Genetic strategies for the quantitative control of cell-matrix mechanobiology

University Of California Berkeley, Berkeley CA

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Abstract

DESCRIPTION (provided by applicant): It is now widely acknowledged that cell behavior is highly sensitive to mechanical crosstalk with the extracellular matrix (ECM). While many powerful methods have been developed to control this communication through manipulation of the ECM, there are few tools available for the direct, cell-intrinsic control of cellular mechanotransductive signaling. In this proposal we advance and apply a genetic strategy we recently developed in which we control cell-ECM mechanical signaling through inducible expression of mechanotransductive genes. We have shown that this method enables graded and dynamic control of cortical stiffness, traction force generation, cell migration speed, and ECM remodeling. We have also shown that this approach vastly outperforms traditional pharmacologic strategies in terms of dose-response relationship, target availability, toxicity, and duration of action. We now propose to develop a second generation of this strategy and leverage it to address two unmet needs in the field of cell mechanobiology: First, we will place two genes under the control of promoters that can be induced or suppressed by two different small molecules, thereby enabling orthogonal control over two mechanotransductive genes. We will use this capability to construct a phase diagram of cell mechanical properties that quantitatively maps how the myosin activators Rho- associated kinase and myosin light chain kinase contribute to mechanobiological phenotype. Second, we will apply this strategy to quantitatively control how ECM mechanical properties regulate two important cell behaviors: cell motility speed and neural stem cell neurogenesis. In successful, this will enable us to decouple mechanically-triggered cell behaviors from the inputs themselves, thus potentially offering a way to rewire cell-matrix crosstalk to achieve desired phenotypic endpoints in arbitrarily specified microenvironments. This could offer a new and very powerful way to engineer cell behavior at cell-material interfaces in vitro and in vivo. Taken together, these studies will provide key proof of-principle for this approach as a tool for both quantitative cell biological discovery and cell ad tissue engineering/regenerative medicine applications.