Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy

Objective and Impact Statement: We describe an electroenzymatic mediator (EM) sensor based on an electroenzymatic assembly peak separation strategy, which can efficiently realize the simultaneous detection of 3 typical cardiovascular disease (CVD) metabolites in 5 μl of plasma under one test. This w...

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Main Authors: Anran Zheng, Chao Li, Shengkai Xu, Zhen Guo, Chuanyu Li, Changsong Zhang, Jia Yao, Zhiqi Zhang, Jinze Li, Lutao Du, Shasha Zhao, Chuanxin Wang, Wei Zhang, Lianqun Zhou
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2023-01-01
Series:BME Frontiers
Online Access:https://spj.science.org/doi/10.34133/bmef.0027
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author Anran Zheng
Chao Li
Shengkai Xu
Zhen Guo
Chuanyu Li
Changsong Zhang
Jia Yao
Zhiqi Zhang
Jinze Li
Lutao Du
Shasha Zhao
Chuanxin Wang
Wei Zhang
Lianqun Zhou
author_facet Anran Zheng
Chao Li
Shengkai Xu
Zhen Guo
Chuanyu Li
Changsong Zhang
Jia Yao
Zhiqi Zhang
Jinze Li
Lutao Du
Shasha Zhao
Chuanxin Wang
Wei Zhang
Lianqun Zhou
author_sort Anran Zheng
collection DOAJ
description Objective and Impact Statement: We describe an electroenzymatic mediator (EM) sensor based on an electroenzymatic assembly peak separation strategy, which can efficiently realize the simultaneous detection of 3 typical cardiovascular disease (CVD) metabolites in 5 μl of plasma under one test. This work has substantial implications toward improving the efficiency of chronic CVD assessment. Introduction: Monitoring CVD of metabolites is strongly associated with disease risk. Independent and time-consuming detection in hospitals is unfavorable for chronic CVD management. Methods: The EM was flexibly designed by the cross-linking of electron mediators and enzymes, and 3 EM layers with different characteristics were assembled on one electrode. Electrons were transferred under tunable potential; 3 metabolites were quantitatively detected by 3 peak currents that correlated with metabolite concentrations. Results: In this study, the EM sensor showed high sensitivity for the simultaneous detection of 3 metabolites with a lower limit of 0.01 mM. The linear correlation between the sensor and clinical was greater than 0.980 for 242 patients, and the consistency of risk assessment was 94.6%. Conclusion: Metabolites could be expanded by the EM, and the sensor could be a promising candidate as a home healthcare tool for CVD risk assessment.
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spelling doaj-art-2e29f08195cf4b4cb01329f9a7043ab32025-08-20T02:15:47ZengAmerican Association for the Advancement of Science (AAAS)BME Frontiers2765-80312023-01-01410.34133/bmef.0027Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly StrategyAnran Zheng0Chao Li1Shengkai Xu2Zhen Guo3Chuanyu Li4Changsong Zhang5Jia Yao6Zhiqi Zhang7Jinze Li8Lutao Du9Shasha Zhao10Chuanxin Wang11Wei Zhang12Lianqun Zhou13CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou 215153, Jiangsu Province, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou 215153, Jiangsu Province, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan 250033, Shandong, China.School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China.Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan 250033, Shandong, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.Objective and Impact Statement: We describe an electroenzymatic mediator (EM) sensor based on an electroenzymatic assembly peak separation strategy, which can efficiently realize the simultaneous detection of 3 typical cardiovascular disease (CVD) metabolites in 5 μl of plasma under one test. This work has substantial implications toward improving the efficiency of chronic CVD assessment. Introduction: Monitoring CVD of metabolites is strongly associated with disease risk. Independent and time-consuming detection in hospitals is unfavorable for chronic CVD management. Methods: The EM was flexibly designed by the cross-linking of electron mediators and enzymes, and 3 EM layers with different characteristics were assembled on one electrode. Electrons were transferred under tunable potential; 3 metabolites were quantitatively detected by 3 peak currents that correlated with metabolite concentrations. Results: In this study, the EM sensor showed high sensitivity for the simultaneous detection of 3 metabolites with a lower limit of 0.01 mM. The linear correlation between the sensor and clinical was greater than 0.980 for 242 patients, and the consistency of risk assessment was 94.6%. Conclusion: Metabolites could be expanded by the EM, and the sensor could be a promising candidate as a home healthcare tool for CVD risk assessment.https://spj.science.org/doi/10.34133/bmef.0027
spellingShingle Anran Zheng
Chao Li
Shengkai Xu
Zhen Guo
Chuanyu Li
Changsong Zhang
Jia Yao
Zhiqi Zhang
Jinze Li
Lutao Du
Shasha Zhao
Chuanxin Wang
Wei Zhang
Lianqun Zhou
Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy
BME Frontiers
title Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy
title_full Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy
title_fullStr Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy
title_full_unstemmed Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy
title_short Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy
title_sort efficient simultaneous detection of metabolites based on electroenzymatic assembly strategy
url https://spj.science.org/doi/10.34133/bmef.0027
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