Diffusion Dynamics in Biofilms with Time-Varying Channels

TL;DR

This paper models the diffusion of signaling molecules in biofilms with channels that change over time, capturing the transition from isotropic to anisotropic diffusion during biofilm maturation.

Contribution

It introduces a time-varying channel model for biofilm diffusion, extending previous static models to better represent biofilm development stages.

Findings

TVC exhibits hybrid diffusion behavior combining isotropic and anisotropic features.

Mutual information increases with AI count, proximity, anisotropy, and shorter interference.

Model scalability demonstrated for larger biofilms and longer timescales.

Abstract

A biofilm is a self-contained community of bacteria that uses signaling molecules called autoinducers (AIs) to coordinate responses through the process of quorum sensing. Biofilms exhibit a dual role that drives interest in both combating antimicrobial resistance (AMR) and leveraging their potential in bioprocessing, since their products can have commercial potential. Previous work has demonstrated how the distinct anisotropic channel geometry in some biofilms affects AIs propagation therein. In this paper, a 2D anisotropic biofilm channel model is extended to be a time-varying channel (TVC), in order to represent the diffusion dynamics during the maturation phase when water channels develop. Since maturation is associated with the development of anisotropy, the time-varying model captures the shift from isotropic to anisotropic diffusion. Particle-based simulation results illustrate how the TVC is a hybrid scenario incorporating propagation features of both isotropic and anisotropic diffusion. This hybrid behavior aligns with biofilm maturation. Further study of the TVC includes characterization of the mutual information (MI), which reveals that an increased AI count, reduced transmitter -- receiver distance, greater degree of anisotropy, and shorter inter-symbol interference lengths increase the MI. Finally, a brief dimensional analysis demonstrates the scalability of the anisotropic channel results for larger biofilms and timescales.