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基于反向疫苗学鉴定新型潜在抗结核疫苗候选物

Identification of Novel Potential Vaccine Candidates against Tuberculosis Based on Reverse Vaccinology.

作者信息

Monterrubio-López Gloria P, González-Y-Merchand Jorge A, Ribas-Aparicio Rosa María

机构信息

Departamento de Microbiología, Escuela Nacional de Ciencias Biológicas (ENCB), Instituto Politécnico Nacional (IPN), Prolongación de Carpio y Plan de Ayala S/N, Colonia Santo Tomás, 11340 México, DF, Mexico.

出版信息

Biomed Res Int. 2015;2015:483150. doi: 10.1155/2015/483150. Epub 2015 Apr 15.

Abstract

Tuberculosis (TB) is a chronic infectious disease, considered as the second leading cause of death worldwide, caused by Mycobacterium tuberculosis. The limited efficacy of the bacillus Calmette-Guérin (BCG) vaccine against pulmonary TB and the emergence of multidrug-resistant TB warrants the need for more efficacious vaccines. Reverse vaccinology uses the entire proteome of a pathogen to select the best vaccine antigens by in silico approaches. M. tuberculosis H37Rv proteome was analyzed with NERVE (New Enhanced Reverse Vaccinology Environment) prediction software to identify potential vaccine targets; these 331 proteins were further analyzed with VaxiJen for the determination of their antigenicity value. Only candidates with values ≥0.5 of antigenicity and 50% of adhesin probability and without homology with human proteins or transmembrane regions were selected, resulting in 73 antigens. These proteins were grouped by families in seven groups and analyzed by amino acid sequence alignments, selecting 16 representative proteins. For each candidate, a search of the literature and protein analysis with different bioinformatics tools, as well as a simulation of the immune response, was conducted. Finally, we selected six novel vaccine candidates, EsxL, PE26, PPE65, PE_PGRS49, PBP1, and Erp, from M. tuberculosis that can be used to improve or design new TB vaccines.

摘要

结核病(TB)是一种慢性传染病,被认为是全球第二大死因,由结核分枝杆菌引起。卡介苗(BCG)对肺结核的疗效有限以及耐多药结核病的出现,使得需要更有效的疫苗。反向疫苗学利用病原体的整个蛋白质组,通过计算机方法选择最佳疫苗抗原。使用NERVE(新增强反向疫苗学环境)预测软件分析结核分枝杆菌H37Rv蛋白质组,以鉴定潜在的疫苗靶点;使用VaxiJen对这331种蛋白质进一步分析,以确定它们的抗原性值。仅选择抗原性值≥0.5、粘附素概率为50%且与人蛋白质或跨膜区域无同源性的候选物,得到73种抗原。这些蛋白质按家族分为七组,并通过氨基酸序列比对进行分析,选择出16种代表性蛋白质。对每个候选物进行文献检索、使用不同生物信息学工具进行蛋白质分析以及免疫反应模拟。最后,我们从结核分枝杆菌中选择了六种新型疫苗候选物,即EsxL、PE26、PPE65、PE_PGRS49、PBP1和Erp,可用于改进或设计新型结核病疫苗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efec/4413515/b3f51251ed6f/BMRI2015-483150.001.jpg

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