70% in large-scale Y2H interaction datasets for yeast [Bader and Hogue 2002, Bader et al. 2004].
Co-Immunoprecipitation/Affinity Purification (AP) Followed by Mass Spectrometry (Co-IP/AP followed by MS)
Complementing the in vivo Y2H screens are the in vitro Co-IP/AP followed by MS screens that identify whole complexes of interacting proteins, from which the binary interactions between proteins can be inferred [Golemis and Adams 2002, Rigaut et al. 1999, Köcher and Superti-Furga 2007, Dunham et al. 2012]. The Co-IP/AP followed by MS screens consist of two steps: co-immunoprecipitation/affinity purification and mass spectrometry (Figure 2.2). In the first step, cells are lysed in a radioimmunoprecipitation assay (RIPA) buffer. The RIPA buffer enables efficient cell lysis and protein solubilization while avoiding protein degradation and interference with biological activity of the proteins. A known member of the set of proteins (the protein of interest or bait) is epitope-tagged and is either immunoprecipitated using a specific antibody against the tag or purified using affinity columns recognizing the tag, giving the interacting partners (preys) of the bait. Normally, this purification step is more effective when two consecutive purification steps are used with proteins that are doubly tagged (hence called tandem affinity purification or TAP). This results in an enrichment of native multi-protein complexes containing the bait. The individual components within each such purified complex are then screened by gel electrophoresis and identified using mass spectrometry.
Figure 2.2 Schematic representation of the co-immunoprecipitation/affinity purification followed by mass spectrometry (Co-IP/AP followed by MS) protocol. The protein of interest (bait) is targeted with a specific antibody and pulled down with its interactors in a cell lysate buffer. The individual components of the pulled-down complex are identified using mass spectrometry. These days, liquid chromatography with mass spectrometry (LCMS) instead of running the gel is increasingly being used more frequently for as a combined physical-separation and MS-analysis technique [Pitt 2009].
In one of the first applications of TAP/MS, Ho et al. [2002] expressed 10% of the coding open reading frames from yeast, and the identified interactions connected 25% of the yeast proteome as multi-protein complexes. Subsequently, Gavin et al. [2002], Gavin et al. [2006], and Krogan et al. [2006] purified 1,993 and 2,357 TAP-tagged proteins covering 60% and 72% of the yeast proteome, and identified 7,592 and 7,123 protein interactions from yeast, respectively. One of the first proof-of-concept studies for humans applied AP/MS to characterize interactors using 338 bait proteins that were selected based on their putative involvement in diseases, and the study identified 6,463 interactions between 2,235 proteins [Ewing et al. 2007].
Comparison of Y2H and AP/MS Experimental Techniques
A majority of the interaction data collected so far has come from Y2H screening. For example, approximately half of the data available in databases including IntAct [Hermjakob et al. 2004, Kerrien et al. 2012] and MINT [Zanzoni et al. 2002, Chatr-Aryamontri et al. 2007] are from Y2H screens [Brückner et al. 2009] (more sources of PPI data are listed in Table 2.2). This could in part be attributed to the inaccessibility of mass spectrometry due to the expensive large equipment that is required. But, in general, Y2H and AP/MS techniques are complementary in the kind of interactors they detect. If a set of proteins form a stable complex, then an AP/MS screen can determine all the proteins within the complex, but may not necessarily confirm every interacting pair (the binary interactions) within the complex. On the other hand, a Y2H screen can detect whether any given two proteins directly interact. While stable interactions between co-complexed proteins can be accurately determined using AP/MS techniques, Y2H techniques are useful for identifying transient interactions between the proteins. However, due to considerable functional cross-talk within cells, Y2H can also report an interaction even when the proteins are not directly connected. In addition, some types of interactions can be missed in Y2H due to inherent limitations in the technique—e.g., interactions involving membrane proteins, or proteins requiring posttranslational modifications to interact—but these limitations may also occur with AP/MS-based approaches [Brückner et al. 2009]. Therefore, only a combination of different approaches that necessarily also includes computational methods (to filter out the incorrectly detected interactions) will eventually lead to a fairly complete characterization of all physiologically relevant interactions in a given cell or organism.
Protein-Fragment Complementation Assay (PCA)
PCA is a relatively new technique which can detect in vivo protein interactions as well as their modulation or spatial and temporal changes [Michnick 2003, Morell et al. 2009, Tarassov et al. 2008]. Similar to Y2H, PCA is based on the principle of splitting a reporter protein into two fragments, each of which cannot function alone [Michnick 2003]. However, unlike Y2H, PCA is based on the formation of a biomolecular complex between the bait and prey, where both are fused to the split domains of the reporter. Importantly, the formation of this complex occurs in competition with alternative endogenous interaction partners present within the cell. The interaction brings the two split fragments in proximity enabling their non-covalent reassembly, folding, and recovery of protein reporter function [Morell et al. 2009]. Typically, the reporter proteins are fluorescent proteins, and the formation of biomolecular complexes is visualized using biomolecular fluorescence complementation (BIFC). BIFC can also be used to map the interaction surfaces of these complexes. This enables investigation of competitive binding between mutually exclusive interaction partners as well as comparison of their intracellular distributions [Grinberg et al. 2004].
PCA can be used as a screening tool to identify potential interaction partners of a specific protein [Remy and Michnick 2004, Remy et al. 2007], or to validate the interactions detected from other techniques such as Y2H [Vo et al. 2016]. In one of the first applications of PCA on a genome-wide in vivo scale, Tarassov et al. [2008] identified 2,770 interactions among 1,124 proteins from S. cerevisiae. Vo et al. [2016] used PCA as an orthogonal assay to reconfirm the interactions detected in S. pombe (from the FissionNet network consisting of 2,278 interactions; discussed earlier). PCA has also been employed to validate interactions between membrane proteins or membrane-associated proteins [Babu et al. 2012, Shoemaker and Panchenko 2007] (discussed next).
Techniques for Inferring Membrane-Protein Interactions
Membrane proteins are attached to or associated with membranes of cells or their organelles, and constitute approximately 30% of the proteomes of organisms [Carpenter et al. 2008, Von Heijne 2007, Byrne and Iwata 2002]. Being non-polar (hydrophobic), membrane proteins are difficult to crystallize using traditional X-ray crystallography compared to soluble proteins, and are the least studied among all proteins using high-throughput proteomics techniques [Carpenter et al. 2008].
Membrane proteins are involved in the transportation of ions, metabolites, and larger molecules such as proteins, RNA, and lipids across membranes, in sending and receiving chemical signals and propagating electrical impulses across membranes, in anchoring enzymes and other proteins to membranes, in controlling membrane lipid composition, and in organizing and maintaining the shape of organelles and the cell itself [Lodish et al. 2000]. In humans, the G-protein-coupled-receptors (GPCRs), which are membrane proteins involved in signal transduction across membranes, alone account for 15% of all membrane proteins; and 30% of all drug targets are GPCRs [Von Heijne 2007]. Due to the key roles of membrane proteins, identifying interactions involving these proteins has important applications especially in drug development.
Membrane protein complexes are notoriously difficult to study using traditional high-throughput techniques [Lalonde et al. 2008]. Intact membrane-protein complexes are difficult to pull down using conventional AP/MS systems. This is due in part to the hydrophobic
