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Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection
Journal article   Open access   Peer reviewed

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection

Elena Zaslavsky, German Nudelman, Susanna Marquez, Uri Hershberg, Boris M. Hartmann, Juilee Thakar, Stuart C. Sealfon and Steven H. Kleinstein
BMC bioinformatics, v 14(6), pp S1-S1
17 Apr 2013
DOI: https://doi.org/10.1186/1471-2105-14-S6-S1
PMID: 23734902
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1186/1471-2105-14-s6-s1View
Published, Version of Record (VoR)CC BY V4.0,  Open
url
https://doi.org/10.1186/1471-2105-14-S6-S1View
Published, Version of Record (VoR) Open

Abstract

Biochemical Research Methods Biochemistry & Molecular Biology Biotechnology & Applied Microbiology Life Sciences & Biomedicine Mathematical & Computational Biology Science & Technology
Background: H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology. Results: Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog. Conclusions: We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections.

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10 citations in Web of Science
11 citations in Scopus

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UN Sustainable Development Goals (SDGs)

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#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Biochemical Research Methods
Biotechnology & Applied Microbiology
Mathematical & Computational Biology
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