Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo

With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available...

Descripción completa

Detalles Bibliográficos
Autores: Coray, Raffaele, Navarro, Paula, Scaramuzza, Stefano, Stahlberg, Henning, Castaño-Díez, Daniel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/388540
Acceso en línea:http://hdl.handle.net/10261/388540
https://api.elsevier.com/content/abstract/scopus_id/85201674906
Access Level:acceso abierto
Palabra clave:Contrast transfer function
Cryo electron tomography
Fiducial tracking
Subtomogram averaging
Tilt series alignment
Tomogram reconstruction
id ES_405ec3cccfa48fc95eca557256be4e52
oai_identifier_str oai:digital.csic.es:10261/388540
network_acronym_str ES
network_name_str España
repository_id_str
spelling Automated fiducial-based alignment of cryo-electron tomography tilt series in DynamoCoray, RaffaeleNavarro, PaulaScaramuzza, StefanoStahlberg, HenningCastaño-Díez, DanielContrast transfer functionCryo electron tomographyFiducial trackingSubtomogram averagingTilt series alignmentTomogram reconstructionWith the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities.H.S. acknowledges support by the Swiss National Science Foundation (grants CRSII5_177195 and 310030_188548). D.C.-D. acknowledges support by the Human Frontiers Science Program (HFSP) (grant RGP0017/2020), the Swiss National Science Foundation (grant 205321 179041), and the Spanish Ministry of Science and Innovation (grant PID2021-127309NB-I00 funded by AEI/10.13039/501100011033/FEDER, UE). P.N. acknowledges support from the Swiss National Science Foundation (Starting Grant TMSGI3_218251).Peer reviewedElsevierSwiss National Science FoundationHuman Frontier Science ProgramMinisterio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)European CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/388540https://api.elsevier.com/content/abstract/scopus_id/85201674906reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-127309NB-I00The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.str.2024.07.003https://doi.org/10.1016/j.str.2024.07.003Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3885402026-05-22T06:33:51Z
dc.title.none.fl_str_mv Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
title Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
spellingShingle Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
Coray, Raffaele
Contrast transfer function
Cryo electron tomography
Fiducial tracking
Subtomogram averaging
Tilt series alignment
Tomogram reconstruction
title_short Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
title_full Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
title_fullStr Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
title_full_unstemmed Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
title_sort Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo
dc.creator.none.fl_str_mv Coray, Raffaele
Navarro, Paula
Scaramuzza, Stefano
Stahlberg, Henning
Castaño-Díez, Daniel
author Coray, Raffaele
author_facet Coray, Raffaele
Navarro, Paula
Scaramuzza, Stefano
Stahlberg, Henning
Castaño-Díez, Daniel
author_role author
author2 Navarro, Paula
Scaramuzza, Stefano
Stahlberg, Henning
Castaño-Díez, Daniel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Swiss National Science Foundation
Human Frontier Science Program
Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Contrast transfer function
Cryo electron tomography
Fiducial tracking
Subtomogram averaging
Tilt series alignment
Tomogram reconstruction
topic Contrast transfer function
Cryo electron tomography
Fiducial tracking
Subtomogram averaging
Tilt series alignment
Tomogram reconstruction
description With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities.
publishDate 2024
dc.date.none.fl_str_mv 2024
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/388540
https://api.elsevier.com/content/abstract/scopus_id/85201674906
url http://hdl.handle.net/10261/388540
https://api.elsevier.com/content/abstract/scopus_id/85201674906
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-127309NB-I00
The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.str.2024.07.003
https://doi.org/10.1016/j.str.2024.07.003
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869406745157173248
score 15,81155

Similares en LA Referencia