Proximity labeling of protein complexes and cell-type-specific organellar proteomes in Arabidopsis enabled by TurboID.

Andrea Mair,Tess C Branon,Alice Y Ting,Dominique C Bergmann,Shou-Ling Xu

doi:10.7554/elife.47864

Abstract

Defining specific protein interactions and spatially or temporally restricted local proteomes improves our understanding of all cellular processes, but obtaining such data is challenging, especially for rare proteins, cell types, or events. Proximity labeling enables discovery of protein neighborhoods defining functional complexes and/or organellar protein compositions. Recent technological improvements, namely two highly active biotin ligase variants (TurboID and miniTurbo), allowed us to address two challenging questions in plants: (1) what are in vivo partners of a low abundant key developmental transcription factor and (2) what is the nuclear proteome of a rare cell type? Proteins identified with FAMA-TurboID include known interactors of this stomatal transcription factor and novel proteins that could facilitate its activator and repressor functions. Directing TurboID to stomatal nuclei enabled purification of cell type- and subcellular compartment-specific proteins. Broad tests of TurboID and miniTurbo in Arabidopsis and Nicotiana benthamiana and versatile vectors enable customization by plant researchers.

Highlights

All major processes of life, including growth and development and interactions among cells, organisms and the environment, rely on the activity and co-operation of hundreds of proteins
As was observed in other organisms, both TbID and mTb showed greatly increased activity compared to BirA*, which mainly achieved weak self-labeling within 1 h of biotin treatment (Figure 1B–C, Figure 1—figure supplements 3 and 4)
Our experiments presented in this study demonstrate that the new biotin ligase versions TbID and mTb drastically improve the sensitivity of proximity labeling (PL) in plants, compared to previously used BirA*, and tolerate a range of experimental conditions

Summary

Introduction

All major processes of life, including growth and development and interactions among cells, organisms and the environment, rely on the activity and co-operation of hundreds of proteins To fully understand these processes on a cellular level, we must know all players present in a cell or cell type at a specific location and time. This requires information about transcription and chromatin state, as well as about protein abundance and protein complex compositions. A large international effort, the ‘human cell atlas’ project, is taking a first step in this direction It aims to characterize all cell types in the human body, using recent advancements in high-throughput single cell and multiplex techniques (Regev et al, 2017; Stuart and Satija, 2019). While several groups have produced single-cell gene expression profiles (e.g. Efroni et al, 2015; Ryu et al, 2019; Denyer et al, 2019; Nelms and Walbot, 2019) and tissue/cell-type-specific profiles of active translation (e.g. Vragovicet al., 2015; Tian et al, 2019), we lack effective tools to obtain precise information about protein distribution, abundance and the composition of protein complexes

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