Here we present protocols for affinity purification of protein complexes and their separation by blue native PAGE, followed by protein correlation profiling using label free quantitative mass spectrometry. This method is useful to resolve interactomes into distinct protein complexes.
Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological processes. Affinity purification coupled to mass spectrometry (AP-MS) has become the method of choice for identifying protein-protein interactions. However, conventional AP-MS studies provide information on protein interactions, but the organizational information is lost. To address this issue, we developed a strategy to unravel the distinct functional assemblies a protein might be involved in, by resolving affinity-purified protein complexes prior to their characterization by mass spectrometry. Protein complexes isolated through affinity purification of a bait protein using an epitope tag and competitive elution are separated through blue native electrophoresis. Comparison of protein migration profiles through correlation profiling using quantitative mass spectrometry allows assignment of interacting proteins to distinct molecular entities. This method is able to resolve protein complexes of close molecular weights that might not be resolved by traditional chromatographic techniques such as gel filtration. With little more work than conventional AP-geLC-MS/MS, we demonstrate this strategy may in many cases be adequate for obtaining protein complex topological information concomitantly to identifying protein interactions.
In cells, most proteins perform their functions through transitory protein-protein interactions or by forming stable protein assemblies. Characterizing protein interactions is crucial for fully understanding cellular processes. Affinity purification in combination with mass spectrometry (AP-MS) is one of the most commonly applied strategies to identify native protein interactions. Significant improvements in instrument capabilities achieved in the last decade have made this approach extremely powerful. It is important to note that the interactions identified by AP-MS experiments include a mixture of direct and indirect associations between bait and preys. In addition, often proteins take part in several different complexes within the same cellular context, which might have different biological roles, and therefore the interactors that are identified by AP-MS might represent a mix of distinct protein assemblies or functional entities. It is not possible to derive such topological information a priori from the mono-dimensional lists of proteins generated by simple AP-MS experiments. However, the technique can be exploited further to define the architecture of protein complexes by combining it with one or more methods to resolve these assemblies.
In order to resolve the topology of protein interactions identified through AP-MS, several strategies have been applied. One approach is to perform iterative AP-MS experiments using the preys identified in a previous round of experiments as baits 1. Although very informative, this is quite a labor intensive task both experimentally and analytically. Protein cross-linking in combination with mass spectrometry is increasingly being used to derive topological information on protein complexes 2,3,4,5. However, computational analysis of cross-linked peptides still remains a challenging task and hence is the bottleneck in the workflow. The advent of MS-cleavable cross-linking reagents should facilitate mapping of the amino acid residues that are in close proximity in interacting proteins 6,7. Another alternative is to combine affinity purification with prior orthogonal separation techniques 8,9. Chromatographic fractionation by gel filtration or ion exchange, or sucrose gradient fractionation have also recently been used in combination with quantitative mass spectrometry to describe multiprotein complexes at a system-wide level, by-passing the complex isolation step 10,11,12,13. Blue native polyacrylamide gel electrophoresis (BN-PAGE) has been widely applied to investigate native protein interactions, typically those involving mitochondrial membrane protein complexes 14. This separation technique was also recently used in combination with label-free protein quantification and correlation profiling, not only on mitochondrial complexes 15,16,17, but also for unravelling other protein complexes from whole cells 18,19. We hypothesized that the combination of affinity purification with subsequent native fractionation approaches and quantitative MS should provide a useful strategy for resolving multiple protein assemblies containing a particular protein.
Here we describe a method that combines generic epitope-based affinity purification with blue native polyacrylamide gel electrophoresis of the isolated complexes, followed by quantitative mass spectrometry and protein correlation profiling, to resolve the multiple assemblies a protein might be involved in. We employ mouse embryonic stem cells where a protein of interest fused to an epitope tag is expressed from the endogenous locus to achieve close to physiological abundance and ensure efficient native complex isolation. This approach unravels the multiple interactions a protein engages in, resolving them into distinct assemblies based on their correlation profiles, whilst requiring no more work than conventional geLC-MS 20.
1. Isolation of Native Protein Complexes by FLAG Affinity Purification
2. Blue Native PAGE
3. Mass Spectrometry Analysis
Note: All subsequent steps should be performed in a laminar flow hood if possible to ensure cleanliness of the samples. All solutions should be prepared with HPLC-grade water. Discuss this protocol with the Mass Spectrometry laboratory that will carry out the analysis.
4. Data Analysis
Figure 1. Screenshot of Perseus data upload window. The figure shows the steps for loading protein identification and quantification data into Perseus. Please click here to view a larger version of this figure.
Figure 2. Screenshot of Perseus window for filtering of entries corresponding to contaminants, reverse hits and proteins identified by site. Selecting Filter rows by categorical column opens a new window for selecting the types of protein entries to be eliminated from the dataset. Please click here to view a larger version of this figure.
Figure 3. Screenshot of Perseus normalization window. Selecting Divide in the Normalization menu opens a new window, with different options. Selecting Sum divides the intensity value of a protein in each fraction by the total intensity of that protein across all fractions. Please click here to view a larger version of this figure.
Figure 4. Screenshot of Perseus showing migration profile plots. Proteins can be selected in the matrix below the profiles to highlight their corresponding profile. The tool bar can be used to edit and export the profiles. Please click here to view a larger version of this figure.
Figure 5. Screenshot of Perseus hierarchical clustering window. The figure shows the settings for hierarchical clustering of proteins using Manhattan (L1) distance metric. Please click here to view a larger version of this figure.
Figure 6. Screenshot of Perseus showing dendrogram and protein intensities heatmap. The workflow on the right hand side of the main panel shows each step undertaken and the resulting matrix, and can be used to undo any step. The workflow can also branch from any intermediate matrix. Please click here to view a larger version of this figure.
The workflow of the Affinity purification Blue native protein Correlation profiling by Mass Spectrometry (ABC-MS) strategy is depicted in Figure 7. Native protein complexes around a protein of interest are isolated by affinity purification using antibodies against an epitope tag (in this case FLAG) and competitive elution. The complexes are resolved by BN-PAGE, and the whole gel lane is excised into 48 sections, and prepared for shotgun LC-MS/MS. Quantitative MS information is used to generate a migration profile for each identified protein across the blue native separation. Proteins that interact to form a distinct complex display similar migration profiles with superimposable peaks. When a protein of interest takes part in more than one assembly, multiple peaks are observed in its migration profile, given the sub-complexes are within the resolving power of the blue native gel. A systematic comparison of the migration profiles can be achieved by protein correlation profiling using hierarchical clustering. The dendrogram and the peak intensities for all fractions are visualized in a heat-map, facilitating the identification of interacting proteins that belong to distinct protein complexes (Figure 8).
We used this strategy to analyze the interacting partners of Mta2, a core subunit of the NuRD chromatin remodeling complex 20. As shown in Figure 9, the migration profile of Mta2 displayed two peaks of distinct intensities between 700 kDa and 1.2 MDa, with the lower mass peak displaying higher abundance. Other NuRD core subunits, including Mta1/3, Hdac1/2 and Mbd3, showed identical separation pattern, albeit the peaks for some of the subunits, namely Chd4, Gatad2a/b and Rbbp4/7, had the inverse abundance distribution (Figure 9A, B). In contrast, the profile of Cdk2ap1, a regulatory factor that recruits the NuRD complex to Wnt gene promoters 23, only displayed the higher mass peak (Figure 9C), and so did Sall4, a transcriptional repressor that has also been shown to bind NuRD 20,24,25. Thus, fractionation of affinity purified Mta2-associated proteins by blue native PAGE was able to resolve two different forms of the NuRD complex.
ABC-MS also allows the identification of novel interactors whilst assigning them to particular protein entities. Through examination of the proteins clusters and fraction intensities represented in a heat-map we detected a strong correlation between NuRD subunits and Wdr5, a regulatory subunit of the MLL methyltransferase complex 26, with Wdr5 displaying two migration peaks coincident with the two NuRD peaks (Figure 8), suggesting a novel interaction between Wdr5 and NuRD. We confirmed this interaction by co-immunoprecipitation and co-migration in size exclusion chromatography 20.
The choice of distance metric calculation in the hierarchical clustering will influence the shape of the clusters and hence the correlations. We recommend experimenting with the different metrics to achieve the best fit with existing interaction knowledge of the protein or complex of interest. Generally we achieved best results with the Manhattan (L1) distance metric 20. Pearson correlation or Euclidean distance metrics have also been reported for identifying complexes based on alternative fractionation techniques 10,11,12.
The quantitative MS data obtained from the blue native fractions can also be used to determine the stoichiometry of protein complexes. The iBAQ (intensity based absolute quantification) value provides a measure of relative abundance of the identified proteins 27,28. The iBAQ values for the protein complex members in all the fractions within a migration profile peak are normalized to that of the bait protein to obtain relative amounts. The normalized iBAQs across a profile peak for a given protein complex member should follow a horizontal trend, and the trend values reflect the stoichiometry of the interacting proteins relative to the bait protein. For a more detailed representation of stoichiometry calculations, see 20.
Figure 7: Schematic workflow summarizing the ABC-MS strategy. This figure is modified from 20. Please click here to view a larger version of this figure.
Figure 8. Hierarchical clustering of BN-PAGE migration profiles of Mta2 interactors. Mta2-associated proteins were clustered based on the similarity of their migration profiles. Only a subset of the heat-map containing the NuRD complex is shown (enclosed in the blue box). The yellow box highlights the strong correlation of Wdr5 with the NuRD complex. The annotated molecular weights were estimated from the migration distances of protein standards run in the same gel. This research was originally published in Molecular and Cellular Proteomics 20 the American Society for Biochemistry and Molecular Biology. Please click here to view a larger version of this figure.
Figure 9. BN-PAGE migration profile of NuRD subunits and associated proteins. A) Mta2 and NuRD subunits present at a similar intensity pattern. B) Mta2 and NuRD subunits with the inverse intensity pattern. C) Mta2 and Cdk2ap1, which is present only in the higher molecular weight NuRD entity. The annotated molecular weights were estimated from the migration profile of the protein standards. This research was originally published in Molecular and Cellular Proteomics 20 the American Society for Biochemistry and Molecular Biology. Please click here to view a larger version of this figure.
Supplemental data: Sample dataset. MaxQuant-derived proteingroups.txt file containing protein identifications and quantification values from an ABC-MS experiment. This research was originally published in Molecular and Cellular Proteomics 20 the American Society for Biochemistry and Molecular Biology. Please click here to download this file.
Here, we describe the use of affinity purification followed by blue native gel electrophoresis in combination with quantitative mass spectrometry to resolve protein complexes. This approach offers a method to unravel one-dimensional protein interaction lists into functional protein assemblies.
We demonstrate the method based on the use of epitope-tagged proteins. However, if a cell line expressing a tagged protein is not available, an alternative might be to use antibodies against the protein of interest, provided there is a peptide available to achieve native competitive elution. The amount of starting material and quantity of beads might need to be modified depending on the expression level of the target protein. We typically perform this protocol with 2-5 x 108 cells starting material, and this is sufficient even for proteins with low expression level. The lysis buffer composition should be chosen empirically to achieve near to complete solubilization of the bait. This might be challenging for some types of proteins, in particular chromatin binding or membrane proteins. Alternative options include increasing the amount of salt, provided that the protein complex under study is stable in high salt, or using sonication and/or nuclease treatment for chromatin binding proteins 20,29. In the case of membrane proteins, switching detergent to DDM or digitonin may be advisable 30. In the case of DNA binding proteins, it is useful to include a nuclease such as benzonase during the purification step 20. Complete removal of nucleic acids ensures that the interactions detected occur between proteins and are not mediated by DNA.
A critical element to consider when using this approach is the stability of the complex under investigation. The procedure is long and may involve preserving the protein complex overnight. We have achieved good success with two chromatin remodeling complexes (D. Bode and M. Pardo, data not shown), but this should be evaluated. The affinity purification step may be shortened if required.
Alternative techniques that allow native fractionation, such as size exclusion chromatography, have been widely used for over 50 years to characterize protein complexes. We and others have shown that the resolution of blue native PAGE is superior to that achieved using size exclusion chromatography 20,31,32,33. Another advantage of blue native PAGE is that it does not require chromatography systems, which are expensive, but rather uses protein electrophoretic equipment that is widespread in laboratories. In terms of hands-on time, this method does not involve more work than the traditional geLC-MS/MS approach or offline chromatographic fractionation. However, as most fractionation techniques do, it has a limit to their resolution. Complexes that are very homogeneous or close in mass and shape may be beyond the resolution offered by blue native PAGE, and hence the protocol as reported here might not be universally successful in resolving distinct complexes with shared subunits. Encouragingly, we have been successful in separating two very similar tetrameric complexes sharing three subunits (M. Pardo, manuscript in preparation).
Since mass spectrometry has become increasingly sensitive, even minute amounts of non-specific interactors and contaminants can be detected in AP-MS samples. The approach presented here might aid in the discrimination of real interactors from background contamination in the affinity purification by focusing the attention on proteins with migration peaks that coincide with bait migration peaks at higher molecular weight than that of the monomeric proteins.
Several groups have used fractionation techniques followed by protein correlation profiling to delineate protein complexes at cellular scale without the need for previous isolation 10,11,12,34. However, this can result in failure to detect sub-stoichiometric interactions. The incorporation of an enrichment step through affinity purification can help to overcome this. The approach described here should be generally useful for exploring the topology of protein complexes and unraveling the multiple complexes a given protein takes part in within the same cellular context. The strategy is simple and amenable to laboratories that may not have expensive chromatographic fractionation equipment to resolve protein complexes.
The authors have nothing to disclose.
This work was funded by the Wellcome Trust (WT098051).
Protein G Dynabeads | Life Technologies | 10003D | |
FLAG antibody M2 | Sigma-Aldrich | F1804 | |
Tween-20, protein grade, 10% solution | Millipore | 655206 | |
Dimethyl pimelimidate | Sigma-Aldrich | 80490 | |
0.2 M Triethanolamine buffer, pH 8.2 | Sigma-Aldrich | T0449 | |
3x FLAG peptide | Sigma-Aldrich | F4799 | |
Vivaspin 5K NMWCO, PES | Sartorius | VS0112 | |
NativePAGE 3-12% Bis-Tris gel | Life Technologies | BN1001 | |
20x NativePAGE Running Buffer | Life Technologies | BN2001 | |
20x NativePAGE Cathode Additive | Life Technologies | BN2002 | |
4x NativePAGE sample loading buffer | Life Technologies | BN2003 | |
NativeMARK | Life Technologies | LC0725 | |
NativePAGE 5% G-250 sample additive | Life Technologies | BN2004 | |
Nunc conical bottom 96-well plate, polypropylene | Thermo | 249944 | |
Multiscreen HTS 96-well filtration system | Thermo | MSDVN6550 | |
Nunc 96-well cap natural | Thermo | 276002 | |
TCEP (Tris(2-carboxyethyl)phosphine hydrochloride) | Sigma-Aldrich | 646547 | |
Iodoacetamide | Sigma-Aldrich | I1149 | |
Acetonitrile, HPLC grade | Fisher Scientific | A/0627/17 | |
Trypsin, sequencing grade | Roche | 11418475001 | |
Software | |||
MaxQuant (software) | N.A. | N.A. | http://www.biochem.mpg.de/5111795/maxquant |
Perseus (software) | N.A. | N.A. | http://www.biochem.mpg.de/5111810/perseus |