An Agent-Based Numerical Approach to Lenski's Long Term Experiment

Abstract

In this thesis, we introduce and discuss two models of bacterial evolution within the framework of Lenski's experiment, which studies the evolution of bacterial colonies in a fixed environment over many generations. In the first model, we simulate the infinite-sites model, in which bacteria are characterized by their fitness. We consider exponential and Gaussian distributions for fitness draws and compare the results to analytical predictions. In this case, we primarily look at long-term fitness trajectories in both the strong selection weak mutation and clonal interference regimes. In the second model, we begin to explore the effects of bacterial competence, the intra-generation sharing of DNA, within the context of the spin glass model both with and without epistasis. We seek to understand the effects of bacterial competence as a function of the parameters chosen.