Co-operation between the PAI and RED subdomains of Pax-8 in the interaction with the thyroglobulin promoter

Pax proteins are transcription factors that play an important role in the differentiation of several cell types. These proteins bind to specific DNA sequences through the paired domain. This evolutionarily conserved element is composed of two subdomains (PAI and RED), located at the N- and C-terminals, respectively. Due to the presence of these two subdomains, Pax proteins may recognize DNA in different modes, a possibility that has not been exhaustively explored yet. The C site of the thyroglobulin promoter is bound by the thyroid-specific transcription factor Pax-8. In this study we have characterized the mode by which the Pax-8 paired domain interacts with the C site. Results allow the identification of the respective positions of the PAI and RED subdomains when the full-length protein is bound to the C site. The binding of the isolated PAI and RED subdomains to the C site and to several related mutants was also evaluated. Both subdomains interact with DNA as a monomer and display a lower binding affinity than the full-length protein. Therefore, the Pax-8 paired domain–C site interaction occurs through a co-operation between the two subdomains. The binding properties of the PAI subdomain suggest that the co-operation between PAI and RED subdomains does not merely consist of the sum of contacts established by the single subdomain: the presence of the RED subdomain is necessary for correct DNA recognition by the PAI subdomain, thus accounting for a sort of chronology of events during DNA binding. Since the RED subdomain is much more variable than the PAI subdomain among Pax proteins, these results could explain how distinct Pax proteins may select different target genes.

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Estrogen receptor action through target genes with classical and alternative response elements

Pure and Applied Chemistry ◽

10.1351/pac200375111757 ◽

2003 ◽

Vol 75 (11-12) ◽

pp. 1757-1769 ◽

Cited By ~ 12

Author(s):

P. J. Kushner ◽

P. Webb ◽

R. M. Uht ◽

M.-M. Liu ◽

R. H. Price

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Target Genes ◽

Cell Types ◽

Binding Domain ◽

Environmental Estrogens ◽

Alternative Response ◽

Promoter Elements ◽

Response Elements

The estrogen receptors alpha and beta (ERα and ERβ) mediate the changes in gene expression from physiological and environmental estrogens. Early studies identified classical estrogen response elements (EREs) in the promoter region of target genes whose expression is regulated by estrogen and to which the ERs bind via their DNA-binding domain (DBD). EREs in the pituitary prolactin promoter, for example, mediate an activation by both ERα and ERβ albeit with different affinities for different ligands. Full activation in most cell types requires the integrity of the activation function 2 (AF-2) in the receptors ligand binding domain (LBD), which is engaged by estrogens and disengaged by tamoxifen, raloxifene, and other antiestrogens. However, in some cells and ERE contexts, the AF-1 in the ERα amino terminal domain (NTD) is sufficient. We now know that ERs also regulate expression of target genes that do not have EREs, but instead have various kinds of alternative response elements that bind heterologous transcription factors whose activity is regulated by interactions with ERs. Thus, ERα activates genes, including collagenase and cyclin D1, an important mediator of cellular proliferation, by AP-1 and CRE sites, which bind Jun/Fos or Jun/ATF-2 transcription factors. ERα also activates gene expression through GC-rich elements that bind the SP1 transcription factor. Finally, we also know that ERs mediate inhibition of the expression of many genes. In one well-studied instance, ERs counterexpression of genes involved in the inflammatory response by inhibiting the action at tumor necrosis factor response elements (TNF-REs) that bind the NFkappaB transcription factor. ERβ is especially efficient at this inhibition. ERα activation of AP-1/CRE target genes is of special interest because of the putative role of these target genes in mediating proliferation. The AF-1 and AF-2 functions of ERα are both needed for this activation in most cell types. However, in uterine cells, the AF-1 function is sufficient. Thus, the antiestrogen tamoxifen, which allows AF-1, mimics estrogen and drives activation of AP-1/CRE target genes and proliferation of uterine cells. This estrogen-like action, which can increase the risk of uterine cancer, complicates the use of tamoxifen to prevent breast cancer. Surprisingly, ERβ inhibits AP-1/CRE target genes in the presence of estrogen. When both receptors are present, ERβ efficiently opposes activation by ERα. Moreover, ERβ activates the AP-1/CRE target genes in the presence of antiestrogens especially so-called "complete" antiestrogens raloxifene, and ICI 182, 780. We here review the evidence for different kinds of promoter elements that mediate ER action, for the differential ligand preferences of ERα and ERβ at these different elements, and the potential mechanisms by which they are mediated. One attractive strategy for the investigation and comparison of potential environmental estrogens is to assay their activity in cell culture systems using reporter genes with simplified promoter elements. Thus, the findings of complexity in ERα and ERβ activation at different types of response elements needs to be taken into account in the development and interpretation of assays using simplified promoter elements systems.

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Regulatory Network Analysis in Estradiol-Treated Human Endothelial Cells

International Journal of Molecular Sciences ◽

10.3390/ijms22158193 ◽

2021 ◽

Vol 22 (15) ◽

pp. 8193

Author(s):

Daniel Pérez-Cremades ◽

Ana B. Paes ◽

Xavier Vidal-Gómez ◽

Ana Mompeón ◽

Carlos Hermenegildo ◽

...

Keyword(s):

Endothelial Cells ◽

Transcription Factor ◽

Transcription Factors ◽

Regulatory Network ◽

Mirna Target ◽

Target Genes ◽

Functional Characterization ◽

Human Endothelial Cells ◽

Mrna Targets ◽

Canonical Pathways

Background/Aims: Estrogen has been reported to have beneficial effects on vascular biology through direct actions on endothelium. Together with transcription factors, miRNAs are the major drivers of gene expression and signaling networks. The objective of this study was to identify a comprehensive regulatory network (miRNA-transcription factor-downstream genes) that controls the transcriptomic changes observed in endothelial cells exposed to estradiol. Methods: miRNA/mRNA interactions were assembled using our previous microarray data of human umbilical vein endothelial cells (HUVEC) treated with 17β-estradiol (E2) (1 nmol/L, 24 h). miRNA–mRNA pairings and their associated canonical pathways were determined using Ingenuity Pathway Analysis software. Transcription factors were identified among the miRNA-regulated genes. Transcription factor downstream target genes were predicted by consensus transcription factor binding sites in the promoter region of E2-regulated genes by using JASPAR and TRANSFAC tools in Enrichr software. Results: miRNA–target pairings were filtered by using differentially expressed miRNAs and mRNAs characterized by a regulatory relationship according to miRNA target prediction databases. The analysis identified 588 miRNA–target interactions between 102 miRNAs and 588 targets. Specifically, 63 upregulated miRNAs interacted with 295 downregulated targets, while 39 downregulated miRNAs were paired with 293 upregulated mRNA targets. Functional characterization of miRNA/mRNA association analysis highlighted hypoxia signaling, integrin, ephrin receptor signaling and regulation of actin-based motility by Rho among the canonical pathways regulated by E2 in HUVEC. Transcription factors and downstream genes analysis revealed eight networks, including those mediated by JUN and REPIN1, which are associated with cadherin binding and cell adhesion molecule binding pathways. Conclusion: This study identifies regulatory networks obtained by integrative microarray analysis and provides additional insights into the way estradiol could regulate endothelial function in human endothelial cells.

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Regulation of Pax-3 expression in the dermomyotome and its role in muscle development

Development ◽

10.1242/dev.120.4.957 ◽

1994 ◽

Vol 120 (4) ◽

pp. 957-971 ◽

Cited By ~ 63

Author(s):

M. Goulding ◽

A. Lumsden ◽

A.J. Paquette

Keyword(s):

Transcription Factors ◽

Muscle Development ◽

Cell Types ◽

Axial Skeleton ◽

Mouse Embryos ◽

Related Gene ◽

Paired Domain ◽

Trunk Musculature ◽

Somitic Mesoderm

The segmented mesoderm in vertebrates gives rise to a variety of cell types in the embryo including the axial skeleton and muscle. A number of transcription factors containing a paired domain (Pax proteins) are expressed in the segmented mesoderm during embryogenesis. These include Pax-3 and a closely related gene, Pax-7, both of which are expressed in the segmental plate and in the dermomyotome. In this paper, we show that signals from the notochord pattern the expression of Pax-3, Pax-7 and Pax-9 in somites and the subsequent differentiation of cell types that arise from the somitic mesoderm. We directly assess the role of the Pax-3 gene in the differentiation of cell types derived from the dermomyotome by analyzing the development of muscle in splotch mouse embryos which lack a functional Pax-3 gene. A population of Pax-3-expressing cells derived from the dermomyotome that normally migrate into the limb are absent in homozygous splotch embryos and, as a result, limb muscles are lost. No abnormalities were detected in the trunk musculature of splotch embryos indicating that Pax-3 is necessary for the development of the limb but not trunk muscle.

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Mediator complex subunit Med19 binds directly GATA transcription factors and is required with Med1 for GATA-driven gene regulation in vivo

Journal of Biological Chemistry ◽

10.1074/jbc.ra120.013728 ◽

2020 ◽

Vol 295 (39) ◽

pp. 13617-13629

Author(s):

Clément Immarigeon ◽

Sandra Bernat-Fabre ◽

Emmanuelle Guillou ◽

Alexis Verger ◽

Elodie Prince ◽

...

Keyword(s):

Transcription Factors ◽

Target Genes ◽

Direct Interaction ◽

Mediator Complex ◽

Loss Of Function ◽

Transcriptional Responses ◽

Rna Pol Ii ◽

Evolutionarily Conserved

The evolutionarily conserved multiprotein Mediator complex (MED) serves as an interface between DNA-bound transcription factors (TFs) and the RNA Pol II machinery. It has been proposed that each TF interacts with a dedicated MED subunit to induce specific transcriptional responses. But are these binary partnerships sufficient to mediate TF functions? We have previously established that the Med1 Mediator subunit serves as a cofactor of GATA TFs in Drosophila, as shown in mammals. Here, we observe mutant phenotype similarities between another subunit, Med19, and the Drosophila GATA TF Pannier (Pnr), suggesting functional interaction. We further show that Med19 physically interacts with the Drosophila GATA TFs, Pnr and Serpent (Srp), in vivo and in vitro through their conserved C-zinc finger domains. Moreover, Med19 loss of function experiments in vivo or in cellulo indicate that it is required for Pnr- and Srp-dependent gene expression, suggesting general GATA cofactor functions. Interestingly, Med19 but not Med1 is critical for the regulation of all tested GATA target genes, implying shared or differential use of MED subunits by GATAs depending on the target gene. Lastly, we show a direct interaction between Med19 and Med1 by GST pulldown experiments indicating privileged contacts between these two subunits of the MED middle module. Together, these findings identify Med19/Med1 as a composite GATA TF interface and suggest that binary MED subunit–TF partnerships are probably oversimplified models. We propose several mechanisms to account for the transcriptional regulation of GATA-targeted genes.

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HOT or not: examining the basis of high-occupancy target regions

10.1101/107680 ◽

2017 ◽

Cited By ~ 3

Author(s):

Katarzyna Wreczycka ◽

Vedran Franke ◽

Bora Uyar ◽

Ricardo Wurmus ◽

Altuna Akalin

Keyword(s):

Transcription Factor ◽

Transcription Factors ◽

Binding Sites ◽

Cell Types ◽

Data Sets ◽

Gene Promoters ◽

Quadruplex Dna ◽

Golden Standard ◽

Multiple Cell ◽

Multiple Species

AbstractHigh-occupancy target (HOT) regions are the segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and the associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solemnly defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed “hyper-ChIPable” regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers and enrichment of RNA-DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies.

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Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

10.1101/168419 ◽

2018 ◽

Cited By ~ 10

Author(s):

Mehran Karimzadeh ◽

Michael M. Hoffman

Keyword(s):

Transcription Factor ◽

Transcription Factors ◽

Binding Sites ◽

Cell Types ◽

Transcription Factor Binding ◽

Regulatory Function ◽

Factor Binding ◽

Link Type ◽

Genomic Regions ◽

Factor Sequence

AbstractMotivationIdentifying transcription factor binding sites is the first step in pinpointing non-coding mutations that disrupt the regulatory function of transcription factors and promote disease. ChIP-seq is the most common method for identifying binding sites, but performing it on patient samples is hampered by the amount of available biological material and the cost of the experiment. Existing methods for computational prediction of regulatory elements primarily predict binding in genomic regions with sequence similarity to known transcription factor sequence preferences. This has limited efficacy since most binding sites do not resemble known transcription factor sequence motifs, and many transcription factors are not even sequence-specific.ResultsWe developed Virtual ChIP-seq, which predicts binding of individual transcription factors in new cell types using an artificial neural network that integrates ChIP-seq results from other cell types and chromatin accessibility data in the new cell type. Virtual ChIP-seq also uses learned associations between gene expression and transcription factor binding at specific genomic regions. This approach outperforms methods that predict TF binding solely based on sequence preference, pre-dicting binding for 36 transcription factors (Matthews correlation coefficient > 0.3).AvailabilityThe datasets we used for training and validation are available at https://virchip.hoffmanlab.org. We have deposited in Zenodo the current version of our software (http://doi.org/10.5281/zenodo.1066928), datasets (http://doi.org/10.5281/zenodo.823297), predictions for 36 transcription factors on Roadmap Epigenomics cell types (http://doi.org/10.5281/zenodo.1455759), and predictions in Cistrome as well as ENCODE-DREAM in vivo TF Binding Site Prediction Challenge (http://doi.org/10.5281/zenodo.1209308).

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An Algorithm for Cellular Reprogramming

10.1101/162974 ◽

2017 ◽

Cited By ~ 1

Author(s):

Scott Ronquist ◽

Geoff Patterson ◽

Markus Brown ◽

Stephen Lindsly ◽

Haiming Chen ◽

...

Keyword(s):

Cell Cycle ◽

Transcription Factor ◽

Transcription Factors ◽

Cell Biology ◽

Human Fibroblasts ◽

Cell Types ◽

Approximate Model ◽

Cellular Reprogramming ◽

Biological Processes ◽

Moderate Complexity

AbstractThe day we understand the time evolution of subcellular elements at a level of detail comparable to physical systems governed by Newton’s laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology, providing data-guided frameworks that allow us to develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. In this paper, we describe an approach to optimizing the use of transcription factors (TFs) in the context of cellular reprogramming. We construct an approximate model for the natural evolution of a cell cycle synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points along the cell cycle. In order to arrive at a model of moderate complexity, we cluster gene expression based on the division of the genome into topologically associating domains (TADs) and then model the dynamics of the TAD expression levels. Based on this dynamical model and known bioinformatics, such as transcription factor binding sites (TFBS) and functions, we develop a methodology for identifying the top transcription factor candidates for a specific cellular reprogramming task. The approach used is based on a device commonly used in optimal control. Our data-guided methodology identifies a number of transcription factors previously validated for reprogramming and/or natural differentiation. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes.Significance StatementReprogramming the human genome toward any desirable state is within reach; application of select transcription factors drives cell types toward different lineages in many settings. We introduce the concept of data-guided control in building a universal algorithm for directly reprogramming any human cell type into any other type. Our algorithm is based on time series genome transcription and architecture data and known regulatory activities of transcription factors, with natural dimension reduction using genome architectural features. Our algorithm predicts known reprogramming factors, top candidates for new settings, and ideal timing for application of transcription factors. This framework can be used to develop strategies for tissue regeneration, cancer cell reprogramming, and control of dynamical systems beyond cell biology.

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PICH, an ATP-dependent chromatin remodeling protein, transcriptionally co-regulates oxidative stress response.

10.1101/2021.07.21.453306 ◽

2021 ◽

Author(s):

Anindita Dutta ◽

Apurba Das ◽

Deep Bisht ◽

Vijendra Arya ◽

Rohini Muthuswami

Keyword(s):

Oxidative Stress ◽

Transcription Factor ◽

Transcriptional Regulation ◽

Stress Response ◽

Chromatin Remodeling ◽

Dna Sequences ◽

Target Genes ◽

Antioxidant Response ◽

Oxidative Stress Response ◽

Antioxidant Genes

Cells respond to oxidative stress by elevating the levels of antioxidants, signaling, and transcriptional regulation often implemented by chromatin remodeling proteins. The study presented in this paper shows that the expression of PICH, an ATP-dependent chromatin remodeler, is upregulated during oxidative stress in HeLa cells. We also show that PICH regulates the expression of Nrf2, a transcription factor regulating antioxidant response, both in the absence and presence of oxidative stress. In turn, Nrf2 regulates the expression of PICH in the presence of oxidative stress. Both PICH and Nrf2 together regulate the expression of antioxidant genes and this transcriptional regulation is dependent on the ATPase activity of PICH. In addition, H3K27ac modification also plays a role in activating transcription in the presence of oxidative stress. Co-immunoprecipitation experiments show that PICH and Nrf2 interact with H3K27ac in the presence of oxidative stress. Mechanistically, PICH recognizes ARE sequences present on its target genes and introduces a conformational change to the DNA sequences leading us to hypothesize that PICH regulates transcription by remodeling DNA. PICH ablation leads to reduced expression of Nrf2 and impaired antioxidant response leading to increased ROS content, thus, showing PICH is essential for the cell to respond to oxidative stress.

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Unification of Opposites between Two Antioxidant Transcription Factors Nrf1 and Nrf2 in Mediating Distinct Cellular Responses to the Endoplasmic Reticulum Stressor Tunicamycin

Antioxidants ◽

10.3390/antiox9010004 ◽

2019 ◽

Vol 9 (1) ◽

pp. 4 ◽

Cited By ~ 11

Author(s):

Yu-ping Zhu ◽

Ze Zheng ◽

Shaofan Hu ◽

Xufang Ru ◽

Zhuo Fan ◽

...

Keyword(s):

Endoplasmic Reticulum ◽

Transcription Factor ◽

Transcription Factors ◽

Er Stress ◽

Target Genes ◽

Cellular Responses ◽

Water Soluble ◽

Heme Oxygenase 1 ◽

Nuclear Factor ◽

Activating Transcription Factor

The water-soluble Nrf2 (nuclear factor, erythroid 2-like 2, also called Nfe2l2) is accepted as a master regulator of antioxidant responses to cellular stress, and it was also identified as a direct target of the endoplasmic reticulum (ER)-anchored PERK (protein kinase RNA-like endoplasmic reticulum kinase). However, the membrane-bound Nrf1 (nuclear factor, erythroid 2-like 1, also called Nfe2l1) response to ER stress remains elusive. Herein, we report a unity of opposites between these two antioxidant transcription factors, Nrf1 and Nrf2, in coordinating distinct cellular responses to the ER stressor tunicamycin (TU). The TU-inducible transcription of Nrf1 and Nrf2, as well as GCLM (glutamate cysteine ligase modifier subunit) and HO-1 (heme oxygenase 1), was accompanied by activation of ER stress signaling networks. Notably, the unfolded protein response (UPR) mediated by ATF6 (activating transcription factor 6), IRE1 (inositol requiring enzyme 1) and PERK was significantly suppressed by Nrf1α-specific knockout, but hyper-expression of Nrf2 and its target genes GCLM and HO-1 has retained in Nrf1α−/− cells. By contrast, Nrf2−/−ΔTA cells with genomic deletion of its transactivation (TA) domain resulted in significant decreases of GCLM, HO-1 and Nrf1; this was accompanied by partial decreases of IRE1 and ATF6, rather than PERK, but with an increase of ATF4 (activating transcription factor 4). Interestingly, Nrf1 glycosylation and its trans-activity to mediate the transcriptional expression of the 26S proteasomal subunits, were repressed by TU. This inhibitory effect was enhanced by Nrf1α−/− and Nrf2−/−ΔTA, but not by a constitutive activator caNrf2ΔN (that increased abundances of the non-glycosylated and processed Nrf1). Furthermore, caNrf2ΔN also enhanced induction of PERK and IRE1 by TU, but reduced expression of ATF4 and HO-1. Thus, it is inferred that such distinct roles of Nrf1 and Nrf2 are unified to maintain cell homeostasis by a series of coordinated ER-to-nuclear signaling responses to TU. Nrf1α (i.e., a full-length form) acts in a cell-autonomous manner to determine the transcription of most of UPR-target genes, albeit Nrf2 is also partially involved in this process. Consistently, transactivation of ARE (antioxidant response element)-driven BIP (binding immunoglobulin protein)-, PERK- and XBP1 (X-box binding protein 1)-Luc reporter genes was mediated directly by Nrf1 and/or Nrf2. Interestingly, Nrf1α is more potent than Nrf2 at mediating the cytoprotective responses against the cytotoxicity of TU alone or plus tBHQ (tert-butylhydroquinone). This is also further supported by the evidence that the intracellular reactive oxygen species (ROS) levels are increased in Nrf1α−/− cells, but rather are, to our surprise, decreased in Nrf2−/−ΔTA cells.

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TGF-β regulates the expression of transcription factor KLF6 and its splice variants and promotes co-operative transactivation of common target genes through a Smad3–Sp1–KLF6 interaction

Biochemical Journal ◽

10.1042/bj20081434 ◽

2009 ◽

Vol 419 (2) ◽

pp. 485-495 ◽

Cited By ~ 32

Author(s):

Luisa M. Botella ◽

Francisco Sanz-Rodriguez ◽

Yusuke Komi ◽

Africa Fernandez-L ◽

Elisa Varela ◽

...

Keyword(s):

Transcription Factor ◽

Target Genes ◽

Transforming Growth Factor ◽

Splice Variants ◽

Biological Activities ◽

Resonance Energy ◽

Transforming Growth Factor Β1 ◽

Full Length ◽

Specific Cell ◽

Tgf Β1

KLF6 (Krüppel-like factor 6) is a transcription factor and tumour suppressor with a growing range of biological activities and transcriptional targets. Among these, KLF6 suppresses growth through transactivation of TGF-β1 (transforming growth factor-β1). KLF6 can be alternatively spliced, generating lower-molecular-mass isoforms that antagonize the full-length WT (wild-type) protein and promote growth. A key target gene of full-length KLF6 is endoglin, which is induced in vascular injury. Endoglin, a homodimeric cell membrane glycoprotein and TGF-β auxiliary receptor, has a pro-angiogenic role in endothelial cells and is also involved in malignant progression. The aim of the present work was to explore the effect of TGF-β on KLF6 expression and splicing, and to define the contribution of TGF-β on promoters regulated by co-operation between KLF6 and Sp1 (specificity protein 1). Using co-transfection, co-immunoprecipitation and fluorescence resonance energy transfer, our data demonstrate that KLF6 co-operates with Sp1 in transcriptionally regulating KLF6-responsive genes and that this co-operation is further enhanced by TGF-β1 through at least two mechanisms. First, in specific cell types, TGF-β1 may decrease KLF6 alternative splicing, resulting in a net increase in full-length, growth-suppressive KLF6 activity. Secondly, KLF6–Sp1 co-operation is further enhanced by the TGF-β–Smad (similar to mothers against decapentaplegic) pathway via the likely formation of a tripartite KLF6–Sp1–Smad3 complex in which KLF6 interacts indirectly with Smad3 through Sp1, which may serve as a bridging molecule to co-ordinate this interaction. These findings unveil a finely tuned network of interactions between KLF6, Sp1 and TGF-β to regulate target genes.

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