Evolution induced state shifts in a long-term microbial community experiment

• 成果类型: Article
• 署名作者: Kivikoski, Mikko; Cairns, Johannes; Hogle, Shane L.; Pausio, Sanna; Becks, Lutz; Mustonen, Ville; Hiltunen, Teppo
• 署名单位: University of Helsinki; University of Helsinki; University of Turku; University of Turku; University of Konstanz
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.2533269123
• 发表日期: 2026-06-02
• 页码: e2533269123
• 关键词: ECO-EVOLUTIONARY DYNAMICS; experimental evolution; microbial communities; state shifts; DYNAMICS; adaptation; resistance; mutations; MODEL; cost

摘要

Biological communities are complex, dynamic systems that underpin ecosystem functionality, yet their long-term dynamics and predictability remain poorly understood. Understanding how Darwinian evolution shapes these systems through eco-evolutionary feedback is a central challenge in ecology and evolution. Experimental studies using simplified microbial assemblages have yielded important insights into the ecological principles governing community states. However, an important knowledge gap is how selection within member species drives changes of community state in multispecies systems. Here, we present a four-year evolution experiment involving a 23-species synthetic bacterial community propagated in two environments: a control medium and the same medium supplemented with the antibiotic streptomycin. Through combined analyses of community composition and genome evolution, we quantified the temporal changes in species abundances and the evolutionary trajectories of individual community members. The extended duration of the experiment enabled the detection of adaptive mutations and community state shifts that occur only over long evolutionary timescales. We show that community dynamics are environment dependent and reproducible across replicates and that evolution of streptomycin resistance in a previously streptomycin-sensitive species on its own can induce abrupt community state shifts. Our results provide a direct demonstration of eco-evolutionary feedbacks within a multispecies community, revealing how a single adaptive mutation can reorganize complex ecological networks.