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使用tcrdist3发现生物标志物的TCR元克隆型:鉴定公共的、HLA限制的SARS-CoV-2相关TCR特征。

TCR meta-clonotypes for biomarker discovery with tcrdist3: identification of public, HLA-restricted SARS-CoV-2 associated TCR features.

作者信息

Mayer-Blackwell Koshlan, Schattgen Stefan, Cohen-Lavi Liel, Crawford Jeremy Chase, Souquette Aisha, Gaevert Jessica A, Hertz Tomer, Thomas Paul G, Bradley Philip, Fiore-Gartland Andrew

机构信息

Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA.

Immunology Department, St. Jude Children's Research Hospital, Memphis, USA.

出版信息

bioRxiv. 2021 Mar 19:2020.12.24.424260. doi: 10.1101/2020.12.24.424260.

Abstract

As the mechanistic basis of adaptive cellular antigen recognition, T cell receptors (TCRs) encode clinically valuable information that reflects prior antigen exposure and potential future response. However, despite advances in deep repertoire sequencing, enormous TCR diversity complicates the use of TCR clonotypes as clinical biomarkers. We propose a new framework that leverages antigen-enriched repertoires to form meta-clonotypes - groups of biochemically similar TCRs - that can be used to robustly identify and quantify functionally similar TCRs in bulk repertoires. We apply the framework to TCR data from COVID-19 patients, generating 1831 public TCR meta-clonotypes from the 17 SARS-CoV-2 antigen-enriched repertoires with the strongest evidence of HLA-restriction. Applied to independent cohorts, meta-clonotypes targeting these specific epitopes were more frequently detected in bulk repertoires compared to exact amino acid matches, and 59.7% (1093/1831) were more abundant among COVID-19 patients that expressed the putative restricting HLA allele (FDR < 0.01), demonstrating the potential utility of meta-clonotypes as antigen-specific features for biomarker development. To enable further applications, we developed an open-source software package, , that implements this framework and facilitates flexible workflows for distance-based TCR repertoire analysis.

摘要

作为适应性细胞抗原识别的机制基础,T细胞受体(TCR)编码反映先前抗原暴露和潜在未来反应的具有临床价值的信息。然而,尽管在深度库测序方面取得了进展,但巨大的TCR多样性使TCR克隆型作为临床生物标志物的应用变得复杂。我们提出了一个新框架,该框架利用富含抗原的库来形成元克隆型——生化相似的TCR组——可用于在大量库中稳健地识别和量化功能相似的TCR。我们将该框架应用于COVID-19患者的TCR数据,从17个具有最强HLA限制证据的SARS-CoV-2抗原富集库中生成了1831个公共TCR元克隆型。应用于独立队列时,与精确的氨基酸匹配相比,靶向这些特定表位的元克隆型在大量库中更频繁地被检测到,并且在表达推定限制HLA等位基因的COVID-19患者中,59.7%(1093/1831)更为丰富(FDR<0.01),这证明了元克隆型作为生物标志物开发的抗原特异性特征的潜在效用。为了实现进一步的应用,我们开发了一个开源软件包, ,它实现了这个框架,并促进了基于距离的TCR库分析的灵活工作流程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbfd/7992027/891667834dfd/nihpp-2020.12.24.424260-f0001.jpg

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