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Identification of transcriptome signatures and biomarkers specific for potential developmental toxicants inhibiting human neural crest cell migration

机译:鉴定潜在抑制人类神经rest细胞迁移的潜在发育毒物的转录组特征和生物标记

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The in vitro test battery of the European research consortium ESNATS ('novel stem cell-based test systems') has been used to screen for potential human developmental toxicants. As part of this effort, the migration of neural crest (MINC) assay has been used to evaluate chemical effects on neural crest function. It identified some drug-like compounds in addition to known environmental toxicants. The hits included the HSP90 inhibitor geldanamycin, the chemotherapeutic arsenic trioxide, the flame-retardant PBDE-99, the pesticide triadimefon and the histone deacetylase inhibitors valproic acid and trichostatin A. Transcriptome changes triggered by these substances in human neural crest cells were recorded and analysed here to answer three questions: (1) can toxicants be individually identified based on their transcript profile; (2) how can the toxicity pattern reflected by transcript changes be compacted/dimensionality-reduced for practical regulatory use; (3) how can a reduced set of biomarkers be selected for large-scale follow-up? Transcript profiling allowed clear separation of different toxicants and the identification of toxicant types in a blinded test study. We also developed a diagrammatic system to visualize and compare toxicity patterns of a group of chemicals by giving a quantitative overview of altered superordinate biological processes (e.g. activation of KEGG pathways or overrepresentation of gene ontology terms). The transcript data were mined for potential markers of toxicity, and 39 transcripts were selected to either indicate general developmental toxicity or distinguish compounds with different modes-of-action in read-across. In summary, we found inclusion of transcriptome data to largely increase the information from the MINC phenotypic test.
机译:欧洲研究协会ESNATS的体外测试电池(“基于新型干细胞的测试系统”)已用于筛选潜在的人类发育毒物。作为这项工作的一部分,神经rest(MINC)分析的迁移已用于评估对神经c功能的化学作用。除已知的环境毒物外,它还鉴定了一些药物样化合物。命中包括HSP90抑制剂格尔德霉素,化学治疗性三氧化二砷,阻燃剂PBDE-99,农药三唑酮和组蛋白脱乙酰酶抑制剂丙戊酸和曲古抑菌素A。记录并分析了这些物质在人的神经rest细胞中触发的转录组变化。在这里回答三个问题:(1)是否可以根据其转录本来单独鉴定毒物; (2)如何将转录本变化所反映的毒性模式压实/降低尺寸,以用于实际监管用途; (3)如何选择减少的生物标志物集进行大规模随访?抄本分析可以清楚地分离出不同的毒物,并在盲法研究中鉴定出毒物类型。我们还开发了一个图解系统,以通过定量概述改变的上级生物学过程(例如KEGG途径的激活或基因本体论术语的过多代表)来可视化和比较一组化学品的毒性模式。挖掘成绩单数据以寻找潜在的毒性标记,并选择39个成绩单以表明一般的发育毒性或区分具有不同作用方式的化合物。总而言之,我们发现包含转录组数据可大大增加MINC表型测试的信息。

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