Issue 4, 2025

One-pot isothermal CRISPR/Dx system for specific and sensitive detection of microRNA

Abstract

MicroRNA (miRNA) is a promising biomarker for the early diagnosis of pancreatic cancer. To enable sensitive and reliable miRNA detection, we have developed a one-pot isothermal CRISPR/Dx detection system by combining rolling circle amplification (RCA) and CRISPR/Cas12a. RCA and CRISPR/Cas12a reactions are carried out in a single closed tube, bypassing the transferring step. We demonstrate the feasibility of our one-pot CRISPR/Dx system in detecting pancreatic cancer by targeting miR-25, miR-191, miR-205, and miR-1246. When applied to fluorescence- and lateral flow strip paper-based detection platforms, our one-pot CRISPR/Dx system detects synthetic miR-25 at a LOD of 6.60 fM and 500 fM, respectively. It has high targeting specificity, as shown by its ability to discriminate miR-25 with a single-base mutation and highly homologous miRNA species. It is also successfully generalized to detect other pancreatic cancer-associated miRNAs, including miR-191, miR-205, and miR-1246. Importantly, our one-pot CRISPR/Dx system enables specific and sensitive detection of endogenous miR-25 in the human pancreatic cancer cell line PANC-1. We have successfully developed a one-pot isothermal CRISPR/Dx system for detecting miRNA with high specificity and sensitivity. It is highly flexible and economical, as a common crRNA can detect different miRNAs and only requires minor modifications to the locking padlock probe. Therefore, it can potentially be translated into clinical settings and POCT for the diagnosis of various human cancers.

Graphical abstract: One-pot isothermal CRISPR/Dx system for specific and sensitive detection of microRNA

Supplementary files

Article information

Article type
Paper
Submitted
13 Sep 2024
Accepted
13 Nov 2024
First published
14 Nov 2024

Anal. Methods, 2025,17, 823-833

One-pot isothermal CRISPR/Dx system for specific and sensitive detection of microRNA

X. Li, Z. Huang, C. Lau, J. Li, M. Zou, W. Wu, X. Chen, J. Li, Y. Huang, T. Wang, Y. Li, M. Xu, X. Huang, H. Zhu and C. Yang, Anal. Methods, 2025, 17, 823 DOI: 10.1039/D4AY01695E

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