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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2015
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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. |
format | Online Article Text |
id | pubmed-4615372 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
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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