The distinct sensorial characteristics of local cheeses influence consumer preferences, and make an essential contribution to the local economy. Microbial diversity in cheese is among the fundamental contributors to sensorial and qualitative characteristics. However, knowledge regarding the existence of microbial patterns associated with regional production practices in ripened cheeses remains limited. The present research was conducted to test the hypothesis that the background metagenome of cheeses could be used as a marker of their origin. We compared Irish versus Eastern Mediterranean cheeses-namely Greek and Cypriot-using High Throughput Sequencing (HTS). The study identified a significantly distinct separation among cheeses originating from the three different countries, in terms of the total microbial community composition. The use of machine learning and biomarkers discovery algorithms defined key microbes that differentiate each geographic region. Finally, the development of interaction networks revealed that the key species developed mostly negative interactions with the other members of the communities, highlighting their dominance in the community. The findings of the present research demonstrate that metagenome could indeed be used as a biological marker of the origin of mature cheeses, and could provide further insight into the dynamics of microbial community composition in ripened cheeses.
Keywords: 16S rDNA; ITS loci; biomarkers; cheese; high throughput sequencing; lactic acid bacteria; metataxonomic sequencing; microbiome; ripened cheeses; starter cultures.