Rapid and Label-Free Single-Nucleotide Discrimination via an Integrative Nanoparticle–Nanopore Approach
Source abstract
Abstract
Single-nucleotide polymorphism (SNP) is an important biomarker for disease diagnosis, treatment monitoring, and development of personalized medicine. Recent works focused primarily on ultrasensitive detection, while the need for rapid and label-free single-nucleotide discrimination techniques, which are crucial criteria for translation into clinical applications, remains relatively unexplored. In this work, we developed a novel SNP detection assay that integrates two complementary nanotechnology systems, namely, a highly selective nanoparticle-DNA detection system and a single-particle sensitive nanopore readout platform, for rapid detection of single-site mutations. Discrete nanoparticle-DNA structures formed in the presence of perfectly matched (PM) or single-mismatched (SM) targets exhibited distinct size differences, which were resolved on a size-tunable nanopore platform to generate corresponding "yes/no" readout signals. Leveraging the in situ reaction monitoring capability of the nanopore platform, we demonstrated that real-time single-nucleotide discrimination of a model G487A mutation, responsible for glucose-6-phosphate dehydrogenase deficiency, can be achieved within 30 min with no false positives. Semiquantification of DNA samples down to picomolar concentration was carried out using a simple parameter of particle count without the need for sample labeling or signal amplification. The unique combination of nanoparticle-based detection and nanopore readout presented in this work brings forth a rapid, specific, yet simple biosensing strategy that can potentially be developed for point-of-care application.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Nanopore and Nanochannel Transport Studies · Advanced biosensing and bioanalysis techniques · Microfluidic and Bio-sensing Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemical and Biomolecular Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore
References (40)
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