期刊
ACS APPLIED NANO MATERIALS
卷 3, 期 12, 页码 11709-11714出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsanm.0c03001
关键词
sensor array; DNA; bacterial detection; nanographene oxide (nGO); MoS2; fluorescence
资金
- USDA National Institute of Food and Agriculture, AFRI project [2018-67021-27973, 2017-07822]
- National Institutes of Health [1R15GM12811501]
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.
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