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 populations...

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Veröffentlicht in:Journal of Visualized Experiments 2017-12 (130)
Hauptverfasser: Gómez-Villafuertes, Rosa, Paniagua-Herranz, Lucía, Gascon, Sergio, de Agustín-Durán, David, Ferreras, María de la O, Gil-Redondo, Juan Carlos, Queipo, María José, Menendez-Mendez, Aida, Pérez-Sen, Ráquel, Delicado, Esmerilda G., Gualix, Javier, Costa, Marcos R., Schroeder, Timm, Miras-Portugal, María Teresa, Ortega, Felipe
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Sprache:eng
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Zusammenfassung: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.
ISSN:1940-087X
1940-087X
DOI:10.3791/56291