Project description:Differentiation of CD4+T-cells into effector subsets is a critical component of the adaptive immune system and an incorrect response can lead to autoimmunity or immune deficiency. Cellular differentiation including T-cell differentiation is accompanied by large-scale epigenetic remodeling, including changes in DNA methylation at key regulators of T-cell differentiation. The TET family of enzymes were recently shown to be able to catalyse methylated cytosine (5mC) into 5-hydroxymethylcytosine (5hmC) enabling a pathway of active removal of DNA methylation. Here, we characterize 5hmC, 5mC and transcriptional dynamics during human CD4+T-cell polarisation in a time series approach and relate these changes to profiles in ex-vivo CD4+memory subsets. We observed large-scale remodelling during early CD4+T-cell differentiation which was predictive of subsequent changes during late time points, these changes were also related to disease associated regions which we show can act as functional regulatory elements. This dataset was designed to assess how gene expression changes over time during human CD4+T-cell polarization towards Th1 and Th2. Gene expression was assessed in relationship to 5hmC and DNA methylation levels and changes (see data series), we observed characteristic gene expression for the specific time points and stimuli or cell type and the expression was correlated with gene body 5hmC as well as anticorrelated with promoter DNA methylation levels. This submission contains data from transcription profiling by array of human CD4+T-cells, Th1/Th2 polarized time-series and primary memory subsets. It is part of series containing 5hmC and DNA methylation profiling of the same samples. See related experiments E-MTAB-4685, E-MTAB-4686, E-MTAB-4688, E-MTAB-4689.
Project description:Differentiation of CD4+T-cells into effector subsets is a critical component of the adaptive immune system and an incorrect response can lead to autoimmunity or immune deficiency. Cellular differentiation including T-cell differentiation is accompanied by large-scale epigenetic remodeling, including changes in DNA methylation at key regulators of T-cell differentiation. The TET family of enzymes were recently shown to be able to catalyse methylated cytosine (5mC) into 5-hydroxymethylcytosine (5hmC) enabling a pathway of active removal of DNA methylation. Here, we characterize 5hmC, 5mC and transcriptional dynamics during human CD4+T-cell polarisation in a time series approach and relate these changes to profiles in ex-vivo CD4+memory subsets. We observed large-scale remodelling during early CD4+T-cell differentiation which was predictive of subsequent changes during late time points, these changes were also related to disease associated regions which we show can act as functional regulatory elements. This dataset was designed to assess how DNA methylation differs between in-vivo derived CD4+memory T-cell subsets. DNA methylation was assessed in relationship to gene expression levels and changes (see data series), we observed anticorrelation between promoter DNA methylation levels and gene expression. This submission contains data from DNA methylation profiling of primary human CD4+T-cell memory subsets. This is part of a series, containing transcription and DNA methylation profiling of the same samples. See related experiments E-MTAB-4685, E-MTAB-4686, E-MTAB-4687, E-MTAB-4688
Project description:Differentiation of CD4+T-cells into effector subsets is a critical component of the adaptive immune system and an incorrect response can lead to autoimmunity or immune deficiency. Cellular differentiation including T-cell differentiation is accompanied by large-scale epigenetic remodeling, including changes in DNA methylation at key regulators of T-cell differentiation. The TET family of enzymes were recently shown to be able to catalyse methylated cytosine (5mC) into 5-hydroxymethylcytosine (5hmC) enabling a pathway of active removal of DNA methylation. Here, we characterize 5hmC, 5mC and transcriptional dynamics during human CD4+T-cell polarisation in a time series approach and relate these changes to profiles in ex-vivo CD4+memory subsets. We observed large-scale remodelling during early CD4+T-cell differentiation which was predictive of subsequent changes during late time points, these changes were also related to disease associated regions which we show can act as functional regulatory elements. This dataset was designed to assess how TET1 affects gene expression during human CD4+T-cell differentiation. We observed that TET1 was highly expressed in primary lymphocytes compared to other human tissues and loss of TET1 gene expression was seen within 6 hours of naïve CD4+T-cell activation. Primary human naïve T-cells were transfected with different TET1 containing plasmids and polarized towards Th1 for 24h. When comparing cells transfected with full length TET1 to catalytically inactive TET1, we observed mis-expression of several cytokine/chemokine genes related to T-cell differentiation. This was not observed for cells expressing the catalytic domain of TET1. Note that the expression array only targets the DNA binding domain of the TET1 gene, therefore we validated ectopic expression of TET1 by qPCR targeting the catalytic domain. This submission contains data from Transcription profiling by array of primary human CD4+T-cells overexpressing TET1 polarized towards Th1. See related experiments: E-MTAB-4686, E-MTAB-4687, E-MTAB-4688, E-MTAB-4689.
Project description:Differentiation of CD4+T-cells into effector subsets is a critical component of the adaptive immune system and an incorrect response can lead to autoimmunity or immune deficiency. Cellular differentiation including T-cell differentiation is accompanied by large-scale epigenetic remodeling, including changes in DNA methylation at key regulators of T-cell differentiation. The TET family of enzymes were recently shown to be able to catalyse methylated cytosine (5mC) into 5-hydroxymethylcytosine (5hmC) enabling a pathway of active removal of DNA methylation. Here, we characterize 5hmC, 5mC and transcriptional dynamics during human CD4+T-cell polarisation in a time series approach and relate these changes to profiles in ex-vivo CD4+memory subsets. We observed large-scale remodelling during early CD4+T-cell differentiation which was predictive of subsequent changes during late time points, these changes were also related to disease associated regions which we show can act as functional regulatory elements. This dataset was designed to assess how gene expression changes over time during human CD4+T-cell polarization towards Th1 and Th2. DNA methylation was assessed in relationship to 5hmC levels and changes (see data series), we observed that regions gaining 5hmC early was highly predictive of regions losing DNA methylation during late time points. This submission contains data from the DNA methylation by array profiling of human CD4+T-cells in-vitro polarized towards Th1 and Th2 time-series. It is part of series containing 5hmC and DNA methylation profiling of the same samples. See related experiments E-MTAB-4685, E-MTAB-4686, E-MTAB-4687, E-MTAB-4689.
Project description:Differentiation of CD4+T-cells into effector subsets is a critical component of the adaptive immune system and an incorrect response can lead to autoimmunity or immune deficiency. Cellular differentiation including T-cell differentiation is accompanied by large-scale epigenetic remodeling, including changes in DNA methylation at key regulators of T-cell differentiation. The TET family of enzymes were recently shown to be able to catalyse methylated cytosine (5mC) into 5-hydroxymethylcytosine (5hmC) enabling a pathway of active removal of DNA methylation. Here, we characterize 5hmC, 5mC and transcriptional dynamics during human CD4+T-cell polarisation in a time series approach and relate these changes to profiles in ex-vivo CD4+memory subsets. We observed large-scale remodelling during early CD4+T-cell differentiation which was predictive of subsequent changes during late time points, these changes were also related to disease associated regions which we show can act as functional regulatory elements. This dataset was designed to assess how 5-hydroxymethylcytosine (5hmC) changes over time during human CD4+T-cell polarization towards Th1 and Th2. We tested an early (1 day) and late (5 day) timepoint to distinguish between replication-independent (early) and replication-dependent (late) changes. When comparing the time-series profiles, we observed an early gain followed by a late loss of 5hmC suggesting active 5hmC remodelling precedes lineage specification in CD4+T-cells. This submission contains the data from genome-wide 5-hydroxymethylcytosine (5hmC) profiling by hMeDIP-seq in primary human CD4+T-cells polarized towards Th1 and Th2 time-series. This submission is part of series containing 5hmC and DNA methylation profiling of the same samples. See related experiments E-MTAB-4685, E-MTAB-4687, E-MTAB-4688, E-MTAB-4689.
Project description:Host defense against diverse pathogens involves the recruitment and differentiation of CD4+ T effector subsets including T helper 1 (Th1), Th2, Th17 and induced regulatory T (Treg) cells. Surface phenotype studies have revealed subset-specific surface markers for the identification and purification of human primary CD4+ T effector subsets. In the present study, we aimed to characterize the mRNA and large intergenic non-coding RNA (lincRNA) expression differences between human primary CD4+ T effector subsets and identify potential subset-specific genes. To achieve this goal, mRNA and lincRNA microarray profiling of flow cytometry-sorted human primary Th1, Th2, Th17 and Treg cells was performed. Principal component and pathway analyses revealed subset-specific gene expression patterns. A Th2-specific lincRNA, GATA3-AS1, also termed FLJ45983, was identified in primary immune cells and tissues, as well as in in vitro polarized CD4+ T effector subsets. Further analysis showed that GATA3-AS1 was a potential diagnostic marker in allergy, a Th2-associated disease. This first systematic genome-wide analysis of gene expression differences between primary CD4+ T effector subsets may help to identify novel regulatory protein-coding genes and lincRNAs regulating CD4+ T cell subset differentiation, as well as potential diagnostic markers. As an example, we identified a GATA3-associated Th2-specific marker lincRNA GATA3-AS1. Gene expression microarray analysis of flow-cytometry sorted human primary naïve CD4+ T cells, CD4+ T central memory cells, Th1, Th2, Th17 and Treg cells from buffy coat of four healthy controls Gene expression microarray analysis was performed using SurePrint G3 Human Gene Expression 8X60K microarray.
Project description:Gene expression data of primary human naive and memory CD4+T lymphocytes purified from peripheral blood are generated to be analyzed in different ways such as for traditional searching of differentially expressed genes between the two cell subsets or in combination to in-silico data of microRNAs target prediction for microRNAs known to be characteristically expressed in the two cell subsets. Two cell subsets (cell types) FACS purified from peripheral blood of six samples/healthy donors (samples #3,5,6,7,026,065). Naive CD4+ T cells were extracted from all 6 samples and 6 biological replicas were obtained (3N, 5N, 6N, 7N, 026N, 065N), while memory CD4+T cells were extracted from 4 samples and 4 biological replicas were obtained (3m, 5m, 6m, 7m). Both naive and memory replicas from samples 3, 5, 6 and 7 were hybridized onto two beadsarrays each while those from samples 026 and 065 were hybridized on 1 beadsarray each (for a total of 18 beadsarrays used). For analysis purposes naive cells samples 3N, 5N, 6N and 7N can be considered paired with memory samples 3m, 5m, 6m and 7m respectively, since they are obtained from the same blood samples/healthy donors.
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: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.
Project description:Interventions: Group A:Carbohydrates + early postoperative enteral nutrition;Group B:Carbohydrate;Group C:Perioperative routine management
Primary outcome(s): Quality of life assessment;Nutritional risk screening (NRS-2002 scale);Human body composition analysis and determination;Time of first postoperative exhaust and defecation;Postoperative complications and length of stay;T lymphocyte subsets (CD4+, CD8+)
Study Design: Parallel