MexXY RND pump of Pseudomonas aeruginosa PA7 effluxes bi-anionic β-lactams carbenicillin and sulbenicillin when it partners with the outer membrane factor OprA but not with OprM
Bibliographic record
Abstract
Antibiotic resistance in Pseudomonas aeruginosa is a serious concern in healthcare systems. Among the determinants of antibiotic resistance in P. aeruginosa , efflux pumps belonging to the resistance–nodulation–division (RND) family confer resistance to a broad range of antibacterial compounds. The MexXY efflux system is widely overexpressed in P. aeruginosa isolates from cystic fibrosis (CF) patients. MexXY can form functional complexes with two different outer membrane factors (OMFs), OprA and OprM. In this study, using state-of-the-art genetic tools, the substrate specificities of MexXY–OprA and MexXY–OprM complexes were determined. Our results show, for the first time, that the substrate profile of the MexXY system from P. aeruginosa PA7 can vary depending on which OM factor (OprM or OprA) it complexes with. While both MexXY–OprA and MexXY–OprM complexes are capable of effluxing aminoglycosides, the bi-anionic β-lactam molecules carbenicillin and sulbenicillin were found to only be the substrate of MexXY–OprA. Our study therefore shows that by partnering with different OMF proteins MexY can expand its substrate profile.
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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".