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A phylogenetic model for the recruitment of species into microbial communities and application to studies of the human microbiome

机译:一种系统发育模型,用于募集种类分为微生物群落及其微生物组研究的应用

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Understanding when and why new species are recruited into microbial communities is a formidable problem with implications for managing microbial systems, for instance by helping us better understand whether a probiotic or pathogen would be expected to colonize a human microbiome. Much theory in microbial temporal dynamics is focused on how phylogenetic relationships between microbes impact the order in which those microbes are recruited; for example, species that are closely related may competitively exclude each other. However, several recent human microbiome studies have observed closely related bacteria being recruited into microbial communities in short succession, suggesting that microbial community assembly is historically contingent, but competitive exclusion of close relatives may not be important. To address this, we developed a mathematical model that describes the order in which new species are detected in microbial communities over time within a phylogenetic framework. We use our model to test three hypothetical assembly modes: underdispersion (species recruitment is more likely if a close relative was previously detected), overdispersion (recruitment is more likely if a close relative has not been previously detected), and the neutral model (recruitment likelihood is not related to phylogenetic relationships among species). We applied our model to longitudinal human microbiome data, and found that for the individuals we analyzed, the human microbiome generally follows the underdispersion (i.e., nepotism) hypothesis. Exceptions were oral communities and the fecal communities of two infants that had undergone heavy antibiotic treatment. None of the datasets we analyzed showed statistically significant phylogenetic overdispersion.
机译:了解新物种征集进入微生物社区的时间和为何是对管理微生物系统的影响是一个强大的问题,例如通过帮助我们更好地了解益生菌或病原体是否会被殖民调节人类微生物组。微生物时间动态的许多理论集中在微生物之间的系统发育关系如何影响那些微生物的顺序;例如,密切相关的物种可以竞争地区彼此排除。然而,最近的几种人类微生物组研究观察到密切相关的细菌在短时间内招募到微生物社区中的微生物社区,这表明微生物群落大会在历史上占有目的,但近亲排斥的近亲可能并不重要。为了解决这一点,我们开发了一种数学模型,该模型描述了在系统发育框架内随时间在微生物群中检测到新物种的顺序。我们使用我们的模型来测试三种假设的装配模式:UNDERPERSION(如果先前检测到近亲相对),如果先前未被检测到紧密相对,则更有可能更有可能更有可能),以及中立模型(招聘)可能性与物种之间的系统发育关系无关。我们将模型应用于纵向人类微生物组数据,并发现对于我们分析的个体,人类微生物组通常遵循下分层(即,射出)假设。例外是口头社区和两名婴儿的粪便群落经历了重质抗生素治疗。我们分析的数据集没有显示出统计学上显着的系统发育过度分散。

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