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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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Birse N, Burns DT, Walker MJ, Quaglia M, Elliott CT. Food allergen analysis: A review of current gaps and the potential to fill them by matrix-assisted laser desorption/ionization. Compr Rev Food Sci Food Saf 2023; 22:3984-4003. [PMID: 37530543 DOI: 10.1111/1541-4337.13216] [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: 10/28/2022] [Revised: 07/01/2023] [Accepted: 07/10/2023] [Indexed: 08/03/2023]
Abstract
Food allergy remains a public health, business, and regulatory challenge. Risk analysis (RA) and risk management (RM) of food allergens are of great importance and analysis for food allergens is necessary for both. The current workhorse techniques for allergen analysis (enzyme linked immunosorbent assay [ELISA] and real-time polymerase chain reaction) exhibit recognized challenges including variable and antibody specific responses and detection of species DNA rather than allergen protein, respectively. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) enables protein identification, with potential for multiplex analysis and traceability to the System of International units (SI), aiding global measurement standardization. In this review, recent literature has been systematically reviewed to assess progress in LC-MS/MS and define the potential and benefits of matrix-assisted laser desorption/ionization-time-of-flight MS (MALDI-ToF-MS) technology for allergen analysis. MALDI-ToF-MS of initially intact protein is already applied to verify in silico-derived peptide sequences for LC-MS/MS analysis. We describe the origins of MALDI and its future perspectives, including affinity bead-assisted assays coupled to MALDI. Based on the proliferation of reliable and reproducible MALDI-based clinical applications, the technique should emulate the detection capability (sensitivity) of established allergen detection techniques, whilst reducing technical support and having equivalent multiplexing potential to competing techniques, for example, LC-MS/MS and ELISA. Although unlikely to offer inherent SI traceability, MALDI-based allergen analysis will complement existing MS approaches for allergens. Affinity bead-MALDI appears capable of higher throughput at lower cost per sample than almost any existing technique, enabling repeated sub-sampling as a way to reduce representative sampling issues.
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Affiliation(s)
- Nicholas Birse
- Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Duncan Thorburn Burns
- Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Michael J Walker
- Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | | | - Christopher T Elliott
- Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
- School of Food Science and Technology, Faculty of Science and Technology, Thammasat University (Rangsit Campus), Khlong Luang, Pathum Thani, Thailand
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