Molecular Epidemiology of Penicillinase-Producing <i>Neisseria gonorrhoeae</i> Isolates and Their <i>bla</i><sub>TEM-135</sub> Gene Variant in Bangkok, Thailand, 2015–2017
Bibliographic record
Abstract
Penicillinase-producing Neisseria gonorrhoeae (PPNG) possessing blaTEM-135 is a serious public health threat. With only a single change in the amino acid sequence, blaTEM-135 could evolve into a TEM-type extended-spectrum beta-lactamase (ESBL), which hydrolyzes extended-spectrum cephalosporins, including ceftriaxone and cefixime. We investigated the molecular epidemiological characteristics, types of plasmids in PPNG isolates, and prevalence of PPNG clinical isolates producing TEM-135 beta-lactamases. N. gonorrhoeae multi-antigen sequence typing (NG-MAST) was used to determine the molecular epidemiological characteristics of 99 PPNG isolates collected from 2015 to 2017. A mismatch amplification mutation assay was used to examine the blaTEM-135 gene prevalence. Of the 89 identified NG-MAST sequence types, 65 (73.0%) were novel. Only 17.7% (43/243) of PPNG isolates belonged to 16 genogroups. The most frequent plasmid was African, followed by Rio/Toronto, and Asian. The blaTEM-135 allele was found in Rio/Toronto plasmids. The blaTEM-135 allele was present in 23.2% (23/99) of the PPNG isolates. PPNG isolates expressing TEM-135 beta-lactamase exhibited significantly higher penicillin MIC (minimum inhibitory concentration) values than TEM-1 PPNG isolates. The PPNG isolates showed high genetic diversity and a high proportion of blaTEM-135 alleles. Mutation of the blaTEM-135 allele is worrisome as only one mutation could cause TEM-1 to evolve into an ESBL variant that degrades ceftriaxone. Ongoing surveillance of blaTEM-135 and new PPNG isolates is imperative.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".