The detection of pathogenic microorganisms in foods remains a challenging since the safety of foodstuffs has to be ensured by the food producing companies. Conventional methods for the detection and identification of bacteria mainly rely on specific microbiological and biochemical identification. Biomolecular methods, are commonly used as a support for traditional techniques, thanks to their high sensitivity, specificity and not excessive costs. However, new methods like biosensors for example, can be an exciting alternative to the more traditional tecniques for the detection of pathogens in food. In this study we report Salmonella enterica serotype Enteritidis DNA detection through a novel class of label-free biosensors: microcantilevers (MCs). In general, MCs can operate as a microbalance and is used to detect the mass of the entities anchored to the cantilever surface using the decrease in the resonant frequency. We use DNA hybridization as model reaction system and for this reason, specific single stranded probe DNA of the pathogen and three different DNA targets (single-stranded complementary DNA, PCR product and serial dilutions of DNA extracted from S. Enteritidis strains) were applied. Two protocols were reported in order to allow the probe immobilization on cantilever surface: i) MC surface was functionalized with 3-aminopropyltriethoxysilane and glutaraldehyde and an amino-modified DNA probe was used; ii) gold-coated sensors and thiolated DNA probes were used in order to generate a covalent bonding (Th-Au). For the first one, measures after hybridization with the PCR product showed related frequency shift 10 times higher than hybridization with complementary probe and detectable signals were obtained at the concentrations of 103 and 106 cfu/mL after hybridization with bacterial DNA. There are currently optimizations of the second protocol, where preliminary results have shown to be more uniform and therefore more precise within each of the three hybridizations.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.