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Dynamic switching of lateral inhibition spatial patterns

Hes genes are transcriptional repressors activated by Notch. In the developing mouse neural tissue, HES5 expression oscillates in neural progenitors (Manning et al. 2019 Nat. Commun. 10, 1–19 (doi:10.1038/s41467-019-10734-8)) and is spatially organized in small clusters of cells with synchronized ex...

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Autores principales: Hawley, Joshua, Manning, Cerys, Biga, Veronica, Glendinning, Paul, Papalopulu, Nancy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399705/
https://www.ncbi.nlm.nih.gov/pubmed/36000231
http://dx.doi.org/10.1098/rsif.2022.0339
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author Hawley, Joshua
Manning, Cerys
Biga, Veronica
Glendinning, Paul
Papalopulu, Nancy
author_facet Hawley, Joshua
Manning, Cerys
Biga, Veronica
Glendinning, Paul
Papalopulu, Nancy
author_sort Hawley, Joshua
collection PubMed
description Hes genes are transcriptional repressors activated by Notch. In the developing mouse neural tissue, HES5 expression oscillates in neural progenitors (Manning et al. 2019 Nat. Commun. 10, 1–19 (doi:10.1038/s41467-019-10734-8)) and is spatially organized in small clusters of cells with synchronized expression (microclusters). Furthermore, these microclusters are arranged with a spatial periodicity of three–four cells in the dorso-ventral axis and show regular switching between HES5 high/low expression on a longer time scale and larger amplitude than individual temporal oscillators (Biga et al. 2021 Mol. Syst. Biol. 17, e9902 (doi:10.15252/msb.20209902)). However, our initial computational modelling of coupled HES5 could not explain these features of the experimental data. In this study, we provide theoretical results that address these issues with biologically pertinent additions. Here, we report that extending Notch signalling to non-neighbouring progenitor cells is sufficient to generate spatial periodicity of the correct size. In addition, introducing a regular perturbation of Notch signalling by the emerging differentiating cells induces a temporal switching in the spatial pattern, which is longer than an individual cell’s periodicity. Thus, with these two new mechanisms, a computational model delivers outputs that closely resemble the complex tissue-level HES5 dynamics. Finally, we predict that such dynamic patterning spreads out differentiation events in space, complementing our previous findings whereby the local synchronization controls the rate of differentiation.
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spelling pubmed-93997052022-08-24 Dynamic switching of lateral inhibition spatial patterns Hawley, Joshua Manning, Cerys Biga, Veronica Glendinning, Paul Papalopulu, Nancy J R Soc Interface Life Sciences–Mathematics interface Hes genes are transcriptional repressors activated by Notch. In the developing mouse neural tissue, HES5 expression oscillates in neural progenitors (Manning et al. 2019 Nat. Commun. 10, 1–19 (doi:10.1038/s41467-019-10734-8)) and is spatially organized in small clusters of cells with synchronized expression (microclusters). Furthermore, these microclusters are arranged with a spatial periodicity of three–four cells in the dorso-ventral axis and show regular switching between HES5 high/low expression on a longer time scale and larger amplitude than individual temporal oscillators (Biga et al. 2021 Mol. Syst. Biol. 17, e9902 (doi:10.15252/msb.20209902)). However, our initial computational modelling of coupled HES5 could not explain these features of the experimental data. In this study, we provide theoretical results that address these issues with biologically pertinent additions. Here, we report that extending Notch signalling to non-neighbouring progenitor cells is sufficient to generate spatial periodicity of the correct size. In addition, introducing a regular perturbation of Notch signalling by the emerging differentiating cells induces a temporal switching in the spatial pattern, which is longer than an individual cell’s periodicity. Thus, with these two new mechanisms, a computational model delivers outputs that closely resemble the complex tissue-level HES5 dynamics. Finally, we predict that such dynamic patterning spreads out differentiation events in space, complementing our previous findings whereby the local synchronization controls the rate of differentiation. The Royal Society 2022-08-24 /pmc/articles/PMC9399705/ /pubmed/36000231 http://dx.doi.org/10.1098/rsif.2022.0339 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
Hawley, Joshua
Manning, Cerys
Biga, Veronica
Glendinning, Paul
Papalopulu, Nancy
Dynamic switching of lateral inhibition spatial patterns
title Dynamic switching of lateral inhibition spatial patterns
title_full Dynamic switching of lateral inhibition spatial patterns
title_fullStr Dynamic switching of lateral inhibition spatial patterns
title_full_unstemmed Dynamic switching of lateral inhibition spatial patterns
title_short Dynamic switching of lateral inhibition spatial patterns
title_sort dynamic switching of lateral inhibition spatial patterns
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399705/
https://www.ncbi.nlm.nih.gov/pubmed/36000231
http://dx.doi.org/10.1098/rsif.2022.0339
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