Sepsis gene expression profiling: murine splenic compared with hepatic responses determined by using complementary DNA microarrays.

OBJECTIVE

DNA microarrays allow genome-wide assessment of changes in relative messenger RNA abundance and thus can be used to monitor changes in gene expression. The aim of this series of experiments was to gain experience in sepsis gene expression profiling in a well-accepted model of murine polymicrobial abdominal sepsis and begin characterizing (in the parlance of genomics) the sepsis "transcriptome."

DESIGN

Prospective animal study.

SETTING

University-based animal research facility.SUBJECTS C57BL/6 mice.

INTERVENTIONS: After induction of general anesthesia, cecal ligation and puncture were performed to induce peritonitis and polymicrobial sepsis. The control group had sham laparotomy only. Three samples of spleen and liver were collected from septic and sham animals at 24 hrs after laparotomy. Changes in expression were measured for 588 annotated mouse genes by using a commercially available complementary DNA microarray kit.

MEASUREMENTS AND MAIN

RESULTS

Broad-scale gene expression profiles were characterized for septic liver and spleen and compared with sham controls. The analytical tools used included commercially available software packages and a novel analysis program. Very little overlap was observed in the septic gene expression profiles of these two organs. Most of the genes identified have previously been linked to regulation of the inflammatory response; importantly, however, some have not. In addition, hierarchical cluster analysis showed that cecal ligation and puncture at 24 hrs induced coordinate expression of genes that alter cell signaling and survival pathways in spleen, consistent with previously published reports of sepsis-induced splenocyte apoptosis. The current limitations of microarray analysis as reflected in these studies are also discussed.

CONCLUSIONS

Microarray technology provides a powerful new tool for rapidly analyzing tissue-specific changes in gene expression induced by sepsis in animal models. To our knowledge, these data constitute the first report on the use of microarrays to determine the sepsis transcriptome.