Pertactin-negative Bordetella pertussis strains in Canada: characterization of a dozen isolates based on a survey of 224 samples collected in different parts of the country over the last 20 years
Bibliographic record
Abstract
OBJECTIVE: To detect and characterize pertactin-negative Bordetella pertussis in Canada, especially for isolates collected in recent years. METHODS: A total of 224 isolates from the years 1994-2013 were screened by Western immuno-blot for expression of pertactin. Pertactin-negative isolates were characterized by serotyping, pulsed-field gel electrophoresis (PFGE), and genotyping of their pertactin, fimbriae 3, pertussis toxin subunit 1, and pertussis toxin gene promoter region, as well as the complete sequence of the pertactin gene. RESULTS: Twelve isolates were pertactin-negative, giving an overall prevalence of 5.4%. However, no such isolate was found prior to 2011 and 17.8% of 62 isolates examined in 2012 were pertactin-negative. Ten pertactin-negative isolates contained a significant mutation in their pertactin (prn) genes. IS481 was found in the prn genes of eight isolates, while a single point mutation occurred either in the coding region (resulting in a premature stop codon) or in the promoter region (preventing gene transcription) in two other isolates. PFGE analysis also showed multiple profiles suggesting that several independent genetic events might have led to the emergence of these pertactin-negative strains rather than expansion of a single clone. CONCLUSIONS: As reported elsewhere, pertactin-negative B. pertussis has emerged in Canada in recent years, notably in 2012. This coincided with an increase in pertussis activity in Canada. A further systematic study with a larger geographical representative sample is required to determine how these vaccine-negative strains may contribute to the overall changing epidemiology of pertussis in Canada.
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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 | 0.001 |
| 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 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".