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Liu J, Wu Y, Gao GF. A Structural Voyage Toward the Landscape of Humoral and Cellular Immune Escapes of SARS-CoV-2. Immunol Rev 2025; 330:e70000. [PMID: 39907512 DOI: 10.1111/imr.70000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2024] [Accepted: 01/08/2025] [Indexed: 02/06/2025]
Abstract
The genome-based surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the past nearly 5 years since its emergence has refreshed our understanding of virus evolution, especially on convergent co-evolution with the host. SARS-CoV-2 evolution has been characterized by the emergence of sets of mutations that affect the functional properties of the virus by altering its infectivity, virulence, transmissibility, and interactions with host immunity. This poses a huge challenge to global prevention and control measures based on drug treatment and vaccine application. As one of the key evasion strategies in response to the immune profile of the human population, there are overwhelming amounts of evidence for the reduced antibody neutralization of SARS-CoV-2 variants. Additionally, data also suggest that the levels of CD4+ and CD8+ T-cell responses against variants or sub-variants decrease in the populations, although non-negligible cross-T-cell responses are maintained. Herein, from the perspectives of structural immunology, we outline the characteristics and mechanisms of the T cell and antibody responses to SARS-CoV and its variants/sub-variants. The molecular bases for the impact of the immune escaping variants on the interaction of the epitopes with the key receptors in adaptive immunity, that is, major histocompatibility complex (MHC), T-cell receptor (TCR), and antibody are summarized and discussed, the knowledge of which will widen our understanding of this pandemic-threatening virus and assist the preparedness for Pathogen X in the future.
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Affiliation(s)
- Jun Liu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yan Wu
- Department of Pathogen Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - George F Gao
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
- The D. H. Chen School of Universal Health, Zhejiang University, Hangzhou, China
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2
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Emmelot ME, Bodewes R, Maissan C, Vos M, de Swart RL, van Els CACM, Kaaijk P. Impact of genotypic variability of measles virus T-cell epitopes on vaccine-induced T-cell immunity. NPJ Vaccines 2025; 10:36. [PMID: 39979288 PMCID: PMC11842548 DOI: 10.1038/s41541-025-01088-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Accepted: 02/11/2025] [Indexed: 02/22/2025] Open
Abstract
After the COVID-19 pandemic, significant increases in measles cases were observed globally. Community-wide vaccination remains the most effective strategy for preventing measles. However, it is crucial to understand whether prevalent genotypes, when circulating in populations with suboptimal vaccination coverage, may undergo adaptive mutations that allow them to escape vaccine-induced immunity. In this study, a bioinformatics-guided approach was used to predict universal helper T-cell epitopes specific to the measles vaccine virus (vaccine-MeV) presented by multiple HLA-DR, -DP, and -DQ alleles to achieve population-wide coverage. By using MeV-specific T-cell lines, we identified 37 functional epitopes out of 83 predicted candidates, including 25 novel ones. Strikingly, 73% of these epitope regions were associated with sequence variations in wild-type viruses. More importantly, we demonstrated that mutations disrupted the ability of vaccine-induced CD4+ T cells to respond to circulating viruses. Consequently, mutations in epitope regions of circulating viruses may affect the effectiveness of vaccine-induced T-cell immunity.
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Affiliation(s)
- Maarten E Emmelot
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Rogier Bodewes
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Cyril Maissan
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Martijn Vos
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Rik L de Swart
- Department of Viroscience, Erasmus MC, Rotterdam, The Netherlands
| | - Cécile A C M van Els
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Division Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Patricia Kaaijk
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
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3
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Tian J, Shang B, Zhang J, Guo Y, Li M, Hu Y, Bai D, She J, Han Y, Guo P, Huang M, Wang Y, Liu M, Zhang J, Ye B, Guo Y, Yang M, Lin Y, Zhang T, Sun X, Yuan X, Zhang D, Xu Z, Chai Y, Qi J, Liu K, Tan S, Zhao Y, Zhou J, Song R, Gao GF, Liu J. T cell immune evasion by SARS-CoV-2 JN.1 escapees targeting two cytotoxic T cell epitope hotspots. Nat Immunol 2025; 26:265-278. [PMID: 39875585 DOI: 10.1038/s41590-024-02051-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 12/03/2024] [Indexed: 01/30/2025]
Abstract
Although antibody escape is observed in emerging severe acute respiratory syndrome coronavirus 2 variants, T cell escape, especially after the global circulation of BA.2.86/JN.1, is unexplored. Here we demonstrate that T cell evasion exists in epitope hotspots spanning BA.2.86/JN.1 mutations. The newly emerging Q229K at this conserved nucleocapsid protein site impairs HLA-A2 epitope hotspot recognition. The association between HLA-A24 convalescents and T cell immune escape points to the spike (S) protein epitope S448-456NYNYLYRLF, with multiple mutations from Delta to JN.1, including L452Q, L452R, F456L, N450D and L452W, and N450D, L452W and L455S. A cliff drop of immune responses was observed for S448-456NYNYRYRLF (Delta/BA.5.2) and S448-456NYDYWYRSF (JN.1), but with immune preservation of S448-456NYDYWYRLF (BA.2.86). Structural analyses showed that hydrophobicity exposure determines the pronounced escape of L452R and L455S mutants, which was further confirmed by T cell receptor binding. This study highlights the characteristics and molecular mechanisms of the T cell immune escape for JN.1 and provides new insights into understanding the dominant circulation of variants, from the viewpoint of cytotoxic T cell evasion.
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Affiliation(s)
- Jinmin Tian
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Bingli Shang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China
| | - Jianing Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuanyuan Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Min Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuechao Hu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dan Bai
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, China
| | - Junying She
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China
| | - Yang Han
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, China
| | - Peipei Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Mengkun Huang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, China
| | - Yalan Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Maoshun Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jie Zhang
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Infectious Diseases, Beijing, China
| | - Beiwei Ye
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yaxin Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mengjie Yang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China
| | - Ying Lin
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Ting Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, China
| | - Xin Sun
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xiaoju Yuan
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Danni Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ziqian Xu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing, China
| | - Yan Chai
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Jianxun Qi
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Kefang Liu
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Shuguang Tan
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Yingze Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing, China.
| | - Jikun Zhou
- The Fifth Hospital of Shijiazhuang, Shijiazhuang, China.
| | - Rui Song
- Beijing Ditan Hospital, Capital Medical University, Beijing, China.
| | - George F Gao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, China.
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing, China.
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China.
- The D. H. Chen School of Universal Health, Zhejiang University, Hangzhou, China.
| | - Jun Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, China.
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing, China.
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4
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Pandey RP, Kumar S, Rao DN, Gupta DL. Emerging severe acute respiratory syndrome coronavirus 2 variants and their impact on immune evasion and vaccine-induced immunity. Trans R Soc Trop Med Hyg 2024; 118:761-772. [PMID: 39297227 DOI: 10.1093/trstmh/trae060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 07/24/2024] [Accepted: 08/30/2024] [Indexed: 12/14/2024] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants harboring mutations in the structural protein, especially in the receptor binding domain (RBD) of spike protein, have raised concern about potential immune escape. The spike protein of SARS-CoV-2 plays a vital role in infection and is an important target for neutralizing antibodies. The mutations that occur in the structural proteins, especially in the spike protein, lead to changes in the virus attributes of transmissibility, an increase in disease severity, a notable reduction in neutralizing antibodies generated and thus a decreased response to vaccines and therapy. The observed multiple mutations in the RBD of the spike protein showed immune escape because it increases the affinity of spike protein binding with the ACE-2 receptor of host cells and increases resistance to neutralizing antibodies. Cytotoxic T-cell responses are crucial in controlling SARS-CoV-2 infections from the infected tissues and clearing them from circulation. Cytotoxic T cells efficiently recognized the infected cells and killed them by releasing soluble mediator's perforin and granzymes. However, the overwhelming response of T cells and, subsequently, the overproduction of inflammatory mediators during severe infections with SARS-CoV-2 may lead to poor outcomes. This review article summarizes the impact of mutations in the spike protein of SARS-CoV-2, especially mutations of RBD, on immunogenicity, immune escape and vaccine-induced immunity, which could contribute to future studies focusing on vaccine design and immunotherapy.
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Affiliation(s)
- Ramendra Pati Pandey
- School of Health Sciences and Technology (SOHST), UPES, Dehradun, Uttarakhand, India-248007
| | - Sachin Kumar
- School of Allied Health Sciences and Management, Delhi Pharmaceutical Sciences and Research University, New Delhi, India-110017
| | - D N Rao
- Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, India-110029
| | - Dablu Lal Gupta
- Department of Biochemistry, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India-492099
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Tang YS, Tan CW, Chong KC, Chen C, Sun Y, Yiu K, Ling KC, Chan KKP, Peiris M, Mok CKP, Hui DS. Determination of T cell response against XBB variants in adults who received either monovalent wild-type inactivated whole virus or mRNA vaccine or bivalent WT/BA.4-5 COVID-19 mRNA vaccine as the additional booster. Int J Infect Dis 2024; 149:107271. [PMID: 39426493 DOI: 10.1016/j.ijid.2024.107271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 08/20/2024] [Accepted: 10/14/2024] [Indexed: 10/21/2024] Open
Abstract
OBJECTIVES As the SARS-CoV-2 virus evolves more rapidly than vaccines are updated, T cell immunity potentially confers protection against disease progression and death from new variants. In this study, we aimed to assess whether the current boosting vaccination schemes offer sufficient T cell protection against new SARS-CoV-2 variants. METHODS A total of 292 adults who had received the second booster of either monovalent wild-type (WT) vaccines (inactivated virus or mRNA) (Cohort 1) or the second/third booster of bivalent WT/BA.4-5 mRNA vaccine (Cohort 2) were recruited in Hong Kong. All participants showed no serological evidence of recent infection of SARS-CoV-2. Blood samples of each participant were collected before and 1 month after receiving the booster. T cell and antibody responses were determined by flow cytometry and neutralization test, respectively. RESULTS Among all vaccination strategies, only the adults who had received the bivalent vaccine as the third booster dose significantly elicited T cell responses to the XBB variant. Either monovalent or bivalent mRNA but not inactivated virus vaccine as the second/third booster induced antibody against different XBB variants. CONCLUSION Receiving bivalent mRNA vaccine as the third booster is preferable to induce both T cell and antibody responses against XBB.
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Affiliation(s)
- Yun Sang Tang
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, PR China; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Chee Wah Tan
- Program in Emerging Infectious Diseases, Duke-National University of Singapore Medical School, Singapore, Singapore; Department of Microbiology and Immunology, Infectious Diseases Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ka Chun Chong
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, PR China; Centre for Health Systems and Policy Research, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Chunke Chen
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, PR China; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Yuanxin Sun
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, PR China; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Karen Yiu
- Department of Medicine & Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Kwun Cheung Ling
- Department of Medicine & Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Ken K P Chan
- Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China; Department of Medicine & Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
| | - Malik Peiris
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, PR China; Centre for Immunology and Infection, Hong Kong SAR, PR China
| | - Chris Ka Pun Mok
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, PR China; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China; SH Ho Research Centre for Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China; School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, PR China.
| | - David S Hui
- Department of Medicine & Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China; SH Ho Research Centre for Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, PR China
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6
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Zhu B, Lin H, Huang JS, Zhang W. Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Its Variants Omicron, BA.5, EG.5, and JN.1 for Viral Infectivity, Virulence and Immune Escape. Viruses 2024; 16:1192. [PMID: 39205166 PMCID: PMC11360586 DOI: 10.3390/v16081192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 07/21/2024] [Accepted: 07/24/2024] [Indexed: 09/04/2024] Open
Abstract
Semi-covariance has attracted significant attention in recent years and is increasingly employed to elucidate statistical phenomena exhibiting fluctuations, such as the similarity or difference in charge patterns of spike proteins among coronaviruses. In this study, by examining values above and below the average/mean based on the positive and negative charge patterns of amino acid residues in the spike proteins of SARS-CoV-2 and its current circulating variants, the proposed methods offer profound insights into the nonlinear evolving trends in those viral spike proteins. Our study indicates that the charge span value can predict the infectivity of the virus and the charge density can estimate the virulence of the virus, and both predicated infectivity and virulence appear to be associated with the capability of viral immune escape. This semi-covariance coefficient analysis may be used not only to predict the infectivity, virulence and capability of immune escape for coronaviruses but also to analyze the functionality of other viral proteins. This study improves our understanding of the trend of viral evolution in terms of viral infectivity, virulence or the capability of immune escape, which remains further validated by more future studies and statistical data.
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Affiliation(s)
- Botao Zhu
- Department of Electrical and Computer engineering, Western University, London, ON N6A 5B9, Canada;
| | - Huancheng Lin
- School of Information Technology, Carleton University, Ottawa, ON K1S 5B6, Canada;
| | - Jun Steed Huang
- School of Information Technology, Carleton University, Ottawa, ON K1S 5B6, Canada;
| | - Wandong Zhang
- Human Health Therapeutics Research Centre, National Research Council of Canada, 1200 Montreal Road, Building M54, Ottawa, ON K1A 0R6, Canada
- Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
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7
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Brummelman J, Suárez-Hernández S, de Rond L, Bogaard-van Maurik M, Molenaar P, van Wijlen E, Oomen D, Beckers L, Rots NY, van Beek J, Nicolaie MA, van Els CACM, Boer MC, Kaaijk P, Buisman AM, de Wit J. Distinct T cell responsiveness to different COVID-19 vaccines and cross-reactivity to SARS-CoV-2 variants with age and CMV status. Front Immunol 2024; 15:1392477. [PMID: 38774878 PMCID: PMC11106399 DOI: 10.3389/fimmu.2024.1392477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 04/09/2024] [Indexed: 05/24/2024] Open
Abstract
Introduction Accumulating evidence indicates the importance of T cell immunity in vaccination-induced protection against severe COVID-19 disease, especially against SARS-CoV-2 Variants-of-Concern (VOCs) that more readily escape from recognition by neutralizing antibodies. However, there is limited knowledge on the T cell responses across different age groups and the impact of CMV status after primary and booster vaccination with different vaccine combinations. Moreover, it remains unclear whether age has an effect on the ability of T cells to cross-react against VOCs. Methods Therefore, we interrogated the Spike-specific T cell responses in healthy adults of the Dutch population across different ages, whom received different vaccine types for the primary series and/or booster vaccination, using IFNɣ ELISpot. Cells were stimulated with overlapping peptide pools of the ancestral Spike protein and different VOCs. Results Robust Spike-specific T cell responses were detected in the vast majority of participants upon the primary vaccination series, regardless of the vaccine type (i.e. BNT162b2, mRNA-1273, ChAdOx1 nCoV-19, or Ad26.COV2.S). Clearly, in the 70+ age group, responses were overall lower and showed more variation compared to younger age groups. Only in CMV-seropositive older adults (>70y) there was a significant inverse relation of age with T cell responses. Although T cell responses increased in all age groups after booster vaccination, Spike-specific T cell frequencies remained lower in the 70+ age group. Regardless of age or CMV status, primary mRNA-1273 vaccination followed by BNT162b2 booster vaccination showed limited booster effect compared to the BNT162b2/BNT162b2 or BNT162b2/mRNA-1273 primary-booster regimen. A modest reduction in cross-reactivity to the Alpha, Delta and Omicron BA.1, but not the Beta or Gamma variant, was observed after primary vaccination. Discussion Together, this study shows that age, CMV status, but also the primary-booster vaccination regimen influence the height of the vaccination-induced Spike-specific T cell response, but did not impact the VOC cross-reactivity.
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Affiliation(s)
- Jolanda Brummelman
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Sara Suárez-Hernández
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Lia de Rond
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Marjan Bogaard-van Maurik
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Petra Molenaar
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Emma van Wijlen
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Debbie Oomen
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Lisa Beckers
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Nynke Y. Rots
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Josine van Beek
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Mioara A. Nicolaie
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Cécile A. C. M. van Els
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
- Infectious Diseases and Immunology, Department of Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands
| | - Mardi C. Boer
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Patricia Kaaijk
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Anne-Marie Buisman
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Jelle de Wit
- Center for Infectious Disease Control, Dutch National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
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8
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Sop J, Traut CC, Dykema AG, Hunt JH, Beckey TP, Basseth CR, Antar AAR, Laeyendecker O, Smith KN, Blankson JN. Bivalent mRNA COVID vaccines elicit predominantly cross-reactive CD4 + T cell clonotypes. Cell Rep Med 2024; 5:101442. [PMID: 38423018 PMCID: PMC10983033 DOI: 10.1016/j.xcrm.2024.101442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 12/28/2023] [Accepted: 02/03/2024] [Indexed: 03/02/2024]
Abstract
Bivalent COVID vaccines containing mRNA for ancestral and Omicron BA.5 spike proteins do not induce stronger T cell responses to Omicron BA.5 spike proteins than monovalent vaccines that contain only ancestral spike mRNA. The reasons for this finding have not been elucidated. Here, we show that healthy donors (HDs) and people living with HIV (PLWH) on antiretroviral therapy mostly target T cell epitopes that are not affected by BA.5 mutations. We use the functional expansion of specific T cells (FEST) assay to determine the percentage of CD4+ T cells that cross-recognize both spike proteins and those that are monoreactive for each protein. We show a predominance of cross-reactive CD4+ T cells; less than 10% percent of spike-specific CD4+ T cell receptors were BA.5 monoreactive in most HDs and PLWH. Our data suggest that the current bivalent vaccines do not induce robust BA.5-monoreactive T cell responses.
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Affiliation(s)
- Joel Sop
- Department of Medicine, Johns Hopkins Medicine, Baltimore, MD, USA
| | - Caroline C Traut
- Department of Medicine, Johns Hopkins Medicine, Baltimore, MD, USA
| | - Arbor G Dykema
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins Medicine, Baltimore, MD, USA; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA
| | - Joanne H Hunt
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Baltimore, MD, USA
| | - Tyler P Beckey
- Department of Medicine, Johns Hopkins Medicine, Baltimore, MD, USA
| | | | | | - Oliver Laeyendecker
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), NIH, Baltimore, MD, USA
| | - Kellie N Smith
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins Medicine, Baltimore, MD, USA; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA.
| | - Joel N Blankson
- Department of Medicine, Johns Hopkins Medicine, Baltimore, MD, USA.
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9
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Gan M, Cao J, Zhang Y, Fu H, Lin X, Ouyang Q, Xu X, Yuan Y, Fan X. Landscape of T cell epitopes displays hot mutations of SARS-CoV-2 variant spikes evading cellular immunity. J Med Virol 2024; 96:e29452. [PMID: 38314852 DOI: 10.1002/jmv.29452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/17/2024] [Accepted: 01/23/2024] [Indexed: 02/07/2024]
Abstract
The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been accompanied by the emergence of viral mutations that pose a great challenge to existing vaccine strategies. It is not fully understood with regard to the role of mutations on the SARS-CoV-2 spike protein from emerging viral variants in T cell immunity. In the current study, recombinant eukaryotic plasmids were constructed as DNA vaccines to express the spike protein from multiple SARS-CoV-2 strains. These DNA vaccines were used to immunize BALB/c mice, and cross-T cell responses to the spike protein from these viral strains were quantitated using interferon-γ (IFN-γ) Elispot. Peptides covering the full-length spike protein from different viral strains were used to detect epitope-specific IFN-γ+ CD4+ and CD8+ T cell responses by fluorescence-activated cell sorting. SARS-CoV-2 Delta and Omicron BA.1 strains were found to have broad T cell cross-reactivity, followed by the Beta strain. The landscapes of T cell epitopes on the spike protein demonstrated that at least 30 mutations emerging from Alpha to Omicron BA.5 can mediate the escape of T cell immunity. Omicron and its sublineages have 19 out of these 30 mutations, most of which are new, and a few are inherited from ancient circulating variants of concerns. The cross-T cell immunity between SARS-CoV-2 prototype strain and Omicron strains can be attributed to the T cell epitopes located in the N-terminal domain (181-246 aa [amino acids], 271-318 aa) and C-terminal domain (1171-1273 aa) of the spike protein. These findings provide in vivo evidence for optimizing vaccine manufacturing and immunization strategies for current or future viral variants.
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Affiliation(s)
- Mengze Gan
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Jinge Cao
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Yandi Zhang
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Fu
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaosong Lin
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Qi Ouyang
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Xinyue Xu
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
| | - Yin Yuan
- Department of Pediatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xionglin Fan
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China
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10
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Govindaraj S, Cheedarla N, Cheedarla S, Irby LS, Neish AS, Roback JD, Smith AK, Velu V. COVID-19 vaccine induced poor neutralization titers for SARS-CoV-2 omicron variants in maternal and cord blood. Front Immunol 2023; 14:1211558. [PMID: 37465682 PMCID: PMC10350671 DOI: 10.3389/fimmu.2023.1211558] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/12/2023] [Indexed: 07/20/2023] Open
Abstract
Introduction Maternally derived antibodies are crucial for neonatal immunity. Understanding the binding and cross-neutralization capacity of maternal and cord antibody responses to SARS-CoV-2 variants following COVID-19 vaccination in pregnancy can inform neonatal immunity. Methods Here we characterized the binding and neutralizing antibody profile at delivery in 24 pregnant individuals following two doses of Moderna mRNA-1273 or Pfizer BNT162b2 vaccination. We analyzed for SARS-CoV-2 multivariant cross-neutralizing antibody levels for wildtype Wuhan, Delta, Omicron BA1, BA2, and BA4/BA5 variants. In addition, we evaluated the transplacental antibody transfer by profiling maternal and umbilical cord blood. Results Our results reveal that the current COVID-19 vaccination induced significantly higher RBD-specific binding IgG titers in cord blood compared to maternal blood for both the Wuhan and Omicron BA1 strain. Interestingly, the binding IgG antibody levels for the Omicron BA1 strain were significantly lower when compared to the Wuhan strain in both maternal and cord blood. In contrast to the binding, the Omicron BA1, BA2, and BA4/5 specific neutralizing antibody levels were significantly lower compared to the Wuhan and Delta variants. It is interesting to note that the BA4/5 neutralizing capacity was not detected in either maternal or cord blood. Discussion Our data suggest that the initial series of COVID-19 mRNA vaccines were immunogenic in pregnant women, and vaccine-elicited binding antibodies were detectable in cord blood at significantly higher levels for the Wuhan and Delta variants but not for the Omicron variants. Interestingly, the vaccination did not induce neutralizing antibodies for Omicron variants. These results provide novel insight into the impact of vaccination on maternal humoral immune response and transplacental antibody transfer for SARS-CoV-2 variants and support the need for bivalent boosters as new variants emerge.
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Affiliation(s)
- Sakthivel Govindaraj
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
- Division of Microbiology and Immunology, Emory Vaccine Center, Emory University, Atlanta, GA, United States
| | - Narayanaiah Cheedarla
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Suneethamma Cheedarla
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - LesShon S. Irby
- Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, GA, United States
| | - Andrew S. Neish
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - John D. Roback
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Alicia K. Smith
- Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, GA, United States
| | - Vijayakumar Velu
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, United States
- Division of Microbiology and Immunology, Emory Vaccine Center, Emory University, Atlanta, GA, United States
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11
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Westphal T, Mader M, Karsten H, Cords L, Knapp M, Schulte S, Hermanussen L, Peine S, Ditt V, Grifoni A, Addo MM, Huber S, Sette A, Lütgehetmann M, Pischke S, Kwok WW, Sidney J, Schulze zur Wiesch J. Evidence for broad cross-reactivity of the SARS-CoV-2 NSP12-directed CD4 + T-cell response with pre-primed responses directed against common cold coronaviruses. Front Immunol 2023; 14:1182504. [PMID: 37215095 PMCID: PMC10196118 DOI: 10.3389/fimmu.2023.1182504] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 04/06/2023] [Indexed: 05/24/2023] Open
Abstract
Introduction The nonstructural protein 12 (NSP12) of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has a high sequence identity with common cold coronaviruses (CCC). Methods Here, we comprehensively assessed the breadth and specificity of the NSP12-specific T-cell response after in vitro T-cell expansion with 185 overlapping 15-mer peptides covering the entire SARS-CoV-2 NSP12 at single-peptide resolution in a cohort of 27 coronavirus disease 2019 (COVID-19) patients. Samples of nine uninfected seronegative individuals, as well as five pre-pandemic controls, were also examined to assess potential cross-reactivity with CCCs. Results Surprisingly, there was a comparable breadth of individual NSP12 peptide-specific CD4+ T-cell responses between COVID-19 patients (mean: 12.82 responses; range: 0-25) and seronegative controls including pre-pandemic samples (mean: 12.71 responses; range: 0-21). However, the NSP12-specific T-cell responses detected in acute COVID-19 patients were on average of a higher magnitude. The most frequently detected CD4+ T-cell peptide specificities in COVID-19 patients were aa236-250 (37%) and aa246-260 (44%), whereas the peptide specificities aa686-700 (50%) and aa741-755 (36%), were the most frequently detected in seronegative controls. In CCC-specific peptide-expanded T-cell cultures of seronegative individuals, the corresponding SARS-CoV-2 NSP12 peptide specificities also elicited responses in vitro. However, the NSP12 peptide-specific CD4+ T-cell response repertoire only partially overlapped in patients analyzed longitudinally before and after a SARS-CoV-2 infection. Discussion The results of the current study indicate the presence of pre-primed, cross-reactive CCC-specific T-cell responses targeting conserved regions of SARS-CoV-2, but they also underline the complexity of the analysis and the limited understanding of the role of the SARS-CoV-2 specific T-cell response and cross-reactivity with the CCCs.
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Affiliation(s)
- Tim Westphal
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Infection Research Deutsches Zentrum für Infektionsforschung (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany
| | - Maria Mader
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hendrik Karsten
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Leon Cords
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maximilian Knapp
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sophia Schulte
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Lennart Hermanussen
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sven Peine
- Institute of Transfusion Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Vanessa Ditt
- Institute of Transfusion Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alba Grifoni
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA, United States
| | - Marylyn Martina Addo
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Infection Research Deutsches Zentrum für Infektionsforschung (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany
- Department for Clinical Immunology of Infectious Diseases, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany
- Institute of Infection Research and Vaccine Development, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Samuel Huber
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA, United States
| | - Marc Lütgehetmann
- German Center for Infection Research Deutsches Zentrum für Infektionsforschung (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany
- Institute of Medical Microbiology, Virology and Hygiene, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sven Pischke
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Infection Research Deutsches Zentrum für Infektionsforschung (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany
| | - William W. Kwok
- Benaroya Research Institute at Virginia Mason, Seattle, WA, United States
| | - John Sidney
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA, United States
| | - Julian Schulze zur Wiesch
- Infectious Diseases Unit I, Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Infection Research Deutsches Zentrum für Infektionsforschung (DZIF), Partner Site Hamburg-Lübeck-Borstel-Riems, Hamburg, Germany
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12
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Wolday D, Fung CYJ, Morgan G, Casalino S, Frangione E, Taher J, Lerner-Ellis JP. HLA Variation and SARS-CoV-2 Specific Antibody Response. Viruses 2023; 15:906. [PMID: 37112884 PMCID: PMC10143129 DOI: 10.3390/v15040906] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 03/29/2023] [Accepted: 03/29/2023] [Indexed: 04/03/2023] Open
Abstract
Differences in SARS-CoV-2-specific immune responses have been observed between individuals following natural infection or vaccination. In addition to already known factors, such as age, sex, COVID-19 severity, comorbidity, vaccination status, hybrid immunity, and duration of infection, inter-individual variations in SARS-CoV-2 immune responses may, in part, be explained by structural differences brought about by genetic variation in the human leukocyte antigen (HLA) molecules responsible for the presentation of SARS-CoV-2 antigens to T effector cells. While dendritic cells present peptides with HLA class I molecules to CD8+ T cells to induce cytotoxic T lymphocyte responses (CTLs), they present peptides with HLA class II molecules to T follicular helper cells to induce B cell differentiation followed by memory B cell and plasma cell maturation. Plasma cells then produce SARS-CoV-2-specific antibodies. Here, we review published data linking HLA genetic variation or polymorphisms with differences in SARS-CoV-2-specific antibody responses. While there is evidence that heterogeneity in antibody response might be related to HLA variation, there are conflicting findings due in part to differences in study designs. We provide insight into why more research is needed in this area. Elucidating the genetic basis of variability in the SARS-CoV-2 immune response will help to optimize diagnostic tools and lead to the development of new vaccines and therapeutics against SARS-CoV-2 and other infectious diseases.
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Affiliation(s)
- Dawit Wolday
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON M5G 1Z5, Canada
| | - Chun Yiu Jordan Fung
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON M5G 1Z5, Canada
| | - Gregory Morgan
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON M5G 1Z5, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5G 1Z5, Canada
| | - Selina Casalino
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON M5G 1Z5, Canada
| | - Erika Frangione
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON M5G 1Z5, Canada
| | - Jennifer Taher
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5G 1Z5, Canada
| | - Jordan P. Lerner-Ellis
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1Z5, Canada; (C.Y.J.F.); (G.M.); (S.C.); (E.F.); (J.T.)
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON M5G 1Z5, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5G 1Z5, Canada
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