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Record W2972653216 · doi:10.1016/s1473-3099(19)30446-3

Emergence of dominant toxigenic M1T1 Streptococcus pyogenes clone during increased scarlet fever activity in England: a population-based molecular epidemiological study

2019· article· en· W2972653216 on OpenAlexfundno aff
Nicola N. Lynskey, Elita Jauneikaite, Ho Kwong Li, Xiangyun Zhi, Claire E. Turner, Mia Mosavie, Max Pearson, Masanori Asai, Ludmila Lobkowicz, J. Yimmy Chow, Julian Parkhill, Theresa Lamagni, Victoria J. Chalker, Shiranee Sriskandan

Bibliographic record

VenueThe Lancet Infectious Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsnot available
FundersMedical Research CouncilNIHR Imperial Biomedical Research CentreBiotechnology and Biological Sciences Research CouncilPublic Health EnglandRosetrees TrustMedical Research Council CanadaResearch Councils UKImperial College LondonImperial College Healthcare NHS TrustNational Institute for Health and Care ResearchImperial College Healthcare CharityWellcome Trust
KeywordsScarlet feverStreptococcus pyogenesBiologyMolecular epidemiologyMicrobiologyEpidemiologyPharyngitisStreptococcusVirologyGenotypeBacteriaMedicineGeneGeneticsStaphylococcus aureus

Abstract

fetched live from OpenAlex

Background Since 2014, England has seen increased scarlet fever activity unprecedented in modern times. In 2016, England's scarlet fever seasonal rise coincided with an unexpected elevation in invasive Streptococcus pyogenes infections. We describe the molecular epidemiological investigation of these events. Methods We analysed changes in S pyogenes emm genotypes, and notifications of scarlet fever and invasive disease in 2014–16 using regional (northwest London) and national (England and Wales) data. Genomes of 135 non-invasive and 552 invasive emm 1 isolates from 2009–16 were analysed and compared with 2800 global emm 1 sequences. Transcript and protein expression of streptococcal pyrogenic exotoxin A (SpeA; also known as scarlet fever or erythrogenic toxin A) in sequenced, non-invasive emm 1 isolates was quantified by real-time PCR and western blot analyses. Findings Coincident with national increases in scarlet fever and invasive disease notifications, emm 1 S pyogenes upper respiratory tract isolates increased significantly in northwest London in the March to May period, from five (5%) of 96 isolates in 2014, to 28 (19%) of 147 isolates in 2015 (p=0·0021 vs 2014 values), to 47 (33%) of 144 in 2016 (p=0·0080 vs 2015 values). Similarly, invasive emm 1 isolates collected nationally in the same period increased from 183 (31%) of 587 in 2015 to 267 (42%) of 637 in 2016 (p<0·0001). Sequences of emm 1 isolates from 2009–16 showed emergence of a new emm 1 lineage (designated M1 UK )—with overlap of pharyngitis, scarlet fever, and invasive M1 UK strains—which could be genotypically distinguished from pandemic emm 1 isolates (M1 global ) by 27 single-nucleotide polymorphisms. Median SpeA protein concentration in supernatant was nine-times higher among M1 UK isolates (190·2 ng/mL [IQR 168·9–200·4]; n=10) than M1 global isolates (20·9 ng/mL [0·0–27·3]; n=10; p<0·0001). M1 UK expanded nationally to represent 252 (84%) of all 299 emm 1 genomes in 2016. Phylogenetic analysis of published datasets identified single M1 UK isolates in Denmark and the USA. Interpretation A dominant new emm 1 S pyogenes lineage characterised by increased SpeA production has emerged during increased S pyogenes activity in England. The expanded reservoir of M1 UK and recognised invasive potential of emm 1 S pyogenes provide plausible explanation for the increased incidence of invasive disease, and rationale for global surveillance. Funding UK Medical Research Council, UK National Institute for Health Research, Wellcome Trust, Rosetrees Trust, Stoneygate Trust.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.310
Teacher spread0.290 · 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

Citations248
Published2019
Admission routes1
Has abstractyes

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