Characterization of an inducible vancomycin resistance system in <i>Streptomyces coelicolor</i> reveals a novel gene (<i>vanK</i>) required for drug resistance
Bibliographic record
Abstract
Vancomycin is the front-line therapy for treating problematic infections caused by methicillin-resistant Staphylococcus aureus (MRSA), and the spread of vancomycin resistance is an acute problem. Vancomycin blocks cross-linking between peptidoglycan intermediates by binding to the D-Ala-D-Ala termini of bacterial cell wall precursors, which are the substrate of transglycosylase/transpeptidase. We have characterized a cluster of seven genes (vanSRJKHAX) in Streptomyces coelicolor that confers inducible, high-level vancomycin resistance. vanHAX are orthologous to genes found in vancomycin-resistant enterococci that encode enzymes predicted to reprogramme peptidoglycan biosynthesis such that cell wall precursors terminate in D-Ala-D-Lac rather than D-Ala-D-Ala. vanR and vanS encode a two-component signal transduction system that mediates transcriptional induction of the seven van genes. vanJ and vanK are novel genes that have no counterpart in previously characterized vancomycin resistance clusters from pathogens. VanK is a member of the Fem family of enzymes that add the cross-bridge amino acids to the stem pentapeptide of cell wall precursors, and vanK is essential for vancomycin resistance. The van genes are organized into four transcription units, vanRS, vanJ, vanK and vanHAX, and these transcripts are induced by vancomycin in a vanR-dependent manner. To develop a sensitive bioassay for inducers of the vancomycin resistance system, the promoter of vanJ was fused to a reporter gene conferring resistance to kanamycin. All the inducers identified were glycopeptide antibiotics, but teicoplanin, a membrane-anchored glycopeptide, failed to act as an inducer. Analysis of mutants defective in the vanRS and cseBC cell envelope signal transduction systems revealed significant cross-talk between the two pathways.
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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) | 0.001 | 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".