Literature DB >> 33679697

Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis.

Sabrina Pollastro1,2, Marie de Bourayne3, Giulia Balzaretti1,2, Aldo Jongejan4, Barbera D C van Schaik4, Ilse T G Niewold1, Antoine H C van Kampen4, Bernard Maillère3, Niek de Vries1,2.   

Abstract

High-throughput T-cell receptor repertoire sequencing constitutes a powerful tool to study T cell responses at the clonal level. However, it does not give information on the functional phenotype of the responding clones and lacks a statistical framework for quantitative evaluation. To overcome this, we combined datasets from different experiments, all starting from the same blood samples. We used a novel, sensitive, UMI-based protocol to perform repertoire analysis on experimental replicates. Applying established bioinformatic routines for transcriptomic expression analysis we explored the dynamics of antigen-induced clonal expansion after in vitro stimulation, identified antigen-responsive clones, and confirmed their activation status using the expression of activation markers upon antigen re-challenge. We demonstrate that the addition of IL-4 after antigen stimulation drives the expansion of T cell clones encoding unique receptor sequences. We show that our approach represents a scalable, high-throughput immunological tool, which can be used to identify and characterize antigen-responsive T cells at clonal level.
Copyright © 2021 Pollastro, de Bourayne, Balzaretti, Jongejan, van Schaik, Niewold, van Kampen, Maillère and de Vries.

Entities:  

Keywords:  T cell responses; T-cell receptor; adaptive immune receptor repertoire; bioinformatics; immunoinformatics; next generation sequencing

Year:  2021        PMID: 33679697      PMCID: PMC7932994          DOI: 10.3389/fimmu.2020.609624

Source DB:  PubMed          Journal:  Front Immunol        ISSN: 1664-3224            Impact factor:   7.561


  32 in total

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Authors:  Auda A Eltahla; Simone Rizzetto; Mehdi R Pirozyan; Brigid D Betz-Stablein; Vanessa Venturi; Katherine Kedzierska; Andrew R Lloyd; Rowena A Bull; Fabio Luciani
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2.  T cell immunity. Functional heterogeneity of human memory CD4⁺ T cell clones primed by pathogens or vaccines.

Authors:  Simone Becattini; Daniela Latorre; Federico Mele; Mathilde Foglierini; Corinne De Gregorio; Antonino Cassotta; Blanca Fernandez; Sander Kelderman; Ton N Schumacher; Davide Corti; Antonio Lanzavecchia; Federica Sallusto
Journal:  Science       Date:  2014-12-04       Impact factor: 47.728

3.  Immunology: The patterns of T-cell target recognition.

Authors:  Sai T Reddy
Journal:  Nature       Date:  2017-06-21       Impact factor: 49.962

4.  Human T-cell memory consists mainly of unexpanded clones.

Authors:  Paul L Klarenbeek; Paul P Tak; Barbera D C van Schaik; Aeilko H Zwinderman; Marja E Jakobs; Zhuoli Zhang; Antoine H C van Kampen; René A W van Lier; Frank Baas; Niek de Vries
Journal:  Immunol Lett       Date:  2010-07-16       Impact factor: 3.685

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Journal:  Sci Transl Med       Date:  2016-03-30       Impact factor: 17.956

6.  Human CD4+ T-cell repertoire of responses to influenza A virus hemagglutinin after recent natural infection.

Authors:  C M Gelder; K I Welsh; A Faith; J R Lamb; B A Askonas
Journal:  J Virol       Date:  1995-12       Impact factor: 5.103

7.  Bystander stimulation of activated CD4+ T cells of unrelated specificity following a booster vaccination with tetanus toxoid.

Authors:  Gianfranco Di Genova; Natalia Savelyeva; Amy Suchacki; Stephen M Thirdborough; Freda K Stevenson
Journal:  Eur J Immunol       Date:  2010-04       Impact factor: 5.532

8.  Single-cell TCRseq: paired recovery of entire T-cell alpha and beta chain transcripts in T-cell receptors from single-cell RNAseq.

Authors:  David Redmond; Asaf Poran; Olivier Elemento
Journal:  Genome Med       Date:  2016-07-27       Impact factor: 11.117

9.  Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

Authors:  David Zemmour; Rapolas Zilionis; Evgeny Kiner; Allon M Klein; Diane Mathis; Christophe Benoist
Journal:  Nat Immunol       Date:  2018-02-12       Impact factor: 25.606

10.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

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