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3 results on '"Amy, L."'

1. A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses

Author

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

2. Evaluation of a Salmonella Vectored Vaccine Expressing Mycobacterium avium Subsp. paratuberculosis Antigens Against Challenge in a Goat Model.

Author

Faisal, Syed M., Yan, Falong, Chen, Tsai-Tzu, Useh, Nicodemus M., Guo, Shanguang, Yan, Weiwei, Wang, Shih-Jon, Glaser, Amy L., McDonough, Sean P., Singh, Bhupinder, and Chang, Yung-Fu

Subjects
BACTERIAL vaccines, SALMONELLA, MYCOBACTERIUM avium, PARATUBERCULOSIS, ANTIGENS, GOATS as laboratory animals, CYTOKINES
Abstract

Johnes disease (JD), caused by Mycobacterium avium subsp paratuberculosis (MAP), occurs worldwide as chronic granulomatous enteritis of domestic and wild ruminants. To develop a cost effective vaccine, in a previous study we constructed an attenuated Salmonella strain that expressed a fusion product made up of partial fragments of MAP antigens (Ag85A, Ag85B and SOD) that imparted protection against challenge in a mouse model. In the current study we evaluated the differential immune response and protective efficacy of the Sal-Ag vaccine against challenge in a goat model as compared to the live attenuated vaccine MAP316F. PBMCs from goats vaccinated with Sal-Ag and challenged with MAP generated significantly lower levels of IFN-γ, following in vitro stimulation with either Antigen-mix or PPD jhonin, than PBMC from MAP316F vaccinated animals. Flow cytometric analysis showed the increase in IFN-γ correlated with a significantly higher level of proliferation of CD4, CD8 and γδT cells and an increased expression of CD25 and CD45R0 in MAP316F vaccinated animals as compared to control animals. Evaluation of a range of cytokines involved in Th1, Th2, Treg, and Th17 immune responses by quantitative PCR showed low levels of expression of Th1 (IFN-γ, IL-2, IL-12) and proinflammatory cytokines (IL-6, IL-8, IL-18, TNF-α) in the Sal-Ag immunized group. Significant levels of Th2 and anti-inflammatory cytokines transcripts (IL-4, IL-10, IL-13, TGF-β) were expressed but their level was low and with a pattern similar to the control group. Over all, Sal-Ag vaccine imparted partial protection that limited colonization in tissues of some animals upon challenge with wild type MAP but not to the level achieved with MAP316F. In conclusion, the data indicates that Sal-Ag vaccine induced only a low level of protective immunity that failed to limit the colonization of MAP in infected animals. Hence the Sal-Ag vaccine needs further refinement to increase its efficacy. [ABSTRACT FROM AUTHOR]

Published
2013
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3. A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses.

Author

Mitchell, Hugh D., Eisfeld, Amie J., Sims, Amy C., McDermott, Jason E., Matzke, Melissa M., Webb-Robertson, Bobbi-Jo M., Tilton, Susan C., Tchitchek, Nicolas, Josset, Laurence, Li, Chengjun, Ellis, Amy L., Chang, Jean H., Heegel, Robert A., Luna, Maria L., Schepmoes, Athena A., Shukla, Anil K., Metz, Thomas O., Neumann, Gabriele, Benecke, Arndt G., and Smith, Richard D.

Subjects
RESPIRATORY infections, INFLUENZA viruses, SARS disease, CORONAVIRUSES, PANDEMICS, PUBLIC health, PATHOLOGY, SARS virus
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. [ABSTRACT FROM AUTHOR]

Published
2013
Full Text
View/download PDF

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