Fungal community analysis by large-scale sequencing of environmental samples.

Fungi are an important and diverse component of soil communities, but these communities have proven difficult to study in conventional biotic surveys. We evaluated soil fungal diversity at two sites in a temperate forest using direct isolation of small-subunit and internal transcribed spacer (ITS) rRNA genes by PCR and high-throughput sequencing of cloned fragments. We identified 412 sequence types from 863 fungal ITS sequences, as well as 112 ITS sequences from other eukaryotic microorganisms. Equal proportions of Basidiomycota and Ascomycota sequences were present in both the ITS and small-subunit libraries, while members of other fungal phyla were recovered at much lower frequencies. Many sequences closely matched sequences from mycorrhizal, plant-pathogenic, and saprophytic fungi. Compositional differences were observed among samples from different soil depths, with mycorrhizal species predominating deeper in the soil profile and saprophytic species predominating in the litter layer. Richness was consistently lowest in the deepest soil horizon samples. Comparable levels of fungal richness have been observed following traditional specimen-based collecting and culturing surveys, but only after much more extensive sampling. The high rate at which new sequence types were recovered even after sampling 863 fungal ITS sequences and the dominance of fungi in our libraries relative to other eukaryotes suggest that the abundance and diversity of fungi in forest soils may be much higher than previously hypothesized. All sequences were deposited in GenBank, with accession numbers AY 969316 to AY 970290 for the ITS sequences and AY 969135 to AY 969315 for the SSU sequences.

Assessment of soil microbial community structure by use of taxon-specific quantitative PCR assays.

Here we describe a quantitative PCR-based approach to estimating the relative abundances of major taxonomic groups of bacteria and fungi in soil. Primers were thoroughly tested for specificity, and the method was applied to three distinct soils. The technique provides a rapid and robust index of microbial community structure.