Clinical validation of SERS metasurface SARS-CoV-2 biosensor

Bilgin, Buse and Torun, Hülya and Ilgü, Müslüm and Yanık, Cenk and Batur, Sükrü Numan and Çelik, Süleyman and Öztürk, Meriç and Dogan, Özlem and Ergönül, Önder and Solaroglu, Ihsan and Can, Füsun and Onbasli, Mehmet Cengiz (2022) Clinical validation of SERS metasurface SARS-CoV-2 biosensor. In: Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry, Virtual, Online

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The real-Time polymerase chain reaction (RT-PCR) analysis using nasal swab samples is the gold standard approach for COVID-19 diagnosis. However, due to the high false-negative rate at lower viral loads and complex test procedure, PCR is not suitable for fast mass screening. Therefore, the need for a highly sensitive and rapid detection system based on easily collected fluids such as saliva during the pandemic has emerged. In this study, we present a surface-enhanced Raman spectroscopy (SERS) metasurface optimized with genetic algorithm (GA) to detect SARS-CoV-2 directly using unprocessed saliva samples. During the GA optimization, the electromagnetic field profiles were used to calculate the field enhancement of each structure and the fitness values to determine the performance of the generated substrates. The obtained design was fabricated using electron beam lithography, and the simulation results were compared with the test results using methylene blue fluorescence dye. After the performance of the system was validated, the SERS substrate was tested with inactivated SARS-CoV-2 virus for virus detection, viral load analysis, cross-reactivity, and variant detection using machine learning models. After the inactivated virus tests are completed, with 36 PCR positive and 33 negative clinical samples, we were able to detect the SARS-CoV-2 positive samples from Raman spectra with 95.2% sensitivity and specificity.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: COVID-19; Genetic algorithm; Metasurface; Oligonucleotide; Plasmonics; Raman; Surface-enhanced raman spectroscopy
Divisions: Sabancı University Nanotechnology Research and Application Center
Depositing User: Cenk Yanık
Date Deposited: 22 Aug 2022 13:38
Last Modified: 22 Aug 2022 13:38

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