This five-year project finished in mid-2022.
Early plant pathogen detection is a prerequisite for border biosecurity. Here we validated a previous PCR method for the detection of pathogenic pseudomonads, showing the potential through comparative genomics to detect strains of otherwise uncharacterized pathogenicity.
To improve on the efficiency of developing and using genome sequences to identify pathogen species and markers indicative of pathogenicity, we explored metagenomics sequencing, comparing Illumina HiSeq and Oxford Nanopore Technology.
Using DNA of kiwifruit plants simultaneously infected with three Pseudomonas syringae and one Pectobacterium actinidiae strains as a model system, we were able to detect the pathogens in symptomatic and asymptomatic tissue regardless of the long (nanopore) or short read (HiSeq) platform. This approach was tested with additional pathogens, Xylella fastidiosa in NZ indigenous plants growing overseas (B3), and Xanthomonas citri subsp. malvacearum in cotton (Australian RRD4P research). With HiSeq we were able to identify the pathogens to the pathovar level by detecting specific genetic markers sequences within the sequencing data. With nanopore, we were able to identify some of the pathogens to the strain level. Others that were only assigned to closely related strains was likely due to the limited number of microbial genomes in the reference database and so the building of a custom reference database is recommended.
Nanopore sequencing has a much faster turnaround than HiSeq and it brings the possibility of metagenome-assembled genomes with longer contigs which confers better identification than HiSeq.
With the development here of pathogenicity markers and bioinformatic pipelines, and continued advances in nanopore as a sequencing platform, this has been considered with MPI to be the diagnostic platform going forward and feeds into their implementation of this technology for the detection of bacterial plant pathogens.
The Zotero database can be found on the B3 homepage under ‘Outputs’.