Department of Mathematics, Imperial College London SW7 2AZ, United Kingdom.
Centre for Mathematical Biology, Department of Mathematical Sciences, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom.
Phys Rev E. 2019 Jun;99(6-1):062413. doi: 10.1103/PhysRevE.99.062413.
There are numerous biological scenarios in which populations of cells migrate in crowded environments. Typical examples include wound healing, cancer growth, and embryo development. In these crowded environments cells are able to interact with each other in a variety of ways. These include excluded-volume interactions, adhesion, repulsion, cell signaling, pushing, and pulling. One popular way to understand the behavior of a group of interacting cells is through an agent-based mathematical model. A typical aim of modellers using such representations is to elucidate how the microscopic interactions at the cell-level impact on the macroscopic behavior of the population. At the very least, such models typically incorporate volume-exclusion. The more complex cell-cell interactions listed above have also been incorporated into such models; all apart from cell-cell pulling. In this paper we consider this under-represented cell-cell interaction, in which an active cell is able to "pull" a nearby neighbor as it moves. We incorporate a variety of potential cell-cell pulling mechanisms into on- and off-lattice agent-based volume exclusion models of cell movement. For each of these agent-based models we derive a continuum partial differential equation which describes the evolution of the cells at a population level. We study the agreement between the agent-based models and the continuum, population-based models and compare and contrast a range of agent-based models (accounting for the different pulling mechanisms) with each other. We find generally good agreement between the agent-based models and the corresponding continuum models that worsens as the agent-based models become more complex. Interestingly, we observe that the partial differential equations that we derive differ significantly, depending on whether they were derived from on- or off-lattice agent-based models of pulling. This hints that it is important to employ the appropriate agent-based model when representing pulling cell-cell interactions.
在许多生物场景中,细胞群体在拥挤的环境中迁移。典型的例子包括伤口愈合、癌症生长和胚胎发育。在这些拥挤的环境中,细胞能够以多种方式相互作用。这些相互作用包括排斥体积相互作用、黏附、排斥、细胞信号传递、推动和拉动。一种理解相互作用细胞群体行为的流行方法是通过基于代理的数学模型。使用此类表示形式的建模者的一个典型目标是阐明细胞水平的微观相互作用如何影响群体的宏观行为。至少,此类模型通常包含体积排斥。上述更复杂的细胞-细胞相互作用也已被纳入此类模型;除了细胞-细胞拉动之外的所有相互作用。在本文中,我们考虑了这种代表性不足的细胞-细胞相互作用,其中活跃的细胞在移动时能够“拉动”附近的邻居。我们将各种潜在的细胞-细胞拉动机制纳入基于代理的有向和无向网格体积排除细胞运动模型中。对于每个基于代理的模型,我们推导出一个描述细胞群体水平演变的连续偏微分方程。我们研究了基于代理的模型与连续、基于群体的模型之间的一致性,并比较和对比了一系列基于代理的模型(考虑了不同的拉动机制)。我们发现基于代理的模型和相应的连续模型之间通常具有良好的一致性,但随着基于代理的模型变得更加复杂,一致性会变差。有趣的是,我们观察到我们推导的偏微分方程差异很大,具体取决于它们是从基于有向或无向网格的拉动代理模型推导而来的。这表明在表示拉动细胞-细胞相互作用时,采用适当的基于代理的模型很重要。