Two particle-picking procedures for filamentous proteins: SPHIRE-crYOLO filament mode and SPHIRE-STRIPER.


Journal

Acta crystallographica. Section D, Structural biology
ISSN: 2059-7983
Titre abrégé: Acta Crystallogr D Struct Biol
Pays: United States
ID NLM: 101676043

Informations de publication

Date de publication:
01 Jul 2020
Historique:
received: 28 02 2020
accepted: 01 06 2020
entrez: 7 7 2020
pubmed: 7 7 2020
medline: 14 5 2021
Statut: ppublish

Résumé

Structure determination of filamentous molecular complexes involves the selection of filaments from cryo-EM micrographs. The automatic selection of helical specimens is particularly difficult, and thus many challenging samples with issues such as contamination or aggregation are still manually picked. Here, two approaches for selecting filamentous complexes are presented: one uses a trained deep neural network to identify the filaments and is integrated in SPHIRE-crYOLO, while the other, called SPHIRE-STRIPER, is based on a classical line-detection approach. The advantage of the crYOLO-based procedure is that it performs accurately on very challenging data sets and selects filaments with high accuracy. Although STRIPER is less precise, the user benefits from less intervention, since in contrast to crYOLO, STRIPER does not require training. The performance of both procedures on Tobacco mosaic virus and filamentous F-actin data sets is described to demonstrate the robustness of each method.

Identifiants

pubmed: 32627734
pii: S2059798320007342
doi: 10.1107/S2059798320007342
pmc: PMC7336381
doi:

Substances chimiques

Actins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

613-620

Informations de copyright

open access.

Références

Nature. 2017 Jul 13;547(7662):185-190
pubmed: 28678775
J Struct Biol. 2016 Sep;195(3):325-336
pubmed: 27424268
J Struct Biol. 2009 May;166(2):205-13
pubmed: 19374019
J Vis Exp. 2017 May 16;(123):
pubmed: 28570515
Curr Opin Struct Biol. 2018 Oct;52:16-24
pubmed: 30056307
Structure. 2020 Apr 7;28(4):437-449.e5
pubmed: 32084355
Nat Struct Mol Biol. 2018 Jun;25(6):528-537
pubmed: 29867215
Structure. 2012 Feb 8;20(2):237-47
pubmed: 22325773
BMC Bioinformatics. 2017 Nov 29;18(1):529
pubmed: 29187165
Nat Methods. 2019 Nov;16(11):1153-1160
pubmed: 31591578
BMC Bioinformatics. 2017 Jul 21;18(1):348
pubmed: 28732461
J Struct Biol. 2007 Jan;157(1):38-46
pubmed: 16859925
IEEE Trans Pattern Anal Mach Intell. 1986 Jun;8(6):679-98
pubmed: 21869365
J Struct Biol. 2017 Jun;198(3):163-176
pubmed: 28193500
J Struct Biol. 2015 Feb;189(2):114-22
pubmed: 25486611
J Struct Biol. 2001 Feb-Mar;133(2-3):90-101
pubmed: 11472081
Commun Biol. 2019 Jun 19;2:218
pubmed: 31240256
J Struct Biol. 2015 Feb;189(2):87-97
pubmed: 25528571
Science. 2017 Oct 6;358(6359):45-46
pubmed: 28983039
Nat Methods. 2019 Nov;16(11):1146-1152
pubmed: 31591575
J Struct Biol. 2004 Jan-Feb;145(1-2):29-40
pubmed: 15065671
J Struct Biol. 2020 Jun 1;210(3):107498
pubmed: 32276087
J Struct Biol. 2018 Apr;202(1):1-12
pubmed: 29191673

Auteurs

Thorsten Wagner (T)

Department of Structural Biochemistry, Max Planck Institute of Molecular Physiology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Luca Lusnig (L)

Department of Structural Biochemistry, Max Planck Institute of Molecular Physiology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Sabrina Pospich (S)

Department of Structural Biochemistry, Max Planck Institute of Molecular Physiology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Markus Stabrin (M)

Department of Structural Biochemistry, Max Planck Institute of Molecular Physiology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Fabian Schönfeld (F)

Department of Structural Biochemistry, Max Planck Institute of Molecular Physiology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Stefan Raunser (S)

Department of Structural Biochemistry, Max Planck Institute of Molecular Physiology, Otto-Hahn-Strasse 11, 44227 Dortmund, Germany.

Articles similaires

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages
Photosynthesis Ribulose-Bisphosphate Carboxylase Carbon Dioxide Molecular Dynamics Simulation Cyanobacteria

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Yoan Martínez-López, Paulina Phoobane, Yanaima Jauriga et al.
1.00
Blood-Brain Barrier Machine Learning Humans Support Vector Machine Software
1.00
Humans Magnetic Resonance Imaging Brain Infant, Newborn Infant, Premature

Classifications MeSH