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马尔他布鲁氏菌的免疫信息学分析,以寻求一种合适的抗布鲁氏菌病疫苗。

Immunoinformatics analysis of Brucella melitensis to approach a suitable vaccine against brucellosis.

作者信息

Hashemzadeh Pejman, Nezhad Saba Asgari, Khoshkhabar Hossein

机构信息

Department of Medical Biotechnology, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Lorestan, Iran.

Department of Immunology, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Lorestan, Iran.

出版信息

J Genet Eng Biotechnol. 2023 Nov 29;21(1):152. doi: 10.1186/s43141-023-00614-6.

DOI:10.1186/s43141-023-00614-6
PMID:38019359
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10686926/
Abstract

BACKGROUND

Brucellosis caused by B. melitensis is one of the most important common diseases between humans and livestock. Currently, live attenuated vaccines are used for this disease, which causes many problems, and unfortunately, there is no effective vaccine for human brucellosis. The aim of our research was to design a recombinant vaccine containing potential immunogenic epitopes against B. melitensis.

METHODS

In this study, using immunoinformatics approaches, 3 antigens Omp31, Omp25, and Omp28 were identified and the amino acid sequence of the selected antigens was determined in NCBI. Signal peptides were predicted by SignaIP-5.0 server. To predict B-cell epitopes from ABCpred and Bcepred servers, to predict MHC-I epitopes from RANKPEP and SYFPEITHI servers, to predict MHC-II epitopes from RANKPEP and MHCPred servers, and to predict CTL epitopes were used from the CTLPred server. Potentially immunogenic final epitopes were joined by flexible linkers. Finally, allergenicity (AllerTOP 2.0 server), antigenicity (Vaxijen server), physicochemical properties (ProtParam server), solubility (Protein-sol server), secondary (PSIPRED and GRO4 servers) and tertiary structure (I-TASSER server), refinement (GalaxyWEB server), validation (ProSA-web, Molprobity, and ERRAT servers), and optimization of the codon sequence (JCat server) of the structure of the multi-epitope vaccine were analyzed.

RESULTS

The analysis of immunoinformatics tools showed that the designed vaccine has high quality, acceptable physicochemical properties, and can induce humoral and cellular immune responses against B. melitensis bacteria. In addition, the high expression level of recombinant antigens in the E. coli host was observed through in silico simulation.

CONCLUSION

According to the results in silico, the designed vaccine can be a suitable candidate to fight brucellosis and in vitro and in vivo studies are needed to evaluate the research of this study.

摘要

背景

由羊种布鲁氏菌引起的布鲁氏菌病是人和家畜中最重要的常见疾病之一。目前,减毒活疫苗用于该病,这引发了许多问题,而且不幸的是,尚无针对人类布鲁氏菌病的有效疫苗。我们研究的目的是设计一种包含针对羊种布鲁氏菌潜在免疫原性表位的重组疫苗。

方法

在本研究中,使用免疫信息学方法,鉴定出3种抗原Omp31、Omp25和Omp28,并在NCBI中确定所选抗原的氨基酸序列。通过SignaIP-5.0服务器预测信号肽。使用ABCpred和Bcepred服务器预测B细胞表位,使用RANKPEP和SYFPEITHI服务器预测MHC-I表位,使用RANKPEP和MHCPred服务器预测MHC-II表位,并使用CTLPred服务器预测CTL表位。潜在的免疫原性最终表位通过柔性接头连接。最后,分析了多表位疫苗结构的致敏性(AllerTOP 2.0服务器)、抗原性(Vaxijen服务器)、理化性质(ProtParam服务器)、溶解性(Protein-sol服务器)、二级结构(PSIPRED和GRO4服务器)和三级结构(I-TASSER服务器)、优化(GalaxyWEB服务器)、验证(ProSA-web、Molprobity和ERRAT服务器)以及密码子序列优化(JCat服务器)。

结果

免疫信息学工具分析表明,设计的疫苗具有高质量、可接受的理化性质,并且能够诱导针对羊种布鲁氏菌的体液免疫和细胞免疫反应。此外,通过计算机模拟观察到重组抗原在大肠杆菌宿主中的高表达水平。

结论

根据计算机模拟结果,设计的疫苗可能是对抗布鲁氏菌病的合适候选疫苗,需要进行体外和体内研究以评估本研究成果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/e465e0a080aa/43141_2023_614_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/09e4acc7aaab/43141_2023_614_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/e465e0a080aa/43141_2023_614_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/22782b53d9e5/43141_2023_614_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/08a8bfa3e304/43141_2023_614_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/9a45ba5f054d/43141_2023_614_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/706fa1e72f91/43141_2023_614_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/1e78c4c13013/43141_2023_614_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/098f37d3917b/43141_2023_614_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/11dd469332d4/43141_2023_614_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/fc57636ec5c2/43141_2023_614_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/09e4acc7aaab/43141_2023_614_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37d4/10686926/e465e0a080aa/43141_2023_614_Fig10_HTML.jpg

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