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...

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Authors: Coray, R, Navarro González, Paula, Scaramuzza, S, Stahlberg, H, Castaño Díez, D
Format: article
Status:Published version
Publication Date:2024
Country:España
Institution:Universidad de Sevilla (US)
Repository:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:dnet:idus________::e31be23307d2d1c60c8c96ca382488f3
Online Access:https://hdl.handle.net/11441/186032
https://doi.org/10.1016/j.str.2024.07.003
Access Level:Open access
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spelling Automated fiducial-based alignment of cryo-electron tomography tilt series in DynamoCoray, RNavarro González, PaulaScaramuzza, SStahlberg, HCastaño Díez, DWith 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.Cell PressArquitectura y Tecnología de ComputadoresTEP123: Metalurgia e Ingeniería de los MaterialesMinisterio de Ciencia e Innovación (MICIN). España2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/186032https://doi.org/10.1016/j.str.2024.07.003reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésStructure, 32 (10), 1808 p.. PID2021-127309NB-I00https://www.cell.com/structure/fulltext/S0969-2126(24)00241-7?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0969212624002417%3Fshowall%3Dtrueinfo:eu-repo/semantics/openAccessoai:dnet:idus________::e31be23307d2d1c60c8c96ca382488f32026-06-17T12:51:07Z
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, R
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, R
Navarro González, Paula
Scaramuzza, S
Stahlberg, H
Castaño Díez, D
author Coray, R
author_facet Coray, R
Navarro González, Paula
Scaramuzza, S
Stahlberg, H
Castaño Díez, D
author_role author
author2 Navarro González, Paula
Scaramuzza, S
Stahlberg, H
Castaño Díez, D
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Arquitectura y Tecnología de Computadores
TEP123: Metalurgia e Ingeniería de los Materiales
Ministerio de Ciencia e Innovación (MICIN). España
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
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/186032
https://doi.org/10.1016/j.str.2024.07.003
url https://hdl.handle.net/11441/186032
https://doi.org/10.1016/j.str.2024.07.003
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Structure, 32 (10), 1808 p..
PID2021-127309NB-I00
https://www.cell.com/structure/fulltext/S0969-2126(24)00241-7?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0969212624002417%3Fshowall%3Dtrue
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cell Press
publisher.none.fl_str_mv Cell Press
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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