Objective To validate the different expressions of human fxyd6 gene between normal bile duct tissues and malignant tumor tissues, and to observe the subcellular localization of human fxyd6 gene in human cholangiocarcinoma cells. MethodsThe different expressions between normal bile duct tissues and malignant tumor tissues were identified by RT-PCR. In situ polymerase chain reaction （IS-RT-PCR） was applied to detect the subcellular localization of fxyd6 gene in paraffin sections of human cholangiocarcinoma cells. Image analysis software was used to semiquantitatively determine the difference between normal and malignant tissues. ResultsHuman fxyd6 gene was highly expressed in cholangiocarcinoma tissues and lowly expressed in normal ones. There was a significant difference between the expressions of carcinoma cells and normal cells （P＜0.05）. IS-RT-PCR showed that fxyd6 gene localized in the kytoplasma of epithelial cells of human cholangiocarcinoma. ConclusionHuman fxyd6 gene may act as an essential component of the malignant transformation process in human cholangiocarcinoma.
ObjectiveTo investigate the molecular pathogenesis of pulmonary fibrosis induced by bleomycin in a murine model,and provide novel insights for clinical diagnosis and treatment.
MethodsFrom Gene Expression Omnibus,we downloaded microarray data extracted from experiments of bleomycin induced pulmonary fibrosis in wild-type mice. With BRB-Array Tools,differentially expressed genes at different time points during disease development were screened,selected and analyzed by DAVID software.
ResultsBRB array analysis identified 45101 differentially expressed genes. After induction by bleomycin on 7th day,1164 genes and 735 genes were significantly up-regulated and down-regulated (P<0.05,fold change>2),respectively. On 14th day,731 genes and 390 genes were significantly up-regulated and down-regulated (P<0.05,fold change>2),respectively. DAVID analysis revealed that the up-regulated genes were significantly enriched in cell cycle,p53 signaling and chemokine signaling pathway,damaging reaction and collagen metabolism gene sets. While the down-regulated genes were enriched in the drug metabolism pathway gene set.
ConclusionsBioinformatics methodologies are able to efficiently analyze microarray data and extract its underlying information,provide novel insights for major molecular events and shift of cell signaling pathway during pulmonary fibrosis progression,and furthermore,finding molecular markers for early diagnosis and therapeutic targets.
ObjectiveTo analyze the expression profile changes of osteogenic-related genes during spontaneous calcification of rat bone marrow mesenchymal stem cells (BMSCs).
MethodsBMSCs were isolated from 3-day-old healthy Sprague Dawley rats;cells at the 4th generation were used to establish the spontaneous calcification model in vitro. Spontaneous calcification process was recorded by inverted phase contrast microscope observation and alizarin red staining after 7 and 14 days of culture. For gene microarray analysis, cell samples were collected at 0, 7, and 14 days after culture; the differentially expressed genes were analyzed by bioinformatics methods and validated by real-time quantitative PCR (RT-qPCR) assay.
ResultsRat BMSCs calcified spontaneously in vitro. When cultured for 7 days, the cells began to aggregate and were weakly positive for alizarin red staining. After 14 days of culture, obvious cellular aggregation and typical mineralized nodules were observed, the mineralized nodules were brightly positive for alizarin red staining. A total of 576 gene probe-sets expressed differentially during spontaneous calcification, corresponding 378 rat genes. Among them, 359 gene probe-sets expressed differentially between at 0 and 7 days, while only 13 gene probe-sets expressed differentially between at 7 and 14 days. The 378 differentially expressed genes were divided into 6 modes according to their expression profiles. Moreover, according to their biological functions, differentially expressed genes related to bone cell biology could be classified into 7 major groups:angiogenesis, apoptosis, bone-related genes, cell cycle, development, cell communication, and signal pathways related to osteogenic differentiation. In cell cycle group, 12 down-regulated genes were linked with each other functionally. Matrix metalloproteinase 13 (Mmp13), secreted phosphoprotein 1 (Spp1), Cxcl12, Mmp2, Mmp3, Apoe, and Itga7 had more functional connections with other genes. The results of genes Spp1, Mgp, Mmp13, Wnt inhibitory factor 1, Cxcl12, and cyclin A2 by RT-qPCR were consistent with that of gene microarray.
ConclusionThe first 7 days after rat BMSCs were seeded are a key phase determining the fate of spontaneous calcification. Multiple genes related with cell communication, bone-related genes, cell cycle, transforming growth factor-β signaling pathway, mitogen-activated protein kinase signaling pathway, and Wnt signaling pathway are involved during spontaneous calcification.
Circular RNA are one kind of non-coding RNA, charactered by covalently closed rings. They can influence biological functions such as cell transduction and protein synthesis. They are associated with pathogenesis of many diseases and become a novel family of biomarkers. Now we try to introduce the origin, structure, function of circular RNA and the involved research methodology. Furthermore, we primarily discuss their application in the tuberculosis research.
Objective To explore the mode and role of differential expression of circular RNAs (circRNAs) in myelodysplastic syndrome (MDS). Methods We preprocessed and analyzed the circRNA expression profile datasets GSE163386, GSE94591, and GSE81173 in the GEO (Gene Expression Omnibus) database. By using the circBank database and the ENCORI, miRDB, and miRWalk databases to predict microRNAs (miRNAs) that interacted with differentially expressed circRNAs and messenger RNAs (mRNAs), the circRNA-miRNA-mRNA axis was constructed. We retrieved miRNAs related to MDS in PubMed and further obtained competing endogenous RNA (ceRNA) networks related to MDS by taking intersections. Results Through analysis, 128 differentially expressed circRNAs were identified, 48 highly expressed, and 80 low expressed. Among differentially expressed circRNAs with multiple differences>10, 3 were upregulated and 11 were downregulated. Through analysis, 101 differentially expressed mRNA were identified, with 9 upregulated and 92 downregulated. Intersecting with the MDS related miRNAs retrieved by PubMed, we further obtained the MDS related ceRNA network, namely circRNA (has_circ_0061137)-miRNA (has-miR-16-5p)-mRNA (RUBCNL, TBC1D9, SLC16A6) and circRNA (has_circ_0061137)-miRNA (has-miR-125b-5p)-mRNA (CCR5, SLC16A6, IRF4), all of which were downregulated. Conclusion The ceRNA networks revealed in this study may help elucidate the circRNA mechanism in MDS.
ObjectiveTo explore the pathogenesis of tuberculosis and provide new ideas for its early diagnosis and treatment.MethodsGSE54992 gene expression profile was obtained from the gene expression database. Differentially expressed genes (DEGs) were screened using National Center forBiotechnology Information platform, and GO enrichment analysis, pathway analysis, pathway network analysis, gene network analysis, and co-expression analysis were performed to analyze the DEGs.ResultsCompared with the control group, a total of 3 492 genes were differentially expressed in tuberculosis. Among them, 1 686 genes were up-regulated and 1 806 genes were down-regulated. DEGs mainly involved small molecule metabolic processes, signal transduction, immune response, inflammatory response, and innate immune response. Pathway analysis revealed chemokine signaling pathway, tuberculosis, NF-Kappa B signaling pathway, cytokine-cytokine receptor interaction, and so on; gene signal network analysis found that the core genes were AKT3, PLCB1, MAPK8, and NFKB1; co-expression network analysis speculated that the core genes were PYCARD, TNFSF13, PHPT1, COMT, and GSTK1.ConclusionsAKT3, PYCARD, IRG1, CD36 and other genes and their related biological processes may be important participants in the occurrence and development of tuberculosis. Bioinformatics can help us to comprehensively study the mechanism of disease occurrence, which can provide potential targets for the diagnosis and treatment of tuberculosis.
Chronic cerebral hypoperfusion (CCH) plays an important role in the occurrence and development of vascular dementia (VD). Recent studies have indicated that multiple stages of immune-inflammatory response are involved in the process of cerebral ischemia, drawing increasing attention to immune therapies for cerebral ischemia. This study aims to identify potential immune therapeutic targets for CCH using bioinformatics methods from an immunological perspective. We identified a total of 823 differentially expressed genes associated with CCH, and further screened for 9 core immune-related genes, namely RASGRP1, FGF12, SEMA7A, PAK6, EDN3, BPHL, FCGRT, HSPA1B and MLNR. Gene enrichment analysis showed that core genes were mainly involved in biological functions such as cell growth, neural projection extension, and mesenchymal stem cell migration. Biological signaling pathway analysis indicated that core genes were mainly involved in the regulation of T cell receptor, Ras and MAPK signaling pathways. Through LASSO regression, we identified RASGRP1 and BPHL as key immune-related core genes. Additionally, by integrating differential miRNAs and the miRwalk database, we identified miR-216b-5p as a key immune-related miRNA that regulates RASGRP1. In summary, the predicted miR-216b-5p/RASGRP1 signaling pathway plays a significant role in immune regulation during CCH, which may provide new targets for immune therapy in CCH.
The rapid development of high-throughput chromatin conformation capture (Hi-C) technology provides rich genomic interaction data between chromosomal loci for chromatin structure analysis. However, existing methods for identifying topologically associated domains (TADs) based on Hi-C data suffer from low accuracy and sensitivity to parameters. In this context, a TAD identification method based on spatial density clustering was designed and implemented in this paper. The method preprocessed the raw Hi-C data to obtain normalized Hi-C contact matrix data. Then, it computed the distance matrix between loci, generated a reachability graph based on the core distance and reachability distance of loci, and extracted clustering clusters. Finally, it extracted TAD boundaries based on clustering results. This method could identify TAD structures with higher coherence, and TAD boundaries were enriched with more ChIP-seq factors. Experimental results demonstrate that our method has advantages such as higher accuracy and practical significance in TAD identification.
ObjectiveThe role of ferroptosis-related genes in the occurrence and development of lung injury caused by sepsis was investigated by bioinformatics methods, and the closely related genes were predicted. MethodsThe Dataset GSE154653 was downloaded from the gene expression database (GEO), and a total of 8 cases of microarray gene set were included in normal group and lipopolysaccharide (LPS)-induced sepsis lung tissue. The differential expression genes (DEGs) were screened out under conditions of |log2 FC|>1 and P.adj<0.05. Meanwhile, the selected DEGs were combined with the driver and suppressor genes of ferroptosis downloaded from the ferroptosis database (FerrDb) to obtain the differential genes associated with ferroptosis in sepsis (Fe-DEGs). These Fe-DEGs were further analyzed using R language, DAVID, and STRING online tools to identify GO-KEGG functions and pathways, and the construction of PPI network. Results The Bioinformatics approach screened out 3533 DEGs and intersected 53 key genes related to ferroptosis. The further biological process (BP) of GO enrichment analysis mainly involves the positive regulation of transcription, the positive regulation of RNA polymerase II promoter transcription, the cytokine mediated signaling pathway, and the positive regulation of angiogenesis. The molecular function (MF) mainly involves the same protein binding, transcriptional activation activity and REDOX enzyme activity. The pathways are enriched in iron death, HIF-1 signaling pathway and AGE-RAGE signaling pathway. Five key Fe-DEGs genes were screened by constructing PPI network, including CYBB, LCN2, HMOX1, TIMP1 and CDKN1A. Conclusion CYBB、LCN2、HMOX1、TIMP1 and CDKNIA genes may be key genes involved in ferroptosis of lung tissue caused by sepsis.
ObjectiveTo investigate the significant genes in Mesio-temporal lobe epilepsy (MTLE) and explore the molecular mechanism of MTLE.MethodsThe microarray data of MTLE were downloaded from the Gene Expression Omnibus (GEO) database and analyzed by bioinformatics methods using GEO2R tool, Venny2.1.0, FUNRICH and Cytoscape software, DAVID and String databases.ResultsOf all the 331 differentially expressed genes(DEGs), 46 genes were down-regulated and 285 genes were up-regulated in dataset GSE88992; Furthermore, the core module genes were identified from those DEGs, which were expressed mostly in plasma membrane and extracellular space; The major molecular funtion were chemokine activity, cytokine activity and chemokine receptor binding; The main biological pathways involved neutrophil chemotaxis, inflammatory response and positive regulation of ERK1 and ERK2 cascade; The KEGG analysis showed DEGs enriched in Chemokine signaling pathway, Cytokine-cytokine receptor interaction and Complement and coagulation cascades. In addition, ten hub genes (Il6, Fos, Stat3, Ptgs2, Ccl2, Timp1, Cd44, Icam1, Atf3, Cxcl1) were found to significantly express in the MTLE.ConclusionThe pathogenesis of MTLE involves multiple genes, and multiple cell signaling pathways. Thus investigations of these genes may provide valuable insights into the mechanism of MTLE.
