Molecular signatures of sepsis - Multiorgan gene expression profiles of systemic inflammation

During sepsis the host's system-wide response to microbial invasion seems dysregulated. Here we explore the diverse multiorgan transcriptional programs activated during systemic inflammation in a cecal ligation/puncture model of sepsis in rats. Using DNA microarrays representing 7398 genes, we examined the temporal sequence of sepsis-induced gene expression patterns in major organ systems including lung, liver, kidney, thymus, spleen, and brain. Although genes known to be associated with systemic inflammation were identified by our global transcript analysis, many genes and expressed sequence tags not previously linked to the septic response were also elucidated. Taken together, our results suggest activation of a highly complex transcriptional response in individual organs of the septic animal. Several overlying themes emerged from our genome-scale analysis that includes 1) the sepsis response elicited gene expression profiles that were either organ-specific, common to more than one organ, or distinctly opposite in some organs; 2) the brain is protected from sepsis-induced gene activation relative to other organs; 3) the thymus and spleen have an interesting cohort of genes with opposing gene expression patterns; 4) genes with proinflammatory effects were often balanced by genes with anti-inflammatory effects (eg, interfeukin-1 beta /decoy receptor, xanthine oxidase/superoxide dismutase, Ca2+-dependent PLA(2)/Ca2+-independent PLA(2)); and 5) differential gene expression was observed in proteins responsible for preventing tissue injury and promoting homeostasis including anti-proteases (TIMP-1, Cpi-26), oxidant neutralizing enzymes (metallothionein), cytokine decoy receptors (interleukin-1RII), and tissue/vascular permeability factors (aquaporin 5, vascular endothelial growth factor). This global perspective of the sepsis response should provide a molecular framework for future research into the pathophysiology of systemic inflammation. Understanding, on a genome scale, how an organism responds to infection, may facilitate the development of enhanced detection and treatment modalities for sepsis.