In silico vaccine design: Targeting highly epitopic regions of Clostridium perfringens type D epsilon toxin and Clostridium novyi type B alpha toxin for optimal immunogenicity

被引:0
作者
Ashoori, Nastaran [1 ]
Ranjbar, Mohammad Mehdi [2 ]
Schirhagl, Romana [1 ]
机构
[1] Univ Groningen, Univ Med Ctr Groningen, Antonius Deusinglaan 1, NL-9713AW Groningen, Netherlands
[2] Agr Res Educ & Extens Org AREEO, Razi Vaccine & Serum Res Inst, Karaj, Iran
来源
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL | 2024年 / 25卷
关键词
Vaccines; Machine learning; In silico; Toxins; PEPTIDE VACCINE; IMMUNOINFORMATICS; IDENTIFICATION; SORDELLII; PROTEIN; VIRUS; SHEEP; GENE;
D O I
10.1016/j.csbj.2024.08.009
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Livestock infections caused by highly toxic bacteria, such as Clostridium perfringens type D and Clostridium novyi type B, present significant challenges in veterinary medicine. Such infections often require complex and elusive treatment regimens. Developing effective vaccines tailored to combat these specific pathogens remains a pressing need within the field. These bacteria are notorious for their extreme toxicity and the difficulty in culturing them for vaccine production. To address this challenge, we engineered a new potential vaccine candidate capable of neutralizing the virulence of both bacterial strains. Leveraging computational techniques, we identified epitopic regions within C. perfringens Epsilon Toxin (ETX) and C. novyi Alpha Toxin (ATX). Through fusion gene design, we integrated these epitopic regions alongside the PADRE-peptide sequence. The PADRE-peptide serves as a universal adjuvant to induce an immune response. The culmination of our efforts materialized in a Recombinant Fusion Protein D (rFPD), a novel vaccine construct designed to elicit robust and specific immune defenses against both bacterial species. By combining in-silico design and molecular engineering, our study represents a promising stride toward combating the impact of these pathogenic bacteria in livestock.
引用
收藏
页码:153 / 164
页数:12
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