Fundamentals of protein interaction network mapping
2015; Springer Nature; Volume: 11; Issue: 12 Linguagem: Inglês
10.15252/msb.20156351
ISSN1744-4292
AutoresJamie Snider, Max Kotlyar, Punit Saraon, Zhong Yao, Igor Jurišica, Igor Štagljar,
Tópico(s)Fungal and yeast genetics research
ResumoReview17 December 2015Open Access Fundamentals of protein interaction network mapping Jamie Snider Jamie Snider Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Max Kotlyar Max Kotlyar Princess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada Search for more papers by this author Punit Saraon Punit Saraon Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Zhong Yao Zhong Yao Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Igor Jurisica Igor Jurisica Princess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada Search for more papers by this author Igor Stagljar Corresponding Author Igor Stagljar Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Jamie Snider Jamie Snider Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Max Kotlyar Max Kotlyar Princess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada Search for more papers by this author Punit Saraon Punit Saraon Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Zhong Yao Zhong Yao Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Igor Jurisica Igor Jurisica Princess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada Search for more papers by this author Igor Stagljar Corresponding Author Igor Stagljar Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for more papers by this author Author Information Jamie Snider1, Max Kotlyar2, Punit Saraon1, Zhong Yao1, Igor Jurisica2 and Igor Stagljar 1 1Donnelly Centre, Department of Biochemistry, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada 2Princess Margaret Cancer Center, IBM Life Sciences Discovery Centre, University Health Network, Ontario, Canada *Corresponding author. Tel: +1 416 946 7828; Fax: +1 416 978 8287; Email: [email protected] Molecular Systems Biology (2015)11:848https://doi.org/10.15252/msb.20156351 PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Studying protein interaction networks of all proteins in an organism (“interactomes”) remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow-up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research. The importance of studying PPIs As the basic unit of life, cells represent complex biological entities, whose normal function revolves around a delicate interplay between multiple diverse biomolecular systems. Proteins are vital components of these systems, acting as molecular machines, sensors, transporters, and structural elements (among others), with interactions between proteins, hereinafter called protein–protein interactions (PPIs), being key to their function. Protein–protein interactions are inherently dynamic in nature, adjusting in response to different stimuli and environmental conditions. This provides considerable flexibility in function and allows cells to adapt in a measured way to changing circumstances. Even a subtle dysfunction of PPIs can have major systemic consequences, perturbing interconnected cellular networks and producing disease phenotypes (Barabási et al, 2011). Developing in-depth, dynamic PPI maps is therefore critically important in helping us comprehend these complex processes, and identify new proteins and PPIs suitable for therapeutic intervention. Over the years, we have seen an emergence and growth of a wide range of exciting technologies for the identification and characterization of PPIs. Selecting “the best” technology for a given research application is thus non-trivial. Here, we highlight the strengths and weaknesses of various methodologies, to aid in selecting the appropriate method for the problem at hand. Note that this review does not aim to cover all PPI methods; instead, we focus on newer approaches and earlier methods that remain widely used, and strongly impacted research. Key considerations While numerous methods are available for the large-scale study of PPIs, there is no one “perfect” method for all situations, and each has its own strengths and weaknesses. When selecting a suitable method to study interacting partners of a protein of interest, the following factors should be considered: The Goal of the Study must be clearly defined. Discovery-driven studies usually aim to explore interactomes in an unbiased manner on a proteome-wide scale. In contrast, targeted interactome studies focus on a subset of PPIs and therefore confine themselves to smaller libraries or arrays corresponding to a defined set of candidate interaction partners. Different methods are better suited to certain classes of proteins as well as to formats and scales, and selection of one that best matches the research goals is critical. The Distinct Nature of the PPIs Being Studied. All PPIs have intrinsic biophysical properties, giving each its own unique features. Some important characteristics to consider are the PPI “strength” (binding affinity), and whether the interaction is transient or stable (Perkins et al, 2010). Different bioassays display variable sensitivity, and although generally all can detect stable PPIs, only a fraction are capable of detecting transient interactions. It is also important to determine whether or not posttranslational modifications, co-factors, or additional binding partners are required (e.g., a PPI may be mediated indirectly through a protein complex), as well as where in the cell interactions are expected to occur, since the selected assay must be compatible with these elements. Time/Cost Constraints. Not all methods scale-up equally, and some, while offering powerful advantages on a smaller-scale, can become significantly more expensive and time-consuming as the number of interactions studied increases. Additionally, the time and cost required to develop the necessary reagents (e.g., specific constructs, libraries) needs to be considered. Specialized Equipment and Expertise. Finally, it is important to ensure that all necessary resources and knowledge required to fully take advantage of a particular method are available. Although the majority of methods are straightforward, some do require specific instrumentation and expertise. Most methods, especially those that attempt to study interactomes on a genomewide scale, also require strong bioinformatics support for analysis and data cleaning. Guide to available methods While many PPI assays exist, we present below some of the newer and more widely used approaches, providing a concise overview of their key principles, advantages, and limitations. Key references for each technique, including examples of their large-scale application, can also be found in Table 1. Table 1. Useful literature references for protein–protein interactions (PPI) methods Assay Relevant literature reviewing or introducing technique Examples of interaction studies using technique Y2H Hamdi and Colas (2012); Ferro and Trabalzini (2013); Stasi et al (2015) Yu et al (2008); Weimann et al (2013); Rajagopala et al (2014); Rolland et al (2014); Grossmann et al (2015) MYTH Snider et al (2010); Petschnigg et al (2012) Snider et al (2013); Lam et al (2015); Gulati et al (2015) LUMIER Blasche and Koegl (2013) Barrios-Rodiles et al (2005); Xu et al (2014); Taipale et al (2014); Sahni et al (2015) MAPPIT Sahni et al (2015); Lievens et al (2011); Lemmens et al (2015) Lievens et al (2009); Bovijn et al (2013); Rolland et al (2014) KISS Lievens et al (2014) Amano et al (2015) BIFC Kerppola (2008); Zhang et al (2015) Lee et al (2011b); Snider et al (2013); Cooper et al (2015) MaMTH Petschnigg et al (2014) – BRET/FRET Ciruela (2008); Xie et al (2011); Ma et al (2014) Kocan et al (2008); Audet et al (2010); Mandić et al (2014); Sauvageau et al (2014) AP-MS Dunham et al (2012) Wang and Huang (2008); Babu et al (2012); Havugimana et al (2012) BioID-MS Roux et al (2012) Kim et al (2014); Dingar et al (2015); Lambert et al (2015) PLA Koos et al (2014) Chen et al (2014) LRC-TriCEPS Frei et al (2013) Frei et al (2012) AVEXIS Sanderson (2008); Kerr and Wright (2012); Sun et al (2012) Bushell et al (2008); Martin et al (2010); Crosnier et al (2011) The yeast two hybrid (Y2H) Principle Originally developed 25 years ago (Fields & Song, 1989), the Y2H assay (Fig 1A) remains one of the most popular PPI methods. Y2H-based systems can be used to detect interactions between two proteins, protein and nucleic acid, and also in small-molecule screens (Hamdi & Colas, 2012; Ferro & Trabalzini, 2013). The classic Y2H involves the physical separation of two functional moieties of a transcription factor, specifically a DNA-binding domain (BD) and a transcriptional activation domain (AD), and their fusion to candidate interacting proteins. If a protein bearing an AD interacts with, or comes in close proximity to, a protein bearing a BD, the AD and BD are able to function together as a transcription factor, and direct expression of a reporter gene (Fields & Song, 1989). Figure 1. Overview of interaction proteomics technologiesSchematic representations of selected newer and widely used PPI assays. (A) Yeast Two Hybrid (Y2H). (B) Membrane Yeast Two Hybrid (MYTH) and Mammalian Membrane Two Hybrid (MaMTH). (C) Luminescence-based Mammalian Interactome Mapping (LUMIER). (D) Mammalian Protein-Protein Interaction Trap (MAPPIT). (E) Kinase Substrate Sensor (KISS). (F) Bimolecular Fluorescence Complementation (BiFC). (G) Bioluminescence/Fluorescence Resonance Energy Transfer (B/FRET). (H) Affinity Purification-Mass Spectrometry (AP-MS). (I) Proximity-dependent Biotin Identification Coupled to Mass Spectrometry (BioID-MS). (J) Proximity Ligation Assay (PLA). (K) Ligand-Receptor Capture-Trifunctional Chemoproteomics Reagents (LRC-TRiCEPS). (L) Avidity-based Extracellular Interaction Screen (AVEXIS). Download figure Download PowerPoint Advantages The Y2H approach is simple, well established, and low cost and can be easily set up in most laboratory environments. Y2H is scalable and effective for use in both large-scale screening studies, and smaller efforts investigating specific PPIs. Another benefit is that the assay is carried out in vivo in the context of the yeast cell, helping avoid some of the complications and artifacts associated with cell lysis. This assay is best suited for the detection of binary interactions (Hamdi & Colas, 2012; Ferro & Trabalzini, 2013). Limitations The use of a yeast host means that the PPIs from other organisms may in some cases not be detectable, due to poor expression, or a lack of necessary posttranslational modifications, cofactors, or other binding partners. The method requires that both interacting proteins access the nucleus (in order to drive transcription of reporter), which means that proteins confined to particular cellular environments (e.g., the membrane) cannot be studied in their full-length form. The proteins used in this method are also often overexpressed, which can lead to non-specific interactions. Altogether, these effects can lead to a high false-positive rate, necessitating careful follow-up analysis to identify true, biologically relevant interactions. The readout of this method is also indirect, preventing spatial or temporal analysis of PPIs (Hamdi & Colas, 2012; Ferro & Trabalzini, 2013). Membrane yeast two hybrid (MYTH) Principle The MYTH assay (Fig 1B) is designed for the analysis of the interactions of membrane proteins. It is based on a split-ubiquitin approach, whereby the ubiquitin protein is divided into two distinct fragments—an N-terminal fragment called “Nub” and a C-terminal fragment called “Cub”. The Cub moiety is conjugated to an artificial transcription factor and then fused to a cytosolic terminus of a membrane-bound protein (the “bait”). The Nub moiety is fused to potential interacting partners (“preys”), which can be either membrane-associated or soluble. Interaction of bait and prey proteins brings the Nub and Cub moieties into close proximity, allowing them to form a “pseudoubiquitin” molecule, which is recognized by cellular deubiquitinating enzymes that cleave after the Cub C-terminus. This releases the transcription factor, which then enters the nucleus and activates a reporter system (Stagljar et al, 1998; Snider et al, 2010). Advantages Membrane yeast two hybrid is simple, low cost, and scalable for use in both low- and high-throughput (HT) formats. It is easy to establish in any laboratory environment and requires no specialized equipment. The assay is performed in vivo in a yeast host, allowing for the study of the interactions of membrane proteins in their full-length form and in the proper context of a membrane environment. This is a significant advantage over the classical Y2H. MYTH is best suited for the detection of binary interactions(Paumi et al, 2007; Deribe et al, 2009; Snider et al, 2010, 2013). Limitations Membrane yeast two hybrid suffers from some of the same disadvantages as the classical Y2H, including the problems associated with the expression, modification, and interaction of non-native proteins in a yeast host, and artifacts resulting from protein overexpression. Also, MYTH can only be used with membrane proteins that have at least one terminus in the cytosol (where the necessary deubiquitinating enzymes are located). Additionally, soluble proteins cannot be used as baits in the MYTH system, unless they are exceptionally large or anchored to intracellular structures (thereby preventing diffusion of the bait-transcription factor into the nucleus and interaction-independent activation of the reporter system). The readout of this method is also indirect, preventing spatial or temporal analysis of PPIs (Snider et al, 2010). Luminescence-based mammalian interactome mapping (LUMIER) Principle The LUMIER assay (Fig 1C) is a co-immunoprecipitation-based approach. In this method, one protein (“A”) is fused to Renilla luciferase, while another protein (“B”) is linked to an affinity tag (e.g., FLAG, HA, protein A). Tagged constructs are transfected into appropriate cell lines where they are overexpressed. Cells are then lysed and protein “B” is immunoprecipitated using an appropriate antibody against the affinity tag. Interaction with protein “A” is assessed by measuring luciferase activity brought down with protein “B” (Barrios-Rodiles et al, 2005; Blasche & Koegl, 2013). Advantages The LUMIER assay is easy to perform and can be used in a HT screening format. It does not require specialized equipment, beyond standard reagents for cell culture and instrumentation to measure bioluminescence. The approach can be used in different cell lines, providing the option of studying PPIs for a given organism in an appropriate ex vivo format. Note that this assay is well suited for studying binary interactions, although indirect interactions can also be detected (Barrios-Rodiles et al, 2005; Blasche & Koegl, 2013; Taipale et al, 2014). Limitations A major disadvantage of the LUMIER method is that it requires lysis of cells prior to immunoprecipitation, a process that can result in the disruption of weak and transient PPIs, as well as the introduction of potential artifacts (e.g., by bringing together proteins in the lysate, which might not normally interact with one another in the cell, destabilizing proteins and exposing previously concealed non-native binding surfaces). The LUMIER assay must be carefully controlled, to normalize for differences in transfection efficiency and expression, and minimize background signal. The assay is not ideal for studying how PPIs change spatially, over time or in response to different environmental conditions (Barrios-Rodiles et al, 2005; Blasche & Koegl, 2013). Mammalian protein–protein interaction trap (MAPPIT) Principle The MAPPIT assay (Fig 1D) is designed for use in mammalian cell lines and is based on a cytokine signal transduction mechanism. A “bait” protein is fused to the C-terminus of a cytokine receptor deficient in binding to STAT3 (required for signal transduction), while “prey” proteins are fused to receptor fragments containing functional STAT3 recruitment sites. An interaction between a bait and prey proteins produces a functionally competent receptor, which, in response to cytokine ligand stimulation, activates STAT3 molecules (through intermediate JAK kinase activity), allowing them to enter the nucleus and induce transcription of a reporter system (e.g., luciferase; Ulrichts et al, 2009). Advantages Mammalian protein–protein interaction trap provides a powerful way to examine mammalian PPIs directly in the context of the mammalian cell and is suitable for use in both HT library and array screening formats. The assay is easy to perform and does not require specialized equipment, beyond the necessary cell culture reagents and instrumentation to measure bioluminescence or fluorescence. Note that this method is best suited for studying binary interactions (Lievens et al, 2009, 2011). Variations of MAPPIT are effective for use in small-molecule screening approaches (Eyckerman et al, 2005; Caligiuri et al, 2006; Lievens et al, 2011). Limitations Anchoring of the interaction sensor (i.e., the cytokine receptor) to the plasma membrane requires that PPIs occur in the cytoplasmic submembrane region, preventing detection of interaction with preys localized to other subcellular compartments. This anchoring (and the large size of the bait tag) may also block certain PPIs due to steric issues beyond those occurring in many other methodologies (Lievens et al, 2009). Finally, the method is also not compatible with full-length transmembrane proteins and is not suitable for spatial or temporal analysis of PPIs. Kinase substrate sensor (KISS) Principle Kinase substrate sensor (Fig 1E) is a recently developed mammalian two-hybrid approach designed to measure intracellular PPIs. In this assay, a “bait” protein is fused to the kinase domain of TYK2, while “preys” are coupled to a gp130 cytokine receptor fragment carrying TYK2 substrate motifs. Interaction of bait and prey results in phosphorylation of gp130 by TYK2, resulting in docking and activation of STAT3, which can then enter the nucleus and activate transcription of a STAT3-dependent reporter system (e.g., luciferase; Lievens et al, 2014). Advantages Kinase substrate sensor allows assessment of PPIs directly in living mammalian cells and is sensitive enough to detect dynamic changes in response to physiological or pharmacological challenges. The method is effective for use with both membrane and cytosolic proteins and is best suited for measuring binary interactions (Lievens et al, 2014). Limitations Like many other assays, the KISS readout is indirect, preventing spatial or temporal analysis of PPIs. The assay relies on endogenous STAT3, making this approach unsuitable for studying interactions involving proteins or stimuli that affect STAT3 signaling (Lievens et al, 2014). Bimolecular fluorescence complementation (BiFC) Principles Bimolecular fluorescence complementation (Fig 1F) is based on the division of a fluorescent protein (e.g., YFP) into two distinct non-fluorescent fragments, which are then fused to “bait” and “prey” proteins of interest. Interaction between bait and prey allows the two non-fluorescent fragments to associate and form a fluorescent complex, which can be viewed by microscopy or flow cytometry (Kerppola, 2008; Zhang et al, 2015). Advantages Bimolecular fluorescence complementation allows direct visualization of PPIs in living cells, providing spatial information about the subcellular location where PPIs are occurring. The method is highly sensitive and can be used to detect interactions between proteins expressed at endogenous or near-endogenous levels, as well as weak and transient interactions. The method can be used for different organisms, is simple to set up, and is cost-effective. Different fluorescent proteins can also be used in combination, allowing the visualization of multiple PPIs in parallel in single cells. The method is best suited for detecting binary interactions (Hu et al, 2002; Kerppola, 2008; Zhang et al, 2015). Limitations Bimolecular fluorescence complementation is not ideal for measuring PPI dynamics or real-time changes, due to a delay in generation of fluorescence upon protein interaction, as well as the irreversible nature of fluorochrome formation (Kerppola, 2008). Another disadvantage of BiFC includes functionality of fusion proteins, as is the case for other techniques involving protein tagging. Lastly, in some cases false-positive fluorescent signals can be detected by BiFC due to fluorescence intensity of reconstituted fragments arising irrespective of (or from non-specific) interaction between two proteins under investigation (Miller et al, 2015). Mammalian membrane two hybrid (MaMTH) Principle Mammalian membrane two hybrid (Fig 1B) is a recently developed in vivo proteomics technology designed for the analysis of mammalian membrane PPIs. The assay is based on the principle of split-ubiquitin, wherein reconstitution of inactive fragments of ubiquitin (Nub and Cub) upon interaction of proteins to which they are fused leads to release of an artificial transcription factor, and subsequent expression of a reporter system (luciferase in the case of MaMTH; Petschnigg et al, 2014). Advantages Mammalian membrane two hybrid allows the analysis of the interactions of full-length mammalian membrane proteins directly in their natural cellular context. The assay is low cost, highly scalable, and readily transferable to virtually any cell line of interest. No specialized equipment is required, beyond standard cell culture reagents and tools necessary for monitoring luciferase activity. One of the key advantages of MaMTH is its high sensitivity, making it suitable for both the measurement of weak/transient interactions, and for monitoring dynamic, “condition-dependent” PPIs (i.e., which change in response to agonist, phosphorylation state, mutation etc.). The method is best suited for the detection of binary PPIs (Petschnigg et al, 2014). Limitations For MaMTH to function, the bait must be associated with the membrane or other intracellular structures, to prevent non-specific activation of the reporter system (note that like MYTH, preys can be either soluble or membrane-bound). Additionally, the termini of the membrane protein fused to Cub must be cytosolic, in order to provide access to the deubiquitinating proteases responsible for cleavage and release of transcription factor. The method is also not suitable for spatial or real-time temporal analysis of PPIs (Petschnigg et al, 2014). Fluorescence resonance energy transfer (FRET) Principle Fluorescence resonance energy transfer (Fig 1G) is based on the non-radiative transfer of energy from an excited donor fluorophore to a nearby acceptor molecule. Donor and acceptors are selected such that the absorption spectrum of the acceptor fluorophore overlaps with the emission spectrum of the donor. In this approach, one protein of interest is fused to the donor, while the other is fused to the acceptor. If the two proteins interact or come into close proximity with one other, the donor and acceptor fluorophores are also brought together. Excitation of the donor in this case does not lead to photon release, but rather energy transfer to the nearby acceptor, which in turn produces an emission signal. This emission signal is distinct from the signal that would be observed for donor alone, and is used to monitor PPI (Ma et al, 2014). Advantages A major advantage of FRET is its ability to monitor instantaneous, real-time PPIs, allowing the measurement of short-lived transient interactions. In addition, FRET can be used directly in the context of live cells and allows detection of interaction sites. Also, due to the reversible nature of the fluorophore interaction, complex interaction dynamics can be monitored such as the dynamic equilibrium between complex formation and dissociation (Ma et al, 2014). Limitations For FRET to function, protein fusions to appropriate fluorophores need to be generated (the technical demands of which may vary depending upon the fluorophores selected). In addition, for a strong FRET readout, close spatial proximity of the fluorophores is required for the energy transfer to occur. FRET also has decreased sensitivity compared to other fluorescence-based approaches like BiFC or BRET, as there tends to be strong background autofluorescence in cells upon sample illumination. For this reason, many controls are necessary to quantify the changes in fluorescence intensity in the presence and absence of energy transfer, and particularly weak interactions producing a signal close to background may be difficult to detect. Depending upon the fluorophores selected, photobleaching can also result in loss of signal over time (Boute et al, 2002; Ma et al, 2014). Bioluminescence resonance energy transfer (BRET) Principle The BRET assay (Fig 1G) has been developed to diminish a major limitation of FRET—the strong background signal that results from the direct excitation between the donor and acceptor fluorophores. In BRET, a protein of interest is fused to Renilla luciferase (“RLuc”, serving as the energy donor), while its interacting partner is fused to either green or yellow fluorescent protein (GFP or YFP, serving as the energy acceptor). When donors and acceptors are brought into close proximity (< 100 Å) by interaction of their fusion partners, energy transfer occurs, producing fluorescent signal which is monitored to detect the PPIs (Boute et al, 2002; Hamdan et al, 2006). Advantages Like FRET, BRET is able to monitor instantaneous real-time PPIs, functions directly in the context of live cells, and provides information about the cellular location at which an interaction occurs (Boute et al, 2002; Hamdan et al, 2006; Xie et al, 2011). However, BRET also has greater sensitivity than FRET, with lower background (Boute et al, 2002). Limitations The major limitations of BRET are similar to those of FRET, including the need for the generation of fusion proteins, and the efficiency of the assay being dependent on close spatial proximity of the donor and acceptor (in order for proper energy transfer to occur; Hamdan et al, 2006). BRET signal also tends to be significantly weaker than that produced by FRET (Hamdan et al, 2006; Xie et al, 2011). In addition, the analysis of PPIs using BRET and FRET is not as easily scalable to HT screening applications as other methods, making it better suited to screens involving a more limited number of potential hits. Affinity purification–mass spectrometry (AP-MS) Principle Affinity purification–mass spectrometry (Fig 1H) is a popular technology that has gained considerable attention over the past decade. The general principle involves immobilization of “bait” protein of interest on a solid support (most frequently agarose or magnetic beads), and use of this coupled “bait” to capture target protein(s) from a soluble phase. Once affinity-purified, captured proteins are usually digested with proteases (e.g., trypsin), to generate peptides, which in turn are sub-fractionated using high-pressure liquid chromatography (HPLC) and then ionized and detected using a mass spectrometer. AP-MS can be conducted either with endogenous, native protein baits (using specific antibodies raised against them) or with protein baits to which a standardized “epitope tag” (e.g., TAP-, FLAG-, c-myc-, HA-, His-, protein A-, Strep-Tag) is fused. The choice of the most appropriate affinity purification method depends on a combination of factors, including the availability of antibodies, the type of a protein under investigation, and the scale of the conducted analysis (Dunham et al, 2012). Advantages Affinity purification–mass spectrometry is a library-independent method with true genomewide H
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