The oncoprotein c-MYC regulates a large array of genes which play important roles in growth regulation and metabolism. It is dysregulated in >70% of human cancers. The silencer NHEIII1 located upstream of the P1 promoter regulates up-to 80% of c-MYC transcription and includes a G-quadruplex structure (Pu27) that is required for promoter inhibition. We have identified, for the first time, a family of seventeen G-quadruplex-forming motifs with >90% identity with Pu27, located on different chromosomes throughout the human genome, some found near or within genes involved in stem cell maintenance or neural cell development. Notably, all members of the Pu27 family interact specifically with NHEIII1 sequence, in vitro. Crosslinking studies demonstrate that Pu27 oligonucleotide binds specifically to the C-rich strand of the NHEIII1 resulting in the G-quadruplex structure stabilization. Pu27 homologous sequences (Pu27-HS) significantly inhibit leukemic cell lines proliferation in culture. Exposure of U937 cells to the Pu27-HS induces cell growth inhibition associated with cell cycle arrest that is most likely due to downregulation of c-MYC expression at the RNA and/or protein levels. Expression of SOX2, another gene containing a Pu27-HS, was affected by Pu27-HS treatment as well. Our data suggest that the oligonucleotides encoding the Pu27 family target complementary DNA sequences in the genome, including those of the c-MYC and SOX2 promoters. This effect is most likely cell type and cell growth condition dependent. The presence of genomic G-quadruplex-forming sequences homologous to Pu27 of c-MYC silencer and the fact that they interact specifically with the parent sequence suggest a common regulatory mechanism for genes whose promoters contain these sequences.G-quadruplex forming sequences are particularly enriched in the promoter regions of eukaryotic genes, especially of oncogenes. One of the most well studied G-quadruplex forming sequences is located in the nuclease hypersensitive element (NHE) III The presence of secondary structure in guanine-rich oligonucleotides was first documented in the late 1980’s . G-quadrOne of the most well studied G-quadruplex forming sequences is located in the promoter region of the c-MYC oncogene. The c-MYC gene product is a transcription factor that can activate and/or repress the expression of a large array of genes  that arec-MYC are multiple and complex. One of the major sites of control for human c-MYC transcription has been localized in the region -115 base pairs upstream of the P1 promoter which has been designated as the nuclease hypersensitive element (NHE) III1 This sequence controls >80% of c-MYC expression . The oligonucleotides were purchased from Oligos etc.   at 500μM and stored at -20°C.The sequences for Pu27 and 17 homologous oligonucleotides located in different chromosomes were determined using a BLAT search of Pu27 on the human GRch38 genome assembly  (deg x cm2 x decimole-1).Oligonucleotide samples were diluted at 5μM in TM buffer (50mM TRIS-HCl/2.5mM MgCl32P-ATP (3μCu) using T4 PNK and 1x kinase buffer for 20 minutes at 37°C. Unincorporated nucleotides were removed using G-25 Sephadex columns. Samples  were then mixed with cold oligonucleotide, boiled for ten minutes and allowed to anneal overnight. An equal volume of 2x glycerol dye was added and run on a 15% native acrylamide gel at 250V for 3h. Bands were visualized by exposing a Kodak phosphor-imager screen and scanned using a Molecular Imager  then to Kodak film for 12h at -80°C.Oligonucleotides were 5’-labeled with 1 of the c-MYC promoter (TS), was incubated with 100,000cpm of 32P-labeled Pu27 or Pu-HS in 20mM HEPES (pH 7.9), 25mM KCl, 2mM MgCl2, 0.1mM EDTA, 0.2mM DTT, 2mM spermidine and 10% glycerol for 15 min at 37°C. For the competition assay, increasing concentrations of “cold” Pu27 oligonucleotide (1nM to 1μM) were added to each labeled oligonucleotide and incubated for an additional 15 min. After incubation, an equal volume of 2x glycerol dye was added. Complexes  were resolved by electrophoresis on a 5% non-denaturing polyacrylamide gel, and visualized as described above.PCR product of 134bp covering the NHEIII1 were hybridized with Pu27 or Pu27 containing the cross-linker [3-cyanovinylcarbazole (CNVK) kindly provided by Dr. Niles A. Pierce] that was incorporated at the position 1 = PuK1 or position 12 = PuK12 of the Pu27 nucleotide sequence (PuK1 and PuK12 were synthetized by IDT). The cross-linking protocol follows the methodology described by Dr. Pierce   . Data ar6cells/5ml in the presence of 10μM Pu27-HS compared to untreated for 72h. At this time point cells were collected and divided in 3 tubes to perform FACS analysis, RNA extraction and protein extraction.U937 were cultured at 1x10® reagent  and stored at -80°C until samples for 3 separate experiments were collected. RNA extraction was performed following manual instruction and concentration measured on NanoDrop 2000 . The purified RNA (0.1μg/ sample) was used to generate cDNA with the SuperSript® VILO cDNA synthesis Kit following the instruction manual. To detect the expression of c-MYC and SOX2 primer pairs were designed  and form the 4 Leukemia cell lines previously used in this study as described above. cDNA was generated with 100ng of RNA and evaluated in RTq-PCR. The primers sequences are located in T values obtained from normal donors and leukemia cells. A CT value above 34 was considered not determined.RNA was extracted from 1x106 cells/5ml in the presence of 10μM either Pu27-HS compared to untreated cells for 3 days. Cells were collected, washed in PBS and fixed in 70% ethanol and stored at -20°C for at least 2 hrs. Cell suspensions were then washed in PBS and incubated with 5μl 7AAD  for 20min on ice then analyzed on FACSCalibur . FACS data analyses were performed using the multicycle analysis program from FCS Express4 software . Data are expressed as percent of cells in each cell cycle sub-group averaged for 3 separate experiments.U937 were cultured at 1x105 cells/5ml in the presence of Pu27 or Pu27-HS (10μM) compared to untreated cells for 3 days. Total protein lysates was prepared using M-Per lysis buffer  containing protease inhibitors  according to manufacturer instruction and quantified using Coomassie Protein reagent . Equal amounts of protein were run in 4–15% gradient gel (Bio-Rad) for 1h at 70 V, and then transferred to PVDF membrane using an Iblot (Invitrogen™). The membrane was blocked with 5% non-fat dry milk, washed in PBST (PBS/0.05% Tween), hybridized for 1h at RT with anti-c-MYC antibody or anti-Sox2 , α-tubulin or β-tubulin , were used to normalize the protein loading followed by washes in PBST, then incubated 1h at RT with goat anti-mouse antibody. The protein was visualized using femto-chemiluminescence reagent (Thermo Scientific™ Pierce™).U937 were cultured at 1x10All data are expressed as mean +/- standard deviation (SD) between untreated versus treated and assessed using unpaired two-tailed Student T-test and one-way ANOVA. Data were considered significant for p-value < 0.05.http://genome.ucsc.edu)] with Pu27ge identified 17 homologous sequences (from 88% to 100% homology) localized on different chromosomes , (http://www.cbrc.jp/research/db/TFSEARCH.html)]. Common binding sites for GR-α, TFII-I, RXR-α and MZF1 (with 1 to 4 binding sites) were identified within all members of the Pu27 family. Putative binding sites for STAT4, c-ETS1 and ELK-1 were also found in most of the Pu27-HS, while SP1, IKZF1, GATA1 or P53 were found in 1 or 2 sequences only (The low complexity and repetitive pattern of the Pu27-HS suggests the presence of binding sites for transcription factors (TF). In fact, it has been shown that the P0-P1 region of lin, SP1 –60 and 4lin, SP1 . Therefoces only .Although the Pu27-HS are of different lengths, they all contain a common core of four consecutive runs of three to four guanines suggesting the capability to form G-quadruplex structures. Therefore oligonucleotides encoding each Pu27-HS were analyzed by Circular Dichroism spectrometry (CD). All of the Pu27 family members formed an intramolecular parallel G-quadruplex evidenced by the presence of a peak of Molecular Ellipticity (θ) at 260-262nm . The higc-MYC promoter region  is a photoactive nucleoside analogue originally described by Yoshimura et.al. [CNVK. Since the crosslink with CVNK is stable even at high temperature [To further characterize the binding of Pu27 to its target sequence and determine the mechanism by which this binding could alter cleotide . The croa et.al. , 66, thac-MYC promoter NHEIII1, it is conceivable that other genes containing these sequences could be regulated in the same manner. Among the genes containing such sequences, SOX2 is the most likely to be expressed in the hematopoietic progenitor cells present in leukemia cell lines. The SOX2 promoter contains a G-quadruplex forming sequence of the Pu27 family: Pu3+. SOX2 is a transcription factor present in stem cells involved in the maintenance of stem cell self-renewal and is also part of the transcription cocktail along with c-MYC for the generation and maintenance of iPSC. Furthermore, SOX2 and c-MYC are present at the same transcription sites of a large variety of genes [SOX2 gene was indeed expressed in all cells leukemia and normal PBMC  was considered significant for a number of cycles below 34 for highly expressed and CT values between 34 and 35 for lowly expressed and not detected for CT values above 35. The data show that Pu3+, Pu11 and Pu14 were highly expressed in all four cell lines and PBMC indicating their presence in the untranslated mRNA- while Pu2, Pu16 and Pu20 were expressed in leukemic cells and less in PBMC  that may involve intra-chromosomal and inter-chromosomal interactions. Such interactions have been reported for enhancers localized at sites distant from the gene promoter such as in the β-globin cluster gene [c-MYC transcription, as enhancers have been found as far as 335Kb from the c-MYC promoter [1 further suggesting a role in LCR for this silencing element. Another possibility is that one or more of these Pu27-HS may be transcribed into a noncoding transcript which will interact specifically with the parent Pu27 target sequence. Such an interaction if it occurs would be expected to stabilize the G-quadruplex structure keeping the transcription in off position and would be sequence and gene specific. In fact, we found that most of the sequences of the Pu27 family are present in the transcriptome. The relative expression of such sequences seems to be proportional to their presence in the UTR of transcribed genes such as SOX2, NAV2 or SPTLC2 and would likely be cell/tissue specific. It is thus possible that in normal cell function the G-quadruplex contained in the newly transcribed mRNA regulates further transcription in a DNA-RNA back-loop binding as it has been demonstrated for c-MYC 5’UTR mRNA [The oligonucleotides encoding all the Pu27-HS were confirmed to form G-quadruplex and to bind specifically to the double stranded Pu27 parent sequence in NHEIIIll lines . We showter gene  and eventer gene ). There promoter , 75 and promoter  and TCF-promoter , 78. At UTR mRNA . The low1 on c-MYC regulation and therefore they may define concordant pathways for gene regulation. This also predicts cell specificity for these sequences. In this work, the comparison of the effect of the different Pu27-HS on the expression of c-MYC and SOX2 revealed that the majority of these G-quadruplex sequences affect both genes expression in the same manner suggesting that this will be true for all the genes containing such sequences. Furthermore, most of the Pu27-HS affect cells similarly as Pu27 suggesting that they are interchangeable, and confirmed the binding of the Pu27-HS to the same sequences in the gene promoters. This will be in concordance with different regulatory mechanisms utilized by the Pu27-HS depending most likely on the binding site (in the gene or 5’UTR-mRNA) and the cell type/condition (see further for possible mechanisms in c-MYC and SOX2 expression (silencing these genes) Pu3+ -which is located in the SOX2 transcribed region- upregulated these two genes expression suggesting different mechanisms of action for Pu27 and Pu3+ to control their respective gene expression at least in this leukemic cell line. It is possible that the difference in gene regulation for Pu27 and Pu3+ depend on the position of their genomic counterpart within their respective gene. Notably, U937 cells were not very sensitive to Pu3+ at day 5 , for genes involved in DNA replication and in the check points  thus interfering with the cell cycle progression at different level . Notably1 in Triplex manner  in all the Pu27 homologous sequences [1 requirement for c-MYC transcription silencing is dependent upon formation of G-quadruplex structures [-MYC transcription. In leukemia, c-MYC overexpression may be caused by translocation or amplification implying that the control normally exerted by NHEIII1 through stable G-quadruplex structure is abolished, thereby freeing TF binding sites that could promote c-MYC expression. The addition of exogenous Pu27 that bind specifically to NHEIII1 could stabilize the G-quadruplex either by strand invasion of the complementary C-rich strand (as suggested by the crosslinking experiment describe herein) or by Hoogsteen hydrogen bonds on the G-rich strand [1.It is interesting to speculate about the reason for the existence of these G-quadruplex motifs which contain a similar core of oligonucleotides sequence but are located in different chromosomes. It is possible that quadruplex-forming sequences represent a generalized mechanical feature as suggested by Sen et al. , 84 to sequences  favors aequences . MZF1 maequences , it has equences . Furtherructures , 40, 86.h strand  occupyinc-MYC and SOX2, neural cell differentiation  or near gene involved in senescence such as BRD7 suggested a shared regulatory mechanism involving sequence specific interactions of either genomic DNA sequences or transcripts of G-quadruplex-forming sequences. Regardless, we believe that the growth inhibitory effects of the Pu27 family of oligonucleotides may provide an opportunity to effectively target c-MYC expression that could be exploited for cancer therapy.Nevertheless, the finding of these almost identical nucleotide sequences located in the promoter region of genes involved in stem cell maintenance such as S1 Fig(A): Circular dichroism spectra for 4 extra oligosequences from the Pu27 family compared to Pu27. (B): Specificity of four extra Pu27-HS binding to Pu27 target sequence in the c-MYC promoter. (C): Specificity of Pu27 binding to its target sequence, no competition observed by a different G-quadruplex forming oligonucleotide sequences (K-RAS). (D): Specificity of Pu27 binding to its target sequence in the c-MYC promoter, no binding with the G-quadruplex forming oligonucleotides AS1411 or K-RAS. (PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Histone modification and remodeling play crucial roles in regulating gene transcription. These post-translational modifications of histones function in a combinatorial fashion and can be recognized by specific histone-binding proteins, thus regulating gene transcription. Therefore, understanding the combinatorial patterns of the histone code is vital to understanding the associated biological processes. However, most of the datasets regarding histone modification and chromatin regulation are scattered across various studies, and no comprehensive search and query tool has yet been made available to retrieve genes bearing specific histone modification patterns and regulatory proteins.For this reason, we developed the Yeast Nucleosome Atlas database, or the YNA database, which integrates the available experimental data on nucleosome occupancy, histone modifications, the binding occupancy of regulatory proteins, and gene expression data, and provides the genome-wide gene miner to retrieve genes with a specific combination of these chromatin-related datasets. Moreover, the biological significance analyzer, which analyzes the enrichments of histone modifications, binding occupancy, transcription rate, and functionality of the retrieved genes, was constructed to help researchers to gain insight into the correlation among chromatin regulation and transcription.http://cosbi3.ee.ncku.edu.tw/yna/.Compared to previously established genome browsing databases, YNA provides a powerful gene mining and retrieval interface, and is an investigation tool that can assist users to generate testable hypotheses for studying chromatin regulation during transcription. YNA is available online at  The eukaryotic genome is packaged into nucleosomes, each of which consists of approximately 147 base pairs of DNA wrapped around a histone octamer and constitutes fundamental unit of the chromatin structure . The hisSaccharomyces cerevisiae [Saccharomyces cerevisiae [Previous studies have produce several valuable genome-wide datasets of histone modifications, binding occupancy of chromatin-regulating factors, and gene expression in the yeast revisiae -21. Howerevisiae ,23. SGD revisiae , to disprevisiae . Yet therevisiae . The chrhttp://cosbi3.ee.ncku.edu.tw/yna/.Hence we developed the Yeast Nucleosome Atlas database, or the YNA database, to integrate available chromatin related datasets into one platform and to provide a comprehensive query and investigation tool. In YNA, approximately 100 deposited data tracks of nucleosome occupancy, histone modifications, binding occupancy of chromatin-related regulatory proteins are integrated in the database. Besides, YNA also collected global gene expression data and MIPS FunCat functional catalogue for functional analysis. Most importantly, YNA provides the genome-wide gene miner to retrieve genes with user-specified filtering criteria based on the collected datasets. The retrieved genes can be utilized for further analysis. Furthermore, YNA also provides the biological significance analyzer to present the tendency of these chromatin-regulating features for the retrieved genes. This helps users obtain hypotheses to investigate chromatin structure and transcription regulation. Therefore, YNA is a discovery tool that provides the comprehensive investigation for chromatin structure, and can help users propose testable hypotheses for studying chromatin regulation during transcription. YNA is available online at The construction and architecture of YNA are shown in Figure In YNA, all collected datasets can be classified into 8 classes based on the properties. These 8 classes are the genome summary information, the nucleosome positioning data, the histone modification data, the histone variant data, the binding occupancy data of regulatory proteins, the gene expression data, the expression data of mutant cells, and the data of MIPS functional category.The yeast genome summary was retrieved from Saccharomyces Genome Database (SGD) ,23. The Three datasets of genome-wide nucleosome organization maps are included in the YNA database -16. In Yset1Δ, ubp8Δ, and ubp10Δ, are also included.Post-translational modifications of histones play crucial roles in altering chromatin structure and creating marks for the binding sites of specific chromatin regulatory proteins, thereby regulating genomic expression behaviors . In YNA,In eukaryotes, transcription is regulated by hundreds of proteins. These proteins consist of sequence-specific DNA-binding proteins, chromatin regulators, elongation regulators and transcription factors ,28. We gH2A.Z, the histone variant of H2A, has been widely studied and is thought to regulate several biological processes. The global H2A.Z map is also included in the YNA database .The expression data of each gene are collected in YNA . The adoarp8Δ, ino80Δ, set1Δ, and H3K4R (the replacement of lysine 4 with arginine in histone H3), are also collected in YNA [ino80Δ and arp8Δ genes are defective in DNA double-strand break repair and in gene transcription. The dataset includes the fold-change of expression levels in the ino80Δ and arp8Δ mutant cells, compared to wild type cells.The expression data of mutant cells, including d in YNA ,31. Ino8MIPS FunCat  ,33 is a We implemented the genome-wide gene miner in YNA to retrieve genes that match the filtering criteria. The genome-wide miner has three main filter set, which are chromatin structure regulation filter, expression level filter, and functional category filter, respectively. The three filters can be used with combination.The main purpose of chromatin structure regulation filter is to query for genes that match specific chromatin-regulating features, such as histone modifications, histone variants and binding occupancy of regulatory proteins, in promoters or coding regions. In this filter set, users are able to specify the threshold ratios relative to the background. The region options consist of (I) coding region of genes, (II) promoter region, which is defined between 500 bp upstream and 100 bp downstream from the gene start site, (III) both coding and promoter regions, and (IV) either of the two regions, separately. To achieve better query performance, we reprocessed all data from original sequence-formatted rows into individual gene regions and eliminated those non-coding sequences to abandon superfluous noises. While executing the query process, YNA globally traverses all sample values inside targeted regions from the rearranged data to filter out those target genes matching the defined criteria.ino80Δ, arp8Δ, set1Δ, H3K4R) comparing to wild types [The format of expression data deposited in YNA are measured by each gene and can be roughly divided into two types. The first type is quantified transcriptional property such as transcription rate and the counts of mRNA copies per cell, which directly deliver the information of gene's capability . The othld types ,31. ExprThe functional category filter provides the interface to fetch those genes that match the MIPS Functional Catalogue. In this filter set, users are able to specify keywords or category numbers to retrieve those genes with matching functional categories.The genome-wide gene miner provides the interface for users to extract genes that match the query criteria. To gain insight into the correlation between chromatin structure and transcription regulation of the retrieved genes, we implemented the biological significance analyzer along with the query results. The analyzer provides the enrichment analyses in four aspects: (I) the enrichment of histone modifications, which calculates the significance levels of the specific histone modification patterns in promoters and coding regions; (II) the enrichment of binding occupancy of regulatory proteins, which calculates the significance levels of regulatory protein binding events in promoters and coding regions; (III) mRNA transcription rate, which evaluates the significance levels of the transcription rate of the retrieved genes. The transcription rate is divided into 5 groups: "greater than 50 mRNA/hr", "16 - 50 mRNA/hr", "4 - 16 mRNA/hr", "1 - 4 mRNA/hr", and "less than 1 mRNA/hr"; and (IV) the functional enrichment of MIPS functional categories of the retrieved genes.p-values in the four analyses are converted into positive correlated scores by taking the negative logarithm and are then displayed as pie plots.The main algorithm to analyze the significance is based on Fisher Exact Test. Fisher Exact Test is used for analyzing the statistical significance of the proportion representing some categorized data subsets, such as those classified feature patterns mentioned above, within a given gene list relative to the genomic abundance ratio with the same property . YNA adoThe biological significance analyzer only displays those significantly enriched features . The resulting analysis demonstrates the tendency of these features shared by the retrieved genes. Moreover, this provides hypotheses for the combinatorial effects of those significant chromatin-regulating features for downstream analysis.The construction of YNA is based on CodeIgniter PHP Framework and MySQL database management system. The design layout of website interface was extended from YAML CSS Framework and jQWidgets. To improve the browse experience and performance, we developed vast JavaScript (ECMAScript) applications. Furthermore, all query operations in YNA are achieved in REST  architectural style. The sequence maps of chromatin structure regulations are presented as static images, which are produced by MatplotLib, a library of the Python scripting language.The YNA database provides three main functional modes for users to investigate the regulations for chromatin structure: (I) The query mode contains the manipulation panel of the genome-wide gene miner and the gene query engine Figure ; (II) ThThe genome-wide gene miner is the main function in the query mode. Users are able to specify filtering criteria based on the three filter sets, i.e. chromatin structure regulation filter, expression level filter, and functional category filter, and then execute the query to retrieve genes that match the filtering criteria Figure . The chrIn the list mode, the retrieved genes are displayed in the table. The genes are also analyzed through the biological significance analyzer in terms of four aspects: histone modifications, binding occupancy of regulatory proteins, transcription rates, and functional categories. All of the displayed table contents and charts can be downloaded in multiple file types . The interface of the list table and biological significance analyzer mounted in list mode can be viewed in Figures In the detail mode, the summary of the specifically selected gene is exhibited. The summary includes the information of the specified gene and sequence maps of multiple chromatin-related datasets, including nucleosome positioning, histone modifications and the binding occupancy of regulatory proteins, near the gene region. These sequence maps are shown in log2 fold-change ratios to represent the enrichment or depletion of specific chromatin regulation patterns Figure .All processed plain text files of chromatin-related datasets are annotated with their sources and are available for downloading in the statistics page. We also provided a detailed tutorial page so that users can fully utilize functions in YNA.S. cerevisiae, histone acetylation and methylation are widely studied and are thought to regulate gene transcription [To demonstrate the usability of YNA, we query genes with specific filtering criteria in the genome-wide gene miner. The retrieved genes are further analyzed in the biological significance analyzer to gain insight into information of the retrieved genes. In cription . Hence wp-values of 10-93 and 10-28, respectively, through the biological significance analyzer  and methylation (H3K4me3) are highly correlated with transcription activities . MoreoveYNA deposits genome-wide chromatic-regulation datasets for elucidating the transcriptional mechanisms caused by alterations on chromatin structure. However, these datasets came from several studies, and the experimental procedures may vary from one laboratory to another, thus resulting in potential systematic biases. In systems biology, a cellular system is perturbed and measured by high-throughput technologies . Hence, Saccharomyces cerevisiae strain S288c or W303, which share very similar genetic background and culture condition (cells growing to log-phase at 30°C in YPD). Hence the systematic bias of condition variation in the data integration of YNA is not severe. Besides, to provide more detailed information for each dataset, we have marked out the experimental environments and the assay resolutions for which the high-throughput experiments were performed.In YNA, we collected the datasets of histone modifications, protein binding occupancy and expression data from multiple studies. In these data, the yeast strains used for chromatin immunoprecipitation or expression profiling experiments are derived either from yeast On the other hand, it is well known that post-translational modifications of histones, particularly acetylation and methylation, play wide-spread roles in transcription regulations. But nowadays the genome-wide sequence maps of histone modification are still not completely available for all possible combinations of those features in all different cellular conditions ,8. Furthhttp://cosbi3.ee.ncku.edu.tw/yna/. We recommend users to browse YNA by Google Chrome. Other modern browsers such as Microsoft IE9, Apple Safari and Mozilla Firefox 21 also perform well in YNA. JavaScript is required in YNA functionality and should be enabled.YNA is available at In this study, we developed the YNA database, which integrates a number of scattered datasets of histone modifications, binding occupancy of regulatory proteins, gene expression data, and functional categories. Most importantly, YNA provides the genome-wide gene miner that allows user to retrieve genes based on combinatorial filtering criteria of specific histone modification patterns, expression levels, and functional categories. These retrieved genes can be further analyzed using the biological significance analyzer for the enrichments of specific chromatin-related features. Therefore, YNA is an investigation and discovery tool that can be used to mine proper targeted genes and to propose testable hypotheses for further chromatin studies. YNA will be updated regularly to keep with the latest chromatin-regulation datasets.SGD, Saccharomyces Genome Database; MIPS, Munich Information Center for Protein Sequence; FunCat, Functional Catalogue; YNA, Yeast Nucleosome Atlas database.The authors declare that they have no competing interests.PCH processed collected datasets and constructed YNA website. PCH and THY wrote the manuscript. HJL provided essential guidance and inspected biological issues. HJL and WSW conceived the research topics. PCH, THY and HJL proofread the manuscript. All authors have read and approved the final manuscript.


Knockdown or overexpression of these proteins indicate that they cooperate in activating IRES-dependent translation during myoblast differentiation, in a promoter-dependent manner. Importantly, mRNA transfection and promoter deletion experiments clearly demonstrate the impact of the FGF1 promoter on the activation of IRES-dependent translation via p54nrb and hnRNPM. Accordingly, knockdown of either p54 or hnRNPM also blocks endogenous FGF1 induction and myotube formation, demonstrating the physiological relevance of this mechanism and the role of these two proteins in myogenesis. Our study demonstrates the cooperative function of hnRNPM and p54nrb as regulators of IRES-dependent translation and indicates the involvement of a promoter-dependent mechanism.Fibroblast growth factor 1 (FGF1) is induced during myoblast differentiation at both transcriptional and translational levels. Here, we identify hnRNPM and p54 Gene expression in eukaryotes is regulated at multiple levels. Transcription, as well as post-transcriptional processes such as mRNA splicing, polyadenylation, degradation and translation, require a wide range of multi-component cellular machines in order to finely control protein production. For a long time, these steps have been considered to be a simple linear assembly line. Then, it has become apparent that gene expression, including steps such as transcription, capping, splicing, polyadenylation, RNA export and degradation, is coordinated in a complex and extensively coupled network , 2. HoweThe fibroblast growth factor 1 (FGF1) gene provides an attractive system to decipher a mechanism of coupling between transcription and translation. Indeed, we have shown that this growth factor is induced by a transcription-translation coupling mechanism during myoblast differentiation . The FGFTranscription from each promoter generates alternative splicing of exon 1, leading to four mRNAs with distinct 5' untranslated regions (5'UTR), each of them expressing the same protein, FGF1. Two of these 5' UTRs contain internal ribosome entry sites (IRES) . IRESs hThe concept of a nuclear event governing formation of the “IRESome”, the ribonucleoprotein complex responsible for activation of IRES-dependent translation, has been reported in the literature for c-myc and Smad1 IRESs, although the cell factors responsible for this process have not been identified , 18. FurAlthough the FGF1 IRES A has been reported to be stimulated during myoblast differentiation and muscle regeneration, nothing was known about ITAFs responsible for such regulation . Biomolenrb/NONO bound (directly or indirectly) to FGF1 promoter A and IRES A in differentiating myoblasts (C2C12). Knockdown and overexpression approaches revealed that p54nrb and hnRNPM are required to activate the IRES-dependent translation in a promoter-dependent manner. Furthermore, p54nrb and/or hnRNPM knockdown inhibited myotube formation. Altogether, this study identifies a novel regulation of FGF1 gene expression, implying a cooperation between promoter and translational regulators to promote the time controlled process of myoblast differentiation.In the present report, we identified hnRNPM and p54nrb cDNAs were the gifts of M. Swanson and A. Krainer, respectively. cDNAs were PCR-amplified and introduced into the pTRIP-DU3-MCS vector (pTRIP-p54 and pTRIP-HM) , 28nrb, cription . Severalthe IRES . The duantiation .nrb with the promoter was analyzed by chromatin immunoprecipitation (ChIP), using DNA extracts either from proliferating or differentiating myoblasts (nrb interact (directly or indirectly) with FGF1 promoter A and IRES A only in differentiating myoblasts. In contrast the two proteins very poorly interact with the FGF2 IRES, and such interaction did not increase during differentiation  or hnRNPM (siM) (renilla luciferase (LucR) and firefly luciferase (LucF) separated by the FGF1 IRES, was under the control of either the CMV promoter or the FGF1 promoter A (The role of p54PM (siM) . Myoblasomoter A . Endogennrb  or inactivated (promoter mutation).The present data suggest that IRESome formation occurs in the nuclear compartment. The regulating features of p54The importance of ITAF subcellular localization in the regulation of their activity appeared a few years ago, with the first observation that a nuclear event is required in the control of c-myc IRES activity . Later, nrb. Interestingly, nuclear interaction of hnRNPM and p54nrb has been previously reported [nanos mRNA by binding to its 3' UTR [The IRES-regulating function of hnRNPM discovered in our study represents a novel finding, as well as its cooperative activity with p54reported . Like otreported , 40. Ints 3' UTR . The addnrb/NONO is also a multifunctional protein. It has been previously shown to associate with 5' splicing sites in large transcription-splicing complexes, providing a direct role for this protein in linking transcription to splicing [nrb also behaves as a specific transcriptional activator, binding to the intracisternal A particle proximal enhancer element, and as an RNA binding protein, preferentially binding to the sequence UAGGGA/U identified by SELEX [nrb has been identified as an ITAF of the myc family IRESs , and has also been shown to stimulate the APAF-1 IRES [nrb is able to cooperate with hnRNPM, suggesting that the two proteins may activate the FGF1 IRES as a complex. Unexpectedly, hnRNPM overexpression is inhibitory, whereas knockdown experiments clearly showed it is required for both IRES and promoter activation. We hypothesize that excess of hnRNPM might inhibit p54nrb functions on FGF1 gene expression, presumably by preventing p54nrb binding to FGF1 DNA and RNA due to an inadequate stoechiometry of the two proteins.p54splicing , 45. P54by SELEX . In addiF-1 IRES . Here weAlthough the proteins are expressed in proliferating cells, they are not found in the complex with the IRES or the promoter A. This suggests that the proteins might carry different post-translational modifications. Alternatively these proteins could join the complex through the interaction with another protein, which is absent in the proliferating cells and remains to be discovered. This could also explain that overexpressed hnRNPM is not functional.Very few proteins were bound to the EMCV IRES, which may be explained by the low efficiency of the EMCV IRES in myoblasts. However, we were also surprised that no transcription factor was bound to promoter DNA. This indicates that BIA-MS does not provide an exhaustive view of all proteins bound to RNA or DNA and that one can miss important proteins. This also explains that we have missed hnRNPM present in the promoter-bound complex.nrb and hnRNPM with RNA has not been demonstrated, the present study strongly suggest that the two proteins are ITAFs involved in FGF1 IRES activation. However The BIA-MS data provides a list of additional proteins bound to the FGF1 IRES, including histones and splicing factors. These proteins may participate in the IRESome ribonucleoprotein.Although the direct interaction of p54nrb asks the question of how a promoter is able to impact on translation, which is in principle cytoplasmic.Promoter-dependent translation controlled by hnRNPM and p54nrb might be first recruited to the promoter, where they would contribute to transcription activation. This process would also facilitate hnRNPM and p54nrb binding onto mRNA IRES and subsequently activate IRES-dependent translation. A recent study supports the hypothesis of a co-transcriptional ITAF binding, by showing that the translation elongation factor eEF1A1 couples transcription to translation during heat shock response [nrb may well have a similar mode of action, except that they bind to the mRNA 5’UTR and directly activate IRES-dependent translation by their ITAF function.One among several possible models, one can propose transcription/translation coupling: hnRNPM and p54response . These aOther hnRNPs have been previously described for their involvement in transcription: hnRNPK, reported as a transcription factor interacting with the RNA polymerase II machinery in the c-myc promoter, and hnRNP A1, involved in the transcription of the KRAS proto-oncogene , 49. Mornrb might be their effect on mRNA stability. Binding of these proteins to the FGF1 promoter would not have an effect on transcription but would facilitate their binding to the nascent mRNA, resulting in mRNA stabilization, as has been shown for the yeast protein Dbf2P [nrb binding to mRNA might have the double effect of stabilizing the FGF1 mRNA and activating the IRES. Anyway, further investigation is needed to determine whether the promoter-dependent function of hnRNPM and p54nrb involves transcription enhancement or RNA stabilization.An alternative model to explain promoter-dependent regulation of translation by hnRNPM and p54in Dbf2P . These anrb and hnRNPM function in myoblast differentiation. It clearly appears that p54nrb and hnRNPM are important for myotube formation and such a role is novel for these two proteins. We have previously shown that FGF1 is required for myoblast differentiation [nrb may act on the expression of additional IRES-containing genes, including Smad5 and utrophin A IRESs whose activites have been reported in myoblasts [nrb in the promoter-dependent regulation of such IRESs during muscle development.An important feature of our study is the physiological relevance of p54yoblasts , 52, 53.As seen with the coordination of transcription and mRNA processing, such as splicing, whose regulators often exhibit the additional function of ITAFs (i.e. hnRNPs), one can expect that the promoter-dependent translation mechanism described in our study will extend to other IRES-containing mRNAs. Such a mechanism becomes more significant for genes that are induced in response to conditions that block cap-dependent translation, such as stress. Coupling of IRES activation with the promoter guarantees that the induction of a given gene in response to a specific stimulus will result in the synthesis of that gene product.S1 FileTotal or nuclear extracts of differentiating C2C12 myoblasts were injected see  as analy(DOC)Click here for additional data file.S2 Filenrb (sip54) or control (sic). RNA levels and luciferase activities are presented in Figs nrb and hnRNPM expression was analysed by Western blot following single knockdown with siRNA siM  or sip54  or double knockdown with the two siRNAs together .C2C12 cells were first transfected with bicistronic plasmids and 48h later with siRNAs targeting hnRNPM (siM), p54(TIF)Click here for additional data file.S3 Filenrb (sip54) or siRNA control (sic). SiM and siP54 corresponded to sequences different from that of the siRNA smartpools used in C2C12 cells co-transfected with bicistronic plasmids and 48h later with a siRNA against hnRNPM (siM), p54(TIF)Click here for additional data file.S4 Filerenilla luciferase activities were measured. Values are presented as well as the LucF/LucR (F/R) ratio representing the IRES activity. Experiments were performed in biological triplicates and repeated three times. The Student test was used (mean +- standard deviation).(Table A) C2C12 cells were transfected with bicistronic plasmids containing the FGF1 promoter and IRES see  and with(DOC)Click here for additional data file.


The molecular mechanism that maintains the pluripotency of embryonic stem cells (ESCs) is not well understood but may be reflected in complex biological networks. However, there have been few studies on the effects of transcriptional and post-transcriptional regulation during the development of ESCs from the perspective of computational systems biology. In this study, we analyzed the topological properties of the “core” pluripotency transcription factors (TFs) OCT4, SOX2 and NANOG in protein-protein interaction networks (PPINs). Further, we identified synergistic interactions between these TFs and microRNAs (miRNAs) in PPINs during ESC development. Results show that there were significant differences in centrality characters between TF-targets and non-TF-targets in PPINs. We also found that there was consistent regulation of multiple “core” pluripotency TFs. Based on the analysis of shortest path length, we found that the module properties were not only within the targets regulated by common or multiple “core” pluripotency TFs but also between the groups of targets regulated by different TFs. Finally, we identified synergistic regulation of these TFs and miRNAs. In summary, the synergistic effects of “core” pluripotency TFs and miRNAs were analyzed using computational methods in both human and mouse PPINs. ESCs are derived from the inner cell mass of the mammalian blastocyst in vivo and in vitroAccording to previous studies, a small set of TFs, including OCT4, SOX2 and NANOG comprise the “core” pluripotency factors in ESCs in vivo. However it is not clear how the target genes of “core” pluripotency TFs regulate ESC development synergistically with miRNAs.Besides the traditional genetic impacts on the maintenance of ESC pluripotency, epigenetic regulation is also involved in the process of ESC development. In particular, more and more studies have found that miRNAs play important roles during the development of ESCs In this study, we identified protein-protein interaction networks (PPINs) and analyzed the topological properties of the target genes of OCT4, SOX2 and NANOG in human and mouse ESCs. Further, we explored the effects of miRNAs on the post-transcriptional regulation of the target genes of these three “core” pluripotency TFs. We found that the centrality of “core” pluripotency transcription factor target genes is higher than that of randomly selected genes in PPINs. Furthermore, when genes are regulated by more “core” pluripotency TFs, they show more properties of centrality. The target genes regulated by both transcriptional and post-transcriptional methods also have higher centrality properties in PPINs. These results indicate that there are both the complex interactions between different “core” pluripotency TFs during ESC development within transcriptional levels and the interactions occur across both transcriptional and post-transcriptional levels in biological networks.In order to obtain comprehensive target datasets of “core” pluripotency TFs in ESCs, we manually collected related articles in PubMed. Finally, 10 articles and their corresponding datasets were extracted and used in this study . The humhttp://theBioGRID.org/) and the Human Protein Reference Database (HPRD) (http://www.hprd.org/) In order to avoid any bias due to the data source, protein-protein interaction data were also downloaded from two different databases: the Biological General Repository for Interaction Datasets (BioGRID) version 3.2.110 (http://mirecords.biolead.org/), which includes 284 miRNAs, 1,101 targets with 2,087 edges in the human and 145 miRNAs, 266 targets with 442 edges in the mouse http://diana.cslab.ece.ntua.gr/DianaToolsNew/index.php), which includes 111 miRNAs, 862 targets with 1,093 edges in the human and 44 miRNAs, 75 targets with 104 edges in the mouse Targets of miRNAs were downloaded from two different databases, which cover both human and mouse species. The first one is the miRecords dataset , Betweenness (BC), Closeness, Clustering Coefficient (CC), Degree, Eccentricity, Neighborhood Connectivity (NC), Radiality, Stress and Topological Coefficient (TC) were used to analyze the targets of OCT4, SOX2, NANOG and miRNAs (TarBases and miRecords) in the PPINs of the BioGRID and HPRD databases . All theAll the above topological properties can be used to measure the centrality of nodes in biological networks. General speaking, the higher the centrality of one node, the more important roles it plays in biological networks. For detailed description, we took some properties as examples to illustrate their meanings. ASPL is defined as the average shortest path length between a node and all the nodes in biological networks. Closeness centrality is defined as the reciprocal of the average shortest path length of one node which can be used as a measure of how fast information spreads from a given node to all other reachable nodes in biological networks. In undirected biological networks (such as PPINs), CC of a node is defined as the proportion of the observed connections between the neighbors of this node against the maximum number of possible connections among them. CC is used to indicate the close extent of the local neighborhood of one node. Degree is one simplest and most used topological index, which is defined as the number of nodes directly connected to a given node. TC is a relative measurement of the tendency of one node in biological networks to have shared interactive partners with other nodes. For more in-depth interpretation of these concepts, one can get the exact definitions of these topological properties from A total of 2,512 human pluripotency “core” TF targets were identified in the collected articles. Among these targets, 42.9% were shared by at least two TFs, corresponding to 1,017 targets. The number of OCT4, SOX2 and NANOG targets was 623, 1,435 and 1,885 respectively, while the proportion shared by other TFs was 77.5%, 69.5% and 54.5% respectively . SimilarWe mapped the targets of the three TFs and miRNAs into the PPINs and obtained sub-networks consisting only of “core” pluripotency TF targets and their direct neighbors  to S9. FP values<0.05 with t test, processed with R version 3.0.2).The topological properties were analyzed with Cytoscape version 3.0.2, especially the NetworkAnalyzer tools. To begin with, the most connected components of protein-protein interaction networks were extracted from BioGRID, including 9,552 nodes with 52,202 edges in the human and 3,831 nodes with 7,123 edges in the mouse. The same analysis identified 9,205 nodes and 36,748 edges in the most connected component of the HPRD database. Finally, topological properties were analyzed with NetworkAnalyzer and filtered using strict statistical parameters  and non-TF-targets . First we analyzed human PPINs. The results showed that the ASPL of SOX2-targets and NANOG-targets was shorter compared with non-targets, in both the BioGRID and HPRD datasets. We also found that radiality of SOX2-targets and NANOG-targets was greater than non-targets in both BioGRID and HPRD resources. Furthermore, the degree of the NANOG-targets was also significantly different compared with non-NANOG-targets in BioGRID and HPRD, indicating that many proteins are connected with NANOG-targets. Without consistent significant results, the SOX2-targets were only found to have higher degree values compared with non-SOX2-targets in HPRD, while similar results were not found in BioGRID. With regard to OCT4-targets, BC differed significantly between OCT4-targets and non-OCT4-targets in both BioGRID and HPRD databases, indicating that the shortest paths going through OCT4 targets were more than a random choice. This indicates that OCT4 targets may be internal module proteins and are more likely to locate in the hub position in networks. In summary, a certain degree of higher centrality in PPINs was found in human “core” pluripotency targets compared with non-TF-targets .Similar results were also obtained in the mouse. For NANOG-targets, 6 measurements were found to differ significantly from those in non-NANOG-targets, including ASPL, Closeness, Degree, NC, Radiality and Stress. For SOX2-targets, 5 measurements in total were significantly different compared with non-SOX2-targets: ASPL, Closeness, Degree, NC and Radiality. For OCT4-targets, 5 measurements were found to differ from non-OCT4-targets, including BC, Degree, NC, Stress and TC. Taking these measurement results together, the target genes of “core” pluripotency transcription factors show higher centrality properties in mouse PPINs .Through the analysis of the distributions of “core” pluripotency TF targets, we identified many genes regulated by at least two TFs . This reSimilar results were also found in the mouse. Among the ten centrality properties, none of them was found to differ between 1TF-targets and 2TF-targets. When compared with 3TF-targets, only ASPL, Closeness and Radiality were found to be different from those of 2TF-targets. The greatest diversity was found between the groups of the 1TF-targets and 3TF-targets, where we found differences in five measurements: ASPL, Closeness, Eccentricity, Radiality and Stress .P values of the t tests were 4.99E-5, 0.001 and 3.90E-286; while when the number was 3, the P value was 7.98E-258 for values from the HPRD database  analysis across human and mouse species. We found that the background averages of PPIN SPLs were 4.227, 4.201 and 5.125 in HPRD, human BioGRID and mouse BioGRID respectively. First, the smaller SPLs were detected within TF targets compared with the background SPLs. As shown in database . Similardatabase  and 9. Fdatabase , 8 and 9Based on the evidence that epigenetic regulation may play important roles in ESC development, we attempted to analyze the effects of post-transcriptional regulation on the targets of “core” pluripotency TFs in PPINs. As typical forms of post-transcriptional regulation, miRNA targets were obtained for further analysis from two different sources, including miRecords and TarBase. Results show that there were some significant different characteristics between TF-miRNA targets and TF-non-miRNA targets in the both two PPINs from human BioGRID and HPRD databases. The differences were found in both miRecords and TarBase. First, we found that OCT4-miRNA targets were different from OCT4-non-miRNA targets in several centrality properties, including Degree, Stress and TC . Second,Further, in order to identify the more obvious effects of miRNA regulation on the development of ESCs, we compared TF-miRNA target genes to non-TF-non-miRNA target genes in the human. Interestingly, as expected we found a significant difference between TF-miRNA and non-TF-non-miRNA targets on the topological properties of components of PPINs. First, OCT4-miRNA targets were found to have higher centrality properties compared with non-OCT4-non-miRNA genes in PPINs, with higher values of ASPL, BC, Degree, Stress, Radiality and TC . Second,In order to overcome species bias, we conducted the same experiments in mouse ESCs. Interestingly, the results showed the same tendency as above in data from all the dataset sources. Firstly, the TF-miRNA targets also showed higher centrality properties compared with TF-non-miRNA targets  and 10. In this study, we globally analyzed the topological properties of targets of the “core” pluripotency TFs in PPINs, including OCT4, SOX2 and NANOG. In addition, the post-transciptional effects of miRNAs on these TFs were also analyzed in both human and mouse. Up to ten topological properties were included in the analysis process, including Shortest Path Length, Betweeness, Closeness, Cluster Coefficient, Degree, Eccentricity, Neighborhood Connectivity, Radiality, Stress and Topological Coefficient. All the above analyses were processed in three protein-protein interaction datasets , two miRNA target datasets (miRecords and TarBase) and two species (human and mouse). Though there were different dataset scales of the three “core” TF targets between different databases and species, the common characteristic of these three “core” TFs in biological networks were still observed in our research. The use of several data sources and measurements in this study ensures the robust nature of the results obtained. Besides, all the above analysis was based on ESCs datasets. Consider the similar property of “stemness” with ESCs in many other types of stem cells, especially induced pluripotent stem cells, we infer that these three “core” TFs will have similar roles and characteristics in biological networks. With the increasing of high throughput datasets about targets of the “core” pluripotency TFs in other types of stem cells, similar research should be processed and compared with current results.in vivo during the development of ESCs We found significant differences in centrality properties between “core” pluripotency TF-targets and non-TF-targets in PPINs. These results were widespread in HPRD, human BioGRID and mouse BioGRID datasets. The numbers of centrality properties were 6 and 8 in human and mouse respectively. The former contained ASPL, BC, Degree, Eccentricity, Radiality and Stress, while the latter comprised ASPL, BC, Closeness, Degree, NC, Radiality, Stress and TC. Comparing the two results, we found that ASPL, BC, Degree, Radiality and Stress were robust and only CC among the 10 measurements could not be detected, which is used to judge the close link of node neighborhoods in biological networks. The reason why CC did not appear in the analysis was not clear. It may be because the targets of “core” pluripotency TFs perform their functions in relative isolation which may help to avoid harm to the complex environment We found synergistic regulation of multiple “core” pluripotency TFs during the development of ESCs. As we hypothesized, no difference in topological properties was found between 1TF-targets, 2TF-targets and 3TF-targets in human PPINs, including HPRD and human BioGRID. The same tendency was also found in mouse PPINs from BioGRID. Based on these results, it can be seen that although the number of TFs regulating common target genes increases from 1 to 3, their centrality properties do not increase accordingly. This indicates that pluripotency related genes may be regulated by 1 or 2 or even 3 TFs, but the genes are no different from the biological system viewpoint. In other words, the number of TFs that regulate the common pluripotency genes is not important. This means that the seemingly unnecessary TFs may provide compensatory regulation in the molecular pathways of ESC development The module properties within the inner “core” pluripotency TFs were detected through the analysis of shortest path length in PPINs. Through these experiments, we found that the shortest path length of targets regulated by common TFs were smaller than those of randomly selected background values. This indicates that the genes regulated by common “core” pluripotency TFs are in close communication in PPINs and that this will be helpful in synergistically and quickly maintaining the pluripotency of ESCs We also found that miRNAs play important roles in the regulation of “core” pluripotency TFs during the development of ESCs as a way of post-transcriptional regulation in PPINs. The difference of centrality properties observed between TF-miRNA targets and TF-non-miRNA targets was found in both human and mouse PPINs. Further, the differences in topological properties between TF-miRNA targets and non-TF-non-miRNA target genes were more obvious in PPINs. These different centrality properties show different close extent and different importance in computational biological network view. Considering the effects that miRNAs impose to the “core” TFs on these properties in PPINs, it is observed that there is synergistic regulation between themselves. The synergistic regulation of “core” pluripotency TFs and miRNAs will enhance the function of targets. In consideration of the drastic effects of TFs and the minor regulation of miRNAs, the synergism of these three “core” TFs and miRNAs may help to achieve their aims of regulation about pluripotency, like one machine which has many gear wheel of different size. As an example, myocyte enhancer factor2 (MEF2) which is a target of both NANOG and miRNA, is an important transcription factor regulating the survival and development of many types of cells Figure S1Sub-network of OCT4 in HPRD.(PDF)Click here for additional data file.Figure S2Sub-network of SOX2 in HPRD.(PDF)Click here for additional data file.Figure S3Sub-network of NANOG in HPRD.(PDF)Click here for additional data file.Figure S4Sub-network of OCT4 in human BioGRID.(PDF)Click here for additional data file.Figure S5Sub-network of SOX2 in human BioGRID.(PDF)Click here for additional data file.Figure S6Sub-network of NANOG in human BioGRID.(PDF)Click here for additional data file.Figure S7Sub-network of OCT4 in mouse BioGRID.(PDF)Click here for additional data file.Figure S8Sub-network of SOX2 in mouse BioGRID.(PDF)Click here for additional data file.Figure S9Sub-network of NANOG in mouse BioGRID.(PDF)Click here for additional data file.Table S1Targets of “core” pluripotency TFs in the human.(XLS)Click here for additional data file.Table S2Targets of “core” pluripotency TFs in the mouse.(XLS)Click here for additional data file.


Candida albicans is the most frequently isolated human fungal pathogen and can cause a range of mucosal and systemic infections in immunocompromised individuals. Morphogenesis, the ability to undergo a reversible transition from budding yeast to elongated filaments, is an essential virulence trait. The yeast-to-filament transition is associated with expression of genes specifically important for filamentation as well as other virulence-related processes, and is controlled, in part, by the key transcriptional regulators Nrg1 and Ume6. Both of these regulators are themselves controlled at the transcriptional level by filament-inducing environmental cues, although little is known about how this process occurs. In order to address this question and determine whether environmental signals regulate transcription of UME6 and NRG1 via distinct and/or common promoter elements, we performed promoter deletion analyses. Strains bearing promoter deletion constructs were induced to form filaments in YEPD plus 10% serum at 37°C, Spider medium (nitrogen and carbon starvation) and/or Lee’s medium pH 6.8  and reporter gene expression was measured. In the NRG1 promoter we identified several distinct condition-specific response elements for YEPD plus 10% serum at 37°C and Spider medium. In the UME6 promoter we also identified response elements for YEPD plus 10% serum at 37°C. While a few of these elements are distinct, others overlap with those which respond to Lee’s pH 6.8 medium. Consistent with UME6 possessing a very long 5’ UTR, many response elements in the UME6 promoter are located significantly upstream from the coding sequence. Our data indicate that certain distinct condition-specific elements can control expression of C. albicans UME6 and NRG1 in response to key filament-inducing environmental cues. Because C. albicans encounters a variety of host microenvironments during infection, our results suggest that UME6 and NRG1 expression can be differentially modulated by multiple signaling pathways to control filamentation and virulence in vivo. Candida albicans is an opportunistic human fungal pathogen and a significant cause of disease in immunocompromised individuals such as AIDS patients, organ transplant recipients and cancer patients on chemotherapy [C. albicans can disseminate and cause life-threatening, systemic infections [Candida species are the fourth leading cause of hospital-acquired bloodstream infections in the U.S. [otherapy –4. It isotherapy , 6. In afections , 7. Withthe U.S. , 9.C. albicans, morphogenesis, the ability to transition between oval-shaped budding yeast cells and filaments (elongated cells attached end-to-end), is an essential virulence property of this organism [C. albicans to undergo a reversible transition from yeast to filaments is required for virulence in a mouse model of systemic candidiasis [While several traits contribute to the pathogenesis of organism , 7, 10. organism –17. Furtorganism , 19. Sevdidiasis , 20–24.C. albicans yeast-to-filament transition, including 37°C, serum, human hormones, starvation and neutral pH [C. albicans transcriptional regulators are known to play critical roles in this process. Importantly, two of these regulators, Nrg1 and Ume6, are themselves controlled at the transcriptional level by filament-inducing conditions. Nrg1, a zinc finger DNA-binding protein, functions (via recruitment of the Tup1 corepressor) as a key transcriptional repressor of filament-specific genes under non-filament-inducing conditions [NRG1 transcript is down-regulated, causing the expression of filament-specific genes. In addition, the Nrg1 repressor is transiently displaced from hyphal-specific promoters via activation of the cAMP-PKA pathway in the presence of serum at 37°C [nrg1Δ/Δ mutant is avirulent and constitutive high-level expression of NRG1 has also been shown to block the yeast-to-filament transition, leading to highly attenuated virulence in a mouse model of systemic candidiasis [A variety of host environmental cues are known to trigger the utral pH –27. Thesutral pH . Severalnditions , 22. In  at 37°C . The nrgdidiasis , 21, 22.UME6 transcript. UME6 is also a downstream target of multiple filamentous growth transcriptional regulators [UME6 expression are important for determining C. albicans morphology and Ume6 protein stability is controlled by both oxygen- and CO2-sensing pathways [ume6Δ/Δ mutant is attenuated for virulence and constitutive high-level expression of UME6 increases hyphal formation in vivo and is sufficient to promote virulence in a mouse model of systemic candidiasis [NRG1 and UME6 function together in a feedback loop to promote filament-specific gene expression in the presence of strong filament-inducing conditions [Ume6, also a zinc finger DNA-binding protein, is a filament-specific transcriptional regulator that is required for hyphal extension . A variegulators . Both thpathways , 32. Thedidiasis , 30. We UME6 and NRG1 play in regulating both the C. albicans yeast-filament transition and virulence have been well-characterized, considerably less is known about the exact mechanism(s) by which host environmental signals control expression of these key regulators at the transcriptional level. In this study we characterize the promoters of both NRG1 and UME6 and identify elements that respond to specific filament-inducing conditions. We also determine the extent to which these elements and, by inference, the upstream signaling pathways which target these elements, overlap. Overall, our results provide new and important information about how environmental cues, similar to those encountered in the host, regulate the expression of two key transcription factors that govern filamentation and virulence in the major human fungal pathogen C. albicans.While the critical roles that both 600 ~ 4.0 and then diluted 1:10 into pre-warmed YEPD + 10% serum at 37°C and 1:20 into Spider medium at 30°C. For Lee’s medium inductions, 10 mL of an overnight culture of cells grown in YEPD at 30°C was centrifuged, washed and resuspended in 5 mL 1X PBS. 2.5 mL of this cell suspension was inoculated into pre-warmed Lee’s pH 6.8 or Lee’s pH 4.5 medium at 30°C. Cells were harvested 30 minutes following induction in serum medium at 37°C, 6 hours following induction in Spider medium at 30°C and 1 hour following induction in Lee’s pH 6.8 medium for total RNA isolation. To determine the effect of farnesol on lacZ reporter gene expression, strains were grown overnight in YEPD medium at 30°C to OD600 ~ 4.0. Cells were then diluted 1:10 into pre-warmed YEPD at 30°C in the presence and absence of 40 μM farnesol . Aliquots of cells were harvested from both the initial overnight culture as well as the diluted cultures (30 minutes following dilution) for RNA extraction.YEPD (yeast-extract peptone dextrose) medium at 30°C was used as a standard non-filament-inducing condition . PreparaNRG1 promoter deletion strains were constructed as follows: varying regions of the NRG1 upstream intergenic region were amplified by PCR from C. albicans SC5314 genomic DNA using primers 1–16  as well as strong filament-inducing (YEPD plus 10% serum at 37°C) conditions. We observed the strongest level of lacZ down-regulation (8-fold) in response to filament induction with the strain containing the 2.9 kb NRG1 upstream intergenic region reporter construct  (default parameters) [C. albicans mating and morphogenesis. Previous studies have also identified binding sites in this region for other transcriptional regulators of morphogenesis including Ndt80 and Efg1 [NRG1 promoter is located within the 2.9 kb upstream region.In order to identify the onstruct  which waonstruct . This lenduction , 40. In ameters)  identifiand Efg1 , 43. TakUME6 upstream region is required for C. albicans filamentation in response to serum at 37°C [S. theromphilus lacZ reporter in response to growth in serum at 37°C. These results suggested that critical UME6 promoter elements are located in this region. However, to ensure that we did not overlook important, but non-essential UME6 promoter elements, we conducted an in silico analysis (as described above) for 7 kb of the UME6 upstream intergenic region and identified putative binding sites for a variety of key C. albicans filamentous growth transcriptional regulators including Rim101, Cph1 and Fkh2. Results of this analysis are consistent with those of a previous study showing that cph1Δ/Δ and fkh2Δ/Δ deletion strains are defective for UME6 induction in response to hyphal-inducing conditions [UME6 upstream region [UME6 upstream region. In addition, a number of the factors which bind to these sites have been shown to control UME6 expression [UME6 transcript has an exceptionally long 3 kb 5’ UTR which functions in translational inhibition [in silico analysis, suggest that the UME6 promoter is located in the 7 kb upstream region.We have recently demonstrated that a 6 kb  at 37°C . In addinditions . Previoum region –45. Impopression , 44, 45.hibition . These pNRG1 promoter are important for controlling expression in response to specific filament-inducing conditions, we conducted a promoter deletion analysis. Various deletions of the NRG1 promoter were fused to a S. thermophilus lacZ reporter [C. albicans RPS1 locus. lacZ expression was measured using qRT-PCR under both non-inducing conditions (YEPD at 30°C) as well as several known filament-inducing conditions. Time points used to harvest cells for each filament-inducing condition used in the deletion analyses described in this study were specifically chosen to observe maximal transcriptional effects (ie: NRG1 down-regulation and UME6 induction) based on pilot experiments.In order to determine which elements in the reporter  and inteNRG1 promoter deletions were induced to form filaments in YEPD + 10% serum at 37°C. As noted previously, we observed ~8-fold down-regulation of lacZ expression in the reporter strain carrying the full-length -2.9 kb NRG1 promoter fragment in response to growth in serum at 37°C  did not significantly down-regulate lacZ expression. Interestingly, we also observed that the -2.5 kb to -2.9 kb region was sufficient to direct > 2-fold lacZ down-regulation. Taken together, these results suggest that the NRG1 promoter region from -2.1 kb to -2.9 kb contains two Spider condition-specific negative elements; the first element is located between -2.1 kb and -2.5 kb and the second element is between -2.5 kb and -2.9 kb.In order to identify elements important for down-regulation of t 6 hrs. . Spider r medium . The regC. albicans cells can be induced to form filaments when diluted from a saturated overnight culture into non-inducing media, such as YEPD at 30°C [NRG1 promoter did not show down-regulation in response to dilution in YEPD at 30°C, we did observe that certain NRG1 promoter deletion constructs showed down-regulation of lacZ expression at 30 minutes growth in YEPD at 30°C following dilution from the zero time point overnight culture  induction of lacZ expression in response to serum and temperature [UME6 promoter length to 7 kb reduced lacZ up-regulation to ~8-fold, suggesting that this region contains a serum and temperature-responsive negative element   . An addiUME6 promoter elements, strains carrying UME6 promoter deletions were induced to form filaments in Lee’s pH 6.8 at 30°C (Lee’s pH 4.5 at 30°C was used as a non-inducing control). Cells were harvested 1 hour following induction for total RNA isolation and qRT-PCR analysis. We observed ~14-fold lacZ induction with both the 7 kb and 6 kb UME6 promoters  and neutral pH Click here for additional data file.S2 Table(PDF)Click here for additional data file.


The process of generating differentiated cell types performing specific effector functions from their respective undifferentiated precursors is dictated by extracellular signals, which alter the host cell’s capacity to perform cellular functions. One major mechanism for bringing about such changes is at the level of transcription. Thus, the transcription-related induction of previously silent genes and suppression of active genes in response to extracellular signals can result in the acquisition of new functions by the cells. The general transcriptional machinery, which comprised of RNA Polymerase II and associated initiation factors, assemble into preinitiation complexes at the core promoters of eukaryotic protein coding genes in response to the signal-dependent activation of corresponding regulatory factors that bind to promoter and enhancer elements . The ratEvery event in the life cycle of a lymphocyte is modulated by the signals they receive. For instance, expression of the B cell antigen receptor (BCR) on the surface of B cells is a hallmark of various stages of B cell development, with signaling through the BCR being important during both early/antigen-independent (tonic) and late/antigen-dependent phases of development . HoweverThe B (and T) lymphocytes also perform a unique developmental program because they have an unparalleled genetic makeup – the genetic loci that encode their cell surface receptors are in an “unrearranged” or “germline” configuration during the early stages of development. Thus, while expressing stage-specific genes and transcription factors during each developmental stage, lymphocytes also need to undergo rearrangement of their cognate receptor loci in a strictly ordered fashion to generate a pool of receptor proteins that, individually, are capable of recognizing specific antigens that are encountered at a much later step . Hence, Germline configurations of antigen receptor loci in B and T lymphocytes have hundreds of variable (V) region gene-segments, which have the potential to combine with a select few diversity (D) and joining (J) gene-segments to create recombined genes encoding numerous receptors that can recognize a vast repertoire of antigens , 7. GiveRecombination and transcription are coupled during hematopoietic development –13. The Because mature B cells encounter a variety of antigens, they undergo both Class-Switch recombination (CSR) and somatic hypermutation (SHM) to diversify their antibody repertoire by utilizing enzymes such as AID. Given that these processes involve DNA breaks, they must be extremely tightly regulated to maintain genomic integrity , 21. KenThe ultimate role of immune cells is to mount an effective adaptive or innate response against pathogens . Hence, Mechanisms that regulate communication between enhancers and promoters are complex and involve many transcription factors, accessory molecules and chromatin regulators . Given tThe 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.


Protein localization and dynamics can now be visualized in living cells using the fluorescent protein fusion technique, but it is still difficult to selectively detect molecules with a specific function. As a posttranslational protein modification is often associated with a specific function, marking specifically modified protein molecules in living cells is a way to track an important fraction of protein. In the nucleus, histones are subjected to a variety of modifications such as acetylation and methylation that are associated with epigenetic gene regulation. RNA polymerase II, an enzyme that transcribes genes, is also differentially phosphorylated during the initiation and elongation of transcription. To understand the mechanism of gene regulation in vivo, we have developed methods to track histone and RNA polymerase II modifications using probes derived from modification-specific monoclonal antibodies. In Fab-based live endogenous modification labeling (FabLEM), fluorescently labeled antigen-binding fragments (Fabs) are loaded into cells. Fabs bind to target modifications in the nucleus with a binding time of a second to tens of seconds, and so the modification can be tracked without disturbing cell function. For tracking over longer periods of time or in living animals, we have also developed a genetically encoded system to express a modification-specific intracellular antibody (mintbody). Transgenic fruit fly and zebrafish that express histone H3 Lys9 acetylation-specific mintbody developed normally and remain fertile, suggesting that visualizing histone modifications in any tissue in live animals has become possible. These live cell modification tracking techniques will facilitate future studies on epigenetic regulation related to development, differentiation, and disease. Moreover, these techniques can be applied to any other protein modification, opening up new avenues in broad areas in biology and medicine. Thanks to the discovery of fluorescent proteins and development of live cell microscopy technologies, any protein can now be visualized in living cells and in organisms   is specifically enriched in transcription start sites and enhancers of active or potentially active genes Fig. . Others,Histone modifications change locally and globally during development and differentiation and in response to external stimuli. As dysregulation of histone modifications is often associated with diseases such as cancer (Portela and Esteller RNA polymerase II (RNAP2) is a multi-subunit DNA-dependent RNA polymerase that transcribes most genes and some small noncoding RNA. The catalytic, largest, subunit of RNA polymerase II Rpb1) harbors heptapeptide (YSTPSPS) repeats at the C-terminal domain (CTD)  with a fluorescent dye and loaded it into cells. However, this initial attempt using the whole IgG did not work well; cytoplasmically loaded IgG did not enter the nucleus because it is bigger than the nuclear pore  were suitable for detecting the endogenous histone modifications  will be valuable tools for understanding the dynamics of histone modifications and transcription in both cell cultures and in vivo. In particular, developing a panel of mintbody probes specific to various modifications should be encouraged, as the genetically encoded system is versatile and convenient to use. In addition, cells expressing mintbodies will be useful for screening and evaluating potential diagnostic inhibitors that affect epigenetic modifications. While other techniques such as FRET-based sensors can also monitor epigenetic regulation in living cells, in particular the balance between the modifying and demodifying enzymes, they cannot quantify the endogenous modifications themselves even though they seem to be suitable for assaying the effects of inhibitors (Sasaki et al.


Omi/HtrA2 gene promoter contains a CpG island at −709~+37 bp, and eight heat shock transcription factor 1 (HSF1) sites, two Sp1 transcription factor (SP1)sites, one activator protein (AP) site, seven p53 sites, and four YY1 transcription factor(YY1) sites were predicted in the core areas. Furthermore, we found that p53 and HSF1 specifically binds to the Omi/HtrA2 promoter using chromatin immunoprecipitation analysis. These results provide a foundation for understanding Omi/HtrA2 regulatory mechanisms, which could further understanding of HtrA-associated diseases.HtrA serine peptidase 2 (HtrA2), also named Omi, is a pro-apoptotic protein that exhibits dramatic changes in expression levels in a variety of disorders, including ischemia/reperfusion injury, cancer, and neurodegeneration. In our study, Omi/HtrA2 protein levels were high in the heart, brain, kidney and liver, with elevated heart/brain expression in aging mice. A similar expression pattern was observed at the mRNA level, which suggests that the regulation of Omi/HtrA2 is predominately transcriptional. Promoter binding by transcription factors is the main influencing factor of transcription, and to identify specific promoter elements that contribute to the differential expression of mouse Omi/HtrA2, we constructed truncated Omi/HtrA2 promoter/luciferase reporter vectors and analyzed their relative luciferase activity; it was greatest in the promoter regions at −1205~−838 bp and −146~+93 bp, with the −838~−649 bp region exhibiting negative regulatory activity. Bioinformatics analysis suggested that the  Omi/HtrA2, a mitochondrial pro-apoptotic protein, is member of the High Temperature Requirement (HtrA) family. Abnormal gene expression and localization of Omi/HtrA2 has been associated with a variety of disease. For instance, Omi/HtrA2 expression is elevated in lung adenocarcinoma , hepatocPromoters, which are located upstream of genes, are key points for modulating transcriptional levels. Gene promoters have many transcriptional binding sites, which can bind specific transcription factors and influence the mRNA expression levels and chromatin organization of the gene. CpG islands are DNA sequences that are rich in CG nucleotides. They often are observed around the promoter region and the first exon of genes, where they are associated with major epigenetic changes such as methylation, which influences the expression of the associated genes. Therefore, it is important to consider both the transcription factor binding sites and the potential occurrence of CpG islands to obtain a multilevel understanding of the regulatory mechanism of genes.Omi/HtrA2 gene and analyzed its sequence using bioinformatics . To study the core region of the promoter, we constructed an Omi/HtrA2 promoter/luciferase reporter vector, as well as several deletion mutants, which we transfected into murine fibroblast cells (NIH3T3), rat myocardial cells (H9c2) and human embryonic kidney cell (HEK-293) cells. This research provides a theoretical basis for study of the transcriptional regulation and function of the Omi/HtrA2 gene.In our study, we amplified the promoter of the mouse To determine whether Omi/HtrA2 is differentially expressed in tissues of young and aging mice, we performed Western blotting. For both the young and aging mice, Omi/HtrA2 showed a pattern of high protein expression in the heart, brain, kidney and liver, and lower expression in the lung and spleen. However, the balance of the expression appeared to shift, with the greatest expression in the kidney and liver for the young mice and the greatest expression in the heart and brain for the aging mice A,B. The To determine whether the differential expression of mouse Omi/HtrA2 is regulated at the level of transcription, we assessed mRNA levels by QRT-PCR C. A simiOmi/HtrA2 gene promoter, we amplified different lengths of the mouse Omi/HtrA2 gene promoter by PCR. Five products were amplified using F1–F5 as upstream primers with R as a downstream primer  and the five truncated Omi/HtrA2 gene promoter luciferase plasmids into NIH3T3, H9c2 and HEK-293 cells, with pRL renilla luciferase control reporter vector (pRL-TK) as internal control. Relative luciferase activity (RLA) as an index of promoter activity was tested 48h after transfection using a dual-luciferase reporter assay system (Omi/HtrA2 gene promoter. The activities of pGL3-472 (−379~+93 bp) and pGL3-742 (−649~+93 bp) were not significantly different from that of pGL3-239 (−146~+93 bp). Furthermore, the activity of pGL3-931 (−838~+93 bp) was lower than pGL3-742 (−649~+93 bp) suggesting that a negative regulatory element exists in the −838~−649 bp region of the Omi/HtrA2 promoter.To identify the core regions of the mouse y system . SignifiIn order to investigate the transcriptional factors that regulate the expression of mouse Omi/HtrA2, bioinformatics analysis was performed using online tools.Network Promoter Prediction assessed the core areas of the Omi/HtrA2 promoter, and two potential core active regions (−359~−310 bp and −1197~−1148 bp) with relatively high scores were identified in this promoter sequence. One CpG island was predicted in this promoter, which was located from −709 to +37 bp .Omi/HtrA2 gene by using online tools TFSEARCH, JAPAR and PROMO. This includes eight Heat shock transcription factor 1 (HSF1) sites, two SP1 sites, one AP site, seven p53 sites, four YY1 sites  and prepared several truncation mutations, which we ligated proximal to a luciferase reporter gene. The results demonstrated that −359 to 310 bp and 1197 to 1148 bp may be core regions of the Omi/HtrA2 promoter. Furthermore, the −709~+37 bp region is predicted to constitute a CpG island. The latter prediction presumes that DNA Methylation of the Omi/HtrA2 promoter is likely to be an important factor in regulating Omi/HtrA2 mRNA levels.cis-acting element or constitute a CpG island.Notably, bioinformatic predictions for the Omi/HtrA2 active regions were consistent with the functional data obtained from luciferase assays. The RLA of pGL3-1298 (−1205~+93 bp) and pGL3-239 (−146~+93 bp) was significantly higher than pGL3-931 (−838~+93 bp) and pGL3-basic,, suggesting that −1205~−838 bp and −146~+93 bp comprise an active region of the Omi/HtrA2 promoter; consistently, −1197~−1148 bp was predicted as an active region by bioinformatics analysis. The activity of pGL3-931 (−838~+93 bp) was lower than pGL3-742 (−649~+93 bp), suggesting that −838~−649 bp region might contain an inhibitory C. elegans, HSF1 mediates chaperone activity in muscle cells and neurons and is associated with aging  2014-0007)  and used at 6 months of age (“young”) or 24 months of age (“aging”). All the animal experiments followed the 2.NIH3T3, H9c2, and HEK293 cell lines were purchased from the Basic Medical Cell Center of Peking Union Medical College . H9c2 and HEK-293 cells were cultured in Dulbecco’s modified Eagle’s medium (high glucose) with 10% fetal calf serum. NIH3T3 cells were grown in Dulbecco’s modified Eagle’s medium (high glucose) with 10% calf serum. The cells were cultured at 37 °C and 5% CO260/OD280 ratios of 1.8–2.0 were selected for subsequent experiments.Genomic DNA was extracted from adult mouse hearts using the Universal Genomic DNA Extraction Kit Ver. 3.0 . The concentration and purity of DNA was assessed using an ultramicro spectrophotometer . DNA samples with ODOmi/HtrA2 gene promoter sequence, together with the start site of the NCBI gene . To prepare promoter deletions, DNA fragments of different sizes were amplified using a shared reverse primer (R) and 5 different forward PCR primers: F1, 239 bp (−146~+93 bp), F2, 472 bp (−379~+93 bp), F3, 742 bp (−649~+93 bp), F4, 931 bp (−838~+93 bp), and F5, 1298 bp (−1205 ~+93 bp). The primer sequences are shown in To prepare a full-length Omi/HtrA2 promoter luciferase constructs, we amplified a 1298 bp fragment (−1205 to +93 bp), which includes the mouse ® HS DNA Polymerase  in a 50 µL reaction mixture containing 10 μL 5× PrimeSTAR Buffer (Mg2+ plus), 1 μL PrimeSTAR HS DNA Polymerase (2.5 U/μL), 4 μL dNTP Mixture (2.5 mM each), 1 µL of each primer (10 µmol/L), and 1 µL of DNA template (<1 µg). The PCR amplification protocol was as follows: denaturation at 94 °C for 2 min; 35 cycles of denaturation at 95 °C for 30 s, annealing at 62.4 °C for 45 s, and extension at 68 °C for 30–90 s ; and final extension at 68 °C for 10 min. Samples were stored at 4 °C. All PCR products were verified by agarose gel electrophoresis and sequencing.The DNA fragments were amplified using PrimeSTARPCR products were purified using a DNA gel extraction kit , and then sticky end products were produced using a DNA A-Tailing Kit  with a 20 μL reaction mixture containing 15 μL purified PCR products, 4 μL A-Tailing Mix, and 1 μL A-Tailing Enzyme (2.5 U/μL). The reaction mixture was incubated at 72 °C for 30 min and then stored at 4 °C. The A-tailing products were cloned into pMD18-T vector  to produce recombinant constructs (pMD18-T-239 to pMD18-T-1298) which were confirmed by sequencing.KpnI  and HindIII , and the fragments of the recombinant constructs were subcloned into pGL3. The ligation mixtures, including 0.3 μg of recombinant fragments (KpnI/HindIII), 0.1 μg of pGL3-basic plasmid (KpnI/HindIII), 1 μL of 10× buffer M, and 1U of T4 ligase in a final volume of 10 μL, were incubated at 16 °C overnight and then 65 °C for 5 min. The ligation mixtures were transformed into E. coli DH5α cells. The positive recombinant clones  were extracted with a plasmid mini kit  according to the manufacturer’s instructions. Recombinant plasmids were verified by sequencing and double digestion with KpnI and HindIII.Recombinant constructs pMD18-T-239 to pMD18-T-1298 and pGL3 luciferase reporter vector  were digested for 4h at 37 °C with 4 cells/well and randomly divided into 7 groups: control (no transfection), pGL3-basic (no insert), pGL3-239, pGL3-472, pGL3-742, pGL3-931, and pGL3-1298. The medium was aspirated and replaced with serum-free medium without antibiotics 4 h before transfection according to the protocol of Lipofectamine 2000 . Lipofectamine 2000 (0.4 µL) was diluted with 25 µL Opti-MEM; and 100 ng of plasmid encoding Firefly luciferase and 10 ng of internal control plasmid encoding Renilla luciferase pRL-TK  were diluted with 25 µL Opti-MEM® Reduced-Serum Medium . The mixtures were incubated for 20 min at room temperature and then were added to the cells with antibiotic-free complete medium. Cell lysates were harvested 48 h after transfection. Firefly luciferase and Renilla luciferase activity were tested using the Dual-Glo® Luciferase Assay System  according to the manufacturer’s instructions. Firefly and Renilla luciferase activity were measured using a GloMax® 96 Microplate Luminometer , and the relative luciferase activity (RLA) was determined by calculating their ratio.Cells were inoculated in 96-well plates at a density of 5 × 10http://www.fruitfly.org/seq_tools/promoter.html). The CpG island of the mouse Omi/HtrA2 promoter was predicted by CpG Island Searcher  with lower limit values of the Observed/Expected ratio > 0.60 and GC content >50%. Transcription factors and their binding sites in the Omi/HtrA2 promoter were predicted by TFSEARCH , JAPAR  and PROMO .In order to estimate the characteristic of the mouse Omi/HtrA2 promoter, bioinformatics analysis was done using online tools. The core activity of the mouse Omi/HtrA2 promoter was predicted by Network Promoter Prediction  in adult and aging mouse hearts using the RNAprep pure Tissue Kit . The first cDNA strand was synthesized using a 1st-Strand cDNA Synthesis Kit , and then real time PCR was performed using the SYBR PrimeScript RT-PCR Kit . All of the procedures were performed according to the manufacturer’s instructions. Primers of mouse Omi/HtrA2 and GAPDH for QRT-PCR (SYBR) were designed and synthesized as follow: GAPDH-F: 5’-CTCTCTGCTCCTCCCTGTTCC-3’; GAPDH-R, 5’-CGTTCACACCGACCTTCACC-3’; Omi-F, 5’-ATCTCCTTTGCCATCCCTTC-3’; Omi-R, 5’-GGTCAGCATCATCACTCCAA-3’. The expression of Omi/HtrA2 mRNA in different tissues was calculated by the 2w/v) formaldehyde for 15 min. Cross-linked chromatin was then prepared and sonicated to an average size of 500 bp. DNA fragments were immunoprecipitated with antibodies specific to HSF1 , p53 , or control rabbit, mouse IgG at 4 °C overnight. After reversal of cross-linking, the immunoprecipitated chromatin was amplified by primers corresponding to core regions of the Omi/HtrA2 promoter. Primers were designed and synthesized as follow: Omi promoter-F, 5’-GCTACCGTCGTGCCCTGCTT-3’; Omi promoter-R, 5’-ATGCCCGAAGGCTCCAGTTT-3’.The ChIP assay was performed according to the instructions of the Magna ChIP G Tissue Kit . Briefly, mouse heart were treated with 1% . HSF1 and p53 can bind to Omi/HtrA2 promoter, and are likely to be important transcriptional factors in regulating Omi/HtrA2 mRNA levels.