To register

Understanding the link between sequence and resistance for antimicrobial resistance genes is of outmost importance in our field. I will share our recent work on the deep mutational scanning of two drug resistance enzymes. In one project, we examine the trade-off between resistance to an antifungal drug and activity on the canonical substrate of the drug target. We show that the trade-off between the two functions is very steep and is shaped by the difference in dose response functions of drug resistance and nutrient use. The two fitness functions are nearly perfectly negatively correlated, which means no single mutation can lead to resistance while also maintaining growth in conditions that require this enzyme.

In the second project, we examine how expression level affects the fitness landscape of an antibiotic resistance protein. By measuring the effect of all single mutations at optimal and several suboptimal expression levels, we show that optimal expression can mask the effects of many deleterious mutations on enzyme function. Surprisingly, some beneficial mutations also appear to be masked at optimal expression level. Protein expression level is therefore an important factor shaping the fitness landscape of resistance enzymes. These two studies illuminate how complex resistance evolution can be in heterogeneous growth and cellular environments.