MétaCan
Menu
Back to cohort
Record W2032638170 · doi:10.1128/mbio.01074-14

Global Population Structure and Evolution of Bordetella pertussis and Their Relationship with Vaccination

2014· article· en· W2032638170 on OpenAlexaff
Marieke J Bart, Simon R. Harris, Abdolreza Advani, Yoshichika Arakawa, Daniela Bottero, Valérie Bouchez, Pamela K. Cassiday, Chuen‐Sheue Chiang, Tine Dalby, Norman K. Fry, María Emilia Gaillard, Marjolein van Gent, Nicole Guiso, Hans O. Hallander, Eric T. Harvill, Qiushui He, Han G. J. van der Heide, Kees Heuvelman, Daniela Hozbor, Kazunari Kamachi, Gennady I. Karataev, Ruiting Lan, Anna Lutyńska, Ram P. Maharjan, Jussi Mertsola, Tatsuo Miyamura, Sophie Octavia, Andrew Preston, Michael A. Quail, Vitali Sintchenko, Paola Stefanelli, M. Lucia Tondella, Raymond S. W. Tsang, Yinghua Xu, Shu-Man Yao, Shumin Zhang, Julian Parkhill, Frits R. Mooi

Bibliographic record

VenuemBio · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsPublic Health Agency of Canada
FundersNational Medical Research CouncilNational Institute of General Medical SciencesChinese University of Hong KongWellcome TrustUniversity of Hong KongRijksinstituut voor Volksgezondheid en MilieuNational Health and Medical Research Council
KeywordsBordetella pertussisBiologyComparative genomicsHost adaptationPertussis toxinVaccinationVirulenceWhooping coughGenePathogenImmunityPopulationVirologyMicrobiologyGeneticsGenomeGenomicsImmune systemBacteriaMedicineG protein

Abstract

fetched live from OpenAlex

Bordetella pertussis causes pertussis, a respiratory disease that is most severe for infants. Vaccination was introduced in the 1950s, and in recent years, a resurgence of disease was observed worldwide, with significant mortality in infants. Possible causes for this include the switch from whole-cell vaccines (WCVs) to less effective acellular vaccines (ACVs), waning immunity, and pathogen adaptation. Pathogen adaptation is suggested by antigenic divergence between vaccine strains and circulating strains and by the emergence of strains with increased pertussis toxin production. We applied comparative genomics to a worldwide collection of 343 B. pertussis strains isolated between 1920 and 2010. The global phylogeny showed two deep branches; the largest of these contained 98% of all strains, and its expansion correlated temporally with the first descriptions of pertussis outbreaks in Europe in the 16th century. We found little evidence of recent geographical clustering of the strains within this lineage, suggesting rapid strain flow between countries. We observed that changes in genes encoding proteins implicated in protective immunity that are included in ACVs occurred after the introduction of WCVs but before the switch to ACVs. Furthermore, our analyses consistently suggested that virulence-associated genes and genes coding for surface-exposed proteins were involved in adaptation. However, many of the putative adaptive loci identified have a physiological role, and further studies of these loci may reveal less obvious ways in which B. pertussis and the host interact. This work provides insight into ways in which pathogens may adapt to vaccination and suggests ways to improve pertussis vaccines. IMPORTANCE Whooping cough is mainly caused by Bordetella pertussis, and current vaccines are targeted against this organism. Recently, there have been increasing outbreaks of whooping cough, even where vaccine coverage is high. Analysis of the genomes of 343 B. pertussis isolates from around the world over the last 100 years suggests that the organism has emerged within the last 500 years, consistent with historical records. We show that global transmission of new strains is very rapid and that the worldwide population of B. pertussis is evolving in response to vaccine introduction, potentially enabling vaccine escape.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.209
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations315
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuemBioSame topicBacterial Infections and VaccinesFrench-language works237,207