A network integration approach to predict conserved regulators related to pathogenicity of influenza and SARS-CoV respiratory viruses.
Identifieur interne : 001A04 ( Main/Exploration ); précédent : 001A03; suivant : 001A05A network integration approach to predict conserved regulators related to pathogenicity of influenza and SARS-CoV respiratory viruses.
Auteurs : Hugh D. Mitchell [États-Unis] ; Amie J. Eisfeld ; Amy C. Sims ; Jason E. Mcdermott ; Melissa M. Matzke ; Bobbi-Jo M. Webb-Robertson ; Susan C. Tilton ; Nicolas Tchitchek ; Laurence Josset ; Chengjun Li ; Amy L. Ellis ; Jean H. Chang ; Robert A. Heegel ; Maria L. Luna ; Athena A. Schepmoes ; Anil K. Shukla ; Thomas O. Metz ; Gabriele Neumann ; Arndt G. Benecke ; Richard D. Smith ; Ralph S. Baric ; Yoshihiro Kawaoka [États-Unis] ; Michael G. Katze ; Katrina M. WatersSource :
- PloS one [ 1932-6203 ] ; 2013.
Descripteurs français
- KwdFr :
- Animaux, Cellules épithéliales (immunologie), Cellules épithéliales (métabolisme), Cellules épithéliales (virologie), Gènes régulateurs, Humains, Interactions hôte-pathogène (génétique), Modèles statistiques, Muqueuse respiratoire (immunologie), Muqueuse respiratoire (métabolisme), Muqueuse respiratoire (virologie), Orthomyxoviridae (pathogénicité), Orthomyxoviridae (physiologie), Poumon (immunologie), Poumon (métabolisme), Poumon (virologie), Régulation de l'expression des gènes, Réplication virale, Transcriptome, Virulence, Virus du SRAS (pathogénicité), Virus du SRAS (physiologie).
- MESH :
- génétique : Interactions hôte-pathogène.
- immunologie : Cellules épithéliales, Muqueuse respiratoire, Poumon.
- métabolisme : Cellules épithéliales, Muqueuse respiratoire, Poumon.
- pathogénicité : Orthomyxoviridae, Virus du SRAS.
- physiologie : Orthomyxoviridae, Virus du SRAS.
- virologie : Cellules épithéliales, Muqueuse respiratoire, Poumon.
- Animaux, Gènes régulateurs, Humains, Modèles statistiques, Régulation de l'expression des gènes, Réplication virale, Transcriptome, Virulence.
English descriptors
- KwdEn :
- Animals, Epithelial Cells (immunology), Epithelial Cells (metabolism), Epithelial Cells (virology), Gene Expression Regulation, Genes, Regulator, Host-Pathogen Interactions (genetics), Humans, Lung (immunology), Lung (metabolism), Lung (virology), Models, Statistical, Orthomyxoviridae (pathogenicity), Orthomyxoviridae (physiology), Respiratory Mucosa (immunology), Respiratory Mucosa (metabolism), Respiratory Mucosa (virology), SARS Virus (pathogenicity), SARS Virus (physiology), Transcriptome, Virulence, Virus Replication.
- MESH :
- genetics : Host-Pathogen Interactions.
- immunology : Epithelial Cells, Lung, Respiratory Mucosa.
- metabolism : Epithelial Cells, Lung, Respiratory Mucosa.
- pathogenicity : Orthomyxoviridae, SARS Virus.
- physiology : Orthomyxoviridae, SARS Virus.
- virology : Epithelial Cells, Lung, Respiratory Mucosa.
- Animals, Gene Expression Regulation, Genes, Regulator, Humans, Models, Statistical, Transcriptome, Virulence, Virus Replication.
Abstract
Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel "crowd-based" approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse 'omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models.
Url:
DOI: 10.1371/journal.pone.0069374
PubMed: 23935999
Affiliations:
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Le document en format XML
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Luna</name></author><author><name sortKey="Schepmoes, Athena A" sort="Schepmoes, Athena A" uniqKey="Schepmoes A" first="Athena A" last="Schepmoes">Athena A. Schepmoes</name></author><author><name sortKey="Shukla, Anil K" sort="Shukla, Anil K" uniqKey="Shukla A" first="Anil K" last="Shukla">Anil K. Shukla</name></author><author><name sortKey="Metz, Thomas O" sort="Metz, Thomas O" uniqKey="Metz T" first="Thomas O" last="Metz">Thomas O. Metz</name></author><author><name sortKey="Neumann, Gabriele" sort="Neumann, Gabriele" uniqKey="Neumann G" first="Gabriele" last="Neumann">Gabriele Neumann</name></author><author><name sortKey="Benecke, Arndt G" sort="Benecke, Arndt G" uniqKey="Benecke A" first="Arndt G" last="Benecke">Arndt G. Benecke</name></author><author><name sortKey="Smith, Richard D" sort="Smith, Richard D" uniqKey="Smith R" first="Richard D" last="Smith">Richard D. Smith</name></author><author><name sortKey="Baric, Ralph S" sort="Baric, Ralph S" uniqKey="Baric R" first="Ralph S" last="Baric">Ralph S. Baric</name></author><author><name sortKey="Kawaoka, Yoshihiro" sort="Kawaoka, Yoshihiro" uniqKey="Kawaoka Y" first="Yoshihiro" last="Kawaoka">Yoshihiro Kawaoka</name><affiliation><country>États-Unis</country><placeName><settlement type="city">Madison (Wisconsin)</settlement><region type="state">Wisconsin</region></placeName><orgName type="university" n="3">Université du Wisconsin à Madison</orgName></affiliation></author><author><name sortKey="Katze, Michael G" sort="Katze, Michael G" uniqKey="Katze M" first="Michael G" last="Katze">Michael G. Katze</name></author><author><name sortKey="Waters, Katrina M" sort="Waters, Katrina M" uniqKey="Waters K" first="Katrina M" last="Waters">Katrina M. Waters</name></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2013" type="published">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Epithelial Cells (immunology)</term><term>Epithelial Cells (metabolism)</term><term>Epithelial Cells (virology)</term><term>Gene Expression Regulation</term><term>Genes, Regulator</term><term>Host-Pathogen Interactions (genetics)</term><term>Humans</term><term>Lung (immunology)</term><term>Lung (metabolism)</term><term>Lung (virology)</term><term>Models, Statistical</term><term>Orthomyxoviridae (pathogenicity)</term><term>Orthomyxoviridae (physiology)</term><term>Respiratory Mucosa (immunology)</term><term>Respiratory Mucosa (metabolism)</term><term>Respiratory Mucosa (virology)</term><term>SARS Virus (pathogenicity)</term><term>SARS Virus (physiology)</term><term>Transcriptome</term><term>Virulence</term><term>Virus Replication</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Animaux</term><term>Cellules épithéliales (immunologie)</term><term>Cellules épithéliales (métabolisme)</term><term>Cellules épithéliales (virologie)</term><term>Gènes régulateurs</term><term>Humains</term><term>Interactions hôte-pathogène (génétique)</term><term>Modèles statistiques</term><term>Muqueuse respiratoire (immunologie)</term><term>Muqueuse respiratoire (métabolisme)</term><term>Muqueuse respiratoire (virologie)</term><term>Orthomyxoviridae (pathogénicité)</term><term>Orthomyxoviridae (physiologie)</term><term>Poumon (immunologie)</term><term>Poumon (métabolisme)</term><term>Poumon (virologie)</term><term>Régulation de l'expression des gènes</term><term>Réplication virale</term><term>Transcriptome</term><term>Virulence</term><term>Virus du SRAS (pathogénicité)</term><term>Virus du SRAS (physiologie)</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Host-Pathogen Interactions</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Interactions hôte-pathogène</term></keywords><keywords scheme="MESH" qualifier="immunologie" xml:lang="fr"><term>Cellules épithéliales</term><term>Muqueuse respiratoire</term><term>Poumon</term></keywords><keywords scheme="MESH" qualifier="immunology" xml:lang="en"><term>Epithelial Cells</term><term>Lung</term><term>Respiratory Mucosa</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Epithelial Cells</term><term>Lung</term><term>Respiratory Mucosa</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Cellules épithéliales</term><term>Muqueuse respiratoire</term><term>Poumon</term></keywords><keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>Orthomyxoviridae</term><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="pathogénicité" xml:lang="fr"><term>Orthomyxoviridae</term><term>Virus du SRAS</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Orthomyxoviridae</term><term>Virus du SRAS</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Orthomyxoviridae</term><term>SARS Virus</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Cellules épithéliales</term><term>Muqueuse respiratoire</term><term>Poumon</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Epithelial Cells</term><term>Lung</term><term>Respiratory Mucosa</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Gene Expression Regulation</term><term>Genes, Regulator</term><term>Humans</term><term>Models, Statistical</term><term>Transcriptome</term><term>Virulence</term><term>Virus Replication</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Animaux</term><term>Gènes régulateurs</term><term>Humains</term><term>Modèles statistiques</term><term>Régulation de l'expression des gènes</term><term>Réplication virale</term><term>Transcriptome</term><term>Virulence</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel "crowd-based" approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse 'omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models. </div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Washington (État)</li><li>Wisconsin</li></region><settlement><li>Madison (Wisconsin)</li></settlement><orgName><li>Université du Wisconsin à Madison</li></orgName></list><tree><noCountry><name sortKey="Baric, Ralph S" sort="Baric, Ralph S" uniqKey="Baric R" first="Ralph S" last="Baric">Ralph S. Baric</name><name sortKey="Benecke, Arndt G" sort="Benecke, Arndt G" uniqKey="Benecke A" first="Arndt G" last="Benecke">Arndt G. Benecke</name><name sortKey="Chang, Jean H" sort="Chang, Jean H" uniqKey="Chang J" first="Jean H" last="Chang">Jean H. Chang</name><name sortKey="Eisfeld, Amie J" sort="Eisfeld, Amie J" uniqKey="Eisfeld A" first="Amie J" last="Eisfeld">Amie J. Eisfeld</name><name sortKey="Ellis, Amy L" sort="Ellis, Amy L" uniqKey="Ellis A" first="Amy L" last="Ellis">Amy L. Ellis</name><name sortKey="Heegel, Robert A" sort="Heegel, Robert A" uniqKey="Heegel R" first="Robert A" last="Heegel">Robert A. Heegel</name><name sortKey="Josset, Laurence" sort="Josset, Laurence" uniqKey="Josset L" first="Laurence" last="Josset">Laurence Josset</name><name sortKey="Katze, Michael G" sort="Katze, Michael G" uniqKey="Katze M" first="Michael G" last="Katze">Michael G. Katze</name><name sortKey="Li, Chengjun" sort="Li, Chengjun" uniqKey="Li C" first="Chengjun" last="Li">Chengjun Li</name><name sortKey="Luna, Maria L" sort="Luna, Maria L" uniqKey="Luna M" first="Maria L" last="Luna">Maria L. Luna</name><name sortKey="Matzke, Melissa M" sort="Matzke, Melissa M" uniqKey="Matzke M" first="Melissa M" last="Matzke">Melissa M. Matzke</name><name sortKey="Mcdermott, Jason E" sort="Mcdermott, Jason E" uniqKey="Mcdermott J" first="Jason E" last="Mcdermott">Jason E. Mcdermott</name><name sortKey="Metz, Thomas O" sort="Metz, Thomas O" uniqKey="Metz T" first="Thomas O" last="Metz">Thomas O. Metz</name><name sortKey="Neumann, Gabriele" sort="Neumann, Gabriele" uniqKey="Neumann G" first="Gabriele" last="Neumann">Gabriele Neumann</name><name sortKey="Schepmoes, Athena A" sort="Schepmoes, Athena A" uniqKey="Schepmoes A" first="Athena A" last="Schepmoes">Athena A. Schepmoes</name><name sortKey="Shukla, Anil K" sort="Shukla, Anil K" uniqKey="Shukla A" first="Anil K" last="Shukla">Anil K. Shukla</name><name sortKey="Sims, Amy C" sort="Sims, Amy C" uniqKey="Sims A" first="Amy C" last="Sims">Amy C. Sims</name><name sortKey="Smith, Richard D" sort="Smith, Richard D" uniqKey="Smith R" first="Richard D" last="Smith">Richard D. Smith</name><name sortKey="Tchitchek, Nicolas" sort="Tchitchek, Nicolas" uniqKey="Tchitchek N" first="Nicolas" last="Tchitchek">Nicolas Tchitchek</name><name sortKey="Tilton, Susan C" sort="Tilton, Susan C" uniqKey="Tilton S" first="Susan C" last="Tilton">Susan C. Tilton</name><name sortKey="Waters, Katrina M" sort="Waters, Katrina M" uniqKey="Waters K" first="Katrina M" last="Waters">Katrina M. Waters</name><name sortKey="Webb Robertson, Bobbi Jo M" sort="Webb Robertson, Bobbi Jo M" uniqKey="Webb Robertson B" first="Bobbi-Jo M" last="Webb-Robertson">Bobbi-Jo M. Webb-Robertson</name></noCountry><country name="États-Unis"><region name="Washington (État)"><name sortKey="Mitchell, Hugh D" sort="Mitchell, Hugh D" uniqKey="Mitchell H" first="Hugh D" last="Mitchell">Hugh D. Mitchell</name></region><name sortKey="Kawaoka, Yoshihiro" sort="Kawaoka, Yoshihiro" uniqKey="Kawaoka Y" first="Yoshihiro" last="Kawaoka">Yoshihiro Kawaoka</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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