Evidence map›Paper›PMID 37737287›Full record

ArticleScientific reports2023

An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern.

Carmina Angelica Perez-Romero, Lucero Mendoza-Maldonado, Alberto Tonda, Etienne Coz, Patrick Tabeling, Jessica Vanhomwegen, John MacSharry, Joanna Szafran, Lucina Bobadilla-Morales, Alfredo Corona-Rivera and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Carmina Angelica Perez-Romero *Departamento de Investigación, Universidad Central de Queretaro (UNICEQ), Av. 5 de Febrero 1602, San Pablo, Santiago de Querétaro, 76130, Qro., Mexico.
Lucero Mendoza-Maldonado *Hospital Civil de Guadalajara "Dr. Juan I. Menchaca", Salvador Quevedo y Zubieta 750, Independencia Oriente, C.P. 44340, Guadalajara, Jalisco, México.
Alberto TondaUMR 518 MIA Paris-Saclay, INRAE, AgroParisTech, Université Paris-Saclay, 91120, Palaiseau, France.ORCID http://orcid.org/0000-0001-5895-4809
Etienne CozCBI, ESPCI Paris, Université PSL, CNRS, 75005, Paris, France.
Patrick TabelingCBI, ESPCI Paris, Université PSL, CNRS, 75005, Paris, France.
Jessica VanhomwegenCIBU, Institut Pasteur, 25-28 rue du Dr Roux, 75015, Paris, France.
John MacSharrySchool of Microbiology and School of Medicine, University College Cork, College Rd, University College, Cork, Ireland.ORCID http://orcid.org/0000-0002-9528-6261
Joanna SzafranSchool of Microbiology and School of Medicine, University College Cork, College Rd, University College, Cork, Ireland.
Lucina Bobadilla-MoralesHospital Civil de Guadalajara "Dr. Juan I. Menchaca", Salvador Quevedo y Zubieta 750, Independencia Oriente, C.P. 44340, Guadalajara, Jalisco, México.
Alfredo Corona-RiveraHospital Civil de Guadalajara "Dr. Juan I. Menchaca", Salvador Quevedo y Zubieta 750, Independencia Oriente, C.P. 44340, Guadalajara, Jalisco, México.
Eric ClaassenAthena Institute, Vrije Universiteit, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.
Johan GarssenDivision of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0002-8678-9182
Aletta D KraneveldDivision of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0001-9819-383X
Alejandro Lopez-RinconDivision of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands. a.lopezrincon@uu.nl.ORCID http://orcid.org/0000-0003-4491-5889

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the COVID-19 pandemic winds down, it leaves behind the serious concern that future, even more disruptive pandemics may eventually surface. One of the crucial steps in handling the SARS-CoV-2 pandemic was being able to detect the presence of the virus in an accurate and timely manner, to then develop policies counteracting the spread. Nevertheless, as the pandemic evolved, new variants with potentially dangerous mutations appeared. Faced by these developments, it becomes clear that there is a need for fast and reliable techniques to create highly specific molecular tests, able to uniquely identify VOCs. Using an automated pipeline built around evolutionary algorithms, we designed primer sets for SARS-CoV-2 (main lineage) and for VOC, B.1.1.7 (Alpha) and B.1.1.529 (Omicron). Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for the main lineage and each variant in a matter of hours. Preliminary in-silico validation showed that the sequences in the primer sets featured high accuracy. A pilot test in a laboratory setting confirmed the results: the developed primers were favorably compared against existing commercial versions for the main lineage, and the specific versions for the VOCs B.1.1.7 and B.1.1.529 were clinically tested successfully.

Indexed as

COVID-19SARS-CoV-2Artificial IntelligenceHumansPandemics

Identifiers

PMID37737287
PMCPMC10516913

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.