Viability Differentiation Improves the Diagnostic Potential of 16S rRNA Gene Sequencing in Ready-to-Eat Meat Manufacturing
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Molecular-based microbiological approaches have become valuable tools for the food industry. However, even the most advanced molecular techniques are limited in their ability to differentiate based on viability creating the potential for biased results when applied to the food industry. The objective of this study was to generate a viable microbial bio-map of a commercial ready-to-eat (RTE) meat manufacturing process and assess its utility as a diagnostic tool. Product samples were collected from a commercial RTE meat manufacturing facility at various locations throughout processing. Samples were homogenized and aliquoted for culture-based microbial isolation and 16S rRNA gene sequencing. Homogenates were split into pairs and subject to either no treatment (Control) or treated with 25 μM PMAxx (PMA) to remove free and non-viable cellular DNA. Overall, PMA treatment resulted in a less rich microbial community compared to Control samples. Paired analysis revealed that the impact of PMA varied by location with the greatest effects being observed at the beginning and end of manufacturing. Both Control and PMA treated samples identified a shift in the microbial population after thermal processing; however, only PMA treated samples identified a secondary shift in the microbial population occurring after slicing. Taxonomic analysis identified Lactobacillus as a predominant genera in sliced and packaged products. These results were further confirmed by the identification of Lactobacillus sakei on packaged product using a culture-based approach. These results suggest PMA treatment provides a higher level of sequencing resolution by removing background DNA.
Importance
Microbial bio-mapping is a valuable tool for the meat and poultry industry to assess process control and evaluate the efficacy of intervention systems. In recent years it has become more common to incorporate the use of molecular techniques, such as qPCR and 16S rRNA, to quantitatively track target pathogens and gain a more holistic understanding of the microbial community throughout processing. One major limitation we face when applying these DNA-based techniques to the food industry is their inability to differentiate between DNA from viable versus non-viable cells, which may result in the false identification of pathogenic or spoilage microorganisms and bias microbiota results. To practically apply this technology in a ready-to-eat meat manufacturing setting, it is crucial to develop and validate strategies that are capable of differentiating between viable and non-viable cellular DNA.
