关键词: Metabolomics cardiomyocytes dosing neurons pesticides threshold analysis

来  源:   DOI:10.1093/toxsci/kfae101

Abstract:
While classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of sub-cytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. The data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate sub-cytotoxic metabolomic responses at doses of 0.1 µM and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics (EDm) of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays.
摘要:
虽然经典的分子生物学测定法可以提供细胞对化学挑战的反应的量度,它们依靠单一的生物学现象来推断更广泛的细胞代谢反应。这些方法并不总是提供必要的灵敏度来回答亚细胞毒性作用的问题。它们也不适用于所有细胞类型。同样,精品测定法,如心肌细胞搏动率可以间接测量细胞代谢反应,但他们也一样,仅限于测量特定的生物学现象,并且通常仅限于单个细胞类型。由于这些原因,毒理学研究人员需要新的方法来确定不同细胞类型中各种剂量的代谢变化,特别是在低剂量的情况下。本文收集的数据表明,基于LC-MS/MS的非靶向代谢组学具有特征不可知的数据视图,结合一套统计方法,包括适应性环境阈值分析,提供了一个多才多艺的,健壮,和整体方法直接监测整体细胞代谢组学对农药的反应。当使用这种方法研究两种不同的细胞类型时,人类心肌细胞和神经元,这种方法揭示了在0.1µM和1µM的毒死蜱和西维因剂量下单独的亚细胞毒性代谢组学反应.这些发现表明,这种非靶向代谢组学的不可知方法可以为通过代谢组学(EDM)确定化学挑战的有效剂量提供新工具。比如杀虫剂,在代谢组学反应的直接测量中,该反应不是细胞类型特异性的或使用传统测定法可观察到的。
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