Switching and growth for microbial populations in catastrophic responsive environments

TL;DR

This paper uses a theoretical model to explore how microbial populations benefit from stochastic switching between phenotypes in environments with catastrophic events that respond to the population's composition.

Contribution

It introduces a model showing that microbial switching strategies are advantageous in responsive environments, highlighting conditions where switching maximizes growth.

Findings

Switching can be beneficial in catastrophic responsive environments.

Two strategies emerge: no switching and tuned switching.

The optimal strategy depends on environmental responsiveness and model parameters.

Abstract

Phase variation, or stochastic switching between alternative states of gene expression, is common among microbes, and may be important in coping with changing environments. We use a theoretical model to assess whether such switching is a good strategy for growth in environments with occasional catastrophic events. We find that switching can be advantageous, but only when the environment is responsive to the microbial population. In our model, microbes switch randomly between two phenotypic states, with different growth rates. The environment undergoes sudden "catastrophes", the probability of which depends on the composition of the population. We derive a simple analytical result for the population growth rate. For a responsive environment, two alternative strategies emerge. In the "no switching" strategy, the population maximises its instantaneous growth rate, regardless of catastrophes. In the "switching" strategy, the microbial switching rate is tuned to minimise the environmental response. Which of these strategies is most favourable depends on the parameters of the model. Previous studies have shown that microbial switching can be favourable when the environment changes in an unresponsive fashion between several states. Here, we demonstrate an alternative role for phase variation in allowing microbes to maximise their growth in catastrophic responsive environments.