Investigating the Molecular Function of Gene Expression in Relation to Respiratory Syncytial Virus Infections

Studies have shown that up to 68% of infants may be infected with respiratory syncytial virus (RSV) in their first year of life, and almost all children are infected by the age of two. In this study, using bioinformatics analysis, the genes in the pathways related to respiratory syncytial virus (RSV) infection were examined and nominated.

By referring to the GEO database, the appropriate dataset was selected for analysis. This dataset included gene expression profiles in respiratory syncytial virus (RSV) infection. Gene clusters with high and low expression were categorized. Rich databases such as Enrichr, STRING, and Panther were used for more accurate data evaluation. Finally, the candidate genes were isolated, and their protein relationship was also measured.

A total of 740 and 822 genes had high and low expressions, respectively. These genes can play a role in RSV infection pathways in children. The NOD-like receptor, Epstein-Barr-influenza, tuberculosis, leishmaniasis, necroptosis, and salmonella pathways are highly expressed, and the pathways of coronavirus, herpes virus, immune system deficiency, Th1 lymphocyte cell receptor, ribosome, NFKappa B, and PDL1 had low expression at checkpoints of the cell cycle.

The present study revealed that important proteins and genes played a major role in strengthening RSV inflammation in children, among which STAT3, TLR4, RPL26A, STAT1, and MAPK4 showed a more prominent role in this pathway.