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• W2972570795 abstract "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 β-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." @default.
• W2972570795 created "2019-09-19" @default.
• W2972570795 creator A5022537162 @default.
• W2972570795 creator A5078843899 @default.
• W2972570795 date "2019-09-09" @default.
• W2972570795 modified "2023-10-17" @default.
• W2972570795 title "Diagnostic Optical Sequencing" @default.
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• W2972570795 doi "https://doi.org/10.1021/acsami.9b12568" @default.
• W2972570795 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31496215" @default.
• W2972570795 hasPublicationYear "2019" @default.
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