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Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity
Published on: March 11, 2015
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A Mixed-Culture Biofilm Model with Cross-Diffusion
Kazi A Rahman1, Rangarajan Sudarsan2,3, Hermann J Eberl4,5
1Department Mathematics and Statistics, University of Guelph, Guelph, ON, N1G 2W1, Canada. krahman@uoguelph.ca.
Bulletin of Mathematical Biology
|November 20, 2015
Summary
We developed a new model for mixed-culture biofilms where species movement is interdependent. This cross-diffusion model impacts local biomass distribution but not total biomass, advancing biofilm research.
Area of Science:
- Microbiology
- Mathematical Biology
- Biophysics
Background:
- Biofilms are complex microbial communities crucial in various environments.
- Existing deterministic models often oversimplify ecological interactions within biofilms.
- Understanding interspecies dynamics is key to predicting biofilm behavior.
Purpose of the Study:
- To propose a novel deterministic continuum model for mixed-culture biofilms.
- To incorporate interdependent species movement via a degenerate cross-diffusion system.
- To compare two distinct derivations of the proposed model.
Main Methods:
- Developing a deterministic continuum model with cross-diffusion.
- Deriving the model from both discrete lattice equations and continuous mass balances.
- Conducting numerical simulations for competition, allelopathy, and aerobic/anaerobic systems.
Main Results:
- Both derivations yield the same partial differential equation (PDE) model under specific closure assumptions.
- Cross-diffusion significantly influences the local spatial distribution of microbial biomass.
- Overall system biomass and other lumped quantities remain unaffected by cross-diffusion.
Conclusions:
- The proposed cross-diffusion model offers a more nuanced representation of mixed-culture biofilms.
- Cross-diffusion is critical for understanding spatial structuring within biofilms.
- The model provides a generalized framework applicable to diverse biofilm ecological scenarios.

