From one to many: ecology and stochasticity in the evolution of drug resistance

The evolution of antimicrobial resistance is compromising our ability to treat various infectious diseases. A major question is how best to dose drugs to treat patients effectively but avoid de novo evolution of resistance in pathogen populations. An ongoing debate centres on whether the conventional wisdom of using the maximal tolerable dose is really best. In this talk I will explore how two factors may shift our thinking on this question: (1) demographic stochasticity, which is relevant in initially small resistant mutant populations; and (2) ecological interactions among pathogens, including both competitive and protective effects. I will draw on two case studies from my research, one theoretical (mathematical modelling of chronic viral infections) and one experimental (in vitro tests with the pathogenic bacterium Pseudomonas aeruginosa). I will also briefly touch on links between drug resistance and the more general concept of “evolutionary rescue” in threatened populations.

Recent publication:

HK Alexander, RC MacLean (2020). Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells. Proc. Nat. Acad. Sci. (USA) 117:19455-19464.