The homeodomain transcription factor, PITX2 is associated with tumorigenesis of multiple cancers. In this research, we aimed to study the expression, function and mechanism of PITX2 in lung adenocarcinoma (LUAD).The TCGA dataset was used to analyze the expression and clinical significance of PITX2 in LUAD. The expression of PITX2 in tumor samples and LUAD cell lines was examined by quantitative real-time PCR (qRT-PCR) and western blotting. Small interfering RNAs (siRNAs) were constructed to knockdown PITX2 and to determine the physiological function of PITX2 in vitro. Xenograft model was used to confirm the role of PITX2 in vivo.PITX2 was overexpressed in LUAD and patients with high level of PITX2 had a worse overall survival and an advanced clinical stage. Knockdown of PITX2 inhibited cell proliferation, migration and invasion of LUAD cells. Further study revealed that the oncogenic role of PITX2 was dependent on activating Wnt/β-catenin signaling pathway, especially by transcriptionally regulating the Wnt gene family member, WNT3A. Lastly, we identified miR-140-5p as a negative mediator of PITX2 by binding its 3′UTR and ectopic expression of miR-140-5p inhibited progression of LUAD cells via suppressing the expression of PITX2.Up-regulation of PITX2 acts as an oncogene in LUAD by activating Wnt/β-catenin signaling pathway, suggesting that PITX2 may serve as a novel diagnostic and prognostic biomarker in LUAD.The online version of this article (10.1186/s12935-019-0800-7) contains supplementary material, which is available to authorized users. Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer, with an increasing morbidity and mortality rate over the past decades , 2. MultThe homeobox genes are a group of genes containing homeobox (a 180 base pairs long DNA sequence) and encode homeodomain proteins that act as transcription factors . Many hoEarlier researches have discovered that homeobox genes are actively involved in the regulation of the Wnt pathway –17. PartMiRNAs, a class of 18–25 nucleotide non-coding RNAs, have emerged as key regulators of gene expression at the post-translational level by combining with the 3′UTRs (untranslated regions) of their target mRNAs . The miRhttps://genomecancer.ucsc.edu/) /2). And the tumor tissues were immunohistochemically stained with corresponding antibodies. All animal studies were conducted in accordance with NIH animal use guidelines and protocols were approved by Nanjing Medical University Animal Care Committee.LUAD tumor cells were transfected with shRNAs or control plasmids before transplantation. Six female nude mice (4–6 weeks old) per group were purchased from Nanjing Medical University School of Medicine’s accredited animal facility. 2 × 10t test was used to assess the differences between two groups. Chi square test was performed to analyze the differences between variables. Bivariate correlations between study variables were calculated by Pearson’s correlation coefficients. Kaplan–Meier method was used to plot survival curves. Statistical analysis was performed using SPSS Statistics software (version 20.0). p < 0.05 was considered statistically significant. Graphs were made using the GraphPad Prism 6.0 software package.Generally experiments were repeated for three times and data were presented as the mean ± SD. Student’s By analyzing the TCGA dataset (TCGA_LUAD_exp_Hi-SeqV2-2015-02-24), the expression of PITX2 was upregulated in LUAD tissues (n = 511) compared with normal tissues (n = 58)  were used and tumors were harvested at 6 weeks after transplantation Fig. a. The voTo determine the regulatory miRNAs of PITX2, three miRNA prediction datasets were analyzed and the results showed that miR-140-5p potentially bound to PITX2 Fig. a. AccordIn this study, we found that PITX2 was significantly upregulated in LUAD tissues and correlated with dismal overall survival and advanced clinical stages of patients. Knockdown of PITX2 inhibited tumor growth of LUAD both in vitro and in vivo. And PITX2 exerted its oncogenic role via activating Wnt/β-catenin pathway, especially by regulating the transcription of WNT3A. Furthermore, we found that miR-140-5p was a target of PITX2 and suppressed the progression of LUAD Fig. .Fig. 7PIThe progression of cancer is closely linked to activation of oncogenes and inactivation of tumor suppressor genes –44. LUAD552 [In aspect of mechanism, we found that PITX2 promoted LUAD progression as least partially by activating Wnt/β-catenin pathway. Wnt/β-catenin pathway causes an accumulation of β-catenin in the cytoplasm and its eventual translocation into the nucleus to act as a transcriptional coactivator of transcription factors that belong to the TCF/LEF family . Wnt/β-c552 . WNT3A h552 . And ourMicroRNAs regulate post-transcriptional gene expression via binding to the 3′UTR of mRNA, and either inhibit protein translation or destabilize target mRNA . TechnolTo sum up, our study identified PITX2 as a novel oncogene in LUAD. PITX2 promoted progression of LUAD partially by activating Wnt/β-catenin pathway, especially by transcriptional regulating the crucial member of Wnt ligands family, WNT3A. Further research revealed that miR-140-5p directly targeted the 3′UTR of PITX2 and suppressed the progression of LUAD. The miR-140-5p-PITX2-WNT3A axis provides a new sight into the tumorigenesis of LUAD and may represent a potential biomarker and a promising therapeutic target for LUAD patients.Additional file 1: Table S1. 317 genes used for pathway analysis.Additional file 2: Table S2. Sequences of qRT-PCR primers.Additional file 3: Table S3. Sequences of shRNAs and miRNA mimics.Additional file 4: Table S4. Clinical data of 60 LUAD patients.


Slug is one of the Wnt/β-catenin target genes and can induce epithelial–mesenchymal transition (EMT). Previously, we have shown that not only wild-type LEF-1 but also LEF-1 lacking the amino-terminal β-catenin–binding region can induce EMT, suggesting that LEF-1 acts independently of β-catenin. Because it has been reported that LEF-1 interacts with β-catenin outside the amino-terminal domain, namely, in the middle part of the molecule, the possible participation of β-catenin has not been formally ruled out. To determine the involvement of β-catenin in the LEF-1–induced EMT, we produced MDCK cells with a deletion of the β-catenin gene and then expressed LEF-1 in the cells. We found that LEF-1 induced EMT in those cells. In the absence of β-catenin, γ-catenin has been shown to take over the role of β-catenin. To examine this possibility, we first established MDCK cells with a double knockout of β-catenin and γ-catenin genes and then expressed LEF-1 in these cells. We found that LEF-1 can induce EMT in these cells; therefore, we conclude that neither β-catenin nor γ-catenin expression is necessary for the LEF-1–mediated induction of EMT.Transcription factor lymphoid-enhancer–binding factor 1 (LEF-1) is a key molecule in the Wnt/β-catenin signaling pathway.  •LEF-1 is a key molecule in the canonical β-catenin-dependent Wnt signaling pathway.•LEF-1 can induce EMT.•LEF-1 can induce EMT in cells with a double knockout of β-catenin and γ-catenin genes.•Neither β-catenin nor γ-catenin expression is necessary for the induction of EMT. We found that expression of LEF-1 induces EMT in these cells. We also generated MDCK cells in which β-catenin and γ-catenin genes were disrupted to rule out the possible compensation of β-catenin by γ-catenin. We found that LEF-1 induces EMT in these cells. These results revealed that LEF-1 induces EMT independently of β-catenin and γ-catenin.22.1CTNNB1 gene, and for γ-catenin, in exon 3 of the canine JUP gene. The sequences of oligonucleotides were as follows: β-catenin gRNA, 5′-ACCGGAAACAGCTCGCTGTACTGCG-3′ and 5′-AAACGCAGTACAGCGAGCTGTTTCC-3′; γ-catenin gRNA, 5′-ACCGCACCAAACTGCTCAACGACGG-3′ and 5′-AAACCGTCGTTGAGCAGTTTGGTGC-3′. Synthesized oligonucleotides for target KO gRNA were annealed and cloned at SapI sites into the pCGSapI vector, which was then transfected into JM109 cells. Clones were purified and subjected to DNA sequence analysis to check the oligonucleotide insert . Selection markers for cell transfection were neomycin (G418), hygromycin, and blasticidin resistance genes.Mouse LEF-1 cDNA was kindly provided by Rolf Kemler . HA-tagged LEF-1 expression vector (pCAGGS-LEFHA) has been described previously 2.2MDCK cells were cultured in Dulbecco's modified Eagle's medium (DMEM) containing 10% of fetal calf serum. The cells were transfected with 10 µg of the expression vectors or KO vectors by the calcium phosphate method 2.3Mouse monoclonal antibodies (mAbs) against E-cadherin, β-catenin, γ-catenin, fibronectin, and p120-catenin were purchased from Transduction Laboratories . A mouse mAb against vinculin and a rat mAb against HA were bought from Sigma  and Roche Diagnostics GmbH , respectively. A rabbit mAb against Slug was acquired from Cell Signaling Technology Japan . A goat polyclonal antibody against ZEB1 was purchased from Santa Cruz Biotechnology . All secondary antibodies were acquired from Jackson ImmunoResearch Laboratories .2.4Cells were grown on coverslips for 48 h, fixed with 3% paraformaldehyde in PBS for 20 min, and permeabilized with 0.1% Triton X-100 in PBS. After blocking, the fixed cells were incubated with primary and secondary antibodies as described previously 2.5Immunoblot analysis was carried out as described elsewhere 2.6Each KO cell line was lysed in TNE buffer containing 0.5% SDS, collected, and supplemented with 200 µg/ml proteinase K , with incubation at 50 °C for 3 h. Equal volumes of phenol and chloroform were added, and the mixture was rotated at 4 °C for 30 min; this procedure was performed twice. After centrifugation, supernatants were collected and mixed with a double volume of EtOH. The precipitate was dissolved in TE buffer containing 20 µg/ml DNase-free RNase , with incubation at 37 °C for 30 min. After the second precipitation with EtOH and centrifugation, the precipitates were dissolved in TE buffer and employed as a template for PCR.2.7SmaI site of the pBluescript II KS (+) vector. After transformation, plasmids were purified and subjected to genomic-DNA sequence analysis .These procedures were carried out and confirmed β-catenin and γ-catenin gene KOs. GoTaq DNA polymerase  was used for PCRs. PCR conditions were optimized for each primer pair as previously described 33.1In our previous study, we have reported that not only wild-type LEF-1 but also an amino terminus–deleted mutant LEF-1, ΔNLEF-1, which cannot interact with β-catenin, has an ability to induce EMT CTNNB1; To determine whether β-catenin is required for induction of LEF-1–induced EMT, we disrupted the β-catenin gene using the CRISPR/Cas9 gene editing system. We targeted the 20-nucleotide sequences upstream of the protospacer-adjacent motif (PAM) sequence in exon 4 of the canine β-catenin gene -tagged mouse LEF-1 expression vector into β-cat KO cells to determine whether LEF-1 can induce EMT without β-catenin. As expected, expression of LEF-1 induced morphological changes in β-cat KO cells toward the fibroblastic phenotype A. Immuno3.2Some studies have shown that γ-catenin too has an ability to bind LEF-1 JUP; To perform the KO of γ-catenin, we searched for a target site (20-nucleotide sequence) upstream of the PAM sequence in exon 3 of the canine γ-catenin gene  interacting with LEF-1 via a site other than the N-terminal region is necessary for understanding the mechanism of EMT induction by LEF-1.


The results showed that GPC3 expression levels in lung SCC tissues and cells were significantly elevated, and the high expression of GPC3 significantly promoted cell growth and tumorigenesis and repressed cell apoptosis, as well as increased β-catenin expression. Moreover, knockdown of β-catenin obviously weakened GPC3 role in the promotion of cell proliferation and tumorigenesis, as well as the inhibition of cell apoptosis. In conclusion, the present study demonstrates that up-regulation of GPC3 accelerates the progression of lung SCC in a β-catenin-dependent manner. Our study provides a theoretical basis for GPC3/β-catenin as a novel diagnostic marker and therapeutic target for lung SCC.As a cell surface proteoglycan anchored by glycosyl-phosphatidylinositol, Glypican-3 (GPC3) is reported to be highly expressed in hepatocellular carcinoma (HCC) and to promote cell proliferation and tumorigenesis through activating Wnt/β-catenin signalling. GPC3 is also overexpressed in lung squamous cell carcinoma (SCC), but its effects and mechanisms in the progression of lung SCC remain unknown. The present study aims to explore the role and molecular mechanism of GPC3 in the occurrence and development of lung SCC. Immunohistochemistry, Western blot (WB) and real-time PCR (RT-PCR) assays were used to determine the expression patterns of GPC3 in lung SCC tissues and cells. MTT, flow cytometry and  Lung cancer is one of the most frequently diagnosed malignancies and is the leading cause of cancer-related deaths in the world . Non-smaGlypican-3 (GPC3) is a cell surface proteoglycan anchored by glycosyl-phosphatidylinositol, which was first discovered in patients with Simpson–Golabi–Behmel syndrome . GPC3 seCapurro et al.  reportedThirty paired lung SCC tissues and paracancerous tissues acquired from patients with primary lung SCC who underwent surgical resection in the Third Hospital of Hebei Medical University between January 2015 and September 2017 were included in our study. All tissue samples were collected instantly after surgery and stored in liquid nitrogen for further experiments. The experimental work with human samples was carried out in accordance with the World Medical Association Declaration of Helsinki, and all subjects signed informed consents.All tissue samples were fixed in 10% formalin, embedded in paraffin and cut into 4-μm-thick slides for immunohistochemistry staining. Following antigen retrieval with citrate buffer (pH 6.0) at 100°C for 20 min, slides were incubated with 3% BSA diluted with PBS at room temperature for 1 h and subsequently incubated with anti-GPC3 antibody  overnight at 4°C. Then, the slides were incubated with horseradish peroxidase (HRP)–conjugated secondary antibody at room temperature for 1 h, followed by incubation with 3,3′-diaminobenzidine chromogenic reagent and Haematoxylin counterstaining.2.The human lung SCC cell lines NCI-H520, NCI-H226 and SK-MES-1, as well as the human normal lung cell line BEAS-2B, were all purchased from the American Type Culture Collection ; the human lung SCC cell line LTEP-s was purchased from BeNa Culture Collection . For cell culture, LTEP-s cells were cultured in DMEM with high glucose ; NCI-H520 and NCI-H226 cells were cultured in RPMI-1640 medium ; SK-MES-1 cells were cultured in MEM , all with 10% foetal bovine serum  and 1% penicillin and streptomycin supplement. All cells were maintained in a humidified incubator at 37°C with 5% COhttps://rnaidesigner.thermofisher.com/rnaiexpress/) was used to design the shRNA. The sequences with high score were selected and the knockdown efficiency was verified by real-time PCR (RT-PCR) and immunofluorescence technologies. To establish stable expressing cell lines, 400 μg/ml G418 and/or puromycin (Life Technologies) was added to the culture medium 48 h after transfection. After 7 days of G418 and/or puromycin treatment, cells were trypsinised and grown in a 96-well dish and expanded. shRNA sequences targeting human GPC3 and β-catenin genes are listed as follows:Lentiviruses containing GPC3-overexpressing plasmids (with neomycin resistance) and shRNAs targeting GPC3  and β-catenin genes , as well as their negative control (NC) nucleotide sequences, were all designed and synthesised by GenePharma . The online software . Then, the membranes were sealed with 5% non-fat milk and incubated with primary antibodies against PI3K , β-catenin , AKT1 , Wnt , STAT1  or GAPDH  overnight at 4°C, followed by probing with HRP–conjugated secondary antibodies  at 37°C for 1 h. After washing three times with PBS, the membranes were incubated with enhanced chemiluminescence reagents . For quantification, the Western blotting bands were quantified by ImageJ software  after background subtraction. The protein expression level was normalised to GAPDH expression.Ct−ΔΔ method. Primers used in the present study were provided by Beijing Genomics Institute  and listed as follows:Total RNA from lung SCC cells or tissue samples was extracted using TRIzol reagent  according to the manufacturer’s description. Then, a total of 1 μg of total RNA from each sample was used to form the first-strand cDNA with M-MLV Reverse Transcriptase , and RT-PCR was performed using SYBR Premix ExTaqII (Tli RNaseH Plus)  on the ABI 7500 Real-time PCR Instrument  in a 20-μl system. The relative expression of mRNA was calculated by the 2GPC3:Forward (F): 5′-TCATGCAAGGCTGTATGGCA-3′,Reverse (R): 5′-TGCCAATCTGTAAGTCTAGCCC-3′;Wnt1:(F): 5′-CAAGATCGTCAACCGAGGCT-3′,(R): 5′-AAGGTTCATGAGGAAGCGCA-3′;β-catenin:(F): 5′-GCGCCATTTTAAGCCTCTCG-3′,(R): 5′-GGCCATGTCCAACTCCATCA-3′;PI3K:(F): 5′-CCAGGGAAATTCTGGGCTCC-3′,(R): 5′-TGTATTCAGTTCAATTGCAGAAGGA-3′;AKT1:(F): 5′-CCAGCCTGGGTCAAAGAAGT-3′,(R): 5′-TGTACTCCCCTCGTTTGTGC-3′;STAT1:(F): 5′-CACAAGGTGGCAGGATGTCT-3′,(R): 5′-TCCCCGACTGAGCCTGATTA-3′;GAPDH:(F): 5′-AAAGCCTGCCGGTGACTAAC-3′;(R): 5′-GACTCCACGACGTACTCAGC-3′.4 LTEP-s/SK-MES-1 cells transfected with sh-GPC3 or sh-NC, vector-GPC3, vector-NC, or vector-NC + sh-NC, vector-GPC3 + sh-NC, vector-NC + sh-β-catenin, vector-GPC3 + sh-β-catenin were suspended with 100 μl of complete culture medium and then seeded into 96-well plates. After 24, 48, 72 or 96 h of culture, 10 μl of MTT  solution was added to each well and incubated for an additional 4 h at 37°C in the dark. Subsequently, the medium was replaced with 100 μl of DMSO to dissolve the formazan. The absorbance of each well was measured at 570 nm using a microplate reader  to evaluate cell viability.A total of 2×10LTEP-s/SK-MES-1 cells were grown in 24-well plates overnight, and then different treatments, including sh-GPC3, sh-NC, vector-GPC3, vector-NC, vector-NC+sh-NC, vector-GPC3+sh-NC, vector-NC+sh-β-catenin, and vector-GPC3+sh-β-catenin, were given to these cells. After 48 h of treatment, cells were collected and submitted to apoptosis detection with the Annexin V (FITC)/propidium iodide (PI) Apoptosis Detection Kit  according to the manufacturer’s instructions.5 cells/well and cultured for 48 h. Then, the cells were fixed with paraformaldehyde for 15 min at room temperature and incubated with rabbit polyclonal GPC3 antibody  or rabbit polyclonal β-catenin antibody , followed by the corresponding fluorescent secondary antibodies . Nuclear DNA was labelled in blue with DAPI at a 1:10000 dilution . Then, the glass coverslips were sealed with antifade reagent  and submitted to a laser scanning microscope  with a magnification of 400×.Transfected LTEP-s and SK-MES-1 cells were plated on glass coverslips in a 24-well dish at a density of 2×10in vivo tumorigenesis assay. Mice were fed in specific pathogen-free (SPF) conditions with standard food and water and submitted to a 12-h light/dark cycle. To explore the function of GPC3/β-catenin in the tumorigenesis of lung SCC cells, LTEP-s or SK-MES-1 cells (1 × 107 cells diluted in 200 μl of PBS) with stable expression of vector-NC+sh-NC, vector-GPC3+sh-NC, vector-NC+sh-β-catenin or vector-GPC3 + sh-β-catenin were subcutaneously injected into nude mice, with five mice in each group. All mice were killed after 21 days of implantation, and tumours were removed and weighed. All protocols involving animals were carried out in accordance with the Animal Experiment Ethics Review of the Third Hospital of Hebei Medical University.Male BALB/c nude mice weighing 18–20 g purchased from Shanghai Biomodel Organism Science & Technology Development Co., Ltd.  were used for the t test using SPSS 19.0 software. P-values less than 0.05 were regarded as statistically significant.All experiments were performed at least three times, and the data are presented as the mean ± standard deviation (SD). Differences between the experimental groups were assessed by Student’s To explore the function of GPC3 in the occurrence and development of lung SCC, we first compared GPC3 expression patterns in lung SCC tissue samples and matched non-tumour tissues through immunohistochemistry, Western blot (WB) and RT-PCR. The results demonstrated that GPC3 expression at both the protein and mRNA levels was elevated in lung SCC tissues compared with adjacent non-tumour tissues A–C. In avice versa   and was GPC3 functions entirely differently in various types of tumours. Specifically, GPC3 has been reported to be expressed at low levels in ovarian carcinoma , mesotheIn addition, we postulated that β-catenin was closely involved in the process by which GPC3 obviously accelerated lung SCC progression. β-catenin, an irreplaceable member of the classical Wnt signalling pathway, is activated and translocates to the nucleus when Wnt proteins bind to the frizzled (Fz) receptors in a paracrine pattern . It has In conclusion, the present study reveals, for the first time that GPC3 accelerates the progression of lung SCC in a β-catenin-dependent manner. Our study provides a theoretical basis for the GPC3/β-catenin axis serving as a novel therapeutic target for lung SCC.


The migration of HUVECs was measured by wound healing assays and transwell migration assays. Capillary formation was measured using tube formation assays. Immunocytochemistry (ICC) analysis was used to evaluate VEGF and RAMP2 expression in HUVECs. The relevant signaling molecules were detected with western blot. Our study shows that IMD could promote H/R impaired HUVECs migration and tube formation in vitro. On the other hand, inhibition of Wnt/β-catenin signaling led to the suppression of this promotion of migration and tube formation. This result suggests that Wnt/β-catenin signaling is correlated to IMD induced angiogenesis. Analysis of results from ICC assays indicated that IMD works through increasing levels of VEGF and RAMP2. Meanwhile, the Wnt/β-catenin signaling specific inhibitor IWR-1-endo was shown to down-regulate VEGF and RAMP2 expression. Western blot results further confirmed the signaling mechanism by which IMD promotes angiogenesis. Thus, Wnt/β-catenin signaling plays an important role in IMD induced neovascularization. The data further suggest that the PI3K axis contributes positively downstream.Intermedin (IMD) is a member of the calcitonin gene-related peptide (CGRP) superfamily and a pro-angiogenic factor. In the present study, we identified activation of the Wnt/β-catenin signaling pathway by IMD. Adding CoCl Renal ischemia-reperfusion injury (IRI) plays an important role in ischemic acute renal failure (ARF), which carries high morbidity and mortality following kidney transplantation and shock. Few effective therapeutic options exist to treat ARF . The kidin vitro [Intermedin (IMD), also known as adrenomedullin-2 (AM2), is a recently identified peptide that belongs to the calcitonin gene-related peptide (CGRP) family ,10. Recein vitro ,16. Sevein vitro .However, no evidence elucidates the connection between IMD and canonical Wnt signaling during neovascularization. In this study, we identify the mechanism of IMD under H/R conditions.2. Intermedin/adrenomedullin-2  treatment was prepared by adding IMD into DMEM for a final concentration of 20 ng/ml [Human umbilical vein endothelial cells (HUVECs) was obtained from the Cell Bank of the Chinese Academy of Sciences  and cultured in DMEM  with 10% fetal bovine serum . Cell cultures were kept in an incubator maintained at 37 °C in a humidified atmosphere with 5% CO20 ng/ml . Inhibit2) in DMEM. Reoxygenation was achieved by washing with phosphate-buffered saline (PBS) 3 times and changing the medium to DMEM for 1 h in an incubator. The experiment was divided into groups as follow: untreated HUVECs in serum-free culture medium ; H/R model (H/R); HUVECs preincubated with IMD for 1 h at 37 °C then changed to culture medium as for the H/R group (H/R + IMD); HUVECs preincubated with IWR-1-endo in incubator for 1 h, then changed to culture medium as for the IMD + H/R group with IWR-1-endo added (H/R + IMD + IWR).A chemical model of hypoxia was established with HUVECs by adding cobalt chloride  were added into the serum-free culture medium. After 24 h of hypoxia and 1 h reoxygenation, 20 μl of 5 mg/ml MTT  was added into each well, followed by incubation for 4 h in a condition protected from light. Then, the cell supernatant was discarded, and 150 µl dimethyl sulfoxide (DMSO) was administered with gently shaking for 10–15 min. The absorbance was recorded at 490 nm with a Microplate Spectrophotometer .The viability of cells in the H/R model was assessed using the 3--2,5-diphenyl tetrazolium bromide (MTT) assay. HUVECs were incubated in 96-well culture plates  overnight at a concentration of 1 × 10HUVECs were seeded in 6-well culture plates , then incubated. After reaching 70–80% confluence, cell monolayers were scratched with a sterile plastic tip (10 μl). Then, they were cultured in FBS-free culture medium, washed with PBS 3 times, then subjected to various treatments as indicated in the description of the four experimental groups. At 0 h and 24 h following scratching of the monolayers, cell migration in five randomly selected fields was observed using an optical microscope (×100 magnification). Images were captured using a digital camera .4 cells/well in 200 µl DMEM medium supplemented with 1% FBS were placed in the upper chamber . 24-Well culture plates . The lower chamber was filled with medium containing 10% FBS (600 µl). After 24 h migration, the cells that had not migrated on the upper surface of the membrane were scraped gently with a cotton swab. The migrated cells were fixed in 95% ethyl alcohol for 15–20 min and stained with 0.1% crystal violet for 15 min, then washed three times with PBS. Cells were counted in three randomly selected fields under an optical microscope (×200 magnification) and photographed using a digital camera .Cell migration was assessed using a transwell migration assay. HUVECs were harvested from each group. 2 × 104 cells/well) in 100 µl DMEM medium supplemented with 1% FBS. These aliquots of cell cultures were added to each well and incubated at 37 °C, 5% CO2 for 12 h. Tube formation was observed using a light microscope (×100 magnification) and photographed with a digital camera .96-Well plates were pre-chilled. Each well was coated with 50 µl of 50% Matrigel , which was polymerized for 30 min at 37 °C. HUVECs were harvested from each group , following the manufacturer’s instructions, for visualization using diaminobenzidine (DAB). Cells were then counterstained with Mayer' Hematoxylin  to label the nuclei. The primary antibodies used are as follows: VEGF ; RAMP-2 . Slides were observed using a light microscope (×100 magnification) and photographed with a digital camera .Cells attached to coverslips were fixed in 4% paraformaldehyde for 10–15 min. Then, they were permeabilized for 10 min with 0.5% Triton X-100. Next, we used Histostain The method of RT-PCR was described in our previous work . Real-tiHUVECs from each group were added in RIPA lysis buffer . Protein concentrations were measured using a BCA Protein Assay kit . Proteins were separated on 10% SDS-polyacrylamide gels assayed by immunoblot using β-catenin antibody , p-β-catenin (Ser675) antibody , GSK3β (Ser9) antibody duet , and β-actin antibodies . Secondary antibody used was (HRP)-conjugated goat anti-rabbit or anti-mouse IgG  at 1:5000. Signals were visualized with super enhanced chemiluminescence (ECL) detection reagent  and detected by Quantity One analysis system (Bio-Rad).p < .05 were considered statistically significant.Photographs were analyzed using Image J software and Image pro-plus 6.0 . Data are presented as mean ± SD. The statistically significant differences were identified by one-way analysis of variance (ANOVA), followed by LSD test. Values of 2 to establish a stable H/R model in vitro to mimic the pathological process of IRI. The MTT assay was used to determine the proper dose of CoCl2. As shown in 2 (p < .05). This condition was used for the following experiments.HUVECs were incubated with CoClThe wound healing assay and transwell migration assay were used to assess the migration capability of HUVECs. By comparing the wound area among groups , we obseIn order to elucidate the mechanism of the pro-angiogenic effect induced by IMD, we performed an ICC assay. This assay was used to test the expression of VEGF and IMD acceptor RAMP2. HUVECs treated with IMD expressed more VEGF and RAMP2 than did the H/R group. However, H/R cells treated with IMD and IWR-1-endo showed no increase in levels of VEGF and RAMP2. The mRNA expression levels of RAMP2 and VEGF in each group were measured by RT-PCR. Compare with the HR group, treatment with IMD significantly increased the mRNA expression of RAMP2 and VEGF. In the inhibitor group, IWR-1-endo initiate the degradation of RAMP2 and VEGF mRNA .To explore the mechanism of benefits induced by IMD, we evaluated crucial proteins of the Wnt/β-catenin signaling pathway in each group . WesternKidney is especially sensitive to IRI. The pathological process of IRI includes tubular cell injury and peritubular capillary damage. IMD has broad biological effects. Our study explores the mechanism by which IMD, serving as a pro-angiogenic factor, protects renal tubular epithelial cells from IRI . Throughin vitro. We established four different condition groups: normal, H/R, H/R + IMD, H/R + IMD + IWR-1-endo. Then, we observed differences in these groups. We found that in the H/R group, the migration ability of HUVECs were lower than in the normal group. Migration ability was restored with the addition of IMD. This result was in agreement with that of the in vitro tube formation assay, a representative test of neovascularization. Interestingly, the Wnt/β-catenin signaling inhibitor IWR-1-endo attenuated the protection of IMD. In neovascularization, many cytokines are produced that work together to manage this physiological process. VEGF is a potent pro-angiogeneic factor with strong abilities to promote proliferation, permeability and chemotaxis. The expression of VEGF is sensitive to β-catenin/TCF [In the present study, we used HUVECs to model neovascularization enin/TCF ,20,21. Henin/TCF ,22. We menin/TCF ,23. We cFurther, we investigated the molecular mechanism of Wnt/β-catenin signaling activated by IMD. GSK-3β is a component of the β-catenin destruction complex which mediates β-catenin degradation. Wnt signaling activity inactivation can lead to β-catenin accumulated in the cytoplasm . Cytosolin vivo we intended to do as an independent part may help us to get much more evidence. In conclusion, our study revealed that exogenous IMD up-regulates the expression of VEGF and RAMP2 at least partially via activating Wnt/β-catenin signaling, finally promoting angiogenesis of H/R impaired HUVECs in vitro.Although our current study provided significant results, there are still some limitations. Firstly, the mechanism of neovascularization is very complicated; some details of crosstalk interaction are still obscured in ambiguity whose resolution requires further research. Secondly, this study only analyzed the protection of exogenic IMD, while the decrease of endogenic IMD could be another interesting point. Thirdly, the further experiment


The introduction of novel therapies targeting either proteasome overload, the multiple myeloma (MM) microenvironment and/or immune effectors has dramatically improved the outcome of MM patients; nonetheless MM ultimately relapses and remains a deadly disease . The lacWe recently provided evidence of the oncogenic role of PRMT5 in MM . PRMT5 ivia the preferential methylation of H4R3 over H3R8, and controls the expression of key survival genes by cooperating with specific ATP-dependent chromatin remodelers, co-repressors, and co-activators. Its oncogenic activity extends beyond epigenetic effects, since PRMT5 also targets multiple non-histone proteins including p53, E2F1 and Sm proteins; as well as regulates splicing machinery, as critical component of the methylosome [We went on to delineate its mechanism of action in MM. PRMT5 is a versatile enzyme whose activity accounts for concomitant effects of histone and non-histone proteins targets, both in the cytoplasm and the nucleus. Among its functions, it induces transcriptional repression hylosome .via histone methylation or regulation of splicing machinery. These studies may not only delineate additional biologic sequelae of PRMT5 inhibition, but also identify potential biomarkers to inform clinical practice. Importantly, efforts are underway to develop a more potent and selective PRMT5 inhibitor for clinical translation, alone and in scientifically-informed combination therapies. Ultimately, targeting PRMT5 and its broad biologic sequelae in tumor cells represents a promising novel therapeutic strategy to improve patient outcome in patients with MM and other cancers.Our study demonstrates the functional significance of PRMT5 and validates the anti-MM activity of EPZ015666 in murine xenograft models of human MM, providing the framework for clinical trials targeting PRMT5 in relapsed MM (Figure


Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous ‘big data’ integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells’ actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions. Computational biology has successfully identified disease-linked genes [Computational biology has made vast strides. Rather than being a ‘second fiddle’ to experiments, it now often leads research. When the number of candidate experimental targets is daunting, computational biology can come to the rescue to filter, prioritize, and provide data-based hypotheses and leads. Vast and heterogeneous data are increasingly accessible, and computational biology can efficiently integrate these diverse information-rich resources, evaluate, and interpret the outcomes ,2. With ed genes ,19,20 aned genes ,22,23. Ned genes  in applied genes ,42,43,44ed genes ,50,51,52ed genes ,54, and ed genes . As the ed genes .no molecule exists in the cell as a mere string with covalently linked chemical blocks. Biological macromolecules fold as they are being synthesized either into stable three-dimensional shapes or into multiple interconverting states to populate an ensemble of ‘intrinsically disordered’ states [In line with the aim of this Special Issue, here, we focus on computational structural biology. It is convenient for scientists to consider biological molecules in terms of their sequences. Such a simplification bypasses the challenge of reliably modeling their structures on a large scale under diverse conditions and accounting for their function-related fluctuations. However, in reality, ’ states ,58,59. Thttp://www.cbd.cmu.edu/about-us/what-is-computational-biology/), frames computational biology by asking the broad question of how to “learn and use models of biological systems constructed from experimental measurements”. The aim is not necessarily to increase the understanding of the system, which may be so complex that it may not be fully understood or predicted; instead, the aim can be the creation of the model itself, even if currently unproven. Nevertheless, as scientists, our quest is always to understand.Bob Murphy, the head of the Computational Biology Department at Carnegie Melon University  identifying a new Switch-II pocket binding ligand (2C07) of the active GTP-bound state, transforming the pocket to that observed in the GDP-bound state [G12D [Computational biologists are driven by a fundamental ‘quest to understand.’ They exploit ‘big data’ and statistical trends for leads and search the experimental literature for functional observations. When possible, they cross-feed with experimental collaborators. This approach spawns more robust prediction schemes and allows reconciling experimental observations. It additionally leads to deeper understanding and innovative ideas, such as, for instance, the role of calmodulin in phosphatidylinositol-4,5-bisphosphate 3-kinase α (PI3Kα) activation in oncogenic KRas signaling and signaling selectivity at the membrane ,81,82,83nd state , and expte [G12D , as can te [G12D , redefinte [G12D , developte [G12D , proposite [G12D ,97, descte [G12D , and finte [G12D . Additiote [G12D ,110,111.Intertwined with computational biology, computational structural biology has continued to chart its path. After 50–60 years, the problem of predicting the three-dimensional structures of proteins from their sequences remains unsolved. With the apparent stalling in the progress of the ‘true’ ab-initio folding from ‘first principles’, focus has shifted to three components in modeling algorithms: the energy function, the conformational search, and the model selection ,115,116.Among the tenets that computational structural biology may increasingly embrace in the next few years are integrated deep neural networks, Markov state models, and metastable states for sampling conformational space, which will permit mining the entire free-energy landscape, thus providing insight into biological macromolecular actions, including catalysis ,128,129 th nearest-neighbor and maximum information spanning tree method, but still, solvation entropy is not computable from standard simulations. Implicit solvent methods could play an important role in this field. Indeed, with more refined solvation models, several proteins could be correctly folded . Even enhanced sampling methods providing free-energy landscape are not able to dissect the contributions to free energy. Similar to other free-energy methods, these are very slow. Entropy can be now accurately addressed for solutes by the kng group ,141). Fr(a)Modeling large molecular assemblies and critically figuring out their assembly–disassembly processes in the cell to regulate its functions(b)Modeling chromatin structure and dynamics and, especially, figuring out their regulation(c)Regulation of signaling in key protein nodes and between them in the cell(d)Modeling and prediction of drug resistance(e)Integration of experimental statistical ‘big data’ and the structural landscapes to model cells (tissues) behavior and system complexity(f)Precision medicine, to identify and predict drug targets, and drug discovery(g)Figuring out how the microbiota hijacks cell signaling and cell response to infection(h)Efficient sampling of the conformational space(i)Modeling across scales(j)Figuring out molecular mechanisms in detail and how these are commandeered by mutations in disease(k)Untangling redundant signaling pathways in the cell(l)Designing functional molecules and cells(m)Generating detailed, high-fidelity, synthetic biological data in silico to test hypotheses and advance model building, testing, and biological knowledge.Below, we list some of the areas that we foresee as taking the center stage and gaining momentum in the next years. In many, machine intelligence and an increasing level of automation are expected to become methodological requisites. In particular, we posit that a combination of deep neural networks (DNN) and Markov state models (MSM) is applicable to most of the topics on the list:PLOS Medicine, PLOS Computational Biology, PLOS ONE , and other journals [Bioinformatics is undergoing a revolution. Traditional statistical approaches increasingly give way to advanced algorithms. Advances in machine learning have been shown capable of representing potential-energy surfaces by fitting large data sets from electronic structure calculations , and a ‘journals , illustrNonetheless, the hallmarks have not changed. The key is to solve the questions that are still unanswered. The quest is to understand observations at the detailed level and to predict them. The paradigm underlying computational structural biology argues that to truly understand, one must have knowledge of the structure. Computational structural biology is a vast field. In this review, large areas of research are only sketched, and some are altogether missing. Our aim is to indicate highly important tasks that can be addressed by structural modeling and simulation and can thus be inspiring for the readers. Examples are provided to show that the methods and computational power are (and will be more and more) adequate for the tasks listed.


PH) is a common pregnancy complication, harmful to brain development. This study investigated whether and how PH affected Wnt pathway in the brain. Pregnant rats were exposed to hypoxia (10.5% O2) or normoxia . Foetal brain weight and body weight were decreased in the PH group, the ratio of brain weight to body weight was increased significantly. Prenatal hypoxia increased mRNA expression of Wnt3a, Wnt7a, Wnt7b and Fzd4, but not Lrp6. Activated β‐catenin protein and Fosl1 expression were also significantly up‐regulated. Increased Hif1a expression was found in the PH group associated with the higher Wnt signalling. Among 5 members of the Sfrp family, Sfrp4 was down‐regulated. In the methylation‐regulating genes, higher mRNA expressions of Dnmt1 and Dnmt3b were found in the PH group. Sodium bisulphite and sequencing revealed hyper‐methylation in the promoter region of Sfrp4 gene in the foetal brain, accounting for its decreased expression and contributing to the activation of the Wnt‐Catenin signalling. The study of PC12 cells treated with 5‐aza further approved that decreased methylation could result in the higher Sfrp4 expression. In the offspring hippocampus, protein levels of Hif1a and mRNA expression of Sfrp4 were unchanged, whereas Wnt signal pathway was inhibited. The data demonstrated that PH activated the Wnt pathway in the foetal brain, related to the hyper‐methylation of Sfrp4 as well as Hif1a signalling. Activated Wnt signalling might play acute protective roles to the foetal brain in response to hypoxia, also would result in disadvantageous influence on the offspring in long‐term.Prenatal hypoxia ( Epigenetic mechanisms regulate many aspects of cellular function such as transcription and post‐translation modification.22.12; normoxia) throughout pregnancy. The other group was exposed to hypoxia  in a plexiglass chamber from GD 4 to 21. At GD 21, some of pregnant dams were anaesthetized intraperitoneally with sodium pentobarbital , foetuses were removed through surgical hysterotomy and weighed immediately. The foetal brain was isolated and weighed, then frozen in liquid nitrogen and stored in −80°C freezer. Other pregnant rats were allowed to give birth naturally. The male offspring at 6‐week old were used for testing. All experimental procedures and protocols were approved by the Institutional Animal Care and Use Committee and in accordance with the Guidelines for the Care and Use of Laboratory Animals.Sprague‐Dawley rats (3 months old) were obtained from Soochow University Experimental Animal Center and housed in a controlled environment at 22°C with a 12/12 hour light‐dark cycle. Food and water were available ad libitum. One female rat was mated with 2 male rats. When vaginal plugs were observed in the following morning, the day was recorded as the first day of gestation (GD 1). Pregnant rats were randomly divided into 2 groups: The control group was kept in normal atmospheric conditions  were loaded to 10% SDS‐PAGE gels and transferred to PVDF membrane. Hif1a, β‐catenin, active‐β‐catenin and actin protein abundance were measured using primary antibodies , ,  and ; Blots were visualized using chemiluminescence detection . Imaging signals were digitized and analysed with UVP imaging system , and relative density of bands was normalized to actin as a control.2.3−ΔΔCT method.Total RNA was extracted from foetal forebrain and offspring hippocampus using RNAiso Plus (TaKaRa). Purified total RNA (500 ng) was then reversely transcribed using the RevertAid First Strand cDNA Synthesis Kit (Thermo Scientific) following the manufacturer's instructions. Primers for q‐PCR assays were designed using the Primer Express 4.0 software Table. . q‐PCR w2.4Genomic DNA from brain tissue samples was extracted using phenol:chloroform:isoamyl alcohol  and treated with sodium bisulphite with EZ DNA Methylation™‐GOLD Kit (Zymo Research) according to manufacturer's protocols. Unmethylated cytosine residues were converted to thymines, whereas methyl‐cytosines remain unmodified. PCR amplification was prepared for target CpG regions. After PCR amplification and library construction, products were sequenced on the Illumina MiSeq platform according to manufacturer's protocols. Methylation levels of 32 CpG sites in Sfrp4 were measured. Each tested CpG site was named according to its relative distance (in bp) to transcriptional start site (TSS). The percentage of methylation level of each CpG site was calculated as the ratio of methylated cytosines/total tested cytosines. The average methylation level was calculated using methylation levels of all measured CpG sites within the gene.2.5Spatial learning and memory in offspring was assessed using Morris water amazes. It consisted of 2 parts: a submerged platform (26 cm in height and 10 cm in diameter) and a circular pool (0.46 m in depth and 1.2 m in diameter). The rats were trained for 7 days with 4 acquisition trials each day. In each trial, rats were placed in the pool facing towards the wall. It was ended until it found the hidden platform, or until a limited time (60 seconds for a rat) elapsed, then the rat was guided to the platform and stay on it for 15 seconds. Swim speed, latency and travel distance to reach the platform were recorded. At the end of the day of acquisition training, the probe test to evaluate reference memory component in rats was used after the hidden platform was removed. The number of target approaches was recorded. All activities of rats in the tests were monitored, recorded and analysed using MT‐200 water maze video tracking system 2.6−7 mol/L) for 48 hour before harvesting. Expression of Dnmts, Sfrp4, Wnt3a, Wnt5a, Fzd4, Lrp6 and Catenin were examined by q‐PCR or Western Blot.PC12 cells  were cultured at 37°C in Dulbecco's modified Eagle's medium  containing 10% (v/v) heat‐inactivated foetal bovine serum  and 100 mg/mL penicillin G and 100 mg/mL streptomycin sulphate. After seeded in 6 cm dishes overnight, cells were treated with 5‐aza‐2′‐deoxycytidine  were used to analyse the data. The 2‐way analysis of variance (ANOVA) was conducted to analyse the water maze data. Other data were determined by the Student's 33.1P < .05)   Figure C. Blood ) Table. .3.2P < .01) , whereas there was no difference in Wnt2 and Wnt5a , whereas Lrp6 was unchanged  in the PH group, whereas total β‐catenin protein remained unchanged  , although mRNA expressions of the other 4 Sfrp family members were not changed , although Dnmt3a mRNA was not changed   abrogate Wnt signalling by forming complexes with Frizzled family protein to block Wnt signalling. The q‐PCR showed significant Sfrp4 down‐regulation in the foetal forebrain in PH group  Figure D, sugges3.4P < .05) . Wnt signalling and Fosl1 that were all increased in the foetal forebrain were decreased in the hippocampus of adolescent offspring  Figure . Hif1a p) Figure A. The ex) Figure C.There w) Figure B, D.3.5P < .05)    showed a significant increase in escape latency from day 3 to day 5  Figure A, and th) Figure B. Swim s) Figure C. In the) Figure D. These 3.6P < .05)    following hypoxia. The foetal brain weight was significantly decreased too, showing that PH not only affected general growth in utero, but also delayed brain development. Notably, IUGR led to increased risks of neurodevelopmental impairment during childhood.Wnt3a and Wnt7a are known to activate Wnt/β‐catenin signalling pathway, and participate in synaptogenesis and brain development.5C is catalysed by DNA methyltransferase (Dnmt),Secreted frizzled‐related proteins (SFRPs), as negative inhibitors of the Wnt pathway,The Wnt pathway is an essential signalling cascade that regulates cellular survival and differentiation, usually working as a positive factor in nervous systems. The Wnt signalling is abnormally activated in the progression of carcinoma, whereas down‐regulated in AD and PD.In summary, prenatal hypoxia significantly affected foetal brain development and caused activation of the Wnt signalling, which might be partly mediated by an increased Hif1a and functional loss of Sfrp4 through DNA methylation. This is the first time to demonstrate that Sfrp4‐mediated epigenetic methylation may be involved in possible protective mechanisms by the activation of Wnt/β‐catenin against hypoxia in the foetal brain. Notably, disadvantageous effects of the over‐activity of Wnt/β‐catenin signalling were also linked to a negative change in Sfrp4 associated with an suppressed Wnt/β‐catenin signalling later in the offspring brain. The new information gained contribute to further understanding the mechanisms underlying development of certain brain diseases and benefiting further investigation of early prevention of those health problems.The authors confirm that there are no conflicts of interest.Yingying Zhang, Mengshu Zhang, Bin Wei, Axin He and Lingjun Li, Likui Lu performed the research, Yingying Zhang, Mengshu Zhang, Xiang Li and Miao Sun analysed the data and wrote the paper, Miao Sun and Zhice Xu contributed essential reagents or tools. Miao Sun, Zhice Xu and Lubo Zhang designed the research study and wrote the paper. Click here for additional data file.


Drosophila larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. We show that all body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. We used TEM to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN ‘labeled line’ connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. We generated a recurrent network model that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors.Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. Here, we characterize  C. elegans , premotor interneurons (PMNs), proprioceptors, and descending command-like neurons . A parti elegans , there hDrosophila larva executes multiple behaviors, in particular forward versus backward crawling  and nine abdominal segments  MNs that provide octopaminergic innervation to most muscles  Forward and backward locomotion may use the same intrasegmental contraction patterns, and only the direction of the wave changes. (2) Different muscles/MNs could be used in each behavior. (3) One or more muscles/MNs may show a different time of recruitment in each behavior. (4) PMNs or MNs could have asymmetric morphology along the anteroposterior body axis, resulting in a different time of recruitment in each behavior. (5) One or more PMNs could be active only in forward or backward locomotion, changing the phase relationship of their target MNs. Here we use pan-muscle activity imaging, comprehensive TEM reconstruction of all MNs and well-connected PMNs, functional optogenetics, and development of a recurrent network model to sequentially test each of these hypotheses.Intrasegmental differences between forward and backward locomotion could be due to recruitment of different muscles for each behavior, or changes in the timing of muscle recruitment. To distinguish between these mechanisms, we performed ratiometric calcium imaging to map the activation onset of each body wall muscle during forward and backward locomotion. To date only muscle contraction data have been reported, not muscle activity data, and only for five of the 30 body wall muscles , showing that individual longitudinal muscles contract prior to individual transverse muscles during forward locomotion . Muscle R44H10-LexA, which has variable expression in sparse to dense patterns of muscles. For this experiment we analyzed larvae with dense muscle expression. We imaged both forward and backward locomotion in 1 st and 2nd instar larvae , and muscles 2, 11, and 18  . The VO To understand how motor patterns are generated, it is essential to map connectivity from muscles to MNs, and from MNs to PMNs. In this section, we fully reconstruct all 31 MNs in segment A1, and below we fully reconstruct 118 PMNs providing input to these MNs. These data on neuronal morphology, synapse localization, and connectivity will generate testable hypotheses for how different motor behaviors are generated.C. elegans  . Here, w elegans , we obse elegans . In concr = 0.97), which we averaged for subsequent analysis. This validated the quality and reproducibility of the MN dendritic synapse data and highlighted the stereotypy of MN postsynaptic locations in the neuropil. Next, we performed unbiased clustering of MNs based on postsynaptic synapse similarity, and found a highly ordered hierarchical relationship between postsynapse localization and innervation of spatial muscle groups  ; and two MNs innervating the three VO muscles . We found that MNs innervating muscles 11, 18 and the VOs each targeted postsynapses to a unique region of the neuropil. The VO MNs have a medial postsynaptic distribution not seen in other neurons in the same co-active muscle group ; MN11 haThere are two hypotheses for how co-active MNs are recruited. Each pool of co-active MNs may be innervated by a distinct pool of PMNs (labeled line), or alternatively each pool of co-active MNs may be innervated by different combinations of PMNs . To distinguish between these models, we identified and reconstructed all PMNs in the TEM volume with dense monosynaptic contacts to A1 MNs. The names of each premotor neuron along with previously published synonyms is given in As this is the first comprehensive characterization of larval PMNs, we first quantified key features of this population. The morphology of each of the 118 pair of PMNs is shown in Following our characterization of the PMN population, we next asked whether there are PMNs dedicated to innervating individual spatial or co-active MNs, or MNs differentially recruited during forward and backward locomotion. We identified PMNs innervating MNs of a single spatial muscle group , as wellNext we examined the five MNs that showed differential recruitment during forward versus backward locomotion , to see if they were selectively innervated by ‘labeled lines’ of PMNs. We found that all PMNs innervate multiple MNs, and there is no evidence for specific PMNs innervating specific MNs, whether they are differentially recruited or not . We concLastly, we tested whether our connectomic data could be used to predict the timing of MN recruitment. We found that the PMN A27h  is stronAsymmetric dendrite morphology can be an important determinant of neuronal function, such as in the direction-selective T4/T5 neurons in the adult visual system . SimilarDrosophila larval forward and backward crawling. To assess whether the reconstructed PMN connectome is capable of producing the observed timing of MN/muscle activation, we developed a recurrent network model of two adjacent segments. Previous models have focused on wave propagation during forward and backward crawling by modeling the average activity of excitatory and inhibitory subpopulations in each segment . With the exception of s models , the netcomotion , while ocomotion . Our stu elegans .PMNs, in addition to connecting to MNs, make presynapses onto other neurons , generatThe previously described forward-specific excitatory PMN A27h , with F3Next, we examined circuit motifs composed of a backward-specific PMN, A27k  . A27k exC. elegans  MNs in each spatial muscle groups receive inputs from overlapping but not identical array of PMNs. (ii) Different MNs in the same spatial muscle group receive a different number of synapses from the same PMN. (iii) MNs in the same spatial muscle group vary in overall dendritic size and total number of postsynapses, thereby resulting in MNs of the same spatial muscle group falling into different co-activated muscle groups.We demonstrate that during both forward and backward locomotion, most of longitudinal and transverse muscles of a given segment contract as early and late groups, respectively. In contrast, muscles with oblique or acute orientation often show different phase relationships during forward and backward crawling. Future studies will be needed to provide a biomechanical explanation for why oblique muscles – but not longitudinal or transverse muscles – need to be recruited differentially during forward or backward crawling. Also, it will be interesting to determine whether the VO or VL MNs are responsible for elevating the ventral cuticular denticles during propagation of the peristaltic wave; if the VOs, it would mean that lifting the denticles occurs at different phases of the crawl cycle in forward and backward locomotion.Drosophila olfactory , as well as incomplete characterization of PMN and MN biophysical properties. Recent studies have suggested that models constrained by TEM reconstructions of neuronal connectivity are capable of predicting features of neuronal activity and function in the lfactory  and visulfactory  systems,lfactory . For thelfactory , is suffC. elegans . Candidate PMNs that met these criteria could be excluded however if left/right orthologs could not be identified, or if gaps prevented reliable reconstruction of the PMN in the neuropil regions of T3, A1, and A2 segments.f is the mean synapse similarity between all synapses of neuron i and neuron skj. d is the Euclidean distance between synapses s and k such that synapse k is the closest synapse of neuron j to synapse s of neuron i. σ is a bandwidth term that determines what is considered close. isn and jkn are the fraction of synapses for neuron i and neuron j that are within ω of synapse s and synapse k respectively. For MN inputs, σ = ω = 2 μm. Clustering was performed by using the average synapse similarity scores for the left and right hemisegments as a distance metric, and linkage was calculated using the average synapse similarity. For comparing the distributions across individual axes, a two sample Kolmogorov-Smirnov test was used to determine significance.Synapse spatial distributions were generated using custom MATLAB scripts, which are deposited at GitHub . Spatialhttps://seaborn.pydata.org/generated/seaborn.clustermap.html). For https://seaborn.pydata.org/generated/seaborn.distplot.html).Weighted PMNs to MNs connectivity matrix was acquired from CATMAID TEM volume as percentage of total number of postsynaptic links to these target MNs. We then calculated the average of left and right pairs of PMNs and MNs. Next, we summed the mean connections from PMNs to all MNs innervating muscle groups defined in 2% melted agarose was used to make pads with similar size: 25 mm (W) X 50 mm (L) X 2 mm (H). Using tungsten wire, a shallow ditch was made on agarose pads to accommodate the larva. To do muscle ratiometric calcium imaging in intact animals, a first or second instar larvae expressing GCaMP6f and mCherry in body wall muscles were washed with distilled water, then moved into a 2% agarose pad on the slide. A 22 mm ×40 mm cover glass was put on the larva and pressed gently to gently constrain larval locomotion. The larva was mounted dorsolaterally or ventrolaterally to image a different set of muscles  whereas the ventrolateral mount excludes the dorsal-most muscles ; imaging was done with a 10x objective on an upright Zeiss LSM800 microscope. We recorded a total of 38 waves (24 forward and 14 backward) from four different animals, and examined muscle calcium activity in two subsequent hemi-segments for each wave. Muscle length measurement was done using custom MATLAB scripts where muscle length was measured on a frame by frame basis. Calcium imaging data were also analyzed using custom MATLAB scripts. Due to movement artifacts, ROIs were updated on a frame by frame basis to track the muscle movement. ROIs that crossed other muscles during contraction were discarded. In no single preparation was it possible to obtain calcium traces for all 30 muscles. Instead, we used only preparations in which at least 40% of the muscles could be recorded. In order to align crawl cycles that were of variable time and muscle composition, we first produced a two dimensional representation of each crawl cycle using PCA. Crawl cycles were represented as circular trajectories away from, and back towards the origin  similar https://imagej.net/fiji) and GCaMP6m and jRCaMP1b channels were separated. The ΔF/F0 of each ROI was calculated as (F-F0)/F0, where F0 was averaged over ~1 s immediately before the start of the forward or backward waves in each ROI.For dual-color and single-color calcium imaging in fictive preps, freshly dissected brains were mounted on 12 mm round Poly-D-Lysine Coverslips (Corning BioCoat) in HL3.1 saline , which wFor PMNs that we could identify using Gal4 lines, we crossed the Gal4 line to UAS-Cherry and used Chat:GFP to detect cholinergic neurons , anti-GAhttps://imagej.net/Fiji), Photoshop, and Illustrator . Brightness and contrast adjustments were applied to the entire image uniformly; mosaic images were assembled in Photoshop .Standard confocal microscopy, immunocytochemistry and MCFO methods were performed as previously described for larvae . PrimaryWe constructed a recurrent network representing the activity of PMNs, which we denote by the vector MNs follow similar dynamics:To generate PMNs and MNs corresponding to the A2 segment, we duplicated the A1 MNs and the PMNs we reconstructed for which no corresponding neuron in the next anterior segment was reconstructed. This produces a connectivity matrix with an approximate block structure:The model parameters .The total cost, equal to  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Drosophila larval locomotion. The authors examine muscle recruitment during forward and backward crawling and identify specific muscles that show differential activation timing between forward and backward crawling. Examining the connectivity between MNs and PMNs with synaptic resolution reveals evidence for both a "labelled line" as well as "combinatorial code" type PMN-MN network. This represents a significant advance in our understanding of directional control of locomotion.This work provides an extensive and comprehensive analysis of premotor interneurons (PMNs), motor neurons (MNs) and muscles governing Decision letter after peer review:Drosophila" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Ronald Calabrese as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "A multilayer circuit architecture for the generation of distinct locomotor behaviors in The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:Drosophila larva. It can be divided into three parts. The first part describes the muscles involved and their activity during forward and backward locomotion using calcium imaging; the second part utilizes the EM volume of the larval CNS to identify the motor neurons and premotor neurons, and their synaptic connectivity patterns; the third part invokes modeling to simulate how the basic network may function during the two behavioral events. The uniqueness of the paper lies in its comprehensiveness, as all  of the above components are evaluated at a whole segment level. Overall, this study represents a significant advance in our understanding of directional control of locomotion.This manuscript investigates the neural mechanisms by which two distinct aspects of locomotion, forward and backward movements, are brought about in Essential revisions:1) In the first experiment  the authors perform an elegant and comprehensive analysis of muscle activity during forward and backward crawling cycle. This culminates into identification of specific muscles  that are recruited at distinct times in forward versus backward crawling . This finding sets the stage for the rest of the paper for finding a model of how neurons recruit these muscles. Unfortunately, the following sections lack specific references  to these muscles and the reader is left searching for an explanation in dense data figures and supp. Highlighting MNs and PMNs that recruit these specific muscles, in every section is essential for coherence, furthermore a lack of identification of MNs and PMNs to drive differential recruitment of some of these specific muscles, requires an explanation (e.g. VO muscle group).2) In Figure 2-3, the authors suggest co-activation based hierarchical clustering as a better grouping of functional muscle types, compared to previously used "spatial clusters". However with respect to MN postsynaptic sites , a thorough examination  is only performed for spatial clusters. Moreover co-activation based clusters show a weak segregation of postsynaptic MN sites. It would help if there were quantitative analysis of the clusters the authors have used for the remainder of the manuscript.Additionally, authors could perform a comparison between MNs innervating differential recruited muscles and MNs innervating muscles that show identical recruitment during forward and backward crawling. This will inform whether the postsynaptic density could provide any useful information to explain the muscle recruitment.3) The PMN-MN connectivity analysis is impressive in scope (number of neurons traced) and detail (neurotransmitter identities). Although the authors elegantly show potential for both "labelled line" and "combinatorial code" based on this connectivity, it would once more help if authors could highlight whether it is labelled line or combinatorial input that drives MNs for the specific muscles that show differential recruitment timing.4) The authors show a first comprehensive connectivity constrained model of PMN-MN network capable of producing muscle activity patterns observed during crawling forwards and backwards. Although the model is neatly verified by accompanying imaging experiments, it would have been more satisfying if there were fewer constraints on PMN activity, given the authors are anyways optimizing the model to get the muscle activity observed in the imaging data. Specifically, the PMNs that show the most distinct recruitment during forward versus backward crawling (A27h and A18b3) are imposed in the model. It would be interesting to see if the differential A27h and A18b3 activation emerges from connectivity constraints. Furthermore, some speculation regarding how descending neurons might impose the activity patterns on the PMN-MN network will be beneficial. Essential revisions:1) In the first experiment  the authors perform an elegant and comprehensive analysis of muscle activity during forward and backward crawling cycle. This culminates into identification of specific muscles  that are recruited at distinct times in forward versus backward crawling . This finding sets the stage for the rest of the paper for finding a model of how neurons recruit these muscles. Unfortunately, the following sections lack specific references  to these muscles and the reader is left searching for an explanation in dense data figures and supp. Highlighting MNs and PMNs that recruit these specific muscles, in every section is essential for coherence, furthermore a lack of identification of MNs and PMNs to drive differential recruitment of some of these specific muscles, requires an explanation (e.g. VO muscle group).This is an excellent point, with which we fully agree. We now modify Figures 3, 4, 5, 7, and 8 to better highlight the differentially active muscles, MNs and PMNs. In new Figure 3H-I, we add new data on the timing of the differentially-active muscles, and a larger summary as requested below. In new Figure 3—figure supplement 2, we identify the differentially-active muscles by blue/red coloring. In Figure 4, we label the differentially active MNs. In new Figure 5E-H, we characterize neuropil postsynaptic localization for the most differentially-active MNs . In new Figure 7G, we have quantified the connectivity pattern between the 118 PMNs and the differentially-active MNs. Finally, in new Figure 8 we now show the cellular morphology of the differentially active MNs in new panels 8A-E. Thus, we now trace these differentially-active muscles and MNs throughout the paper, which gives a common thread for interpreting each dataset.2) In Figure 2-3, the authors suggest co-activation based hierarchical clustering as a better grouping of functional muscle types, compared to previously used "spatial clusters". However with respect to MN postsynaptic sites , a thorough examination  is only performed for spatial clusters. Moreover co-activation based clusters show a weak segregation of postsynaptic MN sites. It would help if there were quantitative analysis of the clusters the authors have used for the remainder of the manuscript.We have reorganized the panels in Figure 5 and rewrote the result section to make it more reader friendly. We now clearly mention in the text that unbiased hierarchical clustering analysis results in better segregation of spatial clusters than the co-active muscle clusters . Also, we have now done a thorough examination of MN postsynaptic sites for forward (FWD) and backward (BWD) co-active clusters as well as for spatial clusters . We agree with your interpretation and now strengthen our conclusion that MNs innervating spatial muscle groups form a quantitatively better myotopic map compared to MNs innervating co-active muscle groups. See subsection “Co-active motor neurons have dispersed postsynaptic sites within the dorsal neuropil”.Additionally, authors could perform a comparison between MNs innervating differential recruited muscles and MNs innervating muscles that show identical recruitment during forward and backward crawling. This will inform whether the postsynaptic density could provide any useful information to explain the muscle recruitment.Following this helpful suggestion, we have made new panels . We show that three out of four differentially recruited MNs show quantitatively different spatial segregation of postsynaptic sites when compared with MNs that are co-active with them during either forward and backward crawling. However, MN2 is differentially-recruited yet shows no clear segregation of postsynapses within the neuropil compared to other neurons in its FWD or BWD co-active muscle group. Thus, we conclude that distinct postsynaptic localization is not required to establish temporally distinct MN recruitment. See paragraph three of subsection “Co-active motor neurons have dispersed postsynaptic sites within the dorsal neuropil”.3) The PMN-MN connectivity analysis is impressive in scope (number of neurons traced) and detail (neurotransmitter identities). Although the authors elegantly show potential for both "labelled line" and "combinatorial code" based on this connectivity, it would once more help if authors could highlight whether it is labelled line or combinatorial input that drives MNs for the specific muscles that show differential recruitment timing.Thank you for this comment. We have now made a new Figure 7, where we address several questions revolving around "labelled line" vs "combinatorial code" models of connectivity. First, we show that while some PMNs show a “labelled line” connectivity patterns with MNs in a single forward or backward co-active muscle group, the majority of PMNs exhibit connectivity patterns consistent with the "combinatorial code" model . Next, in new Figure 7G, we show that essentially none of the PMNs specifically connect to individual MNs with differential recruitment during forward versus backward locomotion . This also supports the "combinatorial code" model. See paragraph three of subsection “TEM reconstruction of 118 premotor neurons reveals premotor neuron pools targeting each group of co-active motor neurons”.4) The authors show a first comprehensive connectivity constrained model of PMN-MN network capable of producing muscle activity patterns observed during crawling forwards and backwards. Although the model is neatly verified by accompanying imaging experiments, it would have been more satisfying if there were fewer constraints on PMN activity, given the authors are anyways optimizing the model to get the muscle activity observed in the imaging data. Specifically, the PMNs that show the most distinct recruitment during forward versus backward crawling (A27h and A18b3) are imposed in the model. It would be interesting to see if the differential A27h and A18b3 activation emerges from connectivity constraints. Furthermore, some speculation regarding how descending neurons might impose the activity patterns on the PMN-MN network will be beneficial.We agree that inferring the selectivity of the A27h and A18b PMNs from the connectome alone would be compelling. We therefore re-ran our simulations but without a penalty to promote the activity of these neurons to be consistent with what is known. We found that the A27h neuron maintained its selectivity consistent with experiment, but A18b was no longer specifically active during backward locomotion. We interpret this to mean that the PMN-MN connectome is insufficient to capture the selectivity of A18b to backward locomotion, which is consistent with our recent study that showed that it is directly activated by a descending neuron not included in our model . In contrast, our model accurately predicts the FWD-specific activity of A27h, raising the possibility that A27h activity can be generated from the current pool of 118 PMNs without descending input. We have added a description of these results in paragraph two of subsection “A recurrent network model that generates the observed forward and backward pattern of muscle activity” and a new Figure 9—figure supplement 2.


Substantial evidence indicates that β-catenin is a pivotal regulator that contributes to the initiation and development of various types of diseases. Recently, β-catenin can be detected in human serum and also reported to be correlated with several disease progression in a little research. However, very little is known about the relationship between serum β-catenin and HBV-related liver disease.Serum levels of β-catenin, from 77 patients with chronic hepatitis B (CHB), 63 patients with hepatitis B associated liver cirrhosis (HBLC), 61 patients with hepatocellular carcinoma (HCC), 41 healthy HBV carriers (HHCs) and 78 healthy controls (HCs) were measured by ELISA. Correlations of serum β-catenin with viral replication and liver necroinflammation parameters were analyzed. The receiver operating characteristic (ROC) curve was used to assess the discriminating power of serum β-catenin to grade different stages of HBV-related disorders. Human hepatic cell line L02 was transfected with a HBV plasmid, and β-catenin levels and the underlying mechanism were analyzed.Chronic hepatitis B and HBLC patients but not HHC or HCC showed significantly higher serum β-catenin levels than HCs. β-catenin levels were not correlated with HBV DNA levels but were correlated with necroinflammation parameters. HBV-infected cell model showed elevated levels of phosphorylation at Ser473 in Akt (p-Akt), phosphorylation at Ser9 in GSK3β (p-GSK3β) and β-catenin, all of which was blocked by treatment with Akt inhibitor LY294002. Additionally, ROC analysis of β-catenin for discriminating patients with CHB from HHCs, which yielded an AUC of 0.71  with 64.93% sensitivity, 73.17% specificity and 69.05% accuracy. ROC analysis of β-catenin for discriminating patients with HCC from chronic HBV infection mainly including CHB and HBLC, which yielded an AUC of 0.75  with 66.43% sensitivity, 75.41% specificity and 70.92% accuracy.HBV infection enhances β-catenin expression by activating Akt/GSK3β signaling. Serum β-catenin levels are correlated with necroinflammation parameters but not with viral load. Serum β-catenin has potential to discriminate the phase of HBV-related disorders, particularly predicts the patients with CHB from HHCs and also predicting HCC form chronic HBV infection. Hepatitis B virus (HBV) infection is one of the most important infectious diseases in the digestive system, which leads to a wide spectrum of liver disease ranging from acute and chronic hepatitis (CHB), hepatitis B associated liver cirrhosis (HBLC) and hepatocellular carcinoma (HCC). Despite the advent of effective vaccines, as well as other disease control measures, including antiviral therapy, HBV infection is still a serious global health problem . The mecWnt/β-catenin signaling pathway is a cell signal transduction pathway that has been linked to a number of disease conditions, including neurodegenerative diseases, psychiatric diseases, cancers, asthma, and even wound healing . The cenRecently, apart from accumulation of β-catenin expression in cytoplasm or nuclear translocation, β-catenin levels can be detected in human serum and also have been reported to correlate with several disease progression, including hepatitis C-associated hepatocellular carcinoma, type 2 diabetes mellitus, postmenopausal osteoporosis –13. SincSerum samples (n = 320) with HBV-related disorders, healthy HBV carrier and healthy controls were prospectively recruited from the Second Affiliated Hospital of Chongqing Medical University from May 2016 to May 2017. The patients with HBV-related disorders had not received antiviral treatment within 6 months prior to this study’s enrollment. These serum samples were divided into four groups. Group 1  included patients with chronic hepatitis. Group 2  included patients with histological proven hepatitis B associated liver cirrhosis. Group 3  included patients with histological proven HCC. Group 4  included healthy HBV carriers with low replicative (HBV DNA < 2000 IU/mL) and normal ALT. Group 5  included normal healthy subjects with no history of liver disease that were negative for HCV and HBV. The clinicopathological data of the subjects in this study at initial diagnosis were collected, which included gender, age, liver function tests and HBV DNA levels are presented in Table pcDNA3.1-HBV plasmid contain 1.3 or 1.1 fold HBV genome fragment were constructed in our laboratory. The antibodies included anti-β-catenin , anti-glycogen synthase kinase (GSK)-3β, anti-phospho-GSK3β, anti-Akt, anti-phospho-Akt , anti-β-actin  and Horseradish peroxidase-conjugated anti-mouse, anti-rabbit IgG antibodies .2. Transfection of L02 cells with pcDNA3.1-HBV (1.3 or 1.1) or its control pcDNA3.1 was conducted using lipofectamine 2000 (Invitrogen) according to the manufacturer’s recommendation. And the cells were collected after transfection for indicated time for the subsequent experiment.Human hepatic cell line L02 was grown in DMEM  supplemented with 10% heat-inactivated FBS , 100 U/mL penicillin, and 100 U/mL streptomycin. Cell culture was maintained at 37 °C in a humid atmosphere containing 5% COSerum levels of β-catenin were measured by a commercially available enzyme-linked immunosorbent assay by ELISA kit  according to the manufacturer’s instructions.Western blot analysis was applied to detected levels of β-catenin, GSK3β, p-GSK3β (Ser9), Akt, p-Akt (Ser473) and β-actin in cells. Briefly, the cells were collected and washed with ice-cold PBS, then lysed on ice in radio immunoprecipitation assay (RIPA) buffer. Samples containing equal amount of proteins were separated in 10% SDS-PAGE and blotted onto the PVDF membranes. Then the membranes were blocked with 5% bovine serum albumin and incubated with anti-β-catenin, anti-GSK3β, anti-p-GSK3β, anti-Akt, anti-p-Akt and β-actin , followed by incubation with secondary antibodies conjugated with horseradish peroxidase. The proteins of interest were detected using the SuperSignal West Pico Chemiluminescent Substrate kit. The results were recorded by the Bio-Rad Electrophoresis Documentation  and Quantity One Version 4.5.0.The cells were plated and cultured onto cleaned-up cover slips, and were washed with phosphate-buffered saline (PBS) and fixed in 4% paraformaldehyde, then permeabilized with 0.2% Triton X-100. Cover slips were rinsed and incubated with blocking serum for 15 min at 37 °C and then incubated with anti-β-catenin antibody (1:100 dilution) overnight at 4 °C. After three washes with PBS, the cells were stained with the corresponding Alexa fluor 647-conjugated antibody. To visualize nuclei, cells were stained with 10 µg/mL DAPI. The fluorescent images were then observed and analyzed using a multilaser confocal microscope.2O2 in methanol to block endogenous peroxidase. And the sections were incubated with the anti-β-catenin antibody (1:200 dilution), followed by incubation with secondary antibody tagged with the peroxidase enzyme and were visualized with 0.05% DAB until the desired brown reaction product was obtained. All slides were observed under a Nikon E400 Light Microscope and representative photographs were taken.For IHC analysis, the sections from the formalin fixed, paraffin-embedded tissues were deparaffinized and rehydrated. Then the sections were boiled for 10 min in 0.01 M citrate buffer and incubated with 0.3% H6 cells/mL. One hundred microliter of the cell suspension (1 × 105 cells) was mixed with 5 mL of Annexin V-FITC and 5 μL of propidium iodide according to the manufacturer’s instruction. The mixed solution was gently vortexed and incubated in dark at room temperature (25 °C) for 15 min. Four hundred microliter of 1× dilution buffer was then added to each tube and apoptosis analysis was performed by BD FACS Canto™ II flow cytometer.Annexin V-PI staining was also used to evaluate the apoptosis of L02 cells. Annexin V-FITC apoptosis kit were purchased from Becton–Dickinson . The cells were harvested after treatment, washed twice with pre-chilled PBS and resuspended in 1× binding buffer at a concentration of 1 × 104 cells per well. The release of LDH from cells to the culture medium was detected by a LDH Cytotoxicity Assay Kit  to evaluate the cytotoxicity. The LDH release was quantified by measuring the UV absorbance at 490 nm.First of all, cells were transfected with or without plasmids as described above for indicated time in a 6-well plate. After that, the cells were seeded onto a 96-well plate at a density of 1 × 10L02 cells were transfected with pcDNA3.1-HBV (1.3 or 1.1) or pcDNA3.1 for 24 h and then lysed with Trizol . Complementary single-stranded DNA was synthesized from total RNA by reverse transcription . Primers were also synthesized by Invitrogen. PCR primers were as follows: β-catenin primers: (forward) 5′-CTGCAGGGGTCCTCTGTG-3′ and (reverse) 5′-TGCATATGTCGCCACACC-3′; β-actin primers: (forward) 5′-TCCCTGGAGAAGAGCTACGA-3′ and (reverse) 5′-AGCACTGTGTTGGCGTACAG-3′. Reactions were performed in triplicate using SYBR Green master mix  and normalized to GAPDH mRNA level using the ΔΔCt method.The differences in the results of cells were analyzed using one way ANOVA followed by the Student–Newman–Keuls test, and the differences in the results of serum β-catenin levels were performed using Mann–Whitney test. ROC curves were generated to classify patients in different groups, as well as for the evaluation of the diagnostic potential of serum β-catenin via calculation of the area under the ROC curve (AUC), sensitivity and specificity according to standard formulas. All statistical analyses were performed using GraphPad Prism software . Statistical differences are presented at probability levels of p < 0.05, p < 0.01 and p < 0.001.To assess whether serum β-catenin levels are abnormally altered in HBV-relative liver diseases, including CHB, HBLC and HCC, we detected and analyzed its levels in these groups of patients and HCs. CHB and HBLC patients showed significantly higher serum β-catenin levels than HCs Fig. a. While 10 IU/mL), intermediate virus load (≥ 5–7 log10 IU/mL) and low virus load (< 5 log10 IU/mL). We found that average levels of serum β-catenin was not proportional to the increase of serum HBV DNA in CHB patients  and HBV 1.1-fold genome plasmid (pcDNA-HBV1.1) were transfected into human hepatic cell line L02 to establish an HBV-infected hepatic cell model. The protein expression and distribution of β-catenin was analyzed by western blot and immunofluorescence assay, respectively. HBV-infected L02 cells showed an elevated β-catenin expression, which mainly accumulated in the cytoplasm and nucleus Fig. a, b. AddEnhanced β-catenin was found in HBV-infected hepatic cells. We then explore whether elevated protein levels of β-catenin was resulted by its gene levels. No obvious change of gene levels of β-catenin was observed in HBV-infected hepatic cell model Fig. a, suggesWe next evaluated differentiating power of β-catenin for progression of HBV-related liver diseases. The ROC analysis indicated that diagnostic value of serum β-catenin yielded an AUC of 0.71  with 64.93% sensitivity, 73.17% specificity and 69.05% accuracy  serum β-catenin levels correlate with liver necroinflammation and may predict the patients with CHB from HHC and also predict HBV-related HCC form chronic HBV infection (CHB and HBLC) in clinical samples. By using the HBV-infected cell model, we confirm that Akt/GSK3β signaling activation mediates accumulation of β-catenin. Therefore, our data support the notion that serum β-catenin may be a useful tool for assessing HBV-related liver diseases.


Mammalian motor circuits display remarkable cellular diversity with hundreds of motor neuron (MN) subtypes innervating hundreds of different muscles. Extensive research on limb muscle-innervating MNs has begun to elucidate the genetic programs that control animal locomotion. In striking contrast, the molecular mechanisms underlying the development of axial muscle-innervating MNs, which control breathing and spinal alignment, are poorly studied.mEbf1-mEbf4) in spinal MNs and employ genetic approaches in both nematodes and mice to investigate their function in axial MN development.Our previous studies indicated that the function of the Collier/Olf/Ebf (COE) family of transcription factors (TFs) in axial MN development may be conserved from nematodes to simple chordates. Here, we examine the expression pattern of all four mouse COE family members (mEbf1 and mEbf2 are expressed in distinct MN clusters (termed “columns”) that innervate different axial muscles. Mouse Ebf1 is expressed in MNs of the hypaxial motor column (HMC), which is necessary for breathing, while mEbf2 is expressed in MNs of the medial motor column (MMC) that control spinal alignment. Our characterization of Ebf2 knock-out mice uncovered a requirement for Ebf2 in the differentiation program of a subset of MMC MNs and revealed for the first time molecular diversity within MMC neurons. Intriguingly, transgenic expression of mEbf1 or mEbf2 can rescue axial MN differentiation and locomotory defects in nematodes (Caenorhabditis elegans) lacking unc-3, the sole C. elegans ortholog of the COE family, suggesting functional conservation among mEbf1, mEbf2 and nematode UNC-3.We report that Ebf2 in mouse axial MNs. Because human mutations in COE orthologs lead to neurodevelopmental disorders characterized by motor developmental delay, our findings may advance our understanding of these human conditions.These findings support the hypothesis that genetic programs controlling axial MN development are deeply conserved across species, and further advance our understanding of such programs by revealing an essential role for The online version of this article (10.1186/s13064-018-0125-6) contains supplementary material, which is available to authorized users. The mammalian neuromuscular system is essential for distinct motor behaviors ranging from locomotion and dexterity to basic motor functions, such as breathing and maintenance of spinal alignment . The undThe identity of MN subtypes that belong to a specific column, termed “columnar identity”, is defined by combinatorial expression of transiently expressed TFs , 4, 5. FA large body of work on limb-innervating MNs (LMC) demonstrated that combinatorial TF expression is also necessary for further diversification of MNs within the same column, providing evidence for molecular diversity within the LMC column. This molecular diversity of LMC MNs correlates with innervation of distinct muscle groups , 5, 10. Drosophila melanogaster) and nematodes , suggesting that an MMC-like population likely represents the ancestral condition of MNs in bilaterians , vsIs48 [unc-17prom::gfp]. The following rescuing transgenic strains using the MN-specific promoter of unc-3prom (558 bp) were generated: two rescuing transgenic lines  for MN > mEbf1 in the unc-3 (n3435); juIs14 background, two rescuing transgenic lines  for MN > mEbf2 in the unc-3 (n3435); juIs14 background, two rescuing transgenic lines  for MN > mEbf1 in the unc-3 (e151); vsIs48 background, and two rescuing transgenic lines  for MN > mEbf2 in the unc-3 (e151); vsIs48 background.Nematode escribed . Two stris study . Cholineunc-3prom::mEbf1::unc-54 3’UTR construct and the unc-3prom::mEbf2::unc-54 3’UTR construct were generated to contain a 558 bp proximal fragment (immediately upstream of ATG) of the unc-3 promoter amplified from C. elegans wild type (N2) genomic DNA. In addition, each construct contains corresponding mEbf1 or mEbf2 coding sequences amplified from mouse cDNA and fused to C. elegans unc-54 3’UTR. Fragments were assembled through the Gibson Assembly method, which can be found at https://www.neb.com/applications/cloning-and-synthetic-biology/dna-assembly-and-cloning/gibson-assembly. These constructs were injected at 25 ng/μl into both unc-3(n3435); juIs14 [acr-2prom::gfp] and unc-3(e151); vsIs48 [unc-17prom::gfp] mutant strains together with myo-2prom::GFP (co-injection marker results in gfp labeled pharynx) and a carrier plasmid that serves as filler DNA (pBluescript). At least two stable transgenic lines were established for each construct and tested for rescue of the unc-3 mutant phenotypes.The Young-adult nematodes (2 days old) were transferred to an NGM plate containing a droplet (100 μl) of M9 buffer. After 1 min of adaptation, the number of body bends for 30 s was quantified as previously described . A movemCiona intestinalis COE were downloaded from Ensembl Genome Browser. While a single isoform was found for UNC-3, Collier and Ciona COE, several protein isoforms for mouse Ebfs were reported in Ensembl. The longest mEbf1, mEbf2, mEbf3, and mEbf4 isoforms were considered for the generation of the phylogenetic tree shown in Fig. http://phylogeny.lirmm.fr using the “one-click” mode  ) 22], w, wC. eleematodes . To testematodes  and couni) By uncovering an essential role for mEbf2 in the differentiation of MMC neurons, which innervate epaxial muscle and control spinal alignment, and (ii) By revealing that molecular diversity does exist within MMC neurons as Ebf2 is expressed in a significant fraction (~ 40%) of these MNs. Third, our cross-species transgenic rescue experiments provide evidence for functional equivalence between COE orthologs, suggesting that the function of these TFs in the development of axial muscle-innervating MNs is conserved from nematodes to mammals. Altogether, this study indicates that a viable approach for advancing our understanding of axial MN development may lie in comparative studies of the genetic programs that specify invertebrate and vertebrate MNs.While there is a remarkable wealth of developmental studies focusing on limb-muscle innervating MNs, the development of axial muscle-innervating MNs, which control more than half of all skeletal muscles in mammals, has received much less attention . In thisEbf2. The availability of such markers would not only decipher the extent of molecular diversity within the MMC neurons [The requirement of Ebf2 for differentiation of a subset of MMC neurons is reminiscent of previous observations in the cerebellar cortex , 62, whe neurons , but als neurons –66. LastC. elegans, the sole COE ortholog UNC-3 is expressed in post-mitotic MNs that innervate axial muscle [Ciona intestinalis [Zcoe2 appears to also be expressed in axial muscle-innervating MNs [collier/knot is not expressed in body wall-muscle innervating MNs [C. elegans, Ciona intestinalis, zebrafish and mouse MNs use acetylcholine (ACh). It is tempting to speculate that both cholinergic and glutamatergic MNs were present in the common ancestor to all bilaterians, which is thought to have had a fairly complex nervous system and likely used an axial-like locomotor circuit to move [Comparison of the role of COE family TFs in MNs of nematodes, simple chordates, and mice (this study) suggests that COE TFs played an ancient role in axial muscle-innervating MNs. In the nematode l muscle , 25. Thistinalis . Interesting MNs . Here, wting MNs c). It hating MNs , 2. Duriting MNs . Fly MNs to move , 67, 68,C. elegans are required for locomotion, whereas, in mice, HMC and MMC neurons have adopted a more specialized role . To accommodate this functional change, it is conceivable that during evolution modifications have occurred in the molecular programs that specify axial muscle-innervating MNs. In C. elegans axial MNs, UNC-3 is required for axon guidance, ACh biosynthesis, expression of conserved MN-specific TFs , and induction of a large battery of MN identity-defining genes  [C. elegans MNs  , 25. HowMNs Fig. , this abunc-3 function in C. elegans MNs, as assessed by monitoring expression of two MN identity markers (acr-2/AChR and unc-17/VAChT)  Fig. b-c. Quitdes Fig. d, indicades Fig. a. We thebnc-1/BNC, cfi-1/Arid3a) that work together with UNC-3 to determine axial MN differentiation in C. elegans also control aspects of axial MN development in mice [Neuronal control of muscle associated with the central body axis is an ancient and essential function of both invertebrate and vertebrate nervous systems. Here, we provide evidence for an ancient role of the COE family of TFs in axial MN development. In the future, it will be interesting to examine whether other evolutionarily conserved TFs  in Ebf2lacZ/+ spinal cords at e12.5 (N = 3). The position of Ebf2-expressing motor neurons  within the MMC column was analyzed along the medio-lateral axis at three specific rostro-caudal regions of the spinal cord . Below each image, arbitrary units (a. u.) of bGal fluorescence intensity are shown along the medio-lateral axis of the MMC (see Methods). C: Schematic summary of data shown in panel B. At rostral brachial and thoracic regions, Ebf2 positive cells are mainly located at the center of the MMC column, whereas at caudal brachial regions, Ebf2 motor neurons are mainly located medially within the MMC. (PDF 4639 kb)Additional file 2:Figure S1. Additional characterization of Ebf expression in the mouse spinal cord. A: RNA ISH at e13.5 reveals Ebf1, Ebf2 and Ebf3 expression in DRG neurons (red circles). B: Double immunofluorescence staining for bGal (Ebf2 reporter in green) and Lhx3 (MMC marker in red) reveals co-localization (arrows) at a late embryonic stage (e18.5). A representative image is shown from the lumbar region. A subset of Lhx3 positive neurons expresses bGal (Ebf2), which is also the case at earlier (e13.5) stages  revealed co-localization in WT e13.5 spinal cord selectively at thoracic levels, indicating Ebf1 expression in HMC neurons. N = 3. (PDF 2267 kb)