1. A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses
- Author
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Gabriele Neumann, Anil K. Shukla, Athena A. Schepmoes, Laurence Josset, Bobbi Jo M. Webb-Robertson, Michael G. Katze, Chengjun Li, Yoshihiro Kawaoka, Katrina M. Waters, Amy C. Sims, Hugh D. Mitchell, Ralph S. Baric, Jean H. Chang, Thomas O. Metz, Melissa M. Matzke, Richard D. Smith, Robert A. Heegel, Susan C. Tilton, Amy L. Ellis, Amie J. Eisfeld, Nicolas Tchitchek, Jason E. McDermott, Maria L. Luna, Arndt Benecke, Pacific Northwest National Laboratory (PNNL), University of Wisconsin-Madison, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), University of Washington [Seattle], Physiopathologie des Maladies du Système Nerveux Central, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), The University of Tokyo (UTokyo), Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH), Department of Health and Human Services [HHSN272200800060C], NIH [P41 GM103493], Mazalérat, Charlotte, Expression des Gènes et comportement adaptatifs = Molecular Genetics, Neurophysiology and Behavior (NPS-15), Neurosciences Paris Seine (NPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Neuroscience Paris Seine (NPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Proteomics ,Microarrays ,Viral pathogenesis ,viruses ,lcsh:Medicine ,Disease ,Virus Replication ,Transcriptome ,Emerging Viral Diseases ,Pandemic ,Genes, Regulator ,lcsh:Science ,Lung ,Regulator gene ,0303 health sciences ,Multidisciplinary ,biology ,Virulence ,Proteomic Databases ,030302 biochemistry & molecular biology ,General Medicine ,Genomics ,Orthomyxoviridae ,3. Good health ,Severe acute respiratory syndrome-related coronavirus ,Host-Pathogen Interactions ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,General Agricultural and Biological Sciences ,Research Article ,Computer Modeling ,Computational biology ,Respiratory Mucosa ,Microbiology ,General Biochemistry, Genetics and Molecular Biology ,Virus ,03 medical and health sciences ,Virology ,Genetics ,Animals ,Humans ,[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Gene Networks ,Biology ,030304 developmental biology ,Regulatory Networks ,Models, Statistical ,lcsh:R ,Computational Biology ,Epithelial Cells ,biology.organism_classification ,Animal Models of Infection ,Viral replication ,Gene Expression Regulation ,Virulence Factors and Mechanisms ,Computer Science ,lcsh:Q ,Genome Expression Analysis ,Viral Transmission and Infection - Abstract
International audience; 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.
- Published
- 2013