Learning the space-time phase diagram of bacterial swarm expansion

Coordinated dynamics of individual components in active matter are an essential aspect of life on all scales. Establishing a comprehensive, causal connection between intracellular, intercellular, and macroscopic behaviors has remained a major challenge due to limitations in data acquisition and anal...

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Bibliographic Details
Main Authors: Jeckel, Hannah, Jelli, Eric, Hartmann, Raimo, Singh, Praveen K., Mok, Rachel V. (Rachel Verla), Totz, Jan Frederik, Vidakovic, Lucia, Eckhardt, Bruno, Dunkel, Jorn, Drescher, Knut
Other Authors: Massachusetts Institute of Technology. Department of Mathematics
Format: Article
Language:English
Published: National Academy of Sciences 2020
Online Access:https://hdl.handle.net/1721.1/125022
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Summary:Coordinated dynamics of individual components in active matter are an essential aspect of life on all scales. Establishing a comprehensive, causal connection between intracellular, intercellular, and macroscopic behaviors has remained a major challenge due to limitations in data acquisition and analysis techniques suitable for multiscale dynamics. Here, we combine a high-throughput adaptive microscopy approach with machine learning, to identify key biological and physical mechanisms that determine distinct microscopic and macroscopic collective behavior phases which develop as Bacillus subtilis swarms expand over five orders of magnitude in space. Our experiments, continuum modeling, and particle-based simulations reveal that macroscopic swarm expansion is primarily driven by cellular growth kinetics, whereas the microscopic swarming motility phases are dominated by physical cell–cell interactions. These results provide a unified understanding of bacterial multiscale behavioral complexity in swarms. ©2019 National Academy of Sciences Keywords: collective behavior; swarming; cell–cell interactions; microbiology; biofilm