The role of the accompanying microbiota in the presence of Listeria monocytogenes on meat processing surfaces is not yet understood, especially in industrial production conditions. In this study, 300 conveyor belt samples from the cutting room of a swine slaughterhouse were collected during production. The samples were subjected to the detection of L. monocytogenes. Recovered strains were characterized by serogrouping-PCR, InlA Sanger sequencing and for their ability to form biofilm. A selection of isolates was compared with core genome multi-locus sequence typing analysis (cgMLST). The sequencing of the V4 region of the 16S RNA gene of the microorganisms harvested from each sample was carried out in parallel using the Illumina MiSeq platform. Diversity analyses were performed and MaAsLin analysis was used to assess the link between L. monocytogenes detection and the surrounding bacteria. The 72 isolates collected showed a low genetic diversity and important persistence characteristics. L. monocytogenes isolates were not stochastically distributed on the surfaces: the isolates were detected on three out of six production lines, each associated with a specific meat cut: the half carcasses, the bostons and the picnics. MaAsLin biomarker analysis identified the taxa Veillonella (p ≤ 0.0397) as a bacterial determinant of the presence of L. monocytogenes on processing surfaces. The results of this study revealed a heterogenous contamination pattern of the processing surfaces by L. monocytogenes and targeted a bacterial indicator of the presence of the pathogen. These results could lead to a better risk assessment of the contamination of meat products.

The microorganisms found on fresh, raw meat cuts at a slaughterhouse can influence the meat’s safety and spoilage patterns along further stages of processing. However, little is known about the general microbial ecology of the production environment of slaughterhouses. We used 16s rRNA sequencing and diversity analysis to characterize the microbiota heterogeneity on conveyor belt surfaces in the cutting room of a swine slaughterhouse from different production lines (each associated with a particular piece/cut of meat). Variation of the microbiota over a period of time (six visits) was also evaluated. Significant differences of alpha and beta diversity were found between the different visits and between the different production lines. Bacterial genera indicative of each visit and production line were also identified. We then created random forest models that, based on the microbiota of each sample, allowed us to predict with 94% accuracy to which visit a sample belonged and to predict with 88% accuracy from which production line it was taken. Our results suggest a possible influence of meat cut on processing surface microbiotas, which could lead to better prevention, surveillance, and control of microbial contamination of meat during processing.

It is profitable to export fresh meat overseas, where it is often regarded as a premium commodity. Meeting this demand for fresh meat, however, necessitates long export times, during which uncontrolled temperature increases can affect the microbiological quality of the meat and thereby, reduce shelf life or compromise food safety. To study the impact of temperature deviations on microbial community composition and diversity, we used 16S rRNA gene sequencing for Listeria monocytogenes and Salmonella spp. detection to describe the surface microbiota of eight batches of vacuum-packed loins stored at −1.5 °C (control) for 56 days and subjected to a 2 °C or 10 °C temperature deviation for a few hours (mimicking problems regularly encountered in the industry) at day 15 or 29. The presence of pathogens was negligible. The applied temperature deviations were not associated with different microbiota. Sequencing analysis showed the presence of Yersinia, an unexpected pathogen, and relative abundance increased in the groups subjected to temperature deviations. Over time, Lactobacillales_unclassified genus became the main constituent of the microbiota of vacuum-packed pork loins. Although the microbiota of the eight batches appeared similar at the beginning of storage, differences were revealed after 56 days, suggesting unequal aging of the microbiota.