Escherichia coli, the histone‐like nucleoid structuring (H‐NS) protein also functions as negative regulator of rcsA transcription. However, the exact mode of regulation of rcsA transcription by H‐NS has not been studied extensively. Here, we report the multicopy effect of dominant‐negative hns alleles on the transcription of rcsA based on expression of cps‐lac transcriptional fusion in ∆lon, ∆lon rpoB12, ∆lon rpoB77 and lon+ strains. Our results indicate that H‐NS defective in recognizing curved DNA fails to repress rcsA transcription significantly, while nonoligomeric H‐NS molecules still retain the repressor activity to an appreciable extent. Together with bioinformatics analysis, our study envisages a critical role for the putative curved DNA region present upstream of rcsA promoter in the transcriptional regulation of rcsA by H‐NS.It is well established that in  Cescapsule expression suppressionCpscapsular polysaccharideH‐NShistone‐like nucleoid structuringLB mediumLuria–Bertani mediumODoptical densityRcsAregulator of capsule synthesis ArpoBRNA polymerase beta subunitEscherichia coli, the genetic material is organized in the form of nucleoid and the DNA‐binding proteins such as histone‐like proteins serve as a dynamic scaffold for nucleoid organization E. coli is one of the major components of the nucleoid. hns gene was identified by Pon et al. E. coli chromosome. H‐NS protein comprises 137 amino acids with 15.5 kDa molecular weight. Although initial studies suggested that H‐NS is involved only in the organization of chromosome, the identification that H‐NS has higher propensity to bind to DNA, especially the AT‐rich sequences, clearly indicated the regulatory function associated with H‐NS E. coli genes is affected in hns mutant In H‐NS binding does not seem to occur with any obvious sequence specificity H‐NS itself acts as a repressor for its own promoter, and apart from H‐NS, StpA, Fis and CspA also play a role in the regulation of H‐NS expression lon mutant of E. coli by two novel rpoB mutations, namely rpoB12 and rpoB77. Genetic and molecular analyses clearly showed that downregulation of rcsA transcription is the primary reason for the elicitation of this capsule expression suppression (Ces) phenotype by these two rif alleles. Furthermore, our study clearly indicated that the presence of functional H‐NS is mandatory for both the rpoB mutations to function as capsule expression suppressors in the ∆lon strain of E. colircsA transcription, and their study also revealed the involvement of a small RNA, namely DsrA located downstream of rcsA, in the regulation of rcsA by H‐NS. DsrA binds to H‐NS and thereby inhibits the action of H‐NS on rcsA transcription. However, the mode of binding and the exact binding region for H‐NS in the promoter region of rcsA have not been reported so far. They have suggested that the upstream region of rcsA promoter might possess bending/curved DNA region rcsA promoter through bioinformatics analyses rcsA promoter. Furthermore, we have shown that the H‐NS molecule which is defective in the formation of higher‐order oligomers can still function as a repressor at the rcsA promoter. The bioinformatics analyses show that the region around 400 bp upstream of rcsA promoter might serve as H‐NS binding site.Very recently, we have reported the suppression of overexpression of genes implicated in colanic acid capsular polysaccharide (Cps) synthesis in ∆The media  composition used in this entire study is essentially as described in Ref. E. coli K‐12, and the genetic nomenclature is according to Refs Table hns, namely pLGhns‐∆64, pLGhns‐P116S, pLGhns‐T55P, pLGhns‐L26P and pLGhns+, were procured from J Gowrishankar, CDFD, Hyderabad, India. The plasmids were isolated from relevant strains using the alkaline lysis method lon cps‐lac), SG201781 (lon+cps‐lac), MMRT6 (∆lon cps‐lac rpoB12) and MMRT23 (∆lon cps‐lac rpoB77), were transformed with the relevant clones. The CaCl2‐mediated transformation technique was followed. As the vector backbone (pLG339) bears kanamycin as selection marker, the transformants were selected on LB plates containing kanamycin. Representative transformants from each case were selected and purified for further use.The strains bearing the plasmids harbouring the dominant‐negative alleles of cps‐lac fusion) was subcultured into 5 mL of M9 minimal medium containing glucose as carbon source and grown at 30 °C. The cultures were allowed to attain mid‐log phase, and then, the optical density of the cultures was recorded at 600 nm wavelength. The beta‐galactosidase expressed from cps‐lac fusion was assayed as described in Ref. 0.1 mL of overnight cultures of each strain (carrying rcsA including the upstream region of rcsA promoter (till ‐600) was retrieved from Ecocyc.org, and the structure of the DNA sequence was elucidated using the software model.it (http://hydra.icgeb.trieste.it/dna/index.php). Further analyses/manipulations of the structure were carried out using pymol .The DNA sequence of the coding region of rpoB mutations capable of suppressing the overproduction of colanic acid Cps in lon mutant of E. coli, we have substantiated the role of functional H‐NS in the elicitation of Ces phenotype by the two rpoB mutations, namely rpoB12  and rpoB77  hns in Ces strains (∆lon rpoB12 and ∆lon rpoB77) and in parental strains (∆lon and lon+) was studied . For information of different dominant‐negative alleles of hns used in this study  was also used, as in this case the result could be presumed and it can be used for better comparison. All the clones were transformed into the relevant strains, namely SG20780 (∆lon cps‐lac), SG20781 (lon+cps‐lac), MMRT6 (∆lon cps‐lac rpoB12) and MMRT23 (∆lon cps‐lac rpoB77). In each case, a transformant was purified, cells were grown overnight in minimal glucose medium containing kanamycin till mid‐log phase and β‐galactosidase assay was carried out as described in hns+ clone reduced the expression of cps‐lac fusion to an appreciable degree in all the strains  which is defective in binding to curved DNA, the expression level of cps‐lac has gone up to appreciable levels in all the above‐mentioned strains. Comparative analyses of the multicopy effect of hns+ and hnsP116S alleles on the expression of cps‐lac fusion in the relevant strains clearly show the inability of the mutant form of H‐NSP116S molecules to exert complete repressor activity like the wild‐type although it is reported to retain nonspecific DNA‐binding activity  to bind to such putative bendable/curved region of rcsA promoter could be the cause for higher level of cps‐lac expression in the relevant strains. Introduction of pLG‐hns∆64 increased the cps‐lac expression to some extent that clearly implies that the H‐NS molecules bearing only the N‐terminal region are not completely defective in repression at rcsA promoter.In our earlier study pertaining to the isolation and characterization of novel hnsL26P and pLGhnsT55P, when introduced into the strains, namely SG20780 (∆lon cps‐lac), SG20781 (lon+cps‐lac), MMRT6 (∆lon cps‐lac rpoB12) and MMRT23 (∆lon cps‐lac rpoB77), surprisingly decreased the cps‐lac expression remarkably. The hns alleles cloned into these vectors result in the amino acid substitution at N‐terminal region (at amino acid positions T55P and L26P), which is expected to affect the oligomerization property of H‐NS molecules. This indirectly but strongly supports the view that even the oligomerization‐defective H‐NS could interfere with cps‐lac expression perhaps by repressing rcsA transcription  region of H‐NS is involved in the oligomerization rpoB12 and rpoB77 mutations, and we have predicted the presence of bendable DNA sequence upstream of the rcsA promoter rcsA promoter is probably bendable in nature. Using the software model.it, we have modelled the DNA region present upstream of rcsA, and the image was further manipulated by pymol software. Figure rcsA transcription.H‐NS has been shown to bind to the curved DNA region preferentially lon mutant of E. coli. Detailed study on these aspects revealed that stabilization of two Lon substrates, namely RcsA (the positive regulator of cps transcription) and SulA (cell division inhibitor that gets induced upon DNA damage), is the main reason for the elicitation of the above‐mentioned phenotypes, respectively ssrA and a novel allele of dnaJ (faa) rif (rpoB) mutations capable of suppressing either one or both of the phenotypes of lon mutant. In such an attempt, we were indeed successful in isolating two such novel rif alleles (rpoB12 and rpoB77) that could suppress only the overproduction of capsule synthesis. Detailed analyses showed that the elicitation of this Ces phenotype by these rif mutations primarily stems from the downregulation of rcsA transcription. Our study also revealed the requirement of functional H‐NS in the elicitation of Ces phenotype rcsA has been reported, the exact mode of regulation of rcsA transcription by H‐NS has not been reported to date.Overproduction of colanic acid Cps and extreme sensitivity to DNA‐damaging agents are considered as the iconic phenotypes of a hns have been isolated hns such as hnsP116S, hnsT55P, hnsL26P, hns∆64 and hns+, in phenotypically Ces strains such as MMRT6 (∆lon rpoB12) and MMRT23 (∆lon rpoB77) and also in ∆lon and lon+ strains has clearly revealed that the hnsP116S allele that codes for H‐NS but is defective in recognizing curved DNA almost completely abolished the elicitation of Ces phenotype in both ∆lon rpoB12 and ∆lon rpoB77 strains. This effect was seen even in ∆lon and lon+ strains. This indirectly implies that the region upstream of rcsA promoter might possess putative curvature which might play an important role in the regulation of rcsA transcription by H‐NS.Much of the information about the properties of different domains of H‐NS came from the analyses of effect of different mutations on the functionality of H‐NS. Systematic mutational analyses with H‐NS revealed that C‐terminal region is crucial for DNA binding and the central and N‐terminal regions are involved in the formation of oligomer/higher‐order oligomerization hns alleles coding for the amino acid substitutions, namely T55P and L26P (which are defective in the formation of higher‐order oligomers), significantly reduced the cps‐lac expression not only in the ∆lon rpoB12 and ∆lon rpoB77 strains but also in the ∆lon and lon+ strains; that is, the effect is albeit closer to that of wild‐type H‐NS. This was totally unexpected as we imagined that the mutant forms of H‐NS cannot form higher‐order oligomers and therefore will not be able to repress rcsA transcription. But the fact that we have made such an observation compelled us to make a model that in a nonoligomeric state and even without forming higher‐order oligomers, these mutant forms of H‐NS perhaps might be able to bind to DNA and function as repressors for rcsA transcription. Williams et al. hns alleles, namely L26P and T55P, drastically decreased the expression of semisynthetic 5A6Agal promoter. Similar analyses with one other H‐NS‐regulated gene, namely proU, indicate that the expression of its promoter was not found to be identical to that of 5A6Agal promoter. These observations signify the fact that the regulatory function of H‐NS depends on the sequence features of the promoters also. In similar analyses, it was also found that introduction of clone bearing hns allele (P116S) elevated the expression of 5A6Agal promoter to an appreciable degree, while the same was once again not found to be true with proU promoter. It has been reported that the upstream region of 5A6Agal promoter bears a curvature proU, the presence of any curved DNA region has not been reported and notably the repression by H‐NS essentially needs extensive nucleoprotein formation at the proU promoter proU promoter region.Further, the clones bearing 5A6Agal promoter and rcsA promoter is found to be similar in the presence of different dominant‐negative hns alleles. These observations clearly favour the notion that the upstream region of rcsA might possess curved DNA which would serve as binding region for H‐NS, thus aiding H‐NS to transcriptionally regulate rcsA expression.The expression pattern of SM designed the study, performed experiments, analysed the results and wrote the manuscript. MK performed the experiments. MHM analysed the results, wrote the manuscript and provided resources for the study.


Drosophilla cell type where LADs have previously been mapped, they are neither H3K9me2-enriched nor overlapped with the domains of heterochromatin protein 1a (HP1a).In most mammalian cell lines, chromatin located at the nuclear periphery is represented by condensed heterochromatin, as evidenced by microscopy observations and DamID mapping of lamina-associated domains (LADs) enriched in dimethylated Lys9 of histone H3 (H3K9me2). However, in Kc167 cell culture, the only Drosophila third instar larvae. Strikingly, contrary to Kc167 cells of embryonic origin, in neurons and, to a lesser extent, in glia and the fat body, HP1a domains appear to overlap strongly with LADs in both the chromosome arms and pericentromeric regions. Accordingly, centromeres reside closer to the nuclear lamina in neurons than in Kc167 cells. As expected, active gene promoters are mostly not present in LADs, HP1a and Pc domains. These domains are occupied by silent or weakly expressed genes with genes residing in the HP1a-bound LADs expressed at the lowest level.Here, using cell type-specific DamID we mapped genome-wide LADs, HP1a and Polycomb (Pc) domains from the central brain, Repo-positive glia, Elav-positive neurons and the fat body of Drosophila cell types, we discovered the existence of peripheral heterochromatin, similar to that observed in mammals. Our findings support the model that peripheral heterochromatin matures enhancing the repression of unwanted genes as cells terminally differentiate.In various differentiated The online version of this article (10.1186/s13072-018-0235-8) contains supplementary material, which is available to authorized users. Eukaryotic chromosomes are subdivided into less condensed euchromatin and more densely packed heterochromatin. The facultative heterochromatin that is dispersed on the chromosome arms (hereafter ChAs) is mostly composed of silent tissue-specific genes and transposable elements (TEs), whereas pericentromeric and telomeric regions highly enriched in satellite DNA, TEs and other repeats form the constitutive heterochromatin  . ImmDrosophila, nematode and mammalian cell lines [Drosophila, LADs have previously only been mapped in cultured Kc167 cells of embryonic origin [Drosophila cell types may be bound by HP1a or, to a greater extent, by Pc.The nuclear envelope is lined with A- and B-type lamin filaments which, together with numerous lamin-binding proteins, compose the nuclear lamina . Usill lines –13. LADsll lines , 11, 12.ll lines –22. In mll lines , 23–25, ll lines . The H3Kll lines –28, and ll lines –32. Bindll lines –38, thusll lines ). Howevec origin . MoreoveDrosophila third instar larvae were previously mapped genome wide [Drosophila. Finally, we revealed that centromeres are positioned closer to the nuclear lamina in Drosophila neurons than in Kc167 cells.Recent modifications of the DamID technique have made it possible to map the interactions of proteins of interest (POIs) with chromatin in a particular cell type within complex tissues –46. Usinome wide . In thiselav-GAL4 driver and a UAS-FLP transgene  algorithm  to 55% (in glia) of the length of ChAs, whereas HP1a domains cover 6–26% and Pc domains—12–24% of ChAs  in e genome , the LADp < 10−4, permutation test). Moreover, the increased overlap between LADs and HP1a domains in the analyzed organs/cell types relative to Kc167 cells is characteristic not only for ChAs but also for the pericentromeric regions  than that in LADs without HP1a binding, where it appears to be the same as in the whole ChAs. We, thus, propose that TEs in the central brain may participate in the recruitment of HP1a to LADs.To test the hypothesis that HP1a binding in LADs may be mediated by TEs, we analyzed the distribution of 3183 TE insertions in the ChAs of Drosophila males, but not in females [Previously, the preferential binding of HP1a with the X chromosome as compared to autosomes was revealed in adult  females . In agreTo analyze the expression levels of genes residing in LADs, Pc and HP1a domains, we employed previously obtained RNA-seq data for the central brain and fat bodies isolated from the third instar larvae males GSE75835 ), or for835 , or However, in Kc167 cells, median expression level of genes, whose promoters  are located in the HP1a domains, appears to be increased compared to the rest of the ChAs Fig. a, therefIn attempts to clarify the effect of HP1a on those genes, we used publicly available microarray expression data for the control and HP1a-depleted Kc167 cells from GSE18092 . Out of Drosophila tissues represented in the FlyAtlas database [p < 10−4 for each POI, permutation test). Yet, a small fraction of those promoters  are intersected with LADs, Pc or HP1a domains in at least one cell type, and only the minor fraction of them overlaps with the LADs, Pc or HP1a domains conserved among various cell types . Upon examination of DamID profiles, we noticed that some promoters of tissue-specifically expressed genes lose their interactions with the nuclear lamina, whereas their bodies stay in contact. For example, the log2(Dam-Lam/Dam) profile in neurons has a dip at the promoter region of neuron-specific CG13579 gene, whereas the elevated association with the nuclear lamina is revealed along its body  values around TSSs for the genes aligned in the 5′ → 3′ direction and overlapped by their bodies with the corresponding domain type. We found that the higher genes are expressed—the weaker the Lam, Pc or HP1a binding at their promoters  antibodies marking the centromeres , 57 and Drosophila LADs were identified only in the Kc167 cell culture of embryonic origin [Drosophila third instar larvae. This allows us for the first time to reveal inter-LADs common to all cell types, which carry the vast majority of ubiquitously expressed gene promoters  by BestGene company (http://www.thebestgene.com/). All DamID transgenic flies used in the study are available from the Bloomington Drosophila Stock Center under accession numbers #65429–65432 (intein system) and #65433–65436 (stop-cassette excision system). The repo-FLP stock [elav-GAL4 (#8760), UAS-FLP (#8208) and UAS-RedStinger (#8547) stocks were obtained from the Bloomington Drosophila Stock Center. To perform DamID in the fat body, intein excision was induced by 4-hydroxytamoxifen . For that, 4-HT was added to the fly food at a final concentration of 25 μM and then mated female flies were allowed to lay eggs on this food. Thus, larvae were exposed to 4-HT from hatching until they were collected in the third instar stage. To perform DamID in the central brain of third instar larvae, the spontaneous excision of intein (without 4-HT induction) [Fly stocks were maintained under standard conditions at 25 °C. Transgenic fly lines bearing LP stock  was kindA few dozen central brains or fat bodies from wandering third instar male larvae or, in case of Repo-positive glia or Elav-positive neurons, from a mix of male and female larvae were manually dissected and collected as described previously . Isolati2 transformed. Since for each POI the dynamic range of log2-transformed profiles in different organs/cell types was rather different and we wanted to make cross-tissue comparisons, quantile normalization between organs/cell types was applied. We propose that variability in the dynamic range is caused by the different DamID approaches used (the induced/uninduced intein and stop-cassette excision systems) and has no biological relevance. This is supported by the high correlation between DamID profiles in the central brain and neurons, while the dynamic ranges of log2 profile in these organs/cell types were quite different. On the contrary, a substantially lower correlation was observed between the central brain and glial cells, which were just slightly different in the dynamic ranges of log2 profiles.Sequencing reads from two biological replicates of Dam, Dam-Lam, Dam-HP1a or Dam-Pc samples for each organ/cell type were adapter clipped and uniquely mapped to the dm3/R5 genomic assembly by “bowtie2” . Reads whttps://github.com/foriin/DamID-seq). For determination of Pc domains, we applied three-state HMM, as for unknown reasons two-state HMM overestimated domain presence in the central brain (not shown). The domains for Lam, HP1a and Pc in Kc167 cells generated by DamID microarray approach [HP1a and Lam domain calling was performed with a two-state HMM algorithm  appearsapproach ) most prapproach . To perfapproach  in R to 2-transformed values (with p < 0.05) and averaged between replicates. Differentially expressed genes upon HP1a KD were determined using the “limma” R package [p values < 0.05 were used for further analysis.RNA-seq data for the central larval brain and fat body were taken from GSE75835 , and for package . Only geDrosophila tissues/organs in the whole-transcriptome RNA-chip data (GSE7763 [If at least 3 (out of 4) present calls  in each of 15 adult and larval GSE7763 ) were fo763  were2(Dam-POI/Dam) values across seven genomic bins centered at gene promoters (three bins upstream and three bins downstream from the zero bin) were calculated. Only genes overlapped with the corresponding domain type by their bodies and only the upstream bins not overlapped with other genes and the downstream bins carrying the corresponding gene were taken for the analysis.To generate the lists of tissue-specific genes expressed in neurons or glia, we employed RNA-seq data from larval neurons or glial cells (GSE71104 ). TPM vaDrosophila dm3/R5 genome assembly . As we considered only uniquely mapped reads during DamID-seq analysis, the TE sequences were mostly excluded from the identified LADs and HP1a domains. Therefore, the observed number of insertion events was counted as a number of overlapping events between positions of TEs, extended by 0.5 kb from their ends, and the domains.Genomic positions for 3183 TE insertions in the e et al. ) were dop value estimation, the Mann–Whitney (M–W) U test was used for comparison of two sample distributions. p values for occasional gene/domain or domain/domain overlapping were estimated by permutation test with 10,000 permutations.For Drosophila medium (Gibco) supplemented with 10% heat-inactivated FBS (Gibco), 50 units/ml penicillin and 50 µg/ml streptomycin.Kc167 cells obtained from Drosophila Genomics Resource Center were grown in Schneider’s Immunostaining was performed as previously described in  with somZ-axis. Images were processed and analyzed using IMARIS 7.4.2 software (Bitplane AG) with a blind experimental setup. Images were thresholded to eliminate hybridization and immunostaining background effects. The distances between signals and the nuclear envelope were counted as previously described [Three-dimensional image stacks were recorded with a confocal LSM 510 Meta laser scanning microscope (Zeiss). Optical sections were captured at 0.4–0.6-μm intervals along the escribed . BrieflyAdditional file 1. Scheme of fly crossing for DamID in neurons.Additional file 2. Figures S1–S9.Additional file 3. Table S1: HP1a, Lam and Pc domain coordinates in the central brain, neurons, glia and fat body.Additional file 4. Table S2: The percentage of intersected domain length from total POI domain length  in the central brain, neurons, glia, fat body and Kc167 cells separately for ChAs, CHet, 4th chromosome and non-repetitive part of X chromosome.Additional file 5. Table S3: Expression of genes according to the RNA-seq data from [ata from , 49 withAdditional file 6. Table S4: Differentially expressed gene list upon HP1a KD in Kc167 cells with the indication of intersection of gene bodies with HP1a, Lam or Pc domains. Microarray expression data were from [ere from .Additional file 7. Table S5: List of ubiquitously expressed genes based on microarray expression data from [ata from  with theAdditional file 8. Table S6: Distances from the CenpA signals to the nuclear lamina in Elav-positive neurons and Kc167 cells.Additional file 9. Table S7: HTS raw data parameters.


Most mammalian RNA polymerase II initiation events occur at CpG islands, which are rich in CpGs and devoid of DNA methylation. Despite their relevance for gene regulation, it is unknown to what extent the CpG dinucleotide itself actually contributes to promoter activity. To address this question, we determined the transcriptional activity of a large number of chromosomally integrated promoter constructs and monitored binding of transcription factors assumed to play a role in CpG island activity. This revealed that CpG density significantly improves motif-based prediction of transcription factor binding. Our experiments also show that high CpG density alone is insufficient for transcriptional activity, yet results in increased transcriptional output when combined with particular transcription factor motifs. However, this CpG contribution to promoter activity is independent of DNA methyltransferase activity. Together, this refines our understanding of mammalian promoter regulation as it shows that high CpG density within CpG islands directly contributes to an environment permissive for full transcriptional activity. Gene regulation establishes correct spatio-temporal expression patterns essential for cellular function. Expression is controlled at multiple levels, including recognition of specific DNA sequences by transcription factors (TFs), chromatin structure, modifications of nucleosomes, and methylation of DNA. While the majority of transcription factors recognize complex motifs of several nucleotides, it is unclear whether lower complexity sequence features, such as dinucleotides, contribute independently to gene activity. CpG is the most studied dinucleotide in mammalian genomes and the site of cytosine methylation . In mammWhy CpG density is increased in CGIs remains unclear, as well as whether the CpG dinucleotide plays a role in transcriptional and/or epigenetic regulation. One explanation portrays CGIs as a footprint of evolution due to lower mutation rates of unmethylated CpGs . In suppTaken together, CpGs could have a general effect on promoter activity that is distinct from their occurrence as a part of complex TF motifs. Distinguishing these scenarios is not trivial. It requires knowledge of TF binding within CGIs and testing the contribution of CpGs to promoter activity. While the former can be addressed using ChIP-seq, the latter requires a reporter assay that quantifies transcriptional output as a function of sequence mutations. Due to the high frequency of the CpG dinucleotide, this requires many mutations and measuring many variants. Thus far, most high-throughput transcriptional reporter assays in higher eukaryotes used transient transfection . ChromosHere, we investigate the contribution of CpGs to transcriptional activity and binding of transcription factors to their motifs in CGIs. We contrast hundreds of mutant sequences after inserting them into the same genomic site in mouse embryonic stem cells (ESCs). The resulting loss- and gain-of-function experiments reveal that CpGs contribute to transcriptional output independent of DNA methylation.Transcriptional Activity in Chromatin). With TrAC-seq, promoter sequences are cloned in a pooled format and inserted into a defined genomic locus. The resulting transcripts are sequenced and assigned to their specific promoters using barcodes (BCs)  to upstream regulatory regions that are not part of the transcript. Toward this goal, we designed a parallel reporter assay called TrAC-seq (es (BCs) C. BC freTo control for the contribution of chromatin and the local genetic environment, we integrated the library of promoter-barcode constructs into the beta-globin locus in ESCs using recombinase-mediated cassette exchange (RMCE) . This reSupplemental Figs. S1A,B, S4A,B, S4E–G, S5A,B), enabling the measurement of up to ∼3100 promoter-BC constructs within a single experiment. In total, we tested more than 10,000 promoter-BC constructs representing ∼270 unique promoter sequences.The mean signal of all BCs corresponding to one promoter allowed us to reproducibly quantify the relative activity of promoters within a pool (Escherichia coli). These have a CpG density comparable to CGIs but have not evolved binding sites for eukaryotic TFs. Combined with a minimal promoter, their activity, however, is barely detectable by TrAC-seq compared to a selection of active housekeeping gene promoters . Binding was indistinguishable between SP1 and SP3, which recognize similar low complexity motifs and displayed comparably low enrichments . This limited an in-depth analysis of binding sites but allowed the classification of promoters as bound or unbound .We profiled four TFs with CpGs in their canonical motifs and relatively broad expression pattern . To test how CpG frequency relates to binding, we contrasted CpG density with TF binding independent of motif. For both factors, binding is more prevalent in windows with higher CpG density (OE ≥ 0.6) . Windows with both high CpG density and motif occurrence are bound at high frequency, with NRF1 occupying ∼45% and GABPA ∼70% of these windows . They account for ∼40% of all binding events for NRF1 and ∼15%–20% for GABPA.As expected, presence of motifs of at least intermediate motif score are a poor predictor of binding for these two factors, since only 10% and ∼5% of all genomic windows with NRF1 and GABPA motifs are bound, respectively (E ≥ 0.6) C,D. For Supplemental Fig. S3B,C). For GABPA, CpG density predicts binding better than motif alone, which is not the case for NRF1 . Combining motif score and regional CpG density in an additive model using logistic regression improves the predictive power over individual measures . If only windows with OE ≥ 0.6 are considered, almost all windows with top-scoring motifs are bound (roughly 90% for GABPA and 80% for NRF1) . Taken together, this suggests that increasing CpG density does not simply enrich for bound motifs because the motifs themselves contain a CpG, but that CpG density itself contributes to binding, which, in turn, might affect transcriptional output of CGI promoters.To move beyond this binarized comparison, we explored the predictive power of CpG and motif over a continuous range. This revealed that binding increases with CpG density and starts to diminish around the CGI threshold , which displayed variable expression . We focused on two promoters with high activity (Snx3 [∼400 bp] and Pwp2 [∼460 bp]) and systematically mutated their CpGs. To reduce the likelihood of changing motif-CpGs, we used the binding data described above to identify bound motifs. We divided each promoter into four (Pwp2) or five (Snx3) regions and generated all possible combinations of regions with either wild-type (WT) sequence or regions in which all CpGs outside of bound TF binding sites of SP1, SP3, GABPA, and NRF1 were mutated . This time, CpGs were randomly chosen to generate elements with 100%, 75%, 50%, 25%, and 0% of non-motif-CpGs. Here, we included an additional 17 published ChIP-seq data sets to define non-motif-CpGs . Moreover, CpGs to be mutated were randomly selected for each CpG density to ensure that effects are not due to absence of the same set of mutated CpGs of a particular promoter. This more comprehensive set of promoters shows a similar response; removing non-motif-CpGs lowers the transcriptional activity in most cases  , suggestPwp2 promoter at 10-bp resolution enabled us to define regions critical for transcriptional activity due to TF binding and non-motif-CpGs for further mutational analysis.Having characterized the regulatory function of the Pwp2 promoter lying in regions with minor or no effect on activity. We randomly selected subsets of these CpGs, generated 11 mutants with different CpG densities  and increased the activity as high as ∼54% of WT by adding more CpGs  from our parental line and performed the same genomic integration . We then tested CpG density promoter mutants and compared their activity to the wild-type parental cells. This revealed that CpG contribution to promoter activity is independent of DNA methyltransferases , in line with our previous findings that CpGs indeed protect against DNA methylation. These CpG-poor promoters  show very low to no transcriptional activity in both wild-type and DNA methyltransferase TKO cells. We conclude that within the tested constructs, de novo methylation occurs at already inactive CpG-poor promoters but does not account for differential expression of CpG-rich and CpG-poor promoters.Next, we measured the actual DNA methylation of several mutant CGI promoters , strongly arguing that primarily CpG density increases activity.A previous study suggested that the open chromatin structure of CGIs depends on high G and C content as well as high CpG density . Since wSupplemental Fig. S3D). This is consistent with studies showing that CpG-rich artificial sequences display marks of open chromatin  signal, and another loxP site was synthetized and cloned into a plasmid backbone containing ampicillin resistance (R Electrocomp Cells (Thermo Fisher Scientific). A dilution of 1:10,000 was distributed on a LB agar plate containing 50 mg/L ampicillin to estimate transformation efficiency. The rest was incubated in 50 mL LB containing 50 mg/L ampicillin shaking at 300 rpm at 37°C overnight. Plasmids were isolated using a Qiagen Plasmid Midi kit.A cassette containing a sistance . BarcodeSupplemental Table S1) and one of the indexing primers containing the Illumina flow cell annealing sequences using Phusion Hot Start II polymerase (Thermo Fisher Scientific). PCR products were purified using AmPure XP beads  and directly sequenced using MiSeq 500- or 600-cycle kits (Illumina). The vector was cut with SphI and PacI or NheI, and a sequence containing a CpG-free eGFP and the annealing sequence for primer DH.P6  was inserted. For an alternative construct, the insert contained a 31-bp minimal promoter in front of eGFP. RMCE was performed as described . PCR products were purified using AmPure XP beads  and sequenced using a 50-cycle kit on HiSeq 2500.RNA was isolated from cell lines containing the expression libraries with a Qiagen RNeasy Mini kit with on-column DNase digestion and reverse-transcribed using Takara PrimeScript RT Reagent kit (#RR047A). For DNA isolation, cell pellets were suspended in Bradley Buffer, 6 μL RNase A (10 mg/mL) was added, and samples were incubated (1 h at 37°C). Subsequently, 30 μL Proteinase K (1 mg/mL) was added, and samples were incubated at 50°C overnight. Then, DNA was extracted using Phenol:Chloroform. DNA and cDNA barcodes were amplified with KAPA HiFi HotStart using primer DH.P6 and indexing primer . Amplified DNA was purified with Ampure beads, and sequencing libraries were prepared using the Illumina NEBNext ChIP-seq library prep kit with 96 dual indexing and sequenced on a MiSeq (600 cycles).Cells containing integrated mutant CGI promoter libraries were plated at low density, 96 clones picked and expanded to a minimum of 20,000 cells before lysing with Bradley Buffer (10 mM Tris-HCl (pH 7.5), 10 mM EDTA (pH 8.0), 0.5% SDS, 10 mM NaCl), and DNA extracted. DNA was bisulfite-converted using a Zymo lightning conversion kit (D5046) and cleaned up using MagBeads (Zymo). Converted DNA was amplified with primers RSG353 and RSG354 . For mutant promoter libraries, reads were matched to the reference sequences using the “stringdistmatrix” function in R .FASTQ files were trimmed to the promoter sequence and aligned to mm9 using Bowtie  for librion in R , which, Supplemental Fig. S1C).Barcodes were extracted from each second read and matched to the aligned reads by read ID. Only barcodes that were associated with one unique sequence or with a sequence where the ratio of the second most abundant sequence to the most abundant sequence was below 0.3 were used for the analysis . The first ratio can be understood as being proportional to the RNA counts per single cell, to which a constant pseudocount of α is added. α was set to 0.05 as this was the smallest value of α that roughly stabilized the variance in all libraries. Log2 promoter activities were calculated as the mean of the log2 enrichments of all barcodes assigned to the particular promoter. All plots displaying expression data show mean log2 activities of three replicates unless indicated otherwise.Transcriptional analysis was performed in triplicate following genomic insertion. Barcode sequences were extracted, and the frequency of each barcode sequence was calculated to get counts for each sample. Genomic DNA and RNA samples were scaled to each other by normalizing to the smaller total number of counts. Only barcodes that were sufficiently represented on genomic DNA  were used for further analysis. In case a barcode was sufficiently represented on genomic DNA but not sequenced in the RNA fraction, we assumed that this reflects lack of activity and assigned 0 counts to the RNA barcode. Enrichments of barcodes in the RNA sample were then calculated as The significance of Spearman's correlations was calculated using permutation tests.Samples were mapped to the mm9 assembly of the mouse genome using the R package QuasR , which i2 scale) with respect to a uniform background. For more details, see Supplemental Methods.Peaks were called using Peakzilla with default parameters . PositioSupplemental Methods.For a given cut-off on either CpG density (observed over expected), motif score, or the probability of being bound predicted by a logistic regression that uses both CpG density and motif score as input, the fraction of genomic windows larger or equal to the cut-off that are bound (precision) and the number of bound genomic windows larger or equal to the cut-off divided by the total number of bound windows  were calculated. Precision-recall curves were determined by varying the corresponding cut-offs over the entire range of values . For more details, see Sequences were aligned to mutant promoter libraries using QuasR  default The following ChIP-seq data sets were downloaded from GEO: NANOG, MYCN, POU5F1 (OCT4), SMAD1, SOX2, STAT3, TFCP2L1, ZFX (GSE11431) , REXO1 , TBX3 G, TCF3 G, YY1 GS, ZIC2 G, CTCF G, NFYA G, NRF1 G, REST G.DNase hypersensitivity data set was retrieved from GEO under the accession number (GSE67867) .http://fantom.gsc.riken.jp) (The CAGE data set was downloaded from the FANTOM Consortium homepage (iken.jp) .Supplemental Table S3.For a complete overview, see https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE116704. Sequences and primers of expression libraries are provided in Supplemental Files.The raw sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO;


The regulation of genome architecture is a key determinant of gene transcription patterns and neural development. Advances in methodologies based on chromatin conformation capture (3C) have shed light on the genome-wide organization of chromatin in developmental processes. Here, we review recent discoveries regarding the regulation of three-dimensional (3D) chromatin conformation, including promoter–enhancer looping, and the dynamics of large chromatin domains such as topologically associated domains (TADs) and A/B compartments. We conclude with perspectives on how these conformational changes govern neural development and may go awry in disease states. The human and mouse genomes consist of ∼6 and ∼5 billion base pairs, respectively, and are packaged in chromosomes that are contained within a nucleus with a diameter of only ∼5 μm. Chromosomes possess multilayered structures that can be broadly classified on the basis of classical cytological and biochemical analyses either as euchromatin, an open chromatin state characteristic of gene-rich regions, or as heterochromatin, a closed chromatin state characteristic of gene-poor regions. At a higher level of resolution, local associations between gene promoters and other regulatory elements, such as enhancers, define the structural relations within active transcriptional domains .High-throughput chromatin conformation capture (3C) techniques have recently allowed the categorization of chromosomal domains into two major classes Figure . In thisin vitro , defined as genomic regions that contact the nuclear lamina, constitute heterochromatin at the nuclear periphery . LADs rell cycle , LAD forll cycle . Anotherll cycle . Liquid ll cycle . The B cll cycle , which pll cycle .Although these various studies have elucidated the framework for 3D organization of the genome, many questions regarding TAD formation – including the role of transcription, whether loop extrusion is asymmetric, and the relevance of DNA replication – remain unanswered. In addition, the mechanisms underlying A/B compartmentalization remain largely elusive. A key unanswered question regarding genome architecture is, how do local and global-scale associations, including those mediated by A/B compartments and TADs, govern changes in transcription and cell fate during development. In this review, we focus on studies on neural development in an attempt to tackle this question.The 3D architecture of chromatin changes markedly during the neural development of pluripotent stem cells. Assays based on micrococcal nuclease (MNase) or DNase I accessibility or on histone extraction have revealed that the chromatin state is globally open in embryonic stem cells (ESCs) and becomes condensed during differentiation into neural progenitor cells (NPCs) . Even amSo, how are TADs and A/B compartments regulated during neural development? TADs are structurally dynamic overall , but TADIn contrast to TADs, A/B compartments are differentially regulated during neural development. Recent studies have examined and compared genome-wide 3D chromatin organization during neural differentiation from ESCs  by Hi-C in cis and in trans (How then are regions in the A compartment regulated? High-level interactions within the A compartment in ESCs can be explained in part by long-range (>30 Mb) associations between active promoters, enhancers, and actively transcribed genes both in trans . In addiin trans . GAM conin trans ] in ESCsin trans . Given tin trans , it is pin trans , degradain trans , suggestOn the basis of classical immunocytochemical analyses, nuclear bodies, which are subcompartments within the nucleus, were hypothesized to serve as hubs for active or inactive gene loci , althougvia self-aggregation within and between PRC1 and PRC2  can mediate the association of a midbrain-specific enhancer and the promoter of the Meis2 gene during midbrain development, with the subsequent dissociation of PcG proteins resulting in the activation of Meis2 expression in the midbrain   . MoreoveAs mentioned above, most TAD boundaries are conserved between ESCs and neural cells, but a fraction of TAD boundaries appears to emerge and disappear during neural differentiation  – althouin cis. In situ Hi-C experiments with NeuN-positive mouse neocortical neurons revealed that the Pcdh gene clusters are organized as multiple small TADs (∼100 kb in length) nested into a larger TAD that encompasses at least 1.2 Mb. The 5′ end of the Pcdhα cluster is bound to the 3′ end of the Pcdhγ cluster  gene clusters. Pcdh proteins regulate axonal targeting, synapse formation, and dendritic arborization through their homophilic trans-interactions . The vas cluster . This TA cluster . The uni cluster . Forced  cluster . Given tWith regard to the mechanism responsible for the TAD structure of Pcdh gene clusters, deposition of H3K9me3 by the histone methyltransferase Setdb1   appears Regulation of CTCF binding and TAD structure by Setdb1 is not restricted to Pcdh gene clusters. Loss of Setdb1 in neocortical neurons thus resulted in the emergence of more than 3000 ectopic CTCF-binding sites . Setdb1 The regulation of 3D chromatin structure has been studied with regard to its role in determination of gene transcription patterns. New technologies such as high-resolution 3C-based methods have revealed that neural development is accompanied by changes in genome organization at the levels of both interactions between large compartments and local interactions such as those between enhancers and promoters. Such advances in basic knowledge concerning chromatin structure will facilitate our understanding of the mechanisms and relevance of chromatin regulation during neural development and the pathogenesis of related diseases. Given the heterogeneity of NPCs and neurons, analyses at the single-cell level will be especially important for studies of neural development, and the recent implementation of advanced single-cell RNA-seq, ChIP-seq, DamID, ATAC-seq, and Hi-C technologies should prove highly informative in this regard . The spaAs suggested in the case of the Pcdh gene clusters, aberrant changes in 3D chromatin structure may give rise to neurodevelopmental disorders . Indeed,YK and YG wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


To determine the role of constraint loss on cis element evolution, we examined the recent appearance of a thiamine starvation regulated promoter in Candida glabrata. This species lacks the ancestral transcription factor Thi2, but still has the transcription factor Pdc2, which regulates thiamine starvation genes, allowing us to determine the effect of constraint change on a new promoter. We identified two different cis elements in C. glabrata - one present in the evolutionarily recent gene called CgPMU3, and the other element present in the other thiamine (THI) regulated genes. Reciprocal swaps of the cis elements and incorporation of the S. cerevisiaeThi2 transcription factor-binding site into these promoters demonstrate that the two elements are functionally different from one another. Thus, this loss of an imposed constraint on promoter function has generated a novel cis sequence, suggesting that loss of trans constraints can generate a non-convergent pathway with the same output.Regulatory networks often converge on very similar  However, this upregulation differed between the ancestral THI promoters and the CgPMU3 promoter. We conclude that loss of Thi2 and selection for a newly regulated gene confers a different path across the evolutionary landscape than the THI genes that are conserved within the Ascomycete lineage.Here, we used truncation analysis to identify regions of THI promoters required for upregulation of expression during thiamine starvation. We identified an 11 base pair (bp) region that is essential for upregulation in C. glabrata wild-type (S. cerevisiae wild-type (Cgthi3∆ (DG141), and Cgpdc2∆ (DG271), Scthi2∆ (DC126), Scthi3∆ (DC143)  and transformed into a diploid strain to delete ScPDC2. We covered this deletion with a URA3+ plasmid (pRS316) containing ScPDC2. Through random sporulation, we identified haploid colonies that were Scpdc2Δ. To construct a Scpdc2∆ strain capable of growth in glucose medium, ScPDC1 was overexpressed in this strain: ScPDC1 was amplified by PCR and cloned by homologous recombination (pdc2∆ strain on a LEU2+ plasmid (pRS315) under the control of the ScADH1 promoter. This strain was then grown on SD  plates with 5-FOA to select against the URA3+ plasmid containing ScPDC2. For sequencing of the CgPMU3 promoter in the SEL-seq experiment, the entire PMU gene family  was deleted with NATMX6 in a C. glabrata wild-type strain (Table S1).Most of the experiments were performed in ild-type  and S. cild-type  strains.HIS3+ plasmid (pRS313) containing YFP in a wild-type strain  or smaller regions of the promoters of these genes were driving expression of yellow fluorescent protein (YFP). The promoters were amplified by PCR (Table S1) and cloned by homologous recombination into a 600 0.2-0.5). Cells were harvested by centrifugation, washed 3 times with sterile water, inoculated into thiamine replete (0.4 mg/L) and starvation (no thiamine added) conditions in SD medium lacking histidine, and grown at 30° overnight (∼18 h). Mean fluorescence  of each strain was measured using a fiow cytometer with a 533/30 FL1 filter set . In almost all cases, background fluorescence was less than 12,000 a.u.; however, there is variability of fluorescence based on precise growth conditions and we included positive and negative controls in each experiment.To measure induction of the THI pathway genes, fluorescence of cells containing plasmids with promoters driving YFP was quantified by flow cytometry. Cells were grown at 30° in thiamine replete SD medium lacking histidine  to logarithmic growth phase . The three PCR products – two CgPMU3 promoter PCR products and the ScTHI5 open reading frame (Table S1) – were gap repaired (CgPMU3 promoter (Cgpmu1-3∆NATMX6 described above) and we collected 131,000 independent transformants. Approximately, 5% of transformants were judged as highly expressing during thiamine starvation (based on YFP expression). We pooled the transformants and took a time zero sample for deep sequencing of the CgPMU3 promoter. Based on sampling of unique sequences, we generated ∼90,000 unique sequences to query. We then grew the cultures in SD medium lacking thiamine and histidine for three successive days with 1:1000 dilution every 24 h . We monitored fluorescence by flow cytometry and observed the frequency of cells that were highly fluorescent jump from 6 to >90% in 24 h. We collected three independently grown cultures (in medium lacking thiamine) to purify DNA and amplify the CgPMU3 promoter for next generation sequencing on a MiSeq . Sequences were extracted in Geneious, and at least 2x1750 sequences were analyzed for each sample. We sorted the sequences, identified the number of unique sequences, and quantified the percent representation of the sequence in the total sequences. We verified that extraction of a different subset did not alter the results – i.e., the same sequences were repeatedly identified as enriched.To perform the SEL-seq experiment with the ScTHI5 confers a growth advantage to C. glabrata during thiamine starvation. Figure S2 shows the frequency of abundant sequences after selection in thiamine starvation in the SEL-seq experiment. Table S2 shows the raw data from the seven samples sequenced in the SEL-seq experiment. Table S3 lists the sequences that were highly enriched after selection in thiamine starvation. Figure S3 aligns the sequences in Table S3 with C. glabrata THI promoters. Figure S4 shows a scanning mutagenesis of the 13 bp THI UAS in the CgPET18 promoter. Figure S5 is a schematic of S. cerevisiae promoters with the locations of binding sites as well as mutations and deletions made in this study. Figure S6 demonstrates that S. cerevisiae THI promoters are dependent on Pdc2, Thi2, and Thi3. Supplemental material available at figshare: https://doi.org/10.25387/g3.10308194.All strains, plasmids, and raw data are available upon request. Table S1 lists the primers used in this study to generate strains and plasmids. Figure S1 demonstrates that CgPMU3 promoter fused to the open reading frame of yellow fluorescent protein (YFP). Induction of the promoter was quantified using flow cytometry to measure the fluorescence of YFP in the cells. First, we truncated in 100 bp increments and then in 20 bp increments from -1000 bp (referring to the location upstream of the start codon) to the start codon (data not shown). We narrowed the beginning of the upstream activating sequence (UAS) to between -260 bp and -240 bp. Performing a MEME motif discovery analysis  this motif has appeared by chance in the promoters, as the sequences are imperfect matches with the CgPMU3 UAS, or 2) this motif is present, but does not have a critical role in thiamine starvation regulation by our assay. Regardless, this suggests that CgPMU3 appears to have a different UAS requirement from the other THI genes. It is worth noting that CgPMU3 is a recent duplicate of a phosphatase gene and only acquired thiamine regulation in C. glabrata  possibilities being queried for high-level expression during thiamine starvation, we replaced the 11 bp UAS with all four nucleotides in each position (incorporated into a primer – Table S1) and selected for high-level expression during thiamine starvation. Because C. glabrata is auxotrophic for thiamine and addition of ScTHI5 restores prototrophy .Because the CgPMU3 promoter upstream of the ScTHI5 ORF, replacing the CgPMU3 UAS with all four nucleotides, allowing multiple sequence options to replace the UAS. The selection was successful but limited in terms of exploring the 4 million possibilities. We obtained 105 transformants, and observed ∼90,000 unique sequences with the 20 most abundant sequences representing 9.7% in our sampling sequencing prior to selection . It is likely that PCR and primer synthesis introduced biases that led to a few abundant sequences, and a diversity of other sequences. However, after selection, the 20 most abundant sequences (which were different from the preselection sequences) represented on average 72.5% of the total sequences, indicating that some sequences conferred a strong selective advantage. To begin to eliminate sequences that might simply confer a high level expression independent of the THI pathway, we performed a parallel selection in a Cgpdc2Δ strain, expecting that if a sequence was abundant in the Cgpdc2Δ strain, that it was a sequence that allowed for higher-level expression of the ScTHI5 construct independent of the THI pathway . Eight sequences were >90 fold enriched in a THI pathway dependent manner, and all contained a 5′-CTG-3′ motif (Table S3). Interestingly, two sequences that we identified were a 10/11 bp and 8/11 bp match for a sequence element in the CgPET18 promoter, different from the PMU3 UAS in CgPMU3 UAS .Using a fusion PCR method, we gap repaired the CgPMU3, we took a parallel approach to the CgPMU3 promoter, and truncated the CgPET18, CgTHI10, CgTHI4, and CgTHI20 promoters. We narrowed down the beginning of a regulatory sequence in these promoters to a few base pairs . Only the CgPET18 promoter sequence contains a 5′-CGT-3′ motif that is critical for the CgPMU3 UAS element, perhaps explaining why we enriched for CgPET18 elements in the SEL-seq experiment.To determine regions that are important for thiamine regulation in THI promoters other than se pairs . After apromoter , that clpromoter , and thaPacI restriction enzyme site in the context of the 1000 bp promoter and determined whether this element is critical for upregulation of the CgPET18 and CgTHI10 promoters , and determined that the xxCCGTxxAxxTG nucleotides were important for expression . There is overlap between the CgPMU3 and THI UAS in terms of both possessing a 5′-CGT-3′; however, CGT is not absolutely required as CgTHI10 does not contain this sequence, and the remaining nucleotides are not easily aligned with the CgPMU3 UAS. Thus, we have identified two UAS elements that do not appear related to one another: the CgPMU3 UAS , THI4, and THI20 are present in the genomes of Saccharomycetaceae and regulated by thiamine starvation, we consider these genes and promoters to have been present in the common ancestor . We then mutated them in the ScTHI5 and ScTHI20 promoters, and assayed the ability of these promoters to induce expression during thiamine starvation (Thi2 binding site: at -110 bp in ScTHI5p and at -170 bp in ScTHI20p) did disrupt upregulation  were regulated in S. cerevisiae , and overexpression of THI3 can compensate for the loss of THI2 presumably by making Pdc2 fully active while in a complex with Thi3  behave similarly to S. cerevisiae promoters but only require Pdc2 and Thi3 , but Pho2 has a much more permissive recognition site , but still gives the same output as many other THI genes. It seems as if the simplest solution for this new promoter would be to evolve the standard ancestral THI UAS, but CgPMU3 did not acquire that solution, either because of genetic constraints or because of genetic drift. However, the selective requirement for a thiamine repressible phosphatase important for the recycling of thiamine was likely present in the history of C. glabrata (Thi2 in C. glabrata acted as a constraint in the evolution of the thiamine starvation induction of the CgPMU3 gene, yielding the only high-fitness solution to the problem. Further dissection of how each promoter functions is required to understand the precise mechanism of CgPMU3 upregulation. However, this work suggests that caution should be taken when investigating the incorporation of new genes into an existing regulatory pathway, as gain/loss of a constraint may change cis architecture in unforeseen ways.Characterization of the


They can cause cancer, reproductive and developmental issues, damage to the immune system, and can deeply interfere with the endocrine system. Dioxins toxicity is mediated by the Aryl-hydrocarbon Receptor (AhR) which mediates the cellular metabolic adaptation to these planar aromatic xenobiotics through the classical transcriptional regulation pathway, including AhR binding of ligand in the cytosol, translocation of the receptor to the nucleus, dimerization with the AhR nuclear translocator, and the binding of this heterodimeric transcription factor to dioxin-responsive elements which regulate the expression of genes involved in xenobiotic metabolism. 2,3,7,8-TCDD is the most toxic among dioxins showing the highest affinity toward the AhR receptor. Beside this classical and well-studied pathway, a number of papers are dealing with the role of epigenetic mechanisms in the response to environmental xenobiotics. In this review, we report on the potential role of epigenetic mechanisms in dioxins-induced cellular response by inspecting recent literature and focusing our attention on epigenetic mechanisms induced by the most toxic 2,3,7,8-TCDD.Dioxins are highly toxic and persistent halogenated organic pollutants belonging to two families i.e., Polychlorinated Dibenzo- Dioxins are highly toxic and persistent organic pollutants, distributing throughout the environment and accumulating in the food chain, mainly in the animal’s fatty tissues. They can cause cancer, reproductive and developmental issues, damage to the immune system, and can deeply interfere with the endocrine system ,2,3,4. DDue to their high toxicity and environmental persistence, many efforts for real-time monitoring of these organic pollutants have been realized ,9,10, unp-Dioxins (PCDDs) and Polychlorinated Dibenzo Furans (PCDFs). All dioxins consist of two benzene rings connected by one or two oxygen atoms; they can bind between four to eight chlorines atoms, generating a wide family of conformers (75 PCDDs congeners and 135 PCDFs congeners) whose molecular reactivity toward cellular targets can change dramatically determining different levels of toxicity. Among these 210 congeners, the 2,3,7,8-tetrachlorinated (TCDD) species have the highest toxicity. Toxicity drastically decreases when adding non-lateral chlorines or removing lateral chlorine from the two aromatic rings [These halogenated organic compounds belong to two families i.e., Polychlorinated Dibenzo-ic rings . This beic rings ,13 betweic rings  expresseThe proposed molecular mechanism of PCDD/Fs envisages the binding of the dioxin to the cytosolic AhR which is a transcriptional regulator of cell growth, differentiation and migration. CYP1A1 gene (coding for cytochrome P-450 1A1) and other Ah-responsive genes that regulate the expression of the genes involved in polycyclic aromatic hydrocarbon metabolism and detoxification [Dioxins are responsible for a wide variety of toxic and biochemical effects via AhR-mediated signaling pathways. The mechanism includes AhR binding of the toxic ligand in the cytoplasm and the following translocation of the receptor to the nucleus. It was also demonstrated that the heat shock protein HSP90 is capable of interacting with the AhR in cytoplasm. The HSP90/AhR interaction has the functional role of maintaining the cytosolic receptor conformation so that it is able to bind TCDD over the time. Upon ligand binding, the AhR undergoes a conformational change in the PAS A (Per-Arnt-Sim) domain, which facilitates its nuclear translocation and its consequent dimerization with the Ah receptor nuclear translocator (Arnt). The conformational change in the PAS A domain is concomitant with the dissociation from HSP90 protein and allows the conserved nuclear localization sequence in the N-terminal (42 amino acids) to stimulate the nuclear translocation of the AhR-TCDD complex, which is further facilitated by importins. After the translocation of AhR in the nucleus, there is its dimerization with Arnt and this new formed heterodimeric transcription factor binds to Xenobiotic-Responsive Elements (XRE)  upstreamfication . CYP1A1 gene. Following transcriptional activation, AhR is released from DNA and is rapidly exported from the nucleus and degraded via the ubiquitin-mediated 26S proteasome pathway [P-450 1A1 is one of the main xenobiotic metabolizing enzymes and TCDD is one of the most potent inducers of the  pathway . PAI1), led researchers to discover a novel Nonconsensus XRE (NC-XRE) recognition site which confers to TCDD-AhR complex the possibility to stimulate gene expression independently from the presence of the Arnt [Recently, several genome-wide transcriptional studies have identified numerous AhR target genes that lack the canonical XRE recognition site in the promoters region. Characterization of one of these target genes, i.e., the Plasminogen Activator Inhibitor 1 , activated by TCDD, plays a role in developmental toxicity and hepatocarcinogenecity induced by dioxin . Also, tproteins . Many stproteins ,26.AhR may also interact with the nuclear transcription factor NF-κB (Nuclear Factor kappa-light-chain-enhancer of activated B cells) by regulating inflammation in the lung and other tissues . AhR activation also increases the stability of Nrf2 (Nuclear factor-erythroid 2-related factor 2), a transcription factor which induces the expression of antioxidants and phase II enzymes, i.e., detoxifying enzymes, thus amplifying the induction of genes encoding enzymes involved in the detoxification and the elimination of xenobiotics .The biochemical and toxic effects of TCDD and related compounds substantially vary between different species, strains, target tissue or organ, age, and sex . ExposurAhR/Arnt complex can indeed interact with several cofactors and consequently AhR activity can be modified throughout the cell cycle reflecting the nature of the interaction with each specific recruited cofactor. Cofactors recruitment in both XRE and NC-XRE pathways has a direct impact on epigenetic changes associated with AhR-mediated gene expression. In this review, we will focus on the recent literature dealing with epigenetic mechanisms induced by 2,3,7,8-TCDD, considering three main epigenetic mechanisms, i.e., DNA methylation, histone modifications and non-coding RNAs (ncRNAs).Environmental epigenetics is the study of the molecular mechanisms which takes place between environmental factors and the epigenome capable of altering the biology of organs, tissues and cells, resulting in adaptive evolutionary changes and/or diseases development .Disease susceptibility depends on a complex interplay between the individual genetic profile and epigenetic modulations induced by endogenous or exogenous environmental factors ,33. EpigEpigenetic mechanisms can be summarized in three principal classes depending of the specific mechanism and target see , i.e., DDNA methylation is a covalent modification of DNA by enzymatic addition of methyl groups to the 5-position of cytosine bases. For vertebrates, the CG dinucleotide sequence is one of the principal targets of DNA methylation because it is preferentially recognized by DNA methyltransferases (DNMTs) which use S-adenosylmethionine  as a metIn addition to 5-methylcytosine, mammalian DNA contains also low levels of various modified DNA bases, such as the 5-hydroxymethylcytosine, arising from DNA damage, which are generally eliminated by DNA repair processes. Anyway, Tahiliani et al. discovered the existence of the enzyme TET1 (ten-eleven translocation protein) 5-methylcytosine oxidase catalyzing the formation of 5-hydroxymethylcytosine from 5-methylcytosine .It has been proposed that 5-hydroxymethylcytosine might have a role in direct DNA demethylation. The oxidation of 5-methylcytosine at methylated CpG sites is known to inhibit the binding of the methyl-CpG binding domain of the methyl-CpG binding protein 2 (MeCP2), which is a transcriptional repressor, suggesting a potential regulatory role of 5-hydroxymethylcytosine . MoreoveAnother kind of epigenetic process is histone modifications at specific sites. In eukaryotic cells, genomic DNA is packaged into chromatin by four core histones  and the linker histone (H1). The main chromatin modifications are histone acetylation and deacetylation at specific Lysine residues which dynamically activate or inhibit gene expression remodeling chromatin, thus making accessible or not specific genomic sites.Acetylation usually stimulates gene activity and depends on chemical reactions catalyzed by enzymes i.e., histone acetyltransferases (HATs), histone deacetylases (HDACs) and by acetyl-coenzyme A (AcCoA) ,45. DereHistone phosphorylation takes place principally but not exclusively on serines, threonines and tyrosines in the N-terminal of histone tails. The levels of these modifications are controlled by kinases and phosphatases that add and remove the phosphate groups respectively .Another kind of histone modification is the deimination, a reaction which involves the conversion of arginine in citrulline.Other histones modifications include ADP ribosilation on glutamate and arginine residues, ubyquitilation and sumoylation . The ncRNAs derive from non-coding regions of the mammalian genome which are transcribed and processed into small and large non-coding RNA molecules . ncRNAs miRNAs are small (18–22 nucleotides), highly conserved, ncRNAs synthesized in the nucleus, maturating in the cytoplasm. They regulate gene expression by binding to complementary sequences on target mRNAs determining translational repression or target degradation with consequent gene silencing . The ana−1 of TCDD reduced the colitis symptoms through the activation of the AhR pathway, leading to a differential expression of the pathology-involved genes, i.e., Foxp3 and IL-17. The increased methylation of CpG islands (CpGs) of Foxp3 promoter and the demethylation of CpGs of IL-17 promoter, due to acute colitis induced in C57BL/6 mice, were reversed after TCDD treatment.In the last years, many studies have shown an association between TCDD exposure and altered DNA methylation in mice. Singh et al.  have demFoxp3 promoter and hypermethylation of the IL-17 promoter, as assessed by band intensities of demethylated and methylated primers. Further in vitro experiments with activated T cells from C57BL/6 mice and methylation PCR assays confirmed that TCDD induces partial demethylation in H19 gene was significantly decreased, while the IGF2 gene expression was reduced, but not significantly. Methylation analysis of the H19/IGF2 imprint control region, using bisulfate genomic sequencing, determined that more CpGs from the TCDD-treated group were methylated than those from controls. Furthermore, the 5’ promoter region showed a higher proportion of methylated CpGs in TCDD-treated embryos compared to controls. DNMT activity increased in TCDD-exposed targets, indicating its possible role in altering the methylation pattern after TCDD exposure.Wu et al.  instead DNMT3a, correlated to the over-expression of DNMT3a. Furthermore, the authors noted a significant change in DNA methylation level on gestation day 13.5, resulting from the over-expression of DNMT1 and DNMT3a. These findings suggest that methylation and the over-expression of DNMT1 and DNMT3a could be the epigenetic mechanisms that cause palate malformation in fetal mice induced by maternal exposure to TCDD. In a recent study, Wang and coworkers  investigcfos promoter, while 14 out of the 34 CG sites were hypermethylated in the ahrra promoter [dnmt gene expression [dnmt1 and dnmt3b2 and the down-regulation of dnmt3a1, dnmt3b1 and dnmt3b4 [A couple of recent papers have reported on the toxic developmental effects of TCDD in embryos, larvae and adult zebrafish ,56. BothCyp1a1 proximal promoter (−500 and −420) within 24 h in C57BL/6J mice liver [Cyp1a1 transcriptional activation preceded Cyp1a1 promoter demethylation, indeed Cyp1a1 mRNA was detectable in 6 h, which is earlier than CpG demethylation which was observed 24 h later. The authors observed a gradual decline in 5-methylcytosine and 5-hydroxymethylcytosine at the same CpGs (−420), indicating a progressive demethylation that involved the transition of 5-methylcytosine to 5-hydroxymethylcytosine intermediate typical of the Tet-mediated demethylation process. In support of Tet proteins involvement in Ahr-dependent active demethylation, the authors observed the Ahr-dependent occurrence of Tet3 at the Cyp1a1 promoter. Additionally, Tet2 and Tet3 knockdown suppressed dioxin-induced demethylation in an artificially-methylated promoter. ChIP assay of the base excision repair proteins (BER) revealed that Apex1 and thymine DNA glycosylase (Tdg) also occurred at the Cyp1a1 promoter in an Ahr-directed manner, although only Tdg knockdown inhibited dioxin-induced demethylation of the methylated plasmid [Amenya and coworkers in a recent paper reported that treatment with TCDD induced the demethylation of two CpGs at the The previously mentioned studies, summarized in CYP1A1 and CYP1B1 genes using human breast cancer cell line MCF-7 and Human hepatic cancer cell line HepG2 cells. Chromatin immunoprecipitation assays revealed that 100 nM TCDD increased histone modifications in the promoter regions of CYP1A1 and CYP1B1 in MCF-7 and in HepG2 cells. Histone acetylation was found at the levels of Lys 9 and 14 of histone H3. Trimethylation of H3 and acetylation of H4 at the level of Lys 4 were also found. The extent of each histone modification at the CYP1A1 promoter was greater in HepG2 cells than in MCF-7 cells. On the contrary, the extent of the modifications at the CYP1B1 promoter was much less in HepG2 cells then in MCF-7 cells both before and after dioxin treatment [CYP1B1 promoter as a consequence of the recruitment of transcriptional coactivator p300 responsible for catalyzing direct histone acetylations and thus for contributing to maximal dioxin induction of CYP1B1, as also previously observed [CYP1B1 enhancer. The authors attributed this different behavior to the higher grade of CpGs methylation at the promoter of CYP1B1 in HepG2 cells with respect to MCF-7 cells, which prevent the recruitment of TATA-binding protein (TBP) and RNA Polymerase II [In 2010, Beedanagari et al.  studied reatment . The aboobserved . On the erase II .CYP1A1 promoter in human prostate cell lines PWR-1E and RWPE-1 [CYP1A1 due to TCDD exposure [In a precedent study, Okino et al. demonstrated that TCDD led to the increasing of histone acetylation at H3 and H4 within d RWPE-1 . The autexposure .Recently, Yuan et al. studied the effects of DNA methylation and histone acetylation on TCDD-induced cleft palate in fetal mice (C57BL/6J mice) . Mice weTGF-β3) gene expression, increased HAT activity and H3 iper-acetylation [Their results indicate that TCDD-induced cleft palate at the critical period of palate fusion (gestation days 13.5–14.5) is characterized by increased Transforming Growth Factor β  development. Due to its high-affinity for AhR, TCDD is able to promote a strong AhRC transcriptional activation.RB1 and to test if HDAC8 expression was directly affected by AhR, the authors used hepatocytes isolated from AhR-wild type and AhR-null mice that were treated with TCDD. The authors found increased HDAC8 and decreased Rb1 expression in dioxin-treated AhR-wild type primary hepatocytes but not in those from AhR-null mice, demonstrating the role of AhR in determining HDAC8 over-expression and, consequently, the down-regulation of the tumor suppressor gene RB1. The modulation regulatory effect of RB1 by HDAC 8 was also determined by using hepatoma cells with ectopic HDAC 8 expression but transfected with AHR shRNAi. The hepatoma cells (SK-Hep1) with ectopic HDAC 8 expression reversed the enhancing effects of AHR knockdown on both the expression of RB1 and p53. These very interesting results indicate that HDAC8 is a direct physiological target of AhR and that Rb1 in turn regulates cellular proliferation as a consequence of AhR activation.Very recently, Wang et al.  studied The evidence of histones deacetylation on tumor-suppressive genes suggests that HDAC is involved in tumor formation and progression. Treating hepatocellular carcinoma with HDAC inhibitors can, at least partially, repress tumor proliferation and transformation by promoting the expression of tumor-suppressive genes . It is wp-dioxin resulted in a concomitant recruitment of Carbamoyl Phosphate Synthase 1 (CPS1) to the NC-XRE site in cultured C57BL6 mouse primary hepatocytes [In a recent study, Joshi et al. demonstrated that AhR binding to the NC-XRE in response to 2,3,7,8-tetrachlorodibenzo-atocytes .PADI2), which encodes for the chromatin-modifying protein Peptidylarginine Deiminase 2 (PADI2) [CPS1 is a nuclear protein and in the hepatocytes is responsible for carbamylation (homocitrullination) of a functionally important histone H1 lysine residue (H1K34) implicated in transcriptional regulation. The authors thus demonstrated that homocitrullination is a novel epigenetic mark promoting chromatin remodeling into a more accessible, transcriptionally-active conformation. CPS1 promotes enhanced expression of the Peptidylarginine Deiminase 2 gene ( (PADI2) . PADI2 h (PADI2) . Table 2Few studies concerning the role on ncRNAs in determing epigenic toxicity of TCDD are present in literature. Non-coding RNAs do not contain functional open reading frames, cannot encode proteins, and are transcribed from the entire genome . SeveralIGF2 presented specific embryo age-associated differences during the entire development of the pathology. In particular, the expression levels of lncRNA H19 varied with the stages of TCDD-induced palatogenesis between embrionyc days 13.5 and 15.5, that are important for the development of palate. The authors found that the expression levels of lncRNA H19 in TCDD-treated mice were lower on embryonic days 13.5 and 15.5 compared with those of the control, while a high expression was observed on day 14.5. Therefore, lncRNA H19 is suggested to be the primary contributor to the development of cleft palate induced by TCDD.Recently, Gao et al.  demonstrIGF2 expression levels, i.e., the expression levels of IGF2 gene were found to be higher on embryonic days 13.5 and 15.5, and lower on 14.5, thus showing an opposite expression trend with respect to lncRNA H19. These findings suggest that lncRNA H19 may function through the interaction with IGF2 [Moreover, the same authors observed an inverse correlation between lncRNA H19 and ith IGF2 . Anyway,The number of papers on the roles of ncRNAs is fortunately growing and they will provide new insights into the toxicology induced by environmental chemicals. Different kinds of these environmental pollutants, including organic chemicals , heavy mFurthermore, TCDD-mediated alterations in miRNA expression may be involved in cancer, hepatic injury, apoptosis, and cellular development . From the literature, it is not clear how the toxic effects of TCDD are regulated by certain miRNAs. In particular, the possibility that miRNAs might modulate mRNA levels and consequently TCDD-induced toxicity has not been fully explored and understood. An important study by Tsuchiya and coworkers reported that the lower expression of miRNA-27b due to AhR-regulated genes increased CYP1B1 levels . CYP1B1 Ahr-null mice, in dioxin-sensitive Long-Evans  rats versus dioxin-resistant Han/Wistar  rats and in rat 5L and mouse Hepa-1 hepatoma cells in culture. In another study, it has been reported that treatment with TCDD in vivo caused few changes in miRNAs levels in mouse or rat livers; those changes that were statistically significant were of modest magnitude . The autAhr-null mice compared to mice with WT AHR or between L-E rats (that have WT AHR) compared to H/W rats (whose AHR has a large deletion in the transactivation domain). The authors concluded that it is unlikely that mRNA down-regulation is mediated by dioxin-induced miRNAs and that miRNAs do not play a significant role in dioxin toxicity in adult rodent livers [Treatment with 2,3,7,8-tetrachlorodibenzo-p-dioxin in vivo caused few changes in miRNA levels in mouse or rat livers, and those changes that were statistically significant were of modest magnitude. Hepatoma cells in culture also exhibited few changes in miRNA expression levels in response to TCDD. Only few miRNAs, and especially miRNA 122a, differed in expression between t livers . Thus, iAhR gene. The downregulated expression of these miRNAs suggests that they may be involved in further pathways inducing the AhR in fetal thymi. Similarly, the authors also observed the downregulated expression of some other miRNAs  in fetal thymi post-TCDD exposure. Using the microRNA.org database for the prediction of miRNAs targets, they observed that these miRNAs possessed a highly complementary sequence for the 3′UTR of CYP1A1 gene, which may explain the ability of TCDD to induce CYP1A1 gene through this epigenetic mechanism [Singh and coworkers  demonstrechanism . All theNew studies on the TCDD-induced epigenetic modulation through ncRNAs in vivo and in vitro will have fundamental importance in order to better understand TCDD-mediated toxicity and to find alternative molecular pathways.A growing body of literature is demonstrating the sensitivity of the epigenome to environmental pollutants such as TCDD in a variety of cells, tissues and animal models. Although molecular pathways involved in the alteration of an epigenetic landscape in response to dioxins are largely unknown, several mechanisms of AhR-dependent histone modification, DNA methylation and ncRNAs regulation mechanisms have been described. Epigenetic mechanisms represent an important way through which the genome responds to the environment, leading progressively to permanent changes in gene expression, affecting the phenotypes. It is important to point out that TCDD is usually found in the environment as a component of complex pollutants mixtures, and this situation is far from the laboratory exposure conditions and the evidence from human-based epidemiological observation cannot often be directly related to the results obtained from the animal models. Nevertheless, the development of new sequencing and biochemical techniques are allowing researchers to access the epigenome to understand the interfaces between epigenetics, TCDD exposure and disease-related phenotypes. These new scientific approaches will allow for a systematic analysis of the signaling pathways and molecular mechanisms and how they are linked to environmental exposure. In this frame, further studies are required, not only for the understanding of how environmental signals are translated into epigenetic changes, but also to understand if they are transmitted to the germ-line and thus to the offspring. In particular, it is important to figure out if epigenetic modifications reprogramming is transient, persists or if it is further modified throughout the course of the life of the organism, and how environmental factors are able through germ cell epigenetic modification to be permanently transmitted across the generations. It is worth noting that the three epigenetic mechanisms above described are intertwined and thus are able also to jointly affect transcript stability, DNA folding, nucleosome positioning, chromatin compaction, and ultimately nuclear organization in the framework of very complex interaction networks.For instance, histone deacetylation and methylation at specific amino acid residues contribute to the establishment of DNA methylation patterns. miRNAs expression is controlled by DNA methylation in miRNAs encoding genes, and, in turn, miRNAs have been shown to modify DNA methylation. Future studies that include comprehensive investigations of multiple epigenetic mechanisms might help understand the timing and participation of DNA methylation, histone modifications and miRNAs in determining the environmental effects on disease development.In the last years, a wide range of new molecular biology techniques have allowed for the comprehension of the complex scenario of the epigenetic molecular basis. Among these techniques there are chromatin immunoprecipitation, fluorescent in situ hybridization, methylation-sensitive restriction enzymes, DNA adenine methyltransferase identification (DamID), and bisulfite sequencing. Furthermore, computational epigenetics, taking advantage of bioinformatics methods, will fulfill an important role in unraveling these interlaced molecular networks. An increasing number of clinical and preclinical studies have shown that most of the epigenetic changes are reversible. These findings offer novel insights to develop new preventive and therapeutic strategies taking advantage of molecules that modify the activities of epigenetic-involved enzymes and molecules such as DNMTs and HDACs and of miRNA. Several drugs able to stimulate histone acetylation and DNA hypomethylation have been designed and developed in order to restore the normal transcription level of genes. In this view, future epidemiology studies will have the fundamental role of evaluating the effects of environmental exposure on the epigenome, how these effects are influenced by the interaction with other risk factors, and how they can be mitigated by the correct lifestyles or by new drugs.From a general point of view, future researches should also be addressed to environmental xenobiotics efficient monitoring in order to reduce exposure and to prevent chronic and acute diseases.


Allele-specific transcriptional regulation, including of imprinted genes, is essential for normal mammalian development. While the regulatory regions controlling imprinted genes are associated with DNA methylation (DNAme) and specific histone modifications, the interplay between transcription and these epigenetic marks at allelic resolution is typically not investigated genome-wide due to a lack of bioinformatic packages that can process and integrate multiple epigenomic datasets with allelic resolution. In addition, existing ad-hoc software only consider SNVs for allele-specific read discovery. This limitation omits potentially informative INDELs, which constitute about one fifth of the number of SNVs in mice, and introduces a systematic reference bias in allele-specific analyses.Here, we describe MEA, an INDEL-aware Methylomic and Epigenomic Allele-specific analysis pipeline which enables user-friendly data exploration, visualization and interpretation of allelic imbalance. Applying MEA to mouse embryonic datasets yields robust allele-specific DNAme maps and low reference bias. We validate allele-specific DNAme at known differentially methylated regions and show that automated integration of such methylation data with RNA- and ChIP-seq datasets yields an intuitive, multidimensional view of allelic gene regulation. MEA uncovers numerous novel dynamically methylated loci, highlighting the sensitivity of our pipeline. Furthermore, processing and visualization of epigenomic datasets from human brain reveals the expected allele-specific enrichment of H3K27ac and DNAme at imprinted as well as novel monoallelically expressed genes, highlighting MEA’s utility for integrating human datasets of distinct provenance for genome-wide analysis of allelic phenomena.https://github.com/julienrichardalbert/MEA.Our novel pipeline for standardized allele-specific processing and visualization of disparate epigenomic and methylomic datasets enables rapid analysis and navigation with allelic resolution. MEA is freely available as a Docker container at The online version of this article (10.1186/s12864-018-4835-2) contains supplementary material, which is available to authorized users. BWA and Bowtie2 allele-specific alignment results. (XLSX 49 kb)Additional file 3: Table S2. Human RNAseq, ChIPseq and WGBS allele-specific alignment results. (TXT 6957 kb)Additional file 4:Table S3. List of datasets used in this study and their source. (XLSX 11 kb)


We aimed to elucidate the role and molecular mechanisms of FOXM1 in regulating metastasis in oesophageal squamous cell carcinoma (ESCC) as well as its clinical implications.The expression levels of four isoforms of FOXM1 were analysed by real‐time PCR. Next, genetically modification using overexpression and RNAi systems and transwell were employed to examine FOXM1c function in invasion and migration. Dual luciferase and ChIP assays were performed to decipher the underlying mechanism for transcriptional regulation. The expression levels of FOXM1 and IRF1 were determined by immunohistochemistry staining in ESCC specimens.The FOXM1c was predominantly overexpressed in ESCC cell lines compared to the other FOXM1 isoforms. Ectopic expression of FOXM1c promoted invasion and migration of ESCC cells lines, whereas downregulation of FOXM1c inhibited these processes. Moreover, FOXM1c expression was positively correlated with IRF1 expression in ESCC cell lines and tumour specimens. IRF1 is, at least in part, responsible for FOXM1c‐mediated invasion and migration. Mechanistically, we identified IRF1 as a transcriptional target of FOXM1c and found a FOXM1c‐binding site in the IRF1 promoter region. Furthermore, high expression levels of both FOXM1c and IRF1 were positively associated with low survival rate and predicted a poor prognosis of oesophageal cancer patients.FOXM1c promotes the metastasis by transcriptionally targeting IRF1 and may serve as a potential prognostic predictor for oesophageal cancer. FOXM1b could be SUMOylated at lysine 463, thus promoting breast cancer metastasis.In this study, we investigated the abundance of each FOXM1 isoform in oesophageal cancer cells and found that FOXM1c was the predominant isoform. FOXM1c modulates oesophageal cancer invasion and migration by regulating IRF1 transcription and subsequently MMP2/9 expression. We further observed that both FOXM1c and IRF1 were positively correlated with poor prognosis and low survival rate in oesophageal cancer patients. These findings suggest that FOXM1c and IRF1 may be potential diagnostic biomarkers and drug targets for oesophageal cancer.22.12.Four human ESCC cell lines, KYSE510, KYSE180, Eca109 and TE1, were cultured in plastic flasks as adherent monolayers in RPMI‐1640 medium  supplemented with 10% foetal bovine serum  and 5% penicillin‐streptomycin antibiotics  and were maintained at 37°C in a humidified incubator with 5% CO2.2FOXM1c‐1# and shFOXM1c‐2# Eca109 stable cell lines with 500 ng per well in six‐well plate. RNA and protein samples were collected at 48 and 72 hours post‐transfection, respectively, for further detection.For generation of the overexpression vector of FOXM1c and RNAi vectors of FOXM1c and IRF1, the coding sequence (CDS) and the shRNA sequences of FOXM1c and IRF1 were inserted into the pCDH‐puro and pLKO.1 vectors  and were packaged into lentiviruses. The sequences of the shRNAs of FOXM1c and IRF1 are as follows: sh‐FOXM1c‐1#: 5'‐CCGGGGACCCAGGGTCTCCACAATTCTCGAGAATTGTGGAGACCCTGGGTCCTTTTTG‐3', sh‐FOXM1c‐2#: CCGGATTGCCCGAGCACTTGGAATCCTCGAGGATTCCAAGTGCTCGGGCAATTTTTTG. sh‐IRF1‐1#: 5'‐CCGGGGCTAGAGATGCAGATTAATTCTCGAGAATTAATCTGCATCTCTAGCCTTTTTG‐3', sh‐IRF1‐2#: 5'‐CCGGGGGCTCATCTGGATTAATAAACTCGAGTTTATTAATCCAGATGAGCCCTTTTTG‐3'. Two restoring plasmids with synonymous mutation of FOXM1c in shRNA targets region were designed and constructed using KOD‐Plus‐Mutagenesis kit . pCDH‐puro‐FOXM1c was used as PCR template. Mutation primers were listed as follows: shFOXM1c‐1#‐Restore‐F: 5'‐GCTTCCCGAGCACTTGGAATCACAG‐3', shFOXM1c‐1#‐Restore‐R: 5'‐TGTGGAGACCCTGGGTCCAGTGGCT‐3'; shFOXM1c‐2#‐Restore‐F: 5'‐TTTAGAGTCACAGCAGAAACGACCG‐3', shFOXM1c‐2#‐Restore‐R: 5'‐ TGCTCGGGCAATTGTGGAGACCCTG‐3'. Stable cell lines were established by screening with puromycin at a concentration of 5 μg/mL 48 hours after infection with the lentivirus and confirmed by Western blot analysis. The cells were seeded into six‐well plates in antibiotic‐free medium at 50% density and transfected with the FOXM1c siRNA duplex , IRF1 siRNA duplex  or control siRNA duplex (5'‐UUCUCCGAACGUGUCACGU‐3') oligonucleotides at a final concentration of 20 μmol/L using Lipofectamine 3000  according to the manufacturer's instructions. After 48 hours, cells were collected for qPCR, Western blot and transwell assays. For FOXM1c rescue assay, the restoring plasmids were transiently transfected into sh2.3FOXM1a, FOXM1b, FOXM1c, FOXM1d and IRF1 genes were performed on an ABI Prism 7900 System with SYBR Premix Ex Taq II (TaKaRa). The primers were designed against the region that locates exclusively in each isoforms. And the specificity and amplification efficiency were verified previously.TM Real‐Time PCR software, and the relative expression was analysed using the 2−ΔΔCt method. Three separate experiments were performed.Total RNA was extracted from oesophageal cancer cells using TRIzol reagent (Life Technology). Next, cDNA was obtained from 2 μg of total RNA using a reverse transcription kit . qRT‐PCR analyses of the expression of the 2.4A peptide identical to the FOXM1a/c exon Va‐encoding sequence (HWTQGLHNCPSTWN) was synthesized and then conjugated with keyhole limpet haemocyanin (KLH) as the immunogen. Then, the KLH‐conjugate protein was immunized in Balb/C mice to generate monoclonal antibody (McAb) according to a standard protocol. The specificity of this McAb, termed Va, was verified by Western blotting Figure B.2.5Cancer cells were harvested and lysed with cell lysis buffer  containing protease inhibitor cocktail and phosphatase inhibitor A and B . The Western blot process was conducted according to the standard protocol, and the blots were visualized by an enhanced chemiluminescence (ECL) system. The antibodies against the following proteins were used in the immunoblotting assay: IRF1 , MMP2 , MMP9 , E‐cadherin , vimentin , snail  and β‐actin .2.6TM III  and counterstained with 10% haematoxylin. Finally, slices were dehydrated and mounted with resinene. The staining index (0‐12) was defined as the staining intensity (negative (0); weak (1); moderate (2); strong (3)) multiplied by the proportion of positive staining (0%‐25% (1); 25%‐50% (2); 50%‐75% (3); 75%‐100% (4)). The staining results were scored by two experienced pathologists blinded to the clinical data.Cancer tissues from 120 paraffin‐embedded ESCC patients were obtained from the tissue bank at Fudan University Shanghai Cancer Center, and utilization of samples was approved by the Ethics Committee at Fudan University Shanghai Cancer Center. The ESCC paraffin‐embedded tissues were cut into 5‐μm‐thick slices. The in situ expression of FOXM1c and IRF1 was detected by IHC staining using an anti‐Va antibody and anti‐IRF1  antibody. Briefly, slices were deparaffinized in xylol, heated for antigen retrieval using 10 mmol/L sodium citrate (pH 6.0), treated with 3% hydrogen peroxide to inhibit endogenous peroxidase activity and blocked using 1% BSA/PBS. Slices were put in a wet box and incubated with anti‐Va and anti‐IRF1 antibody at 4°C overnight. Reactions were developed using GTvision2.7NM_002198.2) relative to the transcriptional start site was subcloned into the KpnI and XhoI sites of the pGL3‐basic vector (Promega), using the following primers: forward‐KpnI: 5'‐CGGGTACCCGACCTTGAAAACTACTCAGC‐3' and reverse‐XhoI: 5'‐CCTCTCGAGAAGAGGGAAGAAGGCAGAG‐3'. Four truncated vectors were also established based on potential FOXM1 binding sites predicted in the website https://www.genomatix.de/URLHASH;. All reporter plasmid constructs were verified by sequencing.A 958 bp sequence from −820 to +138 bp of IRF1  (serum‐free medium) with or without a matrigel‐coated membrane for the invasion or migration assays, respectively, following addition of complete RPMI 1640 medium with 10% FBS in the lower well. After culturing for 24, 48 or 72 hours as indicated in the figure legends of Figures For transwell assay, cancer cells were digested and counted after transient or stable transfection and were seeded with 5 × 10For wound healing assays, Eca109 cells were transfected with FOXM1c‐, IRF1‐specific siRNA, or scramble siRNA when the confluency reached 80%. Twenty‐four hours after transfection, cells were digested and plated into six‐well plates with 90% confluency. The next day a wound was created by manually scratching the cell monolayer with a 200 μL pipette tip. The culture medium was discarded, and the plates were washed twice with 0.1 M PBS to remove floating cells and cell debris. The cells were then incubated in RPMI‐1640 medium supplemented with 2% FBS. Cell migration into the wound was observed at three time points  in three randomly selected microscopic fields for each condition and time point. The images were captured using phase microscope and analysed with Image J software  by measuring the wound healing area. The rate of wound healing (scratch closure) = [(wound area at 0 hour − wound area at 24 or 48 hours)/wound area in 0 hour] ×100%.2.9For analysis of the effect of FOXM1c on regulating IRF1 transcription, we employed dual luciferase reporter assays as described previously.2.106) were prepared for ChIP assays using a ChIP assay kit  according to the manufacturer's protocol. The resulting immunoprecipitated DNA specimens were analysed using three ChIP primers to amplify three regions of the IRF1 promoter; the PCR products were 198, 220 and 194 bp. The ChIP primers are as follows: 5'‐GATTTCCCCTGGTCCAGCA‐3' (forward) and 5’‐GAATCTCCCGACTGGCAGC‐3’ (reverse). The PCR products were resolved electrophoretically on a 2% agarose gel and visualized using ethidium bromide staining.ChIP assays were used to identify the physical binding of FOXM1c to the IRF1 promoter. Oesophageal cancer cells (2 × 102.11t test (two‐tailed). All data are shown as the mean ± SD Experiments were repeated at least three times. P values less than 0.05 were considered significant.Statistical evaluation was conducted with SPSS 22.0 . The chi‐square test was used to analyse the relationship between clinicopathological parameters and the expression of CD59. The 5‐year overall survival (OS) and disease‐free survival (DFS) were calculated by the Kaplan‐Meier method, and differences in variables were compared using log‐rank tests. The significance of the in vitro and in vivo data was determined using Student's 33.1Although FOXM1 was highly expressed in oesophageal cancer and correlated with poor prognosis,To further verify the expression of FOXM1c at the protein level, we generated a mouse monoclonal antibody (McAb) directly against the exon Va (thus named Va), which is only contained in FOXM1a and FOXM1c.3.2Given the evidence that FOXM1 coincides with metastasis of breast cancer, pancreatic cancer and prostate cancer,FOXM1c in the above three cell lines. We observed dramatically decreased expression of FOXM1c at both the mRNA and protein levels after FOXM1c knockdown  into the pGL3 vector to generate the reporter pGL3 plasmid. Next, this plasmid was co‐transfected into 293T cells with the pRL inter‐control plasmid and different doses of the FOXM1c‐expressing plasmid. The results showed that the transcriptional activity represented by the relative luciferase activity was gradually elevated by the FOXM1c plasmid in a dose‐dependent manner Figure A. In conTo further determine the FOXM1c binding sites in the IRF1 promoter region, we constructed a series of pGL3 plasmids containing 5' truncations of the IRF1 promoter with different lengths Figure C. These We next performed ChIP assays to further verify the physical binding of FOXM1c to the promoter region identified above. After 293T cells were transiently transfected with the Flag‐FOXM1c‐expressing plasmid, we found that an anti‐Flag antibody but not isotype IgG could effectively capture the binding site of FOXM1c Figure E,F. Ther3.5To investigate the relationship between the expression levels of FOXM1c and IRF1 in clinical specimens, we collected 120 oesophageal cancer samples Table A. The st4FOXM1 produces four isoforms due to alternative splicing. FOXM1a function has been poorly characterized due to its extremely low expression, FOXM1b and FXOM1c mainly regulate oncogene transcription in the nucleus, and FOXM1d promotes cancer EMT and progression via interactions with ROCKs in the cytoplasm.cis‐elements, thus resulting in the different binding transcription factors. AP‐2 and TP53 regulate MMP‐2 transcription, while NF‐κB, PEA‐3 and AP‐1 regulate MMP‐9 transcription.Various MMPs are required in multi‐step processes during tumour metastasis by degrading the extracellular matrix surrounding the tumour.As a transcription factor, FOXM1 regulates many genes that are involved in different stages of cancer, including initiation, progression and metastasis.In summary, we determined that FOXM1c was the predominant isoform among the four isoforms of FOXM1 in oesophageal cancer. Moreover, we unveiled a novel mechanism of FOXM1c in regulating cancer invasion and migration, that is, FOXM1c transcriptionally regulated IRF1 by directly binding to its promoter region, and IRF1 further modulated MMP2/9 expression. Using clinical samples, we further demonstrated the close correlation between FOXM1c and IRF1 expression levels, and their expression levels were highly associated with oesophageal prognosis. These findings suggest the potential of FOXM1c and/or IRF1 as independent prognosis biomarkers or drug targets for oesophageal cancer.The authors declare no conflict of interest. Click here for additional data file.