Most tested compounds induced cell death through apoptosis and necrosis. There was no correlation established between beta adrenoblocker anticancer activity and their selectivity to beta adrenoreceptors.Beta adrenoblockers are a large class of drugs used to treat cardiovascular diseases, migraines, glaucoma and hyperthyroidism. Over the last couple of decades, the anticancer effects of these compounds have been extensively studied. However, the exact mechanism is still not known, and more detailed studies are required. The aim of our study was to evaluate the anticancer activity of beta adrenoblockers in non-small cell lung cancer cell lines A549 and H1299. In order to find the relationship with their selectivity to beta adrenoreceptors, selective  and non-selective  beta blockers were tested. The effect on cell viability was evaluated by MTT assay, and the activity on cell ability to form colonies was tested by clonogenic assay. The type of cell death was evaluated by cell double staining with Hoechst 33342 and Propidium iodide. The most active adrenoblockers against both tested cancer cell lines were propranolol and betaxolol. They completely inhibited lung cancer cell colony formation at 90% of the EC Lung cancer is the most common type of cancer and a leading cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018 .The catecholamines norepinephrine and epinephrine, also called noradrenaline and adrenaline, are neurotransmitters that tare simultaneously released from the sympathetic nervous system and adrenal gland as a response to physiological and psychological stress, otherwise called flight-or-fight response. They regulate the activity of organs and cells related to stimulation of the sympathetic nerve system. According to scientists, the elevated concentration of catecholamines promotes growth of lung adenocarcinoma micro metastasis . ConversBeta adrenoblockers are a large class of drugs mainly used to manage cardiovascular diseases, migraines, glaucoma and hyperthyroidism. Over the last couples of decades, the anticancer effects of these compounds have been extensively studied. The first evidence about beta adrenoreceptor involvement in lung cancer development occurred in 1989 . AccordiAccording to the results of clinical trials, beta adrenoblockers increase the survival rate of patients suffering from breast, prostate, ovarian, colorectal, skin and lung cancer. In recent years, new evidence has shown that overall survival of patients, who received beta adrenoblockers combined with radiotherapy, increased by 22% compared to the control group . DespiteAlthough the anticancer activity of beta adrenoblockers has been observed for almost two decades, no unified anticancer mechanism of action was discovered. Considering the problem and prevalence of lung cancer treatment, we decided to investigate the anticancer activity of beta adrenoblockers in the NSCLC lines A549 and H1299. These cell lines are derived from lung adenocarcinomas, but they represent different cell types. A549 cell line is a type II alveolar epithelium of characteristic morphology and functions ,23, and In this work, the beta adrenoblockers’ effect on cell viability, clonogenicity and the type of cell death was investigated. As the model compounds for our study, we chose the first-generation beta adrenoblockers acting as antagonists on both beta-1 and beta-2 adrenoreceptors . Also, the second-generation beta adrenoblockers, which bind stronger to the beta-1 receptors, were selected . Pindolol also has partial agonist activity ,28. We a50 values of both most active compounds, propranolol showed a stronger effect on viability of the H1299 cell line, while betaxolol acted in the same way in both cell lines (p < 0.05) (All tested compounds reduced NSCLC cell viability at the highest used concentration of 500 µM. Propranolol and betaxolol were the most active compounds in both cell lines a. After  < 0.05) b.50 values were 119.3 ± 12.7 µM and 98.8 ± 10.3 µM in A549 and H1299 cell lines, respectively). Betaxolol activity was about twice lower compared to propranolol .Propranolol possessed the highest antiproliferative activity  (The tested beta adrenoblockers showed a different effect on NCLSC cell colony formation . Propran < 0.05) a,b. All Slightly weaker than propranolol and betaxolol, the number and area of A549 cell colonies was reduced by metoprolol at the higher used concentration in this study. The non-selective beta blockers timolol and pindolol and the selective beta blocker esmolol were found to possess a similar activity between them. Also, these non-selective beta blockers were less active compared to propranolol and betaxolol. The lowest inhibition of A549 cell colony formation ability was established for the selective beta blocker atenolol.p < 0.05). The most active compounds were propranolol and betaxolol, while esmolol and metoprolol showed slightly lower activity (p < 0.05).Similar trends of the effect of beta blockers on the H1299 cell line have been identified in the study. All compounds except atenolol had a statistically significant reduction in the number of colonies and the area occupied by these cells  (p > 0.05).Only betaxolol at a concentration of 10% of EC < 0.05) c,d. NoneMost tested compounds induced cell death through apoptosis and necrosis. In A549 cell lines, apoptosis was mainly induced, while in H1299 cell line compounds induced both apoptosis and necrosis .50 value (p < 0.05) . Only atenolol at a lower concentration did not induce apoptosis in the H1299 cell line (p > 0.05)  a. No sta > 0.05) b.No statistically significant difference was found between the beta adrenoblockers’ effect on cell apoptosis between cell lines.p < 0.05) (p < 0.05).Beta adrenoblockers mainly induced necrosis in H1299, but not in the A549 cell line c. All of < 0.05) d. Metopr50 values can be explained by the fact that the expression of receptors varies between different types of cell lines. In general, it is thought that non-selective beta adrenoblockers have a stronger effect on cell viability than that of beta-1 selective compounds [The effect of beta adrenoblockers on cell viability is a common subject of different scientific studies. Propranolol after 72 h of incubation inhibited cell viability of lung cancer A375 and melanoma P8 cell lines at concentrations 77.30 and 60.30 μM, respectively . Similarp < 0.05), while betaxolol activity was the same in both cell lines (p > 0.05). However, both NSCLC cell lines, A549 and H1299, possess the K-Ras gene mutation that is thought to be responsible for lower sensitivity to non-selective beta adrenoblockers [We found that the antiproliferative activity of beta adrenoblockers is not correlating with their selectivity to the receptors and might be dependent on the compound lipophilicity and membrane stabilizing activity. Beta-2 adrenoreceptors in lung adenocarcinoma are responsible for lymphatic permeation and vascular invasion . Howeverblockers . In addiblockers .The effect of beta adrenoblockers on colony formation is not a common subject of scientific research. Min discovered that propranolol and atenolol at 10 µM concentrations suppresses the growth and ability of A549 and H0CC-15 cells, treated by NNK, to form colonies . In thisZhang concluded that a 100 μM concentration of metoprolol does not cause apoptosis in pancreatic cell lines . In thisIn another study, propranolol at 50 μM concentration did not cause apoptosis of gastric adenocarcinoma in the BGC-823 and SGC-7901cell lines, but in combination with radiotherapy after 48 h incubation it induced apoptosis, clonogenic survivability and cell viability . In our In order to evaluate impact of beta adrenergic receptors on the type of cell death, the effect of the beta-2 selective adrenoblocker butoxamine, non-selective propranolol and beta-1 selective metoprolol were used to induce apoptosis in a PC-2 pancreatic cancer cell line . The apoAtenolol (99% pure), betaxolol (96% pure), esmolol (98% pure), timolol (99% pure) and pindolol (99% pure) were purchased from Abcam , metoprolol (98% pure) was purchased from Alfa Aesar , and propranolol (99% pure) was purchased from Acros Organic . All tested compounds were dissolved in dimethylsulfoxide  which was obtained from Sigma-Aldrich Co. .TrypLE Express, Dulbecco’s modified Eagle high glucose medium (DMEM GlutaMAX), fetal bovine serum (FBS), penicillin/streptomycin solution , and phosphate buffered saline  were purchased from Gibco . The aqueous 16% paraformaldehyde solution (PFA), the Hoechst 33342 (1 mg/mL) solution, and the Propidium iodide (1 mg/mL) solution were obtained from Thermo Fisher Scientific .3--2,5-diphenyltetrazolium bromide  and crystal violet (≥90%) were purchased from Sigma-Aldrich Co. . Ethanol (96.6%) was obtained from Stumbras, LLC .All cell culture plastic ware was purchased from Thermo Fisher Scientific, Corning  and Techno Plastic Products .2. All cell cultures routinely were grown to 70% confluence and trypsinized with 0.125% TrypLE™ Express solution  before passage. They were used until passage 20.Human NSCLC cell lines A549 and H1299 were obtained from the American Type Culture Collection . Both cell lines were cultured in Dulbecco’s Modified Eagle’s Medium GlutaMAX , supplemented with 10% FBS and 1% antibiotics. Cells were incubated at 37 °C temperature in a humidified atmosphere containing 5% COCell viability was evaluated by MTT assay, as described elsewhere . BrieflyAfter 72 h, 20 µL of MTT 0.5 mg/mL solution was added into each well of a 96-well plate, and cells were incubated at 37 °C for 3 h. Next, the supernatant was removed and the formed formazan crystals were dissolved in 100 µL of DMSO. The absorbance was measured at 570 nm and 630 nm reference wavelengths using a multi-detection microplate reader. Experiments were repeated three times independently and the results were presented as means ± SD.50) values, reducing cell viability by 50%, were calculated.Applying Hill fit to compound dose—cell metabolic activity (absorbance) curves, the half maximal effective concentration  and analysed using Genesys software . The number and percentage area of colonies were calculated.The compound effect on cell colony formation was tested by clonogenic assay as described elsewhere . Briefly2. Next, either 10 or 90% of EC50 values of adrenoblockers were added to the wells. After 72 h, 3 µL of aqueous solution of Hoechst 33342 (1 mg/mL) and 1 µL of aqueous solution of Propidium iodide (1 mg/mL) were added to each well. After 10 min, images of cells were taken by an inverted fluorescent microscope . Apoptotic and necrotic cells were counted, and the percentage number of cells was calculated.Lung cancer cells were seeded in 24-well plates at a concentration 15,000 cells/well and incubated for 24 h at 37 °C in an atmosphere containing 5% COHoescht 33342 is a cell permeable dye and binds to the DNA in cells. Therefore, the stained nuclei of vital cells emit blue-cyan fluorescent light and are visible as blue colored. Apoptotic cells display condensed DNA and fragmented nuclei in blue. Propidium iodide is not cell permeable and binds to the double-stranded DNA of cells where the plasma membrane has been compromised. Non-viable, necrotic cells are seen as red colored. Propidium iodide does not stain live or early apoptotic cells due to the presence of an intact plasma membrane .t-test was used and p-values were calculated. A value of p < 0.05 was considered as the level of significance.A statistical analysis was performed using Microsoft Office Excel 2007 software , evaluating an average and standard deviation of at least three measurements. A Student’s 50 values were 251.3 ± 14.6 µM and 252.2 ± 7.6 µM in A549 and H1299 cell lines, respectively). Therefore, it could be concluded that the cytotoxicity of beta adrenoblockers against the tested lung cancer cell lines is not dependent on their selectivity on beta adrenoreceptors.Our results show that both selective and non-selective beta adrenoblockers, especially betaxolol and propranolol, reduce the viability of the NSCLC cell lines H1299 and A549. Propranolol, which is a non-selective beta adrenoblocker, showed the strongest effect on H1299 cell viability, while the selective agent betaxolol possessed a similar activity against both tested cell lines. Betaxolol activity was about twice lower compared to propranolol (ECOverall, it has been established that betablockers inhibit the formation of cell colonies and induce apoptosis and necrosis. No statistically significant difference was found between the beta adrenoblocker effect on cell apoptosis in both NSCLC cell lines. In A549 cell lines, apoptosis was mainly induced, while the H1299 cell line compounds induced both apoptosis and necrosis.The anticancer activity of the tested beta adrenoblockers is not related to the selectivity to beta adrenoreceptors. Therefore propranolol and betaxolol showed the strongest anticancer activity in vitro, and both compounds are worthy of further investigation and could be considered as therapeutic alternatives with regard to solving chemoresistance.


In endoscopic core ESCC biopsies taken from 61 patients who underwent neoadjuvant chemotherapy (NAC) (5‐fluorouracil and cisplatin), low MRE11A and high UBQLN4 protein levels were associated with reduced pathological response to NAC . Multivariable analysis of surgically resected ESCC tissues from 59 patients revealed low MRE11A and high UBLQN4 expression as independent factors that can predict shorter overall survival . Suppression of MRE11A expression was associated with cisplatin resistance in ESCC cell lines. Additionally, MRE11A was found to be ubiquitinated after cisplatin treatment. We observed an amplification of UBQLN4 gene copy numbers and an increase in UBQLN4 protein levels in ESCC tissues. Binding of UBQLN4 to ubiquitinated‐MRE11A increased MRE11A degradation, thereby regulating MRE11A protein levels following DNA damage and promoting cisplatin resistance. In summary, MRE11A and UBQLN4 protein levels can serve as predictors for NAC response and as prognostic markers in ESCC patients.Resistance to standard cisplatin‐based chemotherapies leads to worse survival outcomes for patients with esophageal squamous cell carcinoma (ESCC). Therefore, there is an urgent need to understand the aberrant mechanisms driving resistance in ESCC tumors. We hypothesized that ubiquilin‐4 (UBQLN4), a protein that targets ubiquitinated proteins to the proteasome, regulates the expression of Meiotic Recombination 11 Homolog A (MRE11A), a critical component of the MRN complex and DNA damage repair pathways. Initially, immunohistochemistry analysis was conducted in specimens from patients with ESCC  and demonstrated their clinical utility. Briefly, we showed that cisplatin treatment promotes Meiotic Recombination 11 Homolog A (MRE11A) ubiquitination. Binding of ubiquilin‐4 (UBQLN4) to ubiquitinated‐MRE11A increased MRE11A degradation, thereby promoting cisplatin resistance. Both MRE11A and UBQLN4 can predict neoadjuvant chemotherapy response and serve as prognostic markers in ESCC patients. AbantibodyAJCCAmerican Joint Committee on CancerCo‐IPCo‐ImmunoprecipitationDSBdouble‐strand breakEACesophageal adenocarcinomaESCAesophageal carcinomaESCCesophageal squamous cell carcinomaEVempty vectorFFPEformalin‐fixed paraffin‐embeddedIFimmunofluorescenceIHCimmunohistochemistrymAbmonoclonal antibodyMRE11AMeiotic Recombination 11 Homolog AMRNMRE11‐RAD50‐NBS1NACneoadjuvant chemotherapyNSnot significantOSoverall survivalOVoverexpressionpAbpolyclonal antibodySDstandard deviationTCGAThe Cancer Genome AtlasUBAubiquitin‐associated domainUblubiquitin‐like domainUBQLN4ubiquilin‐41Esophageal cancer represents the 7th cause of cancer death globally . The twoThe MRE11‐RAD50‐NBS1 (MRN) complex has an important role in DDR and chemotherapy treatment. MRN complex sensors and orchestrates DDR in double‐strand breaks (DSB), stalled replication forks, dysfunctional telomeres, and immune responses , 18. AltUbiquilin family proteins function as adaptors between ubiquitinated proteins and the proteasome , 28, 29.MRE11A gene are rare in ESCC tumors. UBQLN4 has a role in controlling nuclear protein levels by targeting ubiquitinated proteins to the proteasome  ESCC patients who underwent NAC followed by surgery at Keio University Hospital, Department of Surgery, Tokyo, Japan, between 2011 and 2016. These patients did not undergo adjuvant treatment. Specimens met the following criteria: (a) histologically proven ESCC, (b) no previous history of chemotherapy or chemoradiotherapy for any malignancies, and (c) no microscopic residual tumor (R0). For NAC, cisplatin plus 5‐fluorouracil was repeated twice every 3 weeks (day 1: cisplatin by 80 mg·m mg·m−2) . Tumor rH‐score values. Univariate and multivariate analysis was performed to determine associations between H‐scores and clinical variables.Formalin‐fixed paraffin‐embedded tissues from 59 surgically resected ESCC primary tumors were obtained from patients who underwent up‐front surgery at Keio University Hospital from 1997 to 2002 . IHC forAll of the experiments followed World Medical Association Declaration of Helsinki and the NIH Belmont Report principles. Tissue specimens were coded according to HIPAA recommendation. This study was approved by Keio University School of Medicine Ethics Committee with a registration number of 2016‐0233 and 2016‐241. All human samples and clinical information for this study were obtained according to the protocol guidelines approved by the Joint Institutional Review Board of Providence Saint John's Health Center/ Saint John's Cancer Institute and the Western Institutional Review Board (USA).2.22. All human cell lines have been authenticated using short tandem repeat profiling within the last 3 years. All experiments were performed with mycoplasma‐free cell lines.Established human ESCC cell lines TE‐4 (CVCL_3337), TE‐8 (CVCL_1766), and TE‐10 (CVCL_1760) were obtained from Keio University. Cell lines were cultured in Dulbecco's modified Eagle's medium or RPMI supplemented with 10% FBS at 37 °C with 5% CO2.3−1.MRE11A EX‐q‐0491‐M35 and the empty control vector EX‐EGFP‐M35 were from Genecopoeia, Rockville, MD, USA; ubiquitin B pCMV6 vector and the empty vector (EV) were from Origene, Rockville, MD, USA; UBQLN4 was cloned in pLNCX2 plasmid as described previously . For stam of cisplatin  supplemented medium for 3 days. Afterward, the medium was replaced and the cell lines were cultured until the resistant clones proliferated; the treatment was repeated with 3 μm and then 5 μm of cisplatin supplemented medium. Then, the cell lines were continuously cultured in 2.5 μm of cisplatin for 4 weeks. Cell lines were recovered in cisplatin‐free medium and used for further assays. For knockdown experiments, TE‐4 cell lines were transfected with 20 nm pool siRNA UBQLN4 or nontargeting Pool  using jetPRIME Polyplus transfection . TE‐8 and TE‐10 cell lines were transfected with 50 nm pool siRNA MRE11A or nontargeting Pool  using jetPRIME Polyplus transfection.For establishment of cisplatin‐resistant ESCC cell lines, TE‐8 and TE‐10 cell lines were cultured in 2 μ2.4mantra snap Software 1.03 . H‐scores were calculated using the inform 2.4 software (Perkin Elmer) and following manual instructions. Briefly, the tumor area was segmented from the stromal area and nuclei/cytoplasm compartments were distinguished by detecting the intensity of hematoxylin and/or 3,3'‐diaminobenzidine (DAB) staining. The optical signal threshold to classify the score into 4‐bins was set to 0.05, 0.12, and 0.2. Five slides per case were analyzed and the average H‐score was then used as the final value. The cutoff values for UBQLN4 and MRE11A were determined by considering H‐score values for the mean value observed in normal adjacent epithelia esophagus tissues plus 10 SD.Endoscopic biopsy specimens and surgically resected ESCC tumors were stained with UBQLN4 monoclonal antibody  and/or MRE11A polyclonal antibody  as previously described . Images 2.5m MG‐132  and/or 5 μm cisplatin for 12 h. After incubation, cell lines were washed and lysed in Co‐Immunoprecitation (Co‐IP) buffer  by gently pipetting. The whole‐cell (WC) lysates were quantified by bicinchoninic acid assay, and 250 μg of WC lysate  was incubated with UBQLN4 mAb  and mouse (G3A1) mAb control ; or UBQLN4‐Ps318 pAb  and mouse (G3A1) mAb control ; or MRE11A pAb  and normal rabbit pAb control ; or DDDDK tag pAb and normal rabbit pAb control  in Co‐IP buffer. Immunocomplex was further incubated with Dynabeads™ Protein A  for 1 h at 4 °C. Only for the experiment showed in Fig. m of recombinant human USP2 catalytic domain protein  for 30 min at 37 °C, as indicated. Beads were washed three times with Co‐IP buffer, recovered, and boiled in Fluorescent Master Mix for 5 min at 95 °C in a dry bath. After centrifugation, the supernatants (SN) were recovered and protein concentration was adjusted to 1 μg·μL−1 with 1× MM reagent. Samples were analyzed by automated western blot system [Cell lines were transfected with MRE11A and UBB plasmids as indicated in each experiment. After 24 h, cell lines were treated with 5 μt system , 34.2.67/mL. The sorting microfluidic chip was precoated with On‐chip T‐buffer before loading the sample. After priming the chip, excessive T‐buffer was removed from all reservoirs, and replaced with fresh culture medium. Then, the prepared samples were loaded. Gates were set and the samples were sorted according to the cell size and GFP positivity of interest. The sorted samples were retrieved, and the sorting process was repeated three times to increase the purity of the sorted cell lines. After sorting, cell lines were immediately cultured until 80% confluence and then frozen.The microfluidic chip‐based cell sorter, On‐chip Sort , equipped with blue (488 nm), violet (405 nm), and red (637 nm) lasers, was used according to the manufacturer's protocol. TE‐8 and TE‐10 UBQLN4‐OV cell lines were harvested, centrifuged, and diluted to 1 × 102.74) were seeded in 8‐well Falcon™ chambered culture slides (Fisher Scientific) and incubated for 48 h, followed by treatment with 5 μm cisplatin for 12 h. After that, cell lines were fixed and the protocol was followed as described in [imagej software .Cell lines (1–1.5 × 10ribed in  except t2.83) were seeded in a 96‐well plate. The number of viable cells was assessed using a Cell Titer‐Glo Luminescent  according to the manufacturers' instructions. For colony formation, ESCC cell lines (2 × 103) were seeded in a 6‐well plate and after 12 days of incubation processed as previously described [ESCC cell lines  with or without 5 μm MG‐132 at different time points . After incubation times, cell lines were harvested and processed for protein extraction. Western blot for MRE11A and β‐actin was performed and their expression was quantified over time and adjusted to β‐actin levels [TE‐10 cell lines (80% confluency) were incubated with 200 μg·mLn levels , 34, 35.2.106 cells/dish) were cultured in 100‐mm dishes and harvested with 3 mL cold PBS/phosphatase inhibitor buffer. Cells were centrifuged and the WC pellet was gently suspended in 500 µL 1× hypotonic buffer and incubated for 15 min on ice. Then, 25 µL of detergent was added to induce cell lysis. After cell lysis, the cytoplasmic fraction (supernatant) was separated from the nuclear fraction (pellet) by centrifugation (for 30 s at 14 000 g). Then, the nuclear fraction (pellet) was resuspended in 50 µL of the complete lysis buffer and incubated with 2.5 µL detergent for 30 min on ice. The nuclear lysates were centrifuged for 10 min at 14 000 g. The nuclear fraction (supernatant) was then collected. Both nuclear and cytoplasmic fractions were analyzed by automated western blot.Nuclear and cytoplasmic fractions were isolated from the TE‐10 and TE‐8 cell line with the Nuclear Extract Kit . Cells  and the protein concentration was adjusted to 0.5–1 μg·μL−1. The results were analyzed using the Compass Software (Protein Simple) and imagej software . The primary Ab dilutions are shown in Table Automated western blot was performed according to the manufacturer's protocol . Br2.12t‐test was used for normally distributed data, and the nonparametric Wilcoxon rank‐sum test was used for non‐normally distributed data. One‐way ANOVA test and Bonferroni post hoc test was applied in the quantification of IF assays. Two‐way ANOVA test and the Bonferroni post hoc test were applied for cell proliferation and drug sensitivity analysis. Correlation analyses were performed using Pearson's or Spearman's correlation coefficient (r) according to the data distribution. OS was compared using the Kaplan–Meier method and log‐rank test. Multivariable analysis was performed by the Cox proportional regression model to analyze the independent predictor for OS. Significant factors considering the covariate factors and age were included for the multivariable analysis. A two‐sided P < 0.05 was considered statistically significant: *P < 0.05; **P < 0.01; ***P < 0.001 and NS, not significant. All analyses were performed with graphpad prism 5  or r version 3.5.0 , and th33.1MRE11A expression was analyzed in the The Cancer Genome Atlas (TCGA) esophageal carcinoma (ESCA) dataset [n = 186) of which all 95 ESCCs were analyzed  in about 4% (4 of 95) and reduced in 15% (z‐score ≤ −1.5) of ESCC patients  clinically annotated  compared to primary ESCC tumors  had a worse prognosis compared to those with high MRE11A expression  = 5.11, 95% confidence interval (CI) 1.45–18.03, Table To further elucidate the clinical significance of MRE11A, IHC was performed and SCC Fig. A. PatienH‐score values demonstrated that MRE11A expression was significantly increased in responder (n = 8) compared to nonresponder ESCC patients who underwent NAC  in ESCC cell lines and analyzed them for cisplatin sensitivity. MRE11A knockdown promoted cisplatin resistance in ESCC cell lines Fig. . ConversIn order to determine whether MRE11A was associated with cisplatin resistance, we established two cisplatin‐resistant ESCC cell lines. Cisplatin resistance in ESCC cell lines was confirmed by drug sensitivity assays Fig. ,J. In ag3.3We first examined the expression of MRE11A and UBQLN4 protein levels in three ESCC cell lines . Western blot analysis showed that when ESCC cell lines have increased UBQLN4, they consistently have low MRE11A protein levels Fig. . EctopicOur hypothesis is that during DNA damage ubiquitinated‐MRE11A levels increased in the DNA damage sites and UBQLN4 may help in promoting the proteasome‐mediated degradation. Thus, we examined the interaction between MRE11A and UBQLN4 using Co‐IP assays. For Co‐IPs, the ESCC cell lines were treated with cisplatin (to enhance the levels of ubiquitinated‐MRE11A and promote the interaction with UBQLN4) and with MG‐132 inhibitor . As shown in Fig. Then, we performed experiments to assess the changes in ubiquitinated‐MRE11A after cisplatin‐induced DNA damage. To do this, we transfected TE‐10 UBQLN4‐OV cells with UBB‐DDK and used anti‐DDK antibody to immunoprecipitate endogenous tagged ubiquitinated‐MRE11A in cisplatin‐treated ESCC cell lines in the presence or absence of MG‐132. To demonstrate that ubiquitinated‐MRE11A was bound to the beads, we pretreated the immunocomplexes with buffer or the recombinant catalytic domain of the de‐ubiquitinase USP2. If the interaction would be mediated by ubiquitination, USP2 would reduce the binding of MRE11A in the immunocomplexes. Ubiquitinated‐MRE11A levels were increased in ESCC cell lines treated with cisplatin in the presence of MG‐132 compared to absence of MG‐132 Fig. A. MoreovUsing Co‐IPs, we assessed for ubiquitinated‐MRE11A binding to UBQLN4. To do that, we transfected TE‐10 UBQLN4‐OV cells with UBB‐DDK and used anti‐DDK antibody to co‐immunoprecipitate endogenous ubiquitinated‐MRE11A DDK‐tagged and UBQLN4 in cisplatin‐treated ESCC cell lines in the presence of MG‐132. Ubiquitinated‐MRE11A co‐immunoprecipitated with UBQLN4 in ESCC cell lines Fig. . These rIn order to analyze MRE11A protein stability in the presence of high UBQLN4 levels, cycloheximide chase assays were performed in UBQLN4‐OV cell lines and compared to respective control EV cell lines. A significant decrease was observed for MRE11A protein levels in UBQLN4‐OV compared to the control EV cell lines Fig. . In IF a3.4UBQLN4 was highly expressed (mRNA z‐score ≥ 1.5) in about 24% (23 of 95) and decreased in only 2% (mRNA z‐score ≤ 1.5) of ESCC patients  in this region in primary ESCC tumors using the TCGA ESCA dataset. Forty‐four (48.4%) of the primary ESCC tumors showed a gain in the copy number for the UBQLN4 gene  was significantly higher than normal adjacent esophageal epithelia  had a significantly worse prognosis compared to those with low UBQLN4  and high UBQLN4/low MRE11A (n = 10) showed that patients with high UBQLN4/low MRE11A have a worse prognosis  compared to the responder group (n = 8)  compared to si‐Ctrl‐treated cell lines Fig. . UBQLN4 3.6Since UBQLN4 expression determines resistance to cisplatin in ESCC cell lines, we assumed that UBQLN4 may reduce the DNA damage after cisplatin treatment. To determine the DNA damage, two markers (53BP1 and γ‐H2AX) were analyzed by IF in TE‐10 and TE‐8 EV and UBQLN4‐OV cell lines cisplatin‐treated or untreated. As anticipated, ESCC cell lines with UBQLN4‐OV presented a reduction in 53BP1 Fig.  and γ‐H24in vitro using two cisplatin‐resistant ESCC cell lines. In addition, low MRE11A expression in up‐front surgically resected ESCC tissues was related to significantly worse OS. It is accepted that the loss of MRN complex function results in DNA repair deficiency and increase sensitivity to DNA damaging therapies [This study showed that low MRE11A expression in tumor biopsies taken prior to NAC was associated with cisplatin resistance in ESCC, which was further validated herapies , 18, 22.herapies , 24, 25.herapies .in vitro results demonstrated that UBQLN4 OV alleviated DNA damage induced by cisplatin, while UBQLN4 knockdown caused the opposite effects.In ESCC patients, UBQLN4 expression was increased and associated with increased gene copy number. Moreover, UBQLN4 protein levels were found to be increased in core biopsies from ESCC patients who have poor response to NAC. Multivariable analysis showed that UBQLN4 was an independent prognostic factor to predict OS. These results suggest a potential role for UBQLN4 to predict cisplatin resistance in ESCC tumors. Additionally, our In order to identify molecular mechanisms regulating MRE11A expression at the DSB sites, we interrogated its relationship with UBQLN4. We demonstrated that DNA damage, induced by cisplatin, promotes UBQLN4 increase at DSB in ESCC cell lines. Furthermore, ubiquitinated‐MRE11A interacted with UBQLN4 during DNA damage induced by cisplatin, to be efficiently targeted to the proteasome for degradation. These results validated our previous observations demonstrating that UBQLN4 and ubiquitinated‐MRE11A accumulate at the DSB after inducing DNA damage in other solid tumors . In addiUBQLN2 and UBQLN4 have a conserved role as regulators of endoplasmic reticulum stress, autophagy, and mTOR signaling . In regaVarious attempts have been made to predict prognosis for patients with locally advanced ESCC after NAC, including diagnostic imaging , tumor m5UBQLN4 gene upregulates UBQLN4 expression in ESCC. Mechanistically, cisplatin treatment increased ubiquitinated‐MRE11A, which is targeted to the proteasome by UBQLN4 and leads to cisplatin resistance in vitro. As both MRE11A and UBQLN4 expressions were associated with clinical outcomes, they could serve as predictors for cisplatin‐based NAC response and survival outcomes in patients with primary ESCC tumors.Decreased MRE11A expression is associated with cisplatin resistance in primary ESCC tumors and cell lines. On contrary, increased copy number for The authors declare no conflict of interest.H‐score), writing—original draft preparation, reviewing, and editing. YS involved in data acquisition, analysis and interpretation , reviewing and editing. TN involved in data acquisition, analysis and interpretation , reviewing and editing. S‐CC involved in basic statistical and clinical analyses , reviewing, and editing. RDJ involved in data interpretation, reviewing, and editing. SH involved in clinical data analysis, reviewing, and editing. SO involved in clinical data analysis, reviewing, and editing. YS involved in conceptualization and design, reviewing, and editing. HT involved in conceptualization and design, reviewing, and editing. YK involved in conceptualization and design, reviewing, and editing. DSBH involved in conceptualization and design, supervision, funding, writing, reviewing, and editing. MAB involved in conceptualization and design, supervision, methodology, data acquisition, and interpretation , writing original draft, reviewing, and editing. All authors have read and agreed to publish the current version of the manuscript.TM involved in conceptualization and design, methodology, data acquisition, and interpretation  comparing si‐Ctrl and si‐MRE11A (pool siRNA) in TE‐10 (A) and TE‐8 (B) cisplatin‐resistant (Cis‐Res) cell lines. C‐D. Drug sensitivity assays comparing si‐Ctrl or si‐MRE11A (pool siRNA) in TE‐10 (C) and TE‐8 (D) cisplatin‐resistant (Cis‐Res) cell lines treated with different cisplatin concentrations . E‐F. Western blot analysis for MRE11A, UBQLN4, and β‐actin (loading control) comparing EV and MRE11A‐OV in TE‐10 (E) or TE‐8 (F) cisplatin‐resistant (Cis‐Res) cell lines. G‐H. Drug sensitivity assays comparing cisplatin‐resistant (Cis‐Res) TE‐10 (G) or TE‐8 (H) cell lines with EV or MRE11A‐OV and treated with different cisplatin concentrations (***P < 0.001). Error bars represent the mean ± SD from n = 3 replicates. Statistical differences were tested using two‐way ANOVA test and post hoc Bonferroni test .Click here for additional data file.Fig. S3. Ubiquitinated‐MRE11A interacts with UBQLN4. A. IP assay in TE‐10 UBQLN4‐OV and UBB‐OV cell lines that were treated with cisplatin (5 μm) and MG‐132 (5 μm) using anti‐DDK IgG Ab or control IgG Ab. Before elution, the immunocomplexes were treated for 30 min at 37 °C with 50 nm of recombinant human catalytic domain of USP2 or buffer as indicated. MRE11A and ubiquitinated protein levels (ubiquitinated‐MRE11A) were assessed in whole‐cell (WC) lysates and IP fractions (IP). B. Co‐IP assay in TE‐10 UBQLN4‐OV and UBB‐OV cell lines that were treated with cisplatin (5 μm) and MG‐132 (5 μm) using anti‐MRE11A IgG Ab or control IgG Ab. UBQLN4, DDK tag, and MRE11A (loading control) protein levels were assessed in whole‐cell (WC) lysates and Co‐IP fractions (Co‐IP).Click here for additional data file.Fig. S4. UBQLN4 promotes MRE11A degradation in ESCC cell lines. A‐D. Immunofluorescence staining for MRE11A was performed in cisplatin‐treated  or untreated TE‐10 EV (A), TE‐10 UBQLN4‐OV (B), TE‐8 EV (C), and TE‐8 UBQLN4‐OV (D) cell lines. MRE11A (red), DAPI (blue), and the merged images are shown. Scale bars = 10 µm. E‐F. Quantification of MRE11A fluorescence intensity per cell in TE‐10 (E) and TE‐8 (F) cell lines . G‐H. Western blot for UBQLN4, MRE11A, and LSD1 (loading control) in the nuclear fractions isolated from TE‐10 (G) and TE‐8 (H) cell lines that were untreated or treated with cisplatin (5 μm). Error bars represent the mean ± SD from n = 3 replicates. Statistical differences were tested using ordinary one‐way ANOVA test and Bonferroni post hoc test (E and F).Click here for additional data file.Fig. S5. Staining patterns observed in IHC analysis for UBQLN4, A. Representative images are shown for the different IHC staining patterns observed in the ESCC surgical specimens. H‐scores = 0–50; 51–100; 101–150; 151–20; 201–250; 251–300. Scale bars = 50 µm. B. Correlation of nuclear and cytosolic staining H‐score values for UBQLN4 .Click here for additional data file.Fig. S6. Ubiquitinated‐MRE11A interacts with UBQLN4. A‐B. Immunofluorescence staining for γ‐H2AX was performed in cisplatin‐treated  or untreated TE‐4 si‐Ctrl (A) and si‐UBQLN4 (B) cell lines. γ‐H2AX (green), DAPI (blue), and the merged images are shown. Scale bars = 10 µm. C. Quantification of γ‐H2AX fluorescence intensity per cell in TE‐4 cell lines . D‐E. Immunofluorescence staining for γ‐H2AX was performed in cisplatin‐treated  or untreated TE‐8 si‐Ctrl (D) and si‐MRE11A (E) cell lines. γ‐H2AX (green), DAPI (blue), and the merged images are shown. Scale bars = 10 µm. F. Quantification of γ‐H2AX fluorescence intensity per cell in TE‐8 cell lines . G. Immunofluorescence staining for endogenous UBQLN4 and γ‐H2AX were performed in cisplatin‐treated  or untreated TE‐4 cell lines. UBQLN4 (red), γ‐H2AX (green), DAPI (blue), and the merged images are shown. Scale bars = 10 µm. H. Correlation between UBQLN4 and γ‐H2AX levels in cisplatin‐treated TE‐4 cell lines . Error bars represent the mean ± SD from n = 3 replicates. Statistical differences were tested using ordinary one‐way ANOVA test and Bonferroni post hoc test (C and F).Click here for additional data file.Fig. S7. Western blot uncropped images.Click here for additional data file.Fig. S8. Western blot uncropped images.Click here for additional data file.Table S1. List of antibodies (Ab) and dilutions utilized in this study.Click here for additional data file.


ESR2), which also impacts inflammatory signaling of the colon. However, whether ERβ impacts the chromatin interaction (cistrome) of the main NFκB subunit p65 (RELA) is not known. We used p65 chromatin immunoprecipitation followed by sequencing (ChIP-Seq) in two different CRC cell lines, HT29 and SW480, with and without expression of ERβ. We here present the p65 colon cistrome of these two CRC cell lines. We identify that RELA and AP1 motifs are predominant in both cell lines, and additionally describe both common and cell line-specific p65 binding sites and correlate these to transcriptional changes related to inflammation, migration, apoptosis and circadian rhythm. Further, we determine that ERβ opposes a major fraction of p65 chromatin binding in HT29 cells, but enhances p65 binding in SW480 cells, thereby impacting the p65 cistrome differently in the two cell lines. However, the biological functions of the regulated genes appear to have similar roles in both cell lines. To our knowledge, this is the first time the p65 CRC cistrome is compared between different cell lines and the first time an influence by ERβ on the p65 cistrome is investigated. Our work provides a mechanistic foundation for a better understanding of how estrogen influences inflammatory signaling through NFκB in CRC cells.Inflammation is a primary component of both initiation and promotion of colorectal cancer (CRC). Cytokines secreted by macrophages, including tumor necrosis factor alpha (TNFα), activates the pro-survival transcription factor complex NFκB. The precise mechanism of NFκB in CRC is not well studied, but we recently reported the genome-wide transcriptional impact of TNFα in two CRC cell lines. Further, estrogen signaling influences inflammation in a complex manner and suppresses CRC development. CRC protective effects of estrogen have been shown to be mediated by estrogen receptor beta (ERβ,  Colorectal cancer (CRC) accounts for the third highest number of cancer deaths among both women and men in the Western world . Benign During inflammation, cytokines such as tumor necrosis factor alpha (TNFα) are released by macrophages. TNFα activates the nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) transcription factor complex, which in turn induces several oncogenes and signaling pathways involved in tumor initiation and progression –7. ConstESR2) is present in epithelial colon and rectal cells  is upregulated in breast cancer, where it promotes cell proliferation and interacts with p65  and HT29 (RRID: CVCL_0320), previously generated to express ERβ and corresponding mock control cells , 30, 31,6 cells were used. Cells were treated with TNFα  Sigma-Aldrich) for 30 min and washed with PBS before cross-linking. Cells were first cross-linked with 2 mM disuccinimidyl glutarate (DSG)  for 45 min during shaking. After washing  to remove DSG, they were cross-linked again with formaldehyde (1%) for 10 min during shaking. The double crosslinking was used to capture both short- and long-range p65 chromatin interactions. Glycine  quenched the cross-linking reaction. After washing (twice with PBS), cells were collected and pelleted by centrifugation. Cell pellets were further processed at 4°C using ice cold reagents. After lysis in LB1  for 10 min, and centrifugation , pellets were suspended in LB2  for 5 min, centrifuged, and dissolved in LB3 buffer  to separate nuclear chromatin. Sonication generated 200-500 bp long fragments of chromatin. Following centrifugation , supernatants were collected in low-binding DNA tubes and incubated overnight with p65 antibody [Invitrogen, mouse monoclonal, cat no: 33-9900, lot no: QJ216251, RRID : AB_2533153, validated in  for Bioinformatics and Expression Analysis (BEA). DNA libraries were prepared using the NEB Next Ultra II DNA Library Prep Kit for Illumina (p/n NEB #E7645) and quality confirmed using TapeStation . Libraries were loaded (1.8 pM end concentration of 1%) and sequenced  using NextSeq 550 (Illumina).Spliced Transcripts Alignment to a Reference (STAR) was used to map unique ChIP-Seq reads to the human reference genome assembly hg38 (GRCh38) with the alignIntronMax flag set to 1. Peak calling was performed using Hypergeometric Optimization of Motif Enrichment (HOMER) over input with a four-fold enrichment as cutoff and applying a false discovery rate (FDR) less than 0.001. Peaks which overlapped within 200 bp and were present in at least two out of three biological replicates were used for downstream analysis. Raw tag counts were normalized using R and binding pattern differences were identified with edgeR package. To cluster and visualize the different peaks, Complex heatmap from R was used. Promoter regions were defined as -1kb to +100bp from TSS and genomic distribution of binding sites were identified by HOMER. Gene functional annotation was performed using Database for Annotation Visualization and Integrated Discovery (DAVID), with P <0.05 considered as significant.The p65 ChIP-Seq data is deposited in the Gene Expression Omnibus (GEO) repository (GSE160856), TNFα bead array gene expression data was published previously (available at GSE65979), and SW480ERβ input and HT29ERβ input controls (GSE149979).First, to understand the role of p65 transcriptional activity and oncogenic functions in CRC, we aimed to characterize its genome-wide binding in human CRC cells and correlate this to the TNFα-mediated transcriptional impact in the same cells. We used two well-characterized human colorectal adenocarcinoma cell lines: HT29 from a female primary tumor and SW480 from a male Dukes’ type B primary tumor.). We next used HOMER to determine DNA motifs of the identified peaks. As expected, we identified RELA as the top motif, followed by JUN-AP1, in both cell lines  procedure to capture long-range interactions of p65, we analyzed the chromatin bound by p65 in triplicate experiments of each cell line, HT29 and SW480. The sequencing produced between 24M and 65M (80%) of high-quality mapped reads per sample Table S1NFKBIB, NFKBIZ, TNFAIP3 (BCL3 (BIRC3 (NFκB2 (p52) and RELB, tumor suppressor p53, TNIP1, and CREB1 , and KCNH3, ). Pathway analysis of genes bound by p65 (-50kb to +2kb of TSS) revealed that genes with transcriptional regulatory functions (e.g. JUND), cell adhesion and migration , NFκB signaling, TNFα signaling, and apoptosis were enriched. This is in accordance with general NFκB functions  of genes . Other known targets were differently bound and regulated in HT29  and SW480  cells  transcriptome data set of the same cells . We foun1) cells Table S3To explore the extent that p65 binding is conserved between colon and breast cancer, we compared our generated p65 cistrome (colon) with previously published p65 ChIP-Seq data of the ER-positive breast cancer cell line MCF7. We selected a data set that also used double crosslinking . A heatmin vivo  TNFα-mediated upregulation of VEGFA, AGO2 and IGFL4. We thus identified that ERβ reduces a sizeable fraction of p65 binding, modifying TNFα regulation in HT29 cells, especially for genes involved in e.g. cell proliferation and cell-cell adhesion.We also compared the p65 ChIP-Seq data with corresponding TNFα gene expression data, with and without ERβ  remained. However, a high number (5796) of new p65 binding sites appeared in presence of ERβ .DUSP5 [which regulates inflammatory gene expression of TNFα . Among these, expression was attenuated in most (24), and enhanced in some (14). Genes suppressed by ERβ included BCL3, BIRC3, CCL20, NFκB2 and RELB  between the two cell lines, with and without ERβ Figure 7ll lines . OverallActivation of NFκB in the intestinal epithelia can lead to colitis-induced CRC . Our stuBMAL2, CLOCK). A previous study has shown that dysregulation of circadian rhythm increases the risk for colorectal cancer (CLOCK gene mutations have been identified in 53% of CRC with microsatellite instability (MSI)  in colon of HFD-fed mice  . Moreovety (MSI) . In breaty (MSI) , 53. In ty (MSI) , 55. In se model . We havefed mice . Here, iInterestingly, p65 chromatin binding appears relatively distinct between the two CRC cell lines, in support with the fine-tuned cell-specific manner whereby NFκB controls transcriptional regulation. The cell lines are indeed different in several respects. While both are derived from primary colon adenocarcinomas, the HT29 cell line is derived from a likely pre-menopausal (44-year-old) woman, whereas SW480 originates from a 50-year-old man , 58. We While the p65 binding pattern was similar between the two CRC cell lines, the p65 cistrome of breast cancer cell line MCF7 was more distinctly different. One of the well-known interaction-partner of p65 is the p53 protein . MCF7 ceWe have previously shown that TNFα triggers a transcriptional response in both CRC cell lines, and that ERβ modulates this . Here, wThe strength of this study includes the genome-wide approach to decrypt these interactions, which together with the validated high-quality ChIP-Seq data generates unbiased and reliable data. The significance of these findings is reinforced by the use of two different CRC cell lines and the comparison with transcriptional impact, as well as comparisons between our results and published data generated from cells of other origin. A shortcoming includes the use of exogenous expression of ERβ in the CRC cell lines. However, cell lines mostly lack endogenous expression of ERβ , 22. FurIn conclusion, we provide a mechanistic foundation for a better understanding of how estrogen influences inflammatory signaling through NFκB in CRC cells.The p65 ChIP-Seq data is deposited in the Gene Expression Omnibus (GEO) repository (GSE160856), TNFα bead array gene expression data was published previously (available at GSE65979), and SW480ERβ input and HT29ERβ input controls (GSE149979).CW contributed to conceptualization. Methodology performed by RI, LH, and AA. Validation done by RI and LH. Formal analysis was done by RI and LH. Curation, RI. RI and CW wrote the first original draft and all authors commented or edited. Visualization, RI. Supervision, CW and AA. Project administration, CW. All authors contributed to the article and approved the submitted version.National Cancer Institute at the National Institutes of Health (R01CA172437), the Swedish Cancer Society , Swedish Research Council (2017–01658), and Region Stockholm (HMT grant 20170804). RI was supported by a PhD student grant (KID) from the Karolinska Institutet.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The present Nigerian transmission network is faced with the difficulty of evacuating and dispatching reliable and quality electricity supply and simultaneously maintaining an operational standard of security to prevent any collapses. Therefore, this study developed a novel technique to optimize electrical current flow to provide in-depth research and analysis of current flowing in the transmission network circuit prone to danger during short-circuit faults. The research methodology involved the generation of unbalanced short-circuit calculations at every single node of the three-phase network using the symmetrical component method. Numerical simulation of different types of unbalanced short-circuit fault into the entire 330kV transmission network using unbalanced fault algorithms written in a flexible MATLAB program environment is also performed on every bus. The influence of these short-circuit faults is examined on the generated spectrum of line current magnitude. This study then generates a series of unbalanced current circuit and line losses analysis that unveils the different scenarios regarding existing network performance. The method adopted is promising. It established the most critical lines (about 20) with high unbalanced current magnitudes and high line losses during the disturbance. Based on the result analysis, four (quad) bundles of conductors is designed as a proposed modification to the upgrade of all critical double circuit lines and the conversion of single critical lines on the 330kV transmission network to improve the power transfer capability and also meet the future transmission network development plan. Furthermore, recommendations that are considered desirable in this study are proffered to ensure acceptable power quality and security in the network. Novel technique, optimize current, symmetrical component algorithm, Numerical simulation, line current spectrum, unbalanced current circuit, critical lines losses, Quad bundle parameter Therefore, it has become essential to operating energy delivered to transmission lines at maximum efficiency . Unfortu4Globally, many major blackouts caused by power system insecurity have been traced to fault on power lines. For example, the North American transmission system's interruption, occurring in 2003, interrupted supply for over 50 million people . The twoTherefore, this study provides in-depth knowledge of the flow of current in the network to solve the challenging problems inherent in designing the present and future power systems to deliver increasing electrical energy safely and in a sustainable economic manner. The more the power that flows through the power lines, the more will be the current that flows and consequently the power quality will decline. This study's uniqueness is in the novel technique developed to optimize the flow of electrical current, a significant quantity, in the network, which provides insight into the contingency analysis of the transmission lines' security dispatch operation. The approach involves the numerical simulation of various aspects of unbalance faults; single-line to the ground (SLG), line-line (LL), double line to ground (DLG) into each line of the three-phase network. The study's generated results showed that most of the lines (about 20) have high levels of unbalanced current magnitudes. The analysis covers all the 33 lines for the simulated 28 buses and categorized into four scenarios based on their characteristics, as revealed in this study, making it easy to determine and analyse the critical lines or weak areas with high losses. Further analysis of the result of the unbalanced current circuit and power line losses leads to the proposed reconductoring of quad bundles conductor design. Recommendations are made for the critical weak lines by supplying relevant information to improve the network's weak lines and future expansion planning.2The data collected from PHCN includes the 330-kV transmission network in Nigeria, with particular attention to the schematic diagram of the entire single-line diagram, line data, and bus data. The data employed in the analysis are generated by the simulation of different types of unbalanced short-circuit faults into the network using unbalanced fault algorithms written in a flexible MATLAB program environment at every bus to examine their effects line current. The systematic, theoretical analysis of the methods applied and principles associated with the study areas discussed.2.1In this study, the Nigerian power network is used as the test system. The one-line diagram of the existing 28 bus and thirty-three (33) branches of the 330-kV Nigerian power system is given in 2.2The power system in any electrical circuit is analysed by calculating the system voltages and/or currents under normal and abnormal scenarios . However2.31.Single Line to Ground Fault (SLGF) involves the positive sequence, negative sequence, and zero sequences. For a fault at bus K, a phase to ground, the symmetrical components of fault current are given in Eqs. The various unbalanced fault expressions are given in Eqs. 2.Line-to-Line Fault (LLF): involves two conductors exposed to each other through fault impedance3.Double line-to-ground fault (DLGF): with this fault type, two-line conductors or phases come in contact both with each other through an impedance The fault phase current isThe phase currents are obtained from Eq. (8)is the prefault phase voltage at bus i.Using the sequence network components of the fault current, the symmetrical components of the ith bus voltages during fault are obtained as presented in Eqs. The phase voltages during fault areThe symmetrical components of fault current in line i to j are given as presented in Eqs. 2.4The current dependent load model is used in which load changing is in direct proportion to current at constant voltage and constant power. Since current is required to flow in every branch of the network, the injection model of the current, shown in Therefore, The current flowing through the power line at any bus K is determined by Eq. (16)If Hence, the real and reactive components of bus current in terms power and voltage buses are respectively given asUsing Eqs. However, for this study, the line currents' results, obtained by using 2.5By consider a three-phase transmission line with fault at node k, the model of a simulated fault is as shown in Thus, the fault current is given by Because the system is complex, MATLAB software is employed to maintain the same computational flow chart. The MATLAB code starts by identifying the system input arguments in which variables are manly positive and zero sequence impedance, as presented in 3Various aspects of faulted bus simulations begin from Kainji bus one and end at Gombe bus twenty-eight for each of the 33-line currents are generated. Since the network is quite extensive, this paper only presents few samples of the faulted bus  showing simulations for each of the 33 branches and 28 bus lines current as presented in Tables 3.1It has been discovered from the literature that most of the system collapses were a result of unbalance current in the three-phase when a fault occurs. Tables 3.1.1A large number of balanced currents characterizes the lines under this category. They are not affected by the faults occurring at different test system locations, as shown in 3.1.2In this category, the unbalanced current circuit ranges from 10 to12 in number, is associated with a double circuit, as presented in 3.1.3These lines have a particular shared characteristic of a single circuit except line 21–22 (Afam-Alaoji) with double circuits. There are ten (10) lines in this category, having a significant unbalance current ranging from 18 to 21 in numbers. However, the five lines, i.e., 12–13 (Omotosho-Benin), 13–18 (Benin-Onitsha), 15–17 (Sapele Aladja), 16–17(Delta-Aladja), and 21–22 (Afam-Alaoji) from the eastern part will not trip on 330kV grid with any of these northern faulted buses, 26 (Kano), 27 (Jos) and 28 Gombe) as presented in 3.1.4The eleven (11) lines in this category are the worst in unbalanced current circuits on the 330kV grid. When a short circuit occurs, all the faulted 28 buses affect these lines. These are the most critical lines when a fault occurs because only the faulted bus 28 has a balanced current circuit in all the three phases of the different unbalanced faults, as shown in 3.2To achieve higher efficiency and stability in the system, it became necessary to unveil lines that experience high power loss in this study based on the result of the unbalanced current analysis. The results of all the line current magnitudes obtained  and double circuit (DC) on the network. A careful study of these critical lines showed that these lines need ‘upgrade’ or ‘conversion’ as the case may be. It should be noted here that most of the existing double circuits are double conductor bison. The proposed specifications required for the construction of quad bundle conductors are presented in Eqs. The resistance (RT) of the four-conductor bundle is calculated using On substituting, we have (for one conductor)Resistance (R) =0.01507 Ω/km for four bundle conductors.The Geometric Mean Radius (GMR) and GMD are given in Eqs. System of conductors is 14m while the bundle diameter for a four-bundle conductor arrangement is 64.6 cm. The radius of the camel conductor is 0,015075m.where:L) are calculated using Eqs. The Line Inductance (L) and Inductive Reactance :The line Susceptance is calculated using Thus, the generated electrical line parameters  times on fault between 6/5/2015 and 1/9/2017, which is clear evidence of inadequate protection relaying scheme. It should also be noted that these lines are connected to either the generator bus or Osogbo bus , or Benin bus , except Alaoji-Onitsha. Thus, these lines will collapse in the event of significant fault occurrence without adequate protection relaying scheme.•It is discovered from •Further investigation in the study revealed that additional lines are required from Shiroro, Benin, Omotosho substations, and the modification of these lines to form part of North West ting. A similar transformation can be implemented from Gombe, Kano, and a new substation (links Gombe) to form part of the North East ring.•A new substation should be introduced at Kangiwa , about 189 KM and 122 KM away from Kainji and Birnin Kebbi. It is worth mentioning here that line 1–2 (Kainji-Birnin Kebbi), a single circuit and long line that is not limited by stability limits, has the lowest magnitude level of the balanced current circuit as presented in •There is an urgent request to replace those identified critical lines with the newly designed specifications for quad bundle conductors, as shown in •The transmission grid may also need to be made more ‘intelligent’ through the configuration and training of Artificial Neural Network (ANN). That way, applying a set of line currents obtained from the numerical simulation of various aspects of faults  branches of the Nigerian 330kV transmission network when subjected to various aspects of asymmetrical faults at twenty-eight (28 buses) different locations. An ideal algorithm was developed for a set of unbalanced short-circuit calculations models of the network. It simulated the unbalanced short-circuit faults  into each line of three-phase networks. The novel approach was implemented to form the basis to develop a strategy that identified the network's different problem areas, such as current unbalance circuit, high line current magnitude and losses, and critical weak lines. Based on these findings, the lines revealed that enough provision was not provided to have a close loop in the system. The study moved further to explore calculation and design parameters for the critical lines that require urgent attention as a power grid strengthening strategy. The study unveiled the Nigerian 330kV national grid's terrible and unsatisfactory state and proffered recommendations that need modifications to promote better efficiency, reliability, and security in the power line network. It is evident from the study that the priory of the transmission line expansion plan is of more priority over an increase in generation capacity for the evacuation of the generated energy. The data generated in this study will help system expansion planning, utilities desirous of minimizing network losses, and policymakers wishing to formulate more effective policies.Ademola Abdulkareem: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Wrote the paper.A. Adesanya: Performed the experiments; Wrote the paper.A. F. Agbetuyi & A. S. Alayande: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.10.13039/501100012497Covenant University Centre for Research, Innovation and Discovery.This work was supported by the Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.


Cell lines are widely used in research and for diagnostic tests and are often shared between laboratories. Lack of cell line authentication can result in the use of contaminated or misidentified cell lines, potentially affecting the results from research and diagnostic activities. Cell line authentication and contamination detection based on metagenomic high-throughput sequencing (HTS) was tested on DNA and RNA from 63 cell lines available at the Canadian Food Inspection Agency’s National Centre for Foreign Animal Disease. Through sequence comparison of the cytochrome c oxidase subunit 1 (COX1) gene, the species identity of 53 cell lines was confirmed, and eight cell lines were found to show a greater pairwise nucleotide identity in the COX1 sequence of a different species within the same expected genus. Two cell lines, LFBK-αvβ6 and SCP-HS, were determined to be composed of cells from a different species and genus. Mycoplasma contamination was not detected in any cell lines. However, several expected and unexpected viral sequences were detected, including part of the classical swine fever virus genome in the IB-RS-2 Clone D10 cell line. Metagenomics-based HTS is a useful laboratory QA tool for cell line authentication and contamination detection that should be conducted regularly. There have been reports where the cell line was misidentified by the source institute, rendering the results of any publication using that cell line questionable. For example, the KB cell line, believed to be oral or squamous cell carcinoma2, and the KU7 cell line believed to be derived from bladder cancer cells3, were both found to be HeLa cells. Vaughn et al.2 found 631 publications published between the years 2000–2014 that mentioned the use of the KB cell line, of which 574 articles were describing it incorrectly. These, and other papers describing misidentified cell lines, have been and may continue to be cited and used in other studies, thus potentially invalidating the research2. As an increasing number of cell lines are reported as being contaminated or misidentified, many scientific journals including Nature and PLOS ONE have now put policies in place for the authentication of cell lines used in their publications4. Two of the main causes of cell line misidentification are cross-contamination between cell lines and mislabeling of tubes or culture flasks4. Cross-contamination may occur within cell lines of the same species (intra-species cross-contamination) or between different species (inter-species cross-contamination). Cell lines may also be completely overgrown and replaced by a contaminating cell line5. Regularly confirming the identity of cell lines can prevent contamination and mislabeling errors from affecting future research and diagnostic test results.Cell line authentication is an essential part of ensuring the validity of research and diagnostic results. Misidentified or contaminated cell lines can present irreproducible or inaccurate results which may mislead future research1. As each human cell line has originated from a different individual, STR profiling allows for differentiation between them. For non-human cell lines, using genes such as the mitochondrial gene cytochrome c oxidase subunit I (COX1) for DNA barcoding may be used to determine the species of origin. Due to frequent third-position base substitutions in this gene there is a high rate of molecular evolution leading to diversification, which can even differentiate between various phylogeographic groups of the same species6. The species can then be determined by comparing the DNA barcode profile of a cell line to databases of these sequences 1. However, STR/SNP and COX 1-based methods do not provide information on the presence and type of microbial contamination.One of the methods used for cell line identification is short tandem repeat (STR) profiling, which has been widely used for human identification in forensicsShotgun metagenomic sequencing allows sequencing of a broader spectrum of DNA or RNA in a sample. Thus, it can be used for species identification of cell lines and potentially detect the presence of bacterial, viral, or fungal contamination. If specific STR and SNP loci are amplified prior to sequencing, STR/SNP profiling may be reliably implemented for the confirmation of the specific cell line. In this study, high-throughput sequencing (HTS) was performed on DNA and cDNA extracts from each of 63 cell lines available at the Canadian Food Inspection Agency (CFIA) National Centre of Foreign Animal Disease (NCFAD) to verify the species of origin and presence of microbial contamination.2, except for Trichoplusia ni cells which were grown with shaking at 27 °C for 24 h before collection. Adherent cell lines were dissociated using 0.25% Trypsin-0.1% EDTA, and cells in suspension were spun down at 4 °C for 10 min at a relative centrifugal force of 600, and re-suspended in culture media. An aliquot of cells was stained with 0.2% trypan blue and counted using a Cellometer Auto T4 counter (Nexcelom Bioscience).A total of 63 cell lines available at the NCFAD were seeded from frozen stocks and grown for 48 h at 37 °C and 5% CO6 viable cells using the manufacturer’s recommended protocol. The DNA and RNA were eluted into 50–100 μL of AE elution buffer (QIAGEN). Qubit dsDNA Broad Range (BR) and RNA High Sensitivity (HS) kits (Thermo Fisher Scientific) were used to quantify DNA and RNA in the extracts on the DS-11 FX fluorometer (Denovix).DNeasy Blood and Tissue kit (QIAGEN) was used to isolate DNA and RNA from ~ 2.5 × 10Invitrogen ezDNase enzyme (Thermo Fisher Scientific) was used for the digestion of cellular DNA within extracted nucleic acid prior to cDNA synthesis. Superscript IV First-Strand Synthesis module (Thermo Fisher Scientific) was used for the synthesis of the first strand of cDNA using a 1:1 ratio of random hexamers and oligo-dTs and 300 ng of RNA. The NEBNext Ultra II Second-Strand synthesis module (New England Biolabs) was used according to the manufacturer’s protocol to generate the second strand of cDNA. QIAQuick PCR purification kit (QIAGEN) was used to purify the double-stranded cDNA and eluted in EB buffer (QIAGEN) according to the manufacturer’s recommended protocol. The Qubit dsDNA BR kit (Thermo Fisher Scientific) was then used to quantify the cDNA using a DS11 FX fluorometer.Sequencing was performed separately on the DNA and cDNA samples with the cDNA samples separated into two runs including a test run with a smaller number of samples due to the timing of the availability of the samples Tables  and 2. LLibrary preparation for the cDNA samples was subsequently performed with the Nextera XT Library Prep kit (Illumina) following the manufacturer’s protocol due to a switch over of Illumina library preparation methods in the laboratory. In the first run, 26 samples were pooled and loaded at a final concentration of 10 pM with 1% PhiX, and sequencing was performed again on the Illumina MiSeq using a V2 flow cell with a 300-cycle (2 × 150 bp) cartridge. In the second run of cDNA samples, 65 samples were pooled at a final concentration of 18 pM with 1% PhiX, and sequencing was performed on a V3 flow cell with a 600-cycle (2 × 300 bp) cartridge.7 software . To determine the species of the cell line, metagenomic analysis was performed using the nf-villumina8 (v2.0.0) Nextflow9 workflow on the concatenated DNA and cDNA sequencing data. As part of the nf-villumina workflow, Illumina PhiX Sequencing Control V3 reads were removed using BBDuk10, and poor quality reads and adaptors were removed using fastp11. Taxonomic classification of the filtered reads was performed with Kraken 212 using an index of NCBI RefSeq sequences for bacteria, archaea, viruses and the GRCh38 human genome , and with Centrifuge using an index of NCBI nt sequences (downloaded and built 2020-02-04). Quality filtered reads were assembled into contigs with Megahit13, Shovill14, and Unicycler15, which were queried against the NCBI nt database  using nucleotide BLAST+17 (v2.11.0)  restricting the search to eukaryotic NCBI nt database entries (i.e. belonging to NCBI taxonomic ID (taxid) 2759). The processed reads for each cell line were mapped against the top matching COX1 sequence identified by BLAST analysis using Snippy (v4.6.0)18 as part of the nf-illmap Nextflow workflow (v1.0.0)19. The resulting BAM alignment file was loaded into Geneious v.9.1.820 where a threshold for coverage depth was set to a minimum of three, and variants were called using the Find Variations/SNPs tools with default settings except Minimum Coverage = 3 and Minimum Variant Frequency = 0.75. Variants were only called if the read depth had a minimum coverage of 3×. MDBK-HS-1 is from the cell lines available at CFIA NCFAD in Winnipeg, Manitoba, Canada while MDBK-HS-2 came from the CFIA NCAD laboratory in Lethbridge, Alberta, Canada. For cell lines where the observed species from the top BLAST match was not as expected based on laboratory records, the reads were additionally mapped to the CytB gene sequence using the same methods as was used for mapping to the COX1 sequences.iGenomX DNA sequencing reads were demultiplexed using the fgbio21. As part of DAMIAN analysis, raw sequencing reads were trimmed using Trimmomatic22 with default settings and assembled using SPAdes23. Contigs were taxonomically classified using nucleotide BLAST+ (v2.11.0) (DAMIAN BLAST+ option “progressive”) and the NCBI nt database . Trimmed reads were mapped to the viral genomes identified by DAMIAN and additional nucleotide BLAST analysis using the nf-illmap workflow. Variants were called in Geneious V.9.1.820 using the method described above.RNA and DNA viruses and bacteria were identified from the cell line DNA and cDNA sequencing data using DAMIANCOX1 gene of the top mitochondrial genome BLAST match for each cell line. All observed species in this list matched the species recorded in the institute’s cell line inventory list. This list also includes five archived cell lines that have been documented as “unknown” which did not have a defined species listed.Table 25; however, there were no BLAST results from the LFBK-αvβ6 de novo assembled contigs that corresponded to the Bos taurus genome or mitogenome. All BLAST results matched sequences from the Sus scrofa genome and mitogenome. Figure B. taurus and S. scrofa COX1 sequences. A total of 880 reads from LFBK-αvβ6 mapped to the S. scrofa COX1 gene and had a breadth of coverage of 100% with 0 total variants  between the mapped reads and the reference, while only 77 reads mapped to the B. taurus reference COX1 gene with a breadth of coverage of 44.1% and 98 total variants  than the expected species based on available documentation. For these samples, reads were mapped against the COX1 sequences from both the expected and observed species. This analysis showed that, when reads were mapped against a reference sequence representing the expected species, more variants were observed than when they were mapped against a reference representing the observed species, suggesting that the cell line is derived from a different species than was expected  sequence. While the Cytb sequences between the observed and expected species also share a high similarity , Table b analysis are consistent with those of the COX1 analysis suggesting with higher confidence that the cell lines are derived from a different species than expected.Eight cell lines  were found to align better to the ed Table . The COX26. Reads that were classified as classical swine fever virus (CSFV) were also found in the IB-RS-2 Clone D10 cell line with a 39.5% breadth of coverage across the viral genome with seven total variants relative to the reference genome. In the T. ni insect cell line, reads identified as Flock House virus had a breadth of coverage of 85.1% across the reference genome with two total variants  in CPAE, and the common porcine circovirus 1 (PCV1) in swine-derived PK-15 (PCV+) cells. Sequences matching these viruses were detected as expected, and PCV1 was also found in all four IPAM clones . Examining the polymorphic isoenzyme profiles between species for cell line confirmation has limitations including limited species range, low sensitivity of detection, and complex data interpretation.COX1 sequence that was consistent with the expected species; the reads from each of these cell lines had a breadth of coverage of > 95% across the COX1 gene, and no more than five variants compared to the reference. LFBK-αvβ6 and SCP-HS cells were found to be from a different genus than expected, suggesting that the cell lines had been misidentified, contaminated, or mislabeled. When reads from the LFBK-αvβ6 and SCP-HS cell lines were mapped to the COX1 genes corresponding to the species identified by BLAST analysis, no variants were observed in either sample. The porcine DNA found within the LFBK-αvβ6 cell line is consistent with a published erratum that this cell line is of porcine origin25. LFBK-αvβ6 isoenzyme patterns are also consistent with cultures of porcine origin (unpublished results).In this study, 53 of the 63 cell lines had a COX1 and Cytb genes were used as an indication of how similar the cell line was to a particular species. The difference in the number of variants between the expected and observed species varied for each cell line (between 9–64 variants for COX1 and 1–68 for CytB); however, in each case, the number of variants was higher when aligned to the expected species as compared to the observed species, except for PaLu and PaSPT where the reads mapped to the Cytb gene had a higher number of SNPs to the observed species than the expected. Turner et al.27 describes the morphological differences between species of the Chlorocebus genus of Old World monkeys, and reported that various geographical locations may permit deviation from the predicted morphology of these species. Thus, the species of the individual animal from which each of these cell lines originated was likely misidentified. It was also noticed that the number of variants in the bat cell lines (PaLu and PaSPT) was considerably higher in the observed species  compared to all of the other cell lines (6 or fewer variants). The genus Pteropus is known to be very diverse with a large number of species28, therefore, additional investigation will be required to determine if the cell lines are, in fact P. ornatus, as identified here, or if there was a misidentification between closely related species when the cell line was originally created.Assembled sequences from eight of the cell lines showed a higher pairwise nucleotide identity to a different species within the same genus than what was expected Table . Five of29, while non-human cell lines are best identified using DNA barcoding with the COX1 gene6. The International Cell Line Authentication Committee (ICLAC) keeps a Register of all known misidentified or cross-contaminated cell lines. As of this study, the Register was last updated March 25, 2020 and contains a total of 509 cell lines that are misidentified; of these only 38 were nonhuman cell lines30. This is likely not because human cell lines are more susceptible to contamination compared to nonhuman cell lines, but rather, because there is more information available for human cell lines in addition to the limitations of STR profiling which is only applicable for single species differentiation30. Thus, the method described here is useful since it can identify the species as well as the presence of contaminants such as other cell lines, mycoplasma, or viruses1.The current gold standard for the authentication of human cell lines is STR profilingmycoplasma contamination of cell lines. Depending on the species of mycoplasma, the effects on the cells vary from changes in protein and nucleic acid synthesis levels to a complete loss of the culture31. Detection of contamination is difficult, due in part to the small size (0.3–0.8 µM)32 of the mycoplasma cells, which allows them to pass through filters33. Additionally, high concentrations of mycoplasma are possible without any obvious visual signs33. In this study, mycoplasma was not detected in any of the 63 cell lines tested. This result was expected as the NCFAD currently has quality control procedures in place to check for mycoplasma contamination in their cultures, and the results here are consistent with the systems in place.Experimental results can be negatively impacted due to 34 and was present in the CPAE and OA3.Ts cell lines. Human adenovirus C was found in both HEK-293 and A549 cells. PCV1, a ubiquitous virus in pigs, was found as expected in the PK-15 (PCV +) cell line and in all four of the IPAM clones tested. Retroviral sequences are common in the genomes of their hosts due to insertion into the host genome25. The near-complete genome (99.3% breadth of coverage with 77 variants) of murine leukemia virus (MuLV) was detected in the P3X63-Ag8 cell line. Partial genomes from retroviruses such as avian leukosis virus (ALV) and porcine endogenous retrovirus (PERV) were detected in some cell lines.The presence of certain viruses was expected in some of the cell lines. Bovine viral diarrhea virus 2 (BVDV2) is a common contaminant in fetal bovine serum28, however, testing of this cell line obtained from the American Type Culture Collection (ATCC) by Bolin, et al.35 detected the virus in this clone. The presence of the entire CSFV genome was also found in the same cell line used by the Pirbright Institute, UK .Sequencing reads covering 39.5% of the CSFV genome were found in the cell line IB-RS-2 Clone D10 with seven total variants shared between the reads mapped and the reference genome. This clone was originally determined to be free of CSFV contaminationmycoplasma) or the presence of unexpected viruses.Cell line authentication is important for the reproducibility and accuracy of research and diagnostics involving cell lines as it can help identify unexpected errors and contamination in archived material and cell lines obtained from other sources. This study confirmed the species identity of 63 cell lines that are available at the Canadian Food Inspection Agency’s National Centre for Foreign Animal Disease. Of these cell lines, five were previously undefined, eight were determined to be derived from a different species within the same genus than was expected, and two were identified as species from different genera than expected. The methods described in this study or other comparable methods can be useful as they provide a single approach for species identification, as well as for the detection of contamination (e.g.,


Malignant pleural mesothelioma (MPM) is an aggressive malignancy with a severe prognosis, and with a long-standing need for more effective therapeutic approaches. However, treatment with immune checkpoint inhibitors is becoming an increasingly effective strategy for MPM patients. In this scenario, epigenetic modifications may negatively regulate the interplay between immune and malignant cells within the tumor microenvironment, thus contributing to the highly immunosuppressive contexture of MPM that may limit the efficacy of immunotherapy. Aiming to further improve prospectively the clinical efficacy of immunotherapeutic approaches in MPM, we investigated the immunomodulatory potential of different classes of epigenetic drugs  guadecitabine, histone deacetylase inhibitors VPA and SAHA, or EZH2 inhibitors EPZ-6438) in epithelioid, biphasic, and sarcomatoid MPM cell lines, by cytofluorimetric and real-time PCR analyses. We also characterized the effects of the DHA, guadecitabine, on the gene expression profiles (GEP) of the investigated MPM cell lines by the nCounter platform. Among investigated drugs, exposure of MPM cells to guadecitabine, either alone or in combination with VPA, SAHA and EPZ-6438 demonstrated to be the main driver of the induction/upregulation of immune molecules functionally crucial in host-tumor interaction  in all three MPM subtypes investigated. Additionally, GEP demonstrated that treatment with guadecitabine led to the activation of genes involved in several immune-related functional classes mainly in the sarcomatoid subtype. Furthermore, among investigated MPM subtypes, DHA-induced CDH1 expression that contributes to restoring the epithelial phenotype was highest in sarcomatoid cells. Altogether, our results contribute to providing the rationale to develop new epigenetically-based immunotherapeutic approaches for MPM patients, potentially tailored to the specific histologic subtypes. Malignant pleural mesothelioma (MPM) is a low-frequency thoracic neoplasm arising from mesothelial cells of the pleural cavity, featuring a high aggressiveness  . The proDespite the accumulation of novel insights about MPM biology ,11 and tEpigenetic modifications include principally DNA methylation, post-translational modifications (PTMs) of histone proteins, chromatin remodeling components, histone variant exchange, and non-coding RNAs ,22. UnliOther epigenetic compounds have been demonstrated to modulate immune cell transcriptional programs. Tazemetostat (EPZ-6438), an inhibitor of the enhancer of zeste homologue 2 (EZH2i) favored chemokine-dependent T cell attraction as a consequence of enhanced expression of the immunostimulatory molecules in cancer . FurtherBased on the encouraging sensitivity of MPM to immunotherapy and on the promising immunomodulatory effects of epigenetic remodeling, this study focused to compare the properties of different classes of epigenetic drugs, including agents recently used in clinical trials , on MPM cell lines belonging to the three main subtypes. The identification of guadecitabine as the main driver of the greatest immunomodulatory effects led us to expand the characterization of the DHA activity by analyzing changes in gene expression profiles (GEP) of MPM cell lines belonging to the three subtypes and elucidating the biologic functions of genes representing the expression signature of epigenetically-treated vs. untreated MPM cells. Results obtained provide the rationale for the development of new more effective epigenetic-based immunotherapeutic strategies for the treatment of MPM patients also relating to their histologic prognosis.p ≤ 0.05) in 4/5  treated cell lines, as compared to untreated cells  in 4/5  treated cell lines, as compared to untreated cells  up-regulated the expression in the two constitutively positive sarcomatoid cell lines  induced by the different investigated epigenetic drugs alone or in combinations, in 5 MPM cell lines. Baseline levels of NY-ESO-1 and MAGE-A1 were negative in five and two (one epithelioid and one biphasic) cell lines, respectively; all cell lines were constitutively positive for MAGE-A3 expression. A de novo expression of NY-ESO-1 was induced by guadecitabine and guadecitabine-based combinations in 5/5 MPM cell lines . No indull lines . No indull lines . Finallyll lines . No signll lines .p ≤ 0.05) up-regulation of CDH1 expression was observed in 1 (epithelioid)/3 CDH1-positive cell lines after guadecitabine and guadecitabine-combined treatments, and in one biphasic cell line treated with VPA or guadecitabine plus VPA. Other treatments did not induce any modulation of CDH1 expression in investigated cell lines  genes were differentially  expressed in treated vs. untreated cells. Mean of 68.3% (range: 46.7–83.7%) and 31.7% (range: 16.3–53.3%) DEG were respectively up-regulated (FC ≥ 0.58) and downregulated (FC ≤ −0.58), in the 10 investigated MPM cell lines, by treatment.According to Ingenuity Pathway Analysis (IPA), 248 canonical pathways were modulated (Z-score ≥ 2 or Z-score ≤ −2) in treated compared to untreated cells, in at least one cell line . Among tIPA upstream regulator analysis identified 660 upstream regulators responsible for changes in the expression profiles of at least one MPM cell line after guadecitabine treatment . Among tStemming from these results, we performed a subtype-specific investigation of the modulation of functional classes of immune-related genes, after guadecitabine treatment.A strongly upregulated expression of multiple CTA genes was observed in all the three DHA-treated subtypes . Comprehp < 0.001) was proved between changes  induced by guadecitabine in the constitutive levels of investigated genes expression, measured by quantitative real-time PCR or by nCounter multiplex gene expression analysis in the 10 MPM cell lines  ligand CD74, which represents an independent prognostic factor of survival for MPM patients, whatever the histological subtype, being, however, more expressed in the epithelial type; indeed, its low tumoral expression was associated with dismal prognosis . Some stAlthough the number of investigated MPM cell lines was limited, the sensitivity to epigenetic drugs treatment, heterogeneously observed among MPM cell lines belonging to the three different subtypes, was more evident in the most aggressive sarcomatoid MPM subtype, supporting the need to develop personalized combination therapies to render these aggressive tumors more responsive to immunotherapy.Comprehensively these studies laid the groundwork for planning further in vivo studies to demonstrate the potential of guadecitabine-based immunotherapeutic strategies for MPM treatment, considering also the influence of MPM subtypes in the epigenetic drugs’ sensitivity.Ten MPM cell lines were selected in order to represent the three main subtypes: the epithelioid Meso1 and Meso6, the biphasic Meso4, Meso5, Meso7 and Meso13, and the sarcomatoid Meso2, Meso3, Meso8 and Meso11. All cell lines were established by our group from pleural effusions of MPM patients deal with in the University Hospital of Siena, under approval by the Committee on Human Research. All cell lines were cultured in HAM’s F-12 medium  supplemented with 10% heat-inactivated fetal bovine serum , 2 mML-glutamine, and 100 µg/µL of penicillin/streptomycin .PE mouse anti-human ICAM-1 clone 84H10 monoclonal antibody (mAb) was purchased from Beckman Coulter and alexafluor 488 mouse anti-human HLA-ABC (class I) clone W6/32 mAb was purchased from Biolegend. Guadecitabine was purchased from MedChemExpress LLC ; HDAC inhibitors, VPA and SAHA, were purchased from Sigma Aldrich Corporation  and Cayman Chemical , respectively and the EZH2i EPZ-6438 was purchased from Selleck Chemicals .6/13 mL of complete medium (day 0) and treated with 1 µM guadecitabine . Correlation between mFC in the expression of selected genes, measured by nCounter assay and quantitative real-time PCR analyses, was evaluated by Pearson’s correlation coefficient (r).Statistical analyses were carried out by GraphPad Prism 7.05 .


Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium  Pseudomonas aeruginosa is an environmental generalist and an opportunistic pathogen capable of infecting a wide variety of hosts ranging from plants to humans [o humans , 2. Morpo humans . Phenotyo humans , mediateo humans –8, rearro humans –11 or byo humans .P. aeruginosa strains are large (5–7 Mbp) and encode a variety of regulatory circuits. These provide a remarkable phenotypic plasticity and a high adaptation potential to the opportunistic pathogen. For the successful colonizing of new habitats, P. aeruginosa must maintain this adaptation potential even under constant conditions. However, as it has been observed for various bacteria and yeasts, constant conditions favor the genetic selection of niche specialists, which have a higher fitness, but show fitness decay in other environments [The genomes of ronments . The traronments –18.P. aeruginosa and recorded the type and frequency of mutations as well as their effect on bacterial fitness as compared to S. enterica. We used DNA repair-deficient bacterial strains characterized with ~100 times higher mutation rates in order to accelerate MA. Each of the species was continuously cultivated in the exponential phase under weak and strong bottlenecking conditions. In the context of experimental evolution, strong bottlenecking and a lower size of the effective population are thought to promote fixation of random mutations and, since most mutations are deleterious, lead to a loss of fitness. Conversely, weak bottlenecking enables natural selection and is more favorable to the fixation of beneficial and elimination of harmful mutations [P. aeruginosa, but not S. enterica hypermutator strains adapt to planktonic rich medium conditions by evolving increased growth performance. We show that the increase in fitness in P. aeruginosa was associated with an increased rate of phase variation events in the promoter regions of genes involved in membrane and cell wall biogenesis. Furthermore, the fine-tuning of cyclic di-guanylate (c-di-GMP) signaling-governed pathways was observed, indicating that P. aeruginosa adapts to lifestyles between planktonic and biofilm growth modes.In this study, we performed mutation accumulation (MA) experiments in the environmental bacterium utations , 20. Of P. aeruginosa and S. enterica were taken from a PA14 transposon insertion library [mutS gene was replaced with an Frt-Kanamycin-Frt cassette in the S. enterica serovar Typhimurium LT2 background), respectively. Bacterial cultures were grown in 96-well plates with continuous shaking at 180 rpm. To synchronize the growth of the studied species, P. aeruginosa and S. enterica cultures were grown at 37 °C in LB medium  and at 30 °C in LB medium supplemented with 0.2% glucose, respectively  and weak bottleneck (WBN) cultures were diluted to 1 and 100 cells per 100 μl, respectively, and S. enterica cultures were diluted to 1 (SBN) and 250 (WBN) cells per 100 μl (see Supplementary Note SStarting cell lines of https://www.python.org/). The sequencing coverage was analyzed using SAMtools and was determined to be on average 32×. After quality filtering of specific nucleotide variations, mutations were checked using Integrative Genomics Viewer (v.2.3.98) [For whole-genome sequencing, genomic DNA was isolated from, in total, 83 planktonic overnight cultures using the DNeasy Blood & Tissue kit  and fragmented using the S2/E210 Focused-ultrasonicator  to achieve 400-nt-long fragments. Libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina  according to the manufacturer’s instructions. The libraries were sequenced using Illumina MiSeq (2 × 250-bp paired-ended reads). Reads were mapped to PA14 reference genome using Burrow–Wheeler Aligner , re-mapphttps://www.perl.org/) and C shell scripts. Differential gene expression was estimated with the help of custom R scripts utilizing DESeq2 [RNA sequencing was performed for three randomly selected clonal isolates from each WBN cell line. RNA was extracted from the logarithmic stage cultures of the selected clones and further processed as described in the protocol in Supplementary Note Sg DESeq2 , tidyverGalleria mellonella (greater wax moth) infection model [Fitness was analyzed by determining the optical density of the cultures throughout the growth phase. Swimming assays were performed as previously described . Virulenon model . Biofilmon model , 30. In on model . The detP. aeruginosa mutant through defined weak bottlenecks (WBNs) in standard laboratory conditions  measurements demonstrated that evolved P. aeruginosa WBN clones developed a shortened lag phase   rates in P. aeruginosa, no differences in nucleotide substitution rates between WBN and SBN cell lines in either of the species were detected, indicating that there was no clear selection pattern for SNPs in the various bottlenecking conditions of our MA experiment.To identify mutation patterns that reflect the st) Fig. . Among tS. enterica WBN and SBN cell lines, and the rate of intragenic indels in P. aeruginosa WBN cell lines was comparable to that of the S. enterica WBN cell lines. However, the rate of intragenic indels in P. aeruginosa SBN cell lines was ~50% higher as compared to the P. aeruginosa WBN cell lines   Fig. . IntrageP. aeruginosa as compared to S. enterica (p < 0.001 for WBN cell lines and p = 0.09 (nonsignificant) in SBN cell lines, Mann–Whitney test). Interestingly, we found an enrichment in intergenic indels that preceded genes of the functional COG category “cell wall/membrane/envelope biogenesis”  exclusively in the P. aeruginosa WBN cell lines, indicating that there was a positive selection for the respective indels.In the intergenic regions, the rate of indels did not differ between WBN and SBN cell lines of the same species Fig. . HoweverP. aeruginosa WBN clones, we re-analyzed the previously recorded genome sequences of 414 P. aeruginosa clinical isolates [P. aeruginosa indels that were exclusively found in WBN cell lines were also found in at least one and up to 213 clinical isolates. At the same time only 9 out of 22 indels that recorded exclusively in upstream gene regions in P. aeruginosa SBN cell lines were found in at least one clinical isolate. The significantly higher rate of intragenic WBN indels that were found in the clinical isolates  implies that the intergenic indels in the P. aeruginosa WBN cell lines are subject to positive selection also in P. aeruginosa clinical isolates, probably, due to their effect on the transcription and/or translation of downstream genes. Since a majority of the indels are within homopolymeric tracts, phase variation might facilitate adaptation to rapidly varying environments without the requirement for random mutations.To further confirm that the indels in the intergenic homopolymeric tracts are under positive selection in the isolates . Thirty P. aeruginosa WBN clones are translated into fitness changes, we randomly selected three isolates from each of the five WBN cell lines and compared the gene expression profile of these 15 evolved WBN clones with that of the starting cell line  genes, including PA14_14330 (spcS ortholog), exoY, pscBCDE, exsABC, PA14_42380 (exsD ortholog), PA14_42410 (exsE ortholog), popDBN, pcrDGHRV, pcr1-4 orthologs, pscNOPQRTU, and PA14_42630. The rsmZ/rsmY-downregulating clones also showed lower expression of type-VI secretion system (T6SS) genes , fha1, hsiB1, hsiC1, hcp1, clpV1) , PA14_20760 (cheR ortholog), and chemotaxis transducers PA14_28050, PA14_58650, PA14_61300, and PA14_67010) , PA14_64050 (pleD ortholog), and PA14_56280 (sadC ortholog)) were found in two thirds of the clones (9 out of 15). Changes in expression of rsmZ, rsmY, and genes encoding T3SS, T6SS, and di-guanylate cyclases are well known to be linked to the switch between motile and sessile lifestyles [To obtain a deeper understanding of how the genetic changes in the ne Table . The expfestyles –43. ThisWe observed a high variation in swimming motility between individual WBN clones Fig. . Their pG. mellonella model, showed extreme variability with phenotypes ranging from almost avirulent to more virulent than the starting cell line , which ulations , 48. A bP. aeruginosa strain evolved higher fitness in LB through a multitude of different pathways related to membrane biogenesis and fine-tuning of the balance between fast growing planktonic and sessile biofilm-associated lifestyles. We speculate that phase variation due to indels in intergenic homopolymeric tracts and adaptive changes engaging complex regulatory circuits with highly redundant c-di-GMP metabolic enzymes act in synergy, allowing P. aeruginosa to produce phenotypic diversity, maintain high versatility, and efficiently colonize new habitats.In conclusion, we demonstrated that the WBN clones of the hypermutator Supplemental MaterialTable S1