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
Department of Twin Research & Genetic Epidemiology, King's College London, London, United Kingdom.
University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, Netherlands.
PeerJ. 2018 Feb 7;6:e4303. doi: 10.7717/peerj.4303. eCollection 2018.
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.
肠道微生物群中的微生物基于共享的生态位特化以及各个分类群之间的特定相互作用形成亚群落。定义这些群落的微生物间关系可从多个样本中分类群的共现情况推断出来。在此，我们提出一种方法来识别不同肠道微生物群共现网络中的可比群落，并通过比较三个地理上不同人群的肠道微生物群群落结构来展示其用途。我们整合了来自2764名英国人、1023名荷兰人和639名以色列人的肠道微生物群概况，推导了它们的操作分类单元之间的共现网络，并在其中检测出可比群落。比较不同人群时，我们发现数据集之间的群落结构比随机预期的要显著更相似。在各数据集中映射群落时，我们还表明群落在不同人群中与宿主表型可能具有相似的关联。这项研究表明，肠道微生物群中的群落结构在不同人群中是稳定的，并描述了一种有助于以群落为中心进行比较微生物组分析的新方法。
