Detection of Phytophthora, Pythium, Globisporangium, Hyaloperonospora, and Plasmopara Species in High-Throughput Sequencing Data by In Silico and In Vitro Analysis Using Microbe Finder (MiFi)

Abstract

Species identification of plant pathogenic oomycetes based on morphology is challenging because of the limited number of variable characters available. Hence, pure culture isolation followed by internal transcribed spacer sequencing is routinely conducted for diagnostic purposes. E-probe Diagnostic Nucleic acid Analysis (EDNA), a pipeline that couples high-throughput sequencing and metagenomic sequence analysis, is a detection system used to identify targets without relying on often time-consuming serological and molecular approaches. The EDNA pipeline, implemented through the Microbe Finder (MiFi), was used to design short species-specific sequences (e-probes) with sizes from 40 to 80 nucleotides and to detect plant pathogenic oomycetes in metagenomic data. To avoid false positives and increase target specificity, we removed the e-probes with sequences similar to nontarget species in NCBI's nucleotide database. The designed e-probes were tested using in silico simulated metagenomes with different target pathogen and host sequence levels. E-probes of Phytophthora nicotianae were further tested with metagenomes generated using nanopore sequencing. In silico detection with 100% sensitivity was obtained at 0.01 to 1% pathogen read abundances with the three e-probe lengths tested. MiFi also successfully identified Ph. nicotianae in the sequenced metagenomes with nanopore DNA sequencing. Thus, EDNA-MiFi could enable rapid detection (<24 h from sample collection to diagnosis) without requiring post-sequencing processing. EDNA, as implemented in the MiFi web application, is a powerful tool for detecting oomycetes from metagenomic samples. Our study shows the outstanding potential of EDNA-MiFi coupled with nanopore sequencing for plant and possible on-site pathogen diagnosis. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .