P-334 - Evaluating long-read metabarcoding to detect fungal and oomycete pathogens in the OSU Plant Clinic

The Oregon State University Plant Clinic diagnoses fungal and oomycete diseases by culturing pathogens from plant tissue and/or by pathogen-specific molecular assays (e.g. qPCR, PCR). However, culturing often limits pathogen identification to the genus-level, requires expertise in fungal morphology, and is not scalable. Likewise, most molecular assays only test for a single pathogen and therefore are inefficient when testing for multiple pathogens. To overcome these limitations, we evaluated the use of long-read metabarcoding using Oxford Nanopore Technologies sequencing for pathogen detection. We selected 40 representative samples diagnosed with various fungal, oomycete, or abiotic diseases as a proof of concept for analysis. Barcode regions were amplified directly from diseased plant tissue. For fungal samples, the full-length ITS region was amplified; and for oomycete samples, the rps10 and adjacent tRNA region was amplified. For samples with abiotic diseases, both the ITS and rps10 regions were amplified to check for fungal or oomycete pathogens that could lead to false diagnoses. We sequenced the amplicons on the MinION Mk1b sequencer and assigned taxonomy to reads to determine the identity of all fungal and oomycete taxa present in each sample. We then compared these results to the clinical diagnosis for each sample to characterize their accuracy for identifying fungal and oomycete pathogens.