Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria.
Fakultät für Chemie, Institut für Biophysikalische Chemie, Universität Wien, Wien 1090, Austria.
Anal Chem. 2023 Jul 18;95(28):10686-10694. doi: 10.1021/acs.analchem.3c01393. Epub 2023 Jul 6.
Polyphenols, prevalent in plants and fungi, are investigated intensively in nutritional and clinical settings because of their beneficial bioactive properties. Due to their complexity, analysis with untargeted approaches is favorable, which typically use high-resolution mass spectrometry (HRMS) rather than low-resolution mass spectrometry (LRMS). Here, the advantages of HRMS were evaluated by thoroughly testing untargeted techniques and available online resources. By applying data-dependent acquisition on real-life urine samples, 27 features were annotated with spectral libraries, 88 with fragmentation, and 113 by MS matching with PhytoHub, an online database containing >2000 polyphenols. Moreover, other exogenous and endogenous molecules were screened to measure chemical exposure and potential metabolic effects using the Exposome-Explorer database, further annotating 144 features. Additional polyphenol-related features were explored using various non-targeted analysis techniques including MassQL for glucuronide and sulfate neutral losses, and MetaboAnalyst for statistical analysis. As HRMS typically suffers a sensitivity loss compared to state-of-the-art LRMS used in targeted workflows, the gap between the two instrumental approaches was quantified in three spiked human matrices (urine, serum, plasma) as well as real-life urine samples. Both instruments showed feasible sensitivity, with median limits of detection in the spiked samples being 10-18 ng/mL for HRMS and 4.8-5.8 ng/mL for LRMS. The results demonstrate that, despite its intrinsic limitations, HRMS can readily be used for comprehensively investigating human polyphenol exposure. In the future, this work is expected to allow for linking human health effects with exposure patterns and toxicological mixture effects with other xenobiotics.
多酚广泛存在于植物和真菌中,由于其具有有益的生物活性特性,在营养和临床环境中受到了深入研究。由于其复杂性,采用非靶向方法进行分析是有利的,通常使用高分辨率质谱(HRMS)而不是低分辨率质谱(LRMS)。在这里,通过彻底测试非靶向技术和可用的在线资源,评估了 HRMS 的优势。通过在真实尿液样本上应用数据依赖型采集,使用光谱库注释了 27 个特征,使用碎片注释了 88 个特征,使用 PhytoHub(一个包含 >2000 种多酚的在线数据库)进行 MS 匹配注释了 113 个特征。此外,还使用 Exposome-Explorer 数据库筛选了其他外源性和内源性分子,以测量化学暴露和潜在的代谢效应,进一步注释了 144 个特征。使用各种非靶向分析技术(包括用于葡萄糖醛酸和硫酸盐中性损失的 MassQL 以及用于统计分析的 MetaboAnalyst)探索了其他多酚相关特征。由于 HRMS 与靶向工作流程中使用的最先进的 LRMS 相比通常会出现灵敏度损失,因此在三种加标人基质(尿液、血清、血浆)以及真实尿液样本中定量了两种仪器方法之间的差距。两种仪器都显示出可行的灵敏度,在加标样本中 HRMS 的中位检测限为 10-18 ng/mL,LRMS 的检测限为 4.8-5.8 ng/mL。结果表明,尽管 HRMS 存在内在局限性,但它可以很容易地用于全面研究人体多酚暴露情况。在未来,这项工作有望将人体健康效应与暴露模式联系起来,并将毒理学混合物效应与其他外源性化学物质联系起来。