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Review
. 2013 Oct 31;25(3):228-39.
doi: 10.1016/j.smim.2012.11.001. Epub 2012 Dec 5.

Systems approaches to influenza-virus host interactions and the pathogenesis of highly virulent and pandemic viruses

Affiliations
Review

Systems approaches to influenza-virus host interactions and the pathogenesis of highly virulent and pandemic viruses

Marcus J Korth et al. Semin Immunol. .

Abstract

Influenza virus research has recently undergone a shift from a virus-centric perspective to one that embraces the full spectrum of virus-host interactions and cellular signaling events that determine disease outcome. This change has been brought about by the increasing use and expanding scope of high-throughput molecular profiling and computational biology, which together fuel discovery in systems biology. In this review, we show how these approaches have revealed an uncontrolled inflammatory response as a contributor to the extreme virulence of the 1918 pandemic and avian H5N1 viruses, and how this response differs from that induced by the 2009 H1N1 viruses responsible for the most recent influenza pandemic. We also discuss how new animal models, such as the Collaborative Cross mouse systems genetics platform, are key to the necessary systematic investigation of the impact of host genetics on infection outcome, how genome-wide RNAi screens have identified hundreds of cellular factors involved in viral replication, and how systems biology approaches are making possible the rational design of new drugs and vaccines against an ever-evolving respiratory virus.

Keywords: Computational biology; Genomics; Inflammation; Influenza virus; Interferon; Systems biology.

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Figures

Fig. 1
Fig. 1
Overview of advances in the use of high-throughput approaches to study influenza virus–host interactions and viral pathogenesis. Advances in computational methods are now beginning to provide the means to integrate the diverse types of data and information obtained from these approaches to yield systems-level insights into virus–host interactions, the antiviral response, and innate and adaptive immunity.
Fig. 2
Fig. 2
Differential induction of inflammatory gene expression by influenza viruses causing mild or severe respiratory disease. Shown are changes in inflammatory gene expression profiles over time in the lungs of mice infected with A/Texas/36/91 (a nonpathogenic seasonal isolate), A/CA/04/2009 (a mildly pathogenic 2009 H1N1 pandemic isolate), or highly pathogenic mouse-adapted 2009 H1N1, r1918, or avian H5N1 viruses. Expression values are represented as the average of the log2 ratio of infected to respective mock-infected samples for three biological replicates per condition. Red and green indicate that gene expression is increased or decreased relative to mock, respectively.
Fig. 3
Fig. 3
Comparison of transcriptional profiles elicited by A/Texas/36/91 (a nonpathogenic seasonal isolate), CA/04/2009 (a mildly pathogenic 2009 H1N1 pandemic isolate), or highly pathogenic mouse-adapted 2009 H1N1, r1918, or avian H5N1 viruses. Nonparametric multidimensional scaling was used to represent the Euclidian distance between samples on each day post infection. The matrix distance was calculated using the list of genes that are represented in Fig. 2.
Fig. 4
Fig. 4
Genetic diversity across pre-Collaborative Cross mouse lines results in differential host response to influenza virus infection. Shown is the relationship between weight loss and viral titer for 209 pre-Collaborative Cross mouse lines infected with influenza virus A/PR/8. Dashed line indicates limit of detection for viral titer.
Fig. 5
Fig. 5
The kinetics of virus-driven immune activation is a central component of virus–host interactions and a key factor in viral pathogenesis. Mathematical approaches discussed in the text for studying highly time-resolved data, time-dependent therapeutic intervention, and virus–host interactions are indicated.

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