National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101 Beijing, China.
University of Chinese Academy of Sciences, 100049 Beijing, China.
Sci Adv. 2024 Jul 26;10(30):eadn0092. doi: 10.1126/sciadv.adn0092.
Reconstruction maps of cryo-electron microscopy (cryo-EM) exhibit distortion when the cryo-EM dataset is incomplete, usually caused by unevenly distributed orientations. Prior efforts had been attempted to address this preferred orientation problem using tilt-collection strategy and modifications to grids or to air-water interfaces. However, these approaches often require time-consuming experiments, and the effect was always protein dependent. Here, we developed a procedure containing removing misaligned particles and an iterative reconstruction method based on signal-to-noise ratio of Fourier component to correct this distortion by recovering missing data using a purely computational algorithm. This procedure called signal-to-noise ratio iterative reconstruction method (SIRM) was applied on incomplete datasets of various proteins to fix distortion in cryo-EM maps and to a more isotropic resolution. In addition, SIRM provides a better reference map for further reconstruction refinements, resulting in an improved alignment, which ultimately improves map quality and benefits model building.
冷冻电子显微镜(cryo-EM)的重构图谱在 cryo-EM 数据集不完整时会出现失真,通常是由不均匀分布的取向引起的。先前已经尝试使用倾斜采集策略以及对网格或气-水界面的修改来解决这个首选方向问题。然而,这些方法通常需要耗时的实验,并且效果总是依赖于蛋白质。在这里,我们开发了一种包含去除未对准粒子和基于傅里叶分量信噪比的迭代重建方法的程序,通过使用纯计算算法来恢复缺失数据来纠正这种失真。这种称为信噪比迭代重建方法(SIRM)的程序被应用于各种蛋白质的不完整数据集,以纠正 cryo-EM 图谱中的失真并获得更各向同性的分辨率。此外,SIRM 为进一步的重建细化提供了更好的参考图谱,从而提高了对齐度,最终提高了图谱质量并有利于模型构建。