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Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus-host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE.

Metagenomics studies have accelerated the discovery of novel or divergent viruses of the honey bee. However, most of these studies predominantly focused on RNA viruses, and many suffer from the relatively low abundance of viral nucleic acids in the samples (i.e., compared to that of the host). Here, we explored the virome of the Ethiopian honey bee, Apis mellifera simensis , using an unbiased metagenomic approach in which the next-generation sequencing step was preceded by an enrichment protocol for viral particles. Our study revealed five well-known bee viruses and 25 atypical virus species, most of which have never been found in A. mellifera before. The viruses belong to Iflaviridae , Dicistroviridae , Secoviridae , Partitiviridae , Parvoviridae , Potyviridae, and taxonomically unclassified families. Fifteen of these atypical viruses were most likely plant-specific, and the remaining ten were presumed to be insect-specific. Apis mellifera filamentous virus (AmFV) was found in one sampling site out of 10. Two samples contained high read counts of a virus similar to Diatraea saccharales densovirus (DsDNV), which is a virus that causes high mortality in the sugarcane borer. AmFV and the DsDNV-like virus were the only DNA viruses found. Three viruses that primarily infect Drosophila spp. were also discovered: La Jolla virus (LJV), Kilifi virus (KiV), and Thika virus. Our study suggests that phoretic varroa mites are involved in the transmission of LJV and KiV and that both viruses replicate in mites and adult bees. We also found an overwhelming dominance of the deformed wing virus type B variant, which fits well with the apparently harmless infestation by Varroa destructor . It was suggested that Ethiopian bees have developed tolerance against virus infections as the result of natural selection.

A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon.

A major limitation for better understanding the role of the human gut virome in health and disease is the lack of validated methods that allow high throughput virome analysis. To overcome this, we evaluated the quantitative effect of homogenisation, centrifugation, filtration, chloroform treatment and random amplification on a mock-virome (containing nine highly diverse viruses) and a bacterial mock-community (containing four faecal bacterial species) using quantitative PCR and next-generation sequencing. This resulted in an optimised protocol that was able to recover all viruses present in the mock-virome and strongly alters the ratio of viral versus bacterial and 16S rRNA genetic material in favour of viruses (from 43.2% to 96.7% viral reads and from 47.6% to 0.19% bacterial reads). Furthermore, our study indicated that most of the currently used virome protocols, using small filter pores and/or stringent centrifugation conditions may have largely overlooked large viruses present in viromes. We propose NetoVIR (Novel enrichment technique of VIRomes), which allows for a fast, reproducible and high throughput sample preparation for viral metagenomics studies, introducing minimal bias. This procedure is optimised mainly for faecal samples, but with appropriate concentration steps can also be used for other sample types with lower initial viral loads.

Animal host-microbe interactions are a relevant concern for wildlife conservation, particularly regarding generalist pathogens, where domestic host species can play a role in the transmission of infectious agents, such as viruses, to wild animals. Knowledge on viral circulation in wild host species is still scarce and can be improved by the recent advent of modern molecular approaches. We aimed to characterize the fecal virome and identify viruses of potential conservation relevance of diarrheic free-ranging wolves and sympatric domestic dogs from Central Portugal, where a small and threatened wolf population persists in a highly anthropogenically modified landscape. Using viral metagenomics, we screened diarrheic stools collected from wolves ( n = 8), feral dogs ( n = 4), and pet dogs ( n = 6), all collected within wolf range. We detected novel highly divergent viruses as well as known viral pathogens with established effects on population dynamics, including canine distemper virus, a novel bocavirus, and canine minute virus. Furthermore, we performed a 4-year survey for the six wolf packs comprising this endangered wolf population, screening 93 fecal samples from 36 genetically identified wolves for canine distemper virus and the novel bocavirus, previously identified using our metagenomics approach. Our novel approach using metagenomics for viral screening in noninvasive samples of wolves and dogs has profound implications on the knowledge of both virology and wildlife diseases, establishing a complementary tool to traditional screening methods for the conservation of threatened species. [ABSTRACT FROM AUTHOR]