P07 | Pilot study to develop a microbiome mapping strategy in raw milk cheeses for predicting the biological risk profile

S. Giacomozzi, V. Indio, G. Guluzade, T. Dalmonte, Y.T. Mekonnen, B. Barzagli, A. Seguino, A. Serraino, A. De Cesare | Dip. di Scienze Mediche Veterinarie, Alma Mater Studiorum, Università degli Studi di Bologna, Italy

Purpose. Longitudinal analysis of food microbiomes during the production process allows for the evaluation of changes in microbial populations that can favor pathogen colonization. Methods. In this pilot study, the microbiomes of 28 samples from the same batch of cheese and 3 environmental samples taken from a dairy farm in the Emilia-Romagna region were characterized. The analyzed samples were raw milk (n=3), warm milk (n=1), whey (n=3), brine liquid (n=1), curd (n=3), post-steaming cheese (n=1), post-brining cheese (n=1), post-antimold cheese (n=1), and cheese after 7, 15, 30, 45, 60, 75, and 90 days of aging, tested both internally (1 sample for each time point) and on the rind (1 sample for each time point). The three environmental samples were obtained from manhole swabs in the production area (1 pool of 5 swabs) and from the aging boards at 3 and 75 days. All collected samples underwent DNA extraction, library preparation, and shotgun sequencing on the Illumina NovaSeq 6000 platform. Taxonomic classification was performed using the kaiju tool against reference nr_euk after cleaning the sequences of the host genome (Bos taurus). Correlation analysis between microbiomes was conducted at the genus level using R by applying the cor function (stats package, method: pearson). Salmonella, Campylobacter, Listeria monocytogenes, and Staphylococcus aureus were searched for in milk and dairy product samples using a culture method. In environmental samples, only Listeria monocytogenes. Results. The dominant genera in raw milk microbiomes were found to be Lactococcus, Pseudomonas, and Acinetobacter, while in the curd and cheese during ripening, the main genera were Lactococcus, Streptococcus, and Lactobacillus. The microbiomes of the samples characterized during the production process were found to be correlated to varying degrees, with the exception of the brine, which was not correlated with the other samples. The microbiomes of the swabs taken from the manholes were found to be correlated with those of raw milk and warm milk, while those on the 75-day aging shelves were correlated with the microbiomes of the cheese rind at the same aging time, with a clear presence of Penicillium in both samples. The microbiomes identified in the three serum and curd sampling units were completely overlapping, while for the milk samples, overlap was not always observed. Regarding pathogens, the culture analysis only revealed the presence of Staphylococcus aureus, while Salmonella, Campylobacter, and Listeria monocytogenes were consistently undetectable in 25 g or ml of the sample. Analysis of the abundance of the described pathogen reads showed values >60 rpm (reads per million) only for S. aureus. Conclusions. The longitudinal study of microbiomes during the production process allows for monitoring the dynamics of microbial populations and the colonization of foodborne pathogens responsible for illnesses. The activities of this project were funded by the MASAF project, Supply Chain Agreement, Model Stable, Ministerial Decree No. 0673777 of 22/12/2021, V Notice No. 0182458 of 22/04/2022 and subsequent amendments.