Department of Bioengineering, Rice University, Houston, TX 77030.
Verna and Marrs Mclean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030.
Proc Natl Acad Sci U S A. 2021 Jan 12;118(2). doi: 10.1073/pnas.2013756118.
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.
在本文中，我们提出了一种改进的冷冻电子显微镜（cryo-EM）单颗粒重建方法，称为 OPUS-SSRI（稀疏性和光滑性正则化成像）。在 OPUS-SSRI 中，我们将空间变化的稀疏性和光滑性先验信息纳入其中，以提高电子密度图的规则性，并设计了一种实空间惩罚函数。此外，我们将反向投影步骤定义为局部核回归，并提出了一种求解由此产生的优化问题的一阶方法。在我们测试的七个 cryo-EM 数据集上，OPUS-SSRI 相对于常用的单颗粒 cryo-EM 图像处理软件 RELION 3.0 提高分辨率的平均幅度为 0.64 Å，最大提高幅度为 1.25 Å。我们期望 OPUS-SSRI 能够成为 cryo-EM 单颗粒分析领域中非常有价值的工具。OPUS-SSRI 的实现可以在 https://github.com/alncat/cryoem 找到。
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