The adaptive immune system in vertebrates has evolved to recognize non-self-antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared six metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR β-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

中文翻译：

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TCRMatch：根据与先前表征的受体的序列相似性预测T细胞受体特异性

脊椎动物中的适应性免疫系统已经进化为识别非自身抗原，例如由传染原和突变的癌细胞表达的蛋白质。T细胞通过表达抗原特异性受体的多样性而在抗原识别中发挥重要作用，这些抗原特异性受体结合表位以启动靶向免疫反应。高通量测序的最新进展使得能够常规生成T细胞受体（TCR）库数据。在这些数据中鉴定不同TCR靶向的特定表位将是有价值的。为此，我们利用了自2004年以来在免疫表位数据库（IEDB）中指定的已知表位特异性的TCR不断增加的优势。我们比较了六个序列相似性指标，以确定它们预测两个TCR是否相同的能力。表位特异性。我们发现，全面的k-mer匹配方法产生了最佳结果，我们已将其实施到TCRMatch中，TCRMatch是一种开放可访问的工具（http://tools.iedb.org/tcrmatch/），它将TCRβ-链CDR3序列作为输入，在IEDB中标识具有匹配项的TCR，并报告每个匹配项的特异性。我们预计，该工具将提供对受体库和单细胞测序实验中捕获的T细胞反应的新见解，并将促进监测和治疗传染性，变态性和自身免疫性疾病以及癌症的新策略的开发。在IEDB中标识具有匹配项的TCR，并报告每个匹配项的特异性。我们预计，该工具将提供对受体库和单细胞测序实验中捕获的T细胞反应的新见解，并将促进监测和治疗传染性，变态性和自身免疫性疾病以及癌症的新策略的开发。在IEDB中标识具有匹配项的TCR，并报告每个匹配项的特异性。我们预计，该工具将提供对受体库和单细胞测序实验中捕获的T细胞反应的新见解，并将促进监测和治疗传染性，变态性和自身免疫性疾病以及癌症的新策略的开发。