Synergistic dual-signal amplification aptasensor and AuNPs@TtTp COF-based SERS platform for ultrasensitive detection of SARS-CoV-2 receptor-binding domain

Early and accurate detection of the virus SARS-CoV-2, responsible for COVID-19 pandemic, is essential for controlling the disease spread. However, existing diagnostic platforms are constrained by cost, turnaround time, or limited sensitivity. Surface-enhanced Raman scattering (SERS) technique offers an attractive alternative, though conventional SERS substrates suffer from limited reproducibility and weak, non-specific analyte binding.

This study presents developing a highly sensitive and selective signal-off SERS aptasensor for detecting SARS-CoV-2 by combining a gold-nanoparticle-embedded covalent organic framework (AuNPs@TtTp COF) substrate with Au@4ATP@Ag@Au core-shell SERS tags functionalized with the virus RBD (receptor binding domain)-specific DNA aptamer. Target-induced disassembly of the tag-aptamer-COF hotspot architecture produces a concentration-dependent decrease in SERS intensity, giving a detection limit of 1.3 × 10^-17 g/mL over a dynamic range of 1 × 10^-16 - 1 × 10^-10 g/mL, with RSD values of 6.65 - 7.61% across replicate spots and substrates. Molecular dynamics simulations of three candidate aptamer-RBD complexes identifies the TZ1 model as most stable (binding free energy -57.99 kcal/mol). The aptasensor detects RBD in diluted human saliva, with results closely matching those of a commercial antigen test-kit.

By embedding gold nanoparticles within a triazine-linked COF and pairing them with dual-shell Au@4ATP@Ag@Au SERS tags, this platform achieves reproducible, ultrasensitive detection of the SARS-CoV-2 RBD, several orders of magnitude below other alternatives and outperforming previously reported SERS-based sensors for the same target. Because the design relies only on swapping the aptamer sequence to redirect target recognition, this strategy offers a readily adaptable template for rapid, low-cost diagnostics against other viral pathogens, and its performance in real saliva samples points toward a practical route from bench-scale detection to point-of-care screening.