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Application of Ecological Network Theory to the Human Microbiome
In healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pa...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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Hindawi Publishing Corporation
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2648623/ https://www.ncbi.nlm.nih.gov/pubmed/19259330 http://dx.doi.org/10.1155/2008/839501 |
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author | Foster, James A. Krone, Stephen M. Forney, Larry J. |
author_facet | Foster, James A. Krone, Stephen M. Forney, Larry J. |
author_sort | Foster, James A. |
collection | PubMed |
description | In healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pathogen invasions or causing other clinically relevant problems. Some diseases, such as bacterial vaginosis, have exactly this sort of community etiology. Mathematical network theory is ideal for studying the ecological networks of interacting species that comprise the human microbiome. Theoretical networks require little consortia specific data to provide insight into both normal and disturbed microbial community functions, but it is easy to incorporate additional empirical data as it becomes available. We argue that understanding some diseases, such as bacterial vaginosis, requires a shift of focus from individual bacteria to (mathematical) networks of interacting populations, and that known emergent properties of these networks will provide insights that would be otherwise elusive. |
format | Text |
id | pubmed-2648623 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-26486232009-03-03 Application of Ecological Network Theory to the Human Microbiome Foster, James A. Krone, Stephen M. Forney, Larry J. Interdiscip Perspect Infect Dis Review Article In healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pathogen invasions or causing other clinically relevant problems. Some diseases, such as bacterial vaginosis, have exactly this sort of community etiology. Mathematical network theory is ideal for studying the ecological networks of interacting species that comprise the human microbiome. Theoretical networks require little consortia specific data to provide insight into both normal and disturbed microbial community functions, but it is easy to incorporate additional empirical data as it becomes available. We argue that understanding some diseases, such as bacterial vaginosis, requires a shift of focus from individual bacteria to (mathematical) networks of interacting populations, and that known emergent properties of these networks will provide insights that would be otherwise elusive. Hindawi Publishing Corporation 2008 2008-10-29 /pmc/articles/PMC2648623/ /pubmed/19259330 http://dx.doi.org/10.1155/2008/839501 Text en Copyright © 2008 James A. Foster et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Foster, James A. Krone, Stephen M. Forney, Larry J. Application of Ecological Network Theory to the Human Microbiome |
title | Application of Ecological Network Theory to the Human Microbiome |
title_full | Application of Ecological Network Theory to the Human Microbiome |
title_fullStr | Application of Ecological Network Theory to the Human Microbiome |
title_full_unstemmed | Application of Ecological Network Theory to the Human Microbiome |
title_short | Application of Ecological Network Theory to the Human Microbiome |
title_sort | application of ecological network theory to the human microbiome |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2648623/ https://www.ncbi.nlm.nih.gov/pubmed/19259330 http://dx.doi.org/10.1155/2008/839501 |
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