Microbial food spoilage is responsible for a considerable amount of waste and can cause food-borne diseases in humans, particularly in immunocompromised individuals and children. Therefore, preventing microbial food spoilage is a major concern for health authorities, regulators, consumers, and the food industry. However, the contamination of food products is difficult to control because there are several potential sources during production, processing, storage, distribution, and consumption, where microorganisms come in contact with the product. Here, we use high-throughput full-length 16S rRNA gene sequencing to provide insights into bacterial community structure throughout a pork-processing plant. Specifically, we investigated what proportion of bacteria on meat are presumptively not animal-associated and are therefore transferred during cutting via personnel, equipment, machines, or the slaughter environment. We then created a facility-specific transmission map of bacterial flow, which predicted previously unknown sources of bacterial contamination. This allowed us to pinpoint specific taxa to particular environmental sources and provide the facility with essential information for targeted disinfection. For example, Moraxella spp., a prominent meat spoilage organism, which was one of the most abundant amplicon sequence variants (ASVs) detected on the meat, was most likely transferred from the gloves of employees, a railing at the classification step, and the polishing tunnel whips. Our results suggest that high-throughput full-length 16S rRNA gene sequencing has great potential in food monitoring applications.

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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.

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Contamination of beer arises in 50% of all events at the late stages of production, the filling area. Hereby, biofilms, being consortia of microorganisms embedded in a matrix composed of extracellular polymeric substances, play a critical role. To date, most studies have focused on the presence of (biofilm forming) microorganisms within this filling environment. Our aim was to characterize the microbial status as well as the presence of possible biofilms at a can filling line for beer by determining the presence of microorganisms and their associated matrix components (carbohydrates, proteins and extracellular DNA (eDNA)). Targeted qPCR confirmed the presence of microorganisms at ten sites during operation and three after cleaning (from 23 sites respectively). The evaluation of carbohydrates, eDNA and proteins showed that 16 sites were positive for at least one component during operation and four after cleaning. We identified one potential biofilm hotspot, namely the struts below the filler, harboring high loads of bacteria and yeast, eDNA, carbohydrates and proteins. The protein pattern was different than that of beer. This work deepens our understanding of biofilms and microorganisms found at the filling line of beer beverages at sites critical for production.

Safe and hygienic water distribution is essential for maintaining product quality and safety. It is known that biofilms alter the appearance and microbial quality of water along the distribution chain. Yet, biofilms in water hoses throughout the food processing environment have not been investigated in detail. Here, microbial communities from water hoses and other environmental sites in contact with water, in addition to the source water itself, were studied in the meat processing environment. Biofilms were present in all water hoses as determined by the presence of bacterial DNA and biofilm matrix components (carbohydrates, extracellular DNA, and proteins). The microbial community of the biofilms was dominated by Proteobacteria, represented mainly by Comamonadaceae and Pseudoxanthomonas. Moreover, genera that are associated with an intracellular lifestyle (e.g., Neochlamydia and Legionella) were present. Overall, the microbial community of biofilms was less diverse than the water microbial community, while those from the different sample sites were distinct from each other. Indeed, only a few phyla were shared between the water hose biofilm and the source water or associated environmental samples. This study provides first insights towards understanding the microbiota of water hose biofilms in the food processing environment.

Microbial food spoilage is responsible for a considerable amount of waste and can cause food-borne diseases in humans, particularly in immunocompromised individuals and children. Therefore, preventing microbial food spoilage is a major concern for health authorities, regulators, consumers, and the food industry.However, the contamination of food products is difficult to control because there are several potential sources during production, processing, storage, distribution, and consumption, where microorganisms come in contact with the product. Here, we conduct the first study that uses high-throughput full-length 16S rRNA gene sequencing to provide novel insights into bacterial community structure throughout a pork processing plant. Specifically, we investigated what proportion of bacteria on meat are not animal-associated and are therefore transferred during cutting via personnel, equipment, machines, or the slaughter environment. We then created a facility-specific transmission map of bacterial flow which revealed previously unknown sources of bacterial contamination. This allowed us to pinpoint specific taxa to particular environmental sources and provide the facility with essential information for targeted disinfection. For example, Moraxella spp., a prominent meat spoilage organism which was one of the most abundant amplicon sequence variants (ASVs) detected on the meat, was most likely transferred from the gloves of employees, a railing at the classification step, and the polishing tunnel whips. Finally, we provide evidence that 1000 sequences per sample provides a reasonable sequencing depth for microbial source tracking in food processing, suggesting that this approach could be implemented in regular monitoring systems. BackgroundAs the world population is expected to rise to 9.8 billion by 2050, the global demand for food will increase by approximately 70 % in order to satisfy human needs. Resolving this issue, while also reducing greenhouse gas emissions and protecting valuable ecosystems is one of the greatest challenges of our era. Food security experts estimate that 46 % of the required additional food demand can be achieved by increasing food production, whereas the remaining proportion needs to be attained through sustaining the productive capacity (34 %) and better food demand management (20 %) (Keating et al.

Traditionally, the microbiological status of meat is determined by culture-based techniques, although many bacteria are not able to grow on conventional media. The aim of this study was to obtain quantitative data on total bacterial cell equivalents, as well as taxa-specific abundances, on carcass surfaces during pig slaughter using quantitative real-time PCR. We evaluated microbial contamination patterns of total bacteria, Campylobacter, Escherichia coli, Lactobacillus group, Listeria monocytogenes, Salmonella, and Pseudomonas species throughout slaughtering and on different carcass areas. In addition, we compared contamination levels of breeding sow carcasses with fattening pig carcasses, and we assessed the efficacy of carcass polishing machines under two water amount conditions. Our results demonstrate that relevant meat-spoilage organisms show similar contamination patterns to total bacteria. The highest bacterial load was detected in the stunning chute (4.08 × 105 bacterial cell equivalents per cm2) but was reduced by 3 log levels after singeing and polishing (P < 0.001). It increased again significantly by a 4.73-fold change until the classification step. Levels of Campylobacter, Lactobacillus, and Pseudomonas species and of E. coli followed a similar trend but varied between 0 and 2.49 × 104 bacterial cell equivalents per cm2. Microbial levels did not vary significantly between sampled carcass areas for any analyzed taxa. Running the polishing machine with a low water amount proved to be less prone to microbial recontamination compared with a high water amount (17.07-fold change, P = 0.024). In the studied slaughterhouse, slaughter of breeding sows did not produce microbiologically safe meat products (>104 cells per cm2) and the implementation of specific hazard analysis critical control point systems for the slaughter of breeding sows should be considered. A larger cohort from different abattoirs is needed to confirm our results and determine whether this is universally valid.