Simulation of Emergent Spatial Organization in Multicellular Ensembles
Thank you Ana Ferreira, Justin Hsia, and Team Turing for all of your guidance and support during the summer!
Abstract: The spontaneous generation of patterning in an ensemble of otherwise homogeneous cells is of interest for studying biological development and engineering complex biological systems. It has been shown that these patterns arise as the result of inherent instabilities within a network, such as lateral-inhibition signaling as demonstrated by the Notch-Delta pathway. Although these models have been proven to work for a stationary aggregate of cells, it is unclear how such networks behave in a dynamic multicellular organism. We analyze these architectures by expanding upon the preexisting high-level spatial language, Proto. We present a simulation engine that incorporates cell-body collisions, growth, division, and motion that allows for various cell-cell interactions. By adopting a bottom-up, modular implementation paradigm, we aim to provide both higher-level functions for biological phenomena, such as growth and division. At the same time, we intend to still allow access to generalizable low-level functions that allow biologists to model novel mechanisms for cell-cell communication and interactions. We then use our engine to evaluate two potential mechanisms for spatial patterning. The first is lateral-inhibition through a Notch-Delta inspired system, where cells are capable of inhibiting each other to form checkerboard-like patterns. Second, we examine cell sorting by introducing cells that bind with each other with varying strengths, where having cells randomly express either strongly- or weakly-adhesive membrane proteins. These result in a core of tightly-bound cells surrounded by a periphery of the more weakly-bound cells. We envision that our platform will allow researchers to more readily explore complex behavior that arises from simple local contact rules, helping guide the development of novel synthetic platforms.