Abstract
Microbial pathogens may be present in different types of foods, and hence the development of novel methods to assure consumers' safeness is of great interest. Molecular methods are known to provide sensitive and rapid results; however, they are typically targeted approaches. In recent years, the advent of non-targeted approaches based on next-generation sequencing (NGS) has emerged as a rational way to proceed. This technology allows for the detection of several pathogens simultaneously. Furthermore, with the same set of data, it is possible to characterize the microorganisms in terms of serotype, virulence, and/ or resistance genes, among other molecular features. In the current study, a novel method for the detection of Listeria monocytogenes based on the "quasimetagenomics" approach was developed. Different enrichment media and immunomagnetic separation (IMS) strategies were compared to determine the best approach in terms of L. monocytogenes sequences generated from smoked salmon samples. Finally, the data generated were analyzed with a user-friendly workflow that simultaneously provided the species identification, serotype, and antimicrobial resistance genes. The new method was thoroughly evaluated against a culture-based approach, using smoked salmon inoculated with L. monocytogenes as the matrix of choice. The sequencing method reached a very low limit of detection (LOD50, 1.2 CFU/ 25 g) along with high diagnostic sensitivity and specificity (100%), and a perfect correlation with the culture-based method (Cohen's k = 1.00). Overall, the proposed method overcomes all the major limitations reported for the implementation of NGS as a routine food testing technology and paves the way for future developments taking its advantage into consideration.