Building an HIV data mashup using Bio2RDF

We present an update to the Bio2RDF Linked Data Network, which now comprises ～30 billion statements across 30 data sets. Significant changes to the framework include the accommodation of global mirrors, offline data processing and new search and integration services. The utility of this new network of knowledge is illustrated through a Bio2RDF-based mashup with microarray gene expression results and interaction data obtained from the HIV-1, Human Protein Interaction Database (HHPID) with respect to the infection of human macrophages with the human immunodeficiency virus type 1 (HIV-1).     

Anti-Vpr activity of a yeast chaperone protein

Human immunodeficiency virus type 1 (HIV-1) viral protein R (Vpr) exerts multiple effects on viral and host cellular activities during viral infection, including nuclear transport of the proviral integration complex, induction of cell cycle G(2) arrest, and cell death. In this report, we show that a fission yeast chaperone protein Hsp16 inhibits HIV-1 by suppressing these Vpr activities. This protein was identified through three independent genome-wide screens for multicopy suppressors of each of the three Vpr activities. Consistent with the properties of a heat shock protein, heat shock-induced elevation or overproduction of Hsp16 suppressed Vpr activities through direct protein-protein interaction. Even though Hsp16 shows a stronger suppressive effect on Vpr in fission yeast than in mammalian cells, similar effects were also observed in human cells when fission yeast hsp16 was expressed either in vpr-expressing cells or during HIV-1 infection, indicating a possible highly conserved Vpr suppressing activity. Furthermore, stable expression of hsp16 prior to HIV-1 infection inhibits viral replication in a Vpr-dependent manner. Together, these data suggest that Hsp16 inhibits HIV-1 by suppressing Vpr-specific activities. This finding could potentially provide a new approach to studying the contribution of Vpr to viral pathogenesis and to reducing Vpr-mediated detrimental effects in HIV-infected patients.     

Genome-scale RNAi screen for host factors required for HIV replication

Human immunodeficiency virus (HIV)-1 depends on the host cell machinery to support its replication. To discover cellular factors associated with HIV-1 replication, we conducted a genome-scale siRNA screen, revealing more than 311 host factors, including 267 that were not previously linked to HIV. Surprisingly, there was little overlap between these genes and the HIV dependency factors described recently. However, an analysis of the genes identified in both screens revealed overlaps in several of the associated pathways or protein complexes, including the SP1/mediator complex and the NF-kappaB signaling pathway. cDNAs for a subset of the identified genes were used to rescue HIV replication following knockdown of the cellular mRNA providing strong evidence that the following six genes are previously uncharacterized host factors for HIV: AKT1, PRKAA1, CD97, NEIL3, BMP2K, and SERPINB6. This study highlights both the power and shortcomings of large scale loss-of-function screens in discovering host-pathogen interactions.     

Knockdown screens to knockout HIV-1

Three recent screens use siRNAs to identify host genes that are critical for HIV-1 replication. These screens have uncovered hundreds of human genes not previously known to be commandeered by the virus during infection. Although some caveats remain, this screening approach opens up a new landscape of viral-host interactions for future exploration.     

Viral Bimolecular Fluorescence Complementation: A Novel Tool to Study Intracellular Vesicular Trafficking Pathways

The Human Immunodeficiency Virus type 1 (HIV-1) accessory protein Nef interacts with a multitude of cellular proteins, manipulating the host membrane trafficking machinery to evade immune surveillance. Nef interactions have been analyzed using various in vitro assays, co-immunoprecipitation studies, and more recently mass spectrometry. However, these methods do not evaluate Nef interactions in the context of viral infection nor do they define the sub-cellular location of these interactions. In this report, we describe a novel bimolecular fluorescence complementation (BiFC) lentiviral expression tool, termed viral BiFC, to study Nef interactions with host cellular proteins in the context of viral infection. Using the F2A cleavage site from the foot and mouth disease virus we generated a viral BiFC expression vector capable of concurrent expression of Nef and host cellular proteins; PACS-1, MHC-I and SNX18. Our studies confirmed the interaction between Nef and PACS-1, a host membrane trafficking protein involved in Nef-mediated immune evasion, and demonstrated co-localization of this complex with LAMP-1 positive endolysosomal vesicles. Furthermore, we utilized viral BiFC to localize the Nef/MHC-I interaction to an AP-1 positive endosomal compartment. Finally, viral BiFC was observed between Nef and the membrane trafficking regulator SNX18. This novel demonstration of an association between Nef and SNX18 was localized to AP-1 positive vesicles. In summary, viral BiFC is a unique tool designed to analyze the interaction between Nef and host cellular proteins by mapping the sub-cellular locations of their interactions during viral infection.     

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

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.     

Network based analysis of hepatitis C virus core and NS4B protein interactions

Hepatitis C virus (HCV) is a major cause of chronic liver disease worldwide. Here we attempt to further our understanding of the biological context of protein interactions in HCV pathogenesis, by investigating interactions between HCV proteins Core and NS4B and human host proteins. Using the yeast two-hybrid (Y2H) membrane protein system, eleven human host proteins interacting with Core and 45 interacting with NS4B were identified, most of which are novel. These interactions were used to infer overall protein interaction maps linking the viral proteins with components of the host cellular networks. Core and NS4B proteins contribute to highly compact interaction networks that may enable the virus to respond rapidly to host physiological responses to HCV infection. Analysis of the interaction networks highlighted enriched biological pathways likely influenced in HCV infection. Inspection of individual interactions offered further insights into the possible mechanisms that permit HCV to evade the host immune response and appropriate host metabolic machinery. Follow-up cellular assays with cell lines infected with HCV genotype 1b and 2a strains validated Core interacting proteins ENO1 and SLC25A5 and host protein PXN as novel regulators of HCV replication and viral production. ENO1 siRNA knockdown was found to inhibit HCV replication in both the HCV genotypes and viral RNA release in genotype 2a. PXN siRNA inhibition was observed to inhibit replication specifically in genotype 1b but not in genotype 2a, while SLC25A5 siRNA facilitated a minor increase in the viral RNA release in genotype 2a. Thus, our analysis can provide potential targets for more effective anti-HCV therapeutic intervention.     

In silico prediction of HIV-1-host molecular interactions and their directionality

Human immunodeficiency virus type 1 (HIV-1) continues to be a major cause of disease and premature death. As with all viruses, HIV-1 exploits a host cell to replicate. Improving our understanding of the molecular interactions between virus and human host proteins is crucial for a mechanistic understanding of virus biology, infection and host antiviral activities. This knowledge will potentially permit the identification of host molecules for targeting by drugs with antiviral properties. Here, we propose a data-driven approach for the analysis and prediction of the HIV-1 interacting proteins (VIPs) with a focus on the directionality of the interaction: host-dependency versus antiviral factors. Using support vector machine learning models and features encompassing genetic, proteomic and network properties, our results reveal some significant differences between the VIPs and non-HIV-1 interacting human proteins (non-VIPs). As assessed by comparison with the HIV-1 infection pathway data in the Reactome database (sensitivity > 90%, threshold = 0.5), we demonstrate these models have good generalization properties. We find that the ‘direction’ of the HIV-1-host molecular interactions is also predictable due to different characteristics of ‘forward’/pro-viral versus ‘backward’/pro-host proteins. Additionally, we infer the previously unknown direction of the interactions between HIV-1 and 1351 human host proteins. A web server for performing predictions is available at http://hivpre.cvr.gla.ac.uk/.     

CD4-gp120 interaction interface - a gateway for HIV-1 infection in human: molecular network,modeling and docking studies

The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4–gp120 interaction interface has been studied through a comprehensive protein–protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.     

A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1-human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1-human interaction network. Novel HIV-1-human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed.     

A Computational Model of Inhibition of HIV-1 by Interferon-Alpha

Type 1 interferons such as interferon-alpha (IFNα) inhibit replication of Human immunodeficiency virus (HIV-1) by upregulating the expression of genes that interfere with specific steps in the viral life cycle. This pathway thus represents a potential target for immune-based therapies that can alter the dynamics of host-virus interactions to benefit the host. To obtain a deeper mechanistic understanding of how IFNα impacts spreading HIV-1 infection, we modeled the interaction of HIV-1 with CD4 T cells and IFNα as a dynamical system. This model was then tested using experimental data from a cell culture model of spreading HIV-1 infection. We found that a model in which IFNα induces reversible cellular states that block both early and late stages of HIV-1 infection, combined with a saturating rate of conversion to these states, was able to successfully fit the experimental dataset. Sensitivity analysis showed that the potency of inhibition by IFNα was particularly dependent on specific network parameters and rate constants. This model will be useful for designing new therapies targeting the IFNα network in HIV-1-infected individuals, as well as potentially serving as a template for understanding the interaction of IFNα with other viruses.     

Carboxyl terminus of hVIP/mov34 is critical for HIV-1-Vpr interaction and glucocorticoid-mediated signaling

Human immunodeficiency virus, type 1 (HIV-1) vpr is a highly conserved gene among lentiviruses. The diverse functions of Vpr support interactions of this HIV accessory protein with host cell partners of important pathways. hVIP/mov34 (human Vpr Interacting Protein) is one of these identified Vpr ligands. hVIP is a 34-kDa member of the eIF3 family that is vital for early embryonic development in transgenic mice and important in cell cycle regulation. Its interaction with Vpr, however, is not yet clearly defined. Therefore, we constructed a panel of deletion mutants of this cytoplasmic cellular ligand to map the protein domain that mediates its interaction with Vpr. We observed that the carboxyl-terminal region of hVIP is critical for its interaction with Vpr. In the absence of Vpr or HIV infection, full-length hVIP is expressed in the cytoplasm. The cytoplasmic localization pattern of full-length hVIP protein, however, is shifted to a clear nuclear localization pattern in cells expressing both hVIP and Vpr. In contrast, Vpr did not alter the localization pattern of hVIP mutants, which have their carboxyl-terminal domain deleted. The movement of hVIP supported prior work that suggested that Vpr triggers activation of the GR receptor complex. In fact, we also observed that dexamethasone moves hVIP into the nucleus and that glucocorticoid antagonists inhibit this effect. Interestingly, the expression of an hVIP carboxyl-terminal mutant, which is not responsive to Vpr, is also not responsive to dexamethasone. These data illustrate that the carboxyl-terminal domain of hVIP is critical for mediating hVIP-Vpr interaction as well as for its glucocorticoid response. These results support the view that hVIP is a member of the complex array of nucleocytoplasmic shuttling proteins that are regulated by HIV infection and glucocorticoids.     

The biological context of HIV-1 host interactions reveals subtle insights into a system hijack

Background  

In order to replicate, HIV, like all viruses, needs to invade a host cell and hijack it for its own use, a process that involves multiple protein interactions between virus and host. The HIV-1, Human Protein Interaction Database available at NCBI's website captures this information from the primary literature, containing over 2,500 unique interactions. We investigate the general properties and biological context of these interactions and, thus, explore the molecular specificity of the HIV-host perturbation. In particular, we investigate (i) whether HIV preferentially interacts with highly connected and 'central' proteins, (ii) known phenotypic properties of host proteins inferred from essentiality and disease-association data, and (iii) biological context (molecular function, processes and location) of the host proteins to identify attributes most strongly associated with specific HIV interactions.