Development of nucleic acid based lateral flow assays for SARS-CoV-2 detection

Area of Science:

• Biotechnology
• Molecular Diagnostics
• Nanotechnology

Background:

• Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) remains a significant global health threat.
• Accurate and rapid detection of SARS-CoV-2 is essential for disease control.
• While real-time reverse transcriptase polymerase chain reaction (RT-PCR) is standard, alternative molecular detection methods are needed.

Purpose of the Study:

• To develop and optimize lateral flow assay (LFA) models for the molecular detection of SARS-CoV-2 N protein genes.
• To evaluate the impact of various parameters on LFA performance for viral detection.

Main Methods:

• Designed three sandwich lateral flow assay models (1A, 1B, 1.2) using gold nanoparticles as labels.
• Investigated probe concentrations on gold nanoparticles, sandwich model types, and membrane materials (M170).
• Assessed buffer efficiency and determined the limit of detection (LOD) for the target gene.

Main Results:

• Model 1B combined with the M170 membrane demonstrated optimal performance.
• Model 1.2 achieved a low limit of detection of 5 picomolar (pM) for the target gene.
• All investigated parameters significantly influenced the molecular detection capabilities of the lateral flow assays.

Conclusions:

• Optimized lateral flow assay models show promise for sensitive SARS-CoV-2 detection.
• These findings contribute to the development of nucleic acid-based LFAs for viral detection.
• The study provides a foundation for detecting SARS-CoV-2 and its mutated variants using advanced lateral flow systems.