More generally, we show that conserved TF occupancy sites are indicative of active regulatory regions and strong gene expression that is sustained during maturation. Our results suggest that evolutionary turnover of TF binding sites associates with changes in the underlying chromatin structure, driving transcriptional divergence. We provide examples of how this framework can be applied to understand epigenomic variation in specific regulatory regions, such as the β-globin gene locus. Our findings have important implications for understanding epigenomic changes that mediate variation in cellular differentiation across species, while also providing a valuable resource for studies of hematopoiesis.Erythropoiesis is one of the best understood examples of cellular differentiation. Morphologically, erythroid differentiation proceeds in a nearly identical fashion between humans and mice, but recent evidence has shown that networks of gene expression governing this process are divergent between species. We undertook a systematic comparative analysis of six histone modifications and four transcriptional master regulators in primary proerythroblasts and erythroid cell lines to better understand the underlying basis of these transcriptional differences. Our analyses suggest that while chromatin structure across orthologous promoters is strongly conserved, subtle differences are associated with transcriptional divergence between species. Many transcription factor (TF) occupancy sites were poorly conserved across species  but were more conserved between proerythroblasts and cell lines derived from the same species. We found that certain  cis-regulatory module that drives expression of human, but not mouse, GDF15, a gene implicated in iron homeostasis. Our results provide a resource to aid researchers in interpreting genetic and epigenetic differences between species.The process whereby blood progenitor cells differentiate into red blood cells, known as erythropoiesis, is very similar between mice and humans. Yet, while studies of this process in mouse have substantially improved our knowledge of human erythropoiesis, recent work has shown a significant divergence in global gene expression across species, suggesting that extrapolation from mouse models to human is not always straightforward. In order to better understand these differences, we have performed a comparative epigenomic analysis of six histone modifications and four master transcription factors. By globally comparing chromatin structure across primary cells and model cell lines in both species, we discovered that while chromatin structure is well conserved at orthologous promoters, subtle changes are predictive of species-specific gene expression. Furthermore, we discovered that the genomic localizations of master transcription factors are poorly conserved, and species-specific losses or gains are associated with changes to the underlying chromatin structure and concomitant gene expression. By using our comparative epigenomics framework, we identified a putative human-specific  TAL1) MAPK) pathway, gene profiles were markedly divergent between species during differentiation SEC23B, but the phenotype could not be recapitulated in mouse models SEC23A, a SEC23B paralog, varied between mice and humans, suggesting a reason for these divergent phenotypes. Moreover, these expression differences were accompanied by variation in TF occupancy proximal to SEC23A in erythroid cell lines suggesting that species-specific differences in transcription may be due to evolutionary divergence in TF occupancy and the epigenome Indeed, these recent studies independently identified a large global divergence in temporal patterns of gene expression between human and mouse at critical, canonical stages of terminal erythroid differentiation Our results suggest that chromatin structure and function is generally well conserved both between species and in erythroid cell models, although certain modifications are under greater constraint than others. In contrast, only ∼25% of the occupancy sites of most TFs are conserved between species, whereas we observed a 2-fold increase in conservation rates for erythroid cell models, validating K562 and G1E cell lines as species-specific model systems for studying such TFs. Nevertheless, we find that CRMs co-occupied by KLF1, GATA1, and TAL1 are significantly more conserved than any lower order combination of these factors and are strictly localized near highly-expressed genes that play a key role in defining erythroid cell state, suggesting that these regions are under strong evolutionary constraint to regulate common features of mammalian erythropoiesis. Moreover, although we show that chromatin structure is largely conserved between similar developmental cell-types across species, subtle changes in chromatin structure are associated with transcriptional divergence. Based on multiple lines of evidence, we suggest that evolutionary changes in transcription are partially driven by large-scale loss or gain of master TF occupancy that associate with changes to the underlying chromatin structure. In addition, these results provide a resource that can aid in translating findings from mouse erythropoiesis to the analogous process in humans.Gata1-null erythroid cells containing an estrogen-inducible Gata1 transgene; herein G1E).For each species, we compiled chromatin immunoprecipitation high-throughput sequencing (ChIP-seq) data sets of histone modifications  and master TFs of erythropoiesis  at the ProE stage of erythroid differentiation  [15]–. F1 penalty. Our derived models of ProE gene expression learned across both species using six histone modifications and four TFs performed well: without over fitting, these models are able to explain between 58% and 61% of the variation in gene expression for each species based upon the coefficient of determination , lost (mouse-specific), compensatory, and two additional subcategories of conserved occupancy sites, Across all TFs, genes proximally occupied by at least one conserved TF were expressed at significantly higher levels across all cell states, from ProE to orthochromatic erythroblasts (OrthEs) .. The seApplying this method to cross species differences in expression, we discover that genes proximally occupied by a strongly gained TF site show human-specific expression during terminal erythroid differentiation .. IntereAs a general principle, our observations show that conserved TF occupancy across species is associated with both strong gene expression and active regulatory states. Indeed, while this principle has been shown for conserved GATA1 DNA binding motifs on a small scale, we have confirmed this principle for multiple master regulators with biochemical data across both genomes To illustrate specific features of epigenomic conservation and divergence during cellular differentiation, we examined a few well-known regulatory regions involved in erythropoiesis, leveraging our framework to gain further insight into the physiological relevance of these differences. We first describe two regions of general epigenomic conservation with subtle, but important, differences.We investigated the well studied locus control region (LCR) of the developmentally regulated β-like globin genes st and 3rd HSs are two of the highly constrained CRMs co-occupied by GATA1, TAL1, and KLF1, confirming that these HSs are under strict evolutionary constraint. We observe stronger KLF1 intensity at HS1 compared to HS2 in human, but stronger KLF1 intensity at HS2 versus HS1 in mouse. Additionally, we observe increased NFE2 occupancy at HS3 in humans compared to the same region in mouse. Furthermore, the first four HSs in the LCR are associated with strong/poised enhancer states in humans whereas they are associated with strong/weak enhancer states in mice. Finally, although GATA1 and TAL1 occupy HS4 across species, the specific binding sites in this HS appear to be different for human and mouse , but an erythroid phenotype could not be recapitulated in mouse models SEC23B, and this gene is similarly expressed between species  or polycomb repression (state 14), whereas the region around mouse Sec23a is comparatively open for transcription  is one of the most highly expressed genes in human differentiating erythroblasts but is absent in mouse erythroblasts , TFs (e.g. ZFPM1 and SPI1/PU.1) non-coding RNAs, and methylation patterns that may be important for understanding species-specific differences in erythropoiesis. Furthermore, we cannot exclusively rule out the possibility that certain peaks are “hyper-ChIPable” due to a lack of IgG control datasets, although recent work provides convincing evidence that this consideration, while critical in yeast, is far less of a concern in complex metazoans We have made all of our results publically available as filetypes that are quickly loaded into standard genome browsers (IGV and UCSC Genome Browser). These data could guide investigators in choosing appropriate model systems for studying blood diseases or other aspects of erythropoiesis as well as aid in the interpretation of their results. Overall, our comparative epigenomics approach has successfully explained a significant portion of the transcriptional divergence observed during erythroid differentiation in mice and humans.Hg19 and mm10 were used throughout the entire analysis as reference genomes for all human and mouse cell types, respectively. Orthologous genes were defined using Ensembl mouse to human ortholog matching and were downloaded from BioMart; genes which matched one: many were excluded from all analyses, resulting in 15506 one: one orthologous genes used for analysis. A smaller subset of orthologous genes (6596) with well-defined canonical transcripts from RefSeq was used for all quantitative promoter analyses. To compare mm10 to hg19, the UCSC liftOver tool was used to lift coordinates over from one genome to another with one: one matching and 10% sequence conservation required. PAVIS was also used to annotate genomic regions such as TF-occupancy peaks based upon proximity to known genes https://www.ncbi.nlm.nih.gov/books/NBK158900/). Raw reads were aligned to the hg19 and mm10 genomes using Bowtie v0.12.9 with options “-v 2 -m 3 —strata –best” 2 scaled and read into R 3.0. NGSplot was used to plot normalized average intensity curves across 15506 orthologous genes (-2000 from TSS to +2000 after TES) for all ChIP-seq datasets ChIP-seq datasets were either downloaded from NCBI GEO or from the ENCODE project's homepage .. SRA fiTF-occupancy peaks were initially called using MACS 1.4 to estimate fragment size http://genome.cse.ucsc.edu/cgi-bin/hgEncodeVocab?ra=encode%2Fcv.ra&term=%22GATA1_(SC-266)%22 and 2TAL1_(SC-12984)%22). Importantly, these peaks were all significantly enriched for the TF canonical motif  for each TF in each species, suggesting that immunoprecipitation was nominally successful. Indeed, western blots in human and mouse cell types suggest that these antibodies are specific for both human and mouse TFs . Five human time points  and four mouse time points  with three replicates each were used in this analysis. Similar to ChIP-seq data processing, SRA files were transformed to FASTQ using FASTQ-dump. RNA-seq data was processed with the Tuxedo Tools Suite using the same options as recent protocols, except CuffQuant and CuffNorm were used to derive normalized  and raw count data for each transcript Single-end RNA-seq datasets of primary erythroblasts were downloaded from NCBI GEO (GSE53983) 1-penalization  to view epigenomic mark intensity files We have made aligned and processed ChIP-seq data for all six histone modifications, four transcription factors, and derived chromatin states for all cell-types available on GEO at GSE59801. Gene expression data processed in our pipeline is also available as aligned reads and as FPKM and counts for each gene. Furthermore, robustly defined transcription factor occupancy peaks and information regarding conservation, gain, or loss across species as discussed in the analyses is also made available in the same location.S1 FigConservation of histone modifications in orthologous promoters continued from . A)–B) Corresponding plots for A) H3K4me1 and B) H3K36me3. Left: Average curves of normalized log2 fold changes across 15506 orthologous genes for each histone mark. The size of each gene is normalized in order to represent the average shape of histone mark intensity. Middle: Heatmaps are clustered by the similarity of the pearson r for histone mark intensities between all cell-types. hProEs are CD71+ mProEs are Ter119+, K562 cells are a human erythroid cell line, and G1E/G1E-ER cells are a mouse erythroid cell line. Replicates are included as independent observations. Right: For each category shown , the average pearson correlation between each replicate of that type and each replicate of human ProEs is presented as boxplots. Abbreviations used: hProE, human pro-erythroblast; mProE, mouse pro-erythroblast.(PDF)Click here for additional data file.S2 FigH3K4me3 and H3K27me3 associate with expressed and repressed genes, respectively. A) Cumulative density function of H3K4me3 and H3K27me3 intensity across promoter regions. H3K4me3 is enriched at about ∼50% of orthologous genes while H3K27me3 is enriched at ∼20% of orthologous genes. These two marks are found together at about 2% of orthologous genes. B) Genes with H3K4me3  are highly expressed while genes with H3K27me3  are repressed. Genes with both marks show a slight increase in expression compared to H3K27me3 alone. Abbreviations used: rpm, reads per million.(PDF)Click here for additional data file.S3 FigPatterns of transcription factor occupancy across promoters. A)–D) Left: Average curves of normalized log2 fold changes across 15506 orthologous genes for each TF occupancy. The size of each gene is normalized in order to represent the average shape of histone mark intensity. Right: Example heatmaps are ordered by intensity of aligned reads per million for each species. Abbreviations used: hProE, human pro-erythroblast; mProE, mouse pro-erythroblast.(PDF)Click here for additional data file.S4 FigDivergence of transcription factor intensity in orthologous promoters. A)–D) Left: Heatmaps are clustered by the similarity of the pearson r for TF occupancy intensities between all cell-types. hProEs are CD71+ cells, peripheral blood derived erythroblasts, or CD36+ mProEs are Ter119+ or FDCPmix cells, K562 cells are a human erythroid cell line, and G1E/G1E-ER cells are a mouse erythroid cell line. Replicates are included as independent observations. Right: For each category shown , the average spearman correlation between each replicate of that type and each replicate of human ProEs is presented as boxplots. Abbreviations used: hProE, human pro-erythroblast; mProE, mouse pro-erythroblast.(PDF)Click here for additional data file.S5 FigAlternate estimates of transcription factor occupancy conservation. A) For each TF , the estimated conservation rate (0–100%) of TF peaks between human and mouse ProEs are displayed. The lower bound represents the percentage of human peaks in orthologous genomic regions that are also present in mouse (left box). The middle estimate is the percentage of mouse peaks in orthologous genomic regions also present in human (middle box). The upper estimate is the same as the middle estimate, except that we first restricted to only the top 25% of peaks in mouse (left box). Conserved peaks are peaks that overlap in orthologous genomic regions, and compensatory peaks are peaks that are within +/- 5 kbs of the original peak. We expected to observe at least a small increase in the total percentage of conserved peaks for each TF, since stronger peak signals may be more indicative of function. Indeed, we observed a moderate increase (average increase of 18%) in percentage of conservation across each TF but also a significant drop (average 2.5-fold decrease) in the total number of conserved peaks. B) Similar to A), except that that the estimated number of conserved peaks are displayed instead of the percentage. Please note that this is the total number of overlapping mapped peaks, and not the total number of mapped peaks. Abbreviations used: ProE, pro-erythroblast.(PDF)Click here for additional data file.S6 FigGraphical depiction of TF occupancy lift over and comparison. A) Briefly, for each TF occupancy peak , we determined if it is co-occupied (+/- 1000 bps) by any of the other TFs resulting in 7 different combinatorial groups . A narrow region (+/- 50bp) around the summit of each of these TF occupancy peaks is mapped from mouse ProEs (mm10) to hg19 and its corresponding group (including no overlap) is computed similarly in human ProEs. ‘n’ is the total number of mapped peaks for each group and ‘xi’ is the number of mapped peaks that fall into the ‘i’th group. Abbreviations used: ProE, pro-erythroblast.(PDF)Click here for additional data file.S7 FigTransition matrix of chromatin state HMM. A) Transition matrix of the consensus HMM for each state. Blue represents increased probability of transition between states. Abbreviations used: HMM, hidden markov model.(PDF)Click here for additional data file.S8 FigFold enrichments of genomic regions for consensus HMM. A), C), E) Fold enrichments for hProEs, K562 cells, and mProEs on the consensus model derived across all cell types. B), D), F) Fold enrichment in 200bp bins around the TSS for each cell state. Blue represents increased fold enrichment versus expected. Abbreviations used: hProE, human pro-erythroblast; mProE, mouse pro-erythroblast; HMM, hidden markov model; TSS, transcription start site.(PDF)Click here for additional data file.S9 FigIndividual cell-type chromatin state HMMs. A)–C) From left to right: emission probability matrix, fold enrichment matrix, fold enrichment around the TSS, and transition probability matrix for HMMs derived solely for each cell type , K562 cells, B), and mProE, C)). Darker blue represents increased probability (for emission probability matrix and transition probability matrix) or increased fold enrichment versus expected (for enrichment in genomic regions and around the TSS). Abbreviations used: hProE, human pro-erythroblast; mProE, mouse pro-erythroblast; HMM, hidden markov model; TSS, transcription start site.(PDF)Click here for additional data file.S10 FigChromatin state fold enrichment versus expected in K562 cells. Identical regions as investigated in Abbreviations used: ProEs, pro-erythroblasts.(PDF)Click here for additional data file.S11 FigInter- and intra-species gene expression. Spearman correlations for gene expression profiles between mouse and human primary ProEs, BasoEs , PolyEs, and OrthEs as well as erythroid cell lines, K562 and G1E, represented as a heatmap. The histogram in the legend represents the number of cells in the heatmap with a given correlation. Across all cell types, human and mouse gene expression profiles are more similar within- than between-species. Abbreviations used: ProEs, pro-erythroblasts; eBasoE, early basophilic erythroblasts; BasoE, basophilic erythroblasts; lBasoE, late basophilic erythroblasts; PolyE, polychromatic erythroblasts; OrthE, orthochromatic erythroblasts.(PDF)Click here for additional data file.S12 FigGene expression for transcription factor conservation classes in human terminal erythroid differentiation. A)–D) Gene expression patterns during terminal erythroid differentiation based upon proximity to TF occupancy sites for varying TF occupancy conservation Click here for additional data file.S13 FigCross species gene expression for transcription factor conservation classes. A)–D) Cross species gene expression patterns during terminal erythroid differentiation based upon proximity to TF occupancy sites for varying TF occupancy conservation Click here for additional data file.S14 FigApplying the comparative epigenomics framework to BCL11A. A) Chromatin states learned from the HMM and TF intensities are shown for BCL11A in human ProEs. B) Chromatin states learned from the HMM and TF intensities are shown for Bcl11a in mouse ProEs. C) Genomic conservation of a GATA1/TAL1 binding site in an erythroid-specific enhancer across species. D) Gene expression patterns during terminal erythroid differentiation are shown for BCL11A by species. Error bars represent the mean +/- the standard deviation. Abbreviations used: ProE, pro-erythroblast; HMM, hidden markov model.(PDF)Click here for additional data file.S15 FigComparative epigenomics of the SEC23B locus. Chromatin states learned from the HMM and TF intensities are shown for A) SEC23B in human and B) Sec23b in mouse. Legend for the HMM is shown in Abbreviations used: ProE, pro-erythroblast; HMM, hidden markov model.(PDF)Click here for additional data file.S1 TableRaw ChIP-seq datasets. ChIP-seq datasets for each cell-type analyzed in this manuscript. Raw data was available on either NCBI GEO or the ENCODE website. Abbreviations used: ChIP-seq, chromatin immunoprecipitation high-throughput sequencing.(PDF)Click here for additional data file.S2 TableChIP-seq summary statistics. Summary statistics for each ChIP-seq dataset used in the analysis. Abbreviations used: none.(PDF)Click here for additional data file.S3 TableValues for correlation matrices. Spearman correlation matrices for H3K4me3, H3K27me3, and H3K4me1. Matrices shown examples of biological replicate correlations for each mark as well as low correlations between K562 and G1E cell types. Abbreviations used: ChIP-seq, chromatin immunoprecipitation followed by high-throughput sequencing.(PDF)Click here for additional data file.S4 TableGATA1, TAL1, and KLF1 conserved regions. Coordinates in hg19 for human ProEs. Regions are centered around KLF1 peaks lifted over from mouse ProEs. Abbreviations used: ProE, pro-erythroblast.(PDF)Click here for additional data file.S5 TableChromatin state functional enrichment for HMM. Values corresponding to the heatmaps shown in Abbreviations used: none.(PDF)Click here for additional data file.S6 TablePredictive promoter models of transcription. Both the species-specific and consensus models applied to promoter marks are applied to gene expression across terminal erythroid differentiation. Abbreviations used: none.(PDF)Click here for additional data file.S1 DatasetMouse proerythroblast TAL1 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S2 DatasetMouse proerythroblast NFE2 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S3 DatasetMouse proerythroblast KLF1 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S4 DatasetMouse proerythroblast GATA1 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S5 DatasetHuman proerythroblast TAL1 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S6 DatasetHuman proerythroblast NFE2 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S7 DatasetHuman proerythroblast KLF1 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.S8 DatasetHuman proerythroblast GATA1 motif discovery results. Raw motif results. Abbreviations used: none.(ZIP)Click here for additional data file.


Human pluripotent stem cells provide a versatile platform for regenerative studies, drug testing and disease modeling. That the expression of only four transcription factors, Oct4, Klf4, Sox2 and c-Myc (OKSM), is sufficient for generation of induced pluripotent stem cells (iPSCs) from differentiated somatic cells has revolutionized the field and also highlighted the importance of OKSM as targets for genome editing. A number of novel genome-editing systems have been developed recently. In this review, we focus on successful applications of several such systems for generation of iPSCs. In particular, we discuss genome-editing systems based on zinc-finger fusion proteins (ZFs), transcription activator-like effectors (TALEs) and an RNA-guided DNA-specific nuclease, Cas9, derived from the bacterial defense system against viruses that utilizes clustered regularly interspaced short palindromic repeats (CRISPR). Genome editing systems based on zinc-finger fusion proteins (ZFs), transcription activator-like effectors (TALEs) and an RNA-guided DNA-specific nuclease (Cas9) can be successfully used for generation of induced pluripotent stem cells.ZF-TFs and TALENs fused with different transcriptional domains can modulate expression of master genes of pluripotency, such as Oct4, Sox2, Klf4 and c-Myc.Oct4, which makes this system a very attractive tool for generation of iPSCs.The CRISPR/Cas9 fusion with the histone acetyltransferase domain of p300 can reactivate on its own the epigenetically silenced locus of As generation of iPSCs requires p53 inactivation, which, in turn, provokes tumorigenesis, it will be interesting to see whether temporal Cas9d-mediated inhibition of p53 downstream targets, but not p53 itself, is sufficient to trigger dedifferentiation without affecting the quality control.One downside of the iPSCs generation process is its low efficacy. In this respect, what will happen when the precision of genome editing systems is combined with the power of small molecule inhibitors that reverse the epigenetic state of differentiated cells?1 (2 Both activity and expression of these transcription factors (TFs) are repressed in normal somatic cells and hence their re-activation is instrumental for the re-programming of somatic cells into the iPSCs. The originally described direct delivery of the corresponding cDNAs into somatic cells cannot be utilized for the purpose of gene therapy, because of the possibility of DNA recombination. Another approach is via pharmacological enhancement of the downstream targets of OSKM.6 An alternative approach of OSKM re-activation in differentiated cells can be achieved through specific targeting of transcription activators by means of genome editing.The emergence of genome-editing technologies over the past several years has flourished the investigation of human cellular disease models. Recent achievements in generation of pluripotent stem cells (PSCs) from patients and specific differentiation of these cells into various somatic cell types greatly facilitated the studies on pathophysiology of socially important diseases . PSCs in1 . PluripoAs of today, several efficient systems of genome manipulation have been described based on various classes of DNA-binding chimeric proteins such us zinc-finger proteins (ZFs), transcription activator-like effectors (TALEs) and the guide RNA (gRNA)-driven Cas9d mutant (CRISPR) system. In this review, we discuss the exploitation of various genome editing techniques for successful and robust generation of iPSCs from human somatic cells.ZFNs (zinc-finger nucleases) genome-editing system utilizes chimeric proteins that consist of highly specific 'zinc finger' (ZF) DNA-binding domains fused to a nuclease domain of the restriction endonuclease FokI . Each fi7 insects 8Danio rerio,9 mice,10 rats,11 pigs,12 human cell lines13 and iPSCs.15ZFN system has been successfully applied for the modification of various genomes, including plants,16 Further, the bi-allelic correction of the point mutation (Glu342Lys) in the α1-antitrypsin gene (A1AT or SERPINA1) by ZNF system and subsequent re-introduction of differentiated iPSCs into the liver of the recipient mouse resulted in the restoration of structure and function of A1AT both in vitro and in vivo.17ZNF system showed promising results in gene therapy of the mutation causing sickle cell anemia in human iPSCs.18 insects,19 nematodes,20 the fish,21 amphibians,22 mice,23 rats,24 rabbits,25 cancer human cell lines, hESCs and iPSCs.27 The most important component of this system is a site-specific DNA-binding protein TALE isolated from a pathogenic for plant organism Xanthomonas. Another TALE-like protein derived from a pathogenic bacterium Ralstonia can also be used for specific editing.28 The DNA-binding domain represents a TALE tandem repeats of 33–35 amino acids. TALE repeats have similar sequences and differ only in the two highly variable amino acids at positions 12 and 13 , which form the basis for specific-nucleotide recognition.29 Four tandem repeats Asn-Asn, Asn-Ile, His-Asp and Asn-Gly are sufficient for recognition of guanine, adenine, cytosine and thymine, and, hence, for generation of TALEs with unique properties  of Arabidobsis thaliana.31 The second component comprises CIB1 (interaction partner with CRY2), fused to a transcription activation domain , CIB1:TAD. In the absence of light TALE:CRY2 binds to the promoter region of a target gene, whereas the complex CIB1:TAD remains unbound  has been developed.mponents . The fir unbound . The tre unbound . In addi32This approach allows studying the effect of selected chromatin modifications on the expression of specific genes. For example, the TALEs domain fused to the catalytic domain of TET1 protein (ten-eleven translocation), which oxidizes 5-methylcytosine to methylated cytosine (5 mC), was reported to cause a significant demethylation in the CpG-rich chromatin.33 Although the exact mechanism of CRISPR/Cas9 action is still under investigation, it is deemed that clustered regularly interspaced short palindromic repeats (CRISPR) along with short spacer DNA fragments that derive from previous encounters with viruses are transcribed into long CRISPR RNAs (crRNAs). When combined with transactivation crRNA (tracrRNA), these crRNA:tracrRNA duplexes provide a 'search engine' for the Cas9 nuclease to attack specific viral DNAs34  and highly efficient production of bi-allelic knockout in hPSCs lines. First of all generation of hPSCs lines that express Cas9, the invariable component of the CRISPR/Cas system, was performed for creating such platform. For the next step the lipid-mediated transfection of small RNAs was determined as efficient for co-transfection of multiple gRNAs for multiplexed genome editing during a desirable stage of hPSC. To make the iCRISPR platform more flexible, special iCas9 hPSC lines were engineered for doxycycline-inducible expression of Cas9 through TALEN-mediated gene targeting. Thereby, this platform allows successful one-step generation of double- and triple-knockout hPSC lines as well as stage-specific inducible gene knockouts during differentiation of hPSC.47Furthermore, the CRISPR system with dead Cas9 nuclease (dCas9) protein fused with a transcription activation domain  has beenOct4 (POU5F1) gene is the critical one.51 The Octamer-binding TF4 (Oct4) protein belongs to the family of homeodomain-containing transcription factors. Mechanistically, Oct4 not only positively affects transcription of genes required for pluripotency and self-renewal but also prevents the expression of TFs that drive differentiation of stem cells.52 The regulatory mechanisms of Oct4 gene expression are quite complex. The Oct4 gene is controlled by a TATA-less promoter (53 There are four conservative regions (CRs) in the regulatory sequences of the Oct4 gene: CR1, CR2, CR3 and CR4.54 CR1  and the most distal conserved region CR4 are the regions critically important for regulation of Oct4 gene expression by several transcription factors, including Sp1 and RAR  domain function as potent transcriptional repressors via recruitment of the histone deacetylase (NuRD) complex, The latter includes histone deacetylases (HDACs), histone methyltransferase (SETDB1) and heterochromatin protein 1 (HP1).68 Stabilization of the repressive complex on chromatin is maintained by binding of KAP1 with HP1 through interaction with H3K9me3. How the KRAB domain interacts with transcriptional co-activators is not known yet. One possibility is that KRAB–ZFs fusion may interfere with other transcriptional repressors , thus mediating the 'inhibition of inhibitors'. Irrespective of the exact mechanism, these results indicate that KRAB–ZFs can function as an activator of silenced genes in specific chromatin context.KRAB-associated protein 1 (KAB1) is one of the main co-repressors of KRAB and interacts with box A subsequently recruiting lysine methyltransferase SETDB1 to tri-methylate H3-K9 (H3K9me3).Oct4, Sox2, Klf4 and c-Myc genes, which are critical for the maintenance and acquisition of pluripotency. The levels of activation for these genes were comparable to the ones observed in ES cells and did not require additional active epigenetic agents.69 Over 300 promoter region-targeting ZFs fused with the p65 subunit of NF-B were designed to target 1 kb (from –800 to +200 bp) region of the promoter around transcriptional start sites for each of Oct4, Sox2, Klf4 and c-Myc. Each designed ZF-coding sequence was cloned between the N-terminal nuclear localization signal and the C-terminal NF-B p65 activation domain. To identify critical binding sites for ZF fusions to upregulate transcription, the upstream enhancer and the region downstream of the transcriptional start site were explored. Three out of the six constructs were shown by RT-PCR and western blotting to activate Oct4 more than 16-fold in HEK293 cells. The best two of the three activator of Oct4 are located in the upstream enhancer region of the gene. Also, the highest transcription activation of Sox2 and Oct4 in HEK293 was achieved with ZF-TFs containing VP64 or 2xp65 activation domains, respectively. However, the same ZFs fused to VP16 and VP64 domains failed to activate Oct4 efficiently. Apparently, the ability of ZF-TFs to activate transcription depends on the cell type, the exact functional domain fused to ZF-TFs and the chromatin context of the targeted gene.69 In this respect, it can be speculated that depending on the epigenetic state of chromatin in the target locus, different functional domains fused to ZFs may exhibit various efficacies.69ZF-TFs have been used for targeting of Sox2 and Klf4 genes in HEK293 cancer cell line.70 TALEs genome-editing system has also been used for reactivation of the Oct4 gene.71 Designed TALEs efficiently upregulated Oct4 transcription in ESCs, but failed to activate this gene in ESC-derived neural stem cells (NSCs) because of the repressive epigenetic state of the corresponding genomic locus. Chemical inhibition of histone deacetylases (HDAC) by VPA  and DNA methyltransferases by 5-azaC, respectively, greatly facilitated the effect of designed TALEs on expression of the epigenetically silenced Oct4 promoter in NSC.71 This result suggests that designed TALEs can be used for reprogramming somatic cells into iPSCs.The TALE-TF system has successfully been employed to activate Oct4 by targeting its distal enhancer (DE). Reactivation of the endogenous Oct4 by TALE-VP64 was sufficient for epigenetic reprogramming of fibroblasts into iPSC in the absence of exogenous factors Oct4 or Nanog.72 Mechanistically, TALE-VP64 likely recruited histone acetyltransferase (HAT) p300 to acetylate histones. In this respect, both TALE-VP64 and sgRNA/dCas-VP64 chimeras were shown to interact with p300 in human and mouse cells.73TALE-VP64 fusion can induce transcription of endogenous Oct4 gene. The binding region from –120 to –80 bp was the most efficient for TALE-VP64-mediated activation, while Cas9d was highly effective when targeted by sgRNA to the region from –147 to –89 bp upstream of the transcription start site  system has been utilized for regulation of transcription.Oct4, Sox2 and Ilirn genes by an inducible Tet-on CRISPR/dCas9 system has been developed for human and mouse cells.76 This system is based on the dCas9 protein fused to several copies of the viral transcription activation domain VP16. It was shown that dCas9-VP160  efficiently activated endogenous genes when targeted by specific sgRNA to the region within 300 bp upstream of the transcriptional start site. The most efficient gene activation was achieved by clusters of 3-4 sgRNAs binding to the proximal promoters, suggesting a synergistic mode of action.76 Simultaneous induction of at least three different endogenous genes was achieved with the CRISPR-on system in this study.76Recently, a multiplexed activation of endogenous Oct4 and Nanog genes, TALE-TFs were much superior in their ability to activate transcription during the reprogramming of both MEFs and EpiSCs.77 Expression of Cas9d alone failed to reprogram cells into iPSCs despite modest upregulation of mRNA expression and positive effect in the luciferase reporter assay. It was likely due to an inefficient recruitment of p300 HAT to acetylate histones at the target site.77A recent report shed some light on the mechanistic differences in gene regulation by TALEs and Cas9d proteins. While TALE-TFs and CRISPR systems were comparable in their ability to repress transcription of endogenous 78 Specifically, the dCas9-p300 HAT protein targeted by a pool of gRNAs to the PE of Oct4 gene 30-fold more potently activated transcription compared with dCas9-VP64. Moreover, this approach may be transferrable to other genome-editing systems , thus making it a versatile technology for targeted gene activation.In line with this notion, a recent report described a fusion construct between dCas9 and the histone acetyltransferase (HAT) domain of p300 as a powerful transcription activator.Systems for genome editing and manipulation with gene expression based on DNA-binding ZFs, TALEs and CRISPR/Cas9 molecules fused to special functional or nuclease domain could be used in various areas of modern bioengineering. In particular, genome-editing systems represent a promising approach for generation of iPSCs (see 80 One of the critical effectors of c-Myc overexpression is the major mammalian tumor suppressor TP53.81 TP53 is the guardian of genome protecting the organism from cancer as well as infertility or aging.83Importantly, genome-editing systems have a significant advantage over the existing OSKM scheme of generating iPSCs. The problem with OSKM is the induction of genomic instability and tumor formation especially by c-Myc and, to a lesser extent, Klf4. Comparative analysis of stem cells reprogrammed by expressing c-Myc revealed genomic deletions and amplifications, characteristic of oncogene-induced DNA replication stress.p21 gene, whose product, in turn, blocks proliferation and triggers differentiation of pluripotent cells.85 To circumvent this problem several approaches have been described. For example, direct inactivation of p53 significantly increased the efficacy of iPSCs generation.86 Alternatively, inhibition of Notch signaling whose downstream target is p21 with small molecules also facilitated iPSCs generation.87 However, inactivation of p53 results in genomic instability and inactivation of Notch promotes differentiation of iPSCs into neural progenitors.88 In this respect, genome editing of downstream targets that prevent de-differentiation, for example, temporal inactivation of p21 or PUMA, would seem an ideal way to control these unwanted biological effects.89Among a large number of regulated genes, p53 activates expression of the Obviously, as any experimental system, genome-editing systems have their own limitations, that is, their efficacy varies greatly depending on the chromatin accessibility of a regulatory region selected for targeting, its proximity to the promoter or enhancer of the gene of interest, accessibility to other TFs for binding and so on. However, these obstacles will be avoidable in future once the working range and preferable epigenetic makeup of chromatin is determined for each particular targeting TF fusion.Oct4. However, very recent data on epigenetic re-activation by targeting of the dCas9-p300 HAT domain fusion provide optimism on this end.78 Furthermore, there is a wealth of data arguing that isolated activation of the Oct4 gene is not sufficient for generation of iPSCs. In this respect, it may be beneficial to combine the precision of genome-editing tools with a wider effect of pharmacological inhibitors. Future studies should test this intriguing possibility, which will then broaden the area of applications for the genome-editing tools.Another potential limitation of this approach is based on the fact that most of the genome-editing systems fail to re-activate on their own epigenetically silenced genetic loci, such as


Background. Not all yeast alcohol dehydrogenase 2 (ADH2) are repressed by glucose, as reported in Saccharomyces cerevisiae. Pichia stipitis ADH2 is regulated by oxygen instead of glucose, whereas Kluyveromyces marxianus ADH2 is regulated by neither glucose nor ethanol. For this reason, ADH2 regulation of yeasts may be species dependent, leading to a different type of expression and fermentation efficiency. Lachancea fermentati is a highly efficient ethanol producer, fast-growing cells and adapted to fermentation-related stresses such as ethanol and organic acid, but the metabolic information regarding the regulation of glucose and ethanol production is still lacking.Methods. Our investigation started with the stimulation of ADH2 activity from S. cerevisiae and L. fermentati by glucose and ethanol induction in a glucose-repressed medium. The study also embarked on the retrospective analysis of ADH2 genomic and protein level through direct sequencing and sites identification. Based on the sequence generated, we demonstrated ADH2 gene expression highlighting the conserved NAD(P)-binding domain in the context of glucose fermentation and ethanol production.Results. An increase of ADH2 activity was observed in starved L. fermentati (LfeADH2) and S. cerevisiae (SceADH2) in response to 2% (w/v) glucose induction. These suggest that in the presence of glucose, ADH2 activity was activated instead of being repressed. An induction of 0.5% (v/v) ethanol also increased LfeADH2 activity, promoting ethanol resistance, whereas accumulating acetic acid at a later stage of fermentation stimulated ADH2 activity and enhanced glucose consumption rates. The lack in upper stream activating sequence (UAS) and TATA elements hindered the possibility of Adr1 binding to LfeADH2. Transcription factors such as SP1 and RAP1 observed in LfeADH2 sequence have been implicated in the regulation of many genes including ADH2. In glucose fermentation, L. fermentati exhibited a bell-shaped ADH2 expression, showing the highest expression when glucose was depleted and ethanol-acetic acid was increased. Meanwhile, S. cerevisiae showed a constitutive ADH2 expression throughout the fermentation process.Discussion. ADH2 expression in L. fermentati may be subjected to changes in the presence of non-fermentative carbon source. The nucleotide sequence showed that ADH2 transcription could be influenced by other transcription genes of glycolysis oriented due to the lack of specific activation sites for Adr1. Our study suggests that if Adr1 is not capable of promoting LfeADH2 activation, the transcription can be controlled by Rap1 and Sp1 due to their inherent roles. Therefore in future, it is interesting to observe ADH2 gene being highly regulated by these potential transcription factors and functioned as a promoter for yeast under high volume of ethanol and organic acids. Lachancea sp, a type of yeast, is no stranger to the study of alcohol dehydrogenase (ADH) gene isolations and biochemical characterizations. A decade ago, ethanol metabolism in Lachancea sp. has been studied by Lachancea species. ADH catalyzes the final metabolic step in ethanol fermentation and plays an important role for general metabolic pathways of yeast to yield energy as well as to proliferate under anaerobic conditions . This is an important criterion in order to observe the expression or activity of a glucose-regulated ADH2 gene. L. fermentati was isolated from a fermented nypa sap of Nypa fruticans located in Telok Intan, Malaysia (S. cerevisiae exhibited 98–99% similarity with the S. cerevisiae of Chicha strain ( KC183723.1). As expected, the L. fermentati ITS sequence exhibited a 100% similarity with the strain SHM1 (accession number JN674449.1). Yeast Peptone Dextrose (YPD) medium  was used for the culture maintenance at 30 °C.Malaysia . The IntL. fermentati and S. cerevisiae were subjected to partial ADH2 PCR amplification by using denatured primer , before submitted for DNA sequencing . The deposited nucleotide sequences (accession number: KU203771) were then translated into peptide sequences using a translational tool from ExPASy  and peptide alignments were performed by using SDSC Biology Workbench 3.2. Phylogenetic analysis based on the model of Pearson and the neighbor-joining analysis was performed with 1,000 replicates of bootstrap test by using MEGA 6.06 software.Both d primer . The ADH260∕A280 spectrophotometric absorption ratio  and RNA Bioanalyzer 2100 Plant Nano chip  to determine the RNA integration number (RIN) values. The RNA quality was also tested by electrophoresis on 1% (w/v) agarose gel. cDNA was synthesized from the isolated high-quality RNA by using one-step RT-qPCR iScript™ reverse transcription supermix .Total RNA was extracted using the Presto™ Mini RNA Yeast Kit  following the protocol provided by the manufacturer. RNA concentration and quality were determined using the ASaccharomyces cerevisiae ADH2 was available at the Saccharomyces cerevisiae Genome Database (http://www.yeastgenome.org/). The primers for S. cerevisiae were designed by using the software Primer Express , while the primers for L. fermentati were designed based on the multi-alignment of ADH2 gene sequences from the Saccharomyces, Kluyveromyces, and Lachancea families. Actin1 (ACT1) was chosen as the reference gene for normalizations  , 0.75 nM of forward and reverse primers, 2 µl of 10-fold diluted cDNA, and deionized water to reach the final volume. Real-time PCR experiments were carried out in two replicates, of which each real-time PCR was performed in duplicate on each sample. A negative control without the cDNA template was included. The thermal amplification program used was as follows: 95 °C for 30 s; 40 cycles of 95 °C for 10 s; and 60 °C for 30 s before the melt-curve was collected from 58 °C to 90 °C. Ct) of the studied gene normalized with the Ct of a reference gene, ACT1  glucose (for repression) and 0.5% (vv−1) ethanol (for derepression) were added in 100 ml of YPD medium at 30 °C with 200 rpm of agitation after 24 h because there was no glucose remained in the medium. Following the induction, fermentation was extended for one hour before cells were completely harvested and protein was extracted for ADH2 activity determination.In ADH2 protein induction study, 2% . The cell suspension was lysed via the sonication method  for 2.5 min, with 5 s of pulses. The supernatant was collected as protein extract after 10 min of centrifugation at 8,000 × g with a temperature of 4 °C. Total protein concentration was determined by the method of Bradford , as specified by the manufacturer.S. cerevisiae and L. fermentati cells were used in the measurement of ADH2 activity. The reaction for ADH2 assay was performed in 0.3 ml of total volume containing 20 mM of sodium pyrophosphate buffer (pH 7.8), 3.3% (v/v) of ethanol, 7.5 mM of NAD+ and <10 µg of ADH (protein), with 7–8 min of reaction time. ADH2 activity was measured by increasing 340 nm absorbance in response to NADH or acetaldehyde production. The units/ml of ADH2 activity was calculated by using 6.22 of the millimolar extinction coefficient of β-NADH at 340 nm. One unit of NAD+ converts 1.0 µmole of ethanol to acetaldehyde per minute at pH 7.8 and 25 °C  and 0.05 ml of absolute ethanol dissolved in 50 ml of 0.1 M Tris–HCl buffer (pH 8.5) until the desired purple staining was formed . The fermentation medium of 2% YPD  was prepared at 100 ml in a 500 ml Erlenmeyer flask, where the fermentations were all carried out in similar condition. Before the fermentation, the starting density (OD600) of all cultures was 0.5. Over the course of the 30 h fermentation, samples were collected every 6 h to monitor the growth, ethanol, organic acid and residual glucose concentrations. Repeats were performed in triplicate. The fermentation products were centrifuged at 8,000 × g for 10 min to separate the cells from the analytes. The supernatants were stored at −20 °C until used for the ethanol and glucose assays while the precipitants were used in the RNA extraction and ADH assays.Seed cultures of The content of the ethanol in the fermentation samples was determined based on the 96-microwell plate system using the ethanol extraction method . The sug2SO4, with pH 2.8. The flow rate of the mobile phase was adjusted to 0.9 ml/min and the temperature was fixed at 25 °C.Analyzes of organic acids, such as ethanoic acid (acetic acid) were performed by High-Performance Liquid Chromatography, using an Agilent Poroshell 120 EC-C18 column. The column and mobile phase line of the instrument were thoroughly washed with 50% Acetonitrile/50% water of mobile solution. The running buffer or eluent that was used to detect weak acids contained 1 mmol/l of sulfuric acid and 8 mmol/l of NaS. cerevisiae, other non-conventional yeast production systems such as Hansenula polymorpha, Kluyveromyces lactis, Pichia pastoris, and Yarrowia lipolytica have been regarded as a eukaryote model with growing importance  can provide an alternative biomanufacturing platforms primarily as a promoter. To date, L. fermentati has not yet been widely considered for industrial usages.While the era of yeast synthetic biology began in the well-characterized model organism portance . These yL. fermentati exhibited higher affinity for glucose and ethanol, as shown by a 2.5-fold increase in 0.5% (vv−1) ethanol and 0.5-fold increase in 2% (wv−1) glucose  exhibited a low expression level in high glucose and ethanol throughout the 72 h of 150 g/L glucose fermentation  for the first time. The 912 bp-length ADH2 nucleotide sequences amplified from L. fermentati was very different from the well-known yeast ADH2 sequences. The highest similarity score of ADH2 sequences amplified from L. fermentati strain SHM1 ( KU203771) was 88.6% with L. kluyveri ADH2 ( AAP51047.1). The nucleotide sequences and motifs observed in ADH2 gene in L. fermentati were highly conserved. But the analysis showed that there were a few variations found to the other existing ADH2 sequences from different species. L. fermentati. The analysis of ADH2 sequences from L. fermentati successfully identified the highly preserved amino acids and the zinc-binding motifs. Based on the protein alignments, several residues were believed to have a species-related function as observed in Iso-37, Glu-117, Glu-175, Cys-183, Thr-228, Val-231 and Gly-276. It is, therefore, important to study on the role of these residues toward the expression of this gene as they could provide be a useful indication on the nature of regulation of this protein. In this assignment, Thr-228 and Val-231 were the residues included in sequences for gene expression throughout the yeast fermentation study. Typically the HXXXH motifs containing imidazole ring has been well described in yeast as the site where metal ion exchange happens in zinc-containing enzymes. Currently, both S. cerevisiae and L. fermentati exhibited conservation of this zinc binding sites at residues 48–55 based on the HXXXH motif and residues 64–74 according to the Interpro analysis , S. cerevisiae S288c (NM_001182812.1), K. marxianus (KF678866.1) and L. fermentati ( KU203771) showed some irregularities in the conservation sites of UAS and TATA sequences  in the absence of UAS and TATA.In promoter . The invpromoter . It is wpromoter . FollowiL. fermentati would be readily transcribed. The lack in adjacent upper stream-activating sequences, however, left the sequence incomplete for Adr1 binding. Nonetheless, within the sequence of ADH2, there are other potential regulatory genes which made up the complex transcriptional network in yeast. These genes which exist in abundance can promote ADH2 regulation inadvertently providing suitable condition which stimulates them. In L. fermentati, regulatory genes or activator-binding protein such as the zinc finger transcription factor (Sp1) and repressor/activator site binding protein (Rap1) are believed to equally participate in ADH2 gene regulation. Sp1 contains a highly conserved DNA-binding domain composed of three zinc fingers close to the C-terminus with serine/threonine- and glutamine-rich domains in their N-terminal regions. This protein is an extremely versatile protein involved in the expression of many different genes which differs between the cell types during development. Given that there are at least 11 sites for the binding of Sp1 in the L. fermentati ADH2 gene and its importance in many gene activations, it is predicted that the cells would not survive without their presence. So far, little is known how Sp1 act on natural promoters in combination with other transcription factors in vivo  and was found to be conserved in the nucleotide sequence of ADH2 from L. fermentati. Therefore, the ADH2 gene could harbor its function through various promoters and activators without having the UAS and TATA regions to activate it through Adr1.The presence of RAP1 transcriptor factor which was known to activate most ribosomal protein and glycolysis enzymes can function as a strong key promoter to ADH2 gene in the presence of glucose. The Rap1 site appears to mediate the response of these genes to the appearance or disappearance of glucose; for example, their expression is coordinately down-regulated upon depletion of glucose at the diauxic shift . The preL. fermentati and S. cerevisiae were performed.In general, ADH2 has a broader role in the yeast cell physiology and growth than previously reported, as this gene can either be involved in the utilization of non-fermentable carbon sources, carbohydrate and nitrogen metabolism or protein synthesis depends on its type of species . In the S. cerevisiae and L. fermentati were harvested at different growth stages. The cell harvest obtained from the basal (zero h), exponential , mid-exponential (18th h) and stationary (30th h) phases, along the 30 h length of 2% (w/v) glucose fermentation. The regulations of ADH2 in both yeasts were influenced by cell growth, ethanol production as well as glucose consumption as shown in In analyzing ADH2 expression, cells from S. cerevisiae ADH2 improved showing its activation during exponential growth phase. The trend of ADH2 expression follows the order of consumption and ended with ethanol as well as by-product production. The availability of glucose can influence the repression of ADH2 in the waking phase of fermentation. But once the glucose was completely used up, ethanol or even acetate would take up the role of ADH2 derepression. It has been reported that, at the transcriptional level, the up-regulation of glucose-repressible ADH2 is a result of an increase in ethanol or acetate production . PDC plays a role in acetaldehyde formation during the conversion of pyruvate to acetaldehyde, where it may have led to the reduction of ethanol concentration (S. cerevisiae and L. fermentati has been the result of ethanol. This could be explained by L. fermentati ADH2 affinity for ethanol which exhibited lower Km compared to S. cerevisiae ADH2 (The outcome of ADH2 gene expression from ntration . This wontration . The maiiae ADH2 .L. fermentati again indicated that ADH2 transcription was not compelled to the regulation of glucose-ethanol alone. The increased level of acetic acid might also involve in the regulatory mechanism of ADH2 gene expression, in which the function of this weak acid was known to retain the redox potential under fermentative condition.In this observation, the activity of ADH2 was identical to the transcriptional profiles of ADH2 exhibited over the fermentation course. The bell-shaped curve of ADH2 activity in Acetic acid co-production can influence yeast ADH2 activity during cell growth via the metabolic oxidation of carbon sources that generates large amounts of organic acids. To manage the cytosolic pH homeostasis, the production of acids must be kept in equilibrium with their utilizations . As ADH2L. fermentati (S. cerevisiae ADH2 activity appeared not to be regulated by acetic acid (Subsequent experiments performed in glucose fermentation also showed that ADH2 activity was very much regulated by acetic acid produced by rmentati . Howevertic acid .L. fermentati to prevent cell-induced apoptosis, the role of ADH2 could not be ruled out. Acetic acid can easily penetrate the cell wall and induced cell death and one way to decelerate this process is through promoting ADH2 expression or activity (According to activity . Hence, L.fermentati was found high in the presence of acetic acid and ethanol. These concentrations were equivalent to 0.835 mmol/L of acetic acid and 10.62 g/L of ethanol when L. fermentati ADH2 activity reached its highest level. Subsequently, ADH2 activities subsided when acetic acid was suppressed. Based on these results, we described that the approach of LfeADH2 in gene transcription was not strictly glucose-regulated, as specifically observed in previous experiments performed in most of the wild-type S. cerevisiae (ADH2 activity in yeasts come in handy as it has the advantage to promote organic acid and ethanol tolerance and to maintain the relative production of ethanol. In revisiae .L. fermentati ADH2 showed protective roles toward intracellular processes during ethanol fermentation. The up-regulation of L. fermentati ADH2 in the presence of glucose and ethanol showed that ADH2 enabled both glucose utilization and ethanol production to occur simultaneously. Acetic acid also is a precursor to ADH2 activity, and L. fermentati has showed to demonstrate a higher tolerance to acetic acid prior to the increase in ADH2 activity. L. fermentati which plays an important role to the cause of gene transcription influencing protein expression during glucose fermentation. Generally, ADH2 has become of practical importance for bioethanol production from L. fermentati, as this gene was highly regulated at the highest level of ethanol fermentation. The mechanism of Adr1–ADH2 binding in L. fermentati can be unique but the absence of UAS and TATA elements would mean that the gene was unable to be transcribed based on the glucose-repressible condition. Alternatively, the presence of other well-described regulating genes such as Rap1 and Sp1 could be of importance to the activation of L. fermentati ADH2. Based on this preliminary study of ADH2 from L. fermentati, it is of great interest to describe the mechanism of ADH2 activation and which type of gene regulations that mostly affect the transcription process. Through this knowledge, the probable use of the ADH2 gene in L. fermentati as a promoter in a facilitating ethanol synthesis from highly rich acetic acid medium of lignocellulosic hydrolysates could be significant.Many of the cellular and metabolic features of 10.7717/peerj.1751/supp-1Table S1Click here for additional data file.10.7717/peerj.1751/supp-2Figure S1Click here for additional data file.


However, under conditions that maximize CodY activity, braB expression was similar in wild-type and codY null mutant cells. Nonetheless, expression from the braB promoter was significantly elevated in cells containing partially active mutant versions of CodY or in wild-type cells under growth conditions leading to intermediate levels of CodY activity. This novel pattern of regulation was shown to be due to two opposing mechanisms, negative and positive, by which CodY affects braB expression. A strong CodY-binding site located downstream of the transcription start point conferred negative regulation by direct interaction with CodY. Additionally, sequences upstream and downstream of the promoter were required for repression by a second pleiotropic B. subtilis regulator, ScoC, whose own expression is repressed by CodY. ScoC-mediated repression of braB in codY null mutants cells was as efficient as direct, CodY-mediated repression in wild-type cells under conditions of high CodY activity. However, under conditions of reduced CodY activity, CodY-mediated repression was relieved to a greater extent than ScoC-mediated repression was increased, leading to elevated braB expression. We conclude that restricting increased expression of braB to conditions of moderate nutrient limitation is the raison d’être of the feed-forward regulatory loop formed by CodY and ScoC at the braB promoter. The increase in BraB expression only at intermediate activities of CodY may facilitate the uptake of BCAA when they are not in excess but prevent unneeded BraB synthesis when other BCAA transporters are active.The global transcriptional regulator, CodY, binds strongly to the regulatory region of the  Bacillus subtilis BraB, a branched-chain amino acid permease, is under both negative and positive control by a global transcriptional regulator CodY. The negative control is direct and the positive control is indirect and mediated by another B. subtilis pleiotropic transcriptional regulator, ScoC, which, in turn, is repressed by CodY. Thus, CodY and ScoC form a feed-forward regulatory loop at the braB promoter. In a very unusual manner, the interaction of CodY and ScoC results in high braB expression only at intermediate CodY activities; braB expression remains low both at high and low CodY activities. The novel regulation of braB shows that important, novel regulatory phenomena can be missed by analyzing null mutants in regulatory genes but revealed by using mutants with partial activity.Expression of  Bacillus subtilis   –11 and Ge (ILV)] , 11–14. braB gene proved to be directly repressed by two proteins, CodY and another pleiotropic regulator, ScoC (formerly known as hpr or catA)  and  and braBbraB242-gfp translational fusion was introduced into the wild-type strain, the codY null mutant, and a codY point mutant (R61K) strain with intermediate residual activity. In all cases, the level of braB expression was rather similar across the cell population (codY (R61K) mutant strain had elevated expression compared to the wild-type and codY null mutant strains.A pulation , eliminabraB regulation observed results from CodY binding independently to negative and positive regulatory sites within the braB regulatory region. If so, the positive and negative effects of fully active CodY might balance each other, but, at intermediate levels of CodY activity, positive regulation might dominate. The CodY-binding sites I and II are located upstream and downstream of the braB promoter in positions appropriate for positive and negative regulation, respectively. To determine their independent effects, we created additional lacZ fusions containing truncated versions of the braB regulatory region lacking the upstream CodY-binding site III (braB184-lacZ and braB162-lacZ) or sites III and I (braB144-lacZ) or the downstream site II (braB156-lacZ) We initially hypothesized that the very unusual pattern of 56-lacZ) .  (To confirm that site I is not involved in ctively) .braB242-lacZ fusion .The p3 mutation reduced the affinity of CodY for site II ≥10-fold . The p2 braB242-lacZ fusion 8-fold consistent with relief from CodY-mediated repression  than did CodY (KD≈5 nM) (braB-CodY complex as evidenced by formation of ScoC-specific complexes with higher mobility and the decrease in the amount of braB-CodY complexes with lower mobility (braB-ScoC complex cannot be recognized confidently because of the low mobility of CodY-specific complexes (complexes containing both proteins would have a similar low mobility). However, by comparing and braB-ScoC complexes than to free braB DNA, confirming competition between the two proteins for binding. A similar competition between CodY and ScoC was previously detected at the oppA promoter -ATP. oBB67 and oBB358 start 96 bp or 12 bp upstream of the XbaI site (and 112 bp or 28 bp upstream of the EcoRI site) used for cloning, respectively, and oBB102 starts 36 bp downstream of the HindIII site that serves as a junction between the promoters and the lacZ part of the braB fusion.The PCR products containing the regulatory region of the The procedures for gel shift and DNase I footprinting experiments were as described .braB PCR product, containing the entire braB regulatory region, was synthesized with oBB724 and oBB725 as primers. Plasmid pBB1845 (braB242-gfp) was created by cloning the EcoRI- and SalI-treated PCR product between the EcoRI and XhoI sites of an integrative plasmid pMMB759 (tet), containing a gene encoding a monomeric version (A206K) of GFPmut2 [braB insert within pBB1845 was identical to the insert in pBB1593 (braB242-lacZ). B. subtilis strain BB4082 carrying the braB242-gfp fusion at the lacA locus was isolated after transforming strain BB2263 (lacA::spc) with pBB1845, by selecting for resistance to tetracycline, conferred by the plasmid, and screening for loss of the spectinomycin-resistance marker, which indicated a double crossover, homologous recombination event.A 0.24-kb braB242-gfp fusion, were grown until mid- to late-exponential phase in TSS + 16 aa medium, centrifuged and resuspended in TSS medium at OD600≈3. The images were collected at a 1,500 ms exposure time using the 100x (1.3 N.A.) objective of the Zeiss Axio Observer.Z1 fluorescent microscope (Zeiss) with the Colibri.2 LED light source, and the ORCA-R2 digital charge-coupled device camera . Zen Pro 2012 software (Zeiss) was used to acquire, view, and analyze the images.Cells, containing the 5 and His6-ScoC were purified to near homogeneity as described previously [CodY-Hiseviously , 24.β-Galactosidase specific activity was determined as described previously .braB transcript abundance during exponential growth using oligonucleotides oSRB339 and oSRB340 as described [B. subtilis strain SMY chromosomal DNA to generate the standard curve. rpoC transcript was used to normalize mRNA abundance.RNA isolation, DNA depletion, and cDNA synthesis were performed as previously described . Quantitescribed , except


LMNA, LMNB1, and LMNB2. Mutations in the LMNA gene are associated with a group of phenotypically diverse diseases referred to as laminopathies. Lamins interact with a large number of binding partners including proteins of the nuclear envelope but also chromatin-associated factors. Lamins not only constitute a scaffold for nuclear shape, rigidity and resistance to stress but also contribute to the organization of chromatin and chromosomal domains. We will discuss here the impact of A-type Lamins loss on alterations of chromatin organization and formation of chromatin domains and how disorganization of the lamina contributes to the patho-physiology of premature aging syndromes.Lamins are intermediate filaments that form a complex meshwork at the inner nuclear membrane. Mammalian cells express two types of Lamins, Lamins A/C and Lamins B, encoded by three different genes,  In interphase eukaryotic cells, the nucleus appears as a heterogeneous compartment filed with chromatin. Chromatin structure can be functionnaly divided into heterochromatin (condensed and non-active) and euchromatin (less condensed and active). Chromatin dynamics involves a number of proteins such as DNA binding factors, enzymes involved in histone marks deposition or reading, nucleosome sliding, eviction or replacement and molecules regulating DNA methylation.Several nuclear substructures can be visualized using phase contrast microscopy and a highly complex organization is observable by fluorescence microscopy. Most of the nuclear substructures, including the nuclear pore complex (NPC), the nuclear lamina (NL), and more than 10 different types of nuclear bodies have been characterized .The nucleus is delimited by the nuclear envelope (NE) that lies at the interface between this compartment and the cytoplasm, segregates the DNA from the cytoplasm and allows communication between these two compartments. The NE consists of three intimately linked substructures: the nuclear membranes, the NL and the NPCs. The outer nuclear membrane (ONM) is continuous with the endoplasmic reticulum and shares some features with this cytoplasmic organelle. The NE is interrupted by the nuclear pores allowing connections between the ONM and inner nuclear menbranes (INM), but more importantly nucleocytoplasmic transport. The INM is composed of Lamins and specific integrated proteins called nuclear envelope transmembrane proteins (NETs). To date, more than 90 NETs have been identified, but only a small subset is fully characterized .Caenorhabditis elegans, there is only one Lamin protein . By providing a strong mechanical scaffold for stable nuclear organization, Lamins play different structural roles such as the maintenance of the nuclear shape, rigidity and resistance to mechanical stress . Lamins also contribute to the maintenance of genome integrity through the recruitment of the DNA damage response machinery , Emery–Dreifuss Muscular Dystrophy (EDMD), Limb-Girdle Muscular Dystrophy (LGMD), Familial Partial Lipodystrophy (FPLD), Acro-Mandibular Dysplasia (MAD), Charcot-Marie-Tooth, type B (CMT2B) or Restrictive Dermopathy (RD) while Lamin B is mutated in adult-onset demyelinating leukodystrophy (ADLD) . More particularly, TRF1 and TRF2 are found all along the T2AG3 repeats and are the main actors in the recruitment of the others , the TCAB1 shuttling factor, SnRNP components (NHP2 and NOP10 required for telomerase activity), the TIN2 shelterin component or the regulator of telomerase length helicase, RTEL1 . Unlike the classical TPE signature, this phenomenon is not continuous and relies in changes of the chromatin conformation. Interestingly, TPE-OLD also occurs in pathologies and was first described in Facio-Scapulo-Humeral Dystrophy, an age-dependent muscular dystrophy linked to the 4q subtelomere located at the NP and bound by A-type Lamins . The role of telomere silencing by TPE or TPE-OLD, especially in pathologies is still in infancy (Overall, telomere positioning to the NP is variable between species and might be determined by subtelomere composition, although this remains to be determined for most human subtelomeres. Thus, transcriptional regulation of natural subtelomeric genes in human cells likely depends on telomere length, the structure of the telomeric chromatin but also on the composition of the subtelomeric regions and spatial distribution of chromosome ends. In addition, as observed experimentally using artificial systems , age-depan cells . It was an cells . This phe Lamins  (Figure  infancy , 2015. HWe highlighted here the diverse function of a number of proteins implicated in the filamentous network forming the NE. Some of them interact directly with chromatin, regulate chromatin architecture and organize the topology of chromosomal domains. In such a scenario, mutations in Lamins A/C or genes encoding other INM-associated factors in diseases and decrease in Lamin B1 upon senesecence contribute to physiological or pathological aging at different levels. Moreover, even if anchoring of genes at the NL might contribute to gene repression as suggested by artificial tethering systems , the mecBoth authors have contributed equally to the writing of the manuscript, edition and preparation of the figures.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.


Lastly, our 3C assay was able to detect a long DNA loop between the hiNOS enhancer and core promoter site, and ChIP loop assay confirmed that p300 binds to AP-1 and RNA pol II proteins. Overall, our results suggest that coactivator p300 mediates cytokine-induced hiNOS transactivation by forming a distant DNA loop between its enhancer and core promoter region.p300, a ubiquitous transcription coactivator, plays an important role in gene activation. Our previous work demonstrated that human inducible nitric oxide synthase (hiNOS) expression can be highly induced with the cytokine mixture (CM) of TNF-α + IL-1β + IFN-γ. In this study, we investigated the functional role of p300 in the regulation of hiNOS gene expression. Our initial data showed that overexpression of p300 significantly increased the basal and cytokine-induced hiNOS promoter activities in A549 cells. Interestingly, p300 activated cytokine-induced hiNOS transcriptional activity was completely abrogated by deleting the upstream hiNOS enhancer at -5 kb to -6 kb in the promoter. Furthermore, p300 over-expression increased cytokine-induced transcriptional activity on a heterologous minimal TK promoter with the same hiNOS enhancer. Site-directed mutagenesis of the hiNOS AP-1 motifs revealed that an intact upstream (-5.3kb) AP-1 binding site was critical for p300 mediated cytokine-induced hiNOS transcription. Furthermore, our ChIP analysis demonstrated that p300 was binding to Jun D and Fra-2 proteins at -5.3 kb AP-1 binding site  The expression of inducible nitric oxide synthase (iNOS) can be activated by immunologic and inflammatory stimuli such as cytokines or lipopolysaccharide (LPS) in different types of cells and tissues , 2]. Th. Th2]. TIn previous studies, p300, a transcriptional coactivator had been shown to be important for transactivation of the murine iNOS promoter. LPS/IFN-γ induced p300 binding and iNOS promoter activity. p300 interacted with downstream NF-κB and AP-1 motifs in the -1.5 kb murine iNOS promoter . HoweverThe University of Pittsburgh institutional review board (IRB) approved this study. The IRB approval number is PRO1210076. The approval protocol title is “Liver Tissue and Cell Distribution System (LTCDS)”. Human hepatocytes were isolated from histological normal operative wedge resections by using collagenase perfusion. In detail, hepatocytes were separated from non-parenchymal cells by differential centrifugation four times at 50xg. The hepatocytes were then further purified over a 30% Percoll gradient at a concentration of 1 million hepatocytes per ml of Percoll to obtain a highly purified cell population. Hepatocyte purity by microscopy was >98% and viability consistently exceeded 95% by trypan blue exclusion. We confirm that any donors of hepatocytes used for this study provided written informed consent.Human recombinant TNF-α, IL-1β and IFN-γ proteins were purchased from R&D Systems. Lipofectamine 2000 was obtained from Life technologies. Antibodies against p300, AP-1 and polymerase II were acquired from Santa Cruz Biotechnology. All other reagents were obtained from Sigma.CCGTAACACTC-3′5′-CCAGCTT; Pr8-1d, CCGTAACGCCC-3′5′-TTTGTGT. Confirmation of the mutant constructs was accomplished with DNA sequencing analysis by the University of Pittsburgh Sequencing Facility.The p300 expression vector pcDNA3.1-p300 was purchased from Addgene. The human iNOS promoter reporter plasmid vector piNOS (7.2)luc contains -7.2 kb of upstream 5’-flanking DNA linked to the luciferase reporter gene and have been described previously . The mut6 human hepatocytes were grown in DMEM with 10% low endotoxin FBS, 100 units/ml penicillin, 100 μg/ml streptomycin, 2 mM l-glutamine and 15 mM Hepes, pH 7.4. Cells were plated onto 6 well cell culture plates (Corning) and stimulated with a cytokine mixture (CM) of TNF-α  + IL-1 β(100 units/ml) + IFN-γ(250 units/ml).The A549 cell line was obtained from the ATCC and cultured in medium as previously described ..et al. hAlthough our data  showed tOur results support that p300 has an important role in human iNOS gene transcription. Under cytokine stimulation, p300 interacts with Jun D, and Fra 2 proteins, thereby increasing AP-1 binding to its -5.3 kb response element in the human iNOS promoter. It also forms a complex with RNA Pol II at the TATA box of human iNOS core promoter. We demonstrate that long range DNA looping occurs at the human iNOS promoter. This looping is induced by cytokines and requires the presence of AP-1, Jun D, Fra2, and p300-associated basal transcriptional machinery. The distal AP-1 binding site at -5.3 kb interacts via p300 with the proximal TATA site to create this DNA loop to participate in CM induced hiNOS transcription . Taken tS1 FigVector p300 was overexpressed in the rescue group. Three similar Western blot experiments were quantified for p300 proteins after normalization with control group.(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.