Nuclear remodeling to a condensed state is a hallmark of spermatogenesis. This is achieved by replacement of histones with protamines. Regions retaining nucleosomes may be of functional significance. To determine their potential roles, sperm from wild type and transgenic mice harboring a single copy insert of the human protamine cluster were subjected to Micrococcal Nuclease-seq. CENTIPEDE, a hierarchical Bayesian model, was used to identify multiple spatial patterns, "footprints", of MNase-seq reads along the sperm genome. Regions predicted by CENTIPEDE analysis to be bound by a regulatory factor in sperm were correlated with genomic landmarks and higher order chromatin structure datasets to identify potential roles for these factors in regulating either prior or post spermatogenic, i.e., early embryonic events. This approach linked robust endogenous protamine transcription and transgene suppression to its chromatin environment within topologically associated domains. Of the candidate enhancer-bound regulatory proteins, Ctcf, was associated with chromatin domain boundaries in testes and embryonic stem cells. The continuity of Ctcf binding through the murine germline may permit rapid reconstitution of chromatin organization following fertilization. This likely reflects its preparation for early zygotic genome activation and comparatively accelerated preimplantation embryonic development program observed in mouse as compared to human and bull. Spermatogenesis is characterized by a series of morphological changes resulting in a motile, haploid and highly condensed cell. This is achieved in part through the compaction and restructuring of its nuclear architecture. The haploid expression and progressive deposition of transition proteins (Tnp) and protamines (Prm) within the chromatin fiber displaces the majority of histones from the double helixNuclease mapping in conjunction with high-throughput DNA sequencing has become a powerful tool to rapidly and efficiently survey chromatin landscapes678Genomic regulation requires the ordered positioning of DNA within the limited confines of the nucleus. This is accomplished primarily through the folding and looping of chromatin which simultaneously permits interactions between distant genomic regions while reducing the physical volume of the genome. These structural features can be globally mapped through the use of high throughput proximity ligation assays 1012To understand the cell type specific chromatin packaging strategy employed within the male gamete, mouse sperm were nuclease digested and the concomitant released nucleosome-associated DNAs subjected to high throughput sequencing. The susceptibility of the spermatozoon to enzymatic dissection was compared in sperm from wild type mice and a homozygous transgenic mouse model harboring a single copy insert of the human protamine locus. This 40 kb sequence was stable over many generations and did not alter spermatogenesis or impact fertilityNucleosome-associated DNAs were released from wild type and transgenic mouse sperm with either Micrococcal Nuclease (MNase) or DNA fragmentation factor (DFF)151618In contrast to a prior study that interrogated crosslinked mouse sperm chromatin, nucleosome coverage was not elevated within gene deserts 20. Sperm6Testis RNA and sperm protein levels were analyzed to determine if the absence of altered chromatin structure in transgenic sperm was due to transcriptional/translational regulation or impaired incorporation of the transgenic proteins during chromatin condensation. RNA-seq analysis of total transgenic testis RNAs demonstrated that the transgenes were transcribed but exhibited reduced expression relative to their orthologs and analogs in mouse and human testis (GSE69434), respectively . The aveTo identify potential causes of transgene suppression nuclease sensitivity within the transgenic and human protamine loci were compared. MNase digestion of transgenic mouse and human sperm chromatin demonstrated that the human protamine locus exhibited elevated nuclease sensitivity in either context . HoweverCandidate chromatin and genomic features that may contribute to haploid PRM transcription and nuclease sensitivity in sperm were identified within 5 Mb regions centered on the protamine loci . Analysi11The chromatin domains harboring the endogenous and transgenic protamine loci exhibited varied amounts of intrachromosomal contacts. Domain structure is known to be demarcated by Ctcf binding which is also responsible for mediating the DNA looping events. Analysis of round spermatid Ctcf ChIP-seq data23Round spermatid ChIP-seq and sperm MNase-seq data were used to infer the binding status of Ctcf. In mature sperm this factor is predicted to remain bound to conserved motifs within the endogenous and transgenic protamine loci. In wild type mice this association was verified in the preceding cell type and presumed to be similarly bound within the transgenic sequence. This suggested that motifs contained within the transgenic protamine locus could be accessed and bound by their cognate factors. Therefore, suppression of the transgenes was likely not to due blocked protein binding within the integrated locus. However, removed from its endogenous chromatin domain the transgenic protamines would be reliant upon factor(s) binding to neighboring DNA elements to contribute to locus control.To determine whether the mouse spermatozoal chromatin landscape contains factors of potential regulatory importance in addition to Ctcf, sites corresponding to known position weight matrices (PWMs)27nd most abundant of these factors in testis  identified a subset of overlapping motifs utilized by the homeobox domain protein family n = 27;  but exhin testis . The EsxApproximately 95–99% of the histones have undergone replacement by protamines following spermatogenic nuclear remodeling in mouse, yet MNase digestion of sperm chromatin reveals a similar relationship between several chromatin binding proteins and nucleosome periodicity in the histone-depleted gamete. Recapitulating observations from somatic cells3334−16 – 6.2 × 10−286). Rest, Foxj2, and Pou2f1 sites in sperm were also significantly enriched within promoters of genes expressed in the male germline (P < 8.2 × 10−6–1.9 × 10−79), residing within regions marked by active histone modifications in testis. Motifs bound by Foxj2 and Pou2f1 were found within 4,386 testis promoters suggesting that these transcription factors are important regulators of spermatogenic transcription. A similar analysis of all RefSeq gene promoters demonstrated that only Rest exhibited a significant enrichment within this broad set of regions (P < 2.5 × 10−171). Ctcf sperm footprints were not enriched in the above promoter sets but were significantly associated with predicted testis enhancers reflecting the role of this factor in regulating chromatin interactions (P < 3.6 × 10−224). Bound motifs corresponding to Foxj2 and Rest were also significantly associated with testis enhancers though to a lesser degree .To infer likely prior and future functions of the bound motifs observed in mature sperm chromatin, their occupancy in known regulatory regions and promoters were compared. Analysis of ENCODE testis ChIP-seq datasets highlighted associations between nuclease footprints and active chromatin featuresTo identify candidate regulators of protamine transcription the distribution of sperm nuclease footprints was determined within the 5 Mb search regions  housing 2337−3–5.5 × 10−8). Transcription of these sequences has recently been demonstrated as necessary for zygotic maturation−6 and P < 2.5 × 10−4, respectively).The group of homeobox domain motifs identified by hierarchical clustering did not exhibit a significant association with testis promoters or regulatory regions. Rather this group of related factors, including Hoxd8 (Homeobox D8), Tlx2 , and Lhx5 (LIM homeobox protein 5), were significantly enriched upstream of ribosomal RNA sequences (P < 2.7 × 10−38). In total the merged set of bound homeobox domain motifs overlapped 31% of all olfactory receptor gene promoters (354/1130). The alternative Pou2f1 motif was also significantly enriched within these regions . Similarly, a set of Ctcf nuclease footprints was enriched within the promoters of genes differentially expressed in mouse embryo pronuclei relative to oocytes .Ctcf footprints identified in sperm significantly overlapped ChIP-seq peaks associated with this factor in round spermatids  to a greater degree than unbound sites .ChIP-seq analysis of Ctcf binding in round spermatids and CENTIPEDE footprinting in mature sperm suggest that of the 42,493 Ctcf peaks identified in the prior cell type approximately 82% are evicted during the histone-protamine transition. Motifs that remain occupied in mouse sperm are significantly enriched within Ctcf ChIP-seq peaks from testis and embryonic stem cells, although the sites occupied by this factor in sperm are relatively few in number  exhibited a greater degree of conservation than sites lacking a nuclease footprint , buffered with 50 mM Tris-HCl, pH 7.9. The sample was digested for 5 minutes and the reactions were stopped with the addition of 0.5 M EDTA pH 8.0 to a final concentration of 20 mM. The cell suspension was then rotated at 4 °C for 30 minutes prior to centrifugation at 20,000 rcf for 10 minutes. Sperm digested with DNA Fragmentation Factor (DFF) were similarly collected and permeabilized. Following washing sperm were resuspended to 5 × 106 cells/mL in 1x NEB1  (New England BioLabs), supplemented with 10 mM dithiothreitol. Following incubation at 37 °C for 30 minutes the sperm suspension was diluted to 2.5 × 106 cells/mL with prewarmed 1x NEB1. The sample was digested for 16 hours at 37 °C following the addition of 10 units Tobacco Etch Virus (TEV) protease and 24 of μl DFF enzyme.All procedures were carried out with Wayne State University IRB approval. Animal protocols were carried out in accordance with the approved guidelines of Wayne State University Animal Protocol IACUC A 12-01-13. The use of human tissues was approved by the Wayne State University Human Investigation Committee and carried out under Wayne State University Human Investigation Committee IRB Protocol 095701MP2E(5R). All human samples used in this study were obtained after informed consent. Wild-type C57BL/6 mice were purchased from Charles River Laboratories, Inc, Wilmington, MA. Homozygous transgenic mice from transgenic line HP3.1 were bred as describedHuman sperm nucleosome libraries were prepared as above with the following adjustments. Following liquefaction sperm were washed twice and frozen as dry pellets in liquid nitrogen. Sperm were thawed on ice and washed twice with PBS prior to permeabilization with Triton X-100 and subject to nuclease digestion as above.Enzymatically released soluble DNAs were recovered from the supernatant to a fresh screw cap tube and digested overnight with proteinase K at 55 °C in the presence of 1% β-mercaptoethanol. The remaining sperm pellets were washed once with PBS and similarly digested by proteinase K alongside tail clips from the sacrificed mice. The DNAs were recovered by phenol–chloroform extraction, precipitated with ethanol and quantified with Picogreen (Invitrogen). Genomic DNA from wild type and transgenic tail clips were digested with MNase and purified as above. Mononucleosome DNA fragments were resolved by gel electrophoresis and extracted from separate agarose plugs with the Qiagen MinElute Gel Extraction kit. Digested control genomic DNAs were gel size selected (~150 bp) and similarly purified. Recovered DNAs were quantified as above and used to construct multiplexed DNA sequencing libraries with the NEBNext ChIP-Seq kit (New England BioLabs). All libraries were subjected to 50 cycles of paired-end sequencing on the Illumina HiSeq 2500 or MiSeq platforms.Total RNAs were separately isolated from the decapsulated testes of four transgenic adult mice. Following homogenization in 0.5 ml RLT buffer (Qiagen) supplemented with 1.5% β-mercaptoethanol (Amresco) with a PRO Scientific 200 homogenizer , RNAs were extracted as described62DNA sequencing libraries were aligned to the mouse genome assembly mm10 with Bowtie (version 2.0.2)Transgenic testis RNA sequencing libraries were aligned to the custom mm10 genome with Tophat (version 2.0.9)http://promoter.bx.psu.edu/hi-c/)11Published single-end datasets used in the current study were restricted to a similar criterion ignoring the paired requirement. Processing of alignment files, including midpoint and 5′ calculations, genomic intersections, and Jaccard statistics were carried out with the samtools (version 0.1.19)73Basic protamines were independently isolated from wild type and transgenic cauda epididymal mouse sperm and ejaculated human sperm. All samples contained at least 10 million cells. Spermatozoa were lysed by hypotonic shock and the chromatin solubilized as described4. Genomes were scanned to identify sequences that best conformed to known position weight matrix motif (PWM) models for each factor tested2 likelihood ratio between the probability that the sequence is generated by the PWM model and the background probability . Motif instances with a PWM value >13 were selected . Motifs instances within a 2 kb window exhibiting a mappability score ≥99% were ranked according to their PWM values and the top quintile used for the primary footprinting analysis. The average conservation score  was calculated for each motif. The average 5-base percent GC dinucleotide frequency immediately up- and downstream of each site, excluding the motif sequence, was also calculated to determine the potential impact of sequence context on binding predictions or as a possible experimental confounder. To infer the binding status of a site the CENTIPEDE algorithm was applied to approximately 2 kb windows centered on each selected motif (motif ± 1 kb). CENTIPEDE uses a negative-multinomial distribution to model the total number of reads but also the spatial pattern of fragment midpoints around the motif instances. The model is specific for each TF motif, and then a posterior probability of binding is reported for each motif instance. Subsequently, a generalized linear model was used to evaluate the predictive value of the three scored variables  and the posterior probabilities of those factors:Sequencing read midpoint coordinates and motif positions were prepared for nuclease footprinting analysis with in-house scripts prior to implementation of the CENTIPEDE algorithm in Rl, PMWl is the PWM value and GC and PhastCons represent the average 5-base percent GC dinucleotide frequency flanking the motif and the conservation score of the motif, respectively. A z-score was calculated for each of the coefficients . Factors for which the Z-score associated with the PWM values were greater than or equal to 5 were used for further analysis. Note that the Z-score should not be confused with the values of the dependent variables of the logistic model (1) as it measures by aggregating all the motif locations genome-wide the statistical association between the variables and the footprint locations with high CENTIPEDE posterior values. Within this set of factors motifs exhibiting a posterior probability ≥0.95 were considered bound. The extended analysis of the 5 Mb search regions was performed as described with the following changes. All sites identified within the search regions meeting the following criterion were included in the footprint analysis regardless of their PWM rank: mappability scores ≥90%, PWM values ≥14. A reduced stringency analysis of potential Ctcf sites was also undertaken in which all motifs with a PWM value ≥13 were evaluated. The completed set of occupied Ctcf sites in sperm were used to intersect spermatid ChIP-seq peakswhere Footprints were lifted over to Mm 9 genome build for comparisons with ENCODE datasets36Accession Number: GEO accession number: GSE78075. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi.How to cite this article: Johnson, G. D. et al. Nuclease Footprints in Sperm Project Past and Future Chromatin Regulatory Events. Sci. Rep.6, 25864; doi: 10.1038/srep25864 (2016).


We have found that interferon production is suppressed by compounds that prevent bromodomains from interacting with acetylated histones at the interferon gene promoter. This is a new way in which interferon production is regulated to combat bacterial or viral infection. IFNB  gene transcription induced by ligands that activate TLR3 (Toll-like receptor 3) and TLR4. In the present study, we found that BI-2536 is likely to exert this effect by preventing the interaction of the transcription factors IRF3 (interferon-regulatory factor 3) and c-Jun with the IFNB promoter, but without affecting the TBK1 {TANK [TRAF (tumour-necrosis-factor-receptor-associated factor)-associated nuclear factor κB activator]-binding kinase 1}-catalysed phosphorylation of IRF3 at Ser396, the dimerization and nuclear translocation of IRF3 or the phosphorylation of c-Jun and ATF2 (activating transcription factor 2). Although BI-2536 inhibits few other kinases tested, it interacts with BET  family members and displaces them from acetylated lysine residues on histones. We found that BET inhibitors that do not inhibit PLKs phenocopied the effect of BI-2536 on IFNB gene transcription. Similarly, BET inhibitors blocked the interaction of IRF5 with the IFNB promoter and the secretion of IFNβ induced by TLR7 or TLR9 ligands in the human plasmacytoid dendritic cell line GEN2.2, but without affecting the nuclear translocation of IRF5. We found that the BET family member BRD4 (bromodomain-containing protein 4) was associated with the IFNB promoter and that this interaction was enhanced by TLR3- or TLR4-ligation and prevented by BI-2536 and other BET inhibitors. Our results establish that BET family members are essential for TLR-stimulated IFNB gene transcription by permitting transcription factors to interact with the IFNB promoter. They also show that the interaction of the IFNB promoter with BRD4 is regulated by TLR ligation and that BI-2536 is likely to suppress IFNB gene transcription by targeting BET family members.PLK (Polo-like kinase) inhibitors, such as BI-2536, have been reported to suppress  IFNB gene). The activation of these receptors leads to the recruitment of the adaptor protein, TRIF [Toll/IL-1R (interleukin 1 receptor) domain-containing adaptor inducing IFNβ], which triggers the activation of TBK1 {TANK [TRAF (tumour-necrosis-factor-receptor-associated factor)-associated nuclear factor κB activator]-binding kinase 1} complexes by a mechanism that is not yet understood. Once activated, TBK1 complexes catalyse the phosphorylation of IRF3 (interferon-regulatory factor 3), which is followed by the dimerization of IRF3 and its translocation to the nucleus, where it binds to IFNB promoters to stimulate IFNB gene transcription } method.RAW cells (1.5×10promoter  and the promoter  have beeIfnb mRNA induced by either poly(I:C)  or LPS  was also prevented by the inclusion of BI-2536 (1.0 μM). In contrast, BI-2536 did not suppress the poly(I:C)-stimulated . Consistent with these observations, the production of imulated A or LPS-imulated B activatted , indicating that it does not affect the interaction of IFNβ with IFNAR, or the activation or activity of JAK1 or TYK2. These findings indicated that the initial steps in the positive-feedback loop (see the Introduction) were unaffected by BI-2536.The inclusion of BI-2536 in the cell culture medium had no effect on the IFNβ-stimulated phosphorylation of STAT1 at TyrIfnb mRNA in primary bone-marrow-derived macrophages is unaffected up to 2 h by the potent and specific JAK inhibitors ruxolitinib and tofacitinib  phosphorylates IRF5 at Sercription . Similar6 or JQ1 D.Ifnb gene transcription induced by LPS, poly(I:C) or viral infection  and PCAF (p300/CBP-associated factor) are reported to be needed for Ifnb gene transcription [Ifnb promoter by activating these or other HATs and/or by inhibiting HDACs is unknown, but viral infection has been reported to induce the localized hyperacetylation of histones at the Ifnb promoter [Interestingly, poly(I:C) and LPS enhanced the association of BRD4 with the hibitors C–4F. To cription ,44. Whetpromoter . AlternaThe finding that compounds developed as protein kinase inhibitors interact strongly with the bromodomains of BET family members and prevent their interaction with acetylated lysine residues ,46 has fSalmonella enterica serotype Typhimurium delayed or prevented the death of these mice, whereas a single injection of I-BET administered after LPS had already induced inflammation overcame this inflammatory condition [The overproduction of IFNβ is a major cause of endotoxaemia and endotoxic shock in mice, since mice lacking expression of the genes encoding IFNβ or IFNAR are resistant to LPS-induced endotoxaemia ,47,48. Iondition . BI-2536ondition , and onlondition ,52. Thes


Anabaena sp. PCC 7120, the ferric uptake regulator FurA functions as a global transcriptional regulator. Despite several analyses have focused on elucidating the FurA-regulatory network, the number of target genes described for this essential transcription factor is limited to a handful of examples. In this article, we combine an in silico genome-wide predictive approach with experimental determinations to better define the FurA regulon. Predicted FurA-binding sites were identified upstream of 215 genes belonging to diverse functional categories including iron homeostasis, photosynthesis and respiration, heterocyst differentiation, oxidative stress defence and light-dependent signal transduction mechanisms, among others. The probabilistic model proved to be effective at discerning FurA boxes from non-cognate sequences, while subsequent electrophoretic mobility shift assay experiments confirmed the in vitro specific binding of FurA to at least 20 selected predicted targets. Gene-expression analyses further supported the dual role of FurA as transcriptional modulator that can act both as repressor and as activator. In either role, the in vitro affinity of the protein to its target sequences is strongly dependent on metal co-regulator and reducing conditions, suggesting that FurA couples in vivo iron homeostasis and the response to oxidative stress to major physiological processes in cyanobacteria.In the filamentous cyanobacterium  Cyanobacteria are oxygen-evolving photosynthetic prokaryotes found in virtually all ecosystem habitats on the Earth . As primSeveral large-scale studies have indicated that primary production and nitrogen fixation in the open ocean is greatly influenced by iron bioavailability ,7, thereBecause iron is scarcely soluble in aqueous environments at neutral pH, cyanobacteria have evolved strategies to efficiently scavenge ,12, to i2+ complexes to cis-acting regulatory elements known as Fur boxes, located in the promoter regions of iron-responsive genes  and shaking (120 rpm). Chlorophyll a (Chl) was determined in methanol extracts , re-suspended in the same iron-free medium and further grown for 72 h. Glassware used in these experiments was soaked with 6 M HCl and extensively rinsed with Milli-Q water to remove residual iron. For transcriptional analyses during heterocyst differentiation, the Anabaena sp. strains were cultured as previous described (3 (BG-110) and resuspended in the same nitrogen-free medium. Cultures were further incubated until mature heterocysts were observed .For iron depletion experiments, exponentially growing filaments (3–5 µg Chl/ml) from standard BG-11 were collected by filtration, washed three times with BG-11 medium without iron (BG-11escribed . ExponenAnabaena sp. PCC 7120 FurA protein was expressed in Escherichia coli BL21 (DE3) and purified according to previously described methods (Supplementary Table S1. Electrophoretic mobility shift assays (EMSA) were performed as described previously  gene was included as non-specific competitor DNA in all assays , which means that most of non-cognate sequences resulted in negative scores. The score range of a weight-matrix is defined as the values between the minimum and the maximum scores that can be obtained for the sequence more dissimilar to the model and the consensus sequence, respectively. The matrix used in our study had a score range between −41.7 and 17.2 bits. The score distribution of the non-cognate sequences indicated that most of them obtained negative scores, which constitutes the expected behaviour for a matrix with a good classification performance. In contrast, the sites recognized by the transcriptional regulator in experimental determinations scored at higher values, close to the matrix maximum score. The statistical assessment of the performance of our model showed that the matrix was effective at discriminating between cognate and non-cognate sites since for the selected cut-off score of 10 bits, the parametric ℘-value for distribution comparison is rather low (7.43 × 10−5), with a significance value of 0.01% .In order to characterize the FurA regulon in the nitrogen-fixing cyanobacterium g assays ,36. Afteitations , we haveAnabaena sp. PCC 7120, including the chromosome and all the six natural cytosolic plasmids .Given the high performance of the matrix built, we scanned the complete genome of plasmids , to locaPredicted FurA-binding sites were identified upstream of 101 genes with known or putative functions according to the cyanobacteria genome database CyanoBase . Severalalr0397 (schT), alr3242 (hutA2) and all1101, all of them coding for TonB-dependent receptors, as well as the nine-gene cluster all2649-all2641 encoding polyketide synthases and non-ribosomal peptide synthetases involved in siderophore biosynthesis , a probable Zn2+/Fe2+ permease , the znuAB operon  encoding components of a high affinity zinc-uptake system , and a cation-efflux system protein . Given the connection between iron homeostasis and oxidative stress, it was not surprising that candidate FurA-binding sites were associated to genes encoding proteins involved in defences against oxidative stress, such as the flavodiiron protein Flv3  or the putative alkylhydroperoxidase encoded by gene all5371.As expected for the master regulator of iron homeostasis , predictynthesis . Howeverynthesis , includiease all03, the znasl7641), the bacteriorhodopsin Asr  and the adenylate cyclases CyaD and CyaC . In addition, Fur-binding sites were found upstream of three genes encoding transcriptional regulators , as well as in the promoter regions of at least other 10 genes encoding proteins involved in signal transduction mechanisms  or cytochrome c oxidase . High-score FurA-binding sites were detected not only upstream of the iron-stress-induced flavodoxin (isiB), but also in front of the gene encoding the photosystem (PS) I subunit psaK (asr4775).As expected, photosynthesis and respiration contained several predicted FurA targets encoding iron-containing enzymes, e.g. NADH dehydrogenase , patA  and patS (asl2301). It is worth noting that the Fox gene alr1728 , the pentose phosphate cycle , as well as the biosynthesis of fatty acids , amino acids , riboflavin  and peptidoglycan . Curiously, putative FurA-binding sites were detected in several transposases . In the experimental validation, we made special emphasis in putative novel targets involved in distinctive processes of cyanobacteria as microbial group, such as oxygenic photosynthesis, heterocyst differentiation or light-dependent signal-transduction mechanisms, among others. EMSA analyses were carried out using 300- to 400-bp-DNA fragments corresponding to the promoter regions of each selected gene, encompassing the predicted FurA-binding sites. To confirm the specificity of bindings, all assays included the promoter region of the itor DNA . The impown gene  and isiAne  and NADH dehydrogenases , a fact that presumably occurred as a consequence of the metal co-repressor scarcity. However, despite the in vitro affinity of FurA strongly depended in all cases of the presence of metal co-repressor , the expression of several target genes like znuA, amt4, aphC, psaK, alr0240 and pbpH did not increase but rather decreased under iron deprivation (Supplementary Table S3). Decrease in transcript abundance of such FurA direct targets under iron limitation could reflect an iron-dependent transcriptional activation by FurA, a fact previously observed with other FurA targets  were clearly induced under the same environment (Supplementary Table S3), suggesting an iron-dependent transcriptional activation of FurA on the expression of these novel targets. A slightly inductive effect of FurA overexpression was also observed in the ferric-dicitrate permease encoding gene all2586 (Supplementary Table S3), although this fact was relatively expected according to our experience, since a similar behaviour has been observed with all the iron metabolism players so far described as FurA targets . It was remarkable the strong induction of Anabaena bacteriorhodopsin Asr under iron starvation, even in a FurA overexpression phenotype.In most cases, the depletion of metal co-regulator mitigates the transcriptional effect of FurA overexpression, either when the protein acted as repressor or as activator of gene expression. Some FurA-repressed targets including Supplementary Table S4, the overexpression of the metalloregulator led to a clear increase in transcript abundance of hetC, alr1728 and patA, while influence on asr1734 transcription level was quite weak. However, the slight induction of the heterocyst differentiation regulator Asr1734 could be in fact the result of a FurA-mediated transcriptional activation, maybe diminished or modulated by the variety of other co-acting signals that influence the heterocyst development  annotated in the Anabaena sp. PCC 7120 genome . Considering the different models proposed to discern the stoichiometry of Fur–DNA interactions , as proposed by Napolitano and co-workers with the FurB/Zur paralog from Anabaena sp.  encoding seven non-ribosomal peptide synthetases and two polyketide synthases involved in the biosynthesis of siderophores . As we could infer from the in vitro DNA-binding assays, the FurA transcriptional modulation depended in all cases on the presence of metal co-regulator and reducing conditions. Despite Fur-mediated direct activation as been observed in several heterotrophic bacteria  are co-modulated by other transcriptional regulators that have the opposite effect to FurA under iron limitation. Hence, downregulation of possible activators or the induction of another repressor under low-iron environment could explain the transcriptional response observed in these FurA-regulated genes. That is the case of znuAB operon, which encodes components of a high-affinity zinc uptake mechanism and is co-regulated in Anabaena sp. PCC 7120 by FurB/Zur  constitutes ∼2.4% of the protein-encoding genes in PCC 7120 . ORFs asPCC 7120 . TranspoPCC 7120 . TranscrAnabaena sp. PCC 7120, a filamentous cyanobacterium commonly used as a model organism for studying processes such as photosynthesis, nitrogen fixation, cell differentiation and multicellularity in prokaryotes. Our genome-wide prediction of candidate FurA-binding sites supported by experimental validations is particularly relevant given the potentially essential role of this metalloregulator in the physiology of Anabaena sp. . Funding for Open Access: MINECO [BFU2012-31458].Conflict of interest statement. None declared.


HMGA1 gene had significantly smaller islets and decreased insulin content in their pancreata, suggesting that HMGA1 may have a direct role in insulin transcription and secretion. Herein, we investigate the regulatory roles of HMGA1 in insulin transcription. We provide evidence that HMGA1 physically interacts with PDX-1 and MafA, two critical transcription factors for insulin gene expression and beta-cell function, both in vitro and in vivo. We then show that the overexpression of HMGA1 significantly improves the transactivating activity of PDX-1 and MafA on human and mouse insulin promoters, while HMGA1 knockdown considerably decreased this transactivating activity. Lastly, we demonstrate that high glucose stimulus significantly increases the binding of HMGA1 to the insulin (INS) gene promoter, suggesting that HMGA1 may act as a glucose-sensitive element controlling the transcription of the INS gene. Together, our findings provide evidence that HMGA1, by regulating PDX-1- and MafA-induced transactivation of the INS gene promoter, plays a critical role in pancreatic beta-cell function and insulin production.The high-mobility group AT-hook 1 (HMGA1) protein is a nuclear architectural factor that can organize chromatin structures. It regulates gene expression by controlling the formation of stereospecific multiprotein complexes called “enhanceosomes” on the AT-rich regions of target gene promoters. Previously, we reported that defects in HMGA1 caused decreased insulin receptor expression and increased susceptibility to type 2 diabetes mellitus in humans and mice. Interestingly, mice with disrupted  Production and secretion of insulin from beta cells of the pancreas maintain glucose homeostasis in vertebrates (from fish to human). Absence or dysfunction of beta cells results in diabetes mellitus, a set of genetically heterogeneous disorders featured by high blood sugar and related complications. The majority of diabetes is type 2 diabetes, which is featured by defects in both pancreatic insulin secretion (beta-cell dysfunction) and peripheral insulin action (insulin resistance) , 2. TherInsulin production in beta cells is controlled at both transcriptional and translational levels . High glINS) gene expression has been characterized by several groups. A 500-bp stretch of DNA upstream of the INS transcription start site controls its transcription. Several cis-acting regulatory sequences reside in this region, with highly conserved A3, C1, E1, and CRE cis-acting regulatory elements  is an architectural transcription factor that binds to the minor groove of AT-rich regions of DNA . This bi animals . Furtherype mice , and reppromoter .INS gene by synergizing with PDX-1 and MafA. Additionally, the effect of glucose on HMGA1 affinity to the INS gene promoter was also investigated.In this study, we investigated whether HMGA1 can directly activate the 35S-labeled PDX-1 and MafA proteins were synthesized in vitro using the TNT-T7 quick-coupled transcription/translation system (Promega), as previously reported , streptomycin (100 μg/ml), 50 μM beta-mercaptoethanol, and 100 mM HEPES buffer (Sigma). Nuclear extracts were prepared from cultured cells as described previously (Human embryonic kidney (HEK) 293 cells and human epithelial carcinoma (HeLa) cells were cultured in DMEM (Invitrogen) supplemented with 10% fetal bovine serum (FBS), 2 mM glutamine, penicillin (100 U/ml), and streptomycin (100 μg/ml) in a humidified 5% COeviously , 42. ForINS genes were amplified from genomic DNA, using modified specific primers (Table phINS-Luc) and mouse (pmINSII-Luc) luciferase (Luc) reporter plasmids. The expression plasmids were as follows: pcDNA3/HA-HMGA1 ; pcDNA3-MafA ; pSG5-ATG-hPDX-1 . For gene silencing experiments, mouse and human anti-HMGA1 small interfering RNAs (siRNAs) (Santa Cruz Biotech) were used. In all knockdown experiments, cells were transfected with 100 pmol of HMGA1 siRNA in 6 well plates, and incubated without further treatment for 72 h before being used in subsequent analyses. Transient transfections of cultured cells were carried out using the Lipofectamine 2000 method (Invitrogen), and Luc activity was assayed 48–96 h later, using the dual-luciferase reporter assay system (Promega) (The promoter regions of human and mouse rs Table . SequencPromega) .2 atmosphere at 37°C. For insulin secretion, INS-1 cells were transiently transfected at 60% confluence with HMGA1 siRNA or negative control siRNA as above. Seventy-two hours later the tissue culture medium was switched to fresh medium containing 5 mmol/l glucose and the cells were grown for additional 18 h. After this, the cells were washed with Hanks’ balanced salt solution (HBSS) containing 140 mM NaCl, 4.7 mM KCl, 1.2 mM KH2PO4, 1.16 mM MgSO4, 20 mM HEPES, 2.5 mM CaCl2, 25.5 mM NaHCO3, 0.2% BSA, and further incubated for 2 h in either low (3 mM) or high (15 mM) glucose condition. Then, the insulin concentration in the medium was measured by a commercial rat insulin ELISA kit (Mercodia Inc.).INS-1 cells (ATCC) were cultured in RPMI-1640 medium (GIBCO) supplemented with 10% FBS, 2 mM glutamine, penicillin (100 U/ml), streptomycin (100 μg/ml), 50 μM beta-mercaptoethanol, 100 mM HEPES, in a humidified 5% COInsI gene promoter were used for PCR amplification of immunoprecipitated DNA, using PCR ready-to-go beads . Rat InsI (NC_005100.3): for 5′-CTGGGAAATGAGGTGGAAAA-3′ (−328/−308 from the trasncription start site); rev 5′-AGGAGGGGTAGGTAGGCAGA-3′ (−108/−88 from the trasncription start site). PCR products were electrophoretically resolved on 1.5% agarose gel and stained with ethidium bromide staining solution. PCR products were confirmed by sequence analysis.Chromatin immunoprecipitation (ChIP) was performed in INS-1 cells as described previously . As soon18S ribosomal RNA in each sample, and cDNAs were synthesized from 2 μg of total RNA using the RETROscript first strand synthesis kit (Ambion). Primers for rat InsI, HMGA1, PDX-1, MafA, and Rps9 were designed according to sequences from the GenBank database . RNA levels were normalized against standard . All PCRt-tests. A p-value <0.05 (two-tailed) was considered significant.All calculations were performed with SPSS 20.0 statistical software (SPSS Inc.). Mean values were compared with INS genes. Binding sites for HMGA1, PDX-1, and MafA were identified within the promoter of the rat Ins gene by sequence analysis with MatINspector . Bioinformatics analysis of the human and mouse INS promoters predicted no HMGA1 binding sites, although the existence of non-recognizable DNA motifs cannot be completely excluded. Instead, binding sites for PDX-1 and MafA were predicted in these promoters as for the rat Ins gene. Consistent with this DNA promoter analysis, the existence of HMGA1 in a cocomplex with PDX-1 was demonstrated previously by us and others in supershift experiments in electrophoretic mobility shift assays using anti-HMGA1 and anti-PDX-1 antibodies, in the presence of the rat InsI E2A3/4 mini-enhancer DNA  alone. An ulterior increase in promoter activity was found in the presence of a combination of two of these transcription factors, while a further additive effect was observed in the promoter activity of phINS-Luc in cells overexpressing all three proteins  together. Comparable or better results were obtained in HEK-293 cells when the mouse Ins promoter (pmInsII-Luc) was utilized for transactivation assays ; drafting of the manuscript ; critical revision and editing of the manuscript . All authors have approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Most genomic variants associated with phenotypic traits or disease do not fall within gene coding regions, but in regulatory regions, rendering their interpretation difficult. We collected public data on epigenetic marks and transcription factor binding in human cell types and used it to construct an intuitive summary of regulatory regions in the human genome. We verified it against independent assays for sensitivity. The Ensembl Regulatory Build will be progressively enriched when more data is made available. It is freely available on the Ensembl browser, from the Ensembl Regulation MySQL database server and in a dedicated track hub. Despite our increasing knowledge of genomes and their variants, the downstream effects of sequence variants and the affected cellular mechanisms are still poorly understood. In particular, a large number of the variants identified in genome-wide association studies are located in non-protein coding regions , and areCis-regulatory elements are short segments of the genome that either recruit transcription factors (TFs) or affect the properties of the messenger RNA as it is being transcribed [There is still much to learn about the dynamic regulation of gene expression ,4. Cis-rnscribed . Gene exnscribed -8. The Dnscribed  and cancnscribed . Finallynscribed , and whinscribed .cis-regulatory elements. Chromatin immuno-precipitation (ChIP) coupled with either genome-wide tiling microarrays  or direhIP-chip -16) makehIP-chip , throughhIP-chip . RegionshIP-chip , nucleashIP-chip  or assayhIP-chip .Significant efforts to provide genome-wide maps of histone modifications have already proved successful in elucidating some of the basic patterns associated with promoter and enhancer regions ,15,22,23One important challenge is to bring together and standardize these studies, in order to integrate all the information into a coordinated regulatory annotation of the genome. To address this challenge we developed the Ensembl Regulatory Build, within the Ensembl project , to provWe defined genomic regions of interest characterised by biochemical activity through a four-step Regulatory Build process that combined all available data, summarised in Figure We first reduced all the experimental data for each cell type into a cell type-specific annotation of the genome. This can be done with segmentation tools, such as Segway  or ChromBy overlapping these segmentation states, produced by unsupervised machine learning, with known genomic features, we assigned them functional labels, such as ‘predicted promoter with TSS’ (where TSS is transcription start site), ‘predicted transcribed region’, ‘predicted promoter flank’, ‘predicted enhancer’, ‘CTCF enriched’, ‘predicted repressed’, ‘predicted low activity’, ‘predicted heterochromatin’. To ensure the broadest applicability of our approach, we minimized the use of known epigenetic marks when assigning labels, rather using prior annotations. We nonetheless verified after the fact that states with similar labels display similar histone marks, as shown in Figure We then defined consensus regions of interest, referred to as ‘MultiCell’ regulatory features. To do so, for each of the labels ‘predicted promoter with TSS’, ‘predicted promoter flank’, ‘predicted enhancer’ and ‘CTCF enriched’, we computed a summary function, which represents at any given base pair how many cell types have one of the corresponding segmentation states. We then computed contiguous regions where this summary function is above a threshold, set to optimally fit the global TF binding signal see  section.Finally, the MultiCell features defined above were annotated with cell type-specific activity levels. This activity level was obtained by querying, for each feature, the presence or absence of cell type-specific evidence associated with that feature’s label.We examined the properties of the consensus annotation, as shown in Table To corroborate our annotation, we compared it with other reference annotations. Of the 217,516 strict TSS calls found with CAGE tags by the FANTOM 5 consortium , 88.9% wBy design, this annotation of the genome is focused on the pragmatic need to define epigenomic markers across samples. Its regulatory features are phenomenological, that is, defined by biochemical signal alone . If onlyA key parameter that can distort the segmentation is the number of states used by the machine-learning algorithm. Instead of trying to optimize the number of states, we circumvented this issue by focusing on the biologically meaningful labels that are ultimately provided to the user. There are only eight such labels, and Figure The build process reduces inherently noisy and complex biological data into a tidy and easy to understand summary. Consequently, subtle patterns can be masked from the user. To mitigate this loss of information, all the data used in the Regulatory Build, namely the experimental signal and the segmentations, are available through the Ensembl Browser.The Ensembl Regulatory Build is by no means a final product, rather a continuing process that will be extended and enriched in the coming years. In future Ensembl releases, we will be importing more and more datasets, covering more cell types, as they are made available. This will provide greater sensitivity to detect transient elements that are only active in a few cell types. Also, we are starting to receive normal cell and tissue data, as opposed to cell lines. Coupled with knowledge of cell differentiation pathways, these data will help illuminate the key epigenomic marks associated with cell fate.We will also be refining our annotation of regulatory features. The architecture of the Ensembl Regulatory Build process will allow us to take full advantage of ongoing research in machine learning, and genome segmentation in particular. We hope to extend the vocabulary used to describe the elements and the activity levels. For example, we wish to distinguish poised, repressed and closed elements, instead of applying a binary active/inactive notation.cis-regulatory elements. A number of experimental assays are being investigated, such as statistical correlation [The remaining open question is how to confidently assign gene targets to relation , chromatrelation -38 or exrelation ,40. The relation , variantrelation , and nowThe Ensembl Regulatory Build aims to provide the most up-to-date and comprehensive survey of the regulatory elements of the genome, in the same way the Ensembl Genebuild maintains a reliable summary of known gene sequences. Centralizing datasets from various large-scale projects, we process them with a uniform pipeline, then compute an exhaustive and robust annotation of the regulatory elements of the genome. Although this annotation will likely evolve in the years to come, the regions are already assigned stable identifiers, providing a solid framework for ongoing epigenomic research.We chose to run our segmentation (see below) on a pre-selected set of ChIP-Seq assays  along with DNaseI hypersensitivity and a control ChIP-Seq experiment. We therefore downloaded from ENCODE 2 and Epigenomics Roadmap all the raw read datasets produced by ChIP-Seq and DNaseI hypersensitivity experiments on the 18 cell types that had all of the above required assays: A549, DND-41, GM12878, H1-hESC, HeLa-S3, HepG2, HMEC, HSMM, HSMMtube, HUVEC, IMR90, K562, Monocytes-CD14+, NH-A, NHDF-AD, NHEK, NHLF, Osteoblast. Including replicates and control samples, this amounted to 740 datasets, all referenced in the Ensembl homo_sapiens_funcgen_76_38 MySQL database.Most studies using epigenomic data present their own analysis and results, which often differ from each other in small, but relevant details. In the current absence of standardized practices, and to make all data as homogeneous as possible, raw sequencing reads from these experiments were processed with a uniform in-house analysis pipeline.For each ChIP-Seq experiment, the raw sequencing reads were mapped to the GRCh38 human genome assembly using bwa samse  with defWe called punctate peaks using SWEMBL . We filtTo detect broader regions, such as H3K36me3 and H3K27me3 enrichment, we used CCAT . We filtThe coverage signal was normalized within each dataset using align2rawsignal , with opt, we computed a summary function pt across the genome representing the number of overlapping peak calls at that position divided by the number of assays. This function represents an approximate binomial estimator for the existence of a peak across the observed experiments.For each TF We then computed an overall TF binding probability function assuming approximate independence between the binding probabilities of the different transcription factors:s we constructed a summary function fs representing for each base pair the number of cell types that are in state s at that position. We computed the enrichment of contiguous regions where fs was strictly positive for TF binding, TSSs and exonic regions. We also computed the Pearson correlation of fs to the CTCF density. The state s was then assigned a label using the decision tree represented in Figure For each segmentation state cis-regulatory elements, promoters and insulators, are correlated to TF binding. Given a cutoff k we computed the enrichment for TF binding signal pTF of regions where fs was strictly greater than k. If we found a value of k such that this enrichment was greater than 2, then the segmentation state was retained for the next step.We assume that the labels we are interested in, namely l, we then set a cutoff kl that maximized the F-score Fl,k where Sl is the set of states which were assigned that label and passed the above test, and:For each label k, we computed the contiguous regions where fl was greater than kl.Having computed For simplicity, enhancer elements that overlapped promoter flanks were merged into the latter. Promoter-flanking regions that overlapped promoters were merged into the flanks of the promoter element. Because of their structural significance, CTCF binding sites were not merged into overlapping elements.pTF was greater than 0 did not overlap one of the segmentation-based annotations defined above, it was added into the Build, marked as ‘TF binding site’.If any contiguous regions where Finally, we computed the overlap of all observed open chromatin regions. If one of those did not overlap any of the annotations defined above, it was added into the Build, labeled as ‘Open Chromatin’.We then annotated the activity of these features in each cell type with a binary active/inactive label. For each region defined by segmentation data, we searched for an overlap in that cell type’s segmentation with a state that had the same label. For each region defined from TF binding sites, we searched for an overlap with a TF binding site detected on that cell type. Finally, for each region defined from open chromatin peaks, we searched for overlap with an open chromatin peak observed in that cell type.The VISTA enhancers were downloaded from the Ensembl database. The FANTOM5 enhancers and promoters were downloaded from the FANTOM5 servers . These tThe Ensembl eHive framework  was usedAll Ensembl data and source code are freely available and may be downloaded in their entirety from the Ensembl website . Additio


CHD1 and CHD2 chromatin remodeling enzymes play important roles in development, cancer and differentiation. At a molecular level, the mechanisms are not fully understood but include transcriptional regulation, nucleosome organization and turnover.Here we show human CHD1 and CHD2 enzymes co-occupy active chromatin regions associated with transcription start sites (TSS), enhancer like regions and active tRNA genes. We demonstrate that their recruitment is transcription-coupled. CHD1 and CHD2 show distinct binding profiles across active TSS regions. Depletion of CHD1 influences chromatin accessibility at TSS and enhancer-like chromatin regions. CHD2 depletion causes increased histone H3 and reduced histone variant H3.3 occupancy.We conclude that transcription-coupled recruitment of CHD1 and CHD2 occurs at transcribed gene TSSs and at intragenic and intergenic enhancer-like sites. The recruitment of CHD1 and CHD2 regulates the architecture of active chromatin regions through chromatin accessibility and nucleosome disassembly.The online version of this article (doi:10.1186/1756-8935-8-4) contains supplementary material, which is available to authorized users. ATP-dependent chromatin remodeling enzymes disrupt DNA-histone interactions facilitating nucleosome mobilization, including the disassembly, eviction, sliding and spacing of nucleosomes . The abiMammalian CHD1 has important biological roles in stem cell function, prostate cancer and transcription, while CHD2 has emerged as an important regulator of genetic stability, development, kidney function, muscle cell and hematopoietic differentiation –15. In mper se is not clear although both are present at transcribed gene promoters [Interestingly, CHD family remodelers function as chromatin readers in some cases by recognizing specific histone modifications . For exaromoters . For exaromoters , 22, whiromoters –25. In tromoters , 21.in vitro is associated with CHD1 recruitment in mammalian cells [The fission yeast CHD1 homologue Hrp1 was shown to co-purify with the fission yeast mediator complex . Consistan cells . Surprisan cells . Unlike an cells . In mousan cells . It was http://genome.ucsc.edu/ENCODE/). Closer inspection of the data demonstrates that neither H3K4me3 nor micrococcal nuclease (MNase) sensitive DNA at the NDR is correlated to CHD1 or CHD2. We demonstrate that both CHD1 and CHD2 are recruited in association with the RNA polymerase II (Pol II) machinery to active chromatin regions. Depletion of CHD1 in human cells reduces the accessibility of active regions as measured by DNase sensitivity. We also show that at active chromatin regions H3 occupancy is increased following knockdown of CHD2 suggesting a role in promoting nucleosome disassembly at active regions genome-wide. Knockdown of CHD2 also leads to a reduction in the relative enrichment of H3.3 further supporting a role for CHD2 in nucleosome turnover. We speculate that noncoding transcription at regulatory elements such as promoters, enhancers and active tRNA loci functions partially to modulate the chromatin environment through the recruitment and action of transcription coupled factors such as the remodeling enzymes CHD1 and CHD2.To examine how subclass I CHD remodelers, CHD1 and CHD2 are recruited and function in human cells, we first carefully examined the occupancy of each in relation to chromatin states utilizing data from the Encyclopedia of DNA Elements (ENCODE) consortium . Previous studies have demonstrated in model organisms and human cells that CHD1 remodelers are recruited to promoters in a gene expression-dependent manner [in vivo since occupancy is strongly reduced or absent at weak promoters, which are marked by H3K4me2/3.We analyzed CHD1 and CHD2 occupancy by calculating the enrichment of CHD1 and CHD2 from ChIP-seq data in relation to the chromatin states delineated by Ernst et al.. The chrein CTCF . The prot manner , 30. Impt manner . This suet al. demonstrated that the chromodomains of Drosophila melanogaster CHD1 are critical for CHD1 function but not recruitment and concluded that ChIP-seq studies were needed to confirm this [We hypothesized that the presence and absence of the Pol II transcription machinery occupancy may explain the difference in occupancy observed between the active and weak promoter states respectively. Consistent with this notion, Pol II was strongly enriched at active promoters only, whereas the H3K4me2/3 levels were comparable at both promoter states Figure B. This wirm this . Our anairm this , 32. Theet al. hypothesized that this may drive recruitment of the CHD family of remodeling enzymes to active promoters, where nucleosome disassembly provides naked DNA [CHD remodeling enzymes also contain nonsequence-specific DNA binding domains, which play important roles in the regulation of chromatin remodeling. Zentner aked DNA . In humaaked DNA . Thus, iaked DNA . Groupinet al. were identified through combinations of H3K4-methylation including the enhancer-specific H3K4me1 and histone acetylation . This produced 9,827 CHD1 peaks and 7,736 CHD2 peaks. For CHD1 and CHD2 respectively, 94% and 78% of high confidence peaks fell within a region associated with the active promoter or enhancer chromatin state 4 or both, based on chromatin states defined by Ernst et al.   with a set al., for murine Chd1 or using ChIP-exo to gain a more exact chromatin remodeler-DNA footprint [The majority of CHD1 and CHD2 sites overlapped (60%) Figure B. Despitootprint , 40.P <0.001). The inactive PRSS1 gene promoter was used as a control. Consistent with the proposed model of Pol II-driven recruitment, the binding of both CHD1 and CHD2 to the NPM1 gene promoter was significantly increased . Thus, we conclude that CHD1 and CHD2 are recruited with the Pol II machinery. The Henikoff laboratory recently demonstrated that a catalytically inactive, ATPase mutant of murine Chd1 reduces Pol II release from promoters, resulting in increased Pol II occupancy at TSSs. Consistent with our data  to block elongation and synchronize transcription at the initiation stage . Inaccessible centromeric repeats were used as a negative control and remained inaccessible  define regions of accessible chromatin associated with TSSs of expressed genes, while intergenic and intragenic DHS represent potential enhancer regions associated with transcription factor binding sites . We anale Figure A. The dee Figure B. Yet, sDHS are embedded within chromatin marked by H3K4me2/3 at TSS and at intergenic and intragenic DHS sites including enhancers –46. One One possible explanation for the effect of CHD1 on chromatin accessibility could be through the disassembly of nucleosomes. In fission yeast, the CHD1 homologues Hrp1 and Hrp3 function to reduce H3 occupancy at promoter regions , 19. In To analyze H3 occupancy and H3.3 occupancy by ChIP-qPCR, we first tested the specificity of the total H3 and H3.3 antibodies with recombinant human H3.1 and H3.3 proteins. The anti-H3 antibody detected both H3.1 and H3.3, while the H3.3 specific antibody detected only recombinant H3.3 protein by western blotting . Double CHD1 and CHD2 knockdowns showed an additive effect with an elevated H3 occupancy compared to the single CHD2 knockdown . Similar results were obtained at intragenic and intergenic DHS sites with CHD2 knockdown giving significantly elevated H3 occupancy and reduced H3.3 enrichment . Similar trends were also observed at active tRNA loci associated DHS for both H3 and H3.3 .We selected TSS, intragenic, intergenic and tRNA-associated DHS sites, as well as a number of non-DHS control loci. for analysis by ChIP-qPCR Figure . At TSSsSurprisingly, DNase accessibility, H3 occupancy and H3.3 enrichment do not appear to be directly related in this study since, CHD1 affects accessibility strongly with weaker affects on H3 occupancy, while CHD2 affects H3 occupancy and H3.3 enrichment without affecting accessibility. Nucleosome occupancy is not the only factor that regulates chromatin accessibility. Accessible chromatin sites at intergenic loci for example show higher nucleosome occupancy and smaller nucleosome-free regions than transcription start sites but are still highly accessible , 49. Acchrp1 and hrp3 deletions increase promoter H3 occupancy but do not affect MNase sensitivity of promoter regions [It is perhaps less surprising that the strong increase in H3 occupancy does not restrict chromatin accessibility since previous studies in fission yeast revealed that  regions , 19. One regions .Our analysis of ChIP-seq data for the CHD1 and CHD2 in human cells helps to reinterpret previously suggested models of CHD1 and CHD2 recruitment. We show that the recruitment is transcription-coupled and not driven by H3K4me2/3 or binding to NDR regions. The primary mechanisms of CHD1 recruitment to promoters and active chromatin regions must be driven by interactions between CHD1 and the mediator and must facilitate chromatin transcription (FACT); polymerase associated factor (PAF); and Spt-, Ada-, and Gcn5 acetyltransferase (SAGA) complexes , 38, 39.An important role of CHD1 is to facilitate Pol II transcription through chromatin, regulating nucleosome turnover and transcription coupled chromatin assembly , 18, 29.CHD2 has been linked to genetic stability, DNA repair and differentiation. In muscle cell differentiation, the myogenic transcription factor MyoD requires CHD2 for H3.3 deposition into muscle specific gene promoters. The strongest effects were likely seen at muscle-specific genes in this study since these regions are heavily transcribed in the model used . We obseThe transcription coupled recruitment of both CHD1 and CHD2 suggest that transcription could also play a role in noncoding regions of the genome such as promoters, enhancers, and active tRNA loci. Previous reports have suggested such functions for Pol II transcription at tRNA genes, leading to the hypothesis that Pol III transcription is facilitated by the Pol II associated machinery , 35. ActWe conclude that CHD1 and CHD2 are recruited along with the transcription machinery to promoters and enhancer sites associated with transcription. For CHD1, this establishes a clear model of recruitment via interactions with Pol II-associated complexes. This provides a basis for interpretation of previous studies and models of CHD1 recruitment. At active regions, CHD1 and CHD2 cooperate to regulate the chromatin architecture. Thus, transcription coupled chromatin remodeling promotes chromatin accessibility and nucleosome disassembly at transcribed regulatory regions.http://genome.ucsc.edu/ENCODE/). The files used in this study are listed in Additional file http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/). All ChIP-seq data, including CHD1 and CHD2 occupancy, was measured as the fold enrichment over input. Where indicated in the text, differences between chromatin states were tested for significance using the Kruskall-Wallis test with Dunn’s post-test correction. High confidence CHD1 and CHD2 peaks were calculated using model-based analysis for ChIP-seq (MACS) with a stringency cut off of 1 × 10-15 and binding sites within 200 bp or less were merged [Data from the ENCODE project were accessed and downloaded through the UCSC web portal , which was supplemented with 10% fetal bovine serum, 10 U/mL penicillin and 10 U/mL streptomycin (Life Technologies). To arrest transcriptional elongation K562 cells were treated overnight (12 h) with 100 μM 5,6-dichloro-1-β-D-ribofuranosyl-1H-benzimidazole (DRB)  or vehicle (DMSO).6 cells.siRNA targeting CHD1 (s2974 and s2975) and CHD2 (s2979), as well as nontargeting negative controls, were obtained from Life Technologies . The transfection protocol was performed as per manufacturer’s instructions with the following electroporation parameters: three pulses, 1,450 v, and 10 ms pulse width. The final total concentration of siRNA per sample was 25 nM in 8 mL of antibiotic-free RPMI 1640 medium with 10% serum per 3 × 106 K562 cells was isolated using the RNeasy plus kit . A total of 1 μg of RNA was reverse-transcribed using Superscript™ III First Strand Synthesis Supermix  according to the manufacturer’s instructions. Resultant cDNA was diluted 1:20, and qPCR analysis of CHD1 and CHD2 transcript abundance was normalized to GAPDH using Taqman assays .RNA from 5 × 106 K562 were lyzed using single detergent lysis buffer  and protein concentration was calculated using the BCA protein assay . A total of 40 μg of protein per sample was denatured and resolved on a 4 to 12% Bis-Tris gel with MOPS running buffer . Gels were then wet-transferred to a 0.2-μM PVDF membrane  at a constant voltage of 100 V for 120 min. Membranes were air-dried, reactivated for 5 min in methanol and then blocked for 4 h at room temperature in 5% milk in PBS with 0.1% Tween. Membranes were incubated overnight in primary antibodies at 1:1,000 dilution in blocking buffer then washed three times for 10 min each in PBS 0.1% Tween and incubated for 1 h at room temperature in secondary antibody . Finally, the PBS-Tween washes were repeated, and the membranes were developed with chemiluminescent ECL substrates. Antibodies used were as follows: CHD1 , CHD2 , and H3 , all at a concentration of 1:1,000.For western blotting, 5 × 106 K562 cells were used per reaction and the resultant DNA was diluted to 1 in 400 in qPCR reactions. Accessibility was calculated as; 2(Ct(undigested)-Ct(digested)). We then normalized each loci to the percentage of accessibility in control siRNA treated cells. Primers were designed to DNase hypersensitivity peaks in K562 cells based on ENCODE data. For TSS, DHS regions we focused on expressed genes, whereas for intragenic and intergenic regions, we selected DHS sites observed when looking for accessible and inaccessible TSS regions. For tRNA loci, we chose loci from expressed tRNA genes that did not overlap with an annotated TSS but did overlap with a DHS. Primers are listed in Additional file To measure chromatin accessibility, we used the EpiQ™ chromatin analysis kit  according to the manufacturer’s instructions at 28 hours post transfection with siRNA. Briefly, 0.25 × 10K562 cells were fixed in 1% paraformaldehyde for 8 minutes, and ChIP was performed using the iDeal ChIP-seq kit  according to the manufacturer’s instructions. Chromatin extracts from one million cells were sonicated to yield 100 to 500 bp fragments using a Bioruptor™ Plus (Diagenode) on high power for two rounds of 12 cycles with 30s on 30s off at 4°C. Antibodies used in ChIP were as follows; CHD1 - 3 μl per reaction of #4351 , CHD2 - 3 μl per reaction of ab68301 , H3 - 2 μl per reaction of ab1791 , and H3.3 - 3 μl per reaction of 09–838 . Primers for qPCR were designed across DNase hypersensitivity sites at TSS regions, intergenic or intragenic regions, or active tRNA loci and are listed in Additional file CHD7 occupancy at promoter chromatin states in K562 and H1 embryonic stem cells (ESCs). The occupancy of CHD7 was calculated as the fold enrichment over input. (PDF 1 MB)Additional file 1:Recruitment of CHD1 and CHD2 to active tRNA loci. (A) The occupancy of CHD1 and CHD2 across BRF1 and BRF2 binding sites in K562 cells was calculated as the fold enrichment over input. (B) A selected, expressed tRNA gene in an intergenic region showing BRF1, CHD1, CHD2 and Pol II occupancy in K562 cells. (PDF 1 MB)Additional file 2:Average enrichment of Pol II, Pol II ser2, CHD1 and CHD2 at transcribed genes. Transcribed genes were identified as in the top quintile of Pol II ser 2 occupancy and analyzed for Pol II, CHD1 and CHD2 enrichment across the gene plus 2.5 kb up and downstream. (PDF 361 KB)Additional file 3:CHD1 and CHD2 siRNA knockdown. (A) Transcript abundance of CHD1 and CHD2 relative to GAPDH in K562 cells 48 h following siRNA transfection. (B) Western blot analysis of CHD1 and CHD2 expression 72 h following transfection. (PDF 2 MB)Additional file 4:Analysis of H3.3 antibody specificity by western blot and ChIP-qPCR. (A) The reactivity of total H3 and H3.3 specific antibodies toward 10 to 250 ng of recombinant human H3.1 and H3.3 was analyzed by western blot. (B) The relative enrichment of H3.3 to total H3 was examined by ChIP qPCR at active GAPDH and inactive MYOD gene TSS and the active NPM1 promoter and NPM1 intron. (PDF 1 MB)Additional file 5:ENCODE data files used.(PDF 37 KB)Additional file 6:Primers for qPCR.(PDF 40 KB)Additional file 7:


Escherichia coli contains seven copies of the rRNA operon in the genome. The presence of multiple rRNA operons is an advantage for increasing the level of ribosome, the key apparatus of translation, in response to environmental conditions. The complete sequence of E. coli genome, however, indicated the micro heterogeneity between seven rRNA operons, raising the possibility in functional heterogeneity and/or differential mode of expression. The aim of this research is to determine the strength and regulation of the promoter of each rRNA operon in E. coli. For this purpose, we used the double-fluorescent protein reporter pBRP system that was developed for accurate and precise determination of the promoter strength of protein-coding genes. For application of this promoter assay vector for measurement of the rRNA operon promoters devoid of the signal for translation, a synthetic SD sequence was added at the initiation codon of the reporter GFP gene, and then approximately 500 bp-sequence upstream each 16S rRNA was inserted in front of this SD sequence. Using this modified pGRS system, the promoter activity of each rrn operon was determined by measuring the rrn promoter-directed GFP and the reference promoter-directed RFP fluorescence, both encoded by a single and the same vector. Results indicated that: the promoter activity was the highest for the rrnE promoter under all growth conditions analyzed, including different growth phases of wild-type E. coli grown in various media; but the promoter strength of other six rrn promoters was various depending on the culture conditions. These findings altogether indicate that seven rRNA operons are different with respect to the regulation mode of expression, conferring an advantage to E. coli through a more fine-tuned control of ribosome formation in a wide range of environmental situations. Possible difference in the functional role of each rRNA operon is also discussed.The model prokaryote  E. coli cells, there are as many as 70,000 ribosomes per cell, while at lower growth rates, this number is reduced to less than 20,000  between BglII and EcoT221 sites. About 500 bp-long sequence of seven rrn operons, each including both P1 and P2 promoters, were inserted into this pGRS vector in front of this synthetic SD sequence to construct the rRNA promoter assay vectors (pGRS-rrnA to pGRS-rrnH) (For quantitative measurement of the promoter activity promoter . For meaprimers) . For meaE. coli, cells grown in LB for various times were harvested by centrifugation, resuspended in phosphate-buffered saline, and diluted with phosphate-buffered saline to obtain approximately the same cell density (0.6 A600nm unit) for all samples. For measurement of bulk fluorescence, aliquots of a 0.3-mL cell suspension were added to 0.4 x 96 flat-bottom wells, and the fluorescence was measured with a FL600 Bio-Tek Microplate Fluorescence Reader . The net fluorescence value was measured after subtraction of the background fluorescence, which was determined by using E. coli cultures with pGRS vector without promoter insertion.The promoter activity was determined by measuring GFP and RFP fluorescence according to the standard procedure . In brieFis protein was expressed using pFis expression vector that was constructed using pET21a vector, and affinity-purified using the standard purification procedure of His-tagged transcription factors . The purTaq DNA polymerase , and pairs of rrn primers Click here for additional data file.S1 Tablerrn operon, 313 to 554 bp sequences, shown in For cloning the promoter region sequence upstream from 16S rRNA gene of each (PDF)Click here for additional data file.


Vibrio cholerae, the causative agent of the ongoing 7th cholera pandemic. The expression of cholera toxin (CT) and toxin coregulated pilus (TCP), the major virulence factors of V. cholerae, is controlled through a regulatory cascade involving activation of ToxT with synergistic coupling interaction of ToxR/ToxS with TcpP/TcpH. We present evidence that anethole inhibits in vitro expression of CT and TCP in a toxT-dependent but toxR/toxS-independent manner and through repression of tcpP/tcpH, by using bead-ELISA, western blotting and quantitative real-time RT-PCR assays. The cyclic AMP (cAMP)-cAMP receptor protein (CRP) is a well-studied global signaling system in bacterial pathogens, and this complex is known to suppress expression of tcpP/tcpH in V. cholerae. We find that anethole influences the virulence regulatory cascade by over-expressing cyaA and crp genes. Moreover, suppression of toxigenic V. cholerae-mediated fluid accumulation in ligated ileum of rabbit by anethole demonstrates its potentiality as an antivirulence drug candidate against the diseases caused by toxigenic V. cholerae. Taken altogether, these results revealing a mechanism of virulence inhibition in V. cholerae by the natural compound anethole, may have relevance in designing antivirulence compounds, particularly against multiple antibiotic resistant bacterial pathogens.Use of natural compounds as antivirulence drugs could be an alternative therapeutic approach to modify the outcome of bacterial infections, particularly in view of growing resistance to available antimicrobials. Here, we show that sub-bactericidal concentration of anethole, a component of sweet fennel seed, could suppress virulence potential in O1 El Tor biotype strains of toxigenic  Vibrio cholerae, the causative agent of cholera epidemics is a growing concern.The current status of emergence of multidrug resistant (MDR) pathogenic bacteria has caused loss of the effectiveness of antimicrobial agents against them . Like otctxAB genes) is the major virulence factor in toxigenic V. cholerae, and is mostly responsible for the profuse watery diarrhea leading to severe dehydration  at 37°C for O1 El Tor/O139 strains  for 15 min at room temperature. Samples were then treated with protease inhibitor cocktail  and whole-cell lystaes were prepared by ultrasonic treatment (Astrason W-385 ultrasonic processor) with 5 to 7 pulses of 30 sec each. Proteins from equal volume of cell extracts of all samples were separated by SDS-PAGE using 15% (wt/vol) polyacrylamide gels, transferred to a polyvinylidene difluoride (PVDF) membrane in a Trans-blot apparatus , and probed with either rabbit polyclonal anti-TcpA (1:3000 dilution) or anti-TcpP antibody (1:500 dilution) followed by HRP-conjugated anti-rabbit IgG. Expression of desired proteins was then visualized by using Amersham ECL western blotting detection reagents , according to the product guideline. The signal intensity of specific protein bands were determined with the ImageJ software (http://imagej.nih.gov/ij/), and normalized to that of wild type without anethole samples.To analyze the effect of anethole on TcpA and TcpP expression, whole-cell lysates were prepared as described previously  with somIn vivo effect of anethole on CT production was analyzed by a rabbit ileal loop (RIL) assay using New Zealand white male rabbits (ca 1.8 kg) as described previously [8 CFU/loop), either in the presence (0.08–10 mg per loop) or absence of anethole (1% methanol). Loops were then placed back in the peritoneal cavity. After 6 h incubation, the animals were euthanized by injecting 200 mg/kg pentobarbital . Fluid accumulation (FA) ratio (ml of fluid per cm of the loop), total bacterial number by plating on thiosulfate-citrate-bile salts-sucrose (TCBS) agar  plates and total amount of CT produced in intestinal fluid of each loop by bead-ELISA were then measured. RILs without apparent fluid accumulation were also washed internally with PBS and the washings were analyzed for total bacterial count and CT production. All animal experiments were performed according to the Guidelines for Animal Experimentation of Osaka Prefecture University and approved by the Animal Experiment Committee of Osaka Prefecture University.eviously . BrieflyV. cholerae cells grown under desired conditions by using TRIzol reagent (Invitrogen), according to the product guidelines. Isolated RNA was treated with RNase-free DNase I  to avoid genomic DNA contamination. The reverse transcription was performed from 1 μg of RNA, according to the instruction of quick RNA-cDNA kit (Applied Biosystems Inc.). The obtained cDNA was diluted 1:4 with nuclease-free water, and 4 μl was used for qRT-PCR assay. The qRT-PCR assay was carried out by following the TaqMan probe method with each gene-specific primers, probes and TaqMan Gene Expression master mix (Applied Biosystems Inc.). PCR conditions were 50°C for 2 min, 95°C for 10 min and 40 cycles, each having 95°C for 15 sec and 60°C for 1 min in an ABI PRISM 7500 sequence detection system (Applied Biosystems Inc.). Genomic DNA and DNase-treated RNA that had not been reverse transcribed were used as positive and negative controls, respectively. The housekeeping gene recA was used as an internal control. The relative transcription of each gene in comparison with the internal control was analyzed as described previously [Total RNA was extracted from eviously .cyaA and crp deletion mutants in the strain CRC41 was performed by following in-frame deletion mutagenesis as described previously [cyaA and crp genes with desired deletion were cloned into the MCS of the suicide vector pWM91 [cyaA and pΔcrp, respectively. The resulting plasmids were then electroporated into E. coli strain DH5αλpir for maintaining and subsequently to the SM10λpir [V. cholerae strain CRC41 via conjugation. Resolution of the cointegration was done by sucrose-encounter selection. Recombination and the loss of the wild-type allele were confirmed by PCR using primers flanking the deletions. pCyaA and pCRP were constructed in pBR322 vector to analyze the complementation effect of the proteins in respective V. cholerae mutants. To construct pCyaA, a 2.65-kb fragment that include entire cyaA gene (VC0122) with 126-bp upstream of putative promoter region, was amplified and cloned in to the compatible sites of pBR322. By following the same procedure entire crp gene (VC2614) including 183-bp of putative promoter region was cloned in to pBR322 to construct pCRP.Construction of eviously . Brieflyor pWM91  to constSM10λpir  to mobilV. cholerae strains and found that up to 100 μg/ml of anethole did not have any detectable effect on the growth of these strains  in a dose-dependent manner. As shown in V. cholerae, expression of TcpA (the major subunit of TCP) was also examined. For this purpose, western blot analysis was carried out from the same CRC41 cultures, used to see the dose-dependent effect of anethole on CT production inhibition. As expected, reduction of TcpA expression was observed  assay, and monitored fluid accumulation, CT production and V. cholerae viability. As shown in 8 CFU of a toxigenic strain CRC41 as compared to loop in which bacteria were inoculated without anethole. Thus, CT production as indicated by fluid accumulation was inhibited by anethole in a dose-dependent manner under in vivo conditions. There was no significant difference in bacterial counts in the ileal loop fluids, recovered from assays with and without anethole, suggesting that reduced fluid accumulation was not due to bacterial growth inhibition, but for reduced virulence expression in V. cholerae by anethole.To test whether anethole can effectively suppress expression of CT by toxigenic toxT, toxR, toxS, tcpP, tcpH and hns were analyzed via qRT-PCR assay. The relative transcription level of each gene was normalized with that of housekeeping gene recA, which was used as an internal control.To determine at which point of the virulence regulatory cascade anethole affected CT and TCP expression, transcription level of various regulatory genes, including Based upon our initial experiments showing the trend of inhibition of CT expression , a cultuctxA gene transcription was repressed ~10-fold. Transcription of major colonization factor tcpA was also repressed ~60-fold. At this stage, transcription of other virulence regulatory genes was also repressed by anethole, at various extents: toxT (~13-fold), tcpP (2.3-fold) and tcpH (2.8-fold). On the other hand, transcription of toxR, toxS and hns were not affected significantly. Under shaking condition (recA was not affected in presence of anethole compared to the untreated controls at either culture conditions (data not shown).As shown in ondition , the tratcpP transcription by qRT-PCR . The relative signal intensities of TcpP by western blot  correlat qRT-PCR . The reltcpPH, the effect of anethole on the transcription of probable upstream regulators was also examined. tcpPH are overlapping operons and positively regulated by the membrane-located transcription factor AphA/AphB in V. cholerae [tcpPH promoter and can negatively regulate the expression of tcpPH [tcpPH, including cyaA, crp, hapR, aphA and aphB in the presence of anethole.Since there are also upstream regulatory genes for cholerae . The cycof tcpPH , 32, wheof tcpPH . TherefocyaA , crp  and hapR  increased but aphA  decreased significantly in the presence of 50 μg/ml anethole compared to those of cultures without anethole. Although we observed certain variation in expression of these genes under stationary and shaking condition  leading to transcription of toxT [toxT transcription initially and subsequently prevent the activation of auto-regulatory loop of toxT transcription. Thus, due to the failure of activation of auto-regulatory loop of toxT transcription at initial stationary phase, further activation of toxT transcription  restored their growth rate to the level of the wild type strain (data not shown). Unfortunately, we failed to analyze the effect of anethole on CT production in these mutants, since they showed significant growth inhibition at 50 μg/ml anethole compared to anethole-free culture  in V. cholerae, which causes degradation of TcpP [V. cholerae. But, we failed to find any significant differences of rseP and degS in their transcription level between anethole-treated and untreated cells Click here for additional data file.S2 Figx-axis indicates the culture conditions used to analyze the samples. Primary y-axis indicates the OD value of the culture at 600nm and secondary y-axis indicates the bacterial viability as CFU/ml at desired time points.(TIF)Click here for additional data file.S3 FigV. cholerae cells cultured (A) at 4 h of stationary and (B) followed by 2 h of shaking conditions. ‘C’ indicates the control value of each target gene transcription without anethole (arbitrarily taken as 1). Data are presented as the average ± SD of three independent experiments.Relative transcription level of the genes were examined both in the presence (50 μg/ml) and absence (0.5% methanol) of anethole, with (TIF)Click here for additional data file.S1 Table600, Optical density at 600nm. V. cholerae cells were co-cultured with different concentrations of anethole in AKI medium with initial 4 h of stationary followed by 4 h of shaking, and OD600 of each culture was measured by a spectrophotometer. In all cases, values represent the mean (OD600) ± SD of three independent bacterial cultures at respective anethole concentration.OD(PDF)Click here for additional data file.


We also showed that TATA box promoters are specifically potentiated by processed TFIIA. Processed TFIIA, but not unprocessed TFIIA, associated with the TATA box. In a TLP-knocked-down condition, not only the amounts of TATA box-bound TFIIA but also those of chromatin-bound TBP were significantly increased, resulting in the stimulation of TATA box-mediated gene expression. Consequently, we suggest that TLP works as a negative regulator of the TFIIA processing and represses TFIIA-governed and TATA-dependent gene expression through preventing TFIIA maturation.TBP-TFIIA interaction is involved in the potentiation of TATA box-driven promoters. TFIIA activates transcription through stabilization of TATA box-bound TBP. The precursor of TFIIA is subjected to Taspase1-directed processing to generate α and β subunits. Although this processing has been assumed to be required for the promoter activation function of TFIIA, little is known about how the processing is regulated. In this study, we found that TBP-like protein (TLP), which has the highest affinity to TFIIA among known proteins, affects Taspase1-driven processing of TFIIA. TLP interfered with TFIIA processing  The assembly of the transcription initiation complex on a promoter region is a critical step in gene expression. The TATA box is a promoter-proximal regulatory element that is responsible for high transcription efficiency of RNA polymerase II (polII)-dependent genes ,2. It isXenopus embryo was rescued by the introduction of uncleavable TFIIA  was identified as one of the TFIIA-binding proteins with the highest affinity ,18. TLP,osophila ,27. Furtociation . Howeverin vivo. We propose as a new mechanism that TLP represses promoter activity by preventing Taspase1-mediated processing of TFIIA. We also found that the TFIIAαβ itself is not involved in TATA box-mediated transcription activation and the processing of the TFIIAαβ precursor by Taspase1 is essential for full potentiation of TATA box promoters in cultured human cells. The role of TLP-TFIIA interaction is thought to be a critical determinant for expression of TATA box genes.In this study, we examined the effect of TLP-TFIIA interaction on TATA promoters and found that TLP represses TATA box-driven gene expression Human HCT116 cells and HeLa cells were maintained in Dulbecco's modified MEM with high and low concentration of glucose, respectively (Sigma-Aldrich) at 37°C in the presence of 10% fetal calf serum. Knockdown experiments were performed as described previously . Lipofecth aspartic acid and 275th glycine were substituted by alanine in the DGAA mutant.Mammalian expression plasmids: expression plasmids for flag/oligohistidine-tagged (FH)-TLP, FH-N37E, FH-TFIIA-L, FH-TFIIA-S and FH-MyoD were described previously ,29. pCInTBP, Taspase1, TFIIAαβ and TFIIAγ were subcloned into a pET-3a vector (Novagen). An FH-tag was added to each of the amino terminal ends of the open reading frames of TBP and Taspase1, and oligohistidine (His)-tag was linked to that of TFIIAγ.Bacterial expression plasmids: open reading frames of p21 were amplified from human genomic DNA and cloned into a pGL4 vector by a standard PCR-based method. p21-168/GL4, p21-65/GL4 and p21-5/GL4 harbor distinct length of the p21 promoter as shown in Figure GAPDH gene, was also generated as described above. GAPDHmutTATA/GL4, which is a mutant construct of GAPDHWT/GL4, has a disrupted TATA box sequence.Reporter plasmids for luciferase assay: a pGL4.10 vector was used for construction of reporter plasmids. Promoter regions of human Preparation of total cellular RNAs and reverse transcription PCR (RT-PCR) and quantitative PCR (qPCR) were performed as previously described ,30. SemiA luciferase assay was performed as previously described . In a TLCell extracts were prepared as previously described . Three hProteins were separated by SDS-PAGE, transferred to an Immobilon-P PVDF membrane (Millipore), and detected by an ImmnoStar Zeta (Wako) by using specific antibodies and appropriate horseradish peroxidase-conjugated secondary antibodies including anti (α)-rabbit IgG and α-mouse IgG. The primary antibodies used included α-p53 antibody (Santa Cruz), α-β-actin antibody (Sigma-Aldrich), α-GAPDH antibody (Santa Cruz), α-α-tubulin antibody (Santa Cruz), α-p21 antibody (Santa Cruz) and α-FLAG M5 antibody (Sigma-Aldrich). Anti-TLP, α-TFIIAαβ, α-TFIIAγ, α-TBP and α-TFIIB antibodies were used as antigen-purified antibodies.ChIP was performed by a previously described method . Briefly32P-γ-ATP as previously described  and incubated at 37°C for 30 min to form TBP-TFIIA complex. Labeled probe DNA was then added to the mixture and incubated at 30°C for 45 min to form protein-DNA complex. Protein-DNA complexes were separated by 4% native PAGE and detected by autoradiography. If necessary, unlabeled probe DNA was added to the binding reaction as a competitor.EMSA was conducted with purified recombinant proteins. Double-stranded DNA carrying a GAPDH TATA box sequence (sense: CGGTTTCTATAAATTGAGCC) was labeled with escribed , and 80 E. coli., and the recombinant proteins were induced by isopropyl-1-thio-β-D-galactoside. Cells were lysed with lysis buffer . Proteins were purified from lysates using anti-Flag M2 Affinity Gel or Ni-NTA Agarose (QIAGEN). Although TFIIAαβ has no appending tags, it binds to Ni-NTA due to an oligohistidine moiety in the central region of the polypeptide. Affinity carriers were washed three times with lysis buffer, and M2 and Ni-NTA-bound proteins were eluted with FLAG peptide and imidazole, respectively.FH-TBP, FH-Taspase1, TFIIAαβ and His-TFIIAγ were transformed into BL21 (DE3) 2, 100 mM KCl, 0.2 mM EDTA, 5 mM dithiothreitol, 10% glycerol) and incubated at 37°C for 1 h. M2 Agarose-bound FH-Taspase1 was eliminated from the TFIIA solution by centrifugation centrifuge. Processing of the TFIIAαβ precursor was checked by SDS-PAGE and silver staining.For preparation of processed TFIIAα and β subunits, 1 μg of the TFIIAαβ precursor was mixed with M2 Agarose-bound FH-Taspase1 in a reaction buffer . NF1, TAp63 and p21 is potentiated by TLP through its recruitment to a promoter region   was not increased by TLP knockdown  Figure . In contn Figure . Rather,d Figure . These rin vivo promoter-associating capacity of TFIIA. ChIP results confirmed that TFIIA was enriched in TATA promoters  and GAPDH promoters. In a TLP-knocked-down condition, the TATA box-harboring p21 promoter exhibited higher activity than that of the control one . Additionally, we examined three TLP mutants R55E, R52E and N37E. While R55E has normal TFIIA binding ability, R52E and N37E have been shown to be defective just in TFIIA binding ability   ,27. On t Figures . Since 2in vivo (data not shown). Our previous works have further shown that TLP has one-order higher affinity to TFIIA than TBP does  does not undergo proteolytic processing . On the tivation , severaltivation ,16,40. Ttivation  and 6. Mtivation . TFIIAγ tivation , and thetivation  and 6D. tivation . This cotivation , processet al. demonstrated by in vitro analysis that TLP prevents TBP-TATA box complex formation as the first step through competing with TBP for TFIIA binding , which is rather dependent on TLP. Actually, promoter recruitment of unprocessed TFIIAαβ has been reported. Takeda et al. demonstrated that unprocessed TFIIAαβ associates with TATA-less promoters of p16Ink4a and p19Arf genes and enhances expression of those genes during mouse craniofacial morphogenesis (We demonstrated that unprocessed TFIIAαβ is inactive in TATA promoter activation. On the other hand, unprocessed TFIIAαβ has much more capacity to activate a subset of TLP-dependent TATA-less promoters Figure . We founogenesis . Thus, tWe propose a TLP-governed promoter selection model of TFIIA Figure . TLP inh