1
|
Zhang RY, Zhou SH, Feng RR, Wen Y, Ding D, Zhang ZM, Wei HW, Guo J. Adjuvant-Free COVID-19 Vaccine with Glycoprotein Antigen Oxidized by Periodate Rapidly Elicits Potent Immune Responses. ACS Chem Biol 2023; 18:915-923. [PMID: 37009726 PMCID: PMC10081833 DOI: 10.1021/acschembio.3c00050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 03/23/2023] [Indexed: 04/04/2023]
Abstract
Modification of antigens to improve their immunogenicity represents a promising direction for the development of protein vaccine. Here, we designed facilely prepared adjuvant-free vaccines in which the N-glycan of SARS-CoV-2 receptor-binding domain (RBD) glycoprotein was oxidized by sodium periodate. This strategy only minimally modifies the glycans and does not interfere with the epitope peptides. The RBD glycoprotein oxidized by high concentrations of periodate (RBDHO) significantly enhanced antigen uptake mediated by scavenger receptors and promoted the activation of antigen-presenting cells. Without any external adjuvant, two doses of RBDHO elicited 324- and 27-fold increases in IgG antibody titers and neutralizing antibody titers, respectively, compared to the unmodified RBD antigen. Meanwhile, the RBDHO vaccine could cross-neutralize all of the SARS-CoV-2 variants of concern. In addition, RBDHO effectively enhanced cellular immune responses. This study provides a new insight for the development of adjuvant-free protein vaccines.
Collapse
Affiliation(s)
- Ru-Yan Zhang
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| | - Shi-Hao Zhou
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| | - Ran-Ran Feng
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| | - Yu Wen
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| | - Dong Ding
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| | - Zhi-Ming Zhang
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| | - Hua-Wei Wei
- Jiangsu East-Mab Biomedical Technology
Co. Ltd, Nantong 226499, China
| | - Jun Guo
- Key Laboratory of Pesticide & Chemical Biology of
Ministry of Education, International Joint Research Center for Intelligent Biosensing
Technology and Health, Hubei International Scientific and Technological Cooperation Base
of Pesticide and Green Synthesis, College of Chemistry, Central China Normal
University, Wuhan 430079, China
| |
Collapse
|
2
|
Bavoso A, Ostuni A, De Vendel J, Bracalello A, Shcheglova T, Makker S, Tramontano A. Aldehyde modification and alum coadjuvancy enhance anti-TNF-α autovaccination and mitigate arthritis in rat. J Pept Sci 2014; 21:400-7. [PMID: 25424319 DOI: 10.1002/psc.2718] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2014] [Revised: 10/17/2014] [Accepted: 10/27/2014] [Indexed: 12/21/2022]
Abstract
Experimental vaccination to induce antibodies (Abs) capable of cytokine antagonism shows promise as a novel immunotherapy for chronic inflammatory disease. We prepared a hybrid antigen consisting of residues 141-235 of rat TNF-α fused to the C-terminus of glutathione-S-transferase (GST), chemically modified to incorporate aldehyde residues, for development of an auto-vaccine eliciting anti-rTNF-α Abs. In rat immunization the soluble aldehyde-modified fusion protein did not generate observable Ab responses. By contrast, vaccination with the aldehyde-modified fusion protein adsorbed on alum induced anti-TNF-α autoAbs with high titer and neutralizing activity. Induction of adjuvant arthritis in rats pre-immunized with unmodified fusion protein or a control protein in alum resulted in severe inflammation and joint damage, whereas the disease induced in rats immunized with the aldehyde-bearing fusion protein in alum was markedly attenuated. Similar results were obtained in a collagen-induced rat arthritis model. Anti-collagen II IgG Ab titers did not deviate significantly in groups pre-immunized with modified fusion protein and control protein, suggesting that anti-TNF vaccination did not skew the immune response related to disease induction. This study demonstrates synergy between particulate alum and protein bound carbonyl residues for enhancement of protein immunogenicity. The antigen-specific co-adjuvant system could prove advantageous for breaking tolerance in emerging auto-vaccination therapies targeting inflammatory cytokines as well as for enhancing a broader category of subunit vaccines. Aldehyde adduction introduces a minimal modification which, together with the established use of alum as a safe adjuvant for human use, could be favorable for further vaccine development.
Collapse
Affiliation(s)
- Alfonso Bavoso
- Department of Sciences, University of Basilicata, 85100, Potenza, Italy
| | | | | | | | | | | | | |
Collapse
|
3
|
Benchmarking B-cell epitope prediction for the design of peptide-based vaccines: problems and prospects. J Biomed Biotechnol 2010; 2010:910524. [PMID: 20368996 PMCID: PMC2847767 DOI: 10.1155/2010/910524] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2009] [Revised: 12/12/2009] [Accepted: 02/18/2010] [Indexed: 11/18/2022] Open
Abstract
To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function) and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays). These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g., unmatched electrical charges along the peptide-protein sequence alignments). If the data are partitioned with respect to these factors, iterative parallel benchmarking against the resulting subsets of data provides a basis for systematically identifying and addressing the limitations of methods for B-cell epitope prediction as applied to vaccine design.
Collapse
|