Classification and 3D averaging with missing wedge correction in biological electron tomography
Classification and 3D averaging with missing wedge correction in biological electron tomography
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DOI：
10.1016/j.jsb.2008.02.008
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发表时间：
2008-06-01
影响因子：
3
通讯作者：
Subramaniam, S.
中科院分区：
文献类型：
--
作者：
Bartesaghi, A.;Sprechmann, P.;Subramaniam, S.
使用电子晶体学和单粒子电子显微镜确定生物大分子的3D结构的策略利用了从结构均匀的标本的2D投影图像获得的信息的平均化的强大工具。相比之下，电子断层摄影方法经常被用来研究异质的，一个一类的对象，如整个细胞的图像平均策略是不适用的3D结构。然而，复杂的实体，如细胞和病毒，包含许多大分子的多个副本，可以单独进行3D平均。在这里，我们提出了一个完整的框架，对齐，分类，并平均的体积来自电子断层扫描，计算效率高，有效地占丢失的楔形，是固有的有限角度的电子断层扫描。在倒易空间中将缺失数据建模为乘法掩模，我们表明缺失楔形的效果可以在所有对齐和分类操作中无缝地考虑。我们使用谐波分析中的卷积定理解决对齐问题，从而消除了对需要穷举角度搜索的方法的需要，并采用迭代方法来对齐和分类，不需要使用外部参考。我们证明，我们的方法可以成功地应用于3D分类和平均体模体积，以及实验获得的断层图像GroEL的分析结果可以定量地与预期的结果进行比较。(c)2008年爱思唯尔公司All rights reserved.
Strategies for the determination of 3D structures of biological macromolecules using electron crystallography and single-particle electron microscopy utilize powerful tools for the averaging of information obtained from 2D projection images of structurally homogeneous specimens. In contrast, electron tomographic approaches have often been used to study the 3D structures of heterogeneous, one-of-a-kind objects such as whole cells where image-averaging strategies are not applicable. Complex entities such as cells and viruses, nevertheless, contain multiple copies of numerous macromolecules that can individually be subjected to 3D averaging. Here we present a complete framework for alignment, classification, and averaging of volumes derived by electron tomography that is computationally efficient and effectively accounts for the missing wedge that is inherent to limited-angle electron tomography. Modeling the missing data as a multiplying mask in reciprocal space we show that the effect of the missing wedge can be accounted for seamlessly in all alignment and classification operations. We solve the alignment problem using the convolution theorem in harmonic analysis, thus eliminating the need for approaches that require exhaustive angular search, and adopt an iterative approach to alignment and classification that does not require the use of external references. We demonstrate that our method can be successfully applied for 3D classification and averaging of phantom volumes as well as experimentally obtained tomograms of GroEL where the outcomes of the analysis can be quantitatively compared against the expected results. (c) 2008 Elsevier Inc. All rights reserved.