分歧(语言学)
微生物种群生物学
微生物群
生物
生态系统
集合(抽象数据类型)
生态学
群落结构
多样性(政治)
生化工程
进化生物学
计算生物学
计算机科学
生物信息学
遗传学
工程类
社会学
细菌
哲学
语言学
人类学
程序设计语言
作者
Michael Silverstein,Jennifer Bhatnagar,Daniel Segrè
标识
DOI:10.1101/2023.08.03.551516
摘要
Microbial communities are shaped by the metabolites available in their environment, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. To this end, we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the diverse assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively smaller ones, is necessary and sufficient to recapitulate all of our experimental observations. In addition to pointing to a fundamental principle of community assembly, the divergence-complexity effect has important implications for microbiome engineering applications, as it can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions.
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