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基于超高分辨质谱的有机卤代物非靶标筛查高精度算法的开发与应用。

Development and Application of a High-Precision Algorithm for Nontarget Identification of Organohalogens Based on Ultrahigh-Resolution Mass Spectrometry.

机构信息

Department of Civil and Environmental Engineering, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan.

Research and Analytical Center for Giant Molecules, Graduate School of Science, Tohoku University, 6-3 Aoba, Aramaki, Aoba-Ku, Sendai 980-8578, Japan.

出版信息

Anal Chem. 2020 Oct 20;92(20):13989-13996. doi: 10.1021/acs.analchem.0c02899. Epub 2020 Sep 30.

Abstract

Brominated and/or chlorinated organic compounds (referred to as organohalogens) are frequently detected in natural and engineered environments. However, ultrahigh-resolution mass spectrometry (UHR-MS)-based nontargeted identification of organohalogens remains challenging because of the coexistence of a vast number of halogenated and nonhalogenated organic molecules. In this study, a new algorithm, namely, the NOMDBP code, was developed to simultaneously identify organohalogens and non-organohalogens from the UHR-MS spectra of natural and engineered waters. In addition to isotopic patterns, for the first time, three optional filter rules [, selection for minimum nonoxygen heteroatoms, inspection of the presence of newly formed halogenated disinfection byproducts (Xn-DBPs), and of their precursors] were incorporated into our code, which can accurately identify DBP-associated peaks and further elucidate Xn-DBP generation and transformation mechanisms. The formula assignment ratio against 2815 previously reported organohalogens, and their 11,583 isotopologues exceeded 97%. Application of our algorithm to disinfected natural organic matter indicated that oxygen-containing Xn-DBP species accounted for a majority of the Xn-DBPs. Furthermore, brominated Xn-DBPs (Br-DBPs) were characterized by a higher degree of unsaturation compared to chlorinated Xn-DBPs. In addition to electrophilic substitution and electrophilic addition reactions, the decomposition/transformation pathway was found to be another important mechanism in Br-DBP formation. The results of this study highlight the superior potential of our code for the efficient detection of yet unknown organohalogens (including organohalogens bearing nonoxygen heteroatoms) in a nontargeted manner and for the identification of their generation mechanism occurring during the disinfection process.

摘要

溴代和/或氯代有机化合物(简称有机卤化物)经常在自然和人工环境中被检测到。然而,由于卤代和非卤代有机分子的大量共存,基于超高效分辨率质谱(UHR-MS)的非靶向有机卤化物识别仍然具有挑战性。在本研究中,开发了一种新的算法,即 NOMDBP 代码,用于从自然和人工水中的 UHR-MS 光谱中同时识别有机卤化物和非有机卤化物。除了同位素模式外,我们的代码首次纳入了三个可选的过滤规则 [最小非氧杂原子选择、新形成的卤代消毒副产物(Xn-DBPs)的存在检查以及它们的前体],这可以准确识别与 DBP 相关的峰,并进一步阐明 Xn-DBP 的生成和转化机制。与之前报道的 2815 种有机卤化物及其 11583 种同位素的公式赋值比例超过 97%。将我们的算法应用于消毒的天然有机物表明,含氧 Xn-DBP 物种占 Xn-DBPs 的大部分。此外,与氯代 Xn-DBPs 相比,溴代 Xn-DBPs(Br-DBPs)具有更高的不饱和程度。除了亲电取代和亲电加成反应外,还发现分解/转化途径是 Br-DBP 形成的另一个重要机制。本研究的结果突出了我们的代码在非靶向方式下高效检测未知有机卤化物(包括含非氧杂原子的有机卤化物)及其在消毒过程中生成机制的卓越潜力。

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