Structural basis of broad-spectrum β-lactam resistance in Staphylococcus aureus
Bibliographic record
Abstract
Abstract Broad-spectrum β-lactam antibiotic resistance in Staphylococcus aureus is a global healthcare burden 1,2 . In clinical strains, resistance is largely controlled by BlaR1 3 , a receptor that senses β-lactams through the acylation of its sensor domain, inducing transmembrane signalling and activation of the cytoplasmic-facing metalloprotease domain 4 . The metalloprotease domain has a role in BlaI derepression, inducing blaZ (β-lactamase PC1) and mecA (β-lactam-resistant cell-wall transpeptidase PBP2a) expression 3–7 . Here, overcoming hurdles in isolation, we show that BlaR1 cleaves BlaI directly, as necessary for inactivation, with no requirement for additional components as suggested previously 8 . Cryo-electron microscopy structures of BlaR1—the wild type and an autocleavage-deficient F284A mutant, with or without β-lactam—reveal a domain-swapped dimer that we suggest is critical to the stabilization of the signalling loops within. BlaR1 undergoes spontaneous autocleavage in cis between Ser283 and Phe284 and we describe the catalytic mechanism and specificity underlying the self and BlaI cleavage. The structures suggest that allosteric signalling emanates from β-lactam-induced exclusion of the prominent extracellular loop bound competitively in the sensor-domain active site, driving subsequent dynamic motions, including a shift in the sensor towards the membrane and accompanying changes in the zinc metalloprotease domain. We propose that this enhances the expulsion of autocleaved products from the active site, shifting the equilibrium to a state that is permissive of efficient BlaI cleavage. Collectively, this study provides a structure of a two-component signalling receptor that mediates action—in this case, antibiotic resistance—through the direct cleavage of a repressor.
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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 | 0.001 |
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".