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

MacPherson JI, Dickerson JE, Pinney JW, Robertson DL - PLoS Comput. Biol. (2010)

Bottom Line: 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.Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.

ABSTRACT
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.

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An example portion of the interactions matrix used in biclustering.(A) Shows an example portion of the interactions matrix. ‘1’ represents the presence of a given interaction, while ‘0’ the absence of that interaction, between a human protein interactant (shown left) and an HIV protein; the interaction having a given outcome (shown above). The entire matrix was biclustered to identify sets of host proteins that undergo the same set of HIV-1 interactions. (B) Shows an example bicluster that would be found in the portion of matrix given in (A).
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pcbi-1000863-g002: An example portion of the interactions matrix used in biclustering.(A) Shows an example portion of the interactions matrix. ‘1’ represents the presence of a given interaction, while ‘0’ the absence of that interaction, between a human protein interactant (shown left) and an HIV protein; the interaction having a given outcome (shown above). The entire matrix was biclustered to identify sets of host proteins that undergo the same set of HIV-1 interactions. (B) Shows an example bicluster that would be found in the portion of matrix given in (A).

Mentions: To computationally identify more complex patterns of virus-host interaction, we investigated human proteins that take part in more than one distinct PPI with HIV-1 proteins. An outline of our method for analysis of HIV-1 interaction is given in figure 1. As a first step towards identifying key host functions known to be involved in HIV infection, we use biclustering to define groups of human proteins that share a common set (or ‘profile’) of HIV-1 interactions, in terms of HIV-1 protein interactant and interaction type (figure 2). The binary interaction matrix contained 1434 rows, 1292 columns and 3939 positive values, corresponding to human proteins, all types of HIV-1 interaction and all HIV-1-human PPIs, respectively. Biclustering of this matrix yielded 1306 biclusters that include a minimum of two human proteins, each with a minimum of two distinct HIV-1 interactions. We identified 279 from 1306 biclusters that were statistically significant () by Monte Carlo simulation. A table with details of all significant biclusters, including their constituent human proteins, HIV-1 proteins, interaction types and links to the HHPID are given in supplementary Table S1.


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

MacPherson JI, Dickerson JE, Pinney JW, Robertson DL - PLoS Comput. Biol. (2010)

An example portion of the interactions matrix used in biclustering.(A) Shows an example portion of the interactions matrix. ‘1’ represents the presence of a given interaction, while ‘0’ the absence of that interaction, between a human protein interactant (shown left) and an HIV protein; the interaction having a given outcome (shown above). The entire matrix was biclustered to identify sets of host proteins that undergo the same set of HIV-1 interactions. (B) Shows an example bicluster that would be found in the portion of matrix given in (A).
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Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2912648&req=5

pcbi-1000863-g002: An example portion of the interactions matrix used in biclustering.(A) Shows an example portion of the interactions matrix. ‘1’ represents the presence of a given interaction, while ‘0’ the absence of that interaction, between a human protein interactant (shown left) and an HIV protein; the interaction having a given outcome (shown above). The entire matrix was biclustered to identify sets of host proteins that undergo the same set of HIV-1 interactions. (B) Shows an example bicluster that would be found in the portion of matrix given in (A).
Mentions: To computationally identify more complex patterns of virus-host interaction, we investigated human proteins that take part in more than one distinct PPI with HIV-1 proteins. An outline of our method for analysis of HIV-1 interaction is given in figure 1. As a first step towards identifying key host functions known to be involved in HIV infection, we use biclustering to define groups of human proteins that share a common set (or ‘profile’) of HIV-1 interactions, in terms of HIV-1 protein interactant and interaction type (figure 2). The binary interaction matrix contained 1434 rows, 1292 columns and 3939 positive values, corresponding to human proteins, all types of HIV-1 interaction and all HIV-1-human PPIs, respectively. Biclustering of this matrix yielded 1306 biclusters that include a minimum of two human proteins, each with a minimum of two distinct HIV-1 interactions. We identified 279 from 1306 biclusters that were statistically significant () by Monte Carlo simulation. A table with details of all significant biclusters, including their constituent human proteins, HIV-1 proteins, interaction types and links to the HHPID are given in supplementary Table S1.

Bottom Line: 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.Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus