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Detection of stable community structures within gut microbiota co-occurrence networks from different human populations

Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an app...

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Autores principales: Jackson, Matthew A., Bonder, Marc Jan, Kuncheva, Zhana, Zierer, Jonas, Fu, Jingyuan, Kurilshikov, Alexander, Wijmenga, Cisca, Zhernakova, Alexandra, Bell, Jordana T., Spector, Tim D., Steves, Claire J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807925/
https://www.ncbi.nlm.nih.gov/pubmed/29441232
http://dx.doi.org/10.7717/peerj.4303
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author Jackson, Matthew A.
Bonder, Marc Jan
Kuncheva, Zhana
Zierer, Jonas
Fu, Jingyuan
Kurilshikov, Alexander
Wijmenga, Cisca
Zhernakova, Alexandra
Bell, Jordana T.
Spector, Tim D.
Steves, Claire J.
author_facet Jackson, Matthew A.
Bonder, Marc Jan
Kuncheva, Zhana
Zierer, Jonas
Fu, Jingyuan
Kurilshikov, Alexander
Wijmenga, Cisca
Zhernakova, Alexandra
Bell, Jordana T.
Spector, Tim D.
Steves, Claire J.
author_sort Jackson, Matthew A.
collection PubMed
description Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses.
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spelling pubmed-58079252018-02-13 Detection of stable community structures within gut microbiota co-occurrence networks from different human populations Jackson, Matthew A. Bonder, Marc Jan Kuncheva, Zhana Zierer, Jonas Fu, Jingyuan Kurilshikov, Alexander Wijmenga, Cisca Zhernakova, Alexandra Bell, Jordana T. Spector, Tim D. Steves, Claire J. PeerJ Bioinformatics Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses. PeerJ Inc. 2018-02-07 /pmc/articles/PMC5807925/ /pubmed/29441232 http://dx.doi.org/10.7717/peerj.4303 Text en ©2018 Jackson et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Jackson, Matthew A.
Bonder, Marc Jan
Kuncheva, Zhana
Zierer, Jonas
Fu, Jingyuan
Kurilshikov, Alexander
Wijmenga, Cisca
Zhernakova, Alexandra
Bell, Jordana T.
Spector, Tim D.
Steves, Claire J.
Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
title Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
title_full Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
title_fullStr Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
title_full_unstemmed Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
title_short Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
title_sort detection of stable community structures within gut microbiota co-occurrence networks from different human populations
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807925/
https://www.ncbi.nlm.nih.gov/pubmed/29441232
http://dx.doi.org/10.7717/peerj.4303
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