Phenotypic heterogeneity as a strategy for speeding up adaptive evolution at minimal cost

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Bacillus subtilis shows phenotypic variability in the stationary growth phase. In particular, a well-defined fraction of isogenic cells differentiates into the state of competence for transformation. Here we address the question whether this type of behaviour is optimal to speed up adaptation while minimizing the cost of competence development. We will generate mutants in B. subtilis which differentiate at different rates, and use a strain in which the entire population deterministically enters the state of competence. We plan to perform evolution experiments to quantify the rate of fitness increase for these different strategies of competence control. In particular we will address the following specific questions: What is the optimum rate and strategy of competence differentiation for speeding up adaptation? How do these rates and strategies depend on mutation rates? How does genetic drift affect the optimum rate of differentiation? Since the molecular details of differentiation and transformation are well characterized, the adaptation rates obtained from this project can serve as a basis for mathematical modelling of recombination control strategies. The results will deepen our understanding of the biological significance of phenotypic variability.