Publication: Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms
Authors
Martínez Sánchez, Antonio ; Kochovsk, Zdravko ; Laugks, Ulrike ; Meyer zum Alten Borgloh, Johannes ; Chakraborty, Saikat ; Pfeffer, Stefan ; Baumeister, Wolfgang ; Lucic, Vladan
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Publisher
Nature Research
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DOI
https://doi.org/10.1038/s41592-019-0675-5
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info:eu-repo/semantics/article
Description
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. This document is the Accepted version of a Published Work that appeared in final form in Nature Methods. To access the final edited and published work see https://doi.org/10.1038/s41592-019-0675-5
Abstract
With faithful sample preservation and direct imaging of fully hydrated biological material, cryo-electron tomography provides an accurate representation of molecular architecture of cells. However, detection and
precise localization of macromolecular complexes within cellular environments is aggravated by the presence of many molecular species and molecular crowding. We developed a template-free image processing procedure for accurate tracing of complex networks of densities in cryo-electron tomograms, a comprehensive and automated detection of heterogeneous membrane-bound complexes and an unsupervised classification (PySeg). Applications to intact cells and isolated endoplasmic reticulum (ER) allowed us to detect and classify small protein complexes. This classification provided sufficiently homogeneous particle sets and initial references to allow subsequent de novo subtomogram averaging. Spatial distribution analysis showedthat ER complexes have different localization patterns forming nanodomains. Therefore this procedure
allows a comprehensive detection and structural analysis of complexes in situ.
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Citation
Nature Methods 17, 209–216 (2020)
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