论文标题
学习在受限细胞迁移中的细胞细胞相互作用的动力学
Learning the dynamics of cell-cell interactions in confined cell migration
论文作者
论文摘要
从伤口愈合到癌症转移的生理过程中细胞的迁移动力学依赖于接触介导的细胞 - 细胞相互作用。这些相互作用在塑造迁移细胞的随机轨迹方面起着关键作用。虽然已经开发了单个细胞随机迁移动力学的数据驱动的物理形式,但相互作用细胞行为动力学的框架仍然难以捉摸。在这里,我们监视最小实验细胞对撞机中的随机细胞轨迹:一个哑铃形的微图案,对细胞对进行重复的细胞碰撞。我们观察到不同的特征行为,包括在碰撞时互相逆转,跟随并滑行。利用这一大型实验数据集的耦合细胞轨迹,我们推断出一种相互作用的运动方程,该方程式可以准确预测观察到的相互作用行为。我们的方法表明,可以通过排斥和摩擦相互作用来描述相互作用的非癌性MCF10A细胞。相反,癌性MDA-MB-231细胞表现出吸引人和抗跨相互作用,从而促进了这些细胞观察到的主要相对滑动行为。基于这些实验推断的相互作用,我们展示了该框架如何推广以提供对不同细胞类型的各种细胞相互作用行为的统一描述。
The migratory dynamics of cells in physiological processes, ranging from wound healing to cancer metastasis, rely on contact-mediated cell-cell interactions. These interactions play a key role in shaping the stochastic trajectories of migrating cells. While data-driven physical formalisms for the stochastic migration dynamics of single cells have been developed, such a framework for the behavioral dynamics of interacting cells still remains elusive. Here, we monitor stochastic cell trajectories in a minimal experimental cell collider: a dumbbell-shaped micropattern on which pairs of cells perform repeated cellular collisions. We observe different characteristic behaviors, including cells reversing, following and sliding past each other upon collision. Capitalizing on this large experimental data set of coupled cell trajectories, we infer an interacting stochastic equation of motion that accurately predicts the observed interaction behaviors. Our approach reveals that interacting non-cancerous MCF10A cells can be described by repulsion and friction interactions. In contrast, cancerous MDA-MB-231 cells exhibit attraction and anti-friction interactions, promoting the predominant relative sliding behavior observed for these cells. Based on these experimentally inferred interactions, we show how this framework may generalize to provide a unifying theoretical description of the diverse cellular interaction behaviors of distinct cell types.