2024

DNA-directed formation of plasmonic core-satellite nanostructures for quantification of hepatitis C viral RNA.

Chemical science Jaitpal S, Ng KW, San Juan AM, Martinez C, Phillips C, Tripathy S, Mabbott S
阅读原文 PDF DOI PubMed

组成图示

示意图生成中

传感器类型

检测对象

检测原理

检测灵敏度

效应效果

传感器的构成

中文摘要

英文摘要

Hepatitis C virus (HCV) continues to be a significant public health challenge, affecting an estimated 71 million people globally and posing risks of severe liver diseases. Despite advancements in treatments, diagnostic limitations hinder the global elimination efforts targeted by 2030. This study introduces an innovative diagnostic approach, integrating catalytic hairpin assembly (CHA) with plasmonic core-satellite gold nanoparticle (AuNP) assemblies, to enable sensitive and specific detection of HCV RNA. We optimized the stoichiometry of DNA hairpins to form highly stable three-way junctions (3WJs), minimizing non-specific reactions in an enzyme-free, isothermal amplification process. The resulting dual-transduction biosensor combines colorimetric and surface-enhanced Raman spectroscopy (SERS) techniques, utilizing the Raman reporter malachite green isothiocyanate (MGITC) for signal generation. Our system targets a conserved 23-nucleotide sequence within the HCV 5'-UTR, essential for RNA replication, facilitating pan-genotypic HCV detection that complements direct-acting antiviral strategies. We evaluated the biosensor's efficacy using fluorescence spectroscopy, native PAGE, AFM, and TEM. Findings indicate that the 60 nm core AuNPs surrounded by 20 nm satellite AuNPs achieved a ten-fold increase in sensitivity over the 10 nm satellites, detecting HCV RNA concentrations as low as 1.706 fM. This sensitivity is crucial, given the extremely low viral loads present during early infection stages. Our research demonstrates the promise of enzyme-free molecular biosensors for HCV, with the potential to provide cost-efficient, rapid, point-of-care testing, although further sensitivity enhancements are needed to address the challenges of early-stage detection.

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