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Title | Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens. |
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Journal, issue, pages | Structure, Vol. 30, Issue 3, Page 408-417.e4, Year 2022 |
Publish date | Mar 3, 2022 |
Authors | Jan Böhning / Tanmay A M Bharat / Sean M Collins / |
PubMed 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, ...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-TV) to tomographic reconstruction. We show that CS-TV 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-TV allows improvement of the resolution of STA maps. We further demonstrate that the CS-TV 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. |
External links | Structure / PubMed:35051366 / PubMed Central |
Methods | EM (tomography) |
Structure data | EMDB-13881: |
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