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An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus

BACKGROUND: TSST-1 is a secretory and pyrogenic superantigen that is being responsible for staphylococcal mediated food poisoning and associated clinical manifestations. It is one of the main targets for the construction of vaccine candidates against Staphylococcus aureus. Most of the vaccines have...

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Autores principales: Kolla, Harish Babu, Tirumalasetty, Chakradhar, Sreerama, Krupanidhi, Ayyagari, Vijaya Sai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8112219/
https://www.ncbi.nlm.nih.gov/pubmed/33974183
http://dx.doi.org/10.1186/s43141-021-00160-z
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author Kolla, Harish Babu
Tirumalasetty, Chakradhar
Sreerama, Krupanidhi
Ayyagari, Vijaya Sai
author_facet Kolla, Harish Babu
Tirumalasetty, Chakradhar
Sreerama, Krupanidhi
Ayyagari, Vijaya Sai
author_sort Kolla, Harish Babu
collection PubMed
description BACKGROUND: TSST-1 is a secretory and pyrogenic superantigen that is being responsible for staphylococcal mediated food poisoning and associated clinical manifestations. It is one of the main targets for the construction of vaccine candidates against Staphylococcus aureus. Most of the vaccines have met failure due to adverse reactions and toxicity reported during late clinical studies. To overcome this, an immunoinformatics approach is being used in the present study for the design of a multi-epitope vaccine to circumvent the problems related to toxicity and allergenicity. RESULTS: In this study, a multi-epitope vaccine against Staphylococcus aureus targeting TSST-1 was designed through an immunoinformatics approach. B cell and T cell epitopes were predicted in silico and mapped with linkers to avoid junctional immunogenicity and to ensure the efficient presentation of exposed epitopes through HLA. β-defensin and PADRE were adjusted at the N-terminal end of the final vaccine as adjuvants. Physiochemical parameters, antigenicity, and allergenicity of the vaccine construct were determined with the help of online servers. The three-dimensional structure of the vaccine protein was predicted and validated with various tools. The affinity of the vaccine with TLR-3 was studied through molecular docking studies and the interactions of two proteins were visualized using LigPlot(+). The vaccine was successfully cloned in silico into pET-28a (+) for efficient expression in E. coli K12 system. Population coverage analysis had shown that the vaccine construct can cover 83.15% of the global population. Immune simulation studies showed an increase in the antibody levels, IL-2, IFN-γ, TGF-β, B cell, and T cell populations and induced primary, secondary, and tertiary immune responses. CONCLUSION: Multi-epitope vaccine designed through a computational approach is a non-allergic and non-toxic antigen. Preliminary in silico reports have shown that this vaccine could elicit both B cell and T cell responses in the host as desired.
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spelling pubmed-81122192021-05-12 An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus Kolla, Harish Babu Tirumalasetty, Chakradhar Sreerama, Krupanidhi Ayyagari, Vijaya Sai J Genet Eng Biotechnol Research BACKGROUND: TSST-1 is a secretory and pyrogenic superantigen that is being responsible for staphylococcal mediated food poisoning and associated clinical manifestations. It is one of the main targets for the construction of vaccine candidates against Staphylococcus aureus. Most of the vaccines have met failure due to adverse reactions and toxicity reported during late clinical studies. To overcome this, an immunoinformatics approach is being used in the present study for the design of a multi-epitope vaccine to circumvent the problems related to toxicity and allergenicity. RESULTS: In this study, a multi-epitope vaccine against Staphylococcus aureus targeting TSST-1 was designed through an immunoinformatics approach. B cell and T cell epitopes were predicted in silico and mapped with linkers to avoid junctional immunogenicity and to ensure the efficient presentation of exposed epitopes through HLA. β-defensin and PADRE were adjusted at the N-terminal end of the final vaccine as adjuvants. Physiochemical parameters, antigenicity, and allergenicity of the vaccine construct were determined with the help of online servers. The three-dimensional structure of the vaccine protein was predicted and validated with various tools. The affinity of the vaccine with TLR-3 was studied through molecular docking studies and the interactions of two proteins were visualized using LigPlot(+). The vaccine was successfully cloned in silico into pET-28a (+) for efficient expression in E. coli K12 system. Population coverage analysis had shown that the vaccine construct can cover 83.15% of the global population. Immune simulation studies showed an increase in the antibody levels, IL-2, IFN-γ, TGF-β, B cell, and T cell populations and induced primary, secondary, and tertiary immune responses. CONCLUSION: Multi-epitope vaccine designed through a computational approach is a non-allergic and non-toxic antigen. Preliminary in silico reports have shown that this vaccine could elicit both B cell and T cell responses in the host as desired. Springer Berlin Heidelberg 2021-05-11 /pmc/articles/PMC8112219/ /pubmed/33974183 http://dx.doi.org/10.1186/s43141-021-00160-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Kolla, Harish Babu
Tirumalasetty, Chakradhar
Sreerama, Krupanidhi
Ayyagari, Vijaya Sai
An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus
title An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus
title_full An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus
title_fullStr An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus
title_full_unstemmed An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus
title_short An immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen TSST-1 of Staphylococcus aureus
title_sort immunoinformatics approach for the design of a multi-epitope vaccine targeting super antigen tsst-1 of staphylococcus aureus
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8112219/
https://www.ncbi.nlm.nih.gov/pubmed/33974183
http://dx.doi.org/10.1186/s43141-021-00160-z
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