Screening Biomarkers Related With Leukocyte Responses Early Post-burn Injury:Analysis Of Differentially Gene Expression Profiling Data And Detection In Mice

BackgroundSevere burns could cause immune dysfunction which is considered to be one of the important factors of causing a variety of complications such as multiple organ dysfunction syndrome(MODS)and systemic inflammatory response syndrome(SIRS)in patients.The current burning immune research has focused on cells,the mechanism of immune factors or infection,organ damage and other aspects.There is rarely research or analysis focused on the changes of gene transcription of post burn in depth.The analysis of gene chip data and application of bioinformatics technology can help us to find new diagnostic and therapeutic target in the early after burn injury.We had found that circulating leukocyte in mice showed a series of dysfunction of biological process post burn by bioinformatics analysis of the gene expression profiling data,and the function of immune system process,response to stimulus were altered throughout the whole process of the early after burn injury,some studies showed that Myd88,Stat3,Statl,Jun gene may play important roles related stimulation post burn.So,to enhance our understanding of the regulatory mechanisms of the molecular related immune genes after burn,and to screen the genes related with leukocyte responses in mice and identifie several potential biomarkers for burn treatment,we will use the bioinformatic analysis of the gene expression profiling data to select the differentially expressed genes(DEGs)related to leukocyte responses to burns,then the genes were transferred to STRING to construct the protein-protein interaction(PPI)network.Biological annotation of the sub-networks was executed using the software Cytoscape.Western blotting was used to verify the DEGs identified in mice.ObjectivesTo screen the genes related with leukocyte responses in mice early after burn injury by bioinformatic analysis of the gene expression profiling data.Real-time PCR and western blotting were used to detect the expression of those genes.Methods1.Description and analysis of date setsWe download the GSE7404 microarray expression profile from the Gene Expression Omnibus database.We extracted the raw files on thermal injury(MUS musculus,25%TBSA,full thickness)at 1 day post burn for further analysis,a total of 8 samples were available,including 4 thermal injury samples and 4 controls.2.Identification of differentially expressed genes(DEG)Statistical analyses were performed using open-source software R3.02 version.Background correction were performed with the robust multiarray average(RMA)to obtain expression profile data,Student's t-test and ratio method(fold change FC)were used to identify differentially expressed genes between thermal injury and controls.3.Functional enrichment analysis and post burn protein-protein interaction network related immune process constructionThe DEGs were submitted to the Search Tool for the Retrieval of Interacting Genes(STRING)9.1 after implementing in the DAVID tool.,the interaction scores of at least 0.4(Medium confidence)were selected to construct protein-protein interaction network(PPI),then Gene Ontology gene(GO)enrichment analysis were used to select the gene related immune process.The Markov Cluster(MCL)algorithm was applied to identify disease-related modules,and the Cytoscape Network Analysis plugin was used to calculate the degrees of nodes in the network.4.Detection of the expression of the DEGs related immune process for post burn in mice32 adult BALB/c mice(by the experimental Animal Center of Southern Medical University)were selected and randomly divided into two groups,one is controls,another is 1 day post burn.The model of third-degree burn wound was designed on the hairless area of 4cmx4cm with 97? hot water for 15 seconds after anesthetized with 1%pentobarbital sodium.We used real-time PCR and western blotting to analysis the expression of LCK?CDK1?JUN?CD19 and STAT1 in whole blood leukocytes of mice.5 Statistical analyses:Statistical analyses were performed using open-source Statistical software R version 3.02 and SPSS 19.0.The gene expression profile data were recalculated and normalized using the Robust Multi-array Average(RMA)algorithm.The Student's t-test and the fold-change(FC)method were used to select DEGs between burn injury and sham burn controls.All genes with P-values<0.01 and|logFC|>1 were set as the cutoff values to identify DEGs for further analysis.The differences of expression of DEGs were performed by One Way ANOVA.Results1 The results of gene chip analysisOf 1825 immune system process-related DEGs screened at 1 day post-burn,including 658 up-regulated genes and 1167 down regulated genes.2 Construction and analysis of protein-protein interaction networkThe network has 1211 nodes and 5176 sides.The genes in the centre of the interaction network with higher degrees may play an important role in the progression of the disease.We found that in this network,STAT1,JUN,LCK,CD40,STAT3,CD19,CD86,CDKn1a,CDK1 and Ptpn6 genes are in the center of the network and have the highest degree.Using BinGo,we found that LCK,CDK1,JUN,CD 19 and STAT1 of the 5 genes occupy central positions in the MCL network module,have higher degrees and may play important roles in the process of di sease.3.Detection of the expression of the DEGsThe expression of JUN and CDK1 were significantly higher than sham group(P<0.01),while the expression of STAT1 was significantly lower(P<0.01)at 1 day post burn,the differences were statistically significant and consistent with those bioinformatic analysis.But the expression of LCK and CD 19 are not consistent with those bioinformatic analysis,and there is no significant difference comparing with group sham(P>0.05).Conclusion1.The circulating leukocyte in mice showed a series of dysfunction of biological process post burn2.STAT1,JUN,LCK,CD40,STAT3,CD19,CD86,CDKn1a,CDK1 and Ptpn6 genes are in the center of the network and have the highest degree.Using BinGo we found that LCK,CDK1,JUN,CD19 and STAT1 occupy a central position in the PPI network related to immune system process,they may play important roles in the changes of immune system function early after burn injury.3.RT-PCR and Western blotting results were consistent with those bioinformatic analysis of STAT1,CDK1 and JUN.but not consistent with those bioinformatic analysis of LCK and CD19.These results indicate that STAT1,JUN and CDK1 genes might be critical players in the development of leukocyte response in mice early after burn injury Our finding provides new insights into the pathogenesis of leukocyte response to burn injury and identifies several potential biomarkers for burn treatment.