An IoT-enabled hybrid paper/polymer-based microfluidic device for rapid detection of Campylobacter jejuni in foods.

Abstract

Campylobacter jejuni is the leading bacterial cause of foodborne gastroenteritis worldwide and represents a major public health concern. We report an IoT-enabled hybrid paper/polymer-based microfluidic device for rapid detection of C. jejuni in food matrices. This platform integrates recombinase polymerase amplification (RPA), CRISPR/Cas12a-based sequence recognition, and lateral flow readout within a foldable paper-based architecture incorporating PDMS reservoirs. An IoT workflow was established to enable automated image capture, result classification, and centralized data transmission. Analytical performance was evaluated using both pure cultures and food samples. This assay specifically detected C. jejuni with no observed cross-reactivity among the tested strains and achieved a limit of detection of 5800 CFU mL-1 using the developed microfluidic device. In chicken breast samples, C. jejuni was reliably detected at initial inoculation levels of 100 to 103 CFU g-1 following 6-12 h of enrichment, while higher contamination levels (>103 CFU g-1) were detectable without enrichment. The complete workflow from DNA extraction to visual readout was completed in ∼1 h. By integrating microfluidic sensing, automated data interpretation, and IoT-enabled connectivity, this platform provides a practical and scalable approach for decentralized screening and rapid monitoring of C. jejuni in agri-food system.