Genetic strategies for the quantitative control of cell-matrix mechanobiology

描述（由申请人提供）：现在人们普遍认为细胞行为对细胞外基质（ECM）的机械串扰高度敏感。虽然已经开发了许多强大的方法来通过操纵ECM来控制这种通信，但很少有工具可用于直接的、细胞内在的细胞机械转导信号控制。在本提案中，我们提出并应用了我们最近开发的一种遗传策略，通过诱导表达机械转导基因来控制细胞- ecm机械信号。我们已经证明，这种方法能够分级和动态控制皮质刚度、牵引力产生、细胞迁移速度和ECM重塑。我们还表明，这种方法在剂量-反应关系、靶点可利用性、毒性和毒性方面大大优于传统的药理学策略

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.