5 Oral - Platform Session 1 Complex Traits
Wednesday June 08, 9:00 AM - 9:15 AM

Authors:
Sam Apodaca ¹; Kara Schmidlin ¹; Daphne Newell ^1,2; Kerry Geiler-Samerotte ^1,2

Affiliations:
1) Arizona State University Biodesign Institute, Tempe, AZ; 2) Arizona State University School of Life Sciences, Tempe, AZ

Keywords:
Experimental evolution

A major challenge for modern medicine is the increasing prevalence of drug-resistant microbes. In parallel with efforts to discover candidates for new antimicrobials, research is increasingly focusing on how the efficacy of existing drugs can be extended. For example, collateral sensitivity is an evolutionary phenomenon in which the mutation that allows a microbe to resist one drug makes it more susceptible to a second drug. While it has been suggested that this could be a potential treatment strategy, it only becomes viable if the phenomenon can be predicted and reproduced reliably across multiple resistant mutants. To make such predictions, we believe that it is necessary to consider all resistance mutations that can occur in a given drug condition, not just the most successful one. To do this, we utilized a library of molecularly barcoded S. cerevisiae to study the evolution of resistance to two drugs, fluconazole and radicicol. This enabled us to observe ~300,000 lineages as they evolved in 12 different concentrations and combinations of the two drugs over 200 generations. Sequencing data was used to track barcode frequencies over time, allowing us to identify hundreds of resistant lineages as they arose and quantify differences in how resistance evolution occurs under different conditions. To explore the collateral fitness effects of these resistance mutations, adaptive lineages from the evolved populations were pooled together and their fitnesses were remeasured in each of the 12 drug conditions. We successfully identified many lineages demonstrating collateral sensitivity, in other words, lineages that possessed mutations that were highly adaptive in their home environment but deleterious in others. But these patterns of collateral sensitivity were not reliable across different mutants. Barcode frequencies revealed that adaptive lineages from the same home conditions did not have similar, predictable fitness when exposed to non-home environments. Finally, we isolated lineages of interest and used whole-genome sequencing to identify the specific mutations that conferred these fitness effects. Our barcode system has allowed us to expand on previous research into collateral sensitivity by greatly increasing the number of lineages that can be studied simultaneously, highlighting the importance of accounting for more than just the highest frequency mutations when making predictions about adaptation.