Modular CRISPR−Cas12a-Activated Gold Nanoparticle Assay for Rapid Visual Detection of Hepatocellular Carcinoma-Related miRNAs
MicroRNAs (miRNAs) are emerging biomarkers for early hepatocellular carcinoma (HCC) detection, but most CRISPR-Cas12a assays rely on reverse transcription and preamplification and often lack simple visual readouts. Here, we develop a reverse transcription-free, cleavage-guided strategy that converts miRNA recognition into visual outputs. In the presence of the target miRNA, a scaffold RNA forms an active crRNA that triggers Cas12a trans-cleavage using a preformed dsDNA activator, enabling two readout formats. In a homogeneous non-crosslinking colorimetric assay (mC-NCA), Cas12a cleavage regulates π-π-stacking-mediated gold nanoparticle (AuNP) aggregation to produce a rapid visual colorimetric response. In a heterogeneous versatile lateral flow assay (mC-vLFA), the cleavage of partially hybridized DNA-magnetic bead probes generates a target-dependent test line while maintaining a built-in control line. Using miRNA-21 and miRNA-122 as targets, mC-NCA shows calculated limits of detection (LODs) of 1.62 and 1.64 fM with a linear range of 50 fM-500 pM, whereas mC-vLFA shows calculated LODs of 1.59 and 1.40 fM with a linear range of 10 fM-10 nM. In a preliminary clinical evaluation, both formats show good agreement with reverse-transcription quantitative polymerase chain reaction (RT-qPCR) and clinical assessment while enabling faster detection with minimal instrumentation. Overall, this dual-readout platform couples RT-free CRISPR-Cas12a miRNA recognition with cleavage-directed visual signal transduction, enabling rapid and low-instrument-dependence CRISPR diagnostics for miRNAs.
Authors
- J Y Chen
- Lingxin Chen (ORCID: https://orcid.org/0000-0002-3764-3515)
- Chengwei Liang (ORCID: https://orcid.org/0000-0001-5347-6019)
- Zhiyang Zhang (ORCID: https://orcid.org/0000-0001-8274-1272)
- Hongxiao Sun
- Xiaokun Wang (ORCID: https://orcid.org/0000-0003-3982-1394)
- Yujie Feng
- Rui Wang
- Yinghui Sun
Institutions
- Qingdao University (CN)
- Qingdao University of Science and Technology (CN)
- Shaoxing University (CN)
- Chinese Academy of Sciences (CN)
- Yantai Institute of Coastal Zone Research (CN)
- Affiliated Hospital of Qingdao University (CN)
- Institute for Advanced Study (DE)
- Intelligent Health (United Kingdom) (GB)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-06-09
- DOI
- https://doi.org/10.1021/acssensors.6c00916
- Primary Topic
- CRISPR and Genetic Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province
- Key Technology Research and Development Program of Shandong