<i>ampG</i> Gene of <i>Pseudomonas aeruginosa</i> and Its Role in β-Lactamase Expression
Bibliographic record
Abstract
In enterobacteria, the ampG gene encodes a transmembrane protein (permease) that transports 1,6-GlcNAc-anhydro-MurNAc and the 1,6-GlcNAc-anhydro-MurNAc peptide from the periplasm to the cytoplasm, which serve as signal molecules for the induction of ampC β-lactamase. The role of AmpG as a transporter is also essential for cell wall recycling. Pseudomonas aeruginosa carries two AmpG homologues, AmpG (PA4393) and AmpGh1 (PA4218), with 45 and 41% amino acid sequence identity, respectively, to Escherichia coli AmpG, while the two homologues share only 19% amino acid identity. In P. aeruginosa strains PAO1 and PAK, inactivation of ampG drastically repressed the intrinsic β-lactam resistance while ampGh1 deletion had little effect on the resistance. Further, deletion of ampG in an ampD-null mutant abolished the high-level β-lactam resistance that is associated with the loss of AmpD activity. The cloned ampG gene is able to complement both the P. aeruginosa and the E. coli ampG mutants, while that of ampGh1 failed to do so, suggesting that PA4393 encodes the only functional AmpG protein in P. aeruginosa. We also demonstrate that the function of AmpG in laboratory strains of P. aeruginosa can effectively be inhibited by carbonyl cyanide m-chlorophenylhydrazone (CCCP), causing an increased sensitivity to β-lactams among laboratory as well as clinical isolates of P. aeruginosa. Our results suggest that inhibition of the AmpG activity is a potential strategy for enhancing the efficacy of β-lactams against P. aeruginosa, which carries inducible chromosomal ampC, especially in AmpC-hyperproducing clinical isolates.
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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) | 0.001 | 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 | 0.001 |
| 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".