MAPPING THE MICROBIAL CONTAMINATION IN FOOD AND FOOD PROCESSING ENVIRONMENT

The quality and food safety has always been an object of study for microbiology. For this reason, research is focused on both microorganisms of technological interest responsible for metabolic processes, such as fermentation, and important to define the sensory characteristics of the finished product, and food-spoilers microorganisms, that are responsible for the food spoilage. The microorganisms that inhabit the food processing environments play also an important role, since cross-contamination phenomena can occur during the processing phases. Monitoring the presence of spoilage microorganisms in food-processing environment, can be very usefull in order to prevent the spread along the processing chain and consequently the transition to the finished product, preserving the food quality and safety. The methodological approach to study the microbiota has changed and microbial species and strains can be identified and monitored with higher levels of speed, reliability and sensitivity The aim of the present work was the study of the microbiota of different dairy manufactures, fresh meat and surface samples from the related processing environments by using the new culture-independent method based on high-performance sequencing (high-throughput sequencing, HTS). Different ecosystems were studied, in order to investigate the microbiota composition and the specific role of the microorganisms in each food matrix and the possible overlap with the microbiota on utilized tools, equipment and processing surfaces. Several kind of dairy manufactures and meat, as well as environmental samples from surfaces and associated processing tools were taken into account. Moreover, a novel approach for of the identification of oligotypes present in foods and environments was used, focusing on the Pseudomonas genus. Oligotyping is a computational method that allows to explain the ecologically significant differences between closely related organisms, going over the species identification. Thanks to the different HTS approaches it was possible to obtain a complete image of the typical microbiome of certain food matrices and their processing environments. In the present study the presence of a selected core microbiota was identified, consisting of a few species well adapted to the considered environment. However a different distribution and varable relative abindance among the samplkes was observed between food and environment, and can be speculated that there is an influence by the environmental microbiota on the food matrices. The high-throughput sequencing demonstred to be a suitable approach to the study of the microbiota of dairy manifactures and meat, as well as for environmental samples from food processing surfaces, allowing to monitor the microbiota during the various stages of production. The characterization of the environmental microbiota and the understanding of the correlation between ecological factors and the microbiota of food are of crucial importance for the control of food quality and safety. Getting a description of the surface microbiota in the food processing plant and monitoring changes over time could represent a good start point to map the sources of contamination. Also understand the composition of the microbiota calling it beyond the species identification is a crucial step to investigate the diversity of microorganisms recognized as spoilers in the food industry. In this context, the dell'Oligotyping use allows in-depth analysis of microbial consortia in food and related environments

Processing environment and ingredients are both sources of Leuconostoc gelidum, which emerges as a major spoiler in ready-to-eat meals

Mesophilic and psychrotrophic organism viable counts, as well as high-throughput 16S rRNA gene-based pyrosequencing, were performed with the aim of elucidating the origin of psychrotrophic lactic acid bacteria (LAB) in a ready-to-eat (RTE) meal manufacturing plant. The microbial counts of the products at the end of the shelf life were greatly underestimated when mesophilic incubation was implemented due to overlooked, psychrotrophic members of the LAB. Pseudomonas spp., Enterobacteriaceae, Streptococcaceae, and Lactobacillus spp. constituted the most widespread operational taxonomic units (OTUs), whereas Leuconostoc gelidum was detected as a minor member of the indigenous microbiota of the food ingredients and microbial community of the processing environment, albeit it colonized samples at almost every sampling point on the premises. However, L. gelidum became the most predominant microbe at the end of the shelf life. The ability of L. gelidum to outgrow notorious, spoilage-related taxa like Pseudomonas, Brochothrix, and Lactobacillus underpins its high growth dynamics and severe spoilage character under refrigeration temperatures. The use of predicted metagenomes was useful for observation of putative gene repertoires in the samples analyzed in this study. The end products grouped in clusters characterized by gene profiles related to carbohydrate depletion presumably associated with a fast energy yield, a finding which is consistent with the fastidious nature of highly competitive LAB that dominated at the end of the shelf life. The present study showcases the detrimental impact of contamination with psychrotrophic LAB on the shelf life of packaged and cold-stored foodstuffs and the long-term quality implications for production batches once resident microbiota are established in the processing environment

Bacterial biogeographical patterns in a cooking center for hospital foodservice

Microbial contamination in foodservice environments plays a fundamental role in food quality and safety. In such environments the composition of the microbiota is influenced by the characteristics of the specific surfaces and by food handling and processing and a resident microbiota may be present in each site. In this study, the bacterial biogeographical patterns in a hospital cooking center was studied by 16S rRNA-based culture-independent high-throughput amplicon sequencing in order to provide a comprehensive mapping of the surfaces and tools that come in contact with foods during preparation. Across all area, surface swab-samples from work surfaces of different zones were taken: food pre-processing rooms (dedicated to fish, vegetables, and red and white meat), storage room and kitchen. The microbiota of environmental swabs was very complex, including more than 500 operational taxonomic units (OTUs) with extremely variable relative abundances (0.02-99%) depending on the species. A core microbiota was found that was common to more than 70% of the samples analyzed and that included microbial species that were common across all areas such as Acinetobacter, Chryseobacterium, Moraxellaceae, and Alicyclobacillus, although their abundances were below 10% of the microbiota. Some surfaces were contaminated by high levels of either Pseudomonas, Psychrobacter, Paracoccus, or Kocuria. However, beta diversity analysis showed that, based on the composition of the microbiota, the environmental samples grouped according to the sampling time but not according to the specific area of sampling except for the case of samples from the vegetable pre-processing room that showed a higher level of similarity. The cleaning procedures can have a very strong impact on the spatial distribution of the microbial communities, as the use of the same cleaning tools can be even a possible vector of bacterial diffusion. Most of the microbial taxa found are not those commonly found in food as spoilers or hazardous bacteria, which indicates that food and storage conditions can be very selective in the growth of possible contaminants

Coexistence of Lactic Acid Bacteria and Potential Spoilage Microbiota in a Dairy Processing Environment

Microbial contamination in food processing plants can play a fundamental role in food quality and safety. In this study, the microbiota in a dairy plant was studied by both 16S rRNA- and 26S rRNA-based culture-independent high-throughput amplicon sequencing. Environmental samples from surfaces and tools were studied along with the different types of cheese produced in the same plant. The microbiota of environmental swabs was very complex, including more than 200 operational taxonomic units with extremely variable relative abundances (0.01 to 99%) depending on the species and sample. A core microbiota shared by 70% of the samples indicated a coexistence of lactic acid bacteria with a remarkable level of Streptococcus thermophilus and possible spoilage-associated bacteria, including Pseudomonas, Acinetobacter, and Psychrobacter, with a relative abundance above 50%. The most abundant yeasts were Kluyveromyces marxianus, Yamadazyma triangularis, Trichosporon faecale, and Debaryomyces hansenii. Beta-diversity analyses showed a clear separation of environmental and cheese samples based on both yeast and bacterial community structure. In addition, predicted metagenomes also indicated differential distribution of metabolic pathways between the two categories of samples. Cooccurrence and coexclusion pattern analyses indicated that the occurrence of potential spoilers was excluded by lactic acid bacteria. In addition, their persistence in the environment can be helpful to counter the development of potential spoilers that may contaminate the cheeses, with possible negative effects on their microbiological quality