In order to identify factors involved in transcription of human snRNA genes and 3′ end processing of the transcripts, we have carried out CRISPR affinity purification in situ of regulatory elements (CAPTURE), which is deadCas9-mediated pull-down, of the tandemly repeated U2 snRNA genes in human cells. CAPTURE enriched many factors expected to be associated with these human snRNA genes including RNA polymerase II (pol II), Cyclin-Dependent Kinase 7 (CDK7), Negative Elongation Factor (NELF), Suppressor of Ty 5 (SPT5), Mediator 23 (MED23) and several subunits of the Integrator Complex. Suppressor of Ty 6 (SPT6); Cyclin K, the partner of Cyclin-Dependent Kinase 12 (CDK12) and Cyclin-Dependent Kinase 13 (CDK13); and SWI/SNF chromatin remodelling complex-associated SWI/SNF-related, Matrix-associated, Regulator of Chromatin (SMRC) factors were also enriched. Several polyadenylation factors, including Cleavage and Polyadenylation Specificity Factor 1 (CPSF1), Cleavage Stimulation Factors 1 and 2  were enriched by U2 gene CAPTURE. We have already shown by chromatin immunoprecipitation (ChIP) that CSTF2—and Pcf11 and Ssu72, which are also polyadenylation factors—are associated with the human U1 and U2 genes. ChIP-seq and ChIP-qPCR confirm the association of SPT6, Cyclin K, and CDK12 with the U2 genes. In addition, knockdown of SPT6 causes loss of subunit 3 of the Integrator Complex (INTS3) from the U2 genes, indicating a functional role in snRNA gene expression. CAPTURE has therefore expanded the repertoire of transcription and RNA processing factors associated with these genes and helped to identify a functional role for SPT6. Human small non-coding RNAs (snRNAs) are required for expression of the vast majority of our protein-coding genes due to their important roles in pre-mRNA processing ,2. UnlikMany proteins involved in transcription of the pol II-dependent human snRNA genes and processing of the transcripts have been identified. These include Oct-1 that binds directly to the DSE ,10,11 anIn addition, a specialized little elongation complex (LEC) is recruited to these genes ,22 to faThe negative elongation factor (NELF) and DRB sensitivity-inducing factor (DSIF), comprising SPT4 and SPT5, play key roles in regulating the early elongation checkpoint during transcription of protein coding genes . NELF anPhosphorylation of residues in the Tyr1Ser2Pro3Thr4Ser5Pro6Ser7 repeats of the carboxyl-terminal domain (CTD) of the large subunit of pol II also play a role in expression of human snRNA genes ,29. MutaMore than 30 years ago now, it was shown that the 3′ box is only efficiently recognized if transcription is initiated from a pol II-dependent snRNA gene promoter ,36. ManyIn order to obtain a more complete picture of the proteins associated with the pol II-dependent snRNA genes, we have used the CAPTURE system, where biotinylated, enzymatically dead (d) Cas9 is directed to genes by guide RNAs in order to pull-down the gene region with associated proteins after crosslinking . We haveUsing the CAPTURE system targeting the DSE or PSE, many factors already shown or expected to be associated with human snRNA genes are specifically enriched, including, pol II, CDK7, NELF, the SPT5 subunit of DSIF, MED23, TFIIS, the SSRP1 subunit of the FACT complex , and sevChIP-seq and ChIP-qPCR of the U2 genes validates the association of SPT6 and CDK12 with these genes. In addition, knockdown of SPT6 causes loss of subunit 3 (INTS3) of the Integrator Complex, indicating that SPT6 helps to recruit Integrator to cleave the nascent RNA upstream of the 3′ box.CAPTURE has therefore expanded the repertoire of transcription and RNA processing factors associated with the U2 genes, helped to identify SPT6 as a key player in Integrator recruitment to these genes, and suggested a role for the kinase CDK12 in their expression.l-glutamine, 50 U/mL penicillin, and 50 µg/mL streptomycin and incubated at 37 °C in 5% CO2.Human embryonic kidney (HEK) 293 were grown in Dulbecco’s modified Eagle’s medium (DMEM)  with 10% fetal bovine serum, 2 mM http://n2t.net/addgene:62987 (accessed on 1 March 2022); RRID:Addgene_62987)) and cloning back into the pX462 backbone [BbsI. The dCas9BAP and BirA plasmids are described in [The mutation H840A was introduced into Cas9 by PCR of the FCas9 nickase (D10A) gene in pX462 (pSpCas9n(BB)-2A-Puro (PX462) V2.0 was a gift from Feng Zhang  and maintained in 1 μg/mL puromycin ).g for 5 min at 4 °C to isolate the nuclei. The nuclei were resuspended in 5 mL nuclear lysis buffer  + PhosSTOP )) and incubated for 10 min at room temperature. The suspended nuclei were then mixed with 15 mL of 8 M urea buffer and centrifuged ) at 16,100× g for 25 min at room temperature. Nuclei were then re-suspended in 5 mL nuclear lysis buffer and mixed with 15 mL of 8 M urea buffer  + PhosSTOP  and centrifuged at 16,100× g for 25 min at room temperature. The samples were washed twice more in 5 mL nuclear lysis buffer and mixed with 15 mL of 8 M urea buffer, followed by centrifugation at 16,100× g for 5 min at room temperature. Pelleted chromatin was then washed twice with 5 mL cell lysis buffer. The chromatin pellet was resuspended in 5 mL of IP binding buffer without NaCl  and PhosSTOP )) and aliquoted into Eppendorf tubes. Chromatin was then subjected to sonication to 200 bp on the Q Sonica Thermocube Q800R   was washed 3 times in 1 mL of IP binding buffer and added to soluble chromatin. After overnight incubation at 4 °C, streptavidin beads were collected by centrifugation at 800× g for 3 min at 4 °C. The beads were then washed 5 times with 1 mL of IP binding buffer  and proteins were then de-crosslinked by increasing the NaCl  concentration to 3 M and boiling it at 95 °C for 1 h. The samples were sent to the Advanced Proteomics Facility, Department of Biochemistry Oxford. The samples were digested with trypsin FASP. Peptides were separated by nano liquid chromatography  coupled in line a Q Exactive mass spectrometer equipped with an EASY-spray source  using Solvent A . Peptides were trapped onto a C18 PepMac100 precolumn  using Solvent A . The peptides were further separated onto an EASY-spray RSLC C18 column  using a 60 min linear gradient (15% to 35% solvent B (0.1% formic acid in acetonitrile)) at a flow rate 200 nL/min . The raw data were acquired on the mass spectrometer  in a data-dependent acquisition mode (DDA). Full-scan MS spectra were acquired in the Orbitrap . The 10 most intense peaks were selected for higher-energy collision dissociation (HCD) fragmentation at 30% of normalized collision energy. HCD spectra were acquired in the Orbitrap at resolution 17,500, AGC target 5 × 104 maximum injection time 120 ms with fixed mass at 180 m/z. Charge exclusion was selected for unassigned and 1+ ions. The dynamic exclusion was set to 20 s. For CAPTURE pulldown protein identification, MS/MS spectra were searched using MaxQuant (version 1.6.3.4) and filtered in Perseus. Search parameters included trypsin or LysC cleavage with up to two missed cleavage events. Searches also permitted variable modifications of methionine oxidation or acetylation, and carbamidomethylation as fixed modification. Precursor ion tolerance was 20 ppm. Peptide assignments were filtered to a false discovery rate (FDR) of 1% on the peptide level. The data are displayed in Streptococcus pyogenes and common contaminants. During database searches, cysteines (C) were considered to be fully carbamidomethylated , methionine (M) to be fully oxidised , all N-terminal residues to be acetylated . Two missed cleavages were permitted. Peptide mass tolerance was set at 50 ppm and 0.02 Da on the precursor and fragment ions respectively. Protein identification was filtered at FDR below 1%. The data are displayed in CAPTURE was carried out essentially as described in . As a coWestern blot analysis was performed as previously described  using ap7 HEK293 cells crosslinked with 1% formaldehyde at room temperature for 10 min. For qPCR, the Ct value (copies/µL) for each sample was quantified relative to the standard and the IgG control Ct value was subtracted. The resulting values are the % of input being pulled down as shown in the ChIP graphs. Experiments were replicated at least three times and each ChIP sample was measured in triplicate by qPCR. Data presented represent the mean ± SEM (standard error of the mean) of three independent experiments. IgG IP was carried out for each experiment and any signal below that of IgG was considered as background and subtracted from the specific antibody value. The value for the U2 PSE primers was normalized to 1 before calculating the SEM for the other primer pairs. The antibodies used are listed in https://www.cellsignal.co.uk/products/primary-antibodies/spt6-d6j9h-rabbit-mab/15616) (accessed on 1 March 2022) (CDK12 Novus-https://www.novusbio.com/products/crkrs-antibody_nb100-87011) (accessed on 1 March 2022) (Cyclin K https://www.fortislife.com/products/primary-antibodies/rabbit-anti-cyclin-k-antibody/BETHYL-A301-939) (accessed on 1 March 2022).ChIP and qPCR were performed essentially as described by  using apThe primers used for qPCR are listed in CDK12 ChIP-seq in HEK293 CDK12as cells was performed with the LSBio CDK12 antibody listed in RNU2 locus (U2 snRNA genes) was obtained from GenBank (U57614.1) and re-analysed as previously described [The Gencode V35 annotation, based on the hg38 version of the human genome, was used to extract the list of snRNA genes, excluding snRNA pseudogenes and pol III transcribed snRNA genes. The DNA sequence of the human escribed . HEK293 escribed . HeLa Chescribed .RNU2 gene or to the GRCh38.p13 reference sequence with STAR version 2.7.3a [RNU2 gene and to the human genome to calculate for each sample the normalization factor. Library-size normalized bedGraph files were created with BEDtools genomecov. Profiles across the RNU2 gene were created with GraphPad Prism 9.1 ).Adapters were trimmed with Cutadapt  version n 2.7.3a  and the n 2.7.3a  version n 2.7.3a  version RNU2 gene or to the GRCh38.p13 reference sequence with STAR version 2.7.3a and the parameters: --runThreadN 16 --readFilesCommand gunzip -c -k --limitBAMsortRAM 20000000000 --outSAMtype BAM SortedByCoordinate. SAMtools version 1.9 was used to retain the properly paired and mapped reads (-f 3) and to create strand-specific BAM files. SAMtools was used to obtain the number of reads mapping to the RNU2 gene and to the human genome to calculate for each sample the normalization factor. Library-size normalized bedGraph files were created with BEDtools genomecov. Profiles across the RNU2 gene were created with GraphPad Prism 9.1.Chromatin RNA-seq were analysed as previously described . BrieflyCRISPR affinity purification in situ of regulatory elements (CAPTURE) exploits dCas9 directed to specific gene regions by RNA guides followed by crosslinking to capture the associated proteins . As the We first carried out some experiments using FLAG-tagged dCas9 (FdCas9) to identify guides that are specific for the region targeted and to ensure that dCAS9 targeted to the genes does not interfere with transcription. We designed and tested a range of single and paired guides a. PairedGuides targeting DSE, PSE, and the 3′ box were cloned into pX462  with an ChIP-qPCR across the U2 snRNA genes shows clearly that dCas9 is not targeted to the different genomic regions with the same efficiency. For example, the recruitment of Cas9 to the 3′ box region is low relative to the DSE and PSE. This may be due to the transcriptional complex associated with this region of the U2 snRNA genes blocking FdCas9 access. In addition, pairs of guides were not more efficient than single guides. Based on these results, guides G3 and G6 were chosen for further experiments targeting the DSE and PSE regions of the U2 snRNA gene, respectively, and 3′ box region CAPTURE was not attempted.In order to assess the specificity of the guides, the PSE region of the U1 snRNA genes was also analysed by qPCR when targeting the U2 PSE region with the G6 guide e. AlthouOnce the guides were chosen, stable cell (SC) lines were generated for FdCas9 only and FdCas9 + Guide 3 (FdCas9 + G3). dCas9 expression was confirmed by Western blot a and FdCAs the streptavidin–biotin interaction is stronger than an antibody–antigen interaction, stable cell lines expressing dCas9BAP and BirA were generated. Western blot confirmed that dCas9BAP is expressed and biotinylated in vivo c. ChIP qhttp://geneontology.org (accessed on 1 March 2022)) for Reactome pathways enrichment analysis [U2 snRNA gene CAPTURE was carried out by transiently transfecting Guides 3 or 6 into the HEK293 cell line stably expressing dCas9BAP and BirA. The cells were crosslinked with formaldehyde and pull-down of the dCas9 using streptavidin beads was carried out as detailed in analysis ,56 and panalysis . TCEA1/2analysis . As it ianalysis . The rolanalysis  in expreOther transcription factors that were enriched include the elongation factor SPT6 ,42; CyclInterestingly, the protein-coding gene factors involved in termination and RNA 3′ end formation, CSTF1, CSTF2, and CPSF1 were also enriched in the CAPTURE dataset. CSTF2 (CSTF64), Pcf11, and Ssu72 have already been shown to be associated with the U2 gene by ChIP and PCF11 and Ssu72 aid termination of transcription .Several subunits of snRNPs, including the SF3B4 and SF3B6 subunits of the U2 snRNP, and several pre-mRNA/mRNA binding or splicing factors, including U2AF1, SF1, SRSF1, SRSF3, SRS7, and SRS9 were also, surprisingly, enriched by CAPTURE. As U snRNA genes are intronless, these factors would have a splicing-independent role, if any, in the regulation of expression of the U2 snRNA genes. Many of these could well be interacting with the dCas9 or the associated RNA non-specifically. However, the U2 snRNP has been shown to facilitate 3′ end formation of the intronless and non-polyadenylated transcripts from replication-activated histone genes .The streptavidin–biotin CAPTURE therefore appears to be quite efficient as many expected proteins were enriched, many proteins were enriched in both the DSE and PSE CAPTURE datasets and in most cases, proteins were not present at all in the negative control .In order to validate the association of some CAPTUREd factors with the U2 snRNA genes, we have reanalysed our previously published SPT6 ChIP-seq datasets from 293 CDK12 analogue-sensitive (as) cells (in the absence of inhibitor)  and founCyclin K was enriched with the U2 PSE guide CAPTURE, suggesting that CDK12 and/or CDK13 are recruited to U2 genes. We performed CDK12 ChIP-seq in 293 CDK12as cells in the absence of inhibitor  and ChIPTranscription initiation of snRNA genes is mediated by transcription factors like Oct-1, which recognize the DSE element, and by PTF binding to the PSE, which nucleates a pre-initiation complex similar to that on protein-coding genes ,14,15,64Gratifyingly, many factors with known roles in snRNA gene expression or that had previously been shown to be associated with these genes were enriched by CAPTURE. The RPB2 subunit of pol II, CDK7, SPT5, NELF, TFIIS, XRN2, MED23, and the SSRP1 subunit of FACT and the polyadenylation factor, CSTF2 were all enriched, in addition to several subunits of Integrator, including INTS11, the catalytic subunit.1S2P3T4S5P6S7. Phosphorylation of the CTD on Ser2 by CDK9 and Ser7 by CDK7 helps to recruit Integrator [The enrichment of Cyclin K suggests that its partners CDK12 and/or CDK13 are also part of the transcription machinery and we have validated CDK12 association by ChIP and ChIP-seq. CDK12 is a transcription elongation and pol II CTD kinase  with mantegrator . CDK12 cWe also validated the association of SPT6, which we have shown plays an important role in Integrator recruitment to the U2 snRNA genes in addition to other ncRNA genes . Loss ofIt will be interesting to investigate the potential roles of SPT6 and CDK12 in coupling transcription initiation from an snRNA promoter to 3′ box recognition. For example, phosphorylation of the pol II CTD and/or SPT6 by CDK12  could enThe SWI/SNF-related, matrix-associated, actin-dependent regulators of chromatin (SMARC)A4, A5, CC1, and CE1 factors are part of the SWI/SNF chromatin remodelling complex . The SWICAPTURE has therefore implicated more ‘protein-coding gene’ transcription and RNA processing factors in snRNA gene expression.Drosophila melanogaster histone genes [In common with other published dCas9 pull-down studies, including Cas9 locus-associated proteome (CLASP) of ne genes , we retrDespite this, CAPTURE has helped us to identify SPT6 and CDK12/Cyclin K as novel components of the transcription machinery associated with the human U2 snRNA genes. Thus, although the association and potential role of interesting chromatin remodelling, transcription, and RNA processing factors—picked up by CAPTURE on these genes—remain to be validated, streptavidin–biotin CAPTURE has proven useful to identify factors involved in expression of the human U2 snRNA gene.


COL1A1 encodes the type I collagen α1 chain, which shows the highest abundance among members of the collagen family and is widely expressed in different mammalian cells and tissues. However, its molecular characteristics are not completely elucidated. In this study, the molecular profiles of COL1A1 and characteristics of the COL1A1 protein were investigated using a promoter activity assay and multiple bioinformatics tools. The results showed that the 5′ flanking region of porcine COL1A1 contained two CpG islands, five core promoter sequences, and twenty-six transcription factor-binding sites. In the luciferase assay, the upstream 294 bp region of the initiation codon of COL1A1 showed the highest activity, confirming that this section is the core region of the porcine COL1A1 promoter. Bioinformatic analysis revealed that COL1A1 is a negatively charged, hydrophilic secreted protein. It does not contain a transmembrane domain and is highly conserved in humans, mice, sheep, and pigs. Protein interaction analysis demonstrated that the interaction coefficient of COL1A1 with COL1A2, COL3A1, ITGB1, and ITGA2 was greater than 0.9, suggesting that this protein plays a crucial role in collagen structure formation and cell adhesion. These results provide a theoretical basis for further investigation of the functions of porcine COL1A1. The extracellular matrix (ECM) consists of approximately 300 proteins that collectively provide mechanical support and perform signaling functions in mammalian cells . The evoType I collagen is the most widely expressed member of the collagen family of proteins and is the main component of the skin, bone, cornea, and other tissues . Type I COL1A1 encodes the type I collagen α1 chain, which is associated with cell proliferation, invasion [COL1A1 is located on chromosome 12 and has a total length of 18,094 bp (NC_010454) and high GC content (59.8%). According to the gene expression atlas analysis , COL1A1 is widely expressed in different porcine tissues and cells, such as the corpus callosum, stomach, epididymis, omentum, mesenteric lymph nodes, and porcine fetal fibroblasts, suggesting that the COL1A1 locus can be used as a candidate safe harbor to mediate the wide expression of foreign genes in the porcine genome [COL1A1 have not been extensively studied. The gene promoter is a complex area containing numerous binding sites for transcription factors, which determines the transcription start site and frequency [COL1A1 was predicted and analyzed, and promoter activity was verified. Furthermore, the structure and function of porcine COL1A1 were predicted. The results provide valuable information for further studies on the functions of porcine COL1A1.invasion ,11, and invasion ,13,14. Iinvasion , skeletainvasion , osteogeinvasion , osteopoinvasion , and othinvasion . In addiinvasion ,21,22,23e genome . Howeverrequency . TherefoCOL1A1 (2405 bp before the initiation codon) was obtained from the National Center for Biotechnology Information database. The core active region of the COL1A1 promoter was predicted using Network Promoter Prediction online software. CpG islands were predicted using MethPrimer. Putative promoter transcription factor-binding sites were predicted using Jaspar 2022. Sequences 500 bp before the initiation codon in humans, mice, sheep, and pigs were downloaded from the National Center for Biotechnology Information database and compared with the results of analysis of the core promoter of porcine COL1A1. The detailed software information is presented in The 5′ flanking region of COL1A1 promoter vectors of different lengths, genomic DNA was extracted from porcine embryonic fibroblast (PEF) cells using the TIANapm Genomic DNA Kit  and used as a template for polymerase chain reaction (PCR). Five promoters of pig COL1A1 with different lengths were obtained. As a positive control, the cytomegalovirus (CMV) promoter was also cloned from the pX458 vector using PCR. The promoters included 334 bp , 498 bp , 905 bp , 1478 bp , 2445 bp , and 548 bp . The primer sequences are shown in TM Gel DNA Recovery Kit .To construct porcine COL1A1 promoter constructs of different lengths, namely pGL3-294, pGL3-458, pGL3-865, pGL3-1438, pGL3-2405, and the CMV promoter, pGL3-CMV, were ligated into the pGL3-Basic vector using seamless cloning technology [TM Gel DNA Recovery Kit in accordance with the manufacturer’s protocol. The purified PCR products and linearized vectors were reconstituted and ligated as follows: 1 μL PCR product, 1 μL linearized vector, 5 μL 2× ClonExpress Mix, and water , followed by a reaction at 50 °C for 30 min. The recombinant plasmids were transformed into DH5α competent cells and cultivated on Luria-Bertani solid medium containing ampicillin. The next day, a single colony was selected for sequencing using the universal primer, RVPrimer3 . Colonies with correct sequences were expanded and cultured, and all plasmids were extracted in large quantities using EndoFree Plasmid Midi Kits  for subsequent cell transfection.The pig chnology . To dete2 in a humidified incubator . Both PEF and IPI-2I cells were mycoplasma-free.PEFs were isolated from a single 35-day-old Large White pig fetus by our lab, and maintained in Dulbecco’s modified Eagle’s medium  supplemented with 15% fetal bovine serum (Gibco), 1% penicillin/streptomycin (Gibco), 1% GlutaMAX (Gibco), 1% non-essential amino acids (Gibco), and 1% sodium pyruvate (Gibco). The cells were passaged for six generations prior to transfection. Porcine intestinal epithelial (IPI-2I) cells, a cell line established from the porcine ileum, were a kind gift from Prof. Shaobo Xiao . The cells were cultured in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 1% penicillin/streptomycin, and 1% GlutaMAX. All cells were maintained at 37 °C and 5% CO5) were co-transfected with 2 μg pGL3 series firefly luciferase plasmids and 10 ng Renilla luciferase plasmids using a Basic Primary Fibroblasts Nucleofector Kit  in accordance with the manufacturer’s instructions. The optimal transfection procedures for the PEFs and IPI-2I cells were U-023 and S-005, respectively. The cells were then transferred into 12-well plates and cultured at 37 °C in an incubator with 5% CO2. The medium was replaced 6 h after transfection.The cells were transferred into a 10 cm dish two days before transfection. When the cells reached 80–90% confluence, they . Twenty-four hours after transfection, the cells were harvested for lysis, and 20 μL of the supernatant lysate was transferred to a new opaque white 96-well plate. Subsequently, 100 μL of firefly fluorescence substrate was added to each well, and the fluorescence signal intensity of the firefly was detected using a microplate reader . Renilla luciferase substrate (100 μL) was added to detect the Renilla luciferase signal, and relative luciferase activity was calculated as the ratio of firefly fluorescence to Renilla luciferase fluorescence. Transfection efficiency was based on co-transfected Renilla luciferase values. For each construct in each experiment, at least three transfections were carried out.Transcriptional activity of the porcine Amino acid sequences of COL1A1 from different species, including humans, mice, sheep, and pigs, were downloaded from the UniProt database and compared. The physicochemical properties were analyzed using ProtParam. Hydrophilicity or hydrophobicity was predicted using ProtScale. Signalp-5.0 and TMHMM-2.0 software were used to analyze the signal peptide and transmembrane domain of the protein. The secondary structure, domain, and tertiary structure of COL1A1 protein were predicted using SOPMA, InterPro domain, and Swiss-Model software. Protein interaction analysis was performed using STRING software. Detailed information on the software and websites is provided in Renilla luciferase fluorescence) was presented as the means ± standard errors (SEM). Differences were accessed and analyzed by using a one-way analysis of variance (ANOVA) followed by Fisher’s least significant difference test as a multiple comparison test with SPSS 20.0 . p values less than 0.05 were considered significantly different. Data were virtualized using GraphPad Prism 6.0.0 .The relative luciferase activity  than that of the pGL3-458 (−458–0 bp), pGL3-865 (−865–0 bp), pGL3-1438 (−1438–0 bp), and pGL3-2405 (−2405–0 bp) vectors  in humans, mice, sheep, and pigs were highly conserved. In addition, studies in humans and mice have shown that the core promoter of COL1A1 is in this region [COL1A1 may be located 500 bp before the ATG codon. The results of the luciferase assay in porcine PEF and IPI-2I cells showed that the core promoter was 294 bp before ATG, although the porcine COL1A1 promoter (2405 bp before ATG) showed promoter activity.Bioinformatics analysis and luciferase assays are common methods for studying the core and regulatory regions of promoters ,43. To us region ,44. ConsCOL1A1 based on comparison with transcription factors that bind at −294 to 0 and −458 to −294 bp. This result is consistent with the findings of previous studies which demonstrated that MZF1 can negatively regulate COL1A1 expression in gastric adenocarcinoma and breast cancer [COL1A1 in humans, thus positively regulating its expression [COL1A1 in NIH3T3 fibroblasts in mice, and SP1 may interfere with the transcriptional activation of NFIC. However, in the herpes simplex virus thymidine kinase (TK1) promoter, the binding sites of SP1 and NFIC are inconsistent, and both SP1 and NFIC can enhance transcriptional activity [COL1A1 promoter, suggesting that both SP1 and NFIC positively regulate the expression of porcine COL1A1. GATA2 is a member of the GATA family of transcription factors, which have important roles in cell proliferation and differentiation. A previous study reported a negative correlation between GATA2 and COL1A1 expression in patients with breast and ovarian cancers [GATA2-knockdown in vascular endothelial cells led to upregulated expression of COL1A1 [COL1A1. In addition, the CEO database showed that the GlI–Krüppel family of zinc finger protein transcription factors (YY1) [SOX gene family (SOX10) [COL1A1 expression. The effect of the overexpression or knockdown of related transcription factors on the activity or expression of the porcine COL1A1 promoter should be further explored. In addition, the detection of GpC islands in the promoter region suggests that DNA methylation plays an important role in regulating COL1A1 expression.Interestingly, the activity of the promoter decreased significantly as the promoter fragment increased in length in different porcine cells and showed the lowest level for the promoter of −2405 to −1458 bp. Negative regulatory elements may be present in the region from −1458 to −294 bp. Hence, we predicted the transcription factors in this region and mainly detected MZF1, SP1, GATA2, NFIC, and other transcription factor-binding sites. MZF1, a member of the C2H2-type zinc finger protein family, is involved in the proliferation and differentiation of blood cells . MZF1 mat cancer ,28. As at cancer . Many stt cancer ,49,50 anpression . Howeveractivity . We did  cancers . Moreovers (YY1) , tryptoprs (YY1) ,34, SOX  (SOX10) ,36, and  (SOX10) ,38 may hProtein domains are units of protein structure, function, and evolution . PorcineCOL1A1 exhibits typical eukaryotic promoter characteristics, with five promoter sequences, two CpG islands, and multiple negative transcription factor binding sites that regulate its expression. The core promoter region is 294 bp upstream of the initiation codon. As a negatively charged, hydrophilic secreted, and non-transmembrane protein, COL1A1 may play a crucial role in collagen structure formation and cell adhesion. This study provides an important theoretical basis for further studies of the transcriptional regulatory mechanism and functions of porcine COL1A1.The 5′ flanking region of porcine


The greatest remaining challenge in understanding genome regulation is to elucidate the full panoply of effects following from 3D genome organization and its temporal dynamics. Despite this field predating the discovery of transcription factors and epigenetics by 100 years, we probably know less than 10% of how 3D genome regulation works. Outstanding questions remain regarding the mechanisms underlying rapid versus post-mitotic gene repositioning, how the distinctive genome organization patterns of different tissues translates to fine-tuning of gene expression specifically in those tissues, the role of repositioning of non-gene loci such as enhancers and miRNA-encoding regions, the contributions of dynamic versus developmental genome repositioning events, the range of roles for nuclear bodies, and the interplay between genome organization and other factors such as epigenetics, nuclear transport, and mechanics to name a few. Major technical challenges range from understanding the relationship between chromosome connections to nuclear structures and the mechanics and physical forces that follow to quantitative aspects such as distinguishing how much genome organization or epigenetics each contribute to gene expression or determining the extent of phase separation that actually occurs in cells. The goal of the new Section on Nuclear Organization and Dynamics is to not only highlight such studies, but also provide a platform to help the field identify best practices and uniform standards so that it is easier to compare the results of different studies.The field of genome organization effectively started when microscope advances in the 1830s allowed resolution to 1 µm  and thusTechnique development has been central to the evolution of the modern field of nuclear organization and dynamics. Refinements in the sensitivity of nucleotide hybridization approaches set the stage for observations from Harinder Singh, Amanda Fisher and others that important developmental genes reposition in a tissue-specific manner during development from the nuclear periphery to the interior as they become activated . Global 1) Cell type specific patterning vs. environmental responses. Some of the earliest observations that invigorated the modern field were of tissue-specific repositioning of important developmental genes in tissue differentiation , but hig2) Rapid versus mitosis-dependent genome organization changes and the relative contributions of directed vs. stochastic forces. Several experimental systems indicated a requirement of cells to go through mitosis to achieve changes in genome organization . Howeverin vitro systems had an effect on the efficiency of retrovirus insertion and Tn3 resolvase function (3) What tethers different chromosome regions to different nuclear bodies and the nuclear envelope and what kinds of physical forces are involved? Genes appear to be tethered to the nuclear envelope through larger complexes involving at least the intermediate filament lamin polymer, nuclear membrane proteins, transcriptional regulators, and epigenetic enzymes . Howeverfunction . It is pfunction  and if t4) Mechanisms and relative contributions. Thus far researches have mostly just observed that an aspect of genome organization or dynamics correlates with or directs changes in gene expression: the molecular mechanisms and regulation behind these changes still need to be investigated. Moreover, it could be argued that these mechanisms “fine tune” genome regulation, but understanding for example what contribution comes from a change in DNA folding recruiting more transcriptional regulators compared to what contribution comes from generating a localized concentration of a transcription factor around a nuclear body requires development of a new set of tools. It will also be important to integrate data from many different approaches to explain poor position-function correlations for genes. While DamID studies found many genes that changed expression corresponding to their changing position, there were also many genes that repositioned without changing expression or that changed expression without repositioning. The former could be explained if genes adjacent to one another move together but only the one that also has transcriptional regulators present is altered in expression, but the latter was more inexplicable. This was made the more confusing when knockdown of nuclear membrane proteins that appear to be necessary for gene repositioning events not only blocked gene repositioning but also affected expression of many genes that did not change position . Some of5) Lack of consistency and uniform standards across the field. As funders increasingly push for re-use of existing datasets, it has become commonplace to use a Hi-C, DamID, or ChIP-Seq dataset acquired in one tissue system to interrogate a mechanism or pathway using another tissue system where partners and behavior may differ. It is also very common to just use an available IMAGE clone cDNA when studying a protein without testing if that particular splice variant is the one expressed in the tissue/experimental systems being used. Moreover, many commonly used cancer cell lines have such a high rate of ploidy and other genome changes that labs using the “same” cell line could get differing results just because of these changes. These experimental deficiencies can yield both false-negative and false-positive results. In the currently trendy area of phase separation, different labs use different temperatures to achieve phase separation while some use molecular crowders and there are many other parameters that vary between published studies. It would be very useful to establish some common controls and standards to be run with each such study. As noted earlier, we still know very little about transcription factor targets and since most transcription factors act as heterodimers and their partners can change from tissue to tissue, we need complete transcription factor target studies for both binding and transcription in not just one cell type but all cell types for all transcription factors to model these questions to explain why only some genes and not others are affected. The 4D Nucleome venture led to great advances in technologies and identification of novel mechanisms; however, it did nothing to address the issues noted above and the vast majority of 4D Nucleome studies used cancer cell lines in 2D that are aberrant in myriad ways from ploidy to cell responses to “tissueness”. While many experimental approaches can only be performed in tissue culture, cells in culture are generally exposed to 100x more oxygen than cells in a tissue and 3D contacts and tension on a cell in the tissue environment differ enormously from 2D tissue culture resulting in differences in nuclear morphology, nuclear mechanics, and mechanosignal transduction. Such issues could in part explain historical poor correlations between gene position and function, contradictory findings between different labs, and many other problems in the field. These issues could be addressed through community changes and networks using uniform standards to map genome architecture, transcription factor binding, enhancers, epigenetics and many other factors across all tissues for humans and each major experimental organism.Only when the issues raised above have been addressed will it be possible to establish a Grand Unified Theory of Nuclear Organization. The umbrella of nuclear and genome organization and dynamics keeps growing, including both aspects such as Epigenomics and Epigenetics, Developmental Epigenetics, Cancer Cell Biology, Stem Cell Research, and Signaling that are covered elsewhere at Frontiers in Cell and Developmental Biology and aspects that do not have their own Sections such as Nucleoskeletal and Cell Mechanics, NPC Structure and Function, and Mechanosignal Transduction. Thus, while the original intended focus for this section was on genome regulation from 3D genome organization and dynamics, the Nuclear Organization and Dynamics Section will be happy to entertain papers from this wider range of areas that currently do not have their own Section in the journal.


The eukaryotic nucleus displays a variety of membraneless compartments with distinct biomolecular composition and specific cellular activities. Emerging evidence indicates that protein-based liquid–liquid phase separation (LLPS) plays an essential role in the formation and dynamic regulation of heterochromatin compartmentalization. This feature is especially conspicuous at the pericentric heterochromatin domains. In this review, we will describe our understanding of heterochromatin organization and LLPS. In addition, we will highlight the increasing importance of multivalent weak homo- and heteromolecular interactions in LLPS-mediated heterochromatin compartmentalization in the complex environment inside living cells. The eukaryotic nuclei are heterogeneous containing multiple membraneless organelles with distinct compositions, metabolism, and dynamics . In eukaIn vivo, the two components can be distinguished by differential DNA staining under the microscope  during the interphase. In the last decades, several groups have investigated the composition, function, and dynamics of heterochromatin compartments ..35–38].Further, the droplets formed by LLPS might undergo a further transition to less reversible gel-like and, at extreme conditions, solid condensates. This process is named phase transition , right. in vivo and in vitro results show that α-Syn can form liquid-like droplets, which eventually transform into amyloid-hydrogel-containing oligomers and fibrillar species ..47–55]. t manner . The cont manner . BesidesLLPS was shown to drive heterochromatin compartmentalization, such as 1) pericentric heterochromatin foci which could be mediated by heterochromatin protein 1 (HP1) , 53BP1 , methyl-Xist long non-coding RNA initiated X chromosome inactivation (XCI) by recruiting ubiquitous Xist-RNA binding proteins (RBPs) via the multivalent E-repeat element of the Xist. Yet, the maintenance of the inactive X compartment is independent of Xist RNA (LLPS is involved in Xist RNA  61].Fi.FiXist Xist-dependent silencing to Xist-independent during embryonic stem (ES) cell differentiation [XCI is the transcription repression of one X chromosome in female cells to ensure equivalent expression levels of X-located alleles between male and female cells . Heterocntiation ,69.Xist contains multiple functional elements featured with repetitive motifs including the E-repeat element [The long non-coding RNA  element . The E-r element ,69–72.Xist-protein interactions via the Xist∆E (E-repeat depletion form of Xist) or depletion of PTBP1, MATR3, TDP-43, and CELF1 resulted in more dispersed Xist foci with increased foci number. This could be rescued by targeted expression of the above mentioned genes [Xist transcripts into individual Xist foci, their localization and stabilization. During differentiation, the X-chromosome gene silencing state could not be maintained in cells expressing Xist∆E, accompanied by decreased DNA and H3K27me3 intensities within Xi [In vitro, the PTBP1 LLPS was enhanced by E-repeat RNA and CELF1, whereas the TDP-43 or MATR3 phase separations were diminished by point mutations [In vivo, the point mutations that abolished the LLPS of TDP-43 or MATR3 failed to rescue the gene silencing in the differentiating cells with Xist∆E expression [Xist and enforce X-chromosome gene silencing. Moreover, CELF1 enrichment at Xi remained upon depletion of Xist [Xist-independent manner in the Xist-independent stage.In ES cells, disrupting ed genes . This leithin Xi , indicatithin Xi , TDP-43 ithin Xi , and MATithin Xi . In vitrutations . In vivopression . Thus, t of Xist , indicatMethyl-CpG binding protein 2 (MeCP2) is the most studied member of the methyl-CpG binding domain (MBD) containing proteins, which recognize the 5-methyl-cytosine (5mC) modification in the DNA. MeCP2 has been shown to form LLPS in the absence of DNA in physiological concentrations ,59. MeCPThere is a certain controversy concerning the results obtained regarding the effect of 5mC containing DNA in MeCP2 LLPS. In all studies, 5mC containing DNA promoted LLPS formation, but they showed different outcomes when comparing the effect of 5mC on the size of the droplets relative to the respective unmethylated DNA. A potential explanation for this phenomenon could be the different distances between MeCP2 binding sites  in the different studies . With a Recent modeling studies suggest that immobilization of a protein capable of LLPS reduces the compartment size , and thiIn addition to limiting the compartment size, 5mC also plays a role in targeting MeCP2 to heterochromatin regions. MeCP2 mutants that affect the MBD binding to 5mC are not located in the heterochromatin  but, wheHeterochromatin binding protein 1 (HP1) is a non-histone chromosome-binding protein . HP1α, oin vitro experiments can be used to better understand how these membraneless compartments are formed in vivo. However, it is remarkable how small variations of any of the components of the reaction  affect the final result of droplet formation or growth. Thus, it is increasingly important to establish standards in LLPS research and to quantitatively analyze the consequences caused by local perturbation  both in vitro and in vivo. Only with such combined approaches, it will become possible to: i) compare results of different studies; ii) explore how LLPS dysfunctioning relates to (patho)physiology; and iii) elucidate how multiple factors come together or not to shape subcellular compartmentalization  and, as such, regulate cellular metabolism and cell fate decisions.As seen in the previous chapters, LLPS is one of the major driving forces for heterochromatin compartmentalization and


Growth differentiation factor 11 (GDF11) has been implicated in rejuvenating functions in age-related diseases. The molecular mechanisms connecting GDF11 with these anti-aging phenomena, including reverse age-related cardiac hypertrophy and vascular and neurogenic rejuvenation, remain unclear. In this study, we sought to uncover the molecular functions of GDF11 using bioinformatics and network-driven analyses at the human gene and transcription levels using the gene co-expression network analysis, the protein–protein interaction network analysis, and the transcription factor network analysis. Our findings suggested that GDF11 is involved in a variety of functions, such as apoptosis, DNA repair, telomere maintenance, and interaction with key transcription factors, such as MYC proto-oncogene, specificity protein 1, and ETS proto-oncogene 2. The human skin fibroblast premature senescence model was established by UVB. The treatment with 10 ng/mL GDF11 in this cell model could reduce cell damage, reduce the apoptosis rate and the expression of caspase-3, and increase the length of telomeres. Therefore, our findings shed light on the functions of GDF11 and provide insights into the roles of GDF11 in aging. According to a report published by the Department of Economic and Social Affairs, Population Division, United Nations, the number of people aged 65 years or over was 727 million worldwide in 2020, with the global elderly population increasing and estimated to reach 1.5 billion by 2050  and nonhomologous end-joining [NHEJ]). In the adipose tissue, we found that the GDF11 module was involved in single- and double-stranded DNA repair by GG-NER, BER, MMR, and HDR. Double-stranded break repair is also found in the left ventricle, involving HDR and NHEJ, whereas only BER is involved in the pituitary. Moreover, the GDF11 module functions as a DNA damage checkpoint in the tibial nerve.3.4Telomeres and telomerases are likely to play roles in circadian biological clocks involving cellular replicative senescence. Previous studies have focused primarily on telomere maintenance and slowing the aging process . Our resGenetic co-expression network studies surrounding GDF11 have also implicated GDF11 in relieving ER stress caused by aging in the NCAM signaling pathway, which could benefit cell survival and regeneration; in the toll-like receptor pathway for necroptosis, which could help to clear aging cells; in the PI3K/AKT signaling for proliferation; and lastly, in the MAPK/ERK signaling for proliferation and angiogenesis. Our findings involving apoptosis, DNA repair, telomere maintenance, and other GDF11 functions may help explain the role of GDF11 in reversing age-related diseases.3.5Using the protein networks from the STRING databases, we searched GDF11 and its first (yellow) and second (lavender) layer neighboring proteins and visualized the protein networks using Cytoscape .The GDF11 STRING network in 3.6We used FANTOM5 , a comprFrom our data, we concluded that the most common transcription factor neighbors of GDF11 are cAMP response element-binding protein 1 (CREB1) and nuclear transcription factor Y subunit alpha (NFYA), which is identified in 93.42% of cell types (Table S3). These findings suggested that CREB1 and NFYA are highly conserved and related to the most common function of GDF11 across cell types and systems. CREB1 connects GDF11 with CTCF , ETS pr3.7P < 0.01). Furthermore, RT-qPCR was carried out to detect the telomere length of cells in each group (P < 0.01). The findings revealed that the telomere length of cells in the control group, the Model group, and the Model + GDF11 group was 9.274 ± 0.732, 5.489 ± 0.387, and 7.236 ± 0.449, respectively. Based on the above experimental results, we could conclude that GDF11 can effectively alleviate the premature senescence of HSFs induced by UVB.To further explore the role of GDF11 in the premature senescence of cells, we established an HSF premature senescence model and treated it with GDF11, followed by detection of the cell-related indicators. The cell morphology of each group is shown in 4Previous studies have shown that GDF11 may reverse age-related heart hypertrophy, improve nervous system function, and increase angiogenesis in aging animals ,4. DurinBased on our bioinformatics analyses of gene co-expression networks, protein–protein interaction networks, and transcription factor networks, we found that GDF11 is involved in apoptosis, DNA repair, telomere maintenance, transcriptional regulation, cell survival, angiogenesis, and cellular regeneration. We also identified potential novel-related transcription factors of GDF11, including MYC, SP family, CREB1, and ETS2. In the subsequent sections, we have discussed the common and novel functions uncovered by our GDF11 network analyses in detail.Based on the human genetic data analysis, apoptosis is the most common function of GDF11 among systems . Apoptosis plays a significant role in longevity . Along wOur results indicate that GDF11 is also involved in DNA damage repair and DNA damage checkpoints. DNA damage occurs constantly in human cells and can be attributed to environmental factors, such as UV or X-ray exposure. Extensive and cumulative DNA damage results in cell carcinogenesis, cell death, or apoptosis. Along with aging, the rate of DNA repair decreases, and a large amount of DNA damage occurs. In this case, age-related diseases are prone to occur, which can, sometimes, even cause cancer . FurtherTERT gene expression, and silencing of ETS2 results in decreased TERT gene expression [TERT can be inhibited by E2F transcription factor 1 (E2F1) [TERT and telomere length. It can promote telomere synthesis by upregulating TERT transcription through SP1, ETS2, and MYC. At the same time, TERT and telomere synthesis can be inhibited by MYC and E2F1, and the MYC feed-forward reaction can precisely regulate TERT levels. This bidirectional regulation of telomerase is necessary. TERT overexpression induces tumor-like hyperproliferation, which is unfavorable for tissue and organ stability. However, with the bidirectional regulation of TERT transcription, telomeres can be regulated by controlling levels, which prolong telomere length, slow down cell senescence, restore organ function, maintain body homeostasis, and prolong the life of an organism to a certain extent. A recent study has shown that GDF11 has a positive effect on the maintenance of telomere length, which supports the conclusions of this study; however, it does not provide a specific mechanistic analysis [TERT transcription to maintain telomere length, which provides new directions and targets for subsequent experimental verification.Our results also link GDF11 with telomere function. Telomeres are regions of repetitive nucleotide sequences at each end of a chromosome, which protect the end of the chromosome from deterioration or fusion with neighboring chromosomes. During chromosome replication, the enzymes that duplicate DNA cannot continue their duplication to the end of a chromosome. Thus, in each replication, the end of the chromosome is shortened, which has been associated with aging. The length of telomeres has become a symbol of longevity, and telomere shortening is associated with age-related diseases. Therefore, prolonging telomere length has become a significant research direction to delay aging. Our research suggests that GDF11 can upregulate telomeres by regulating telomerase reverse transcriptase (TERT) through the transcription-related factors SP1, ETS2, and GDF11/SMAD/CTCF/MYC signaling pathways. Telomerase acts as reverse transcriptase in telomere elongation. TERT is a catalytic subunit of telomerase, which, together with the telomerase RNA component, is the most important unit of the telomerase complex. The TERT gene promoter region has SP1-, ETS2-, and MYC-binding sites, and the three could synergistically activate TERT transcription and direct telomere elongation . Among tpression . MYC plapression . MYC canpression . From ou1 (E2F1) , which ianalysis . In this5From our bioinformatics network analyses, it could be concluded that inhibiting apoptosis, repairing DNA damage, and maintaining telomere length are closely related to aging. These are the main mechanisms for promoting proliferation and maintaining normal physiological functions in aging organisms, which can explain the anti-aging effects of GDF11 in various tissues and organs. The results of our gene co-expression network and transcription factor network analyses complemented each other. Taken together, in our study, these functions of GDF11 could explain the anti-aging phenomenon and involve the related transcription factors in the process, including MYC, SP1, and ETS2.in silico predictions of GDF11 functions, revealing both previously known  and novel  functions of GDF11, which may underlie its anti-aging effects. Although we used multiple credible databases and complementary methodologies to cross-validate our findings, the accuracy of our results relies on the quality and comprehensiveness of the datasets involved, and further experimental testing is warranted to validate our predictions resulting from network analyses. It is our goal that these findings contribute to clarifying mechanisms involving GDF11 in rejuvenation and identify candidate biomarkers or therapeutic targets for future research.In summary, our comprehensive network analysis of GDF11 provides


Transcription factors directly regulate gene expression by recognizing and binding to specific DNA sequences, involving the dynamic alterations of chromatin structure and the formation of a complex with different kinds of cofactors, like DNA/histone modifying-enzymes, chromatin remodeling factors, and cell cycle factors. Despite the significance of transcription factors, it remains unclear to determine how these cofactors are regulated to cooperate with transcription factors, especially DNA/histone modifying-enzymes. It has been known that DNA/histone modifying-enzymes are regulated by post-translational modifications. And the most common and important modification is phosphorylation. Even though various DNA/histone modifying-enzymes have been classified and partly explained how phosphorylated sites of these enzymes function characteristically in recent studies. It still needs to find out the relationship between phosphorylation of these enzymes and the diseases-associated transcriptional regulation. Here this review describes how phosphorylation affects the transcription activity of these enzymes and other functions, including protein stability, subcellular localization, binding to chromatin, and interaction with other proteins. Protein phosphorylation is crucial for various cellular processes, including cell growth, DNA damage, metabolism, inflammation. By definition, various protein kinases phosphorylate serine (Ser), threonine, and tyrosine of targeted proteins. Phosphorylation is one of the most common post-translational modifications (PTMs). It generally alters the structural conformation and interaction of proteins, by which it directly influences protein stability, cellular localization, protein/DNA binding, and enzymatic activity .www.phosphosite.org) and the Kinexus PhosphoNET (www.phosphonet.ca). Among these reported proteins, there are some transcriptional factors (TFs) and the cofactors. It has been clearly defined how TFs and the cofactors organize and regulate gene transcription. In general, TFs firstly occupy DNA elements in a sequence-specific manner, and then recruit the RNA polymerases to the gene’s promoter region, which simultaneously involve chromatin remodeling complexes and histone (de)acetyltransferases for promoter accessibility . Ly. Ly54]. KMT1A, known as SUV39H1, is phosphorylated at residues Tyr297 (mouse Tyr303 and flies Tyr308) by receptor-type tyrosine kinase ERBB4, which enhances the tri-methylation activity of histone H3K9 . And theProtein arginine methyltransferases 1 (PRMTs) are a kind of enzymes, which are mainly responsible for histone arginine methylation in cells and regulate the cell cycle and cell proliferation by remodeling chromatin status. Phosphorylation of PRMTs is essential for its enzymatic activity and protein stability. It is reported that PRMT1 is phosphorylated at Ser297 in normal liver cells, while it is dephosphorylated by PP2A at this site in response to alcohol and other oxidative stresses . It suggHistone lysine demethylases (KDMs), in contrast to KMTs, function to remove methyl groups of methylated histone proteins. The alters on histone methylation by KDMs regulate gene expression in the processes of development and tumor growth . And KDMHistone acetyltransferases (HATs) are major players in epigenetically modulating gene transcription via acetylation on histones Fig. . They reUntil now, P300 is the most studied protein about its functions influenced by phosphorylation. Among these phosphorylated sites we have summarized, phosphorylation of Ser1834 by AKT, Ser2271, Ser2279, Ser2291, and Ser2315 by mTOR, and Ser2279, Ser2315, and Ser2366 by extracellular signal-regulated kinase 2 (ERK2), significantly enhances P300 acetylation activity –107. P30AKT also phosphorylates the acetyltransferase p300/CBP-associated factor (PCAF) and increases its acetylation on high-mobility group AT-hook 2 (HMGA2) at lysine 26 (K26) for esophageal squamous cell carcinoma growth . The pho+ as a cofactor for the enzyme activity. In addition, other transcription factors, such as TCF1 and LEF1, is discovered recently to own the ability of deacetylating H3K9ac and H3K27ac [Histone acetylation and deacetylation are dynamic processes dependent on cell states. Histone acetylation and deacetylation are performed by KAT family proteins and histone deacetylases (HDACs). There are four classes of HDACs based on their homologous protein sequences: the class I RPD3-like proteins including HDAC1, HDAC2, HDAC3, and HDAC8; class II HDA1-like proteins are HDAC4, HDAC5, HDAC6, HDAC7, HDAC9, and HDAC10; class III sirt2-like proteins containing SIRT1, SIRT2, SIRT3, SIRT4, SIRT5, SIRT6, and SIRT7; class IV protein is HDAC11. Many HDACs, which belong to class I, II, IV, require a zinc ion to deacetylate acetylated lysine, but for the class III HDACs, the proteins require NAD H3K27ac . But herIn class I HDACs, HDAC1 is phosphorylated by various protein kinases and the specific sites directly influence HDAC1 subcellular localization, enzymatic activity and protein stability Table . One of Phosphorylation by various serine/threonine kinases alters the subcellular localization of HDACs. HDAC4, as one of class II HDACs, is commonly verified to be phosphorylated at Ser246, Ser467, and Ser632 by calmodulin kinase II (CaMKII), which lead to nuclear export of HADC4 to the cytoplasm –150. Ano+) as a cofactor. It is originally discovered in yeast and characterized to deacetylate histones for transcription repression [SIRT (1–7) belongs to the class III HDACs with nicotine adenine dinucleotide (NADpression . Structupression . P53 acepression . The phopression –189. SIRpression –192. AndIt is worth noting that several enzymes, including EZH2, P300, KAT7, KAT13A, and almost of HDACs, own a relatively large number of functional phosphorylation sites in the summarized tables. EZH2 is comprised of SANT domain, CXC domain, and catalytic SET domain. The phosphorylated sites in the N-terminal domain of EZH2 by various protein kinases not only inhibits its methylation activity, but also promotes its ubiquitination for degradation. Only one site, Thr350, can be phosphorylated and activates enzymatic activity of EZH2. And phosphorylation of Ser646 in the region of SET domain of EZH2 promotes its degradation in malignant lymphoma . Even itIn this review, we specifically discuss how phosphorylation regulates two kinds of transcription cofactors, including DNA methylation/demethylation-related enzymes and histone-modifying enzymes (the model in Fig. Since the discovery of histone PTMs, it has been evidenced to be dynamic and reversible . DNA and


Ten GWAS-important for KOA SNPs of eight candidate genes  were studied. To assess the link between SNPs and KOA susceptibility, logistic regression (to establish independent SNP effects) and MB-MDR (to identify SNP–SNP interactions) were used. As a result of this genetic analysis, the associations of individual SNPs with KOA have not been proven. Eight loci out of ten tested SNPs interacted with each other (within twelve genetic models) and determined susceptibility to KOA. The greatest contribution to the disease development were made by three polymorphisms/genes such as rs6976 (C>T) GLT8D1, rs56116847 (G>A) SBNO1, rs6499244 (T>A) NFAT5 (each was included in 2/3 [8 out 12] KOA-responsible genetic interaction models). A two-locus epistatic interaction of rs56116847 (G >A) SBNO1 × rs6499244 (T>A) NFAT5 determined the maximum percentage (0.86%) of KOA entropy. KOA-associated SNPs are regulatory polymorphisms that affect the expression/splicing level, epigenetic modification of 72 genes in KOA-pathogenetically significant organs such as skeletal muscles, tibial arteries/nerves, thyroid, adipose tissue, etc. These putative KOA-effector genes are mainly involved in the organization/activity of the exoribonuclease complex and antigen processing/presentation pathways. In conclusion, KOA susceptibility among Europeans of Russia is mediated by intergenic interactions (but not the main effects) of GWAS-important SNPs.This study was conducted to examine the associations between genome-wide association studies (GWAS)-important single nucleotide polymorphisms (SNPs) and knee osteoarthritis (KOA) among Europeans of Russia. The present replicative study (“patient-control” design has been used) was carried out on 1000 DNA samples from KOA ( Osteoarthritis (OA) is a common chronic degenerative joint disease , resultip < 5 × 10−8)  KOA-responsible genetic interaction models). The highest Wald index  was in a four–level genetic model: rs6499244 (T>A) NFAT5 × rs56116847 (G>A) SBNO1 × rs6976 (C>T) GLT8D1 × rs2820443 (T>C) LYPLAL1  was found for some SNPs genotypic combinations such as TT(rs6499244)NFAT5 × AG(rs56116847)SBNO1 × CT(rs6976)GLT8D1, TT(rs6499244)NFAT5 x AG(rs56116847)SBNO1 × AG(rs11177)GNL3, TT(rs6499244)NFAT5 × AG(rs56116847)SBNO1 × CT(rs6976)GLT8D1 xTT(rs2820443)LYPLAL1, TT(rs6499244)NFAT5 × AG(rs56116847)SBNO1 × AG(rs11177)GNL3 × TT(rs2820443)LYPLAL1, TT(rs6499244)NFAT5 × AG(rs56116847)SBNO1 × AG(rs11177)GNL3 × CT(rs6976)GLT8D1   factors . The gre LYPLAL1 . Very im6)GLT8D1 .SBNO1 and rs6499244 (T>A) NFAT5 possessed a strong KOA effect (registering the maximum KOA entropy percentage-0.86%).Five of the investigated 315 SNPs  were missense loci leading to amino acid substitutions in the GNL3 , SPCS1 , NEC4  and SBNO1  proteins. The above changes were predicted to be tolerated (SIFT tools information) and benign , and only Pro>Ala replacement at position 225 in NEC4 protein (rs1029871) was possibly damaging ) . Epigenetic modification of DNA regions near eighteen genes  can be caused by eight KOA-involved SNPs and 292 loci out of 309 in LD SNPs (94.50%) due to the regulation of the activity of enhancers  and promoters , communication of specific DNA sites with protein-regulators  and factors that promote the transcription process  by changing the structure of chromatin  . LYPLAL1 (rs2820436 and rs2820443), GNL3 (rs11177), GLT8D1 (rs6976), WWP2 (rs34195470) and NFAT5 (rs6499244) were localized in the enhancer DNA regions at chondrocyte cell culture (E049(Epigenome ID)/STRM.CHON.MRW.DR.MSC(Mnemonic)), primary osteoblast cells (E129(Epigenome ID)/BONE.OSTEO(Mnemonic)); loci of LYPLAL1 (rs2820443), GNL3 (rs11177) and GLT8D1 (rs6976) genes have been positioned in the adipocytes promoter sites (E023(Epigenome ID)/FAT.MSC.DR.ADIP(Mnemonic)); specific nucleotide changes of GNL3 (rs11177), GLT8D1 (rs6976) and SBNO1 (rs56116847) genes were situated in the enhancer positions of peripheral blood T helper cells (E043(Epigenome ID)/BLD.CD4.CD25M.TPC(Mnemonic)).It is important to underline that almost all KOA-associated polymorphic variants (with the exception of rs1060105) and a majority of strongly-linked loci exhibit their outstanding epigenetic effects in KOA-impact cell cultures and tissues such as primary osteoblast cells, chondrocytes, adipocytes, etc. For example, SNPs of genes such as SBNO1, rs11177 GNL3, rs6499244 NFAT5, rs6976 GLT8D1) .The four KOA-associated loci (rs1060105  GLT8D1)  and 70 h GLT8D1)  were modABCB9, ALAS1, ARL6IP4, C12orf65, CCDC62, CDK2AP1, CLEC18A, CLEC18C, COG4, DNAH1, EXOSC6, GLT8D1, GLYCTK, GLYCTK-AS1, GNL3, IL34, ITIH1, ITIH4, KMT5A, LYPLAL1-AS1, MPHOSPH9, MUSTN1, NEK4, NFAT5, NOB1, NPIPB14P, NQO1, NT5DC2, OGFOD2, PBRM1, PDXDC2P, PITPNM2, POC1A, PPM1M, PRKCD, RFT1, RILPL2, RIMKLBP2, RP11-168J18.6, RP11-282O18.3, RP11-296I10.3, RP11-392O17.1, RP11-394B2.1, RP11-394B2.5, RP11-546D6.3, RP11-894J14.2, RP11-972P1.11, RP5-1157M23.2, RP5-966M1.5, RP5-966M1.7, SBNO1, SERBP1P3, SFMBT1, SLC30A10, SMG1P7, SMIM4, SPCS1, TMEM110, WDR82, WWP2, ZC3H11B)  (Changes in the gene quantitative traits (transcription and splicing) in different organs  due to the allele-specific effects of the eight studied SNPs and high-LD loci (283 out 309 SNPs [91.59%]) have been detected as potential predictors of KOA. In total, the 61 genes transcription (ZC3H11B)  and 24 g0, WWP2)  may be cSTIMATE-MUSTN1, STIMATE–TMEM110, STIMATE–MUSTN1, MRC1–STAB1, ARID2–PBRM1, NQO2–NQO1 (indicators of weight were 0.71–0.86)  .GNL3, rs1060105 SBNO1, rs2820436 and rs2820443 LYPLAL1, rs56116847 SBNO1, rs6976 GLT8D1, rs6499244 NFAT5 and rs34195470 WWP2). The greatest contribution to the KOA susceptibility was made by the three polymorphisms/genes rs6499244 (T>A) NFAT5, rs6976 (C>T) GLT8D1, and rs56116847 (G>A) SBNO1 (each was included in 2/3 [8 out 12] KOA-responsible genetic interaction models). The associations between individual SNPs and KOA predisposition have not been supported. The present “patient-control” study demonstrated that KOA susceptibility among Europeans of Russia can be caused by intergenic interactions of eight GWAS-important SNPs (rs11177 NFAT5. For rs6499244 NFAT5 (located on chromosome 16q22.1), in silico data indicated its pronounced functional actions by influences on enhancer sequences in chondrocytes (E049(Epigenome ID)/STRM.CHON.MRW.DR.MSC(Mnemonic)), primary osteoblast cells (E129(Epigenome ID)/BONE.OSTEO(Mnemonic)), primary T-regulatory and T-helper cells of peripheral blood (E044(Epigenome ID)/BLD.CD4.CD25.CD127M.TREGPC(Mnemonic) and E043(Epigenome ID)/BLD.CD4.CD25M.TPC(Mnemonic), respectively), fat nuclei (E063(Epigenome ID)/FAT.ADIP.NUC(Mnemonic)), promoter sites in fat nuclei (E063(Epigenome ID)/FAT.ADIP.NUC(Mnemonic)), transcriptional levels of 10 genes , and transcript alternative splicing of four genes  in the skeletal muscles, fatty tissue, thyroid gland, and other KOA-related organs. In a previous GWAS, the causal link between rs6499244 (T>A) NFAT5 and KOA risk was shown [NFAT5 (r2 = 0.91), with an increased level of DNA methylation in the WWP2 gene in patients with OA [PDXDC2P, CLEC18A, NOB1, NFAT5, IL34 [nuclear factor gene of activated T cells 5 (NFAT5) encodes a transcription factor that manages the quantitative expression traits of genes implicated in the regulation of osmoprotective and inflammatory reactions [NFAT5 in the formation of innate immunity by activating gene expression in macrophages during TLR (Toll-like receptor) ligation [NFAT5 also plays an important role in the proliferation of synoviocytes themselves [NFAT5 expression was found in the synovial membrane [NFAT5 indirectly affects the migration of myoblasts during skeletal muscle myogenesis via the CYR61-dependent pathway [The outcome of this work demonstrated involvement in the KOA genetic architecture  of rs6499244 (T>A) as shown . The potas shown ,72,73. Reactions ,75,76,77ligation ,79. TLR2ligation . NFAT5 aemselves . A highemembrane . NFAT5 i pathway . Transcr pathway ,84,85.SBNO1 as a KOA risk locus were first established by Tachmazidou et al. in GWAS on samples of European origin from UK Biobank and Arthritis Research UK Osteoarthritis Genetics (arcOGEN) [NFAT5, makes the greatest contribution to KOA susceptibility (0.86% of the disease entropy) among Europeans of Russia. The literature data indicate a serious epigenetic potential (relationship with the level of methylation in cartilage) of the locus rs56116847 (G>A) SBNO1 [ABCB9, ARL6IP4, C12orf65, CDK2AP1, KMT5A, MPHOSPH9, OGFOD2 and RILPL2) and sQTL of four genes  in fibroblasts cell culture, tibial nerve, skeletal muscles, whole blood, etc. The KMT5A gene  is closely related to the regulation of various biological processes such as DNA replication, chromosome condensation and activation of DNA replication checkpoints, cell proliferation, etc. [KMT5A regulates the transcription of Ras, p53 and Wnt genes [Wnt is well known for its participation in osteogenesis due to activation of the signaling pathways such as Wnt/calcium, Wnt/cyclic adenosine monophosphate (cAMP), Wnt/c-Jun NH(2)-terminal protein kinase (JNK) and Wnt/β-catenin [ERa plays responsible role in cartilage degradation [KMT5A in the proliferation and metastasis of osteosarcoma cells through the transmission of β-catenin signals is also known [The data for rs56116847 (G>A) arcOGEN) . AccordiA) SBNO1 . The infnt genes ,88,89. F-catenin . ERa plaso known .GLT8D1 locus in the KOA-important intergenic interactions among Europeans of Russia. The rs6976 GLT8D1 association with OA was shown in three previously-published GWAS in Europeans [GLT8D1 with KOA in Europeans [GLT8D1 and one of the statistical models of the shape of the proximal femur in patients with hip OA of European origin was shown [GLT8D1 is functionally significant when associated with active enhancers in chondrocyte cell culture (E049(Epigenome ID)/STRM.CHON.MRW.DR.MSC(Mnemonic)), primary osteoblast cells (E129(Epigenome ID)/BONE.OSTEO(Mnemonic)), in skeletal muscle microtubule cells (E121(Epigenome ID)/MUS.HSMMT(Mnemonic)), and active promoters in adipocytes (E023(Epigenome ID)/FAT.MSC.DR.ADIP(Mnemonic)) and chondrocytes (E049(Epigenome ID)/STRM.CHON.MRW.DR.MSC(Mnemonic)). The rs6976 (C>T) GLT8D1 locus is linked to four non-synonymous SNPs , which determine amino acid modification in three proteins such as GNL3 , SPCS1 (Pro41Ala) and NEC4 (Pro225Ala). The SNP rs6976 studied by us is associated with the expression/splicing parameters of 28 genes  in the tibial artery/nerve, skeletal muscles, thyroid gland, adipose tissue, etc. The data about rs6976 as a functional-impact locus were previously presented in other sources [GLT8D1 was found to be associated with a lower level of methylation in the STAB1 gene in the cartilage of OA patients [SPCS1 (rs6617) and GNL3 (rs11177), which are strongly coupled with rs6976 GLT8D1, with a significant imbalance of gene expression  in cartilage and other joint tissues such as ligaments, meniscus, adipose tissue, synovial membrane, were shown [GNL3 with the OA risk in both European and Asian populations [p ≤ 5 × 10−8) [We have identified the most substantial contribution of the rs6976 (C>T) uropeans ,32,35. Huropeans ,92 and ouropeans  of signiuropeans , Africanuropeans  and Euroas shown . In accoas shown ,96. Accoulations ,32,99, i × 10−8) ,32.GLT8D1 gene, located in the 3p21.1 region, encodes a protein from the glycosyltransferase family. Glycosyltransferases are a family of enzymes that catalyze the biosynthesis of oligosaccharides, polysaccharides and glycoconjugates [GLT8D1 gene and its corresponding protein. The GNL3 gene encodes a guanine-nucleotide-binding protein (nucleostemin), which plays an important role in many processes occurring in the cell, including participation in stem cell proliferation, regulation of the cell cycle, maintenance of telomerase activity [GNL3 is expressed in mesenchymal stem cells, from which chondrocytes originate [GNL3 gene expression in synovial tissue/fluid samples was significantly higher in the group of patients with primary OA compared with the control cohort [The njugates . To dateactivity ,102,103.riginate , shows ariginate . In a stl cohort . The nucl cohort .This study has certain limitations, which include the following: (a) only ten SNP of KOA candidate genes have been studied in the work and the inclusion of more loci in the analysis may cause a “shift” in the estimates of the intergenic interactions role of the examined loci in the formation of KOA; (b) the results of this work were not replicated on another sample from the same population or samples of another ethnic group; (c) this study did not take into account all possible risk factors for KOA  and, accordingly, their effects as covariates were not taken into account when evaluating associations; and (d) much broader experimental evidence of the functional effects of SNPs determining susceptibility to KOA is required (only in silico data were used in this work).In the current study it has been revealed that the KOA susceptibility among Europeans of Russia is mediated by intergenic interactions (but not the independent effects) of GWAS-important SNPs.


The Myc Network, comprising a small assemblage of bHLH-ZIP transcription factors, regulates many hundreds to thousands of genes involved in proliferation, energy metabolism, translation and other activities. A structurally and functionally related set of factors known as the Mlx Network also supervises some of these same functions via the regulation of a more limited but overlapping transcriptional repertoire. Target gene co-regulation by these two Networks is the result of their sharing of three members that suppress target gene expression as well as by the ability of both Network’s members to cross-bind one another’s consensus DNA sites. The two Networks also differ in that the Mlx Network’s control over transcription is positively regulated by several glycolytic pathway intermediates and other metabolites. These distinctive properties, functions and tissue expression patterns potentially allow for sensitive control of gene regulation in ways that are differentially responsive to environmental and metabolic cues while allowing for them to be both rapid and of limited duration. This review explores how such control might occur. It further discusses how the actual functional dependencies of the Myc and Mlx Networks rely upon cellular context and how they may differ between normal and neoplastic cells. Finally, consideration is given to how future studies may permit a more refined understanding of the functional interrelationships between the two Networks. Myc dysregulation in cancer: a brief history. Since its identification over 40 years ago as the human cellular ortholog of the transforming avian oncogene , the MYCer types ,3,4. Thier types ,3,4. For cancers ,7,8,9,10ignaling ,12. Indearcinoma ,14,15,16MYC’s discovery, and coinciding with a period during which its central role in naturally occurring oncogenesis became established, the Myc protein was identified as a bHLH-ZIP transcription factor that was dependent upon and subject to regulation by a small collection of other bHLH-ZIP proteins  separated by five nucleotides , Mlx−/− (MlxKO) and “double knockout” Myc−/− × Mlx−/− (mmDKO) murine embryonic fibroblasts (MEFs) and hepatocytes have indicated that, in addition to the gene sets mentioned above, those pertaining to aging, senescence and responses to and repair of DNA damage are also common targets [As mentioned above, Myc directly regulates hundreds to thousands of genes although their precise numbers and the magnitude of the regulation depend on cell type, stage of development and Myc levels ,41,42,51 targets ,80.0 state and enter S-phase. Conversely, Myc-Max binding to low-affinity E boxes or ChoREs might be displaced by MondoA/ChREBP-Mlx heterodimers as the latter translocate to the nucleus in response to changes in intracellular metabolites and/or pH or as Myc levels naturally decline during quiescence [a. Co-binding to shared target gene sites. The fact that Myc and Mlx Network members can cross-bind to one another’s DNA sites in some genes whereas in other cases, they bind separate E boxes and ChoREs provides additional opportunities for distinct types of co-regulation  28,38,3,72,73,81iescence ,33,34,35iescence ,31,36,76iescence ,78,83.TXNIP (thioredoxin-interacting protein) gene, which encodes a member of the α-arrestin family that is negatively regulated by Myc and positively regulated by MondoA and ChREBP  being another that is positively co-regulated by ChREBP and Myc in ways that are variably responsive to glucose [One actual example of such transcriptional fine-tuning involves the d ChREBP  [72,84,8promoter ,88. In aectively ,89,90. Tectively . CompletHK2 gene . HK2′s ee to G6P . Most ot glucose ,63,91. Ta. The Extended Myc Network’s roles in normal hepatocyte proliferation. The strong but transient induction of Myc in the normal liver in response to proliferative stimuli was first observed over 35 years ago. These signals included partial hepatectomy (PH), carbon tetrachloride- or phenobarbtol-induced injury and treatment with the peroxisome proliferator-activated receptor α (PPARα) agonist Wy-14,643 ,93. In aLoxP/Cre strain of mice that allowed for Myc’s hepatocyte-specific knockout (KO) [Determining whether Myc induction was actually necessary for proliferation was directly addressed in vivo with a out (KO) . By measout (KO) .Myc with varying degrees of efficiency (approx. 50–90%) and then shortly thereafter measuring the regenerative response to PH over the ensuing 2–7 days. Baena et al. determined that Myc was necessary for regeneration in adult livers but not in neonatal livers whereas Li et al. and Sanders et al., both concluded that Myc was dispensable for liver regeneration in young adult mice [The second approach, used by 3 different groups, involved the conditional excision of ult mice ,97,98.PH, while long considered the “gold standard” by which liver regeneration is appraised, has several limitations and drawbacks . First, FAH genes leads to the gradual accumulation of toxic tyrosine breakdown products such as succinylacetate, progressive hepatocyte death and eventual hepatic failure. A Fah KO mouse model of HT fully recapitulates the human disease [Fah+/+ hepatocytes, which then migrate to the liver, gradually replace the recipient’s moribund Fah−/− hepatocytes and ultimately contribute as much as 80% to the recipient’s hepatocyte mass [Fah+/+ cells over several months. The model also allows for the delivery of two or more populations of Fah+/+ hepatocytes to the same animal, thereby allowing competitive studies to be performed in a manner analogous to that long done with hematopoietic cells [Reasoning that PH might be insufficiently sensitive to identify Myc-dependent effects on hepatocyte proliferation, we have instead relied upon a murine model of Type I hereditary tyrosinemia (HT) . HT is a disease . As is tyte mass . Rather ic cells . Assuminic cells ,96,97,98Myc had been knocked out peri-natally by Cre recombinase driven by an albumin promoter (MycKO hepatocytes) [Fah−/− animals receiving only single Fah+/+ donor hepatocyte populations showed that the time to achieve Nitisinone independence, the total liver weights and the contribution of donor cells to recipient livers were the same in the WT and KO donor groups. Importantly, immuno-staining of tissue sections performed near the end of the observation period showed that Myc protein was expressed only in the regenerating FAH+ hepatic nodules originating from the expansion of WT hepatocytes. Thus the regenerative capacity of MycKO hepatocytes was not due to the selective expansion of a minority population that had escaped Myc gene excision and retained a proliferative advantage. Repeating these experiments under competitive transplant conditions confirmed that WT and MycKO hepatocytes were equally proficient at reconstituting the recipient livers [The FAH model has been used to compare the repopulation potential of WT hepatocytes to those in which tocytes) . Initialt livers . These rFah−/− mice were performed with mixed populations of WT and ChrebpKO hepatocytes or WT and MycKO × ChrebpKO double KO” (mcDKO) hepatocytes [ChrebpKO cells was reduced by more than half (28%) after hepatic reconstitution, thereby indicating their significant competitive disadvantage [Myc loss alone was insufficient to inhibit repopulation [Chrebp loss to further compromise regeneration.In follow-up to the above studies, the contributions of the Myc and Mlx Networks to hepatic regeneration were compared. The study’s rationale was based on the above-discussed dispensability for Myc in hepatocyte proliferation , on the atocytes . In the dvantage . Even mopulation , it neveChrebpKO phenotypes. Second, the conclusion that mcDKO hepatocytes were more compromised than ChrebpKO hepatocytes was only inferred given that it was based on separate competitive transplants that did not directly pit the two KO populations against one another. Therefore, to address both questions in the same study, Wang et al. examined the consequences of genetically ablating Mlx, which allows for the functional inactivation of both ChREBP and MondoA (MlxKO x MycKO double knockout (mmDKO) hepatocytes  induced by the enforced expression of various mutant forms of β-catenin and yes-associated protein (YAP) [MlxKO hepatocytes may have accounted for the occurrence of these tumors only in older mice. Together with previous findings of frequent Mlx copy number loss in a variety of human cancer types [b. Mlx functions as a tumor suppressor. An unexpected finding observed in the livers of 36% of older in (YAP) ,80,110. er types , these rMyc−/− embryos have long been known to die in mid-gestation, partially deleting Myc during embryogenesis allows for post-natal survival and results in the pups and their internal organs being smaller than normal due to the tissues containing fewer cells of otherwise normal size [Myc gene was gradually inactivated in vitro over the course of 5–7 days after early passage primary MEFs had been generated [0/G1 but then further consolidated in both G0/G1 and G2/M over the ensuing week [2/M-arrested population originated from cells that had been in S-phase at the end of the first week and then subsequently progressed into G2/M but were unable to exit and re-enter G0/G1 as Myc levels continued their decline [c. The Extended Myc Network’s role in fibroblast proliferation. Although mal size ,111,112.mal size ,50. In aMyc inactivation markedly suppressed but did not entirely inhibit proliferation [Myc+/+ cells from which they were derived. Normal-near normal doubling times could be restored by re-expressing Myc or other members of the Myc family  or any one of three different Myc target genes [Myc was deleted appear to play significant roles in determining their reliance on Myc for maintaining proliferation.An exception to the above findings was observed in an unusual strain of immortalized Rat fibroblasts in which feration . Rather,et genes ,114,115.Mlx in primary MEFs did not itself impair proliferation but did result in some unanticipated behaviors when combined with Myc knockout [MycKO MEFs while also displaying similar cell cycle profiles. However, between days 14 and 21, they spontaneously resumed proliferating at rates exceeding those of comparably aged WT MEFs. It was concluded that the permanent growth-arrest associated with Myc inactivation requires an intact Mlx Network and is consistent with Mlx’s previously proposed role as a tumor suppressor or negative regulator of growth [The inactivation of knockout . Not unef growth ,37,50.MycKO MEFs could be reversed by co-inactivating Mlx prompted an investigation into whether a similar down-regulation of Mlx in Myc−/− rat fibroblasts might explain their continued, albeit markedly slowed, proliferation [Myc−/− cells expressed similar levels of the truncated α and β isoforms of Mlx, both of which localize to the cytoplasm because they lack GSMs at their N-termini [That the permanent growth arrest of primary feration ,47. Wher-termini , the lat-termini ,68,70; 1-termini . CollectMyc or Myc+Mlx [MycKO and mmDKO cells, which growth-arrested immediately upon target gene(s) excision, the immortalized KO cells continued to proliferate, albeit at somewhat slower rates. These studies indicated that the proliferative defects of MycKO MEFs can also be rescued by inactivating one or perhaps both of the tumor suppressors that are targeted by T antigen, namely p53 and Rb [TFIIB gene, which encodes a key factor involved in the RNA polymerase III-specific transcription of tRNA and 5S ribosomal genes and which is necessary for maintaining proliferation, is repressed by p53 and Rb and induced by Myc [TERT) gene, which is necessary for imparting and maintaining the immortalized state in some cell types [MycKO and mmDKO MEFs [2/M block. Each of these gene sets was enriched in ways that were consistent with the resumption of proliferation by the DKO cells [Another unexpected discovery was made when the above MEFs were first immortalized by SV40 T antigen prior to the knockout of  Myc+Mlx ,116. Unl3 and Rb . The gend by Myc . Similarll types ,120,121.DKO MEFs . Gene seKO cells .MycKO and mmDKO primary MEFs, and to a lesser extent MlxKO MEFs, also displayed a number of properties that were indicative of premature senescence and/or aging [Day 7–14 or aging ,123,124.d. The Myc and Mlx Networks regulate common as well as distinct metabolic processes. The Myc and Mlx Networks regulate several metabolic pathways cooperatively, most notably those involving glycolysis and mitochondrial structure and function ,78,79,80Myc−/− rat fibroblasts [Conspicuous abnormalities in glycolysis and mitochondrial structure and function were first documented in the previously mentioned, roblasts ,61,62,63roblasts ,61,62. Troblasts ,63,64. Croblasts . Many geroblasts ,80.Myc−/− fibroblasts showed up to five-fold reduced amounts and/or activities of Complexes I, II, III, V and of ETC supercomplexes comprised of varying stoichiometries of Complexes I, III and IV [Myc+/+ cells [Myc−/− fibroblasts, a two-fold reduction in mitochondrial mass, a ten-fold reduction in basal Oxphos and the complete failure to up-regulate Oxphos the usual two-three-fold in response to the Oxphos uncoupler FCCP and the glycolysis inhibitor 2-deoxyglucose [Non-denaturing blue native gel electrophoresis (BNGE) and enzymatic assays of electron transport chain complex (ETC) function in I and IV ,125. TheI and IV ,126. BecI and IV ,128,129./+ cells ,61,64. Tyglucose .Myc−/− rat fibroblasts [Further consistent with the above studies were the results obtained when the mitochondrial fission protein Drp1 was constitutively expressed in immortalized but otherwise normal rat fibroblasts . In vitrroblasts  These inroblasts ,136. In roblasts ,137.A wider role for Myc in maintaining ATP levels and the bio-energetic consequences of being unable to do so was subsequently extended to three different human cancer cell lines treated with nine different small molecule Myc inhibitors with four different mechanisms of action . Within Because Myc over-expression has long been known to block differentiation in a number of settings and cell types ,140,141 A seemingly universal finding in the above cell lines and others following the inhibition or inactivation of Myc (or N-Myc in the case of neuroblastoma cell lines) was an increased rate of fatty acid β-oxidation (FAO) and the cytoplasmic accumulation of neutral lipid ,144,145.MycKO MEFs also showed significant metabolic disturbances although they were somewhat different and less pronounced than those encountered in iummortalized Rat Myc−/− fibroblasts [MycKO cells also accumulated neutral lipid and produced higher levels of ROS, most of which appeared to be of mitochondrial origin [Primary growth-arrested roblasts ,50. For l origin ,62.MlxKO MEFs proliferated at rates comparable to those of their WT counterparts, few if any changes indicative of mitochondrial dysfunction were observed [MycKO MEFs indicating that the loss of the Mlx Network did not further impact the deficits arising in response to Myc loss.Consistent with the finding that primary observed . AlthougMyc inactivation on mitochondrial structure and function in the liver were examined in the same study that had demonstrated no effect on hepatocyte repopulation [MycKO mice failed to show any of the marked differences in ETC complex structure and function previously observed in fibroblasts [MycKO livers. Despite these indistinguishable profiles, the OCRs of MycKO liver mitochondria in response to ADP, pyruvate, malate and succinate were diminished relative to the WT mitochondria although Complex V activity, as measured by the in situ assessment of ATPase function was increased. The significance of this latter finding is unclear although it conceivably represents a compensatory change intended to normalize the consequences of the Complex I and Complex II functional deficits. Thus, despite the lack of any demonstrable structural abnormalities resembling those of MycKO fibroblasts, MycKO livers nevertheless demonstrated similar, albeit less severe, functional impairments. This argued that, in the context of hepatocyte transplantation studies  to be the accumulation of excess lipid. As already discussed above, this is presumed to be the consequence of an exaggerated uptake of exogenous fatty acids that outpaces their ability to be catabolized into energy-generating substrates in functionally defective mitochondria [Further evidence of subtle functional defects in  WT mice . The difchondria ,144,145.MycKO, ChrebKO and mcDKO livers were compared [ChrebpKO and mcDKO livers was more elevated than that of MycKO livers which, as noted previously, was already higher than that of WT mice [MlxKO and mmDKO groups [MlxKO and mmDKO mice than it does in MycKO, ChrebpKO or mcDKO mice. Eventually, however, all KO groups accumulated about the same abnormally high lipid content with little additional accrual and thereby suggesting that this represented an upper limit of hepatic lipid capacity. A group of 163 liver transcripts, selected because of their strong association with non-alcoholic fatty liver disease also showed a progressive enrichment as the Extended Myc Network was progressively dismantled [Two more in vivo studies have examined the cooperative cross-talk between the Myc and Mlx Networks in maintaining metabolic balance in the liver ,79. In t WT mice  This sugO groups . Older msmantled .MycKO, MlxKO and mmDKO MEFs 10 days after initiating knockout of the respective genes [MlxKO cells was less than one-fourth as large as that of MycKO cells, with 61.8% of Mlx-regulated transcripts being co-regulated by Myc and 14.5% of Myc-regulated transcripts being co-regulated by Mlx. ChIP-seq results from the ENCODE data base [MycKO and MlxKO MEFs, respectively, were direct targets of these factors, with 22% of these directly binding both Myc and Mlx. In accordance with the model shown in e. The overlap of target gene expression. Global transcriptional profiling performed on primary ve genes  confirmeve genes ,28,37,79ata base  indicateMycKO MEFs and 31 were enriched in mmDKOs MEFs, none were enriched in MlxKO MEFs. This was very different from the case in livers where many of the same mitochondria-related genes that had been identified as being mostly down-regulated in MycKO livers were more down-regulated in ChrebpKO, MlxKO livers and even more so in mmDKO livers [MlxKO cells [MycKO MEFs relative to WT, 30 being enriched in mmDKO MEFs and 13 being enriched in MlxKO MEFs [To identify functionally related categories of genes under the control of the above Networks, both directed and unbiased GSEA were performed using the EnrichR tool kit, which contains a large number of independent data bases, including those from the KEGG, mSigDB C2 and Mitoproteome repositories . Seven mO livers ,79. HoweKO cells . AnotherxKO MEFs ,150. ColMycKO and mmDKO MEFs also displayed numerous features that were consistent with premature aging and senescence [MycKO and mmDKO MEFs  with ten of the sets also being enriched in MlxKO MEFs [As mentioned above, primary nescence . Thus itnescence . A finalxKO MEFs . Given txKO MEFs ,153,154.MlxKO and mmDKO livers and analyzed with gene sets previously shown to comprised of transcripts encoded by direct Myc or MondoA/ChREBP target genes. A number of differentially expressed transcripts overlapped, particularly in the case mmDKO livers whose dysregulated transcript repertoire was the largest. This again pointed to at least additive if not synergistic cooperation between the Myc and Mlx Networks in regulating transcripts previously thought to be under the purview of only one Network  that the top functional categories of transcripts encoded proteins involved in mitochondrial and ribosomal structure and function, thus confirming previous findings and those of the MEF studies described above [− 2.5 kb of the transcriptional start sites) bound Myc, 748 that bound Mlx and 2433 that bound both Myc and Mlx [Having previously examined the outcomes of altered gene expression profiles in  Network . This deed above ,50,55,80 and Mlx ,148. As  and Mlx ,38. Site and Mlx ,43,44.A separate analysis of the above target genes’ proximal promoters indicated that the E boxes and ChoREs contained within them were not randomly distributed relative to one another. Rather, two general types of binding sites were observed. The first contained only a single consensus element, indicating that both Myc and Mlx likely shared one another’s binding sites as mentioned above. In the second case, multiple tightly clustered E boxes and ChoREs were observed. This indicated that many of the previously observed ChIP peaks likely represented integrated signals from multiple sites that either co-bound Myc and Mlx Network members or bound them in such close proximity that they could not be resolved .The functional categories of genes identified by these binding differences were also quite distinct. For example, genes bound exclusively by Myc were more likely to be involved in cell cycle regulation, growth factor responses and Oxphos whereas Mlx-bound genes were more likely to be involved in FAO, the TCA cycle and xenobiotic metabolism. However, these functional categories overlapped considerably and particularly so in the case of those involving ribosome structure and function and translation . MoreoveLDHA, which encodes the A isoform of lactate dehydrogenase, are up-regulated and thus collectively contribute to the Warburg effect via a common mechanism [PDK1 gene, which encodes a kinase (pyruvate dehydrogenase kinase 1) that phosphorylates mitochondrial pyruvate dehydrogenase (PDH) at three sites, inhibits its activity and helps to redirect pyruvate’s to lactate instead of acetyl coenzyme A and thereby providing the electron acceptor NAD+ necessary for sustaining the more proximal steps of glycolysis [Slc2a2, which encodes the major hepatic glucose transporter Glut2 [Pklr expression is directly regulated by both the Myc and Mlx Networks had been previously provided by work performed in rat insulinoma cells which showed the Pklr gene’s proximal promoter to be associated with paused RNA Pol II that accumulated around the transcriptional start site [Pklr’s induction in response to glucose could be abrogated by the highly specific Myc inhibitor 10058-F4 [Pklr expression by Myc and ChREBP is reminiscent of the regulation of TXNIP described above [Slc2a2 and Pfkl by either the Myc or Mlx Networks has not been reported, we have identified the direct binding of Myc to the proximal promoters of these genes in HepG2 HB cells using data from the ENCODE consortium as well as binding of Mlx to the promoter region of the latter gene [PFKLR gene could be up-regulated in HCC cells in response to Myc overexpression [In cells expressing high or otherwise “pathological” levels of Myc, most if not all of the genes that encode glycolytic enzymes, as well as echanism ,155,156.ycolysis ,158. Theer Glut2 . Supportart site ,160,161.10058-F4 ,162. Theed above ,88. Althter gene , Wang anpression .In summary, substantial regulatory overlap exists among genes that are subject to direct control by the two components of the Extended Myc Network . Those dThe more than two decade period during which the individual components of the Extended Myc Network have been identified and their functional frameworks and cross-talk contextualized has yielded a model that is both simple and elegant in its design  9,18,20,51,140. Despite the depth and breadth of our current understanding, several major questions remain to be more fully resolved. Chief among these are the precise conditions under which Myc Network target genes become fully subject to regulation by the Mlx Network and vice versa. It is likely that changes in such target gene preference arise either as a result of members from both Networks binding to their individual consensus binding sites in close proximity to one another as well as to competition for the same binding sites. Do these represent functionally distinct gene sets? Elegant work has demonstrated the existence of a large complex of factors that associate with and are in turn regulated by Myc following its binding to promoter/enhancer regions of its target genes and that are necessary for transcriptional activation ,164,165.Chrebp, Mondoa, Mlx and/or other members of the Network might also be useful in determining the degree to which lymphoid activation depends upon the extracellular nutrient milieu to achieve the ideal degree of activation.Another area for future exploration concerns the role(s) for the Mlx Network in modulating both normal and tumor-associated immune responses, particularly in the case of T cell activation where Myc has been deemed essential in up-regulating the bursts in glycolytic and glutaminolytic activities that accompany and are required for this process ,167,168.Might the Myc and Mlx Networks “communicate” by virtue of microRNAs (miRNAs) whose transcriptional regulation by one Network might post-transcriptionally regulate members of the other Network? Although Myc is known to induce the expression of many miRNAs and Myc mRNA is itself a miRNA target, little information exists regarding miRNAs in the regulation of or by any members of the Mlx Network ,173,174.Finally, as clinically relevant pharmacologic targeting of Myc slowly becomes an increasingly realistic goal using agents that inhibit the formation of Myc-Max heterodimers, their binding to DNA or their activation of RNA Pol II-mediated transcription, it is reasonable to ask how such drugs might affect binding by Mlx Network members ,176,177.