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The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus

BACKGROUND: The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune respon...

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Autores principales: McDermott, Jason E., Mitchell, Hugh D., Gralinski, Lisa E., Eisfeld, Amie J., Josset, Laurence, Bankhead, Armand, Neumann, Gabriele, Tilton, Susan C., Schäfer, Alexandra, Li, Chengjun, Fan, Shufang, McWeeney, Shannon, Baric, Ralph S., Katze, Michael G., Waters, Katrina M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5035469/
https://www.ncbi.nlm.nih.gov/pubmed/27663205
http://dx.doi.org/10.1186/s12918-016-0336-6
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author McDermott, Jason E.
Mitchell, Hugh D.
Gralinski, Lisa E.
Eisfeld, Amie J.
Josset, Laurence
Bankhead, Armand
Neumann, Gabriele
Tilton, Susan C.
Schäfer, Alexandra
Li, Chengjun
Fan, Shufang
McWeeney, Shannon
Baric, Ralph S.
Katze, Michael G.
Waters, Katrina M.
author_facet McDermott, Jason E.
Mitchell, Hugh D.
Gralinski, Lisa E.
Eisfeld, Amie J.
Josset, Laurence
Bankhead, Armand
Neumann, Gabriele
Tilton, Susan C.
Schäfer, Alexandra
Li, Chengjun
Fan, Shufang
McWeeney, Shannon
Baric, Ralph S.
Katze, Michael G.
Waters, Katrina M.
author_sort McDermott, Jason E.
collection PubMed
description BACKGROUND: The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. RESULTS: We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine tumor necrosis factor alpha (TNFα) promote pathogenesis, presumably through excessive inflammation. CONCLUSIONS: The current study provides validation of network modeling approaches for identifying important players in virus infection pathogenesis, and a step forward in understanding the host response to an important infectious disease. The results presented here suggest the role of Kepi in the host response to SARS-CoV, as well as inflammatory activity driving pathogenesis through TNFα signaling in SARS-CoV infections. Though we have reported the utility of this approach in bacterial and cell culture studies previously, this is the first comprehensive study to confirm that network topology can be used to predict phenotypes in mice with experimental validation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0336-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-50354692016-09-29 The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus McDermott, Jason E. Mitchell, Hugh D. Gralinski, Lisa E. Eisfeld, Amie J. Josset, Laurence Bankhead, Armand Neumann, Gabriele Tilton, Susan C. Schäfer, Alexandra Li, Chengjun Fan, Shufang McWeeney, Shannon Baric, Ralph S. Katze, Michael G. Waters, Katrina M. BMC Syst Biol Research Article BACKGROUND: The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. RESULTS: We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine tumor necrosis factor alpha (TNFα) promote pathogenesis, presumably through excessive inflammation. CONCLUSIONS: The current study provides validation of network modeling approaches for identifying important players in virus infection pathogenesis, and a step forward in understanding the host response to an important infectious disease. The results presented here suggest the role of Kepi in the host response to SARS-CoV, as well as inflammatory activity driving pathogenesis through TNFα signaling in SARS-CoV infections. Though we have reported the utility of this approach in bacterial and cell culture studies previously, this is the first comprehensive study to confirm that network topology can be used to predict phenotypes in mice with experimental validation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0336-6) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-23 /pmc/articles/PMC5035469/ /pubmed/27663205 http://dx.doi.org/10.1186/s12918-016-0336-6 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
McDermott, Jason E.
Mitchell, Hugh D.
Gralinski, Lisa E.
Eisfeld, Amie J.
Josset, Laurence
Bankhead, Armand
Neumann, Gabriele
Tilton, Susan C.
Schäfer, Alexandra
Li, Chengjun
Fan, Shufang
McWeeney, Shannon
Baric, Ralph S.
Katze, Michael G.
Waters, Katrina M.
The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus
title The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus
title_full The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus
title_fullStr The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus
title_full_unstemmed The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus
title_short The effect of inhibition of PP1 and TNFα signaling on pathogenesis of SARS coronavirus
title_sort effect of inhibition of pp1 and tnfα signaling on pathogenesis of sars coronavirus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5035469/
https://www.ncbi.nlm.nih.gov/pubmed/27663205
http://dx.doi.org/10.1186/s12918-016-0336-6
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