Global profiling of plant nuclear membrane proteome in Arabidopsis

A smaller promiscuous biotin ligase for proximity biotinylation called BioID2 enables more-selective targeting of fusion proteins, requires less biotin supplementation, exhibits enhanced labeling of proximate proteins, and demonstrates the use of a flexible linker to modulate the biotin-labeling radius.

Mapping protein-protein interactions for chromatin-associated proteins remains challenging. Here we explore the use of BioID, a proximity biotinylation approach in which a mutated biotin ligase (BirA*) is fused to a bait of interest, allowing for the local activation of biotin and subsequent biotinylation of proteins in the bait vicinity. BioID allowed for successful interactome mapping of core histones and members of the mediator complex. We explored the background signal produced by the BioID approach and found that using distinct types of controls increased the stringency of our statistical analysis with SAINTexpress. A direct comparison of BioID with our AP-MS protocol optimized for chromatin-associated protein complexes revealed that the approaches identified few shared interaction partners and enriched for distinct biological processes; yet, both approaches permitted the recovery of biologically meaningful interactions. While no clear bias could be observed for either technique toward protein complexes of particular functions, BioID allowed for the purification of proteins of lower cellular abundance. Finally, we were able to identify a strong association of MED4 with the centrosome by BioID and validated this finding by immunofluorescence. In summary, BioID complements AP-MS for the study of chromatin-associated protein complexes.

Protein-protein interactions govern almost all cellular functions. These complex networks of stable and transient associations can be mapped by affinity purification mass spectrometry (AP-MS) and complementary proximity-based labeling methods such as BioID. To exploit the advantages of both strategies, we here design and optimize an integrated approach combining AP-MS and BioID in a single construct, which we term MAC-tag. We systematically apply the MAC-tag approach to 18 subcellular and 3 sub-organelle localization markers, generating a molecular context database, which can be used to define a protein’s molecular location. In addition, we show that combining the AP-MS and BioID results makes it possible to obtain interaction distances within a protein complex. Taken together, our integrated strategy enables the comprehensive mapping of the physical and functional interactions of proteins, defining their molecular context and improving our understanding of the cellular interactome.