AutoGDeterm: Automatic Geometry Determination for Electron Tomography

Yu Chen; Zihao Wang; Lun Li; Jingrong Zhang; Xiaohua Wan; Fei Sun; Fa Zhang

doi:10.26599/TST.2018.9010036

Tsinghua Science and Technology 2018, 23(4): 369-376 https://doi.org/10.26599/TST.2018.9010036

Open Access | Issue | Published: 16 August 2018

AutoGDeterm: Automatic Geometry Determination for Electron Tomography

Show Author's Information Hide Author's Information Yu Chen, Zihao Wang, Lun Li, Jingrong Zhang, Xiaohua Wan, Fei Sun(

), Fa Zhang(

)

High Performance Computer Research Center, ICT, CAS, Beijing 100101, China.

University of Chinese Academy of Sciences, Beijing 100101, China.

Center for Biological Imaging, IBP, CAS and the National Key Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Beijing 100101, China.

Keywords:

electron tomography, geometry determination, human intervention, full automation, AutoGDeterm, comparable accuracy

Cite this article:

Chen Y, Wang Z, Li L, et al. AutoGDeterm: Automatic Geometry Determination for Electron Tomography. Tsinghua Science and Technology, 2018, 23(4): 369-376. https://doi.org/10.26599/TST.2018.9010036

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Abstract

Electron Tomography (ET) is an important method for studying cell ultrastructure in three-dimensional (3D) space. By combining cryo-electron tomography of frozen-hydrated samples (cryo-ET) and a sub-tomogram averaging approach, ET has recently reached sub-nanometer resolution, thereby realizing the capability for gaining direct insights into function and mechanism. To obtain a high-resolution 3D ET reconstruction, alignment and geometry determination of the ET tilt series are necessary. However, typical methods for determining geometry require human intervention, which is not only subjective and easily introduces errors, but is also labor intensive for high-throughput tomographic reconstructions. To overcome these problems, we have developed an automatic geometry-determination method, called AutoGDeterm. By taking advantage of the high-contrast re-projections of the Iterative Compressed-sensing Optimized Non-Uniform Fast Fourier Transform (NUFFT) reconstruction (ICON) and a series of numerical analysis methods, AutoGDeterm achieves high-precision fully automated geometry determination. Experimental results on simulated and resin-embedded datasets show that the accuracy of AutoGDeterm is high and comparable to that of the typical “manual positioning” method. We have made AutoGDeterm available as software, which can be freely downloaded from our website http://ear.ict.ac.cn.

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AutoGDeterm: Automatic Geometry Determination for Electron Tomography

Show Author's information Hide Author's Information Yu Chen, Zihao Wang, Lun Li, Jingrong Zhang, Xiaohua Wan, Fei Sun(

), Fa Zhang(

)

High Performance Computer Research Center, ICT, CAS, Beijing 100101, China.

University of Chinese Academy of Sciences, Beijing 100101, China.

Center for Biological Imaging, IBP, CAS and the National Key Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Beijing 100101, China.

Abstract

Keywords: electron tomography, geometry determination, human intervention, full automation, AutoGDeterm, comparable accuracy

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Publication history

Received: 06 September 2017

Accepted: 01 November 2017

Published: 16 August 2018

Issue date: August 2018

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Acknowledgements

We acknowledge Albert Lawrence and his colleagues at UCSD for our acquisition of the simulated data. This research was supported by the National Natural Science Foundation of China (Nos. U1611263, U1611261, 61232001, 61472397, 61502455, and 61672493) and the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase), the Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB08030202), and the National Key Research and Development Program of China (No. 2017YFA0504702).