Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/111386
Title: | Detection of antibodies against endemic and SARS-CoV-2 coronaviruses with short peptide epitopes |
Author(s): | Szardenings, Michael Delaroque, Nicolas Kern, Karolin Ramirez-Caballero, Lisbeth Puder, Marcus Ehrentreich-Förster, Eva Beige, Joachim Zürner, Sebastian Popp, Georg Wolf, Johannes Borte, Stephan M. |
Issue Date: | 2023 |
Type: | Article |
Language: | English |
Abstract: | (1) Background: Coronavirus proteins are quite conserved amongst endemic strains (eCoV) and SARS-CoV-2. We aimed to evaluate whether peptide epitopes might serve as useful diagnostic biomarkers to stratify previous infections and COVID-19. (2) Methods: Peptide epitopes were identified at an amino acid resolution that applied a novel statistical approach to generate data sets of potential antibody binding peptides. (3) Results: Data sets from more than 120 COVID-19 or eCoV-infected patients, as well as vaccinated persons, have been used to generate data sets that have been used to search in silico for potential epitopes in proteins of SARS-CoV-2 and eCoV. Peptide epitopes were validated with >300 serum samples in synthetic peptide micro arrays and epitopes specific for different viruses, in addition to the identified cross reactive epitopes. (4) Conclusions: Most patients develop antibodies against non-structural proteins, which are useful general markers for recent infections. However, there are differences in the epitope patterns of COVID-19, and eCoV, and the S-protein vaccine, which can only be explained by a high degree of cross-reactivity between the viruses, a pre-existing immune response against some epitopes, and even an alternate processing of the vaccine proteins. |
URI: | https://opendata.uni-halle.de//handle/1981185920/113340 http://dx.doi.org/10.25673/111386 |
Open Access: | Open access publication |
License: | (CC BY 4.0) Creative Commons Attribution 4.0 |
Journal Title: | Vaccines |
Publisher: | MDPI |
Publisher Place: | Basel |
Volume: | 11 |
Issue: | 9 |
Original Publication: | 10.3390/vaccines11091403 |
Page Start: | 1 |
Page End: | 18 |
Appears in Collections: | Open Access Publikationen der MLU |
Files in This Item:
File | Description | Size | Format | |
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vaccines-11-01403.pdf | 5.89 MB | Adobe PDF | View/Open |