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Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework

The gut microbiota is well known to affect host metabolic phenotypes. The systemic effects of the gut microbiota on host metabolism are generally evaluated via the comparison of germfree and conventional mice, which is impossible to perform for humans. Hence, it remains difficult to determine the im...

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Autores principales: Heinken, Almut, Thiele, Ines
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615372/
https://www.ncbi.nlm.nih.gov/pubmed/25901891
http://dx.doi.org/10.1080/19490976.2015.1023494
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author Heinken, Almut
Thiele, Ines
author_facet Heinken, Almut
Thiele, Ines
author_sort Heinken, Almut
collection PubMed
description The gut microbiota is well known to affect host metabolic phenotypes. The systemic effects of the gut microbiota on host metabolism are generally evaluated via the comparison of germfree and conventional mice, which is impossible to perform for humans. Hence, it remains difficult to determine the impact of the gut microbiota on human metabolic phenotypes. We demonstrate that a constraint-based modeling framework that simulates “germfree” and “ex-germfree” human individuals can partially fill this gap and allow for in silico predictions of systemic human-microbial co-metabolism. To this end, we constructed the first constraint-based host-microbial community model, comprising the most comprehensive model of human metabolism and 11 manually curated, validated metabolic models of commensals, probiotics, pathogens, and opportunistic pathogens. We used this host-microbiota model to predict potential metabolic host-microbe interactions under 4 in silico dietary regimes. Our model predicts that gut microbes secrete numerous health-relevant metabolites into the lumen, thereby modulating the molecular composition of the body fluid metabolome. Our key results include the following: 1. Replacing a commensal community with pathogens caused a loss of important host metabolic functions. 2. The gut microbiota can produce important precursors of host hormone synthesis and thus serves as an endocrine organ. 3. The synthesis of important neurotransmitters is elevated in the presence of the gut microbiota. 4. Gut microbes contribute essential precursors for glutathione, taurine, and leukotrienes. This computational modeling framework provides novel insight into complex metabolic host-microbiota interactions and can serve as a powerful tool with which to generate novel, non-obvious hypotheses regarding host-microbe co-metabolism.
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spelling pubmed-46153722016-02-03 Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework Heinken, Almut Thiele, Ines Gut Microbes Research Papers The gut microbiota is well known to affect host metabolic phenotypes. The systemic effects of the gut microbiota on host metabolism are generally evaluated via the comparison of germfree and conventional mice, which is impossible to perform for humans. Hence, it remains difficult to determine the impact of the gut microbiota on human metabolic phenotypes. We demonstrate that a constraint-based modeling framework that simulates “germfree” and “ex-germfree” human individuals can partially fill this gap and allow for in silico predictions of systemic human-microbial co-metabolism. To this end, we constructed the first constraint-based host-microbial community model, comprising the most comprehensive model of human metabolism and 11 manually curated, validated metabolic models of commensals, probiotics, pathogens, and opportunistic pathogens. We used this host-microbiota model to predict potential metabolic host-microbe interactions under 4 in silico dietary regimes. Our model predicts that gut microbes secrete numerous health-relevant metabolites into the lumen, thereby modulating the molecular composition of the body fluid metabolome. Our key results include the following: 1. Replacing a commensal community with pathogens caused a loss of important host metabolic functions. 2. The gut microbiota can produce important precursors of host hormone synthesis and thus serves as an endocrine organ. 3. The synthesis of important neurotransmitters is elevated in the presence of the gut microbiota. 4. Gut microbes contribute essential precursors for glutathione, taurine, and leukotrienes. This computational modeling framework provides novel insight into complex metabolic host-microbiota interactions and can serve as a powerful tool with which to generate novel, non-obvious hypotheses regarding host-microbe co-metabolism. Taylor & Francis 2015-04-22 /pmc/articles/PMC4615372/ /pubmed/25901891 http://dx.doi.org/10.1080/19490976.2015.1023494 Text en © 2015 The Author(s). Published with license by Taylor & Francis Group, LLC http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted.
spellingShingle Research Papers
Heinken, Almut
Thiele, Ines
Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
title Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
title_full Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
title_fullStr Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
title_full_unstemmed Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
title_short Systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
title_sort systematic prediction of health-relevant human-microbial co-metabolism through a computational framework
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615372/
https://www.ncbi.nlm.nih.gov/pubmed/25901891
http://dx.doi.org/10.1080/19490976.2015.1023494
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