Background: Chronic ethanol consumption induces pancreatic β-cell dysfunction and metabolic syndrome.Results: Ethanol-induced Atf3 inhibits glucokinase transcriptional activity through direct binding or Atf3/Pdx-1/Hdac1 axis on glucokinase promoter.Conclusion: ATf3 fosters β-cell dysfunction via Gck down-regulation and triggers T2D, which is ameliorated by in vivo Atf3 silencing.Significance: The presented data uncover a new role for Atf3 as a potential therapeutic target in treating type 2 diabetes. Gck gene expression and promoter activity in pancreatic β-cells were suppressed by chronic ethanol exposure in vivo and in vitro, whereas expression of activating transcription factor 3 (Atf3) and its binding to the putative Atf/Creb site (from −287 to −158 bp) on the Gck promoter were up-regulated. Furthermore, in vitro ethanol-induced Atf3 inhibited the positive effect of Pdx-1 on Gck transcriptional regulation, enhanced recruitment of Hdac1/2 and histone H3 deacetylation, and subsequently augmented the interaction of Hdac1/Pdx-1 on the Gck promoter, which were diminished by Atf3 siRNA. In vivo Atf3-silencing reversed ethanol-mediated Gck down-regulation and β-cell dysfunction, followed by the amelioration of impaired glucose tolerance and insulin resistance. Together, we identified that ethanol-induced Atf3 fosters β-cell dysfunction via Gck down-regulation and that its loss ameliorates metabolic syndrome and could be a potential therapeutic target in treating type 2 diabetes. The Atf3 gene is associated with the induction of type 2 diabetes and alcohol consumption-induced metabolic impairment and thus may be the major negative regulator for glucose homeostasis.Chronic ethanol consumption induces pancreatic β-cell dysfunction through glucokinase (Gck) nitration and down-regulation, leading to impaired glucose tolerance and insulin resistance, but the underlying mechanism remains largely unknown. Here, we demonstrate that  Chronic ethanol consumption is well established as an independent risk factor for type 2 diabetes (T2D)Gck down-regulation, little is known about the exact role and regulatory mechanism of Atf3 in ethanol-induced Gck down-regulation.Glucokinase plays a critical role in blood glucose homeostasis, serving as a glucose sensor for glucose-stimulated insulin secretion in pancreatic β-cells and as the major regulator of glucose uptake in hepatocytes , 10. RecGck promoter, respectively, and are positive regulators for Gck gene expression . All experiments were performed between passage P4 and P20. Islet cells were isolated from overnight-fasted C57BL/6 mice using a previously described collagenase digestion technique (Rat INS-1 pancreatic β-cells were cultured in RPMI 1640 medium containing 11.1 mm) and time points . Thereafter, the effective concentration (100 mm) and time (24 h) of ethanol, which show the most effective effects on the decrease of insulin content and ATP production and the increase of apoptosis, were selected. The treatment of ethanol with less than 50 mm or more than 100 mm did not have effective effects. Although there are still conflicting claims in the relative calculation between millimolar and in vivo percentage (%) of blood alcohol levels  and time (24 h) of ethanol is currently accepted and considered as an acute ethanol consumption in an in vitro model  and the changes of phenotypes (apoptosis), we have treated the INS-1 cells or isolated islet cells with ethanol at the different concentrations  ethanol diet for 8 weeks as reported previously  originally purchased from The Jackson Laboratory  were used in all experiments. Individually caged mice were placed on a Lieber-Decarli regular liquid diet . Mice were pair-fed with the control eviously . All aniATF3 and ATF3 with a C-terminal deletion and cDNA expression vectors were generous gifts from Dr. T. Hai (Ohio State University). ATF3 cDNA was amplified by PCR using the primer forward 5′-GGAATTCGCAAAGTGCCGAAACAAG-3′ and reverse 5′-ACGCGTCGACTTAGCTCTGCAATGTTCC-3′ and cloned into pcDNA3 or pEGFP-C2 (Invitrogen). Pdx-1 expression vector (pcDNA3/Pdx-1) was provided by Dr. T. Stein (Ohio State University). Rat Gck promoter reporter pRGP-1003/Luc, pRGP-404/Luc, pRGP-287/Luc, and pRGP-84/Luc were kindly provided by Dr. Y. Ahn (Yonsei University College of Medicine). pRGP-158/Luc vector, deletion mutant, or site-mutated plasmids were constructed in the pGL3-Gck/Luc plasmid by the two-step PCR method or QuikChange site-directed mutagenesis (Stratagene) according to the manufacturer's instructions. The used primer sets for each mutated construct are follows: pRGP-158/Luc, forward 5′-TTTCTCTATCGATAGGTACCGGTGACAGGAGTAGAGAG-3′ and reverse 5′-CCAAGCTGATCTCGAGCCCG-3′; mCREB1, forward 5′-CTGCTCCTTAGTAAGTGATACAGGCACTAAGGCAC-3′ and reverse 5′-GTGCCTTAGTGCCTGTATCACTTACTAAGGAGCAG-3′; mCREB2, forward 5′-GTAACAGGCACTAAGGCACAAACCTGGGAACTGAGCAG-3′ and reverse 5′-CTGCTCAGTTCCCAGGTTTGTGCCTTAGTGCCTGTTAC-3′; mCREB3, forward 5′-CACTGACCTGGGAACTGGCCAGGTGGTAATGTCTAC-3′ and reverse 5′-GTAGACATTACCACCTGGCCAGTTCCCAGGTCAGTG-3′; mCREB4, forward 5′-CTGGCAGTCACTGCAGATACAGGGTGACAGAGTG-3′ and reverse 5′-CACTCTGTCACCCTGTATCTGCAGTGACTGCCAG-3′; mCREB5, forward 5′-CACTGCAGTGACAGGGATACAGAGTGGTCCCATG-3′ and reverse 5′-CATGGTGACCACTCTGTATCCCTGTCACTGCAGTG-3′; mCREB6, forward 5′-CACTGCAGATACAGGGATACAGAGTGGTCACCAT-3′ and reverse 5′-ATGGTGACCACTCTGTATCCCTGTATCTGCAGTG-3′; mAP1, forward 5′-GTCTACCAGGCTGGCATACACTGCAGTGACAGGG-3′ and reverse 5′-CCCTGTCACTGCAGTGTATGCCAGCCTGGTAGAC-3′; mAP2, forward 5′-GACAGGGTGACAG AGTGTACACCATGGTGACAGGAG-3′ and reverse 5′-CTCCTGTCACCATGGTGTACACTCTGTCACCCTGTC-3′; mPdx-1, forward 5′-CTGCATGGTGGCTCTAGATATAGAATGGTCACCATAG-3′ and reverse 5′-CTATGGTGACCATTCTATATCTAGAGCCACCATGCAG-3′; ΔPdx-1, forward 5′-GTTTTCTGCATGGTGGAATGGTCACCATAGAAAC-3′ and reverse 5′-GTTTCTATGGTGACCATTCCACCATGCAGAAAAC-3′; and ΔATF, forward 5′-GGCTGGCAGTCACTGCAGTGGTCACCATGGTG-3′ and reverse 5′-CACCATGGTGACCACTGCAGTGACTGCCAGCC-3′.Human wild-type After transfection or treatment, the cells were lysed, and luciferase activity was measured using the Luciferase Assay System .Atf3- (sc-72029) and mouse (sc-38761) or rat Pdx-1 (sc-10840) siRNAs were purchased from Santa Cruz Biotechnology. The cells were plated at 60–70% confluence and transfected with siRNA complexes or only with transfection reagents using Lipofectamine 2000 (Invitrogen) following the protocol recommended by the manufacturer.The human (sc-29757) or rat Gck (NM_010292), forward 5′-GTGCTGCTCAAGCTGGTAGA-3′ and reverse 5′-GCGATTTATGACCCCCGCTA-3′; rat Gck (NM_001270849), forward 5′-GACAGTC CTCACCTGCAACA-3′ and reverse 5′-GCATTTGTTGGTGCCCAGAG-3′; mouse Glut2 (NM_031197), forward 5′-ACCGGGATGATTGGCATGTT-3′ and reverse 5′-GAACACGTAAGGCCCAAGGA-3′; rat Glut2 (NM_012879), forward 5′-ACTGGCACATCCTACTTGGC-3′ and reverse 5′-CAGTCGACGCCTCTTCCTTT-3′; mouse Atf3 (NM_007498), forward 5′-GGAAAACTGGCTTCCTGTGC-3′ and reverse 5′-TGGCCATTGGACAACCTCAA-3′; rat Atf3 (NM_012912), forward 5′-CTCTAGCCGCTCTCTGGACC-3′ and reverse 5′-CGGCATTCACACTCTCCAGT-3′; mouse Gapdh (NM_008084), forward 5′-GGTTGTCTCCTGCGACTTCA-3′ and reverse 5′-TAGGGCCTCTCTTGCTCAGT-3′; and rat Gapdh (NM_017008), forward 5′-GGACCAGGTTGT CTCCTGTG-3′ and reverse 5′-ATTCGAGAGAAGGGAGGGCT-3′. The quantitative reverse transcriptase-PCR analysis was performed by using SYBR Green PCR Supermix (Bio-Rad) to detect the real time quantitative PCR products of reverse-transcribed cDNA according to the manufacturer's instructions  and was subjected to reverse transcription using reverse transcriptase (Promega) at 42 °C for 1 h, and the resulting cDNA was amplified by PCR using gene-specific primers. The primers were designed using the Primer 3 program and cross-checked by a BLAST search of the NCBI database. The primer sets are as follows: mouse ructions . The prim Tris-HCl, pH 7.9, 1.5% glycerol, 50 μg/ml BSA, 1 mm DTT, 0.5 mm phenylmethylsulfonyl fluoride, 2 μg of poly(dI-dC), 1 ng of 32P-labeled probe (5′-TGCAGTGACAGGGTGACAGA-3′), and 10 μg of nuclear extract. Reactions were incubated at 25 °C for 20 min and subsequently analyzed by electrophoresis through nondenaturing stock polyacrylamide gels (6 or 10%) in 0.5× TBE buffer containing 44.5 mm Tris-HCl, pH 8.2, 44.5 mm boric acid, and 1 mm EDTA. After the gel was pre-run at 100 V for 2 h, electrophoresis was performed at 270 V for 2 h at 4 °C. The gels were exposed to x-ray films using two intensifying screens at −70 °C.DNA mobility shift assays were performed as described previously . In brieBlood was collected by cardiac puncture from mice that had fasted overnight. Sera and relevant peripheral tissues were stored at −20 °C and used subsequently to assess the levels of triglycerides. Triglycerides were measured by colorimetric assays. For glucose tolerance test and insulin tolerance test, the mice were fasted at 8:00 a.m. for 6 h and then injected intraperitoneally with 1g/kg glucose or 1.5 units/kg regular human insulin, respectively. Blood samples were collected from the tail vein at time 0 (before injection), 30, 60, 90, and 120 min after injection, and the blood glucose level was measured using a portable glucose meter  . The levCells were lysed in RIPA buffer at 4 °C, vortexed, and then centrifuged at 16,000 rpm for 10 min at 4 °C. The supernatant was mixed in Laemmli loading buffer, boiled for 4 min, and then subjected to SDS-PAGE. For endogenous complexes, mitochondrial lysates (1 mg) fractionated from the cells were immunoprecipitated with 2 μg of antibody and immunoblotted.in situ apoptosis detection kit  as described previously  for 15 min. All procedures were performed as described previously .3), and formaldehyde cross-links were reversed by heating at 65 °C for 6 h. Proteinase K was added to the reaction mixtures and incubated at 45 °C for 1 h. DNAs of the immunoprecipitates and control input DNAs were purified using a QIAquick PCR purification kit (Qiagen Inc.) and then analyzed by regular PCR using rat Gck promoter-specific primers. Alternatively, quantitative PCR was performed using the same primers in the presence of SYBR Green PCR Supermix (Bio-Rad) to detect the real time quantitative PCR products of chromatin immunoprecipitation samples according to the manufacturer's instructions (Gck promoter (−283 to −135), forward 5′-CGTAGAGGGCTCTGCTCCTT-3′ and reverse 5′-CAAAGGCCTCTCTACTCCTGTC-3′; rat Gck promoter (−127 to −28), forward 5′-GTCCCAGTTTTCTGCATGGT-3′ and reverse 5′-GAGTAGATGCCTCCCGTCAG-3′; and qChIP analysis of rat Gck promoter (−125 to +15), forward 5′-CCCAGTTTTCTGCATGGTGG-3′ and reverse 5′-CGAGCTCAGTCACAGTCGAT-3′.The ChIP assays were performed according to the manufacturer's protocol . In brief, after treatment, cells were cross-linked with 1% formaldehyde in medium for 15 min at 37 °C and then washed with ice-cold PBS and resuspended in 200 μl of SDS sample buffer containing protease inhibitor mixture. The suspension was sonicated 10 times for 30 s with a 1-min cooling period on ice between times and pre-cleared with 20 μl of protein A-agarose beads blocked with sonicated salmon sperm DNA for 30 min at 4 °C. The beads were removed, and the chromatin solution was immunoprecipitated overnight with anti-Atf3, Pdx-1, Stat5, Ac-K18 histone H3 , Ac-K8 histone H4 , and polymerase II  antibodies at 4 °C, followed by incubation with protein A-agarose beads for an additional hour at 4 °C. The immunocomplexes were eluted with 100 μl of elution buffer  was used to deliver siRNA via intravenous injection . Similarly, mRNA levels (D–F) of Gck and Glut2, a glucose transporter, and the Luc activity (G and H) of rat pancreatic Gck promoter pRGP-1003/Luc were significantly reduced in islet cells or INS-1 cells exposed to 100 mm ethanol, which was ameliorated by 4-methylpyrazole, an inhibitor of cytochrome P4502E1 . Ethanol treatment significantly decreased the Luc activity of the Gck promoter between −1003 and −287 bp, although we did not detect significant reductions between −158 and −84 bp, suggesting that the consensus binding site for a repressive transcription factor induced by ethanol was located between −287 and −158 bp. These results were confirmed using the pRGP-287/Luc and pRGP-158/Luc constructs (B). Also, we know that de novo protein synthesis as a repressive transcriptional factor is required for ethanol-repressed Gck transcriptional activity using cycloheximide, a de novo protein synthesis inhibitor (C and D).To determine the region of -1 cells A. Ethanonstructs B. Also, nhibitor , C and DGck promoter activity, we investigated how Gck promoter activity is regulated by searching a 129-bp consensus sequence between −287 and −158 bp of the 5′-flanking region of the Gck promoter using the TRANSFAC transcription factor binding database. Illustrated in Fig. 3A, five potential binding sites for Atf/Creb that contained the TAAC, TGAA, TGAG, or TGAC element, in addition to two binding sites for Ap-1 (GTCA), were found in the Gck promoter region . Because stress-inducible Atf3 is still considered as a dual-face transcription factor that activates or represses a gene expression  (B–F). So, we wondered whether ethanol exposure affects Atf3 gene expression in vivo and in vitro (G and H). Atf3 was strongly increased in pancreatic tissue and islet cells of ethanol-fed mice or ethanol-treated INS-1 cells, indicating that de novo protein synthesis of Atf3 protein by ethanol may act as a negative transcription regulator to reduce Gck gene expression.To understand the molecular mechanisms by which ethanol inhibits pression , we firsA shows that ATF3 overexpression repressed Gck transcriptional activity through a direct interaction with the consensus binding sites of Atf/Creb located between −287 and −158 bp of the Gck promoter. The specific role of Atf3 within the proximal −287-bp region of the Gck promoter was confirmed by cotransfection with ATF3 or inactive ATF3(ΔC) and pRGP-287/Luc or pRGP-158/Luc . The pRGP-287/Luc activity was significantly decreased by Atf3, but there was a small reduction by Atf3 in pRGP-158/Luc-transfected cells. A TRANSFAC search revealed that the pRGP-158/Luc promoter also has two potential binding sites for Atf/Creb (TGAC) and one for Ap-1 (GTCA), but mutations of their consensus elements were not responsive to Atf3 (data not shown). Therefore, to confirm the functional activity of putative binding sites for Atf3 in pRGP-287/Luc, plasmids containing the putative binding sites were reconstructed by point mutagenesis . As shown in Fig. 4D, only pRGP-287(mCreb6)/Luc, which contains point mutations at the neighboring sites for mCreb4 and mCreb5, did not respond to ATF3 overexpression or ethanol treatment, whereas other constructs containing potential Atf3-binding site mutations still responded to them, suggesting that Creb4 and Creb5, located between −185 and −174 bp of the Gck promoter, are essential for the inhibitory responsiveness of ethanol-induced Atf3. These are also confirmed by electrophoretic mobility shift assays (EMSAs) using a labeled oligonucleotide covering the −190 to −171-bp region (Creb4/5(W)) in cells overexpressing ATF3, ATF3(ΔC), or ATF3(ΔN) . Binding complexes were observed in nuclear extracts of ATF3- or ATF3(ΔN)-transfected cells but not in those of ATF3(ΔC)-transfected cells. Addition of an excess amount of the unlabeled competitor Creb4/5(W) (50- or 100-fold) completely blocked the binding of Atf3 to the Gck promoter. To increase the specificity of the −190 to −171-bp region, three 20-bp wild-type oligonucleotides (Ap-1(W), Creb1(W), and Creb2/3(W)) that cover the putative binding site containing the sequence of response elements for Ap-1 or Atf/Crebs, respectively, and the mutated oligonucleotide Creb4/5(M), originating from wild-type Creb4/5(W), were designed . A 100-fold molar excess of unlabeled oligonucleotide for wild-type Creb4/5(W) (2nd lane) completely abolished the formation of the binding complex in nuclear extracts of ethanol-treated cells, whereas any oligonucleotides for mutated Creb4/5(M), including wild-type Ap-1(W), Creb1(W), and Creb2/3(W), did not compete . The specificity of Atf3 in the binding complexes was also confirmed in the results of a supershift assay using an anti-Atf3 antibody. The Atf3-DNA binding was much stronger in ethanol-treated INS-1 cells (no competitor lane) than those in nontreated cells (control). The recruitment of Atf3 to the Gck promoter was confirmed in vivo by chromatin immunoprecipitation. A 149-bp PCR product covering the putative Atf/Creb (from −283 to −135) of Gck promoter was detected in the nuclear extracts of ethanol-treated cells, but not in untreated cells, immunoprecipitated with the anti-Atf3 antibody (H and I). There was no binding in chromatin immunoprecipitated with the anti-Stat5 antibody. As well, chromatin binding in anti-Atf3 immunoprecipitates was significantly increased in Atf3-transfected or ethanol-treated cells, which was strongly decreased by Atf3 siRNA , indicating that Atf3 is specifically recruited to Atf/Creb binding region of the Gck promoter to result in a decrease of its transcriptional activity in ethanol-treated cells.Fig. 4Gck expression are controversial (Gck expression (A). The reduction of the Gck promoter activity by Atf3 or ethanol was potently increased by Pdx-1 depletion (B), whereas the recovering effects of Pdx-1 were potentiated by Atf3 silencing or ATF3(ΔC) (C and D), suggesting that Pdx-1 may counteract the repressive effects of Atf3 or ethanol on Gck transcriptional activity. Two putative Pdx-1-binding sites, TAAT and TGAT from −105 to −94 bp, were 72 bp from the core Atf/Creb binding sequence in the pRGP-287/Luc reporter (E). To determine whether these sites include the binding region for Pdx-1, we generated constructs via the deletion  or point mutation  of putative binding sites for Pdx-1 in the pRGP-287/Luc-promoter. Pdx-1-enhanced pRGP-287/Luc activity was significantly decreased in pRGP-287(ΔPdx-1)/Luc or pRGP-287(mPdx-1)/Luc-transfected cells, indicating that the conserved binding site of Pdx-1 is located between −105 and −94 bp of the Gck promoter. The counteracting roles of Atf3 and Pdx-1 on Gck transcriptional regulation were further confirmed by using the construct in which Atf3-binding sites in Gck promoter are deleted . The reduction of its activity by Atf3 was potentiated by the deletion of the Pdx-1-binding site (ΔPdx-1), which was rescued by the deletion of the Atf3-binding site, indicating that Atf3 and Pdx-1 may have opposite effects on Gck transcriptional activity through a direct interaction. Next, we hypothesized that the negative effect of ethanol on Pdx-1-mediated Gck transcriptional activation may be caused via the up-regulation of Atf3, which prevents Pdx-1 recruitment to its putative binding site in the Gck promoter. To this, cells exposed to ethanol in the presence of Atf3 siRNA were assayed by ChIP analysis using primer sequences covering the Pdx-1-binding site (from −127 to −28). The binding of Pdx-1 to the putative binding region of the Gck promoter was reduced in ethanol-treated cells but not in Atf3 siRNA  or ATF3(ΔC)-transfected cells (data not shown), suggesting that induced Atf3 may indirectly suppress Gck transcriptional activity by preventing Pdx-1 recruitment to its putative binding site.Although the effects of Pdx-1 on oversial , our datpression A. The reepletion B, whereaATF3(ΔC) , C and Dreporter E. To detAtf3 may inhibit Pdx-1-mediated Gck transcription by decreasing histone acetylation on the Gck promoter, we have quantified the amount of Gck gene promoter associated with acetylated histone H3 or H4. To this, ChIP analysis was performed by using the primers covering Pdx-1-binding sites from −127 to −28 bp. As expected, histone H3 acetylation on the Gck promoter was lower in ethanol-treated (A) or ATF3-overexpressed cells (B), correlated with reduction in p300 binding, whereas the recruitment of histone deacetylase, Hdac1 and -2, to the Pdx-1 binding region of Gck promoter was increased in ethanol-treated cells, which were markedly attenuated and reversely rescued by Atf3 depletion or trichostatin A (TSA), an inhibitor of histone deacetylase . Also, quantitative PCR using ChIP samples revealed that ethanol-induced Atf3 directly binds to the Gck promoter despite no Atf3-binding sites, whereas recruitment of Pdx-1, Ac-H3, and RNA polymerase II to the promoter was significantly reduced in ethanol-treated cells, which were reversely attenuated by Atf3 depletion (D), demonstrating the specificity of their recruitment by Atf3. Additionally, the inhibition of histone deacetylase activity by TSA may partially restore the recruitment of Pdx-1, Ac-H3, and polymerase II to the Gck promoter after ethanol treatment, although there was no impact on Atf3 recruitment (E), indicating that Atf3 may be an upstream regulator of Hdac1/2 activation.Next, to examine whether -treated A or ATF3ed cells B, correlf3 siRNA C. Also, epletion D, demonsruitment E, indicaGck transcriptional activity by enhancing the activity of histone deacetylase (A). The increase of pRGP-158/Luc activity by Pdx-1 was significantly decreased by ethanol treatment or ATF3 overexpression, which was restored by TSA or Atf3 siRNA, indicating that the activated histone deacetylase may play an essential role in the inhibitory effects of Atf3 on Pdx-1-mediated Gck transcriptional activity. Also, ethanol-induced Atf3 inhibits Pdx-1-mediated Gck transcriptional activity by triggering a physical in vitro and in vivo interaction of Pdx-1 with Hdac1 rather than p300 (B and C). Immunoprecipitated Pdx-1 directly interacted with endogenous Atf3 induced by ethanol or overexpressed GFP-ATF3 but not with GFP-ATF3(ΔC). Conversely, the interaction of p300 with Flag-Pdx-1 was significantly decreased by ethanol treatment or ATF3 overexpression. Additionally, Gck down-regulation in ethanol-treated β-cells was correlated with the induction of Atf3 and the reduction of nuclear localization of Pdx-1, which were reversely rescued by Atf3 siRNA (D).We next investigated whether ethanol-induced Atf3 could inhibit Pdx-1-dependent cetylase A. The inhan p300 , B and Cf3 siRNA D.Gck down-regulation and metabolic syndrome, a loss-of-function study was performed through in vivo Atf3 siRNA injection. Among four siRNA candidates, we selected 356-Atf3 siRNA, which had the highest efficiency for Atf3 silencing in various tissues (A and B). As expected, the impaired glucose tolerance  and insulin tolerance  induced by ethanol consumption were markedly inhibited by the administration of Atf3 siRNA. Triglyceride accumulation and reduced plasma insulin levels in ethanol-fed mice were also attenuated by Atf3 knockdown (G and H), correlated with restoring the reduced ATP (I). Similarly, the reduction in glucose-stimulated insulin secretion  and the production of nitrite or ROS (K) in islet cells of ethanol-fed mice also depended on the presence of Atf3. Together with the amelioration of pancreatic β-cell dysfunction, in vivo Atf3 silencing inhibited ethanol-induced β-cell apoptosis, which was associated with the restoration of Gck, insulin, and Pdx-1 expression (L and M). These results suggest that the Atf3 gene is associated with the induction of T2D and alcohol consumption-induced metabolic impairment and thus may play a major negative regulator for glucose homeostasis.To confirm the specific upstream role of Atf3 on ethanol consumption-induced  tissues , A and Bnce ITT; F inducednockdown , G and Huced ATP I. Similaon GSIS; J and thee or ROS K in islepression , L and MGck gene expression through direct interaction with the Atf/Creb-binding site (−185/−174) of the Gck promoter. Additionally, Atf3 directly interacts with Pdx-1 and specifically recruits Hdac1/2 to the Gck promoter in ethanol-treated β-cells, thereby repressing functional Pdx-1 on Gck transcriptional regulation. In vivo Atf3 silencing ameliorates ethanol-mediated metabolic syndrome and pancreatic β-cell dysfunction. All of these findings are summarized in In this study, we provide evidence that ethanol-induced Atf3 suppresses Gck transcriptional activity in ethanol-fed mice, based on the following observations. (i) The reduction of Gck transcriptional activity by ethanol was potentiated by Atf3, which was inhibited by Atf3 depletion. (ii) Two putative Atf3-binding sites that are essential for the inhibitory responsiveness by Atf3 were identified between −185 and −174 bp of the Gck promoter. (iii) Atf3 also binds to the Pdx-1-binding sites between −102 and −92 of the Gck promoter, resulting in chromatin remodeling via histone H3 deacetylation.This study demonstrates a functional role of Atf3 as a major upstream regulator that negatively regulates Glut2, and Gck . Despite the lack of an Atf3-binding site, Atf3 still induced a small reduction in pRGP-287(ΔAtf)/Luc activity, which was similar to the small reduction in the pRGP-158/Luc promoter  on the pRGP-158/Luc promoter, the product does not contain Atf3-binding sites and may present only low responsiveness for Atf3. Therefore, it is important to determine how Atf3 acts as a negative upstream regulator for Pdx-1 functional activity at the −158-bp proximal region of the Gck promoter. Quantitative ChIP assay revealed that ethanol-induced Atf3 binds to the proximal −158-bp region, whereas recruitments of Pdx-1, acetylated H3, and RNA polymerase II were significantly decreased in ethanol-treated cells, which were ameliorated by Atf3 depletion (D), demonstrating that Atf3 association with Gck promoter is a critical step for histone H3 deacetylation. Despite the decreased recruitment to the Gck promoter and expression of Pdx-1 in ethanol-treated cells, how the formation of Atf3/Pdx-1/Hdac1/2 complexes is increased in response to ethanol is unknown. Previously, it was demonstrated that Pdx-1 phosphorylation may determine the interaction of Pdx-1 with p300/Cbp or Hdac1/2 in the regulation of the insulin gene, which may depend on the concentration of glucose . Therefore, to define the precise role of Atf3 in ethanol-mediated Gck down-regulation and β-cell dysfunction, additional studies using pancreas-specific knock-out models are required. Nevertheless, we propose that in vivo Atf3 silencing may be sufficient to improve metabolic syndrome and pancreatic β-cell dysfunction by ameliorating ethanol-induced Gck down-regulation. In contrast with the ameliorating effects of Atf3-silencing mice in vivo, it will be possible that Atf3 knock-out mice may conversely potentiate ethanol-mediated Gck down-regulation and β-cell dysfunction. Because stress-inducible Atf3 is a dual-face transcription factor that activates or represses gene expression . From these results, we propose that Atf3 may play an important role in ethanol-mediated metabolic alteration, and it may be strongly associated with T2D.We also confirmed the specific upstream role of Atf3 in chronic ethanol-induced y system . In vivo β-cells , A and Bpression , it may pression , 40. FurGck promoter may have been a major molecular mechanism by which ethanol reduced Gck expression and pancreatic β-cell dysfunction and apoptosis. Also, Atf3-dependent interaction of Pdx-1 with Hdac1/2 and subsequent inactivation of Pdx-1 and chromatin remodeling may represent an additional molecular mechanism by which ethanol-induced Atf3 decreases Gck down-regulation (Gck transcriptional activation via direct binding to the putative binding site and by indirect binding with Pdx-1/Hdac1/2 on the Gck promoter. Additionally, our findings suggest that strategies based on the inhibition of Atf3 may be of benefit in the treatment of ethanol-mediated glucose impairment and metabolic syndrome.In this study, the direct interaction of Atf3 with the Atf/Creb-binding site of the gulation . Taken t


The sympathetic nervous system is essential for maintaining mammalian homeostasis. How this intricately connected network, composed of preganglionic neurons that reside in the spinal cord and post-ganglionic neurons that comprise a chain of vertebral sympathetic ganglia, arises developmentally is incompletely understood. This problem is especially complex given the vertebral chain of sympathetic ganglia derive secondarily from the dorsal migration of ‘primary' sympathetic ganglia that are initially located several hundred microns ventrally from their future pre-synaptic partners. Here we report that the dorsal migration of discrete ganglia is not a simple migration of individual cells but a much more carefully choreographed process that is mediated by extensive interactions of pre-and post-ganglionic neurons. Dorsal migration does not occur in the absence of contact with preganglionic axons, and this is mediated by BDNF/TrkB signalling. Thus BDNF released by preganglionic axons acts chemotactically on TrkB-positive sympathetic neurons, to pattern the developing peripheral nervous system. The signals that pattern the sympathetic nervous system are not fully understood. Here the authors show that the dorsal migration of the primary sympathetic ganglia in chick embryos is orchestrated by BDNF/TrkB signalling and requires contact with preganglionic axons. The molecular and cellular interactions that orchestrate the patterning of the vertebrate peripheral nervous system (PNS) have yet to be fully elucidated. On delamination from the neural tube, trunk neural crest cells destined to form the vertebral chain of sympathetic ganglia migrate ventrally to the vicinity of the dorsal aorta where they aggregate and condense to form the primary chain of sympathetic ganglia composed of differentiated sympathetic neurons and precursor cells34568910The more recent advances in molecular data on signals1213141516To address this challenge, we have designed novel interrogation techniques to visualize and quantify cellular and molecular dynamics during sympathetic nervous system development in living chick embryo explants. In previous work we have shown that the initial ventral migration of neural crest cells destined to form the chain of primary sympathetic ganglia do so via SDF-1/CXCR4 signallingTime-lapse confocal microscopy of fluorescently labelled primary sympathetic ganglia cells revealed a series of well-ordered steps that appear to be choreographed to position the secondary sympathetic ganglia adjacent to the ventral root. In the first step, a small number of cells on the dorsal side of the primary sympathetic ganglia extend multiple processes restricted in orientation towards the ventral root  perinotochordal area, the behaviour of primary sympathetic ganglia cells was dramatically altered . InitialTo investigate the molecular cues mediating the tight relationship between the primary sympathetic ganglia and ventral root, we used laser capture microdissection coupled with quantitative polymerase chain reaction (qPCR) gene profiling18in situ hybridization on E4 trunk tissue for BDNF mRNA and found expression in dorsal root ganglia, medial neural tube, ventral neural tube and ventral root -sorted cells and ventral neural tube-dissected tissue and performed qPCR for BDNF mRNA. We found BDNF mRNA expression in the ventral neural tube (as expected) and in the Schwann cell population in the ventral root  or a dominant negative TrkB construct expressing EGFP (DN-TrkB-EGFP) . TrackinConversely, the DN-TrkB embryos showed that dorsal migration was drastically impaired, with proper secondary sympathetic ganglia failing to form adjacent to the splanchnic nerve . DN-TrkBQuantification of the distance primary sympathetic ganglia cells migrated towards the ventral root after alterations in TrkB expression, demonstrated the dramatic extent to which cells failed to reach their permanent location . Measure1423et al.826The dynamic response of primary sympathetic ganglia cells to TrkB/BDNF chemotactic signals associated with preganglionic sympathetic axons, controls the permanent sympathetic ganglia pattern. This study demonstrates that primary to secondary sympathetic ganglia migration involves a transition from individual to coordinated cell migration. Our time-lapse imaging from show this occurs in a series of well-coordinated steps that include symmetry breaking, directed migration, then re-aggregation of cells within the primary sympathetic ganglia at the final permanent location adjacent to the spinal nerve  and 2. Oin vitroin vivo3132Trkb−/− or Bdnf−/− mice failed to show a defect in sympathetic ganglia, however, these reports used superior cervical ganglia for their investigations  was added 1:5 to the injection needle to visualize injection of the constructs. Constructs were electroporated into pre-migratory neural crest cells using gold-coated Genetrode elextrodes  and electroporator  with five 50-ms pulse of 20 V. Eggs were resealed with adhesive tape and incubated at 38 °C for 3–4 days. After incubation, we evaluated each embryo before manipulation for brightness and uniformity of EGFP label using a fluorescein isothiocyanate (FITC) filter to observe GFP-positive cells Axiovert microscope  with a 10 × /0.3 objective (Carl Zeiss). We selected embryos that were healthy and well labelled.Fertilized White Leghorn chicken eggs  were placed in a incubator at 37 °C  until appropriate age of development. Eggs were rinsed with 70% alcohol, 3 ml albumin was removed and windowed and staged according to Hamburger and Hamilton Tissue was collected by laser capture microdissection  at HH St. 10 and incubated for 72 h. Embryos were then sectioned transversely, using a feather blade (∼150-μm thick), between the fore- and hindlimbs and placed on a Millicell culture insert . BDNF-  or PBS-soaked Affigel beads  were placed in the slices along the dorsal migratory path of neural crest cells but in ectopic locations that the cells normally avoid , using fine glass pipettes and tungsten needles. The Millipore filter was then placed in a glass bottom Petri dish and tissue time-lapse imaged. For function-blocking experiments, trunk transverse tissue sections were cultured as above and the following function blocking antibodies were added to the culture media: anti-BDNF  or anti-trkB .et al.Embryos were collected in PBS and fixed in 4% paraformaldehyde (PFA) for 4 h. Embryos for immunohistochemistry were fixed as above and processed as in Kasemeier-Kulesa The entire coding sequence of chick TrkB (F. Lefcort) was subcloned into the EGFP-expressing vector, pMES to generate FL-chTrkB-GFP. A dominant negative form of the receptor was generated using PCR with primers to amplify the region from the start codon, and terminating immediately after the transmembrane domain, before the phospho-tyrosine signalling domains. Forward primer 5′-GAATTCATGGTGTCCTGGCGGCGGAG-3′ and reverse primer 5′-CCCGGGTTATGTCATCCCAATGATGACCGCAT-3′. This segment was then subcloned into the EGFP-expressing vector, pMES to generate DN-TrkB-GFP.in situ probe was generated by designing a gene fragment  to the chick BDNF gene incorporating EcoRI restriction site at the 5′-end and BamHI at the 3′end (NCBI Accession #NM_001031616) and inserted into pDrive cloning vector at the EcoRI and BamHI sites (Qiagen). For the antisense probe, vector was linearized with Kpn1 and synthesized with SP6 RNA polymerase. For the sense probe, vector was linearized with Not1and synthesized with T7 RNA polymerase.The chick BDNF In situ hybdrization was carried out as in WilkinsonEmbryos were collected and fixed as above and dehydrated in a methanol gradient and store at −20°C. Embryo were then rehydrated and vibratome sectioned at 100 μm under RNase free condition. http://rsb.info.nih.gov/ij/). Statistical analysis was performed using the Student's t-test.Three-dimensional image z-stacks were collected on an inverted laser scanning confocal microscope  using either a Plan-Neofluar 10 × /0.3, Plan-Neofluar 40 × /0.75 or C-Apochromat 40 × /1.2 W objective (Carl Zeiss). For embryo explant time-lapse microscopy, the microscope was surrounded with a snug-fitting cardboard box and thermal insulation  with a table-top incubator  fed into one side of the box . The EGFP plasmid was excited with the 488-nm laser line using the FITC filter. Time-lapse images were recorded every 5 min for an average of 12–16 h. Images were collected, processed and analysed using AIM software (Carl Zeiss) and ImageJ v1.30 software  to calculate the area covered.For distance of SG cluster to ventral root, the centre of mass of the area determined above was used to measure the distance to the perpendicular of the ventral root on static images from time-lapse session.How to cite this article: Kasemeier-Kulesa, J. C. et al. TrkB/BDNF signalling patterns the sympathetic nervous system. Nat. Commun. 6:8281 doi: 10.1038/ncomms9281 (2015).Supplementary Figure 1Symmetry Breaking of the Primary Sympathetic Ganglia ClusterCluster Migration of the Primary Sympathetic Ganglia. Sympathetic ganglia labeled with cytoplasmic (yellow) and nuclear (purple) label. Fiduciary mark (upper left hand corner in purple).Re-aggregation of the Primary Sympathetic Ganglia at the Ventral RootDynamic Interplay of the Primary Sympathetic Ganglia Towards the Ventral RootDynamic Interplay of the Pre-Ganglionic Axon Projections with the Primary Sympathetic GangliaTransection of the Ventral Root and Response of the Primary Sympathetic GangliaAblation of the Ventral Root and Response of the Primary Sympathetic GangliaReposition of the Ventral Root and Response of the Primary Sympathetic GangliaEctopic Transplantation of BDNF bead and Response of the Primary Sympathetic GangliaBlocking of BDNF Signaling and Response of the Primary Sympathetic Ganglia


Smad7 (I-Smad7), which mediates negative feedback for TGFβ signalling. We present evidence suggesting that zebrafish Ldb2a binds and directly activates the I-Smad7 gene, whereas it binds and represses the ligand gene, Squint (Sqt), which drives positive feedback. Thus, the fine tuning of TGFβ signalling derives from positive and negative control by Ldb2a. Expression of ldb2a is itself activated by TGFβ signals, suggesting potential feed-forward loops that might delay the negative input of Ldb2a to the positive feedback, as well as the positive input of Ldb2a to the negative feedback. In this way, precise gene expression control by Ldb2a enables an initial build-up of signalling via a fully active positive feedback in the absence of buffering by the negative feedback. In Ldb2a-deficient zebrafish embryos, homeostasis of TGFβ signalling is perturbed and signalling is stably enhanced, giving rise to excess mesoderm and endoderm, an effect that can be rescued by reducing signalling by the TGFβ family members, Nodal and BMP. Thus, Ldb2a is critical to the homeostatic control of TGFβ signalling and thereby embryonic patterning.As some of the most widely utilised intercellular signalling molecules, transforming growth factor β (TGFβ) superfamily members play critical roles in normal development and become disrupted in human disease. Establishing appropriate levels of TGFβ signalling involves positive and negative feedback, which are coupled and driven by the same signal transduction components (R-Smad transcription factor complexes), but whether and how the regulation of the two can be distinguished are unknown. Genome-wide comparison of published ChIP-seq datasets suggests that LIM domain binding proteins (Ldbs) co-localise with R-Smads at a substantial subset of R-Smad target genes including the locus of inhibitory  A LIM domain binding protein mediates both positive and negative feedback to fine-tune the regulation of transcription in response to transforming growth factor β signalling during embryonic development. Ldb2a is itself activated by TGFβ signals. Thus, when Ldb2a levels are initially low, TGFβ signalling can self-amply and build up signal via positive feedback without being countered by negative feedback. We show that this regulatory mechanism is active in developing zebrafish embryos, where a loss of Ldb2a results in the over production of mesodermal and endodermal tissue types as a consequence of elevated TGFβ family signalling.Cells depend on signals from their microenvironment to carry out their normal functions and coordinate responses. Once initiated, such signals often self-amplify via positive feedback to reach a sufficient level, when negative feedback can then be employed to dampen excess signalling. These feedback loops dynamically add or remove signalling components to maintain homeostasis. Their activation is often driven by the same signal transduction components, making it difficult to understand how signalling builds up in the first place. Here we find that the transcription co-factor Ldb2a enables differential response dynamics of negative and positive feedback upon the induction of TGFβ signalling. We show that Ldb2a directly activates expression of a TGFβ inhibitor that mediates negative feedback, while also repressing expression of TGFβ ligands that drive positive feedback. Moreover, expression of  In vertebrates, the transforming growth factor β (TGFβ) superfamily comprises a large number of ligands, including TGFβs, Nodal, Activin, and bone morphogenetic proteins (BMPs), each of which can direct lineage-specific transcriptional responses that regulate biological processes as diverse as cell proliferation, differentiation, apoptosis, and severe diseases caused by their mis-regulation . In respI-Smad genes, leading to their up-regulation in vivo [Smad7 can be induced by R-Smad3 expression [The level of TGFβ signalling is established by homeostatic regulation, which dynamically adds or removes signalling components to maintain a sufficient and constant level of activity. For example, TGFβ signals activate expression of their own ligands –9. After in vivo ,9. In zepression . It has pression –20. Howein vivo functional and phenotypic data showing that Ldb2 regulates Nodal/BMP signalling and is required for early embryogenesis. Furthermore, we identify I-Smad7 and a Nodal ligand, Sqt, as direct target genes activated or suppressed respectively by Ldb2a, and show that the fine tuning of TGFβ family signalling requires both positive and negative control by Ldb2a complexes.LIM domain binding proteins (Ldbs) are multi-functional non-DNA binding adaptor proteins that assemble TF complexes on target genes –25. CompI-Smad6 and I-Smad7  and Gata1/2 on DNA via motifs including Ebox, GATA, and Ets ,24,29. Gin vivo, we first monitored their expression during early embryonic development when TGFβ family members are known to be critical. Throughout early zebrafish development, ldb2a shows greater specificity than the ubiquitous ldb1a, ldb1b, or ldb2b  embryos  , while the level of total Smad2/3 was comparable to the wild-type control  and squint (sqt)  . Expressud stage  and remaud stage . These gldb2a morphants, expression of ntl, a mesendoderm marker, was expanded towards the presumptive ectoderm , markers of the mesendoderm-derived lateral mesoderm, such as a lateral mesodermal gene, hand2, a pronephric duct gene, pax2.1, and a haemangioblast gene, scl, displayed up-regulated expression in ldb2a morphants  but less severely compared to the ventrally expressed genes , as shown by increased expression of shh (notochord) and myoD (somite) in the 10%–30% most affected ldb2a morphants  inhibitor, SB431542, ldb2a morphants were rescued with respect to ectopic expression of cyc  , in order to biotinylate Ldb2a in vivo; we then precipitated Biotin-Ldb2a-chromatin using streptavidin beads for subsequent analyses. We previously showed that the loss of Ldb2a exerted opposite effects on expression of different sets of genes induced by the same R-Smad pathways . Altogether these data suggest that Ldb2a directly activates expression of Smad7 but suppresses that of TGFβ family ligand genes, uncoupling the negative and positive feedbacks that are otherwise induced by the same R-Smad signalling.Upon on (MBT) , suggestATG site . For ChIlleagues  for the  its own , togetheSmad7 and Sqt genes contain conserved SBE, E-box, and GATA motifs  was more significant than on other mesodermal lineages , as the ventro-lateral and posterior mesendoderm is formed by exposure to a combination of Nodal and BMP morphogens during gastrulation [Knockdown of rulation –35. We hLdb2a gene might itself be bound by R-Smads and transcribed in response to TGFβ family signalling. Thus, an Ldb2a-mediated coherent feed-forward loop slows down the transcriptional response of I-Smad7. As a consequence, Ldb2a discriminates the response speeds of the positive and negative feedback circuits during signal propagation, allowing the accumulation of signalling through positive feedback before the negative feedback is fully established. Recent publications [Insight into the biological significance of the discrimination among R-Smad targets by Ldb2a was provided by the discovery that the ications ,50 have All animal experiments were performed under a Home Office Licence according to the Animals Scientific Procedures Act 1986, UK, and approved by local ethics committees.http://www.ncbi.nlm.nih.gov/geo). For Smad1 (ChIP-seq in murine G1ER cells), Smad3 (murine pro-B cells), and Ldb1 (murine bone marrow cells), their mapped reads on the MM8 genome (bed format) were used for peak calling analysis using MACS (version 1.4.2), while IgG was used as the negative control. Genome-wide comparison of ChIP-seq datasets was performed as previously described [x-axes) (y-axes) was visualised by Java Treeview with the average reads density calculated in 100-bp bins ±2.5 kb around each Smad peak position suggested by MACS. These plots show the overlaps between Ldb1 binding regions and the enriched sites of Smad1/3 genome-wide. The location of Scl, Gata2, Smad1, Gata1, and Smad3 binding in relation to Ldb1-enriched sites was also visualised  were downloaded from the NCBI gene expression omnibus   in relatsualised . These pgata1a:GFP)la781 [Wild-type and Tg(FP)la781  embryos FP)la781 .MO oligonucleotides  using total RNA extracted from 24 hpf embryos, with gLdb2 FWD1 and gLdb2 REV1 primers  by aspirating through 23G syringes and incubated on ice for 10 minutes, followed by a brief centrifugation. Supernatants were separated into duplicates for each assay. 50 μl and 25 μl of the supernatant were used to measure the activity of luciferase and β-galactosidase, respectively, as described [50 pg SBE-luciferase  or Id1-Bescribed .Total RNA was isolated with the RNAeasy Microkit (QIAGEN). Quantitative PCR was performed with SybrGreen (Applied Biosystem). Data were collected with the ABI-PRISM 7000 or 7500 Sequence Detection system. β-actin1/2, EF1α, and GAPDH were used as internal controls. The relative abundance for each sample was computed by the comparative method (∆∆Ct). Statistical analysis was by the two-sample equal variance t-test. Error bars indicate the standard deviation. Primers are listed in ldb2a. The template DNA of sgRNA was generated by PCR with Phusion polymerase (NEB) in HF buffer with a unique oligonucleotide encoding a T7 polymerase-binding site and the sgRNA target sequence (zLdb2a-ATG sgRNA F) and a reverse oligonucleotide encoding the remainder of the sgRNA sequence (sgRNA-R). In vitro transcription was performed with 100 ng purified DNA template using the Megascript T7 kit (Ambion), and sgRNA purified by phenol chloroform extraction and isopropanol precipitation. sgRNA was stored in aliquots at −80 °C. To generate ldb2a mutants, 1 ng NLS-Cas9 protein and 500 pg sgRNA were injected into the cell of 1-cell stage embryos. The control group was injected with 1 ng NLS-Cas9 alone.The sgRNA sequence targets the sense strand near the ATG of ldb2a HRMA F1/ldb2a HRMA R1 primers. Details of the qPCR followed by HRMA were described previously [Genomic DNA was extracted by homogenizing single zebrafish embryos in 20 μl of 50 mM NaOH, followed by incubation at 95°C for 8 minutes , cooling to 4°C, and addition of 2 μl (10%) of 1 mM Tris-HCl (pH = 8) to neutralize the solution . A 178-beviously . PCR proChIP-seq and ChIP-qPCR of endogenous Ldb1  on murine Flk1+ BL-CFCs isolated from day 4 EBs was performed as described . 36-bp rin vivo biotinylation method described previously [ChIP-qPCR analyses of Ldb2a in zebrafish gastrula embryos were performed as described , using teviously  for the The following previously published datasets were used: Ldb1, Scl, and Gata2 in murine bone marrow cells , Ldb1 inS1 Data(XLSX)Click here for additional data file.S1 Figy-axis), the relative locations of sites bound by Ldb1 (light green), Scl (orange), Gata2 (navy), Smad1 (sky blue), Gata1 (purple), and Smad3 (red) are displayed within a 5-kb window centred on the Ldb1 bound site. Intensity at position 0 indicates co-occupancy. ChIP-seq datasets of Ldb1, Scl and Gata2 analysed here were obtained from murine bone marrow cells, while those of Smad1/Gata1 and Smad3 were performed in murine G1ER and pro-B cells, respectively [Genome-wide comparison of different ChIP-seq datasets shows that Ldb1, Scl, Gata2, Gata1, R-Smad1, and R-Smad3 co-occupy a subset of Ldb1 binding sites across the genome. For each Ldb1 binding site Click here for additional data file.S2 Figldb2a is present in the notochord (red arrows) and the PLM (black arrowheads). Embryos were co-stained with myoD to define the stage. (B) After somitogenesis, ldb2a expression becomes more specific in blood vessels (red arrowhead). Maternal/zygotic ldb2a is ubiquitously expressed in cleavage- and blastula-stage embryos, shown by RT-qPCR analysis (C) and whole-mount in situ hybridisation (D–F). RT-qPCR primers are separated by the exon-exon boundary on the 3′ end, to reduce the genomic background.(A) During mid-late somitogenesis, (TIF)Click here for additional data file.S3 Figldb2a gene are shown in red rectangles. ldb2a ATG MO1 targets the ATG site of ldb2a, whereas ldb2a splice MO2 spans the intron3/exon4 boundary. (B) RT-PCR analysis showed a reduction in the correctly spliced product, together with the formation of two aberrantly spliced products in ldb2a splice MO2 injected embryos. (C) Based on the sequences of three spliced products in ldb2a splice morphants, we drew the genomic structures of full length and truncated ldb2a with early stop codons (black asterisks). (D–E) To test the efficiency of ldb2a ATG MO1, it was injected with GFP-tagged ldb2a mRNA. The GFP fluorescence was significantly reduced in morphants. (F–K) Both ldb2a ATG MO and splice MO exert the same effects on expression of gastrula germ layer genes, such as cyc and gata2. (L–Q) At the shield stage, increased cyc expression in morphants can be rescued by co-injection of ldb2a mRNA. Embryonic views:  animal pole view with dorsal to the right;  dorsal view with animal pole to the top. (R–T) During somitogenesis, the increased expression of scl and bmp4 in morphants can be rescued by co-injection of ldb2a mRNA. Embryos were co-stained with myoD to help define the stage. Flat-mount embryos are shown in dorsal view, anterior to the left. ∼70% of the morphants injected with ldb2a mRNA showed rescued morphology during gastrulation and ∼50% showed rescued morphology during somitogenesis. (U) High resolution melt analysis (HRMA) is the quantitative analysis of the melt curve of a DNA fragment following amplification by PCR. It detects differences in the melting temperature of heteroduplexes containing insertions or deletions (indel) from wild-type homoduplexes. This technique enables a simple, fast, efficient, and sensitive detection of the indels created in the F0 generation. HRMA of F0 mosaic ldb2a mutant zebrafish embryos is shown here. Mosaic mutants can be easily distinguished from control embryos injected with the same amount of Cas9 without the sgRNA by a change in the shape of the melt curve. (V–W) A significant proportion of mosaic F0ldb2a mutants showed increased expression of cyc, phenocopying the morphants. We are in the process of generating stable mutant lines and will further characterise the phenotype and genotype. The wildtype control refers to uninjected embryos that are stage matched.(A) MO target sites in the (TIF)Click here for additional data file.S4 Figldb2a morphants stayed the same as in wild-type siblings. (B) The relative luminescence of the Id1-BRE2-luciferease reporter in ldb2a morphants was unchanged at the shield stage. As a positive control for the activity of Id1-BRE2-luciferease reporter, heat-shocked Tg(hsp70I:dnBmpr-GFP) embryos displayed reduced luminescence compared to heat-shocked wild-type siblings. Error bars are based on two technical replicates in one experiment that represents three independent experiments. (C-D) Expression of bmp4 was increased during somitogenesis (black arrows). Three independent experiments were performed, with the total number of embryos analysed indicated. The wildtype control refers to uninjected embryos that are stage matched.(A) At shield stage, the p-Smad1/5/8 level in (TIF)Click here for additional data file.S5 Figotx2, was reduced in ldb2a morphants. (C–F’) Expression of mixer was increased at the shield stage and remained evident in the endoderm of 80% epiboly ldb2a morphants (red arrowheads). (G–J’) Expression of eve1 and gsc was significantly increased. (A–B’): three independent experiments, with the total number of analysed embryos indicated in each panel; (C–D’) and (G–J’): two independent experiments; (E–F’): one experiment, complementary to (C–D’). The wildtype control refers to uninjected embryos that are stage matched.(A–B’) Expression of a neural ectodermal gene, (TIF)Click here for additional data file.S6 Figlmo2, gata2, fli1, gata1, draculin, pax8, and lim1 was increased in ldb2a morphants. (O) The mRNA level of fli1 was significantly up-regulated in ldb2a morphants, shown by RT-qPCR. (P–Q) The GFP intensity in ldb2a MO injected Tg(gata1:GFP) embryos was increased compared to uninjected siblings. Expanded expression of GFP in ldb2a morphants suggests an increase in the number of Gata1 positive cells. (A–B): five independent experiments with the total number of embryos analysed indicated in each panel; (C–N): two independent experiments; (O): two independent experiments, each with three technical replicates; (P–Q): ∼100 embryos of each group were examined and ∼80% of the morphants showed the phenotype (Q). The wildtype control refers to uninjected embryos that are stage matched.(A–N) During somitogenesis, expression of (TIF)Click here for additional data file.S7 Figtie1 (A–B), dll4 (C–D), and deltaC (E–F) was increased in the trunk and tail of ldb2a morphants. Embryonic view: lateral view of trunk and tail, with posterior to the right. ISH shown in this figure was repeated four times, with numbers of analysed embryos indicated. The wildtype control refers to uninjected embryos that are stage matched.At 24 hpf, expression of (TIF)Click here for additional data file.S8 Figsmad7 morphants, shown by the western blot using a Smad6/7 antibody. β-actin was the loading control. The wildtype control refers to uninjected embryos that are stage matched.The level of Smad7 protein was significantly decreased in shield-stage (TIF)Click here for additional data file.S9 Figldb2a mRNA at 1-cell stage showed no obvious morphological defect (A–B), no change in cyc expression at the shield stage (C–D), or expression of scl and bmp4 (E–J). (C–D) was observed in three independent experiments, whereas (E–J) was observed in two independent experiments. The wildtype control refers to uninjected embryos that are stage matched.Embryos injected with 50pg (TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


We have used chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) to profile Gro recruitment in two Drosophila cell lines. We find that Gro predominantly binds at discrete peaks (<1 kilobase). We also demonstrate that blocking Gro oligomerization does not reduce peak width as would be expected if Gro oligomerization induced spreading along the chromatin from the site of recruitment. Gro recruitment is enriched in “active” chromatin containing developmentally regulated genes. However, Gro binding is associated with local regions containing hypoacetylated histones H3 and H4, which is indicative of chromatin that is not fully open for efficient transcription. We also find that peaks of Gro binding frequently overlap the transcription start sites of expressed genes that exhibit strong RNA polymerase pausing and that depletion of Gro leads to release of polymerase pausing and increased transcription at a bona fide target gene. Our results demonstrate that Gro is recruited to local sites by transcription factors to attenuate rather than silence gene expression by promoting histone deacetylation and polymerase pausing.Gene expression is regulated by the complex interaction between transcriptional activators and repressors, which function in part by recruiting histone-modifying enzymes to control accessibility of DNA to RNA polymerase. The evolutionarily conserved family of Groucho/Transducin-Like Enhancer of split (Gro/TLE) proteins act as co-repressors for numerous transcription factors. Gro/TLE proteins act in several key pathways during development , and are implicated in the pathogenesis of several human cancers. Gro/TLE proteins form oligomers and it has been proposed that their ability to exert long-range repression on target genes involves oligomerization over broad regions of chromatin. However, analysis of an endogenous  Drosophila) to gain insight into how and where it binds with respect to target genes and to identify factors associated with its binding. We find that Groucho binds in discrete peaks, frequently at transcription start sites, and that blocking Groucho from forming oligomers does not significantly change the pattern of Groucho recruitment. Although Groucho acts as a repressor, Groucho binding is enriched in chromatin that is permissive for transcription, and we find that it acts to attenuate rather than completely silence target gene expression. Thus, Groucho does not act as an “on/off” switch on target gene expression, but rather as a “mute” button.Repression by transcription factors plays a central role in gene regulation. The Groucho/Transducin-Like Enhancer of split (Gro/TLE) family of co-repressors interacts with many different transcription factors and has many essential roles during animal development. Groucho/TLE proteins form oligomers that are necessary for target gene repression in some contexts. We have profiled the genome-wide recruitment of the founding member of this family, Groucho (from  Understanding how transcription factors regulate gene expression is essential for determining how genetically identical cells adopt different fates during animal development. The expression of key genes involved with cell fate determination is often controlled by spatially restricted localization or activity of transcriptional repressors. Many repressors do not have intrinsic repressive activity but recruit co-factors that inhibit productive transcription.Drosophila (Gro), and four orthologs in humans (TLE1-4) and mouse (Gro-related-gene: Grg1-4) (reviewed in DrosophilaThe Groucho/Transducin-Like Enhancer of split (Gro/TLE) family of co-repressors are conserved across metazoa and include a single ortholog in in vitroThe primary structure of Gro/TLE proteins includes five distinguishable regions, of which the most highly conserved are the N-terminal glutamine-rich Q domain and the C-terminal WD-repeat domain Drosophila S2 cells and in overexpression assays in the fly Drosophila; fushi tarazu (ftz) gene by ectopic expression of Hairy induces histone deacetylation for several kilobases around ftzDrosophilain vivoOne model for Gro repression is that upon recruitment to a target site by a DNA binding transcription factor, Gro oligomerizes along the DNA and recruits factors that modify chromatin to inhibit transcription from promoters that may be over 1 kb from the initial recruitment site Drosophila mutation revealed that oligomerization is not always required for the co-repressor function of Gro. MB12gro is a single base pair substitution in the translation initiator ATG codon (ATG-ATA) that leads to an N-terminal truncation, deleting much of the Q-domain in vitro and is expressed at <5% normal levels in early embryos. Nevertheless, MB12gro is not a null: maternal mutant embryos have intermediate segmentation phenotypes and retain more body mass than the null, indicating that MB12 retains some co-repressor activity. The MB12gro mutation has differential effects on the expression of target genes in vivo. For example, repression of the tailless (tll) gene by the Capicua-Gro complex is relatively normal in MB12gro embryos while repression of snail by Huckebein-Gro fails. Thus, there are differential requirements for oligomerization via the Q domain during Gro-mediated repression.Analysis of an endogenous Drosophila cell culture. In addition, we have focused on Gro recruitment at a known target locus [E(spl)mβ-HLH] to establish a model for Gro function as a co-repressor.In this study we have used chromatin immunoprecipitation followed by high throughput sequencing analysis (ChIP-seq) to profile the genome-wide recruitment of wild-type and non-oligomerizing Gro at high resolution in single cell types using To profile genome-wide Gro binding in Kc167 cells, we performed ChIP-seq using a previously validated anti-Gro antibody gro transcript led to a dramatic reduction of the number of significant peaks, demonstrating that ChIP with the anti-Gro antibody reflects bona fide Gro binding , tested its recruitment (using an anti-GFP antibody) in Kc167 cells depleted of endogenous Gro, and compared replicate samples as above . To compRh5).We first examined the breadth of peaks bound by Gro in Kc167 cells to determine if Gro is recruited to discrete sites or spreads along the DNA - or if both types of recruitment occur but are target dependent. The model that Gro spreads along chromatin (via Q domain oligomerization) to act as a long-range repressor predicts that Gro peaks would be typically greater than 1 kilobase wide and range to several kilobases Trl)] ] . The conTrl)] . This inWe also compared the profile of Gro peak widths with those of other transcriptional regulators in Kc167 cells for which ChIP-seq data was currently available. Gro peaks were broader than those produced by GAF, but were narrower than Tramtrack (Ttk), Kruppel (Kr), Zn finger homeodomain 1 (Zfh1) and C-terminal Binding Protein (CtBP) ChIP-seq peaks in Kc167 cells . Peaks fOur data demonstrate that Gro binding is not typically spread over multi-kilobase regions of the genome, while the conditions and analysis we used did not exclude the recovery of ≥2 kb peaks. However, several genomic regions contain clusters of discrete Gro peaks that are spread across several kilobases  that couEnhancer of Split Complex [E(spl)-C] (E(spl)-C genes) in the absence of Notch signaling in Kc167 cells E(spl)-C. The Gro peaks overlapped Su(H) peaks close to E(spl)mβ-HLH and E(spl)m3-HLH (E(spl)mβ-HLH and E(spl)m3-HLH was increased in Kc167 cells treated with Gro RNAi -C] . Gro hasl)m3-HLH . The expGro RNAi .gro RNAi Kc167 cells. There were very few genes differentially expressed genes and when looking at the whole transcriptome, we did not observe a general induction of genes  closely associated with ChIP-seq peaks in RNA-seq analysis (E(spl)-C is upregulated when Gro is depleted by RNAi.To test if depletion of Gro is sufficient to induce gene expression of repressed targets, we compared gene expression by RNA-seq of untreated and analysis , althougGro is recruited as a co-factor by many different DNA-binding transcription factors in addition to Su(H), thus Gro peaks are not expected to contain one consensus DNA binding sequence. In agreement with this, no single consensus motif was found in the high confidence Gro peaks . InsteadGene Ontology analysis revealed that the terms over-represented in the genes nearest Gro binding sites in Kc167 cells included “cell morphogenesis”, “imaginal disc development” and “neuron differentiation” . These tTo determine if the features of Gro recruitment we observe in Kc167 cells are common to other cell types, we performed ChIP-seq to profile Gro binding in S2 cells. Both Kc167 and S2 cell cultures are derived from late embryonic cells and have properties related to plasmatocytes, but they express distinct profiles of genes In common with Kc167 cells, Gro peaks in S2 cells were enriched for GAF, Mad, Brk and Hairy binding sites, but also for l(3)neo38 motifs . Gene OnWe also tested if depletion of Gro is sufficient to induce gene expression of repressed targets in S2 cells. Similar to Kc167 cells, the depletion of Gro from S2 cells by RNAi treatment resulted in very few differentially expressed genes and did not lead to general upregulation of Gro target genes .Rh5 locus) was not affected by blocking oligomerization and peaks bound by GroL38D,L87D-GFP at the E(spl)mβ-HLH locus closely resembled those bound by Gro-GFP mβ-HLH contains acetylated histones H3 and H4, but the levels are lower at sites where Gro binds around the gene mβ-HLH gene, which undergoes increased transcription when Gro is depleted mβ-HLH locus, which is a high confidence target of Gro repression in Kc167 cells mβ-HLH locus where distinct Gro peaks lie less than 2 kb apart, either side of the coding region  enhancer element g region . It seemg region , S7.By selecting our superset of high confidence peaks common to all datasets for endogenous Gro and Gro-GFP, we may have excluded some “real” peaks from our general analysis. However, the properties of the peaks excluded from the superset did not differ significantly from the peaks in the superset. In general, peaks that were unique to one replicate were narrower than those included in the superset, further supporting the argument that our conditions and analyses were not biased against recovering broad peaks .33% of our high confidence Gro ChIP-seq peaks overlapped previously published Gro DamID peaks. This overlap is relatively low, however, a comparable level of overlap (34%) is observed between GAF ChIP-seq and GAF DamID peaks . The DamConsistent with Martinez and Arnosti cis-regulatory elements to target promoters.While we do observe some peaks of Gro binding in intergenic regions that may be associated with enhancer elements that are more than 1 kb from the nearest annotated TSS, our data support a model in which Gro is recruited locally by transcription factors and does not spread along the chromatin by oligomerization when it acts on a distant target promoter. Thus, it is most likely that Gro recruited to distant regulatory elements is brought into the proximity of target promoters by “looping” of the DNA. It is well established that chromatin looping can facilitate gene activation by bringing factors bound at intergenic enhancers into contact with the transcription machinery gro RNAi in either Kc167 or S2 cells mβ-HLH. It is possible that loss of Gro may have led to increased variability in target gene expression, and the average expression values from many cells in our two biological replicates is unlikely to be sufficient to show any change in variability. However, genome-wide loss of Gro from its targets may not facilitate recruitment of activating factors in the absence of other changes in the nuclear environment . In addition, the residual Gro in these cells may be sufficient to maintain repression of most target genes mβ-HLH. This indicates that the level of Gro binding may be dependent on oligomerization at a subset of targets. Genetic evidence indicates that gro is not expressed in vast surplus to requirement as many genetic interactions can be detected with gro heterozygotes. For example, multiple gro mutations were isolated in screens for dominant suppressors of DomroPrevious overexpression studies in S2 cells and in the fly indicate that oligomerization affects how Gro acts in cells h5 locus  althoughgro is sufficient to maintain histones in a hypoacetylated state or that there are subtle changes to acetylation levels that cannot be accurately detected by ChIP-seq methods. Furthermore, loss of repression and gene activation are separable processes and depletion of Gro did not facilitate the recruitment and activity of histone acetylases at levels that we could detect.Our results are generally consistent with those from previous studies that identified an association of Gro with hypoacetylated histones H3 and H4 Drosophila embryo Drosophila embryonic neuroblasts relies on five short pulses of Notch signaling that occur within 4 hours Drosophila DmD8 cells, and this activation is correlated with reduced RNAP II pausing E(spl)mβ-HLH, a gene known to be a target of Gro repression via recruitment by Su(H) in Kc167 cells. Although much is known about the molecular mechanisms that control the P-TEFb checkpoint and RNAP II pausing, very little is known about which contextual factors determine the extent of RNAP II pausing. Future studies will address whether Gro interacts with known regulators of the P-TEFb checkpoint to promote RNAP II pausing in a gene-specific manner.Recent studies have revealed that regulation of promoter proximal pausing by RNAP II is a major point of control of the expression of many genes that respond to developmental and environmental cues. Paused polymerase is highly enriched at genes in stimulus-responsive pathways Finally, the finding that Gro target genes are transcribed is consistent with several other genome-wide studies that show association of repressors with actively transcribed loci Drosophila Genomics Resource Centre (DGRC) T. Murphy, unpublished]. Double-stranded RNA against gro was generated using the Megascript T7 kit following manufacturer's instructions (Life Technologies) and BAC13F13  as the template following the approach of gro 3′-UTR so that only transcripts from the endogenous gro gene were targeted for destruction. The following primers were directed against Gro 3′ UTR (from 95 bp to 683 bp downstream of stop codon) with the additional T7 recognition sequence underlined. Forward: TAATACGACTCACTATAGG CAACAGCAGCAGCATCGGCAG-3′5′-. Reverse: TAATACGACTCACTATAGG TGGAGGGACGTTGGGAGGTAAG-3′5′- .Gro and GroL38D;L87D cDNA was generated by PCR from cDNA templates PCR4-TOPO-Gro Drosophila Genomics Resource Center (DGRC). Transfections were performed using Effectene according to the manufacturer's instructions (Qiagen). Successful transfection and knockdown were assessed by western blot  with Bowtie version 2.1.0 p values generated in MACS. The per cent overlap was determined between samples at various ranks and the point of maximum per cent overlap was used as a cutoff to generate a list of peaks present in both samples. Typically, the majority of binding sites had a FDR less than 10%.To identify binding sites present in two biological replicate samples (or between conditions), a large number of peaks were identified in each sample and peaks were ranked by ChIPpeakAnno version 2.10.0 To compare the level of binding at particular genomic locations, Rsamtools in R/Bioconductor was used to count reads at 100 bp intervals across the genome. edgeR was used to normalize and identify significant differences between samples Centrimo version 4.9.1 Pause ratios were calculated by HOMER . mRNA libraries were generated following the manufacturer's instructions (NEBnext mRNA Library Prep Master Mix – E6110S). Samples were sequenced on the Illumina MiSeq following the manufacturer's protocol and paired-end 36 bp reads generated. For all samples two biological replicates were sequenced, and at least 7 million reads generated per replicate.Illumina paired-end reads were aligned to genome (BDGP 5.70) with Bowtie version 2.1.0 The accession number for the Illumina Sequencing data from this study on ArrayExpress is E-MTAB-2316.Figure S1Comparison of peak widths in individual endogenous Gro ChIP-seq replicates. A) Density plot showing peak widths obtained from replicate 1 of endogenous Gro ChIP-seq analysis. The peak widths of subsets of this replicate are shown as indicated. B) Density plot showing peak widths obtained from replicate 2 of endogenous Gro ChIP-seq analysis. The peak widths of subsets of this replicate are shown as indicated.(PDF)Click here for additional data file.Figure S2Overlap between ChIP-seq peaks and DamID peaks in Kc167 cells. A) Venn diagram illustrating the overlap between the high confidence superset of Gro ChIP-seq peaks  and peak(PDF)Click here for additional data file.Figure S3Comparison of peak widths obtained with Gro-DamID with replicates of endogenous and Gro-GFP ChIP-seq. Density plot showing peak widths obtained from Gro-DamID analysis (PDF)Click here for additional data file.Figure S4www.modencode.org) excluding the Gro peaks (the superset of high confidence peaks from this study) and cMyc (accession number GSM970847 on GEO at NCBI).Comparison of ChIP-seq peak widths obtained for transcriptional regulators in Kc167 cells. Density plot showing peak widths obtained via ChIP-seq for various transcriptional regulators in Kc167 cells as indicated. All data is from the modENCODE project ((PDF)Click here for additional data file.Figure S5gro RNAi treated Kc167 cells. A) Plot illustrating the log fold changes (logFC) for all expressed genes (grey) and with genes mapping nearest to a Gro binding site (red). B) Density plot illustrating the distribution of log fold changes (logFC) for all expressed genes and genes nearest to a Gro binding site.Gene expression profiles of untreated and (PDF)Click here for additional data file.Figure S6gro RNAi treated S2 cells. A) Plot illustrating the log fold changes (logFC) for all expressed genes (grey) and with genes mapping nearest to a Gro binding site (red). B) Density plot illustrating the distribution of log fold changes (logFC) for all expressed genes and genes nearest to a Gro binding site.Gene expression profiles of untreated and (PDF)Click here for additional data file.Figure S7Characterization of Gro-GFP and GroL38D,L87D-GFP recruitment and expression in Kc167 cells. A) Venn diagram showing the overlap between Gro-GFP and GroL38D,L87D-GFP peaks in Kc167 cells. B) Plot showing the log fold change (FC) of Gro-GFP and GroL38D,L87D-GFP peaks (100 bp fragment nearest the summit of each peak) in Kc167 cells after normalization in edgeR (PDF)Click here for additional data file.Figure S8Comparison of gene expression in cells expressing Gro-GFP and L38D,L87D-GFP by RNA-seq analysis. A) Plot illustrating the log fold changes (logFC) for all expressed genes (grey), genes mapping nearest to a Gro binding site (red) and genes mapping nearest to peaks bound by L38D,L87D-GFP (blue) in Kc167 cells. B) Density plot illustrating the distribution of log fold changes (logFC) for all expressed genes (grey), genes nearest to a Gro binding site (red) and genes nearest L38D,L87D-GFP peaks (blue) in Kc167 cells. C) Plot illustrating the log fold changes (logFC) for all expressed genes (grey), genes mapping nearest to a Gro binding site (red) and genes mapping nearest to peaks bound by L38D,L87D-GFP (blue) in S2 cells. D) Density plot illustrating the distribution of log fold changes (logFC) for all expressed genes (grey), genes nearest to a Gro binding site (red) and genes nearest L38D,L87D-GFP peaks (blue) in S2 cells.(PDF)Click here for additional data file.Figure S9E(spl)mβ-HLH locus in Kc167 cells. A) Plot of average level of H3 acetylation across the E(spl)mβ-HLH locus from untreated cells (black) and cells treated with gro RNAi (red). Profiles were taken from the average normalized counts of 100 bp fragments from an analysis in edgeR gro RNAi samples for histone H3 acetylation. Note: this shows −log10  peaks. D) Normalized plot of H4 acetylation across the E(spl)mβ-HLH locus from untreated cells (black) and cells treated with gro RNAi (red). E) Plot of the individual replicate samples used to make the plot in D . F) Regions that are significantly different between untreated and gro RNAi samples for histone H4 acetylation. Note: this shows -log10  peaks.Profiles of Histone H3 and H4 acetylation at the (PDF)Click here for additional data file.Figure S10Gro is enriched at paused transcripts. Density plot showing the pause ratio of all transcripts (black) and transcripts associated with Gro binding (red).(PDF)Click here for additional data file.Protocol S1Additional details of the (DOCX)Click here for additional data file.Table S1High confidence Gro ChIP-seq peaks identified in Kc167 cells.(XLS)Click here for additional data file.Table S2gro RNAi treated Kc167 cells.Comparison of gene expression by RNA-seq analysis of untreated and (XLSX)Click here for additional data file.Table S3High confidence Gro ChIP-seq peaks identified in S2R+ cells.(XLS)Click here for additional data file.Table S4gro RNAi treated S2 cells.Comparison of gene expression by RNA-seq analysis of untreated and (XLSX)Click here for additional data file.Table S5Comparison of gene expression via RNA-seq analysis of Kc167 cells expressing Gro-GFP and L38D,L87D-GFP.(XLSX)Click here for additional data file.Table S6Comparison of gene expression via RNA-seq analysis of S2 cells expressing Gro-GFP and L38D,L87D-GFP.(XLSX)Click here for additional data file.


Recent chromatin immunoprecipitation (ChIP) experiments in fly, mouse, and human have revealed the existence of high-occupancy target (HOT) regions or “hotspots” that show enrichment across many assayed DNA-binding proteins. Similar co-enrichment observed in yeast so far has been treated as artifactual, and has not been fully characterized.S. cerevisiae, the collective enrichment phenomenon is strongly associated with proximity to noncoding RNA genes and with nucleosome depletion. DNA sequence motifs that confer binding affinity for the proteins are largely absent from these hotspots, suggesting that protein-protein interactions play a prominent role. The hotspots are condition-specific, suggesting that they reflect a chromatin state or protein state, and are not a static feature of underlying sequence. Additionally, only a subset of all assayed factors is associated with these loci, suggesting that the co-enrichment cannot be simply explained by a chromatin state that is universally more prone to immunoprecipitation.Here we reanalyze ChIP data from both array-based and sequencing-based experiments to show that in the yeast Together our results suggest that the co-enrichment patterns observed in yeast represent transcription factor co-occupancy. More generally, they make clear that great caution must be used when interpreting ChIP enrichment profiles for individual factors in isolation, as they will include factor-specific as well as collective contributions. These regions have been alternatively called “TF colocalization hotspots”[Drosophila melanogaster TFs with diverse functions using the DamID method in cultured embryonic cells[Drosophila[C. elegans[In addition to mapping canonical transcription factor (TF) binding sites, chromatin immunoprecipitation (ChIP) experiments have revealed genomic loci at which many DNA-binding proteins display a signal of enrichment despite the absense of an otspots” and “higotspots”. Their eic cells. In thatosophila–5 and th elegans genomes. elegans. Similar elegans identifi elegans.in vitro binding sites. Direct protein-protein interactions between the involved fly TFs have also not been observed, complicating any model involving a transcription factory. The authors of the mouse study[A number of mechanisms have been proposed to explain the observed co-enrichment across ChIP experiments. Chromatin loops could cross-link to multifunctional “transcription factories” or enhanceosomes. Non-seqse study, by contin vivo protein binding data has been collected for the yeast Saccharomyces cerevisiae[The present study was motivated by the fact that, although extensive genome-wide revisiae–13, no arevisiae and Harbrevisiae, the autUnlike in higher eukaryotes, the collective enrichment patterns in yeast are not associated with sequence-predicted protein-DNA binding affinity for any of the TFs involved. Rather, sequence and functional analysis reveals that the most significant features of co-enriched probed regions are: (i) the extent of nucleosome depletion, (ii) expression of proximal genes, and (iii) the proximity to noncoding RNA genes, the majority of which encode tRNAs and snoRNAs. Additionally, the co-enrichment hotspots are occupied chiefly in rich-media (YPD) conditions, while, strikingly, the phenomenon is abrogated in the majority of environmental perturbation and stress conditions.without performing their normalization procedure across experiments (see Methods). To characterize the shared component of the ChIP profiles collected in rich media (YPD), we computed the median log2 fold-enrichment (MLFE) across 195 TFs as a measure of co-enrichment for each probe. The distribution of MLFE across probes was skewed heavily to the right . The more specific ncRNA categories of tRNAs, snoRNAs, and snRNAs were all significantly co-enriched as well. There were not enough probes corresponding to rRNA genes to establish statistical significance.A first glance at the most highly co-enriched probed regions revealed a preponderance of telomeres and noncoding RNAs (ncRNAs) Table . To syst2 ChIP-chip fold enrichment (MFE) across all rich media experiments. For each feature, the probe family co-occupancy ΔĀ was defined as the difference in mean co-occupancy within each probe family and mean co-occupancy at all other probes. The p-value was determined using a t-test. Significant p-values are highlighted.Probes were mapped to a feature if there was any overlap between the probe and feature. For each probe, the co-occupancy was defined as the median logt = 0.67, p = 0.51). Therefore, nucleolar and centromeric tRNA genes seem to participate in the collective enrichment phenomenon to an equal degree.A subset of yeast tRNA genes have been demonstrated to colocalize to the nucleolus. We therefore asked whether TF co-enrichment is associated with nucleolar localization. We used the classification of yeast tRNA genes as nucleolar or non-nucleolar based on a three-dimension model of the yeast genome derived from chromatin conformation capture data by Duan et al.. HoweverBecause telomeres and tRNA genes are associated with repetitive elements, 16 in aM was defined for each probe as the median log2 fold enrichment across all rich media ChIP-chip experiments, and the familyM among probes in a family and all other probes. The p-value was calculated using a t-test. Similarly, the absolute intensity A for each probe in each experiment was defined as the mean  intensity between the red and green channels; the median A was calculated across all experiments for each probe; and the family ΔĀ was reported as the difference in mean A among probes within a family and all other probes. Probe mapping and categories for comparison are as follows (see Methods for details of probe categorization): (A) Probes with high overlap vs. all other probes. (B) Probes with any overlap vs. all other probes. (C) Probes with low overlap or neighboring vs. non-neighboring probes  (D) Neighboring probes vs. non-neighboring probes  Significant co-enrichmentp-values are highlighted yellow; significant intensity (ΔĀ) p-values, which may signify cross-hybridization, are highlighted red.TF co-enrichment A plot of MLFE versus distance between the center of each probe and the center of the nearest ncRNA gene Figure  shows a p = 2.9 × 10−24, t-test; rabbit IgG: ΔMLFE = −0.13; p = 1.9 × 10−23, t-test; Figure Biases in IP efficiency and shearing based on chromatin state have been shown to be important in the interpretation of ChIP experiments, 24. To p = 2.1 × 10−116, t-test; Figure The ChIP-chip experiments that we re-analyzed for this study all relied on myc-tagged proteins. In humans, the c-Myc protein is localized to the nucleolus, raising the possibility that myc-tagged proteins in the ChIP experiment would be artificially biased towards tRNAs genes, some of which cluster in the nucleolus–27. To rDrosophila[2 fold enrichment (LFE) for each TF and (i) the median log2 fold-enrichment (MLFE) over all other TFs profiled in rich media, and (ii) the regional in vitro binding affinity predicted from DNA sequence using a position-specific affinity matrix for the TF from protein-binding microarray (PBM) data from Badis et al.[r = 0.31), indicating that the co-enrichment signal contributes to their IP profile to a significant extent. A notable exception is Yap1p, whose LFE is significantly anticorrelated with the MLFE of all of other factors. For a smaller number of TFs, LFE correlates with predicted affinity, but always to a lesser extent than with MLFE (mean r = 0.04), with the exception of Abf1p.The canonical view holds that the DNA-binding domain (DBD) of a TF is responsible for its recruitment to specific sequences in the genome. However, highly specific yet DBD-independent recruitment to sites of co-occupancy has been demonstrated using recombinant Bicoid protein in osophila. The lans et al. and Zhu s et al.  and accordingly, ribosomal proteins as a whole are strongly enriched . Because ribosomal protein (RP) promoters are known to be particularly active[r = 0.17, p = 1.1 × 10−40; Figure r = −0.31, p = 1.3 × 10−122; Figure To explore other relationships between genome function and TF co-enrichment, we looked for Gene Ontology (GO) categories of proximal genes Table . For evey active, we werer = 0.07, r = 0.06, and r = 0.06, respectively). Binding by these factors has previously been shown to drive nucleosome depletion at RP promoters[We were also interested in whether the TF co-enrichment profile was correlated with affinity for TFs. We calculated the predicted affinity of each probe for a compendium of TFs. Among TF affinities predicted from protein binding microarray (PBM) data, only affinity for Rsc30p, Rsc3p, and Rap1p correlated with MLFE  conditions, providing a uniform chromatin context for comparison across factors. Examining ncRNA loci in experimental perturbation (“stress”) conditions reveals dramatically reduced co-enrichment Figures  and5. Up-values are highlighted in yellow.Criterion for probe mapping is the same as in Figure Interestingly, those TFs that do not participate in ChIP co-enrichment at ncRNA genes as strongly in rich media conditions are more likely to be ChIP-enriched at ncRNA genes in other conditions. The most notable example of this is Ste12p, which is enriched at ncRNA genes upon exposure to alpha mating factor, but not in the absence of alpha factor or in the presence of 1-butanol. Dig1p, which is also associated with the mating response, behaves differently: it is not enriched at ncRNA genes in rich media, and is also not enriched at them in the presence of alpha mating factor and 1-butanol. Finally, among the other TFs that exhibit ncRNA depletion in rich media, Mot3p shows a loss of this depletion in the presence of hydrogen peroxide or sulfometuron methyl. The fact that enrichment at ncRNA genes is both factor and condition specific supports that the ChIP co-enrichment is not solely determined by the chromatin state at the co-enriched loci, and is dependent on the identity and activity of the binding proteins.2O2 condition showed an enrichment surpassing a threshold of p < (0.05/748 categories). In addition, the correlation between co-enrichment and expression is much weaker during oxidative stress .To directly compare co-enrichment between YPD and perturbed conditions, we looked at the hydrogen peroxide condition, which has the highest number of factors assayed in common with YPD. We then calculated MLFE in each condition using only the subset of factors that was assayed in both, and performed GO analysis Figure  and expr2O2 conditions, and the top GO enrichments are shown for YPD. The highlighted row is the only category that is significant in H2O2 after Bonferroni correction. Expression values were obtained from Huebert and Gasch (2012) as described in Methods.TFs in this analysis were restricted to the subset shared between YPD and HFor validation purposes, we compared three Ste12p ChIP-Seq datasets, one of which was performed in pseudohyphal conditions and two in exposure to alpha mating factor, 34. Botet al.[et al.[Our reanalysis of the ChIP-chip compendia of Lee et al. and Harb[et al. has reve[et al.. Because[et al. and Harb[et al., and are[et al. found co[et al., motivatin vitro, in which case they ought to display a higher level of nonspecific binding relative to nucleosome-occupied and heterochromatic regions. However, we have shown here that the hotspot phenomenon can only be partly explained in terms of chromatin accessibility, because even when using the same antibody, the ChIP enrichment at hotspots depends on which TF carries the affinity tag. This is consistent with the recent observation in fly Kc cells[Genomic recruitment of transcription factors is usually conceptualized as binding of the DNA-binding domain of the protein to high-affinity consensus sequences in the DNA, contingent on the local accessibility of the DNA. Our finding that many studied yeast transcription factors preferentially immunoprecipitate with nucleosome-depleted DNA is consistent with previous observations that TFs will nonspecifically bind to naked DNA at a low level. Within Kc cells and in cKc cells that thein vitro sequence specificity as measured by protein binding microarrays (PBMs) and in vivo occupancy as measured by ChIP-chip[de novo motif discovery. The co-enrichment could also be the result of competitive binding by different TFs in different subsets of cells and at different times, as has been suggested by recent work[Both the ChIP and DamID method can detect TFs that are near DNA but not necessarily contacting it. Consequently, the observed co-enrichment signal could be due to the proximity of probed regions to the TFs rather than due to direct interactions with them. Indeed, for individual yeast TFs, indirect interactions have been proposed in order to account for the poor correlation between hIP-chip. Fly andhIP-chip, 7. Our ent work, 42.Several lines of cytological evidence from mammalian cells suggest that transcription by polymerase II occurs at nuclear foci comprising many polymerase molecules and transcription factors, termed “transcription factories”. If suchOur results show that the median enrichment across all TFs is far more predictive of the ChIP landscape of a typical individual yeast TF than DNA sequence is. This agrees with a recent study of the interaction between chromatin accessibility and sequence specificity. While thttp://www.ebi.ac.uk/arrayexpress/) using accession numbers E-WMIT-1 and E-WMIT-10, respectively. Protocol information for each array  was extracted from the files E-WMIT-1.sdrf.txt and E-WMIT-10.sdrf.txt, available in the directory ftp://ftp.ebi.ac.uk/pub/databases/microarray/data/experiment/WMIT/. Raw intensity information was downloaded from the tab-delimited text files in E-WMIT-1.raw.zip and E-WMIT-10.raw.zip available in the FTP directory specified within the aforementioned text files. The column headers in all of these text files were found to be corrupted. Therefore, they were split between nine different formats. Each format was manually curated to locate the correct median foreground and background red and green intensity columns, using the presence of a background-subtracted log ratio column as a validation. Four of the experimental conditions had array data in the database that also had corrupted rows, where the number of columns was not consistent throughout the whole file; data associated with these conditions  were discarded. Raw intensities were loaded into R and Loess normalization was performed on each array (to account for dye-specific response functions) using the normalizeWithinArrays function of the limma package[The original raw ChIP-chip data, 12 were package, resulti package, 22, whiTy-flanked vs. Ty-absent tRNAs, and to divide snoRNAs into H/ACA-box vs. C/D-box and intron-derived vs. extragenic snoRNAs. The array design includes both probes that are centered on tRNAs, and probes that only overlap partially with tRNAs. For each category of genomic feature, we defined the probes that were centered on the feature (“high overlap” > 25 bp), those with a partial overlap (“low overlap” ≤ 25 bp), those that were neighboring , and all other probes.The genomic coordinates of probes were mapped to the chromosome sequences contained in the GFF-formatted sequence and annotation available from the Saccharomyces Genome Database (SGD), dated 2t-tests for probes corresponding to each class and sub-class of features defined above , they also had higher median intensities . Therefore, we excluded them from our analysis. Additionally, many families of ncRNA probes had lower median intensities, presumably due to their relatively short length. Using a conservative criterion for classification  and as TF targets, we compared the mean log2 fold enrichment among ncRNA probes and among annotated targets with that of all other probes. A significant difference in means was defined as a t-test passing a p-value threshold of 0.05, Bonferroni corrected for the number of tests.Annotated targets for each TF were defined as probes that overlapped or were neighboring (within 100 bp of) regions reported by MacIsaac et al. within tAffinityProfile utility in the MatrixREDUCE package as described previously[2O2 condition were obtained from[The affinity of each probed region for TFs was calculated using two published libraries of protein binding microarray (PBM)-derived position weight matrices (PWMs), 29. Theeviously. The Peaeviously. For eacned from, and proFunctional enrichment of probes by Gene Ontology (GO) categories was deteCondition specificity was calculated as follows: For each YPD experiment, we calculated the Pearson correlation between the TF’s occupancy and the median occupancy across all other rich media TF experiments, and also the correlation between its occupancy and its predicted affinity as predicted from PBM data. TFs for which no PBM-derived matrix was available were excluded. In cases for which two matrices were available – from both Badis et al. and Zhu http://www.ncbi.nlm.nih.gov/geo). These data include mapped peaks, but not genome-wide mapping of reads; therefore, read alignment results from ELAND were downloaded and processed using MACS[ChIP-seq data from Lefrancois et al. and Zhening MACS as descring MACS.