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Nanopore-Sequencing Metabarcoding for Identification of Phytopathogenic and Endophytic Fungi in Olive ( Olea europaea ) Twigs.

Ioannis TheologidisTimokratis KaramitrosAikaterini-Eleni VichouDimosthenis Kizis
Published in: Journal of fungi (Basel, Switzerland) (2023)
Metabarcoding approaches for the identification of plant disease pathogens and characterization of plant microbial populations constitute a rapidly evolving research field. Fungal plant diseases are of major phytopathological concern; thus, the development of metabarcoding approaches for the detection of phytopathogenic fungi is becoming increasingly imperative in the context of plant disease prognosis. We developed a multiplex metabarcoding method for the identification of fungal phytopathogens and endophytes in olive young shoots, using the MinION sequencing platform (Oxford Nanopore Technologies). Selected fungal-specific primers were used to amplify three different genomic DNA loci (ITS, beta-tubulin, and 28S LSU) originating from olive twigs. A multiplex metabarcoding approach was initially evaluated using healthy olive twigs, and further assessed with naturally infected olive twig samples. Bioinformatic analysis of basecalled reads was carried out using MinKNOW, BLAST+ and R programming, and results were also evaluated using the BugSeq cloud platform. Data analysis highlighted the approaches based on ITS and their combination with beta-tubulin as the most informative ones according to diversity estimations. Subsequent implementation of the method on symptomatic samples identified major olive pathogens and endophytes including genera such as Cladosporium , Didymosphaeria , Paraconiothyrium , Penicillium, Phoma, Verticillium , and others.
Keyphrases
  • cell wall
  • data analysis
  • high throughput
  • single molecule
  • real time pcr
  • healthcare
  • bioinformatics analysis
  • quality improvement
  • antimicrobial resistance
  • circulating tumor
  • cell free
  • sensitive detection