AI 中文总结
研究异质细胞混合物中的趋化作用，推广自发生趋化模型，分析集体迁移模式，发现耦合迁移产生传播阶地，推导出前沿迁移速度表达式，揭示异质性对传感器细胞迁移的影响，提供理解异质自发生趋化理论框架。
AI 中文摘要
趋化作用是细胞群体在发育过程和免疫反应中集体迁移的基础。虽然单细胞类型集体趋化的理论研究受到了广泛关注，但涉及多种相互作用细胞类型的异质趋化仍知之甚少。在此，我们推广了一个异质自发生趋化模型并分析了由此产生的集体迁移模式。我们表明两种细胞类型之间的耦合迁移会产生“传播阶地”——以不同速度移动的耦合行进前沿。仅传感器细胞群体引领迁移集体，较慢的混合传感器 - 消费者细胞群体随后。我们的分析表明这些前沿通过自发生趋化因子梯度的动力学耦合。我们仅根据模型参数和实验可测量量推导出两个前沿迁移速度的解析表达式。我们的分析结果表明异质性可通过传感器细胞的自发生趋化增强远程迁移。虽然传感器细胞可从与消费者细胞混合中受益，但后者与同类型细胞混合时迁移更有效。总之，我们的结果为理解异质自发生趋化提供了一个全面的理论框架。
英文摘要
Chemotaxis underlies the collective migration of cell populations in developmental processes and immune responses. While the theoretical investigation of single-cell-type collective chemotaxis has received considerable attention, heterogeneous chemotaxis involving multiple interacting cell types remains poorly understood. Here, we generalise a model of heterogeneous self-generated chemotaxis and analyse the resulting collective migration patterns. We show that coupled migration between two cell types gives rise to \emph{propagating terraces} -- coupled travelling fronts moving at different speeds. While a sensor-only population leads the migrating collective, a slower mixed sensor-consumer population follows. Our analysis reveals that these fronts are coupled via the dynamics of the self-generated chemoattractant gradients. We derive analytical expressions for the migration speeds of the two fronts just in term of model parameters and experimentally measurable quantities. Our analytical results reveal that heterogeneity can enhance long-range migration via self-generated chemotaxis for sensor cells. While sensor cells can leverage benefit from mixing with consumer cells, the latter migrate more efficiently when mixing with cells of the same type. Together, our results provide a comprehensive theoretical framework for understanding heterogeneous self-generated chemotaxis.
