Immunological investigation of a multiepitope peptide vaccine candidate based on main proteins of SARS-CoV-2 pathogen
Multiepitope vaccines could induce multiantigenic immunity against large complex pathogens with different strain variants. Herein, the in silico, in vitro and in vivo studies were used to design and develop a novel candidate antigenic multiepitope vaccine against SARS-CoV-2 pathogen. The designed mu...
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Veröffentlicht in: | PloS one 2022-06, Vol.17 (6), p.e0268251-e0268251 |
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Sprache: | eng |
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Zusammenfassung: | Multiepitope vaccines could induce multiantigenic immunity against large complex pathogens with different strain variants. Herein, the in silico, in vitro and in vivo studies were used to design and develop a novel candidate antigenic multiepitope vaccine against SARS-CoV-2 pathogen. The designed multiepitope construct targets the spike glycoprotein (S), membrane protein (M), and nucleocapsid phosphoprotein (N) of SARS-CoV-2 (i.e., the S-N-M construct). This construct contains the cytotoxic T lymphocyte (CTL)-, helper T lymphocyte (HTL)-, and linear B lymphocyte (LBL)-inducing epitopes. The multiepitope s-n-m fusion gene was subcloned in prokaryotic (pET24a) and eukaryotic (pcDNA3.1) expression vectors. Its expression was evaluated in mammalian cell line using LL37 cell penetrating peptide. Moreover, the recombinant multiepitope S-N-M peptide was produced in E. coli strain. Finally, mice were immunized using homologous and heterologous regimens for evaluation of immune responses. Our data indicated that the multiepitope S-N-M peptide construct combined with Montanide 720 in homologous regimen significantly stimulated total IgG, IgG2a, IFN-γ, TNF-α, IL-15, IL-21 and IL-6, and Granzyme B secretion as compared to other groups. Moreover, the pcDNA-s-n-m/ LL37 nanoparticles significantly induced higher immune responses than the naked DNA in both homologous and heterologous regimens. In general, our designed multiepitope vaccine construct can be considered as a vaccine candidate in SARS-CoV-2 infection model. |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0268251 |