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

M Mikko Kivikoski (Department of Computer Science, University of Helsinki) J Johannes Cairns (Department of Computer Science, University of Helsinki) S Shane L. Hogle (Department of Biology, University of Turku) S Sanna Pausio (Department of Biology, University of Turku) L Lutz Becks (Aquatic Ecology and Evolution, Department of Biology, University of Konstanz) V Ville Mustonen (Department of Computer Science, University of Helsinki) T Teppo Hiltunen (Department of Biology, University of Turku)

Abstract

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.

Article Details

Volume / Issue Vol. 123, Issue 22
Published June 02, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (7)

M

Mikko Kivikoski

Department of Computer Science, University of Helsinki

J

Johannes Cairns

Department of Computer Science, University of Helsinki

S

Shane L. Hogle

Department of Biology, University of Turku

S

Sanna Pausio

Department of Biology, University of Turku

L

Lutz Becks

Aquatic Ecology and Evolution, Department of Biology, University of Konstanz

V

Ville Mustonen

Department of Computer Science, University of Helsinki

T

Teppo Hiltunen

Department of Biology, University of Turku