Abstract
A two-dimensional nanoparticle-single-stranded DNA (ssDNA) array has been assembled for the detection of bacterial species using machine-learning (ML) algorithms. Out of 60 unknowns prepared from bacterial lysates, 54 unknowns were predicted correctly. Furthermore, the nanosensor array, supported by ML algorithms, was able to distinguish wild-type Escherichia coli from its mutant by a single gene difference. In addition, the nanosensor array was able to distinguish untreated wild-type E. coli from those treated with antimicrobial drugs. This work demonstrates the potential of nanoparticle-ssDNA arrays and ML algorithms for the discrimination and identification of complex biological matrixes.
| Original language | English |
|---|---|
| Pages (from-to) | 11709-11714 |
| Number of pages | 6 |
| Journal | ACS Applied Nano Materials |
| Volume | 3 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 24 2020 |
Keywords
- DNA
- MoS
- bacterial detection
- fluorescence
- nanographene oxide (nGO)
- sensor array
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