Cell-extracellular matrix (ECM) interactions play a critical role in regulating important biological phenomena, including morphogenesis, tissue repair, and disease states. In vivo, cells are subjected to various mechanical, chemical, and electrical cues to collectively guide their functionality within a specific microenvironment. To better understand the mechanisms regulating cell adhesive, differentiation, and motility dynamics, researchers have developed in vitro platforms to synthetically mimic native tissue responses. While important information about cell-ECM interactions have been revealed using these systems, a knowledge gap currently exists regarding how cell responses in static environments relate to the dynamic cell-ECM interaction behaviors observed in vivo. Advances at the intersection of materials science, biophysics, and cell biology have recently enabled the production of dynamic ECM mimics where cells can be exposed to controlled mechanical, electrical or chemical cues to directly decouple cell-ECM related behaviors from cell-cell or cell-environmental factors. Utilization of these dynamic synthetic biomaterials will enable discovery of novel mechanisms fundamental in tissue development, homeostasis, repair, and disease.

In this dissertation, the primary goal was to evaluate how mechanical changes in the ECM regulate cell motility and polarization responses. This was accomplished through two major aims:​ 1) by developing a modular image processing tool that could be applied in complex synthetic in vitro microenvironments to asses cell motility dynamics, and 2) to utilize that tool to advance understanding of mechanobiology and mechanotransduction processes associated with development, wound healing, and disease progression. Therefore, the first portion of this thesis (Chapters 2 and 3) dealt with proof of concept for our newly developed automated cell tracking system, termed ACTIVE (automated contour-based tracking for in vitro environments), while the second portion of this thesis (Chapter 4-7) addressed applying this system in multiple experimental designs to synthesize new knowledge regarding cell-ECM or cell-cell interactions.

In Chapter 1, we introduced why cell-ECM interactions are essential for in vivo processes and highlighted the current state of the literature. In Chapter 2, we demonstrated that ACTIVE could achieve greater than 95% segmentation accuracy at multiple cell densities, while improving two-body cell-cell interaction error by up to 43%. In Chapter 3 we showed that ACTIVE could be applied to reveal subtle differences in fibroblast motility atop static wrinkled or static nonwrinkled surfaces at multiple cell densities. In Chapters 4 and 5, we characterized fibroblast motility and intracellular reorganization atop a dynamic shape memory polymer biomaterial, focusing on the role of the Rho-mediated pathway in the observed responses. We then utilized ACTIVE to identify differences in subpopulation dynamics of monoculture versus co-culture endothelial and smooth muscle cells (Chapter 6). In Chapter 7, we applied ACTIVE to investigate E. coli biofilm formation atop poly(dimethylsiloxane) surfaces with varying stiffness and line patterns. Finally, we presented a summary and future work in Chapter 8. Collectively, this work highlights the capabilities of the newly developed ACTIVE tracking system and demonstrates how to synthesize new information about mechanobiology and mechanotransduction processes using dynamic biomaterial platforms.