Department of Agrobiotechnology, IFA-Tulln, Institute of Bioanalytics and Agro-Metabolomics, University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad-Lorenz-Str. 20, 3430, Tulln, Austria.
FFoQSI - Austrian Competence Centre for Feed and Food Quality, Safety & Innovation, FFoQSI GmbH, Technopark 1C, 3430, Tulln, Austria.
Anal Bioanal Chem. 2020 Apr;412(11):2607-2620. doi: 10.1007/s00216-020-02489-9. Epub 2020 Feb 20.
This paper describes the validation of an LC-MS/MS-based method for the quantification of > 500 secondary microbial metabolites. Analytical performance parameters have been determined for seven food matrices using seven individual samples per matrix for spiking. Apparent recoveries ranged from 70 to 120% for 53-83% of all investigated analytes (depending on the matrix). This number increased to 84-94% if the recovery of extraction was considered. The comparison of the fraction of analytes for which the precision criterion of RSD ≤ 20% under repeatability conditions (for 7 replicates derived from different individual samples) and intermediate precision conditions (for 7 technical replicates from one sample), respectively, was met (85-97% vs. 93-94%) highlights the contribution of relative matrix effects to the method uncertainty. Statistical testing of apparent recoveries between pairs of matrices exhibited a significant difference for more than half of the analytes, while recoveries of the extraction showed a much better agreement. Apparent recoveries and matrix effects were found to be constant over 2-3 orders of magnitude of analyte concentrations in figs and maize, whereas the LOQs differed less than by a factor of 2 for 90% of the investigated compounds. Based on these findings, this paper discusses the applicability and practicability of current guidelines for multi-analyte method validation. Investigation of (apparent) recoveries near the LOQ seems to be insufficiently relevant to justify the enormous time-effort for manual inspection of the peaks of hundreds of analytes. Instead, more emphasis should be put on the investigation of relative matrix effects in the validation procedure. Graphical abstract.
本文描述了一种基于 LC-MS/MS 的方法,用于定量分析 > 500 种次级微生物代谢产物。通过对每种基质的 7 个独立样本进行加标,确定了 7 种基质的分析性能参数。对于 53-83%的所有研究分析物(取决于基质),表观回收率在 70-120%之间。如果考虑提取回收率,这一数字增加到 84-94%。对在重复性条件下(7 个源自不同个体样本的重复)和中间精密度条件下(7 个来自一个样本的技术重复)满足精密度标准 RSD≤20%的分析物分数进行比较(85-97%与 93-94%),突出了相对基质效应对方法不确定性的贡献。对成对基质之间的表观回收率进行统计学检验,发现超过一半的分析物存在显著差异,而提取回收率的一致性要好得多。在 fig 和玉米中,分析物浓度的 2-3 个数量级范围内,表观回收率和基质效应被发现是恒定的,而 90%的研究化合物的 LOQs 相差不到 2 倍。基于这些发现,本文讨论了当前多分析物方法验证指南的适用性和实用性。在接近 LOQ 时研究(表观)回收率似乎与手动检查数百种分析物的峰的巨大时间和精力投入不够相关。相反,应更加强调在验证过程中研究相对基质效应。