Categorizing spatiotemporal dynamics of bacterial swarm fronts

Low-dimensional effective models have proved to be an essential tool for analyzing extensive high-dimensional complex biophysical data, enabling computationally efficient characterizations of the dynamics of living systems. Recent advances in automated experimental imaging allow recording the collective motion of bacterial swarms across Bacillus Subtilis' single-gene knockouts, whose morphology exhibit a rich breadth of macroscopic phenomenology based on their genotype. Here, we reduce the complex dynamics of the multicellular system to the time evolution of closed curves by representing the swarms by their moving boundary. The curves provide a three-dimensional spacetime surface representation of each mutant's phenomenology. We model these spacetime surfaces using a simple geometric model incorporating gauge invariances and physical constraints. Utilizing modern inference techniques for dynamical systems, we infer the parameters of this simplified model for each mutant and use the results to cluster the spatiotemporal phenotype of the swarm shape dynamics under varying genotypes.