Pyrosequencing reveals regional differences in fruit-associated fungal communities

Abstract

We know relatively little of the distribution of microbial communities generally. Significant work has examined a range of bacterial communities, but the distribution of microbial eukaryotes is less well characterized. Humans have an ancient association with grape vines (Vitis vinifera) and have been making wine since the dawn of civilization, and fungi drive this natural process. While the molecular biology of certain fungi naturally associated with vines and wines is well characterized, complementary investigations into the ecology of fungi associated with fruiting plants is largely lacking. DNA sequencing technologies allow the direct estimation of microbial diversity from a given sample, avoiding culture-based biases. Here, we use deep community pyrosequencing approaches, targeted at the 26S rRNA gene, to examine the richness and composition of fungal communities associated with grapevines and test for geographical community structure among four major regions in New Zealand (NZ). We find over 200 taxa using this approach, which is 10-fold more than previously recovered using culture-based methods. Our analyses allow us to reject the null hypothesis of homogeneity in fungal species richness and community composition across NZ and reveal significant differences between major areas.

Figure 1

Number of reads and OGUs at class and phylum level, and the number of reads at order level. The correlation between diversity (number of OGUs) and abundance (number of reads) for all classes is shown in the line plot and with two pie charts for phylum level. The distribution of reads at the order level is shown as a pie chart. Representative sequences that were not assigned to either a class or order given our Bayesian 70% bootstrap cut-off are designated unclassified (but will likely have been classified at higher levels, see Supporting Information Table S1).

Figure 2

The differences in fungal communities on ripe Chardonnay grapes between four NZ regions. The size (area) of the circle representing each region is proportional to the observed OGU richness for that region (refer to Table 1). The thickness of lines connecting regions corresponds to the Jaccard similarity (= 1-dissimilarity) between relative 98% OGU abundances in each region. The pie charts show the breakdown of read abundance by genus, with OGUs unclassified at this level removed. Only the labels for the eight most abundant genera are shown, as rare genera are not readily discernable in the plots.

Figure 3

Non-metric multidimensional scaling (NMDS) plot based on Jaccard dissimilarities calculated from read numbers among the 253 inferred OGUs between replicate samples of communities from the four regions. Stress is 0.19. WA, West Auckland; HB, Hawke's Bay; MB, Marlborough; CO, Central Otago.