Miguel Angel Muñoz
Universida de Granada, Spain
Analytical and computational approach to rapid eco-evolutionary dynamics: rapid emergence of tolerance by lag in bacterial communities
Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intermingle much more tightly than traditionally assumed, especially in communities of microorganisms. Developing novel analytical and computational approaches to shed light onto these complex problems is a challenge of utmost practical and theoretical relevance. Within this context, here we scrutinize recent experimental results showing evidence of very rapid evolution of tolerance by lag in bacterial communities that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the communities evolve to develop a distribution of lag times — i.e. the times that individual bacteria typically remain in a dormant state to cope with stress — whose mean fits the antibiotic exposure time. We develop a parsimonious individual-based stochastic model mimicking the actual demographic processes of the experimental setup; individuals are characterized by a single phenotypic trait: their intrinsic lag time, which is inherited with variation by its progeny. The model is able to reproduce remarkably well most empirical observations. Furthermore, we develop and apply a general mathematical framework allowing us to describe the original “many-particle” stochastic model by means of a macroscopic equation akin to the one proposed by Crow and Kimura in the context of population genetics, generalized to this eco-evolutionary context and that explains quite well the computational results. The work presented here represents a benchmark for the mathematical framework designed to tackle similar complex problems where ecological and evolutionary processes cannot be disentangled from each other, thus opening broad research avenues.