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.
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:Disturbed expression of microRNAs (miRNAs) in regulatory T-cells (Tregs) leads to development of autoimmunity in experimental mouse models. However, the miRNA expression signature characterizing Tregs of autoimmune diseases, such as rheumatoid arthritis (RA) has not been determined yet. Moreover, the technical limitations prevented the analysis of such minute T-cell population as naive and memory Tregs. In this study we have used a microarray approach to comprehensively analyze miRNA expression signatures of naive Tregs (CD4+CD45RO-CD25++), memory Tregs (CD4+CD45RO+CD25+++), as well as conventional naive (CD4+CD45RO-CD25-) and memory (CD4+CD45RO+CD25-) T-cells (Tconvs) derived from peripheral blood of RA patients, and matched healthy controls. Differential expression of selected miRNAs was validated by TaqMan-based qRT-PCR. We found a positive correlation between increased expression of miR-451 in T-cells of RA patients and disease activity score (DAS28), ESR levels, and serum levels of IL-6. Moreover, we found characteristic, disease and treatment independent, global miRNA expression signatures defining naive Tregs, memory Tregs, naive Tconvs and memory Tconvs. The analysis allowed us to define miRNAs characteristic for a general naive phenotype (e.g. miR-92a), a general memory phenotype (e.g. miR-21, miR-155), and most importantly miRNAs specifically expressed in both naive and memory Tregs, defining as such the Treg phenotype (i.e. miR-146a, miR-3162, miR-1202, miR-1246a, and miR-4281). MicroRNA profiling was performed in four CD4+ T-cell subsets: naive Tconventional (CD3+CD8-CD45RO-CD25-), naive Tregulatory (CD3+CD8-CD45RO-CD25+), memory Tconventional (CD3+CD8-CD45RO+CD25-), and memory Tregulatory (CD3+CD8-CD45RO+CD25+) derived from 2 healthy controls, and 6 rheumatoid arthritis patients (total n=8).
Project description:TIGIT+ Tregs suppress Th1 and Th17 responses while sparing Th2 responses. Analysis of global gene expression of TIGIT+ vs. TIGIT- Tregs from naive mice reveled that TIGIT+ Tregs display an activated phenotype and are enriched for Treg signature genes including the Treg effector molecule Fgl2 which enables them to selectively spare Th2 responses. TIGIT+ and TIGIT- Tregs were sorted from naïve Foxp3-GFP KI mice (pooled spleen and lymph nodes) TIGIT: T cell immunoreceptor with Ig and ITIM domains
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:We used microarray to compare gene expression between CD161++/CD161+/CD161-CD8+ T cells from human cord blood. Lymphocytes from freshly obtained human cord blood samples were isolated by Ficoll density centrifugation. CD8+ T cells were purified by negative selection using magnetic beads and subsequently labelled with fluorescent antibodies prior to sorting using MoFlo MLS cell sorter (Dako).