Scheme: Newton Advanced Fellowship
Organisation: University of Oxford
Dates: Mar 2015-Feb 2017
Summary: The rate at which pathogenic bacteria evolve resistance to antibiotics is dramatically decreasing the efficacy of current antimicrobial treatments. It may seem a surprising statement but, after more than a century of using antimicrobials in the clinic, some of the evolutionary forces that drive the emergence and spread of drug resistance in pathogenic bacteria are still poorly understood. For instance, most of our understanding of drug resistance adaptation assumes that genetically-identical cells in a constant environment present similar susceptibility and resistance profiles. But recent technological advances in microfluidics, time-lapse microscopy and image analysis have shown that clonal bacterial populations can be very diverse, and that bacterial communities can actually employ this phenotypic heterogeneity as a strategy to survive in unpredictable environments. The objective of this project is to examine the implications of cell-to-cell variability in the ecological and evolutionary processes driving antibiotic resistance adaptation. In order to address this problem we use an interdisciplinary approach that combines high-throughput single-cell observations and experimental evolution in a microbial microcosms, with a data-driven mathematical approach that integrates theory developed in the context of systems biology into a population-genetics framework.