3df1461f-2cfc-439f-8ff3-a746aa33f622 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001005047 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:In order to characterize the T cell receptor (TCR) repertoire of DQ2.2-glut-L1-specific T cells, we performed high-throughput DNA sequencing of rearranged TCR-α and TCR-β genes of the single HLA-DQ2.2:DQ2.2-glut-L1 tetramer binding CD4+ T cells isolated from six T-cell lines (TCLs) of four Celiac disease patients.
| EGAS00001003673 | EGA
Project description:In order to characterize the T cell receptor (TCR) repertoire of DQ2.5-hor-3-specific T cells, we performed high-throughput DNA sequencing of rearranged TCR-α and TCR-β genes of the single HLA-DQ2.5:DQ2.5-hor-3- tetramer binding CD4+ T cells isolated from biopsies of celiac disease patients. We also sequenced the TCR of the T-cell clones (TCCs) that were generated by cloning by limited dilution and antigen-free expansion of HLA-DQ2.5:DQ2.5-hor-3-tetramer binding CD4+ T cells from biopsies of celiac disease patients.
| EGAD00001005048 | EGA
Project description:In order to characterize the T cell receptor (TCR) repertoire of DQ2.5-hor-3-specific T cells, we performed high-throughput DNA sequencing of rearranged TCR-α and TCR-β genes of the single HLA-DQ2.5:DQ2.5-hor-3- tetramer binding CD4+ T cells isolated from biopsies of celiac disease patients. We also sequenced the TCR of the T-cell clones (TCCs) that were generated by cloning by limited dilution and antigen-free expansion of HLA-DQ2.5:DQ2.5-hor-3-tetramer binding CD4+ T cells from biopsies of celiac disease patients.
| EGAS00001003674 | EGA
Project description:In order to characterize the T cell receptor (TCR) repertoire of gluten specific T cells, we performed high-throughput DNA sequencing of rearranged TCR-α and TCR-β genes of the single HLA-DQ2.5:DQ2.5-gluten tetramer binding CD4+ T cells isolated from blood, biopsies and T cell line from celiac disease patients.
| EGAD00001006977 | EGA
Project description:HLA-E molecules can present self and pathogen-derived peptides to both NK-cells and T-cells. T-cells that recognize HLA-E peptides via their T-cell receptor (TCR) are termed donor-unrestricted T-cells due to restricted allelic variation of HLA-E. The composition and repertoire of HLA-E TCRs is not known so far. We performed TCR sequencing on CD8+ T-cells from 21 individuals recognizing HLA-E tetramers (TM) folded with 2 Mtb HLA-E restricted peptides. We sorted HLA-E Mtb TM+ and TMCD8+ T-cells directly ex vivo and performed bulk RNA-sequencing and single cell TCR sequencing. The identified TCR repertoire was diverse and showed no conservation between and within individuals. TCRs selected from our single cell TCR sequencing data could be activated upon HLA-E/peptide stimulation, although not robust, reflecting potentially weak interactions between HLA-E peptide complexes and TCRs. Thus, HLA-E Mtb specific T-cells have a highly diverse TCR repertoire.
2024-02-04 | GSE236154 | GEO
Project description:PBMCs from 4 donors were stained with the influenza A virus HLA-A24/PB1 498-505 tetramer. Two donors (non-LIFT8 and non-LIFT12) showed TCR independent KIR binding to tetramers whereas the other two donors (Non-LIFT14 and Non-LIFT10) showed TCR specific binding. Cells were single-cell sorted on a BD Aria III into 96-well plates containing 0.5 μl dNTP mix (10 mM), 0.5 μl oligo-dT pri- mer (5 μM), and 1 μl lysis buffer (prepared by adding 1 μl RNase inhibitor to 19 μl Triton X-100 solution, 0.2% v/v).
2021-04-08 | E-MTAB-10109 | biostudies-arrayexpress
Project description:<p>High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.</p>
| phs001678 | dbGaP
Project description:In this study relative quantitative analysis of endogenous peptides by mass spectrometry combined with neural network analysis have been used to address why the alpha- or beta-chain sharing human leukocyte antigen (HLA)-DQ molecules DQ2.5, DQ2.2 and DQ7.5 display different risks for celiac disease. Celiac disease is caused by intolerance to cereal gluten proteins, and HLA-DQ molecules are involved in the disease pathogenesis by presentation of gluten peptides to CD4+ T cells. It has recently been shown that T cells of DQ2.5 and DQ2.2 patients recognize different sets of gluten epitopes suggesting that these celiac disease associated DQ molecules select different peptides for display. To explore whether this is the case, we performed a comprehensive, large-scale comparison of the endogenous self-peptides bound to HLA-DQ molecules of B-lymphoblastoid cell lines (B-LCLs). Peptides were eluted from affinity-purified HLA molecules of nine cell lines and subjected to quadrupole orbitrap mass spectrometry and MaxQuant software analysis. Altogether, 12712 endogenous peptides were identified at very different relative abundances. Hierarchical clustering of normalized quantitative data demonstrated significant differences in repertoires of peptides between the three DQ variant molecules. The neural network-based method, NNAlign, was used to identify peptide-binding motifs. The binding motifs of DQ2.5 and DQ7.5 concurred with previously established binding motifs. The binding motif of DQ2.2 was strikingly different from that of DQ2.5 with position P3 being a major anchor having a preference for threonine and serine. This is notable as three recently identified epitopes of gluten recognized by T cells of DQ2.2 celiac patients harbor serine at position P3. The study demonstrates that relative quantitative comparison of endogenous peptides sampled from our protein metabolism by HLA molecules provides clues to understand HLA association with disease.
2014-12-04 | PXD001205 | Pride
Project description:Individuals with narcolepsy suffer from abnormal sleep patterns due to loss of neurons that uniquely supply hypocretin (HCRT). Previous studies found the associations of narcolepsy with human leukocyte antigen (HLA)-DQ6 allele and T-cell receptor α (TRA) J24 gene segment and also suggested that in vitro-stimulated T cells can target HCRT. However, DQ6+ individuals generate DQ6-HCRT tetramer+/TRAJ24+ TCRs. Without a proof that an HCRT-reactive cell expressing such TCRs has expanded in vivo, T cell-mediated autoimmunity in narcolepsy remains speculative. Here, we isolated DQ6-HCRT tetramer+/CD4+ T cells (low frequency, <0.04%) from DQ6+ individuals with/without narcolepsy. Within 74 informative TRAJ24+ TCRαβ from 8/12 patients and 11/12 controls, we identified a conserved family of clonotypes shared by 2 patients and 2 controls using identical α/β genes. TRAJ24-G allele+ clonotypes only expanded in the two patients, whereas a TRAJ24-C allele+ clonotype expanded in a control. A representative tetramer+/G-allele+ TCR showed signaling reactivity to the physiologically modified form of the epitope HCRT87-97. Clonally expanded G-allele+ T cells also exhibited an unconventional effector phenotype. In vivo expansion of HCRT-reactive TRAJ24-G allele+ cells provides critical evidence for an autoimmune contribution to narcolepsy development.
2019-10-15 | GSE135852 | GEO
Project description:We applied a cell population transcriptomics strategy to sorted human memory CD8 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and understand the phenotype of tuberculosis (TB)-specific T cells. We found a 41-gene signature that could discriminate between memory CD8 T cells from healthy LTBI subjects and noninfected controls. The gene signature was dominated by genes known to be associated with mucosal associated invariant T cells (MAITs) and reflected the lower frequency of MAITs observed in individuals with LTBI. There was no evidence for a conventional CD8 T cell specific signature between the two cohorts. We therefore investigated the MAITs in more detail in these cohorts. Phenotyping based on Vα7.2 and CD161 expression and MR1 tetramers revealed 2 distinct populations of CD8+Vα7.2+CD161+ T cells: MR1 tetramer+ and MR1 tetramer−, both of which had a distinct gene expression profile compared to CD8 memory T cells. Transcriptomic analysis of LTBI vs. noninfected individuals did not reveal significant differences for MR1 tetramer+ cells. However, gene expression of MR1 tetramer− cells showed a very different profile with large inter-individual diversity and a TB-specific signature. This was further strengthened by a more diverse TCR-α and -β repertoire of MR1 tetramer− cells as compared to MR1 tetramer+. Thus, cell population transcriptomics revealed a dominant MAIT signature in CD8 memory T cells that upon detailed investigation provided novel insights into the phenotype of different MAIT populations implicated in tuberculosis.
2020-05-13 | GSE132932 | GEO