Institute of Biological Information Processing (IBI-7: Structural Biochemistry) and JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, 52425, Jülich, Germany.
Institute of Biological Information Processing (IBI-7: Structural Biochemistry) and JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, 52425, Jülich, Germany; Physics Department, Heinrich-Heine-Universität Düsseldorf, 40225, Düsseldorf, Germany.
Prog Biophys Mol Biol. 2021 Mar;160:16-25. doi: 10.1016/j.pbiomolbio.2020.11.007. Epub 2021 Feb 6.
Recent steps towards automation have improved the quality and efficiency of the entire cryo-electron microscopy workflow, from sample preparation to image processing. Most of the image processing steps are now quite automated, but there are still a few steps which need the specific intervention of researchers. One such step is the identification and separation of helical protein polymorphs at early stages of image processing. Here, we tested and evaluated our recent clustering approach on three datasets containing amyloid fibrils, demonstrating that the proposed unsupervised clustering method automatically and effectively identifies the polymorphs from cryo-EM images. As an automated polymorph separation method, it has the potential to complement automated helical picking, which typically cannot easily distinguish between polymorphs with subtle differences in morphology, and is therefore a useful tool for the image processing and structure determination of helical proteins.
最近在自动化方面的进展提高了整个冷冻电子显微镜工作流程的质量和效率,从样品制备到图像处理。现在,大多数图像处理步骤已经相当自动化,但仍有一些步骤需要研究人员的具体干预。其中一个步骤是在图像处理的早期阶段识别和分离螺旋蛋白多态体。在这里,我们在三个包含淀粉样纤维的数据集上测试和评估了我们最近的聚类方法,证明了所提出的无监督聚类方法能够自动有效地从冷冻电镜图像中识别多态体。作为一种自动化的多态体分离方法,它有可能补充自动化的螺旋挑选,因为自动化的螺旋挑选通常难以区分形态上只有细微差异的多态体,因此它是螺旋蛋白图像处理和结构确定的有用工具。