Department of Biotechnology and Biological Sciences, Institute of Advanced Research (IAR), Gandhinagar, Gujarat, India.
Emory Vaccine Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA.
Methods Mol Biol. 2020;2131:265-275. doi: 10.1007/978-1-0716-0389-5_14.
Immunoinformatic plays a pivotal role in vaccine design and development. While traditional methods are exclusively depended on immunological experiments, they are less effective, relatively expensive, and time-consuming. However, recent advances in the field of immunoinformatics have provided innovative tools for the rational design of vaccine candidates. This approach allows the selection of immunodominant regions from the sequence of whole genome of a pathogen. The identified immunodominant region could be used to develop potential vaccine candidates that can trigger protective immune responses in the host. At present, epitope-based vaccine is an attractive concept which has been successfully trailed to develop vaccines against a number of pathogens. In this chapter, we outline the methodology and workflow of how to deploy immunoinformatics tools in order to identify immunodominant epitopes using Shigella as a model organism. The immunodominant epitopes, derived from S. flexneri 2a using this workflow, were validated using in vivo model, indicating the robustness of the outlined workflow.
免疫信息学在疫苗设计和开发中起着关键作用。虽然传统方法完全依赖于免疫学实验,但它们的效果较差,相对昂贵,且耗时较长。然而,免疫信息学领域的最新进展为疫苗候选物的合理设计提供了创新工具。这种方法允许从病原体的全基因组序列中选择免疫显性区域。鉴定出的免疫显性区域可用于开发潜在的疫苗候选物,这些候选物可以在宿主中引发保护性免疫反应。目前,基于表位的疫苗是一个有吸引力的概念,已经成功地用于开发针对多种病原体的疫苗。在本章中,我们概述了如何使用免疫信息学工具来识别免疫显性表位的方法和工作流程,以志贺氏菌作为模型生物。使用此工作流程从 S. flexneri 2a 获得的免疫显性表位,通过体内模型进行了验证,表明了所概述的工作流程的稳健性。