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Catechol oxidase nanozyme based colorimetric sensors array for highly selective distinction among multiple

Jian-Hang Yin1, Mengxuan Liu1, Chengwu Lan1

  • 1College of Materials Science and Engineering, Jilin Institute of Chemical Technology, Jilin, 132022, China.

Analytica Chimica Acta
|October 12, 2023
PubMed
Summary

A novel colorimetric sensor array using copper nanoclusters (CuNCs) offers a rapid and sensitive method for detecting structurally similar catecholamines (CAs). This advanced sensor array successfully distinguishes between various CAs and their mixtures in real samples.

Keywords:
Catechol oxidaseColorimetric sensor arrayCuNCsNeurotransmitterSelective sensor

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Area of Science:

  • Analytical Chemistry
  • Nanotechnology
  • Biochemistry

Background:

  • Monitoring catecholamines (CAs) with similar structures is challenging due to the need for high sensitivity and selectivity.
  • Existing detection methods often lack the speed and specificity required for real-time analysis of complex biological samples.

Purpose of the Study:

  • To develop a novel, rapid, sensitive, and selective colorimetric sensor array for detecting multiple catecholamines (CAs) with similar structures.
  • To utilize copper nanoclusters (CuNCs) protected by various ligands as enzyme mimics for CA detection.

Main Methods:

  • Construction of a colorimetric sensor array using CuNCs protected by tannic acid (CuNCs@TA), ascorbic acid (CuNCs@AA), and polymethylacrylic acid (CuNCs@PMAA).
  • Utilizing the catechol oxidase-like activity of CuNCs to catalyze CAs, leading to observable color changes.
  • Employing Cr6+-modification to enhance the enzymatic activity of CuNCs.
  • Applying Linear Discriminant Analysis (LDA) for data processing and pattern recognition of CAs and their mixtures.

Main Results:

  • The CuNCs array demonstrated selective catalytic activity towards catechol-type analogues, including epinephrine (EP), dopamine (DA), norepinephrine (NE), and l-dopa.
  • Cr6+-modification improved the steady-state kinetics of the CuNCs' enzymatic activity.
  • The sensor array successfully distinguished between different CAs and their binary/ternary mixtures based on absorbance changes at 485 nm.
  • Achieved low detection limits (LOD) in the range of 10^-8 to 10^-9 mol/L for CA detection.
  • Successfully identified four CA analogues in real biological samples.

Conclusions:

  • The developed CuNCs-based colorimetric sensor array provides a fast, sensitive, and selective platform for monitoring structurally similar catecholamines.
  • This approach offers a convenient experimental basis for the analysis of complex CA mixtures in various applications.
  • The study highlights the potential of engineered nanomaterials as enzyme mimics for advanced biosensing applications.