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Investigating fungal diversity through metabarcoding for environmental samples: assessment of ITS1 and ITS2 Illumina sequencing using multiple defined mock communities with different classification methods and reference databases

Summary

Scientists developed a comprehensive method for identifying different fungi in environmental samples using DNA sequencing technology called metabarcoding. They tested 37 mixtures of known fungi species to compare different approaches, including which DNA markers to use, which reference databases to search, and which computer analysis methods to apply. The study found that the choice of method significantly affects results, with some approaches better at genus-level identification and others at species identification, helping researchers select the best approach for their specific needs.

Background

Fungi are diverse organisms with important roles in ecosystems and significant impacts on human health and food safety. Metabarcoding using the internal transcribed spacer (ITS) region is the standard method for identifying fungal species in complex environmental samples, but multiple methodological choices affect classification accuracy.

Objective

To evaluate the optimal setup for fungal metabarcoding using Illumina sequencing by assessing different sequenced regions (ITS1 and ITS2), reference databases (UNITE versus BCCM/IHEM), bioinformatics software (BLAST versus mothur), and taxonomic classification levels using 37 defined mock communities.

Results

Classification performance varied depending on all tested variables, with 56-100% of species correctly assigned. ITS2 showed slightly better precision than ITS1 with comparable recall. The BCCM/IHEM database outperformed UNITE, and BLAST provided better performance but required expert curation while mothur performed better in automated workflows. Genus-level classification consistently outperformed species-level classification, while abundance estimation from read counts performed poorly.

Conclusion

Metabarcoding with Illumina sequencing effectively investigates fungal diversity in complex environmental samples, though optimal setup depends on specific research objectives. The choice of ITS region, database, and classification method significantly impacts results, with genus-level classification recommended over species-level when discriminatory power is limited for certain taxa.
  • Published in:BMC Genomics,
  • Study Type:Comparative Methodological Study,
  • Source: PMID: 40770684, DOI: 10.1186/s12864-025-11917-y
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