Streamlined structure determination by cryo-electron tomography and subtomogram averaging using TomoBEAR

Nikita Balyschew, Artsemi Yushkevich, Vasilii Mikirtumov, Ricardo M. Sanchez, Thiemo Sprink and Mikhail Kudryashev ()
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Nikita Balyschew: Max Planck Institute of Biophysics
Artsemi Yushkevich: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Vasilii Mikirtumov: Max Planck Institute of Biophysics
Ricardo M. Sanchez: Max Planck Institute of Biophysics
Thiemo Sprink: Charité-Universitätsmedizin Berlin
Mikhail Kudryashev: Max Planck Institute of Biophysics

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract Structures of macromolecules in their native state provide unique unambiguous insights into their functions. Cryo-electron tomography combined with subtomogram averaging demonstrated the power to solve such structures in situ at resolutions in the range of 3 Angstrom for some macromolecules. In order to be applicable to the structural determination of the majority of macromolecules observable in cells in limited amounts, processing of tomographic data has to be performed in a high-throughput manner. Here we present TomoBEAR—a modular configurable workflow engine for streamlined processing of cryo-electron tomographic data for subtomogram averaging. TomoBEAR combines commonly used cryo-EM packages with reasonable presets to provide a transparent (“white box”) approach for data management and processing. We demonstrate applications of TomoBEAR to two data sets of purified macromolecular targets, to an ion channel RyR1 in a membrane, and the tomograms of plasma FIB-milled lamellae and demonstrate the ability to produce high-resolution structures. TomoBEAR speeds up data processing, minimizes human interventions, and will help accelerate the adoption of in situ structural biology by cryo-ET. The source code and the documentation are freely available.

Date: 2023
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DOI: 10.1038/s41467-023-42085-w

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