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      Personalized whole‐body models integrate metabolism, physiology, and the gut microbiome

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          Abstract

          Comprehensive molecular‐level models of human metabolism have been generated on a cellular level. However, models of whole‐body metabolism have not been established as they require new methodological approaches to integrate molecular and physiological data. We developed a new metabolic network reconstruction approach that used organ‐specific information from literature and omics data to generate two sex‐specific whole‐body metabolic ( WBM) reconstructions. These reconstructions capture the metabolism of 26 organs and six blood cell types. Each WBM reconstruction represents whole‐body organ‐resolved metabolism with over 80,000 biochemical reactions in an anatomically and physiologically consistent manner. We parameterized the WBM reconstructions with physiological, dietary, and metabolomic data. The resulting WBM models could recapitulate known inter‐organ metabolic cycles and energy use. We also illustrate that the WBM models can predict known biomarkers of inherited metabolic diseases in different biofluids. Predictions of basal metabolic rates, by WBM models personalized with physiological data, outperformed current phenomenological models. Finally, integrating microbiome data allowed the exploration of host–microbiome co‐metabolism. Overall, the WBM reconstructions, and their derived computational models, represent an important step toward virtual physiological humans.

          Abstract

          Sex‐specific, whole‐body human metabolic models were developed and constrained with physiological, dietary, and metabolomic data. They recapitulate known whole‐body metabolic functions and enable mechanistic exploration of host‐microbiome co‐metabolism.

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          Most cited references67

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          The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon.

          The microbiome is being characterized by large-scale sequencing efforts, yet it is not known whether it regulates host metabolism in a general versus tissue-specific manner or which bacterial metabolites are important. Here, we demonstrate that microbiota have a strong effect on energy homeostasis in the colon compared to other tissues. This tissue specificity is due to colonocytes utilizing bacterially produced butyrate as their primary energy source. Colonocytes from germfree mice are in an energy-deprived state and exhibit decreased expression of enzymes that catalyze key steps in intermediary metabolism including the TCA cycle. Consequently, there is a marked decrease in NADH/NAD(+), oxidative phosphorylation, and ATP levels, which results in AMPK activation, p27(kip1) phosphorylation, and autophagy. When butyrate is added to germfree colonocytes, it rescues their deficit in mitochondrial respiration and prevents them from undergoing autophagy. The mechanism is due to butyrate acting as an energy source rather than as an HDAC inhibitor. Copyright © 2011 Elsevier Inc. All rights reserved.
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            A protocol for generating a high-quality genome-scale metabolic reconstruction.

            Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.
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              Reorganizing the protein space at the Universal Protein Resource (UniProt)

              The mission of UniProt is to support biological research by providing a freely accessible, stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces. UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. A key development at UniProt is the provision of complete, reference and representative proteomes. UniProt is updated and distributed every 4 weeks and can be accessed online for searches or download at http://www.uniprot.org.
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                Author and article information

                Contributors
                ines.thiele@nuigalway.ie
                ronan.mt.fleming@gmail.com
                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                10.1002/(ISSN)1744-4292
                MSB
                msb
                Molecular Systems Biology
                John Wiley and Sons Inc. (Hoboken )
                1744-4292
                28 May 2020
                May 2020
                : 16
                : 5 ( doiID: 10.1002/msb.v16.5 )
                : e8982
                Affiliations
                [ 1 ] School of Medicine National University of Ireland Galway Ireland
                [ 2 ] Discipline of Microbiology School of Natural Sciences National University of Ireland Galway Ireland
                [ 3 ] APC Microbiome Cork Ireland
                [ 4 ] Luxembourg Centre for Systems Biomedicine University of Luxembourg Esch‐sur‐Alzette Luxembourg
                [ 5 ] Department of Psychiatry and Psychotherapy University Medicine Greifswald Greifswald Germany
                [ 6 ] Division of Analytical Biosciences Leiden Academic Centre for Drug Research Faculty of Science University of Leiden Leiden The Netherlands
                [ 7 ]Present address: Department of Chemical Engineering, and Initiative for Biological Systems Engineering (IBSE) Indian Institute of Technology Chennai India
                Author notes
                [*] [* ] Corresponding author. Tel: +353 91 49 5201; E‐mail: ines.thiele@ 123456nuigalway.ie

                Corresponding author. Tel: +31 71 527 6229; E‐mail: ronan.mt.fleming@ 123456gmail.com

                Author information
                https://orcid.org/0000-0002-8071-7110
                https://orcid.org/0000-0001-6938-8072
                https://orcid.org/0000-0003-1861-0037
                https://orcid.org/0000-0001-5346-9812
                Article
                MSB198982
                10.15252/msb.20198982
                7285886
                32463598
                253cad16-9585-4381-92ef-7ee4cf4f7f27
                © 2020 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 May 2019
                : 18 December 2019
                : 23 December 2019
                Page count
                Figures: 7, Tables: 3, Pages: 24, Words: 19266
                Funding
                Funded by: Fonds National de la Recherche Luxembourg (FNR)
                Award ID: FNR/A12/01
                Award ID: FNR/O16/11402054
                Funded by: National Centre of Excellence in Research (NCER) on Parkinson's disease
                Funded by: EC|Horizon 2020 Framework Programme (H2020)
                Award ID: 668738
                Award ID: 757922
                Categories
                Article
                Articles
                Custom metadata
                2.0
                May 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.3 mode:remove_FC converted:28.05.2020

                Quantitative & Systems biology
                flux balance analysis,human metabolism,metabolic modeling,microbiome,computational biology,metabolism

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