Toward an integrative understanding of mammalian cell motility

在过去几年中，在了解哺乳动物细胞运动的许多详细动力学机制方面取得了重大进展。这些包括局灶粘连的作用，肌动蛋白流动的时空组织，前缘膜对肌动蛋白聚合的反应，以及相反的肌凝蛋白微丝在后部产生收缩应力中的作用。现在是时候将这些知识结合到一个数学模型中，该模型可以处理整个细胞的形态动力学，并将运动与机械数据（如牵引力测量）和亚细胞信号信息（如特定分子参与者的定位数据）相关联。本研究旨在构建并验证内皮细胞模型。从数学方面来看，新元素包括将上述所有过程嵌入到移动的细胞几何中，通过相场方法实现；后者在从凝固到多相流体流动等领域的许多移动边界问题中显示出其相关性。实验数据将利用最先进的微流体装置获得，以提供受控的细胞环境，并将包括信号分子的空间模式（位置和激活）以及力的测量。模型预测将在许多不同的细胞系和受到各种药理学治疗的细胞中进行测试。获得细胞运动的定量理解对于许多关键的生物医学系统都很重要，从癌症转移到对病原体的炎症反应。生物物理工具已经达到了人们可以获得运动机制各个部分的高质量数据的程度；例如，我们可以测量细胞在其移动的基底上施加的力。与此同时，计算建模的进步已经展示了如何解决涉及流体流动和发生在移动域内的化学反应的复杂问题。我们的建议旨在结合这两种能力，实验生物物理学和计算建模，以创建一种定量方法来研究特定类型的哺乳动物细胞的运动。一旦成功，我们的方法可以扩展到其他类型的细胞和在更复杂的空间中移动的细胞。最终的回报将是增加基本的理解和提高影响细胞运动的能力，也许可以防止原发肿瘤的细胞在目标组织中建立继发菌落。该提案是为了响应DMS/NIGMS联合倡议，以支持生物和数学科学的界面研究而提交的。该基金由数学科学部的数学生物学项目资助，并由美国国家科学基金会物理部的生命系统物理学项目共同资助。

There has been significant progress over the last few years in understanding many of the detailed dynamical mechanisms underlying mammalian cell motility. These include the role of focal adhesions, the spatio-temporal organization of actin flow, the response of the leading-edge membrane to actin polymerization and conversely the role of myosin minifilaments in creating contractile stress at the rear. It is now an opportune time to combine this knowledge into a mathematical model which can treat the morphodynamics of the whole cell, and correlate motion with both mechanical data (such as traction-force measurements) and sub-cellular signaling information (such as localization data for specific molecular players.) This proposal aims at constructing and validating such a model for endothelial cells. From the mathematics side, the novel element includes embedding all of the aforementioned processes into a moving cell geometry, enabled by the phase-field approach; the latter has shown its relevance in many moving boundary problems in fields ranging from solidification to multiphase fluid flow. Experimental data will be obtained by utilizing state-of-the-art microfluidic devices so as to provide controlled cell environments and will include the measurement of spatial patterns of signaling molecules (location and activation) as well as forces. Model predictions will be tested in a number of different cell lines and in cells subject to a variety of pharamacological treatments.Obtaining a quantitative understanding of cell motility is of importance for many critical biomedical systems, ranging from cancer metastases to inflammatory response to pathogens. Biophysical tools have reached the point where one can obtain high-quality data about various parts of the motility mechanism; for example, we can measure the forces exerted by the cell on the substrate on which it moves. At the same time, advances in computational modeling have shown how to tackle complex problems involving fluid flow and chemical reactions taking place inside a moving domain. Our proposal aims at combining these two capabilities, experimental biophysics and computational modeling to create a quantitative approach to the motion of a specific type of mammalian cell. Once successful, our methodology could be extended to other cell types and to cells moving in more complicated spaces. The eventual payoff would be both an increased fundamental understanding and an increased capability of affecting cell motility, perhaps to prevent cells from a primary tumor from establishing secondary colonies in target tissues.The proposal was submitted in response to the Joint DMS/NIGMS Initiative to Support Research at the Interface of the Biological and Mathematical Sciences. The grant is funded by the Program of Mathematical Biology of the Division of Mathematical Sciences and co-funded by the Program Physics of Living Systems in the Physics Division of NSF.