Volume 2, 2023

Rapid detection of Candida albicans in urine by an Electrochemical Impedance Spectroscopy (EIS)-based biosensor

Abstract

Candida albicans is a fungal organism commonly found in the human body, including the genitourinary tract. Overgrowth of this yeast can lead to candiduria, the abnormal presence of C. albicans in urine. The detection of candiduria relies on various methods that offer sensitivity and specificity for accurate diagnosis, but none of them is rapid and cost-effective. Biosensors may offer an answer; in particular, impedance-based biosensors have shown promise in addressing the detection of C. albicans since they offer high sensitivity, simplicity of fabrication, excellent selectivity, real-time detection, and cost-effectiveness. However, variations in the working surface of commercial screen-printed electrodes as well as manual functionalization can impact robustness and reproducibility. In this paper, we describe significant advances that we introduced to perform electrochemical impedance spectroscopy for biosensing purposes. Specifically, we designed a microfluidic cell for standardizing the electrode functionalization and target detection, ensuring sensor reproducibility and robustness. By optimizing several parameters like the flow rate and the density of antibodies on the electrode surface, we could achieve a limit of detection of 10 CFU mL−1 in urine with a measurement that lasted for less than 90 minutes. The modularity of the device and the measurement procedure makes the described biosensor extendable for conducting high-throughput analyses.

Graphical abstract: Rapid detection of Candida albicans in urine by an Electrochemical Impedance Spectroscopy (EIS)-based biosensor

Supplementary files

Article information

Article type
Paper
Submitted
03 Aug 2023
Accepted
03 Oct 2023
First published
10 Oct 2023
This article is Open Access
Creative Commons BY license

Sens. Diagn., 2023,2, 1597-1604

Rapid detection of Candida albicans in urine by an Electrochemical Impedance Spectroscopy (EIS)-based biosensor

T. D'Aponte, M. De Luca, N. Sakač, M. Schibeci, A. Arciello, E. Roscetto, M. R. Catania, V. Iannotti, R. Velotta and B. Della Ventura, Sens. Diagn., 2023, 2, 1597 DOI: 10.1039/D3SD00209H

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