Objective By using bioinformatics methods, we screened the core pathogenic genes and main signaling pathways of GP from related datasets, and predicted potential therapeutic targets and effective intervention Chinese herbal medicines.

Method GP-related targets were collected from the GeneCards database and standardized via the Uniprot database. The intestinal inflammation dataset (GSE14841) and the malnutrition dataset (GSE43698) from the Gene Expression Omnibus (GEO) were extracted and combined. The differentially expressed genes (DEGs) of GP were screened using the Limma package in R language. The DAVID database was used for GO analysis and KEGG enrichment analysis of DEGs. The STRING database was used to construct the protein-protein interaction network (PPI), and the Cytoscape software and its plugins were used to screen the core genes of the sub-network. The core genes were mapped with the Coremine Medical database to screen for potential traditional Chinese medicines that could treat GP.

Result A total of 58 DEGs were screened out. The results of enrichment analysis showed that the DEGs were mainly involved in biological processes such as the recognition of viral proteins by the host cell membrane receptors, and the activities of cytoplasmic hydrolases and transferases. They were located in the actin cytoskeleton (AC), the cytosolic DNA-Sensing and the STING (cGAS-STING), mitogen-activated protein kinase (MARK) and toll-like receptor (TLR) signaling pathways. Through the PPI, the top 10 key genes in terms of the Degree value were identified: interferon induced with helicase C domain 3 (IFIH3), interferon induced with helicase C domain 1 (IFIH1), mitochondrial antiviral signaling protein (MAVS), C-C motif chemokine ligand 5 (CCL5), toll-like receptor 4 (TLR4), nuclear factor-kappa B (NF-κB), ras-related C3 botulinum toxin substrate 2 (RAC2), toll-like receptor 9 (TLR9), early growth response 1 (EGR1), erb-B2 receptor tyrosine kinase 3 (ERBB3). TLR4, TLR9, NF-κB and ERBB3 were the four core genes identified in the inflammatory response to GP infection. A total of 50 potential traditional Chinese medicines for treating GP were predicted, and the categories of traditional Chinese medicines mainly included four types such as heat-clearing and detoxifying medicines, tonifying deficiency medicines, exterior-releasing medicines, and astringent antidiarrheal medicines.

Conclusion This study applied bioinformatics methods to identify four core genes related to GP and 50 potential targeted traditional Chinese medicines, providing new ideas and theoretical basis for the development of natural medicines for the prevention and treatment of GP.