five

A Simple High-Content Cell Cycle Assay Reveals Frequent Discrepancies between Cell Number and ATP and MTS Proliferation Assays

收藏
NIAID Data Ecosystem2026-03-07 收录
下载链接:
https://figshare.com/articles/dataset/_A_Simple_High_Content_Cell_Cycle_Assay_Reveals_Frequent_Discrepancies_between_Cell_Number_and_ATP_and_MTS_Proliferation_Assays_/704625
下载链接
链接失效反馈
官方服务:
资源简介:
In order to efficiently characterize both antiproliferative potency and mechanism of action of small molecules targeting the cell cycle, we developed a high-throughput image-based assay to determine cell number and cell cycle phase distribution. Using this we profiled the effects of experimental and approved anti-cancer agents with a range mechanisms of action on a set of cell lines, comparing direct cell counting versus two metabolism-based cell viability/proliferation assay formats, ATP-dependent bioluminescence, MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) reduction, and a whole-well DNA-binding dye fluorescence assay. We show that, depending on compound mechanisms of action, the metabolism-based proxy assays are frequently prone to 1) significant underestimation of compound potency and efficacy, and 2) non-monotonic dose-response curves due to concentration-dependent phenotypic ‘switching’. In particular, potency and efficacy of DNA synthesis-targeting agents such as gemcitabine and etoposide could be profoundly underestimated by ATP and MTS-reduction assays. In the same image-based assay we showed that drug-induced increases in ATP content were associated with increased cell size and proportionate increases in mitochondrial content and respiratory flux concomitant with cell cycle arrest. Therefore, differences in compound mechanism of action and cell line-specific responses can yield significantly misleading results when using ATP or tetrazolium-reduction assays as a proxy for cell number when screening compounds for antiproliferative activity or profiling panels of cell lines for drug sensitivity.
创建时间:
2016-01-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作