Measuring air metagenomic diversity in an agricultural ecosystem

Affiliations
  • 1Natural History Museum, London SW7 5BD, UK; Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki 00014, Finland.
  • 2Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK; Enza Zaden, Enkhuizen 1602 DB, the Netherlands.
  • 3Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK.
  • 4Crop Genetics Department, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK.
  • 5Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK. Electronic address: richard.leggett@earlham.ac.uk.
  • 6Natural History Museum, London SW7 5BD, UK. Electronic address: matt.clark@nhm.ac.uk.

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Abstract

All species shed DNA during life or in death, providing an opportunity to monitor biodiversity via environmental DNA (eDNA). In recent years, combining eDNA, high-throughput sequencing technologies, bioinformatics, and increasingly complete sequence databases has promised a non-invasive and non-destructive environmental monitoring tool. Modern agricultural systems are often large monocultures and so are highly vulnerable to disease outbreaks. Pest and pathogen monitoring in agricultural ecosystems is key for efficient and early disease prevention, lower pesticide use, and better food security. Although the air is rich in biodiversity, it has the lowest DNA concentration of all environmental media and yet is the route for windborne spread of many damaging crop pathogens. Our work suggests that ecosystems can be monitored efficiently using airborne nucleic acid information. Here, we show that the airborne DNA of microbes can be recovered, shotgun sequenced, and taxonomically classified, including down to the species level. We show that by monitoring a field growing key crops we can identify the presence of agriculturally significant pathogens and quantify their changing abundance over a period of 1.5 months, often correlating with weather variables. We add to the evidence that aerial eDNA can be used as a source for biomonitoring in terrestrial ecosystems, specifically highlighting agriculturally relevant species and how pathogen levels correlate with weather conditions. Our ability to detect dynamically changing levels of species and strains highlights the value of airborne eDNA in agriculture, monitoring biodiversity changes, and tracking taxa of interest.