Coutinho Felipe H, Meirelles Pedro M, Moreira Ana Paula B, Paranhos Rodolfo P, Dutilh Bas E, Thompson Fabiano L
Universidade Federal do Rio de Janeiro (UFRJ)/Instituto de Biologia (IB) , Rio de Janeiro , Brazil ; Radboud University Medical Centre, Radboud Institute for Molecular Life Sciences, Centre for Molecular and Biomolecular Informatics (CMBI) , Nijmegen , The Netherlands.
Universidade Federal do Rio de Janeiro (UFRJ)/Instituto de Biologia (IB) , Rio de Janeiro , Brazil.
PeerJ. 2015 Jun 16;3:e1008. doi: 10.7717/peerj.1008. eCollection 2015.
Associations between microorganisms occur extensively throughout Earth's oceans. Understanding how microbial communities are assembled and how the presence or absence of species is related to that of others are central goals of microbial ecology. Here, we investigate co-occurrence associations between marine prokaryotes by combining 180 new and publicly available metagenomic datasets from different oceans in a large-scale meta-analysis. A co-occurrence network was created by calculating correlation scores between the abundances of microorganisms in metagenomes. A total of 1,906 correlations amongst 297 organisms were detected, segregating them into 11 major groups that occupy distinct ecological niches. Additionally, by analyzing the oceanographic parameters measured for a selected number of sampling sites, we characterized the influence of environmental variables over each of these 11 groups. Clustering organisms into groups of taxa that have similar ecology, allowed the detection of several significant correlations that could not be observed for the taxa individually.
微生物之间的关联广泛存在于地球的海洋之中。了解微生物群落是如何组装的，以及物种的存在与否如何与其他物种相关联，是微生物生态学的核心目标。在此，我们通过大规模荟萃分析，结合来自不同海洋的180个新的公开宏基因组数据集，研究海洋原核生物之间的共现关联。通过计算宏基因组中微生物丰度之间的相关分数，创建了一个共现网络。在297种生物之间总共检测到1906个相关性，将它们分为占据不同生态位的11个主要组。此外，通过分析为选定数量的采样点测量的海洋学参数，我们表征了环境变量对这11个组中每一组的影响。将生物聚类为具有相似生态学的分类群组，使得能够检测到几个单独分类群无法观察到的显著相关性。
