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Bacterial Signaling

Bacterial Signaling

Bacterial signaling can occur within bacteria (intracellular) or between bacteria (intercellular). At times, a group of bacteria behaves like a community. To achieve this, they engage in quorum sensing, the perception of higher cell density that causes changes in gene expression. Quorum sensing involves both extracellular and intracellular signaling. The signaling cascade starts with a molecule called an autoinducer (AI). Individual bacteria produce AIs that move out of the bacterial cell...

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Related Experiment Video

Updated: Jun 23, 2025

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

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Published on: January 31, 2020

Electrical signaling in three-dimensional bacterial biofilms using an agent-based fire-diffuse-fire model.

Victor Carneiro da Cunha Martorelli¹, Emmanuel Akabuogu¹, Rok Krašovec²

¹Biological Physics, Department of Physics and Astronomy, University of Manchester, Oxford Rd., Manchester M13 9PL, United Kingdom and Division of Infection, Lydia Becker Institute of Immunology and Inflammation, School of Biological Sciences, University of Manchester, Oxford Rd., Manchester M13 9PT, United Kingdom.

Physical Review. E

|June 22, 2024

Summary

This summary is machine-generated.

Electrical signals in bacterial biofilms are modeled using agent-based simulations. Biofilm size, potassium ion properties, and geometry influence signal propagation, revealing complex behaviors like superdiffusion.

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Area of Science:

Microbiology
Biophysics
Computational Biology

Background:

Bacterial biofilms exhibit complex electrical signaling behaviors.
Understanding these signals is crucial for comprehending biofilm dynamics and interactions.
Previous models have not fully captured the 3D electrical dynamics influenced by ion transport and biofilm structure.

Purpose of the Study:

To model and analyze electrical signaling in three-dimensional bacterial biofilms using agent-based methods.
To investigate the influence of potassium ion (K+) properties and biofilm geometry on signal propagation.
To explore the impact of structural defects on electrical wavefront dynamics.

Main Methods:

Utilized agent-based modeling to simulate electrical signaling in Escherichia coli biofilms.
Incorporated experimental data to model potassium ion wavefronts under blue light stress.
Analyzed wavefront propagation, velocity, and mean-square displacement (MSD) across various biofilm geometries and defect inclusions.

Main Results:

Electrical signaling initiates only after biofilms exceed a critical size threshold.
Potassium ion diffusivity and threshold concentration significantly impact wavefront velocity and propagation dynamics (subdiffusive vs. superdiffusive).
Biofilm geometry and the presence of cylindrical defects introduce additional kinetic regimes to wavefront propagation and MSD.

Conclusions:

Biofilm size, K+ ion transport properties, and structural features collectively govern electrical signal propagation.
The study provides insights into the complex biophysical mechanisms underlying electrical communication in bacterial communities.
Agent-based models offer a powerful framework for dissecting emergent phenomena in microbial systems.