Phenotype Switching and Mutations in Random Environments

Abstract

Cell populations can benefit from changing phenotype when the environment changes. One mechanism for generating these changes is stochastic phenotype switching, whereby cells switch stochastically from one phenotype to another according to genetically determined rates, irrespective of the current environment, with the matching of phenotype to environment then determined by selective pressure. This mechanism has been observed in numerous contexts, but identifying the precise connection between switching rates and environmental changes remains an open problem. Here, we introduce a simple model to study the evolution of phenotype switching in a finite population subject to random environmental shocks. We compare the successes of competing genotypes with different switching rates, and analyze how the optimal switching rates depend on the frequency of environmental changes. If environmental changes are as rare as mutations, then the optimal switching rates mimic the rates of environmental changes. If the environment changes more frequently, then the optimal genotype either maximally favors fitness in the more common environment or has the maximal switching rate to each phenotype. Our results also explain why the optimum is relatively insensitive to fitness in each environment.

Bet-hedging in stochastically switching environments

“…Based on numerical simulations, a link between the rate at which the environment switches and the rate at which a bimorphic phenotype of bacteria changes its subtype has been conjectured already in that paper (Acar et al, 2007). This conjecture has been confirmed in a time-discrete setup considering models with a finite number of individuals (King and Masel, 2007;Fudenberg and Imgof, 2012). The implications of periodic environments have been analyzed by Pang and Tzeng (2008) and Gaal et al (2012).…”

Evolutionary dynamics of competing phenotype-structured populations in periodically fluctuating environments

“…Previous work suggests that the likelihood of species coexistence is increased by temporal variations in the environment. More recent models have looked at adaptive strategies, including stochastic phenotype switching, emerging in the stochastic environments [21,22,23,24,25]. Muller et al [22] theoretically investigated the environmental conditions that would lead to the emergence of bet-hedging, noting the importance of the fluctuation timescales on the success of the adaptation strategy.…”

The impact of bottlenecks on microbial survival, adaptation, and phenotypic switching in host-pathogen interactions

“…; Patra and Klumpp ). The role of finite population size and the conditions in which optimal switching rates can evolve were characterized in (King and Masel ; Fudenberg and Imhof ). When populations are too small, for example if phenotypic switches occur less often in a population than environments change, it becomes difficult for optimal switching rates to evolve, and strains would be expected to exhibit suboptimal switching.…”

“…When switching rates are able to adapt thereby increasing long-term population growth rates, the optimal switching rates in a slowly fluctuating environment are inversely proportional to the environmental durations (Lachmann and Jablonka 1996;Gaal et al 2010;Patra and Klumpp 2015). The role of finite population size and the conditions in which optimal switching rates can evolve were characterized in (King and Masel 2007;Fudenberg and Imhof 2012). When populations are too small, for example if phenotypic switches occur less often in a population than environments change, it becomes difficult for optimal switching rates to evolve, and strains would be expected to exhibit suboptimal switching.…”