PhytoFrontiers (Dec 2023)

Evaluation of Metabarcoding Methods for Plant Disease Surveillance

  • Eric A. Newberry,
  • Subodh Srivastava,
  • Schyler O. Nunziata,
  • Reny Mathew,
  • Nakhla Mark,
  • Yazmín Rívera

DOI
https://doi.org/10.1094/PHYTOFR-01-23-0002-R
Journal volume & issue
Vol. 3, no. 4
pp. 785 – 794

Abstract

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Metabarcoding holds great potential for general plant pathogen surveillance by providing an untargeted profile of the host microbiome. However, the standard marker utilized for microbiome analysis of prokaryotes, the 16 rRNA gene, offers limited diagnostic utility as it provides phylogenetic resolution primarily at the genus level, and universal primers often co-amplify plant DNA. Here, we evaluated two recently published universal primer sets targeting the DNA gyrase and RNA polymerase ß subunit genes (gyrB and rpoB, respectively), relative to a plant discriminating 16S primer set (799F/1115R), as disease surveillance tools. Comparative analysis of a mock bacterial community, as well as naturally infected citrus variegated chlorosis samples, indicated that the gyrB method displayed optimal performance in the amplification of DNA across a broad taxonomic spectrum of plant-pathogenic bacteria, providing resolution at the species and, in some cases, subspecies levels. It also generated high-quality datasets with minimal to no co-amplification of plant DNA, outperforming the rpoB and 16S assays in these regards. Further evaluation revealed that the gyrB method displayed an overall linear trend in the detection of several diverse bacterial pathogens; however, it was at least an order of magnitude less sensitive than a standard real-time PCR assay. Finally, we demonstrate the potential of this method to disentangle a mixed population of Pantoea spp. associated with a rice-bacterial blight outbreak and identify putative novel pathogens that would otherwise be overlooked with conventional PCR-based tests. This work represents steps toward establishing a robust, untargeted metabarcoding method for general plant disease surveillance. [Figure: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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