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
Authored by Marta Ginovart, Xavier Portell, Clara Prats, Jared L Wilmoth, Peter W Doak, Andrea Timm, Michelle Halsted, John D Anderson, Scott T Retterer, Miguel Fuentes-Cabrera
Date Published: 2018
DOI: 10.3389/fmicb.2018.00033
Sponsors:
No sponsors listed
Platforms:
NetLogo
Model Documentation:
ODD
Flow charts
Model Code URLs:
Model code not found
Abstract
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.
Tags
Agent-based modeling
carbon
Pseudomonas aeruginosa
System
Sensitivity-analysis
Communities
Succession
Components
Nitrogen dynamics
Reveals
Type vi secretion
Silicon
microwell arrays
Microbial succession
Microbial organization
Spatial
confinement
Soils parameterization
Microwell chip