2021 Annual Meeting
(226g) Investigating the Spatiotemporal Patterns of Bacteria Using Computational Tools
Author
This work uses computational methods to probe the fundamental interactions of microbial communities. An agent-based model that simulates the physical interactions of self-propelled microbes is extended to evaluate polydisperse bacterial shapes and incorporate molecule secreting and sensing. This model is used to evaluate the influence of chemical and physical interactions on the collective dynamics of a bacterial community containing two species. The results are compared to recent experimental work provided by Limoli et al. (eLife 8:e47365, 2019) visualising the early interactions between a multispecies community of bacteria relevant to clinical situations, such as respiratory infections and chronic wounds. This provides insight into the âfightingâ process in which P. aeruginosa, rod-shaped bacteria, are able to sense secreted products from S. aureus, sphere-shaped bacteria, and change their motility behaviour from collective movement to single-cell exploration with increased velocity. This produces a dynamic situation in which the P. aeruginosa surround and âattackâ the S. aureus groups and significantly inhibit growth of these sphere-shaped bacteria.
This work provides a valuable tool to probe the fundamental controlling mechanisms and expected spatiotemporal patterns of diverse multispecies microbial communities. This is a key component in understanding how bacteria sense and respond to each other more generally, and how we may be able to rationally manipulate interspecies behaviour during infections - whether that means preventing bacteria with harmful effects (such as P. aeruginosa and S. aureus within the airways of cystic fibrosis patients) from engaging in physical interactions or bringing species together who synergise to produce a beneficial effect.