Ghostbuster: A phase retrieval diffraction tomography algorithm for cryo-EM.

Cryogenic electron microscopy Diffraction tomography Ewald sphere curvature correction Phase retrieval Single particle reconstruction

Journal

Ultramicroscopy
ISSN: 1879-2723
Titre abrégé: Ultramicroscopy
Pays: Netherlands
ID NLM: 7513702

Informations de publication

Date de publication:
12 Apr 2024
Historique:
received: 20 12 2023
revised: 16 03 2024
accepted: 01 04 2024
medline: 21 4 2024
pubmed: 21 4 2024
entrez: 20 4 2024
Statut: aheadofprint

Résumé

Ewald sphere curvature correction, which extends beyond the projection approximation, stretches the shallow depth of field in cryo-EM reconstructions of thick particles. Here we show that even for previously assumed thin particles, reconstruction artifacts which we refer to as ghosts can appear. By retrieving the lost phases of the electron exitwaves and accounting for the first Born approximation scattering within the particle, we show that these ghosts can be effectively eliminated. Our simulations demonstrate how such ghostbusting can improve reconstructions as compared to existing state-of-the-art software. Like ptychographic cryo-EM, our Ghostbuster algorithm uses phase retrieval to improve reconstructions, but unlike the former, we do not need to modify the existing data acquisition pipelines.

Identifiants

pubmed: 38642481
pii: S0304-3991(24)00041-X
doi: 10.1016/j.ultramic.2024.113962
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

113962

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Joel Yeo (J)

NUS Graduate School for Integrative Sciences and Engineering Programme, National University of Singapore, 119077 Singapore, Singapore; Department of Physics, National University of Singapore, 117551 Singapore, Singapore; Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, 138634 Singapore, Singapore.

Benedikt J Daurer (BJ)

Center for Bio-Imaging Sciences, National University of Singapore, 117557 Singapore, Singapore; Diamond Light Source, Harwell Campus, Didcot, OX11 0DE, UK.

Dari Kimanius (D)

MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK; CZ Imaging Institute, 3400 Bridge Parkway, Redwood City, CA 94065, USA.

Deepan Balakrishnan (D)

Department of Biological Sciences, National University of Singapore, 117558 Singapore, Singapore; Center for Bio-Imaging Sciences, National University of Singapore, 117557 Singapore, Singapore.

Tristan Bepler (T)

Simons Machine Learning Center, New York Structural Biology Center, New York, NY, USA.

Yong Zi Tan (YZ)

Department of Biological Sciences, National University of Singapore, 117558 Singapore, Singapore; Center for Bio-Imaging Sciences, National University of Singapore, 117557 Singapore, Singapore; Disease Intervention Technology Laboratory (DITL), Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, 138648 Singapore, Singapore; Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, 138673 Singapore, Singapore.

N Duane Loh (ND)

NUS Graduate School for Integrative Sciences and Engineering Programme, National University of Singapore, 119077 Singapore, Singapore; Department of Physics, National University of Singapore, 117551 Singapore, Singapore; Department of Biological Sciences, National University of Singapore, 117558 Singapore, Singapore; Center for Bio-Imaging Sciences, National University of Singapore, 117557 Singapore, Singapore. Electronic address: duaneloh@nus.edu.sg.

Classifications MeSH