Cytoskeletal Oscillations: Mathematical Modeling Integrated with Experiments

描述（由申请人提供）： 所有细胞的一个重要特性是它们感知和响应环境的能力。通常，适当的反应涉及细胞形态的大规模变化。例如，环境因素，如激素或生长因子，可导致细胞分化、增殖或迁移。细胞形状的这些全局变化是高度协调的，需要肌动蛋白细胞骨架的动态调节。因此，了解肌动蛋白细胞骨架和相关的调节蛋白如何作为一个完整的系统发挥作用是细胞生物学的一个核心挑战。细胞骨架的自发性质只能借助于数学建模和计算机模拟来理解。利用理论和实验的相互作用，该项目旨在获得细胞圆化过程中发生的细胞形态振荡的机械理解。我们设想，以及提供洞察动态细胞骨架系统，这种方法将提供洞察其他 基本的生物过程，如细胞分裂和变形虫迁移。此外，由于许多疾病，包括癌症，涉及细胞骨架的失调，对该系统的机械理解可能会导致治疗疾病的新的治疗策略。该项目的总体目标是：1）了解肌动蛋白细胞骨架如何自组织以产生细胞形状的持续振荡; 2）开发数学模型，预测化学和机械扰动对振荡行为的影响。最初的模型将被开发来测试我们的假设，振荡 这是RhoA活性行波的结果。波阵面通过涉及鸟嘌呤核苷酸交换因子（GEF）募集的正反馈循环传播，从而加速RhoA的激活。一个缓慢的负反馈回路，涉及GTdR激活蛋白（GAP），使RhoA失活，确保RhoA活性保持局部的波传播。为了验证这一假设，我们开发了三个目标，将实验研究与计算分析和数学建模相结合。在目的I单细胞实验进行表征振荡细胞和测试模型预测的动态结构和机械化学性质。正确利用和解释目标1中产生的数据需要使用计算方法。目标2的重点是开发先进的图像处理工具。在目标3多相模型，空间和时间上解决化学物种，细胞膜，皮层和胞质溶胶的开发和测试，通过直接比较与目标1的实验结果。

DESCRIPTION (provided by applicant): Summary An important property of all cells is their ability to sense and respond to their environment. Often the appropriate response involves large scale changes in cell morphology. For example environmental cues, such as hormones or growth factors, can lead to cell differentiation, proliferation, or migration. These global changes in cell shape are highly coordinated and require dynamic regulation of the actin cytoskeleton. Therefore understanding how the actin cytoskeleton and associated regulatory proteins function as an integrated system is a central challenge for cell biology. The self-emergent properties of the cytoskeleton can only be understood with the aid of mathematical modeling and computational simulations. Using the interplay of theory and experiment, this project seeks to gain a mechanistic understanding of the oscillations in cell morphology that occur during cell rounding. We envision that as well as providing insight into a dynamic cytoskeletal system, this approach will provide insight into other fundamental biological processes, such as cell division and amoeboid migration. Moreover, because many disorders, including cancer, involve a dysregulation of the cytoskeleton, a mechanistic understanding of this system may lead to novel therapeutic strategies for treating disease. The overarching goals of this project are: 1) to understand how the actin cytoskeleton self-organizes to generate sustained oscillations in cell shape and 2) to develop mathematical models that predict the consequences of chemical and mechanical perturbations on the oscillatory behavior. The initial models will be developed to test our hypothesis that oscillations occur as a result of a traveling wave of RhoA activity. The wave front is propagated by a positive feedback loop involving the recruitment of guanine nucleotide exchange factors (GEFs), which accelerate activation of RhoA. A slow negative feedback loop involving GTPase activating proteins (GAPs), which deactivate RhoA, ensures RhoA activity remains localized as the wave travels. To test this hypothesis we have developed three aims that integrate experimental investigations with computational analysis and mathematical modeling. In Aim I single cell experiments are performed to characterize the dynamic structural and mechanochemical properties of oscillating cells and test model predictions. Proper utilization and interpretation o the data generated in Aim 1 requires the use of computational approaches. The development of advanced image processing tools is the focus of Aim 2. In Aim 3 multiphase models that spatially and temporally resolve chemical species, cell membranes, the cortex and cytosol are developed and tested through direct comparisons with the experimental results of Aim 1.