Reference compounds for characterizing cellular injury in high-content cellular morphology assays

This data accompanies the manuscript "Reference compounds for characterizing cellular injury in high-content cellular morphology assays". <br> Abstract: Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. We generated cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds causing cellular damage produced bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this <em>Resource</em> will help with assay optimization and compound prioritization in complex cellular assays like cell painting. <br> This dataset is composed of four parts: (1) List of extracted features from cell painting experiments. (2) Processed live-cell imaging data. (3) Processed intracellular glutathione data. (4) ALARM NMR and UPLC-MS data for KAT inhibitors.

本数据集配套发表手稿《用于表征高内涵细胞形态学分析中细胞损伤的参考化合物（Reference compounds for characterizing cellular injury in high-content cellular morphology assays）》。
摘要：在复杂细胞分析中高效识别具有不良作用机制的化合物，仍缺乏稳健且可推广的研究方案。此类方案可用于高通量筛选阶段的命中化合物优先级排序，最终助力药物开发过程中的预测毒理学研究。我们以浓度反应分析形式，为U-2 OS细胞中的218种典型细胞毒性与干扰性化合物构建了细胞绘画（cell painting）及细胞健康谱。多种引发细胞损伤的化合物可呈现具有生物活性的细胞绘画形态特征，涵盖细胞骨架毒素、遗传毒素（genotoxins）、非特异性亲电试剂及氧化还原活性化合物。此外，我们证实，质量欠佳的赖氨酸乙酰转移酶（lysine acetyltransferase）抑制剂与非特异性亲电试剂，可与选择性更优的同类化合物区分开来。我们认为，如本资源（Resource）中所表征的这类细胞毒性与干扰性参考化合物，若被有目的地纳入分析体系，将有助于复杂细胞分析（如细胞绘画实验）中的分析优化与化合物优先级排序。
本数据集由四部分构成：(1) 细胞绘画实验提取的特征列表；(2) 处理后的活细胞成像数据；(3) 处理后的细胞内谷胱甘肽数据；(4) 针对赖氨酸乙酰转移酶抑制剂的ALARM NMR（ALARM NMR）与UPLC-MS（UPLC-MS）数据。