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Hu W, Xiong Z, Meng X, Wu Y, Tong P, Gao J, Li X, Chen H. Lipid matrix-specific pretreatment method for enhancing the extractability and allergenicity maintenance of bovine milk allergens in ELISA detection. Food Chem 2024; 452:139462. [PMID: 38723563 DOI: 10.1016/j.foodchem.2024.139462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/21/2024] [Accepted: 04/21/2024] [Indexed: 06/01/2024]
Abstract
The presence of various components in the food matrix makes allergen detection difficult and inaccurate, and pretreatment is an innovative breakthrough point. Food matrices were categorised based on their composition. Subsequently, a pretreatment method was established using a combination of ultrasound-assisted n-hexane degreasing and weakly alkaline extraction systems to enhance the detection accuracy of bovine milk allergens. Results showed that more allergens were obtained with less structural destruction, as demonstrated using immunological quantification and spectral analysis. Concurrently, allergenicity preservation was confirmed through liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, a KU812 cell degranulation model, and western blotting. The method exhibited good accuracy (bias, 8.47%), repeatability (RSDr, 1.52%), and stability (RSDR, 5.65%). In foods with high lipid content, such as chocolate, the allergen content was 2.29-fold higher than that of commercial kits. Laser confocal scanning microscopy (LCSM) and scanning electron microscopy (SEM) analyses revealed a significant decrease in fat content after post-pretreatment using our method. In addition, colloidal stability surpassed that achieved using commercial kits, as indicated through the PSA and zeta potential results. The results demonstrated the superiority of the extractability and allergenicity maintenance of lipid matrix-specific pretreatment methods for improving the accuracy of ELISA based allergen detection in real food.
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Affiliation(s)
- Wei Hu
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; School of Food Science and Technology, Nanchang University, Nanchang 330031, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China
| | - Ziyi Xiong
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; School of Food Science and Technology, Nanchang University, Nanchang 330031, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China
| | - Xuanyi Meng
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China; Sino-German Joint Research Institute, Nanchang University, Nanchang 330047, China
| | - Yong Wu
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China; Sino-German Joint Research Institute, Nanchang University, Nanchang 330047, China
| | - Ping Tong
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; School of Food Science and Technology, Nanchang University, Nanchang 330031, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China
| | - Jinyan Gao
- School of Food Science and Technology, Nanchang University, Nanchang 330031, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China
| | - Xin Li
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; School of Food Science and Technology, Nanchang University, Nanchang 330031, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China.
| | - Hongbing Chen
- State Key Laboratory of Food Science and Resource, Nanchang University, Nanchang 330047, China; Jiangxi Province Key Laboratory of Food Allergy, Nanchang 330047, China; Sino-German Joint Research Institute, Nanchang University, Nanchang 330047, China
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Yang S, Lin H, Yang P, Meng J, Abdallah MF, Shencheng Y, Li R, Li J, Liu S, Li Q, Lu P, Zhang R, Li Y. Advancing High-Throughput MS-Based Protein Quantification: A Case Study on Quantifying 10 Major Food Allergens by LC-MS/MS Using a One-Sample Multipoint External Calibration Curve. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:6625-6637. [PMID: 38494953 DOI: 10.1021/acs.jafc.3c08362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The LC-MS-based method has emerged as the preferred approach for quantifying food allergens. However, the preparation of a traditional calibration curve (MSCC) is labor-intensive and error-prone. Here, a sensitive and robust LC-MS/MS method for quantifying 10 major food allergens was developed and validated, where the one-sample multipoint external calibration curve (OSCC) was employed instead of MSCC. By employing the multiple isotopologue reaction monitoring (MIRM) technique with only one spiked level in the blank, OSCC can be effectively established. Results demonstrate that the proposed method exhibits excellent performance in selectivity, sensitivity, accuracy, and precision, comparable to that of the traditional MSCC. Additionally, this strategy allows for isotope sample dilution by monitoring the less abundant MIRM channel. Moreover, the developed method was successfully applied to investigate the contamination of 10 food allergens in commercial food products. With its high throughput and robustness, the MIRM-OSCC-LC-MS/MS methodology has many potential applications, especially in the MS-based protein quantification analysis.
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Affiliation(s)
- Shupeng Yang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Haopeng Lin
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Peijie Yang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Junhong Meng
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Mohamed F Abdallah
- Department of Food Technology, Safety and Health, Ghent University, Coupure Links 653, Ghent 9000, Belgium
- Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, Assiut University, Assiut 71515, Egypt
| | - Yingnan Shencheng
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Ruohan Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Jianxun Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Shuyan Liu
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Qianqian Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Peng Lu
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Rong Zhang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
| | - Yi Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China
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Kiyota K, Yoshimitsu M, Matsui H. Determination of degradation degree of ovalbumin in hen’s egg enzymatic hydrolysates using liquid chromatography–tandem mass spectrometry. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2022. [DOI: 10.1007/s11694-022-01591-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Wang G, Yu X, Cong Y, Li L. Cow milk αs1-casein induces allergic responses in a mouse model of atopy. FOOD SCIENCE AND HUMAN WELLNESS 2022. [DOI: 10.1016/j.fshw.2022.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Ho CW, Hsu JL, Chen SH, Liaw ET, Liu SS, Huang ES, Chen YK, Jean Huang CC, Yu HS. Development and validation of mass spectrometry-based method for detecting shrimp allergen tropomyosin. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.112367] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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