Detection and separation of heterogeneity in molecular complexes by statistical analysis of their two-dimensional projections
Detection and separation of heterogeneity in molecular complexes by statistical analysis of their two-dimensional projections
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DOI：
10.1016/j.jsb.2007.11.007
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发表时间：
2008-04-01
影响因子：
3
通讯作者：
Orlova, Elena V.
中科院分区：
文献类型：
--
作者：
Elad, Nadav;Clare, Daniel K.;Orlova, Elena V.
通过低温电子显微镜和单粒子分析确定分子结构的进展导致了可实现的分辨率的改进。然而，在许多情况下，限制因素是样品的结构异质性。为了解决这个问题，我们已经开发了一种基于二维图像的统计分析的方法，以检测和分类例如由配体的可变占用引起的局部结构变化。图像通过两个连续的多变量统计分析（MSA）阶段进行分类，以剖析出两个主要的变化来源，即平面外方向和局部结构变化。由局部变化引起的异质结由MSA检测，其揭示了高阶本征图像中的显著峰。揭示局部峰值的特征图像用于自动分类。类之间的差异评价允许有和没有配体的分子图像的歧视。该方法非常快速，不依赖于任何初始三维模型，并且可以检测图像集合中的甚至较小的亚群。使用这种技术的战略是在模型数据集上开发的。在这里，我们证明了成功的应用这种方法的模型和真实的EM数据伴侣蛋白底物和核糖体配体复合物。(C)2007年爱思唯尔公司All rights reserved.
Progress in molecular structure determination by cryo electron microscopy and single particle analysis has led to improvements in the resolution achievable. However, in many cases the limiting factor is structural heterogeneity of the sample. To address this problem, we have developed a method based on statistical analysis of the two-dimensional images to detect and sort localised structural variations caused, for example, by variable occupancy of a ligand. Images are sorted by two consecutive stages of multivariate statistical analysis (MSA) to dissect out the two main sources of variation, namely out of plane orientation and local structural changes. Heterogeneity caused by local changes is detected by MSA that reveals significant peaks in the higher order eigenimages. The eigenimages revealing local peaks are used for automated classification. Evaluation of differences between classes allows discrimination of molecular images with and without ligand. This method is very rapid, independent of any initial three-dimensional model, and can detect even minor subpopulations in an image ensemble. A strategy for using this technique was developed on model data sets. Here, we demonstrate the successful application of this method to both model and real EM data on chaperonin-substrate and ribosome-ligand complexes. (C) 2007 Elsevier Inc. All rights reserved.