In Silico-Guided Sequence Modification of Epitopes in Cancer Vaccine Development

A comprehensive approach to developing a multi-epitope vaccine against Mycobacterium tuberculosis: from in silico design to in vitro immunization evaluation

Introduction

The Bacillus Calmette-Guérin (BCG) vaccine, currently used against tuberculosis (TB), exhibits inconsistent efficacy, highlighting the need for more potent TB vaccines.

Materials and methods

In this study, we employed reverse vaccinology techniques to develop a promising multi-epitope vaccine (MEV) candidate, called PP13138R, for TB prevention. PP13138R comprises 34 epitopes, including B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes. Using bioinformatics and immunoinformatics tools, we assessed the physicochemical properties, structural features, and immunological characteristics of PP13138R.

Results

The vaccine candidate demonstrated excellent antigenicity, immunogenicity, and solubility without any signs of toxicity or sensitization. In silico analyses revealed that PP13138R interacts strongly with Toll-like receptor 2 and 4, stimulating innate and adaptive immune cells to produce abundant antigen-specific antibodies and cytokines. In vitro experiments further supported the efficacy of PP13138R by significantly increasing the population of IFN-γ+ T lymphocytes and the production of IFN-γ, TNF-α, IL-6, and IL-10 cytokines in active tuberculosis patients, latent tuberculosis infection individuals, and healthy controls, revealing the immunological characteristics and compare the immune responses elicited by the PP13138R vaccine across different stages of Mycobacterium tuberculosis infection.

Conclusion

These findings highlight the potential of PP13138R as a promising MEV candidate, characterized by favorable antigenicity, immunogenicity, and solubility, without any toxicity or sensitization.

Assessment of SARS-CoV-2 specific CD4(+) and CD8 (+) T cell responses using MHC class I and II tetramers

The success of SARS-CoV-2 (CoV-2) vaccines is measured by their ability to mount immune memory responses that are long-lasting. To achieve this goal, it is important to identify surrogates of immune protection, namely, CoV-2 MHC Class I and II immunodominant pieces/epitopes and methodologies to measure them. Here, we present results of flow cytometry-based MHC Class I and II QuickSwitch^TM platforms for assessing SARS-CoV-2 peptide binding affinities to various human alleles as well as the H-2 Kb mouse allele. Multiple SARS-CoV-2 potential MHC binders were screened and validated by QuickSwitch testing. The screen included 31 MHC Class I and 19 MHC Class II peptides predicted to be good binders by the IEDB web resource provided by NIAID. While several predicted peptides with acceptable theoretical Kd showed poor MHC occupancies, fourteen MHC class II and three MHC class I peptides showed promiscuity in that they bind to multiple MHC molecule types. In addition to providing important data towards the study of the SARS-CoV-2 virus and its presented antigenic epitopes, the peptides identified in this study can be used in the QuickSwitch platform to generate MHC tetramers. With those tetramers, scientists can assess CD4 + and CD8 + immune responses to these different MHC/peptide complexes.