Exploring Yeast Biological Limits: A Pareto Front Approach

The overall aim of this two-year project is to describe how yeast traits reach optimization during evolution by examining the phenotypes and genotypes of strains on Pareto fronts.In all organisms, biological traits are optimized for competitive advantage in their environment.

Yet, our understanding of trait development, trade-offs and their constraints is at a nascent stage due to studies on limited datasets and a missing step connecting genotypes to trait optimization.Initially, I will leverage the natural diversity of over 1000 Saccharomyces cerevisiae strains to delineate the constraints of trait optimization, known as Pareto fronts, using phenotypic data.

Subsequently, I will establish correlations between the shape of Pareto fronts and the genetic differences among strains.

Additionally, I will evolve strains situated along and beyond the Pareto frontier to explore the dynamics of trait optimization emergence and determine whether there are definitive phenotypic and genetic thresholds that resist further optimization.S. cerevisiae, a commonly used model organism, will be crucial in addressing optimization problems in more complex organisms and other research fields like optimized bioproduction.

The incorporation of state-of-the-art technology for automated evolution and phenotyping, coupled with the knowledge of leading experts in genomics and evolution from both Harvard University and Gothenburg University, will significantly contribute to the success of this project.