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微生物的基因组组成和系统发育可预测它们在环境中的共生情况。

Genome composition and phylogeny of microbes predict their co-occurrence in the environment.

作者信息

Kamneva Olga K

机构信息

Department of Biology, Stanford University, Stanford, California, United States of America.

出版信息

PLoS Comput Biol. 2017 Feb 2;13(2):e1005366. doi: 10.1371/journal.pcbi.1005366. eCollection 2017 Feb.

Abstract

The genomic information of microbes is a major determinant of their phenotypic properties, yet it is largely unknown to what extent ecological associations between different species can be explained by their genome composition. To bridge this gap, this study introduces two new genome-wide pairwise measures of microbe-microbe interaction. The first (genome content similarity index) quantifies similarity in genome composition between two microbes, while the second (microbe-microbe functional association index) summarizes the topology of a protein functional association network built for a given pair of microbes and quantifies the fraction of network edges crossing organismal boundaries. These new indices are then used to predict co-occurrence between reference genomes from two 16S-based ecological datasets, accounting for phylogenetic relatedness of the taxa. Phylogenetic relatedness was found to be a strong predictor of ecological associations between microbes which explains about 10% of variance in co-occurrence data, but genome composition was found to be a strong predictor as well, it explains up to 4% the variance in co-occurrence when all genomic-based indices are used in combination, even after accounting for evolutionary relationships between the species. On their own, the metrics proposed here explain a larger proportion of variance than previously reported more complex methods that rely on metabolic network comparisons. In summary, results of this study indicate that microbial genomes do indeed contain detectable signal of organismal ecology, and the methods described in the paper can be used to improve mechanistic understanding of microbe-microbe interactions.

摘要

微生物的基因组信息是其表型特性的主要决定因素,然而,不同物种之间的生态关联在多大程度上可以由它们的基因组组成来解释,这在很大程度上仍是未知的。为了弥补这一差距,本研究引入了两种新的全基因组微生物-微生物相互作用的成对测量方法。第一种方法(基因组内容相似性指数)量化了两种微生物之间基因组组成的相似性,而第二种方法(微生物-微生物功能关联指数)总结了为给定的一对微生物构建的蛋白质功能关联网络的拓扑结构,并量化了跨越生物体边界的网络边的比例。然后,这些新指数被用于预测来自两个基于16S的生态数据集的参考基因组之间的共现情况,同时考虑到分类群的系统发育相关性。研究发现,系统发育相关性是微生物之间生态关联的一个强有力的预测指标,它解释了共现数据中约10%的方差,但基因组组成也是一个强有力的预测指标,当所有基于基因组的指数结合使用时,即使在考虑了物种之间的进化关系之后,它也能解释高达4%的共现方差。就其本身而言,本文提出的指标比以前报道的依赖代谢网络比较的更复杂方法解释的方差比例更大。总之,本研究结果表明,微生物基因组确实包含可检测到的生物体生态学信号,并且本文所述方法可用于提高对微生物-微生物相互作用的机制理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f50/5313232/f68eb1ccbbb7/pcbi.1005366.g001.jpg

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