Analysis of the multiparametric cell cycle data

• Published in: Methods in cell biology Vol. 186; p. 271
• Main Authors: Jacobberger, James W, Sramkoski, R Michael, Stefan, Tammy, Bray, Chris, Bagwell, C Bruce
• Format: Journal Article
• Language: English
• Published: United States 2024
• Subjects: Animals; Cell Cycle; DNA; Flow Cytometry - methods; Humans; Cytometry; Flow cytometry; Probability state modeling; DNA analysis; Mathematical modeling; Cell cycle states; DNA content; Immunofluorescence
• ISSN: 0091-679X
• DOI: 10.1016/bs.mcb.2024.02.021

This chapter was originally written in 2011. The idea was to give some history of cell cycle analysis before and after flow cytometry became widely accessible; provide references to educational material for single parameter DNA content analysis, introduce and discuss multiparameter cell cycle analysis in a methodological style, and in a casual style, discuss aspects of the work over the last 40years that we have given thought, performing some experiments, but didn't publish. It feels like there is a linear progression that moves from counting cells for growth curves, to counting labeled mitotic cells by autoradiography, to DNA content analysis, to cell cycle states defined by immunofluorescence plus DNA content analysis, to extraction of cell cycle expression profiles, and finally to probability state modeling, which should be the "right" way to analyze cytometric cell cycle data. This is the sense of this chapter. In 2023, we have updated it, but the exciting, expansive aspects brought about by spectral and mass cytometry are still young and developing, and thus have not been vetted, reviewed, and presented in mature form.