Machine-Learning Single-Stranded DNA Nanoparticles for Bacterial Analysis

被引：19

作者：

Nandu, Nidhi ^{[1
]}

Smith, Christopher W. ^{[1
]}

Uyar, Taha Bilal ^{[1
]}

Chen, Yu-Sheng ^{[1
]}

Kachwala, Mahera J. ^{[1
]}

He, Muhan ^{[1
]}

Yigit, Mehmet, V ^{[1
,2
]}

机构：

[1] SUNY Albany, Dept Chem, Albany, NY 12222 USA

[2] SUNY Albany, RNA Inst, Albany, NY 12222 USA

来源：

ACS APPLIED NANO MATERIALS | 2020年 / 3卷 / 12期

基金：

美国食品与农业研究所; 美国国家卫生研究院;

关键词：

sensor array; DNA; bacterial detection; nanographene oxide (nGO); MoS2; fluorescence; GRAPHENE OXIDE; ADSORPTION; ARRAY;

D O I：

10.1021/acsanm.0c03001

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

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.

引用

收藏

页码：11709 / 11714

页数：6

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