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      The gut microbiota modulates host amino acid and glutathione metabolism in mice

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          Abstract

          The gut microbiota has been proposed as an environmental factor that promotes the progression of metabolic diseases. Here, we investigated how the gut microbiota modulates the global metabolic differences in duodenum, jejunum, ileum, colon, liver, and two white adipose tissue depots obtained from conventionally raised (CONV-R) and germ-free (GF) mice using gene expression data and tissue-specific genome-scale metabolic models (GEMs). We created a generic mouse metabolic reaction (MMR) GEM, reconstructed 28 tissue-specific GEMs based on proteomics data, and manually curated GEMs for small intestine, colon, liver, and adipose tissues. We used these functional models to determine the global metabolic differences between CONV-R and GF mice. Based on gene expression data, we found that the gut microbiota affects the host amino acid (AA) metabolism, which leads to modifications in glutathione metabolism. To validate our predictions, we measured the level of AAs and N-acetylated AAs in the hepatic portal vein of CONV-R and GF mice. Finally, we simulated the metabolic differences between the small intestine of the CONV-R and GF mice accounting for the content of the diet and relative gene expression differences. Our analyses revealed that the gut microbiota influences host amino acid and glutathione metabolism in mice.

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          Most cited references43

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          Developmental regulation of intestinal angiogenesis by indigenous microbes via Paneth cells.

          The adult mouse intestine contains an intricate vascular network. The factors that control development of this network are poorly understood. Quantitative three-dimensional imaging studies revealed that a plexus of branched interconnected vessels developed in small intestinal villi during the period of postnatal development that coincides with assembly of a complex society of indigenous gut microorganisms (microbiota). To investigate the impact of this environmental transition on vascular development, we compared the capillary networks of germ-free mice with those of ex-germ-free animals colonized during or after completion of postnatal gut development. Adult germ-free mice had arrested capillary network formation. The developmental program can be restarted and completed within 10 days after colonization with a complete microbiota harvested from conventionally raised mice, or with Bacteroides thetaiotaomicron, a prominent inhabitant of the normal mouse/human gut. Paneth cells in the intestinal epithelium secrete antibacterial peptides that affect luminal microbial ecology. Comparisons of germ-free and B. thetaiotaomicron-colonized transgenic mice lacking Paneth cells established that microbial regulation of angiogenesis depends on this lineage. These findings reveal a previously unappreciated mechanism of postnatal animal development, where microbes colonizing a mucosal surface are assigned responsibility for regulating elaboration of the underlying microvasculature by signaling through a bacteria-sensing epithelial cell.
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            Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease.

            Several liver disorders result from perturbations in the metabolism of hepatocytes, and their underlying mechanisms can be outlined through the use of genome-scale metabolic models (GEMs). Here we reconstruct a consensus GEM for hepatocytes, which we call iHepatocytes2322, that extends previous models by including an extensive description of lipid metabolism. We build iHepatocytes2322 using Human Metabolic Reaction 2.0 database and proteomics data in Human Protein Atlas, which experimentally validates the incorporated reactions. The reconstruction process enables improved annotation of the proteomics data using the network centric view of iHepatocytes2322. We then use iHepatocytes2322 to analyse transcriptomics data obtained from patients with non-alcoholic fatty liver disease. We show that blood concentrations of chondroitin and heparan sulphates are suitable for diagnosing non-alcoholic steatohepatitis and for the staging of non-alcoholic fatty liver disease. Furthermore, we observe serine deficiency in patients with NASH and identify PSPH, SHMT1 and BCAT1 as potential therapeutic targets for the treatment of non-alcoholic steatohepatitis.
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              Plasma metabolomic profile in nonalcoholic fatty liver disease.

              The plasma profile of subjects with nonalcoholic fatty liver disease (NAFLD), steatosis, and steatohepatitis (NASH) was examined using an untargeted global metabolomic analysis to identify specific disease-related patterns and to identify potential noninvasive biomarkers. Plasma samples were obtained after an overnight fast from histologically confirmed nondiabetic subjects with hepatic steatosis (n = 11) or NASH (n = 24) and were compared with healthy, age- and sex-matched controls (n = 25). Subjects with NAFLD were obese, were insulin resistant, and had higher plasma concentrations of homocysteine and total cysteine and lower plasma concentrations of total glutathione. Metabolomic analysis showed markedly higher levels of glycocholate, taurocholate, and glycochenodeoxycholate in subjects with NAFLD. Plasma concentrations of long-chain fatty acids were lower and concentrations of free carnitine, butyrylcarnitine, and methylbutyrylcarnitine were higher in NASH. Several glutamyl dipeptides were higher whereas cysteine-glutathione levels were lower in NASH and steatosis. Other changes included higher branched-chain amino acids, phosphocholine, carbohydrates (glucose, mannose), lactate, pyruvate, and several unknown metabolites. Random forest analysis and recursive partitioning of the metabolomic data could separate healthy subjects from NAFLD with an error rate of approximately 8% and separate NASH from healthy controls with an error rate of 4%. Hepatic steatosis and steatohepatitis could not be separated using the metabolomic profile. Plasma metabolomic analysis revealed marked changes in bile salts and in biochemicals related to glutathione in subjects with NAFLD. Statistical analysis identified a panel of biomarkers that could effectively separate healthy controls from NAFLD and healthy controls from NASH. These biomarkers can potentially be used to follow response to therapeutic interventions. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                msb
                Molecular Systems Biology
                John Wiley & Sons, Ltd (Chichester, UK )
                1744-4292
                1744-4292
                October 2015
                16 October 2015
                : 11
                : 10
                : 834
                Affiliations
                [1 ]Department of Biology and Biological Engineering, Chalmers University of Technology Gothenburg, Sweden
                [2 ]Science for Life Laboratory, KTH - Royal Institute of Technology Stockholm, Sweden
                [3 ]Department of Molecular and Clinical Medicine, Wallenberg Laboratory, University of Gothenburg Gothenburg, Sweden
                [4 ]Novo Nordisk Foundation Center for Basic Metabolic Research, Section for Metabolic Receptology and Enteroendocrinology, Faculty of Health Sciences, University of Copenhagen Copenhagen, Denmark
                Author notes
                *Corresponding author. Tel: +46 31 772 3140; Fax: +46 31 772 3801; E-mail: adilm@ 123456scilifelab.se

                Subject Categories Genome-Scale & Integrative Biology; Metabolism; Microbiology, Virology & Host Pathogen Interaction

                [†]

                These authors contributed equally to this work

                Article
                10.15252/msb.20156487
                4631205
                26475342
                4478bb77-782e-45c8-bf80-59bb527e7bf8
                © 2015 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 August 2015
                : 23 September 2015
                : 25 September 2015
                Categories
                Articles

                Quantitative & Systems biology
                genome-scale metabolic models,germ-free mice,glutathione metabolism,metabolomics,transcriptomics

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