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从环境和全基因组序列数据中发现共存微生物的全球网络。

A global network of coexisting microbes from environmental and whole-genome sequence data.

机构信息

Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, CH-8057 Zürich, Switzerland.

出版信息

Genome Res. 2010 Jul;20(7):947-59. doi: 10.1101/gr.104521.109. Epub 2010 May 10.

Abstract

Microbes are the most abundant and diverse organisms on Earth. In contrast to macroscopic organisms, their environmental preferences and ecological interdependencies remain difficult to assess, requiring laborious molecular surveys at diverse sampling sites. Here, we present a global meta-analysis of previously sampled microbial lineages in the environment. We grouped publicly available 16S ribosomal RNA sequences into operational taxonomic units at various levels of resolution and systematically searched these for co-occurrence across environments. Naturally occurring microbes, indeed, exhibited numerous, significant interlineage associations. These ranged from relatively specific groupings encompassing only a few lineages, to larger assemblages of microbes with shared habitat preferences. Many of the coexisting lineages were phylogenetically closely related, but a significant number of distant associations were observed as well. The increased availability of completely sequenced genomes allowed us, for the first time, to search for genomic correlates of such ecological associations. Genomes from coexisting microbes tended to be more similar than expected by chance, both with respect to pathway content and genome size, and outliers from these trends are discussed. We hypothesize that groupings of lineages are often ancient, and that they may have significantly impacted on genome evolution.

摘要

微生物是地球上最丰富和最多样化的生物。与宏观生物相比,它们的环境偏好和生态相互依存关系仍然难以评估,需要在不同的采样地点进行繁琐的分子调查。在这里,我们对环境中以前采样的微生物谱系进行了全球元分析。我们将公开可用的 16S 核糖体 RNA 序列按各种分辨率水平分组为操作分类单位,并系统地在这些分类单位中搜索跨环境的共现情况。事实上,自然存在的微生物表现出许多显著的谱系间关联。这些关联范围从仅包含少数几个谱系的相对特定分组,到具有共享生境偏好的较大微生物组合。许多共存的谱系在系统发育上是密切相关的,但也观察到了大量的远缘关联。完全测序基因组的可用性增加,使我们能够首次搜索此类生态关联的基因组相关性。共存微生物的基因组往往比随机预期更相似,无论是在途径内容还是基因组大小方面,并且还讨论了这些趋势的异常值。我们假设谱系的分组通常是古老的,它们可能对基因组进化产生了重大影响。

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