Single-Molecule Analysis of SARS-CoV-2 Double-Stranded Polynucleotides Using Solid-State Nanopore with AI-Assisted Detection and Classification: Implications for Understanding Disease Severity
Issued Date
2023-01-01
Resource Type
eISSN
25766422
Scopus ID
2-s2.0-85182582249
Journal Title
ACS Applied Bio Materials
Rights Holder(s)
SCOPUS
Bibliographic Citation
ACS Applied Bio Materials (2023)
Suggested Citation
Alam I., Boonkoom T., Pitakjakpipop H., Boonbanjong P., Loha K., Saeyang T., Vanichtanankul J., Japrung D. Single-Molecule Analysis of SARS-CoV-2 Double-Stranded Polynucleotides Using Solid-State Nanopore with AI-Assisted Detection and Classification: Implications for Understanding Disease Severity. ACS Applied Bio Materials (2023). doi:10.1021/acsabm.3c00998 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/95542
Title
Single-Molecule Analysis of SARS-CoV-2 Double-Stranded Polynucleotides Using Solid-State Nanopore with AI-Assisted Detection and Classification: Implications for Understanding Disease Severity
Corresponding Author(s)
Other Contributor(s)
Abstract
This study utilized solid-state nanopores, combined with artificial intelligence (AI), to analyze the double-stranded polynucleotides encoding angiotensin-converting enzyme 2, receptor-binding domain, and N protein, important parts of SARS-CoV-2 infection. By examining ionic current signals during DNA translocation, we revealed the dynamic interactions and structural characteristics of these nucleotide sequences and also quantified their abundance. Nanopores of sizes 3 and 10 nm were efficiently fabricated and characterized, ensuring an optimal experimental approach. Our results showed a clear relationship between DNA capture rates and concentration, proving our method’s effectiveness. Notably, longer DNA sequences had higher capture rates, suggesting their importance for potential disease marker analysis. The 3 nm nanopore demonstrated superior performance in our DNA analysis. Using dwell time measurements and excluded currents, we were able to distinguish the longer DNA fragments, paving the way for a DNA length-based analysis. Overall, our research underscores the potential of nanopore technology, enhanced with AI, in analyzing COVID-19-related DNA and its implications for understanding disease severity. This provides insight into innovative diagnostic and treatment strategies.