数字农科院2.0

Development and Validation of a QconCAT-Based LC-MS/MS Method for the Quantification of 12 Food Allergens in Foods

文献类型： 外文期刊

作者： Shencheng, Yingnan;Zhou, Meizhen;Zhao, Yumeng;Li, Siyi;Lin, Haopeng;Abdallah, Mohamed F.;Zhang, Rong;Liu, Shuyan;Li, Yi;Yang, Shupeng

作者机构：

关键词： food allergen;QconCAT;mass spectrometry;food safety;quantitative measurement

期刊名称： JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY

ISSN： 0021-8561

年卷期： 2025 年

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Accurate detection of food allergens is crucial to ensuring food safety. This study introduces a novel LC-MS/MS method integrated with QconCAT technology for the cost-effective quantification of 12 food allergens including milk, eggs, peanuts, soybeans, wheat, sesame, and six tree nuts. Characteristic peptides were selected for specificity, stability, and resilience to heat processing using LC-HRMS, addressing inconsistencies found in prior peptide selection. Stable isotope-labeled QconCAT proteins, expressed in Escherichia coli, served as internal standards, overcoming the high cost of synthesized peptides. The proposed LC-MS/MS method, spiked with QconCAT, exhibited high sensitivity (LOD: 1-3 mg/kg, LOQ: 2-5 mg/kg), excellent linearity (R-2 > 0.995), good accuracy (recovery: 80.2-103.5%), and precision (RSD < 13.8%). Testing of Chinese food samples revealed undeclared allergens in 33.3% of dumplings/steamed buns and 42.9% of mooncakes, demonstrating practical applicability. This cost-effective, high-throughput approach enhances multiallergen detection, supporting regulatory compliance and consumer safety.

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