A novel classification system based on cheese microbial profiles for the assessment of cheese typicity

Cheese typicity reflects the unique characteristics influenced by raw ingredients, traditional tools employed, environmental and production conditions, the cheese-making process and the specific geographical region of origin. In the present study, the typicity of Greek cheeses was studied and compared with cheeses from various countries worldwide, based on microbiota profiles. The dataset included publicly available and 63 newly generated sequences, totaling 322 cheese samples, derived from seven different countries. The analysis incorporated next generation sequencing (NGS) technology, with Illumina sequencing of the 16S rRNA gene hypervariable regions V3-V4, followed by a standardized analytical pipeline process. Through de novo clustering, four main Cheese Microbial Profiles (CMP) - clusters and nine sub-clusters were identified. Core microbiota was identified within sub-clusters. The dominant bacterial genera were Lactobacillus in CMP1, Lactococcus in CMP2 and CMP3, and Streptococcus in CMP4. Distinct cheese types exhibited a statistically significant tendency for specific microbial profiles within clusters. However, no clear signatures of geographic origin were detected, nor were associations found between microbial communities and cheese production parameters such as cheese type, milk source, starter culture addition or milk pasteurization. Additionally, we developed a novel model capable of accurately classifying new cheese samples into clusters and sub-clusters, based on their bacterial ecological community structure. Our findings could support future initiatives, especially when combined with multi-omic approaches, to better identify cheese typicity, verify authenticity, potentially trace geographical origin, and ultimately enhance the quality and safety of cheeses.