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A sensitive and selective electrochemical sensing strategy based on NbCT nanoplate-supported bacteria imprinted polymer.

作者信息

Gharibi Mahdi, Cetinkaya Ahmet, Kaskatepe Banu, Erol Hilal Basak, Gurbuz Havva Nur, Uzunoglu Aytekin, Ozkan Sibel A

机构信息

Ankara University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey.

University of Health Sciences, Gülhane Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey; Hacettepe University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey; Ankara University, Faculty of Pharmacy, Department of Pharmaceutical Microbiology, Ankara, Turkey.

出版信息

Talanta. 2025 Sep 2;298(Pt A):128792. doi: 10.1016/j.talanta.2025.128792.

Abstract

The rapid and sensitive detection of Staphylococcus aureus (S. aureus), a Gram-positive bacterium responsible for a wide range of infections, at a low cost, is crucial for diagnosing bacterial infections. In this protocol, an NbCT MXene nanoplate (NbCT NP)-supported bacteria-imprinted polymer (BIP)-based electrochemical sensor was proposed for the highly sensitive detection of bacteria. The BIP sensor was designed using an electropolymerization (EP) approach on a glassy carbon electrode (GCE) using S. aureus as a template and p-aminobenzoic acid (p-ABA) as a functional monomer. By integrating NbCT NP, the BIP-based electrochemical sensor's active surface area and porosity were increased. The designed BIP-based electrochemical sensor achieved a wide detection range of 10°-10 CFU mL and a low detection limit (LOD) of 0.095 log [CFU mL]. Moreover, the determination of S. aureus with high selectivity in the presence of Gram-negative and positive bacteria showed that the sensor has excellent analytical performance. Both the electrochemical and morphological characterizations of the S.aureus/p-ABA/NbCT NP/BIP-GCE sensor were evaluated using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and scanning electron microscopy (SEM). The developed sensor exhibited excellent repeatability and reproducibility, with relative standard deviations ranging from 0.41 % to 1.93 % in both standard and urine solutions. In addition, the sensor exhibited high specificity, successfully distinguishing S. aureus from Gram-negative (Escherichia coli and Klebsiella pneumoniae), Gram-positive (Enterococcus faecalis and Bacillus subtilis), uric acid, and their mixtures. The applicability of this approach to detect bacteria in complicated samples shows that it has tremendous potential in public health-related domains. Also, the study's green profile was assessed using multiple evaluation tools, including the Blue Applicability Grade Index (BAGI), the Analytical Greenness Assessment Tool for Molecularly Imprinted Polymer Synthesis (AGRREMIP), the Analytical Greenness Metric (AGREE), and the Analytical Greenness Preparation Tool (AGREEprep).

摘要

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