Structural and kinetic analyses of penicillin-binding protein 4 (PBP4)-mediated antibiotic resistance in Staphylococcus aureus
Bibliographic record
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) causes serious community-acquired and nosocomial infections worldwide. MRSA strains are resistant to a variety of antibiotics, including the classic penicillin and cephalosporin classes of β-lactams, making them intractable to treatment. Although β-lactam resistance in MRSA has been ascribed to the acquisition and activity of penicillin-binding protein 2a (PBP2a, encoded by mecA ), it has recently been observed that resistance can also be mediated by penicillin-binding protein 4 (PBP4). Previously, we have shown that broad-spectrum β-lactam resistance can arise following serial passaging of a mecA -negative COL strain of S. aureus, creating the CRB strain. This strain has two missense mutations in pbp4 and a mutation in the pbp4 promoter, both of which play an instrumental role in β-lactam resistance. To better understand PBP4's role in resistance, here we have characterized its kinetics and structure with clinically relevant β-lactam antibiotics. We present the first crystallographic PBP4 structures of apo and acyl-enzyme intermediate forms complexed with three late-generation β-lactam antibiotics: ceftobiprole, ceftaroline, and nafcillin. In parallel, we characterized the structural and kinetic effects of the PBP4 mutations present in the CRB strain. Localized within the transpeptidase active-site cleft, the two substitutions appear to have different effects depending on the drug. With ceftobiprole, the missense mutations impaired the K m value 150-fold, decreasing the proportion of inhibited PBP4. However, ceftaroline resistance appeared to be mediated by other factors, possibly including mutation of the pbp4 promoter. Our findings provide evidence that S. aureus CRB has at least two PBP4-mediated resistance mechanisms.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".