Reduction of the microbial load in meat maturation rooms with and without alkaline electrolyzed water fumigation

Dry-aging is a process during which meat is stored within maturation chambers at low temperatures and low relative humidity, resulting in improved tenderness and flavor development. The cuts are exposed to the atmosphere by hanging them or setting them on racks in the maturation chamber without any protective packaging. Animals and humans are usually the major sources of bacterial food contamination in the meat industry, but other routes might be involved. Therefore, procedures to reduce or eliminate pathogens from surfaces are crucial for an effective hazard analysis critical control point program in the food industry and other environments. This study aimed to assess the survival of Listeria monocytogenes, Escherichia coli, Salmonella spp., and Staphylococcus aureus on the inner surface of dry aging chambers. Moreover, we tested the efficacy of alkaline electrolyzed water (REW) for its eventual application within a procedure aimed at reducing foodborne pathogens during meat storage. Environmental conditions inside the dry aging cabinet determine a reduction of circa 3 log CFU/cm2 of the considered microorganisms on the inner surface in 24 hours. Additionally, the nebulization of alkaline electrolyzed water with the smoking system increased the count reduction in 24 hours due to environmental conditions for L. monocytogenes (~1 log CFU/cm2) and for S. aureus (~2 log CFU/cm2). In this context, the use of REW can be justified for routine cleaning procedures of the surfaces, with the added value of being safe to handle, not containing environmental pollutants, and making it unnecessary to rinse surfaces due to its instability

Time-series sewage metagenomics distinguishes seasonal, human-derived and environmental microbial communities potentially allowing source-attributed surveillance

Sewage metagenomics has risen to prominence in urban population surveillance of pathogens and antimicrobial resistance (AMR). Unknown species with similarity to known genomes cause database bias in reference-based metagenomics. To improve surveillance, we seek to recover sewage genomes and develop a quantification and correlation workflow for these genomes and AMR over time. We use longitudinal sewage sampling in seven treatment plants from five major European cities to explore the utility of catch-all sequencing of these population-level samples. Using metagenomic assembly methods, we recover 2332 metagenome-assembled genomes (MAGs) from prokaryotic species, 1334 of which were previously undescribed. These genomes account for ~69% of sequenced DNA and provide insight into sewage microbial dynamics. Rotterdam (Netherlands) and Copenhagen (Denmark) show strong seasonal microbial community shifts, while Bologna, Rome, (Italy) and Budapest (Hungary) have occasional blooms of Pseudomonas-dominated communities, accounting for up to ~95% of sample DNA. Seasonal shifts and blooms present challenges for effective sewage surveillance. We find that bacteria of known shared origin, like human gut microbiota, form communities, suggesting the potential for source-attributing novel species and their ARGs through network community analysis. This could significantly improve AMR tracking in urban environments.</p

Monitoring and preventing foodborne outbreaks: are we missing wastewater as a key data source?

In 2022, the number of foodborne outbreaks in Europe increased by 43.9%, highlighting the need to improve surveillance systems and design outbreak predictive tools. This review aims to assess the scientific literature describing wastewater surveillance to monitor foodborne pathogens in association with clinical data. In the selected studies, the relationship between peaks of pathogen concentration in wastewater and reported clinical cases is described. Moreover, details on analytical methods to detect and quantify pathogens as well as wastewater sampling procedures are discussed. Few papers show a statistically significant correlation between high concentrations of foodborne pathogens in wastewater and the occurrence of clinical cases. However, monitoring pathogen concentration in wastewater looks like a promising and cost-effective strategy to improve foodborne outbreak surveillance. Such a strategy can be articulated in three steps, where the first one is testing wastewater with an untargeted method, like shotgun metagenomic, to detect microorganisms belonging to different domains. The second consists of testing wastewater with a targeted method, such as quantitative polymerase chain reaction, to quantify those specific pathogens that in the metagenomic dataset display an increasing trend or exceed baseline concentration thresholds. The third involves the integrated wastewater and clinical data analysis and modeling to find meaningful epidemiological correlations and make predictions