Academic Journal
Hybrid cellular automaton-based model for quorum sensing-controlled biofilm evolution.
| Τίτλος: | Hybrid cellular automaton-based model for quorum sensing-controlled biofilm evolution. |
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| Συγγραφείς: | Sarukhanian S; Research Center of the Artificial Intelligence Institute, Innopolis University, 1, Universitetskaya Str., Innopolis, 420500, Russia., Kuttler C; Technical University of Munich, 3, Boltzmann Str., Garching, 85747, Germany., Maslovskaya A; Research Center of the Artificial Intelligence Institute, Innopolis University, 1, Universitetskaya Str., Innopolis, 420500, Russia. Electronic address: a.maslovskaya@innopolis.ru. |
| Πηγή: | Computers in biology and medicine [Comput Biol Med] 2026 Aug 15; Vol. 213, pp. 111852. Date of Electronic Publication: 2026 Jul 10. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE |
| Imprint Name(s): | Publication: New York : Elsevier Original Publication: New York, Pergamon Press. |
| Ιατρικοί όροι (MeSH): | Quorum Sensing*/physiology , Biofilms*/growth & development , Models, Biological* , Computer Simulation* |
| Περίληψη: | Computational modeling and in silico studies are critical for understanding how the spatial organization of biofilms contributes to antimicrobial tolerance and persistence. The paper presents a novel hybrid computational framework for the discrete-in-space dynamical modeling of bacterial biofilms. The approach combines a cellular automaton, which generates naturalistic biofilm morphology on a hexagonal lattice, with discrete analogues of reaction-diffusion equations governing the distribution of nutrients and signaling molecules. This design incorporates a quorum sensing feedback mechanism that links local signaling molecule concentration to biofilm spreading. The simulation system was developed in C# on the Unity platform, and the source code together with a Windows executable release was deposited on Zenodo. The biological plausibility of the simulated AHL and population dynamics was assessed through a semi-qualitative comparison with published experimental observations. The results reproduce distinct growth regimes ranging from sparse, branched colonies to compact biofilms with continuous fronts. A two-parameter analysis reveals a curved transition boundary in the nutrient-threshold plane, demonstrating that the effective quorum sensing activation threshold depends on nutrient availability. The qualitative comparison shows that the model can generate a biologically plausible transient AHL profile, including signal accumulation, formation of a maximum, and subsequent decrease, together with saturating population dynamics. This comparison is not intended as quantitative validation of absolute timing, concentration, or the detailed biochemical mechanism of AHL removal. These results support the proposed approach as a mechanistic tool for studying how quorum sensing and nutrient limitation jointly shape biofilm morphology. By providing an interpretable mechanistic simulation framework with explicit state variables, transition operators, and experimentally comparable outputs, the model establishes a basis for future AI-assisted workflows for diffusion-solver acceleration and automated parameter calibration. (Copyright © 2026 Elsevier Ltd. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Bacterial biofilm; Cellular automaton; Discrete reaction-diffusion model; In silico study; Quorum sensing; Simulation of bacterial growth |
| Entry Date(s): | Date Created: 20260710 Date Completed: 20260722 Latest Revision: 20260722 |
| Update Code: | 20260723 |
| DOI: | 10.1016/j.compbiomed.2026.111852 |
| PMID: | 42431014 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1879-0534 |
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| DOI: | 10.1016/j.compbiomed.2026.111852 |