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Development and application of a metabolomic tool to assess exposure of an estuarine amphipod to pollutants in the environment

机译:一种代谢组工具的开发和应用,评估雌卤氨碱两亲对环境中污染物的暴露

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摘要

Identifying major adverse effects on aquatic organisms in environmental samples is still challenging, and metabolomic approaches have been utilized as non-target screening techniques in the context of ecotoxicology. While existing methods have focused on statistical tests or univariate analysis, there is the need to further explore a multivariate analytical method that captures synergetic effects and associations among metabolites and toxicants. Here we show a new tool for screening sediment toxicity in the environment. First, we constructed predictive models using the metabolomic profiles and the result of exposure tests, to discriminate the toxic effects of target substances. The developed models were then applied to sediment samples collected from an actual urban area that contain chromium, nickel, copper, zinc, cadmium, fluoranthene, nicotine, and osmotic stress, incorporated with exposure tests of the benthic amphipod Grandidierella japonica. As a result, the fitted models showed high predictive power (Q~2 > 0.71) and could detect toxicants from mixed chemical samples across a wide range of concentrations in test datasets. The application of the constructed models to river sediment and road dust samples indicated that almost all target substances were less toxic compared with the effects at LC50 levels. Only zinc showed slight increasing trends among samples, suggesting that the proposed method can be used for prioritization of toxicants. The present work made a direct connection between chemical exposures and metabolomic responses, and draws attention to the need for further studies on interactive mechanisms of metabolites in toxicological assessments.
机译:鉴定对环境样本中水生生物的主要不良反应仍然是挑战性,并且代谢组方法已被用作生态毒理学背景下的非目标筛选技术。虽然现有方法侧重于统计检验或单变量分析,但需要进一步探索多变量分析方法,捕获代谢物和毒物之间的协同效应和关联。在这里,我们展示了一种用于筛选环境中沉积物的新工具。首先,我们使用代谢物简谱构建预测模型和曝光试验的结果,以区分靶物质的毒性作用。然后将开发的模型应用于从含有铬,镍,铜,锌,镉,氟,尼古丁和渗透胁迫的实际城市地区收集的沉积物样本,并入含有Benthic Amphipod Grandidierella japonica的暴露试验。结果,拟合模型显示出高的预测性(Q〜2> 0.71),并且可以在测试数据集中的各种浓度范围内检测来自混合化学样品的毒物。构造模型在河流沉积物和道路粉尘样品中的应用表明,与LC50水平的效果相比,几乎所有靶物质都含量较小。只有锌在样品中显示出轻微的趋势,表明所提出的方法可用于毒物的优先排序。本作者在化学曝光和代谢物反应之间直接连接,并提请注意进一步研究毒理学评估中代谢产物的交互机制。

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