Gene Ontology Function Research Articles

MO242: Intrarenal Single Cell Sequencing of Hepatitis B Virus Associated Membranous Nephropathy

Abstract BACKGROUND AND AIMS The pathogenesis underlying hepatitis B virus (HBV)-associated membranous nephropathy (MN) remains incompletely understood. METHOD To decipher the etiopathogenesis of HBV-associated MN, intrarenal single-cell RNA sequencing (scRNA-seq) was applied to the kidney biopsy from a HBV-associated MN patient and a health control to define the transcriptomic landscape at single-cell resolution. Differentially expressed genes (DEGs) and enrichment analysis were compared between HBV-associated MN and anti-PLA2R positive idiopathic membranous nephropathy (IMN) using intrarenal scRNAseq. RESULTS We generated 4114 intrarenal single-cell transcriptomes from a HBV-associated MN patient by single-cell RNA-sequencing. We found that kidney podocytes cells in the HBV-associated MN patient displayed increased expression of several genes, including EDIL3, GPC6, HSPA5 and CTGF, which were closely related to extracellular matrix formation. Kidney endothelial cells of HBV-associated MN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling, NOD-like receptor signaling, NF-kappa B signaling pathway and Toll-like receptor signaling pathway. TNF signaling pathway and IL-17 signaling pathway activation were confirmed in proximal tubule cells from the HBV-associated MN patient. Moreover, ligand-receptor analysis highlighted the extensive communication of mesangial cells, which infers great importance in HBV-associated MN. Furthermore, gene ontology (GO) function enrichment analysis revealed that DEGs of endothelial cells from the HBV-associated MN patient were enriched in interleukin-6 secretion and interleukin-1 secretion when compared with anti-PLA2R positive IMN. CONCLUSION These results offer new insight into the pathogenesis of HBV-associated MN.

Mechanism of Qingwei Powder in treatment of periodontitis based on UPLC-Q-TOF-MS, GC-MS, network pharmacology and molecular docking

The present study explored the mechanism of Qingwei Powder(QP) in the treatment of periodontitis based on chromatography-mass spectrometry and network pharmacology-molecular docking techniques. UPLC-Q-TOF-MS and GC-MS were used to identify the chemical constituents of QP. The active components and targets were screened out through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), and their targets were predicted using SwissTargetPrediction. Targets related to periodontitis were obtained from GeneCards, OMIM, and DisGeNET. Venn diagram was constructed using Venny 2.1 to obtain the intersection targets. Cytoscape 3.7.2 was used to construct the "chemical component-target-disease" network. The targets were analyzed for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment by clusterProfiler R, and the "chemical component-target-pathway" network was constructed. The binding activity of the active components to the target proteins was verified by molecular docking. A total of 189 chemical components were obtained by UPLC-Q-TOF-MS and GC-MS, including 39 active components with 180 potential targets related to periodontitis. Target enrichment analysis of the active components yielded 92 KEGG pathways. Twenty KEGG pathways, 34 active components, and 99 targets were involved in the "chemical component-target-pathway" network. Molecular docking verified a good binding ability of the key targets to the key compounds. This study preliminarily indicates that QP is effective in treating periodontitis through multiple components, multiple targets, and multiple pathways, which reflects the complex system of Chinese medicine. This study provides the theoretical foundation for the subsequent research on the material basis and key quality attributes of QP.

Identification and validation of a novel prognostic signature based on transcription factors in breast cancer by bioinformatics analysis.

Breast cancer (BRCA) is the leading cause of cancer mortality among women, and it is associated with many tumor suppressors and oncogenes. There is increasing evidence that transcription factors (TFs) play vital roles in human malignancies, but TFs-based biomarkers for BRCA prognosis were still rare and necessary. This study sought to develop and validate a prognostic model based on TFs for BRCA patients. Differentially expressed TFs were screened from 1,109 BRCA and 113 non-tumor samples downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify TFs associated with overall survival (OS) of BRCA, and multivariate Cox regression analysis was performed to establish the optimal risk model. The predictive value of the TF model was established using TCGA database and validated using a Gene Expression Omnibus (GEO) data set (GSE20685). A gene set enrichment analysis was conducted to identify the enriched signaling pathways in high-risk and low-risk BRCA patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the TF target genes were also conducted separately. A total of 394 differentially expressed TFs were screened. A 9-TF prognostic model, comprising PAX7, POU3F2, ZIC2, WT1, ALX4, FOXJ1, SPIB, LEF1 and NFE2, was constructed and validated. Compared to those in the low-risk group, patients in the high-risk group had worse clinical outcomes (P<0.001). The areas under the curve of the prognostic model for 5-year OS were 0.722 in the training cohort and 0.651 in the testing cohort. Additionally, the risk score was an independent prediction indicator for BRCA patients both in the training cohort (HR =1.757, P<0.001) and testing cohort (HR =1.401, P=0.001). It was associated with various cancer signaling pathways. Ultimately, 9 overlapping target genes were predicted by 3 prediction nomograms. The GO and KEGG enrichment analyses of these target genes suggested that the TFs in the model may regulate the activation of some classical tumor signaling pathways to control the progression of BRCA through these target genes. Our study developed and validated a novel prognostic TF model that can effectively predict 5-year OS for BRCA patients.

The Network Pharmacology Study of Dahuang Fuzi Decoction for Treating Incomplete Intestinal Obstruction.

Objective To explore the mechanism of Dahuang Fuzi decoction in the treatment of incomplete intestinal obstruction (IIO) based on network pharmacology and molecular docking. Methods The chemical components of Rhubarb, Aconite, and Asarum were searched by the Traditional Chinese Medicine Systems Pharmacology database, where the possible active components were screened by oral bioavailability and drug likeness as filtering indicators. The relevant targets in the Swiss Target Prediction database were obtained according to the structure of the chemical components confirmed by the PubChem database. Disease targets of IIO were collected using GeneCards and OMIM databases. We obtained the cross-target using VENNY to capture the common targets. PPI analysis was performed on the intersection genes combined with Cytoscape 3.7.2. Gene Ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out by David database. The core targets and active ingredients were molecularly docked through AutoDock Vina software to predict the detailed molecular mechanism of Dahuang Fuzi decoction for treating IIO. Results There are 45 active components in Dahuang Fuzi decoction, with 709 corresponding targets, 538 IIO targets, and 97 common targets, among which kaempferol, deltoin, and eupatin are the main active ingredients. 10 core targets were obtained by protein-protein interaction network analysis. Through GO enrichment analysis, it was found that Dahuang Fuzi decoction may be involved in biological processes such as signal transduction, anti-apoptosis, promotion of gene expression, regulation of cell proliferation, and differentiation. Besides, KEGG pathway analysis revealed that it mainly relates to PI3K-AKT signal pathway and HIF-1 signal pathway, etc. Molecular docking results showed that the active ingredients of Dahuang Fuzi decoction possess a good binding activity with the core targets. Conclusion Dahuang Fuzi decoction may act on target genes such as TNF, IL6, AKT1, VEGFA, SRC, EGFR, and STAT3 through active ingredients such as kaempferol, deltoin, and eupatin to regulate signaling pathways such as PI3K-AKT and HIF-1 and reduce the expression of various inflammatory factors such as TNF-α, IL-6, iNOS, and COX-2 to play a role in the treatment of IIO.

Urolithin A as a Potential Drug for the Treatment of Spinal Cord Injuries: A Mechanistic Study Using Network Pharmacology Approaches.

Objective This research was focused to examine the potential targets, action network, and mechanism of urolithin A (UA) in spinal cord injury (SCI) management exploiting the network pharmacology (NP). Methods We used the SwissTargetPrediction, PharmMapper, and TargetNet databases to obtain UA action targets. We searched the OMIM, GeneCards, CTD, and DrugBank databases to screen selected target genes for SCI treatment. The intersection of target genes between the UA and SCI databases was obtained by constructing Venn diagrams, which led to the identification of common druggable targets for the disease. The relationship network of the targets was built with Cytoscape 3.7.2, and the protein interaction network was analyzed with the STRING platform. The protein-protein interaction (PPI) network can be built on the STRING database. Gene Ontology (GO) function and KEGG pathway analyses of target intersections were completed with the DAVID 6.8 database. We constructed preliminary network targets for actions underlying UA-SCI interactions. Using the AutoDock software, we examined the molecular docking interactions between UA and its target proteins and further verified the mechanism of the action of UA. Results We obtained 318 UA drug targets and 1492 SCI disease targets. We identified a total of 118 common UA-SCI targets. Based on the PPI analysis, we identified MAPK1, SRC, AKT1, HRAS, MAPK8, HSP90AA1, MAPK14, JAK2, ESR1, and NF-κB1 as possible therapeutic targets. Enrichment analysis revealed that the PI3K-AKT, VEGF, and TNF signaling pathways could be critical for the NP analysis. Molecular docking indicated that UA had a strong affinity for docked proteins (binding energy range: −6.3 to −9.3 kcal mol−1). Conclusions We employed an NP approach to validate and predict the underlying mechanisms associated with UA therapy for SCI. An additional purpose of this study was to provide a theoretical basis for further experimental studies on UA's potential in SCI treatment.

Methylsulfonylmethane protects against lethal dose MRSA-induced sepsis through promoting M2 macrophage polarization

BackgroundMulti-drug-resistant bacterial infections, which have become a global threat, lack effective treatments. The discoveries of non-antibiotics with different modes of antibacterial action, such as methylsulfonylmethane (MSM), are a promising new treatment for multi-drug-resistant pathogens. MethodsWe constructed a mouse peritonitis infection model to evaluate the effects of MSM against methicillin-resistant Staphylococcus aureus (MRSA) infection. The time-kill kinetics of MSM against MRSA and the effect of MSM on the integrity of bacterial cell membrane were measured. Viability effects of MSM on THP1 cells were performed by CCK-8 cytotoxicity assay. Systematic inflammatory factor levels of mice were detected using ELISA. The immune response of peritoneal macrophages during MRSA-infection was evaluated using RNA sequencing. Gene Ontology function, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, and correlation analyses were applied to analysis RNA sequencing data. RT-qPCR, western blotting and flow cytometry were performed to analysis the gene and protein expression levels of macrophages. ResultsIn in vitro experiments, MSM did not show significant killing effects on the growth of MRSA directly and did not destroy bacterial membrane integrity. MSM also displayed no significant effects on the proliferative capacity of THP1 cells. However, MSM treatment protected mice against a lethal dose MRSA-infection and decreased systemic inflammation. MSM upregulated metabolic pathway in peritoneal macrophages, especial glycolysis, during MRSA infection. MSM increased the expression of M2 markers (such as Arg1), promoted phosphorylation of STAT3 (which regulates M2 polarization), and decreased the expression of M1 markers in peritoneal macrophages. Additionally, MSM treatment increased the expression of H3K18 lactylation specific target genes, including Arg1. GNE-140, the LDHA-specific inhibitor of glycolysis, blocked the MSM-induced Arg1 expression in this disease model. ConclusionsMSM protects against MRSA infection through immunomodulation. MSM promotes the expression of Arg1 by lactate-H3K18la pathway to control macrophage to M2 polarization; it firstly provides therapeutic potential for drug-resistant infections and sepsis.

Artemisinin Alleviates Intestinal Inflammation and Metabolic Disturbance in Ulcerative Colitis Rats Induced by DSS.

Objective This study is aimed to reveal the possible mechanisms of artemisinin in the treatment of ulcerative colitis (UC) through bioinformatics analysis and experimental verification in UC model rats. Methods Firstly, we searched two microarray data of the Gene Expression Omnibus (GEO) database to explore the differentially expressed genes (DEGs) between UC samples and normal samples. Then, we selected DEGs for gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The acute UC model of rats was established by using 3.5% dextran sulfate sodium (DSS) for 10 days to verify the core pathway. Finally, we evaluated the therapeutic effect of artemisinin at the molecular level and used metabonomics to study the endogenous metabolites in the rat serum. Results We screened in the GEO database and selected two eligible microarray datasets, GSE36807 and GSE9452. We performed GO function and KEGG pathway enrichment analyses of DEGs and found that these DEGs were mainly enriched in the inflammatory response, immune response, and IL-17 and NF-κB signaling pathways. Finally, we verified the IL-17 signaling pathway and key cytokines, and ELISA and immunohistochemical results showed that artemisinin could downregulate the expression of proinflammatory cytokines such as IL-1β and IL-17 in the IL-17 signaling pathway and upregulate the expression of the anti-inflammatory cytokine PPAR-γ. Metabolomics analysis showed that 33 differential metabolites were identified in the artemisinin group (AG) compared to the model group (MG). Differential metabolites were mainly involved in alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies. Conclusion In this study, we found that artemisinin can significantly inhibit the inflammatory response in UC rats and regulate metabolites and related metabolic pathways. This study provides a foundation for further research on the mechanism of artemisinin in the treatment of UC.

M6A Regulator-Mediated RNA Methylation Modification Patterns are Involved in the Pathogenesis and Immune Microenvironment of Depression.

Depression is a genetical disease characterized by neuroinflammatory symptoms and is difficult to diagnose and treat effectively. Recently, modification of N6-methyladenosine (m6A) at the gene level was shown to be closely related to immune regulation. This study was conducted to explore the effect of m6A modifications on the occurrence of depression and composition of the immune microenvironment. We downloaded gene expression profile data of healthy and depressed rats from the Gene Expression Omnibus. We described the overall expression of m6A regulators in animal models of depression and constructed risk and clinical prediction models using training and validation sets. Bioinformatics analysis was performed using gene ontology functions, gene set enrichment analysis, gene set variation analysis, weighted gene co-expression network analysis, and protein-protein interaction networks. We used CIBERSORT to identify immune-infiltrating cells in depression and perform correlation analysis. We then constructed two molecular subtypes of depression and assessed the correlation between the key genes and molecular subtypes. Through differential gene analysis of m6A regulators in depressed rats, we identified seven m6A regulators that were significantly upregulated in depressed rats and successfully constructed a clinical prediction model. Gene Ontology functional annotation showed that the m6A regulators enriched differentially expressed genes in biological processes, such as the regulation of mRNA metabolic processes. Further, 12 hub genes were selected from the protein-protein interaction network. Immune cell infiltration analysis showed that levels of inflammatory cells, such as CD4 T cells, were significantly increased in depressed rats and were significantly correlated with the depression hub genes. Depression was divided into two subtypes, and the correlation between hub genes and these two subtypes was clarified. We described the effect of m6A modification on the pathogenesis of depression, focusing on the role of inflammatory infiltration.

Network Pharmacology-Based Strategy for Exploring the Pharmacological Mechanism of Honeysuckle (Lonicer japonica Thunb.) against Newcastle Disease.

Objective Newcastle disease causes huge economic losses in the global poultry industry. An efficient treatment is needed to deal with the variable immunogenicity of the Newcastle disease virus (NDV). This study utilized network pharmacology to study the potential therapeutic targets of Honeysuckle (Lonicer japonica Thunb.) against Newcastle disease. Methods Venny online analysis was used to analyze the potential overlapping targets of Honeysuckle and Newcastle disease. Hub genes were obtained using the STRING database and Cytoscape 3.8.2 software. Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis using the DAVID online tool were performed on these targets. Results Twenty-five overlapping targets were identified. The PPI network construction results included 23 nodes of 25 genes and 95 edges. It was found that the IL-6 node had the largest degree. STAT1 and IRF1, CASP9, and CASP3 had the same as well as strongest interaction strengths. GO functions, such as “cytokine activity,” had a regulatory effect on NDV. The “Toll-like receptor signaling Pathway” “Nod-like receptor signaling pathway,” “RIG-I-like receptor signaling pathway,” and “Apoptosis,” which were obtained using KEGG analysis, also indicated that these pathways can act on NDV to enhance immune function. Conclusions In this study, the potential targets and mechanisms of action of Honeysuckle against Newcastle disease were explored through network pharmacology, which provided a theoretical basis for the treatment of Newcastle disease and provided new ideas for the development of traditional Chinese medicine for the poultry industry.

Differential gene screening and functional analysis in docetaxel-resistant prostate cancer cell lines*

Abstract Objective Docetaxel-based combination chemotherapy has traditionally been the standard treatment for metastatic castration-resistant prostate cancer (PCa). However, most patients eventually develop resistance to this treatment, which further reduces their survival. This study aimed to determine key molecular genes in docetaxel-resistant PCa cell lines using bioinformatic approaches. Methods The analysis of microarray data GSE33455 (including DU-145/DU-145R and PC-3/PC-3R cell lines) obtained from the Gene Expression Omnibus (GEO) database was performed using GEO2R. Differentially expressed genes (DEGs) of DU-145/DU-145R and PC-3/PC-3R cell lines were selected, and the intersection of DEGs between the two groups was obtained. DEGs were annotated with the Gene Ontology (GO) function and enriched with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway using an online platform (https://cloud.oebiotech.cn/task/detail/array_enrichment/). The online tool Search Tool for the Retrieval of Interacting Genes (https://string-db.org/) was used to obtain the DEG network graph and matrix list, which was imported into Cytoscape 3.6.1 and analyzed using the Molecular Complex Detection plug-in to detect potential functional modules in the network. Results A total of 131 intersection DEGs were identified between non-treated and docetaxel-resistant PCa cell lines. GO functional annotation showed that the main genes involved were present in the plasma membrane and were involved in positive regulation of ubiquitin-protein transferase activity, positive regulation of pseudopodium assembly, centriolar subdistal appendage, and heterophilic cell-cell adhesion via plasma membrane cell adhesion molecules. KEGG pathway enrichment analysis revealed that DEGs were mainly involved in IL-17 signaling pathway, cytokine-cytokine receptor interaction, rheumatoid arthritis, legionellosis, and folate biosynthesis. We identified two distinct hubs of DEGs: (1) CD274, C-X-C motif chemokine ligand (CXCL)1, DExD/H-box helicase 58, CXCL2, CXCL8, colony-stimulating factor 2, C-X-C motif chemokine receptor 4 (CXCR4), CXCL5, and CXCL6 and (2) argininosuccinate lyase, argininosuccinate synthase 1, and asparagine synthetase. Except for the CXCR4 gene that was downregulated, the other 11 genes showed upregulated expression. Conclusion Certain differential genes may be potential targets for predicting and treating metastatic docetaxel-resistant PCa.

OTOP2, Inversely Modulated by miR-3148, Inhibits CRC Cell Migration, Proliferation and Epithelial-Mesenchymal Transition: Evidence from Bioinformatics Data Mining and Experimental Verification.

IntroductionColorectal cancer (CRC) represents one of the most frequent human malignancies with its underlying pathogenesis still unclear. The prevalence of multi-omics in screening biomarkers associated with CRC has largely accelerated our understanding into the pathophysiology of CRC. The present work aimed to mine the Gene Expression Omnibus (GEO) datasets associated with CRC studies and identify potential targets correlated with CRC pathogenesis.MethodsWe screened the DEGs in GSE50760 and GSE104178 and performed functional Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Furthermore, the overlapped DEGs were subjected to functional GO enrichment and KEGG pathway enrichment analysis. The protein–protein interaction (PPI) network and miRNA-mRNA network were constructed based on the overlapped DEGs. The in vitro functional assays including qRT-PCR, caspase-3 and -9 activity assay, wound healing assay, CCK-8 assay and luciferase reporter assay were performed to determine the role of OTOP2/miR-3148 axis in regulating CRC cell progression.ResultsFifty-three overlapped genes were screened over GSE50760 and GSE104178 and ten hub genes were identified by PPI network analysis. Expression levels of GCG, SST, NPY, GUCA2B, PYY, UCN3, GUCA2A, TMEM82 and BEST4 were not correlated with the overall survival of patients with CRC. However, the high expression of otopetrin 2 (OTOP2) in the CRC tissues was significantly correlated with better overall survival of patients with CRC. The expression of OTOP2 in CRC tissues was significantly lowever than that in normal ones. The in vitro functional assays demonstrated that OTOP2 silence reduced caspase-3/-9 activities, promoted cell migration, proliferation and epithelial–mesenchymal transition in HT29 and SW620 cells. Furthermore, miR-3148 could inversely regulate OTOP2 expression in CRC cell lines.ConclusionCollectively, the work suggested the potential role of the OTOP2/miR-3148 axis in the pathophysiology of CRC by mining the GEO database.

The Systematic Analysis of Exercise Mechanism in Human Diseases

Background As a part of a healthy lifestyle, exercise has been proven to be beneficial for the treatment of diseases and the prognosis of patients. Based on this, our research focuses on the impact of exercise on human health. Methods To study and analyze the samples in the GSE18966 gene expression profile, we first performed an analysis on the differential expressed genes (DEGs) through GEO2R, and then the DEGs enrichment in Gene Ontology functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways through the Database for Annotation, Visualization and Integrated Discovery database was conducted. Then, we delved into the gene set enrichment in KEGG through gene set enrichment analysis. After that, we achieved the construction of the protein-protein interaction (PPI) network of DEGs based on the Search Tool for the Retrieval of Interacting Genes online database, and the hub genes were screened and identified. Results We identified 433 upregulated DEGs and 186 downregulated DEGs from the samples before and after exercise in GSE18966. Through analysis, it was found that these DEGs-enriched pathways, such as the VEGF signaling pathway, the Wnt signaling pathway, and the insulin signaling pathway, were all involved in the regulation of various diseases. Then, GSEA analysis revealed that glycosaminoglycan biosynthesis chondroitin sulfate, type II diabetes mellitus, and basal cell carcinoma were related with exercise samples. The effects of these pathways on various diseases could be improved through exercise. Finally, 3 upregulated hub genes (VEGFA, POMC, and NRAS) and 3 downregulated hub genes (HRAS, NCOR1, and CAV1) were identified through the PPI network. Conclusions The bioinformatic analysis of samples before and after exercise provides key pathways and genes related to exercise to regulate various diseases, which confirms that exercise has an important influence on the treatment of many diseases.

The Anticancer Mechanisms of Scutellaria barbata against Lung Squamous Cell Carcinoma

Objective. Scutellaria barbata (S. barbata) is a Chinese traditional medicinal crop with anti-inflammatory as well as anticancer properties. To explore the anticancer mechanisms of functional monomers of S. barbata against lung squamous cell carcinoma (LUSC), a network pharmacology approach and molecular docking were utilized. Methods. The expression profile of genes encoding functional monomer components in S. barbata was obtained from the Traditional Chinese Medicine Systems Pharmacology platform (TCMSP) database. Expression data of LUSC-related genes were acquired from DisGeNET, GeneCards, OMIM, DrugBank, and TTD databases. The target genes of S. barbata that confer anticancer effects against LUSC were obtained by considering the intersecting genes between S. barbata target genes and LUSC-related genes. The potential regulatory pathways enriched in these intersected genes were identified using the KOBAS database, and Gene Ontology (GO) function enrichment analysis was performed using the online tool DAVID. The relationship network of S. barbata functional monomer components-action targets-disease-pathways was established using Cytoscape 3.8.2, and the protein-protein interaction network of those intersected genes was established using the STRING database. Finally, the hub genes were screened by using CytoNCA, a plug-in of Cytoscape, and hub gene expressions in LUSC were evaluated via the Gene Expression Profiling Interactive Analysis (GEPIA) database. AutoDockTools and PyMOL software were employed to verify the molecular docking on disease target proteins and drug functional molecules. Results. In S. barbata, 104 target genes and 20 hub genes encoding functional components against LUSC were screened out, six of which were significantly differentially expressed between LUSC samples and normal tissue samples in the GEPIA database. Here, GO analysis illustrated the involvement of these genes in the signal transduction and positive regulation of transcription from RNA polymerase II promoter and negative regulation of apoptosis, while KEGG pathway enrichment analysis demonstrated that these genes were mainly involved in several pathways, for instance, AGE-RAGE, PI3K-Akt, p53, and MAPK signaling pathway. There are four main functional components docking with six key target proteins, all of which have strong binding activity. Conclusions. We predicted the molecular mechanisms and signaling pathways of genes encoding functional components in S. barbata against LUSC. These discoveries offer novel understanding for further study, laying a scientific foundation for the production of synthetic monomer components of S. barbata.

Research Highlights

Research Highlights

Long non-coding RNAs in Sus scrofa ileum under starvation stress.

ObjectiveIn this study, we aimed to identify long non-coding RNAs (lncRNAs) that play important roles in starvation stress, analyze their functions, and discover potential molecular targets to alleviate starvation stress to provide a theoretical reference for subsequent in-depth research.MethodsWe generated a piglet starvation stress animal model. Nine Yorkshire weaned piglets were randomly divided into a long-term starvation stress group (starved for 72 h), short-term starvation stress group (starved for 48 h), and the control group. LncRNA libraries were constructed using high-throughput sequencing of piglet ileums.ResultsWe obtained 11,792 lncRNAs, among which, 2,500 lncRNAs were novel. In total, 509 differentially expressed (DE)lncRNAs were identified in this study. Target genes of DElncRNAs were predicted via cis and trans interactions, and functional and pathway analyses were performed. Gene ontology functions and Kyoto encyclopedia of genes and genomes analysis revealed that lncRNA-targeted genes mainly participated in metabolic pathways, cellular processes, immune system processes, digestive systems, and transport activities. To reveal the mechanism underlying starvation stress, the interaction network between lncRNAs and their targets was constructed based on 26 DElncRNAs and 72 DEmRNAs. We performed an interaction network analysis of 121 DElncRNA–DEmRNA pairs with a Pearson correlation coefficient greater than 0.99.ConclusionWe found that MSTRG.19894.13, MSTRG.16726.3, and MSTRG.12176.1 might play important roles in starvation stress. This study not only generated a library of enriched lncRNAs in piglets, but its outcomes also provide a strong foundation to screen key lncRNAs involved in starvation stress and a reference for subsequent in-depth research.

Mechanism of the Salvia miltiorrhiza-Codonopsis pilosula drug pair in the treatment of premature ovarian failure based on network pharmacology-molecular docking

Abstract Objective: Premature ovarian failure (POF) is a disease characterized by irregular menstruation and results in infertility which markedly affects the reproductive health of women. The Salvia miltiorrhiza-Codonopsis pilosula drug pair is effective at treating POF; however, knowledge of the mechanisms of S. miltiorrhiza-C. pilosula in the treatment of POF is lacking. Thus, we carried out network pharmacology and molecular docking to clarify the mechanisms of this drug pair. Methods: The core components and targets of S. miltiorrhiza-C. pilosula were obtained using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database and UniProt database, and the disease targets related to POF were searched using different tools to obtain the overlapping target genes of S. miltiorrhiza and C. pilosula. A protein interaction network of the intersection target was constructed using STRING database, and the network of “traditional Chinese medicine-active ingredient-intersection target-disease” and “pathways-targets” was constructed using Cytoscape 3.8.0. The DAVID online tool was also used to determine the gene ontology functions and Kyoto Encyclopedia of Genes and Genomes pathways associated with the intersection target genes. Finally, the binding ability of the drug to the active components and potential targets were predicted using molecular docking. Results: S. miltiorrhizae-C. pilosula had 72 active components, 128 targets, 3,775 POF targets, and 106 common targets. The potential targets were mainly related to the biological processes of DNA-binding transcription factor binding, RNA polymerase II-specific DNA-binding transcription factor binding, transcription factor activity, steroid receptor activity, and hypoxia response. Further, the Kyoto Encyclopedia of Genes and Genomes enrichment pathways included PI3K-Akt signaling pathway, apoptosis, interleukin (IL)-17 signaling pathway, relaxin signaling pathway, and other biological pathways. Conclusion(s): S. miltiorrhiza-C. pilosula can inhibit ovarian granulosa cell apoptosis and improve ovarian hemodynamics through multiple targets and multiple pathways and help treat POF.

A Systematic Review of Candidate Genes for Major Depression.

Background and Objectives: The aim of this systematic review was to analyse which candidate genes were examined in genetic association studies and their association with major depressive disorder (MDD). Materials and Methods: We searched PUBMED for relevant studies published between 1 July 2012 and 31 March 2019, using combinations of keywords: “major depressive disorder” OR “major depression” AND “gene candidate”, “major depressive disorder” OR “major depression” AND “polymorphism”. Synthesis focused on assessing the likelihood of bias and investigating factors that may explain differences between the results of studies. For selected gene list after literature overview, functional enrichment analysis and gene ontology term enrichment analysis were conducted. Results: 141 studies were included in the qualitative review of gene association studies focusing on MDD. 86 studies declared significant results (p < 0.05) for 172 SNPs in 85 genes. The 13 SNPs associations were confirmed by at least two studies. The 18 genetic polymorphism associations were confirmed in both the previous and this systematic analysis by at least one study. The majority of the studies (68.79 %) did not use or describe power analysis, which may have had an impact over the significance of their results. Almost a third of studies (N = 54) were conducted in Chinese Han population. Conclusion: Unfortunately, there is still insufficient data on the links between genes and depression. Despite the reported genetic associations, most studies were lacking in statistical power analysis, research samples were small, and most gene polymorphisms have been confirmed in only one study. Further genetic research with larger research samples is needed to discern whether the relationship is random or causal. Summations: This systematic review had summarized all reported genetic associations and has highlighted the genetic associations that have been replicated. Limitations: Unfortunately, most gene polymorphisms have been confirmed only once, so further studies are warranted for replicating these genetic associations. In addition, most studies included a small number of MDD cases that could be indicative for false positive. Considering that polymorphism loci and associations with MDD is also vastly dependent on interpersonal variation, extensive studies of gene interaction pathways could provide more answers to the complexity of MDD.

Bell’s Palsy May Associate with Increased IL1R1: A Pilot Novel Gene and lncRNA Study

Background: Bell’s palsy is a widespread disease of the peripheral nervous system which causes not only physical disorders but also mental suffering as well. However, the etiological factor of Bell’s palsy is still unclear. The present study aimed to search for potential influencing factors by identifying the key genes and long non-coding RNAs (lncRNAs) involved in patients with Bell’s palsy using RNA-Seq data based on bioinformatics tools. Methods: Differentially expressed genes (DEGs) and differentially expressed lncRNAs (DELs) in patients before and after therapy, and that in normal control group were identified. The competing endogenous RNAs (ceRNAs) regulatory network was constructed by integrating lncRNA-mRNA pairs, miRNA-mRNA regulatory pairs, and miRNA-lncRNA pairs using Cytoscape. The Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses of DEGs and DELs were evaluated to explore their functions. The targeted corresponding genes and pathogens were verified by ELISA and q-PCR. Results: In the present study, hub proteins such as CXCR2 and IL1R1 in PPI network and 1039 lncRNA-mRNA co-expression pairs (eg., CYYR1-AS1-MDM2) were identified. 739 miRNA-mRNA pairs (eg., hsa-miR-147a-IL1R1), 255 miRNA-lncRNA pairs, and 363 mRNA-lncRNA co-expression pairs were included in ceRNA regulatory network. Meanwhile, CYYR1-AS1 was enriched into most pathways, including Epstein-Barr virus (EBV) infection. Subsequently, validation of neuroinflammation relevant IL1R1 and EBV showed that IL1R1 was upregulated in the serum of patients with Bell’s palsy before therapy, while EBV was not found among them. Conclusion: We hypothesized that etiological factor of Bell's palsy correlate to complex miRNA-lncRNA-mRNA interacting networks and IL1 might be involved in inflammation and immune regulation in the onset of Bell's palsy.

Transcriptome Analysis of the Kidney of Obscure Puffer, Takifugu obscurus, Challenged with Poly(I:C).

Obscure puffer, Takifugu obscurus, is an important aquaculture species in China, but the disease problem of this species seriously affects its production and causes huge economic losses. In order to reveal the molecular mechanism of disease resistance, polyinosinic-polycytidylic acid [poly(I:C)] was used to stimulate obscure puffer. At 0, 12, and 48 h (named To0, To12, and To48) after poly(I:C) challenge, the kidneys from obscure puffer were collected for transcriptome sequencing. A total of 54,816 transcripts was generated. Pairwise comparison of the sequencing libraries of tissue samples at these three time points revealed that the number of differentially expressed genes (DEGs) at To12 vs To0, To48 vs To0, and To48 vs To12 were 2039, 776, and 2579, respectively. Gene Ontology (GO) function classification analysis revealed that some DEGs were annotated to GO items for membrane, biological process, molecular function, and metabolic process. Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis of DEGs demonstrated that they mainly presented in immune-related pathways, such as Toll-like receptor signaling pathway, Retinoic acid-inducible gene-I-like receptor signaling pathway and NOD-like receptor signaling pathway. Then, eight genes were randomly selected from immune-related genes for real-time quantitative reverse transcription PCR verification (RT-qPCR), and 22 key immune DEGs were used to construct network functions. This study has obtained a large number of information resources about the transcriptome of obscure puffer, which can provide references for further research on the anti-virus response of obscure puffer.

A Network Pharmacology Study on the Active Components and Targets of the Radix Ginseng and Radix Bupleuri Herb Pair for Treating Nonalcoholic Fatty Liver Disease.

Objective To explore the potential active components and corresponding target herb pairs of Radix Ginseng (Renshen) and Radix Bupleuri (Chaihu) in the treatment of nonalcoholic fatty liver disease (NAFLD) through network pharmacology and in vitro experiments. Methods The active components and potential targets of the herb pair of Renshen and Chaihu were screened through a network database system, and Venn analysis was performed with the obtained NAFLD targets. The intersecting targets were analysed for gene ontology (GO) functions and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways, and a protein-protein interaction (PPI) network was generated. Cytoscape software was used to construct active component-target networks of the Renshen and Chaihu herb pair. Free fatty acids were added to the HepG2 cell line to create high-fat models that were treated with different concentrations of stigmasterol. The effect of stigmasterol on the lipid metabolism in HepG2 cells and PPARγ-knockdown cells was determined by oil red O staining, Nile red staining, and TG level. PPARγ and UCP-1 mRNA, and protein expression levels were detected by qRT-PCR and Western blot analyses, respectively. Results Twenty active components obtained from the Renshen and Chaihu herb pair were identified. The herb pair active component-target network showed that both Renshen and Chaihu contained stigmasterol and kaempferol as active components. The PPI network comprised 63 protein nodes. GO enrichment analysis and KEGG pathway enrichment analysis showed that the targets were mainly involved in lipid metabolism. Eight core targets were identified: AKT1, PPARG, MAPK3, TNF, TP53, SIRT1, STAT3, and PPARA. In vitro experiments demonstrated that stigmasterol reduced lipid accumulation and TG levels in HepG2 cells, and the mechanism may have been related to the activation of the PPARγ-UCP-1 signalling pathway. Conclusion This study preliminarily illustrated the potential components and corresponding core targets of the Renshen and Chaihu herb pair in treating NAFLD. The effect of stigmasterol on the PPARγ-UCP-1 signalling pathway in enhancing lipid metabolism may represent one of the mechanisms of the Renshen and Chaihu herb pair in the treatment of NAFLD. The results provide new evidence and research insights to reveal the roles of Renshen and Chaihu in the management of NAFLD.