Computational Models of Actin Regulation Driving Cytoskeletal Dynamics, Cell Polarity and Motion
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Author(s)
Hladyshau, Siarhei
Advisor(s)
Tsygankov, Denis
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Abstract
Cell morphodynamics is a fundamental biological process required for the healthy functioning of a eukaryotic organism. Understanding its regulatory mechanisms is needed for developing new strategies to treat numerous diseases, including cancer metastasis, excessive angiogenesis, congenital disorders, and chronic wounds. My work focuses on Rho family GTPases (RhoA, Rac1, and Cdc42), known as the key regulators of actin cytoskeleton and cell motion. I developed a computational platform that allowed me to study different configurations of GTPase signaling pathways and capture the complex spatiotemporal distribution of these proteins driving cytoskeletal organization and dynamics. I applied this platform to investigate signaling bistability and the mechanisms of polarity establishment in yeast. I also used this methodology to study wave dynamics of GTPases and F-actin in the cortex of Patiria miniata and Xenopus laevis oocytes. I quantitatively reproduced different actin behaviors in these two organisms and revealed a critical role of quasi-static, low-amplitude patterns in the emergence of complex wave dynamics. Finally, I studied the regulation of cell ruffling by Cdc42 and Rac1 in epithelial breast cancer cells and mouse embryonic fibroblasts. Using my computational approach, I showed that cell edge velocity is regulated by the kinetic rate of GTPase activation rather than the concentration of the active molecules. My analysis also suggested that the timing of Rac1 and Cdc42 activity is cell-type dependent. I developed a model that reproduced such dependences and showed that feedback from Cdc42 and Rac1 was sufficient to control the activation delay when these GTPases have a common upstream regulatorily motif. I developed a series of image analysis pipelines for these studies that allowed precise tracking of GTPase activity and cell edge motion in simulations and experimental data.
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Date
2023-04-27
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Dissertation