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

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 enviro...

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Bibliographic Details
Published in:	Frontiers in microbiology 2018-02, Vol.9, p.33-33
Main Authors:	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
Format:	Article
Language:	eng
Subjects:	agent-based modeling BASIC BIOLOGICAL SCIENCES Matemàtiques i estadística Mathematical modelling MATHEMATICS AND COMPUTING microbial organization microbial succession Microbiology Models matemàtics Pseudomonas aeruginosa silicon microwell arrays spatial confinement theory and applications Type VI secretion Àrees temàtiques de la UPC
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Summary:	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 H1-Type VI secretion system (T6SS) mutants of . 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.
ISSN:	1664-302X 1664-302X