Abstract

Microbial communities play an important role in organismal and ecosystem health. While high‐throughput metabarcoding has revolutionized the study of bacterial communities, generating comparable viral communities has proven elusive, particularly in wildlife samples where the diversity of viruses and limited quantities of viral nucleic acid present distinctive challenges. Metagenomic sequencing is a promising solution for studying viral communities, but the lack of standardized methods currently precludes comparisons across host taxa or localities. Here, we developed an untargeted shotgun metagenomic sequencing protocol to generate comparable viral communities from noninvasively collected faecal and oropharyngeal swabs. Using samples from common vampire bats (Desmodus rotundus), a key species for virus transmission to humans and domestic animals, we tested how different storage media, nucleic acid extraction procedures and enrichment steps affect viral community detection. Based on finding viral contamination in foetal bovine serum, we recommend storing swabs in RNAlater or another nonbiological medium. We recommend extracting nucleic acid directly from swabs rather than from supernatant or pelleted material, which had undetectable levels of viral RNA. Results from a low‐input RNA library preparation protocol suggest that ribosomal RNA depletion and light DNase treatment reduce host and bacterial nucleic acid, and improve virus detection. Finally, applying our approach to twelve pooled samples from seven localities in Peru, we showed that detected viral communities saturated at the attained sequencing depth, allowing unbiased comparisons of viral community composition. Future studies using the methods outlined here will elucidate the determinants of viral communities across host species, environments and time.

Highlights

  • While viruses are often extracted from an aliquot of supernatant (Baker et al, 2013; Tse et al, 2012; Wu et al, 2012), extraction from the swab itself may be desirable for samples stored in RNAlater (Vo & Jedlicka, 2014). These extraction procedures need to be tested and optimized for more widespread use in noninvasive viral metagenomics. Another challenge for viral metagenomics is that since genomes are sequenced at random, larger host and bacterial genomes are preferentially detected relative to smaller viral genomes (Nakamura et al, 2009; Yang et al, 2011)

  • We created a bioinformatic pipeline for virus discovery and viral community analyses in shotgun metagenomic data from vampire bat samples (Supporting Information Appendix S2: Figure S1)

  • The majority of viral reads were assigned to the family Flaviviridae, with 41% and 30% of viral reads for the two foetal bovine serum (FBS) batches, respectively, assigned to bovine viral diarrhoea virus 3 (BVDV‐3)

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Summary

| INTRODUCTION

Microbial communities of bacteria and viruses play important roles in ecosystem function (Strickland, Lauber, Fierer, & Bradford, 2009; Strom, 2008; Suttle, 2007; van der Heijden, Bardgett, & Straalen, 2008) and in maintaining the health of organisms (Ley, Turnbaugh, Klein, & Gordon, 2006; Manrique et al, 2016; Muegge et al, 2011). While viruses are often extracted from an aliquot of supernatant (Baker et al, 2013; Tse et al, 2012; Wu et al, 2012), extraction from the swab itself may be desirable for samples stored in RNAlater (Vo & Jedlicka, 2014) These extraction procedures need to be tested and optimized for more widespread use in noninvasive viral metagenomics. Another challenge for viral metagenomics is that since genomes are sequenced at random, larger host and bacterial genomes are preferentially detected relative to smaller viral genomes (Nakamura et al, 2009; Yang et al, 2011) For this reason, samples are often enriched for viruses using methods including nuclease treatment, filtration of host/bacterial particles, density gradient centrifugation and removal of rRNA (Hall et al, 2014; Kleiner, Hooper, & Duerkop, 2015; Kohl et al, 2015).

| MATERIALS AND METHODS
| RESULTS
Enriched Non-enriched
| DISCUSSION
Findings
DATA ACCESSIBILITY
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