Vitis vinifera is one of the most widely cultivated fruit crops with a great economic impact on the global industry. As a plant, it is naturally colonised by a wide variety of both prokaryotic and eukaryotic microorganisms that interact with grapevine, having either beneficial or phytopathogenic effects, who play a major role in fruit yield, grape quality and, ultimately, in the evolution of grape fermentation and wine production. Therefore, the objective of this study was to extensively characterize the natural microbiome of grapevine. Considering that the majority of microorganisms are uncultivable, we have deeply studied the microflora of grapevine leaves using massive parallel rDNA sequencing, along its vegetative cycle. Among eukaryotic population the most abundant microorganisms belonged to the early diverging fungi lineages and Ascomycota phylum, whereas the Basidiomycota were the least abundant. Regarding prokaryotes, a high diversity of Proteobacteria, Firmicutes and Actinobacteria was unveiled. Indeed, the microbial communities present in the vineyard during its vegetative cycle were shown to be highly structured and dynamic. In all cases, the major abundant microorganisms were the yeast-like fungus Aureobasidium and the prokaryotic Enterobacteriaceae. Herein, we report the first complete microbiome landscape of the vineyard, through a metagenomic approach, and highlight the analysis of the microbial interactions within the vineyard and its importance for the equilibrium of the microecosystem of grapevines.

Grapes and wine musts harbour a complex microbiome, which plays a crucial role in wine fermentation as it impacts on wine flavour and, consequently, on its final quality and value. Unveiling the microbiome and its dynamics, and understanding the ecological factors that explain such biodiversity, has been a challenge to oenology. In this work, we tackle this using a metagenomics approach to describe the natural microbial communities, both fungal and bacterial microorganisms, associated with spontaneous wine fermentations. For this, the wine microbiome, from six Portuguese wine appellations, was fully characterized as regards to three stages of fermentation – Initial Must (IM), and Start and End of alcoholic fermentation (SF and EF, respectively). The wine fermentation process revealed a higher impact on fungal populations when compared with bacterial communities, and the fermentation evolution clearly caused a loss of the environmental microorganisms. Furthermore, significant differences (p<0.05) were found in the fungal populations between IM, SF and EF, and in the bacterial population between MI and SF. Fungal communities were characterized by either the presence of environmental microorganisms and phytopathogens in the initial musts, or yeasts associated with alcoholic fermentations in wine must samples as Saccharomyces and non-Saccharomyces yeasts (as Lachancea, Metschnikowia, Hanseniaspora, Hyphopichia, Sporothrix, Candida and Schizosaccharomyces). Among bacterial communities, the most abundant family was Enterobacteriaceae; though families of species associated with the production of lactic acid (Lactobacillaceae, Leuconostocaceae) and acetic acid (Acetobacteriaceae) were also detected. Interestingly, a biogeographical correlation for both fungal and bacterial communities was identified between wine appellations at IM suggesting that each wine region contains specific and embedded microbial communities which may contribute to the uniqueness of regional wines.

Forest decline diseases are complex processes driven by biotic and abiotic factors. Although information about host–microbiome–environment interactions in agricultural systems is emerging rapidly, similar studies on tree health are still in their infancy. We used acute oak decline (AOD) as a model system to understand whether the rhizosphere physicochemical properties and microbiome are linked to tree health by studying these two factors in healthy and diseased trees located in three sites in different AOD stages—low, mid and severe. We found significant changes in the rhizosphere properties and microbiome composition across the different AOD sites and between the tree health conditions. Rhizosphere pH correlated with microbiome composition, with the microbial assemblages changing in more acidic soils. At the severe AOD site, the oak trees exhibited the lowest rhizosphere pH and distinct microbiome, regardless of their health condition, whereas, at the low and mid-stage AOD sites, only diseased trees showed lower pH and the microbial composition differed significantly from healthy trees. On these two sites, less extreme soil conditions and a high presence of host-beneficial microbiota were observed in the healthy oak trees. For the first time, this study gathers evidence of associations among tree health conditions, rhizosphere properties and microbiome as well as links aboveground tree decline symptoms to the belowground environment. This provides a baseline of rhizosphere community profiling of UK oak trees and paves the way for these associations to be investigated in other tree species suffering decline disease events.

The pinewood nematode, Bursaphelenchus xylophilus, is native to North America but it only causes damaging pine wilt disease in those regions of the world where it has been introduced. The accurate detection of the species and its dispersal routes are thus essential to define effective control measures. The main goals of this study were to analyse the genetic diversity among B. xylophilus isolates from different geographic locations and identify single nucleotide polymorphism (SNPs) markers for geographic origin, through a comparative transcriptomic approach. The transcriptomes of seven B. xylophilus isolates, from Continental Portugal (4), China (1), Japan (1) and USA (1), were sequenced in the next generation platform Roche 454. Analysis of effector gene transcripts revealed inter-isolate nucleotide diversity that was validated by Sanger sequencing in the genomic DNA of the seven isolates and eight additional isolates from different geographic locations: Madeira Island (2), China (1), USA (1), Japan (2) and South Korea (2). The analysis identified 136 polymorphic positions in 10 effector transcripts. Pairwise comparison of the 136 SNPs through Neighbor-Joining and the Maximum Likelihood methods and 5-mer frequency analysis with the alignment-independent bilinear multivariate modelling approach correlated the SNPs with the isolates geographic origin. Furthermore, the SNP analysis indicated a closer proximity of the Portuguese isolates to the Korean and Chinese isolates than to the Japanese or American isolates. Each geographic cluster carried exclusive alleles that can be used as SNP markers for B. xylophilus isolate identification.