Mechanics of lamellipodial stability, turning and self-polarization

描述（由申请人提供）：细胞运动呈阶梯状-细胞体突出、分级粘附、收缩和向前移位。一般来说，突起是基于肌动蛋白阵列的生长，粘附依赖于粘附蛋白的快速动力学，并且肌球蛋白倾向于收缩肌动蛋白凝胶导致向前移位。细胞通过使用许多类型的运动附属物和运动行为在不同的环境中移动。我们集中研究称为板状伪足的运动附属物-由许多细胞在平面上部署的细分支肌动蛋白-肌球蛋白网络。在板状体中，分子过程自组织成一个复杂的分子机器，执行一个连贯的机械动作。经过几十年的深入研究，稳定的板状幼体运动的分子清单和一般原理变得越来越清楚。然而，伤口愈合，转移和组织发育的重要生理过程需要阐明不稳定的细胞运动。除了生理和临床应用，定量了解这种运动是细胞生物学的一个基本问题，也是对我们对活跃的自组织细胞骨架的初步认识的一个关键考验。 具体来说，人们对细胞如何启动运动、转动和分裂的了解很少。虽然有一个重要的作用，调节这些过程的生化途径，我们的目标是了解他们的力学通过研究鱼类上皮角膜细胞的优势，顺利整合的运动步骤。计算建模是一个不可或缺的工具的发现，所以我们提出了一个建模/实验调查的不稳定运动。 初步的数据和模型提示，产生力的蛋白质分布和细胞运动和几何形状的相互依赖性是细胞极化，转向和分裂的基础。具体而言，我们假设运动启动的机制是一个正反馈，其中在最初对称的细胞的预期后方的粘附减弱导致局部增加肌动蛋白流，这进一步增加了粘附断裂。这种反馈导致不可逆的不对称流动和重新分布的肌球蛋白，肌动蛋白和粘附细胞。类似地，细胞后部粘附的不对称释放与梯度肌动蛋白周转和偏斜肌动蛋白流动相结合，产生正反馈，产生细胞转向。最后，我们假设，有多余的膜或不足的肌动蛋白的原因增加固有的波动肌动蛋白密度的细胞放大肌球蛋白产生的不稳定性，导致不均匀的突起和细胞分裂。我们将测试这些假设的粘弹性收缩肌动球蛋白网络的移动边界lamellipodium开发模型。我们将模拟连续的确定性和随机离散模型，并预测关键蛋白质的分布，流动和力，以及细胞形状和速度。我们将通过将预测与从野生型和扰动细胞获得的数据进行比较来校准和测试模型。 这项工作将导致先进的理解细胞运动，也将产生广泛适用的新的数学工具，以及数学模型组件，可以集成到现有的细胞迁移模型。

DESCRIPTION (provided by applicant): Cell motility goes in steps - protrusion, graded adhesion, contraction and forward translocation of the cell body. In general, protrusion is based on growth of actin arrays, adhesion depends on rapid dynamics of adhesion proteins, and myosin tendency to contract actin gel leads to the forward translocation. Cells move through diverse environments by employing many types of motile appendages and locomotory behaviors. We concentrate on the well studied motile appendage called lamellipodium - thin branched actin-myosin network deployed by many cells on flat surfaces. In the lamellipodium, molecular processes self-organize into a complex molecular machine executing a coherent mechanical action. As a result of decades of intense study, molecular inventory and general principles of steady lamellipodial locomotion are becoming clear. However, crucial physiological processes of wound healing, metastasis and tissue development require elucidation of unsteady cell movements. Besides physiological and clinical applications, quantitative understanding of such movements is a fundamental problem of cell biology and a critical test of our fledgling knowledge of active self-organizing cytoskeleton. Specifically, there is little understanding of how cells initiate motility, turning and splitting. Though there is a significant role for biochemical pathways regulating these processes, we aim to understand their mechanics by studying fish epithelial keratocytes that have an advantage of smooth integration of the motility steps. Computational modeling is an indispensable tool of discovery, so we propose a modeling/experimental investigation of the unsteady movements. Preliminary data and modeling hint that interdependence of force-generating protein distributions and cell movement and geometry underlies cell polarization, turning and splitting. Specifically, we hypothesize that the mechanism of motility initiation is a positive feedback in which the weakening of adhesion at the prospective rear of an initially symmetric cell causes local increase of actin flow, which further increases adhesion breakage. This feedback leads to irreversible asymmetric flows and re-distribution of myosin, actin and adhesions that polarize the cell. Similarly, asymmetric release of adhesions at the cell rear coupled with graded actin turnover and skewed actin flow creates a positive feedback generating cell turning. Finally, we hypothesize that having excess membrane or insufficient actin causes increased inherent fluctuations of actin density in the cell amplified by myosin-generated instabilities leading to uneven protrusions and to cell splitting. We will test these hypotheses by developing models of the viscoelastic contractile actomyosin network in the moving-boundary lamellipodium. We will simulate continuous deterministic and stochastic discrete models and predict key proteins' distributions, flows and forces, as well as cell shapes and speeds. We will calibrate and test the models by comparing the predictions with data obtained from wild type and perturbed cells. This work will result in advanced understanding of cell motility, and will also produce broadly applicable novel mathematical tools as well as mathematical model components that can be integrated with existing models of cell migration.