霉菌毒素检测:从多毒素分析到代谢组学

Mycotoxins Pub Date : 2017-01-31 DOI:10.2520/MYCO.67-1-8
R. Krska, M. Sulyok, F. Berthiller, R. Schuhmacher
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引用次数: 17

摘要

真菌毒素是一种有毒的真菌代谢物,广泛存在于农产品中。包括最近启动的欧洲项目“MyToolBox”在内的几个研究项目旨在采用综合方法——将收获前和收获后的措施与有效的控制监测工具相结合。后者对于为消费者提供食品安全以及确定减少真菌毒素的缓解措施的效果至关重要。分析化学,特别是质谱分析,已经以惊人的速度发展起来。虽然几年前,只能测量单一毒素,但明显的趋势是采用多种毒素方法,提供更详细的图像。其中一个例子是我们最近开发的多分析物LC-MS/MS方法,该方法能够分别测定培养物、谷物、食品和饲料产品中的大约380种真菌、细菌和植物代谢物。基于lc - ms的筛选在发现新型真菌毒素偶联物(即所谓的“隐蔽”形式的真菌毒素)方面也一直发挥着至关重要的作用。代谢组学作为所谓的组学学科的最新发展,显示出巨大的潜力,可以在很宽的浓度范围内一次确定数百到数千种代谢物。在用1+1标记和未标记前体混合物处理的生物/食品样品进行测量后,可以通过新型软件工具(“MetExtract”)可靠地自动检测标记特异性同位素模式。在一项初步研究中,该方法的巨大潜力进一步被最普遍的镰刀菌毒素脱氧雪腐镰刀菌醇的新型植物源生物转化产物的成功和自动化检测所强调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mycotoxin testing: From Multi-toxin analysis to metabolomics
Mycotoxins are toxic fungal metabolites, occurring on a wide range of agricultural products. Several research projects, including the recently started European project “MyToolBox”, aim for integrated approaches – combining preand post-harvest measures with efficient monitoring tools for control. The latter is crucial to provide food safety for the consumers and to determine the efficacy of mitigation measures to reduce mycotoxins. Analytical chemistry, in particular mass spectrometry, has evolved with a tremendous pace. While years ago, only single toxins could be measured, a clear trend is towards multi-toxin methods, providing a far more detailed picture. One example is a multi-analyte LC-MS/MS method which has recently been developed by us and which is capable of determining some 380 fungal, bacterial and plant metabolites, respectively, in cultures, cereals, food and feed products. LC-MSbased screening has also been playing a vital role in the discovery of novel mycotoxin conjugates so called “masked” forms of mycotoxins. Metabolomics has emerged as the latest of the so-called –omics disciplines and shows great potential to determine hundreds to thousands of metabolites at once over a wide range of concentrations. After measurement of biological/food samples treated with a 1+1 mixture of labelled and non-labelled precursors, labelling-specific isotopic patterns can be reliably and automatically detected by means of the novel software tool (“MetExtract”). In a preliminary study, the great potential of the presented approach is further underlined by the successful and automated detection of novel plant-derived biotransformation products of the most prevalent Fusarium mycotoxin deoxynivalenol.
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