In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
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).
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
|---|---|
| Enthalten in: |
Scientific reports - 11(2021), 1 vom: 22. Feb., Seite 4290 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Phan, Isabelle Q [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Epitopes, B-Lymphocyte |
|---|
| Anmerkungen: |
Date Completed 08.03.2021 Date Revised 16.11.2022 published: Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1038/s41598-021-83730-y |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM321778472 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM321778472 | ||
| 003 | DE-627 | ||
| 005 | 20231226202630.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1038/s41598-021-83730-y |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1072.xml |
| 035 | |a (DE-627)NLM321778472 | ||
| 035 | |a (NLM)33619344 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Phan, Isabelle Q |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19 |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 08.03.2021 | ||
| 500 | |a Date Revised 16.11.2022 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a 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) | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 7 | |a Epitopes, B-Lymphocyte |2 NLM | |
| 700 | 1 | |a Subramanian, Sandhya |e verfasserin |4 aut | |
| 700 | 1 | |a Kim, David |e verfasserin |4 aut | |
| 700 | 1 | |a Murphy, Michael |e verfasserin |4 aut | |
| 700 | 1 | |a Pettie, Deleah |e verfasserin |4 aut | |
| 700 | 1 | |a Carter, Lauren |e verfasserin |4 aut | |
| 700 | 1 | |a Anishchenko, Ivan |e verfasserin |4 aut | |
| 700 | 1 | |a Barrett, Lynn K |e verfasserin |4 aut | |
| 700 | 1 | |a Craig, Justin |e verfasserin |4 aut | |
| 700 | 1 | |a Tillery, Logan |e verfasserin |4 aut | |
| 700 | 1 | |a Shek, Roger |e verfasserin |4 aut | |
| 700 | 1 | |a Harrington, Whitney E |e verfasserin |4 aut | |
| 700 | 1 | |a Koelle, David M |e verfasserin |4 aut | |
| 700 | 1 | |a Wald, Anna |e verfasserin |4 aut | |
| 700 | 1 | |a Veesler, David |e verfasserin |4 aut | |
| 700 | 1 | |a King, Neil |e verfasserin |4 aut | |
| 700 | 1 | |a Boonyaratanakornkit, Jim |e verfasserin |4 aut | |
| 700 | 1 | |a Isoherranen, Nina |e verfasserin |4 aut | |
| 700 | 1 | |a Greninger, Alexander L |e verfasserin |4 aut | |
| 700 | 1 | |a Jerome, Keith R |e verfasserin |4 aut | |
| 700 | 1 | |a Chu, Helen |e verfasserin |4 aut | |
| 700 | 1 | |a Staker, Bart |e verfasserin |4 aut | |
| 700 | 1 | |a Stewart, Lance |e verfasserin |4 aut | |
| 700 | 1 | |a Myler, Peter J |e verfasserin |4 aut | |
| 700 | 1 | |a Van Voorhis, Wesley C |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Scientific reports |d 2011 |g 11(2021), 1 vom: 22. Feb., Seite 4290 |w (DE-627)NLM215703936 |x 2045-2322 |7 nnns |
| 773 | 1 | 8 | |g volume:11 |g year:2021 |g number:1 |g day:22 |g month:02 |g pages:4290 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1038/s41598-021-83730-y |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 11 |j 2021 |e 1 |b 22 |c 02 |h 4290 | ||