Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
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 population...
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ri-123456789-246712021-07-09T20:38:07Z Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations 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 Neuroscience Live imaging single cell tracking lineage progression adult neural stem cell neural cells lineage tree timelapse video-microscopy 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. 2018-01-25T20:30:14Z 2018-01-25T20:30:14Z 2017-12-16 article https://repositorio.ufrn.br/jspui/handle/123456789/24671 10.3791/56291 Keywords: Neuroscience, Issue eng Acesso Aberto application/pdf |
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eng |
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Neuroscience Live imaging single cell tracking lineage progression adult neural stem cell neural cells lineage tree timelapse video-microscopy |
| spellingShingle |
Neuroscience Live imaging single cell tracking lineage progression adult neural stem cell neural cells lineage tree timelapse video-microscopy 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 Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations |
| 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. |
| format |
article |
| author |
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_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_sort |
Gómez-Villafuertes, Rosa |
| title |
Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations |
| 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 |
| publishDate |
2018 |
| url |
https://repositorio.ufrn.br/jspui/handle/123456789/24671 |
| work_keys_str_mv |
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