Snail1 transcriptional factor plays a key role in the control of epithelial to mesenchymal transition and fibroblast activation. As a consequence, Snail1 expression and function is regulated at multiple levels from gene transcription to protein modifications, affecting its interaction with specific cofactors. In this review, we describe the different elements that control Snail1 expression and its activity both as transcriptional repressor or activator. Epithelial to mesenchymal transition (EMT) is a progressive and reversible process that promotes epithelial cells to acquire a mesenchymal phenotype. During this transition, the cell-cell junction structures, including adherens junctions and desmosomes, are disassembled. Cells lose their cobblestone appearance and adopt a spindle-shaped morphology. EMT provides epithelial cells with different traits relevant for tumorigenesis since, upon EMT, cells become more motile and invasive, become more resistant to pro-apoptotic stimuli, reprogram their metabolism, and acquire characteristics of cancer stem cells. For these reasons, EMT has attracted the attention of many cancer biologists and has been extensively studied in recent years. Many excellent and recent reviews have addressed different insights in EMT and the acquisition of high-grade malignancy ,2,3.Snai1 depletion severely impacts mesoderm formation during embryogenesis [EMT is orchestrated by a set of EMT-activating transcriptional factors (EMT-TFs), whose core set includes Snail1 (Snail), Snail2 (Slug), Twist1, Zeb1, and Zeb2 , and Snaogenesis . For thiogenesis . Besidesogenesis , a proceogenesis . WithoutSnail1 expression was initially studied analyzing its mRNA. First, studies on the control of Snail1 were based on transcription and carried out with human and mouse proximal promoters that present less than 50% of homology. Accordingly, although many similarities are present, transcription factor binding elements described in one of these species cannot automatically be extrapolated to the other. In Snai1 transcription and activity of a 900 pb fragment of the Snai1 proximal promoter [Snai1 promoter in mouse is controversial. The initial observations using a dominant negative form of Smad4 pointed to a Smad4-independent activation [Snai1 promoter was activated by TGFβ through the action of Smad2, -3, and -4 [Smad2 ablation in keratinocytes show an enhanced EMT during skin cancer formation and progression. In these animals, Smad4 binds to the Snai1 promoter, and additional Smad3 or Smad4 knockdown abrogates Snai1 overexpression [TGFβ was the first factor reported to stimulate promoter . H-Ras tpromoter . The roltivation ; howeverpression .Snai1 gene expression concomitant to an increased binding of Smads to the proximal promoter. While HMGA2 binds to two A/T rich motifs at the −131/−92 region, Smad3 and -4, which physically interact with HMGA2, associate preferentially with the −230/−178 sequence [Snai1 promoter is required for rapid Snai1 activation upon TGFβ stimulation. Accordingly, knockdown of either c-Myc or Smad3/4 in epithelial cells eliminated Snail1 induction by TGFβ [Snai1 promoter depending on Myc and Smad4 [HMGA2 cooperates with the TGFβ/Smad pathway in the activation of sequence . Myc bin by TGFβ . The hepnd Smad4 .Snai1 gene has been studied in palatal shelves during the degradation of the midline epithelial seam. To activate expression of Snai1 in palatal explants, TGFβ3 stimulates binding of Twist1/E47 dimers to the Snai1 promoter; without E47, Twist1 represses Snai1 expression [Snai1 promoter, leading to its transcription [The mechanism regulating the expression of the pression . Finallycription .SNAI1 transcription is also controlled by TGFβ and canonical Smads. In many cases, interference with this pathway decreases SNAI1 mRNA; for instance, in A549 non-small lung cancer cells, the natural dietary flavonoid Kaempferol reverses TGFβ1-mediated SNAI1 induction by weakening Smad3 binding to the promoter. This is dependent on the selective downregulation of the AKT1-dependent phosphorylation of Smad3 at T179 [SNAI1 promoter and reduces its transcription [SNAI1 promoter prevents that of Smad3/4 [In humans,  at T179 . In HCCLcription . Liver XSNAI1 transcription and promoter activity. Initial reporter assays with truncated promoters transfected in colon and pancreas cancer cells mapped the NFκB-responsive element to a sequence (−194/−78) located immediately upstream the minimal promoter (−78/+59) [SNAI1 promoter [SNAI1 RNA and promoter activity [SNAI1 RNA through the activation of NFκB [NFκB is another potent stimulator of −78/+59) . Erythroequence −4/−78 locactivity ,20. This of NFκB  and Smad of NFκB .SNAI1 transcription is STAT3. Chromatin immunoprecipitation assays in cisplatin-resistant atypical teratoid/rhabdoid tumor cells indicated that STAT3 also binds to the SNAI1 promoter, although in a more distant region than NFκB [SNAI1 induction by TGF-β in cooperation with Ras [SNAI1 promoter; inhibition of STAT3 abrogated the hepatitis virus C core-induced Snail1 expression [SNAI1 promoter [Another well documented factor that regulates han NFκB . STAT3 wwith Ras . In hepapression . Additiopromoter .SNAI1 transcription; indeed, the minimal promoter fragment (−78/+59) is dependent on the ERK signaling pathway [SNAI1 expression in human skin and cultured human keratinocytes. Different MAPK pathways  participate in this SNAI1 regulation, AP-1 sites present in human or mouse promoters and interacting with c-Jun are especially relevant for UV irradiation-increased SNAI promoter activity [SNAI1 promoter [SNAI1 promoter activity [Factors downstream MAPK also bind and control  pathway . Ultraviactivity . Osteoblpromoter . In humaactivity .SNAI1 promoter [SNAI1 expression in FGF2-activated cells [EGR1 promoter and represses the expression of this transcriptional factor [SNAI1 promoter, limiting its own transcription [HGF also stimulates Snail1 through MAPK stimulation and through Egr1 that binds to the promoter . Egr1 ised cells . Remarkal factor , demonstcription . As disccription , such seSNAI1 transcription [SNAI1 transcription; only metastasis-associated protein 3 (MTA3), aryl hydrocarbon receptor, and CBX8 repress SNAI1 [Besides these factors, other unrelated proteins, also presented in cription ,44,45,46SNAI1 transcription is also regulated by epigenetic modifications at the promoter and enhancer regions. Initial epigenetic studies demonstrated that demethylation of the Snai1 promoter accompanies its transcription in spindle or dedifferentiated cells and is associated with an increase in acetylated histone H4 [SNAI1 promoter. For instance, in colon cancer cells, the SNAI1 promoter is regulated by phosphorylated p68 RNA helicase, which induces the dissociation of the HDAC1 from the SNAI1 promoter and activates its transcription [SNAI1 is a direct target of JMJD5 and demethylated H3K36me2 [SNAI1 promoter site [SNAI1 transcription through the enhancement of histone H3 K9 deacetylation. In one study, HOPX epigenetically suppressed SRF-dependent SNAI1 transcription by recruiting histone deacetylase activity [SNAI1 promoter together with EZH2 and SUZ12, which increased the trimethylation of H3 on K27 repressing Snai1 transcription [Snai1 promoter to induce transcription and enhance cell motility [SNAI1 promoter [SNAI1 transcription [SNAI1 gene.stone H4 . After tcription . In breaH3K36me2 . HIV enhter site . In nasoactivity . Other ecription ; SETDB1 cription ; PDHE1α,motility ; MSK1, wcription . In geneSNAI1 gene acts as an enhancer. Contacting with the constitutively packaged promoter in a poised chromatin structure, this enhancer promotes the transcription associated with the enrichment of H3K4 dimethylation and H3 acetylation, at both the enhancer and the promoter [SNAI1 transcription is also controlled by a long noncoding RNA, lncRNA-a7, which acts in cis as an enhancer [SNAI1 mRNA [Finally, a conserved 3’ region in the promoter . SNAI1 tenhancer . AccordiAI1 mRNA .SNAI1 RNA levels. The earlier miRNA shown to bind to a highly conserved 3’ untranslated region (UTR) in SNAI1 mRNA was the p53-dependent miR-34 in colon, breast and lung carcinomas. These results unveiled a link between p53, miR-34, and Snail1 in the regulation of cancer cell EMT programs [Many microRNAs (miRNAs) have been shown to negatively correlate with Snail1 levels in a variety of cellular contexts; however, only some of them directly bind and reduce programs . Preventprograms . In factprograms . These lprograms  and deteprograms .Snai1 3’ UTR [Snai1 3’UTR [SNAI1 mRNA in other cellular systems [The family of miR-30 is also involved in Snail1 repression. During differentiation of tracheal chondrocytes miR-125b and miR-30a/c keep Snail1 at low levels through their binding to the 1 3’ UTR . In murii1 3’UTR . In livei1 3’UTR . miR-30c systems ,67. Acco systems .SNAI1 [SNAI1 mRNA in other systems: miR-211-5p in renal cancer [Several experimental evidences also implicate miR-153 in controlling Snail1 and EMT. In hepatocellular carcinoma, miR-153 inhibits EMT by targeting SNAI1 . Indeed,SNAI1 . Besidesl cancer  and miR-l cancer .SNAI1 mRNA. Curiously, other transcriptional factors related to EMT  are also translationally enriched upon enforced YB-1 expression [Snail1 translation is also regulated both through cap-dependent and -independent mechanisms. Increased expression of Snail1 and a concomitant EMT is promoted by transfection of the Y-box binding protein-1 (YB-1), a protein that activates cap-independent translation of Snail1 mRNA . This ripression  and contpression ,76,77. ISnail1 translation is also regulated through eIF4E- and cap-dependent translation. For instance, TGFβ-induced phosphorylation of eIF4E contributes to Snail1 expression during EMT . AccordiSnai1 mRNA coding sequence, enhancing its presence in polysomes [Finally, Snail1 translation is also controlled by methylation of its mRNA. Methytransferase-like 3 (METTL3) modifies a GGAC motif present in the olysomes .N-terminus, called the SNAG domain with a special relevance for the binding of co-repressors; other relevant regions are the Ser-rich subdomain (SRD) (amino acids 90–120) and the nuclear-export sequence (NES) (amino acids 138–146) [Snail1 protein comprises two very well defined parts: the N-terminal or regulatory domain (amino acids 1–148) and the C-terminal or DNA-binding domain . The reg138–146)   .Snail is a short-lived protein  since it is rapidly ubiquitinated and degraded by the 26S proteasome system . Snail1 Binding of Snail1 to the F-box module is often associated with Snail1 phosphorylation, although this is not always a prerequisite. The best example of a phosphorylation-dependent interaction is the one with FBXW1, commonly known as β-TrCP1 (β-transducin-repeat containing protein) . SCF-FBXThe fact that in many cells Snail1 degradation is independent on GSK-3β suggested the participation of other E3s; accordingly, SCF-FBXL14 was identified as a potent, phosphorylation-independent Snail1 E3 ligase . FBXL14 An independent shRNA screening identified SCF-FBXL5 as a nuclear Snail1 E3 ubiquitin ligase binding to Snail1 C-terminal and targeting lysines 85, 146, and 234 . BesidesFinally, another E3 ligase acting on Snail1 is FBXO45 (F-box/SPRY domain–containing protein 1). Besides Snail1, this enzyme targets Snail2, Zeb1/2, and Twist1 . In contIt is remarkable that most FBX proteins controlling Snail1 stability are regulated by miRNAs: miR-17/20a controls FBXL14 , miR-27aAs stated before, Snail1 degradation is intimately related with its phosphorylation status . For thiC-terminal domain , which play a decisive role in substrate stabilization . Snail1 Snail1 transcriptional action requires its accumulation in the nucleus, which seems to be the consequence of inhibited export. Besides being required for function, retention in the nucleus also indirectly controls Snail1 stability, since the most active Snail1 ligases (βTrCP1 and Fbxl14) are located in the cytosol . NuclearSnail1 nuclear retention is triggered by GSK-3β inhibition. This is accomplished after Wnt stimulation that promotes the Axin2/GSK-3β nuclear export; therefore, phosphorylation-induced Snail1 traffic to the cytosol is blocked . Akt phoBesides interacting with proteins involved in its stability or subcellular localization, Snail1 binds to other factors required for its transcriptional function. Although initially described as a repressor, several reports have determined that Snail1 also actively participates on gene transcription through its binding to mesenchymal promoters ,146. ThiThe capability of Snail1 to inhibit gene transcription requires its interaction with specific E-boxes presenting a core sequence of 5’-CACCTG-3’ . This binding is mediated by the C-terminal Snail1 domain containing four zinc-fingers. Interestingly, the presence of a Smad-binding element closer to the E-box (about 100 bp) enhances Snail1 repression since Snail1 interacts with the Smad3/Smad4 complex . This caN-terminal end. For instance, Snail1 associates with the histone deacetylase (HDAC) complex Sin3a/HDAC1/HDAC2; this binding is dependent on the integrity of the SNAG domain [In contrast to the Drosophila orthologue , Snail1 G domain . It is uG domain ,153,154.G domain . Snail1 G domain   are also necessary for Snail1-dependent E-cadherin repression . PRC2 biAnother co-repressor binding to the Snail1 SNAG sequence is G9a, which forms part of the G9a histone methyltransferase/DNA methyltransferases complex . This coSnail1 SNAG domain also binds to Lysyl oxidase-like 2 (LOXL2) . AlthougCDH1 (E-cadherin), is followed by the later interaction with mesenchymal genes, such as FN1 (fibronectin), concomitant with the transcriptional activation of these genes [Although Snail1 has been extensively studied as a transcriptional repressor, increasing evidence indicates that it also directly activates transcription. Binding of Snail1 to activated promoters of several genes has been reported ,170,171.se genes . Whereasse genes . Snail1 se genes . In bothse genes . Recentlse genes . Accordise genes . At presSNAI1 mRNA by activating miR-34 [As previously indicated see , Snail1 g miR-34 . Snail1 g miR-34 ; as a cog miR-34 . Other ag miR-34 . Howeverg miR-34 . It is ug miR-34  or the mg miR-34 , is contSnail1 also binds to Akt2 , a proteCDH1 and an inducer of EMT and invasion in tumor cells [Since Snail1 was characterized in 2000 as a transcriptional repressor of or cells ,182, it


E. coli from exponential phase to stationary, the genome expression pattern is altered markedly. For this alteration, the transcription apparatus is altered by binding of anti-sigma factor Rsd to the RpoD sigma factor for sigma factor replacement, while the translation machinery is modulated by binding of RMF to 70S ribosome to form inactive ribosome dimer. Using the PS-TF screening system, a number of TFs were found to bind to both the rsd and rmf promoters, of which the regulatory roles of 5 representative TFs  were analyzed in detail. The results altogether indicated the involvement of a common set of TFs, each sensing a specific environmental condition, in coordinated hibernation of the transcriptional and translational apparatus for adaptation and survival under stress conditions.During the growth transition of  Escherichia coli K-12 growth from exponential phase to stationary, marked alteration takes place in the pattern of overall genome expression through modulation of both parts of the transcriptional and translational apparatus. In transcription, the sigma subunit with promoter recognition properties is replaced from the growth-related factor RpoD by the stationary-phase-specific factor RpoS. The unused RpoD is stored by binding with the anti-sigma factor Rsd. In translation, the functional 70S ribosome is converted to inactive 100S dimers through binding with the ribosome modulation factor (RMF). Up to the present time, the regulatory mechanisms of expression of these two critical proteins, Rsd and RMF, have remained totally unsolved. In this study, attempts were made to identify the whole set of transcription factors involved in transcription regulation of the rsd and rmf genes using the newly developed promoter-specific transcription factor (PS-TF) screening system. In the first screening, 74 candidate TFs with binding activity to both of the rsd and rmf promoters were selected from a total of 194 purified TFs. After 6 cycles of screening, we selected 5 stress response TFs, ArcA, McbR, RcdA, SdiA, and SlyA, for detailed analysis in vitro and in vivo of their regulatory roles. Results indicated that both rsd and rmf promoters are repressed by ArcA and activated by McbR, RcdA, SdiA, and SlyA. We propose the involvement of a number of TFs in simultaneous and coordinated regulation of the transcriptional and translational apparatus. By using genomic SELEX (gSELEX) screening, each of the five TFs was found to regulate not only the rsd and rmf genes but also a variety of genes for growth and survival.In the process of IMPORTANCE During the growth transition of E. coli from exponential phase to stationary, the genome expression pattern is altered markedly. For this alteration, the transcription apparatus is altered by binding of anti-sigma factor Rsd to the RpoD sigma factor for sigma factor replacement, while the translation machinery is modulated by binding of RMF to 70S ribosome to form inactive ribosome dimer. Using the PS-TF screening system, a number of TFs were found to bind to both the rsd and rmf promoters, of which the regulatory roles of 5 representative TFs  were analyzed in detail. The results altogether indicated the involvement of a common set of TFs, each sensing a specific environmental condition, in coordinated hibernation of the transcriptional and translational apparatus for adaptation and survival under stress conditions. Escherichia coli K-12 strain contains as many as 70,000 ribosomes per cell, while at lower growth rates, this number is reduced to less than 20,000 , 55 amino acid residues in length ppGpp    and by tosphate) . The sigosphate) –26. ppGpsphate) – or RNAP-sphate) – and modusphate) –. On the sphate) –. Based oondition . Since tE. coli K-12, we developed two in vitro systems: the “genomic SELEX” (currently designated gSELEX) system for searching of regulatory target promoters by a test sigma factor or TF and the promoter-specific transcription factor (PS-TF) screening system for searching of TFs involved in regulation of a test promoter. By using the gSELEX screening in vitro, we have identified the whole set of regulatory targets for RNAP sigma factors (www.shigen.nig.ac.jp/ecoli/tec/]). In parallel with the gSELEX screening, we developed the PS-TF screening system for searching of TFs involved in regulation of one specific promoter , McbR (MqsR-controlled colonic acid and biofilm regulator), RcdA (regulator of csgD), SdiA (suppressor of cell division inhibitor), and SlyA . Regulatory functions have been analyzed in detail for these TFs.For quick shortcut screening of regulatory proteins for each promoter in  factors , 34 and promoter . The sucund RNAP , 37. Herrsd and rmf promoters, we employed in this study the PS-TF screening system in vitro . Within the 300-bp-long rsd probe, two RpoD-dependent transcription start sites exist at −146 and −51 bp upstream, respectively, of the translation initiation site  was mixed with 20 pmol each of the purified TFs, and after incubation for 20 min at 37°C, the mixtures were directly subjected to the mixed PAGE. For identification of the whole set of TFs involved in regulation of the in vitro , using r10.1128/mSystems.00057-18.2TABLE S1E. coli K-12 is described in reference www.shigen.nig.ac.jp/ecoli/tec/). Download TABLE S1, PDF file, 0.1 MB.TFs used for PS-TF screening. (A) Characterized TFs. (B) Uncharacterized TFs. Note that the list of uncharacterized TFs in part B was prepared 4 years ago when we started this project, but the regulatory functions have since been identified for 14 TFs. Since the numbering of TFs used in PS-TF screening, as shown in Copyright © 2018 Yoshida et al.2018Yoshida et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mSystems.00057-18.1FIG S1FIG S1, PDF file, 0.02 MB.Sequences of the probes used for PS-TF screening. Download Copyright © 2018 Yoshida et al.2018Yoshida et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the rsd and rmf probes, although the binding affinities appeared different between these TFs  were estimated to bind only to the rmf promoter, while 2 TFs (DsdC and PaaX) were bound only to the rsd promoter  signals for cell-cell communication are recognized by SdiA and McbR. SdiA senses a set of homoserine lactone (HSL) AI-1 (autoinducer-1) signals GTTAATTA(AT)-3′  -3′ , exists ing site .rmf promoter for these five TFs, using a total of 8 smaller segments of the rmf promoter , but the growth rate of the arcA mutant was less than 30% of that of the wild type, suggesting the requirement of ArcA for normal growth. After a 24-h culture, the level of cell growth was less than 75% for all these mutants, and the growth retardation was maximum (less than 50% of the wild-type level) for the mutant lacking arcA. These findings indicate the involvement of all five TFs for normal growth of E. coli K-12 W3110. In particular, ArcA was needed for growth even during exponential growth.In order to examine possible roles of five selected TFs on the expression of retarded . The grorsd and rmf genes by using quantitative real-time PCR (qRT-PCR). In wild-type E. coli, the level of rsd mRNA increased transiently during the growth transition from exponential to stationary phase  was significantly lower than that of the wild type , implying that overexpression of SlyA interferes with normal growth of E. coli K-12. In contrast, the growth rates of TF-expressing cells were essentially the same between the other four TFs  at about half the level of the wild type, but after the late log phase, the growth of cells overexpressing mcbR and arcA suddenly stopped, and afterward the cells showed a gradual decrease in cell density (mcbR and arcA), indicating the requirement of McbR and ArcA for survival upon entry into the stationary phase.To confirm the involvement of the five stress response TFs in transcription regulation of the  manners . One unee parent ; slyA, irsd and rmf mRNA by qRT-PCR. In the wild-type E. coli, the level of rsd mRNA stays rather constant throughout growth transition  were overexpressed . The level of Rsd protein stayed unaltered in the presence and absence of repressor ArcA (arcA lane). Comparing the levels of mRNA   and C bu of mRNA  and prot of mRNA , a consirsd mRNA in the arcA and slyA mutants. The level of RpoD-associated Rsd was then measured after affinity purification of His-tagged RpoD-Rsd complexes. The amount of RpoD-bound Rsd was decreased for cells lacking the activators McbR, SdiA, RcdA, and SlyA , and cell adhesion . Since as many as 13 species of TFs are under the direct control of ArcA, a large group of stress response genes should be indirectly regulated by ArcA  and AI-2 , has been established for cell-cell communication for E. coli . Seven TFs are also under the control of SdiA  signal, AI-1  or ChIP-DNA sequencing (ChIP-Seq) analyses  the regulatory proteins are not always expressed in E. coli cells (www.shigen.nig.ac.jp/ecoli/tec/]), (iv) a set of regulatory proteins involved in regulation of a single and the same promoter compete with each other for binding to the overlapping DNA sites  gSELEX screening of regulatory target promoters, genes, and operons by a specific regulatory protein  soli cells , (iii) sNA sites , 42, andpression , 70. To  protein , 59 and 12 W3110 . The gSEX system , 58.in vitro of regulatory target promoters, genes, and operons, we developed PS-TF screening in vitro of TFs involved in regulation of specific promoters. Even though the laborious work of TF purification is needed for application of this experimental system, the TF collection, once established, could be used for identification of the whole set of TFs for any promoter on the E. coli genome. Using the PS-TF screening system, we have already identified as many as 15 TFs for the promoter of the sdiA gene encoding the key regulator of cell division and cell-cell communication  after 6 cycles of screening for experimental confirmation of their participation in regulation in vitro and in vivo of the rsd and rmf promoters. Taken together with the gSELEX screening of the whole set of regulatory targets by these 5 TFs, we propose a model, shown in E. coli K-12 from exponential growth to the stationary phase, a number of TFs, each sensing different environmental factors or conditions, participate in the coordinated and simultaneous regulation of the synthesis of Rsd and RMF, both of which are involved in the conversion of key components of the gene expression into inactive storage forms for hibernation.In this study, we performed a systematic application of the PS-TF screening, for the first time, for identification of TFs involved in regulation of the rsd and rmf genes, we identified 11 TFs that bind only the rmf probe and at least 2 TFs that bind only to the rsd probe. The regulatory modes of these TFs specific for the synthesis of only Rsd or RMF await further studies.In addition to a set of TFs for coordinated regulation of the Upon entry into the stationary phase, the pattern of genome expression changes markedly through two modes of control of the gene expression apparatus: (i) the decreased level of both parts of the transcriptional and translational apparatus and (ii) the modulation of activity and specificity of the transcription and translation apparatus ppGpp, which is induced in the absence of nutrient supply. It binds to either the RpoZ omega subunit of RNAP  or RNAP-rsd and rmf genes by at least five representative TFs . ArcA, the response regulator of the ArcBA TCS, is a well-characterized global regulator that regulates a large number of genes for metabolism in response to the lack of oxygen supply -type QS signal AI-1 . RcdA was identified as a regulator of the csgD gene encoding the master regulator of biofilm formation in E. coli K-12 -type minor sigma factor FecI, which is required for transcription of the fecABCDE operon for ferric citrate transport  and SlyA 567 ΔlacZ4787(::rrnB-3) λ−rph-1 Δ(rhaD-rhaB)568 hsdR514] and its mutant strains with mcbR, rcdA, sdiA, or slyA deleted were obtained from the Keio collection . The arcA-deleted mutant strain of BW25113 was constructed by replacing the gene with a kanamycin cassette as used for construction of the Keio collection. The deletion of the arcA gene was confirmed by PCR. For TF overexpression, E. coli K-12 strain AG1 [genotype recA1 endA1 gyrA96 thi-1 hsdR17(rK−mK+) supE44 relA1] was transformed with each of the TF expression plasmids from the ASKA clone library .The genome of 0 type A  was usedllection  of the E library  that werE. coli cells were grown in Luria broth (LB) at 37°C with shaking. For analysis of ribosome profiling, cells were grown 37°C with shaking at 120 rpm in medium E containing 2% polypeptone and 0.5% glucose (600).For TF overexpression,  glucose . Cell grE. coli K-12 W3110 type A genome DNA as a template and inserted into pET21α vector. Expression of a total of more than 200 His-tagged TFs was performed in E. coli BL21. His-tagged TFs were affinity purified according to the standard procedure  was added for induction of TF expression. The cells were harvested, suspended in a lysis buffer, and disrupted by sonication. After DNase I treatment, cell lysates were incubated on ice for 3 h for digestion of genomic DNA and centrifuged to remove cell debris. After addition of NaCl and imidazole to make the final concentrations of 1 M and 20 mM, respectively, the cleared cell lysates were adsorbed onto a filter column of nickel-charged nitrilotriacetic acid (NTA) agarose resin (Qiagen). After washing the protein-bound Ni-NTA column with a washing buffer (20 mM imidazole in 50 mM K phosphate buffer containing 500 mM NaCl), the column-bound His-tagged TFs were eluted with an elution buffer (washing buffer containing 250 mM imidazole). The purity of each peak was checked by SDS-PAGE. Peak fractions containing TFs without contaminant proteins were pooled and dialyzed against the storage buffer . The purity of TFs used in this study was more than 90%, as checked by staining of SDS-PAGE gels. PS-TF screening was repeated six times using two or three different batches (see details in the text).Expression plasmids of all TFs were constructed according to the standard procedure . In brierocedure , 55, 59.rsd and rmf promoter regions indicated in E. coli K-12 W3110 DNA as the template  Regulatory targets (ArcA plus AcP). (B) Regulatory targets (McbR). (C) Regulatory targets (RcdA). (D) Regulatory targets . (E) Regulatory targets (SlyA). Download Copyright © 2018 Yoshida et al.2018Yoshida et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the rsd and rmf promoters. In brief, three DNA probes were constructed by PCR amplification. These DNA probes were mixed with each of 199 species of purified TFs, and after incubation at 37°C for 20 min were directly subjected to PAGE for detection of DNA-protein complexes under the standard conditions  screening system . This PSnditions .E. coli cells using NucleoSpin RNA Plus (Macherey-Nagel). cDNA samples were synthesized using the PrimeScript RT reagent kit . The primers used in qRT-PCR are shown in Ex Taq 2 . In each experiment, total DNA of E. coli (Affymetrix) was added to the reaction mixture. The number of PCR cycles was determined in order to obtain DNA within the linear amplification range from the amplification curve. The copy numbers of samples were obtained after quantitative amplification of the target gene. Threshold cycle (TC) values of sample DNAs were normalized to the reference TC values obtained using the known amount of E. coli DNA  was transformed into test E. coli strains. Cells were inoculated for 9 h in LB medium with 30 μg/ml of chloramphenicol and 50 μM IPTG at 37°C under aeration with constant shaking at 150 rpm. Cells were harvested by centrifugation and lysed in lysis buffer . A portion of lysed solution was kept for detection of both Rsd and His-tagged RpoD in total cell extracts. The supernatant was applied to an Ni-NTA agarose column (Qiagen). After the column was washed with 10 column volumes of the lysis buffer, the bound proteins were eluted with lysis buffer containing 200 mM imidazole. Mixtures of 20 μg total cell extracts and 2 μg each of purified Rsd and His-tagged RpoD proteins were subjected to 12% SDS-PAGE. For detection of His-tagged RpoD, the gel was stained with Coomassie blue, while for detection of Rsd, the gel was subjected to Western blot analysis  and mixed with an equal volume of glass beads . The homogenate was then centrifuged at 15,000 rpm for 10 min at 4°C. The supernatant was layered on top of a 5 to 20% linear sucrose density gradient made in the association buffer and centrifuged in an SW41 Ti rotor (Beckman) at 40,000 rpm for 1.5 h at 4°C. After centrifugation, the absorbance of the sucrose gradient was measured at 260 nm with a UV-1800 spectrophotometer . The ratio between 70S and 100S ribosomes was calculated for each peak by using Systat software for peak separation analysis .E. coli K-12 W3110 genome was prepared after sonication of purified genome DNA and cloned into multicopy plasmid pBR322. In each gSELEX screening, the DNA mixture was regenerated by PCR. For gSELEX screening, 5 pmol of the mixture of DNA fragments and 10 pmol purified His-tagged TF were mixed in a binding buffer . The sequences of DNA fragments obtained by the genomic SELEX screening were identified by a SELEX-chip method as described previously (The genomic SELEX (gSELEX) screening was carried out as previously described , 59. A meviously , 60.


Escherichia coli and most other Gram-negative bacteria, CP is produced by a single enzyme, carbamoylphosphate synthase (CPSase), encoded by the carAB operon. This particular situation poses a question of basic physiological interest: what are the metabolic controls coordinating the synthesis and distribution of this high-energy substance in view of the needs of both pathways? The study of the mechanisms has revealed unexpected moonlighting gene regulatory activities of enzymes and functional links between mechanisms as diverse as gene regulation and site-specific DNA recombination. At the level of enzyme production, various regulatory mechanisms were found to cooperate in a particularly intricate transcriptional control of a pair of tandem promoters. Transcription initiation is modulated by an interplay of several allosteric DNA-binding transcription factors using effector molecules from three different pathways , nucleoid-associated factors (NAPs), trigger enzymes (enzymes with a second unlinked gene regulatory function), DNA remodeling (bending and wrapping), UTP-dependent reiterative transcription initiation, and stringent control by the alarmone ppGpp. At the enzyme level, CPSase activity is tightly controlled by allosteric effectors originating from different pathways: an inhibitor (UMP) and two activators (ornithine and IMP) that antagonize the inhibitory effect of UMP. Furthermore, it is worth noticing that all reaction intermediates in the production of CP are extremely reactive and unstable, and protected by tunneling through a 96 Å long internal channel.In all organisms, carbamoylphosphate (CP) is a precursor common to the synthesis of arginine and pyrimidines. In  E. coli mutants by RR Roepke, as quoted in , encoded by the carAB operon   plays a dual metabolic role as it is required for both the de novo synthesis of arginine and pyrimidines Fig. . The exiin Tatum . Ten yeain Tatum . In EschE. coli CPSase is predominantly regulated at the transcriptional level as indicated by an almost perfect correlation between the levels of mRNA and enzyme activity over a large repression–derepression range  family of DNA-binding transcription factors  in the presence of excess arginine by hexameric ArgR  and pyrD  of pyrimidine biosynthesis  genes, and first discovered as a host-encoded protein involved in site-specific integration of bacteriophage lambda , a heterodimeric protein of similar subunits encoded by the carA expression , another NAP, was equally proposed to be involved in regulation of E. coli UMP kinase is a homohexameric protein, whereas most other AMP, GMP and UMP kinases are small monomeric proteins that share significant sequence homology  that controls the de novo synthesis of all other pyrimidine nucleotides  (Han and Turnbough n = 1 to > 30), which are not further elongated into productive full-length mRNA molecules  and of the spacing between the − 10 promoter region and the transcription start site  (Han and Turnbough Besides and independent of the complex TF-dependent regulation of transcription initiation that is operative at rather high UTP levels (0.9–1.4 mM), P1 activity is also regulated by a reiterative transcription control mechanism when the UTP level is low (0.9–50 µM)  encoded by carA and a large carB encoded subunit of 118,000 (1073 aa residues), that catalyzes the synthesis of CP from ammonia and also carries all the effector binding sites  thus ensures sufficient CP supply for the synthesis of arginine in this condition. The antagonistic effects of UMP and IMP may contribute to a correct balance between the production of purine and pyrimidine nucleotides in the cell. All three effector molecules primarily exert their effect on CPSase activity by modifying the apparent affinity of the enzyme for Mg2+ATP by approximately one order of magnitude, hence modulating the saturation of the enzyme by its substrate 4 species depending on the presence of effector molecules  in the presence of the inhibitor UMP  but this “monomeric” form readily converts to dimeric (αβ)E. coli harbors only a single enzyme that produces all the CP for both pathways, raises the need for a complex regulation of its synthesis at both the level of enzyme synthesis and enzyme activity. Such a combination is desirable and even indispensable since regulation of enzyme synthesis and allosteric regulation of enzyme activity operate at a different time scale. Regulation of enzyme synthesis by inhibition of transcription initiation affects the first step of gene expression and hence avoids waste of energy in the production of unnecessary mRNA and protein molecules, whereas fast inhibition/activation of enzyme activity by allosteric effector molecules allows fast adaptation of CP production in function of the needs of both pathways. This is particularly important in the case of CP, a labile molecule that should not accumulate in the cell. CP decomposition would not only represent a waste of energy (two moles of ATP are required to produce one mole of CP) but also generates the highly toxic cyanate. At the transcriptional level, the dual role of CP in the E. coli metabolism is reflected in the differential control mechanisms of the tandem pair of promoters directing transcription of the carAB operon. The downstream promoter P2 is repressed by arginine-bound ArgR, whereas the upstream promoter P1 is regulated by various mechanisms and effectors from both the pyrimidine and purine biosynthetic pathways. This situation ensures that enough CP is synthesized for the arginine pathway in conditions where P1 is repressed and vice versa that enough CP is produced for de novo pyrimidine synthesis when P2 is shut down upon high arginine supply. The antagonistic effects of ornithine (activator) and UMP (inhibitor) on CPSase activity and the consumption of CP as a substrate by the two carbamoylating enzymes  involved in the synthesis of arginine and UMP further ensure this delicate balance between CP production and CP consumption in function of the cellular requirements for both pathways. Much of the reaction mechanisms and their regulation, the enzyme structure and the protection of the highly labile intermediates in the production of CP could be solved by a combination of enzymatic, biochemical, genetic and structural studies with wild-type and mutant enzymes. These studies also revealed the presence of three distantly situated active sites connected through a 96Å internal tunnel. The study of transcriptional regulation of the carAB operon has revealed a complex interplay of several allosteric DNA-binding transcription factors using effector molecules from three different pathways , nucleoid-associated factors (NAPs), and trigger enzymes. Furthermore, DNA topology changes, UTP-dependent RNAP stuttering and stringent control by the alarmone ppGpp are involved as well. In this respect, regulation of CP production is an interesting example of the combined use of different gene regulatory mechanisms and effector molecules to coordinate the synthesis of a single metabolite involved in two distinct pathways. It also illustrates the diversity, flexibility and versatility of bacterial regulatory mechanisms. However, even though numerous players have been identified in the control of carAB transcription and CPSase activity, the mechanisms are not fully elucidated and much remains to be discovered on their interplay. ‘Avis aux amateurs’.The unique position of CP as a precursor common to the biosynthesis of arginine and pyrimidines, combined with the observation that


C. elegans, sperm-inherited chromatin states transmitted to the primordial germ cells in offspring influence germline transcription and development. We show that sperm chromosomes inherited lacking the repressive histone modification H3K27me3 are maintained in that state by H3K36me3 antagonism. Inheritance of H3K27me3-lacking sperm chromosomes results in derepression in the germline of somatic genes, especially neuronal genes, predominantly from sperm-inherited alleles. This results in germ cells primed for losing their germ cell identity and adopting a neuronal fate. These data demonstrate that histone modifications are one mechanism through which epigenetic information from a father can shape offspring gene expression and development.Paternal epigenetic inheritance is gaining attention for its growing medical relevance. However, the form in which paternal epigenetic information is transmitted to offspring and how it influences offspring development remain poorly understood. Here we show that in  C. elegans, sperm-inherited chromatin states influence transcription and cell identity in the germ cells of offspring.The mechanisms of paternal epigenetic inheritance and its influence on offspring are still poorly understood. Here the authors provide evidence that in  The gametes, sperm and oocyte, are the conduits through which epigenetic information is passed from one generation to the next. Investigating epigenetic inheritance via the maternal line is complicated by the many non-epigenetic factors the oocyte provides to the embryo1. For this reason, the field of epigenetic inheritance largely focuses on transmission via sperm. DNA methylation and non-coding RNAs (ncRNAs) are epigenetic carriers that are transmitted by sperm to the embryo and that have been shown to influence gene expression in offspring4. Modified histones can also be passed, but their role in intergenerational and transgenerational epigenetic inheritance is less clear. In mammals, the sperm genome is primarily packaged with protamines and, while there is current debate about the degree to which the sperm genome retains histones, there is consensus that marked histones are found on developmentally important loci7. Despite this observation and mounting suggestive evidence10, establishing a causal role for sperm-inherited histone marks in regulating offspring transcription and development has been an ongoing challenge. We took advantage of features of C. elegans to tackle this issue.There is growing awareness that development and health are influenced by epigenetic information passed from parents to offspringC. elegans sperm retain nucleosomes and histone marking genome-wide11 and that C. elegans Polycomb Repressive Complex 2 (PRC2) maintains inherited states of H3K27me3 during embryogenesis12. In wild-type embryos H3K27me3 is enriched over genes that were silent in the parental germline14. H2K27me3 marking inherited from hermaphrodite parent worms is essential for germline development in offspring, since hermaphrodite parents lacking PRC2 generate offspring in which the primordial germ cells die during early larval development15. We thus hypothesize that transmission of chromatin states from parent germ cells via sperm and oocyte to the nascent germ cells in offspring protects germline-appropriate gene expression patterns in the developing and adult germline.We previously showed that C. elegans.In this work we investigate how chromatin states inherited from parents are maintained in offspring and whether inherited states are important for offspring transcription and development. We elucidate a mechanism through which an inherited H3K27me3(−) state is propagated from parent germ cells (sperm) to offspring germ cells. We show that inheriting a sperm genome lacking the repressive mark H3K27me3 results in derepression of many genes for somatic development, especially neuronal genes, in offspring germlines. This results in germ cells that in a sensitized genetic background lose their germ cell identity and adopt a neuronal fate. Taken together, these findings establish a cause–effect relationship between sperm-inherited histone marks and offspring transcription and development in C. elegans embryos inherit some chromosomes with and some chromosomes without H3K27me3, PRC2 maintains inherited states by (1) restoring levels of H3K27me3 on H3K27me3(+) chromosomes after DNA replication and (2) failing to de novo methylate H3K27me3(−) chromosomes12. The ability of PRC2 to restore levels of H3K27me3 after genome duplication is likely explained by the EED subunit of PRC2 (MES-6 in worms) binding to H3K27me3 and stimulating the methyltransferase activity of the EZH2 subunit (MES-2 in worms)17. How PRC2 is prevented from de novo methylating chromosomes inherited lacking H3K27me3 is less clear. One possibility is that chromosomes lacking H3K27me3 are unable to recruit and stimulate PRC2 activity. Another possibility is that these chromosomes bear an opposing mark that antagonizes PRC2 activity. Likely candidates for antagonizing PRC2 activity are histone marks associated with gene expression, hereafter referred to as active marks, and their corresponding histone modifiers19.When 20 and H3K4me2/321, respectively. We generated embryos that inherited H3K27me3(+) oocyte chromosomes and H3K27me3(−) sperm chromosomes by mating wild-type females with PRC2 mutant males , P- for paternal H3K27me3(−)). We assessed whether sperm-inherited chromosomes retained the H3K27me3(−) state or acquired H3K27me3, by tracking the status of H3K27me3 on sperm-inherited chromosomes during early embryogenesis. To facilitate analysis of sperm vs. oocyte chromosomes, we performed this analysis in a temperature-sensitive plk-1 mutant background that keeps sperm-inherited and oocyte-inherited chromosomes in separate nuclei for many divisions22  chromosomes during early embryogenesis, we monitored sperm chromosomes through rounds of cell division in embryos lacking a maternal load of MES-4 or SET-2, which generate the active marks H3K36me2/3les Fig. . To incrs22 Fig. .Fig. 1MaK27me3 M+P− plk-1 embryos, we observed that one nucleus in each cell contained all H3K27me3(+) chromosomes (oocyte-inherited) and the other nucleus contained H3K27me3(−) chromosomes (sperm-inherited). In control and SET-2-lacking embryos, this pattern persisted in all cells during the early divisions and in the P lineage (germ lineage) throughout embryogenesis . At the 1-cell stage, all K27me3 M+P− embryos examined contained sperm chromosomes lacking detectable H3K27me3 irrespective of maternal MES-4 . In the presence of maternal MES-4, this state was maintained in all embryos up to the 4-cell stage (n = 21) and in most embryos up to the 40-cell stage (n = 15/19). In the absence of maternal MES-4, all 2-cell embryos examined acquired some H3K27me3 on sperm chromosomes (n = 6). The levels of H3K27me3 on sperm and oocyte chromosomes became indistinguishable in embryos by the 4-cell stage (n = 4) and at later stages (n = 15). This gradual acquisition of H3K27me3 matches the gradual loss of H3K36me3 in the absence of maternal MES-423. Thus, MES-4 inhibits PRC2 activity, presumably through MES-4-mediated methylation of H3K36, to maintain the paternal H3K27me3(−) state. These findings show that the H3K27me3(−) state is maintained by opposing PRC2 activity with active marks and also suggest that PRC2 does not require H3K27me3 to seed its activity, as observed in mouse embryonic stem cells24.In all 2-cell cis, thus eliminating alternative epigenetic carriers that function in trans , and (3) DNA methylation, which also functions in cis, must be eliminated as a potential mediator of the observed transcriptional changes. We met the third criterion by using the model system C. elegans, which lacks canonical DNA methylation. We met the remaining criteria by comparing transcription from sperm-inherited and oocyte-inherited alleles in genetically identical  worms  genetically identical individuals display different transcriptional outcomes as a result of inheriting different chromatin states, (2) transcriptional changes must be demonstrated to occur in rms Fig.  that inhK27me3 M+P− embryos have different chromatin states on their sperm-inherited and oocyte-inherited genomes and that those states are maintained in all cells of early embryos12. As embryos develop, the gamete-inherited chromatin states are rewritten in somatic cells but maintained through the five cell divisions that generate the two primordial germ cells (PGCs) present in newly hatched larvae12  between parental strains  to compare transcription from sperm-inherited and oocyte-inherited genomes. This allowed us to determine whether transcriptional changes occurred in cis  or in trans .We showed previously that e12 Fig. . When neK27me3 M+P− compared to K27me3 M+P+ worms  in ing Fig. . These fcis with increased transcription from the sperm allele specifically . The observation that these genes are more upregulated from sperm alleles than oocyte alleles led us to hypothesize that the presence of H3K27me3 on the oocyte genome acts as a barrier against transcriptional activation of germline-inappropriate genes. H3K27me3 on the oocyte-inherited genome would not be expected to protect it from factors that would shut down expression of germline-appropriate genes. This may explain the observation that downregulated genes were downregulated from both sperm and oocyte alleles. This led us to wonder if the global pattern of misexpression resulting from altered sperm chromatin was a concerted deviation from a germline program. To explore this, we performed gene ontology analysis on upregulated and downregulated genes. We found that downregulated genes are enriched for genes involved in reproduction and that upregulated genes are enriched for genes involved in somatic development, especially neuronal development  nor do they significantly upregulate unc-119 transcript. Performing this analysis in a sensitized genetic background in which the maternal load of PRC2 was reduced by half (mes-3/+ heterozygous mother) rendered ~30% of K27me3 M+P− worms sterile (n = 267/894); <0.3% of K27me3 M+P+ worms were rendered sterile (n = 2/870). In this background, we found that the unc-119::GFP neuronal reporter was expressed in a significant percentage of sterile K27me3 M+P− adult germlines (Supplementary Table n = 1/146) and never observed in the germlines from the rare sterile K27me3 M+P+ worms. These findings indicate that deviation from a germline program in K27me3 M+P− worms is progressive and strongly suggest that loss of H3K27me3 from the sperm-inherited genome results in a failure to maintain germ cell identity rather than a failure to establish it.To test whether germlines in K27me3 M+P− germlines, we stained UNC-119::GFP(+) K27me3 M+P− germlines for UNC-64, a neuronally expressed plasma membrane protein involved in synaptic vesicle fusion25. We detected this protein in all of the germlines analyzed (n = 6) 26 and HTP-3 27. We found that PGL-1 and HTP-3 were below detection (or nearly so) in 100% (n = 27) and 28% (n = 60) of sterile K27me3 M+P− germlines analyzed, respectively, regardless of whether or not they expressed the neuronal GFP reporter  germlines, indicating that the normally syncytial germ cells had cellularized. In some cases, we observed axo-dendritic structures emanating from these bright GFP(+) cells  Fig. . To testter Fig. . Althougrns Fig. . Of noterns Fig. . Consistlls Fig. . Our finC. elegans sperm-inherited chromatin states influence germ cell identity in offspring. Because we observe reprogramming of germ cells toward neuronal cells in adult K27me3 M+P− germlines but only rarely in larval K27me3 M+P− germlines, we conclude that offspring germ cells lose rather than fail to establish their germ cell identity. These findings reveal that in worms, sperm-inherited H3K27me3 is transmitted to offspring germ cells to prevent germline-inappropriate transcription and thus protect germ cell identity.Establishment and maintenance of chromatin states are critical during development and aging. During early development, inherited chromatin states must be rewritten to enable differentiation of different lineages. During aging, established chromatin states must be maintained to preserve cell-type-specific gene expression patterns and thus protect cell identity. Defects in these processes can lead to severe developmental defects and cancer. Whether chromatin states established in the parent and transmitted to offspring via sperm or oocyte influence the establishment and/or maintenance of cell fates in those offspring is a critical question in the field. Our findings demonstrate that in vab-7 gene, which encodes a neuronal transcription factor28; vab-7 is not expressed in wild-type germlines but becomes upregulated in K27me3 M+P− germlines. Examples of the alternative scenario are genes that encode neuronal specification factors 28 that are highly expressed in both wild-type and K27me3 M+P− germlines. Regardless of the exact cascade of gene activation, our expression analysis of K27me3 M+P− germlines suggests a programmatic shift toward a neuronal program and supports the hypothesis that an upstream factor(s) is altering gene expression in a concerted manner, especially from the H3K27me3-depleted sperm genome.Altogether, our findings point to a model in which gamete-inherited patterns of H3K27me3 act as a barrier to inappropriate transcription; in germ cells, this barrier function is particularly important in suppressing transcription of factors that could drive germ cells toward alternative cell identities Fig. . In the 7, this work implicates sperm-inherited chromatin states as one mechanism through which environmentally induced changes to parental epigenomes can impact the development and health of future generations.Our findings establish a causal role for sperm-inherited histone marks influencing transcription in offspring and reveal their role in protecting cell identity. Together with observations that in mammals, sperm retain modified histones over developmentally important genesEscherichia coli OP50 and maintained at 15 °C (fem-2 and plk-1 containing strains) or 20 °C . To generate females, fem-2 strains were raised at 24 °C until L4.Worms were maintained on nematode growth medium (NGM) agar plates spotted with All strains are in the N2 background except CB4856 and SS1292.N2 wild-type isolate from Bristol, England.CB4856 wild-type isolate from Hawaii.fem-2(b245ts) III - mutation CRISPR-engineered into CB4856.SS1292 fem-2(b245ts) III.DH0245 fem-2(b245ts) III; mes-4(bn73) V. SS1229 mes-3(bn35) I/hT2-GFP ; fem-2(b245ts) III.SS1167 mes-3(bn35) I/hT2-GFP ; him-8(e1489) IV.SS1099 plk-1(or683) III; fog-1(e2121) unc-11(e47) I/hT2 [qIs48] (I:III); itIs37[pAA64: pie-1p::mCHERRY::his-58+unc-119(+)].OCF65 mes-3(bn35) I/hT2-GFP; edIs6[unc-119::GFP+rol-6(su1006)] IV.SS1424 set-2(bn129) fem-2(b245ts) III.SS1298 Specimens were flattened between a slide and a coverslip by wicking away buffer (see below). Slides were frozen in liquid nitrogen, coverslips were removed, then slides were fixed in methanol (10 min) and acetone (10 min) and allowed to air dry for up to 3 days. Slides were blocked  for 25 min, then incubated with primary antibodies overnight at 4 °C. Slides were washed 3× in PBST , blocked for 5 min, incubated with secondary antibodies and DAPI at room temperature for 2 h, and washed 3× in PBST. Coverslips were mounted on slides with gelutol. Slides were allowed to dry for up to 3 days before being imaged.22, 1:50,000 rabbit anti-PGL-1 serum23, 1:500 guinea pig anti-HTP-3 serum24. Secondary antibodies conjugated to Alexa Fluor: 488 goat anti-mouse (Life cat#A11001), 488 goat anti-rabbit (Molecular Probes cat#A-11008), 594 goat anti-rabbit (Life cat#A11012), and 594 goat anti-guinea pig (Molecular Probes cat#A11076) were used at 1:300 with 0.05 μg/mL 4′,6-diamidino-2-phenylindole (DAPI).Primary antibodies and their dilutions were as follows: 1:30,000 of 2.45 mg/mL mouse anti-H3K27me3 , 1:3000 original stock solution of rabbit anti-H3K27me3 , 1:4000 of 0.4 mg/mL mouse anti-GFP (Roche cat#11 814 460 001 lot#14158300), 1:4000 rabbit anti-UNC-64 serumAll images were acquired using the following: Yokogawa CSUX-1 spinning disk scanner, Nikon  TE2000-E inverted stand, Hamamatsu ImageEM X2 camera, solid state 405, 488, and 561 nm laser lines, 435–485, 500–550, and 573–613 fluorescent filters, Nikon Plan Apo VC 60×/1.40 oil objective, Nikon Plan Apo 100×/1.40 oil objective, and Micro-Manager software.plk-1; fog-1 unc-11 females  or set-2 fem-2(ts) females  or mes-3 M-Z-; him-8 (P−) males  on plates with mes-4 RNAi, empty vector RNAi, or OP50  with 1 mM levamisole on polylysine-coated slides. Embryos attached to slides were fixed and stained as described above. Stacks of optical sections were acquired on a Solamere spinning disk confocal system as described above. Stacks were collapsed into maximum intensity projections using Micro-Manager. Single-channel and merge images were generated in Photoshop. To assess the appearance of H3K27me3 on sperm chromosomes in embryos with and without a maternal load of MES-4, optical sections of K27me3 M+P- embryos from fem-2(ts) mothers  or from fem-2(ts); mes-4(bn73) mothers  were stained for DNA and H3K27me3 and scored for: 1) undetectable H3K27me3 on some chromosomes, 2) reduced levels of H3K27me3 on some chromosomes relative to other chromosomes, or 3) indistinguishable levels of H3K27me3 on all chromosomes.les Fig.  or fem-2fem-2(ts) females were mated to N2 (P+) or mes-3 M-Z-; him-8 (P−) males for ~48 h. Gravid females were transferred to 100 µL S Basal , H20 to 1 L) on gelatin chrom alum-coated slides and incubated overnight in a humid chamber at 20 °C. Starved K27me3 M+P− and K27me3 M+P+ L1s were transferred to polylysine-coated slides. L1s attached to slides were fixed and stained as described above. Stacks of optical sections were acquired on a Solamere spinning disk confocal system as described above. Stacks were collapsed into maximum intensity projections using Micro-Manager. Single-channel and merge images were generated in Photoshop.mes-3/hT2-GFP; fem-2(ts) females were mated to either mes-3/hT2-GFP; unc-119 (P+) or mes-3 M+Z−; unc-119 (P−) males to generate K27me3 M+P+ and K27me3 M+P− worms, respectively. 146 L4 K27me3 M+P− larvae were cut at the pharynx to extrude their anterior germline for assessment of UNC-119::GFP expression in germ cells. Sterile adults on day 1 of adulthood (n = 267) were moved to new plates for live analysis to determine whether germ cells expressed UNC-119::GFP. Sterile day 1 adults that lacked germline expression of UNC-119::GFP were allowed to age at 20 °C for a repeat analysis of UNC-119::GFP expression in germ cells on day 2 of adulthood. L4s, day 1 sterile adults, and day 2 sterile adults were analyzed for germ cell expression of UNC-119::GFP on a Leica MZ16F microscope equipped with a GFP filter. Germlines were imaged for GFP expression both by live imaging of whole worms and by fixing dissected germlines in egg buffer with 1 mM levamisole and 0.5% tween on polylysine-coated slides and immunostaining for GFP, UNC-64, PGL-1, and/or HTP-3. Stacks of optical sections were acquired on a Solamere spinning disk confocal system controlled by Micro-Manager software as described above. Stacks were collapsed into maximum intensity projections using Micro-Manager and stitched together into composite images using Photoshop. Single-channel and merge images were generated in Photoshop. In some cases  females were mated to mes-3/hT2-GFP; fem-2 (P+) or mes-3 M+Z−; fem-2 (P−) males at 15 °C. mes-3/+; fem-2 K27me3 M+P+ and M+P− L4s  were cloned to individual plates and allowed to lay eggs for ~24 h, then transferred to fresh plates each day until no more embryos were laid. Embryos from K27me3 M+P+ and M+P− hermaphrodites were incubated at 15 °C until day 1 adulthood, then hermaphrodites were scored as sterile (no embryos in the uterus) or fertile .fem-2 (CB4856 (hybrid) or N2 (non-hybrid) background) hermaphrodites were mated to either mes-3/hT2-GFP; him-8 (P+) or mes-3 M-Z-; him-8 males (P−) to generate genetically identical mes-3/+; fem-2/+; him-8/+ K27me3 M+P+ and M+P− offspring, respectively. In addition, feminized fem-2 (CB4856 background) were mated to wild-type N2 males to generate “wild-type” hybrid offspring. mes-3/+; fem-2/+; him-8/+(K27me3 M+P+ and M+P−) and fem-2/+ (“wild-type” hybrid) L4 offspring were picked and allowed to age overnight to generate K27me3 M+P+, K27me3 M+P−, and “wild-type” hybrid day 1 adults. ~50 germlines were dissected from day 1 adults in egg buffer with 1 mM levamisole, 0.5% tween and transferred into 300 µL of ice-cold TRIzol reagent (Life Technologies), then stored at −80 °C. Samples were subjected to 3 freeze-thaw cycles. One microliter linear polyacrylamide was added to each sample, vortexed, then transferred to Phase Lock Gel-Heavy 2 mL tubes to extract the aqueous phase. 0.75 volume isopropanol was added to each sample and incubated overnight at −20 °C. RNA was isolated via ethanol precipitation and rehydrated in 14.5 µL RNase-free H2O. 2.5 µL were used to assess RNA quality  and concentration (Qubit Quant-IT RNA Assay Kit). The remaining 12 µL were depleted of rRNA (NEBNext rRNA Depletion Kit) and used for library preparation (NEBNext Ultra RNA Library Prep Kit). Libraries were sequenced on an Illumina HiSeq4000 to acquire paired-end 100 bp reads. Four biological replicates each were generated for K27me3 M+P−, K27me3 M+P+, and “wild-type” hybrid samples.Feminized 29. Only reads with one unique mapping were allowed. Otherwise default options were used. Reads mapping to ribosomal RNAs were removed from further analysis. HTSeq30 was used to obtain read counts per transcript. DESeq231 was used to determine differentially expressed genes from HTSeq counts. A Benjamini–Hochberg multiple hypothesis corrected p-value cutoff of 0.1 was used as a significance cutoff to identify significantly differentially expressed genes between K27me3 M+P− and M+P+ germlines.For differential expression analysis, raw sequences were mapped to transcriptome version WS220 using TopHat2To identify RNA-sequencing (RNA-seq) reads coming from the Hawaiian or Bristol parent in the hybrid offspring germlines, the annotated single nucleotide polymorphisms (SNPs) of the Hawaiian strain CB4856 genome compared to the Bristol strain N2 WS220 genome were downloaded from WormBase. 126,615 unique SNPs were downloaded, of which 25,980 SNPs mapped to an exon in a total of 9146 coding genes, according to WormBase. Henceforth, we refer to these SNPs as exonic SNPs.K27me3 M+P− and M+P+ replicate experiments. A further quality control step was imposed. For the Bristol and Hawaiian RNA-seq data, we calculated a distance score between the mismatch 0 and mismatch 1 read counts for each transcript. For each transcript i in the Hawaiian RNA-seq data, a score hzi was calculated: hzi = (hmm1i − hmm0i)/(hmm1i + hmm0i) where hmm1i and hmm0i denote the normalized read counts for transcript i from mapping with a mismatch 1 and with a mismatch 0 to the Bristol genome, respectively. In the same way, we defined bzi, bmm1i, and bmm0i for transcripts from mapping our Bristol RNA-seq data. For Hawaiian transcript reads from exonic SNPs, we expect hzi to be close to 1; all reads should have mapped when allowing 1 mismatch, and none should have mapped when allowing no mismatches. For Bristol transcript reads from exonic SNPs, we expect bzi to be close to 0, as the number of reads from both mappings should have been very similar. We removed transcripts that did not follow these requirements. If a transcript i had a hzi < 0.75 for the Hawaiian RNA-seq data, or an absolute value |bzi| > 0.25 for the Bristol RNA-seq data, that transcript was removed from further analysis. These requirements removed 1080 transcripts with exonic SNPs. For the remaining 8066 transcripts we obtained from the hybrid K27me3 M+P− and M+P+ RNA-seq data, we determined the transcript reads from the sperm allele (Bristol) as reads that mapped when allowing 0 mismatches. We determined the transcript reads from the oocyte allele (Hawaii) as reads that mapped when allowing 1 mismatch but that did not map when allowing 0 mismatches. We thus calculated transcript reads from the oocyte allele by subtracting reads that mapped when allowing 0 mismatches  from reads that mapped when allowing 1 mismatch .RNA-seq reads from the Bristol strain, Hawaiian strain, and hybrids were mapped to the Bristol (N2) genome version WS220 using TopHat2, once allowing 1 mismatch in a read and a second time not allowing a mismatch. Reads overlapping exonic SNP positions were identified, and HTSeq was used to count these SNP-containing reads for each transcript. Counts per transcript were normalized by the number of total transcript reads, including non-SNP-overlapping reads, for each of the libraries sequenced. An average count per transcript was obtained by averaging the replicates for each of the Bristol, Hawaiian, and hybrid K27me3 M+P− or M+P+, to be at least 0.5. Because our goal was to use SNP-containing transcript reads as a proxy for total transcript reads, we filtered out transcripts that had a greater than 2.5-fold difference between the log2 of SNP-containing reads versus the log2 of total reads for a given transcript in hybrid germlines (Hawaii mother and Bristol father). This requirement removed 190 genes and left 2,606 transcripts for further analysis. To avoid dividing by zero when calculating log fold changes and to reduce the effect of noise on low read counts, we added a pseudo-count of 0.5 to all remaining transcripts from oocyte alleles and sperm alleles in both conditions.Many genes with exonic SNPs were not expressed in any of our germline RNA-seq data. We filtered out these non-expressed transcripts from further analysis by requiring the normalized read counts from the sperm allele or oocyte allele in at least one condition, K27me3 M+P− comparison (FDR < 0.05) were used to perform GO analysis  and downregulated genes (342 genes) in the “wild-type” hybrid vs t-tests and Wilcoxon rank sum tests were performed using R. Four biological replicates of sequencing data were used. No replicates were omitted. Differential expression analysis was performed using DESeq2, which uses negative binomial generalized linear models. Adjusted p-values were calculated using the Benjamini-Hochberg method performed by DESeq2.Sample sizes and statistical tests used are described in the figure legends. Paired student’s Further information on experimental design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Adult stem cells play a critical role in tissue homeostasis and repair. Aging leads to a decline in stem cells’ regenerative capacity that contributes significantly to the maintenance of organ and tissue functions. Age-dependent genomic and epigenetic modifications together play a role in the disruption of critical cellular pathways. However, the epigenetic mechanisms responsible for the decline of adult stem cell functions remain to be well established. Here, we investigated age-dependent, genome-wide alterations in the chromatin accessibility of primary human adipose-derived stem cells (ASCs) in comparison to age-matched fibroblasts via ATAC-seq technology. Our results demonstrate that aging ASCs possess globally more stable chromatin accessibility profiles as compared to aging fibroblasts, suggesting that robust regulatory mechanisms maintain adult stem cell chromatin structure against aging. Furthermore, we observed age-dependent subtle changes in promoter nucleosome positioning in selective pathways during aging, concurrent with altered small ubiquitin-related modifier (SUMO) protein expression under stress conditions. Together, our data suggest a significant role for nucleosome positioning in sumoylation pathway regulation in stress response during adult stem cell aging. The differences described here between the chromatin structure of human ASCs and fibroblasts will further elucidate the mechanisms regulating gene expression during aging in both stem cells and differentiated cells. Additionally, exhaustion of the stem cell pool through impaired intrinsic regenerative capacity further contributes to the aging process1. Age-related genomic and epigenetic changes both influence cellular pathways during adult stem cell aging.Aging is characterized by a progressive decline in intrinsic tissue physiology and homeostasis. Adult stem cells are crucial for the regeneration of functionally differentiated cells in the maintenance of organismal homeostasis. However, stem cells are themselves subject to the aging process through the accumulation of toxic metabolites, DNA damage, epigenetic alterations, aggregation of damaged proteins, and mitochondrial dysfunction6, and their application in clinical regenerative medicine has similarly been extensively explored7. However, despite these investigations, our understanding of human ASC aging, remains to be well elucidated. We previously examined the transcriptome of ASCs and terminally differentiated fibroblasts during aging8 and demonstrated that in contrast to fibroblasts, ASCs maintain globally stable transcriptomes during aging. Several specific pathways, however, demonstrated age-dependent differential gene expression during aging in a cell-specific fashion. For example, genes involved in cell cycle control were up-regulated in aging ASCs but not in aging fibroblasts.Primary human adipose-derived stem cells (ASCs) provide a robust model system for studying stem cell aging due to their relative abundance and accessibility. ASCs have been used to study age-associated decline of differentiation and regeneration potentials, among other pathways9. In eukaryotes, the chromatin structure regulation of transcription factor binding accessibility represents a significant level of control for modulating gene expression10. Age-related alterations in the chromatin structure have been observed in both yeast and mammals11. For example, in yeast, Saccharomyces cerevisiae (S. Cerevisiae), global transcriptional up-regulation was associated with nucleosome loss during aging12. Similarly, mouse germinal vesicle stage oocytes demonstrate changes in histone methylation during aging14 and aging human CD8 T cells are characterized by changes in chromatin openness patterns15.It has been well documented that the regulation of transcription involves numerous factors and cascading pathways that lead to specific interactions of regulatory factors with DNA binding motifs in genomic control regions such as promoters16. In general, nucleosome remodeling in response to physiological perturbations, including the eviction, appearance, or repositioning of one or two nucleosomes in the promoter region, typically increases the accessibility of binding sites for transcription factors that mediate transcriptional changes17. However, nucleosome positioning is not an absolute determining factor for gene transcription activity and likewise, major shifts in gene expression are not always associated with changes in nucleosome configuration18. For example, in S. Cerevisiae, the nucleosome position permits the binding of transcription factors Rap1 and Fhl1 to ribosomal gene promoters in the absence of active transcription17. It is clear that the effect of nucleosome position on gene transcription is complex19 and that predicting transcriptional activity based on promoter nucleosome position is not always directly feasible17, as transcription activation requires other regulators. The presence of these factors could be dynamic, such as when responding to environmental stimuli. A conserved feature of aging across organisms is the induction of stress response pathways in which signaling molecules and transcription regulators direct adaptive responses to various forms of cellular damage20. However, the stress response and repair mechanisms themselves become impaired during aging, as observed in Caenorhabditis elegans (C. elegans), where aging results in decreased resistance to multiple stresses and dysfunctional stress response pathways21. Although the regulatory molecules involved in the heat shock response (HSR) are known to become impaired during aging22, the regulation of HSR in human adult stem cells and the precise molecular mechanisms governing aging in these cells remain poorly understood. Importantly, the relationship between nucleosome position and transcriptional activity during aging has yet to be studied in primary human stem cells. As such, the elucidation of this mechanism is crucial to advancing our knowledge of transcriptional regulation in primary human cells.Nucleosomes are comprised of a 146 bp DNA sequence coiled around 8 histone protein cores and represent the fundamental units of eukaryotic chromatin. Specific alterations in nucleosome positioning in promoter regions are associated with gene expression regulationFollowing our investigation of the age-dependent changes in trancriptome profiles of ASCs, we examined the epigenetic contribution of chromatin accessibility to gene expression regulation during aging of stem cells as compared to differentiated cells in this study. We employed ATAC-seq technology to investigate the genome-wide chromatin accessibility profiles of ASCs and fibroblasts in an age-dependent manner. We observed that the global chromatin structure of ASCs is more accessible than that of fibroblasts. Furthermore, the position of nucleosomes flanking TSSs is well maintained globally during aging in ASCs, but not in fibroblasts, suggesting that a robust regulatory mechanism supports a stable chromatin structure in stem cells as compared to somatic cells during aging.25. Alterations in global protein sumoylation have been observed in cultured human cells after heat shock, an acute proteotoxic stressor27. Although the difference in the promoter nucleosome position did not affect SUMO protein expression of the two cell types under non-stressed conditions, a significant change in SUMO-1 protein expression was observed in old ASCs under stress conditions, representing increased sensitivity to stress-regulated SUMO-1 protein expression in old as compared to young ASCs, an age-related change that was not observed in old fibroblasts when compared to young fibroblasts. The data presented here suggest a mechanism in which age-dependent alterations in the transcriptional activity of sumoylation factors are regulated by shifts in chromatin accessibility via nucleosome re-positioning.Despite the age-dependent differences in chromatin stability between ASCs and fibroblasts, we observed subtle differential changes in nucleosome positioning in the promoters of genes encoding SUMO proteins. Stress response pathways are regulated at multiple levels, including by sumoylation, a post-translational protein modification by small ubiquitin-related modifier (SUMO)28. We investigated the Tn5 transposase accessibility profiles of primary human ASCs isolated from 6 young and 7 old donors and compared them with those of age-matched human fibroblasts from 4 young and 4 old donors  and similarity matrix analyses Fig. , taking 8. As shown in Fig. To assess the impact of chromatin accessibility in TSS flanking regions on gene expression in adult stem cells, we compared ASC ATAC-seq signal intensity in TSS flanking regions to transcript read counts from our ASC RNA-seq data set29, a nucleosome position analysis software. Because nucleosomes flanking TSS, defined as −1 for up-stream of TSS and +1 for down-stream of TSS, have been implicated in the regulation of gene expression16, we specifically targeted these regions for the NucleoATAC analysis. We observed a distinctive difference between ASC and fibroblast young and old groups in the +1 and −1 nucleosome positions in promoter regions, indicating that aging has a differential impact on the two cell types. As shown in  among all groups Fig. . Consist31. Using this approach, we demonstrated that, in fibroblasts, members of the protein sumoylation pathway are enriched in the group with minimal changes in the −1 nucleosome position between the young and old patients , as well as after recovery from HS. We observed that after 1 h of HS at 42 °C, the SUMO-1 protein level was significantly (p < 0.05) increased in ASC-old as compared to prior to HS  increased in the fibroblast-young group after HS, an increase that was slightly reduced after the 1 h recovery period Fig. . The fibGene expression is regulated at multiple levels, including the rate of transcription, RNA processing, mRNA stability, and protein translation. We measured age-related changes in the transcript levels of SUMO-1 and SUMO-2 in ASCs in response to HS and recovery from HS. We detected a statistically significant increase of SUMO-1 transcript levels in ASCs from old, but not young, patients after a 2-hour recovery following HS Fig. . ChangesTogether, our data suggest that ASCs and fibroblasts respond differently to HS-induced stress and recovery via distinct SUMO protein level alterations in a cell-specific manner during aging. Aging ASCs demonstrate overall increased SUMO protein level expression after stress exposure, a pattern that is significant for SUMO-1. Surprisingly, in contrast, young ASCs demonstrate minimal shifts in SUMO protein levels after HS or recovery. In contradistinction, young fibroblasts demonstrate a more robust increase in global SUMO expression relative to old fibroblasts under these conditions. While both SUMO-1 and SUMO-2,3 expression are increased post HS and recovery in young and old fibroblasts, this pattern is statistically significant only for the SUMO-2,3 protein, in contrast to the significant increase in SUMO-1 after stress in old ASCs.These data are concurrent with our observed differential, cell-specific, age-related shifts in positioning of +1 and −1 nucleosomes in the promoter regions of SUMO genes and support an important role for alterations in chromatin structure as a cell- and age-specific mechanism for the functional regulation of protein sumoylation in response to cellular stress.In this study, we employed ATAC-seq to examine the chromatin accessibility profiles of human ASCs and fibroblasts in a cell-specific manner during aging. Our data demonstrates distinctive differences in Tn5 digestion patterns between the two cell types, with ASCs displaying a globally more open chromatin structure that is well maintained during aging. The distribution patterns of +1 and −1 nucleosome position further reveal a differential impact of aging on ASCs and fibroblasts. ASCs are characterized by well-maintained nucleosome positions during aging, in contrast to fibroblasts, whose nucleosome positions are altered during aging. More detailed examination of differential positioning of +1 and −1 nucleosomes, specifically in promoter region, led to identification of differential nucleosome positions in the promoters of genes involved in the protein sumoylation pathway in both cell types. To determine whether there is a regulatory link between differential nucleosome positioning and gene expression, we investigated SUMO protein expression under non-stress and stress conditions in ASCs and fibroblasts in relation to aging. As suggested by differential chromatin accessibility profiles, we observed a concurrent differential expression of SUMO proteins in an age- and cell-specific manner in response to heat shock. Together our data reveal that subtle changes in nucleosome positions during aging is correlated with differential stress response in ASCs, suggesting that nucleosome position change is a distinct mechanism regulating the stress response in human adult stem cells.16. As such, we compared the promoter chromatin accessibility profiles relative to their transcriptional activity, as examined in our prior genome-wide transcriptional profiling of ASCs and fibroblasts8. As expected, our data demonstrate that in ASCs, the genes expressed at low levels tend to have less accessible promoters. However, genes expressed at high levels have a wide variability in their promoter accessibility profiles. This is consistent with prior studies in other organisms and cells19. Thus, genes expressed at high levels are characterized by variably open chromatin in promoter regions, suggesting that differential binding of transcription factors play an important role in regulating expression of these genes.In both stem and differentiated cells, Tn5 fragmentation is highly enriched in promoter regions compared to other regions. Previous studies have associated chromatin accessibility in the promoter region with regulation of gene expression+ T cells34. Considering our observations that the nucleosome position profiles of ASCs and fibroblasts are distinctively different, and more importantly, that the promoter nucleosome profiles of ASCs are globally well maintained during aging while that of the fibroblasts are subject to wide variability during aging, our results further enforce the link between specific chromatin conformations and aging in a cell-specific manner. These results are consistent with the changes in the age-specific transcriptomes of ASCs and fibroblasts that we previously reported. Consequently, we believe that the stability of nucleosome position profiles and transcriptome activity are tightly linked in ASCs, reflecting the critical homeostatic mechanisms intrinsic to stem cells, in contrast to differentiated cells36, such fibroblasts.In prior studies, the nucleosome position flanking the TSS has been shown to influence gene expression in both yeast and human CD437. Sumoylation has been shown to regulate the function of proteins by specifically modifying their stability, protein-protein interactions, and cellular localization37. The mammalian SUMO protein family is composed of four members, SUMO-1-4, with SUMO-4 being the least understood38. SUMO-1 is ~50% homologous with SUMO-2 and SUMO-3, while SUMO-2 and SUMO-3 are 97% homologous with one another39. Although protein sumoylation by the SUMO variants affect cellular processes differently, genetic and biochemical studies show that the 3 variants may play partially redundant roles42. In vivo, SUMO-1 and SUMO-2,3 conjugate to distinct substrates and their ability to form polymeric SUMO chains differ39. SUMO-2 and SUMO-3 contain internal sumoylation sites that link SUMO molecules. SUMO-1 can be incorporated in these chains but the lack of internal consensus sumoylation sites in SUMO-1 hinders further chain elongation43. In addition, SUMO-1 prefers to be associated with the nuclear envelope and nucleolus, while SUMO-2,3 are localized mainly in the nucleoplasm44. The SUMO-4 mRNA appears to be expressed only in kidney and spleen cells45, however, in vivo expression of SUMO-4 has yet to be reported38.Although the nucleosome positioning profiles of ASCs are globally stable during aging, we successfully identified age-related changes in the nucleosome position of specific regulatory pathways including protein sumoylation, a post-translational modification. Protein sumoylation is increasingly shown to be implicated in many cellular processes, including gene expression regulation and maintenance of chromatin integrityOur investigation of SUMO1-3 in human ASCs and fibroblasts reveal that under non-stress conditions, SUMO1-3 protein expression is stable during aging under non-stress conditions. However, in response to heat shock, SUMO-1 is significantly upregulated in old ASCs, but not in old fibroblasts. Because SUMO-1 and SUMO-2,3 differ in their binding sequence and subcellular localization, their roles in cellular stress response are likely to differ. Our data point to a specific role for SUMO-1 in regulating the stress response during aging in primary human adult stem cells. SUMO-2,3 protein expression after heat shock are only significantly increased in young fibroblasts, suggesting an age-dependent dysregulation of this pathway in aged differentiated cells. Our data demonstrates that the promoter nucleosome position of SUMO genes in old fibroblasts becomes more variable as compared to young fibroblasts. In contrast, the −1 nucleosome position in old ASCs resides within a narrower range. Although the promoter nucleosome position is not the single determining factor for transcriptional activation, a permissive positioning of nucleosomes could allow transcription to proceed when necessary transcriptional factors become available. It is thus possible that the difference in nucleosome positioning in aging ASCs and fibroblasts results in differential SUMO expression under stress conditions.HSF1) function in response to stress in HeLa cells46. Further, SUMO-2,3 protein expression is required for human bone osteosarcoma epithelial cells to survive heat shock in27. In fact, at least 120 SUMO substrates involved in a diverse set of cellular processes have been identified in mammals, suggesting a broad and important role for these proteins in multiple cellular pathways37.Since adult human stem cells are critical for tissue homeostasis and regeneration, they must be equipped with robust protective mechanisms against a variety of intrinsic and extrinsic insults. We hypothesize, based on our data, that the increased sensitivity of SUMO expression in old ASCs in response to heat shock may represent a stem cell-specific protective regulatory mechanism against the accumulation of age-dependent defects arising from intrinsic or extrinsic cellular stress. In support of this hypothesis, SUMO-1 has been shown to be an important modulator of the heat shock transcription factor 1 . Informed consent was obtained from all tissue donors and all methods were performed in accordance with the relevant guidelines and regulations. Subcutaneous abdominal adipose tissues were excised from healthy donors during abdominoplasties. The tissues were immediately transferred to the laboratory. The adipose tissue was dissected from skin and stored at −70 °C in 50 mL conical tubes until ASC isolation. No cryopreservation or other agents were used in the freezing of the adipose tissue specimens. Skin specimens were processed immediately for dermal fibroblasts without storage at −70 °C.47. Isolated ASCs were cultured in Dulbecco’s Modified Eagle Medium/F12  supplemented with 100 I.U./mL penicillin and 100 (μg/mL) streptomycin (Gibco Life Technologies Co.) and 10% FBS  at 37 °C with 5% CO2. The culture media was changed every three days. All analyses were conducted with early passage ASCs (p < 4).ASCs were isolated from 13 tissue samples of females ranging in age from 25 to 75, according to a standard collagenase protocol48. The cells were cultured under 5% CO2 at 37 °C, and the culture media, same as that used for ASCs, were changed every three days. All analyses were conducted with early passage fibroblasts (p < 7).Fibroblasts were isolated from 8 females ranging in age from 25 to 64, using the method previously described49. The quality of libraries was assessed using a Bioanalyzer HS-DNA chip (Agilent). Concentrations were quantified using the KAPA Library Quantification Kit (Sigma-Alderich). Pooled, barcoded ATAC-seq libraries were sequenced on the Illumina NextSeq. 500 platform to generate 75-bp paired-end reads.Approximately 150,000 ASCs or fibroblasts isolated from each tissue specimen were used to prepare ATAC-seq libraries according to published protocols50 to remove Illumina adapters and low quality base calls on both ends (Phred < 3). Trimmed reads were mapped to the reference human genome assembly GRCh37 (hg19) using Bowtie251, allowing fragments up to 2 kb to be aligned (“-X 2000”). The alignment result was further processed by SAMtools52 to remove low quality alignments , duplicate reads, reads mapped to mitochondria, and reads mapped to ENCODE blacklisted genomic regions. All mapped reads were offset by +4 bp for the +strand and −5 bp for the -strand. The distribution of paired-end sequencing fragment sizes was assessed using Qualimap53.Sequencing reads were trimmed using Trimmomatic54 and UCSC command line utilities to generate tracks for visualization, for which purpose the visualization tracks were normalized to one million reads per sample. For each cell type, an average track was generated by merging replicate tracks using BEDtools (“unionbedg”) and using the average tag density of replicate tracks as the final tag density. MACS255 was used to identify open chromatin regions (or peaks) for each replicate, requiring peak calling FDR to be lower than 0.05 (with parameter “-q 0.05 -nomodel -shift 37 -extsize 73”). Peaks were merged for the same cell types using BEDtools. Individual peaks separated by <100 bp were stitched together. Gene target for each peak was identified as the gene with nearest TSS to the peak, using HOMER suite (“annotatePeaks -size given”)56. The HOMER annotation process also performed compartment analysis and enrichment analysis after separating the peaks into four categories: Intergenic, Intron, Promoter-TSS (−1kb to +100 bp of TSS) and Others.Genome-wide tag density was computed using BEDtools29 package with default parameters. RefSeq TSS regions (−1 kb to 1 kb around each TSS) were used as input regions of interest for NucleoATAC analysis. Position of the immediate upstream nucleosome (−1) and downstream nucleosome (+1) for each TSS were used for downstream analysis.Nucleosome positions were calculated using the NucleoATAC software16. We used 30 bp to take into the account the higher innate variability of human samples. The grouped genes were analyzed for pathway enrichment using Reactome Pathway Database57.Genes were grouped according to the change of positioning of +1 and −1 nucleosomes during aging, including <30 bases and >30 bases for either or both promoter nucleosomes. Previous studies considered the dyads of nucleosomes that differ by 10–20 as “well-localized”2. For heat shock, the cells were transferred to an incubator maintained at 42 °C with 5% CO2 and incubated for 1 h. At the end of the incubation, cells were briefly washed with PBS and proteins were extracted on plate using RIPA lysis buffer (VWR) with protease inhibitors (Roche Life Science) at 4 °C for 30 min. For heat shock recovery experiments, the cells were incubated at 37 °C under 5% CO2 for 1 h after heat shock. Cell lysates were isolated as described above. Whole cell lysate from untreated cells were processed using the same procedure. The cell lysates were cleared of debris by centrifugation at 4 °C for 15 min. Protein concentration was quantified using the BCA assay  according to the manufacturer’s instructions.ASCs and fibroblasts were seeded in 12 well plates and cultured to 80% confluence at 37 °C under 5% COet al.58. Briefly, 20 μg of cell lysates were diluted to a final volume of 200 μL with PBS (Life Technologies) and loaded onto a dot-blot device, Minifold-I 96-Well System , following the manufacturer’s instructions. The primary antibodies used were: rabbit anti-human SUMO-1 and SUMO-2,3 . The secondary antibody used was HRP conjugated anti-rabbit IgG . The blots were developed using ECL™ Western Blotting Detection Reagents . Protein dots were visualized using Amersham Imager 600 . Intensity of each dot was analyzed using Image J59.Dot blot analysis was carried out as described by Castoralova 60 and SUMO transcript levels were normalized to that of GAPDH.Total RNA was isolated using TRIzol reagent (Invitrogen) from control and HS treated ASCs of 3 young and 3 old donors and cDNA was synthesized with oligo(dT) primers from 0.5 μg of total RNA using the High-Capacity RNA-to-cDNA kit (Applied Biosystems) according to the manufacturer’s instructions. PCR amplification was carried out using SYBR™ Green PCR Master Mix (Applied Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems). Cycling conditions included pre-denaturation at 95 °C for 10 min followed by 40 cycles of denaturation at 95 °C for 15 s and extension at 60 °C for 1 min. All primers are listed in Supplemental Table 62 were performed using Excel 2016. In all tests, values of P < 0.05 were considered statistically significant.For data analyses, two-tailed Student’s t-tests and Kolmogorov-Smirnov testhttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE105077).The datasets supporting the conclusions of this article are available in the standard public repository GEO (the Gene Expression Omnibus, Supplemental Information