Geographical and Cultivar Features Differentiate Grape Microbiota in Northern Italy and Spain Vineyards

• Published in: Frontiers in microbiology 2018-05, Vol.9, p.946-946
• Main Authors: Mezzasalma, Valerio, Sandionigi, Anna, Guzzetti, Lorenzo, Galimberti, Andrea, Grando, Maria S, Tardaguila, Javier, Labra, Massimo
• Format: Article
• Language: English
• Subjects: fruit microbiome; high throughput sequencing; Microbiology; soil microbiome; Vitis vinifera; wine
• ISSN: 1664-302X; 1664-302X
• DOI: 10.3389/fmicb.2018.00946

Recent studies have highlighted the role of the grapevine microbiome in addressing a wide panel of features, ranging from the signature of field origin to wine quality. Although the influence of cultivar and vineyard environmental conditions in shaping the grape microbiome have already been ascertained, several aspects related to this topic, deserve to be further investigated. In this study, we selected three international diffused grapevine cultivars (Cabernet Sauvignon, Syrah, and Sauvignon Blanc) at three germplasm collections characterized by different climatic conditions [Northern Italy (NI), Italian Alps (AI), and Northern Spain (NS)]. The soil and grape microbiome was characterized by 16s rRNA High Throughput Sequencing (HTS), and the obtained results showed that all grape samples shared some bacterial taxa, regardless of sampling locality (e.g., , , , and other genera belonging to Alphaproteobacteria, Gammaproteobacteria, and Actinobacteria). However, some Operational Taxonomic Units (OTUs) could act as geographical signatures and in some cases as cultivar fingerprint. Concerning the origin of the grape microbiome, our study confirms that vineyard soil represents a primary reservoir for grape associated bacteria with almost 60% of genera shared between the soil and grape. At each locality, grapevine cultivars shared a core of bacterial genera belonging to the vineyard soil, as well as from other local biodiversity elements such as arthropods inhabiting or foraging in the vineyard. Finally, a machine learning analysis showed that it was possible to predict the geographical origin and cultivar of grape starting from its microbiome composition with a high accuracy (9 cases out of 12 tested samples). Overall, these findings open new perspectives for the development of more comprehensive and integrated research activities to test which environmental variables have an effective role in shaping the microbiome composition and dynamics of cultivated species over time and space.