Fluorescence Event Counting for miRNA Detection Enabled by Surface-Confined Hybridization Chain Reaction with Integrated Optical Gain
MicroRNAs (miRNAs) are key biomarkers for disease diagnosis and biological research, yet their reliable quantification in complex samples remains challenging. Fluorescence-based detection is often limited by heterogeneous amplification efficiency and the inherent variability of intensity-based readouts, making measurements vulnerable to both biochemical and optical fluctuations. Although digital approaches such as digital PCR can mitigate some of this variability, they pose a significant barrier to access due to their reliance on specialized micro-partitioning devices and instrumentation. To address this, we developed an accessible, microscopy-based event-counting strategy. Our design integrates a microlens array for optical signal enhancement with a surface-confined hybridization chain reaction (HCR). This configuration transduces miRNA targets into spatially discrete, countable fluorescence events, enabling reproducible quantification under a unified imaging and analysis framework on a standard widefield microscope. The assay demonstrates log-log linearity from 10 fM to 1 nM and achieves detection limits of 2.36-3.34 fM for three model miRNAs (miR-21, miR-122, and miR-155). In a 50% serum matrix, it maintains accurate quantification with recoveries of 93-112%. By shifting the readout from error-prone analog intensity measurements to robust event counting, this work provides a scalable and accessible platform for miRNA profiling.
Authors
- Hu Shi (ORCID: https://orcid.org/0000-0002-5466-5783)
- Xiangmeng Qu (ORCID: https://orcid.org/0000-0002-8400-8477)
- Lianyu Lu
- Hui Yang (ORCID: https://orcid.org/0000-0002-6800-6308)
- Wei Ye (ORCID: https://orcid.org/0009-0005-1605-8922)
- Jienan Shen (ORCID: https://orcid.org/0000-0002-5544-9441)
- Tingting Zhan
- Rui Hao
Institutions
- National Sun Yat-sen University (TW)
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- Shenzhen Institutes of Advanced Technology (CN)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-08-20
- DOI
- https://doi.org/10.1021/acssensors.6c01199
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Science and Technology Foundation of Shenzhen City
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- China Postdoctoral Science Foundation
- Basic and Applied Basic Research Foundation of Guangdong Province