Insulin, MAPK, VEGF, Hypoxia, and mTOR core) activities of the mTOR pathway. Discovered transcription factors are classified as “process-specific” or “pathway-ubiquitous” with highlights toward their regulating/regulated activities within the mTOR pathway. Our transcription regulation results will facilitate further research on investigating the control mechanism in mTOR pathway.The mammalian target of rapamycine (mTOR) pathway is a key regulator of cellular growth, development, and ageing, and unraveling its control is essential for understanding life and death of biological organisms. A motif-discovery workbench including nine tools was used to identify transcription factors involved in five basic ( Computational analysis of transcription regulation of biological pathways is a challenging task because a single pathway may be interconnected to multiple upstream and downstream pathways and, as a consequence, might be regulated by various groups of transcription factors  pathway genes was investigated by using nine public motif-discovery tools published in the last decade. TOR was first discovered in yeast , where the polymerase II transcription initiation complex forms, and distantly located enhancer regions that may interact with one or more promoter sites of neighboring genes  and included 49 human genes with 43 orthologous partners in mouse. Promoter regions of 5000 base pairs upstream and 500 base pairs downstream with their representative transcriptional start sites (TSS) were retrieved from the DBTSS database , programs with diverse methodologies  and programs that link the results to the expression data to augment probability likelihood of predicted motifs . Next, each of selected program had to fulfill the following four characteristics: (1) capability to handle a large data size (300 Kb) and return results in less than 24 h; (2) report motif results for each DNA sequence or report motif results across the whole dataset; (3) execute a software operation without manual parameter adjustment; and (4) annotate resulted motifs in currently available databases.Five main programs, which report identified motifs in each sequence, namely, Pscan  transcription-factor motifs per gene, shown above the red horizontal line in Supporting Figure gene threshold (Gene_TH). This resulted in 24 genes, possessing more than 26 predicted motifs in their promoters for human, including their multiple occurrences.To find the most co-regulated genes within the dataset, the average number of transcription factors per gene was calculated by dividing the total number of TFBS motifs found by PScan, PASTAA, MEME_Chip, TFM-Explorer, and XXmotif in a human dataset , by the total number of genes in the human dataset (49) that resulted in 26.43 (gene threshold were taken and denoted as those above a transcription factor threshold (TF_TH). This selection showed that at least half of the 24 genes possessed each of the 24 above-selected transcription-factor motifs in their promoters. The top-occurring transcription factors was SP1 with its highest frequency and top occurrence of seven copies in the RPS6KA3 gene, and the last-occurring transcription factor was ARNT found in 12 genes with single occurrence  human transcription factors found in the promoters of genes above the mTOR core and ten modules for convenience to point out to the transcription factors involved in different activities of the mTOR pathway. Modules were then classified into pre-core transcriptional modules and post-core transcriptional modules according to their place within the pathway.The intersection zone was used to produce an mTOR map by CellDesigner4.3 . Activities of various modules with assigned transcription factors are discussed in the next sub-sections.Transcription factors (TF) and genes allocated in the intersection zone (see Methods) were selected as candidates for regulating an mTOR pathway. The initial identified number of TFs was 61 for human and 50 for mouse with 21 orthologs , and PLAG1 (Pleiomorphic adenoma gene 1 protein).In module 7). Inhibition of ESR1 affects activation of S6K1/2 and stimulates phosphorylation of S6K1/2 and 4EBP in the presence of Leucine. ELK1 and ESR1 are regulated by a mTOR MAPK signaling pathway and a VEGF angiogenesis signaling pathway with crosstalk.Both ELK1 (an ETS domain-containing protein) and ESR1 (a nuclear steroid receptor) interact with the MAPK3 gene  and influencing autophagy (module 8) . Moreover, MZF1 is also involved in activating or deactivating the PTEN gene, which is known as a tumor suppressor (module 2). MZF1 binding motifs were also found in VEGFA promoter, suggesting regulation of the VEGF pathway (module 7), in E1F4E1B promoter implying involvement in cell development (module 7), and in ULK1 promoter indicating connection with autophagy process in mTOR (module 8) [27]. Accordingly, MZF1 is a ubiquitous plays an important role in regulation of the whole mTOR pathway.A myeloid-zinc-finger (MZF1) TF function, which is a granulocyte precursor in bone marrow, in the mTOR pathway is not yet discovered. Found in the multiple promoters of module 1 it can be presumed that MZF1 changes the transcription inside the pathway by influencing INS (dependent on growth factors and hormones) or by regulating the MAPK cascade and RPS6K gene (module 1), IRS1, PIK3R1, PIK3CA (module 2), TNF (module 3), and TSC2 (module 4). Akhtar et al. (The third transcription factor contributing largely to the pre-core modules one and two is PLAG1 (pleiomorphic adenoma gene 1 protein). It regulates a range of mTOR processes involved in cell proliferation, organ growth, and apoptosis. In our research, it is found in the promoters of INS, RPS6KA2  and 2  share SP1, MZF1, and PLAG1 transcription factors. Apart from it, module 2 has FOXF2 (forkhead box F2) and TBP (TATA-binding protein). FOXF2 and TBP are already known in the context of co-regulation with MTOR, RDS1, (adenine-repressible gene) and TFAP2A  , leading to inhibition of the whole mTOR pathway via a negative-feedback loop , a PTEN gene, which is an inhibitor of the mTOR pathway thought the PIP3 (module 2) and RRAGD genes (module 5). TFAP2A is thus involved in processes of organ development and negative cell proliferation at the same time. One of the probable scenarios concerning TFAP2A is that by inhibition of IRS1, PIK3R2 (module 2), and RRAGD (module 5) genes, TFAP2A stimulates the PTEN transcription immobilizing mTOR pathway and negative feedback loop may exist between insulin-signaling module 2 and amino-acid balance module 5. Surprisingly, a TF characteristic for yeast RDS1 (an adenine-repressible gene), responsible for the regulation of transcription from RNA polymerase II, is identified in the human data set. RDS1 binding motif is found in the promoters of IRS1, AKT1 (threonine-protein kinase) genes of pre-core module 2, and the RRAGC (Ras-related GTP binding C) gene of post-core module 5. It is difficult to assess RDS1 functions in an mTOR pathway due to the fact that it is only been found in yeast to date. However, in yeast organisms, it is responsible for transcription regulation and response to xenobiotic stimulus. In human organisms, its function may be very similar to the function in yeast, and human ortholog might be identified in the future.In consideration of the locations of TFAP2A binding motifs, it is noteworthy that TFAP2A can regulate the mTOR pathway and, in particular, its module 2) and, second, being regulated by the availability of amino acids or generally intracellular xenobiotics (RRAGC in module 5). The above-described finding on RDS1 activity indicates the existence of crosstalk between module 2  and module 5  transcription regulation and existence of a negative feedback loop between them. This is a biologically reasonable finding as insulin-control amino-acid metabolism is tightly related to amino-acid-uptake balance.RDS1 can influence the mTOR pathway from two sides: first, being regulated by growth factors and hormones  and proper functioning of this receptor. Current knowledge indicates that the HIF1- and/or HIF2-mediated hypoxia responses can be oncogenic as well as tumor suppressive  is one that regulates gene expression in hypoxia In the core of mTOR pathway KLF4 (Kruppel-like factor 4) inhibits the MTOR gene and has an anti-proliferative effect on the whole mTOR pathway   positively regulates genes of the mTOR/S6K pathway, so it belongs both to the mTOR Module 7 is associated with VEGF  pathway-advancing cell growth, organ development, and protein formation. This transcriptional module possesses four transcription factors, namely, SP1, ESR1, E2F1, and EGR1, with three first TFs tightly associated with the activities of the mTOR pathway.module 7 specific TF, directs cell differentiation. It was discovered that its level in a prostate cancer was raised, showing a pro-oncogenic character; however, in other tumor types , EGR1 exhibits features of a tumor suppressor by activating p53 and PTEN to halt the transcription of other genes in the mTOR pathway , which is An E2F group affects activation of RPS6KB1 (S6K) and stimulates phosphorylation of S6K and 4EBP in the presence of Leucine. E2F1 integrates cell division (as well as cell growth) and induces an apoptotic response  from the results analysis where those identified by main and supportive motifs discovery tools used in our study , FOXF2 , KLF4 (mTOR core), ARNT , E2F1, and EGR1 . The second group includes SP1, MZF1, PLAG1, TFAP1A, TBP, and RDS1. Among member of the second group, MZF1, PLAG1, TFAP1A, and RDS are newly identified. Other transcription factors identified in the promoters of genes in our analysis are EGR2, EGR3, YY1, SREBF1, SREBF2, ELF1, and ARID3A. They are less frequently share by the promoters in our dataset but they are well-known to be involved in the mTOR pathway regulation .The first group of TFs includes ESR1, ELK1  of the human transcription factors were found to be conserved in the case of a mouse. Among them most confident are SP1, TFAP2A, MZF1, EGR3, KLF4, USF1, KLF9, and ARNT (Supporting Figure de novo motif discovery.The results described in the paper indicate that the proper selection of online motif-discovery tools without parameters tuning is feasible to bring accurate results for the discovery transcription regulation on medium size data. However the aim to reduce false positives might result in the omitting low sensitivity-degenerate motifs (Polouliakh et al., Agnieszka Jablonksa analyzed data and wrote the manuscript. Natalia Polouliakh discussed the research and wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity.Burkholderia xenovorans, a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018.A software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed, we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from These studies provide the proof of concept and validation of a systematic approach to the discovery of the biological activity for proteins of unknown function, in this case a TR. Bxe_B3018 is a methylglyoxal responsive TR that controls the expression of an operon composed of a putative efflux system.The online version of this article (doi:10.1186/1471-2164-15-1142) contains supplementary material, which is available to authorized users. Early researchers established that functional context is often associated with genome organization when they observed that genes for complex traits are often clustered within a genome , 2. By cIn-vivo experiments that provide candidate effector metabolites can suffer from limitations of solubility, uptake or efflux of the candidate effector metabolite. Mutations either knocking out or over expressing the TR can be lethal or generate a global response, making interpretation extremely complex. Additional approaches are needed to overcome these limitations and facilitate TR function discovery and characterization.We sought to capitalize upon the physical clustering of genes of related function and the frequent collocation of the TR with its operon to help guide our experimental investigation of TR function. TRs allow or repress transcription in response to the presence of an effector molecule that influences their association or dis-association with their target DNA operator sequence (DOS) . BacteriBurkholderia xenovorans TR, Bxe_B3018, of unknown function to test the method. Bxe_B3018 is widely conserved among the Burkholderia and Pseudomonas genus but absent in most other bacteria. Sequence homology analysis suggests that it is a member of the TetR-family of TRs. The DOS for Bxe_B3018 and its orthologs among the Burkholderia genus has the general sequence of C (T/G)AGAA (T/C)GATC (G/A)TTCT (C/A)C; this sequence is also present in its own promoter region and the promoter regions of an unknown function gene, bxe_B3017 in B. xenovorans, N,N-dimethylaminoacetone [(2.4 ± 0.2) mM] or methylglyoxal [(1.9 ± 0.5) mM] were added to the reaction mixture without previous pre-incubation; we therefore concluded that aminopropan-2-ol was not interfering with the binding of these other compounds in our assay.GST-Bxe-B3018 binds its DOS to form a TR/DOS complex in the absence of an effector molecule with a Results from electrophoresis mobility shift assays were consistent with the observations obtained from the anisotropy experiments for aminoacetone (Aa), methylglyoxal (Mgx) and aminopropna-2-ol (Ap) Figure . The thiin-vitro-identified effector molecules  as well as the non-effector (animopropan-2-ol) were capable of affecting the expression of the genes in the operon . Bxe_B3018 binds its DOS in the absence of an effector molecule; incubation of B. xenovorans with the effector molecules should cause Bxe_B3018 to release its DOS increasing the rate of translation of the genes encoding bxe_B3016, bxe_B3017, bxe_B3018 and bxe_B3019. Aminoacetone and aminopropan-2-ol showed no effect on the expression of the regulated genes with concentrations up to 10 mM of each effector. Addition of 10 mM of methylglyoxal and incubation for an hour led to a 40-fold increase in the expression of the regulated genes  and a 100-fold increase in the expression of the TR (bxe_B3018), of as measured by real-time PCR (rtPCR).These in-vivo results suggest that methylglyoxal was the only effector molecule able to increase translation of the genes in the operon.Real-time PCR experiments were utilized to determine whether the As early as the 1930’s, geneticists observed that genes encoding for proteins responsible for complex traits are often clustered within the genome , 34, 35.B. xenovorans TR of unknown function, Bxe_B3018. It is widely conserved among the Burkholderia and Pseudomonas genus but absent in most other bacteria. There are more than 140 TRs common among the members of the Burkholderia genus that have not been fully functionally annotated. Characterization of these TRs is vital to the understanding of the metabolism of this genus, which is characterized by having members with excellent environmental adaptability and/or high pathogenicity. Function Discovery V1.0 analysis suggested that Bxe_B3018 may be involved in the glycine, serine and threonine degradation pathway. The operon regulated by Bxe_B3018 is found upstream from several genes involved in this metabolism. Our software analysis coupled with our in-vitro and in-vivo experiments suggests that it responds to a metabolite from the glycine, serine and threonine metabolism pathway, methylglyoxal. Fluorescence anisotropy experiments suggest that Bxe_B3018 binds methylglyoxal with a dissociation constant of ~2 mM. Millimolar concentrations of methylglyoxal in bacterial cells have been previously reported AGAATGATCGTTCTACCCTT-3′) and its complement sequence (5′-AAGGGTAGAACGATCATTCTCCCTCG-3′) were dissolved in distilled water to a concentration of 100 μM. The annealing reaction was performed by incubating a 20 μM solution of the two oligonucleotides in 20 mM Tris-Cl, 100 mM NaCl and 1 mM MgCl2 at pH 7.5 at 95°C in a heat block for 5 min, then the block was removed from the heat source and allowed to reach room temperature. The progressive decline to room temperature allowed the annealing to occur. The fluorescence polarization experiments were performed in 20 mM Tris-Cl, 60 mM KCl, 40 mM NaCl, 0.5 mM EDTA, 1.0 mM DTT, 1.0 mM MgCl2 and 100 μM/mL BSA at pH 7.5 (buffer D). The 200 μL reaction mixture was prepared in the following order: first 10× Buffer D was added to the wells of a black 96-well; then 20× Fluorescein-labeled DOS was added to a final concentration of 1 nM; then distilled water was added to complete the 200 μL reaction volume minus the GST-Bxe_B3018 reaction volume. Finally, the reaction was initiated by the addition of the appropriate amount the GST-Bxe_B3018 . The reactions were mixed by pipetting and incubated for one hour at 30°C in the dark. The Fluorescein-labeled DOS was excited with polarized light through an excitation filter of 485/20 nm and the emission was measured with an emission filter of 528/20 nm with a dichroic mirror of 510 nm. Fluorescence polarization was monitored with a BioTek - Synergy H4 hybrid Microplate Reader and anisotropy values calculated automatically with the Gen5 software using the standard G factor of 0.85.The Fluorescein-labeled DNA Operator Sequence (DOS) . The aminoacetone, aminopropan-2-ol and methylglyoxal concentrations ranged from 10 to 20 mM. The reaction mixtures were incubated at room temperature for 30 min. A 5% native polyacrylamide gel was pre-run for 20 min at 8 V/cm in TBE buffer composed of 44 mM Tris, 44 mM Borate, 1.0 mM EDTA at pH 8.3. Then, the samples were loaded and run at 8 V/cm until the bromophenol yellow (loading dye) migrated 1/3 down the gel. Gels were stained with ethidium bromide, imaged on a BIORAD ChemiDoc XRS imaging station.The DOS utilized in these experiments was obtained from the upstream promoter region of Bxe_B3018. The double stranded DOS was obtained from the annealing of two synthetic oligonucleotides. The synthetic oligonucleotides used consist of a 5′-CGAGGGAGAATGATCGTTCTACCCTT-3′ sequence and its reverse complement of oligonucleotides (5′-AAGGGTAGAACGATCATTC-TCCCTCG-3′). The annealing reaction was performed as explained above. The DOS was further diluted to 2 μM. The GST-Bxe_B3018 protein was diluted to a stock solution of 17 μM in buffer B containing 25% glycerol. The reaction mixtures consisted of 1.0 μM of DOS and protein concentrations of 10 μM in 20 mM Tris-Cl, 500 μM EDTA, 5% glycerol, 200 μM DTT, 0.001% Triton X, 50 mM NaCl, 5 mM MgClB. xenovorans cells were grown in tripticase soy broth until they reached 0.6 OD600nm. One mL aliquots were treated with 1 mM aminoacetone, aminopropan-2-ol or methylglyoxal and incubated for 30 min under constant shaking. B. xenovorans cell were collected by centrifugation at 6,000 × g and RNA was isolated from the treated cells using the Qiagen RNeasy-mini-kit (Qiagen) followed by removal of DNA using a Turbo DNA-free kit (Life Technologies) according to manufacturer’s instructions. The RNA was then analyzed for purity and concentration on a Nano Drop 1000 spectrophotometer. 100 ng of RNA was converted to cDNA in a 20 μL reaction using High Capacity RNA-to-cDNA (Life Technologies) following the manufacturer’s protocol. Real-Time PCR assays were run in triplicate using 2 μL of a 1:10 dilution of cDNA per reaction. MGB TaqMan® assays for Bxe_B3016, Bxe_B3017, Bxe_B3018 and 16 s were designed and ordered from Life Technologies Custom TaqMan Gene Expression assay design tool (https://www.lifetechnologies.com/order/custom-genomic-products/tools/gene-expression/). Reactions were carried out using TaqMan® Fast Universal PCR Master Mix (2×), No AmpErase UNG (ABI #4352042) on ABI 7500 DX instruments run in fast mode with the following cycling parameters: 1 cycle 95°C for 20 s followed by 40 cycles 95°C for 3 s and 60°C for 30 s. Data were analyzed using the Data Assist v3.01 Real-Time PCR analysis software (Life Technologies). The relative gene expression values were determined using the 2-∆∆CT method [T was compared across all data sets.G ABI #43042 on ABThere were no vertebrate or invertebrate subjects used in this investigation.Code. Zip folder containing all files required to run the Java™ application. The files need to be extracted to the same folder and then the FunctionDiscoveryV1.0.jar interface can be launched. For detailed instructions on how to use the interface please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (ZIP 415 KB)Additional file 1: Result BetI. Function Discovery V1.0 output (.html format) for the glycine betaine biosynthesis regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 596 KB)Additional file 2: Result CatR. Function Discovery V1.0 output (.html format) for the benzoate degradation regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 258 KB)Additional file 3: Result CymR. Function Discovery V1.0 output (.html format) for the p-cumate catabolism regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 85 KB)Additional file 4: Result CysB. Function Discovery V1.0 output (.html format) for the sulfur metabolism regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 676 KB)Additional file 5: Result GlpR. Function Discovery V1.0 output (.html format) for the glycerol metabolism regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 684 KB)Additional file 6: Result HpaR. Function Discovery V1.0 output (.html format) for the hydroxyphenylacetate catabolism regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 380 KB)Additional file 7: Result KynR. Function Discovery V1.0 output (.html format) for the oxidative tryptophan degradation regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 476 KB)Additional file 8: Result HutC. Function Discovery V1.0 output (.html format) for the histidine degradation regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 726 KB)Additional file 9: Result RcoM. Function Discovery V1.0 output (.html format) for the carbon monoxide oxidation regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 36 KB)Additional file 10: Result ModE. Function Discovery V1.0 output (.html format) for the molybdate transport regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 732 KB)Additional file 11: Burkholderia or Pseudomonas genomes. (PDF 15 KB)Additional file 12: Figure Af1: Dendrogram of microbial Bxe_B3018 Homologues. BLAST analysis (utilizing a 40 aa-IDc) identified the existence of 81 homologs. These homologs were found only in Result Bxe_B3018. Function Discovery V1.0 output (.html format) for the previously unknown function transcriptional regulator . For detailed instructions on how to analyze the results please refer to the Function Discovery V1.0, a gene neighborhood analysis tool section in the Results part of the main text. (HTML 551 KB)Additional file 13: Additional file 14: Figure Af2: Structures for the library of candidate effector metabolites predicted from the analysis of the Function Discovery V1.0 output for Bxe_B3018. (PDF 16 KB)Additional file 15: Figure Af3: Flowchart describing the steps used by the Function Discovery V1.0 software to predict the metabolic involvement of a given TR. (PDF 9 KB)


However, molecular mechanisms underlying DUSP5 induction are not well known. Here, we found that the DUSP5 mRNA induction depends on a transcriptional regulation by the MAPK pathway, without any modification of the mRNA stability. Two contiguous CArG boxes that bind serum response factor (SRF) were found in a 1 Kb promoter region, as well as several E twenty-six transcription factor family binding sites (EBS). These sites potentially bind Elk-1, a transcription factor activated by ERK1/2. Using wild type or mutated DUSP5 promoter reporters, we demonstrated that SRF plays a crucial role in serum induction of DUSP5 promoter activity, the proximal CArG box being important for SRF binding in vitro and in living cells. Moreover, in vitro and in vivo binding data of Elk-1 to the same promoter region further demonstrate a role for Elk-1 in the transcriptional regulation of DUSP5. SRF and Elk-1 form a ternary complex (Elk-1-SRF-DNA) on DUSP5 promoter, consequently providing a link to an important negative feedback tightly regulating phosphorylated ERK levels.Serum stimulation of mammalian cells induces,  Mitogen-activated protein kinases (MAPK) cascades are a conserved group of signal transduction pathways responsible for the transduction of various signals to a large number of cellular protein substrates . The MAPDUSP5 expression has been shown to alter the decision of growth arrest versus proliferation of human cancer cells [DUSP5 and DUSP6 are known to be induced by ERK signaling –12, and er cells , 19.DUSP6 expression have been largely elucidated, contrary to those controlling DUSP5 expression. It has been shown that DUSP6 is regulated by the MAPK pathway, at the transcriptional level, through a conserved binding site for transcription factors of the E twenty-six family (ETS) Ets-1 and Ets-2, within a 508 bp promoter region. [5’-GGA(A/T)-3’, defines this family of transcription factors, including Ets-1, Ets-2 and Elk-1. For the DUSP6 gene, Ets-1 and Ets-2 are supposed to be bound to their responsive element in the basal state, presumably associated with co-repressors [DUSP6 not only is regulated by the MAPK pathway at the transcriptional level but also at the post-transcriptional level as MEK-ERK pathway has been shown to stabilize DUSP6 mRNA [Mechanisms regulating  region. , 12, 20. region. . The higpressors . ERK-phopressors –24. DUSPSP6 mRNA .DUSP5, one previous study has demonstrated in a human colon-cancer cell line that p53 could bind to a sequence located approximately 1.2 kb upstream of the transcription start site and induce DUSP5 expression [DUSP5 by p53 does not explain how MAPK pathway activation is responsible for the induction of DUSP5 expression.Concerning pression . NeverthDUSP5 gene by the MAPK pathway at the transcriptional and/or post-transcriptional level. Bioinformatic analysis allowed us to identify many EBS, putatively binding Elk-1, a member of the ternary complex factors (TCF) sub-family of ETS transcription factors, as well as binding sites for the serum response factor (SRF), namely CArG boxes, in a ~ 1kb promoter region of DUSP5. The combination of one EBS and one CArG box corresponds to a serum responsive element (SRE). In the present work we found that DUSP5 mRNA is a short-lived messenger rapidly induced by ERK activation and that its mRNA stability is independent from the activation of the MAPK pathway, unlike DUSP6. Different experimental approaches were used to understand the role of the regulatory components of the DUSP5 promoter. Our findings indicate altogether that the ternary complex SRF-Elk-1-SRE is crucial in regulating DUSP5 transcription, providing a mechanistic link between MAPK pathway signaling and DUSP5 induction.The purpose of this paper was to determine the precise mechanism of regulation of the Actinomycin D and cycloheximide were purchased from Sigma-Aldrich. Wortmannin was from Calbiochem. The MEK inhibitor UO126 was from Promega. Disuccinimidyl glutarate (DSG) was from SantaCruz Biotechnology.NIH/3T3 (mouse fibroblast) cell line was purchased from ATCC (American Type Culture Collection) and maintained in Dulbecco’s Modified Eagle’s Medium, containing 10% foetal calf serum (FCS) and antibiotics. Serum starvation and stimulation consisted of maintaining cells in respectively 0.25% or 20% FCS.® cDNA Reverse Transcription Kit, Applied Biosytem cat # 4368814). Real-time PCR was done using a light cycler instrument . The relative gene expression was calculated using the 2-ΔCT method.Total RNA was extracted from cultured cells using the RNeasy Mini Kit from Qiagen and was reverse transcribed to generate cDNA (High-Capacity® (#9102), pAKT (1:1000) from Cell Signaling Technology® (#9271), t-AKT (1:1000) from Cell Signaling Technology® (#9272), and GAPDH (1:2000) from Santa-Cruz Biotechnology (sc-25778) were used. Secondary antibodies used were peroxidase-conjugated antirabbit IgG at 1:10000 or peroxidase-conjugated antimouse at 1/10000. The specific complexes were detected using the enhanced chemiluminescence (ECL) system from Amersham Pharmacia Biotech.Whole cell lysates were analyzed by Western Blotting. Briefly, cells were lysed in 50mM TrisHCl (pH 7.5)/ 1mM EDTA/ 150mM NaCl/ 1% Nonidet P-40 and a cocktail of protease and phosphatase inhibitors . Protein concentration was determined using the Bradford reagent (Bio-Rad). Twenty μg of lysate were subjected to SDS–PAGE on 10% acrylamide gels and transferred onto nitrocellulose membranes (Amersham Pharmacia Biotech). Nonspecific protein-binding sites were blocked by incubation for 1 hour at room temperature in 50mM Tris-HCl (pH8), 150mM NaCl and 0.1% Tween 20 (TBS-T) containing 10% nonfat dry milk. Incubation with primary antibodies was carried in the same buffer overnight at 4°C. Antibodies directed against pERK from Santa Cruz Biotechnology (1:1000), Inc. (sc-7383); total ERK (1:10000) from Cell Signaling TechnologyDUSP5 gene, containing a putative TATA box, was isolated by PCR from a rat bacterial artificial chromosome (BAC) CH230-312K10 (CHORI.ORG) and sub-cloned into pGL3b plasmid (Promega) containing the reporter firefly luciferase. Three shorter reporter plasmids bearing different lengths of DUSP5 promoter region were then produced. Responsive elements in the shortest plasmid (165 bp) were mutated at various sites with the QuikChange® Site-Directed Mutagenesis Kit (Stratagene).A promoter region of 975 base-pair of the Plasmids SRF-VP16, Elk-VP16, Elk-En, and Elk-VP16 (L158P) were a gift from A.D. Scharrocks and E.R. Vickers , 27. SRFSRF or two Elk-1 siRNA were transfected simultaneously at the concentration of 50 nmol/L each with Lipofectamine Plus (Invitrogen) in three independent experiments. A scramble siRNA was used as control (5'-GCCACTACCTCGTTTCACA-3'). After transfection, the level of mRNA knockdown was assessed by reverse transcription quantitative PCR.Small interfering RNA (siRNA) were purchased from Eurofins MWG Operon. Two mouse 32P-labeled fragments of the DUSP5 promoter and of an unrelated probe. To demonstrate the specificity of DNA/protein complex formation, a 20-fold molar excess of the various unlabeled probes was used. To demonstrate the presence of a specific protein in the complexes, nuclear extracts were mixed with 2 μg of the following antibodies: SRF from Santa Cruz Biotechnology, Inc. (sc-13029X), HA-probe from Santa Cruz Biotechnology, Inc. (sc-805X), or rabbit Ig G from Santa Cruz Biotechnology, Inc. (sc-2027). A representative experiment of at least three independent ones is presented.EMSA was performed using nuclear extracts of NIH/3T3 cells, different 5’-GAGACTGAGGGTGGCAAGAG (forward primer) and 5’-ACTGGCTGTGAGCACGTATG (reverse primer) and DUSP5 promoter: 5’-CCACTTCCTCTTTCTCGCTCT (forward primer) and 5’CGCAGGGTTTTATGTGAATG (reverse primer).NIH/3T3 cells were serum starved for 24 hours and then stimulated with 20% FCS for 30 minutes. A two-step cross linking procedure was used: incubation with 2 mM of disuccinimidyl glutarate (DSG) for 45 minutes prior to cross-linking with formaldehyde (1%) for 10 minutes at room temperature. Cross-linking was stopped by adding glycine and the cells lysed. Nuclear lysates were sonicated under conditions yielding fragments ranging from 200 to 800 bp. ChIP was performed by using the ChIP-Adem-Kit (Ademtech) and the automated purification system “KingFisherDuo” (ThermoFisher). Cross-linking was reversed by incubation at 65°C (5 hours or overnight). Antibodies against Elk1 and SRF from Santa Cruz Biotechnology and an antibody against Elk1 from Millipore were used. After digestion with Proteinase K , DNA was purified and used for qPCR. The results were reproduced in three independent experiments. The following mouse oligonucleotides were used for qRT-PCR in ChIP assays: DUSP5 intron 3: Statistical significance was determined using the Student’s test (online GraphPad Software).DUSP5 mRNA, we first evaluated the response of DUSP5 gene to extracellular signals , with a further increase of about twenty fold at 60 (P = 4.10−3) and 80 minutes (P < 1.10−4), in parallel with an increased ERK phosphorylation. The DUSP5 mRNA increase was inhibited by 50 to 70% in the presence of UO126 (MEK inhibitor) and not significantly affected (about 30% decreased at 60 min and 30% increased at 80 min) by the PI3K inhibitor wortmannin. We confirmed at the protein level, that DUSP5 increased in parallel with the serum stimulation and decreased with MEK-15344021ERK inhibition. On the opposite, DUSP5 protein levels were not affected by the PI3K inhibitor. We can conclude that DUSP5 is an early response gene and that its induction by FCS in NIH/3T3 cells is essentially dependent on the MEK/ERK pathway.To study the induction of  signals . NIH/3T3DUSP5 mRNA after serum stimulation was essentially due to an activation of transcription or was dependent on the mRNA stability, the serum treatment of NIH/3T3 cells was combined with low dose actinomycin D  or cycloheximide (protein synthesis inhibitor) treatment. While actinomycin D efficiently inhibited the increase of DUSP5 mRNA level, cycloheximide treatment had no effect  which is not stabilized by ERK activation, unlike DUSP6 [To test whether the rapid and consistent accumulation of o effect . These dke DUSP6 .DUSP5 gene, a search for transcription factors binding sites in the promoter sequence using the Transcription Element Search System (TESS) program from the Department of Biology of the University of Pennsylvania (http://www.cbil.upenn.edu/cgi-bin/tess/tess) revealed the presence of many core sequences GGA(A/T) or GGA(A/C) potentially implicated in the binding of ETS-domain transcription factors (EBS) [DUSP5 gene. To test this hypothesis and in order to determine the core regulatory region of the promoter, EBS located in the 5’ region of the sequence were progressively deleted to obtain the four constructs represented in P <0.05). An identical level of stimulation was observed with the four constructs. Within the limits of transfection experiments, this suggests that the shortest DUSP5 promoter construct is sufficient to elicit a significant serum response, excluding a major role for sequences upstream the nucleotide -165 in transcriptional regulation. These induction levels (i.e. between 2 and 4) have already been observed for the DUSP6 promoter [DUSP5 and DUSP6 expression decreases. These low induction levels of DUSP5 and DUSP6 can be explained by this negative-feedback mechanism. Similar experiments were conducted in the rat pheochromocytoma-derived PC12 cell line, with nerve growth factor (NGF) as stimulation. Identical results were observed (data not shown).To understand the mechanisms of transcriptional regulation of the rs (EBS) . We hypors (EBS) , were inpromoter , 20. ERKpromoter . When ERDUSP5 promoter is sufficient to enable activation of transcription by serum and growth factors, such as NGF, known to activate the MAPK pathway.Altogether, these results suggest that the proximal part of the The sequence of the proximal promoter region is reported in DUSP5 promoter regulation, the shortest DUSP5 promoter reporter was transfected with plasmids expressing SRF or Elk-1 (HA tagged) separately or in combination (P < 1.10−3) with a further increase when SRF and Elk-1 were combined with or without serum stimulation. To study the regulation of DUSP5 mRNA at the endogenous level, we performed siRNA silencing of SRF and Elk-1. SRF and Elk-1 siRNA transfection led to a significant decrease in DUSP5 mRNA induction levels after serum stimulation in comparison with the control situation, i.e. transfection with a control siRNA   or Elk-1t manner . In Fig t manner  and 7A.DUSP5 promoter.These results suggest that both SRF and Elk-1 may cooperate to induce the activity of DUSP5 reporter vector and analyzed after transfection in NIH/3T3 cells. Mutations of the CArG boxes performed in our study were in agreement with a reported mutation [GGAA and GGAC respectively) were mutated to TTC as described previously [To study in more detail promoter consensus sequences necessary and sufficient for regulation by serum, single or combined mutation of each CArG and EBS site were performed in the shortest mutation , 36 resumutation . The puteviously , 38.P < 0.05) (P < 0.05): no induction by SRF-VP16 was observed and the induction by Elk-VP16 was reduced by 50%, indicating that, at least, one CArG site integrity is necessary for SRF action and required for optimal stimulation by Elk-VP16. Single mutation of each EBS did not influence the responses to SRF or Elk dominant positive forms (not shown). The same result was obtained with mutation of both EBS (P < 0.05) reduced to the level observed with the double mutant CArG (P < 0.05) (P < 0.05)  . Mutatioboth EBS , suggestant CArG . The samant CArG . Mutatio < 0.05) . This re < 0.05) .DUSP5 promoter activity was investigated in the presence of Elk-VP16 and Elk-VP16(L158P) mutant [DUSP5 gene activation by Elk-VP16 (Elk-1 can regulate the expression of target genes through SRF-independent and SRF-dependent mechanisms . In the ) mutant : only thElk-VP16 .DUSP5 promoter. 5’ 32P labelled oligonucleotides utilized to study the binding of SRF are represented in DUSP5 promoter even in the absence of serum stimulation .EMSA experiments were performed to study the binding of SRF and Elk-1 to CArG boxes and putative EBS over the Then the interaction of Elk-1 with promoter sequences was investigated. The probes that were used are listed in DUSP5 proximal promoter region, we performed ChIP experiments (DUSP5 encompassing the two CArG boxes and the EBS. No significant enrichment was seen using primers amplifying the intron 3 of DUSP5 gene (used as negative control).To further evaluate the binding of SRF and Elk-1 in the eriments . Using Seriments  and Elk-eriments  antibodiDUSP5 gene expression. First, we confirmed that DUSP5 is an early response gene and that the MEK-ERK pathway is essentially involved in the regulation of DUSP5 mRNA expression in NIH/3T3 cell line [DUSP5 expression and also found that PI3K pathway inhibition, as compared with induction with PDGF alone, decreased DUSP5 mRNA levels of ~ 45% (30% in our work after 60 minutes of FCS stimulation) [In this study, we investigated the mechanisms involved in the regulation of ell line , 42, 43.ell line . AKT negell line  and thenulation) .DUSP5 gene expression is regulated at the transcriptional level and that DUSP5 mRNA is not stabilized by the MEK-ERK pathway, contrary to DUSP6 [DUSP6 mRNA half-life is very short (about nine minutes) and ERK activation results in the stabilization of DUSP6 mRNA  [DUSP5 mRNA half-life remained unchanged after MAPK pathway inhibition. Previous work has shown that DUSP5 interacts with ERK and is responsible for its nuclear anchoring, but this binding is not accompanied by the catalytic activation of the phosphatase [DUSP5 mRNA half-life is also comparable to that of the early response gene c-fos mRNA (about 8 to 24 minutes according to the studied cell lines) [DUSP5 mRNA may lead to quick variation of DUSP5 protein level and enzymatic activity, responsible for a tight control of pERK levels.We found that to DUSP6 . When MAminutes) . ERK is minutes) . On the l lines) . The rapDUSP5 promoter sequence, which could provide a link with the MAPK pathway regulation through the binding of TCF. The presence of multiple binding motifs for ETS-domain transcription factors has previously been reported as a characteristic of Elk-1 target genes [DUSP5 promoter is sufficient for its basal and serum or growth factor-induced activity, excluding a major role for EBS located in the distal part of the promoter.We identified several EBS in the proximal and distal part of the et genes . HoweverDUSP5 promoter region using the Vertebrate Multiz Alignment & Conservation track [via ERK activation, SRF is involved in nucleoprotein complexes containing members of the TCF subfamily of the ETS domain transcriptional regulators, such as Elk-1 and recruited to EBS [DUSP5 gene expression for several reasons. Elk-1 is phosphorylated by ERK [DUSP5 and DUSP6 mRNA levels and found no inhibitory effect for DUSP5 but only for DUSP6. In an extensive attempt to identify candidate transcription factor binding sites in genes regulated by specific signaling pathways in growth factor-stimulated human glioblastoma cell line, Tullai et al. [DUSP5 promoter. However, fully experimental validation of the putative CArG box remained to be provided.We also identified in this proximal part two contiguous CArG boxes binding SRF. Tandem CArG elements have been described only for few genes, including SRF itself, whereas multiple non-contiguous CArG boxes in CArG containing genes are frequently found . An analon track  within ton track . The secd to EBS . This pad to EBS –54. Bindd to EBS , 53, 55.d by ERK , 56, 57,d by ERK . Furtherd by ERK  tested ti et al.  reportedDUSP5 promoter activity. SRF-En has been shown to repress c-fos promoter activity and this effect was abolished by mutating the c-fos CArG box [vinculin [DUSP5 promoter activity.As expected, the dominant negative SRF-En and Elk-En repressed CArG box . Elk-En CArG box . Moreovevinculin . On the vinculin , 58. In DUSP5 promoter stimulated with serum suggest that the proximal CArG box may play a regulatory key role in DUSP5 expression. Consistently, EMSA suggests that SRF may bind the proximal CArG box with higher affinity than the distal CArG. We suppose that only one of the two contiguous CArG boxes of the DUSP5 promoter could play a predominant role in vivo because steric hindrance should exclude the possibility that both CArG boxes were bound by SRF homodimers [DUSP5 abolished the induction by the serum or SRF-VP16, but surprisingly not completely by Elk-VP16. Residual activations by Elk-VP16 of c-fos SRE reporter vectors containing ETS mutated binding site have already been reported in serum deprived NIH/3T3 cells [DUSP5 promoter gene does not seem to be essential to activate transcription, as suggested by induction of luciferase activity by the serum and Elk-VP16 in the context of double EBS mutation. On the contrary, the protein-protein interaction between SRF and Elk-1 seems to be essential for efficient ternary complex formation, as highlighted by the absence of induction of DUSP5 promoter reporter with the mutant Elk-VP16 (L158P) which has lost its ability to bind SRF. Likewise, the mutant dominant negative Elk-En(L158P), which is not able to bind SRF either, has been shown to cause little repression of an SRE reporter vector (containing both SRF and EBS), but on the contrary can efficiently repress a reporter containing just ETS motifs [Our luciferase reporter assays with different mutants of the modimers , 60. Mormodimers . As expeT3 cells , 35. We S motifs . Thus ElS motifs .DUSP5 promoter, as already proposed for c-fos [DUSP5 promoter to activate transcription, without necessarily binding to the EBS. One previous ChIP-Seq study identified in a mammary human cell line the putative promoter region of DUSP5 as significantly enriched in Elk-1 signal [Our results suggest a model in which SRF is constitutively bound to the or c-fos . Upon acor c-fos , 62 and 1 signal  in accorin vitro [DUSP5 gene in living cells (data not shown). Using a ChIP method including a two-step cross-linking that first stabilizes large multiprotein complexes over DNA with DSG followed by the conventional formaldehyde cross-linking, we successfully demonstrated the presence of Elk-1 over the SRE of the DUSP5 gene in NIH/3T3 cells. This pitfall supports the hypothesis of a direct protein-protein interaction between Elk-1 and SRF without necessarily DNA binding. Our EMSA performed with recombinant Elk-1-HA, demonstrated, in vitro, the presence of Elk-1 in the supershifted bands obtained with anti-HA antibody and suggested that the mutation created in the putative proximal EBS site (i.e. GGAC) of the DUSP5 promoter may be deleterious for Elk-1 binding. The putative core sequence of the proximal EBS site (i.e. GGAC) of the DUSP5 promoter identified by the TESS program has until recently only been described in vitro but not in vivo [We hypothesize that Elk-1 could interact directly with SRF, independently of its binding to EBS, as already described in vitro , 65. A din vitro . Convent in vivo . However in vivo  identifirsk which is itself phosphorylated and activated by MAPK, has been shown to enhance the rate and affinity with which SRF associates with the SRE [Furthermore our data suggesting that serum stimulation may result in increased binding capacity of SRF to CArG boxes is consistent with results previously reported –69. Site the SRE . Increas the SRE , 68. Mor the SRE .DUSP5 promoter in the basal state, and Elk-1 could also be recruited at the DUSP5 promoter through direct association with SRF regardless of its DNA-binding or through its binding site and activate transcription. Thus induction of DUSP5 by the MEK-ERK pathway serves as an important feedback loop that controls activation of ERK1/2.In summary, we have shown that the DUSP5 phosphatase is regulated at the transcriptional level by the MAPK pathway and that SRE is involved in the regulation of this early response gene. We propose a model in which SRF is bound to


In transcription controlled by σ54, the Eσ54-promoter closed complex requires ATP hydrolysis by an associated bacterial enhancer-binding protein (bEBP) for the transition to open complex and transcription initiation. Given the wide host range of Salmonella enterica serovar Typhimurium, it is an excellent model system for investigating the roles of RpoN and its bEBPs in modulating the lifestyle of bacteria. The genome of S. Typhimurium encodes 13 known or predicted bEBPs, each responding to a unique intracellular or extracellular signal. While the regulons of most alternative sigma factors respond to a specific environmental or developmental signal, the RpoN regulon is very diverse, controlling genes for response to nitrogen limitation, nitric oxide stress, availability of alternative carbon sources, phage shock/envelope stress, toxic levels of zinc, nucleic acid damage, and other stressors. This review explores how bEBPs respond to environmental changes encountered by S. Typhimurium during transmission/infection and influence adaptation through control of transcription of different components of the S. Typhimurium RpoN regulon.Transcription sigma factors direct the selective binding of RNA polymerase holoenzyme (Eσ) to specific promoters. Two families of sigma factors determine promoter specificity, the σ Salmonella enterica subsp. enterica serovar Typhimurium is the most common serotype of Salmonella enterica subspecies, which causes tens of millions of cases of salmonellosis and more than 100,000 deaths worldwide each year . However, the core enzyme alone cannot recognize specific promoter sequences; the variable sigma (σ) subunit confers DNA-binding specificity to ensure that transcription starts at the appropriate promoter sequence  family and the σ54 (RpoN) family. The σ70 family includes the housekeeping sigma factor (σ70/D) and all of the alternative sigma factors, except σ54. These σ70-type sigma factors, which in Salmonella include σ70/D, σ24/E, σ32/H, σ38/S, and σ28, exhibit similar structure and recognize promoter sequences with −35 (TTGACA) and −10 (TATAAT) promoter elements that are conserved to varying extents. When Eσ70 binds to promoter sequences, it initially forms a closed complex, where no DNA melting has occurred. Free energy from specific interactions of Eσ70 with promoter DNA activate conformational changes in both Eσ70 and DNA to form a stable open complex in which duplex DNA is opened at the +1 transcription start site and the template strand moves into the active site of RNAP  and −12 (GG) upstream of the transcription start site . Cellular processes regulated by σ54-dependent bEBPs in S. Typhimurium include nitrogen metabolism in response to limiting nitrogen conditions [NtrC , Keener and Kustu, S. Typhimurium identified RpoN as important in colonization of chicks, pigs, cattle and mice; transposon mutants in bEBP genes ntrC (glnG) and prpR were attenuated in at least two animal hosts and RpoN-regulated genes argT, glnA, glnL, and gfrACDEF  were attenuated in at least two animal hosts , phosphotransferase regulation domains (PRDs) or ligand-binding domains. One bEBP, PspF, lacks a regulatory domain, but a separate protein, PspA, controls PspF activity. The PspF-PspA system, which is required for S. Typimurium virulence in a mouse model  that are response regulators of TCSs, in which a sensor kinase protein recognizes the cellular signal, autophosphorylates, and transfers the phosphate to a conserved aspartate residue of the response regulator. Phosphorylation of the regulatory domain stimulates the bEBP to interact with enhancer sequence(s) and the Eσ54 closed complex, activating open complex formation  and glnHQ (glutamine transport) together contribute to S. Typhimurium virulence in a mouse model and increased survival in macrophages  and enzymes required for utilization of the imported sugar/amino sugar , resulting in expression of S. Typhimurium can utilize D-glucosaminate as both a carbon and nitrogen source  simultaneously  domain with a non-heme iron center that recognizes NO  reductase genes, 54-dependent transcription of putative RNA repair operons of S. Typhimurium , stimulating transcription of the rsr-yrlBA-rtcBA operon  will give a clearer picture of how bEBPs can alter the lifestyle of S. Typhimurium and other pathogens to improve their chances of survival during the infection process.The σCH, AK, and DS each made substantial intellectual contributions to the work, participated in the writing of the mini-review, and approved it for publication.Salmonella RpoN regulon and putative RNA repair operon, respectively.NSF (MCB-1051175) and NIH (R21 AI117102-01A1) grants (to ACK) funded the study of the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The high mobility group protein A1 (HMGA1) is a master regulator of chromatin structure mediating its major gene regulatory activity by direct interactions with A/T-rich DNA sequences located in the promoter and enhancer regions of a large variety of genes. HMGA1 DNA-binding through three AT-hook motifs results in an open chromatin structure and subsequently leads to changes in gene expression. Apart from its significant expression during development, HMGA1 is over-expressed in virtually every cancer, where HMGA1 expression levels correlate with tumor malignancy. The exogenous overexpression of HMGA1 can lead to malignant cell transformation, assigning the protein a key role during cancerogenesis. Recent studies have unveiled highly specific competitive interactions of HMGA1 with cellular and viral RNAs also through an AT-hook domain of the protein, significantly impacting the HMGA1-dependent gene expression. In this review, we discuss the structure and function of HMGA1-RNA complexes during transcription and epigenomic regulation and their implications in HMGA1-related diseases. HMGA1 belongs to the high mobility group (HMG) protein family, comprising a variety of non-histone proteins involved in global chromatin remodeling . Though HMGA1 proteins are typically highly expressed during development where several studies assign them important roles in regulating normal cell proliferation, embryonic cell growth and cell differentiation ,12,13,14In recent studies, we have identified highly specific interactions of HMGA1a protein with the nuclear non-coding 7SK RNA and the transactivating response element (TAR) located in the nascent transcript of HIV-1 ,24,25. 7While the interaction of HMGA1 with DNA via its three AT-hook motifs has been extensively studied during the last decades ,33, RNA-In 2007, a study by Manabe and colleagues pointed at a role of HMGA1 during exon-skipping of presenilin-2 pre-mRNA, which results in the production of a deleterious protein isoform found in brains of patients suffering from Alzheimer’s disease, and thus provided first evidence for a specific RNA affinity of HMGA1 . In moreAside from the interaction with 7SK RNA, we have recently shown that HMGA1 also specifically binds a RNA structure located in the nascent transcript of the HIV-1 genome, known as the transactivating response element (HIV-1 TAR) . HIV-1 tThe fact that one of the high-affinity DNA-binding domains of HMGA1 (the first AT-hook motif) is the binding site for 7SK RNA suggests a role of 7SK RNA as a competitive regulator of those HMGA1 functions necessitating a direct interaction of HMGA1 with DNA, such as chromatin regulation and enhanceosome formation see .Indeed, the overexpression of the 7SK loop 2 substructure as a chimera with the EBER2 RNA of Epstein-Barr Virus in a cell culture model, taking advantage of the strong EBER2 promoter ,40, leadThe first AT-hook motif of HMGA1 contributes the majority of HMGA1’s DNA binding capacity . BindingIn fact, we have shown a gene-specific cooperation of HMGA1 and P-TEFb during gene expression regulation . ImportaIn the case of HIV-1 transcription, the 7SK/P-TEFb complex has been shown previously to be located in close proximity to the HIV-1 core promoter, but a mechanism for its recruitment remained unexplored . SubsequThe 7SK/HMGA1 interaction not only regulates HMGA1 function, but is also essential for the recruitment of 7SK-bound P-TEFb to cellular and viral promoters, establishing plasticity between HMGA1-dependent chromatin remodeling and P-TEFb-dependent transcription elongation regulation.HMGA1 has been previously implicated in HIV-1 infection as a host cellular co-factor recruiting the nucleosome remodeling complex SWI/SNF to the HIV-1 LTR, being involved in HIV-1 splice site regulation and contributing to the HIV-1 pre-integration complex ,48,49,50Interestingly, our recent findings of HMGA1 being a recruiting factor for CTIP2-inactivated P-TEFb to the HIV-1 core promoter constitute another mechanism of HMGA1-mediated HIV-1 silencing ,47. WhetTaken together, HMGA1 depicts a host cellular co-factor involved in a large variety of aspects during HIV-1 infection, some of which may synergize, especially those involved in HIV-1 transcription regulation.Abnormally high expression rates of HMGA1 constitute a hallmark for the vast majority of cancers see  and geneThus, targeting HMGA1 is increasingly gaining attention in the field of anti-cancer therapeutical approaches (reviewed in ). RecentTargeting HMGA1 function in gene expression regulation by 7SK Loop2 RNA, as demonstrated in our studies, may establish another promising approach for fighting HMGA1-dependent cancerogenesis ,24. The In the case of HIV-1 infection, HMGA1 affects viral gene expression by at least two different mechanisms: A direct binding to HIV-1 TAR, preventing Tat-mediated transcription activation and the recruitment of CTIP2 and CTIP2-inactivated P-TEFb complex ,45. BothTargeting HMGA1 function is also challenged by the fact that HMGA1 asides from its crucial role during development also is responsible for gene regulatory activity on cellular promoters during homeostasis. Indeed, HMGA1 is required for physiological expression of the insulin receptor  and glucTaken together, HMGA1 has been proven to be a key player during cancerogenesis and an important host cellular factor for the expression of a variety of viral genomes. Targeting HMGA1 function by an overexpression or delivery of the Loop2 region of its endogenous interaction partner 7SK RNA may thus add to a growing number of different approaches for fighting HMGA1-related diseases.


GATA1 genes, TR4-regulated target genes in human erythroid cells remain unknown. Here, we identified TR4 binding sites genome-wide using chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq) as human primary CD34+ hematopoietic progenitors differentiated progressively to late erythroid precursors. We also performed whole transcriptome analyses by RNA-seq to identify TR4 downstream targets after lentiviral-mediated TR4 shRNA knockdown in erythroid cells. Analyses from combined ChIP-seq and RNA-seq datasets indicate that DR1 motifs are more prevalent in the proximal promoters of TR4 direct target genes, which are involved in basic biological functions . In contrast, other non-DR1 repeat motifs  are more prevalent at gene-distal TR4 binding sites. Of these, approximately 50% are also marked with epigenetic chromatin signatures  associated with enhancer function. Thus, we hypothesize that TR4 regulates gene transcription via gene-proximal DR1 sites as TR4/TR2 heterodimers, while it can associate with novel nuclear receptor partners (such as RXR) to bind to distant non-DR1 consensus sites. In summary, this study reveals that the TR4 regulatory network is far more complex than previously appreciated and that TR4 regulates basic, essential biological processes during the terminal differentiation of human erythroid cells.We previously reported that TR2 and TR4 orphan nuclear receptors bind to direct repeat (DR) elements in the ε- and γ-globin promoters, and act as molecular anchors for the recruitment of epigenetic corepressors of the multifaceted DRED complex, thereby leading to ε- and γ-globin transcriptional repression during definitive erythropoiesis. Other than the ε- and γ-globin and the  Sequential genome-wide binding studies investigated by deep sequencing (ChIP-seq) represent a powerful tool for investigating the temporal sequence of gene activation and repression events that take place as cells differentiate. Here, we report the binding of an “orphan” nuclear receptor (one for which no ligand has been identified) to its cognate genomic regulatory sites and perform the functional analysis to validate its downstream targets as precursor cells differentiate from very early human hematopoietic progenitors into red blood cells. We discovered that when this receptor is bound at gene proximal promoters, it recognizes a different DNA sequence than when it binds to more distant regulatory sites (enhancers and silencers). Since this receptor can either activate or repress specific target genes, the data suggest the intriguing possibility that the two different modes of DNA recognition may reflect association of the receptor with different partner molecules when regulating gene expression from proximal or distal sequences. Hereditary Persistence of Fetal Hemoglobin (HPFH) mutations have high levels of fetal γ-hemoglobin (HbF) that aberrantly persist into adulthood Sickle cell disease (SCD) is an inherited blood disorder caused by a missense mutation in the adult β-globin gene and affects 70,000–90,000 people in the United States and millions worldwide cis-element, a consensus binding site for non-steroidal nuclear receptors −/−/TR4−/− mutant embryos bearing a human β-globin YAC transgene that ε- and γ-globin gene expression was elevated in definitive erythrocytes We previously identified an essential direct repeat 1 (DR1) in vitro and in vivo studies have shown that TR4 is capable of binding to an imperfect DR consensus sequence separated by zero to five spacer nucleotides (DR0 - DR5) Compared with TR2, TR4 appears to play a more prominent role in γ-globin repression during definitive erythropoiesis GATA1, which is stage-specifically bound by TR4 at a DR1 element located within the GATA1 hematopoietic enhancer (G1HE) Prior to the present study, genome-wide TR4 binding site analysis was performed in four ENCODE cell lines: K562 embryonic erythroleukemia cells, HepG2 liver carcinoma cells, HeLa cervical carcinoma cells and GM12878 immortalized lymphoblast cells bona fide TR4-regulated downstream target genes during human erythroid differentiation ex vivo.In this study, we resolved the genome-wide binding of TR4 in differentiating human erythroid cells by performing chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq). We also performed whole transcriptome analyses by RNA-seq to identify genes that are regulated by TR4 both before and after lentiviral-mediated TR4 shRNA knockdown in erythroid cells. We found that TR4 preferentially binds to DR1 elements in the promoters of such direct target genes, and that the majority of these genes encode proteins that participate in fundamental biological functions such as mRNA processing, translation, RNA splicing and primary metabolic processes. Interestingly, we also found an increased occurrence of non-DR1 repeat elements  bound by TR4 at sites located more than 10 Kbp away from the nearest gene. This raised the tantalizing possibility that TR4 might heterodimerize with nuclear receptors other than TR2, thereby allowing TR4 to elicit unique transcriptional responses when acting at proximal (promoter) and distal (enhancer and silencer) regulatory sites during human erythropoiesis. In support of this hypothesis, we detected a specific TR4/RXR interaction in MEL cells in which biotin-tagged TR4 was forcibly expressed. In summary, these combined ChIP-seq and RNA-seq analyses provide a genome-wide map of TR4 binding sites as well as a comprehensive list of + hematopoietic progenitor cells were cultured ex vivo using a previously described two-phase erythroid differentiation system Figure S1). D8, D11 and D14 cells were separately harvested for ChIP-seq and RNA-seq assays.Primary human CD34+ cell cultures and generated a total of 32, 54 and 55×106 TR4 ChIP-enriched, 50-bp short reads, respectively . To further assess the quality of the ChIP-seq data, thirty peaks detected at all three differentiation stages were further evaluated by ChIP-qPCR, and a strong correlation (0.82) between the two independent assays was observed for those peaks .We then performed TR4 ChIP-seq on D8, D11 and D14 cells from two independent differentiating CD34ectively Table 1.Annotation of TR4 peaks was based on the shortest distance from the center of a peak to the transcription start site (TSS) of the nearest RefSeq gene. Each TR4 peak was then categorized according to position: within the gene or in the 5′ or 3′ flanking genomic sequences  lying within the gene and promoter .Unlike the increased percentage of peaks found in the proximal promoter as erythroid cells differentiated, the percentage of TR4 peaks in distal II (10 to 100 Kbp from TSS or TES) and gene deserts (>100 Kbp away from TSS or TES) lying both 5′ and 3′ to genes decreased between days 8 and 14  4 days after initiating erythroid differentiation. Forty-eight hours following infection, the cells were then subjected to puromycin selection. The knockdown RNA samples were harvested at day 11 for RNA-seq analysis using an Illumina HiSeq2000 platform. Prior to submitting the samples for RNA-seq, we confirmed that there was a significant reduction in TR4 protein levels (∼70%) in cells transduced with either shRNA lentivirus by immunoblotting . Of these common targets, 80%  were transcriptionally induced while the remaining 20%  were repressed after TR4 diminution, suggesting that TR4 acts predominantly as a (direct or indirect) repressor of target genes in differentiating erythroid cells.Overall, 15,024 (84% of expressed) genes met a minimum established threshold of 0.1 FPKM in at least one mRNA dataset . After applying double cutoffs of fold change ≥2 and FPKM ≥0.1 in either shRNA-treated or control dataset, we identified 2,861, and 2,884 genes that were differentially expressed after infection with the anti-TR4-sh#174 or -sh#658 lentiviruses, respectively. Of these, 2,188 (∼76%) differentially expressed genes were common in both shRNA-treated datasets, which included both direct and indirect TR4 target genes (Gene ontology (GO) analysis showed that TR4-repressed genes encode proteins that are components of the plasma membrane and extracellular matrix or are involved in diverse cellular processes such as signal transducing activity, calcium ion binding functions, inflammatory responses, chemotaxis and others . To determine whether these putative targets with TR4 proximal promoter binding are in fact regulated by TR4, we investigated the expression profile of these genes in D11 cells after lentiviral-mediated TR4 shRNA knockdown. For each of the 130 genes with TR4 peaks in the proximal promoter at D11 . Since genes encoding such critical physiological functions are more likely to be protected by redundant or compensatory activity, this could partially explain why we did not detect greater than 2-fold change in expression of most of these 130 genes  of all TR4 peaks were found in gene proximal promoters TCA de novo transcription binding site discovery program, from the Genomatix data analysis package as well as DREME We used CoreSearch, the all peaks  . Of the D8 peaks , 257 and 490 peaks were located in the proximal promoter or >10 Kbp away from the nearest gene, respectively. Comparing these two groups, we found that only the frequency of the DR1 motif was reduced (from 28% to 8%), but all other motifs significantly increased  at each differentiation stage. The analysis revealed that the sequences at the center of all peaks across differentiation days 8,11 and 14 were generally more highly conserved than the flanking sequences across either vertebrate, mammalian or primate species , a random sequence of the same length (250 bp) and GC content from the same chromosome was used to compute a background conservation score. These analyses revealed that the peaks in the proximal promoters of D8, D11 and D14 cells showed the highest conservation across vertebrate, mammalian and primate species (We therefore next asked if any enhancer marks were present in the sequences (±2 Kbp) immediately adjacent to each TR4 peak that was located >10 Kbp from the nearest gene using ENCODE data from analysis of the K562 erythroid cell line de novo motif analysis to identify other enriched transcription factor binding sites (TFBS) within distant TR4 peaks using CoreSearch and DREME. This analysis did not reveal any single overrepresented TFBS at any stage of erythroid differentiation (data not shown). For example, at day 14, a variety of sites (including MZF1 or GATA1) were scattered among these peaks, suggesting that TR4 might interact directly or indirectly with these transcription factors to regulate specific target genes from great distances.We next performed We further queried the sequences of each peak (250 bp) in the proximal promoters and lying >10 Kbp from genes using the “overrepresented transcription factor binding modules” analytical tool from Genomatix. This analysis tool searches for all TFBS and generates statistics on possible TFBS pairs (modules) within the input sequences over the genomic background. Of the top ten transcription factor families that could interact with the NR2 family (to which TR4 belongs), there was no overlap in the TFBS pairs between gene-proximal and -distal TR4-bound peaks, possibly suggesting that TR4 collaborates with distinct transcription factors in gene-proximal and -distal regulatory elements in a highly tissue-specific manner to exert its effects on transcription Table 3.In summary, we found that TR4 peaks located far from genes had significant cross species conservation and some of these also bore enhancer signature epigenetic marks. However, using multiple analysis tools, we were unable to identify any preferred transcriptional co-effectors in the hypothesized TR4-mediated long-range gene regulatory sites.+ cells as they differentiate into erythroid cells. These analyses revealed 1,025, 373 and 325 TR4 binding sites in erythroid cells at early through late differentiation stages . Of these binding sites, the frequency of TR4 proximal promoter binding rose from 25% to 60% between the proerythroblastic and reticulocyte stages (from day 8 to day 14). De novo motif analysis revealed that in proximal promoters, DR1 NR binding sites and ETS motifs were the most overrepresented sequences. This conclusion is consistent with our previous TR4 ChIP-seq study examining TR4 binding in four ENCODE cell lines K562, HepG2, HeLa and GM12878 in vivo genome-wide TR4 ChIP analyses indicate that TR4 preferentially binds to DR1 elements in the proximal promoters in ENCODE cell lines In this study, we surveyed all orphan nuclear receptor TR4 binding sites throughout the genome as well as its downstream targets using ChIP-seq and RNA-seq in human primary CD34Our combined ChIP-seq and RNA-seq data suggest that TR4 acts primarily as a transcriptional activator at the proximal promoter of target genes, and most of these are involved in fundamental physiological functions  during erythropoiesis. This observation also agrees with an earlier study in which we reported that target genes  exhibiting TR4 proximal promoter binding encode constituents of the spliceosome and the ribosome or are involved in other mRNA metabolic processes Tr2 and Tr4 alleles leads to greater γ-globin induction in definitive erythrocytes of mutants bearing a human β-globin YAC transgene than mice bearing single Tr2 or Tr4 null mutations The expression of most TR4 direct targets with peaks in the proximal promoter was only weakly reduced in abundance (<2-fold change) after TR4 knockdown. This could be a consequence of the residual TR4 protein (30%) in the knockdown cells that may still be able to execute much of TR4 normal function, or of compensation by other nuclear receptor such as TR2, or both. In an earlier study, we observed that the combined loss of More recently, with the advent of deep sequencing technologies the genome-wide nuclear receptor binding site analyses of ERα, AR, GR, PPARγRXR and VDR have suggested that nuclear receptors act far more frequently (>60%) from distant sites than do other classic transcription factors that bind to the proximal promoters bona fide target genes. For example, in the present study, when we assigned the TR4 distal peaks to the closest differentially expressed gene, instead of the physically closest gene, the median distance was more than 900 Kbp. In other nuclear receptor studies, the median distance from GR binding sites to their closest activated or repressed targets was 11 Kbp or 146 Kbp, respectively One major conceptual and experimental challenge is how we might link the binding of distant nuclear receptor sites to their cis-regulatory potential. However, the mechanism underlying such distal regulation is still largely unknown, although it has previously been speculated that chromatin modifying cofactors might aid nuclear receptors in regulating transcriptional targets from a distance Both sequence conservation and the coincidence of enhancer epigenetic signatures indicate that a significant fraction of TR4 distal binding sites have When we restricted the binding site motif analysis exclusively to repeat elements using the NHR-scan program, we discovered that while DR1 was the most represented motif in TR4 proximal promoter bound peaks, other nuclear receptor binding motifs  were more frequently represented in peaks lying greater than 10 Kbp away from the nearest gene. Hence, we speculate that within the nuclear receptor superfamily, TR4 binds to promoter DR1 element of its targets most often by heterodimerizing with TR2, but that TR4 exerts its long-range regulatory effects by binding to DR4, ER6 and IR1 gene-distal repeat elements, perhaps in association with other nuclear receptors such as RXR.One curiosity we report was that over half of the TR4 binding peaks reported here did not contain any recognizable nuclear receptor repeat element. It has been proposed that nuclear receptors can modulate gene expression by interfering with other transcription factors to alter target gene expression, referred to as “transcriptional crosstalk” In this study, we also found that TR4 protein was expressed more abundantly at later erythroid differentiation stages. Based on the expression profiling of differentially expressed genes (fold change ≥2 and FPKM ≥0.1 in any dataset) after TR4 depletion, we found that TR4 most often acts as a repressor. During the progression of erythroid differentiation the majority of genes become repressed and chromatin becomes condensed. The more abundant expression of TR4 during later stages might be required to fulfill these suspected repressor functions during differentiation. However, it seems contradictory that TR4 increases in expression as the total number of TR4 binding peaks diminish as erythroid cells mature. One possible explanation is that TR4 might be temporarily required for the initiation of transcriptional repression by recruiting repressive cofactors to target gene loci thereby facilitating chromatin condensation. During the process of chromatin condensation, after TR4 has fulfilled its function (bringing corepressors to chromatin) it might be released from its target binding sites. That could partially explain why we observe an opposite trend of increasing TR4 expression at the same time as the number of TR4 binding sites diminishes later during erythroid differentiation.bona fide, direct target genes.Finally, we note that reducing the abundance of TR4 in human erythroid cells resulted in the down-regulation of genes enriched in erythroid differentiation and gas transport. However, the closest TR4 binding to these genes was >1 Mbp away. In this regard, it is difficult to distinguish whether these genes are under TR4 long-range regulation or whether they are only indirectly affected by TR4 depletion. While we have definitively documented that TR2/TR4 heterodimer binding at the γ-globin promoter DR1 site was a prerequisite for γ-globin silencing in definitive erythroid cells Research on human specimens was conducted in full compliance with federal and institutional regulations and guidelines.+ hematopoietic progenitor cells, isolated from the peripheral blood of healthy adult donors following granulocyte colony-stimulating factor (G-CSF) mobilization, were purchased from the Fred Hutchinson Cancer Research Center. Briefly, these cells were cultured ex vivo using a two-phase culture method, as described previously Cryopreserved primary human CD348 cells were harvested on culture days 8, 11 or 14 and cross-linked with formaldehyde. Chromatin in complex with TR4 was then sonicated and incubated with rabbit anti-TR4 antibody ChIP was performed as described previously ChIP-enriched and input control DNA libraries were sequenced on an Illumina HiSeq 2000. DNA sequencing reads that passed FastQC quality control were aligned to the reference genome , and peaks were identified using MACS (version 1.4) Database for Annotation, Visualization and Integrated Discovery (DAVID) webtool  The pLKO.1-puromycin resistant lentiviral shRNAs (short hairpin RNAs) used to reduce TR4 mRNA levels were purchased from Sigma-Aldrich (TRCN0000245174 and TRCN0000021658). The pLKO.1 control vector was generated as described previously + cells on days 8, 11 or 14 was purified by ISOGEN (Nippon Gene). RNA integrity and quality were verified using a 2100 Bioanalyzer (Agilent Technologies). The RNA integrity number (RIN) for all RNA samples used in this study was 10, indicating that the RNA quality was maximal.Total RNA from CD34+ RNA was purified using poly-dT oligo-attached magnetic beads from 10 µg of total RNA extracted from day 8, 11 and 14 differentiated erythroid cells, and then sheared into short pieces. These RNA fragments were reverse-transcribed using random primers into double-stranded cDNA fragments. Finally, these cDNA fragments were end repaired and Illumina adapters were appended to both ends. After PCR amplification, cDNA fragments of approximately 200 bp in length were selected for library generation and were sequenced in a paired-end 72-bp sequencing format using the Illumina Genome Analyzer IIx system at the University of Michigan DNA Sequencing Core. For erythroid cells in which TR4 was depleted using lentiviral shRNAs, the process was the same except that the sequencing platform was a paired-end 50-bp format on an Illumina Hiseq2000.Construction of the RNA-seq libraries was performed according to the manufacturer's instructions (Illumina). In brief, polyABoth DREME Fragments Per Kilobase of transcript per Million mapped reads (FPKM)]. The expression data has been deposited in the NCBI Gene Expression Omnibus (GSE54602 and GSE54760).For RNA-seq data analysis, we aligned the raw reads from ELAND to the human genome  using TopHat (version v2.0.10) with default settings The generation of biotin-tagged TR4 in MEL cells was described previously After SDS-PAGE, the proteins were transferred to a nitrocellulose membrane (Li-Cor) and probed with TR4, RXR , RAR  as well as fluorescence-conjugated secondary antibodies (Li-Cor). The proteins were visualized on an Odyssey infrared imaging system (Li-Cor).http://hgdownload.cse.ucsc.edu/goldenPath/hg19/phastCons46way/README.txt). The total PhastCons score of the individual nucleotides was then divided by the length (250 bp) to achieve an average PhastCons score for each peak.The center 250 bp of each ChIP-seq peak was examined for interspecies sequence conservation by calculation of PhastCons scores. In detail, the PhastCons scores of 46 vertebrate species and two subsets including 33 placental mammal species and 10 primate species were first extracted from the UCSC table browser  and, if there was a predicted DR, IR or ER repeat element , we ensured that the amplicon included that region. For RNA-seq data validation, we randomly selected twenty genes that were broadly expressed and performed RT-qPCR. Primer pairs were designed to span exon/intron junctions. The methods for RNA extraction, cDNA synthesis and qPCR were as described previously Figure S1ex vivo. (A) Immunoblots of TR4 and β-actin  during erythroid differentiation on day 8, 11 and 14. (B) Quantification of the TR4 expression by normalized it to the signal intensity of β-actin (**p<0.01 and error bars represent s.e.m.).Expression of TR4 as human erythroid cells differentiate (PDF)Click here for additional data file.Figure S2A representative view of TR4 binding as erythroid differentiation progresses at the proximal promoter of the CHMP4B gene by integrative genomics viewer (IGV). The red lines indicated TR4 binding at differentiation days 8, 11 and 14; the blue lines represent the corresponding input controls in the same sequences.(PDF)Click here for additional data file.Figure S3A) TR4 binding detected by ChIP-seq was validated by ChIP-qPCR. (B) Gene expression detected by RNA-seq was validated using RT-qPCR. The relative fold change in TR4 enrichment or the gene expression in all assays was normalized to that of day 8 erythroid cells and the data are presented as binary logarithms (log2). The Pearson's correlation coefficient, r, for each data set is indicated.Validation of TR4 ChIP-seq and RNA-seq data. ((PDF)Click here for additional data file.Figure S4Distribution of peaks located >10 Kbp from the nearest genes. Peaks located 10–100 Kbp upstream , 10–100 Kbp downstream  or >100 Kbp either 5′ or 3′ from the nearest genes (gene desert) are graphed. The bin size is 10 Kbp for 5′ distal II and 3′ distal II and 100 Kbp for the gene deserts.(PDF)Click here for additional data file.Figure S5A) or gene expression (B) given the distance (from peak center) to the nearest TSS in day 8, 11 and 14 erythroid cells. The gene expression profile was generated by RNA-seq and measured as FPKM.TR4 peaks close to TSSs are more enriched and are associated with higher gene transcription levels. Box-and-whisker diagrams illustrating the correlation of peak enrichment ((PDF)Click here for additional data file.Figure S6Comparison of the average PhastCons scores of TR4 peaks and random control sequences among the peaks located at the proximal promoter, >10 Kbp from genes or of all identified peaks at day 8 (upper panels) or day 11 (lower panels) of differentiation.(PDF)Click here for additional data file.Table S1+ cells after TR4 depletion by two different shRNA-encoding lentiviruses Click here for additional data file.