, Su M, Wei L, Jia W, Jia W Abstract CONTEXT: Bile acids (BAs) have been suggested as key mediators of the improvements in glucose metabolism after Roux-en-Y gastric bypass (RYGB). OBJECTIVE: To test whether the individual or a group of BAs have potential value to predict diabetes remission after RYGB. DESIGN AND PATIENTS: A retrospective cohort of 38 Chinese obese patients with type 2 diabetes (T2DM) who had undergone RYGB and a cross-sectional cohort of 327 subjects from the Shanghai Obesity Study (SHOS) were involved in the study. MAIN OUTCOME AND MEASURES: We applied a targeted metabolomics approach to quantitatively measure 26 serum BAs. The relative proportion of each BA in total BAs was calculated. RESULTS: In the metabolic surgery study, RYGB was effective in the reduction of body weight in both remission and non-remission groups. The reductions of BMI in both groups were 7.34±2.10kg/m(2) and 6.31±2.38kg/m(2) respectively (p=0.14). Patients in the remission group had shorter duration of diabetes, lower glycated haemoglobin (HbA1c), higher C-peptide and chenodeoxycholic acid (CDCA) proportion at baseline compared with the non-remission group. Multiple logistic regression indicated that a higher level of CDCA relative to TBA (CDCA %) and shorter duration of diabetes at baseline were associated with a greater chance of diabetes remission. The odd ratios were 0.19 (95%CI, 0.05 to 0.74), 1.77 (95%CI, 1.13 to 2.76) respectively after adjusted for age, gender and BMI. In the cross-sectional study, CDCA% was significantly higher in obese individuals with T2DM than the NGT group. Correlation analysis showed CDCA% was positively correlated with BMI, HbA1c, TG, LDL-c, and negatively correlated with HDL-c and diabetes duration. CONCLUSION: Increased CDCA, a major primary bile acid, was correlated with shorter duration of T2DM which was associated with a higher possibility of remission after surgery. CDCA% might act as a potential prognostic marker of RYGB. PMID: 26425885 [PubMed - as supplied by publisher]

Dietary Modulation of Gut Microbiota Contributes to Alleviation of Both Genetic and Simple Obesity in Children. EBioMedicine. 2015 Aug;2(8):966-82 Authors: Zhang C, Yin A, Li H, Wang R, Wu G, Shen J, Zhang M, Wang L, Hou Y, Ouyang H, Zhang Y, Zheng Y, Wang J, Lv X, Wang Y, Zhang F, Zeng B, Li W, Yan F, Zhao Y, Pang X, Zhang X, Fu H, Chen F, Zhao N, Hamaker BR, Bridgewater LC, Weinkove D, Clement K, Dore J, Holmes E, Xiao H, Zhao G, Yang S, Bork P, Nicholson JK, Wei H, Tang H, Zhang X, Zhao L Abstract UNLABELLED: Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader-Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation. RESEARCH IN CONTEXT: Poorly managed diet and genetic mutations are the two primary driving forces behind the devastating epidemic of obesity-related diseases. Lack of understanding of the molecular chain of causation between the driving forces and the disease endpoints retards progress in prevention and treatment of the diseases. We found that children genetically obese with Prader-Willi syndrome shared a similar dysbiosis in their gut microbiota with those having diet-related obesity. A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces. PMID: 26425705 [PubMed]

Warpgroup: Increased Precision of Metabolomic Data Processing by Consensus Integration Bound Analysis. Bioinformatics. 2015 Sep 30; Authors: Mahieu NG, Spalding J, Patti GJ Abstract MOTIVATION: Current informatic techniques for processing raw, chromatography/mass spectrometry data break down under several common, non-ideal conditions. Importantly, hydrophilic liquid interaction chromatography (a key separation technology for metabolomics) produces data which are especially challenging to process. We identify three critical points of failure in current informatic workflows: compound specific drift, integration region variance, and naive missing value imputation. We implement the Warpgroup algorithm to address these challenges. RESULTS: Warpgroup adds peak subregion detection, consensus integration bound detection, and intelligent missing value imputation steps to the conventional informatic workflow. When compared to the conventional workflow, Warpgroup made major improvements to the processed data. The coefficient of variation for replicate injections of a complex Escherichia Coli extract were halved (a reduction of 19%). Integration regions across samples were much more robust. Additionally, many signals lost by the conventional workflow were "rescued" by the Warpgroup refinement, thereby resulting in greater analyte coverage in the processed data. AVAILABILITY AND IMPLEMENTATION: Warpgroup is an open source R package available on GitHub at github.com/nathaniel-mahieu/warpgroup. The package includes example data and XCMS compatibility wrappers for ease of use. CONTACT: nathaniel.mahieu@wustl.edu and gjpattij@wustl.edu SUPPLEMENTARY INFORMATION: Supplementary information is available online. PMID: 26424859 [PubMed - as supplied by publisher]

Integrated metabolomics, transcriptomics and proteomics identifies metabolic pathways affected by Anaplasma phagocytophilum infection in tick cells. Mol Cell Proteomics. 2015 Sep 30; Authors: Villar M, Ayllon N, Alberdi P, Moreno A, Moreno M, Tobes R, Mateos-Hernandez L, Weisheit S, Bell-Sakyi L, de la Fuente J Abstract Anaplasma phagocytophilum is an emerging zoonotic pathogen that causes human granulocytic anaplasmosis. These intracellular bacteria establish infection by affecting cell function in both the vertebrate host and the tick vector, Ixodes scapularis. Previous studies have characterized the tick transcriptome and proteome in response to A. phagocytophilum infection. However, in the post-genomic era, the integration of omics datasets through a systems biology approach allows network-based analyses to describe the complexity and functionality of biological systems such as host-pathogen interactions and the discovery of new targets for prevention and control of infectious diseases. This study reports the first systems biology integration of metabolomics, transcriptomics and proteomics data to characterize essential metabolic pathways involved in the tick response to A. phagocytophilum infection. The ISE6 tick cells used in this study constitute a model for hemocytes involved in pathogen infection and immune response. The results showed that infection affected protein processing in endoplasmic reticulum and glucose metabolic pathways in tick cells. These results supported tick-Anaplasma co-evolution by providing new evidence of how tick cells limit pathogen infection, while the pathogen benefits from the tick cell response to establish infection. Additionally, ticks benefit from A. phagocytophilum infection by increasing survival while pathogens guarantee transmission. The results suggested that A. phagocytophilum induces protein misfolding to limit the tick cell response and facilitate infection, but requires protein degradation to prevent ER stress and cell apoptosis to survive in infected cells. Additionally, A. phagocytophilum may benefit from the tick cells ability to limit bacterial infection through PEPCK inhibition leading to decreased glucose metabolism, which also results in the inhibition of cell apoptosis that increases infection of tick cells. These results support the use of this experimental approach to systematically identify cell pathways and molecular mechanisms involved in tick-pathogen interactions. Data are available via ProteomeXchange with identifier PXD002181. PMID: 26424601 [PubMed - as supplied by publisher]

Increase the accessibility and scale of targeted metabolomics: Construction of a human urinary metabolome-wide multiple reaction monitoring library using directly-coupled reversed-phase and hydrophilic interaction chromatography. Anal Chim Acta. 2015 Sep 24;894:65-75 Authors: Yan Z, Yan R Abstract Multiple reaction monitoring (MRM) is wildly employed to research drug absorption, distribution, metabolism, excretion and pharmacokinetics in pharmaceutical and clinical laboratories. Recently, scientists in these areas have shown great interest in utilization of metabolomics to evaluate drug efficacy and toxicity. MRM-based targeted metabolomics is intrinsically more sensitive and selective than MS based untargeted metabolomics in complex biological samples. MRM also minimizes data complexity for fast and focused analysis of core metabolites. Nevertheless, to mitigate the intrinsic targeted nature of MRM and promote it as a discovery toolbox for metabolomics, larger scale MRM assays providing more comprehensive biological information are highly desirable. Here, we employed data-dependent and data-independent strategies to perform extensive MS/MS mapping of human urinary metabolome with the assistance of a directly-coupled reversed-phase liquid chromatography and hydrophilic interaction chromatography (RPLC-HILIC) for simultaneous profiling of hydrophilic and hydrophobic metabolites. RPLC-HILIC enables to save time, limit sample consumption and facilitate data interpretation by removing data redundancy occurring between separate RPLC and HILIC methods. Major product ions in the raw MS/MS spectra were used to build a human urinary metabolome-wide MRM library which contains 749 refined MRM tags in negative ion mode with 198 of them being unambiguously or tentatively assigned for particular metabolites. The library relieves researchers from the most time-consuming setup of massive MRM transitions and making an important step toward large-scale targeted urinary metabolomics. PMID: 26423629 [PubMed - in process]

Related Articles Normal adult survival but reduced Bemisia tabaci oviposition rate on tomato lines carrying an introgression from S. habrochaites. BMC Genet. 2014;15:142 Authors: Lucatti AF, Meijer-Dekens FR, Mumm R, Visser RG, Vosman B, van Heusden S Abstract BACKGROUND: Host plant resistance has been proposed as one of the most promising approaches in whitefly management. Already in 1995 two quantitative trait loci (Tv-1 and Tv-2) originating from S. habrochaites CGN1.1561 were identified that reduced the oviposition rate of the greenhouse whitefly (Trialeurodes vaporariorum). After this first study, several others identified QTLs affecting whitefly biology as well. Generally, the QTLs affecting oviposition were highly correlated with a reduction in whitefly survival and the presence of high densities of glandular trichomes type IV. The aim of our study was to further characterize Tv-1 and Tv-2, and to determine their role in resistance against Bemisia tabaci. RESULTS: We selected F2 plants homozygous for the Tv-1 and Tv-2 QTL regions and did three successive backcrosses without phenotypic selection. Twenty-three F2BC3 plants were phenotyped for whitefly resistance and differences were found in oviposition rate of B. tabaci. The F2BC3 plants with the lowest oviposition rate had an introgression on Chromosome 5 in common. Further F2BC4, F2BC4S1 and F2BC4S2 families were developed, genotyped and phenotyped for adult survival, oviposition rate and trichome type and density. It was possible to confirm that an introgression on top of Chr. 5 (OR-5), between the markers rs-2009 and rs-7551, was responsible for reducing whitefly oviposition rate. CONCLUSION: We found a region of 3.06 Mbp at the top of Chr. 5 (OR-5) associated with a reduction in the oviposition rate of B. tabaci. This reduction was independent of the presence of the QTLs Tv-1 and Tv-2 as well as of the presence of trichomes type IV. The OR-5 locus will provide new opportunities for resistance breeding against whiteflies, which is especially relevant in greenhouse cultivation. PMID: 25539894 [PubMed - indexed for MEDLINE]

Related Articles Sampling of intracellular metabolites for stationary and non-stationary (13)C metabolic flux analysis in Escherichia coli. Anal Biochem. 2014 Nov 15;465:38-49 Authors: Millard P, Massou S, Wittmann C, Portais JC, Létisse F Abstract The analysis of metabolic intermediates is a rich source of isotopic information for (13)C metabolic flux analysis ((13)C-MFA) and extends the range of its applications. The sampling of labeled metabolic intermediates is particularly important to obtain reliable isotopic information. The assessment of the different sampling procedures commonly used to generate such data, therefore, is crucial. In this work, we thoroughly evaluated several sampling procedures for stationary and non-stationary (13)C-MFA using Escherichia coli. We first analyzed the efficiency of these procedures for quenching metabolism and found that procedures based on cold or boiling solvents are reliable, in contrast to fast filtration, which is not. We also showed that separating the cells from the broth is not necessary in isotopic stationary state conditions. On the other hand, we demonstrated that the presence of metabolic intermediates outside the cells strongly affects the transient isotopic data monitored during non-stationary (13)C-labeling experiments. Meaningful isotopic data can be obtained by recovering intracellular labeled metabolites from pellets of cells centrifuged in cold solvent. We showed that if the intracellular pools are not separated from the extracellular ones, accurate flux maps can be established provided that the contribution of exogenous compounds is taken into account in the metabolic flux model. PMID: 25102204 [PubMed - indexed for MEDLINE]

Related Articles NMR-based investigation of the Drosophila melanogaster metabolome under the influence of daily cycles of light and temperature. Mol Biosyst. 2015 Sep 30; Authors: Gogna N, Singh VJ, Sheeba V, Dorai K Abstract We utilized an NMR-based metabolomic approach to profile the metabolites in Drosophila melanogaster that cycle with a daily rhythm. (1)H 1D and 2D NMR experiments were performed on whole-body extracts sampled from flies that experienced strong time cues in the form of both light and temperature cycles. Multivariate and univariate statistical analysis was used to identify those metabolites whose concentrations oscillate diurnally. We compared metabolite levels at two time points twelve hours apart, one close to the end of the day and the other close to the end of the night, and identified metabolites that differed significantly in their relative concentrations. We were able to identify 14 such metabolites whose concentrations differed significantly between the two time points. The concentrations of metabolites such as sterols, fatty acids, amino acids such as leucine, valine, isoleucine, alanine and lysine as well as other metabolites such as creatine, glucose, AMP and NAD were higher close to the end of the night, whereas the levels of lactic acid, and a few amino acids such as histidine and tryptophan were higher close to the end of the day. We compared signal intensities across 12 equally spaced time points for these 14 metabolites, in order to profile the changes in their levels across the day, since the NMR metabolite peak intensity is directly proportional to its molar concentration. Through this report we establish NMR-based metabolomics combined with multivariate statistical analysis as a useful method for future studies on the interactions between circadian clocks and metabolic processes. PMID: 26422411 [PubMed - as supplied by publisher]

Related Articles The metabolomics of asthma control: a promising link between genetics and disease. Immun Inflamm Dis. 2015 Sep;3(3):224-38 Authors: McGeachie MJ, Dahlin A, Qiu W, Croteau-Chonka DC, Savage J, Wu AC, Wan ES, Sordillo JE, Al-Garawi A, Martinez FD, Strunk RC, Lemanske RF, Liu AH, Raby BA, Weiss S, Clish CB, Lasky-Su JA Abstract Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative "omics" approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), - using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites-monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control. PMID: 26421150 [PubMed]

Related Articles Metabolomics in childhood diabetes. Pediatr Diabetes. 2015 Sep 30; Authors: Frohnert BI, Rewers MJ Abstract Recent increases in the incidence of both type 1 (T1D) and type 2 diabetes (T2D) in children and adolescents point to the importance of environmental factors in the development of these diseases. Metabolomic analysis explores the integrated response of the organism to environmental changes. Metabolic profiling can identify biomarkers that are predictive of disease incidence and development, potentially providing insight into disease pathogenesis. This review provides an overview of the role of metabolomic analysis in diabetes research and summarizes recent research relating to the development of T1D and T2D in children. PMID: 26420304 [PubMed - as supplied by publisher]

Related Articles Metabolome analysis reveals the effect of carbon catabolite control on the poly(γ-glutamic acid) biosynthesis of Bacillus licheniformis ATCC 9945. J Biosci Bioeng. 2015 Sep 23; Authors: Mitsunaga H, Meissner L, Palmen T, Bamba T, Büchs J, Fukusaki E Abstract Poly(γ-glutamic acid) (PGA) is a polymer composed of l- and/or d-glutamic acids that is produced by Bacillus sp. Because the polymer has various features as water soluble, edible, non-toxic and so on, it has attracted attention as a candidate for many applications such as foods, cosmetics and so on. However, although it is well known that the intracellular metabolism of Bacillus sp. is mainly regulated by catabolite control, the effect of the catabolite control on the PGA producing Bacillus sp. is largely unknown. This study is the first report of metabolome analysis on the PGA producing Bacillus sp. that reveals the effect of carbon catabolite control on the metabolism of PGA producing Bacillus licheniformis ATCC 9945. Results showed that the cells cultivated in glycerol-containing medium showed higher PGA production than the cells in glucose-containing medium. Furthermore, metabolome analysis revealed that the activators of CcpA and CodY, global regulatory proteins of the intracellular metabolism, accumulated in the cells cultivated in glycerol-containing and glucose-containing medium, respectively, with CodY apparently inhibiting PGA production. Moreover, the cells seemed to produce glutamate from citrate and ammonium using glutamine synthetase/glutamate synthase. Pulsed addition of di-ammonium hydrogen citrate, as suggested by the metabolome result, was able to achieve the highest value so far for PGA production in B. licheniformis. PMID: 26419706 [PubMed - as supplied by publisher]

Related Articles Metabolomic charactetization of yeast cells after dehydration stress. Int Microbiol. 2014 Sep;17(3):131-9 Authors: López-Martínez G, Borrull A, Poblet M, Roy NR, Cordero-Otero R Abstract In this study, we analyzed the metabolite features of the yeasts Saccharomyces cerevisiae, Naumovia castellii, and Saccharomyces mikatae. The three species are closely related genetically but differ in their tolerance of desiccation stress. Specifically, we determined whether certain metabolites correlated with cell viability after stress imposition. The metabolomics profiles of these strains were compared before cell desiccation and after cell rehydration. In S. mikatae, the presence of lysine or glutamine during rehydration led to a 20% increase in survival whereas during dehydration the levels of both amino acids in this yeast were drastically reduced. [Int Microbiol 2014; 17(3):131-139]. PMID: 26419452 [PubMed - in process]

Related Articles Metabolic changes in rat urine after acute paraquat poisoning and discriminated by support vector machine. Biomed Chromatogr. 2015 Sep 29; Authors: Wen C, Wang Z, Zhang M, Wang S, Geng P, Sun F, Chen M, Lin G, Hu L, Ma J, Wang X Abstract Paraquat is quick-acting and non-selective, killing green plant tissue on contact, it is also toxic to human beings and animals. In this study, we developed a urine metabonomic method by gas chromatography-mass spectrometry to evaluate the effect of acute paraquat poisoning on rats. Pattern recognition analysis, including both partial least squares-discriminate analysis and principal component analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared to the control group, the level of benzeneacetic acid and hexadecanoic acid of the acute paraquat poisoning group (intragastric administration 36 mg/kg) increased, while the level of butanedioic acid, pentanedioic acid, altronic acid decreased. Based on these urinary metabolomics data, support vector machine was applied to discriminate the metabolomic change of paraquat groups from control group which achieved 100% classification accuracy. In conclusion, metabonomic method combined with support vector machine can be used as a useful diagnostic tool in paraquat poisoned rats. This article is protected by copyright. All rights reserved. PMID: 26419410 [PubMed - as supplied by publisher]

Related Articles Spatial H2O2 signaling specificity: H2O2 from chloroplasts and peroxisomes modulates the plant transcriptome differentially. Mol Plant. 2014 Jul;7(7):1191-210 Authors: Sewelam N, Jaspert N, Van Der Kelen K, Tognetti VB, Schmitz J, Frerigmann H, Stahl E, Zeier J, Van Breusegem F, Maurino VG Abstract Hydrogen peroxide (H2O2) operates as a signaling molecule in eukaryotes, but the specificity of its signaling capacities remains largely unrevealed. Here, we analyzed whether a moderate production of H2O2 from two different plant cellular compartments has divergent effects on the plant transcriptome. Arabidopsis thaliana overexpressing glycolate oxidase in the chloroplast (Fahnenstich et al., 2008; Balazadeh et al., 2012) and plants deficient in peroxisomal catalase (Queval et al., 2007; Inzé et al., 2012) were grown under non-photorespiratory conditions and then transferred to photorespiratory conditions to foster the production of H2O2 in both organelles. We show that H2O2 originating in a specific organelle induces two types of responses: one that integrates signals independently from the subcellular site of H2O2 production and another that is dependent on the H2O2 production site. H2O2 produced in peroxisomes induces transcripts involved in protein repair responses, while H2O2 produced in chloroplasts induces early signaling responses, including transcription factors and biosynthetic genes involved in production of secondary signaling messengers. There is a significant bias towards the induction of genes involved in responses to wounding and pathogen attack by chloroplastic-produced H2O2, including indolic glucosinolates-, camalexin-, and stigmasterol-biosynthetic genes. These transcriptional responses were accompanied by the accumulation of 4-methoxy-indol-3-ylmethyl glucosinolate and stigmasterol. PMID: 24908268 [PubMed - indexed for MEDLINE]

Biomarkers in Transplantation- Proteomics and Metabolomics. Ther Drug Monit. 2015 Aug 28; Authors: U C, Klawitter J, Klawitter J Abstract Modern multi-analyte "omics" technologies allow for the identification of molecular signatures that confer significantly more information than measurement of a single parameter as typically used in current medical diagnostics. Proteomics and metabolomics bioanalytical assays capture a large set of proteins and metabolites in body fluids, cells or tissues and, complementing genomics, assess the phenome. Proteomics and metabolomics contribute to the development of novel predictive clinical biomarkers in transplantation in two ways: They can be used to generate a diagnostic fingerprint or they can be used to discover individual proteins and metabolites of diagnostic potential.Much fewer metabolomics than proteomics biomarker studies in transplant patients have been reported and, in contrast to proteomics discovery studies, new lead metabolite markers have yet to emerge.Most clinical proteomics studies have been discovery studies. Several of these studies have assessed diagnostic sensitivity and specificity. Nevertheless, none of these newly discovered protein biomarkers has yet been implemented in clinical decision making in transplantation. The currently most advanced markers discovered in proteomics studies in transplant patients are the chemokines CXCL-9 and CXCL-10, which have successfully been validated in larger multi-center trials in kidney transplant patients. These chemokines can be measured using standard immunoassay platforms, which should facilitate clinical implementation. Based on the published evidence, it is reasonable to expect that these chemokine markers can help guiding and individualizing immunosuppressive regimens, may be able to predict acute and chronic T cell and anti-body mediated rejection and may be useful tools for risk stratification of kidney transplant patients. PMID: 26418702 [PubMed - as supplied by publisher]

Transcription factor StWRKY1 regulates phenylpropanoid metabolites conferring late blight resistance in potato. J Exp Bot. 2015 Sep 28; Authors: Yogendra KN, Kumar A, Sarkar K, Li Y, Pushpa D, Mosa KA, Duggavathi R, Kushalappa AC Abstract Quantitative resistance is polygenically controlled and durable, but the underlying molecular and biochemical mechanisms are poorly understood. Secondary cell wall thickening is a critical process in quantitative resistance, regulated by transcriptional networks. This paper provides compelling evidence on the functionality of StWRKY1 transcription factor, in a compatible interaction of potato-Phytophthora infestans, to extend our knowledge on the regulation of the metabolic pathway genes leading to strengthening the secondary cell wall. A metabolomics approach was used to identify resistance-related metabolites belonging to the phenylpropanoid pathway and their biosynthetic genes regulated by StWRKY1. The StWRKY1 gene in resistant potato was silenced to decipher its role in the regulation of phenylpropanoid pathway genes to strengthen the secondary cell wall. Sequencing of the promoter region of StWRKY1 in susceptible genotypes revealed the absence of heat shock elements (HSEs). Simultaneous induction of both the heat shock protein (sHSP17.8) and StWRKY1 following pathogen invasion enables functioning of the latter to interact with the HSE present in the resistant StWRKY1 promoter region. EMSA and luciferase transient expression assays further revealed direct binding of StWRKY1 to promoters of hydroxycinnamic acid amide (HCAA) biosynthetic genes encoding 4-coumarate:CoA ligase and tyramine hydroxycinnamoyl transferase. Silencing of the StWRKY1 gene was associated with signs of reduced late blight resistance by significantly increasing the pathogen biomass and decreasing the abundance of HCAAs. This study provides convincing evidence on the role of StWRKY1 in the regulation of downstream genes to biosynthesize HCAAs, which are deposited to reinforce secondary cell walls. PMID: 26417019 [PubMed - as supplied by publisher]

Deletion of glycerol channel aquaporin-9 (Aqp9) impairs long-term blood glucose control in C57BL/6 leptin receptor-deficient (db/db) obese mice. Physiol Rep. 2015 Sep;3(9) Authors: Spegel P, Chawade A, Nielsen S, Kjellbom P, Rützler M Abstract Deletion of the glycerol channel aquaporin-9 (Aqp9) reduces postprandial blood glucose levels in leptin receptor-deficient (db/db) obese mice on a C57BL/6 × C57BLKS mixed genetic background. Furthermore, shRNA-mediated reduction of Aqp9 expression reduces liver triacylglycerol (TAG) accumulation in a diet-induced rat model of obesity. The aim of this study was to investigate metabolic effects of Aqp9 deletion in coisogenic db/db mice of the C57BL/6 background. Aqp9(wt) db/db and Aqp9(-/-) db/db mice did not differ in body weight and liver TAG contents. On the C57BL/6 genetic background, we observed elevated plasma glucose in Aqp9(-/-) db/db mice (+1.1 mmol/L, life-time average), while plasma insulin concentration was reduced at the time of death. Glucose levels changed similarly in pentobarbital anesthetized, glucagon challenged Aqp9(wt) db/db and Aqp9(-/-) db/db mice. Liver transcriptional profiling did not detect differential gene expression between genotypes. Metabolite profiling revealed a sex independent increase in plasma glycerol (+55%) and glucose (+24%), and reduction in threonate (all at q < 0.1) in Aqp9(-/-) db/db mice compared to controls. Metabolite profiling thus confirms a role of AQP9 in glycerol metabolism of obese C57BL/6 db/db mice. In this animal model of obesity Aqp9 gene deletion elevates plasma glucose and does not alleviate hepatosteatosis. PMID: 26416971 [PubMed]

Detection of metabolites discriminating subtypes of thyroid cancer: molecular profiling of FFPE samples using the GC/MS approach. Mol Cell Endocrinol. 2015 Sep 25; Authors: Wojakowska A, Chekan M, Marczak Ł, Polanski K, Lange D, Pietrowska M, Widlak P Abstract One of the critical issues in thyroid cancer diagnostic is differentiation between follicular adenoma, follicular carcinoma and the follicular variant of papillary carcinoma, which in some cases is not possible based on histopathological features only. In this paper we performed molecular profiling of thyroid tissue aiming to identify metabolites characteristic for different types of thyroid cancer. FFPE tissue specimens were analysed from 5 different types of thyroid malignancies (follicular, papillary/classical variant, papillary/follicular variant, medullary and anaplastic cancers), benign follicular adenoma and normal thyroid. Extracted metabolites were identified and semi-quantified using the GC/MS approach. There were 28 metabolites identified, whose abundances were significantly different among different types of thyroid tumours, including lipids, carboxylic acids, and saccharides. We concluded, that multi-component metabolome signature could be used for classification of different subtypes of follicular thyroid lesions. Moreover, potential applicability of the GC/MS-based analysis of FFPE tissue samples in diagnostics of thyroid cancer has been proved. PMID: 26415588 [PubMed - as supplied by publisher]