Electron Bio-Imaging Centre, Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, UK; Department of Chemistry, University of York, York, UK.
Department of Chemistry, University of York, York, UK.
Structure. 2022 Apr 7;30(4):522-531.e4. doi: 10.1016/j.str.2022.01.005. Epub 2022 Feb 11.
Despite the abundance of available software tools, optimal particle selection is still a vital issue in single-particle cryoelectron microscopy (cryo-EM). Regardless of the method used, most pickers struggle when ice thickness varies on a micrograph. IceBreaker allows users to estimate the relative ice gradient and flatten it by equalizing the local contrast. It allows the differentiation of particles from the background and improves overall particle picking performance. Furthermore, we introduce an additional parameter corresponding to local ice thickness for each particle. Particles with a defined ice thickness can be grouped and filtered based on this parameter during processing. These functionalities are especially valuable for on-the-fly processing to automatically pick as many particles as possible from each micrograph and to select optimal regions for data collection. Finally, estimated ice gradient distributions can be stored separately and used to inspect the quality of prepared samples.
尽管有大量可用的软件工具,但在单颗粒冷冻电子显微镜(cryo-EM)中,最佳粒子选择仍然是一个至关重要的问题。无论使用哪种方法,当微观图上的冰厚发生变化时,大多数选择器都会遇到困难。IceBreaker 允许用户通过均衡局部对比度来估计相对冰梯度并使其变平。它允许从背景中区分粒子,并提高整体粒子选择性能。此外,我们为每个粒子引入了一个对应于局部冰厚的附加参数。具有定义冰厚的粒子可以在处理过程中基于此参数进行分组和过滤。这些功能对于实时处理非常有价值,可以自动从每个微观图中选择尽可能多的粒子,并选择最佳区域进行数据收集。最后,估计的冰梯度分布可以单独存储,并用于检查样品制备的质量。