An Inexpensive and Quantitative Approach for Measuring Cytotoxicity
Quantification of cytotoxicity is a common readout for many drug discovery endeavors. Programmed cell death occurs in response to a range of stresses or signals and results from the activation of one or more signaling cascades, including those characteristic of apoptosis, anoikis, necrosis, necroptosis, and autophagic cell death, and the limitations of the various current assays have been recently reviewed. Furthermore, death is generally cell autonomous and results in loss of cell adhesion complicating image-based assays of adherent cells. Detachment from the growth support or neighboring cells is not only a cell death response but also leads to cell death through anoikis; therefore, flow-based methods can overestimate cytotoxicity.
While many assays have been developed to quantify specific aspects of cell death, it has been suggested that to detect the broad spectrum of cell death cascades with high sensitivity, measurements of multiple relatively early indicators should be integrated. Such an approach is generally impractical for high-content screening because of the cost and time associated with multiple often incompatible assays. Most techniques for image-based analysis of the effects of small-molecule compounds use techniques such as immunostaining that are expensive, require extensive optimization, and are incompatible with living cells, or multiple dyes necessitating fixation and multiple processing steps (typically 5–10 steps in commercial kits).
We propose an alternative image-based cytotoxicity assay for adherent cells that integrates measurement of organelle ultrastructural changes and alterations in mitochondrial function associated with programmed cell death. Unlike many cell death assays, this method uses only two dyes that can be added to cells together without a washing step, requires minimal handling or optimization, and is easily analyzed using multivariate methods available in multiple commercial and open-source software packages to enable quantification of single cells. Multivariate image analysis algorithms attempt to integrate as much of the information of each cell that can be extracted. This approach takes a broad variety of measurements (referred to as “features”) from each cell to obtain a “feature-fingerprint.” These are then compared to reference “feature-fingerprints,” and each cell is classified to the closest matching reference dataset. Using these techniques, subcellular localization of proteins, cellular subpopulations, and drug mechanism of action have been correctly classified with often greater than 95% accuracy.
In this study, we describe a simple approach to quantify cytotoxicity in adherent cells based on multivariate analysis of cells stained with the inexpensive dye, nonyl acridine orange (NAO), and a nuclear stain (MVA-NAO). NAO is a lipophilic cationic dye with some preference for binding cardiolipin and has been shown to also be partially sensitive to the mitochondrial membrane potential. We compare MVA-NAO classification with more traditional measures of apoptosis and find that it provides improved classification in screening, quantified as improved Z′ factor (Z′), a standard screening assay metric. Moreover, this dye combination can be used to quantify EC50 values when used in a dose–response format. With an average cost that ranges from $0.1–10 per plate (depending on the nuclear stain), compared to commercial kits that average $50 per plate, this method is particularly well suited for applications involving large numbers of samples, such as high-content screening.
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ASSAY & Drug Development Technologies, published by Mary Ann Liebert, Inc., offers a unique combination of original research and reports on the techniques and tools being used in cutting-edge drug development. GEN presents here one article "A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis."