MRM3-based LC-MS multi-method for the detection and quantification of nut allergens

Food allergies have become a global challenge to food safety in industrialized countries in recent years. With governmental monitoring and legislation moving towards the establishment of threshold allergen doses, there is a need for sensitive and quantitative analytical methods for the determination of allergenic food contaminants. Targeted proteomics employing liquid chromatography-mass spectrometry (LC-MS) has emerged as a promising technique that offers increased specificity and reproducibility compared to antibody and DNA-based technologies. As the detection of trace levels of allergenic food contaminants also demands excellent sensitivity, we aimed to significantly increase the analytical performance of LC-MS by utilizing multiple reaction monitoring cubed (MRM3) technology. Following a bottom-up proteomics approach, including a straightforward sample preparation process, 38 MRM3 experiments specific to 18 proteotypic peptides were developed and optimized. This permitted the highly specific identification of peanut, almond, cashew, hazelnut, pistachio, and walnut. The analytical performance of the method was assessed for three relevant food matrices with different chemical compositions. Limits of detection were around 1 mu g/g or below in fortified matrix samples, not accounting for the effects of food processing. Compared to an MRM-based approach, the MRM3-based method showed an increase in sensitivity of up to 30-fold. Regression analysis demonstrated high linearity of the MRM3 signal in spiked matrix samples together with robust intersample reproducibility, confirming that the method is highly applicable for quantitative purposes. To the best of our knowledge, we describe here the most sensitive LC-MS multi-method for food allergen detection thus far. In addition, this is the first study that systematically compares MRM3 with MRM for the analysis of complex foods.

近年来，食物过敏已成为工业化国家食品安全面临的全球性挑战。随着政府监管和立法朝着确定过敏原阈值剂量的方向发展，需要有灵敏的定量分析方法来测定食物中的过敏原污染物。采用液相色谱 - 质谱联用（LC - MS）的靶向蛋白质组学已成为一种很有前景的技术，与基于抗体和DNA的技术相比，它具有更高的特异性和重现性。由于检测痕量水平的食物过敏原污染物也需要极高的灵敏度，我们旨在通过利用多重反应监测立方（MRM3）技术显著提高LC - MS的分析性能。按照自下而上的蛋白质组学方法，包括一个简单的样品制备过程，针对18种蛋白质型肽段开发并优化了38个MRM3实验。这使得能够高度特异性地鉴定花生、杏仁、腰果、榛子、开心果和核桃。对三种化学成分不同的相关食物基质评估了该方法的分析性能。在强化基质样品中，检测限约为1微克/克或更低，未考虑食品加工的影响。与基于MRM的方法相比，基于MRM3的方法灵敏度提高了多达30倍。回归分析表明，在加标基质样品中MRM3信号具有高度线性，且样品间重现性良好，证实该方法非常适用于定量分析。据我们所知，我们在此描述了迄今为止用于食物过敏原检测的最灵敏的LC - MS多方法。此外，这是首次针对复杂食物分析系统地比较MRM3和MRM的研究。