In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity

Abstract

Shigellosis or bacillary dysentery is an important cause of diarrhea, with the majority of the cases occurring in developing countries. Considering the high disease burden, increasing antibiotic resistance, serotype-specific immunity and the post-infectious sequelae associated with shigellosis, there is a pressing need of an effective vaccine against multiple serotypes of the pathogen. In the present study, we used bio-informatics approach to identify antigens shared among multiple serotypes of Shigella spp. This approach led to the identification of many immunogenic peptides. The five most promising peptides based on MHC binding efficiency were a putative lipoprotein (EL PGI I), a putative heat shock protein (EL PGI II), Spa32 (EL PGI III), IcsB (EL PGI IV) and a hypothetical protein (EL PGI V). These peptides were synthesized and the immunogenicity was evaluated in BALB/c mice by ELISA and cytokine assays. The putative heat shock protein (HSP) and the hypothetical protein elicited good humoral response, whereas putative lipoprotein, Spa32 and IcsB elicited good T-cell response as revealed by increased IFN-γ and TNF-α cytokine levels. The patient sera from confirmed cases of shigellosis were also evaluated for the presence of peptide specific antibodies with significant IgG and IgA antibodies against the HSP and the hypothetical protein, bestowing them as potential future vaccine candidates. The antigens reported in this study are novel and have not been tested as vaccine candidates against Shigella. This study offers time and cost-effective way of identifying unprecedented immunogenic antigens to be used as potential vaccine candidates. Moreover, this approach should easily be extendable to find new potential vaccine candidates for other pathogenic bacteria.

Immuno-informatics Analysis to Identify Novel Vaccine Candidates and Design of a Multi-Epitope Based Vaccine Candidate Against Theileria parasites

“…Since the experimental methods are difficult and time-consuming, the immuno-informatics approach can narrow down a vast number of potential molecules to be tested, thus increasing the chance of finding better candidates. Numerous studies have shown that epitopes based vaccines could be effective in elucidating protective immunity against various pathogens such as influenza A, hepatitis B and C virus, Leishmania and Shigella ( 28 – 32 ). In this study, using immuno-informatics-driven vaccine target screening strategy, the available transcriptomic and proteomic data for Theileria parasites were analyzed to predict proteins/epitopes for vaccine development that could elicit protective humoral and cellular immune response.…”

Immunoinformatics Approach for Multiepitope Vaccine Prediction from H, M, F, and N Proteins of Peste des Petits Ruminants Virus

“…The validity and benefits of peptide vaccines designed by bioinformatics tools had been verified by appreciable research [24]. The availability of the complete genome, proteome sequences, and pathogenesis of many pathogenic microorganisms contributed to the production of a vaccine through bioinformatics [24, 39]. In this study, the predicted epitopes from B and T lymphocytes would help in the development of a more effective, reliable, preventive, and therapeutic vaccine against the PPRV than the conventional methods.…”

Designing a less immunogenic nattokinase from Bacillus subtilis subsp. natto: a computational mutagenesis

“…Linear B-cell epitopes prediction tools generated better accuracy than the discontinuous B-cell epitopes prediction. Several studies even only used linear B-cell tools for the prediction for the epitopes [46,55,56]. Entropy method (ExPaSy) was one way to determine the conserved residues.…”