Mechanisms of severe acute respiratory syndrome coronavirus-induced acute lung injury.
Identifieur interne : 001152 ( PubMed/Corpus ); précédent : 001151; suivant : 001153Mechanisms of severe acute respiratory syndrome coronavirus-induced acute lung injury.
Auteurs : 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. BaricSource :
- mBio [ 2150-7511 ] ; 2013.
English descriptors
- KwdEn :
- Acute Lung Injury (pathology), Acute Lung Injury (virology), Animals, Blood Coagulation, Disease Models, Animal, Fibrinolysis, Gene Expression Profiling, Host-Pathogen Interactions, Lung (pathology), Lung (virology), Mice, Mice, Inbred C57BL, Mice, Knockout, Proteome (analysis), SARS Virus (pathogenicity), Time Factors, Urokinase-Type Plasminogen Activator (genetics), Urokinase-Type Plasminogen Activator (metabolism).
- MESH :
- chemical , analysis : Proteome.
- chemical , genetics : Urokinase-Type Plasminogen Activator.
- chemical , metabolism : Urokinase-Type Plasminogen Activator.
- pathogenicity : SARS Virus.
- pathology : Acute Lung Injury, Lung.
- virology : Acute Lung Injury, Lung.
- Animals, Blood Coagulation, Disease Models, Animal, Fibrinolysis, Gene Expression Profiling, Host-Pathogen Interactions, Mice, Mice, Inbred C57BL, Mice, Knockout, Time Factors.
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.
DOI: 10.1128/mBio.00271-13
PubMed: 23919993
Links to Exploration step
pubmed:23919993Le document en format XML
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Baric</name></author></analytic><series><title level="j">mBio</title><idno type="eISSN">2150-7511</idno><imprint><date when="2013" type="published">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Acute Lung Injury (pathology)</term><term>Acute Lung Injury (virology)</term><term>Animals</term><term>Blood Coagulation</term><term>Disease Models, Animal</term><term>Fibrinolysis</term><term>Gene Expression Profiling</term><term>Host-Pathogen Interactions</term><term>Lung (pathology)</term><term>Lung (virology)</term><term>Mice</term><term>Mice, Inbred C57BL</term><term>Mice, Knockout</term><term>Proteome (analysis)</term><term>SARS Virus (pathogenicity)</term><term>Time Factors</term><term>Urokinase-Type Plasminogen Activator (genetics)</term><term>Urokinase-Type Plasminogen Activator (metabolism)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Proteome</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Urokinase-Type Plasminogen Activator</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Urokinase-Type Plasminogen Activator</term></keywords><keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="pathology" xml:lang="en"><term>Acute Lung Injury</term><term>Lung</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Acute Lung Injury</term><term>Lung</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Blood Coagulation</term><term>Disease Models, Animal</term><term>Fibrinolysis</term><term>Gene Expression Profiling</term><term>Host-Pathogen Interactions</term><term>Mice</term><term>Mice, Inbred C57BL</term><term>Mice, Knockout</term><term>Time Factors</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">23919993</PMID><DateCompleted><Year>2014</Year><Month>01</Month><Day>22</Day></DateCompleted><DateRevised><Year>2020</Year><Month>04</Month><Day>04</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2150-7511</ISSN><JournalIssue CitedMedium="Internet"><Volume>4</Volume><Issue>4</Issue><PubDate><Year>2013</Year><Month>Aug</Month><Day>06</Day></PubDate></JournalIssue><Title>mBio</Title><ISOAbbreviation>mBio</ISOAbbreviation></Journal><ArticleTitle>Mechanisms of severe acute respiratory syndrome coronavirus-induced acute lung injury.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.1128/mBio.00271-13</ELocationID><ELocationID EIdType="pii" ValidYN="Y">e00271-13</ELocationID><Abstract><AbstractText Label="UNLABELLED">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.</AbstractText><AbstractText Label="IMPORTANCE" NlmCategory="OBJECTIVE">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.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Gralinski</LastName><ForeName>Lisa E</ForeName><Initials>LE</Initials><AffiliationInfo><Affiliation>Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bankhead</LastName><ForeName>Armand</ForeName><Initials>A</Initials><Suffix>3rd</Suffix></Author><Author ValidYN="Y"><LastName>Jeng</LastName><ForeName>Sophia</ForeName><Initials>S</Initials></Author><Author ValidYN="Y"><LastName>Menachery</LastName><ForeName>Vineet D</ForeName><Initials>VD</Initials></Author><Author ValidYN="Y"><LastName>Proll</LastName><ForeName>Sean</ForeName><Initials>S</Initials></Author><Author ValidYN="Y"><LastName>Belisle</LastName><ForeName>Sarah E</ForeName><Initials>SE</Initials></Author><Author ValidYN="Y"><LastName>Matzke</LastName><ForeName>Melissa</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Webb-Robertson</LastName><ForeName>Bobbie-Jo M</ForeName><Initials>BJ</Initials></Author><Author ValidYN="Y"><LastName>Luna</LastName><ForeName>Maria L</ForeName><Initials>ML</Initials></Author><Author ValidYN="Y"><LastName>Shukla</LastName><ForeName>Anil K</ForeName><Initials>AK</Initials></Author><Author ValidYN="Y"><LastName>Ferris</LastName><ForeName>Martin T</ForeName><Initials>MT</Initials></Author><Author ValidYN="Y"><LastName>Bolles</LastName><ForeName>Meagan</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Chang</LastName><ForeName>Jean</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><LastName>Aicher</LastName><ForeName>Lauri</ForeName><Initials>L</Initials></Author><Author ValidYN="Y"><LastName>Waters</LastName><ForeName>Katrina M</ForeName><Initials>KM</Initials></Author><Author ValidYN="Y"><LastName>Smith</LastName><ForeName>Richard D</ForeName><Initials>RD</Initials></Author><Author ValidYN="Y"><LastName>Metz</LastName><ForeName>Thomas O</ForeName><Initials>TO</Initials></Author><Author ValidYN="Y"><LastName>Law</LastName><ForeName>G Lynn</ForeName><Initials>GL</Initials></Author><Author ValidYN="Y"><LastName>Katze</LastName><ForeName>Michael G</ForeName><Initials>MG</Initials></Author><Author ValidYN="Y"><LastName>McWeeney</LastName><ForeName>Shannon</ForeName><Initials>S</Initials></Author><Author ValidYN="Y"><LastName>Baric</LastName><ForeName>Ralph S</ForeName><Initials>RS</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>P41 GM103493</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>T32 GM008719</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>UL1 RR024140</GrantID><Acronym>RR</Acronym><Agency>NCRR NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>5UL1RR024140</GrantID><Acronym>RR</Acronym><Agency>NCRR NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>8 P41 GM103493-10</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>HHSN272200800060C</GrantID><Acronym>AI</Acronym><Agency>NIAID NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType><PublicationType UI="D013487">Research Support, U.S. Gov't, P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2013</Year><Month>08</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>mBio</MedlineTA><NlmUniqueID>101519231</NlmUniqueID></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D020543">Proteome</NameOfSubstance></Chemical><Chemical><RegistryNumber>EC 3.4.21.73</RegistryNumber><NameOfSubstance UI="D014568">Urokinase-Type Plasminogen Activator</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D055371" MajorTopicYN="N">Acute Lung Injury</DescriptorName><QualifierName UI="Q000473" MajorTopicYN="Y">pathology</QualifierName><QualifierName UI="Q000821" MajorTopicYN="Y">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001777" MajorTopicYN="N">Blood Coagulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004195" MajorTopicYN="N">Disease Models, Animal</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005342" MajorTopicYN="N">Fibrinolysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D020869" MajorTopicYN="N">Gene Expression Profiling</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D054884" MajorTopicYN="Y">Host-Pathogen Interactions</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008168" MajorTopicYN="N">Lung</DescriptorName><QualifierName UI="Q000473" MajorTopicYN="Y">pathology</QualifierName><QualifierName UI="Q000821" MajorTopicYN="Y">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D051379" MajorTopicYN="N">Mice</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008810" MajorTopicYN="N">Mice, Inbred C57BL</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018345" MajorTopicYN="N">Mice, Knockout</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D020543" MajorTopicYN="N">Proteome</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D045473" MajorTopicYN="N">SARS Virus</DescriptorName><QualifierName UI="Q000472" MajorTopicYN="Y">pathogenicity</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013997" MajorTopicYN="N">Time Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014568" MajorTopicYN="N">Urokinase-Type Plasminogen Activator</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate 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