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Image analysis of neural stem cell division patterns in the zebrafish brain
Proliferating stem cells in the adult body are the source of constant regeneration. In the brain, neural stem cells (NSCs) divide to maintain the stem cell population and generate neural progenitor cells that eventually replenish mature neurons and glial cells. How much spatial coordination of NSC d...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5969287/ https://www.ncbi.nlm.nih.gov/pubmed/29125897 http://dx.doi.org/10.1002/cyto.a.23260 |
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author | Lupperger, Valerio Buggenthin, Felix Chapouton, Prisca Marr, Carsten |
author_facet | Lupperger, Valerio Buggenthin, Felix Chapouton, Prisca Marr, Carsten |
author_sort | Lupperger, Valerio |
collection | PubMed |
description | Proliferating stem cells in the adult body are the source of constant regeneration. In the brain, neural stem cells (NSCs) divide to maintain the stem cell population and generate neural progenitor cells that eventually replenish mature neurons and glial cells. How much spatial coordination of NSC division and differentiation is present in a functional brain is an open question. To quantify the patterns of stem cell divisions, one has to (i) identify the pool of NSCs that have the ability to divide, (ii) determine NSCs that divide within a given time window, and (iii) analyze the degree of spatial coordination. Here, we present a bioimage informatics pipeline that automatically identifies GFP expressing NSCs in three‐dimensional image stacks of zebrafish brain from whole‐mount preparations. We exploit the fact that NSCs in the zebrafish hemispheres are located on a two‐dimensional surface and identify between 1,500 and 2,500 NSCs in six brain hemispheres. We then determine the position of dividing NSCs in the hemisphere by EdU incorporation into cells undergoing S‐phase and calculate all pairwise NSC distances with three alternative metrics. Finally, we fit a probabilistic model to the observed spatial patterns that accounts for the non‐homogeneous distribution of NSCs. We find a weak positive coordination between dividing NSCs irrespective of the metric and conclude that neither strong inhibitory nor strong attractive signals drive NSC divisions in the adult zebrafish brain. © 2017 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC. |
format | Online Article Text |
id | pubmed-5969287 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59692872018-05-30 Image analysis of neural stem cell division patterns in the zebrafish brain Lupperger, Valerio Buggenthin, Felix Chapouton, Prisca Marr, Carsten Cytometry A Original Articles Proliferating stem cells in the adult body are the source of constant regeneration. In the brain, neural stem cells (NSCs) divide to maintain the stem cell population and generate neural progenitor cells that eventually replenish mature neurons and glial cells. How much spatial coordination of NSC division and differentiation is present in a functional brain is an open question. To quantify the patterns of stem cell divisions, one has to (i) identify the pool of NSCs that have the ability to divide, (ii) determine NSCs that divide within a given time window, and (iii) analyze the degree of spatial coordination. Here, we present a bioimage informatics pipeline that automatically identifies GFP expressing NSCs in three‐dimensional image stacks of zebrafish brain from whole‐mount preparations. We exploit the fact that NSCs in the zebrafish hemispheres are located on a two‐dimensional surface and identify between 1,500 and 2,500 NSCs in six brain hemispheres. We then determine the position of dividing NSCs in the hemisphere by EdU incorporation into cells undergoing S‐phase and calculate all pairwise NSC distances with three alternative metrics. Finally, we fit a probabilistic model to the observed spatial patterns that accounts for the non‐homogeneous distribution of NSCs. We find a weak positive coordination between dividing NSCs irrespective of the metric and conclude that neither strong inhibitory nor strong attractive signals drive NSC divisions in the adult zebrafish brain. © 2017 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC. John Wiley and Sons Inc. 2017-11-10 2018-03 /pmc/articles/PMC5969287/ /pubmed/29125897 http://dx.doi.org/10.1002/cyto.a.23260 Text en © 2017 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Lupperger, Valerio Buggenthin, Felix Chapouton, Prisca Marr, Carsten Image analysis of neural stem cell division patterns in the zebrafish brain |
title | Image analysis of neural stem cell division patterns in the zebrafish brain |
title_full | Image analysis of neural stem cell division patterns in the zebrafish brain |
title_fullStr | Image analysis of neural stem cell division patterns in the zebrafish brain |
title_full_unstemmed | Image analysis of neural stem cell division patterns in the zebrafish brain |
title_short | Image analysis of neural stem cell division patterns in the zebrafish brain |
title_sort | image analysis of neural stem cell division patterns in the zebrafish brain |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5969287/ https://www.ncbi.nlm.nih.gov/pubmed/29125897 http://dx.doi.org/10.1002/cyto.a.23260 |
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