lncRNA IL-17RA-1 Attenuates LPS-Induced Sepsis via miR-7847-3p/PRKCG-Mediated MAPK Signaling Pathway

Sepsis represents a syndrome of systemic inflammatory response, which is mostly a result of infection with various pathogenic microorganisms, characterized by an uncontrolled infection response of the organism leading to life-threatening organ dysfunction. Long noncoding RNA (lncRNA), as competing endogenous RNA, can affect the binding of microRNA (miRNA) to mRNA, thus influencing the development of sepsis. In this study, based on transcriptome data from GEO database, we screened differentially expressed lncRNAs and constructed lncRNA-miRNA-mRNA network. And pathway IL-17RA-1/miR-7847-3p/protein kinase C gamma (PRKCG) coexpression network was successfully sorted out. The effect of this network on LPS-induced sepsis model in THP-1 cells was also verified by CCK-8, scratch, ELISA, Western blot, and qRT-PCR assays. Corresponding binding sites of miR-7847-3p to IL-17RA-1 and miR-7847-3p to PRKCG were verified using dual luciferase gene reporter assays, respectively. Compared with control, si-IL-17RA-1 significantly inhibited the cell viability and migration ability of THP-1, and levels of proinflammatory factors IL-6, IL-1 beta, and TNF-alpha secreted were markedly decreased, and the expression of IL-17RA-1, PRKCG, p-MEKK1, and p-JNK were markedly reduced. In addition, IL-17RA-1 could target binding to miR-7847-3p and inhibit its expression, and miR-7847-3p could also bind to PRKCG. Our experiments demonstrate that IL17-RA-1 attenuates the sepsis response through the miR-7847-3p/MAPK pathway, and this competing endogenous RNA (ceRNA) network may be a potential approach to predict and combat sepsis.

Automated summary

This study screened differentially expressed lncRNAs and constructed an lncRNA-miRNA-mRNA network based on transcriptome data. It identified the IL-17RA-1/miR-7847-3p/PRKCG coexpression network and verified its effect in an LPS-induced sepsis model. The findings suggest that this competing endogenous RNA (ceRNA) network may be a potential approach to predict and combat sepsis.