Averaging of Electron Subtomograms and Random Conical Tilt Reconstructions through Likelihood Optimization
Averaging of Electron Subtomograms and Random Conical Tilt Reconstructions through Likelihood Optimization
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DOI：
10.1016/j.str.2009.10.009
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发表时间：
2009-12-09
期刊：
影响因子：
5.7
通讯作者：
Carazo, Jose-Maria
中科院分区：
文献类型：
--
作者：
Scheres, Sjors H. W.;Melero, Roberto;Carazo, Jose-Maria
无参考平均的三维电子显微镜（3D-EM）重建与傅立叶空间中的空白区域代表了一个紧迫的问题，在电子层析成像和单粒子分析。我们提出了一个最大似然算法的同时对齐和分类subtomographs或随机圆锥倾斜（RCT）重建，在缺失的数据区域的傅立叶分量被视为隐藏变量。该算法的行为进行了探讨，使用模拟数据的测试，而应用到实验数据显示，产生无监督类平均的subtomograms的groEL/groES复合物和RCT重建的p53。后一种应用用于获得p53的可靠的从头结构，其可以解决关于其四级结构的不确定性。
The reference-free averaging of three-dimensional electron microscopy (3D-EM) reconstructions with empty regions in Fourier space represents a pressing problem in electron tomography and single-particle analysis. We present a maximum likelihood algorithm for the simultaneous alignment and classification of subtomograms or random conical tilt (RCT) reconstructions, where the Fourier components in the missing data regions are treated as hidden variables. The behavior of this algorithm was explored using tests on simulated data, while application to experimental data was shown to yield unsupervised class averages for subtomograms of groEL/groES complexes and RCT reconstructions of p53. The latter application served to obtain a reliable de novo structure for p53 that may resolve uncertainties about its quaternary structure.