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find Author "Lu Cong" 2 results
  • Bioinformatics analysis of transcriptome sequencing of early hypoxia damage in photoreceptor 661W cell line

    ObjectiveTo analyze the early changes of gene expression levels and signaling pathways in 661W cell line under hypoxic conditions and to find potential functional target genes.MethodsThe cultured mouse 661W cells were divided into hypoxia treatment group and normoxia control group. Cells in the hypoxia treatment group were cultured in a three-gas incubator with volume fraction of 1% and 5% CO2 at 37 ℃. Cells in the normoxia control group were cultured in an incubator at 37 ℃ with volume fraction of 5% CO2. High-throughput sequencing technology was used to sequence the transcriptome of 661W cell treated with hypoxia and normoxia for 4 hours to screen for differentially expressed genes (DEG). Clustering heat map analysis, gene ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction network (PPI) analysis were performed. The reverse transcription-polymerase chain reaction (RT-PCR) was used to verify the accuracy of the sequencing results.ResultsA total of 506 differentially expressed genes were screened, including 459 up-regulated genes and 47 down-regulated genes. GO functional enrichment analysis showed that the main biological processes of DEG were the cell's response to hypoxia, glycolysis, negative regulation of cell proliferation and apoptosis. hypoxia inducible factor (HIF)-1α pathway, glycolysis, Forkhead box O (FoxO) pathway, Insulin signaling pathway and Adenosine 5'-monophosphate-activated protein kinase (AMPK) pathway were involved in the above process. PPI analysis results showed that hub genes related to hypoxia were Aldoa, Aldoc, Gpi1, Hk2, Hk1, Pfkl, Pfkp, Vhl, Fbxo10 and Fbxo27. The RT-PCR results showed that the relative expression levels of 15 DEG mRNA in the hypoxic treatment group were higher than that of the normoxic control group, and the difference was statistically significant (P<0.05). The mRNA expression levels of N-myc downstream-regulated gene-1 (Ndrg1), Mt1, and vascular endothelial growth factor A (VEGFA) were time-dependent on hypoxia.ConclusionsUnder hypoxia, DEG is mainly related to glucose metabolism, cell response to hypoxia, regulation of proliferation and apoptosis. HIF-1α pathway, glycolysis, FoxO pathway and AMPK pathway are involved in the early changes of 661W cells under hypoxia. Aldoa, Aldoc, Gpi1, Hk2, Hk1, Pfkl, Pfkp, Vhl, Fbxo10, Fbxo27 may play key roles in the response of 661W cells to hypoxia. Ndrg1, Mt1 and VEGFA could be potential functional target genes for the study of ischemia and hypoxia-related fundus diseases.

    Release date:2021-04-19 03:36 Export PDF Favorites Scan
  • Transcriptome sequencing of transgelin-2 inhibiting high glucose induced microglia inflammation

    ObjectiveTo analyze the change of differential genes and signaling pathways in high glucose induced BV2 cells, and to explore the mechanism of transgelin-2 (TAGLN2) regulating cellular inflammatory response and metabolic process. MethodsAn experimental study. The cultured BV2 cells were divided into mannitol treatment (Man) group, glucose treatment (Glu) group, overexpression control Glu treatment (Con) group, overexpression TAGLN2 Glu treatment group, silence control Glu treatment (shCon Glu) group, and silence TAGLN2 Glu treatment (shTAGLN2 Glu) group. Cells in the Man group were cultured in modified Eagle high glucose medium (DMEM) containing 25 mmol/L mannitol and 25 mmol/L glucose, cells in other groups (Glu group, Con Glu group, TAGLN2 Glu group, shCon Glu group and shTAGLN2 Glu group) were cultured in DMEM medium containing 50 mmol/L glucose. After 24 hours of cells culture, transcriptome sequencing of cells in each group were performed using high-throughput sequencing technology, and significantly differentially expressed genes (DEG) were screened. |log2 (fold change)|≥1 and P≤0.05 were adopted as criteria to screen for DEG. Gene Ontology (GO) function enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction network analysis were performed. Real-time polymerase chain reaction (RT-PCR) was used to detect the relative expression level of DEG mRNA. The data between groups were compared by independent sample t-test. ResultsWhen compared with Man group, a total of 517 differentially expressed genes were screened in Glu group, which including 277 up-regulated genes and 240 down-regulated genes. KEGG pathway enrichment analysis showed that the up-regulated genes were significantly enriched in immune system processes such as nuclear factor (NF)-κB signal pathway, Jak-signal transducers and activators of transcription (STAT) signal pathway, while down-regulated genes were significantly enriched in glycosaminoglycan degradation and glyceride metabolic pathway. Compared with Con Glu group, a total of 480 DEG were screened in TAGLN2 Glu group, among which 147 up-regulated and 333 down-regulated genes were detected. Up-regulated genes were significantly enriched in the metabolic processes of fatty acid, glyceride and pyruvate, while down-regulated genes were significantly enriched in immune system processes such as NF-κB signal pathway, Jak-STAT signal pathway and tumor necrosis factor (TNF) signal pathway. Compared with shCon Glu group, a total of 582 DEG were screened in shTAGLN2 Glu group, among which 423 up-regulated and 159 down-regulated genes were detected. Up-regulated DEG were significantly enriched in immune system processes such as TNF signal pathway and chemokine signal pathway, while down-regulated DEG were significantly enriched in pattern recognition receptor signal pathway. RT-PCR results showed that the relative expression levels of DEG mRNA Card11 (t=13.530), Icos (t=3.482), Chst3 (t=6.949), Kynu (t=5.399), interleukin (IL)-1β (t=2.960), TNF-α (t=5.800), IL-6(t=3.130), interferon-γ (t=7.690) and IL-17 (t=6.530) in the TAGLN2 Glu treatment group were decreased significantly compared with Con Glu group, and the difference was statistically significant. ConclusionTAGLN2 can inhibit glucose induced microglia inflammation by NF-κB and Jak-STAT signaling pathways, Card11, Icos, Chst3 and Kynu play an important role in the anti-inflammatory process of TAGLN2.

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