Virus ecology and 7-year temporal dynamics across a permafrost thaw gradient.

Soil microorganisms are pivotal in the global carbon cycle, but the viruses that affect them and their impact on ecosystems are less understood. In this study, we explored the diversity, dynamics, and ecology of soil viruses through 379 metagenomes collected annually from 2010 to 2017. These samples spanned the seasonally thawed active layer of a permafrost thaw gradient, which included palsa, bog, and fen habitats. We identified 5051 virus operational taxonomic units (vOTUs), doubling the known viruses for this site. These vOTUs were largely ephemeral within habitats, suggesting a turnover at the vOTU level from year to year. While the diversity varied by thaw stage and depth-related patterns were specific to each habitat, the virus communities did not significantly change over time. The abundance ratios of virus to host at the phylum level did not show consistent trends across the thaw gradient, depth, or time. To assess potential ecosystem impacts, we predicted hosts in silico and found viruses linked to microbial lineages involved in the carbon cycle, such as methanotrophy and methanogenesis. This included the identification of viruses of Candidatus Methanoflorens, a significant global methane contributor. We also detected a variety of potential auxiliary metabolic genes, including 24 carbon-degrading glycoside hydrolases, six of which are uniquely terrestrial. In conclusion, these long-term observations enhance our understanding of soil viruses in the context of climate-relevant processes and provide opportunities to explore their role in terrestrial carbon cycling.

DRAM for distilling microbial metabolism to automate the curation of microbiome function.

Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

Healthy human gut phageome.

The role of bacteriophages in influencing the structure and function of the healthy human gut microbiome is unknown. With few exceptions, previous studies have found a high level of heterogeneity in bacteriophages from healthy individuals. To better estimate and identify the shared phageome of humans, we analyzed a deep DNA sequence dataset of active bacteriophages and available metagenomic datasets of the gut bacteriophage community from healthy individuals. We found 23 shared bacteriophages in more than one-half of 64 healthy individuals from around the world. These shared bacteriophages were found in a significantly smaller percentage of individuals with gastrointestinal/irritable bowel disease. A network analysis identified 44 bacteriophage groups of which 9 (20%) were shared in more than one-half of all 64 individuals. These results provide strong evidence of a healthy gut phageome (HGP) in humans. The bacteriophage community in the human gut is a mixture of three classes: a set of core bacteriophages shared among more than one-half of all people, a common set of bacteriophages found in 20-50% of individuals, and a set of bacteriophages that are either rarely shared or unique to a person. We propose that the core and common bacteriophage communities are globally distributed and comprise the HGP, which plays an important role in maintaining gut microbiome structure/function and thereby contributes significantly to human health.

Comparative Metagenomics of Eight Geographically Remote Terrestrial Hot Springs.

Hot springs are natural habitats for thermophilic Archaea and Bacteria. In this paper, we present the metagenomic analysis of eight globally distributed terrestrial hot springs from China, Iceland, Italy, Russia, and the USA with a temperature range between 61 and 92 (∘)C and pH between 1.8 and 7. A comparison of the biodiversity and community composition generally showed a decrease in biodiversity with increasing temperature and decreasing pH. Another important factor shaping microbial diversity of the studied sites was the abundance of organic substrates. Several species of the Crenarchaeal order Thermoprotei were detected, whereas no single bacterial species was found in all samples, suggesting a better adaptation of certain archaeal species to different thermophilic environments. Two hot springs show high abundance of Acidithiobacillus, supporting the idea of a true thermophilic Acidithiobacillus species that can thrive in hyperthermophilic environments. Depending on the sample, up to 58 % of sequencing reads could not be assigned to a known phylum, reinforcing the fact that a large number of microorganisms in nature, including those thriving in hot environments remain to be isolated and characterized.

Prokaryotic-virus-encoded auxiliary metabolic genes throughout the global oceans.

BACKGROUND: Prokaryotic microbes have impacted marine biogeochemical cycles for billions of years. Viruses also impact these cycles, through lysis, horizontal gene transfer, and encoding and expressing genes that contribute to metabolic reprogramming of prokaryotic cells. While this impact is difficult to quantify in nature, we hypothesized that it can be examined by surveying virus-encoded auxiliary metabolic genes (AMGs) and assessing their ecological context. RESULTS: We systematically developed a global ocean AMG catalog by integrating previously described and newly identified AMGs and then placed this catalog into ecological and metabolic contexts relevant to ocean biogeochemistry. From 7.6 terabases of Tara Oceans paired prokaryote- and virus-enriched metagenomic sequence data, we increased known ocean virus populations to 579,904 (up 16%). From these virus populations, we then conservatively identified 86,913 AMGs that grouped into 22,779 sequence-based gene clusters, 7248 (~ 32%) of which were not previously reported. Using our catalog and modeled data from mock communities, we estimate that ~ 19% of ocean virus populations carry at least one AMG. To understand AMGs in their metabolic context, we identified 340 metabolic pathways encoded by ocean microbes and showed that AMGs map to 128 of them. Furthermore, we identified metabolic "hot spots" targeted by virus AMGs, including nine pathways where most steps (≥ 0.75) were AMG-targeted (involved in carbohydrate, amino acid, fatty acid, and nucleotide metabolism), as well as other pathways where virus-encoded AMGs outnumbered cellular homologs (involved in lipid A phosphates, phosphatidylethanolamine, creatine biosynthesis, phosphoribosylamine-glycine ligase, and carbamoyl-phosphate synthase pathways). CONCLUSIONS: Together, this systematically curated, global ocean AMG catalog and analyses provide a valuable resource and foundational observations to understand the role of viruses in modulating global ocean metabolisms and their biogeochemical implications. Video Abstract.

Identification of novel positive-strand RNA viruses by metagenomic analysis of archaea-dominated Yellowstone hot springs.

There are no known RNA viruses that infect Archaea. Filling this gap in our knowledge of viruses will enhance our understanding of the relationships between RNA viruses from the three domains of cellular life and, in particular, could shed light on the origin of the enormous diversity of RNA viruses infecting eukaryotes. We describe here the identification of novel RNA viral genome segments from high-temperature acidic hot springs in Yellowstone National Park in the United States. These hot springs harbor low-complexity cellular communities dominated by several species of hyperthermophilic Archaea. A viral metagenomics approach was taken to assemble segments of these RNA virus genomes from viral populations isolated directly from hot spring samples. Analysis of these RNA metagenomes demonstrated unique gene content that is not generally related to known RNA viruses of Bacteria and Eukarya. However, genes for RNA-dependent RNA polymerase (RdRp), a hallmark of positive-strand RNA viruses, were identified in two contigs. One of these contigs is approximately 5,600 nucleotides in length and encodes a polyprotein that also contains a region homologous to the capsid protein of nodaviruses, tetraviruses, and birnaviruses. Phylogenetic analyses of the RdRps encoded in these contigs indicate that the putative archaeal viruses form a unique group that is distinct from the RdRps of RNA viruses of Eukarya and Bacteria. Collectively, our findings suggest the existence of novel positive-strand RNA viruses that probably replicate in hyperthermophilic archaeal hosts and are highly divergent from RNA viruses that infect eukaryotes and even more distant from known bacterial RNA viruses. These positive-strand RNA viruses might be direct ancestors of RNA viruses of eukaryotes.

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets.

Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations.

BACKGROUND: Microbes and their viruses are hidden engines driving Earth's ecosystems from the oceans and soils to humans and bioreactors. Though gene marker approaches can now be complemented by genome-resolved studies of inter-(macrodiversity) and intra-(microdiversity) population variation, analytical tools to do so remain scattered or under-developed. RESULTS: Here, we introduce MetaPop, an open-source bioinformatic pipeline that provides a single interface to analyze and visualize microbial and viral community metagenomes at both the macro- and microdiversity levels. Macrodiversity estimates include population abundances and α- and ß-diversity. Microdiversity calculations include identification of single nucleotide polymorphisms, novel codon-constrained linkage of SNPs, nucleotide diversity (π and θ), and selective pressures (pN/pS and Tajima's D) within and fixation indices (FST) between populations. MetaPop will also identify genes with distinct codon usage. Following rigorous validation, we applied MetaPop to the gut viromes of autistic children that underwent fecal microbiota transfers and their neurotypical peers. The macrodiversity results confirmed our prior findings for viral populations (microbial shotgun metagenomes were not available) that diversity did not significantly differ between autistic and neurotypical children. However, by also quantifying microdiversity, MetaPop revealed lower average viral nucleotide diversity (π) in autistic children. Analysis of the percentage of genomes detected under positive selection was also lower among autistic children, suggesting that higher viral π in neurotypical children may be beneficial because it allows populations to better "bet hedge" in changing environments. Further, comparisons of microdiversity pre- and post-FMT in autistic children revealed that the delivery FMT method (oral versus rectal) may influence viral activity and engraftment of microdiverse viral populations, with children who received their FMT rectally having higher microdiversity post-FMT. Overall, these results show that analyses at the macro level alone can miss important biological differences. CONCLUSIONS: These findings suggest that standardized population and genetic variation analyses will be invaluable for maximizing biological inference, and MetaPop provides a convenient tool package to explore the dual impact of macro- and microdiversity across microbial communities. Video abstract.

Diversity and ecological footprint of Global Ocean RNA viruses.

DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and "species"-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

Cryptic and abundant marine viruses at the evolutionary origins of Earth's RNA virome.

Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem players, RNA viruses are insufficiently studied outside disease settings. In this study, we analyzed ≈28 terabases of Global Ocean RNA sequences to expand Earth's RNA virus catalogs and their taxonomy, investigate their evolutionary origins, and assess their marine biogeography from pole to pole. Using new approaches to optimize discovery and classification, we identified RNA viruses that necessitate substantive revisions of taxonomy (doubling phyla and adding >50% new classes) and evolutionary understanding. "Species"-rank abundance determination revealed that viruses of the new phyla "Taraviricota," a missing link in early RNA virus evolution, and "Arctiviricota" are widespread and dominant in the oceans. These efforts provide foundational knowledge critical to integrating RNA viruses into ecological and epidemiological models.

Cenote-Taker 2 democratizes virus discovery and sequence annotation.

Viruses, despite their great abundance and significance in biological systems, remain largely mysterious. Indeed, the vast majority of the perhaps hundreds of millions of viral species on the planet remain undiscovered. Additionally, many viruses deposited in central databases like GenBank and RefSeq are littered with genes annotated as 'hypothetical protein' or the equivalent. Cenote-Taker 2, a virus discovery and annotation tool available on command line and with a graphical user interface with free high-performance computation access, utilizes highly sensitive models of hallmark virus genes to discover familiar or divergent viral sequences from user-input contigs. Additionally, Cenote-Taker 2 uses a flexible set of modules to automatically annotate the sequence features of contigs, providing more gene information than comparable tools. The outputs include readable and interactive genome maps, virome summary tables, and files that can be directly submitted to GenBank. We expect Cenote-Taker 2 to facilitate virus discovery, annotation, and expansion of the known virome.

iVirus 2.0: Cyberinfrastructure-supported tools and data to power DNA virus ecology.

Microbes drive myriad ecosystem processes, but under strong influence from viruses. Because studying viruses in complex systems requires different tools than those for microbes, they remain underexplored. To combat this, we previously aggregated double-stranded DNA (dsDNA) virus analysis capabilities and resources into 'iVirus' on the CyVerse collaborative cyberinfrastructure. Here we substantially expand iVirus's functionality and accessibility, to iVirus 2.0, as follows. First, core iVirus apps were integrated into the Department of Energy's Systems Biology KnowledgeBase (KBase) to provide an additional analytical platform. Second, at CyVerse, 20 software tools (apps) were upgraded or added as new tools and capabilities. Third, nearly 20-fold more sequence reads were aggregated to capture new data and environments. Finally, documentation, as "live" protocols, was updated to maximize user interaction with and contribution to infrastructure development. Together, iVirus 2.0 serves as a uniquely central and accessible analytical platform for studying how viruses, particularly dsDNA viruses, impact diverse microbial ecosystems.

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation.

BACKGROUND: Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). RESULTS: The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. CONCLUSION: Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses 'hidden' in diverse sequence datasets.

Potential virus-mediated nitrogen cycling in oxygen-depleted oceanic waters.

Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ viruses might impact nitrogen (N) cycling via AMGs. Identified viral genomes encoded six N-cycle AMGs associated with denitrification, nitrification, assimilatory nitrate reduction, and nitrite transport. The majority of these AMGs (80%) were identified in T4-like Myoviridae phages, predicted to infect Cyanobacteria and Proteobacteria, or in unclassified archaeal viruses predicted to infect Thaumarchaeota. Four AMGs were exclusive to anoxic waters and had distributions that paralleled homologous microbial genes. Together, these findings suggest viruses modulate N-cycling processes within the ETSP OMZ and may contribute to nitrogen loss throughout the global oceans thus providing a baseline for their inclusion in the ecosystem and geochemical models.

The Gut Virome Database Reveals Age-Dependent Patterns of Virome Diversity in the Human Gut.

The gut microbiome profoundly affects human health and disease, and their infecting viruses are likely as important, but often missed because of reference database limitations. Here, we (1) built a human Gut Virome Database (GVD) from 2,697 viral particle or microbial metagenomes from 1,986 individuals representing 16 countries, (2) assess its effectiveness, and (3) report a meta-analysis that reveals age-dependent patterns across healthy Westerners. The GVD contains 33,242 unique viral populations (approximately species-level taxa) and improves average viral detection rates over viral RefSeq and IMG/VR nearly 182-fold and 2.6-fold, respectively. GVD meta-analyses show highly personalized viromes, reveal that inter-study variability from technical artifacts is larger than any "disease" effect at the population level, and document how viral diversity changes from human infancy into senescence. Together, this compact foundational resource, these standardization guidelines, and these meta-analysis findings provide a systematic toolkit to help maximize our understanding of viral roles in health and disease.

Biotic and Environmental Drivers of Plant Microbiomes Across a Permafrost Thaw Gradient.

Plant-associated microbiomes are structured by environmental conditions and plant associates, both of which are being altered by climate change. The future structure of plant microbiomes will depend on the, largely unknown, relative importance of each. This uncertainty is particularly relevant for arctic peatlands, which are undergoing large shifts in plant communities and soil microbiomes as permafrost thaws, and are potentially appreciable sources of climate change feedbacks due to their soil carbon (C) storage. We characterized phyllosphere and rhizosphere microbiomes of six plant species, and bulk peat, across a permafrost thaw progression (from intact permafrost, to partially- and fully-thawed stages) via 16S rRNA gene amplicon sequencing. We tested the hypothesis that the relative influence of biotic versus environmental filtering (the role of plant species versus thaw-defined habitat) in structuring microbial communities would differ among phyllosphere, rhizosphere, and bulk peat. Using both abundance- and phylogenetic-based approaches, we found that phyllosphere microbial composition was more strongly explained by plant associate, with little influence of habitat, whereas in the rhizosphere, plant and habitat had similar influence. Network-based community analyses showed that keystone taxa exhibited similar patterns with stronger responses to drivers. However, plant associates appeared to have a larger influence on organisms belonging to families associated with methane-cycling than the bulk community. Putative methanogens were more strongly influenced by plant than habitat in the rhizosphere, and in the phyllosphere putative methanotrophs were more strongly influenced by plant than was the community at large. We conclude that biotic effects can be stronger than environmental filtering, but their relative importance varies among microbial groups. For most microbes in this system, biotic filtering was stronger aboveground than belowground. However, for putative methane-cyclers, plant associations have a stronger influence on community composition than environment despite major hydrological changes with thaw. This suggests that plant successional dynamics may be as important as hydrological changes in determining microbial relevance to C-cycling climate feedbacks. By partitioning the degree that plant versus environmental filtering drives microbiome composition and function we can improve our ability to predict the consequences of warming for C-cycling in other arctic areas undergoing similar permafrost thaw transitions.

Viral Ecogenomics of Arctic Cryopeg Brine and Sea Ice.

Arctic regions, which are changing rapidly as they warm 2 to 3 times faster than the global average, still retain microbial habitats that serve as natural laboratories for understanding mechanisms of microbial adaptation to extreme conditions. Seawater-derived brines within both sea ice (sea-ice brine) and ancient layers of permafrost (cryopeg brine) support diverse microbes adapted to subzero temperatures and high salinities, yet little is known about viruses in these extreme environments, which, if analogous to other systems, could play important evolutionary and ecosystem roles. Here, we characterized viral communities and their functions in samples of cryopeg brine, sea-ice brine, and melted sea ice. Viral abundance was high in cryopeg brine (1.2 × 108 ml-1) and much lower in sea-ice brine (1.3 × 105 to 2.1 × 105 ml-1), which roughly paralleled the differences in cell concentrations in these samples. Five low-input, quantitative viral metagenomes were sequenced to yield 476 viral populations (i.e., species level; ≥10 kb), only 12% of which could be assigned taxonomy by traditional database approaches, indicating a high degree of novelty. Additional analyses revealed that these viruses: (i) formed communities that differed between sample type and vertically with sea-ice depth; (ii) infected hosts that dominated these extreme ecosystems, including Marinobacter, Glaciecola, and Colwellia; and (iii) encoded fatty acid desaturase (FAD) genes that likely helped their hosts overcome cold and salt stress during infection, as well as mediated horizontal gene transfer of FAD genes between microbes. Together, these findings contribute to understanding viral abundances and communities and how viruses impact their microbial hosts in subzero brines and sea ice.IMPORTANCE This study explores viral community structure and function in remote and extreme Arctic environments, including subzero brines within marine layers of permafrost and sea ice, using a modern viral ecogenomics toolkit for the first time. In addition to providing foundational data sets for these climate-threatened habitats, we found evidence that the viruses had habitat specificity, infected dominant microbial hosts, encoded host-derived metabolic genes, and mediated horizontal gene transfer among hosts. These results advance our understanding of the virosphere and how viruses influence extreme ecosystems. More broadly, the evidence that virally mediated gene transfers may be limited by host range in these extreme habitats contributes to a mechanistic understanding of genetic exchange among microbes under stressful conditions in other systems.

Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks.

Microbiomes from every environment contain a myriad of uncultivated archaeal and bacterial viruses, but studying these viruses is hampered by the lack of a universal, scalable taxonomic framework. We present vConTACT v.2.0, a network-based application utilizing whole genome gene-sharing profiles for virus taxonomy that integrates distance-based hierarchical clustering and confidence scores for all taxonomic predictions. We report near-identical (96%) replication of existing genus-level viral taxonomy assignments from the International Committee on Taxonomy of Viruses for National Center for Biotechnology Information virus RefSeq. Application of vConTACT v.2.0 to 1,364 previously unclassified viruses deposited in virus RefSeq as reference genomes produced automatic, high-confidence genus assignments for 820 of the 1,364. We applied vConTACT v.2.0 to analyze 15,280 Global Ocean Virome genome fragments and were able to provide taxonomic assignments for 31% of these data, which shows that our algorithm is scalable to very large metagenomic datasets. Our taxonomy tool can be automated and applied to metagenomes from any environment for virus classification.

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

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.