4.6 Article

Development and Validation of a Bioinformatic Workflow for the Rapid Detection of Viruses in Biosecurity

Journal

VIRUSES-BASEL
Volume 14, Issue 10, Pages -

Publisher

MDPI
DOI: 10.3390/v14102163

Keywords

biosecurity; virology; bioinformatics; high-throughput sequencing; Oxford Nanopore; Illumina; DNA; RNA

Categories

Funding

  1. Ministry for Primary Industries Operational Research Programme [406084]

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The field of biosecurity has greatly benefited from high-throughput sequencing technologies, but the bioinformatics tools designed for rapid analysis of these sequencing datasets are not developed with biosecurity applications in mind. Many current virus-detection pipelines are not adequate for identifying plant- and animal-infecting viruses. Our work demonstrated that several methods provide sensitive and specific detection of agriculturally important viruses in a timely manner, providing a key piece of ground truthing for method development in this space.
The field of biosecurity has greatly benefited from the widespread adoption of high-throughput sequencing technologies, for its ability to deeply query plant and animal samples for pathogens for which no tests exist. However, the bioinformatics analysis tools designed for rapid analysis of these sequencing datasets are not developed with this application in mind, limiting the ability of diagnosticians to standardise their workflows using published tool kits. We sought to assess previously published bioinformatic tools for their ability to identify plant- and animal-infecting viruses while distinguishing from the host genetic material. We discovered that many of the current generation of virus-detection pipelines are not adequate for this task, being outperformed by more generic classification tools. We created synthetic MinION and HiSeq libraries simulating plant and animal infections of economically important viruses and assessed a series of tools for their suitability for rapid and accurate detection of infection, and further tested the top performing tools against the VIROMOCK Challenge dataset to ensure that our findings were reproducible when compared with international standards. Our work demonstrated that several methods provide sensitive and specific detection of agriculturally important viruses in a timely manner and provides a key piece of ground truthing for method development in this space.

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