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A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis
In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Company of Biologists Ltd
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5576075/ https://www.ncbi.nlm.nih.gov/pubmed/28652318 http://dx.doi.org/10.1242/bio.025148 |
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author | Uriu, Koichiro Bhavna, Rajasekaran Oates, Andrew C. Morelli, Luis G. |
author_facet | Uriu, Koichiro Bhavna, Rajasekaran Oates, Andrew C. Morelli, Luis G. |
author_sort | Uriu, Koichiro |
collection | PubMed |
description | In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease. |
format | Online Article Text |
id | pubmed-5576075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Company of Biologists Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-55760752017-09-11 A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis Uriu, Koichiro Bhavna, Rajasekaran Oates, Andrew C. Morelli, Luis G. Biol Open Methods & Techniques In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease. The Company of Biologists Ltd 2017-06-29 /pmc/articles/PMC5576075/ /pubmed/28652318 http://dx.doi.org/10.1242/bio.025148 Text en © 2017. Published by The Company of Biologists Ltd http://creativecommons.org/licenses/by/3.0This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Methods & Techniques Uriu, Koichiro Bhavna, Rajasekaran Oates, Andrew C. Morelli, Luis G. A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
title | A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
title_full | A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
title_fullStr | A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
title_full_unstemmed | A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
title_short | A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
title_sort | framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis |
topic | Methods & Techniques |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5576075/ https://www.ncbi.nlm.nih.gov/pubmed/28652318 http://dx.doi.org/10.1242/bio.025148 |
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