Evidence of MexT-Independent Overexpression of MexEF-OprN Multidrug Efflux Pump of Pseudomonas aeruginosa in Presence of Metabolic Stress
Bibliographic record
Abstract
BACKGROUND: The Pseudomonas aeruginosa MexEF-OprN efflux pump confers resistance to clinically significant antibiotics. Regulation of mexEF-oprN operon expression is multifaceted with the MexT activator being one of the most prominent regulatory proteins. METHODOLOGY: We have exploited the impaired metabolic fitness of a P. aeruginosa mutant strain lacking several efflux pump of the resistance nodulation cell division superfamily and the TolC homolog OpmH, and isolated derivatives (large colony variants) that regained fitness by incubation on nutrient-rich medium in the absence of antibiotics. Although the mexEF-oprN operon is uninducible in this mutant due to a 8-bp mexT insertion present in some P. aeruginosa PAO1 strains, the large colony variants expressed high levels of MexEF-OprN. Unlike large colony variants obtained after plating on antibiotic containing medium which expressed mexEF-oprN in a MexT-dependent fashion as evidenced by clean excision of the 8-bp insertion from mexT, mexEF-oprN expression was MexT-independent in the large colony variants obtained by plating on LB alone since the mexT gene remained inactivated. A search for possible regulators of mexEF-oprN expression using transposon mutagenesis and genomic library expression approaches yielded several candidates but proved inconclusive. SIGNIFICANCE: Our results show that antibiotic and metabolic stress lead to up-regulation of MexEF-OprN expression via different mechanisms and that MexEF-OprN does not only extrude antimicrobials but rather serves other important metabolic functions.
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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 | 0.000 |
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".