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Published on: May 23, 2020
Biomimicry of quorum sensing using bacterial lifecycle model.
Ben Niu1, Hong Wang, Qiqi Duan
1College of Management, Shenzhen University, Shenzhen 518060, China. drniuben@gmail.com
BMC Bioinformatics
|July 3, 2013
Summary
This study introduces LCM-QS, a computational model simulating bacterial quorum sensing (QS) using an individual-based approach. This model enhances bacterial cooperation for efficient nutrient finding, inspiring new swarm intelligence algorithms.
Area of Science:
- Computational Biology
- Microbiology
- Artificial Intelligence
Background:
- Quorum sensing (QS) is crucial for bacterial survival and communication.
- Existing simulation models often lack population diversity due to uniform individual updates.
- There's a need for models that capture individual bacterial behavior and collective intelligence.
Purpose of the Study:
- To present LCM-QS, a novel computational model simulating bacterial quorum sensing (QS).
- To utilize an individual-based modeling approach within the Agent-Environment-Rule (AER) framework.
- To explore bacterial evolution and macroscopic behavior at the single-cell level.
Main Methods:
- Developed the LCM-QS model based on the bacterial lifecycle model (LCM) and AER scheme.
- Integrated sub-models for chemotaxis with QS, reproduction/elimination, and migration.
- Conducted comparative experiments in a 3-D environment with varying nutrient and noxious distributions.
Main Results:
- LCM-QS effectively simulates bacterial evolution and macroscopic behavior.
- Direct comparison of chemotaxis with and without QS demonstrated QS's efficiency.
- Artificial bacteria using QS rapidly located nutrient concentrations (global optima).
Conclusions:
- Biomimicking QS via the lifecycle model enhances cooperative search for resources.
- Artificial bacteria with QS communication abilities gather valuable information for directed movement.
- The model inspires the development of novel swarm intelligence optimization algorithms for real-world problems.
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