Technical Center of Dalian Customs, Dalian 116000, China.
School of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China.
Anal Methods. 2022 Jan 20;14(3):233-240. doi: 10.1039/d1ay01576a.
The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The -plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise -test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 μg kg and 0.3-2.1 μg kg in bovine and piscine muscle matrices, respectively.
基于代谢组学的分析策略在非靶向筛选污染物方面表现出优势，特别是在食品安全领域的未知和意外（U&U）污染物方面，但数据分析通常是该策略的瓶颈。在这项研究中，开发了一种基于超高效液相色谱-串联质谱（UHPLC-MS/MS）结果的新型基于代谢组学的分析方法，用于准确、快速和全面地非靶向筛选 34 种作为 U&U 污染物添加到牛和鱼肉基质中的药物和个人护理产品（PPCPs）。设计了三个浓度组（20、50 和 100ng mL），有意模拟对照组和实验组，以发现标记化合物，其中采用了多元和单变量分析。在多元分析中，每个浓度组在 PCA 和 OPLS-DA 图中与其他两个组完全分离，为区分组间标记化合物奠定了基础。OPLS-DA 中的 -plot、置换和投影变量重要性（VIP）用于筛选和鉴定标记化合物，然后通过单变量分析中的两两 -test 和倍数变化判断进一步验证。结果表明，两种肌肉基质中添加的 34 种 PPCPs 均被鉴定为标记化合物，证明了这种新型基于代谢组学的非靶向筛选方法的有效性和实用性，特别是在食品安全控制领域面对大量的 PPCPs 和各种动物基质时。此外，34 种 PPCPs 在牛和鱼肉基质中的检出限（LOD）分别计算为 0.2-2.6μg kg 和 0.3-2.1μg kg。
