As a master regulator of jasmonic acid (JA)–signaled plant immune responses, the basic helix-loop-helix (bHLH) Leu zipper transcription factor MYC2 differentially regulates different subsets of JA–responsive genes through distinct mechanisms. However, how MYC2 itself is regulated at the protein level remains unknown. Here, we show that proteolysis of MYC2 plays a positive role in regulating the transcription of its target genes. We discovered a 12-amino-acid element in the transcription activation domain (TAD) of MYC2 that is required for both the proteolysis and the transcriptional activity of MYC2. Interestingly, MYC2 phosphorylation at residue Thr328, which facilitates its turnover, is also required for the MYC2 function to regulate gene transcription. Together, these results reveal that phosphorylation-coupled turnover of MYC2 stimulates its transcription activity. Our results exemplify that, as with animals, plants employ an “activation by destruction” mechanism to fine-tune their transcriptome to adapt to their ever-changing environment. The plant hormone jasmonic acid (JA) regulates a wide range of plant immune responses involving genome-wide transcriptional reprogramming that are regulated by the basic helix-loop-helix (bHLH) Leu zipper transcription factor MYC2. As a master regulator of JA signaling, MYC2 differentially regulates the transcription of different branches of JA–responsive genes through distinct molecular mechanisms. Here, we provide evidence that phosphorylation-dependent turnover of MYC2 is coupled with its function. We show that, during JA response, high accumulation of the MYC2 protein correlates with peaked expression of early wound-responsive genes that are positively regulated by MYC2, whereas low accumulation of the MYC2 protein correlates with peaked expression of late pathogen-responsive genes that are negatively regulated by MYC2. We discovered a 12-amino-acid element in the transcription activation domain of MYC2 that is required for both the proteolysis and the transcriptional activity of MYC2. Interestingly, MYC2 phosphorylation at residue Thr328, which facilitates its turnover, is also important for the MYC2 function to regulate transcription. Together, these results reveal that phosphorylation and turnover of MYC2 are tightly linked with its function to regulate the transcription of JA–responsive genes. Our results exemplify that plants employ proteolysis-coupled transcription as mechanism to fine-tune their responses to versatile stresses. Plants are continuously challenged by various biotic and abiotic stresses with diverse modes of attack. In response to an attack, plant cells undergo dramatic transcriptional reprogramming to efficiently coordinate the activation of attacker-specific immune responses so that the optimal resistance is attained. Equally importantly, when the attacking alarm is relieved, plants cells must effectively suppress their immune responses at the right time to minimize the cost of defense. Therefore, plant cells have involved elaborate regulatory mechanisms to keep defense-related gene transcription tightly in check.Among the best-characterized molecular signals regulating plant immune responses is the jasmonic acid (JA) family of oxylipins, which orchestrate genome-wide transcriptional reprogramming of plant cells to coordinate defense-related processes. Much of our understanding of the JA signal transduction pathway has come from the recent elucidation of the molecular details of JA-regulated gene transcription through MYC2, a basic helix-loop-helix (bHLH)-type transcription factor that regulates diverse aspects of JA responses In mammalian, phosphorylation and the ubiquitin-proteasome system (UPS)-mediated proteolysis are prominent posttranslational mechanisms that control transcription factors In this report, we investigated if MYC2 is regulated by posttranscriptional mechanisms. Our findings revealed that UPS-mediated proteolysis is involved directly and mechanistically in the regulation of MYC2 and demonstrate that plants employ proteolysis-coupled transcription as a mechanism to control their responses to various environmental stresses.myc2-2 mutant LIPOXYGENASE2 (LOX2) as a representative marker gene for wound response PDF1.2 as a representative marker gene for pathogen response LOX2 mRNA levels showed a pronounced increase at 3 h and reached to a maximum at 6 h; LOX2 mRNA levels then showed a tendency of reduction and returned to basal levels at 48 h after MeJA treatment  and the reatment . Parallereatment . These rMYC2 mRNA levels quickly reached to a maximum at 0.5 h after MeJA treatment then showed a tendency of reduction in the duration of the experiment. We then used the MYC2-4myc-15 plants, which express a functional MYC2-4myc fusion protein  ERF1, the transcription factor OCTADECANOID-RESPONSIVE ARABIDOPSIS AP2/ERF-domain protein 59 (ORA59), which directly binds the promoter of PDF1.2PDF1.2 expression. First, MeJA-induced expression levels of ORA59 was dramatically increased in myc2-2 than those in WT  assays using the previously described pro:MYC2-GFP35S plants ORA59 promoter   . Togethein planta, we generated pro:MYC2-GUS35S, pro:MYC2-GFP35S and pro:MYC2-4myc35S constructs and introduced them into the myc2-2 mutants. The resulting stable transgenic lines including MYC2-GUS-18, MYC2-GFP-12 and MYC2-4myc-15, which expressed comparable transcript levels of the respective transgene and rescued the JA-insensitive phenotype of the myc2-2 mutant  that is enriched in acidic amino acids , which are usually acidic, overlap closely with the TADs of unstable transcription factors no acids . To test6 plants , indicat6 plants . In summΔDE-GFP-6MYC2 plants indicated that deletion of the DE does not affect the binding capacity of MYC2 to the promoter of ORA59 . We found that CIAP treatment led to a slightly faster migration of the MYC2-4myc fusion protein, implying that the slower migrating form of the fusion protein was phosphorylated  were introduced into the myc2-2 mutant under the 35S promoter. Transgenic lines T328A-4myc-23MYC2, S330A-4myc-13MYC2, S334A-4myc-11MYC2 and T336A-4myc-18MYC2, in which the expression levels of the respective transgenes were comparable to those of the MYC2-4myc-10 plants  did not show constant expression of defense genes without the JA signal Several lines of evidence hint the existence of protein regulation for the function of MYC2 in regulating JA-dependent plant immunity. For example, it has been shown that In this study, we found a temporal correlation between the MYC2 protein accumulation and its differential effects on the expression of wound responsive genes and pathogen responsive genes: high accumulation of the MYC2 protein correlates with peaked expression of the branch of early wound-responsive genes that are positively regulated by MYC2, whereas low accumulation of the MYC2 protein correlates with peaked expression of the branch of late pathogen-responsive genes that are negatively regulated by MYC2 . ClearlyThe existence of a temporal correlation between MYC2 protein accumulation and its function to differentially regulate wound response and pathogen response suggests that protein stability may play a role in MYC2 regulation. Indeed, we describe here that MYC2 is subjected to UPS-dependent proteolysis and demonstrate that UPS-dependent proteolysis of MYC2 is part of the JA signaling. It is well known that UPS-dependent proteolysis plays an important role in nearly every aspect of plant biology, including plant hormone signaling. In these instances UPS either degrades transcription factors to suppress transcription or degrades transcription repressors to activate gene expression Our finding that UPS-mediated proteolysis is involved directly and mechanistically in the regulation of MYC2 fits well with a scenario in the animal and yeast called “activation by destruction”, in which UPS-mediated proteolysis can activate the activity of the transcriptional regulators it destroys Arabidopsis thaliana ecotype Columbia (Col-0) was used as wild type (WT). T-DNA insertion mutant myc2-2 was previously described Arabidopsis plants were grown in Murashige and Skoog (MS) media at 22°C with a 16-h-light/8-h-dark photoperiod (light intensity 120 µM photons m−2s−1) as previously described pro:MYC2-GUS35S was prepared by inserting PCR-amplified coding sequence of MYC2 and Glucuronidase (GUS) into the KpnI-SpeI sites and SalI-PstI sites of the binary vector pCAMBIA2300 under the control of cauliflower mosaic virus 35S promoter. The pro:MYC2-GFP35S and pro:MYC2-4myc35S constructs used in this study were previously described pro:MYC2ΔDE-GFP35S construct, coding sequence of MYC2 truncated DE domain was amplified with Gateway-compatible primers. The PCR product was cloned by pENTR Directional TOPO cloning kit (Invitrogen) and then recombined with the binary vector pGWB5  pENTR-MYC2T328ApENTR-MYC2 was then combined with binary vector pGWB17  pro:MYC2T328A-4myc35S construct. Similarly, we generated pro:MYC2S330A-4myc35S, pro:MYC2S334A-4myc35S, pro:MYC2T336A-4myc35S constructs. All primers used for DNA construct generation are listed in The Agrobacterium tumefaciens strain GV3101 (pMP90), which was used for transformation of Arabidopsis plants by vacuum infiltration The above constructs were then transformed into N. benthamiana leaves as previously described ORA59 promoter was amplified cloned into pENTR using the pENTR Directional TOPO cloning kit (Invirogen). To generate ORA59 promoter with mutations, site-directed mutagenesis was used to delete the CACGTG motif in the P1 region of the ORA59 promoter , and pro:MYC2ΔDE35S-GFP (pro:MYC2ΔDE35S). We used a low-light cooled CCD imaging apparatus (NightOWL II LB983 with indigo software) to capture the LUC image and to count luminescence intensity. The leaves were sprayed with 100 mM luciferin and were placed in darkness for 3 min before luminescence detection.The transient expression assays were performed in promoter  using thSaccharomyces cerevisiae AH109. The MATCHMAKER GAL4-based Two-Hybrid System 3 (Clontech) was used for the transactivation activity assay. Each yeast liquid culture was serially diluted to OD600 = 0.6, and 5 µl of each dilution was inoculated onto SD/-Ade/-His/-Trp synthetic dropout medium. The expressed proteins in yeast strains were analyzed by immunoblot experiments. Proteins fused with the GAL4 DNA binding domain were detected using anti-myc antibody.Full-length coding sequence and TAD truncation of MYC2 were amplified with listed primers see  online. For qRT-PCR analysis, seedling were harvested and frozen in liquid nitrogen for RNA extraction. RNA extraction and qRT-PCR analysis were performed as previously described Details for protein extraction and immunoblot assays were described recently N. benthamiana leaves that transiently expressing MYC2-4myc or MYC2-4myc-15 seedlings were homogenized with ice-cold extraction buffer . After protein extraction, 20 µL protein G plus agarose (Santa Cruz) was added to the 2-mg extracts to reduce nonspecific immunoglobulin binding. After 1 h of incubation, the supernatant was transferred to a new tube. myc antibody-bound agarose beads (Santa Cruz) were then added to each reaction for 4 h at 4°C. The precipitated samples were washed at least four times with the extraction buffer and then eluted by adding 1× SDS protein loading buffer with boiling for 5 min.A phosphor-portein enrichment kit (Clontech) was used to column-purify phospho-proteins according to the manufacturer's protocol.pro:MYC2-GFP35S seedlings were used for ChIP experiments. GFP antibody (Abcam) was used to immunoprecipitate the protein-DNA complex. Chromatin precipitated without antibody was used as negative control, while the isolated chromatin before precipitation was used as input control. The enrichment of DNA fragments was determined by semiquantitative PCR. Primers used for ChIP-PCR were listed in ChIP was performed as previously described Escheichia coli (E. coli) used in this assay was previously described 2 and 10 mM EDTA with or without proteins at room temperature for 20 min. For nonlabeled probe competition, nonlabeled probe was added to the reactions. The probe sequences used in MESA were listed in Recombinant MYC2 protein in MYC2-4myc-15 transgenic plants were resolved on SDS-PAGE and visualized by silver staining. A protein band of approximately 70 KD was cut from the gel and digested with trypsin overnight at 37°C. Peptides were extracted sequentially with 5% formic acid (FA)/50% acetonitrile and 0.1% FA/75% acetonitrile, dried under vacuum, then resuspended in 0.1% FA. LC-MS/MS and data analysis were performed as described previously The anti-myc immunoprecitipitates from Botrytis cinerea on MEA medium  in Petri dishes for 14 days at 24°C with 12 h photoperiod before collection of spores. Spore inoculums were prepared by harvesting spores in water, filtration though nylon mesh to remove hyphae and suspension in potato dextrose broth to a concentration of 105 spores/ml. Detached rosette leaves of 28-d-old plants were placed in Petri dishes containing 0.8% agar, with the petiole embedded in medium. Each leaf was inoculated with a single 5 µl droplet of B. cinerea inoculums. Trays were covered with lids and kept under the same conditions as for plant growth. Photographs were taken after 3 days and mean lesion sizes of 20 leaves from 20 plants of various genotypes were compared using a Student's t-test assuming equal variance.Grow Figure S1pro:MYC2-GUS35S, pro:MYC2-GFP35S or pro:MYC2-4myc35S in the Genetic Background of myc2-2. (A) Transgene expression levels in the indicated plants revealed by qRT-PCR analysis. Total RNA was extracted from 7-day-old seedlings for qRT-PCR analysis. qRT-PCR amplifications were normalized to the expression of ACTIN7. Values are mean ± SD of three replicates. (B) Ten-day-old seedlings of WT, myc2-2 and MYC2 overexpression lines were grown on 1/2 MS medium without or with 20 µM JA.Generation of Transgenic Plants Containing (PDF)Click here for additional data file.Figure S2ORA59 in Response to MeJA Treatment. Seven-day-old WT and myc2-2 seedlings were treated with 100 µM MeJA for indicated times before total RNAs were extracted for qRT-PCR assays. Values are mean ± SD of three replicates. The experiments were repeated three times with similar results.Time-Course Expression of (PDF)Click here for additional data file.Figure S3MYC2. Seven-day-old seedlings of MYC2-GUS-18, MYC2-GFP-12 and MYC2-4myc-15 were treated with (+) or without (−) 100 µM CHX for 2 h or 50 µM MG132 for 6 h. Subsequently, the expression of MYC2 was analyzed using qRT-PCR. qRT-PCR amplifications were normalized to the expression of ACTIN7. Values are mean ± SD of three replicates.CHX but not MG132 Induces the Transcription of (PDF)Click here for additional data file.Figure S4MYC2. (A) Seven-day-old seedlings of MYC2-GFP-12 and MYC2-4myc-15 were treated with 100 µM MeJA and/or 100 µM CHX for 6 h and the expression of MYC2 was quantified with qRT-PCR. qRT-PCR amplifications were normalized to the expression of ACTIN7. Values are mean ± SD of three replicates. (B) Seven-day-old seedlings of MYC2-GFP-12 and MYC2-4myc-15 plants were treated treated with 100 µM MeJA and/or 50 µM MG132 for indicated times and the expression of MYC2 was analyzed using qRT-PCR. qRT-PCR amplifications were normalized to the expression of ACTIN7. Values are mean ± SD of three replicates.Effect of CHX or MG132 on MeJA-induced Transcription of (PDF)Click here for additional data file.Figure S5Immunoblot Analysis of MYC2 and MYC2ΔTAD Proteins in Yeast Shown in (PDF)Click here for additional data file.Figure S6pro:MYC2ΔDE-GFP35S or pro:MYC2-GFP35S in the Genetic Background of myc2-2. Transgene expression levels in the indicated plants revealed by RT-PCR analysis. Total RNA was extracted from seven-day-old seedlings for RT-PCR analysis. Expression of ACTIN7 was used as an internal control.Generation of Transgenic Plants Containing (PDF)Click here for additional data file.Figure S7ΔDE Still Bind to the Promoter of ORA59. Enrichment of the DNA fragment (P1) shown in MYC2ΔDE-GFP-6 was immuno-precipitated with an anti-GFP antibody, and the presence of the indicated DNA in the immune complex was determined by RT-PCR. The ACTIN2 promoter fragment was used as a negative control.MYC2(PDF)Click here for additional data file.Figure S8MYC2 Gene in the Genetic Background of myc2-2. Transgene expression levels in the indicated plants revealed by qRT-PCR analysis. Total RNA was extracted from seven-day-old seedlings for qRT-PCR analysis. qRT-PCR amplifications were normalized to the expression of ACTIN7. Values are mean ± SD of three replicates.Generation of Transgenic Plants Containing Indicated Point Mutations of the (PDF)Click here for additional data file.Table S1DNA primer pairs used for construct generation.(PDF)Click here for additional data file.Table S2DNA primer pairs used for qRT-PCR and ChIP-PCR assays.(PDF)Click here for additional data file.Table S3Oligonucleotide probes used in EMSA.(PDF)Click here for additional data file.


The current study describes the identification of the promoters involved in AS-48 expression. Seven putative promoters have been here amplified, and separately inserted into the promoter-probe vector pTLR1, to create transcriptional fusions with the mCherry gene used as a reporter. The activity of these promoter regions was assessed measuring the expression of the fluorescent mCherry protein using the constitutive pneumococcal promoter PX as a reference. Our results revealed that only three promoters PA, P2(2) and PD1 were recognized in Enterococcus faecalis, Lactococcus lactis and Escherichia coli, in the conditions tested. The maximal fluorescence was obtained with PX in all the strains, followed by the P2(2) promoter, which level of fluorescence was 2-fold compared to PA and 4-fold compared to PD1. Analysis of putative factors influencing the promoter activity in single and double transformants in E. faecalis JH2-2 demonstrated that, in general, a better expression was achieved in presence of pAM401-81. In addition, the P2(2) promoter could be regulated in a negative fashion by genes existing in the native pMB-2 plasmid other than those of the as-48 cluster, while the pH seems to affect differently the as-48 promoter expression.The enterocin AS-48 is the best characterized antibacterial circular protein in prokaryotes. It is a hydrophobic and cationic bacteriocin, which is ribosomally synthesized by enterococcal cells and post-translationally cyclized by a head-to-tail peptide bond. The production of and immunity towards AS-48 depend upon the coordinated expression of ten genes organized in two operons,  Enterococcus strains, with antimicrobial activity against food-borne pathogenic and food-spoilage bacteria. These characteristics, together with its stability and solubility over wide pH and temperature ranges, confer a clear potential to be used as food biopreservative  , although only nine  were identified in the bac cluster bac cluster a protein homologous to As-48D1, the proposed immunity determinant against AS-48, was not considered. However, the mutants that were described in that work show that the deletion of the region where the immunity protein As-48D1 is encoded, clearly makes a difference in the phenotype in terms of resistance against AS-48 bacC and bacD genes , and also on a putative promoter proposed for the bacC gene  and T2 (6.4 kb), corresponding to the expression of the two operons as-48ABC and 1DD1EFGHas-48C, respectively , possibly transcribed from an internal promoter, encodes at least the last four genes (as-48EFGH) Transcriptional analysis of the ectively . A post-1 and T2 are constitutively expressed, while transcription from putative internal promoters might be regulated All the commented features are in agreement with the general trend in bacteria, where numerous genes are organized in operons transcribed from the same promoter into a single polycistronic mRNA molecule, although many genes could also be transcribed from internal promoters located at intergenic regions or within adjacent genes as-48 gene cluster and in elucidating the regulation of the gene expression. Thus, an accurate identification of the promoters is crucial. Such information could also help to explain the failure in the heterologous expression of AS-48 in other lactic acid bacteria, especially in Lactococcus lactisgenerally recognized as safe) bacterium of great biotechnological interest. Additionally, the identification of promoters, particularly those strong and inducible, provides a potent biotechnological tool for research and industry E. faecalis (ca. 60% A+T). In these genomes, stretches resembling −10 elements (5′-TATAAT-3′) are frequent and, therefore, the definitive identification of promoters from sequence information remains more difficult as-48 promoter regions identified in silico measuring their different expression level in diverse strains. For this, we carried out transcriptional fusions of each putative promoter fragment to drive the expression of a synthetic mCherry gene codon-optimized for Enterococcus into the pTLR1 vector as-48 cluster according to two software analyses and cloned each fragment to drive the expression of the mCherry reporter gene in three bacterial strains, E. faecalis, L. lactis and E. coli, using the previously characterized promoter PX of Streptococcus pneumoniae for comparison Our group has provided valuable information regarding the impact of the amino acids in the propeptide sequence that are involved in the head-to-tail peptide bond formation Escherichia coli was grown at 37°C with shaking in Luria broth  and selected with erythromycin  for cells harboring the pTLR1-derivatives. E. faecalis and L. lactis were routinely grown in brain heart infusion  at 37°C and M17 (Scharlau) plus glucose (0.5%), GM17, at 30°C, respectively. Erythromycin at 10 µg/ml and/or chloramphenicol at 20 µg/ml  were added to the culture medium for cells harboring pTLR1 derivative plasmids or pAM401-81 plasmid, respectively.Bacterial strains and vectors used in this work are listed in For fluorescence detection, several culture media were assayed: the chemically defined media CDM-PC E. coli TOP10 was used in cloning experiments. The preparation of chemiocompetent cells to be transformed with plasmid DNA and ligation products was done by the calcium chloride protocol as described by Seidman et al. L. lactis and E. faecalis was performed according to the methods described by Holo and Nes et al.E. coli using the Plasmid Mini I kit from Omega bio-tek . PCR products were purified with the AccuPrep PCR Purification Kit  and sequenced. Restriction enzymes were obtained from Thermo Scientific , ligase from Invitrogen , TaqDNA polymerase from MBL ; and used as recommended by the suppliers. DNA was sequenced using an ABI PRISM Dye Terminator Cycle Sequencing Ready Reaction .The plasmid-free strain as-48 or bac regions  and BPROM  Putative promoter regions from X from S. pneumoniae upstream of mCherryas-48 locus of E. faecalis . The PCR conditions were the same for all the amplifications performed: 96°C 2′, 30× , 72°C 2′. The amplified DNA fragments containing the presumed promoter regions were cut with BglII and BamHI and ligated into pTLR1 previously digested with the same enzymes, obtaining the pTLR1-derivative constructions shown in E. coli TOP10. The desired orientation of the fragments was determined by colony PCR using the forward primer of each promoter and the pTLR-rev primer, which anneals in the vector backbone  is a vector for promoter analysis that contains the strong promoter Pbackbone . The ver600 nm 0.05 and then grown for 18 h at 30°C for Lactococcus or 37°C for E. coli and Enterococcus. During cultivation the spectrophotometer simultaneously provided quantitatively online data every 10 minutes of cell density (OD600) and in vivo mCherry fluorescence measured at an excitation wavelength of 590 nm and an emission wavelength of 620 nm. E. coli cultures were grown with continuous shaking and stopped 1 min before measuring the OD and fluorescence. In the case of E. faecalis and L. lactis shaking was applied only for 10 second before taking the measurements of OD and fluorescence.Each assay was repeated in triplicate in a 96-well optical flat-bottom microplate  and monitored with an Infinite 200 Pro microplate spectrophotometer . Briefly, each transformant was separately inoculated into three wells with a final volume of 100 µl/well of the CM-G medium with the appropriate antibiotics at an ODIn order to determine the influence of the pH, the medium was adjusted at different pH values  using 0.1 M phosphate buffer according to Gomori p value) was considered. The average data from duplicate trials ± standard deviation was determined.The statistical analysis of the data was performed using the IBM SPSS statistics 20 . Data relating to microbiological density and fluorescence under different conditions were subjected to ANOVA. Tukey was used as a post-hoc test to determine significant differences between promoters and a 0.05 signification level , 5 µl of cells were placed on slides and observed in an Olimpus BX51 microscopy (model BX51TF with a power supply unit Olimpus U-RFL-T SN 1101008) using a TRITC filter (excitation 590 nm and emission 620 nm). The images were taken at 250 ms of excitation.E. faecalis strains was performed as described by Fernández et al.The antibacterial activity of diverse AS-48-producing as-48/bac21 gene cluster expression have been proposed  http://linux1.softberry.com) In previous works e.g.  several proposed . To unamAs a result, we have selected the following promoter regions putatively involved in the expression of the AS-48 character :A promoter: it is a region with canonical −10 and −35 regions, separated by a correct spacing that could allow for the binding of the vegetative σ factor of the bacterial RNA polymerase without the need for an activator i) The PC promoter: Fernández et al.as-48BC genes overlapped and they had a coupled transcription from the PA promoter in absence of a specific promoter for as-48B. This fact does not invalidate, however, the possibility that as-48C could have its own promoter (PC) as it had been proposed for its counterpart bacCbacC would encode a shorter protein (57 residues), starting 246 nt downstream from bacB, which does not overlap with bacB as, in fact, it was proposed for its homologous as-48C in the as-48ABC operon as-48C gene. It contains motifs that match the consensus sequence at the most conserved positions of the hexamers and an appropriate spacer in accordance with the two predictive programs used (ii) The Pams used .2 promoter: according to Díaz et al.1DD1EFGHas-48C operon. However, there are discrepancies between Martínez-Bueno et al.et al.1as-48C or bacD 400 bp and 500 bp, respectively, from the previous predicted ORF. Additionally, the software used in the predictions also shows two possible promoters in the region. Therefore, we decided to clone the two putative promoters, namely P2(1) and P2(2), to clarify this point (iii) The Pis point .D1 promoter: the possibility of an internal promoter in the 1DD1EFGHas-48C operon, from which the gene 1as-48D might be transcribed has been also investigated. This new promoter might be located in a 439 nt fragment upstream from the start codon of 1as-48D containing a −10 and a −35 consensus sequence with 4 out of 6 matches (bac21 cluster iv) The P matches . This pu3 promoter: the putative P3 promoter firmly postulated by both, Díaz et al.et al.as-48EFGH genes should be located in the 204 nt intergenic region identified between the 1as-48D and as-48E genes, where a plausible −10 and −35 region separated by a correct spacing was found (promoter P3(1)) (1as-48D and a series of conserved sequences separated by 9 nt (named promoter P3(2)) has been also cloned according to the prediction.v) The Pr P3(1)) . Additio1DD1EFGHas-48ABC, as-48C, as-48C, 1as-48D and as-48EFGH genes, the presumed promoter fragments were amplified and separately inserted into the promoter-probe vector pTLR1, creating several transcriptional fusions with the mCherry gene, which is codon optimized for expression in LAB X promoter from S. pneumoniae, which in the absence of the pneumococcal MalR regulator is constitutively expressed E. coli TOP10, and transferred to the LAB hosts L. lactis LM2301 and the well-characterized laboratory strain E. faecalis JH2-2.To map more precisely the promoter regions driving the expression of E. coli, being paler in the LAB hosts indicating roughly the strength of the promoters cloned. This result was confirmed by microscopic analysis during both exponential and stationary phase (data not shown). However the most quantitative results were obtained with E. faecalis, L. lactis and E. coli transformants by measuring the simultaneous cell growth and fluorescence during prolonged cultivations using a microplate reader spectrophotometer. To optimize the cultural conditions, we assayed two chemically defined media (CDM-PC and -BP), a semi-defined complex medium (CM-G) specifically designed for AS-48 production and purification purposes, and two complex media (GM17 and LB). The basal arbitrary units of fluorescence (AU) detected before inoculation for CDM-PC (315.8), CDM-BP (316.3), CM-G (401.0), LB (695.8) and GM17 (2943.0), revealed that although CM-G had higher background fluorescence than the CDMs, this medium allows the growth of the different strains to higher OD. Therefore, we chose CM-G for the fluorescence assays.The mCherry expression can be detected in different ways A and the suitability of the P2(2) proposed by Tomita et al.E. coli and in the two lactic acid bacteria investigated. Apart from this, our results confirm the existence of the internal PD1 promoter suggested by Martínez-Bueno et al.C, P2(1), P3(1) and P3(2), did not express the mCherry protein in any of the culture conditions assayed, being for this reason discarded (data not shown). PA, P2(2) and PD1 contain the typical −16 region, reinforcing the interest of this region for the promoter activity. The absence of PC is in accordance with the expression pattern observed by Fernández et al.as-48ABC operon. In this operon, the PA promoter controls the normal expression of as-48-ABC genes rendering the transcript T1 that undergoes a post-transcriptional processing, and arises two different transcripts TA and TBC with distinct half-life and stability, ensuring the appropriate stoichiometry of the different gene products  identified by Díaz et al.as-48EFGH), could only be explained by transcription from the internal PD1 promoter here identified. This conclusion is in accordance with the loss of transcription observed in JH2-2 (pAM401EH) transformants where the 1as-48A-D genes were deleted 1 as it was suggested by 1EFGH are transcribed together since no P3 promoter could drive the expression of the T3 detected by The absence of mCherry expression driven from PX promoter from S. pneumoniae was the strongest one in E. coli as well as in both, L. lactis and E. faecalis, under these experimental conditions. It is worth noting that among the three functional as-48 promoters identified in this work, P2(2) directs the highest levels of transcription with maximal fluorescence values ranging from 2585 AU in E. coli to 984 AU in E. faecalis or 1206 AU in L. lactis, being E. coli the exception where PA reaches a maximum fluorescence value of ca. 3600 AU . Finally, the PD1 promoter shows a basal and maintained expression, of around 25% compared with that of P2(2) in LAB or 20% in case of E. coli. This expression level must be enough to ensure its protective functional role in the cells (2(2) was 2-fold compared to pTLR1-PA and 4-fold compared to pTLR1-PD1. Although the level of expression was lower in LAB strains than in E. coli, the ratio between each promoter was maintained. Our cumulative results indicate that the mCherry fluorescence increased in parallel with OD600 during the exponential phase of growth reaching the maximal values during the transition to stationary phase.As it is shown in  3600 AU . All thihe cells  and 3, tE. faecalis S-48 strain by the presence of genes harbored in its genome or in pMB-2 (the native plasmid found in this strain) or even to be influenced by the presence of pAM401-81 (with only the as-48 gene cluster cloned). Furthermore, an adapted response to the cultural conditions cannot be discarded in whichever condition. To address these questions, we have designed different experiments in E. faecalis to compare the fluorescence emitted during the growth of the JH2-2 transformants containing PA, P2(2) or PD1 cloned into pTLR1, with that of the double transformants containing, additionally, either pAM401-81 or pMB-2, both of them compatible with pTLR1. In the results exposed in 2(2) and PA promoters (2(2) reaches values of 1065 AU at 22 h, which are higher (p = 0.018) than those obtained for the single JH2-2(pLTR1-P2(2)) transformants, although the most noticeable result is the remarkably reduced fluorescence  repeatedly observed in presence of pMB-2. These results are also in accordance with the minor amounts of secreted AS-48 observed by JH2-2(pMB-2) compared to that of JH2-2(pAM401-81) transformants  are slightly higher in presence of pAM401-81 but more reduced when pMB-2 is present, with significant differences after 14 h of growth  according to the statistical analysis performed.It is likely that the promoters here identified could be regulated in the native romoters  and 4. Tformants . In relaA and P2(2) promoters confirmed that the highest expression levels are achieved at the high pHs (ca. 8) with significant results  from 16 and 18 h of growth  in the presence of pMB-2 (2(2) controls the expression of the 1DD1EFGHas-48C genes encoding two ABC transporters for secretion (1Das-48C) and self-protection (as-48EFGH), in addition to the immunity determinant (1as-48D) against AS-48. As it can be seen in 2(2) was retarded in E. faecalis JH2-2 (pMB-2) and the fluorescence levels were visibly lower at any pH assayed. These results, that have been several times repeated, confirm the above suggestion on the P2(2) promoter, in the sense that it could be regulated in a negative fashion by genes existing in the native pMB-2 plasmid different from those of the as-48 cluster.As above, the response of the aline pH . The mosof pMB-2 . PromoteA, PC, PD1 and two regions for P2 and for P3) putatively involved in the full expression of the AS-48 character, which is dependent on the co-ordinated expression of the 1DD1EFGHas-48ABCC genes. Identifying promoters in this locus is relevant to understand how AS-48 is produced, and how to engineer strains to more effectively produce AS-48. The corresponding amplified regions were cloned into the promoter-probe vector pTLR1 by transcriptional fusions with the mCherry gene. The fluorescence emitted by the transformants with the pTLR1-derivatives during a prolonged incubation in CM-G medium, allowed us to ratify the existence of the PA promoter (driving the expression of the as-48ABC operon) and, more importantly, to definitively localize the P2(2) promoter (involved in the transcription of the second operon 1DD1EFGHas-48CC), and the internal PD1 promoter, presumably responsible for the transcription of the last four genes (as-48EFGH) together with the immunity determinant 1as-48D. The other promoter regions studied, included the P3 promoter reiteratively proposed The current study analyses the functionality of seven promoter regions (namely Pas-48 cluster in LAB strains was the P2(2) promoter here identified, which seems negatively regulated by genes present in pMB-2 plasmid and up-regulated by high pHs and genes of the as-48 cluster, although having a strong basal activity in the absence of regulators. It is tempting to speculate with a membrane stress caused by AS-48 as the trigger for an increased transcription from P2(2) that could involve alternative extracellular function σ factors. This stress could be controlled in cells containing pMB-2 by additional mechanisms encoded in this plasmid whereas in the cells transformed with pAM401-81 this function is overtaken by the two ABC-transporters coded in the 1DD1EFGHas-48C operon. Additionally, the pMB-2 plasmid is a pheromone-responding plasmid involved in conjugation process between enterococcal communities in natural environments. Cells harboring pMB-2 have the capability to elicit a complex response to sex pheromones secreted by the receptor cells, inducing coordinated responses among members of a community and resulting in the formation of cell aggregates that allow clumping of cells to facilitate efficient conjugal transfer of this plasmid. Expression of genes involved in secretion of the bactericidal AS-48 bacteriocin, rapidly kill conventional recipient enterococcal cells preventing the conjugation process, being a disadvantage relative to the transfer of the pMB-2-plasmid from bacteriocin-producing donors, as it has been already demonstrated in a recent study about the transferability of R-Plasmid in bacteriocin-producing E. coli donors A and PD1 promoters have a strength that is one half and one quarter, respectively, compared to P2(2). Both promoters drive a constitutive transcription in all the assay conditions, although the presence of the as-48 genes and the pH seem to enhance their expression.Remarkably, the strongest promoter of the as-48 promoters is organism dependent. Thus, the strength of all these promoters was highest in E. coli, while in LAB strains only minor differences could be observed. Surprisingly the three promoters of the as-48 cluster perform slightly better in lactococcal cells  and JH2-2(pMB-2) against JH2-2 used as indicator strain.(TIF)Click here for additional data file.Figure S2A promoter during prolonged growth in CM-G medium at different pH values normalized by the OD 600 nm in E. faecalis JH2-2 (pTLR1-PA) (low panels). The growth of cultures was monitored at a wavelength of 600 nm (upper panels). Fluorescence emission of mCherry was recorded at 620 nm after excitation at a wavelength of 590 nm (medium panels). pH 6 (red), pH 6.5 (green), pH 7.0 (purple), pH 7.5 (sky blue), and pH 8.0 (orange). Standard deviation bars for the different replicates are included.Influence of pMB-2 and pAM401-81 plasmids in the expression of P(TIF)Click here for additional data file.Figure S32(2) promoter during prolonged growth in CM-G medium at different pH values normalized by the OD 600 nm in E. faecalis JH2-2 (pTLR1-P2(2)) (low panels). The growth of cultures was monitored at a wavelength of 600 nm (upper panels). Fluorescence emission of mCherry was recorded at 620 nm after excitation at a wavelength of 590 nm (medium panels). pH 6 (red), pH 6.5 (green), pH 7.0 (purple), pH 7.5 (sky blue), and pH 8.0 (orange). Standard deviation bars for the different replicates are included.Influence of pMB-2 and pAM401-81 plasmids in the expression of P(TIF)Click here for additional data file.Figure S4D1 promoter during prolonged growth in CM-G medium at different pH values normalized by the OD 600 nm in E. faecalis JH2-2 (pTLR1-PD1) (low panels). The growth of cultures was monitored at a wavelength of 600 nm (upper panels). Fluorescence emission of mCherry was recorded at 620 nm after excitation at a wavelength of 590 nm (medium panels). pH 6 (red), pH 6.5 (green), pH 7.0 (purple), pH 7.5 (sky blue), and pH 8.0 (orange). Standard deviation bars for the different replicates are included.Influence of pMB-2 and pAM401-81 plasmids in the expression of P(TIF)Click here for additional data file.Table S1Sequence of promoter regions studied in this work. The predicted -10 and -35 sequences are underlined and depicted in bold.(DOCX)Click here for additional data file.


Regulation of gene expression is central to cell growth, differentiation and diseases. Context specific and signal dependent regulation of gene expression is achieved to a large part by transcription factors. Cardiac transcription factors regulate heart development and are also involved in stress regulation of the adult heart, which may lead to cardiac hypertrophy. Hypertrophy of cardiac myocytes is an outcome of the imbalance between prohypertrophic factors and anti-hypertrophic factors. This is initially a compensatory mechanism but sustained hypertrophy may lead to heart failure. The growing knowledge of transcriptional control mechanisms is helpful in the development of novel therapies. This review summarizes the role of cardiac transcription factors in cardiac hypertrophy, emphasizing their potential as attractive therapeutic targets to prevent the onset of heart failure and sudden death as they can be converging targets for current therapy.  Transcription factors are sequence-specific DNA binding proteins that control the process of transcription , 2. TheyTranscription factors (TFs) are classified into two broad categories viz., General Transcription Factors (GTFs) and Gene Specific Transcription factors (GSTFs). GTFs are involved in formation of the pre-initiation complex that binds to the promoter region of DNA and regulates the basal transcriptional regulation . On the 1) [2+ - Calcineurin – NFAT signaling, G-Protein Coupled Receptor (GPCR) signaling, Mitogen Activating Protein Kinase (MAPK) signaling, PI3 Kinase signaling via receptor kinase etc.  [Cardiac hypertrophy is the cellular response to stress which helps terminally differentiated cardiac myocytes to sustain workload. Prolonged hypertrophy is maladaptive and associated with a significant thickening of ventricular walls and resulting in progression to heart failure . It is c1) , 12. Ind . 1). This review focuses on the transcription factors that are predominantly expressed in myocardium and regulate the expression of cardiac genes encoding proteins which further govern the structure and function of cardiomyocytes. These transcription factors represent promising targets for novel treatment strategies and therapeutic drugs which could act either by stimulating the transcription of specific genes required for a desired beneficial effect, or by inhibiting the transcription of genes affecting cardiac hypertrophy. Since this disease is regulated by multiple pathways and various transcription factors, which are also involved in cross talk with other signaling components, there is a need of thorough study in order to establish efficient therapeutic strategies.Although numerous biomechanical forces and pathological conditions can result in myocardial dysfunction, it is hypothesized that there is a final common pathway in which transcriptional alterations occur in sarcomeric gene expression, and that this pathway is common to different forms of pathologic hypertrophy. This makes it possible to view cardiac hypertrophy as a gene regulatory disorder. There are numerous transcription factors which have been implicated to be involved in cardiac development and diseases  containing TFs and possess preferential binding to the specific consensus DNA binding sequence (A/T)GATA(A/G) . The famGATA-4 is one of first transcription factors expressed in cardiac cells and plays an important role in transcriptional regulation during cardiac development and growth as well as in cardiac hypertrophy and heart failure , 22. Thein-vitro and in-vivo studies [Initiation of a hypertrophic stimulus results in enhanced DNA-binding activity of GATA-4 which has been confirmed by several  studies -32. The  studies , Endothe studies  or α-adr studies . Rather, studies , ISO [29 studies  have beeHypertrophic stimulus is associated with activation of several signal transduction pathways which ultimately activate GATA-4. Protein phosphorylation is pivotal in regulation of cellular processes such as cell growth, division, differentiation and apoptosis. Similarly, it plays a vital role in regulation of cardiac hypertrophic response through GATA-4. Pressure overload, ISO, PE, ET-1, Angiotensin-II, Phorbol 12-Myristate 13-Acetate (PMA), each induced activation of GATA-4 by phosphorylation , 35-37. in vivo [In addition, induction by PE leads to Rho A mediated sarcomeric reorganization via p38 MAPK and promotes direct phosphorylation of GATA-4 at ser-105 in vivo .GATA-4 activity is negatively regulated by Glycogen Synthase Kinase -3β (GSK-3β) through nucleo-cytoplasmic shuttling of GATA-4. In its activated state, GSK-3β phosphorylates the N-terminal domain of GATA-4 protein. GATA-4 phosphorylation leads to a decrease in its nuclear levels through the nuclear exportin Crm1 . ConsequActivity of GATA-4 is a result of cooperation with a number of other transcription factors and co-activators. p300 possesses intrinsic histone acetyltransferase (HAT) activity which is required for synergistic transcriptional activation of GATA-4. The C-terminal Zinc-Finger domain of GATA-4 is known to interact with various transcriptional activators such as GATA-6, MEF-2, NFAT, Nkx-2.5, SRF, dHAND and YY1 -46, wherThe GATA transcription factors are well characterized and studied transcription factors involved in hypertrophic cardiomyopathy. Furthermore, they are involved in interaction with many other signaling components of various hypertrophic pathways. Therefore, targeting the transcription factors of this family and their interaction with other signaling components provides an attractive therapeutic opportunity in the treatment of cardiac hypertrophy.The myocyte enhancer factor-2 (MEF-2) transcription factors are a family containing a MADS  domain and an adjacent MEF-2 specific domain which together bind to their cognate DNA sequence CAT(A/T)GTA(G/A) , 49. TheThe MEF-2 binding motif has been identified within promoter region of cardiac genes . MEF-2 t2+ signaling owing to activation of Ca2+ - binding proteins, calcium calmodulins (CaMs) and their downstream effector calmodulin kinases (CaMKs) and calcineurin which induce cardiac hypertrophy [Hypertrophic signaling pathways that lead to the activation of MEF-2 transcription factors chiefly include phosphorylation by p38 MAPK , ERK5 alertrophy , 58. CaMertrophy . Phosphoertrophy -62. Thisertrophy -66. Calcertrophy . The exaMEF-2 also interacts with various co-activators such as GATA-4 , NFAT 6, MyoD 6, Smad prDrosophila gene tinman [Drosophila, which establishes its importance in heart development. Further, the expression of Csx/Nkx-2.5 is restricted to heart in various vertebrate species from Zebra fish to Humans [Csx/Nkx-2.5 is a homeobox containing gene identified originally as a vertebrate homolog of the e tinman , 71. A no Humans . The homo Humans . Pressuro Humans , 73, 74.o Humans . Overall6GG [Serum Response Factor (SRF) is a MADS-box transcription factor binds to the CArG box DNA consensus CC(A/T)6GG . These b6GG , 77. Myo6GG . It also6GG . The pro6GG . Inducti6GG . These e) is selectively expressed in ventricles, predominantly in the right ventricle. The gene HAND2  is expressed both in atria and ventricles [These are basic helix-loop-helix transcription factors having role in cardiac development and diseases . Mainly ntricles . The expntricles , 84. In ntricles . The canntricles . Also, ontricles . Since n2+ results in the dephosphorylation and nuclear translocation of cytoplasmic latent NFAT transcription factors [Besides these, scientists are exploring more transcription factors which can be involved in cardiomyopathies. Of these, recently the TEA domain factors have found to be implicated in cardiac specific gene expression and the hypertrophic response of primary cardiomyocytes to hormonal and mechanical stimuli. All TEAD family members contain an evolutionarily conserved 72-amino acid DNA binding domain (TEAD) and bind to the sequence 5′-CATTCC(T/A)-3′ located in the promoter/enhancer region of numerous striated and smooth muscle genes. It also regulates the gene expression by combinatorial interactions with adjacently bound transcriptional regulators and co-activators . Most st factors . It furt factors . They liThe anti-hypertrophic effects in cardiomyocyes can be mediated via inhibitory pathways by transcriptional repressors or suppression of pro-hypertrophic pathways. The transcription factors that regulate these effects are anti-hypertrophic transcription factors. They help in preventing the occurrence of the hypertrophic state by promoting anti-hypertrophic events.The Forkhead/winged family of transcription factors is an essential factor involved in development. It is characterized by a conserved DNA binding domain known as Forkhead box (Fox) that targets a DNA binding sequence TTGTTTAC . The ForFoxO transcription factors modulate response to stress conditions, cell-cycle progression, protein degradation and apoptosis , 95. Pos2+-Calcineurin pathway has been found to be associated with FoxO transcription factors in regulating hypertrophic growth in cardiomyocytes [A number of signaling cascades are involved in cardiac hypertrophy of which the Camyocytes . Overexpmyocytes , 102. Inmyocytes , 104. SiMicrophthalmia Transcription Factor (MITF) is a basic helix-loop-helix leucine zipper DNA binding protein . This trMITF is upregulated by phosphorylation through MAPK pathway -110. β-AYY1 is a 65-kDa multifunctional zinc finger ubiquitously expressed transcription factor, belonging to the human GLI-Kruppel family of nuclear proteins and essential for mammalian embryonic development , 114. Idgridlock) is a hairy related basic helix-loop-helix (bHLH) transcriptional repressor. It is known to be expressed during cardiovascular development and is involved in maintenance of ventricular function [in vivo and in vitro. It was further established through reporter assays that CHF1/Hey2 can directly block activation of ANF, a hypertrophy-associated gene. Also, it was found to interact with GATA-4 in order to attenuate the hypertrophic transcriptional program [CHF1  and target pathophysiological load (vasodilators and diuretics). Although this could be viewed as an indirect targeting of transcription factors but this approach lacks specificity and has limited potential given the redundancy and extensive cross-talk between upstream signaling cascades. Moreover, these therapies greatly vary in effectiveness depending on the signaling pathway targeted and in spite of such conventional therapy cardiomyopathies are an increasing cause of mortality worldwide. Developing drug molecules that will selectively affect particular transcription factors and suppress their activity can be of great therapeutic interest. Transcription factors have ligand-binding, dimerization, transeffector, DNA-binding, nuclear-localization, and regulatory domains, which may be targeted directly by small molecule drugs. Hence, the design of therapeutic agents targeted at pro-hypertrophic transcription factors regulating the initial expression should be the ultimate goal. So far, several agents have been shown to utilize the modulation and/or inhibition of NF-κB to carry out some part of their therapeutic purpose such as glucocorticoids, nonsteroidal anti-inflammatory agents (NSAID), vitamin E, curcumin, thiols, cyclosporin, rifampicin, dithiocarbamates, methotrexate, thalidomide, leflunomide and various fungal and bacterial metabolites. Another approach is promoting the activity of anti-hypertrophic transcription factors. This will provide a protective mechanism to the cells in order to prevent further hypertrophic derangement of gene expression. Other promising alternatives include artificial transcription factor mimics, which consist of normal transcription factor domains conjugated with synthetic compounds targeting DNA-binding domains or regulatory domains. Recent progress in molecular biology has provided new techniques to inhibit target gene expression. Antisense strategy that is complimentary to the mRNA of interest and therefore regulates transcription of disease related genes has important therapeutic potential. Novel molecular strategy in which synthetic double-stranded DNA with high affinity for a target transcription factor may be introduced into cells as “decoy” elements to bind the transcription factor and alter gene expression. Antisense oligodeoxynucleotides are useful tools for the anti-gene strategies for gene therapy and in the study of transcriptional regulation [Cardiac hypertrophy can thus be viewed as a gene regulatory disorder. Cardiac transcription factors are key players that regulate inducible gene expression in cardiac myocytes. The identification of transcription factors as the key regulatory molecules in this process and the analysis of their structure and function have revealed that these proteins are potential targets for therapeutic intervention. They organize the first crucial step in establishing gene function i.e. transcription of information in DNA into mRNA. Translation of mRNA results in synthesis of proteins that manifest hypertrophic conditions further leading to heart failure. Presently, the drugs with anti-hypertrophic activity target the outside-in signaling: i.e. they block hormones , calcium triggers (Cagulation . For insgulation . For the


P. falciparum is poorly understood. Dynamic or stable association of epigenetic marks with genomic features provides important clues about their function and helps to understand how histone variants/modifications are used for indexing the Plasmodium epigenome. We describe a novel, linear amplification method for next-generation sequencing (NGS) that allows unbiased analysis of the extremely AT-rich Plasmodium genome. We used this method for high resolution, genome-wide analysis of a histone H2A variant, H2A.Z and two histone H3 marks throughout parasite intraerythrocytic development. Unlike in other organisms, H2A.Z is a constant, ubiquitous feature of euchromatic intergenic regions throughout the intraerythrocytic cycle. The almost perfect colocalisation of H2A.Z with H3K9ac and H3K4me3 suggests that these marks are preferentially deposited on H2A.Z-containing nucleosomes. By performing RNA-seq on 8 time-points, we show that acetylation of H3K9 at promoter regions correlates very well with the transcriptional status whereas H3K4me3 appears to have stage-specific regulation, being low at early stages, peaking at trophozoite stage, but does not closely follow changes in gene expression. Our improved NGS library preparation procedure provides a foundation to exploit the malaria epigenome in detail. Furthermore, our findings place H2A.Z at the cradle of P. falciparum epigenetic regulation by stably defining intergenic regions and providing a platform for dynamic assembly of epigenetic and other transcription related complexes.Epigenetic regulatory mechanisms and their enzymes are promising targets for malaria therapeutic intervention; however, the epigenetic component of gene expression in  Plasmodium falciparum is a unicellular pathogen that is responsible for the most severe form of malaria. Similar to other eukaryotic organisms, its genome is organized into chromosomes by proteins called histones. Modification or replacement of these histones has marked effects on the packaging grade of DNA and instructs the recruitment of protein complexes, thereby regulating essential cellular processes such as gene expression and replication. Here we unveil the genome-wide localization of two histone H3 modifications (K9ac/K4me3) and a histone variant, H2A.Z, during development of the parasite in the human red blood cells. We find that all three epigenetic features are predominantly present in intergenic regions of the P. falciparum genome, suggesting an interconnecting role in regulation of gene expression. H2A.Z levels appear to be largely invariable throughout intraerythrocytic development while placement/removal of the histone marks is dynamic with H3K9ac and H3K4me3 being transcription-coupled and stage-specific, respectively. These observations support a model in which H2A.Z-containing nucleosomes serve to demarcate regulatory regions in the parasite's genome and promote transcription initiation by guiding chromatin modifying and transcription initiating complexes. The findings and methodological developments presented in this paper provide a cornerstone for future epigenome research in eukaryotic pathogens and vital information to understand and to interfere with parasite development and survival. Plasmodium falciparum, the deadly protozoan parasite, causes malaria via the invasion of erythrocytes. During its ∼48 h asexual reproductive cycle within human red blood cells (RBC), the parasite exploits and remodels the host cell, multiplies and finally ruptures the RBC to invade fresh erythrocytes. This process demands the timely expression of distinct sets of proteins P. berghei ookinete P. falciparumP. falciparum genes, however, fall outside these H3K9me3/HP1-marked heterochromatic domains. Therefore the malaria epigenome, unlike its human counterpart, is dominated by histone modifications generally associated with transcriptionally active states of genes  as well as RNA-seq analysis of the transcriptome throughout P. falciparum at multiple stages of intraerythrocytic development (iRBC cycle). Given that analysis of highly AT-rich sequences provided a major challenge and hindered quantitative analysis of the malaria genome and recently published amplification-free method In this study we applied state-of-the-art deep-sequencing technology to explore the epigenome (ChIP-seq) and transcriptome (RNA-seq) of P. falciparum.Finally, we determined the correlation of the different amplification methods by plotting the tag counts in 150 bp windows against the unamplified control. As expected, both 12- and 6-cycle PCR-amplified genomic sequences deviate substantially from the amplification-free sequences both in coding and intergenic regions, whereas the correlation between T7 and no amplification is linear . In concP. falciparum genome , we generated genome-wide profiles of histone H3 lysine 4 tri-methylation (H3K4me3), histone H3 lysine 9 acetylation (H3K9ac) and histone H2A variant (H2A.Z) at 4 stages  during the iRBC cycle . A minimm genome . To corr regions  and coveOur extensive ChIP-seq dataset provides detailed insight into the dynamics of the epigenome during intraerythrocytic development (discussed below), which confirms and very significantly extends our earlier findings on H3K4me3 and H3K9ac obtained by the use of microarray technology P. falciparum genome annotation. Given the high sensitivity of the method we obtained sequence reads from most coding regions of the Plasmodium genome indicating that over 90% of all genes are expressed to some extent (0.1–50000 tags/1000 bp) during intraerythrocytic development. As expected, the transcription profile of our parasite culture exhibits good general correlation with the recently published P. falciparum transcriptome 2 = 0.73–0.78 for comparable stages). However, correlations between 2 subsequent stages within either of the datasets (representing a 5 or 8 hour stage advance) are higher than those of similar time-points between the datasets. These differences likely result from differences in parasite strain/clone, culturing conditions and synchronicity/staging, stressing that for precise correlation of histone marks to RNA levels it is necessary to generate transcriptome data from the same parasite population used for epigenome analysis.To correlate epigenetic features with steady state level of mRNAs, RNA-seq was performed at 8 time-points during the iRBC cycle on polyA+ RNA . The obtNormalisation methods presume equal transcriptional activity across stages . However, transcriptional activity has been shown to significantly vary, being low after invasion of a red blood cell and reaching the highest level at trophozoite stage P. falciparum genome encodes for multiple histone variants , but their localization and function has remained elusive. To explore the function of the histone variants we set out to analyze the genomic localization of H2A.Z. Since the N-terminus amino acid sequence of PfH2A.Z is distinct from that of other eukaryotes, an antibody against its N-terminal peptide was raised and proved to recognize both acetylated and non-acetylated forms of the protein . var genes have been shown to be expressed in a mutually exclusive manner during ring stage var genes are active in our parasite population and the ring-stage acetylation is observed at almost all upsB type promoters, it seems that this modification has no direct causal relation with the expression of these genes. It is intriguing however that this marking is specific to 1–2 nucleosomes located directly adjacent to/overlapping with SPE2 repeats (Another intriguing example of H2A.Z-independent H3K9ac (and H3K4me3) marking during early stages of the iRBC cycle  can be o repeats , which hTo assess the role of these epigenomic features in relation to gene expression, we first computed the average gene profiles of euchromatic genes with different mRNA levels  within each stage and compared them among stages . These pNext we investigated whether the increased level of these marks at the promoter of genes follows the changes in gene expression through intraerythrocytic development. We performed k-means clustering of euchromatic genes based on the relative abundance of their transcript across 8 stages . Then, wP. falciparum genome. As such they likely provide a platform for histone modifying enzymes to place and/or remove H3K9ac in a transcription-coupled manner, while H3K4me3 appears to be deposited in a stage-specific manner.In summary, our data supports a hypothetical model in which H2A.Z-containing nucleosomes serve as a constant mark of intergenic regions in the Plasmodium falciparum. Our findings reveal important insights into the dynamic as well as static components of the malaria epigenome and how they contribute to the control of gene expression.In this study we present detailed genome-wide localization maps and comprehensive analysis of three epigenetic features accompanied by in-depth transcriptome sequencing during the intraerythrocytic development of the protozoan parasite, P. falciparum), severely hampering the quality and quantitation of the sequence data. Omitting PCR amplification altogether has been reported to circumvent this problem efficiently P. falciparum genome, and for the first time enables highly quantitative analysis of extremely AT-rich intergenic regions (even up to 100%). Importantly, by using the unbiased protocol to sequence mono-nucleosomal DNA fragments we clearly demonstrate that nucleosome occupancy is comparable between coding and intergenic regions of the P. falciparum genome  responsible for placement/removal of these marks and their mechanisms of recruitment are indispensable to elucidate the order of events and the underlying mechanism.Similar to H2A.Z, H3K9ac is also a common feature of euchromatic intergenic regions in the Plasmodium genome as most promoters and even the 3′ end of genes are acetylated to some extent as compared to coding bodies of genes . Medium was changed at every 10 hours, but not less than 10 h before collection. After 20 h post-invasion (hpi), double volume of medium was added to ensure optimal development of the parasites. The culture was divided to separate culture flasks (20 ml each) but these were mixed with every change of medium. Samples for RNA and chromatin isolation were collected at every 5 or 10 hpi, respectively . ParasitP. falciparum parasites. For profiling of canonical H2A, parasites were transfected with a pARL-1a- plasmid All experiments were carried out on 3D7 P. falciparum mixed stage parasites (The H2A.Z antibody (PFC0920w) was created by immunizing rabbits with the peptide ATA-KVIGGKVGGKVGG conjugated to keyhole limpet cyanin (KLH). Antibody was purified by affinity chromatography using the same peptide. The specificity of the antibody was tested in dotblot with the same as well as an acetylated version (K6 and K10) of this peptide and in Western blot against total nuclear extract from arasites .The immunization of the rabbit for H2A.Z antibody production used in this study was carried out in strict accordance with the regulations and recommendations of the Dutch Law for Animal Experimentation (WOD). The immunization experiment was carried out at the Central Animal Laboratory of the Radboud University Medical Center and was approved by the Committee for Animal Experiments of the Radboud University (Permit Number: KUNDEC2001-83). All efforts were made to minimize suffering of the rabbit during immunization and the final bleeding was carried out under hypnorm anesthesia.in vitro cultured ring stage malaria parasites . Nuclei were isolated after saponin lysis of the red blood cells (0.05% saponin in PBS) and lysis of the parasites  on a 0.25 M sucrose cushion. Following Proteinase K digestions at 37°C for 4 h  remaining proteins were removed by phenol-chlorophorm extraction and genomic DNA was precipitated in the presence of EtOH (2.5 volume) and sodium-acetate (0.1 volume of 3 M). DNA pellets were dissolved in TE (50 ng/ul) and sonicated to fragments of 100–700 bp in 100 ul aliquots using the Bioruptor UCD200 (Diagenode).Genomic DNA was extracted from Native ChIP was carried out as described earlier Parasite Culture) at 8 time-points covering all stages of the intraerythrocytic development. RNeasy Mini Kit (Qiagen) was used according to manufacturer's instructions (12 columns were used for RNA isolation of each sample and the resulting RNA was further cleaned on two columns). DNase treatment was performed on the columns  at both rounds of purification. Total RNA was directly subjected to a single round of polyA-selection  to enrich for mRNAs. Subsequently, 3–5 µg total RNA-equivalent polyA+ mRNA was fragmented by hydrolysis in 40 mM Tris-Acetate pH 8.2, 100 mM potassium acetate, 30 mM magnesium acetate for 1 min 45 sec at 85°C followed by purification via precipitation.RNA was isolated from 20 ml synchronous culture  in the presence of 1× first strand buffer (Invitrogen), 11 µg AT-corrected nonamer primers (76%AT), 10 mM DTT, 1 mM each of dNTPs and 40 units RNasin Plus RNase inhibitor (Promega) in 20 µl total volume. The reaction was incubated at 37°C for 10 minutes and subsequently at 42°C for 1 hour. A similar reaction lacking reverse transcriptase (RT- control) was assembled to check for any genomic DNA contamination by qPCR and was negative for all samples.E. coli DNA Polymerase I  and E. coli DNA ligase  in the presence of RNase H . The 150 µl reaction mixture in 1× second strand buffer (Invitrogen) supplemented with 0.2 mM each of dNTPs was incubated at 16°C for 2 hours. Afterwards, ds cDNA was purified using MinElute Reaction Clean-up Kit (Qiagen). ∼40 ng of each sample ranging in size from 100 bp–1 kb was used for sequencing sample preparation as described below.Single-stranded cDNA was converted to double-stranded cDNA by in vitro transcribed using T7 polymerase. cDNA synthesis from the resulted RNAs is initiated from a primer complementary to the adapter A ensuring that the library will only contain full-length fragments with two distinct adapters. After removal of excess primers via gel extraction, DNA fragments are directly used for cluster formation and sequencing.To avoid any changes in the composition of the samples due to PCR amplification we developed an unbiased linear T7 amplification method that produces highly representative sequencing libraries (detailed protocol has been submitted to Nature Protocols and available upon request). In short: End repaired and A-tailed DNA fragments are ligated with custom adapters (A and B) corresponding to the two strand of the Illumina adapters, one of which (B) is extended by the T7 promoter sequence. Ligated and size selected DNA fragments are then To test the newly developed linear amplification protocol, 40 ng of the sonicated genomic DNA was used for library preparation by standard PCR-based (Illumina) or our T7 amplification protocols, and 400 ng DNA was processed by the amplification-free method For ChIP-seq or RNA-seq analysis 6–40 ng immunoprecipitated and mono-nucleosomal input DNA or ds cDNA was used for preparation of sequencing libraries by the T7 amplification method.Plasmodium falciparum genome assembly (PlasmoDB v6.1) for ChIP and input samples or against the Plasmodium falciparum annotated transcripts (PlasmoDB v6.1) for mRNA samples using BWA Sequencing libraries (32.5 pmol each) were loaded on the Illumina Genome Analyzer IIx and sequenced for 76 cycles from one side of the fragments (Standard Cluster Generation Kit v2 and 2×36-cycle sequencing kit v3). Quality filtered 76 bp sequence reads were mapped against the For comparative analysis a common number of uniquely mapped reads were picked for each dataset, respectively: 10 M for genomic DNA; 5.5 M for ChIPed; 11 M for input, 8.2 M for mRNA samples. .Plasmodium falciparum genome (PlasmoDB v6.1).Coverage plots were generated by counting the number of overlapping, uniquely mapped 76 bp tags in 10 bp windows and visualized in SignalMap (NimbleGen). Ratio tracks were obtained by dividing the tag counts with the corresponding tag counts of the amplification-free method, smoothened by moving average method (in a 150 bp window) and displayed on a log2 scale. GC-track was generated by plotting the GC-content (%) per 150 bp window of the For scatter plots the number of uniquely mapped tags were counted in 150 bp windows (based on the location of the first base) and plotted against the corresponding value of the amplification-free sample. These 150 bp windows were assigned to coding and intergenic regions (genome annotation PlasmoDB v6.1) if more than half of their sequence falls into either of these categories. To correlate the coverage with AT-content, these 150 bp windows have been grouped on the bases of their AT-content and the average number of unique and non-unique randomly placed tags mapping to these groups was displayed.P. falciparum genome (PlasmoDB v6.1) were determined and mapped against this reference genome. Sequence tags at the size of 10–40, 42, 44, 46, 48, 50, 52, 60, 70, 76, 80, 90, 100, 125 and 150 bases were generated using a python script that uses all positions in the genome sequences as a start and takes the given number of bases (length) including and upstream of the starting base. Mapability at each position of the genome was calculated by counting the number of overlapping, uniquely mapped tags in a 10 bp window and plotted as a percent of maximum. For general mapability the percentage of uniquely mapable tags in the whole genome were defined and plotted according to their read length. To determine mapability in subsections of the genome  tags were assigned to the specified regions if at least 50% of the tag falls within these regions (intersections were done using a Perl script).To calculate theoretical mapability, all possible sequence tags of a given length that can be obtained from the Plasmodium falciparum heterochromatin protein 1 (PfHP1) published by Flueck et al.Boxplots were generated in R from the ratios of the tag counts in the ChIPed vs input or input vs genomic DNA datasets using standard settings. Tags were assigned to the coding or intergenic regions (genome annotation PlasmoDB v6.1) if more than 50% of the tag falls within these regions. Heterochromatic regions were defined based on genome-wide localization of For comparison of different datasets on nucleosome occupancy raw MAINE-seq data for three stages P. falciparum transcriptome (annotated transcripts PlasmoDB v6.1) and 1.9 M uniquely mapped tags were randomly selected from each. The sum of all tags mapping to one gene was determined for each dataset and correlations were obtained in R on log-transformed values using default settings.To determine correlations between RNA-seq data from Otto and colleagues vs input datasets has been computed in each individual windows and averaged in the corresponding window of all genes with similar expression levels .Average gene profiles were computed for ∼2600 genes within the euchromatic domain  with coding body of 1–10 kb  and a minimum of 800 bp intergenic regions on both sides (to minimize overlap with flanking region of nearby genes). The coding body of these genes was divided into twenty equal size windows and four 150 bp windows immediately up- or downstream represented flanking sequences. The ratio of the tag counts in the ChIPed For expression profiling of genes, RNA-seq sequence reads from 8 stages of the RBC cycle were mapped against the transcriptome  and 8.2 M uniquely mapped tags were randomly selected from each. To provide better approximation of the true transcriptional activity, tag density (per 1000 bp) values at each stage were adjusted by a scaling factor derived from total RNA yield and the average number of nuclei, respectively (see http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23787). All data is also available at PlasmoDB (www.plasmodb.org).Raw sequencing data and processed data files described in this publication are deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE23787 for mono-nucleosomal inputs, H2A, H2A.Z, H3K9ac and H3K4me3 ChIP-seq and RNA-seq expression data . hpi: hours post-invasion (B) Representative image of Giemsa stained blood smear at each time point. Percentage of ring (R), trophozoite (T) or schizont (S) stage parasites and the number of nuclei per parasite have been defined by visual inspection of 1000 infected red blood cells.Sample collection scheme. (A) Collection scheme for total RNA (every 5h) and nuclei (every 10h) from highly synchronous (5.54 MB PDF)Click here for additional data file.Figure S2Plasmodium falciparum genome. (A-C) Plasmodium falciparum genomic sequence (PlasmoDB v6.1) was used to generate all possible reads of fixed length. Reads were mapped back onto the genome and the percentage of the uniquely mapable fragments (mapping to a unique position in the genome) were plotted according to the length of the sequence tags in the (A) whole genome (B) euchromatic or repeat-rich and multi gene family containing heterochromatic domains (C) euchromatic coding and AT-rich intergenic regions, respectively. (D-E) Representative screenshot displaying the percentage of uniquely mapable fragments of 36bp, 52bp, 76bp and 100bp in the heterochromatic (D) and euchromatic (E) domains.Mapability of sequences reads with different length on the highly AT-rich (1.40 MB PDF)Click here for additional data file.Figure S3P. falciparum genome at four different stages of intra-erythrocytic development . (B) Representative screenshot showing direct comparison of H4_ChIP-on-chip (log2-ratio ChIP-over-genomic DNA) Nucleosome occupancy is similar between coding and intergenic regions. (A) Box-plot displaying the ratios of mono-nucleosomal vs genomic DNA tag counts in every coding (C) and intergenic (IG) region of the (0.72 MB PDF)Click here for additional data file.Figure S4Plasmodium falciparum parasites. Colour code indicates the level of correlation . (B) Graph showing the scaling factor used for scaling of RNA-seq data to better approximate transcriptional activity per nucleus. Scaling factor is calculated based on the amount of total RNA collected from each stage, divided by the average number of nuclei per parasite in that stage.RNA-seq interdataset comparison and scaling method. (A) R2-correlation values from pair-wise comparison of our 8 stages RNA-seq and 7 stages of published RNA-seq data (0.23 MB PDF)Click here for additional data file.Figure S5H. sapiens, P. falciparum, T. brucei, T. gondii. The highly conserved core domain is surrounded by a dashed line. Acetylated lysines at the N-terminus of H2A.Z are bolded and underlined. The peptide used for immunisation is highlighted in yellow. (B) Dot blot experiment demonstrating similar affinity of the H2A.Z antibody to the acetylated and non-acetylated peptide. (C) The H2A.Z antibody specifically recognises its target protein in total nuclear isolate from asynchronous parasite culture.Generation and characterisation of polyclonal H2A.Z antibody. (A) Alignment of the protein sequence of histone H2A and H2A.Z proteins from (0.91 MB PDF)Click here for additional data file.Figure S6Generation and characterisation of H2A-Ty1 strain. (A) Map of the pARL-1a-Ty1-H2A plasmid transfected into 3D7 parasites. (B) Western blot demonstrating specific recognition of the Ty1-tagged H2A protein by the BB2 antibody in the transgenic parasite line. (C) Immunofluorescent assay showing nuclear localisation of the ectopically expressed Ty1-H2A protein at all stages of the intra-erythrocytic cycle.(0.95 MB PDF)Click here for additional data file.Figure S7H3K9ac and H3K4me3 shows very similar localisation to H2A.Z. Average profile of H2A.Z occupancy, H3K9ac and H3K4me3 marking over euchromatic genes in schizont stage parasites. The coding region is indicated by the arrow (divided into 20 bins), 5′ and 3′ intergenic regions are displayed as 4 blocks of 150bp.(0.17 MB PDF)Click here for additional data file.Figure S8H2A.Z occupancy is invariable, while H3K9ac and H3K4me3 markings are dynamic through the intra-erythrocytic cycle. Screenshot of same chr2 region as shown in (0.49 MB PDF)Click here for additional data file.Figure S9Regions specifically acetylated on H3K9 independent of H2A.Z during trophozoite stage, might corresponds to origins of replication. Screenshot of the H2A.Z, H3K9ac and H3K4me3 ChIP-seq coverage plots at four stages of intra-erythrocytic development  from a subsection of chromosome 10. The region with increased H3K9ac only in trophozoite stage is surrounded by a dashed line.(1.53 MB PDF)Click here for additional data file.Figure S10SPE2 repeats upstream of upsB type var genes carry H3K9ac and H3K4me3 independent of H2A.Z. Screenshot of the H2A.Z, H3K9ac and H3K4me3 ChIP-seq coverage plots at four stages of intra-erythrocytic development  from the distal end of chromosome 2. SPE2 repeat containing region carrying H3K9ac and H3K4me3 during ring stage is surrounded by a dashed line.(1.13 MB PDF)Click here for additional data file.Figure S11H2A.Z occupancy and H3K9ac marking upstream of genes correlates with steady state mRNA levels. Average profile of H2A.Z occupancy, H3K9ac and H3K4me3 marking over groups of genes with different mRNA levels at four stages of intra-erythrocytic development. To avoid signal coming from the neighbouring genes, only euchromatic genes (∼2600) with a minimum of 800bp intergenic region on both sides were included in this analysis. Coding body is indicated by the arrow (divided into 20 bins), 5′ and 3′ intergenic regions are displayed as 4 blocks of 150bp.(0.72 MB PDF)Click here for additional data file.


Bmal1−/− mice upon time-restricted feeding, for which a rhythmic, but slightly delayed, binding of SREBP1 was maintained. Collectively, our results show that besides the nutrient-driven regulation of SREBP1 nuclear translocation, a second layer of modulation of SREBP1 transcriptional activity, strongly dependent from the circadian clock, exists. This system allows us to fine tune the expression timing of SREBP1 target genes, thus helping to temporally separate the different physiological processes in which these genes are involved.In mammals, the circadian clock allows them to anticipate and adapt physiology around the 24 hours. Conversely, metabolism and food consumption regulate the internal clock, pointing the existence of an intricate relationship between nutrient state and circadian homeostasis that is far from being understood. The Sterol Regulatory Element Binding Protein 1 (SREBP1) is a key regulator of lipid homeostasis. Hepatic SREBP1 function is influenced by the nutrient-response cycle, but also by the circadian machinery. To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulates SREBP1 activity, we evaluated the genome-wide binding of SREBP1 to its targets throughout the day in C57BL/6 mice. The recruitment of SREBP1 to the DNA showed a highly circadian behaviour, with a maximum during the fed status. However, the temporal expression of SREBP1 targets was not always synchronized with its binding pattern. In particular, different expression phases were observed for SREBP1 target genes depending on their function, suggesting the involvement of other transcription factors in their regulation. Binding sites for Hepatocyte Nuclear Factor 4 (HNF4) were specifically enriched in the close proximity of SREBP1 peaks of genes, whose expression was shifted by about 8 hours with respect to SREBP1 binding. Thus, the cross-talk between hepatic HNF4 and SREBP1 may underlie the expression timing of this subgroup of SREBP1 targets. Interestingly, the proper temporal expression profile of these genes was dramatically changed in  Circadian rhythmicity is part of our innate behavior and controls many physiological processes, such as sleeping and waking, activity, neurotransmitter production and a number of metabolic pathways. In mammals, the central circadian pacemaker in the hypothalamus is entrained on a daily basis by environmental cues (i.e. light), thus setting the period length and synchronizing the rhythms of all cells in the body. In the last decades, numerous investigations have highlighted the importance of the internal timekeeping mechanism for maintenance of organism health and longevity. Indeed, the reciprocal regulation of circadian clock and metabolism is now commonly accepted, although still poorly understood at the molecular level. Our global analysis of DNA binding along the day of Sterol Regulatory Element Binding Protein 1 (SREBP1), a key regulator of lipid biosynthesis, represents the first tool to comprehensively explore how its activity is connected to circadian-driven regulatory events. We show that the regulation of SREBP1 action by nutrients relies mainly on the control of its subcellular localization, while the circadian clock influences the promoter specific activity of SREBP1 within the nucleus. Furthermore, we identify the Hepatocyte Nuclear Factor 4 (HNF4) as a putative player in the cross-talk between molecular clock and metabolic regulation. Mammals possess an internal circadian clock which allows them to anticipate and adapt to daily environmental changes −/−;cry2−/−cry1 mice, a normal expression pattern of several SREBP1 target genes can be restored by an imposed rhythmic food intake The Sterol Regulatory Element Binding Protein 1 (SREBP1), a basic Helix-Loop-Helix-Leucine Zipper (bHLH-LZ) transcription factor, plays a key role in the regulation of lipid biosynthesis, which is one of the most feeding-related function in the liver To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulate SREBP1 activity, we evaluated the genome-wide binding of SREBP1 to its targets along the day in wild-type mice. Our results define SREBP1 binding pattern in the physiological context of both rhythmic food absorption and circadian rhythm and they give the first tools to comprehensively explore how SREBP1 activity is connected to circadian-driven regulatory events.Srebp1 gene itself . ChIP-seq with an antibody that recognizes both SREBP1 isoforms was performed at each time point. The SREBP1 antibody was tested extensively  and has e itself . 53% of e itself , the fire itself . The obse itself . CollectSREBP1 binding sites identified in this study are grouped in four clusters with a slightly shifted phase. To better investigate the features of these sites we calculated the number of nucleotides spanned by each peak and found that sites belonging to cluster A (236 out of 448) were narrow, with a typical length of about 200 nucleotides . These pTo explore the cellular processes that are regulated by SREBP1 along the day, we annotated each site with the nearest Ensembl transcript. We used DAVID In Bmal1−/−) only during the darkness period for one week before collecting liver samples every four hours. Upon this experimental conditions, the circadian clock was completely disrupted in −/−Bmal1 mice, as demonstrated by the flattened expression of key core and output components of the clock, such as Clock1, Cry1, Cry2, D site albumin promoter binding protein (Dbp), Rev-Erbα and Kruppel-like factor 10 (Klf10) . However, the heatmap rendering of their expression patterns .To understand the molecular mechanism underlying the different temporal expression of SREBP1 target genes, we first explored the possible involvement of the network SREBP1-SP1-NFY-HNF4 in determining the functional effect of the binding of SREBP1 to its targets. To check for the presence of a pattern characterizing the three groups of SREBP1 target genes identified earlier see , we eval (Klf10) . Body we−/− mice . Importa−/− mice . Accordi onwards  and its  onwards . We next onwards . Finally−/− mice . Most SRpatterns  revealedn factor . Accordin factor  were nown factor . This ph−/−Bmal1 may perturb, at least in part, the phase of several SREBP1 target genes. Indeed, in WT mice, the temporal expression profile of SREBP1 and REV-ERBs is very different  in the liver along an entire day. SREBP1 binds to 448 sites with an oscillatory profile that is temporally coherent with the phase of its maximal expression. Within SREBP1 binding sites, four distinct groups are clearly distinguishable. The first set (cluster A) contains peaks that are likely the more relevant in the transcriptional regulation mediated by SREBP1 as they are the closest to TSS and they are bound more rhythmically by SREBP1. Importantly, in more than 60% of these sites we identified the direct repeat 5′-ATCACCCCAC-3′ that was described as the Sterol regulatory proteins Responsive Elements (SRE) in several promoters, such as the human LDL receptor promoter et al have published a list of liver SREBP1 target genes obtained from a genome-wide study of mice subjected to 24 hours fasting followed by 12 hours refeeding with high carbohydrate diet 5′ACTACANNTCCC-3′) was identified as a preferred site for SREBP1 binding, and no enrichment of the predicted NFY binding site was identified. The difference between this data set and ours can most likely be attributed to the difference in the specific experimental conditions, acute challenge on the one hand and physiological condition on the other hand (present study). Consistent with our study, both SP1 and NFY proteins were recruited on more than 30% of SREBP1 target genes in a genome-wide analysis of SREBP1 binding in HepG2 cell line SREBP1 is a highly circadian transcription factor whose activity is strongly regulated by nutrient availability through the insulin signaling pathway. In mouse liver SREBP1 expression displays a daily rhythm with a peak in the nocturnal feeding period under standard housing condition of mice Pck-1) gene by impairing the recruitment of the transcriptional coactivator Peroxisome Proliferator-Activated Receptors γ Coactivator -1 (PGC-1) on HNF4α Pparα) gene, that was shown to be crucially regulated by HNF4 In the liver the expression of several known SREBP1c target genes is decreased in fasted mice, when the levels of SREBP1 are very low and increased upon refeeding, when both SREBP1 expression and nuclear translocation are induced −/−;cry2−/−cry1 mice, RF restores the oscillatory circadian expression profile of a number of “feeding driven” transcripts, although with a small delay in their phase of expression, showing that the circadian clock anticipates changes in the feeding state and accelerates the transcriptional response to an acute activation or repression by feeding −/−Bmal1 mice, rhythmic SREBP1 expression and activity, that are drastically flattened when mice are fed ad libitum (data not shown), are reinstated upon RF, although with a deferred phase. Notably, growth and metabolic defects that were reported in −/−Bmal1 mice either at older age or under different feeding regimens −/−Bmal1 mice at 8–10 month of age have an impaired insulin release due to the absence of a functional clock in pancreatic beta-cells −/−Bmal1 mice at 3 month of age upon RF. Conversely, the expression of REV-ERBα, that is directly regulated by BMAL1, is constantly downregulated. This event leads to the derepression of the Insulin Induced 2 (Insig2) gene, encoding a trans-membrane protein that sequesters SREBP proteins to the endoplasmic reticulum membranes, thus interfering with the proteolytic activation of SREBPs, in agreement to what was shown in REV-ERBα−/− mice −/−Bmal1 mice the phase of SREBP1 recruitment to DNA is shifted, but we do not observe a longer SREBP1 accumulation on its targets, suggesting that the absence of a functional clock is not significantly altering its degradation process. In conclusion, our results show that besides the nutrient-driven regulation of SREBP1 nuclear accumulation, a second layer of modulation of SREBP1 transcriptional activity exists and is strongly dependent from the circadian core clock. This system allows to fine tune the expression timing of SREBP1 target genes, thus helping to temporally separate the different physiological processes in which these genes are involved. Thus, SREBP1 is situated at the interface of the circadian and the metabolic regulation and its study promises to shed light on the emerging association between diabetes, obesity, sleep, and circadian timing.In recent years, growing evidences have highlighted the impact of circadian gene networks on nutrient balance and, on the other hand, the regulation of the circadian clock by metabolism and food consumption −/−Bmal1 mice were a kind gift from Dr. Frédéric Gachon and were generated as previously described All animal experiments and procedures were approved by the Swiss Veterinary Office (authorisation VD-1453.4). C57BL/6 male were purchased from Charles River. Perfused livers were processed for chromatin preparation as previously described http://www.Bioconductor.org). Normalized expression signals were calculated from Affymetrix CEL files using RMA normalization method. For quantitative RT-PCR analysis, the retrotranscription has been done using iScript cDNA synthesis kit  and following the manufacturer's instructions. The primers sequences are shown in 36b4 and the Rps9 expression level in each sample using the qBase Software.About 100 mg of snap-frozen liver tissue were used for RNA preparation with the TRIzol reagent (Invitrogen) followed by purification with miRNeasy Mini Kit (Qiagen), according to manufacturer's instructions. For microarray analysis 500 ng of total RNA from each liver sample at the same time point were pooled and analyzed on Mouse Gene 1.0ST arrays according to the manufacturer's instructions (Affymetrix). All statistical analyses were performed with the statistical language R and various Bioconductor packages ) using Bowtie The mapped reads were shifted to account for the length of the inserts based on the average fragment size, namely 190 184 204 199 202 208 and 176, for each of the seven libraries. The fragment size was divided by two and half of the read length was subtracted resulting in a shift of 55, 52, 62, 60, 61, 64, and 48 nucleotides from ZT02 to ZT26.We fragmented the genome into 500 nucleotide blocks and collected the counts within each block for SREBP1 as well as for input experiments. We kept all blocks for which we had a signal equivalent to 40 tags in at least one time point of the SREBP1 experiment. We log transformed the data after adding 1 pseudo count and quantile normalized both SREBP1 and input experiments. We selected blocks with a log2 signal SREBP1/input greater than 2, i.e. at least a four-fold enrichment of the SREBP1 signal in comparison to the input signal in at least one time point. We repeated this procedure by shifting the block definition of half the length of the blocks and merged the overlapping blocks that passed these criteria.To define proper “peaks” in these wide regions, we look for shorter regions accounting for most of the counts. For this, we repeatedly consider the two borders along 50 nucleotides, and discard the one with less read counts if we keep 75% of the total reads in the remaining region. This operation is repeated with shorter borders until no further refinement is possible.We used the MEME suite Before fitting a cosine function to estimate the amplitude and the phase of the oscillation in a 24 hour period, counts in the refined peaks were quantified and normalized according to the total number of non redundant mapped reads for each given library.We used the function x(t) = b0+b1*cos(b3+2π*t/24) to perform a least squared fitting of temporal profiles. The parameter b0 represents the mean signal, b1 the amplitude of the oscillation, and b3*24/2π the phase. These parameters were estimated by nonlinear least-squares using the Gauss-Newton algorithm.For the microarray temporal profile analysis we used the function −/−Bmal1 mice we used the functiongt, b1gt, b3gt the associated coefficients.while when we compared WT and http://cyclix.vital-it.ch.Illumina sequencing data for the ChIP-seq are available at GEO as the GSE48375. Additional processed data and visualization tools are provided at Figure S1Fatty acid synthase (Fasn) and Low density lipoprotein receptor (Ldlr) promoters. Neg1 and Neg2 were used as negative control loci, and correspond to a site specifically recognized by Pol III and to a region between a exon 6 and intron 6–7 of the glyceraldehyde 3-phosphate dehydrogenase (Gapdh) gene, respectively. Fold enrichments relative to the negative controls are greater than 40-fold for Fasn and about 10-fold for Ldlr. (B) In samples processed in absence of antibody none of the tested sequences was significantly enriched. Primer sequences are listed in Validation of SREBP1 antibody for ChIP experiments. (A) C57BL/6 mice were fasted 24 hours and re-fed for 12 hours before liver collection for chromatin preparation. SREBP1 binding was tested on two positive control loci, the (PDF)Click here for additional data file.Figure S2Temporal relationship of SREBP1 and Pol II profiles and mRNA accumulation of SREBP1 putative target genes. Phase histograms for SREBP1 target genes belonging to clusters A1, A2 and A3. While SREBP1 binding phases are sharply concentrated between ZT14 and ZT18 for all genes, the temporal distribution of Pol II recruitment and mRNA expression is different in the three clusters. The phases are plotted only for genes with an amplitude P-value<0.05 for mRNA.(PDF)Click here for additional data file.Figure S3−/−Bmal1 mice. Body weight (A) and daily food intake (B) were measured in Bmal1−/− and control mice at 14 week of age. (C) −/−Bmal1 (red line) and control mice (black line) were fed only during the night for one week before the sacrifice. Plasma glucose levels were measured at the indicated time points (n = 3–6).Metabolic parameters in (PDF)Click here for additional data file.Figure S4Bmal1−/− mice. The graph shows the smoothing of phase distributions of the genes belonging to the three clusters . Only genes showing a P-value<0.05 in wild-type mice are plotted.Phases distribution of SREBP1 target genes in (PDF)Click here for additional data file.Table S1Sequencing data for the ChIP-seq of SREBP1: Number of sequenced and non-redundant tags at each time point.(PDF)Click here for additional data file.Table S2Enrichment of motifs for SREBP1, SP1, NFY and HNF4 in SREBP1 peaks. To estimate the empirical P-Value for motifs discovered by MEME, we randomly selected 1000 groups of 236 regions and counted the number of matches of the indicated motifs in these regions. The random regions were selected to bear the same characteristics as the cluster A regions: their size and distance to TSS are similar to the ones of cluster A regions, and they are close to the TSS of genes expressed in our dataset . For all 1000 random groups, we found less matches than in the regions associated to SREBP, showing that these motifs are enriched with an empirical P-Value<0.001.(PDF)Click here for additional data file.Table S3Functional annotation clustering of putative SREBP1 targets using DAVID tools. The annotation links the sites belonging to cluster A to the closest gene irrespective of the distance. In total, 219 out of 236 sites have functional annotation. The genes associated to each functional term that was significantly enriched are shown. P-value = Modified Fisher's Exact Test, B = Benjamini corrected P-value.(TXT)Click here for additional data file.Table S4Functional annotation clustering of putative SREBP1 targets displaying a different combination of binding sites for SP1, NFY and/or HNF4. Functional annotation clustering for the four sub-groups of putative SREBP1 target genes presenting a different combination of binding sites for NFY, SP1 and/or HNF4. The genes associated to each functional term that was significantly enriched are shown. P-value = Modified Fisher's Exact Test, B = Benjamini corrected P-value.(XLSX)Click here for additional data file.Table S5−/− mice for genes reported in −/− mice (NRC samples). Mice were fed only during the night (ZT12–ZT24) for one week before collecting liver. Reported data are from 2 pools/condition (n = 3–5).Gene expression profiles in liver tissue of wild type and Bmal1(TXT)Click here for additional data file.Table S6Frequency of HNF4 motifs in putative SREBP1 targets with a different temporal expression profile. The percentages refer to the frequency of the HNF4 motif that was discovered by MEME in the regions under SREBP1 peaks of the three cluster of genes with different temporal expression profile. HNF4 motifs were significantly enriched in the peaks of genes expressed between ZT4.4 and ZT13 .(PDF)Click here for additional data file.Table S7Primer sequences used in qPCR analysis of gene expression.(PDF)Click here for additional data file.Table S8Primer sequences used in ChIP-qPCR experiments.(PDF)Click here for additional data file.