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Identification of Novel Candidate CD8(+) T Cell Epitopes of the SARS-CoV2 with Homology to Other Seasonal Coronaviruses
Cross-reactive T cell immunity to seasonal coronaviruses (HCoVs) may lead to immunopathology or protection during SARS-CoV2 infection. To understand the influence of cross-reactive T cell responses, we used IEDB (Immune epitope database) and NetMHCpan (ver. 4.1) to identify candidate CD8(+) T cell e...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8225204/ https://www.ncbi.nlm.nih.gov/pubmed/34073934 http://dx.doi.org/10.3390/v13060972 |
Sumario: | Cross-reactive T cell immunity to seasonal coronaviruses (HCoVs) may lead to immunopathology or protection during SARS-CoV2 infection. To understand the influence of cross-reactive T cell responses, we used IEDB (Immune epitope database) and NetMHCpan (ver. 4.1) to identify candidate CD8(+) T cell epitopes, restricted through HLA-A and B alleles. Conservation analysis was carried out for these epitopes with HCoVs, OC43, HKU1, and NL63. 12/18 the candidate CD8(+) T cell epitopes (binding score of ≥0.90), which had a high degree of homology (>75%) with the other three HCoVs were within the NSP12 and NSP13 proteins. They were predicted to be restricted through HLA-A*2402, HLA-A*201, HLA-A*206, and HLA-B alleles B*3501. Thirty-one candidate CD8(+) T cell epitopes that were specific to SARS-CoV2 virus (<25% homology with other HCoVs) were predominantly identified within the structural proteins (spike, envelop, membrane, and nucleocapsid) and the NSP1, NSP2, and NSP3. They were predominantly restricted through HLA-B*3501 (6/31), HLA-B*4001 (6/31), HLA-B*4403 (7/31), and HLA-A*2402 (8/31). It would be crucial to understand T cell responses that associate with protection, and the differences in the functionality and phenotype of epitope specific T cell responses, presented through different HLA alleles common in different geographical groups, to understand disease pathogenesis. |
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