Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations

Detalhes bibliográficos
Autor(a) principal: Gómez-Villafuertes, Rosa
Data de Publicação: 2017
Outros Autores: Paniagua-Herranz, Lucía, Gascon, Sergio, Agustín-Durán, David de, Ferreras, María de la O, Gil-Redondo, Juan Carlos, Queipo, María José, Menendez-Mendez, Aida, Pérez-Sen, Ráquel, G. Delicado, Esmerilda, Gualix, Javier, Costa, Marcos Romualdo, Schroeder, Timm, Miras-Portugal, María Teresa, Ortega, Felipe
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRN
Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/24671
Resumo: Understanding the mechanisms that control critical biological events of neural cell populations, such as proliferation, differentiation, or cell fate decisions, will be crucial to design therapeutic strategies for many diseases affecting the nervous system. Current methods to track cell populations rely on their final outcomes in still images and they generally fail to provide sufficient temporal resolution to identify behavioral features in single cells. Moreover, variations in cell death, behavioral heterogeneity within a cell population, dilution, spreading, or the low efficiency of the markers used to analyze cells are all important handicaps that will lead to incomplete or incorrect read-outs of the results. Conversely, performing live imaging and single cell tracking under appropriate conditions represents a powerful tool to monitor each of these events. Here, a time-lapse video-microscopy protocol, followed by post-processing, is described to track neural populations with single cell resolution, employing specific software. The methods described enable researchers to address essential questions regarding the cell biology and lineage progression of distinct neural populations.
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spelling Gómez-Villafuertes, RosaPaniagua-Herranz, LucíaGascon, SergioAgustín-Durán, David deFerreras, María de la OGil-Redondo, Juan CarlosQueipo, María JoséMenendez-Mendez, AidaPérez-Sen, RáquelG. Delicado, EsmerildaGualix, JavierCosta, Marcos RomualdoSchroeder, TimmMiras-Portugal, María TeresaOrtega, Felipe2018-01-25T20:30:14Z2018-01-25T20:30:14Z2017-12-16https://repositorio.ufrn.br/jspui/handle/123456789/2467110.3791/56291 Keywords: Neuroscience, IssueengNeuroscienceLive imagingsingle cell trackinglineage progressionadult neural stem cellneural cellslineage treetimelapse video-microscopyLive Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populationsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleUnderstanding the mechanisms that control critical biological events of neural cell populations, such as proliferation, differentiation, or cell fate decisions, will be crucial to design therapeutic strategies for many diseases affecting the nervous system. Current methods to track cell populations rely on their final outcomes in still images and they generally fail to provide sufficient temporal resolution to identify behavioral features in single cells. Moreover, variations in cell death, behavioral heterogeneity within a cell population, dilution, spreading, or the low efficiency of the markers used to analyze cells are all important handicaps that will lead to incomplete or incorrect read-outs of the results. Conversely, performing live imaging and single cell tracking under appropriate conditions represents a powerful tool to monitor each of these events. Here, a time-lapse video-microscopy protocol, followed by post-processing, is described to track neural populations with single cell resolution, employing specific software. 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dc.title.pt_BR.fl_str_mv Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
title Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
spellingShingle Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
Gómez-Villafuertes, Rosa
Neuroscience
Live imaging
single cell tracking
lineage progression
adult neural stem cell
neural cells
lineage tree
timelapse video-microscopy
title_short Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
title_full Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
title_fullStr Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
title_full_unstemmed Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
title_sort Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
author Gómez-Villafuertes, Rosa
author_facet Gómez-Villafuertes, Rosa
Paniagua-Herranz, Lucía
Gascon, Sergio
Agustín-Durán, David de
Ferreras, María de la O
Gil-Redondo, Juan Carlos
Queipo, María José
Menendez-Mendez, Aida
Pérez-Sen, Ráquel
G. Delicado, Esmerilda
Gualix, Javier
Costa, Marcos Romualdo
Schroeder, Timm
Miras-Portugal, María Teresa
Ortega, Felipe
author_role author
author2 Paniagua-Herranz, Lucía
Gascon, Sergio
Agustín-Durán, David de
Ferreras, María de la O
Gil-Redondo, Juan Carlos
Queipo, María José
Menendez-Mendez, Aida
Pérez-Sen, Ráquel
G. Delicado, Esmerilda
Gualix, Javier
Costa, Marcos Romualdo
Schroeder, Timm
Miras-Portugal, María Teresa
Ortega, Felipe
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Gómez-Villafuertes, Rosa
Paniagua-Herranz, Lucía
Gascon, Sergio
Agustín-Durán, David de
Ferreras, María de la O
Gil-Redondo, Juan Carlos
Queipo, María José
Menendez-Mendez, Aida
Pérez-Sen, Ráquel
G. Delicado, Esmerilda
Gualix, Javier
Costa, Marcos Romualdo
Schroeder, Timm
Miras-Portugal, María Teresa
Ortega, Felipe
dc.subject.por.fl_str_mv Neuroscience
Live imaging
single cell tracking
lineage progression
adult neural stem cell
neural cells
lineage tree
timelapse video-microscopy
topic Neuroscience
Live imaging
single cell tracking
lineage progression
adult neural stem cell
neural cells
lineage tree
timelapse video-microscopy
description Understanding the mechanisms that control critical biological events of neural cell populations, such as proliferation, differentiation, or cell fate decisions, will be crucial to design therapeutic strategies for many diseases affecting the nervous system. Current methods to track cell populations rely on their final outcomes in still images and they generally fail to provide sufficient temporal resolution to identify behavioral features in single cells. Moreover, variations in cell death, behavioral heterogeneity within a cell population, dilution, spreading, or the low efficiency of the markers used to analyze cells are all important handicaps that will lead to incomplete or incorrect read-outs of the results. Conversely, performing live imaging and single cell tracking under appropriate conditions represents a powerful tool to monitor each of these events. Here, a time-lapse video-microscopy protocol, followed by post-processing, is described to track neural populations with single cell resolution, employing specific software. The methods described enable researchers to address essential questions regarding the cell biology and lineage progression of distinct neural populations.
publishDate 2017
dc.date.issued.fl_str_mv 2017-12-16
dc.date.accessioned.fl_str_mv 2018-01-25T20:30:14Z
dc.date.available.fl_str_mv 2018-01-25T20:30:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv https://repositorio.ufrn.br/jspui/handle/123456789/24671
dc.identifier.doi.none.fl_str_mv 10.3791/56291 Keywords: Neuroscience, Issue
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identifier_str_mv 10.3791/56291 Keywords: Neuroscience, Issue
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