Epithelial Cell Mechanobiology in Mechanically Heterogeneous Microenvironments

项目摘要 在发育和疾病过程中，上皮细胞可以集体迁移，有或没有经历上皮细胞迁移。 间充质转化（EMT），通过异质基质，使基本过程，如 分支形态发生、纤维化和肿瘤侵袭。细胞外基质（ECM） 超出当前ECM刚度的特性，例如限制和过去的ECM刚度，可以从根本上 改变上皮细胞的反应通过一系列项目，结合实验和模拟， 建议将揭示新的模式集体细胞的行为矩阵的异质刚度和 地形我们将测量基底膜缺陷周围上皮细胞的EMT和迁移 （BM）样矩阵，确定由于缺陷诱导的EMT的3D侵入，建立计算模型以 了解速率依赖性EMT演变，并阻止BM降解。我们亦会评估 上皮细胞是否可以深入到它们的基质中进行感知，并根据远处的硬化改变反应， 矩阵。在另一个项目中，我们将研究细胞片如何在3D样的封闭环境中迁移， 可调刚度和形貌。我们将把细胞核的形状与细胞骨架的重组联系起来， 细胞如何适应过去和现在基质的不同硬度。这些项目的成果将使新的 上皮细胞对基质异质性的反应的基本理解， 这是一个尚未探索的领域，可以揭示纤维化和癌症等疾病的新靶点。

PROJECT SUMMARY During development and disease, epithelial cells can migrate collectively, with or without undergoing epithelial- mesenchymal transition (EMT), through heterogeneous matrices, enabling fundamental processes such as branching morphogenesis, fibrosis, and tumor invasion. We have shown that extracellular matrix (ECM) properties beyond the current ECM stiffness, such as confinement and past ECM stiffness, can fundamentally alter epithelial responses. Through a collection of projects, combining experiments and simulations, this proposal will reveal new modes collective cell behaviors in matrices of heterogeneous stiffness and topography. We will measure EMT and migration of epithelial cells around defects in a basement membrane (BM)-like matrix, determine 3D invasion due to defect-induced EMT, build a computational model to understand rate-dependent EMT evolution, and pharmacologically disrupt BM degradation. We will also assess whether the epithelial cells can sense deeply into their matrix and alter responses based on distant stiffening of the matrix. In another project, we will investigate how cell sheets migrate in 3D-like confined environments of tunable stiffness and topography. We will connect nuclear shape with cytoskeletal reorganization to understand how cells adapt to distinct stiffnesses of past and present matrices. Outcomes of these projects will enable new fundamental understanding of epithelial cell responses to matrix heterogeneities that have remained unexplored and could reveal novel targets for diseases such as fibrosis and cancer.