上海交通大学学报（医学版）

上海交通大学学报（医学版）

• 论著（基础研究） • 上一篇    下一篇

结核分枝杆菌RD12区T细胞表位分布情况预测及分析

叶 娟1，张舒林2，刘文第1   

  1. 1.河南中医学院 医学免疫学重点实验室， 郑州 450008； 2.上海交通大学 基础医学院免疫学与微生物学系， 上海 200025
  • 出版日期:2014-01-28 发布日期:2014-01-29
  • 通讯作者: 张舒林, 电子信箱: shulinzhang@sjtu.edu.cn; 刘文第, 电子信箱: wendiliu@163.com。
  • 作者简介:叶 娟（1989—）， 女， 硕士生; 电子信箱: yejuan0229@126.com。
  • 基金资助:

    “十二五”国家科技重大专项（2013ZX10003002-005）；国家自然基金项目（81271794）；上海市科委技术支撑项目（12441903300）

Prediction and analysis of the distribution of T cell epitopes encoded by the specific RD12 region of Mycobacterium tuberculosis

YE Juan1, ZHANG Shu-lin2, LIU Wen-di1   

  1. 1.Key Laboratory of Medical Immunology, Henan University of Traditional Chinese Medicine, Zhengzhou 450008, China; 2.Department of Immunology and Microbiology, Basic Medicine Faculty of Shanghai Jiao Tong University, Shanghai 200025, China
  • Online:2014-01-28 Published:2014-01-29
  • Supported by:

    Major Science and Technology Program in the National “12th 5-year Plan” of China，2013ZX10003002-005； National Natural Science Foundation of China， 81271794； Shanghai Science and Technology Commission Foundation， 12441903300

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摘要：

目的 预测并分析结核分枝杆菌（MTB）RD12区4个抗原的CD4+T和CD8+T细胞表位分布情况。方法 在NCBI数据库上查询并获得各个抗原的氨基酸序列，用Blast分析其与MTB复合群及人类蛋白的同源性。利用SYFPEITHI、NETCTL、BIMAS和NetMHC数据库预测并分析MTB的RD12区抗原CD8+ T细胞表位的分布情况；利用NetMHC数据库预测并分析MTB的RD12区抗原的CD4+ T细胞表位的分布情况。然后，综合CD4与CD8表位预测，筛选出优势表位肽段。结果 通过预测与分析，初步筛选出MTB的RD12区4个抗原的CD8+ T细胞候选表位16个；CD4+ T细胞的强结合候选表位234个，弱结合候选表位505个，综合CD4与CD8表位预测并分析，最终筛选出13个优势表位肽段。结论 预测出来的T细胞候选表位将为结核病的特异性诊断及新的抗结核多表位疫苗的研究奠定基础。

关键词: 结核分枝杆菌, RD12区, T细胞, 表位分析

Abstract:

Objective To predict and analyze distribution of CD4+ T cell and CD8+ T cell epitopes encoded by the specific RD12 region of Mycobacterium tuberculosis (MTB). Methods The amino acid sequences of the antigens were obtained by online NCBI database. The homology between MTB complex and human proteins was analyzed by BLAST. The distribution of CD8+ T cell epitopes was predicted by SYFPEITHI, NETCTL, BIMAS, and NetMHC databases. The distribution of CD4+ T cell epitopes was predicted by NetMHC databases. After analyzing distribution of CD4+ and CD8+ T cell epitopes, the superior epitopes were selected. Results Sixteen candidate CD8+ T cell epitopes binding to 4 amino acids and 234 strong and 505 weak candidate CD4+ T cell epitopes binding to 15 amino acids were screened preliminarily, respectively. Thirteen superior epitopes were selected. Conclusion The candidate T cell epitopes may help lay a foundation for the research of multiepitope candidate vaccines and early diagnosis of tuberculosis.

Key words: Mycobacterium tuberculosis, specific RD12 region, T cell, epitope analysis