尖锋集体细胞迁移和入侵的离散和连续数学模型

Matthew J Simpson, Keeley M Murphy, Scott W McCue, Pascal R Buenzli
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引用次数: 0

摘要

描述生物细胞种群的空间扩散和入侵的数学模型通常是在使用反应扩散方程的连续体建模框架中建立的。虽然基于线性扩散的连续统模型通常被用于捕获关键的实验观测,但线性扩散无法预测经常在实验中观察到的定义良好的尖锐锋。这一观察结果激发了非线性退化扩散的使用,然而这些非线性模型和相关参数缺乏明确的生物学动机和解释。在这里,我们采用不同的方法,通过开发一个随机离散模型,结合生物启发机制,然后推导出反应扩散连续体极限。受实验观察的启发,模拟中的代理将细胞外物质沉积在晶格上,这些物质局部沉积在基体上,并且代理的运动与基体密度成正比。模拟二维圆屏障分析的离散模拟说明了离散模型如何支持平滑和锐锋密度分布,这取决于衬底沉积的速率。将离散模型粗粒度化,得到一种新的偏微分方程(PDE)模型,其解精确地逼近离散模型的平均数据。新的离散模型和pde近似提供了一个简单的,具有生物学动机的框架,用于模拟具有明确定义的尖锐前沿的细胞群体的扩散,生长和入侵
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Discrete and continuous mathematical models of sharp-fronted collective cell migration and invasion
Mathematical models describing the spatial spreading and invasion of populations of biological cells are often developed in a continuum modelling framework using reaction-diffusion equations. While continuum models based on linear diffusion are routinely employed and known to capture key experimental observations, linear diffusion fails to predict well-defined sharp fronts that are often observed experimentally. This observation has motivated the use of nonlinear degenerate diffusion, however these nonlinear models and the associated parameters lack a clear biological motivation and interpretation. Here we take a different approach by developing a stochastic discrete lattice-based model incorporating biologically-inspired mechanisms and then deriving the reaction-diffusion continuum limit. Inspired by experimental observations, agents in the simulation deposit extracellular material, that we call a substrate, locally onto the lattice, and the motility of agents is taken to be proportional to the substrate density. Discrete simulations that mimic a two--dimensional circular barrier assay illustrate how the discrete model supports both smooth and sharp-fronted density profiles depending on the rate of substrate deposition. Coarse-graining the discrete model leads to a novel partial differential equation (PDE) model whose solution accurately approximates averaged data from the discrete model. The new discrete model and PDE approximation provides a simple, biologically motivated framework for modelling the spreading, growth and invasion of cell populations with well-defined sharp fronts
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