Unveiling bacterial communication with a MATLAB GUI implementing the diffusion-based quorum sensing model.
GUI
MATLAB
Organism and diffusion coefficient
Quorum sensing
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
07 Jun 2024
07 Jun 2024
Historique:
received:
09
01
2024
accepted:
30
05
2024
medline:
8
6
2024
pubmed:
8
6
2024
entrez:
7
6
2024
Statut:
epublish
Résumé
Bacteria employ quorum sensing as a remarkable mechanism for coordinating behaviors and communicating within their communities. In this study, we introduce a MATLAB Graphical User Interface (GUI) that offers a versatile platform for exploring the dynamics of quorum sensing. Our computational framework allows for the assessment of quorum sensing, the investigation of parameter dependencies, and the prediction of minimum biofilm thickness required for its initiation. A pivotal observation from our simulations underscores the pivotal role of the diffusion coefficient in quorum sensing, surpassing the influence of bacterial cell dimensions. Varying the diffusion coefficient reveals significant fluctuations in autoinducer concentration, highlighting its centrality in shaping bacterial communication. Additionally, our GUI facilitates the prediction of the minimum biofilm thickness necessary to trigger quorum sensing, a parameter contingent on the diffusion coefficient. This feature provides valuable insights into spatial constraints governing quorum sensing initiation. The interplay between production rates and cell concentrations emerges as another critical facet of our study. We observe that higher production rates or cell concentrations expedite quorum sensing, underscoring the intricate relationship between cell communication and population dynamics in bacterial communities. While our simulations align with mathematical models reported in the literature, we acknowledge the complexity of living organisms, emphasizing the value of our GUI for standardizing results and facilitating early assessments of quorum sensing. This computational approach offers a window into the environmental conditions conducive to quorum sensing initiation, encompassing parameters such as the diffusion coefficient, cell concentration, and biofilm thickness. In conclusion, our MATLAB GUI serves as a versatile tool for understanding the diverse aspects of quorum sensing especially for non-biologists. The insights gained from this computational framework advance our understanding of bacterial communication, providing researchers with the means to explore diverse ecological contexts where quorum sensing plays a pivotal role.
Identifiants
pubmed: 38849458
doi: 10.1038/s41598-024-63661-0
pii: 10.1038/s41598-024-63661-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
13104Informations de copyright
© 2024. The Author(s).
Références
Rutherford, S. T. Bacterial quorum sensing: Its role in virulence and possibilities for its control. Cold Spring Harb. Perspect. Med. 2(11), a012427. https://doi.org/10.1101/cshperspect.a012427 (2012).
doi: 10.1101/cshperspect.a012427
pubmed: 23125205
pmcid: 3543102
Pérez-Velázquez, J., Gölgeli, M. & García-Contreras, R. Mathematical modelling of bacterial quorum sensing: a review. Bull. Math. Biol. 78, 1585–1639 (2016).
doi: 10.1007/s11538-016-0160-6
pubmed: 27561265
Lu, L. et al. Screening strategies for quorum sensing inhibitors in combating bacterial infections. J. Pharm. Anal. 12, 1–14 (2022).
doi: 10.1016/j.jpha.2021.03.009
pubmed: 35573879
Ahmad, I., Khan, M. S. A., Husain, F. M., Zahin, M. & Singh, M. Bacterial quorum sensing and its interference: Methods and significance. Microbes Microbial Technol. Agric. Environ. Appl. 127–161 (2011).
Miller, C. & Gilmore, J. Detection of quorum-sensing molecules for pathogenic molecules using cell-based and cell-free biosensors. Antibiotics 9, 259 (2020).
doi: 10.3390/antibiotics9050259
pubmed: 32429345
pmcid: 7277912
Montagut, E. J. & Marco, M. P. Biological and clinical significance of quorum sensing alkylquinolones: Current analytical and bioanalytical methods for their quantification. Anal. Bioanal. Chem. 413, 4599–4618 (2021).
doi: 10.1007/s00216-021-03356-x
pubmed: 33959788
Xu, Y., Dhaouadi, Y., Stoodley, P. & Ren, D. Sensing the unreachable: Challenges and opportunities in biofilm detection. Curr. Opin. Biotechnol. 64, 79–84 (2020).
doi: 10.1016/j.copbio.2019.10.009
pubmed: 31766008
Frederick, M. R., Kuttler, C., Hense, B. A. & Eberl, H. J. A mathematical model of quorum sensing regulated eps production in biofilm communities. Theor. Biol. Med. Model. 8, 1–29 (2011).
doi: 10.1186/1742-4682-8-8
Emerenini, B. O., Hense, B. A., Kuttler, C. & Eberl, H. J. A mathematical model of quorum sensing induced biofilm detachment. PLoS ONE 10, e0132385 (2015).
doi: 10.1371/journal.pone.0132385
pubmed: 26197231
pmcid: 4511412
Brown, D. Linking molecular and population processes in mathematical models of quorum sensing. Bull. Math. Biol. 75, 1813–1839 (2013).
doi: 10.1007/s11538-013-9870-1
pubmed: 23892934
Stewart, P. S. Diffusion in biofilms. J. Bacteriol. 185, 1485–1491 (2003).
doi: 10.1128/JB.185.5.1485-1491.2003
pubmed: 12591863
pmcid: 148055
Pikulin, V. P. & Pohozaev, S. I. Equations in Mathematical Physics: A Practical Course (Springer Science and Business Media, 2012).
Alberghini, S. et al. Consequences of relative cellular positioning on quorum sensing and bacterial cell-to-cell communication. FEMS Microbiol. Lett. 292, 149–161 (2009).
doi: 10.1111/j.1574-6968.2008.01478.x
pubmed: 19187204
Ward, J. P. et al. Mathematical modelling of quorum sensing in bacteria. Math. Med. Biol. 18, 263–292 (2001).
doi: 10.1093/imammb/18.3.263
Sonner, S., Efendiev, M. A. & Eberl, H. J. On the well-posedness of a mathematical model of quorum-sensing in patchy biofilm communities. Math. Methods Appl. Sci. 34, 1667–1684 (2011).
doi: 10.1002/mma.1475
Gölgeli Matur, M. Mathematical Modeling of Quorum Sensing: Two different approaches. Ph.D. thesis, Technische Universität München (2013).
Monod, J. The growth of bacterial cultures. Annu. Rev. Microbiol. 3, 371–394 (1949).
doi: 10.1146/annurev.mi.03.100149.002103
Kelly, W. R., Hornberger, G. M., Herman, J. S. & Mills, A. L. Kinetics of btx biodegradation and mineralization in batch and column systems. J. Contam. Hydrol. 23, 113–132 (1996).
doi: 10.1016/0169-7722(95)00092-5
Kim, D.-J., Choi, J.-W., Choi, N.-C., Mahendran, B. & Lee, C.-E. Modeling of growth kinetics for pseudomonas spp. during benzene degradation. Appl. Microbiol. Biotechnol. 69, 456–462 (2005).
doi: 10.1007/s00253-005-1997-z
pubmed: 15856223
Gude, S. et al. Bacterial coexistence driven by motility and spatial competition. Nature 578, 588–592 (2020).
doi: 10.1038/s41586-020-2033-2
pubmed: 32076271
Ajijah, N., Fiodor, A., Pandey, A. K., Rana, A. & Pranaw, K. Plant growth-promoting bacteria (pgpb) with biofilm-forming ability: A multifaceted agent for sustainable agriculture. Diversity 15, 112 (2023).
doi: 10.3390/d15010112