Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with septic cardiomyopathy being a common and severe complication. Despite its significant clinical impact, the molecular mechanisms underlying sepsis-induced cardiomyopathy (SICM) remain incompletely understood. In this study, we performed a comparative analysis of whole transcriptome profiles using RNA sequencing in mouse hearts in two widely used mouse models of septic cardiomyopathy. CLP-induced sepsis was achieved by surgical cecal ligation and puncture, while LPS-induced sepsis was induced using a 5 mg/kg intraperitoneal (IP) injection of lipopolysaccharide (LPS). For consistency, we utilized sham-operated mice as the control for septic models. Our aim was to identify key genes and pathways involved in the development of septic cardiomyopathy and to evaluate the similarities and differences between the two models. Our findings demonstrated that both the CLP and lipopolysaccharide LPS methods could induce septic heart dysfunction within 24 h. We identified common transcriptional regulatory regions in the septic hearts of both models, such as Nfkb1, Sp1, and Jun. Moreover, differentially expressed genes (DEGs) in comparison to control were involved in shared pathways, including regulation of inflammatory response, regulation of reactive oxygen species metabolic process, and the JAK-STAT signaling pathway. However, each model presented distinctive whole transcriptome expression profiles and potentially diverse pathways contributing to sepsis-induced heart failure. This extensive comparison enhances our understanding of the molecular basis of septic cardiomyopathy, providing invaluable insights. Accordingly, our study also contributes to the pursuit of effective and personalized treatment strategies for SICM, highlighting the importance of considering the specific causative factors.
Keywords: cecal ligation and puncture; gene sequencing; lipopolysaccharide; sepsis-induced cardiomyopathy; septic animal models; whole transcriptome profiles.