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Dissecting Host-virus Interaction in Lytic Replication of a Model Herpesvirus
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Inferring host gene subnetworks involved in viral replication
Deborah Chasman1, Brandi Gancarz2, Linhui Hao3
1Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Plos Computational Biology
|May 31, 2014
Summary
This study introduces a computational method to map how host genes influence viral replication. The approach identifies key host-virus interactions and predicts new factors involved in infection.
Area of Science:
- Computational Biology
- Virology
- Systems Biology
Background:
- Identifying host factors that regulate viral replication is crucial for understanding host-virus interactions.
- Systematic, genome-wide loss-of-function screens can reveal genes affecting viral replication.
- Inferring the specific pathways of host-virus modulation from experimental data remains challenging.
Purpose of the Study:
- To develop and validate a computational approach for inferring host-virus interaction pathways.
- To identify host factors that directly or indirectly modulate viral replication.
- To predict novel host genes involved in viral replication and their direct interfaces with viruses.
Main Methods:
- Combined an integer linear programming model with a diffusion kernel method.
- Utilized viral phenotypes from single-host-gene mutants and a background network of host intracellular interactions.
- Inferred host-virus interaction subnetworks by integrating experimental data with network information.
Main Results:
- The method generated ensembles of subnetworks explaining observed viral phenotypes.
- It accurately predicted unassayed host factors modulating viral replication, outperforming several baseline methods.
- Identified host factors predicted to be direct interfaces with viral components, with some supported by independent data.
Conclusions:
- The developed computational approach effectively infers host-virus interaction pathways.
- The method provides high-confidence predictions of host factors involved in viral replication.
- This approach aids in uncovering mechanisms of viral pathogenesis and identifying potential therapeutic targets.
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