The microbiome analysis of ripen grape berries supports the complex etiology of sour rot

Abstract

Sour rot (SR) is a grapevine disease complex that is not completely understood in its etiology and epidemiology. Recently, SR has received special attention due to its increasing economic importance due to crop losses and reduced wine quality. In this study, the fungal and bacterial microbiota of healthy (i.e., without rot symptoms) and rotten (i.e., exhibiting visual and olfactory SR symptoms) ripe bunches were characterized across 47 epidemics (39 vineyards in six Italian grape-growing areas) over three years. The 16S rRNA gene, ITS high-throughput amplicon sequencing, and quantitative PCR were used to assess the relative abundance and dynamic changes of microorganisms associated with SR. The estimators of genera richness of fungal communities within samples indicated a significantly different diversity between healthy and rotten bunches. For bacterial communities, the healthy and rotten bunches significantly differed in the total number of species, but not in abundance distribution across species. The bunch status (i.e., healthy and rotten) was a significant source of diversity (p < 0.01) when the community composition between samples was evaluated, indicating that microbiome composition varied between healthy and rotten bunches. In particular, healthy and rotten bunches shared 43.1 and 54.8% of fungal and bacterial genera, respectively; 31.3% (fungal) and 26.2% (bacterial) genera were associated with rotten bunches only. The yeast genera Zygosaccharomyces, Zygoascus, Saccharomycopsis, Issatchenkia, and Pichia and the bacterial genera Orbus, Gluconobacter, Komagataeibacter, Gluconacetobacter, and Wolbachia were strongly associated with bunches showing SR symptoms based on a linear discriminant analysis. These microorganisms have been associated with Drosophila insects in literature. The relationships between the microflora associated with SR-affected bunches and the roles of Drosophila in SR development need further investigation, which may open perspectives for more effective disease control.

Keywords: Enterobacteriaceae; Vitis vinifera; acetic acid bacteria; bunch microflora; high-throughput sequencing; minor grape rots; non-Saccharomyces yeasts.

Figure 1

Venn diagram illustrating the overlap of the number of SVs identified in the fungal (A) and bacterial (B) microbiota between grapevine bunches showing sour rot symptoms or not (referred to as healthy).

Figure 2

Relative abundance of fungal (A) and bacterial (B) genera in grapevine bunches showing sour rot symptoms (light blue line) or not (red line); the number between brackets shows the ratio of the number of reads in rotten vs. healthy bunches.

Figure 3

Boxplot illustrating the differences in the fungal (A,B) and bacterial (C,D) communities in healthy (red) and rotten (light blue) bunches based on Chao1 (A,C) and Shannon (B,D) diversity indicators. The box extends from the 25th to the 75th quartile of the data distribution, the line crossing the box represents the median, and the black diamond indicates the average; whiskers extend to the maximum and minimum.

Figure 4

Principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity metrics, showing the distance in the fungal (A) and bacterial (B) communities present in healthy (red dots) and rotten (light blue dots) bunches. Areas show distinct clustering of healthy (red) and rotten (light blue) bunches.

Figure 5

Graphical summary of LEfSe analysis for fungal (A) and bacterial (B) communities in healthy (red) and rotten bunches (light blue). The LDA score represents the extent to which the genera differ among the groups: the higher the positive score, the higher the increase in the relative abundance of the genus concerning rotten bunches, and the lower the negative score, the higher the increase in the relative abundance of the genus in rotten concerning healthy bunches. Full and diagonally striped bar colors mean p-values <0.01 and <0.05, respectively.

Figure 6

SparCC correlation analysis for fungal communities in rotten bunches. Nodes represent taxa at the genus level. Node size is based on the number of connections to each taxon. Edges represent correlations between pairs: red and blue edges represent positive and negative correlations, respectively; the value is the correlation coefficient between taxa. The nodes are colored based on phyla: green for Ascomycota and orange for Basidiomycota.

Figure 7

SparCC correlation analysis for bacterial communities in rotten bunches. Nodes represent taxa at the genus level. Node size is based on the number of connections to each taxon. Edges representing correlations between pairs: red and blue edges represent positive and negative correlations, respectively; the value is the correlation coefficient between taxa. The nodes are colored based on phyla: green for Proteobacteria, orange for Actinobacteria, purple for Firmicutes, pink for Bacteroidetes, green for Gemmatimonadota, yellow for Bacteroidota, and brown for Verrucomicrobiota.

Figure 8

Schematic relationship of the interactions between yeasts and bacteria associated with grape sour rot and Drosophila spp., as from literature. These relationships agree with the microbial composition of the SR-affected bunches in this study. Flying adults carry microorganisms on both external parts of their bodies and in the gut as symbionts, which provide multiple benefits to insects. Adults deposit eggs in the berry pulp through berry skin lesions (e.g., D. melanogaster) or directly (e.g., D. suzukii) so that the epiphytic yeasts and bacteria can penetrate the pulp or enter the pulp through vectoring on fly body parts or vertical transmission (adults to eggs). Larvae develop into the berry feeding the endophytic microorganisms and berry pulp components through modifications induced by insect-released enzymes; this results in faster offspring development. Larvae also delay wound healing through movement. Endophytic microorganisms grow and produce berry rot and the compounds associated with sour rot (ethanol, acetic acid, gluconic acid, etc.). Some of these compounds are volatiles that attract flies.