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Published on: May 2, 2018
Insights into transcriptomic changes in blood of a mouse model of LPS-induced peritonitis
Huijuan Li1, Jianfeng Zhang2, Yulong Sun3
1School of Electrical Engineering, Shaanxi Polytechnic University, Xianyang 712000, China.
LPS-induced peritonitis is a prevalent clinical condition with incompletely understood underlying mechanisms. This study aimed to characterize the gene transcriptome and key proteins in the blood of mice with LPS-induced peritonitis. We established a mouse peritonitis model by administering LPS (10 mg/kg, i.p.) and collected blood samples (n = 6 per group) for bulk RNA sequencing. Through various bioinformatics approaches, we identified 290 differentially expressed genes (242 upregulated and 48 downregulated). Functional enrichment revealed the activation of inflammation-related pathways (e.g., NOD-like and Toll-like receptor signaling) and the suppression of adaptive immunity pathways (e.g., Th1/Th2 cell differentiation and T cell receptor signaling). From these, eight hub proteins (LDLR, FNBP1L, SNX18, FAM20C, INPP5F, PACSIN1, ZAP70, and SYNJ2) were identified, and their structural stability was confirmed via 300 ns molecular dynamics simulations. Critically, to validate our findings at the cellular level and in a clinical context, we further integrated four independent public single-cell RNA-sequencing datasets from human sepsis patients. This cross-platform analysis confirmed that the expression patterns of our hub genes are conserved in human patients with high cell-type specificity (e.g., ZAP70 downregulation in T cells and LDLR upregulation in monocytes). Moreover, a module score derived from these genes demonstrated strong clinical relevance, as it significantly distinguished sepsis patients from healthy controls and stratified clinical subtypes of sepsis. In conclusion, by integrating bulk transcriptomics, molecular dynamics, and cross-platform single-cell data, this research provides multi-scale insights into the systemic inflammatory mechanisms of peritonitis. It identifies therapeutic targets with clinical translational potential.
LPS-induced peritonitis is a prevalent clinical condition with incompletely understood underlying mechanisms. This study aimed to characterize the gene transcriptome and key proteins in the blood of mice with LPS-induced peritonitis. We established a mouse peritonitis model by administering LPS (10 mg/kg, i.p.) and collected blood samples (n = 6 per group) for bulk RNA sequencing. Through various bioinformatics approaches, we identified 290 differentially expressed genes (242 upregulated and 48 downregulated). Functional enrichment revealed the activation of inflammation-related pathways (e.g., NOD-like and Toll-like receptor signaling) and the suppression of adaptive immunity pathways (e.g., Th1/Th2 cell differentiation and T cell receptor signaling). From these, eight hub proteins (LDLR, FNBP1L, SNX18, FAM20C, INPP5F, PACSIN1, ZAP70, and SYNJ2) were identified, and their structural stability was confirmed via 300 ns molecular dynamics simulations. Critically, to validate our findings at the cellular level and in a clinical context, we further integrated four independent public single-cell RNA-sequencing datasets from human sepsis patients. This cross-platform analysis confirmed that the expression patterns of our hub genes are conserved in human patients with high cell-type specificity (e.g., ZAP70 downregulation in T cells and LDLR upregulation in monocytes). Moreover, a module score derived from these genes demonstrated strong clinical relevance, as it significantly distinguished sepsis patients from healthy controls and stratified clinical subtypes of sepsis. In conclusion, by integrating bulk transcriptomics, molecular dynamics, and cross-platform single-cell data, this research provides multi-scale insights into the systemic inflammatory mechanisms of peritonitis. It identifies therapeutic targets with clinical translational potential.
