Development of a multi-mycotoxin LC-MS/MS method for the determination of biomarkers in pig urine

开发用于测定猪尿中多种霉菌毒素生物标志物的 LC-MS/MS 方法

阅读:12
作者:Agnieszka Tkaczyk, Piotr Jedziniak

Abstract

An LC-MS/MS method has been developed for the sensitive and selective determination of 35 mycotoxins (biomarkers of exposure) in pig urine samples. Sample preparation includes creatinine adjustment (with the developed LC-UV method) with enzymatic hydrolysis of pig urine samples followed by liquid-liquid (LLE) extraction. The LLE protocol, as well as enzymatic hydrolysis for indirect mycotoxin glucuronides determination, was optimized in this study. Additionally, two other sample preparation protocols were compared with the developed LLE method: immunoaffinity columns and solid-phase extraction cartridges (Oasis HLB). The detection and quantification of the biomarkers were performed using triple quadrupole mass spectrometry.The method was validated with regard to the guidelines specified by the EMEA (European Medicines Agency). The extraction recoveries were higher than 60% for 77% of the analytes studied, with the intra- and inter-day relative standard deviation being lower than 20% for most of the compounds at four different concentration levels. The limits of quantification ranged from 0.1 ng/mL for zearalenone and sterigmatocystin to 8 ng/mL for nivalenol. To the best knowledge of the authors, the matrix effect was evaluated for the first time in this study for six different urine samples, and the coefficient of variation was found to be lower than 15% for most analytes studied. Finally, the developed method was applied to analyse 56 pig urine samples. Deoxynivalenol (1-20 ng/mL), zearalenone (0.1-1.5 ng/mL) and ochratoxin A (1.5-15 ng/mL) were the main analytes detected in these samples. Moreover, the co-occurrence of alternariol monomethyl ether and alternariol in pig urine is reported herein for the first time.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。