Department of Mathematics, The Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK.
The Maxwell Institute for Mathematical Sciences, School of Mathematics, University of Edinburgh, Edinburgh, EH9 3FD, Scotland, UK.
J Math Biol. 2024 Feb 26;88(3):32. doi: 10.1007/s00285-024-02047-2.
Collective cell migration is a multicellular phenomenon that arises in various biological contexts, including cancer and embryo development. 'Collectiveness' can be promoted by cell-cell interactions such as co-attraction and contact inhibition of locomotion. These mechanisms act on cell polarity, pivotal for directed cell motility, through influencing the intracellular dynamics of small GTPases such as Rac1. To model these dynamics we introduce a biased random walk model, where the bias depends on the internal state of Rac1, and the Rac1 state is influenced by cell-cell interactions and chemoattractive cues. In an extensive simulation study we demonstrate and explain the scope and applicability of the introduced model in various scenarios. The use of a biased random walk model allows for the derivation of a corresponding partial differential equation for the cell density while still maintaining a certain level of intracellular detail from the individual based setting.
细胞集体迁移是一种多细胞现象，出现在各种生物背景下，包括癌症和胚胎发育。“集体性”可以通过细胞间相互作用来促进，例如共同吸引和运动抑制接触。这些机制通过影响 Rac1 等小 GTPase 的细胞内动力学来作用于细胞极性，这对于定向细胞迁移至关重要。为了模拟这些动力学，我们引入了一个有偏差的随机游走模型，其中偏差取决于 Rac1 的内部状态，而 Rac1 状态受到细胞间相互作用和趋化性线索的影响。在广泛的模拟研究中，我们展示并解释了所引入模型在各种情况下的范围和适用性。使用有偏差的随机游走模型可以为细胞密度导出相应的偏微分方程，同时仍保持从基于个体的设置中获得的一定程度的细胞内细节。
