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Modern benchtop DNA synthesis techniques and increased concern of emerging pathogens have elevated the importance of screening oligonucleotides for pathogens of concern. However, accurate and sensitive characterization of oligonucleotides is an open challenge for many of the current techniques and ontology-based tools. To address this gap, we have developed a novel software tool, SeqScreen, that can accurately and sensitively characterize short DNA sequences using a set of curated Functions of Sequences of Concern (FunSoCs), novel functional labels specific to microbial pathogenesis which describe the pathogenic potential of individual proteins. We show that our ensemble machine learning model after training on these curations can label sequences with FunSoCs via an imbalanced multi-class and multi-label classification task with high accuracy. In summary, SeqScreen represents a first step towards a novel paradigm of functionally informed pathogen characterization from genomic and metagenomic datasets. SeqScreen is open-source and freely available for download at: https://www.gitlab.com/treangenlab/seqscreen

BackgroundIncreasingly, researchers use protein-coding genes from targeted PCR amplification or direct metagenomic sequencing in community and population ecology. Analysis of protein-coding genes presents different challenges from those encountered in traditional SSU rRNA studies. Most protein-coding sequences are annotated based on homology to other computationally-annotated sequences, which can lead to inaccurate annotations. Therefore, the results of sensitive homology searches must be validated to remove false-positives and assess functionality. Multiple lines of in silico evidence can be gathered by examining conserved domains and residues identified through biochemical investigations. However, manually validating sequences in this way can be time consuming and error prone, especially in large environmental studies.ResultsAn automated pipeline for protein active site validation (PASV) was developed to improve validation and partitioning accuracy for protein-coding sequences, combining multiple sequence alignment with expert domain knowledge. PASV was tested using commonly misannotated proteins: ribonucleotide reductase (RNR), alternative oxidase (AOX), and plastid terminal oxidase (PTOX). PASV partitioned 9,906 putative Class I alpha and Class II RNR sequences from bycatch in a global viral metagenomic investigation with >99% true positive and true negative rates. PASV predicted the class of 2,579 RNR sequences in >98% agreement with manual annotations. PASV correctly partitioned all 336 tested AOX and PTOX sequences.ConclusionsPASV provides an automated and accurate way to address post-homology search validation and partitioning of protein-coding marker genes. Source code is released under the MIT license and is found with documentation and usage examples on GitHub at https://github.com/mooreryan/pasv.

The increasing use of reclaimed water for irrigation in areas lacking access to advanced wastewater treatment and reclaimed water distribution systems calls for an examination of irrigation-site-based treatment technologies that can improve the quality of this alternative water source. To address this need, we investigated the impact of zero-valent iron (ZVI)-sand filtration on the bacterial community structure and functional potential of conventionally treated reclaimed water utilized in downstream applications. Over a 2-month period, reclaimed water was collected from a tertiary wastewater treatment plant in the Mid-Atlantic, U.S. and trucked to our greenhouse facility. The water was stored in rain barrels and then filtered through one ZVI-sand filter every 5 days. Filtrate was then subjected to enumeration, phylotyping, shiga toxin screening, and antimicrobial susceptibility testing of Escherichia coli. Aliquots of filtrate were also DNA extracted, and purified DNA was subjected to 16S rRNA gene sequencing and metagenomic shotgun sequencing. The genera Dechloromonas, Desulfotomaculum, Leptonema, and Thermomonas, which contain denitrifying and sulfate reducing species, commonly used in bioremediation, and known to increase the inherent reactivity of ZVI, were significantly more relatively abundant in ZVI-sand filtered reclaimed water compared to reclaimed water. The concentration of E. coli in ZVI-sand filtered reclaimed water was significantly lower compared to that of reclaimed water, and cefoxitin- and tetracycline-resistant E. coli were undetectable after ZVI-sand filtration. ZVI-sand filtration reduced the occurrence of human as well as plant pathogenic genera (Aeromonas, Mycobacterium, Shewanella, Acidovorax, Agrobacterium, and Clavibacter) but increased the proportion of Azospira, a nitrogen fixing bacterial genera, in the microbial community. Our exploratory functional analysis showed a modest non-significant increase in the proportion of open reading frames for genes associated with iron uptake, oxidative stress, as well as defense and repair mechanisms after ZVI-sand filtration. These data indicate an iron rich environment in the filter causing an oxidative stress response by the bacterial community present in the reclaimed water. Our findings demonstrate that ZVI-sand filtration effectively filters conventionally treated reclaimed water. Longer-term, field-based studies are needed to evaluate the effectiveness of the filter in agricultural settings and inform the development of future agricultural water reuse regulations.

Salmonellosis is a leading cause of foodborne illness worldwide. Salmonella infections have most often been associated with food-related risk factors, including the consumption of eggs and poultry. Recently, socioeconomic, agricultural and environmental factors, including drinking water source, have also been shown to influence the risk of salmonellosis. However, there are few data evaluating the association between consuming private well water and risk of Salmonella infections. Here, we examined the association between the prevalence of private drinking water wells and the incidence of salmonellosis in Maryland. Culture-confirmed salmonellosis case data (2007–2016) were obtained from the Foodborne Diseases Active Surveillance Network. Cases were linked by zip code with data from the Maryland well permits registry, the 2010 U.S. Census, the 2016 American Community Survey, and the USDA Agricultural Census. Well prevalence and salmonellosis incidence rates were calculated by zip code, and associations were evaluated using negative binomial regression models. From 2007 to 2016, a total of 8850 salmonellosis cases were reported in Maryland. Annual incidence rates ranged from 12.98 to 17.25 per 100,000 people. Prevalence of private wells in a zip code was statistically significantly associated with salmonellosis incidence at a statewide level (Incidence Rate Ratio [IRR] = 1.62; 95% Confidence Interval [CI] = 1.35, 1.93) and in the coastal zone of Maryland (IRR = 1.61; 95% CI = 1.31, 1.99). The presence of broiler chicken operations and the percentage of people living below the poverty level were also significantly associated with salmonellosis incidence at the zip code level in the coastal zone. To our knowledge, these are the first U.S. data to characterize the relationship between private drinking water wells and the risk of salmonellosis using an ecological study design. Our findings provide support for Salmonella testing of private wells in Maryland, as well as strengthening private well water regulations and improving the education of homeowners on well maintenance.

Chaperonins are protein-folding machinery found in all cellular life. Chaperonin genes have been documented within a few viruses, yet, surprisingly, analysis of metagenome sequence data indicated that chaperonin-carrying viruses are common and geographically widespread in marine ecosystems. Also unexpected was the discovery of viral chaperonin sequences related to thermosome proteins of archaea, indicating the presence of virioplankton populations infecting marine archaeal hosts. Virioplankton large subunit chaperonin sequences (GroELs) were divergent from bacterial sequences, indicating that viruses have carried this gene over long evolutionary time. Analysis of viral metagenome contigs indicated that: the order of large and small subunit genes was linked to the phylogeny of GroEL; both lytic and temperate phages may carry group I chaperonin genes; and viruses carrying a GroEL gene likely have large double-stranded DNA (dsDNA) genomes (>70 kb). Given these connections, it is likely that chaperonins are critical to the biology and ecology of virioplankton populations that carry these genes. Moreover, these discoveries raise the intriguing possibility that viral chaperonins may more broadly alter the structure and function of viral and cellular proteins in infected host cells.

Rapid advancements in synthetic biology and nucleic acid synthesis, in particular concerns about its intentional or accidental misuse, call for more sophisticated screening tools to identify genes of interest within short sequence fragments. One major gap in predicting genes of concern is the inadequacy of current tools and ontologies to describe the specific biological processes of pathogenic proteins. The objective of this work is to design software that sensitively assigns taxonomic classifications, functional annotations, and biological processes of interest to short nucleotide sequences of unknown origin (50bp-1,000bp). The overarching goal is to perform sensitive characterization of short sequences and highlight specific pathogenic biological processes of interest (BPoIs). The SeqScreen software executes these tasks in analytical workflows with Nextflow and outputs results in a tab-delimited report. Local and global alignments differentiate hits to taxonomically-related sequences from similar but unrelated sequences, and an ensemble approach leverages multiple tools and databases to assign a variety of functional terms to each query sequence. Final biological process assessments are made from the predicted functional annotations, which leverage information in pre-existing databases, as well as new custom biocurations. Machine learning models predict each biological process of interest on large protein databases before incorporation into the SeqScreen framework to streamline computational efficiency, ensure reproducible results, allow for version control, and facilitate the review of the automated predictions by expert biocurators. The SeqScreen source code is available at https://gitlab.com/treangenlab/seqscreen.

Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses., Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses. We summarize the ideas generated by participants of the Mid-Atlantic Microbiome Meet-up in January 2019. While it was clear from the presentations that most fields have advanced beyond simple associative and descriptive analyses, most fields lack essential elements needed for the development and application of accurate microbiome predictions. Participants stressed the need for standardization, reproducibility, and accessibility of quantitative tools as key to advancing predictions in microbiome analysis. We highlight hurdles that participants identified and propose directions for future efforts that will advance the use of prediction in microbiome research.

Campylobacter is a leading cause of bacterial foodborne illness in the United States. Campylobacter infections have most often been associated with food-related risk factors, such as the consumption of poultry and raw milk. Socioeconomic, agricultural and environmental factors, including drinking water source, can also influence the risk of campylobacteriosis. Approximately 19% of Maryland residents rely on private wells as their sole source of water. Given that the federal Safe Drinking Water Act does not regulate the water quality of private wells, these could be important non-foodborne transmission pathways for Campylobacter. To address this issue, data on the number of culture-confirmed cases of Campylobacter infection in Maryland between 2007 and 2016 were obtained from the Foodborne Diseases Active Surveillance Network. Cases were linked by zip code with data from the Maryland well permits registry, the 2010 U.S. Census, the 2016 American Community Survey, and the USDA Agricultural Census. Campylobacteriosis incidence rates and well prevalence were calculated by zip code. Negative binomial regression models were then constructed to evaluate the association between the prevalence of private wells, presence/absence of animal feeding operations and the incidence of campylobacteriosis across the physiographic provinces in Maryland. From 2007 to 2016, a total of 5746 cases of campylobacteriosis were reported in Maryland, and annual incidence rates ranged from 6.65 to 11.59 per 100,000 people. In our statewide analysis, a significant positive association was observed between well prevalence and increased campylobacteriosis incidence at the zip code level (Incidence Rate Ratio (IRR) = 1.35, 95% Confidence Interval (CI) = 1.11, 1.63). A significant positive association was also observed between well prevalence and increased campylobacteriosis incidence in the Appalachian and Coastal provinces of Maryland (IRR = 2.94, 95% CI = 1.11, 7.76 and IRR = 1.70, 95% CI = 1.25, 2.31, respectively). The presence of broiler chicken operations, increasing median age and percentage of residents living in poverty were also significantly associated with campylobacteriosis incidence at the zip code level in some physiographic provinces in Maryland. To our knowledge, these are the first US data to demonstrate an association between prevalence of private wells and campylobacteriosis incidence at the zip code level.

Lotic surface water sites (e.g. creeks) are important resources for localized agricultural irrigation. However, there is concern that microbial contaminants within untreated surface water may be transferred onto irrigated soil and crops. To evaluate this issue, water samples were collected between January 2017 and August 2018 from a freshwater creek used to irrigate kale and radish plants on a small farm in the Mid-Atlantic, United States. In addition, on one sampling date, a field survey was conducted in which additional water (creek source and point-of-use) and soil samples were collected to assess the viral and bacterial communities pre- and post- irrigation. All samples were processed for DNA extracts and shotgun sequenced on the Illumina HiSeq platform. The resulting metagenomic libraries were assembled de novo and taxonomic and functional features were assigned at the contig and peptide level. From these data, we observed that Betaproteobacteria (e.g. Variovorax) dominated the water, both at the source and point-of-use, and Alphaproteobacteria (e.g. Streptomyces) dominated both pre- and post-irrigated soil. Additionally, in the creek source water there were variations in the abundance of the dominant bacterial genera and functional annotations associated with seasonal characteristics (e.g. water temperature). Antibiotic resistance genes and virulence factors were also identified in the creek water and soil, with the majority specific to their respective habitat. Moreover, an analysis of clustered regularly interspaced short palindromic repeat (CRISPR) arrays showed the persistence of certain spacers through time in the creek water, as well as specific interactions between creek bacteriophages and their hosts. Overall, these findings provide a more holistic picture of bacterial and viral composition, dynamics, and interactions within a freshwater creek that can be utilized to further our knowledge on its suitability and safety for irrigation.

Shotgun metagenomics, which allows for broad sampling of viral diversity, has uncovered genes that are widely distributed among virioplankton populations and show linkages to important biological features of unknown viruses. Over 25% of known dsDNA phage carry the DNA polymerase I (polA) gene, making it one of the most widely distributed phage genes. Because of its pivotal role in DNA replication, this enzyme is linked to phage lifecycle characteristics. Previous research has suggested that a single amino acid substitution might be predictive of viral lifestyle. In this study Chesapeake Bay virioplankton were sampled by shotgun metagenomic sequencing (using long and short read technologies). More polA sequences were predicted from this single viral metagenome (virome) than from 86 globally distributed virome libraries (ca. 2,100, and 1,200, respectively). The PolA peptides predicted from the Chesapeake Bay virome clustered with 69% of PolA peptides from global viromes; thus, remarkably the Chesapeake Bay virome captured the majority of known PolA peptide diversity in viruses. This deeply sequenced virome also expanded the diversity of PolA sequences, increasing the number of PolA clusters by 44%. Contigs containing polA sequences were also used to examine relationships between phylogenetic clades of PolA and other genes within unknown viral populations. Phylogenic analysis revealed five distinct groups of phages distinguished by the amino acids at their 762 (Escherichia coli IAI39 numbering) positions and replication genes. DNA polymerase I sequences from Tyr762 and Phe762 groups were most often neighbored by ring-shaped superfamily IV helicases and ribonucleotide reductases (RNRs). The Leu762 groups had non-ring shaped helicases from superfamily II and were further distinguished by an additional helicase gene from superfamily I and the lack of any identifiable RNR genes. Moreover, we found that the inclusion of ribonucleotide reductase associated with PolA helped to further differentiate phage diversity, chiefly within lytic podovirus populations. Altogether, these data show that DNA Polymerase I is a useful marker for observing the diversity and composition of the virioplankton and may be a driving factor in the divergence of phage replication components.

The use of irrigation water sourced from reclamation facilities and untreated surface water bodies may be a practical solution to attenuate the burden on diminishing groundwater aquifers. However, comprehensive microbial characterizations of these water sources are generally lacking, especially with regard to variations through time and across multiple water types. To address this knowledge gap we used a shotgun metagenomic approach to characterize the taxonomic and functional variations of microbial communities within two agricultural ponds, two freshwater creeks, two brackish rivers, and three water reclamation facilities located in the Mid-Atlantic, United States. Water samples (n = 24) were collected from all sites between October and November 2016, and filtered onto 0.2 μm membrane filters. Filters were then subjected to total DNA extraction and shotgun sequencing on the Illumina HiSeq platform. From these data, we found that Betaproteobacteria dominated the majority of freshwater sites, while Alphaproteobacteria were abundant at times in the brackish waters. One of these brackish sites was also host to a greater abundance of the bacterial genera Gimesia and Microcystis. Furthermore, predicted microbial features (e.g. antibiotic resistance genes (ARGs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) arrays) varied based on specific site and sampling date. ARGs were found across samples, with the diversity and abundance highest in those from a reclamation facility and a wastewater-impacted freshwater creek. Additionally, we identified over 600 CRISPR arrays, containing ∼2600 unique spacers, suggestive of a diverse and often site-specific phage community. Overall, these results provide a better understanding of the complex microbial community in untreated surface and reclaimed waters, while highlighting possible environmental and human health impacts associated with their use in agriculture.

The CRISPR-Cas system is one means by which bacterial and archaeal populations defend against viral infection which causes 20 to 50% of cell mortality in the ocean. We tested the hypothesis that certain viral genes are preferentially targeted for the initial attack of the CRISPR-Cas system on a viral genome. Using CASC, a pipeline for CRISPR spacer discovery, and metagenome data from oceanic microbes and viruses, we found a clear subset of viral genes with high match frequencies to CRISPR spacers. Moreover, we observed a many-to-many relationship of spacers and viral genes. These high-match viral genes were involved in nucleotide metabolism, DNA methylation, and viral structure. It is possible that CRISPR spacer matching is an evolutionary algorithm pointing to those viral genes most important to sustaining infection and lysis. Studying these genes may advance the understanding of virus-host interactions in nature and provide new technologies for leveraging CRISPR-Cas systems in beneficial microbes., Viral infection exerts selection pressure on marine microbes, as virus-induced cell lysis causes 20 to 50% of cell mortality, resulting in fluxes of biomass into oceanic dissolved organic matter. Archaeal and bacterial populations can defend against viral infection using the clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) system, which relies on specific matching between a spacer sequence and a viral gene. If a CRISPR spacer match to any gene within a viral genome is equally effective in preventing lysis, no viral genes should be preferentially matched by CRISPR spacers. However, if there are differences in effectiveness, certain viral genes may demonstrate a greater frequency of CRISPR spacer matches. Indeed, homology search analyses of bacterioplankton CRISPR spacer sequences against virioplankton sequences revealed preferential matching of replication proteins, nucleic acid binding proteins, and viral structural proteins. Positive selection pressure for effective viral defense is one parsimonious explanation for these observations. CRISPR spacers from virioplankton metagenomes preferentially matched methyltransferase and phage integrase genes within virioplankton sequences. These virioplankton CRISPR spacers may assist infected host cells in defending against competing phage. Analyses also revealed that half of the spacer-matched viral genes were unknown, some genes matched several spacers, and some spacers matched multiple genes, a many-to-many relationship. Thus, CRISPR spacer matching may be an evolutionary algorithm, agnostically identifying those genes under stringent selection pressure for sustaining viral infection and lysis. Investigating this subset of viral genes could reveal those genetic mechanisms essential to virus-host interactions and provide new technologies for optimizing CRISPR defense in beneficial microbes.

The Mid-Atlantic Microbiome Meet-up (M3) organization brings together academic, government, and industry groups to share ideas and develop best practices for microbiome research. In January of 2018, M3 held its fourth meeting, which focused on recent advances in biodefense, specifically those relating to infectious disease, and the use of metagenomic methods for pathogen detection. Presentations highlighted the utility of next-generation sequencing technologies for identifying and tracking microbial community members across space and time. However, they also stressed the current limitations of genomic approaches for biodefense, including insufficient sensitivity to detect low-abundance pathogens and the inability to quantify viable organisms. Participants discussed ways in which the community can improve software usability and shared new computational tools for metagenomic processing, assembly, annotation, and visualization. Looking to the future, they identified the need for better bioinformatics toolkits for longitudinal analyses, improved sample processing approaches for characterizing viruses and fungi, and more consistent maintenance of database resources. Finally, they addressed the necessity of improving data standards to incentivize data sharing. Here, we summarize the presentations and discussions from the meeting, identifying the areas where microbiome analyses have improved our ability to detect and manage biological threats and infectious disease, as well as gaps of knowledge in the field that require future funding and focus. Electronic supplementary material The online version of this article (10.1186/s40168-018-0582-5) contains supplementary material, which is available to authorized users.

In order to determine the role of the database in taxonomic sequence classification, we examine the influence of the database over time on k-mer-based lowest common ancestor taxonomic classification. We present three major findings: the number of new species added to the NCBI RefSeq database greatly outpaces the number of new genera; as a result, more reads are classified with newer database versions, but fewer are classified at the species level; and Bayesian-based re-estimation mitigates this effect but struggles with novel genomes. These results suggest a need for new classification approaches specially adapted for large databases.

The throughput of DNA sequencing continues to increase, allowing researchers to analyze genomes of interest at greater depths. An unintended consequence of this data deluge is the increased cost of analyzing these datasets. As a result, genome and metagenome annotation pipelines are left with a few options: (i) search against smaller reference databases, (ii) use faster, but less sensitive, algorithms to assess sequence similarities, or (iii) invest in computing hardware specifically designed to improve BLAST searches such as GPGPU systems and/or large CPU-rich clusters.We present a pipeline that improves the speed of amino acid sequence homology searches with a minimal decrease in sensitivity and specificity by searching against hierarchical clusters. Briefly, the pipeline requires two homology searches: the first search is against a clustered version of the database and the second is against sequences belonging to clusters with a hit from the first search. We tested this method using two assembled viral metagenomes and three databases (Swiss-Prot, Metagenomes Online, and UniRef100). Hierarchical cluster homology searching proved to be 12-times faster than BLASTp and produced alignments that were nearly identical to BLASTp (precision=0.99; recall=0.97). This approach is ideal when searching large collections of sequences against large databases.

Objective Zero-valent iron sand filtration can remove multiple contaminants, including some types of pathogenic bacteria, from contaminated water. However, its efficacy at removing complex viral populations, such as those found in reclaimed water used for agricultural irrigation, has not been fully evaluated. Therefore, this study utilized metagenomic sequencing and epifluorescent microscopy to enumerate and characterize viral populations found in reclaimed water and zero-valent iron-sand filtered reclaimed water sampled three times during a larger greenhouse study. Results Zero-valent iron-sand filtered reclaimed water samples had significantly less virus-like particles than reclaimed water samples at all collection dates, with the reclaimed water averaging between 108 and 109 and the zero-valent iron-sand filtered reclaimed water averaging between 106 and 107 virus-like particles per mL. In addition, for both sample types, viral metagenomes (viromes) were dominated by bacteriophages of the order Caudovirales, largely Siphoviridae, and genes related to DNA metabolism. However, the proportion of sequences homologous to bacteria, as well as the abundance of genes possibly originating from a bacterial host, was higher in the viromes of zero-valent iron-sand filtered reclaimed water samples. Overall, zero-valent iron-sand filtered reclaimed water had a lower total concentration of virus-like particles and a different virome community composition compared to unfiltered reclaimed water. Electronic supplementary material The online version of this article (10.1186/s13104-019-4251-y) contains supplementary material, which is available to authorized users.

Agricultural ponds have a great potential as a means of capture and storage of water for irrigation. However, pond topography (small size, shallow depth) leaves them susceptible to environmental, agricultural, and anthropogenic exposures that may influence microbial dynamics. Therefore, the aim of this project was to characterize the bacterial and viral communities of pond water in the Mid-Atlantic United States with a focus on the late season (October–December), where decreasing temperature and nutrient levels can affect the composition of microbial communities. Ten liters of freshwater from an agricultural pond were sampled monthly, and filtered sequentially through 1 and 0.2 μm filter membranes. Total DNA was then extracted from each filter, and the bacterial communities were characterized using 16S rRNA gene sequencing. The remaining filtrate was chemically concentrated for viruses, DNA-extracted, and shotgun sequenced. Bacterial community profiling showed significant fluctuations over the sampling period, corresponding to changes in the condition of the pond freshwater (e.g., pH, nutrient load). In addition, there were significant differences in the alpha-diversity and core bacterial operational taxonomic units (OTUs) between water fractions filtered through different pore sizes. The viral fraction was dominated by tailed bacteriophage of the order Caudovirales, largely those of the Siphoviridae family. Moreover, while present, genes involved in virulence/antimicrobial resistance were not enriched within the viral fraction during the study period. Instead, the viral functional profile was dominated by phage associated proteins, as well as those related to nucleotide production. Overall, these data suggest that agricultural pond water harbors a diverse core of bacterial and bacteriophage species whose abundance and composition are influenced by environmental variables characteristic of pond topology and the late season.

Accurate species-level taxonomic classification and profiling of complex microbial communities remains a challenge due to homologous regions shared among closely related species and a sparse representation of non-human associated microbes in the database. Although the database undoubtedly has a strong influence on the sensitivity of taxonomic classifiers and profilers, to date, no study has carefully explored this topic on historical RefSeq releases and explored its impact on accuracy. In this study, we examined the influence of the database, over time, on k-mer based sequence classification and profiling. We present three major findings: (i) database growth over time resulted in more classified reads, but fewer species-level classifications and more species-level misclassifications; (ii) Bayesian re-estimation of abundance helped to recover species-level classifications when the exact target strain was present; and (iii) Bayesian reestimation struggled when the database lacked the target strain, resulting in a notable decrease in accuracy. In summary, our findings suggest that the growth of RefSeq over time has strongly influenced the accuracy of k-mer based classification and profiling methods, resulting in different classification results depending on the particular database used. These results suggest a need for new algorithms specially adapted for large genome collections and better measures of classification uncertainty.

The discovery of abundant viruses in the oceans and on land has ushered in a quarter century of groundbreaking advancements in our understanding of viruses within ecosystems. Two types of observations from environmental samples--direct counts of viral particles and viral metagenomic sequences--have been critical to these discoveries. Accurate direct counts have established ecosystem-scale trends in the impacts of viral infection on microbial host populations and have shown that viral communities within aquatic and soil environments respond to both short term and seasonal environmental change. Direct counts have been critical for estimating viral production rate, a measurement essential to quantifying the implications of viral infection for the biogeochemical cycling of nutrients within ecosystems. While direct counts have defined the magnitude of viral processes; shotgun sequences of environmental viral DNA--virome sequences--have enabled researchers to estimate the diversity and composition of natural viral communities. Virome-enabled studies have found the virioplankton to contain thousands of viral genotypes in communities where the most dominant viral population accounts for a small fraction of total abundance followed by a long tail of diverse populations. Detailed examination of long virome sequences has led to new understanding of genotype-to-phenotype connections within marine viruses and revealed that viruses carry metabolic genes that are important to maintaining cellular energy during viral replication. Increased access to long virome sequences will undoubtedly reveal more genetic secrets of viruses and enable us to build a genomics rulebook for predicting key biological and ecological features of unknown viruses.

One consistent finding among studies using shotgun metagenomics to analyze whole viral communities is that most viral sequences show no significant homology to known sequences. Thus, bioinformatic analyses based on sequence collections such as GenBank nr, which are largely comprised of sequences from known organisms, tend to ignore a majority of sequences within most shotgun viral metagenome libraries. Here we describe a bioinformatic pipeline, the Viral Informatics Resource for Metagenome Exploration (VIROME), that emphasizes the classification of viral metagenome sequences (predicted open-reading frames) based on homology search results against both known and environmental sequences. Functional and taxonomic information is derived from five annotated sequence databases which are linked to the UniRef 100 database. Environmental classifications are obtained from hits against a custom database, MetaGenomes On-Line, which contains 49 million predicted environmental peptides. Each predicted viral metagenomic ORF run through the VIROME pipeline is placed into one of seven ORF classes, thus, every sequence receives a meaningful annotation. Additionally, the pipeline includes quality control measures to remove contaminating and poor quality sequence and assesses the potential amount of cellular DNA contamination in a viral metagenome library by screening for rRNA genes. Access to the VIROME pipeline and analysis results are provided through a web-application interface that is dynamically linked to a relational back-end database. The VIROME web-application interface is designed to allow users flexibility in retrieving sequences (reads, ORFs, predicted peptides) and search results for focused secondary analyses.

Virioplankton play a crucial role in aquatic ecosystems as top-down regulators of bacterial populations and agents of horizontal gene transfer and nutrient cycling. However, the biology and ecology of virioplankton populations in the environment remain poorly understood. Ribonucleotide reductases (RNRs) are ancient enzymes that reduce ribonucleotides to deoxyribonucleotides and thus prime DNA synthesis. Composed of three classes according to O2 reactivity, RNRs can be predictive of the physiological conditions surrounding DNA synthesis. RNRs are universal among cellular life, common within viral genomes and virioplankton shotgun metagenomes (viromes), and estimated to occur within >90% of the dsDNA virioplankton sampled in this study. RNRs occur across diverse viral groups, including all three morphological families of tailed phages, making these genes attractive for studies of viral diversity. Differing patterns in virioplankton diversity were clear from RNRs sampled across a broad oceanic transect. The most abundant RNRs belonged to novel lineages of podoviruses infecting α-proteobacteria, a bacterial class critical to oceanic carbon cycling. RNR class was predictive of phage morphology among cyanophages and RNR distribution frequencies among cyanophages were largely consistent with the predictions of the “kill the winner–cost of resistance” model. RNRs were also identified for the first time to our knowledge within ssDNA viromes. These data indicate that RNR polymorphism provides a means of connecting the biological and ecological features of virioplankton populations.

Background Shotgun metagenomics has become an important tool for investigating the ecology of microorganisms. Underlying these investigations is the assumption that metagenome sequence data accurately estimates the census of microbial populations. Multiple displacement amplification (MDA) of microbial community DNA is often used in cases where it is difficult to obtain enough DNA for sequencing; however, MDA can result in amplification biases that may impact subsequent estimates of population census from metagenome data. Some have posited that pooling replicate MDA reactions negates these biases and restores the accuracy of population analyses. This assumption has not been empirically tested. Results Using mock viral communities, we examined the influence of pooling on population-scale analyses. In pooled and single reaction MDA treatments, sequence coverage of viral populations was highly variable and coverage patterns across viral genomes were nearly identical, indicating that initial priming biases were reproducible and that pooling did not alleviate biases. In contrast, control unamplified sequence libraries showed relatively even coverage across phage genomes. Conclusions MDA should be avoided for metagenomic investigations that require quantitative estimates of microbial taxa and gene functional groups. While MDA is an indispensable technique in applications such as single-cell genomics, amplification biases cannot be overcome by combining replicate MDA reactions. Alternative library preparation techniques should be utilized for quantitative microbial ecology studies utilizing metagenomic sequencing approaches.