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      An integrative analysis of tissue-specific transcriptomic and metabolomic responses to short-term dietary methionine restriction in mice

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          Abstract

          Dietary methionine restriction (MR) produces a coordinated series of transcriptional responses in peripheral tissues that limit fat accretion, remodel lipid metabolism in liver and adipose tissue, and improve overall insulin sensitivity. Hepatic sensing of reduced methionine leads to induction and release of fibroblast growth factor 21 (FGF21), which acts centrally to increase sympathetic tone and activate thermogenesis in adipose tissue. FGF21 also has direct effects in adipose to enhance glucose uptake and oxidation. However, an understanding of how the liver senses and translates reduced dietary methionine into these transcriptional programs remains elusive. A comprehensive systems biology approach integrating transcriptomic and metabolomic readouts in MR-treated mice confirmed that three interconnected mechanisms (fatty acid transport and oxidation, tricarboxylic acid cycle, and oxidative phosphorylation) were activated in MR-treated inguinal adipose tissue. In contrast, the effects of MR in liver involved up-regulation of anti-oxidant responses driven by the nuclear factor, erythroid 2 like 2 transcription factor, NFE2L2. Metabolomic analysis provided evidence for redox imbalance, stemming from large reductions in the master anti-oxidant molecule glutathione coupled with disproportionate increases in ophthalmate and its precursors, glutamate and 2-aminobutyrate. Thus, cysteine and its downstream product, glutathione, emerge as key early hepatic signaling molecules linking dietary MR to its metabolic phenotype.

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              Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption.

              Metabolomics is an emerging tool that can be used to gain insights into cellular and physiological responses. Here we present a metabolome differential display method based on capillary electrophoresis time-of-flight mass spectrometry to profile liver metabolites following acetaminophen-induced hepatotoxicity. We globally detected 1,859 peaks in mouse liver extracts and highlighted multiple changes in metabolite levels, including an activation of the ophthalmate biosynthesis pathway. We confirmed that ophthalmate was synthesized from 2-aminobutyrate through consecutive reactions with gamma-glutamylcysteine and glutathione synthetase. Changes in ophthalmate level in mouse serum and liver extracts were closely correlated and ophthalmate levels increased significantly in conjunction with glutathione consumption. Overall, our results provide a broad picture of hepatic metabolite changes following acetaminophen treatment. In addition, we specifically found that serum ophthalmate is a sensitive indicator of hepatic GSH depletion, and may be a new biomarker for oxidative stress. Our method can thus pinpoint specific metabolite changes and provide insights into the perturbation of metabolic pathways on a large scale and serve as a powerful new tool for discovering low molecular weight biomarkers.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 May 2017
                2017
                : 12
                : 5
                : e0177513
                Affiliations
                [1 ]Laboratory of Computational Biology, Pennington Biomedical Research Center, Baton Rouge, LA, United States of America
                [2 ]Laboratory of Nutrient Sensing and Adipocyte Signaling, Pennington Biomedical Research Center, Baton Rouge, LA, United States of America
                [3 ]Program in Cardiovascular & Metabolic Disorders and Centre for Computational Biology, Duke-NUS Graduate Medical School, Singapore
                [4 ]Department of Nutrition, Georgia State University, Atlanta, GA, United States of America
                INRA, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: DW TWG.

                • Data curation: SG LAF TWG.

                • Formal analysis: SG LAF.

                • Funding acquisition: DW TWG.

                • Investigation: DW KPS.

                • Methodology: DW KPS.

                • Project administration: TWG.

                • Resources: TWG.

                • Software: SG.

                • Supervision: TWG.

                • Validation: LAF DW KPS.

                • Visualization: SG LAF.

                • Writing – original draft: SG.

                • Writing – review & editing: SG LAF TWG.

                Author information
                http://orcid.org/0000-0001-7125-7995
                Article
                PONE-D-17-09446
                10.1371/journal.pone.0177513
                5433721
                28520765
                f663c18e-9583-45cf-b110-55705227295c
                © 2017 Ghosh et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 March 2017
                : 29 April 2017
                Page count
                Figures: 8, Tables: 4, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: 2RO1 DK 096311
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000041, American Diabetes Association;
                Award ID: 1-12-BS-58
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000041, American Diabetes Association;
                Award ID: 7-13-MI-05
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: 3P30 GM118430
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: 3P30 DK072476
                Funded by: funder-id http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: 1F32 DK098918
                Award Recipient :
                This work was supported in part by American Diabetes Association 1-12-BS-58 (TWG), National Institutes of Health DK-096311 (TWG), American Diabetes Association 7-13-MI-05 (TWG), National Institutes of Health 1F32DK098918-01 (DW). SG was supported by funding from the National Medical Research Council and Ministry of Health, Singapore. This work also made use of the Genomics core facilities supported by National Institutes of Health 3P30-GM118430 (TWG) and National Institutes of Health 3P30 DK072476.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolic Pathways
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Biochemistry
                Lipids
                Fatty Acids
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Amino Acid Metabolism
                Physical Sciences
                Chemistry
                Chemical Compounds
                Organic Compounds
                Amino Acids
                Sulfur Containing Amino Acids
                Methionine
                Physical Sciences
                Chemistry
                Organic Chemistry
                Organic Compounds
                Amino Acids
                Sulfur Containing Amino Acids
                Methionine
                Biology and Life Sciences
                Biochemistry
                Proteins
                Amino Acids
                Sulfur Containing Amino Acids
                Methionine
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolomics
                Biology and Life Sciences
                Biochemistry
                Peptides
                Glutathione
                Custom metadata
                SAGE data are available from GEO and under accession number GSE92463 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE92463).

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                Uncategorized

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