Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.

Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automat...

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Autores principales:	Daniel Schindler, Ted Moldenhawer, Maike Stange, Valentino Lepro, Carsten Beta, Matthias Holschneider, Wilhelm Huisinga
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/1cf0a1b778c3431d86da42407979ca62
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spelling	oai:doaj.org-article:1cf0a1b778c3431d86da42407979ca622021-12-02T19:58:02ZAnalysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.1553-734X1553-735810.1371/journal.pcbi.1009268https://doaj.org/article/1cf0a1b778c3431d86da42407979ca622021-08-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009268https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.Daniel SchindlerTed MoldenhawerMaike StangeValentino LeproCarsten BetaMatthias HolschneiderWilhelm HuisingaPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 8, p e1009268 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Daniel Schindler Ted Moldenhawer Maike Stange Valentino Lepro Carsten Beta Matthias Holschneider Wilhelm Huisinga Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
description	Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.
format	article
author	Daniel Schindler Ted Moldenhawer Maike Stange Valentino Lepro Carsten Beta Matthias Holschneider Wilhelm Huisinga
author_facet	Daniel Schindler Ted Moldenhawer Maike Stange Valentino Lepro Carsten Beta Matthias Holschneider Wilhelm Huisinga
author_sort	Daniel Schindler
title	Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
title_short	Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
title_full	Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
title_fullStr	Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
title_full_unstemmed	Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
title_sort	analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/1cf0a1b778c3431d86da42407979ca62
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Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.

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