The hepatic nuclear factor HNF4α is a versatile transcription factor and controls expression of many genes in development, metabolism and disease. To delineate its regulatory gene network in colon cancer and to define novel gene targets a comprehensive genome-wide scan was carried out at a resolution of 35 bp with chromatin IP DNA obtained from the human colon carcinoma cell line Caco-2 that is a particularly rich source of HNF4α. More than 90% of HNF4α binding sites were mapped as promoter distal sequences while enhancer elements could be defined to foster chromatin loops for interaction with other promoter-bound transcription factors. Sequence motif analysis by various genetic algorithms evidenced a unique enhanceosome that consisted of the nuclear proteins ERα, AP1, GATA and HNF1α as cooperating transcription factors. Overall >17,500 DNA binding sites were identified with a gene/binding site ratio that differed >6-fold between chromosomes and clustered in distinct chromosomal regions amongst >6600 genes targeted by HNF4α. Evidence is presented for nuclear receptor cross-talk of HNF4α and estrogen receptor α that is recapitulated at the sequence level. Remarkably, the Y-chromosome is devoid of HNF4α binding sites. The functional importance of enrichment sites was confirmed in genome-wide gene expression studies at varying HNF4α protein levels. Taken collectively, a genome-wide scan of HNF4α binding sites is reported to better understand basic mechanisms of transcriptional control of HNF4α targeted genes. Novel promoter distal binding sites are identified which form an enhanceosome thereby facilitating RNA processing events. Finally, we analyzed HNF4α binding sites for enriched binding motifs and identified cooperating transcription factors that appeared to act in concert with HNF4α in an enhanceosome of transcriptional regulation.Hepatic nuclear factor HNF4α is a member of the nuclear receptor superfamily and an extremely versatile transcription factor OTC) and further improved based on the frequency of HNF4α -motifs within the enriched regions, as determined by the MATCH algorithm Table S1). Moreover, a low stringency data set was generated by merging ES data detected with the MAT and Tilemap algorithms. This resulted in a total of 25,419 ES (Table S2).Chromatin IP experiments were performed with Caco-2 cell cultures and an antibody highly specific for HNF4α. Notably, total input as well as IP-DNA from three independent biological replicates was obtained and subjected to an optimized protocol for unbiased amplification according to the manufactures recommendation . The amplified DNA from independent experiments was hybridized to Affymetrix Human tiling 2.0R arrays with a genome-wide resolution of 35 bp. Then, raw data were examined for enriched regions by use of three independent algorithms TAS . InitialAAT (R00114), GCC (R08885), PCK (R12074), APOB (R01612), CYP2C9 (R15905), AKR1C4 (R13037), ACADM (R15923) or CYP27A1 (R15917). In the case of SHBG (R15941), ES were determined within a few hundred base pairs relative to the reported binding sites. Other binding sites described in literature, like ALDH2 (R15845), could not be confirmed. However, quantification by real time PCR showed that the ALDH2 site was not enriched in the primary IP-DNA. As the HNF4α protein functions in a tissue specific manner, it is not unexpected that some ES are not bound in Caco-2 cells; their accessibility rather depends on chromatin organization, which in turn depends on the cell type. This is supported by independent investigations, where significant differences in DNA binding sites in different cell types had been observed Additionally, 15 ES of known HNF4α gene targets were chosen and their enrichment in the primary IP-DNA was determined by realtime quantitative PCR. For all selected sites enrichment could be confirmed. Thus the robustness and quality of the data was validated Fig. 2. Table S3).ChIP-enriched regions were examined for HNF4α binding motifs with the MATCH algorithm de novo definition of the HNF4α motif  Fig. 3c.The distance from HNF4α binding site to the closest transcription start site (TSS) of a RefSeq gene was determined. Here, a nearly 5-fold overrepresentation of binding sites in the promoter region of −1000 to 0 relative to the TSS was observed  and the chromosomal distribution of ES is not randomly distributed; rather clusters are formed . Indeed, most enhancers appear to be promiscuous and thus regulate multiple genes Table S8).The distribution of identified ES across the chromosomes varied >6 fold. Strikingly, the Y chromosome is devoid of HNF4α ES . These transcription factors are known to compete with HNF4α for common binding sites To search for transcription factor cross-talk the ChIP regions for overrepresented motifs were considered. Among the motifs with the highest enrichment are matrices similar to the HNF4α binding motif, e.g. those for COUP-TF, PPAR or LEF1 (The high sequence similarity of binding sites for HNF4α and estrogen receptor (ERα) is of considerable importance Fig. 9c.As the ERα motif overlaps partially with the HNF4α motif, it is tempting to speculate that such enrichment within the ChIP regions is due to a functional connection between the two factors. Recently, a genome-wide map of ERα binding sites was reported Data from the present study was compared with published data in order to identify regions which overlap amongst these studies Fig. 10.de novo identified genes were grouped (Table S9). Many of the targeted genes are involved in different metabolic processes, e.g. lipid, organic acid or carbohydrate metabolism. Categories related to transport, i.e. lipid transport, were significantly overrepresented as was fatty acid and cholesterol metabolism Based on Gene Ontology the de novo identified HNF4α gene targets, Caco-2 cell cultures were treated with an inducer of HNF4α protein HNF1α promoter was increased Table S10). Of these, 383 genes were up-regulated and 153 down regulated. The promoter sequences of regulated genes were analyzed for HNF4α binding sites and compared with the list of newly identified ChIP-chip gene targets. An overlap of 63% or 336 differentially expressed genes (Table S11) were identified as HNF4α gene targets, therefore confirming the functional importance of the ES identified in the ChIP-chip assay.A common approach to identify genes targeted by a transcription factor is to determine mRNA abundance caused by its increased or diminished transcriptional activity as investigated in human embryonic kidney HEK293  and hepaTable S10). Importantly, the highest overlap was obtained in studies that employed knock-down siRNA experiments to validate their findings Finally, published data on HNF4α overexpressing mammalian cell lines was compared with data of the present study. The overlap ranged from 65 to 94% of the genes identified . Note, of the 41 known and 14 novel protein coding genes on the Y chromosome (http://www.ensembl.org/index.html) several function in testis development and gender determination and include the SRY and TSPY proteins. While no vital genes are located on the Y chromosome several diseases can be linked to defective Y chromosome. It is tempting to speculate that the significant overlap between the ERα and the HNF4α motif and the functional interaction of these transcription factors possible determined, at least in part, evolution and thus gene selection of the Y chromosome.Moreover, the distribution of identified ES across the chromosomes varied considerably and the chromosomal distribution of ES was not randomly distributed; rather clusters were identified , Fig. 7.Note, enhancer elements are constituted by clusters of binding sites for different transcription factors Based on a thorough and detailed motif analysis, a close relationship between HNF4α and AP1, GATA, ERα or HNF1α binding could be established. While single cases of synergistic action of HNF4α with HNF1α Table S11) were identified as HNF4α gene targets, therefore confirming the functional importance of the ES identified in the ChIP-chip assay. Hence, for some of the identified genes the biological relevance could be established. Nonetheless, further studies are in need to determine functional importance for the many other ES sites, and this could possibly be achieved with an additional control in ChIP-chip studies where the DNA binding domain of HNF4α has been disabled.To further probe the functional importance of the newly identified binding sites transcript expression of targeted genes at varying HNF4α protein levels was studied. These studies confirmed 536 unique RefSeq-annotated genes to be differentially expressed. The promoter sequences of regulated genes were further analyzed and 63% or 336 differentially expressed genes  was used. Fragmentation success was confirmed with he Agilent Bioanalyzer 2100. The labeled samples were hybridized to Affymetrix Human tiling 2.0R arrays with a 35 base pair resolution.Three samples displaying high enrichment for positive controls were selected for ChIP-chip experiments. Total input DNA from three independent biological replicates was diluted to the same concentration as the corresponding ChIP-sample and amplified in parallel with ChIP-samples from the three independent biological replicates. Amplification was performed according to the Affymetrix protocol. The cycle number and amount of http://g2.trac.bx.psu.edu/). After intersection enriched regions shorter than 200 bp were removed.Raw data (CEL-files generated by GCOS after scanning) were analyzed for enriched regions by three independent algorithms, TAS Table S12. Δct-values were calculated versus diluted total input, and calculation of ΔΔct-values was performed using a β-actin negative control.ChIP-DNA from three independent experiments was used for further validation. Realtime PCR was performed on the Light Cycler  with the following conditions: denaturation at 94°C for 120 s, extension at 72°C for different times and fluorescence at different temperatures. Primer sequences, annealing times and temperatures, extension times and fluorescence temperatures are summarized in http://genome.ucsc.edu/). The average conservation scores were plotted against the nucleotides position.ES centers or peak positions detected by MAT were analyzed with CEAS http://www.biostat.jhsph.edu/~hji/cisgenome/). Additionally, identification of enriched motifs within ChIP-chip detected regions was done with CEAS http://www.genomatix.de/index.html).Sequence analysis for the detection of TF binding motifs was done with MATCH http://genome.ucsc.edu/. The closest TSS to each ES center was calculated in the application Microsoft Excel.The distribution of binding sites relative to TSS was analyzed, and a list of all RefSeq genes and their TSS was obtained from http://genome.ucsc.edu/. The number of ChIP regions and of regions from the random control set which overlap introns was determined using the intersect function of the Galaxy tool (http://g2.trac.bx.psu.edu/).Enrichment of binding sites in introns was determined in RefSeq genes and their intron/exon structure was obtained from http://www.biostat.jhsph.edu/~hji/cisgenome/). ES were determined for all RefSeq genes with transcript coding regions within 100,000 bp from the center of the ES. All RefSeq genes associated with an ES were joined into a single list which was used for Gene Ontology categorization. Gene Ontology categorization was done with GOFFA Association of binding sites identified by ChIP-chip with RefSeq annotated genes was performed with the software tool CisGenome Click here for additional data file.Table S2LowstringencySet.(XLS)Click here for additional data file.Table S3−10. Motifs with less than 50 hits in the HNF4α ChIP enriched regions and less than 25 hits in the random control regions have been excluded. P-Values<0E-15 were set to zero by Excel.Motif enrichment analysis with MATCH (DOC)Click here for additional data file.Table S4Motif enrichment analysis with RegionMiner . Analysis of motif enrichment for single transcription factor matrices was performed with Genomatix RegionMiner. Cutoffs for enriched or depleted motifs were set to |Fold Change|>1,3 and |Z-score|>20.(DOC)Click here for additional data file.Table S5Enrichment analysis for transcription factor matrices families. Analysis of enrichment for transcription factor matrices families was performed with Genomatix RegionMiner. Cutoffs for enriched or depleted families were set to |Fold Change|>1,3 and |Z-score|>20.(DOC)Click here for additional data file.Table S6http://genome.ucsc.edu/).HNFα binding site frequency varies between chromosomes. The number of HNF4α binding sites on different chromosomes was compared with the number of RefSeq annotated genes and the length of the chromosomes. Chromosome length and gene numbers were retrieved from ((DOC)Click here for additional data file.Table S7HNF4α binding site clusters. HNF4α binding site clusters were identified by scanning the genome for regions containing 10 or more binding sites within a window of 100.000 bp. Genes with a TSS located within or close to these clusters with a high density of binding sites are given in the last column.(DOC)Click here for additional data file.Table S8Genes closest to novel HNF4alpha binding sites.(XLS)Click here for additional data file.Table S9Gene ontology terms of metabolism, development and transport are overrepresented among HNF4α RefSeq target genes identified in this study. Genes were analyzed with the Arraytrack Software tool GOFFA (DOC)Click here for additional data file.Table S10Gene regulation upon Aroclor1254 treatment of Caco-2 cells.(XLS)Click here for additional data file.Table S11Comparison of RefSeq-annotated HNF4α targets identified by ChIP-chip to HNF4α targets identified by expression profiling in this study and in different publications. In the second column, the number of reported target genes from the relevant study, which could be associated to a current RefSeq annotation, is given. In the third column, the number of those RefSeq annotation is given, which could be also associated with a target gene identified in our ChIP-chip study. As 6670 from 18274 RefSeq Gene Symbols were identified as potential targets by ChIP-chip, the expected overlap by chance was 6670/18274*536 = 36%.(DOC)Click here for additional data file.Table S12Real-time PCR primer sequences and amplification protocol.(DOC)Click here for additional data file.


Klebsiella pneumoniae nif gene cluster, divided into seven operons, is one of the most studied systems. Its nitrogen fixation capacity is subject to complex cascade regulation and physiological limitations. In this report, the entire K. pneumoniae nif gene cluster was reassembled as operon-based BioBrick parts in Escherichia coli. It provided ∼100% activity of native K. pneumoniae system. Based on the expression levels of these BioBrick parts, a T7 RNA polymerase–LacI expression system was used to replace the σ54-dependent promoters located upstream of nif operons. Expression patterns of nif operons were critical for the maximum activity of the recombinant system. By mimicking these expression levels with variable-strength T7-dependent promoters, ∼42% of the nitrogenase activity of the σ54-dependent nif system was achieved in E. coli. When the newly constructed T7-dependent nif system was challenged with different genetic and physiological conditions, it bypassed the original complex regulatory circuits, with minor physiological limitations. Therefore, we have successfully replaced the nif regulatory elements with a simple expression system that may provide the first step for further research of introducing nif genes into eukaryotic organelles, which has considerable potentials in agro-biotechnology.Biological nitrogen fixation is a complex process requiring multiple genes working in concert. To date, the  Klebsiella pneumoniae has been extensively studied at the genetic level. A cluster of 21 genes organized into seven operons is required for the biosynthesis, activity, and regulation of nitrogenase, a complex enzyme consisting of two component metalloproteins. The process of dinitrogen reduction is stringently controlled in this organism, and nif gene transcription is regulated by a cascade system nifLA operon. Under nitrogen-limiting conditions, NtrC is phosphorylated and activates transcription of the nifLA operon. In the second tier of regulation, the nifLA gene products then control expression of the remaining nif operons. NifL regulates the activity of NifA in response to both nitrogen and oxygen 54-holoenzyme form of RNA polymerase (σ54), initiates transcription at the other nif promoters Nitrogen fixation is a pivotal process in global nitrogen cycling and is of huge ecological and agronomic importance. The ability to fix nitrogen is distributed in bacteria and archaea One of the fundamental aims of synthetic biology is to design regulatory and metabolic pathways that can be readily introduced into different biological systems to provide novel functions. An important consideration in the synthetic design is to achieve balanced levels of gene expression in order to provide the appropriate stoichiometry of molecular components. Quantitative and synthetic biology (QSB) is a powerful biotechnological tool that uses quantitative analysis and engineering approaches to manipulate biological systems to obtain the balanced expression of multiple genes. In prokaryotes, gene expression is mainly controlled at the transcriptional level, and the promoter is the most manipulatable element K. pneumoniae nif gene cluster was transferred into Escherichia coli thus creating the first engineered diazotroph nif cluster in this way is complicated by the number of gene products involved and the complex nitrogenase assembly pathway, which involves the biosynthesis of unique metalloclusters. Furthermore, as the ratios of the nif-encoded proteins are important for both nitrogenase biosynthesis In the 1970s, the nif genes to determine whether the recombinant genes could work independently of the native regulatory factors. T7 RNA polymerase is a single ∼100-kDa polypeptide that is widely used for gene expression in both prokaryotes and eukaryotes nif operons, the nif promoters were replaced with T7 promoter variants according to required promoter strengths. The lac operator was used to regulate the T7 promoters so that nif gene expression was responsive only to the small molecular inducer isopropyl-β-thiogalactoside (IPTG). Finally, we reassembled the recombinant nif genes to generate an active cluster that provided a high level of nitrogenase activity. Replacing the optimum T7 promoter with other T7 promoter variants resulted in a lower level of nitrogenase activity, confirming that coordinated and balanced expression of the nif gene cluster was essential for maximum activity. After induction, the recombinant system bypasses the native regulatory networks and some of the intrinsic physiological limitations.Here we used the T7 RNA polymerase transcription system for the expression of rpoN::kan, ntrBC::kan mutant alleles were moved into strain JM109 by P1 transduction. The himA::kan and himD::Tet mutations were constructed by a one-step method for gene inactivation in E. coli through λ Red recombination system Bacterial strains and plasmids used in this study are listed in E. coli growth were prepared as previously described 2HPO4, 3.4 g KH2PO4, 26 mg CaCl2·2H20, 30 mg MgSO4, 0.3 mg MnSO4, 36 mg ferric citrate, 7.6 mg Na2MoO4·2H20, 10 µg para-aminobenzoic acid, 5 µg biotin, 2% (w/v) glucose, and a nitrogen source as indicated . When necessary, 50 µg/ml ampicillin, 25 µg/ml chloramphenicol, 10 µg/ml tetracycline, and 25 µg/ml kanamycin were used.Luria-Bertani (LB) broth and M9 medium for 54-dependent nif operons with BioBrick interfaces. To construct pKU7017, seven nif operons were PCR-amplified from plasmid pRD1 XbaI and SpeI and inserted into the XbaI site of pACYC184, and then another six operons were assembled onto the plasmid backbone in sequence.The rationale of the genetic design is outlined in the nif operons (the nifLA operon was not included), in which all nif promoters and terminators were replaced with T7 promoter variants and T7 terminators, respectively. Single base-pair substitutions were introduced according to the relative strength of T7 promoter variants nif promoter-lacZ fusions. Primers with SpeI-HindIII restriction sites were used to amplify nif operons without the promoter and terminator, and then the SpeI-HindIII fragments were inserted into XbaI-HindIII sites of vector pET28a (Novagen). A synonymous mutation was made to delete the HindIII restriction site in the nifHDKTY operon. Because XbaI and SpeI are isocaudomers, this process created a mixed SpeI-XbaI junction that could not be cut with either endonuclease and did not influence the subsequent assembly of modulons. The nif genes with variant T7 promoters and corresponding T7 terminators were PCR amplified, each operon was also flanked with SpeI-XbaI restriction sites and a unique restriction site showed in Plasmid pKU7180 is a pACYC184 derivative carrying six tet promoter. To substitute the tetracycline resistance (tet) gene with the T7 RNAP gene on pBR322, we created an NcoI restriction site at the translation start site of the tet gene, then cloned the T7 RNAP gene into the NcoI/BamHI sites of the newly constructed vector. Plasmid pKU7450 is a pBluescript II SK (+) derivative carrying the Ptet::T7 RNAP cassette. The cassette was cut with HindIII/SacI from pKU7093 and then cloned into the multiple cloning site of pBluescript II SK (+).Plasmid pKU7093 is a pBR322 derivative containing the T7 RNA polymerase gene (T7 RNAP) under the control of the nif promoters to the lacZ gene. It is a pRW50 derivative, in which the segment of E. coli trp operon was deleted, and it contains the original ribosome binding site upstream and complete ORF encoded by lacZ. The nif promoters were PCR amplified from plasmid pRD1 Plsmid pRWX2 were used for the transcriptional fusions of E. coli MG1655 lacZYA mutant strain VH100T was co-transformed with pST1021 (from which the K. pneumoniae nifA gene is constitutively expressed) and the relevant plasmid containing the appropriate nif promoter (nifp) –lacZ fusion. Cells were grown overnight in M9 medium and then diluted into 10 ml fresh M9 medium, and β-galactosidase activities were measured when cells reached logarithmic growth phase.β-galactosidase assays were performed according to Miller K. pneumoniae M5a1, and E. coli JM109 (pKU7017) strains, cells were initially grown overnight in M9 medium. For optimal IPTG induction, the JM109  strain was grown in M9 medium to an OD600 of 0.4–0.6. The cells were then diluted into 5 ml nitrogenase activity assay medium in 25 ml sealed tubes (supplemented with appropriate antibiotics and IPTG), and grown to a final OD600 of ∼0.4. Air in the tube was repeatedly evacuated and flushed with argon. After incubation at 30°C (or 37°C) for 16–20 hr, 1 ml acetylene was injected, and the gas phase was analysed 3 hr later with a SHIMADZU GC-2014 gas chromatograph. Data presented are mean values based on at least three replicates.The acetylene reduction method was used to assay the nitrogenase activity as described The proteins were applied to a 10% (w/v) SDS/polyacrylamide gel and then analyzed by immunoblotting. The immunoblots were probed with a 1∶1000 dilution of NifH rabbit polyclonal antibody. The antiserum against NifH was a gift from Prof. Jilun Li of China Agriculture University. The antibody-antigen complex was visualized with alkaline phosphatase conjugated to goat anti–rabbit IgG. For western blot analysis, samples were taken just after testing nitrogenase activity, with 20 mg total protein (or supernatant) after sonication loaded for each sample.K. pneumoniae nif gene cluster, we first followed the BioBrick design principles nif operons with restriction sites. Each operon was also flanked with a unique restriction site to facilitate individual module replacement , and measured β-galactosidase activities. Under these conditions, the native nifJ and nifH promoters exhibited the highest expression levels amongst these σ54-dependent promoters, whereas the nifU and nifF promoter had the lowest expression level  was used to drive the structural genes nifHDKTY, which are highly expressed in diazotrophs, as the nitrogenase component proteins can represent up to 10% of total cell protein under nitrogen-fixing conditions nifJ, which is also highly expressed. A weak promoter  containing the redesigned nif gene cluster, hereafter referred to as the T7-dependent nif expression system. Transcription from the T7 promoters was driven by a separated plasmid (pKU7450), in which T7 RNA polymerase was expressed from the constitutive tet promoter . Notably, nitrogenase activity decreased at higher IPTG concentrations . This ctrations , possiblnif expression cassette and, in particular, the importance of relative promoter strengths, each of the six modulons was reconstructed by replacing the optimum T7 promoter with the other two T7 promoter variants, resulting in 12 alternative modulons. For example, PT7WT, the nifHDKTY modulon, was replaced with either the PT7M5 or the PT7M6 promoter variants to drive expression of the nifHDKTY modulon. When each of the variant modulons was introduced as single substitutions in the complete nif expression cassette, most replacements resulted in lower nitrogenase activities , and the genes himA and himD, encoding the α and ß subunits of IHF respectively  or 10 mM glutamine was present in the medium  or the wild-type T7 promoter (pKU7380). The level of activity in each case in the presence of ammonium was similar to that exhibited by the T7 nif cassette lacking nifL and nifA  may exist for modulating the system output in relation to the nitrogen source.K. pneumoniae, nifLA expression is oxygen sensitive nif promoters is repressed by oxygen, because NifL inhibits the activity of the NifA transcriptional activator in the presence of oxygen nif gene expression of the T7-dependent nif system, cells were grown aerobically and induced with IPTG under aerobic conditions. Western blotting with antibody raised against nitrogenase Fe protein indicated that the amount of NifH expressed was similar under both anaerobic and aerobic conditions, either 2 hr or 14 hr post induction . However, NifH apparently failed to fold properly, since no protein was evident in the supernatant after sonication and centrifugation of the cells  present in their promoters nif cassette in which transcription of the nif operons is driven by T7 RNA polymerase specific promoters and terminators. In this redesigned system, the native NifL and NifA regulatory proteins and the NifA UAS target sequences were removed. This should ablate the currently known mechanisms for transcriptional regulation in response to oxygen and fixed nitrogen. Accordingly, the T7-dependent nif system successfully bypasses oxygen regulation of nif transcription mediated by the NifL-NifA regulatory system , the T7 dependent nif system ; (B), the T7 dependent nif system including the nifLA operon driven by the T7 promoter ; (C), the T7 dependent nif system including the nifLA operon driven by the native σ54-dependent promoter . Activities were measured with cultures grown with 10 mM glutamate (black bars) or 10 mM ammonium (gray bars) after induction with 0.2 mM IPTG. Each experiment was repeated at least three times, and the error bars represent the standard error.(TIF)Click here for additional data file.Figure S2Influence of ammonium on the nitrogenase activity of T7 dependent nif cassette constructions. Nitrogenase activities of constructs with different promoter strengths (see gths see  were mea(TIF)Click here for additional data file.Table S1β-galactosidase activities expressed from K. pneumoniae nif promoters. β-galactosidase activities are shown as a percentage of nifHDKTY promoter activity. (Note that the nifLA promoter is not included). Each experiment was repeated at least three times, and the values shown are standard error.(DOC)Click here for additional data file.


The analysis revealed a differential expression of genes involved in metabolism, transport and host-pathogen interaction. Many of them appeared to be among the genes previously reported to be controlled by the CovRS two-component system. Indeed, the transcription profile of a ΔcovRS strain grown in high-glucose conditions was profoundly affected. In particular, of the total genes described to be regulated by glucose, ∼27% were under CovRS control with a functional role in protein synthesis, transport, energy metabolism and regulation. Among the CovRS dependent genes, we found bibA, a recently characterized adhesin involved in bacterial serum resistance and here reported to be down-regulated by glucose. ChIP analysis revealed that in the presence of glucose, CovR binds bibA promoter in vivo, suggesting that CovR may act as a negative regulator or a repressor. We also demonstrated that, as for other target promoters, chemical phosphorylation of CovR in aspartic acid increases its affinity for the bibA promoter region. The data reported in this study contribute to the understanding of the molecular mechanisms modulating the adaptation of GBS to glucose.Although the contribution of carbohydrate catabolism to bacterial colonization and infection is well recognized, the transcriptional changes during these processes are still unknown. In this study, we have performed comparative global gene expression analysis of GBS in sugar-free  Streptococcus agalactiae (GBS) is a Gram-positive β-haemolytic human pathogen commonly residing in the gastrointestinal tract of up to 50% of the healthy population. Although GBS is commonly associated with neonatal diseases Streptococcus pneumoniae, Streptococcus pyogenes and GBS has been recently proposed by Shelburne and colleagues The ability of GBS to survive in specific human niches mainly depends on its capacity to activate a number of regulatory networks. This is achieved by controlling at a transcriptional level the production of proteins involved in adhesion, nutrient acquisition, and survival against host immune system Pathogenic streptococci use two-component regulatory systems (TCS) to sensing signals from the environment and efficiently respond to them. The capsule synthesis regulator (CovRS) is the most studied TCS in GBS, reported to be responsible for the modulation of transcription for up to 7% of total genes in vitro model to define the response of GBS to glucose. Comparative gene expression analysis revealed that not only many transport and metabolic genes were affected, but also genes involved in host-pathogen interactions. We also provide evidence that CovR controls approximately one third of glucose-dependent genes, including virulence determinants such as bibA and the cyl gene cluster. Moreover, we identified a conspicuous group of glucose-regulated genes independent from CovR control, whose regulation appears to involve other regulatory proteins. The data reported in this paper aim to improve the understanding of the physiological mechanisms underlying GBS adaptation to glucose-rich environments.In this study we setup an ovRS come from an internal strain collection and have been previously described Escherichia coli DH10BT1, HK100 and BL21 (DE3) were obtained from Invitrogen and used for cloning  and expression (BL21 DE3) strains. Unless otherwise specified, for experiments testing the effect of glucose on transcriptional regulation, bacteria were grown in THB until late exponential phase, centrifuged and then resuspended in a complex medium (CM) containing 10 g/liter proteose peptone, 5 g/liter Trypticase peptone, 5 g/liter yeast extract, 2.5 g/liter KCl, 1 mM urea and 1 mM arginine. When they reached the mid exponential phase they were centrifuged, supernatant removed and resuspended in CM in the absence or presence of 55 mM glucose for 30 minute. Escherichia coli strains were grown in Luria–Bertani broth and supplemented with 100 µg ml−1 ampicillin.GBS type V strain 2603V/R and isogenic mutant strain 2603ΔccovRS, both grown as described in the previous paragraph. For each condition, four independent cultures were carried out in parallel. Total RNA was extracted from each culture with the RNeasy Mini Kit and treated with RNase-free DNase (both from Qiagen) according to the manufacturer's instructions. The concentration of total RNA was determined using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies). RNA integrity was verified using a Bioanalyzer 1000 (Agilent). RNAs from each culturing condition were pooled and subjected to cDNA synthesis and labeling, which were performed at Roche NimbleGen, Inc. . Changes in gene expression levels were evaluated by using the NimbleGen GBS DNA microarray . Hybridizations, staining, and processing were also performed at Roche NimbleGen. Scanned image and data were extracted and analyzed internally using NimbleScan software, as previously described http://www.ebi.ac.uk/microarray-as/ae/) and the submission accession number is E-MTAB-1100.Microarray comparison was performed for the wild-type strain 2603 V/R and the isogenic mutant strain ΔpotB, bibA, cfb, cylX, sap, sag1333, sag2021, sag0677 and gyrA are reported in T method potB, bibA, cfb, cylX, sap, sag1333, sag2021, sag0677 mRNA levels were normalized to gyrA, used as a housekeeping gene. The specificity of the amplified fragment was demonstrated by the melting curve, where a single peak was observed for each sample amplified with potB, bibA, cfb, cylX, sap, sag1333, sag2021, sag0677 and gyrA primers.Reverse transcription-polymerase chain reaction (RT-PCR) was carried out on 1 µg total RNA using ImProm-II reverse transcriptase and random primers (Promega). Real-time quantitative PCR was performed using Fast start universal SYBR Green Master (Roche) according to manufactur's instruction, in a Light Cycler 480 System (Roche). All samples were run in triplicate on 96-well optical PCR plates (Roche Diagnostics). The specific primers used to amplify cDNA fragments corresponding to E.coli, covR DNA coding sequence (sag1625) was amplified by PCR from GBS type V strain 2603V/R. Oligonucleotides used for amplification of the covR gene incorporated an NdeI or XhoI site in the forward or reverse primers, respectively (+ vector (Novagen). In order to express proteins, the plasmid containing covR gene was introduced into BL21 (DE3) (Invitrogen). E. coli BL21 (DE3) harboring covR was grown at 37°C to an OD600 of 0.5 in LB containing 100 µg ml−1 ampicillin. Expression of the recombinant protein was induced with 1mM isopropyl-beta-D-thiogalactopyranoside  and the culture shaken for 3h at the same temperature. After 3 hours, the cells were harvested by centrifugation, resuspended and disrupted by sonication. The purification on the soluble fraction was performed with His Gravi Trap columns . Protein concentration was calculated using the Bradford assay To produce a recombinant CovR as histidine–fusion protein in ectively , and werbibA promoter, a biotinylated DNA fragment corresponding to the promoter region of bibA (sag2063) was amplified by PCR from the GBS type V strain 2603V/R  of either unlabelled PbibA (as a specific competitor) or the promoter region of sag0017 (pscB) gene  amplified by PCR from GBS type V strain 2603V/R chromosome using specific primers  for 45 minutes at 4°C and incubated overnight with an anti-CovR mouse serum. CovR-DNA complexes were immuno-precipitated with 50% protein A slurry for 3 hours at 4°C in sterile disposable mini-columns (Bio-Rad). After four washing steps, the immuno-complexes were treated with RNase A and digested overnight with proteinase K. Cross-linking was reversed for 6 hours at 65°C and DNA extracted with organic solvents. The presence of the target promoter sequences in the chromatin immunoprecipitates was detected by quantitative real-time PCR. Quantitative real-time polymerase chain reaction (qPCR) analyses were performed on a Light Cycler 480 System (Roche) using LightCycler 480 SYBR Green I Master mix (Roche). After an initial denaturation step for 10 min at 95°C, amplification was conducted for 50 cycles with 10 s at 95°C, followed by 10 s primer annealing at 50°C and final extension at 72°C for 20 s. The purified DNA from ChIP experiments before (input) and after (eluate) the immune-precipitation was used for qPCR. Primers sets for the amplification of cylX, cfb, bibA and sag0017 promoter regions are listed in 2603 V/R GBS wild type strain and isogenic mutant strain ΔP<0.01), of which 257 were up-regulated and 383 were down-regulated. As expected, among the most regulated functional families, we found genes related to both energy metabolism and transport/binding  before been transferred for 30 minutes in a CM devoid of sugars (referred as no glucose condition) or containing 55 mM glucose (therein after referred as high glucose condition). A total of 640 genes were differentially regulated  and sag2167(arc-2), encoding for a carbamate kinase and an ornithine carbamoyltransferase, being highly down-regulated (up to 20-fold). Both enzymes are components of the arginine deiminase system, which has been suggested to sustain bacterial survival in acidic environments by catalyzing the release of ammonia from arginine sag1907 gene (eda-2), encoding for keto-hydroxyglutarate-aldolase/keto-deoxy-phosphogluconate aldolase, was also found to be among the most down-regulated. Conversely, few genes were slightly up-regulated, such as the ones belonging to the aspartate and serine metabolism families. A drastic down-regulation (up to 130-fold) of genes implicated in the metabolism of complex sugars was observed, as well as the locus comprising the ORFs from sag0033 to sag0042, codifying for components of the nan operon, responsible for the transport and metabolism of sialic acid. The list also encompasses: a carbohydrate kinase (sag1906) belonging to the PfkB family; a putative hexulose-6-phosphate synthase sag1812(ulaD); L-a ribulose-5-phosphate 4-epimerase sag1810(araD); a putative hexulose-6-phosphate isomerase (sag1811); and the sag0118(rbsK) gene encoding for a ribokinase. Genes encoding for proteins required for fermentation processes were also found to be down-regulated, including sag1637, sag0053 and sag0054, annotated as alcohol dehydrogenases . The down-regulation of genes codifying for proteins implicated in the biosynthesis and degradation of polysaccharides such as sag1901, glucuronyl hydrolase; sag0041, acetyl xylan esterase; sag1216, pullulanase; sag0856, glycogen synthase (glgA); sag0854, glucose-1-phosphate adenylyltransferase (glgC); sag0853 glycogen branching enzyme (glgB), was also observed.The expression of genes involved in a wide range of metabolic pathways was found to be dramatically modulated after 30 minutes in 55 mM glucose, indicating a rapid adaptation of GBS central metabolism to the availability of new nutrients. Transcript changes were observed in genes involved in aminoacid biosynthesis, with sag0745, coding for a putative transporter of the NRAMP family, involved both in Mn2+ and Fe2+ uptake sag1590, sag1591, sag1631 (belonging to the trk family) and sag1090. We also observed a fivefold up-regulation of the sag1711 gene, coding for a putative CorA protein involved in magnesium transport dps gene sag1444, coding for a putative peptide/proton symporter sag0947 to sag0949); a spermidine-putrescine transporter, potABCD (sag1108 to sag1111), implicated in the pathogenesis of Streptococcus pneumoniaesag0290 to sag0292 operon (regulated up to 8-fold), encoding a putative polar amino acid ABC transporter; the sag1145 gene, encoding for the sodium:alanin symporter protein; the sag0715 to sag0718 and sag0947 to sag0949 genes, encoding for amino acid ABC transporters. Furthermore, the transcription of genes encoding an ABC transporter specific for glycine betaine (sag0241 to sag0244), whose accumulation in Bacillus subtilis and Lactococcus lactis confers protection against osmotic and cold stress, was up-regulated sag1441 to sag1443 ORFs, encoding for the maltose-maltodextrin transport system ; sag0955 and sag1925 (msmK) genes, encoding a sugar-ABC transporter and a sugar transport ATP-binding protein, respectively; the ribose ABC transporter region ; the cellobiose ABC transporter sag0328(celC) to sag0330(celB). Moreover several phosphotransferase systems (PTS), that allow the uptake of various carbohydrate sources, such as sag1805, sag1813, sag1814, sag1948–1951, sag1898–1902 and sag0192 were found to be highly down-regulated (up to 120-fold).Several genes encoding transport proteins were found to be up-regulated in high glucose conditions. These included cyl gene cluster (sag0662 to sag0673), required for GBS hemolysin production cfb gene (sag2043), encoding the CAMP factor sag2063). Among factors involved in host cell adherence and invasion and repressed by glucose, we report sag1234, a gene encoding for the laminin binding protein Lmb, which promotes GBS adherence to host cells through the binding to laminin SodA (sag0788), a gene which plays a crucial role in oxidative stress sag1197), which cleaves hyaluronic acid, a connective tissue component promoting GBS spreading during infection, was significantly reduced. On the contrary, sag0677, a gene encoding an unknown function LPXTG protein, and sag2021, codifying a GP-340 binding protein sag1739(cydC) to sag1744, grouped in an operon previously reported to be involved in the respiration metabolism and to play a role in virulence and GBS growth in vivoPathogenic bacteria, by modulating the expression of surface-associated or secreted virulence factors, can adapt to host conditions and improve their capacity to persist in specific niches. In our experimental conditions the transcription of several known or putative virulence factors was down-regulated. In particular, the sag1677, that codes for a universal stress protein, whose expression was highly down-regulated (27-fold) following exposure to glucose. Several genes, including sag1135, sag1136 and sag1137, encoding for proteins involved in the stress response, were also down-regulated. Interestingly, these proteins are homologs to Gls24, a general stress protein of Enterococcus faecalis which has been reported to have a crucial role in stress response as well as in virulence The incubation of GBS in a high glucose medium results in a considerable change in the expression of genes involved in adaptation and stress response. A dramatic change was observed in the transcript of sag1128, sag2017, sag0554, belonging to the putative Cro/CI family and sag1749, sag1655, sag0427, being part of the putative Mer family of regulators, were 2–5 fold up-regulated. Of interest, the latter family has been reported to act as a key activator of the nitric oxide defense system in pneumococci, thus ensuring both survival and systemic infection sag0707). Bioinformatic analysis revealed that a number of transcriptional regulators, that were highly down-regulated under glucose conditions (up to 20-fold), has a cre box sequence in their promoter region (http://regprecise.lbl.gov/RegPrecise/gmregulon.jsp?gmproject_id=6875). They included: sag0277, encoding a Mga-like protein, a positive regulator of virulence in GAS sag1348, fruR, lactose phosphotrasferase system repressor; sag0119, rbsR, ribose operon repressor; sag0042, phosphosugar-binding transcriptional regulator belonging to RpiR family; sag2073, a transcriptional regulator belonging to GntR family and sag2161, encoding for a transcriptional regulator of the Crp/Fnr family.After 30 minutes of incubation with 55 mM glucose several transcriptional regulators were modulated. In particular, covRS mutant strain to glucose availability under the experimental conditions used for 2603 V/R GBS wild type  was comparable in the absence or presence of glucose, at prolonged incubation time rate GBS growth rate was higher at 55mM glucose (covRS mutant (defined as glucose-dependent-covRS independent genes) and showed the same regulation state of the wild type strain, while 174 genes were exclusively regulated in the wild type strain (referred as glucose dependent-covRS dependent genes), with 52 up-regulated and 127 down-regulated  presents a specific binding motif for CovR, as reported by Lamy et al.bibA promoter in vivo by Chromatin immune-precipitation (ChIP) analysis of bacterial cultures exposed for 30 minutes to 55 mM glucose. Protein-DNA complexes were immunoprecipitated with CovR antiserum and analyzed by qRT-PCR for the presence of bibA promoter region, using cylX and cfb promoters as positive controls and sag0017 promoter as negative. The amount of each promoter region in the eluate was first normalized to the amount in the input and subsequently reported as fold changes compare to wild type grown without glucose. As shown in bibA promoter region in GBS cultures exposed to high glucose (55 mM) levels compared to sugar-free conditions. This level is comparable to the levels of cfb promoter (4.7 fold) and cylX promoter (6.9 fold), whereas the negative control sag0017 promoter shows little or no changes upon high glucose exposure. As expected in the eluate from the isogenic ΔcovRS deletion mutant grown with or without glucose the level of PCR products is close to the detection limit. These data clearly show that CovR in presence of high glucose is able to bind bibA promoter region in vivo.To better define the mechanism of action of CovRS on the transcription of putative virulence factors, we investigated the regulatory activity of CovRS on the promoter of bibA promoter region, we performed electrophoresis mobility shift assay (EMSA) experiments by incubating a biotin-labeled DNA fragment corresponding to the promoter region of bibA with increasing amounts of recombinant CovR. We observed that the minimal quantity of protein necessary to induce a significant shift in the mobility of the bibA promoter was 2 µM (data not shown). To verify whether the binding of CovR to PbibA was specific, we performed competitive EMSA by incubating recombinant CovR protein with both 250- and 500-fold excess of unlabeled PbibA (specific competitor) or sag0017, a promoter lacking the binding motif for CovR (non-specific competitor). As displayed in PbibA fragment, while the addition of increasing quantities of unlabeled sag0017 had no effect on the ability of CovR to bind to PbibA. These data postulate a preferential binding of CovR to PbibA. Recently, Jiang and colleagues bibA promoter compared to the untreated recombinant CovR. The shift delay of the band relative to the phospho-CovR/PbibA complex was visible at a lower concentration than the one needed for the un-phosphorylated form of the protein. Altogether, these data confirm the capability of CovR to bind specifically the bibA promoter and that phosphorylation of CovR increases the binding to PbibA.To confirm that CovR interacts directly with the Escherichia coli subgroup that has adapted to grow as a harmless commensal in carbon-rich human intestine, but rapidly become invasive in the nutritionally poorer urinary tract Staphylococcus aureus, its colony spreading phenotype requires the expression of the agr gene, which is positively regulated by environmental glucose and carbon sources in vitro model used in this study, although hardly resembling a physiological status of GBS, mimics the adaptation of this bacterium to standard laboratory conditions in which is common the use of high-glucose media (i.e. THB). One of the limitations for setting in vitro experiments looking at the effect of carbon sources on bacterial response is the fact that, differently from what happens in vivo where the system is rapidly buffered (i.e. blood) metabolites generated during the incubation of bacteria with sugars may alter the pH of the milieu. In order to precisely delineate the impact of glucose on global GBS transcriptome and avoid the contribution of pH alteration to the modulation of gene expression, we limited the duration of the experiments to 30 minutes, a time point at which pH remained unvaried (data not shown).Glucose and other carbon sources are known to influence the lifestyle of many pathogens that adapt their metabolism to the nutritional composition of their host niches. Indeed, bacteria have evolved sophisticated methods for sensing carbon source availability to face the inter-bacterial competition for energy sources. For example, Alteri and co-workers have recently described a uropathogenic Streptococccus pneumoniae, Streptococcus pyogenes and GBS mal), a phosphotransferase (PTS) and a sucrose hydrolase (scrB), they observed an attenuated virulence in vivo were found to be down-regulated in our study, suggesting that the presence of high glucose levels may attenuate carbohydrate metabolism, rendering their expression dispensable. In line with this, we found a number of metabolic systems down-regulated by glucose such as genes involved in polyamine transport, biosynthesis and degradation of polysaccharides  and fermentation processes. We also observed that bacteria grown in high glucose are dividing more rapidly (data not shown), thus, as expected, genes encoding for DNA replication, recombination, repair and for membrane biosynthesis were found to be highly up-regulated, while genes encoding for enzymes involved in substrate degradation were found to be down-regulated  and invasive transcriptome profile (ITP). Interestingly, invasive strains show a mutated covS gene allele carrying 7-bp frameshift mutation. Experimental observation strongly support that the covS mutation is responsible for the PTP to ITP transition occurring during invasive infections bibA promoter in the presence of glucose by a phosphorylation dependent mechanism, postulate indeed that the mechanism of regulation is independent on CovR expression. Of interest, a few pH-dependent family genes reported by Santi and colleagues The exposure of GBS to glucose appears to modulate several genes coding for cell envelope proteins, likely to be involved in host-pathogen interactions. Although the number of up-regulated cell envelop genes is superior to the down-regulated ones, among the latter we found genes encoding for pore-forming toxins, such as hemolysin β, known to be crucial in promoting cell invasion and lysis argR (sag0500) and members of the AraC family (sag0432) and Rgg/GadR/MutR family (sag 1490), were among the genes differently modulated by glucose in the ΔCovRS background. In addition, a number of genes encoding for DNA and RNA metabolism, amino acid transport and enzymes involved in substrate degradation were also found to be uniquely modulated by glucose in the CovRS mutant strain.Somewhat surprisingly, the analysis of the genes modulated by glucose in a CovRS defective strain revealed a consistent number of genes (∼ 300) regulated under such conditions but not in wild type bacteria. This phenotype may indicate that a number of alternative regulatory mechanisms are activated by glucose when CovR is not expressed. Indeed, we found that a dozen of transcriptional regulators, including the arginine repressor In this paper, by defining the response of GBS to glucose we observed an extensive re-modeling of bacterial transcriptome. We also provide evidence that under such conditions, CovR plays a pivotal role by controlling a large number of glucose-dependent genes. Future investigation are deserved to understand whether strain-specific CovRS mutations alter the adaptive response to glucose availability and how this reflects into the infectious lifestyle of this pathogen.Figure S1Growth curve of 2603V/R strain in medium containing 55mM glucose or in sugar-free medium. Bacteria were grown in THB at 37°C until late exponential phase, centrifuged and then resuspended in a complex medium (CM). When they reached the mid exponential phase they were centrifuged, supernatant removed and resuspended in CM in the absence or presence of 55 mM glucose.(TIF)Click here for additional data file.Table S1qRT PCR validation of regulated genes.(XLS)Click here for additional data file.Table S2Primers used in this study.(XLS)Click here for additional data file.Table S3Expression of glucose-dependent/CovRS-dependent genes.(XLSX)Click here for additional data file.Table S4Expression of glucose-dependent/CovRS-independent genes.(XLSX)Click here for additional data file.


Saccharomyces cerevisiae can be performed by at least two distinct pathways and is influenced by the phosphorylation status of the carboxy-terminal domain (CTD) of RNA polymerase II (Pol II). Late termination of mRNAs is performed by the CPF/CF complex, the recruitment of which is dependent on CTD-Ser2 phosphorylation (Ser2P). Early termination of shorter cryptic unstable transcripts (CUTs) and small nucleolar/nuclear RNAs (sno/snRNAs) is performed by the Nrd1-Nab3-Sen1 (NNS) complex that binds phosphorylated CTD-Ser5 (Ser5P) via the CTD-interacting domain (CID) of Nrd1p. In this study, mutants of the different termination pathways were compared by genome-wide expression analysis. Surprisingly, the expression changes observed upon loss of the CTD-Ser2 kinase Ctk1p are more similar to those derived from alterations in the Ser5P-dependent NNS pathway, than from loss of CTD-Ser2P binding factors. Tiling array analysis of ctk1Δ cells reveals readthrough at snoRNAs, at many cryptic unstable transcripts (CUTs) and stable uncharacterized transcripts (SUTs), but only at some mRNAs. Despite the suggested predominant role in termination of mRNAs, we observed that a CTK1 deletion or a Pol II CTD mutant lacking all Ser2 positions does not result in a global mRNA termination defect. Rather, termination defects in these strains are widely observed at NNS-dependent genes. These results indicate that Ctk1p and Ser2 CTD phosphorylation have a wide impact in termination of small non-coding RNAs but only affect a subset of mRNA coding genes.Transcription termination in  Transcription termination is essential for generating normal transcripts and for the release of RNA Polymerase II (Pol II) from the DNA template, which prevents interference between adjacent transcription units. Transcription termination also plays an important role in the control of pervasive and hidden transcription. In yeast, transcription of mRNA coding genes is terminated by the Cleavage and Polyadenylation Factor/Cleavage factor I and II (CPF/CFI-II) that also cleaves the nascent RNA and polyadenylates the released transcript. The Nrd1p-Nab3p-Sen1p (NNS) complex terminates transcription of sn-/snoRNAs and cryptic unstable transcripts (CUTs), one of the main products of hidden transcription. NNS-dependent termination is tightly coupled to nuclear RNA processing by the Rrp6p/exosome complex The carboxy-terminal domain (CTD) of Rpb1 subunit of Pol II The Ser2/Ser5 phosphorylation gradients have been proposed to form a ‘CTD code’, sequentially recruiting proteins important for efficient transcription and co-transcriptional chromatin modification The CTD phosphorylation status is also thought to direct the choice between the two main yeast transcription termination pathways The distinction between the early and late termination pathways may not be strict, since several factors, including Pcf11p, appear to be involved in termination by both the “early” and “late” pathway ctk1Δ cells By contributing to the establishment of the CTD phosphorylation gradient, the CTD-Ser2 kinase Ctk1p is thought to influence the choice between the termination pathways. Loss of Ser2P affects the recruitment of late termination factors, such as Pcf11p and Rtt103p. Surprisingly however, a 3′-processing but not a termination defect has been observed at a CPF-dependent model gene in ctk1Δ were much more similar to mutation of the NNS-complex subunit Sen1p, than to mutation of CTD-Ser2P binding factors. Genome-wide tiling array analysis of CTK1 deletion shows readthrough at 42% of all snoRNAs, as well as readthrough at several CUTs and stable uncharacterized transcripts (SUTs). Unexpectedly we also found that a ctk1Δ strain does not present a major defect in mRNA termination as we only detected transcriptional readthrough at a few mRNA-coding genes. Our results show that the role of Ctk1p in early termination is more prominent than previously thought and suggest a significant impact of Ser2 phosphorylation on the mechanism of NNS-dependent termination.To investigate the role of Ctk1p systematically, we performed genome-wide expression analysis of Ctk1p mutants and several CTD binding factors. Surprisingly, the overall expression changes of CTK1 or BUR1 under the control of the GAL1 promoter was performed as described Yeast strains used in this study are listed in RNA was isolated by phenol extraction from cultures grown to early mid-log phase. Northern blot analysis was performed using standard protocols. Hybridization was performed either in 6× SSC, 5× Denhardt's solution, 0.1% SDS and 100 µg/nl fragmented haring sperm DNA buffer or in UltraHyb buffer (Ambion). Quantification of the signals was carried out using a Storm 820 phosphoimager. Oligonucleotide probes and primers used to amplify the PCR probes are listed in 2HPO4, 4 mM NaH2PO4, 200 mM sodium acetate, 0.25% NP-40, 2 mM EDTA, 1 mM EGTA, 5% glycerol, 20 mM PMSF, 1 mM benzamidine, EDTA-free protease inhibitor cocktail from Roche) and flash frozen. Cells were disrupted using a ball mill  and the extract cleared at 13krpm for 25 min. Immunoprecipitation assays were performed using IgG Fast Flow Sepharose beads . Proteins were eluted for 15 min at 37°C with 60 µl of lysis buffer and 80 µl 4× Laemmli buffer containing 50 mM DTT. RNAseA treatment was performed after IP on beads washed once with 1 ml Lysis buffer (10 µg/ml RNaseA for 20 min in 25°C).For immunoprecipitations, cells were grown to OD 1.0–1.6 and harvested. The cell pellet was resuspended in 4 ml of Lysis buffer , containing protease and phosphatase inhibitors using a genie-disruptor (Scientific Industries). Western blot analysis was performed using antibodies 8WG16 (gift from H.T.M. Timmers), 3E8, 3E10, 4E12 (Millipore) To analyze the phosphorylation status of RNA Pol II CTD after Ctk1p and Bur1p depletion, 4OD units of exponentially growing cells were harvested after growth in the appropriate medium and resuspended in 150 µl of 8 M urea. Cells were broken in a Magnalyser (Roche) and the lysate was cleared by centrifugation for 2 min at 4000 rpm. Alternatively, exponentially growing pcf11-2 and pcf11-ts2) were profiled two times from single inoculated cultures. Sets of mutants were grown alongside corresponding wt cultures and processed in parallel. Growth of ctk1Δ and rpb1-S2A for rpb1-S2A strain grew very poorly in SC. Dual-channel 70-mer oligonucleotide arrays were employed with a common reference wt RNA. All steps after RNA isolation were automated using robotic liquid handlers. These procedures were first optimized for accuracy (correct fold-change) and precision (reproducible result), using spiked-in RNA for calibration SEN1 and PCF11 were compared to wt Mat a strains. The reported fold-change is an average of the replicate mutant profiles versus the average of all wildtypes. Microarray data have been submitted to the ArrayExpress database (http://www.ebi.ac.uk/microarray) under accession number E-MTAB-1261 and to the GEO database (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE40254Each mutant strain was profiled four times from two independently inoculated cultures and harvested in early mid-log phase in SC medium with 2% glucose. An exception is Pcf11, for which two different alleles (ctk1Δ as described previously ctk1Δ and wt was more than 0.6 in the 150 bp regions downstream of the 3′ end (at least 4 out of 6 25 bp regions). Transcripts for which the 3′ end was less than 150 bp from the following transcript were excluded. Metagene analysis was performed by averaging the intensity over 25 bp regions for all ORFs and snoRNAs. For visualization in ctk1Δ using the library tilingArray in R http://steinmetzlab.embl.de/holstegeLabArray/.Tiling arrays were performed for two independent replicates of wt and 500 ml of cultures in early mid-log phase were crosslinked with 1% formaldehyde for 20 min at 25°C. The reaction was stopped with 300 mM glycine. Cells were washed with ice-cold TBS and FA lysis buffer . Cells were disrupted in FA-lysis containing protease and phosphatase inhibitors using a gene-disruptor. Chromatin was fragmented by sonication , resulting in fragment sizes of 300–500 bp. Chromatin extracts were incubated overnight at 4°C with antibody , 2 µl 3E8, 2 µl 3E10, 10 µl 4E12). 20 µl of dry protein A (for α-Nrd1) or protein A+G beads  were added and incubated for 1.5 hr at RT. For TAP-Pcf11, 20 µl of IgG sepharose beads were used. The beads were washed 2× with FA-lysis buffer, 2× with FA lysis buffer containing 500 mM NaCl, 2× with 10 mM Tris pH 8, 0.25 M LiCl, 0.5% Nonidet P-40, 0.5% sodium deoxycholate, 1 mM EDTA and 1× with TE pH 8.0. Samples were eluted with TE-SDS 1% at 65°C. Crosslinking was reversed at 65°C for ∼16 hr with 5 µg RNAse. Samples were treated with Proteinase K for 2 hr at 37°C. DNA was recovered with phenol extraction and a PCR purification kit (Qiagen). Samples were analyzed by qPCR with the primer pairs in ctk1Δ mutant were compared with expression changes of mutants of different CTD-interacting factors .Expression profiles that describe the genome-wide changes in gene expression upon mutation of different regulatory factors can provide detailed phenotypical information. For example similarities between the genome-wide expression signatures derived from mutation of different factors can indicate different types of interactions, including same protein complex or regulatory pathway membership  factors . For eac factors . Most tep<0.05, fold change (FC)>1.7). In keeping with previous observations that similar expression profiles may reflect interactions, loss of Ctk1p results in mRNA expression changes that overlap with changes observed upon mutation of several different binding partners of CTD-Ser2P. For example, the expression changes in ctk1Δ overlap with changes observed upon deletion of the Ser2P binder Set2p  er Set2p . Upon bier Set2p . As expe2p STE11. Besides2p STE11. Gene sectk1Δ is more similar to sen1-1, a member of the Ser5P binding NNS-complex, than to any of the Ser2P binding factors , it is clear that integrity of Ctk1p is nevertheless important for appropriate termination of snoRNAs.Deletion of n sen1-1 . To confene HEM4 , indicatnd snR82 . The samctk1Δ/rrp6Δ mutants when its conversion to the mature form is less efficient) migrates anomalously, with longer forms that extend in some cases for several hundred bases. These transcripts likely derive from delayed termination events that in most cases depend on the NNS pathway, since they are degraded in the wild type strain.In all these cases we also noticed that the snoRNA precursor , CUT152 and SUT277, upstream of the GRE1, ASK10, and ERF2 genes, respectively . This was confirmed by northern analysis for a few model genes in a ctk1Δ strain (BIO4/5 and MF(ALPHA)2 2 . Readthr(ALPHA)2 , F. MoreTogether these experiments reveal that the absence of Ctk1p has a general impact in termination of snoRNAs and likely other NNS-dependent transcripts but only affects termination of a subset of mRNA coding genes.ctk1Δ was dependent on its kinase activity. A kinase independent role for Ctk1p in the release of basal initiation factors from elongating polymerase has previously been described in vitroSNR13 transcripts revealed readthrough defects to similar levels as in ctk1Δ cells only when the kinase activity of Ctk1p is fully impaired in the Ctk1-D324N mutant  and combined the two in a double GALCTK1/PGALBUR1P strain. Depletion of Ctk1p for 3 hours was effective in preventing Ser2P to similar levels as in a ctk1Δ strain  than in ctk1Δ cells  is recruited at snoRNA genes in a Ctk1p-dependent manner.A different pattern is observed for Pcf11p. We observed recruitment of Pcf11p to snoRNA genes that was highest in the termination region. The Pcf11p ChIP signal was seemingly similar in wild type and 1Δ cells –L. Howevctk1Δ cells, suggests that transcription termination is delayed in the absence of functional Ctk1p. It has recently been shown that termination is sensitive to the elongation properties of RNA pol II, with “faster” polymerase mutants delaying termination and which is suggested to depend on the existence of kinetic competition between transcription and termination ctk1Δ cells, presumably because of the low or absent Ser2P levels, RNA polymerase might behave as a fast mutant with regard to termination. We therefore investigated whether altering the elongation properties of RNA Pol II might impact the delayed termination phenotype of ctk1Δ cells. Spt5p is an elongation factor that has an important role in regulating the processivity of RNA Pol II spt5ΔCTR) is lethal in a ctk1Δ strain. We therefore introduced the spt5ΔCTR mutation in a PGalCTK1 strain and analyzed the effects of Ctk1p depletion in an spt5ΔCTR context. We performed these experiments in an rrp6Δ background to visualize CUTs or snoRNA precursors as before. The spt5ΔCTR mutation alone produced slightly shorter precursors at most NNS-dependent genes  is not observed in the spt5ΔCTR context.The observation that longer transcripts, presumably representing primary termination products, can be observed at NNS-dependent transcription units in nt genes , consistrpb1-S2A mutant shows similar expression changes as ctk1Δ, lacking extensive additional changes compared to ctk1Δ that would be expected upon a global termination defect. These results indicate that Ser2P is not essential for the late termination pathway, but has in fact a more prominent role in the early termination pathway than previously anticipated. The current model that the early termination pathway is dependent on CTD-Ser5P and the late termination pathway on Ser2P The results show that removal of the CTD-Ser2P kinase Ctk1 results in readthrough at many snoRNAs, CUTs, SUTs and some mRNAs. Although several mRNAs show readthrough, there is no global defect in mRNA termination. The possibility that this is caused by residual Ser2P has been ruled out, since the The finding that Ser2P is not essential for mRNA termination by the CPF/CF complex is surprising, since previous studies have demonstrated that several of its subunits  are recruited in a Ctk1p- (and Ser2P-) dependent manner. Binding of Pcf11p and another termination factor, Rtt103p, to the CTD has clearly been shown to be dependent on Ser2P on the CTD ctk1Δ or in kinase dead cells than in S2A cells, in which every Ser2 in the CTD has been mutated to alanine. Although this might suggest that Ctk1p also exerts its role in NNS-dependent termination via the phosphorylation of other substrates, the clear effect of the S2A mutation, both on model substrates and genome-wide, indicates a positive role of the CTD-Ser2P phosphoisoform. Previously, several genome-wide studies have shown that Ser2P is low in the early phases of transcription, i.e. at positions where NNS termination occurs The extensive readthrough observed at NNS-terminated genes is indicative of an important role of Ctk1p in termination at these targets. We observed a somewhat stronger effect in It is theoretically possible that Ctk1p affects a minor component of termination at snoRNAs and CUTs that is CPF-dependent. Consistently, we and others have recently shown that the NNS- and the CPF/CF pathway can recognize very similar signals and the choice of the pathway is strongly dependent on the position of the signals relative to the transcription start site ctk1Δ strain to give longer transcripts. Instead, we observe a clear upshift in size of the whole set of snoRNAs precursors (or CUTs) analyzed in this context, most of which are unstable and NNS-dependent .How does phosphorylation of the CTD at Ser2 impact NNS termination? One possibility is that the onset of Ser2P, occurring relatively early in transcription e mutant –I, S6. T1Δ cells  and S5, ctk1Δ cells and its suppression by the spt5ΔCTR mutant (rpb1-E1103G) and interpreted to indicate kinetic competition between termination and elongation rpb1-E1103G mutation was shown to aggravate the termination phenotype of sen1 mutants ctk1Δ cells (or a S2A-CTD Rpb1p mutant) the absence of Ser2P translates into Pol II transcriptional properties that resemble those of a “fast” Pol II mutant. The spt5ΔCTR mutant might suppress the delayed termination phenotype by impacting the transcription properties of the Ser2P-less polymerase. The results presented in this study indicate that further mechanistic analyses of Ctk1 and CTD-Ser2P are both required and will likely be rewarding, given the altered role that the results demonstrate for both.Alternatively, Ser2P could affect the processivity or the speed of the polymerase and progressively induce a termination mode that favors the function of the CPF/CF complex at the end of mRNA genes. This effect might be already detected in a termination-sensitized context at NNS terminators. This could easily explain the delayed termination phenotype (of which the readthrough might be the extreme consequence) in R mutant . DelayedFigure S1Loss of CTK1 results in readthrough at snoRNAs.  Northern blot analysis of snR43, snR82, and snR60 transcripts in ctk1Δ and sen1-1 cells The positions of the probes are indicated above the Northern blots. Readthrough transcripts (RT) and precursor transcripts are indicated. RT species are detected with probes in the downstream genes. TUB1 mRNA was used as a loading control.(TIF)Click here for additional data file.Figure S2Loss of CTK1 results in readthrough at CUTs, SUTs and small ORFs. Northern blot analysis of transcripts derived from (A) SER3, (B) BIO5 and (C) CUT882. Readthrough transcripts (RT) and longer unstable transcripts are indicated. Note that RT transcripts at the CUT882 locus are not efficiently detected by northern blot unless degradation is also impaired in the ctk1Δ/rrp6Δ double mutant. (D) Northern blot analysis of NEL025c, NGR060w CUTs and snR33 precursors in strains metabolically depleted for Ctk1p and/or Bur1p in Pgal-CTK1 and Pgal-BUR1 strains. An rrp6Δ background was used to allow detection of unstable RNA species. Transcripts were revealed with double stranded probes that span the entire gene. (E–F) Metagene analysis displaying the average probe intensity over 25 bp regions in wt and ctk1Δ, aligned by the 3′ end of small (<600 bp) or long (>3000 bp) ORFs.(TIF)Click here for additional data file.Figure S3ctk1Δ cells are not generally defective for mRNA termination. Northern blot analysis of CYC1, ACT1 and ARO8 RNAs in a ctk1Δ strain. Thermosensitive mutants of the CPF/CF complex (rna14-3 and rna15-2) were used for comparison. The analysis was also performed in an rrp6Δ background to allow detection of unstable RNA species (right). Note the presence of high levels of readthrough transcripts that are partially unstable in CPF/CF mutants at the non-permissive temperature (2 hours at 37°C). Normally terminated RNAs are instead produced in ctk1Δ cells.(TIF)Click here for additional data file.Figure S4Loss of Ctk1p mainly affects the levels of Rpb1 CTD-Ser2P. (A and B). Western blot analysis showing the levels of the different Rpb1 CTD phosphoisoforms in a ctk1Δ cells (A) and in conditions of metabolic depletion of Ctk1p and/or Bur1p (B). Depletions of Ctk1p and Bur1p was obtained by growth of Pgal-CTK1 or Pgal-BUR1 strains in the presence of glucose for 6 hours.(TIF)Click here for additional data file.Figure S5Recruitment of termination factors at snoRNA termination sites in ctk1Δ.  Positions of the genomic regions analyzed by ChIP-qPCR.  ChIP analysis of Rpb3 in wt and ctk1Δ at snR5, snR13 and snR82. ChIP values represent the average of 3 biological replicates as in snR5, snR13 and snR82 in wt and ctk1Δ cells. Average of 4 biological replicates.  Pcf11-TAP occupancy at snR5, snR13 and snR82 in wt and ctk1Δ. Average of 2 biological replicates. All ChIP values represent percent enrichment TEL V is used as a negative control. Nrd1p and Pcf11p levels relative to Rpb3p are shown in (TIF)Click here for additional data file.Figure S6Nrd1p association with Rpb1p is higher in ctk1Δ cells. Co-immunoprecipitation experiment using Nrd1p-TAP as bait. Associated proteins are revealed by western blot using specific antibodies as indicated. Immunoprecipitation was performed in the presence or absence of RNase A. An increased association of Nrd1p with RNA Pol II and specifically the CTD-Ser5P form was consistently observed. Dashed line indicates removal of lanes from blot.(TIF)Click here for additional data file.Table S1List of genes in the clusters of .(XLSX)Click here for additional data file.Table S2Yeast strains.(XLS)Click here for additional data file.Table S3Northern probes and ChIP primers.(XLS)Click here for additional data file.


Identification of regulatory elements within the genome is crucial for understanding the mechanisms that govern cell type–specific gene expression. We generated genome-wide maps of open chromatin sites in 3T3-L1 adipocytes (on day 0 and day 8 of differentiation) and NIH-3T3 fibroblasts using formaldehyde-assisted isolation of regulatory elements coupled with high-throughput sequencing (FAIRE-seq). FAIRE peaks at the promoter were associated with active transcription and histone modifications of H3K4me3 and H3K27ac. Non-promoter FAIRE peaks were characterized by H3K4me1+/me3-, the signature of enhancers, and were largely located in distal regions. The non-promoter FAIRE peaks showed dynamic change during differentiation, while the promoter FAIRE peaks were relatively constant. Functionally, the adipocyte- and preadipocyte-specific non-promoter FAIRE peaks were, respectively, associated with genes up-regulated and down-regulated by differentiation. Genes highly up-regulated during differentiation were associated with multiple clustered adipocyte-specific FAIRE peaks. Among the adipocyte-specific FAIRE peaks, 45.3% and 11.7% overlapped binding sites for, respectively, PPARγ and C/EBPα, the master regulators of adipocyte differentiation. Computational motif analyses of the adipocyte-specific FAIRE peaks revealed enrichment of a binding motif for nuclear family I (NFI) transcription factors. Indeed, ChIP assay showed that NFI occupy the adipocyte-specific FAIRE peaks and/or the PPARγ binding sites near PPARγ, C/EBPα, and aP2 genes. Overexpression of NFIA in 3T3-L1 cells resulted in robust induction of these genes and lipid droplet formation without differentiation stimulus. Overexpression of dominant-negative NFIA or siRNA–mediated knockdown of NFIA or NFIB significantly suppressed both induction of genes and lipid accumulation during differentiation, suggesting a physiological function of these factors in the adipogenic program. Together, our study demonstrates the utility of FAIRE-seq in providing a global view of cell type–specific regulatory elements in the genome and in identifying transcriptional regulators of adipocyte differentiation. Humans consist of a few hundred types of specialized-function cells. Spatial and temporal transcriptional regulation of genes is essential for manifestation of cellular phenotypes. Identification of regulatory regions in the genome is central to understanding the mechanism of cell type–specific gene regulation. Recently developed high-throughput sequencing technology and computational analyses allow genome-wide investigation of the genome's chromatin structure. Using the FAIRE-seq technique, we identified the genome's open chromatin regions, which harbor regulatory elements in adipocytes. Open chromatin regions distal to genes' transcription start sites significantly differ among cell types. Multiple cell type–specific open chromatin regions exist near genes regulated during adipocyte differentiation. Computational motif analysis of adipocyte-specific open chromatin regions revealed enrichment of a binding motif for the NFI transcription factor family. These factors bind to the regulatory elements near adipogenic PPARγ, C/EBPα, and aP2 genes and regulate their expression. Overexpression of NFIA in 3T3-L1 cells resulted in robust induction of these genes and lipid droplet formation without differentiation stimulus and knockdown of NFIA or NFIB significantly suppressed both induction of genes and lipid accumulation during differentiation. Our study demonstrates the utility of FAIRE-seq in providing a global view of regulatory elements and in identifying transcriptional regulators of cellular functions. Sequencing allowed identification and mapping of the human genome Traditionally, regulatory elements have been identified by DNase I hypersensitivity assay combined with Southern blot analysis and secretes hormones and metabolites to communicate with other organs, maintaining systemic metabolic homeostasis The adipocyte is central in controlling energy balance and whole-body glucose and lipid homeostasis cis-regulatory elements in the genome and identifying transcriptional regulators of adipocyte differentiation.Our study took an unbiased approach to mapping adipocyte-specific regulatory elements in the genome by using FAIRE in 3T3-L1 adipocytes (on day 0 and day 8 of differentiation) and NIH-3T3 fibroblasts. We show that the FAIRE peaks contain regulatory elements such as promoters, enhancers and insulators, and that adipocyte-specific non-promoter FAIRE peaks are functionally linked to genes regulated during differentiation—about half these peaks being overlapped by PPARγ. We show that highly regulated genes in adipocyte differentiation are associated with clusters of multiple adipocyte-specific non-promoter FAIRE peaks. Furthermore, because FAIRE does not require a prioi knowledge of bound transcription factors, we could employ computational motif analyses of DNA sequences from the adipocyte-specific FAIRE peaks in an unbiased manner and identify a motif for nuclear family I (NFI) transcription factors in addition to motifs for PPAR and C/EBPs. We show the functional role of NFIA and NFIB in adipocyte differentiation. We demonstrate the utility of FAIRE-seq both in providing a global view of cell type–specific −4. By using ChIP-seq analyses, we also generated genome-wide maps of binding sites for PPARγ, the master regulator of adipocyte differentiation, for RXRα, its heterodimer partner, for histone H3 lysine 4 trimethylation (H3K4me3), and for CCCTC-binding factor (CTCF) Regulatory elements in the genome are characterized by open chromatin structures accessible to regulatory factors Klf15 and Pparg, both transcription factors up-regulated by differentiation, and both important in adipocyte differentiation Klf15, Pparg, CebpaMgllSrebf1 and cidecWe next compared the FAIRE peaks in 3T3-L1 cells on day 0 and day 8 and in NIH-3T3 cells. The promoter FAIRE peaks were relatively constant among the three groups. Over 70% of those peaks on day 0 and day 8 3T3-L1 cells and in NIH-3T3 cells were shared by all three groups . In contTo determine whether non-promoter FAIRE peaks were functionally associated with cell type–specific gene expression, we analyzed the relationship between the presence of the adipocyte- or preadipocyte-specific non-promoter FAIRE peaks and the change in gene expression during adipocyte differentiation. Those FAIRE peaks were enriched in the vicinity of genes, expression levels of which were highly induced or suppressed during adipocyte differentiation . Importa−055) (PPARγ is key regulator of adipocyte development −055) . An exteAs shown in genomic loci  and S3, Genes that were highly induced by adipocyte differentiation often harbored multiple adipocyte-specific FAIRE peaks and/or PPARγ binding sites in their vicinity, as suggested by the linear correlation between the number of the associated adipocyte-specific FAIRE peaks and the robustness of the induction of the gene by adipocyte differentiation . See Fi and testRecent genome-wide studies revealed clustering of open chromatin regions detected by Dnase I hypersensitivity assay or by FAIRE in the genomes of CD4+ T cells −12, one-sided Fisher test). Neighbors of randomly selected genes were not significantly up-regulated GCCAAThere were several other motifs for transcription factors, their functions not previously linked to adipocyte differentiation  and S7. We next asked whether overexpression of these factors influence adipocyte differentiation. We amplified NFIA and NFIB coding sequences from cDNA prepared from adipocytes, and cloned them into retroviral pMXs-puro vectors. We also made a dominant negative NFIA that lacks the C-terminal transactivation/repression domain (NFIA-DN) To dissect the mechanism by which NFIs regulate PPARγ, C/EBPα and aP2, we examined DNA sequences of the adipocyte-specific FAIRE peaks and/or the PPARγ binding sites in the vicinity of these factors and found that some of them have NFI binding motifs as listed in Collectively, we demonstrated that the combination of FAIRE-seq and computational motif analyses is useful in identifying novel regulators of adipocyte differentiation.The 3T3-L1 adipogenic cell line was established by isolating clonal sublines of mouse fibroblast line 3T3 cis-regulatory elements are often not conserved between human and murine adipocytes even though the expression pattern of genes is conserved could be a mechanism by which cells maintain key gene regulations against genomic changes during evolution. Clustering of regulatory elements could also result from an accumulative effect of such evolutional genomic changes.We demonstrated that genome-wide mapping of open chromatin regions by FAIRE-seq is a simple, accurate method that allows a snapshot view of regulatory elements in the genome. Although open chromatin regions detected by FAIRE-seq include promoters of transcribed genes, enhancers and insulators, open chromatin regions that vary in two different conditions likely contain regulatory elements that play roles in the specific biological process. By comparing open chromatin regions in preadipocytes and adipocytes, we identified the adipocyte- and preadipocyte-specific FAIRE peaks in the genome. Functionally, we demonstrated that the adipocyte-specific FAIRE peaks were associated with genes up- regulated by adipogenesis while the preadipocyte-specific FAIRE peaks were associated with genes down-regulated by adipogenesis . Adipocyand discover unknown DNA binding factors that co-localize with the transcription factors of interest, for example, see Computational motif analysis is used to discover new transcription-factor binding motifs in sequences inferred from genome-wide studies such as ChIP-seq To our knowledge, few studies have employed motif analysis and our unbiased approaches in investigating enhancer-like DNA regions. Mikkelsen et al. recently employed ChIP-seq for H3K27ac to define enhancer regions specific for adipocyte differentiation. Both studies similarly detected the motifs for PPAR, C/EBPs and AP-1 in the most enriched motifs. There are, however, differences. Mikkelsen discovered PLZF and SRF as novel negative regulators Siersbæk et al. recently employed DNase-seq to investigate genome-wide change in open chromatin structure at various time points during 3T3-L1 differentiation Nfia, Nifb, Nifc and Nfix-deficient mice were documented The NFI family was identified as site-specific DNA-binding protein that bound to the adenovirus origin of replication 3T3-L1, NIH-3T3, 3T3-F442A and HEK293T cells were maintained in DMEM, supplemented with 10% FBS. For adipocyte differentiation, two days after confluence, 3T3-L1 cells were treated with dexamethasone (1 µM), IBMX (0.5 mM), and insulin (5 µg/ml) (DMI) for 48 hours, followed by treatment with insulin alone, with medium replacement every two days thereafter. For differentiation of 3T3-F442A, cells were treated with insulin (5 µg/ml) after confluence, with medium replacement every two days.All animal works have been conducted according to the institutional guidelines.Generation of characterization of antibodies for human PPARγ and human RXRα was described previously 6 cells were re-suspended in 800 µl of MC lysis buffer  and incubated on ice for ten minutes. After spinning for four minutes at 8000 rpm, the pellet was re-suspended in 400 µl SDS lysis buffer  and incubated on ice for ten minutes. Glass beads  (Polysciences Inc. #05483-250) were added and the DNA was sheared by sonicator. Next, we added 200 µl cold ChIP dilution buffer , and after spinning for one minute at 8,000 rpm, supernatant was transferred to a new 1.5 ml tube. Aliquote was taken, de-crosslinked, purified by phenol/chloroform extraction, and run on a gel to ensure average fragment sizes of 300 bp. Remaining samples were processed three times by phenol/chloroform extraction to recover DNA not bound by nucleosome in the water phase. The samples were de-crosslinked by overnight incubation at 65°C and purified by ethanol precipitation. They were subsequently treated with RNase A , purified by QIAquick PCR purification kit (Qiagen) and used for subsequent analyses.FAIRE experiments were performed based on a protocol published by Giresi et al. ChIP was performed as descried previously −4. Operations such as intersections, unions, and subtractions of genome regions were performed with a web-based GALAXY genome analysis tool High-throughput sequencing was performed by using the Genome Analyzer System (GA II) (Illumina) as described elsewhere Average profiling of FAIRE and histone modifications near transcription start sites or FAIRE peaks were generated using “sitepro” in the CEAS package −4. We then classified each peak into tertiles  for either day the peak that had the higher percentile  Statistical clustering analyses of the PPARγ binding sites and the adipocyte-specific FAIRE peaks were performed as described in references −4 and p-value report threshold of 0.05. We used the licensed version of TRANSFAC database (Release 2010.4) Enrichment analyses of known motifs were performed with AME ver. 4.6.0 in the MEME suite −4, normalized by total nucleotide length. Motif enrichment ratios were determined by dividing the normalized adipocyte enrichment values by preadipocyte values.Motif enrichment ratios (adipocyte-/preadipocytes-specific FAIRE) for motifs in the TRANSFAC or JASPAR CORE database were determined by a method described in reference MEME ver. 4.3.0 The Gel shift assay and luciferase reporter assay were performed as previously described The 3T3-L1 cells were transfected with either control siRNA or siRNA for murine NFIA and NFIB  by using Lipofectamine RNAiMAX (Invitrogen) just before they reached confluence. Induction of differentiation (the DMI treatment) was started two days after confluence, as described in a method for differentiation of 3T3-L1 cells.The 3T3-L1 adipocytes were washed with PBS, fixed with formalin for 30 minutes at room temperature, rinsed with 60% isopropanol and stained with oil red O solution—freshly made by mixing 0.5% oil red O in isopropyl alcohol and water (3∶2)—and left to sit for one hour; the cells were then washed with water and dried.Total RNA was isolated using TRIzol reagent (Invitrogen), then 0.5 µg of the total RNA was reverse transcribed using high-capacity cDNA reverse transcription kits (Applied Biosystems #4375222) and random hexamers. Real-time quantitative PCR (SYBR green) analysis was performed on a 7900HT Fast Real-Time PCR System (Applied Biosystems). Primer sequences are listed in Transcriptome analysis of 3T3-L1 during differentiation by using a GeneChip Mouse Genome 430 2.0 array (Affimetrix) was described previously We amplified NFIA and NFIB coding sequences from cDNA prepared from adipocytes using primers listed in FAIRE-seq and ChIP-seq raw data are deposited into the DNA data bank of Japan (DDBJ accession number: DRA000378).Figure S1Genomic distribution and characterization of promoter and non-promoter FAIRE peaks in 3T3-L1. (A) Location analysis of FAIRE peaks relative to RefSeq genes in 3T3-L1 (day 0). Promoter FAIRE peaks were defined as those located within +/−500 bp of RefSeq transcription start sites (TSSs). Notably, only 8% of the non-promoter FAIRE peaks were located in the −5 kb proximal promoter region, and the vast majority of them were located in distal regions such as introns and intergenic regions. (B) Average profiles of FAIRE and H3K4me3 signals around the TSSs of genes with high, moderate and low expression levels. Signal intensity from microarray data was used for classification by the signal's expression levels. The X-axis indicates distance from the TSS. (C) Percent fractions of the FAIRE peaks (promoter and non-promoter) that overlapped CTCF binding sites as well as H3K4me1 and H3K4me3 positive regions. (D) Average profiles of FAIRE, H3K4me1, H3K4me3, and H3K27ac signals around the FAIRE peaks in promoter and non-promoter regions. The X-axis shows distance from the center of the FAIRE peaks. The FAIRE peaks located within +/−100 bp from RefSeq TSSs were analyzed for promoter FAIRE peaks. The promoter FAIRE peaks showed H3K4me3(+)/H3K4me1(−) modification whereas the non-promoter FAIRE peaks showed H3K4me3(−)/H3K4me1(+) modification.(TIF)Click here for additional data file.Figure S2Mgll, Adipor2 and Slc2a4. Clusters of multiple adipocyte-specific FAIRE peaks and/or PPARγ binding sites were located in genomic regions near Mgll (A), Adipor2 (B) and Slc2a4(Glut4) (C) in 3T3-L1 adipocytes. In some cases—e.g., Slc2ar4 (Glut4) and Ybx2 in (C)—multiple genes were located in such regions. Bars below the FAIRE signal represent statistically significant FAIRE positive peaks (FDR<10−4). Red asterisks indicate the adipocyte-specific FAIRE peaks on day 8 (see Adipor2 tested in Clustering of multiple adipocyte-specific non-promoter FAIRE peaks and PPARγ binding sites near (TIF)Click here for additional data file.Figure S3Cebpa, Srebf1and Cidec. Clusters of multiple adipocyte-specific FAIRE peaks and/or PPARγ binding sites were located in genomic regions near Cebpa (A), Srebf1 (B) and Cidec (C).Clustering of multiple adipocyte-specific non-promoter FAIRE peaks and PPARγ binding sites near (TIF)Click here for additional data file.Figure S4Binding sites for PPARγ and RXRα in 3T3-L1 cells. (A) De novo motif analysis (MEME) of the center 150 bp of the PPARγ/RXRα binding regions (top 400) in 3T3-L1, day 8. Of note, there is a 5′ extension AGT, which corresponds to the interaction between the PPARγ hinge region and DNA identified by crystal structure analysis (TIF)Click here for additional data file.Figure S5Mrpl12, Slc25a10 and Gcgr and (B) co-regulated Hsd11b1, G0s2 and Lamb3. Note, there are clusters of the adipocyte-specific FAIRE peaks (asterisks) and the PPARγ binding sites encompassing the co-regulated genes. (C) Microarray analysis showing co-regulation of Mrpl12, Slc25a10 and Gcgr, and co-regulation of Hsd11b1, G0s2 and Lamb3 included in the clusters of multiple adipocyte-specific FAIRE peak and PPARγ binding sites.Co-regulation of neighboring genes during adipocyte differentiation.  Genomic loci near (A) co-regulated (TIF)Click here for additional data file.Figure S6Known motif enrichment analysis of the adipocyte- or preadipocyte-specific FAIRE peaks (JASPAR CORE motifs). Enrichment analysis of the adipocyte- (left) and the preadipocyte-specific (right) FAIRE peaks for known motifs in the JASPAR CORE database performed with AME in the MEME suite by the same methods used in (TIF)Click here for additional data file.Figure S7De novo motif analysis of the adipocyte-specific FAIRE peaks. MEME ver. 4.3.0 was used to identify de novo motifs over-represented in the adipocyte- and preadipocyte-specific FAIRE peaks and PPARγ binding sites. After removing repeat regions, DNA sequences from the center 150 bp regions of top 800 cell type–specific FAIRE peaks with higher signals were used for the analyses. Identified enriched de novo motifs were analyzed by TOMTOM in the MEME suite for comparison against a database of known motifs.(TIF)Click here for additional data file.Figure S8Suppression of adipocyte differentiation by knockdown of NFIA and NFIB by using different siRNAs.(TIF)Click here for additional data file.Figure S9Comparison of FAIRE Peaks between undifferentiated 3T3-L1 and NIH-3T3 cells. (A) A heat map showing enrichment of the 3T3-L1- and NIH-3T3-specific FAIRE peaks in the vicinity (+/−25 kb from TSS) of genes sorted by using the ratio of expression levels in 3T3-L1 or NIH-3T3. The FAIRE peaks specific to 3T3-L1 or NIH-3T3 were enriched in the vicinity of genes whose expression levels were higher in 3T3-L1 or NIH-3T3, respectively. (B) Known motif analysis of the 3T3-L1-specific FAIRE peaks (vs NIH-3T3). The binding motif for EBF and PPARγ/RXR were among the top scored motifs.(TIF)Click here for additional data file.Figure S10The enrichment ratios of the top motifs in Mikkelsen's study (TIF)Click here for additional data file.Figure S11Klf5, Pparg and Cebpa gene. DHS stands for DNase I hypersensitive sites.Comparison of DNase-seq in Siersbæk's study (TIF)Click here for additional data file.Table S1Sequences of primers.(DOC)Click here for additional data file.