Evidence map›Paper›PMID 33619344›Full record

ArticleScientific reports2021

In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19.

Isabelle Q Phan, Sandhya Subramanian, David Kim, Michael Murphy, Deleah Pettie, Lauren Carter, Ivan Anishchenko, Lynn K Barrett, Justin Craig, Logan Tillery and 15 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% of its field
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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Performance assessment of a new serological diagnostic test for COVID-19 with candidate peptides from spike and nucleocapsid viral proteins.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. A contemporary review on the important role ofInformatics in medicine unlocked · 2022
    Review
  19. Article
  20. 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

25 authors at 4 institutions in 1 country.

Isabelle Q PhanSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Sandhya SubramanianSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
David KimSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Michael MurphyDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Deleah PettieDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Lauren CarterDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Ivan AnishchenkoSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Lynn K BarrettSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Justin CraigSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Logan TillerySeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Roger ShekSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Whitney E HarringtonCenter for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, USA.
David M KoelleDivision of Allergy and Infectious Diseases, Department of Medicine, Center for Emerging and Re-Emerging Infectious Diseases (CERID), University of Washington, Seattle, WA, USA.
Anna WaldDivision of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA.
David VeeslerDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Neil KingDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Jim BoonyaratanakornkitDivision of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA.
Nina IsoherranenDepartment of Pharmaceutics, University of Washington, Seattle, WA, USA.
Alexander L GreningerDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
Keith R JeromeDepartment of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
Helen ChuDivision of Allergy and Infectious Diseases, Department of Medicine, Center for Emerging and Re-Emerging Infectious Diseases (CERID), University of Washington, Seattle, WA, USA.
Bart StakerSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Lance StewartSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Peter J MylerSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA.
Wesley C Van VoorhisSeattle Structural Genomics Center for Infectious Disease (SSGCID), Seattle, WA, USA. wesley@uw.edu.
University of Washington · USCenter for Infectious Disease Research · USFred Hutch Cancer Center · USInfectious Disease Research Institute · US

Funding

Cutaneous Pathogen-Specific Tissue Resident Memory T Cells in Human AgingR01AG064800 · NIA · UNIVERSITY OF WASHINGTON · PI KOELLE, DAVID M · 2019 to 2023
$3.5M
Structural Studies of Coronavirus Fusion ProteinsR01GM120553 · NIGMS · UNIVERSITY OF WASHINGTON · PI VEESLER, DAVID · 2016 to 2020
$1.7M
The Effect of Maternal Cells on Infant ImmunityK08AI135072 · NIAID · SEATTLE CHILDREN'S HOSPITAL · PI HARRINGTON, WHITNEY ELIZABETH · 2018 to 2022
$854k
NIAID NIH HHS HHSN272201700059CNIAID NIH HHS K08 AI135072NIA NIH HHS R01 AG064800NIGMS NIH HHS R01 GM120553NIGMS NIH HHS R01GM120553NIH HHS R01AG064800
6 · The paper itself

Abstract

Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N = 80 samples from persons with RT-PCR confirmed SARS-CoV-2 infection), and a specificity of 97.2% (N = 106 control samples).

Indexed as

COVID-19Enzyme-Linked Immunosorbent AssayEpitopes, B-LymphocyteHumansReal-Time Polymerase Chain ReactionSARS-CoV-2Signal-To-Noise RatioEpitopes, B-Lymphocyte

Identifiers

PMID33619344
PMCPMC7900118
OpenAlexW3132938113

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.