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

Author

Listed:
  • Sergio Cruz-León

    (Max Planck Institute of Biophysics)

  • Tomáš Majtner

    (Max Planck Institute of Biophysics)

  • Patrick C. Hoffmann

    (Max Planck Institute of Biophysics)

  • Jan Philipp Kreysing

    (Max Planck Institute of Biophysics
    IMPRS on Cellular Biophysics)

  • Sebastian Kehl

    (Max Planck Computing and Data Facility)

  • Maarten W. Tuijtel

    (Max Planck Institute of Biophysics)

  • Stefan L. Schaefer

    (Max Planck Institute of Biophysics)

  • Katharina Geißler

    (Max Planck Institute of Biophysics
    IMPRS on Cellular Biophysics)

  • Martin Beck

    (Max Planck Institute of Biophysics
    Goethe University Frankfurt)

  • Beata Turoňová

    (Max Planck Institute of Biophysics)

  • Gerhard Hummer

    (Max Planck Institute of Biophysics
    Goethe University Frankfurt)

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.

Suggested Citation

  • Sergio Cruz-León & Tomáš Majtner & Patrick C. Hoffmann & Jan Philipp Kreysing & Sebastian Kehl & Maarten W. Tuijtel & Stefan L. Schaefer & Katharina Geißler & Martin Beck & Beata Turoňová & Gerhard Hu, 2024. "High-confidence 3D template matching for cryo-electron tomography," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47839-8
    DOI: 10.1038/s41467-024-47839-8
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    References listed on IDEAS

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