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Liu A, Jiang M, Wu Y, Guo H, Kong L, Chen Z, Luo Z. A rapid and sensitive aptamer-based biosensor for beta-lactoglobulin in milk. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024. [PMID: 38682261 DOI: 10.1039/d4ay00460d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/01/2024]
Abstract
Beta-lactoglobulin (β-Lg), a prominent milk protein, is a major contributor to milk allergies. The quantitative assessment of β-Lg is a valuable method for assessing the allergenic potential of dairy products. In this study, a specific aptamer, β-Lg-01, with an affinity constant (KD) of 28.6 nM for β-Lg was screened through seven rounds of magnetic bead SELEX (MB-SELEX). A novel bio-layer interferometry (BLI)-based aptasensor was developed, which had a limit of detection (LOD) of 0.3 ng mL-1, a linear range of 1.5 ng mL-1-15 μg mL-1, and a recovery rate of 102-116% among the milk samples. This aptasensor provides a potential tool for the detection and risk assessment of β-Lg within 10 min.
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Affiliation(s)
- Anqi Liu
- School of Life Sciences and Medicine, Shandong University of Technology, Zibo, 255049, China.
| | - Meng Jiang
- Hangzhou Institute of Medicine Chinese Academy of Sciences, 310022, China.
| | - Yuyin Wu
- School of Agriculture Engineering and Food Science, Shandong University of Technology, Zibo, 255049, P. R. China
| | - Han Guo
- Hangzhou Institute of Medicine Chinese Academy of Sciences, 310022, China.
| | - Ling Kong
- School of Life Sciences and Medicine, Shandong University of Technology, Zibo, 255049, China.
| | - Zhiwei Chen
- School of Life Sciences and Medicine, Shandong University of Technology, Zibo, 255049, China.
- School of Agriculture Engineering and Food Science, Shandong University of Technology, Zibo, 255049, P. R. China
- Institute of Food and Nutrition Science, Shandong University of Technology, Zibo, 255049, P. R. China
| | - Zhaofeng Luo
- Hangzhou Institute of Medicine Chinese Academy of Sciences, 310022, China.
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Yu X, Pu H, Sun DW. Developments in food neonicotinoids detection: novel recognition strategies, advanced chemical sensing techniques, and recent applications. Crit Rev Food Sci Nutr 2023:1-19. [PMID: 38149655 DOI: 10.1080/10408398.2023.2290698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
Neonicotinoid insecticides (NEOs) are a new class of neurotoxic pesticides primarily used for pest control on fruits and vegetables, cereals, and other crops after organophosphorus pesticides (OPPs), carbamate pesticides (CBPs), and pyrethroid pesticides. However, chronic abuse and illegal use have led to the contamination of food and water sources as well as damage to ecological and environmental systems. Long-term exposure to NEOs may pose potential risks to animals (especially bees) and even human health. Consequently, it is necessary to develop effective, robust, and rapid methods for NEOs detection. Specific recognition-based chemical sensing has been regarded as one of the most promising detection tools for NEOs due to their excellent selectivity, sensitivity, and robust interference resistance. In this review, we introduce the novel recognition strategies-enabled chemical sensing in food neonicotinoids detection in the past years (2017-2023). The properties and advantages of molecular imprinting recognition (MIR), host-guest recognition (HGR), electron-catalyzed recognition (ECR), immune recognition (IR), aptamer recognition (AR), and enzyme inhibition recognition (EIR) in the development of NEOs sensing platforms are discussed in detail. Recent applications of chemical sensing platforms in various food products, including fruits and vegetables, cereals, teas, honey, aquatic products, and others are highlighted. In addition, the future trends of applying chemical sensing with specific recognition strategies for NEOs analysis are discussed.
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Affiliation(s)
- Xinru Yu
- School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China
- Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
- Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
| | - Hongbin Pu
- School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China
- Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
- Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
| | - Da-Wen Sun
- School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China
- Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
- Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China
- Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science Centre, University College Dublin, National University of Ireland, Belfield, Dublin 4, Ireland
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