Towards optimized viral metagenomes for double-stranded and single-stranded DNA viruses from challenging soils

Abstract

Soils impact global carbon cycling and their resident microbes are critical to their biogeochemical processing and ecosystem outputs. Based on studies in marine systems, viruses infecting soil microbes likely modulate host activities via mortality, horizontal gene transfer, and metabolic control. However, their roles remain largely unexplored due to technical challenges with separating, isolating, and extracting DNA from viruses in soils. Some of these challenges have been overcome by using whole genome amplification methods and while these have allowed insights into the identities of soil viruses and their genomes, their inherit biases have prevented meaningful ecological interpretations. Here we experimentally optimized steps for generating quantitatively-amplified viral metagenomes to better capture both ssDNA and dsDNA viruses across three distinct soil habitats along a permafrost thaw gradient. First, we assessed differing DNA extraction methods (PowerSoil, Wizard mini columns, and cetyl trimethylammonium bromide) for quantity and quality of viral DNA. This established PowerSoil as best for yield and quality of DNA from our samples, though ∼1/3 of the viral populations captured by each extraction kit were unique, suggesting appreciable differential biases among DNA extraction kits. Second, we evaluated the impact of purifying viral particles after resuspension (by cesium chloride gradients; CsCl) and of viral lysis method (heat vs bead-beating) on the resultant viromes. DNA yields after CsCl particle-purification were largely non-detectable, while unpurified samples yielded 1–2-fold more DNA after lysis by heat than by bead-beating. Virome quality was assessed by the number and size of metagenome-assembled viral contigs, which showed no increase after CsCl-purification, but did from heat lysis relative to bead-beating. We also evaluated sample preparation protocols for ssDNA virus recovery. In both CsCl-purified and non-purified samples, ssDNA viruses were successfully recovered by using the Accel-NGS 1S Plus Library Kit. While ssDNA viruses were identified in all three soil types, none were identified in the samples that used bead-beating, suggesting this lysis method may impact recovery. Further, 13 ssDNA vOTUs were identified compared to 582 dsDNA vOTUs, and the ssDNA vOTUs only accounted for ∼4% of the assembled reads, implying dsDNA viruses were dominant in these samples. This optimized approach was combined with the previously published viral resuspension protocol into a sample-to-virome protocol for soils now available at protocols.io, where community feedback creates ‘living’ protocols. This collective approach will be particularly valuable given the high physicochemical variability of soils, which will may require considerable soil type-specific optimization. This optimized protocol provides a starting place for developing quantitatively-amplified viromic datasets and will help enable viral ecogenomic studies on organic-rich soils.

Coming-of-Age Characterization of Soil Viruses: A User’s Guide to Virus Isolation, Detection within Metagenomes, and Viromics

“…Consequently, to desorb virions, various chemical reagents with different charges and physical methods are employed [5]. Virus desorption methods in particular should be tailored to specific soil types [35,[153][154][155]. We therefore first suggest characterizing a soil to understand its anion/cation-exchange capacity (a measure of how many ions can be retained on soil particle surfaces [156]) and, separately, the diversity of the associated microbial community (e.g., via 16S rRNA gene surveys).…”

“…Presumably this technique would not work to remove all niVLPs, because, as noted, a VLP could become non-infectious due to defects in genes or nucleic acid structure rather than due to pores in capsids (Section 4.1). Nevertheless, PMA treatment is still useful, as one environmental metagenomic study, in which samples were collected from a clean-room floor, found that removal of relic DNA allowed detection of microbes and viruses that were not otherwise detected due to their low prevalence relative to that of relic DNA [155]. Once PMA treatment is performed, or any method of eDNA removal, qPCR can be used with 16S or 18S rRNA gene primers [184] to check to see if microbial DNA is still present in a virome, either because microbial relic DNA was not removed during PMA treatment or microbial DNA remained within intact ultrasmall microbial cells (Section 4.3).…”

“…A library method also was recently developed that included novel adapter attachment chemistry, which permits quantitative amplification and sequencing of ssDNA, dsDNA, and damaged DNA in parallel [217]. To test its fidelity, this method was first applied to mock viral communities [214] and since has been shown to capture both ssDNA and dsDNA viruses in many environments including soil from picogram-level input DNA [155,218]. Library preparation kits and protocols able to generate quantitative metagenomes from nanogram DNA inputs are thus now readily available and should be primarily used, as opposed to non-quantitative amplification.…”

“…To aid in the detection of ssDNA viruses, many studies have utilized the fact that the majority of ssDNA viruses are circular and encode known marker genes, such as homologs of genes encoding the rolling-circle replication-associated protein [36,155,206,219]. To date, there has only been one study that quantitatively amplified both ssDNA and dsDNA viruses from the soil samples [155]. Using known ssDNA virus marker genes, it suggested that ssDNA viruses were a small fraction of the microbial viruses observed (~4%).…”

Benchmarking protocols for the metagenomic analysis of stream biofilm viromes

“…For identification and classification of viral contigs, we used MetaPhinder (v2.1, Jurtz et al, 2016) through the web interface hosted at the Center for Genomic Epidemiology at the Danish Technical University (DTU). Additionally, we queried the Viral_rep and Phage_F domains of the PFAM database using hmmsearch (HMMER v3, Eddy, 2011) to identify ssDNA contigs (Trubl et al, 2019).…”