Abstract
How cells with different genetic makeups compete in tissues is an outstanding question in developmental biology and cancer research. Studies in recent years have revealed two fundamental mechanisms of cell competition, driven by short-range biochemical signalling or by long-range mechanical stresses within the tissue. In both scenarios, the outcome of cell competition has generally been characterised using population-scale metrics. However, the underlying strategies for competitive interactions at the single-cell level remain elusive. Here, we develop a cell-based computational model for competition assays informed by high-throughput timelapse imaging experiments. By integrating physical cell interactions with cellular automata rules for proliferation and apoptosis, we find that the emergent modes of cell competition are determined by a trade-off between entropic and energetic properties of the mixed tissue. While biochemical competition is strongly sensitive to local tissue organisation, mechanical competition is largely driven by the difference in homeostatic pressures of the two competing cell types. These findings suggest that competitive cell interactions arise when the local tissue free energy is high, and proceed until free energy is minimised.
