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Chen Y, Gong C, Chen K, Wang Z, He M, Wang P, Chen K, Jiao Y, Yang Y. G-quadruplex DNA-based colorimetric biosensor for the ultrasensitive visual detection of strontium ions using MnO 2 nanorods as oxidase mimetics. Mikrochim Acta 2024; 191:213. [PMID: 38512701 DOI: 10.1007/s00604-024-06293-5] [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: 12/11/2023] [Accepted: 03/01/2024] [Indexed: 03/23/2024]
Abstract
Strontium-90 (90Sr) is a major radioactive component that has attracted great attention, but its detection remains challenging since there are no specific energy rays indicative of its presence. Herein, a biosensor that is capable of rapidly detecting Sr2+ ions is demonstrated. Simple colorimetric method for sensitive detection of Sr2+ with the help of single-stranded DNA was developed by preparing MnO2 nanorods as oxidase mimic catalysis 3,3',5,5'-tetramethylbenzidine (TMB). Under weakly acidic conditions, MnO2 exhibited a strong oxidase-mimicking activity to oxidize colorless TMB into blue oxidation products (oxTMB) with discernible absorbance signals. Nevertheless, the introduction of a guanine-rich DNA aptamer inhibited MnO2-mediated TMB oxidation and reduced oxTMB formation, resulting in blue fading and diminished absorbance. Upon the addition of strontium ions to the system, the aptamers formed a stable G-quadruplex structure with strontium ions, thereby restoring the oxidase-mimicking activity of MnO2. Under the best experimental conditions, the absorbance exhibits a linear relationship with the Sr2+ concentration within the range 0.01-200 μM, with a limit of detection of 0.0028 µM. When the concentration of Sr2+ from 10-8 to 10-6 mol L-1, a distinct color change gradient could be observed in paper-based sensor. We successfully applied this approach to determine Sr2+ in natural water samples, obtaining recoveries ranging from 97.6 to 103% with a relative standard deviation of less than 5%. By providing technical solutions for detection, our work contributed to the effective monitoring of transportation of radioactive Sr in the environment.
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Affiliation(s)
- Yiting Chen
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Chunhui Gong
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Kaiwei Chen
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Ziwei Wang
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Manli He
- Department of General Education, Army Engineering University of PLA, Nanjing, 211101, China
| | - Peng Wang
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Kai Chen
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yan Jiao
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yi Yang
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China.
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Zhu J, Wang D, Yu H, Yin H, Wang L, Shen G, Geng X, Yang L, Fei Y, Deng Y. Advances in colorimetric aptasensors for heavy metal ion detection utilizing nanomaterials: a comprehensive review. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:6320-6343. [PMID: 37965993 DOI: 10.1039/d3ay01815f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Heavy metal ion contamination poses significant environmental and health risks, necessitating rapid and efficient detection methods. In the last decade, colorimetric aptasensors have emerged as powerful tools for heavy metal ion detection, owing to their notable attributes such as high specificity, facile synthesis, adaptability to modifications, long-term stability, and heightened sensitivity. This comprehensive overview summarizes the key developments in this field over the past ten years. It discusses the principles, design strategies, and innovative techniques employed in colorimetric aptasensors using nanomaterials. Recent advancements in enhancing sensitivity, selectivity, and on-site applicability are highlighted. The review also presents application studies of successful heavy metal ion detection using colorimetric aptasensors, underlining their potential for environmental monitoring and health protection. Finally, future directions and challenges in the continued evolution of these aptasensors are outlined.
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Affiliation(s)
- Jiangxiong Zhu
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
| | - Danfeng Wang
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
| | - Hong Yu
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
| | - Hao Yin
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
| | - Lumei Wang
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
| | - Guoqing Shen
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
| | - Xueqing Geng
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
| | - Linnan Yang
- School of Big Data, Yunnan Agricultural University, Kunming 650201, China
| | - Yongcheng Fei
- Eryuan County Inspection and Testing Institute, Yunnan 671299, China
| | - Yun Deng
- Department of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.
- Yunnan Dali Research Institute of Shanghai Jiao Tong University, Yunnan 671000, China
- Eryuan County Inspection and Testing Institute, Yunnan 671299, China
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Qi Y, Li B, Song D, Xiu FR, Gao X. Ultrafast colorimetric detection of Cr(VI) based on competition of 8-HQ to Cr(VI) and TMB oxides using GO/AuNPs nanocomposites as peroxidase mimic. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 297:122722. [PMID: 37080054 DOI: 10.1016/j.saa.2023.122722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/27/2023] [Accepted: 04/07/2023] [Indexed: 05/03/2023]
Abstract
Rapid detection of ultra-trace heavy metal chromium is very important for ecological environment. Herein, a rapid colorimetric assay was constructed for detecting hexavalent chromium (Cr(VI)) in environment water through the strong peroxidase mimicking activity of graphene oxide/gold nanoparticles (GO/AuNPs) nanocomposites and competition of Cr(VI) to 3,3',5,5'-tetramethylbenzidine (TMB) oxides and 8-hydroxyquinoline (8-HQ). Cr(VI) could effectively prevent the reaction between 8-HQ and TMB oxides to restore the blue color of the system. The detection limit for Cr(VI) was as low as0.018 µM by spectroscopic absorption. Paper-based colorimetric analysis had the detection limit of0.153 µM. The high sensitivity was basically due to the strong peroxidase mimicking activity of GO/AuNPs nanocomposite from synergistic coupling action and the firm chelation between 8-HQ and Cr(VI) from inner-sphere surface complexation. The detection results for real water sample showed that the analysis had feasibility in practical application. It is worth mentioning that the assay is performed by one-step mixing mode at room temperature, and a single test can be completed in half a minute. Indeed, this work not only provided an extremely easy method for real-time detecting Cr(VI) in the environment, but also verified the vitality of colorimetric strategy based on the strong peroxidase mimicking activity and competitive reaction.
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Affiliation(s)
- Yingying Qi
- College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China.
| | - Bingjie Li
- College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Dandan Song
- College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Fu-Rong Xiu
- College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Xiang Gao
- College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
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Qi Y, Sun Y, Song D, Wang Y, Xiu F. PVC dechlorination residues as new peroxidase-mimicking nanozyme and chemiluminescence sensing probe with high activity for glucose and ascorbic acid detection. Talanta 2023. [DOI: 10.1016/j.talanta.2022.124039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Zhang Q, Zhang Z, Xu S, Da L, Lin D, Jiang C. Enzyme-free and rapid visual quantitative detection for pesticide residues utilizing portable smartphone integrated paper sensor. JOURNAL OF HAZARDOUS MATERIALS 2022; 436:129320. [PMID: 35739808 DOI: 10.1016/j.jhazmat.2022.129320] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/28/2022] [Accepted: 06/05/2022] [Indexed: 06/15/2023]
Abstract
Serious toxicity for organisms from pesticide glyphosate (Gly) residues to the ecosystem and human health has become a consensus. Rapid and selective detection of glyphosate, especially using a simple and portable instrument, is highly desired. In this work, we develop a novel enzyme-free rapid and visual ratiometric fluorescence sensor for selectively quantitative detecting glyphosate by integrating the designed blue carbon nanodots (CDs) and gold nanoclusters (Au NCs). The fluorescence of CDs can be quickly quenched via aggregation-caused quenching (ACQ) within 2 s after introducing glyphosate, resulting from the formation of CDs-Gly-CDs complex aggregation. While the Au NCs serve as the reference signal without any change, therefore leading to obvious and instant ratiometric fluorescence variation from blue to pink to orange. The broad linear range was obtained from 0 to 180 nM with a satisfactory detection limit of 4.19 nM. Furthermore, this approach was successfully applied to detect glyphosate in real samples and a portable smartphone platform integrated paper sensor was developed for in-site visual quantitative glyphosate detection, offering a promising strategy for the construction of enzyme-free trace hazard detection system.
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Affiliation(s)
- Qianru Zhang
- Institute of Solid State Physics, Chinese Academy of Sciences, Hefei, Anhui 230031, China; Department of Chemistry, University of Science and Technology of China, Hefei 230026, China; School of Chemistry and Materials Engineering, Huainan Normal University, Huainan, Anhui 232038, China
| | - Zhong Zhang
- Institute of Solid State Physics, Chinese Academy of Sciences, Hefei, Anhui 230031, China
| | - Shihao Xu
- Institute of Solid State Physics, Chinese Academy of Sciences, Hefei, Anhui 230031, China
| | - Liangguo Da
- School of Chemistry and Materials Engineering, Huainan Normal University, Huainan, Anhui 232038, China.
| | - Dan Lin
- Institute of Solid State Physics, Chinese Academy of Sciences, Hefei, Anhui 230031, China; State Key Laboratory of Transducer Technology, Chinese Academy of Sciences, Hefei, Anhui 230031, China.
| | - Changlong Jiang
- Institute of Solid State Physics, Chinese Academy of Sciences, Hefei, Anhui 230031, China; State Key Laboratory of Transducer Technology, Chinese Academy of Sciences, Hefei, Anhui 230031, China.
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