Prophage identification and molecular analysis in the genomes of Pseudomonas aeruginosa strains isolated from critical care patients

Prophages are bacteriophages integrated into the bacterial host's chromosome. This research aims to analyze and characterize the existing prophages within a collection of 53 Pseudomonas aeruginosa strains from intensive care units (ICUs) in Portugal and Spain. A total of 113 prophages were localized in the collection, with 18 of them being present in more than one strain simultaneously. After annotation, five of them were discarded as incomplete, and the 13 remaining prophages were characterized. Of 13, 10 belonged to the siphovirus tail morphology group, 2 to the podovirus tail morphology group, and 1 to the myovirus tail morphology group. All prophages had a length ranging from 20,199 to 63,401 bp and a GC% between 56.2% and 63.6%. The number of open reading frames (ORFs) oscillated between 32 and 88, and in 3/13 prophages, more than 50% of the ORFs had an unknown function. With our findings, we show that prophages are present in the majority of the P. aeruginosa strains isolated from Portuguese and Spanish critically ill patients, many of them found in more than one circulating strain at the same time and following a similar clonal distribution pattern. Although a great sum of ORFs had an unknown function, number of proteins in relation to viral defense (anti-CRISPR proteins, toxin/antitoxin modules, proteins against restriction-modification systems) as well as to prophage interference into their host's quorum sensing system and regulatory cascades were found. This supports the idea that prophages have an influence in bacterial pathogenesis and anti-phage defense. IMPORTANCE Despite being known for decades, prophages remain understudied when compared to the lytic phages employed in phage therapy. This research aims to shed some light into the nature, composition, and role of prophages found within a set of circulating strains of Pseudomas aeruginosa, with special attention to high-risk clones. Given the fact that prophages can effectively influence bacterial pathogenesis, prophage basic research constitutes a topic of growing interest. Furthermore, the abundance of viral defense and regulatory proteins within prophage genomes detected in this study evidences the importance of characterizing the most frequent prophages in circulating clinical strains and in high-risk clones if phage therapy is to be used.

What Lies Beneath? Taking the Plunge into the Murky Waters of Phage Biology

The sequence revolution revealed that bacteria-infecting viruses, known as phages, are Earth's most abundant biological entities. Phages have far-reaching impacts on the form and function of microbial communities and play a fundamental role in ecological processes. However, even well into the sequencing revolution, we have only just begun to explore the murky waters around the phage biology iceberg. Many viral reads cannot be assigned to a culturable isolate, and reference databases are biased toward more easily collectible samples, which likely distorts our conclusions. This minireview points out alternatives to mapping reads to reference databases and highlights innovative bioinformatic and experimental approaches that can help us overcome some of the challenges in phage research and better decipher the impact of phages on microbial communities. Moving beyond the identification of novel phages, we highlight phage metabolomics as an important influencer of bacterial host cell physiology and hope to inspire the reader to consider the effects of phages on host metabolism and ecosystems at large. We encourage researchers to report unassigned/unknown sequencing reads and contigs and to continue developing alternative methods to investigate phages within sequence data.

Longitudinal metatranscriptomic sequencing of Southern California wastewater representing 16 million people from August 2020-21 reveals widespread transcription of antibiotic resistance genes

Municipal wastewater provides a representative sample of human fecal waste across a catchment area and contains a wide diversity of microbes. Sequencing wastewater samples provides information about human-associated and medically important microbial populations, and may be useful to assay disease prevalence and antimicrobial resistance (AMR). Here, we present a study in which we used untargeted metatranscriptomic sequencing on RNA extracted from 275 sewage influent samples obtained from eight wastewater treatment plants (WTPs) representing approximately 16 million people in Southern California between August 2020 - August 2021. We characterized bacterial and viral transcripts, assessed metabolic pathway activity, and identified over 2,000 AMR genes/variants across all samples. Because we did not deplete ribosomal RNA, we have a unique window into AMR carried as ribosomal mutants. We show that AMR diversity varied between WTPs (as measured through PERMANOVA, P < 0.001) and that the relative abundance of many individual AMR genes/variants increased over time (as measured with MaAsLin2, P_adj < 0.05). Similarly, we detected transcripts mapping to human pathogenic bacteria and viruses suggesting RNA sequencing is a powerful tool for wastewater-based epidemiology and that there are geographical signatures to microbial transcription. We captured the transcription of gene pathways common to bacterial cell processes, including central carbon metabolism, nucleotide synthesis/salvage, and amino acid biosynthesis. We also posit that due to the ubiquity of many viruses and bacteria in wastewater, new biological targets for microbial water quality assessment can be developed. To the best of our knowledge, our study provides the most complete longitudinal metatranscriptomic analysis of a large population's wastewater to date and demonstrates our ability to monitor the presence and activity of microbes in complex samples. By sequencing RNA, we can track the relative abundance of expressed AMR genes/variants and metabolic pathways, increasing our understanding of AMR activity across large human populations and sewer sheds.

Characterization of the human gut virome in metabolic and autoimmune diseases

The intestinal microbiome is dominated by bacteria and plays a pivotal role in the occurrence and development of disease, including several metabolic and autoimmune disorders. While intestinal viral communities, primarily made up of bacteriophages, are also thought to play a role in disease pathogenesis in the gastrointestinal tract, they have received much less attention than intestinal bacteria. Thus, there is limited information about the relationship between bacteriophages and disease. This review explores a potential role for the intestinal viral microbiome in various metabolic and autoimmune diseases.

Individual-based model highlights the importance of trade-offs for virus-host population dynamics and long-term co-existence

Viruses play diverse and important roles in ecosystems. In recent years, trade-offs between host and virus traits have gained increasing attention in viral ecology and evolution. However, microbial organism traits, and viral population parameters in particular, are challenging to monitor. Mathematical and individual-based models are useful tools for predicting virus-host dynamics. We have developed an individual-based evolutionary model to study ecological interactions and evolution between bacteria and viruses, with emphasis on the impacts of trade-offs between competitive and defensive host traits on bacteria-phage population dynamics and trait diversification. Host dynamics are validated with lab results for different initial virus to host ratios (VHR). We show that trade-off based, as opposed to random bacteria-virus interactions, result in biologically plausible evolutionary outcomes, thus highlighting the importance of trade-offs in shaping biodiversity. The effects of nutrient concentration and other environmental and organismal parameters on the virus-host dynamics are also investigated. Despite its simplicity, our model serves as a powerful tool to study bacteria-phage interactions and mechanisms for evolutionary diversification under various environmental conditions.

RNN-VirSeeker: A Deep Learning Method for Identification of Short Viral Sequences From Metagenomes

Viruses are the most abundant biological entities on earth, and play vital roles in many aspects of microbial communities. As major human pathogens, viruses have caused huge mortality and morbidity to human society in history. Metagenomic sequencing methods could capture all microorganisms from microbiota, with sequences of viruses mixed with these of other species. Therefore, it is necessary to identify viral sequences from metagenomes. However, existing methods perform poorly on identifying short viral sequences. To solve this problem, a deep learning based method, RNN-VirSeeker, is proposed in this paper. RNN-VirSeeker was trained by sequences of 500bp sampled from known Virus and Host RefSeq genomes. Experimental results on the testing set have shown that RNN-VirSeeker exhibited AUROC of 0.9175, recall of 0.8640 and precision of 0.9211 for sequences of 500bp, and outperformed three widely used methods, VirSorter, VirFinder, and DeepVirFinder, on identifying short viral sequences. RNN-VirSeeker was also used to identify viral sequences from a CAMI dataset and a human gut metagenome. Compared with DeepVirFinder, RNN-VirSeeker identified more viral sequences from these metagenomes and achieved greater values of AUPRC and AUROC. RNN-VirSeeker is freely available at https://github.com/crazyinter/RNN-VirSeeker.

Virtifier: a deep learning-based identifier for viral sequences from metagenomes

MOTIVATION

Viruses, the most abundant biological entities on earth, are important components of microbial communities, and as major human pathogens, they are responsible for human mortality and morbidity. The identification of viral sequences from metagenomes is critical for viral analysis. As massive quantities of short sequences are generated by next-generation sequencing, most methods utilize discrete and sparse one-hot vectors to encode nucleotide sequences, which are usually ineffective in viral identification.

RESULTS

In this article, Virtifier, a deep learning-based viral identifier for sequences from metagenomic data is proposed. It includes a meaningful nucleotide sequence encoding method named Seq2Vec and a variant viral sequence predictor with an attention-based long short-term memory (LSTM) network. By utilizing a fully trained embedding matrix to encode codons, Seq2Vec can efficiently extract the relationships among those codons in a nucleotide sequence. Combined with an attention layer, the LSTM neural network can further analyze the codon relationships and sift the parts that contribute to the final features. Experimental results of three datasets have shown that Virtifier can accurately identify short viral sequences (<500 bp) from metagenomes, surpassing three widely used methods, VirFinder, DeepVirFinder and PPR-Meta. Meanwhile, a comparable performance was achieved by Virtifier at longer lengths (>5000 bp).

AVAILABILITY AND IMPLEMENTATION

A Python implementation of Virtifier and the Python code developed for this study have been provided on Github https://github.com/crazyinter/Seq2Vec. The RefSeq genomes in this article are available in VirFinder at https://dx.doi.org/10.1186/s40168-017-0283-5. The CAMI Challenge Dataset 3 CAMI_high dataset in this article is available in CAMI at https://data.cami-challenge.org/participate. The real human gut metagenomes in this article are available at https://dx.doi.org/10.1101/gr.142315.112.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MCRL: using a reference library to compress a metagenome into a non-redundant list of sequences, considering viruses as a case study

MOTIVATION

Metagenomes offer a glimpse into the total genomic diversity contained within a sample. Currently, however, there is no straightforward way to obtain a non-redundant list of all putative homologs of a set of reference sequences present in a metagenome.

RESULTS

To address this problem, we developed a novel clustering approach called 'metagenomic clustering by reference library' (MCRL), where a reference library containing a set of reference genes is clustered with respect to an assembled metagenome. According to our proposed approach, reference genes homologous to similar sets of metagenomic sequences, termed 'signatures', are iteratively clustered in a greedy fashion, retaining at each step the reference genes yielding the lowest E values, and terminating when signatures of remaining reference genes have a minimal overlap. The outcome of this computation is a non-redundant list of reference genes homologous to minimally overlapping sets of contigs, representing potential candidates for gene families present in the metagenome. Unlike metagenomic clustering methods, there is no need for contigs to overlap to be associated with a cluster, enabling MCRL to draw on more information encoded in the metagenome when computing tentative gene families. We demonstrate how MCRL can be used to extract candidate viral gene families from an oral metagenome and an oral virome that otherwise could not be determined using standard approaches. We evaluate the sensitivity, accuracy and robustness of our proposed method for the viral case study and compare it with existing analysis approaches.

AVAILABILITY AND IMPLEMENTATION

https://github.com/a-tadmor/MCRL.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Explainable deep neural networks for novel viral genome prediction

Viral infection causes a wide variety of human diseases including cancer and COVID-19. Viruses invade host cells and associate with host molecules, potentially disrupting the normal function of hosts that leads to fatal diseases. Novel viral genome prediction is crucial for understanding the complex viral diseases like AIDS and Ebola. While most existing computational techniques classify viral genomes, the efficiency of the classification depends solely on the structural features extracted. The state-of-the-art DNN models achieved excellent performance by automatic extraction of classification features, but the degree of model explainability is relatively poor. During model training for viral prediction, proposed CNN, CNN-LSTM based methods (EdeepVPP, EdeepVPP-hybrid) automatically extracts features. EdeepVPP also performs model interpretability in order to extract the most important patterns that cause viral genomes through learned filters. It is an interpretable CNN model that extracts vital biologically relevant patterns (features) from feature maps of viral sequences. The EdeepVPP-hybrid predictor outperforms all the existing methods by achieving 0.992 mean AUC-ROC and 0.990 AUC-PR on 19 human metagenomic contig experiment datasets using 10-fold cross-validation. We evaluate the ability of CNN filters to detect patterns across high average activation values. To further asses the robustness of EdeepVPP model, we perform leave-one-experiment-out cross-validation. It can work as a recommendation system to further analyze the raw sequences labeled as ‘unknown’ by alignment-based methods. We show that our interpretable model can extract patterns that are considered to be the most important features for predicting virus sequences through learned filters.

Informative Regions In Viral Genomes

Viruses, far from being just parasites affecting hosts' fitness, are major players in any microbial ecosystem. In spite of their broad abundance, viruses, in particular bacteriophages, remain largely unknown since only about 20% of sequences obtained from viral community DNA surveys could be annotated by comparison with public databases. In order to shed some light into this genetic dark matter we expanded the search of orthologous groups as potential markers to viral taxonomy from bacteriophages and included eukaryotic viruses, establishing a set of 31,150 ViPhOGs (Eukaryotic Viruses and Phages Orthologous Groups). To do this, we examine the non-redundant viral diversity stored in public databases, predict proteins in genomes lacking such information, and used all annotated and predicted proteins to identify potential protein domains. The clustering of domains and unannotated regions into orthologous groups was done using cogSoft. Finally, we employed a random forest implementation to classify genomes into their taxonomy and found that the presence or absence of ViPhOGs is significantly associated with their taxonomy. Furthermore, we established a set of 1457 ViPhOGs that given their importance for the classification could be considered as markers or signatures for the different taxonomic groups defined by the ICTV at the order, family, and genus levels.

Viruses in fermented foods: are they good or bad? Two sides of the same coin

The emergence of Coronavirus disease 2019 as a global pandemic has increased popular concerns about diseases caused by viruses. Fermented foods containing high loads of viable fungi and bacteria are potential sources for virus contamination. The most common include viruses that infect bacteria (bacteriophage) and yeasts reported in fermented milks, sausages, vegetables, wine, sourdough, and cocoa beans. Recent molecular studies have also associated fermented foods as vehicles for pathogenic human viruses. Human noroviruses, rotavirus, and hepatitis virus have been identified in different fermented foods through multiple routes. No severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) virus or close members were found in fermented foods to date. However, the occurrence/persistence of other pathogenic viruses reveals a potential vulnerability of fermented foods to SARS-CoV-2 contamination. On the other side of the coin, some bacteriophages are being suggested for improving the fermentation process and food safety, as well as owing potential probiotic properties in modern fermented foods. This review will address the diversity and characteristics of viruses associated with fermented foods and what has been changed after a short introduction to the most common next-generation sequencing platforms. Also, the risk of SARS-CoV-2 transmission via fermented foods and preventive measures will be discussed.

The Fennoscandian Shield deep terrestrial virosphere suggests slow motion 'boom and burst' cycles

The deep biosphere contains members from all three domains of life along with viruses. Here we investigate the deep terrestrial virosphere by sequencing community nucleic acids from three groundwaters of contrasting chemistries, origins, and ages. These viromes constitute a highly unique community compared to other environmental viromes and sequenced viral isolates. Viral host prediction suggests that many of the viruses are associated with Firmicutes and Patescibacteria, a superphylum lacking previously described active viruses. RNA transcript-based activity implies viral predation in the shallower marine water-fed groundwater, while the deeper and more oligotrophic waters appear to be in ‘metabolic standby’. Viral encoded antibiotic production and resistance systems suggest competition and antagonistic interactions. The data demonstrate a viral community with a wide range of predicted hosts that mediates nutrient recycling to support a higher microbial turnover than previously anticipated. This suggests the presence of ‘kill-the-winner’ oscillations creating slow motion ‘boom and burst’ cycles.

Karin Holmfeldt et al. sequence metagenomes and metatranscriptomes of viruses in deep groundwaters down to 448 m below the surface. The results reveal ecological dynamics of viruses including slow motion ‘boom and burst’ cycles and a ‘kill the winner’ model potentially driven by viral predation.

Analysis of metagenome-assembled viral genomes from the human gut reveals diverse putative CrAss-like phages with unique genomic features

CrAssphage is the most abundant human-associated virus and the founding member of a large group of bacteriophages, discovered in animal-associated and environmental metagenomes, that infect bacteria of the phylum Bacteroidetes. We analyze 4907 Circular Metagenome Assembled Genomes (cMAGs) of putative viruses from human gut microbiomes and identify nearly 600 genomes of crAss-like phages that account for nearly 87% of the DNA reads mapped to these cMAGs. Phylogenetic analysis of conserved genes demonstrates the monophyly of crAss-like phages, a putative virus order, and of 5 branches, potential families within that order, two of which have not been identified previously. The phage genomes in one of these families are almost twofold larger than the crAssphage genome (145-192 kilobases), with high density of self-splicing introns and inteins. Many crAss-like phages encode suppressor tRNAs that enable read-through of UGA or UAG stop-codons, mostly, in late phage genes. A distinct feature of the crAss-like phages is the recurrent switch of the phage DNA polymerase type between A and B families. Thus, comparative genomic analysis of the expanded assemblage of crAss-like phages reveals aspects of genome architecture and expression as well as phage biology that were not apparent from the previous work on phage genomics.

Seeker: alignment-free identification of bacteriophage genomes by deep learning

Recent advances in metagenomic sequencing have enabled discovery of diverse, distinct microbes and viruses. Bacteriophages, the most abundant biological entity on Earth, evolve rapidly, and therefore, detection of unknown bacteriophages in sequence datasets is a challenge. Most of the existing detection methods rely on sequence similarity to known bacteriophage sequences, impeding the identification and characterization of distinct, highly divergent bacteriophage families. Here we present Seeker, a deep-learning tool for alignment-free identification of phage sequences. Seeker allows rapid detection of phages in sequence datasets and differentiation of phage sequences from bacterial ones, even when those phages exhibit little sequence similarity to established phage families. We comprehensively validate Seeker's ability to identify previously unidentified phages, and employ this method to detect unknown phages, some of which are highly divergent from the known phage families. We provide a web portal (seeker.pythonanywhere.com) and a user-friendly Python package (github.com/gussow/seeker) allowing researchers to easily apply Seeker in metagenomic studies, for the detection of diverse unknown bacteriophages.

Lysogeny in the oceans: Lessons from cultivated model systems and a reanalysis of its prevalence

In the oceans, viruses that infect bacteria (phages) influence a variety of microbially mediated processes that drive global biogeochemical cycles. The nature of their influence is dependent upon infection mode, be it lytic or lysogenic. Temperate phages are predicted to be prevalent in marine systems where they are expected to execute both types of infection modes. Understanding the range and outcomes of temperate phage-host interactions is fundamental for evaluating their ecological impact. Here, we (i) review phage-mediated rewiring of host metabolism, with a focus on marine systems, (ii) consider the range and nature of temperate phage-host interactions, and (iii) draw on studies of cultivated model systems to examine the consequences of lysogeny among several dominant marine bacterial lineages. We also readdress the prevalence of lysogeny among marine bacteria by probing a collection of 1239 publicly available bacterial genomes, representing cultured and uncultivated strains, for evidence of complete prophages. Our conservative analysis, anticipated to underestimate true prevalence, predicts 18% of the genomes examined contain at least one prophage, the majority (97%) were found within genomes of cultured isolates. These results highlight the need for cultivation of additional model systems to better capture the diversity of temperate phage-host interactions in the oceans.

Phages and their potential to modulate the microbiome and immunity

Bacteriophages (hence termed phages) are viruses that target bacteria and have long been considered as potential future treatments against antibiotic-resistant bacterial infection. However, the molecular nature of phage interactions with bacteria and the human host has remained elusive for decades, limiting their therapeutic application. While many phages and their functional repertoires remain unknown, the advent of next-generation sequencing has increasingly enabled researchers to decode new lytic and lysogenic mechanisms by which they attack and destroy bacteria. Furthermore, the last decade has witnessed a renewed interest in the utilization of phages as therapeutic vectors and as a means of targeting pathogenic or commensal bacteria or inducing immunomodulation. Importantly, the narrow host range, immense antibacterial repertoire, and ease of manipulating phages may potentially allow for their use as targeted modulators of pathogenic, commensal and pathobiont members of the microbiome, thereby impacting mammalian physiology and immunity along mucosal surfaces in health and in microbiome-associated diseases. In this review, we aim to highlight recent advances in phage biology and how a mechanistic understanding of phage-bacteria-host interactions may facilitate the development of novel phage-based therapeutics. We provide an overview of the challenges of the therapeutic use of phages and how these could be addressed for future use of phages as specific modulators of the human microbiome in a variety of infectious and noncommunicable human diseases.

PuMA: A papillomavirus genome annotation tool

High-throughput sequencing technologies provide unprecedented power to identify novel viruses from a wide variety of (environmental) samples. The field of ‘viral metagenomics’ has dramatically expanded our understanding of viral diversity. Viral metagenomic approaches imply that many novel viruses will not be described by researchers who are experts on (the genomic organization of) that virus family. We have developed the papillomavirus annotation tool (PuMA) to provide researchers with a convenient and reproducible method to annotate and report novel papillomaviruses. PuMA currently correctly annotates 99% of the papillomavirus genes when benchmarked against the 655 reference genomes in the papillomavirus episteme. Compared to another viral annotation pipeline, PuMA annotates more viral features while being more accurate. To demonstrate its general applicability, we also developed a preliminary version of PuMA that can annotate polyomaviruses. PuMA is available on GitHub (https://github.com/KVD-lab/puma) and through the iMicrobe online environment (https://www.imicrobe.us/#/apps/puma).

A Lactococcal Phage Protein Promotes Viral Propagation and Alters the Host Proteomic Response During Infection

The lactococcal virulent phage p2 is a model for studying the Skunavirus genus, the most prevalent group of phages causing milk fermentation failures in cheese factories worldwide. This siphophage infects Lactococcus lactis MG1363, a model strain used to study Gram-positive lactic acid bacteria. The structural proteins of phage p2 have been thoroughly described, while most of its non-structural proteins remain uncharacterized. Here, we developed an integrative approach, making use of structural biology, genomics, physiology, and proteomics to provide insights into the function of ORF47, the most conserved non-structural protein of unknown function among the Skunavirus genus. This small phage protein, which is composed of three α-helices, was found to have a major impact on the bacterial proteome during phage infection and to significantly reduce the emergence of bacteriophage-insensitive mutants.

Phage community involvement in fermented beverages: an open door to technological advances?

Bacteriophages (phages) are considered the most abundant biological entities on Earth. An increasing interest in understanding phage communities, also called viromes or phageomes, has arisen over the past decade especially thanks to the development and the accessibility of Next Generation Sequencing techniques. Despite the increasing amount of available metagenomic data on microbial communities in various habitats, viromes remain poorly described in the scientific literature particularly when it comes to fermented food and beverages such as wine and cider. In this review, a particular attention is paid to the current knowledge on phage communities, with a special focus on fermented food viromes and the methodological tools available to undertake their study. There is a striking lack of available data on the fermented foods and beverages viromes. As far as we know, and although a number of phages have been isolated from wine, no general study has to date been carried out to assess the diversity of viromes in fermented beverages and their possible interactions with microbiota throughout the fermentation process. With the aim of establishing connections between the currently used technologies to carry out the analysis of viromes, possible applications of current knowledge to fermented beverages are examined.

Between a Rock and a Soft Place: The Role of Viruses in Lithification of Modern Microbial Mats

Stromatolites are geobiological systems formed by complex microbial communities, and fossilized stromatolites provide a record of some of the oldest life on Earth. Microbial mats are precursors of extant stromatolites; however, the mechanisms of transition from mat to stromatolite are controversial and are still not well understood. To fully recognize the profound impact that these ecosystems have had on the evolution of the biosphere requires an understanding of modern lithification mechanisms and how they relate to the geological record. We propose here viral mechanisms in carbonate precipitation, leading to stromatolite formation, whereby viruses directly or indirectly impact microbial metabolisms that govern the transition from microbial mat to stromatolite. Finding a tangible link between host-virus interactions and changes in biogeochemical processes will provide tools to interpret mineral biosignatures through geologic time, including those on Earth and beyond.

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

The study of soil viruses, though not new, has languished relative to the study of marine viruses. This is particularly due to challenges associated with separating virions from harboring soils. Generally, three approaches to analyzing soil viruses have been employed: (1) Isolation, to characterize virus genotypes and phenotypes, the primary method used prior to the start of the 21st century. (2) Metagenomics, which has revealed a vast diversity of viruses while also allowing insights into viral community ecology, although with limitations due to DNA from cellular organisms obscuring viral DNA. (3) Viromics (targeted metagenomics of virus-like-particles), which has provided a more focused development of ‘virus-sequence-to-ecology’ pipelines, a result of separation of presumptive virions from cellular organisms prior to DNA extraction. This separation permits greater sequencing emphasis on virus DNA and thereby more targeted molecular and ecological characterization of viruses. Employing viromics to characterize soil systems presents new challenges, however. Ones that only recently are being addressed. Here we provide a guide to implementing these three approaches to studying environmental viruses, highlighting benefits, difficulties, and potential contamination, all toward fostering greater focus on viruses in the study of soil ecology.

PHAST, PHASTER and PHASTEST: Tools for finding prophage in bacterial genomes

PHAST (PHAge Search Tool) and its successor PHASTER (PHAge Search Tool - Enhanced Release) have become two of the most widely used web servers for identifying putative prophages in bacterial genomes. Here we review the main capabilities of these web resources, provide some practical guidance regarding their use and discuss possible future improvements. PHAST, which was first described in 2011, made its debut just as whole bacterial genome sequencing and was becoming inexpensive and relatively routine. PHAST quickly gained popularity among bacterial genome researchers because of its web accessibility, its ease of use along with its enhanced accuracy and rapid processing times. PHASTER, which appeared in 2016, provided a number of much-needed enhancements to the PHAST server, including greater processing speed (to cope with very large submission volumes), increased database sizes, a more modern user interface, improved graphical displays and support for metagenomic submissions. Continuing developments in the field, along with increased interest in automated phage and prophage finding, have already led to several improvements to the PHASTER server and will soon lead to the development of a successor to PHASTER (to be called PHASTEST).

The crAss-like Phage Group: How Metagenomics Reshaped the Human Virome

Metagenomics is currently the primary means for identifying new viruses. One of the most impactful metagenomic discoveries is that of crAssphage, the most abundant human-associated virus that is found in about 50% of human gut viromes where it can comprise up to 90% of the virus sequences. Although initial genome analysis of crAssphage failed to detect related phages, or functionally annotate most of the genes, subsequent reanalysis with powerful computational methods and larger databases led to the identification of an expansive group of crAss-like phages. The functions of most crAssphage proteins were predicted, including unusual ones such as giant RNA polymerase polyproteins. The host range of the crAss-like phages consists of various members of the bacterial phylum Bacteroidetes as demonstrated by CRISPR spacer analysis and by analysis of genes acquired by phages from the hosts. New metagenomic studies vastly expanded the crAss-like phage group and demonstrated its global spread and ancient association with primates. The first members of the crAss-like group was recently isolated and shown to infect the bacterium Bacteroides intestinales. Characterization of this phage validated the predicted podovirus-like virion structure and the identity of the major capsid protein and other predicted virion proteins, including three RNA polymerase subunits.

A Protocol for Extraction of Infective Viromes Suitable for Metagenomics Sequencing from Low Volume Fecal Samples

The human gut microbiome (GM) plays an important role in human health and diseases. However, while substantial progress has been made in understanding the role of bacterial inhabitants of the gut, much less is known regarding the viral component of the GM. Bacteriophages (phages) are viruses attacking specific host bacteria and likely play important roles in shaping the GM. Although metagenomic approaches have led to the discoveries of many new viruses, they remain largely uncultured as their hosts have not been identified, which hampers our understanding of their biological roles. Existing protocols for isolation of viromes generally require relatively high input volumes and are generally more focused on extracting nucleic acids of good quality and purity for down-stream analysis, and less on purifying viruses with infective capacity. In this study, we report the development of an efficient protocol requiring low sample input yielding purified viromes containing phages that are still infective, which also are of sufficient purity for genome sequencing. We validated the method through spiking known phages followed by plaque assays, qPCR, and metagenomic sequencing. The protocol should facilitate the process of culturing novel viruses from the gut as well as large scale studies on gut viromes.

Dynamics of crAssphage as a human source tracking marker in potentially faecally polluted environments

Recent studies have shown that crAssphage is abundant in human faecal samples worldwide. It has thus been postulated as a potential microbial source tracking (MST) marker to detect human faecal pollution in water. However, an effective implementation of crAssphage in water management strategies will depend on an understanding of its environmental dynamics. In this work, the abundance and temporal distribution of crAssphage was analysed in the effluent of wastewater treatment plants using different sewage treatments, and in two rivers (water and sediments) that differ in pollution impact and flow regime. Additionally, the influence of environmental conditions (temperature and rainfall) on the removal of the marker was studied along a river section, and natural inactivation was assessed by a mesocosms approach. Molecular and culture-based tools were used to compare crAssphage abundance and dynamics with those of bacteria and bacteriophages currently applied as global indicators (E. coli, somatic coliphages, Bacteroides GA17 bacteriophages, and the human-associated MST markers HF183 and HMBif). CrAssphage concentrations in sewage effluent and river samples were similar to those of HF183 and HMBif and higher than other general and/or culture-based indicators (by 2-3 orders of magnitude). Measurement of crAssphage abundance revealed no temporal variability in the effluent, although rainfall events affected the dynamics, possibly through the mobilisation of sediments, where the marker was detected in high concentrations, and an increase in diffuse and point pollution. Another factor affecting crAssphage inactivation was temperature. Its persistence was longer compared with other bacterial markers analysed by qPCR but lower than culturable markers. The results of this study support the use of crAssphage as a human source tracking marker of faecal pollution in water, since it has similar abundances to other molecular human MST markers, yet with a longer persistence in the environment. Nevertheless, its use in combination with infectious bacteriophages is probably advisable.

Mining, analyzing, and integrating viral signals from metagenomic data

BACKGROUND

Viruses are important components of microbial communities modulating community structure and function; however, only a couple of tools are currently available for phage identification and analysis from metagenomic sequencing data. Here we employed the random forest algorithm to develop VirMiner, a web-based phage contig prediction tool especially sensitive for high-abundances phage contigs, trained and validated by paired metagenomic and phagenomic sequencing data from the human gut flora.

RESULTS

VirMiner achieved 41.06% ± 17.51% sensitivity and 81.91% ± 4.04% specificity in the prediction of phage contigs. In particular, for the high-abundance phage contigs, VirMiner outperformed other tools (VirFinder and VirSorter) with much higher sensitivity (65.23% ± 16.94%) than VirFinder (34.63% ± 17.96%) and VirSorter (18.75% ± 15.23%) at almost the same specificity. Moreover, VirMiner provides the most comprehensive phage analysis pipeline which is comprised of metagenomic raw reads processing, functional annotation, phage contig identification, and phage-host relationship prediction (CRISPR-spacer recognition) and supports two-group comparison when the input (metagenomic sequence data) includes different conditions (e.g., case and control). Application of VirMiner to an independent cohort of human gut metagenomes obtained from individuals treated with antibiotics revealed that 122 KEGG orthology and 118 Pfam groups had significantly differential abundance in the pre-treatment samples compared to samples at the end of antibiotic administration, including clustered regularly interspaced short palindromic repeats (CRISPR), multidrug resistance, and protein transport. The VirMiner webserver is available at http://sbb.hku.hk/VirMiner/ .

CONCLUSIONS

We developed a comprehensive tool for phage prediction and analysis for metagenomic samples. Compared to VirSorter and VirFinder-the most widely used tools-VirMiner is able to capture more high-abundance phage contigs which could play key roles in infecting bacteria and modulating microbial community dynamics.

TRIAL REGISTRATION

The European Union Clinical Trials Register, EudraCT Number: 2013-003378-28 . Registered on 9 April 2014.

The Human Gut Microbiome: From Association to Modulation

Our understanding of the human gut microbiome continues to evolve at a rapid pace, but practical application of thisknowledge is still in its infancy. This review discusses the type of studies that will be essential for translating microbiome research into targeted modulations with dedicated benefits for the human host.

The North Sea goes viral: Occurrence and distribution of North Sea bacteriophages

Marine viruses are dominated by phages and have an enormous influence on microbial population dynamics, due to lysis and horizontal gene transfer. The aim of this study is to analyze the occurrence and diversity of phages in the North Sea, considering the virus-host interactions and biogeographic factors. The virus community of four sampling stations were described using virus metagenomics (viromes). The results show that the virus community was not evenly distributed throughout the North Sea. The dominant phage members were identified as unclassified phage group, followed by Caudovirales order. Myoviridae was the dominant phage family in the North Sea, which occurrence decreased from the coast to the open sea. In contrast, the occurrence of Podoviridae increased and the occurrence of Siphoviridae was low throughout the North Sea. The occurrence of other groups such as Phycodnaviridae decreased from the coast to the open sea. The coastal virus community was genetically more diverse than the open sea community. The influence of riverine inflow and currents, for instance the English Channel flow affects the genetic virus diversity with the community carrying genes from a variety of metabolic pathways and other functions. The present study offers the first insights in the virus community in the North Sea using viromes and shows the variation in virus diversity and the genetic information moved from coastal to open sea areas.

Does the microbiome and virome contribute to myalgic encephalomyelitis/chronic fatigue syndrome?

Myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) (ME/CFS) is a disabling and debilitating disease of unknown aetiology. It is a heterogeneous disease characterized by various inflammatory, immune, viral, neurological and endocrine symptoms. Several microbiome studies have described alterations in the bacterial component of the microbiome (dysbiosis) consistent with a possible role in disease development. However, in focusing on the bacterial components of the microbiome, these studies have neglected the viral constituent known as the virome. Viruses, particularly those infecting bacteria (bacteriophages), have the potential to alter the function and structure of the microbiome via gene transfer and host lysis. Viral-induced microbiome changes can directly and indirectly influence host health and disease. The contribution of viruses towards disease pathogenesis is therefore an important area for research in ME/CFS. Recent advancements in sequencing technology and bioinformatics now allow more comprehensive and inclusive investigations of human microbiomes. However, as the number of microbiome studies increases, the need for greater consistency in study design and analysis also increases. Comparisons between different ME/CFS microbiome studies are difficult because of differences in patient selection and diagnosis criteria, sample processing, genome sequencing and downstream bioinformatics analysis. It is therefore important that microbiome studies adopt robust, reproducible and consistent study design to enable more reliable and valid comparisons and conclusions to be made between studies. This article provides a comprehensive review of the current evidence supporting microbiome alterations in ME/CFS patients. Additionally, the pitfalls and challenges associated with microbiome studies are discussed.

Targeted Genome Editing of Virulent Phages Using CRISPR-Cas9

This protocol describes a straightforward method to generate specific mutations in the genome of strictly lytic phages. Briefly, a targeting CRISPR-Cas9 system and a repair template suited for homologous recombination are provided inside a bacterial host, here the Gram-positive model Lactococcus lactis MG1363. The CRISPR-Cas9 system is programmed to cleave a specific region present on the genome of the invading phage, but absent from the recombination template. The system either triggers the recombination event or exerts the selective pressure required to isolate recombinant phages. With this methodology, we generated multiple gene knockouts, a point mutation and an insertion in the genome of the virulent lactococcal phage p2. Considering the broad host range of the plasmids used in this protocol, the latter can be extrapolated to other phage-host pairs.

The 'Neglected' Soil Virome - Potential Role and Impact

Bacteriophages are among the most abundant and diverse biological units in the biosphere. They have contributed to our understanding of the central dogma of biology and have been instrumental in the evolutionary success of bacterial pathogens. In contrast to our current understanding of marine viral communities, the soil virome and its function in terrestrial ecosystems has remained relatively understudied. Here, we examine, in a comparative fashion, the knowledge gathered from studies performed in soil versus marine settings. We address the information with respect to the abundance, diversity, ecological significance, and effects of, in particular, bacteriophages on their host's evolutionary trajectories. We also identify the main challenges that soil virology faces and the studies that are required to accompany the current developments in marine settings.

Extraction and Purification of Viruses from Fecal Samples for Metagenome and Morphology Analyses

The human enteric virome consists of endogenous retro elements and viruses that infect the host and members of the gut microbiome (GM). Mounting evidence suggests that the gut virome plays a central role in maintaining homeostasis and via the GM influences immunology of the host. To thoroughly characterize the gut virome, it is often very useful to first separate and concentrate extracellular viral-like particles (eVLPs) enabling an integrative characterization of them. Here, we describe a detailed protocol for extraction and concentration of the viral fraction from fecal samples based on a polyethylene glycol precipitation (PEG) approach. These procedures maximize the yields of eVLPs (and their DNA) with high purity well suited for down-stream analysis such as quantification and morphological assessment, determination of phage-host pairs as well as virome sequencing.

Discovery of an expansive bacteriophage family that includes the most abundant viruses from the human gut

Metagenomic sequence analysis is rapidly becoming the primary source of virus discovery ^1–3. A substantial majority of the currently available virus genomes comes from metagenomics, and some of these represent extremely abundant viruses even if never grown in the laboratory. A particularly striking case of a virus discovered via metagenomics is crAssphage, which is by far the most abundant human-associated virus known, comprising up to 90% of the sequences in the gut virome ⁴. Over 80% of the predicted proteins encoded in the approximately 100 kilobase crAssphage genome showed no significant similarity to available protein sequences, precluding classification of this virus and hampering further study. Here we combine comprehensive search of genomic and metagenomic databases with sensitive methods for protein sequence analysis to identify an expansive, diverse group of bacteriophages related to crAssphage and predict the functions of the majority of phage proteins, in particular, those that comprise the structural, replication and expression modules. Most if not all of the crAss-like phages appear to be associated with diverse bacteria from the phylum Bacteroidetes, which includes some of the most abundant bacteria in the human gut microbiome and are also common in various other habitats. These findings provide for experimental characterization of the most abundant but poorly understood members of the human-associated virome.

Phage hunters: Computational strategies for finding phages in large-scale 'omics datasets

A plethora of tools exist for identifying phage sequences in bacterial genomes, single cell amplified genomes, and host-associated and environmental metagenomes. Yet because the genetics of phages and their hosts are closely intertwined, distinguishing viral from bacterial signal remains an ongoing challenge. Further the size, quantity and fragmentary nature of modern 'omics datasets ushers in a new set of computational challenges. Here, we detail the promises and pitfalls of using currently available gene-centric or k-mer based tools for identifying prophage sequences in genomes and prophage and viral contigs in metagenomes. Each of these methods offers a unique piece of the puzzle to elucidating the intriguing signatures of phage-host coevolution.

Genome Engineering of Virulent Lactococcal Phages Using CRISPR-Cas9

Phages are biological entities found in every ecosystem. Although much has been learned about them in past decades, significant knowledge gaps remain. Manipulating virulent phage genomes is challenging. To date, no efficient gene-editing tools exist for engineering virulent lactococcal phages. Lactococcus lactis is a bacterium extensively used as a starter culture in various milk fermentation processes, and its phage sensitivity poses a constant risk to the cheese industry. The lactococcal phage p2 is one of the best-studied models for these virulent phages. Despite its importance, almost half of its genes have no functional assignment. CRISPR-Cas9 genome editing technology, which is derived from a natural prokaryotic defense mechanism, offers new strategies for phage research. Here, the well-known Streptococcus pyogenes CRISPR-Cas9 was used in a heterologous host to modify the genome of a strictly lytic phage. Implementation of our adapted CRISPR-Cas9 tool in the prototype phage-sensitive host L. lactis MG1363 allowed us to modify the genome of phage p2. A simple, reproducible technique to generate precise mutations that allow the study of lytic phage genes and their encoded proteins in vivo is described.

VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data

BACKGROUND

Identifying viral sequences in mixed metagenomes containing both viral and host contigs is a critical first step in analyzing the viral component of samples. Current tools for distinguishing prokaryotic virus and host contigs primarily use gene-based similarity approaches. Such approaches can significantly limit results especially for short contigs that have few predicted proteins or lack proteins with similarity to previously known viruses.

METHODS

We have developed VirFinder, the first k-mer frequency based, machine learning method for virus contig identification that entirely avoids gene-based similarity searches. VirFinder instead identifies viral sequences based on our empirical observation that viruses and hosts have discernibly different k-mer signatures. VirFinder's performance in correctly identifying viral sequences was tested by training its machine learning model on sequences from host and viral genomes sequenced before 1 January 2014 and evaluating on sequences obtained after 1 January 2014.

RESULTS

VirFinder had significantly better rates of identifying true viral contigs (true positive rates (TPRs)) than VirSorter, the current state-of-the-art gene-based virus classification tool, when evaluated with either contigs subsampled from complete genomes or assembled from a simulated human gut metagenome. For example, for contigs subsampled from complete genomes, VirFinder had 78-, 2.4-, and 1.8-fold higher TPRs than VirSorter for 1, 3, and 5 kb contigs, respectively, at the same false positive rates as VirSorter (0, 0.003, and 0.006, respectively), thus VirFinder works considerably better for small contigs than VirSorter. VirFinder furthermore identified several recently sequenced virus genomes (after 1 January 2014) that VirSorter did not and that have no nucleotide similarity to previously sequenced viruses, demonstrating VirFinder's potential advantage in identifying novel viral sequences. Application of VirFinder to a set of human gut metagenomes from healthy and liver cirrhosis patients reveals higher viral diversity in healthy individuals than cirrhosis patients. We also identified contig bins containing crAssphage-like contigs with higher abundance in healthy patients and a putative Veillonella genus prophage associated with cirrhosis patients.

CONCLUSIONS

This innovative k-mer based tool complements gene-based approaches and will significantly improve prokaryotic viral sequence identification, especially for metagenomic-based studies of viral ecology.

Metagenomic Approaches to Assess Bacteriophages in Various Environmental Niches

Bacteriophages are ubiquitous and numerous parasites of bacteria and play a critical evolutionary role in virtually every ecosystem, yet our understanding of the extent of the diversity and role of phages remains inadequate for many ecological niches, particularly in cases in which the host is unculturable. During the past 15 years, the emergence of the field of viral metagenomics has drastically enhanced our ability to analyse the so-called viral ‘dark matter’ of the biosphere. Here, we review the evolution of viral metagenomic methodologies, as well as providing an overview of some of the most significant applications and findings in this field of research.

Intriguing Interaction of Bacteriophage-Host Association: An Understanding in the Era of Omics

Innovations in next-generation sequencing technology have introduced new avenues in microbial studies through “omics” approaches. This technology has considerably augmented the knowledge of the microbial world without isolation prior to their identification. With an enormous volume of bacterial “omics” data, considerable attempts have been recently invested to improve an insight into virosphere. The interplay between bacteriophages and their host has created a significant influence on the biogeochemical cycles, microbial diversity, and bacterial population regulation. This review highlights various concepts such as genomics, transcriptomics, proteomics, and metabolomics to infer the phylogenetic affiliation and function of bacteriophages and their impact on diverse microbial communities. Omics technologies illuminate the role of bacteriophage in an environment, the influences of phage proteins on the bacterial host and provide information about the genes important for interaction with bacteria. These investigations will reveal some of bio-molecules and biomarkers of the novel phage which demand to be unveiled.

Virome Assembly and Annotation: A Surprise in the Namib Desert

Sequencing, assembly, and annotation of environmental virome samples is challenging. Methodological biases and differences in species abundance result in fragmentary read coverage; sequence reconstruction is further complicated by the mosaic nature of viral genomes. In this paper, we focus on biocomputational aspects of virome analysis, emphasizing latent pitfalls in sequence annotation. Using simulated viromes that mimic environmental data challenges we assessed the performance of five assemblers (CLC-Workbench, IDBA-UD, SPAdes, RayMeta, ABySS). Individual analyses of relevant scaffold length fractions revealed shortcomings of some programs in reconstruction of viral genomes with excessive read coverage (IDBA-UD, RayMeta), and in accurate assembly of scaffolds ≥50 kb (SPAdes, RayMeta, ABySS). The CLC-Workbench assembler performed best in terms of genome recovery (including highly covered genomes) and correct reconstruction of large scaffolds; and was used to assemble a virome from a copper rich site in the Namib Desert. We found that scaffold network analysis and cluster-specific read reassembly improved reconstruction of sequences with excessive read coverage, and that strict data filtering for non-viral sequences prior to downstream analyses was essential. In this study we describe novel viral genomes identified in the Namib Desert copper site virome. Taxonomic affiliations of diverse proteins in the dataset and phylogenetic analyses of circovirus-like proteins indicated links to the marine habitat. Considering additional evidence from this dataset we hypothesize that viruses may have been carried from the Atlantic Ocean into the Namib Desert by fog and wind, highlighting the impact of the extended environment on an investigated niche in metagenome studies.

Aquatic viral metagenomics: Lights and shadows

Viruses are the most abundant biological entities on Earth, exceeding bacteria in most of the ecosystems. Specially in oceans, viruses are thought to be the major planktonic predators shaping microorganism communities and controlling ocean biological capacity. Plankton lysis by viruses plays an important role in ocean nutrient and energy cycles. Viral metagenomics has emerged as a powerful tool to uncover viral diversity in aquatic ecosystems through the use of Next Generation Sequencing. However, many of the commonly used viral sample preparation steps have several important biases that must be considered to avoid a misinterpretation of the results. In addition to biases caused by the purification of virus particles, viral DNA/RNA amplification and the preparation of genomic libraries could also introduce biases, and a detailed knowledge about such protocols is required. In this review, the main steps in the viral metagenomic workflow are described paying special attention to the potential biases introduced by each one.