Hypocotyl cell elongation related to photomorphogenesis in Arabidopsis seedlings is regulated by a network involving ethylene, auxin, and brassinosteroid signalling that is mediated by interactions among ERF72, ARF6, and BZR1, forming a revised BZR-ARF-PIF/DELLA-ERF (BAP/DE) module. in vitro and in vivo, and it antagonised regulation by ARF6 and BZR1 of the transcription of BEE3 and XTH7. In addition, light modulated the subcellular localisation of ERF72 and transcription of ERF72 through the EIN2-EIN3/EIL1 pathway, facilitating the function of ERF72 in photomorphogenesis. The expression of BEE3 and XTH7 was also regulated by the EIN2-EIN3/EIL1 pathway. Our findings indicate that a revised BZR-ARF-PIF/DELLA-ERF (BAP/DE) module integrates light and hormone signals to regulate hypocotyl elongation in Arabidopsis.The phytohormones brassinosteroid (BR), auxin, and gibberellin (GA) regulate photomorphogenesis-related hypocotyl elongation in Arabidopsis via the co-operative interaction of BZR-ARF-PIF/DELLA (BAP/D) transcription factors/regulators. In addition, ethylene activates the PIF3 or ERF1 pathway through EIN3/EIL1 to balance hypocotyl elongation in Arabidopsis seedlings. However, the mechanism by which ethylene is co-ordinated with other phytohormones to produce light-regulated hypocotyl growth remains elusive. In this study, we found that hypocotyl cell elongation is regulated by a network involving ethylene, auxin, and BR signalling, which is mediated by interactions among ERF72, ARF6, and BZR1. ERF72 interacted directly with ARF6 and BZR1  After germination, plants exhibit two distinct adaptations to the surrounding environment. Seedlings grown in darkness exhibit elongated hypocotyls and the formation of an apical hook, while development of the cotyledons, apical meristem, and root system is inhibited; this is termed skotomorphogenesis. In contrast, seedlings grown in light and undergoing photomorphogenesis are characterised by inhibited hypocotyl elongation, accelerated root growth, opened and green cotyledons, and no apical hook . Both skshy2-2 grown in the dark show short hypocotyls, expanded cotyledons, open apical hooks, and true leaf primordia, suggesting an important role for auxin in regulating photomorphogenesis  at the cell surface and transduces the signal to activate the transcription factors BRASSINOZALE-RESISTANT1 (BZR1) and BZR2 , which regulate the expression of BR-responsive genes . ArabidoEXP8, BIM1, BEE1/3, PREs, HAT2, IBH1, HFR1, PAR1/2, and EXO) -induced degradation of DELLA proteins via the ubiquitin-proteasome pathway . DELLAs ETHYLENE RESPONSE FACTOR1 (ERF1), and the other depends on the induction of PIF3; both are direct targets of EIN3. Under dark conditions, PIFs promote hypocotyl elongation, and soil-dependent ethylene accumulation leads to ERF1-mediated thickening of the hypocotyl cell wall and inhibition of etiolated hypocotyl elongation. The increased level of ethylene also represses biosynthesis of the chlorophyll precursor protochlorophyllide in the cotyledons via the PIF3 pathway. Protochlorophyllide, when present at high levels, can cause photo-oxidative damage after light absorption. However, when seeds germinate in the presence of light or when seedlings emerge from the soil, PIFs are degraded and the ethylene-induced increased abundance of PIF3 stimulates hypocotyl elongation. In contrast, ERF1 is stabilised in the presence of light, and further stimulation of ERF1 by ethylene has no effect on growth , ETR2, ETHYLENE RESPONSE SENSOR1 (ERS1), ERS2, and ETHYLENE-INSENSITIVE4 (EIN4), that relieve repression by CONSTITUTIVE TRIPLE RESPONSE1 (CTR1) of the downstream signalling component EIN2 . EIN2 isERF72 (35S::MAERF) exhibited the constitutive photomorphogenesis phenotype of a short hypocotyl, no apical hook, and open cotyledons in darkness, compared with the wild-type, the erf mutant, and plants overexpressing wild-type ERF72 (35S::MCERF). Transcriptomic analyses showed that light-regulated genes and ARF6- and BZR1-target genes were enriched among ERF72-related differentially expressed genes. We further demonstrated that ERF72 interacted with ARF6 and BZR1 to repress their activation of the transcription of target genes. Moreover, light modulated the subcellular localisation of ERF72 and the transcription of ERF72 through the EIN2-EIN3/EIL1 pathway. The expression of BEE3 and XTH7 was also regulated by the EIN2-EIN3/EIL1 pathway under any light regimen. Our results suggest that a revised BZR-ARF-PIF/DELLA-ERF (BAP/DE) module is involved in integrating light and hormone signalling pathways to control cell elongation in Arabidopsis hypocotyls.In this study, we found that transgenic Arabidopsis seedlings overexpressing stable Arabidopsis thaliana plants used in this study were of the Col-0 ecotype. The T-DNA insertion mutant erf (Stock No: CS849696) was obtained from The Arabidopsis Information Resource  and confirmed by genotyping, PCR, and RT-PCR (JXB online). All seeds were surface-sterilised and sown on half-strength Murashige and Skoog (MS) medium containing 1.5% sucrose and 0.7% agar, and incubated at 4 °C under dark conditions for 3 d. The plates were then irradiated with white light for 6 h to promote germination and subsequently kept either in darkness set periods of time or under continuous red light (60 µmol m–2 s–1), far-red light (5 µmol m–2 s–1), blue light (7 µmol m–2 s–1), or white light (60 µmol m–2 s–1) for 5 d. For the light-to-dark transition experiments, seedlings were grown under continuous light or dark conditions for 7 d, and then transferred to the opposite conditions for set periods of time. For cycloheximide (CHX) treatment, seedlings were grown in continuous light for 7 d, transferred to plates containing half-strength MS medium with or without 100 μM CHX, and then placed in the light or darkness for set periods of time. The seedlings were then collected for experimental use.The https://imagej.nih.gov/ij/).Images of the hook and hypocotyl phenotypes of seedlings were obtained using an EOS60D digital camera . Cell length was determined using a confocal laser-scanning microscope . Hypocotyl length and cell length were measured using the ImageJ software (MCERF) and stable ERF72  lacking a stop codon were amplified by RT-PCR and inserted into the BamHI and NotI restriction sites of the plasmid pE2c , which harbours a triple HA-tag, to generate the construct pE2c-MC(/A)ERF72-HA. The MAERF72 fragment was inserted into the same restriction sites of pE6c (Addgene) containing a yellow fluorescent protein (YFP) tag to generate the construct pE6c-MAERF-YFP. In addition, the MC(/A)ERF72 fragment was inserted into pMDC32 using the Gateway LR II kit  to generate the 35S::MC(/A)ERF-HA and 35S::MAERF-YFP constructs. To generate a native promoter-driven plant expression vector, the 1443-bp DNA fragment upstream of the ATG codon of ERF72 was amplified and used to replace the 35S promoter of the 35S::MAERF construct to generate PERF72::MAERF. The full-length cDNAs of ARF6 and BZR1 lacking a stop codon were amplified by RT-PCR and inserted into the BamHI and NotI restriction sites of pE3c (Addgene), which harbours a triple MYC-tag, to generate the constructs pE3c-ARF6 and pE3c-BZR1, respectively.The full-length cDNAs of the wild-type (WT) ERF72 (BEE3 was amplified and inserted into the BamHI and AscI restriction sites of pGPTV to generate the PBEE3::GUS (β-glucuronidase) construct. In addition, the 2023-bp DNA fragment upstream of the ATG codon of XTH7 was amplified and inserted into the HindIII and AscI restriction sites of pGPTV to generate the PXTH7::GUS construct. The promoter fragment of ERF72 was cut from PERF72::MAERF and inserted into the HindIII and AscI restriction sites of pGPTV to generate the PERF72::GUS construct. For the 4×GCC-like box construct, DNA fragments containing the G1 or G2 box from the BEE3 promoter and G3 or G4 box from the XTH7 promoter were synthesised and inserted into the AscI and XbaI sites or the SalI and XbaI sites of pE1n, respectively. Using two pairs of isocaudomers, SpeI and XbaI in pE1-G1/G2 or SalI and XhoI in pE1-G3/G4, four copies of the GCC-like box fragments were made and inserted into the AscI and XbaI restriction sites of pGPTV to generate the P4×G1::GUS or P4×G2::GUS constructs, or into the HindIII and SalI restriction sites of pGPTV to generate the P4×G3::GUS or P4×G4::GUS constructs.For promoter activity assays, the 2553-bp DNA fragment upstream of the ATG codon of ARF6, ARF6N, and ARF6C were subcloned from pE3c-ARF6 and inserted into the BamHI and NotI restriction sites of pE1c to generate the pE1c-ARF6N and pE1c-ARF6C constructs. The ARF6N/ARF6C fragment was inserted into pDEST-GBKT7 using the Gateway LR II kit to generate the pGBKT7-ARF6N/ARF6C construct. The full-length cDNA of ERF72 was amplified by PCR and inserted into pGADT7 using EcoRI and BamHI restriction sites to generate pGADT7-ERF72.To produce constructs for yeast two-hybrid assays, truncated fragments of BZR1-MYC fragment of pE3c-BZR1 was inserted into p28a-DEST using the Gateway LR II kit to generate the pET28a-BZR1-MYC construct, and the ERF72 fragment from pE2c-MCERF72-HA was inserted into pHIS-6p-MBP using the BamHI and NotI restriction sites to generate pHIS-MBP-ERF.To construct vectors for the production of recombinant proteins, the ARF6 and BZR1 fragments were digested from pE3c-ARF6/BZR1 by BamHI and XhoI or BamHI and XbaI, and subcloned into 35S::NLuc digested with BamHI and XhoI or BamHI and XbaI to generate 35S::ARF6/BZR1-NLuc. The ERF72 fragment was inserted into the KpnI and SalI restriction sites of 35S::CLuc to generate the 35S::CLuc-ERF vector.To construct vectors for firefly luciferase (LUC) complementation imaging (LCI) assays ERF, 35S::MAERF-YFP, and PERF72::MAERF were separately introduced into Agrobacterium GV3101, and then transformed into WT Arabidopsis plants to generate the 35S::MCERF, 35S::MAERF, and 35S::MAERF-YFP transgenic lines, or into the erf mutant to generate the PERF72::MAERF transgenic line, using the floral dip transformation method . T3-generation homozygous transformants carrying a single insertion were used in subsequent experiments.The constructs n method . The trahttp://www.novogene.com/) with an Illumina HiSeq 2000 sequencer. The sequencing data were deposited in the NCBI’s Sequence Read Archive  under accession number SRP125848. Low-quality bases (Q<20) at the ends of the sequencing reads were trimmed using the SolexaQA software (www.arabidopsis.org) using the TopHat software  using an RNA Extraction Kit . A total of 3.0 µg of RNA was used to generate sequencing libraries using the NEBNext Ultra RNA Library Prep Kit following the manufacturer’s instructions , and index codes were added to attribute sequences to each sample. Solexa sequencing was performed as a commercial service at Novogene  were considered to indicate a significant difference of target gene expression. The primers used are listed in For qRT-PCR analysis, total RNA was isolated using an RNA Extraction Kit , and first-strand cDNA was synthesised from 3.0 µg of RNA using a reverse transcriptase . qRT-PCR was performed using TransStart Tip Green qPCR Super Mix following the manufacturer’s instructions (TransGen). Three biological replicates were performed per sample, and expression levels were normalised to that of pGADT7-ERF72 and the activation domain (AD) fusion plasmid pGBKT7-ARF6N/ARF6C were transformed into Saccharomyces cerevisiae AH109. Different combinations of AD and BD fusion plasmids were generated by mating. Yeast strains were grown on SD/–Trp–Ura–His dropout plates containing 1 mM 3-amino-1,2,4-triazole (3-AT) to confirm their interactions.The GAL4 DNA-binding domain (BD) fusion plasmid Escherichia coli BL21 (DE3) and induced by isopropyl β-D-1-thiogalactopyranoside (IPTG). Briefly, E. coli BL21 cells containing pET28a-BZR1-MYC and pHIS-MBP-ERF were induced for 8 h with 0.1 mM IPTG at 16 °C, and subjected to ultrasonic treatment in lysis buffer . After centrifugation, the supernatant was used as the crude protein extract.BZR1-MYC and MBP-ERF fusion proteins were expressed in For pull-down assays, crude protein extracts were added to binding buffer , followed by incubation at 4 °C for 1 h with gentle rotation. Amylose resin (20 μl) was added, followed by incubation for 1 h to precipitate MBP-containing proteins. The resin was washed five times in binding buffer.Seedlings were ground to powder in liquid nitrogen, and total proteins were extracted in buffer . The protein concentration was determined using a Bio-Rad Protein Assay Kit with bovine serum albumin as the standard. Following resolution by SDS-polyacrylamide gel electrophoresis, proteins were transferred to a polyvinylidene difluoride membrane  under 200 mA constant current for 45 min in transfer buffer . Anti-HA  and anti-MYC  antibodies were used to visualise protein bands.Agrobacterium cells containing constructs were suspended in infiltration medium  to an optical density at 600 nm (OD600) of 1.0, and every pair of constructs were mixed in equimolar ratios. Luciferase activity was assayed using a Lumazone FA1300 Imaging System .LCI assays were carried out as described previously (CNX5 (At5g55130), and the input DNA amount. Data are presented as means (SD) of three biological replicates. The primers used for qPCR are listed in Chromatin immunoprecipitation (ChIP)-qPCR assays were performed as described previously (5) were isolated from 4-week-old rosette leaves and transfected with 30 μg of DNA  and incubated overnight as described previously (Arabidopsis mesophyll protoplasts (2 × 10P<0.05).Statistical analyses were performed using the Data Processing System . One-wayhttps://www.ncbi.nlm.nih.gov/sra) under accession number SRP125848. Sequence data can be found in TAIR (https://www.arabidopsis.org/) under the following accession numbers: ERF72 (At3g16770), ARF6 (At1g30330), BZR1 (At1g75080), BEE3 (At1g73830), XTH7 (At4g37800), CNX5 (At5g55130), UBC30 (At5g56150), PP2A (At1g69960), EIN3 (At3g20770), and Actin2 (At3g18780).The RNA-seq data are deposited in the Sequence Read Archive at NCBI (ERF72 (35S::MCERF) and proteolysis-resistant ERF72  , HRE2 (ERF71), RELATED TO AP2.12 , RAP2.2 (ERF75), and RAP2.3 (ERF72) (::MAERF) , and founditions . We detepocotyls , D. Theserf, 35S::MCERF, and 35S::MAERF plants was significantly shorter under continuous red, far-red, and blue light conditions than under dark conditions, and the hypocotyl lengths of plants grown under white light were shortest compared with those grown under monochromatic light or dark conditions  value of each gene using a cut-off of a two-fold change and an adjusted P-value <0.05 between two samples, 849 DEGs were identified between 35S::MAERF  and WT plants (256 up-regulated and 593 down-regulated), 779 DEGs between OE and erf plants (216 up-regulated and 563 down-regulated), and 49 DEGs between erf and WT plants (17 up-regulated and 32 down-regulated). Using a Venn diagram to analyse the DEGs of OE versus WT, OE versus erf, and erf versus WT plants based on the RNA-seq data, we identified 674 ERF72-related DEGs, including 176 up-regulated (26%) and 498 down-regulated genes (74%)  .35S::MAERF seedlings led us to investigate the relationships between ERF72-related DEGs, light-regulated genes, ARF6-target genes, and BZR1-target genes. In our RNA-seq dataset, we found 2813 light-regulated genes, 2376 ARF6-target genes, and 3803 BZR1-target genes, among which 233 light-regulated genes, 84 ARF6-target genes, and 155 BZR1-target genes were ERF72-responsive DEGs   , indicat of ARF6 , B, whilin vitro , which de signal , E, suggBR-enhanced expression 3 (BEE3) and the BZR1-target gene xyloglucan endo/transglycosidase hydrolase 7 (XTH7), which are related to cell elongation  and XTH7 (G3 and G4) were predicted to bind ERF72 , and the XTH7 promoter contains one BRRE element and one G-box (PP2A), but this was markedly depressed by the co-expression of ARF6-MYC and ERF72-HA  and TGTCGG elements in the promoter sequences of target genes, and BZR1 binds to the BRRE (GGTGTG) and G-box (CACGTG) elements  locus , is reported to be a primary determinant of enhanced survival of completely submerged rice plants (SLENDER RICE1 (SLR1) and SLENDER RICE-LIKE1 (SLRL1) and concomitantly diminishing the expression of GA-inducible genes in submerged conditions in rice  family are involved in hypoxia-induced shoot elongation and photomorphogenesis in plants . Under d in rice . ArabidoERF71–75 . In our nditions . These r35S::MAERF, erf, and WT seedlings (Rumex palustris petioles (BEE3 and XTH7, which are target genes of ARF6 and BZR1, respectively. The results showed that ERF72 interacts with ARF6 and BZR1 (BEE3 promoter and directly antagonising the effect of BZR1 on transcription of XTH7. In addition, a previous study showed that DELLAs interact with and inhibit DNA binding by ERF72 (To determine the mechanism by which ERF72 regulates hypocotyl elongation in Arabidopsis seedlings, we performed RNA-seq of dark-grown eedlings . Light-rpetioles . Therefoand BZR1 , inhibitERF72 is a candidate target of EIN3 (ERF72 promoter to activate the transcription of ERF72 under dark conditions (ERF72 was markedly lower in ein2-5 mutant and ein3-1 eil1-1 double-mutant seedlings than in the WT under both dark and light conditions. These results demonstrated that ERF72 is a target gene of EIN3, and the transcription of ERF72 is regulated by the EIN2-EIN3/EIL1 pathway in Arabidopsis. Previous studies have shown that COP1 stabilises EIN3 levels by directly targeting EBF1 and EBF2 for ubiquitination under dark conditions (EBF1/EBF2 E3 ligases to attenuate ethylene-mediated responses (ERF72 and increased the abundance of ERF72 in Arabidopsis seedlings (ERF72, despite ERF72 being localised in the cytoplasm, while ARF6 and BZR1 in the nucleus regulate the expression of target genes. This results in expression of a large number of cell elongation-related genes to mediate skotomorphogenic growth. Following exposure of dark-grown seedlings to light, ERF72 is translocated to the nucleus by an unknown mechanism, and interacts with ARF6 and BZR1 to attenuate the transcriptional regulation of target genes of ARF6 and BZR1. As a result, hypocotyl growth is inhibited and seedlings undergo photomorphogenesis. In our study, overexpression of MAERF led to accumulation of ERF72 in nuclei in dark-grown transgenic seedlings, which limited regulation by ARF6 and BZR1 of the expression of cell elongation-related genes, resulting in photomorphogenic growth. Our results suggest that light, auxin, BR, and ethylene signalling through the revised BAP/DE module play harmonious roles in the regulation of hypocotyl elongation in Arabidopsis seedlings.nditions ; indeed,eedlings . These reedlings . In darkBEE3 and XTH7 was dramatically down-regulated in ein2-5 and ein3-1 eil1-1 seedlings compared to the WT under both dark and light conditions. Several putative EBS-like sites were predicted in the region upstream of the ATG site in the BEE3 and XTH7 promoters, which require further confirmation by a GUS activity assay (BEE3 and XTH7 are the potential target genes of EIN3. However, the expression of BEE3 and XTH7 were also regulated by different light conditions in ein2-5 and ein3-1 eil1-1 seedlings. In addition, we found that BEE3 and XTH7 are the target genes of ARF6 and BZR1, respectively. And ERF72, as one of the target genes of EIN3, interacts with ARF6 and BZR1 to separately regulate the transcriptional activity of ARF6 on BEE3 and that of BZR1 on XTH7. We also found that the expression of BEE3 and XTH7 was dramatically decreased in 2-DAG seedlings of 35S::MAERF plants compared with the WT and erf under dark conditions. These results suggested that the expression of BEE3 and XTH7 are fine-tuned by light and phytohormones via merging the EIN2-EIN3/EIL1 pathway and BAP/DE module during seedling photomorphogenesis in Arabidopsis.Interestingly, the expression of ty assay . These rJXB online.Supplementary data are available at Table S1. List of primers used in this study.Table S2. RNA-seq data and its alignment to the Arabidopsis reference genome.Table S3. List of differentially expressed genes.Table S4. Raw data for promoter activity analysis.ERF72 expression in the WT, erf mutant, 35S::MAERF, and 35S::MCERF transgenic lines.Fig. S1. erf, and transgenic plants under dark conditions.Fig. S2. Cotyledon development of WT, ARF6, BZR1, BEE3, and XTH7 detected in seedlings of WT, erf, and 35S::MAERF grown under dark conditions.Fig. S3. Expression of BEE3 and XTH7 promoters and the constructs used for GUS assays.Fig. S4. Locations of GCC-like boxes in the BEE3 and XTH7 promoters.Fig. S5. Locations of the putative EBS-like sites in the Supplementary MaterialClick here for additional data file.Supplementary Table S3Click here for additional data file.


Modules of interacting components arranged in specific network topologies have evolved to perform a diverse array of cellular functions. For a network with a constant topological structure, its function within a cell may still be tuned by changing the number of instances of a particular component  or by modulating the intrinsic biochemical properties of a component . How such perturbations affect cellular response dynamics remains poorly understood. Here, we explored these effects in a common decision-making motif, cross-antagonism with autoregulation, by synthetically constructing this network in yeast.We employed the engineering design strategy of reuse to build this topology with a single protein building block, TetR, creating necessary components through TetR mutations and fusion partners. We then studied the impact of several topology-preserving perturbations – strength of cross-antagonism, number of operator sites in a promoter, and gene dosage – on decision-making behavior. We found that reducing TetR repression strength, which hinders cross-antagonism, resulted in a loss of mutually exclusive cell responses. Unexpectedly, increasing the number of operator sites also impeded decision-making exclusivity, which may be a consequence of the averaging effect that arises when multiple transcriptional activators and repressors are accommodated at a given locus. Stochastic simulations of this topology revealed that, even for networks with high TetR repression strength and a low number of operator sites, increasing gene dosage can reduce exclusivity in response dynamics. We further demonstrated this result experimentally by quantifying gene copy numbers in selected yeast clones with differing phenotypic responses.Our study illustrates how parameters that do not change the topological structure of a decision-making network can nonetheless exert significant influence on its response dynamics. These findings should further inform the study of native motifs, including the effects of topology-preserving mutations, and the robust engineering of synthetic networks.The online version of this article (10.1186/s12859-019-2866-6) contains supplementary material, which is available to authorized users. Systems biology studies have identified numerous molecular networks that govern diverse cellular processes such as stem cell differentiation and the cell cycle . The arrSaccharomyces cerevisiae that share the same underlying network topology, but vary in their gene dosage, number of transcription factor binding sites, and/or repression strength.Starting with a biological system with a given topology, its behavior can be modified in two key ways: by adjusting the intrinsic properties of its components  or by modulating the quantities of its components . Understanding how such modifications yield qualitative differences in behavior can not only enable us to construct synthetic circuits with less iteration, but can also elucidate how such changes can lead to disease. Towards this goal, we constructed a series of synthetic circuits in Numerous studies utilizing systems modeling have proposed the cross-antagonism with autoregulation (CAA) network topology to drive decision-making behavior in various contexts –9. The CModeling studies of the CAA network have yielded several important predictions. First, the CAA network alone is sufficient to yield non-genetic multi-modality, with each cell randomly choosing one of multiple fates. Second, strong mutual repression is essential for exclusive expression of either transcription factor, and in turn, its expression program. Third, the distribution of cells among the three states can be modulated by adjusting the relative strengths of transcription activation and repression , 12. TheSaccharomyces cerevisiae composed of mutants and fusions of a single core protein. Our circuit offers the following advantages: the core protein building block, tetracycline repressor (TetR) [Using the engineering design strategy of reuse , which ar (TetR) , is not The response dynamics and decision-making exclusivity of this synthetic CAA network were then probed through a number of perturbations that do not alter the topology: modulating the strength of transcriptional repression, changing the number of operator sites, and altering gene dosage. A reduction in repression strength hindered the emergence of exclusive cell fates due to limited cross-antagonism. Increasing the number of operator sites also led to loss of exclusivity, likely due to the population averaging effects that arise when multiple activators and repressors can be simultaneously recruited to the same locus. As predicted by stochastic simulations and validated experimentally with individual CAA-containing clones, increasing the number of gene copies hinders exclusive decision-making. Our study reveals the significant roles that promoter architecture and gene dosage can play in modulating the dynamic behavior of a network without fundamentally changing its topological structure.TA and TB, each promoting its own synthesis and inhibiting the synthesis of the other. In our network, TA and TB are each represented with an activator-repressor pair, so the implemented network is composed of four proteins with four topological connections  and an additional four in the dimerization domain , as previously described . We will0 and TetR1, yielding transcriptional activators, tTA0 and tTA1, with different operator and dimerization specificities. To enable tracking of transcription factor levels via microscopy and flow cytometry, tTA0 was additionally fused to GFP and tTA1 to mCherry.The CAA circuit requires pairs of transcriptional activators and repressors. We fused the VP16 activation domain  separate0 and TetR1 can be used directly as the two repressors in the CAA circuit; in addition to these repressors, we constructed another set by fusing the strong SSN6 repression domain from yeast [0 and TetR1, yielding tTS0 and tTS1. We refer to repressors comprising TetR alone or TetR-SSN6 fusions as tTS, using weak or strong, respectively, to identify the specific protein.Since TetR by itself exerts transcriptional repression, TetRom yeast  to the C0-2x, tetO0-7x, tetO1-2x, and tetO1-7x.The canonical method for gene regulation by TetR involves placement of the tetO operator sequence, which consists of tandem repeats of a 19-bp sequence, upstream of the gene of interest. In the literature, both two (tetO-2x) and seven (tetO-7x) repeats of the base tetO sequence have been described . TetR is0, is regulated by a synthetic promoter containing a defined number of tetO0 operator sites. Basal transcription and subsequent translation leads to production of the tTA0 protein; in the absence of tetracycline, this protein can bind to the tetO0 sequences and hence promote its own synthesis in a positive feedback loop. Analogous inclusion of tetO1 operator sites in the promoter before the tTA1 gene creates a positive feedback loop for the other variant.Having defined a complete parts list based on the design strategy of reuse, we translated the CAA wiring map into a gene regulatory network Fig. e. The fu1 gene under control of a synthetic promoter containing tetO0 operator sites and, analogously, the tTS0 gene under control of a synthetic promoter containing tetO1 operator sites. This arrangement accomplishes two tasks. First, placement of the tTS genes downstream of operator-specific sequences couples their expression to the relevant activators: tTS1 is transcribed as part of the tTA0-mediated feedback loop and tTS0 is transcribed as part of the tTA1-mediated feedback loop. Second, a tTS0 dimer can bind to the tetO0-containing promoter and suppress activation exerted by the tTA0-mediated feedback loop, and the tTS1 protein dimer can bind to the tetO1-containing promoter and suppress activation exerted by the tTA1-mediated feedback loop. Taken together, the circuit is composed of two opposing sides, representing TA and TB in the minimal CAA model. TA consists of tTA0, tTS1, and tetO0, while TB consists of tTA1, tTS0, and tetO1 , we placed a minimal CYC1 promoter (containing a TATA box) at the 3′ end. Next, we added the tTA gene to the 3′ end of the CYC1 promoter, and a CYC1 terminator at the 3′ end of the tTA gene. We then placed another copy of the CYC1 promoter at the 5′ end of the tetO operator site(s). Next, we added the tTS gene to the 5′ end of this second CYC1 promoter. Finally, another copy of the CYC1 terminator was added to the 5′ end of the tTS gene.0 and tTS1 on one plasmid, and tTA1 and tTS0 on another (details described in Methods). Simultaneous transformation of both plasmids into yeast cells yields colonies on selective medium. Cells within each colony are genotypically identical; however, the genotype of two colonies resulting from the same transformation reaction can be different, because each of the two plasmids can integrate in one or more copies. This difference in gene dosage can potentially yield a difference in the dynamic behavior or phenotype of the circuit.Circuit genes were cloned into separate, chromosomally integrating plasmids with tTAAfter obtaining transformant clones for the different variants of the synthetic CAA circuit Fig. , top rowAnalysis of expression revealed that for approximately the first 4 h after the removal of doxycycline, there is no significant expression of GFP or mCherry over background. Subsequently, fluorescence continues to rise in most clones, becoming very strong by the 16-h timepoint. Density plots of GFP and mCherry from flow cytometry data at the 16-h timepoint reveal two important points -space and the relative proportions of cells committing to the different states [TA, low TB) and  are eliminated, rendering the overall system monostable [Our previous simulations and analysis of the CAA network topology indicate that the strength of repression exerted by t states , 21. Furnostable , 21.We evaluated these predictions experimentally by comparing two variants of our synthetic circuits: one with weak repression activity conferred by occlusion of the promoter via binding of TetR and another with strong repression achieved by the SSN6 domain. Unlike TetR alone, TetR fused to SSN6 can potentially exert multiple types of repressive activity at the promoter, by interfering with the mediator complex to halt transcription by RNA polymerase II and by recruiting histone de-acetylation machinery to inactivate the promoter . Both ciComparison of GFP and mCherry expression profiles reveals the following. First, none of the clones of the weak-repression circuit examined exhibit both the  and the  exclusive states  and  states representing committed, mature cell lineages [TA, TB) state should be closer to the origin than to the  point on the phase plot [In the context of stem-cell lineage commitment, the CAA topology models the behavior of a bipotent progenitor, with the ; ; ; and . If each population is either present or absent, then 16 potential response profiles (or phase portraits) are possible. The actual number is significantly higher given that the population centroids and the distribution of cells across the four populations can also both vary  can yield highly similar response profiles, or phenotypes, suggesting that the basic CAA topology yields a limited number of response profile archetypes. To explore this further, we applied a clustering method to all response profiles.n × n grid, and a distance metric was computed for each pair of response profiles (see Methods). The distances were used as input into the partitioning around medoids (PAM) algorithm, which partitions data points into groups through iterative optimization [n, the number of bins for each of the two dimensions, and k, the number of clusters, were obtained empirically by varying both parameters, and analyzing silhouette scores of the resulting clusterings.Briefly, each clonal response profile was binned into an mization , to obtaCluster analysis  population  can be further extended by leveraging more sophisticated programming of eukaryotic transcription factor function . AdditioIn this study, we used a synthetic biology approach to explore the plasticity of the response of a common decision-making topology, the CAA. We employed the engineering principle of reuse to construct this topology from a single core protein part, TetR, which was tuned through mutation to achieve two orthogonal specificities and through fusion partners to create the desired activating and repressive activities. We found that our synthetic CAA circuit is robust in yielding discrete population states, though the relative distribution of cells across these states can vary as a function of applied perturbations. We specifically examined perturbations to the CAA network that do not change its topological structure but that have the potential to influence its dynamic behavior, focusing on the strength of transcriptional repression, the number of operator sites, and gene dosage.When the strength of transcriptional repression is attenuated, the negative coupling between the two transcriptional nodes is reduced, allowing both transcription factor abundances to rise and leading to a loss of transcriptional exclusivity. When the number of operator sites is increased in the CAA network, we unexpectedly found that exclusivity in decision-making was also hindered, due in part to the fact that both activating and repressive proteins act on the promoters, leading to an averaging effect that prevents either transcription factor from attaining a significantly greater concentration than its counterpart. Finally, we found both computationally and experimentally that gene dosage plays a critical role in balancing the abundance of network components, which in turn dictates whether the CAA topology can engender exclusive cell states. Our results demonstrate that perturbations that preserve the topology of a gene regulatory network can nonetheless significantly modulate response dynamics of the network.0 in the text.Transcriptional activator genes were constructed as follows .0 and tTA1 activator genes (together with the respective GFP or mCherry fusion) were cloned in via the BamHI and NotI sites, while the repressor genes, tTS0 and tTS1, were cloned in via the AflII and XhoI sites. Different tetO operator sequences were either purchased or constructed via PCR. These sequences were cloned into the plasmids via AvrII and ClaI cloning.The tTAThe base plasmid for the circuit series was constructed as follows. Plasmid pNAS001.1 was digested with AvrII and ClaI, and the tetO-2x sequence was ligated into it to construct plasmid pNAS004.1. Similarly, the tetO-4C5G-2x sequence was ligated into the pNAS001.1 plasmid (digested with AvrII and ClaI). Primers NASo099 and NASo100 were used to amplify the kanamycin resistance gene (KanR) from the pUG6-tTA plasmid, and this was ligated into the two plasmids. This yields two constructs with KanR driven by tetO-2x and tetO-4C5G-2x, respectively.Primers NASo112 and NASo113 were used to amplify the KanR cassette from the plasmid containing the tetO-2x sequence, and the resulting product was cloned into plasmid eco007  via XmaI0 and tTA1 are present in sufficient quantities. Hence, addition of G418 to the culture medium will inhibit growth of cells not expressing significant levels of both tTA proteins. This mechanism facilitates additional perturbations.The pNAS135 plasmid consists of two copies of the KanR gene, driven by the tetO-2x and tetO-4C5G-2x operators. In the context of the circuit, the KanR protein is expressed when either or both of tTAReagents for cloning were obtained from the following sources: restriction enzymes from New England Biolabs, Phusion polymerase from Finnzymes, and custom oligonucleotides from Integrated DNA Technologies.The NASy001 strain was constructed by transforming BMA64-1A  yeast ceAfter obtaining transformants for the different variations of the CAA circuit, we performed a global survey of behavior. For each circuit variant, several individual clones were separately inoculated into selective liquid medium, supplemented with 5 μg/mL doxycycline. In the presence of high levels of doxycycline, the TetR proteins cannot bind to DNA, and hence their activation or repression activity is abrogated, resulting in complete inhibition of the circuit. After overnight growth in liquid medium, the cultures were diluted into fresh medium containing doxycycline, and incubated for another 6–8 h to enable cells to leave the lag phase. Subsequently, the cultures were centrifuged, washed twice with PBS, and resuspended in fresh medium lacking doxycycline to allow expression of the circuit. Since the activator for Set 0 is fused to GFP, and the activator for Set 1 is fused to mCherry, the levels of the transcription factors can be tracked by assaying for GFP and mCherry expression.n × n grid, with n bins each for GFP and mCherry. For plotting all figures, n = 100 was used while for clustering of response profiles, n = 10 was used.GFP and mCherry expression was assessed by flow cytometry using a BD LSRFortessa instrument (BD Biosciences) equipped with 488-nm and 561-nm lasers for excitation and 530/30 and 610/20 emission filters, respectively. Data files from the instrument were imported into the FlowJo software, and the FSC-H, FSC-W, FSC-A, and SSC-A parameters were used to exclude events not corresponding to individual yeast cells. After gating, custom R programs were used to pool flow cytometry data and trim outlier events. Subsequently, each response profile was binned into an For cluster analysis of flow cytometry data, a distance metric was computed between each pair of binned response profiles. Each binned response profile was treated as a vector, and the Manhattan distance metric  was usedFor selected clones, the numbers of integrated copies of the two plasmids were estimated using digital PCR on an OpenArray Real-Time PCR System (Life Technologies). Briefly, clones were inoculated and grown in selective medium containing high levels of doxycyline to suppress circuit expression. Saturated cultures were then processed to extract purified genomic DNA. The genomic DNA was digested overnight at 37 °C with SacI-HF (New England Biolabs). The digested genomic DNA was then appropriately diluted and used as template in separate digital PCR reactions along with TaqMan probes (Life Technologies) targeting the GFP, mCherry, or ALG9 genes. For quantifying the number of integrated copies, both GFP and mCherry are considered proxies of their respective plasmids, with the native yeast gene ALG9 being an endogenous control.GFP and mCherry expression dynamics of individual cells were monitored using a protocol modified from the literature . Cells fA mathematical model of the CAA circuit was constructed similarly to our previous models , 21, butAdditional file 1:Supporting figures, table, video legends, and model details. (PDF 2765 kb)Additional file 2:Video of strong inhibition in the CAA circuit. (AVI 51461 kb)Additional file 3:Video of weak inhibition in the CAA circuit. (AVI 51461 kb)


TP63 was identified and validated to be a direct target of TRPS1-CHD4/NuRD(MTA2) complex, which represses TP63 expression by involving decommission of TP63 enhancer in the described precision-guided manner, leading to a reduction of the ΔNp63 level and contributing to migration and invasion of cancer cells.Transcriptional repressor GATA binding 1 (TRPS1), an atypical GATA transcription factor, functions as a transcriptional repressor and is also implicated in human cancers. However, the underlying mechanism of TRPS1 contributing to malignancy remains obscure. In the current study, we report that TRPS1 recognizes both gene proximal and distal transcription start site (TSS) sequences to repress gene expression. Co-IP mass spectrometry and biochemical studies showed that TRPS1 binds to CHD4/NuRD(MTA2). Genome-wide and molecular studies revealed that CHD4/NuRD(MTA2) is required for TRPS1 transcriptional repression. Mechanically, TRPS1 and CHD4/NuRD(MTA2) form precision-guided transcriptional repression machinery in which TRPS1 guides the machinery to specific target sites by recognizing GATA elements, and CHD4/NuRD(MTA2) represses the transcription of target genes. Furthermore,  How TRPS1 functions as a transcriptional repressor is largely unknown.Transcriptional repressor GATA binding 1 (TRPS1), an atypical member of the family of GATA transcriptional factors, has been characterized as the first example of a GATA protein with intrinsic transcriptional repression activity for >15 years2. TRPS1 was also implicated in cancer as its elevated expression was observed in various human malignancies, including osteosarcoma3, colon cancer4, and breast cancer5. By using in vivo transposon-based forward genetic screening aimed at screening breast cancer-driver genes, we6 and others7 recently identified TRPS1 as a driver gene in breast cancer indicating its role in breast cancer pathogenesis. However, how TRPS1 contributes to breast cancer is still obscure.Mutations in TRPS1 were documented to be an underlying cause of Tricho-rhino-phalangeal syndrome type I, an autosomal-dominant disorder characterized by craniofacial and skeletal malformations8. The CHD3-CHD4 subfamily, which lacks a DNA-binding domain, includes CHD3  and CHD4 , which are the central components of the nucleosome-remodeling and histone deacetylase  complex9, which mainly functions in transcriptional repression10. CHD4 is an essential subunit for the transcriptional repressive function of NuRD complex, and multiple domains of CHD4 are required for transcriptional repression by NuRD complexes11.CHD (chromodomain helicase DNA-binding protein) proteins are important regulators of transcription and can be divided into three subfamilies: CHD1-CHD2, CHD3-CHD4, and CHD5-CHD912, which is commonly mutated in human cancers and is well documented as an important tumor-suppressor gene13. Unlike p53, owing to the complexity of the TP63 gene, the role of p63 in cancer is still controversial and an area of intense research. TP63 encodes multiple p63 isoforms14 that can be placed in two categories: TAp63 and ΔNp63, which are with and without an N-terminal transactivation domain, respectively. Experimental evidence suggests that TAp63 acts as a tumor suppressor, whereas ΔNp63 has oncogenic functions16. ΔNp63 has been suggested to be an important driver for promoting breast tumor progression and metastasis by transcriptional activation of MTSS117 or PI3K/CD44v6 axis18. However, transcriptional regulation of TP63 in breast cancer is still not fully understood.p63 is a member of the p53 familyTP63 gene was repressed by this precision-guided machinery of TRPS1-CHD4/NuRD(MTA2) complex, which decommissions its enhancer leading to a decrease in ΔNp63 and enhancing the metastatic ability of breast cancer cells.In this study, we addressed how TRPS1 functions as a transcriptional repressor and contributes to breast cancer pathogenesis. Our results illustrated that TRPS1 repressed gene expression by forming a transcriptional repression complex, TRPS1-CHD4/NuRD(MTA2), and directed the complex to transcriptional regulatory regions in a precision-guided manner. We further identified that the ABCA12 gene, TSS proximal region of SETD7 gene, and both TSS proximal and distal regions of NAALADL2 gene  analysis in T47D cells with antibodies against TRPS1 Fig. .To furthene Fig. . The chrsis Fig. .Fig. 1GeTRPS1. Consistent with the current notion that TRPS1 functions as a transcriptional repressor, ABCA12, NLGN1, NHLRC1, SETD7, RNF43, NAALADL2, and NTN4 genes, with TRPS1 enrichment at their regulatory regions according to the ChIP-seq and ChIP-qPCR analysis, showed upregulated transcription upon silencing TRPS1. This was evident by the >2-fold change (p < 0.05) observed in RNA-seq data and confirmed by reverse transcription qPCR , respectively . We hypothesized that TRPS1 might recruit other regulatory factors to form a functional machinery to repress gene expression. Upon re-analysis of the TRPS1 interactome reported by our group previously, we found that CHD3/4, HDAC1/2, MTA2, GATA2A/B, and RBBP4/7, which are core components of the NuRD complex19, were included in the TRPS1 interactome list20 , and analyzed the transcription output mediated by this dysfunctional complex by RNA-seq and compared it with that without silencing CHD4. The correlation analysis between TRPS1- and CHD4-mediated transcription output exhibits a high R-value , suggesting that TRPS1 and CHD4/NuRD(MTA2) were functionally linked in determining the transcriptional outputs in our investigating system  was required as an essential and functional component of the TRPS1 transcriptional repression complex. We first silenced  was requtem Fig. . ConsistABCA12, NLGN1, NHLRC1, SETD7, RNF43, NAALADL2, and NTN4 together with TRPS1 enrichment  and those lacking the transactivation domain (ΔNp63)21. From RNA-seq data, we found that only expression of isoforms coding ΔNp63 was detectable and showed upregulation upon silencing TRPS1 or CHD4  complex. For this purpose, HD4 Fig. . TP63 enHD4 Fig. . By usinles Fig. . These r22. Via retrieving and analyzing H3K27ac ChIP-seq data for T47D (GSM1693025), we found that the additional region at upstream of P1 but not P1 and P2 shows enrichment of H3K27ac, suggesting that the additional region at upstream of P1 is an enhancer and TRPS1 was likely to repress TP63 expression by targeting both enhancer and P2 promoter of TP63  machinery repressed ΔNp63 expression by directly targeting its enhancer, we performed ChIP-qPCR and detected ~7-fold enrichment of TRPS1 and ~5-fold enrichment of CHD4 at the TP63 enhancer. These observations indicated that the TRPS1-CHD4/NuRD(MTA2) machinery directly targeted TP63 enhancer  complex, we carried out enhancer trap analysis via cloning TP63 enhancer sequence in pGL3-basic coupled with minimal cytomegalovirus (CMV) promoter driving the luciferase gene followed by luciferase reporter assay. The results showed that the luciferase activity of TP63 enhancer was significantly attenuated upon overexpression of TRPS1. On the other hand, TPRS1 was unable to attenuate luciferase activity when TP63 enhancer was mutated from GATA to GATC in the central GATA-binding sequence  complex and reduced transcription of TP63 enhancer causing a significant decrease in luciferase activity comparable to that of full-length TRPS1, indicating that C-terminal region of TRPS1 is a repression domain  in a precision-guided manner contributes to repression of ΔNp63 expression. It is worthy to further investigate how enhancer, P1, and P2 cooperate to mediate the transcription output of TP63 by TRPS1.To further confirm that nce Fig. . These r4/NuRDMTA complex,in Figs. . Furtherin Figs. . Our cur23  and between CHD4 and TP63   Fig. . Also, bval Fig. . Taken tTP63 enhancer leading to reduced metastatic ability of breast cancer cells and better survival of breast cancer patients. An oncogenic role was ascribed to CHD4 for initiating and supporting tumor-suppressor gene silencing in human colorectal cancer26. CHD4 constitutes an essential component of the NuRD complex, which interacts with sequence-specific transcriptional repressors and functions as a multi-protein transcriptional co-repressor27. One of the typical members of the GATA family, GATA3, was reported to interact with G9A/NuRD(MTA3) to suppress breast cancer metastasis through targeting the promoters of an array of genes involved in important cellular signaling pathways regulating cell migration and invasion28. In our current study, we demonstrated that the atypical GATA member, TRPS1, interacted with CHD4/NuRD(MTA2) to form a transcriptional repressive, precision-guided machinery and targeted both proximal and distal TSS regions of target genes extending the current notion of GATA/NuRD transcriptional repressive function. GATA3 was reported to recruit MTA3 and not MTA2 in MCF7 cells28. We showed here that TRPS1 recruited MTA2 in MCF7 cells, indicating differential usage of MTA species specific to different members from the same gene family depending upon the cellular context. In this respect, both GATA3 and TRPS1 were able to regulate multiple genes in the EMT pathway28, although the underlying mechanisms are currently not known. Nevertheless, our identification of TRPS1-CHD4/NuRD(MTA2) complex-regulated genes, which are enriched in cell adhesion and cell migration pathways, provides additional support and mechanistic insight into breast cancer metastasis.Herein, we have provided evidence that TRPS1 functions as a transcriptional repressor by recruiting CHD4/NuRD(MTA2) to suppress the expression of target genes. Through physical interaction, TRPS1 and CHD4/NuRD(MTA2) act in an interdependent fashion to execute transcription repression in a precision-guided manner. For example, the expression of ΔNp63 was suppressed by TRPS1-CHD4/NuRD(MTA2), which decommissioned TP63, is a p53 family member involved in a diverse range of biological processes, including embryonic development, cell migration, cell proliferation, differentiation, survival, and apoptosis34. The role of TP63 in oncogenesis is controversial due to the complexity of the TP63 gene, which encodes multiple p63 isoforms14, including TAp63 with tumor-suppressive function and ΔNp63 that has an oncogenic role16. TAp63 and ΔNp63 are the products of two alternative promoters, P1 and P2, respectively, and have pleiotropic functions. Our observation that the TRPS1-CHD4/NuRD(MTA2) complex transcriptionally represses TP63 via involving decommission of TP63 enhancer and leading to a reduction of ΔNp63 provided additional mechanistic insight into the transcriptional regulation of TP63. Thus the TPRS1-CHD4/NuRD(MTA2) complex is upstream of ΔNp63, which is the main isoform in breast cancer.The p63 protein, encoded by TP63 enhancer and repressing ΔNp63 expression. Our data provide mechanistic insights into how TRPS1 functions as a transcription repressor elucidating a new molecular mechanism underlying the transcription regulation of TP63 and providing a link between TRPS1 and migration and invasion of breast cancer cells. Our results help in understanding the complexity of the functions of GATA family members and support the pursuit of TRPS1, NuRD, and ΔNp63 as the potential prognostic indicators and/or therapeutic targets of breast cancer.In summary, our findings revealed that TRPS1 recruits CHD4/NuRD(MTA2) complex forming precision-guided machinery for the transcriptional repression of specific genes. We have shown that TRPS1 reduced the metastatic ability of breast cancer cells by involving decommission of 293T cells were cultured in Dulbecco’s modified Eagle’s medium (Life Technologies) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin–streptomycin solution (Life Technologies). MDA-MB-231 cells were maintained in L-15 media with 10% FBS and 1% penicillin–streptomycin solution (Life Technologies). T47D and MCF7 cells were cultured in Roswell Park Memorial Institute medium-1640 (RPMI-1640) (Life Technologies) supplemented with 10% FBS and 1% penicillin–streptomycin solution (Life Technologies).TRPS1, CHD4, or TP63 (coding ΔNp63) and control siRNA (GenePharma) were transfected into cells using Lipofectamine RNAiMAX reagent (Invitrogen). siRNA sequences are listed in Supplementary Table Small interfering RNAs (siRNAs) against Total RNA was extracted using the RNeasy Kit (Qiagen) and reverse transcription of RNA was performed using the PrimeScript RT Reagent Kit (Takara) according to the manufacturers’ instructions. Real-time PCR reactions were performed with SYBR Premix Ex Taq (Takara) in the Bio-Rad CFX96 Real-Time PCR System (Bio-rad). Endogenous β-actin was used for normalization. The primers sequences for real-time RT-PCR are listed in Supplementary Table Endogenous Co-IP was performed using anti-TRPS1 antibody (R&D systems), control polyclonal immunoglobulin G , and Dynabeads Protein G  according to the manufacturers’ instructions. For exogenous Co-IP, we transfected flag-TRPS1 plasmid into 293T cells with PEI. Cells were lysed after 48 h and incubated with flag agarose. Subsequently, western blot analysis of NURD, CHD4, MTA2, HDAC1, HDAC2, and RBBP4/7 was performed.E. coli DE3 strain. Protein purification was performed according to 6×His-tagged protein purification protocol using Ni-beads following the manufacturer’s protocol (Qiagen).Series of TRPS1 truncates were cloned into pET.MBP.3C for generating recombinant proteins. Only TRPS1-∆N (residues 881–1294) could be overexpressed as soluble recombinant protein in Cells were treated with formaldehyde to create protein–DNA crosslinks, and the crosslinked chromatin was extracted and sheared by sonication. Protein G beads were precleared and blocked with 1% bovine serum albumin. Sheared chromatin was used for immunoprecipitation with normal IgG, TRPS1, or CHD4 antibodies. The immuno-precipitates were washed, eluted, and de-crosslinked. After proteins and RNA were degraded by treatment with proteinase K and RNase A, DNA was purified, followed by quantification PCR. Primer sequences used for ChIP-qPCR experiments are listed in Supplementary Table CHD4 and his-tag antibodies were acquired from Abcam. The TRPS1 antibody was purchased from R&D Systems. β-Actin antibody and anti-mouse secondary antibody were purchased from Proteintech. The ΔNp63 antibody was bought from Abways Technology. Anti-rabbit secondary antibody and anti-goat secondary antibody were purchased from Santa Cruz Biotechnology.For western blotting, protein lysates were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred to a polyvinylidene difluoride membrane, and immunoblotted with antibodies. Blots were developed with enhanced chemiluminescence western blotting reagent (Pierce/Thermo Scientific).TP63-minimal CMV-Luc, a 1.6-kb fragment of human TP63 enhancer coupled with minimal CMV promoter was cloned into the pGL3-Basic plasmid (NheI and HindIII sites) upstream of the firefly luciferase gene (Promega). For mutant human TP63-minimal CMV-Luc, conserve sequence WGATAR of human TP63 enhancer was mutated into WGATCR using the QuikChange II XL Site-Directed Mutagenesis Kit (Agilent Technologies); the corresponding wild-type plasmid was used for mutating A to C following the manufacturer’s procedures.For human TP63-minimal CMV-Luc, mutant TP63-minimal CMV-Luc, flag-TRPS1, or truncated TRPS1 plasmids containing Renilla luciferase (pRL-SV40). The pRL-SV40 plasmid served as an internal control for normalizing the transfection efficiency. Firefly and Renilla luciferase activities were measured 48 h after transfection with the Dual-Luciferase System (Promega) using a CentroLB960 96-well luminometer (Berthold Technologies).For the luciferase reporter assay, 293T cells were transfected with 5) in 0.5% serum-containing RPMI-1640 were plated in the upper chamber and 600 μl RPMI-1640+10% FBS in the lower chamber as a chemoattractant. For the invasion assay, an 8-μm pore size BD Matrigel Invasion Chamber was used. After 72 h for migration assay and 144 h for invasion assay, cells on the upper side of the filter were removed and cells that remained adherent to the underside of membranes were fixed in formaldehyde, followed by staining with crystal violet. The number of migrated cells was counted using a microscope. Three contiguous fields of each sample were examined using a 20× objective to obtain representative images of cells that migrated/invaded across the membrane.For in vitro migration assay, an 8-μm pore size Boyden chamber  was used. Cells . Total RNA was depleted of rRNA using Ribozero (Illumina), followed by library preparation and next-generation sequencing. The Gene Expression Omnibus (GEO) accession number for the ChIP-seq and expression data reported in this paper is GSE114213.36. Second, DNA-binding motifs over-represented in these peak regions were found using cisFinder, a method by clustering position frequency matrices37. All motifs with a false discovery rate <0.05 were defined as TRPS1-binding motifs. After that, the motifs were multiply aligned with clustal Omega, and the aligned motifs were used for calculating the entropy for each position of the certain nucleotide with the method of WebLogo38. Finally, the multiplty aligned sequences of nucleotides were filtered with a sliding-window of 10 bp and the entropy value of 2.5. It means that only 10bp continuous nucleotides which has entropy values larger than 2.5 will be kept for logo presentation. For RNA-seq analysis, the reads were aligned with STAR 1.5.2, and the aligned reads were next used to quantify the expression level of the genes with HTSeq 0.9.0. The genes with >2 count per million corresponding to a count of 6–7 reads in sample’s expression were used for the differential expression analysis. A trimmed mean of M-values between each pair of samples was performed for normalization. Then the differentially expressed genes were called and used for enrichment analysis and visualization.Both the ChIP-seq and RNA-seq data were first trimmed of sequencing adaptors and low sequencing quality end, and the reads passing the quality control were then used for sequence alignment and subsequent analysis. For ChIP-Seq analysis, the reads were aligned to the human reference genome with BWA 0.7.12-r1039. The peaks of ChIP-seq experiment were called from the aligned reads with MACS2 2.1.1.20160309, and the peaks were then annotated for their positions according to the gene structure. The sequences of the peaks were extracted as well for further motif analysis using a python script programmed by our group. The genes with the shortest distance to the peaks were used for enrichment analysis and visualization. To determine TRPS1 motifs, first, the coordinates of the peaks of the TRPS1-binding sites from the ChIP-seq analysis were called with MACS2Supplementary LegendsFigure S1Figure S2Supplementary Table 1Supplementary Table 2Supplementary Table 3Supplementary Table 4Reporting checklist from original submission


P. aeruginosa, the sRNAs involved in quorum sensing (QS) regulation and their function are still largely unknown. Here, we explored how the prrH locus sRNA influences P. aeruginosa virulence in the context of the QS regulatory network. First, gain- and loss-of-function studies showed that PrrH affects pyocyanin, elastase and rhamnolipid production; biofilm formation; and swimming and swarming motility and impaired the viability of P. aeruginosa in human whole blood. Next, our investigation disclosed that LasI and PhzC/D were directly repressed by PrrH. In addition, RhlI, the key member of the rhl QS system, diminished the expression of PrrH and enhanced the expression of downstream genes. Bioinformatics analysis found two binding sites of RhlR, the transcription factor of the rhl system, on the promoter region of prrH. Further β-galactosidase reporter and qPCR assays confirmed that PrrH was transcriptionally repressed by RhlR. Collectively, our data identified a novel RhlI/R-PrrH-LasI/PhzC/PhzD regulatory circuitry that may contribute to P. aeruginosa pathogenesis. Our findings indicate that PrrH is a quorum regulatory RNA (Qrr) in P. aeruginosa and provide new insight into PrrH’s function.Small regulatory RNAs (sRNAs) act as key regulators in many bacterial signalling cascades. However, in  Pseudomonas aeruginosa (P. aeruginosa) is the cause of a variety of human infections, including acute infections in patients who are injured or severely burned and chronic lung infections in individuals with cystic fibrosis [P. aeruginosa pathogenicity is due to mainly a large amount of cell-associated and extracellular virulence factors, many of which are regulated by two acyl-homoserine lactone (AHL) quorum sensing (QS) systems, LasI-LasR (las system) and RhlI-RhlR (rhl system) [las system, the lasI gene product directs the formation of the diffusible extracellular signal N-(3-oxododecanoyl)-L-HSL (3-oxo-C12-HSL), which interacts with LasR to activate a number of virulence factors, including the LasA and LasB elastases, exotoxin A, and alkaline protease. In an analogous manner, the rhlI and rhlR genes encode for an N-butanoyl-L-homoserine lactone (C4-HSL) synthase and receptor, respectively. The downstream virulence genes of the rhl system include those encoding pyocyanin, rhamnolipids and the type III secretion system [P. aeruginosa strains, las and rhl systems are hierarchically connected, and both rhlR and rhlI are positively regulated by the las system [rhl QS system [Pseudomonas quinolone signal (PQS) system, which is regulated by mainly the pqs operon [The opportunistic pathogen fibrosis . P. aeru system) . In the lactone C-HSL synts system . However 3-oxo-C1-HSL, whiS system . In addis operon .P. aeruginosa, ReaL is negatively regulated by the las system and enhances the synthesis of PQS by targeting PqsC [las and rhl system, is limited. An extensive investigation of quorum regulatory RNAs (Qrrs) [P. aeruginosa virulence.Small regulatory RNAs (sRNAs) are central regulators of gene expression in bacteria and post-transcriptionally control target genes by limited base pairing with their mRNAs, thus negatively or positively affecting the transcript stability and/or the translation rate ,9. In reing PqsC . In addiing PqsC . Howevers (Qrrs)  will helprrF locus. Transcription of PrrH initiates at the 5’ end of prrF1, proceeds through the prrF1 terminator and prrF1-prrF2 intergenic sequence, and terminates at the 3’ end of the prrF2 gene. The widely known function of this sRNA family is its participation in iron homeostasis, homologous to the RyhB RNAs encoded by Escherichia coli, Shigella flexneri, Shigella dysenteriae, and Vibrio cholerae [P. aeruginosa. Further evidence demonstrated that the LasI and phzA-G operons were direct targets of PrrH. More importantly, we also disclosed that the virulence inhibition function of PrrH was under the control of the rhl system. Our findings highlight the importance of PrrH in P. aeruginosa pathogenesis and implicate PrrH as a potential therapeutic target for P. aeruginosa.PrrH is characterized as a haem-responsive sRNA encoded by the cholerae ,20. In tP. aeruginosa virulence and bloodstream infection ability in vitro.PrrH influences prrH gene-deficient and overexpression strains in PAO1 , as well as a prrH-overexpression strain in the ΔprrH mutation background (ΔprrH/PrrH). The expression levels of the PrrH in all these strains were confirmed by RT-qPCR . Compared to the wild-type strain, the strain with overexpression of prrH had slightly repressed growth, and deficiency in prrH barely affected growth . However, it was notably that overexpression of prrH inhibited the production of pyocyanin , pyocyanin synthesis was decreased in a dose-dependent manner  medium and whole blood, we reduced the application number in whole blood to 10% and extended the incubation time. The result showed that the expression of prrH was enhanced at 4 h and faded at 8 h , the mid-exponential phase (t = 4 h) and the early stationary phase (t = 6 h) in a corresponding culture model . As shown in lasI, as well as treatment with 3-oxo-C12-HSL barely affected PrrH expression AG-3’ or 5’-CT(N12)GC-3’ in the promoter region may be potential targets of RhlR. Based on this model, within the −100 bp region upstream of PrrH, two RhlR consensus binding sites were found , the β-galactosidase activity of pQF50-PprrH was greatly elevated compared to that of the control, while overexpression of RhlR impaired this activity (rhl system.Since the gene expression-regulated function of RhlI is mediated by the transcription factor (TF) RhlR, we further used the bioinformatics tool PRODORIC, a comprehensive database for gene regulation and expression in prokaryotes, to analyse the DNA motif recognized by RhlR. It seems that genes, such as re found D. Then, activity E. Moreovactivity F. These P. aeruginosa QS circuit and the function of PrrH.Taken together, our results elucidate a novel RhlI/R-PrrH-LasI/PhzC/PhzD signalling cascade and further identify the importance of PrrH in inhibiting pyocyanin synthesis and virulence , which sP. aeruginosa. Our results elucidate the new regulation mechanism and function of PrrH.In this study, we disclose a novel QS/PrrH-PhzC/PhzD regulatory circuitry, that is, RhlI/R represses the expression of PrrH, whereas the expression of PrrH reduces the levels of LasI, RhlI and PhzC/PhzD, thereby inhibits QS signalling and abrogates QS-promoted virulence in prrF locus sRNAs in P. aeruginosa is the tandem arrangement of the prrF1 and prrF2 genes, allowing for expression of a third sRNA, PrrH [prrF locus sRNAs have focused on the role of PrrF in iron homeostasis or PQS regulation [prrF1-prrF2 intergenic sequence (PrrHIG) [prrH resulted in a change in virulence and bloodstream infection ability. However, our genetic manipulation not only changed the PrrH level but also caused gain or loss of PrrF expression. In addition, the recognition site of PrrH on LasI, PhzC and PhzD was not in PrrHIG but shared with PrrF. Thus, the assessed function of PrrH in our work relies on that of the prrH locus sRNAs and not on PrrH only.One of the most fascinating aspects of the NA, PrrH . Most regulation ,19,27,28(PrrHIG) . In thisP. aeruginosa PAO1, pyocyanin is synthesized from chorismate in a complex series of intermediates by enzymes encoded by the homologous phzA1B1C1D1E1F1G1 and phzA2B2C2D2E2F2G2 operons. The two phz operons are 98.3% identical at the DNA level [In NA level ,29. As aVibrio harveyi and Vibrio cholera, LuxO activates the expression of the Qrr sRNAs, which in turn repress the expression of the QS master regulators LuxR and LuxO [P. aeruginosa is a model for studies of QS. However, the homologous Qrr sRNAs in P. aeruginosa have not yet been characterized. Here, we showed that RhlI/R directly repressed PrrH and promoted PhzC/D expression, while PhzC/D was negatively regulated by PrrH. This finding suggests that RhlI/R, PrrH and PhzC/D combine in a feed-forward loop to regulate pyocyanin production. On the other hand, PrrH also repressed RhlI/R expression  through targeting LasI, forming a negative-negative feedback loop to fine-tune QS. Our data suggest that prrH locus sRNAs may be the Qrr sRNAs of P. aeruginosa.It has been shown that the transcription of quite a few sRNAs is regulated by TFs and that many sRNAs regulate TF-encoding genes. This strategy implies that TFs, sRNAs and target genes may form a complex regulatory circuit ,9,30. Foand LuxO ; thus, sP. aeruginosa. MvfR, for example, was transcriptionally activated under low-iron concentrations or by the cell–cell signalling molecules 4-hydroxy-2-heptylquinoline (HHQ) and 3,4-dihydroxy-2-heptylquinoline (PQS), subsequently controlling transcription of iron-related genes and many virulence-related factors [P. aeruginosa.A few publications have reported several genes involved in the link between iron and QS systems in  factors ,35. Prev factors . Its tar factors ,27. In oP. aeruginosa virulence and bloodstream infection ability in vitro. Our findings advance the fundamental understanding of QS circuits in P. aeruginosa and indicate that PrrH might be a potential target for therapeutic development.In summary, we disclose a novel QS-PrrH regulatory circuit and demonstrate that PrrH is capable of repressing The bacterial strains and plasmids used in this study are listed in Table S1. Bacteria were grown in LB medium or on LB plates containing 1.5% agar, unless otherwise indicated. When necessary, antibiotics were used at the following concentrations: 100 μg/ml ampicillin (AMP), 25 μg/ml gentamicin (GM), 16 μg/ml chloramphenicol (CM), and 2, 8, and 32 μg/ml AZM.prrH, pROp200-lasI, pROp200-rhlI and pROp200-rhlR, respectively. For another PrrH expression vector, pSTV28-prrH, the prrH gene was cloned into the PstI/Hind III sites of pSTV28.The whole sequence of PrrH or the coding sequences of LasI, RhlI and RhlR were cloned into the EcoRΙ site of pROp200 with a Ready-to-Use Seamless Cloning Kit  to generate expression vectors named pROp200-gfp translational fusion vectors pUCP30T-lasI-gfp, pUCP30T-phzC-gfp and pUCP30T-phzD-gfp, the coding sequence of GFP was first cloned into XbaI/HindIII sites downstream of the Plac promoter in pUCP30T to generate the reporter vector pUCP30T-gfp, and then a wild-type fragment of LasI, PhzC or PhzD mRNA that contained putative binding sites for PrrH was PCR amplified and inserted into the XbaI/NcoI sites upstream of the first codon of GFP in the pUCP30T-gfp vector. pUCP30T-mRNA-mut-gfp, which carried a mutated sequence in the complementary site for PrrH was generated using fusion PCR based on wild-type pUCP30T-mRNA-gfp.To construct the target-lacZ reporter was used for prrH promoter analysis. A DNA fragment of the prrH promoter spanning −92 to + 74 was PCR-amplified and inserted into BamHI/Hind III sites upstream of the lacZ reporter in pQF50 to generate pQF50-PprrH.The plasmid pQF50 containing a promoter-less All constructs were confirmed by direct sequencing. Primers used in this study are listed in Table S2.prrH in PAO1 as described by Zeng et al in our previous work [prrH was cloned into XbaI/SacI sites in pGSM to generate the recombinant plasmid pGSM-ΔprrH, and then it was transformed into PAO1 to generate a prrH mutant strain (PAO1ΔprrH).The sacB-based suicide vector system was employed for the knockout of ous work . BrieflyTM 7 Dx system  using SYBR Green qPCR Master Mix . The expression levels of the target genes were normalized to the expression of an internal control gene (rpoD) using the 2−ΔΔCt method. The sequences of the primers are listed in Table S2.Total RNA was extracted using RNAiso Plus reagent . Reverse transcription  was performed with the PrimeScript RT Reagent Kit . The cDNA was subjected to qPCR on a ViiAE. coli DH5α carrying the reporter pUCP30T-mRNA-gfp or pUCP30T-mRNA-mut-gfp combined with pSTV28 or pSTV28-prrH was grown overnight (8∼10 h) at 37°C and was re-incubated to 0.5 McFarland standard (MCF), and then 100 μl of cultures were added into 3 mL of LB to grow for 6 h. Subsequently, cultures were collected by centrifugation and washed twice and resuspended in 0.9% NaCl, and 200 μl aliquots were transferred to black polystyrene 96-well microplates with a clear, flat bottom. The absorbance (Abs595) and fluorescence intensity (F485/535) were measured in a Tecan Infinity M1000Pro Reader. GFP activity was expressed in arbitrary units (AU) as F485/535/Abs595. All of the tests were carried out independently and at least in triplicate.β-galactosidase assays were carried out by the Miller method when cells were grown to mid-log phase at 37°C . All of P. aeruginosa culture supernatant was extracted with 3 ml of chloroform and 1 ml of 0.2 N HCl, and then the absorbance of the extract was measured at 520 and 600 nm. The concentration of pyocyanin was determined using the following formula: (A520/A600×17.072) = μg/ml [Pyocyanin in 5 ml of  = μg/ml . All of P. aeruginosa cultures supernatant was determined by elastin-Congo red (ECR)  assay [2 and 3 mg /ml ECR. Reaction tube was incubated 4 h at 37°C with shaking and then 100 μl of 0.12 M EDTA was added to stop reaction. Insoluble ECR was removed by centrifugation, and the OD495 was measured. All results were analyzed of three independent experiments.Elastase activity in a) assay . Mid-exp2 at OD600 of 0.05 and incubated at 37°C for 8 h. 1ml of culture supernatant was acidified (pH 2.5 ± 0.2) using 1 N HCl, rhamnolipid was extracted with 4 ml chloroform. Then 3 ml of chloroform extract was allowed to react with 100 µl of 1 g/l of methylene blue and 2 ml of distilled water, the OD638 was measured. All results were analyzed of three independent experiments.The detection of rhamnolipid was based on the experimental method used by Neissa M. Pinzon with some modifications . Mid-expA biofilm formation assay was performed as described previously by Sara Carloni . Mid-expP. aeruginosa strains were grown in LB medium to the mid-exponential phase, and 5 μl of the culture was spotted onto swarming medium (LB containing 0.5% agar and 5 g/l glucose) and swimming medium (tryptone broth containing 0.3% agar), respectively [ectively . Swarmin6 CFU of the indicated PAO1 strain in 0.9% NaCl was added to whole blood to produce a final concentration of 90% whole blood in a 200 μl volume. Samples were taken at time 0, 30, 60, 90, and 120 min, serially diluted, and plated on LB agar plates for CFU enumeration [Whole blood was partitioned into wells of a 96-well round bottom plate, and 1 × 10meration . ExperimFor the whole blood killing assay, informed consent was obtained from each volunteer, and the study was approved by the Ethics Committee of Guangdong Provincial Hospital of Traditional Chinese Medicine .P-value (P) of 0.01 < P < 0.05 are represented by *, P < 0.01 are represented by **, and P < 0.001 are represented by ***.Data of the results from multiple independent experiments are expressed as the mean ± standard deviation (SD). The differences between groups were analysed using Student’s t-test when two groups were compared or one-way ANOVA when more than two groups were compared. All analyses were performed using GraphPad Prism, version 5 . Differences with a Click here for additional data file.


The transcription factor Oct4 plays a pivotal role in the pre-implantation development of the mouse embryo. DNA methyltransferase 1 (Dnmt1) maintains the changes in DNA methylation during mammalian early embryonic development. Little is known of the role of Oct4 in DNA methylation in mice. In this study, Kunming white mice were used as an animal model to reveal any correlation between DNA methylation and Oct4 during mammalian embryonic development.Dnmt1 and Oct4 were initially studied using real-time PCR. They exhibited different patterns during the pre-implantation stage. Moreover, by using a promoter assay and ChIP analysis, we found that the transcriptional activities of Dnmt1 in mouse NIH/3 T3 cells and CCE cells were regulated by Oct4 through direct binding to the − 554 to − 294 fragment of the upstream regulation element of Dnmt1. The downregulation of Dnmt1 expression and enzyme activity by mouse Oct4 were further confirmed by transfecting Oct4 siRNA into mouse CCE cells.The expressions of Dnmt1 transcription, especially during the early stages of mouse pre-implantation embryo development.Our results indicate that Oct4 is involved in DNA methylation through the regulation of The online version of this article (10.1186/s11658-018-0104-2) contains supplementary material, which is available to authorized users. The transcription factors Oct4, Sox2, Klf4 and c-Myc (referred to as the OSKM factors or Yamanaka factors) are essential for mammalian embryo development, especially in the embryonic pre-implantation stage . A previRecently, a novel type of stem cells called induced pluripotent stem (iPS) cells was successfully generated through retroviral introduction of the genes for the critically important OSKM factors. The highest efficiencies of induced pluripotency were achieved with combinations of all four factors .Although little information is available on the molecular biology events that occur during embryonic pre-implantation and further development, there is sufficient evidence to indicate that these four factors have important functions in maintaining pluripotency and differentiation potential . HoweverOct4 has been demonstrated to be a key transcription factor controlling pre-implantation development in the mouse embryo . NotablyDnmt1 results in extensive demethylation of the genome DNA, embryonic lethality, loss of imprinting, and alterations in X chromosome inactivation during mouse embryonic development, while the absence of Dnmt1 leads to the death of ES cells [Dnmt1 knockdown in germline cells leads to their immediate apoptosis [DNA methylation is an important epigenetic modification event during mouse embryonic development and in the processes of somatic cell reprogramming and gene silencing –12. DnmtES cells . Dnmt1 kpoptosis .During mouse oogenesis and pre-implantation development, Dnmt1 transcripts and protein were found to be expressed and proven to be responsible for the maintenance of methylation during pre-implantation stages other than the eight-cell embryo .Dnmt1 and Oct4 during the pre-implantation stage. The luciferase promoter assay and chromatin immunoprecipitation (ChIP) were performed to investigate the binding of Oct4 to the cis-regulation element of Dnmt1. RNAi of Oct4 in mouse CCE cells was also carried out to examine whether the expression level and enzyme activity of Dnmt1 was regulated by Oct4 in vitro. Our results are consistent with those in an earlier report [Dnmt1 and that this would also be true for human mesenchymal stem cells.The expression of Oct4 and DNA methylation have been shown to be critical in the development of the mammalian pre-implantation embryo and in cell reprogramming . Howeverr report . Thus, wDnmt1 in the embryos increased from the zygote to the 4-cell stage and dramatically decreased from the 8-cell stage onwards  was found in the − 475 to − 468 bp region relative to the transcription start site (TSS). To confirm the potential Oct4-binding site, four luciferase reporters were constructed and transfected in two different cell lines.Dnmt1 promoter (-P1–4) was detected, indicating that the Oct4 positive regulatory element in the region between − 554 and − 294 bp relative to TSS could be lacking.The results showed that the relative luciferase activities were higher in the groups that were co-transfected with Dnmt1-P1, 2 and 3 and Oct4 than in the separate control Fig. , b and eDnmt1 and the transcription activation efficiency of Oct4 . Additionally, to associate the Oct4-binding siteinformation in the Dnmt1 promoter, a high association score was obtained for Oct4 (0.955676) based on the relative distance to the TSS of Dnmt1, indicating that Dnmt1 is one of the potential target genes for Oct4 in human and mouse embryonic stem cells.Next, we examined whether Oct4 binds to the The ChIP assay was employed to investigate the binding affinity. The chromatin (from CCE cells) was immunoprecipitated with anti-RNA Pol II antibody (as a positive control), anti-IgG antibody (as a negative control), and a specific antibody against mouse Oct4. As shown in Fig. Oct4  of the R2- and R3-transfected groups were 1.5 to 2 times lower than those of the negative control. The change rates and the amounts of Dnmt1 in the three siRNA CCE were approximately 60–80% of those of the negative control Fig.  and d. TDnmt1 and Oct4 in pre-implantation embryos of the Kunming white mouse.Kunming white mice are widely used as model animals in China. The dynamic expression and cellular localization of Dnmt1 and Oct4 in pre-implantation embryos of other mouse strains have been reported , but litIt is well known that epigenetic modification of the genome plays important roles in mouse early development. Many studies have shown that the global DNA methylation levels gradually decrease from 1-cell to 16-cell or morula stage embryos , but reaDnmt1 levels are inversely related to Oct4 mRNA levels during pre-implantation embryo stages. Our results show that the mRNA level of Dnmt1 before the 4-cell stage was relatively higher than that from the 8-cell stage onwards, further indicating that Dnmt1 is a maintenance methyltransferase in the pre-implantation period [Dnmt1 or caused by de novo methyltransferases (Dnmt3a and Dnmt3b) [Dnmt1 also responds to the global DNA methylation levels during the mouse pre-implantation stage. Furthermore, while initially present as a maternal transcription factor in the oocyte [Oct4 level is gradually raised by the embryo throughout the pre-implantation period and correlates with an undifferentiated phenotype. This indicates that Oct4 could function as a key player and construct gene regulation networks with other genes during mouse early development.In this study, we found that n period , 24. The Dnmt3b) . This exe oocyte , the OctOct4 increases with embryonic development and peaks during the blastocyst stage, as has also been reported in other mouse strains [Dnmt1.In a previous study, Oct4 was observed to be located in the ICM cells of blastocysts . It is w strains . InspireDnmt1 transcription is regulated by Oct4. Sequential deletion promoters of mouse Dnmt1 were isolated and cloned into luciferase reporter vectors, including a luciferase plasmid bearing a mutation in the − 475 to − 468 bp Oct4 binding motif. Using transfection assays, we found that no significant difference in the luciferase activities of mouse Dnmt1 among the Dnmt1 P-1 to P-3 groups when co-transfected with mouse Oct4, but significant differences were observed between those groups and the respective control treatments. On the other hand, the luciferase activity of Dnmt1 P-4 was obviously lower than those of Dnmt1 P-1 to − 3 groups, indicating that there is a cis-regulatory element of Oct4 in the mouse Dnmt1 promoter region (the region from − 554 to − 294 bp). Because of the endogenous high expression of Oct4 in CCE cells, we found that their luciferase basal activity was higher than that for NIH cells without overexpression of external Oct4 when co-transfected with mouse Dnmt1-P1 promoter. Meanwhile, the luciferase activity in CCE cells was lower than that for control cells (Dnmt1-Pwt promoter) when co-transfected with mouse Dnmt1-Pmu promoter, but there was no significant difference between Dnmt1-Pmu promoter-transfected groups with or without overexpression of external Oct4  was defined as the fractional cycle number by the method of global minimum. The ratio change in Oct4 and Dnmt1 relative to the Gapdh control gene was determined using the 2-△△Ct method [Fifty embryos were used for each time point, and three replicates were performed for each stage. Total RNA extraction, cDNA synthesis from all the samples, and real-time PCR were conducted according to the manufacturer’s instructions as described previously . Gapdh wt method . Data arp < 0.05). All primers used for the study are listed in Additional file A Kruskal-Wallis test, which was conducted with GraphPad Prism 5 software (GraphPad Software), was used to determine if there was a significant difference between the means (Dnmt1 gene were generated via PCR and subcloned into the pGL3-Basic Vector (Promega Corp.) within the Mlu I and Hind III sites. The software Promoter 2.0 Prediction Server (http://diyhpl.us/~bryan/irc/protocol-online/protocol-cache/TFSEARCH.html) was used to predict the transcription start sites of mouse Dnmt1. Luciferase plasmid bearing a mutation in the − 475 to − 468 bp Oct4-binding motif was constructed via PCR-mediated mutagenesis using primers containing the mutations. The software TFSEARCH ver. 1.3. (http://diyhpl.us/~bryan/irc/protocol-online/protocol-cache/TFSEARCH.html) and PROMO searching tools  were employed to analyze all possible binding sites on the sense and antisense chains of the mouse Dnmt1 promoter. Mouse Oct4 were amplified and cloned into the pcDNA3.1 expression vector (Invitrogen) using gene-specific open reading frame (ORF) primers as described in our previous study [The 1228-, 931-, 554- and 294-bp fragments of the 5′-flanking regions of the mouse us study . All insDnmt1 promoter, which were cloned into the pGL3-Basic luciferase reporter vector;500 ng of normal or truncated constructs or mutants of the mouse Oct4-pcDNA3.1 expression plasmid;10, 50, 100, 200 or 500 ng of pRL-TK (Promega) at 100 ng/well.Using Lipofectamine 2000 (Invitrogen), mouse fibroblast cell line NIH/3 T3 cells were transfected with the following plasmids:Renilla luciferase from pRL-TK was employed as an internal control for transfection efficiency. Firefly luciferase and Renilla luciferase readings were obtained using the Dual-Luciferase Reporter Assay System (Promega) and GloMax 20/20 Luminometer (Promega). Cell culture, transient transfection and luciferase assays were performed as reported previously [eviously . For CCEeviously , 36.http://www.maayanlab.net/ESCAPE) and the GEO database with ID number GSE11431 were used to confirm whether Oct4 binds to the Dnmt1 promoter in vitro as described previously [The online program ESCAPE  was used to transfect the Stealth RNAi siRNA against Oct4 into CCE cells. The Stealth RNAi Negative Control Duplexes (Invitrogen Life Technologies) were used as a negative control. BLOCK-It Alexa Fluor Red Fluorescent Oligo (Invitrogen) was used to facilitate the assessment and optimize the delivery of double-stranded RNA oligonucleotides into the CCE cells. These siRNA sequences were submitted to a BLAST search to ensure that only the mouse 2 incubator.RNAi transfection was conducted according to the manufacturer’s instructions. Gene knockdown assays were performed after the complexes were added to the cells and incubated for 48 h at 37 °C in a COReal-time PCR and western blotting were conducted to investigate the mRNA and protein expression levels of mouse Oct4 and confirm whether Dnmt1 was downregulated. Total RNA extraction, cDNA synthesis, and real-time PCR were performed as described above. Total proteins were extracted from the RNAi-transfected CCE cells following the procedure detailed in the manual of the “NE-PER Nuclear and Cytoplasmic Extraction Reagents” . The protein concentration was measured using a bicinchoninic acid assay on a NanoDrop 2000 spectrophotometer. Western blotting analysis was performed as described previously . The antDnmt1 by direct binding to a specific site on the Dnmt1 promoter. The total amount of Dnmt1 in CCE cells is reduced by Oct4 as evidenced by the results of the knockdown assay. These findings might reveal a correlation between Oct4 and Dnmt1 during the stages of mouse pre-implantation embryo development and provide new insights into the mechanism of the early stages of mammalian embryonic development.Our results demonstrate that Oct4 plays an important role in the transcription of Additional file 1:Figure S1. Promoter analysis of mouse Dnmt1 in NIH3T3 and CCE cells using the luciferase assay. A – The promoter activity of mouse Dnmt1 in NIH3T3 and CCE cells. Oct4-pcDNA3.1 (100 ng) plasmid was co-transfected with Dnmt1-P1 into NIH3T3 and CCE cells. B – The promoter activity of mouse Dnmt1-Pwt and -Pmu in CCE cells. Oct4-pcDNA3.1 (100 ng) plasmid was co-transfected with Dnmt1-Pwt and -Pmu into CCE cells. The total amount of the transfected plasmid, including the pRL-TK control vector (100 ng/well), was adjusted to 1.0 μg with pcDNA3.1 empty vectors. Firefly and Renilla luciferase activities were measured 48 h after the transfection. The relative luciferase activity was calculated by dividing the activity of firefly luciferase by the activity of Renilla luciferase. The data are presented as the means ± SD for triplicate transfections. (TIF 306 kb)Additional file 2:Figure S2. The results of the sensitive two-color EMSA assay showed direct binding of Oct4 to the mouse Dnmt1 promoter in vitro. A quantity of 20 ng of mouse Dnmt1 promoter (the region from − 554 to − 294 bp relative to TSS) was added to samples containing different amounts of Oct4 in 1 × binding buffer as described in the Methods section. The images were taken using an alpha gel imaging system. Lanes: (1) DL2000 markers; (2) 20 ng mouse Dnmt1 promoter; (3–9) 20 ng mouse Dnmt1 promoter interacting with increasing amounts  of mouse Oct4 protein;  40 ng Oct4 protein without any mouse Dnmt1 promoter. A – Image of the EMSA gel stained with SYBR Green EMSA DNA stain to show DNA. B – The same gel stained with SYPRO Ruby EMSA protein stain to show the protein. (TIF 589 kb)Additional file 3:Figure S3. Dnmt1 assay results show the promoted amount of Dnmt1 in NCI-H157 cells when overexpressed with mouse Oct4. A – Illustrated standard curve generated with Dnmt1 Standard. B and C – The final OD  and the amount of Dnmt1 were enhanced in the Oct4+ group when compared with the control (Oct4− group). The results are presented as the means ± SD. The final values of (OD 450 nm – 650) from triplicate transfected samples were measured using a microplate reader. * and **Statistically significant difference of the comparisons with the negative control as determined with Student’s t-test at p < 0.05 and 0.01. (TIF 576 kb)Additional file 4:Table S1. List of primer sequences used in real-time PCR, promoter analyses and ChIP assay. (DOCX 12 kb)