Macrolide Resistance by Ribosomal Mutation in Clinical Isolates of <i>Streptococcus pneumoniae</i> from the PROTEKT 1999-2000 Study
Bibliographic record
Abstract
Sixteen (1.5%) of the 1,043 clinical macrolide-resistant Streptococcus pneumoniae isolates collected and analyzed in the 1999-2000 PROTEKT (Prospective Resistant Organism Tracking and Epidemiology for the Ketolide Telithromycin) study have resistance mechanisms other than rRNA methylation or efflux. We have determined the macrolide resistance mechanisms in all 16 isolates by sequencing the L4 and L22 riboprotein genes, plus relevant segments of the four genes for 23S rRNA, and the expression of mutant rRNAs was analyzed by primer extension. Isolates from Canada (n = 4), Japan (n = 3), and Australia (n = 1) were found to have an A2059G mutation in all four 23S rRNA alleles. The Japanese isolates additionally had a G95D mutation in riboprotein L22; all of these originated from the same collection center and were clonal. Three of the Canadian isolates were also clonal; the rest were not genetically related. Four German isolates had A2059G in one, two, and three 23S rRNA alleles and A2058G in two 23S rRNA alleles, respectively. An isolate from the United States had C2611G in three 23S rRNA alleles, one isolate from Poland had A2058G in three 23S rRNA alleles, one isolate from Turkey had A2058G in four 23S rRNA alleles, and one isolate from Canada had A2059G in two 23S rRNA alleles. Erythromycin and clindamycin resistance gradually increased with the number of A2059G alleles, whereas going from one to two mutant alleles caused sharp rises in the azithromycin, roxithromycin, and rokitamycin MICs. Comparisons of mutation dosage with rRNA expression indicates that not all alleles are equally expressed. Despite their high levels of macrolide resistance, all 16 isolates remained susceptible to the ketolide telithromycin (MICs, 0.015 to 0.25 microg/ml).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".