Enhanced expression of the MYC transcription factor is observed in the majority of tumors. Two seemingly conflicting models have been proposed for its function: one proposes that MYC enhances expression of all genes, while the other model suggests gene-specific regulation. Here, we have explored the hypothesis that specific gene expression profiles arise since promoters differ in affinity for MYC and high-affinity promoters are fully occupied by physiological levels of MYC. We determined cellular MYC levels and used RNA- and ChIP-sequencing to correlate promoter occupancy with gene expression at different concentrations of MYC. Mathematical modeling showed that binding affinities for interactions of MYC with DNA and with core promoter-bound factors, such as WDR5, are sufficient to explain promoter occupancies observed in vivo. Importantly, promoter affinity stratifies different biological processes that are regulated by MYC, explaining why tumor-specific MYC levels induce specific gene expression programs and alter defined biological properties of cells.DOI:http://dx.doi.org/10.7554/eLife.15161.001 Genes with the potential to cause tumors and cancer are commonly called oncogenes. One example of an oncogene encodes for a protein called MYC and many tumors contain high levels of this protein. MYC is a transcription factor and studies of aggressive tumors suggested that, like most other transcription factors, MYC binds to and regulates the activity of a small number of genes in tumors. However, other studies went on to show that MYC actually binds to thousands of genes and somehow only regulates a subset of them during tumor development.Lorenzin et al. set out to understand how this process works by generating human cells in which the concentration of MYC protein could be altered. In the experiments, the concentration was varied from normal healthy levels to the high levels found in aggressive tumors. The amount of MYC bound to genes and the extent to which it activated the genes inside these cells was also measured.Lorenzin et al. found that increasing MYC levels from normal to tumor-specific levels did not affect MYC binding at genes where the transcription factor was already strongly bound in normal cells. Rather, MYC binding increased only at genes that were weakly bound in normal cells. Consistent with this observation, only genes at which MYC was weakly bound in normal cells were activated by increasing MYC levels. This observation suggests that increasing the concentration of MYC protein from normal to tumor-specific levels “fills up” previously empty binding sites around these genes with the transcription factor.Lorenzin et al. also used mathematical modeling to understand how the concentrations of MYC in normal and tumor cells might explain how MYC behaves in cells. Together, the results imply that the MYC transcription factor regulates distinct sets of genes in normal and tumor cells according to how much MYC is present. Further studies may show that the altered regulation of a tumor-specific set of genes is important for tumor development and could use this new information to identify new targets for treating MYC-driven tumors.DOI:http://dx.doi.org/10.7554/eLife.15161.002 Deregulated expression of one of the three members of the MYC gene family  is observed in the majority of human tumors . A broadMYC proteins are transcription factors that bind DNA as part of several protein complexes; best understood is a dimeric complex of MYC with its partner protein MAX that activates transcription via binding to a specific DNA motif termed E-box with a consensus sequence of CACGTG . To reprGiven this global binding pattern, it is surprising that MYC-driven tumors can be recognized by a specific set of up- and down-regulated MYC target genes that holds considerable prognostic and therapeutic value . One hypWe show here that the divergent models can be reconciled with experimental observations without the need to invoke productive and non-productive modes of DNA binding. We analyzed U2OS cells that express a doxycycline-inducible allele of MYC  and charTo determine the effect of changes in MYC levels on DNA binding and gene expression, we have previously engineered U2OS cells to express a doxycycline-inducible allele of MYC . We chosTet-on cells had previously shown that endogenous MYC binds to about 5,500 promoters and that this number increases to about 8,400 MYC-bound promoters upon addition of doxycycline . This prompted us to analyze whether the anti-correlation between occupancy by endogenous MYC and recruitment of exogenous MYC is evident globally , which are strongly occupied by endogenous MYC, and did not further decrease upon addition of doxycycline. In contrast, MXD6 occupancy was higher for two genes , which are poorly bound by endogenous MYC, but strongly decreased upon induction of MYC. Taken together, the easiest model to explain the data is to suggest that a few hundred of promoters are saturated by endogenous MYC in U2OS cells and that overexpression of MYC leads to saturation of the majority of MYC-binding sites in promoters  and used it as a measure for the apparent binding affinity  showed the lowest EC50 values, followed by genes encoding proteins involved in biosynthetic processes, translation and ribosome biogenesis  analysis , which uogenesis . These gogenesis . At the 0 values . We hypo50 values, we wondered which factors account for promoter affinity towards MYC. In a complex with MAX, MYC directly contacts E-box sequences in DNA. We initially tested whether the known DNA binding properties of MYC/MAX heterodimers can explain the EC50 values measured in ChIP-sequencing experiments. The heterodimer makes both base-specific contacts and contacts to the phosphate backbone of DNA and hence binds to canonical E-boxes (CACGTG), non-canonical E-boxes (CANNTG) and DNA with a random sequence (EboxK) or unspecific binding sites (NNNNNNK)   illustraKNNNNNN)  (see redKNNNNNN) . The res1x102 μM . Compari50 values than those predicted by the affinity to E-box-DNA, indicating that binding to DNA alone is not sufficient to account for the chromatin occupancy of MYC observed by ChIP-sequencing. Model simulations predict that a reduction of the dissociation constant of MYC and E-boxes by about one order of magnitude shifts the EC50 value into the measured range of MYC molecules .The majority of E-boxes located in promoters showed considerably lower EColecules . To explolecules . In contolecules . In addiolecules  and witholecules . This obolecules . Recent olecules . MYC binC BoxIII , a domai of WDR5 . This va50 value of 0.27 μM; The model predicts that occupancy by MYC is strongest at promoters containing both E-boxes and WDR5-binding sites but is also high for promoters bound by WDR5 but lacking E-boxes (ECWBM'), which is strongly compromised in binding to WDR5 . By using previously published datasets , whereas indirectly repressed genes ('Down (indirect)' in Finally, a prominent discrepancy among reports analyzing the transcriptional consequences of MYC level manipulation is the presence or absence of direct MYC-mediated repression . As diredatasets , we idenanalysis  as well analysis . Accordianalysis , show siThe aim of this study was to understand whether an analysis of MYC function at different protein levels in combination with mathematical modeling can reconcile two seemingly conflicting observations: Whereas MYC regulates specific genes in some biological settings ('specifier model'), in others MYC enhances expression of all genes transcribed by RNA polymerase II ('amplifier model'). Our study has led to two major conclusions.The first conclusion is that direct interaction with DNA alone is not sufficient to account for the observed occupancies of core promoters by MYC/MAX complexes. This result is in agreement with experimental observations showing that the positions occupied by MYC/MAX complexes across the human genome closely correlate with the RNA polymerase II transcription machinery even on promoters, which do not contain E-boxes . The conThe mathematical analysis shows that the interaction of MYC/MAX with promoter-bound WDR5 can strongly enhance occupancy of core promoters. Consistent with this finding, a mutant allele of MYC unable to bind to WDR5 shows much reduced binding to high-affinity promoters. MYC does not only interact with WDR5, but with several components of the transcription machinery including P-TEFb, TBP and TRRAP . Additioin vivo.Most likely, therefore, genome-wide occupancies of MYC/MAX complexes result both from interactions of MYC/MAX complexes with DNA and from protein/protein interactions with resident chromatin proteins. We propose that the dependence of MYC/MAX chromatin binding on interactions with proteins that are themselves influenced by existing gene expression patterns at different physiological states of cells, contributes to specific gene regulation by MYC even though MYC´s mechanism of action is the same at all promoters  by MYC changes in this setting. Importantly, measurements of MYC levels and modeling approaches show that promoters can be saturated by levels of MYC that are reached in proliferating cells . As a re50 values stratify classes of promoters of genes that encode proteins that differ in function, we propose that this will alter the physiological and metabolic state  supplemented with 10% FCS  and 1% penicillin/streptomycin (Sigma-Aldrich). IMECs and HMLE cells were cultivated in DMEM/F12 (co) supplemented with 1% penicillin/streptomycin (Sigma-Aldrich), 10 µg/ml insulin (Sigma-Aldrich), 0.5 µg/ml hydrocortisone (Sigma-Aldrich) and 20 ng/ml EGF . MCF10A cells were cultivated in DMEM/F12  supplemented with 5% horse serum (Sigma-Aldrich), 10 µg/ml insulin (Sigma-Aldrich), 0.5 µg/ml hydrocortisone (Sigma-Aldrich) and 20 ng/ml EGF (Life Technologies) and 100 ng/ml choleratoxin (Sigma-Aldrich). Cell lines were tested for mycoplasma and authenticated by STR profiling . They were not found to be on the list of commonly misidentified cell lines  and received from research labs, companies (HCT116: LGC genomics) or public repositories (HEK293: ATCC).For siRNA transfections, the RNAiMAX reagent (Thermo Fisher Scientific) and the Opti-MEM medium (Thermo Fisher Scientific) were used following the manufacturers’ instructions. A pool of siRNA against MYC  and a control pool of siRNA  were purchased from GE Healthcare. Cells were harvested 48 hr after transfection.MYC was cloned into the pETM11 (EMBL-Heidelberg) vector. The protein was expressed as an N-terminally His-tagged protein in ArcticExpress (DE3)RIL cells  after an OD of 0.8 was reached by induction with 0.1 mM isopropyl-β-thiogalactoside (IPTG) at 14°C for 18 hr. The protein was purified to homogeneity by metal affinity chromatography  followed by anion exchange chromatography (AEC). AEC was performed using a MonoQ 10/100 GL column  equilibrated with 20 mM HEPES pH 8.0 and 0.25 M NaCl. The protein did not bind to the column but eluted in the flow through. Size exclusion chromatography was performed using a HiLoad 16/60 Superdex 200 prep grade column  to confirm its monomeric state and exclude aggregation. The protein was concentrated after AEC to 0.59 mg/ml based on the calculated extinction coefficient using ProtParam (SwissProt) and then flash frozen adding 10% glycerol for storage.The mRNA sequence of the dimerization and DNA-binding domain of human Cells were either lysed in lysis buffer  with protease and phosphatase inhibitor cocktails (Sigma-Aldrich) or harvested by trypsinization, counted and lysed directly in SDS sample buffer. The same number of cells or total protein amount was loaded for each sample on Bis-Tris or Tris-Glycine gels and transferred to PVDF membranes .To detect the MYC protein the 9E10 antibody (amino acids: 410–419) or the anti-MYC antibody  were used. To detect Vinculin the V9131 anti-Vinculin antibody (Sigma-Aldrich) was used.The immunoblots were visualized and quantified using the LAS-4000 mini  or the Odyssey CLx Infrared Imaging System .The number of MYC molecules/cell was calculated by comparing the signal of recombinant MYC protein with cell lysates from U2OS cells in biological triplicates in quantitative immunoblots (Odyssey CLx Infrared Imaging System). To determine the nuclear MYC concentration, the size of U2OS nuclei was obtained from . BiologiChIP and ChIP-sequencing was performed as described previously . BrieflyFor RT-qPCR analysis, total cellular RNA was extracted using the peqGOLD TriFast  reagent. The first strand synthesis was performed using M-MLV Reverse Transcriptase (Thermo Fisher Scientific) and random hexamer primers . Results were normalized to β2-microglobulin expression. Primers are listed in For RNA-sequencing, total RNA was extracted using the RNeasy mini columns  including on-column DNase I digestion. PolyA+-RNA was isolated from total RNA with the NEBNext Poly(A) mRNA Magnetic Isolation Module . The NEBNext Ultra RNA Library Prep Kit for Illumina was used for library preparation following the manufacturer’s instruction. Size selection of the libraries was performed with the AMPure XP Beads , followed by 12 PCR cycles for amplification. Library quantification and quality was assessed using the Experion Automated Electrophoresis System . The libraries were sequenced with the Illumina Genome Analyzer IIx .2 of the median normalized values were displayed as density plots on R using 'sm' library density function.U2OS cells were treated with doxycycline/ethanol and were fixed with 4% paraformaldehyde. Fixed cells were treated with blocking solution  for 45 min after washing. Primary antibodies were incubated overnight at 4°C and incubated for 1 hr with the corresponding fluorescently labeled secondary antibodies at room temperature after washing . Cells were mounted on object glass slides using aqua-fluoromount (Sigma) after washing and imaged under a confocal microscope (Nikon Ti-Eclipse). For fluorescent intensity measurement, ImageJ 1.50hr  was usedFor RNA-sequencing, reads were aligned to the human reference genome (hg19) using BOWTIE v.0.12.8. The obtained BAM files were used for further analysis with R/BioConductor. For differential gene expression analysis EdgeR was employed. The rpkm values were calculated by mapping the read counts to the exons of the corresponding gene. Heat maps showing the gene expression changes were obtained using R.ChIP-sequencing data were obtained from  and analPeak calling was performed with MACS v.1.4.2 , SICER v.1.1   and CCATTo analyze the occurrence of E-boxes in the MYC peak the CentriMo tool from the MEME Suite  was used7 reads were randomly chosen from fastq files (GSE60897), mapped with BOWTIE and reads in a window of ± 100 bp around the center of the MYC peak were counted using Seqminer. For Venn diagrams, publicly available peak annotations (GSE60897) were used and the overlap was calculated using Bedtools. For binned plots, genes were sorted and divided in equally sized-groups and the median or mean values are shown. As few genes show very high EC50 values, sometimes one or two bins were not shown in the plots, for clarity.To calculate the distribution around the TSSs (heat maps) or the center of the MYC peak (occupancy), Seqminer v.1.3.3 was used. Heat maps were visualized using Treeview. MYC and H3K4me3 occupancies (in – and + Dox) were calculated using a window of ± 100 bp for the center of the MYC peak and used to obtain MYC recruitment. DNA binding of MYC and a mutant of MYC that is compromised in binding to WDR5, was analyzed similar: 5x1050 values for MYC binding at each promoter were calculated using the MYC nuclear concentrations and MYC occupancy in – and +Dox. MYC occupancy was calculated by subtracting the tag values of the input from the tag values of the MYC ChIP and resulting negative values were set to 0. The Michaelis-Menten model was used to perform the fitting of the data in GraphPad Prism and to calculate maximal occupancy of MYC and the EC50 values.EC50 values for regulation of MYC target genes, the MYC depletion RNA-sequencing experiment and the Dox titration RNA-sequencing experiment were used. The fold change of expression for each gene was calculated relative to siMYC. Only activated genes were considered. The EC50 values were obtained using the fold change values and the nuclear MYC concentrations. Michaelis-Menten model was used to perform the fitting of the data in GraphPad Prism. To statistically test the difference of the distribution of the EC50 values of different gene sets, the Mann-Whitney-Wilcoxon test was used. For functional analysis of the genes, Gene Set Enrichment Analyses (GSEA) were performed with the C5 collection of gene sets from the MSigDB (http://www.broadinstitute.org/gsea/msigdb) using the GSEAPreranked tool, where indicated. Gene ontology analysis was performed using DAVID  and algebraic equations describing conservation relations. Model design, the particular equations and parameters are listed in the Appendix 1. An extended model analysis is provided in Appendix 2. Steady-state solutions were calculated by setting all time derivatives to zero and solving the resulting algebraic equation system numerically. All calculations were performed using Mathematica 10.2 .http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE77356The data sets supporting the results of this article are available in the Gene Expression Omnibus repository, GEO: GSE77356. Data access:  In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been favorably evaluated by Jessica Tyler (Senior editor) and three reviewers, one of whom, Chi Dang, is a member of our Board of Reviewing Editors. The following individual involved in review of your submission has agreed to reveal their identity: David Levens (peer reviewer).Thank you for submitting your article "Different promoter affinities account for specificity in MYC-dependent gene regulation" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission. The requested revision mostly requires additional analysis of extant data and does not necessarily require new experiments. For major point #1, it is possible that you may have the data already as alluded to in the Walz et al. paper  that employed large-scale ChIP to propose MYC occupancy dependance by promoter affinity. Using mathematical modeling, Lorenzin et al. are able to assign a binding affinity to each promoter (EC50) and make the intriguing conclusion that E box binding alone is not strong enough to explain how MYC is tethered to the majority of its DNA targets. Finally, the authors measure gene expression by titrating the level of MYC which, consistent with their model, reveals a correlation between promoter affinity and the level to which expression from these genes was increased. Specifically, they demonstrate that high-affinity binding sites are almost fully occupied by MYC and could not be further bound, resulting in a seemingly lack of gene activation by ectopic MYC. This is best illustrated in an artificial system of U2OS cells that have relatively low MYC levels despite being a cancer cell line. Upon activation of ectopic MYC, genes encoding ribosome biogenesis genes, which have high-affinity MYC binding sites, could not be further bound and hence do not seem to be activated. However, knockdown of endogenous MYC in U2OS cells resulted in diminished binding of MYC and expression of ribosome biogenesis genes. By monitoring MXD at E-boxes, the authors show an in vivo competition with MYC that is sensitive to MYC levels. The authors also show that MIZ repression explains most of the negative gene regulation with MYC that is again dependent on the level of MYC binding. Overexpression of MYC, on the other hand, results in MYC binding to lower affinity sites, resulting in ectopic activation of genes such as those involved in angiogenesis and suppression of cell adhesion genes. The authors also use publicly available data for the MYC-mediated mouse lymphoma and also documented MYC's role in inducing ribosome biogenesis genes . Using data deposited on WDR5, the authors corroborate the role of WDR5 in recruiting MYC to DNA for gene regulation. In addition, the experimental data, the authors also provide mathematical modeling, providing further insights into how MYC binding affinities affect gene expression and drive specific biological functions.Overall, this body of work is compelling, although the authors should openly acknowledge that the U2OS cell line is complicated by its intolerance of high expression of MYC  The authors use recombinant, purified protein to calibrate immunoblots in order to calculate the absolute number of MYC molecules per cell using cell lysate. This method however will only indicate the average level of MYC for the entire population. It remains possible that some cells express no MYC while others express levels of MYC far exceeding the average. The authors should employ immunofluorescence or a similar technique to demonstrate MYC expression in their system is relatively homogenous.2) In 3) The author's analysis of transcription upon knock-down of MYC revealed that high-affinity promoters showed the greatest change in gene expression upon MYC depletion. This finding seems to be in disagreement with the finding from Nie et al.  in which B cells expressing very low levels of MYC show a proportional decrease of MYC binding to all genomic targets. Can the authors resolve this discrepancy? At the very least, the authors should perform ChIPseq upon MYC knock-down in their U2OS model and determine promoter occupancy to complement their gene expression experiments.4) There appears to be somewhat of a disconnect between the accounting of MYC binding at promoters and the heat map shown in +, E-box- promoters? This class should be considered, too. What is the extent of MYC binding, expression levels and functional GSEA for this class of promoters?5) There are several issues related to the model. The authors only model the influence of WDR in concert with E-boxes; what is the level of binding and the influence of MYC at WDR6) The model assumes equilibrium (or at least steady state) binding. While this is often a reasonable assumption, at promoters, in vivo, there are many energy-dependent and kinetic steps, that might skew that apparent on and off rates. For example, the authors' own previous work showed that MYC degradation during the transcription-cycle might be required to increase expression. Such degradation will increase the apparent MYC off-rate, artificially depressing apparent affinity of MYC for the promoter. The kinetic limitations of the model should be discussed in the text or in the supplemental material.7) Some discussion of expression levels for the various functional classes of MYC-target promoters is warranted. It has previously been suggested that MYC binding is related to output levels. It may be that some cellular processes (such as translation) demand high output, and that it is the high level of transcription at these genes that licenses MYC binding, that in turn stimulates more transcription. Accompanying Tables of genes in groups identified in the Figures should be provided. . Further, the authors should provide an analysis of selected metabolic pathways, such as glycolysis and glutaminolysis, that may be regulated in U2OS cells. Overall, this body of work is compelling, although the authors should openly acknowledge that the U2OS cell line is complicated by its intolerance of high expression of MYC  to doxycycline and hence long-term ectopic expression of MYC induces apoptosis in U2OS cells ; therefore all subsequent analyses were performed 28-30 hours after addition of doxycycline.” at the beginning of the Results section.This nuance could well skew MYC's ectopic activities that are specific for this cell line and hence not generalizable to cancer cells driven by high MYC such as Burkitt's lymphoma or neuroblastoma. For example, the authors should compare the 'ectopic' MYC targets among the different datasets . Are there cell-type-independent MYC ectopic target genes similar to cell-type-independent core MYC targets that are involved in ribosome biogenesis?In reply to this comment, we compared the functional groups of low-affinity target genes defined in the U2OS cell system with those the Eµ-Myc model and describe the data in the new panels H and I of Essential revisions:1) The authors use recombinant, purified protein to calibrate immunoblots in order to calculate the absolute number of MYC molecules per cell using cell lysate. This method however will only indicate the average level of MYC for the entire population. It remains possible that some cells express no MYC while others express levels of MYC far exceeding the average. The authors should employ immunofluorescence or a similar technique to demonstrate MYC expression in their system is relatively homogenous.To address the cell-to-cell variance of MYC levels, we performed immunofluorescence of MYC with three different antibodies at physiological and ectopic MYC concentrations. The new 2) In In the former version of the manuscript we quantified a small range of defined amounts of recombinant MYC protein. We calibrated the cellular MYC concentration in cells treated with a concentration of doxycycline, which leads to a signal close to that of the recombinant protein. We then estimated concentrations in all other conditions based on relative changes and assumed linearity .We agree with the reviewers that an absolute estimation of MYC levels at each condition  is more reliable. We therefore repeated the experiment using an extended range of standards covering the signal intensity from all biological conditions analyzed in biological triplicates and calculated a fitting model for the titration of recombinant MYC protein (which indeed does not behave linear). This regression analysis was used to estimate cellular MYC concentrations. The numbers are very similar for low cellular MYC concentrations  and differ by a maximal factor of three for the highest doxycycline concentration if compared with the former analysis. The new blots are shown in 3) The author's analysis of transcription upon knock-down of MYC revealed that high-affinity promoters showed the greatest change in gene expression upon MYC depletion. This finding seems to be in disagreement with the finding from Nie et al.  in which B cells expressing very low levels of MYC show a proportional decrease of MYC binding to all genomic targets. Can the authors resolve this discrepancy? At the very least, the authors should perform ChIPseq upon MYC knock-down in their U2OS model and determine promoter occupancy to complement their gene expression experiments.To address this comment, we performed a new MYC ChIP-sequencing experiment upon depletion of MYC by siRNA and a side-by-side ChIP-sequencing experiment with control cells (siCtr). The data is presented in the new We think that our data fit well to those reported by Nie et al. For instance, in Figure S2F of Nie et al. , MYC binding in T4 (after 4 hours of activation) is not uniform across all genes and MYC binding further increases at T14 on some promoters that are weakly bound at T4 , but appears to be saturated at T4 at high affinity binding sites (e.g. group “I”).4) There appears to be somewhat of a disconnect between the accounting of MYC binding at promoters and the heat map shown in To address these comments, we include a new supplemental Figure , in whic+, E-box- promoters? This class should be considered, too. What is the extent of MYC binding, expression levels and functional GSEA for this class of promoters?5) There are several issues related to the model. The authors only model the influence of WDR in concert with E-boxes; what is the level of binding and the influence of MYC at WDR+CACGTG--genes is higher than WDR5-CACGTG--, but lower than WDR5+CACGTG+- genes (description in the aforementioned paragraph).In response to this comment, we included the group of “WDR5-bound DNA sites without canonical E-boxes” as a fourth class in our model. The reviewers are correct in expecting that this is an interesting group, as binding to those sites is predicted to be high at endogenous MYC concentrations in U2OS cells (see new 6) The model assumes equilibrium (or at least steady state) binding. While this is often a reasonable assumption, at promoters, in vivo, there are many energy-dependent and kinetic steps, that might skew that apparent on and off rates. For example, the authors' own previous work showed that MYC degradation during the transcription-cycle might be required to increase expression. Such degradation will increase the apparent MYC off-rate, artificially depressing apparent affinity of MYC for the promoter. The kinetic limitations of the model should be discussed in the text or in the supplemental material.As the reviewers point out, binding of MYC to promoters can be affected by several regulated processes that may change the kinetic rates of association (“on-rate”) or of dissociation (“off-rate”). To our knowledge, experimental data on the kinetics of “on-rate” and “off-rate” constants or the respective kinetic rate laws of MYC is not yet available. Moreover, ChIP-sequencing experiments are based on the general notion that the number of DNA-bound molecules (tags) presumably does not change (at least) for the time frame of conducting the experiment. We therefore used the steady state assumption for calculating apparent dissociation constants, which imply ratios on the “on rates” and “off rates”. We mention this limitation in the main text  and refer to appendix 1 for further discussion of this assumption. In order to check for the robustness of the model with respect to the specific values of these dissociation constants, we varied them over a broad range see  and disc7) Some discussion of expression levels for the various functional classes of MYC-target promoters is warranted. It has previously been suggested that MYC binding is related to output levels. It may be that some cellular processes (such as translation) demand high output, and that it is the high level of transcription at these genes that licenses MYC binding, that in turn stimulates more transcription.Our analysis of MYC binding at endogenous concentrations clearly – and in agreement with the reviewers’ standpoint – demonstrated that target genes are characterized by high expression  and openAccompanying Tables of genes in groups identified in the Figures should be provided. .Gene sets used in the study are now provided in Further, the authors should provide an analysis of selected metabolic pathways, such as glycolysis and glutaminolysis, that may be regulated in U2OS cells.50 values of selected metabolic pathways and included these analyses in 50 values for glycolysis, lipid- and purine metabolism (We analyzed the EC


FCGRT gene encoding the alpha chain of hFcRn. The data obtained from site-directed mutagenesis in transient transfection experiments indicate that the Sp1 sites at positions -641, -635, and -313, CF1/YY1 elements at positions -586 and -357, and the AP-1 motif at -276 within the-660/-233 fragment of the human FCGRT promoter (hFCGRT) participate in the regulation of human FCGRT in all selected cell lines. However, their individual contribution to promoter activity is not equivalent. The Sp1 binding site at -313 and the AP-1 site at -276 are critical for the activity of the hFCGRT promoter in epithelial and endothelial cells. Moreover, the CF1/YY1 site at -586 in differentiated THP-1 cells, plays an essential role in the transcriptional activity of the promoter. In addition, the C/EBPbeta binding site at -497 of the hFCGRT promoter in epithelial and endothelial cells, and the C/EBPbeta motif located at -497 and -233 within the hFCGRT promoter in differentiated THP-1 cells may function as positive regulatory sequences in response to LPS or PMA stimulation. EMSA and supershift analyses showed that the functionally identified binding motifs in the hFCGRT promoter were able to specifically interact with their corresponding  transcription factors (TFs), suggesting their possible involvement in the regulation of the human FCGRT gene expression.Human epithelial, endothelial and PMA-differentiated THP-1 cell lines were used as model systems to study the transcriptional regulation of the human  FCGRT gene. A more complete understanding of this gene regulation will provide a possibility to modulate the biological functions of hFcRn, with potential future applications, for example in the therapy of IgG-mediated autoimmune diseases. Knowledge of the exon/intron organization and sequence of the gene encoding human FcRn α chain (FCGRT) ATP was obtained from Hartmann Analytic GmbH (Germany). NucleoSpin RNA II kit was acquired from Macherey-Nagel GmbH (Germany).Dulbecco’s modified Eagle’s medium, RPMI 1640 medium, Minimum Essential Medium alpha (MEM-α) were obtained from the Laboratory of Biopreparations of the Institute of Immunology and Experimental Therapy . Tissue culture plates were purchased from Costar (USA). Bacterial LPS from 2 in a humidified incubator. In the PMA stimulation experiments, HSkMEC, Lu 106 and Caco-2 cells were cultured in growth medium with 5% FBS in the presence of 100 ng/ml PMA for 6 hours. For the LPS treatment, these cells were incubated in medium supplemented with 5% normal human serum containing 5 g/ml LPS (Escherichia coli 055:B5) for 1 or 6 hours.The human colon epithelial cell line Caco-2, human monocyte cell line THP-1, and human promyelocytic leukemia cell line HL-60 were obtained from the American Type Culture Collection (ATCC). The Caco-2 cells were grown in Dulbecco’s modified Eagle’s medium supplemented with 12% fetal bovine serum (FBS), 0.03% L-glutamine, 100 units/ml penicillin, 100 g/ml streptomycin, and 1% non-essential amino acids. THP-1 cells were cultured in RPMI 1640 medium supplemented with 10% FBS, 0.03% L-glutamine, 25 mM HEPES, 1 mM sodium pyruvate, 100 units/ml penicillin, and 100 g/ml streptomycin. To induce monocytes to macrophage differentiation, THP-1 cells were grown in the presence of 10 ng/ml PMA for 3 days. The Lu 106 epithelium-like cell line, human umbilical vein endothelial cell line (HUVEC), and human skin microvascular endothelial cell line (HSkMEC)  were pur6) using the NucleoSpin RNA II kit according to the manufacturer’s recommendations. First-strand cDNA was synthesized from total RNA using SuperScript III Reverse Transcriptase and an oligo(dT)23 primer as recommended by the manufacturer. PCR was performed using the following mixture: 25 u/ml Taq DNA polymerase (DreamTaq) in the buffer provided, 1.5 mM MgCl2, 0.2 mM dNTP mix, 0.2 μM concentrations of each primer and 2 μl cDNA in a 20 μl final volume. PCR was initiated with a denaturing step at 94°C for 3 min followed by 35 amplification cycles (25 for GAPDH) consisting of a denaturing step at 94°C for 1 min (30 s for GAPDH), annealing at 58°C for 1 min , and extension at 72°C for 1 min. At the end of the 35 cycles (25 for GAPDH), reaction was run for an additional 10 min at 72°C and then maintained at 4°C until analyzed by 1.5% agarose gel electrophoresis.Total RNA was isolated from cells ; FcRn2 . The cDNA was also amplified by GAPDH-specific primers  as a control to monitor the quality of the RNA purification and cDNA synthesis. The PCR products for human FCGRT were extracted from the gel and purified using the QIAquick Gel Extraction Kit and then sequenced by GENOMED S.A. .The following primers specific for human Nuclear extracts were prepared from: PMA-differentiated THP-1 cells, differentiated THP-1 after stimulation with LPS, Lu 106, Caco-2 and endothelial cell lines (untreated and treated either with PMA or LPS), according to the method of Schreiber et al.  with min2, 50 mM NaCl). Wild-type ds-oligonucleotides (double-stranded oligonucleotides) were employed either as probes following the 5′-end labeling using [γ-32P]ATP and T4 polynucleotide kinase, or as unlabeled competitors. The mutated ds-oligonucleotides were only used as competitors. Single-stranded oligonucleotides (wild type and mutated) were synthesized and purified on HPLC by GENOMED S.A. . They represented the sequences of the hFCGRT promoter encompassing the putative transcription factor binding motifs. The sense sequences of the oligonucleotides used in EMSA are shown in To prepare the double-stranded DNA oligonucleotides (wild-type and its mutated version) for EMSA, single-stranded forward and reverse oligonucleotides were annealed by heating to 95°C and cooling slowly to room temperature in annealing buffer  for 15 min on ice followed by the addition of approximately 70 fmol of 32P-labeled probe and an additional 30 min incubation at room temperature. In competition experiments, a 100-fold molar excess of unlabeled competitor (wild type or mutant ds-oligonucleotide) was preincubated with the extract before the addition of the labeled probe. For supershift assays, nuclear extract in binding buffer (without DTT) was preincubated with a rabbit polyclonal antibody against the transcription factor or non-immune rabbit IgG for 60 min on ice, and then with poly(dI-dC)·poly(dI-dC) for 15 min prior to incubation with the radiolabeled probe. Two microgram of antibody was used in each supershift assay. Subsequently, the samples were resolved on 5% polyacrylamide gels in 0.5 x TBE buffer . Electrophoresis was performed at 180 V for 2 h at room temperature. After electrophoresis, the gels were autoradiographed by exposure to storage phosphor screens for 24–72 h at -20°C, and the DNA-protein complexes were analyzed using a phosphor imager (Typhoon 8600) equipped with ImageQuant software (Molecular Dynamics).DNA binding reactions were performed by preincubating the nuclear extract (10–15 μg of protein) with 2 μg of poly(dI-dC)·poly(dI-dC) in binding buffer  with KpnI and AvrII. Then this fragment was subcloned into the KpnI/NheI sites of the promoterless firefly luciferase reporter vector, pGL3-basic, to obtain the wild type hFCGRT promoter reporter construct, designated as pGL3-711(WT). The orientation and nucleotide sequence of the DNA fragment (-660/+52) inserted into the pGL3-basic luciferase vector was verified by sequencing . Mutant promoter constructs were generated from the pGL3-711(WT) plasmid using the QuickChange Lightning Site-directed Mutagenesis Kit, according to the manufacturer’s recommendations. Primer sets used to create the desired mutations in the transcription factor binding sites within the fragment (-660/+52) of the hFCGRT promoter are listed in hFCGRT promoter. Therefore, mutant promoter constructs were also generated, carrying mutations in all binding sites specific for a given transcription factor. The pGL3-711(mSp1-1+2) mutant construct served as a template to obtain the pGL3-711(mSp1-1+2+3) mutant construct containing the mutated Sp1 binding sites at positions -641, -635 and -313. The pGL3-711(mC/EBPβ-1) construct, carrying a mutation in the C/EBPβ site at position -497 was used to generate the pGL3-711(mC/EBPβ-1+2) reporter construct containing mutations in both C/EBPβ motifs (at -497 and -233). The pGl3-711(mCF1-1) construct with a mutation of the CF1/YY1 site at position -586 served as a template to create the pGL3-711(mCF1-1+2) construct carrying mutations in CF1/YY1 binding sites located at positions -586 and -357. The promoter reporter constructs were purified using Plasmid Midi AX Kit and all mutations were confirmed by DNA sequencing.The DNA fragment (bases -660 to +52) of the hransIT-2020 reagent as described by the manufacturer. Briefly, the day before transfection, Caco-2, Lu106 and HSkMEC cells were seeded at a density of 1.9–2.3 x 105 cells/well, and THP-1 at 1 x 106 cells/well, in 1 ml of complete growth medium. Directly before transfection, the cells were washed twice with PBS and once with the complete growth medium without antibiotics and incubated in 1 ml of the same medium for 1–2 h. DNA complexes with TransIT-2020 reagent were prepared as follows: 0.9–1.8 μg/well of promoter luciferase construct, or the promoterless luciferase pGL3-basic plasmid (negative control), plus 0.1–0.2 μg/well of Renilla luciferase vector (phRG-B) in 100 μl of Opti-MEM I reduced serum medium were gently mixed with TransIT-2020 reagent. The ratio of TransIT-2020 reagent to DNA was optimized for each cell type. After incubation of the mixtures at room temperature for 20 min, generated complexes were added to the wells with cells (100 μl of each complex into one well) and incubated at 37°C in 5% CO2. Twenty-four hours after transfection, the cells were washed twice with PBS and lysed in 250 μl/well of 1x passive lysis buffer. The lysates were centrifuged at 3000 g for 5 min at room temperature to remove cell debris and then the supernatants were assayed for luciferase activity. The transfected THP-1 cells were exposed to PMA (100 ng/ml) for 4 hours prior to lysis. Firefly and Renilla luciferase activities in 20 μl of cell lysate was measured according to the Dual Luciferase Reporter Assay System protocol using a Glomax 20/20 luminometer. In each experiment, the firefly luciferase activity from various promoter luciferase constructs and pGL3-basic plasmid was normalized to the Renilla luciferase activity driven by the cotransfected phRG-B vector. The normalized transcriptional activity of the mutant constructs and pGl3-basic plasmid was presented as a percentage of the normalized activity of the wild-type pGL3-711(WT) construct, which was defined as 100%.Transient transfections of all cell types were carried out in 12-well tissue culture plates using Tt test.Data from transient transfection assays are presented as means ± SD of three to six independent experiments performed in duplicate for each construct. Statistical analysis of the results was carried out using two-way analysis of variance (ANOVA) as well as Student’s FCGRT, human epithelial and endothelial cell lines and PMA-differentiated THP-1 cells were used. These cell lines were chosen, because they represent cell types that have been found to express hFcRn in vivo. Although hFcRn was previously reported to be expressed in THP-1 cells ATP and T4 polynucleotide kinase.To test whether the potential regulatory elements interact with nuclear extracts (from the selected cell lines), and to identify the transcription factors specifically binding to these regulatory motifs, EMSA and antibody supershift assays were performed. Double-stranded oligonucleotides for these experiments were prepared by annealing the complementary single-stranded oligonucleotides representing sequences of the hFCGRT promoter are presented in Figs Representative results from EMSA and supershift tests of the hFCGRT promoter, supershift assays were performed with antibodies against the Sp family transcription factors. The upper complex 1 supershifted with antibodies specific for Sp1  with nuclear extracts resulted in two specific protein-DNA complexes (FCGRT promoter. The lower mobility of the DNA-protein complex formed with the CF1-1 oligonucleotide (The (CF1-1) oligonucleotide, corresponding to the hobserved , lane 2,observed , lane 3.observed , lane 4.observed , lane 3,observed , lane 4 observed , lane 5.omplexes , lane 2.omplexes , lane 3,omplexes , lane 4.omplexes , lane 3.omplexes , lane 4.cleotide , lane 2,cleotide , lane 2,cleotide , lane 5.FCGRT promoter. The C/EBPβ transcription factor is expressed at a low level in normal cells, but can be drastically and rapidly induced in many cells by cytokines and mitogens such as LPS or PMA, indicating that C/EBPβ may be involved in the transcriptional regulation of genes in inflammatory situations. Expression of C/EBPβ was shown to be increased during monocyte differentiation  had a dramatic effect on the promoter activity in all the selected cells, as there was an 85–89% decrease observed in the luciferase activity. When the Sp1 sites at positions -641, -635, and -313 were mutated simultaneously [pGL3-711(mSp1-1+2+3) construct], luciferase expression driven by this mutant construct was comparable to that of the wild-type pGL3-711 (WT) in Lu 106 cells, while in Caco-2, THP-1 and HSkMEC cells it was reduced only to 55–60% of the wild-type promoter activity, essentially abating the positive effect of the Sp1 site at -313. These results indicated that the Sp1 sites located at positions -641, -635, and -313 acted as positive regulators of the hFCGRT promoter activity. The Sp1 motif at -313 may be the most important regulatory sequence for transcription of the human FCGRT gene in all model cells, because mutation of this site had a stronger effect on promoter activity than did mutations in the Sp1 binding sites at -641 and -635. The data also suggested that the partly overlapping Sp1 sites at positions -641 and -635 might suppress the positive effect of the Sp1 sequence at-313 on the human FCGRT gene transcription.To investigate the function of individual Sp1 sites, each Sp1 site alone or in several combinations was mutated in the pGl3-711(WT) promoter construct. The activities of mutant promoters were compared to that of the wild-type promoter construct. As shown in FCGRT promoter in Caco-2, Lu 106, HSkMEC and THP-1 cells. Mutation of the AP-1 binding site at position -276 caused a decrease in the activity of the hFCGRT promoter in Caco-2 and HSkMEC cells to a level that was not significantly different from that of the promoterless luciferase plasmid pGL3-basic, while in Lu106 and THP-1 cells the activity of the promoter was decreased to 23% and 29%, respectively, compared to the wild-type promoter activity.The pGL3-711(mAP1) construct carrying mutation in the AP-1 motif demonstrated drastic reduction in the ability to drive the reporter activity , suggestFCGRT promoter is presented in Functional analysis of the CF1/YY1 binding sites within the hFCGRT promoter activity to about half in these cell lines. The CF1 double mutant [pGL3-711(mCF1-1+2) construct] did not cause a more drastic reduction in the promoter activity, suggesting the presence of a potential interaction between nuclear factors that bind to these cis elements. In contrast, mutation of the CF1/YY1 site at -586 resulted in a significant decrease in reporter activity in the THP-1 cell line, comparable to the activity of pGL3-basic, indicating that this CF1/YY1 site functions as a critical positive regulatory element of the hFCGRT promoter in THP-1 cells. On the other hand, mutation of the CF1/YY1 site at -357 and the CF1double mutant caused a very slight decrease of the promoter activity in this cell line, suggesting that the strong activation of the hFCGRT promoter in THP1 cells by the CF1 site at -586 is neutralized by the repressive effect of the CF1/YY1 motif at position -357.Mutation of the CF1/YY1 binding site at position -586 [pGL3-711(mCF1-1) construct] reduced the promoter activity by about 60% in Caco-2 and Lu 106 cells, and by 47% in HSkMEC cells. Mutation of the CF1/YY1 motif at position -357 [pGL3-711 construct], with the C/EBPβ site at -233 left intact, or in the opposite situation when the mutation was introduced in the C/EBPβ site at -233 [pGL3-711(mC/EBPβ-2) construct] and the C/EBPβ site at -497 was left unchanged. Mutations in both C/EBPβ motifs [pGL3-711(mC/EBPβ-1+2) construct] resulted in a decreased activity of the hFCGRT promoter by almost 50% in THP-1 treated with PMA+LPS  is regulated remains unknown. Previous publications presenting the exon-intron structure and sequence of the human FCGRT gene [FCGRT expression at the level of transcription. Deletion of the 434 bp segment of the hFCGRT promoter revealed that the sequence from nt -660 to -233 is essential for the basal promoter function [FCGRT promoter abolished almost all of the promoter activity. The potential binding sites for the Sp family as well as YY1, AP-1, and C/EBPβ factors were predicted within this region based on computer analysis. The aim of this study was to examine whether these potential regulatory elements are involved in hFCGRT promoter activation in human epithelial, endothelial, and differentiated THP-1 cell lines, and to identify transcription factors that specifically bind to these motifs.A substantial body of research exists on the structure, function and physiological significance of the hFcRn receptor. However, the mechanism by which the expression of the human GRT gene , as wellGRT gene , served function . RemovalFCGRT promoter, act interdependently and functionally cooperate in the regulation of constitutive transcription of the human FCGRT gene in epithelial, endothelial, and differentiated THP-1 cells. However, their individual contribution to the promoter activity is not equivalent. The Sp1-binding site at -313 and the AP-1 site at -276 are critical for the activity of the hFCGRT promoter in epithelial and endothelial cells. Moreover, the CF1/YY1 site at -586 in differentiated THP-1 cells plays an essential role in transcriptional activity of the hFCGRT. Mutation of the Sp1 site at -313, the AP-1 motif at -276 or the CF1/YY1 site at -586 (in differentiated THP-1 cells) results in a dramatic loss of promoter activity, strongly suggesting cooperative interactions between nuclear factors that bind to these cis-elements, so that the disruption of binding of any factor leads to a strong destabilization of the transcriptional machinery. It seems likely that this is an important step required to initiate the transcription machinery. These interactions may be necessary to open the nucleosomal structure facilitating transcription. It is possible that they play a role in the recruitment of transcription initiation complex onto the core promoter. This possibility cannot be excluded, considering the fact that the hFCGRT promoter does not contain a typical TATA sequence and Inr element. Reports concerning interactions between Sp1 and TBP or TAF 110 [FCGRT promoter, mutation in which caused only a modest decrease in the promoter activity, are also likely to be operative in the regulation of the human FCGRT gene. These sites may have an effect on the function of the key transcriptional activators via recruitment of the transcriptional coactivators or/and by a competive mechanism. As it is shown in The results obtained from site-directed mutagenesis in transient transfection experiments Figs –10 and t TAF 110 , the abi TAF 110  also supFCGRT gene in THP-1 and Caco-2 cell lines through binding NF-κB transcription factors to NF-κB specific binding sites located in introns 2 and 4 [via JAK-STAT signaling [FCGRT expression under stimulated conditions [FCGRT promoter in epithelial and endothelial cells  and drove promoter activity in intestinal cell lines. The Sp1 motif in the mouse Fcgrt promoter is critical in regulating the basal promoter function [FCGRT promoter, were able to specifically interact with their corresponding TFs  suggesting a possible involvement of these transcription factors in the regulation of the basal expression of the human FCGRT gene , Lu 106 (D and D1), HUVEC (E and E1) cells were incubated with labeled probes in the absence of competitor  or in the presence of a 100-fold molar excess of competitor: Sp1-1+2 (WT)–unlabeled wild-type probe Sp1-1+2 ; Sp1-3(WT)–unlabeled wild-type probe Sp1-3 ; mSp1-1+2 –unlabeled probe Sp1-1+2 containing mutation in the Sp1 sequence at positions -641 and -635 ; mSp1-2 –unlabeled probe Sp1-1+2 containing mutation in the Sp1 sequence at position -635, ; mSp1-3 –unlabeled probe Sp1-3 containing mutation in the Sp1 sequence at position -313 . Labeled probe Sp1-1+2(WT) alone ; labeled probe Sp1-3(WT) alone . DNA-protein complexes were resolved on 5% non-denaturing polyacrylamide gels and analyzed in a phosphor imager (Typhoon 8600) using ImageQuant software (Molecular Dynamics). Positions of the specific DNA-protein complexes are indicated by arrows.(TIF)Click here for additional data file.S2 Fig32P-labeled wild-type probe: Sp1-1+2(WT) (C–E), Sp1-3(WT) (C1–E1). Labeled probe alone ; labeled probe incubated with nuclear extract in the absence of antibodies , in the presence of rabbit polyclonal antibodies: anti-Sp1 , anti-Sp2 , anti-Sp3 , anti-AP-2 , normal rabbit IgG . Shifted bands are indicated with an asterisk. Results were analyzed by a phosphor imager.Supershift experiments were performed by preincubating the nuclear extract from Caco-2 (C and C1), Lu 106 (D and D1) and HUVEC (E and E1) cells on ice for 1 h with 2 μg of rabbit polyclonal antibodies specific for Sp family transcription factors or normal rabbit IgG prior to the addition of (TIF)Click here for additional data file.S3 Fig32P-labeled probe–AP1(WT) with the nuclear extract from Caco-2 , Lu 106  and HUVEC cells . Competition experiments were performed in the presence of a 100-fold molar excess of the unlabeled probe AP1(WT)  or in the presence of its mutated version in which the putative AP-1 binding site at position -276 was mutagenized–mAP1 . Supershift experiments were performed by preincubating the nuclear extracts with rabbit polyclonal anti-c-Fos antibody , anti-c-Jun antibody , normal rabbit IgG , prior to the addition of 32P-labeled probe AP1(WT). Labeled probe AP1(WT) alone ; labeled probe AP1(WT) incubated with nuclear extract in the absence of antibodies . Position of the shifted complex is marked with an asterisk. Results were analyzed by a phosphor imager.Arrows indicate specific complex that formed during incubation of the wild-type AP1 (TIF)Click here for additional data file.S4 Fig32P-labeled wild-type probes were incubated with nuclear extracts from Caco-2 , Lu 106  and HUVEC cells  in the absence of competitor  or in the presence of a 100-fold molar excess of competitor: CF1-1(WT)–unlabeled wild type probe CF1-1 ; CF1-2 (WT)–unlabeled wild type probe CF1-2 ; mCF1-1 –probe CF1-1 with mutation in the CF1 element at position -586 ; mCF1-2 –probe CF1-2 containing mutation in the CF1 site at position -357 . Supershift experiments were performed by preincubating the nuclear extract with rabbit polyclonal anti-YY1 antibody , anti-Sp1 antibody , normal rabbit IgG , prior to the addition of 32P-labeled wild-type probe: CF1-1(WT) (C1–E1); CF1-2(WT) (F1–H1). Labeled probes incubated with nuclear extract in the absence of antibodies . Labeled probe CF1-1(WT) alone ; labeled probe CF1-2(WT) alone . Arrows indicate specific DNA-protein complexes and asterisk indicates the supershifted complex. Results were analyzed by a phosphor imager.In EMSA, (TIF)Click here for additional data file.


Saccharomyces cerevisiae methylation marks at K4, K36, and K79 of histone H3 are associated with gene transcription. Although Set2-mediated H3K36 methylation is enriched throughout the coding region of active genes and prevents aberrant transcriptional initiation within coding sequences, it is not known if transcription of one locus impacts the methylation pattern of neighbouring areas and for how long H3K36 methylation is maintained after transcription termination. Our results demonstrate that H3K36 methylation is restricted to the transcribed sequence only and the modification does not spread to adjacent loci downstream from transcription termination site. We also show that H3K36 trimethylation mark persists in the locus for at least 60 minutes after transcription inhibition, suggesting a short epigenetic memory for recently occurred transcriptional activity. Our results indicate that both replication-dependent exchange of nucleosomes and the activity of histone demethylases Rph1, Jhd1 and Gis1 contribute to the turnover of H3K36 methylation upon shut-down of transcription.Post-translational modifications of core histones play an important role in the epigenetic regulation of chromatin dynamics and gene expression. In  Saccharomyces cerevisiae, histone H3 lysines 4, 36 and 79  are methylated by histone methyltransferases Set1, Set2 and Dot1, respectively [In eukaryotic cells, genomic DNA is packaged into a nucleoprotein structure known as chromatin. Nucleosome, a fundamental repeating unit of chromatin, consists of 146 base pairs of DNA wrapped around an octameric core composed of two molecules of each histone protein: H3, H4, H2A and H2B . One sucectively . Set2-meectively , 11. H3Kectively . H3K36meectively . Furtherectively .Saccharomyces cerevisiae—Rph1, Jhd1 and Gis1 have been associated with H3K36 demethylation [It was long thought that histone methylation is a static modification, however the identification of the first histone demethylase LSD1 (lysine-specific demethylase 1), revealed methylation to be reversible and dynamic epigenetic mark , 18. Rechylation –24.Although genome-wide mappings of histone modifications have confirmed a strong correlation between active transcription and H3K36me3, the dynamics and turnover mechanisms of this modification are not fully understood. For example, it is not clear whether an active transcription in one locus could influence the modification of H3K36 in neighbouring chromatin domains and what are the mechanisms restricting the spreading of H3K36me3. Also the dynamics and mechanisms of H3K36 demethylation after transcription repression are not entirely clear. To clarify the mechanisms regulating H3K36 methylation and demethylation in chromatin, we investigated the dynamics of H3K36 trimethylation in an inducible-repressible gene locus. This experimental system allows rapid shut-down of gene transcription and the turnover of H3K36me3 can be monitored in the absence of continuous transcriptional activity in the locus. We show that H3K36 methylation is brought to the gene in transcription-coupled manner and the modification does not spread outside of the actively transcribed locus. Also, we demonstrate that turnover of the H3K36 methylation mark is relatively slow taking more than 60 minutes after transcription termination. Our data suggests that both replication-dependent exchange of histones and passive demethylation of K36 by histone demethylases contribute to the erasure of H3K36 methylation mark upon shut-down of transcription.Saccharomyces cerevisiae strains were congenic with strain W303 and are given in GAL-VPS13-3kb-term (AKY212) strain contains the terminator sequence of FBA1 gene at 3220 bp downstream from the VPS13 start-codon [RPH1, JHD1 and GIS1 genes with hphMX, natMX6 and kanMX markers, respectively. These strains in turn were used to create the deletion mutant strain of all three demethylases (AKY975). The overall fitness of deletion strains was similar to wt, since the deletion mutants grew at the same rate as wt strain at different temperatures and carbon sources  or anti-histone H3 trimethyl-K36 (Abcam). Co-precipitated DNA was analysed by quantitative real-time PCR using ABI Prism 7900HT Fast Real-Time PCR System and LightCycler 480 Real-Time PCR System under standard conditions . Maxima SYBR Green/ROX qPCR master mix (Thermo Scientific) was used. PCRs were done with primer pairs covering the coding region of VPS13 and chromosome VI right arm telomere region for normalization. The VPS13 primers were specific for the sequences at 2.6, 3, 3.6 and 4 kb downstream from the start-codon of GAL-VPS13. The sequences of primers are listed in the Cells were grown overnight in yeast extract-peptone (YP) medium containing 2% glucose or 2% galactose as a carbon source. 15 ml of mid-log phase cells (200 ml for Set2 detection experiments) were fixed in 1% formaldehyde for overnight galactose and glucose timepoint samples for ChIP assays. Transcription repression was carried out by shifting overnight galactose-grown cells into medium containing 2% glucose. Samples were taken at different time points  after shift to glucose and fixed for ChIP assay. For cell cycle arrest experiments, α-factor mating pheromone (GenScript) was used at the final concentration of 100 nM, and cell cycle status during the experiment was confirmed by flow cytometry analysis . ChIP asS. cerevisiae is relatively compact containing short genes and very little space between the ORFs. These features complicate the studies of transcription-dependent dynamics of histone modifications in yeast, as the chromatin modification pattern in any particular locus is likely to be influenced by the activity of several neighbouring genes. To overcome these difficulties, we used a 9.4 kb long GAL-VPS13 gene with transcriptional terminator sequence inserted at 3 kb downstream of the start site . As expected, the nucleosomal structure in GAL-VPS13 locus was recovered within minutes after transcriptional termination Click here for additional data file.S2 Fig(EPS)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


HP1 family are elementary components of heterochromatin and are generally assumed to play a central role in the creation of a rigid, densely packed heterochromatic network that is inaccessible to the transcription machinery. Here, we demonstrate that the fission yeast HP1 protein Swi6 exists as a single highly dynamic population that rapidly exchanges in cis and in trans between different heterochromatic regions. Binding to methylated H3K9 or to heterochromatic RNA decelerates Swi6 mobility. We further show that Swi6 is largely dispensable to the maintenance of heterochromatin domains. In the absence of Swi6, H3K9 methylation levels are maintained by a mechanism that depends on polymeric self‐association properties of Tas3, a subunit of the RNA‐induced transcriptional silencing complex. Our results disclose a surprising role for Swi6 dimerization in demarcating constitutive heterochromatin from neighboring euchromatin. Thus, rather than promoting maintenance and spreading of heterochromatin, Swi6 appears to limit these processes and appropriately confine heterochromatin.Proteins of the conserved  The basic unit of chromatin is the nucleosome, which consists of two copies each of the histone proteins H2A, H2B, H3, and H4. The flexible N‐termini of histone proteins are subject to various posttranslational modifications associated with different types of chromatin. Originally defined cytologically as chromosome regions that do not undergo post‐mitotic decondensation but remain condensed during interphase, a distinct type of chromatin referred to as heterochromatin is generally characterized by histone hypoacetylation and specific methylation of lysine 9 of the histone H3 tail (H3K9me). This mark is a binding site for proteins containing a so‐called chromodomain (CD), such as proteins of the heterochromatin protein 1 (HP1) family that recognize and bind methylated H3K9 via their CDs  in C. elegans showed only little variation ‐mediated assembly and silencing of heterochromatin  of 535 ms  = a(1 − exp(−bx))) with an R‐squared value of 0.9964  resulted in a good fit to a two‐component model with t1/2 values of the individual components in a physiological range  experiments, a fluorescent region is irreversibly bleached by a short laser pulse and the recovery of the fluorescence signal measured over time , we investigated percentage recovery after photobleaching. FM is the proportion of bleached proteins replaced by unbleached proteins during the experiment. Thus, FM at a given locus can be determined by dividing fluorescence intensity at the end of the time lapse (F∞) by fluorescence intensity before the bleaching event . If a second, static or low‐mobility population of Swi6 existed, FM should be less than 1. However, several experimental artifacts can bias estimation of this ratio and need to be taken into account for a precise determination of FM. First, and consistent with a previous report, we observed that heterochromatin domains are highly mobile in S. pombe . The KR25A mutation in the hinge region of Swi6 does not affect H3K9 binding but abolishes RNA binding and nuclear import of Swi6. Therefore, fusion of an SV40 nuclear localization signal (NLS) to the N‐terminus of the Swi6‐KR25A is required  with ions Fig A, as welells Fig B, levelsells Fig E and F. ells Fig A and D.per se in blocking the propagation of H3K9 methylation. Therefore, we assessed by ChIP–PCR H3K9 methylation at the IRC1R boundary in cells that express Swi6 bearing single point mutations in either the CSD (swi6L315E), which abolish dimerization of Swi6 , which abolish H3K9me2 binding   in wild‐type and swi6Δ cells argues against the deposition of H3K9me2 through the canonical RNAi‐mediated heterochromatin assembly pathway  that can undergo polymeric self‐association in vitro  only very few Swi6 molecules are engaged in heterochromatin spreading by oligomerization at telomeres, and (iii) Swi6 is dispensable to the expansion of centromeric heterochromatin. Rather, it appears to be involved in the demarcation of centromeric heterochromatin from neighboring euchromatin by a mechanism that remains to be fully elucidated. We discuss below the implications of these findings for the mechanisms of heterochromatin formation and repression in fission yeast.In this study, we have reanalyzed the dynamics of the ions Fig , we founin vivo experiments using Swi6 overexpression to force the expansion of heterochromatin . Antibodies for Western blotting were used at the following concentrations: Swi6 , tubulin , 491‐nm and 561‐nm laser lines , a Semrock Di01‐T488/568 dichroic, and Semrock FF01‐525/40‐25 and FF01‐440/521/607/700‐25 emission filters. All devices were piloted with the software Visiview . For FRAP experiments, a VisiFRAP module (Visitron), a 473‐nm laser line and a chroma Z405/473rpc‐xt dichroic were installed on the setup. The bleach region was a diffraction‐limited spot, and the bleach time was 20 ms.For each FRAP experiment, a time series of 120 images of a fixed confocal plane was acquired every 60 ms, while the bleach pulse was aimed and triggered manually by mouse click. Additionally, in order to calculate the recovery percentage of the bleached foci, a stack was taken before and after the time series acquisition. All images were acquired at 30°C. Cells were grown in YES medium to exponential phase and imaged on a slide harboring an agarose patch containing YES medium with 3% glucose.et al, et al, et al, Exponentially growing cells were synchronized in G1/S phase by a 4‐h treatment with 15 mM hydroxyurea and released into the cell cycle after a wash with YES medium. The cells were imaged in a Ludin Chamber with a lectin‐coated glass slide . FRAP experiments were performed for approximately 3 h after release, each time‐point representing the recovery curve of a locus from a different cell. All images were acquired at 30°C. M phase was not included in the FRAP analysis as Swi6 becomes dispersed  laser and a Plan‐Apochromat 63×/1.40 Oil DIC M27 objective. The devices were piloted with ZEN Black 2010 software.et al, t1/2), we performed an exponential one‐component curve fit based on the formula y(x) = a(1 − exp(−bx)). The boxplots of the t1/2 values were made in RStudio.The acquired images were analyzed using custom script in the open‐source software Fiji (Schindelin y(x) = a(1 − exp(−bx)), while the two‐component fits were based on y(x) = a(1 − exp(−bx)) + c(1 − exp(−dx)).To obtain mean recovery curves of the different conditions, we normalized each individual series of intensities to the mean of its last 15 time‐points post‐recovery. Of these normalized intensity series, aligned to the bleaching time‐point, the means were calculated and loaded into the curve fitting toolbox of Matlab . The one‐component fits were based on the formula et al, H3K9me2 ChIP experiments were performed with an H3K9me2‐specific mouse monoclonal antibody from Wako . Anti‐H3K9me antibody was used at 1 μg per mg of whole‐cell extract (WCE). Cells were processed for ChIP analysis as previously described , which include the ChIP‐seq data of the RS designed and carried out most of the experiments. RK‐S performed ChIP, generated libraries for next‐generation sequencing, and analyzed ChIP‐seq. CK prepared RNA for sRNA deep sequencing. MAK and LG assisted with data analysis and establishment of the methods. MB obtained funding, designed experiments, and oversaw the study. MB and RS wrote the manuscript.The authors declare that they have no conflict of interest.AppendixClick here for additional data file.Expanded View Figures PDFClick here for additional data file.Movie EV1Click here for additional data file.Review Process FileClick here for additional data file.


The late phase of adenovirus gene expression is controlled by proteins made in the intermediate phase, including L4 proteins of 22,000- and 33,000-Da apparent molecular mass (L4-22K and -33K proteins) that are expressed initially from the L4 promoter (L4P). The L4P is activated by a combination of viral proteins and cellular p53 and is ultimately inhibited again by its own products. Here, we have examined the L4P of human adenovirus type 5 in detail and have defined its transcription start site, which our data suggest is positioned by a weak TATA box. Rather than contributing positively to promoter activity, a putative initiator element at the transcription start site acts as a target for negative regulation imposed on the L4P by cellular TFII-I. We show that this TFII-I inhibition is relieved by one of the previously defined viral activators of the L4P, the E4 Orf3 protein, which alters the pool of TFII-I in the cell. We also explore further the negative regulation of the L4P by its products and show that the L4-33K protein is more significant in this process than L4-22K. It is the combined actions of positive and negative factors that lead to the transient activation of the L4P at the onset of the late phase of adenovirus gene expression.IMPORTANCE The adenovirus replication cycle proceeds through multiple phases of gene expression in which a key step is the activation of late-phase gene expression to produce proteins from which progeny particles can be formed. Working with human adenovirus type 5, we showed previously that two proteins expressed from the L4 region of the viral genome perform essential roles in moving the infection on into the late phase; these two proteins are produced by the action of a dedicated promoter, the L4P, and without them the infection does not proceed successfully to progeny generation. In this new work, we delineate further aspects of L4P activity and regulation. Understanding how the L4P works, and how it contributes to activation of the late phase of infection, is important to our understanding of natural infections by the virus, in which late gene expression can fail to occur, allowing the virus to persist. During a lytic infection, human adenovirus type 5  gene expression occurs through a coordinated cascade that begins with expression of early genes and progresses through an intermediate phase to full activation of the virus late genes. The majority of these late genes are part of the major late transcription unit (MLTU), which is divided into five gene blocks, termed L1 to L5, each of which has a single polyadenylation site. The MLTU is controlled by the major late promoter (MLP) and is initially transcribed as a single pre-mRNA that undergoes extensive alternative splicing and polyadenylation to generate the full repertoire of late mRNAs  was resolved by the discovery of a novel promoter termed the L4 promoter (L4P) situated within the L4-100K open reading frame, which drives initial expression of the L4-22K and L4-33K genes . DeletioBoth viral and cellular proteins have previously been identified as regulators of the L4P. Exogenous expression of the Ad5 E1A, IVa2, and E4 Orf3 proteins was shown to induce L4P activity in luciferase reporter plasmid assays . The celin vitro studies that demonstrated its ability to bind the initiator element (Inr) of promoters and to support basal transcription  stress, leading to its nuclear translocation , 26. TFIIn this study, we have further characterized the nature of the L4P and its regulation by viral and cellular factors. Having identified the L4P 5′ transcription start site (TSS) by 5′ rapid amplification of cDNA ends (RACE), we observed a potential Inr element at the site. However, mutational analysis showed that although this Inr element bound TFII-I, it was inhibitory for the L4P. The viral L4P activator, E4 Orf3, was also found to work via this Inr element, correlating with its ability to cause changes in TFII-I. Finally, we found that L4-33K, rather than L4-22K, is the more potent negative feedback regulator of the L4P.wt300 or the E4 Orf3 mutant inOrf3 . Western blot protein detection used the following antibodies at the indicated dilutions: 1:10,000 mouse anti-p53 , 1:10,000 rabbit anti-Ad late proteins (AdJLB1) (p53 knockdown was achieved as described previously  using va(AdJLB1) , 1:500 r(AdJLB1) , 1:25,002 in Dulbecco's modified Eagle medium (DMEM) supplemented with 10% fetal calf serum (FCS). All cells were seeded at the appropriate density 24 h prior to the respective procedure. Plasmid and virus DNA transfections were carried out using Transit-LT1 (Mirus) according to the manufacturer's instructions at a ratio of 2 μl reagent per μg of DNA. Where appropriate, DNA transfections were standardized within an experiment to a constant amount of DNA per well using empty vector. siRNA transfections were performed using Lipofectamine 2000 (Invitrogen) according to the manufacturer's instructions, using a ratio of 1 μl reagent per 25 pmol siRNA to achieve a 50 nM final siRNA concentration.All cells were maintained at 37°C, 5% COLuciferase reporter assays were performed essentially as previously described . BrieflyWhole-cell lysates were harvested from 24-well cultures in 1× sample buffer and boiled for 10 min. Typically, 5 to 10% of the sample was separated by SDS-PAGE. Proteins were transferred onto Hybond-ECL nitrocellulose membranes , and Western blot analyses were performed using HRP-conjugated secondary antibodies and SuperSignal West Femto Maximum Sensitivity chemiluminescence reagent (Thermo Scientific) as previously described .TC) method, according to the experimental requirements. Primers were used at a standard final concentration of 200 nM, and all primer sets were validated for efficiency and specificity using standard curve and melting curve analyses, respectively. For L4-100K and -22K mRNAs, the primers were the following Ad5 genome positions : forward  and reverse . For L4-100K, -33K, and -22K, they were as follows: forward  and reverse . For LacZ, they were as follows: 5′-GAAAGCTGGCTACAGGAAG and 5′-GCAGCAACGACGTCA. β-Actin primers were taken from reference Total RNA was harvested from cells using a GenElute Mammalian Total RNA Miniprep kit (Sigma). RNA was first treated with DNase I (Promega), and then, 500 ng of DNA-free RNA was subjected to reverse transcription (RT) using the GoScript Reverse Transcription system (Promega) with oligo(dT) or random hexamer primers according to the manufacturer's instructions. Typically, 25 to 50 ng of cDNA was used for quantitative-PCR (qPCR) amplification analysis with Brilliant III Ultrafast SYBR green Mastermix (Agilent Technologies) on an MX3005P thermocycler (Stratagene) using universal cycling conditions. The manufacturer's software was used for quantitation of cDNA, either by absolute copy number analysis with a standard curve or by the relative cycle threshold quantitation  according to the manufacturer's instructions. Essentially, 1 μg total RNA was treated with calf intestine alkaline phosphatase to remove the 5′ phosphate group of RNA molecules lacking a 5′ cap. The 5′ cap of the mRNA was subsequently removed through the addition of tobacco acid pyrophosphatase, thus exposing a 5′ phosphate group to which an RNA adaptor was ligated using T4 RNA ligase. Reverse transcription was then performed on the ligated RNA using random hexamer primers and Moloney murine leukemia virus (M-MLV) reverse transcriptase. cDNA was subjected to nested PCR using two forward primers complementary to the 5′ adaptor sequence and two reverse primers complementary to the shared L4-22K and L4-33K mRNA sequence [5′ position (length)]: 26782 (24 nt) and 26530 (20 nt). PCRs were performed with GoTaq Hot Start Polymerase (Promega) using the following cycling conditions: 94°C for 1 min; 35 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 30 s; and a final extension of 72°C for 7 min. Selected PCR products were excised from the agarose gel, purified using the GeneJet gel extraction kit (Thermo Scientific), and cloned into the pGEM-T Easy vector (Promega), and individual clones were subjected to DNA-sequencing analysis.TC value of immunoprecipitated DNA with that of an aliquot of the total input DNA.Chromatin immunoprecipitations were performed as previously described , except Previous studies found that the crucial activating sequences of the L4P lie within nucleotides 25887 to 26125 of the Ad5 genome . HoweverOur previous studies to determine the regulatory sequences of the L4P responsive to p53 focused on the region 25887 to 26098 , based oWe previously observed that the cotransfected adenovirus genome was a more potent inducer of L4P 25887-to-26098 activity than the cocktail of activators , and thein silico  defined by Morris et al.  Fig. 3AFig. 3A. n silico , 37. A sn silico , and a wn silico  39–41);–41;in siBoth the location of the putative Inr sequence at the L4P TSS and its high level of similarity to the consensus for such elements suggested that it might be functionally significant. To investigate this, we mutated the predicted Inr sequence within the 25887-to-26125 L4P reporter construct  and B. TTo confirm this effect, we used an alternative system to measure the basal activity of the Inr mutant L4P. The pA-22KFLAG plasmid contains Ad5 genomic sequence from nucleotide 25887 through the L4P TSS and the complete L4-22K coding region, concluding with an added C-terminal FLAG epitope cDNA sequence , and so in silico analysis  element within the L4P whose activity within the promoter was repressive rather than activating. In common with other Inr elements, the L4P Inr mediated binding of the cellular factor TFII-I to the promoter. The previously defined the viral L4P activator, E4 Orf3, was found also to work via the Inr element, its positive effect correlating with its ability to cause a change in TFII-I. Finally, we reexamined negative-feedback regulation of the L4P and found that L4-33K is the principal effector of this control.The early understanding of eukaryotic transcription focused on the idea of a fixed site of initiation that was associated with an upstream TATA box, but it is now clear that this model fits only a minority of promoters. Constitutively active promoters more typically initiate over a broad region, while even among promoters that have a defined TSS, only around 20% have a recognizable TATA box . A numbein silico review of the L4P, the most prominent potential core promoter feature was a putative Inr element at the TSS. However, the start sites we mapped did not correspond to the typical position for promoters in which the TSS is fixed by a functional Inr element. In such promoters, initiation normally occurs on the almost invariant A rather than on upstream pyrimidines, as in the L4P, although the TSS position can vary around an Inr element depending on the strength and position of the Inr relative to the TATA box ; with the consensus RGWYV, this element is found at +28/32 to the TSS and is a secondary binding site for TFII-D  in the MLTU transcript . This inIt is possible that inhibitions of the L4P by TFII-I and L4-33K are related phenomena, though such a scenario is unlikely for two reasons. First, TFII-I is sufficient for inhibition of the L4P in the absence of L4-33K, as our luciferase reporter studies were performed in the absence of any L4 gene products. Second, we have demonstrated that L4-33K accumulates only once activation of the L4P is well under way, suggesting that by this time repression of the L4P by TFII-I has been efficiently relieved by E4 Orf3. However, it is possible that L4-33K is required to recruit TFII-I back onto the L4P at later times of infection. Further studies would be needed to explore this possibility and to test directly the effects of these regulators on the L4P in the context of virus infection.In conclusion, our new data shed further light on the regulation of the activity of the Ad5 L4P during the intermediate phase of the infectious cycle that signifies the transition from early to late patterns of gene expression. The present understanding of the activity of the L4P can be summarized as follows. A combination of viral and cellular factors exert both positive and negative regulation of the promoter, leading to a brief transient wave of activity that provides principally the L4-22K protein; this protein has been shown to act on the MLP and on MLTU RNA processing , 12, 15.