Protein–protein interaction networks have been generated using AP-MS and Y2H targeting various organisms, ranging from bacteria to humans. Yeast two-hybrid screenings consist of testing all pair wise combinations of proteins, which generates a collection of binary interactions. High-throughput Y2H maps have been generated for Saccharomyces cerevisiae [16
], Caenorhabditis elegans
] and humans [10
]. Affinity tag purification-mass spectrometry approaches identify groups of proteins that participate in complexes and these have been used to study the cellular make-up of Escherichia coli
], S. cerevisiae
] and human cells [14
]. While AP-MS assays have a higher propensity of detecting stable, stoichiometric complexes, Y2H screens tend to detect transient protein interactions [47
]. Therefore the data from both approaches are complementary with respect to revealing physical connections between proteins, complexes and biological processes.
These unbiased approaches have also been used to study PPIs between proteins that are derived from a specific virus. For example, an intraviral Hepatitis C (HCV) Y2H interaction map was built using a limited set of predefined coding segments, which revealed the functional interactions between the proteins in the viral life cycle when a cell culture system is absent [15
]. Also, using a Y2H approach, intraviral protein–protein interaction networks have been generated for two herpesviruses, Kaposi sarcoma-associated herpesvirus (KSHV) and Varicella-Zoster virus (VZV) [40
]. The resulting PPI networks appear as a single highly connected module whereas cellular networks (e.g. yeast and human) have been observed to be organized in functional modules. Despite a broad range of pathogenicity, herpesviruses share a significant percentage of common conserved genes and the authors attempted to define a core set of interactions conserved among these viruses. Calderwood et al. proteomically interrogated another herpesvirus, Epstein-Barr virus (EBV), by classifying the genes into two evolutionary classes based on conservation and showed enrichment for interactions among proteins in the same evolutionary class [6
]. Another example of an intraviral PPI network based yeast-two-hybrid matrix analysis was obtained for SARS coronavirus [43
]. SARS-CoV has 14 ORFs, most of whose functions are unknown. Interestingly, one of the accessory proteins turned out to be highly connected, and the authors propose that although not essential for viral replication in cell culture systems, it could enhance the global stability of the SARS proteome network and pathogenicity.
These pair-wise interaction studies have also been extended into studying the interaction landscape between viral proteins and host factors. For example, Lotteau and colleagues published a proteome-wide, Y2H-based mapping of interactions among HCV and human proteins. They reported 314 interactions (in addition to 170 literature curated interactions) and discovered that HCV CORE protein was a major perturbator of the insulin, Jak/STAT and TGFβ pathways [11
]. More recently, another study targeted Vaccinia virus, a large double stranded DNA virus with more than 280 ORFs and a prototype of the Orthopoxvirus, which includes several pathogenic poxviruses such as variola virus, a lethal human-specific pathogen that causes smallpox [49
]. The authors reported a comprehensive yeast-two hybrid screening with 109 protein–protein interactions between vaccinia proteins and human proteins and provided functional insight into a number of uncharacterized viral proteins. Finally, Shapira et al. introduced a multilayered approach to uncover pathways in H1N1 infection by combining yeast-two-hybrid analysis and genome-wide expression profiling [38
]. They found human factors mediating virus–host interactions, which were further studied via depletion analysis in primary lung cells. These types of unbiased physical and regulatory models of virus–host interactions provide a promising direction for the unveiling of new virus biology and development of new viral drugs [31
Collectively, the global network properties of human proteins targeted by pathogens, including bacteria and viruses, were recently studied [13
]. It was observed that pathogenic proteins preferentially interact with human hub proteins and “bottleneck” factors in human pathways. Although 190 pathogens were analyzed in this study, 98.3% of the interactions were obtained from viruses and 77.9% of them were associated with HIV. Interactions of each of its 18 proteins have been individually studied in numerous labs, mostly using Y2H, but also AP/MS, in vitro
binding and other methodologies. In an attempt to catalog these data, the National Institute of Allergy and Infectious Diseases Division of AIDS (NIAID) has initiated the development of an HIV-1 Human Protein Interaction database [33
]. From HIV relevant publications, 2589 unique HIV-human PPIs among 1448 human proteins were curated (); 32% of these interactions are reported to be direct, physical interactions. Surprisingly, 37% of the human proteins on this list interact with more than one HIV-1 protein. For example, mitogen-activated protein kinase 1 (MAPK1), a signaling protein, has been described to interact with 10 HIV proteins.
Fig. 1 Literature derived HIV–human protein–protein interaction map. A network displaying HIV-human interactions derived from the National Institute of Allergy and Infectious Diseases Division of AIDS (NIAID) HIV-1 Human Protein Interaction Database. (more ...)
Since the HIV-human interactions are mostly literature-curated [8
], it is hard to know if the nature of the interactions are physiologically relevant or due to the apparent bias in the literature towards highly studied proteins [48
]. The fact that the number of direct interactions reported for each protein vary considerably, ranging from only one for polymerase or reverse transcriptase and up to 219 for the 14 kDa protein Tat, suggests that this database includes false positives for some proteins while for others there still might be host interactors to be discovered. Therefore, although there have been a variety of excellent studies on HIV-1 human interactions, providing invaluable information about host factors crucial for HIV pathogenicity, a systematic approach of building the HIV-1–host protein–protein interaction network would help to get a clearer picture of the interconnection of the different virus components with the host cell. In this paper, we describe such an approach, based on AP-MS methodology, and describe how it can be used to proteomically interrogate HIV as well as other viruses.