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Simulated actin reorganization mediated by motor proteins

机译:运动蛋白介导的模拟肌动蛋白重组

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Author summaryCell shape is dictated by a scaffolding network called the cytoskeleton. Actin filaments, a main component of the cytoskeleton, are found predominantly at the periphery of the cell, where they organize into different patterns in response to various stimuli, such as progression through the cell cycle. The actin filament reorganizations are mediated by motor proteins from the myosin superfamily. Using a realistic stochastic model that simulates actin filament and motor protein dynamics and interactions, we systematically vary motor protein kinetics and investigate their effect on actin filament organization. Using novel measures of spatial organization, we quantify conditions under which motor proteins, either alone or in combination, can produce the different actin filament organizations observed in vitro and in vivo. These results yield new insights into the role of motor proteins, as well as into how multiple types of motors can work collectively to produce specific actomyosin network patterns. Cortical actin networks are highly dynamic and play critical roles in shaping the mechanical properties of cells. The actin cytoskeleton undergoes significant reorganization in many different contexts, including during directed cell migration and over the course of the cell cycle, when cortical actin can transition between different configurations such as open patched meshworks, homogeneous distributions, and aligned bundles. Several types of myosin motor proteins, characterized by different kinetic parameters, have been involved in this reorganization of actin filaments. Given the limitations in studying the interactions of actin with myosin in vivo, we propose stochastic agent-based models and develop a set of data analysis measures to assess how myosin motor proteins mediate various actin organizations. In particular, we identify individual motor parameters, such as motor binding rate and step size, that generate actin networks with different levels of contractility and different patterns of myosin motor localization, which have previously been observed experimentally. In simulations where two motor populations with distinct kinetic parameters interact with the same actin network, we find that motors may act in a complementary way, by tuning the actin network organization, or in an antagonistic way, where one motor emerges as dominant. This modeling and data analysis framework also uncovers parameter regimes where spatial segregation between motor populations is achieved. By allowing for changes in kinetic rates during the actin-myosin dynamic simulations, our work suggests that certain actin-myosin organizations may require additional regulation beyond mediation by motor proteins in order to reconfigure the cytoskeleton network on experimentally-observed timescales.
机译:作者摘要细胞形状由称为细胞骨架的支架网络决定。肌动蛋白丝是细胞骨架的主要成分,主要存在于细胞的外围,在那里它们响应各种刺激(例如通过细胞周期的进展)组织成不同的模式。肌动蛋白丝重组由肌球蛋白超家族的运动蛋白介导。使用模拟肌动蛋白丝和运动蛋白动力学和相互作用的逼真随机模型,我们系统地改变运动蛋白动力学并研究它们对肌动蛋白丝组织的影响。使用新的空间组织测量方法,我们量化了运动蛋白(单独或组合)可以产生在体外和体内观察到的不同肌动蛋白丝组织的条件。这些结果为运动蛋白的作用以及多种类型的运动如何协同工作以产生特定的肌动球蛋白网络模式提供了新的见解。皮质肌动蛋白网络是高度动态的,在塑造细胞的机械特性中起着关键作用。肌动蛋白细胞骨架在许多不同的环境中经历显着重组,包括在定向细胞迁移期间和细胞周期过程中,当皮质肌动蛋白可以在不同的构型之间转换时,例如开放补丁网状结构、均匀分布和对齐的束。几种类型的肌球蛋白运动蛋白,其特征是不同的动力学参数,参与了肌动蛋白丝的重组。鉴于在体内研究肌动蛋白与肌球蛋白相互作用的局限性,我们提出了基于随机代理的模型,并开发了一套数据分析措施来评估肌球蛋白运动蛋白如何介导各种肌动蛋白组织。特别是,我们确定了单个运动参数,例如运动结合率和步长,这些参数产生具有不同收缩力水平和不同肌球蛋白运动定位模式的肌动蛋白网络,这些参数先前已通过实验观察到。在两个具有不同动力学参数的运动群体与同一肌动蛋白网络相互作用的模拟中,我们发现运动可能以互补的方式起作用,通过调整肌动蛋白网络组织,或者以拮抗的方式起作用,其中一种运动占主导地位。该建模和数据分析框架还揭示了实现运动群体之间空间隔离的参数制度。通过允许肌动蛋白-肌球蛋白动态模拟期间动力学速率的变化,我们的工作表明,某些肌动蛋白-肌球蛋白组织可能需要运动蛋白介导之外的额外调节,以便在实验观察到的时间尺度上重新配置细胞骨架网络。

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