Invasions by non-native forest pathogens are a major threat facing forests worldwide. Early detection and eradication are the most economical and feasible means of preventing outbreaks. Current detection methods that combine culture-based and molecular diagnostics haven proven insufficient, because they require specialized skills and are too targeted, too slow or too costly for the rapid identification of unknown microbial pathogens, all of which confine early detection efforts. Oxford Nanopore Technologies has released a series of nanopore sequencers that can provide users a variety of metagenomic sequencing abilities in their own labs. This technology is physically small and highly portable, has extremely low capital investments, provides real-time analysis, and has simplistic operation, making it an appealing method for molecular disease diagnostics. Despite these advantages, nanopore sequencing has not been readily adopted by the forestry industry, and comprehensive tests of its efficacy in forest pathosystems and under in-field conditions are needed. Adapting this technology for tree diagnostics will be an important step in improving forest security through better diagnostics and simpler and faster detection of invasive pests.
This study is aimed at comparing the performance of the nanopore sequencer (MinION Mk1C) to the well-established high-throughput sequencing platform Illumina, in terms of identification of pine needle-associated fungal species. DNA was extracted from 145 samples of pine needles from various locations in Sweden, and the ITS regions (ITS1, 5.8S and ITS2 for the Nanopore sequences, only ITS2 for the Illumina) were amplified through PCR for each of the samples - a metabarcoding approach. The nanopore sequencing was done in our lab, while the Illumina service was provided by NovoGene. The relevant parameters for comparison, for the detection and identification of pine pathogens, are i) number of species detected ii) the read distribution among identified species iii) taxonomic resolution provided by the sequencing platform. Computing power and storage are therefore required for data analysis of both the Nanopore and the Illumina sequencing metabarcoding data.