Cytoskeletal Oscillations: Mathematical Modeling Integrated with Experiments

描述(由申请人提供)： 概述所有细胞的一个重要属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，可以导致细胞分化、增殖或迁移。这些细胞形状的全球变化是高度协调的，需要对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调控蛋白如何作为一个完整的系统发挥作用是细胞生物学面临的一个中心挑战。只有借助数学建模和计算模拟才能理解细胞骨架的自涌现特性。利用理论和实验的相互作用，这个项目试图从机制上理解细胞舍入过程中细胞形态的振荡。我们设想，除了提供对动态细胞骨架系统的洞察之外，这种方法还将提供对其他 基本的生物过程，如细胞分裂和变形虫迁移。此外，由于包括癌症在内的许多疾病涉及细胞骨架的失调，从机制上理解这一系统可能会导致治疗疾病的新的治疗策略。该项目的主要目标是：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)开发预测化学和机械扰动对振荡行为的后果的数学模型。最初的模型将被用来测试我们的假设 发生的原因是RhoA活动的一波行进。波前是通过一个正反馈回路传播的，涉及鸟嘌呤核苷酸交换因子(GEF)的招募，它加速了RhoA的激活。一个缓慢的负反馈环涉及GTP酶激活蛋白(GAP)，它使RhoA失活，确保RhoA活性在波传播时保持局部。为了验证这一假设，我们制定了三个目标，将实验研究与计算分析和数学建模相结合。在目标I中，进行了单电池实验，以表征振荡电池的动态结构和机械力化学性质，并测试模型预测。要正确利用和解释目标1中产生的数据，需要使用计算方法。开发先进的图像处理工具是目标2的重点。在目标3中，开发了在空间和时间上分解化学物种、细胞膜、皮质和细胞质的多相模型，并通过与目标1的实验结果进行直接比较来进行测试。

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.