Published in

Oxford University Press, The Plant Cell, 11(32), p. 3388-3407, 2020

DOI: 10.1105/tpc.20.00235

Links

Tools

Export citation

Search in Google Scholar

Establishment of Proximity-dependent Biotinylation Approaches in Different Plant Model Systems

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Abstract Proximity labeling is a powerful approach for detecting protein-protein interactions. Most proximity labeling techniques use a promiscuous biotin ligase or a peroxidase fused to a protein of interest, enabling the covalent biotin labeling of proteins and subsequent capture and identification of interacting and neighboring proteins without the need for the protein complex to remain intact. To date, only a few studies have reported on the use of proximity labeling in plants. Here, we present the results of a systematic study applying a variety of biotin-based proximity labeling approaches in several plant systems using various conditions and bait proteins. We show that TurboID is the most promiscuous variant in several plant model systems and establish protocols that combine mass spectrometry-based analysis with harsh extraction and washing conditions. We demonstrate the applicability of TurboID in capturing membrane-associated protein interactomes using Lotus japonicus symbiotically active receptor kinases as a test case. We further benchmark the efficiency of various promiscuous biotin ligases in comparison with one-step affinity purification approaches. We identified both known and novel interactors of the endocytic TPLATE complex. We furthermore present a straightforward strategy to identify both nonbiotinylated and biotinylated peptides in a single experimental setup. Finally, we provide initial evidence that our approach has the potential to suggest structural information of protein complexes.