Systems Biology of Molecular Noise in Yeast

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DESCRIPTION (provided by applicant): Proper assessment by cells of extracellular cues is essential for the normal functioning of all organisms. However, the ability of cells to respond properly to their environment is limited by biological variability or "noise" in the responses of individual cells. This is true of even genetically identical cells in a homogenous environment. Our global hypothesis is that there exist genetically-encoded cellular control systems akin to those used in human-engineered systems that modulate noise and shape phenotypic outcomes, particularly in complex cellular circuits involved in cell differentiation. We seek to test this hypothesis through a combination of i) theory- guided directed experiments, and ii) high-throughput forward genetics that exploit precise measurements of individual cell phenotypes. As a model system, we have chosen the pheromone response differentiation pathway of the budding yeast Saccharomyces cerevisiae, which offers numerous experimental advantages. We seek to continue an already-productive collaboration that brings together theoretical expertise in engineering control systems and stochastic theories with expertise in high-throughput model organism genetics and molecular biology. To achieve our goals, we will build on substantial preliminary work to 1) understand the mechanism of noise suppression by an inhibitor of the pheromone pathway MAP kinase- responsive transcriptional activator, 2) identify the genetic determinants of noise modulation during pheromone signaling, and 3) test the hypothesis that multiple feedback controls act as a system to prevent catastrophic signal transduction events. Together these systems-level studies will reveal the genetic mechanisms by which cells control molecular noise to achieve responses that are quantitatively reproducible. PUBLIC HEALTH RELEVANCE: Given the central role of MAP kinase signaling in human cancers, understanding the mechanisms of noise suppression within a MAPK signaling cascade may impact our understanding of tumor progression and heterogeneity while exposing weak links in the system for therapeutic intervention.