Detection of Enriched T Cell Epitope Specificity in Full T Cell Receptor Sequence Repertoires
Detection of Enriched T Cell Epitope Specificity in Full T Cell Receptor Sequence Repertoires
复制标题
DOI：
10.3389/fimmu.2019.02820
复制
发表时间：
2019-11-29
影响因子：
7.3
通讯作者：
Meysman, Pieter
中科院分区：
文献类型：
--
作者：
Gielis, Sofie;Maris, Pieter;Meysman, Pieter
高通量T细胞受体（TCR）测序允许表征个体的TCR库并直接查询其免疫状态。然而，将这些测序的TCR与其抗原靶标偶联仍然是一项重要的任务。在本文中，我们提出了一种新的策略来注释完整的TCR序列库与它们的表位特异性。该策略基于机器学习算法来学习识别特定表位所共有的TCR模式。然后将这些结果与统计分析相结合，以评估库数据中每个表位的特异性表位反应性TCR序列的出现。以这种方式，我们可以直接研究完整TCR库靶向相关疫苗或病原体的特异性表位的能力。我们通过独立鉴定TCR库靶向的表位，在与疫苗监测和传染病诊断相关的三个独立数据集上证明了这种方法的可用性。所开发的方法可作为学术使用的网络工具在tcrex.biodatamining.be上免费获得。
High-throughput T cell receptor (TCR) sequencing allows the characterization of an individual's TCR repertoire and directly queries their immune state. However, it remains a non-trivial task to couple these sequenced TCRs to their antigenic targets. In this paper, we present a novel strategy to annotate full TCR sequence repertoires with their epitope specificities. The strategy is based on a machine learning algorithm to learn the TCR patterns common to the recognition of a specific epitope. These results are then combined with a statistical analysis to evaluate the occurrence of specific epitope-reactive TCR sequences per epitope in repertoire data. In this manner, we can directly study the capacity of full TCR repertoires to target specific epitopes of the relevant vaccines or pathogens. We demonstrate the usability of this approach on three independent datasets related to vaccine monitoring and infectious disease diagnostics by independently identifying the epitopes that are targeted by the TCR repertoire. The developed method is freely available as a web tool for academic use at tcrex.biodatamining.be.