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Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome.
Sci Rep. 2020 08 25; 10(1):14179.SR

Abstract

A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development.

Authors+Show Affiliations

Mayo Clinic Vaccine Research Group, Mayo Clinic, Guggenheim Building 611C, 200 First Street SW, Rochester, MN, 55905, USA.Mayo Clinic Vaccine Research Group, Mayo Clinic, Guggenheim Building 611C, 200 First Street SW, Rochester, MN, 55905, USA.Mayo Clinic Vaccine Research Group, Mayo Clinic, Guggenheim Building 611C, 200 First Street SW, Rochester, MN, 55905, USA.Mayo Clinic Vaccine Research Group, Mayo Clinic, Guggenheim Building 611C, 200 First Street SW, Rochester, MN, 55905, USA. poland.gregory@mayo.edu.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32843695

Citation

Crooke, Stephen N., et al. "Immunoinformatic Identification of B Cell and T Cell Epitopes in the SARS-CoV-2 Proteome." Scientific Reports, vol. 10, no. 1, 2020, p. 14179.
Crooke SN, Ovsyannikova IG, Kennedy RB, et al. Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome. Sci Rep. 2020;10(1):14179.
Crooke, S. N., Ovsyannikova, I. G., Kennedy, R. B., & Poland, G. A. (2020). Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome. Scientific Reports, 10(1), 14179. https://doi.org/10.1038/s41598-020-70864-8
Crooke SN, et al. Immunoinformatic Identification of B Cell and T Cell Epitopes in the SARS-CoV-2 Proteome. Sci Rep. 2020 08 25;10(1):14179. PubMed PMID: 32843695.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome. AU - Crooke,Stephen N, AU - Ovsyannikova,Inna G, AU - Kennedy,Richard B, AU - Poland,Gregory A, Y1 - 2020/08/25/ PY - 2020/05/20/received PY - 2020/07/31/accepted PY - 2020/8/27/entrez PY - 2020/8/28/pubmed PY - 2020/9/15/medline SP - 14179 EP - 14179 JF - Scientific reports JO - Sci Rep VL - 10 IS - 1 N2 - A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development. SN - 2045-2322 UR - https://www.unboundmedicine.com/medline/citation/32843695/Immunoinformatic_identification_of_B_cell_and_T_cell_epitopes_in_the_SARS_CoV_2_proteome_ L2 - https://doi.org/10.1038/s41598-020-70864-8 DB - PRIME DP - Unbound Medicine ER -