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将高分辨率质谱数据与暴露和毒性预测相联系,以推进高通量环境监测。

Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring.

机构信息

Oak Ridge Institute for Science and Education (ORISE) Participant, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States.

U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States.

出版信息

Environ Int. 2016 Mar;88:269-280. doi: 10.1016/j.envint.2015.12.008. Epub 2016 Jan 23.

Abstract

There is a growing need in the field of exposure science for monitoring methods that rapidly screen environmental media for suspect contaminants. Measurement and analysis platforms, based on high resolution mass spectrometry (HRMS), now exist to meet this need. Here we describe results of a study that links HRMS data with exposure predictions from the U.S. EPA's ExpoCast™ program and in vitro bioassay data from the U.S. interagency Tox21 consortium. Vacuum dust samples were collected from 56 households across the U.S. as part of the American Healthy Homes Survey (AHHS). Sample extracts were analyzed using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS) with electrospray ionization. On average, approximately 2000 molecular features were identified per sample (based on accurate mass) in negative ion mode, and 3000 in positive ion mode. Exact mass, isotope distribution, and isotope spacing were used to match molecular features with a unique listing of chemical formulas extracted from EPA's Distributed Structure-Searchable Toxicity (DSSTox) database. A total of 978 DSSTox formulas were consistent with the dust LC-TOF/molecular feature data (match score≥90); these formulas mapped to 3228 possible chemicals in the database. Correct assignment of a unique chemical to a given formula required additional validation steps. Each suspect chemical was prioritized for follow-up confirmation using abundance and detection frequency results, along with exposure and bioactivity estimates from ExpoCast and Tox21, respectively. Chemicals with elevated exposure and/or toxicity potential were further examined using a mixture of 100 chemical standards. A total of 33 chemicals were confirmed present in the dust samples by formula and retention time match; nearly half of these do not appear to have been associated with house dust in the published literature. Chemical matches found in at least 10 of the 56 dust samples include Piperine, N,N-Diethyl-m-toluamide (DEET), Triclocarban, Diethyl phthalate (DEP), Propylparaben, Methylparaben, Tris(1,3-dichloro-2-propyl)phosphate (TDCPP), and Nicotine. This study demonstrates a novel suspect screening methodology to prioritize chemicals of interest for subsequent targeted analysis. The methods described here rely on strategic integration of available public resources and should be considered in future non-targeted and suspect screening assessments of environmental and biological media.

摘要

目前,暴露科学领域越来越需要能够快速筛选环境介质中可疑污染物的监测方法。基于高分辨率质谱(HRMS)的测量和分析平台已经可以满足这一需求。在这里,我们描述了一项研究的结果,该研究将 HRMS 数据与美国环保署的 ExpoCast™ 计划的暴露预测以及美国跨机构 Tox21 联盟的体外生物测定数据联系起来。作为美国健康家园调查(AHHS)的一部分,从美国各地的 56 户家庭中收集了真空灰尘样本。使用液相色谱飞行时间质谱(LC-TOF/MS)和电喷雾电离对样品提取物进行分析。平均而言,每个样本(基于精确质量)在负离子模式下可识别约 2000 个分子特征,在正离子模式下可识别 3000 个分子特征。精确质量、同位素分布和同位素间距用于将分子特征与从美国环保署的分布式结构可搜索毒性(DSSTox)数据库中提取的独特化学公式列表进行匹配。共有 978 个 DSSTox 公式与灰尘 LC-TOF/分子特征数据一致(匹配分数≥90);这些公式映射到数据库中 3228 种可能的化学品。将唯一的化学物质分配给给定的公式需要进行额外的验证步骤。根据 ExpoCast 和 Tox21 的丰度和检测频率结果以及暴露和生物活性估计,对每个可疑化学物质进行了后续确认的优先级排序。具有较高暴露和/或毒性潜力的化学品进一步使用 100 种化学标准混合物进行检查。通过公式和保留时间匹配共确认 33 种化学物质存在于灰尘样本中;其中近一半似乎没有在已发表的文献中与房屋灰尘有关。在至少 56 个灰尘样本中的 10 个样本中发现的化学物质匹配包括胡椒碱、N,N-二乙基间甲苯酰胺(DEET)、三氯生、邻苯二甲酸二乙酯(DEP)、丙酸丙酯、对羟基苯甲酸甲酯、磷酸三(1,3-二氯-2-丙基)酯(TDCPP)和尼古丁。本研究展示了一种新颖的可疑筛选方法,可优先考虑随后进行靶向分析的感兴趣的化学物质。这里描述的方法依赖于现有公共资源的战略整合,应在未来对环境和生物介质进行非靶向和可疑筛选评估中加以考虑。

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