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Adapt or perish: Evolutionary rescue in a gradually deteriorating environment

Authors :
Loïc Marrec
Anne-Florence Bitbol
Laboratoire Jean Perrin (LJP)
Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Ecole Polytechnique Fédérale de Lausanne (EPFL)
HAL-SU, Gestionnaire
Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Source :
Genetics, Genetics, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩, Genetics, Genetics Society of America, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

We investigate the evolutionary rescue of a microbial population in a gradually deteriorating environment, through a combination of analytical calculations and stochastic simulations. We consider a population destined for extinction in the absence of mutants, which can only survive if mutants sufficiently adapted to the new environment arise and fix. We show that mutants that appear later during the environment deterioration have a higher probability to fix. The rescue probability of the population increases with a sigmoidal shape when the product of the carrying capacity and of the mutation probability increases. Furthermore, we find that rescue becomes more likely for smaller population sizes and/or mutation probabilities if the environment degradation is slower, which illustrates the key impact of the rapidity of environment degradation on the fate of a population. We also show that our main conclusions are robust across various types of adaptive mutants, including specialist and generalist ones, as well as mutants modeling antimicrobial resistance evolution. We further express the average time of appearance of the mutants that do rescue the population and the average extinction time of those that do not. Our methods can be applied to other situations with continuously variable fitnesses and population sizes, and our analytical predictions are valid in the weak-to-moderate mutation regime.<br />Comment: 36 pages, 18 figures

Details

ISSN :
00166731
Database :
OpenAIRE
Journal :
Genetics, Genetics, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩, Genetics, Genetics Society of America, 2020, 216 (2), pp.573-583. ⟨10.1534/genetics.120.303624⟩
Accession number :
edsair.doi.dedup.....9876e1acf2de302f1a32b08499e912dc
Full Text :
https://doi.org/10.1101/2020.05.05.079616