A microfluidic biosensor for rapid and automatic detection of Salmonella using metal-organic framework and Raspberry Pi

Rapid screening of pathogenic bacteria contaminated foods is crucial to prevent food poisoning. However, available methods for bacterial detection are still not ready for in-field screening because culture is time-consuming; PCR requires complex DNA extraction and ELISA lacks sensitivity. In this study, a microfluidic biosensor was developed for rapid, sensitive and automatic detection of Salmonella using metal-organic framework (MOF) NH2-MIL-101(Fe) with mimic peroxidase activity to amplify biological signal and Raspberry Pi with self-developed App to analyze color image. First, the target bacteria were separated and concentrated with the immune magnetic nanobeads (MNBs), and labeled with the immune MOFs to form MNB-Salmonella-MOF complexes. Then, the complexes were used to catalyze colorless o-phenylenediamine and H2O2 to produce yellow 2,3-diaminophenazine (DAP). Finally, the image of the catalysate was collected under the narrow-band blue light and analyzed using the Raspberry Pi App to determine the bacterial concentration. The experimental results showed that this biosensor was able to detect Salmonella Typhimurium from 1.5 × 101 to 1.5 × 107 CFU/mL in 1 h with the lower detection limit of 14 CFU/mL. The mean recovery for Salmonella in spiked chicken meats was ~112%. This biosensor integrating mixing, separation, labelling and detection onto a single microfluidic chip has demonstrated the merits of automatic operation, fast reaction, less reagent and small size, and is promising for in-field detection of foodborne bacteria.