WGS analysis of a penicillin-resistant Neisseria meningitidis strain containing a chromosomal ROB-1 β-lactamase gene
Bibliographic record
Abstract
Objectives: Neisseria meningitidis is rarely penicillin resistant. We describe WGS analysis of a penicillin-resistant N. meningitidis collected from a case of invasive meningococcal disease. Methods: Serogrouping, serotyping and serosubtyping were performed with specific antibodies. β-Lactamase was detected by nitrocefin. MICs were determined by Etest and agar dilution. Sequencing of N. meningitidis genomes was done on the Illumina MiSeq platform and genome data were analysed using the Bacterial Isolate Genome Sequence Database (BIGSdb) on the PubMLST Neisseria website (https://pubmlst.org/neisseria/). Transformation was used to confirm the genetic basis of the penicillin resistance. Results: An N. meningitidis blood isolate from a female patient in her mid-50s with a painful and septic left shoulder was found to have penicillin MIC values of 3-12 mg/L. The isolate was typed as Y: 14, 19: P1.- and ST3587, and was weakly β-lactamase positive. WGS analysis identified a full-length copy of the β-lactamase gene blaROB-1, which was contained on a 1719 bp insert with a G + C content of 41.7% (versus a G + C content of N. meningitidis of 51.7%), suggesting that the blaROB-1 gene came from a different bacterial species. A GenBank analysis of the blaROB-1 gene insert found 99.77% identity with a DNA segment found in plasmid pB1000' from Haemophilus influenzae. Transformation of a penicillin-susceptible strain with the blaROB-1 gene conferred β-lactamase activity and penicillin resistance. Conclusions: N. meningitidis serogroup Y, ST3587 can carry and express the blaROB-1 gene, leading to penicillin resistance. It is highly likely that the N. meningitidis isolate acquired the blaROB-1 gene from H. influenzae.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".