Multidrug efflux pumps of Pseudomonas aeruginosa show selectivity for their natural substrates

Front Microbiol. 2025 Jan 9:15:1512472. doi: 10.3389/fmicb.2024.1512472. eCollection 2024.

Abstract

Antibiotic-resistant Gram-negative bacteria are an increasing threat to human health. Strategies to restore antibiotic efficacy include targeting multidrug efflux pumps by competitive efflux pump inhibitors. These could be derived from natural substrates of these efflux systems. In this work, we aimed to elucidate the natural substrates of the clinically relevant Mex efflux pumps of Pseudomonas aeruginosa by an untargeted metabolomic approach. We constructed a PA14 mutant, genetically deleted in the major multidrug efflux pumps MexAB-OprM, MexCD-OprJ, MexXY-OprM, and MexEF-OprN and expressed in this mutant each efflux pump individually from an inducible promoter. Comparative analysis of the exo-metabolomes identified 210 features that were more abundant in the supernatant of efflux pump overexpressors compared to the pump-deficient mutant. Most of the identified features were efflux pump specific, while only a few were shared among several Mex pumps. We identified by-products of secondary metabolites as well as signaling molecules. Supernatants of the pump-deficient mutant also showed decreased accumulation of fatty acids, including long chain homoserine lactone quorum sensing molecules. Our data suggests that Mex efflux pumps of P. aeruginosa appear to have dedicated roles in extruding signaling molecules, metabolic by-products, as well as oxidized fatty acids. These findings represent an interesting starting point for the development of competitive efflux pump inhibitors.

Keywords: Pseudomonas aeruginosa; antibiotic resistance; metabolomics; multidrug efflux; natural substrates.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. L. Mazza received financial support from the National MD-PhD program of the Swiss National Science Foundation (grant number 501100001711-214541). We further acknowledge support from the Bridge funding program from the Swiss National Science Foundation (grant number 40B2-0_211759).