Spatiotemporal Distribution of the Environmental Microbiota in Food Processing Plants as Impacted by Cleaning and Sanitizing Procedures: the Case of Slaughterhouses and Gaseous Ozone

Abstract

Microbial complexity and contamination levels in food processing plants heavily impact the final product fate and are mainly controlled by proper environmental cleaning and sanitizing. Among the emerging disinfection technologies, ozonation is considered an effective strategy to improve the ordinary cleaning and sanitizing of slaughterhouses. However, its effects on contamination levels and environmental microbiota still need to be understood. For this purpose, we monitored the changes in microbiota composition in different slaughterhouse environments during the phases of cleaning/sanitizing and ozonation at 40, 20, or 4 ppm. Overall, the meat processing plant microbiota differed significantly between secondary processing rooms and deboning rooms, with a greater presence of psychrotrophic taxa in secondary processing rooms because of their lower temperatures. Cleaning/sanitizing procedures significantly reduced the contamination levels and in parallel increased the number of detectable operational taxonomic units (OTUs), by removing the masking effect of the most abundant human/animal-derived OTUs, which belonged to the phylum Firmicutes Subsequently, ozonation at 40 or 20 ppm effectively decreased the remaining viable bacterial populations. However, we could observe selective ozone-mediated inactivation of psychrotrophic bacteria only in the secondary processing rooms. There, the Brochothrix and Pseudomonas abundances and their viable counts were significantly affected by 40 or 20 ppm of ozone, while more ubiquitous genera like Staphylococcus showed a remarkable resistance to the same treatments. This study showed the effectiveness of highly concentrated gaseous ozone as an adjunct sanitizing method that can minimize cross-contamination and so extend the meat shelf life.IMPORTANCE Our in situ survey demonstrates that RNA-based sequencing of 16S rRNA amplicons is a reliable approach to qualitatively probe, at high taxonomic resolution, the changes triggered by new and existing cleaning/sanitizing strategies in the environmental microbiota in human-built environments. This approach could soon represent a fast tool to clearly define which routine sanitizing interventions are more suitable for a specific food processing environment, thus limiting the costs of special cleaning interventions and potential product loss.

Keywords: RNA-based surveillance; environmental microbiota; gaseous ozone; meat processing plants; spoilage bacteria.

FIG 1

(a) Stacked bar plots showing the microbiota composition (relative abundance) in phylum, class, and family taxon ranks, with a color coding key; samples are grouped according to the origin (plant and room type) and then according to the temporal phase (BC, ACS, or AOT). (b) Venn diagram displaying the number of shared OTUs at the genus level (or the highest taxonomic rank available when genus determination was not achievable) among the four environments considered (A-DR, A-PR, B-PR, and C-DR). (c) Box plots displaying the logarithmically transformed relative abundances of core OTUs in the four environments; Kruskal-Wallis test P values are displayed, and different box plot colors highlight significantly different abundances (P < 0.05 [FDR adjusted], Kruskal-Wallis and Wilcoxon tests).

FIG 2

Co-occurrence networks of bacterial oligotypes belonging to Achromobacter, Acinetobacter, Psychrobacter, Pseudomonas, Propionibacterium, Carnobacterium, Streptococcus, and Staphylococcus. Each network is based on the log-transformed relative abundance matrix of each genus, and the edges represent significant positive correlations (co-occurrence) between the oligotypes (nodes) by means of Spearman’s correlations (rho > 0.6; FDR, P < 0.001). Nodes were made proportional to the weighted degree (total occurrence of an oligotype in the whole data set) and are colored in relation to the species of belonging. Edges were made proportional to the Spearman’s rho value. The M and D values shown in the box represent the modularity (clustering coefficient) and density (calculated using the ratio of the number of edges) of each genus-based network.

FIG 3

TVCs detected in the four environments (A-DR, A-PR, B-PR, and C-DR) across the three temporal phases, i.e., BC, ACS, and AOT performed at 40 ppm (A-DR and A-PR), 20 ppm (B-PR), or 4 ppm (C-DR) of ozone (concentrations used are displayed for each environment). Box plot colors highlight significant differences (P < 0.05 [FDR adjusted], Kruskal-Wallis and Wilcoxon tests) among the TVCs of the three temporal phases (BC, ACS, and AOT).

FIG 4

(a and b) Box plots displaying abundance decreases of the core OTUs (a) and the variations of α-diversity measures (b) that occurred in each environment before (BC) (blue) and after (ACS) (orange) the cleaning/sanitizing phase. Asterisks highlight significant differences (FDR-adjusted P value from Wilcoxon’s test); *, 0.05; **, 0.01; ***, 0.001. (c) PCoA chart displaying the weighted UniFrac distance matrix (β-diversity) of the environment PR of plant A before (BC) and after (ACS) cleaning/sanitizing procedures; BC and ACS are different communities (P < 0.001 [FDR adjusted], ANOSIM and Adonis tests).

FIG 5

(a) Pseudo-heatmap summarizing the abundance variations of the 10 core OTUs (>50% of the total abundance in >80% of the samples) occurred during the ozone treatments. Asterisks highlight significant decreases in relative abundances in each environment after ozone treatment at 40, 20, or 4 ppm (FDR-adjusted P value from Wilcoxon’s test). *, 0.05; **, 0.01; ***, 0.001. (b) Viable counts of Brochothrix, Pseudomonas, and Staphylococcus before (ACS) and after (AOT 20) the 20-ppm ozonation carried out in the environment B-PR; box plot colors highlight significant differences between ACS and AOT 20 counts (P < 0.05 [FDR adjusted], Wilcoxon’s test).