Abstract
BackgroundThe 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.ResultsWe 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.ConclusionsThe 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 materialThe online version of this article (doi:10.1186/s12918-016-0336-6) contains supplementary material, which is available to authorized users.
Highlights
The complex interplay between viral replication and host immune response during infection remains poorly understood
We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis
We used the transcriptomic data from this experiment to generate modules using the weighted gene correlation network analysis (WGCNA), which establishes groups or modules of genes representing the main expression patterns in the process being studied [20]
Summary
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 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. Infected patients typically presented with fever and evidence of respiratory illness, general malaise and lower respiratory tract symptoms including cough and shortness of breath, and had an overall fatality rate of approximately 10 % [5] Despite this threat we are poorly prepared to develop rapid strategies to ameliorate coronavirus disease severity in an outbreak setting. High throughput molecular approaches offer a way to discover novel host response genes, proteins, and pathways that contribute to the systems-level development of pathogenesis
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