Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens
File(s)
Published version
Author(s)
Böhning, Jan
Bharat, Tanmay AM
Collins, Sean M
Type
Journal Article
Abstract
Cryoelectron tomography (cryo-ET) and subtomogram averaging (STA) allow direct visualization and structural studies of biological macromolecules in their native cellular environment, in situ. Often, low signal-to-noise ratios in tomograms, low particle abundance within the cell, and low throughput in typical cryo-ET workflows severely limit the obtainable structural information. To help mitigate these limitations, here we apply a compressed sensing approach using 3D second-order total variation (CS-TV2) to tomographic reconstruction. We show that CS-TV2 increases the signal-to-noise ratio in tomograms, enhancing direct visualization of macromolecules, while preserving high-resolution information up to the secondary structure level. We show that, particularly with small datasets, CS-TV2 allows improvement of the resolution of STA maps. We further demonstrate that the CS-TV2 algorithm is applicable to cellular specimens, leading to increased visibility of molecular detail within tomograms. This work highlights the potential of compressed sensing-based reconstruction algorithms for cryo-ET and in situ structural biology.
Date Issued
2022-03-03
Date Acceptance
2021-12-22
Citation
Structure, 2022, 30 (3), pp.408-417.e4
ISSN
0969-2126
Publisher
Elsevier
Start Page
408
End Page
417.e4
Journal / Book Title
Structure
Volume
30
Issue
3
Copyright Statement
© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/35051366
PII: S0969-2126(21)00462-7
Subjects
Cryoelectron Microscopy
Electron Microscope Tomography
Electrons
Image Processing, Computer-Assisted
Macromolecular Substances
Signal-To-Noise Ratio
compressed sensing
cryo-electron microscopy
cryo-EM
cryo-ET
electron cryomicroscopy
image processing
in situ structural biology
subtomogram averaging
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2022-01-19