Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.

During the last decade, a consensus has emerged that the stochastic triggering of an excitable system drives pseudopod formation and subsequent migration of amoeboid cells. The presence of chemoattractant stimuli alters the threshold for triggering this activity and can bias the direction of migrati...

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Autores principales:	Debojyoti Biswas, Peter N Devreotes, Pablo A Iglesias
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b0514cdcea0a4b858d11cf6895b42937
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spelling	oai:doaj.org-article:b0514cdcea0a4b858d11cf6895b429372021-12-02T19:57:33ZThree-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.1553-734X1553-735810.1371/journal.pcbi.1008803https://doaj.org/article/b0514cdcea0a4b858d11cf6895b429372021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1008803https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358During the last decade, a consensus has emerged that the stochastic triggering of an excitable system drives pseudopod formation and subsequent migration of amoeboid cells. The presence of chemoattractant stimuli alters the threshold for triggering this activity and can bias the direction of migration. Though noise plays an important role in these behaviors, mathematical models have typically ignored its origin and merely introduced it as an external signal into a series of reaction-diffusion equations. Here we consider a more realistic description based on a reaction-diffusion master equation formalism to implement these networks. In this scheme, noise arises naturally from a stochastic description of the various reaction and diffusion terms. Working on a three-dimensional geometry in which separate compartments are divided into a tetrahedral mesh, we implement a modular description of the system, consisting of G-protein coupled receptor signaling (GPCR), a local excitation-global inhibition mechanism (LEGI), and signal transduction excitable network (STEN). Our models implement detailed biochemical descriptions whenever this information is available, such as in the GPCR and G-protein interactions. In contrast, where the biochemical entities are less certain, such as the LEGI mechanism, we consider various possible schemes and highlight the differences between them. Our simulations show that even when the LEGI mechanism displays perfect adaptation in terms of the mean level of proteins, the variance shows a dose-dependence. This differs between the various models considered, suggesting a possible means for determining experimentally among the various potential networks. Overall, our simulations recreate temporal and spatial patterns observed experimentally in both wild-type and perturbed cells, providing further evidence for the excitable system paradigm. Moreover, because of the overall importance and ubiquity of the modules we consider, including GPCR signaling and adaptation, our results will be of interest beyond the field of directed migration.Debojyoti BiswasPeter N DevreotesPablo A IglesiasPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1008803 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Debojyoti Biswas Peter N Devreotes Pablo A Iglesias Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
description	During the last decade, a consensus has emerged that the stochastic triggering of an excitable system drives pseudopod formation and subsequent migration of amoeboid cells. The presence of chemoattractant stimuli alters the threshold for triggering this activity and can bias the direction of migration. Though noise plays an important role in these behaviors, mathematical models have typically ignored its origin and merely introduced it as an external signal into a series of reaction-diffusion equations. Here we consider a more realistic description based on a reaction-diffusion master equation formalism to implement these networks. In this scheme, noise arises naturally from a stochastic description of the various reaction and diffusion terms. Working on a three-dimensional geometry in which separate compartments are divided into a tetrahedral mesh, we implement a modular description of the system, consisting of G-protein coupled receptor signaling (GPCR), a local excitation-global inhibition mechanism (LEGI), and signal transduction excitable network (STEN). Our models implement detailed biochemical descriptions whenever this information is available, such as in the GPCR and G-protein interactions. In contrast, where the biochemical entities are less certain, such as the LEGI mechanism, we consider various possible schemes and highlight the differences between them. Our simulations show that even when the LEGI mechanism displays perfect adaptation in terms of the mean level of proteins, the variance shows a dose-dependence. This differs between the various models considered, suggesting a possible means for determining experimentally among the various potential networks. Overall, our simulations recreate temporal and spatial patterns observed experimentally in both wild-type and perturbed cells, providing further evidence for the excitable system paradigm. Moreover, because of the overall importance and ubiquity of the modules we consider, including GPCR signaling and adaptation, our results will be of interest beyond the field of directed migration.
format	article
author	Debojyoti Biswas Peter N Devreotes Pablo A Iglesias
author_facet	Debojyoti Biswas Peter N Devreotes Pablo A Iglesias
author_sort	Debojyoti Biswas
title	Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
title_short	Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
title_full	Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
title_fullStr	Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
title_full_unstemmed	Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
title_sort	three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/b0514cdcea0a4b858d11cf6895b42937
work_keys_str_mv	AT debojyotibiswas threedimensionalstochasticsimulationofchemoattractantmediatedexcitabilityincells AT peterndevreotes threedimensionalstochasticsimulationofchemoattractantmediatedexcitabilityincells AT pabloaiglesias threedimensionalstochasticsimulationofchemoattractantmediatedexcitabilityincells
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Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells.

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