Metabolic complexity drives divergence in microbial communities

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 novel 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 simpler ones which then participate in cross-feeding between community members, 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.微生物群落（microbial communities）的组成由环境中可获得的代谢物（metabolites）所塑造，但调控不同群落在任意给定条件下趋向汇聚抑或分化的核心原理仍未明确，这为微生物组工程（microbiome engineering）的可行性带来了根本性的科学疑问。为此，我们针对一组在代谢复杂度逐步递增的实验室培养条件下生长的天然微生物群落，开展了纵向群落组装动态的研究。我们发现，在代谢简单的培养环境中，不同微生物群落的组成会逐渐趋于一致；但随着环境代谢复杂度提升，群落组成反而出现分化——我们将这一全新现象命名为分化-复杂度效应（divergence-complexity effect）。对这些群落的比较分析显示，该分化现象由群落多样性以及一类能够降解复杂代谢物的特化类群（specialist taxa）的多样组合共同驱动。群落动态的生态学模型表明，代谢本身的层级化结构——即复杂分子经酶促降解为逐步简化的中间产物，随后参与群落成员间的互养（cross-feeding）过程——足以且必须重现我们所有的实验观测结果。除了揭示群落组装的一项核心原理之外，分化-复杂度效应对微生物组工程应用亦具有重要价值：它可帮助我们识别能够维持多种群落状态的环境，从而助力目标生态系统功能的筛选与构建。