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

Quantifying cytostatic and cytotoxic outcomes are integral components of characterizing perturbagens used as research tools and in drug discovery pipe-lines. 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.