Cargando…
Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
BACKGROUND: To contain the pandemics caused by SARS-CoV-2, early detection approaches with high accuracy and accessibility are critical. Generating an antigen-capture based detection system would be an ideal strategy complementing the current methods based on nucleic acids and antibody detection. Th...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038641/ https://www.ncbi.nlm.nih.gov/pubmed/33889450 http://dx.doi.org/10.7717/peerj.11232 |
_version_ | 1783677422577647616 |
---|---|
author | Zhuang, Siqi Tang, Lingli Dai, Yufeng Feng, Xiaojing Fang, Yiyuan Tang, Haoneng Jiang, Ping Wu, Xiang Fang, Hezhi Chen, Hongzhi |
author_facet | Zhuang, Siqi Tang, Lingli Dai, Yufeng Feng, Xiaojing Fang, Yiyuan Tang, Haoneng Jiang, Ping Wu, Xiang Fang, Hezhi Chen, Hongzhi |
author_sort | Zhuang, Siqi |
collection | PubMed |
description | BACKGROUND: To contain the pandemics caused by SARS-CoV-2, early detection approaches with high accuracy and accessibility are critical. Generating an antigen-capture based detection system would be an ideal strategy complementing the current methods based on nucleic acids and antibody detection. The spike protein is found on the outside of virus particles and appropriate for antigen detection. METHODS: In this study, we utilized bioinformatics approaches to explore the immunodominant fragments on spike protein of SARS-CoV-2. RESULTS: The S1 subunit of spike protein was identified with higher sequence specificity. Three immunodominant fragments, Spike(56-94), Spike(199-264), and Spike(577-612), located at the S1 subunit were finally selected via bioinformatics analysis. The glycosylation sites and high-frequency mutation sites on spike protein were circumvented in the antigen design. All the identified fragments present qualified antigenicity, hydrophilicity, and surface accessibility. A recombinant antigen with a length of 194 amino acids (aa) consisting of the selected immunodominant fragments as well as a universal Th epitope was finally constructed. CONCLUSION: The recombinant peptide encoded by the construct contains multiple immunodominant epitopes, which is expected to stimulate a strong immune response in mice and generate qualified antibodies for SARS-CoV-2 detection. |
format | Online Article Text |
id | pubmed-8038641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80386412021-04-21 Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Zhuang, Siqi Tang, Lingli Dai, Yufeng Feng, Xiaojing Fang, Yiyuan Tang, Haoneng Jiang, Ping Wu, Xiang Fang, Hezhi Chen, Hongzhi PeerJ Bioinformatics BACKGROUND: To contain the pandemics caused by SARS-CoV-2, early detection approaches with high accuracy and accessibility are critical. Generating an antigen-capture based detection system would be an ideal strategy complementing the current methods based on nucleic acids and antibody detection. The spike protein is found on the outside of virus particles and appropriate for antigen detection. METHODS: In this study, we utilized bioinformatics approaches to explore the immunodominant fragments on spike protein of SARS-CoV-2. RESULTS: The S1 subunit of spike protein was identified with higher sequence specificity. Three immunodominant fragments, Spike(56-94), Spike(199-264), and Spike(577-612), located at the S1 subunit were finally selected via bioinformatics analysis. The glycosylation sites and high-frequency mutation sites on spike protein were circumvented in the antigen design. All the identified fragments present qualified antigenicity, hydrophilicity, and surface accessibility. A recombinant antigen with a length of 194 amino acids (aa) consisting of the selected immunodominant fragments as well as a universal Th epitope was finally constructed. CONCLUSION: The recombinant peptide encoded by the construct contains multiple immunodominant epitopes, which is expected to stimulate a strong immune response in mice and generate qualified antibodies for SARS-CoV-2 detection. PeerJ Inc. 2021-04-08 /pmc/articles/PMC8038641/ /pubmed/33889450 http://dx.doi.org/10.7717/peerj.11232 Text en © 2021 Zhuang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Zhuang, Siqi Tang, Lingli Dai, Yufeng Feng, Xiaojing Fang, Yiyuan Tang, Haoneng Jiang, Ping Wu, Xiang Fang, Hezhi Chen, Hongzhi Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
title | Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
title_full | Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
title_fullStr | Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
title_full_unstemmed | Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
title_short | Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) |
title_sort | bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (sars-cov-2) |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038641/ https://www.ncbi.nlm.nih.gov/pubmed/33889450 http://dx.doi.org/10.7717/peerj.11232 |
work_keys_str_mv | AT zhuangsiqi bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT tanglingli bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT daiyufeng bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT fengxiaojing bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT fangyiyuan bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT tanghaoneng bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT jiangping bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT wuxiang bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT fanghezhi bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 AT chenhongzhi bioinformaticpredictionofimmunodominantregionsinspikeproteinforearlydiagnosisofthesevereacuterespiratorysyndromecoronavirus2sarscov2 |