Project description:Human FOXP3+CD25+CD4+ regulatory T cells (Tregs) play a dominant role in the maintenance of immune homeostasis. Several genes are known to be important for murine Tregs, but for human Tregs the genes and underlying molecular networks controlling the suppressor function still largely remain unclear. We here performed a high-time-resolution dynamic analysis of the transcriptome during the very early phase of human Treg/ CD4+ T-effector cell activation. After constructing a correlation network specific for Tregs based on these dynamic data, we described a strategy to identify key genes by directly analyzing the constructed undirected correlation network. Six out of the top 10 ranked key hubs are known to be important for Treg function or involved in autoimmune diseases. Surprisingly, PLAU (the plasminogen activator urokinase) was among the 4 new key hubs. We here show that PLAU was critical for expression regulation of FOXP3, EOS and several other important Treg genes and the suppressor function of human Tregs. Moreover, we found Plau inhibits murine Treg development and but promotes the suppressive function. Further analysis unveils that PLAU is particularly important for memory Tregs and that PLAU mediates Treg suppressor function via STAT5 and ERK signaling pathways. Our study shows the potential for identifying novel key genes for complex dynamic biological processes using a network strategy based on high-time-resolution data, and highlights a critical role of PLAU in both human and murine Tregs. The construction of a dynamic correlation network of human Tregs provides a useful resource for the understanding of Treg function and human autoimmune diseases. The high-time-resolution time-series transcriptomic data during the very early phase of human Treg/Teff activation could be generally used for further mechanistic analysis of human Treg function. These data could be further used for biological network analysis, dynamic analysis, modeling by experimental researchers, bioinformaticians, computational biologists and systems biologists. We have measured the genome-wide expression of 38,500 genes (probes) by performing a high-time-resolution time-series analysis during the activation process of human regulatory T cells /CD4+ T-effector cells at 19 time points for the first 6h with an equal interval of 20 min. We have also overexpressed the GARP gene in human effector T cells and measured the genome-scale expression for the GARP-overexpressed cells and ThGFP cells at time point 0, 100 and 360min following activation. The stimulation source used in this work is a combination of anti-CD3/-CD28 Dynal beads with IL2 100U/ml.

Project description:Though T cell expansion and effector differentiation are triggered and, perhaps, maintained by antigen, the proliferative behaviors of CD4+ and CD8+ T cells responding to timed antigen presentation have rarely been compared side by side. Proliferation and effector differentiation of TCR transgenic and polyclonal T cells were analyzed following transient and continuous TCR signals. We found CD4+ T cell proliferation to be dependent on prolonged antigen presence, whereas CD8+ T cells were able to divide and differentiate into effector cells in the absence of it. We excluded CD4+ T cell proliferation to be abrogated by coinhibitory signals or the lack of inflammatory stimuli and found that autonomous proliferation of CD8* T cells was independent of any MHC class I signals. Gene expression analyses illustrated differences in global gene transcription between the two subsets following stimulation periods of different lengths. These T cell data reflect the MHC class difference in that class II but not class I molecules were stabilized on activated DCs in vivo, suggesting a coevolution of MHC molecules and their respective T cell subsets. Samples 1-12: Analysis on day 2. Purified CD4+ AND-TCR transgenic cells andÂ CD8+ OT1-TCR transgenic cells were separately stimulated with anti-CD3 and anti-CD28 antibodies. 48 hours later, the cells were sorted again to a purity of >99 %. Extracted total RNA was amplified twice and hybridized on Affymetrix Mouse 430A2 microarrays. First, we analysed the changes of the CD4+ and CD8+ T cells after stimulation. Second, we compared the differences of the changes between the two cell types after stimulation. For each of the four groups (CD4+ and CD8+, stimulated and unstimulated), we analysed three independent biological replicates. Samples 13-28: Analysis on day 5. AND and OT1 TCR-transgenic T cells were prepared as described before, but transferred into mice that do not or do present their respective antigens. 72 hours later, the cells were FACS-sorted twice to >99 % purity, directly into Trizol. For each of the six groups (CD4+ and CD8+, unstimulated, transient (2 days) and continuous (5 days) stimulation), three independent biological replicates were analyzed, except for CD4+ unstimulated and CD4+ transient, with two replicates each.

Dataset Information

Sequence analysis of CD4 Treg, CD8 Treg and CD8 effector

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