Co-Occurrence of Listeria spp. and Spoilage Associated Microbiota During Meat Processing Due to Cross-Contamination Events

Abstract

A large part of foodborne outbreaks related to Listeria monocytogenes are linked to meat and meat products. Especially, recontamination of meat products and deli-meat during slicing, packaging, and repackaging is in the focus of food authorities. In that regard, L. monocytogenes persistence in multi-species biofilms is one major issue, since they survive elaborate cleaning and disinfection measures. Here, we analyzed the microbial community structure throughout a meat processing facility using a combination of high-throughput full-length 16S ribosomal RNA (rRNA) gene sequencing and traditional microbiological methods. Samples were taken at different stages during meat cutting as well as from multiple sites throughout the facility environment to capture the product and the environmental associated microbiota co-occurring with Listeria spp. and L. monocytogenes. The listeria testing revealed a widely disseminated contamination (50%; 88 of 176 samples were positive for Listeria spp. and 13.6%; 24 of 176 samples were positive for L. monocytogenes). The pulsed-field gel electrophoresis (PFGE) typing evidenced 14 heterogeneous L. monocytogenes profiles with PCR-serogroup 1/2a, 3a as most dominant. PFGE type MA3-17 contributed to the resilient microbiota of the facility environment and was related to environmental persistence. The core in-house microbiota consisted mainly of the genera Acinetobacter, Pseudomonas, Psychrobacter (Proteobacteria), Anaerobacillus, Bacillus (Firmicutes), and Chryseobacterium (Bacteroidota). While the overall microbial community structure clearly differed between product and environmental samples, we were able to discern correlation patterns regarding the presence/absence of Listeria spp. in both sample groups. Specifically, our longitudinal analysis revealed association of Listeria spp. with known biofilm-producing Pseudomonas, Acinetobacter, and Janthinobacterium species on the meat samples. Similar patterns were also observed on the surface, indicating dispersal of microorganisms from this multispecies biofilm. Our data provided a better understanding of the built environment microbiome in the meat processing context and promoted more effective options for targeted disinfection in the analyzed facility.

Keywords: Listeria monocytogenes; meat processing; microbial communities; microbiome; spoilage.

Figure 1

Occurrence of apathogenic listeria and Listeria monocytogenes during meat cutting. Number of samples positive or negative for Listeria spp. for each sampling position. Sample categories are abbreviated: “product” (P), “food contact surface” (FCS), “non-FCS” (NFCS), and “personnel” (PE).

Figure 2

Pulsed-field gel electrophoresis (PFGE) cluster analysis with restriction enzyme AscI for L. monocytogenes (n = 58) isolated during meat cutting.

Figure 3

(A) Change in alpha diversity indices of meat samples over time. Boxes indicate the interquartile range (from 75 to 25th) of the data. Whiskers extend to the most extreme value within 1.5 times interquartile range and dots represent outliers beyond that range. (B) Non-metric multidimensional scaling (nMDS) plot of Bray-Curtis distances based on 16S ribosomal RNA (rRNA) gene libraries obtained from meat samples. Each point represents values from individual libraries with colors expressing meat samples from different positions along the processing line.

Figure 4

Phylum-level classification of 16S rRNA gene sequence reads parted by sampling position and type (meat or environment). Data represent average of amplicon sequence variant (ASV) counts from replicate libraries for each category. Sample categories are abbreviated: “product” (P), “food contact surface” (FCS), “non-FCS” (NFCS), and “personnel” (PE).

Figure 5

Heatmap of the top 50 most abundant genera grouped by position and split by type. Data represent average of ASV counts from replicate 16S rRNA gene libraries for each category. Sample categories are abbreviated: “product” (P), “food contact surface” (FCS), “non-FCS” (NFCS), and “personnel” (PE).

Figure 6

Heatmap showing the correlation of individual genera between samples with or without listeria. Red color shows a positive correlation and blue color illustrates a negative correlation with the presence of listeria. The saturation of the color indicates the strength of the correlation coefficient. Only significant (p ≤ 0.05) taxa are shown.

Figure 7

Barplots of ASVs that were significantly differentially abundant (p ≤ 0.05) between meat and surface samples with and without listeria. Positive values indicate higher abundance in samples with listeria and negative values depict higher abundance in samples where listeria is absent. Significant ASVs are plotted individually and colored according to their family-level classification.