A minority of final stacks yields superior amplitude in single-particle cryo-EM

Jianying Zhu, Qi Zhang, Hui Zhang, Zuoqiang Shi (), Mingxu Hu () and Chenglong Bao ()
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Jianying Zhu: Tsinghua University
Qi Zhang: Key Laboratory of Protein Sciences (Tsinghua University), Ministry of Education
Hui Zhang: Tsinghua University
Zuoqiang Shi: Tsinghua University
Mingxu Hu: Key Laboratory of Protein Sciences (Tsinghua University), Ministry of Education
Chenglong Bao: Tsinghua University

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract Cryogenic electron microscopy (cryo-EM) is widely used to determine near-atomic resolution structures of biological macromolecules. Due to the low signal-to-noise ratio, cryo-EM relies on averaging many images. However, a crucial question in the field of cryo-EM remains unanswered: how close can we get to the minimum number of particles required to reach a specific resolution in practice? The absence of an answer to this question has impeded progress in understanding sample behavior and the performance of sample preparation methods. To address this issue, we develop an iterative particle sorting and/or sieving method called CryoSieve. Extensive experiments demonstrate that CryoSieve outperforms other cryo-EM particle sorting algorithms, revealing that most particles are unnecessary in final stacks. The minority of particles remaining in the final stacks yield superior high-resolution amplitude in reconstructed density maps. For some datasets, the size of the finest subset approaches the theoretical limit.

Date: 2023
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DOI: 10.1038/s41467-023-43555-x

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