Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms
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 aggrava...
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| Veröffentlicht in: | Nature methods 2020-02, Vol.17 (2), p.209-216 |
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| creator | Martinez-Sanchez, Antonio Kochovski, Zdravko Laugks, Ulrike Meyer zum Alten Borgloh, Johannes Chakraborty, Saikat Pfeffer, Stefan Baumeister, Wolfgang Lučić, Vladan |
| description | 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.
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. |
| doi_str_mv | 10.1038/s41592-019-0675-5 |
| format | Article |
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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.</description><identifier>ISSN: 1548-7091</identifier><identifier>EISSN: 1548-7105</identifier><identifier>DOI: 10.1038/s41592-019-0675-5</identifier><identifier>PMID: 31907446</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>631/114/1564 ; 631/114/794 ; 631/1647/2258/1258/1260 ; 631/45/612/1237 ; Animals ; Bioinformatics ; Biological materials ; Biological Microscopy ; Biological Techniques ; Biomedical and Life Sciences ; Biomedical Engineering/Biotechnology ; Classification ; Cluster Analysis ; Cryoelectron Microscopy - methods ; Electrons ; Endoplasmic reticulum ; Image detection ; Image processing ; Life Sciences ; Localization ; Macromolecules ; Male ; Membrane proteins ; Membranes ; Mice ; Molecular structure ; Preservation ; Protein binding ; Proteins ; Proteomics ; Rats ; Rats, Wistar ; Reproducibility of Results ; Sample preservation ; Spatial analysis ; Spatial distribution ; Structural analysis ; Technology application</subject><ispartof>Nature methods, 2020-02, Vol.17 (2), p.209-216</ispartof><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2020</rights><rights>COPYRIGHT 2020 Nature Publishing Group</rights><rights>2020© The Author(s), under exclusive licence to Springer Nature America, Inc. 2020</rights><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2020.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c576t-5dc292828cd1c4eb0ac309f6a856e73abb76ea1c6e1a489a27ee00cedf63cdc23</citedby><cites>FETCH-LOGICAL-c576t-5dc292828cd1c4eb0ac309f6a856e73abb76ea1c6e1a489a27ee00cedf63cdc23</cites><orcidid>0000-0003-3698-7436 ; 0000-0002-6307-8441 ; 0000-0002-5865-2138</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41592-019-0675-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41592-019-0675-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31907446$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Martinez-Sanchez, Antonio</creatorcontrib><creatorcontrib>Kochovski, Zdravko</creatorcontrib><creatorcontrib>Laugks, Ulrike</creatorcontrib><creatorcontrib>Meyer zum Alten Borgloh, Johannes</creatorcontrib><creatorcontrib>Chakraborty, Saikat</creatorcontrib><creatorcontrib>Pfeffer, Stefan</creatorcontrib><creatorcontrib>Baumeister, Wolfgang</creatorcontrib><creatorcontrib>Lučić, Vladan</creatorcontrib><title>Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms</title><title>Nature methods</title><addtitle>Nat Methods</addtitle><addtitle>Nat Methods</addtitle><description>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.
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.</description><subject>631/114/1564</subject><subject>631/114/794</subject><subject>631/1647/2258/1258/1260</subject><subject>631/45/612/1237</subject><subject>Animals</subject><subject>Bioinformatics</subject><subject>Biological materials</subject><subject>Biological Microscopy</subject><subject>Biological Techniques</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical Engineering/Biotechnology</subject><subject>Classification</subject><subject>Cluster Analysis</subject><subject>Cryoelectron Microscopy - methods</subject><subject>Electrons</subject><subject>Endoplasmic reticulum</subject><subject>Image detection</subject><subject>Image processing</subject><subject>Life 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| subjects | 631/114/1564 631/114/794 631/1647/2258/1258/1260 631/45/612/1237 Animals Bioinformatics Biological materials Biological Microscopy Biological Techniques Biomedical and Life Sciences Biomedical Engineering/Biotechnology Classification Cluster Analysis Cryoelectron Microscopy - methods Electrons Endoplasmic reticulum Image detection Image processing Life Sciences Localization Macromolecules Male Membrane proteins Membranes Mice Molecular structure Preservation Protein binding Proteins Proteomics Rats Rats, Wistar Reproducibility of Results Sample preservation Spatial analysis Spatial distribution Structural analysis Technology application |
| title | Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms |
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