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

作者：Zhenwei Luo, A.A. Campos-Acevedo, Longfei Lv, Qinghua Wang, Jianpeng Ma · 发表于：Proceedings of the National Academy of Sciences · 年份：2021 · DOI：10.1073/pnas.2013756118 · 被引用次数：10 · 研究领域：Advanced Electron Microscopy Techniques and Applications、Electron and X-Ray Spectroscopy Techniques、Geophysical and Geoelectrical Methods

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.