Coupling phenotype stability to growth rate overcomes limitations of bet-hedging strategies
Coupling phenotype stability to growth rate overcomes limitations of bet-hedging strategies
Abstract Microbes in the wild face highly variable and unpredictable environments, and are naturally selected for their average growth rate across environments. Apart from using sensory-regulatory systems to adapt in a targeted manner to changing environments, microbes employ bet-hedging strategies where cells in an isogenic population switch stochastically between alternative phenotypes. Yet, bet-hedging suffers from a fundamental trade-off: increasing the phenotype switching rate increases the rate at which maladapted cells explore alternative phenotypes, but also increases the rate at which cells switch out of a well-adapted state. Consequently, it is currently believed that bet-hedging strategies are only effective when the number of possible phenotypes is limited and when environments last for sufficiently many generations. However, recent experimental results show that gene expression noise generally decreases with growth rate, suggesting that phenotype switching rates may systematically decrease with growth rate. We here show that such growth rate dependent stability (GRDS) can almost completely overcome the trade-off that limits bet-hedging, allowing for effective adaptation even when environments are diverse and change rapidly. GRDS allows cells to be more explorative when maladapted, and more phenotypically stable when well-adapted. We further show that even a small decrease in switching rates of faster growing phenotypes can substantially increase long-term fitness of bet-hedging strategies. Together, our results suggest that stochastic strategies may play an even bigger role for microbial adaptation than hitherto appreciated.
van Nimwegen Erik、de Groot Daan H.、Bruggeman Frank J.、Tjalma Age J.
Biozentrum, University of Basel, and Swiss Institute of BioinformaticsBiozentrum, University of Basel, and Swiss Institute of Bioinformatics||Systems Biology Lab, AIMMS, VU UniversitySystems Biology Lab, AIMMS, VU UniversitySystems Biology Lab, AIMMS, VU University||AMOLF
微生物学分子生物学生物科学理论、生物科学方法
van Nimwegen Erik,de Groot Daan H.,Bruggeman Frank J.,Tjalma Age J..Coupling phenotype stability to growth rate overcomes limitations of bet-hedging strategies[EB/OL].(2025-03-28)[2025-05-01].https://www.biorxiv.org/content/10.1101/2022.04.12.488059.点此复制
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