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Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks.

van Dijk D, Ertaylan G, Boucher CA, Sloot PM - BMC Syst Biol (2010)

Bottom Line: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation.We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes.Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Science, University of Amsterdam, Sciencepark 107, 1098 XG Amsterdam, The Netherlands. d.vandijk@uva.nl

ABSTRACT

Background: The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics.

Results: Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems.

Conclusions: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

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Degree distributions of HDFs on a log-log scale. P(k) is the fraction of nodes with degree k. A: Only connections of HDFs to HIV proteins. B: Only HDF-HDF connections. Both distributions were fitted with a power law (P(k) = k-γ) with A: γ = 2.3, and B: γ = 2.3, showing the scale-free nature of both networks.
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Figure 4: Degree distributions of HDFs on a log-log scale. P(k) is the fraction of nodes with degree k. A: Only connections of HDFs to HIV proteins. B: Only HDF-HDF connections. Both distributions were fitted with a power law (P(k) = k-γ) with A: γ = 2.3, and B: γ = 2.3, showing the scale-free nature of both networks.

Mentions: HIV has many interactions with human proteins, and on many levels. Yet these interactions become meaningful only when we can put them into context. Therefore we have enriched our HIV-1 human protein interaction network with interactions from human protein interaction databases BIND, BioGRID and HPRD (see methods). First we have included interactions between the HDFs (the local network) and interactions with non-HDF human proteins (the global network). The resulting network is a human protein interaction network where HIV interacting human proteins or HDFs are connected to each other and also to non-HDF human proteins. Figure 3 shows an abstract representation of the structure of this network. In Figure 4 two degree distributions of the networks are shown. In Figure 4-A, we can see the degree distribution of HDFs considering only interactions with HIV proteins. In Figure 4-B, we only consider the HDF-HDF interactions. On both graphs the power-law distribution indicates the scale-free nature of the networks, caused by a topology where most proteins have few connections, but a small number of proteins are highly connected, thus acting as hubs. Networks with scale-free properties are thought to be resilient to random perturbations and are therefore robust [5].


Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks.

van Dijk D, Ertaylan G, Boucher CA, Sloot PM - BMC Syst Biol (2010)

Degree distributions of HDFs on a log-log scale. P(k) is the fraction of nodes with degree k. A: Only connections of HDFs to HIV proteins. B: Only HDF-HDF connections. Both distributions were fitted with a power law (P(k) = k-γ) with A: γ = 2.3, and B: γ = 2.3, showing the scale-free nature of both networks.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2913931&req=5

Figure 4: Degree distributions of HDFs on a log-log scale. P(k) is the fraction of nodes with degree k. A: Only connections of HDFs to HIV proteins. B: Only HDF-HDF connections. Both distributions were fitted with a power law (P(k) = k-γ) with A: γ = 2.3, and B: γ = 2.3, showing the scale-free nature of both networks.
Mentions: HIV has many interactions with human proteins, and on many levels. Yet these interactions become meaningful only when we can put them into context. Therefore we have enriched our HIV-1 human protein interaction network with interactions from human protein interaction databases BIND, BioGRID and HPRD (see methods). First we have included interactions between the HDFs (the local network) and interactions with non-HDF human proteins (the global network). The resulting network is a human protein interaction network where HIV interacting human proteins or HDFs are connected to each other and also to non-HDF human proteins. Figure 3 shows an abstract representation of the structure of this network. In Figure 4 two degree distributions of the networks are shown. In Figure 4-A, we can see the degree distribution of HDFs considering only interactions with HIV proteins. In Figure 4-B, we only consider the HDF-HDF interactions. On both graphs the power-law distribution indicates the scale-free nature of the networks, caused by a topology where most proteins have few connections, but a small number of proteins are highly connected, thus acting as hubs. Networks with scale-free properties are thought to be resilient to random perturbations and are therefore robust [5].

Bottom Line: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation.We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes.Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

View Article: PubMed Central - HTML - PubMed

Affiliation: Computational Science, University of Amsterdam, Sciencepark 107, 1098 XG Amsterdam, The Netherlands. d.vandijk@uva.nl

ABSTRACT

Background: The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics.

Results: Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems.

Conclusions: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

Show MeSH
Related in: MedlinePlus