Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis

In the last decade, cellular forces in three-dimensional hydrogels that mimic the extracellular matrix have been calculated by means of Traction Force Microscopy (TFM). However, characterizing the accuracy limits of a traction recovery method is critical to avoid obscuring physiological information...

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Autores: Barrasa Fano, Jorge, Shapeti, Apeksha, de Jong, J., Ranga, A., Sanz Herrera, José Antonio, Van Oosterwyck, Hans
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/153730
Acceso en línea:https://hdl.handle.net/11441/153730
https://doi.org/10.1016/j.actbio.2021.03.014
Access Level:acceso abierto
Palabra clave:Angiogenesis
Cell mechanics
Computational mechanics
Digital image analysis
Forward and inverse methodologies
Traction force microscopy
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spelling Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesisBarrasa Fano, JorgeShapeti, Apekshade Jong, J.Ranga, A.Sanz Herrera, José AntonioVan Oosterwyck, HansAngiogenesisCell mechanicsComputational mechanicsDigital image analysisForward and inverse methodologiesTraction force microscopyIn the last decade, cellular forces in three-dimensional hydrogels that mimic the extracellular matrix have been calculated by means of Traction Force Microscopy (TFM). However, characterizing the accuracy limits of a traction recovery method is critical to avoid obscuring physiological information due to traction recovery errors. So far, 3D TFM algorithms have only been validated using simplified cell geometries, bypassing image processing steps or arbitrarily simulating focal adhesions. Moreover, it is still uncertain which of the two common traction recovery methods, i.e., forward and inverse, is more robust against the inherent challenges of 3D TFM. In this work, we established an advanced in silico validation framework that is applicable to any 3D TFM experimental setup and that can be used to correctly couple the experimental and computational aspects of 3D TFM. Advancements relate to the simultaneous incorporation of complex cell geometries, simulation of microscopy images of varying bead densities and different focal adhesion sizes and distributions. By measuring the traction recovery error with respect to ground truth solutions, we found that while highest traction recovery errors occur for cases with sparse and small focal adhesions, our implementation of the inverse method improves two-fold the accuracy with respect to the forward method (average error of 23% vs. 50%). This advantage was further supported by recovering cellular tractions around angiogenic sprouts in an in vitro model of angiogenesis. The inverse method recovered higher traction peaks and a clearer pulling pattern at the sprout protrusion tips than the forward method. Statement of significance: Biomaterial performance is often studied by quantifying cell-matrix mechanical interactions by means of Traction Force Microscopy (TFM). However, 3D TFM algorithms are often validated in simplified scenarios, which do not allow to fully assess errors that could obscure physiological information. Here, we established an advanced in silico validation framework that mimics real TFM experimental conditions and that characterizes the expected errors of a 3D TFM workflow. We apply this framework to demonstrate the enhanced accuracy of a novel inverse traction recovery method that is illustrated in the context of an in vitro model of sprouting angiogenesis. Together, our study shows the importance of a proper traction recovery method to minimise errors and the need for an advanced framework to assess those errors. © 2021 Acta Materialia Inc.Ministerio de Educación, Cultura y Deporte CAS17/0 0 096Ministerio de Economía y Competitividad PGC2018-097257-B-C31European Research Council FP7/2007–2013 308223ElsevierMecánica de Medios Continuos y Teoría de EstructurasTEP245: Ingeniería de las EstructurasMinisterio de Educación, Cultura y Deporte (MECD). EspañaMinisterio de Economía y Competitividad (MINECO). EspañaEuropean Research Council (ERC)2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/153730https://doi.org/10.1016/j.actbio.2021.03.014reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésActa Biomaterialia, 126, 326-338.CAS17/0 0 096PGC2018-097257-B-C31https://www.sciencedirect.com/science/article/pii/S1742706121001550info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1537302026-06-17T12:51:07Z
dc.title.none.fl_str_mv Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
title Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
spellingShingle Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
Barrasa Fano, Jorge
Angiogenesis
Cell mechanics
Computational mechanics
Digital image analysis
Forward and inverse methodologies
Traction force microscopy
title_short Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
title_full Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
title_fullStr Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
title_full_unstemmed Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
title_sort Advanced in silico validation framework for three-dimensional Traction Force Microscopy and application to an in vitro model of sprouting angiogenesis
dc.creator.none.fl_str_mv Barrasa Fano, Jorge
Shapeti, Apeksha
de Jong, J.
Ranga, A.
Sanz Herrera, José Antonio
Van Oosterwyck, Hans
author Barrasa Fano, Jorge
author_facet Barrasa Fano, Jorge
Shapeti, Apeksha
de Jong, J.
Ranga, A.
Sanz Herrera, José Antonio
Van Oosterwyck, Hans
author_role author
author2 Shapeti, Apeksha
de Jong, J.
Ranga, A.
Sanz Herrera, José Antonio
Van Oosterwyck, Hans
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Mecánica de Medios Continuos y Teoría de Estructuras
TEP245: Ingeniería de las Estructuras
Ministerio de Educación, Cultura y Deporte (MECD). España
Ministerio de Economía y Competitividad (MINECO). España
European Research Council (ERC)
dc.subject.none.fl_str_mv Angiogenesis
Cell mechanics
Computational mechanics
Digital image analysis
Forward and inverse methodologies
Traction force microscopy
topic Angiogenesis
Cell mechanics
Computational mechanics
Digital image analysis
Forward and inverse methodologies
Traction force microscopy
description In the last decade, cellular forces in three-dimensional hydrogels that mimic the extracellular matrix have been calculated by means of Traction Force Microscopy (TFM). However, characterizing the accuracy limits of a traction recovery method is critical to avoid obscuring physiological information due to traction recovery errors. So far, 3D TFM algorithms have only been validated using simplified cell geometries, bypassing image processing steps or arbitrarily simulating focal adhesions. Moreover, it is still uncertain which of the two common traction recovery methods, i.e., forward and inverse, is more robust against the inherent challenges of 3D TFM. In this work, we established an advanced in silico validation framework that is applicable to any 3D TFM experimental setup and that can be used to correctly couple the experimental and computational aspects of 3D TFM. Advancements relate to the simultaneous incorporation of complex cell geometries, simulation of microscopy images of varying bead densities and different focal adhesion sizes and distributions. By measuring the traction recovery error with respect to ground truth solutions, we found that while highest traction recovery errors occur for cases with sparse and small focal adhesions, our implementation of the inverse method improves two-fold the accuracy with respect to the forward method (average error of 23% vs. 50%). This advantage was further supported by recovering cellular tractions around angiogenic sprouts in an in vitro model of angiogenesis. The inverse method recovered higher traction peaks and a clearer pulling pattern at the sprout protrusion tips than the forward method. Statement of significance: Biomaterial performance is often studied by quantifying cell-matrix mechanical interactions by means of Traction Force Microscopy (TFM). However, 3D TFM algorithms are often validated in simplified scenarios, which do not allow to fully assess errors that could obscure physiological information. Here, we established an advanced in silico validation framework that mimics real TFM experimental conditions and that characterizes the expected errors of a 3D TFM workflow. We apply this framework to demonstrate the enhanced accuracy of a novel inverse traction recovery method that is illustrated in the context of an in vitro model of sprouting angiogenesis. Together, our study shows the importance of a proper traction recovery method to minimise errors and the need for an advanced framework to assess those errors. © 2021 Acta Materialia Inc.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/153730
https://doi.org/10.1016/j.actbio.2021.03.014
url https://hdl.handle.net/11441/153730
https://doi.org/10.1016/j.actbio.2021.03.014
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Acta Biomaterialia, 126, 326-338.
CAS17/0 0 096
PGC2018-097257-B-C31
https://www.sciencedirect.com/science/article/pii/S1742706121001550
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 Elsevier
publisher.none.fl_str_mv Elsevier
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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