Bioinformatics analysis of sequential gene expression profiling after skin and skeletal muscle wound in mice

It is of great value to use bioinformatics methods to screen the core differentially expressed genes (DEGs) at different times after mouse skin and skeletal muscle wound, and to explore the relationship between them and the wound age. To this end, we downloaded the gene expression profiles of GSE140517 and GSE23006 from the NCBI-GEO gene database, used GEO2R online tools and Venn diagrams to screen out DEGs at different times and common-DEGs. The Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) channel analysis were carried out through the DAVID website respectively. Use STRING tool to build a Protein-protein Interaction (PPI) network, and use Cytoscape software to screen out core DEGs. The results showed that 13, 53, 43 and 13 core DEGs were screened out in the 6 h, 12 h, 24 h and common-DEGs group after wound. There were 7 core DEGs (Cxcl2, Cxcl3, Il1b, Ptgs2, Cxcl1, Timp1, Ccl3) in both the different time point and the common DEGs group. Meanwhile, there are 1 core DEGs (Ccl4) specifically expressed in the 6 h, 29 specifically expressed core DEGs (Isg20, Rtp4, Fcgr1, Ifi44, Trim30a, etc.) in the 12 h, and 18 specifically expressed core DEGs (Ccr7, Myd88, Igsf6, Ccr2, Gpsm3, etc.) in the 24 h, there are 6 core DEGs (Ccl4, Ccl7, Saa3, Cxcl5, Ccl2, Lcn2) specifically expressed in the common-DEGs group. The results of GO and KEGG analysis showed that the deterioration and exudation of the inflammatory response were the main cause at 6 h after wound. In addition to inflammation at 12 h and 24 h, the systemic immune response against viral and bacterial infections also gradually increased. In summary, the core DEGs selected in this study have combined characteristics, consistent with the healing function at the corresponding time point, and they are also has specificity and correlation with wound age. Therefore, by detecting the changes in the expression of co-expressed core DEGs at different times after wound, as well as detecting specific expressed DEGs at a specific time point or a specific period of time, it is very promising to provide help for the wound age estimation. However, limited by the GSE140517 gene expression profile in the database, only the difference in gene expression at different times within 24 h after wound was explored, and the research on the late wound age still needs to be further in-depth.