Ppp2r1a, encoding the Aα subunit of PP2A. We performed transcriptome and phosphoproteome analysis in mouse livers at the age of 3 months and identified 2695 differentially expressed genes and 549 upregulated phosphoproteins in homozygous knockout mouse livers compared with WT littermates. In particular, the expression of metabolic enzymes Cyp2e1, Cyp1a1, Cyp1a2, Mdr1a, and Abcg2 was dramatically altered in homozygous knockout mouse livers. We also demonstrated that activation of PP2A reversed the decline of metabolic enzyme expression in primary mouse hepatocytes. We found that specific PP2A holoenzymes were involved in metabolic enzyme induction through dephosphorylation of transcription factors, nuclear receptors, or the target enzymes themselves, leading to dysregulation of xenobiotic metabolism or drug-induced hepatotoxicity. Notably, we confirmed that a regulatory axis, PP2A B56α–aryl hydrocarbon receptor–Cyp1a1, was involved in benzo(a)pyrene-induced cytotoxicity through dephosphorylation of the metabolic nuclear receptor, aryl hydrocarbon receptor, at serine 36. In addition, we showed that PP2A B56δ complexes directly dephosphorylated the multidrug efflux pump MDR1 (encoded by multi-drug resistance gene 1), contributing to drug resistance against the chemotherapeutic 5-fluorouracil. Taken together, these novel findings demonstrate the involvement of PP2A in the regulation of liver metabolism.Protein phosphatase 2A (PP2A) is a serine/threonine dephosphorylating enzyme complex that plays numerous roles in biological processes, including cell growth and metabolism. However, its specific actions in many of these critical pathways are unclear. To explore mechanisms underlying metabolic enzyme regulation in the liver, we investigated the key pathways involved in regulation of xenobiotic-metabolizing enzymes in a mouse model with hepatocyte-specific deletion of  Biotransformation is essential in mediating biological effects in response to xenobiotics, environmental pollutants, or drugs, and it depends on the activity of metabolic enzymes . The metvia binding of their cognate ligands . Using this model, we identify the critical pathways regulated by specific PP2A holoenzymes in development of liver fibrosis . Pathways associated with metabolism were the most significantly affected . Next, the identified DEGs were subjected to Gene Set Enrichment Analysis, and six gene sets were significantly recognized (p < 0.05) . The functional annotation revealed that drug metabolism CYP, drug metabolism other enzymes, steroid hormone biosynthesis, metabolism of xenobiotics by CYP, and retinol metabolism were suppressed, whereas the ubiquitin-mediated proteolysis was activated. Moreover, we noted that the changes in the expression of CYP450 genes were the most pronounced . Taken together, these findings indicate a critical role of PP2A in regulating the hepatic metabolism.To address the role of PP2A in the regulation of liver metabolism, liver tissues from WT and homozygous knockout (HO) mice at the 3 months of age were collected and subjected to transcriptome analysis (n = 3). We identified 2695 differentially expressed genes (DEGs) (mapping to 3453 transcripts), of which 1242 and 1453 were upregulated and downregulated, respectively, in HO mouse with fold change ≥2 or ≤−2  appeared in liver tissues from HO mice at the age of 3 months (p < 0.05) (A). Additional analysis by Molecule Activity Predictor program showed that the pathways underlying xenobiotic metabolisms, including AHR, xenobiotic metabolism, and CAR were significantly suppressed (B–D). However, pathways implicated in drug resistance were activated (E). Collectively, these results demonstrate that PP2A is involved in the regulation of xenobiotic/drug metabolism and drug transport.To clarify the mechanism by which PP2A was involved in the regulation of liver metabolism, we performed phosphoproteome analysis by nano–reversed-phase LC–tandem mass spectrometry (MS/MS), as described previously . About 53 months . Particu3 months . Next, w < 0.05) . Of the  < 0.05) A. Additippressed , B–D. Hoctivated E. CollecA, we identified 120 metabolic DEGs, with 59 upregulated and 61 downregulated (B). In addition, perturbation in the following five toxicity pathways, liver necrosis/cell death, PXR/RXR activation, NRF2-mediated oxidative stress, hepatic cholestasis, and molecular mechanism of cancer were predicted from DEGs of phase III enzymes (B). These results suggest that PP2A is involved in regulation of the cellular responses and liver injuries, at least in part, through the modulation of metabolic enzymes.To profile the metabolic enzymes affected by deletion of PP2A Aα subunit, we analyzed the altered metabolic enzyme genes in HO mouse liver. As shown in Figure 3egulated . Of thesegulated B. In add enzymes B. These C, the mRNA levels of nine or 28 metabolic DEGs were significantly increased  or decreased , respectively in HO mouse livers compared with those in WT littermates, 73.3% of which were consistent with transcriptome analysis. In general, depletion of PP2A Aα subunit in hepatocytes led to decreased expression of solute carrier subfamilies and Cyp450 subfamilies but increased expression of ABC subfamilies. Notably, we validated 60 metabolic DEGs at the protein expression level by proteomics analysis (D). The results showed that MDR1- and ABCG2-positive stainings were increased by 1.48- and 1.04-fold, respectively, in HO mice compared with that in WT mice (E).Next, we verified 45 metabolic enzymes from the transcriptome data by quantitative PCR. As shown in Figure 3analysis . In addianalysis D. The re WT mice E.A). The protein levels of CYP2E1, CYP1A1, CYP1A2, and CYP2A5 in cultured primary hepatocytes were decreased in a time-dependent manner (B). First, we treated primary mouse hepatocytes with 0, 1, and 2 μM FTY720, an agonist of PP2A, respectively. As a result, FTY720 treatment led to a significant decrease in Cyp1a1, Cyp1a2, Cyp2e1, and Cyp2a5 enzyme mRNA level in primary hepatocytes isolated from WT mice (C). This was further confirmed by enzyme activity and immunoblotting analysis (D and E). However, FTY720 treatment failed to affect the enzyme expression in hepatocytes isolated from HO mice (D), suggesting that PP2A enzyme activity is critical for maintaining liver metabolic enzymes. Taken together, these results indicate that the regulatory role of PP2A in xenobiotic/drug metabolism was distinct toward different phases of metabolic enzymes.We assessed whether PP2A activation affected the expression of metabolic enzymes. Primary hepatocytes from WT mouse were isolated and cultured for 4, 24, and 48 h, respectively A. The prt manner B. First, WT mice C. This wanalysis , D and E HO mice D, suggesA and Fig. S3B). In addition, 5-fluorouracil, cisplatin, or paclitaxel treatment had no effect on mRNA expression of Mdr1a, Abcc3, or Abcg2  but led to an increase at the protein level . Notably, the induction of transporter protein (phase III enzymes) in HO mouse livers was more profound. Taken together, these observations suggest that PP2A might play a critical role in determining chemical-induced hepatotoxicity through both transcriptional and PTMs of metabolic enzymes.Xenobiotic-induced toxicity depends predominantly on biotransformation, which is mediated by metabolic enzymes. Next, we investigated the effect of PP2A inactivation on the induction of metabolic enzymes and hepatotoxicity induced by various chemicals or drugs. Primary hepatocytes isolated from WT or HO mice were subjected to treatment with 15 different chemicals or drugs, respectively. As a result, the treatment of benzo(a)pyrene (BaP), 3-methylcholane, pyrazole, ethanol, acetaminophen, adriamycin (ADR), methotrexate, or 5-fluorouracil led to a decreased cell viability in a dose-dependent manner but greatly attenuated in hepatocytes from HO mice  (A). Since B55α, B56α, B56ε, and B56δ subunits were dramatically decreased in HO mouse liver (A) and examined the induction of 20 metabolic enzymes in cells upon the suppression of specific B subunit in response to treatment of various chemicals or drugs (B). Furthermore, the suppression of Aα or B55α subunit resulted in a decline in the induction of metabolic enzymes, including Cyp1a1, Cyp2b6, Cyp2c8, Cyp2c9, Cyp2c18, Cyp2c19, Cyp3a7, and Cyp4a11. In addition, the mRNA level of five transport proteins remained unchanged when HepaRG cells were treated with various chemicals or drugs. The family subtypes of CYP in human and mouse are shown in 10 was used as a threshold for determining toxicity in response to xenobiotic treatments . In parallel, B56δ suppression led to a dramatic decrease in mitochondrial damage induced by 5-fluorouracil . Collectively, these results suggest that dysregulation of metabolic enzymes because of the lack of specific PP2A holoenzymes confers cells with sensitivity to xenobiotic-induced hepatotoxicity.Next, we addressed which specific PP2A complex was responsible for the modifications of metabolic enzymes. Given the abundance and stability of CYP in HepaRG cells , we firs < 0.05) A. Since se liver , we specse liver A and exaor drugs . Notablyor drugs B. Furtheeatments . We founeatments . MoreoveA and http://phospho.elm.eu.org) . Importantly, these 44 transcriptional regulators have been previously reported to be regulated by PP2A . IPA predicted that the remaining 12 transcriptional regulators might potentially be the regulatory targets of PP2A . These results suggest that PP2A might regulate the expression of metabolic enzymes via dephosphorylation of transcription factors. Subsequent phosphoproteome analysis showed the enhanced phosphorylation of 53 metabolic enzymes upon the deletion of PP2A Aα subunit . In addition, 30.2% of these enzymes displayed changes in phosphorylation status coupling with altered protein levels, suggesting that the dephosphorylation of these transcription factors might be a critical mode of action for the modulation of metabolic enzymes. Furthermore, IPA predicted that PP2A B55α, B56α, B56δ, or B56ε holoenzyme might be involved in the regulation of various metabolic enzymes  software . As a result, 456 upstream factors were identified to be involved in regulating these metabolic DEGs. Of these upstream factors, 24% was classified as transcriptional regulators and nuclear receptors . Correspondingly, the p-AHR at serine 36 was decreased by 64.2% in HepaRG-SHGFP cells treated with BaP. In contrast, we observed an enhanced p-AHR at serine 6 and a decreased induction of Cyp1a1 in HepaRG-SHB56α and HepaRG-SHAα cells upon BaP treatment (B), indicating that PP2A might be responsible for dephosphorylation of p-AHR. Coimmunoprecipitation (co-IP) assay confirmed the interaction between Cα subunit and AHR (C) and between B56α subunit and AHR in HepaRG cells (D). In agreement with these observations, cell viability was decreased by 29.8% in HepaRG-SHGFP cells treated with 20 μM BaP. However, this effect was attenuated by 72.5% and 77.2%, respectively, in HepaRG-SHB56α and HepaRG-SHAα cells (E and F), indicating the involvement of PP2A B56α complexes in regulating BaP-induced cytotoxicity. Similar results were found with other toxicity end points, including apoptosis, MMP, and ROS generation. In particular, the effects of PP2A B56α suppression in attenuating mitochondrial damage were the most profound. These results confirmed that the regulatory axis of PP2A B56α–AHR–Cyp1a1 was implicated in mediating BaP-induced cytotoxicity. Taken together, PP2A plays an important role in regulation of the transcriptional activation of metabolic enzymes through dephosphorylation of the key transcription factors, demonstrating a key mode of action in metabolism in response to environmental stresses.As described previously, the change of Cyp1a1 expression affected by PP2A activation was the most profound. To validate the reliability of regulatory mode, we performed functional assays and analysis of protein interactions in representative regulatory axes. First, we assumed a possible regulatory axis of specific PP2A complex–phosphorylated AHR (p-AHR)–Cyp1a1. To test this hypothesis, we treated HepaRG cells expressing shRNAs targeting distinct PP2A subunit with 20 μM BaP, an agonist of AHR signal pathway. In agreement with the results from primary mouse hepatocytes, Cyp1a1 induction declined by 68.5% and 71.7%, respectively, in HepaRG-SHAα or HepaRG-SHB56α cells following BaP treatment A. Corresreatment B, indica and AHR C and betRG cells D. In agrAα cells , E and FA), whereas the mRNA levels remained unchanged. In contrast, we hardly detected the phosphorylation of MDR1 in hepatocytes isolated from WT mice. Importantly, the co-IP assay revealed that MDR1 was in complex with PP2A Cα subunit (B), indicating that PP2A was directly involved in regulation of MDR1. In agreement to these observations, the functional assay revealed that the content of rhodamine 123 (Rh123) accumulated in hepatocytes was four-fold higher in WT mice than HO mice (C), indicating that phosphorylation of MDR1 led to a faster efflux attributable to enhanced transporter activity of MDR1. In particular, activation of PP2A resulted in increased Rh123 accumulation in human hepatocarcinoma cells resistance to ADR (HepG2/ADR cells) (D). Collectively, these results demonstrate that PP2A is involved in regulation of MDR1 activity by direct dephosphorylation, conferring cells with drug resistance.Since PP2A was predicted to regulate the expressions of metabolic enzymes by dephosphorylation of transporter proteins, next, we examined the phosphorylation status of MDR1 in cells expressing shAα (HepaRG-SHAα cells). As a result, 5-fluorouracil treatment led to an enhanced phosphorylation level of MDR1 in HepaRG-SHAα cells A, wherea subunit B, indica HO mice C, indicaR cells) D. CollecE). Next, we generated stable HepG2/ADR cells overexpressing B56δ or B56α subunit (with FLAG tagged). Immunofluorescence analysis showed that B56δ overexpression led to a downregulation of phosphorylated MDR1 and the increased protein levels (F). In contrast, we failed to observe these effects in cells overexpressing B56α subunit. Although MDR1 expression was hardly detected in HepG2 cells, the suppression of B56δ remarkably upregulated the MDR1 protein as determined by both immunofluorescence and immunoblotting analyses (A and B), implicating a role of B56δ subunit in modulating MDR1 expression. Importantly, co-IP assay confirmed the interaction between B56δ subunit and MDR1 (G), indicating that PP2A-B56δ holoenzyme might be responsible for MDR1 dephosphorylation.Next, we determined which PP2A complex participated in the regulation of MDR1. Immunoblotting analysis showed the significant increase of MDR1 protein levels in three types of ADR-resistant cell lines, including MCF-7/ADR, HepG2/ADR, and K562/ADR, compared with corresponding ADR-sensitive cells. As suppression of B56δ or B56α attenuated the cytotoxicity induced by 5-fluorouracil, we determined the expression of B56δ and B56α subunit in these ADR-resistant tumor cell lines. B56δ expression declined while no obvious change was noted in B56α expression E. Next, n levels F. In conanalyses , A and Band MDR1 G, indicaH), indicating that B56δ-containing holoenzyme takes part in the reversal of drug resistance. Correspondingly, the cytotoxicity was increased by 17.7% in HepG2/ADR-FLAG-B56δ cells compared with that in HepG2/ADR-puro cells in response to 10 μM ADR treatment (I). In contrast, we failed to observe similar effects in HepG2/ADR-FLAG-B56α cells upon ADR treatment. Collectively, these results reveal that PP2A B56δ holoenzyme was indispensable for regulating MDR1 stability and activity, demonstrating a potential role of PP2A B56δ holoenzyme in drug resistance.Previous studies have reported that phosphorylation was essential for ubiquitination-mediated degradation of MDR1. Thus, we speculated that PP2A-B56δ holoenzyme might be involved in regulation of MDR1 protein stability. To test this hypothesis, we overexpressed B56δ subunit or treated HepG2/ADR cells with verapamil, an MDR1 inhibitor, and found an increasing accumulation of Rh123 in HepG2/ADR cells H, indicareatment I. In conThe understanding of the regulatory mechanism by which xenobiotic-induced modifications of metabolic enzymes was critical for the prediction of consequent pharmacological and toxicological effects. In this study, we integrated the transcriptome and phosphoproteome analysis results  gene (HO) and matched WT mouse was generated as described previously . Ppp2r1aloxp/+ mice with genetic background of FVB.129S were purchased from the Jackson Laboratory (strain 017441), which contained loxP sites flanking exons 5 to 6 of the Ppp2r1a gene. Primary hepatocytes were isolated from WT or HO female mice at the age of 3 months by two-step collagenase perfusion  were purchased from Thermo Fisher Scientific. For induction of differentiation, HepaRG cells were incubated in Williams' E medium containing 1.7% dimethyl sulfoxide for 14 days. All animal protocols were approved by the Animal Care and Use Committee of the Model Animal Research Center of Sun Yat-sen University.Mouse model with hepatocyte-specific deletion of eviously . In detaThe shRNAs against specific PP2A subunit were generously provided by Dr William C. Hahn . Considering the abundance of metabolic enzymes in AML12 cells  and the feasibility of gene suppression on primary mouse hepatocyte, we chose HepaRG cells or HepG2/ADR cells to explore the role of specific PP2A subunits. To generate stable cell lines, the pLKO.1-puro shGFP and pLKO.1-puro vectors containing shRNA targeting Aα, B56α, B55α, B56δ, or B56ε were introduced into HepaRG cells, HepG2 cells, or HepG2/ADR cells, respectively, by lentivirus infection and selected with puromycin (1 μg/ml).www.uniprot.org, 201,705) proteome sequence databases, and the parameters were set as described previously . The expression level of gene was normalized by fragments per kilobase per million). DEGs were defined with the following screening criteria: absolute log2 (fold change) ≥1 and p < 0.05 in mouse liver tissues. The upregulated phosphoproteins  were selected with the thresholds log2 (fold change) ≥0.26.Liver tissues from female WT and HO mice (n = 3) at the 3 months of age were collected and subjected to nano reversed-phase LC–electrospray ionization–MS/MS analysis as previously described . Raw dateviously . Peptidep < 0.05. In addition, DEGs were subjected to analyses for identifications of upstream regulators, adverse effect prediction, and interaction network.The analysis of DEPPs or genes was conducted with IPA software. Ingenuity knowledge–based tool was used to identify significant canonical pathways and characterize the diseases and functions for the DEGs and DEPPs. Pathways were considered significantly enriched when p < 0.05.Gene Ontology, KEGG enrichment analyses, and Gene Set Enrichment Analysis were performed using the clusterProfiler package in R, version 4.1.0. “Mm.h.all.v7.1” and “Mm.c2.cp.kegg.v7.1” entrez.gmt were chosen as the gene set database. A gene set is a group of genes that share pathways, functions, chromosomal localization, or other features. The pathways were considered significantly enriched when 4 per well. About 24 h after seeding, the cells were treated with various chemicals for 24 h. As the subtype variability of phase II enzymes was remarkable, we mainly selected the agonists including 15 chemicals or drugs that were corresponding to the induction of phase I enzymes and the transporters (phase III enzymes). The reference dose for metabolic enzyme induction of each chemical or drug was derived from ToxCast/Tox21 of Environmental Protection Agency. The cell viability was determined by using Cell Proliferation Assay Kit (Promega).Primary hepatocytes were seeded into 96-well plates with a density of 1 × 103 per well. About 24 h after deeding, the HepaRG cells were treated with drugs or chemicals for 24 h, followed by incubation with 100 μl mixed fluorescent dye (Invitrogen) including ethidium homodimer-1 (1 μM), Image-iT TMRM (1×), and CellROX Deep Red Reagent (5 μM) for 30 min. The cultures were washed with PBS for three times and stained with Hoechst 33342 (5 μg/ml). Next, the living-cell imaging was examined under the Operetta CLS Cell Imaging System (PerkinElmer) at 63× objective. Images were analyzed by the cytotoxicity module (PerkinElmer). With these three fluorescent dyes, we were able to quantitatively examine different end points including apoptosis, MMP, and ROS, respectively.HepaRG cells were seeded on 96-well black plates with transparent bottom (PerkinElmer) at a density of 8 × 1010 was used to determine the threshold of chemical-induced biological end points, apoptosis, MMP, and ROS.The BMD modeling was employed to analyze the dose–response effects on cytotoxicity induced by xenobiotics or drugs  . In this−ΔΔCT method and normalized with β-actin gene. The primers used for qRT–PCR are listed in Total RNA was extracted with Trizol reagent (Invitrogen), and complementary DNA was synthesized from 1 μg of total RNA using PrimeScript RT Master Mix. Quantitative real-time PCR was performed by SYBR Green PCR Master Mix (Toyobo), and mRNA expression levels were measured by Applied Biosystems 7500 Real-Time PCR Systems. The relative expression level was calculated by 2g for 20 min at 4 °C. About 3 mg of supernatant was incubated with specific antibody overnight at 4 °C and followed by the addition of protein G-Sepharose beads  for 2 h at 4 °C. The protein G beads were eluted in 2× SDS sample buffer followed by SDS-PAGE and immunoblotting. For the immunoblotting analysis of phosphorylated protein, cells were lysed directly on the plate using 2× SDS loading sample buffer. Soluble proteins (30 μl) were subjected to 3 to 8% gradient acrylamide gel for SDS-polyacrylamide gel electrophoresis before immunoblotting. The primary antibodies used in this study are listed in For co-IP assay, cell pellets or fresh liver tissues were homogenized in ice-cold radioimmunoprecipitation assay lysis buffer (Beyotime) containing protease and phosphatase inhibitor (Roche Applied Science). The lysates were centrifuged at 12,000HepG2 cells or HepG2-ADR cells (human hepatocarcinoma cells resistance to ADR) were fixed with 4% paraformaldehyde for 15 min, permeabilized with 0.2% Triton X-100 for 5 min, washed with PBS–Tween, and blocked by 3% fetal bovine serum for 1 h. Next, HepaRG cells were incubated with primary antibody against MDR1 (1:500 dilution) overnight and followed by incubation with second antibody Alexa Fluor 488-conjugated goat anti-rabbit IgG (1:1000 dilution) for 1 h. Next, the slides were counterstained with 4,6-diamidino-2-phenylindole (1 μg/ml) and examined with an LSM510 META laser scanning confocal (Leica) under a magnification 200×. Quantification was performed using ImageJ software , and the results were expressed as a percent of positive staining area.5/ml and cultured overnight. About 24 h after seeding, the cells were incubated with 10 μM Rh123 for 1 h and followed by the washing with ice-cold PBS. The accumulation of Rh123 in cells was quantitatively determined by fluorescence inverted microscope with an excitation wavelength of 488 nm with 100× magnification (Leica).HepG2-ADR cells were seeded into 6-well plates at a density of 2 × 10t test (two groups) or one-way ANOVA (for more than two groups). The difference was considered statistically significant at p < 0.05.Data are shown as the mean ± SD. All statistical analyses were performed by GraphPad Prism software . Statistical differences between groups were determined by Student's All data are contained within the article. This article contains supporting information, including five supporting figures, eight supporting tables, and seven supporting information.This article contains The authors declare that they have no conflicts of interest with the contents of this article.


S. agglomeratus 5-1-3 showed that Clusters 3, 6, 12, 21, and 28 were used to synthesize NRPs. Here, we examined secondary metabolites of S. agglomeratus 5-1-3 isolated from soils in the Qinghai-Tibet Plateau, China, for NRPs with antibacterial activity.New antibiotics are urgently needed in clinical treatment of superdrug-resistant bacteria. Nonribosomal peptides (NRPs) are a major source of antibiotics because they exhibit structural diversity, and unique antibacterial mechanisms and resistance. Analysis of gene clusters of Streptomyces strains with distinct colony morphological characteristics from 7 soil samples. We screened 8 Streptomyces strains resistant to methicillin-resistant Staphylococcus aureus (MRSA). We then selected S. agglomeratus 5-1-3 for further study based on results of an antibacterial activity test. Here, we isolated three compounds from S. agglomeratus 5-1-3 and characterized their properties. The crude extract was extracted with ethyl acetate and purified with column chromatography and semipreparative high-performance liquid chromatography (HPLC). We characterized the three compounds using NMR analyses as echinomycin (1), 5,7,4ʹ-trihydroxy-3.3′,5′-trimethoxy flavone (2), and 2,6,2′, 6′-tetramethoxy-4,4-bis-biphenyl (3). We tested the antibacterial activity of pure compounds from strain 5-1-3 with the Oxford cup method. NRP echinomycin (1) showed excellent anti-MRSA activity with a minimum inhibitory concentration (MIC) of 2.0 μg/mL. Meanwhile, MIC of compound 2 and 3 was 128.0 μg/mL for both. In addition, 203 mg of echinomycin was isolated from 10 L of the crude extract broth of strain 5-1-3.We isolated a total of 36 S. agglomeratus 5-1-3 with strong resistance to MRSA was isolated from the soils in the Qinghai-Tibet Plateau. Strain 5-1-3 had a high yield of echinomycin (1) an NRP with a MIC of 2 μg/mL against MRSA. We propose that echinomycin derived from S. agglomeratus 5-1-3 may be a potent antibacterial agent for pharmaceutical use.In this study, The online version contains supplementary material available at 10.1186/s12934-023-02018-0. Staphylococcus aureus (MRSA) is one of the most common pathogenic bacteria in hospital and community infections [Staphylococcus aureus has been found in the United States [Methicillin-resistant fections , 2. MRSAfections . A localfections , 5. MRSAfections , oxacillfections , penicilfections , and thefections , 10. Vand States . TherefoLysobacter sp. RH2180-5 using the silkworm infection model. Meanwhile, teixobactin was characterized from uncultured Eleheria terrae [Streptomyces have been an important source of antibiotic discovery [Traditionally, NRAPs are characterized by chemical and mechanistic diversity, and they are an important source of discovery of novel antibiotics . Most ofa terrae . This sha terrae –16, and iscovery –19.Streptomyces belongs to the phylum Actinomycetes. There are more than 1000 species of Streptomyces that are mainly found in soil. Streptomyces are filamentous Gram-positive bacteria reproducing mainly through spore formation; they are basically harmless to the human body. Streptomyces is an important antibiotic-producing genus, and approximately 2/3 of the antibiotics used in clinical practice are derived from Streptomyces, including streptomycin, tetracycline, erythromycin, neomycin, and kanamycin [Streptomyces is vital to the development of new antibiotics.anamycin –19. ReseStreptomyces with antibacterial activity in soils in extreme environments that may provide new resources for the research and development of microbial natural products [4 km2, accounting for more than 60% of the permafrost area in China. The average annual temperature in the hinterland of the plateau is below 0 ℃, and the warmest monthly average temperature is below 10 ℃ [Streptomyces strains with distinct colony morphological characteristics were isolated from 7 soil samples collected in the Qinghai-Tibet Plateau, and then 8 Streptomyces strains resistant to MRSA were screened, and S. agglomeratus 5-1-3 was selected for further study based on results of the antibacterial activity test. Analysis of gene clusters of S. agglomeratus 5-1-3 showed that Clusters 3, 6, 12, 21, and 28 were used to synthesize NRPs. Therefore, the aim of this study was to search for NRPs with antibacterial activity among S. agglomeratus 5-1-3 secondary metabolites.Some studies have shown that there may be undiscovered species of products –25. The low 10 ℃ –28. In t− 3 gradient, 200 µL of the suspension was spread on a Gauze No. 1 solid medium supplemented with nalidixic acid and cultivated at 28 °C under aerobic conditions. The isolated strain, showing a yellow basal mycelium, a white aerial mycelium, and a powdery surface on Gauze’s No. 1 solid medium, was purified and named strain 5-1-3. The pure culture was preserved in glycerol (25%) and stored at − 80 °C before use [https://www.ncbi.nlm.nih.gov/) to identify the most similar sequences, while phylogenetic trees were constructed using MEGA 5.0 based on the 16S rRNA sequence [Strain 5-1-3 was isolated from soils in the Wuli region in the Qinghai-Tibet Plateau , China, at an elevation of 4595 m. Samples were obtained in April 2014. First, a square 5-point sampling method was used to collect soil samples to a depth of 0 to 30 cm, and then thoroughly mixed in a sterilized box. In accordance with the sampling principles for soil microbial analysis, all sampling processes and transport were kept sterile and samples were transported to the laboratory at − 20 ℃ after collection. Second, approximately 0.1 g of soil was dispersed in 0.9 mL of LB liquid medium and placed in 1.5 ml sterile centrifuge tubes. Samples were incubated at 30 °C and 100 r/min for 30 min and allowed to stand for 20 min. Then, using a tenfold gradient dilution to make a 10fore use , 30. As fore use , isolatesequence . EvolutiStreptomyces strains isolated from the Qinghai-Tibet Plateau, and an almost complete 16S rRNA gene sequence (1355 bp) was determined  analysis showed that the whole genome of 5-1-3 contained 29 secondary metabolite synthesis gene clusters, and four of these gene clusters had 100% similarity, namely, Cluster 1, Cluster 15, Cluster 27, and Cluster 29 , Staphylococcus aureus (S. aureus), and MRSA. E. coli and S. aureus were obtained from the Key Laboratory of Extreme Environmental Microbial Resources and Engineering, while MRSA was obtained from the Centre for Molecular Biology, Swansea University School of Medicine, UK. Our results showed that the diameter of the inhibition zone of the extracts of strain 5-1-3 against the above pathogenic bacteria were 25 mm  and two oxygenated methylenes ; therefore, we concluded that there were 2 serine units in this cyclic peptide. There were also six aromatic ring quaternary carbon signals , ten aromatic tertiary carbons , and two carbonyl carbons ; based on literature, we identified them as two quinoxaline-2 carboxylic acid residues. A comprehensive analysis of 1H and 13C NMR data of the compound showed that cyclopeptide compound 1 contained 2 alanines, 2 N-methylvaline, 2 serines, 2 sulfur-containing amino acids, and 2 quinoxalin-2 carboxylic acids. Based on NMR spectroscopic analyses , four aromatic tertiary carbons , one carbonyl carbon (δC 178.3), and three methoxyl carbons . Using this information, the analysis of the 1H-NMR spectrum -biphenyl [Compound biphenyl  Fig. 4)3 was isoStaphylococcus aureus has been found in the United States [Vancomycin has a certain inhibitory effect on MRSA and it is commonly used in clinical treatment of systemic infections caused by MRSA. However, with the extensive application of vancomycin in clinical practice, vancomycin-resistant d States .1–3 was tested with the Oxford cup method. Echinomycin (1) exhibited excellent anti-MRSA activity with a MIC of 2.0 μg/mL  showed excellent anti-MRSA activity with an MIC of 2.0 μg/mL. This is a very valuable antibacterial activity result, which indicates that echinomycin can be used as a lead antibacterial compound in which to study the active group to provide sources for the development of new active molecules against MRSA.MRSA showed some resistance to erythromycin, rifampicin, and vancomycin. Therefore, antibiotics commonly used in hospitals have poor bactericidal efficacy against MRSA. The antibacterial activity of compounds S. agglomeratus 5-1-3 isolated from the soils of the Wuli region in the Qinghai-Tibet Plateau and evaluated anti-MRSA activity of its secondary metabolites. AntiSMASH analysis showed that the whole genome of strain 5-1-3 contained 29 secondary metabolite synthesis gene clusters, of which 5 were related to the synthesis of NRPs. A further chemical investigation of the extract of strain 5-1-3 led to the discovery of one NRP, elucidated as echinomycin, a good antibacterial agent, and two other types of compounds, 5,7,4′-trihydroxy-3.3′,5′-trimethoxy.We characterized 1 can be used as a starter molecule against MRSA for further studies on the structure–activity relationships.flavone and 2,6,2′,6′-tetramethoxy-4,4′-bis-biphenyl, both displaying antibacterial activities. We conclude that strain 5-1-3 can be used as a new source of NRPs, and compound http://antismash.secondarymetabolites.org/, antiSMASH). First, we selected “Submit Bacterial sequence” option, second, we entered the NCBI accession number corresponding to strain 5-1-3 or the full genome sequence in FASTA format. Three parameters were selected for analysis: ClusterFinder, the ClusterFinder Algorithm for BGC Border Prediction, and Extra Features. The Extra Features analysis includes KnownClusterBlast, SubClusterBlast, and ActiveSiteFinder.The antibiotics and secondary metabolites corresponding to the potential secondary metabolite synthesis gene cluster in strain 5-1-3 were analyzed through the online website , and allowed to solidify. In addition, another sterilized solid medium of hot LB agar was cooled to approximately 50 °C and mixed with test bacteria, and 5 mL of the medium mixed with bacteria were added to the solidified medium (upper layer). The Oxford cup  was aseptically placed vertically on the surface of the medium and gently pressurized to ensure a seal with the medium, and 100 μL of extract or pure compound test solution was added into the cup without overflow. Then, the culture was placed at 37 °C for 24 h. The diameter of the inhibition zone was measured with Vernier calipers. All tests were repeated three times. Data were processed in SPSS (PASW Statistics 18), and the results were expressed as means ± standard deviation (SD).The test method was as follows. First, bacterial colonies were selected from the slant culture medium of the test bacteria and inoculated into 50 mL sterile normal saline solution. After 24 h at 37 °C, the bacterial solution was diluted to an OD3: MeOH, 1:1). Fraction A-1 was purified using semipreparative high-performance liquid chromatography (HPLC) with a C18 column  using a 6:4 (2.0 mL/min) ratio of acetonitrile to distilled water to obtain compound 1. Fraction C was purified using semipreparative HPLC  to obtain compounds 2 and 3.Bacterial colonies were grown in Gauze’s No. 1 solid medium in a 1 L conical flask and maintained in a shaking incubator (120 rpm and 28 °C) for 30 days. Bacterial cells were collected following centrifugation at 1200 rpm for 10 min. We used 100% (v/v) ethyl acetate to extract the crude extract from collected 5-1-2 strain until the strain became colorless. The crude extract was separated and purified on a silica gel column (200–300 mesh) and eluted with gradient mixtures of chloroform–ethyl acetate  to give four fractions (A–D). We then performed repeated separation of fraction A with Sephadex LH-20 , and residual CHCl3 , and DMSO  were used as internal standards.The pure active compound was characterized with NMR analyses and comparisons with the literature. Structural identification of the purified compound was clarified with a DRX-400 spectrometer  using spectroscopic techniques for Additional file 1: Figure S11H NMR spectrum of compound 1 in CDCl3 (400 MHz). Figure S213C NMR spectrum of compound 1 in CDCl3 (100 MHz). Figure S31H NMR spectrum of compound 2 in DMSO (400 MHz). Figure S413C NMR spectrum of compound 2 in DMSO (100 MHz). Figure S51H NMR spectrum of compound 3 in CDCl3 (400 MHz). Figure S613C NMR spectrum of compound 3 in CDCl3 (100 MHz).


The histone variant macroH2A1.1 plays a role in cancer development and metastasis. To determine the underlying molecular mechanisms, we mapped the genome-wide localization of endogenous macroH2A1.1 in the human breast cancer cell line MDA-MB-231. We demonstrate that macroH2A1.1 specifically binds to active promoters and enhancers in addition to facultative heterochromatin. Selective knock down of macroH2A1.1 deregulates the expression of hundreds of highly active genes. Depending on the chromatin landscape, macroH2A1.1 acts through two distinct molecular mechanisms. The first mitigates excessive transcription by binding over domains including the promoter and the gene body. The second stimulates expression of RNA polymerase II (Pol II)-paused genes, including genes regulating mammary tumor cell migration. In contrast to the first mechanism, macroH2A1.1 specifically associates with the transcription start site of Pol II-paused genes. These processes occur in a predefined local 3D genome landscape, but do not require rewiring of enhancer-promoter contacts. We thus propose that macroH2A1.1 serves as a transcriptional modulator with a potential role in assisting the conversion of promoter-locked Pol II into a productive, elongating Pol II. Summary: Histone variant macroH2A1.1 binding to the TSS of genes dependent on Pol II pausing stimulates transcription by promoting Pol II release in a human triple-negative breast cancer cell model. Histone post-translational modifications, DNA-binding factors and architectural proteins regulate genome organization and dynamics . In addiH2AFY gene  produces two splicing isoforms, mH2A1.1 and mH2A1.2, the sequences of which differ in a 30 amino acid region within the macro domain , a vertebrate-specific  histone o domain .In vitro studies have demonstrated that nucleosomal mH2A1 interferes with binding of the transcription factor NF-κB and inhibits nucleosome sliding by the remodeling complex SWI/SNF and initiation of RNA polymerase II (Pol II) transcription  of related genes. Conversely, genes inhibited by mH2A1.1 recruit this histone variant over larger domains, present further upstream and downstream of the TSS. Mechanistically, we determined that the expression level of mH2A1.1-activated genes is dependent on Pol II pausing. mH2A1.1 appears to regulate Pol II turnover at the TSS by inhibiting the release of paused Pol II. Linking differential recruitment of mH2A1.1 to mode of action, our work clarifies the ambivalence of the roles attributed to mH2A.1.1 in transcription regulation in cancer cells.Fig. S1A,B) . Among the 945 genes for which expression was significantly modified in the mH2A1.1 KD cells, 533 genes (56.3%) were downregulated  and 412 genes (43.7%) were upregulated  (Tables S1 and S2). Altered expression of a subset of genes was confirmed by RT-qPCR using two different siRNAs directed against mH2A1.1 . All mH2A1.1-regulated genes, both RGs and AGs, were found among the moderately to highly expressed genes in WT MBA-MB231 cells  in the MDA-MB-231 cell line, which expresses mH2A1.1 at higher levels than other types of breast cancer cell lines  . We comp31 cells B,C. Sile31 cells B,C. We cTable S4, Fig. S2A-D) and generated ChIP-seq data for mH2A1.1 (Table S5). The obtained dataset was compared with the one obtained using a commercially available ChIP-grade antibody  directed against total mH2A1 . The two datasets were highly similar with a Pearson coefficient correlation (PCC) of 0.92 .We developed a chromatin immunoprecipitation (ChIP)-grade polyclonal antibody that exclusively recognizes mH2A1.1 (Ab αmH2A1.1) . H3K9me3 marks, known to be over-represented in this TNBC cell line relative to other cancer cell lines . Interestingly, we found that in heterochromatin domains levels of H3K9me3 and H3K27me3 tended to be inversely proportional . Moreover, we found that high H3K27me3-H3K9me3 difference was mainly associated with genomic regions whereas low H3K27me3-H3K9me3 difference characterized intergenomic regions . We propose that, in this cell line, the ratio between H3K27me3 and H3K9me3 could be used to distinguish ‘facultative-like’ heterochromatin and ‘constitutive-like’ heterochromatin. We found that mH2A1.1 and PARP1 binding were proportional to the relative abundance of H3K27me3 versus H3K9me3 , indicating that these two proteins predominantly associate with ‘facultative-like heterochromatin’ in the MDA-MB-231 TNBC cell line.We next examined whether mH2A1.1 binding occurred in specific chromatin environments. We analyzed the correlation between mH2A1.1 and a subset of heterochromatin marks , chromatin-bound components  as well as euchromatin marks  at a genome-wide level D. Bindinll lines , overlapWhen specifically examining the chromatin landscape at promoters (TSS±1 kb), we found that mH2A1.1 enrichment correlated with H3K4me3 and H3K27ac, as well as with BRD4, H3.3 and Pol II binding A,B, suggFig. S3F).We next questioned whether this profile was linked to the mechanism by which mH2A1.1 regulates gene expression. To this end, we separately determined mH2A1.1 binding at genes repressed or activated (RGs and AGs) by mH2A1.1. At both gene categories, mH2A1.1 was highly enriched at the TSS A,B. HoweFig. S4A,B). H3.3 follows the same binding profile as mH2A1.1. BRD4, RING1B and PARP1 were mainly enriched at the TSS, and slightly more at high-PI genes , a PI value that can be used as a threshold to distinguish paused from not paused genes (Table S3). In agreement, the average PI of these genes was significantly higher than any other gene category tested  showed that the amount of Pol II at promoter regions was increased by approximately threefold upon siRNA reduction of mH2A1.1 . On average, we observed that depletion of mH2A1.1 induces an increase in the PI (ratio between promoter region and gene body) of RBL1, GTF2H3 and E2F3 genes by factors of 1.4, 1.6 and 1.7, respectively. These results suggest that mH2A1.1 enhances gene expression by promoting Pol II pause release.The majority of mH2A1.1-AGs (85%) had a PI >2  . Strikingly, mH2A1.1-bound regions frequently formed large domains comprising a group of enhancers marked with H3K27ac (P<2.2×10−16 and odds ratio=7.35)  A,B. Enhaio=5.26)   were generally unaffected by the absence of mH2A1.1. Hence, chromatin interaction landscapes at mH2A1.1-regulated genes do not appear to require mH2A1.1. Quantification of the PCHiC interactions showed that mH2A1.1-AGs have on average a greater number of interactions than mH2A1.1-RGs , suggesting that AGs and RGs reside within two types of interaction landscapes. Moreover, we noted that mH2A1.1 enrichment was greater at enhancers associated with RGs than at those associated with AGs . Active chromatin marks and co-activators were also more abundant at RG-related enhancers than AG-related ones  , an observation in agreement with the fact that RGs are on average more transcribed than AGs . For example, we observed an increase in the intensity of some interactions at the RG FRAS1 upon mH2A1.1 depletion , and at other AGs for which 3D organization remained unaffected by mH2A1.1 depletion . We conclude that chromatin looping does not interfere with the potential role of mH2A1.1 in Pol II release.Although loss of mH2A1.1 did not induce any global changes in promoter contact numbers or frequencies, closer inspection of the interaction landscape of a few mH2A1.1-regulated genes revealed reproducible changes in the intensity of interactions between certain enhancers in mH2A1.1 KD versus WT cells . The two first processes were expected based on earlier studies . Using immunofluorescence against cytoskeleton proteins , we observed that cytoskeleton organization was modified by the loss of mH2A1.1 . It would hence be interesting to determine whether the molecular mechanism by which the mH2A1.2 splicing isoform modulates transcription regulation, as well as the interplay between both isoforms.mH2A1.1-target genes are involved in four main processes: cell cycle (9% of mH2A1.1-target genes), DNA repair (4%), cytoskeleton organization and cell adhesion (19%) . Overall, we conclude that mH2A1.1 impedes the migration capacity of MDA-MB-231 breast cancer cells in part by promoting expression of genes modulating cell migration capacity.Strikingly, mH2A1.1-AGs involved in cytoskeleton organization and cell adhesion were also amongst genes with a high Pol II PI compared with mH2A1.1-RGs C,D, and Regulating gene expression in a particular cell type requires fine-tuning of the transcriptional response. The concentration and the relative ratio between factors required for these regulatory mechanisms ensure rapid adjustments to maintain homeostasis or to respond to stimuli and stress. In this study, we identify the histone variant mH2A1.1 as a means to operate these adjustments in TNBC cells.Fig. S3A-E)  . Moreove. S3A-E) A-C. All Fig. S5C,D). Importantly, these domains were also characterized by the presence of RING1B and the Polycomb-induced histone modification H2AK119ub . With the identification of specific PRC1 variants at a large number of active loci, it is now accepted that the presence of Polycomb subunits does not always correlate with transcriptional repression states  and led to an accumulation of Pol II at their TSSs E, 6H. ItThe fact that mH2A1.1 binds specifically to the TSS of genes it activates in MDA-MB-231 cells is particularly intriguing here. The only other study that included an analysis of the genomic localization of this histone variant was performed in the murine muscle cell line C2C12 . In thisFig. S3A). A fraction of these sites is devoid of H3K27me3 and could correspond to the identified mH2A localization at constitutive heterochromatin . This difference may be a feature of the MDA-MB-231 cell line, a high migratory capacity cancer cell line in which H3K9me3 histone marks are distributed unusually . Different hypotheses could explain this result. The first hypothesis could be that mH2A1 isoforms (mH2A1.1 and mH2A1.2) have redundant actions at heterochromatin. Here, we specifically depleted mH2A1.1 without affecting the expression of mH2A1.2 . The presence of mH2A1.2 could be sufficient to maintain gene silencing, although mH2A1.2-occupied silent genes were also not reactivated upon mH2A1.2 knockdown . In Montpellier, MDA-MB-231 cells were cultured in DMEM supplemented with 10% fetal calf serum and penicillin/streptomycin (100 µg/ml each) and regularly tested for Mycoplasma infection.MDA-MB-231, HEK-293T and MCF7 cell lines were purchased from ATCC, and were maintained and amplified in Dulbecco's Modified Eagle's (DMEM) for HEK-293T and MDA-MB-231 cells, and in DMEM-F12 for MCF7 cells, supplemented with gentamycin (50 µg/ml) (Gibco), fetal bovine serum  and sodium pyruvate . Cells were maintained in a humidified incubator at 37°C with 5% COTable S8. Cells were recovered for experiments 2 and 3 days after plasmid and siRNA transfection, respectively.At 30-50% confluence, transfection of siRNA (11 nM) was performed using INTERFERin (Polyplus-Ozyme) according to the manufacturer's protocol. Cells for the control condition were transfected with INTERFERin without any siRNA. Transfection of plasmid (1 μg) was carried out with FuGene HD (Promega) according to the manufacturer's protocol. siRNA and plasmids are listed in Table S4. Rabbit anti-mH2A1.1 antibody was generated according to an immunization protocol from Agro-Bio . Membranes were next incubated with secondary antibody 0.4% Tween 20, 5% milk in PBS for 1 h at RT with rotation and the signal was detected using chemiluminescence . Secondary antibodies are described in Table S4. Signal quantifications were carried out with Image Lab software (Bio-Rad).Cells were lysed and subjected to western blot analysis as previously described . BrieflyTable S9. qRT-PCR was performed using iTAq Universal SYBR Green (Bio-Rad) according to the manufacturer's instructions. At least two independent experiments were performed for each condition. The relative expression levels of mRNA were normalized to RPLP0 mRNA expression and evaluated according to the 2−ΔΔCt method . Purified RNA was reversed transcribed to cDNA using Maxima H Minus First Strand cDNA Synthesis Kit (Promega). The sequences of the primers used are given in t method .Table S4. The coverslips were finally incubated with Hoechst  for 30 min and then mounted with VECTASHIELD mounting media (Vector Laboratories). Images were acquired with a Zeiss LSM 710 BiG confocal microscope using an 63× PL APO oil DIC On 1.4 objective for all experiments. Images were taken in z-stacks with a voxel size of 300 nm. Images shown are z-stacks or maximum intensity projections of z-stacks.Two- or three-days post-transfection, cells were fixed with 4% paraformaldehyde for 15 min for MDA-MB-231 cells and 10 min for HEK-293T at RT. Cell permeabilization was carried out using 0.1% Triton X-100 in PBS for 10 min at RT. Cells were then blocked with 5% BSA, 0.15% Tween 20 in PBS for 1 h at RT. Next, cells were incubated with primary antibody O/N at 4°C. Cells were then incubated with Alexa Fluor-conjugated secondary antibody for 1 h at RT. Actin was labeled using cytoPainter Phalloidin iFluor diluted 1:1000 with secondary antibody according to the manufacturer's protocol . Antibody references and dilutions are provided in g for 20 min) and washed with washing buffer . Nuclei were then resuspended in sonication buffer . Chromatin was sheared using a Bioruptor (Diagenode)  in order to obtain chromatin fragments with an average size of 300-500 bp. The quality and size of chromatin fragments was monitored by ethidium bromide-stained agarose gel electrophoresis after DNA purification. Then, 100 μg of DNA was incubated with antibody O/N at 4°C on a rotation wheel. Antibodies are described in Table S4. Protein A magnetic dynabeads  were added for 3 h at 4°C on a rotation wheel. Immunoprecipitates were then exposed to serial washes for 5 min each on a rotation wheel at 4°C in the following buffers (twice in each buffer): WBI: 2 mM EDTA, 20 mM Tris, pH 8.1, 1% Triton X-100, 150 mM NaCl; WBII: 2 mM EDTA, 20 mM Tris, pH 8.1, 1% Triton X-100, 500 mM NaCl; WBIII: 1 mM EDTA, 10 mM Tris, pH 8.1, 250 mM LiCl, 1% sodium deoxycholate, 1% NP-40; and WBIV: 1 M EDTA, 10 mM Tris, pH 8.1. Chromatin was eluted from the magnetic beads with DNA isolation buffer  for 1 h at 65°C under agitation. Extracts were reverse-crosslinked with SDS O/N at 65°C. RNAs were degraded with RNase A and proteins were finally degraded with proteinase K. The same procedure was performed for input (10 μg of DNA). DNA was finally extracted with a phenol-chloroform extraction. Quantity and quality of DNA was tested with a nanodrop spectrophotometer . Samples were sequenced by the GeT core facility, Toulouse, France (http://get.genotoul.fr). Sequencing was performed using a HiSeq 3000-HWI-J00115 (Illumina) according to the manufacturer's protocol. The same procedure was used for ChIP-qPCR. Sequences of the primers used for qPCR are given in Table S9. For western blot analysis, extracts  were processed as for ChIP extracts, but were not incubated with RNase A and proteinase K. Extracts were then subjected to western blot analysis as previously described in the ‘Western blotting’ section. To compare different extracts, we loaded 2% input, 0.5% input, 0.5% NoIP fraction and 20% IP fraction. Percentages given are relative to the DNA quantity used for ChIP . After 10 min in ice, cell lysis was amplified with a 2 ml dounce (Kimble Chase) to enhance the separation of nuclei from cytoplasm. Cell lysis buffer containing lysed cells was deposited into a pillow buffer . Nuclei were then pelleted by centrifugation , nuclei were lysed in Nuclei Lysis Buffer  at 4°C for 2 h and then sonicated for ten cycles at 4°C using a Bioruptor Pico device from Diagenode. For immunoprecipitation of H3K4me1, H3K4me3 and H3K27ac, 150 µl of chromatin  and 4.5 µg of the corresponding antibodies were used. For Pol II, 850 µl of chromatin  and 20 µg of the corresponding antibody were used. Each ChIP run was sequenced by the MGX GenomiX platform (Montpellier) using a Hi-seq 2500 Illumina sequencer. ChIP-qPCR of Pol II was carried out following the same protocol as for Pol II ChIP-seq. qPCR was performed on ChIP samples and input (1% of DNA used for ChIP). qPCR results are normalized using the signal obtained with the input and expressed as percentage of input. Primers used are given in Table S9.ChIP-seq of H3K27ac, H3K4me1, H3K4me3, H3K36me3 and Pol II was performed essentially as previously described . Brieflyhttp://get.genotoul.fr) with the TruSeq Stranded total RNA Kit (Illumina) according to the manufacturer's instructions. Sequencing was performed using a HiSeq 3000-HWI-J00115 according to the manufacturer's protocol.Total RNA was isolated using the RNeasy Midi Kit (QIAGEN). RNA-seq quality and quantity controls were performed using a Nanodrop spectrophotometer  and a 5300 Fragment Analyzer system (Agilent). Library preparation and sequencing was carried out by the GeT core facility , H3K27me3 (GSM2258850) and corresponding input (GSM2258864) in MDA-MB-231 cells were downloaded from Gene Expression Omnibus (GEO accession number: GSE85158) (GSM2862187), RING1B (GSM2862179), PCGF2 (GSM2862185) and H2AK119ub (GSM2862181) in MDA-MB-231 cells were downloaded from Gene Expression Omnibus (GEO accession number: GSE107176) (GSM3398219), and corresponding input (GSM3398220) in MDA-MB-231 cells were downloaded from Gene Expression Omnibus (GEO accession number: GSE120313) (GSM1517306) in MDA-MB-231 cells were downloaded from Gene Expression Omnibus (GEO accession number: GSE61916)  . NormR parameters were adjusted depending on the bigwig profiles for each ChIP-seq data. mH2A1.1-specific peaks were used for all analysis and correspond to the commun peaks between mH2A1.1 and mH2A1 ChIP-seq. The number of peaks for each ChIP-seq dataset are listed in Table S5. All downstream analyses were mainly performed with R studio. ChIP-seq signal and peaks positions visualization were obtained with IGV  . Published ChIP-seq data for H3K9me3 (SE85158) , and re-E107176) , and re-E120313)  and re-aSE61916)  and re-aSE61916) . Details0 -view) . Convers0 -view) . Correspwith IGV . Boxplotwith IGV . Distribig. S3D) . Statistn=25,668 annotated genes). SEs were determined with ROSE utility tools based on H3K27ac signal (options: stitching_distance=12.5 kb and TSS_exclusion_zone_size: 2500 bp)  to avoid TSS bias A-C Blin. TSS ann2500 bp) D,E (Lové2500 bp) .n=10,564 genes). ‘Paused’ genes were defined as genes with a PI >2 (n=7208) (n=3356).PI was defined previously  as the r(n=7208) . ‘Not paIntersection of peaks was determined with the function findOverlaps from the GenomicRanges package . Note thCorrelation heatmaps using bigWig of indicated ChIP-seq were created with multiBigwigSummary (with or without the options: -bins) and plotCorrelation (option: -spearman correlation heatmap) from DeepTools utilities (3.1.3) .P-value, represented by asterisks . Groups used for the analysis were divided in equal size according to the ChIP-seq signal.Fisher test heatmaps were created using ggplot2 . Each sqFig. S5C to compare the relative enrichment between mH2A1.1-target genes and their associated enhancers. On profiles and heatmaps, gene directionality was ignored, meaning that all gene bodies are artificially placed on the right-hand side of the plots.Metagene analysis profiles were performed with the R Seqplot package  using bibigWig signals of the indicated ChIP-seq data were calculated with R studio based on bigWig files. For all the figures, the sum bigWig file (bin of 50 bp) was calculated on specific genomic regions and normalized to the width of the specific genomic regions.Table S5. Low-quality reads and duplicates were then filtered out using SAMtools  (g×106)/(RCp×L), where RCg corresponds to the number of reads mapped to the gene, RCp to the number of reads mapped to all protein-coding genes and L to the length of the gene in base pairs. FPKM gene counts in control conditions were used to classify genes according to their gene expression level in four equal-sized categories . FPKM gene counts in the mH2A1.1 KD condition were also calculated and used to generate the graph in Padj<0.1. The corresponding volcano plot was created with the EnhancedVolcano package  . The reads were mapped to the human reference genome GRCh38 using the default parameters of STAR (2.5.1) . Details -rmdup) . Unstran -rmdup) . Gene co -rmdup) . FPKM foe, 2018) A. mH2A1.Table S8). PCHiC was essentially performed as described by PCHiC data were generated for MDA-MB 231 cells in control and mH2A1.1 KD cells using siRNA#1 (see the ‘Transfection of siRNAs and plasmids’ section and https://github.com/yousra291987/ChiCMaxima)  after processing the fastq files with custom scripts, essentially performing the same analysis as HiCUP . CompariCMaxima) . ChiCMaxCMaxima) . More thTables S6 and S7. A selection of genes related to their functions was identified with biomaRt package [function getBM] (n=2509) using attributes=’ensemble gene_id’ annotation from the biomaRt package, overlaps of genes with mH2A1.1-regulated genes were identified . For genes related to cell cycle (GO:0007049), cell cycle process (GO:0022402), cell division (GO:0051301) and cell growth (GO:0016049) (n=656), overlaps of genes with mH2A1.1-regulated genes were identified . Finally, for genes related to DNA repair (GO:0006281) and cellular response to DNA damage stimulus (GO:0006974) (n=533), overlaps of genes with mH2A1.1-regulated genes were identified . For Fisher test heatmaps with PI, only genes with a PI were used. n indicates the number of genes used for the analysis in Fig. S7E.GO analysis was performed with limma package (--function goana) (3.8)  and corrgetBM] , 2009. FTranswell migration assays were performed using Transwell plates with 0.8 µm pore polycarbonate membranes . Three days post-siRNA transfection, MDA-MB-231 cells were seeded in the upper chamber without FBS and allowed to invade to the reverse side of the chamber under chemoattractant conditions with 10% FBS-containing medium in the lower chamber. Following incubation for 16 h at 37°C, the cells were fixed with 3.7% formaldehyde for 2 min at RT. Cell permeabilization was carried out by incubation in 100% methanol for 20 min at RT. Cells were then stained with Giemsa for 15 min at RT. The final total cell number between conditions was always checked by wide-field microscopy to avoid proliferation bias for migratory cell comparison. Non-migrated cells were finally removed from the upper chamber using a cotton swab. Migrated cells adhering to the underside of the chamber were photographed using a light microscope at 200× magnification . Cell counting was performed with ImageJ in ten different fields per condition . Three iP-values ≤0.05 were considered as significant or highly significant when ≤0.01 (given as *P≤0.05; **P≤0.01; ***P≤0.001; ****P≤0.0001. Fisher exact test was used to perform enrichment tests of ChIP-seq peaks. Base sets were defined from all the ChIP-seq data or based on TSS annotations.All western blot, qRT-PCR and Boyden chamber assay experiments were repeated at least twice as independent biological replicates and results are presented as mean±s.d. All statistical analyses were performed with R. For western blotting, qRT-PCR and Boyden chamber assays, Wilcoxon tests were used to compare mean values between conditions.


We developed a novel fluorescence polarization (FP) assay focused on the PPI between an AC1 peptide and CaM and used this assay to screen over 23,000 compounds for inhibitors of the AC1-CaM PPI. Next, we used a cellular NanoBiT assay to validate 21 FP hits for inhibition of the AC1-CaM PPI in a cellular context with full-length proteins. Based on efficacy, potency, and selectivity for AC1, hits 12, 13, 15, 18, 20, and 21 were prioritized. We then tested these compounds for inhibition of AC1 activity in cyclic AMP (cAMP) accumulation assays, using HEK293 cells stably expressing AC1. Hit 15 contained a dithiophene scaffold and was of particular interest because it shared structural similarities with our recently reported benzamide series of AC1 inhibitors. We next tested a small set of 13 compounds containing the dithiophene scaffold for structure-activity relationship studies. Although many compounds were non-selective, we observed trends for tuning AC1/AC8 selectivity based on heterocycle type and substituents. Having an ethyl on the central thiophene caused the scaffold to be more selective for AC8. Cyclization of the alkyl substituent fused to the thiophene significantly reduced activity and also shifted selectivity toward AC8. Notably, combining the fused cyclohexane-thiophene ring system with a morpholine heterocycle significantly increased potency at both AC1 and AC8. Through designing a novel FP screen and NanoBiT assay, and evaluating hits in cAMP accumulation assays, we have discovered a novel, potent, dithiophene scaffold for inhibition of the AC1- and AC8-CaM PPI. We also report the most potent fully efficacious inhibitor of AC8 activity known to-date.Genetic and preclinical studies have implicated adenylyl cyclase 1 (AC1) as a potential target for the treatment of chronic inflammatory pain. AC1 activity is increased following inflammatory pain stimuli and AC1 knockout mice show a marked reduction in responses to inflammatory pain. Previous drug discovery efforts have centered around the inhibition of AC1 activity in cell-based assays. In the present study, we used an  Adenylyl Cyclase Type 1 (AC1) is a promising target for treating chronic inflammatory pain. The overlapping neuronal expression of membrane-bound AC proteins prioritizes obtaining selectivity when targeting a single isoform . Studiesi/o and Gβγ subunits inhibit the activity of AC1, whereas Gαs and Ca2+/calmodulin (CaM) stimulate AC1 activity, with Ca2+/CaM exhibiting particularly robust stimulation  studies. Collectively, this demonstrates the utility and robustness of these methods to identify novel inhibitor scaffolds that target the AC/CaM PPIs.AC1 signaling centers around its ability to synthesize the second-messenger cyclic adenosine monophosphate (cAMP) from ATP, and this primary function of AC1 is regulated by several signaling proteins. Gαmulation . Therefotivation . These dThe human CaM (hCaM) bacterial expression vector was constructed as previously described . BrieflyThe NanoBiT PPI TK/BiT MCS vectors were purchased from Promega  for cell-based NanoBiT experiments. The hCaM residues 1–149, residues 1–1,248 of rat AC8 (rAC8), and the human AC1 (hAC1) residues 1–1,118 were cloned into the NanoBiT vectors per manufacturers’ protocols, using the restriction sites NheI/XhoI for hCaM and BglII/XhoI. All DNA sequences were confirmed with Sanger sequencing .E. Coli and incubated at 37°C with shaking at 275–300 RPM until the OD600 reached 2.0. The bacterial culture was placed on ice with gentle mixing before protein production induction with isopropyl-β-D-1-thiogalactoside (RPMI) at a final concentration of 1.0 mM. Protein production continued for an additional 16 h at 18°C with shaking at 300 RPM. The bacterial culture was pelleted and resuspended in 50 ml of resuspension buffer  per 1 L of original bacterial culture. The resuspended bacterial cells were then subjected to a freeze-thaw cycle using LN2. The resuspended cells were thawed, supplemented with 1 mg/ml chicken egg lysozyme , and agitated on a tube rotator for 1 h before being subjected to two more freeze-thaw cycles with LN2. After cell lysis was complete, 100 μg DNase (Roche) was added to reduce viscosity and prepare the sample for centrifugation. The lysed cells were then subjected to ultracentrifugation at 100,000 x g to clear the lysate from the supernatant. The separated supernatant was purified as described previously with minor modifications . Purified GST-CaM was eluted using a gradient elution over 10 column volumes of 50 mM Tris pH 7.5, 1 mM CaCl2, and 10 mM glutathione. Peak fractions were collected and analyzed with SDS-PAGE gel electrophoresis to assess their purity. Fractions greater than 90% pure were pooled and exhaustively dialyzed against 20 mM HEPES pH 7.4, 100 mM KCl, at 4°C to remove Ca2+, before samples were aliquoted, flash-frozen in LN2, and stored at −80°C. To purify tag-free CaM, we incubated GST-CaM with His-tagged TEV protease at a 20:1 M ratio (GST-CaM/TEV) while dialyzing the sample against 20 mM HEPES pH 7.4, 100 mM KCl, 1 mM CaCl2. Dialysis and TEV treatment proceeded overnight at 4°C. The TEV treated CaM sample was then loaded onto an IMAC to separate 6XHis-tagged GST and TEV from CaM. The resulting flow-through fractions were collected and analyzed with SDS-PAGE and Coomassie staining. Fractions determined to be 95% pure CaM were concentrated to >10 mg/ml using an Amicon centrifugal concentrator with a 3kD cutoff . Samples of pure CaM were aliquoted, flash-frozen in LN2, and stored at -80°C. Production of 15N-labeled CaM for NMR experiments was accomplished as described above, with the only modification being that bacterial culturing was completed in M9 minimal media supplemented with 1 g of 15NH4Cl per L.hCaM was expressed and purified as described previously with minor modifications . Brieflyications . Briefly2), 3X calmidazolium (CDZ) in FP assay buffer, or 3X DMSO in FP assay buffer was added to their respective wells. Next, 20 μl of 3X GST-CaM in FP assay buffer was added to all wells, and the plate was incubated at room temperature for 30 min. Lastly, 20 μl of 3X AC peptide in FP assay buffer was added to all wells, and the plate was incubated in the dark at room temperature for either the amount of time indicated for the assay optimization experiments or 2 h for the high-throughput screening experiments. Fluorescence was then measured, and the polarization output was calculated using the measured intensities of emitted light parallel and perpendicular to the excitation light, shown in Peptides for adenylyl cyclase proteins, AC1 and AC8, were generated based on the residues or domains known to interact with CaM . The pepThe FDA-approved library  was screened at a final concentration of 14.5 μM (0.72% DMSO). On the day of the assay, a “middle” plate (ThermoFisher #264574) was created to simplify the addition of 20 μl of 3X compound to the final assay plate. First, using a Hamilton MircroLab Star liquid-handling robot, 2 μl of 2 mM compound from the FDA stock plate was added to the middle plate containing 90 μl of FP assay buffer. Next, 20 μl of 3X compound from the middle plate was added to the assay plate (Corning #3575). Controls were then added to empty wells . Next, 20 μl of 3X GST-CaM  was added to the entire plate, and the assay mixture was incubated for 30 min at room temperature. Finally, 20 μl of 3X AC1 C1b Cy5 labeled peptide  was added to the entire plate, and the assay mixture was incubated at room temperature in the dark for 2 h before polarization was measured as described above.The Microsource spectrum collection (MMSP)  was screened as outlined above for the FDA-approved library with some minor differences. First, the stock concentration of compounds was 10 mM. Therefore, the middle plate contains 1 μl of MMSP compounds with 90 μl of FP assay buffer (concentration of the compound in the middle plate: 109.8 μM). To achieve the desired 3X concentration in the test plate, 12 μl of FP assay buffer was added to the test plate before adding 8 μl of the compound from the middle plate (3X compound in test plate: 43.9 μM). After compounds were added to the test plates addition of controls, GST-CaM, and Cy5-labeled AC1 C1b peptide were completed as described for the FDA-approved library. The test plate’s final concentration of MMSP compounds was 14.64 μM (0.147% DMSO).The screening protocol for the ChemBridge DIVERSet library  of compounds as described for the FDA-approved library with the same minor differences as the MMSP library described above. The test plate’s final concentration of ChemBridge DIVERSet compounds was 14.64 μM (0.147% DMSO).For the ChemDiv CNS targeted library  of compounds, the protocol is the same as that outlined for the FDA-approved library, with minor differences as the MMSP and ChemBridge DIVERSet libraries. The test plate’s final ChemDiv CNS targeted compounds’ concentration was 14.64 μM (0.147% DMSO).2. Cells were plated at 25,000 cells/well in 96-well half area plates (Corning #3885) pretreated with poly-d-lysine. Cells were cultured for 16 h before transfection with Lipofectamine 3,000  and the designated AC-CaM NanoBiT DNA constructs described above. Transfections were performed according to the manufacturer’s protocol, and transfected cells were incubated for 40–44 h before compound treatment.The AC8/CaM NanoBiT assays were performed mainly as previously described . The AC1On the day of the assay, the culture medium was removed and replaced with 50 μl of 1X Compound, BAPTA-AM  (Sigma-Aldrich), or vehicle in HBSS  supplemented with 20 mM HEPES pH 7.4. The assay plate was then incubated at 37°C for 30 min before 12.5 μl of 5X NanoGlo Live-cell substrate , prepared according to the manufacturer’s protocol, was added to each well. Next, the plate was read on a BioTek Synergy 2 plate reader at 37°C in luminescence mode for 30 min to establish a baseline for the protein-protein interaction. Next, 12.5 μl of 6X Thapsigargin  was added to each well, and luminescence was read for an additional 60 min. The area under the curve (AUC) analysis quantified the AC-CaM association for vehicle, BAPTA-AM, and compound-treated cells. Using the AUC for compound-treated cells, the data were normalized to vehicle with 1 μM thapsigargin added (100%) and 50 μM BAPTA-AM (0%). Data were analyzed using GraphPad Prism 8, with each data set representing a mean of three independent experiments (N = 3) ± SEM.2. Cells were plated at 25,000 cells/well in 96-well half area plates (Corning #3885) coated with poly-d-lysine and allowed to incubate for 40–44 h. On the day of the assay, culture media was aspirated and replaced with 25 μl of 2X compound in HBSS supplemented with 20 mM HEPES pH 7.4 or 2X vehicle (HBSS supplement with 20 mM HEPES pH 7.4). After adding the compound or vehicle, the plate was incubated at 37°C for 30 min. Next, 25 μl of 2X CellTiter-Glo 2.0 reagent  was added, and the plate was mixed on an orbital shaker for 30 min to induce cell lysis and equilibrate the plate to room temperature. Luminescence was then measured for 30 min to establish a stable signal. The final three luminescence values from the 30-min read were averaged and used to assess cell viability. Cell viability for tested compounds was normalized relative to vehicle (100%) and wells containing buffer with no cells (0%). Data represent the mean of three independent experiments (N = 3) ± SEM.Cell viability measurements were performed using a BioTek Synergy 2 plate reader luminescence mode. HEK293T cells were cultured in Gibco DMEM supplemented with 10% FBS (Gibco) and 1% Penicillin/Streptomycin at 37°C and 5% CO2. Cells were then treated with varying concentrations of inhibitors for 30 min, followed by treatment with calcium ionophore A23187 (3 μM) in 500 μM 3-isobutyl-1-methylxanthine (IBMX), a phosphodiesterase inhibitor, for 1 h at RT . Finally, Cisbio HTRF detection reagents were added and incubated for 1–24 h at RT. Plates were read according to manufacturer’s protocol on an HTRF-compatible plate reader at 620 and 665 nm cAMP concentrations were interpolated from a cAMP standard curve. Data represents the mean ± SEM of IC50 values or percent of maximum A23187 inhibition from the mean of three independent experiments (N = 3). For cytotoxicity assays, compounds were tested at 30 μM and this protocol was used with the exception of detection reagents; CellTiter-Glo 2.0 reagent was used according to manufacturer’s protocol and luminescence was read on the Synergy Neo2 plate reader. Data are normalized to cells treated with vehicle (100%) or 2% tween (0%) and are represented as the percent of vehicle, from the average of three independent experiments (N = 3).Cryopreserved HEK293 cells with AC3 and AC6 knocked out, and stably expressing AC1, AC2, AC5, or AC8  for AC1-C1b, AC8-Nt, and AC8-C2b were quantified to be 31.5, 136.5, and 48.5 nM, respectively (2+ chelator) showed the interaction to be Ca2+ dependent, which was expected  of positive and negative control, and μp,n representing the mean of the positive and negative control.Intending to identify small molecule inhibitors that selectively target the AC1/CaM PPI, we developed and optimized an FP assay for a high-throughput screening (HTS) campaign. For simplicity, peptides will be denoted AC1-C1b, AC8-Nt, and AC8-C2b, all containing an N-terminal Cy5 fluorophore label. The FP assays for AC8-Nt and AC8-C2b, established previously , were usectively . The natexpected . Incorpo 15.1 μM  (Gietzen 15.1 μM . The AC1 15.1 μM . Through 15.1 μM  shown be 15.1 μM . With a i), calculated using the Cheng-Prusoff equation  assessment in the AC1/CaM and AC8/CaM FP assays. Compounds were assessed based on their inhibition constants  using the AC1/CaM FP assay. Compounds were screened individually at a single concentration of 14.5 μM. The results of screening the FDA-approved library are shown in We screened 2,320 compounds from the Microsource Spectrum Collection  at a single concentration of 14.6 μM. Hits were identified using a 5 SD. below the mean of the vehicle control (1% DMSO) cutoff and validated with a single concentration in the AC1/CaM FP assay as outlined for the FDA-Approved library. The results of screening the MMSP library are shown in in silico to retain only compounds with desirable drug-like properties . A total of 10,240 compounds were screened and hits identified using the same 5 SD. Hits were validated with a single concentration in the AC1/CaM FP assay as outlined for the FDA-Approved library. The results of screening the ChemBridge DIVERSet library can be seen in The ChemBridge DIVERSet Library  is comprised of a compound collection that has been stringently filtered i values for the AC1/CaM FP assay.The ChemDiv CNS targeted library  is comprised of compounds selected for CNS protein targets (98 protein sub-families/unit targets) based on literature searches (ranging from 2014-present) as well as novel X-ray and Cryo-EM structures deposited in the PDB. These searches are designed to identify chemical structures and substructures more likely to penetrate the blood-brain barrier due to their physicochemical properties and known activities. The criteria for evaluating the screening data produced with the CDI library were the same as for the previous libraries screened. 7,680 compounds from the CDI library were screened against the AC1/CaM FP assay. The results of screening the CDI library are shown in i values for all hit compounds are summarized in In total, 21,258 compounds from four compound libraries were screened in the AC1/CaM FP assay. From these screens, 25 validated hits were repurchased as a powder for CRC analysis. CRCs were generated for hits in the AC1/CaM primary assay and AC8/CaM counterscreen assays. Data were normalized to the vehicle  and the 100 μM CDZ positive control (100% inhibition). However, as CDZ is not a complete inhibitor of the AC-CaM interaction, it did not abolish the FP signal altogether. As a result, several hit compounds inhibited the FP signal greater than 100%, using CDZ inhibition as a comparator. The CRCs and structures of the hit compounds for the FDA-approved, MMSP, and ChemBridge libraries are shown in 1 (tolonium chloride) from the MMSP library, with a Ki of 0.29 μM for AC1-C1b/CaM (IC50 = 1.24 μM), 2.3 μM for AC8-Nt/CaM, and 0.44 μM for AC8-C2b/CaM. The second most potent hit, 2, also from the MMSP library, has an almost identical structure to 1, differing by the addition of a methyl group on the tricyclic scaffold. The Ki values for 2, 0.51 μM for AC1-C1b/CaM (IC50 = 2.18 μM), 3.2 μM for AC8-Nt/CaM, and 0.82 μM for AC8-C2b/CaM, are nearly identical to those obtained for 1. Further, 1 and 2 achieved 75–80% inhibition relative to the positive control (100 μM CDZ) in the AC1 and AC8/CaM FP assays at the highest concentration tested (100 μM). These two compounds did not exhibit a significant selectivity for the AC1/CaM interaction versus either AC8/CaM interaction, evidenced by similar Ki values. These compounds share a phenothiazine scaffold present in the known CaM binder, trifluoperazine  and will be discussed below (2 (methylene blue) is a known nonspecific PPI inhibitor, although it was identified as a hit against AC1 , respectively. Hits 3, 4, and 7 (Ki for AC1/CaM FP = 4.1 μM) were the duplicate hits identified in the FDA-approved and MMSP library screens. These three hits have been previously identified as AC8/CaM inhibitors  for AC1 over AC8 in the FP assays. Hit 6 inhibited the AC1/CaM FP assay to 131% relative to the positive control due to CDZ’s incomplete inhibition of the FP signal. Only hits 6 and 3 outperformed the positive control in the AC1/CaM FP assay. Hits 6 and 8 were the only non-CDI library compounds tested that preferentially inhibited AC1/CaM over AC8/CaM in the FP assays . However, we placed an equal priority on potent compounds and those that exhibit selectivity for inhibition of AC1-CaM over AC8-CaM. We, therefore, moved forward with 21  to enter cells and chelate free Ca2+. After this initial treatment, NanoBiT substrate was added, and baseline luminescence was measured continuously for 30 min. Finally, cells were treated with buffer, thapsigargin, or calcium ionophore A23187, and luminescence was monitored continuously for an additional 60 min. The response to vehicle or Ca2+ regulating mobilizing agents (Thapsigargin or A23187) in the absence or presence BAPTA-AM was assessed using the area under the curve (AUC) for the 25 min following the baseline luminescence read. Initial optimization efforts revealed poor results for the combinations with LgBiT attached to AC1 and SmBiT attached to CaM. This result is likely either the result of the LgBiT occluding CaM binding to the AC1 protein or the BiT fragments being too distant to associate and form functional NanoLuc enzyme. These Ca2+ sensitivity experiment results prompted us to use SmBiT-AC1 with LgBiT-CaM  to assess our initial hits using NanoBiT. This vector combination showed the most robust increase in luminescence with thapsigargin compared to A23187. In addition, the SmBiT-AC1 and LgBiT-CaM fusion protein combination was responsive to thapsigargin in terms of reversal of the decrease in luminescence from pre-incubation with BAPTA-AM  as a cell-based orthogonal assay to test the hits identified in the AC1/CaM FP pilot screen. The NanoBiT assay provides a cellular context to examine compound activity and utilizes full-length adenylyl cyclase. We have applied this system in a prior study to assess the AC8/CaM PPI . In the APTA-AM .12 (Benzbromarone). In the NanoBiT assay, 12 was the most potent hit with an IC50 of 1.70 ± 1.17 μM and 4.53 ± 1.15 μM for the AC1/CaM and AC8/CaM PPI, respectively. Cell viability at the AC1/CaM IC50 was at 90% for 12. Despite performing well in the NanoBiT assay, 12 was not the most potent hit in the AC1/CaM FP assay with an IC50 of 33 μM and a Ki of 7.8 μM. In the FP assay, 12 was approximately 7- and 3-fold selective for AC1-C1b/CaM over AC8-Nt/CaM and AC8-C2b/CaM, respectively. This selectivity is not entirely lost in the NanoBiT assay but is a theme observed for several hit compounds tested.Pairing the NanoBiT assay with the Cell-Titer Glo 2.0 assay allowed us to monitor a decrease in the NanoBiT signal and ensure this signal loss was not a result of cell death or loss of membrane integrity. The CRCs for hit compounds in the NanoBiT and cell viability assays are shown in 3, 7, 13, and 18, with IC50 values below 20 μM for the AC1/CaM and AC8/CaM NanoBiT assays. These compounds were moderately selective for AC1 in the FP assays, but selectivity was lost in the NanoBiT assay. Interestingly, the AC selectivity of 18 flipped from what was observed in the FP assay, where 18 was selective for AC1-C1b/CaM over both the AC8/CaM FP constructs; in the NanoBiT assay, 18 was ∼3-fold selective for AC8 over AC1. This phenomenon was not specific to 18. For example, the hit compounds 6 and 21 were 2- to 4-fold selective for AC8 over AC1 in the NanoBiT assay but exhibited near total selectivity for AC1-C1b/CaM over the AC8/CaM constructs in the FP assays. We will discuss possible explanations for this reversal of selectivity below.The next most potent hits in cells were 3 had the greatest decrease in cell viability of 25% at its AC1/CaM IC50 (17.9 ± 1.15 μM) and 70% at 100 μM. For hits 7, 13, and 18, cell viability was between 96–100% at their respective AC1/CaM IC50 values. For 7 and 13, cell viability was reduced by ∼50% at the highest concentration tested (316 μM), but 90% cell viability was observed for 18 at this concentration. From the remaining pilot screen, only hits 1, 2, 9, and 11 exhibited a reduction in cell viability greater than 10% at their respective AC1/CaM IC50 values. Although 1 was the most potent in the FP assays, this was not the case in the NanoBiT assay. 1 was more potent in the AC8/CaM NanoBiT assay, with IC50 values of 8.4 and 32.9 μM in the AC8 and AC1/CaM NanoBiT assay, respectively. The remainder of the pilot screen hits tested in vitro had AC1/CaM IC50 values between 20 and ∼100 μM or did not inhibit the AC/CaM PPI in the NanoBiT assay. For simplicity, the remaining sets were separated by a range of IC50 values from the AC1/CaM NanoBiT assay: Set A—IC50 values from 1 to 20 μM: 3, 7, 12, 13, and 18; Set B—IC50 values from 21 to 30 μM: 4, 15, and 21; Set C—IC50 values from 30 to 40 μM: 1, 6, and 10; Set D—IC50 values from 41 to 150 μM: 2, 5, 8, 9, 11, 14, and 20; Set E—No Inhibition in NanoBiT assay: 16, 17, and 19.With respect to cell viability, amongst all the pilot screen hits, 1H-15N HSQC spectra of 15N-CaM in the presence or absence of the compound. We tested hit compounds 12, 13, 15, 18, and 21 at 5 equivalent molar excess of CaM concentration and observed chemical shift perturbations (CSP) for multiple CaM residues  for each compound, in AC1-HEK Δ3/6 KO cells. Hit 12 displayed the highest potency against AC1 at 4.09 μM, with 15 following closely at 4.89 μM; both of these compounds were equally efficacious, displaying ∼75% inhibition of AC1 activity (data not shown). Hits 18 and 21 were slightly less potent at 6.70 and 8.77 μM, respectively. 18 and 21 also displayed lower efficacies, at ∼70 and ∼50%, respectively. Finally, hits 13 and 20 were significantly less potent at AC1 than other hits evaluated, at 31.0 and 66.3 μM, respectively.From the hits identified among FP screens and NanoBiT assays, six were selected for characterization of activity against AC1, based on their potency and selectivity profiles as well as favorable drug-like properties. Hits from the CDI library  the combined potency and selectivity in the FP assays, 2) efficacy for PPI inhibition in the NanoBiT assay, and 3) drug-like physicochemical properties. To accomplish this, we utilized HEK Δ3/6 KO cells expressing AC1 or AC8. The data shown in 50 values (µM) for each compound, in AC1- and AC8-HEK Δ3/6 KO cells, respectively. Testing of the dithiophene compounds, referred to hereafter as CDI analogs (22–33) were purchased from ChemDiv, along with the original dithiophene hit 15. For the first piperidine series (22–24), SAR was relatively flat with modest changes to either the piperidine or alkyl group on the thiophene leading to equipotent analogs. 24 was the most potent of this cohort versus AC1 with an IC50 value of 2.75 μM. This molecule also was equipotent against AC8 with an IC50 values of 2.70 μM. Moving from a piperidine to the matched molecular pair N-alkylated piperazine analogs  provides a slight reduction in AC1 activity (2—3-fold) compared to the piperidine containing counterpart. The piperazine modification also had varying effects on AC8, particularly with the ethyl-thiophene derivatives  slightly favoring AC8 over AC1. The next two analogs  contained a fused cyclic alkane to the central thiophene of the scaffold, as opposed to methyl or ethyl substitution. Each exhibited marked reduction of activity against both AC1 and AC8 compared to nearest neighbor analogs non-cyclic analog. The reduction was greater against AC1, thus making these analogs more selective for AC8, with 28 being 2-fold more potent at AC8. In both AC1- and AC8-overexpressing HEK cells, several of these compounds displayed approximately 100% inhibition of cAMP accumulation, as well as low-micromolar IC50 values at both AC1 and AC8. 29 maintained the N-methylpiperazine and ethyl substituent off the central thiophene, but swapped the second thiophene heterocycle for a phenyl ring. When compared to its matched molecular pair in 15, 29 exhibited about a 2- and 3-fold reduction in AC1 and AC8 potency, respectively. 30–32 swapped the piperazine for a morpholine moiety. Notably, this modification decreased both AC1 and AC8 potency for the matched molecular pairs that incorporated either the piperazine or piperidine with one exception. 32 actually displayed an improved potency against A23187-stimulated cAMP accumulation in AC1-HEK cells with an IC50 at AC1 of 0.89 µM. This molecule was also modestly selective over AC8 with an IC50 of 1.86 µM. Interestingly, although 32 is slightly more potent against AC1, the AC8 potency makes this compound the most potent AC8 inhibitor known to date. The final analog in this SAR set was 33, which moved from the N-cyclic alkane substituent and incorporated a 2-aminopyridine. This compound displayed similar potency to the piperidine series (22–24), with modest selectivity for AC8. Concentration-response curves for selected analogs  are presented in Among the hits that were identified and characterized for AC1 activity inhibition, the dithiophene scaffold of compound  analogs , with A215, 24, 25, and 32 in cAMP assays against AC2 and AC5 as representative isoforms from Groups II and III, respectively, of AC isoforms. We used AC2-HEK Δ3/6 KO and AC5-HEK Δ3/6 KO cells and tested each of the four compounds at 30 μM, assessing percent inhibition, shown in 15 displayed modest inhibition at AC2 and AC5 . Compound 25 also partially inhibited AC2 and AC5 activity . 15 and 25 are structurally almost identical, differing only in the substituent on the central thiophene (ethyl on 15 versus methyl on 25), which may explain why these had similar activity against AC2 and AC5. On the other hand, compounds 24 and 32, having a piperidine and morpholine heterocycle, respectively, showed very little inhibition against AC2 and AC5 (<16%). Interestingly, in our previous studies we have observed AC1 inhibitors to modestly potentiate AC2 at 10 and 30 μM, thus, the inhibition at 30 µM was a bit unexpected but may be a result of the different mode of action for this scaffold. This will be investigated in future studies.To determine whether these compounds were selective for AC1 and AC8 over other isoforms, we tested 2+ dependent CaM binding has been previously established  that incorporated the residues on AC1 or AC8 where Caablished . In the ablished . Furtherablished . Therefohe assay . A drawb50 and percent inhibition relative to the positive control (100 μM CDZ = 100% inhibition) in the AC1/CaM FP assay. In addition to the reduction in hits from the CDI library (32–9), five compounds identified in the FDA-approved MMSP and ChemBridge library screens did not exhibit significant inhibition of AC1/CaM in the FP assay after fresh powder stocks were ordered. Two of those compounds were from the ChemBridge DIVERSet library, two were from the Microsource spectrum collection (ethyl quinine and rivastigmine tartrate), and one was from the FDA-approved library (nicotine ditartrate). Compounds that exhibited poor potency or inhibition in the AC1/CaM FP assay were tested in the AC8/CaM FP assays to gather information about what chemical scaffolds/structures tended to be more selective for the AC8/CaM interaction(s) over the AC1/CaM interaction. As a result, 25 of the original 54 hit compounds were advanced for further characterization.Approximately 21,000 compounds from 4 different chemical libraries were screened using the AC1/CaM FP assay. The pilot screen identified 54 compounds . However, due to library duplication, three compounds  were identified as hits in the FDA-Approved and MMSP libraries. An additional three compounds, Chicago Sky blue, Protoporphyrin IX, and Chlorophyllide Cu complex, were removed after their chemical structures were unfavorable for further development. The availability of ChemDiv CNS library stocks permitted initial concentration-response curve assessments to be made before ordering powder stocks. From the original 32 ChemDiv hits, 9 were advanced to the next phase of screening based on their approximate IC1 and 2, contain a phenothiazine structure. These hits have the same phenothiazine scaffold as the known CaM antagonist trifluoperazine (TFP). This common substructure could indicate that the AC/CaM inhibition observed for 1 and 2 results from CaM binding rather than AC binding. However, TFP poorly inhibited AC1/CaM in the FP assay with only 30% inhibition at 100 μM for AC1/CaM. Further, our prior testing with TFP in the AC8/CaM FP assays found that it could inhibit AC8-Nt/CaM (∼85% at 100 μM) but did not inhibit AC8-C2b/CaM (3). Despite their structural similarities, 2 has been found to reduce pain caused by cancer treatment as an oral rinse, alleviate the pain that accompanies a propofol injection, and reduce lower back pain as an intradiscal injection , and blockade of the GABA receptor  is a long carbon chain or linker (6 carbons or more). As these linkers will afford flexibility to these compounds, it may be possible that these aliphatic “tails” allow for more significant inhibition by binding to a hydrophobic pocket. However, further studies examining the binding site would need to confirm this notion. Apart from 20, all the validated hits from the CDI library inhibited the AC1/CaM FP assay but could not inhibit both AC8/CaM FP assays. However, the hits from the CDI library exhibited a lower degree of inhibition in the AC1/CaM FP assay as compared to the hits from the FDA-approved or the MMSP libraries.Characterization of hits centered around CRC analysis of the primary AC1/CaM FP assay, with counter screening efforts to identify hit compounds that selectively inhibited the AC1/CaM interaction over the AC8/CaM interaction(s). The two most potent hits identified in the FP pilot screen, njection . Althougreceptor . Acting Of the 25 compounds, 21 were advanced for testing in NanoBiT assays. The goal of this AC1/CaM FP HTS was to identify novel structures capable of disrupting the AC1-C1b/CaM and AC1/CaM interactions. In pursuit of this goal, two assays were developed to detect this interaction in both a biochemical setting and in a living cellular environment. Screening ∼22,000 compounds from four unique chemical libraries has yielded small molecule inhibitors with interesting and novel chemical scaffolds that can disrupt the AC1/CaM interaction.12 was the most potent compound in the AC1/CaM NanoBiT assay. 12 (Benzbromarone) contains a 1-Benzfuran scaffold with an ethyl group substituted at the C-2 position and a 3,5-dibromo-4-hydroxybenzyl group at the C-3 position. Although 12 is labeled as a uricosuric agent and a known xanthine oxidase inhibitor, 12 was never approved by the FDA due to reports of acute liver toxicity . 15 was then confirmed as an AC1/AC8 non-selective hit against full-length AC1- and AC8-CaM in the NanoBiT assay . Compound 15 also had a number of favorable drug like properties (molecular weight = 415 g/mol and LogP = 0.53) and possessed multiple sites amenable to explore SAR. Lastly, we observed that compound 15 shared some structural overlap with a benzamide series of compounds that are known inhibitors of AC1 activity with selectivity vs. AC8  via an amide, which directly overlaps with the benzamide series (32). Importantly, 32 is the most potent inhibitor of AC8 activity known to-date, although this compound also potently inhibits AC1 activity. Overall, the limited SAR on this series suggests that AC1 and AC8 potency and selectivity can be tuned individually. AC1 activity was favored more by a methyl-substituent on the thiophene ring, whereas AC8 activity was favored more so by the ethyl in the same position. The cylcohexane-fused thiophene selectivity was highly dependent on the nature of the N-heterocycle with piperazine favoring AC8 activity and morpholine favoring AC1. These preliminary SAR data points will now inform design of future analogs to tune both AC1 and AC8 selectivity inhibitors from within the same series. As previously mentioned, some differences in potency and selectivity in cellular assays may be attributed to the differential interactions of AC1 and AC8 with CaM. Additionally, it is possible that other proteins within the cellular environment may affect the activity of these compounds.As we characterized the hits from our FP screen, we began to focus on the unique chemotypes we identified in the process. Among the AC1-selective hits with regard to disruption of the AC1 peptide-CaM interaction in the FP assay was hit  vs. AC8 . We selee series . The cen1H-15N HSQC spectra obtained for 12, 18, and 21 at 5EQ molar excess showed CaM was fully saturated or in fast exchange. To be in fast exchange, peaks exhibiting chemical shifts in the presence of a compound must move smoothly from free to bound (red)  . In inteAdcy8 mRNA expression increased in the anterior cingulate cortex (ACC) in a mouse model of neuropathic pain, although AC8 knockout does not play a role in mechanical hypersensitivity after inflammation (s and forskolin. This dithiophene scaffold provides a novel AC1/AC8 inhibitor scaffold which is highly potent and may potentially be useful for treatment of chronic pain and anxiety.Through development of a novel fluorescence polarization assay, screening of over 21,000 compounds for inhibition of AC1 and/or AC8, and validation of activity in novel NanoBiT assays, we have discovered a novel dithiophene scaffold. Interestingly, the dithiophene scaffold shares structural similarities with the AC1 inhibitor benzamide series . Unlike ammation . This su