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Cheng B, Xia X, Han Z, Yu H, Xie Y, Guo Y, Yao W, Qian H, Cheng Y. A ratiometric fluorescent "off-on" sensor for acrylamide detection in toast based on red-emitting copper nanoclusters stabilized by bovine serum albumin. Food Chem 2024; 437:137878. [PMID: 37913709 DOI: 10.1016/j.foodchem.2023.137878] [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: 06/14/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 11/03/2023]
Abstract
Acrylamide, as a Class 2A carcinogen, poses serious threats to human health. To achieve rapid and accurate determination of acrylamide in food, a ratiometric fluorescent "off-on" sensor was designed by incorporating red-emitting copper nanoclusters and glutathione. Copper nanoclusters with bimodal emission at 395 nm and 650 nm (excited at 310 nm) were synthesized by using bovine serum albumin as the ligand and ascorbic acid as the reductant. With glutathione addition, the fluorescence intensity at 650 nm gradually decreased, while the case at 395 nm slightly increased. The quenched fluorescence at 650 nm was subsequently restored by acrylamide through thiol-ene Michael addition reaction between acrylamide and glutathione. The constructed sensor showed excellent performance towards acrylamide detection in the range of 5-300 μM with a detection limit of 1.48 μM, and was further applied to real-sample detection of acrylamide in toast and exhibited good recoveries (90.29-101.30 %), indicating potential applications of this sensor.
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Affiliation(s)
- Baoxin Cheng
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Xiuhua Xia
- Wuxi Vocational Institute of Commerce, Wuxi 214122, China
| | - Zhiqiang Han
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi 214122, China
| | - Hang Yu
- Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi 214122, China
| | - Yufei Xie
- Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi 214122, China
| | - Yahui Guo
- Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi 214122, China
| | - Weirong Yao
- Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi 214122, China
| | - He Qian
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi 214122, China
| | - Yuliang Cheng
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.
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2
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Zhou Z, Tian D, Yang Y, Cui H, Li Y, Ren S, Han T, Gao Z. Machine learning assisted biosensing technology: An emerging powerful tool for improving the intelligence of food safety detection. Curr Res Food Sci 2024; 8:100679. [PMID: 38304002 PMCID: PMC10831501 DOI: 10.1016/j.crfs.2024.100679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/03/2024] Open
Abstract
Recently, the application of biosensors in food safety assessment has gained considerable research attention. Nevertheless, the evaluation of biosensors' sensitivity, accuracy, and efficiency is still ongoing. The advent of machine learning has enhanced the application of biosensors in food security assessment, yielding improved results. Machine learning has been preliminarily applied in combination with different biosensors in food safety assessment, with positive results. This review offers a comprehensive summary of the diverse machine learning methods employed in biosensors for food safety. Initially, the primary machine learning methods were outlined, and the integrated application of biosensors and machine learning in food safety was thoroughly examined. Lastly, the challenges and limitations of machine learning and biosensors in the realm of food safety were underscored, and potential solutions were explored. The review's findings demonstrated that algorithms grounded in machine learning can aid in the early detection of food safety issues. Furthermore, preliminary research suggests that biosensors could be optimized through machine learning for real-time, multifaceted analyses of food safety variables and their interactions. The potential of machine learning and biosensors in real-time monitoring of food quality has been discussed.
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Affiliation(s)
- Zixuan Zhou
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
| | - Daoming Tian
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
- Beidaihe Rest and Recuperation Center of PLA, Qinhuangdao, 066000, China
| | - Yingao Yang
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
| | - Han Cui
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
- State Key Laboratory of Food Nutrition and Safety, Tianjin University of Science & Technology, Tianjin, 300457, China
| | - Yanchun Li
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
| | - Shuyue Ren
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
| | - Tie Han
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
| | - Zhixian Gao
- Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Environmental and Operational Medicine, Tianjin, 300050, China
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3
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Guo M, Wang K, Lin H, Wang L, Cao L, Sui J. Spectral data fusion in nondestructive detection of food products: Strategies, recent applications, and future perspectives. Compr Rev Food Sci Food Saf 2024; 23:e13301. [PMID: 38284587 DOI: 10.1111/1541-4337.13301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/27/2023] [Accepted: 12/31/2023] [Indexed: 01/30/2024]
Abstract
In recent years, the food industry has shown a growing interest in the development of rapid and nondestructive analytical methods. However, the utilization of a solitary nondestructive detection technique offers only a constrained extent of physical or chemical insights regarding the sample under examination. To overcome this limitation, the amalgamation of spectroscopy with data fusion strategies has emerged as a promising approach. This comprehensive review delves into the fundamental principles and merits of low-level, mid-level, and high-level data fusion strategies within the domain of food analysis. Various data fusion techniques encompassing spectra-to-spectra, spectra-to-machine vision, spectra-to-electronic nose, and spectra-to-nuclear magnetic resonance are summarized. Moreover, this review also provides an overview of the latest applications of spectral data fusion techniques (SDFTs) for classification, adulteration, quality evaluation, and contaminant detection within the purview of food safety analysis. It also addresses current challenges and future prospects associated with SDFTs in real-world applications. Despite the extant technical intricacy, the ongoing evolution of online data fusion platforms and the emergence of smartphone-based multi-sensor fusion detection technology augur well for the pragmatic realization of SDFTs, endowing them with formidable capabilities for both qualitative and quantitative analysis in the realm of food analysis.
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Affiliation(s)
- Minqiang Guo
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
- College of Food Science and Engineering, Xinjiang Institute of Technology, Aksu, Xinjiang, China
| | - Kaiqiang Wang
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Hong Lin
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Lei Wang
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Limin Cao
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Jianxin Sui
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
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Li L, Zhang T, Zhang L, Li W, Xu T, Wang L, Liu C, Li W, Li J, Lu R. One-step fabrication of flexible polyamide@Ag-dodecanethiol membranes for highly sensitive SERS detection of thiram. NANOTECHNOLOGY 2023; 35:105601. [PMID: 38035399 DOI: 10.1088/1361-6528/ad115e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 11/30/2023] [Indexed: 12/02/2023]
Abstract
The surface-enhanced Raman scattering (SERS) is an effective spectral technology based on Raman scattering, but in practice, the commonly used SERS substrates suffer from low sensitivity and poor stability. In order to overcome these limitations, the SERS substrates were prepared from hydrophobic modification of dodecanethiol (C12) coupled with a flexible substrate, which was then used for pesticides detection in water. A flexible PA@Ag-C12 substrate with surface functionalization has been obtained. This work aims to investigate the self-assembly of Ag NPs modified with C12 onto polyamide (PA) membranes. Initially, transmission electron microscopy and scanning electron microscopy were used to analyze the substrate's morphology. Then with the help of an energy-dispersive spectrometer, sulfur content of C12-modified Ag NPs was analyzed. In order to determine the hydrophobicity of the modified Ag NPs, the contact angle was used. The results indicate that the gap between Ag NPs on PA membrane can be effectively controlled in order to prevent Ag NPs from aggregating. Furthermore, the finite-difference time-domain analysis indicated that the PA@Ag-C12 substrate exhibited a stronger electromagnetic enhancement effect than the PA@Ag substrate. By reducing NPs gaps on the PA membrane, the number of 'hot spots' increased, and the SERS performance of the substrate was improved as a result. According to the results of this study, this method can greatly reduce the manufacturing costs and time costs of the SERS substrate while maintaining the original uniformity. The SERS performance of PA@Ag-C12 was found to be three orders of magnitude better than that of PA@Ag direct self-assembled substrate, and the detection limit for Rhodamine 6G (R6G) was approximately 8.47 × 10-14M. On the basis of the PA@Ag-C12 substrate, thiram is detectable at a detection limit of 5.88 × 10-11M with a high degree of sensitivity and repeatability.
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Affiliation(s)
- Lujie Li
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
| | - Tingting Zhang
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
| | - Lan Zhang
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
| | - Wei Li
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
| | - Tao Xu
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
| | - Lingling Wang
- Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, 510070, People's Republic of China
| | - Chang Liu
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, People's Republic of China
| | - Weihua Li
- School of Environment and Energy Engineering, Anhui Provincial Key Laboratory of Environmental Pollution Control and Resource Reuse, Anhui Jianzhu University, Hefei, People's Republic of China
| | - Jiansheng Li
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
| | - Rui Lu
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China
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5
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Wu L. Smart and Multifunctional Nanomaterials and Applications for Food Safety. BIOSENSORS 2023; 13:928. [PMID: 37887121 PMCID: PMC10605715 DOI: 10.3390/bios13100928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023]
Abstract
Due to growing concerns about food safety and public health, the contaminants or residues of various harmful substances in food have received much attention in recent years [...].
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Affiliation(s)
- Long Wu
- Hainan Engineering Research Center of Aquatic Resources Efficient Utilization in South China Sea, Key Laboratory of Seafood Processing of Haikou, School of Food Science and Technology, Hainan University, Haikou 570228, China; ; Tel.: +86-0898-66193581
- Key Laboratory of Tropical Fruits and Vegetables Quality and Safety for State Market Regulation, Hainan Institute for Food Control, Haikou 570314, China
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6
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Wang G, Bai X, Ren Y, Su Y, Han J. Development of nucleotide signatures for common poisonous organisms provides a new strategy for food poisoning diagnosis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 265:115529. [PMID: 37776823 DOI: 10.1016/j.ecoenv.2023.115529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/12/2023] [Accepted: 09/25/2023] [Indexed: 10/02/2023]
Abstract
DNA barcoding is widely used in toxic species authentication, but due to serious DNA degradation of forensic materials, the application of full-length barcode sequences in food poisoning diagnosis is greatly limited. Nucleotide signature, a shorter specific molecular marker, derived from traditional DNA barcoding has been proposed as an emerging tool of toxic species detection in deeply processed materials. In this study, to resolve the frequent food poisoning accidents with unknown origin, we envisioned developing a nucleotide signature data set of common poisonous organisms and combining high-throughput sequencing (HTS) to reveal the poisoning cause. Ninety-three individuals and 1093 DNA barcode sequences of twelve common poisonous plants, fish, mushrooms and their related species were collected. Through sequence alignment and screening, the nucleotide signatures were respectively developed and validated as their specific molecular markers. The sequence length varied from 19 bp to 38 bp. These fragments were conserved within the same species or genera, and the specificity between related species has been also demonstrated. To further evaluate the application potential of nucleotide signature in forensic diagnosis, simulated forensic specimens (SFS) containing different poisonous ingredients were sequenced by HTS with PCR-free libraries. As a result, the nucleotide signature was successfully captured from original HTS data without assembly and annotation, accompanied by a high detection sensitivity of 0.1 ng/µl in mixture system. Therefore, this method was suitable for the assay of forensic materials with serious DNA degradation. The present study undoubtedly provides a new perspective and strong support for the detection of toxic ingredients and the diagnosis of food poisoning.
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Affiliation(s)
- Gang Wang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Xuanjiao Bai
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Ying Ren
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Yuying Su
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
| | - Jianping Han
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
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7
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Li Y, Li P, Yu X, Zheng X, Gu Q. Exploitation of In Vivo-Emulated In Vitro System in Advanced Food Science. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023. [PMID: 37023249 DOI: 10.1021/acs.jafc.2c07289] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Reasonable model construction contributes to the accuracy of experimental results. Multiple in vivo models offer reliable choices for effective evaluation, whereas their applications are hampered due to adverse features including high time-consumption, high cost and ethical contradictions. In vivo-emulated in vitro systems (IVE systems) have experienced rapid development and have been brought into food science for about two decades. IVE systems' flexibly gathers the strengths of in vitro and in vivo models into one, reflecting the results in an efficient, systematic and interacted manner. In this review, we comprehensively reviewed the current research progress of IVE systems based on the literature published in the recent two decades. By categorizing the IVE systems into 2D coculture models, spheroids and organoids, their applications were systematically summarized and typically exemplified. The pros and cons of IVE systems were also thoroughly discussed, drawing attention to present challenges and inspiring potential orientation and future perspectives. The wide applicability and multiple possibilities suggest IVE systems as an effective and persuasive platform in the future of advanced food science.
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Affiliation(s)
- Yonglu Li
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, Zhejiang, People's Republic of China
- Key Laboratory for Food Microbial Technology of Zhejiang Province, Hangzhou, 310018, Zhejiang, People's Republic of China
| | - Ping Li
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, Zhejiang, People's Republic of China
- Key Laboratory for Food Microbial Technology of Zhejiang Province, Hangzhou, 310018, Zhejiang, People's Republic of China
| | - Xin Yu
- Department of Food Science and Nutrition, Zhejiang University, Hangzhou 310058, People's Republic of China
- Zhejiang Key Laboratory for Agro-food Processing, Fuli Institute of Food Science, and National Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang University, Hangzhou 310058, People's Republic of China
| | - Xiaodong Zheng
- Department of Food Science and Nutrition, Zhejiang University, Hangzhou 310058, People's Republic of China
- Zhejiang Key Laboratory for Agro-food Processing, Fuli Institute of Food Science, and National Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang University, Hangzhou 310058, People's Republic of China
| | - Qing Gu
- School of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, Zhejiang, People's Republic of China
- Key Laboratory for Food Microbial Technology of Zhejiang Province, Hangzhou, 310018, Zhejiang, People's Republic of China
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Wang X, Yuan N, Huang L, Huang P, Du X, Lu X. N, N'-methylene bisacrylamide/divinyl benzene based-highly cross-linked hybrid monolithic column: Production and its applications for powerful capture of four chlorophenols. Talanta 2023; 254:124150. [PMID: 36481394 DOI: 10.1016/j.talanta.2022.124150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 11/24/2022] [Accepted: 11/26/2022] [Indexed: 12/03/2022]
Abstract
In this paper, the role of the halogen bond in capillary monolithic column microextraction was explored for the first time. Benzene-1,3,5-tricarbohydrazide (BTH) was synthesized as a functional monomer, N, N'-methylene bisacrylamide (MBA) and divinyl benzene (DVB) were used as cross-linking agents, the hybrid monolithic column of poly (BTH-co-DVB-co-MBA) was prepared using methanol and polyethylene glycol as pore-forming agents and azodiisobutyronitrile as the initiator. Due to the existence of BTH, a large number of nitrogen atoms (Lewis base) were introduced into the monolithic column, which could form a halogen bond with chlorine-containing organic pollutants and enhance its adsorption performance. Based on the monolithic column, a sensitive and environment-friendly solid-phase microextraction technology was studied. The monolithic column was integrated with high-performance liquid chromatography (HPLC) to extract and detect four kinds of chlorophenol in real water samples. Under best conditions, the method showed excellent extraction ability and linearity, with a linear correlation coefficient of 0.9958-0.9987, a low detection limit (LOD) of 0.04-0.23 μg L-1 (S/N = 3), and relative standard deviation (RSD) less than 3.09%. The recovery rate was kept between 87.30% and 123.00%, and the RSD was less than 3.83%, which indicated that the column had powerful capture performance, high precision, and strong anti-matrix interference ability in the real sample, and had potential application value in practical work.
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Affiliation(s)
- Xuemei Wang
- Key Laboratory of Bioelectrochemistry & Environmental Analysis of Gansu Province, Key Lab of Eco-Environments Related Polymer Materials of MOE, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, 730070, PR China.
| | - Na Yuan
- Key Laboratory of Bioelectrochemistry & Environmental Analysis of Gansu Province, Key Lab of Eco-Environments Related Polymer Materials of MOE, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, 730070, PR China
| | - Lixia Huang
- Key Laboratory of Bioelectrochemistry & Environmental Analysis of Gansu Province, Key Lab of Eco-Environments Related Polymer Materials of MOE, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, 730070, PR China
| | - Pengfei Huang
- Key Laboratory of Bioelectrochemistry & Environmental Analysis of Gansu Province, Key Lab of Eco-Environments Related Polymer Materials of MOE, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, 730070, PR China
| | - Xinzhen Du
- Key Laboratory of Bioelectrochemistry & Environmental Analysis of Gansu Province, Key Lab of Eco-Environments Related Polymer Materials of MOE, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, 730070, PR China
| | - Xiaoquan Lu
- Key Laboratory of Bioelectrochemistry & Environmental Analysis of Gansu Province, Key Lab of Eco-Environments Related Polymer Materials of MOE, College of Chemistry and Chemical Engineering, Northwest Normal University, Lanzhou, 730070, PR China
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9
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Ding Y, Huang C, Zhang Y, Wang J, Wang X. Magnetic microbead enzyme-linked immunoassay based on phage encoded protein RBP 41-mediated for rapid and sensitive detection of Salmonella in food matrices. Food Res Int 2023; 163:112212. [PMID: 36596140 DOI: 10.1016/j.foodres.2022.112212] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/07/2022] [Accepted: 11/15/2022] [Indexed: 11/27/2022]
Abstract
Rapid and sensitive quantitative detection methods are required to monitor and detect Salmonella throughout the food supply chain and early prevention of foodborne disease outbreaks. In this study, a magnetic microbead enzyme-linked immunoassay (MELISA) based on phage receptor binding protein was developed for rapid enrichment and detection of Salmonella in complex food matrices. RBP 41 from phage T102 acted as a species-specific recognition element for Salmonella by exploiting its strong binding capacity to Salmonella surface receptors. RBP 41-MBs were prepared by coupling recombinant RBP 41 with MBs and used to separate and enrich Salmonella cells from spiked food samples. The captured complexes were further integrated with ELISA procedures by HRP-labeled anti-Salmonella antibody for rapid and accurate detection of Salmonella. The whole method took <1.5 h and the detection limit was 10 CFU/mL. Therefore, MELISA was successfully developed for the detection of Salmonella in various spiked food samples (skim milk, lettuce, and chicken breast). The ELISA reaction process of this method was carried out on magnetic beads. It simplified the process of the traditional ELISA method and reduces the reaction time. This study expanded the use of phage-associated proteins and demonstrated the promising prospects for practical applications in the detection of foodborne pathogens.
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Affiliation(s)
- Yifeng Ding
- Key Laboratory of Environment Correlative Dietology, Huazhong Agricultural University, Wuhan 430070, China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
| | - Chenxi Huang
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
| | - Yiming Zhang
- Key Laboratory of Environment Correlative Dietology, Huazhong Agricultural University, Wuhan 430070, China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
| | - Jia Wang
- Key Laboratory of Environment Correlative Dietology, Huazhong Agricultural University, Wuhan 430070, China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
| | - Xiaohong Wang
- Key Laboratory of Environment Correlative Dietology, Huazhong Agricultural University, Wuhan 430070, China; College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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10
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Liu S, Zhao K, Huang M, Zeng M, Deng Y, Li S, Chen H, Li W, Chen Z. Research progress on detection techniques for point-of-care testing of foodborne pathogens. Front Bioeng Biotechnol 2022; 10:958134. [PMID: 36003541 PMCID: PMC9393618 DOI: 10.3389/fbioe.2022.958134] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 06/30/2022] [Indexed: 11/21/2022] Open
Abstract
The global burden of foodborne disease is enormous and foodborne pathogens are the leading cause of human illnesses. The detection of foodborne pathogenic bacteria has become a research hotspot in recent years. Rapid detection methods based on immunoassay, molecular biology, microfluidic chip, metabolism, biosensor, and mass spectrometry have developed rapidly and become the main methods for the detection of foodborne pathogens. This study reviewed a variety of rapid detection methods in recent years. The research advances are introduced based on the above technical methods for the rapid detection of foodborne pathogenic bacteria. The study also discusses the limitations of existing methods and their advantages and future development direction, to form an overall understanding of the detection methods, and for point-of-care testing (POCT) applications to accurately and rapidly diagnose and control diseases.
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Affiliation(s)
- Sha Liu
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Kaixuan Zhao
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Meiyuan Huang
- Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Department of Pathology, Central South University, Zhuzhou, China
| | - Meimei Zeng
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Yan Deng
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Song Li
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Hui Chen
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Wen Li
- College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, China
| | - Zhu Chen
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
- *Correspondence: Zhu Chen,
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11
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Li Y, Man S, Ye S, Liu G, Ma L. CRISPR-Cas-based detection for food safety problems: Current status, challenges, and opportunities. Compr Rev Food Sci Food Saf 2022; 21:3770-3798. [PMID: 35796408 DOI: 10.1111/1541-4337.13000] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/23/2022] [Accepted: 05/26/2022] [Indexed: 12/12/2022]
Abstract
Food safety is one of the biggest public issues occurring around the world. Microbiological, chemical, and physical hazards can lead to food safety issues, which may occur at all stages of the supply chain. In order to tackle food safety issues and safeguard consumer health, rapid, accurate, specific, and field-deployable detection methods meeting diverse requirements are one of the imperative measures for food safety assurance. CRISPR-Cas system, a newly emerging technology, has been successfully repurposed in biosensing and has demonstrated huge potential to establish conceptually novel detection methods with high sensitivity and specificity. This review focuses on CRISPR-Cas-based detection and its current status and huge potential specifically for food safety inspection. We firstly illustrate the pending problems in food safety and summarize the popular detection methods. We then describe the potential applications of CRISPR-Cas-based detection in food safety inspection. Finally, the challenges and futuristic opportunities are proposed and discussed. Generally speaking, the current food safety detection methods are still unsatisfactory in some ways such as being time-consuming, displaying unmet sensitivity and specificity standards, and there is a comparative paucity of multiplexed testing and POCT. Recent studies have shown that CRISPR-Cas-based biosensing is an innovative and fast-expanding technology, which could make up for the shortcomings of the existing methods or even replace them. To sum up, the implementation of CRISPR-Cas and the integration of CRISPR-Cas with other techniques is promising and desirable, which is expected to provide "customized" and "smart" detection methods for food safety inspection in the coming future.
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Affiliation(s)
- Yaru Li
- State Key Laboratory of Food Nutrition and Safety, Key Laboratory of Industrial Microbiology, Ministry of Education, Tianjin Key Laboratory of Industry Microbiology, National and Local United Engineering Lab of Metabolic Control Fermentation Technology, China International Science and Technology Cooperation Base of Food Nutrition/Safety and Medicinal Chemistry, College of Biotechnology, Tianjin University of Science & Technology, Tianjin, China
| | - Shuli Man
- State Key Laboratory of Food Nutrition and Safety, Key Laboratory of Industrial Microbiology, Ministry of Education, Tianjin Key Laboratory of Industry Microbiology, National and Local United Engineering Lab of Metabolic Control Fermentation Technology, China International Science and Technology Cooperation Base of Food Nutrition/Safety and Medicinal Chemistry, College of Biotechnology, Tianjin University of Science & Technology, Tianjin, China
| | - Shengying Ye
- Pharmacy Department, The 983th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army, Tianjin, China
| | - Guozhen Liu
- School of Life and Health Sciences, The Chinese University of Hong Kong, Shenzhen, China
| | - Long Ma
- State Key Laboratory of Food Nutrition and Safety, Key Laboratory of Industrial Microbiology, Ministry of Education, Tianjin Key Laboratory of Industry Microbiology, National and Local United Engineering Lab of Metabolic Control Fermentation Technology, China International Science and Technology Cooperation Base of Food Nutrition/Safety and Medicinal Chemistry, College of Biotechnology, Tianjin University of Science & Technology, Tianjin, China
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