Homologous Recombination Drives Both Sequence Diversity and Gene Content Variation in Neisseria meningitidis
Bibliographic record
Abstract
The study of genetic and phenotypic variation is fundamental for understanding the dynamics of bacterial genome evolution and untangling the evolution and epidemiology of bacterial pathogens. Neisseria meningitidis (Nm) is among the most intriguing bacterial pathogens in genomic studies due to its dynamic population structure and complex forms of pathogenicity. Extensive genomic variation within identical clonal complexes (CCs) in Nm has been recently reported and suggested to be the result of homologous recombination, but the extent to which recombination contributes to genomic variation within identical CCs has remained unclear. In this study, we sequenced two Nm strains of identical serogroup (C) and multi-locus sequence type (ST60), and conducted a systematic analysis with an additional 34 Nm genomes. Our results revealed that all gene content variation between the two ST60 genomes was introduced by homologous recombination at the conserved flanking genes, and 94.25% or more of sequence divergence was caused by homologous recombination. Recombination was found in genes associated with virulence factors, antigenic outer membrane proteins, and vaccine targets, suggesting an important role of homologous recombination in rapidly altering the pathogenicity and antigenicity of Nm. Recombination was also evident in genes of the restriction and modification systems, which may undermine barriers to DNA exchange. In conclusion, homologous recombination can drive both gene content variation and sequence divergence in Nm. These findings shed new light on the understanding of the rapid pathoadaptive evolution of Nm and other recombinogenic bacterial pathogens.
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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 | 0.000 | 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) | 0.000 | 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".