To evaluate the potential biological involvement of miRNA expression in the immune response and beta cell function in T1D. We screened 377 serum miRNAs of 110 subjects divided into four groups: healthy individuals (control group) and patients at different stages of T1D progression, from the initial immunological manifestation presenting islet autoantibodies (AbP group) until partial and strong beta cell damage in the recent (recent T1D group) and long-term T1D, with 2 to 5 years of disease (T1D 2-5y group).Conclusions/Interpretation. Our data suggests a potential influence of DEMs on disease progression from the initial autoimmune lesion up to severe beta cell dysfunction and the role of miRNAs hsa-miR-16 and hsa-miR-200a-3p as biomarkers of T1D progression. The results revealed 69 differentially expressed miRNAs (DEMs) in relation to controls. Several miRNAs were correlated with islet autoantibodies , age, and C-peptide levels, mainly from AbP, and recent T1D groups pointing these miRNAs as relevant to T1D pathogenesis and progression. Several miRNAs were related to metabolic derangements, inflammatory pathways, and several other autoimmune diseases. Pathway analysis of putative DEM targets revealed an enrichment in pathways related to metabolic syndrome, inflammatory response, apoptosis and insulin signaling pathways, metabolic derangements, and decreased immunomodulation. One of the miRNAs' gene targets was DYRK2 , which is an autoantigen targeted by an antibody in T1D. ROC curve analysis showed hsa-miR-16 and hsa-miR-200a-3p with AUCs greater than for glucose levels, with discriminating power for T1D prediction greater than glucose levels.  They can be released actively by cells or during tissue damage and have been used as biomarkers of destruction or regeneration of beta cells and of altered immunological activity, revealing mechanisms underlying the pathophysiology of type 1 diabetes . A previThe study was approved by the Ethical Committee of Hospital das Clinicas, Faculdade de Medicina, Universidade de São Paulo (Cappesq 11601), and followed the guidelines of the Declaration of Helsinki. Informed consent was obtained from all patients. Collected serum samples were stored at −80°C until use. Hemolyzed samples were excluded.n = 25), newly diagnosed patients with T1D with duration ≤6 months , patients with T1D with 2 to 5 years of duration , and islet autoantibody negative healthy individuals . Exclusion criteria comprised other types of diabetes, use of medications except insulin, a febrile state within 10 days prior to blood collection, and individuals with liver, kidney, thyroid, and inflammatory/autoimmune diseases.We screened 377 serum miRNAs of 110 subjects divided into four groups according to ADA criteria : individp < 0.05). AbP group presented intermediate characteristics (lower HbA1c and IA2A and higher C-peptide levels than both groups with T1D) and differed from the controls by higher IAA and GADA levels. HLA high-risk alleles for diabetes  were less frequent in the control group (p < 0.05).Demographic characteristics, such as age, self-reported skin color, and sex were similar between groups . PatientμL serum samples using the miRNeasy Serum/Plasma kit , and the reverse transcription reaction was performed using Megaplex™ RT Human Pool A , TaqMan® MicroRNA Reverse Transcription Kit , according to manufacturer's instructions. The RT products were preamplified according to the manufacturer's protocol—Megaplex™ pool for microRNA Expression Analysis . Real-Time RT-PCR was performed using the TLDA TaqMan® Low Density Array-Card A v2.0 for humans (384 microRNAs), according to manufacturer's instructions, on the QuantStudio12K Flex .RNA/miRNAs were isolated from 200 http://zmf.umm.uni-heidelberg.de/mirwalk2), TargetScan Human v7.2, 2018 (https://www.targetscan.org/vert_72/), and IPA software . Pathway enrichment analysis was performed using IPA and KEGG database (https://www.genome.jp/kegg/tool/map_pathway1.html), considering only experimentally validated DEM targets and prioritized targets related to beta cell function and autoimmune manifestations.The potential targets of the differentially expressed miRNAs (DEMs) were predicted using miRWalk v2.0, 2018 , HbA1c by HPLC, and C-peptide levels by radioimmunoassay . IAA, GADA, and IA2A levels were determined by radioimmunoassay . The normal values for 700 healthy controls (3 SD) were <100nU/mL, <25 IU/mL, and <125 IU/mL, respectively. ZnT8A levels were measured by ELISA . The normal value in 321 healthy controls was ≤16 IU/mL (3 SD).τ comparative method [ΔΔCt-), using global normalization and Benjamini and Hochberg's false discovery rate method, and represented as fold change (FC) in relation to controls. Values >1 were considered increased and < 1 decreased. Variable distributions were verified by the Shapiro–Wilk normality test. Numerical variables with parametric and nonparametric distributions were analyzed by ANOVA and Kruskal–Wallis with Tukey's or Dunn's multiple comparisons posttest, respectively. Correlations were performed using the Spearman correlation test. Qualitative variables were compared using chi-square test or Fisher's exact test . Data were considered significant at p < 0.05. Fisher exact test and the Benjamini and Hochberg's false discovery method were applied to obtain the target pathways in IPA analysis.The analysis of miRNAs expression used the Cloud program , an online data analysis software of the Ce method . The thrWe performed miRNA profiling from 110 subjects divided into four groups   comprisiWe observed that T1D progression leads to a predominance of miRNAs upregulation in serum when compared to controls. The most upregulated DEMs were miR-200a-3p, in both the AbP and recent T1D groups and miR-346 in T1D 2-5y group, respectively. The downregulated miR-16 was the only miRNA that differed from controls simultaneously in the three groups.p < 0.0025 and AUC = 0.8342, p < 0.0004, respectively) presenting higher discriminating power, even when we compared to the glucose ROC curve (Receiver operating characteristic (ROC) curve analysis revealed that miR-16-5p and miR-200a-3p can be used as T1D predictors .Five miRNAs  were downregulated only in the AbP group, whereas miR-323a-3p and miR-874-3p were upregulated both in the recent T1D and T1D 2-5y groups. Most of the other miRNAs from cluster A were increased only in the AbP and T1D 2-5y groups.Fifty-nine 15.6%) of the 377 miRNAs evaluated were not expressed in any group . The influence of glucose levels was suggested by both positive and negative correlations of glucose and/or HbA1c levels with several up and downregulated miRNAs. The correlations of miRNA with C-peptide levels and with age were usually negative in both clusters.IA2A, GADA, and Znt8A levels correlated positively with 13, 12, and 1 miRNAs, respectively. Negative correlations were found for IA2A levels with miR-19a-3p and for ZnT8A levels with miR-100-5p and miR-16-5p Tables –6. CorreIn both clusters, most pathways potentially regulated by DEMs were related to cancer, cell growth and metabolism , insulin production, and axon guidance/neurotrophin signaling pathways. Adherens junction and apoptosis pathways were enriched by DEMs' targets from the T1D 2-5y group.The deregulated miRNAs were referred to several biological pathways by the miRWalk database, retrieving 206 and 140 pathways modulated by up- and downregulated miRNAs in cluster A Suppl. . In bothPathway enrichment analyses were performed using KEGG and IPA software. Figures Targeting and pathway analysis using IPA software identified highly predicted and/or experimentally observed targeting information from 10 DEMs (out of 16) in the AbP group with 359 targets: 1 DEM (out of 4) in the recent T1D group with 198 targets and 45 DEMs (out of 64) in the T1D 2-5y group with 1033 targets.After excluding cancer-related pathways, we identified a total of 366, 320, and 425 enriched canonical pathways related to DEMs' targets from the AbP, recent T1D, and T1D 2-5y groups, respectively Suppl. . The topβ-oxidation III, salvage pathways of pyrimidine deoxyribonucleotides, pentose phosphate, and NAD biosynthesis III pathways  signaling, cell cycle regulation by antiproliferative BTG family proteins, cell cycle checkpoint control, EGF signaling, senescence, and autophagy pathways. miR-200a-3p has the most targets related to metabolic pathways, e.g., ascorbate recycling, PRPP (phosphoribosyl pyrophosphate) biosynthesis I, glutathione redox reaction II, melatonin degradation II, fatty acid pathways .We identified miRNA dysregulation during T1D evolution. By comparing patients at different stages of disease progression with healthy individuals, from the initial immunological manifestation (one to three autoantibodies in AbP group) until partial and strong beta cell damage in the recent T1D and T1D 2-5y groups, we have found 69 differentially expressed miRNAs. These miRNAs have predicted targets related to immune regulation, metabolism, glucose homeostasis, cell proliferative/survival mechanisms, and beta cell function. Dysregulated expression of miRNAs pointed to possible mechanisms underlying the pathophysiology of T1D. The AbP group could also provide the effects of miRNA dysregulation and pathways predicted to be activated during the onset of islet autoimmunity that are unrelated to blood glucose levels. The most enriched pathways potentially regulated by DEMs were related to immune cell activation, inflammation, and apoptosis.The miR-200a-3p was the most highly expressed miRNA in AbP and recent T1D groups positively correlated to IA2A and GADA levels, suggesting a robust association with T1D pathogenesis. miR-200a was previously reported to be highly expressed in beta cells , being aOther important target of this miRNA is the thioredoxin-interacting protein (TXNIP). Its proapoptotic and diabetogenic function prevents beta cell function via induction of miR-200a in vitro. The TXNIP/miR-200/Zeb1/E-cadherin signaling pathway links miR-200 to beta cell apoptosis and diabetes and links TXNIP to inhibition of epithelial-mesenchymal transition (EMT), a process involved in beta cell expansion , predictBesides miR-200a-3p, other upregulated miRNAs (miR-181a and miR-323) were also described as inhibitors of EMT , which cAmong the upregulated DEMs, we also observed miR-296, miR-874 , and miR-518, all previously associated with apoptosis signaling . Others p = 0.004), probably subjected to effects of longer diabetes duration, decreasing antibody titers, and to other stimuli such as metabolic disturbances. Exceptions to all trends in immune activation were observed for miR-100-5p, negatively correlated to ZnT8A  , 22 and  = 0.044), and oppignaling .r = −0.358; p = 0.044). The most enriched pathways for miR-16 predicted targets were related to cell cycle regulation and division, checkpoint control, and DNA repair , probably influenced its great decline in the T1D 2-5y group. Other five miRNAs downregulated only in the AbP group are involved in immune regulation (miR-195-5p and miR-590-5p) [The insulin resistance due to autoimmune aggression and the release of inflammatory cytokines might function decreasing the levels and the protective role of miR-16 . miR-16 -590-5p) , cell pr-590-5p) , 35, and-590-5p) . Their dTherefore, parts of upregulated genes, including those in the AbP group, reveal a profile toward inflammation, apoptosis, and commitment of beta cell and insulin secretion, evidencing cluster A DEMs as relevant to autoantibody development, decreased C-peptide levels, T1D pathogenesis, and progression. Few miRNAs were associated with immunomodulation and anti-inflammatory effects.The expression of most miRNAs of the cluster A followed a similar pattern in the three groups, although not always with statistical significance. The worsening of beta cell function, dysregulation of glucose levels, and insulin resistance probably accounted for the progressive upregulated trend of the expression of these miRNAs toward the T1D 2-5y group, particularly for miR-518b and miR-323a-3p, interfering negatively with beta cell expansion  and insun = 51) conferred similar results. Most upregulated miRNAs were present in human pancreatic beta cells [Thus, the altered expression of miRNAs from cluster A may be implicated in the cycle of damage regeneration of beta cells, inflammation, and metabolic disorders, contemplating insulin resistance and later, hyperglycemia. Cluster B , upregulated in the three groups, seems to activate the protein kinase RNA-activated; an interferon-inducible kinase maybe related to defense against viruses .The analysis using miRWalk and KEGG databases reinforced the relevance of both clusters in the autoimmune process. The potential biological pathways enriched by DEMs targeted oncogenic/proliferative and metabolic pathways, processes related to cell differentiation, migration, survival, apoptosis, neural development, insulin signaling, and immune system pathways. Most of these pathways are essential for proper lymphocyte development and function, and their enrichment, which was greater in cluster A, may be a reflection of the autoimmune activity.Interestingly, these pathways were enriched by up- and downregulated miRNAs from both clusters, although through different targets.Pathways related to survival (autophagy in cluster A) and self-renewal capacity (regulating pluripotency of stem cells in cluster B) were less modulated by downregulated miRNAs, perhaps in an attempt to contain the self-aggression.Pathway enrichment analyses were performed using KEGG and IPA software. Figures HIPK1) and B  and by downregulated miRNAs in clusters A (BRWD1) and B .Genes related to B and T cell differentiation/function were targeted by upregulated miRNAs in cluster A  and B (KCNJ6) and downregulated miRNAs in clusters A PLAG1) and B FBXO28). Importantly, one of the miRNAs' gene targets from cluster A was DYRK2 , which is an autoantibody target antigen in T1D . The DEM and B (F8. ImportOne of the most significantly enriched canonical pathways in the three groups , pathogeOn the opposite direction, there was the aryl hydrocarbon receptor pathway, enriched in all three groups. It modulates the development and functionality of immune cells and suppresses the expression of inflammatory cytokines during diabetes development . DEMs frIn general, DEMs from all groups target mechanisms related to growth, cell cycle regulation, apoptosis, inflammation, defense, and neuronal pathways, whereas few of them favored defense against an autoimmune offensive. The commitment of these pathways increased progressively from AbP to the recent T1D and then to T1D 2-5y group, which regulated the largest number of targets in most pathways, many of them expressing innate and adaptive immune responses. The metabolic dysregulation probably influenced these results.Of note, similar pathways were enriched by both up- and downregulated miRNAs, triggered probably by different causal hits. Other possibility is the intense metabolic derangement due to glucose/lipotoxicity and inflammatory cytokines, eliciting miRNAs from inflammatory pathways. This can also explain some inconsistent results in the literature, where the same miRNA predisposed or protected from T1D or other autoimmune diseases. Diabetes duration, age of patients, and glucose levels could have acted in miRNA deregulation during disease progression and taken part in these inconsistencies, pointing to the importance of these variables in disease determinations. This can be further evidenced when considering the 69 miRNAs from clusters A to B, where 26 DEMs correlated with glycemic status, 19 with autoantibodies levels and ongoing islet autoimmunity, and 20 miRNAs correlated negatively with age. T1D duration influenced positively and negatively the levels of 19 miRNAs and their association with autoantibody titers, which are known to decrease with time. However, these results should be considered carefully, considering the sample size and low serum RNA yield.Although the serum miRNA profile might not mirror the situation in the affected pancreas, it is notable that most of the DEMs of our cohort are miRNAs enriched in beta cells, suggesting they may correlate with the severity of beta cell injury. Ongoing destruction of beta cells could result in diffusion of islet-enriched miRNAs into serum, as observed during the autoimmune attack in animal models of diabetes . FurtherIn conclusion, our data suggested the potential role of miRNAs favoring the preponderance of pathways compromising beta cell function throughout diabetes progression like increased apoptosis, inhibition of EMT, impaired TREG function, inflammatory pathways like STAT3 and PTEN, and senescence probably being indirect signs of islet autoimmunity and metabolic derangements due to gluco-lipid toxicity. The higher discriminating power for T1D prediction for miR-200a-3p and miR-16-5p, distinguishing patients from the different stages of T1D, suggested both miRNAs as potential biomarkers and targets for beta cell recovery.


Background and Objectives: The global spread of carbapenem resistance and the resulting increase in mortality forced the World Health Organization (WHO) to claim carbapenem-resistant enterobacteriaceae (CRE) as global priority pathogens. Our study aimed to determine the prevalence of carbapenemase-encoding genes and major plasmid incompatibility groups among Gram-negative hospital-based isolates in Egypt. Material and Methods: This cross-sectional study was carried out at Mansoura University Hospitals over 12 months, from January to December 2019. All the isolates were tested for carbapenem resistance. The selected isolates were screened by conventional polymerase chain reaction (PCR) for the presence of carbapenemase genes, namely KPCbla, IMPbla, VIMbla, and NDM-1bla. PCR-based plasmid replicon typing was performed using the commercial PBRT kit. Results: Out of 150 isolates, only 30 (20.0%) demonstrated carbapenem resistance. Klebsiella pneumoniae was the most resistant of all isolated bacteria, and NDMbla was the predominant carbapenemases gene, while the most prevalent plasmid replicons were the F replicon combination  and A/C. Plasmids were detected only in Klebsiella pneumoniae, Escherichia coli, Enterobacter cloacae, and Pseudomonas aeruginosa. Remarkably, we found a statistically significant association between carbapenemase genes and plasmid replicons, including NDMbla, IncA/C, and IncX. Conclusions: Our study demonstrated an alarming rise of plasmid-mediated carbapenem-resistant bacteria in our locality. The coexistence of resistance genes and plasmids highlights the importance of a targeted antibiotic surveillance program and the development of alternative therapeutic options at the local and international levels. Based on our results, we suggest a large-scale study with more Enterobacteriaceae isolates, testing other carbapenemase-encoding genes, and comparing the replicon typing method with other plasmid detection methods. We also recommend a national action plan to control the irrational use of antibiotics in Egypt. The unrestricted access to antibiotics and empirical and preventive overuse, together with the antibiotic addition to animal food, may be responsible for the dramatic increase in drug-resistant bacteria, especially in hospitals .Enterobacteriaceae and Pseudomonas, are frequently implicated in hospital infections, representing a significant clinical and socioeconomic burden [Although all bacteria have the potential to develop antibiotic resistance, Gram-negative bacteria, particularly c burden .Since extended-spectrum β-lactamase (ESBL)-producing bacteria became a dramatic reality, this imposed a change in the first-line empirical treatment from penicillins to carbapenems ,4.enterobacteriaceae (CRE) as global priority pathogens [The global spread of carbapenem resistance and the resulting increase in mortality forced the World Health Organization (WHO) to claim carbapenem-resistant athogens ,5,6,7.Enzyme-mediated resistance to carbapenems is mediated by beta-lactamases that are capable of inactivating carbapenems and other beta-lactam antibiotics and are hence referred to as carbapenemases . This tyEnterobacteriaceae contain a wide range of carbapenemases from the three Ambler classes of β-lactamases: A, B, and D [Klebsiella pneumoniae carbapenemase gene (KPC), Verona integron-encoded metallo-β -lactamase gene (VIM), IMP-type metallo-β-lactamase gene (IMP), New Delhi metallo-β-lactamase gene (NDM), and oxacillinase group of β-lactamases gene (OXA-48) are the most potent carbapenemase-producing genes in terms of carbapenem hydrolysis and geographic spread [B, and D . The Klec spread .Enterobacteriaceae strains worldwide [Although several studies have been carried out on the detection of plasmid-mediated clinical isolates of orldwide ,11,12,13orldwide ,15.Hence, we performed this study to determine the prevalence of carbapenemase-encoding genes and major plasmid incompatibility groups among Gram-negative hospital-based isolates in Egypt.A cross-sectional observational study was conducted in the period between January 2019 and December 2019 at Mansoura University Hospitals. The study was compliant with the Helsinki Declaration, and all included patients signed informed consent forms. In this specific form, it was explicitly written that data derived from routine exams performed in the Mansoura University Hospitals could be used for research if anonymized.In the present study we enrolled (a) adult patients (>18 year) who were (b) immunocompetent and (c) who signed the informed consent form. Likewise, we excluded (a) pediatric patients, (b) transplanted patients, (c) HIV-positive patients, and (d) patients undergoing chemotherapy, immunotherapy, or radiotherapy.Over the period of one year, a total of 150 Gram-negative isolates were tested. All isolates were identified based on colony morphology, Gram staining, and biochemical tests  , followed by confirmation using the Vitek 2 system  according to the manufacturer’s instructions.Antimicrobial susceptibility testing was performed according to Clinical and Laboratory Standards Institute recommendations (M100 document) . The difThe selected isolates were resistant to ertapenem (≤18 mm), imipenem (≤19 mm), and/or meropenem (≤19 mm). The resistant isolates were confirmed by the Vitek 2 system  at MIC values ≥ 2 µg/mL for ETP and ≥4 µg/mL for IPM and MEM.NDMbla, KPCbla, IMPbla, and VIMbla) as follows.PCR testing was performed for the detection of different carbapenemase genes  , and incubating them at 37 °C for 18 h. An amount of 1 mL of the overnight bacterial culture was centrifuged at 8000× g for 10 min). The clarified supernatant was transferred to a clean 1.5 mL Eppendorf tube. The isolated DNAs from boiled lysates were checked for quality and purity by Nanodrop ; good-quality DNA had an A260/A280 ratio of 1.8–2.0. All DNA samples were stored at −80 °C until used for gene detection.Lysate preparations were clarified by centrifugation : F 5′-CATGGTTTGGTGGTTCTTGT-3′ and R 5′-ATAATTTGGCGGACTTTGGC-3′ to amplify 488 bp fragment [VIMbla which belongs to class B metallo-b-lactamases (MBLs): F 5′-ATTGGTCTATTTGACCGCGTC-3′ and 5′-TGCTACTCAACGACTGAGCG-3′ that amplify 780 bp fragment [NDM-1bla : F 5′-GGTTTGGCGATCTGGTTTTC-3′ and R 5′-CGGAATGGCTCATCACGATC-3′ to amplify 621 bp fragment  and 500 mM KCl, and 40 µM of deoxynucleotide triphosphate (dNTPs) were used. To obtain this concentration, a mix of 18 µL 2x Taq PCR master mix, 4.5 µL distilled water, and 0.25 µL of each forward and reverse primers was added to 2 µL of supernatant containing DNA used as the template for the PCR reaction . Perkin-Elmer’s thermal cycler  was programmed for pre-denaturation at 95 °C for 5 min, 35 cycles of reaction at 95 °C for 45 s for denaturation, 48 °C for 30 s with KPCbla, 52 °C for IMPbla, VIMbla, and NDMbla for annealing and extension at 72 °C for 45 s, and final extension at 72 °C for 7 min. The amplified product was electrophoresed after application of ethidium-bromide-stained 1.5% agarose gel for the detection of specific bp products for each gene.Amounts of 50 ng of DNA, 0.25 pM of each forward and reverse primer, 2 µL of Taq polymerase in a buffer containing 100 mM Tris-HCl, 1.5 mM of MgClThis kit is a set of 8 specific standard PCR assays optimized to perform 8 multiplex PCRs for the amplification of 25 replicons, HI1, HI2, I1, I2, X1, X2, L/M, N, FIA, FIB, FIC, FII, FIIS, FIIK, W, Y, P, A/C, T, K, U, R, B/O, HIB-M, and FIB-M, representative of major plasmid incompatibility groups and replicase genes identified on resistance plasmids circulating among Gram-negative bacteria  ,12,13,14For PBRT, total DNA was obtained by the boiling lysis method according to the manufacturer’s instructions . DNA purp-value was ≤0.05.After anonymizing all clinical and demographic inpatient data, the statistical analysis was performed. Data were entered and analyzed using IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY, USA: IBM Corp. Quantitative data were expressed as frequency and percentage. The Chi-Square test (or Fisher’s exact test) was used for qualitative data from two groups. For qualitative data from more than two groups, the Chi-Square test with the Bonferroni method was used. For any of the used tests, results were considered statistically significant if the Klebsiella pneumoniae, 8 (26.7%) were Escherichia coli, 5 (16.7%) were Enterobacter cloacae, 4 (13.3%) were Pseudomonas aeruginosa, and 3 (10%) were Citrobacter freundii. Klebsiella pneumoniae was the most frequent carbapenem-resistant organism isolated from wounds. Positive cultures were mostly obtained from cutaneous wound aspirates, blood cultures, catheter tips, and sputum. For more details, see Among 150 isolates, only 30 (20%) demonstrated carbapenem resistance. Out of the 30 isolates, 10 (33.3%) were NDM 15bla (50%) was the highest, followed by VIMbla 9 (30%), IMPbla 8 (26.7%), and KPCbla 7 (23.3%). Out of the 30 tested isolates, 21 harbored at least one of the carbapenemase-producing genes; however, there was no statistically significant difference in the distribution of genes in different organisms. Klebsiella pneumoniae had the most copies of the NDMbla gene (six isolates), followed by Escherichia coli (five isolates). However, nine isolates, including three Klebsiella pneumoniae, two Enterobacter cloacae, two Pseudomonas aeruginosa, one Citrobacter freundii, and one Escherichia coli, did not have any of these genes.The frequency of carbapenemase-encoding genes in tested organisms is shown in E. coli and one Enterobacter cloacae).Some isolates exhibited a heterogeneous pattern of carbapenemase-encoding genes, ranging from dual positivity (six isolates) to triple positivity (three isolates), while quadruple positivity was detected in two isolates ), with a statistically significant difference . On the other hand, samples with no detectable plasmids were three Citrobacter freundii (60%) and two Pseudomonas aeruginosa (40%).Plasmids were detected in 25 isolates  isolates, FIIK in 4/10 (40%) isolates, and A/C, FIB, P, and R in 3/10 (30%) isolates each. Among Escherichia coli isolates, replicons A/C, FIIK, I1 α, L, and R were found three out of eight (37.5%) of isolates, whereas replicons FIA and FII  and FIB  were most abundant among Enterobacter cloacae and Pseudomonas . On the other hand, two replicons were detected in four Klebsiella pneumoniae isolates. Remarkably, polyreplicons were found in 13 isolates, with plasmid replicons ranging from 3 to 8. The most frequent replicons detected were FIB, I1α, and FIIK in eight isolates, followed by FIA and R in seven isolates each.An analysis of the data in Multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria infections are critical challenges for public health institutes due to limited antibiotic choices and high mortality ,22,23. TKlebsiella pneumoniae and Escherichia coli topped the list of carbapenem-resistant bacteria. In line with our findings, Raheel et al. described that 34.1% of the isolated Enterobacteriaceae were carbapenem resistant [K. pneumoniae and Escherichia coli were isolated at rates of 47.6% and 28.6%, respectively [In our study, 20% of the isolates were carbapenem resistant. esistant . Similarectively .NDMbla was the most frequently detected in 15 isolates. The solidity of our results was also confirmed by a 2-year study focused on Enterobacteriaceae isolates in 40 countries around the world, in which NDMbla was the most common gene  linked to carbapenem resistance [K. pneumoniae isolates, NDMbla was the most dominant gene (92.9%) [Interestingly, when we looked at the prevalence of different carbapenemase genes, sistance . Additio (92.9%) .NDMbla, KPCbla, and VIMbla were the most common resistance genes in patients with surgical site infections [KPCbla was also found in 13.6% of isolates in a recent study at Ain Shams University Hospital [Focusing on Egypt, similar findings were reported in a study by El-Kholy and her colleagues, in which fections ; blaKPC Hospital . The widTo our surprise, we detected a higher prevalence of concurrent multiple carbapenemases, namely dual positivity in six isolates, triple positivity in three isolates, and quadruple positivity in two isolates. In accordance with our results, multidrug resistance strains are continuously reported worldwide ,30, and Escherichia coli, Enterobacter cloacae, and Klebsiella pneumoniae. In coherence with the findings of Zharikova et al., the absence of plasmid replicons in Citrobacter freundii isolates may be explained by the small plasmid size (2–15 kb) that was hardly detected by our method [Remarkably, we detected plasmid replicons in 25 isolates (83.3%), prevalently carried by r method Enterobacteriaceae worldwide [Enterobacteriaceae were carbapenem resistant, with one Klebsiella pneumoniae carrying multireplicon plasmids (Inc types A/C and FII) [Remarkably, polyreplicons were found in 13 isolates, with plasmid replicons ranging from 3 to 8. The most frequent replicons detected were FIB, I1α, and FIIK in eight isolates, followed by FIA and R in seven isolates each. Moreover, InF  multireplicon plasmids in different combinations with other plasmids were detected in this study. In the literature, replicons F, A/C, and I1α are regarded as the main plasmid families associated with the spread of resistance genes in isolated orldwide . A recenand FII) . The impEnterobacteriaceae [In line with previously published Chinese and European reports, we found that the IncF plasmid was prevalent in carbapenem-resistant eriaceae ,36. IncFeriaceae .In some organisms (three isolates), there were no detected genes and no plasmid replicons, with the possibility of different resistance mechanisms other than carbapenemase production. On the other hand, some organisms expressed resistance genes without detectable plasmids (two isolates), with the possibility of the presence of a small plasmid or the presence of these genes on the bacterial chromosome. In addition, there were some organisms with plasmids detected but no resistance genes detected (six isolates), with the possibility of the presence of genes other than those tested in this study.Klebsiella pneumoniae had a 50% prevalence of Inc I1α, 40% of Inc FIIK, 30% of Inc A/C, 30% of FIB, 30% of P, and 30% of R. Escherichia coli, on the other hand, had a comparable plasmid replicon pattern with 37.5% Inc A/C, 37.5% FIIK, 37.5% I1, 37.5% L, and 37.5% R.Evaluating in greater detail the replicon prevalence in different Enterobacteriaceae, Escherichia coli isolates [Klebsiella isolates . Interestingly, we reported infrequent plasmid amplicons, such as IncY, in accordance with some previous studies [Conversely, Johnson et al. described the Inc FIB plasmid as the most frequent plasmid type linked to the spread of several ESBL genes in isolates . In the  studies ,39.Escherichia coli isolate displaying both the NDMbla gene and the IncA/C plasmid replicon. Pal et al. also reported an association between the NDM-7bla gene and the IncX3 plasmid in multidrug-resistant Escherichia coli isolates from the Arabian Peninsula [As regards the association between carbapenemase genes and plasmid replicons, we found an eninsula .This article presents several strengths but also has some limitations connected with the study design (single year) and the heterogeneity of the samples; at the same time, it could also be regarded as a starting point for a more extensive yearly evaluation of the MDR population in our locality.Enterobacteriaceae isolates, testing other carbapenemase-encoding genes, and comparing the replicon typing method with other plasmid detection methods. We also recommend a national action plan to control the irrational use of antibiotics in Egypt.Our study demonstrated an alarming rise of plasmid-mediated carbapenem-resistant bacteria in our locality. The coexistence of resistance genes and plasmids highlights the importance of a targeted antibiotic surveillance program and the development of alternative therapeutic options at the local and international levels. Based on our results, we suggest a large-scale study with more


Zanthoxylum armatum establishes apomictic reproduction, hence only female trees are cultivated. However, male and hermaphrodite flowers have recently appeared in female plants, resulting in a dramatic yield reduction. To date, the genetic basis underlying sex determination and apomixis in Z. armatum has been largely unknown. Here, we observed abortion of the stamen or carpel prior to primordium initiation, thus corroborating the potential regulation of MADS-box in sex determination. In Z. armatum, a total of 105 MADS-box genes were identified, harboring 86 MIKC-type MADSs with lack of FLC orthologues. Transcriptome analysis revealed candidate MADSs involved in floral organ identity, including ten male-biased MADSs, represented by ZaMADS92/81/75(AP3/PI-like), and twenty-six female-specified, represented by ZaMADS80/49 (STK/AGL11-like) and ZaMADS42 (AG-like). Overexpressing ZaMADS92 resulted in earlier flowering, while ZaMADS80 overexpression triggered precocious fruit set and parthenocarpy as well as dramatic modifications in floral organs. To characterize their regulatory mechanisms, a comprehensive protein-protein interaction network of the represented MADSs was constructed based on yeast two-hybrid and bimolecular fluorescence complementation assays. Compared with model plants, the protein interaction patterns in Z. armatum exhibited both conservation and divergence. ZaMADS70 (SEP3-like) interacted with ZaMADS42 and ZaMADS48 (AP3-like) but not ZaMADS40 (AP1-like), facilitating the loss of petals in Z. armatum. The ZaMADS92/ZaMADS40 heterodimer could be responsible for accelerating flowering in ZaMADS92-OX lines. Moreover, the interactions between ZaMADS80 and ZaMADS67(AGL32-like) might contribute to apomixis. This work provides new insight into the molecular mechanisms of MADS-boxes in sex organ identity in Z. armatum.As a typical dioecious species,  Zanthoxylum armatum DC, an evergreen dioecious tree belonging to the genus Zanthoxylum of family Rutaceae, is native to China and mainly distributed throughout Asia. This species, so-called Green Huajiao, has long been consumed as a spice and a traditional herbal medicine, attracting increasing attention very recently , which is also involved in floral meristem specification, while the B function is exerted via APETALA3 (AP3) and PISTILLATA (PI) and the C function by AGAMOUS (AG). Additionally, class D specifies the ovule identity represented by SEEDSTICK (STK/AGL11), SHATTERPROOF1 (SHP1/AGL1), and SHATTERPROOF2 (SHP2/AGL5). Class E genes SEPALLATA1 (SEP1/AGL2), SEP2/AGL4, SEP3/AGL9, and SEP4/AGL3 are required for the formation of all whorls of floral organs. For floral organ determination, class A+E genes specify sepals, A+B+E specify petals, B+C+E specify stamens, C+E specify carpels and C+D+E specify ovules, which function by protein interactions with each other and formation of tetrameric complexes   .Z. armatum can successfully trigger fruit set, bypassing fertilization via apomixis. Similar to citrus, Z. armatum is a typical sporophytic apomictic plant in which adventitious embryos are developed from nucellar cells, leading to ovule development. Apomixis may occur when abortion of sexual reproduction is caused by the mutation of corresponding genes and thus regulated by a molecular framework similar to sexual reproduction. So far, several genes have been identified associated with different types of apomixis  in Hieracium  identity. Moreover, functional characterizations and protein interactions were performed to reveal the possible involvements and molecular mechanisms of the candidates in floral organ initiation and development. Our findings lay the foundation for elucidating the molecular basis underlying sex determination and apomixis in Zanthoxylum armatum DC cv. ‘Jiuyeqing’ used in this study was cultivated in the germplasm nursery of Chongqing University of Arts and Sciences, Yongchuan District, Chongqing, China. Flowers and fruits at different developmental stages were harvested from 5-year-old male and female plants of Z. armatum, respectively. In brief, three vital periods of floral differentiation and development in male plants were collected, including stamen primordia differentiation (MFS1), stamen initiation (MFS2) and floral development (MFS3). Eight important periods of pistil and fruit development in female plants were sampled, which includes fruit set and fruit development period. There were four stages in fruit set period, such as pistil primordia differentiation (FFS1), ovule initiation (FFS2), ovule development, approximately 10 days and 17 days after ovule initiation, marked as FFS3 and FFS4, respectively. Afterwards, fruit samples at four developmental stages were collected, that was 20, 50, 80, and 110 days after fruit set, named as FFS5, FS6, FFS7, and FFS8, respectively. All the samples were collected from 9 individual plants and tissues from 3 plants were pooled and set as one replicate. Three biological replicates were performed in each experiment. All the tissues were placed in tubes, frozen in liquid nitrogen and then stored at -80° C until further use.® UltraTM RNA Library Prep Kit for Illumina®  following manufacturer’s recommendations. Briefly, mRNA was purified using poly-T oligo-attached magnetic beads. Then first and second strand cDNA were synthesized, DNA fragments were adenylated and ligated with NEBNext adaptor. Subsequently, cDNA fragments with preferentially 250~300 bp in length were purified with AMPure XP system , size-selected, adaptor-ligated, and then PCR performed and its products were purified (AMPure XP system). Finally, the library preparations were sequenced on an Illumina Novaseq platform and 150 bp paired-end reads were generated.Total RNA from different tissues including the flower and fruit was isolated by using QIAGEN RNeasy Plant Mini Kit. 1 µg RNA was used as input material for library construction. Sequencing libraries were generated using NEBNextde novo transcriptome assembly, functional annotation and screening of differentially expressed genes (DEGs) were performed. Trinity software (https://github.com/trinityrnaseq/trinityrnaseq/wiki) was employed to pool and assemble all the clean reads. To obtain functional annotation, the assembled contigs and unigenes were aligned against six public databases  using BLASTx . DESeq2 was employed to identify DEGs from transcriptome data. FDR< 0.001 and the absolute value of Log2 ratio > 1 was used to judge the significance of gene expression difference  and amino acids of the putative MADS-box genes. The query protein sequences were then subjected to NCBI BlastP analysis. Finally, all candidate MADS-box proteins were confirmed by comparison with the conserved domain against NCBI CDD (https://www.ncbi.nlm.nih.gov/cdd/) and Pfam (http://pfam.xfam.org/).The transcriptome data conducted in this study was used to search for MADS-box transcription factors in Arabidopsis M-type MADS and MIKC MADS family protein sequences were downloaded from Plant Transcription Factor Database v5.0 (http://planttfdb.gao-lab.org/). The alignments of amino acid sequences of AtMADSs and ZaMADSs were performed using Clustal X. A phylogenetic tree was constructed using MEGA5.0 software by the Neighbor-joining method, with a bootstrap test replicated 1,000 times, the p-distance method and pairwise deletion. An online software Evolview v2 (https://www.evolgenius.info/evolview/) was employed to embellish the phylogenetic tree. MEME suite (http://meme-suite.org/tools/meme) was employed to analyze the conserved motifs of MADS proteins. And the parameters were set as follows: maximum number of motifs, 10; minimum width, 6; and maximum width, 50.The MADS-box genes among flower and fruit development were subjected to the online software UniProt (https://www.uniprot.org/), String (https://cn.string-db.org/), and GeneMANIA (http://genemania.org/).To obtain protein‐protein interactions among MADSs, the differentially expressed ZaMADSs and their truncated versions were amplified by PCR and cloned into pGBKT7 vector  by using Takara In-Fusion HD cloning kit. Primers were listed in ZaMADSs-pGBKT7 plasmids were transformed into Y2H Gold yeast cells and spread onto SD/-Trp, SD/-Trp/X-α-gal and SD/-Trp/X-α-gal/AbA plates for transcriptional activation determination. Empty pGBKT7 vector was also transformed into the yeast cells as a negative control.The GAL4-based yeast two-hybrid (Y2H) system was employed to assay the transcriptional activity of the central ZaMADSs of the protein interaction network, including ZaMADS40, ZaMADS42, ZaMADS50, ZaMADS70, ZaMADS80, ZaMADS89 and ZaMADS92. The full-length cDNA sequence of these ZaMADSs with no transcriptional activation activity above tested were used as baits. The full-length cDNAs of the different ZaMADS genes, including ZaMADS40, ZaMADS42, ZaMADS48, ZaMADS50, ZaMADS54, ZaMADS57, ZaMADS67, ZaMADS70, ZaMADS74, ZaMADS75, ZaMADS89 and ZaMADS95 were amplified using the primers listed in Y2H system was also carried out to investigate protein interactions. The full length or truncated ZaMADS80 and ZaMADS92 were ligated into the pNC-BiFC-Enn vector to generate nYFP fusion proteins, while the ORFs of ZaMADS75, ZaMADS40 and ZaMADS67 were ligated into the pNC-BiFC-Ecn vector to generate cYFP fusion proteins by using Nimble Cloning kit . The primers used were listed in Nicotiana benthamiana. After 72h of co-culture, the fluorescent protein signals were visualized by Leica DMi8 confocal laser scanning microscopy  at Yangtze University.The vectors of BiFC (pNC-BiFC-Ecn and pNC-BiFC-Enn) and protocol of the BiFC assay were performed as described in our previous study . In brieZaMADS80 and ZaMADS92 overexpression (OX) plants, the ORF sequences of these two genes without the stop codon were amplified using TransStart FastPfu Fly DNA Polymerase  and primers listed in ZaMADS80 and K303-ZaMADS92 were transferred to Agrobacterium tumefaciens GV3101 for wild-type tomato (Solanum lycopersicum L. cv. Micro-Tom) genetic transformation according to A. tumefaciens harbored ZaMADS92 overexpression vector was transformed into Arabidopsis thaliana by floral dipping. The positive transgenic lines were screened with 100 mg/L kanamycin and confirmed by PCR. The T2 transgenic seedlings were used to observe the phenotypic characteristics.To generate ZaMADS80-OX lines, 7-day fruit was collected, fixed in Carnoy’s Fluid for 48 h at 4°C, sectioned, stained with Safranin O-fast green, and photographed by a standard bright field light microscope  with a CCD camera. In addition, we observed the flowering time, the morphology of flower and fruit in wild-type and ZaMADS92-OX Arabidopisis.Phenotypical characterization was performed on at least three independent transgenic tomato lines. For flower organ formation and development, the morphology of flower organs including sepals, petals and stamens was observed by a Cannon EOS 5D Mark digital camera  and a Leica S9i stereomicroscope , while the flowering time, the number of sepals and petals in each flower, as well as the quantity of flowers were documented. For fruit initiation and development, the fruit and sepal morphology were visualized, while the pistil size, the rate of fruit set and the number of seeds were counted. To observe the parthenocarpy feature of the MADS genes were screened from the MFB, F and MFF transcriptome databases, respectively (unpublished data). After searching for the typic MADS-box domains and deletions of duplicate sequences, a total of 105 MADS-box genes were identified in Z. armatum and named ZaMADS1 to ZaMADS105 , 24 fruit samples (F), and 6 male/female flowers (MFF) were assembled independently, and therefore generated three transcriptome databases, which contain 100238, 141105, and 77247 unigenes in MFB, F, and MFF libraries, respectively. Among them, 65, 136 and 86 candidate MADS-box genes were classified into two categories, M-type (type I) and MIKC MADS (type II), harboring 19 and 86 members, respectively   of ZaMADS MIKCC -type genes. There were seven, six, five, eleven, seven, seven, and six MIKCC members in AP3/PI, AGL15/18, AGL32, AGL2-, AP1-, AG-, and AGL32-like subfamilies, respectively. In contrast to Arabidopsis, the above eight MIKCC subclusters were expanded by gene duplication. In addition, the remaining four subgroups consisted of only a few members, while FLC-like only existed in Arabidopsis , which was found in the N-terminus of the seventeen M-type ZaMADS genes except for ZaMADS2 and ZaMADS18 , two SOC-like genes (ZaMADS95 and ZaMADS96) and one SVP-like gene (ZaMADS89), while twenty-six MADSs were specifically restricted to female floral primordia and fruit, especially two STK/AGL11 like genes (ZaMADS80 and ZaMADS49), one AG-like gene (ZaMADS42), two SOC-like genes (ZaMADS47 and ZaMADS68), two AGL2-like genes (ZaMADS53 and ZaMADS32) and two AGL32-like genes (ZaMADS64 and ZaMADS67) (To investigate the roles of aMADS67) Figure 2MADSs, namely ZaMADS92, ZaMADS57 (AGL1-like), ZaMADS61(AGL61-like) and ZaMADS70 (SEP3-like), displayed remarkable upregulation with stamen initiation and development, whereas six genes, including ZaMADS89, ZaMADS95, ZaMADS96, ZaMADS98 (AGL15-like), ZaMADS74(AGL6-like) and ZaMADS78(AGL19-like), showed dramatic declines in their transcripts  exhibited relatively high transcript accumulation in pistil primordia and strongly downregulated following fruit set (FFS1 to FFS4)  and three AGL2-like  orthologous genes gradually increased with fruit set and expansion (FFS1 to FFS6), but significantly decreased response to fruit maturation, indicating that these genes might participate in apomixis and fruit growth. Additionally, we observed that ZaMADS67, an AGL32 homolog, was strictly restricted to enlarged and mature fruit  and ZaMADS70(1-131)  plants , accompanied by thicker fruit stalks and enlarged sepals, facilitating the larger size of the ovaries. However, at this time, wild-type ovaries remained unchanged and underwent swelling just post anthesis and 72 h after pollination. Additionally, ZaMADS80-OX plants had thicker and shorter stigmas. We also observed that the sepals in several transgenic lines failed to scroll and enclosed the ovaries after fruit set, while the petals and stigmas remained attached to the fruit  and hormone application, the transition from female to male or hermaphrodite flowers occurred  as well as the requirements of floral organ identity in unisexual flowers of dioecious plants. Additionally, Z. armatum lacks the FLC ortholog .Previous studies have revealed close correlations between MADS-box genes and sex determination . In Z. abidopsis . The exportholog , which iortholog . We hypoArabidopsis, ap3 and pi mutants displayed fewer carpels in the third whorl than the usual number of stamens, while in AP3/PI overexpression lines, there are many more stamens in the inner whorl than the usual number of carpels  exhibited female flower-limited expression, implying the involvement in gynoecium development  in Litchi female flowers  are involved in apomixis.In addition, a series of modifications in floral organs were observed in X plants 6, indicswelling , indicatZ. armatum, except for ZaMADS50(SEP1/AGL2-like) and ZaMADS70 (SEP3/AGL9-like), several MADS domain proteins representing the AP1, AP3/PI, SVP, SOC1, and AG subfamilies tested in this study, essential regulators for floral organ specification, exhibited no transcriptional activation activities  interacted with ZaMADS74 (AGL6-like) and ZaMADS89 (SVP-like), but not ZaMADS50 and ZaMADS70  , Chongqing talent program for Zexiong Chen, Scientific Technological Research Program of Chongqing Municipal Education Commission (No. KJZD-K201901303), and National Key Research and Development Project (No. 2019YFD1001205). The funders have no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


PROS1 not only plays an important role in the blood coagulation system, and recent studies have found that it was correlated with the development of tumors, especially related to tumor immune infiltration. However, the study of underlying role and mechanism of PROS1 in gliomas, especially in low-grade gliomas, is almost absent.Glioma is the most common cancer in the central nervous system, and low grade gliomas are notorious for many types of tumors and heterogeneity. PROS1 based on multi-omics analyses. In addition, Cell counting kit-8 (CCK-8) assay, colony formation assay, 5-Ethynyl-2’-deoxyuridine (EdU) incorporation assay, and Transwell assays were performed to evaluate cell proliferation and invasion. qRT-PCR and immunohistochemistry were used to evaluate the expression of PROS1 in LGG.We integrated the information of patients with LGG in The Cancer Genome Atlas (TCGA) cohort and Chinese Glioma Genome Atlas (CGGA) cohort. Then, we systematically demonstrated the differences and prognostic prognosis value of PROS1 was a valuable prognostic marker and may influence tumour development via distinct mechanisms, including expression of DNA methyltransferase, RNA modification, and DNA mismatch repair system genes, copy number variation, single nucleotide variation frequency, genomic heterogeneity, cancer stemness, DNA methylation, and alternative PROS1 splicing. Our analyses indicated that the long non-coding RNA RP3-525N10.2 may “decoy” or “guide” the transcription factor NFKB1 and prevent its association with PROS1, thereby reducing PROS1 expression and improving poor LGG prognosis. PROS1 expression was also closely associated with tumour infiltration by immune cells, especially tumour-associated macrophages, as well as the expression of various immune checkpoint inhibitors, immunomodulators, and immune cell markers.Various bioinformatics approaches revealed that RP3-525N10.2-NFKB1-PROS1 triplet-mediated PROS1 expression could serve as a biomarker for cancer diagnosis, prognosis, therapy selection, and follow-up in LGG patients.long non-coding RNA The online version contains supplementary material available at 10.1186/s12967-022-03536-y. MGMT) methylation, codeletion of chromosome arms 1p and 19q, and isocitrate dehydrogenase (IDH) mutations to provide insight into LGG pathogenesis and advance cancer therapies for patients with LGGs [PROS1 has been identified as a potential target gene in several types of human cancers, including papillary thyroid carcinoma, oral squamous cell carcinoma, malignant thyroid cancer, intrahepatic cholangiocellular carcinoma, and glioblastoma [PROS1 expression, its prognostic value, and the underlying mechanisms in gliomas, especially in LGGs, is still missing. Additionally, the correlations of PROS1 expression with multi-omic data and tumour infiltration by immune cells in LGG remain undetermined.Glioma is the most common malignancy in the brain. Low-grade gliomas , originating from neuroepithelial tissue , have hiith LGGs , 4. Howeith LGGs . PROS1 iith LGGs . PROS1 iith LGGs . Tumour-ith LGGs . PROS1 pith LGGs . Moreoveblastoma –16. HowePROS1 gene expression data were downloaded from the GTEx portal (https://gtexport.org/home/), the Cancer Cell Line Encyclopedia database , the TCGA database (https://genome-cancer.ucsc.edu/), and the CGGA database (http://www.cgga.org.cn/). These data were normalized, and differential expression analyses were performed for PROS1 using the R package “limma” [ “limma” .http://www.sangerbox.com/tool) was used to validate the pan-cancer expression of PROS1 and explore the correlation of PROS1 expression with the expression of DNA methyltransferases, RNA modification genes, and DNA mismatch repair system genes, as well as copy number variation, single nucleotide variation frequency, genomic heterogeneity, and cancer stemness using Spearman’s or Pearson’s method.The free data analysis platform Sangerbox (http://gepia.cancer-pku.cn/index.html) is a free web tool based on TCGA and GTEx data. In the current study, PROS1 expression, survival analysis, and possible involvements of lncRNAs and TFs were evaluated using the GEPIA modules “Expression DIY” and “Survival”. In addition, the relationships between PROS1 and Gene markers were determined using Spearman’s correlation coefficient in the module “Correlation analysis”.GEPIA (https://cistrome.shinyapps.io/timer/) is a web server for the comprehensive analysis of tumour-infiltrating immune cells. In our study, PROS1 expression and survival were evaluated using the “Gene” and “Survival” modules. TIMER was also applied to investigate the relationships between PROS1 expression and different gene marker sets of immune cells using the “Correlation” module [TIMER  and GAPDH  were used for qPCRs. Ten formalin-fixed, paraffin-embedded LGG tissues and normal brain tissues were used for immunohistochemistry stainings.Since there are no specific LGG cell lines, common glioma cell lines  and the human astrocyte cell line NHA were used. Cells were cultured in Dulbecco’s modified Eagle’s medium (Gibco) containing 10% heat-inactivated foetal bovine serum and 1% penicillin/streptomycin. Real-time PCR was conducted to compare gene expression in 30 tumour samples with that in adjacent normal tissue. Real-time PCR was performed in triplicate using samples derived from three independent experiments. Primers for Short hairpin RNA (shRNA) against PROS1 (shPROS1) and a negative control shRNA (sh NC) were designed and synthesised by genomeditech . In addition, the pcDNA3.1 vector (Vigene Biology) containing the full-length cDNA sequence of PROS1 was used to overexpress PROS1. The empty pcDNA3.1 vector was used as a negative control. The lentivirus pLent-shPROS1-GFP-Puro or its negative control (NC) pLent-GFP-Puro (genomeditech) was used to infect GBM cells with enhanced infection solution (genomeditech) according to the manufacturer’s protocol. Similarly, pLent-PROS1-GFP-Puro lentivirus or empty vector (vector) pLent-GFP-Puro lentivirus (genomeditech) was used to overexpress genes. Seventy two hours after the cells were infected with lentivirus, 2 μg/ml puromycin was added to kill the cells that had not been transfected.U87 and U251 cells was assessed with the Cell Counting Kit-8  reagent according to the manufacturer’s instructions. Cells were inoculated on 96- well plates at a density of 1000 cells per well with 100 μl of medium. Every 24 h for a total of 96 h, CCK8 solution (10 μl) was added to each well, and the cells were further incubated at 37 °C for 3 h. The absorbance of each well was measured at 450 nm with a spectrophotometer.U87 and U251 Cells were prepared into a single-cell suspension, respectively, and seeded into a six-well plate (200 cells/well) for two-week incubation to form colonies. After staining with 0.01% crystal violet (Sigma), the colonies were subjected to microscopic examination. The rate of colony formation and survival fraction were calculated.4 cells were added into Matrigel-coated upper Transwell chambers for the invasion assay. The lower chambers were filled with DMEM containing 10% FBS. After incubation at 37 °C for 24 h, cells on the lower surface of the membrane were fixed in 100% methanol and stained with 0.1% crystal violet dye for 20 min at room temperature. Finally, after washing with PBS, cells were imaged in five randomly selected fields under a light microscope (Olympus Corporation) at × 100 magnification.2 × 10According to the manufacturer’s instructions, EdU Kit  was utilized to monitor the proliferation of transfected cells. Zeiss Axiophot Photomicroscope  was used to capture representative images.Genomic heterogeneity includes the parameters TMB, MATH, tumour ploidy, HRD, LOH, MSI, NEO, and tumour purity , 30. Canhttps://biit.cs.ut.ee/methsurv/) was used to evaluate the effects of methylation levels and PROS1 expression on prognosis in LGG [http://www.oncosplicing.com/) to explore differential alternative splicing events of PROS1 in LGG [MethSurv  is a large collection of publicly available cancer microarray datasets [www.oncolnc.org), a tool for interactive explorations of survival correlations, contains survival data of 8,647 patients from 21 cancer studies supported by the TCGA. The relationships between PROS1 expression and patient prognosis  were visualised with forest plots and Kaplan–Meier curves.The PrognoScan database (datasets . The Onchttp://www.genemania.org) was used to construct the PROS1 interaction network [https://string-db.org/) was used to construct the protein–protein interaction network of PROS1 [The GeneMANIA database ( network . The STRof PROS1 .http://biocc.hrbmu.edu.cn/CancerSEA/home.jsp), a database that aims to comprehensively decode functional states of cancer cells at single-cell resolution, was used to explore PROS1 functions [CancerSEA , based on tumour pretreatment expression profiles, can estimate multiple published transcriptomic biomarkers to predict patient responses. It was used to investigate the association between PROS1 expression and therapy outcomes in clinical studies of immune checkpoint blockade [TIDE  and significantly decreased in 17 tumour types  compared to that in normal samples. However, PROS1 expression was not significantly different among MESO, PCPG, READ, SKCM, and UVM. Moreover, Sangerbox tools were used to validate mRNA expression results. As shown in Fig. PROS1 expression in COAD, GBM, KIRC, KIRP, LGG, PAAD, PRAD, SKCM, STAD, TGCT, and THCA was significantly increased when compared to that in control samples of the genotype-tissue expression (GTEx) project, whereas in BLCA, BRCA, CESC, CHOL, HNSC, KICH, LAML, LUAD, LUSC, OV, READ, UCEC, and USC, PROS1 expression was substantially decreased. Taken together, PROS1 was upregulated in GBM, LGG, KIRC, KIRP, PAAD, PRAD, STAD, and THCA, and downregulated in BLCA, BRCA, CESC, CHOL, HNSC, KICH, LAML, LUAD, LUSC, OV, UCEC, and USC, demonstrating that PROS1 may function as a vital regulator of carcinogenesis in 20 different types of cancer. We additionally analysed PROS1 expression in 31 types of tissues using the GTEx dataset  of 0.934 (0.922–0.946) suggests that the PROS1 gene may have the potential to identify LGG tissues. At the protein level, immunohistochemistry stainings were used to investigate the PROS1 expression in 15 paired tumour samples compared with adjacent normal tissues. The analysis demonstrated that PROS1 levels were substantially increased in LGG tissues  and 44 RNA modifications  across most human cancers, but especially in patients with LGG, which indicates that PROS1 may mediate tumorigenesis by epigenetic modification. DNA mismatches are potentially mutagenic and, thus, must be corrected by the mismatch repair system to maintain the integrity of the genetic information. As shown in Fig. MLH1, MSH2, MSH6, PMS2, and EPCAM) and PROS1, which suggested that the mismatch repair system may play a critical role in regulating tumorigenesis of PROS1. We analysed SNP data to detect variants and their frequencies in LGG. As shown in Fig. PROS1 expression levels revealed IDH1, TP53, ATRX, CIC, TTN, FUBP1, MUC16, NOTCH1, PIK3CA, and EGFR as the top 10 mutated genes, with mutation percentages of 76%, 45%, 33%, 20%, 12%, 9%, 7%, 7%, 6%, and 6%, respectively  were detected by the Kruskal–Wallis test , cytosine-5-methylation (m5C), and N6-methyladenosine (m6A) are common epigenetic modifications, so we explored their correlations with PROS1 expression was significantly correlated with the expression of four DNA methyltransferases. To explore the potential mechanism between PROS1 expression and DNA methylation, MethSurv was utilised to investigate the impact of different methylation levels and PROS1 expression on the prognosis in LGG. As shown in a heatmap , mutant-allele tumour heterogeneity , tumour ploidy , homologous recombination deficiency , loss of heterozygosity , DNA methylation-based stemness , enhancer elements/DNA methylation-based stemness , epigenetically regulated DNA methylation-based stemness , and RNA expression-based stemness  were significantly different from those of PROS1 . All other examined clinical parameters were not significantly correlated with PROS1 expression , and the pan-cancer analysis demonstrated similar results for disease-specific survival, disease-free interval, and progression-free interval  with high expression and prognostic significance in LGG  cell-mediated cytotoxicity. Consistent with the results of the GO and KEGG analyses, GSEA, including KEGG  signalling. These results strongly imply that PROS1 participates in the regulation of immune responses in LGG.GO and KEGG enrichment analyses were used to investigate ses Fig. A–D. NotaEGG Fig. E and ReaEGG Fig. F pathwayPROS1 in LGG tissues at the single-cell level, CancerSEA was used to explore phenotypes possibly regulated by PROS1. As shown in t-SNE and box plots . As shown in Fig. To explore the functions of PROS1 may play a critical role in the immune system. Therefore, we investigated the relationships between PROS1 expression and immune cell infiltration. According to analyses of the Tumor Immune Estimation Resource (TIMER) database, six types of immune cells  were associated with PROS1 expression and prognosis in patients with LGG , stromal score , and estimated immune score .The functional enrichment results indicated that LGG Fig. A, B. FurLGG Fig. C, D showLGG Fig. E. To anaPROS1 expression and immune responses, the TIMER and GEPIA databases were utilised to validate the association between PROS1 expression and immune cell markers in LGG. The genes listed in Table PROS1 was significantly correlated with that of most immune cell markers  in the TIMER and GEPIA databases are shown in Fig. PROS1 may play a critical role in LGG immunity and may be a potential immunotherapy target.The correlation analysis between immunomodulators and ors Fig. A. Based pes Fig. B. NotablPROS1 as a biomarker by comparing its performance with those of standardised biomarkers. We found that PROS1 alone had an AUC value > 0.5 in 8 of the 20 examined ICB subcohorts  but inferior to MSI, CD27A, TIDE, IFNG, Merck18, and CD8. Our results also indicated that high PROS1 expression was correlated with worse PD1 outcomes in kidney renal clear cell carcinoma (Braun2020_PD1 Clear), melanoma , PD-ligand 1 (LI) (BladderMariathasan2018_PDL1 mUC), ACT melanoma (Lauss2017_ACT), and CTLA4 (Nathanson2017_CTLA4 Post) but achieved good CTLA4 therapeutic outcomes in melanoma (Nathanson2017_CTLA4 Pre), and kidney renal clear cell carcinoma (Miao2018_ICB Clear) cancer cohorts  models . Immune cell infiltration and tumour microenvironment, immune checkpoint inhibitors, immunomodulators, immune cell markers, and therapeutic outcomes in clinical studies of immune checkpoint blockade were subsequently explored, and we identified significant correlations with PROS1 expression. Notably, a connection between PROS1 expression and TAMs was revealed. Moreover, PROS1 functions at the single-cell level, as well as the involvement of lncRNA-TF-gene triplets, were explored in LGG. Finally, PROS1 expression was comprehensively analysed in combination with clinical diagnosis, treatment, and multi-omics data, including DNA methyltransferase expression and functional DNA methylation, expression of RNA modification and DNA mismatch repair system genes, copy number variation and single nucleotide variation frequency, PROS1 alternative splicing, tumour genomic heterogeneity, and cancer stemness. These results suggest the involvement of PROS1 in glioma carcinogenesis. This conclusion is supported by a study indicating that PROS1 may play a vital role in the development of GBM by influencing cellular proliferation, migration, invasion, and apoptosis [In patients with LGG, the correlations of poptosis .PROS1 expression in LGG. Among seven TFs that may interact with PROS1, NFKB1 was identified based on expression, survival, and correlation analyses. A previous study has shown that the lncRNA SLC26A4-AS1 promotes NPTX1 transcriptional activity by recruiting NFKB1, thereby exerting antiangiogenic effects in glioma cells [PROS1 and NFKB1, but only lncRNA RP3-525N10.2 met all screening conditions, was significantly upregulated in LGG, and had the potential to improve the prognosis of patients with LGG. Taken together, our study findings suggest that lncRNA RP3-525N10.2 may decoy or guide NFKB1, thereby reducing PROS1 expression and improving the poor prognosis in patients with LGG.Because lncRNAs and TFs have been widely found to play indispensable roles in the occurrence and progression of tumours, the LncMAP database was used to explore TFs and lncRNAs that may regulate ma cells . In the PROS1 functions, we annotated its functions using GO, KEGG pathways, and GESA. The results demonstrated that PROS1-related genes were focused on well-known processes, including T-cell receptor signalling, KEGG cancer pathways, transforming growth factor-β signalling, JAK-STAT signalling, and various other immune-related pathways. Functional analyses at the single-cell level showed that PROS1 was upregulated in glioma cells, promoting cell invasion. Based on these results, we explored the relationships between PROS1-related genes and the prognosis of patients with LGG.In view of the finite studies on PROS1 expression was significantly positively correlated with the presence of most immune cells in LGG tissue, the expression of biomarkers by tumour-infiltrating immune cells, and the expression of immune checkpoint genes. Among these immune cells, TAMs are a rich cellular component of the brain TME that possess both tumour-promoting and immunosuppressive capacities [PROS1 is secreted by TAMs/microglia and subsequently physically associates with and activates AXL in mesenchymal glioma sphere cultures [PROS1 expression is significantly correlated with TAMs and might partially account for PROS1-mediated oncogenic mechanisms in LGG. Taken together, TAMs play a unique role in tumours, and LGG is no exception. Additionally, the significant association between immune checkpoint genes and PROS1 indicated that targeting PROS1 might increase the efficacy of immunotherapy in LGG, which was consistent with the Tumor Immune Dysfunction and Exclusion (TIDE) results. According to the DSigDB database, spiperone PC3, thapsigargin PC3, quercetin CTD 00006679, and pentabromodiphenyl ether CTD 00003077 were the best drug candidates.Immune cell infiltration in the tumour microenvironment and sufficient expression of immune checkpoint genes can alter the efficacy of chemotherapy, radiotherapy, or immunotherapy, thereby influencing the prognosis of patients with cancer. Our results demonstrated that pacities . Ubil etpacities . Maimon pacities . Sadahircultures . The TAMcultures , 25. Thecultures  are listThis study has some limitations. First, the TCGA and CGGA databases inevitably neglect the inner tumour heterogeneity in different databases. Second, the possible mechanisms of DNMTs, MMRs, DNA methylation, alternative splicing, the identified lncRNA-TF-gene triplet and the roles of PROS1 in tumour migration, immune cell infiltration, and tumour escape should be explored in more detail in future studies. Third, although targeting PROS1 in patients with LGG is promising, a concern may be that PROS1 inhibits BBB breakdown, as it exerts a protective effect at the BBB .PROS1 is upregulated in LGG and various other types of human cancers and may serve as a novel prognostic biomarker in LGG. PROS1 plays a vital pathogenic role in the immuno-oncological context of the TME, affects the infiltration of tumour tissue by immune cells, and influences patient prognosis. Poor prognosis is associated with epigenetic modifications, genomic heterogeneity, cancer stemness, and alternative splicing of PROS1. Moreover, we identified a possible regulatory mechanism of PROS1 in LGG, namely the lncRNA RP3-525N10.2-NFKB1-PROS1 triplet . Table S3. Univariate regression and multivariate survival method  of prognostic covariates LGG patients. Figure S1.PROS1 expression in 31 types of tissues using the GTEx dataset. Figure S2.PROS1 expression in 21 tumour cell lines using the Cancer Cell Line Encyclopedia database. Figure S3. PROS1 expression between tumour and normal tissues using The Cancer Genome Atlas (TCGA) database. Figure S4. PROS1 expression is associated with positive result of genomic heterogeneity and cancer stemness. Figure S5. PROS1 expression is associated with negative result of genomic heterogeneity and cancer stemness. Figure S6. Correlation between PROS1 expression and clinical parameters of patients with LGG. Figure S7. Correlation between PROS1 expression and disease-specific survival in 33 tumours from the TCGA database. Figure S8. Correlation between PROS1 expression and disease-free interval in 33 tumours from the TCGA database. Figure S9. Correlation between PROS1 expression and progression-free interval in 33 tumours from the TCGA database. Figure S10. Single-cell analysis of PROS1 functions in patients with LGG. Figure S11. Correlation between PROS1 expression and TAMs immune cell markers in LGG.


Missense variants were present in both conditions, presumably with loss- or gain-of-functions. KCNK18 nonsense/frameshift variants were found in painless/painful-DN, making a causal role in pain less likely. Surprisingly, premature stop-codons with likely nonsense-mediated RNA-decay were more frequent in painful-DN. Although limited in number, painful-DN patients with ion channel gene variants reported higher maximal pain during the night and day. Moreover, painful-DN patients with TRP variants had abnormal thermal thresholds and more severe pain during the night and day. Our results suggest a role of ion channel gene variants in neuropathic pain, but functional validation is required.Neuropathic pain is common in diabetic peripheral neuropathy (DN), probably caused by pathogenic ion channel gene variants. Therefore, we performed molecular inversion probes-next generation sequencing of 5 transient receptor potential cation channels, 8 potassium channels and 2 calcium-activated chloride channel genes in 222 painful- and 304 painless-DN patients. Twelve painful-DN (5.4%) patients showed potentially pathogenic variants  in ANO3 ( Neuropathic pain (NeuP) is caused by damage or disease of the somatosensory nervous system . Around Several small-scale studies have investigated why some patients with diabetic neuropathy develop painful-DN, while others do not . Female SCN9A gene encoding Nav1.7, in contrast, led to congenital insensitivity to pain, while gain-of-function mutations have been linked to a spectrum of pain disorders, including painful-DN [v1.7 variants report more severe burning pain and increased pressure stimuli sensitivity, compared to painful- DN patients without the SCN9A variant [In recent years, genetic causes of NeuP have partially been resolved, and next-generation sequencing (NGS) has been increasingly performed to identify genes and genetic variants associated with NeuP . Pathoge variant ,11. Howe2+-activated Cl- channel from the ANO family, which interacts with TRPV1, leading to pain enhancement in sensory neurons, while ANO3 regulates pain processing via increasing the Slack channels’ activity in DRG neurons [Apart from VGSCs, other ion channels are also essential for proper functioning of the nervous system . It has  neurons ,17,18.Our hypothesis is that in addition to VGSCs, variants in other ion channels are involved in painful-DN. Therefore, we analyzed seven Kv, five TRP, two ANO and one HCN ion channel genes expressed in peripheral nerves, using single molecule molecular inversion probes-next generation sequencing (smMIPs-NGS) in patients with painful-DN and painless-DN. The painless-DN group was included to identify variants linked to the absence of pain, which may play role in pain resilience and to exclude common variants present frequently in both patient groups. We also assessed if these variants were linked to specific clinical manifestations.In total, 612 patients with DN were included, 393 from the Heinrich Heine University , and 219 from the University of Manchester . Of these, 86 patients were excluded, due to low DNA quality, MIP failure, incomplete clinical data or withdrawal of formal consent. Among the enrolled patients, 222 had painful-DN and 304 had painless-DN. The mean age at recruitment was 64.5 years old (SD +/−11.2 years). Sex distribution in the study group was 372 (70.7%) males versus 154 (29.3%) females. The higher male prevalence was present in both phenotypes. Clinical characteristics of the study population are presented in ANO1, and exon 3 of TRPV1), and MIPs for 14 exons covered the targeted region of > 20×/bp only partially  of 15 ICG, data of 50 samples from 5 different NGS runs were used. An overall coverage of more than 30×/bp was obtained for 93% of the on-target regions. Exons and exon-flanking sequences of ten gene areas have an average coverage of >90%. Four exons had poor coverage (<20×/bp) or were completely missing . The clinical characteristics of painful-DN patients with ICG VUS are presented in n = 9) reported higher mean maximal pain scores during 24 h (PI-NRS 7.2 +/−2.4), compared to patients with painful-DN without an ICG variant . However, due to the small sample size, statistical analysis was not possible . It seems that patients with painless-DN with an ICG VUS variant reported less often autonomic complains, especially diarrhea, dry mouth, orthostatic dizziness, sheet intolerance and restless leg; however, the group size (n = 4) is too small to draw a definite conclusion. The clinical characteristic and autonomic complaints in patients with painless- DN and ICG variant are presented in In 304 patients with painless-DN, 13 different potentially pathogenic heterozygous variants were identified. Fourteen (4.6%) patients had a potentially pathogenic variant in one of the fifteen ICG, but none had more than one ICG variant . In two nd TRPV4 . Seven oANO3, HCN1, KCNK18, TRPA1, TRPM8, TRPV4. Three patients (1.4%) had a potentially pathogenic variant in ANO3, one (0.5%) in HCN1, two (0.9%) in KCNK18, three (1.4%) in TRPA1, three (1.4%) in TRPM8, one (0.5%) in TRPV4. In patients with SFN and NeP, the frequency of  pathogenic variants in the sodium ion channels was slightly higher; 5.1% for SCN9A, 3.7% for SCN10A and 2.9% for SCN11A [ANO1, KCNK18, KCNQ3, TRPA1, TRPM8, TRPV1 and TRPV4. Potentially causative variants were identified in one patient (0.3%) in ANO1, three (1%) in KCNK18, one (0.3%) in KCNQ3, two (0.7%) in TRPA1, one (0.3%) in TRPM8, three (1%) in TRPV1 and three (1%) in TRPV4. Four of these genes  have not been linked to a painful phenotype or to pain insensitivity before in HGMD. We did not find any potentially pathogenic variant in the following six genes from our gene panel: KCNA2, KCNA4, KCNNA, KCNQ5, KCNS1, TRPV3.In our cohort of patients with DN, twelve patients with painful-DN (5.4%) and fourteen patients with painless-DN (4.6%) harbored at least one potentially pathogenic variant in the ICG gene, respectively linked to pain or no pain. Only one patient with painful-DN had two heterozygous variants TRPA1 c.2481del and TRPM8 c.1437G>T. In total, we identified 13 different potentially pathogenic variants in painful-DN located in KCNK18 variants c.414_415del and c.361dup and TRPA1 c.352C>G. Our patients did not report migraines during clinical investigation. However, questions about headaches or migraines were not included in the standard questionnaires and we were not able to contact the patients to confirm the lack of migraine symptoms. The presence of these variants in both phenotypes might be explained by other mutations in the genes not included in our gene panel or non-genetic risk factors contributing to a painful phenotype [SCN10A c.368C>T, VUS and ANO1 c.1892G>A, VUS, and SCN10A c.1141A>G, possibly pathogenic and TRPV4 c.958C>T, VUS.The same missense variants were not present in any of the ICG genes in painful- and painless-DN, with the exception of migraine-related henotype . In two All variants meeting our criteria were variants of uncertain clinical significance, making it difficult to draw a definite conclusion on a causative role. However, this is not surprising, since most of the variants we identified were novel and we could only rely on in-silico predictions without segregation analysis in families or functional studies. The development of NGS and more affordable cost of sequencing have resulted in recent years in the identification of a significant number of VUS and part of them have been proved to be pathogenic over the time .The VUS detected in our study either change the protein via substitutions of conserved amino acids (missense VUS) or are generally predicted to lead to the absence of the protein, because of nonsense mediated decay, triggered by a premature stop codon (nonsense/frameshift VUS). For the latter group, the KCNK18 gene contained premature stop codons in both painful- and painless-DN, making a causal role of haploinsufficiency of these genes on the pain phenotype unlikely. For the other nonsense/frameshift variants, this is not the case. Although NMD is most likely, truncated non-functional protein or alternative processes, such as frameshift mutation-induced alternative translation initiation (fsATI), have also been reported , requiriOverlap exists between the genes with missense mutations in painful- and painless-DN, but this does not disqualify the role they might have, as it has been reported that missense mutations can lead to gain or loss-of-functions with possible opposite effects on pain sensitivity, highlighting the importance of functional effect rather than the variation itself. Additional support for functional relevance is for the 3 VUS in TRPV1 and 1 VUS in ANO3, located in the transmembrane domain, which can directly affect channel properties e.g., channel gating . Two misANO3 gene were detected in painful-DN and one missense heterozygous variant in the ANO1 gene in painless-DN. These genes belong to Ca2+-activated Cl- channels and they are highly expressed in dorsal root ganglia (DRG) [Three missense heterozygous variants in the ia (DRG) ,18. ANO3ia (DRG) ,30. A LOVoltage-dependent potassium channels are crucial for controlling the excitability of nociceptors and pain processing . A heterWe identified several variants located in TRP channels both in painful- and painless- DN. TRPV1, TRPM8, and TRPA1 are thermal and chemical detectors that activate sensory neurons to produce pain, while TRPV4 mediates nociceptive behaviors by hyper- and hypotonic stimuli . Three TSimilar to TRPA1, TRPM8 modulates the cold sensation and its activation produces analgesia in chronic neuropathic pain states ,43. In pTRPV1 and TRPV4 belong to the transient receptor potential vanilloid family and most of the VUS in these genes were present in painless-DN. In total, three missense VUS in TRPV1 were present in painless-DN, all located in the functional domain of the channel; c.1450G>C in transmembrane domain II, c.1781C>T and c.1790C>T both in transmembrane domain IV. Activation of TRPV1 results in the generation of action potentials and in many cases, pain . Moreoven = 9) had higher mean pain scores compared to patients with painful-DN without the potentially causative ICG variant (n = 150). Determining clinically important differences in pain is challenging [Patients with painful-DN with an ICG VUS , Heinrich Heine University, Düsseldorf, Germany or at the University of Manchester, Manchester, United Kingdom. They were examined between June 2014 and September 2016. Only patients aged above 18 years old and those diagnosed with diabetes mellitus type 1 or type 2  were eligible for this study. Demographic data, medical history, age of onset of complaints, duration of symptoms, altered pain sensation and family history were recorded. Pain intensity was evaluated using the 11-point Numerical Rating Scale (PI-NRS) from 0–10, where 0 means “no pain” and 10 refers to “the worst pain imaginable.” For all the patients, informed consent was obtained and a blood sample for genetic analysis was drawn.® device. NeuP was diagnosed as reported before [For the patients with painful-DN, quantitative sensory testing of the lower limb was performed on the dorsum of the foot using the Medocd before . The diad before . The DN ® Blood Core Kit , according to the manufacturer’s instructions at Maastricht UMC+, and IRCCS Neurological Institute Carlo Besta. DNA samples were coded and stored in the central DNA bank at Maastricht UMC+ and IRCCS Neurological Institute Carlo Besta in −20 °C.Genomic DNA was extracted from whole blood using the NucleoSpin8 Blood Isolation Kit  or QIAamp DNA Blood Maxi Kit, PuregeneGene candidates for smMIPs-NGS were selected based on their role with pain in OMIM and the literature, high expression in peripheral nerve DRG and/or trigeminus cells, and by comparative and integrative genomics, with SCN9A co-expression described by Szklarczyk et al. . The fifhttp://shendurelab.github.io/MIPGEN/, accessed on 2 September 2014). The number smMIPs per gene and size of targeted coding region per gene have been given in In total, 295 single-molecule molecular inversion probes (smMIPs) were designed to capture exon and exon-flanking intron sequences (+/−20 bps) of 15 ion channel gene candidates , using aSmMIP-NGS was performed as described before . In brieSequenced data were analyzed using an smMIPs-NGS pipeline developed by Maastricht UMC+ in collaboration with Radboud University . The smMExonic variants and exonic flanking regions (+/−20 bps) with >20× coverage and an alternative variant call of >30% were analyzed in further detail. Common SNPs were excluded from the analysis; only variants with dbSNP < 5%, ExAC < 5% and in house database of 12,244 exomes < 1% were included. Alamut Visual  software was used for variant interpretation. Variants were classified according to the practice guidelines of the Association for Clinical Genetic Science (ACGS) . Potentit-test was used to analyze continuous variables and chi-square test was applied for categorical variables. The significance level was defined as 0.05.The independent Student’s


NMU, NMUR1, NMUR2, and the mast cell (MC) marker, CPA3, in the SM of KOA patients categorized as normal weight , overweight , and obese . To study NMU/NMUR expression in MCs, we compared the MC-rich fraction (MC-RF), CD88(+) MC-RF, and CD88(−) MC-RF, extracted using magnetic isolation, with the MC-poor fraction (MC-PF). While NMU and NMUR2 expression were comparable, NMUR1 was significantly elevated in OW and OB compared to NW. Moreover, CPA3 levels were significantly greater in OB than NW. NMUR1 and CPA3 expression were significantly higher in both the CD88(+) and CD88(−) MC-RF than MC-PF. Therefore, NMUR1 expression was elevated in the SM of OB KOA patients, and its expression was found in MCs. Further investigation to analyze the NMU/NMUR1 pathway in MC may provide a link between obesity and KOA pathology.Obesity is a risk factor for knee osteoarthritis (KOA). Neuromedin U (NMU) and NMU receptors (NMUR1 and NMUR2) are associated with obesity-related disorders and found in mast cells (MCs), which are elevated in osteoarthritis. However, NMU/NMUR expression was not examined in the synovial membrane (SM) or synovial MCs of obese osteoarthritis patients. We compared expression of  Research suggests that being obese is associated with an elevated prevalence and occurrence of osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints ,2. Such According to several studies, synovial neuropeptides may contribute to OA pathology ,4,5,6,7.NMU mRNA was observed in antigen-presenting cells, such as monocytes and dendritic cells. Meanwhile, NMUR1 mRNA is present in T cells, natural killer cells, eosinophils, and mast cells (MCs) [ls (MCs) ,12,13,18ls (MCs) ,20,21 anls (MCs) ,23,24, sls (MCs) ,26. Givels (MCs) ,28, we hComplement receptors (CRs) play an important role in innate immune defense and local inflammation . ComplemNMU, NMUR1, NMUR2, and the MC marker, CPA3, in the synovium of obese OA patients and examined whether NMU/NMUR expression is found in synovial CD88(+) and CD88(−) MCs subsets.Here, we studied the expression of p = 0.023 and p = 0.010, respectively). In contrast, the percentage of patients with Kellgren and Lawrence grade 2, 3, and 4 (p = 0.675) KOA was not different among the BMI groups.The patients’ clinical features are presented in NMU/NMURs and CPA3 mRNA in NW, OW, and OB groups was estimated by qPCR . Similarly, no significant differences were noted in NMU levels  and CD88(+) MC fractions was estimated by qPCR  MC-rich fraction (MC-RF) (CD88 than the CD88(−) MC-RF  MC-RF than the MC-PF  A and CD8 (MC-RF) B–F. We cNMUR1 expression was elevated in the SM of OB compared to NW individuals. Further, NMUR1 expression was detected in MC fractions, suggesting that MCs may contribute to the NMU/NMUR system in the osteoarthritic synovium of obese patients.This study in patients with KOA found that NUMR1 were increased in the SM of OW and OB patients, suggesting that increased NUMR1 expression in the SM may contribute to obesity-related synovial pathology. To the contrary, NMU was shown to suppress autoantibody-mediated arthritis in a murine collagen-induced arthritis model. NMU-23 administration induced the expansion of innate lymphoid cells and elevated eosinophil, IL-4, IL-5, and IL-13 expression in the joint of CIA mice [According to a recent report, low-grade inflammation, or metainflammation, plays a role in the pathogenesis of obesity and obesity-related diseases . OB and CIA mice . As MCs NUMR1 and CPA3 expression were significantly higher than in OB than NW patients. Therefore, our findings suggest that elevated NMUR1 and CPA3 expression is associated with obesity but not age.A previous study reported that, compared to NW individuals, OW and OB patients undergo TKA at a younger age . ConsistCPA3, were observed in the SM of obese KOA patients, we investigated the expression of NMU/NMURs in MCs. Our results suggest that NMUR1 is expressed in synovial MCs and that elevated NMUR1 may reflect an increase in MCs in the SM. Furthermore, given that previous studies have identified CD88(+) and CD88(−) MC subsets in SM, skin, and lung [CPA3 and NMUR1. According to a prior study in mice, activation of the NMU/NMUR1 pathway in MCs results in degranulation and neutrophil infiltration [Many immune cell types engaged in obese OA pathology are present in the SM . NMU andand lung ,38,39, aand lung , we addiltration . Additioltration . Moreoveltration . As CD88ltration , this evNMUR2 mRNA in the SM, with particularly high levels in CD88(−) MCs. However, as NMUR2 did not differ among the BMI groups, we propose that NMUR2 may play a limited role in obesity-related synovial pathology.While NMUR1 expression was predominantly reported in peripheral tissues, NMUR2 was mostly observed in the central nervous system (CNS) ,46,47,48NMUR1 compared to the non-MC fraction. However, MC-PF isolated by magnetic beads contained a mixed cell population, including fibroblasts, macrophages, B cells, and T cells. The comparison of NMUR1 expression in MC and particular cell types requires isolation using a cell sorter. Second, the role of NMU/NMUR1 on synovial MCs remains unclear. Finally, the reason NMUR2 expression was detected mainly in the CD88(−) MCs remains unclear.There were several limitations in this study. First, we showed that MC fractions highly expressed NMU/NMUR expression in MCs.All participants received total knee arthroplasty (TKA) at our hospital, during which time SM samples were extracted. In total, we extracted 206 SM samples from female patients with radiographic KOA. We promptly froze a small portion of each sample in liquid nitrogen and stored it at −80 °C in preparation for RNA extraction. Samples extracted from five obese KOA patients were used to examine The study protocol was approved by our institutional Ethics Review Board . Written informed consent was obtained from all subjects for participation and the extraction of their synovial tissue one day before TKA. This study complied with the principles of the Declaration of Helsinki.2, n = 79), overweight , and obese . Expression levels of NMU/NMURs and the MC marker, CPA3, in the SM determined using real-time PCR were compared between pairs of the BMI groups.We grouped the patients according to the World Health Organization’s body mass index (BMI) definitions as follows: normal-weight (BMI < 25 kg/mGAPDH) was determined using the delta-delta CT method. Relative expression was calculated when the average gene expression (Gene/GAPDH) level in the NW group was 1.SM samples in TRIzol reagent  were homogenized using the polytron homogenizer. The samples were subsequently lysed in 1 mL of TRIzol mixed with 0.2 mL chloroform and vortexed for 30 s before being transferred to a MaXtract high-density tube . Following a centrifugation step , the resulting aqueous phase was mixed with an equal volume of isopropanol containing a precipitation carrier . After removing the supernatant, the RNA pellet was rinsed with 75% ethanol and subjected to centrifugation . After removing the supernatant, the RNA pellet was left to dry before dissolving in RNase-free water. The total RNA concentration was determined with a spectrophotometer . An OD 260/280 ratio greater than 1.8 was used for qPCR analysis. We also confirmed that gel electrophoresis showed clear bands of 28S and 18S. A 1-μg amount of the total RNA was subjected to a cDNA synthesis procedure using Superscript III based on the manufacturer’s protocol (Invitrogen). The qPCR procedure we adopted using SYBR Green is published in detail elsewhere ,50. The NMU/NMUR expression in MCs, we extracted an MC-rich fraction (MC-RF) and MC-poor fraction (MC-PF) from 5 SM samples from obese KOA patients using magnetic isolation [To evaluate solation ,28. As dsolation , we furtNMU/NMUR expression. Gene expression (Gene/GAPDH) was determined using the delta-delta CT method. Relative expression was calculated when the average gene expression (Gene/GAPDH) level in MC-PF was 1.To obtain these MC-RFs, fresh SM samples were promptly placed in a collagenase solution overnight for collagenase digestion. The following day, a portion of the cells extracted by this process were used to confirm cell viability by PI staining . The remaining cells were incubated for 30 min at 4 °C with biotin-conjugated anti-THY-1 , anti-CD3 (T lymphocyte marker), anti-CD14 (monocyte/macrophage marker), anti-CD19 (B lymphocyte marker), and anti-CD235a (erythroid cell marker) antibodies according to our previous studies ,27,28. ANMU/NMURs and CPA3 was determined using Spearman’s correlation coefficient; and comparison of gene expression between MC-RF and MC-PF was conducted using the Mann–Whitney U test. p < 0.05 was indicative of statistical significance.Statistical analyses were conducted using SPSS 25.0. All data were tested for normality using Shapiro–Wilk’s test. The Kruskal–Wallis test was used to compare gene expression among the three BMI groups. To create a matched cohort of NW and OB OA patients, we calculated each individual’s propensity score based on the baseline clinical variables, age, and proportion with Kellgren and Lawrence grade 2–4. Analysis of categorical variables was performed using Fisher’s exact test; the relationship between NMUR1 expression was increased in the SM of obese OA patients and its expression was found in MCs. A further investigation to analyze NMU/NMUR1 pathway in MC may provide a link between obesity and KOA pathology.In conclusion,