title: Switching and growth for microbial populations in catastrophic responsive environments.
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 maximizes its instantaneous growth rate, regardless of catastrophes. In the switching strategy, the microbial switching rate is tuned to minimize the environmental response. Which of these strategies is most favorable depends on the parameters of the model. Previous studies have shown that microbial switching can be favorable when the environment changes in an unresponsive fashion between several states. Here, we demonstrate an alternative role for phase variation in allowing microbes to maximize their growth in catastrophic responsive environments.
authors.affiliation: SUPA, The University of Edinburgh, Edinburgh, United Kingdom.
authors.forename: Paolo
authors.initials: P
authors.lastname: Visco
authors.forename: Rosalind J
authors.initials: RJ
authors.lastname: Allen
authors.forename: Satya N
authors.initials: SN
authors.lastname: Majumdar
authors.forename: Martin R
authors.initials: MR
authors.lastname: Evans
mesh_terms: D001419:Bacteria / Q000254:growth & development*; D001703:Biophysics / Q000379:methods*; D004777:Environment; D015870:Gene Expression; D005786:Gene Expression Regulation; D008829:Microbiology; D008954:Models, Biological; D015233:Models, Statistical; D010641:Phenotype; D011336:Probability; D015398:Signal Transduction; D013269:Stochastic Processes