Abstract

Cryo-electron tomography (cryo-ET) allows for label-free high-resolution imaging of macromolecular assemblies in their native cellular context. However, the localization of macromolecules of interest in tomographic volumes can be challenging. Here we present a ligand-inducible labeling strategy for intracellular proteins based on fluorescent, 25-nm-sized, genetically encoded multimeric particles (GEMs). The particles exhibit recognizable structural signatures, enabling their automated detection in cryo-ET data by convolutional neural networks. The coupling of GEMs to green fluorescent protein-tagged macromolecules of interest is triggered by addition of a small-molecule ligand, allowing for time-controlled labeling to minimize disturbance to native protein function. We demonstrate the applicability of GEMs for subcellular-level localization of endogenous and overexpressed proteins across different organelles in human cells using cryo-correlative fluorescence and cryo-ET imaging. We describe means for quantifying labeling specificity and efficiency, and for systematic optimization for rare and abundant protein targets, with emphasis on assessing the potential effects of labeling on protein function.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call