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亚颗粒平均工作流程中选择膜相关颗粒的策略。

Strategies for picking membrane-associated particles within subtomogram averaging workflows.

机构信息

Institute of Structural and Molecular Biology, Birkbeck College, Malet St., London, WC1E 7HX, UK.

Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA.

出版信息

Faraday Discuss. 2022 Nov 8;240(0):101-113. doi: 10.1039/d2fd00022a.

Abstract

Cryo-electron tomography (cryo-ET) with subtomogram averaging (STA) has emerged as a key tool for determining macromolecular structure(s) and . However, processing cryo-ET data with STA currently requires significant user expertise. Recent efforts have streamlined several steps in STA workflows; however, particle picking remains a time-consuming bottleneck for many projects and requires considerable user input. Here, we present several strategies for the time-efficient and accurate picking of membrane-associated particles using the COPII inner coat as a case study. We also discuss a range of particle cleaning solutions to remove both poor quality and false-positive particles from STA datasets. We provide a step-by-step guide and the necessary scripts for users to independently carry out the particle picking and cleaning strategies discussed.

摘要

冷冻电子断层扫描(cryo-ET)与子断层平均(STA)已成为确定大分子结构的关键工具。然而,目前使用 STA 处理 cryo-ET 数据需要大量的用户专业知识。最近的努力简化了 STA 工作流程中的几个步骤;然而,对于许多项目来说,粒子挑选仍然是一个耗时的瓶颈,需要相当多的用户输入。在这里,我们提出了几种使用 COPII 内壳作为案例研究的高效、准确的膜相关粒子挑选策略。我们还讨论了一系列粒子清洗解决方案,以从 STA 数据集中去除质量差和假阳性的粒子。我们提供了一个逐步的指南和必要的脚本,供用户独立进行讨论的粒子挑选和清洗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/12e8/9642003/82d4972ca682/d2fd00022a-f1.jpg

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