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RhlR quorum-sensing receptor ligand sensitivity regulates the differential expression of phenazine genes in Pseudomonas aeruginosa

Pope, A. N.; Bavda, V. R.; Schumacher, M. L.; Mendoza, A. G.; Stringer, A. M.; Mallery, C. P.; Czachor, A.; Kurtz, A. F.; Liang, B.; Ke, X.; Wade, J. T.; Paczkowski, J. E.

2025-12-08 microbiology
10.64898/2025.12.08.692981 bioRxiv
Show abstract

Bacteria control individualistic and group behaviors using a form of cell-cell communication called quorum sensing. Quorum sensing relies on the production of chemical signals called autoinducers and the subsequent detection of those signals by a cognate receptor. Many Gram-negative bacteria use the LuxR-type family of transcription factor receptors that bind to acyl-homoserine lactone autoinducer signals to regulate their function as DNA-binding proteins. A subclass of this family of transcription factor receptors requires their cognate autoinducer to fold and dimerize to bind DNA to regulate gene expression and, thus, traits associated with quorum sensing, such as biofilm formation and virulence factor production. Here, we use a chemical-genetic approach to determine the structural basis for ligand selection by the quorum-sensing receptor RhlR from Pseudomonas aeruginosa. The native ligand for RhlR is N-butyryl-L-homoserine lactone, and this protein-ligand interaction is important for initiating gene expression in P. aeruginosa. We determine key residues that drive ligand specificity and selectivity of RhlR to define the role of ligand-driven RhlR-dependent gene regulation of quorum-sensing traits, namely the differential expression of the phenazine genes, which encode the enzymes responsible for the synthesis of the redox-sensitive virulence factor pyocyanin, among other phenazines. Furthermore, we provide a chemical-genetic framework for future studies aimed at disrupting the RhlR-ligand interaction to suppress virulence in P. aeruginosa, an important nosocomial pathogen with widespread antimicrobial resistance.

Published in Journal of Bacteriology (predicted rank #2) · training set

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