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A Label-Free Carbohydrate-Based Electrochemical Sensor to Detect Escherichia coli Pathogenic Bacteria Using D-mannose on a Glassy Carbon Electrode

Controlling water and food contamination by pathogenic organisms requires quick, simple, and low-cost methods. Using the affinity between mannose and type I fimbriae in the cell wall of Escherichia coli (E. coli) bacteria as evaluation elements compared to the conventional plate counting technique e...

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Detalles Bibliográficos
Autores principales: Hargol Zadeh, Sakineh, Kashanian, Soheila, Nazari, Maryam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296727/
https://www.ncbi.nlm.nih.gov/pubmed/37366984
http://dx.doi.org/10.3390/bios13060619
Descripción
Sumario:Controlling water and food contamination by pathogenic organisms requires quick, simple, and low-cost methods. Using the affinity between mannose and type I fimbriae in the cell wall of Escherichia coli (E. coli) bacteria as evaluation elements compared to the conventional plate counting technique enables a reliable sensing platform for the detection of bacteria. In this study, a simple new sensor was developed based on electrochemical impedance spectroscopy (EIS) for rapid and sensitive detection of E. coli. The biorecogniton layer of the sensor was formed by covalent attachment of p-carboxyphenylamino mannose (PCAM) to gold nanoparticles (AuNPs) electrodeposited on the surface of a glassy carbon electrode (GCE). The resultant structure of PCAM was characterized and confirmed using a Fourier Transform Infrared Spectrometer (FTIR). The developed biosensor demonstrated a linear response with a logarithm of bacterial concentration (R(2) = 0.998) in the range of 1.3 × 10 (1)~1.3 × 10(6) CFU·mL(−1) with the limit of detection of 2 CFU·mL(−1) within 60 min. The sensor did not generate any significant signals with two non-target strains, demonstrating the high selectivity of the developed biorecognition chemistry. The selectivity of the sensor and its applicability to analysis of the real samples were investigated in tap water and low-fat milk samples. Overall, the developed sensor showed to be promising for the detection of E. coli pathogens in water and low-fat milk due to its high sensitivity, short detection time, low cost, high specificity, and user-friendliness.