ArticleProceedings of the National Academy of Sciences of the United States of America2014
Probing nuclear pore complex architecture with proximity-dependent biotinylation.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 348 papers.
What it found
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Who cites it
348 citing papers in PubMed, 585 citations in OpenAlex.
- Review
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288 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
Proximity-dependent biotin identification (BioID) is a method for identifying protein associations that occur in vivo. By fusing a promiscuous biotin ligase to a protein of interest expressed in living cells, BioID permits the labeling of proximate proteins during a defined labeling period. In this study we used BioID to study the human nuclear pore complex (NPC), one of the largest macromolecular assemblies in eukaryotes. Anchored within the nuclear envelope, NPCs mediate the nucleocytoplasmic trafficking of numerous cellular components. We applied BioID to constituents of the Nup107-160 complex and the Nup93 complex, two conserved NPC subcomplexes. A strikingly different set of NPC constituents was detected depending on the position of these BioID-fusion proteins within the NPC. By applying BioID to several constituents located throughout the extremely stable Nup107-160 subcomplex, we refined our understanding of this highly conserved subcomplex, in part by demonstrating a direct interaction of Nup43 with Nup85. Furthermore, by using the extremely stable Nup107-160 structure as a molecular ruler, we defined the practical labeling radius of BioID. These studies further our understanding of human NPC organization and demonstrate that BioID is a valuable tool for exploring the constituency and organization of large protein assemblies in living cells.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.