A Microfluidics and Agent -Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

作者：Wilmoth Jared L; Doak Peter W; Timm Andrea; Halsted Michelle; Anderson John D; Ginovart Marta; Prats Clara; Portell Xavier; Retterer Scott T^*; Fuentes Cabrera Miguel^*

来源：Frontiers in Microbiology, 2018, 9: 33.

DOI：10.3389/fmicb.2018.00033

• agent-based modeling
• Pseudomonas aeruginosa
• Type VI secretion
• silicon microwell arrays
• microbial succession
• microbial organization
• spatial confinement

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of Hi Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.

• 出版日期2018-2-6