Image-Enabled Cell Sorting Using the BD CellView Technology
Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
This chapter is an extension of the original publication by Schraivogel et al. (Science 375:315–320, 2022) which described, for the first time, image-enabled and high-speed cell sorting based on the BD CellView technology. It summarizes the technical aspects of the instrument in an easy-to-digest form and provides example-based guidance toward implementation of the CellView-based image cell sorting technology. As an example, it explains how to use the image-enabled cell sorter to analyze the chemically induced fragmentation of the Golgi apparatus in HeLa cells—an experiment that was alluded to in the original publication but was not included in the manuscript due to space constraints. The chemically induced Golgi fragmentation sort illustrates an elegant example of the utility of image-enabled cell sorting as a significant expansion of the single-cell toolbox. It is such a striking phenotype when analyzed with image cytometry but undetectable when using conventional flow cytometry. Described in a straightforward and concise manner, this experiment serves as a standard system assurance for image-based cell sorters.
Original language | English |
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Title of host publication | Flow Cytometry Protocols |
Editors | Teresa S. Hawley, Robert G. Hawley |
Number of pages | 14 |
Publisher | Humana Press |
Publication date | 2024 |
Edition | 5 |
Pages | 145-158 |
Chapter | 8 |
ISBN (Print) | 978-1-0716-3737-1 |
ISBN (Electronic) | 978-1-0716-3738-8 |
DOIs | |
Publication status | Published - 2024 |
Series | Methods in Molecular Biology |
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Volume | 2779 |
ISSN | 1064-3745 |
Bibliographical note
Publisher Copyright:
© The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2024.
- Chemically induced Golgi fragmentation, Flow cytometry, High-speed cell sorting, Image-enabled cell sorting, On the fly image analysis parameters
Research areas
ID: 388585370