Plasmid-Mediated Penicillin and Tetracycline Resistance Among Neisseria gonorrhoeae Isolates in South Africa: Prevalence, Detection and Typing Using a Novel Molecular Assay
Bibliographic record
Abstract
BACKGROUND: To detect and type plasmids responsible for penicillin and tetracycline resistance in Neisseria gonorrhoeae isolates using a novel duplex polymerase chain reaction (PCR) assay. METHODS: A duplex PCR assay, to detect and type penicillinase-producing N. gonorrhoeae (PPNG), and plasmid-mediated tetracycline resistant N. gonorrhoeae (TRNG), was developed on the basis of published single assays. Gonococcal Isolate Surveillance Project control strains were used in assay development and then 209 consecutive N. gonorrhoeae isolates, collected from men with urethral discharge in 2008, were tested. Controls included Asia, Africa, and Toronto β-lactamase plasmids, as well as American and Dutch TRNG plasmids. PCR amplicons were detected using an Agilent 2100 Bioanalyzer. Minimum inhibitory concentrations (MIC) were determined with E tests. Penicillinase production was detected using Nitrocefin solution. RESULTS: Among 209 gonococcal isolates, 54 (25.8%) PPNG and 154 (73.3%) TRNG were detected. The MIC50 and MIC90 values were determined for penicillin (0.19 and 32 mg/L) and tetracycline (6 and 16 mg/L). The assay detected the Africa-type (35.2%), the Toronto-type (44.4%), and a new type (20.3%) of β-lactamase plasmid. The American-type TRNG plasmid was 3-fold more frequent as compared with the Dutch-type. Although there was no overall association between the detection of PPNG and TRNG plasmids, only American type TRNG contained β-lactamase-encoding plasmids (P < 0.0001). CONCLUSIONS: The prevalence of plasmid-mediated resistance to tetracycline, and to a lesser extent penicillin, is high and neither drug is likely to have any future role in the treatment of gonorrhoea in South Africa. A novel β-lactamase plasmid was detected during the study and requires further characterization.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".