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1000
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Abstract/Summary
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Proactive approaches in preventing future epidemics include pathogen discovery prior to their emergence in human and/or animal populations. Playing an important role in pathogen discovery, high-throughput sequencing (HTS) enables the characterization of microbial and viral genetic diversity within a given sample. In particular, metagenomic HTS allows the unbiased taxonomic profiling of sequences; hence, it can identify novel and highly divergent pathogens such as viruses. Newly discovered viral sequences must be further investigated using genomic characterization, molecular and serological screening, and/or invitro and invivo characterization. Several outbreak and surveillance studies apply unbiased generic HTS to characterize the whole genome sequences of suspected pathogens. In contrast, this study aimed to screen for novel and unexpected pathogens in previously generated HTS datasets and use this information as a starting point for the establishment of an early warning system (EWS). As a proof of concept, the EWS was applied to HTS datasets and archived samples from the 2018–9 West Nile virus (WNV) epidemic in Germany. A metagenomics read classifier detected sequences related to genome sequences of various members of Riboviria. We focused the further EWS investigation on viruses belonging to the families Peribunyaviridae and Reoviridae, under suspicion of causing co-infections in WNV-infected birds. Phylogenetic analyses revealed that the reovirus genome sequences clustered with sequences assigned to the species Umatilla virus (UMAV), whereas a new peribunyavirid, tentatively named ‘Hedwig virus’ (HEDV), belonged to a putative novel genus of the family Peribunyaviridae. In follow-up studies, newly developed molecular diagnostic assays detected fourteen UMAV-positive wild birds from different German cities and eight HEDV-positive captive birds from two zoological gardens. UMAV was successfully cultivated in mosquito C6/36 cells inoculated with a blackbird liver. In conclusion, this study demonstrates the power of the applied EWS for the discovery and characterization of unexpected viruses in repurposed sequence datasets, followed by virus screening and cultivation using archived sample material. The EWS enhances the strategies for pathogen recognition before causing sporadic cases and massive outbreaks and proves to be a reliable tool for modern outbreak preparedness.
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