Biological & Soft Matter Seminar: Natural Selection in the Wake of Catastrophe

Abstract:

Living organisms, from bacteria to humans, are more likely to survive if their traits enhance fitness. In populations well adapted to their environmental niches, natural selection proceeds via rare beneficial mutations. But when catastrophe transforms the environment, existing variation can immediately fuel adaptation. In this talk, I’ll present a data-validated theory of natural selection in the wake of catastrophe, which unveils a simple law of recovery: the mean fitness relaxes inversely with time, with a prefactor proportional to the number of traits coupled to the post-catastrophe environment. This law is an evolutionary analog of the equipartition principle in statistical mechanics, with time playing the role of inverse temperature. Applying our approach to experimental fitness landscapes measured in E. coli under antibiotic stress, we point to two effective traits in each. The resulting trait adaptation does not follow gradient ascent on a fitness landscape. Instead, it follows the Levenberg-Marquardt optimization algorithm. Near fitness peaks, adaptation trajectories are biased against greediness - from an optimization perspective, post-catastrophic adaptation is optimistic.