Yu Miao, Liu Jiyan, Wang Thanh, Zhang Aiqian, Wang Yawei, Zhou Qunfang, Jiang Guibin
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Talanta. 2016 May 15;152:9-14. doi: 10.1016/j.talanta.2016.01.047. Epub 2016 Jan 25.
It is hard to quantify the trace pollutants in the environment without the corresponding reference standards. Structure identifications of unknown organic pollutants are thus of great importance in environmental analysis. As for polybrominated diphenyl ethers (PBDE) with one substituent of methoxyl group, there are 837 congeners, but only 32 standards are commercially available. In this work, an effective method based on gas chromatography coupled with mass spectrometry (GC-MS) was proposed to predict the potential structures of methoxylated polybrominated diphenyl ethers (MeO-PBDEs). The mass fragmentation pattern using SIM mode not only provided the useful information on the substitution position of methoxyl group, the number of Br atoms, but also guaranteed the high sensitivity for trace analysis. Br distribution patterns of the unknown MeO-PBDEs were revealed by a linear regression model with dummy variables which described the retention time relationship between MeO-PBDEs and the corresponding PBDEs on different types of GC columns. This method was successfully used to identify three new MeO-PBDEs metabolites of BDE-28 as 4-MeO-BDE-22, 4'-MeO-BDE-25 and 4-MeO-BDE-31 in the pumpkins. Therefore, the newly developed structure prediction model based on GC-MS behavior is helpful in the evaluation of unknown PBDE metabolites in the environment.
没有相应的参考标准,就很难对环境中的痕量污染物进行量化。因此,未知有机污染物的结构鉴定在环境分析中具有重要意义。至于带有一个甲氧基取代基的多溴二苯醚(PBDE),有837种同系物,但只有32种标准品可商购。在这项工作中,提出了一种基于气相色谱-质谱联用(GC-MS)的有效方法来预测甲氧基化多溴二苯醚(MeO-PBDEs)的潜在结构。采用选择离子监测(SIM)模式的质谱碎裂模式不仅提供了有关甲氧基取代位置、溴原子数目的有用信息,还保证了痕量分析的高灵敏度。通过带有虚拟变量的线性回归模型揭示了未知MeO-PBDEs的溴分布模式,该模型描述了MeO-PBDEs与相应PBDEs在不同类型气相色谱柱上的保留时间关系。该方法成功地用于鉴定南瓜中BDE-28的三种新的MeO-PBDEs代谢物,即4-MeO-BDE-22、4'-MeO-BDE-25和4-MeO-BDE-31。因此,新开发的基于GC-MS行为的结构预测模型有助于评估环境中未知的PBDE代谢物。