RaFAH: Host prediction for viruses of Bacteria and Archaea based on protein content

Novel phage infecting the Roseobacter CHUG lineage reveals a diverse and globally distributed phage family

Bacteriophages play an essential role in shaping the diversity and metabolism of bacterial communities. Marine Roseobacter group is an abundant heterotrophic bacterial group that is involved in many major element cycles, especially carbon and sulfur. Members of the Roseobacter CHUG (Clade Hidden and Underappreciated Globally) lineage are globally distributed and are activated in pelagic marine environments. In this study, we isolated and characterized a phage, CRP-810, that infects the CHUG strain FZCC0198. The genome of CRP-810 was dissimilar to those of other known phages. Additionally, 251 uncultured viral genomes (UViGs) closely related to CRP-810 were obtained from the uncultivated marine viral contig databases. Comparative genomic and phylogenetic analyses revealed that CRP-810 and these related UViGs exhibited conserved genome synteny, representing a new phage family with at least eight subgroups. Most of the CRP-810-type phages contain an integrase gene, and CRP-810 can be integrated into the host genome. Further analysis revealed that three CRP-810-type members were prophages found in the genomes of marine SAR11, Poseidonocella, and Sphingomonadaceae. Finally, viromic read-mapping analysis showed that CRP-810-type phages were globally distributed and displayed distinct biogeographic patterns related to temperature and latitude. Many members with a lower G + C content were mainly distributed in the trade station, whereas members with a higher G + C content were mainly distributed in polar and westerlies station, indicating that the niche differentiation of phages was subject to host adaptation. Collectively, these findings identify a novel phage family and expand our understanding of phylogenetic diversity, evolution, and biogeography of marine phages.

IMPORTANCE

The Roseobacter CHUG lineage, affiliated with the Pelagic Roseobacter Cluster (PRC), is widely distributed in the global oceans and is active in oligotrophic seawater. However, knowledge of the bacteriophages that infect CHUG members is limited. In this study, a CHUG phage, CRP-810, that infects the CHUG strain FZCC0198, was isolated and shown to have a novel genomic architecture. In addition, 251 uncultured viral genomes closely related to CRP-810 were recovered and included in the analyses. Phylogenomic analyses revealed that the CRP-810-type phages represent a new phage family containing at least eight genus-level subgroups. Members of this family were predicted to infect various marine bacteria. We also demonstrated that the CRP-810-type phages are widely distributed in global oceans and display distinct biogeographic patterns related to latitude. Collectively, this study provides important insights into the genomic organization, diversity, and ecology of a novel phage family that infect ecologically important bacteria in the global ocean.

Methanotrophic Methanoperedens archaea host diverse and interacting extrachromosomal elements

Methane emissions are mitigated by anaerobic methane-oxidizing archaea, including Methanoperedens. Some Methanoperedens host huge extrachromosomal genetic elements (ECEs) called Borgs that may modulate their activity, yet the broader diversity of Methanoperedens ECEs is understudied. Here we report small enigmatic linear ECEs, circular viruses and unclassified ECEs that are predicted to replicate within Methanoperedens. Linear ECEs have inverted terminal repeats, tandem repeats and coding patterns that are strongly reminiscent of Borgs, but they are only 52-145 kb in length. As they share proteins with Borgs and Methanoperedens, we refer to them as mini-Borgs. Mini-Borgs are genetically diverse and can be assigned to at least five family-level groups. We identify eight families of Methanoperedens viruses, some of which encode multi-haem cytochromes, and circular ECEs encoding transposon-associated TnpB genes with proximal population-heterogeneous CRISPR arrays. These ECEs exchange genetic information with each other and with Methanoperedens, probably impacting their archaeal host activity and evolution.

Tools and methodology to in silico phage discovery in freshwater environments

Freshwater availability is essential, and its maintenance has become an enormous challenge. Due to population growth and climate changes, freshwater sources are becoming scarce, imposing the need for strategies for its reuse. Currently, the constant discharge of waste into water bodies from human activities leads to the dissemination of pathogenic bacteria, negatively impacting water quality from the source to the infrastructure required for treatment, such as the accumulation of biofilms. Current water treatment methods cannot keep pace with bacterial evolution, which increasingly exhibits a profile of multidrug resistance to antibiotics. Furthermore, using more powerful disinfectants may affect the balance of aquatic ecosystems. Therefore, there is a need to explore sustainable ways to control the spreading of pathogenic bacteria. Bacteriophages can infect bacteria and archaea, hijacking their host machinery to favor their replication. They are widely abundant globally and provide a biological alternative to bacterial treatment with antibiotics. In contrast to common disinfectants and antibiotics, bacteriophages are highly specific, minimizing adverse effects on aquatic microbial communities and offering a lower cost-benefit ratio in production compared to antibiotics. However, due to the difficulty involving cultivating and identifying environmental bacteriophages, alternative approaches using NGS metagenomics in combination with some bioinformatic tools can help identify new bacteriophages that can be useful as an alternative treatment against resistant bacteria. In this review, we discuss advances in exploring the virome of freshwater, as well as current applications of bacteriophages in freshwater treatment, along with current challenges and future perspectives.

Decoding huge phage diversity: a taxonomic classification of Lak megaphages

High-throughput sequencing for uncultivated viruses has accelerated the understanding of global viral diversity and uncovered viral genomes substantially larger than any that have so far been cultured. Notably, the Lak phages are an enigmatic group of viruses that present some of the largest known phage genomes identified in human and animal microbiomes, and are dissimilar to any cultivated viruses. Despite the wealth of viral diversity that exists within sequencing datasets, uncultivated viruses have rarely been used for taxonomic classification. We investigated the evolutionary relationships of 23 Lak phages and propose a taxonomy for their classification. Predicted protein analysis revealed the Lak phages formed a deeply branching monophyletic clade within the class Caudoviricetes which contained no other phage genomes. One of the interesting features of this clade is that all current members are characterised by an alternative genetic code. We propose the Lak phages belong to a new order, the 'Grandevirales'. Protein and nucleotide-based analyses support the creation of two families, three sub-families, and four genera within the order 'Grandevirales'. We anticipate that the proposed taxonomy of Lak megaphages will simplify the future classification of related viral genomes as they are uncovered. Continued efforts to classify divergent viruses are crucial to aid common analyses of viral genomes and metagenomes.

Correlation between the gut microbiome and neurodegenerative diseases: a review of metagenomics evidence

A growing body of evidence suggests that the gut microbiota contributes to the development of neurodegenerative diseases via the microbiota-gut-brain axis. As a contributing factor, microbiota dysbiosis always occurs in pathological changes of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. High-throughput sequencing technology has helped to reveal that the bidirectional communication between the central nervous system and the enteric nervous system is facilitated by the microbiota's diverse microorganisms, and for both neuroimmune and neuroendocrine systems. Here, we summarize the bioinformatics analysis and wet-biology validation for the gut metagenomics in neurodegenerative diseases, with an emphasis on multi-omics studies and the gut virome. The pathogen-associated signaling biomarkers for identifying brain disorders and potential therapeutic targets are also elucidated. Finally, we discuss the role of diet, prebiotics, probiotics, postbiotics and exercise interventions in remodeling the microbiome and reducing the symptoms of neurodegenerative diseases.

Advances in phage-host interaction prediction: in silico method enhances the development of phage therapies

Phages can specifically recognize and kill bacteria, which lead to important application value of bacteriophage in bacterial identification and typing, livestock aquaculture and treatment of human bacterial infection. Considering the variety of human-infected bacteria and the continuous discovery of numerous pathogenic bacteria, screening suitable therapeutic phages that are capable of infecting pathogens from massive phage databases has been a principal step in phage therapy design. Experimental methods to identify phage-host interaction (PHI) are time-consuming and expensive; high-throughput computational method to predict PHI is therefore a potential substitute. Here, we systemically review bioinformatic methods for predicting PHI, introduce reference databases and in silico models applied in these methods and highlight the strengths and challenges of current tools. Finally, we discuss the application scope and future research direction of computational prediction methods, which contribute to the performance improvement of prediction models and the development of personalized phage therapy.

Biological and bioinformatic tools for the discovery of unknown phage-host combinations

The field of microbial ecology has been transformed by metagenomics in recent decades and has culminated in vast datasets that facilitate the bioinformatic dissection of complex microbial communities. Recently, attention has turned from defining the microbiota composition to the interactions and relationships that occur between members of the microbiota. Within complex microbiota, the identification of bacteriophage-host combinations has been a major challenge. Recent developments in artificial intelligence tools to predict protein structure and function as well as the relationships between bacteria and their infecting bacteriophages allow a strategic approach to identifying and validating phage-host relationships. However, biological validation of these predictions remains essential and will serve to improve the existing predictive tools. In this review, I provide an overview of the most recent developments in both bioinformatic and experimental approaches to predicting and experimentally validating unknown phage-host combinations.

Hiding in plain sight: The discovery of complete genomes of 11 hypothetical spindle-shaped viruses that putatively infect mesophilic ammonia-oxidizing archaea

The genome of a putative Nitrosopumilaceae virus with a hypothetical spindle-shaped particle morphology was identified in the Yangshan Harbour metavirome from the East China Sea through protein similarity comparison and structure analysis. This discovery was accompanied by a set of 10 geographically dispersed close relatives found in the environmental virus datasets from typical locations of ammonia-oxidizing archaeon distribution. Its host prediction was supported by iPHoP prediction and protein sequence similarity. The structure of the predicted major capsid protein, together with the overall N-glycosylation site, the transmembrane helices prediction, the hydrophilicity profile, and the docking simulation of the major capsid proteins, indicate that these viruses resemble spindle-shaped viruses. It suggests a similarly assembled structure and, consequently, a possibly spindle-shaped morphology of these newly discovered archaeal viruses.

Ultraconserved bacteriophage genome sequence identified in 1300-year-old human palaeofaeces

Bacteriophages are widely recognised as rapidly evolving biological entities. However, knowledge about ancient bacteriophages is limited. Here, we analyse DNA sequence datasets previously generated from ancient palaeofaeces and human gut-content samples, and identify an ancient phage genome nearly identical to present-day Mushuvirus mushu, a virus that infects gut commensal bacteria. The DNA damage patterns of the genome are consistent with its ancient origin and, despite 1300 years of evolution, the ancient Mushuvirus genome shares 97.7% nucleotide identity with its modern counterpart, indicating a long-term relationship between the prophage and its host. In addition, we reconstruct and authenticate 297 other phage genomes from the last 5300 years, including those belonging to unknown families. Our findings demonstrate the feasibility of reconstructing ancient phage genome sequences, thus expanding the known virosphere and offering insights into phage-bacteria interactions spanning several millennia.

IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning

BACKGROUND

The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses.

FINDINGS

We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals.

CONCLUSIONS

IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.

Comparative Analyses of Bacteriophage Genomes

Bacterial viruses (bacteriophages or phages) are the most abundant and diverse biological entities on Earth. There is a renewed worldwide interest in phage-centered research motivated by their enormous potential as antimicrobials to cope with multidrug-resistant pathogens. An ever-growing number of complete phage genomes are becoming available, derived either from newly isolated phages (cultivated phages) or recovered from metagenomic sequencing data (uncultivated phages). Robust comparative analysis is crucial for a comprehensive understanding of genotypic variations of phages and their related evolutionary processes, and to investigate the interaction mechanisms between phages and their hosts. In this chapter, we present a protocol for phage comparative genomics employing tools selected out of the many currently available, focusing on complete genomes of phages classified in the class Caudoviricetes. This protocol provides accurate identification of similarities, differences, and patterns among new and previously known complete phage genomes as well as phage clustering and taxonomic classification.

Bacteriophages: Vectors of or weapons against the transmission of antibiotic resistance genes in hospital wastewater systems?

Antimicrobial resistance poses a serious threat to human health and is responsible for the death of millions of people annually. Hospital wastewater is an important hotspot for antibiotic-resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). However, little is known about the relationship between phages and ARGs in hospital wastewater systems (HWS). In the present study, the viral diversity of 12 HWSs using data from public metagenomic databases was investigated. Viruses were widely found in both the influent and effluent of each HWS. A total of 45 unique ARGs were carried by 85 viral contigs, which accounted for only 0.14% of the total viral populations, implying that ARGs were not commonly present in phages. Three efflux pump genes were identified as shared between phages and bacterial genomes. However, the predominant types of ARGs in HWS such as aminoglycoside- and beta-lactam-resistance genes were rarely found in phages. Based on CRISPR spacer and tRNA matches, interactions between 171 viral contigs and 60 antibiotic-resistant genomes were predicted, including interactions involving phages and vancomycin-resistant Enterococcus_B faecium or beta-lactam-resistant Klebsiella pneumoniae. More than half (56.1%) of these viral contigs indicated lytic and none of them carried ARGs. As the vOTUs in this study had few ARGs and were primarily lytic, HWS may be a valuable source for phage discovery. Future studies will be able to experimentally validate these sequence-based results to confirm the suitability of HWS phages for pathogen control measures in wastewater.

Exploring the Archaeal Virosphere by Metagenomics

During the past decade, environmental research has demonstrated that archaea are abundant and widespread in nature and play important ecological roles at a global scale. Currently, however, the majority of archaeal lineages cannot be cultivated under laboratory conditions and are known exclusively or nearly exclusively through metagenomics. A similar trend extends to the archaeal virosphere, where isolated representatives are available for a handful of model archaeal virus-host systems. Viral metagenomics provides an alternative way to circumvent the limitations of culture-based virus discovery and offers insight into the diversity, distribution, and environmental impact of uncultured archaeal viruses. Presently, metagenomics approaches have been successfully applied to explore the viromes associated with various lineages of extremophilic and mesophilic archaea, including Asgard archaea (Asgardarchaeota), ANME-1 archaea (Methanophagales), thaumarchaea (Nitrososphaeria), altiarchaea (Altiarchaeota), and marine group II archaea (Poseidoniales). Here, we provide an overview of methods widely used in archaeal virus metagenomics, covering metavirome preparation, genome annotation, phylogenetic and phylogenomic analyses, and archaeal host assignment. We hope that this summary will contribute to further exploration and characterization of the enigmatic archaeal virome lurking in diverse environments.

Viruses under the Antarctic Ice Shelf are active and potentially involved in global nutrient cycles

Viruses play an important role in the marine ecosystem. However, our comprehension of viruses inhabiting the dark ocean, and in particular, under the Antarctic Ice Shelves, remains limited. Here, we mine single-cell genomic, transcriptomic, and metagenomic data to uncover the viral diversity, biogeography, activity, and their role as metabolic facilitators of microbes beneath the Ross Ice Shelf. This is the largest Antarctic ice shelf with a major impact on global carbon cycle. The viral community found in the cavity under the ice shelf mainly comprises endemic viruses adapted to polar and mesopelagic environments. The low abundance of genes related to lysogenic lifestyle (<3%) does not support a predominance of the Piggyback-the-Winner hypothesis, consistent with a low-productivity habitat. Our results indicate a viral community actively infecting key ammonium and sulfur-oxidizing chemolithoautotrophs (e.g. Nitrosopumilus spp, Thioglobus spp.), supporting a "kill-the-winner" dynamic. Based on genome analysis, these viruses carry specific auxiliary metabolic genes potentially involved in nitrogen, sulfur, and phosphorus acquisition. Altogether, the viruses under Antarctic ice shelves are putatively involved in programming the metabolism of ecologically relevant microbes that maintain primary production in these chemosynthetically-driven ecosystems, which have a major role in global nutrient cycles.

Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy

Bacteriophages, or phages, are viruses that infect bacteria shaping microbial communities and ecosystems. They have gained attention as potential agents against antibiotic resistance. In phage therapy, lytic phages are preferred for their bacteria killing ability, while temperate phages, which can transfer antibiotic resistance or toxin genes, are avoided. Selection relies on plaque morphology and genome sequencing. This review outlines annotating genomes, identifying critical genomic features, and assigning functional labels to protein-coding sequences. These annotations prevent the transfer of unwanted genes, such as antimicrobial resistance or toxin genes, during phage therapy. Additionally, it covers International Committee on Taxonomy of Viruses (ICTV)-an established phage nomenclature system for simplified classification and communication. Accurate phage genome annotation and nomenclature provide insights into phage-host interactions, replication strategies, and evolution, accelerating our understanding of the diversity and evolution of phages and facilitating the development of phage-based therapies.

Viruses in deep-sea cold seep sediments harbor diverse survival mechanisms and remain genetically conserved within species

Deep sea cold seep sediments have been discovered to harbor novel, abundant, and diverse bacterial and archaeal viruses. However, little is known about viral genetic features and evolutionary patterns in these environments. Here, we examined the evolutionary ecology of viruses across active and extinct seep stages in the area of Haima cold seeps in the South China Sea. A total of 338 viral operational taxonomic units are identified and linked to 36 bacterial and archaeal phyla. The dynamics of host-virus interactions are informed by diverse antiviral defense systems across 43 families found in 487 microbial genomes. Cold seep viruses are predicted to harbor diverse adaptive strategies to persist in this environment, including counter-defense systems, auxiliary metabolic genes, reverse transcriptases, and alternative genetic code assignments. Extremely low nucleotide diversity is observed in cold seep viral populations, being influenced by factors including microbial host, sediment depth, and cold seep stage. Most cold seep viral genes are under strong purifying selection with trajectories that differ depending on whether cold seeps are active or extinct. This work sheds light on the understanding of environmental adaptation mechanisms and evolutionary patterns of viruses in the sub-seafloor biosphere.

Revisiting evolutionary trajectories and the organization of the Pleolipoviridae family

Archaeal pleomorphic viruses belonging to the Pleolipoviridae family represent an enigmatic group as they exhibit unique genomic features and are thought to have evolved through recombination with different archaeal plasmids. However, most of our understanding of the diversity and evolutionary trajectories of this clade comes from a handful of isolated representatives. Here we present 164 new genomes of pleolipoviruses obtained from metagenomic data of Australian hypersaline lakes and publicly available metagenomic data. We perform a comprehensive analysis on the diversity and evolutionary relationships of the newly discovered viruses and previously described pleolipoviruses. We propose to classify the viruses into five genera within the Pleolipoviridae family, with one new genus represented only by virus genomes retrieved in this study. Our data support the current hypothesis that pleolipoviruses reshaped their genomes through recombining with multiple different groups of plasmids, which is reflected in the diversity of their predicted replication strategies. We show that the proposed genus Epsilonpleolipovirus has evolutionary ties to pRN1-like plasmids from Sulfolobus, suggesting that this group could be infecting other archaeal phyla. Interestingly, we observed that the genome size of pleolipoviruses is correlated to the presence or absence of an integrase. Analyses of the host range revealed that all but one virus exhibit an extremely narrow range, and we show that the predicted tertiary structure of the spike protein is strongly associated with the host family, suggesting a specific adaptation to the host S-layer glycoprotein organization.

A systematic analysis of marine lysogens and proviruses

Viruses are ubiquitous in the oceans, exhibiting high abundance and diversity. Here, we systematically analyze existing genomic sequences of marine prokaryotes to compile a Marine Prokaryotic Genome Dataset (MPGD, consisting of over 12,000 bacterial and archaeal genomes) and a Marine Temperate Viral Genome Dataset (MTVGD). At least 40% of the MPGD genomes contain one or more proviral sequences, indicating that they are lysogens. The MTVGD includes over 12,900 viral contigs or putative proviruses, clustered into 10,897 viral genera. We show that lysogens and proviruses are abundant in marine ecosystems, particularly in the deep sea, and marine lysogens differ from non-lysogens in multiple genomic features and growth properties. We reveal several virus-host interaction networks of potential ecological relevance, and identify proviruses that appear to be able to infect (or to be transferred between) different bacterial classes and phyla. Auxiliary metabolic genes in the MTVGD are enriched in functions related to carbohydrate metabolism. Finally, we experimentally demonstrate the impact of a prophage on the transcriptome of a representative marine Shewanella bacterium. Our work contributes to a better understanding of the ecology of marine prokaryotes and their viruses.

Zero-shot-capable identification of phage-host relationships with whole-genome sequence representation by contrastive learning

Accurately identifying phage-host relationships from their genome sequences is still challenging, especially for those phages and hosts with less homologous sequences. In this work, focusing on identifying the phage-host relationships at the species and genus level, we propose a contrastive learning based approach to learn whole-genome sequence embeddings that can take account of phage-host interactions (PHIs). Contrastive learning is used to make phages infecting the same hosts close to each other in the new representation space. Specifically, we rephrase whole-genome sequences with frequency chaos game representation (FCGR) and learn latent embeddings that 'encapsulate' phages and host relationships through contrastive learning. The contrastive learning method works well on the imbalanced dataset. Based on the learned embeddings, a proposed pipeline named CL4PHI can predict known hosts and unseen hosts in training. We compare our method with two recently proposed state-of-the-art learning-based methods on their benchmark datasets. The experiment results demonstrate that the proposed method using contrastive learning improves the prediction accuracy on known hosts and demonstrates a zero-shot prediction capability on unseen hosts. In terms of potential applications, the rapid pace of genome sequencing across different species has resulted in a vast amount of whole-genome sequencing data that require efficient computational methods for identifying phage-host interactions. The proposed approach is expected to address this need by efficiently processing whole-genome sequences of phages and prokaryotic hosts and capturing features related to phage-host relationships for genome sequence representation. This approach can be used to accelerate the discovery of phage-host interactions and aid in the development of phage-based therapies for infectious diseases.

Genomic diversity and biogeographic distributions of a novel lineage of bacteriophages that infect marine OM43 bacteria

The marine methylotrophic OM43 clade is considered an important bacterial group in coastal microbial communities. OM43 bacteria, which are closely related to phytoplankton blooms, have small cell sizes and streamlined genomes. Bacteriophages profoundly shape the evolutionary trajectories, population dynamics, and physiology of microbes. The prevalence and diversity of several phages that infect OM43 bacteria have been reported. In this study, we isolated and sequenced two novel OM43 phages, MEP401 and MEP402. These phages share 90% of their open reading frames (ORFs) and are distinct from other known phage isolates. Furthermore, a total of 99 metagenomic viral genomes (MVGs) closely related to MEP401 and MEP402 were identified. Phylogenomic analyses suggest that MEP401, MEP402, and these identified MVGs belong to a novel subfamily in the family Zobellviridae and that they can be separated into two groups. Group I MVGs show conserved whole-genome synteny with MEP401, while group II MVGs possess the MEP401-type DNA replication module and a distinct type of morphogenesis and packaging module, suggesting that genomic recombination occurred between phages. Most members in these two groups were predicted to infect OM43 bacteria. Metagenomic read-mapping analysis revealed that the phages in these two groups are globally ubiquitous and display distinct biogeographic distributions, with some phages being predominant in cold regions, some exclusively detected in estuarine stations, and others displaying wider distributions. This study expands our knowledge of the diversity and ecology of a novel phage lineage that infects OM43 bacteria by describing their genomic diversity and global distribution patterns. IMPORTANCE OM43 phages that infect marine OM43 bacteria are important for host mortality, community structure, and physiological functions. In this study, two OM43 phages were isolated and characterized. Metagenomic viral genome (MVG) retrieval using these two OM43 phages as baits led to the identification of two phage groups of a new subfamily in the family Zobellviridae. We found that group I MVGs share similar genomic content and arrangement with MEP401 and MEP402, whereas group II MVGs only possess the MEP401-type DNA replication module. Metagenomic mapping analysis suggests that members in these two groups are globally ubiquitous with distinct distribution patterns. This study provides important insights into the genomic diversity and biogeography of the OM43 phages in the global ocean.

Protein embeddings improve phage-host interaction prediction

With the growing interest in using phages to combat antimicrobial resistance, computational methods for predicting phage-host interactions have been explored to help shortlist candidate phages. Most existing models consider entire proteomes and rely on manual feature engineering, which poses difficulty in selecting the most informative sequence properties to serve as input to the model. In this paper, we framed phage-host interaction prediction as a multiclass classification problem that takes as input the embeddings of a phage's receptor-binding proteins, which are known to be the key machinery for host recognition, and predicts the host genus. We explored different protein language models to automatically encode these protein sequences into dense embeddings without the need for additional alignment or structural information. We show that the use of embeddings of receptor-binding proteins presents improvements over handcrafted genomic and protein sequence features. The highest performance was obtained using the transformer-based protein language model ProtT5, resulting in a 3% to 4% increase in weighted F1 and recall scores across different prediction confidence thresholds, compared to using selected handcrafted sequence features.

iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria

The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived sequences lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e., for a number of viruses they yield erroneous predictions or no prediction at all. Here, we describe iPHoP, a two-step framework that integrates multiple methods to reliably predict host taxonomy at the genus rank for a broad range of viruses infecting bacteria and archaea, while retaining a low false discovery rate. Based on a large dataset of metagenome-derived virus genomes from the IMG/VR database, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated viruses.

Genetic determinants of host tropism in Klebsiella phages

Bacteriophages play key roles in bacterial ecology and evolution and are potential antimicrobials. However, the determinants of phage-host specificity remain elusive. Here, we isolate 46 phages to challenge 138 representative clinical isolates of Klebsiella pneumoniae, a widespread opportunistic pathogen. Spot tests show a narrow host range for most phages, with <2% of 6,319 phage-host combinations tested yielding detectable interactions. Bacterial capsule diversity is the main factor restricting phage host range. Consequently, phage-encoded depolymerases are key determinants of host tropism, and depolymerase sequence types are associated with the ability to infect specific capsular types across phage families. However, all phages with a broader host range found do not encode canonical depolymerases, suggesting alternative modes of entry. These findings expand our knowledge of the complex interactions between bacteria and their viruses and point out the feasibility of predicting the first steps of phage infection using bacterial and phage genome sequences.

Spatiotemporal Dynamics of Coastal Viral Community Structure and Potential Biogeochemical Roles Affected by an Ulva prolifera Green Tide

The world's largest macroalgal green tide, caused by Ulva prolifera, has resulted in serious consequences for coastal waters of the Yellow Sea, China. Although viruses are considered to be one of the key factors in controlling microalgal bloom demise, understanding of the relationship between viral communities and the macroalgal green tide is still poor. Here, a Qingdao coastal virome (QDCV) time-series data set was constructed based on the metagenomic analysis of 17 DNA viromes along three coastal stations of the Yellow Sea, covering different stages of the green tide from Julian days 165 to 271. A total of 40,076 viral contigs were detected and clustered into 28,058 viral operational taxonomic units (vOTUs). About 84% of the vOTUs could not be classified, and 62% separated from vOTUs in other ecosystems. Green tides significantly influenced the spatiotemporal dynamics of the viral community structure, diversity, and potential functions. For the classified vOTUs, the relative abundance of Pelagibacter phages declined with the arrival of the bloom and rebounded after the bloom, while Synechococcus and Roseobacter phages increased, although with a time lag from the peak of their hosts. More than 80% of the vOTUs reached peaks in abundance at different specific stages, and the viral peaks were correlated with specific hosts at different stages of the green tide. Most of the viral auxiliary metabolic genes (AMGs) were associated with carbon and sulfur metabolism and showed spatiotemporal dynamics relating to the degradation of the large amount of organic matter released by the green tide. IMPORTANCE To the best of our knowledge, this study is the first to investigate the responses of viruses to the world's largest macroalgal green tide. It revealed the spatiotemporal dynamics of the unique viral assemblages and auxiliary metabolic genes (AMGs) following the variation and degradation of Ulva prolifera. These findings demonstrate a tight coupling between viral assemblages, and prokaryotic and eukaryotic abundances were influenced by the green tide.

Advances in the field of phage-based therapy with special emphasis on computational resources

In the current era, one of the major challenges is to manage the treatment of drug/antibiotic-resistant strains of bacteria. Phage therapy, a century-old technique, may serve as an alternative to antibiotics in treating bacterial infections caused by drug-resistant strains of bacteria. In this review, a systematic attempt has been made to summarize phage-based therapy in depth. This review has been divided into the following two sections: general information and computer-aided phage therapy (CAPT). In the case of general information, we cover the history of phage therapy, the mechanism of action, the status of phage-based products (approved and clinical trials) and the challenges. This review emphasizes CAPT, where we have covered primary phage-associated resources, phage prediction methods and pipelines. This review covers a wide range of databases and resources, including viral genomes and proteins, phage receptors, host genomes of phages, phage-host interactions and lytic proteins. In the post-genomic era, identifying the most suitable phage for lysing a drug-resistant strain of bacterium is crucial for developing alternate treatments for drug-resistant bacteria and this remains a challenging problem. Thus, we compile all phage-associated prediction methods that include the prediction of phages for a bacterial strain, the host for a phage and the identification of interacting phage-host pairs. Most of these methods have been developed using machine learning and deep learning techniques. This review also discussed recent advances in the field of CAPT, where we briefly describe computational tools available for predicting phage virions, the life cycle of phages and prophage identification. Finally, we describe phage-based therapy's advantages, challenges and opportunities.

Bioinformatics approaches for unveiling virus-host interactions

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

Genomic analysis and characterization of phages infecting the marine Roseobacter CHAB-I-5 lineage reveal a globally distributed and abundant phage genus

Marine phages play an important role in marine biogeochemical cycles by regulating the death, physiological metabolism, and evolutionary trajectory of bacteria. The Roseobacter group is an abundant and important heterotrophic bacterial group in the ocean, and plays an important role in carbon, nitrogen, sulfur and phosphorus cycling. The CHAB-I-5 lineage is one of the most dominant Roseobacter lineages, but remains largely uncultured. Phages infecting CHAB-I-5 bacteria have not yet been investigated due to the lack of culturable CHAB-I-5 strains. In this study, we isolated and sequenced two new phages (CRP-901 and CRP-902) infecting the CHAB-I-5 strain FZCC0083. We applied metagenomic data mining, comparative genomics, phylogenetic analysis, and metagenomic read-mapping to investigate the diversity, evolution, taxonomy, and biogeography of the phage group represented by the two phages. The two phages are highly similar, with an average nucleotide identity of 89.17%, and sharing 77% of their open reading frames. We identified several genes involved in DNA replication and metabolism, virion structure, DNA packing, and host lysis from their genomes. Metagenomic mining identified 24 metagenomic viral genomes closely related to CRP-901 and CRP-902. Genomic comparison and phylogenetic analysis demonstrated that these phages are distinct from other known viruses, representing a novel genus-level phage group (CRP-901-type). The CRP-901-type phages do not contain DNA primase and DNA polymerase genes, but possess a novel bifunctional DNA primase-polymerase gene with both primase and polymerase activities. Read-mapping analysis showed that the CRP-901-type phages are widespread across the world's oceans and are most abundant in estuarine and polar waters. Their abundance is generally higher than other known roseophages and even higher than most pelagiphages in the polar region. In summary, this study has greatly expanded our understanding of the genetic diversity, evolution, and distribution of roseophages. Our analysis suggests that the CRP-901-type phage is an important and novel marine phage group that plays important roles in the physiology and ecology of roseobacters.

Phage-Host Prediction Using a Computational Tool Coupled with 16S rRNA Gene Amplicon Sequencing

Metagenomics studies have revealed tremendous viral diversity in aquatic environments. Yet, while the genomic data they have provided is extensive, it is unannotated. For example, most phage sequences lack accurate information about their bacterial host, which prevents reliable phage identification and the investigation of phage-host interactions. This study aimed to take this knowledge further, using a viral metagenomic framework to decipher the composition and diversity of phage communities and to predict their bacterial hosts. To this end, we used water and sediment samples collected from seven sites with varying contamination levels in the Ebrié Lagoon in Abidjan, Ivory Coast. The bacterial communities were characterized using the 16S rRNA metabarcoding approach, and a framework was developed to investigate the virome datasets that: (1) identified phage contigs with VirSorter and VIBRANT; (2) classified these contigs with MetaPhinder using the phage database (taxonomic annotation); and (3) predicted the phages' bacterial hosts with a machine learning-based tool: the Prokaryotic Virus-Host Predictor. The findings showed that the taxonomic profiles of phages and bacteria were specific to sediment or water samples. Phage sequences assigned to the Microviridae family were widespread in sediment samples, whereas phage sequences assigned to the Siphoviridae, Myoviridae and Podoviridae families were predominant in water samples. In terms of bacterial communities, the phyla Latescibacteria, Zixibacteria, Bacteroidetes, Acidobacteria, Calditrichaeota, Gemmatimonadetes, Cyanobacteria and Patescibacteria were most widespread in sediment samples, while the phyla Epsilonbacteraeota, Tenericutes, Margulisbacteria, Proteobacteria, Actinobacteria, Planctomycetes and Marinimicrobia were most prevalent in water samples. Significantly, the relative abundance of bacterial communities (at major phylum level) estimated by 16S rRNA metabarcoding and phage-host prediction were significantly similar. These results demonstrate the reliability of this novel approach for predicting the bacterial hosts of phages from shotgun metagenomic sequencing data.

Phage Therapy for Crops: Concepts, Experimental and Bioinformatics Approaches to Direct Its Application

Phage therapy consists of applying bacteriophages, whose natural function is to kill specific bacteria. Bacteriophages are safe, evolve together with their host, and are environmentally friendly. At present, the indiscriminate use of antibiotics and salt minerals (Zn²⁺ or Cu²⁺) has caused the emergence of resistant strains that infect crops, causing difficulties and loss of food production. Phage therapy is an alternative that has shown positive results and can improve the treatments available for agriculture. However, the success of phage therapy depends on finding effective bacteriophages. This review focused on describing the potential, up to now, of applying phage therapy as an alternative treatment against bacterial diseases, with sustainable improvement in food production. We described the current isolation techniques, characterization, detection, and selection of lytic phages, highlighting the importance of complementary studies using genome analysis of the phage and its host. Finally, among these studies, we concentrated on the most relevant bacteriophages used for biocontrol of Pseudomonas spp., Xanthomonas spp., Pectobacterium spp., Ralstonia spp., Burkholderia spp., Dickeya spp., Clavibacter michiganensis, and Agrobacterium tumefaciens as agents that cause damage to crops, and affect food production around the world.

Impact of HIV infection and integrase strand transfer inhibitors-based treatment on the gut virome

Viruses are the most abundant components of the human gut microbiome with a significant impact on health and disease. The effects of human immunodeficiency virus (HIV) infection on gut virome has been scarcely analysed. Several studies suggested that integrase strand transfers inhibitors (INSTIs) are associated with a healthier gut. Thus, the objective of this work was to evaluate the effects of HIV infection and INSTIs on gut virome composition. 26 non-HIV-infected volunteers, 15 naive HIV-infected patients and 15 INSTIs-treated HIV-infected patients were recruited and their gut virome composition was analysed using shotgun sequencing. Bacteriophages were the most abundant and diverse viruses present in gut. HIV infection was accompanied by a decrease in phage richness which was reverted after INSTIs-based treatment. β-diversity of phages revealed that samples from HIV-infected patients clustered separately from those belonging to the control group. Differential abundant analysis showed an increase in phages belonging to Caudoviricetes class in the naive group and a decrease of Malgrandaviricetes class phages in the INSTIs-treated group compared to the control group. Besides, it was observed that INSTIs-based treatment was not able to reverse the increase of lysogenic phages associated with HIV infection or to modify the decrease observed on the relative abundance of Proteobacteria-infecting phages. Our study describes for the first time the impact of HIV and INSTIs on gut virome and demonstrates that INSTIs-based treatments are able to partially restore gut dysbiosis at the viral level, which opens several opportunities for new studies focused on microbiota-based therapies.

vHULK, a New Tool for Bacteriophage Host Prediction Based on Annotated Genomic Features and Neural Networks

Background

The experimental determination of a bacteriophage host is a laborious procedure. Thus, there is a pressing need for reliable computational predictions of bacteriophage hosts.

Materials and Methods

We developed the program vHULK for phage host prediction based on 9504 phage genome features, which consider alignment significance scores between predicted proteins and a curated database of viral protein families. The features were fed to a neural network, and two models were trained to predict 77 host genera and 118 host species.

Results

In controlled random test sets with 90% redundancy reduction in terms of protein similarity, vHULK obtained on average 83% precision and 79% recall at the genus level, and 71% precision and 67% recall at the species level. The performance of vHULK was compared against three other tools on a test data set with 2153 phage genomes. On this data set, vHULK achieved better performance at both the genus and the species levels than the other tools.

Conclusions

Our results suggest that vHULK represents an advance on the state of art in phage host prediction.

Daily Reports on Phage-Host Interactions

Understanding phage-host relationships is crucial for the study of virus biology and the application of phages in biotechnology and medicine. However, information concerning the range of hosts for bacterial and archaeal viruses is scattered across numerous databases and is difficult to obtain. Therefore, here we present PHD (Phage & Host Daily), a web application that offers a comprehensive, up-to-date catalog of known phage-host associations that allows users to select viruses targeting specific bacterial and archaeal taxa of interest. Our service combines the latest information on virus-host interactions from seven source databases with current taxonomic classification retrieved directly from the groups and institutions responsible for its maintenance. The web application also provides summary statistics on host and virus diversity, their pairwise interactions, and the host range of deposited phages. PHD is updated daily and available at http://phdaily.info or http://combio.pl/phdaily.

PhageCocktail: An R package to design phage cocktails from experimental phage-bacteria infection networks

BACKGROUND AND OBJECTIVE

Phage therapy is a resurgent strategy used in medicine and the food industry to lyse bacteria that cause damage to health or spoil a food product. Frequently, phage-bacteria infection networks have a large size, making it impossible to manually study all possible phage cocktails. Thus, this article presents an R package called PhageCocktail to automatically design efficient phage cocktails from phage-bacteria infection networks.

METHODS

This R package includes four different methods for designing phage cocktails: ExhaustiveSearch, ExhaustivePhi, ClusteringSearch, and ClusteringPhi. These four methods are explained in detail and are evaluated using 13 empirical phage-bacteria infection networks. More specifically, runtime and expected success (fraction of lysed bacteria) are analyzed.

RESULTS

The four methods have variations in terms of runtime and quality of the results. ExhaustiveSearch always provides the best possible phage cocktail, but its runtime could be long. ExhaustivePhi only focuses on one cocktail size, the one estimated as the best; thus, its runtime is less than ExhaustiveSearch, but it can produce cocktails with more phages than necessary. ClusteringSearch and ClusteringPhi are very fast (generally, less than one millisecond), providing always immediate results due to clustering techniques, but their accuracies can be lower, yielding cocktails with lower expected successes.

CONCLUSIONS

The larger the phage-bacteria infection network is, the more complex its analysis is. Thus, this tool eases this task for scientists and other users while designing phage cocktails of good quality. This R package includes four different methods; therefore, users may choose among them, considering their preferences in speed and accuracy of results.

CHERRY: a Computational metHod for accuratE pRediction of virus-pRokarYotic interactions using a graph encoder-decoder model

Prokaryotic viruses, which infect bacteria and archaea, are key players in microbial communities. Predicting the hosts of prokaryotic viruses helps decipher the dynamic relationship between microbes. Experimental methods for host prediction cannot keep pace with the fast accumulation of sequenced phages. Thus, there is a need for computational host prediction. Despite some promising results, computational host prediction remains a challenge because of the limited known interactions and the sheer amount of sequenced phages by high-throughput sequencing technologies. The state-of-the-art methods can only achieve 43% accuracy at the species level. In this work, we formulate host prediction as link prediction in a knowledge graph that integrates multiple protein and DNA-based sequence features. Our implementation named CHERRY can be applied to predict hosts for newly discovered viruses and to identify viruses infecting targeted bacteria. We demonstrated the utility of CHERRY for both applications and compared its performance with 11 popular host prediction methods. To our best knowledge, CHERRY has the highest accuracy in identifying virus–prokaryote interactions. It outperforms all the existing methods at the species level with an accuracy increase of 37%. In addition, CHERRY’s performance on short contigs is more stable than other tools.

Newly identified HMO-2011-type phages reveal genomic diversity and biogeographic distributions of this marine viral group

Viruses play critical roles in influencing biogeochemical cycles and adjusting host mortality, population structure, physiology, and evolution in the ocean. Marine viral communities are composed of numerous genetically distinct subfamily/genus-level viral groups. Among currently identified viral groups, the HMO-2011-type group is known to be dominant and broadly distributed. However, only four HMO-2011-type cultivated representatives that infect marine SAR116 and Roseobacter strains have been reported to date, and the genetic diversity, potential hosts, and ecology of this group remain poorly elucidated. Here, we present the genomes of seven HMO-2011-type phages that were isolated using four Roseobacter strains and one SAR11 strain, as well as additional 207 HMO-2011-type metagenomic viral genomes (MVGs) identified from various marine viromes. Phylogenomic and shared-gene analyses revealed that the HMO-2011-type group is a subfamily-level group comprising at least 10 discernible genus-level subgroups. Moreover, >2000 HMO-2011-type DNA polymerase sequences were identified, and the DNA polymerase phylogeny also revealed that the HMO-2011-type group contains diverse subgroups and is globally distributed. Metagenomic read-mapping results further showed that most HMO-2011-type phages are prevalent in global oceans and display distinct geographic distributions, with the distribution of most HMO-2011-type phages being associated with temperature. Lastly, we found that members in subgroup IX, represented by pelagiphage HTVC033P, were among the most abundant HMO-2011-type phages, which implies that SAR11 bacteria are crucial hosts for this viral group. In summary, our findings substantially expand current knowledge regarding the phylogenetic diversity, evolution, and distribution of HMO-2011-type phages, highlighting HMO-2011-type phages as major ecological agents that can infect certain key bacterial groups.

A Novel and Ubiquitous Marine Methylophage Provides Insights into Viral-Host Coevolution and Possible Host-Range Expansion in Streamlined Marine Heterotrophic Bacteria

The methylotrophic OM43 clade are Gammaproteobacteria that comprise some of the smallest free-living cells known and have highly streamlined genomes. OM43 represents an important microbial link between marine primary production and remineralization of carbon back to the atmosphere. Bacteriophages shape microbial communities and are major drivers of mortality and global marine biogeochemistry. Recent cultivation efforts have brought the first viruses infecting members of the OM43 clade into culture. Here, we characterize a novel myophage infecting OM43 called Melnitz. Melnitz was isolated independently from water samples from a subtropical ocean gyre (Sargasso Sea) and temperate coastal (Western English Channel) systems. Metagenomic recruitment from global ocean viromes confirmed that Melnitz is globally ubiquitous, congruent with patterns of host abundance. Bacteria with streamlined genomes such as OM43 and the globally dominant SAR11 clade use riboswitches as an efficient method to regulate metabolism. Melnitz encodes a two-piece tmRNA (ssrA), controlled by a glutamine riboswitch, providing evidence that riboswitch use also occurs for regulation during phage infection of streamlined heterotrophs. Virally encoded tRNAs and ssrA found in Melnitz were phylogenetically more closely related to those found within the alphaproteobacterial SAR11 clade and their associated myophages than those within their gammaproteobacterial hosts. This suggests the possibility of an ancestral host transition event between SAR11 and OM43. Melnitz and a related myophage that infects SAR11 were unable to infect hosts of the SAR11 and OM43, respectively, suggesting host transition rather than a broadening of host range.

IMPORTANCE Isolation and cultivation of viruses are the foundations on which the mechanistic understanding of virus-host interactions and parameterization of bioinformatic tools for viral ecology are based. This study isolated and characterized the first myophage known to infect the OM43 clade, expanding our knowledge of this understudied group of microbes. The nearly identical genomes of four strains of Melnitz isolated from different marine provinces and the global abundance estimations from metagenomic data suggest that this viral population is globally ubiquitous. Genome analysis revealed several unusual features in Melnitz and related genomes recovered from viromes, such as a curli operon and virally encoded tmRNA controlled by a glutamine riboswitch, neither of which are found in the host. Further phylogenetic analysis of shared genes indicates that this group of viruses infecting the gammaproteobacterial OM43 shares a recent common ancestor with viruses infecting the abundant alphaproteobacterial SAR11 clade. Host ranges are affected by compatible cell surface receptors, successful circumvention of superinfection exclusion systems, and the presence of required accessory proteins, which typically limits phages to singular narrow groups of closely related bacterial hosts. This study provides intriguing evidence that for streamlined heterotrophic bacteria, virus-host transitioning may not be necessarily restricted to phylogenetically related hosts but is a function of shared physical and biochemical properties of the cell.

Phages in the Gut Ecosystem

Phages, short for bacteriophages, are viruses that specifically infect bacteria and are the most abundant biological entities on earth found in every explored environment, from the deep sea to the Sahara Desert. Phages are abundant within the human biome and are gaining increasing recognition as potential modulators of the gut ecosystem. For example, they have been connected to gastrointestinal diseases and the treatment efficacy of Fecal Microbiota Transplant. The ability of phages to modulate the human gut microbiome has been attributed to the predation of bacteria or the promotion of bacterial survival by the transfer of genes that enhance bacterial fitness upon infection. In addition, phages have been shown to interact with the human immune system with variable outcomes. Despite the increasing evidence supporting the importance of phages in the gut ecosystem, the extent of their influence on the shape of the gut ecosystem is yet to be fully understood. Here, we discuss evidence for phage modulation of the gut microbiome, postulating that phages are pivotal contributors to the gut ecosystem dynamics. We therefore propose novel research questions to further elucidate the role(s) that they have within the human ecosystem and its impact on our health and well-being.

OUP accepted manuscript

Motivation

Phage–host associations play important roles in microbial communities. But in natural communities, as opposed to culture-based lab studies where phages are discovered and characterized metagenomically, their hosts are generally not known. Several programs have been developed for predicting which phage infects which host based on various sequence similarity measures or machine learning approaches. These are often based on whole viral and host genomes, but in metagenomics-based studies, we rarely have whole genomes but rather must rely on contigs that are sometimes as short as hundreds of bp long. Therefore, we need programs that predict hosts of phage contigs on the basis of these short contigs. Although most existing programs can be applied to metagenomic datasets for these predictions, their accuracies are generally low. Here, we develop ContigNet, a convolutional neural network-based model capable of predicting phage–host matches based on relatively short contigs, and compare it to previously published VirHostMatcher (VHM) and WIsH.

Results

On the validation set, ContigNet achieves 72–85% area under the receiver operating characteristic curve (AUROC) scores, compared to the maximum of 68% by VHM or WIsH for contigs of lengths between 200 bps to 50 kbps. We also apply the model to the Metagenomic Gut Virus (MGV) catalogue, a dataset containing a wide range of draft genomes from metagenomic samples and achieve 60–70% AUROC scores compared to that of VHM and WIsH of 52%. Surprisingly, ContigNet can also be used to predict plasmid-host contig associations with high accuracy, indicating a similar genetic exchange between mobile genetic elements and their hosts.

Availability and implementation

The source code of ContigNet and related datasets can be downloaded from https://github.com/tianqitang1/ContigNet.

Computational design of phage cocktails based on phage-bacteria infection networks

The misuse and overuse of antibiotics have boosted the proliferation of multidrug-resistant (MDR) bacteria, which are considered a major public health issue in the twenty-first century. Phage therapy may be a promising way in the treatment of infections caused by MDR pathogens, without the side effects of the current available antimicrobials. Phage therapy is based on phage cocktails, that is, combinations of phages able to lyse the target bacteria. In this work, we present and explain in detail two innovative computational methods to design phage cocktails taking into account a given phage-bacteria infection network. One of the methods (Exhaustive Search) always generates the best possible phage cocktail, while the other method (Network Metrics) always keeps a very reduced runtime (a few milliseconds). Both methods have been included in a Cytoscape application that is available for any user. A complete experimental study has been performed, evaluating and comparing the biological quality, runtime, and the impact when additional phages are included in the cocktail.

Predicting the hosts of prokaryotic viruses using GCN-based semi-supervised learning

Background

Prokaryotic viruses, which infect bacteria and archaea, are the most abundant and diverse biological entities in the biosphere. To understand their regulatory roles in various ecosystems and to harness the potential of bacteriophages for use in therapy, more knowledge of viral-host relationships is required. High-throughput sequencing and its application to the microbiome have offered new opportunities for computational approaches for predicting which hosts particular viruses can infect. However, there are two main challenges for computational host prediction. First, the empirically known virus-host relationships are very limited. Second, although sequence similarity between viruses and their prokaryote hosts have been used as a major feature for host prediction, the alignment is either missing or ambiguous in many cases. Thus, there is still a need to improve the accuracy of host prediction.

Results

In this work, we present a semi-supervised learning model, named HostG, to conduct host prediction for novel viruses. We construct a knowledge graph by utilizing both virus-virus protein similarity and virus-host DNA sequence similarity. Then graph convolutional network (GCN) is adopted to exploit viruses with or without known hosts in training to enhance the learning ability. During the GCN training, we minimize the expected calibrated error (ECE) to ensure the confidence of the predictions. We tested HostG on both simulated and real sequencing data and compared its performance with other state-of-the-art methods specifically designed for virus host classification (VHM-net, WIsH, PHP, HoPhage, RaFAH, vHULK, and VPF-Class).

Conclusion

HostG outperforms other popular methods, demonstrating the efficacy of using a GCN-based semi-supervised learning approach. A particular advantage of HostG is its ability to predict hosts from new taxa.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12915-021-01180-4).

Taxonomy-aware, sequence similarity ranking reliably predicts phage-host relationships

Background

Characterizing phage–host interactions is critical to understanding the ecological role of both partners and effective isolation of phage therapeuticals. Unfortunately, experimental methods for studying these interactions are markedly slow, low-throughput, and unsuitable for phages or hosts difficult to maintain in laboratory conditions. Therefore, a number of in silico methods emerged to predict prokaryotic hosts based on viral sequences. One of the leading approaches is the application of the BLAST tool that searches for local similarities between viral and microbial genomes. However, this prediction method has three major limitations: (i) top-scoring sequences do not always point to the actual host; (ii) mosaic virus genomes may match to many, typically related, bacteria; and (iii) viral and host sequences may diverge beyond the point where their relationship can be detected by a BLAST alignment.

Results

We created an extension to BLAST, named Phirbo, that improves host prediction quality beyond what is obtainable from standard BLAST searches. The tool harnesses information concerning sequence similarity and bacteria relatedness to predict phage–host interactions. Phirbo was evaluated on three benchmark sets of known virus–host pairs, and it improved precision and recall by 11–40 percentage points over currently available, state-of-the-art, alignment-based, alignment-free, and machine-learning host prediction tools. Moreover, the discriminatory power of Phirbo for the recognition of virus–host relationships surpassed the results of other tools by at least 10 percentage points (area under the curve = 0.95), yielding a mean host prediction accuracy of 57% and 68% at the genus and family levels, respectively, and drops by 12 percentage points when using only a fraction of viral genome sequences (3 kb). Finally, we provide insights into a repertoire of protein and ncRNA genes that are shared between phages and hosts and may be prone to horizontal transfer during infection.

Conclusions

Our results suggest that Phirbo is a simple and effective tool for predicting phage–host relationships.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01146-6.