High-Throughput 16S rRNA Sequencing to Assess Potentially Active Bacteria and Foodborne Pathogens: A Case Example in Ready-to-Eat Food

Technologies to detect the entire bacterial diversity spectra and foodborne pathogens in food represent a fundamental advantage in the control of foodborne illness. Here, we applied high-throughput 16S rRNA sequencing of amplicons obtained by PCR and RT-PCR from extracted DNA and RNA targeting the entire bacterial community and the active bacterial fraction present in some of the most consumed and distributed ready-to-eat (RTE) salad brands in Europe. Customer demands for RTE food are increasing worldwide along with the number of associated foodborne illness and outbreaks. The total aerobic bacterial count in the analyzed samples was in the range of 2–4 × 106 CFU/g (SD ± 1.54 × 106). Culture validated methods did not detect Salmonella spp., Escherichia coli, and other fecal coliforms. 16S rRNA gene Illumina next-generation sequencing (NGS) data were congruent with these culture-based results and confirmed that these and other well-known foodborne bacterial pathogens, such as Listeria, were not detected. However, the fine-resolution of the NGS method unveiled the presence of the opportunistic pathogens Aeromonas hydrophyla and Rahnella aquatilis (relative frequency of 1.33–7.33%) that were metabolically active in addition to non-pathogenic, active members of Yersinia spp. (relative frequency of 0.0015–0.003%). The common ail and foxA marker genes of Yersinia enterocolitica were not detected by qPCR. Finally, our NGS data identified to non-pathogenic Pseudomonas spp. as the most abundant and metabolically active bacteria in the analyzed RTE salads (53–75% of bacterial abundance). Our data demonstrate the power of sequencing, in parallel, both 16S rRNA and rDNA to identify and discriminate those potentially and metabolically active bacteria and pathogens to provide a more complete view that facilitates the control of foodborne diseases, although further work should be conducted to determine the sensitivity of this method for targeting bacteria.

This work was supported by the Spanish Ministry of Economy and Competitiveness (ref. RTI2018-094248-B-I00) and the Gordon and Betty Moore Foundation (grant 5334).