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Sparseness and Smoothness Regularized Imaging for improving the resolution of Cryo-EM single-particle reconstruction.


ABSTRACT: In this paper, we present a refinement method for cryo-electron microscopy (cryo-EM) single-particle reconstruction, termed as OPUS-SSRI (Sparseness and Smoothness Regularized Imaging). In OPUS-SSRI, spatially varying sparseness and smoothness priors are incorporated to improve the regularity of electron density map, and a type of real space penalty function is designed. Moreover, we define the back-projection step as a local kernel regression and propose a first-order method to solve the resulting optimization problem. On the seven cryo-EM datasets that we tested, the average improvement in resolution by OPUS-SSRI over that from RELION 3.0, the commonly used image-processing software for single-particle cryo-EM, was 0.64 Å, with the largest improvement being 1.25 Å. We expect OPUS-SSRI to be an invaluable tool to the broad field of cryo-EM single-particle analysis. The implementation of OPUS-SSRI can be found at https://github.com/alncat/cryoem.

SUBMITTER: Luo Z 

PROVIDER: S-EPMC7812788 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Sparseness and Smoothness Regularized Imaging for improving the resolution of Cryo-EM single-particle reconstruction.

Luo Zhenwei Z   Campos-Acevedo Adam A AA   Lv Longfei L   Wang Qinghua Q   Ma Jianpeng J  

Proceedings of the National Academy of Sciences of the United States of America 20210101 2


In this paper, we present a refinement method for cryo-electron microscopy (cryo-EM) single-particle reconstruction, termed as OPUS-SSRI (Sparseness and Smoothness Regularized Imaging). In OPUS-SSRI, spatially varying sparseness and smoothness priors are incorporated to improve the regularity of electron density map, and a type of real space penalty function is designed. Moreover, we define the back-projection step as a local kernel regression and propose a first-order method to solve the result  ...[more]

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