纳米孔
免疫分析
纳米技术
化学
计算机科学
信号(编程语言)
数字聚合酶链反应
蛋白质组学
计算生物学
纳米孔测序
定量蛋白质组学
生物系统
灵敏度(控制系统)
材料科学
分析物
DNA
核酸
费斯特共振能量转移
寡核苷酸
生物标志物
生物传感器
分子生物物理学
适体
作者
Liqun He,Breeana Elliott,Philipp Mensing,Kyle Briggs,M. Godin,Jonathan Flax,James L. McGrath,Vincent Tabard‐Cossa
标识
DOI:10.26434/chemrxiv-2025-zth1z
摘要
Digital immunoassays enable highly sensitive detection of biomolecules, offering absolute quantification rather than relying on bulk signal intensity. We adapt a digital immunoassay scheme for a nanopore sensor – a versatile platform for single-molecule counting. Current nanopore sensors have demonstrated great progress when counting nucleic acids but struggle with proteins due to variability in translocation behaviour and limited recognition strategies. While recent advancements have highlighted the promise of nanopore platforms for protein studies, precise quantification remains a challenge. Here, building on previous work, we present a nanopore-based digital immunoassay that employs gold nanoparticle-mediated molecular amplification with single-molecule readout. This approach translates protein recognition into quantifiable DNA, enabling a precise digital assay. This assay employs a DNA NanoLock probe combined with a paramagnetic bead based immunocapture, where the target proteins trigger a structural transformation of the NanoLock, converting their presence into a binary DNA-based signal. By incorporating AuNPs carrying hundreds of DNA proxy reporters, we effectively amplify the detectable signal by two orders of magnitude, significantly improving sensitivity. We validate the performance of this system by detecting glial fibrillary acidic protein (GFAP), a biomarker for traumatic brain injury (TBI) and neurodegenerative diseases, in plasma samples and demonstrate high femtomolar-level sensitivity (~40 pg/mL). Using the NanoLock probe, we further mitigate previous challenges, with reduced assay times (hours), and extended dynamic range (3-log). The self-calibrating nature of this digital approach offers robust, reproducible measurements across different nanopores, eliminating inter-device variability and paving the way towards scalable point-of-care detection.
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