In silico analyses and experimental validation of the MHC class-I restricted epitopes of Ebolavirus GP

Abstract

Ebolavirus (EBOV) causes an extremely high mortality and prevalence disease called Ebola virus disease (EVD). There is only one glycoprotein (GP) on the virus particle surface, which mediates entry into the host cell. MHC class-I restricted CD8 + T cell responses are important antiviral immune responses. Therefore, it is of great importance to understand EBOV GP-specific MHC class-I restricted epitopes within immunogenicity. In this study, computational approaches were employed to predict the dominant MHC class-I molecule epitopes of EBOV GP for mouse H2 and major alleles of HLA class-I supertypes. Our results yielded 42 dominant epitopes in H2 haplotypes and 301 dominant epitopes in HLA class-I haplotypes. After validation by ELISpot assay, in-depth analyses to ascertain their nature of conservation, immunogenicity, and docking with the corresponding MHC class-I molecules were undertaken. Our study predicted MHC class-I restricted epitopes that may aid the advancement of anti-EBOV immune responses. And the integrated strategy of epitope prediction, validation, and comparative analyses were postulated, promising for epitope-based immunotherapy development and application to viral epidemics.

In Silico Analyses, Experimental Verification and Application in DNA Vaccines of Ebolavirus GP-Derived pan-MHC-II-Restricted Epitopes

“…It is universally acknowledged that the MHC class II presentation is required for the activation of Th cells and antiviral immunoprotection [19], yet it has rarely been reported on EBOV GP. Notably, a previous study confirmed the MHC class I presentation of EBOV GP by in silico analyses, exemplifying antigen immunoreactivity research [20]. In this study, the latest bioinformatics and traditional immunological methods were integrated to explore the pan-MHC-II-restricted immune reactivity of EBOV GP, and a series of selective epitopes were screened to aid in vaccine development.…”

Integration: Gospel for immune bioinformatician on epitope-based therapy

“…Recently, immunologists followed this thought in glycoprotein epitope studies of Hantaan virus and Ebola virus, in which five or four affinity algorithms predicted MHC-I and MHC-II restricted epitopes, respectively, selecting epitopes with Rank ≤ 2% 3 or 2 times among toolkits. Strong cellular responses in enzyme-linked immunospot assays with corresponding epitopes validated the effectiveness of this strategy in infectious diseases such as viral hemorrhagic fever virus ( 29 – 31 ).…”

“…On this basis, another direction — further research on the impact of mutation sites — should also be taken into consideration. That is, the mutation site is brought into the original sequence to explore the impact of the mutation site on the affinity and immunogenicity of the specific epitopes ( 29 , 31 ). This analysis of the mutated sequences in silico predicts the approximate direction of evolutionary impacts on immunogenetic variation and deepens the understanding of pathogen conservation.…”

Whole Proteome-Based Therapeutic Targets Annotation and Designing of Multi-Epitope-Based Vaccines against the Gram-Negative XDR-Alcaligenes faecalis Bacterium

“…This also employs the use of subtractive proteomics techniques to design vaccine therapeutics against several organisms [ 26 ]. In several studies, similar in silico techniques were employed in order to propose potent vaccine candidates and to subsequently validate the vaccine candidates experimentally [ 27 , 28 , 29 ]. In a study, the authors performed a comparative analysis of Mycobacterium tuberculosis and identified major and HLA-promiscuous antigenic proteins and peptides which showed strong immunogenicity in in vivo and in vitro analysis [ 29 ].…”

“…In a study, the authors performed a comparative analysis of Mycobacterium tuberculosis and identified major and HLA-promiscuous antigenic proteins and peptides which showed strong immunogenicity in in vivo and in vitro analysis [ 29 ]. In another study, Liu et al predicted the MHC class-1 of Ebolavirus using in silico approaches, and subsequently, their anti-EBOV immune responses were confirmed by in vivo experiments [ 27 ].…”