Screening And Verification Of Differential Factors For Biliary Atresia By Transcriptomics Combined With Proteomics

Objective:Transcriptomics combined with proteomics was used to screen differentially expressed genes in liver tissue samples of biliary atresia（BA）and cholangiectasia（CC）with common expression tendencies at both transcription and translation levels,and further to explore the role of differentially expressed genes（DEGs）in the occurrence and development of liver fibrosis in biliary atresia.Methods:1.Three liver tissue samples from children with BA and three liver tissue samples from children with CC were collected.The high-throughput RNA sequencing technology was applied to detect and compare m RNA expression profiles in the liver tissue samples of the above 6 samples.The limma package in R language with|log₂fold change|1.0 or higher and adj.P-value<0.05 as filter conditions was used to filter differentially expressed m RNAs;2.DIA technology was used to quantitatively analyze protein expressions of the above 6 samples.The MSstats package in R language with adj.P-value<0.05 and the differences between multiple|log₂fold change|acuity 1.0 as screening conditions was used to screen differentially expressed proteins;3.Transcriptomics combined with proteomics was used to screen DEGs with common expression tendencies at both transcription and translation levels.GO function and KEGG pathway enrichment analysis were performed based on these DEG.Cytoscape software was use to construct protein interaction networks of these DEG;4.After expanding the sample size,RT-q PCR was used to verify the expression changes of the four differential genes including ALDH2,GSTP1,CASP1 and STAT1.Results:1.A total of 1348 differentially expressed m RNAs were screened by transcriptomics,among which 636 were up-regulated and 712 down-regulated;2.A total of 906 differentially expressed proteins were screened by proteomic analysis,among which 746 were up-regulated and 160 down-regulated;3.Transcriptomics combined with proteomics analysis of differential m RNAs and differential proteins obtained 62 DEGs with the same expression trendencies.GO analysis showed that these 62 differential expressed genes may be involved in small molecule catabolism,alcohol metabolism and cell response to toxic substances.KEGG enrichment analysis indicated that these 62differential expressed genes may be related to alcoholic liver disease,glycolysis/gluconeogenesis signaling pathways,etc.36 DEGs were found to form an interaction network through protein interaction network analysis,among which 10 DEGs（ADH1A,ADH4,ALDH2,GSTP1,CD44,STAT1,HMOX1,CASP1,AIF1 and GBP2）were closely related to each other;4.Based on literature investigation,four DEGs（ALDH2,GSTP1,CASP1 and STAT1）from the above 10 DEGs were chosen for experimental verification.After expanding the sample size,RT-q PCR detection showed that the transcription levels of GSTP1,CASP1 and STAT1 in BA group were significantly higher than those in control group（P<0.01）,and the transcription level of ALDH2 was significantly lower than that in control group（P<0.01）,which was consistent with our multi-omics data analysis.Conclusion:In this study,transcriptomics combined with proteomics analysis was used to obtain 62 DEGs in liver tissue samples of children with biliary atresia and choledochal cyst for the first time.Ten DEGs（ADH1A,ADH4,ALDH2,GSTP1,CD44,STAT1,HMOX1,CASP1,AIF1 and GBP2）may interact with each other.The expression changes of ALDH2,GSTP1,CASP1 and STAT1 were verified in clinical samples,which may be involved in the occurrence and development of biliary atresia.