Phenotypic heterogeneity and evolutionary games in microbial populations

Abstract

One of the most interesting discoveries of the last decade is the surprising degree of phenotypic variability between individual cells in clonal microbial populations, even in identical environments. While some variation is an inevitable consequence of low numbers of regulatory molecules in cells, the magnitude of the variability is nevertheless an evolvable trait whose quantitative parameters can be "tuned" by the biochemical characteristics and architecture of the underlying gene network. This raises the question of what adaptive advantage might be conferred to cells that implement high variation in their decision-making. Currently, the predominant answer in the field is that stochastic gene expression allows cells to "hedge their bets" against unpredictable and potentially catastrophic environmental shifts. We proposed and experimentally demonstrated an alternative solution: that heterogeneity implements the evolutionarily stable mixed strategy (or mixed ESS), from the field of evolutionary game theory. In a mixed ESS, phenotypic heterogeneity is a result of competitive interactions between cells in the population rather than a response to uncertain environments, so unlike with bet-hedging, in a mixed ESS the evolutionary fitness of different phenotypes is frequency dependent. Each phenotype can invade the other when rare, and the resulting equilibrium-the stable mix of the two-is not necessarily the one that maximizes the population's fitness. We demonstrated these and other predictions of the mixed ESS using engineered "pure strategist" strains of the yeast GAL network. We demonstrated also that the wild type mixed strategist can invade both pure strategists and is uninvasible by either. Taken together, our results provide experimental evidence that evolutionary hawk-dove games between identical cells can explain the phenotypic heterogeneity found in clonal microbial populations.