RNAseq of CD8+ T cells memory subsets in human peripheral blood
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PROVIDER: PRJNA623562 | ENA |
REPOSITORIES: ENA
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Project description:RNAseq of CD8+ T cells memory subsets in human peripheral blood
2020-06-11 | GSE148234 | GEO
Project description:Microarray deconvolution is a technique for quantifying the relative abundance of constituent cells in a mixture based on that mixture's microarray signature and the signatures of the purified constituents. It has been applied to yeast and other systems but not to blood samples. Here we test the ability of this technique to determine the fractions of subsets of memory T cells in peripheral blood mononuclear cell (PBMC) samples. Experiment Overall Design: PBMC samples from several donors were split. One portion of each PBMC sample was set aside, while the remainder of each was sorted into naive, central memory, and effector memory T cell subsets.
2009-07-19 | E-GEOD-11057 | biostudies-arrayexpress
Project description:Mucosa-associated invariant T (MAIT) cells are unconventional innate-like T cells that recognize microbial riboflavin metabolites presented by the MHC class I-like protein MR1. Human MAIT cells predominantly express the CD8α co-receptor (CD8+), with a smaller subset lacking both CD4 and CD8 (DN). However, it is unclear if these two MAIT cell sub-populations distinguished by CD8α represent functionally distinct subsets. To address this, we investigated the phenotypic, transcriptional, and functional differences between CD8+ and DN MAIT cells using human samples from peripheral blood, mucosal tissues, and fetal tissues.
2019-01-02 | GSE120847 | GEO
Project description:The aim was to assess miRNA expression in 3 human ex-vivo CD8+ T cell subsets which span from antigen inexperienced cells (NaM-CM-/ve) to early memory cells (central memory, Tcm) and later stage memory cells (effector memory, Tem) CD8+ T cells were sorted on a FACS Aria II machine. N = naM-CM-/ve = CD8+, CCR7+, CD45RA+, CD45RO-, Tcm = central memory = CD8+, CCR7+, CD45RA-, CD45RO-,Tem= effector memory = CD8+, CCR7-, CD45RA-, CD45RO+ PBMC were isolated from 3 healthy human donors and sorted by FACS into 3 CD8+ T cell subsets. Total RNA was purified using the miRVANA kit (Ambion)
2014-10-24 | E-GEOD-54867 | biostudies-arrayexpress
Project description:CD4+ memory T helper cells are organized in different subsets characterized by distinct functions and chemokine receptor expression patterns induced and maintained by divergent gene programs. We demonstrate here that identical chemokine receptor combinations are sufficient to separate analogous differentiated CD8+ memory T cell subsets with matching cytokine profiles. Tc2, Tc17 and Tc22 type CD8+ T cell subsets, in contrast to classical cytotoxic Tc1 and Tc17+1 cells, possess a CD4 helper type alike phenotype characterized by absent cytotoxicity and SLAMF7 expression as well their ability to express CD40L upon activation. Their highly disparate homing patterns and unique TCR repertoire associates them to distinct immune responses as compared to those cytotoxic CD8+ T cells exert their role in. The dermal T cell gene expression signature and enrichment in psoriasis patients indicates that peripheral helper type CD8+ T cells represent a circulatory variant of skin resident cells.
2020-08-25 | GSE115103 | GEO
Project description:The generation of CD8+ T-cell memory is an important aim of immunization. While several distinct subsets of CD8+ T-cell memory have been described, the lineage relationships between effector (EFF), effector memory (EM) and central memory (CM) T cells remain contentious. Specifically, there is contradictory experimental evidence to support both the linear (Naive>EFF>EM>CM) and progressive differentiation (Naive>CM>EM>EFF) models. In this study, we applied a systems biology approach to examine global transcriptional relationships between the three major CD8+ T cell subsets arising endogenously as a result of vaccination with three different prime-boost vaccine regimens. Differential gene expression analysis and principle component analysis revealed that central memory cells were more closely related to naive T cells than both effector memory and effector cells. When the transcriptional relationships between subsets were enriched in an unbiased fashion with known global transcriptional changes that result when T-cells repeatedly encounter antigen, our analysis favored a model whereby cumulative antigenic stimulation drives differentiation specifically from Naive > CM > EM > EFF. These findings provide an insight into the lineage relationship between mature CD8+ T-cell subsets and will help in the rational design of vaccines aimed at generating effective immune responses against infections and cancer. Effector (EFF), effector memory (EM), central memory (CM) and naive CD8+ T cells from mice spleen. Memory subset arise endogenously as a result of vaccination with three different prime-boost vaccine regimens: DNA-rAd5, rAd5-rAd5 and rAd5-rLCMV.
2013-08-01 | E-GEOD-42459 | biostudies-arrayexpress
Project description:It is unknown whether human lung T cells recirculate or belong to a distinct tissue-specific population. This issue is important for understanding their role in protection against viral infection and their contribution to pathophysiology of lung diseases such as chronic obstructive pulmonary disease. By comparing transcriptional profiles of blood and lung CD8+ T cells, we aimed to reveal specific traits of lung CD8+ T cells. A total of 12 samples was analyzed: 10 patient samples (including 1 technical replicate) and 2 reference samples (including 1 technical replicate). Per patient (in total 3 patients), 3 paired samples were analyzed. These samples were non-naive peripheral blood CD8+ T cells (CD45R0+CD3+CD8+ T cells), memory-type lung CD8+ T cells (CD45R0+CD27+CD3+CD8+ T cells) and effector-type lung CD8+ T cells (CD45R0+CD27-CD3+CD8+ T cells). The reference population consisted of a mix of naive peripheral blood CD8+ T cells from 5 healthy donors.
2011-06-20 | E-GEOD-30027 | biostudies-arrayexpress
Project description:A specialized population of memory CD8+ T-cells resides in the epithelium of the respiratory tract to maintain protection against recurring infections. These cells express CD69 and the integrin αβ7 (CD103) and correspond to tissue resident memory T-cells (TRM) also described in intestine, liver and brain. A less well characterized population of CD103- CD8+ T-cells also resides in lungs and expresses markers characteristic of effector memory T-cells (TEM). We determined the transcriptional profiles of these memory CD8+ T-cell subsets retrieved from human lung resection samples and compared these with corresponding T-cell populations from peripheral blood of the same individuals. Our results demonstrate that each of the populations exhibits a distinct transcriptional identity. We found that the lung environment has a major impact on gene expression profiles. Thus, transcriptomes from CD103+ and CD103- subsets from lungs are much more resemblant to one another than to those from CD103+ or CD103- memory CD8+ T-cells from blood. TRM express specific sets of chemokine receptors, in accordance with their unique migratory properties. Furthermore, these cells constitutively express cytokine and cytotoxic genes for immediate effector function and chemokines to attract auxiliary immune cells. At the same time, multiple genes encoding inhibitory regulators are also expressed. This suggests that rapid ability to unleash effector functions is counterbalanced by programmed restraint, a combination that may be critical in the exposed but delicate tissue of the lung. Comprehensive sets of transcription factors were identified that characterize the memory CD8+ populations in the lungs. Prominent among these were components of the Notch pathway. Using mice genetically lacking expression of the NOTCH1 and NOTCH2 receptors in T-cells, we demonstrated that Notch controls both the number of lung TRM as well as the function of lung TEM. Our data illustrate the adaptation of lung resident T-cells to the requirements of the respiratory epithelial environment. Defining the molecular imprinting of these cells is important for rational vaccine design and may help to improve the properties of T-cells for adoptive cellular therapy. Material was collected from a total of 6 subjects. Three patients underwent a lobectomy for a peripheral primary lung tumor and three received lung transplantation because of end-stage pulmonary disease (COPD). Lung mononuclear cells where isolated after digestion of the partial or complete human lung resection material. Paired peripheral blood mononuclear cells were also isolated. CD8+CD16-CD56- T-cells were sorted for expression of CD103 (ITGAE). Lung and blood derived CD103+ and CD103- T-cell fractions were directly lysed after FACS sorting or stimulated overnight with antiCD3/28 beads. Due to the low frequency of resting (non-stimulated) CD103+ T-cells in peripheral blood this subset was obtained from five non-related buffy coat donors. RNA was isolated from 36 sorted cell samples and hybridized on Illumina HumanHT-12 V4.0 microarrays. Eight microarray samples (including two samples from the buffy coat donors) were excluded after hybridization since their average signal was too low.
2016-10-23 | E-GEOD-61397 | biostudies-arrayexpress
Project description:RNAseq of CD8+ and CD8- MAIT cells in human peripheral blood
| PRJNA494706 | ENA
Project description:Gene expression profiling of human CD8+ CD161hi and CD161lo central and effector memory and naïve T cell subsets. The mechanisms by which IL-17 secreting cells are regulated have not been completely elucidated. We previously identified a population of rhodamine-effluxing memory CD8+ T cells with high expression of CD161 that contributes to immune reconstitution after lymphopenia-inducing chemotherapy. Here we find that CD161hi CD8+ T cells share transcriptional programming with Th17 cells, but most do not secrete IL-17 or proliferate to stimulation through the T cell receptor (TCR). Transcriptional analysis of subsets identified by expression of CD161 and CD62L revealed a novel mechanism of TCR signaling pathway regulation in CD161hi CD8+ T cells that is distinct from that described in anergic or tolerant cells and renders them functionally dependent on costimulation through innate cytokine receptors or CD28. CD161hi CD8+ T cells, induced to proliferate by a TCR signal delivered with costimulation, demonstrated plasticity that was dependent on the nature of costimulation and resulted in expansion of IL-17 secreting cells that could not proliferate to a TCR signal alone or differentiation to Tc1-like cells that proliferated to TCR stimulation in the absence of costimulation. The data show an association between TCR signaling pathway downregulation and type 17 programming in CD161hi CD8+ T cells, whose dysregulation could mediate IL-17 dependent inflammatory diseases. T cell subsets were sort-purified from healthy adults and analyzed by gene expression profiling. Isolation: Effluxing CD161hi and non-effluxing CD161lo CD8+ TCM and TEM subsets were purified using magnetic bead separation and cell sorting to achieve >98% purity, as previously described (35). CD8+ T cells were positively selected using CD8 Microbeads (Miltenyi Biotec, Germany), loaded with Rh123 (Sigma, St. Louis, MO) and cultured for 30 min to allow Rh123 efflux, then labeled with fluorochrome-conjugated antibodies to CD4, CD16, TCRγδ, Vα24, CD8, CD95, CD62L and CD161. CD161hi and CD161lo TCM and TEM subsets were sort-purified on a FACS ARIA equipped with 405 nm, 488 nm and 633 nm lasers (BD Biosciences). CD161hi TCM and TEM subsets were identified as CD62L+/Rh123lo/CD161hi and CD62L-/Rh123lo/CD161hi events, respectively, in the CD4-/CD16-/TcRγδ-/Vα24-/CD8+/CD95+ population. CD161lo TCM and TEM subsets were identified as CD62L+/Rh123hi/CD161int/neg and CD62L-/Rh123hi/CD161int/neg events, respectively, in the CD4-/CD16-/TcRγδ-/Vα24-/CD8+/CD95+ population. Gene expression profiling: RNA was extracted from sort-purified subsets from 6 healthy individuals using the RNeasy Plus Minikit (Qiagen, Valencia, CA) and biotinylated, followed by generation of amplified cRNA for array hybridization using the Illumina TotalPrep RNA Amplification Kit (Applied Biosystems, Foster City, CA). Amplified biotinylated cRNA was then purified before quality control to ensure high quality cRNA was available for hybridization. Labeled cRNA was hybridized to Illumina WG-6 Expression BeadChips v3.0 (Illumina, San Diego, CA), which quantitate expression of 48,802 transcripts derived from the NCBI RefSeq (Build 36.2, Release 22) and UniGene databases (Build 199). BeadChips were washed before reading and image extraction, and then scanned on an Illumina BeadArray Reader. The resulting TIFF images were processed using GenomeStudio Gene Expression Module (GEM) software. Data quality was assessed using the Control Summary feature in GenomeStudio GEM. For a given analysis set, a GenomeStudio Probe-level Final Report was generated by combining the Sample Probe Profile and Control Probe Profile tables. The Final Report comprising the full dataset was initially processed using the Bioconductor package lumi by employing a background correction estimate and quantile normalization. A small adjustment (i.e. 20 counts) was made to the entire dataset to make all intensity signals non-negative and these values were log2-transformed. The dataset was initially filtered using the ‘shorth’ function of the Bioconductor package genefilter, resulting in retention of 31,084 of 48,802 original probes. Each pairwise comparison was further filtered by discarding probes whose signal intensity was less than a defined signal “noise floor” across all arrays in the data subset. This was achieved by calculating the median of the ‘negative control’ probe signals for each array, averaging these values, and setting the noise floor as 3 times this average. Differential gene expression was then determined using the Bioconductor package limma, and a false discovery rate (FDR) method applied to correct for multiple testing. Significant differential gene expression was defined by a log2 ratio > 0.585 (± 1.5-fold) and FDR (adjusted p value) < 0.05.
2011-07-31 | E-GEOD-23663 | biostudies-arrayexpress