The Histidine Kinase VraS Interacts with Vancomycin and Penicillins Through its Membrane‐Anchored N‐terminal Domain
Bibliographic record
Abstract
Multidrug-resistant Staphylococcus aureus (S. aureus) is a major global health threat, with the VraTSR three-component system playing a key role in conferring resistance to cell-wall active antibiotics, through regulation of the cell wall stress stimulon. The molecular signals sensed by VraTSR remain unknown. We investigated interactions of the membrane histidine kinase VraS with β-lactams and glycopeptides. Photo-crosslinking assays with a vancomycin-derived and an ampicillin-derived photoprobe revealed direct interaction of these two classes of antibiotics with full-length VraS. Saturation transfer difference (STD) Nuclear Magnetic Resonance experiments confirmed vancomycin, ampicillin and penicillin G binding to VraS, with the involvement of aryl protons from the antibiotics. STD NMR assays with truncated versions of VraS demonstrated that ampicillin and vancomycin bind to the membrane-anchored N-terminal region of VraS. In contrast, assays with membrane vesicles expressing only VraT or co-expressing VraS/VraT did not show covalent adduct formation between VraT and the vancomycin-derived photoprobe. VraS p-azido-L-phenylalanine mutants demonstrated participation of the extracellular loop of VraS in β-lactam binding. These results demonstrate that vancomycin and penicillins directly interact with VraS, an interaction that could be involved in activation of the cell wall stress stimulon and the mechanisms underlying antibiotic resistance.
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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".