Extensive Genomic Variation within Clonal Complexes of Neisseria meningitidis
Bibliographic record
Abstract
Meningococcal disease is a widely distributed complex disease affecting all age categories. It can cause severe meningitis and septicemia, especially in unvaccinated infants and young children. The causative agent, Neisseria meningitidis (Nm), can be phenotypically and genetically differentiated into serogroups and sequence types (STs) and has a highly dynamic population structure. To obtain a deeper understanding of the epidemiology of Nm, we sequenced seven Nm genomes. Large-scale genomic analysis was conducted with these 7 Nm genomes, 27 additional Nm genomes from GenBank, and 4 other Neisseria genomes. We observed extensive homologous recombination in all gene functional categories among different Nm genomes. Homologous recombination is so frequent that it has resulted in numerous chimeric open reading frames, including genes in the capsule biosynthesis cluster and loci targeted by commercial vaccines. Our results reveal that, despite widespread use, evolutionary relationships inferred from the standard seven-gene multilocus sequence typing (MLST) method could not predict virulence gene content or strain phenotype. In fact, up to 28% of the virulence-associated genes could differ between strains of identical STs. Consistent with previous studies, we found that allelic recombination is also associated with alterations in antibiotic susceptibility. Overall, these findings emphasize the extensive genomic plasticity of Nm and the limitations of standard molecular methods to quantify this genotypic and phenotypic diversity.
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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 | 0.001 |
| 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 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".