Following food microbiome development during shelf-life in the Nextgen era.

Food microbial populations are complex and dynamic: they develop and change their composition all throughout shelf life, establishing tangled interaction that traditional culture-dependent methods cannot completely point out. Thus, in this field, Next generation sequencing has become more interesting since the study of microbial communities has reached a depth of analysis never seen before: species richness and evenness, the detection of rare bacterial populations, the analysis of the genetical responses to food environments are some information provided by Nextgen techniques. In this work an industrial ricotta cheese microbial community was monitored starting from raw materials to product expiry date: Illumina MiSeq 2x300bp 16S amplicon analysis was exploited with a simple protocol for library production, normalization and pooling, in parallel with culture-dependent analysis. On one hand raw material and the product were processed all throughout shelf-life using classic culture-dependent methods while, at the same time, RNA or DNA was extracted from the samples and sequenced with Nextgen approach. Microbial populations were different between the raw matters (whey and cream) and showed typical environmental contaminants, lactic acid bacteria and aerobic spores (Pseudomonas, Aeromonas, Streptococcus, Lactococcus, Kocuria, Hafnia). Most of the microbial populations in the ricotta cheese samples appeared to be composed of Bacillus and Paenibacillus. Both genera derived from spores germination and increased exponentially within two weeks of 8°C storage, reaching 107 CFU/ml; within 20 days cheese pH decreased from 6,4-6,2 to 5,7-5,5, showing acidification due to active bacterial metabolism. With this approach we precisely understood what kind of bacteria were present in the tested products from raw matters to expiry date: these essential informations can be exploited in order to improve ricotta cheese chain production.