Polyomaviruses are a family of DNA tumor viruses that are known to infect mammals and birds. To investigate the deeper evolutionary history of the family, we used a combination of viral metagenomics, bioinformatics, and structural modeling approaches to identify and characterize polyomavirus sequences associated with fish and arthropods. Analyses drawing upon the divergent new sequences indicate that polyomaviruses have been gradually co-evolving with their animal hosts for at least half a billion years. Phylogenetic analyses of individual polyomavirus genes suggest that some modern polyomavirus species arose after ancient recombination events involving distantly related polyomavirus lineages. The improved evolutionary model provides a useful platform for developing a more accurate taxonomic classification system for the viral family Polyomaviridae. Polyomaviruses are a family of DNA-based viruses that are known to infect various terrestrial vertebrates, including humans. In this report, we describe our discovery of highly divergent polyomaviruses associated with various marine fish. Searches of public deep sequencing databases unexpectedly revealed the existence of polyomavirus-like sequences in scorpion and spider datasets. Our analysis of these new sequences suggests that polyomaviruses have slowly co-evolved with individual host animal lineages through an established mechanism known as intrahost divergence. The proposed model is similar to the mechanisms through with other DNA viruses, such as papillomaviruses, are thought to have evolved. Our analysis also suggests that distantly related polyomaviruses sometimes recombine to produce new chimeric lineages. We propose a possible taxonomic scheme that can account for these inferred ancient recombination events.

Viruses with circular ssDNA genomes that encode a replication initiator protein (Rep) are among the smallest viruses known to infect both eukaryotic and prokaryotic organisms. In the past few years an overwhelming diversity of novel circular Rep-encoding ssDNA (CRESS-DNA) viruses has been unearthed from various hosts and environmental sources. Since there is limited information regarding CRESS-DNA viruses in invertebrates, this study explored the diversity of CRESS-DNA viruses circulating among insect populations by targeting dragonflies (Epiprocta), top insect predators that accumulate viruses from their insect prey over space and time. Using degenerate PCR and rolling circle amplification coupled with restriction digestion, 17 CRESS-DNA viral genomes were recovered from eight different dragonfly species collected in tropical and temperate regions. Nine of the genomes are similar to cycloviruses and represent five species within this genus, suggesting that cycloviruses are commonly associated with insects. Three of the CRESS-DNA viruses share conserved genomic features with recently described viruses similar to the mycovirus Sclerotinia sclerotiorum hypovirulence-associated DNA virus 1, leading to the proposal of the genus Gemycircularvirus. The remaining viruses are divergent species representing four novel CRESS-DNA viral genera, including a gokushovirus-like prokaryotic virus (microphage) and three eukaryotic viruses with Reps similar to circoviruses. The novelty of CRESS-DNA viruses identified in dragonflies using simple molecular techniques indicates that there is an unprecedented diversity of ssDNA viruses among insect populations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were “novel” SNVs that had not yet been identified in the global clinical-derived data as of 17^th June 2020 (the day after our last wastewater sampling date). However, between 17^th of June 2020 and 20^th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

Dragonfly cyclovirus (DfCyV), a new species of ssDNA virus discovered using viral metagenomics in dragonflies (family Libellulidae) from the Kingdom of Tonga. Metagenomic sequences of DfCyV were similar to viruses of the recently proposed genus Cyclovirus within the family Circoviridae. Specific PCRs resulted in the recovery of 21 DfCyV genomes from three dragonfly species (Pantala flavescens, Tholymis tillarga and Diplacodes bipunctata). The 1741 nt DfCyV genomes share >95 % nucleotide identity and are classified into 11 subtypes representing a single strain. The DfCyV genomes share 48–63 % genome-wide nucleotide identity with cycloviruses identified in human faecal samples. Recombination analysis revealed three recombinant DfCyV genomes, suggesting that recombination plays an important role in cyclovirus evolution. To our knowledge, this is the first report of a circular ssDNA virus identified in insects, and the data may help elucidate evolutionary links among novel Circoviridae recently identified in animals and environmental samples.

Exogenous feline leukemia virus (FeLV) is a feline Gammaretrovirus that results in a variety of disease outcomes. Endogenous FeLV (enFeLV) is a replication-defective provirus found in species belonging to the Felis genus, which includes the domestic cat (Felis catus). There have been few studies examining interaction between enFeLV genotype and FeLV progression. We examined point-in-time enFeLV and FeLV viral loads, as well as occurrence of FeLV/enFeLV recombinants (FeLV-B), to determine factors relating to clinical disease in a closed breeding colony of cats during a natural infection of FeLV. Coinfections with feline foamy virus (FFV), feline gammaherpesvirus (FcaGHV-1), and feline coronavirus (FCoV) were also documented and analyzed for impact on cat health and FeLV disease. Correlation analysis and structural equation modeling techniques were used to measure interactions among disease parameters. Progressive FeLV disease and FeLV-B presence were associated with higher FeLV proviral and plasma viral loads. Female cats were more likely to have progressive disease and FeLV-B. Conversely, enFeLV copy number was higher in male cats and negatively associated with progressive FeLV disease. Males were more likely to have abortive FeLV disease. FFV proviral load was found to correlate positively with higher FeLV proviral and plasma viral load, detection of FeLV-B, and FCoV status. Male cats were much more likely to be infected with FcaGHV-1 than female cats. This analysis provides insights into the interplay between endogenous and exogenous FeLV during naturally occurring disease, and reveals striking variation in the infection patterns among four chronic viral infections of domestic cats.