Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury
Lisa E. Gralinski,
Armand Bankhead,
Sophia Jeng,
Vineet D. Menachery,
Sean Proll,
Sarah E. Belisle,
Melissa Matzke,
Bobbie-Jo M. Webb-Robertson,
Maria L. Luna,
Anil K. Shukla,
Martin T. Ferris,
Meagan Bolles,
Jean Chang,
Lauri Aicher,
Katrina M. Waters,
Richard D. Smith,
Thomas O. Metz,
G. Lynn Law,
Michael G. Katze,
Shannon McWeeney,
Ralph S. Baric
Affiliations
Lisa E. Gralinski
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Armand Bankhead
Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Portland, Oregon, USA
Sophia Jeng
Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Portland, Oregon, USA
Vineet D. Menachery
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Sean Proll
Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA
Sarah E. Belisle
Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA
Melissa Matzke
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
Bobbie-Jo M. Webb-Robertson
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
Maria L. Luna
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
Anil K. Shukla
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
Martin T. Ferris
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Meagan Bolles
Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Jean Chang
Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA
Lauri Aicher
Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA
Katrina M. Waters
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
Richard D. Smith
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
Thomas O. Metz
Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA
G. Lynn Law
Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA
Michael G. Katze
Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA
Shannon McWeeney
Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Portland, Oregon, USA
Ralph S. Baric
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
ABSTRACT Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV. IMPORTANCE Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI.
