Integrated bioinformatics approach reveals methylation-regulated differentially expressed genes in obesity

ABSTRACT Objective: To identify DNA methylation and gene expression profiles involved in obesity by implementing an integrated bioinformatics approach. Materials and methods: Gene expression (GSE94752, GSE55200, and GSE48964) and DNA methylation (GSE67024 and GSE111632) datasets were obtained from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in subcutaneous adipose tissue of patients with obesity were identified using GEO2R. Methylation-regulated DEGs (MeDEGs) were identified by overlapping DEGs and DMGs. The protein-protein interaction (PPI) network was constructed with the STRING database and analyzed using Cytoscape. Functional modules and hub-bottleneck genes were identified by using MCODE and CytoHubba plugins. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG pathways. To prioritize and identify candidate genes for obesity, MeDEGs were compared with obesity-related genes available at the DisGeNET database. Results: A total of 54 MeDEGs were identified after overlapping the lists of significant 274 DEGs and 11,556 DMGs. Of these, 25 were hypermethylated-low expression genes and 29 were hypomethylated-high expression genes. The PPI network showed three hub-bottleneck genes (PTGS2, TNFAIP3, and FBXL20) and one functional module. The 54 MeDEGs were mainly involved in the regulation of fibroblast growth factor production, the molecular function of arachidonic acid, and ubiquitin-protein transferase activity. Data collected from DisGeNET showed that 11 of the 54 MeDEGs were involved in obesity. Conclusion: This study identifies new MeDEGs involved in obesity and assessed their related pathways and functions. These results data may provide a deeper understanding of methylation-mediated regulatory mechanisms of obesity.

Transcriptional profiling and network pharmacology analysis identify the potential biomarkers from Chinese herbal formula Huosu Yangwei Formula treated gastric cancer in vivo / 中国天然药物

Huosu Yangwei (HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the effective compounds of HSYW and its related anti-tumor mechanisms are not completely understood. In the current study, 160 ingredients of HSYW were identified and 64 effective compounds were screened by the ADMET evaluation. Furthermore, 64 effective compounds and 2579 potential targets were mapped based on public databases. Animal experiments demonstrated that HSYW significantly inhibited tumor growth in vivo. Transcriptional profiles revealed that 81 mRNAs were differentially expressed in HSYW-treated N87-bearing Balb/c mice. Network pharmacology and PPI network showed that 12 core genes acted as potential markers to evaluate the curative effects of HSYW. Bioinformatics and qRT-PCR results suggested that HSYW might regulate the mRNA expression of DNAJB4, CALD, AKR1C1, CST1, CASP1, PREX1, SOCS3 and PRDM1 against tumor growth in N87-bearing Balb/c mice.

Nature-effect relationship research of Curcumae Longae Rhizoma,Curcumae Radix,and Curcumae Rhizoma based on nature combination / 中国中药杂志

Curcumae Longae Rhizoma,Curcumae Radix and Curcumae Rhizoma are different medicinal parts of the same plant.Nevertheless,they are different in medicinal effects due to the different Chinese herbal nature. In this study,traditional Chinese medicines database( TCMD2009),traditional Chinese medicine system( TCMSP),and Ch EMBL database were retrieved to screen the active components and targets,and construct the target PPI network. By a graph theoretic clustering algorithm identifying protein complex algorithm( IPCA),the protein modules were identified and analyzed by gene ontology( GO) enrichment. A comparative study of Curcumae Longae Rhizoma and Curcumae Radix illustrate that Curcumae Longae Rhizoma regulates blood coagulation through P2 RY12,GNG2 and other genes to exert the analgesic effect. Curcumae Radix regulates lipid metabolism,plasma lipoprotein particle levels,platelet activation,response to oxidative stress,apoptotic process through LDLR,APOB,PRKCA,SOD1,TP53 and other genes to perform a function in clearing the heart and cooling the blood. A comparative study of Curcumae Radix and Curcumae Rhizoma demonstrate that Curcumae Rhizoma on regulates the nervous system by GRIA2,GRIA4 and other genes to exert blood-breaking effect; Curcumae Radix regulates lipid metabolism,plasma lipoprotein particle levels,platelet activation,response to oxidative stress,apoptotic process by genes such as CALM1,LPL,APOB,SOD1 and TP53 to play the role of clearing heart and cooling blood. Cluster analysis of the protein interaction network of the nature combination is helpful to explain the intrinsic link between the nature combination and efficacy.

Mechanism of Yang-tonifying herbs distributing along kidney meridians in molecular level by network pharmacology / 中草药

Objective: To predict the unique mechanism of Yang-tonifying herbs distributing along kidney meridians in molecular level through network pharmacology technology. Methods: Eight kidney-yang tonifying herbs with common clinical effects and clear therapeutic effects were selected in study. The chemical ingredients of traditional Chinese medicines were searched by TCMSP database. OB and DL values were applied to screen the active substance and the chemical similarity target prediction methods of Pub Chem database were used to predict the target proteins of TCM; The PPI between the target proteins of the kidney-yang tonifying herbs and the KEGG signal pathway were searched by the STRING database; The nodes in the PPI network were evaluated by the weighted PageRank algorithm and then the core target protein was screened. Using the Cytoscape 3.6.0 software, a compound-target network, a herb-target-PPI network, and a target-pathway network were constructed. Results: Through the network analysis, 21 key targets and 40 signal pathways of the kidney-yang tonifying herbs were screened. The medicinal played the role of warming and tonifying kidney-yang by T cell regulation, sex hormone regulation, immune response, and delaying aging. The mechanism may be related to thyroid hormone signaling pathway, neurotrophin signaling pathway, TNF signaling pathway and estrogen signaling pathway. Conclusion: The method based on network pharmacology could help to find the key targets and signal pathways of the kidney-yang tonifying herbs, which provides useful information and data support for further interpretation of the classification meaning of the kidney-yang tonifying herbs in TCM

MIPCE: An MI-based protein complex extraction technique.

Protein–protein interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. Identifying protein complexes is of great importance for understanding cellular organization and functions of organisms. In this work, a method is proposed, referred to as MIPCE, to find protein complexes in a PPI network based on mutual information.MIPCE has been biologically validated by GO-based score and satisfactory results have been obtained. We have also compared our method with some wellknown methods and obtained better results in terms of various parameters such as precession, recall and F-measure.

Using bioinformatics to analyze the effect of age on fracture healing / 天津医药

Objective To explore the effect of age on the fracture healing through bioinformatical analysis of gene ex?pression data in GEO, and to screen critical molecular targets and pathways involved in this process. Methods Through R programming language, we identified different expressed genes between 26/52 week old rats and 6 week old rats in every time points of the experiment (No fracture;3 days, 1 week, 2 weeks, 4 weeks and 6 weeks after fracture). By comparison of these different expressed genes, those genes that may contribute to fracture healing were identified. Function annotation was conducted based on DAVID database and PPI network that was constructed via STRING database. Results Compared with 6 week old rat, 52 week old rat show more different genes at 2, 4 and 6 weeks after fracture as well as more than intact rats. At the time point of 6 weeks after fracture, 26 week old rat present 4 different genes while 52 week old rat present 99 differ?ent genes compared with 6 week old rat. We totally found 99 genes that might play important roles in the process of fracture healing. These genes involved in biological process related to bone healing, immune, inflammatory and etc. Also, two screened gene enriched KEGG pathways were identified: ECM-receptor interaction and Arachidonic acid metabolism. Through the analysis of PPI network, Pcna, Fn1, Casp3 and etc, who present high density connectivity in PPI network, were screened out. Conclusion Pcna, Casp3 and Fn1 and etc might play important roles in fracture healing through affecting ECM-receptor interaction and Arachidonic acid metabolism.