Bioinformatic identification of novel early stress response genes in rodent models of lung injury

Abstract
Acute lung injury is a complex illness with a high mortality rate (>30%) and often requires the use of mechanical ventilatory support for respiratory failure. Mechanical ventilation can lead to clinical deterioration due to augmented lung injury in certain patients, suggesting the potential existence of genetic susceptibility to mechanical stretch ( 6 , 48 ), the nature of which remains unclear. To identify genes affected by ventilator-induced lung injury (VILI), we utilized a bioinformatic-intense candidate gene approach and examined gene expression profiles from rodent VILI models (mouse and rat) using the oligonucleotide microarray platform. To increase statistical power of gene expression analysis, 2,769 mouse/rat orthologous genes identified on RG_U34A and MG_U74Av2 arrays were simultaneously analyzed by significance analysis of microarrays (SAM). This combined ortholog/SAM approach identified 41 up- and 7 downregulated VILI-related candidate genes, results validated by comparable expression levels obtained by either real-time or relative RT-PCR for 15 randomly selected genes. K-mean clustering of 48 VILI-related genes clustered several well-known VILI-associated genes (IL-6, plasminogen activator inhibitor type 1, CCL-2, cyclooxygenase-2) with a number of stress-related genes (Myc, Cyr61, Socs3). The only unannotated member of this cluster ( n = 14) was RIKEN_1300002F13 EST, an ortholog of the stress-related Gene33/Mig-6 gene. The further evaluation of this candidate strongly suggested its involvement in development of VILI. We speculate that the ortholog-SAM approach is a useful, time- and resource-efficient tool for identification of candidate genes in a variety of complex disease models such as VILI.