Publication
Title
Detection of enriched T cell epitope specificity in full T cell receptor sequence repertoires
Author
Abstract
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.
Language
English
Source (journal)
Frontiers in immunology. - Place of publication unknown
Publication
Place of publication unknown : 2019
ISSN
1664-3224
DOI
10.3389/FIMMU.2019.02820
Volume/pages
10 (2019) , 13 p.
Article Reference
2820
ISI
000502779200001
Pubmed ID
31849987
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Unlocking the TCR repertoire for personalized cancer immunotherapies.
Mining multi-omics interaction data to reveal the determinants and evolution of host-pathogen disease susceptibility.
Intelligent quality control for mass spectrometry-based proteomics
T-cell receptor diversity and AT-rich DNA sensing by glial cells as key features in controlling neurological varicella-zoster virus infections.
An interdisciplinary study on the role of the HLA genes and T-cell diversity as risk factors for herpes zoster.
Predicting Immune responses by Modeling immunoSequencing data (PIMS).
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 03.12.2019
Last edited 02.10.2024
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