Browse
Submit Data
Databases
API
Help

Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

19 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Methylome of CD4+ T cell subsets

ABSTRACT: We compared the methylated and non-methylated regions in the genome of ex vivo-isolated naive CD4+ T cells, Th1 cells, Th17 cells and regulatory T cells by methyl-CpG binding domain protein sequencing (MBD-seq). Naive T cells and Th1 cells share more methylated regions than naive T cells and Th17 cells or Th1 and Th17 cells. However, analysis of the non-methylated regions revealed the highest similarity between Th1 and Th17 cells. Another aim was the analysis of the Th17 lineage on the basis of the methylome. We searched for regions absent in the methylome of Th17 but present in naive T cells, Th1 cells and regulatory T cells. Here, we identified differential methylation in the loci of Il17a, Chn2, Dpp4 and Dclk1. CD4+ T effector cells were prepared ex vivo, stimulated with PMA/Ionomycin, subjected to a comercially available cytokine secretion kit (IL-17A and IFNg), stained by adding fluorescence-labeled antibodies against CD3, CD4 and CD45RB and sorted by flow cytometry. We sorted naive CD4+ T cells (CD3+CD4+CD45RB_high), Th1 cells (CD3+CD4+CD45RB_low_IFNg+IL17A-), Th17 cells (CD3+CD4+CD45RB_low_IFNg-IL17A+) and regulatory T cells (CD3+CD4+CD25++).

ORGANISM(S): Mus musculus

SUBMITTER: Stefan Floess

PROVIDER: E-GEOD-45911 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Methylome of CD4+ T cell subsets

Project description:We compared the methylated and non-methylated regions in the genome of ex vivo-isolated naive CD4+ T cells, Th1 cells, Th17 cells and regulatory T cells by methyl-CpG binding domain protein sequencing (MBD-seq). Naive T cells and Th1 cells share more methylated regions than naive T cells and Th17 cells or Th1 and Th17 cells. However, analysis of the non-methylated regions revealed the highest similarity between Th1 and Th17 cells. Another aim was the analysis of the Th17 lineage on the basis of the methylome. We searched for regions absent in the methylome of Th17 but present in naive T cells, Th1 cells and regulatory T cells. Here, we identified differential methylation in the loci of Il17a, Chn2, Dpp4 and Dclk1.

2013-12-31 | GSE45911 | GEO

TGF-β specifies TFH versus TH17 cell fates in murine CD4+ T cells through c-Maf (Seq02, bulk-RNAseq)

Project description:Naive murine CD4+ T cells from GREAT/SMART-17A mice were cultured under Th1 or Tfh(1 ng/ml TGF-β)-polarizing conditions in 96-well plates coated with anti-CD3/anti-CD28 for 3.5 days; sorted by flow cytometry on IFNg+ (Th1), or CXCR5-IL17A+ (Th17) and CXCR5+IL17A- (Tfh); and subjected to bulk RNA-seq.

2024-03-01 | GSE198374 | GEO

Puniya2021 - Naive CD4+ T cell metabolic model

Project description:CD4+ T cells are critical components in the human immune system. They produce cytokines to fight against pathogens and abnormal cells and stimulate other cells, such as B cells, macrophages, and neutrophils, to generate an immune response. Naive CD4+ T cells are precursor cells that can differentiate into T helper - 1, - 2, - 17 (Th1, Th2, Th17) and regulatory T cells (Tregs) subtypes based on the type of pathogens or disease. The naive CD4+ T cell model consists of 5179 reactions, 3153 metabolites, and 1055 genes. Together with Th1, Th2, and Th17 models, the naive CD4+ T cell model helped identify drug targets and repurposable drugs against autoimmune diseases.

2023-11-27 | MODEL1909260003 | BioModels

Expression data for effector T cells

Project description:In this study, we examined differential gene expression in naïve human CD4+ T cells, as well as in effector Th1, Th17-negative and Th17-enriched CD4- T cell subsets. We observed a marked enrichment for increased gene expression in effector CD4+ T cells compared to naive CD4+ among immune-mediated disease oci genes. Within effector T cells, expression of disease-associated genes was increased in Th17-enriched compared to Th17-negative cells. We used microarray to examine the gene expresssion profile and level of human naïve, Th1 and effector T cell subsets. Human PBMCs were isolated and sorted to naïve, CD161-CCR6- and CD161+CCR6+ memory T cells. Naïve T cells were differentiatied to Th1 cells, and CD161-CCR6- and CD161+CCR6+ memory T cells were in vitro expanded for Th17-negative and Th17-enriched effector T cells. The gene profile was compared among naive, Th1, Th17-negative, and Th17-enriched cell subsets.

2012-05-12 | E-GEOD-32901 | biostudies-arrayexpress

Project Title: Proteome analysis of CD4+ T cell subsets

Project description:Functionally distinct CD4+ helper T (Th) cell subsets, such as Th1, Th2, Th17, and regulatory T cells (Treg), play a pivotal role in the host-defense against pathogen invasion and the pathogenesis of inflammatory disorders. In this project, DIA-MS-based proteome analysis was performed on naïve CD4+ T, Th0, Th1, Th2, Th17 and iTreg cells using Q Exactive HF-X (Thermo Fisher Scientific) to search for proteins that differ among the cell subsets.

2023-01-04 | PXD036065 | JPOST Repository

Transcriptome of CD4+ T cell subsets

Project description:We compared the transcriptome of ex vivo-isolated murine naive CD4+ T cells, Th1 cells and Th17 cells by microarray.

2014-12-31 | GSE58152 | GEO

Expression data for effector T cells

2012-05-13 | GSE32901 | GEO

CD4+ cell transcriptional profiling by RNA sequencing

Project description:<p>We use next generation sequencing to investigate the different transcriptomes of closely related CD4+ T-cells from healthy human donors to elucidate the genetic programs that underlie their specialized immune functions. Six cell types were included: Regulatory T-cells (CD25hiCD127low/neg with >95% FOXP3+ purity), regulatory T-cells activated using PMA/ionomycin, CD25-CD45RA+ ('naive' helper T-cells), CD25-CD45RO+ ('memory' helper T-cells), activated Th17 cells (>98% IL17A+ purity) and activated IL17-CD4+ T-cells (called 'ThPI'). Poly-T capture beads were used to isolate mRNA from total RNA, and fragment sizes of ~200 were sequenced from both ends on Illumina's genome analyzer. We confirm many of the canonical signature genes of T-cell populations, but also discover new genes whose expression is limited to specific CD4 T-cell lineages, including long non-coding RNAs. Additionally, we find that genes encoded at loci linked to multiple human autoimmune diseases are enriched for preferential expression upon T-cell activation, suggesting that an aberrant response to T-cell activation is fundamental to pathogenesis.</p>

| phs000626 | dbGaP

Gene expression data from WT and TET2cKO CD8+ T cells activated in vitro

Project description:The epigenetic modifier TET2 plays a role in cell fate decisions in hematopeotic stem cells and CD4+ Th1 and Th17 differentiation. Here, we demonstrate that loss of TET2 promotes CD8+ memory differentiation following acute viral infection with LCMV-Armstrong. To identify early gene expression changes following TCR activation in WT versus TET2cKO CD8+ T cells, we isolated naive CD8+ T cells and activated them for three days with anti-CD3/CD28+IL-2 and performed microarray analysis.

2017-02-22 | GSE95147 | GEO

CD38-NAD+ Immuno-Metabolic Axis Regulates Potent Anti-Tumor T Response

Project description:Spleens from the B6 mice were isolated and single cell suspension was made. CD4 T cells were purified from the splenocytes using magnetic bead separation. Briefly, Splenocytes were incubated with biotinylated antibody cocktail consisting of antibodies (Biolegend) to CD19, B220, CD11b, CD11c, NK1.1, Gr1, CD25 CD8. After a wash step, cells were incubated with streptavidin conjugated magnetic particles (BD Biosciences). After washing, CD4 T cells were isolated by applying a magnetic field and removing the untouched cells. Purified CD4 T cells were then activated with plate-bound anti-CD3 plus anti-CD28 in presence of either Th1 or Th17 or Th1/17 polarizing condition for 3 days. Total RNA from the 3 days differentiated Th1, Th17 and Th1/17 cells was isolated using mirVana miRNA isolation Kit (Invitrogen).

2017-09-13 | E-MTAB-5237 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data