Single-cell Measurement and Control to Unravel Yeast Gene Expression Heterogeneity

Friday, October 11, 2019 -
2:00pm to 3:00pm
The FUNG Auditorium
Megan N. McClean

Assistant Professor

Biomedical Engineering

University of Wisconsin-Madison

Single-cell Measurement and Control to Unravel Yeast Gene Expression Heterogeneity

Abstract: 

From microbes to cancer, variability in gene expression can lead to nongenetic phenotypic heterogeneity. This heterogeneity is important in determining how populations of cells grow, survive fluctuating environments, and develop drug resistance. For example, Individual yeast cells within isogenic populations show striking heterogeneity in stress tolerance. Though genetic forces (e.g. mutation) determining population heterogeneity are well appreciated, non-genetic forces (e.g. stochastic gene expression) have been less thoroughly elucidated. Recently, we used single-cell RNA sequencing to quantify transcript heterogeneity in Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. There is significant regulatory variation in individual yeast cells, both before and after stress. Heterogeneity in the expression of transcription factor targets implicated regulatory variability in establishing population-level heterogeneity. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1 revealed coordinated and decoupled nucleocytoplasmic shuttling. The live cell imaging coupled with analysis of the single-cell expression data suggests that cells may filter decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells. We have developed an optogenetic toolkit that allows us to construct light-activated transcription factors. Using these transcription factors, we are working to resolve the relationship between bursts of transcription factor activity, burst coordination, and gene expression leading to population-level heterogeneity.  

Bio: 

Dr. Megan N. McClean is an Assistant Professor in the Department of Biomedical Engineering at the University of Wisconsin-Madison. She received her B.A. from the University of California-Berkeley and her Ph.D. from Harvard University, both in Applied Mathematics. During her thesis work with Dr. Sharad Ramanathan, she used computational modeling in combination with single-cell microscopy to understand the mechanisms of crosstalk prevention and signaling specificity in Saccharomyces cerevisiae MAP kinase pathways. Prior to joining UW-Madison, Dr. McClean was a Lewis-Sigler Fellow at Princeton University where she utilized optogenetics, control theory, and synthetic biology to develop tools for controlling biological circuits. At UW-Madison, Dr. McClean’s research group employs systems and synthetic biology approaches to understand biological signal processing in fungi, including human fungal pathogens, with implications for improving treatment strategies. Dr. McClean holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and a Maximizing Investigators’ Research Award from the National Institute of General Medical Sciences.