Self-organization principles of cell cycles and gene expressions in the development of cell populations

Abstract: A big challenge in current biology is to understand the exact self-organization mechanism underlying complex multi-physics coupling developmental processes. With multiscale computations of from subcellular gene expressions to cell population dynamics that is based on first principles, we show that cell cycles can self-organize into periodic stripes in the development of E. coli populations from one single cell, relying on the moving graded nutrient concentration profile, which provides directing positional information for cells to keep their cycle phases in place. Resultantly, the statistical cell cycle distribution within the population is observed to collapse to a universal function and shows a scale invariance. Depending on the radial distribution mode of genetic oscillations in cell populations, a transition between gene patterns is achieved. When an inhibitor-inhibitor gene network is subsequently activated by a gene-oscillatory network, cell populations with zebra stripes can be established, with the positioning precision of cell-fate-specific domains influenced by cells' speed of free motions. Such information may provide important implications for understanding relevant dynamic processes of multicellular systems, such as biological development.