35 resultados para Paired Box Transcription Factors

em Duke University


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High-grade Brainstem Glioma (BSG), also known as Diffuse Intrinsic Pontine Glioma (DIPG), is an incurable pediatric brain cancer. Increasing evidence supports the existence of regional differences in gliomagenesis such that BSG is considered a distinct disease from glioma of the cerebral cortex (CG). In an effort to elucidate unique characteristics of BSG, we conducted expression analysis of mouse PDGF-B-driven BSG and CG initiated in Nestin progenitor cells and identified a short list of expression changes specific to the brainstem gliomagenesis process, including abnormal upregulation of paired box 3 (Pax3). In the neonatal mouse brain, Pax3 expression marks a subset of brainstem progenitor cells, while it is absent from the cerebral cortex, mirroring its regional expression in glioma. Ectopic expression of Pax3 in normal brainstem progenitors in vitro shows that Pax3 inhibits apoptosis. Pax3-induced inhibition of apoptosis is p53-dependent, however, and in the absence of p53, Pax3 promotes proliferation of brainstem progenitors. In vivo, Pax3 enhances PDGF-B-driven gliomagenesis by shortening tumor latency and increasing tumor penetrance and grade, in a region-specific manner, while loss of Pax3 function extends survival of PDGF-B-driven;p53-deficient BSG-bearing mice by 33%. Importantly, Pax3 is regionally expressed in human glioma as well, with high PAX3 mRNA characterizing 40% of human BSG, revealing a subset of tumors that significantly associates with PDGFRA alterations, amplifications of cell cycle regulatory genes, and is exclusive of ACVR1 mutations. Collectively, these data suggest that regional Pax3 expression not only marks a novel subset of BSG but also contributes to PDGF-B-induced brainstem gliomagenesis.

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Transient overexpression of defined combinations of master regulator genes can effectively induce cellular reprogramming: the acquisition of an alternative predicted phenotype from a differentiated cell lineage. This can be of particular importance in cardiac regenerative medicine wherein the heart lacks the capacity to heal itself, but simultaneously contains a large pool of fibroblasts. In this study we determined the cardio-inducing capacity of ten transcription factors to actuate cellular reprogramming of mouse embryonic fibroblasts into cardiomyocyte-like cells. Overexpression of transcription factors MYOCD and SRF alone or in conjunction with Mesp1 and SMARCD3 enhanced the basal but necessary cardio-inducing effect of the previously reported GATA4, TBX5, and MEF2C. In particular, combinations of five or seven transcription factors enhanced the activation of cardiac reporter vectors, and induced an upregulation of cardiac-specific genes. Global gene expression analysis also demonstrated a significantly greater cardio-inducing effect when the transcription factors MYOCD and SRF were used. Detection of cross-striated cells was highly dependent on the cell culture conditions and was enhanced by the addition of valproic acid and JAK inhibitor. Although we detected Ca(2+) transient oscillations in the reprogrammed cells, we did not detect significant changes in resting membrane potential or spontaneously contracting cells. This study further elucidates the cardio-inducing effect of the transcriptional networks involved in cardiac cellular reprogramming, contributing to the ongoing rational design of a robust protocol required for cardiac regenerative therapies.

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Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.

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Animal growth and development depend on the precise control of gene expression at the level of transcription. A central role in the regulation of developmental transcription is attributed to transcription factors that bind DNA enhancer elements, which are often located far from gene transcription start sites. Here, we review recent studies that have uncovered significant regulatory functions in developmental transcription for the TFIID basal transcription factors and for the DNA core promoter elements that are located close to transcription start sites.

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Recent genomic analyses suggest the importance of combinatorial regulation by broadly expressed transcription factors rather than expression domains characterized by highly specific factors.

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Neurodegenerative diseases such as Huntington disease are devastating disorders with no therapeutic approaches to ameliorate the underlying protein misfolding defect inherent to poly-glutamine (polyQ) proteins. Given the mounting evidence that elevated levels of protein chaperones suppress polyQ protein misfolding, the master regulator of protein chaperone gene transcription, HSF1, is an attractive target for small molecule intervention. We describe a humanized yeast-based high-throughput screen to identify small molecule activators of human HSF1. This screen is insensitive to previously characterized activators of the heat shock response that have undesirable proteotoxic activity or that inhibit Hsp90, the central chaperone for cellular signaling and proliferation. A molecule identified in this screen, HSF1A, is structurally distinct from other characterized small molecule human HSF1 activators, activates HSF1 in mammalian and fly cells, elevates protein chaperone expression, ameliorates protein misfolding and cell death in polyQ-expressing neuronal precursor cells and protects against cytotoxicity in a fly model of polyQ-mediated neurodegeneration. In addition, we show that HSF1A interacts with components of the TRiC/CCT complex, suggesting a potentially novel regulatory role for this complex in modulating HSF1 activity. These studies describe a novel approach for the identification of new classes of pharmacological interventions for protein misfolding that underlies devastating neurodegenerative disease.

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BACKGROUND: SOX2 (Sry-box 2) is required to maintain a variety of stem cells, is overexpressed in some solid tumors, and is expressed in epithelial cells of the lung. METHODOLOGY/PRINCIPAL FINDINGS: We show that SOX2 is overexpressed in human squamous cell lung tumors and some adenocarcinomas. We have generated mouse models in which Sox2 is upregulated in epithelial cells of the lung during development and in the adult. In both cases, overexpression leads to extensive hyperplasia. In the terminal bronchioles, a trachea-like pseudostratified epithelium develops with p63-positive cells underlying columnar cells. Over 12-34 weeks, about half of the mice expressing the highest levels of Sox2 develop carcinoma. These tumors resemble adenocarcinoma but express the squamous marker, Trp63 (p63). CONCLUSIONS: These findings demonstrate that Sox2 overexpression both induces a proximal phenotype in the distal airways/alveoli and leads to cancer.

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The brain is a highly adaptable organ that is capable of converting sensory information into changes in neuronal function. This plasticity allows behavior to be accommodated to the environment, providing an important evolutionary advantage. Neurons convert environmental stimuli into long-lasting changes in their physiology in part through the synaptic activity-regulated transcription of new gene products. Since the neurotransmitter-dependent regulation of Fos transcription was first discovered nearly 25 years ago, a wealth of studies have enriched our understanding of the molecular pathways that mediate activity-regulated changes in gene transcription. These findings show that a broad range of signaling pathways and transcriptional regulators can be engaged by neuronal activity to sculpt complex programs of stimulus-regulated gene transcription. However, the shear scope of the transcriptional pathways engaged by neuronal activity raises the question of how specificity in the nature of the transcriptional response is achieved in order to encode physiologically relevant responses to divergent stimuli. Here we summarize the general paradigms by which neuronal activity regulates transcription while focusing on the molecular mechanisms that confer differential stimulus-, cell-type-, and developmental-specificity upon activity-regulated programs of neuronal gene transcription. In addition, we preview some of the new technologies that will advance our future understanding of the mechanisms and consequences of activity-regulated gene transcription in the brain.

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The mechanisms involved in the recognition of microbial pathogens and activation of the immune system have been extensively studied. However, the mechanisms involved in the recovery phase of an infection are incompletely characterized at both the cellular and physiological levels. Here, we establish a Caenorhabditis elegans-Salmonella enterica model of acute infection and antibiotic treatment for studying biological changes during the resolution phase of an infection. Using whole genome expression profiles of acutely infected animals, we found that genes that are markers of innate immunity are down-regulated upon recovery, while genes involved in xenobiotic detoxification, redox regulation, and cellular homeostasis are up-regulated. In silico analyses demonstrated that genes altered during recovery from infection were transcriptionally regulated by conserved transcription factors, including GATA/ELT-2, FOXO/DAF-16, and Nrf/SKN-1. Finally, we found that recovery from an acute bacterial infection is dependent on ELT-2 activity.

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DNaseI footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High-throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. Multiple computational approaches have been developed to identify DNase-seq footprints as predictors of TF binding. However, recent studies have pointed to a substantial cleavage bias of DNase and its negative impact on predictive performance of footprinting. To assess the potential for using DNase-seq to identify individual binding sites, we performed DNase-seq on deproteinized genomic DNA and determined sequence cleavage bias. This allowed us to build bias corrected and TF-specific footprint models. The predictive performance of these models demonstrated that predicted footprints corresponded to high-confidence TF-DNA interactions. DNase-seq footprints were absent under a fraction of ChIP-seq peaks, which we show to be indicative of weaker binding, indirect TF-DNA interactions or possible ChIP artifacts. The modeling approach was also able to detect variation in the consensus motifs that TFs bind to. Finally, cell type specific footprints were detected within DNase hypersensitive sites that are present in multiple cell types, further supporting that footprints can identify changes in TF binding that are not detectable using other strategies.

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Despite an emerging understanding of the genetic alterations giving rise to various tumors, the mechanisms whereby most oncogenes are overexpressed remain unclear. Here we have utilized an integrated approach of genomewide regulatory element mapping via DNase-seq followed by conventional reporter assays and transcription factor binding site discovery to characterize the transcriptional regulation of the medulloblastoma oncogene Orthodenticle Homeobox 2 (OTX2). Through these studies we have revealed that OTX2 is differentially regulated in medulloblastoma at the level of chromatin accessibility, which is in part mediated by DNA methylation. In cell lines exhibiting chromatin accessibility of OTX2 regulatory regions, we found that autoregulation maintains OTX2 expression. Comparison of medulloblastoma regulatory elements with those of the developing brain reveals that these tumors engage a developmental regulatory program to drive OTX2 transcription. Finally, we have identified a transcriptional regulatory element mediating retinoid-induced OTX2 repression in these tumors. This work characterizes for the first time the mechanisms of OTX2 overexpression in medulloblastoma. Furthermore, this study establishes proof of principle for applying ENCODE datasets towards the characterization of upstream trans-acting factors mediating expression of individual genes.

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To provide biological insights into transcriptional regulation, a couple of groups have recently presented models relating the promoter DNA-bound transcription factors (TFs) to downstream gene’s mean transcript level or transcript production rates over time. However, transcript production is dynamic in response to changes of TF concentrations over time. Also, TFs are not the only factors binding to promoters; other DNA binding factors (DBFs) bind as well, especially nucleosomes, resulting in competition between DBFs for binding at same genomic location. Additionally, not only TFs, but also some other elements regulate transcription. Within core promoter, various regulatory elements influence RNAPII recruitment, PIC formation, RNAPII searching for TSS, and RNAPII initiating transcription. Moreover, it is proposed that downstream from TSS, nucleosomes resist RNAPII elongation.

Here, we provide a machine learning framework to predict transcript production rates from DNA sequences. We applied this framework in the S. cerevisiae yeast for two scenarios: a) to predict the dynamic transcript production rate during the cell cycle for native promoters; b) to predict the mean transcript production rate over time for synthetic promoters. As far as we know, our framework is the first successful attempt to have a model that can predict dynamic transcript production rates from DNA sequences only: with cell cycle data set, we got Pearson correlation coefficient Cp = 0.751 and coefficient of determination r2 = 0.564 on test set for predicting dynamic transcript production rate over time. Also, for DREAM6 Gene Promoter Expression Prediction challenge, our fitted model outperformed all participant teams, best of all teams, and a model combining best team’s k-mer based sequence features and another paper’s biologically mechanistic features, in terms of all scoring metrics.

Moreover, our framework shows its capability of identifying generalizable fea- tures by interpreting the highly predictive models, and thereby provide support for associated hypothesized mechanisms about transcriptional regulation. With the learned sparse linear models, we got results supporting the following biological insights: a) TFs govern the probability of RNAPII recruitment and initiation possibly through interactions with PIC components and transcription cofactors; b) the core promoter amplifies the transcript production probably by influencing PIC formation, RNAPII recruitment, DNA melting, RNAPII searching for and selecting TSS, releasing RNAPII from general transcription factors, and thereby initiation; c) there is strong transcriptional synergy between TFs and core promoter elements; d) the regulatory elements within core promoter region are more than TATA box and nucleosome free region, suggesting the existence of still unidentified TAF-dependent and cofactor-dependent core promoter elements in yeast S. cerevisiae; e) nucleosome occupancy is helpful for representing +1 and -1 nucleosomes’ regulatory roles on transcription.

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Endomesoderm is the common progenitor of endoderm and mesoderm early in the development of many animals. In the sea urchin embryo, the Delta/Notch pathway is necessary for the diversification of this tissue, as are two early transcription factors, Gcm and FoxA, which are expressed in mesoderm and endoderm, respectively. Here, we provide a detailed lineage analysis of the cleavages leading to endomesoderm segregation, and examine the expression patterns and the regulatory relationships of three known regulators of this cell fate dichotomy in the context of the lineages. We observed that endomesoderm segregation first occurs at hatched blastula stage. Prior to this stage, Gcm and FoxA are co-expressed in the same cells, whereas at hatching these genes are detected in two distinct cell populations. Gcm remains expressed in the most vegetal endomesoderm descendant cells, while FoxA is downregulated in those cells and activated in the above neighboring cells. Initially, Delta is expressed exclusively in the micromeres, where it is necessary for the most vegetal endomesoderm cell descendants to express Gcm and become mesoderm. Our experiments show a requirement for a continuous Delta input for more than two cleavages (or about 2.5 hours) before Gcm expression continues in those cells independently of further Delta input. Thus, this study provides new insights into the timing mechanisms and the molecular dynamics of endomesoderm segregation during sea urchin embryogenesis and into the mode of action of the Delta/Notch pathway in mediating mesoderm fate.

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Soft-tissue sarcomas (STSs) are rare mesenchymal tumors that arise from muscle, fat and connective tissue. Currently, over 75 subtypes of STS are recognized. The rarity and heterogeneity of patient samples complicate clinical investigations into sarcoma biology. Model organisms might provide traction to our understanding and treatment of the disease. Over the past 10 years, many successful animal models of STS have been developed, primarily genetically engineered mice and zebrafish. These models are useful for studying the relevant oncogenes, signaling pathways and other cell changes involved in generating STSs. Recently, these model systems have become preclinical platforms in which to evaluate new drugs and treatment regimens. Thus, animal models are useful surrogates for understanding STS disease susceptibility and pathogenesis as well as for testing potential therapeutic strategies.