Pangenome analysis of SARS-CoV2 strains to Identify Potential vaccine targets by Reverse Vaccinology

Abstract

BackgroundCoronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) leads to respiratory failure and obstructive alveolar damage, which may be fatal in immunocompromised individuals. COVID-19 pandemic has severe global implications badly, and the situation in the world is depreciating with the emergence of novel variants. The aim of our study is to explore the genome of SARS-CoV2 followed by in silico reverse vaccinology analysis. This will help to identify the most putative vaccine candidate against the virus in a robust manner and enables cost-effective development of vaccines compared with traditional strategies. MethodsThe genomic sequencing data is retrieved from NCBI (Reference Sequence Number NC_045512.2). The sequences are explored through comparative genomics approaches by GENOMICS to find out the core genome. The comprehensive set of proteins obtained was employed in computational vaccinology approaches for the prediction of the best possible B and T cell epitopes through ABCpred and IEDB Analysis Resource, respectively. The multi-epitopes were further tested against human toll-like receptor and cloned in E. coli plasmid vector. FindingsThe designed Multiepitope Subunit Vaccine was non-allergenic, antigenic (0.6543), & non-toxic, with significant connections with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 84.38%. It has 276 amino acids, consisting of an adjuvant with the aid of EAAAK linker, AAY linkers used to join the 4 CTL epitopes, GPGPG linkers used to join the 3 HTL epitopes and KK linkers used to join the 7 B-cell epitopes. MESV docking with human pathogenic toll-like receptors-3 (TLR3) exhibited a stable & high binding affinity. An in-silico codon optimization approach was used in the codon system of E. coli (strain K12) to obtain the GC-Content of Escherichia coli (strain K12): 50.7340272413779 and CAI-Value of the improved sequence: 0.9542834278823386. The multi-epitope vaccines optimized gene sequence was cloned in-silico in E. coli plasmid vector pET-30a (+), BamHI and HindIII restriction sites were added to the N and C-terminals of the sequence, respectively. ConclusionThere is a pressing need to combat COVID-19 and we need quick and reliable approaches against Covid-19. By using In-silico approaches, we acquire an effective vaccine that could trigger adequate immune responses at the cellular and humoral level. The suggested sequences can be further validated through in vivo and in vitro experimentation. Statement of SignificanceCurrent developments in the immunological bioinformatics areas has resulted in different servers and tools that are cost and time efficient for the traditional vaccine development. Though for designing a multiple epitope vaccine the antigenic epitopes prediction of a relevant protein by immunoinformatic methods are very helpful.