Macrolide resistance due to <i>erm</i> (55)
Bibliographic record
Abstract
ABSTRACT Antimicrobial resistance (AMR) is a global threat. The identification and characterization of novel resistance genes is integral to AMR surveillance. The erm (55) gene was originally identified through whole genome sequencing of macrolide-resistant strains of Mycobacterium chelonae . The gene was annotated as a ribosomal methyltransferase, but its role as a determinant of macrolide resistance was not formally demonstrated. Three erm (55) alleles have now been documented. The plasmid-borne erm (55) P , the transposon-associated erm (55) T , and the chromosomal encoded erm (55) C exhibit ≈82% amino acid sequence identity. Here, we confirm that, when expressed from plasmids in a macrolide-susceptible strain of Escherichia coli , all three erm (55) variants confer resistance to azithromycin and clarithromycin. IMPORTANCE Macrolide antibiotics are often the only oral treatment option for infections with rapidly growing mycobacteria such as Mycobacterium abscessus and Mycobacterium chelonae . We previously identified three variants of a newly predicted macrolide resistance gene, erm (55), in M. chelonae , including the first case of a plasmid-mediated macrolide resistance in mycobacteria. The present study provides experimental evidence that the three erm (55) variants confer macrolide resistance and that each variant is unique in the degree to which it reduces susceptibility to clinically relevant macrolides.
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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".