A Cascaded RPA-SDA Amplification Strategy on a Sliding Microfluidic Chip for the Ultrasensitive and Rapid Detection of Shigella
In this study, a sliding microfluidic biosensor integrating RPA-SDA cascaded amplification was developed for the rapid, visual detection of <i>Shigella</i>. A novel RPA primer targeting the specific <i>ipaH</i> gene was designed to include a 5'-end G-quadruplex (G4) sequence and the complementary sequence of an Nt.BstNBI endonuclease recognition site. The RPA product templates a subsequent SDA reaction, generating abundant G4 structures that form peroxidase-mimicking DNAzymes with hemin, catalyzing a TMB reaction that produces a distinct blue color for visual readout (on-chip detection at OD<sub>370</sub>, distinct from conventional tube assays at OD<sub>450</sub>). The core on-chip detection process was completed within 13 min (10 min for SDA and 3 min for color development), achieving a limit of detection of 3.5 × 10<sup>-4</sup> ng/μL for <i>Shigella</i> genomic DNA. This timing explicitly excludes the preceding, off-chip steps of nucleic acid extraction and RPA amplification. Validation using spiked lettuce samples confirmed the platform's high specificity and sensitivity. This work establishes a proof-of-concept for a portable screening tool, highlighting its potential for on-site food safety applications. However, further validation in diverse food matrices and under real-world field conditions is required to fully establish its practical utility.
Authors
- Guorong Fan
- Ying Shang (ORCID: https://orcid.org/0000-0001-6655-2877)
- Nan Yang (ORCID: https://orcid.org/0000-0003-3842-7125)
- Tao Xu
- Wentao Xu (ORCID: https://orcid.org/0000-0002-2302-8490)
- Yunlong Zhang (ORCID: https://orcid.org/0000-0002-2447-9138)
- Nali Zhou
Institutions
- Kunming University of Science and Technology (CN)
- China Agricultural University (CN)
Publication Details
- Journal
- Foods
- Published
- 2025-11-14
- DOI
- https://doi.org/10.3390/foods14223891
- Citations
- 1
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.67
Funders
- National Natural Science Foundation of China
- Putian University