A CRISPR/Cas12a-based digital microfluidic platform for parallel detection of foodborne pathogens.

Authors

Yinglin Wang, Yafang Wu, Xiaotian Huang, Yachen Tian, Qing Liu

Published in

Analytica chimica acta. Volume 1426. Pages 346361. Dec 08, 2026. Epub Oct 05, 2026.

Abstract

Rapid and automated on-chip detection of multiple foodborne bacterial pathogens remains challenging because conventional molecular assays require multistep liquid handling and are difficult to integrate for parallel analysis. Here, we developed an EWOD-based DMF platform integrating RPA with CRISPR/Cas12a for parallel detection of S. aureus, E. coli O157:H7, L. monocytogenes, and C. sakazakii. The 16-site DMF chip was organized into four pathogen-specific detection modules, each containing a positive control, a negative control, and two replicate sample sites, enabling programmable droplet manipulation and sequential on-chip amplification and fluorescence detection without external pumps or complex valves.
Assay conditions were systematically optimized for fluidic compatibility and CRISPR/Cas12a performance. Following off-chip sample preparation and genomic DNA extraction, the automated on-chip RPA amplification and CRISPR/Cas12a detection workflow was completed within approximately 50 min. Under these conditions, the platform achieved detection limits of 10³, 10², 10, and 10² CFU/mL for S. aureus, E. coli O157:H7, L. monocytogenes, and C. sakazakii, respectively. No apparent cross-reactivity was observed among 35 food-associated bacterial strains. In artificially contaminated milk, milk powder, and chicken samples, comparable detection limits were obtained after off-chip sample processing, despite matrix-dependent variations in fluorescence intensity.
These results demonstrate that integrating EWOD-based digital microfluidics with RPA and CRISPR/Cas12a enables rapid, parallelized, and programmable molecular detection of multiple foodborne bacterial pathogens on a compact platform. By integrating droplet manipulation, amplification, and fluorescence detection on-chip, the proposed system reduces reliance on external fluidic components and provides a promising basis for further development toward automated and integrated food-safety testing.

PMID:
42967794
Bibliographic data and abstract were imported from PubMed on 02 Nov 2026.

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