Identification of Novel Direct Stat3 Target Genes for Control of Growth and Differentiation

Abstract

Signal transducer and activator of transcription 3 (Stat3) is a key regulator of gene expression in response to signaling of the glycoprotein 130 (gp130) family cytokines, including interleukin 6, oncostatin M, and leukemia inhibitory factor. Many efforts have been made to identify Stat3 target genes and to understand the mechanism of how Stat3 regulates gene expression. Using the microarray technique, hundreds of genes have been documented to be potential Stat3 target genes in different cell types. However, only a small fraction of these genes have been proven to be true direct Stat3 target genes. Here we report the identification of novel direct Stat3 target genes using a genome-wide screening procedure based on the chromatin immunoprecipitation method. These novel Stat3 target genes are involved in a diverse array of biological processes such as oncogenesis, cell growth, and differentiation. We show that Stat3 can act as both a repressor and activator on its direct target genes. We further show that most of the novel Stat3 direct target genes are dependent on Stat3 for their transcriptional regulation. In addition, using a physiological cell system, we demonstrate that Stat3 is required for the transcriptional regulation of two of the newly identified direct Stat3 target genes important for muscle differentiation.The signal transducer and activator of transcription (STAT) 2 family of transcriptional regulators is activated in response to extracellular signaling proteins, including cytokines and growth factors (1, 2). When cytokines bind to their cell surface receptors, the receptor-associated JAK tyrosine kinases become activated and in turn phosphorylate a single tyrosine residue in the STAT molecule. The phosphorylated STATs then enter the nucleus as dimers and bind to specific DNA sequences in the promoters of their target genes to regulate transcription. Although the seven members of the STAT family have similarity in their molecular structure and function, they play diverse physiological roles in a wide variety of biological processes (3).One member of the STAT family, Stat3, mediates the signaling of cytokines that share the gp130 receptor chain, which include interleukin-6, oncostatin M (OSM), and leukemia inhibitory factor (LIF) (4, 5). In response to gp130 ligand stimulation, Stat3 is phosphorylated on Tyr-705 and forms dimers through phosphotyrosine-Src homology 2 domain interactions (6). The dimerized Stat3 molecules enter the nucleus and bind to a consensus DNA sequence in the promoters of its target genes to regulate transcription (7). The transcriptional activity of Stat3 is mediated by its transcription activation domain located in the carboxyl-terminal end of the molecule (8). In addition to the tyrosine phosphorylation, the Stat3 transcription activation domain contains a serine residue (Ser-724) that is also phosphorylated to achieve maximum transcription activity (9, 10). Analyses of Stat3-dependent enhancersomes demonstrate that Stat3 interacts and recruits other transcription factors and ...

ER stress transcription factor Xbp1 suppresses intestinal tumorigenesis and directs intestinal stem cells

“…Total Stat3 as well as Jak1 and Jak2 was also increased (Fig. 3 A), which might reflect the known capacity of Stat3 to bind its own promoter and to transactivate its transcription (Narimatsu et al, 2001;Lam et al, 2008;Snyder et al, 2008). Increased p-Stat3 was independent of Ire1 as Xbp1 /(IEC) ;Ern1 /(IEC) and Xbp1 /(IEC) ;Ern1 +/+(IEC) epithelia exhibited similar levels (Fig.…”

Genome-wide discovery of functional transcription factor binding sites by comparative genomics: The case of Stat3

“…Indeed, even with the stringent score cutoff imposed, there was a high degree of overlap between the target genes Table 2. The names and gene IDs of the top-10 predicted Stat3-BSs ranked according to phylogenetic conservation and calculated binding score associated to our CBSs and those identified by ChIP methods in 2 distinct cellular systems (13,14), testifying to the validity of our approach. The lists of CBSs generated with our method will be a powerful tool to rapidly identify bona fide TF targets in any given cell system for which relevant gene expression data are available.…”

“…We identified the genes associated to the in vivo-bound genomic sequences reported by Chen et al (13) as described in SI Material and Methods, obtaining a list of 1,575 genes. This was compared with the 146 target genes reported by Snyder et al (14). The overlap resulted in only 17 genes.…”

“…In contrast, the overlap between either experimental set and the genes associated to Stat3-BSs conserved between mouse and at least one other species resulted in 1,155 (73%) and 118 (81%) of the genes found by Chen et al (13) or Snyder et al (14), respectively. When considering only sites conserved in at least 2 other species, we retrieved 811 (51%) and 83 (57%) of the targets identified by Chen et al (13) and Snyder et al (14), respectively. This supports the idea that data obtained in different biological systems display very limited overlap, in agreement with the knowledge that Stat3 can induce distinct target genes in different tissues/conditions.…”

“…To assess the validity of our method compared with the more direct ChIP and sequencing approach, we compared the evolutionary conserved BSs identified above with 2 recently reported experimental datasets obtained by measuring Stat3 occupancy in vivo in ES cells and 3T3 fibroblasts, respectively (13,14). We identified the genes associated to the in vivo-bound genomic sequences reported by Chen et al (13) as described in SI Material and Methods, obtaining a list of 1,575 genes.…”