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mBio. Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury
[Source: mBio, full page: (LINK). Abstract, edited.]
Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury
Lisa E. Gralinski<SUP>a</SUP>, Armand Bankhead III<SUP>b</SUP>, Sophia Jeng<SUP>b</SUP>, Vineet D. Menachery<SUP>a</SUP>, Sean Proll<SUP>c</SUP>, Sarah E. Belisle<SUP>c</SUP>, Melissa Matzke<SUP>d</SUP>, Bobbie-Jo M. Webb-Robertson<SUP>d</SUP>, Maria L. Luna<SUP>d</SUP>, Anil K. Shukla<SUP>d</SUP>, Martin T. Ferris<SUP>e</SUP>, Meagan Bolles<SUP>f</SUP>, Jean Chang<SUP>c</SUP>, Lauri Aicher<SUP>c</SUP>, Katrina M. Waters<SUP>d</SUP>, Richard D. Smith<SUP>d</SUP>, Thomas O. Metz<SUP>d</SUP>, G. Lynn Law<SUP>c</SUP>, Michael G. Katze<SUP>c,g</SUP>, Shannon McWeeney<SUP>b</SUP>, Ralph S. Baric<SUP>a,f</SUP>
<SUP></SUP>
Author Affiliations: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA<SUP>a </SUP>Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Portland, Oregon, USA<SUP>b </SUP>Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA<SUP>c </SUP>Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA<SUP>d </SUP>Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA<SUP>e </SUP>Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA<SUP>f </SUP>Washington National Primate Research Center, University of Washington, Seattle, Washington, USA<SUP>g</SUP>
<SUP></SUP>
Address correspondence to Ralph S. Baric, rbaric@email.unc.edu.
Editor Terence Dermody, Vanderbilt University School of Medicine
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.
Footnotes
Citation Gralinski LE, Bankhead A, III, Jeng S, Menachery VD, Proll S, Belisle SE, Matzke M, Webb-Robertson B-JM, Luna ML, Shukla AK, Ferris MT, Bolles M, Chang J, Aicher L, Waters KM, Smith RD, Metz TO, Law GL, Katze MG, McWeeney S, Baric RS. 2013. Mechanisms of severe acute respiratory syndrome coronavirus-induced acute lung injury. mBio 4(4):e00271-13. doi:10.1128/mBio.00271-13.
Received 18 April 2013 - Accepted 9 July 2013 - Published 6 August 2013
Copyright ? 2013 Gralinski et al.
This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury
Lisa E. Gralinski<SUP>a</SUP>, Armand Bankhead III<SUP>b</SUP>, Sophia Jeng<SUP>b</SUP>, Vineet D. Menachery<SUP>a</SUP>, Sean Proll<SUP>c</SUP>, Sarah E. Belisle<SUP>c</SUP>, Melissa Matzke<SUP>d</SUP>, Bobbie-Jo M. Webb-Robertson<SUP>d</SUP>, Maria L. Luna<SUP>d</SUP>, Anil K. Shukla<SUP>d</SUP>, Martin T. Ferris<SUP>e</SUP>, Meagan Bolles<SUP>f</SUP>, Jean Chang<SUP>c</SUP>, Lauri Aicher<SUP>c</SUP>, Katrina M. Waters<SUP>d</SUP>, Richard D. Smith<SUP>d</SUP>, Thomas O. Metz<SUP>d</SUP>, G. Lynn Law<SUP>c</SUP>, Michael G. Katze<SUP>c,g</SUP>, Shannon McWeeney<SUP>b</SUP>, Ralph S. Baric<SUP>a,f</SUP>
<SUP></SUP>
Author Affiliations: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA<SUP>a </SUP>Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Portland, Oregon, USA<SUP>b </SUP>Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, USA<SUP>c </SUP>Oregon Clinical and Translational Research Institute, Oregon Health Sciences University, Portland, Oregon, USA<SUP>d </SUP>Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA<SUP>e </SUP>Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA<SUP>f </SUP>Washington National Primate Research Center, University of Washington, Seattle, Washington, USA<SUP>g</SUP>
<SUP></SUP>
Address correspondence to Ralph S. Baric, rbaric@email.unc.edu.
Editor Terence Dermody, Vanderbilt University School of Medicine
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.
Footnotes
Citation Gralinski LE, Bankhead A, III, Jeng S, Menachery VD, Proll S, Belisle SE, Matzke M, Webb-Robertson B-JM, Luna ML, Shukla AK, Ferris MT, Bolles M, Chang J, Aicher L, Waters KM, Smith RD, Metz TO, Law GL, Katze MG, McWeeney S, Baric RS. 2013. Mechanisms of severe acute respiratory syndrome coronavirus-induced acute lung injury. mBio 4(4):e00271-13. doi:10.1128/mBio.00271-13.
Received 18 April 2013 - Accepted 9 July 2013 - Published 6 August 2013
Copyright ? 2013 Gralinski et al.
This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
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