Friday, May 9, 2025
5/9/2025
Evolutionary Tradeoffs in Antibiotic Resistance - ABSTRACT Antibiotic resistance emerges when a mutation in a bacterium causes a previously inhibitory concentration of a compound to become survivable. Through the accumulation of mutations conferring varying increases in resistance, already many easy-to-treat infections have become nearly incurable, and are spreading in part anthropogenically. The classical model of resistance evolution, that a resistant mutant has a fitness advantage in the presence of antibiotic use, and so spreads in the population to near fixation, captures the rise of antibiotic resistance, but on closer inspection fails to explain several critical features of resistance. Antibiotic resistance rarely reaches fixation in clinical populations and more importantly, sensitivity is higher than the population-genetic models would predict. Further, despite the widespread prevalence of antibiotic-producing bacteria in the environment, these same bacteria remain surrounded by sensitive neighbors. For these reasons, we hypothesize that the existing model of resistance evolution is incomplete, and that there exist evolutionary factors in the environment which have a potentially countervailing effect on resistance evolution. Our laboratory studies tradeoffs in bacterial evolution with a particular eye towards antibiotic resistance. Resistance provides an almost ideal model system for the study of microbial evolution; fitness can be well defined, imposed selective pressures can be readily tuned, and can emerge either spontaneously or by horizontal gene transfer. Similarly, we study the direct and indirect evolutionary costs of resistance evolution and specialization, and the tradeoffs inherent in mobile genetic elements-borne resistance. In the next five years we will be pursuing a number of related projects deepening and expanding this theme: We will explore a number of a directions related to plasmids and horizontal gene transfer, including their competition with one another on the individual bacterium and population scales, as well as multiple aspects of the interactions between mobile genetic elements and resistance genes and bacteriophage. We will also expand into discovering new mobile genetic elements and their cargo in the wild. We will also relate this historically to the evolution of antibiotic resistance observed over the last eighty years of clinical use. We will continue to pursue this with a mix of laboratory evolution in model systems, and computational analysis and modeling of sequence data.
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