Grape berries harbor a wide range of microbes originating from the vineyard environment, many of which are recognized for their role in the must fermentation process shaping wine quality. To better clarify the contribution of the microbiome of grape fruits during wine fermentation, we used high-throughput sequencing to identify bacterial and fungi communities associated with berries and musts of Cannonau. This is the most important cultivar-wine of Sardinia (Italy) where most vineyards are cultivated without phytochemical treatments. Results suggested that microbiomes of berries collected at four different localities share a core composition characterized by Enterobacteriales, Pseudomonadales, Bacillales, and Rhodospirillales. However, any area seems to enrich berries microbiome with peculiar microbial traits. For example, berries belonging to the biodynamic vineyards of Mamoiada were rich in Bacillales typical of manure (i.e. Lysinibacillus, Bacillus, and Sporosarcina), whereas in the Santadi locality, berries showed soil bacteria such as Pasteurellales and Bacteroidales as well as Rhodospirillales and Lactobacillales which are commonly involved in wine fermentation. In the case of fungi, the most abundant taxa were Dothioraceae, Pleosporaceae, and Saccharomycodaceae, and although the proportion of these families varied among localities, they occurred ubiquitously in all vineyards. During vinification processes performed at the same wine cellar under controlled conditions and without using any yeast starter, more than 50% of bacteria groups of berries reached musts, and each locality had its own private bacteria signature, even if Saccharomyces cerevisiae represented the most abundant fungal species. This work suggests that natural berries microbiome could be influenced by pedoclimatic and anthropologic conditions (e.g., farming management), and the fruits’ microorganisms persist during the fermentation process. For these reasons, a reliable wine genotyping should include the entire holobiont (plant and all its symbionts), and bioprospecting activities on grape microbiota could lead to improved viticulture yields and wine quality.

One of the main goals of the quality control evaluation is to identify contaminants in raw material, or contamination after a food is processed and before it is placed on the market. During the treatment processes, contamination, both accidental and economically motivated, can generate incongruence between declared and real composition. In our study, we evaluated if DNA metabarcoding is a suitable tool for unveiling the composition of processed food, when it contains small trace amounts. We tested this method on different types of commercial plant products by using tnrL marker and we applied amplicon-based high-throughput sequencing techniques to identify plant components in different food products. Our results showed that DNA metabarcoding can be an effective approach for food traceability in different type of processed food. Indeed, the vast majority of our samples, we identified the species composition as the labels reported. Although some critical issues still exist, mostly deriving from the starting composition (i.e., variable complexity in taxa composition) of the sample itself and the different processing level (i.e., high or low DNA degradation), our data confirmed the potential of the DNA metabarcoding approach also in quantitative analyses for food composition quality control.

While safe and of high quality, drinking water can host an astounding biodiversity of microorganisms, dismantling the belief of its “biological simplicity.” During the very few years, we are witnessing an exponential growth in scientific publications, exploring the ecology hidden in drinking water treatment plants (DWTPs) and drinking water distribution system (DWDS). We focused on what happens to the microbial communities from source water (groundwater) throughout the main steps of the potabilization process of a DWTP, located in an urbanized area in Northern Italy. Samples were processed by a stringent water filtration to retain even the smallest environmental bacteria and then analyzed with High-Throughput DNA Sequencing (HTS) techniques. We showed that carbon filters harbored a microbial community seeding and shaping water microbiota downstream, introducing a significant variation on incoming (groundwater) microbial community. Chlorination did not instantly affect the altered microbiota. We were also able to correctly predict (through machine learning analysis) samples belonging to groundwater (overall accuracy was 0.71), but the assignation was not reliable with carbon filter samples, which were incorrectly predicted as chlorination samples. The presence and abundance of specific microorganisms allowed us to hypothesize their role as indicators. In particular, Candidatus Adlerbacteria (Parcubacteria), together with microorganisms belonging to Alphaproteobacteria and Gammaproteobacteria, characterized treated water, but not raw water. An exception, confirming our hypothesis, is given by the samples downstream the filters renewal, which had a composition resembling groundwater. Volatility analysis illustrated how carbon filters represented an ecosystem that is stable over time, probably bearing the environmental conditions that promote the survival and growth of this peculiar microbial community.

Scientists recently reported the unexpected detection of unknown or poorly studied bacterial diversity in groundwater. The ability to uncover this neglected biodiversity mainly derives from technical improvements, and the term “microbial dark matter” was used to group taxa poorly investigated and not necessarily monophyletic. We focused on such under-investigated microbial dark matter of drinking water treatment plant from groundwater, across carbon filters, to post-chlorination. We tackled this topic using an integrated approach where the efficacy of stringent water filtration (10000 MWCO) in recovering even the smallest environmental microorganisms was coupled with high-throughput DNA sequencing to depict an informative spectrum of the neglected microbial diversity. Our results revealed that the composition of bacterial communities varies across the plant system: Parcubacteria (OD1) superphylum is found mainly in treated water, while groundwater has the highest heterogeneity, encompassing non-OD1 candidate phyla (Microgenomates, Saccharibacteria, Dependentiae, OP3, OP1, BRC1, WS3). Carbon filters probably act as substrate for microorganism growth and contribute to seeding water downstream, since chlorination does not modify the incoming bacterial community. New questions arise about the role of microbial dark matter in drinking water. Indeed, our results suggest that these bacteria might play a central role in the microbial dynamics of drinking water.