Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis
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,...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2020.609624/full |
| _version_ | 1819053044191461376 |
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| author | Sabrina Pollastro Sabrina Pollastro Marie de Bourayne Giulia Balzaretti Giulia Balzaretti Aldo Jongejan Barbera D. C. van Schaik Ilse T. G. Niewold Antoine H. C. van Kampen Bernard Maillère Niek de Vries Niek de Vries |
| author_facet | Sabrina Pollastro Sabrina Pollastro Marie de Bourayne Giulia Balzaretti Giulia Balzaretti Aldo Jongejan Barbera D. C. van Schaik Ilse T. G. Niewold Antoine H. C. van Kampen Bernard Maillère Niek de Vries Niek de Vries |
| author_sort | Sabrina Pollastro |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-21T12:29:28Z |
| format | Article |
| id | doaj.art-a544f06d19f944f1a73b442aee6b2615 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-12-21T12:29:28Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-a544f06d19f944f1a73b442aee6b26152022-12-21T19:04:05ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-02-011110.3389/fimmu.2020.609624609624Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression AnalysisSabrina Pollastro0Sabrina Pollastro1Marie de Bourayne2Giulia Balzaretti3Giulia Balzaretti4Aldo Jongejan5Barbera D. C. van Schaik6Ilse T. G. Niewold7Antoine H. C. van Kampen8Bernard Maillère9Niek de Vries10Niek de Vries11Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology and Immunology Centre (ARC), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Experimental Immunology, Amsterdam Infection & Immunity Institute (AIII), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsUniversité Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé, SIMoS, Gif-sur-Yvette, FranceDepartment of Clinical Immunology & Rheumatology, Amsterdam Rheumatology and Immunology Centre (ARC), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Experimental Immunology, Amsterdam Infection & Immunity Institute (AIII), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam Infection & Immunity Institute (AIII), Amsterdam Public Health Research Institute, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam Infection & Immunity Institute (AIII), Amsterdam Public Health Research Institute, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Clinical Immunology & Rheumatology, Amsterdam Rheumatology and Immunology Centre (ARC), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam Infection & Immunity Institute (AIII), Amsterdam Public Health Research Institute, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsUniversité Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé, SIMoS, Gif-sur-Yvette, FranceDepartment of Clinical Immunology & Rheumatology, Amsterdam Rheumatology and Immunology Centre (ARC), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsDepartment of Experimental Immunology, Amsterdam Infection & Immunity Institute (AIII), Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, NetherlandsHigh-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.https://www.frontiersin.org/articles/10.3389/fimmu.2020.609624/fullT-cell receptoradaptive immune receptor repertoireT cell responsesnext generation sequencingbioinformaticsimmunoinformatics |
| spellingShingle | Sabrina Pollastro Sabrina Pollastro Marie de Bourayne Giulia Balzaretti Giulia Balzaretti Aldo Jongejan Barbera D. C. van Schaik Ilse T. G. Niewold Antoine H. C. van Kampen Bernard Maillère Niek de Vries Niek de Vries Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis Frontiers in Immunology T-cell receptor adaptive immune receptor repertoire T cell responses next generation sequencing bioinformatics immunoinformatics |
| title | Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis |
| title_full | Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis |
| title_fullStr | Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis |
| title_full_unstemmed | Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis |
| title_short | Characterization and Monitoring of Antigen-Responsive T Cell Clones Using T Cell Receptor Gene Expression Analysis |
| title_sort | characterization and monitoring of antigen responsive t cell clones using t cell receptor gene expression analysis |
| topic | T-cell receptor adaptive immune receptor repertoire T cell responses next generation sequencing bioinformatics immunoinformatics |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2020.609624/full |
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