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Diarrhoea infection is a major global health public problem and is caused by many organisms including diarrheagenic Escherichia coli pathotypes. The common problem with diarrhoea is the drug resistance of pathogenic bacteria, the most promising alternative means of preventing drug resistance is vaccination. However, there has not been any significant success in the prevention of diarrhoea caused by E. coli through vaccination. Epitope-based vaccine is gaining more attention due to its safety and specificity. Sequence variation of protective antigens of the pathogen has posed a new challenge in the development of epitope-based vaccines against the infection, leading to the necessity of multiepitope based design. In this study, immunoinformatics tools were used to design multiepitope vaccine candidates from plasmid genome sequences of multiple pathotypes of E. coli species involved in diarrhoea infections. The ability of the identified epitopes to be used as a cross-protect multiepitope vaccine was achieved by identifying conserved, immunogenic and antigenic peptides that can elicit CD4 + T-cell, CD8 + T-cell and B-cell and bind to MHC I and II HLA alleles. The molecular docking results of T-cell epitopes showed their well binding affinity to receptive protein and with a wider population coverage. The different multiepitope-based vaccines (MEVCs) candidates were constructed and based on the types of epitope linker they contained. The MEVCs exhibited very good binding interactions with the human immune receptor. Among multiepitope vaccines constructed, MEVC6, MEVCA and MEVCB are more promising as potential vaccine candidates for cross-protection against gastrointestinal infections according to the computational study. It is also hoped that after validation and testing, the predicted multiepitope-based vaccine candidates will probably resolve the challenge of immunological heterogeneity facing enteric vaccine development., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Influenza remains a global health concern due to its potential to cause pandemics as a result of rapidly mutating influenza virus strains. Existing vaccines often struggle to keep up with these rapidly mutating flu viruses. Therefore, the development of a broad-spectrum peptide vaccine that can stimulate an optimal antibody response has emerged as an innovative approach to addressing the influenza threat. In this study, an immunoinformatic approach was employed to rapidly predict immunodominant epitopes from different antigens, aiming to develop an effective multiepitope influenza vaccine (MEV). The immunodominant B-cell linear epitopes of seasonal influenza strains hemagglutinin (HA) and neuraminidase (NA) were predicted using an antibody-peptide microarray, involving a human cohort including vaccinees and infected patients. On the other hand, bioinformatics tools were used to predict immunodominant cytotoxic T-cell (CTL) and helper T-cell (HTL) epitopes. Subsequently, these epitopes were evaluated by various immunoinformatic tools. Epitopes with high antigenicity, high immunogenicity, non-allergenicity, non-toxicity, as well as exemplary conservation were then connected in series with appropriate linkers and adjuvants to construct a broad-spectrum MEV. Moreover, the structural analysis revealed that the MEV candidates exhibited good stability, and the docking results demonstrated their strong affinity to Toll-like receptors 4 (TLR4). In addition, molecular dynamics simulation confirmed the stable interaction between TLR4 and MEVs. Three injections with MEVs showed a high level of B-cell and T-cell immune responses according to the immunological simulations in silico. Furthermore, in-silico cloning was performed, and the results indicated that the MEVs could be produced in considerable quantities in Escherichia coli (E. coli). Based on these findings, it is reasonable to create a broad-spectrum MEV against different subtypes of influenza A and B viruses in silico. [ABSTRACT FROM AUTHOR]

Zika virus (ZIKV) is a flavivirus belonging to the family Flaviviridae. According to the World Health Organization, ZIKV is considered a serious public health problem worldwide because of its association with microcephaly and Guillain-Barré syndrome. There are currently no approved vaccines or specific medical treatments, making both aspects relevant targets for biomedical research. In our study we designed and produced in Escherichia coli a multiepitope vaccine candidate against ZIKV capable of inducing cellular and humoral responses. A chimeric protein was designed based on a series of ZIKV antigenic sequences and a bacterial carrier. Modeling, prediction, and analysis of the recombinant protein structure was performed using Phyre2 and ChimeraX servers. The antigen was produced in Escherichia coli and purified from inclusion bodies. Twenty-six sequences were obtained and analyzed on the Phyre2 and ChimeraX servers. The selected chimera had a hydrophobicity index of - 4.635. The protein was efficiently induced at a lactose concentration of 1.5 g/L, and the SDS-PAGE analysis shows that most of the protein remains in the insoluble fraction. However, the protein was successfully solubilized, refolded and purified. The next step is evaluation in mice to determine the immunogenic response. [ABSTRACT FROM AUTHOR]