Invited Speaker: Dr. Christian Landry

Invited Speaker: Dr. Christian Landry – Université Laval

This seminar will be presented in a hybrid format. Audience members are welcome to attend either in person at the MSL lecture theatre (room 102) or via the zoom link. Those connecting via zoom will be able to ask questions during the Q&A portion using the chat function.

Zoom registration link: https://ubc.zoom.us/meeting/register/u5Mtf-qrqzwjH9RvHbLK45qT0vDfk18YmlPE

Talk title
Navigating protein fitness landscapes in multiple dimensions

Abstract
Proteins could have as many fitness landscapes as they have functions. The relationship between mutations and the performance of any two functions could be positively or negatively correlated, making evolution on one landscape contingent on evolution on the other. Understanding the evolution of proteins therefore requires that we understand how mutations affect the multiple dimensions of the landscapes of protein functions. Here, I will share our recent work on the deep mutational scanning of two drug resistance enzymes in which we examine more than one dimension at a time. 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 proteins. These two studies illuminate how complex protein evolution is in heterogeneous growth and cellular environments.