RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, United States.
Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, United States.
Elife. 2022 Aug 25;11:e79272. doi: 10.7554/eLife.79272.
Previously, we showed that high-resolution template matching can localize ribosomes in two-dimensional electron cryo-microscopy (cryo-EM) images of untilted cells with high precision (Lucas et al., 2021). Here, we show that comparing the signal-to-noise ratio (SNR) observed with 2DTM using different templates relative to the same cellular target can correct for local variation in noise and differentiate related complexes in focused ion beam (FIB)-milled cell sections. We use a maximum likelihood approach to define the probability of each particle belonging to each class, thereby establishing a statistic to describe the confidence of our classification. We apply this method in two contexts to locate and classify related intermediate states of 60S ribosome biogenesis in the cell nucleus. In the first, we separate the nuclear pre-60S population from the cytoplasmic mature 60S population, using the subcellular localization to validate assignment. In the second, we show that relative 2DTM SNRs can be used to separate mixed populations of nuclear pre-60S that are not visually separable. 2DTM can distinguish related molecular populations without the need to generate 3D reconstructions from the data to be classified, permitting classification even when only a few target particles exist in a cell.
此前,我们展示了高分辨率模板匹配可以高精度地定位未倾斜细胞的二维电子冷冻电镜(cryo-EM)图像中的核糖体(Lucas 等人,2021 年)。在这里,我们表明,通过比较使用不同模板的 2DTM 与相同细胞靶标观察到的信噪比(SNR),可以校正噪声的局部变化,并区分聚焦离子束(FIB)铣削细胞切片中的相关复合物。我们使用最大似然方法来定义每个粒子属于每个类别的概率,从而建立一个统计量来描述我们分类的置信度。我们将该方法应用于两个方面,以定位和分类细胞核中 60S 核糖体生物发生的相关中间状态。在第一种情况下,我们使用亚细胞定位将核前 60S 群体与细胞质成熟 60S 群体分离,以验证分配。在第二种情况下,我们表明相对的 2DTM SNR 可用于分离不可视分离的核前 60S 混合群体。2DTM 可以区分相关的分子群体,而无需从要分类的数据中生成 3D 重建,从而允许在细胞中仅存在少量目标粒子时进行分类。