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Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen
Traction force microscopy (TFM) is an important family of techniques used to measure and study the role of cellular traction forces (CTFs) associated with many biological processes. However, current standard TFM methods rely on imaging techniques that do not provide the experimental capabilities nec...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854660/ https://www.ncbi.nlm.nih.gov/pubmed/33531512 http://dx.doi.org/10.1038/s41598-021-81470-7 |
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author | Mulligan, Jeffrey A. Ling, Lu Leartprapun, Nichaluk Fischbach, Claudia Adie, Steven G. |
author_facet | Mulligan, Jeffrey A. Ling, Lu Leartprapun, Nichaluk Fischbach, Claudia Adie, Steven G. |
author_sort | Mulligan, Jeffrey A. |
collection | PubMed |
description | Traction force microscopy (TFM) is an important family of techniques used to measure and study the role of cellular traction forces (CTFs) associated with many biological processes. However, current standard TFM methods rely on imaging techniques that do not provide the experimental capabilities necessary to study CTFs within 3D collective and dynamic systems embedded within optically scattering media. Traction force optical coherence microscopy (TF-OCM) was developed to address these needs, but has only been demonstrated for the study of isolated cells embedded within optically clear media. Here, we present computational 4D-OCM methods that enable the study of dynamic invasion behavior of large tumor spheroids embedded in collagen. Our multi-day, time-lapse imaging data provided detailed visualizations of evolving spheroid morphology, collagen degradation, and collagen deformation, all using label-free scattering contrast. These capabilities, which provided insights into how stromal cells affect cancer progression, significantly expand access to critical data about biophysical interactions of cells with their environment, and lay the foundation for future efforts toward volumetric, time-lapse reconstructions of collective CTFs with TF-OCM. |
format | Online Article Text |
id | pubmed-7854660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78546602021-02-03 Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen Mulligan, Jeffrey A. Ling, Lu Leartprapun, Nichaluk Fischbach, Claudia Adie, Steven G. Sci Rep Article Traction force microscopy (TFM) is an important family of techniques used to measure and study the role of cellular traction forces (CTFs) associated with many biological processes. However, current standard TFM methods rely on imaging techniques that do not provide the experimental capabilities necessary to study CTFs within 3D collective and dynamic systems embedded within optically scattering media. Traction force optical coherence microscopy (TF-OCM) was developed to address these needs, but has only been demonstrated for the study of isolated cells embedded within optically clear media. Here, we present computational 4D-OCM methods that enable the study of dynamic invasion behavior of large tumor spheroids embedded in collagen. Our multi-day, time-lapse imaging data provided detailed visualizations of evolving spheroid morphology, collagen degradation, and collagen deformation, all using label-free scattering contrast. These capabilities, which provided insights into how stromal cells affect cancer progression, significantly expand access to critical data about biophysical interactions of cells with their environment, and lay the foundation for future efforts toward volumetric, time-lapse reconstructions of collective CTFs with TF-OCM. Nature Publishing Group UK 2021-02-02 /pmc/articles/PMC7854660/ /pubmed/33531512 http://dx.doi.org/10.1038/s41598-021-81470-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Mulligan, Jeffrey A. Ling, Lu Leartprapun, Nichaluk Fischbach, Claudia Adie, Steven G. Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
title | Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
title_full | Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
title_fullStr | Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
title_full_unstemmed | Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
title_short | Computational 4D-OCM for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
title_sort | computational 4d-ocm for label-free imaging of collective cell invasion and force-mediated deformations in collagen |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854660/ https://www.ncbi.nlm.nih.gov/pubmed/33531512 http://dx.doi.org/10.1038/s41598-021-81470-7 |
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