This comprehensive and highly integrated systems biology application seeks to delineate the complex host responses that determine the outcome of infections with potentially lethal viruses. To achieve this goal, cells and mice will be infected with wild-type and mutant influenza A, Ebola, and West Nile viruses to collect a variety of sample sets (these activities will be carried out by two Research Projects for influenza and Ebola or West Nile virus, respectively). A Technical Core will perform proteomics, phosphoproteomics, lipidomics, and metabolomics profiling, whereas mRNA and miRNA profiling will be out-sourced on a fee-for-service basis. In addition, multiple biological datasets, including virological data and data on protein-protein interactions, will be generated. All data will be analyzed by a Computational Modeling Core, which will integrate the diverse datasets and build predictive mechanistic and network models, including virtual lung and liver models. Based on these analyses, the two Research Projects will carry out comprehensive validation studies in vitro and in vivo (i.e., in knock-out mice). OMICs studies (as described above) from virus-infected knock-out and matched wild-type mice will be used for a second round of analysis, thereby achieving the systems biology paradigm of Iterative sampling, modeling, and validation. Storage, management, and exchange of the large and diverse datasets, and outreach to the community, will be facilitated by a Data Management and Resources Dissemination Core, whereas an Administrative Core will ensure that all administrative tasks are addressed. In summary, we propose a comprehensive and interactive systems biology program that will enhance predictive modeling of infectious disease and identify critical regulators of severe human virus pathogenicity that may be exploited for the development of therapeutic interventions.

Public Health Relevance

Ebola viruses. West Nile virus and Influenza A viruses are classified as Category A, B and C priority agents, respectively, by the National Institute of Allergy and Infectious Diseases (NIAID). All three viruses have the ability to cause severe and/or fatal infections in humans for reasons that are not completely understood. We seek to combine state-of-the-art systems biology methodology with high level virological, technical and computational expertise to elucidate common and unique mechanisms regulating viral pathogenicity and fatal outcomes in humans infected with these viruses. Project 1: Systems Biology Analysis of Influenza A Virus and Ebola Virus Project Leader (PL): Yoshihiro Kawaoka DESCRIPTION (as provided by applicant): Infections with highly pathogenic avian H5N1 influenza A viruses (lAV) or Ebola viruses (EBOV) cause severe respiratory disease or hemorrhagic fever with high mortality rates in humans. The limited understanding of how these viruses dysregulate the host response impairs effective treatments for virus induced disease. We hypothesize that comparing host responses to H5N1 lAV, EBOV and a range of virulence mutants will allow delineation of common and virus-specific mechanisms of immune subversion and pathogenicity. Here, we propose a highly integrated systems biology approach to address this hypothesis. We will leverage our existing transcriptome and proteome data from cells and mouse lungs infected with H5N1 lAV and mutant viruses, and in Aim 1, similar proteomics and transcriptomics datasets will be acquired for EBOV-infected cells and mice. In addition, we will perform miRNA profiling, phosphoproteomics, metabolomics and lipidomics analyses for both viruses;quantify immune cell trafficking into infected lung or liver tissues;collect transcriptomcs data for immune cell populations isolated from lAV-infected lungs;and provide comprehensive data for lAV and EBOV protein interactions with host proteins. Datasets will be acquired with the assistance of several Cores for sample processing, statistical and computational analyses, and integration with data generated for West Nile virus (WNV) under the second Research Project of this contract. The Computational Modeling Core will produce prioritized regulatory target lists for follow-up analysis, and in Aim 2, targets will be experimentally validated using in vitro systems coupled with perturbation of host factor expression or activity. Selected targets then will be validated in vivo by generation of knockout (KO) mice and assessment of the effects of gene KO on the outcome of infection. To allow refinement of computational models and completion of the systems biology paradigm, we will also obtain samples from KO mice for iterative OMICs studies. Collectively, this strategy is expected to facilitate predictive modeling of disease states associated with severe human viral pathogens and identify important regulators of viral pathogenesis that may be targeted for novel intervention strategies.

Public Health Relevance

Ebola viruses (EBOV) and influenza A viruses (lAV) are classified as 'Category A'and 'Category C'priority agents, respectively, by the National Institute of Allergy and Infectious Diseases (NIAID). Both viruses have the ability to cause severe and/or fatal infections in humans, although the mechanisms are not clearly defined. Here, we seek to identify these mechanisms using a highly collaborative state-of-the-art systems biology methodology, to facilitate better understanding and treatment of EBOV and lAV infections in humans.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI106772-02
Application #
8667401
Study Section
Special Emphasis Panel (ZAI1-EC-M (M1))
Program Officer
Di Francesco, Valentina
Project Start
2013-06-01
Project End
2018-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
2
Fiscal Year
2014
Total Cost
$4,165,640
Indirect Cost
$650,432
Name
University of Wisconsin Madison
Department
Pathology
Type
Schools of Veterinary Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
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