Dataset Information

Automated batch fiducial-less tilt-series alignment in Appion using Protomo.

ABSTRACT: The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy.

SUBMITTER: Noble AJ

PROVIDER: S-EPMC4633401 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Publications

Automated batch fiducial-less tilt-series alignment in Appion using Protomo.

Noble Alex J AJ Stagg Scott M SM

Journal of structural biology 20151009 2

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliabl ...[more]

PMID: 26455557

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Project description:MOTIVATION:Electron tomography (ET) is a widely used technology for 3D macro-molecular structure reconstruction. To obtain a satisfiable tomogram reconstruction, several key processes are involved, one of which is the calibration of projection parameters of the tilt series. Although fiducial marker-based alignment for tilt series has been well studied, marker-free alignment remains a challenge, which requires identifying and tracking the identical objects (landmarks) through different projections. However, the tracking of these landmarks is usually affected by the pixel density (intensity) change caused by the geometry difference in different views. The tracked landmarks will be used to determine the projection parameters. Meanwhile, different projection parameters will also affect the localization of landmarks. Currently, there is no alignment method that takes interrelationship between the projection parameters and the landmarks. RESULTS:Here, we propose a novel, joint method for marker-free alignment of tilt series in ET, by utilizing the information underlying the interrelationship between the projection model and the landmarks. The proposed method is the first joint solution that combines the extrinsic (track-based) alignment and the intrinsic (intensity-based) alignment, in which the localization of landmarks and projection parameters keep refining each other until convergence. This iterative approach makes our solution robust to different initial parameters and extreme geometric changes, which ensures a better reconstruction for marker-free ET. Comprehensive experimental results on three real datasets show that our new method achieved a significant improvement in alignment accuracy and reconstruction quality, compared to the state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION:The main program is available at https://github.com/icthrm/joint-marker-free-alignment. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Dataset Information

Automated batch fiducial-less tilt-series alignment in Appion using Protomo.

Publications

Automated batch fiducial-less tilt-series alignment in Appion using Protomo.

Similar Datasets

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