Single-Cell and Population-Level Analyses Using Real-Time Kinetic Labeling Couples Proliferation and Cell Death Mechanisms.

Dev Cell

Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1130, New York, NY 10029, USA; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; Graduate School of Biomedical Sciences, Icah

Published: October 2019


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Article Abstract

Quantifying cytostatic and cytotoxic outcomes are integral components of characterizing perturbagens used as research tools and in drug discovery pipelines. Furthermore, data-rich acquisition, coupled with robust methods for analysis, is required to properly assess the function and impact of these perturbagens. Here, we present a detailed and versatile method for single-cell and population-level analyses using real-time kinetic labeling (SPARKL). SPARKL integrates high-content live-cell imaging with automated detection and analysis of fluorescent reporters of cell death. We outline several examples of zero-handling, non-disruptive protocols for detailing cell death mechanisms and proliferation profiles. Additionally, we suggest several methods for mathematically analyzing these data to best utilize the collected kinetic data. Compared to traditional methods of detection and analysis, SPARKL is more sensitive, accurate, and high throughput while substantially eliminating sample processing and providing richer data.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810872PMC
http://dx.doi.org/10.1016/j.devcel.2019.08.016DOI Listing

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