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

Matthew Jackson(King's College London), Marc Jan Bonder(University Medical Center Groningen), Zhana Kuncheva(Imperial College London), Jonas Zierer(King's College London), Jingyuan Fu(University Medical Center Groningen), Alexander Kurilshikov(University Medical Center Groningen), Cisca Wijmenga(University Medical Center Groningen), Alexandra Zhernakova(University Medical Center Groningen), Jordana T. Bell(King's College London), Tim D. Spector(King's College London), Claire J. Steves(King's College London)
PeerJ
February 7, 2018
Cited by 63Open Access
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Abstract

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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