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Wu H, Liu L, Wu A, Kuang H, Xu C, Wu X. Broad-specificity and ultrasensitive immunochromatographic detection of bentazone and its metabolites using computer-aided hapten screening. JOURNAL OF HAZARDOUS MATERIALS 2025; 489:137579. [PMID: 39952123 DOI: 10.1016/j.jhazmat.2025.137579] [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: 12/16/2024] [Revised: 02/07/2025] [Accepted: 02/10/2025] [Indexed: 02/17/2025]
Abstract
Bentazone (Ben) is a benzothiadiazole herbicide, and its widespread use can lead to excessive residues in crop products, polluting environmental water and soil. Ben and its metabolites 6-hydroxybentazone, 8-hydroxybentazone, and Bentazone methyl are all toxic to human, therefore it's crucial to detect Ben and metabolites. In this study, the epitope information of Ben was analyzed from molecular space conformation and electrostatic potential distribution. Three novel haptens were prepared by designing and modifying the benzene ring, imine, and carbonyl groups of Ben molecule. The matrix effect enhancement screening method was used to obtain high affinity and broad-spectrum monoclonal antibodies (mAbs). The co-monitoring of Ben and its metabolites could be realized at one time, different from other detection methods. The IC50 values of mAbs against Ben was 1.70 ng/mL. The colloidal gold immunochromatography was firstly developed to detect Ben in lake water, soil, and French bean samples with LOD of 1.47 ng/g, 1.54 ng/g, and 4.83 ng/g, respectively, and detection ranges of 2.52-22.71 ng/g, 2.64-139.73 ng/g, and 8.31-49.36 ng/g, respectively. The recovery rate was 88.5 %-99.5 %, and confirmed by positive Ben samples. The CGIA exhibited excellent detection performance for on-site detection of Ben and metabolites in environmental samples.
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Affiliation(s)
- Huihui Wu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu, 214122, PR China
| | - Liqiang Liu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu, 214122, PR China
| | - Aihong Wu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu, 214122, PR China
| | - Hua Kuang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu, 214122, PR China
| | - Chuanlai Xu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu, 214122, PR China
| | - Xiaoling Wu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, PR China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu, 214122, PR China.
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Xiao J, Qin L, Zhao D, Huang N, Xu W, Zhang L, Pan X, Han S, Ding M, Li L, Le T, Peng D. Monospecific and ultrasensitive detection of ofloxacin: A computational chemistry-assisted hapten screening strategy and analysis of molecular recognition mechanism. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133221. [PMID: 38103295 DOI: 10.1016/j.jhazmat.2023.133221] [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: 10/07/2023] [Revised: 12/04/2023] [Accepted: 12/08/2023] [Indexed: 12/19/2023]
Abstract
Contamination in food and the environment with fluoroquinolones (FQs) has become a serious threat to the global ecological balance and public health safety. Ofloxacin (OFL) is one of the most widely utilized sterilization agents in FQs. In the process of monitoring OFL, broad-spectrum monoclonal antibodies (mAb) cannot meet the demand for monospecific detection. Here, a computational chemistry-assisted hapten screening strategy was proposed in this study. Differences in the properties of antigenic epitopes were precisely extracted through a comprehensive comparative study of 16 common FQs molecules and a monospecific and ultrasensitive mAb-3B4 for OFL was successfully prepared. The screened fleroxacin (FLE) hapten was applied in a heterologous competition strategy resulting in a 20-fold improvement in the half inhibitory concentration (IC50) of mAb-3B4 to 0.0375 μg L-1 and cross-reacted only with marbofloxacin (MAR) in regulated FQs. In addition, a single-chain variable fragment (scFv) for OFL was constructed for the first time with an IC50 of 0.378 μg L-1. Molecular recognition mechanism studies validated the reliability of this strategy and revealed the key amino acid sites responsible for OFL specificity and sensitivity. Finally, ic-ELISA and GICA were established for OFL in real samples. This work provides new ideas for the preparation of monospecific mAb and improves the monitoring system of FQs.
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Affiliation(s)
- Jiaxu Xiao
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Liangni Qin
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Dan Zhao
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Niexie Huang
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Wennuo Xu
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Linwei Zhang
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaoming Pan
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Shiyun Han
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Mingyue Ding
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Long Li
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China
| | - Tao Le
- College of Life Sciences, Chongqing Normal University, Chongqing 401331, China.
| | - Dapeng Peng
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen 518000, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China.
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Song L, Wang Y, Li Q, Wang J, Gao T, An Z, Liu Q, Mao Y, Bu T, Huang X, Ma Y, Wang Z, Zhang X. Production of monoclonal antibody against tylosin and tilmicosin with homogeneous cross-reactivity and its application in lateral flow immunoassay. Mikrochim Acta 2023; 191:42. [PMID: 38114730 DOI: 10.1007/s00604-023-06132-z] [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: 07/25/2023] [Accepted: 11/29/2023] [Indexed: 12/21/2023]
Abstract
To avoid false negative results due to the low cross-reactivity rate (CR) in rapid immunoassay, a group-specific antibody with homogeneous CR toward target compounds is needed for accuracy. In this study, tylosin (TYL) and tilmicosin (TM) were selected as model molecules. Firstly, two-dimensional similarity, electrostatic potential energy, spatial conformation and charge distribution of the haptens TYL-CMO, TYL-6-ACA, TYL-4-APA, TYL-CHO and DES-CMO and target compounds of TYL and TM were obtained using Gaussian 09W and Discovery Studio. The optimal hapten was DES-CMO because it is the most similar to TYL and TM. Subsequently, the mAb 14D5 cell line was obtained with IC50 values of 1.59 and 1.72 ng/mL for TYL and TM, respectively, and a CR of 92.44%. Finally, amorphous carbon nanoparticles (ACNPs) were conjugated with mAb 14D5 to develop an accurate lateral flow immunoassay (LFA) for detection of TYL and TM by the reflectance value under natural light. The recoveries of TYL and TM ranged from 77.18 to 112.04% with coefficient of variation < 13.43%. The cut-off value in milk samples was 8 ng/mL, and the limits of detection were 11.44, 15.96, 22.29 and 25.53 μg/kg for chicken muscle, bovine muscle, porcine muscle and porcine liver samples, respectively, and the results being consistent with HPLC-UV. The results suggest that the developed LFA is accurate and potentially useful for on-site screening of TYL and TM in milk and animal tissue samples.
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Affiliation(s)
- Lianjun Song
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Youyi Wang
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Qingyue Li
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Jinkui Wang
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Tian Gao
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Zhaohuan An
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Qinfang Liu
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Yexuan Mao
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Tong Bu
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Xianqing Huang
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
| | - Yan Ma
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China
- Henan Shuanghui Investment Development Co., Ltd., Luohe, 462005, China
- Henan Technology Innovation Center of Meat Processing and Research, Luohe, 462005, China
| | - Zhanhui Wang
- National Key Laboratory of Veterinary Public Health Security, Beijing Key Laboratory of Detection Technology for Animal Derived Food Safety, College of Veterinary Medicine, China Agricultural University, 100193, Beijing, People's Republic of China
| | - Xiya Zhang
- Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, 63 Nongye Road, Zhengzhou, 450002, Henan, China.
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Li L, Wu S, Si Y, Li H, Yin X, Peng D. Single-chain fragment variable produced by phage display technology: Construction, selection, mutation, expression, and recent applications in food safety. Compr Rev Food Sci Food Saf 2022; 21:4354-4377. [PMID: 35904244 DOI: 10.1111/1541-4337.13018] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/06/2022] [Accepted: 07/08/2022] [Indexed: 01/28/2023]
Abstract
Immunoassays are reliable, efficient, and accurate methods for the analysis of small-molecule harmful substances (such as pesticides, veterinary drugs, and biological toxins) that may be present in food. However, traditional polyclonal and monoclonal antibodies are limited by animal hosts and hinder further development of immunoassays. With the gradual application of phage display technology as an efficient in vitro selection technology, the single-chain fragment variable (scFv) now provides an exciting alternative to traditional antibodies. Efficiently constructed scFv source libraries and specifically designed biopanning schemes can now yield scFvs possessing specific recognition capabilities. A rational mutation strategy further enhances the affinity of scFv, and allows it to reach a level that cannot be achieved by immunization. Finally, appropriate prokaryotic expression measures ensure stable and efficient production of scFv. Therefore, when developing excellent scFvs, it is necessary to focus on three key aspects of this process that include screening, mutation, and expression. In this review, we analyze in detail the preparation and affinity improvement process for scFv and provide insights into the research progress and development trend of scFv-based immunoassay methods for monitoring small-molecule harmful substances.
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Affiliation(s)
- Long Li
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Shuangmin Wu
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Yu Si
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Huaming Li
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Xiaoyang Yin
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Dapeng Peng
- National Reference Laboratory of Veterinary Drug Residues (HZAU) and MOA Key Laboratory for the Detection of Veterinary Drug Residues in Foods, Huazhong Agricultural University, Wuhan, Hubei, China.,Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen, Guangdong, China.,Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.,Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
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