Speaker
Description
Microbes inhabit natural environments that are remarkably dynamic, with sudden environmental shifts that require immediate action by the cell. The genetic control of cellular responses therefore evolve according to the specific demands of their environment, resulting in different strategies such as transcriptional regulation or stochastic switching. However, when microbes are exposed to extreme environments, such as pathogens adapting to clinical antibiotic treatments, complete loss of regulation is frequently observed. Although it is known that the short-term evolution of microbes in new environments tends to favor mutations in regulatory pathways that adapt cell responses to new demands, it is not clear how specific dynamic regimens affect this evolution, or which mechanisms are commonly used by the cell to achieve new regulation strategies. Using continuous cultures of E. coli carrying the tightly regulated tetracycline resistance tet operon, we perform experimental evolution to identify specific types of mutations that adapt drug responses to different dynamical regimens of drug administration. When E. coli cultures are evolved under gradually increasing tetracycline concentrations, we observe a predominance of mutations affecting acrB (efflux pump) and ompR (porin regulator), alternative mechanisms of tetracycline efflux. When the cultures are instead periodically exposed to large doses of antibiotics, a regimen we expected to favor the maintenance of regulation of resistance, we observe dominance of transposon insertions resulting in loss of function of repressor TetR, regulator of efflux pump TetA. We use a mathematical model of the dynamics of antibiotic responses to show that sudden exposure to large drug concentrations can overwhelm regulated responses, which cannot induce resistance fast enough, resulting in fitness advantage for constitutive expression of resistance. These results help explain the loss of regulation of antibiotic resistance by opportunistic pathogens evolving in clinical environments. Elucidating the evolutionary forces that drive pathogens to repurpose resistance mechanisms to resist clinical treatments is essential to anticipate the emergence of resistance in the clinic and point to new public health strategies to prevent it.
