4.7 Article

Metagenomic sequencing for detection and identification of the boxwood blight pathogen Calonectria pseudonaviculata

Journal

SCIENTIFIC REPORTS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-022-05381-x

Keywords

-

Funding

  1. Virginia Agricultural Council [PFJK4I7B]
  2. School of Plant and Environmental Sciences at Virginia Tech
  3. Virginia Tech graduate program in Genetics, Bioinformatics and Computational Biology at Virginia Tech
  4. Virginia Agricultural Experiment Station
  5. Hatch Program of the National Institute of Food and Agriculture, United States Department of Agriculture

Ask authors/readers for more resources

Pathogen detection and identification are crucial for controlling disease outbreaks. Traditional diagnostic methods may not be suitable for distinguishing morphologically similar fungal plant pathogens that grow slowly in culture. Whole genome metagenomic sequencing is a promising technique as it can detect any pathogen without culturing. In this study, the technique was successfully applied to the detection of the fungus Calonectria pseudonaviculata, the causal agent of boxwood blight disease.
Pathogen detection and identification are key elements in outbreak control of human, animal, and plant diseases. Since many fungal plant pathogens cause similar symptoms, are difficult to distinguish morphologically, and grow slowly in culture, culture-independent, sequence-based diagnostic methods are desirable. Whole genome metagenomic sequencing has emerged as a promising technique because it can potentially detect any pathogen without culturing and without the need for pathogen-specific probes. However, efficient DNA extraction protocols, computational tools, and sequence databases are required. Here we applied metagenomic sequencing with the Oxford Nanopore Technologies MinION to the detection of the fungus Calonectria pseudonaviculata, the causal agent of boxwood (Buxus spp.) blight disease. Two DNA extraction protocols, several DNA purification kits, and various computational tools were tested. All DNA extraction methods and purification kits provided sufficient quantity and quality of DNA. Several bioinformatics tools for taxonomic identification were found suitable to assign sequencing reads to the pathogen with an extremely low false positive rate. Over 9% of total reads were identified as C. pseudonaviculata in a severely diseased sample and identification at strain-level resolution was approached as the number of sequencing reads was increased. We discuss how metagenomic sequencing could be implemented in routine plant disease diagnostics.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available