Heart failure with preserved ejection fraction (HFpEF) is an emerging global health problem with less awareness. Renal dysfunction in HFpEF is associated with worse outcome. However, there is lack of rapid, noninvasive and accurate method for risk stratification in HFpEF and renal dysfunction. This study aimed to explore the utility of plasma trimethylamine n-oxide (TMAO) for evaluation of HFpEF and renal function.Plasma TMAO levels were measured in total 324 subjects comprising 228 HFpEF patients and 96 healthy controls.p <  0.01). Subjects in higher TMAO tertile group had more incidences of HFpEF ((78.5%) in tertile 3 vs (73.39%) in tertile 2 vs (59.26%) in tertile 1, p <  0.01). TMAO concentrations were inversely correlated with estimated glomerular filtration rate (eGFR) and HFpEF patients with impaired renal function (eGFR < 60 ml/min/1.73 m2) had higher TMAO than those with normal eGFR (≥ 60 ml/min/1.73 m2) (14.18(10.4–23.06) μg/l vs 10.9(7.48–15.47) μg/l, p < 0.01). Increased TMAO levels were independently associated with higher risk of HFpEF  and renal dysfunction  after adjustment for multiple traditional risk factors. Furthermore, TMAO had good performance at distinguishing HFpEF from controls , and renal dysfunction from normal renal function in HFpEF .TMAO levels were significantly elevated in patients with HFpEF compared with controls (12.65(9.32–18.66) μg/l vs 10.85(6.35–15.58) μg/l, In this cross-sectional study, HFpEF and renal function were closely related with plasma TMAO levels and TMAO may serve as a diagnostic biomarker for HFpEF and renal function. The population affected by heart failure (HF) is growing rapidly nowadays in the world due to ageing and increased incidence of cardiovascular disease risk factors such as obesity and hypertension. Heart failure with preserved ejection fraction (HFpEF) is a diverse syndrome marked by myocyte hypertrophy, concentric left ventricular remodeling, and end-diastolic stiffness. Patients with HFpEF have clinical features of heart failure but exhibit normal or near-normal left ventricular ejection fraction (EF), usually 50% or above. HFpEF patients have a higher morbidity than those with reduced ejection fraction (HFrEF) , but curHFpEF is commonly associated with several comorbidities such as obesity, anemia, diabetes mellitus, and renal dysfunction. Data showed that between 20 and 40% of patients with acute heart failure could eventually develop some degree of renal failure . Notably2, in a hospital-based southern Chinese cohort.Recently, multiple studies have suggested the strong association of gut microbiota with pathogenesis and progression in cardiovascular disease , 6. The n = 152) and eGFR ≥60 group (n = 76) according to eGFR score that calculated with an equation of Modification of Diet in Renal Disease (MDRD) as previously described [2) = 186 × [serum creatinine (mg/dl)] –1.154 × (age) − 0.203 × .We recruited 228 patients (HFpEF group) who were hospitalized for coronary angiography and echocardiography in Xiangya hospital at Central South University, with a diagnosis of HFpEF between June 2014 to September 2019. HFpEF was defined as documented diagnosis of heart failure with ejection fraction > 50% (35 ≤ age ≤ 70). Another 96 healthy controls (CON group) was an independently recruited set who either visited hospital for health screen with no history or symptoms of HF, or underwent coronary artery CT or echocardiography for chest pain but showed negative results. The HFpEF group were further divided into eGFR < 60 group , intestinal dysfunction, gastrointestinal surgery history, organ transplants, choline or betaine or l-carnitine supplementation in recent 6 months, and those who received probiotics or antibiotic treatment within 3 month of enrollment to minimize potential confusing factors.General information including age, sex, weight and height was retrospectively collected from each subject’s medical records. All subjects were informed before enrolled in the study. The study plan was approved by the Ethical Committee of Xiangya Hospital of Central South University.Blood samples were collected using vacutainer tubes after at least 12 h of fasting, then immediately centrifuged and stored at − 70 °C until analysis. Plasma TMAO were measured by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS) using d9-(trimethyl)-labeled internal standards as described previously . To be b2 (m2). Blood pressure was measured after resting for at least 15 min.All laboratory analysis were conducted by automatic biochemical analyzer (HITACHI7170S). Body mass index (BMI) was calculated by weight (kg)/heightt-test or the Mann-Whitney U test was used for differences evaluation between two groups. Comparison between the tertiles was performed using one-way ANOVA. The Spearman correlation analysis was used to examine the correlation between TMAO and eGFR. Logistic regression analysis was performed to examine the odds ratio (OR) and 95% confidence interval (95% CI) of TMAO in HFpEF and in HFpEF with renal dysfunction. Adjustments were made for variables including: age, gender, systolic blood pressure (SBP), percentage of glycosylated hemoglobin (HbA1c%), Creatinine (Cr), triglyceride (TG), high-density lipoprotein (HDL) and low-density lipoprotein (LDL). Because the distributions of TMAO were skewed, they were log-transformed in logistic analysis. The area under the receiver-operating characteristic curve (AUC) was calculated to evaluate the diagnostic value of TMAO in discriminating HFpEF from healthy controls as well as HFpEF with renal dysfunction from those without. A two-tailed p value < 0.05 was considered statistically significant.Statistical presentation and analysis of the current study were performed using the computer SPSS program . Categorical variables are presented as numbers and percentages. Continuous data are presented as mean ± standard deviations (SD) for normal distribution parameters or median  for non-normal distribution parameters. Student’s p < 0.01). 62.72% of HFpEF and 59.38% of CON groups were male. HFpEF patients exhibited higher SBP , fasting glucose (Glu) (5.42(4.87–6.11) mmol/l vs 5(4.68–5.53) mmol/l, p < 0.01), HbA1c% (6.1(5.9–6.2) vs 5.7(5.5–5.7), p < 0.01), Cr (91.95(78.85–103.8) μmol/l vs 82.6(74.3–95.75) μmol/l, p < 0.01), TG (1.69(1.13–2.48) mmol/l vs 1.35(1–1.8) mmol/l, p < 0.01), LDL (2.72(2.22–3.49) mmol/l vs 2.55(2.04–3.01) mmol/l, p < 0.01) and white blood cell (WBC) (6.8(5.5–7.8) × 109/l vs 6.1(5–7.53) × 109/l, p < 0.01) levels than control group. While decreased HDL (1.04(0.87–1.22) mmol/l vs 1.12(0.94–1.43) mmol/l, p = 0.01) and eGFR (54.85(46.57–64.26) ml/min/1.73m2 vs 62.03(52.64–70.74) ml/min/1.73m2, p < 0.01) was observed in HFpEF patients compared with controls. We found no significant differences of height, weight, BMI, diastolic blood pressure (DBP), heart rate (HR), total cholesterol (TC), alanine aminotransferase (ALT), glutamic-pyruvic transaminase (AST), creatine kinase-MB (CK-MB) and percentage of ejection fraction (EF%) between different groups (p > 0.05)   μg/l vs 10.85(6.35–15.58) μg/l, n = 108), median TMAO concentrations in tertile 2 , and highest TMAO concentrations in tertile 3 . As shown in Table p < 0.01). Remarkably upregulated HbA1c% (6.1(5.9–6.5) in tertile 3 vs 6.1(5.7–6.1) in tertile 2 vs 5.7(5.5–6.1) in tertile 1, p = 0.03) and Cr (97(82.1–118.5) μmol/l vs 90.5(82.05–101.4) μmol/l vs 83.1(71.1–94) μmol/l, p < 0.01) levels were observed with increased TMAO concentrations. Accordingly, eGFR levels were decreased with increased TMAO tertiles (51.55(39.72–62.32) ml/min/1.73m2 in tertile 3 vs 56.22(49.27–65.64) ml/min/1.73m2 in tertile 2 vs 61.77(53.16–73.68) ml/min/1.73m2 tertile 1, p < 0.01). While no difference was found in other characteristics including sex, height, weight, BMI, SBP, DBP, HR, Glu, TG, TC, HDL, LDL, ALT, AST, WBC, CK-MB and EF% between different tertiles, it is noteworthy that the incidence of HFpEF significantly increased with increased TMAO tertiles (84 (78.5%) in tertile 3 vs 80 (73.39%) in tertile 2 vs 64 (59.26%) in tertile 1, p < 0.01). TMAO levels were inversely associated with eGFR score by Spearman analysis as shown in Fig. β = − 0.34, p < 0.01). Consequently, we further divided HFpEF patients into eGFR ≥60 group and eGFR < 60 group and observed significantly elevated TMAO concentrations in eGFR < 60 group compared to eGFR ≥60 group (14.18(10.4–23.06) μg/l vs 10.9(7.48–15.47) μg/l, p < 0.01, Fig. To investigate the changes of characteristics with TMAO levels, we further categorized the total study cohort into tertiles according to distribution of plasma TMAO. Subjects had lowest TMAO concentrations in tertile 1  after adjustment for other traditional risk factors including age, sex, SBP, HbA1c, Cr, TG, HDL and LDL. Not only that, TMAO was also an independent risk factor of renal dysfunction in HFpEF patients with an OR of 9.57  even after adjustment of age, sex, SBP, HbA1c, TG, HDL and LDL  were performed by logistic regression analysis Table . Elevatep < 0.01). The best cut-off threshold of TMAO in determining HFpEF and eGFR < 60 was 7.1 μg/l and 8.48 μg/l.At last, we performed receiver operating characteristic curve (ROC) analysis to explore the diagnostic role of TMAO in HFpEF and renal dysfunction. TMAO had good performance in discriminating HFpEF from healthy controls and discriminating eGFR < 60 from eGFR ≥60 in HFpEF patients, with AUCs of 0.63  [2  after adjustment for sex, age, SBP, HbA1c, TG, HDL and LDL by logistic regression in the present study. In experimental mice models, Li demonstrated the contributory role of TMAO in the pathogenesis of endothelial dysfunction and CKD [p < 0.01, best cut-off = 8.48 μg/l, Fig. A cross-sectional study indicated that patients with heart failure with preserved ejection fraction (HFpEF) who had worse right ventricular free wall strain by echocardiography had worse estimated glomerular filtration rate (eGFR), and reduced eGFR was also associated with worse outcomes . In ESCA2) . Heart f2) . There a2) . In addi2) . However2) , 29. Aft2) . Metabol2) . Coincid and CKD . Here weThis study has several limitations. First, this was a single center study, selection bias cannot be excluded. Second, as a cross-sectional study, we were not able to evaluate the future influence of TMAO on advance of HFpEF and its comorbidities. Additionally, we did not include other potential confounding factors such as patients’ nutritional status, recent diet, as well as microbiota profile, which might also influence the results.The present study explored the correlation of plasma TMAO with HFpEF and HFpEF with impaired renal function and revealed abnormal elevated TMAO with increased risk of HFpEF and worse renal comorbid conditions, and suggested the potential utility of plasma TMAO as a useful noninvasive biomarker for auxiliary diagnosis of HFpEF and renal function evaluation in HFpEF.


The mechanisms by which only some rheumatoid arthritis (RA) patients respond favorably to TNF blockade are still poorly characterized. The goal of this study was to identify biological features that explain this differential response using a multilevel transcriptome analysis of the synovial membrane.PH), and CD34-THY1+ fibroblasts were estimated using a cell-type deconvolution approach. TPH association was validated using immunofluorescence. External validation was performed on an independent dataset.Synovial samples from 11 patients on anti-TNF therapy were obtained by arthroscopy at baseline and week 20. Analysis of the synovial transcriptome was performed at the gene, pathway, and cell-type levels. Newly characterized pathogenic cell types in RA, peripheral helper T cells (TP < 5e−30), and an activation of the bone and cartilage regeneration processes (P < 5e−10). Cell-type deconvolution revealed a significant association between low TPH cells at baseline and a better response (P = 0.026). Lower TPH cells were maintained in good responders up to week 20 (P = 0.032). Immunofluorescent analyses confirmed the accuracy of the cell-type estimation  and an association with response. TPH association with anti-TNF response was validated in an independent sample of RA patients (P = 0.0040).After multiple-test correction, 16 and 4 genes were differentially expressed at baseline and week 20, respectively. At the pathway level, 86 and 17 biological processes were significantly enriched at baseline and week 20, respectively. Longitudinal expression changes were associated with a drastic decrease of innate immune activity (A lower abundance in the synovial membrane of the pathogenic T cell type newly associated with RA, peripheral helper T lymphocyte, is associated with a good response to anti-TNF therapy. Major changes in the myeloid cell compartment were also observed in response to therapy. The results of this study could help develop more effective therapies aimed at treating the pathogenic mechanisms in RA that are currently not well targeted by anti-TNF agents. Anti-TNF therapies have been a major breakthrough in the management of rheumatoid arthritis (RA) . To daten = 8 adalimumab-treated patients [The synovial membrane is the target tissue of chronic inflammation in RA , and itspatients  and founhiCXCR5-CD4+T cells in RA. Due to their capacity to provide B cell help, this new T cell subset was described as the peripheral helper T cell (TPH). The relationship of these new pathogenic cell subsets with the response to anti-TNF therapy in RA has not yet been addressed.The cellular composition of tissues and the extent of infiltration of immune cell types has proven to be predictive of disease subtypes of complex diseases like cancer . Very rePH infiltration is associated with a good response to therapy, and these lower levels are maintained through time. A lower baseline presence of myeloid immune cells is also associated with a favorable response and drastic reduction of this cell compartment is the main biological change observed in responders. The results of this study provide a comprehensive look at the biological mechanisms associated with anti-TNF response in RA.In the present study, we have performed a multilevel analysis of the synovial membrane transcriptome to identify critical biological mechanisms associated with response to anti-TNF therapy in RA. Using a longitudinal cohort of patients starting anti-TNF treatment, we identify differentially expressed genes, pathways, and cell types associated with the clinical response at week 20. In the latter analysis, using a cell-deconvolution approach, we find that a lower Tn = 6 infliximab, n = 3 adalimumab, n = 2 etanercept), were enrolled in this study. At the time of enrolment, all patients were naïve to any biological therapy. Response to treatment was defined by the EULAR response criteria [Eleven patients  fulfilling the American College of Rheumatology/European League Against Rheumatism 2010 criteria for RA , with a criteria  after 20Synovial samples were obtained by guided arthroscopy using a 2.7-mm arthroscope  under local anesthesia. In all patients, 6–8 biopsies were taken from the suprapatellar pouch and medial and lateral gutters with a 3-mm grasping forceps before starting a TNF antagonist. All patients underwent a second arthroscopy with synovial sampling after 20 weeks of therapy. Synovial biopsies for mRNA analysis were immediately stored in the RNALater preserving agent  and frozen to − 80 °C until RNA extraction .RNA was extracted from synovial biopsies using the RNA Mini Kit , and the integrity was assessed using BioAnalyzer microfluidic gel analysis . All samples were of high quality (RNA Integrity Number > 8) and were subsequently analyzed using Sentrix whole genome Beadchips WG6 version 2 . Briefly, after RNA isolation, biotin-labeled cRNA was prepared using the Ambion Illumina RNA amplification kit  and Illumina TotalPrep RNA Amplification Kit . Biotin-labeled cRNA (1.5 μg) was hybridized to WG6 v2 Beadchips and scanned on the 500x Illumina BeadStation. Data collection was performed using BeadStudio 3.1.1.0 software .https://www.ncbi.nlm.nih.gov/geo/). Using the keywords “synovial membrane” and “rheumatoid arthritis,” a total of 62 datasets were found that were performed on human samples. From these, after excluding in vitro culture studies and two-color microarrays, only two datasets, GSE57376 [n = 11 RA patients  were collected at week 12 of adalimumab treatment.To perform an independent validation of the cell type associated with treatment response, publicly available transcriptomic datasets (microarray or RNA-seq) were searched in the Gene Expression Omnibus database  enrichment approach [clusterProfiler R package. Genes with a nominally significant differential expression and a fold change > 1.2 were selected as input for this analysis; Bonferroni multiple test correction was applied to determine significant GO terms.After logg ComBat . Differeapproach  implemenhiCXCR5-CD4+ TPH cells were performed using Taqman assays . In the former group, FAM-labeled assays were used to measure the expression of PIK3CD (Hs00192399_m1) and CX3CL1 (Hs00171086_m1) genes, while TIMELESS (Hs01086960_g1) and CTLA4 (Hs01011591_m1) were used as TPH-associated markers. Ribosomal Protein L11  was used as an endogenous control gene, and all assays were performed using the Taqman Universal PCR master mix . Gene expression analysis was performed using the recommended protocol with the Applied Biosystems HT7900 system , and fold-change expression was calculated from the Ct values of the test and endogenous genes using the -2ΔΔCt method. The correlation between microarray gene expression values and RT-PCR values were calculated using Pearson’s product-moment correlation.Real-time quantitative PCR analyses of the genes most significantly associated with treatment response and marker genes for PD-1hiCXCR5-CD+ T cells, we used the set of n = 54 significantly overexpressed genes in TPH reported in the original discovery study [In order to estimate the enrichment of relevant T cell and fibroblast subsets in the synovial membrane samples, we adapted the SPEC (Subset Prediction from Enrichment Correlation) method . Brieflyry study  , Alexa Fluor Plus 647 goat anti-rabbit IgG , and Biotinilated goat anti-mouse IgG2b  plus Streptavidin Texas Red®  were used. Tissue samples were stained with DAPI  and mounted with Fluorescence Mounting Medium . The specificity of the primary antibodies was determined using rabbit and mouse IgG isotype controls  and by the omission of the primary antibody.Immunofluorescence analysis of the Try study . BrieflyDigitally scanned fluorescent images were acquired using a NanoZoomer-2.0 HT C9600 scanner  with a ×20 objective and coupled with a mercury lamp unit L11600-05 and using NDP.scan2.5 software U10074-03 . All images were visualized with the gamma correction set at 1.0 and the sharpen filter enabled in the image controls panel of the NDP.view 2 U12388-01 software . Image analysis was performed using QuPath software . Cell deFrom the 11 RA patients, 8 responded to anti-TNF treatment and 3 patients showed no significant clinical response at week 20 of therapy. The clinical and demographic data of the longitudinal patient cohort are detailed in Table n = 16 genes were differentially expressed between responders and non-responders  while the remaining 3 were overexpressed in non-responders. At the nominal level, 7 out of the 11 differential genes in the synovial membrane at week 0 continued to be differentially expressed between responders and non-responders at week 20  and the gene most highly expressed in non-responders  , GO:0002275|myeloid cell activation involved in immune response  and GO:0002444|myeloid leukocyte mediated immunity . This result suggests that the innate immune system composition in the synovial membrane conditions the response to anti-TNF therapy, with non-responders bearing a higher infiltrate of myeloid lineage cells . Comparing the longitudinal changes in biological pathways in the responder group, we found a profound modification with n = 149 GO terms significantly enriched from week 0 to week 20 , but also several biological processes are activated due to anti-TNF efficacy . In the former group, we found that the biological changes most associated in responders corresponds to the same three GO terms that are consistently different when comparing responders vs non-responders at the two time points: GO:0043299|leukocyte degranulation (adjusted P = 3.26e−32), GO:0002275|myeloid cell activation involved in immune response (adjusted P = 1.14e−31) and GO:0002444|myeloid leukocyte mediated immunity (adjusted P = 2.99e−30). This result corroborates that TNF efficacy is mainly mediated by the drastic inactivation of the innate immune system. Of relevance, the pathways that become activated due to TNF response include biological processes strongly related to the production of the specific components of the joint stromal tissue, including GO:0001501|skeletal system development (adjusted P = 2.11e−10), GO:0001503|ossification (adjusted P = 4.04e−8), GO:0001649|osteoblast differentiation (adjusted P = 2.61e−4), GO:0051216|cartilage development (adjusted P = 8−42e−4) and GO:0002063|chondrocyte development (adjusted P = 8.99e−4). This biological evidence shows that the effective clearance of inflammation is paralleled by the activation of joint tissue reconstruction programs.At the pathway level, at week, 0 rs Table . At weekrs Table . From thPH cells  showed the same trend of association as identified at baseline, although the difference was not statistically significant  . We found a significant correlation between the proportions of PD-1hiCXCR5-CD4+ T cells estimated through our approach and the actual abundance of this pathogenic T cell subtype in the RA synovia , we found a highly similar TPH profile to that of patients at week 20  .Having confirmed the association of T therapy . In the CX3CL1 and downregulation of leukocyte signaling kinase PIK3CD were significantly associated with a better response. At the pathway level, anti-TNF non-responders had a higher activation of myeloid cell immune response processes at baseline. A drastic downregulation of these same innate immunological processes was strongly associated with the efficacy of the drug at week 20. At the cellular level, lower TPH cells were associated with a good response to anti-TNF agents, both at baseline and at week 20. The results from this study provide a multilevel description of the biological determinants of anti-TNF response in RA.The reasons behind the variable efficacy of anti-TNF agents in RA have been elusive. Using single-gene, pathway and cellular deconvolution analyses on longitudinal transcriptomic data from the synovial membrane of RA patients treated with anti-TNF therapy, we have found key biological determinants of the response to this drug. At the gene level, baseline overexpression of the chemokine hiCXCR5-CD4+ T (TPH) cells were found to be significantly expanded in the synovial membrane of seropositive RA patients. Using the genes characterizing this T cell subset, we were able to estimate the presence of a significantly lower number of TPH cells in responders to anti-TNF therapy. This difference was clearly maintained up to week 20 in the good responder group of patients and validated in an independent cohort of patients. The transcriptional similarity between PD-1hiCXCR5-CD4+ T and follicular helper T (TFH) and the in vitro capacity to induce differentiation of memory B cells suggests a peripheral helper phenotype. Our results suggest that an important part of this TPH pathogenic activity in RA is associated with mechanisms that are independent of TNF. TPH may act by recruiting TFH and B cells, promoting local autoantibody production that may not be reflected in the serum, leading to pathogenic immune complex fixation. Furthermore, activated B cells can polarize into different subtypes to produce an array of proinflammatory cytokines other than TNF [PH, the inflammation will have alternative mechanisms to progress despite the reduction of TNF levels by anti-TNF agents.Recent studies based on single-cell analysis techniques have characterized new pathogenic cell subtypes associated with RA. Using single-cell mass cytometry, PD-1than TNF , includithan TNF . This waOur results also suggest that the stromal component of the synovial membrane participates in the favorable response to anti-TNF therapy. Single-cell analysis of the synovial membrane identified three different synovial fibroblast types : CD34-THCX3CL1 and PIK3CD, showing distinctively high expression levels at baseline in responders and non-responders, respectively. From these, only CXC3L1 remains overexpressed in the synovial membrane of responders at week 20. CXC3L1, also known as fractalkine, is a chemokine that can be present as membrane-bound or in soluble forms and is highly expressed in endothelial cells activated by TNF [hi monocytes that patrol endothelium have been shown to rapidly accumulate in sites after activation of the endothelium [At the single gene level, we found two genes, d by TNF . Interacothelium . AccordiPIK3CD is highly expressed in the synovial membrane of patients that will not respond to therapy. Together with PIK3CA and PIK3CB, PIK3CD is a class I phosphoinositide 3-kinase, which is a group of enzymes that phosphorylate inositol lipids and participates in different signaling processes [PIK3CA and PIK3CB are expressed in many different tissues, PIK3CD is limited to the cells of the immune system including T and B lymphocytes [PIK3CD has also been found to be highly expressed in RA synovial fibroblasts [PIK3CD expression in synovial fibroblasts but not in leukocytes [PIK3CD in RA synovial fibroblasts was shown to induce cell growth by sensitizing fibroblasts to platelet-derived growth factor (PDGF) [rocesses . While Pphocytes , neutropphocytes , and macphocytes . More reroblasts . In vitrukocytes . In thesr (PDGF) . Based or (PDGF) .PH proportions (data not shown). This suggests that more precise, molecular quantification techniques like transcriptomic analysis are needed to capture this patient variability. In this regard, the pathway analysis of genes associated with baseline with the response to anti-TNF therapy is in line with previous transcriptomic evidence [The pathway-level analysis of anti-TNF therapy response revealed an important contribution of the myeloid cell load. Our longitudinal data demonstrates that a high myeloid cell activity not only conditions for a poorer response, but also, that it is the biological process which is more highly altered by the drug’s efficacy. The existence of two patient groups in RA with different myeloid leukocyte activation is in high accordance with recent findings using a single-cell RNA-seq analysis. Analyzing the synovial membrane cell composition of a relatively large patient cohort of RA and osteoarthritis individuals, Zhang et al.  identifievidence , in whicPH to predict anti-TNF response. Examples of the disparity between association and prediction have been shown previously for example in genetic polymorphisms associated with the disease risk with insufficient disease prediction [PH abundance would therefore be a useful means to simplify patient recruitment and stratification and test its utility to predict response to anti-TNF therapy.While our results show an association between a new pathogenic cell type and the response to therapy, this does not imply that this information is sufficient to be used to predict treatment response in RA. Aspects like effect size and technical and biological variation can hinder the capacity of a biological marker like Tediction . To fillPH cell number. At the pathway level, response to anti-TNF treatment is strongly linked to an efficacious clearance of myeloid leukocyte activation. At the single-gene level, two genes previously associated with RA pathology, CX3CL1 and PIK3CD, were found to be markers for the anti-TNF response, implicating variability in the immune cell recruitment and fibroblastic growth capacities of the synovial membrane. The results from this study indicate new biological features of anti-TNF response in RA and could be useful starting points to allow for patient stratification and for the development of new therapeutic approaches, alone or in combination with TNF blockers, to achieve a favorable response for a larger number of patients.In the present study, we have performed a multilevel analysis of the RA synovial membrane transcriptome in relation to the anti-TNF therapy response. Using a cell-type deconvolution approach, we have found that a newly characterized pathogenic T cell subtype in RA, peripheral T helper cell, is associated with the lack of response to TNF blocking. Our longitudinal analysis shows that good response at week 20 is preserved by a sustained low TAdditional file 1 : Supplementary Table 1. Marker genes of the three synovial membrane fibroblast types. Supplementary Table 2. Significantly overexpressed genes in PD-1hi T cells according to Rao et al. Supplementary Table 3. Preservation of gene expression differences between baseline and response time point (week 20). Supplementary Figure 1. Preservation of differential expression changes associated to anti-TNF response in the synovium from baseline. Supplementary Figure 2. RTPCR replication of CX3CL1 and PIK3CD genes. Supplementary Figure 3. Association of the three fibroblast subsets at baseline with anti-TNF response. Supplementary Figure 4. Cell types associated with anti-TNF response: differences at week 20. Supplementary Figure 5. QRTPCR replication of TPH biomarker genes CTLA4 and TIMELESS. Supplementary Figure 6. Correlation between PD1hiCXCR5-CD4+ T cell abundance estimation using the cell deconvolution approach with the percentage quantified using immunofluorescence.Additional file 2 :: Supplementary Table 4. Significant GO terms of genes differentially expressed at week 0 between responders and non-responders to anti-TNF therapy. Supplementary Table 5. Significant GO terms of genes differentially expressed at week 20 between responders and non-responders to anti-TNF therapy. Supplementary Table 6. Significant GO terms of genes differentially expressed between week 0 and week 20 in the responder group of patients.


Therefore, we proposed a close correlation between the TNF-α polymorphism  and the disease progress of patients with AECOPD. Comparison of the TNF-α genotypes between the 198 AECOPD diagnosed patients groups and 195 healthy peoples suggested their significant differences of the three genotypes  distribution for TNF-α -308 (P < 0.05), but no differences of that for TNF-α +489. We found that patients with TNF-α -308 GA/AA genotypes showed smaller adjacent arterial diameter, thicker bronchial wall, higher bronchial artery ratio, higher bronchial wall grading, and higher frequency of acute exacerbations than those with TNF-α -308 GG genotype. Patients with TNF-α +489 GA/AA genotypes showed the same AECOPD properties as patients with TNF-α -308 except for the high frequency of acute exacerbations. Further experiment showed that the TNF-α -308 and+489 gene polymorphisms could affect the expression level of TNF-α in macrophages, suggesting the involvement of the macrophage population in disease regulation of AECOPD patients with TNF-α -308G/A and+489G/A genotype heterogeneity. In conclusion, the TNF-α -308 G/A genotype was related to AECOPD susceptibility and progress, while the TNF-α +489G/A genotype was related to AECOPD progress, but not AECOPD susceptibility.Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is becoming a common respiratory disease, leading to increased morbidity and mortality worldwide. Tumor necrosis factor-alpha (TNF- Chronic obstructive pulmonary disease (COPD) refers to a group of chronic inflammatory diseases that cause airflow blockage and breathing-related problems , 2. AlthMacrophages are the most abundant cells in the tumor stroma and exhibit obvious plasticity, which enables them to perform multiple functions in the tumor microenvironment . Tumor-aα, working as a proinflammatory cytokine, plays an important role in an inflammatory response. Many studies show that TNF-α is upregulated in the sputum, broncho alveolar lavage fluid, and bronchial biopsies of patients with COPD [α in the COPD progress. As a well-studied proinflammatory cytokine, many biallelic polymorphisms of TNF-α, including -308G/A (rs1800629), -376G/A (rs1800750), -238G/A (rs361525), and+489 (rs1800610) gene polymorphisms, are discovered. Among these polymorphic sites, -308G/A, -376G/A, and -238G/A polymorphisms are located in the promoter region of the gene, whereas +489 polymorphism is located in the first intron of the gene [α polymorphisms. As the best-studied TNF-α polymorphism [α +489 G/A polymorphism, which is involved in prostate cancer, systemic lupus erythematosus, and rheumatoid arthritis development [α polymorphisms (-308 G/A and+489 G/A) and AECOPD susceptibility of the Shanghai Han Population.Tumor necrosis factor- (TNF-) ith COPD , 14, sug8G/A rs3625, and+4morphism , 17, -30308G/A rs00629, -3morphism , but notmorphism –22. Besielopment , 25. HowThe AECOPD  patients and healthy populations  studied in this work were obtained from the Department of Respiratory Medicine at Minhang Hospital, Fudan University. A total of 198 patients and 195 healthy peoples of the Shanghai Han population were selected from January 2014 to June 2015. The Research Ethics Committees of Minhang Hospital approved the study, and all patients provided written informed consent.1/FVC < 70%; patient respiratory symptoms deteriorated more than the daily variation range, and when there is a need to change the drug regimen, during the disease, patients often had a short-term cough, sputum, shortness of breath and/or exacerbated wheezing, increased sputum, purulent or mucopurulent sputum, fever, and inflammation to significantly exacerbate symptoms. Patients with the genetic predisposition of other diseases, including hypertension, diabetes, coronary heart disease, or rheumatism, were excluded from the sample cohort. As for the control cohort, 195 healthy Han individuals  without disease history of other respiratory or systemic diseases, such as bronchiectasis, pulmonary fibrosis, sarcoidosis, asthma, lung cancer, diabetes, and heart disease, were selected. All of the individuals were confirmed as the normal lung and chest function through high-resolution computerized tomography (HRCT) examination.Specifically, patients were diagnosed as AECOPD according to the criteria described in “Chronic obstructive pulmonary disease treatment guidelines (2013 Revision)” established by the Chinese Medical Association Respiratory Diseases Committee. To be specific, eliminate other disease possibilities, after inhaling bronchodilator, FEVDetailed pathological datum, including medical history, age, gender, smoking index, and specific symptoms  was collected from the patients with AECOPD or the control subjects. Besides, the following two types of COPE classification were considered: Pistolesi et al.  revealedAll patients underwent chest HRCT examination at the end of a calm breath, using a 64-slice helical CT scan, from the apex to the bottom of the lung. Scanning parameters were as follows: voltage 140 kV, thickness 1.25 mm, current 112 mas, pitch 1.375 : 1, and lap speed 12.25 s. Workstation syngo. via was used to read the sections.Two radiologists evaluated the clinical data under double-blinded conditions. The average values of all indicators were taken into analysis. Based on the principles using 960 HU to define the normal lung and low attenuation area (LAA) published by Kitagichi et al. , 29, theα gene polymorphisms located on positions -308 G/A and+489 G/A, which are related to the transcriptional start site (TSS) of the TNF-α gene, were detected in genomic DNA derived from peripheral blood leukocytes. Briefly, 3 mL of blood was drawn from each subject after fasting and stored at -80°C after separation. Gene amplification was conducted using PCR-ABI 2700. Whole blood genomic DNA extraction was performed by Shanghai Yixiang Biotechnology Ltd. DNA was detected after cell lysis, precipitation, protease digestion, DNA adsorption, elution, and agarose gel electrophoresis. The primers for TNF-α -308 were designed as follows: TNF-α-forward (-308): 5′-AGGCCTCAGGACTCAACACA-3′; TNF-α-reverse (-308): 5′-GTTGCTTCTCTCCCTCTT-3′. The primers for TNF-α +489 were designed as follows: TNF-α-forward (+489): 5′-GTGTATGGAGTGAATGAATGAA-3′; TNF-α-reverse (+489): 5′-CCTGAGTGTCTTCTGTGT-3′. The desired gene product was isolated by agarose gel electrophoresis. PCR products were purified and sequenced by Suzhou Genewiz Biotechnology Company. If the result was bimodal at a given position, the position was interpreted as heterozygous; a single peak was interpreted as homozygous.The TNF-α, we downloaded the microarray expression profiles, including GSE71220, GSE42057, and GSE54837, from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi).To gather the expression data of TNF-α concentration assessment using TNF-α (human) EIA Kit .The blood samples from the AECOPD group and control group were obtained in the morning on or before breakfast from the median cubital vein, then immediately centrifuged at 3,000 rpm for 10 minutes. The serum was extracted for TNF-6 cells/mL in RPMI 1640 medium containing 10% FCS and 1% penicillin-streptomycin. Then, the PBMCs were cultured in 24-well plates (500 μl/well) and stimulated for 4 h with phorbol 12-myristate 13-acetate  and ionomycin  in the presence of 1× monensin  to obtain macrophage. The culture supernatants of macrophage were collected, centrifuged for 5 min at 300 g at 4°C, and aliquoted and stored at -80°C until analysis.Whole blood (20-25 mL) collected in tubes containing ethylenediaminetetraacetic acid (EDTA) as anticoagulant was processed between 9 : 00 am and 12 : 00 noon, within 3 h of collection. PBMCs were isolated by Ficoll-Paque  density gradient centrifugation (at 400 g for 30 min at RT with the break turned off) and washed twice with PBS (at 300 g for 10 min at 4°C). PBMCs were resuspended at 2.5 × 10t-test and χ2 test. The Hardy-Weinberg equilibrium was used to calculate the genotypic equilibrium, and the Fisher exact test was used to compare differences between genotype and allele frequency; P < 0.05 was considered as statistically significant.Data were analyzed and graphed using SPSS 19.0 statistical software . Data significance was measured using a The AECOPD cohort consisted of 198 Shanghai Han patients (79.76 ± 8.56 years old). Around 81% of the AECOPD patients were male. A total of 121 (61%) patients were smokers or exsmokers, and 77 patients (39%) stated that they had never smoked.The healthy population consisted of 195 Shanghai Han subjects derived from an anonymous panel of blood donors (81.26 ± 9.29 years old), including 157 males (81%) and 38 females (19%). The statistical analysis revealed no significant difference between the AECOPD cohort and the control subjects in terms of age and gender .α -308G/A and the TNF-α +489G/A gene polymorphisms in the two cohorts were analyzed, respectively  in the AECOPD group were 87.37%, 10.61%, and 2.02%, respectively, while the occurrence rates of the 3 genotypes in the control group were 95.38%, 4.62%, and 0%, respectively. Besides, the frequencies of G and A in the AECOPD group were 92.68% and 7.32%, while the frequencies in the control group were 97.69% and 2.31%, respectively. The results showed a significant difference in genotype frequency of TNF-α between the AECOPD group and control group (P = 0.001), ascribing to the enhanced frequencies of GA and AA in the patient group.For TNF-α +489G/A gene polymorphism, the frequencies of the 3 genotypes  in the AECOPD group were 70.71%, 23.23%, and 6.06%, respectively, while the frequencies of the 3 genotypes in the control group were 75.90%, 20.00%, and 4.10%, respectively. The statistical analysis revealed that there was no significant difference in the occurrence distribution of the 3 TNF-α genotypes between the two groups . Besides, the frequencies of G and A in the AECOPD group were 82.32% and 17.68%, while the frequencies of G and A in the control group were 85.90% and 14.10%, respectively. There was also no significant difference discovered in the occurrence distribution of the 3 TNF-α genotypes between the two groups .For TNF-α-308 or+489 genotypes and AECOPD phenotypes, the adjacent arterial diameter and bronchial wall thickness of AECOPD patients were measured . Two key indexes of the character of AECOPD, the ratio of bronchial wall thickness to adjacent artery diameter  and bronchial wall grading, were calculated. The results showed that the patients with non-GG genotypes (TNF-α-308 and TNF-α +489) had higher bronchial artery ratio and bronchial wall grading, suggesting more serious AECOPD phenotypes (P < 0.05).To investigate the correlation of TNF-measured . As a reα -308, patients carrying non-GG genotypes showed significantly more frequent exacerbations (P = 0.001) and dyspnea (P = 0.007) than patients carrying GG genotype. Unlike TNF-α -308, there was no significant difference between the TNF-α +489AA/GA group and GG group in frequency of acute exacerbations (P = 0.324), while the patients with AA/GA genotype presented a higher ratio of cough to dyspnea than patients with GG genotype (P = 0.001). The detailed data were presented in Furthermore, for TNF-α gene genotypes affect its expression level, we firstly detected the level of TNF-α in blood samples of the AECOPD group and control group. As a result, TNF-α was overexpressed in the AECOPD group  fluid in COPD patients [α in blood was mainly due to the extensive distribution of the macrophage population in the lung, and TNF-α gene genotypes could affect the expression of TNF-α in the lung macrophages. To verify our hypothesis, the PBMCs were isolated from blood samples of AECOPD patients carrying different TNF-α gene genotypes. Then, the cells were cultured and differentiated into macrophage-like cells using PMA. The TNF-α concentration in the culture medium was detected. The result showed that the TNF-α concentration was the highest in the TNF-α -308AA group , bronchial biopsy, and sputum samples of patients with COPD and associated with an elevated risk of acute exacerbation. These findings suggest that TNF-α is potentially involved with a local and systemic inflammatory response in the COPD process and may play an important role in determining the severity of the disease. Our previous study detecting TNF-α in the exhaled breath condensate of patients with AECOPD yielded similar results. Thus, TNF-α is one of the most active inflammatory cytokines in AECOPD. The genetic factor determines the changes in protein structures, which corresponds with pathophysiological changes. Therefore, exploring the relationship of heterogeneity of COPD phenotypes and genotype is necessary and is becoming the future trend for identifying the individualized prevention and treatment programs. The gene coding for TNF-α locates in the histocompatibility complex III region on chromosome 6.It is now widely recognized that COPD is a chronic inflammatory disease, in which multiple inflammatory cells, inflammatory mediators, cytokines in the lung parenchyma, and pulmonary vasculature that ultimately extends to multiple systems in the body are involved. In recent years, TNF-α -308 gene polymorphism in AECOPD susceptibility. Meanwhile, our current study also showed that the TNF-α +489 GA and AA genotypes did not correlate with AECOPD susceptibility in Chinese patients of the Shanghai Han ethnicity, under the results of Hegab et al. [α +489G/A gene polymorphism was correlated to a higher risk of developing breathing problems. This was especially true for patients with COPD without radiographic manifestations of emphysema. Matheson et al. [α +489AA allele had a higher risk of developing breathing problems, which was associated with small airway diseases. Han et al. [α -308 and+489 on macrophages in AECOPD.Our study supported the previous reports about the role of TNF-b et al. , while cb et al. . The maib et al.  yielded n et al.  also desn et al.  found a n et al.  describeα -308 and+489 locus G > A mutation may result in a higher expression value of TNF-α in macrophage. As a proinflammatory factor, TNF-α can induce the onset of COPD. The inflammation in the airway leads to a quick infiltration of neutrophils and promotes neutrophil cell adhesion, elastic peripheral cell dissociation, and proteolytic enzyme activity, which are conducive to the formation of emphysema. TNF-α could also induce the secretion of endothelin-1 by airway smooth muscle cells, resulting in the contraction of airway smooth muscle and airway cell proliferation, causing airway remodeling. TNF-α also promotes the production of IL-6 and IL-8 by bronchial epithelial cells and alveolar macrophages, thereby increasing the damage to lung tissues. In sum, TNF-α -308 and+489 gene polymorphisms are associated with disease severity and poor prognosis of patients with AECOPD in the Chinese Shanghai Han ethnicity. The results laid a theoretical foundation for AECOPD prevention, assessment, and personalized treatment development, thus improving the prognosis of the disease.This study included subjects of the Shanghai Han ethnicity and excluded those with hypertension, diabetes, coronary heart disease, rheumatism, and other genetic diseases. Our hypothesis for the association of the gene polymorphisms and the clinical phenotypes is that the TNF-


When this Special Issue was launched, we cast the net widely in terms of the subject matter we considered suitable for the papers. We stated that papers on “well-established unit operations such as heat treatments and membrane separation in addition to emerging technologies” would be welcomed. The seven papers accepted do, indeed, cover a range of topics including UHT milk, proteolytic digestion, membrane technologies, cheese and yogurt. Three papers ,2,3 invoEach submission explores innovative approaches by the respective authors in their quest to push the boundaries of scientific and technological understanding. Some examples are illustrated below: Chamberland et al.  address As editors of this special issue, we find it appropriate to reflect on how well the scientific originality of the reviewed manuscripts scored against sustainability criteria. The two membrane-based papers concerned with either protein standardization  or milk foods is making through this Special Issue: Processing and Technology of Dairy Products, given its achievement of a high impact factor, its commitment to a rapid turnaround of peer-reviewed manuscripts before publication, and its accessibility to a wide audience.It is important to recognize the valuable dissemination contribution that


Drosophila nervous system makes it an attractive system to address this possibility. We have thus investigated whether IIS in distinct glial cell populations differentially modulates development and lifespan in Drosophila.The increasing age of global populations highlights the urgent need to understand the biological underpinnings of ageing. To this end, inhibition of the insulin/insulin-like signalling (IIS) pathway can extend healthy lifespan in diverse animal species, but with trade-offs including delayed development. It is possible that distinct cell types underlie effects on development and ageing; cell-type-specific strategies could therefore potentially avoid negative trade-offs when targeting diseases of ageing, including prevalent neurodegenerative diseases. The highly conserved diversity of neuronal and non-neuronal  cell types in the We report here that glia-specific IIS inhibition, using several genetic means, delays development while extending healthy lifespan. The effects on lifespan can be recapitulated by adult-onset IIS inhibition, whereas developmental IIS inhibition is dispensable for modulation of lifespan. Notably, the effects we observe on both lifespan and development act through the PI3K branch of the IIS pathway and are dependent on the transcription factor FOXO. Finally, IIS inhibition in several glial subtypes can delay development without extending lifespan, whereas the same manipulations in astrocyte-like glia alone are sufficient to extend lifespan without altering developmental timing.These findings reveal a role for distinct glial subpopulations in the organism-wide modulation of development and lifespan, with IIS in astrocyte-like glia contributing to lifespan modulation but not to developmental timing. Our results enable a more complete picture of the cell-type-specific effects of the IIS network, a pathway whose evolutionary conservation in humans make it tractable for therapeutic interventions. Our findings therefore underscore the necessity for cell-type-specific strategies to optimise interventions for the diseases of ageing. The rapid and projected increase in life expectancy across industrialised nations  will bridaf-16 (the C. elegans insulin receptor orthologue) as a gene whose reduced activity can extend healthy lifespan [FOXO3A gene are associated with longevity in large-scale genome-wide association studies [Drosophila, FOXO is not required for the delayed development, reduced body size, or lowered fecundity from the same interventions [IIS is a highly evolutionarily conserved nutrient sensing pathway responsible for the coordination of nutrition with growth and metabolism across numerous tissues. While this pathway is necessary for appropriate development, its continued activity in adulthood is lifespan-limiting in diverse eukaryotic species , 5. Sinclifespan –10, inhilifespan  or RAS [lifespan , or overlifespan , 14. In  studies , 16, imp studies . At the ventions .Drosophila muscle tissue [Drosophila analogue of liver and adipose tissues) [Drosophila nervous system development, both in reactivating quiescent neuroblasts [Insulin-like Receptor (InR) gene in glia compared to all subclasses of neurons [Drosophila brains [It is likely that the pleiotropic effects of IIS inhibition also derive from diverse effects in distinct cell types, although few studies have extensively defined these cell types for both detrimental and beneficial effects. At the level of lifespan extension, IIS inhibition can promote longevity even when restricted to e tissue , gut ente tissue , or the tissues) , 14, wittissues) . Notablytissues) . Howeverroblasts , 23 and roblasts . In adul neurons . In addi neurons  and in Da brains , 27, sugDrosophila. We find that pan-glial IIS inhibition extends healthy lifespan and delays development, but without any impact on brain size or fecundity. We further describe that the effects on developmental timing and adult lifespan can be separated temporally by life-stage-specific IIS inhibition in glia. Finally, we find that the effects of glial IIS can also be separated spatially among glial subtypes, with reduced IIS in astrocyte-like glia able to extend lifespan without any effect on developmental timing, whereas its inhibition in other glial subtypes delays development without extending lifespan. Taken together, these findings present a robust example of cell-type-specific antagonistic pleiotropy in which a single molecular pathway exerts its opposing effects through distinct cell types, providing another layer of complexity to the understanding of ageing.We have therefore asked whether glial IIS modulates both development and lifespan through distinct glial subclasses in Drosophila lifespan when over-expressed in muscle [repo-GAL4, we found that Pten over-expression in glia significantly increased lifespan . Flies with glial Pten over-expression showed an overall 36% reduced hazard of death . Importantly, this lifespan extension was reproducible in independent experiments and with fly stocks backcrossed to either the outbred wDah or inbred w1118 strains , a lipid phosphatase that antagonises the activity of PI3K and has previously been found to extend n muscle  or pericn muscle . Using tUAS-Pten-G137E transgene with a Drosophila missense mutation analogous to human PTEN-G129E, which impairs PTEN’s lipid phosphatase activity while maintaining its protein phosphatase activity [Pten , but not Pten-G137E , extended healthy lifespan. We then used repo-GAL4 to drive expression in glia and found similar effects for glia-specific over-expression of Pten , but not Pten-G137E , in extending lifespan. In addition, wild-type Pten, but not Pten-G137E, delayed development when expressed in glia  driver reported to express specifically in glia [UAS-mCD8::GFP expression that Glia-GS expressed in glial cells only when flies were fed RU-486 . Flies with adult-onset glial Pten over-expression showed an overall 37% reduced hazard of death . These results suggest that Pten over-expression in glia during development is dispensable for effects on adult lifespan.To determine whether effects on development could contribute to later effects on adult longevity, we next used the GeneSwitch system to drive glial  in glia –35. We fInRDN) or a dominant-negative PI3K (dp110DN) significantly extended lifespan . Notably, whereas ubiquitous reduction of RAS activity downstream of IIS is sufficient to extend lifespan [RasDN, Additional file foxo∆, we observed that Glia-GS driving Pten no longer extended lifespan . While the short-lived nature of foxo-null flies might place limits on epistasis experiments, previous studies have found that multiple lifespan-extending interventions are able to extend the short lifespan of foxo-null flies, including dietary restriction [foxo over-expression [Pten over-expression can extend lifespan.We next investigated other means of IIS inhibition in glia. We found that adult-onset glial expression of either a dominant-negative insulin receptor . Interestingly, however, glial Pten over-expression was still able to delay development marginally in foxo-null flies , suggesting that FOXO is only partially required for the effects of glial IIS inhibition on development. These data suggest that FOXO is necessary for glial Pten over-expression to extend lifespan and is partially required for the effects of glial Pten over-expression on development; however, the effects on each life stage can be separated temporally.We next investigated whether FOXO was necessary for the effects we observed on development. We observed a blunted effect on egg-to-adult timing in Drosophila central nervous system glia comprise distinct subsets with functions that closely parallel their mammalian counterparts [Drosophila blood-brain barrier, cortex glia that surround neuronal cell bodies, ensheathing glia that line the neuropil, and astrocyte-like glia whose processes infiltrate the neuropil  or cortex glia (NP2222-GAL4)  or ensheathing (mz0709-GAL4) glia  alone was sufficient to extend lifespan . Flies with astrocyte-specific Pten over-expression showed an overall 34% reduced hazard of death . This lifespan extension was reproducible in independent experiments . However, our results are highly significant and reproducible and fall in the range we observe for ubiquitous over-expression of PTEN Fig.  as obser–45 days . When he–45 days . HoweverDrosophila, an extensive analysis of single-cell transcriptomes from ageing fly brains has found that glia, but not neurons, show a clear ageing trajectory of transcriptional patterns [C. elegans showing that a small population of astrocyte-like glia can modulate lifespan via secretion of one or more yet-unidentified neuropeptides [Several recent studies lend support to the hypothesis that glia, and astrocytes specifically, play key roles in nervous system ageing across species. Transcriptomic analysis of human brain tissue shows that many genes specific to astrocytes and oligodendrocytes, but few genes specific to neurons, change their regional expression patterns with age . Two othpatterns , with adpatterns . Taken tpeptides . Taken tDrosophila astrocyte-like glia share important functions that could contribute to their ability to modulate nervous system ageing or lifespan. In both mammals and Drosophila, astrocytes express transporters that clear the neurotransmitters glutamate [Drosophila astrocyte-like glia require the Megf10 orthologue Draper to clear neuronal debris during metamorphosis [Drosophila cortex glia [Mammalian astrocytes and lutamate  and GABAlutamate  from synlutamate , 50. In lutamate . Similarorphosis , 53. It tex glia  and enshtex glia  also platex glia , 46. Indtex glia , 56. TheDraper in Drosophila glia after neuronal injury [Drosophila glia reduces their ability to clear axonal debris after axotomy [Finally, our results pose an important question for understanding the evolution of IIS regulation among different cell types. If astrocytic IIS is lifespan-limiting and does not appear to play a central role in development, why has evolution not favoured a dampening of this pathway’s activity in astrocytes? Some hints to answering this question may come from the beneficial role played by glial IIS in clearing debris in the nervous system. For instance, signalling through the insulin receptor and AKT upregulates expression of l injury ; convers axotomy . When ta axotomy . TherefoDrosophila. We have further shown that the trade-off between extended lifespan and delayed development can be compartmentalised among glial cell subtypes, with IIS in astrocyte-like glia as a major modulator of lifespan but not development. As whole-organism IIS inhibition extends lifespan in a broad array of organisms including Drosophila and mice [Our results identify glia, and astrocyte-like glia specifically, as cell types through which IIS inhibition can extend lifespan in and mice , 5, it wStocks were maintained and experiments conducted at 25 °C on a 12 h:12 h light to dark cycle at 60% humidity, on food containing 10% (w/v) brewer’s yeast, 5% (w/v) sucrose, and 1.5% (w/v) agar. For experiments involving the GeneSwitch system, RU-486 (Sigma) dissolved in ethanol was added to the food at a final concentration of 200 μM, with 2 mL/L ethanol used as the vehicle control condition.white Dahomey (wDah) stock was derived by incorporation of the w1118 mutation into the outbred Dahomey background by backcrossing. All fly stocks in this study were back-crossed for six or more generations into the outbred wDah background, except for experiments in Additional file w1118 background. Fly stocks used were repo-GAL4 (Bloomington #7415); Actin5c-GeneSwitch [GSG3285-1 (Glia-GeneSwitch) [NP6293-GAL4 (Kyoto #105188); NP2222-GAL4 (Kyoto #112830); NP2276-GAL4 (Kyoto #112853); mz0709-GAL4 (3rd chromosome) [alrm-GAL4-#2 (3rd chromosome) [UAS-Pten [UAS-Pten3-G137E [UAS-InRDN ; UAS-dp110DN (dp110D954A Bloomington #25918); UAS-RasDN (RasN17 [UAS-mCD8::GFP (Bloomington #5130); and foxo∆ [The wild-type stock Dahomey was collected in 1970 in Dahomey (now Benin) and has since been maintained in large population cages with overlapping generations on a 12 h:12 h light to dark cycle at 25 °C. The neSwitch ; GSG3285eSwitch) , 35; NP6omosome) ; alrm-GAomosome) ; UAS-Pten3-G137E ; UAS-InR (RasN17 ); UAS-mCLifespan assays were carried out as described in detail in , with feFlies from parental crosses were allowed to lay eggs on grape juice plates (recipe and details available in ) for 3-hFlies were collected for lifespan assays and allowed to age to 1 week of age. The wet weights of individual cold-anaesthetised female flies were assessed using a Mettler Toledo AT201 balance with a sensitivity of 0.01 mg.In parallel to lifespan experiments, female flies were collected for quantifying the number of eggs laid. Twelve flies per vial were allowed to lay eggs on vials containing standard food for 24 h at the ages indicated, after which the vials were frozen to prevent larval hatching. After all vials were collected, a Logitech HD Pro C920 camera was used to capture images of the food surface for each vial. These images were processed for automated egg counting using QuantiFly software described in . The sofTubulin84B. Pten primers were designed to amplify both wild-type and G137E mutant UAS-Pten transgenes (Pten_tot primers) or to amplify only wild-type but not G137E mutant UAS-Pten transgenes (Pten_wt primers). Primer sequences were as follows: Pten_tot_for: AATTTCGCGGGAGAGTAGCTG; Pten_tot_rev: ACGGCTACAACATTGGACGA; Pten_wt_for: GTCCAATGTTGTAGCCGTGC; Pten_wt_rev: AGATCATGGTACCGGTTCTGC; Tub84B_for: TGGGCCCGTCTGGACCACAA; Tub84B_rev: TCGCCGTCACCGGAGTCCAT.Total RNA was isolated from 10 to 12 adult fly heads per replicate using standard Trizol (Invitrogen) protocols. RNA samples were treated with Turbo DNAse (Invitrogen) and converted to cDNA using oligod(T) primers and Superscript II reverse transcriptase (Invitrogen). Quantitative RT-PCR was performed using Power SYBR Green PCR Master Mix (ABI) in the Quant Studio 6 Flex system. Relative quantities of transcripts were determined using the relative standard curve method normalised to Immunofluorescence in adult brains was carried out as described in . BrieflyImage stacks were obtained on a Zeiss LSM700 confocal microscope using a × 10 or × 20 objective for whole-brain imaging and a × 63 objective for imaging of glial cell layers in the optic lobe. For whole brains, stacks of 10-μm Z-distance and 11 images per stack were taken. Images were quantified using Fiji software . For whop < 0.05 was considered significant.The statistical test used for each experiment is indicated in the figure legend. Log-rank tests on lifespan and developmental timing data were performed in Microsoft Excel  or GraphAdditional file 1. 4 supplementary figures, 1 supplementary table.Additional file 2. Raw data for lifespan experiments.


Analysis of isolated meninges and cerebrospinal fluid (CSF) of post-mortem MS cases has shown increased gene and protein expression for the pro-inflammatory cytokines: tumour necrosis factor (TNF) and interferon-γ (IFNγ). Here we tested the hypothesis that persistent production of these cytokines in the meningeal compartment and diffusion into underlying GM can drive chronic MS-like GM pathology. Lentiviral transfer vectors were injected into the sagittal sulcus of DA rats to deliver continuous expression of TNF + IFNγ transgenes in the meninges and the resulting neuropathology analysed after 1 and 2 months. Injection of TNF + IFNγ viral vectors, with or without prior MOG immunisation, induced extensive immune cell infiltration  in the meninges by 28 dpi, which remained at 2 months. Control GFP viral vector did not induce infiltration. Subpial demyelination was seen underlying these infiltrates, which was partly dependant on prior myelin oligodendrocyte glycoprotein (MOG) immunisation. A significant decrease in neuronal numbers was seen at 28 and 56 days in cortical layers II-V that was independent of MOG immunisation. RNA analysis at 28 dpi showed an increase in expression of necroptotic pathway genes, including RIP3, MLKL, cIAP2 and Nox2. PhosphoRIP3+ and phosphoMLKL+ neurons were present in TNF + IFNγ vector injected animals, indicating activation of necroptosis. Our results suggest that persistent expression of TNF in the presence of IFNγ is a potent inducer of meningeal inflammation and can activate TNF signalling pathways in cortical cells leading to neuronal death and subpial demyelination and thus may contribute to clinical progression in MS. The progressive phase of multiple sclerosis (MS) is characterised by an increasing burden of white matter demyelination, and axon loss and grey matter (GM) pathology that together contribute to irreversible accumulation of motor, sensory and cognitive symptoms , 29. It In secondary progressive MS (SPMS) post-mortem brains, greater leptomeningeal inflammation and grey matter demyelination were associated with elevated CSF protein levels of the proinflammatory cytokines TNF and IFNγ and the B-lymphocyte chemokine CXCL13 . MoreoveHere we have asked whether chronic demyelination and accumulating neuronal loss can result from persistently elevated levels of TNF and IFNγ in the subarachnoid space of the rat brain. In addition, we have investigated the contribution of anti-myelin autoimmunity to these pathologies in light of the fact that subpial demyelination in a previous acute model  only occFor lentiviral production we utilised a HIV-1 transfer plasmid (pRRL-sincppt-CMV-eGFP-WPRE genome plasmid) that carries the human cytomegalovirus promoter (CMV). Complementary DNA sequences for human tumour necrosis factor (TNF) or interferon gamma (IFNƴ) were codon optimised for rat .Recombinant HIV-1 based lentiviruses were produced using four plasmid co-transfection of HEK-293 T cells as described previously . BrieflyPrimary meningeal cultures were prepared from P4 Sprague Dawley pups. Briefly, the meninges were dissected from the surface of the cortex and digested with papain and DNAse. Cells were plated on poly-l-lysine coated 8-well chamber slides or 24 well plates (Corning) and grown in DMEM/F12  supplemented with 10% calf serum, 1% Penicillin/Streptomycin and 1% L-Glutamine . After 1 week in culture cells were transduced at MOI 50 with LV-TNF, LV-IFNγ or LV-GFP and the supernatant harvested after 24 or 48 h  rats (140-160 g) were obtained from Janvier (France) and kept in groups of four in a 12 h light/dark cycle with food and water provided ad libitum. All animal experiments were carried out under approval from the UK Home Office. For all groups n was 5 to 7 animals with a total of 68 animals for all experiments. Animals were randomly assigned to groups.Sub-clinical MOG-induced EAE was induced as described previously . Rats we8 genomic copies (GC) for TNF and GFP and 5 × 107 GCs for IFNγ. The needle was left in place for 10 min to allow diffusion of the sample from the area of injection and then slowly withdrawn.Rats were either used naïve with no treatment, immunised with MOG in IFA or IFA alone and stereotactic surgery performed at 20–23 days post-immunisation under isofluorane anaesthesia . A 5 mm Quantitative fully automated gait analysis was conducted with the CatWalk system . For the detection of all parameters the camera gain was set to 20 (dB) and the detection threshold to 0.1. For each animal and analysed time point, 6 compliant runs with a run duration of 0.5–5 s and maximum allowed speed variation of 60%, were acquired per trial.Rats were killed by intraperitoneal injection of 200 mg/kg of sodium pentobarbitone and a CSF sample taken from the cisterna magna using a 26G needle (Hamilton) before cessation of breathing, with the animal on a stereotaxic frame. Animals were perfused through the left ventricle with PBS followed by 4% paraformaldehyde at 28 and 56 days post viral injection and tissue prepared as described previously .Protein expression from the injected transgenes was measured in snap-frozen rat CSF on electrochemiluminescence (ECL) Proinflammatory panel 1 human assay plates  as described previously .Cortical tissue for each animal was dissected from 4 × 10 μm sections mounted on RNase free slides using a scalpel, taking extra care not to include meningeal tissue. RNA was extracted using the FFPE mini tissue kit (Qiagen) and quantified using a Nandrop ND1000 spectrophotometer. 700 ng RNA was reverse transcribed for each sample using RT2 First Strand Kit before a proprietary amplification step using the RT2 PreAMP cDNA synthesis kit for the Rat necrosis PCR array . The PreAMP mix was run on RT2 profiler PCR rat necrosis array plates  on a Stratagene MX3005P system. Relative fold changes were calculated using SABiosciences web-based PCR array data analysis tool.For RT-PCR experiments 200 ng of RNA was reverse transcribed using nanoscript2 kit from Primerdesign. Real Time PCR was performed using the Stratagene MX3005P system as described previously . PrimersImmunohistochemistry/immunofluorescence was performed as previously described  using mo2. For lymphocytes, neurons and microglia, the number of cells was calculated from four sections per animal that were spaced 10 μm apart covering a total distance of 80 μm per animal.Meningeal lymphocyte numbers were counted manually from digital images of the CD4, CD8 and CD79a immunostained sections, using a region of interest that spanned from the base of the sagittal sulcus to the position of the lateral blood vessels visible in the meninges, and were expressed as total cells per region of interest. For both neuronal and microglial numbers, regions of interest were drawn that outlined the cortical layers or midline regions using ImageJ. Cortical layers were determined using co-staining with DAPI and Neun/HuCD to identify different cortical regions . NeuN+ aP-value of < 0.05 was considered significant in all cases.Graphpad Prism8 statistical software  was used in all cases to present the data and to conduct statistical analysis. All data on graphs are expressed as mean ± SEM except for PCR data which is shown with propagated standard error. Group comparisons for cell quantifications were analysed by one-way ANOVA with Tukey test for multiple comparisons. For Catwalk data we used two-way repeated measures ANOVA followed by Bonferroni’s post-hoc comparison tests when appropriate. A Primary meningeal cells could be 100% transduced with viral vectors for TNF, IFNγ or eGFP at an MOI of 50, demonstrating good tropism of the VSV-G envelope for meningeal cells  and MOG immunised animals (47% decrease). Vectors were generated by 4-plasmid co-transfection using the pMD2-LgRRE and pRSV-rev packaging plasmids, VSVg envelope plasmid and pRRLsincppt-CMV-TNF/IFNγ-WPRE genome plasmid in Hek293T cells. Human codon optimised TNF or IFNγ sequences were cloned into pRRL-sinccpt-CMV-WPRE HIV-1 genome plasmid under the control of an optimised human cytomegalovirus (CMV) promoter. Rat primary meningeal cells were transduced at MOI 50 with LVs expressing either eGFP, TNF or IFNy. Cells were stained with antibodies specific to human TNF or IFNγ protein 72 h after transduction . Human TNF and IFNγ levels in cell supernatants from rat primary meningeal cells transduced with LVs expressing either TNF or IFNy lentivirus at MOI 100 were measured at 24 and 48 h by enzyme-linked immunosorbent assay for human TNF or IFNγ protein (C).Additional file 2. Quantification of anti-MOG antibody titres in MOG immunised rats. Peripheral anti-MOG titres were quantified in serum from terminal blood samples taken at 28 dpi from rats injected with 5μg of rmMOG: for (A) total IgG, (B) IgG1, and (C) IgG2a. All data is presented as mean ± SEM.Additional file 3. Immunostaining for CNPase at 56 dpi in MOG immunised animals injected with GFP (A) or cytokine (B) viral vectors to confirm demyelination. Scale bar = 300 μm.


The coiled-coil domain containing 50 (CCDC50) protein is a phosphotyrosine-dependent signalling protein stimulated by epidermal growth factor. It is highly expressed in neuronal cells in the central nervous system; however, the roles of CCDC50 in neuronal development are largely unknown. In this study, we showed that the depletion of CCDC50-V2 impeded the neuronal development process, including arbor formation, spine density development, and axonal outgrowth, in primary neurons. Mechanistic studies revealed that CCDC50-V2 positively regulated the nerve growth factor receptor, while it downregulated the epidermal growth factor receptor pathway. Importantly, JNK/c-Jun activation was found to be induced by the CCDC50-V2 overexpression, in which the interaction between CCDC50-V2 and JNK2 was also observed. Overall, the present study demonstrates a novel mechanism of CCDC50 function in neuronal development and provides new insight into the link between CCDC50 function and the aetiology of neurological disorders. CCDC50 is a member of the A20/Tnfaip3 ubiquitin-editing complex and is involved in EGF-receptor-mediated deubiquitination for the inhibition of the downregulation of the EGF receptor (EGFR)4. This protein acts as a multifunctional regulator of inflammation, cell death, and proliferation6. CCDC50 is highly expressed in neuronal cells of the central nervous system (CNS) as well as in immune cells of the bone marrow, spleen, appendix, and lymph nodes11. CCDC50 was shown to be spatiotemporally distributed with the microtubule-based cytoskeleton in hair cells of the organ of Corti, a receptor organ responsible for hearing. Previously, it was demonstrated that the loss of CCDC50 function results in the disorganization of the microtubule-based cytoskeleton in hair cells and causes progressive hearing loss in autosomal dominant deafness 44 (DFN44)3. Although CCDC50 is dynamically expressed during inner ear development, in adults, it is prominently associated with cochlear hair cells, the functional impairment of which leads to alterations in intracortical network activities13. This suggests that CCDC50 may have an imperative role in neuronal development, but direct evidence has not yet been reported.The coiled-coil domain-containing 50 (CCDC50) protein  was identified as a phosphotyrosine-dependent signalling protein in epidermal growth factor (EGF)-stimulated human epidermoid carcinoma cellsCCDC50 gene were previously reported. Human CCDC50 variant 1  contains 306 amino acids (921 bp CDS) with skipping of exon 6, whereas human CCDC50 variant 2  consists of 482 amino acids (1449 bp CDS)14. In addition, mouse Ccdc50 variant 1  lacks exon 6, corresponds to human CCDC50-V1 and encodes a protein of 305 amino acids. Mouse Ccdc50 variant Vx3  corresponds to human CCDC50-V2 was predicted to encode a protein of 480 amino acids (1443 bp CDS). To date, the functional role of human CCDC50-V2 (Ccdc50-Vx3 in mouse), especially in regulating neuronal phenotypes, has yet to be determined.Two isoforms of the human 9. Consequently, a closely related RTK that is activated by NGF, nerve growth factor receptor (NGFR)  and TrkA receptor tyrosine kinase, induces neuronal differentiation by stopping the proliferation of cells. The NGFR signalling pathway is a representative growth factor/receptor pathway with intrinsic tyrosine-kinase activity that promotes structural changes and the axonal growth of neuronal cells7. NGFR, in response to NGF, induces the phosphorylation of JNK isoforms in hippocampal and granular neuron cells in the developing brain15. In addition, in response to sustained activation of ERK, NGF recruits the Shc-Grb2-Sos complex to the TrkA receptor, thereby activating several downstream protein signalling pathways, including the phosphatidylinositol 3-kinase (PI3K) pathway. PI3K then activates JNK, which, through the activation of c-Jun, can promote differentiation17.The complex array of specific cellular responses that relay signals from canonical systems is known to govern cell fate. Two growth hormones, EGF and nerve growth factor (NGF), interact with the receptor tyrosine kinases (RTKs) and stimulate the signalling cascades to induce cell proliferation and differentiation, respectively. Therefore, the signalling molecules provide cues to modulate the activation of the canonical signalling cassette  and drive either proliferation or differentiationIn this study, we uncovered a new mechanism of CCDC50-V2 function in neuronal development. Using multiple types of cultured neurons, we demonstrated that CCDC50-V2 controls neuronal development by regulating axonal guidance, especially during arbor formation, spine density and axonal growth. Moreover, CCDC50-V2 induces the JNK/c-Jun activation and the positive regulation of NGFR expression, while it negatively regulates the EGFR pathway, thereby playing a crucial role in cell fate control during neural development. These findings support an important role for CCDC50-V2 in neuronal development through the regulation of signalling pathways associated with cell fate control and neuronal differentiation.CCDC50, and the axonal and dendritic growth patterns of the transfected neurons were examined using immunocytochemistry and quantitative real time RT-PCR analysis. We observed a significant decrease in axon length in Ccdc50 knockdown mouse hippocampal neurons  against ons Fig. A,B. The bb3 Fig. C. In addtes Fig. D,E. ThesCCDC50 variants in neuronal development, the effect of CCDC50-V1 and CCDC50-V2 knockdown on neuronal differentiation was evaluated. For this purpose, human SH-SY5Y neuroblastoma cells were transfected with two plasmids, shCCDC50-V1 and shCCDC50-V2, which are silencing vectors of human CCDC50-V1 and CCDC50-V2 , and that 81% of the nucleotide sequences and 82% of the amino acid sequences are similar to human CCDC50-V2 (NM_178335.2). To confirm the expression of Ccdc50-Vx3 in mouse primary neurons, we performed RT-PCR analysis with specific primers for mouse CCDC50 , was confirmed  in mouse primary hippocampal neurons compared to that in the control group  is involved in axonal and dendritic outgrowth in both primary and cultured neurons as well as in neuronal development under in vivo conditions.Computational analysis has predicted the existence of a murine 50 Table ; then thice Fig. C. Surpri10. To gain insights into the function of CCDC50 in neuronal development, we investigated the role of CCDC50 through its association with the EGF signalling pathway. The results of the western blot analysis revealed that the overexpression of CCDC50-V2 led to a decrease in EGFR expression and increased phosphorylation of EGFR-Y1045, which is a phenomenon that has been reported in EGFR degradation by ubiquitination20, suggesting the activation of EGFR degradation in CCDC50-V2-overexpressing cells . The IP data showed that CCDC50-V2 interacted strongly with endogenous JNK, particularly the 54-kDa JNK isoform 2 (JNK2), while CCDC50-V1 did not bind it , D2 (amino acids 150–324), and D3 (amino acids 325–482), to determine the region of CCDC50-V2 that binds with JNK2. As demonstrated in Fig. It was previously revealed that CCDC50 consists of one coiled-coil domain and two motifs that interact with ubiquitin domains that are known to function as a binding site for the ubiquitinated EGF receptorIn this study, we show that CCDC50-V2 is associated with the development of neuronal phenotypes. The loss of function of CCDC50-V2 resulted in a decrease of axon and dendrite outgrowth, indicating that CCDC50-V2 plays a crucial role in establishing the axodendritic architecture in neuron cells through the receptor-mediated pathway Fig. . In addi3. CCDC50 is also involved in the regulation of RTK-mediated signalling pathways and acts as a multifunctional regulator of the large RTK family and various ligands28; CCDC50 is therefore presumed to be closely related to growth factor signalling. Here, we observed that CCDC50-V2 inhibits the EGFR signalling pathway by downregulating the EGFR level and suppressing the ERK and AKT signalling cascade via EGFR phosphorylation. However, surprisingly, this phenomenon was not observed for other variants of CCDC50  (data not shown). We also demonstrated that the two variants of CCDC50 were differentially expressed during the cortical neuronal development process in mice29. Unlike that of Ccdc50-V1, the expression of Ccdc50-Vx3 was augmented in cultured primary neurons from mice at DIV 1–5  has more profound effects than CCDC50-V1 on neuronal differentiation in SH-SY5Y cells. CCDC50-V2 silencing inhibited neurite outgrowth in the cells, but CCDC50-V1 silencing increased neurite outgrowth, indicating the opposite effects of the two variants. These findings suggest that there might be a certain mechanism fine-tuning the balance of the variant levels of CCDC50 for proper development of the nervous system. In many cases, variants are known to perform different functions due to post-transcriptional modification of the primary transcript30. Previously, the specific expression patterns of two variants of CCDC50 were identified in hepatocellular carcinoma cells; CCDC50-V1 mRNA expression was shown to be highly increased by alternative splicing (exon skipping)31. From these results, we surmised that the two variants might exhibit functional differences in the regulation of dendritic and axonal outgrowth in neuronal cells and that CCDC50-V2 might play a more critical role than CCDC50-V1 in the process. Further studies on the control of the spatiotemporal expression of the two CCDC50 variants may provide a better understanding of their fine tuning during nervous system development.CCDC50 has been identified as a tyrosine-phosphorylated protein, and the tyrosine phosphorylation of CCDC50 inhibits the downregulation of EGFRCCDC50-V2 significantly reduced the mRNA expression level of neuron-specific cytoskeletal markers such as MAP2 and TUBB3. MAP2 and TUBB3 are involved in microtubule assembly and play a role in determining and stabilizing axonal and dendritic shapes during neuronal development. They are accordingly observed within the axodendritic region of mature neurons33. Thus, the inhibition of neuronal markers and axodendritic architecture disruption in CCDC50-V2-silenced cells further indicates that CCDC50-V2 plays a crucial role in neuronal development. In addition, we observed that the activation of p-JNK and p–c-Jun activity is associated with increased expression of CCDC50-V2. The activation of JNK has been shown to play a crucial role in various pathological and physiological processes, such as cancer and neuronal development (including brain morphogenesis and axodendritic architecture)38. Moreover, c-Jun is a well-known transcription factor required for the regeneration of axons in injured neurons; it aids in the functional recovery of damaged neurons39. Therefore, these findings suggest that CCDC50-V2 induces neuronal characteristics such as neuronal outgrowth, in which the activated JNK/c-Jun pathway might be played an important role.In subsequent functional studies, we demonstrated that CCDC50 regulated not only neurite length but also the number of primary and secondary dendrites as well as dendritic arborization. The knockdown of Furthermore, we uncovered that CCDC50-V2 binds to endogenous JNK (54 kDa) but fails to bind to its substrate c-Jun and upstream kinases, such as MKK4 and MKK7. The truncated mutant study clearly indicated that the V2-specific region containing the amino acids 150–324 has a specific binding site for JNK2. These data suggest that the CCDC50-V2-JNK2 interaction might be linked to JNK activation by CCDC50-V2, with the V2-specific region playing a critical role in the formation of CCDC50-V2 and JNK2 complexes. As we demonstrated that the activation of JNK by CCDC50-V2 is concomitant with the appearance of phosphorylated c-Jun in the nucleus, it is likely that CCDC50-V2 regulates the transcription of genes dependent on c-Jun activity. However, more work on the roles of CCDC50-V2 in the JNK/c-Jun pathway under in vivo conditions needs to be carried out to elucidate the involvement of this pathway in neuronal developmental process.CCDC50-V2 expression, upregulation of NGFR was observed with a concomitant downregulation of EGFR. EGF stimulation produces transient activation of MAPK, leading to cell proliferation, while NGF initiates sustained MAPK activation and induces cell differentiation40. In addition, before cells commit to neuronal differentiation and neurite outgrowth by NGFR activation, it is typically required that they withdraw from the cell cycle to stop their proliferation. This is considered the fundamental event at the beginning of neuronal cell development42. In our study, we ascertained that the expression of CCDC50-V2 caused an increase in NGFR and the phosphorylation of JNK/c-Jun, while it decreased EGFR and ERK phosphorylation. These findings suggest that CCDC50-V2 plays a crucial role in the terminal differentiation of cells into the desired neuronal phenotypes that coincides with proliferation arrest through the regulation of tyrosine receptor kinases such as EGFR and NGFR.In reference to neuronal outgrowth caused by Overall, in this study, we described a new molecular mechanism of CCDC50-V2 function, showing that it is involved in the control of neurite outgrowth, which might be through the positive regulation of NGFR activity and its downstream signalling events. Our findings also provide evidence that CCDC50-V2 negatively regulates the EGFR pathway to play a crucial role in cell fate control during neural development. Finally, the novel molecular mechanism demonstrated in this study will help us understand axodendritic architecture during neuronal development.CCDC50-V2 vector was purchased from OriGENE . This vector was used as a template to generate truncated mutants of CCDC50 . For knockdown of CCDC50 , CCDC50-shRNA was produced by sub-cloning targeted nucleotides into pSuper.gfp/neo .A wild-type human 2 in a 37 °C incubator. The neuronal differentiation method for SH-SY5Y cells was used as described previously with some modifications42. The differentiation of SH-SY5Y cells was carried out in two steps using retinoic acid  and brain-derived neurotrophic factor . The RA medium consisted of DMEM/high glucose with sodium pyruvate without L-glutamine, 1% NEAA, 1% GlutaMAX supplement, 1% penicillin/streptomycin, and 3% FBS. The medium was further supplemented with all-trans RA (10 μM) before it was applied to the cells. After 24 h of RA treatment, half of the medium was replaced with fresh medium containing RA. After 120 h of RA treatment, BDNF medium containing DMEM/high glucose with sodium pyruvate without L-glutamine, 1% NEAA, 1% GlutaMAX supplement, 1% penicillin/streptomycin but without serum was added. Fresh BDNF (50 ng/ml) was added shortly before applying the medium to the cells.Human skin cancer A431 cells, human embryonic kidney HEK293T (293 T) cells and mouse neuronal HT22 cells were grown in Dulbecco’s modified Eagle’s medium (DMEM)/high glucose with L-glutamine and sodium pyruvate  supplemented with 10% foetal bovine serum  and 1% penicillin/streptomycin. Human neuroblastoma SH-SY5Y cells were grown in DMEM/high glucose with sodium pyruvate without L-glutamine , supplemented with 1% non-essential amino acid , 1% GlutaMAX supplement , 1% penicillin/streptomycin , and 10% FBS. The cells were maintained in 5% CO43. Hippocampi and cerebral cortices were dissected from the brains of embryonic day 14 (E14) C57Bl/6 mice or embryonic day 18 (E18) rats and dissociated physically using Pasteur pipettes after trypsin treatment. Plating medium , N-2 supplement , and NEAA) was used to plate the primary neuronal cells. The cells were maintained in neurobasal medium  with B-27 supplement  and 1% GlutaMAX supplement . On day in vitro 3 (DIV 3), mouse neurons were grown on poly-D-lysine -coated glass coverslips and transfected with vector or small interfering RNA (siRNA) using Lipofectamine 2000  or RNAiMAX . On DIV 6, the mouse neurons were used for the indicated experiments. Rat neurons were grown on glass coverslips on DIV 5 and transfected using the calcium-phosphate method.Primary hippocampal and cortical neurons were prepared as previously described5 cells/well in a 6-well plate; primary cultured neurons: 1 × 106 cells/60 mm2 dish). After 36 h of incubation, siRNA transfection was conducted using Lipofectamine RNAiMAX. The concentration of siRNA was 100 nM. The transfected cells were allowed to grow for another 36 h. Afterwards, the cells were harvested, RNA was extracted using an RNeasy Mini Kit , and 1 μg of RNA was reverse-transcribed using an iScript cDNA synthesis kit . Reverse-transcription PCR (RT-PCR) was performed using the AccuPower PCR Premix (Bioneer). Quantitative real-time PCR was performed using the Bio-Rad PCR system (iQ SYBRR Green Supermix). The reactions were performed in triplicate. The PCR primers used in this study are described in Supplementary Table For polymerase chain reaction (PCR), cells were seeded in a plate (293 T and A431 cells: 1 × 102 dishes (1 × 106/well). After 36 h, transfections were performed using Lipofectamine 2000  according to the manufacturer’s protocol. The transfected cells were allowed to grow for another 36 h before the cells were lysed with 600 µl of immunoprecipitation (IP) lysis buffer containing a protease and phosphatase inhibitor cocktail  and centrifuged at 13,000×g for 10 min. The supernatant was incubated with 50 µl of anti-FLAG M2 affinity gel  or protein G-agarose  for 4 h. The beads were washed five times with 1 × Tris-buffered saline buffer. The proteins were eluted with Laemmli sample buffer  and boiled at 95 °C for 20 min. A quarter of the total eluate was resolved using SDS-PAGE with precast protein gels .For protein complex immunoprecipitation (co-IP), cells were seeded in 100-mmFor immunoblotting, protein samples were prepared by cell lysis with radioimmunoprecipitation assay buffer  or IP sample buffer. The protein samples were mixed with Laemmli sample buffer and boiled at 95 °C for 20 min. They were separated using SDS-PAGE (10–15 mA/gel) with precast protein gels. The separated proteins were transferred to a 0.45-μm nitrocellulose membrane  and blocked in 5% skim milk in Tris-buffered saline with Tween 20 for 1 h at room temperature. The membrane was incubated with primary antibodies in Can Get Signal  solution 1 overnight at 4 °C and in secondary antibodies in solution 2 for 1 h at room temperature.Two-fold serial dilutions of purified GST-JNK1 and His-JNK2 proteins  in binding buffer  were spotted onto a nitrocellulose membrane. Dilution of BSA controls were the same as the GST and His tagged proteins. The membrane strip was then blocked using 5% skim milk for 1 h and then was incubated overnight at 4 °C with 300 μg of 293 T cell lysates expressing mock or GFP-CCDC50-V2. The membrane was incubated overnight at 4 °C with an anti-GFP antibody (1:1000) in 1% skim milk binding solution and with a secondary antibody (1:2000) for 1 h at room temperature.For immunocytochemistry, cells were grown on poly-D-lysine-coated glass coverslips. Constructed vectors and siRNA were transfected into A431, SH-SY5Y, HT22, and 293 T cells using Lipofectamine 2000 or RNAiMax. After transfection, A431 and HT22 cells were serum-starved for 18 h and then stimulated with EGF  or nerve growth factor  for the indicated time. The cells were washed once in phosphate-buffered saline (PBS) and fixed in 4% paraformaldehyde (pH 7.4) for 10 min. The fixed cells were blocked in 5% bovine serum albumin for 30 min. The fixed and permeabilized cells were incubated with the indicated primary antibodies (500:1) for 12 h at 4 °C. After the primary antibodies were removed by washing the cells twice with PBS, the cells were incubated with Alexa Fluor-conjugated secondary antibodies (1000:1). The nuclei were stained with 4′, 6-diamidino-2-phenylindole dihydrochloride .44. Individual neurons and fixed cells were imaged using confocal microscopy  with a 20 × and 40 × objective, and the images were printed. To obtain the Sholl profiles of dendritic arbors, printouts were placed under a clear sheet featuring concentric circles with diameters that increased in 20 μm increments. The centre of the circles was placed on the cell body centre, and the number of dendrites that crossed each concentric circle was counted. Quantification of primary and secondary dendrites was also obtained from images of individual neurons taken using a 20 × objective.Neurite outgrowth was analysed using a fluorescence microscope  and NIS-Elements software . Quantification of the neurite length of primary neurons and differentiated SH-SY5Y cells was also determined from images of individual neurons taken using a 10 × objective. Sholl analysis was performed using a previously described modified method45. The density of dendritic protrusions (0.4–2.5 μm) was measured from 70 to 90 dendrites from 14 to 18 neurons; a total dendritic length of ~ 50 μm was measured from the first dendritic branching points. Means from multiple individual dendrites were averaged to obtain a population mean and SD.To analyse dendritic spine density, images were captured using confocal microscopy with a 63 × objective and examined blindly using MetaMorph software , as previously describedp values less than 0.05 were considered significant. Significance levels are expressed as follows: *p < 0.05, **p < 0.01, and ***p < 0.001.All experiments were performed in triplicate. All statistical analyses were performed with GraphPad Prism software  or Microsoft Excel. The error bars represent the standard deviation (SD). An unpaired, two-tailed Student’s t-test or analysis of variance was used for statistical analyses unless otherwise specified. Differences with Supplementary Information.