Fungal Communities of Eucalyptus grandis Leaves Are Influenced by the Insect Pest Leptocybe invasa.

Fungal communities in above-ground tree tissues are hyperdiverse and are influenced by biotic interactions with other organisms living in or on these tissues. These biotic interactions are, however, still poorly understood. In this study, we aimed to understand how insect-associated gall formation on Eucalyptus foliage correlates with the diversity of foliar fungal communities in surrounding healthy leaf tissue, as well as the co-occurrence patterns among the members of the fungal community. We used ITS metabarcoding to characterise the foliar fungal communities of 179 individual E. grandis trees. These trees were assigned to infestation levels of the wasp Leptocybe invasa (Eulophidae: Hymenoptera), which causes gall formation on shoot tips and leaves of its host. Fungal community networks were calculated using a Pearson correlation coefficient. The composition and diversity of fungal communities were influenced by the severity of L. invasa infestations. We identified potential Eucalyptus pathogens with high sequence abundance at all disease severity levels, but network analysis indicated that the co-occurrence of potential pathogens between no to mild and medium to heavy infestation differed significantly. A better understanding of microbial interactions, especially the role of pathogens, can be useful for controlling disease- and beneficial host-associated microbial communities.

Active Fungal Communities in Asymptomatic Eucalyptus grandis Stems Differ between a Susceptible and Resistant Clone.

Fungi represent a common and diverse part of the microbial communities that associate with plants. They also commonly colonise various plant parts asymptomatically. The molecular mechanisms of these interactions are, however, poorly understood. In this study we use transcriptomic data from Eucalyptus grandis, to demonstrate that RNA-seq data are a neglected source of information to study fungal-host interactions, by exploring the fungal transcripts they inevitably contain. We identified fungal transcripts from E. grandis data based on their sequence dissimilarity to the E. grandis genome and predicted biological functions. Taxonomic classifications identified, amongst other fungi, many well-known pathogenic fungal taxa in the asymptomatic tissue of E. grandis. The comparison of a clone of E. grandis resistant to Chrysoporthe austroafricana with a susceptible clone revealed a significant difference in the number of fungal transcripts, while the number of fungal taxa was not substantially affected. Classifications of transcripts based on their respective biological functions showed that the fungal communities of the two E. grandis clones associate with fundamental biological processes, with some notable differences. To shield the greater host defence machinery in the resistant E. grandis clone, fungi produce more secondary metabolites, whereas the environment for fungi associated with the susceptible E. grandis clone is more conducive for building fungal cellular structures and biomass growth. Secreted proteins included carbohydrate active enzymes that potentially are involved in fungal-plant and fungal-microbe interactions. While plant transcriptome datasets cannot replace the need for designed experiments to probe plant-microbe interactions at a molecular level, they clearly hold potential to add to the understanding of the diversity of plant-microbe interactions.