Patterns of HIV-1 protein interaction identify perturbed host-cellular subsystems

MacPherson, J. I., Dickerson, J. E., Pinney, J. W. and Robertson, D. L. (2010) Patterns of HIV-1 protein interaction identify perturbed host-cellular subsystems. PLoS Computational Biology, 6(7), e1000863. (doi: 10.1371/journal.pcbi.1000863) (PMID:20686668) (PMCID:PMC2912648)

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Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection.

Item Type:Articles
Additional Information:JIM is funded by a BBSRC CASE studentship with industry partner Pfizer, and JED by a Wellcome Trust studentship. JWP is supported by a University Research Fellowship from the Royal Society. Thanks also to the Apple Research and Technology Support scheme for support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Glasgow Author(s) Enlighten ID:Robertson, Professor David and Dickerson, Dr Jonathan
Authors: MacPherson, J. I., Dickerson, J. E., Pinney, J. W., and Robertson, D. L.
College/School:College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:PLoS Computational Biology
Publisher:Public Library of Science
ISSN (Online):1553-7358
Copyright Holders:Copyright © 2010 MacPherson et al.
First Published:First published in PLoS Computational Biology 6(7): e1000863
Publisher Policy:Reproduced under a Creative Commons License

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