Department of Physics, University of California, San Diego, La Jolla, California.
Department of Physics and Astronomy, Johns Hopkins University, Baltimore, Maryland; Department of Biophysics, Johns Hopkins University, Baltimore, Maryland.
Biophys J. 2018 Jun 19;114(12):2986-2999. doi: 10.1016/j.bpj.2018.04.020.
Cell-cell communication plays an important role in collective cell migration. However, it remains unclear how cells in a group cooperatively process external signals to determine the group's direction of motion. Although the topology of signaling pathways is vitally important in single-cell chemotaxis, the signaling topology for collective chemotaxis has not been systematically studied. Here, we combine mathematical analysis and simulations to find minimal network topologies for multicellular signal processing in collective chemotaxis. We focus on border cell cluster chemotaxis in the Drosophila egg chamber, in which responses to several experimental perturbations of the signaling network are known. Our minimal signaling network includes only four elements: a chemoattractant, the protein Rac (indicating cell activation), cell protrusion, and a hypothesized global factor responsible for cell-cell interaction. Experimental data on cell protrusion statistics allows us to systematically narrow the number of possible topologies from more than 40,000,000 to only six minimal topologies with six interactions between the four elements. This analysis does not require a specific functional form of the interactions, and only qualitative features are needed; it is thus robust to many modeling choices. Simulations of a stochastic biochemical model of border cell chemotaxis show that the qualitative selection procedure accurately determines which topologies are consistent with the experiment. We fit our model for all six proposed topologies; each produces results that are consistent with all experimentally available data. Finally, we suggest experiments to further discriminate possible pathway topologies.
细胞间通讯在集体细胞迁移中起着重要作用。然而,目前尚不清楚群体中的细胞如何协同处理外部信号,以确定群体的运动方向。尽管信号通路的拓扑结构在单细胞趋化性中至关重要,但群体趋化性的信号拓扑结构尚未得到系统研究。在这里,我们结合数学分析和模拟,找到用于集体趋化性中多细胞信号处理的最小网络拓扑结构。我们专注于果蝇卵室中的边缘细胞簇趋化性,其中已知对信号网络的几种实验扰动的反应。我们的最小信号网络仅包含四个元素:趋化剂、蛋白 Rac(表示细胞激活)、细胞突起和一个假设的负责细胞间相互作用的全局因子。细胞突起统计数据的实验数据使我们能够从超过 40000000 种可能的拓扑结构系统地缩小到只有六个最小拓扑结构,其中四个元素之间有六个相互作用。这种分析不需要相互作用的特定功能形式,只需要定性特征;因此,它对许多建模选择具有鲁棒性。对边缘细胞趋化性的随机生化模型的模拟表明,定性选择过程准确地确定了哪些拓扑结构与实验一致。我们对所有六个提出的拓扑结构进行了拟合;每个拓扑结构都产生与所有可用实验数据一致的结果。最后,我们提出了实验来进一步区分可能的通路拓扑结构。