Towards improved detection and identification of rust fungal pathogens in environmental samples using a metabarcoding approach

Abstract

The dispersion of fungal inocula such as the airborne spores of rust fungi (Pucciniales) can be monitored by metabarcoding the internal transcribed spacer 2 (ITS2) of the rRNA gene in environmental DNAs. This is largely dependent upon a high-quality reference database (refDB) and primers with proper taxonomic coverage and specificity. For this study, a curated ITS2 reference database (named CR-ITS2-refDB) comprising representatives of the major cereal rust fungi and phylogenetically related species was compiled. Inter- and intra-specific variation analyses suggested that the ITS2 region had reasonable discriminating power for the majority of the Puccinia species or species complexes in the database. In silico evaluation of nine forward and seven reverse ITS2 primers, including three newly designed, revealed marked variation in DNA amplification efficiency for the rusts. The theoretical assessment of rust-enhanced (Rust2inv/ITS4var_H) and universal fungal (ITS9F/ITS4) ITS2 primer pairs was validated by profiling the airborne rust fungal communities from environmental samples using a metabarcoding approach. Species or subspecific level identification of the rusts was improved by using CR-ITS2-refDB, and the Automated Oligonucleotide Design Pipeline (AODP), which identified all mutations distinguishing highly conserved DNA markers amongst close relatives. A generic bioinformatics pipeline was developed, including all steps employed in this study from in silico evaluation of primers to accurate identification of short metabarcodes at the level of interest for defining phytopathogens. The results highlighted the importance of primer selection, refDBs that are resolved to reflect phylogenetic relationships, and the use of AODP for improving the reliability of metabarcoding in phytopathogen biosurveillance.