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Analysis On Transcriptome Sequencing And Preconditioning Mechanisms Of Mouse Hippocampus Under Hypoxia Stress

Posted on:2022-02-17Degree:DoctorType:Dissertation
Country:ChinaCandidate:J LiFull Text:PDF
GTID:1480306527991969Subject:Biophysics
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The continuous supply of oxygen and glucose is the basis for ensuring the vitality and function of the brain.Hypoxia often causes tissue,cell function and metabolic disorders.Also,hypoxia is directly related to the occurrence of many tumors.Hypoxia preconditioning(HPC)involves the exposure of organisms,systems,organs,tissues or cells to a brief sub-lethal hypoxic stress,resulting in increasing resistance to a subsequent severe hypoxic stress.HPC can induce endogenous neuroprotective mechanisms through activating oxygen receptor/signal transduction pathway,regulating the transcription and expression of a large number of downstream target genes.Alternative splicing and transcription are tightly couped,which is a biological process in cellular adaptation to hypoxia.There are a large number of specific alternative splicing events in the nervous system,which directly affect the specific differentiation and disease occurrence in nervous system cells.Hypoxia regulation on alternative splicing has been reported,however,most of the work focused on the damage to the body caused by various tumor hypoxic microenvironment.The study of the protective mechanism under HPC on the basis of second-generation transcriptome data is rare.Therefore,in the present study,we developed a Wb HPC mouse model and HT22 cell model.High-throughput transcriptome sequencing techniques,bioinformatics analyses and molecular biology experiments were performed to elucidate the endogenous protective mechanisms of HPC.This work may provide useful help for clinical treatment of solid tumors,vascular diseases and other related diseases.The main research contents and results are as follows:(1)Establishment of WHPC mouse model.The WHPC mouse model was assessed via HE staining tissue morphology,oxidative stress factors testing and the expression levels quantifing of the HIF-1? and HO-1 under HPC.The results showed that the tolerance time of each run lasted significantly longer with an increase in the number of runs.The results of HE staining of the hippocampus CA1 region showed that pyramidal cell damage was alleviated after repeated exposure to systemic hypoxia.We detected the expression levels of the oxidative stress markers SOD and MDA in the Wb HPC mouse model.SOD activity increased and MDA content decreased in exposure to hypoxia for 1 run,2 run,3 run(H1,H2 and H3 group)compared with that in exposure to hypoxia for 0 run(H0 group).However,with continuous hypoxia exposure,SOD activity reduced and MDA content increased in exposure to hypoxia for 4 run(H4 group)compared with H3 group.The expression levels of HIF-1? and HO-1 under HPC were significantly increased in H4 group.To summarize,the Wb HPC mouse model can be used to elucidate the neuroprotective mechanisms of HPC and provide a basic model for further experiments.(2)On the basis of the WHPC mouse,we selected H0,H1 and H4 groups for transcriptome sequencing.Differentially expressed genes(DEGs)analysis were carried out with DESeq2 and edge R.To characterize DEGs functions systematically during the Wb HPC mouse model to systemic hypoxia,we performed Gene Ontology(GO)enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Furthermore,the q RT-PCR assays were performed to validate the 13 key DEGs.GO enrichment analysis showed that DEGs were mainly involved in regulating stress response,cell energy metabolism,anti-inflammatory response,angiogenesis and so on.KEGG enrichment analysis showed that DEGs were mainly involved in the regulation of cholinergic synapses,chemokine signaling pathways,cytokine receptor interactions,TNF,MAPK and other signaling pathways.(3)Clean reads were obtained by RNA-Seq and mapped to the mouse reference genome assembly(mm10)using Hisat2 and STAR software.DASGs in the H0,H1 and H4 groups were detected by r MATS software.We examined expression profile in Edrf1,Lrrc45,Rbm41 and ptk2 using semi-quantitative RT-PCR.GO enrichment analysis revealed that DASGs were mainly involved in the regulation of RNA splicing,RNA polymerase II transcription,histone deacetylation and other biological processes.KEGG enrichment analysis revealed that DASGs involved related signaling pathways such as glucose metabolism,glutamine metabolism,immunomodulation,and physiological rhythm regulation.The RBM41 m RNA level wasn't changed.However,repeated exposure to systemic hypoxia promoted exon skipping in Edrf1?Lrrc45 and ptk2.(4)To further understand the adaptive mechanism of mice in HPC,we developed HT22 HPC cell model.The HT22 cell model was assessed via the rate of cell survival,LDH leakage rate and oxidative stress.The q RT-PCR assays were performed to validate the DEGs including Hbb-bt,Nr4a1,Cyr61,Txnip,Dusp,Ddit4,Glut1 and the semi-quantitative RT-PCR were performed to validate DASGs in TUBD,Ndrg2,PLOD2,Edrf1 and Lrrc45.The results showed that,compared with H0 group,the cell survival rate decreased,the leakage rate of LDH increased,the activity of SOD increased,and the expression level of MDA decreased in H1 group,the cell survival rate increased significantly,LDH leakage rate decreased,SOD activity decreased and MDA expression level increased in H4 group.The relative expression level of DEGs increased significantly in H1 group compared with H0 group.The relative expression level of Txnip has no significant difference and Cyr61,Hbb-bt,Nr4a1,Dusp,Glut1 increased significantly in H4 group compared with H1 group.DASGs validation results showed that TUBD and PLOD2 m RNA levels were unchanged and the repeated exposure to systemic hypoxia promoted exon skipping in Ndrg2?Edrf1and Lrrc45 in H1 group compared with H0 group.Lrrc45 had no significant difference and the repeated exposure to systemic hypoxia promoted exon skipping in TUBD,Ndrg2,PLOD2 and Edrf1 in H4 group compared with H1 group.
Keywords/Search Tags:Hypoxia preconditioning, WHPC mouse model, HT22 cell model, Alternative splicing, Differentially expressed genes, Differential alternative splicing events
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