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

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 diagno...

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Autores principales:	Isabelle Q. Phan, Sandhya Subramanian, David Kim, Michael Murphy, Deleah Pettie, Lauren Carter, Ivan Anishchenko, Lynn K. Barrett, Justin Craig, Logan Tillery, Roger Shek, Whitney E. Harrington, David M. Koelle, Anna Wald, David Veesler, Neil King, Jim Boonyaratanakornkit, Nina Isoherranen, Alexander L. Greninger, Keith R. Jerome, Helen Chu, Bart Staker, Lance Stewart, Peter J. Myler, Wesley C. Van Voorhis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3d810cad4f2b46a1aaf7b89ba641e8bb
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spelling	oai:doaj.org-article:3d810cad4f2b46a1aaf7b89ba641e8bb2021-12-02T14:28:18ZIn silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-1910.1038/s41598-021-83730-y2045-2322https://doaj.org/article/3d810cad4f2b46a1aaf7b89ba641e8bb2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83730-yhttps://doaj.org/toc/2045-2322Abstract 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).Isabelle Q. PhanSandhya SubramanianDavid KimMichael MurphyDeleah PettieLauren CarterIvan AnishchenkoLynn K. BarrettJustin CraigLogan TilleryRoger ShekWhitney E. HarringtonDavid M. KoelleAnna WaldDavid VeeslerNeil KingJim BoonyaratanakornkitNina IsoherranenAlexander L. GreningerKeith R. JeromeHelen ChuBart StakerLance StewartPeter J. MylerWesley C. Van VoorhisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Isabelle Q. Phan Sandhya Subramanian David Kim Michael Murphy Deleah Pettie Lauren Carter Ivan Anishchenko Lynn K. Barrett Justin Craig Logan Tillery Roger Shek Whitney E. Harrington David M. Koelle Anna Wald David Veesler Neil King Jim Boonyaratanakornkit Nina Isoherranen Alexander L. Greninger Keith R. Jerome Helen Chu Bart Staker Lance Stewart Peter J. Myler Wesley C. Van Voorhis In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
description	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).
format	article
author	Isabelle Q. Phan Sandhya Subramanian David Kim Michael Murphy Deleah Pettie Lauren Carter Ivan Anishchenko Lynn K. Barrett Justin Craig Logan Tillery Roger Shek Whitney E. Harrington David M. Koelle Anna Wald David Veesler Neil King Jim Boonyaratanakornkit Nina Isoherranen Alexander L. Greninger Keith R. Jerome Helen Chu Bart Staker Lance Stewart Peter J. Myler Wesley C. Van Voorhis
author_facet	Isabelle Q. Phan Sandhya Subramanian David Kim Michael Murphy Deleah Pettie Lauren Carter Ivan Anishchenko Lynn K. Barrett Justin Craig Logan Tillery Roger Shek Whitney E. Harrington David M. Koelle Anna Wald David Veesler Neil King Jim Boonyaratanakornkit Nina Isoherranen Alexander L. Greninger Keith R. Jerome Helen Chu Bart Staker Lance Stewart Peter J. Myler Wesley C. Van Voorhis
author_sort	Isabelle Q. Phan
title	In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
title_short	In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
title_full	In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
title_fullStr	In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
title_full_unstemmed	In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
title_sort	in silico detection of sars-cov-2 specific b-cell epitopes and validation in elisa for serological diagnosis of covid-19
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3d810cad4f2b46a1aaf7b89ba641e8bb
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In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19

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