title: Negative frequency-dependent interactions can underlie phenotypic heterogeneity in a clonal microbial population.
abstract: Genetically identical cells in microbial populations often exhibit a remarkable degree of phenotypic heterogeneity even in homogenous environments. Such heterogeneity is commonly thought to represent a bet-hedging strategy against environmental uncertainty. However, evolutionary game theory predicts that phenotypic heterogeneity may also be a response to negative frequency-dependent interactions that favor rare phenotypes over common ones. Here we provide experimental evidence for this alternative explanation in the context of the well-studied yeast GAL network. In an environment containing the two sugars glucose and galactose, the yeast GAL network displays stochastic bimodal activation. We show that in this mixed sugar environment, GAL-ON and GAL-OFF phenotypes can each invade the opposite phenotype when rare and that there exists a resulting stable mix of phenotypes. Consistent with theoretical predictions, the resulting stable mix of phenotypes is not necessarily optimal for population growth. We find that the wild-type mixed strategist GAL network can invade populations of both pure strategists while remaining uninvasible by either. Lastly, using laboratory evolution we show that this mixed resource environment can directly drive the de novo evolution of clonal phenotypic heterogeneity from a pure strategist population. Taken together, our results provide experimental evidence that negative frequency-dependent interactions can underlie the phenotypic heterogeneity found in clonal microbial populations.
authors.affiliation: Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: David
authors.initials: D
authors.lastname: Healey
authors.affiliation: Graduate Program in Biophysics, Harvard University, Cambridge, MA, USA.
authors.forename: Kevin
authors.initials: K
authors.lastname: Axelrod
authors.affiliation: Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA gore@mit.edu.
authors.forename: Jeff
authors.identifier: 0000-0003-4583-8555
authors.initials: J
authors.lastname: Gore
mesh_terms: D000222:Adaptation, Physiological; D060965:Clonal Evolution; D005656:Fungal Proteins / Q000235:genetics*; D005690:Galactose / Q000378:metabolism*; D005716:Game Theory; D010641:Phenotype; D012641:Selection, Genetic; D015003:Yeasts / Q000235:genetics* / Q000378:metabolism
chemical_list: D005656:Fungal Proteins; D005690:Galactose
keywords: ecology; evolution; frequency dependence; phenotypic heterogeneity; stochastic gene expression