Detection of Six Commercially Processed Soy ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring

Soybean is one of the major allergenic foods in the United States, European Union, and many other countries. Soybean is commonly processed into different types of soy ingredients to achieve desired properties. The processing, however, may affect the protein profiles and protein structure, thus affecting the detection of soy proteins. Mass spectrometry is a potential alternative to the traditional immunoassays for the detection of soy-derived ingredients in foods. This study aims to develop an LC-MS/MS method that uniformly detects different types of soy-derived ingredients. Target peptides applicable to the detection of six commercial soy ingredients were identified based on the results of MS label-free quantification and a set of selection criteria. The results indicated that soy ingredient processing can result in different protein profiles, mostly affecting the content of minor seed storage proteins. Six soy ingredients were then individually incurred into cookie matrices at different levels. Sample preparation methods were optimized, and a distinct improvement in peptide performance was observed after optimization. Cookies and dough incurred with different soy ingredients at 100 ppm total soy protein showed a similar level of peptide recovery, demonstrating the advantage of the MS method in detecting processed soy ingredients in comparison with antibody-based methods.

大豆是美国、欧盟及诸多其他国家的主要致敏食品之一。大豆常被加工为各类大豆源性配料以获得所需的功能特性，然而加工过程可能会改变蛋白质组谱与蛋白质结构，进而影响大豆蛋白质的检测。质谱法（Mass spectrometry）有望替代传统免疫分析法，用于食品中大豆源性配料的检测。本研究旨在开发一种可统一检测各类大豆源性配料的液相色谱-串联质谱（LC-MS/MS）方法。基于质谱无标记定量（MS label-free quantification）结果与一系列筛选标准，本研究鉴定出可用于6种市售大豆源性配料检测的目标肽段。研究结果表明，大豆配料的加工过程会导致不同的蛋白质组谱，主要影响次要种子贮藏蛋白的含量。随后，本研究将6种大豆源性配料分别以不同浓度掺入曲奇基质中，并对样品前处理方法进行了优化，优化后肽段的检测性能得到显著提升。当总大豆蛋白含量为100 ppm时，添加不同大豆配料的曲奇及面团的肽段回收率水平相近，证明相较于基于抗体的检测方法，本研究所用的质谱法在检测加工型大豆配料方面具有显著优势。