Differentiated oligodendrocytes produce myelin and thereby ensure rapid nerve impulse conduction and efficient information processing in the vertebrate central nervous system. The Krüppel-like transcription factor KLF9 enhances oligodendrocyte differentiation in culture, but appears dispensable in vivo. Its mode of action and role within the oligodendroglial gene regulatory network are unclear. Here we show that KLF9 shares its expression in differentiating oligodendrocytes with the closely related KLF13 protein. Both KLF9 and KLF13 bind to regulatory regions of genes that are important for oligodendrocyte differentiation and equally recognized by the central differentiation promoting transcription factors SOX10 and MYRF. KLF9 and KLF13 physically interact and synergistically activate oligodendrocyte-specific regulatory regions with SOX10 and MYRF. Similar to KLF9, KLF13 promotes differentiation and myelination in primary oligodendroglial cultures. Oligodendrocyte differentiation is also altered in KLF13-deficient mice as demonstrated by a transiently reduced myelin gene expression during the first postnatal week. Considering mouse phenotypes, the similarities in expression pattern and genomic binding and the behaviour in functional assays, KLF9 and KLF13 are important and largely redundant components of the gene regulatory network in charge of oligodendrocyte differentiation and myelination.  In the vertebrate nervous system, the saltatory mode of nerve conduction helps to speed up the transfer and processing of information. It requires axons to be myelinated, either by oligodendrocytes in the central nervous system (CNS) or by Schwann cells in the peripheral nervous system (PNS). Myelinating oligodendrocytes are the terminally differentiated end point of oligodendroglial development and arise from oligodendrocyte progenitor cells (OPCs) in a strictly regulated process that is controlled both by extrinsic as well as intrinsic factors, the latter being organized in a complex gene regulatory network . This geThe Krüppel-like factor 9 (KLF9) is one such transcription factor. It belongs to the Klf group of zinc finger transcription factors that all contain three neighbouring C2H2 zinc fingers in their carboxyterminal DNA-binding domain . Within KLF9 has previously been identified as a transcription factor that is strongly induced in differentiating oligodendrocytes by thyroid hormone (T3) and may constitute an important effector downstream of T3 on the transcriptional level ,9. In agHere, we show that KLF9 cooperates with the oligodendroglial lineage determinant and HMG-domain transcription factor SOX10  as well The mouse N2a neuroblastoma and the human HEK293 kidney cell lines were grown in Dulbecco's modified Eagle's medium supplemented with 10% fetal calf serum. N2a and HEK293 cells were obtained from ATCC. Cell line identity was confirmed by PCR. Data on the rat Oln93 cells are from .d-lysine and laminin-coated dishes and grown in defined basal medium containing N2 supplement, 10 ng/ml PDGF-AA and 10 ng/ml FGF2. For specific gene deletion, membrane-permeable TAT-Cre protein was added at 0.2 nM to proliferating OPC cultures from mice with floxed alleles three days before differentiation  mice or Wistar rats of both sexes. Mouse and rat OPC cultures were prepared from mixed glial cultures by subsequent shake-off and microglia depletion . For stantiation ,16. For Established cell lines were transfected with Superfect reagent for luciferase assays (Qiagen), polyethylenimine for extract preparation and Lipofectamin 2000 (ThermoFisher) for production of retroviruses. Primary oligodendroglial cells were transduced in the OPC stage with retroviruses at a MOI of 0.5–1 or transfected with 20 pM siRNA pools  using Lipofectamine 2000 (Thermo Fischer Scientific).Klf9 (position 530–1264 in NM_010638) between HindIII and EcoRI and the mouse open reading frame of Klf13 (positions 370–1239 in NM_021366.3) between HindIII and XbaI sites of the multiple cloning site, either alone or in-frame behind a myc-tag. Coding sequences were also inserted into pCAG–IRES–GFP , rabbit anti-KLF13 antiserum , rabbit anti-GAPDH antiserum , rabbit anti-SOX10 antiserum , rabbit anti-MBP antiserum , guinea pig MYRF , mouse anti-myc-tag monoclonal  and horseradish peroxidase-labeled protein A . Detection was by chemiluminescence using luminol (Sigma).Gjc2 promoter, 5′-CCTTCTCACCAAGGGAAGGTC-3′ and 5′-GTAACCTTGGTCCCAAGAGACAG-3′ for the Mag promoter, 5′-CTGGTACAGTGAGCAACTCAGG-3′ and 5′-AAAACGCACAGATATGCGCAGG-3′ for the Mbp promoter, 5′-CAGCGTGGGAGGAGAATTCA-3′ and 5′-CCTTTGTTGGGGGCTGCT-3′ for the Aatk promoter, 5′- CCAGGGCATGGGAACGAA-3′ and 5′- CTCCAAACCCTCCAAACAAGC-3′ for the Plp1 enhancer and 5′-GTGGCTGCCAAACTAAGGTG-3′ and 5′-CCTGCTGACTGGGCCACATC-3′ or 5′- TCCAGATGTGAGAGAAAAACAA-3′ and 5′-CACCGAGTACAGAAAAGGTCCA-3′ for neighboring control regions. All samples were processed as technical triplicates. The ΔΔCt method was used to calculate the enrichment obtained in the precipitate with rabbit anti-KLF9 or anti-KLF13 antiserum over pre-immune serum.Primary oligodendroglial cells were treated after maintenance in proliferating conditions or after 6 days of differentiation with 1% paraformaldehyde at room temperature, lysed and used to prepare cross-linked chromatin that was subsequently sheared with a Bioruptor (Diagenode) to fragments of 150–400 bp. Sheared chromatin was precleared and incubated with rabbit anti-KLF9 antiserum, rabbit anti-KLF13 antiserum or rabbit pre-immune serum. After precipitation with BSA-blocked protein A sepharose beads, crosslink reversal at 65°C and proteinase K digestion, DNA was purified with the NucleoSpin Gel and PCR cleanup Kit (Macherey-Nagel) and used for quantitative PCR using the following primer pairs: 5′-ATCTGAATCCATGATTGTCC-3′ and 5′-GTCAGAAGTAGCCAGAGAGACTG-3′ for the fl/flSox10 mice have been described . Sectioning was followed by in situ hybridization with DIG-labeled antisense riboprobes specific for Mbp and Plp1 , Klf13 , Klf14 (for rat 5′- TCCTTCAAGCACAACCCCC -3′ and 5′- GCAAGACTTCCCACTACCCTCT-3′) and Klf16 (for rat 5′-CTTCGCACCTCAAGTCACACC-3′ and 5′-GGCGTGCTTGGTCAGGT-3′). All samples were processed as technical triplicates. Transcript levels were normalized to Rpl8. The ΔΔCt method was used for data analysis.RNA was prepared from primary rodent oligodendroglial cultures under proliferative and differentiation conditions and from mouse spinal cord at P0, P7, P21 and 2 months using Trizol (Invitrogen). After reverse transcription RNA was used for quantitative PCR on a Biorad CFX96 Real Time PCR System using PowerUp SYBR Green Mastermix (Thermo Fisher Scientific). Primer pairs for d before . They we2-fold change ≥±1.0 and adjusted P-value of ≤0.05) was generated using the Wald test. A bi-clustering heatmap was created using the pheatmap R package by plotting log2 transformed expression values in samples to visualize the expression profile of the top 30 differentially expressed genes sorted by their adjusted P-value. Gene ontology (GO) analysis of DEGs with base mean counts ≥20 and an absolute log2-fold change ≥±1.5 was performed using the Gene Ontology enrichment, analysis and visualization tool GOrilla (http://cbl-gorilla.cs.technion.ac.il/) in combination with semantic clustering by REViGO (http://revigo.irb.hr/) (http://software.broadinstitute.org/gsea/index.jsp) was employed to determine whether a defined set of genes shows statistically significant, concordant differences between RNA samples from control and KLF13-deficient samples.Total RNA was isolated from cultured primary mouse oligodendroglia of Klf13-knockout pups and wildtype controls after 6 days of differentiation using the RNeasy Micro Kit (Qiagen). RNA samples (three Klf13-knockout and four control samples) were treated with DNaseI to remove contaminating DNA and quantified using a Qubit 4.0 fluorometer (Life Technologies). RNA integrity was checked on an Agilent 5300 Fragment Analyzer (Agilent Technologies). RNA sequencing libraries were prepared using the NEBNext Ultra II RNA Library Prep Kit for Illumina following the manufacturer's instructions (NEB), multiplexed and sequenced on an Illumina NovaSeq 6000 instrument using a 2 × 150 Pair-End (PE) configuration. On average 67 million reads were generated per library . Sequence analysis and base calling were conducted by NovaSeq Control Software v1.7. Generated raw sequence data were converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20 with one mismatch allowed for index sequence identification. Sequence reads were trimmed using Trimmomatic v.0.36 and mapped to the mouse reference genome available on ENSEMBL using STAR aligner v.2.5.2b. Unique gene hit counts within exon regions were calculated using the Subread package v.1.5.2. Subsequently, DESeq2 was used for downstream differential expression analysis. Gene expression values are deposited in GEO under accession number GSE212736. To identify changes in gene expression upon loss of KLF13, a list of genes with significantly changed expression  . The Genhttp://rsat.sb-roscoff.fr/) was used. Binding motifs for Klf proteins (5′-(A/C)C(G/A/T)CCC-3′) and Sox10 (5′-(A/T)CAA(A/T)-3′) were not only mapped in the oligodendrocyte-specific regulatory sequences studied in luciferase assays  was used to determine a group of 282 among the 1084 genes that were expressed in newly formed or myelinating oligodendrocytes with a FPKM value ≥20. Within this group, 105 genes were solely expressed in newly formed oligodendrocytes, 170 genes in newly formed and myelinating oligodendrocytes and 7 in myelinating oligodendrocytes only. Intersect intervals was then used to map all CNS-specific Sox10 peaks in regions encompassing the 105 genes from newly formed oligodendrocytes and the 177 from myelinating oligodendrocytes genes ±10 kb up- and downstream, leading to the identification of 186 Sox10 peaks for newly formed and 257 Sox10 peaks for myelinating oligodendrocytes. The exact sequences of the Sox10 peaks (with 250 bp on each side) were then retrieved with the help of the program fetch-sequences from UCSC on the Regulatory Sequence Analysis Tools platform, and subsequently analysed for Klf binding motifs.For motif discovery within DNA sequences, the DNA-pattern program of the Regulatory Sequence Analysis Tools . Results from independent animals or separate experiments were treated as biological replicates (n ≥ 3).To determine whether differences in transcript levels, luciferase activities, protein amounts, precipitates or cell numbers were statistically significant, a two-tailed Student's Klf9 and Klf13 . Previous studies had shown that mitogens ,9. Our on Figure . At the Sox10 gene did not affect the expression levels of Klf9 or Klf13  transcript levels arguing that Klf13 expression is not downstream of KLF9 in oligodendroglial cells , Mag, Aatk, Mbp and Plp1 genes that are active in oligodendrocytes  and gene set enrichment analysis (GSEA) of the 278 significantly downregulated genes  revealed an enrichment of terms associated with glial differentiation, myelination and ensheathment of neurons  point to persistent expression of OPC-specific ion channels in KLF13-deficient cells and are indicative of a less differentiated state  as shown in a bi-clustering heatmap with sorting by adjusted e Figure . A more s Figure , F. Othee Figure , F. ThesKlf9 or Klf13 and compared the effect with controls. The percentage of MBP-positive cells after transient knockdown of KLF13 in wildtype oligodendroglial cells was comparable to the one observed after KLF9 knockdown and led to similar impairments of oligodendrocyte differentiation as the constitutive KLF13 deletion  and Nfatc2 ,36. In cWhile we tested only a limited number of regulatory regions in functional assays, bioinformatic analyses point to a broader relevance of the interaction between KLF9/KLF13 and SOX10. Of 186 regions with SOX10 peaks  in or neGjc2 promoter synergistically with KLF9 supports the relevance of the physical interaction for the functional cooperation in reporter gene assays.We also obtained evidence for a physical interaction with SOX10 in co-immunoprecipitation experiments. GST pulldown experiments confirmed the interaction and pointed to an involvement of the region encompassing the dimerization and DNA-binding HMG-domains in Klf protein recognition. The inability of a SOX10 variant with mutation in the dimerization domain to activate the in vivo is less clear and difficult to determine as the consequences of disrupted homodimerization and disturbed interaction with Klf proteins in currently available SOX10 mutants can only be separately assessed on single regulatory regions but not globally. However, the limited impact of the SOX10 dimerization domain mutant on the early steps of oligodendrocyte differentiation in the spinal cord (in vivo.The contribution of this physical interaction to functional cooperation between KLF9 and SOX10 nal cord  argues tIn addition to Klf proteins, SOX10 interacts with MYRF  and is cRegarding further aspects of the molecular mode of action of the Klf proteins, all available data indicate that they bind themselves to DNA. The variability of distances and orientation to known or predicted SOX10 binding sites do not favour a model, in which one factor directly facilitates binding of the other. We also do not know whether recruitment of SOX10 and the Klf proteins follows a specific order and whether Klf proteins have additional functions beyond their activity as transcription factors.The combinatorial mode of gene activation is an easy way for each of the transcription factors to add its unique features to the activation process. KLF9 may for instance contribute T3 effects in this way. However, a combinatorial mode may also mean that most factors are not absolutely essential or even dispensable. This may explain several aspects previously observed for the role of KLF9 and T3 in oligodendrocyte differentiation and myelination .The other intriguing finding of the current study is that KLF9 is largely co-expressed during oligodendroglial development with its close relative KLF13. In contrast, the other two BTEB-subfamily members KLF14 and KLF16 appear to be less relevant in oligodendroglial cells due to low or absent expression. Despite the fact that KLF13 is unresponsive to T3 and cannot mediate T3 effects, both related Klf proteins appear to function in mechanistically similar ways during oligodendrocyte differentiation. They share the ability to bind to oligodendrocyte-specific regulatory regions, interact with SOX10 and MYRF and activate gene expression in synergy with these two transcription factors. Like KLF9, overexpression of KLF13 in oligodendroglial cells increases their differentiation capacity and deficiency decreases it. This functional similarity between KLF9 and KLF13 appears to translate into largely redundant functions during oligodendroglial development. At least partial functional redundancy between KLF9 and KLF13 has also been reported in the nervous system during regulation of clock genes and for hippocampal gene expression ,40. It lA proof of this assumption would require the generation of mouse mutants with deficiencies of both KLF9 and KLF13. Given the widespread roles and expected redundancies of both proteins, constitutive double-deficient mice are likely not viable. An analysis of the functional redundancy of KLF9 and KLF13 would therefore require a conditional deletion strategy and corresponding floxed alleles. At least for KLF13, such a floxed allele is not yet available.Loss of KLF9 had previously been reported to impact remyelination after cuprizone-induced demyelination much more strongly than developmental myelination . This fiNevertheless the presented data go a long way to characterize the role of the closely related KLF9 and KLF13 in oligodendrocyte development and offer deep insights into their functionally redundant molecular mode of action as synergistic transcriptional activators during terminal differentiation and myelination.All data generated or analyzed during this study are included in this published article or deposited in GEO under accession number GSE212736.


SUS1 loss depend on TREX-2 but not on the SAGA DUB module. Notably, an increased dose of the mRNA export factors Mex67 and Dbp5 rescues the growth defect, shortened lifespan, and nuclear accumulation of poly(A)+ RNA in sus1Δ cells, suggesting that boosting the mRNA export process restores the mRNA transport defect and the growth and lifespan damage in sus1Δ cells. Moreover, Sus1 is required for the proper association of Mex67 and Dbp5 with the nuclear rim. Together, these data indicate that Sus1 links transcription and mRNA nuclear export to the lifespan control pathway, suggesting that prevention of an abnormal accumulation of nuclear RNA is necessary for maintenance of a normal lifespan.Eukaryotic gene expression requires multiple cellular events, including transcription and RNA processing and transport. Sus1, a common subunit in both the Spt-Ada-Gcn5 acetyltransferase (SAGA) and transcription and export complex-2 (TREX-2) complexes, is a key factor in coupling transcription activation to mRNA nuclear export. Here, we report that the SAGA DUB module and TREX-2 distinctly regulate yeast replicative lifespan in a Sir2-dependent and -independent manner, respectively. The growth and lifespan impaired by  Saccharomyces cerevisiae is a useful model organism for studying the aging process, and this model is analyzed through two distinct methods: replicative lifespan (RLS) and chronological lifespan (CLS)  overnight at 37°C in a humid chamber. After hybridization, the cells were washed, air-dried, and mounted with mounting solution . ImageJ was used to detect nuclear and cytoplasmic Cy3 signals. At least 100 cells were examined for each of the three independent experiments. The significance of differences between the indicated strains was determined with a two-tailed, unpaired Student’s t-test using GraphPad Prism software . Data represent the mean ± standard deviation (SD) of triplicate experiments.Poly(A)ications . Yeast cADE2 marker inserted into the rDNA array was measured as reported previously [600 were plated at a density of ~400 cells per plate on SC plates containing a low adenine concentration (27 μM). The plates were incubated at 30°C for 2 or 3 days and then stored at 4°C for ~2 weeks to enhance the red color development. Colonies were counted using GeneTools software (Syngene). The percentage of marker loss was calculated by dividing the number of red-sectored colonies by the total number of colonies. Completely red colonies, indicating marker loss before plating, were excluded from the calculation.The rate of marker loss through the unequal recombination of an eviously , 65. CelSupplementary FiguresSupplementary Table 1Supplementary Tables


AMH promoter sequences. A modest estrogen action is also mediated by the membrane G-coupled estrogen receptor GPER. The understanding of these complex regulatory mechanisms helps in the interpretation of serum AMH levels found in physiological or pathological conditions, which underscores the importance of serum AMH as a biomarker of intratesticular steroid concentrations.Anti-Müllerian hormone (AMH) is a distinctive biomarker of the immature Sertoli cell. AMH expression, triggered by specific transcription factors upon fetal Sertoli cells differentiation independently of gonadotropins or sex steroids, drives Müllerian duct regression in the male, preventing the development of the uterus and Fallopian tubes. AMH continues to be highly expressed by Sertoli until the onset of puberty, when it is downregulated to low adult levels. FSH increases testicular AMH output by promoting immature Sertoli cell proliferation and individual cell expression. AMH secretion also showcases a differential regulation exerted by intratesticular levels of androgens and estrogens. In the fetus and the newborn, Sertoli cells do not express the androgen receptor, and the high androgen concentrations do not affect AMH expression. Conversely, estrogens can stimulate AMH production because estrogen receptors are present in Sertoli cells and aromatase is stimulated by FSH. During childhood, sex steroids levels are very low and do not play a physiological role on AMH production. However, hyperestrogenic states upregulate AMH expression. During puberty, testosterone inhibition of AMH expression overrides stimulation by estrogens and FSH. The direct effects of sex steroids on AMH transcription are mediated by androgen receptor and estrogen receptor α action on  Anti-Müllerian hormone (AMH) is a glycoprotein hormone  that belAMH gene is located on chromosome 19p13.3 , AMH is a proven biomarker of the immature Sertoli cell population in normal and pathological conditions [reviewed in ref –39]. Serutations . Undetecutations . In patiutations . In normutations , 43, 44 utations . Conversutations , excessiutations , or hypeutations . During utations , while autations . Conversutations .AMH expression by binding to a specific element on the proximal AMH promoter  or the non-classical (or non-genomic) pathways Figure 32+ transporter ZIP9 has been proposed as a membrane AR that induces the phosphorylation of Erk1/2 and the transcription factors CREB and ATF1  levels in normal boys . This sihalf ERE Figure 1half ERE , and E2 half ERE .We have recently tested the hypothesis that E2 upregulates AMH expression in the prepubertal and pubertal testis, using experimental mouse models. Treatment of 4-day-old mice with ICI 182780, an antagonist of ERα and ERβ, resulted in significant decrease in serum AMH  and GPERAMH promoter prompted us to test whether estrogens could have a direct effect on AMH expression at the individual Sertoli cell level. Luciferase assays clearly indicated that the activity of a 3-kb human AMH promoter was increased after exposure to E2 of SMAT1 Sertoli cells transfected with any of the 3 ERs. However, to elicit a significant response ERβ-transfected SMAT1 needed to be incubated with E2 10-7 M (-9 M (AMH promoter activity while MPP, a specific ERα antagonist, inhibited the AMH promoter activity (via GPER was more modest. Its specificity was confirmed when SMAT1 cells were exposed to the potent and selective GPER agonist G1 or to the selective GPER antagonist G-15 (The existence of an ERE on the 2 10-7 M , a conce2 10-7 M , while E M (-9 M . These oAMH promoter was also observed when a 1926-bp promoter with an intact ERE present at position -1782 was transfected, but no estrogenic activity was detected when using AMH promoter constructs consisting of the proximal 433 bp or of sequences lying between -1926 and -2590 or between -1926 and -3078, which are devoid of the half-ERE (AMH promoter through ERα binding to the half-ERE site present at position -1782 (AMH promoter upregulation induced through the GPER still needs to be elucidated.The upregulation induced by E2 in SMAT1 cells on the 3-kb AMH promoter (The cellular and molecular mechanisms involving ERα and, more modestly, GPER in E2 induction of the activity of the promoter  and of Spromoter  provide promoter , 84 or wpromoter . It coulpromoter .AMH gene transcription. These direct effects are mediated by the classical mechanism involving nuclear AR and ER receptor activity on target gene promoters and, more modestly, by estrogen action through the membrane GPER (AMH production by Sertoli cells reflects the differential regulation exerted by intratesticular levels of androgens and estrogens in the prepubertal testis, with specific variations according to the developmental stage. In the fetus and the newborn, the high intratesticular androgen concentrations do not regulate AMH expression because the AR is not yet expressed in Sertoli cells, whereas intratesticular estradiol can moderately increase AMH production since ERs are present in Sertoli cells and aromatase activity resulting in androgen conversion to estrogens is stimulated by FSH. During childhood in humans, or the quiescent period of the hypothalamic-pituitary-gonadal axis described in most mammals, the extremely low steroid levels do not exert any physiological regulation on AMH production Figure 7All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.Until 2020, RR received royalties for the development of an AMH ELISA kit and honoraria for technology services using the AMH ELISA.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Lamina-associated domains (LADs) are large genomic regions that are positioned at the nuclear lamina. It has remained largely unclear what drives the positioning and demarcation of LADs. Because the insulator protein CTCF is enriched at LAD borders, it was postulated that CTCF binding could position some LAD boundaries, possibly through its function in stalling cohesin and hence preventing cohesin invading into the LAD. To test this, we mapped genome–nuclear lamina interactions in mouse embryonic stem cells after rapid depletion of CTCF and other perturbations of cohesin dynamics.CTCF and cohesin contribute to a sharp transition in lamina interactions at LAD borders, while LADs are maintained after depletion of these proteins, also at borders marked by CTCF. CTCF and cohesin may thus reinforce LAD borders, but do not position these. CTCF binding sites within LADs are locally detached from the lamina and enriched for accessible DNA and active histone modifications. Remarkably, despite lamina positioning being strongly correlated with genome inactivity, this DNA remains accessible after the local detachment is lost following CTCF depletion. At a chromosomal scale, cohesin depletion and cohesin stabilization by depletion of the unloading factor WAPL quantitatively affect lamina interactions, indicative of perturbed chromosomal positioning in the nucleus. Finally, while H3K27me3 is locally enriched at CTCF-marked LAD borders, we find no evidence for an interplay between CTCF and H3K27me3 on lamina interactions.These findings illustrate that CTCF and cohesin are not primary determinants of LAD patterns. Rather, these proteins locally modulate NL interactions.The online version contains supplementary material available at 10.1186/s13059-022-02754-3. The nuclear lamina (NL) is positioned near the inner nuclear membrane and consists of a protein meshwork of A- and B-type lamins and a variety of other proteins. Peripherally positioned chromatin interacts with the NL and comprises approximately a thousand large genomic domains that are up to 10 Mb in size –4).C. elegans) [LADs are strongly enriched for features of heterochromatin. Besides having a low gene density and typically low gene expression levels, LADs replicate late in S-phase, are visible by electron microscopy as densely packed chromatin, and are enriched for the histone modifications H3K9me2 and H3K9me3 , 5–9. Thelegans) , 15. DifTcrb locus resulted in decreased NL interactions up to 100 kb inside the LAD, and this behavior was almost completely recapitulated by deletion of a ~4.5-kb region that included all three CTCF binding sites at this border [One particular aspect of LADs that remains poorly understood is the sharp transition in NL interactions at LAD borders, which suggests the existence of specific mechanisms to define these borders. LAD borders are enriched for active promoters, CpG islands (often at active promoters), and binding of the insulator protein CTCF . While ts border . HoweverCTCF is a broadly expressed and essential zinc-finger protein that interacts with the ring-shaped cohesin complex on the genome , 18. OncIn addition to the genomic features discussed above, in some cell types, H3K27me3 is also enriched near LAD borders , 12. H3KTwo recent developments now allowed us to investigate the interplay between LAD borders and CTCF and cohesin. First, the fusion of endogenous proteins with auxin-inducible degron (AID) tags mediates rapid and near-complete protein depletion, which is particularly useful for essential proteins or complexes such as CTCF and cohesin , 32. SecWe first set out to explore the correlation between CTCF binding (as detected by ChIP-seq) and LAD borders in more detail by comparing these in two mouse and four human cell lines with available NL interaction maps (obtained by DamID). CTCF binding is consistently depleted within LADs and locally enriched near LAD borders, peaking 10 kb outside LADs  and away from (outwards) LADs.CTCF binds the genome in an oriented manner due to a non-palindromic motif. Loops primarily occur between two convergent CTCF motifs –47. To tCTCF is thus positioned at a subset of LAD borders, which raises the question whether these borders are different from LAD borders without CTCF. We classified all LAD borders into two categories based on nearby CTCF binding , which results in 42–62% being classified as “CTCF borders” for the different cell types Fig. B. In accAverage profiles of NL interactions, CTCF, and cohesin binding and publicly available epigenetic data , 40–44 aTo test whether CTCF is directly involved in the demarcation of LAD borders, we used a mESC line with CTCF fused to an auxin-inducible degron (AID) tag . Additio2 ratios of LaminB1/Dam-only to z-scores . We obsSimilar to CTCF, these depletion experiments do not grossly alter the global patterns of NL interactions, although again various changes can be seen Fig. B. IntrigAverage profiles of NL interactions at LAD borders show that RAD21 depletion results in a small decrease in NL interactions around LAD borders marked by CTCF, both outside and inside the LAD  are oftConsistent with previous work , 52, 53,Similar to LAD borders, CTCF binding in LADs is correlated with features of open chromatin , although to a much lesser extent than active genes. CTCF occupancy also coincides with a local decrease and increase of H3K9me2 and H3K27me3, respectively   were both reported to be involved in the peripheral positioning of LAD fragments . FurtherWe first generated calibrated ChIP-seq data for H3K27me3 before and after CTCF depletion in mESCs cultured in 2i conditions. Alignment at LAD borders indicates that the enrichment of H3K27me3 is not affected by CTCF depletion; if anything, it becomes more pronounced Fig. A. Next, We therefore conclude that there is no interplay between CTCF and H3K27me3 in genome positioning at the NL in mESCs. This result also suggests that the genome-wide correlation between NL interactions and H3K27me3 observed after CTCF depletion is not caused by the H3K27me3 marks Fig. D, furtheCombinations of chromosome conformation capture methods and rapid protein depletion experiments revealed how CTCF and cohesin organize the genome in self-associating domains , 57, 58.We find CTCF and cohesin enrichment at LAD borders in all tested mouse and human cell lines, indicating that this is a conserved feature of LADs , 12. OurSmall euchromatin regions inside heterochromatin blocks can be divided in promoter elements and regulatory elements based on genomic features and chromatin marks, both of which are enriched for CTCF binding sites . This isIntriguingly, CTCF and cohesin are dispensable for DNA accessibility at CTCF binding sites in LADs. This is of interest, as artificial decondensation of LADs can induce repositioning from the NL, even without transcriptional activity , 11, 60.Besides local effects at LAD borders and CTCF binding sites, CTCF and cohesin affect the genome-wide pattern of NL positioning quantitatively. We observe the largest effects upon depletion of WAPL and combined depletion of CTCF and WAPL. While these genome-wide changes are difficult to interpret mechanistically, they reveal intriguing correlations. For example, cohesin stabilization disrupts positioning of telomeres and nearby DNA in the nuclear interior, which is a characteristic of genome reorganization in early interphase , 61. WhiIt was previously reported that CTCF is required for the peripheral positioning of integrated LAD fragments . This geA similar dependency for the peripheral position of LAD fragments was shown for EZH2, the methyltransferase responsible for H3K27me3 deposition . This diPrevious work illustrated that chromatin positioning at the NL is not required for genome compartmentalization . Vice-veOverall, our data indicate that CTCF and cohesin are not required for LAD border positioning in mESCs, but only contribute to sharpening of the borders. It thus remains to be elucidated what demarcates LADs. While we cannot rule out that an undiscovered factor is involved, it is also possible that there are no specific characteristics of LAD borders. Rather, the factors that mediate NL interactions may be tightly controlled and result in sharp LAD borders.Constitutive LADs and their borders are conserved between human and mouse cells . While tWe systematically investigated how NL interactions are affected by proteins involved in the loop extrusion process. Remarkably, while cohesin perturbation drastically affects genome compartmentalization, NL interaction patterns are largely unaffected. Rather, CTCF and cohesin promote focal detachment from the NL and affect peripheral positioning of the genome quantitatively.E14Tg2a mouse embryonic stem cells (mESCs) (129/Ola isogenic background) and derived clones were cultured in serum-free DMEM/F12 (Gibco) and Neurobasal (Gibco) medium (1:1), supplemented with N-2 (Gibco), B-27 (Gibco), BSA , 104 U of leukemia inhibitory factor , MEK inhibitor PD0325901 , GSK-3β inhibitor CHIR99021 , and 1-thioglycerol  on 0.1% gelatin-coated plates. Cells were passaged every 2 days. Cells were seeded and incubated overnight before starting protein depletion experiments, at the following densities: for a 96-h time course, 35,000 and 150,000 cells were seeded in 6-well and 10-cm plates, respectively; for a 24-h time course, 0.5 million and 1.5 million cells were seeded in 6-well and 10-cm plates, respectively. During these time courses, the medium was refreshed or cells were split 1:10 every 2 days.Protein depletion was induced by treating cells with a final concentration of 500 μM auxin (IAA) . Time series experiments were performed by inducing protein degradation at different time points and collecting all samples at the end of the time course.https://data.4dnucleome.org/biosources/4DNSRMG5APUM/). These cells were differentiated into neural precursor cells (mNPCs) and cultured as described [F121-9-CASTx129 mESC were cultured in 2i conditions according to the 4D Nucleome guidelines ) and incubated on ice for 15 min, followed by adding 500 μL of low salt/0.4% NP-40 buffer to reach a final concentration of NP-40 at 0.2%. These cells were then rotated at 4 °C for 15 min and centrifuged at 6000 g for 10 min at 4 °C. The obtained cell pellets were resuspended in high salt buffer  at a density of 5 million cells per 100 μl buffer and then rotated overnight at 4 °C. The supernatant was collected for subsequent experiments. For the whole cell lysates, the cells were lysed in RIPA lysis buffer ).To verify protein depletion, AID-tagged mESCs were treated for 6 h with HTM 4 to 12%, Bis-Tris 1.0 mm, Mini Protein Gel, 15-well, NP0323BOX, ThermoFisher SCIENTIFIC) were used to separate the proteins and transferred to preactivated PVDF membranes on a Trans-Blot Turbo Transfer System (Bio-Rad). The blots were incubated with primary antibodies against the following proteins overnight at 4 °C: (1) CTCF , (2) WAPL , (3) ACTB , (4) RAD21 , and (5) HSP90 . After incubation, the blots were washed three times with 0.1% Tween-20 in TBS (TBST) and then incubated with secondary antibody against rabbit IgG at room temperature for 1 h, again followed by three washes with TBST.The nuclear extracts were used for western blot analysis of CTCF, WAPL, and ACTB, and the whole cell lysates were used for western blot analysis of RAD21 and HSP90. Precast gradient SDS-PAGE gels  and sonicated. A total of 25 μg of total protein extracts was run on a gradient (15-4%) Polyacrylamide gel . Proteins were transferred on the nitro-cellulose membrane and checked with Red Ponceau staining for efficient transfer. The membranes were incubated with blocking buffer (5% milk powder in TBST) for 1 h at room temperature and afterwards incubated with primary antibody  in blocking buffer overnight at 4 °C. Membranes were washed with TBST and secondary antibody incubation was performed for 2 h at room temperature in blocking buffer.Protein detection was performed using Biorad Clarity Max ECL substrates and a ChemiDoc MP Imaging System (Bio-Rad).Cell cycle analysis was performed with the Click-iT EdU Alexa Fluor 647 Flow Cytometry Assay Kit (Invitrogen). Briefly, for 1.5 h, mESCs were incubated with 10 μM Click-iT EdU and fixed and permeabilized. Cells were incubated with the Click-iT Plus reaction cocktail for 30 min at room temperature (protected from light) to detect EdU and stained with 4′,6-diamidino-2-phenylindole (DAPI). DAPI and EdU signals were quantified on a BD LSRFortessa analyzer and processed with FlowJo 10.3.m6A-marked DNA was enriched using a sequence of DpnI digestion, PCR adapter ligation, DpnII digestion, and PCR amplification. The resulting amplified material was processed for high-throughput sequencing using an in-house library preparation procedure and sequenced for single-end 140-bp reads on an Illumina HiSeq 2500. Approximately 10 million reads were sequenced for every condition.LaminB1 DamID was performed as described previously , 67. BripA-DamID LaminB1 maps were generated as described . One milATAC-seq libraries were prepared as previously described . Cells wChIP-seq was performed as described but with small modifications . mESCs aRNA was isolated using a standard TRIzol RNA isolation protocol (Ambion). Cells were lysed with 1 mL of TRIzol reagent, after which 200 μL chloroform was added and the mixture was vortexed. Following centrifugation at 12,000 g at for 15 min at 4 °C, the upper phase was homogenized with 0.5 mL of 100% isopropanol. Samples were incubated at room temperature for 10 min and centrifuged at 4 °C for another 10 min. The resulting RNA pellet was washed with ice-cold 75% ethanol, dried at room temperature, and resuspended in RNase-free water. The isolated RNA was treated with DNase using the RNeasy Mini kit (Qiagen). RNA-seq libraries were prepared using a TruSeq Stranded RNA LT Kit (Illumina). The libraries were sequenced for single-end 65-bp reads on an Illumina HiSeq 2500.2-ratio over the Dam control sample was calculated with a pseudo count of 1. At least 2 biological replicates were generated for every experimental condition and the average score was used for downstream analyses. Log2 ratios were converted to z-scores to correct for differences in dynamic range between experiments . For Fig. LADs were determined using hidden Markov modeling on the average NL interaction profile between biological replicates (LAD borders were classified as CTCF borders if a CTCF binding site was within 20 kb outside the LAD (overlapping with the enriched CTCF density). Borders within 10 kb of an active gene (FPKM > 1) were flagged and not used in downstream analyses unless otherwise indicated. LAD borders were assigned to a loop anchor if this was positioned within 20 kb. To determine CTCF orientation at LAD borders, the CTCF motif (JASPAR MA0139.1 ) was useThe detachment score was defined as the difference in mean NL interaction scores between the flanking region  and the CTCF binding site (up to 10 kb). To prevent confounding factors for transcription and border positioning, CTCF binding sites were filtered to be at least 100 kb from active genes and LAD borders.2-fold difference of 0.5 with a false discovery rate of 0.05. Principal component analysis was performed with “plotPCA” from DESeq2, using the top 5000 most variable genes. FPKM values were calculated with “fpkm” from DESeq2, using the combined exon length as gene length. Similar downstream processing was applied to call differential expression in the TT-seq data [RNA-seq reads were mapped against the mm10 reference genome with TopHat2 2.1.1  and filtseq data .ATAC-seq reads were mapped to mm10 with bwa mem 0.7.15-r1140. SAMtools 1.9  was usedq-value cutoff of 0.01.ChIP-seq data were analyzed as previously reported . Reads wThe external datasets that have been used in this study have been referred to in the main text and figure legends. Data identifiers are listed in Additional file Additional file 1: Fig S1. LAD border enrichment of epigenetic marks is independent of CTCF orientation and is conserved between cell types. Fig S2. LaminB1 pA-DamID tracks recapitulate DamID data and can be used to profile NL interactions after rapid protein depletion. Fig S3. Effect of protein depletions on the cell cycle. Fig S4. Further analysis of the effect of CTCF depletion on LAD border positioning. Fig S5. Perturbed NL interactions are limited for outwards oriented LAD borders and caused by changes in LaminB1 reads. Fig S6. Protein depletion by AID-tagging induces a partial effect on CTCF detachment within LADs. Fig S7. Quantification of LAD differences after CTCF depletion and cohesin perturbation. Fig S8. Correlation between LAD features. Fig S9. CTCF depletion and cohesin perturbation affect an overlapping gene set enriched for differentiation genes. Fig S10. H3K27me3 depletion does not affect genome-wide NL interactions.Additional file 2: Table S1. List of datasets used.Additional file 3. Review history


IDO1 and WARS genes and (ii) type I IFN pathway RIG-I, MDA5, and ISG15 genes that collectively contribute to DNA damage resistance and immune evasion. In support of these results, targeting MUC1-C in wild-type BRCA TNBC cells enhanced carboplatin-induced DNA damage and the loss of self-renewal capacity. In addition, MUC1-C was necessary for DNA damage resistance, self-renewal, and tumorigenicity in olaparib-resistant BRCA1-mutant TNBC cells. Analysis of TNBC tumors corroborated that (i) MUC1 and PBRM1 are associated with decreased responsiveness to chemotherapy and (ii) MUC1-C expression is associated with the depletion of tumor-infiltrating lymphocytes (TIL). These findings demonstrate that MUC1-C activates PBRM1, and thereby chromatin remodeling of IFN-stimulated genes that promote chronic inflammation, DNA damage resistance, and immune evasion.The polybromo-1 (PBRM1) chromatin-targeting subunit of the SWI/SNF PBAF chromatin remodeling complex drives DNA damage resistance and immune evasion in certain cancer cells through mechanisms that remain unclear. STAT1 and IRF1 are essential effectors of type I and II IFN pathways. Here, we report that MUC1-C is necessary for PBRM1 expression and that it forms a nuclear complex with PBRM1 in triple-negative breast cancer (TNBC) cells. Analysis of global transcriptional (RNA-seq) and chromatin accessibility (ATAC-seq) profiles further demonstrated that MUC1-C and PBRM1 drive STAT1 and IRF1 expression by increasing chromatin accessibility of promoter-like signatures (PLS) on their respective genes. We also found that MUC1-C, PBRM1, and IRF1 increase the expression and chromatin accessibility on PLSs of the (i) type II IFN pathway MUC1-C is necessary for PBRM1-driven chromatin remodeling in chronic activation of IFN pathway genes that promote DNA damage resistance and immunosuppression. The type I IFN pathway is chronically activated in cancer cells by DNA damage-associated molecular patterns that are generated in part by genomic instability . The cycThe SWI/SNF PBAF chromatin remodeling complex includes the PBRM1, ARID2, and BRD7 subunits . PBRM1 cMUC1 gene evolved in mammals to protect barrier tissues from the loss of homeostasis (MUC1 encodes (i) an N-terminal subunit (MUC1-N) that is shed from the apical cell surface into a protective mucous gel, and (ii) a transmembrane C-terminal (MUC1-C) subunit that activates inflammatory, remodeling, and repair pathways associated with wound repair  cells were cultured in RPMI-1640 medium (Thermo Fisher Scientific) containing 10% FBS (GEMINI Bio-Products), 100 μg/mL streptomycin, 100 U/mL penicillin, and 10 μg/mL insulin. Parental MDA-MB-436 BRCA1 mutant TNBC  and olaparib-resistant MDA-MB-436RR cells (Mycoplasma Detection Kit (Lonza). Cells were maintained in culture for 3–4 months for performing experiments.Human BT-549 RR cells  were culRR cells . Cells wRR cells . Cell au3) were seeded per well in 6-well ultra-low attachment culture plates (Corning) using the MammoCult Human Medium Kit (Stemcell Technologies). The mammospheres were (i) treated with vehicle or 500-ng/mL DOX (doxycycline), (ii) left untreated or treated with GO-203, (iii) treated with vehicle or carboplatin, and (iv) treated with vehicle or olaparib. Mammospheres with diameters >100 μm were counted in triplicate under an inverted microscope.Cells (2.5–5×10MUC1shRNA (MISSION shRNA TRCN0000122938) and a control scrambled shRNA  were inserted into pLKO-tet-puro  as described . CshRNA,Total RNA was isolated using TRizol (Invitrogen). cDNAs was synthesized using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) as previously described . SamplesWhole-cell lysates were prepared in RIPA buffer containing protease inhibitor cocktail (Thermo Fisher Scientific) as described . ImmunobNuclear lysates were isolated as described . NuclearGST, GST-IRF1 , GST-IRF1-N(aa 1–163), GST-IRF1-C(aa 163–325), GST-MUC1-CD , GST-MUC1-CD(aa 1–45), GST-MUC1-CD(aa 46–72), and GST-MUC1-CD(AQA) were prepared as described . PurifieChromatin immunoprecipitation (ChIP) was performed on cells crosslinked with 1% formaldehyde for 5 minutes at 37°C, quenched with 2 mol/L glycine, washed with PBS, and sonicated in a Covaris E220 sonicator to generate 300–600 bp DNA fragments, as described . ImmunopDNase I chromatin accessibility assays were performed as described . The DNA50 value was determined by nonlinear regression of the dose–response data using Prism 9.0 . Cell proliferation was assessed using the Alamar Blue assay (Thermo Fisher Scientific). Fluorescence intensity (560 nm excitation/590 nm emission) was measured in sextuplicate.MDA-MB-436 and MDA-MB-436RR cells were seeded at a density of 6,000 cells per well in 96-well plates. After 24 hours, cells were treated with different concentrations of olaparib. Cell viability was assessed using the Alamar Blue assay (Thermo Fisher Scientific) in sextuplicate wells. The ICin vitro and publicly available TNBC cohort data using the common genes found in the HALLMARK IFN_Gamma_Response and IFN_Alpha_Response pathways.Total RNA from cells cultured in triplicate was used to generate RNA-seq datasets, as described . Raw seqATAC-seq libraries were generated from three biologically independent replicates per condition as described . The accMammospheres were fixed with 4% paraformaldehyde (Sigma-Aldrich) at room temperature for 15 minutes. Samples were incubated with 1% Triton X-100 (Sigma-Aldrich) at room temperature for 10 minutes and blocked with 5% normal goat serum (Gibco). The mammospheres were attached to slides via cytospin at low speed  and stained with anti-γH2AX  and goat anti-rabbit IgG H and L labeled with Alexa Fluor 488 (Abcam) as described . Nuclei 6 tumor cells in 100 μL of a 1:1 solution of medium and Matrigel (BD Biosciences). When the mean tumor volume reached 100–150 mm3, the mice were pair-matched into groups and treated intraperitoneally with PBS or GO-203 (12 μg/g body weight) daily. Tumor measurements and body weights were recorded twice per week. These studies were conducted in accordance with the ethical regulations required for approval by the Dana-Farber Cancer Institute Animal Care and Use Committee (IACUC) under protocol 03–029.Six-week-old female nude mice (The Jackson Laboratory) were injected subcutaneously into the flank with 5×10All patients consented to an institutional review board-approved research protocol in Department of Surgery and Science, Kyushu University (Japan), allowing specimen collection and clinical data. Written informed consent was obtained from each patient, and the study was conducted using anonymized data in accordance with recognized ethical guidelines. Core needle biopsy specimens were obtained from 21 patients with TNBC. Formalin-fixed, paraffin-embedded sections were deparaffinized in xylene and graded concentrations of ethanol and distilled water. Antigen retrieval was performed in citrate buffer . Slides were incubated with anti–MUC1-C  for 8 hours at 4°C, and a MACH 4 Universal HRP-Polymer Detection System  was used for detection. Immunostained sections were counterstained with hematoxylin. MUC1-C staining intensity (IS) and proportion (PS) in cancer cells were scored in a blinded manner and independently by two investigators (N. Yamashita and Y. Inoue). IS scored from 0 to 3. IS0, no staining; IS1, low staining; IS2, moderate staining; IS3, strong staining. PS scored from 0 to 4. PS0, no staining; PS1, <25%; S2, 25%–50%; PS3, 51%–75%, and PS4, >75%. The IHC score was calculated by multiplying the IS and PS . Stromal–tumor-infiltrating lymphocytes (sTIL) were evaluated according to guidelines from the International TILs Working Group . Stromalhttp://kmplot.com/analysis/; ref. Survival curves based on MUC1 and PBRM1 expression levels were generated using the Kaplan–Meier Plotter . BT-549 cells ± MUC1shRNA were previously deposited under GEO accession GSE206212. BT-549 cells ± IRF1shRNA (GSE212168), ±PBRM1shRNA (GSE212169), and MDA-MB-436 cells ± MUC1shRNA (GSE212587) were deposited in GEO SuperSeries accession GSE212170.IRF1 contains an ISRE for STAT1 binding in a promoter-like signature  STAT1 PLS, and that silencing MUC1-C decreases their occupancy TAT1 PLS , with doIn vitro studies demonstrated that the MUC1-C cytoplasmic 72 aa domain binds to IRF1  and that this interaction is conferred by IRF1-N  levels in the tumor microenvironment (TME) that are necessary for T cell proliferation and function  silencing MUC1-C decreases their occupancy  thccupancy . SimilarMDA5 PLS . Consist regions . Moreove regions . Analysisistance . SilenciS region . We founccupancy . SilenciS region . MoreoveThe CSC state is associated with DNA damage resistance . MUC1-C Analysis of scRNA-seq datasets has demonstrated that MUC1 is widely expressed in TNBC tumor cell populations . HoweverIRF1 PLS and ELS regions. In support of a functional MUC1-C, STAT1, and PBRM1 interaction, silencing MUC1-C decreased STAT1 and PBRM1 occupancy. MUC1-C and PBRM1 were also found to be necessary for (i) opening chromatin in the IRF1 PLS and ELS regions and (ii) inducing IRF1 expression. Our results demonstrate that MUC1-C also directly interacts with IRF1 and that silencing MUC1-C decreases occupancy of PBRM1 and IRF1 on STAT1 PLS. Moreover, silencing MUC1-C and PBRM1 decreased chromatin accessibility of the STAT1 PLS, supporting a chronic MUC1-C–driven STAT1/IRF1/PBRM1 auto-inductive signaling network.PBRM1 represses, as well as activates, IFN pathway genes in different cancer cells . PBRM1 sSTAT1, MUC1-C/PBRM1/IRF1 complexes induce chromatin accessibility and expression of the type II IFN pathway IDO1 and WARS genes. In support of a common mechanism for the induction of IRF1 target genes, we also found that MUC1-C/PBRM1/IRF1 complexes are necessary for the induction of chromatin accessibility and the expression of the type I IFN pathway RIG-I and MDA5 genes. These findings and the demonstration that silencing MUC1-C decreases chromatin accessibility and the expression of multiple other ISGs uncovered the involvement of MUC1-C and PBRM1 in chronic activation of type I and II IFN pathways  PBRM1, IRF1, and ISG15 expression, (ii) self-renewal capacity, and (iii) DNA damage resistance. Similar results were obtained with GO-203 treatment of olaparib-resistant TNBC cells, confirming that MUC1-C is a target for suppressing the CSC state and resistance to genotoxic agents.The CSC state is associated with DNA damage resistance and immune evasion . Our ressistance . Of potehibitors . In thisIn extending these findings to TNBC tumors, we found that MUC1 and PBRM1 are associated with decreased RFS in patients treated with chemotherapy. We also found that MUC1-C expression in TNBCs is associated with depletion of sTILs, which decreases responsiveness to chemotherapy and survival . These fSupplementary Figures S1-S9 and Tables S1-S4.S1. Silencing MUC1-C downregulates IRF1 expression in TNBC cells.S2. Effects of silencing MUC1-C on TNBC cells.S3. MUC1-C is necessary for PBRM1 expression A and B.S4. MUC1-C forms a direct complex with IRF1 that activates type I and II ISGs.S5. Common genes regulated in cells silenced for MUC1, IRF1, and PBRM1.S6. Silencing MUC1-C, IRF1, and PBRM1 downregulated IDO1 and WARS in TNBC cells.S7. Silencing of MUC1-C, IRF1, and PBRM1 downregulates RIG-I and MDA5 in TNBC cells.S8. Silencing MUC1-C, IRF1, and PBRM1 downregulates ISG15 expression in TNBC cells.S9. Effects of silencing IRF1 and PBRM1 on BT-549 mammosphere formation and GO-203 treatment on the viability of olaparib-resistant MDA-MB-436RR cells.Table S1. Primers used for qRT-PCR.Table S2. Primers used for ChIP-qPCR and DNase I chromatin accessibility assays.Table S3. Common downregulated 196 DEGs in BT-549 cells with silencing of MUC1, IRF1, and PBRM1.Table S4. Overlapping IFN-pathway genes downregulated in cells with MUC1-C, PBRM1, and IRF1 silencing.Click here for additional data file.


Growth factor-induced, ERK-mediated induction of immediate-early genes (IEGs) is crucial for cell growth and tumorigenesis. Although IEG expression is mainly regulated at the level of transcription elongation by RNA polymerase-II (Pol-II) promoter-proximal pausing and its release, the role of ERK in this process remains unknown. Here, we identified negative elongation factor (NELF)-A as an ERK substrate. Upon growth factor stimulation, ERK phosphorylates NELF-A, which dissociates NELF from paused Pol-II at the promoter-proximal regions of IEGs, allowing Pol-II to resume elongation and produce full-length transcripts. Furthermore, we found that in cancer cells, PP2A efficiently dephosphorylates NELF-A, thereby preventing aberrant IEG expression induced by ERK-activating oncogenes. However, when PP2A inhibitor proteins are overexpressed, as is frequently observed in cancers, decreased PP2A activity combined with oncogene-mediated ERK activation conspire to induce NELF-A phosphorylation and IEG upregulation, resulting in tumor progression. Our data delineate previously unexplored roles of ERK and PP2A inhibitor proteins in carcinogenesis. Growth factor-induced release of RNA Pol-II promoter-proximal pausing is vital for immediate-early gene expression, but its mechanism remains elusive. Here, the authors reveal roles of ERK and PP2A in this process and their dysregulation in cancer. Upon stimulation of cells with growth factors such as epidermal growth factor (EGF), their respective receptor tyrosine kinases (RTKs) activate Ras and recruit Raf family kinases to the plasma membrane, which promotes Raf activation. Activated Raf phosphorylates and activates MEK1/2, which in turn activate ERK1/2 by phosphorylation. A portion of the activated ERK then translocates to the nucleus where it phosphorylates and activates specific substrate proteins, including several transcription factors (TFs) , and promotes the expression of so-called immediate-early genes (IEGs)2. IEGs are a class of genes whose expression is low or undetectable in quiescent cells but is rapidly (within 15–60 min) induced after growth factor stimulation in a manner independent of de novo protein synthesis. Since many of the IEGs encode TFs , their induction further upregulates the expression of various target genes that elicit cell cycle progression , motility, angiogenesis, and others, depending on cell type and stimulus3. Therefore, some IEGs act as proto-oncogenes and promote tumorigenesis.The ERK pathway transduces mitogenic signals and plays a pivotal role in a wide array of biological processes, including cell proliferation, differentiation, and carcinogenesis1. These oncogenes constitutively activate ERK and induce hyperphosphorylation of ERK substrate proteins, each of which contains SP or TP consensus phosphorylation motifs4, thereby leading to carcinogenesis. Moreover, since the phosphorylation level of a protein is determined by the balance between the activities of the related protein kinase and phosphatase, aberrant inactivation of protein phosphatases is also involved in carcinogenesis. Indeed, the activity of protein phosphatase 2A (PP2A), a major cellular Ser/Thr-specific phosphatase, is often suppressed in a variety of cancers by overexpression of endogenous PP2A inhibitor proteins such as SET and cancerous inhibitor of protein phosphatase 2A (CIP2A)5. These molecules directly bind to and inhibit PP2A, thereby contributing to tumor development and progression6. However, the precise role and target of the PP2A inhibition in cancer are not fully understood.Aberrant activation of ERK signaling is frequently observed in human cancers. Gene amplification or gain-of-function mutations of key ERK pathway components, including RTKs , Ras, and BRAF, are common in a variety of cancers7. In general, during the transcription cycle, mRNA synthesis begins with the association of DNA-binding TFs with their target motifs and the recruitment of Pol-Il and general TFs to the promoter region of a gene. This initiation stage is the rate-limiting step for gene expression. Recent studies have, however, revealed that the post-initiation steps, in particular Pol-II pausing and its release into productive elongation, also serve as critical checkpoints for gene expression8. At the early elongation stage, Pol-II synthesizes short nascent RNAs and then pauses ~20–60 nucleotides downstream from transcription start sites (TSSs) where it awaits further signals to resume elongation and to complete the generation of functional full-length mRNAs. This process, termed promoter-proximal pausing (PPP) of Pol-II, is seen in ~60% of expressed mammalian genes, and its stimulus-induced release into productive elongation is thought to be critical for achieving rapid and synchronous gene expression9. Notably, the rapid expression of IEGs is mainly regulated at the level of elongation by PPP and its release10. Indeed, the promoter regions of many IEGs  are constitutively occupied by Pol-II independently of mRNA synthesis in resting cells, and upon growth factor stimulation, Pol-II is released from pausing into active elongation, thereby rapidly inducing IEG expression11. However, the precise mechanism by which growth factors elicit Pol-II pause release on IEGs remains unknown.The transcriptional regulation of gene expression by Pol-II in metazoans is a fundamental but complex process composed of several sequential steps, including initiation, pausing, pause release, elongation, and termination12. PPP is induced mainly by the binding of NELF, which is composed of the four subunits NELF-A, -B, -C (or isoform NELF-D that lacks the first nine NELF-C residues) and -E, to the elongation complex that includes Pol-II and DSIF13. A recent cryo-electron microscopy study of the paused NELF-Pol-II-DSIF complex showed that, of the four NELF subunits, NELF-A is particularly important for the induction of PPP, as the C-terminal part (residues 189–528) of NELF-A forms a tentacle-like extension that directly binds to Pol-II and DSIF, thereby stabilizing Pol-II pausing14. In contrast, Pol-II pause release is mediated by P-TEFb, a kinase complex composed of cyclin-dependent kinase 9 (CDK9) and cyclin T115. P-TEFb phosphorylates Ser2 on the C-terminal domain (CTD) of Pol-II as well as DSIF16. Furthermore, P-TEFb also phosphorylates NELF17. These orchestrated phosphorylation events are thought to induce NELF dissociation from paused Pol-II and allow Pol II to resume elongation. However, recent studies indicate that NELF dissociation can occur independently of P-TEFb19. Indeed, following lipopolysaccharide stimulation, genome-wide NELF dissociation from chromatin takes place normally even in cells genetically deficient for CDK9 (the kinase subunit of P-TEFb)20, indicating the presence of another as yet unidentified mechanism that controls NELF dissociation. Furthermore, although both ERK signaling and NELF-mediated Pol-II regulation play pivotal roles in the induction of IEGs, their functional relationship, if any, remains unexplored.In general, Pol-II pausing and its release are regulated by the coordinated action of negative and positive regulators, including NELF, DRB sensitivity-inducing factor (DSIF), and positive transcription elongation factor-b (P-TEFb)Here, we identified NELF-A, the subunit of NELF that is critical for the stabilization of Pol-II pausing, as a substrate of ERK. We also demonstrate the molecular mechanism by which growth factors induce IEG expression at the level of transcription elongation by controlling PPP. Furthermore, we show that NELF-A phosphorylation is tightly regulated by the balance between ERK and PP2A activities. Therefore, in cancer cells with intact PP2A, oncogene-induced constitutive, but relatively moderate, ERK activity often fails to induce NELF-A phosphorylation, and thus IEG expression is low. However, when PP2A inhibitor proteins, such as SET and CIP2A, are overexpressed, as is frequently found in human cancers, decreased PP2A activity allows enhanced NELF-A phosphorylation; this causes aberrant upregulation of IEGs and associated downstream growth-promoting genes, and tumor progression. Our data provide insights into the roles of ERK and PP2A inhibitor proteins in the etiology of human cancer.4 21, failed to interact with NELF-A, confirming phosphorylation-dependent interaction  (an ERK activator), and incubated it with recombinant GST-NELF-A. The reaction mixture was then separated on SDS-PAGE, and the phosphorylation of GST-NELF-A was monitored by Pro-Q diamond gel staining, which selectively detects phosphorylated proteins Fig. . Active F-A Fig. . Virtual363P  within the SP/TP-rich region (hereafter termed 4A mutations) resulted in a dramatic decrease in TPA-induced NELF-A phosphorylation  in NELF-A, we performed mass spectrometry analysis of Flag-NELF-A purified from TPA-stimulated HEK293 cells. In the LC-MS/MS analysis, which achieved about 76% sequence coverage of NELF-A, we identified one phosphorylation site, S63P Fig. . Ser-to-63P Fig. . This S363P Fig. , suggestion Fig. , whereasion Fig. . Furtherion Fig. , indication Fig. . Therefoits Fig. . Thus, N2 and Ser5  in HEK293-WT and −4A cells, respectively  using quantitative reverse transcription-PCR (qRT-PCR)  or of stress-inducible genes (HSP90AB1 and HSP90AA1) whose induction is regulated by PPP under stress conditions17  or the unphosphorylatable Myc-NELF-A(4A) mutant  Fig. . As anti 23 Fig. . We valiCR) Fig. . Interesses Fig. . In conts17 Fig. , suggest8. To determine whether ERK-mediated NELF-A phosphorylation impacts on these elongation steps, we next analyzed the association of NELF-A and Pol-II with two representative IEG loci (FOS and JUNB) before and 30 min after EGF stimulation by chromatin immunoprecipitation-qPCR (ChIP-qPCR) assays with primer sets specific to the TSSs and other regions of the genes , and the NELF-A occupancy remained high after EGF stimulation . Furthermore, in the absence of EGF, Pol-II was associated only with the TSS of the FOS gene, but not with its downstream gene body regions, indicating that it was proximally paused. However, following EGF stimulation, Pol-II accumulated in the gene body regions, confirming EGF-induced transition of paused Pol-II into productive elongation in HEK293-WT cells. By contrast, in HEK293-4A cells (shown in orange bars), significantly more NELF-A(4A) was found at TSS, compared with WT NELF-A in HEK293-WT cells. In particular, the enhanced association of NELF-A(4A) with the TSS became more evident following EGF treatment, suggesting that NELF-A(4A) efficiently binds to and stalls Pol-II at the promoter-proximal site even after EGF stimulation. Indeed, after EGF addition, the amount of paused Pol-II near the TSS was significantly increased, whereas the levels of processive Pol-II on the gene body regions were markedly decreased in HEK293-4A cells as compared with HEK293-WT cells. Thus, Pol-II remained stalled at the TSS even after EGF stimulation when cellular NELF-A phosphorylation is prevented. Essentially identical results were also obtained for JUNB  carrying intact retinoblastoma (Rb) protein, a key regulator of growth factor-induced cell cycle progression26. We again established HaCaT cell lines in which endogenous NELF-A is depleted and replaced with the Myc-NELF-A or Myc-NELF-A(4A)   Fig. . These cly) Fig.  and the ly) Fig. . Furtherly) Fig. , the ratly) Fig. , and conly) Fig.  were all28. We subcutaneously injected HaCaT-WT or −4A cells into nude mice and monitored tumor growth for 36 days , and A375 (BRafV600E). In control cells (HeLa) with low basal ERK activity, EGF-induced strong ERK activation led to a marked phosphorylation of endogenous NELF-A. Surprisingly, however, little or no phosphorylation of NELF-A was detected in the three cancer cell lines, even though ERK and RSK (an ERK substrate) were constitutively phosphorylated and activated by the oncogenes , H1299 . Similar results were obtained for FOSB expression   and with those of growth-promoting genes  in KRAS-mutated pancreatic cancers  Fig. . Thus, tAF) Fig. , left. SAF) Fig. , right. ers Fig. . Consisters Fig. . We confers Fig.  and IEG ers Fig.  in H12991, less is known about the role of ERK in the regulation of the elongation process. We found that ERK-dependent phosphorylation of NELF-A facilitates the dissociation of NELF from the stalled pol-II at the promoter-proximal regions of IEGs, thereby releasing pol-II into productive elongation. Although P-TEFb is known to phosphorylate NELF-A mainly at T157, T277, and S363 at least in vitro17, the precise mechanisms that regulate in vivo NELF-A phosphorylation have remained obscure. Furthermore, recent studies have reported P-TEFb-independent dissociation of NELF from chromatin20. Therefore, the functional significance of P-TEFb in stimulus-induced NELF dissociation from chromatin is still unclear. In the present study, we showed that upon growth factor stimulation, ERK phosphorylated NELF-A at S363, S393, T396, and T399. These sites are mostly different from those phosphorylated by P-TEFb, and we also observed that CDK9 depletion did not suppress the phosphorylation. Therefore, our data indicate that growth factor-induced NELF-A phosphorylation is mediated by ERK but not by P-TEFb in vivo, and suggest that NELF-A is phosphorylated in a context-dependent manner.In this study, we identified NELF-A as an ERK substrate, and demonstrated that ERK-mediated NELF-A phosphorylation is crucial for growth factor-induced Pol-II pause release and the resulting productive transcription elongation of IEGs, thereby promoting cell growth. While the importance of ERK in the transcription initiation step  is well documented363, S393, T396, and T399. At the same time, P-TEFb is recruited to promoter-proximal regions, where it phosphorylates the Pol-II CTD at Ser2 and DSIF8. These ERK and P-TEFb-mediated multiple phosphorylation events cooperatively induce NELF dissociation from Pol-II and elicit the transition of Pol-II from pausing into productive elongation, thereby inducing IEG expression. ERK also phosphorylates and activates TFs responsible for IEG expression 2, which further increases the rate of the aforementioned transcription cycle. Through these coordinated actions, ERK rapidly and strongly upregulates IEG expression in response to mitogenic stimuli and drives cell cycle progression. Our data reveal a previously unexplored role of ERK in the regulation of IEG expression and the resulting cell growth. Since the ERK phosphorylation sites of NELF-A are evolutionarily conserved among vertebrates, this mechanism of regulating Pol-II elongation might be similarly conserved across species and control growth factor-induced expression of genes with high pausing indices.On the basis of the present results, we propose the following mechanism for growth factor-induced, ERK-mediated IEG expression Fig. , left. UAnother important finding is that PP2A efficiently dephosphorylates NELF-A and thereby rigorously controls the expression levels of IEGs under physiological and pathological conditions. Following TPA stimulation, NELF-A phosphorylation gradually declined and returned to a basal level by about 2 h, even though high ERK activity persisted for more than 4 h. This NELF-A dephosphorylation was repressed by the PP2A inhibitors, but accelerated by a PP2A activator. Thus, the phosphorylation state of NELF-A is principally determined by the balance between ERK and PP2A activities, and its phosphorylation requires a relatively high level of ERK activity to overcome PP2A-mediated dephosphorylation. Furthermore, we showed that suppression of cellular PP2A activity dramatically augmented growth factor-induced IEG expression mainly through enhancing NELF-A phosphorylation. Thus, PP2A-mediated control of the magnitude and duration of NELF-A phosphorylation is vital for the proper regulation of IEG expression. In other words, robust PP2A-mediated NELF-A dephosphorylation serves to buffer ERK activity in order to prevent cells from inadvertent or excessive IEG induction and cell growth.6. Considering that PP2A activity is a key determinant of NELF-A phosphorylation in cancer, the pharmacological reactivation of PP2A would be highly effective in suppressing the expression of IEGs and growth-promoting genes, and thus it may provide significant benefits in cancer treatment.Consistent with this notion, we found here that the constitutive (but relatively moderate) ERK activation induced by oncogenes is insufficient to induce NELF-A phosphorylation. Importantly, however, chemical or genetic suppression of cellular PP2A activity readily induced NELF-A phosphorylation, indicating that PP2A activity is critical in determining the phosphorylation state of NELF-A in cancer cells. Thus, NELF-A is unique among ERK substrates in that its phosphorylation is not simply induced by oncogene-induced ERK activation; rather, it also requires concurrent PP2A suppression in cancer. This PP2A-dependent control of NELF-A phosphorylation provides vital insight into the roles of the PP2A inhibitor proteins in tumorigenesis Fig. , right. 3VO4, 1 mM DTT, 1 mM phenylmethylsulphonyl fluoride (PMSF), 10 μg/ml leupeptin, and 10 μg/ml aprotinin. Lysis buffer B contained 20 mM Tris-HCl (pH 7.5), 0.5% Triton X-100, 10% glycerol, 137 mM NaCl, 2 mM EDTA (pH 8.0), 50 mM β-glycerophosphate, 10 mM NaF, 1 mM Na3VO4, 1 mM DTT, 1 mM PMSF, 10 μg/ml leupeptin, and 10 μg/ml aprotinin. Lysis buffer C contained 20 mM Tris-HCl (pH 7.5), 1% Triton X-100, 0.1% deoxycholate, 10% glycerol, 150 mM NaCl, 50 mM NaF, 1 mM DTT, 1 mM PMSF, 10 μg/ml leupeptin, 10 μg/ml aprotinin, and 100 nM microcystin LR. Kinase buffer contained 25 mM Tris-HCl (pH 7.5), 25 mM MgCl2, 7 mM β-glycerophosphate, 0.5 mM Na3VO4, and 2 mM DTT. Phosphatase buffer contained 25 mM Tris-HCl (pH 7.5), 1 mM EDTA, and 1 mM DTT.Lysis buffer A contained 20 mM Tris-HCl (pH 7.5), 1% Triton X-100, 0.5% deoxycholate, 10% glycerol, 150 mM NaCl, 2 mM EDTA (pH 8.0), 50 mM β-glycerophosphate, 10 mM NaF, 2 mM Na33. pSUPER.retro.puro vector (Oligoengine) was used to generate the NELF-A-shRNA construct  was obtained from Open Biosystems. Myc-NELF-A, Flag-NELF-A, His-NELF-A, Flag-NELF-B, Flag-NELF-C, Flag-NELF-E, HA-SET, Myc-CIP2A, HA-MEK1, Myc-MEK1, HA-ERK2, HRas(G12V), and their derivative mutants were subcloned into pcDNA3 (Invitrogen), pQCXIP, pQCXIH (Clontech), or pWZL-Blast (Addgene). Various point mutants of NELF-A were constructed using PCR-based mutagenesis. A constitutively active MEK1(DD) and a kinase-inactive ERK2(K52N) were described previouslyA375 (CRL-1619) and H1299 (CRL-5803) were obtained from ATCC. HEK293 (RCB1637), COS7 (RCB0539), HeLa (RCB0007), A549 (RCB3677), A431 (RCB0202), and GP2-293 (RCB2354) were obtained from RIKEN cell bank. HaCaT cells were kindly provided by Prof. Dr. N. Fusenig . Cells were maintained in Dulbecco’s modified Eagle medium supplemented with 10% fetal bovine serum, L-glutamate, penicillin, and streptomycin. Where indicated, the cells were stimulated with EGF (20 ng/ml) or TPA (300 nM) for 15 min or the indicated times. Before stimulation, cells were pre-treated with MEK or ERK inhibitors  for 45 min, a Cdk9 inhibitor [100 µM DRB (Cayman)] for 3 h, or with phosphatase inhibitors  for 60 min as indicated, unless otherwise noted.ura3) strain4. TM414 cells were first transformed with the pLexA-WW bait together with a p426ADH-ERK2(PD) expression plasmid. The cells were then further transformed with a mixture of human cDNA libraries  constructed in the pACT2 vector. Transformants were grown on selective medium  containing 3-aminotriazole (1 mM). Yeast colonies exhibiting histidine-independent growth were isolated and further analyzed. For the yeast spot assay, yeast cells were grown on a selection medium containing 3-aminotriazole (1 mM).Yeast three-hybrid analysis was performed using a yeast TM414  according to the manufacturer’s protocol. For siRNA transfection experiments, cells were transfected with an siRNA targeting CDK9 ] overnight at 4 °C. Protein G-Dynabeads (Thermo Fisher) were then added and incubated for 1 h. Immunoprecipitates were washed three times with lysis buffer B. Proteins were separated by SDS-PAGE and immunoblotted with the indicated antibodies.For immunoprecipitation experiments, cell lysates were prepared with lysis buffer A and precleared with protein G-Sepharose beads  at 4 °C for 1 h. Precleared lysates were incubated with an appropriate antibody [anti-Flag M2  or anti-Myc 9E10  antibody] for 3 h with gentle rotation. Protein G-Sepharose beads were then added and incubated for 1 h. Immunoprecipitates were collected by centrifugation and washed three times with lysis buffer A containing 0.1% SDS and subjected to SDS-PAGE. For co-immunoprecipitation assays, cells were harvested with lysis buffer B and sonicated using Qsonica Q700 (QSonica) and centrifuged. The supernatants were incubated with an appropriate antibody  at 4 °C for 12 h with gentle rotation. The purified DNA was subjected to quantitative PCR analysis using Thunderbird SYBR qPCR mix (Toyobo). All primers used were listed in Supplementary Table The ChIP assay was performed using the SimpleChIP Enzymatic Chromatin IP kit (CST) according to the manufacturer’s protocol. Immunoprecipitates were recovered with Protein-G Dynabeads (Invitrogen) together with specific antibodies [anti-Myc 9B11 , anti-Pol II CTD 4H8 , or mouse control IgG3 HaCaT cells/well were seeded in triplicate in DMEM with 10% FBS, and cell growth was monitored each day using the Cell Counting Kit-8 (Dojindo). For the mouse xenograft experiments, five-week-old female BALB/c-nude mice were purchased from Oriental Yeast . 5×106 HaCaT-WT, HaCaT-4A, Ras-HaCaT-WT, or Ras-HaCaT-4A cells suspended in 100 µl Matrigel (Corning) were injected subcutaneously into the left or right side flank of each mouse. Tumor volume (mm3) was measured with calipers and was calculated as (L × W2)/2, where L is length and W is width. This study was conducted in accordance with the Regulations for Animal Care and Use of The University of Tokyo and the Guidelines for Proper Conduct of Animal Experiments by the Science Council of Japan, and was approved by the Animal Experiment Committee at the Institute of Medical Science, The University of Tokyo . The housing conditions for the mice are as follows: temperature 22 ± 2 °C, humidity 55 ± 5%, and light/dark cycle 12 h/12 h (8 a.m.−20 p.m. light).For the cell proliferation assay, 3 × 105 cells were serum-starved for 72 h on a coverslip in a 35-mm dish, and then stimulated with 100 ng/ml EGF for 18 h. After incubation with 10 µM BrdU for 1 h, cells were fixed and incubated with an anti-BrdU antibody (1:10 dilution of Anti-BrdU stock solution supplied by the manufacturer) and a secondary anti-mouse-Ig-fluorescein antibody (1:10 dilution of Anti-mouse-Ig-fluorescein stock solution supplied by the manufacturer). The nuclei were labeled with DAPI. The percentage of BrdU-positive cells was analyzed using Operetta CLS (PerkinElmer) equipped with Harmony software (ver. 4.5).BrdU assay was performed using 5-bromo-2′-deoxy-uridine Labeling and Detection Kit I  according to the manufacturer’s instructions. Briefly, 1 × 10https://xenabrowser.net/), and were analyzed using GraphPad Prism9. Genetic alterations and gene expression in the TCGA clinical samples were visualized as an Oncoprint plot using cBioportal .To compare the gene expression levels between normal and tumor tissues, the gene expression and clinical data of pancreas, skin, lung, and colon cancer patients were retrieved from a combined cohort of TCGA, TARGET, and GTEx samples (TCGA-TARGET-GTEx), and from the International Cancer Genome Consortium (ICGC) using the UCSC Xena Browser  and the growth-related genes. All the experiments shown in Figs. The statistical significance of the difference between mean values was tested by a two-tailed Student’s Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Atherosclerosis (AS), leading to gradual occlusion of the arterial lumen, refers to the accumulation of lipids and inflammatory debris in the arterial wall. Despite therapeutic advances over past decades including intervention or surgery, atherosclerosis is still the most common cause of cardiovascular diseases and the main mechanism of death and disability worldwide. Vascular smooth muscle cells (VSMCs) play an imperative role in the occurrence of atherosclerosis and throughout the whole stages. In the past, there was a lack of comprehensive understanding of VSMCs, but the development of identification technology, including in vivo single-cell sequencing technology and lineage tracing with the CreERT2-loxP system, suggests that VSMCs have remarkable plasticity and reevaluates well-established concepts about the contribution of VSMCs. Transcription factors, a kind of protein molecule that specifically recognizes and binds DNA upstream promoter regions or distal enhancer DNA elements, play a key role in the transcription initiation of the coding genes and are necessary for RNA polymerase to bind gene promoters. In this review, we highlight that, except for environmental factors, VSMC genes are transcriptionally regulated through complex interactions of multiple conserved cis-regulatory elements and transcription factors. In addition, through a series of transcription-related regulatory processes, VSMCs could undergo phenotypic transformation, proliferation, migration, calcification and apoptosis. Finally, enhancing or inhibiting transcription factors can regulate the development of atherosclerotic lesions, and the downstream molecular mechanism of transcriptional regulation has also been widely studied. Atherosclerosis (AS) is a chronic inflammatory process driven by cholesterol accumulation coupled to inflammatory and fibrotic reactions within the arterial wall, and it remains the leading cause of death worldwide . The roles of VSMCs are indispensable for maintaining the normal functions of arterial vessels, including elastic recoil in large elastic arteries and modulation of arterial diameter in middle arteries and arterioles , a coactivator of serum response factor (SRF), is involved in lipid metabolism, vascular inflammation, development of postnatal and embryonic vasculature  is a zinc-finger transcription factor that plays a key role in cellular proliferation, differentiation, apoptosis and the generation of induced pluripotent stem (iPS) cells (McConnell and Yang Octamer-binding transcription factor 4 (OCT4), the main stemness marker whose expression is associated with self-renewal and pluripotency maintenance of embryonic stem cells , is activated by choline, and then up-regulates the expression of its downstream proteins heme oxygenase-1 (HO-1) and NAD[P]H quinone oxidoreductase-1 (NQO-1), which could ameliorate the vascular remodeling via inhibiting the transformation of VSMCs to the synthetic phenotype . Exposure to cholesterol activates all 3 pathways of the UPR, and the increase of KLF4 level has been known primarily via the Perk-eIF2α-Atf4 arm of the endoplasmic reticulum (ER) stress , the key osteogenic regulator for osteoblast differentiation and chondrocyte maturation, represses MYOCD-induced differentiation and promotes the osteogenic transformation of VSMCs via disrupting the formation of the MYOCD and SRF complex  by crosstalk of the classical RelA and alternative RelB NF-κB signaling pathways , could transport into the nucleus to combine with specific regulatory sequences to activate or suppress transcription of target genes, which are related to diverse cardiac pathophysiologic progress, including apoptosis, proliferation, immune regulation and inflammation . Phosphorylated FOXO3, the main forkhead transcription factor related to the regulation of the cell cycle, DNA repair, defense against oxidative stress and longevity, is rendered inactive by exclusion from the nucleus into the cytoplasm and rapid degradation to regulate VSMC proliferation and migration , a ubiquitous transcription factor that regulates cellular oxygenation and metabolic adaptation to hypoxic states, up-regulates macrophage migration inhibitory factor (MIF) expression in VSMCs. The hypoxia-induced MIF expression plays a vital role in increased VSMC proliferation and migration in an autocrine and paracrine manner. Knockdown of HIF-1 prevents any hypoxia-induced migration  efflux to the ECM via down-regulating ankylosis protein homolog (ANKH), a transmembrane protein controlling pyrophosphate secretion (Zhao et al. Transcription factors play an important role in VSMC regulation during atherosclerotic lesions. While previous studies have proved that transcription factors and their target genes can shape complex transcriptional regulatory networks, our understanding of the complexity and vulnerability of these networks is still far from enough. Recently, the application of new biotechnologies provides us with new insights in identifying transcription factors. The links between transcription factors and VSMCs have established a new field for the diagnosis and therapy of atherosclerosis. A deeper understanding of transcriptional regulatory mechanisms will lead to the identification of novel therapeutic targets for atherosclerosis and the development of target-based new anti-atherosclerotic drugs. Besides, research on VSMCs should continue to be in-depth by combining with the regulation of transcription factors. A comprehensive understanding of VSMCs will alleviate the progression of atherosclerosis, which has been proved as a remarkably promising direction.


Zencir et al. Nature Communications 10.1038/s41467-022-30350-3 (2022)1. We agree that our paper shifts our understanding of how acetylation is targeted to transcribed genes and thus the more scrutiny the results receive, the better. With this being said, we respectfully disagree that the loss of histone acetylation in cells treated with the transcription inhibitor, 1,10-phenanthroline , is due to the disruption of histone acetyltransferase (HAT) binding to promoters. Although we do not dispute that the binding of some transcription activators, and thus HATs, may be impacted by this drug, the NuA4/piccolo HAT complex subunit, Epl1, is not lost at most promoters following 1,10-pt treatment. Using DESeq2’s binomial test2 with a lenient cutoff , we observe a statistically significant loss of Epl1 binding at only 3.6% (198/5542) of promoters  Epl1 binding is stable at most promoters, albeit with a small fraction showing decreased binding, and (2) Epl1 is ubiquitously lost from 5′ gene body regions, consistent with our interpretation of transcription-dependent targeting of Epl1 to gene bodies. While the binding of Epl1 to both promoters and gene bodies is difficult to differentiate in the gene-dense yeast genome, the contrasting impact of Epl1 mutation and 1,10-pt treatment on Epl1 binding to these features confirms the specificity of our ChIP-seq experiments and strengthens our finding that Epl1 binding is stable to 1,10-pt at the vast majority of promoters. While Zencir et al. raise good points about the pitfals of metaplots, the heatmaps we included in our original paper address many of the points they now claim to uncover. Despite the limited impact of 1,10-pt on Epl1 occupancy, we observed loss of H4K8ac and H4K12ac at the majority of adjacent +1 nucleosomes 1. As Zencir et al. highlight, the highly expressed ribosomal protein genes are repressed by heat shock and thus will make up a large proportion of the 400 genes they analyzed. Analysis of all genes reveals the flaws of their comparison, as 1,10-pt effects on RNAPII occupancy bear little resemblance to the effects of heat shock on RNAPII serine 5 phosphorylation5  and the lack of colocalization of HATs with acetylation . Admittedly, these are correlative analyses, but we cannot envisage why chromatin-bound HATs would not robustly acetylate nucleosomes, especially those upstream of promoters, unless post-recruitment regulation was involved. While we agree with Zencir et al. that additional experiments mapping HATs and histone acetylation following transcription inhibition would be helpful, we argue that to a large degree these experiments have already been performed. Namely, in mESCs, inhibition of transcription initiation or elongation disrupts the binding of the mammalian homolog of Esa1, Tip60, to gene bodies, which mirrors the impact of 1,10-pt treatment in yeast11. Furthermore, groups using a RNAPII-degron or triptolide to inhibit transcription initiation observed a strong transcription-dependence of H3K27ac in human cell lines13. In our hands, a Rpb2-degron approach revealed close to a 50% reduction in H4K8ac, despite the tendency of this approach to achieve incomplete depletion of transcribing RNAPII12. Thus, multiple groups, using varying methods to block transcription in diverse systems, all observed remarkably similar results. We believe that this is very strong evidence for the generality of our findings, that transcription does indeed shape histone acetylation. Finally, it should be noted that although our work conflicts with the widely accepted model of histone acetylation functioning upstream of transcription, it is compatible with data upon which this model is based. These include four key findings: (1) the interaction of HATs with transcription activators, (2) the requirement of HATs for full gene activation, (3) the packaging of active genes with acetylated histones, and (4) the weakening of chromatin structure by histone acetylation. All of these findings are consistent with a new model based on transcription-stimulation of HAT activity. In this model, HATs, regardless of their mode of targeting, function as components of feed-forward loops that reinforce the active transcription state through acetylating histones.While we welcomed the request to reexamine our data generated from cells treated with 1,10-pt, it is important to note that experiments using 1,10-pt are not the only data supporting the transcription-dependence of histone acetylation in our manuscript4 or +1 nucleosomes14, were calculated using the Java Genomics Toolkit  ngs.IntervalStats script. For DEseq2 analysis2, size factors accounting for sequencing depth and the scaling factors reported in Martin et al.1 were used. For calling NDRs with increased or decreased Epl1 binding, we used lenient cutoffs of a fold change of >1.5 and an adjusted p-value (FDR) of <0.1. For NET-seq data15, processed bedGraphs were downloaded from GSM1673641 and GSM1673642. Sense and antisense read counts in specified windows were calculated using the Java Genomics Toolkit, summed across replicates, and violin plots made in Prism. For RNAPII serine 5 phosphorylation ChIP-seq5, FASTQ files were downloaded from the SRA (SRR8450263 and SRR8450261) and mapped using BWA. Fragment centers, estimated using an assumed fragment length of 150 bp, were counted from the TSS to +400 bp. These were depth normalized to compare to RNAPII normalized as described in Martin et al. Principal component analysis (PCA) was performed on all 5542 genes (TSS+400) using the regularized log transformation and plotPCA functions of DEseq22.FASTQ files were mapped as described in Martin et al. BAM files were filtered for 100–500 bp reads and total read midpoints overlapping nucleosome depleted regionsFurther information on research design is available in the Reporting SummaryPeer Review File