| Literature DB >> 34095773 |
Nidhi Nandu1, Christopher W Smith1, Taha Bilal Uyar1, Yu-Sheng Chen1, Mahera J Kachwala1, Muhan He1, Mehmet V Yigit2.
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.Entities:
Keywords: DNA; MoS2; bacterial detection; fluorescence; nanographene oxide (nGO); sensor array
Year: 2020 PMID: 34095773 PMCID: PMC8174836 DOI: 10.1021/acsanm.0c03001
Source DB: PubMed Journal: ACS Appl Nano Mater ISSN: 2574-0970