Effective bet-hedging through growth rate dependent stability

de Groot, Daan H. and Tjalma, Age J. and Bruggeman, Frank J. and van Nimwegen, Erik. (2023) Effective bet-hedging through growth rate dependent stability. Proceedings of the National Academy of Sciences of the United States of America, 120 (8). e2211091120.

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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 effective only 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. Such growth rate dependent stability (GRDS) causes cells to be more explorative when maladapted and more phenotypically stable when well-adapted, and we show that GRDS can almost completely overcome the trade-off that limits bet-hedging, allowing for effective adaptation even when environments are diverse and change rapidly. 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.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (van Nimwegen)
UniBasel Contributors:van Nimwegen, Erik and de Groot, Daan Hugo
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:National Academy of Sciences
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:21 Feb 2023 09:55
Deposited On:21 Feb 2023 09:55

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