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




Kivikoski, Mikko; Cairns, Johannes; Hogle, Shane L.; Pausio, Sanna; Becks, Lutz; Mustonen, Ville; Hiltunen, Teppo

PublisherNational Academy of Sciences

2026

 Proceedings of the National Academy of Sciences of the United States of America

e2533269123

123

22

0027-8424

1091-6490

DOIhttps://doi.org/10.1073/pnas.2533269123

https://doi.org/10.1073/pnas.2533269123

https://research.utu.fi/converis/portal/detail/Publication/523626051



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.


This study was supported by Finnish Functional Genomics Centre, University of Turku, and Åbo Akademi and Biocenter Finland. We wish to acknowledge CSC—IT Center for Science, Finland, for computational resources.


Last updated on 28/05/2026 07:29:53 AM