The Mi-2/nucleosome remodeling and histone deacetylase (NuRD) complex is a multiprotein machine proposed to regulate chromatin structure by nucleosome remodeling and histone deacetylation activities. Recent reports describing localization of NuRD provide new insights that question previous models on NuRD action, but are not in complete agreement. Here, we provide location analysis of endogenous MBD3, a component of NuRD complex, in two human breast cancer cell lines (MCF-7 and MDA-MB-231) using two independent genomic techniques: DNA adenine methyltransferase identification (DamID) and ChIP-seq. We observed concordance of the resulting genomic localization, suggesting that these studies are converging on a robust map for NuRD in the cancer cell genome. MBD3 preferentially associated with CpG rich promoters marked by H3K4me3 and showed cell-type specific localization across gene bodies, peaking around the transcription start site. A subset of sites bound by MBD3 was enriched in H3K27ac and was in physical proximity to promoters in three-dimensional space, suggesting function as enhancers. MBD3 enrichment was also noted at promoters modified by H3K27me3. Functional analysis of chromatin indicated that MBD3 regulates nucleosome occupancy near promoters and in gene bodies. These data suggest that MBD3, and by extension the NuRD complex, may have multiple roles in fine tuning expression for both active and silent genes, representing an important step in defining regulatory mechanisms by which NuRD complex controls chromatin structure and modification status. Chromatin structure is tightly regulated by multiple mechanisms; its dysregulation is associated with developmental abnormalities and disease. The Mi-2/nucleosome remodeling and histone deacetylase (NuRD) complex is proposed to regulate chromatin structure by changing the location and/or the chemical properties of the fundamental building block of chromatin, the nucleosome. NuRD has been shown by genetics to be important for normal development, yet the detailed mechanism of how NuRD regulates chromatin structure is still unclear. Here, we study the localization and function of MBD3, a component of NuRD, in two human breast cancer cell lines using two independent genomic technologies. Our data demonstrate that existing models, which associate NuRD with transcriptional repression, are not completely correct. Rather, MBD3 showed cell-type specific localization at active genes. Moreover, we found a previously unidentified localization of MBD3 across gene bodies and identified a regulatory role for MBD3 in nucleosome organization. Our data provide a reliable starting point from which to address mechanisms by which NuRD controls chromatin structure and nuclear biology. Since its discovery in the late 1990's by a number of investigators, the Mi-2/nucleosome remodeling and histone deacetylase (NuRD) complex has been proposed to regulate chromatin structure and promote transcriptional repression via its intrinsic nucleosome remodeling and histone deacetylation activities bona fide methyl CpG binding protein, mammalian MBD3 has lost the ability to selectively interact with methylated DNA zNuRD complex contains six core subunits which are invariably encoded by 2 or more gene paralogs, prompting the hypothesis that combinatorial assembly of subunits may contribute to functional specificity Chromatin immunoprecipitation coupled to massively parallel sequencing, ChIP-seq, represents ‘gold standard’ methodology to identify sites of enrichment of a particular protein (or modified protein) across the genome. High quality ChIP-seq data are dependent on a number of technical factors, including antibody quality, fixation conditions (where ChIP is performed from fixed chromatin), chromatin shearing or cleavage with nuclease, and stringency of wash conditions for immune complexes. Progress over the last decade has established the principle that conditions that produce high quality ChIP data for one protein may not necessarily be effective for others. Performing ChIP on chromatin regulators, including NuRD complex, is particularly challenging Here we have analyzed human MBD3 localization across the genome using two complementary genomic approaches. We first used DNA adenine methyltransferase identification (DamID), a methodology independent of antibodies, chromatin shearing and other technically challenging features of ChIP. We also performed ChIP-seq studies of endogenous human MBD3 following optimization of antibody, cross-linking and chromatin shearing. The results of these two techniques were in excellent agreement, suggesting they may not be unduly influenced by technical issues. The resulting, composite location analysis revealed unexpected association of MBD3 with the active fraction of the genome. MBD3 localized preferentially to active promoters characterized by histone marks associated with open chromatin and with genomic regions bearing the properties of enhancers, supporting the emerging evidence that models depicting NuRD's principal functions as a component of repressive chromatin require re-evaluation. In addition, MBD3 coated gene bodies of actively transcribed genes, extending to the transcript end site. Conversely, we also observed association of MBD3 with promoters of genes marked by repressive histone marks, albeit not with the frequency of active promoters, highlighting the likelihood that NuRD action is not unidirectional and is context dependent. Finally, the largest category of loci bound by MBD3 has no obvious association with known chromatin features, underscoring the relative dearth of knowledge on NuRD localization and function.We initiated location analysis of MBD3 in human cells using the DamID technique We prepared two biological replicates of Dam alone and MBD3-Dam fusion for each cell line and performed 2 color hybridization using human promoter arrays. The raw data were processed as described in To assess the relationship of MBD3 localization to gene expression and histone modification patterns, we merged the biological replicates for each cell type, binned promoters into 20 bins from −7 to +3 kb relative to transcription start site (TSS), and calculated occupancy for MBD3 and for H3K4me3 (assessed by ChIP-seq) as described in To describe the binding pattern of MBD3-Dam with promoters, we constructed a composite analysis across all promoters (−3 to +3 kb relative to TSS). MBD3 was prominently enriched in two distinct peaks, each about 1.5 kb from TSS, with a prominent dip at TSS in both cell lines . To asceTo develop an understanding of the association of MBD3 with genic regions not represented on the promoter arrays, we performed MBD3 DamID using a tiling array covering human chromosomes 6, 7, and 8. We constructed a gene model see , observiThe association of MBD3 with overlapping, but distinct, genes in MCF-7 and MDA-231 cells suggested that the MBD3-NuRD complex may play a role in cell-type specific patterns of transcription. To address this issue, we performed Functional Analysis using Broad Institute's Molecular Signature Data Base (MSigDB v 3.0). We specifically asked whether the MBD3-NuRD target genes  and ordering genes by MBD3 density. We once again observed a strong association of MBD3 with actively transcribed genes marked by H3K4me3 . As was The ChIP-seq data permitted us to analyze regions not covered in depth by the DamID analysis. We assessed the overlap of MBD3 peaks with genomic features, finding that MBD3 overlapped with promoters (−3 to +3 kb relative to TSS) and with TSS with high frequency . As was We utilized publicly available data from the ENCODE project Given the prevalence of MBD3 peaks in intergenic regions, we asked whether these loci bore chromatin signatures indicative of function. We plotted the distributions of MBD3 and histone modifications (H3K4me3 and H3K27ac) relative to the MBD3 peak center. Non-TSS MBD3 colocalized with H3K27ac but not with H3K4me3, while MBD3 colocalized with both H3K4me3 and H3K27ac around TSS . Thus, nNext, we quantified the overlap of MBD3 with various patterns of histone marks across the genome by dividing the human genome into 1 kb windows and calculating the enrichment for several chromatin marks in each window see . OverallTo clarify whether MBD3 localization has any correlation with DNA modification in this system, we queried DNA methylation status within MBD3 bound regions. In murine ES cells, Yildirim and colleagues suggested a causal relationship between 5-hmC modification and NuRD localization Distal enhancer elements physically interact with promoter regions and these interactions have a major role in gene regulation To extend these observations to the level of the entire dataset, we plotted MBD3 density at TSS for genes with a Pol II ChIA-PET pair anchored at TSS, ranking genes by MBD3 abundance. Display of MBD3 abundance at the distal ChIA-PET pair in the same order revealed that genes with high level MBD3 at TSS tend to have high MBD3 at the distal region defined by Pol II ChIA-PET as being in proximity in three-dimensional space . These dBecause MBD3 is a component of NuRD complex which contains chromatin remodeling factors (CHD3 and CHD4), we hypothesized that MBD3 regulates nucleosome occupancy at its binding sites. To test this hypothesis, we mapped the nucleosome positions in MBD3 depleted and control MCF-7 cells. We verified that MBD3 was efficiently depleted . Native Chromatin regulators are critical integration points wherein biological signals are converted into alterations in gene expression. These protein machines are essential to normal cell function, to development and to differentiation The use of multiple techniques for location analysis of chromatin associated factors provides an opportunity to control for common technical problems inherent to a single protocol. DamID involves expression of a fusion protein that modifies DNA in its genomic vicinity with detection relying on creation of novel restriction sites. It suffers from poor spatial resolution relative to ChIP and the necessity of exogenous expression of a fusion protein that must faithfully recapitulate the biological properties of the unmodified factor. Chromatin immunoprecipitation relies on biochemical fractionation of chromatin, in many cases following fixation. High quality ChIP results are reliant on antibody affinity and specificity as well as on crosslinking conditions and biochemical fractionation methods. Our results using these two techniques are in excellent agreement, suggesting they are converging on a robust genomic location map for MBD3 in the system chosen. Given the poor concurrence and quality issues  of recenLocalization of MBD3 at promoter regions of active genes marked by H3K4me3 was unexpected given biochemical experiments documenting the failure of NuRD to productively interact with H3K4 methylated peptides While association of MBD3 with active promoters was abundant in our data, we also observed accumulation in regions with local chromatin marks diagnostic of transcriptional repression. A significant number of promoters marked by H3K27me3 in MCF-7 cells also bore a peak of MBD3, in agreement with ChIP-seq for CHD4 in murine ES cells The methyl CpG binding domain family is intimately tied to cytosine modification MBD3 locus in uterine serous carcinoma and frequent point mutations in CHD4 in serous endometrial tumors, suggesting fundamental functions of NuRD in primary tumors Collectively, MBD3 localization supports roles for NuRD complex in regulation of chromatin structure and/or protein modification status at promoters of active genes, at enhancers, at stably repressed genes, and in bodies of actively transcribed genes. Functional data reported here document a role for MBD3, and by extension NuRD, in nucleosome organization, a critical determinant of chromatin structure. Further, they predict novel functions that remain to be described. These predictions clearly indicate that models describing NuRD as a static corepressor are inadequate in the face of emerging genomic data. Rather, it seems likely that NuRD is involved at multiple levels in modulation of epigenetic features to facilitate chromatin biology. Recently, whole-exome sequencing revealed high-frequency deletion of a short segment of chromosome 19 containing the MCF-7, MDA-MB-231, and 293T cells were obtained from the American Type Culture Collection and cultured at 37°C, 5% CO2 in Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F-12) Media containing 10% fetal bovine serum supplemented with penicillin-streptomycin.DamID lentiviral vectors, pLgw-RFC1-V5-EcoDam and pLgw-V5-EcoDam were kindly provided by Dr. Bas van Steensel, Netherlands Cancer Institute. Human MBD3 cDNA (BC043619) was amplified and cloned into pENTR/D-TOPO and then recombined by an LR-reaction into destination vector pLgw-RFC1-V5-EcoDam (pLgw-MBD3-V5-EcoDam). Retroviral knockdown constructs, pSMP-Luc (Addgene plasmid 36394) and pSMP-MBD3_3 (Addgene plasmid 36373) were obtained from Addgene. All constructs were verified by DNA sequencing. Lentivirus production and infection were performed as previously described The DamID experiments were carried out as previously described A two-step normalization approach was used, where the first step is designed to correct for GC bias and dye bias within a chip (intrachip correction) and the second step corrects for variations across chips (interchip correction). The first step was within-chip normalization. First, all probes were binned according to their GC content. The GC content was computed as a ratio of C and G nucleotides to the total number of nucleotides in the probe sequence. The overall variability in GC content values was used to compute bin width according to zero-stage rule The second step was between-chip normalization. Once the data were corrected for dye and GC bias as described in the first step, we employed quantile normalization independently for each histone mark and DNA methylation to correct for between-chip variation.w), signal threshold (s) and p-value threshold (p).The differentially bound “peak” regions for each cell type comparisons were identified using modified ACME algorithm that allows for spooling data across replicates x) of signal values within window of size w (centered at probe) that are greater than 100sth percentile across all replicates. Next, we compute enrichment p-value for probe using hypergeometric distribution as followingN denotes total number of probes, k denotes number of probes in window and r denotes the number of replicates.To identify MBD3 bound peaks, we first compute the number (p). The analysis presented here correspond to signal threshold (s = 0.95), window size (w = 2000) and p-value threshold (p = 0.001) with peaks containing less than six probes excluded.Finally, the peaks are identified as runs of enrichment p-values that are less than p-value threshold  and other published Cancer gene sets. The resulting significance p-values were subjected to Benjamin-Hochberg (FDR) multiple test correction.We employed chromosome bound circular permutations test described in The above approach was utilized to assess enrichment/depletion of overlap in significant DamID peaks (modified ACME peaks with at least 6 promoter probes) and MBD3 ChIP-seq peaks .We also utilized the above approach to assess enrichment/depletion of overlap in significant cell specific DamID peaks (uncommon peaks in MCF-7 and MDA-231 cells) with promoter regions (3 kb upstream and 3 kb downstream of TSS) of Luminal vs. Basal breast cancer differentially expressed genes from Charafe et al ChIP experiments for MBD3 were performed as previously described with several modifications MBD3 ChIP-seq and Input libraries were sequenced using Illumina GAIIx technologies at the NIH Intramural Sequencing Center  or using MiSeq technologies at the NIEHS Epigenomics Core Facility (MDA-231 MBD3 ChIP and replicate Input). Standard Illumina CASAVA 1.8 utilities were used to generate .fastq output files. All libraries were sequenced as single end 36mers.6 MDA −231 cells were crosslinked with 1% formaldehyde at 37°C for 10 min. The anti-H3K4me3  antibody was used. The ChIP-seq libraries were prepared from 10 ng of both Input and ChIP DNA samples using a ChIP-seq sample preparation kit (Illumina) according to the manufacturer's protocol.ChIP experiments for H3K4me3 in MDA-231 cells were carried out using a Magna ChIP kit (Millipore) following the manufacturer's suggested protocols. For each ChIP experiment, 5×10MDA-231 H3K4me3 ChIP-seq and Input libraries were sequenced using Illumina GAII technologies at the University of Missouri DNA Core Facility. For these libraries Illumina CASAVA 1.3 utilities were used to generate .fastq output files. All libraries were sequenced as single end 36mers.Public MCF-7 data used for analyses included: H3K4me3 (GSM945269), H3K9me3 (GSM945857), H3K27ac (GSM945854), H3K27me3 (GSM970218), Reduced Representation Bisulfite (GSM683787), and triplicate expression data  and .Sequenced reads from MDB3 ChIP-seq and Input libraries were combined for replicate samples and filtered based on a mean base quality score <20. Filtered reads were then aligned to the human reference genome  using the Bowtie short-read alignment program  to retain reads mapped to unique genomic locations with at most 2 mismatches. Only non-duplicate reads were used in subsequent peak calling analyses and the generation of coverage tracks. To make the coverage tracks, aligned reads were extended at the 3′ end to a length of 300 bases (the expected genomic fragment size), and bigWig files were generated to visualize aggregate genomic coverageMBD3 peaks for each cell type were identified using SICER with a FDR threshold of 0.001 and the following parameters . Basic quality control of MBD3 ChIP-seq data (ours and others) is provided in hg19 RefSeq transcript model definitions were downloaded from UCSC. Transcripts covering duplicated genomic loci [have exactly same transcription start site (TSS) and end site (TES)] were excluded yielding 31,723 RefSeq transcripts. ChIP-seq peaks were defined as associated with genomic features if they intersect at least 1 bp. Genomic features queried included exons, introns, TSS, TES, promoters (+/− 3 kb from TSS), gene bodies (TSS to TES), and intergenic regions (not in gene body).From the set of 31,723 RefSeq transcripts, we selected full-length gene bodies (i.e. from the transcript start to the 3′ transcript end) larger than 2 kb.Read counts were averaged in 70 bp windows for regions +/− 5 kb from TSS. Within the gene bodies, reads were averaged in windows equal to 1% of the gene length. All window read counts were normalized by the total number of bases in each window and the length of the window.The CpG contents and the ratio of observed versus expected CpG dinucleotides were determined in a 1,001 bp window around TSS (+/− 500 bp) as described Heatmaps represent transcript expression, binding profiles of MBD3 and H3K4me3 in MCF-7 and MDA-231 cells at promoter regions (−7 to +3 kb relative to TSS) and are sorted by MBD3 binding profiles. For DamID data, we iteratively filtered genes as followed: 1) Downloaded hg18/refseq gene table from UCSC browser site . 2) 31,451 genes from chr1-22 and chrX and chrY were retained. 3) 24,983 genes with non-missing gene expression signal were retained. 4) 15,292 genes with at least one microarray probe for each TSS bin were retained. 5) 11,872 genes with unique TSS were retained. 6) 8,207 genes with no 7 kb upstream and no 3 kb downstream neighbors were used in heatmap. For ChIP-seq data, we filtered genes as followed: 1) Transcripts with duplicated genome locus were eliminated. 2) Transcripts were selected with a MAD (Mean Absolute Deviation) higher than 1.0, to further eliminate transcripts with low variability around promoter regions in MBD3-binding profiles; 25,569 transcripts (MCF-7) and 23,605 transcripts (MDA-231) were retained and used in the heatmap.Raw sequencing datasets for MBD3 and histone modifications H3K4me3, H3K27me3, H3K27ac, and H3K9me3 from ENCODE were filtered, mapped, deduplicated, and extended (to 300 bp) as described above. RPKM thresholds for establishing presence or absence of each mark were determined following the method described by Whyte et al for detecting super-enhancers Called MBD3-binding peaks in MCF-7 cells were separated according to whether they overlap with a RefSeq promoter region (TSS +/− 3 kb). Then a region with 3 kb flanking the center of peaks was extracted accordingly. Reads from MBD3, H3K4me3 and H3K27ac profiles were averaged in 60 bp windows for the above region and normalized by the total mapped reads.CpG islands annotation was downloaded from UCSC hg19 genome, and CpG islands were separated according to whether they overlap at least 1 bp with the MBD3-binding peaks. Reduced Representation Bisulfite sequencing data in MCF-7 cells (GSM683787) was downloaded and the methylation levels of the CpG islands associated with MBD3-binding peaks were calculated as the follows: percentage of methylation = total sequenced reads being methylated/total reads being sequenced.The interaction dataset, part of the Pol II Chromatin Interaction Analysis with Paired-End Tag data (Pol II ChIA-PET), GSM970209, were downloaded from GEO database. Then the data were filtered to keep the PET pair ends that have at least one end overlapped with the TSS loci (+/− 3 kb). Among the retained PET pair ends, each end in the PET pair ends was examined as follows: 1) Assign the nearest hg19 Refseq gene if this end is overlapped with TSS loci (+/− 3 kb); 2) Assess if this end was overlapped with the MBD3 peaks; 3) Count the reads from MBD3 ChIP-seq data within the region that is 500 bp flanking the center of this end. The reads were normalized to the total mapped reads.The data are displayed as follows: 1) Sort the read number at TSS end of the filtered ChIA-PET pair ends in a descending order; 2) Plot the sorted read number in upper panel: y-axis is the sorted read number and x-axis is the sorted PET pairs; 3) Plot the read number in lower panel: y-axis is the corresponding read number in the other end and x-axis is the sorted PET ends in the same order as in the upper panel.3C experiment was performed as previously described 5 cells and digested by MNase  for 5 min at 37 °C. Mononucleosomal DNA were collected by gel size selection and pooled. Sequencing libraries were prepared from 1 µg of pooled DNA with TruSeq DNA Sample Preparation Kit. The resulting libraries were sequenced on a HiSeq 2000 (Illumina) as paired end 101mers. To ensure that low quality reads were excluded from the analysis, the raw sequence reads were filtered to remove any entries for which either read in a pair had mean base quality score <20. Filtered reads were aligned to the human genome (GRCh37/hg19) via Bowtie (v0.12.8 with parameters -m 1 –best –strata –chunkmbs 1024 -I 0 -X 1000) http://picard.sourceforge.net). To capture only sequenced reads corresponding to the size of a mononucleosome, filtering was applied to retain only fragments 120–180 bases in length; 90–95% of mapped, deduplicated read pairs per library passed this filter. Each mapped read pair was then converted to a single point at the midpoint of the fragment. The two replicate libraries per condition were merged, and ‘bedGraph’ files were generated  as previously described with some modifications Metagene plots of nucleosome occupancy were generated with mapped MNase-seq fragments downsampled to the same read count per condition . Counts per position were aligned relative to each annotated RefSeq TSS, with the RefSeq loci split into quartiles based on the number of MBD3 ChIP-seq reads mapped to the region +/− 3 kb of the given TSS. The positional counts in each dataset (shMBD3 or shLuc per quartile) were normalized by the mean score over the region +/− 5 kb of TSS, then smoothed with a moving average (period = 50).The microarray data and sequence data from this study are available at the NCBI Gene Expression Omnibus (GEO) under accession number, GSE44737, GSE 44776, and GSE51097.Figure S1Validation of MBD3-Dam construct. A. pLgw-MBD3-V5-EcoDam was transfected to HeLa cells and MBD3-Dam protein was detected by anti-V5 tag antibody. B. pLgw-MBD3-V5-EcoDam was transfected to HeLa cells and the localization of MBD3-Dam protein was determined by immunofluorescence using anti-V5 tag antibody. Nuclear was stained with DAPI.(TIF)Click here for additional data file.Figure S2Comparison of DamID and ChIP-seq data. Representative results for CDH1 and PLS3 loci are shown.(TIF)Click here for additional data file.Figure S3Genome browser view of exemplar CpG island promoters that overlap a peak of MBD3. CpG islands are depicted below the tracks. Methylation or hydroxymethylation data  is displayed below the tracks. Color coding of methylation data is indicated in the figure.(TIF)Click here for additional data file.Figure S4MBD3 peaks in intergenic regions are in physical proximity to promoter. Physical proximity of promoter region and distal MBD3 bound sites are detected by Chromosome Conformation Capture (3C) in MCF-7 cells. The promoter region of NRIP1, NR2F2, and MASTL were examined.(TIF)Click here for additional data file.Figure S5Validation of MBD3 knockdown in MCF-7 cells. Western blot shows MBD3 expression levels in control (shLuc) and MBD3 knockdowned cells. Histone H3 is used as a loading control.(TIF)Click here for additional data file.Figure S6MBD3 impacts nucleosome density at bound promoters and gene bodies. TSS's were binned into 4 equal sized bins by MBD3 occupancy level. Nucleosome position and density were plotted as described in (TIF)Click here for additional data file.Table S1Gene set enrichment in cell-type specific MBD3 DamID peaks.(DOC)Click here for additional data file.Table S2DamID vs ChIP-seq peaks comparison. Peak overlap between DamID and ChIP-seq was calculated with chromosome bound circular permutation method see .(DOC)Click here for additional data file.Table S3Gene set enrichment in cell-type specific MBD3 ChIP-seq peaks.(DOC)Click here for additional data file.Table S4Quality control of MNase-seq data.(XLSX)Click here for additional data file.Table S5Quality control of MBD3 ChIP-seq data. Ours and recently published MBD3 ChIP-seq data  were mapped with Bowtie  to identify reads mapped to unique genomic locations.(XLSX)Click here for additional data file.


Hematopoietic differentiation critically depends on combinations of transcriptional regulators controlling the development of individual lineages. Here, we report the genome-wide binding sites for the five key hematopoietic transcription factors—GATA1, GATA2, RUNX1, FLI1, and TAL1/SCL—in primary human megakaryocytes. Statistical analysis of the 17,263 regions bound by at least one factor demonstrated that simultaneous binding by all five factors was the most enriched pattern and often occurred near known hematopoietic regulators. Eight genes not previously appreciated to function in hematopoiesis that were bound by all five factors were shown to be essential for thrombocyte and/or erythroid development in zebrafish. Moreover, one of these genes encoding the PDZK1IP1 protein shared transcriptional enhancer elements with the blood stem cell regulator TAL1/SCL. Multifactor ChIP-Seq analysis in primary human cells coupled with a high-throughput in vivo perturbation screen therefore offers a powerful strategy to identify essential regulators of complex mammalian differentiation processes. ► Genome-wide TF binding analysis in primary human megakaryocyte ► Regulatory network reconstruction from TF, epigenetic, and expression data ► Simultaneous binding of five TFs marks hematopoietic regulators ► Five-factor binding reveals eight genes essential for zebrafish blood development Connectivity in these networks has historically been determined using individual gene-based assays or inferred from expression profiling. However, gene by gene characterization of regulatory elements is slow and inference of regulatory relationships based on variations in gene expression alone cannot readily differentiate between direct and indirect interactions. New genome-wide technologies permit potentially rapid access to all regions bound by a given factor. However, binding of a factor does not necessarily equate with direct regulation of nearby genes. New strategies are therefore required to identify the subsets of binding events that are central to regulatory network function.Complex gene-regulatory networks control all metazoan development . TranscrHematopoiesis has long served as a model process for studying stem cells . One of Being derived from a common precursor, the MK and erythrocyte lineages share a number of TFs critical for their development, including GATA1, FOG1, SCL, and GFI1b. Other factors, like EKLF (erythroid) and GABPα, FLI1, and RUNX1 (megakaryocytic) have been implicated in the bifurcation of these lineages. Analysis of cell-type specific regulatory elements is consistent with the notion that combinations of these TFs constitute lineage-specific regulatory codes. For example, sites for GATA1 and SCL are found in several erythroid specific enhancers  and seveWe have recently reported genome-wide combinatorial interactions for ten key regulators of hematopoietic stem/progenitor cells in the multipotent mouse hematopoietic progenitor cell line 7 (HPC-7) , which r+ hematopoietic progenitor cells  for 10 days in the presence of thrombopoietin and interleukin-1β . We have previously shown that the or cells , and theid cells . As showRUNX1 and TAL1 loci reproduced the PCR results with specific enrichment of the RUNX1 +23 and SCL +40 regions  is bound by all five TFs  GPut GATA2 D; and  was used to map active promoters, histone H3 acetylation (H3acet) for active promoters as well as more distal elements, and trimethylation of histone H3 lysine 27 (H3K27me3) as a mark for repressed chromatin. All three data sets displayed the expected patterns of enrichment A. We theWith analysis of combinatorial binding patterns, gene set enrichment and chromatin analysis all converging on a consistent role for the GATA1/GATA2/RUNX1/FLI1/SCL core circuit within wider MK transcriptional programs, we next developed a regulatory network model  illustraWith all five factors binding together being the most significant combinatorial pattern in our data set A and thenfatc1. Nfact1 was included because even though NFATC1 had been implicated in transcriptional control in lymphocytes   have a role in transcriptional control and 28 (19%) are involved in signal transduction . Fifty-sphocytes , there won (hpf) A as confcd41 expression at 72 hpf in the caudal hematopoietic tissue (CHT) of MO injected fish using the Tg(cd41:EGFP) transgenic line (cd41low and cd41high are considered to be the markers of hematopoietic stem cells (HSCs) and thrombocytes, respectively. For six genes  MO depletion resulted in a severe decrease in the number of thrombocytes and HSCs. Ncor2 depletion resulted in a mild phenotype. Pdzk1ip1l and nfatc1 MO injected embryos showed no change in the number of cd41 positive cells when compared to control embryos. Taken together, in vivo functional validation therefore demonstrated that genes adjacent to DNA sequences concurrently bound by GATA1, GATA2, RUNX1, FLI1, and SCL are highly enriched for previously unknown hematopoietic regulators.To further explore potential hematopoietic functions for the nine candidate genes, we examined nic line   its mammalian ortholog PDZK1IP1  encodes a membrane associated protein shown to modulate the levels of reactive oxygen species  PDZ SCL see A; (3) th SCL see ; and (4)pression . However34+ HPCs  and we hryocytes .Pdzk1ip1 in mouse embryos. As shown in Pdzk1ip1 was expressed in the midgestation mouse embryo both in the dorsal aorta (AGM region) and fetal liver in the hematopoietic domains that also express Scl. Of note, expression in dorsal aorta endothelium and hematopoietic clusters as well as a subset of fetal liver cells was highly reminiscent of the expression pattern previously seen in transgenic mouse embryos with the +19 enhancer fused to an Scl-promoter-lacZ reporter gene  with a lacZ reporter gene knocked into the ATG start codon of Pdzk1ip1  ESCs displayed lacZ staining . By contrast, 7 of 15 transgenic embryos for the promoter/enhancer construct showed staining, with five of seven embryos displaying strong staining in the fetal liver , MO knockdown did not affect wider aspects of morphology, underscoring the hematopoietic specificity of the uncovered phenotypes. Given that seven MOs affected both erythrocytes and thrombocytes, it is possible that at least some of those genes may operate at the level of immature progenitors or blood stem cells. Given the overlap of key transcriptional regulators in MKs and HSCs, potential functions in blood stem cells might perhaps not be too surprising but will require further fine dissection of knockdown phenotypes.Genes next to regions bound by all five factors were highly enriched for known regulators of MK differentiation and/or function. This observation prompted us to investigate the possibility that genes of unknown hematopoietic function with binding peaks for all five factors may also be enriched for the same functional categories. To provide biological insight, genome-scale hypothesis-generating screens such as ChIP-Seq experiments need to be coupled with meaningful assays for downstream functional validation. Here we took advantage of the zebrafish model because hematopoietic control mechanisms are highly conserved between zebrafish and human/mouse, yet only the zebrafish allows relatively high-throughput knockdown analysis in vivo in the context of a whole animal. Coupling the multifactor ChIP-Seq screen with zebrafish in vivo validation allowed us to identify eight regulators of thrombopoiesis and/or erythropoiesis. Of note, none of the MOs caused a lack of blood circulation and at the concentration used, with the exception of two  with 100 ng/ml human TPO (CellGenix) and 10 ng/ml IL-1β (Miltenyi Biotec) and incubated for 10 days. Flow cytometry was performed on a CyAn ADP 9 color (Beckman Coulter) as described , CD14PB , CD15APC  or V450 , CD34PE , CD41APC , CD42aF , CD66PE , and IgGAPC .Cord blood was obtained after informed consent under a protocol approved by the National Research Ethics Service. CD34-positive cells (≥98%) isolated by magnetic cell sorting (Myltenyi Biotec), were seeded at 1 × 10escribed  using th6 cells and anti-GATA1 , anti-GATA2 , anti-RUNX1 , anti-FLI1 , anti-TAL1 antibody  and nonspecific Rabbit IgG . Samples were sequenced using the Illumina GII Genome Analyzer. Sequence data have been submitted to http://www.ncbi.nlm.nih.gov/geo (GEO record GSE24674).ChIP assays were performed as previously described  with 9.4Three peak finding programs , or at splice junctions   . An aliqy RT-PCR . Total Ry RT-PCR . PhotomiPdzk1ip1 KI ESCs a targeting vector was generated by bacterial recombineering (Pdzk1ip1 (containing the ATG site) were substituted by a LacZ reporter gene and a LoxP-PGK-Neo-LoxP cassette. Targeting was determined by Southern blot using 5′ and 3′ probes outside the targeting vector. Targeted cells were transiently transfected with PGK-Cre for deletion of the Neo cassette (Pdzk1ip1 KI ES were differentiated into embryoid bodies as described (To generate ineering  where 13cassette . Pdzk1ipescribed  and staiescribed . For sorescribed . Cells wPdzk1ip1-Pr/Lac and +19/Pdzk1ip1-Pr/Lac transgenic constructs were generated by inserting a 4.5 kb fragment containing the Pdzk1ip1 promoter and a 640 bp fragment containing the +19 enhancer into the pGLac vector. Methods for transgenic mice generation and in situ hybridization are described elsewhere (lsewhere .


Epigenetics is defined as the study of all inheritable and potentially reversible changes in genome function that do not alter the nucleotide sequence within the DNA. Epigenetic mechanisms such as DNA methylation, histone modification, nucleosome positioning, and microRNAs (miRNAs) are essential to carry out key functions in the regulation of gene expression. Therefore, the epigenetic mechanisms are a window to understanding the possible mechanisms involved in the pathogenesis of complex diseases such as autoimmune diseases. It is noteworthy that autoimmune diseases do not have the same epidemiology, pathology, or symptoms but do have a common origin that can be explained by the sharing of immunogenetic mechanisms. Currently, epigenetic research is looking for disruption in one or more epigenetic mechanisms to provide new insights into autoimmune diseases. The identification of cell-specific targets of epigenetic deregulation will serve us as clinical markers for diagnosis, disease progression, and therapy approaches. In. In78]. Histones are conserved proteins that package and organize DNA. These proteins can be grouped in core histones  and linker histones (H1 and H5). The linker histones bind to the DNA by sealing off the nucleosome at the location where DNA enters and leaves . Histones suffer some posttranslational modifications such as lysine acetylation, and methylation, phosphorylation, ubiquitination, SUMOylation, and ADPribosylation. Histone modifications play an important role in transcriptional regulation, DNA repair, DNA replication and chromosome condensation , 81. Of An example of how these modifications affect transcriptional regulation is the histone deacetylation with the association of 5′ methylcytosine in the DNA, which confers a heterochromatin configuration that makes DNA inaccessible to transcription factors. On the other hand, acetylation of histone tails such as lysine acetylation on histone 3 (H3K9) and DNA demethylation causes euchromatin configuration, which is accessible to transcription machinery . It is iNucleosomes are a complex form of DNA packaged by histones. There are nucleosome positioning patterns that play an important role in transcriptional regulation. Depending on how close nucleosomes are to transcription start sites (TSSs), they may block the activators' and transcription factors' access to the DNA strand thus inhibiting elongation of the transcripts. Active gene promoters have a nucleosome-free region at the 5′ and 3′ untranslated region (UTR) to facilitate the assembly and disassembly of the transcription machinery . For examiRNAs are RNAs that are 18–23 nucleotides in length and function as posttranscriptional regulators. They regulate mRNA translation by binding to complementary sequences that are cut or repressed. Many miRNAs are transcribed from intergenic regions or from introns of protein-coding genes and, sometimes, they are expressed at the same time that the protein gene is transcribed. Just a few miRNAs have been located in exons of protein-coding genes. Of all these miRNAs, the intergenic miRNAs are the only ones which have their own gene promoter and regulatory region .The translational repression and target degradation of mRNAs is achieved by the level of complementarity between miRNA strands and the site in the 3′ UTR targets. If there is complete complementation, there will be cleavage of the mRNAs and this will produce degradation. On the other hand, if there is incomplete complementation, translation will be prevented by taking the transcripts into P bodies to keep them silenced using proteins that prevent translation or removal of the cap structure . AnotherAutoimmune diseases are a complex group of diseases that do not have the same epidemiology, pathology, or symptoms but do have a common origin . All autAs was mentioned at the beginning of this paper, DNA methylation is the most widely studied mechanism in autoimmune diseases. Several studies done so far have found that some diseases such as systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) have global hypomethylation in the cells they target in promoter regions of DNA . StudiesITGAL, CD40LG, PRF1, CD70, IFGNR2, MMP14, LCN2, and in the ribosomal RNA gene promoter (18S and 28S) [SLE is a systemic multiorgan autoimmune disease characterized by autoantibody response to nuclear and/or cytoplasmic antigens. Several studies have shown that there is a global hypomethylation of promoter regions, which contain the genes that are overexpressed in the disease such as and 28S) –27. The and 28S) –95.An example of how hypomethylation alters gene expression in SLE is the hypomethylation of the E1B promoter of CD5 in resting B cells. CD5 is a protein found in B cells that serves to mitigate activating signals from the B cell receptor (BCR) so that B cells are only activated by strong stimuli and not by normal tissue proteins. CD5 has two isoforms: E1A that is expressed on the membrane and E1B that is retained in the cytoplasm. The hypomethylation of E1B promoters may be the consequence of a reduced expression of DNMT1. Therefore, there is an increase in the expression of this CD5 isoform that will cause impairment of cell receptor signaling, which will then promote autoimmunity .Another example is in the Lupus like disease caused by procainamide and hydralazine. These two drugs are DNA methylation inhibitors. As a result, they produce hypomethylation of DNA . ProcainRA is a disease characterized by the progressive destruction of joints by invasive synovial fibroblasts. The RA synovial fibroblasts (RASFs) play a major role in the initiation and perpetuation of the disease . They arSome examples of hypomethylation in RA are in CpG islands upstream of an L1 open-reading frame and the Interleukin-6 (IL-6) promoter gene in monocytes. L1 is one of the major classes of repetitive elements that are spread throughout the genome. They are used as markers because they are methylated in normal synovial tissue. In synovial tissue from patients with RA, L1 is hypomethylated as a consequence of reduced expression of DNMTs. This reduction of methylation in inflammatory response promoter genes causes an overexpression of growth factors and receptors, adhesion molecules, and cytokines. In the end, they will cause irreversible phenotypic changes in synovial fibroblasts , 106.κB). However, when there is a downregulation of this protein because of the hypermethylation of its promoter, the RA synovial cell will be resistant to apoptosis [The other example is the hypomethylation in CpG islands within the IL-6 promoter gene in monocytes. IL-6 is a proinflammatory cytokine that participates in B cell response. When this promoter is hypomethylated, there is an overexpression of IL-6 that will cause an overexpression of pro-inflammatory cytokines at the same time. This will be associated with a local hyperactivation of the inflammation circuit . But thepoptosis , 108.T1D is a T-cell-mediated autoimmune disease that develops in genetically susceptible individuals and affects their endocrine pancreas. There are some mechanisms by which epigenetics may play an important role in T1D by modulating lymphocyte maturation and cytokine gene expression and by differentiation of subtype T helper cells ruled by epigenetic controls. In this autoimmune disease, in contrast to SLE and RA, there is a global hypermethylation activity caused by altered metabolism of homocysteine .Glucose and insulin levels are determinants of methylation . They alMS is a chronic inflammatory disease characterized by myelin destruction followed by a progressive degree of neurodegeneration. Recent studies have shown that the promoter region of peptidyl arginine deiminase type II (PAD2) is hypomethylated . PAD2 plSSc is a rare condition of unknown etiology that is characterized by excessive collagen deposits on skin and other tissues with a progressive vasculopathy. In SSc, there is a hypermethylation of CpG islands in the Fli1 promoter, which is a transcription factor that inhibits collagen production. The reduced expression of Fli1 increases collagen synthesis, that will not be balanced by metalloproteinase activity. This promotes collagen accumulation and, subsequently, the tissue fibrosis that is a characteristic of the disease , 118.Histone modifications in SLE have been studied in murine models and in humans. These studies have found that, during apoptosis, histones can be modified to make them immunogenic. It is noteworthy that in the pathogenesis of SLE, antibodies are directed against components of the cell nucleus that are exposed at the cell surface during apoptosis , 120.The nucleosomes, the primary inciting antigen in SLE, are released in patients with SLE as a result of a disturbed apoptosis or an insufficient clearance of apoptotic debris. During apoptosis, the nucleosome is modified, thereby creating more immunogenic epitopes. Subsequently, epitope spreading will lead to the formation of autoantibodies against unmodified chromatin components , 121. HiThere are other studies that have shown a global acetylation pattern of histone H3 and H4 in active SLE CD4+ T cells . Also, mRA synovial tissue is characterized by an imbalance between HAT and HDAC activity. Cartilage destruction is thought to be mediated by matrix metalloproteinases (MMPs) and enzymes from the ADAMTS  family. Many of these genes are regulated by modifications in the chromatin including acetylation of histones –129.α) synthesis , NF-κB, p38 (mitogen-activated protein kinase), toll-like receptors (TLRs), and IL-6  in lymphocytes. This subset of genes includes the and IL-6 . The trapathways , 135.Histone modifications are also among the mechanisms that cause cardiovascular complications in T1D patients. Chemical modification of the H3K4 and H3K9 has recently been found to be related to the gene expression conferred by hyperglycemia. Transient hyperglycemia promotes gene-activating epigenetic changes and signaling events critical in the development and progression of vascular complications. These epigenetic changes are H3K4 and H3K9 methylation in genes associated with vascular inflammation , 137.TCF7L2, ID2, and SOX2 , and this enhancement produces an inhibitory effect on metalloproteinase expression in synovial fibroblasts [κB pathway in monocytes. This miRNA has a strong correlation with the levels of TNF-α and interleukin-17 (IL-17) [miRNAs are also critical for RA pathogenesis . For exaroblasts . In addi (IL-17) , 141. An (IL-17) .Another miRNA implicated in RA is miR-124, which targets cyclin-dependent kinase 2 (CDK-2). In the basal state, CDK2 represses cell proliferation and arrests the cell cycle at the G1 phase, but in pathologic conditions such as RA, its level decreases. miR-124 also targets monocyte chemoattractant protein 1 (MCP-1), which is responsible for mononuclear phagocytes into the joint. Thus in RA, this miRNA increases cell proliferation and MCP-1 production , 143.Currently, many studies have been focusing on miRNAs involved in MS pathogenesis . A recenIn addition, differentially expressed miRNAs such as miR-17-5p, miR-497, miR-193, and miR-126 have been identified in different lymphocyte subsets including CD4+ T cells, CD8+ T cells, B cells, and CD4+ CD25+ Treg cells from patients with MS. Nevertheless, direct involvement and contribution of dysregulated miRNAs in MS has largely remained unknown and needs additional investigation . It is nOther miRNAs such as miR-124, which is expressed in microglia but not in peripheral monocytes or macrophages, are brain specific. Their function may be to reduce activation of myelin-specific T cells with a marked suppression of the disease, which would make it a key regulator of microglia quiescence and a good prognostic factor for MS .α induce the expression of miR-21, miR-34a, and miR-146a in pancreatic islets thus producing beta-cell failure by increasing proinflammatory cytokines [There are few studies related to miRNAs and T1D pathogenesis. But there are some hypotheses that the function of regulatory T cells (Tregs) is influenced by changes in the expression of specific miRNAs . In Tregytokines , 56, 144This syndrome is characterized by the inflammation and dysfunction of salivary and lacrimal glands, which cause dry mouth and eyes. Some miRNAs seem to play an important role in SS: miR-547-3p, miR-168-3p, miR-150, and miR-149 . The firEpigenetic research has grown and is now providing new insights into autoimmune diseases. This is possible thanks to advances in technological development, which are enabling epigenomic analysis on a large scale. This improvement in the genetic field has enabled us to find new causes that may explain the etiology of autoimmune diseases and, once again, has shown us that this group of diseases is not caused by a single altered component.The candidate gene studies have identified a small set of genes that undergo aberrant DNA demethylation and overexpression in SLE and RA, which are the autoimmune diseases that have been the most widely studied in the last few years. This identification of cell-specific targets of epigenetic deregulation in autoimmune rheumatic disorders will provide clinical markers for diagnosis, disease progression, and response to therapies. However, to achieve this, high-throughput approaches are necessary for screening epigenetic alterations in autoimmune diseases related to specific tissue and cell types that are relevant to disease pathogenesis.Once we have mapped all the altered epigenetic mechanisms that produce each one of the autoimmune diseases, even more research can be done on the therapeutic potential of compounds directed against those epigenetic mechanisms. But to do this, detailed human DNA methylomes, histone modification, and nucleosome positioning maps in healthy and diseased tissues are needed.


The core protein (HBc) of hepatitis B virus (HBV) has been implicated in the malignant transformation of chronically-infected hepatocytes and displays pleiotropic functions, including RNA- and DNA-binding activities. However, the mechanism by which HBc interacts with the human genome to exert effects on hepatocyte function remains unknown. This study investigated the distribution of HBc binding to promoters in the human genome and evaluated its effects on the related genes’ expression.Whole-genome chromatin immunoprecipitation microarray (ChIP-on-chip) analysis was used to identify HBc-bound human gene promoters. Gene Ontology and pathway analyses were performed on related genes. The quantitative polymerase chain reaction assay was used to verify ChIP-on-chip results. Five novel genes were selected for luciferase reporter assay evaluation to assess the influence of HBc promoter binding. The HBc antibody immunoprecipitated approximately 3100 human gene promoters. Among these, 1993 are associated with known biological processes, and 2208 regulate genes with defined molecular functions. In total, 1286 of the related genes mediate primary metabolic processes, and 1398 encode proteins with binding activity. Sixty-four of the promoters regulate genes related to the mitogen-activated protein kinase (MAPK) pathways, and 41 regulate Wnt/beta-catenin pathway genes. The reporter gene assay indicated that HBc binding up-regulates proto-oncogene tyrosine-protein kinase (SRC), type 1 insulin-like growth factor receptor (IGF1R), and neurotrophic tyrosine kinase receptor 2 (NTRK2), and down-regulates v-Ha-ras Harvey rat sarcoma viral oncogene (HRAS).HBc has the ability to bind a large number of human gene promoters, and can disrupt normal host gene expression. Manipulation of the transcriptional profile in HBV-infected hepatocytes may represent a key pathogenic mechanism of HBV infection. Hepatitis B virus (HBV) infection is a serious public health threat. Worldwide, more than 400 million people are infected with HBV. Chronic infection is associated with a high risk of potentially life-threatening liver diseases, including hepatitis, cirrhosis, and hepatocellular carcinoma,2. Howevvia binding to the encoded protein and suppressing its activity[One of the possible mechanisms that contributes to malignant transformation involves HBV-encoded trans-activating factors, which influence particular intracellular signal transduction pathways by altering the host gene expression profile in hepatocytes. Severalactivity. Additioactivity, and havactivity. Collectin vivo studies that showed core particles binding specifically to the HBV pregenome and genome, we hypothesized that HBc may also bind specifically to certain human gene promoters, either through its C-terminal functional domain or its N-terminal assembling domain.HBc is the major capsid protein of the virus and self-assembles to form the subviral 30–32 nm nucleocapsid particles, which package the viral polymerase and pre-genomic RNA during RNA replication. The HBc carboxy-terminus contains two nuclear localization signals in regions of arginine-rich sequences, and an SPRRR motif with several serine residues that are targets of phosphorylation. In geneA recently developed high-throughput strategy to perform targeted or genome-wide studies of transcription binding factors is the chromatin immunoprecipitation (ChIP)-coupled DNA microarray analysis. Known as ChIP-on-chip, this technique couples immunoprecipitation of chromatin-bound transcription factors with the identification of bound DNA sequences through hybridization on DNA microarrays. In the Thirteen unrelated patients, including nine males and four females ranging in age from 19 to 55 years-old (mean: 33.5), diagnosed with chronic hepatitis B (CHB) were recruited to our study. Three male healthy blood donors, whose age and gender matched the patient group, were enrolled as controls. The diagnostic criteria of CHB was based on the combination of clinical history, physical examination, imaging and laboratory data, and/or histology, according to the published guidelines of the Chinese Medical Association[A percutaneous liver biopsy was obtained from all study participants by using a 16 G Tru cut soft tissue biopsy needle. A ~176 mg specimen of normal liver tissue was obtained from the three healthy controls. A 9.3 ~ 19.0 mg total weight specimen of benign liver tissue was obtained from each CHB patient through a sequence of two to four biopsies. All liver samples were evaluated by histological examination, and stored in liquid nitrogen until further use. The clinical characteristics of patients and their corresponding biological samples are listed in TableThe hepatocytes isolated from pooled tissue samples  were cross-linked with formaldehyde and subjected to the standard ChIP procedure, as described elsewhere. BrieflyThe precipitated chromatin samples were sent to Kangcheng Biological Engineering Ltd., Comp.  for hybridization to the NimbleGen HG18 RefSeq Promoter Microarray . The immunoaffinity-enriched DNA was amplified for labeling using the GenomePlex® Whole Genome Amplification kit , according to the manufacturer’s protocol. The amplified DNA samples were purified with a QIAquick spin kit . The purified DNA was quantified using a Nanodrop ND-1000 spectrophotometer . For DNA labeling, as previously described, the Nim8 copies/mL) of HBV-infected patients using the standard phenol-chloroform method. Six overlapping regions of HBV genomic sequence were amplified by PCR, and the length of these products ranged from 534 bp to 654 bp. The sequences represent the entire HBV genome, with each two neighboring fragments overlapping by 79–99 bp of sequence  method[The results from the ChIP-on-chip microarray analysis were verified by qPCR. The reaction was carried out using an iCycler iQ real-time PCR detection system and the iQ SYBR Green Supermix detection reagent . Gene-specific primers were designed with the Beacon Designer software  and are listed in Additional file) method. The % iGenomic fragments (250 ~ 500 bp) encompassing a single HBc peak from the promoter region of selected genes were amplified by PCR from human genomic DNA and cloned into pGL3-basic expression vectors   as an internal control for transfection efficiency, using the JetPEI transfection reagent . After 24 hours, cells were collected and luciferase activities were measured using the Dual-Luciferase Reporter Assay system (Promega). Firefly luciferase activities were normalized to the level of Renilla luciferase activity in each transfection experiment. Relative luciferase levels were expressed as the average of three independent experiments performed in quadruplicate.http://www.geneontology.org). Gene pathway analysis was conducted with the Kyoto Encyclopedia of Genes and Genomes (KEGG) collection of online databases dealing with genomes, enzymatic pathways, and biological chemicals[Raw microarray data were extracted as pair files by the NimbleScan software. We performed median-centering, quantile normalization, and linear smoothing by using the Bioconductor packages, Ringo, Limma, and MEDME. The gene ontology (GO) and pathway analysis of promoter-related genes were carried out online . Statistically significant differences among continuous variables between two independent groups were analyzed by the Mann–Whitney test. A We performed ChIP-on-chip analysis with the NimbleGen HG18 RefSeq Promoter Microarray consisting of 18028 of the best defined human transcript-associated promoters. Hepatocytes infected with HBV and expressing HBV core protein were isolated from CHB patients, immunoprecipitated with HBc antibody, and investigated to determine the genome-wide profile of bound host gene promoters. IgG pre-incubated with 100-fold excess HBc antibody was used as a negative control, and immunoprecipitation of hepatocyte cells from healthy individuals was used as a blank control. Meanwhile, no non-specific hybridization signals between the HBV DNA and the chip probes (NimbleGen HG18 RefSeq Promoter Microarray) were detected. The HBV-infected hepatocyte-specific enrichment that was achieved by sequential immunoprecipitations was expected to facilitate a sufficiently comprehensive identification of HBc binding sites, including the relatively weakly bound sites.p < 0.05) , and annotations for molecular functions were found for 2022 (p = 6.4E-11). The biological processes represented within this dataset of putative HBc targets included: metabolic process ; primary metabolic process ; cellular metabolic process ; and biological regulation   and 3.0749 (p = 1.0E − 03), respectively. The ten molecular functions of the encoded gene products that were most represented within the dataset of putative HBc targets are listed in Tablep = 9.7E-13), followed by catalytic activity  and transcription regulator activity . Further analysis suggested that one of the highly enriched gene promoters was related to an encoded protein product with MAP kinase phosphatase activity and another one was related to a protein with acylglycerol O-acyltransferase activity; the fold-enrichment value of these two was, respectively, 3.5303 (p = 1.4E − 03) and 3.4967 (p = 6.8E − 04)  and 7.5542 (p = 2.8E-08), respectively  were immunoprecipitated by anti-HBc, suggesting that HBc physically interacted with each. Moreover, we tested the promoter sequences that were negative in HBc-ChIP-chip screening, such as the promoter of the tumor protein 53 (p53) gene. As shown in FigureIn order to verify the reliability of the ChIP-on-chip results, qPCR was used to detect the promoter sequences of selected genes in ouput DNA fractions from CHB patients and healthy controls. Twelve genes were selected for this analysis based upon known functions in tumor pathogenesis, and included: fibroblast growth factor 4 (FGF4), v-Ha-ras Harvey rat sarcoma viral oncogene (HRAS), mitogen-activated protein kinase kinase 2/MEK2 (MAP2K2), neurotrophic tyrosine kinase receptor 2 (NTRK2), platelet-derived growth factor A chain (PDGFA), platelet-derived growth factor B chain (PDGFB), Ras guanine nucleotide-releasing factor (RASGRF2), wingless-type MMTV integration site family , type 1 insulin-like growth factor receptor (IGF1R), proto-oncogene tyrosine-protein kinase (SRC), vascular endothelial growth factor-B (VEGFB), and vascular endothelial growth factor-C (VEGFC). The results indicated that the promoters of these 12 genes p < 0.0 were immp < 0.05). In contrast, HBc co-transfection led to significantly less expression of HRAS . The HBc co-transfection slightly decreased the transcriptional activity of the PDGFA and p53 genes, whereas no statistical differences were detected .The above results suggested that HBV core protein can bind to host gene promoters, especially those involved in tumor pathogenesis. To investigate whether HBc binding regulated the transcriptional activity of these host cellular genes, reporter-gene expression assays were carried out. The promoter sequences of five genes  with >15% of output to input, and the promoter sequences of p53 as a negative control were selected for cloning into expression vectors and subsequent analysis. The sequences of the above promoters are listed in Additional fileIn our study, we used the GenomePlex® Whole Genome Amplification ChIP-chip analyses and found that HBc can bind to more than three-thousand promoters in the human genome. Among this set of gene promoters, the high CpG density promoters were the most common. By evaluating the corresponding the GO annotations and the KEGG pathways for genes affiliated with each of these promoters, we determined that HBc tended to target the regulatory regions of genes with molecular function and malignant transformation in the liver cell repertoire. These results were consistent with our previous data showing that HBc preferentially binds CpG islands within the HBV covalently closed circular DNA. To our et al. previously identified 1896 of the 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-responsive genes in mouse liver by using microarray analysis[p < 0.05, compared with control). Moreover, 2883 of 3100 gene promoters were found in all of the four pooled samples investigated by ChIP-on-chip, which indicates that this approach has a good level of repeatability and the reliability. In our study, arrays representing 18028 promoter regions and CpG islands of the whole human genome were used in combination with HBV HBc-based ChIP to identify putative targets of this viral factor. We also identified 266 HBc-bound gene promoters that were different among the four pooled samples. Such apparently inconsistent findings may reflect background differences among the pooled ChIP samples. We found it necessary to use pooled samples for the ChIP-on-chip assays since none of our ChIP samples provided enough DNA for genomic microarray analysis. The practice of pooling ChIP samples for ChIP-on-chip is very common, but is known to produce very high background when the samples are analyzed on genomic tiling arrays[bona fide target of HBc and was used as a positive control in our study[The ChIP technique has proven to be a powerful tool for detecting protein-DNA interactions in living cells, and it is currently the gold standard procedure for identifying target genes of a given transcription factor of interest. Over the last several years, great strides have been made in expanding the use of ChIP from a one gene-at-a-time approach to a global type of analysis by hybridizing samples to genomic microarrays . In suchanalysis. Most reanalysis. Using Canalysis. Consistg arrays. To veriur study,14.in vivo, we have yet to determine the mechanisms mediating this binding specificity. However, based on the fact that HBV core particles specifically bind to the HBV pregenome or genome in vivo, we inferred that the binding specificity to the human genome might be mediated by the C-terminal arginine-rich domain, along with other regulatory regions in the N-terminal assembly domain. Previous studies have shown that a signal for nuclear transport is located near the carboxy termini of HBc, in the arginine-rich domain. This signal is comprised of a set of two direct PRRRRSQS repeats and is highly conserved among mammalian hepadnaviruses[The underlying mechanisms of the interaction between HBc and the human genome are poorly understood. HBc is a 183 residue protein with two domains: the N-terminal 144 amino acid domain that is sufficient for self-assembly into capsid particles, and the C-terminal arginine-rich domain, which shares a high similarity to protamine and functions as a nucleic acid-binding domain,30. Althaviruses. Recentlaviruses. In addiaviruses, which set al.[Previous studies have shown that HBV DNA integration and/or expression of HBV proteins may have direct effects on host cellular functions. Howeveret al. examinedIt is likely that HBc binding does not exert significant regulatory effects on every gene for which its promoter is bound. For some or many genes, HBc may merely mediate a slight modulation of the transcriptional activity. However, the cumulative effect of slight transcriptional modifications across the genome may impact overall cellular function. In our study, we found that HBc can bind to 64 gene promoters of the MAPK pathways, and 41 gene promoters of the Wnt/β-catenin signaling pathways. These two pathways are known to be critically involved in the development of HBV-related hepatocellular carcinoma. The MAPK pathways regulate a variety of normal human cellular activities, including proliferation, differentiation, survival, and death. As such, the components of MAPK signaling play a key role in several steps of tumorigenesis, including cancer cell proliferation, migration, and invasion. MeanwhiWe investigated the functional relevance of HBV core protein binding to five of the genes whose promoters were identified in the ChIP-on-chip analysis. Transcriptional activity assays indicated that SRC, IGF1R, and NTRK2 genes were up-regulated by more than 2-fold when co-transfected with HBc. The HRAS gene, however, was down-regulated in the presence of HBc. SRC is the best characterized member of the family of nine tyrosine kinases that regulates cellular responses to extracellular stimuli, and activated mutants of SRC are oncogenic. Among tIn conclusion, regardless of the mechanisms, the data of our study clearly demonstrate that HBc not only has the ability to bind to a large number of gene promoters in the human genome, but also has the ability to disrupt cellular gene expression of HBV-infected hepatocytes. Although further studies are needed to investigate the possible role of HBc in regulating the transcriptional activity of all cellular genes that HBc can bind, our study provides key insights into the detailed factor(s) and step(s) that HBc works through, or that work through HBc, to regulate host gene transcription. This information provides a new perspective towards understanding the mechanisms of HBV-related liver diseases, such as liver chronicity, fibrogenesis, and carcinogenesis. Manipulation of the transcriptional profile in HBV-infected hepatocytes may represent a key pathogenic mechanism of HBV infection.The authors declare that they have no competing interests.YG designed this study, performed the ChIP experiment, reporter gene analysis, and statistical analysis, and prepared this manuscript. WK and YL collected clinical samples and patient information. WK examined the HBV DNA level and HBV indexes from serum samples and also revised the manuscript. XL and AX performed the qPCR experiment and analyzed the data. YL, JZ, and JZ participated in the reporter gene analysis. ZY helped with manuscript revision. All authors read and approved the final manuscript.This study was supported by grants from the 11th Five-Year Plan of China: the Project for Prevention and Treatment of AIDS, Viral Hepatitis and Other Major Infectious Diseases (No. 2009ZX10004-311-004), the Natural Science Basic Research Program of Shaanxi Province of China (No. 2009JM4005) and the National Natural Science Foundation of China (No. 31271394).Primers of HBV DNA for PCR amplification and PCR products.Click here for filePrimers of qPCR.Click here for fileThe location and sequence list of promoters which were detected by qPCR to verify the reliability of the ChIP-on-chip results.Click here for fileThe Results of ChIP-on-chip analysis.Click here for fileThe Result of pathway analysis.Click here for file


Myofibroblasts (MFBs) are smooth muscle-like cells that provide contractile force required for tissue repair during wound healing. The leading agonist for MFB differentiation is transforming growth factor β1 (TGFβ1) that induces transcription of genes encoding smooth muscle α-actin (SMαA) and interstitial collagen that are markers for MFB differentiation. TGFβ1 augments activation of Smad transcription factors, pro-survival Akt kinase, and p38 MAP kinase as well as Wingless/int (Wnt) developmental signaling. These actions conspire to activate β-catenin needed for expression of cyclin D, laminin, fibronectin, and metalloproteinases that aid in repairing epithelial cells and their associated basement membranes. Importantly, β-catenin also provides a feed-forward stimulus that amplifies local TGFβ1 autocrine/paracrine signaling causing transition of mesenchymal stromal cells, pericytes, and epithelial cells into contractile MFBs. Complex, mutually interactive mechanisms have evolved that permit several mammalian cell types to activate the SMαA promoter and undergo MFB differentiation. These molecular controls will be reviewed with an emphasis on the dynamic interplay between serum response factor, TGFβ1-activated Smads, Wnt-activated β-catenin, p38/calcium-activated NFAT protein, and the RNA-binding proteins, Purα, Purβ, and YB-1, in governing transcriptional and translational control of the SMαA gene in injury-activated MFBs. Among these factors, the leading agonist for MFB differentiation is transforming growth factor β1 (TGFβ1), deposited by injured epithelial and endothelial cells as well as immune cells that infiltrate sites of tissue damage and inflammation. Via rate-limiting, receptor-regulated Smad 2/3/4 nuclear proteins, TGFβ1 activates transcription of genes encoding smooth muscle α-actin (SMαA) and subunits of type I interstitial collagen that are prototypical phenotypic markers for MFB differentiation. Importantly, non-canonical, Smad-independent TGFβ1 signaling additionally activates pro-survival Akt kinase and p38 MAP kinase. Inhibition of GSK3β kinase by activated Akt prevents β-catenin degradation that may be especially important for activating β-catenin-dependent genes such as cyclin D, laminin, fibronectin, and metalloproteinases needed for epithelial cell proliferation, migration, and restoring adhesion of repaired cells to the basement membrane. Importantly, β-catenin occupies a pivotal position in a feed-forward regulatory loop that can enhance expression of TGFβ1 agonist and augment TGFβ1 receptor regulated canonical and non-canonical signaling in injured epithelial cells and mesenchymal stromal cells. While EMT-associated β-catenin signaling can explain transient acquisition of mesenchymal cell-like behavior by damaged epithelial cells, there must be concurrent mechanisms for the specific activation of SMαA and collagen promoters in nearby mesenchymal stromal cells and pericytes, and possibly epithelial cells, to allow their transition into contractile, force-transducing MFBs. This aspect of molecular control will be reviewed with an emphasis on the dynamic interplay between multiple nuclear and cytosolic proteins that collaborate in governing expression of the SMαA gene in injury-activated MFBs.Myofibroblasts (MFBs) are smooth muscle-like cells that provide the contractile force required for tissue repair and remodeling during wound healing. Although transient in the context of normal tissue repair, dysfunctional MFBs that escape clearance and accumulate in healing tissue is a leading cause of chronic fibrotic disease in the cardiopulmonary, renal, and hepatic systems. MFBs arise in proximity to injured epithelial and vascular endothelial beds and have a temporal relationship to the cellular developmental process referred to as epithelial-mesenchymal transition (EMT) required for repair of denuded or damaged basement membranes. Results of lineage-fate mapping studies suggest that MFBs arise TGFβ1 is an essential mediator of MFB differentiation. Wound healing is a complex series of innate-immune responses that have evolved to limit blood loss while sanitizing and physically repairing sites of tissue injury. A provisional matrix constructed of fibrin protein is established by thrombosis very soon after traumatic injury that stanches blood loss and provides a protein-matrix substrate for infiltration of immune cells needed to combat microbial contamination and initiate tissue reconstructive processes [cis-regulatory elements in promoters required for transcriptional activation of genes encoding SMαA [rocesses ,3,4. Immrocesses ,6. Conforocesses ,8. Of parocesses ,10 in parocesses  bind coging SMαA ,13,14 aning SMαA ,16. MFBsing SMαA ,17,18 reConsequences of MFB dysfunction. While SMαA-positive MFBs evolved as transient and beneficial participants in the wound-healing process, chronic MFB differentiation can damage healthy parenchymal tissue in what has been referred to as the medical syndrome of “endless healing” [healing” . There ahealing” ,21,22,23healing” ,25. Excehealing” ,30,31,32healing” ,36,37,38healing” ,39. SMαAhealing” ,41. Therhealing” .The origins of MFBs. Published reports suggest multiple cellular origins for the MFB lineage including resident stromal fibroblasts or progenitor-like cells, circulating fibrocytes migrating to sites of tissue injury following their birth in the bone marrow, and mesenchymal cells arising nearby or directly from injured epithelial or endothelial cell monolayers through the embryologic process referred to as epithelial-  mesenchymal transition (EMT). The cellular, molecular, and developmental details of EMT pathobiology are complex and will not be reviewed in this article. The reader is directed to excellent overviews of EMT in the recent biomedical-research literature that are especially informative with respect to the cellular biology of wound healing in the pulmonary and renal systems [ systems ,24,42,43SMαA gene activators and repressors. With specific regard in this review article to operation of the mammalian SMαA gene, multiple transcriptional regulatory proteins along with their cognate binding sites within promoter DNA have been identified that respond to biomechanical and metabolic signals generated as a consequence of tissue injury. The mechanism for regulation of the SMαA promoter is based on combinatorial interaction of two primary activating systems under control of constitutively expressed proteins including transcriptional enhancing factor 1 (TEF1), serum response factor (SRF), and specificity proteins 1 and 3 (Sp1/3) plus one or more rate-limiting proteins including the TGFβ1 receptor-regulated Smad proteins 2, 3 and 4, myocardin-related transcription factor A (MRTF-A), and calcium/calcineurin-regulated nuclear-factor-of-activated T-cell protein (NFAT). Operating in opposition to these trans-activator proteins is a set of SMαA gene repressor proteins first described by the Getz, Strauch, and Kelm investigative teams [trans-activators  has high affinity for pyrimidine sequences in the SMαA promoter. We have shown that competitive interplay between the TEF1 activator and Purα/Purβ/YB-1 repressors can regulate transcription from a region of the SMαA promoter called MCAT/THR that contains an inverted repeat with a high potential to form single-stranded loops within a thermodynamically favorable  cruciform structure  located in the center of SPUR represents a core Sp1-binding site absolutely required for MFB SMαA gene expression in vitro and in vivo [de novo activation of the SMαA promoter in quiescent stromal fibroblasts possibly by neutralizing and/or displacing pre-bound Pur protein repressors in this segment of DNA. In this regulatory model, Smads occupy and collaboratively activate the SMαA promoter at two sites: the upstream MCAT/THR region mentioned earlier and the downstream SPUR site. Two other SMαA gene repressors, Egr-1 and KLF4, may assist Pur proteins with preventing activator interaction with the promoter by competing with Sp1 for the TCE site within SPUR DNA [Although not identified on the basis of reactivity with single-strand specific chemical modifiers, another region of duplex DNA in the SMαA promoter also is affected by TGFβ1 in a manner that alters Pur protein repressor interaction with the Sp1 promoter . Notably in vivo ,48,61,62 in vivo . One pro in vivo . In thisSPUR DNA ,63.in vivo proof-of-principle, dynamic interplay of SMαA gene transcriptional activators and repressors was operative during the development of TGFβ1-associated chronic graft fibrosis after murine heterotopic heart transplant [trans-activators by Pur protein repressors was reduced in protein extracts prepared from explanted heart grafts in parallel with development of left ventricular fibrosis, which is a hallmark of chronic rejection pathobiology. However, in the heart graft model, SRF rather than Sp1 was the trans-activator targeted by Pur protein repressors [As ansplant ,64. Sequpressors . Along wpressors ,65,66,67pressors . The abiEpigenetic control of SMαA gene expression. Not much is known about the direct influence of small non-coding RNA molecules on SMαA transcription factor functionality in MFBs nor is it clear if epigenetic modulators that alter DNA methylation, histone acetylation, and protein phosphorylation oversee dynamic changes in chromatin structure encompassing the SMαA promoter locus. Some details are emerging, however, showing that expression of certain microRNA species (miRs) during liver fibrosis can alter Smad4 levels that could impact SMαA promoter activity in MFBs [ in MFBs . Additio in MFBs . In part in MFBs . Althoug in MFBs . These fThe G-actin pool provides feedback control of SMαA gene transcription. SMαA gene transcription driven by TGFβ1-regulated Smads can be enhanced during MFB differentiation by collateral signaling generated by increased G-actin monomer polymerization [N-terminal region consisting of a basic amino acid region, a short α-helical region, and a Glu-rich domain. A key feature of actin-mediated SMαA promoter activation is the shuttling of MRTF-A into the nucleus in parallel with its dissociation from G-actin monomers that become depleted by the burst of F-actin polymerization during MFB activation. MRTF-A contains at least one and as many as three Arg-Pro-X-X-X-Glu-Leu (RPEL) motifs near the N-terminus that mediate physical interaction with G-actin [rization ,66,71,72 G-actin ,74,75. P G-actin . The seq G-actin . Both th G-actin ,77, may Smads fine tune SRF-mediated transcription. G-actin physically sequesters MRTF-A and precludes formation of an essential nuclear trans-activation complex with SRF. Accordingly, activation of SMαA gene transcription can proceed, in theory, via biomechanical signaling alone simply mediated by changes in the rate of G-actin polymerization and expansion of the actin cytoskeleton during MFB differentiation. This mechanism is less dependent on availability of paracrine factors in the wounded area such as TGFβ1, although this growth factor certainly can initiate MFB differentiation and amplify the overall response. Elberg and co-workers reported that TGFβ1 did not have a discernable effect on MRTF-A expression or nuclear compartmentalization [et al. reported that physical interaction between Smad3 and SRF is, in fact, required for TGFβ1-dependent activation of the gene encoding SM22α, also known as transgelin, a 22 kDa protein that shares sequence homology with calponin and bundles F-actin to facilitate the formation of stress fibers needed for MFB contractility [trans-activators [lization . MRTF-A lization ,79,80. Aactility ,82.Kapusactility ,79. Quittivators ,34,48.Mechanotransduction influences SRF-mediated transcription. MRTF/SRF signaling is a useful checkpoint device during wound healing that puts SMαA gene transcription under direct control of actin filament assembly required for MFB contractility. In this regard, we and others have determined that up-regulation of SMαA protein expression in stromal fibroblasts can occur in the complete absence of TGFβ1 signaling simply in response to substrate conditions that are favorable for assembly of actin stress fibers. An interesting report by Sandbo et al. outlines a triphasic model for MFB differentiation that involves aspects of both transcriptional and post-transcriptional control [de novo transcription of the MRTF-A gene possibly driven by SRF itself and not dependent on Smad signaling per se [et al. [via its cognate PAR1-dependent GPCR signaling [ control . An initg per se . In thisg per se ,85,86,87 [et al.  may be fignaling  can bothignaling ,90. FollRegulation of actin filament dynamics specifically required for MFB contractility seems to have evolved in parallel with signaling mechanisms that communicate biomechanical information from the extracellular milieu directly to the SMαA gene transcriptional machinery via the integrin family of matrix protein receptors ,92. AccoCell surface injury diversifies Smad protein interactions in MFBs. While TGFβ1-regulated Smad proteins directly activate the SMαA promoter, their ability to interact with other signaling proteins that accumulate during EMT suggests that their function can be shaped to perform other tasks during MFB differentiation not necessarily related to the biogenesis of a specialized contractile apparatus. During pulmonary EMT, a nuclear-protein complex is formed between TGFβ1-regulated Smad2 and a tyrosine-phosphorylated form (Y654) of the β-catenin transcriptional regulatory protein that is the primary downstream mediator of Wingless/int (Wnt) developmental signaling [ignaling . Formatiignaling ,95. Actiignaling ,79.In damaged epithelial cells, nuclear β-catenin activates the T-cell factor 1/lymphoid enhancer factor 1 (TCF1/LEF1) regulatory complex required for mobilizing transcription of genes encoding a variety of basement membrane-repair proteins . ConvergNovel regulation of SMαA promoter activity by crosstalk between Smad3 and β-catenin. Among the genes that can be activated by β-catenin signaling are those related to basement membrane repair, cell migration, and angiogenesis such as fibronectin, laminin-γ2, matrix metalloproteinases, versican, and VEGF. As mentioned earlier, corresponding stiffening of the local extracellular matrix due to ongoing deposition of collagen and fibronectin can influence actin cytoskeleton dynamics and directly drive MRTF/SRF-mediated activation of the SMαA promoter potentially obscuring any separate contributions provided by nuclear β-catenin or β-catenin:Smad complexes. Authentic binding sites for the β-catenin-dependent TCF1 and LEF1 transcription factors presumably are absent in the SMαA and COL1α2 promoters and neither gene is listed in the Stanford University DNA-sequence compilation of canonical Wnt/β-catenin signaling targets [trans-activation potency of Smad2, Smad3, and/or MRTF within the SMαA promoter by forming physical complexes with these or other transcriptional regulatory proteins subsequent to TGFβ1 activation. In this regard, two recent reports have highlighted the potential importance of EMT-associated accumulation of nuclear β-catenin in injured pulmonary [trans-activator availability by preventing the Smad3-mediated recruitment of GSK3β that regulates MRTF ubiquitination and degradation. In this capacity, β-catenin operates as a de-repressor in renal epithelial cells through its ability to form an off-DNA complex with Smad3 that would otherwise limit the extent of SRF-mediated SMαA gene activation by eliminating MRTF. Whether similar strategies are operative in mesenchymal stromal cells, pericytes, or epithelial cells in the context of MFB differentiation and fibrosis will be important subjects for further research inquiry. targets . Neverthulmonary  and renaulmonary  especialulmonary . DisruptA different approach reported by Borok and co-workers showed that physical interaction between SMαA promoter DNA and a ternary complex of β-catenin, Smad3, and CBP (a cyclic AMP-responsive element-binding protein (CREB)-binding protein) was sufficient to mediate SMαA expression in TGFβ1-activated rat RLE-6TN pulmonary epithelial cells . InteresEpithelial-mesenchymal “interaction” is distinct from epithelial-mesenchymal “transition”. While epithelial cells in tissue culture microenvironments appear to be capable of expressing SMαA protein in the context of EMT-associated injury, it also is important to note that canonical Wnt signaling via the GSK3β/β-catenin/TCF1/LEF1 axis has been shown to directly activate TGFβ gene transcription [cription . In naticription . But perRecent reports highlight the complex relationship between Wnt and TGFβ1 signaling pathways that transpire in both epithelial cells and stromal fibroblasts in the context of chronic fibrotic disease. For example, the Wnt ligands Wnt5a and Wnt3a activate TGFβ1 signaling in both embryonic fibroblasts  and inteWound healing agonists augment intracellular calcium. Tissue-specific transcription of the mammalian SMαA promoter in vascular and enteric smooth muscle cells as well as differentiated MFBs depends on the presence of an intact intron 1 sequence containing tandem SRF, nuclear factor of activated T cells (NFAT), and AP1 transcriptional activator protein-binding sites [trpc6 gene product required for calcium influx, calcineurin/NFAT interplay, NFAT nuclear translocation, and transcriptional synergy with SRF within the first intron of the SMαA promoter. Calcineurin-dephosphorylated NFAT has rather weak affinity for its AGGAAA consensus sequence  and requires SRF binding to an adjacent CArG box  to activate target gene promoters [ng sites ,108,109.ng sites . Calcineng sites ,111. Centrpc6 gene have an impaired wound healing response, calcium agonists appear to elicit different responses depending on the tissue source used for MFB isolation [12/13 signaling but subsequent up-regulation of the TRPC6 gene by the same G protein species increased basal calcium influx activity yet blocked MFB accumulation [While fibroblasts lacking the solation ,111,112.Calcium-dependent and -independent modes of SMαA transcriptional control. Signaling related to regulation of calcium homeostasis may have complex effects on genes required for MFB differentiation owing to its essential role outside the nuclear compartment in controlling actin-based contractility and integrin-mediated cell adhesion. As reviewed earlier, actin filament dynamics and cell adhesion directly influence SMαA gene transcription via the MRTF/SRF promoter-activating complex. Calcium control of NFAT/SRF interplay at the intronic AGGAAA/CArG site may operate in parallel with the calcium-insensitive MCAT/THR and CArG box B elements located in the SMαA 5'-flanking region [g region ,107. Howg region , angioteg region ,113, endg region  as well g region  that allg region . This obg region , or enhag region .Non-canonical TGFβ1 signaling in MFBs is provided by p38 MAP kinase. Not withstanding the controversy regarding the precise role of calcium and NFAT in mediating SMαA gene transcription during MFB differentiation, evidence presented by Molkentin and co-workers provides compelling evidence that p38-mediated calcineurin expression seems to be necessary for proper healing of dermal wounds in mice [per se, was inhibited by deletion of the primary p38 target , it is As a final note, in a manner similar to biomechanical-stress injury caused by deposition of rigid scar tissue, hyperosmolarity in kidney tubule epithelium alters actin cytoskeleton dynamics that results in cell shrinkage and shape deformation. Interestingly, p38 MAP kinase in hyperosmotic stress-injured epithelial cells functions as a transcription antagonist and seems to enhance proteosomal degradation of nuclear MRTF needed for SRF-mediated activation of the SMαA promoter . ParadoxThrombin regulates SMαA mRNA translation in MFBs. Along with the regulation of G-actin polymerization, there is another equally important post-transcriptional mechanism for governing SMαA protein expression in MFBs that operates at the level of mRNA translational control. Pro-fibrotic mechanisms that drive tissue repair after traumatic injury have developed under strong evolutionary pressure to rapidly stanch blood loss, close open wounds, and restore capillary beds needed for oxygen delivery. Accordingly, accumulation of SMαA mRNA in the cytosol may increase wound repair efficiency by providing priority access to polysomes for rapid translation and localized deployment of the actin cytoskeleton required for MFB contractility. Further supporting the notion of “fast-track” control over the MFB differentiation process, TGFβ1 is abundantly stockpiled in the extracellular space in a latent state awaiting rapid activation at the moment of tissue injury by the combined action of proteolysis and integrin-mediated mechanotransduction. During periods of ischemic stress associated with wound healing and tissue remodeling subsequent to myocardial infarction, IPF, cirrhosis, and renal allograft vasculopathy, there also appears to a mechanism that allows for preferential translation of mRNAs encoding proteins required for cellular adaptation to low-oxygen conditions [nditions ,118.de novo transcription of the SMαA gene, thrombin augmented SMαA mRNA translational efficiency [Thrombin is a ubiquitous serine protease that not only initiates the enzyme cascade responsible for blood coagulation but also activates stores of latent TGFβ1 and mediates MFB differentiation and tissue remodeling in both native and transplanted heart, lungs, and kidneys ,121,122.ficiency . Thrombificiency . Likewisficiency . In thisficiency . The datCoordination of SMαA transcription and translation in MFBs by an mRNA shuttle. The release of YB-1 from SMαA promoter DNA coupled with its ability to bind SMαA mRNA and shuttle between the nucleus and cytosol is suggestive of a regulatory loop for coordinating SMαA gene output in MFBs at both the transcriptional and translational levels. YB-1 is known to influence mRNA function in several ways including unfolding secondary structural elements in mRNA as well as recruiting other proteins required for ribonucleoprotein (RNP) packaging, transport, turnover, and/or translation [nslation ,126,127.nslation ,130,131.nslation . Moreovenslation . On the nslation ,57, othenslation  and MMP-nslation  are actiRegulatory-protein interplay in the nucleus and cytosol. Purβ is a single-strand specific DNA-unwinding protein previously shown to bind and inhibit the SMαA promoter during arterial smooth muscle phenotypic modulation [dulation ,45,46. Pdulation ,128. Purdulation  and the dulation . Off-DNAdulation . Purα sedulation . We specdulation . Once reThe mRNA porter may utilize microtubules for transport. Post-transcriptional mechanisms that modify mRNA stability and/or translational efficiency provide rapid and flexible control of gene expression that may be particularly important in coordinating not only the initiation but also prompt resolution of wound-healing responses [Drosophila oocytes analogous to its putative role in human neuronal cells [esponses . The hypesponses ,139,140.esponses . Followiesponses . Purα alal cells . Purα teal cells ,130,143.al cells ,34. YB-1al cells . Taken tMicroarray approaches have been used to catalog and classify constituents of the wound-healing transcriptome ,145 but