T cell responses to H1N1v and a longitudinal study of seasonal influenza vaccination - 2012
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ABSTRACT: Systems biology approach to examine effects of seasonal flu vaccination in adults of different ages on gene expression, cytokine stimulation and serum cytokines with parameters such as immune senescence to uncover new markers and mechanisms behind failure of immune function in many older people. 1. Combinatorial tetramer analysis by FACS and/or CyTOF; Phosphoflow. 2. Luminex; Gene expression profiling (Affymetrix microarray). 3. Luminex; Gene expression profiling (Affymetrix microarry); Microneutralization assays. 4. Gene expression profiling (Affymetrix microarray); Immune phenotyping by CyTOF. 5. Gene expression profiling (Affymetrix microarray). 6. Immune phenotyping by CyTOF; Luminex. 7. ELISA.
Project description:Immune profiles were performed retrospectively in highly sensitized kidney transplant candidates Our hypothesis was that baseline differences in immune profiles could help identify candidates that respond to desensitization therapy. Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in 20 highly sensitized kidney transplant candidates undergoing desensitization therapy.
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.
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.
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.
Project description:The purpose of the present studies was to use CyTOF and RNA-Seq technologies to identify cells and genes involved in lacrimal gland repair that could be targeted to treat diseases of lacrimal gland dysfunction. Lacrimal glands of female BALB/c mice were experimentally injured by intra-glandular injection of interleukin 1 alpha (IL-1α). The lacrimal glands were harvested at various time points following injury (1 to 14 days) and used to either prepare single cell suspensions for CyTOF immuno-phenotyping analyses or to extract RNA for gene expression studies using RNA-Seq. CyTOF immuno-phenotyping identified monocytes and neutrophils as the major infiltrating populations 1 and 2 days post injury. Clustering of significantly differentially expressed genes identified 13 distinct molecular signatures: 3 associated with immune/inflammatory processes included genes up-regulated at days 1-2 and 3 associated with reparative processes with genes up-regulated primarily between days 4 and 5. Finally, clustering identified 65 genes which were specifically up-regulated 2 days post injury which was enriched for muscle specific genes. The expression of select muscle-related proteins was confirmed by immunohistochemistry which identified a subset of cells expressing these proteins. Double staining experiments showed that these cells are distinct from the myoepithelial cells. We conclude that experimentally induced injury to the lacrimal gland leads to massive infiltration by neutrophils and monocytes which resolved after 3 days. RNAseq and immunohistochemistry identified a group of cells, other than myoepithelial cells, that express muscle-related proteins that could play an important role in lacrimal gland repair.
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>
Project description:Fresh human breast tumor tissue was dissociated into single cells and viably frozen. Patient samples were annotated as having an ""exhausted"" or ""non-exhausted"" immune environment based on CyTOF characterization of T cell phenotypes (Wagner et al, Cell 2019). 14 samples (7 exhausted, 7 non-exhausted) were selected for scRNA-seq (without prior cell type enrichment) with the goal to compare the two immune environment types and to comprehensively characterize exhaustion-associated features of the tumor microenvironment.
Project description:Introduction: Tobacco smoking generates airway inflammation in chronic obstructive pulmonary disease (COPD), and its involvement in the development of lung cancer is still among the leading causes of early death. Therefore, we aimed to have a better understanding of the disbalance in immunoregulation in chronic inflammatory conditions in smoker subjects with stable COPD (stCOPD), exacerbating COPD (exCOPD), or non-small cell lung cancer (NSCLC). Methods: Smoker controls without chronic illness were recruited as controls. Through extensive mapping of single cells, surface receptor quantification was achieved by single-cell mass cytometry (CyTOF) with 29 antibodies. The CyTOF characterized 14 main immune subsets such as CD4+, CD8+, CD4+/CD8+, CD4 −/CD8−, and g/d T cells and other subsets such as CD4+ or CD8+ NKT cells, NK cells, B cells, plasmablasts, monocytes, CD11cdim, mDCs, and pDCs. The CD4+ central memory (CM) T cells (CD4+/CD45RA−/CD45RO+/CD197+) and CD4+ effector memory (EM) T cells (CD4+/CD45RA−/CD45RO+/CD197−) were FACSsorted for RNA-Seq analysis. Plasma samples were assayed by Luminex MAGPIX® for the quantitative measurement of 17 soluble immuno-oncology mediators (BTLA, CD28, CD80, CD27, CD40, CD86, CTLA-4, GITR, GITRL, HVEM, ICOS, LAG-3, PD-1, PD-L1, PD-L2, TIM-3, TLR-2) in the four studied groups. Results: Our focus was on T-cell-dependent differences in COPD and NSCLC, where peripheral CD4+ central memory and CD4+ effector memory cells showed a significant reduction in exCOPD and CD4+ CM showed elevation in NSCLC. The transcriptome analysis delineated a perfect correlation of differentially expressed genes between exacerbating COPD and NSCLCderived peripheral CD4+ CM or CD4+ EM cells. The measurement of 17 immuno-oncology soluble mediators revealed a disease-associated phenotype in the peripheral blood of stCOPD, exCOPD, and NSCLC patients. Discussion: The applied single-cell mass cytometry, the whole transcriptome profiling of peripheral CD4+ memory cells, and the quantification of 17 plasma mediators provided complex data that may contribute to the understanding of the disbalance in immune homeostasis generated or sustained by tobacco smoking in COPD and NSCLC.
Project description:Primary outcome(s): Concordance rate of both KRAS and NRAS gene exon 2, 3 and 4 mutations between standard genetic testings including sanger sequencing and an established in vitro diagnostic (IVD) kit for KRAS exon2, and a newly developed Luminex-based all RAS assay kit