[Differential gene expression and bioinformatics analysis in sepsis secondary to pneumonia]

To analyze and screen the key genes of sepsis secondary to pulmonary infection by bioinformatics, and to provide theoretical basis for the basic research of the disease and find an ideal animal model program.

Experiment 1 (bioinformatics analysis): gene expression data sets of pulmonary infection secondary sepsis patients and multiple sepsis animal models were screened by Gene Expression Omnibus (GEO) Database, and gene differences were analyzed by R software. Differential genes were analyzed by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Correlation analysis was conducted between differential genes and clinical symptoms in the data set of pulmonary infection secondary sepsis, and the correlation heat map between differential genes and clinical symptoms was drawn. Key genes were screened by weighted gene co-expression network analysis (WGCNA) and protein-protein interaction network analysis (PPIN) clustering. Experiment 2 (sepsis animal model preparation): male mice weighing 21-25 g were randomly divided into the key genes group and the control (Sham) group. And cecal ligation and puncture (CLP) was used to establish mouse sepsis model, while the mice in sham group were performed by exposure of cecum. And all the mice were scarified 24 hours after surgery to extract the total RNA from lung tissue, real time fluorescent quantitative polymerase chain reaction (RT-qPCR) was used to detect mRNA expression of key genes.

Experiment 1 (bioinformatics analysis): 319 differential genes were showed by GSE 134364 and GSE 65682 data set analysis of pulmonary infection secondary sepsis. And there was no genetic difference between community acquired pneumonia (CAP) and hospital acquired pneumonia (HAP) in patients with pulmonary infection secondary to sepsis. Obvious differences existed between differential genes in animal models, and there was no common differential gene. Differential genes in patients and animal models were similarly enriched in GO function, mainly in cell differentiation, regulation of cell process, and regulation of cellular response to stimuli, there were significant differences in pathway enrichment, among which, CLP animal models showed higher consistency with patients. The key genes obtained by WGCNA and PPIN analysis were MAPK14, NLRC4 and LCN2. Experiment 2 (sepsis animal model preparation): animal experiment results showed that the mRNA expressions of MAPK14, NLRC4 and LCN2 in lung tissue of CLP model mice were significantly up-regulated compared with the sham group.

MAPK14, NLRC4 and LCN2 are key genes involved in the regulation of biological processes of pulmonary sepsis secondary to infection, and are potential research directions of this disease. What's more, CLP animal model can better reflect the biological characteristics of patients with pulmonary infection secondary sepsis, and is one of the ideal animal model schemes for pulmonary infection secondary sepsis.