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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.
Afiliación
  • Jackson MA; Department of Twin Research & Genetic Epidemiology, King's College London, London, United Kingdom.
  • Bonder MJ; University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands.
  • Kuncheva Z; Department of Mathematics, Imperial College London, London, United Kingdom.
  • Zierer J; Department of Twin Research & Genetic Epidemiology, King's College London, London, United Kingdom.
  • Fu J; Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.
  • Kurilshikov A; University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands.
  • Wijmenga C; University Medical Center Groningen, Department of Pediatrics, University of Groningen, Groningen, Netherlands.
  • Zhernakova A; University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands.
  • Bell JT; University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands.
  • Spector TD; K.G. Jebsen Coeliac Disease Research Centre, Department of Immunology, University of Oslo, Oslo, Norway.
  • Steves CJ; University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands.
PeerJ ; 6: e4303, 2018.
Article en En | MEDLINE | ID: mdl-29441232
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: PeerJ Año: 2018 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: PeerJ Año: 2018 Tipo del documento: Article País de afiliación: Reino Unido
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