MexEF-OprN Efflux Pump Exports the Pseudomonas Quinolone Signal (PQS) Precursor HHQ (4-hydroxy-2-heptylquinoline)
Bibliographic record
Abstract
Bacterial cells have evolved the capacity to communicate between each other via small diffusible chemical signals termed autoinducers. Pseudomonas aeruginosa is an opportunistic pathogen involved, among others, in cystic fibrosis complications. Virulence of P. aeruginosa relies on its ability to produce a number of autoinducers, including 4-hydroxy-2-alkylquinolines (HAQ). In a cell density-dependent manner, accumulated signals induce the expression of multiple targets, especially virulence factors. This phenomenon, called quorum sensing, promotes bacterial capacity to cause disease. Furthermore, P. aeruginosa possesses many multidrug efflux pumps conferring adaptive resistance to antibiotics. Activity of some of these efflux pumps also influences quorum sensing. The present study demonstrates that the MexEF-OprN efflux pump modulates quorum sensing through secretion of a signalling molecule belonging to the HAQ family. Moreover, activation of MexEF-OprN reduces virulence factor expression and swarming motility. Since MexEF-OprN can be activated in infected hosts even in the absence of antibiotic selective pressure, it could promote establishment of chronic infections in the lungs of people suffering from cystic fibrosis, thus diminishing the immune response to virulence factors. Therapeutic drugs that affect multidrug efflux pumps and HAQ-mediated quorum sensing would be valuable tools to shut down bacterial virulence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".