Metagenomic analysis of viruses from bat fecal samples reveals many novel viruses in insectivorous bats in China

Increasing data indicate that bats harbor diverse viruses, some of which cause severe human diseases. In this study, sequence-independent amplification and high-throughput sequencing (Solexa) were applied to the metagenomic analysis of viruses in bat fecal samples collected from 6 locations in China. A total of 8,746,417 reads with a length of 306,124,595 bp were obtained. Among these reads, 13,541 (0.15%) had similarity to phage sequences and 9,170 (0.1%) had similarity to eukaryotic virus sequences. A total of 129 assembled contigs (>100 nucleotides) were constructed and compared with GenBank: 32 contigs were related to phages, and 97 were related to eukaryotic viruses. The most frequent reads and contigs related to eukaryotic viruses were homologous to densoviruses, dicistroviruses, coronaviruses, parvoviruses, and tobamoviruses, a range that includes viruses from invertebrates, vertebrates, and plants. Most of the contigs had low identities to known viral genomic or protein sequences, suggesting that a large number of novel and genetically diverse insect viruses as well as putative mammalian viruses are transmitted by bats in China. This study provides the first preliminary understanding of the virome of some bat populations in China, which may guide the discovery and isolation of novel viruses in the future.     

Short prokaryotic DNA fragment binning using a hierarchical classifier based on linear discriminant analysis and principal component analysis

Metagenomics is an emerging field in which the power of genomic analysis is applied to an entire microbial community, bypassing the need to isolate and culture individual microbial species. Assembling of metagenomic DNA fragments is very much like the overlap-layout-consensus procedure for assembling isolated genomes, but is augmented by an additional binning step to differentiate scaffolds, contigs and unassembled reads into various taxonomic groups. In this paper, we employed n-mer oligonucleotide frequencies as the features and developed a hierarchical classifier (PCAHIER) for binning short (≤ 1,000 bps) metagenomic fragments. The principal component analysis was used to reduce the high dimensionality of the feature space. The hierarchical classifier consists of four layers of local classifiers that are implemented based on the linear discriminant analysis. These local classifiers are responsible for binning prokaryotic DNA fragments into superkingdoms, of the same superkingdom into phyla, of the same phylum into genera, and of the same genus into species, respectively. We evaluated the performance of the PCAHIER by using our own simulated data sets as well as the widely used simHC synthetic metagenome data set from the IMG/M system. The effectiveness of the PCAHIER was demonstrated through comparisons against a non-hierarchical classifier, and two existing binning algorithms (TETRA and Phylopythia).     

Metagenomic abundance estimation and diagnostic testing on species level

One goal of sequencing-based metagenomic community analysis is the quantitative taxonomic assessment of microbial community compositions. In particular, relative quantification of taxons is of high relevance for metagenomic diagnostics or microbial community comparison. However, the majority of existing approaches quantify at low resolution (e.g. at phylum level), rely on the existence of special genes (e.g. 16S), or have severe problems discerning species with highly similar genome sequences. Yet, problems as metagenomic diagnostics require accurate quantification on species level. We developed Genome Abundance Similarity Correction (GASiC), a method to estimate true genome abundances via read alignment by considering reference genome similarities in a non-negative LASSO approach. We demonstrate GASiC’s superior performance over existing methods on simulated benchmark data as well as on real data. In addition, we present applications to datasets of both bacterial DNA and viral RNA source. We further discuss our approach as an alternative to PCR-based DNA quantification.     

RNA Viral Metagenome of Whiteflies Leads to the Discovery and Characterization of a Whitefly-Transmitted Carlavirus in North America

Whiteflies from the Bemisia tabaci species complex have the ability to transmit a large number of plant viruses and are some of the most detrimental pests in agriculture. Although whiteflies are known to transmit both DNA and RNA viruses, most of the diversity has been recorded for the former, specifically for the Begomovirus genus. This study investigated the total diversity of DNA and RNA viruses found in whiteflies collected from a single site in Florida to evaluate if there are additional, previously undetected viral types within the B. tabaci vector. Metagenomic analysis of viral DNA extracted from the whiteflies only resulted in the detection of begomoviruses. In contrast, whiteflies contained sequences similar to RNA viruses from divergent groups, with a diversity that extends beyond currently described viruses. The metagenomic analysis of whiteflies also led to the first report of a whitefly-transmitted RNA virus similar to Cowpea mild mottle virus (CpMMV Florida) (genus Carlavirus) in North America. Further investigation resulted in the detection of CpMMV Florida in native and cultivated plants growing near the original field site of whitefly collection and determination of its experimental host range. Analysis of complete CpMMV Florida genomes recovered from whiteflies and plants suggests that the current classification criteria for carlaviruses need to be reevaluated. Overall, metagenomic analysis supports that DNA plant viruses carried by B. tabaci are dominated by begomoviruses, whereas significantly less is known about RNA viruses present in this damaging insect vector.     

Viral RNA Intermediates as Targets for Detection and Discovery of Novel and Emerging Mosquito-Borne Viruses

Mosquito-borne viruses encompass a range of virus families, comprising a number of significant human pathogens (e.g., dengue viruses, West Nile virus, Chikungunya virus). Virulent strains of these viruses are continually evolving and expanding their geographic range, thus rapid and sensitive screening assays are required to detect emerging viruses and monitor their prevalence and spread in mosquito populations. Double-stranded RNA (dsRNA) is produced during the replication of many of these viruses as either an intermediate in RNA replication (e.g., flaviviruses, togaviruses) or the double-stranded RNA genome (e.g., reoviruses). Detection and discovery of novel viruses from field and clinical samples usually relies on recognition of antigens or nucleotide sequences conserved within a virus genus or family. However, due to the wide antigenic and genetic variation within and between viral families, many novel or divergent species can be overlooked by these approaches. We have developed two monoclonal antibodies (mAbs) which show co-localised staining with proteins involved in viral RNA replication in immunofluorescence assay (IFA), suggesting specific reactivity to viral dsRNA. By assessing binding against a panel of synthetic dsRNA molecules, we have shown that these mAbs recognise dsRNA greater than 30 base pairs in length in a sequence-independent manner. IFA and enzyme-linked immunosorbent assay (ELISA) were employed to demonstrate detection of a panel of RNA viruses from several families, in a range of cell types. These mAbs, termed monoclonal antibodies to viral RNA intermediates in cells (MAVRIC), have now been incorporated into a high-throughput, economical ELISA-based screening system for the detection and discovery of viruses from mosquito populations. Our results have demonstrated that this simple system enables the efficient detection and isolation of a range of known and novel viruses in cells inoculated with field-caught mosquito samples, and represents a rapid, sequence-independent, and cost-effective approach to virus discovery.     

PhylOTU: a high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data

Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU-finding methods. To circumvent these limitations, we developed PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity?     

Simultaneous virus identification and characterization of severe unexplained pneumonia cases using a metagenomics sequencing technique

Many viruses can cause respiratory diseases in humans. Although great advances have been achieved in methods of diagnosis, it remains challenging to identify pathogens in unexplained pneumonia (UP) cases. In this study, we applied next-generation sequencing (NGS) technology and a metagenomic approach to detect and characterize respiratory viruses in UP cases from Guizhou Province, China. A total of 33 oropharyngeal swabs were obtained from hospitalized UP patients and subjected to NGS. An unbiased metagenomic analysis pipeline identified 13 virus species in 16 samples. Human rhinovirus C was the virus most frequently detected and was identified in seven samples. Human measles virus, adenovirus B 55 and coxsackievirus A10 were also identified. Metagenomic sequencing also provided virus genomic sequences, which enabled genotype characterization and phylogenetic analysis. For cases of multiple infection, metagenomic sequencing afforded information regarding the quantity of each virus in the sample, which could be used to evaluate each viruses’ role in the disease. Our study highlights the potential of metagenomic sequencing for pathogen identification in UP cases.     

Cyanoseq: A database of cyanobacterial 16S rRNA gene sequences with curated taxonomy

Cyanobacteria are photosynthetic bacteria that occupy various habitats across the globe, playing critical roles in many of Earth's biogeochemical cycles both in both aquatic and terrestrial systems. Despite their well-known significance, their taxonomy remains problematic and is the subject of much research. Taxonomic issues of Cyanobacteria have consequently led to inaccurate curation within known reference databases, ultimately leading to problematic taxonomic assignment during diversity studies. Recent advances in sequencing technologies have increased our ability to characterize and understand microbial communities, leading to the generation of thousands of sequences that require taxonomic assignment. We herein propose CyanoSeq ( https://zenodo.org/record/7569105 ), a database of cyanobacterial 16S rRNA gene sequences with curated taxonomy. The taxonomy of CyanoSeq is based on the current state of cyanobacterial taxonomy, with ranks from the domain to genus level. Files are provided for use with common naive Bayes taxonomic classifiers, such as those included in DADA2 or the QIIME2 platform. Additionally, FASTA files are provided for creation of de novo phylogenetic trees with (near) full-length 16S rRNA gene sequences to determine the phylogenetic relationship of cyanobacterial strains and/or ASV/OTUs. The database currently consists of 5410 cyanobacterial 16S rRNA gene sequences along with 123 Chloroplast, Bacterial, and Vampirovibrionia (formally Melainabacteria) sequences.     

Fur Seal Feces-Associated Circular DNA Virus Identified in Pigs in Anhui,China

Fur seal feces-associated circular DNA virus(FSfa CV) is an unclassified circular replication-associated protein(Rep)-encoding single-stranded(CRESS) DNA virus that has been detected in mammals(fur seals and pigs). The biology and epidemiology of the virus remain largely unknown. To investigate the virus diversity among pigs in Anhui Province,China, we pooled 600 nasal samples in 2017 and detected viruses using viral metagenomic methods. From the assembled contigs, 12 showed notably high nucleotide acid sequence similarities to the genome sequences of FSfa CVs. Based on these sequences, a full-length genome sequence of the virus was then obtained using overlapping PCR and sequencing, and the virus was designated as FSfa CV-CHN(Gen Bank No. MK462122). This virus shared 91.3% and 90.9% genome-wide nucleotide sequence similarities with the New Zealand fur seal strain FSfa CV-as50 and the Japanese pig strain FSfa CVJPN1, respectively. It also clustered with the two previously identified FSfa CVs in a unique branch in the phylogenetic tree based on the open reading frame 2(ORF2), Rep-coding gene, and the genome of the reference CRESS DNA viruses.Further epidemiological investigation using samples collected in 2018 showed that the overall positive rate for the virus was 56.4%(111/197) in Anhui Province. This is the first report of FSfa CVs identified in pigs in China, and further epidemiological studies are warranted to evaluate the influence of the virus on pigs.     

An evaluation of candidate plant DNA barcodes and assignment methods in diagnosing 29 species in the genus Agalinis (Orobanchaceae)

? Premise of the study: DNA barcoding has been proposed as a useful technique within many disciplines (e.g., conservation biology and forensics) for determining the taxonomic identity of a sample based on nucleotide similarity to samples of known taxonomy. Application of DNA barcoding to plants has primarily focused on evaluating the success of candidate barcodes across a broad spectrum of evolutionary divergence. Less attention has been paid to evaluating performance when distinguishing congeners or to differential success of analytical techniques despite the fact that the practical application and utility of barcoding hinges on the ability to distinguish closely related species. ? Methods: We tested the ability to distinguish among 92 samples representing 29 putative species in the genus Agalinis (Orobanchaceae) using 13 candidate barcodes and three analytical methods (i.e., threshold genetic distances, hierarchical tree-based, and diagnostic character differences). Due to questions regarding evolutionary distinctiveness of some taxa, we evaluated success under two taxonomic hypotheses. ? Key results: The psbA-trnH and trnT-trnL barcodes in conjunction with the "best close match" distance-based method best met the objectives of DNA barcoding. Success was also a function of the taxonomy used. ? Conclusions: In addition to accurately identifying query sequences, our results showed that DNA barcoding is useful for detecting taxonomic uncertainty; determining whether erroneous taxonomy or incomplete lineage sorting is the cause requires additional information provided by traditional taxonomic approaches. The magnitude of differentiation within and among the Agalinis species sampled suggests that our results inform how DNA barcoding will perform among closely related species in other genera.     

Metagenomic taxonomic classification using extreme learning machines

Next-generation sequencing technologies have allowed researchers to determine the collective genomes of microbial communities co-existing within diverse ecological environments. Varying species abundance, length and complexities within different communities, coupled with discovery of new species makes the problem of taxonomic assignment to short DNA sequence reads extremely challenging. We have developed a new sequence composition-based taxonomic classifier using extreme learning machines referred to as TAC-ELM for metagenomic analysis. TAC-ELM uses the framework of extreme learning machines to quickly and accurately learn the weights for a neural network model. The input features consist of GC content and oligonucleotides. TAC-ELM is evaluated on two metagenomic benchmarks with sequence read lengths reflecting the traditional and current sequencing technologies. Our empirical results indicate the strength of the developed approach, which outperforms state-of-the-art taxonomic classifiers in terms of accuracy and implementation complexity. We also perform experiments that evaluate the pervasive case within metagenome analysis, where a species may not have been previously sequenced or discovered and will not exist in the reference genome databases. TAC-ELM was also combined with BLAST to show improved classification results. Code and Supplementary Results: http://www.cs.gmu.edu/~mlbio/TAC-ELM (BSD License).     

Comprehensive discovery of CRISPR-targeted terminally redundant sequences in the human gut metagenome: Viruses,plasmids, and more

Viruses are the most numerous biological entity, existing in all environments and infecting all cellular organisms. Compared with cellular life, the evolution and origin of viruses are poorly understood; viruses are enormously diverse, and most lack sequence similarity to cellular genes. To uncover viral sequences without relying on either reference viral sequences from databases or marker genes that characterize specific viral taxa, we developed an analysis pipeline for virus inference based on clustered regularly interspaced short palindromic repeats (CRISPR). CRISPR is a prokaryotic nucleic acid restriction system that stores the memory of previous exposure. Our protocol can infer CRISPR-targeted sequences, including viruses, plasmids, and previously uncharacterized elements, and predict their hosts using unassembled short-read metagenomic sequencing data. By analyzing human gut metagenomic data, we extracted 11,391 terminally redundant CRISPR-targeted sequences, which are likely complete circular genomes. The sequences included 2,154 tailed-phage genomes, together with 257 complete crAssphage genomes, 11 genomes larger than 200 kilobases, 766 genomes of Microviridae species, 56 genomes of Inoviridae species, and 95 previously uncharacterized circular small genomes that have no reliably predicted protein-coding gene. We predicted the host(s) of approximately 70% of the discovered genomes at the taxonomic level of phylum by linking protospacers to taxonomically assigned CRISPR direct repeats. These results demonstrate that our protocol is efficient for de novo inference of CRISPR-targeted sequences and their host prediction.     

RiboFR-Seq: a novel approach to linking 16S rRNA amplicon profiles to metagenomes

16S rRNA amplicon analysis and shotgun metagenome sequencing are two main culture-independent strategies to explore the genetic landscape of various microbial communities. Recently, numerous studies have employed these two approaches together, but downstream data analyses were performed separately, which always generated incongruent or conflict signals on both taxonomic and functional classifications. Here we propose a novel approach, RiboFR-Seq (Ribosomal RNA gene flanking region sequencing), for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. Through extensive testing on clonal bacterial strain, salivary microbiome and bacterial epibionts of marine kelp, we demonstrated that RiboFR-Seq could detect the vast majority of bacteria not only in well-studied microbiomes but also in novel communities with limited reference genomes. Combined with classical amplicon sequencing and shotgun metagenome sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification. By recognizing almost all 16S rRNA copies, the RiboFR-seq approach can effectively reduce the taxonomic abundance bias resulted from 16S rRNA copy number variation. We believe that RiboFR-Seq, which provides an integrated view of 16S rRNA profiles and metagenomes, will help us better understand diverse microbial communities.     

Viral metagenomics analysis of planktonic viruses in East Lake, Wuhan, China

East Lake (Lake Donghu), located in Wuhan, China, is a typical city freshwater lake that has been experiencing eutrophic conditions and algal blooming during recent years. Marine and fresh water are considered to contain a large number of viruses. However, little is known about their genetic diversity because of the limited techniques for culturing viruses. In this study, we conducted a viral metagenomic analysis using a high-throughput sequencing technique with samples collected from East Lake in Spring, Summer, Autumn, and Winter. The libraries from four samples each generated 234,669, 71,837, 12,820, and 34,236 contigs (> 90 bp each), respectively. The genetic structure of the viral community revealed a high genetic diversity covering 23 viral families, with the majority of contigs homologous to DNA viruses, including members of Myoviridae, Podoviridae, Siphoviridae, Phycodnaviridae, and Microviridae, which infect bacteria or algae, and members of Circoviridae, which infect invertebrates and vertebrates. The highest viral genetic diversity occurred in samples collected in August, then December and June, and the least diversity in March. Most contigs have low-sequence identities with known viruses. PCR detection targeting the conserved sequences of genes (g20, psbA, psbD, and DNApol) of cyanophages further confirmed that there are novel cyanophages in the East Lake. Our viral metagenomic data provide the first preliminary understanding of the virome in one freshwater lake in China and would be helpful for novel virus discovery and the control of algal blooming in the future.     

Molecular detection and characterisation of black raspberry necrosis virus and raspberry bushy dwarf virus isolates in wild raspberries

Virus‐derived small interfering RNAs (siRNAs) were extracted from leaves of wild raspberries (Rubus idaeus) sampled from three different regions in Finland and subjected to deep sequencing. Assembly of the siRNA reads to contigs and their comparison to sequences in databases revealed the presence of the bipartite positive‐sense single‐stranded RNA viruses, raspberry bushy dwarf virus (RBDV, genus Idaeovirus), and black raspberry necrosis virus (BRNV, family Secoviridae) in 19 and 26 samples, respectively, including 15 plants coinfected with both viruses. Coverage with siRNA reads [21 and 22 nucleotides (nt)] was higher in BRNV‐FI (Finland) RNA1 (79%) than RNA2 (45%). In RBDV, the coverage of siRNA reads was 89% and 90% for RNA1 and RNA2, respectively. Average depth of coverage was 1.6–4.9 for BRNV and 16.5–36.5 for RBDV. PCR primers designed for RBDV and BRNV based on the contigs were used for screening wild raspberry and a few cultivated raspberry samples from different regions. Furthermore, the sequences of BRNV RNA1 and RNA2 were determined by amplification and sequencing of overlapping contigs (length 1000–1200 nt) except for the 3′ and 5′ ends of RNA1 and RNA2 covered by primers. RNA1 of the Finnish BRNV isolate (BRNV‐FI) was 80% and 86% identical to BRNV‐NA (USA) and BRNV‐Alyth (UK), respectively, whereas the identity of NA and Alyth was 79%. RNA2 of BRNV‐FI was 84% and 80% identical to BRNV‐NA and BRNV‐Alyth, respectively, whereas NA and Alyth were 82% identical. Hence, the strains detected in Finland differ from those reported in the UK and USA. Our results reveal the presence of BRNV in Finland for the first time. The virus is common in wild raspberries and nearly identical isolates are found in cultivated raspberries as well. The results show that wild raspberries in Finland are commonly infected with RBDV or BRNV or both viruses and thus are likely to serve as reservoirs of RBDV and BRNV for cultivated Rubus spp.     

Assembly of a Marine Viral Metagenome after Physical Fractionation

Metagenomic analyses of marine viruses generate an overview of viral genes present in a sample, but the percentage of the resulting sequence fragments that can be reassembled is low and the phenotype of the virus from which a given sequence derives is usually unknown. In this study, we employed physical fractionation to characterize the morphological and genomic traits of a subset of uncultivated viruses from a natural marine assemblage. Viruses from Kāne‘ohe Bay, Hawai‘i were fractionated by equilibrium buoyant density centrifugation in a cesium chloride (CsCl) gradient, and one fraction from the CsCl gradient was then further fractionated by strong anion-exchange chromatography. One of the fractions resulting from this two-dimensional separation appeared to be dominated by only a few virus types based on genome sizes and morphology. Sequences generated from a shotgun clone library of the viruses in this fraction were assembled into significantly more numerous contigs than have been generated with previous metagenomic investigations of whole DNA viral assemblages with comparable sequencing effort. Analysis of the longer contigs (up to 6.5 kb) assembled from our metagenome allowed us to assess gene arrangement in this subset of marine viruses. Our results demonstrate the potential for physical fractionation to facilitate sequence assembly from viral metagenomes and permit linking of morphological and genomic data for uncultivated viruses.     

Metagenomic and small-subunit rRNA analyses reveal the genetic diversity of bacteria, archaea, fungi, and viruses in soil

Recent studies have highlighted the surprising richness of soil bacterial communities; however, bacteria are not the only microorganisms found in soil. To our knowledge, no study has compared the diversities of the four major microbial taxa, i.e., bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit [OTU]), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. In this first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse.     

Metagenomic and Small-Subunit rRNA Analyses Reveal the Genetic Diversity of Bacteria, Archaea, Fungi, and Viruses in Soil

Recent studies have highlighted the surprising richness of soil bacterial communities; however, bacteria are not the only microorganisms found in soil. To our knowledge, no study has compared the diversities of the four major microbial taxa, i.e., bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit [OTU]), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. In this first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse.     

Metagenomic Survey for Viruses in Western Arctic Caribou,Alaska, through Iterative Assembly of Taxonomic Units

Pathogen surveillance in animals does not provide a sufficient level of vigilance because it is generally confined to surveillance of pathogens with known economic impact in domestic animals and practically nonexistent in wildlife species. As most (re-)emerging viral infections originate from animal sources, it is important to obtain insight into viral pathogens present in the wildlife reservoir from a public health perspective. When monitoring living, free-ranging wildlife for viruses, sample collection can be challenging and availability of nucleic acids isolated from samples is often limited. The development of viral metagenomics platforms allows a more comprehensive inventory of viruses present in wildlife. We report a metagenomic viral survey of the Western Arctic herd of barren ground caribou (Rangifer tarandus granti) in Alaska, USA. The presence of mammalian viruses in eye and nose swabs of 39 free-ranging caribou was investigated by random amplification combined with a metagenomic analysis approach that applied exhaustive iterative assembly of sequencing results to define taxonomic units of each metagenome. Through homology search methods we identified the presence of several mammalian viruses, including different papillomaviruses, a novel parvovirus, polyomavirus, and a virus that potentially represents a member of a novel genus in the family Coronaviridae.