Open Collections

Study of non-genetic variability and heritability of pheromone signaling in Saccharomyces cerevisiae on a microfluidic device

University of British Columbia

Clonal populations of cells exhibit variability in gene expression despite genetic identity. Single cell technologies have helped identify various sources of such variability. Intrinsic noise in biochemical reactions as well as variability introduced by cell cycle progression and division have been suggested to play a significant role. However, there is a paucity of experimental platforms that can simultaneously measure gene expression and track cell cycle and division through multiple generations in a fully automated fashion. In this thesis I describe a microfluidic-based approach for performing such studies which integrate high- resolution live cell microscopy and automated image analysis to track lineages of multiple yeast strains for up to 8 generations in temporally and chemically controlled environments. This technology is applied to the quantitative study of non-genetic inheritance of the pheromone mitogen activated protein kinase signaling response. These studies demonstrate that the capacity to respond to pheromone is non-genetically passed on to progeny and that this response correlation is maintained between cells that are multiple generations apart. Deletions in the pheromone pathway were found to affect the strength of these correlations. While Δfus3 cells were the most correlated of all screened strains, Δste50 elicited dramatic asymmetry in response between mothers and their daughters leading to highly heterogeneous phenotype. Comparing expression with cell cycle phase and cell age, we present a previously unrecognized role of FUS3 in cell cycle regulation and reveal the pathway’s sensitivity to asymmetric division in the absence of STE50. Our results contribute to the understanding of the origins of heterogeneity in a monoclonal population and elucidate the role of division processes and the cell cycle in giving rise to this cell-to-cell variability.

Text

2012-08-02

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/42859

Genome Science and Technology

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/