journal article·2021-07Open access

Methods to Identify Immunogenic Peptides in SARS‐CoV‐2 Spike and Protective Monoclonal Antibodies in COVID‐19 Patients

Lili Li, Meiling Gao, Jie Li, Shulong Zu, Yanan Wang, Chunfeng Chen, Dingyi Wan, Jing Duan, Roghiyh Aliyari, Jingfeng Wang, Jicai Zhang, Yujie Jin, Weijin Huang, Xiaoxia Jin, Minxin Shi, Youchun Wang, Cheng‐Feng Qin, Heng Yang, Genhong Cheng

Small Methods· Volume 5· Issue 7

Abstract

Abstract The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection and the associated COVID‐19 diseases are an emerging threat to global public health. Although considerable scientific research on the immune, especially antibody, responses to SARS‐CoV‐2 infection have been conducted, additional dominant epitopes and protective antibodies are needed for diagnosis and treatment of COVID‐19 patients. Here, two different phage libraries are used to identify immunogenic epitopes across the spike protein and monoclonal antibodies from COVID‐19 patients. Three peptides are further characterized in the receptor‐binding motif (RBM) and measured their antibody levels in COVID‐19 patients, from which one identifies one most immunodominant epitope with the highest antibody response in COVID‐19 patients and in immunized mice. More importantly, monoclonal antibodies specifically binding to this peptide isolated from COVID‐19 patients have therapeutic potential to neutralize SARS‐CoV‐2 infection. Thus, the approaches to systemically identify immunogenic peptides and directly identify human monoclonal antibodies from patients will provide useful diagnostic and therapeutic tools for COVID‐19 and other emerging infectious diseases.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: SARS-CoV-2 and COVID-19 Research · COVID-19 Clinical Research Studies · vaccines and immunoinformatics approaches

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Center for Systems Medicine Institute of Basic Medical Sciences Chinese Academy of Medical Sciences & Peking Union Medical College Beijing 100005 China

Suzhou Institute of Systems Medicine Suzhou Jiangsu 215123 China

Department of Laboratory Medicine TaiHe Hospital Hubei University of Medicine Shiyan Hubei 442000 China

Suzhou Func Biotech Inc. Suzhou Jiangsu 215123 China

AtaGenix Laboratories (Wuhan) Co., Ltd. Wuhan Hubei 430075 China

Department of Microbiology Immunology & Molecular Genetics University of California Los Angeles Los Angeles CA 90095 USA

Division of HIV/AIDS and Sex‐Transmitted Virus Vaccines Institute for Biological Product Control National Institutes for Food and Drug Control (NIFDC) Beijing 102629 China

Affiliated Tumour Hospital of Nantong University Nantong 226000 China

Department of Virology State Key Laboratory of Pathogen and Biosecurity Beijing Institute of Microbiology and Epidemiology AMMS Beijing 100071 China

Funding

Natural Science Foundation of Hubei Province

References (41)

Show source-provided references
1. 10.1038/s41586-020-2012-710.1038/s41586-020-2012-7 ↗
2. 10.1016/S0140-6736(20)30300-710.1016/S0140-6736(20)30300-7 ↗
3. 10.1016/S1473-3099(20)30068-210.1016/S1473-3099(20)30068-2 ↗
4. 10.1126/science.abd083110.1126/science.abd0831 ↗
5. 10.1038/s41586-020-2571-710.1038/s41586-020-2571-7 ↗
6. 10.7554/eLife.5787710.7554/eLife.57877 ↗
7. 10.7150/ijbs.4512310.7150/ijbs.45123 ↗
8. 10.1128/AAC.00483-2010.1128/AAC.00483-20 ↗
9. 10.1016/j.immuni.2020.04.02310.1016/j.immuni.2020.04.023 ↗
10. 10.1080/22221751.2020.176251510.1080/22221751.2020.1762515 ↗
11. 10.3201/eid2607.20084110.3201/eid2607.200841 ↗
12. 10.1093/cid/ciaa34410.1093/cid/ciaa344 ↗
13. 10.1126/science.abd772810.1126/science.abd7728 ↗
14. 10.1001/jama.2020.478310.1001/jama.2020.4783 ↗
15. 10.1016/j.transci.2020.10279010.1016/j.transci.2020.102790 ↗
16. 10.1126/science.abf073210.1126/science.abf0732 ↗
17. 10.1016/j.cell.2020.02.05210.1016/j.cell.2020.02.052 ↗
18. 10.1038/s41586-020-2180-510.1038/s41586-020-2180-5 ↗
19. 10.1080/21645515.2020.174056010.1080/21645515.2020.1740560 ↗
20. 10.3389/fimmu.2020.57662210.3389/fimmu.2020.576622 ↗
21. 10.1038/s41423-020-0385-z10.1038/s41423-020-0385-z ↗
22. 10.1136/bmj.m436210.1136/bmj.m4362 ↗
23. 10.1126/science.abe240210.1126/science.abe2402 ↗
24. 10.1128/JCM.00797-2010.1128/JCM.00797-20 ↗
25. 10.1016/S0140-6736(20)30788-110.1016/S0140-6736(20)30788-1 ↗
26. 10.1016/j.celrep.2020.10772510.1016/j.celrep.2020.107725 ↗
27. 10.1038/s41467-020-18058-810.1038/s41467-020-18058-8 ↗
28. Shen L. · Emerging Infect. Dis. · 2020 · 9 · 1096
29. 10.1038/s41392-020-00301-910.1038/s41392-020-00301-9 ↗
30. 10.1172/JCI13875910.1172/JCI138759 ↗
31. 10.1126/science.abd425010.1126/science.abd4250 ↗
32. 10.1021/acscentsci.0c0074210.1021/acscentsci.0c00742 ↗
33. 10.2807/1560-7917.ES.2020.25.3.200004510.2807/1560-7917.ES.2020.25.3.2000045 ↗
34. Dobano C. · J. Clin. Microbiol. · 2020 · 59 · e01731
35. 10.1016/j.bios.2020.11245510.1016/j.bios.2020.112455 ↗
36. 10.1093/clinchem/hvaa03810.1093/clinchem/hvaa038 ↗
37. 10.4049/jimmunol.200076710.4049/jimmunol.2000767 ↗
38. 10.1080/22221751.2020.174376710.1080/22221751.2020.1743767 ↗
39. 10.1056/NEJMoa200131610.1056/NEJMoa2001316 ↗
40. 10.1097/00003246-198510000-0000910.1097/00003246-198510000-00009 ↗
41. Janson G. · Bioinformatics · 2017 · 33 · 44410.1093/bioinformatics/btw638 ↗