Enhanced detection of SARS-CoV-2 antibodies using guided-mode resonance biosensors: A label-free approach

This study presents an alternative approach for the label-free and highly sensitive detection of SARS-CoV-2 antibodies using Guided-Mode Resonance (GMR) biosensing technology. The GMR biosensor was optimized using two distinct protein immobilization techniques—glutaraldehyde cross-linking and EDC/NHS covalent binding —applied to a Tantalum dioxide (TaO₂) surface, with the aim of maximizing the sensor's detection capabilities. With an attempt to study surface binding capability between each immobilization technique, the TaO₂ film is prepared by optimizing surface morphology via deposition at different operation pressures, giving film formation with different surface morphology, roughness, and area. At lower pressures, the EDC/NHS immobilization method outperformed glutaraldehyde, achieving a limit of detection (LOD) of 272.4 pg mL⁻¹ at 5 mTorr TaO₂ deposition pressure. However, at 20 mTorr, glutaraldehyde exhibited superior sensitivity, with an LOD of 72.3 pg mL⁻¹, compared to 137.7 pg mL⁻¹ for EDC/NHS. These results suggest that surface roughness and morphology significantly improve protein immobilization and antibody binding efficacy. This high level of sensitivity and versatility underscores the potential of the GMR biosensor for clinical applications, such as early detection of SARS-CoV-2 antibodies, post-vaccine monitoring, and immune response evaluation in low-titer samples. The study also highlights the importance of optimizing surface pressure and immobilization techniques to enhance biosensor sensitivity. The pressure-dependent performance suggests that higher surface area prepared under higher deposition pressure facilitates more efficient protein immobilization, leading to stronger antibody binding events and improved detection limits. Overall, the GMR-based biosensor system offers a promising platform for sensitive, label-free detection of SARS-CoV-2 antibodies, with potential applications in infectious disease diagnostics and monitoring.