Kyoto Encyclopedia Of Genes And Genomes Pathway Analysis Research Articles

LncRNA-miRNA-mRNA Network Analysis Reveals the Potential Biomarkers in Crohn's Disease Rats Treated with Herb-Partitioned Moxibustion.

BackgroundLong noncoding RNA (lncRNA) is receiving growing attention in Crohn’s disease (CD). However, the mechanism by which herb-partitioned moxibustion (HPM) regulates the expression and functions of lncRNAs in CD rats is still unclear. The aim of our study is to identify lncRNA-miRNA-mRNA network potential biological functions in CD.MethodsRNA sequencing and microRNA (miRNA) sequencing were carried out to analyze lncRNA, miRNA and mRNA expression profiles among the CD rats, normal control rats, and CD rats after HPM treatment and constructed the potential related lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein–protein interaction (PPI) analysis and quantitative real-time polymerase chain reaction (qRT-PCR) were performed to explore potentially important genes in ceRNA networks.ResultsA total of 189 lncRNAs, 32 miRNAs and 463 mRNAs were determined as differentially expressed (DE) genes in CD rats compared to normal control rats, and 161 lncRNAs, 12 miRNAs and 130 mRNAs were identified as remarkably DE genes in CD rats after HPM treatment compared to CD rats. GO analysis indicated that the target genes were most enriched in cAMP and in KEGG pathway analysis the main pathways included adipocytokine, PPAR, AMPK, FoxO and PI3K-Akt signaling pathway. Finally, qRT-PCR results confirmed that lncRNA LOC102550026 sponged miRNA-34c-5p to regulate the intestinal immune inflammatory response by targeting Pck1.ConclusionBy constructing a ceRNA network with lncRNA-miRNA-mRNA, PCR verification, and KEGG analysis, we revealed that LOC102550026/miRNA-34c-5p/Pck1 axis and adipocytokine, PPAR, AMPK, FoxO, and PI3K-Akt signaling pathways might regulate the intestinal immune-inflammatory response, and HPM may regulate the lncRNA LOC102550026/miR-34c-5p/Pck1 axis and adipocytokine, PPAR, AMPK, FoxO, and PI3K-Akt signaling pathways, thus improving intestinal inflammation in CD. These findings may be novel potential targets in CD.

Blood Bacterial 16S rRNA Gene Alterations in Women With Polycystic Ovary Syndrome

BackgroundEvidence proved the association between gut microbiome dysbiosis and polycystic ovary syndrome (PCOS) in metabolic disorder, decreased fertility, and hyperandrogenism. However, alterations in blood microbiome of PCOS remained unknown.ObjectiveThis study aims to measure the blood microbiome profile of PCOS patients compared with healthy controls by 16S rRNA sequencing and to investigate its association with PCOS.MethodsIn this case–control study, bacterial DNA in blood of 24 PCOS patients and 24 healthy controls was investigated by 16S rRNA gene sequencing using the MiSeq technology. Alpha and beta diversity were used to analyze within-sample biodiversity and similarity of one group to another, respectively. Linear discriminant analysis effect size (LEfSe) was calculated to determine biomarkers between groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional prediction was performed at genera level.ResultAlpha diversity of blood microbiome decreased significantly in women with PCOS, and beta diversity analysis demonstrated a major separation between the two groups. In the PCOS group, the relative abundance of Proteobacteria, Firmicutes, and Bacteroidetes decreased significantly, while Actinobacteria increased significantly. Cladogram demonstrated the microbiome differences between the two groups at various phylogenic levels. Meanwhile, linear discriminant analysis (LDA) presented significant decreases in Burkholderiaceae, Lachnospiraceae, Bacteroidaceae, Ruminococcaceae, and S24-7 and significant increases in Nocardioidaceae and Oxalobacteraceae of the PCOS group. KEGG pathway analysis at genera level suggested that 14 pathways had significant differences between the two groups.ConclusionOur findings demonstrated that blood microbiome had a significantly lower alpha diversity, different beta diversity, and significant taxonomic variations in PCOS patients compared with healthy controls.

Comprehensive bioinformatics analysis reveals the hub genes and pathways associated with multiple myeloma

ABSTRACT Purpose While the prognosis of multiple myeloma (MM) has significantly improved over the last decade because of new treatment options, it remains incurable. Aetiological explanations and biological targets based on genomics may provide additional help for rational disease intervention. Materials and Methods Three microarray datasets associated with MM were downloaded from the Gene Expression Omnibus (GEO) database. GSE125364 and GSE39754 were used as the training set, and GSE13591 was used as the verification set. The differentially expressed genes (DEGs) were obtained from the training set, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to annotate their functions. The hub genes were derived from the combined results of a protein–protein interaction (PPI) network and weighted gene coexpression network analysis (WGCNA). The receiver operating characteristic (ROC) curves of hub genes were plotted to evaluate their clinical diagnostic value. Biological processes and signaling pathways associated with hub genes were explained by gene set enrichment analysis (GSEA). Results A total of 1759 DEGs were identified. GO and KEGG pathway analyses suggested that the DEGs were related to the process of protein metabolism. RPN1, SEC61A1, SPCS1, SRPR, SRPRB, SSR1 and TRAM1 were proven to have clinical diagnostic value for MM. The GSEA results suggested that the hub genes were widely involved in the N-glycan biosynthesis pathway. Conclusion The hub genes identified in this study can partially explain the potential molecular mechanisms of MM and serve as candidate biomarkers for disease diagnosis.

Identifying absorbable bioactive constituents of Yupingfeng Powder acting on COVID-19 through integration of UPLC-Q/TOF-MS and network pharmacology analysis

ObjectiveYupingfeng Powder (YPF), a kind of preventative patent medicine, is chosen for treatment of coronavirus disease 2019 (COVID-19) due to its high frequency application in respiratory tract diseases, such as chronic obstructive pulmonary disease, asthma, respiratory tract infections, and pneumonia, with the advantage of reducing the relapse rate and the severity. However, the active components of YPF and the mechanisms of components affecting COVID-19 are unclear. This study aimed to determine active constituents and elucidate its potential mechanisms. MethodsUltra performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q/TOF-MS) and liquid chromatography-triple quadrupole mass spectrometry (LC-QQQ-MS) were used to determine the components and absorbable constituents of YPF. Secondly, TCMSP, Drugbank, Swiss and PharmMapper were used to search the targets of absorbable bioactive constituents of YPF, and the targets of COVID-19 were identified based on GeneCards and OMIM databases. STRING database was used to filter the possible inter-protein interactions. Thirdly, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were performed to identify molecular function and systemic involvement of target genes. ResultsA total of 61 components of YPF and 36 absorbable constituents were identified through UPLC-Q/TOF-MS. Wogonin, prim-O-glucosylcimifugin, 5-O-methylvisamminol, astragaloside IV and 5-O-methylvisamminol (hydroxylation) were vital constituents for the treatment of COVID-19, and RELA, TNF, IL-6, MAPK14 and MAPK8ere recognized as key targets of YPF. The major metabolic reactions of the absorbed constituents of YPF were demethylation, hydroxylation, sulfation and glucuronidation. GO and KEGG pathway analysis further showed that the most important functions of YPF were T cell activation, response to molecule of bacterial origin, cytokine receptor binding, receptor ligand activity, cytokine activity, IL-17 signaling pathway, Chagas disease, lipid and atherosclerosis, etc. ConclusionThe approach of combining UPLC-Q/TOF-MS with network pharmacology is an effective tool to identify potentially bioactive constituents of YPF and its key targets on treatment of COVID-19.

Identification of Key Signaling Pathways and Genes in Eosinophilic Asthma and Neutrophilic Asthma by Weighted Gene Co-Expression Network Analysis.

Background: Asthma is a heterogeneous disease with different subtypes including eosinophilic asthma (EA) and neutrophilic asthma (NA). However, the mechanisms underlying the difference between the two subtypes are not fully understood. Methods: Microarray datasets (GSE45111 and GSE137268) were acquired from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in induced sputum between EA (n = 24) and NA (n = 15) were identified by “Limma” package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and Gene set enrichment analysis (GSEA) were used to explore potential signaling pathways. Weighted gene co-expression network analysis (WGCNA) were performed to identify the key genes that were strongly associated with EA and NA. Results: A total of 282 DEGs were identified in induced sputum of NA patients compared with EA patients. In GO and KEGG pathway analyses, DEGs were enriched in positive regulation of cytokine production, and cytokine-cytokine receptor interaction. The results of GSEA showed that ribosome, Parkinson’s disease, and oxidative phosphorylation were positively correlated with EA while toll-like receptor signaling pathway, primary immunodeficiency, and NOD-like receptor signaling pathway were positively correlated with NA. Using WGCNA analysis, we identified a set of genes significantly associated NA including IRFG, IRF1, STAT1, IFIH1, IFIT3, GBP1, GBP5, IFIT2, CXCL9, and CXCL11. Conclusion: We identified potential signaling pathways and key genes involved in the pathogenesis of the asthma subsets, especially in neutrophilic asthma.

Mechanism underlying the effect of Liujunzi decoction on advanced-stage non-small cell lung cancer in patients after first-line chemotherapy.

To further clarify the anticancer mechanisms of Liujunzi decoction and provide possible targets for the treatment of advanced-stage nonsmall cell lung cancer (NSCLC) by re-analyzing differential gene expression profile of peripheral blood mononuclear cells (PBMCs) from Liujunzi decoctiontreated NSCLC patients receiving first-line chemotherapy. The PBMC gene expression microarray data set GSE61926 was retrieved from a high throughput gene expression database. Differentially expressed genes (DEGs) were screened by paired sample t-test and the multiple ratio method. Gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed using the DAVID database. The protein-protein interaction (PPI) network was constructed using interaction gene library retrieval tools and Cytoscape software. A total of 162 DEGs were identified, with 67 upregulated genes and 95 downregulated genes. The functional distribution of Gene Oncology (GO) genes showed that DEGs were mostly concentrated in extracellular regions, calcium ion binding, and transcriptase activity. KEGG pathway analysis showed that cytokine-cytokine receptor interactions were significantly enriched. PPI network analysis screened out the top 10 central protein-coding genes with the highest nodal degree: IL2, PIWIL4, DICER1, PIWIL2, SAA1, XCL1, IL22RA1, ARHGAP11A, DCP1A, and GDNF. Among them, the central protein-coding gene with the highest node degree was IL2. In addition, the central protein-coding genes with high node degrees and high molecular complex detection (MCODE) scores were PIWIL4, DICER1, PIWIL2, and DCP1A, all of which are related to tumor development. One signaling pathway and 10 central protein-coding genes related to anticancer mechanisms were screened by re-analysis of GSE61926 data. IL2, PIWIL4, DICER1, PIWIL2, and DCP1A may have important roles in the mechanism of Liujunzi decoction treatment against NSCLC. Our results suggest that the anticancer mechanism of Liujunzi decoction may be related to gene silencing by RNA and the biological processes of piwi-interacting RNA and other small RNAs.

Network Pharmacology- and Molecular Docking-Based Identification of Potential Phytocompounds from Argyreia capitiformis in the Treatment of Inflammation.

The methanolic extract of Argyreia capitiformis stem was examined for anti-inflammatory activities following network pharmacology analysis and molecular docking study. Based on gas chromatography-mass spectrometry (GC-MS) analysis, 49 compounds were identified from the methanolic extract of A. capitiformis stem. A network pharmacology analysis was conducted against the identified compounds, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology analysis of biological processes and molecular functions were performed. Six proteins (IL1R1, IRAK4, MYD88, TIRAP, TLR4, and TRAF6) were identified from the KEGG pathway analysis and subjected to molecular docking study. Additionally, six best ligand efficiency compounds and positive control (aspirin) from each protein were evaluated for their stability using the molecular dynamics simulation study. Our study suggested that IL1R1, IRAK4, MYD88, TIRAP, TLR4, and TRAF6 proteins may be targeted by compounds in the methanolic extract of A. capitiformis stem to provide anti-inflammatory effects.

Exosomal lncRNA and mRNA profiles in polycystic ovary syndrome: bioinformatic analysis reveals disease-related networks

Research questionWhat is the role of exosomal lncRNAs and mRNAs profiles and their interaction networks in regulating the development of polycystic ovary syndrome (PCOS)? DesignLncRNA microarray was used to analyse the expression profiles of lncRNA and mRNA in follicular fluid exosomes from three patients with polycystic ovary syndrome (PCOS) and three control women. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to explore biological functions of exosomal mRNAs in PCOS. Six PCOS-related genes were selected, and coding-non-coding gene co-expression (CNC) networks and competing endogenous RNA (ceRNA) networks analysis were combined to reveal lncRNA–miRNA–mRNA interaction networks. ResultsA total of 5373 differentially expressed exosomal lncRNAs and 3381 differentially expressed exosomal mRNAs were identified (fold change ≥2 and P < 0.05). Gene ontology analysis indicated that 14 terms of biological process were related to reproductive development. KEGG pathway analysis revealed PCOS-related pathways, such as MAPK signalling pathway and some inflammation-related signalling pathways. Interaction networks of lncRNAs, miRNAs and six PCOS-related genes (IRS1, CYP11A1, BMP6, FSHR, WNT4 and CYP19A1) were constructed. The CNC networks and ceRNA networks analysis uncovered some novel PCOS-related exosomal lncRNA-miRNA-mRNA regulatory networks. ConclusionsDifferential expression profiles of exosomal lncRNAs and mRNAs were identified, and some PCOS-related biological processes and regulatory networks were indicated. LncRNAs and mRNAs in follicular fluid exosomes may play important roles in the follicular development of PCOS.

De Novo Assembly and Annotation of the Vaginal Metatranscriptome Associated with Bacterial Vaginosis.

The vaginal microbiome plays an important role in women’s health and disease. Here we reanalyzed 40 vaginal transcriptomes from a previous study of de novo assembly (metaT-Assembly) followed by functional annotation. We identified 286,293 contigs and further assigned them to 25 phyla, 209 genera, and 339 species. Lactobacillus iners and Lactobacillus crispatus dominated the microbiome of non-bacterial vaginosis (BV) samples, while a complex of microbiota was identified from BV-associated samples. The metaT-Assembly identified a higher number of bacterial species than the 16S rRNA amplicon and metaT-Kraken methods. However, metaT-Assembly and metaT-Kraken exhibited similar major bacterial composition at the species level. Binning of metatranscriptome data resulted in 176 bins from major known bacteria and several unidentified bacteria in the vagina. Functional analyses based on Clusters of Orthologous Genes (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways suggested that a higher number of transcripts were expressed by the microbiome complex in the BV-associated samples than in non-BV-associated samples. The KEGG pathway analysis with an individual bacterial genome identified specific functions of the identified bacterial genome. Taken together, we demonstrated that the metaT-Assembly approach is an efficient tool to understand the dynamic microbial communities and their functional roles associated with the human vagina.

Construction and Analysis of the lncRNA-miRNA-mRNA Network Based on Competing Endogenous RNA in Atrial Fibrillation.

BackgroundAccumulated studies have revealed that long non-coding RNAs (lncRNAs) play critical roles in human diseases by acting as competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-mediated ceRNA in atrial fibrillation (AF) remain unknown. In the present study, we aimed to construct the lncRNA-miRNA-mRNA network based on ceRNA theory in AF by using bioinformatic analyses of public datasets.MethodsMicroarray data sets of GSE115574 and GSE79768 from the Gene Expression Omnibus database were downloaded. Twenty-one AF right atrial appendage (RAA) samples and 22 sinus rhythm (SR) subjects RAA samples were selected for subsequent analyses. After merging all microarray data and adjusting for batch effect, differentially expressed genes were identified. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out. A ceRNA network was constructed.ResultA total of 8 lncRNAs and 43 mRNAs were significantly differentially expressed with fold change >1.5 (p < 0.05) in RAA samples of AF patients when compared with SR. GO and KEGG pathway analysis showed that cardiac muscle contraction pathway were involved in AF development. The ceRNA was predicted by co-expressing LOC101928304/ LRRC2 from the constructional network analysis, which was competitively combined with miR-490-3p. The expression of LOC101928304 and LRRC were up-regulated in myocardial tissue of patients with AF, while miR-490-3p was down-regulated.ConclusionWe constructed the LOC101928304/miR-490-3p/LRRC2 network based on ceRNA theory in AF in the bioinformatic analyses of public datasets. The ceRNA network found from this study may help improve our understanding of lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of AF.

Integrated Analysis of Long Non-Coding RNA -mRNA Profile and Validation in Diabetic Cataract

ABSTRACTPurposeTo illustrate the expression profile of lncRNAs and mRNAs in diabetic cataract (DC) and explore their potential role in the pathogenesis of DC.MethodsLncRNA and mRNA microarray were conducted using the lens epithelium of DC patients (n = 3) and controls from eye bank (n = 3). Further, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to unveil their underlying biological function and signaling pathway. The co-expression network was constructed to explore the relationship between lncRNAs and mRNAs. Then, lens epithelial cells (LECs) were cultured in vitro under high glucose (HG) and normal glucose (NG) groups to further verified the expression profiles of mRNAs. At last, quantitative RT-PCR (qRT-PCR) was performed to confirm the microarray results for the aberrantly expressed lncRNAs, and to unveil the expression prolife of mRNAs in LECs.ResultsEight thousand three hundred and twenty-six lncRNAs and 3303 mRNAs were dysregulated in DC. GO analysis unveiled that the upregulated mRNAs, highest enrichment score of the GO term belonged to oxidation-reduction process, while the highest for downregulated mRNAs went to protein lipidation. In the CC category, the most significant terms for upregulated and downregulated mRNAs appeared in intracellular part and intrinsic component of membrane, respectively. As to MF category, the most significant term for upregulated mRNAs was protein binding, and for downregulated mRNAs was catecholamine binding. KEGG pathways analysis demonstrated that the major enrichment score of pathways in upregulated mRNAs included Glycolysis/Gluconeogenesis, lysosome, carbon metabolism and AGE-RAGE signaling pathway. For the downregulated mRNAs, the glycosphingolipid biosynthesis-lacto and neolacto series pathway was included. Three lncRNAs (LINC01508, MAFA-AS1, MIAT) and the Sirtuin 2 are positively related in the co-expression network.ConclusionsThis study provided an overview of the lncRNAs and mRNAs expression, and suggesting that several aberrantly expressed lncRNAs might participate in the pathogenesis of DC.

Testing lncRNAs signature as clinical stage-related prognostic markers in gastric cancer progression using TCGA database.

LncRNA expression can be conducive to gastric cancer (GC) prognosis. The objective of this study is to ascertain five specific lncRNAs involved in tumor progression of GC and their role as prognostic markers to diagnose clinical stage-wise GC. High-throughput RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database and performed genome-wide lncRNA expression analysis using edgeR package, Bioconductor.org, and R-statistical computing to analyze differentially expressed lncRNA analysis. Cutoff parameters were FDR < 0.05 and |Log2FC| > 2. Total 351 tumor samples with differentially expressed lncRNAs were divided into group-1 lncRNAs such as AC019117.2 and LINC00941, and group-2 lncRNAs such as LINC02410, AC012317.2, and AC141273.1 by 2:1. The Spearman correlation coefficients (p < 0.05) and correlation test function (cor.test ()) were performed for lncRNAs as per clinical stage. Cytoscape software was used to construct lncRNA-mRNA interaction networks. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (p < 0.05) analysis were conducted using the clusterProfiler package. Kaplan-Meier survival analysis was performed to determine the overall survival of patients based on the expression of five lncRNAs in different clinical stages of GC. AC019117.2 and LINC00941 of group 1 inferred a positive correlation with clinical stages of stage I to stage IV, and their expressions were higher in tumor tissues than normal tissues. On the contrary, LINC02410, AC012317.2, and AC141273.1 of group 2 exhibited a negative correlation with clinical stage, and they exhibited more expression in normal tissues compared to tumor tissues. GO and KEGG pathway analysis reported that AC019117.2 may interact with LINC00941 via ITGA3 and trophoblast glycoprotein (TPBG) to foster tumor progression. Tumor-specific group-1 lncRNAs were conducive to the poor overall survival and exhibited a positive correlation with the clinical stages of stage I to stage IV in GC as per the lncRNA-mRNA networking analysis. These five lncRNAs could be considered as clinically useful lncRNA-based prognostic markers to predict clinical stage-wise GC progression.

Pediococcus pentosaceus CECT 8330 protects DSS-induced colitis and regulates the intestinal microbiota and immune responses in mice

BackgroundCompelling evidences demonstrated that gut microbiota dysbiosis plays a critical role in the pathogenesis of inflammatory bowel diseases (IBD). Therapies for targeting the microbiota may provide alternative options for the treatment of IBD, such as probiotics. Here, we aimed to investigate the protective effect of a probiotic strain, Pediococcus pentosaceus (P. pentosaceus) CECT 8330, on dextran sulfate sodium (DSS)-induced colitis in mice.MethodsC57BL/6 mice were administered phosphate-buffered saline (PBS) or P. pentosaceus CECT 8330 (5 × 108 CFU/day) once daily by gavage for 5 days prior to or 2 days after colitis induction by DSS. Weight, fecal conditions, colon length and histopathological changes were examined. ELISA and flow cytometry were applied to determine the cytokines and regulatory T cells (Treg) ratio. Western blot was used to examine the tight junction proteins (TJP) in colonic tissues. Fecal short-chain fatty acids (SCFAs) levels and microbiota composition were analyzed by targeted metabolomics and 16S rRNA gene sequencing, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of orthologous groups of proteins (COG) pathway analysis were used to predict the microbial functional profiles.ResultsP. pentosaceus CECT 8330 treatment protected DSS-induced colitis in mice as evidenced by reducing the weight loss, disease activity index (DAI) score, histological damage, and colon length shortening. P. pentosaceus CECT 8330 decreased the serum levels of proinflammatory cytokines (TNF-α, IL-1β, and IL-6), and increased level of IL-10 in DSS treated mice. P. pentosaceus CECT 8330 upregulated the expression of ZO-1, Occludin and the ratio of Treg cells in colon tissue. P. pentosaceus CECT 8330 increased the fecal SCFAs level and relative abundances of several protective bacteria genera, including norank_f_Muribaculaceae, Lactobacillus, Bifidobacterium, and Dubosiella. Furthermore, the increased abundances of bacteria genera were positively correlated with IL-10 and SCFAs levels, and negatively associated with IL-6, IL-1β, and TNF-α, respectively. The KEGG and COG pathway analysis revealed that P. pentosaceus CECT 8330 could partially recover the metabolic pathways altered by DSS.ConclusionsP. pentosaceus CECT 8330 administration protects the DSS-induced colitis and modulates the gut microbial composition and function, immunological profiles, and the gut barrier function. Therefore, P. pentosaceus CECT 8330 may serve as a promising probiotic to ameliorate intestinal inflammation.

Transcriptome and HPLC Analysis Reveal the Regulatory Mechanisms of Aurantio-Obtusin in Space Environment-Induced Senna obtusifolia Lines.

Senna obtusifolia is a famous medicinal plant that is widely used in Asian countries. Its seed plays an important role in the treatment of many diseases because it contains various anthraquinones and flavonoids. Our previous studies have indicated that three space environment-induced S. obtusifolia lines (SP-lines) i.e., QC10, QC29, and QC46, have higher seed yield and aurantio-obtusin (AO) content. However, the underlying mechanism of higher AO content in SP-lines is still unknown. Herein, transcriptome sequencing and HPLC were employed to analyze the differences between SP-lines and ground control (GC3) and elucidate the regulatory mechanisms of AO accumulation in SP-lines. The results show that 4002 differentially expressed genes (DEGs) were identified in SP-lines versus (vs.) GC3. DEGs in the QC10 vs. GC3, QC29 vs. GC3, and QC46 vs. GC3 comparisons were classified into 28, 36, and 81 GO terms and involved in 63, 74, and 107 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG pathway and gene expression analysis revealed that DEGs involved in anthraquinone pathways were significantly elevated in QC10 and QC46. Integrating the results of GO annotation, KEGG enrichment, and gene expression analysis, we propose that the elevated genes such as DAHPS, DHQS, and MenB enhance the metabolic flux in the anthraquinone pathway and promote AO content in QC10 and QC46. Taken together, this study elucidated the mechanism of AO content in SP-lines and provides valuable genetic information for S. obtusifolia. In addition, to the best of our knowledge, this study presents the first transcriptome analysis of environment-induced medicinal plants and paves the way to select elite S. obtusifolia varieties in the future.

Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG.

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) targets interact via competitive microRNA (miRNA) binding. However, the roles of cancer-specific lncRNAs in the competing endogenous RNA (ceRNA) networks of low-grade glioma (LGG) remain unclear. This study obtained RNA sequencing data for normal solid tissue and LGG primary tumour tissue from The Cancer Genome Atlas database. We used a computational method to analyse the relationships among the mRNAs, lncRNAs, and miRNAs in these samples. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to predict the biological processes (BPs) and pathways associated with these genes. Kaplan-Meier survival analysis was used to evaluate the association between the expression levels of specific mRNAs, lncRNAs, and miRNAs and overall survival. Finally, we created a ceRNA network describing the relationships among these mRNAs, lncRNAs, and miRNAs using Cytoscape 3.5.1. A total of 2555 differentially expressed (DE) mRNAs, 218 DElncRNAs, and 192 DEmiRNAs were identified using R. In addition, GO and KEGG pathway analysis of the mRNAs and lncRNAs in the ceRNA network identified 10 BPs, 10 cell components, 10 molecular functions, and 48 KEGG pathways as selectively enriched. A total of 55 lncRNAs, 50 miRNAs, and 10 mRNAs from this network were shown to be closely associated with overall survival in LGG. Finally, 59 miRNAs, 235 mRNAs, and 17 lncRNAs were used to develop a ceRNA network comprising 313 nodes and 1046 edges. This study helps expand our understanding of ceRNA networks and serves to clarify the underlying pathogenesis mechanism of LGG.

The biomarkers of key miRNAs and gene targets associated with extranodal NK/T-cell lymphoma.

Gene expression profiling studies have shown the pathogenetic role of oncogenic pathways in extranodal natural killer/T-cell lymphoma (ENKL). In this study, we aimed to identify the microRNAs (miRNAs) playing potential roles in ENKL, and to evaluate the genes and biological pathways associated to them. Gene expression profiles of ENKL patients were acquired from the gene expression omnibus (GEO) database. Most differentially expressed (DE)-miRNAs were identified in ENKL patients using limma package. Gene targets of the DE-miRNAs were collected from online databases (miRDB, miRWalk, miRDIP, and TargetScan), and used in Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses on Database for annotation, visualization, and integrated discovery database, and then used in protein–protein interaction (PPI) analysis on STRING database. Hub genes of the PPI network were identified in cytoHubba, and were evaluated in Biological networks gene ontology. According to the series GSE31377 and GSE43958 from GEO database, four DE-miRNAs were screened out: hsa-miR-363-3p, hsa-miR-296-5p, hsa-miR-155-5p, and hsa-miR-221-3p. Totally 164 gene targets were collected from the online databases, and used in the GO and KEGG pathway analyses and PPI network analysis. Ten hub genes of the PPI network were identified: AURKA, TP53, CDK1, CDK2, CCNB1, PLK1, CUL1, ESR1, CDC20, and PIK3CA. Those hub genes, as well as their correlative pathways, may be of diagnostic or therapeutic potential for ENKL, but further clinical evidence is still expected.

Molecular mechanisms of Tanshinone IIA in Hepatocellular carcinoma therapy via WGCNA-based network pharmacology analysis

Hepatocellular carcinoma (HCC) is a worldwide malignant tumor that caused irreversible consequences. Tanshinone IIA has been shown to play a notable role in HCC treatment. However, the potential targets and associating mechanism of Tanshinone IIA against HCC remain unknown. We first screened out 105 overlapping genes by integrating the predicted targets of Tanshinone IIA from multiple databases and the differentially expressed genes of HCC from the Cancer Genome Atlas (TCGA) database. Then, we performed weighted gene co-expression network analysis (WGCNA) using the RNA-seq profiles of overlapping genes and HCC-related clinical information. 23 genes related to clinical tumor grade in the important module were imported for Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) analysis. Comparing the key genes in the important module from WGCNA with the high connectivity nodes from the PPI network, we identified three hub genes, AURKB, KIF11, and PLK1. For further verification, we tested the binding of Tanshinone IIA to three hub genes. The survival curve, receiver operating characteristic (ROC) curve, mRNA expression, and protein expression were also used to validate the hub genes. In the study, WGCNA revealed grade-specific gene modules, and the following KEGG pathway analysis indicated that Tanshinone IIA probably plays therapeutical effect in the development of HCC, especially in the cell cycle. Our result partially explained the pharmacological mechanism of Tanshinone IIA against HCC.

Transcriptome analysis of Crimson seedless grapevine (Vitis vinifera L.) infected by grapevine berry inner necrosis virus

Grapevine fruits produced in China are often infected by grapevine berry inner necrosis virus (GINV). GINV disease is the most economically important viral disease of the grapevine, characterized by discoloration on the fruit surface and necrosis of the flesh. In this study, the transcriptome sequencing technology revealed 1700 differently expressed genes (DEGs), with 846 up-regulated and 854 down-regulated genes in Crimson seedless grapevine during the GINV infection. Both Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to classify the DEGs. The top 10 GO terms were enriched in GINV versus mock, and these enriched GO terms were mainly classified into three categories, namely, 324 cellular components, 2062 biological processes, and 940 molecular functions. Based on the P-values, the KEGG pathway analysis indicated that 96 major pathways were identified in GINV versus mock, and 20 major enrichment pathways were significantly enriched. Using quantitative real-time polymerase chain reaction (qRT-PCR), we validated the differential expression of 12 genes. The expression patterns of 11 genes were consistent with the RNA-sequencing (RNA-seq) results, except for one gene. Thus, our study provides comprehensive transcriptome information on the GINV–grapevine interaction, thereby improving our understanding of virus–host interactions.

Analysis of the drug-target-disease network of trichosanthes-angelica sinensis-frankincense-myrrh in the treatment of breast cancer

This study aims to investigate the key bioactive compounds, potential targets, and molecular mechanisms of Trichosanthes-Angelica sinensis-Frankincense-Myrrh (TAFM) in the treatment of breast cancer using network pharmacology and molecular docking methods. The chemical constituents and related targets of TAFM were obtained using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. GeneCards, Online Mendelian Inheritance in Man (OMIM), Drugbank, and Therapeutic Target Database (TTD) databases were used to identify breast cancer-related targets. Cytoscape 3.9.1 software and the STRING (Search Tool for the Retrieval of Interaction Gene/Proteins) database were used to visualize the drug component-target-disease and protein interaction networks before screening the core components and key targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID (Database for Annotation, Visualization and Integrated Discovery) database, and molecular docking was performed using AutoDock and PyMOL software. We found that the key active ingredients of TAFM in the treatment of breast cancer include β-sitosterol, stigmasterol, ellagic acid, pelargonidin, and petunidin. A total of 38 key targets and hub genes, including ESR1, VEGFA, PTGS2, HSP90AA1, and CASP3, were identified. Molecular docking results confirmed that stigmasterol and Caspase 3 (CASP3) were the most closely related targets. GO enrichment analysis demonstrated that the biological processes involved mainly included drug response, positive apoptosis process regulation, and two-way gene expression regulation. KEGG pathway analysis revealed the involvement of pathways related to cancer, inflammation, and infection-related diseases. The study results provide supportive evidence that β-sitosterol, stigmasterol, ellagic acid, pelargonidin, and petunidin represent the key bioactive ingredients of TAFM that exhibit anti-breast cancer activity through the regulation of estrogen receptor alpha (ESR1), vascular endothelial growth factor A (VEGFA), prostaglandin-endoperoxide synthase 2 (PTGS2), heat shock protein 90 alpha (HSP90AA1), and CASP3 in the treatment of breast cancer.

Exploring the molecular mechanism of Radix Astragali on colon cancer based on integrated pharmacology and molecular docking technique

Objective: The objective of this study was to study the mechanism of Radix Astragali on colon cancer by integrated pharmacology and molecular docking technique. Methods: Integrative pharmacology-based research platform of traditional Chinese medicine (TCMIP) V2.0 was used to obtain the chemical components and corresponding targets of Radix Astragali and the target information of colon cancer to create the main target network of drugs and diseases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out using Hiplot website, and the interaction network of “Traditional Chinese Medicine-component-target-pathway” was established, and molecular docking with main targets was carried out for the key components. Results: Twenty-seven chemical constituents of Radix Astragali, their 254 corresponding targets, and 44 colon cancer-related targets were obtained. Through proteins interacting, 70 nodes were obtained as core targets. GO analysis showed that it mainly acts on lipid metabolism, nuclear receptor activity, phagocytic cup, etc. KEGG pathway analysis showed that it was mainly enriched in the estrogen signaling pathway, C-type lectin receptor signaling pathway, PI3K-Akt signaling pathway, etc. The multidimensional network, quantitative estimate of the drug, and molecular docking showed that the main targets are AKT1, BCL2, and CDK6, and the key components involved are kumatakenin, astragaloside VIII, and choline. Conclusion: Kumatakenin, Astragaloside VIII, Choline and other compounds of Radix Astragali may affect colon cancer by acting on AKT1, BCL2 and other targets, thereby regulating estrogen signaling pathway, C-type lectin receptor signaling pathway, PI3K-Akt signaling pathway and so on. Those will provide theoretical reference for future research on the material basis and mechanism of its pharmacodynamics.