A Reaction-Diffusion-Chemotaxis Model to Understand the Collective Behavior of Microbial Life

Micro-organisms play a pivotal role in the existence and function of life. Despite the simplicity of their anatomy, these creatures display complex phenomena, including autopoiesis, biofilm formation, bioluminescence, and, of course, virulence. Existing literature establishes that these phenomena arise due to microbial communication, such as quorum sensing and chemotaxis. While these communication pathways have been extensively studied in isolation, mathematical models that predict how microorganisms respond collectively when multiple communication pathways are present remain underexplored. To this end, we developed a large-scale Eulerian-Lagrangian numerical framework to investigate the emergent collective dynamics and structures under multiple communication pathways. In this framework, we treat microbes as colloidal particles that can produce, consume, and respond to dissolved species in the suspended media. By tracking the spatiotemporal variation of the dissolved species, we evaluate the dynamical trajectories and states of microbial entities. The framework is able to qualitatively recover some features observed in experiments and provides a scalable method to predict the collective response of microbial life.