The use of binding-prediction models to identify M. bovis-specific antigenic peptides for screening assays in bovine tuberculosis
The use of binding-prediction models to identify M. bovis-specific antigenic peptides for screening assays in bovine tuberculosis
复制标题
DOI：
10.1016/j.vetimm.2011.03.006
复制
发表时间：
2011-06-15
影响因子：
1.8
通讯作者：
Vordermeier, H. Martin
中科院分区：
文献类型：
--
作者：
Jones, Gareth J.;Bagaini, Francois;Vordermeier, H. Martin
鉴定MHC ii类限制性抗原肽以纳入疫苗和/或作为分枝杆菌感染的诊断试验试剂仍然是一个高度优先的研究。为了加速这类肽的发现，已经开发了许多生物信息学工具来预测给定肽是否可能与MHC II类分子形成稳定的结合相互作用。然而，目前还没有专门用于鉴定牛MHC (BoLA) ii类限制性肽的预测工具。利用105个牛分枝杆菌衍生肽刺激牛分枝杆菌感染牛的全血获得的实验免疫原性数据，我们比较了一种新的基于BoLA DRB3结构的预测方法（Hepitom）和人类MHC II类结合预测模型ProPred在预测诱导牛t细胞活化的肽方面的能力。在考虑多肽抗原性的严格切断条件下，Hepitom和ProPred检测免疫原性多肽的敏感性分别为62%和77%。相比之下，Hepitom模型表现出更大的特异性，Hepitom和ProPred的特异性分别为66%和34%。使用所有肽，鉴定出11个牛分枝杆菌蛋白中有7个具有高度免疫原性。当只使用Hepitom预测肽时，除了一种抗原外，其他抗原都被识别出来了，而使用ProPred预测肽时，七个抗原中只有四个被识别出来了。总之，我们证明Hepitom模型是一种有用的预筛选工具，可以为进一步的牛免疫原性研究选择肽，而不会对抗原牛支原体蛋白的鉴定产生重大影响。爱思唯尔B.V.版权所有
The identification of MHC class II-restricted antigenic peptides for inclusion into vaccines and/or as diagnostic test reagents for mycobacterial infections remains a high research priority. To expedite discovery of such peptides, numerous bioinformatic tools have been developed to predict whether a given peptide is likely to form a stable binding interaction with MHC class II molecules. However, no prediction tool dedicated to the identification of bovine MHC (BoLA) class II-restricted peptides is currently available. Using experimental immunogenicity data derived from the stimulation of whole blood of Mycobacterium bovis-infected cattle with 105 individual M. bovis-derived peptides, we have compared the ability of a novel BoLA DRB3 structure-based prediction method (Hepitom) with the human MHC class II binding predictor model ProPred in predicting peptides that induce bovine T-cell activation. When a stringent cut off for considering peptide antigenicity was applied, the sensitivities of Hepitom and ProPred in detecting immunogenic peptides were 62% and 77%, respectively. In contrast, the Hepitom model showed greater specificity, with values of 66% and 34% for Hepitom and ProPred, respectively. Using all peptides, seven out of eleven M. bovis proteins were identified as being highly immunogenic. All but one of these antigens were also identified when just the Hepitom predicted peptides were used, while only four of the seven were identified using the ProPred predicted peptides. In conclusion, we demonstrate that the Hepitom model is a useful pre-screening tool to select peptides for further immunogenicity studies in cattle without major impact on the identification of antigenic M. bovis proteins. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.