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  Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms

Martinez Sanchez, A., Kochovski, Z., Laugks, U., Meyer Zum Alten Borgloh, J., Chakraborty, S., Pfeffer, S., et al. (2020). Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms. NATURE METHODS, 17, 209-216. doi:10.1038/s41592-019-0675-5.

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 Creators:
Martinez Sanchez, Antonio1, Author              
Kochovski, Zdravko1, Author              
Laugks, Ulrike1, Author              
Meyer Zum Alten Borgloh, Johannes1, Author              
Chakraborty, Saikat1, Author              
Pfeffer, Stefan1, Author              
Baumeister, Wolfgang1, Author              
Lucic, Vladan1, Author              
Affiliations:
1Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565142              

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Free keywords: CRYO-EM STRUCTURE; RECEPTOR; VISUALIZATION; SEGMENTATION; CELLS
 Abstract: A template-free image processing approach automatically detects and classifies membrane-bound protein complexes in cryo-electron tomograms of isolated endoplasmic reticulum and in intact cells. 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 showed that 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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Language(s): eng - English
 Dates: 2020
 Publication Status: Published in print
 Pages: 15
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000507799300002
DOI: 10.1038/s41592-019-0675-5
 Degree: -

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Title: NATURE METHODS
Source Genre: Journal
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Publ. Info: MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND : NATURE PUBLISHING GROUP
Pages: - Volume / Issue: 17 Sequence Number: - Start / End Page: 209 - 216 Identifier: ISSN: 1548-7091