Waldmann Tanja, Grinberg Marianna, König André, Rempel Eugen, Schildknecht Stefan, Henry Margit, Holzer Anna-Katharina, Dreser Nadine, Shinde Vaibhav, Sachinidis Agapios, Rahnenführer Jörg, Hengstler Jan G, Leist Marcel
In Vitro Toxicology and Biomedicine, Department inaugurated by the Doerenkamp-Zbinden Chair Foundation, University of Konstanz , 78457 Konstanz, Germany.
Department of Statistics, Technical University of Dortmund , D-44221 Dortmund, Germany.
Chem Res Toxicol. 2017 Apr 17;30(4):905-922. doi: 10.1021/acs.chemrestox.6b00259. Epub 2016 Dec 21.
Analysis of transcriptome changes has become an established method to characterize the reaction of cells to toxicants. Such experiments are mostly performed at compound concentrations close to the cytotoxicity threshold. At present, little information is available on concentration-dependent features of transcriptome changes, in particular, at the transition from noncytotoxic concentrations to conditions that are associated with cell death. Thus, it is unclear in how far cell death confounds the results of transcriptome studies. To explore this gap of knowledge, we treated pluripotent stem cells differentiating to human neuroepithelial cells (UKN1 assay) for short periods (48 h) with increasing concentrations of valproic acid (VPA) and methyl mercury (MeHg), two compounds with vastly different modes of action. We developed various visualization tools to describe cellular responses, and the overall response was classified as "tolerance" (minor transcriptome changes), "functional adaptation" (moderate/strong transcriptome responses, but no cytotoxicity), and "degeneration". The latter two conditions were compared, using various statistical approaches. We identified (i) genes regulated at cytotoxic, but not at noncytotoxic, concentrations and (ii) KEGG pathways, gene ontology term groups, and superordinate biological processes that were only regulated at cytotoxic concentrations. The consensus markers and processes found after 48 h treatment were then overlaid with those found after prolonged (6 days) treatment. The study highlights the importance of careful concentration selection and of controlling viability for transcriptome studies. Moreover, it allowed identification of 39 candidate "biomarkers of cytotoxicity". These could serve to provide alerts that data sets of interest may have been affected by cell death in the model system studied.
转录组变化分析已成为表征细胞对毒物反应的既定方法。此类实验大多在接近细胞毒性阈值的化合物浓度下进行。目前，关于转录组变化的浓度依赖性特征，尤其是从无细胞毒性浓度过渡到与细胞死亡相关的条件下的相关信息很少。因此，尚不清楚细胞死亡在多大程度上混淆了转录组研究的结果。为了填补这一知识空白，我们用浓度递增的丙戊酸（VPA）和甲基汞（MeHg）对分化为人神经上皮细胞的多能干细胞进行了短期（48小时）处理（UKN1试验），这两种化合物的作用模式截然不同。我们开发了各种可视化工具来描述细胞反应，并将总体反应分类为“耐受”（微小转录组变化）、“功能适应”（中度/强烈转录组反应，但无细胞毒性）和“退化”。使用各种统计方法对后两种情况进行了比较。我们确定了（i）在细胞毒性浓度而非无细胞毒性浓度下受调控的基因，以及（ii）仅在细胞毒性浓度下受调控的KEGG通路、基因本体术语组和上位生物学过程。然后将48小时处理后发现的共识标志物和过程与长期（6天）处理后发现的进行叠加。该研究强调了在转录组研究中仔细选择浓度和控制细胞活力的重要性。此外，它还鉴定出39种候选“细胞毒性生物标志物”。这些标志物可用于发出警报，表明在所研究的模型系统中，感兴趣的数据集可能已受到细胞死亡的影响。
