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Updated: Jul 25, 2025

Author Spotlight: Advancing Pathogen Diagnostics with Standardized LAMP
Published on: September 8, 2023
Rapid Detection of SARS-CoV-2 Genetic Targets Using Nanoporous Waveguide Based Competitive Displacement Assay
Megan Makela1, Zhihai Lin2, Pao Tai Lin1,2,3
1Department of Materials Science and Engineering, Texas A&M University, College Station, Texas 77843.
Abstract:
Rapid detection of unlabeled SARS-CoV-2 genetic target was demonstrated using a competitive displacement hybridization assay made by a nanostructured anodized alumina oxide (AAO) membrane. The assay applied the toehold-mediated strand displacement reaction. The nanoporous surface of the membrane was functionalized with a complementary pair consisting of Cy3-labeled probe and quencher-labeled nucleic acids through a chemical immobilization process. In the presence of the unlabeled SARS-CoV-2 target, the quencher-tagged strand of the immobilized probe-quencher duplex was separated from the Cy3-modifed strand. A stable probe-target duplex formed and regained a strong fluorescence signal, thus enabling real-time and label-free SARS-CoV-2 detection. Assay designs with different numbers of base pair (bp) matches were synthesized to compare their affinities. Because of the large surface of a free-standing nanoporous membrane, two orders enhancement of the fluorescence was observed, where the detection limit of the unlabeled concentration can be improved to 1 nM. The assay was miniaturized by integrating a nanoporous AAO layer onto an optical waveguide device. The detection mechanism and the sensitivity improvement of the AAO-waveguide device were illustrated from the finite difference method (FDM) simulation and the experimental results. Light-analyte interaction was further improved due to the presence of the AAO layer, which created an intermediate refractive index and enhanced the waveguide's evanescent field. Our competitive hybridization sensor is an accurate and label-free testing platform applicable to the deployment of compact and sensitive virus detection strategies.
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