How Single Cells Sense Smad3 Signal

Citation

Frick, Christopher Lee (2019) How Single Cells Sense Smad3 Signal. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/WNM4-4R58. https://resolver.caltech.edu/CaltechTHESIS:05222019-160829503

Abstract

Animal cells possess the remarkable ability to send, receive, and respond to molecular signals. Accurate processing of these signals is essential for the development and maintenance of complex cell fates and organization. The regulation of cell behavior in response to signal is mediated by signal transduction pathways, which are highly conserved protein-protein interaction networks. Recent work has shown that the activation of biomolecular networks is highly sensitive to natural cellular variation in protein levels, making it unclear how these pathways accurately and reliably transmit signals in single cells. In this thesis, I address this question in the Transforming Growth Factor-β (Tgf-β) pathway, a major intercellular signaling pathway in animal cells. First, we asked whether extracellular signal is accurately transduced into pathway activation in single cells. Examining pathway dynamics in live reporter cells, we found evidence for fold-change detection. Although the level of nuclear Smad3 varied across cells, the fold change in the level of nuclear Smad3 was a more precise outcome of ligand stimulation. Indeed, by measuring Smad3 dynamics and gene expression in the same cells, we confirm that the fold-change in Smad3 carries signal in the pathway. These findings suggest that cells encode Tgf-β signal in a precise Smad3 fold-change as a strategy for coping with cellular noise. Second, we brought two significant advancements, which enabled us to ask how tightly signaling dynamics dictates target gene expression. By imaging endogenous dynamics of both signaling and gene expression in clonal cells, and correlating the full dynamics with a non-manifold learning approach, we show that knowing the full dynamics of Smad3 is necessary but not sufficient to predict the full dynamics of target gene expression. Indeed, we find evidence for the role of mTOR, MEK5, and cell cycle as cell-specific variables that influence how a cell responds to Smad3. This demonstrates the extent to which, even across clonal cells, response to signal considerably varies, as each cell computes decisions based on its own internal state.

Thesis Files