Oligonucleotide-Driven Nanoparticle Biosensor for Candida albicans Detection in Vaginal Swabs
Year: 2026
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide Vulvovaginal candidiasis (VVC), caused by Candida albicans ( C.albicans ), is a common gynecological infection. VVC is traditionally diagnosed using microbiological culture and microscopy by immunofluorescence, which suffer from limitations such as time-consuming procedures and subjectivity. This study developed a colorimetric biosensor based on gold nanoparticles functionalized with oligonucleotides for the rapid detection of C.albicans . To target the specific hypha wall protein 1 gene (HWP1), thiol-modified oligonucleotide probes were designed and conjugated to the surface of 60 nm citrate-stabilized gold nanoparticles (AuNPs). When the target RNA is present, oligonucleotide hybridization induces nanoparticle aggregation, causing a color shift in the solution from red to transparent, which can be quantitatively detected using UV–visible spectrophotometry. Experimental optimization of salt concentration for hybridization determined the optimal condition as 7 μL of 5 M NaCl, with a limit of detection calculated via the 3σ/slope method of 0.078 nM. Clinical validation using 234 vaginal swab samples provided by Ruijin Hospital (Shanghai, China) demonstrated an achieved sensitivity of 85.0%, specificity of 85.4%, and overall accuracy of 85.3%. Besides, the entire detection process was completed within 40 min without enzymatic amplification. This AuNP-based colorimetric sensor offers advantages of rapidity, low cost, high sensitivity, and specificity, providing an efficient novel method for the early diagnosis of VVC.
Source: ACS Omega
Authors: Linglin Qiu, Cristina de la Encarnacion, Yuji Li, Mengfei Yuan, Jiawei Cao, Qingyue Bao, Lei Zhang, Xiaolan Lu, Xiaojuan Cui
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,935
Funder: Shanghai University
Awards: G3740012647, G5682546011
OpenAlex ID: W7122811621
