Mechanics of lamellipodial stability, turning and self-polarization

描述(申请人提供)：细胞运动分为几个步骤--细胞体的突起、渐变粘连、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，黏附依赖于黏附蛋白的快速动态，肌球蛋白倾向于收缩肌动蛋白凝胶导致向前移位。细胞通过使用多种类型的运动附属物和移动行为在不同的环境中移动。我们集中研究了被许多细胞部署在平面上的运动附属物，称为板磷脂-细枝肌动蛋白-肌球蛋白网络。在板层中，分子过程自组织成一个复杂的分子机器，执行连贯的机械作用。经过几十年的密集研究，分子清单和稳定的板脂运动的一般原理变得清晰起来。然而，伤口愈合、转移和组织发育的关键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外，对这种运动的定量理解是细胞生物学的一个基本问题，也是对我们对主动自组织细胞骨架的初级阶段知识的关键考验。具体地说，人们对细胞如何启动运动、转动和分裂知之甚少。尽管生物化学途径在调节这些过程中起着重要的作用，但我们的目标是通过研究鱼类上皮角质细胞来了解它们的机制，这些细胞具有顺利整合运动步骤的优势。计算模拟是发现过程中不可缺少的工具，因此我们提出了对非定常运动的模拟/实验研究。初步数据和模型提示，产生力量的蛋白质分布与细胞运动和几何形状的相互依赖是细胞极化、转向和分裂的基础。具体地说，我们假设运动性启动的机制是一个正反馈，在初始对称的细胞的预期后部的粘附力的减弱导致局部肌动蛋白流动的增加，从而进一步增加粘附力的断裂。这种反馈导致不可逆的不对称流动和肌球蛋白、肌动蛋白和粘连的重新分布，使细胞极化。类似地，细胞后部粘连的不对称释放，再加上肌动蛋白的分级周转和扭曲的肌动蛋白流动，产生了产生细胞转向的正反馈。最后，我们假设有过多的膜或不足的肌动蛋白导致细胞内肌动蛋白密度的内在波动增加，肌球蛋白产生的不稳定导致不均匀的突起和细胞分裂。我们将通过建立运动边界层中的粘弹性收缩肌球蛋白网络模型来检验这些假设。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野生型和受干扰细胞获得的数据进行比较来校准和测试模型。这项工作将导致对细胞运动性的深入了解，并将产生广泛适用的新型数学工具以及可以与现有细胞迁移模型集成的数学模型组件。

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.