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19 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/11/15PubMed 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.

Characterization of global metabolic profile of Zhi-Zi-Hou-Po decoction in rat bile, urine and feces after oral administration based on a strategy combining LC-MS and chemometrics. J Chromatogr B Analyt Technol Biomed Life Sci. 2016 Nov 3;: Authors: Luo K, Shi Q, Feng F Abstract Identification of metabolic profile of traditional Chinese medicine in vivo is always a challenge task. Usually, screening out and identifying the exogenous compounds manually from total ion chromatograms (TICs) of biologic samples is time-consuming and strenuous. In this study, a systematic identification strategy based on LC-MS was adopted to clarify the metabolic profiling of Zhi-Zi-Hou-Po decoction (ZZHPD) in rat. Bile, urine and feces samples of rat were obtained after oral administration and then analyzed by LC-MS after proper preparation. The xenobiotics were screened out from TICs globally and rapidly by untargeted metabolomics-driven strategy (UMDS) based on the combined of XCMS online (a web-based platform to process LC-MS data), MetAlign (a software to process LC-MS data) and SIMCA-P (a software for data analysis). Most of the xenobiotics were identified by means of series product ions filtering (sPIF), which was based on the database-hit of ZZHPD (including prototype and metabolites). Then the unmatched constituents were identified tentatively and their source and metabolic pathway were clarified by using diagnostic fragment ions strategy (DFIS). As a result, a total of 83 compounds including 44 prototype compounds and 39 metabolites were rapidly identified or tentatively characterized from the biologic samples, and among them, four of which were found for the first time. Further research on the correlations of these prototype compounds and metabolites revealed that glucuronidation is the main metabolic pathways of ZZHPD in rat bile and urine, while prototype compounds were the abundant ingredients detected in rat feces. PMID: 27838179 [PubMed - as supplied by publisher]

19 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/11/12PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Related Articles Immunogenetics of IgG4-Related AIP. Curr Top Microbiol Immunol. 2016 Nov 11; Authors: Ota M, Umemura T, Kawa S Abstract Autoimmune pancreatitis (AIP) is a unique form of chronic pancreatitis characterized by high serum IgG4 concentration and a variety of complicating extra-pancreatic lesions. AIP has the features of a complex disease that is caused by multifactorial genes. However, the genetic factors underlying AIP have not been elucidated conclusively. Association studies by the candidate-gene approach and genome-wide association studies (GWAS) have revealed several susceptibility genes for AIP, including HLA DRB1*04:05-DQB1*04:01, FCRL3, CTLA4, and KCNA3, albeit in small-scale analyses. Thus, GWAS of large sample sizes and multinational collaborative meta-analyses are needed to identify the precise genetic variants that are associated with AIP onset. Systems genetics approaches that integrate DNA sequencing, expression quantitative trait locus (eQTL) mapping, proteomics, and metabolomics will also be useful in clarifying the pathogenesis of AIP. PMID: 27832379 [PubMed - as supplied by publisher]

Related Articles Metabolic alterations by indoxyl sulfate in skeletal muscle induce uremic sarcopenia in chronic kidney disease. Sci Rep. 2016 Nov 10;6:36618 Authors: Sato E, Mori T, Mishima E, Suzuki A, Sugawara S, Kurasawa N, Saigusa D, Miura D, Morikawa-Ichinose T, Saito R, Oba-Yabana I, Oe Y, Kisu K, Naganuma E, Koizumi K, Mokudai T, Niwano Y, Kudo T, Suzuki C, Takahashi N, Sato H, Abe T, Niwa T, Ito S Abstract Sarcopenia is associated with increased morbidity and mortality in chronic kidney disease (CKD). Pathogenic mechanism of skeletal muscle loss in CKD, which is defined as uremic sarcopenia, remains unclear. We found that causative pathological mechanism of uremic sarcopenia is metabolic alterations by uremic toxin indoxyl sulfate. Imaging mass spectrometry revealed indoxyl sulfate accumulated in muscle tissue of a mouse model of CKD. Comprehensive metabolomics revealed that indoxyl sulfate induces metabolic alterations such as upregulation of glycolysis, including pentose phosphate pathway acceleration as antioxidative stress response, via nuclear factor (erythroid-2-related factor)-2. The altered metabolic flow to excess antioxidative response resulted in downregulation of TCA cycle and its effected mitochondrial dysfunction and ATP shortage in muscle cells. In clinical research, a significant inverse association between plasma indoxyl sulfate and skeletal muscle mass in CKD patients was observed. Our results indicate that indoxyl sulfate is a pathogenic factor for sarcopenia in CKD. PMID: 27830716 [PubMed - in process]

Related Articles Recovery of pan-genotypic and genotype-specific amino acid alterations in chronic hepatitis C after viral clearance: transition at the crossroad of metabolism and immunity. Amino Acids. 2016 Nov 10; Authors: Chang ML, Cheng ML, Chang SW, Tang HY, Chiu CT, Yeh CT, Shiao MS Abstract Recovery of amino acid (AA) metabolism and the associated clinical implications in chronic hepatitis C (CHC) patients with sustained virological response (SVR) following anti-hepatitis C virus (HCV) therapy remains elusive. A prospective cohort study was conducted on 222 CHC patients with SVR. Eighty-two age-matched male genotype 1 (G1) and G2 patients underwent paired serum metabolomics analyses with liquid chromatography-tandem mass spectrometry to examine AAs before and 24 weeks after anti-HCV therapy. Before anti-HCV therapy, G1 patients had a higher HCV RNA level than G2 patients. Twenty-four weeks post-therapy versus pre-therapy, repeated-measures ANOVA showed that the levels of alanine aminotransferase and most AAs decreased while those of lipids, glutamine and putrescine increased in CHC patients. The methionine sulfoxide/methionine ratio decreased, while the asymmetric dimethylarginine/arginine, glutamine/glutamate, citrulline/arginine, ornithine/arginine, kynurenine/tryptophan, tyrosine/phenylalanine and Fisher's ratios increased. Genotype-specific subgroup analyses showed that valine and serotonin/tyrosine increased in G1 and that kynurenine and tyrosine/phenylalanine increased and sarcosine decreased in G2 patients. Viral clearance in CHC patients pan-genotypically restored fuel utilization by decelerating the tricarboxylic acid cycle. Following improvement in liver function, the urea, nitric oxide, methionine, and polyamine cycles were accelerated. The cardiometabolic risk attenuated, but the augmented kynurenine pathway activity could increase the oncogenesis risk. The trends in neurotransmitter formation differed between G1 and G2 patients after SVR. Moreover, the HCV-suppressing effect of valine was evident in G1 patients; with the exception of prostate cancer, the oncogenesis risk increased, particularly in G2 patients, at least within 24 weeks post-anti-HCV therapy. PMID: 27830380 [PubMed - as supplied by publisher]

Related Articles iTRAQ-Based Proteomic Analysis of Ginsenoside F2 on Human Gastric Carcinoma Cells SGC7901. Evid Based Complement Alternat Med. 2016;2016:2635483 Authors: Mao Q, Zhang PH, Yang J, Xu JD, Kong M, Shen H, Zhu H, Bai M, Zhou L, Li GF, Wang Q, Li SL Abstract Ginsenoside F2 (F2), a protopanaxdiol type of saponin, was reported to inhibit human gastric cancer cells SGC7901. To better understand the molecular mechanisms of F2, an iTRAQ-based proteomics approach was applied to define protein expression profiles in SGC7901 cells in response to lower dose (20 μM) and shorter duration (12 hour) of F2 treatment, compared with previous study. 205 proteins were screened in terms of the change in their expression level which met our predefined criteria. Further bioinformatics and experiments demonstrated that F2 treatment downregulated PRR5 and RPS15 and upregulated RPL26, which are implicated in ribosomal protein-p53 signaling pathway. F2 also inhibited CISD2, Bcl-xl, and NLRX1, which are associated with autophagic pathway. Furthermore, it was demonstrated that F2 treatment increased Atg5, Atg7, Atg10, and PUMA, the critical downstream effectors of ribosomal protein-p53 signaling pathway, and Beclin-1, UVRAG, and AMBRA-1, the important molecules in Bcl-xl/Beclin-1 pathway. The 6 differentially abundant proteins, PRR5, CISD2, Bcl-xl, NLRX1, RPS15, and RPL26, were confirmed by western blot. Taken together, ribosomal protein-p53 signaling pathway and Bcl-xl/Beclin-1 pathway might be the most significantly regulated biological process by F2 treatment in SGC7901 cells, which provided valuable insights into the deep understanding of the molecular mechanisms of F2 for gastric cancer treatment. PMID: 27829861 [PubMed - in process]

Related Articles The pretransplant systemic metabolic profile reflects a risk of acute graft versus host disease after allogeneic stem cell transplantation. Metabolomics. 2016;12(1):12 Authors: Reikvam H, Hatfield K, Bruserud Ø Abstract Allogeneic stem cell transplantation is used in the treatment of younger patients with severe hematological diseases, especially hematological malignancies, and acute graft versus host disease (GVHD) is then an important immune-mediated posttransplant complication. Several risk factors for acute GVHD have been identified, including pretransplant factors that possibly influence the posttranspant course through their effects on host immunocompetent cells. Metabolic regulation is important for immunoregulation, and we therefore investigated whether the pretransplant metabolic status of allotransplant recipients was associated with later acute GVHD. In our population-based study we investigated the systemic (serum) metabolic profile for 86 consecutive allotransplant recipients. The samples were collected before start of the pretransplant conditioning therapy. Patients who developed later acute GVHD especially showed altered pretransplant amino acid metabolism, including (1) altered metabolism of immunoregulatory branched chain amino acids (leucine, isoleucine and valine); and (2) altered levels of potentially proinflammatory tyrosine metabolites (p-cresol sulphate, 3-phenylpropionate) formed by the gastrointestinal microbial flora. However, isobutyrylcarnitine and propyonylcarnitine levels were also altered; the carnitines are important for the transport of fatty acids and may also be important for the release of immunoregulatory cytokines in allotransplant recipients. These metabolic alterations were associated with an ongoing pretransplant acute phase reaction or early hematopoietic/immune reconstitution. Thus, allotransplant recipients developing acute GVHD showed altered preconditioning/pretransplant levels of several immunoregulatory metabolites. Our hypothesis is that these metabolites alter or activate recipient immunocompetent cells and thereby enhance or initiate anti-recipient immune reactivity. PMID: 27829829 [PubMed - in process]

Related Articles A serum nuclear magnetic resonance-based metabolomic signature of antiphospholipid syndrome. J Pharm Biomed Anal. 2016 Nov 2;: Authors: Palisi A, Grimaldi M, Sabatini P, Montoro P, Scrima M, Rodriquez M, D'Ursi AM Abstract Antiphospholipid syndrome (APS) is a rheumatic inflammatory chronic autoimmune disease inducing hypercoagulable state associated with vascular thrombosis and pregnancy loss in women. Cardiac, cerebral and vascular strokes in these patients are responsible for reduction in life expectancy. Timely diagnosis and accurate monitoring of disease are decisive to improve the accuracy of therapy. In the present work, we present a NMR-based metabolomic study of blood sera of APS patients. Our data show that individuals suffering APS have a characteristic metabolomic profile with abnormalities associated to the metabolism of methyl group donors, ketone bodies and amino acids. We have identified for the first time the metabolomic fingerprint characterizing APS disease having potential application to improve APS timely diagnosis and appropriate therapeutic approaches. PMID: 27829500 [PubMed - as supplied by publisher]

Related Articles Metabolic Profiling and Antioxidant Assay of Metabolites from Three Radish Cultivars (Raphanus sativus). Molecules. 2016 Jan 28;21(2):157 Authors: Park CH, Baskar TB, Park SY, Kim SJ, Valan Arasu M, Al-Dhabi NA, Kim JK, Park SU Abstract A total of 13 anthocyanins and 33 metabolites; including organic acids, phenolic acids, amino acids, organic compounds, sugar acids, sugar alcohols, and sugars, were profiled in three radish cultivars by using high-performance liquid chromatography (HPLC) and gas chromatography time-of-flight mass spectrometry (GC-TOFMS)-based metabolite profiling. Total phenolics and flavonoids and their in vitro antioxidant activities were assessed. Pelargonidins were found to be the major anthocyanin in the cultivars studied. The cultivar Man Tang Hong showed the highest level of anthocyanins (1.89 ± 0.07 mg/g), phenolics (0.0664 ± 0.0033 mg/g) and flavonoids (0.0096 ± 0.0004 mg/g). Here; the variation of secondary metabolites in the radishes is described, as well as their association with primary metabolites. The low-molecular-weight hydrophilic metabolite profiles were subjected to principal component analysis (PCA), hierarchical clustering analysis (HCA), Pearson's correlation analysis. PCA fully distinguished the three radish cultivars tested. The polar metabolites were strongly correlated between metabolites that participate in the TCA cycle. The chemometrics results revealed that TCA cycle intermediates and free phenolic acids as well as anthocyanins were higher in the cultivar Man Tang Hong than in the others. Furthermore; superoxide radical scavenging activities and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging were investigated to elucidate the antioxidant activity of secondary metabolites in the cultivars. Man Tang Hong showed the highest superoxide radical scavenging activity (68.87%) at 1000 μg/mL, and DPPH activity (20.78%), followed by Seo Ho and then Hong Feng No. 1. The results demonstrate that GC-TOFMS-based metabolite profiling, integrated with chemometrics, is an applicable method for distinguishing phenotypic variation and determining biochemical reactions connecting primary and secondary metabolism. Therefore; this study might provide information on the relationship between primary and secondary metabolites and a synergistic antioxidant ability derived from the secondary metabolites in the radish cultivars. PMID: 26828471 [PubMed - indexed for MEDLINE]

Related Articles Precision Nutrition 4.0: A Big Data and Ethics Foresight Analysis--Convergence of Agrigenomics, Nutrigenomics, Nutriproteomics, and Nutrimetabolomics. OMICS. 2016 Feb;20(2):69-75 Authors: Özdemir V, Kolker E Abstract Nutrition is central to sustenance of good health, not to mention its role as a cultural object that brings together or draws lines among societies. Undoubtedly, understanding the future paths of nutrition science in the current era of Big Data remains firmly on science, technology, and innovation strategy agendas around the world. Nutrigenomics, the confluence of nutrition science with genomics, brought about a new focus on and legitimacy for "variability science" (i.e., the study of mechanisms of person-to-person and population differences in response to food, and the ways in which food variably impacts the host, for example, nutrient-related disease outcomes). Societal expectations, both public and private, and claims over genomics-guided and individually-tailored precision diets continue to proliferate. While the prospects of nutrition science, and nutrigenomics in particular, are established, there is a need to integrate the efforts in four Big Data domains that are naturally allied--agrigenomics, nutrigenomics, nutriproteomics, and nutrimetabolomics--that address complementary variability questions pertaining to individual differences in response to food-related environmental exposures. The joint use of these four omics knowledge domains, coined as Precision Nutrition 4.0 here, has sadly not been realized to date, but the potentials for such integrated knowledge innovation are enormous. Future personalized nutrition practices would benefit from a seamless planning of life sciences funding, research, and practice agendas from "farm to clinic to supermarket to society," and from "genome to proteome to metabolome." Hence, this innovation foresight analysis explains the already existing potentials waiting to be realized, and suggests ways forward for innovation in both technology and ethics foresight frames on precision nutrition. We propose the creation of a new Precision Nutrition Evidence Barometer for periodic, independent, and ongoing retrieval, screening, and aggregation of the relevant life sciences data. For innovation in Big Data ethics oversight, we suggest "nested governance" wherein the processes of knowledge production are made transparent in the continuum from life sciences and social sciences to humanities, and where each innovation actor reports to another accountability and transparency layer: scientists to ethicists, and ethicists to scholars in the emerging field of ethics-of-ethics. Such nested innovation ecosystems offer safety against innovation blind spots, calibrate visible/invisible power differences in the cultures of science or ethics, and ultimately, reducing the risk of "paper values"--what people say--and "real values"--what innovation actors actually do. We are optimistic that the convergence of nutrigenomics with nutriproteomics, nutrimetabolomics, and agrigenomics can build a robust, sustainable, and trustworthy precision nutrition 4.0 agenda, as articulated in this Big Data and ethics foresight analysis. PMID: 26785082 [PubMed - indexed for MEDLINE]

Related Articles Metabolic Biomarkers and Neurodegeneration: A Pathway Enrichment Analysis of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis. OMICS. 2016 Nov;20(11):645-661 Authors: Kori M, Aydın B, Unal S, Arga KY, Kazan D Abstract Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) lack robust diagnostics and prognostic biomarkers. Metabolomics is a postgenomics field that offers fresh insights for biomarkers of common complex as well as rare diseases. Using data on metabolite-disease associations published in the previous decade (2006-2016) in PubMed, ScienceDirect, Scopus, and Web of Science, we identified 101 metabolites as putative biomarkers for these three neurodegenerative diseases. Notably, uric acid, choline, creatine, L-glutamine, alanine, creatinine, and N-acetyl-L-aspartate were the shared metabolite signatures among the three diseases. The disease-metabolite-pathway associations pointed out the importance of membrane transport (through ATP binding cassette transporters), particularly of arginine and proline amino acids in all three neurodegenerative diseases. When disease-specific and common metabolic pathways were queried by using the pathway enrichment analyses, we found that alanine, aspartate, glutamate, and purine metabolism might act as alternative pathways to overcome inadequate glucose supply and energy crisis in neurodegeneration. These observations underscore the importance of metabolite-based biomarker research in deciphering the elusive pathophysiology of neurodegenerative diseases. Future research investments in metabolomics of complex diseases might provide new insights on AD, PD, and ALS that continue to place a significant burden on global health. PMID: 27828769 [PubMed - in process]

Related Articles A Conversation on Data Mining Strategies in LC-MS Untargeted Metabolomics: Pre-Processing and Pre-Treatment Steps. Metabolites. 2016 Nov 03;6(4): Authors: Tugizimana F, Steenkamp PA, Piater LA, Dubery IA Abstract Untargeted metabolomic studies generate information-rich, high-dimensional, and complex datasets that remain challenging to handle and fully exploit. Despite the remarkable progress in the development of tools and algorithms, the "exhaustive" extraction of information from these metabolomic datasets is still a non-trivial undertaking. A conversation on data mining strategies for a maximal information extraction from metabolomic data is needed. Using a liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomic dataset, this study explored the influence of collection parameters in the data pre-processing step, scaling and data transformation on the statistical models generated, and feature selection, thereafter. Data obtained in positive mode generated from a LC-MS-based untargeted metabolomic study (sorghum plants responding dynamically to infection by a fungal pathogen) were used. Raw data were pre-processed with MarkerLynx(TM) software (Waters Corporation, Manchester, UK). Here, two parameters were varied: the intensity threshold (50-100 counts) and the mass tolerance (0.005-0.01 Da). After the pre-processing, the datasets were imported into SIMCA (Umetrics, Umea, Sweden) for more data cleaning and statistical modeling. In addition, different scaling (unit variance, Pareto, etc.) and data transformation (log and power) methods were explored. The results showed that the pre-processing parameters (or algorithms) influence the output dataset with regard to the number of defined features. Furthermore, the study demonstrates that the pre-treatment of data prior to statistical modeling affects the subspace approximation outcome: e.g., the amount of variation in X-data that the model can explain and predict. The pre-processing and pre-treatment steps subsequently influence the number of statistically significant extracted/selected features (variables). Thus, as informed by the results, to maximize the value of untargeted metabolomic data, understanding of the data structures and exploration of different algorithms and methods (at different steps of the data analysis pipeline) might be the best trade-off, currently, and possibly an epistemological imperative. PMID: 27827887 [PubMed - in process]

Related Articles MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments. Metabolites. 2016 Nov 02;6(4): Authors: Koch S, Bueschl C, Doppler M, Simader A, Meng-Reiterer J, Lemmens M, Schuhmacher R Abstract Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley. PMID: 27827849 [PubMed - in process]

Related Articles Natural Products from Microalgae with Potential against Alzheimer's Disease: Sulfolipids Are Potent Glutaminyl Cyclase Inhibitors. Mar Drugs. 2016 Nov 02;14(11): Authors: Hielscher-Michael S, Griehl C, Buchholz M, Demuth HU, Arnold N, Wessjohann LA Abstract In recent years, many new enzymes, like glutaminyl cyclase (QC), could be associated with pathophysiological processes and represent targets for many diseases, so that enzyme-inhibiting properties of natural substances are becoming increasingly important. In different studies, the pathophysiology connection of QC to various diseases including Alzheimer's disease (AD) was described. Algae are known for the ability to synthesize complex and highly-diverse compounds with specific enzyme inhibition properties. Therefore, we screened different algae species for the presence of QC inhibiting metabolites using a new "Reverse Metabolomics" technique including an Activity-correlation Analysis (AcorA), which is based on the correlation of bioactivities to mass spectral data with the aid of mathematic informatics deconvolution. Thus, three QC inhibiting compounds from microalgae belonging to the family of sulfolipids were identified. The compounds showed a QC inhibition of 81% and 76% at concentrations of 0.25 mg/mL and 0.025 mg/mL, respectively. Thus, for the first time, sulfolipids are identified as QC inhibiting compounds and possess substructures with the required pharmacophore qualities. They represent a new lead structure for QC inhibitors. PMID: 27827845 [PubMed - in process]

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/11/09PubMed 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.

Transcriptomic Analysis of Responses to Imbalanced Carbon: Nitrogen Availabilities in Rice Seedlings. PLoS One. 2016;11(11):e0165732 Authors: Huang A, Sang Y, Sun W, Fu Y, Yang Z Abstract The internal C:N balance must be tightly controlled for the normal growth and development of plants. However, the underlying mechanisms, by which plants sense and balance the intracellular C:N status correspondingly to exogenous C:N availabilities remain elusive. In this study, we use comparative gene expression analysis to identify genes that are responsive to imbalanced C:N treatments in the aerial parts of rice seedlings. Transcripts of rice seedlings treated with four C:N availabilities (1:1, 1:60, 60:1 and 60:60) were compared and two groups of genes were classified: high C:low N responsive genes and low C:high N responsive genes. Our analysis identified several functional correlated genes including chalcone synthase (CHS), chlorophyll a-b binding protein (CAB) and other genes that are implicated in C:N balancing mechanism, such as alternative oxidase 1B (OsAOX1B), malate dehydrogenase (OsMDH) and lysine and histidine specific transporter 1 (OsLHT1). Additionally, six jasmonate synthetic genes and key regulatory genes involved in abiotic and biotic stresses, such as OsMYB4, autoinhibited calcium ATPase 3 (OsACA3) and pleiotropic drug resistance 9 (OsPDR9), were differentially expressed under high C:low N treatment. Gene ontology analysis showed that high C:low N up-regulated genes were primarily enriched in fatty acid biosynthesis and defense responses. Coexpression network analysis of these genes identified eight jasmonate ZIM domain protein (OsJAZ) genes and several defense response related regulators, suggesting that high C:low N status may act as a stress condition, which induces defense responses mediated by jasmonate signaling pathway. Our transcriptome analysis shed new light on the C:N balancing mechanisms and revealed several important regulators of C:N status in rice seedlings. PMID: 27820840 [PubMed - in process]

Regulation of autoantibody activity by the IL-23-TH17 axis determines the onset of autoimmune disease. Nat Immunol. 2016 Nov 07;: Authors: Pfeifle R, Rothe T, Ipseiz N, Scherer HU, Culemann S, Harre U, Ackermann JA, Seefried M, Kleyer A, Uderhardt S, Haugg B, Hueber AJ, Daum P, Heidkamp GF, Ge C, Böhm S, Lux A, Schuh W, Magorivska I, Nandakumar KS, Lönnblom E, Becker C, Dudziak D, Wuhrer M, Rombouts Y, Koeleman CA, Toes R, Winkler TH, Holmdahl R, Herrmann M, Blüml S, Nimmerjahn F, Schett G, Krönke G Abstract The checkpoints and mechanisms that contribute to autoantibody-driven disease are as yet incompletely understood. Here we identified the axis of interleukin 23 (IL-23) and the TH17 subset of helper T cells as a decisive factor that controlled the intrinsic inflammatory activity of autoantibodies and triggered the clinical onset of autoimmune arthritis. By instructing B cells in an IL-22- and IL-21-dependent manner, TH17 cells regulated the expression of β-galactoside α2,6-sialyltransferase 1 in newly differentiating antibody-producing cells and determined the glycosylation profile and activity of immunoglobulin G (IgG) produced by the plasma cells that subsequently emerged. Asymptomatic humans with rheumatoid arthritis (RA)-specific autoantibodies showed identical changes in the activity and glycosylation of autoreactive IgG antibodies before shifting to the inflammatory phase of RA; thus, our results identify an IL-23-TH17 cell-dependent pathway that controls autoantibody activity and unmasks a preexisting breach in immunotolerance. PMID: 27820809 [PubMed - as supplied by publisher]

Nutrigenomics in the modern era. Proc Nutr Soc. 2016 Nov 7;:1-11 Authors: Mathers JC Abstract The concept that interactions between nutrition and genetics determine phenotype was established by Garrod at the beginning of the 20th century through his ground-breaking work on inborn errors of metabolism. A century later, the science and technologies involved in sequencing of the human genome stimulated development of the scientific discipline which we now recognise as nutritional genomics (nutrigenomics). Much of the early hype around possible applications of this new science was unhelpful and raised expectations, which have not been realised as quickly as some would have hoped. However, major advances have been made in quantifying the contribution of genetic variation to a wide range of phenotypes and it is now clear that for nutrition-related phenotypes, such as obesity and common complex diseases, the genetic contribution made by SNP alone is often modest. There is much scope for innovative research to understand the roles of less well explored types of genomic structural variation, e.g. copy number variants, and of interactions between genotype and dietary factors, in phenotype determination. New tools and models, including stem cell-based approaches and genome editing, have huge potential to transform mechanistic nutrition research. Finally, the application of nutrigenomics research offers substantial potential to improve public health e.g. through the use of metabolomics approaches to identify novel biomarkers of food intake, which will lead to more objective and robust measures of dietary exposure. In addition, nutrigenomics may have applications in the development of personalised nutrition interventions, which may facilitate larger, more appropriate and sustained changes in eating (and other lifestyle) behaviours and help to reduce health inequalities. PMID: 27819203 [PubMed - as supplied by publisher]

Related Articles Adipocyte Ceramides Regulate Subcutaneous Adipose Browning, Inflammation, and Metabolism. Cell Metab. 2016 Oct 21;: Authors: Chaurasia B, Kaddai VA, Lancaster GI, Henstridge DC, Sriram S, Galam DL, Gopalan V, Prakash KN, Velan SS, Bulchand S, Tsong TJ, Wang M, Siddique MM, Yuguang G, Sigmundsson K, Mellet NA, Weir JM, Meikle PJ, Bin M Yassin MS, Shabbir A, Shayman JA, Hirabayashi Y, Shiow ST, Sugii S, Summers SA Abstract Adipocytes package incoming fatty acids into triglycerides and other glycerolipids, with only a fraction spilling into a parallel biosynthetic pathway that produces sphingolipids. Herein, we demonstrate that subcutaneous adipose tissue of type 2 diabetics contains considerably more sphingolipids than non-diabetic, BMI-matched counterparts. Whole-body and adipose tissue-specific inhibition/deletion of serine palmitoyltransferase (Sptlc), the first enzyme in the sphingolipid biosynthesis cascade, in mice markedly altered adipose morphology and metabolism, particularly in subcutaneous adipose tissue. The reduction in adipose sphingolipids increased brown and beige/brite adipocyte numbers, mitochondrial activity, and insulin sensitivity. The manipulation also increased numbers of anti-inflammatory M2 macrophages in the adipose bed and induced secretion of insulin-sensitizing adipokines. By comparison, deletion of serine palmitoyltransferase from macrophages had no discernible effects on metabolic homeostasis or adipose function. These data indicate that newly synthesized adipocyte sphingolipids are nutrient signals that drive changes in the adipose phenotype to influence whole-body energy expenditure and nutrient metabolism. PMID: 27818258 [PubMed - as supplied by publisher]