期刊
ANALYTICA CHIMICA ACTA
卷 1192, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.aca.2021.339373
关键词
Antibiotics resistance gene; Detection; SERS; Siamese neural network
资金
- GACR [21-06065S]
- OP VVV Project NANOTECH ITI II [CZ.02.1.01/0.0/0.0/18_069/0010045]
- Tomsk Polytechnic University Competitiveness Enhancement Program
This study combines DNA-targeted surface functionalization, SERS measurements, and decision system to detect antibiotic susceptibility markers with high confidence, allowing manipulation with complex multicomponent samples and automatically determining the required number of samples, achieving high confidence detection of targeted ODN.
The enormous development and expansion of antibiotic-resistant bacterial strains impel the intensive search for new methods for fast and reliable detection of antibiotic susceptibility markers. Here, we combined DNA-targeted surface functionalization, surface-enhanced Raman spectroscopy (SERS) measurements, and subsequent spectra processing by decision system (DS) for detection of a specific oligonucleotide (ODN) sequence identical to a fragment of blaNDM-1 gene, responsible for beta-lactam antibiotic resistance. The SERS signal was measured on plasmonic gold grating, functionalized with capture ODN, ensuring the binding of corresponded ODNs. Designed DS consists of a Siamese neural network (SNN) coupled with robust statistics and Bayes decision theory. The proposed approach allows manipulation with complex multicomponent samples and predefine the desired detection level of confidence and errors, automatically determining the number of required spectra and samples. In constant to commonly used classification-type SNN, our method was applied to analyze samples with compositions previously unknown to DS. The detection of targeted ODN was performed with >= 99% level of confidence up to 3 x 10(-12) M limit on the background of 10(-10) M concentration of similar but not targeted ODNs. (C) 2021 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据