Date of Award

Winter 12-15-2016

Author's School

Graduate School of Arts and Sciences

Author's Department

Biology & Biomedical Sciences (Computational & Molecular Biophysics)

Degree Name

Doctor of Philosophy (PhD)

Degree Type



Collective migration is the process by which cells organize individual motions to productively migrate as a group and plays a fundamental role in organism development, tissue regeneration, and cancer invasion. In development, coordinated migration facilitates the formation of complex organ structures and is required for proper dissemination of neural crest cells throughout an organism. After injury, this process allows breaches in epithelial layers to be repaired while maintaining tissue integrity, and in cancer, collective behavior enhances invasion of tumor cells into the surrounding tissue. Chapter 1 provides an introduction for the role of collective migration across an organism’s lifespan, the mechanisms used by cells to generate motile force, and the emergence of collective behavior. Chapter 2 dissects the intertwined roles of three fundamental parameters often altered in collective migration processes: cell density, cell adhesion, and cell-cell contractility through the Rho-ROCK-Myosin II signaling axis. Through quantitative analysis of large-scale time-lapse imaging and mathematical modeling, I identify force-sensitive contractility and cell packing as mediators of two distinct classes of collective migration. From these results, I formulate a phase-diagram of collective cell migration and test predictions in an in-vivo epithelium using genetic manipulations to drive collective motion between predicted migratory phases. In Chapter 3, the effect of phenotypic heterogeneity on the organization of cells is examined, providing insight into the effects of early cancer progression on epithelial dynamics. I find that mutant cells within an otherwise wild-type tissue impact organization through local and field-effects, disrupting normal dynamics and leading to cell-type segregation. Chapter 4 provides a theoretical framework for quantitatively understanding and predicting the dynamics of protein interactions underlying biological processes including collective migration. Traditional chemical kinetics approaches break down in situations where components are slow diffusing or in countable numbers, requiring the formulation of new models that take into account this level of complexity. Here I develop an event-driven algorithm that bridges well-mixed and unmixed systems and use it to predict the effect of apparent changes in enzymatic efficiency due to alterations in mobility that may be caused by protein complex formation. Overall the work in this dissertation advances our understanding of the structure and dynamics of collective migration and the parameters governing this process by combining quantitative statistical analysis, mathematical modeling, and in-vivo live imaging.


English (en)

Chair and Committee

Gregory D. Longmore

Committee Members

Elliot Elson, Guy Genin, Robert Mecham, Amit Pathak


Permanent URL: https://doi.org/10.7936/K7G73C31