Characterizing Pareto fronts: Trade-offs in the yeast growth cycle constrain adaptation

点击翻译按钮获取中文摘要

Project Summary/Abstract Adaptive evolution involves optimizing multiple fitness related traits simultaneously. These traits can be projected into a multidimensional space known as trait space. Mapping the trait space accessible by single mutations can reveal the constraints imposed on organismal fitness. The fitness of an organism in an environment is often dependent on more than one trait; for yeast these traits include fermentation, respiration, and stationary phase performance. While in some cases it may be possible to improve multiple fitness related traits independently, certain fitness-related traits can also be constrained due to the pleiotropic effects of other fitness related traits, resulting in a trade-off. Previous work from the Sherlock lab has shown that following evolution in a glucose-containing, carbon-limited medium, that Pareto fronts, indicative of underlying trade-offs, emerge between stationary phase and respiration, and between respiration and fermentation, though not between stationary phase and fermentation. Here, I aim to understand the constraints on fitness in the yeast growth cycle and why such trade-offs emerge among some fitness-related traits but not others. I will evolve barcoded yeast in a non-fermentable carbon source with varying amounts of time spent in stationary phase. This experimental design eliminates selection for fermentation entirely and creates varying degrees of selection for performance in respiration and stationary phase e.g., the two-day transfer regime selects primarily for respiration performance, while in the 10-day transfer regime stationary phase performance will be more important. Under these conditions stationary phase performance may be free to increase unconstrained by fermentation performance resulting in the emergence of a pareto front between these components of organismal fitness. Freedom from fermentation performance constraints may also allow yeast to maximize respiration and stationary phase performances simultaneously. In addition to phenotypic analysis, I will also characterize the molecular basis of the underlying adaptive mutations that emerge to gain insight into the biophysical mechanism(s) preventing multiple traits from being optimized simultaneously. Finally, I will further evolve specific adaptive mutants to gain insight into the role of contingency in determining adaptive outcomes and determine whether specialists for one trait are limited in their future evolutionary trajectories when selected for improvement of a different trait.