Laboratory of Protein Biochemistry, Institute of Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany.
Division of Infection Pathogenesis, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
Methods Mol Biol. 2023;2673:89-109. doi: 10.1007/978-1-0716-3239-0_6.
Antigen complexity represents a major challenge for scoring CD4+ T cell immunogenicity, a key hallmark of immunity and with great potential to improve vaccine development. In this chapter, we provide a comprehensive picture of a pipeline that can be applied to virtually any complex antigen to overcome different limitations. Antigens are characterized by Mass Spectrometry to determine the available protein sources and their abundances. A reconstituted in vitro antigen processing system is applied along with bioinformatics tools to prioritize the list of candidates. Finally, the immunogenicity of candidate peptides is validated ex vivo using PBMCs from HLA-typed individuals. This protocol compiles the essential information for executing the whole pipeline while focusing on the candidate epitope prioritizing scheme.
抗原复杂性是评估 CD4+ T 细胞免疫原性的主要挑战，这是免疫的一个关键标志，具有极大的潜力来改进疫苗的开发。在这一章中，我们提供了一个可以应用于几乎任何复杂抗原的综合方案，以克服不同的限制。通过质谱分析来确定可用的蛋白质来源及其丰度，对抗原进行特征描述。应用重建的体外抗原处理系统和生物信息学工具对候选物进行优先级排序。最后，使用 HLA 分型个体的 PBMC 进行候选肽的免疫原性的体外验证。本方案编译了执行整个方案的必要信息，同时重点介绍了候选表位优先级排序方案。
