Sliding of motor tails on cargo surface due to drift and diffusion affects their team arrangement and collective transport.

IF 2 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Saumya Yadav, Ambarish Kunwar
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引用次数: 4

Abstract

Kinesin is a microtubule-associated motor protein which works in teams to carry the cellular cargo transport. Lipid rafts on membranous cargos reorganize, causing the motors present in these areas to physically cluster. Unregulated clustering of motors leads to diseases such as Leishmaniasis, Newmann-Pick disease, etc. Variousin-vitroand computational studies have reported improved cargo velocity and travel distance of a fluid cargo as compared to a rigid cargo. However, only cargo velocity increases with increase in membrane fluidity of a fluid cargo. Thermal and motor forces acting tangentially on a cargo generate random torque and motor torque respectively, leading to cargo rotation and motor tail sliding on cargo surface. However, it is unknown which of these forces/torques play a crucial role in improving the transport properties. Here, we use computational models that incorporate random torque, motor torque, and combination of both random and motor torques to understand how they influence the clustering of Kinesin motors on cargo surface due to drift and diffusion of their tails. These studies were performed at varying tail diffusivity to understand their effect on clustering of tails in dispersed and clustered arrangement. We find that in dispersed arrangement, random torque does not cause clustering, whereas motor torque is crucial for clustering of tails on cargo surface, and tails sliding due to both random and motor torques have fastest cargo transport and maximum cooperativity. In clustered arrangement, tails slide to form a broad and steady cluster whose size increases with tail diffusivity resulting in decreased cargo runlength, velocity and cooperativity. These findings suggest that increased tail diffusivity negatively impacts the cluster and cargo transport of tails in the clustered arrangement, whereas it aids physical clustering of tails and cargo transport in dispersed arrangement.

机动机尾由于漂移和扩散在货物表面产生滑动,影响了机动机尾的班组安排和集体运输。
运动蛋白是一种微管相关的运动蛋白,它以团队的形式进行细胞货物运输。膜质货物上的脂筏重组,导致这些区域的马达物理聚集。不受控制的运动聚集导致利什曼病、纽曼-匹克病等疾病。各种体外计算研究报告说,与刚性货物相比,流体货物的货物速度和行进距离有所改善。然而,只有货物速度随着流体货物的膜流动性的增加而增加。切向货物的热力和电机力分别产生随机转矩和电机转矩,导致货物旋转和电机尾部在货物表面滑动。然而,尚不清楚这些力/力矩中哪一个在改善输运性能方面起关键作用。在这里,我们使用了包含随机扭矩、电机扭矩以及随机扭矩和电机扭矩的组合的计算模型,以了解它们如何由于尾部的漂移和扩散而影响Kinesin电机在货物表面上的聚类。这些研究是在不同的尾部扩散率下进行的,以了解它们在分散和聚集排列中对尾部聚类的影响。研究发现,在分散排列时,随机力矩不会导致尾部聚类,而电机力矩对尾部在货物表面的聚类至关重要,随机力矩和电机力矩共同作用下的尾部滑动具有最快的货物运输速度和最大的协同性。在集群排列中,尾部滑动形成一个广泛而稳定的集群,集群的大小随着尾部扩散系数的增加而增加,导致货物的行程长度、速度和协同性降低。这些结果表明,尾部扩散率的增加对尾部聚集和货物运输有负面影响,而对分散排列的尾部物理聚集和货物运输有帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Physical biology
Physical biology 生物-生物物理
CiteScore
4.20
自引率
0.00%
发文量
50
审稿时长
3 months
期刊介绍: Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity. Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as: molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division systems biology, e.g. signaling, gene regulation and metabolic networks cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis cell-cell interactions, cell aggregates, organoids, tissues and organs developmental dynamics, including pattern formation and morphogenesis physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation neuronal systems, including information processing by networks, memory and learning population dynamics, ecology, and evolution collective action and emergence of collective phenomena.
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