MétaCan
Menu
Back to cohort
Record W4297850247 · doi:10.3390/zoonoticdis2030014

Tracking Co-Occurrence of N501Y, P681R, and Other Key Mutations in SARS-CoV-2 Spike for Surveillance

2022· article· en· W4297850247 on OpenAlexfundno aff
Carol Lee, Shruthi Mangalaganesh, Michael J. Kuiper, Trevor W. Drew, Seshadri S. Vasan

Bibliographic record

VenueZoonotic Diseases · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilU.S. Food and Drug AdministrationMedical Research CouncilDepartment of Industry, Science, Energy and Resources, Australian GovernmentAustralian e-Health Research CentreAustralian Academy of ScienceCommonwealth Scientific and Industrial Research OrganisationYork University
KeywordsLineage (genetic)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Spike (software development)MutationIn silicoCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakBiologyGeneticsEvolutionary biologyVirologyMedicineGeneOutbreakComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has produced five variants of concern (VOC) to date. The important spike mutation ‘N501Y’ is common to Alpha, Beta, Gamma, and Omicron VOC, while the ‘P681R’ is key to Delta’s spread. We have analysed circa 10 million SARS-CoV-2 genome sequences from the world’s largest repository, ‘Global Initiative on Sharing All Influenza Data (GISAID)’, and demonstrated that these two mutations have co-occurred on the spike ‘D614G’ mutation background at least 5767 times from 12 May 2020 to 28 April 2022. In contrast, the Y501-H681 combination, which is common to Alpha and Omicron VOC, is present in circa 1.1 million entries. Over half of the 5767 co-occurrences were in France, Turkey, or US (East Coast), and the rest across 88 other countries; 36.1%, 3.9%, and 4.1% of the co-occurrences were Alpha’s Q.4, Gamma’s P.1.8, and Omicron’s BA.1.1 sub-lineages acquiring the P681R; 4.6% and 3.0% were Delta’s AY.5.7 sub-lineage and B.1.617.2 lineage acquiring the N501Y; the remaining 8.2% were in other variants. Despite the selective advantages individually conferred by N501Y and P681R, the Y501-R681 combination counterintuitively did not outcompete other variants in every instance we have examined. While this is a relief to worldwide public health efforts, in vitro and in vivo studies are urgently required in the absence of a strong in silico explanation for this phenomenon. This study demonstrates a pipeline to analyse combinations of key mutations from public domain information in a systematic manner and provide early warnings of spread. The study here demonstrates the usage of the pipeline using the key mutations N501Y, P681R, and D614G of SARS-CoV-2.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.293
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

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

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 head0.066
GPT teacher head0.375
Teacher spread0.309 · 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 teacher head, 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZoonotic DiseasesSame topicSARS-CoV-2 and COVID-19 ResearchFrench-language works237,207