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Listeria monocytogenes is an intracellular bacterium that causes serious epidemic and sporadic food-borne illnesses in humans. Rapid and trustworthy methods are necessary for the detection of the pathogen to prevent potential food contamination. The aim of this study was to test a newly developed L. monocytogenes biosensor on actual food samples and validate its ability to detect the presence of pathogens robustly and accurately. The newly developed method uses a cell-based biosensor technology (BERA) and a portable device developed by EMBIO Diagnostics called B.EL.D, and provides results within 3 min. Tests were conducted on ready-to-eat lettuce salads, milk and halloumi cheese and the results indicate that the novel system was able to identify inoculated samples with 98%, 90%, and 91% accuracy, respectively. Furthermore, the limit of detection was determined to be as low as 0.6 log CFU mL−1 or g−1 in all food types. Classification of the samples Above or Below the detection limit was accessed through a newly developed algorithm for each food substrate. Samples were also analyzed with the ISO 11290-1:2017 and 11290-2:2017, in parallel. Thus, it was concluded that the newly developed biosensor can be a useful tool in the food supply chain, decreasing the required time for the detection of pathogens and increasing the number of tested samples before they reach the market.

A Cell-Based Biosensor System for Listeria monocytogenes Detection in Food