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Bacteria and their viruses (phage) are fundamental drivers of many ecosystem processes including global biogeochemistry and horizontal gene transfer. While databases and resources for studying function in uncultured bacterial communities are relatively advanced, many fewer exist for their viral counterparts. The issue is largely technical in that the majority (often 90%) of viral sequences are functionally 'unknown' making viruses a virtually untapped resource of functional and physiological information. Here, we provide a community resource that organizes this unknown sequence space into 27 K high confidence protein clusters using 32 viral metagenomes from four biogeographic regions in the Pacific Ocean that vary by season, depth, and proximity to land, and include some of the first deep pelagic ocean viral metagenomes. These protein clusters more than double currently available viral protein clusters, including those from environmental datasets. Further, a protein cluster guided analysis of functional diversity revealed that richness decreased (i) from deep to surface waters, (ii) from winter to summer, (iii) and with distance from shore in surface waters only. These data provide a framework from which to draw on for future metadata-enabled functional inquiries of the vast viral unknown.

Key Points A newly available quantitative metagenomic pipeline for double-stranded DNA (dsDNA) viruses has facilitated the generation of large-scale, systematic data sets with which to explore marine viral ecology at the gene, population and community levels. The use of protein clusters and shared k-mer-based analyses, including social networks, enables examination of gene diversity and viral ecology, despite the dominance of 'unknown' sequences in marine viromes. Viral auxiliary metabolic genes (AMGs) encompass a wide range of metabolic functions, indicating that viruses can substantially augment marine ecosystem function by altering the metabolism of their hosts. These AMGs are also major contributors to niche differentiation in marine viral communities. Viruses that infect dominant and widespread marine microorganisms have been identified using cultivation-dependent and cultivation-independent techniques, which is expanding our understanding of marine viral diversity. Several cultivation-independent techniques are now available to link viruses to their hosts in complex environments, which is facilitating the exploration of virus–host interactions in nature. Notably, viral tagging suggests that wild marine cyanophages comprise discrete populations, facilitating the application of population-based viral ecology for which decades of existing ecological and evolutionary theory can be leveraged. Phage–bacteria infection networks and quantitative host range analyses help to advance the field towards a more predictive understanding of 'who infects whom?' The main challenges and areas for future research in marine virology are outlined. Marine viruses have important roles in modulating the dynamics of microbial life in the global oceans. Brum and Sullivan discuss the recent technological advances that are facilitating an accelerated pace of discovery in marine virology, including metagenomics and several cultivation-dependent and cultivation-independent tools. Marine viruses have important roles in microbial mortality, gene transfer, metabolic reprogramming and biogeochemical cycling. In this Review, we discuss recent technological advances in marine virology including the use of near-quantitative, reproducible metagenomics for large-scale investigation of viral communities and the emergence of gene-based viral ecology. We also describe the reprogramming of microbially driven processes by viral metabolic genes, the identification of novel viruses using cultivation-dependent and cultivation-independent tools, and the potential for modelling studies to provide a framework for studying virus–host interactions. These transformative advances have set a rapid pace in exploring and predicting how marine viruses manipulate and respond to their environment.

Viruses that infect bacteria (phages) can influence bacterial community dynamics, bacterial genome evolution and ecosystem biogeochemistry. These influences differ depending on whether phages establish lytic, chronic or lysogenic infections. Although the first two produce virion progeny, with lytic infections resulting in cell destruction, phages undergoing lysogenic infections replicate with cells without producing virions. The impacts of lysogeny are numerous and well-studied at the cellular level, but ecosystem-level consequences remain underexplored compared to those of lytic infections. Here, we review lysogeny from molecular mechanisms to ecological patterns to emerging approaches of investigation. Our goal is to highlight both its diversity and importance in complex communities. Altogether, using a combined viral ecology toolkit that is applied across broad model systems and environments will help us understand more of the diverse lifestyles and ecological impacts of lysogens in nature.

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.Classification of archaeal and bacterial viruses can be automated with an algorithm that identifies relationships on the basis of shared gene content.

The diverse rumen virome can modulate the rumen microbiome, but it remains largely unexplored. Here, we mine 975 published rumen metagenomes for viral sequences, create a global rumen virome database (RVD), and analyze the rumen virome for diversity, virus-host linkages, and potential roles in affecting rumen functions. Containing 397,180 species-level viral operational taxonomic units (vOTUs), RVD substantially increases the detection rate of rumen viruses from metagenomes compared with IMG/VR V3. Most of the classified vOTUs belong to Caudovirales , differing from those found in the human gut. The rumen virome is predicted to infect the core rumen microbiome, including fiber degraders and methanogens, carries diverse auxiliary metabolic genes, and thus likely impacts the rumen ecosystem in both a top-down and a bottom-up manner. RVD and the findings provide useful resources and a baseline framework for future research to investigate how viruses may impact the rumen ecosystem and digestive physiology. Here, by mining 975 published rumen metagenomes for viral sequences, the authors construct a global rumen virome database (RVD), providing a resource for characterization of viral diversity, virus-host linkages, and potential roles in affecting rumen functions.

Viruses of microbes impact all ecosystems where microbes drive key energy and substrate transformations including the oceans, humans and industrial fermenters. However, despite this recognized importance, our understanding of viral diversity and impacts remains limited by too few model systems and reference genomes. One way to fill these gaps in our knowledge of viral diversity is through the detection of viral signal in microbial genomic data. While multiple approaches have been developed and applied for the detection of prophages (viral genomes integrated in a microbial genome), new types of microbial genomic data are emerging that are more fragmented and larger scale, such as Single-cell Amplified Genomes (SAGs) of uncultivated organisms or genomic fragments assembled from metagenomic sequencing. Here, we present VirSorter, a tool designed to detect viral signal in these different types of microbial sequence data in both a reference-dependent and reference-independent manner, leveraging probabilistic models and extensive virome data to maximize detection of novel viruses. Performance testing shows that VirSorter's prophage prediction capability compares to that of available prophage predictors for complete genomes, but is superior in predicting viral sequences outside of a host genome (i.e., from extrachromosomal prophages, lytic infections, or partially assembled prophages). Furthermore, VirSorter outperforms existing tools for fragmented genomic and metagenomic datasets, and can identify viral signal in assembled sequence (contigs) as short as 3kb, while providing near-perfect identification (>95% Recall and 100% Precision) on contigs of at least 10kb. Because VirSorter scales to large datasets, it can also be used in \"reverse\" to more confidently identify viral sequence in viral metagenomes by sorting away cellular DNA whether derived from gene transfer agents, generalized transduction or contamination. Finally, VirSorter is made available through the iPlant Cyberinfrastructure that provides a web-based user interface interconnected with the required computing resources. VirSorter thus complements existing prophage prediction softwares to better leverage fragmented, SAG and metagenomic datasets in a way that will scale to modern sequencing. Given these features, VirSorter should enable the discovery of new viruses in microbial datasets, and further our understanding of uncultivated viral communities across diverse ecosystems.

The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes. Viruses are infectious particles that can only multiply inside the cells of microbes and other organisms. Little is known about the genetic differences between virus particles (so-called ‘genetic diversity’), especially compared to what we know about the diversity of bacteria, archaea, and other single-celled microbes. This lack of knowledge hampers our understanding of the role viruses play in the evolution of microbial communities and their associated ecosystems. Studying the genetics of the viruses in these communities is challenging. There is no single ‘marker’ gene that can be used to identify all viruses in environmental samples. Also, many of the fragments of viral genomes that have been identified have not yet been linked to their host microbes. Many viruses integrate their genome into the DNA of their host cell, and there are computational tools available that exploit this ability to identify viruses and link them to their host. However, other viruses can live and multiply inside cells without integrating their genome into the host's DNA. Earlier in 2015, researchers developed a new computational tool called VirSorter that can predict virus genome sequences within the DNA extracted from microbes. VirSorter identifies viral genome sequences based on the presence of ‘hallmark’ genes that encode for components found in many virus particles, together with a reference database of genomes from many viruses. Now, Roux et al.—including some of the researchers from the earlier work—use VirSorter to predict viral DNA from publicly available bacteria and archaea genome data. The study identifies over 12,000 viral genomes and links them to their microbial hosts. These data increase the number of viral genome sequences that are publically available by a factor of ten and identify the first viruses associated with 13 new types of bacteria, which include species that are abundant in particular environments. It is possible for several different viruses to infect a single cell at the same time. Some viruses are known to be able to exchange DNA, and if this happens frequently in other viruses, it could have a big impact on how viruses evolve. Roux et al.'s findings suggest that although it is common for several different viruses to infect the same cell, it is relatively rare for these viruses to exchange genetic material. Roux et al.'s findings demonstrate the value of searching publicly available microbial genome data for fragments of viral genomes. These new viral genomes will serve as a useful resource for researchers as they explore the communities of viruses and microbes in natural environments, the human body and in industrial processes.

Viruses that infect microbial hosts have traditionally been studied in laboratory settings with a focus on either obligate lysis or persistent lysogeny. In the environment, these infection archetypes are part of a continuum that spans antagonistic to beneficial modes. In this Review, we advance a framework to accommodate the context-dependent nature of virus–microorganism interactions in ecological communities by synthesizing knowledge from decades of virology research, eco-evolutionary theory and recent technological advances. We discuss that nuanced outcomes, rather than the extremes of the continuum, are particularly likely in natural communities given variability in abiotic factors, the availability of suboptimal hosts and the relevance of multitrophic partnerships. We revisit the ‘rules of life’ in terms of how long-term infections shape the fate of viruses and microbial cells, populations and ecosystems.In this Review, Correa and colleagues revisit the rules of life for viruses of microorganisms by advancing a conceptual framework that recognizes virus–host interactions across a continuum of infection modalities and by examining the influence of these modalities on viruses, their hosts and ecosystems.

Background Viruses are a significant player in many biosphere and human ecosystems, but most signals remain “hidden” in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced identification tools. Results Here, we introduce VirSorter2, a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection. When benchmarked against genomes from both isolated and uncultivated viruses, VirSorter2 uniquely performed consistently with high accuracy (F1-score > 0.8) across viral diversity, while all other tools under-detected viruses outside of the group most represented in reference databases (i.e., those in the order Caudovirales ). Among the tools evaluated, VirSorter2 was also uniquely able to minimize errors associated with atypical cellular sequences including eukaryotic genomes and plasmids. Finally, as the virosphere exploration unravels novel viral sequences, VirSorter2’s modular design makes it inherently able to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity. Conclusion With multi-classifier and modular design, VirSorter2 demonstrates higher overall accuracy across major viral groups and will advance our knowledge of virus evolution, diversity, and virus-microbe interaction in various ecosystems. Source code of VirSorter2 is freely available ( https://bitbucket.org/MAVERICLab/virsorter2 ), and VirSorter2 is also available both on bioconda and as an iVirus app on CyVerse ( https://de.cyverse.org/de ). 1yUdaVB8pb7ryNSffJakk6 Video abstract

Microbial sulfur metabolism contributes to biogeochemical cycling on global scales. Sulfur metabolizing microbes are infected by phages that can encode auxiliary metabolic genes (AMGs) to alter sulfur metabolism within host cells but remain poorly characterized. Here we identified 191 phages derived from twelve environments that encoded 227 AMGs for oxidation of sulfur and thiosulfate ( dsrA , dsrC/tusE , soxC , soxD and soxYZ ). Evidence for retention of AMGs during niche-differentiation of diverse phage populations provided evidence that auxiliary metabolism imparts measurable fitness benefits to phages with ramifications for ecosystem biogeochemistry. Gene abundance and expression profiles of AMGs suggested significant contributions by phages to sulfur and thiosulfate oxidation in freshwater lakes and oceans, and a sensitive response to changing sulfur concentrations in hydrothermal environments. Overall, our study provides fundamental insights on the distribution, diversity, and ecology of phage auxiliary metabolism associated with sulfur and reinforces the necessity of incorporating viral contributions into biogeochemical configurations. Some bacteriophage encode auxiliary metabolic genes (AMGs) that impact host metabolism and biogeochemical cycling during infection. Here the authors identify hundreds of AMGs in environmental phage encoding sulfur oxidation genes and use their global distribution to infer phage-mediated biogeochemical impacts.