Strategies in evolutionary medicine aim to thwart the evolution of drug resistance by using combinations of drugs that demonstrate “collateral sensitivity,” which is when mutants that resist Drug ‘A’ increase susceptibility to Drug ‘B’. Problematically, it often turns out that resistance and susceptibility are not inextricably linked, and some rare mutations exist that can disrupt these phenotypic correlations. Most technologies cannot quantify the prevalence of collateral sensitivity. We utilize a laboratory evolution platform that is perfect for doing so in the model organism S. cerevisiae. Rather than identifying the most resistant mutants in Drug ‘A’, this platform utilizes thousands of barcoded lineages to explore all mutations that resist Drug ‘A’. Then we quantify their resistance to Drug ‘B’ (and C, D, E…you get the idea). Characterizing these tradeoffs reveals trends and limits that define a fitness landscape. These landscapes have multiple peaks, corresponding to multiple ways to resist a drug that come with different tradeoffs (e.g., some may come without collateral sensitivity). Once we create abstract genotype-phenotype maps, we can make predictions about how organisms will evolve when exposed to new conditions.

Relevant Papers:
-Drug resistant mutants have different fitness tradeoffs link
-Our review on the challenges of predicting evolution and studying adaptive mutations link
-Rare mutations (and other contextual changes) can disrupt correlated phenotypes link
-Abstract genotype-phenotype map example link