Kulawiak Dirk Alexander, Camley Brian A, Rappel Wouter-Jan
Institut für Theoretische Physik, Technische Universität Berlin, Berlin, Germany.
Department of Physics, University of California, San Diego, San Diego, California, United States of America.
PLoS Comput Biol. 2016 Dec 16;12(12):e1005239. doi: 10.1371/journal.pcbi.1005239. eCollection 2016 Dec.
In cancer metastasis, embryonic development, and wound healing, cells can coordinate their motion, leading to collective motility. To characterize these cell-cell interactions, which include contact inhibition of locomotion (CIL), micropatterned substrates are often used to restrict cell migration to linear, quasi-one-dimensional paths. In these assays, collisions between polarized cells occur frequently with only a few possible outcomes, such as cells reversing direction, sticking to one another, or walking past one another. Using a computational phase field model of collective cell motility that includes the mechanics of cell shape and a minimal chemical model for CIL, we are able to reproduce all cases seen in two-cell collisions. A subtle balance between the internal cell polarization, CIL and cell-cell adhesion governs the collision outcome. We identify the parameters that control transitions between the different cases, including cell-cell adhesion, propulsion strength, and the rates of CIL. These parameters suggest hypotheses for why different cell types have different collision behavior and the effect of interventions that modulate collision outcomes. To reproduce the heterogeneity in cell-cell collision outcomes observed experimentally in neural crest cells, we must either carefully tune our parameters or assume that there is significant cell-to-cell variation in key parameters like cell-cell adhesion.
在癌症转移、胚胎发育和伤口愈合过程中,细胞能够协调它们的运动,从而产生集体运动。为了表征这些细胞间相互作用,其中包括运动接触抑制(CIL),微图案化基质常被用于将细胞迁移限制在线性的、准一维的路径上。在这些实验中,极化细胞之间的碰撞频繁发生,且只有几种可能的结果,比如细胞改变方向、相互黏附或彼此交错而过。利用一个集体细胞运动的计算相场模型,该模型包括细胞形状力学和一个用于CIL的最小化学模型,我们能够重现两细胞碰撞中出现的所有情况。细胞内极化、CIL和细胞间黏附之间的微妙平衡决定了碰撞结果。我们确定了控制不同情况之间转变的参数,包括细胞间黏附、推进强度和CIL速率。这些参数为不同细胞类型为何具有不同碰撞行为以及调节碰撞结果的干预措施的效果提出了假设。为了重现神经嵴细胞实验中观察到的细胞间碰撞结果的异质性,我们要么仔细调整参数,要么假设在诸如细胞间黏附等关键参数上存在显著的细胞间差异。