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T细胞受体组库分析的现状与未来展望

A current and future perspective on T cell receptor repertoire profiling.

作者信息

Shen Yiran, Voigt Alexandria, Leng Xuebing, Rodriguez Amy A, Nguyen Cuong Q

机构信息

Department of Infectious Diseases and Immunology, College of Veterinary Medicine, University of Florida, Gainesville, FL, United States.

Department of Microbiology and Immunology, Miller School of Medicine, University of Miami, Miami, FL, United States.

出版信息

Front Genet. 2023 Jun 20;14:1159109. doi: 10.3389/fgene.2023.1159109. eCollection 2023.

Abstract

T cell receptors (TCR) play a vital role in the immune system's ability to recognize and respond to foreign antigens, relying on the highly polymorphic rearrangement of TCR genes. The recognition of autologous peptides by adaptive immunity may lead to the development and progression of autoimmune diseases. Understanding the specific TCR involved in this process can provide insights into the autoimmune process. RNA-seq (RNA sequencing) is a valuable tool for studying TCR repertoires by providing a comprehensive and quantitative analysis of the RNA transcripts. With the development of RNA technology, transcriptomic data must provide valuable information to model and predict TCR and antigen interaction and, more importantly, identify or predict neoantigens. This review provides an overview of the application and development of bulk RNA-seq and single-cell (SC) RNA-seq to examine the TCR repertoires. Furthermore, discussed here are bioinformatic tools that can be applied to study the structural biology of peptide/TCR/MHC (major histocompatibility complex) and predict antigenic epitopes using advanced artificial intelligence tools.

摘要

T细胞受体(TCR)在免疫系统识别和应对外来抗原的能力中发挥着至关重要的作用,这依赖于TCR基因的高度多态性重排。适应性免疫对自身肽的识别可能导致自身免疫性疾病的发生和发展。了解参与这一过程的特定TCR可以为自身免疫过程提供见解。RNA测序(RNA-seq)通过对RNA转录本进行全面和定量分析,是研究TCR库的一种有价值的工具。随着RNA技术的发展,转录组数据必定能为模拟和预测TCR与抗原的相互作用提供有价值的信息,更重要的是,识别或预测新抗原。本综述概述了批量RNA-seq和单细胞(SC)RNA-seq在检查TCR库方面的应用和发展。此外,这里还讨论了可用于研究肽/TCR/主要组织相容性复合体(MHC)结构生物学并使用先进人工智能工具预测抗原表位的生物信息学工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a24f/10319011/bc23a32af356/fgene-14-1159109-g001.jpg

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