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Understanding the host-microbe interactions using metabolic modeling
The human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associa...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7819158/ https://www.ncbi.nlm.nih.gov/pubmed/33472685 http://dx.doi.org/10.1186/s40168-020-00955-1 |
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author | Jansma, Jack El Aidy, Sahar |
author_facet | Jansma, Jack El Aidy, Sahar |
author_sort | Jansma, Jack |
collection | PubMed |
description | The human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using in silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-020-00955-1. |
format | Online Article Text |
id | pubmed-7819158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78191582021-01-22 Understanding the host-microbe interactions using metabolic modeling Jansma, Jack El Aidy, Sahar Microbiome Review The human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using in silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-020-00955-1. BioMed Central 2021-01-20 /pmc/articles/PMC7819158/ /pubmed/33472685 http://dx.doi.org/10.1186/s40168-020-00955-1 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Jansma, Jack El Aidy, Sahar Understanding the host-microbe interactions using metabolic modeling |
title | Understanding the host-microbe interactions using metabolic modeling |
title_full | Understanding the host-microbe interactions using metabolic modeling |
title_fullStr | Understanding the host-microbe interactions using metabolic modeling |
title_full_unstemmed | Understanding the host-microbe interactions using metabolic modeling |
title_short | Understanding the host-microbe interactions using metabolic modeling |
title_sort | understanding the host-microbe interactions using metabolic modeling |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7819158/ https://www.ncbi.nlm.nih.gov/pubmed/33472685 http://dx.doi.org/10.1186/s40168-020-00955-1 |
work_keys_str_mv | AT jansmajack understandingthehostmicrobeinteractionsusingmetabolicmodeling AT elaidysahar understandingthehostmicrobeinteractionsusingmetabolicmodeling |