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Evidence for Complex Interplay between Quorum Sensing and Antibiotic Resistance in Pseudomonas aeruginosa
Abstract
Quorum sensing (QS) is a cell-density-dependent communication system used by a wide range of bacteria to coordinate behaviors. Strategies pertaining to the interference in QS are appealing approaches to control microbial behaviors that depend on QS, including virulence and biofilms.
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“A key factor in its ecological versatility and adaptability is quorum system, a mechanism that coordinates gene expression across populations, regulating crucial processes for pathogenesis, including virulence and antibiotic resistance25,26.”
From Pseudomonas aeruginosa: ecology, evolution, pathogenesis and antimicrobial susceptibility (2025) · cites this paper as [26]
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“Quorum sensing in P. aeruginosa also plays a crucial role in biofilm formation by regulating the expression of genes involved in surface attachment, extracellular matrix (ECM) production and antibiotic resistance, enabling the bacteria to coordinate their behaviour and establish resilient, structured communities25–27.”
From Pseudomonas aeruginosa: ecology, evolution, pathogenesis and antimicrobial susceptibility (2025) · cites this paper as [26]
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Cited by
Pseudomonas aeruginosa: ecology, evolution, pathogenesis and antimicrobial susceptibility
Letizia, M., Diggle, S. P., & Whiteley, M. (2025) · Nature Reviews Microbiology · doi:10.1038/s41579-025-01193-8 · Cited by 231
Metadata
- Authors
- Sikdar, R., & Elias, M. H.
- Venue
- Microbiology Spectrum
- Publisher
- American Society for Microbiology
- Published
- 2022-12-21
- Volume
- 10
- Issue
- 6
- ISSN
- 2165-0497
- Cited by
- 47
- References
- 2
- Language
- en
- Licence
- creativecommons.org/licenses/by/4.0/ (vor)
- journals.asm.org/non-commercial-tdm-license (tdm)
- Funders
- HHS | NIH | National Institute of General Medical Sciences (R35GM133487)
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
