ArticleNature communications2018
An AP-MS- and BioID-compatible MAC-tag enables comprehensive mapping of protein interactions and subcellular localizations.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 153 papers.
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Who cites it
153 citing papers in PubMed.
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- ProteoGyver: a fast, user-friendly tool for routine QC and analysis of MS-based proteomics data.Bioinformatics (Oxford, England) · 2026Article
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- There and back again: a cell biologist's journey from organelles to molecules.Biological chemistry · 2025Review
- Ribosome-binding protein 1 maintains peroxisome biogenesis.Journal of cell science · 2025Article
- State-of-the-Art and Future Directions in Structural Proteomics.Molecular & cellular proteomics : MCP · 2025Review
- A comprehensive PDCoV-host proteome interaction map reveals potential antiviral targets.PLoS pathogens · 2025Article
- Unlocking biological insights from differentially expressed genes: Concepts, methods, and future perspectives.Journal of advanced research · 2025Review
- The CGG triplet repeat binding protein 1 counteracts R-loop induced transcription-replication stress.EMBO reports · 2025Article
- Oncogenic virus hijacks SOX18 pioneer function to enhance viral persistence.Research square · 2025Article
- Deciphering 17-β-hydroxysteroid dehydrogenase 4: from molecular insights to cancer therapeutics.Cancer cell international · 2025Review
93 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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