Transcriptome analysis of freshly sorted and expanded regulatory and conventional T cells
ABSTRACT: Transcriptome analysis of freshly sorted regulatory T cells (CD4+CD25+) and conventional T cells (CD4+CD25-) and of expansion cultures of regulatory T cells (CD4+CD25+CD45RA+) and conventional T cells (CD4+CD25-). Three biological replicates were performed of freshly sorted Treg and Tconv cells each. Four replicates of Treg expansion cultures sorted into CD45RA+/- subpopulations prior to RNA extraction were performed.
Project description:This SuperSeries is composed of the following subset Series: GSE14232: Transcriptome analysis of freshly sorted and expanded regulatory and conventional T cells GSE14233: Detection of differentially methylated regions in CD4+CD25+CD45RA+ regulatory T-cells and conventional CD4+CD25- T-cells GSE14234: Histone H3 Lysine 4 mono-, di- and trimethyl and CTCF in CD4+CD25+CD45RA+ regulatory and conventional CD4+CD25- T-cells Refer to individual Series
Project description:We have previously developed an approach that fractionates genomic DNA fragments depending on their CpG density (methyl-CpG-immunoprecipitation, MCIp), and adapted this approach to identify regions that are differentially methylated in the two closely related regulatory T-cells (Treg cells) and conventional T-cells (Tconv cells). Because Treg cells naturally occur at a relatively low frequency, we used a previously established protocol to expand Treg cells from a stable naïve Treg population that is characterized by the co-expression of CD4, CD25 and CD45RA. We separated gDNA of both expanded T cell lineages (Tregexp and Tconvexp) into unmethylated (CpG) and methylated pools (mCpG) using MCIp and compared cell type-specific differences in DNA methylation by co-hybridization of the two umethylated or the two methylated DNA subpopulations of Treg and Tconv, respectively, to these locus-wide custom tiling arrays. As enriched DNA-fragments from a cell type in the methylated fraction should be depleted in the unmethylated fraction, the signal intensities in CpG pool and mCpG pool hybridizations should complement themselves (“Mirror-Image” approach) and thereby allow the identification of differentially methylated regions (DMR). Because we expected to find lineage-specific methylation differences with greater probability in regions associated with differential transcriptional activity, we limited our analysis to gene loci that showed cell type-specific gene expression in Treg versus Tconv cells plus a handful of control regions that were equally expressed in both cell types. The microarray used in this study covered 12 megabases of the human genome and contained 69 regions (with a median size of 100.000 kb) and 128 proximal promoter regions and 181 genes, which included a number of well known and functionally relevant genes like CD40LG, IFNG, FOXP3, IL2RA and CTLA4. Keywords: MCIp-on-chip; comparative genomic hybridization With MCIp gDNA from Treg or Tconv cells was separated into hypo- and hypermethylated pools. On each array, wheather the two hypomethylated fractions- one from Treg, the other from Tconv cells- or the two hypermethylated fractions were cohybridized. Two biological replicates.
Project description:Analysis of Histone H3 Lysine 4 mono-, di- and trimethyl and the boundary protein CTCF in CD4+CD25+CD45RA+ regulatory T-cells and conventional CD4+CD25- T-cells. To investigate regulatory functions or potential new transcription start sites in Treg and Tconv cells, we investigated the associated histone modifications. Mono- and dimethylation of histone 3 lysin 4 (H3K4) were previously shown to mark enhancer regions, whereas H3K4 trimethylation generally associates with transcription start sites. At imprinted loci, binding of the insulator protein CTCF, which restricts or directs enhancer-promoter interactions, is often regulated by DNA-methylation. Therefore we performed ChIP-on-chip experiments (chromatin immunoprecipitation followed by microarray hybridization; samples were amplified with ligation mediated PCR [see label protocol for the procedure] prior to labeling) for mono- di- and trimethylation of histone 3 lysin 4 and of CTCF in expanded Treg and Tconv cells. Keywords: ChIP-on-chip ChIP-on-chip experiments for H3K4 mono-, di- and trimethyl and CTCF in CD4+CD25+CD45RA+ regulatory T-cells and conventional CD4+CD25- T-cells were co-hybridizied with the input. Three biologiacal replicates (rep1-3) were performed for every histone mark, two CTCF (rep1 and rep2).
Project description:CD4+CD25+FOXP3+ human regulatory T cells (Treg) are essential for self-tolerance and immune homeostasis. Here, we generated genome-wide maps of poised and active enhancer elements marked by histone H3 lysine 4 monomethylation and histone H3 lysine 27 acetylation for CD4+CD25highCD45RA+ naive and CD4+CD25highCD45RA- memory Treg and their CD25- conventional T cell (Tconv) counterparts after in vitro expansion . In addition we generated genome-wide maps of the transcription factors STAT5, FOXP3, RUNX1 and ETS1 in expanded CD4+CD25highCD45RA+ Treg- and CD4+CD25- Tconv to elucidate their role in cell type-specific gene regulation. ChIP-seq of 2 histone marks and transcription factors ETS1, STAT5, FOXP3 and RUNX1 in expanded T cell subpopulations
Project description:Changes in Treg function are difficult to quantify due to the lack of Treg-exclusive markers in humans and the complexity of functional experiments. We sorted naive and memory human Tregs and conventional T cells, and identified genes that identify human Tregs regardless of their state of activation. We developed this Treg signature using Affymetrix human genome U133A 2.0 microarrays. To generate Tregs and Tconvs in multiple states of activation, naïve (CD4+CD25hiCD45RA+) and memory (CD4+CD25hiCD45RA-) Tregs, and naïve (CD4+CD25-CD45RA+) and memory (CD4+CD25-CD45RA-) Tconvs were sorted from blood of 7 healthy adults and RNA was isolated ex vivo or after stimulation for 40h, promoting activation-induced FOXP3 in Tconvs. The gene-expression profile of the eight cell subsets was analyzed. 7 adult healthy control samples were sorted into 4 subsets: naïve (CD4+CD25hiCD45RA+) and memory (CD4+CD25hiCD45RA-) Tregs, and naïve (CD4+CD25-CD45RA+) and memory (CD4+CD25-CD45RA-) Tconvs. These were used for RNA ex vivo and after 40h stimulation with anti-CD3/CD28 beads to induce an activation phenotype.
Project description:Microarray used to detail the global gene transcription underlying sorted IFNg+ and IFNg- Tregs (CD4+CD25+CD127lo) and Tconv (CD4+CD25-CD127+) for fresh (unexpanded) and 14 day expanded cells from human blood. Treg and Tconv were FACS isolated from five healthy subjects (median age of 26, range 22-30). Sorted cells were separated into two groups: the first group was stimulated for 4 hours with PMA/ionomycin and labeled with the IFNg cytokine capture kit (Miltenyi Biotech) followed by FACS isolation of IFNg- and IFNg+ populations. The second set was expanded to day 14 prior to reactivation and cytokine cell capture. For each IFNg sorted population, cells were pelleted and flash frozen before RNA isolation and processing.
Project description:Understanding human Regulatory T cell (Treg) heterogeneity may identify markers of disease pathogenesis and facilitate the development of optimized cellular therapeutics. Previous analysis revealed that the co-inhibitory receptor T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) was highly expressed on tTreg. The negative regulator TIGIT and the co-stimulatory factor CD226 bind the common ligand CD155. Human regulatory T cells (CD4+CD25+CD127-/lo) from adult peripheral blood were sub-fractionated based on the markers CD226 and TIGIT and were subsequently expanded in vitro according to clinical expansion protocols. The transcriptional profile of the final cell products uncovered considerable heterogeneity in terms of in vitro expansion and suppressive capacity. Most notably, the CD226+TIGIT- fraction adopted a transcriptional profile most similar to that of conventional T cells, including the capacity for effector cytokine production. Tregs and corresponding Tconv were expanded from peripheral blood of three normal healthy control male subjects.
Project description:Rationale: COPD is characterized by an abnormal regulatory T cell (Treg) response and increases in Th1 and Th17 cell responses. It is unclear if dysregulation of miRNAs within Treg alters the adaptive immunophenotype in COPD. Objectives: To compare the miRNA profile of COPD Treg cells with that of healthy controls and to explore the function of differentially expressed miRNAs. Methods: Treg cells (CD4+CD25+CD49-CD127-) and T effector (CD4+CD25-) cells were obtained from the peripheral blood of 4 nonsmokers, 4 healthy current smokers, and 4 COPD current smokers for analysis of miRNA expression, matching them for age and sex. We assessed expression initially by microarray analysis on the Illumina miRNA platform then conducted real time RT-PCR validation of the microarray results. 24 samples were analyzed. 8 from each patient group of healthy Normal, Healthy Smoker, and COPD Smoker.
Project description:miRNA expression profiling in highly purified murine CD4+ Tconv and Treg cells. FoxP3-GFP-hCre1a(high) reporter mice were used to separate both populations based on surface markers and presence or absence of GFP. Two-condition experiment, Tconv vs. Treg. Biological replicates: 1 Tconv, 1 Treg, purified from the same pooled mice. One replicate on 1 array.
Project description:In this study, we compared the proteomes of mouse CD4+Foxp3+ regulatory T cells (Treg) and CD4+Foxp3- conventional T cells (Tconv) in order to build a data set of proteins differentially regulated in these two cell populations. The data set contains mass spectrometry results from the analysis of 7 biological replicates of Treg/Tconv cell samples purified by flow cytometry, each experiment performed from a pool of 4-5 mice. Global proteomic analysis of each sample was performed by single-run nanoLC-MS/MS, using chromatographic separation of peptides on 50cm C18 reverse-phase columns, with either a 480min gradient on LTQ-Velos orbitrap mass spectrometer (replicates 1 and 2) or a 300min gradient on Q-Exactive orbitrap mass spectrometer (replicates 3-7). Several MS injection replicates were performed for some experiments, leading to 27 raw files composing the data set. The detailed description of each analysis (file name, sample type, biological replicate number, MS technical replicate number, MS instrument used, sample name in MaxQuant ouput) is given in the table “Files list.txt”.