Stable functional structure despite high taxonomic variability across fungal communities in soils of old-growth montane forests

Abstract

Background Major advances over the past decade in molecular ecology are providing access to soil fungal diversity in forest ecosystems worldwide, but the diverse functions and metabolic capabilities of this microbial community remain largely elusive. We conducted a field survey in montane old-growth broadleaved and conifer forests, to investigate the relationship between soil fungal diversity and functional genetic traits. To assess the extent to which variation in community composition was associated with dominant tree species (oak, spruce, and fir) and environmental variations in the old-growth forests in the Jade Dragon Snow Mountain in Yunnan Province, we applied rDNA metabarcoding. We also assessed fungal gene expression in soil using mRNA sequencing and specifically assessed the expression of genes related to organic matter decomposition and nutrient acquisition in ectomycorrhizal and saprotrophic fungi. Results Our taxonomic profiling revealed striking shifts in the composition of the saprotrophic and ectomycorrhizal guilds among the oak-, fir-, and spruce-dominated forests. The core fungal microbiome comprised only ~ 20% of the total OTUs across all soil samples, although the overlap between conifer-associated communities was substantial. In contrast, seasonality and soil layer explained only a small proportion of the variation in community structure. However, despite their highly variable taxonomic composition, fungal guilds exhibited remarkably similar functional traits for growth-related and core metabolic pathways across forest associations, suggesting ecological redundancy. However, we found that the expression profiles of genes related to polysaccharide and protein degradation and nutrient transport notably varied between and within the fungal guilds, suggesting niche adaptation. Conclusions Overall, our metatranscriptomic analyses revealed the functional potential of soil fungal communities in montane old-growth forests, including a suite of specialized genes and taxa involved in organic matter decomposition. By linking genes to ecological traits, this study provides insights into fungal adaptation strategies to biotic and environmental factors, and sheds light on the importance of understanding functional gene expression patterns in predicting ecosystem functioning.

The mycorrhizal symbiosis: research frontiers in genomics, ecology, and agricultural application

“…The growing availability of mycorrhizal fungal genomes (Lebreton et al, 2021) presents unprecedented opportunities to investigate the functional diversity of soil fungal communities. This can be achieved through expert and accurate annotation of environmental metabarcoding (Anthony et al, 2022), metagenomics (Hagh-Doust et al, 2023, and metatranscriptomic (Auer et al, 2023;Zeng et al, 2023) datasets. The latter approach has been used to examine gene expression in ECM root tips in natural environments, including the effects of anthropogenic N deposition on ECM tree metabolism (Liao et al, 2018;Law et al, 2022;Rivera P erez et al, 2022).…”

“…Anthony et al (2022) showed that tree growth was linked to the gene copy number of genes involved N uptake and assimilation in associated ECM symbionts. By combining highthroughput metabarcoding of fungal species residing in a specific experimental forest site with the sequencing of soil eukaryotic RNA extracts, the precise gene expression of each mycelial network extending beneath a tree species can be evaluated (Auer et al, 2023;Zeng et al, 2023). The use of metatranscriptomics will also help decipher the relative importance of each fungal species within the different soil biota in measuring genes involved in plant nutrition, C cycling, disease resistance, and stress adaptation.…”

“…exhibiting limited functional similarity; see Section V.2). Metatranscriptomics of soil fungal communities (Auer et al, 2023;Zeng et al, 2023) can be used to better understand the role of mycorrhizal networks, including CMN, because they can help identify whether different tree individuals within a plot are truly colonized by the same fungus, and whether the same sets of genes are expressed in different tree individuals. However, several challenges limit the widespread application of metatranscriptomics, including the lower stability of RNA compared with that of DNA, greater difficulty in extracting RNA, and difficulty in obtaining informative messenger RNA transcripts that provide insights into its functional role (Auer et al, 2023).…”