Microbiota and Metabolite Profiling Combined With Integrative Analysis for Differentiating Cheeses of Varying Ripening Ages

Cheese maturation and flavor development results from complex interactions between milk substrates, cheese microbiota and their metabolites. In this study, bacterial 16S rRNA-gene sequencing, untargeted metabolomics (GC-MS) and data integration analyses were used to characterize and differentiate between commercial Cheddar cheeses of varying ripening ages made by the same and different manufacturers. Microbiota and metabolite compositions varied between cheeses of different ages and brands, and could be used to distinguish the cheeses. Individual amino acids and carboxylic acids were positively correlated with the ripening age for some brands. Integration and Random Forest analyses revealed numerous associations between specific bacteria and metabolites including a previously undescribed positive correlation between Thermus and phenylalanine and a negative correlation between Streptococcus and cholesterol. Together these results suggest that multi-omics analysis could be used for better understanding the relationships between cheese microbiota and metabolites during ripening and for discovering biomarkers for validating cheese age and brand authenticity.