33 results on '"Gerritsen, Bram"'
Search Results
2. Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses
- Author
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Hagan, Thomas, Gerritsen, Bram, Tomalin, Lewis E., Fourati, Slim, Mulè, Matthew P., Chawla, Daniel G., Rychkov, Dmitri, Henrich, Evan, Miller, Helen E. R., Diray-Arce, Joann, Dunn, Patrick, Lee, Audrey, Levy, Ofer, Gottardo, Raphael, Sarwal, Minne M., Tsang, John S., Suárez-Fariñas, Mayte, Sékaly, Rafick-Pierre, Kleinstein, Steven H., and Pulendran, Bali
- Published
- 2022
- Full Text
- View/download PDF
3. Pan-vaccine analysis reveals innate immune endotypes predictive of antibody responses to vaccination
- Author
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Fourati, Slim, Tomalin, Lewis E., Mulè, Matthew P., Chawla, Daniel G., Gerritsen, Bram, Rychkov, Dmitry, Henrich, Evan, Miller, Helen E. R., Hagan, Thomas, Diray-Arce, Joann, Dunn, Patrick, Levy, Ofer, Gottardo, Raphael, Sarwal, Minnie M., Tsang, John S., Suárez-Fariñas, Mayte, Pulendran, Bali, Kleinstein, Steven H., and Sékaly, Rafick-Pierre
- Published
- 2022
- Full Text
- View/download PDF
4. The Immune Signatures data resource, a compendium of systems vaccinology datasets
- Author
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Diray-Arce, Joann, Miller, Helen E. R., Henrich, Evan, Gerritsen, Bram, Mulè, Matthew P., Fourati, Slim, Gygi, Jeremy, Hagan, Thomas, Tomalin, Lewis, Rychkov, Dmitry, Kazmin, Dmitri, Chawla, Daniel G., Meng, Hailong, Dunn, Patrick, Campbell, John, Sarwal, Minnie, Tsang, John S., Levy, Ofer, Pulendran, Bali, Sekaly, Rafick, Floratos, Aris, Gottardo, Raphael, Kleinstein, Steven H., and Suárez-Fariñas, Mayte
- Published
- 2022
- Full Text
- View/download PDF
5. Characterization of the ferret TRB locus guided by V, D, J, and C gene expression analysis
- Author
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Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C. G. N., van IJcken, Wilfred F. J., de Boer, Rob J., and Andeweg, Arno C.
- Published
- 2020
- Full Text
- View/download PDF
6. The memory of a killer T cell: models of CD8+ T cell differentiation
- Author
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Gerritsen, Bram and Pandit, Aridaman
- Published
- 2016
- Full Text
- View/download PDF
7. The naive t-cell receptor repertoire has an extremely broad distribution of clone sizes
- Author
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de Greef, Peter C., Oakes, Theres, Gerritsen, Bram, Ismail, Mazlina, Heather, James M., Hermsen, Rutger, Chain, Benjamin, de Boer, Rob J., de Greef, Peter C., Oakes, Theres, Gerritsen, Bram, Ismail, Mazlina, Heather, James M., Hermsen, Rutger, Chain, Benjamin, and de Boer, Rob J.
- Abstract
The clone size distribution of the human naive T-cell receptor (TCR) repertoire is an important determinant of adaptive immunity. We estimated the abundance of TCR sequences in samples of naive T cells from blood using an accurate quantitative sequencing protocol. We observe most TCR sequences only once, consistent with the enormous diversity of the repertoire. However, a substantial number of sequences were observed multiple times. We detect abundant TCR sequences even after exclusion of methodological confounders such as sort contamination, and multiple mRNA sampling from the same cell. By combining experimental data with predictions from models we describe two mechanisms contributing to TCR sequence abundance. TCRa abundant sequences can be primarily attributed to many identical recombination events in different cells, while abundant TCRb sequences are primarily derived from large clones, which make up a small percentage of the naive repertoire, and could be established early in the development of the T-cell repertoire.
- Published
- 2020
8. The naive t-cell receptor repertoire has an extremely broad distribution of clone sizes
- Author
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Sub Theoretical Biology, Theoretical Biology and Bioinformatics, de Greef, Peter C., Oakes, Theres, Gerritsen, Bram, Ismail, Mazlina, Heather, James M., Hermsen, Rutger, Chain, Benjamin, de Boer, Rob J., Sub Theoretical Biology, Theoretical Biology and Bioinformatics, de Greef, Peter C., Oakes, Theres, Gerritsen, Bram, Ismail, Mazlina, Heather, James M., Hermsen, Rutger, Chain, Benjamin, and de Boer, Rob J.
- Published
- 2020
9. Characterization of the ferret TRB locus guided by V, D, J, and C gene expression analysis
- Author
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Translationele immunologie, Infection & Immunity, Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C G N, van IJcken, Wilfred F J, de Boer, Rob J, Andeweg, Arno C, Translationele immunologie, Infection & Immunity, Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C G N, van IJcken, Wilfred F J, de Boer, Rob J, and Andeweg, Arno C
- Published
- 2020
10. The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes
- Author
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de Greef, Peter C, primary, Oakes, Theres, additional, Gerritsen, Bram, additional, Ismail, Mazlina, additional, Heather, James M, additional, Hermsen, Rutger, additional, Chain, Benjamin, additional, and de Boer, Rob J, additional
- Published
- 2020
- Full Text
- View/download PDF
11. Single cell immune profiling of dengue virus patients reveals intact immune responses to Zika virus with enrichment of innate immune signatures
- Author
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Zhao, Yujiao, primary, Amodio, Matthew, additional, Vander Wyk, Brent, additional, Gerritsen, Bram, additional, Kumar, Mahesh M., additional, van Dijk, David, additional, Moon, Kevin, additional, Wang, Xiaomei, additional, Malawista, Anna, additional, Richards, Monique M., additional, Cahill, Megan E., additional, Desai, Anita, additional, Sivadasan, Jayasree, additional, Venkataswamy, Manjunatha M., additional, Ravi, Vasanthapuram, additional, Fikrig, Erol, additional, Kumar, Priti, additional, Kleinstein, Steven H., additional, Krishnaswamy, Smita, additional, and Montgomery, Ruth R., additional
- Published
- 2020
- Full Text
- View/download PDF
12. Author response: The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes
- Author
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de Greef, Peter C, primary, Oakes, Theres, additional, Gerritsen, Bram, additional, Ismail, Mazlina, additional, Heather, James M, additional, Hermsen, Rutger, additional, Chain, Benjamin, additional, and de Boer, Rob J, additional
- Published
- 2020
- Full Text
- View/download PDF
13. The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes
- Author
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de Greef, Peter C., Oakes, Theres, Gerritsen, Bram, Ismail, Mazlina, Heather, James M., Hermsen, Rutger, Chain, Benjamin, de Boer, Rob J., Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Sub Theoretical Biology, and Theoretical Biology and Bioinformatics
- Subjects
0301 basic medicine ,Receptors, Antigen, T-Cell, alpha-beta ,T-Lymphocytes ,Clone (cell biology) ,Adaptive Immunity ,Biochemistry ,0302 clinical medicine ,Immunology and Inflammation ,Receptor repertoire ,T-Lymphocyte Subsets ,Biology (General) ,Receptor ,General Neuroscience ,Repertoire ,High-Throughput Nucleotide Sequencing ,General Medicine ,bioinformatics ,Acquired immune system ,Organ Specificity ,Medicine ,Recombination ,Neutral model ,Algorithms ,Research Article ,Computational and Systems Biology ,Human ,Naive T cell ,QH301-705.5 ,Systems biology ,Science ,Neuroscience(all) ,Sequencing data ,Receptors, Antigen, T-Cell ,Computational biology ,Biology ,Models, Biological ,General Biochemistry, Genetics and Molecular Biology ,Clonal Evolution ,modelling ,03 medical and health sciences ,Immunology and Microbiology(all) ,Humans ,Antigens ,repertoire sequencing ,General Immunology and Microbiology ,Biochemistry, Genetics and Molecular Biology(all) ,T-cell receptor ,Computational Biology ,V(D)J Recombination ,030104 developmental biology ,Evolutionary biology ,Immunologic Memory ,030217 neurology & neurosurgery ,Genetics and Molecular Biology(all) - Abstract
The human naive T-cell receptor (TCR) repertoire is extremely diverse and accurately estimating its distribution is challenging. We address this challenge by combining a quantitative sequencing protocol of TCRA and TCRB sequences with computational modelling. We observed the vast majority of TCR chains only once in our samples, confirming the enormous diversity of the naive repertoire. However, a substantial number of sequences were observed multiple times within samples, and we demonstrated that this is due to expression by many cells in the naive pool. We reason that α and β chains are frequently observed due to a combination of selective processes and summation over multiple clones expressing these chains. We test the contribution of both mechanisms by predicting samples from phenomenological and mechanistically modelled repertoire distributions. By comparing these with sequencing data, we show that frequently observed chains are likely to be derived from multiple clones. Still, a neutral model of T-cell homeostasis cannot account for the observed distributions. We conclude that the data are only compatible with distributions of many small clones in combination with a sufficient number of very large naive T-cell clones, the latter most likely as a result of peripheral selection.
- Published
- 2019
14. Characterization of the ferret TRB locus guided by V, D, J, and C gene expression analysis
- Author
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Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C G N, van IJcken, Wilfred F J, de Boer, Rob J, Andeweg, Arno C, Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C G N, van IJcken, Wilfred F J, de Boer, Rob J, and Andeweg, Arno C
- Abstract
The domestic ferret, Mustela putorius furo, is an important mammalian animal model to study human respiratory infection. However, insufficient genomic annotation hampers detailed studies of ferret T cell responses. In this study, we analyzed the published T cell receptor beta (TRB) locus and performed high-throughput sequencing (HTS) of peripheral blood of four healthy adult ferrets to identify expressed V, D, J, and C genes. The HTS data is used as a guide to manually curate the expressed V, D, J, and C genes. The ferret locus appears to be most similar to that of the dog. Like other mammalian TRB loci, the ferret TRB locus contains a library of variable genes located upstream of two D-J-C gene clusters, followed by a (in the ferret non-functional) V gene with an inverted transcriptional orientation. All TRB genes (expressed or not) reported here have been approved by the IMGT/WHO-IUIS nomenclature committee.
- Published
- 2019
15. Characterization of the ferret TRB locus guided by V, D, J, and C gene expression analysis
- Author
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Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C G N, van IJcken, Wilfred F J, de Boer, Rob J, Andeweg, Arno C, Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Gerritsen, Bram, Pandit, Aridaman, Zaaraoui-Boutahar, Fatiha, van den Hout, Mirjam C G N, van IJcken, Wilfred F J, de Boer, Rob J, and Andeweg, Arno C
- Published
- 2019
16. Characterization of the ferret TRB locus guided by V, D, J, and C gene expression analysis
- Author
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Gerritsen, Bram, primary, Pandit, Aridaman, additional, Zaaraoui-Boutahar, Fatiha, additional, van den Hout, Mirjam C. G. N., additional, van IJcken, Wilfred F. J., additional, de Boer, Rob J., additional, and Andeweg, Arno C., additional
- Published
- 2019
- Full Text
- View/download PDF
17. Decision letter: Human T cell receptor occurrence patterns encode immune history, genetic background, and receptor specificity
- Author
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Elhanati, Yuval, additional and Gerritsen, Bram, additional
- Published
- 2018
- Full Text
- View/download PDF
18. RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data
- Author
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Gerritsen, Bram, Pandit, Aridaman, Andeweg, Arno C, de Boer, Rob J, Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Virology, Sub Theoretical Biology, and Theoretical Biology and Bioinformatics
- Subjects
0301 basic medicine ,Statistics and Probability ,Original Paper ,T cell ,T-Lymphocytes ,Real-time computing ,T-cell receptor ,Receptors, Antigen, T-Cell ,High-Throughput Nucleotide Sequencing ,Statistical model ,Computational biology ,Biology ,Biochemistry ,Polymerase Chain Reaction ,DNA sequencing ,Computer Science Applications ,03 medical and health sciences ,Computational Mathematics ,030104 developmental biology ,medicine.anatomical_structure ,Computational Theory and Mathematics ,medicine ,Humans ,Molecular Biology ,Sequence Analysis - Abstract
Motivation: High Throughput Sequencing (HTS) has enabled researchers to probe the human T cell receptor (TCR) repertoire, which consists of many rare sequences. Distinguishing between true but rare TCR sequences and variants generated by polymerase chain reaction (PCR) and sequencing errors remains a formidable challenge. The conventional approach to handle errors is to remove low quality reads, and/or rare TCR sequences. Such filtering discards a large number of true and often rare TCR sequences. However, accurate identification and quantification of rare TCR sequences is essential for repertoire diversity estimation. Results: We devised a pipeline, called Recover TCR (RTCR), that accurately recovers TCR sequences, including rare TCR sequences, from HTS data (including barcoded data) even at low coverage. RTCR employs a data-driven statistical model to rectify PCR and sequencing errors in an adaptive manner. Using simulations, we demonstrate that RTCR can easily adapt to the error profiles of different types of sequencers and exhibits consistently high recall and high precision even at low coverages where other pipelines perform poorly. Using published real data, we show that RTCR accurately resolves sequencing errors and outperforms all other pipelines. Availability and Implementation: The RTCR pipeline is implemented in Python (v2.7) and C and is freely available at http://uubram.github.io/RTCR/along with documentation and examples of typical usage. Contact: b.gerritsen@uu.nl
- Published
- 2015
19. CD8+ TCR Bias and Immunodominance in HIV-1 Infection
- Author
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Kløverpris, Henrik N, McGregor, Reuben, McLaren, James E, Ladell, Kristin, Harndahl, Mikkel, Stryhn, Anette, Carlson, Jonathan M, Koofhethile, Catherine, Gerritsen, Bram, Kesmir, C., Chen, Fabian, Riddell, Lynn, Luzzi, Graz, Leslie, Alasdair, Walker, Bruce D, Ndung'u, Thumbi, Buus, Søren, Price, David A, Goulder, Philip J, Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Sub Theoretical Biology, and Theoretical Biology and Bioinformatics
- Subjects
Adult ,DNA, Complementary ,T cell ,Immunology ,Antibody Affinity ,Receptors, Antigen, T-Cell ,Epitopes, T-Lymphocyte ,HIV Infections ,Immunodominance ,Human leukocyte antigen ,Biology ,CD8-Positive T-Lymphocytes ,gag Gene Products, Human Immunodeficiency Virus ,Epitope ,Epitopes ,Antigen ,Complementary ,Receptors ,Taverne ,HLA-B Antigens ,medicine ,Immunology and Allergy ,Humans ,Amino Acid Sequence ,gag Gene Products ,Genetics ,Base Sequence ,Immunodominant Epitopes ,T-cell receptor ,DNA ,Sequence Analysis, DNA ,Viral Load ,T-Cell ,medicine.anatomical_structure ,T-Lymphocyte ,HIV-1 ,Female ,Sequence Analysis ,Human Immunodeficiency Virus ,CD8 ,Epitope Mapping - Abstract
Immunodominance describes a phenomenon whereby the immune system consistently targets only a fraction of the available Ag pool derived from a given pathogen. In the case of CD8+ T cells, these constrained epitope-targeting patterns are linked to HLA class I expression and determine disease progression. Despite the biological importance of these predetermined response hierarchies, little is known about the factors that control immunodominance in vivo. In this study, we conducted an extensive analysis of CD8+ T cell responses restricted by a single HLA class I molecule to evaluate the mechanisms that contribute to epitope-targeting frequency and antiviral efficacy in HIV-1 infection. A clear immunodominance hierarchy was observed across 20 epitopes restricted by HLA-B*42:01, which is highly prevalent in populations of African origin. Moreover, in line with previous studies, Gag-specific responses and targeting breadth were associated with lower viral load set-points. However, peptide–HLA-B*42:01 binding affinity and stability were not significantly linked with targeting frequencies. Instead, immunodominance correlated with epitope-specific usage of public TCRs, defined as amino acid residue–identical TRB sequences that occur in multiple individuals. Collectively, these results provide important insights into a potential link between shared TCR recruitment, immunodominance, and antiviral efficacy in a major human infection.
- Published
- 2015
20. CD8+ T-cell receptor bias and immundominance in HIV-1 infection
- Author
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Kløverpris, Henrik N., McGregor, Reuben, McLaren, James E., Ladell, Kristin, Harndahl, Mikkel, Stryhn, Anette, Carlson, Jonathan, Koofhethile, Catherine, Gerritsen, Bram, Kesmir, Can, Chen, Fabian, Riddell, Lynn, Luzzi, Graz, Leslie, Alasdair, Walker, Bruce D., Ndung'u, Thumbi, Buus, Søren, Price, David A., and Goulder, Philip J.
- Subjects
Adult ,DNA, Complementary ,Base Sequence ,Immunodominant Epitopes ,Antibody Affinity ,Receptors, Antigen, T-Cell ,Epitopes, T-Lymphocyte ,HIV Infections ,Sequence Analysis, DNA ,CD8-Positive T-Lymphocytes ,Viral Load ,gag Gene Products, Human Immunodeficiency Virus ,Article ,HLA-B Antigens ,HIV-1 ,Humans ,Female ,Amino Acid Sequence ,Epitope Mapping - Abstract
Immunodominance describes a phenomenon whereby the immune system consistently targets only a fraction of the available antigen pool derived from a given pathogen. In the case of CD8+ T-cells, these constrained epitope targeting patterns are linked to human leukocyte antigen (HLA) class-I expression and determine disease progression. Despite the biological importance of these predetermined response hierarchies, however, little is known about the factors that control immunodominance in vivo. In this study, we conducted an extensive analysis of CD8+ T-cell responses restricted by a single HLA class-I molecule to evaluate the mechanisms that contribute to epitope targeting frequency and antiviral efficacy in HIV-1 infection. A clear immunodominance hierarchy was observed across 20 different epitopes restricted by HLA-B*42:01, which is highly prevalent in populations of African origin. Moreover, in line with previous studies, Gag-specific responses and targeting breadth were associated with lower viral load set-points. However, peptide-HLA-B*42:01 binding affinity and stability were not significantly linked with targeting frequencies. Instead, immunodominance correlated with epitope-specific usage of public TCRs, defined as amino acid residue-identical TRB sequences that occur in multiple individuals. Collectively, these results provide the first insights into a potential link between shared TCR recruitment, immunodominance and antiviral efficacy in a major human infection.
- Published
- 2015
21. RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data
- Author
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Gerritsen, Bram, Pandit, Aridaman, Andeweg, Arno C, de Boer, Rob J, Gerritsen, Bram, Pandit, Aridaman, Andeweg, Arno C, and de Boer, Rob J
- Abstract
MOTIVATION: High Throughput Sequencing (HTS) has enabled researchers to probe the human T cell receptor (TCR) repertoire, which consists of many rare sequences. Distinguishing between true but rare TCR sequences and variants generated by polymerase chain reaction (PCR) and sequencing errors remains a formidable challenge. The conventional approach to handle errors is to remove low quality reads, and/or rare TCR sequences. Such filtering discards a large number of true and often rare TCR sequences. However, accurate identification and quantification of rare TCR sequences is essential for repertoire diversity estimation.RESULTS: We devised a pipeline, called Recover TCR (RTCR), that accurately recovers TCR sequences, including rare TCR sequences, from HTS data (including barcoded data) even at low coverage. RTCR employs a data-driven statistical model to rectify PCR and sequencing errors in an adaptive manner. Using simulations, we demonstrate that RTCR can easily adapt to the error profiles of different types of sequencers and exhibits consistently high recall and high precision even at low coverages where other pipelines perform poorly. Using published real data, we show that RTCR accurately resolves sequencing errors and outperforms all other pipelines.AVAILABILITY AND IMPLEMENTATION: The RTCR pipeline is implemented in Python (v2.7) and C and is freely available at http://uubram.github.io/RTCR/along with documentation and examples of typical usage.CONTACT: b.gerritsen@uu.nl.
- Published
- 2016
22. RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data
- Author
-
Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Gerritsen, Bram, Pandit, Aridaman, Andeweg, Arno C, de Boer, Rob J, Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Gerritsen, Bram, Pandit, Aridaman, Andeweg, Arno C, and de Boer, Rob J
- Published
- 2016
23. MR1-restricted MAIT cells display ligand discrimination and pathogen selectivity through distinct T cell receptor usage
- Author
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Gold, Marielle C, McLaren, James E, Reistetter, Joseph A, Smyk-Pearson, Sue, Ladell, Kristin, Swarbrick, Gwendolyn M, Yu, Yik Y L, Hansen, Ted H, Lund, Ole, Nielsen, Morten, Gerritsen, Bram, Kesmir, Can, Miles, John J, Lewinsohn, Deborah A, Price, David A, Lewinsohn, David M, Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Sub Theoretical Biology, and Theoretical Biology and Bioinformatics
- Subjects
Receptors, Antigen, T-Cell, alpha-beta ,T-Lymphocytes ,Sequence Homology ,Ciencias de la Salud ,Complementarity determining region ,Ligands ,Epitope ,0302 clinical medicine ,Receptors ,Immunology and Allergy ,Gene Rearrangement ,alpha-beta ,Genetics ,0303 health sciences ,biology ,B-Lymphocyte ,Otras Ciencias de la Salud ,Amino Acid ,medicine.anatomical_structure ,Differentiation ,Antigen ,Vitamin B Complex ,purl.org/becyt/ford/3 [https] ,MAIT ,CIENCIAS MÉDICAS Y DE LA SALUD ,T cell ,Molecular Sequence Data ,Immunology ,Receptors, Antigen, T-Cell ,Mucosal associated invariant T cell ,Major histocompatibility complex ,Article ,Cell Line ,03 medical and health sciences ,purl.org/becyt/ford/3.3 [https] ,medicine ,Humans ,Amino Acid Sequence ,Antigens ,030304 developmental biology ,Mucous Membrane ,Sequence Homology, Amino Acid ,Bacteria ,Histocompatibility Antigens Class I ,T-cell receptor ,Histocompatibility Antigens Class II ,Gene rearrangement ,T-Cell ,R1 ,Complementarity Determining Regions ,Clone Cells ,Antigens, Differentiation, B-Lymphocyte ,biology.protein ,alpha-Chain T-Cell Antigen Receptor ,T cell receptor ,Gene Rearrangement, alpha-Chain T-Cell Antigen Receptor ,030215 immunology - Abstract
MAIT cells can discriminate between pathogen-derived ligands in a clonotype-dependent manner, and the TCR repertoire is distinct within individuals, indicating that the MAIT cell repertoire is shaped by prior microbial exposure., Mucosal-associated invariant T (MAIT) cells express a semi-invariant T cell receptor (TCR) that detects microbial metabolites presented by the nonpolymorphic major histocompatibility complex (MHC)–like molecule MR1. The highly conserved nature of MR1 in conjunction with biased MAIT TCRα chain usage is widely thought to indicate limited ligand presentation and discrimination within a pattern-like recognition system. Here, we evaluated the TCR repertoire of MAIT cells responsive to three classes of microbes. Substantial diversity and heterogeneity were apparent across the functional MAIT cell repertoire as a whole, especially for TCRβ chain sequences. Moreover, different pathogen-specific responses were characterized by distinct TCR usage, both between and within individuals, suggesting that MAIT cell adaptation was a direct consequence of exposure to various exogenous MR1-restricted epitopes. In line with this interpretation, MAIT cell clones with distinct TCRs responded differentially to a riboflavin metabolite. These results suggest that MAIT cells can discriminate between pathogen-derived ligands in a clonotype-dependent manner, providing a basis for adaptive memory via recruitment of specific repertoires shaped by microbial exposure.
- Published
- 2014
24. RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data
- Author
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Gerritsen, Bram, primary, Pandit, Aridaman, additional, Andeweg, Arno C., additional, and de Boer, Rob J., additional
- Published
- 2016
- Full Text
- View/download PDF
25. The memory of a killer T cell: models of CD8 + T cell differentiation
- Author
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Gerritsen, Bram, primary and Pandit, Aridaman, additional
- Published
- 2016
- Full Text
- View/download PDF
26. CD8+ TCR Bias and Immunodominance in HIV-1 Infection
- Author
-
Kloverpris, Henrik N., McGregor, Reuben, McLaren, James E., Ladell, Kristin, Harndahl, Mikkel, Buus, Anette Stryhn, Carlson, Jonathan M., Koofhethile, Catherine, Gerritsen, Bram, Kesmir, Can, Chen, Fabian, Riddell, Lynn, Luzzi, Graz, Leslie, Alasdair, Walker, Bruce D., Ndung'u, Thumbi, Buus, Soren, Price, David A., Goulder, Philip J., Kloverpris, Henrik N., McGregor, Reuben, McLaren, James E., Ladell, Kristin, Harndahl, Mikkel, Buus, Anette Stryhn, Carlson, Jonathan M., Koofhethile, Catherine, Gerritsen, Bram, Kesmir, Can, Chen, Fabian, Riddell, Lynn, Luzzi, Graz, Leslie, Alasdair, Walker, Bruce D., Ndung'u, Thumbi, Buus, Soren, Price, David A., and Goulder, Philip J.
- Published
- 2015
27. MR1-restricted MAIT cells display ligand discrimination and pathogen selectivity through distinct T cell receptor usage
- Author
-
Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Gold, Marielle C, McLaren, James E, Reistetter, Joseph A, Smyk-Pearson, Sue, Ladell, Kristin, Swarbrick, Gwendolyn M, Yu, Yik Y L, Hansen, Ted H, Lund, Ole, Nielsen, Morten, Gerritsen, Bram, Kesmir, Can, Miles, John J, Lewinsohn, Deborah A, Price, David A, Lewinsohn, David M, Sub Theoretical Biology, Theoretical Biology and Bioinformatics, Gold, Marielle C, McLaren, James E, Reistetter, Joseph A, Smyk-Pearson, Sue, Ladell, Kristin, Swarbrick, Gwendolyn M, Yu, Yik Y L, Hansen, Ted H, Lund, Ole, Nielsen, Morten, Gerritsen, Bram, Kesmir, Can, Miles, John J, Lewinsohn, Deborah A, Price, David A, and Lewinsohn, David M
- Published
- 2014
28. Parallel In Vivo and In Vitro Melanoma RNAi Dropout Screens Reveal Synthetic Lethality between Hypoxia and DNA Damage Response Inhibition
- Author
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Possik, Patricia A., primary, Müller, Judith, additional, Gerlach, Carmen, additional, Kenski, Juliana C.N., additional, Huang, Xinyao, additional, Shahrabi, Aida, additional, Krijgsman, Oscar, additional, Song, Ji-Ying, additional, Smit, Marjon A., additional, Gerritsen, Bram, additional, Lieftink, Cor, additional, Kemper, Kristel, additional, Michaut, Magali, additional, Beijersbergen, Roderick L., additional, Wessels, Lodewyk, additional, Schumacher, Ton N., additional, and Peeper, Daniel S., additional
- Published
- 2014
- Full Text
- View/download PDF
29. The memory of a killer T cell: models of CD8+ T cell differentiation.
- Author
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Gerritsen, Bram and Pandit, Aridaman
- Abstract
CD8+ T cells have an important role in protection against infections and reinfections of intra‐cellular pathogens like viruses. Naive CD8+ T cells circulating in blood or lymphoid tissues can get activated upon stimulation by cognate antigen. The activated T cells undergo rapid proliferation and can expand more than 104‐folds comprising largely of effector T cells. Upon antigen clearance, the CD8+ T‐cell population contracts due to apoptosis, leaving behind a small population of memory T cells. The timing and mechanisms underlying the differentiation of naive cells into effector cells and memory cells is not yet clear. In this article, we review the recent quantitative studies that support different hypotheses of CD8+ T‐cell differentiation. The March 2016 issue contains a Special Feature on Cutting‐edge single‐cell genomics and modelling in immunology. The recent advent of single‐cell genomics has offered unprecedented possibilities for hypothesis‐independent characterization of cellular heterogeneity and regulatory states. At the same time, the vast datasets produced by these techniques have highlighted the need for new bioinformatics tools to utilize the contained information to the fullest. In this Special Feature, both the experimental methods for producing such data as well as selected modelling approaches are reviewed, with focus on the applications on the study of the immune system. Immunology and Cell Biology thanks the coordinators of this Special Feature ‐ Tapio Lönnberg and Valentina Proserpio ‐ for their planning and input. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
30. CD8+ TCR Bias and Immunodominance in HIV-1 Infection.
- Author
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Kløverpris, Henrik N., McGregor, Reuben, McLaren, James E., Ladell, Kristin, Harndahl, Mikkel, Stryhn, Anette, Carlson, Jonathan M., Koofhethile, Catherine, Gerritsen, Bram, Keşmir, Can, Chen, Fabian, Riddell, Lynn, Luzzi, Graz, Leslie, Alasdair, Walker, Bruce D., Ndung'u, Thumbi, Buus, Spren, Price, David A., and Goulder, Philip J.
- Subjects
- *
HIV infections , *LENTIVIRUS diseases , *BACTERIAL antigens , *EPITOPES , *BACTERIA - Abstract
Immunodominance describes a phenomenon whereby the immune system consistently targets only a fraction of the available Ag pool derived from a given pathogen. In the case of CD8+ T cells, these constrained epitope-targeting patterns are linked to HLA class I expression and determine disease progression. Despite the biological importance of these predetermined response hierarchies, little is known about the factors that control immunodominance in vivo. In this study, we conducted an extensive analysis of CD8+ T cell responses restricted by a single HLA class I molecule to evaluate the mechanisms that contribute to epitopetargeting frequency and antiviral efficacy in HIV-1 infection. A clear immunodominance hierarchy was observed across 20 epitopes restricted by HLA-B*42:01, which is highly prevalent in populations of African origin. Moreover, in line with previous studies, Gag-specific responses and targeting breadth were associated with lower viral load set-points. However, peptide-HLA-11*42:01 binding affinity and stability were not significantly linked with targeting frequencies. Instead, immunodominance correlated with epitope-specific usage of public TCRs, defined as amino acid residue-identical TRB sequences that occur in multiple individuals. Collectively, these results provide important insights into a potential link between shared TCR recruitment, immunodominance, and antiviral efficacy in a major human infection. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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31. Blood integrin- and cytokine-producing T cells are associated with stage and genetic risk score in age-related macular degeneration.
- Author
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Rijken R, Pameijer EM, Gerritsen B, Hiddingh S, Stehouwer M, de Boer JH, Imhof SM, van Leeuwen R, and Kuiper JJ
- Abstract
Age-related macular degeneration (AMD) remains a leading cause of vision loss in the geriatric population. There are age-related changes in peripheral blood leukocyte composition, but their significance for AMD remains unclear. We aimed to determine changes in immune cell populations in the blood of AMD patients. A standardized 31-parameter flow cytometry analysis was conducted on peripheral blood mononuclear cells from 59 patients with early and advanced AMD and 39 controls without AMD, all older than 65 years. Fundus photography and optical coherence tomography were used to classify disease stages and a custom genotype array was used to compute an AMD genetic risk score based on 52 AMD disease risk variants (GRS-52). A generalized linear regression model corrected for age, sex, and smoking status revealed that AMD patients showed decreased frequencies of CD4
+ T helper cell population expressing Integrin Alpha E (CD103) (Padj = 0.019). We further noted that early AMD was characterized by increased interleukin-4 (IL-4)-producing CD4+ T helper cells (Padj = 0.013; <0.001), as well as IL-4-producing cytotoxic CD8+ T cells (Padj = 0.016; <0.001). Reclassification of samples based on the GRS-52 revealed that IL-17-producing T cells decreased incrementally across GRS-52 categories. In AMD, alterations in peripheral blood leukocyte populations are associated with genetic risk score and disease stage and include specifically IL-4 and IL-17A cytokine-producing and CD103 integrin-expressing T cell populations., Competing Interests: Declaration of competing interest All authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)- Published
- 2024
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- View/download PDF
32. CD8+ TCR Bias and Immunodominance in HIV-1 Infection.
- Author
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Kløverpris HN, McGregor R, McLaren JE, Ladell K, Harndahl M, Stryhn A, Carlson JM, Koofhethile C, Gerritsen B, Keşmir C, Chen F, Riddell L, Luzzi G, Leslie A, Walker BD, Ndung'u T, Buus S, Price DA, and Goulder PJ
- Subjects
- Adult, Amino Acid Sequence, Antibody Affinity immunology, Base Sequence, DNA, Complementary genetics, Epitope Mapping, Female, HIV Infections immunology, HLA-B Antigens immunology, Humans, Sequence Analysis, DNA, Viral Load, gag Gene Products, Human Immunodeficiency Virus immunology, CD8-Positive T-Lymphocytes immunology, Epitopes, T-Lymphocyte immunology, HIV-1 immunology, Immunodominant Epitopes immunology, Receptors, Antigen, T-Cell immunology
- Abstract
Immunodominance describes a phenomenon whereby the immune system consistently targets only a fraction of the available Ag pool derived from a given pathogen. In the case of CD8(+) T cells, these constrained epitope-targeting patterns are linked to HLA class I expression and determine disease progression. Despite the biological importance of these predetermined response hierarchies, little is known about the factors that control immunodominance in vivo. In this study, we conducted an extensive analysis of CD8(+) T cell responses restricted by a single HLA class I molecule to evaluate the mechanisms that contribute to epitope-targeting frequency and antiviral efficacy in HIV-1 infection. A clear immunodominance hierarchy was observed across 20 epitopes restricted by HLA-B*42:01, which is highly prevalent in populations of African origin. Moreover, in line with previous studies, Gag-specific responses and targeting breadth were associated with lower viral load set-points. However, peptide-HLA-B*42:01 binding affinity and stability were not significantly linked with targeting frequencies. Instead, immunodominance correlated with epitope-specific usage of public TCRs, defined as amino acid residue-identical TRB sequences that occur in multiple individuals. Collectively, these results provide important insights into a potential link between shared TCR recruitment, immunodominance, and antiviral efficacy in a major human infection., (Copyright © 2015 by The American Association of Immunologists, Inc.)
- Published
- 2015
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33. MR1-restricted MAIT cells display ligand discrimination and pathogen selectivity through distinct T cell receptor usage.
- Author
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Gold MC, McLaren JE, Reistetter JA, Smyk-Pearson S, Ladell K, Swarbrick GM, Yu YY, Hansen TH, Lund O, Nielsen M, Gerritsen B, Kesmir C, Miles JJ, Lewinsohn DA, Price DA, and Lewinsohn DM
- Subjects
- Amino Acid Sequence, Bacteria drug effects, Cell Line, Clone Cells, Complementarity Determining Regions chemistry, Gene Rearrangement, alpha-Chain T-Cell Antigen Receptor genetics, Humans, Ligands, Minor Histocompatibility Antigens, Molecular Sequence Data, Mucous Membrane drug effects, Receptors, Antigen, T-Cell, alpha-beta genetics, Sequence Homology, Amino Acid, T-Lymphocytes drug effects, Vitamin B Complex pharmacology, Antigens, Differentiation, B-Lymphocyte metabolism, Bacteria immunology, Histocompatibility Antigens Class I metabolism, Histocompatibility Antigens Class II metabolism, Mucous Membrane cytology, Mucous Membrane immunology, Receptors, Antigen, T-Cell metabolism, T-Lymphocytes metabolism
- Abstract
Mucosal-associated invariant T (MAIT) cells express a semi-invariant T cell receptor (TCR) that detects microbial metabolites presented by the nonpolymorphic major histocompatibility complex (MHC)-like molecule MR1. The highly conserved nature of MR1 in conjunction with biased MAIT TCRα chain usage is widely thought to indicate limited ligand presentation and discrimination within a pattern-like recognition system. Here, we evaluated the TCR repertoire of MAIT cells responsive to three classes of microbes. Substantial diversity and heterogeneity were apparent across the functional MAIT cell repertoire as a whole, especially for TCRβ chain sequences. Moreover, different pathogen-specific responses were characterized by distinct TCR usage, both between and within individuals, suggesting that MAIT cell adaptation was a direct consequence of exposure to various exogenous MR1-restricted epitopes. In line with this interpretation, MAIT cell clones with distinct TCRs responded differentially to a riboflavin metabolite. These results suggest that MAIT cells can discriminate between pathogen-derived ligands in a clonotype-dependent manner, providing a basis for adaptive memory via recruitment of specific repertoires shaped by microbial exposure., (© 2014 Gold et al.)
- Published
- 2014
- Full Text
- View/download PDF
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