Project 3: Dissecting and evolving the mating module of budding yeast, S. cerevisiae (Murray) (#21-26)We used experiment and theory to ask how yeast cells polarize and pick mating partners. Cell polarization isessential for development and plays an important role in the biology of many human pathogens. Yeast cellspolarize up pheromone gradients but also polarize in spatially uniform pheromone fields. We ruled out twomodels for polarization, the use of a historical mark, and models based on lateral inhibition. Our results supporta new class of model, global integration, which uses actin filaments and positive feedback to integratesignaling throughout the cell: pheromone signaling induces actin polymerization, and secretory vesicles movealong actin filaments to deliver more signaling components. Cells can only detect pheromone gradients over anarrow concentration range. They use the regulated secretion of Bar1, a protease that degrades pheromone,to keep the pheromone concentration at the cell surface in this range. In collaboration with Naama Barkai, wehave shown that although exogenous protease substantially improves the mating of Bar1-deficient cells, itdoes not allow them to discriminate between identically attractive partners, a process that requires cell surfaceboundBar1.We used the mating module to investigate the evolutionary pliability of modules. Much experimental evolutionhas focused on metabolic traits like improved growth on limiting nutrient sources, but we chose to evolve orengineer traits that depended on a signaling module: 1) We developed a laboratory model of sympatricspeciation and used it to evolve a five-fold mating preference30. We developed general methods to map andidentify these mutations, with the goal of revealing the genetic and phenotypic basis of speciation31 2) We triedto evolve cells where DNA damage would activate a reporter of pheromone signaling, but instead producedstrains in which reporter activity varies stochastically within a cell lineage. This trait depends on 4 mutations ofwhich we have mapped two and are close to identifying the other two. 3) We engineered the gradedpheromone response into a hysteretic switch by putting modified signaling proteins under the control of apheromone-inducible promoter. This work shows that expression of a single gene can determine whether apathway responds reversibly to an environmental signal, acts as a bistable switch, or is constitutivelyactivated32.We began work on the fundamental parameters that control evolution. Attempting to evolve the mating moduleprompted us to ask fundamental questions about evolution. These included searching for theory that wouldrelate the rate of evolution to fundamental parameters (population size, mutation rate, interaction betweenmutations, etc.) and devising ways to measure these parameters. In collaboration with M. Desai (a Physicsgraduate student) and D. Fisher, we developed and tested a model that predicted the rate of evolution33, andwe investigated the conditions under which mutators accelerated evolution34. We also made detailedmeasurements of the per-base pair mutation rate35 and showed that the local average of this rate changesacross the genome in concert with the timing of DNA replication, with the latest replicating sequences havingthe highest mutation rate. Further experiments show that early replicating sequences are less likely to berepaired by error-prone DNA polymerases than late replicating sequences.
| Westerman, Erica L; VanKuren, Nicholas W; Massardo, Darli et al. (2018) Aristaless Controls Butterfly Wing Color Variation Used in Mimicry and Mate Choice. Curr Biol 28:3469-3474.e4 |
| Bonham, Kevin S; Wolfe, Benjamin E; Dutton, Rachel J (2017) Extensive horizontal gene transfer in cheese-associated bacteria. Elife 6: |
| Tamari, Zvi; Yona, Avihu H; Pilpel, Yitzhak et al. (2016) Rapid evolutionary adaptation to growth on an 'unfamiliar' carbon source. BMC Genomics 17:674 |
| Kim, Wook; Levy, Stuart B; Foster, Kevin R (2016) Rapid radiation in bacteria leads to a division of labour. Nat Commun 7:10508 |
| Muller, Nicolas; Piel, Matthieu; Calvez, Vincent et al. (2016) A Predictive Model for Yeast Cell Polarization in Pheromone Gradients. PLoS Comput Biol 12:e1004795 |
| Wahl, Mary E; Murray, Andrew W (2016) Multicellularity makes somatic differentiation evolutionarily stable. Proc Natl Acad Sci U S A 113:8362-7 |
| Hormoz, Sahand; Singer, Zakary S; Linton, James M et al. (2016) Inferring Cell-State Transition Dynamics from Lineage Trees and Endpoint Single-Cell Measurements. Cell Syst 3:419-433.e8 |
| Renn, Suzy C P; O'Rourke, Cynthia F; Aubin-Horth, Nadia et al. (2016) Dissecting the Transcriptional Patterns of Social Dominance across Teleosts. Integr Comp Biol 56:1250-1265 |
| Kastman, Erik K; Kamelamela, Noelani; Norville, Josh W et al. (2016) Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species. MBio 7: |
| Lavrentovich, Maxim O; Wahl, Mary E; Nelson, David R et al. (2016) Spatially Constrained Growth Enhances Conversional Meltdown. Biophys J 110:2800-2808 |
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