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Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures
Mobility quantification of single cells and cellular processes in dense cultures is a challenge, because single cell tracking is impossible. We developed a software for cell structure segmentation and implemented 2 algorithms to measure motility speed. Complex algorithms were tested to separate cell...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423175/ https://www.ncbi.nlm.nih.gov/pubmed/30914941 http://dx.doi.org/10.3389/fninf.2019.00015 |
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author | Henkel, Andreas W. Al-Abdullah, Lulwa A. A. D. Al-Qallaf, Mohammed S. Redzic, Zoran B. |
author_facet | Henkel, Andreas W. Al-Abdullah, Lulwa A. A. D. Al-Qallaf, Mohammed S. Redzic, Zoran B. |
author_sort | Henkel, Andreas W. |
collection | PubMed |
description | Mobility quantification of single cells and cellular processes in dense cultures is a challenge, because single cell tracking is impossible. We developed a software for cell structure segmentation and implemented 2 algorithms to measure motility speed. Complex algorithms were tested to separate cells and cellular components, an important prerequisite for the acquisition of meaningful motility data. Plasma membrane segmentation was performed to measure membrane contraction dynamics and organelle trafficking. The discriminative performance and sensitivity of the algorithms were tested on different cell types and calibrated on computer-simulated cells to obtain absolute values for cellular velocity. Both motility algorithms had advantages in different experimental setups, depending on the complexity of the cellular movement. The correlation algorithm (COPRAMove) performed best under most tested conditions and appeared less sensitive to variable cell densities, brightness and focus changes than the differentiation algorithm (DiffMove). In summary, our software can be used successfully to analyze and quantify cellular and subcellular movements in dense cell cultures. |
format | Online Article Text |
id | pubmed-6423175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64231752019-03-26 Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures Henkel, Andreas W. Al-Abdullah, Lulwa A. A. D. Al-Qallaf, Mohammed S. Redzic, Zoran B. Front Neuroinform Neuroscience Mobility quantification of single cells and cellular processes in dense cultures is a challenge, because single cell tracking is impossible. We developed a software for cell structure segmentation and implemented 2 algorithms to measure motility speed. Complex algorithms were tested to separate cells and cellular components, an important prerequisite for the acquisition of meaningful motility data. Plasma membrane segmentation was performed to measure membrane contraction dynamics and organelle trafficking. The discriminative performance and sensitivity of the algorithms were tested on different cell types and calibrated on computer-simulated cells to obtain absolute values for cellular velocity. Both motility algorithms had advantages in different experimental setups, depending on the complexity of the cellular movement. The correlation algorithm (COPRAMove) performed best under most tested conditions and appeared less sensitive to variable cell densities, brightness and focus changes than the differentiation algorithm (DiffMove). In summary, our software can be used successfully to analyze and quantify cellular and subcellular movements in dense cell cultures. Frontiers Media S.A. 2019-03-12 /pmc/articles/PMC6423175/ /pubmed/30914941 http://dx.doi.org/10.3389/fninf.2019.00015 Text en Copyright © 2019 Henkel, Al-Abdullah, Al-Qallaf and Redzic. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Henkel, Andreas W. Al-Abdullah, Lulwa A. A. D. Al-Qallaf, Mohammed S. Redzic, Zoran B. Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures |
title | Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures |
title_full | Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures |
title_fullStr | Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures |
title_full_unstemmed | Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures |
title_short | Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures |
title_sort | quantitative determination of cellular-and neurite motility speed in dense cell cultures |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423175/ https://www.ncbi.nlm.nih.gov/pubmed/30914941 http://dx.doi.org/10.3389/fninf.2019.00015 |
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