High-precision rapid testing of omicron SARS-CoV-2 variants in clinical samples using AI-nanopore

Area of Science:

• Virology
• Bioinformatics
• Nanotechnology

Background:

• The rapid identification of pathogenic viral variants, such as SARS-CoV-2, is crucial for mitigating pandemics, public anxiety, and economic disruption.
• An existing artificial intelligence (AI)-nanopore platform demonstrated rapid and accurate detection of the Wuhan strain of SARS-CoV-2.

Purpose of the Study:

• To investigate the capability of the AI-nanopore platform in recognizing specific viral components.
• To determine if the platform can detect and differentiate various SARS-CoV-2 variants.
• To assess the platform's performance in diagnosing SARS-CoV-2 variants in clinical samples.

Main Methods:

• The AI-nanopore platform was utilized to analyze viral samples.
• The platform's ability to distinguish between different SARS-CoV-2 variants was tested.
• Mutated SARS-CoV-2 strains expressing spike proteins from Delta and Omicron variants were analyzed.
• The platform was applied to detect Omicron variants in saliva specimens from COVID-19 patients.

Main Results:

• The AI-nanopore platform successfully distinguished between different SARS-CoV-2 variants.
• The platform identified mutated SARS-CoV-2 expressing spike proteins characteristic of Delta and Omicron variants, confirming its ability to discriminate based on spike protein mutations.
• In saliva samples from COVID-19 patients, the platform identified Omicron variants with 100% sensitivity and 94% specificity.

Conclusions:

• The AI-nanopore platform is effective in identifying and discriminating between SARS-CoV-2 variants.
• The platform demonstrates potential as a rapid diagnostic tool for detecting SARS-CoV-2 variants, including Omicron, in clinical settings.
• Further validation confirms the platform's utility in real-world diagnostic scenarios.