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Identification of Ku70 Domain-Specific Interactors Using BioID2

Overview
Journal Cells
Publisher MDPI
Date 2021 Apr 3
PMID 33799447
Citations 2
Authors
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Abstract

Since its inception, proximity-dependent biotin identification (BioID), an in vivo biochemical screening method to identify proximal protein interactors, has seen extensive developments. Improvements and variants of the original BioID technique are being reported regularly, each expanding upon the existing potential of the original technique. While this is advancing our capabilities to study protein interactions under different contexts, we have yet to explore the full potential of the existing BioID variants already at our disposal. Here, we used BioID2 in an innovative manner to identify and map domain-specific protein interactions for the human Ku70 protein. Four HEK293 cell lines were created, each stably expressing various BioID2-tagged Ku70 segments designed to collectively identify factors that interact with different regions of Ku70. Historically, although many interactions have been mapped to the C-terminus of the Ku70 protein, few have been mapped to the N-terminal von Willebrand A-like domain, a canonical protein-binding domain ideally situated as a site for protein interaction. Using this segmented approach, we were able to identify domain-specific interactors as well as evaluate advantages and drawbacks of the BioID2 technique. Our study identifies several potential new Ku70 interactors and validates RNF113A and Spindly as proteins that contact or co-localize with Ku in a Ku70 vWA domain-specific manner.

Citing Articles

Analysis of Ku70 S155 Phospho-Specific BioID2 Interactome Identifies Ku Association with TRIP12 in Response to DNA Damage.

Abbasi S, Bayat L, Schild-Poulter C Int J Mol Sci. 2023; 24(8).

PMID: 37108203 PMC: 10138931. DOI: 10.3390/ijms24087041.


Proximity Mapping of CCP6 Reveals Its Association with Centrosome Organization and Cilium Assembly.

Rodriguez-Calado S, Van Damme P, Aviles F, Candiota A, Tanco S, Lorenzo J Int J Mol Sci. 2023; 24(2).

PMID: 36674791 PMC: 9867282. DOI: 10.3390/ijms24021273.

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