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Au nanozyme-based colorimetric sensor array integrates machine learning to identify and discriminate monosaccharides
Sijun Huang1, Henglong Xiang1, Jiachen Lv1
1Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, National Engineering Laboratory for AIDS Vaccine, School of Life Sciences, Jilin University, Changchun, China.
Journal of Colloid and Interface Science
|June 5, 2024
Summary
This study introduces a novel colorimetric sensor array using gold nanoparticles (AuNPs) for identifying different monosaccharides. The sensor array enables accurate detection and quantification of sugars in various applications.
Area of Science:
- Nanomaterials Science
- Analytical Chemistry
- Biochemistry
Background:
- Monosaccharides possess distinct redox properties influencing their reactivity.
- Gold nanoparticles (AuNPs) exhibit glucose oxidase-like (GOx-like) activity, enabling catalytic applications.
- Developing selective and sensitive methods for monosaccharide identification is crucial for industrial, medical, and biological fields.
Purpose of the Study:
- To develop a novel colorimetric sensor array for identifying and quantifying monosaccharides.
- To leverage the GOx-like activity of AuNPs for selective monosaccharide detection.
- To apply advanced data analysis techniques for distinguishing complex sugar mixtures and concentrations.
Main Methods:
- Fabrication of a colorimetric sensor array utilizing AuNPs with GOx-like activity.
- Employing different electron acceptors (O2, ABTS+•, [Ag(NH3)2]+) to catalyze monosaccharide oxidation at varying rates.
- Utilizing linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA) for pattern recognition.
- Implementing a neural network regression model for simultaneous quantification of glucose and fructose.
Main Results:
- The AuNP-based sensor array generated cross-responsive signals based on monosaccharide oxidation.
- LDA and HCA successfully distinguished between different monosaccharides and their mixtures.
- The neural network model accurately estimated simultaneous concentrations of glucose and fructose.
- The sensor array demonstrated high potential for practical monosaccharide detection.
Conclusions:
- A novel colorimetric sensor array based on AuNPs with GOx-like activity was successfully developed for monosaccharide identification.
- The sensor array effectively distinguishes monosaccharides and their mixtures using chemometric analysis.
- Simultaneous quantification of specific monosaccharides like glucose and fructose is achievable.
- This approach holds significant promise for diverse applications in industry, medicine, and biology.
