In silico design and in vivo evaluation of two multi-epitope vaccines containing build-in adjuvant with chitosan nanoparticles against uropathogenic Escherichia coli

A review on the development of bacterial multi-epitope recombinant protein vaccines via reverse vaccinology

Bacterial vaccines play a crucial role in combating bacterial infectious diseases. Apart from the prevention of disease, bacterial vaccines also help to reduce the mortality rates in infected populations. Advancements in vaccine development technologies have addressed the constraints of traditional vaccine design, providing novel approaches for the development of next-generation vaccines. Advancements in reverse vaccinology, bioinformatics, and comparative proteomics have opened horizons in vaccine development. Specifically, the use of protein structural data in crafting multi-epitope vaccines (MEVs) to target pathogens has become an important research focus in vaccinology. In this review, we focused on describing the methodologies and tools for epitope vaccine development, along with recent progress in this field. Moreover, this article also discusses the challenges in epitope vaccine development, providing insights for the future development of bacterial multi-epitope genetically engineered vaccines.

Immunostimulatory chimeric protein encapsulated in gelatin nanoparticles elicits protective immunity against Pseudomonas aeruginosa respiratory tract infection

This study presents the design and fabrication of an innovative vaccine candidate targeting Pseudomonas aeruginosa (P. aeruginosa). The vaccine consists of gelatin nanoparticles (GNPs) encapsulating a chimeric protein (CP) derived from the ExoS and OprI proteins from P. aeruginosa. The physicochemical properties of the GNPs were assessed using dynamic light scattering (DLS) and electron microscopy. The toxicity, encapsulation efficacy, release profile, and effectiveness of CP-encapsulated GNPs (CP-GNPs) in an animal model were investigated. The resulting nanovaccine demonstrated uniform spherical particles with an average size of 135 nm and an encapsulation efficiency of 85 %. The release assay revealed that 23 % of the antigen was released from the CP-GNPs after 20 days. The GNPs did not exhibit any toxic effects on L929 cells in vitro. The formulation induced both systemic and mucosal antibody responses. Additionally, CP-GNPs stimulated cytokine responses, including IFN-γ, IL-4, and IL-17, indicating the induction of both humoral (Th2) and cellular (Th1) responses. The CP-encapsulated GNPs formulation effectively protected the mice lungs against experimental respiratory tract infection, reducing colony count and inflammation. These findings suggest that CP-GNPs hold promise as a potential strategy for preventing respiratory tract infections caused by P. aeruginosa. Further research is needed to explore its clinical application.

AutoEpiCollect, a Novel Machine Learning-Based GUI Software for Vaccine Design: Application to Pan-Cancer Vaccine Design Targeting PIK3CA Neoantigens

Previous epitope-based cancer vaccines have focused on analyzing a limited number of mutated epitopes and clinical variables preliminarily to experimental trials. As a result, relatively few positive clinical outcomes have been observed in epitope-based cancer vaccines. Further efforts are required to diversify the selection of mutated epitopes tailored to cancers with different genetic signatures. To address this, we developed the first version of AutoEpiCollect, a user-friendly GUI software, capable of generating safe and immunogenic epitopes from missense mutations in any oncogene of interest. This software incorporates a novel, machine learning-driven epitope ranking method, leveraging a probabilistic logistic regression model that is trained on experimental T-cell assay data. Users can freely download AutoEpiCollectGUI with its user guide for installing and running the software on GitHub. We used AutoEpiCollect to design a pan-cancer vaccine targeting missense mutations found in the proto-oncogene PIK3CA, which encodes the p110ɑ catalytic subunit of the PI3K kinase protein. We selected PIK3CA as our gene target due to its widespread prevalence as an oncokinase across various cancer types and its lack of presence as a gene target in clinical trials. After entering 49 distinct point mutations into AutoEpiCollect, we acquired 361 MHC Class I epitope/HLA pairs and 219 MHC Class II epitope/HLA pairs. From the 49 input point mutations, we identified MHC Class I epitopes targeting 34 of these mutations and MHC Class II epitopes targeting 11 mutations. Furthermore, to assess the potential impact of our pan-cancer vaccine, we employed PCOptim and PCOptim-CD to streamline our epitope list and attain optimized vaccine population coverage. We achieved a world population coverage of 98.09% for MHC Class I data and 81.81% for MHC Class II data. We used three of our predicted immunogenic epitopes to further construct 3D models of peptide-HLA and peptide-HLA-TCR complexes to analyze the epitope binding potential and TCR interactions. Future studies could aim to validate AutoEpiCollect's vaccine design in murine models affected by PIK3CA-mutated or other mutated tumor cells located in various tissue types. AutoEpiCollect streamlines the preclinical vaccine development process, saving time for thorough testing of vaccinations in experimental trials.

Proteomics-based vaccine targets annotation and design of multi-epitope vaccine against antibiotic-resistant Streptococcus gallolyticus

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine is currently available. Therefore, it is essential to develop an effective S. gallolyticus vaccine. Core proteomics was used in this study together with subtractive proteomics and reverse vaccinology approach to find antigenic proteins that could be utilized for the design of the S. gallolyticus multi-epitope vaccine. The pipeline identified two antigenic proteins as potential vaccine targets: penicillin-binding protein and the ATP synthase subunit. T and B cell epitopes from the specific proteins were forecasted employing several immunoinformatics and bioinformatics resources. A vaccine (360 amino acids) was created using a combination of seven cytotoxic T cell lymphocyte (CTL), three helper T cell lymphocyte (HTL), and five linear B cell lymphocyte (LBL) epitopes. To increase immune responses, the vaccine was paired with a cholera enterotoxin subunit B (CTB) adjuvant. The developed vaccine was highly antigenic, non-allergenic, and stable for human use. The vaccine's binding affinity and molecular interactions with the human immunological receptor TLR4 were studied using molecular mechanics/generalized Born surface area (MMGBSA), molecular docking, and molecular dynamic (MD) simulation analyses. Escherichia coli (strain K12) plasmid vector pET-28a ( +) was used to examine the ability of the vaccine to be expressed. According to the outcomes of these computer experiments, the vaccine is quite promising in terms of developing a protective immunity against diseases. However, in vitro and animal research are required to validate our findings.

Vaccines against extraintestinal pathogenic Escherichia coli (ExPEC): progress and challenges

The emergence of antimicrobial resistance (AMR) is a principal global health crisis projected to cause 10 million deaths annually worldwide by 2050. While the Gram-negative bacteria Escherichia coli is commonly found as a commensal microbe in the human gut, some strains are dangerously pathogenic, contributing to the highest AMR-associated mortality. Strains of E. coli that can translocate from the gastrointestinal tract to distal sites, called extraintestinal E. coli (ExPEC), are particularly problematic and predominantly afflict women, the elderly, and immunocompromised populations. Despite nearly 40 years of clinical trials, there is still no vaccine against ExPEC. One reason for this is the remarkable diversity in the ExPEC pangenome across pathotypes, clades, and strains, with hundreds of genes associated with pathogenesis including toxins, adhesins, and nutrient acquisition systems. Further, ExPEC is intimately associated with human mucosal surfaces and has evolved creative strategies to avoid the immune system. This review summarizes previous and ongoing preclinical and clinical ExPEC vaccine research efforts to help identify key gaps in knowledge and remaining challenges.

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.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.