Protein-protein interactions (PPIs) underlie most, if not all, cellular functions.  The comprehensive mapping of these complex networks of stable and transient associations thus remains a key goal, both for focused biological studies, and for systems biology-based initiatives (where it can be combined with other ‘omics data to gain a better understanding of functional pathways and networks).

Affinity Purification/Mass Spectrometry (AP/MS)

A popular method of choice for interactome analysis is affinity purification of an endogenous or tagged protein followed by mass spectrometry-based identification of all captured proteins (AP-MS). The major strength of this technique is that it can resolve entire multiprotein complexes in a single experiment, providing a "snapshot" of a protein's interactome at a particular time and, if combined with sub-cellular fractionation, in a particular place.


It is important to note that interactions identified by AP-MS do not imply direct association (the proteins may be in the same multi protein complex, but not bound directly).  Direct/binary interactions can be resolved by demonstrating co-precipitation of 2 purified, recombinant proteins, or by using approaches such as yeast two-hybrid screens or imaging-based assays (e.g. FRET, BiFC).   

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A key caveat of AP-MS experiments is that contaminant proteins (e.g. keratins, serum proteins) and proteins that bind nonspecifically to the affinity matrix can account for up to 95% of identified proteins.  The cost and time required to validate putative interaction partners to confirm their physiological relevance highlights the importance of focusing resources on those subsets of potential interactions with a high probability of biological significance. Higher stringency purification methods, such as increasing the salt/detergent concentrations in buffers or multistep purification/elution protocols, can help to overcome the problem of nonspecific binding but can also lead to a loss of low affinity and low abundance specific partner proteins.

Our lab uses a quantitative MS approach based on differential isotopic labeling of proteins or peptides (SILAC; Stable Isotope Labeling by Amino Acids) to distinguish which of the many proteins identified in an AP-MS experiment represent specific binding.  Cells are grown in media containing either standard (Light) versions of the essential amino acids Arginine and Lysine or stable isotope (Heavy) versions that shift the mass/charge ratios of any peptides that contain them. For each identified peptide, a Heavy:Light ratio can be calculated, which represents the relative amount of that particular protein that was enriched in the experimental (Heavy) vs. Control (Light) condition.

This direct inclusion of a negative control provides a background of contaminant proteins that bind nonspecifically to the affinity matrix and/or the fusion tag, against which proteins that bind specifically to the protein of interest clearly stand out.  Proteins can thus be purified under lower stringency conditions, which preserves more specific interactions.

Although AP-MS remains the most commonly used technique for mapping PPIs, its Achilles heel has always been the necessity to break cells open to extract complexes for analysis, which can be disruptive to the underlying PPIs and hinder identification of weak and/or transient associations. The development of complementary proximity labeling approaches that use spatially restricted enzymes to biotinylate neighboring proteins has helped to address this key issue.  

Spatially restricted enzymatic labeling techniques

Two particular proximity labeling techniques, BioID and APEX, have been developed and further optimized for the analysis of multiprotein complexes and for identification of the protein components of specific cellular compartments.

In these approaches, complex members are labeled covalently in vivo, thus eliminating the need for low-stringency purification strategies to preserve their integrity. Furthermore, the high affinity of streptavidin for biotin facilitates efficient recovery of biotinylated proteins from lysates for MS analysis.  These techniques can also be combined with quantitative approaches like SILAC to rapidly and reliably identify high confidence hits.  


As with AP-MS, identification of a protein-protein association using BioID does not imply a direct physical interaction.  


BioID involves expression of a protein of interest fused to a prokaryotic biotin ligase and the subsequent biotinylation of Lysine residues on neighboring proteins (estimated labeling radius ~10 nm) when excess biotin is added to the cells.

As demonstrated in more than 100 publications to date, BioID can be applied to a wide range of cellular proteins, from transcription factors and signaling molecules to ubiquitin ligases and cytoskeletal components.  

Caveats of the original E. coli BirA ligase include the relatively large size of the tag, a DNA binding domain at the N-terminus and the time required for efficient labeling (8-24 hrs).  It has since been mutagenized further to address these concerns, in parallel with the development of biotin ligases from other sources.


Biotinylated proteins can be visualized in fixed cells by staining with fluorophore-tagged streptavidin (note the distinct localized biotinylation patterns for cytoplasmic and nuclear targeted fusion proteins) and in cell lysates by probing Western blots with HRP-tagged streptavidin (* denotes BirA-tagged protein, which biotinylates itself; arrow points to a common contaminant that binds biotin directly.

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Prokaryotic biotin ligases that have been mutagenized for use in BioID experiments. An initial mutations is made to reduce affinity for the active biotinoyl-5'-AMP (so that it diffuses from catalytic site).  Additional mutations have been made to the original E. Coli-derived BirA* to increase labeling time (from 8-24 hrs to <10 min for TurboID) and to remove the DNA binding domain that might cause off-target biotinylation (particularly when mapping interactomes for nuclear proteins).  Smaller and more efficient ligases have also been isolated from other prokaryotes and mutagenized..


APEX is a monomeric peroxidase reporter derived from pea or soybean ascorbate peroxidase that catalyzes the oxidation of biotin-phenol to biotin-phenoxyl in the presence of H2O2, resulting in the biotinylation of proteins in the neighboring region. Biotin-phenoxyl radicals can covalently react with electron-rich amino acids such as Tyr, Trp, His, and Cys. They are short-lived (<5 ms) and estimated to have a labeling radius <20 nm.  

A key advantage of APEX over classic BioID is the significantly faster rate of labeling (load cells with biotin-phenol for 30 min then add H2O2 for 1 min).  

APEX can also catalyze the polymerization and local deposition of diaminobenzidine (DAB), which in turn recruits electron-dense osmium to provide contrast for electron microscopy-based imaging.

When paired with quantitative proteomic approaches, the higher temporal resolution of APEX labeling can facilitate identification of dynamic changes in protein-protein associations over time or in response to cellular perturbation.  

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For more information about about these topics, see:

Trinkle-Mulcahy L.  Recent advances in proximity-based labeling methods for interactome mapping. F1000 Research 2019 Jan 31.

Mehta V and Trinkle-Mulcahy L. Recent advances in large-scale protein interactome mapping. F1000Res 5:782, 2016.

Fox, A, Mehta, V, Boulon, S, Trinkle-Mulcahy, L. Extracting, enriching, and identifying nuclear body sub-complexes using label-based quantitative mass spectrometry. Methods Mol Biol.1262:215-38, 2015.

Mehta, V., Trinkle-Mulcahy, L. Novel methods for studying multiprotein complexes in vivo. F1000 Prime Rep. 5:30, 2013.

Prévost, M., Chamousset, D., Nasa, I., Freele, E., Morrice, N., Moorhead, G., Trinkle-Mulcahy, L. Quantitative fragmentome mapping reveals novel, domain-specific partners for the modular protein RepoMan. Mol Cell Proteomics 12:1468-86, 2013.

Trinkle-Mulcahy L .Resolving protein interactions and complexes by affinity purification followed by label-based quantitative mass spectrometry. Proteomics.12:1623-38, 2012.

Trinkle-Mulcahy L., Boulon S., Lam Y.W., Urcia R., Boisvert F.M., Vandermoere F., Morrice N.A., Swift S., Rothbauer U., Leonhardt H. and Lamond A.I. Identifying specific protein interaction partners using quantitative mass spectrometry and bead proteomes. J Cell Biol. 183:223-39, 2008.