Diffusive Interface Model for Actomyosin Driven Cell Oscillations
Diffusive Interface Model for Actomyosin Driven Cell Oscillations
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DOI：
10.1007/s11538-021-00866-8
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发表时间：
2021-03
影响因子：
3.5
通讯作者：
Xiaoqiang Wang;Liyong Zhu
中科院分区：
文献类型：
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作者：
Xiaoqiang Wang;Liyong Zhu
在本文中，我们建立了肌动球蛋白驱动的细胞振荡的相场模型。在我们的模型中，振荡从肌动蛋白皮层断裂开始。破裂后，由于肌动蛋白和肌球蛋白分布不平衡，不同膜成分的收缩力不平衡，导致脂质转移到凸出的膜室中。因此我们可以观察到细胞振荡。在整个过程中，肌动蛋白和肌球蛋白的聚合和解聚发挥着重要作用。我们在相场方法的框架下给出了详细的公式，其中相场函数用于描述细胞膜的不同部分，并结合肌动蛋白和肌球蛋白在不同成分的分布。整个系统被描述为三维空间中的一组与时间相关的偏微分方程。采用前向欧拉法求解该系统。谱方法用于空间离散化，以提高效率和准确性。根据精心选择的参数，进行三维模拟并与生物图像进行比较。模拟证明肌动球蛋白动力学是细胞振荡的主要原因。此外，我们的方法可以很容易地扩展到细胞极化的模拟。我们还将我们的数值模拟与生物实验进行了比较。该模型给出了将扩散界面方法应用于复杂生物学实验的示例。
In this paper, we build phase-field models for the actomyosin driven cell oscillations. In our modeling, an oscillation starts from an actin cortex breakage. After the breakage, due to the unbalanced distribution of actin and myosin, there is unbalanced contraction force in different membrane components, which then results in the lipids transferring to the bulged membrane compartment. As such we can observe a cell oscillation. During the whole process, the actin and myosin polymerization and depolymerization play important roles. We give detailed formulations under the framework of phase-field methodology, in which phase-field functions are used to describe different parts of the cell membrane, integrated with the distribution of the actin and myosin at different components. The whole system is described as a set of time-dependent partial differential equations in three-dimensional space. Forward Euler method is used to solve the system. The spectral method is used for spatial discretizations for efficiency and accuracy purpose. Given carefully selected parameters, three-dimensional simulations are performed and compared with biological images. The simulations prove that actomyosin dynamics are the major reasons for cell oscillations. Further, our method can be easily extended into the simulations of cell polarization. We also compared our numerical simulations with biological experiments. This modeling gives an example of applying diffusive interface methods toward complex biology experiments.