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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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Related in: MedlinePlus

Comparison of protein pairs within significant biclusters to other protein pairs.Panels A, B and C show the semantic distance distributions for the three GO ontologies: biological process, cellular component and molecular function, respectively, for (i) human protein pairs from significant biclusters (shown in grey) and (ii) all other human protein pairs from PBPs (shown in black). Panel D shows the pairwise sequence similarity distributions for (i) and (ii). These charts show that human proteins from within significant biclusters are more similar in their GO annotation and sequence than other protein pairs ( in a Mann-Whitney U test, in all cases).
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pcbi-1000863-g004: Comparison of protein pairs within significant biclusters to other protein pairs.Panels A, B and C show the semantic distance distributions for the three GO ontologies: biological process, cellular component and molecular function, respectively, for (i) human protein pairs from significant biclusters (shown in grey) and (ii) all other human protein pairs from PBPs (shown in black). Panel D shows the pairwise sequence similarity distributions for (i) and (ii). These charts show that human proteins from within significant biclusters are more similar in their GO annotation and sequence than other protein pairs ( in a Mann-Whitney U test, in all cases).

Mentions: Biclustered proteins are more similar in terms of their GO annotation than would be expected by random chance in all ontologies: molecular function, cellular component and biological function (). Semantic distance distributions for human protein pairs from within biclusters and all other PBP pairings, for each ontology are shown in figure 4, graphs A to C. We identified 75 significant biclusters that include human proteins that are significantly similar in their GO annotation, for at least one ontology, from a possible 204 significant biclusters that include two or more genes with GO annotation (). Details of the intersection between results for each ontology are given in figure 3B.


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

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

Comparison of protein pairs within significant biclusters to other protein pairs.Panels A, B and C show the semantic distance distributions for the three GO ontologies: biological process, cellular component and molecular function, respectively, for (i) human protein pairs from significant biclusters (shown in grey) and (ii) all other human protein pairs from PBPs (shown in black). Panel D shows the pairwise sequence similarity distributions for (i) and (ii). These charts show that human proteins from within significant biclusters are more similar in their GO annotation and sequence than other protein pairs ( in a Mann-Whitney U test, in all cases).
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1000863-g004: Comparison of protein pairs within significant biclusters to other protein pairs.Panels A, B and C show the semantic distance distributions for the three GO ontologies: biological process, cellular component and molecular function, respectively, for (i) human protein pairs from significant biclusters (shown in grey) and (ii) all other human protein pairs from PBPs (shown in black). Panel D shows the pairwise sequence similarity distributions for (i) and (ii). These charts show that human proteins from within significant biclusters are more similar in their GO annotation and sequence than other protein pairs ( in a Mann-Whitney U test, in all cases).
Mentions: Biclustered proteins are more similar in terms of their GO annotation than would be expected by random chance in all ontologies: molecular function, cellular component and biological function (). Semantic distance distributions for human protein pairs from within biclusters and all other PBP pairings, for each ontology are shown in figure 4, graphs A to C. We identified 75 significant biclusters that include human proteins that are significantly similar in their GO annotation, for at least one ontology, from a possible 204 significant biclusters that include two or more genes with GO annotation (). Details of the intersection between results for each ontology are given in figure 3B.

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