Dissecting the molecular mechanisms by which T helper (Th) cells differentiate to effector Th2 cells is important for understanding the pathogenesis of immune-mediated diseases, such as asthma and allergy. Because the STAT6 transcription factor is an upstream mediator required for interleukin-4 (IL-4)-induced Th2 cell differentiation, its targets include genes important for this process. Using primary human CD4(+) T cells, and by blocking STAT6 with RNAi, we identified a number of direct and indirect targets of STAT6 with ChIP sequencing. The integration of these data sets with detailed kinetics of IL-4-driven transcriptional changes showed that STAT6 was predominantly needed for the activation of transcription leading to the Th2 cell phenotype. This integrated genome-wide data on IL-4- and STAT6-mediated transcription provide a unique resource for studies on Th cell differentiation and, in particular, for designing interventions of human Th2 cell responses.

BackgroundChromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-seq) is increasingly being applied to study transcriptional regulation on a genome-wide scale. While numerous algorithms have recently been proposed for analysing the large ChIP-seq datasets, their relative merits and potential limitations remain unclear in practical applications.ResultsThe present study compares the state-of-the-art algorithms for detecting transcription factor binding sites in four diverse ChIP-seq datasets under a variety of practical research settings. First, we demonstrate how the biological conclusions may change dramatically when the different algorithms are applied. The reproducibility across biological replicates is then investigated as an internal validation of the detections. Finally, the predicted binding sites with each method are compared to high-scoring binding motifs as well as binding regions confirmed in independent qPCR experiments.ConclusionsIn general, our results indicate that the optimal choice of the computational approach depends heavily on the dataset under analysis. In addition to revealing valuable information to the users of this technology about the characteristics of the binding site detection approaches, the systematic evaluation framework provides also a useful reference to the developers of improved algorithms for ChIP-seq data.

The development of therapeutic strategies to combat immune-associated diseases requires the molecular mechanisms of human Th17 cell differentiation to be fully identified and understood. To investigate transcriptional control of Th17 cell differentiation, we used primary human CD4 T cells in small interfering RNA (siRNA)-mediated gene silencing and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) to identify both the early direct and indirect targets of STAT3. The integrated dataset presented in this study confirms that STAT3 is critical for transcriptional regulation of early human Th17 cell differentiation. Additionally, we found that a number of SNPs from loci associated with immune-mediated disorders were located at sites where STAT3 binds to induce Th17 cell specification. Importantly, introduction of such SNPs alters STAT3 binding in DNA affinity precipitation assays. Overall, our study provides important insights for modulating Th17-mediated pathogenic immune responses in humans.

A comprehensive in vitro assessment of two commercial metal oxide nanoparticles, TiO2 and ZnO, was performed using human monocyte-derived macrophages (HMDM), monocyte-derived dendritic cells (MDDC), and Jurkat T cell leukemia-derived cell line. TiO2 nanoparticles were found to be non-toxic whereas ZnO nanoparticles caused dose-dependent cell death. Subsequently, global gene expression profiling was performed to identify transcriptional response underlying the cytotoxicity caused by ZnO nanoparticles. Analysis was done with doses 1 µg/ml and 10 µg/ml after 6 and 24 h of exposure. Interestingly, 2703 genes were significantly differentially expressed in HMDM upon exposure to 10 µg/ml ZnO nanoparticles, while in MDDCs only 12 genes were affected. In Jurkat cells, 980 genes were differentially expressed. It is noteworthy that only the gene expression of metallothioneins was upregulated in all the three cell types and a notable proportion of the genes were regulated in a cell type-specific manner. Gene ontology analysis revealed that the top biological processes disturbed in HMDM and Jurkat cells were regulating cell death and growth. In addition, genes controlling immune system development were affected. Using a panel of modified ZnO nanoparticles, we obtained an additional support that the cellular response to ZnO nanoparticles is largely dependent on particle dissolution and show that the ligand used to modify ZnO nanoparticles modulates Zn2+ leaching. Overall, the study provides an extensive resource of transcriptional markers for mediating ZnO nanoparticle-induced toxicity for further mechanistic studies, and demonstrates the value of assessing nanoparticle responses through a combined transcriptomics and bioinformatics approach.

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Th cell subtypes, Th1 and Th2, are involved in the pathogenesis or progression of many immune-mediated diseases, such as type 1 diabetes and asthma, respectively. Defining the molecular networks and factors that direct Th1 and Th2 cell differentiation will help to understand the pathogenic mechanisms causing these diseases. Some of the key factors regulating this differentiation have been identified, however, they alone do not explain the process in detail. To identify novel factors directing the early differentiation, we have studied the transcriptomes of human Th1 and Th2 cells after 2, 6, and 48 h of polarization at the genome scale. Based on our current and previous studies, 288 genes or expressed sequence tags, representing ∼1–1.5% of the human genome, are regulated in the process during the first 2 days. These transcriptional profiles revealed genes coding for components of certain pathways, such as RAS oncogene family and G protein-coupled receptor signaling, to be differentially regulated during the early Th1 and Th2 cell differentiation. Importantly, numerous novel genes with unknown functions were identified. By using short-hairpin RNA knockdown, we show that a subset of these genes is regulated by IL-4 through STAT6 signaling. Furthermore, we demonstrate that one of the IL-4 regulated genes, NDFIP2, promotes IFN-γ production by the polarized human Th1 lymphocytes. Among the novel genes identified, there may be many factors that play a crucial role in the regulation of the differentiation process together with the previously known factors and are potential targets for developing therapeutics to modulate Th1 and Th2 responses.

Th17 cells play an essential role in the pathogenesis of autoimmune and inflammatory diseases. Most of our current understanding on Th17 cell differentiation relies on studies carried out in mice, whereas the molecular mechanisms controlling human Th17 cell differentiation are less well defined. In this study, we identified gene expression changes characterizing early stages of human Th17 cell differentiation through genome-wide gene expression profiling. CD4 ؉ cells isolated from umbilical cord blood were used to determine detailed kinetics of gene expression after initiation of Th17 differentiation with IL1␤, IL6, and TGF␤. The differential expression of selected candidate genes was further validated at protein level and analyzed for specificity in initiation of Th17 compared with initiation of other Th subsets, namely Th1, Th2, and iTreg. This first genome-wide profiling of transcriptomics during the induction of human Th17 differentiation provides a starting point for defining gene regulatory networks and identifying new candidates regulating Th17 differentiation in humans. (Blood. 2012;119(23):e151-e160) IntroductionNaive CD4 ϩ T cells differentiate into functionally distinct lineages in response to environmental cues and interaction with APCs. The nature of invading pathogens determines the cytokine environment in which the cognate Ag recognition by TCR takes place, subsequently influencing the phenotype of differentiating CD4 ϩ Th cells. Classically, presentation of intra-or extracellular pathogens to naive T cells leads to either a Th1 response or a Th2 response, respectively. 1 Today, new functionally distinct subtypes of CD4 ϩ have been identified. 2 Since the original identification of IL17-secreting T cells, 3 further research has led to the definition of an effector Th17 cell lineage. [4][5][6] Shortly after these findings, Th17 cells were characterized also in humans by using peripheral blood T cells and T-cell clones derived from gut tissue of patients having Crohn disease. [7][8][9] Human Th17 cells express CCR6, CCR4, IL23R, and CD161 on their cell membrane. 9,10 The characteristic cytokine secreted by these cells is IL17A (also referred to as IL17). IL17A stimulates the secretion of wide range of proinflammatory chemokines and cytokines. As its receptor is widely expressed, many cells of the immune system as well as other cell types can respond to it. 11 In addition to IL17A, cytokines IL17F, IFN␥, IL22, and IL26 have been shown to be secreted by human Th17 cells. 7 Proper function of Th17 cells is needed for eradication of extracellular bacterial and fungal infections. 11 CD4 ϩ cells isolated from peripheral or cord blood have been used to examine Th17 polarization in human. In several studies, differentiation of naive cells from peripheral blood has not succeeded, or the IL17A production has been markedly less efficient than detected by memory cells. IL17A secretion of polarized cord blood cells is also modest. 12 Human Th17 cells have also been shown to originate from CD161 ϩ precursor cells...

The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding autoantibody positivity or reflect progressive β-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4−CD8− cell fractions and unfractionated peripheral blood mononuclear cell samples longitudinally collected from seven children who developed β-cell autoimmunity (case subjects) at a young age and matched control subjects. We identified transcripts, including interleukin 32 (IL32), that were upregulated before T1D-associated autoantibodies appeared. Single-cell RNA sequencing studies revealed that high IL32 in case samples was contributed mainly by activated T cells and NK cells. Further, we showed that IL32 expression can be induced by a virus and cytokines in pancreatic islets and β-cells, respectively. The results provide a basis for early detection of aberrations in the immune system function before T1D and suggest a potential role for IL32 in the pathogenesis of T1D.