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Quantitative label-free single cell tracking in 3D biomimetic matrices

Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cel...

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Autores principales: Sapudom, Jiranuwat, Waschke, Johannes, Franke, Katja, Hlawitschka, Mario, Pompe, Tilo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658366/
https://www.ncbi.nlm.nih.gov/pubmed/29075007
http://dx.doi.org/10.1038/s41598-017-14458-x
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author Sapudom, Jiranuwat
Waschke, Johannes
Franke, Katja
Hlawitschka, Mario
Pompe, Tilo
author_facet Sapudom, Jiranuwat
Waschke, Johannes
Franke, Katja
Hlawitschka, Mario
Pompe, Tilo
author_sort Sapudom, Jiranuwat
collection PubMed
description Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cell-cell and cell-matrix interactions for many biomedical questions of physiological and pathological processes. However, current live cell imaging and analysis techniques are frequently limited by non-physiological 2D settings. Furthermore, they often rely on cell labelling by fluorescent dyes or expression of fluorescent proteins to enhance contrast of cells, which frequently affects cell viability and behavior of cells. In this work, we present a quantitative, label-free 3D single cell tracking technique using standard bright-field microscopy and affordable computational resources for data analysis. We demonstrate the efficacy of the automated method by studying migratory behavior of a large number of primary human macrophages over long time periods of several days in a biomimetic 3D microenvironment. The new technology provides a highly affordable platform for long-term studies of single cell behavior in 3D settings with minimal cell manipulation and can be implemented for various studies regarding cell-matrix interactions, cell-cell interactions as well as drug screening platform for primary and heterogeneous cell populations.
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spelling pubmed-56583662017-10-31 Quantitative label-free single cell tracking in 3D biomimetic matrices Sapudom, Jiranuwat Waschke, Johannes Franke, Katja Hlawitschka, Mario Pompe, Tilo Sci Rep Article Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cell-cell and cell-matrix interactions for many biomedical questions of physiological and pathological processes. However, current live cell imaging and analysis techniques are frequently limited by non-physiological 2D settings. Furthermore, they often rely on cell labelling by fluorescent dyes or expression of fluorescent proteins to enhance contrast of cells, which frequently affects cell viability and behavior of cells. In this work, we present a quantitative, label-free 3D single cell tracking technique using standard bright-field microscopy and affordable computational resources for data analysis. We demonstrate the efficacy of the automated method by studying migratory behavior of a large number of primary human macrophages over long time periods of several days in a biomimetic 3D microenvironment. The new technology provides a highly affordable platform for long-term studies of single cell behavior in 3D settings with minimal cell manipulation and can be implemented for various studies regarding cell-matrix interactions, cell-cell interactions as well as drug screening platform for primary and heterogeneous cell populations. Nature Publishing Group UK 2017-10-26 /pmc/articles/PMC5658366/ /pubmed/29075007 http://dx.doi.org/10.1038/s41598-017-14458-x Text en © The Author(s) 2017 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Sapudom, Jiranuwat
Waschke, Johannes
Franke, Katja
Hlawitschka, Mario
Pompe, Tilo
Quantitative label-free single cell tracking in 3D biomimetic matrices
title Quantitative label-free single cell tracking in 3D biomimetic matrices
title_full Quantitative label-free single cell tracking in 3D biomimetic matrices
title_fullStr Quantitative label-free single cell tracking in 3D biomimetic matrices
title_full_unstemmed Quantitative label-free single cell tracking in 3D biomimetic matrices
title_short Quantitative label-free single cell tracking in 3D biomimetic matrices
title_sort quantitative label-free single cell tracking in 3d biomimetic matrices
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658366/
https://www.ncbi.nlm.nih.gov/pubmed/29075007
http://dx.doi.org/10.1038/s41598-017-14458-x
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