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非靶向、高分辨率质谱策略用于同时监测大堡礁绿海龟中的外来化合物和内源性化合物。

Non-targeted, high resolution mass spectrometry strategy for simultaneous monitoring of xenobiotics and endogenous compounds in green sea turtles on the Great Barrier Reef.

机构信息

Queensland Alliance for Environmental Health Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, Brisbane, Australia; The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia.

Agrifood Campus of International Excellence (CeiA3), Department of Chemistry and Physics, University of Almeria, European Union Reference Laboratory for Pesticide Residues in Fruit and Vegetables, Almería, Spain.

出版信息

Sci Total Environ. 2017 Dec 1;599-600:1251-1262. doi: 10.1016/j.scitotenv.2017.05.016. Epub 2017 May 14.

Abstract

Chemical contamination poses a threat to ecosystem, biota and human health, and identifying these hazards is a complex challenge. Traditional hazard identification relies on a priori-defined targets of limited chemical scope, and is generally inappropriate for exploratory studies such as explaining toxicological effects in environmental systems. Here we present a non-target high resolution mass spectrometry environmental monitoring study with multivariate statistical analysis to simultaneously detect biomarkers of exposure (e.g. xenobiotics) and biomarkers of effect in whole turtle blood. Borrowing the concept from clinical chemistry, a case-control sampling approach was used to investigate the potential influence of xenobiotics of anthropogenic origin on free-ranging green sea turtles (Chelonia mydas) from a remote, offshore 'control' site; and two coastal 'case' sites influenced by urban/industrial and agricultural activities, respectively, on the Great Barrier Reef in North Queensland, Australia. Multiple biomarkers of exposure, including sulfonic acids (n=9), a carbamate insecticide metabolite, and other industrial chemicals; and five biomarkers of effect (lipid peroxidation products), were detected in case sites. Additionally, two endogenous biomarkers of neuroinflammation and oxidative stress were identified, and showed moderate-to-strong correlations with clinical measures of inflammation and liver dysfunction. Our data filtering strategy overcomes limitations of traditional a priori selection of target compounds, and adds to the limited environmental xenobiotic metabolomics literature. To our knowledge this is the first case-control study of xenobiotics in marine megafauna, and demonstrates the utility of green sea turtles to link internal and external exposure, to explain potential toxicological effects in environmental systems.

摘要

化学污染对生态系统、生物区系和人类健康构成威胁,识别这些危害是一个复杂的挑战。传统的危害识别依赖于事先定义的、化学范围有限的目标,通常不适合探索性研究,如解释环境系统中的毒理学效应。在这里,我们展示了一项非靶向高分辨率质谱环境监测研究,结合多元统计分析,同时检测暴露标志物(如外源性化学物质)和全龟血中的效应标志物。借鉴临床化学的概念,采用病例对照采样方法,研究人为来源的外源性化学物质对来自偏远近海“对照”点的自由放养绿海龟(Chelonia mydas)的潜在影响;以及受城市/工业和农业活动影响的两个沿海“病例”点,在澳大利亚北昆士兰州大堡礁。在病例点检测到多种暴露标志物,包括磺酸(n=9)、氨基甲酸酯杀虫剂代谢物和其他工业化学品;以及 5 种效应标志物(脂质过氧化产物)。此外,还鉴定出两种内源性神经炎症和氧化应激标志物,它们与炎症和肝功能障碍的临床指标呈中度至强相关性。我们的数据过滤策略克服了传统靶向化合物预先选择的局限性,并补充了有限的环境外源性化学物质代谢组学文献。据我们所知,这是海洋巨型动物中外源性化学物质的首例病例对照研究,证明了绿海龟将内部和外部暴露联系起来,以解释环境系统中潜在毒理学效应的实用性。

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