Estimation of metabolite levels in cheese from microbial gene expression

Characterizing aroma and flavours generated during cheese production is of high relevance for the food industry. A deeper comprehension of flavour generation can be achieved by understanding the role of microbial population governing milk processing, and in particular their metabolic activity governed by gene expression. In this work we considered two independent experiments in which gene expression of the microbial population involved in cheese processing is sampled, together with final volatile products quantification. We estimated the final volatile compound profile from the measured metatranscriptomic expression by using machine learning with two different strategies for model training and validation, and we were able to associate specific biochemical pathways to the identified gene signatures.