Controlling Information Propagation in Biofilms with Molecular Communication - 1=Biomaterials and tissue engineering - 2 = Engineering

Context: We have begun to recognize bacteria as not strictly unicellular organisms but also having complex coordinated adaptability to environmental conditions. Localised colonies of bacteria have the capacity of a multicellular organization and cellular differentiation. One common structure is the biofilm, which is a hindrance in some circumstances (e.g., medicine) but could be beneficial in others (e.g., microbial fuel cells, waste remediation). While biofilms have the resilience to external threats, they maintain sophisticated internal structures that likely facilitate coordinated behaviour and information sharing. The use of these structures as communication channels is not well understood, but provide opportunities to model the propagation of information and control how effectively this can be done.

Aims:
This project aims to introduce a communication theoretic approach to the understanding and control of internal biofilm signalling.

Objectives:
1) Develop a mathematical model of how molecular signals propagate in embedded biofilm channels.
2) Develop a communication model to quantify the reliable information throughput of biofilm channels.
3) Design strategies to control biofilm efficacy by disrupting or enhancing biofilm communication channels.
4) Validation of the physical modelling with wet lab imaging of biofilm channels.

Novelty of Methodology:
A communication-centric model for biofilm channels does not yet exist. We will develop novel physical system models of increasing complexity, based on existing images of biofilm channels. Simplifications of the channel geometry will enable the application of existing signal propagation models and results developed for idealised molecular communication systems, such that we can describe the statistics of an end-to-end channel as an aggregation of simplified systems. The new end-to-end channel model will enable corresponding communications analysis, where we propose realistic signalling schemes and then describe the likelihood of successful information transfer. Once we develop an understanding and intuition about the communication capability of biofilm channels, we will be able to identify where the system is most sensitive to parameter perturbations. This will enable us to predict suitable strategies to control biofilm signalling and design experiments for physical validation.