Automated systematic evaluation of cryo-EM specimens with SmartScope
Automated systematic evaluation of cryo-EM specimens with SmartScope
复制标题
使用 SmartScope 对冷冻电镜样本进行自动系统评估
DOI：
10.1101/2022.05.05.490801
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发表时间：
2022
期刊：
影响因子：
7.7
通讯作者：
M. Borgnia
中科院分区：
文献类型：
--
作者：
J. Bouvette;Qinwen Huang;A. Riccio;W. Copeland;A. Bartesaghi;M. Borgnia
在数据收集和处理硬件改进的推动下，单粒子冷冻电子显微镜在结构生物学中迅速获得了相关性。然而，找到稳定成像大分子靶点的条件仍然是确定其结构的最关键障碍。获得最佳的标本需要在显微镜中的多个网格的评价，因为条件是不同的。虽然自动化大大提高了数据收集的速度，但优化仍然是手动进行的。这个费力的过程高度依赖于主观评估，效率低下，容易出错，往往决定了项目的成功。在这里，我们提出了SmartScope，第一个框架，简化，标准化和自动化的标本评估冷冻电子显微镜。SmartScope采用基于深度学习的物体检测来识别和分类适合成像的特征，使其能够以完全自动化的方式进行彻底的样本筛选。网络界面提供了对显微镜自动化操作的远程控制，可以真实的实时访问图像和注释工具。手动注释可用于重新训练特征识别模型，从而提高性能。我们的自动化工具系统评估标本简化结构测定和降低采用低温电子显微镜的障碍。
Propelled by improvements in hardware for data collection and processing, single particle cryo-electron microscopy has rapidly gained relevance in structural biology. Yet, finding the conditions to stabilize a macromolecular target for imaging remains the most critical barrier to determining its structure. Attaining the optimal specimen requires the evaluation of multiple grids in a microscope as conditions are varied. While automation has significantly increased the speed of data collection, optimization is still carried out manually. This laborious process which is highly dependent on subjective assessments, inefficient and prone to error, often determines the success of a project. Here, we present SmartScope, the first framework to streamline, standardize, and automate specimen evaluation in cryo-electron microscopy. SmartScope employs deep-learning-based object detection to identify and classify features suitable for imaging, allowing it to perform thorough specimen screening in a fully automated manner. A web interface provides remote control over the automated operation of the microscope in real time and access to images and annotation tools. Manual annotations can be used to re-train the feature recognition models, leading to improvements in performance. Our automated tool for systematic evaluation of specimens streamlines structure determination and lowers the barrier of adoption for cryo-electron microscopy.
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