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Diagnostic Optical Sequencing

delete2019-09-09
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L
Lee E. Korshoj
P
Prashant Nagpal *
DOI:10.1021/acsami.9b12568delete
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摘要

摘要

En 中文
Advances in precision medicine require high-throughput, inexpensive, point-of-care diagnostic methods with multiomics capability for detecting a wide range of biomolecules and their molecular variants. Optical techniques have offered many promising advances toward such diagnostics. However, the inability to squeeze light with several hundred nanometer wavelengths into angstrom-scale volume for single-nucleotide measurements has hindered further progress. This limitation has been circumvented by analyzing the relative nucleobase content with Raman spectroscopy, in an optical sequencing method. Here, we performed optical sequencing measurements on positively charged silver nanoparticles to achieve 93.3% accuracy for predicting nucleobase content in label-free DNA k-mer blocks (where k = 10) as well as measurements on RNA and chemically modified nucleobases for extensions to transcriptomic and epigenetic studies. Our high-accuracy measurements were then used with a content-scoring database searching algorithm to correctly identify a beta-lactamase gene from the MEGARes antibiotic resistance database and confirm the Pseudomonas aeruginosa pathogen of origin from <12 block content measurements (<15% coverage) of the gene. These results prove the feasibility of an optical sequencing platform as a diagnostic method. With the versatile range of available plasmonic substrates offering simple data acquisition, varying resolution (single-molecule to the ensemble), and multiplexing, this optical sequencing platform has potential as the rapid, cost-effective method needed for broad-spectrum biomarker detection.
Keyword:
optical sequencing
high-throughput diagnostics
biomarker detection
multidrug-resistant bacteria
Raman spectroscopy
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期刊

ACS Applied Materials and Interfaces 封面图
ACS Applied Materials and Interfaces
IF:
8.2
论文数:
6.1W
被引数:
38.7W

机构

University of Colorado System 封面图
University of Colorado System
学者数:
6.3W
论文数: 5.5W
被引数: 1.8K
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