We need to talk about metabarcoding: identification of Phytophthora species in environmental samples

Abstract

The PHYTO-THREATS project aims to address risks to UK forest and woodland ecosystems from pathogenic Phytophthora species, which impact forests and woodlands on a global scale. Trade in ornamental plants, which may harbour invasive pathogens, is a driver of disease outbreaks, so we are examining the distribution and diversity of Phytophthora in UK plant nursery systems, to identify good practices that restrict pathogen spread. ITS1 metabarcoding is a modern, high-throughput, more sensitive alternative to conventional culturing and baiting, for identification of Phytophthora in environmental samples. This approach can potentially detect all species (known or unknown) of the target genus that are present in the sample. However, the method’s extreme sensitivity and prevalence of sequencing artefacts presents problems for identification and interpretation, especially in regulatory contexts. We present evidence from a study that demonstrates the rigorous application of ITS1 metabarcoding using Illumina sequencing for detection and identification of Phytophthora species in environmental samples. We also present THAPBI-pict, a new software tool for Phytophthora ITS1 metabarcoding sequence classification.