Published ahead of print on December 30, 2005, doi:10.1164/rccm.200509-1473OC
© 2006 American Thoracic Society doi: 10.1164/rccm.200509-1473OC
Computational Identification of Key Biological Modules and Transcription Factors in Acute Lung InjuryDepartments of Medicine, Physiology and Biophysics, and Pathology, University of Washington; and the Veterans Affairs Puget Sound Healthcare System Medical Research Service, Seattle, Washington Correspondence and requests for reprints should be addressed to Sina A. Gharib, M.D., Box 356522, 1959 NE Pacific Street, Seattle, WA 98195-6522. E-mail: sagharib{at}u.washington.edu Rationale: Mechanical ventilation augments the acute lung injury (ALI) caused by bacterial products. The molecular pathogenesis of this synergistic interaction remains incompletely understood. Objective: We sought to develop a computational framework to systematically identify gene regulatory networks activated in ALI. Methods: We have developed a mouse model in which the combination of mechanical ventilation and intratracheal LPS produces significantly more injury to the lung than either insult alone. We used global gene ontology analysis to determine overrepresented biological modules and computational transcription factor analysis to identify putative regulatory factors involved in this model of ALI. Results: By integrating expression profiling with gene ontology and promoter analysis, we constructed a large-scale regulatory modular map of the important processes activated in ALI. This map assigned differentially expressed genes to highly overrepresented biological modules, including "defense response," "immune response," and "oxidoreductase activity." These modules were then systematically incorporated into a gene regulatory network that consisted of putative transcription factors, such as IFN-stimulated response element, IRF7, and Sp1, that may regulate critical processes involved in the pathogenesis of ALI. Conclusions: We present a novel, unbiased, and powerful computational approach to investigate the synergistic effects of mechanical ventilation and LPS in promoting ALI. Our methodology is applicable to any expression profiling experiment involving eukaryotic organisms.
Key Words: acute lung injury • gene network • microarray • transcription factor This article has been cited by other articles:
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