ABSTRACT
Foodborne pathogens are of significant concern in the agrifood industry and the development of associated rapid detection and identification methods are of major importance. This paper describes the novel use of resolution-optimized prism-based surface plasmon resonance imaging (RO-SPRI) and data processing for the detection of the foodborne pathogens Listeria monocytogenes and Listeria innocua. With an imaging spatial resolution on the order of individual bacteria (2.7 ± 0.5 µm × 7.9 ± 0.6 µm) over a field of view 1.5 mm2, the RO-SPRI system enabled accurate counting of individual bacteria on the sensor surface. Using this system, we demonstrate the detection of two species of Listeria at an initial concentration of 2 × 102 CFU mL-1 in less than 7 hours. The surface density of bacteria at the point of positive detection was 15 ± 4 bacteria per mm2. Our approach offers great potential for the development of fast specific detection systems based on affinity monitoring.
ABSTRACT
Foodborne diseases are a major concern for both food industry and health organizations due to the economic costs and potential threats for human lives. For these reasons, specific regulations impose the research of pathogenic bacteria in food products. Nevertheless, current methods, references and alternatives, take up to several days and require many handling steps. In order to improve pathogen detection in food, we developed an immune-sensor, based on Surface Plasmon Resonance imaging (SPRi) and bacterial growth which allows the detection of a very low number of Listeria monocytogenes in food sample in one day. Adequate sensitivity is achieved by the deposition of several antibodies in a micro-array format allowing real-time detection. This label-free method thus reduces handling and time to result compared with current methods.
