Insight into Evolution of Bordetella pertussis from Comparative Genomic Analysis: Evidence of Vaccine-Driven Selection
Bibliographic record
Abstract
Despite high vaccine coverage, pertussis incidence has increased substantially in recent years in many countries. A significant factor that may be contributing to this increase is adaptation to the vaccine by Bordetella pertussis, the causative agent of pertussis. In this study, we first assessed the genetic diversity of B. pertussis by microarray-based comparative genome sequencing of 10 isolates representing diverse genotypes and different years of isolation. We discovered 171 single nucleotide polymorphisms (SNPs) in a total of 1.4 Mb genome analyzed. The frequency of base changes was estimated as one per 32 kb per isolate, confirming that B. pertussis is one of the least variable bacterial pathogens. We then analyzed an international collection of 316 B. pertussis isolates using a subset of 65 of the SNPs and identified 42 distinct SNP profiles (SPs). Phylogenetic analysis grouped the SPs into six clusters. The majority of recent isolates belonged to clusters I-IV and were descendants of a single prevaccine lineage. Cluster I appeared to be a major clone with a worldwide distribution. Typing of genes encoding acellular vaccine (ACV) antigens, ptxA, prn, fhaB, fim2, and fim3 revealed the emergence and increasing incidence of non-ACV alleles occurring in clusters I and IV, which may have been driven by ACV immune selection. Our findings suggest that B. pertussis, despite its high population homogeneity, is evolving in response to vaccination pressure with recent expansion of clones carrying variants of genes encoding ACV antigens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".