  Stochastic phenotype switching has been suggested to play a beneficial role
in microbial populations by leading to the division of labour among cells, or
ensuring that at least some of the population survives an unexpected change in
environmental conditions. Here we use a computational model to investigate an
alternative possible function of stochastic phenotype switching - as a way to
adapt more quickly even in a static environment. We show that when a genetic
mutation causes a population to become less fit, switching to an alternative
phenotype with higher fitness (growth rate) may give the population enough time
to develop compensatory mutations that increase the fitness again. The
possibility of switching phenotypes can reduce the time to adaptation by orders
of magnitude if the "fitness valley" caused by the deleterious mutation is deep
enough. Our work has important implications for the emergence of
antibiotic-resistant bacteria. In line with recent experimental findings we
hypothesise that switching to a slower growing but less sensitive phenotype
helps bacteria to develop resistance by exploring a larger set of beneficial
mutations while avoiding deleterious ones.
