Multiparametric Cell Cycle Analysis Using the Operetta High-Content Imager and Harmony Software with PhenoLOGIC.
Multiparametric Cell Cycle Analysis Using the Operetta High-Content Imager and Harmony Software with PhenoLOGIC.
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DOI：
10.1371/journal.pone.0134306
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Massey AJ
中科院分区：
文献类型：
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作者：
Massey AJ
高含量成像是在单细胞水平上确定细胞表型的有力工具。表征小分子对细胞周期分布的影响，对于理解它们的作用机制，特别是在肿瘤学药物发现中，也对于理解潜在的毒理学责任，是很重要的。在这里，高通量的表型分析利用PerkinElmer opetta高内容成像仪和Harmony软件来确定细胞周期分布。使用Harmony软件中的机器学习算法PhenoLOGIC来稳健地分离单个细胞和细胞团。DNA含量、EDU掺入和PHH3(S10)表达水平随后被用来将细胞划分为细胞周期的不同阶段。该检测方法可与额外的药效学标记物多重作用，以评估特定细胞亚群内的细胞周期变化。用该方法测定了γ损伤剂处理后细胞周期分布的变化。同样，该方法可以与Ki67多重检测静止期细胞的比例，并与BrdU双标记法检测S期持续时间。因此，这种方法为小分子作用机制和药物毒性研究提供了一种相对廉价、快速和高通量的表型方法，用于确定准确的细胞周期分布。
High-content imaging is a powerful tool for determining cell phenotypes at the single cell level. Characterising the effect of small molecules on cell cycle distribution is important for understanding their mechanism of action especially in oncology drug discovery but also for understanding potential toxicology liabilities. Here, a high-throughput phenotypic assay utilising the PerkinElmer Operetta high-content imager and Harmony software to determine cell cycle distribution is described. PhenoLOGIC, a machine learning algorithm within Harmony software was employed to robustly separate single cells from cell clumps. DNA content, EdU incorporation and pHH3 (S10) expression levels were subsequently utilised to separate cells into the various phases of the cell cycle. The assay is amenable to multiplexing with an additional pharmacodynamic marker to assess cell cycle changes within a specific cellular sub-population. Using this approach, the cell cycle distribution of γH2AX positive nuclei was determined following treatment with DNA damaging agents. Likewise, the assay can be multiplexed with Ki67 to determine the fraction of quiescent cells and with BrdU dual labelling to determine S-phase duration. This methodology therefore provides a relatively cheap, quick and high-throughput phenotypic method for determining accurate cell cycle distribution for small molecule mechanism of action and drug toxicity studies.