Fall 2013 Seminar Schedule
4PM on Wednesdays in NW 169
23 October- Will Harcombe (Marx Lab), Quantitatively predicting and testing the evolutionary ecology of microbial systems - Metabolic interactions such as cross-feeding and competition are abundant in natural microbial communities, and can be engineered in artificial ones. We show that in spatially structured environments, these interactions give rise to dynamic ecosystem-level effects that defy simple intuition. By implementing dynamic flux balance analysis on a lattice, we simulated the complete metabolic activity of multiple microbial species in time and space, and studied the dynamics of engineered consortia. We predicted, and experimentally confirmed, the convergence of a 2-species mutualistic consortium towards a fixed species ratio, and stable coexistence in a newly engineered 3-member community. Most surprisingly we predicted that colonies that obstruct the flow of nutrients between mutualistic partners can have a paradoxical benefit to the distal pair. This result, confirmed experimentally, illustrates the complex nature of metabolism-mediated interactions in microbial communities. The predictability of these effects highlights the value of multi-level quantitative metabolic modeling in microbial ecology.
6 November- Chris Ford (Regev Lab), title TBD
20 November- Josh Michener (Marx Lab), title TBD
11 December- Cat Adams (Pringle Lab), title TBD
9 October- Elizabeth Jerison (Desai Lab), Adaptive Pleiotropy in Yeast - Although organisms evolve in complex and time-varying environments, little is known about the relationship between these environments from the perspective of adaptation. Here, we investigated the structure of these differences in yeast. We evolved 253 populations in 13 conditions that varied in the degree and type of stress, and measured the fitnesses of the evolved mutants in many of the conditions. We find that groups of evolved mutants, both within and between environments, cluster in phenotype space, giving a measure of the degree of overlap of targets of beneficial mutations in the different conditions. We are unraveling the genetic basis for these patterns using whole-genome sequencing of 253 clones.