Title: Principles of asexual adaptation revealed by experiments in evolution
Description: In asexual populations, whether cancer cells, oceanic plankton, or pathogenic bacteria, lineages do not merge, and evolution proceeds by the successive incorporation of new mutations in independent expanding lineages. Despite such genetic isolation, asexual evolution is profoundly shaped by interactions among organisms and interactions among environmental factors. Even when lineages do not directly harm each other through predation or chemical warfare, mere competition for essential resources induces complex dynamics within and among species. Dynamics can become even more complex when additional environmental stresses, such as antibiotics, interact. Based on observations of adaptation in controlled laboratory populations as well as computer-generated simulations, this dissertation explores evolutionary interactions on three levels: (1) The first chapter studies interactions among competing lineages diverging from a recent clonal ancestor. We find that when many competing mutations spread simultaneously (clonal interference), evolution is driven by the fitness effects and appearance times of only a small minority of favorable mutations. The complexity of the mutation-selection process is thereby greatly reduced, and much of the evolutionary dynamics can be encapsulated in two parameters--an effective selection coefficient and an effective rate of beneficial mutations. (2)

The second chapter uses numerical simulations to study whether interactions between species, through consumption of common resources, can support species coexistence over evolutionary times. We add a slow mutational process to a model in which the environment is complex, and show that while the complexity of the environment promotes the coexistence of multiple species, the micro-adaptation processes within each species destroy such communities. (3) The final chapter of this dissertation considers how the nature of the interactions between drugs--synergy, additivity, or antagonism--affects the speed with which bacteria evolve multi-drug resistance. Analyzing the parallel evolution of hundreds of microbial populations in two-dimensional grids of drug gradients over many generations, we find a correlation between synergy and the rate of adaptation, whereby in more synergistic drug combinations, typically preferred in clinical settings, bacteria evolve resistance faster than in antagonistic combinations.