Association of Neisseria gonorrhoeae genogroups and specific PBP2/MtrR/PorB mutation patterns with susceptibility to penicillin in a susceptible gonococcal population
Bibliographic record
Abstract
Objectives: To ascertain whether the antimicrobial susceptibility of Neisseria gonorrhoeae isolates with differing susceptibilities to penicillin is associated with genogroups (GGs) and combined mutation patterns in PBP2 (penA), the multiple transfer resistance repressor (MtrR; mtrR) and porin B (PorB; porB). Methods: The susceptibility of 146 clinical N. gonorrhoeae isolates to penicillin was determined using the agar dilution method and the interpretation criteria of CLSI. The DNA sequences of penA, mtrR and porB in isolates were compared with WT sequences and mutation patterns were determined. Isolates were typed by N. gonorrhoeae multi-antigen sequence typing (NG-MAST) and STs were grouped into specific GGs. Results: The isolates tested carried 9 mutation patterns in PBP2 and 12 mutation patterns in each of MtrR and PorB. Of the 146 isolates, 121 (82.9%) were grouped into 13 different GGs. Isolates with penicillin MICs of 0.03-0.06 mg/L were significantly associated with GG25 (P < 0.05) and PBP2/MtrR/PorB mutation pattern I/WT/WT (P < 0.01). Isolates with a penicillin MIC of 1.0 mg/L were associated (P < 0.05) with: (i) GG3655 and mutation pattern XXII/A-;G45D/G120K;A121N; (ii) GG921 and mutation pattern IX/G45D/G120D;A121N; and (iii) GG1109 and mutation pattern IX/G45D/WT. Sixty percent (9/15) of penicillin-resistant isolates (MIC ≥2 mg/L) were GG3654 (P < 0.0001) and carried mutation pattern IX/G45D/G120K;A121D or IX/G45D/G120D;A121D (P < 0.05). Conclusions: Specific mutation patterns in PBP2/MtrR/PorB were associated with specific GGs and penicillin susceptibility. This approach of typing strains and resistance patterns is ideal for predicting antimicrobial resistance and should be used in instances in which gonococcal culture is not available but DNA can be obtained from clinical specimens.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".