Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.

Morphogen gradients are crucial for the development of organisms. The biochemical properties of many morphogens prevent their extracellular free diffusion, indicating the need of an active mechanism for transport. The involvement of filopodial structures (cytonemes) has been proposed for morphogen s...

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Autores principales:	Adrián Aguirre-Tamaral, Isabel Guerrero
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/d8a805b42db14a43aa83ada29e2c2443
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spelling	oai:doaj.org-article:d8a805b42db14a43aa83ada29e2c24432021-12-02T19:58:08ZImproving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.1553-734X1553-735810.1371/journal.pcbi.1009245https://doaj.org/article/d8a805b42db14a43aa83ada29e2c24432021-08-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009245https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Morphogen gradients are crucial for the development of organisms. The biochemical properties of many morphogens prevent their extracellular free diffusion, indicating the need of an active mechanism for transport. The involvement of filopodial structures (cytonemes) has been proposed for morphogen signaling. Here, we describe an in silico model based on the main general features of cytoneme-meditated gradient formation and its implementation into Cytomorph, an open software tool. We have tested the spatial and temporal adaptability of our model quantifying Hedgehog (Hh) gradient formation in two Drosophila tissues. Cytomorph is able to reproduce the gradient and explain the different scaling between the two epithelia. After experimental validation, we studied the predicted impact of a range of features such as length, size, density, dynamics and contact behavior of cytonemes on Hh morphogen distribution. Our results illustrate Cytomorph as an adaptive tool to test different morphogen gradients and to generate hypotheses that are difficult to study experimentally.Adrián Aguirre-TamaralIsabel GuerreroPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 8, p e1009245 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Adrián Aguirre-Tamaral Isabel Guerrero Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
description	Morphogen gradients are crucial for the development of organisms. The biochemical properties of many morphogens prevent their extracellular free diffusion, indicating the need of an active mechanism for transport. The involvement of filopodial structures (cytonemes) has been proposed for morphogen signaling. Here, we describe an in silico model based on the main general features of cytoneme-meditated gradient formation and its implementation into Cytomorph, an open software tool. We have tested the spatial and temporal adaptability of our model quantifying Hedgehog (Hh) gradient formation in two Drosophila tissues. Cytomorph is able to reproduce the gradient and explain the different scaling between the two epithelia. After experimental validation, we studied the predicted impact of a range of features such as length, size, density, dynamics and contact behavior of cytonemes on Hh morphogen distribution. Our results illustrate Cytomorph as an adaptive tool to test different morphogen gradients and to generate hypotheses that are difficult to study experimentally.
format	article
author	Adrián Aguirre-Tamaral Isabel Guerrero
author_facet	Adrián Aguirre-Tamaral Isabel Guerrero
author_sort	Adrián Aguirre-Tamaral
title	Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
title_short	Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
title_full	Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
title_fullStr	Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
title_full_unstemmed	Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
title_sort	improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/d8a805b42db14a43aa83ada29e2c2443
work_keys_str_mv	AT adrianaguirretamaral improvingtheunderstandingofcytonememediatedmorphogengradientsbyinsilicomodeling AT isabelguerrero improvingtheunderstandingofcytonememediatedmorphogengradientsbyinsilicomodeling
_version_	1718375809178140672

Improving the understanding of cytoneme-mediated morphogen gradients by in silico modeling.

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