Combining air sampling and DNA metabarcoding to monitor plant pathogens

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dc.contributor.authorReich, Jonathan
dc.contributor.authorChen, Wen
dc.contributor.authorRadford, Devon
dc.contributor.authorTurkington, Kelly
dc.contributor.authorYevtushenko, Dmytro P.
dc.contributor.authorHamelin, Richard
dc.contributor.authorChatterton, Syama
dc.date.accessioned2024-08-21T18:36:30Z
dc.date.available2024-08-21T18:36:30Z
dc.date.issued2023
dc.descriptionOpen access article. Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license (CC BY-NC-ND 4.0) applies
dc.description.abstractMonitoring the air for airborne plant pathogens is an increasingly common method for the management of economically important plant diseases. In Alberta, Canada, several commodity clusters, including dry bean, canola, potato, and wheat, currently support air monitoring research programs for airborne pathogens of interest. In this study, we assessed the feasibility of monitoring for these, and more, plant fungal pathogens simultaneously using two different sampler types (cyclone versus rotation impaction) and by metabarcoding the ITS1 region using the Illumina sequencing platform. We collected air samples from four geographically distant sites across Alberta and monitored four crop types in southern Alberta. Overall, we found weak, but statistically significant, effects of geographic location and crop type on the aeromycobiota community composition. A few common taxa, such as Ramularia, Alternaria, and Epicoccum, constituted the vast majority of reads across all samples. Nevertheless, in each sample, we identified many plant pathogens of interest and organisms that previous research has found antagonistic to those pathogens, highlighting the utility of these approaches in understanding the pathobiome. In assessing the real-world implications of read counts, we discovered that they were only weakly correlated with spore counts quantified by qPCR. The two types of samplers collected different community profiles, reinforcing the importance of carefully considering which sampler type to use in monitoring programs. Taken together, our results show promise for the future of monitoring the air pathobiome, although much more work is required to understand the relationship of airborne communities to their in-field impact on disease development.
dc.description.peer-reviewYes
dc.identifier.citationReich, J., Chen, W., Radford, D., Turkington, K., Yevtushenko, D., Hamelin, R., & Chatterton, S. (2023). Combining air sampling and DNA metabarcoding to monitor plant pathogens. PhytoFrontiers, 3(3), 639-653. https://doi.org/10.1094/PHYTOFR-10-22-0108-R
dc.identifier.urihttps://hdl.handle.net/10133/6876
dc.language.isoen
dc.publisherAPS Publications
dc.publisher.departmentDepartment of Biological Sciences
dc.publisher.facultyArts and Science
dc.publisher.institutionLethbridge Research and Development Centre
dc.publisher.institutionUniversity of British Columbia
dc.publisher.institutionOttawa Research and Development Centre
dc.publisher.institutionLacombe Research and Development Centre
dc.publisher.institutionUniversity of Lethbridge
dc.publisher.urlhttps://doi.org/10.1094/PHYTOFR-10-22-0108-R
dc.subjectAerobiology
dc.subjectAir microbiome
dc.subjectAmplicon sequencing
dc.subjectIllumina
dc.subjectMetabar-coding
dc.subjectNext-generation sequencing
dc.subjectPlant pathogen
dc.subjectqPCR
dc.subjectAir sampling
dc.subject.lcshAir--Microbiology
dc.subject.lcshHigh-throughput nucleotide sequencing
dc.subject.lcshPlant-pathogen relationships
dc.titleCombining air sampling and DNA metabarcoding to monitor plant pathogens
dc.typeArticle
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