Matrix attachment regions (MAR) generally act as epigenetic regulatory sequences that increase gene expression, and they were proposed to partition chromosomes into loop-forming domains. However, their molecular mode of action remains poorly understood. Here, we assessed the possible contribution of the AT-rich core and adjacent transcription factor binding motifs to the transcription augmenting and anti-silencing effects of human MAR 1–68. Either flanking sequences together with the AT-rich core were required to obtain the full MAR effects. Shortened MAR derivatives retaining full MAR activity were constructed from combinations of the AT-rich sequence and multimerized transcription factor binding motifs, implying that both transcription factors and the AT-rich microsatellite sequence are required to mediate the MAR effect. Genomic analysis indicated that MAR AT-rich cores may be depleted of histones and enriched in RNA polymerase II, providing a molecular interpretation of their chromatin domain insulator and transcriptional augmentation activities. In mammalian cells, gene expression is tightly regulated but flexible. This flexibility stems from alterations in chromatin structure that allow gene expression to be modified in response to cellular requirements or extra-cellular signals The discovery that chromatin may be segregated into topologically constrained domains separated by genetic boundary elements such as scaffold or matrix attachment region (MAR) Although the function of MARs appears to be evolutionary conserved, attempts to dissect such elements and ascribe functions at the primary sequence level have generally been unsuccessful. MARs typically contain AT-rich elements that consist of regions of alternating A and T several hundred bases in length, or that contain dispersed short AT-rich patches that have a strong potential for base un-pairing when subjected to superhelical strain A constraint to the usage of MAR elements remains their size, sometimes of several kb, which limits their use, for instance in gene or cell therapy vectors. Defining the elements essential for transcription augmentation and anti-silencing may be of interest, for instance to allow for shorter constructs to be generated. In this study, we therefore attempted to identify functional elements of MARs and to assess their molecular action on chromatin structure. Our results imply that the MAR transcriptional augmentation and anti-silencing activities result from the combination of AT-rich sequences that may be depleted in histones but enriched in RNA-polymerase II, as well as from transcription activating protein binding sites. These results provide a molecular explanation for the epigenetic insulator and transcriptional augmentation activities of MARs.Potent MAR elements were previously identified by scanning the human genome using the SMARScan MAR-prediction program, yielding DNA elements that could potently enhance transgene expression The effect of one of the most potent MAR elements, namely human MAR 1–68, was assessed after insertion upstream of a GFP expression cassette . Stable Previous work with MAR 1–68 indicated that it acts in part to increase the number of transgene copies that stably integrate into the cell genome n microsatellite, but it was devoid of any such binding motif. To assess whether functional properties of MAR 1–68 may be ascribed to these sequences, the full length element was dissected into smaller fragments that were inserted in the MAR-devoid expression vector. The AT-rich core as well as the full-length 5′ flanking region were found to be the most potent among the three MAR 1–68 portions in mediating the anti-silencing and increased transcription effects. These two MAR fragments were of nearly equal strength as that of the full-length MAR 1–68 in terms of the anti-silencing effect, reducing the proportion of non-expressing cells to 25–30% of the total polyclonal cell population, whereas inclusion of non-MAR control sequences had little effect  and the 3′  flanking regions of the MAR 1–68 were amplified using primers listed in Supplementary The AT-rich core region of another human MAR, namely MAR X-29, was amplified using primers listed in Supplementary As negative controls, the MAR fragments were replaced by DNA sequences that encode a part of the Utrophin and/or luciferase genes. The control DNA fragments of 240 to 1652 bp in length were generated by PCR, using luciferase cDNA as template and primers listed in Supplementary Oligonucleotides containing putative binding sites of TFs were designed to avoid the formation of inverted repeats after oligomerization by ligation and cleavage by BamHI and BglII  for GFP fluorescence assays. GFP cytofluorometric analyses were acquired on a FACScalibur flow cytometer (Becton and Dickinson). 100,000 events were analyzed using the GFP (FL-1) channel with setting at 240 V and acquired data were analyzed using the WinMDI 2.8 software. Selected cells were sorted by flow cytometry using the FACSAriaII cell sorter (Becton and Dickinson) in order to obtain 4 sub-populations according to the following criteria: no, low, medium or very high GFP expression. After sorting, 1 million cells of each sub-population were expanded in T-25 tissue culture flasks containing DMEM-F12 complete medium with 500 µg/ml geneticin until confluency.BCtB/EACtA, whereby E corresponds to the PCR efficiency estimated by the LinReg Method and CtA and CtB represent the cycle thresholds for the gene of interest (GFP) or the endogenous reference gene (GAPDH), respectively. The data are representative of three to four independent transfection experiments, each performed in triplicate.DNA was isolated from FACS-sorted cells using the DNeasy Blood & Tissue Kit (Qiagen) following the manufacturer’s instructions. 6 ng of genomic DNA was analyzed by quantitative PCR to determine the copy number of the GFP transgene integrated in the genome of the CHO cells. Analyses were performed in the LightCycler® 480 (Roche), using the Light Cycler SYBR Green Master MIX (2X) and 0.4 µM  of forward and reverse primers, in a final volume of 15 µl. The GFP and GAPDH primers sets used for quantitative DNA PCR amplifications are shown in Supplementary 6 transfected cells using the RNAeasy Kit (QIAGEN) following the manufacturer’s instructions. 1 µg of total RNA was reverse-transcribed with oligo (dT) primers, using First Strand cDNA Synthesis Kit  according to the manufacturer’s instructions. Quantitative PCR was performed with primers specific to GFP and eukaryotic elongation factor 1 α1 (eEFIA1) genes, on a Light Cycler 480 system (Roche) using Roche LightCycler® 480 SYBR Green Master MIX. The GFP and eEFIA primers used for quantitative PCR amplification are shown in Supplementary Total RNA was prepared from approximately 5×10. Correlation analyses of ChIP-Seq tags and MAR predicted locations were performed using the ChIP-Cor tool available on the ChIP-Seq Analysis Server of the Swiss Institute of Bioinformatics . Cumulative ChIP-Seq tag counts were determined over the collection of 1683 human MARs for the genomic regions +/−5 kb from the central positions of the AT rich core of MARs. Tags were counted in consecutive windows of 100 bp and the fold change over the genome-wide average tag count was calculated for each window position. As the MAR AT-rich cores have low complexity sequences with generally lower tag counts, further normalization was required using non-precipitated data set. Normalization over the non-precipitated set was calculated as a fold change for each window position over corrected tag count for the non-precipitated MAR ChIP-Seq profile. Correction was taking into account the global number of tags obtained in the two experiments . ChIP-Seq profiles were obtained for the following histone variants and histone modifications: H2AZ variant, H3K4me1, H3K4me2, H3K4me3, H3K27me1, H3K27me2, H3K27me3, H3K36me1 and H3K36me3. Profiles were in addition obtained for the RNAPol II, and for transcription factors: CTCF and STAT1 (stimulated and non-stimulated cells). Similar bioinformatics tools from the ChIP-Seq Analysis Server of the Swiss Institute of Bioinformatics and normalization method were used to correlate ∼25000 RefSeq transcriptional start sites with histone modifications.Positions of the MAR elements within the human genome were determined using the SMARscan I software Figure S1GFP transgene expression is related to the transgene copy number. CHO-DG44 were stably co-transfected with the constructs containing the full-length MAR 1–68 or the spacer control DNA and with a plasmid encoding an antibiotic resistance gene. The polyclonal cell pools obtained after 1 month of antibiotic selection post-transfection were subjected to cytofluorometry analysis and cell sorting. The cells were sorted into 4 populations according to the levels of GFP fluorescence, as illustrated in panel (A), and they were subsequently expanded for analysis of the relative GFP transgene copy number, illustrated as described in the legend to (PDF)Click here for additional data file.Figure S2GFP mRNA levels are related to the transgene copy number. mRNA was isolated from the cells of Suppl. (PDF)Click here for additional data file.Figure S3Effect of negative control DNA sequences on the occurence of silent and high expressor cells. Spacer DNA of various lengths (3.6 kb to 200 bp), consisting of part of the utrophin or luciferase coding sequences, were used to replace the full-length MAR 1–68 or its deletions derivatives. The proportion of silent and high-expressor cells were determined and displayed as described in the legend to (PDF)Click here for additional data file.Figure S4Effect of transcription factor DNA binding motifs on the occurence of silent and high expressor cells. Oligonucleotides corresponding to DNA sequence motifs predicted to act as binding sites for the SATB1, Hox, Gsh, Fast-1 and CEBP transcription factors by the MatInspector software were mixed and inserted randomly downstream of the extended AT-rich core and upstream of the SV40 promoter of the GFP expression vector depicted in (PDF)Click here for additional data file.Figure S5Effect of negative control DNA sequences on the average GFP fluorescence and transgene copy number. Spacer DNA of various lengths (3.6 kb to 200 bp), consisting of part of the utrophin or luciferase coding sequences, were used to replace the full-length MAR 1–68 or its derivatives. The average GFP fluorescence and transgene copy numbers were determined from polyclonal cell pools generated using the illustrated constructs as described in the legend to (PDF)Click here for additional data file.Figure S61683 predicted human MAR genomic locations were aligned using the central positions of their AT rich cores. ChiP-Seq profiles were calculated over the MAR collection for association with the CTCF transcription factor, for DNAse hypersensitive sites and for the H2AZ histone variant. Tag counts were normalized globally and they are expressed as a fold change over the non-precipitated input DNA profile.(PDF)Click here for additional data file.Table S1Primer sets used to amplify portions of MAR 1–68 and MAR X-29.(PDF)Click here for additional data file.Table S2Primers sets used to amplify control cDNA sequences.(PDF)Click here for additional data file.Table S3Oligonucleotides containing transcription factor binding motifs.(PDF)Click here for additional data file.Table S4Quantitative PCR primer sets for GFP, GAPDH and eEFIA.(PDF)Click here for additional data file.


CC Chemokine Ligand 2 (CCL2) is a potent chemoattractant produced by macrophages and activated astrocytes during periods of inflammation within the central nervous system. Increased CCL2 expression is correlated with disease progression and severity, as observed in pulmonary tuberculosis, HCV-related liver disease, and HIV-associated dementia. The CCL2 distal promoter contains an A/G polymorphism at position -2578 and the homozygous -2578 G/G genotype is associated with increased CCL2 production and inflammation. However, the mechanisms that contribute to the phenotypic differences in CCL2 expression are poorly understood. We previously demonstrated that the -2578 G polymorphism creates a TALE homeodomain protein binding site (TALE binding site) for PREP1/PBX2 transcription factors. In this study, we identified the presence of an additional TALE binding site 22 bp upstream of the site created by the -2578 G polymorphism and demonstrated the synergistic effects of the two sites on the activation of the CCL2 promoter. Using chromatin immunoprecipitation (ChIP) assays, we demonstrated increased binding of the TALE proteins PREP1 and PBX2 to the -2578 G allele, and binding of IRF1 to both the A and G alleles. The presence of TALE binding sites that form inverted repeats within the -2578 G allele results in increased transcriptional activation of the CCL2 distal promoter while the presence of only the upstream TALE binding site within the -2578 A allele exerts repression of promoter activity. S. pneumoniaeChemokines are small proteins (8–10 kDa) that function as chemoattractants to facilitate the migration of immune cells during immune surveillance and periods of inflammation CCL2 is a three-exon gene located at 17q11.2-q12, which is regulated by distal and proximal promoters, each separated by approximately 2.2 kb of DNA in-vitro transcribed and translated interferon regulatory factor (IRF) 1 in gel shift assays Previously, we reported that following activation of human astrocytes with IL-1β, reporter constructs containing the distal promoter for CCL2 comprising the -2578 G allele had a greater fold induction as compared to the A construct in functional assays In this study, we modeled proinflammatory conditions by activating astrocytes with IL-1β that results in transcription of the CCL2 gene and secretion of the CCL2 protein as previously described. We demonstrated the binding of PREP1, PBX2, IRF1 and HoxA9 to the CCL2 distal promoter in both the -2578 A and G alleles via chromatin immunoprecipitation (ChIP) assays. Binding of the TALE proteins to the -2578 A allele was unexpected. However, TALE binding sites are often found in multiple copies, orientations, and spacing, or as inverted repeats Using ChIP analysis, we measured the interactions between the TALE proteins and the distal CCL2 promoter containing either the -2578 A allele or the -2578 G allele. A human astrocytoma cell line (U87-MG) was activated with IL-1β and transfected with firefly luciferase constructs containing a 929 bp fragment representing the distal CCL2 promoter with either the -2578 A allele or the -2578 G allele. In all experiments, U87-MG cells were activated with IL-1β and produced CCL2 (data not shown). ChIP analysis was followed by quantitative PCR qPCR; . The binSince the TALE proteins had a higher percentage of binding to the -2578 G allele, we examined the binding of PREP1 and PBX2 individually and together to the CCL2 distal promoter with the -2578 G allele. U87-MG cells were co-transfected with siRNA and a Firefly Luciferase construct containing a 929 bp fragment with the -2578 G allele. Western blot analyses were used to quantitate the efficiency of PREP1 (protein expression reduced 61% by PREP1-siRNA) and PBX2 (protein expression reduced 97% by PBX2-siRNA) silencing . ChIP waet al. demonstrated that the TALE binding sequence TGACAG is usually found in multiple copies with varying spacing, and they frequently form inverted repeats m or Gm) The observation that the -2578 A allele bound PREP1 and PBX2 suggested that the CCL2 distal promoter contains either a TALE site or another site that could bind these proteins. Site selection experiments performed by Shen Since HOXA9 protein has been shown to form complexes with PBX2 is was not surprising that mutation of the upstream TALE site significantly reduced the amount of CCL2 promoter DNA immunoprecipitated by HoxA9 antibody for both the -2578 A and -2578 G alleles  as was fFinally, immunoprecipitation of the distal CCL2 construct with the mutation in the upstream TALE site with IRF1 antibody significantly reduced the percentage of DNA precipitated for only the -2578 A allele . While tTo elucidate the effects of the upstream TALE site on transcriptional activity, U87-MG cells were transfected with firefly luciferase constructs containing the distal CCL2 promoter element (929 bp fragment) of either the -2578 A allele or the -2578 G allele. The cells were co-transfected with either PREP1 siRNA, PBX2 siRNA, a combination of PREP1 and PBX2 siRNAs, a non-targeting, control siRNA, or no siRNA. Transcriptinal activity of the -2578 A allele increased following silencing of PREP1 and PBX2 . In contm) was 2.2-fold higher than that of the -2578 A allele, supporting a role in the transcriptional repression of the distal promoter . Briefly, 20 ng of the distal promoter pGL4.11 vectors (described in plasmid production) were used as a template along with the following mutated nucleotide primers: Forward, The human astrocytoma cell line U87-MG was acquired from American Type Culture Collection ,  and were maintained in MEM with glutamine supplemented with 10% FBS, 0.1 mM nonessential amino acids (MEM NEAA), and 1 mM sodium pyruvate. In all experiments, U87-MG cells were activated for 3 hours with recombinant Human IL-1β (201-LB) obtained from R&D Systems  as described below.DNA Transfections were described previously Western blot analysis was performed as described previously 6 transfected (as described above) U87-MG cells were treated with 1% formaldehyde for 10 min at room temperature and neutralized with 1× glycine. Nuclei were isolated from IL-1β activated U87-MGs that had been transfected with either -2578G or -2578A containing vectors with and without the upstream mutation. Samples were sonicated to obtain 500 - 800 bp DNA fragments using the Branson sonicator for 13 12-s pulses at 45% amplitude with 1 min of incubation on ice between pulses. Approxamtely 106 cells were used per immunoprecipitation in a 50 µL volume and pre-cleared with 20 µL Dynabeads protein G (Invitrogen) for 16 hours at 4°C. Pre-cleared cell lysates were incubated with either 4 µg of anti-PREP1, anti-PBX2, anti-HoxA9, anti-IRF1 or mouse IgG  antibody (negative control) at 4°C for 6 hours. Lysates were then incubated with proteinase K at 62°C for 4 hours to reverse cross-linking. Lysates were then incubated at 95°C for 10 minutes to denature proteinase K and DNA was isolated using silica columns. Enriched DNA was quantified using real time quantitative PCR (qRT-PCR) by SYBR-Green (Qiagen) with the following primers to select for construct/insert specific DNA: Forward, 5′-AGGGCATCTTTTCTTAATAGAGCAGA-3, and Reverse, 5-CCTTTGCATATATCAGATAGTAAACAC-3′. Analysis of quantitative qRT-PCR data was analyzed using the percent input method. Percentage of total DNA precipitated was calculated by 100×2∧(Ctinput – Ctenriched). Input was determined from 1% of the cell lysate and IgG was used as a negative control.ChIP assays were performed as published previously with modifications using the Magna ChIP G Chromatin Immunoprecipitation kits (20–400) obtained from Millipore.Magna ChIP kit (Millipore). PREP1 (sc 6245X), PBX2 (sc 890X), and GAPDH (sc 47724) antibodies were obtained from Santa Cruz Biotechnologies . HoxA9 (ab33382-100) antibody was obtained from Abcam Inc., Cambridge, MA, USA. Antibodies for normal mouse IgG (12–371), Briefly, 8×10Luciferase assays using the pGL4.11 Firefly and pGL4.74 Renilla vectors were described previously For all experiments, descriptive statistics (mean and standard deviation) were calculated and compared among groups using parametric methods in PRISM statistical software package. The Student's two-sided t test was used to compare two groups . Analysi


Tracking of ancestral histone proteins over multiple generations of genomereplication in yeast reveals that old histones move along genes from 3′toward 5′ over time, and that maternal histones move up to around 400 bpduring genomic replication. Replicating chromatin involves disruption of histone-DNA contacts and subsequentreassembly of maternal histones on the new daughter genomes. In bulk, maternalhistones are randomly segregated to the two daughters, but little is known aboutthe fine details of this process: do maternal histones re-assemble at preferredlocations or close to their original loci? Here, we use a recently developedmethod for swapping epitope tags to measure the disposition of ancestral histoneH3 across the yeast genome over six generations. We find that ancestral H3 ispreferentially retained at the 5′ ends of most genes, with strongestretention at long, poorly transcribed genes. We recapitulate these observationswith a quantitative model in which the majority of maternal histones arereincorporated within 400 bp of their pre-replication locus during replication,with replication-independent replacement and transcription-related retrogradenucleosome movement shaping the resulting distributions of ancestral histones.We find a key role for Topoisomerase I in retrograde histone movement duringtranscription, and we find that loss of Chromatin Assembly Factor-1 affectsreplication-independent turnover. Together, these results show that specificloci are enriched for histone proteins first synthesized several generationsbeforehand, and that maternal histones re-associate close to their originallocations on daughter genomes after replication. Our findings further suggestthat accumulation of ancestral histones could play a role in shaping histonemodification patterns. It is widely believed that chromatin, the nucleoprotein packaged state ofeukaryotic genomes, can carry epigenetic information and thus transmit geneexpression patterns to replicating cells. However, the inheritance of genomicpackaging status is subject to mechanistic challenges that do not confront theinheritance of genomic DNA sequence. Most notably, histone proteins must atleast transiently dissociate from the maternal genome during replication, and itis unknown whether or not maternal proteins re-associate with daughter genomesnear the sequence they originally occupied on the maternal genome. Here, we usea novel method for tracking old proteins to determine where histone proteinsaccumulate after 1, 3, or 6 generations of growth in yeast. To our surprise,ancestral histones accumulate near the 5′ end of long, relatively inactivegenes. Using a mathematical model, we show that our results can be explained bythe combined effects of histone replacement, histone movement along genes from3′ towards 5′ ends, and histone spreading during replication. Ourresults show that old histones do move but stay relatively close to theiroriginal location (within around 400 base-pairs), which places importantconstraints on how chromatin could potentially carry epigenetic information. Ourfindings also suggest that accumulation of the ancestral histones that areinherited can influence histone modification patterns. In addition to the information encoded in DNA sequence, replicating cells can inheritepigenetic information, which refers to variable phenotypes that are heritablewithout an underlying change in DNA sequence. It is widely accepted that chromatin,the nucleoprotein packaging state of eukaryotic genomes, provides one potentialcarrier of epigenetic information. Although definitive proof that chromatin per secarries epigenetic information during replication exists in very few cases The idea that chromatin structure carries epigenetic information poses a centralmechanistic question—since chromosome replication involves dramaticperturbations to chromatin structure ranging from old histone displacement towidespread incorporation of newly synthesized histones, how can chromatin states bestably maintained? To understand the mechanism by which chromatin states could beinherited, it is necessary to understand the unique challenges posed by histoneprotein dynamics during replication Classic radioactive pulse-chase studies demonstrated that, in bulk, maternal histonessegregate equally to the two daughter cells To address these fundamental questions, we carried out a genetic pulse-chase withepitope-tagged histone H3 GAL-based systems for measuringreplication-independent histone dynamics To follow the movement of old histone proteins over multiple cell generations, weutilized a novel pulse-chase technique We used MNase-ChIP Overall, HA/T7 patterns are consistent at 3 and 6 generations, but the dynamic rangeof HA/T7 enrichment diminished from 3 to 6 generations .This isSPA2and BUD3, two genes which both exhibit high and low HA/T7ratios at their 5′ and 3′ ends, respectively , after release into a G2/Mcell cycle block, and at 1, 3, and 6 generations after release. Sequencing readswere mapped to the yeast genome, normalized for read count, and HA/T7 ratioswere computed genome-wide. These data correlated well with our microarray data,and we further validated these measurements by q-PCR at ectively .In previous work, we and others To better visualize these trends, we sorted genes by the extent of ancestral H3retention after 3 generations . RetentiWhat properties of short or highly transcribed genes might lead to loss ofancestral histones? Replication-independent histone replacement occurs mostrapidly over intergenic regions and over the coding regions of highlytranscribed genes Why do old histone proteins accumulate near the 5′ ends of genes? Weconsidered two alternative possibilities for classes of mechanisms causing thispattern. In the first mechanism, we reason that if histone proteins tend tomaintain their locations along the genome, the 5′ enrichment of oldhistones implies that old 3′ histones are evicted and replaced by newhistones during some phase of the cell cycle. However, previous measures ofturnover in G1- or G2/M-arrested yeast A second possible explanation for widespread 5′ accumulation of ancestralhistone proteins is that the histone proteins move from 3′ to 5′over genes over time. This could result from RNA polymerase passage, becausesome RNA polymerases pass histone octamers in a retrograde direction duringtranscription A key question we sought to address in this study is whether maternal histonesre-associate near their original positions after passage of the replicationfork. We reasoned that changes in HA/T7 patterns over the course of severalgenerations might provide insight into the effects of replication on nucleosomedynamics. HA/T7 patterns change dramatically between arrest and 1 generation ofrelease (with or without G2/M arrest) and then are very similar between 1 and 3generations, before the background of nonswitching cells starts to dominate theprofile at 6 generations . As expeWe asked whether these dynamic observations could be used to quantitatively ruleout specific models concerning the mechanisms for segregation of maternalhistones to daughter genomes. However, the resolution of this question iscomplicated by replication-independent processes we discuss above that canremove or shift ancestral histones, and that cannot be fully removedexperimentally . To understand the relationship between theseissues, we designed an analytical model that accounts for three processes thataffect H3 molecules in coding sequences  and thenrpb1-1inactivation on nucleosome positioning p = 9.6439e-19) correlatedwith transcription rate  than was observed , S13. WeOverall, the strong correlation between our model and the experimental datasupports the hypothesis that at least three dynamic processes affect nucleosomesand shape the landscape of ancestral histone retention and provide the firstquantitative estimate of maternal histone dynamics during replication.To further investigate the mechanism of 5′ accumulation, we asked whethergene-specific passback parameters were correlated with specific gene annotations [34],[37HHF2-HHT2). Thus, results with this strain must beinterpreted with extreme caution, as we do not know the effect of wild-type,untagged nucleosomes on the behavior of the epitope-tagged histones.To investigate this link experimentally, we examined whether mutations of the H4tail influenced ancestral histone H3 retention. In an H4K5,12R mutant thatcannot be acetylated on these two tail residues, the 5′-biased HA/T7 waspartially lost , consistNonetheless we present here results of mapping of HA and T7 3 generations afterrelease from the HA/T7 tag swap, since the H4 tail deletion has dramatic effectson global nucleosome dynamics , with loTOP1 deletion at longer genes , but this likely stems from the factthat replication timing correlates with replication-independent turnover SPA2 and BUD3(increased upon deletion of theCAF-1 subunit CAC1 (unpublished data). To further explore therole of CAF-1 in histone retention patterns, we deep sequenced HA and T7 tagsfrom cac1Δ yeast 3 generations after release , which plays a key role in replication-coupled histone depositionand BUD3. In cont release . These dOur results are most consistent with histone retrogression from 3′ to5′ over genes, which raises the question of whether old histones carrymodifications associated with mid- and 3′ coding regions  towards the 5′ end of genes. Alternatively, there couldbe active erasure of these modifications. We therefore compared genes exhibitinghigh levels of ancestral H3 retention with prior genome-wide analyses of histonemodifications More interestingly, we found that genes with high levels of old nucleosomes wereenriched for H3K79me3 throughout their coding regions, particularly at the5′ end . The H3KFinally, we also observed higher levels of H3K36me3 at 5′ and mid-CDS ofgenes exhibiting elevated ancestral histone retention relative to genes withintermediate H3-HA retention . This obThe fate of stable proteins in rapidly dividing cells is of great interest for fieldsfrom protein damage to aging to epigenetic inheritance. In particular, models forthe inheritance of chromatin-based information Most surprising to us was the observation that ancestral H3 molecules accumulatenear the 5′ ends of coding regions, peaking around the +3 nucleosome.The high HA/T7 ratio observed at the 5′ ends of genes is not an artifactof the epitope tags used, as we have observed the converse behavior (high T7/HA)when we switch the epitope tags used (unpublished data). Furthermore, thisunusual behavior is not an artifact of the conditions used for growth arrest andrelease, as we observe a similar 5′/3′ gradient of H3-HA when yeastare subjected to the epitope switch during active midlog growth .GAL-drivenepitope tagged H3 do not provide evidence for ubiquitous 3′ histonereplacement during G1 arrest What is the mechanistic basis for the 5′/3′ gradient of HA/T7 weobserve? We consider two classes of mechanisms—in one, histone proteins donot move laterally and the 5′/3′ gradient results from preferentialloss of 3′ H3/H4, while in the other the gradient results from lateralhistone movement combined with loss at the 5′ end. While we cannotdefinitively answer which mechanism explains our results, we strongly disfavor amodel with preferential 3′ nucleosome eviction and no lateral movementbased on the following observations. First, we tested a number of relevantmutants for changes in the 5′/3′ HA/T7 bias .Loss ofConversely, multiple observations support the hypothesis that H3/H4 proteins movefrom 3′ to 5′ over protein-coding regions over time. First, seminalin vitro studies on transcription of nucleosomal templates showed that severalRNA polymerases can transcribe through a nucleosome without displacing the H3/H4tetramer. The proposed mechanism by which histones remain associated with theDNA is a “bubble propagation” mechanism—DNA partially unwrapsfrom the histones, RNA polymerase enters, and DNA behind the polymerasere-associates with the histone octamer, resulting in a net retrograde movementof histones after the polymerase has passed. This mechanism is relatively wellestablished for SP6 polymerase and RNA Polymerase III rpb1-1 allele results in a net 5′to 3′ shift in the majority of coding region nucleosomes top1Δ mutants exhibit diminished signatures of H3/H4passback . InOur results show a surprising pattern of ancestral histone retention in yeast,with old histone proteins accumulating near the 5′ ends of genes—thehistone proteins located at the +3 nucleosome are the oldest histoneproteins over a typical yeast gene. These data are best explained by a model inwhich H3/H4 proteins shuttle from 3′ to 5′ over coding regions overtime, with eventual loss of old histone proteins when they are eventually movedinto the +1 and +2 nucleosome positions.BUD3) in a large population ofyeast, allow replication to proceed, and measure the new locations of the taggedhistones. Despite numerous attempts, this type of tagging has proven technicallyintractable to date. Here we measure instead the bulk distribution of ancestralhistones. Importantly, this still provides information on locus-specific histonebehavior—as turnover rates are not homogeneous across the genome, evenbefore we release yeast into the cell cycle the landscape of H3-HA exhibitsvariability  during replication. This value has not beenmeasured before but is consistent with several related observations. First,electron microscopy studies on replicating chromatin show a stretch of∼650–1,100 bp of nucleosome-free DNA surrounding replication forksTogether, these results support the prospect of chromatin as a“sloppy” epigenetic information carrier (“sloppy” in thesense that some spreading of histones will preclude mononucleosome-resolutioninformation passage) To further investigate the mechanisms underlying the patterns of ancestral H3retention, we assessed HA/T7 ratios at target genes in 12 mutants and furthercharacterized HA/T7 genome wide for three of these mutants. Interestingly, anumber of histone modifying factors, including Swd1, Swd3, Rtt109, Nhp6, andSet2, had either no effect or subtle effects  on the 5′accumulation of old histones at our target genes .These rThe three mutants we characterized at full genome coverage each had a distincteffect on ancestral H3 retention. Most dramatically, loss of the H4 N-terminaltail abolished the 5′ accumulation of ancestral histones—while theH4 tail deletion results are complicated by the retention of wild-type H3/H4 inthis strain, the fact that similar results were obtained with clean H4K5,12Rmutants  providesS.pombe, indicating that topoisomerases play key roles in histonedynamics top1Δmutants exhibit diminished 5′ accumulation of ancestral H3 and that thiseffect is stronger at longer genes than at shorter genes. As RNA polymerasepassage will cause greater changes in supercoiling over longer genes, thepreferential effects of Top1 on longer genes is consistent with the observationin S. pombe that topoisomerase mutants show evidence of stalledor slowed RNA polymerase over longer genes top1Δ mutants here most closely mimicsthe predictions of our analytical model with both passback and spreading beingcompromised, but since neither of these is likely to be completely eliminated intop1Δ mutants, more detailed kinetic analyses will berequired to make a quantitative statement about the role of Top1 inreplication-related movement of histones.We also observe a similar, albeit muted, effect of Topoisomerase I on the5′ accumulation of ancestral histones. Interestingly, loss of bothtopoisomerase I and II affects nucleosome occupancy and dynamics in GAL-driven Flag-H3) andconfirmed the prediction that caf mutants affectreplication-independent histone replacement caf hir double mutant would be necessary to uncover effectsof replication-coupled spreading. Unfortunately, since both hirand asf mutants are lethal in our strain background, thisprediction cannot be tested at present.Finally, we assessed the role of the histone chaperone CAF-1 in ancestral H3retention. To our surprise, we found that H3-HA exhibited even stronger 5′accumulation in this mutant, with the 5′ peak of HA/T7 occurring closer tothe +1 or +2 nucleosome (compared to the +3 peak location forwild-type strains). This result most closely matches the predictions of a modelin which H3/H4 turnover has been slowed without loss of passback or spreading. We receTaken together, our results provide a surprising view of histone dynamics overmultiple generations, with 5′ accumulation of ancestral histone proteinsover coding regions and little evidence for preferential histone retention atepigenetically regulated loci such as subtelomeric genes. One unanticipatedimplication of this observation is that 3′ histone marks are expected tomove towards the 5′ ends of genes over time, thereby shaping histonemodification profiles , subsequent deletion of thetagged HHF2-HHT2 locus, followed by transformation with a PCRfragment encoding wild-type or mutated HHF2 in combination withtagged HHT2. Deletion of the wild-type locus was confirmed inH4K5,12R mutants, whereas all surviving H4 tail deletion mutants retained a copyof the wild-type HHT2-HHF2 locus.For tag switch experiments, yeast cells were grown overnight in YPD in thepresence of Hygromycin B . The cells were thendiluted 1∶10 into fresh YPD and incubated for 30–36 h. Recombinationwas induced by the addition of 1 µM β-estradiol . Subsequently, cells were diluted 1∶25 in fresh YPD mediato release the cells back into the cell cycle and kept in log phase by 1∶2dilutions into fresh media after each population doubling. Samples were takenafter 1, 2, 3, and 6 cell divisions or after 5 h of G2/M arrest. The number ofpopulation doublings was determined by microscopy and OD. G2/M arrest wasinduced by addition of 15 µg/ml Nocodazole (Sigma-Aldrich) and confirmedby FACS analysis. Strains are listed in 9 cells was washed, resuspended in 400 µl FAlysis buffer , and sheared using aBioruptor (Diagenode) for 6 min with 30 s intervals at high. The solublefraction was diluted 3-fold in buffer 15 mM Tris-HCl pH 7.4, 50 mM NaCl, 1.5 mMCaCl2, 5 mM β-meracptoethanol, 5 mM MgCl2, afterwhich 25 units of micrococcal nuclease (Worthington) were added. The digestionreaction was incubated 20 min at 37°C and stopped by the addition of 10 mMEDTA and 10 mM EGTA; tubes were placed on ice. The majority of obtainedfragments was around 150 bp, as determined on a 2% TAE agarose gelstained with ethidium bromide. The isolated chromatin of the equivalent of3×108 cells was immunoprecipitated overnight at 4°Cusing magnetic Dynabeads (Invitrogen), which were previously incubated withantibody O/N at 4°C.ChIP was performed as described previously ChIP DNA was quantified by real-time quantitative PCR using the SYBR Green PCRMaster Mix (Applied Biosystems) and the ABI PRISM 7500. An input sample was usedto make a standard curve, which was then used to calculate the IP samples, allperformed in the 7500 fast system software. Primers used for qPCR are listed inThe samples were amplified, with a starting amount of up to 75 ng for ChIPsamples, using the DNA linear amplification method described previouslywww.microarrays.org. Labeled probes were hybridized onto ayeast tiled oligonucleotide microarray www.microarrays.org.The arrays were scanned at 5 micron resolution with an Axon LaboratoriesGenePix 4000B scanner running GenePix 5.1. Image analysis and datanormalization were performed as previously described 3 µg of aRNA produced from the linear amplification were used to labelprobe via the amino-allyl method as described on ChIP DNA was treated with CIP . 20–150 ng of CIP treated ChIP DNA fragments wereblunt ended and phosphorylated with the EPICENTRE End-it-Repair kit for 1 h at RT and cleaned up with Qiagen MinElute spin columns. Adenosinenucleotide overhangs were added using EPICENTRE exo-Klenow for 45 min at RT(with 0.2 mM dATP). Illumina genome sequencing adaptors were then ligated usingthe EPICENTRE Fast-Link ligation kit: 11.5 µl A tailed DNA eluted from aMinElute column was mixed with 1.5 µl 10× ligation buffer, 0.75µl 10 mM ATP, 0.5 µl Illumina DNA adaptors, and 1 µl Ligase.The reaction was incubated for 1 h at RT and subsequently supplemented with 7.5µl water, 1 µl 10× buffer, 0.5 µl 10 mM ATP, and 1µl ligase, and incubated overnight at 16°C.The ligation reaction was cleaned up with MinElute columns  and the adaptor ligatedfragments were amplified by PCR as follows: 0.5 µl of each Illuminagenomic DNA sequencing primers, 10 µl 10× Pfx buffer 3 µl 10mM dNTPs, 2 µl 50 mM MgSO4, and 1 µl Pfx DNA polymerase (Invitrogen)were added to 30 µl DNA template in a 100 µl reaction. The cyclingparameters were: (1) 94°C, 2′; (2) 94°C, 15″; (3) 65°C,1′; (4) 68°C, 30″; (5) repeat from (2) 17 times; (6) 68°C,5′. The PCR product (200 to 300 bp in size) was gel purified from a2% TAE agarose gel using the Freeze'N Squeeze columns (BioRad). Gelpurified fragments were finally precipitated with Sodium acetate and Ethanol andpellets were resuspended  in TE buffer and sent forSOLEXA sequencing at the UMass Worcester core deep sequencing facility.9 cells)were flash frozen after formaldehyde crosslinking (1%) and kept at−80°C overnight. Frozen cell pellets were resuspended in 300 µlcell braking buffer  and cell walls were broken down by bead beatingusing 400 µl of 0.5 mm zirconia/silica beads (BioSpec Products) in theBioSpec Mini-BeadBeater Model 8 three times for 1 min with 1 min pauses inbetween. Cell pellets (5 min max speed spin in refrigerated microcentrifuge)were then washed once and resuspended in 800 µl FA lysis buffer (with1× Sigma Protease inhibitors cocktail). Chromatin was sheared bysonication in a cup sonicator  to 250–400 bp fragments.Cells were grown as described above. Cell pellets (∼10The sheared chromatin suspension was pre-cleared with 100 µl ProteinA-agarose slurry (IPA 400 HC RepliGen) at 4°C for 1 h. 100 µl of thepre-cleared solution was saved for the ChIP input sample and 7 µl of RNAPol II antibody  was added to therest and incubated overnight at 4°C with rotation. ChIP DNA isolation andamplification by TLAD was done as described previously www.microarrays.org.Labeled probes were hybridized onto a 4X44K yeast whole genome array (Agilent)at 65°C for 16 h. The arrays were scanned with the Agilent microarrayscanner.2.5 μg of aRNA produced from the linear amplification were used to labelprobes via the amino-allyl method as described on http://www.umassmed.edu/bmp/faculty/rando.cfm and have beendeposited in GEO (Accession # GSE28269).Data are downloadable at S. cerevisiae genome.Nucleosome positions were called from aggregated HA and T7 sequencing of the3 generation sample using Template-Filtering Raw sequencing data of HA and T7 libraries after the tag swap before releasefrom arrest (0 generations), and at 1, 3, and 6 generations after releasewere uniquely mapped to the For aggregated analyses such as those shown in Described in Figure S1Recombination efficiency. Yeast were plated onto nonselective media and ontomedia selecting for the HA tag (linked to Hygro), before(t = 0) and after (t = o/n)inducing recombination. Roughly 2% of yeast fail to swap out theHA-Hygro insert.(PDF)Click here for additional data file.Figure S2HA/T7 at 3 and 6 generations after release. HA/T7 ratios (Log2) forindividual nucleosomes are scatterplotted as indicated, showing goodcorrelation but a slope <1 (red line), consistent with the background ofnonswitching cells observed in (PDF)Click here for additional data file.Figure S3SPA2 (A) and BUD3 (C).  qPCRshown for the 5′ and 3′ ends of SPA2 (B) andBUD3 (D) at the indicated number of generations aftertag-swap and release. Midlog refers to samples taken 3 h after the tag-swapwas induced in exponentially growing cells that had not undergone a recentarrest. Note that only a fraction of all the cells had recombined out theold tag during the 3 h. qPCR amplicon locations are indicated under the geneannotation.Validation of target genes.  Deep sequencing data (3 generations) for(PDF)Click here for additional data file.Figure S4K means clustering of HA/T7 ratios. Log(2) HA/T7 ratios at 3 generationsafter release are shown as a heatmap for all genes, aligned by transcriptionstart site (TSS) and clustered .Selected Gene Ontology (GO) enrichments for the various clusters areindicated to the right of the clusters.(TIF)Click here for additional data file.Figure S5Histone retention anticorrelates with turnover. (A) Average profiles for the5 clusters from (PDF)Click here for additional data file.Figure S6Histone retention anticorrelates with transcription frequency. (A–B) Asin (TIF)Click here for additional data file.Figure S7H3 retention at subtelomeric genes. Median HA/T7 over the 5′ 1 kb ofall genes is plotted versus distance from the closest telomere, with an 80gene running window average shown in red. No specific enrichment of H3-HA isobserved near telomeres. Similar results are found for repetitivesubtelomeric genes (unpublished data).(PDF)Click here for additional data file.Figure S8SPA2 or BUD3 were measured by q-PCRfor the various mutants 3 generations after release or after one round ofreplication arrested in G2/M. 5′/3′ ratio relative to wild-typelevel is plotted on the y-axis. Mutants are as indicated,with swd1, swd3 referring to an average ofsingle replicates with each individual mutant and scc1referring to one experiment using a pGAL1-SCC1 allele thatwas shut off by release into glucose media after the tag switch (leading toa G2/M arrest). Average of mutant/wt, ± S.E.M.(n = 2). Swd1 and Swd3 are componentsof the Set1 complex, which methylates H3K4. Set2 is the H3K36 methylase andScc1 is part of the cohesin complex. (B) 5′/3′ ratio atSPA2 or BUD3 were measured by q-PCRfor the various mutants after one round of replication arrested in G2/M.5′/3′ ratio is plotted on the y-axis withwild-type set to 1. Average ± S.E.M.(n = 2). H4K5,12R is a mutant in whichtwo of the acetylatable lysines of the H4 tail have been replaced byarginine, mimicking the unacetylated state. Rtt109 is a histoneacetyltransferase that binds to Asf1 and acetylates new histone H3 on K56POL30) pointmutants. Average of mutant/wt, ± S.E.M.(n = 2).Mutant analysis of ancestral H3 retention. (A) 5′/3′ ratio at(PDF)Click here for additional data file.Figure S9HA retention on length-normalized genes. (A) All genes were normalized to alength of 1, and genes are ordered by Pol2 ChIP. Log2 HA/T7 ratios are shownas a heatmap. (B) Running window average of data from (A). Note the 5′shift of the downstream edge of the HA/T7 peak with increasing transcriptionrates. (C) Pol2 ChIP for genes as ordered in (A–B). (D) Averages forall length-normalized genes grouped into 6 bins of transcription level.(PDF)Click here for additional data file.Figure S105′ accumulation of ancestral histones occurs in the absence of nutrientstress. (A) Yeast carrying the HA/T7 recombination cassette were growncontinuously in YPD, then were treated with β-estradiol for 6 h toinduce recombination. HA and T7 ChIPs were carried out after 6 h and deepsequenced, and normalized HA/T7 ratios were calculated. Here, genes areordered in 5 clusters as in (TIF)Click here for additional data file.Figure S11A quantitative model accurately captures ancestral H3 retention patterns.Model predictions (red lines) and data (blue lines) for HA/T7 ratios at 1,3, and 6 generations after tag swap are shown for 1–2 kb genes (A) and>2 kb genes (B). The model performs better on longer genes than on shortgenes.(PDF)Click here for additional data file.Figure S12Passback correlates with transcription rate. Estimated passback parametersfor each gene were compared to Pol2 ChIP values for each gene. Scatterplotis colored by density of points—red indicates greater density ofpoints. White line indicates linear fit to dataset,R = 0.12.(PDF)Click here for additional data file.Figure S13Short genes and 3′ ends are poorly predicted by the model. Genes areordered by length, and the difference between model predictions for 3generations and actual data are shown as a heatmap—yellow indicatesthe model predicts excessive old nucleosome loss, or lower HA/T7 ratios thanmeasured. Notably, the +N nucleosome is universally predicted to losemore H3-HA than is measured. This is almost certainly a consequence of thefact that our model considers all genes in isolation—there is no wayfor histones to spread onto the 3′ end of a gene from adjacent genomicloci in this model, although this likely occurs in vivo.(PDF)Click here for additional data file.Figure S14more enriched for Pol2 than those with low HA/T7levels, the opposite of what is seen in wild-type  Tag swap strains carrying anH4 N-terminal tail deletion were processed as in (TIF)Click here for additional data file.Figure S15Replication time has subtle effects of ancestral H3 patterns. (A) Data forthe 20% earliest and 20% latest-replicating (PDF)Click here for additional data file.Figure S16cac1Δ.CAF-1 mutation affects far-5′ end levels of ancestral H3. Averaged datafor clusters 4 and 5  are show(PDF)Click here for additional data file.Figure S17Ancestral H3 retention and histone modification patterns. Modification levels(PDF)Click here for additional data file.Figure S18Role for histone movement in shaping modification landscapes. Schematic forretrograde histone movement in shaping histone modification landscapes.Initial 5′ (green) and 3′ (purple) histone modification statescould, in the absence of erasing enzymes, eventually give rise to skeweddistributions via retrograde motion of old histones bearing 3′modifications such as H3K36me3 (purple). Importantly, after a few celldivisions old histones on average constitute only a minor fraction of allhistones at any given locus Click here for additional data file.Table S1HA/T7 ratios for 3 generations. Log2(HA/T7) for all genes is shown at varyingdistances with respect to the TSS. Genes are sorted according to the medianHA/T7 over the 5′ 1 kb.(XLSX)Click here for additional data file.Table S2Enrichments of genesets for high or low retrograde passback values. A varietyof gene sets were searched for enrichment of relatively high or low valuesfor model estimates of lateral nucleosome movement. Negative KS valuesindicate large 3′ to 5′ lateral movements; positive valuesindicate the converse.(XLSX)Click here for additional data file.Table S3Strain list. Genotypes of strains used in this study.(XLS)Click here for additional data file.Table S4Primers used. Primer sequences.(XLS)Click here for additional data file.Text S1Quantitative model for multigenerational histone dynamics. Detaileddescription of model shown in (PDF)Click here for additional data file.


Three results were obtained: 1) the ie1 promoter is a classical eukaryotic promoter that contains the initiator element (Inr) and TATA box responsible for the basal promoter activity; 2) mutation or truncation of a predicted Sp1 site decreased the level of promoter activity by about 3-fold, indicating that the Sp1 site is an important cis-element of the promoter; and 3) truncation of a 12-bp sequence that resides at -78/-67 of the ie1 promoter decreased the level of promoter activity by about 14-fold, indicating that the 12-bp motif is a critical upstream element of the ie1 promoter for binding of a strong transcription factor to drive the ie1 gene expression in the cells. Further, the 12-bp DNA binding protein was purified from the nuclear proteins of Sf9 cells using DNA affinity chromatography, and was identified as a homologue of the prohibitin2 protein (named as Sf-PHB2) using mass spectrometry. Furthermore, the DNA binding activity of Sf-PHB2 was verified using a super shift analysis.Here, a detailed characterization of the ie1 gene expression by binding to the 12-bp DNA element.These results support that the Sf-PHB2 is a novel transcription factor that drives WSSV  White spot syndrome (WSS), which first appeared in Southeast Asia at the beginning of the 1990s and spread globally, is the most serious infectious disease of cultured shrimp. A sequeie genes have been identified in WSSV, of which 4 exhibit transcription activity[ie1 gene is highly expressed throughout the WSSV infection cycle[ie1 (IE1) contains a Cys2/His2-type zinc finger that is a domain involved in DNA-protein interactions. Therefore, the IE1 protein has been reported to act as a transcription factor[ie1 gene may play critically important roles in the regulation of WSSV transcription and in the infection cycle of the virus.As with most of the large dsDNA viruses, such as baculovirus and herpes virus, WSSV genes can be classified as early or late genes based on their temporal expression profiles. These viruses are expressed in a coordinated and cascaded fashion under the control of several different promoters,10. The activity. The WSSon cycle, the pron factor, and theie1 gene promoter in many cells including Sf9 insect cells[ie1 gene promoter has a putative TATA box and a downstream Inr element that is similar to other WSSV early gene promoters[We have previously reported on the pan-activity of the strong ct cells, the celct cells,15. Baseromoters. Many dsromoters, these pie1 gene was determined and we found that its promoter contained both early and late elements. By functionally mapping a series of the truncates a new 12-bp regulatory element of the ie1 promoter was identified in the -78 to -67 bp region that was related to the transcription start site, which was shown to be essential in controlling the high-level expression of this gene. To delineate the transcription regulation mechanism of the 12-bp element of the WSSV ie1 gene promoter, we further purified the 12-bp DNA binding protein from the Sf9 nuclear extracts using DNA affinity chromatography, and the purified protein was identified as a homologue of the mosquito prohibitin2 using mass spectrometry. The gene encoding the 12-bp binding protein was cloned from Sf9 cells and named sf-phb2. The interaction between Sf-PHB2 and the 12-bp motif was further verified using electrophoretic mobility shift assays (EMSA) and an antibody super shift. In addition, a classical nuclear localization signal and a helix-turn-helix domain that was located in Sf-PHB2 provided structural evidence for its role as a novel transcription factor.In the present study, the transcription start site of the ie1 gene expression by binding to the 12-bp DNA element. These data are important not only to understand of the general mechanisms that control gene expression, but also to provide additional insight into WSSV replication in host cells.These results supported that the Sf-PHB2 protein is a critical transcription factor that drives WSSV ie1 gene, 5'-RACE was performed using the RNA that was isolated from the WSSV infected shrimps with the ie1 gene specific primers. A DNA fragment resulting from the 5'-RACE nested was cloned and sequenced. The sequence analysis revealed that in 6 of the 10 selected clones, the transcription start site was located 24 bp downstream of a putative TATA box (TATATAAG) and 53 bp upstream of the predicted ATG translation start codon. In the other 4 clones, the 5' termini were 52 or 51 bp upstream of the putative ATG. These data indicated that the transcription start point of the ie1 gene initiated from the adenine within the CAGT motif, 53 bp upstream of the ATG codon  was cloned into the phRG-B luciferase reporter vector. A series of deletions and mutations from the 5' side of the ie1 promoter were generated to determine the minimal sequence that was required for the basal level of promoter activity ), 50 bp upstream of the translational start site (p(-335/+3)) and Inr consensus sequence TCAGTC (p(-335/-3)). The results revealed that a deletion of the Inr consensus sequence caused a 10-fold decrease in the level of activity compared to the wild type promoter p(-335/+53), whereas deletions that were downstream of the Inr had no obvious effect on the level of promoter activity  or their proximal downstream p(-135/+53) had no significant effect on the level of promoter activity  Δ) or deletion p(-35/+53) of the potential Sp1-binding motif caused a 2.6-fold or 2.8-fold decrease in the level of promoter activity, respectively, indicating that the Sp1-binding motif and the 80 bp sequence are required for maximal transcription that is driven by the ie1 promoter activity suggested the presence of a new activating promoter element(s) in this 80-bp region. Therefore, we searched for activating element(s) by performing further deletions. The results indicated that the luciferase activity dramatically dropped 14-fold from p(-78/+53) to p(-66/+53)  that binds the 12-bp DNA fragment, the nuclear proteins from the Sf9 cells were purified by binding the biotinylated DNA and using streptavidin affinity chromatography. In SDS-PAGE analysis, the affinity-purified proteins revealed a band of 32 kDa after sliver staining . Furthermore, we predicted the open reading frame of the contig and confirmed the complete cDNA of the gene using BLAST. We nominated the novel gene as sf-phb2 (GenBank accession number HQ337624).It is a common strategy to clone protein family cDNA using degenerate primer PCR. Using one pair of the primers, a partial cDNA of the PHB2 gene was obtained from the Sf9 cells using RT-PCR. To obtain full-length cDNAs of the PHB2 gene from the Sf9 cells, we used this sequence as a query to blast against the sf-phb2 gene is 1297 bp, including 112 nucleotides in the 5' -UTR 285 nucleotides in the 3'-UTR, and an ORF that encodes 299 amino acids, with a predicted mass of 32 KDa. The sequence analysis revealed that the Sf-PHB2 protein contains a PHB domain at residues 41-202, a nuclear localization sequence (NLS) at residues 87-90 and a helix-turn-helix (HTH) domain at residues 136-181.The full length of the Spodoptera frugiperda PHB2 and other PHB2s, the 10 homologous sequences were subjected to a phylogenetic analysis and the resulting identity matrix is shown in FigureBombyx mori L, Culex quinquefasciatus and Drosophila melanogaster, respectively. However,Sf-PHB2 shares only 70.9% of its sequence with its human counterpart.Blastp searches were performed using the amino acid sequence of the Sf-PHB2 from the NCBI database, and the obtained homologues of the Sf-PHB2 are listed in Figureie1 gene expression.Because Sf-PHB2 was purified from the nuclear exacts and contains putative nuclear localization signals, we investigated whether Sf-PHB2 is indeed a nuclear protein. To determine the subcellular distribution pattern of the Sf-PHB2 protein, indirect immunofluorescence staining using Sf-PHB2 antibody was performed in the Sf9 cells. As shown in Figurecis-acting element of the WSSV ie1 promoter.As described above, we purified the Sf-PHB2 protein from the Sf9 cells using DNA affinity chromatography. To further investigate the interaction between the Sf-PHB2 protein and the 12-bp DNA, the affinity of the Sf-PHB2 to the 12-bp sequence was evaluated using an EMSA analysis with nuclear extracts that were prepared from the Sf9 cells. For the super shift assay, a polyclonal antibody was generated against the Sf-PHB2 protein, and the results are shown in Figureie1 gene promoter, we found a new 12-bp regulatory element that is responsible for most of the promoter activity. Furthermore, we purified the 12-bp DNA binding protein using DNA affinity chromatography and identified it as a homologue of the mosquito prohibitin2 using mass spectrometry. Lastly, we verified the DNA-protein interaction between Sf-PHB2 and the 12-bp motif using EMSA and an antibody super shift. In addition, Sf-PHB2, which carried a classical nuclear localization signal and a DNA binding domain HTH, was localized to the nucleolus of the Sf9 cells. These results support that the Sf-PHB2 is a novel transcription factor that drives WSSV ie1 gene expression by binding to the 12-bp DNA element.Taken together, during the functional mapping of the WSSV ie1 gene contains a strong, pan-activity promoter and is highly expressed throughout the infection cycle[ie1 gene was determined using the 5' RACE method at 53 nt upstream of the translation start codon, the transcription of which is initiated at a conserved CAGT subsequence, a motif that is a feature of early genes in many insect baculoviruses[Liu et al. reported that the transcription start site of the ie1 gene was localized 52 nt upstream of the ATG codon[ie1 transcript that is one nucleotide less than that determined here. In addition, as shown in Figureie1 transcription start site, which is similar to the arrangement seen in the insect baculovirus.[ie1 gene, the transcript was present throughout the virus infection cycle[The WSSV on cycle,14. Exproviruses. Liu et TG codon, which llovirus. In all ilovirus.,20. For on cycle, and thecis-acting DNA regulatory elements is a critical step towards understanding gene expression regulation. In the present study, we cloned 388 bp of the 5' upstream promoter of the ie1 gene and analyzed the promoter activity through a deletion and mutation with a luciferase reporter. In the deletion studies, the -35 to +3 region that contained the transcription starting sequence CAGT and a putative TATA box was sufficient for basal promoter activity, whereas the fragment from -235 to +53 exhibited the highest level of promoter activity. The sequence analysis of the 388 bp fragment revealed a stretch of several adjacent putative transcription factor binding sites, of which only the Sp1 binding site was functional. The critical cis-acting sequence of the WSSV ie1 promoter is a 12-bp imperfect inverted repeat, 5'--78ATTTATTCCTAG-67-3', which is predicted to bind an unknown transcription factor that is very important for driving the expression of the ie1 gene. In summary, the core promoter of the ie1 gene consists of a TATA box and the transcription initiating element CAGT, and a tentative Sp1 binding site and the 12-bp imperfect inverted repeat were essential for maximal promoter activity. The transcription start site of the ie1 gene is located within the transcription initiating element CAGT.The identification of functional ie1 gene was used as the affinity material to capture the transcription factor(s) that recognizes this specific DNA sequence from the nuclear proteins of the Sf9 cells, and only Sf-PHB2 was identified as the protein to bind the 12-bp DNA.Thereafter, the 12-bp DNA sequence of the Although very important advances in the understanding of the PHB2 have been made in the decade since its discovery, the functions of PHB2 are studied in vertebrates and only partially understood-25. In aphb2 gene and proposed that Sf-PHB2 acts as a transcription factor to modulate the expression of the WSSV ie1 gene via a 12-bp DNA element in Sf9 cells. In addition, we concluded that this proposed idea is correct. This conclusion rests on four observations. First, DNA affinity chromatography is a powerful method for purifying DNA-binding proteins. Several transcription factors such as the lac repressor protein[ie1 promoter. Third, the NLS of Sf-PHB2 and its expression in the nucleolus of the Sf9 cells support the hypothesis that Sf-PHB2 may play a role as a transcription factor in the regulation of ie1 gene expression. Lastly and most notably, there is a putative helix-turn-helix (HTH) domain at the C-terminal region of Sf-PHB2, which is a typical DNA-binding domain[ie1 and the replication of WSSV in shrimp.In the present study, we cloned sf- protein, Sp1[29 protein, have beg domain, providig domain. In addicis-acting element of the promoter, whereas its homologous proteins in vertebrates play a role in gene expression regulation through the interaction with transcription factors[It is very interesting that Sf-PHB2 can directly bind to the  factors instead  factors,34. It h factors. Therefoie1 gene transcription through the cis-acting motif (ATTCCTAGAAA)[In contrast to our results, Liu et al. reported that signal transducer and activator of transcription (STAT) enhances WSSV CTAGAAA),36. The ie1 promoter has early and late elements that can interpret ie1 expression throughout the infection cycle. Our data proved that Sf-PHB2 is a new transcription factor that drives ie1 expression and results in high level of activity of the ie1 promoter in Sf9 cells. These findings provide insight into transcription regulation and will be helpful in understanding of the life cycle and molecular pathogenesis of WSSV. In the future we will focus on mapping the corresponding functional domains of Sf-PHB2 as a transcription factor, including the transactivation domain and the DNA binding domain. Furthermore, we will confirm that shrimp PHB2 functions as a transcription factor to drive WSSV ie1 gene expression by binding to the 12-bp DNA element.In summary, the present study has demonstrated for the first time that the WSSV ie1 gene expression by binding to the 12-bp DNA element.Sf-PHB2 is a novel transcription factor that drives WSSV Spodoptera frugiperda pupal ovarian tissue was propagated and was maintained at 28°C in serum-free medium  that was supplemented with 50 μg/ml gentamicin.The Sf9 cell line (Invitrogen) from the P. monodon shrimps (15-20 g) was confirmed using two-step PCR, as described previously[g for 30 min. The supernatant was filtered through a 0.45 μm filter for experimental infection or for the extraction of viral DNA.The WSSV infected the healthy subadult eviously. The vireviously, with a P. monodon shrimps were inoculated with WSSV as described previously[For the 5'-RACE analysis, the healthy sub adult eviously. After 4ie1 transcript was identified using rapid amplification of the cDNA 5' ends (5' RACE) with a 5'-RACE kit (Roche), according to the manufacturer's instructions. The total RNA was prepared from the heads of the WSSV-infected shrimp at 6 h post infection. The appropriate gene specific reverse primer R1 (5'-TACAAAGAATCCAGAAATCTCAT-3') was then used for the cDNA synthesis. Before being subjected to PCR, a poly (A) tail was added to the 5' end of the cDNA product using terminal transferase in the presence of dATP. The first round of PCR was performed using the R2 primer (5'-CAAATCAGAATGACCCACTCCATG-3') and an oligodT anchor. The PCR product from the first round was used as the template for the second round of PCR, using the R3 primer (5'-GTACATCCATATGGATGCCGCATT-3') and the anchor primer from the 5' RACE kit. The final product was sequenced, and the resulting sequences were compared with the WSSV genomic sequence using the DNA StriderTM1.3.The 5' region of the ie1 promoter was generated using PCR with the Primer Star high-fidelity Taq DNA polymerase (Takara) and the WSSV genomic DNA as a template. This approach used a forward primer from the 5'-upsteam region of the genomic sequence with a KpnI site and a reverse primer from the downstream region with a HindIII site. This fragment was cloned into a phRG-B vector. A series of 5' and 3' deletion constructs were generated using PCR with a series of primers with enzyme digestion sites (TableThe 388 bp (from-335 to +53 bp in relation to the transcription start site) fragment of WSSV The Sf9 cells were Transfected in 6-well plates with 1 μg of reporter plasmid. The transient transfection was performed using Effective (Qiagen), according to the manufacturer's instructions. At 48 hours post transfection, the cells were harvested and were assayed for reporter gene activity with the dual-luciferase report assay system (Promega). All transfection were performed in triplicate, and data were analyzed by normalizing firefly luciferase activity to Renilla luciferase activity for each sample. Each construct was tested in three independent transfection.For the isolation of the nuclear proteins from the Sf9 cells, NE-PER® nuclear and cytoplasmic extraction reagents (Thermo Scientific) were used. The nuclear proteins were extracted according to the manufacturer's recommendations. The protein concentrations were determined using the Lowry method.The DNA binding protein was purified using magnetic affinity particles that were conjugated with the 12-bp DNA fragment. A number of DNA binding sites were generated using a self-priming PCR method with two synthetic direct repeats of complementary single-stranded 5'-end phosphorylated oligonucleotides that included the 12-bp motif. The following forward (F) and reverse (R) phosphorylated single stranded oligonucleotides were used (the 12-bp DNA element is underlined):5'-phso-ATTCCTAGAAATGGTGTAATCGCATTCCTAGAAATGGTGTAATCGC-3' (F) and 5'- phso- GCGATTACACCATTTCTAGGAATGCGATTACACCATTTCTAGGAAT-3' (R)The concatenated nucleotides were conjugated with magnetic particles using a DNA-binding protein purification kit (Roche). The DNA binding proteins were purified according to the manufacturer's instructions,41. The The excised protein in-gel was sent to Chinese National Center of Biomedical Analysis  for protein identification. Briefly, the protein was digested with trypsin  according to the center proteomic protocols for mass spectrometry. The obtained peptide mass fingerprint (PMF) was used to search through the Swiss-Prot and the National Center for Biotechnology Information (NCBI) non-redundant databases.Spodoptera frugiperda expressed sequence tag (EST) database (http://www.ncbi.nlm.nih.gov/dbEST/) for homologous clones using the BLAST program (http://www.ncbi.nlm.nih.gov/blast/). These ESTs were assembled into contig, and the open reading frames were predicted by ORF finder (http://http//:www.ncbi.nlm.nih.gov/gorf) online software.Using blastp, block maker and CODEHOP,44, a 12The amino acid sequences of the DNA binding protein from Sf9 cells were deduced and nine homologous amino acid sequences were retrieved from GenBank for sequence alignment and phylogenetic analysis. Multiple sequences were aligned with ClutalX, and the phylogenetic analysis of the alignments was conducted using MEGA4. The trees were constructed based on the distances that were obtained using the neighbor-joining method. The reliability of the trees was tested by bootstrapping (1000 replicates) using neighbor-joining and parsimony. The trees were viewed using MEGA4.E. coli using His-tagged pET-30a (Amersham), and was purified using Ni-NTA agarose (Amersham), according to the manufacturer's instructions. Polyclonal antibodies against the DNA binding were generated by immunizing BABL/c mice.The DNA binding protein was expressed in ie1 gene promoter is underlined). The oligonucleotides were end-labeled using the Biotin 3' End DNA Labeling kit (Pierce), according to the manufacturer's instructions. The EMSAs were performed using the Light shift Chemiluminescent EMSA kit (Pierce). A 20 fmol biotin-labeled oligonucleotide was incubated with 10 μg nuclear protein extract from the Sf9 cells for 20 minutes at room temperature in a binding buffer , 250 mM NaCl, 2.5 mM DTT, 5 mM MgCl2 and 20% glycerol). The binding was competed using 5- or 10-fold amounts of the excess unlabeled the oligonucleotides (cold probe). For the super shift, 0.5 or 1 μg of the specific antibody was added after incubation of the nuclear proteins with the biotin-labeled oligonucleotides. The binding complexes were resolved using electrophoresis with 5% native polyacrylamide gel in 0.5 × TBE , which was transferred to nylon membranes (Pierce), UV cross linked, and visualized using the Chemiluminescent Nucleic Acid Detection System (Pierce).The following oligonucleotide was used: 5'-CTCATTTATTCCTAGAAATG GTGTAATC-3'  at a 1:200 dilution was added, and the solution was incubated for 1 h at 37°C. The counter-staining of the nuclei was performed using 4,6-diamidino-2-phenylindole dihydrochloride (DAPI) (Invitrogen). After three washes, the results were observed under a confocal laser scanning microscope (Leica TCS SP2).WSSV: White spot syndrome virus; IE1: Immediate early gene 1; PHB: Prohibitin; HTH: Helix-turn-helix; AcMNPV: Auographa californica multicapsid nuclear polyhedrosis virus; OpMNPV: Orgyia pseudotsugata multicapsid nuclear polyhedrosis virus; AP-1: Activator protein-1; RACE: Rapid amplification of cDNA ends; SP1: Specificity protein-1; TBP: TATA-box-binding protein; EMSA: Electrophoretic mobility-shift assay; MALDI: Matrix assisted laser desorption/ionization; DAPI: 4,6-diamidino-2-phenylindole dihydrochloride; TOF: Time-of-flight; UTR: Untranslated region; Inr: Initiator element.The authors declare that they have no competing interests.GDM and LY carried out the molecular genetics studies and drafted the manuscript. QW carried out virus preparation and cell culture. YDC participated in the sequence alignment. LY and WL carried out plasmid construction and promoter activity assay. JK conceived the experimental design and participated in revising the manuscript. All authors read and approved the final manuscript.


It is known that chromatin features such as histone modifications and the binding of transcription factors exert a significant impact on the “openness” of chromatin. In this study, we present a quantitative analysis of the genome-wide relationship between chromatin features and chromatin accessibility in DNase I hypersensitive sites. We found that these features show distinct preference to localize in open chromatin. In order to elucidate the exact impact, we derived quantitative models to directly predict the “openness” of chromatin using histone modification features and transcription factor binding features, respectively. We show that these two types of features are highly predictive for chromatin accessibility in a statistical viewpoint. Moreover, our results indicate that these features are highly redundant and only a small number of features are needed to achieve a very high predictive power. Our study provides new insights into the true biological phenomena and the combinatorial effects of chromatin features to differential DNase I hypersensitivity. In eukaryotes, DNA is organized into chains of nucleosomes, each of which consists of about 146 bp of DNA wrapped around an octamer of four types of histones . HoweverTraditionally, the experimental technique of choice to discover the DNase I hypersensitive sites is Southern blotting . HoweverIt is generally accepted that histone modifications and the binding of transcription factors are two main effectors for the “openness” of chromatin. Previous studies have shown that histone modifications and transcription factors tend to occur near or just in the DNase I hypersensitive sites , 13. RecAll datasets are from ENCODE project, which aims to build a comprehensive list of functional elements in the human genome . The 10 We obtained genomic locations of 33 chromatin feature profiles, all together including 582489 histone modification peaks (10 HMs) and 443217 transcription factor binding peaks (23 TFs). For each profile, we mapped the peaks of feature onto the genome and examined whether it localized in open chromatin or not. The presence or absence of chromatin feature within accessible chromatin was decided by overlap or nonoverlap with DNase-seq peaks. If there was any amount of overlap within accessible chromatin (DNase-seq peaks), we counted as a presence . Then, wR package [To investigate the quantitative relationship between chromatin accessibility and these chromatin features in DNase I hypersensitive sites, we constructed support vector regression (SVR) models for HM and TF binding features, respectively. Concretely, in every DNase I hypersensitive site, we calculated the maximum signal of DNase-Seq and the corresponding maximum signal of Chip-Seq for each chromatin feature. For the sake of figuring out whether the maximum signal exhibits largest prediction power or not, as a comparison, we also calculated the average signal of Chip-seq and DNase-seq for each hypersensitive region. Then, SVR model was built to predict the chromatin accessibility using signals of these chromatin features. SVR is a machine learning algorithm based on statistical theory for regression problems , 15. We  package .http://dx.doi.org/10.1155/2013/914971). We used the 10-fold cross-validation method to evaluate the prediction power. Specifically, we randomly split our sample dataset into 10 equal size subsets. Among them, 9 subsets were used as training data and the remaining subset was treated as the validation data for testing the model. This process was repeated 10 times and each subset could only be used once as the validation data. After that, we combined the results and plotted the regression relationship between predicted signals and the actual DNase-seq signals. Then, the coefficient of determination (R2) [R2 is also a frequently used measure of the proportion of total variation of outcomes explained by the model. We chose the square root of the coefficient of determination (R) as our prediction power.In order to reduce the computation cost, we randomly selected 5000 DHSs for our samples. The sample size analysis indicated that the prediction power increased only moderately after the size reached 2000. So, the sample size of 5000 is big enough to represent the entire dataset (Supporting Information S1 which is available online at on (R2)  was comp331), two-feature (C332), and three-feature (C333) models were evaluated by their performance.To estimate which feature exhibits the maximal prediction power, we predicted the chromatin accessibility using only one feature. And to investigate whether HM features and TF binding features are redundant, we next predicted the “openness” of chromatin using all features. We also explored the combinatorial effects of these features. All possible one-feature  from ENCODE project , includiR2) is 0.58 indicating that histone modification features explain about 58% variance of chromatin accessibility. In order to examine the quantitative relationship between chromatin accessibility and HM features in a combinatorial manner, we constructed SVR model to predict the “openness” of chromatin in DNase I hypersensitive sites using all histone modification features. We can see from R = 0.67, 0.66,0.63, resp.). These histone modifications are generally enriched in the promoters of expressed genes [R = 0.30,0.23, resp.), which suggests that these modifications are associated with heterochromatin [We next examined the prediction power for every histone modification feature. ed genes  and the hromatin , 22. IntR2) of 0.58 which is equal to that achieved by HM model. These TF binding features can also explain about 58% variance of chromatin accessibility.Previous studies have shown that transcription factors tend to bind onto open chromatin and they are highly correlated with each other , 13. To R = 0.37,0.36,0.33, resp.). ZNF274 and SUZ12 are known to be transcriptional repressors [For the prediction power of particular TF binding feature, there is a difference with that of histone modifications; that is, most transcription factors exhibit important effects to chromatin accessibility . This ispressors , 26. CTCR2 = 0.66) is a little higher (8%) than using only HM or TF binding features, which indicates that these two types of features are highly redundant. To check the importance of different features and their combinatorial effects, we tried to build models with all possible combinations of one to three features (R = 0.45) could achieve about 56% prediction power of the full model (R = 0.81). And there are 110 combinations achieving more than 90% prediction power of the full one. These analyses indicate that most of these features are highly redundant for chromatin accessibility. The previous analyses suggest that both histone modification features and transcription factor binding features are predictive for chromatin accessibility with high accuracy in DNase I hypersensitive sites. So, there is a question that whether the prediction power will increase if we use all these features. To address this question, we directly predicted the “openness” of chromatin using all features. As shown in features . FocusinP < 0.01, hypergeometric test) in the set of 110 models. Interestingly, all these features showed high prediction powers in the one-feature models except H4k20me1 and SUZ12. H4k20me1 is a particular one, which has been reported for the most predictive histone modification for gene expression [By examining the 110 high prediction power combinations, we found that seven chromatin features, H3k4me2, H3k4me3, H3k9ac, H4k20me1, SIN3A, ZNF143, SUZ12, were significantly enriched  in human embryonic stem cell (H1hesc) line. We found that different chromatin features showed different location preference in DHS. This may be due to the particular function of different chromatin features. Thurman et al. have done similar analysis in K562 cell line  for TF bOur results demonstrate that both histone modification (HM) features and transcription factor (TF) binding features account for nearly 58% variance of chromatin accessibility in H1hesc cell line. For histone hallmarks, many activators of gene expression exhibited important impact on the “openness” of chromatin, such as H3k4me  and histIt is generally accepted that cellular factors regulate the complex dynamic change of chromatin structure in a collective manner. We have shown that these features is highly redundant to predict chromatin accessibility and a small subgroup of features are able to achieve a very high prediction power. However, the mechanism of how these features cooperatively impact the openness of chromatin is still unclear, and we must note that our analysis could not reveal the “cause” or “consequence” relationship of HM and TF binding features to chromatin accessibility. Histone modifications play an important role in creating and maintaining the accessible chromatin environment  and may We present genome-wide quantitative analysis of the impact of chromatin features to chromatin accessibility in DNase I hypersensitive sites. Our findings indicate that both histone modifications and the binding of transcription factors could explain nearly 58% variation of the “openness” of chromatin structure. The combinatorial effect analyses reveal that these chromatin features are highly redundant for prediction and H3k4me2, H3k4me3, H3k9ac, SIN3A, and ZNF143 show closest association with chromatin accessibility. Our results provide insights into the systematic effects of chromatin features to differential chromatin accessibility.Online Supporting Information S1. The prediction powers using all features with different sample sizes. In each sample size, we randomly sampled 500 times and modeling according to the procedure discussed in method 2.3 in each sample.Online Supporting Information S2. The input maximum signal dataset including the maximum signals of Chip-seq and DNase-seq in 5000 DNase I hypersensitive sites.Online Supporting Information S3. The input average signal dataset including the average signals of Chip-seq and DNase-seq in 5000 DNase I hypersensitive sites.Online Supporting Information S4. The prediction powers (R) using only one feature.Online Supporting Information S5. The prediction powers (R) using all possible two-feature combinations.Online Supporting Information S6. The prediction powers (R) using all possible three-feature combinations.Online Supporting Information S7. The related R codes are available.Click here for additional data file.


The Transmissible Spongiform Encephalopathies (TSEs) are a group of rare neurodegenerative diseases, which can be transmitted between members of the same species and possibly across different species. The link between the emergence of Bovine Spongiform Encephalopathy (BSE) and the new variant form of Creutzfedlt Jakob Disease (vCJD) has been the cause of much public concern. vCJD is the most widely known of the human TSEs but by no means the most common; inherited and sporadic forms are much more prevalent. The agent responsible for these diseases is a conformationally altered form of a normal cell surface glycoprotein, called the prion protein (PrP). The normal isoform must be present for the disease to progress, and disease incubation time decreases with increased PrP expression. There is still no cure for any of these diseases but recent advances in the understanding of how prion protein expression is regulated at the genetic level, and of exogenous factors modulating expression levels, may provide new insights into potential therapeutic targets for disease management by down regulation of cellular PrP levels. The emergence of the TSEs is not a new event; however before the BSE epidemic in the 1980s their existence was virtually unknown. Human TSEs include, in addition to the widely known vCJD, hereditary forms of CJD, Gerstmann-Sträussler-Scheinker syndrome, fatal familial insomnia and Kuru. In addition, CJD can occur sporadically, possibly caused by somatic mutation in the prion gene. Sporadic and hereditary TSEs account for the majority of human cases .TSE diagnosis is problematic. By the time of symptomatic presentation the disease is advanced, and there is currently no way to reverse the damage. Therefore early diagnosis is essential to maintain the quality of life of the patient. However, currently this is not possible since definitive diagnostic techniques require brain tissue post mortem. This difficulty diagnosing TSEs, accompanied by the long incubation periods reported for these diseases, has impacted on the health service in other areas including the risk of disease transmission through the use of human pituitary derived hormones, by cadaveric grafts, or by transmission from blood or blood products -8.sc during disease  male with advanced vCJD . PrPsc is the disease related form of a normal cellular protein (PrPc). PrPc is a glycophosphatidylinositol (GPI) anchored cell surface glycoprotein. It binds copper via a highly conserved repeat domain in its mainly unstructured N-terminal region, and its C-terminal structured region has high alpha helical content  devised to identify this proteinacious infectious particle . The inf content -17. Whenfunction , 19, and storage , 21, pro storage , 23, sig storage -27, cell storage , 29, and storage , 31. Thec is converted to PrPsc is still a matter of debate. Conversion is thought to occur as a post-translational modification of PrPc, as opposed to a folding mistake during PrPc synthesis. PrPsc would act as a catalyst for this modification. What is certain is that endogenous PrPc is required for conversion and so disease establishment. PrPc knockout mice are resistant to infection with scrapie  or by micro RNAs (miRNAs) binding to sites within the mRNA sequence; and regulation of the protein itself by turnover mechanisms within the cell. The control of transcription is thought to be the most important factor for regulation of protein levels.Eukaryotic promoter control is extremely complex. A pre-initiation complex (PIC) must assemble around the appropriate sequence of DNA, functioning to first uncoil supercoiled DNA, and second to allow the attachment of DNA polymerase and other proteins forming the transcription apparatus, which unzips, transcribes and rezips the DNA of the gene. The PIC is a multi-protein complex, which includes general transcription factors, such as TFIIA - H, and DNA polymerase II. Many genes have a TATA box motif, which provides a binding site for transcription factors, located approximately 25 base pairs upstream of the transcription start site (TSS). For genes lacking a TATA box, prior to the TSS there is an initiator region and this determines the strength of the promoter. In addition to this promoter region, genes may have other regulatory regions, which are usually  located 5’ to the promoter region and may be thousands of base pairs away from the TSS. Depending on the transcription factors that bind them, these regions may enhance or inhibit protein expression , 40.prnp) found that both prion isoforms (PrPc and PrPsc) were encoded by the same gene, and that no evidence of gene rearrangement was seen when comparing scrapie infected tissues to uninfected tissues . In addition, several features typical of housekeeping genes were identified in the promoter (the region of DNA upstream of the putative transcription start site) including a GC rich region lacking a TATA box and three repeats of a sequence encoding Sp1 binding sites. Sp1 factors bind to these GC rich regions and, by direct protein–protein interaction of factors binding adjacent sites, loops the DNA to synergistically activate the gene by directly or indirectly recruiting proteins of the transcription apparatus , which can enhance or inhibit promoter activity dependant on what transcription factors bind to them , myocyte enhancer factor-2 (MEF2), Octamer 1 (Oct-1), myelin transcription factor 1 (MyT1), and nuclear factor of activated T-cells (NFAT).The role of intron 1 in promoter control is further supported by evidence from Premzl et al. . This stThe finding of control elements inside intron 1 is not unusual. Many genes have conserved regulatory regions located within the intron sequences, which may contribute to the control of gene expression -56. Contprnp mRNA and protein expression by 1.5 to 2.5 fold in human cells, and two heat shock elements have been detected in the rat prion promoter , a signalling kinase that modulates transcription factor production and activity   is a highly reactive radical used as a signalling molecule by cells. It has been found that PrPe (nNOS) . Investie (nNOS) , 64, impc at the protein level  or MRE-like sequences. Within the bovine prnp, an inverted MRE at position –2070 and two MRE-like elements at positions –2653 and -2599, differing from the MRE sequence by just one nucleotide, have been located by sequence analysis  is a drug used for the treatment of promyelocytic leukaemia. It is an effective treatment, sending the disease into remission by inducing terminal differentiation of the malignant clone. ATRA has been found to down regulate PrPpression . It is p species .prnp, indicating that ATRA may be more likely to exert a secondary effect through activation of transcription factors rather than direct interaction of RAR with prnp  allowing it bind to Retinoic Acid Response Elements (RAREs) either as a homodimer or as a heterodimer with Retinoic X receptor (RXR). The RAR can act as an enhancer or a repressor of transcriptional activity depending on the orientation in which it binds to DNA . Once bop Figure .ATRA was also found to down regulate PrP expression by , who proc levels, factors that down-regulate expression may have a potential role in disease therapy or management. It might be possible that ATRA and other similarly reacting agents could be used to slow the progression of the disease.Given the correlation of disease progression with PrPc levels may become depleted due to conversion to PrPSc. The loss of function associated with this change, as well as altered metal ion concentrations, could result in the cell up-regulating prnp. This may cause increased levels of PrPc, increased substrate for the conversion reaction, and a further increase in promoter activity causing the disease to progress in an exponential fashion. Down-regulating the promoter and breaking the cycle could be a very important method of therapeutic intervention. In this way, agents that might alter prnp regulatory pathways resulting in PrPc protein down-regulation may have a role in disease management. Copper modulates prnp activity, but this reaction appears variable across different cell lines (prnp could be useful. Copper chelators would have limited application in disease management due to the importance of copper in various enzyme systems including anti-oxidant enzyme such as superoxide dismutase (SOD).During the early stages of disease progression endogenous PrPll lines , 67, so prnp and PrPc expression  has previously been suggested as a potential therapeutic agent for TSE treatment due to findings that the accumulation of PrPhamsters . DMSO ishamsters , 74. In hamsters . The oxiprnp and result in a decrease in the quantity of PrPc protein produced by the cell. Antioxidant replacement, in addition to potentially down regulating PrPc protein expression, could also counteract decreased activity of cellular SODs seen during disease pathogenesis due to aberrant metal metabolism. Mitochondrial SOD/SOD2 synthetic mimetics that can cross the blood brain barrier have been shown to protect SOD2 null mice against spongiform encephalopathy that results due to the null phenotype and may have a potential use in treatment of TSEs (Factors that could maintain low cellular levels of oxidative stress may down-regulate the activity of  of TSEs . Agents c expression is complex. It involves not only the promoter and regulatory regions preceding the promoter, but also intron 1. These control regions may provide targets for controlling PrPc expression levels. Since PrPc is required for disease establishment, and the rate of disease progression is directly related to the level of endogenous PrPc, factors able to down regulate PrPc expression levels could have a role in the management of the TSEs. Such a strategy would require the discovery of compounds that could not only effect the expression of PrP but also that could be delivered into the CNS and enter the cells where PrP conversion occurs. Drug delivery could be the main barrier to develop a strategy related to regulating PrP expression to combat prion diseases. However, such concerns are barriers for most dug based therapeutic strategies. Therefore, a new approach, such as gene regulation, could increase the possibility of finding the appropriate target for a via therapeutic strategy for TSEs.The control of PrP