High-confidence 3D template matching for cryo-electron tomography

Abstract

Cryo-electron tomography (CryoET) resolves individual macromolecules inside living cells. However, the complex composition and high density of cells challenge the faithful identification of features in tomograms. Here, we capitalize on recent advances in electron tomography and demonstrate that 3D template matching (TM) localizes a wide range of structures inside crowded eukaryotic cells with confidence 10 to 100-fold above the noise level. We establish a TM pipeline with systematically tuned parameters for automated, objective and comprehensive feature identification. High-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, lipid membranes and microtubules, and individual subunits, demonstrate that TM is generic. We resolve [~]100-kDa proteins, connect the functional states of complexes to their cellular localization, and capture vaults carrying ribosomal cargo in situ. By capturing individual molecular events inside living cells with defined statistical confidence, high-confidence TM greatly speeds up the CryoET workflow and sets the stage for visual proteomics.