Expression profiling analysis of the metabolic and inflammatory changes following burn injury in rats

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Abstract

Burn injury initiates an inflammatory response as part of the healing process that is associated with extensive metabolic adjustments. While most studies have focused on understanding these changes from a biochemical perspective, not much work has been done to characterize these processes at the gene expression level. As a first step, we have comprehensively analyzed changes in gene expression in rat livers during the first 24 h after burn injury using Affymetrix GeneChips, which showed 339 genes to be differentially expressed at a statistical significance of P < 0.05 and changed at least twofold. Functional classification based on gene ontology terms indicated that two categories, metabolism (28%) and inflammation (14%), accounted for nearly 42%. Detailed analysis of the metabolism group of genes indicated that fatty acid (FA) and triglyceride (TG) biosynthesis in the liver were unchanged, whereas TG utilization, FA import, and β-oxidation increased after burn injury. The increased FA pools after burn injury appear to serve as substrates for ATP production. Following burn injury, the cholesterol biosynthetic pathway was suppressed while cholesterol was increasingly imported and converted into bile acids. The inflammatory gene's that were altered included several classic acute phase response markers, as well as genes involved in the complement, kinin, clotting, and fibrinolytic protein systems. These temporally coordinated changes in gene expression were also corroborated by biochemical measurements for FA, TG, cholesterol, and ATP. Together, these data indicate that FA are increasingly imported and oxidized in the liver to meet the enhanced energy demands arising from an inflammatory response during the first 24 h after burn injury.

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Vemula, M., Berthiaume, F., Jayaraman, A., & Yarmush, M. L. (2004). Expression profiling analysis of the metabolic and inflammatory changes following burn injury in rats. Physiological Genomics, 18, 87–98. https://doi.org/10.1152/physiolgenomics.00189.2003

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