Local computational methods to improve the interpretability and analysis of cryo-EM maps.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
23 02 2021
23 02 2021
Historique:
received:
30
06
2020
accepted:
29
01
2021
entrez:
24
2
2021
pubmed:
25
2
2021
medline:
25
2
2021
Statut:
epublish
Résumé
Cryo-electron microscopy (cryo-EM) maps usually show heterogeneous distributions of B-factors and electron density occupancies and are typically B-factor sharpened to improve their contrast and interpretability at high-resolutions. However, 'over-sharpening' due to the application of a single global B-factor can distort processed maps causing connected densities to appear broken and disconnected. This issue limits the interpretability of cryo-EM maps, i.e. ab initio modelling. In this work, we propose 1) approaches to enhance high-resolution features of cryo-EM maps, while preventing map distortions and 2) methods to obtain local B-factors and electron density occupancy maps. These algorithms have as common link the use of the spiral phase transformation and are called LocSpiral, LocBSharpen, LocBFactor and LocOccupancy. Our results, which include improved maps of recent SARS-CoV-2 structures, show that our methods can improve the interpretability and analysis of obtained reconstructions.
Identifiants
pubmed: 33623015
doi: 10.1038/s41467-021-21509-5
pii: 10.1038/s41467-021-21509-5
pmc: PMC7902670
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1240Références
J Opt Soc Am A Opt Image Sci Vis. 2003 May;20(5):925-34
pubmed: 12747439
Nat Commun. 2020 Jan 2;11(1):55
pubmed: 31896756
RNA. 2020 Dec;26(12):2017-2030
pubmed: 32989043
Structure. 2020 Feb 4;28(2):169-184.e5
pubmed: 31806353
Acta Crystallogr D Struct Biol. 2019 Oct 1;75(Pt 10):861-877
pubmed: 31588918
Structure. 2010 Jul 14;18(7):768-75
pubmed: 20637413
J Struct Biol. 2015 Feb;189(2):114-22
pubmed: 25486611
J Cell Biol. 2020 Jan 6;219(1):
pubmed: 31727777
J Struct Biol. 2013 Feb;181(2):136-48
pubmed: 23261401
Science. 2020 Mar 13;367(6483):1260-1263
pubmed: 32075877
Elife. 2016 Nov 15;5:
pubmed: 27845625
Nature. 2017 Jun 29;546(7660):617-621
pubmed: 28530653
Nat Methods. 2014 Jan;11(1):63-5
pubmed: 24213166
Cell. 2016 Dec 1;167(6):1610-1622.e15
pubmed: 27912064
Appl Opt. 2012 Oct 20;51(30):7362-7
pubmed: 23089793
Cell. 2020 May 14;181(4):877-893.e21
pubmed: 32304664
Methods Enzymol. 2010;482:35-72
pubmed: 20888957
Structure. 2018 Feb 6;26(2):337-344.e4
pubmed: 29395788
Elife. 2020 Jan 17;9:
pubmed: 31951202
Cell. 2020 Dec 10;183(6):1735
pubmed: 33306958
Nature. 2020 Apr;580(7805):658-662
pubmed: 32350467
Nat Methods. 2015 Oct;12(10):943-6
pubmed: 26280328
Elife. 2017 Oct 23;6:
pubmed: 29058676
Appl Opt. 2012 Aug 20;51(24):5903-8
pubmed: 22907020
J Struct Biol. 2019 Oct 1;208(1):43-50
pubmed: 31344437
Acta Crystallogr D Struct Biol. 2018 Jun 1;74(Pt 6):531-544
pubmed: 29872004
J Mol Biol. 2003 Oct 31;333(4):721-45
pubmed: 14568533
Nucleic Acids Res. 2019 Sep 5;47(15):8301-8317
pubmed: 31265110
Acta Crystallogr D Struct Biol. 2018 Jun 1;74(Pt 6):545-559
pubmed: 29872005
Bioinformatics. 2020 Feb 1;36(3):765-772
pubmed: 31504163
Nucleic Acids Res. 2011 Jan;39(Database issue):D456-64
pubmed: 20935055
Methods Enzymol. 2016;579:277-305
pubmed: 27572731
J Struct Biol. 2019 Dec 1;208(3):107397
pubmed: 31568828
Nat Methods. 2016 May;13(5):387-8
pubmed: 27067018
Proc Natl Acad Sci U S A. 2019 Oct 1;116(40):19930-19938
pubmed: 31527277
Methods Enzymol. 2003;374:300-21
pubmed: 14696379
Acta Crystallogr D Struct Biol. 2018 Sep 1;74(Pt 9):814-840
pubmed: 30198894
J Opt Soc Am A Opt Image Sci Vis. 2001 Aug;18(8):1862-70
pubmed: 11488490
Opt Lett. 2011 Sep 1;36(17):3485-7
pubmed: 21886252
J Struct Biol. 2008 Oct;164(1):170-5
pubmed: 18614378
J Struct Biol. 2013 Sep;183(3):342-353
pubmed: 23933392