Emergence of diverse patterns driven by molecular motors in the motility assay.

Brandon Slater, Wonyeong Jung, Taeyoon Kim
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Abstract

Actomyosin contractility originating from interactions between F-actin and myosin motors in the actin cytoskeleton generates mechanical forces and drives a wide range of cellular processes including cell migration and cytokinesis. To probe the interactions between F-actin and myosin motors, the myosin motility assay has been popularly employed, which consists of myosin heads attached to a glass surface and F-actins gliding on the surface via interactions with the heads. Several experiments have shown that F-actins move in a collective fashion due to volume-exclusion effects between neighboring F-actins. Furthermore, Computational models have shown how changes in key parameters lead to diverse pattern formation in motility assay. However, in most of the computational models, myosin motors were implicitly considered by applying a constant propulsion force to filaments to reduce computational cost. This simplification limits the physiological relevance of the insights provided by the models and potentially leads to artifacts. In this study, we employed an agent-based computational model for the motility assay with explicit immobile motors interacting with filaments. We rigorously account for the kinetics of myosin motors including the force-velocity relationship for walking and the binding and unbinding behaviors. We probed the effects of the length, rigidity, and concentration of filaments and repulsive strength on collective movements and pattern formation. It was found that four distinct types of structures-homogeneous networks, flocks, bands, and rings-emerged as a result of collisions between gliding filaments. We further analyzed the frequency and morphology of these structures and the curvature, alignment, and rotational motions of filaments. Our study provides better insights into the origin and properties of patterns formed by gliding filaments beyond what was shown before.

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在运动测定中出现由分子马达驱动的不同模式。
肌动蛋白细胞骨架中的F-肌动蛋白和肌球蛋白马达之间的相互作用产生的肌球蛋白收缩性产生机械力,并驱动广泛的细胞过程,包括细胞迁移和胞质分裂。为了探测F-肌动蛋白和肌球蛋白马达之间的相互作用,肌球蛋白运动测定法已被广泛使用,它由附着在玻璃表面的肌球蛋白头和通过与头的相互作用在表面上滑动的F-肌动蛋白组成。几项实验表明,由于相邻F-肌动蛋白之间的体积排斥效应,F-肌动蛋白以集体的方式移动。此外,计算模型显示了关键参数的变化如何导致运动测定中不同模式的形成。然而,在大多数计算模型中,肌球蛋白马达是通过对细丝施加恒定的推进力来降低计算成本的。这种简化限制了模型提供的见解的生理相关性,并可能导致伪影。在这项研究中,我们采用了一个基于代理的计算模型来进行运动测定,其中明确的不动马达与细丝相互作用。我们严格地解释了肌球蛋白马达的动力学,包括行走的力-速度关系以及结合和非结合行为。我们探讨了细丝的长度、刚度、浓度和排斥强度对集体运动和图案形成的影响。研究发现,由于滑丝之间的碰撞,出现了四种不同类型的结构——均匀的网络、团、带和环。我们进一步分析了这些结构的频率和形态,以及细丝的曲率、排列和旋转运动。我们的研究为滑丝形成的图案的起源和性质提供了更好的见解。
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