Back

Auranofin shows bactericidal activity in Pseudomonas aeruginosa by targeting thiol homeostasis

Luscher, A.; Mattenberger, Y.; Falconnet, L.; Civic, N.; van Delden, C.; Kohler, T.

2026-09-12 microbiology
10.64898/2026.09.11.750932 bioRxiv
Show abstract

The intrinsic resistance of Pseudomonas aeruginosa to many antibiotics is driven by the combined action of the outer membrane permeability barrier and multidrug efflux pumps, limiting the discovery of compounds active against this pathogen. To facilitate identification of antibacterial molecules with intracellular targets, we constructed a hyper-permeable P. aeruginosa PA14 strain lacking the four major Mex efflux systems and expressing the FhuA-derived hyperpore. This strain exhibited markedly increased susceptibility to diverse antimicrobials. Screening of 2,400 predominantly FDA-approved compounds identified the antirheumatic drug auranofin as a potent inhibitor which displayed bactericidal activity against the hyperpermeable strain. Selection of resistant mutants identified gain-of-function mutations in the MexQ efflux pump, indicating that altered substrate specificity of the MexP-MexQ-OpmE efflux system can reduce auranofin susceptibility. To investigate its mode of action, we analyzed mutants defective in the thioredoxin and glutathione redox systems. Whereas disruption of the thioredoxin pathway had no effect on susceptibility, glutathione-deficient mutants were hypersusceptible to auranofin. Exogenous glutathione restored resistance, and intracellular thiol measurements demonstrated that auranofin depletes the cellular thiol pool, consistent with direct neutralization by glutathione. These findings support a model in which auranofin disrupts glutathione-dependent thiol homeostasis in P. aeruginosa. More broadly, our study demonstrates that overcoming permeability and efflux barriers is an effective strategy to reveal antibacterial activities of approved drugs against Gram-negative pathogens.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.