Soile Tuomela

A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments

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.

Genome-wide Profiling of Interleukin-4 and STAT6 Transcription Factor Regulation of Human Th2 Cell Programming

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.

Genome-Wide Identification of Novel Genes Involved in Early Th1 and Th2 Cell Differentiation

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.

Gene Expression Profiling of Immune-Competent Human Cells Exposed to Engineered Zinc Oxide or Titanium Dioxide Nanoparticles

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.

Th1 Response and Cytotoxicity Genes Are Down-Regulated in Cutaneous T-Cell Lymphoma

Purpose: Increased production of Th2 cytokines characterizes Sezary syndrome, the leukemic form of cutaneous T-cell lymphomas (CTCL). To identify the molecular background and to study whether shared by the most common CTCL subtype, mycosis fungoides, we analyzed the gene expression profiles in both subtypes. Experimental Design: Freshly isolated cells from 30 samples, representing skin, blood, and enriched CD4+ cell populations of mycosis fungoides and Sezary syndrome, were analyzed with Affymetrix (Santa Clara, CA) oligonucleotide microarrays, quantitative PCR, or immunohistochemistry. The gene expression profiles were combined with findings of comparative genomic hybridization of the same samples to identify chromosomal changes affecting the aberrant gene expression. Results: We identified a set of Th1-specific genes [e.g., TBX21 (T-bet), NKG7, and SCYA5 (RANTES)] to be down-regulated in Sezary syndrome as well as in a proportion of mycosis fungoides samples. In both Sezary syndrome and mycosis fungoides blood samples, the S100P and LIR9 gene expression was up-regulated. In lesional skin, IL7R and CD52 were up-regulated. Integration of comparative genomic hybridization and transcriptomic data identified chromosome arms 1q, 3p, 3q, 4q, 12q, 16p, and 16q as likely targets for new CTCL-associated gene aberrations. Conclusions: Our findings revealed several new genes involved in CTCL pathogenesis and potential therapeutic targets. Down-regulation of a set of genes involved in Th1 polarization, including the major Th1-polarizing factor, TBX21, was for the first time associated with CTCL. In addition, a plausible explanation for the proliferative response of CTCL cells to locally produced interleukin-7 was revealed.

SATB1 dictates expression of multiple genes including IL-5 involved in human T helper cell differentiation

Special AT-rich binding protein 1 (SATB1) is a global chromatin organizer and a transcription factor regulated by interleukin-4 (IL-4) during the early T helper 2 (Th2) cell differentiation. Here we show that SATB1 controls multiple IL-4 target genes involved in human Th cell polarization or function. Among the genes regulated by SATB1 is that encoding the cytokine IL-5, which is predominantly produced by Th2 cells and plays a key role in the development of eosinophilia in asthma. We demonstrate that, during the early Th2 cell differentiation, IL-5 expression is repressed through direct binding of SATB1 to the IL-5 promoter. Furthermore, SATB1 knockdown-induced up-regulation of IL-5 is partly counteracted by down-regulating GATA3 expression using RNAi in polarizing Th2 cells. Our results suggest that a competitive mechanism involving SATB1 and GATA3 regulates IL-5 transcription, and provide new mechanistic insights into the stringent regulation of IL-5 expression during human Th2 cell differentiation.

Identification of early gene expression changes during human Th17 cell differentiation

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 IL1β, IL6, and TGFβ. 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.

Quantitative proteomics reveals GIMAP family proteins 1 and 4 to be differentially regulated during human T helper cell differentiation

T helper (Th) cells differentiate into functionally distinct effector cell subsets of which Th1 and Th2 cells are best characterized. Besides T cell receptor signaling, IL-12-induced STAT4 and T-bet- and IL-4-induced STAT6 and GATA3 signaling pathways are the major players regulating the Th1 and Th2 differentiation process, respectively. However, there are likely to be other yet unknown factors or pathways involved. In this study we used quantitative proteomics exploiting cleavable ICAT labeling and LC-MS/MS to identify IL-4-regulated proteins from the microsomal fractions of CD4+ cells extracted from umbilical cord blood. We were able to identify 557 proteins of which 304 were also quantified. This study resulted in the identification of the down-regulation of small GTPases GIMAP1 and GIMAP4 by IL-4 during Th2 differentiation. We also showed that both GIMAP1 and GIMAP4 genes are up-regulated by IL-12 and other Th1 differentiation-inducing cytokines in cells induced to differentiate toward Th1 lineage and down-regulated by IL-4 in cells induced to Th2. Our results indicate that the GIMAP (GTPase of the immunity-associated protein) family of proteins is differentially regulated during Th cell differentiation.

Gut-adipose tissue axis in hepatic fat accumulation in humans

BACKGROUND & AIMS Recent evidence suggests that in animals gut microbiota composition (GMC) affects the onset and progression of hepatic fat accumulation. The aim of this study was to investigate in humans whether subjects with high hepatic fat content (HHFC) differ in their GMC from those with low hepatic fat content (LHFC), and whether these differences are associated with body composition, biomarkers and abdominal adipose tissue inflammation. METHODS Hepatic fat content (HFC) was measured using proton magnetic resonance spectroscopy ((1)H MRS). Fecal GMC was profiled by 16S rRNA fluorescence in situ hybridization and flow cytometry. Adipose tissue gene expression was analyzed using Affymetrix microarrays and quantitative PCR. RESULTS The HHFC group had unfavorable GMC described by lower amount of Faecalibacterium prausnitzii (FPrau) (p<0.05) and relatively higher Enterobacteria than the LHFC group. Metabolically dysbiotic GMC associated with HOMA-IR and triglycerides (p<0.05 for both). Several inflammation-related adipose tissue genes were differentially expressed and correlated with HFC (p<0.05). In addition, the expression of certain genes correlated with GMC dysbiosis, i.e., low FPrau-to-Bacteroides ratio. CONCLUSIONS HHFC subjects differ unfavorably in their GMC from LHFC subjects. Adipose tissue inflammation may be an important link between GMC, metabolic disturbances, and hepatic fat accumulation.

An integrative computational systems biology approach identifies differentially regulated dynamic transcriptome signatures which drive the initiation of human T helper cell differentiation

BackgroundA proper balance between different T helper (Th) cell subsets is necessary for normal functioning of the adaptive immune system. Revealing key genes and pathways driving the differentiation to distinct Th cell lineages provides important insight into underlying molecular mechanisms and new opportunities for modulating the immune response. Previous computational methods to quantify and visualize kinetic differential expression data of three or more lineages to identify reciprocally regulated genes have relied on clustering approaches and regression methods which have time as a factor, but have lacked methods which explicitly model temporal behavior.ResultsWe studied transcriptional dynamics of human umbilical cord blood T helper cells cultured in absence and presence of cytokines promoting Th1 or Th2 differentiation. To identify genes that exhibit distinct lineage commitment dynamics and are specific for initiating differentiation to different Th cell subsets, we developed a novel computational methodology (LIGAP) allowing integrative analysis and visualization of multiple lineages over whole time-course profiles. Applying LIGAP to time-course data from multiple Th cell lineages, we identified and experimentally validated several differentially regulated Th cell subset specific genes as well as reciprocally regulated genes. Combining differentially regulated transcriptional profiles with transcription factor binding site and pathway information, we identified previously known and new putative transcriptional mechanisms involved in Th cell subset differentiation. All differentially regulated genes among the lineages together with an implementation of LIGAP are provided as an open-source resource.ConclusionsThe LIGAP method is widely applicable to quantify differential time-course dynamics of many types of datasets and generalizes to any number of conditions. It summarizes all the time-course measurements together with the associated uncertainty for visualization and manual assessment purposes. Here we identified novel human Th subset specific transcripts as well as regulatory mechanisms important for the initiation of the Th cell subset differentiation.