A computational investigation of collective cell migration and oscillation

Abstract

Due to its critical role in important biological processes such as wound healing and cancer metastasis, collective cell migration has always been an area under intense investigation, both experimentally and theoretically, in the past few decades. Recent evidence has demonstrated that, when cultured on micro-patterned surfaces, living cells can move in a coordinated manner and form different migration patterns. However, the fundamental questions of what the key biophysical factors are, that dictate the cell motion modes, is still unclear. Here, I present a theoretical investigation to show that, depending on the strength of cell-cell adhesion and the interplay between myosin contraction and mechanical stretch, cells can adopt distinct migration modes. Specifically, the cell stretch-myosin activity feedback was found to be critical for the assembly of actin contractile cable at the edge of the propagating monolayer, allowing cells to migrate along functionalized patterns on the surface while “flying” over non-adherent areas via the formation of suspended cell bridges. On the other hand, strong cell-cell attachment enables cells to move as a chain along the narrow strip pattern without breaking into individual ones. Furthermore, the presence of random propelling forces breaks the symmetry of the migration pattern of cells and allows them to move in a vortex fashion on patterns with sizes above a critical value, all in good agreement with recent experimental observations. Also, the oscillatory morphodynamics of cohesive tissues, a phenomenon emerging from the collective movement of cells, is also captured by using the aforementioned stretch-myosin feedback in its time-delayed form. By revealing the mechanisms of how biochemical and mechanical cues activate, regulate, and even switch the migration mode of epithelial cells, this work enhances our basic understanding of how processes such as morphogenesis and cancer metastasis take place, as well as provides insights into finding new ways to direct the collective behavior of cells in the future.