Immunoinformatics-based design and evaluation of a multi-epitope vaccine against Vibrio fluvialis

Vibrio fluvialis is an emerging foodborne pathogen causing gastroenteritis and extraintestinal infections, representing a significant public health concern due to rising antimicrobial resistance and the absence of an approved vaccine. This study aimed to design a multi-epitope subunit vaccine against V. fluvialis using immunoinformatics and a standard multi-epitope vaccine design pipeline. Two surface-exposed immunogenic membrane proteins, ATP-dependent zinc metalloprotease FtsH and lytic murein transglycosylase F, were selected as antigenic targets. Ten epitopes, including four MHC class I, four MHC class II, and two B-cell epitopes, were predicted and assembled into a 246 amino acid vaccine construct. The construct showed an antigenicity score of 0.8610. Population coverage analysis indicated that these epitopes could potentially cover 99.97% of the global population. The vaccine exhibited favorable physicochemical properties, with an instability index of 33.18 and a GRAVY score of - 0.282, suggesting stability and hydrophilicity. The tertiary structure was modeled using AlphaFold3 and docked with Toll-like receptor 2, yielding a docking score of - 270.01. Molecular dynamics simulations for 100 ns suggested stability of the vaccine-TLR2 complex. Codon optimization indicated high expression potential in Escherichia coli, with a CAI value of 0.95. Overall, the vaccine showed strong in silico immunogenic potential and requires further experimental validation through in vitro and in vivo studies.

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Publication Details

Journal
Scientific Reports
Published
2026-01-13
DOI
https://doi.org/10.1038/s41598-026-35434-4
Citations
3
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
66.71

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article

Immunoinformatics-based design and evaluation of a multi-epitope vaccine against Vibrio fluvialis

Nantenaina Tombozara, Abeer S. Aloufi, Tariq Aziz, Parveen Qadir et al.
3 citations
Scientific Reports
vaccines and immunoinformatics approaches
66.71
article

Immunoinformatics-based design and evaluation of a multi-epitope vaccine against Vibrio fluvialis

Nantenaina Tombozara, Abeer S. Aloufi, Tariq Aziz, Parveen Qadir, Muhammad Husnain, Maher S. Alwethynani, Muhammad Naveed, Muhammad Nouman Majeed, Ashwag Shami, Muhammad Asim
article en
3 citations

Abstract

Vibrio fluvialis is an emerging foodborne pathogen causing gastroenteritis and extraintestinal infections, representing a significant public health concern due to rising antimicrobial resistance and the absence of an approved vaccine. This study aimed to design a multi-epitope subunit vaccine against V. fluvialis using immunoinformatics and a standard multi-epitope vaccine design pipeline. Two surface-exposed immunogenic membrane proteins, ATP-dependent zinc metalloprotease FtsH and lytic murein transglycosylase F, were selected as antigenic targets. Ten epitopes, including four MHC class I, four MHC class II, and two B-cell epitopes, were predicted and assembled into a 246 amino acid vaccine construct. The construct showed an antigenicity score of 0.8610. Population coverage analysis indicated that these epitopes could potentially cover 99.97% of the global population. The vaccine exhibited favorable physicochemical properties, with an instability index of 33.18 and a GRAVY score of - 0.282, suggesting stability and hydrophilicity. The tertiary structure was modeled using AlphaFold3 and docked with Toll-like receptor 2, yielding a docking score of - 270.01. Molecular dynamics simulations for 100 ns suggested stability of the vaccine-TLR2 complex. Codon optimization indicated high expression potential in Escherichia coli, with a CAI value of 0.95. Overall, the vaccine showed strong in silico immunogenic potential and requires further experimental validation through in vitro and in vivo studies.

Scientific ReportsVol. 16(1)
Princess Nourah bint Abdulrahman University (SA), University of Central Punjab (PK), University of Ioannina (GR), Shaqra University (SA), Institute Malgache De Recherches Appliquées (MG)
Princess Nourah Bint Abdulrahman University
Openalex Percentile: Top 0%
vaccines and immunoinformatics approaches
66.71
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