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Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus
Masateru Taniguchi1, Shohei Minami2, Chikako Ono2,3
1The Institute of Scientific and Industrial Research, Osaka University, Ibaraki, Osaka, Japan. taniguti@sanken.osaka-u.ac.jp.
Nature Communications
|June 18, 2021
Summary
A new AI-powered nanopore technology detects novel coronaviruses, including SARS-CoV-2, without RNA extraction. This rapid, sensitive method offers accurate identification from saliva in just five minutes.
Area of Science:
- Nanotechnology
- Bioinformatics
- Infectious Disease Diagnostics
Background:
- Reverse transcription-polymerase chain reaction (RT-PCR) is the standard for SARS-CoV-2 detection but requires RNA extraction.
- Current methods can be time-consuming and complex, hindering rapid outbreak response.
Purpose of the Study:
- To develop a sensitive, rapid, and RNA-extraction-free method for detecting novel coronaviruses.
- To integrate artificial intelligence with nanopore technology for enhanced viral detection.
Main Methods:
- Developed an 'artificially intelligent nanopore' platform combining machine learning software, a high-precision current measuring instrument, and semiconducting nanopore modules.
- The system analyzes electrical signals generated as coronaviruses pass through nanopores.
- Validated the platform's ability to identify four distinct coronavirus types.
Main Results:
- The artificially intelligent nanopore accurately identified HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2.
- Achieved 90% sensitivity and 96% specificity for SARS-CoV-2 detection in saliva specimens.
- Demonstrated successful detection within a 5-minute measurement period.
Conclusions:
- The AI-nanopore platform provides a sensitive and specific method for rapid coronavirus detection.
- This approach eliminates the need for RNA extraction, simplifying the diagnostic workflow.
- Offers a scalable and cost-effective solution for emerging viral threat surveillance and control.
