Growth and Dynamics of Extended Actin Structures

0240770 Carlsson这项工作旨在阐明细胞整合一组外部输入以确定运动反应的机制。算法的开发用于治疗的交联和弹性的肌动蛋白丝网络中存在的几种类型的交联蛋白。这些用于确定细胞对影响交联和分支速率的外部信号的响应。该算法使用随机增长的方法，它对待肌动蛋白丝的生长，解聚，封盖，分支的形成和分离，并通过交联连接到彼此的长丝附件。弹性效应包括在算法中使用的特殊点的方法。肌动蛋白细胞骨架的三维结构是按照单个亚基的分辨率。模型中的速率参数的值是从简化情况下的体外实验中获得的。该代码还用于评估自发形成局部突起的可能性。模型预测进行了测试聚合实验与几种类型的交联和分支蛋白质。 几乎所有类型的细胞都能以与肌肉细胞截然不同的方式运动：白色血细胞追逐细菌，细胞在受伤后移动以重塑组织，以及迁移癌细胞。这种运动是基于蛋白质肌动蛋白，这是非常丰富的细胞，并积累在长丝。这些细丝可以相互连接，形成网络或其他类型的结构，这些结构可以推动细胞膜，从而导致细胞移动。细胞是否移动以及如何移动的“决定”是基于外部信号，这些信号激活或停用各种类型的细丝连接。但是，对于给定的一组外部信号，肌动蛋白结构究竟会形成什么样的形式，目前还不清楚。计算预测这些结构使用强大的模拟方法的基础上并行计算机。通过建立细胞内肌动蛋白结构对外部信号的反应，人们有望更好地理解与这些肌动蛋白结构相关的疾病的本质。这也将有助于了解癌细胞的迁移，最终有助于癌症治疗的发展。这项赠款是根据联合DMS/NIGMS倡议，以支持研究赠款在数学生物学领域。这是一项由美国国家科学基金会数学科学部（DMS）和美国国立卫生研究院国家普通医学科学研究所（NIGMS）赞助的联合竞赛。

0240770Carlsson This work is aimed at clarifying the mechanisms by which cells integrate a set of external inputs to determine a motility response. Algorithms are developed for treating cross-linking and elasticity of growing actin-filament networks in the presence of several types of cross-linking proteins. These are used to determine the response of a cell to external signals that influence cross-linking and branching rates. The algorithms use a stochastic-growth methodology, which treats actin filament growth, depolymerization, capping, branch formation and detachment, and attachment of filaments to each other by cross-links. Elastic effects are included in the algorithms by the use of a special-points method. The three-dimensional structure of the actin cytoskeleton is followed at a resolution of individual subunits. The values of the rate parameters in the model are obtained from in vitro experiments for simplified cases. The code is also used to evaluate the potential for spontaneous formation of localized protrusions. The model predictions are tested by polymerization experiments with several types of cross-linking and branching proteins. Practically all types of cells are capable of moving in a way very different from muscle cells: white blood cells chasing bacteria, cells moving to remodel tissue after an injury, and migrating cancerous cells. Such motion is based on the protein actin, which is very abundant in cells, and accumulates in long filaments. These filaments can connect to each other, forming networks or other types of structures, which can push against a cell membrane and thus cause the cell to move. The "decision" about whether and how a cell moves is based on external signals, which activate or deactivate various types of filament connections. But it is not known exactly what actin structures form in response to a given set of external signals. The calculations predict these structures using powerful simulation methodologies based on parallel computers. By thus establishing the response of the actin structures in cells to external signals, one can hope to better understand the nature of diseases related to these actin structures. This will also help in understanding the migration of cancerous cells, which could eventually aid the development of cancer treatments. This grant is made under the Joint DMS/NIGMS Initiative to Support Research Grants in the Area of Mathematical Biology. This is a joint competition sponsored by the Division of Mathematical Sciences (DMS) at the National Science Foundation and the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health.