Department of Chemistry, Université de Sherbrooke , Sherbrooke, Quebec J1K 2R1, Canada.
Groupe de Recherche en Pharmacologie Animal du Québec (GREPAQ), Department of Veterinary Biomedicine, Université de Montréal , Saint-Hyacinthe, Quebec J2S 2M2, Canada.
Anal Chem. 2017 Sep 19;89(18):9805-9813. doi: 10.1021/acs.analchem.7b01761. Epub 2017 Sep 1.
Correct identification of a chemical substance in environmental samples based only on accurate mass measurements can be difficult especially for molecules >300 Da. Here is presented the application of spectral accuracy, a tool for the comparison of isotope patterns toward molecular formula generation, as a complementary technique to assist in the identification process of organic micropollutants and their transformation products in surface water. A set of nine common contaminants (five antibiotics, an herbicide, a beta-blocker, an antidepressant, and an antineoplastic) frequently found in surface water were spiked in methanol and surface water extracts at two different concentrations (80 and 300 μg L). They were then injected into three different mass analyzers (triple quadrupole, quadrupole-time-of-fight, and quadrupole-orbitrap) to study the impact of matrix composition, analyte concentration, and mass resolution on the correct identification of molecular formulas using spectral accuracy. High spectral accuracy and ranking of the correct molecular formula were in many cases compound-specific due principally to conditions affecting signal intensity such as matrix effects and concentration. However, in general, results showed that higher concentrations and higher resolutions favored ranking the correct formula in the top 10. Using spectral accuracy and mass accuracy it was possible to reduce the number of possible molecular formulas for organic compounds of relative high molecular mass (e.g., between 400 and 900 Da) to less than 10 and in some cases, it was possible to unambiguously assign one specific molecular formula to an experimental isotopic pattern. This study confirmed that spectral accuracy can be used as a complementary diagnostic technique to improve confidence levels for the identification of organic contaminants under environmental conditions.
仅基于准确质量测量正确识别环境样品中的化学物质可能具有挑战性,尤其是对于 >300 Da 的分子。本文介绍了光谱精度(一种用于生成分子公式的同位素模式比较的工具)的应用,作为一种辅助技术,可用于识别地表水有机污染物及其转化产物。一组在地表水经常发现的九种常见污染物(五种抗生素、一种除草剂、一种β受体阻滞剂、一种抗抑郁药和一种抗肿瘤药)在甲醇和地表水提取物中以两种不同浓度(80 和 300 μg/L)进行了添加。然后将它们注入三种不同的质量分析仪(三重四极杆、四极杆飞行时间和四极杆轨道阱)中,以研究基质组成、分析物浓度和质量分辨率对使用光谱精度正确识别分子公式的影响。在许多情况下,由于影响信号强度的条件,如基质效应和浓度,高光谱精度和正确分子公式的排名主要是特定于化合物的。然而,一般来说,结果表明,较高的浓度和较高的分辨率有利于将正确的公式排在前 10 位。使用光谱精度和质量精度,可以将相对高分子质量(例如 400 至 900 Da 之间)的有机化合物的可能分子公式数量减少到不到 10 个,并且在某些情况下,可以将一个特定的分子公式明确分配给实验同位素模式。这项研究证实,光谱精度可以用作补充诊断技术,以提高在环境条件下识别有机污染物的置信水平。