Evolvability of the toxin-adaptation system in yeast

Crises such as starvation pose a serious threat to microbial populations, prompting cells to adopt survival strategies, such as cooperation or competition. Although cooperation among clones is common, recent studies have shown that yeast cells can kill clonal cells under glucose depletion by secreting autotoxins. Adapted cells survive, whereas non-adapted latecomers are eliminated. Remarkably, this toxin-adaptation (TA) system, which uses the same set of autotoxins, is conserved across distantly related yeast species. This is puzzling because conventional toxin-immunity (TI) systems are prone to exploitation by 'cheaters', cells that benefit from immunity without producing toxins, and typically diverge in an evolutionary arms race. To investigate how this system is maintained, we analysed its evolutionary stability using population dynamics modelling. The system does not evolve in constant environments: cheaters outcompete adaptive cells during continuous starvation, while sensitive cells that produce neither toxin nor immunity dominate in continuous nutrient-rich conditions. However, when the environment switches stochastically between starvation and nutrient-rich phases, with short starvation periods and long nutrient-rich periods, the TA system becomes evolutionarily stable. These findings suggest that fluctuating environments can promote the emergence and long-term maintenance of the TA system, highlighting the critical role of environmental switching in shaping microbial survival strategies.

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Publication Details

Journal
Journal of The Royal Society Interface
Published
2026-07-22
DOI
https://doi.org/10.1098/rsif.2026.0345
Primary Topic
Fungal and yeast genetics research
Type
article
Field-Weighted Citation Impact
0.00

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article

Evolvability of the toxin-adaptation system in yeast

Kunihiko Kaneko, Arisa Oda, Tetsuhiro Hatakeyama, Kunihiro Ohta
Journal of The Royal Society Interface
Fungal and yeast genetics research
article

Evolvability of the toxin-adaptation system in yeast

Kunihiko Kaneko, Arisa Oda, Tetsuhiro Hatakeyama, Kunihiro Ohta
article en

Abstract

Crises such as starvation pose a serious threat to microbial populations, prompting cells to adopt survival strategies, such as cooperation or competition. Although cooperation among clones is common, recent studies have shown that yeast cells can kill clonal cells under glucose depletion by secreting autotoxins. Adapted cells survive, whereas non-adapted latecomers are eliminated. Remarkably, this toxin-adaptation (TA) system, which uses the same set of autotoxins, is conserved across distantly related yeast species. This is puzzling because conventional toxin-immunity (TI) systems are prone to exploitation by 'cheaters', cells that benefit from immunity without producing toxins, and typically diverge in an evolutionary arms race. To investigate how this system is maintained, we analysed its evolutionary stability using population dynamics modelling. The system does not evolve in constant environments: cheaters outcompete adaptive cells during continuous starvation, while sensitive cells that produce neither toxin nor immunity dominate in continuous nutrient-rich conditions. However, when the environment switches stochastically between starvation and nutrient-rich phases, with short starvation periods and long nutrient-rich periods, the TA system becomes evolutionarily stable. These findings suggest that fluctuating environments can promote the emergence and long-term maintenance of the TA system, highlighting the critical role of environmental switching in shaping microbial survival strategies.

Journal of The Royal Society InterfaceVol. 23(240)
Tokyo Woman's Christian University (JP), Life Science Institute (JP), Niels Brock (DK), The University of Tokyo (JP)
Naito Foundation, Japan Agency for Medical Research and Development, Novo Nordisk Fonden, Ohsumi Frontier Science Foundation, Japan Society for the Promotion of Science
Partnerships for the goals
Openalex Percentile: Top 14%
Fungal and yeast genetics research
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