High-Throughput Transcriptomics Screen of ToxCast Chemicals in U-2 OS Cells

IF 3.3 3区 医学 Q2 PHARMACOLOGY & PHARMACY
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Abstract

New approach methodologies (NAMs) aim to accelerate the pace of chemical risk assessment while simultaneously reducing cost and dependency on animal studies. High Throughput Transcriptomics (HTTr) is an emerging NAM in the field of chemical hazard evaluation for establishing in vitro points-of-departure and providing mechanistic insight. In the current study, 1201 test chemicals were screened for bioactivity at eight concentrations using a 24-h exposure duration in the human- derived U-2 OS osteosarcoma cell line with HTTr. Assay reproducibility was assessed using three reference chemicals that were screened on every assay plate. The resulting transcriptomics data were analyzed by aggregating signal from genes into signature scores using gene set enrichment analysis, followed by concentration-response modeling of signatures scores. Signature scores were used to predict putative mechanisms of action, and to identify biological pathway altering concentrations (BPACs). BPACs were consistent across replicates for each reference chemical, with replicate BPAC standard deviations as low as 5.6 × 10−3 μM, demonstrating the internal reproducibility of HTTr-derived potency estimates. BPACs of test chemicals showed modest agreement (R2 = 0.55) with existing phenotype altering concentrations from high throughput phenotypic profiling using Cell Painting of the same chemicals in the same cell line. Altogether, this HTTr based chemical screen contributes to an accumulating pool of publicly available transcriptomic data relevant for chemical hazard evaluation and reinforces the utility of cell based molecular profiling methods in estimating chemical potency and predicting mechanism of action across a diverse set of chemicals.

在 U-2 OS 细胞中对 ToxCast 化学品进行高通量转录组学筛选。
新方法(NAM)旨在加快化学风险评估的步伐,同时降低成本和对动物研究的依赖性。高通量转录组学(HTTr)是化学危害评估领域一种新兴的新方法,可用于建立体外出发点并提供机理见解。在目前的研究中,利用 HTTr 在人类衍生的 U-2 OS 骨肉瘤细胞系中以 24 小时的暴露持续时间筛选了 1201 种测试化学品在 8 种浓度下的生物活性。利用基因组富集分析将基因信号聚合成特征得分,然后对特征得分进行浓度-反应建模,从而分析得到的转录组学数据。特征得分用于预测推定的作用机制,并确定改变生物通路的浓度(BPACs)。每种参比化学物在不同重复中的 BPACs 都是一致的,重复 BPAC 标准偏差低至 5.6 × 10-3 μM,这表明 HTTr 衍生的药效估计值具有内部可重复性。测试化学品的 BPAC 与在同一细胞系中使用细胞绘制相同化学品的高通量表型图谱得出的现有表型改变浓度显示出适度的一致性(R2 = 0.55)。总之,基于 HTTr 的化学筛选有助于积累与化学危害评估相关的公开可用转录组数据,并加强了基于细胞的分子剖析方法在估算化学药效和预测不同化学品作用机制方面的实用性。
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来源期刊
CiteScore
6.80
自引率
2.60%
发文量
309
审稿时长
32 days
期刊介绍: Toxicology and Applied Pharmacology publishes original scientific research of relevance to animals or humans pertaining to the action of chemicals, drugs, or chemically-defined natural products. Regular articles address mechanistic approaches to physiological, pharmacologic, biochemical, cellular, or molecular understanding of toxicologic/pathologic lesions and to methods used to describe these responses. Safety Science articles address outstanding state-of-the-art preclinical and human translational characterization of drug and chemical safety employing cutting-edge science. Highly significant Regulatory Safety Science articles will also be considered in this category. Papers concerned with alternatives to the use of experimental animals are encouraged. Short articles report on high impact studies of broad interest to readers of TAAP that would benefit from rapid publication. These articles should contain no more than a combined total of four figures and tables. Authors should include in their cover letter the justification for consideration of their manuscript as a short article.
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