Colorimetric Detection of SARS-CoV-2 Using Plasmonic Biosensors and Smartphones

Area of Science:

• Nanotechnology
• Biosensing
• Point-of-care diagnostics

Background:

• Accurate and accessible detection of SARS-CoV-2 is crucial for controlling the COVID-19 pandemic.
• Existing diagnostic methods can be costly, require specialized equipment, or have limitations in speed and accessibility.

Purpose of the Study:

• To develop a low-cost, instrument-free colorimetric biosensor for sensitive and rapid detection of SARS-CoV-2.
• To validate the diagnostic accuracy and robustness of the developed biosensor for point-of-care applications.

Main Methods:

• Functionalization of gold nanoparticles (AuNPs) with polyclonal antibodies to create f-AuNPs for SARS-CoV-2 capture.
• Utilizing plasmon coupling in f-AuNPs upon virus binding, leading to intense color changes detectable by the naked eye.
• Employing dynamic light scattering, UV-vis spectroscopy, and smartphone-based image processing with machine learning for quantification and diagnosis.

Main Results:

• Achieved a low detection limit of 0.28 PFU mL⁻¹ in human saliva with high sensitivity.
• Demonstrated 100% accuracy in COVID-19 diagnosis from saliva samples using image processing and machine learning algorithms.
• Confirmed robustness against other viruses (influenza, dengue) and successful detection in river water samples without pretreatment.

Conclusions:

• The developed plasmonic biosensor offers a robust, sensitive, and accurate method for SARS-CoV-2 detection.
• The instrument-free, colorimetric approach coupled with smartphone analysis enables rapid, point-of-care diagnosis suitable for epidemiological control.
• This technology holds potential for widespread deployment in diverse settings due to its low cost and ease of use.