Introducing Nanoscale Electrochemistry in Small-Molecule Detection for Tackling Existing Limitations of Affinity-Based Label-Free Biosensing ApplicationsClick to copy article linkArticle link copied!
- Don Hui LeeDon Hui LeeDepartment of Chemistry, Yonsei University, Seoul 03722, Republic of KoreaCenter for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of KoreaMore by Don Hui Lee
- Won-Yong Lee*Won-Yong Lee*Email: [email protected]Department of Chemistry, Yonsei University, Seoul 03722, Republic of KoreaCenter for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of KoreaMore by Won-Yong Lee
- Jayoung Kim*Jayoung Kim*Email: [email protected]Department of Medical Engineering, College of Medicine, Yonsei University, Seoul 03722, Republic of KoreaMore by Jayoung Kim
Abstract
Electrochemical sensing techniques for small molecules have progressed in many applications, including disease diagnosis and prevention as well as monitoring of health conditions. However, affinity-based detection for low-abundance small molecules is still challenging due to the imbalance in target-to-receptor size ratio as well as the lack of a highly sensitive signal transducing method. Herein, we introduced nanoscale electrochemistry in affinity-based small molecule detection by measuring the change of quantum electrochemical properties with a nanoscale artificial receptor upon binding. We prepared a nanoscale molecularly imprinted composite polymer (MICP) for cortisol by electrochemically copolymerizing β-cyclodextrin and redox-active methylene blue to offer a high target-to-receptor size ratio, thus realizing “bind-and-read” detection of cortisol as a representative target small molecule, along with extremely high sensitivity. Using the quantum conductance measurement, the present MICP-based sensor can detect cortisol from 1.00 × 10–12 to 1.00 × 10–6 M with a detection limit of 3.93 × 10–13 M (S/N = 3), which is much lower than those obtained with other electrochemical methods. Moreover, the present MICP-based cortisol sensor exhibited reversible cortisol sensing capability through a simple electrochemical regeneration process without cumbersome steps of washing and solution change, which enables “continuous detection”. In situ detection of cortisol in human saliva following circadian rhythm was carried out with the present MICP-based cortisol sensor, and the results were validated with the LC–MS/MS method. Consequently, this present cortisol sensor based on nanoscale MICP and quantum electrochemistry overcomes the limitations of affinity-based biosensors, opening up new possibilities for sensor applications in point-of-care and wearable healthcare devices.
Cited By
This article is cited by 3 publications.
- Bohang Wu, Tong Wu, Zehuan Huang, Shaobo Ji. Advancing Flexible Sensors through On-Demand Regulation of Supramolecular Nanostructures. ACS Nano 2024, 18
(34)
, 22664-22674. https://doi.org/10.1021/acsnano.4c08310
- Yanan Li, Hao Zhao, Guanghong Han, Ze Li, Samuel M. Mugo, Hongda Wang, Qiang Zhang. Portable Saliva Sensor Based on Dual Recognition Elements for Detection of Caries Pathogenic Bacteria. Analytical Chemistry 2024, 96
(24)
, 9780-9789. https://doi.org/10.1021/acs.analchem.3c05112
- Bahareh Babamiri, Rad Sadri, Mohammadreza Farrokhnia, Mohsen Hassani, Manpreet Kaur, Edward P. L. Roberts, Mehdi Mohammadi Ashani, Amir Sanati Nezhad. Molecularly Imprinted Polymer Biosensor Based on Nitrogen-Doped Electrochemically Exfoliated Graphene/Ti3 CNTX MXene Nanocomposite for Metabolites Detection. ACS Applied Materials & Interfaces 2024, 16
(21)
, 27714-27727. https://doi.org/10.1021/acsami.4c01973
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.
Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.
The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.