1. High-confidence 3D template matching for cryo-electron tomography.
- Author
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Cruz-León S, Majtner T, Hoffmann PC, Kreysing JP, Kehl S, Tuijtel MW, Schaefer SL, Geißler K, Beck M, Turoňová B, and Hummer G
- Subjects
- Humans, Nuclear Pore ultrastructure, Nuclear Pore metabolism, Microtubules ultrastructure, Microtubules metabolism, Fatty Acid Synthases metabolism, Machine Learning, Imaging, Three-Dimensional methods, Algorithms, Image Processing, Computer-Assisted methods, Electron Microscope Tomography methods, Cryoelectron Microscopy methods, Ribosomes ultrastructure, Ribosomes metabolism, Proteasome Endopeptidase Complex ultrastructure, Proteasome Endopeptidase Complex metabolism, Proteasome Endopeptidase Complex chemistry, Proteomics methods, Software
- Abstract
Visual proteomics attempts to build atlases of the molecular content of cells but the automated annotation of cryo electron tomograms remains challenging. Template matching (TM) and methods based on machine learning detect structural signatures of macromolecules. However, their applicability remains limited in terms of both the abundance and size of the molecular targets. Here we show that the performance of TM is greatly improved by using template-specific search parameter optimization and by including higher-resolution information. We establish a TM pipeline with systematically tuned parameters for the automated, objective and comprehensive identification of structures with confidence 10 to 100-fold above the noise level. We demonstrate high-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, fatty acid synthases, lipid membranes and microtubules, and individual subunits inside crowded eukaryotic cells. We provide software tools for the generic implementation of our method that is broadly applicable towards realizing visual proteomics., (© 2024. The Author(s).)
- Published
- 2024
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