Computational approaches to predict bacteriophage-host relationships

Taxonomic difference in marine bloom-forming phytoplanktonic species affects the dynamics of both bloom-responding prokaryotes and prokaryotic viruses

The production of dissolved organic matter during phytoplankton blooms and consumption by heterotrophic prokaryotes promote marine carbon biogeochemical cycling. Although prokaryotic viruses presumably affect this process, their dynamics during blooms are not fully understood. Here, we investigated the effects of taxonomic difference in bloom-forming phytoplankton on prokaryotes and their viruses. We analyzed the dynamics of coastal prokaryotic communities and viruses under the addition of dissolved intracellular fractions from taxonomically distinct phytoplankton, the diatom Chaetoceros sp. (CIF) and the raphidophycean alga Heterosigma akashiwo (HIF), using microcosm experiments. Ribosomal RNA gene amplicon and viral metagenomic analyses revealed that particular prokaryotes and prokaryotic viruses specifically increased in either CIF or HIF, indicating that taxonomic difference in bloom-forming phytoplankton promotes distinct dynamics of not only the prokaryotic community but also prokaryotic viruses. Furthermore, combining our microcosm experiments with publicly available environmental data mining, we identified both known and novel possible host-virus pairs. In particular, the growth of prokaryotes associating with phytoplanktonic organic matter, such as Bacteroidetes (Polaribacter and NS9 marine group), Vibrio spp., and Rhodobacteriales (Nereida and Planktomarina), was accompanied by an increase in viruses predicted to infect Bacteroidetes, Vibrio, and Rhodobacteriales, respectively. Collectively, our findings suggest that changes in bloom-forming species can be followed by an increase in a specific group of prokaryotes and their viruses and that elucidating these tripartite relationships among specific phytoplankton, prokaryotes, and prokaryotic viruses improves our understanding of coastal biogeochemical cycling in blooms.IMPORTANCEThe primary production during marine phytoplankton bloom and the consumption of the produced organic matter by heterotrophic prokaryotes significantly contribute to coastal biogeochemical cycles. While the activities of those heterotrophic prokaryotes are presumably affected by viral infection, the dynamics of their viruses during blooms are not fully understood. In this study, we experimentally demonstrated that intracellular fractions of taxonomically distinct bloom-forming phytoplankton species, the diatom Chaetoceros sp. and the raphidophycean alga Heterosigma akashiwo, promoted the growth of taxonomically different prokaryotes and prokaryotic viruses. Based on their dynamics and predicted hosts of those viruses, we succeeded in detecting already-known and novel possible host-virus pairs associating with either phytoplankton species. Altogether, we propose that the succession of bloom-forming phytoplankton would change the composition of the abundant prokaryotes, resulting in an increase in their viruses. These changes in viral composition, depending on bloom-forming species, would alter the dynamics and metabolism of prokaryotes, affecting biogeochemical cycling in blooms.

Diversity and potential host-interactions of viruses inhabiting deep-sea seamount sediments

Seamounts are globally distributed across the oceans and form one of the major oceanic biomes. Here, we utilized combined analyses of bulk metagenome and virome to study viral communities in seamount sediments in the western Pacific Ocean. Phylogenetic analyses and the protein-sharing network demonstrate extensive diversity and previously unknown viral clades. Inference of virus-host linkages uncovers extensive interactions between viruses and dominant prokaryote lineages, and suggests that viruses play significant roles in carbon, sulfur, and nitrogen cycling by compensating or augmenting host metabolisms. Moreover, temperate viruses are predicted to be prevalent in seamount sediments, which tend to carry auxiliary metabolic genes for host survivability. Intriguingly, the geographical features of seamounts likely compromise the connectivity of viral communities and thus contribute to the high divergence of viral genetic spaces and populations across seamounts. Altogether, these findings provides knowledge essential for understanding the biogeography and ecological roles of viruses in globally widespread seamounts.

A compendium of ruminant gastrointestinal phage genomes revealed a higher proportion of lytic phages than in any other environments

BACKGROUND

Ruminants are important livestock animals that have a unique digestive system comprising multiple stomach compartments. Despite significant progress in the study of microbiome in the gastrointestinal tract (GIT) sites of ruminants, we still lack an understanding of the viral community of ruminants. Here, we surveyed its viral ecology using 2333 samples from 10 sites along the GIT of 8 ruminant species.

RESULTS

We present the Unified Ruminant Phage Catalogue (URPC), a comprehensive survey of phages in the GITs of ruminants including 64,922 non-redundant phage genomes. We characterized the distributions of the phage genomes in different ruminants and GIT sites and found that most phages were organism-specific. We revealed that ~ 60% of the ruminant phages were lytic, which was the highest as compared with those in all other environments and certainly will facilitate their applications in microbial interventions. To further facilitate the future applications of the phages, we also constructed a comprehensive virus-bacteria/archaea interaction network and identified dozens of phages that may have lytic effects on methanogenic archaea.

CONCLUSIONS

The URPC dataset represents a useful resource for future microbial interventions to improve ruminant production and ecological environmental qualities. Phages have great potential for controlling pathogenic bacterial/archaeal species and reducing methane emissions. Our findings provide insights into the virome ecology research of the ruminant GIT and offer a starting point for future research on phage therapy in ruminants. Video Abstract.

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.

Forty-nine metagenomic-assembled genomes from an aquatic virome expand Caudoviricetes by 45 potential new families and the newly uncovered Gossevirus of Bamfordvirae

Twenty complete genomes (29-63 kb) and 29 genomes with an estimated completeness of over 90 % (30-90 kb) were identified for novel dsDNA viruses in the Yangshan Harbor metavirome. These newly discovered viruses contribute to the expansion of viral taxonomy by introducing 46 potential new families. Except for one virus, all others belong to the class Caudoviricetes. The exception is a novel member of the recently characterized viral group known as Gossevirus. Fifteen viruses were predicted to be temperate. The predicted hosts for the viruses appear to be involved in various aspects of the nitrogen cycle, including nitrogen fixation, oxidation and denitrification. Two viruses were identified to have a host of Flavobacterium and Tepidimonas fonticaldi, respectively, by matching CRISPR spacers with viral protospacers. Our findings provide an overview for characterizing and identifying specific viruses from Yangshan Harbor. The Gossevirus-like virus uncovered emphasizes the need for further comprehensive isolation and investigation of polinton-like viruses.

Bacteriophages, gut bacteria, and microbial pathways interplay in cardiometabolic health

Cardiometabolic diseases are leading causes of mortality in Western countries. Well-established risk factors include host genetics, lifestyle, diet, and the gut microbiome. Moreover, gut bacterial communities and their activities can be altered by bacteriophages (also known simply as phages), bacteria-infecting viruses, making these biological entities key regulators of human cardiometabolic health. The manipulation of bacterial populations by phages enables the possibility of using phages in the treatment of cardiometabolic diseases through phage therapy and fecal viral transplants. First, however, a deeper understanding of the role of the phageome in cardiometabolic diseases is required. In this review, we first introduce the phageome as a component of the gut microbiome and discuss fecal viral transplants and phage therapy in relation to cardiometabolic diseases. We then summarize the current state of phageome research in cardiometabolic diseases and propose how the phageome might indirectly influence cardiometabolic health through gut bacteria and their metabolites.

Virus-prokaryote infection pairs associated with prokaryotic production in a freshwater lake

Viruses infect and kill prokaryotic populations in a density- or frequency-dependent manner and affect carbon cycling. However, the effects of the stratification transition, including the stratified and de-stratified periods, on the changes in prokaryotic and viral communities and their interactions remain unclear. We conducted a monthly survey of the surface and deep layers of a large and deep freshwater lake (Lake Biwa, Japan) for a year and analyzed the prokaryotic production and prokaryotic and viral community composition. Our analysis revealed that, in the surface layer, 19 prokaryotic species, accounting for approximately 40% of the total prokaryotic abundance, could potentially contribute to the majority of prokaryotic production, which is the highest during the summer and is suppressed by viruses. This suggests that a small fraction of prokaryotes and phages were the key infection pairs during the peak period of prokaryotic activity in the freshwater lake. We also found that approximately 50% of the dominant prokaryotic and viral species in the deep layer were present throughout the study period. This suggests that the "kill the winner" model could explain the viral impact on prokaryotes in the surface layer, but other dynamics may be at play in the deep layer. Furthermore, we found that annual vertical mixing could result in a similar rate of community change between the surface and deep layers. These findings may be valuable in understanding how communities and the interaction among them change when freshwater lake stratification is affected by global warming in the future.IMPORTANCEViral infection associated with prokaryotic production occurs in a density- or frequency-dependent manner and regulates the prokaryotic community. Stratification transition and annual vertical mixing in freshwater lakes are known to affect the prokaryotic community and the interaction between prokaryotes and viruses. By pairing measurements of virome analysis and prokaryotic production of a 1-year survey of the depths of surface and deep layers, we revealed (i) the prokaryotic infection pairs associated with prokaryotic production and (ii) the reset in prokaryotic and viral communities through annual vertical mixing in a freshwater lake. Our results provide a basis for future work into changes in stratification that may impact the biogeochemical cycling in freshwater lakes.

Comparative evaluation of bioinformatic tools for virus-host prediction and their application to a highly diverse community in the Cuatro Ciénegas Basin, Mexico

Due to the enormous diversity of non-culturable viruses, new viruses must be characterized using culture-independent techniques. The associated host is an important phenotypic feature that can be inferred from metagenomic viral contigs thanks to the development of several bioinformatic tools. Here, we compare the performance of recently developed virus-host prediction tools on a dataset of 1,046 virus-host pairs and then apply the best-performing tools to a metagenomic dataset derived from a highly diverse transiently hypersaline site known as the Archaean Domes (AD) within the Cuatro Ciénegas Basin, Coahuila, Mexico. Among host-dependent methods, alignment-based approaches had a precision of 66.07% and a sensitivity of 24.76%, while alignment-free methods had an average precision of 75.7% and a sensitivity of 57.5%. RaFAH, a virus-dependent alignment-based tool, had the best overall performance (F1_score = 95.7%). However, when predicting the host of AD viruses, methods based on public reference databases (such as RaFAH) showed lower inter-method agreement than host-dependent methods run against custom databases constructed from prokaryotes inhabiting AD. Methods based on custom databases also showed the greatest agreement between the source environment and the predicted host taxonomy, habitat, lifestyle, or metabolism. This highlights the value of including custom data when predicting hosts on a highly diverse metagenomic dataset, and suggests that using a combination of methods and qualitative validations related to the source environment and predicted host biology can increase the number of correct predictions. Finally, these predictions suggest that AD viruses infect halophilic archaea as well as a variety of bacteria that may be halophilic, halotolerant, alkaliphilic, thermophilic, oligotrophic, sulfate-reducing, or marine, which is consistent with the specific environment and the known geological and biological evolution of the Cuatro Ciénegas Basin and its microorganisms.

Host range and cell recognition of archaeal viruses

Archaea are members of a separate domain of life that have unique properties, such as the composition of their cell walls and the structure of their lipid bilayers. Consequently, archaeal viruses face different challenges to infect host cells in comparison with viruses of bacteria and eukaryotes. Despite their significant impact on shaping microbial communities, our understanding of infection processes of archaeal viruses remains limited. Several receptors used by archaeal viruses to infect cells have recently been identified. The interactions between viruses and receptors are one of the determinants of the host range of viruses. Here, we review the current literature on host ranges of archaeal viruses and factors that might impact the width of these host ranges.

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.

A rumen virosphere with implications of contribution to fermentation and methane production, and endemism in cattle breeds and individuals

Viruses have a potential to modify the ruminal digestion via infection and cell lysis of prokaryotes, suggesting that viruses are related to animal performance and methane production. This study aimed to elucidate the genome-based diversity of rumen viral communities and the differences in virus structure between individuals and cattle breeds and to understand how viruses influence on the rumen. To these ends, a metagenomic sequencing of virus-like particles in the rumen of 22 Japanese cattle, including Japanese Black (JB, n = 8), Japanese Shorthorn (n = 2), and Japanese Black sires × Holstein dams crossbred steers (F1, n = 12) was conducted. Additionally, the rumen viromes of six JB and six F1 that were fed identical diets and kept in a single barn were compared. A total of 8,232 non-redundant viral genomes (≥5-kb length and ≥50% completeness), including 982 complete genomes, were constructed, and rumen virome exhibited lysogenic signatures. Furthermore, putative hosts of 1,223 viral genomes were predicted using tRNA and clustered regularly interspaced short palindromic repeat (CRISPR)-spacer matching. The genomes included 1 and 10 putative novel complete genomes associated with Fibrobacter and Ruminococcus, respectively, which are the main rumen cellulose-degrading bacteria. Additionally, the hosts of 22 viral genomes, including 2 complete genomes, were predicted as methanogens, such as Methanobrevibacter and Methanomethylophilus. Most rumen viruses were highly rumen and individual specific and related to rumen-specific prokaryotes. Furthermore, the rumen viral community structure was significantly different between JB and F1 steers, indicating that cattle breed is one of the factors influencing the rumen virome composition.IMPORTANCEHere, we investigated the individual and breed differences of the rumen viral community in Japanese cattle. In the process, we reconstructed putative novel complete viral genomes related to rumen fiber-degrading bacteria and methanogen. The finding strongly suggests that rumen viruses contribute to cellulose and hemicellulose digestion and methanogenesis. Notably, this study also found that rumen viruses are highly rumen and individual specific, suggesting that rumen viruses may not be transmitted through environmental exposure. More importantly, we revealed differences of viral communities between JB and F1 cattle, indicating that cattle breed is a factor that influences the establishment of rumen virome. These results suggest the possibility of rumen virus transmission from mother to offspring and its potential to influence beef production traits. These rumen viral genomes and findings provide new insights into the characterizations of the rumen viruses.

PB-LKS: a python package for predicting phage-bacteria interaction through local K-mer strategy

Bacteriophages can help the treatment of bacterial infections yet require in-silico models to deal with the great genetic diversity between phages and bacteria. Despite the tolerable prediction performance, the application scope of current approaches is limited to the prediction at the species level, which cannot accurately predict the relationship of phages across strain mutants. This has hindered the development of phage therapeutics based on the prediction of phage-bacteria relationships. In this paper, we present, PB-LKS, to predict the phage-bacteria interaction based on local K-mer strategy with higher performance and wider applicability. The utility of PB-LKS is rigorously validated through (i) large-scale historical screening, (ii) case study at the class level and (iii) in vitro simulation of bacterial antiphage resistance at the strain mutant level. The PB-LKS approach could outperform the current state-of-the-art methods and illustrate potential clinical utility in pre-optimized phage therapy design.

The insights into the phage communities of fermented foods in the age of viral metagenomics

Phages play a critical role in the assembly and regulation of fermented food microbiome through lysis and lysogenic lifestyle, which in turn affects the yield and quality of fermented foods. Therefore, it is important to investigate and characterize the diversity and function of phages under complex microbial communities and nutrient substrate conditions to provide novel insights into the regulation of traditional spontaneous fermentation. Viral metagenomics has gradually garnered increasing attention in fermented food research to elucidate phage functions and characterize the interactions between phages and the microbial community. Advances in this technology have uncovered a wide range of phages associated with the production of traditional fermented foods and beverages. This paper reviews the common methods of viral metagenomics applied in fermented food research, and summarizes the ecological functions of phages in traditional fermented foods. In the future, combining viral metagenomics with culturable methods and metagenomics will broaden the scope of research on fermented food systems, revealing the complex role of phages and intricate phage-bacterium interactions.

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary -and largely uncharacterized- genetics of adsorption, injection, and cell take-over. Here we present a machine learning (ML) approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions amongst 51 Escherichia coli strains and 45 phage λ strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. The most effective ML approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, predicting phage host range with 86% mean classification accuracy while reducing the relative error in the estimated strength of the infection phenotype by 40%. Further, transparent feature selection in the predictive model revealed 18 of 176 phage λ and 6 of 18 E. coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage λ infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. While the genetic variation studied was limited to a focal, coevolved phage-bacteria system, the method's success at recapitulating strain-level infection outcomes provides a path forward towards developing strategies for inferring interactions in non-model systems, including those of therapeutic significance.

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.

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.

Genome analysis of triple phages that curtails MDR E. coli with ML based host receptor prediction and its evaluation

Infections by multidrug resistant bacteria (MDR) are becoming increasingly difficult to treat and alternative approaches like phage therapy, which is unhindered by drug resistance, are urgently needed to tackle MDR bacterial infections. During phage therapy phage cocktails targeting different receptors are likely to be more effective than monophages. In the present study, phages targeting carbapenem resistant clinical isolate of E. coli U1007 was isolated from Ganges River (U1G), Cooum River (CR) and Hospital waste water (M). Capsid architecture discerned using TEM identified the phage families as Podoviridae for U1G, Myoviridae for CR and Siphoviridae for M phage. Genome sequencing showed the phage genomes varied in size U1G (73,275 bp) CR (45,236 bp) and M (45,294 bp). All three genomes lacked genes encoding tRNA sequence, antibiotic resistant or virulent genes. A machine learning (ML) based multi-class classification model using Random Forest, Logistic Regression, and Decision Tree were employed to predict the host receptor targeted by receptor binding protein of all 3 phages and the best performing algorithm Random Forest predicted LPS O antigen, LamB or OmpC for U1G; FhuA, OmpC for CR phage; and FhuA, LamB, TonB or OmpF for the M phage. OmpC was validated as receptor for U1G by physiological experiments. In vivo intramuscular infection study in zebrafish showed that cocktail of dual phages (U1G + M) along with colsitin resulted in a significant 3.5 log decline in cell counts. Our study highlights the potential of ML tool to predict host receptor and proves the utility of phage cocktail to restrict E. coli U1007 in vivo.

With a pinch of salt: metagenomic insights into Namib Desert salt pan microbial mats and halites reveal functionally adapted and competitive communities

IMPORTANCE

The hyperarid Namib Desert is one of the oldest deserts on Earth. It contains multiple clusters of playas which are saline-rich springs surrounded by halite evaporites. Playas are of great ecological importance, and their indigenous (poly)extremophilic microorganisms are potentially involved in the precipitation of minerals such as carbonates and sulfates and have been of great biotechnological importance. While there has been a considerable amount of microbial ecology research performed on various Namib Desert edaphic microbiomes, little is known about the microbial communities inhabiting its multiple playas. In this work, we provide a comprehensive taxonomic and functional potential characterization of the microbial, including viral, communities of sediment mats and halites from two distant salt pans of the Namib Desert, contributing toward a better understanding of the ecology of this biome.

Computational host range prediction-The good, the bad, and the ugly

The rapid emergence and spread of antimicrobial resistance across the globe have prompted the usage of bacteriophages (i.e. viruses that infect bacteria) in a variety of applications ranging from agriculture to biotechnology and medicine. In order to effectively guide the application of bacteriophages in these multifaceted areas, information about their host ranges-that is the bacterial strains or species that a bacteriophage can successfully infect and kill-is essential. Utilizing sixteen broad-spectrum (polyvalent) bacteriophages with experimentally validated host ranges, we here benchmark the performance of eleven recently developed computational host range prediction tools that provide a promising and highly scalable supplement to traditional, but laborious, experimental procedures. We show that machine- and deep-learning approaches offer the highest levels of accuracy and precision-however, their predominant predictions at the species- or genus-level render them ill-suited for applications outside of an ecosystems metagenomics framework. In contrast, only moderate sensitivity (<80 per cent) could be reached at the strain-level, albeit at low levels of precision (<40 per cent). Taken together, these limitations demonstrate that there remains room for improvement in the active scientific field of in silico host prediction to combat the challenge of guiding experimental designs to identify the most promising bacteriophage candidates for any given application.

Viral diversity and dynamics and CRISPR-Cas-mediated immunity in a robust alkaliphilic cyanobacterial consortium

IMPORTANCE

Biotechnology applications utilizing the function of microbial communities have become increasingly important solutions as we strive for sustainable applications. Although viral infections are known to have a significant impact on microbial turnover and nutrient cycling, viral dynamics have remained largely overlooked in these engineered communities. Predatory perturbations to the functional stability of these microbial biotechnology applications must be investigated in order to design more robust applications. In this study, we closely examine virus-microbe dynamics in a model microbial community used in a biotechnology application. Our findings suggest that viral dynamics change significantly with environmental conditions and that microbial immunity may play an important role in maintaining functional stability. We present this study as a comprehensive template for other researchers interested in exploring predatory dynamics in engineered microbial communities.

Prokaryotic virus host prediction with graph contrastive augmentaion

Prokaryotic viruses, also known as bacteriophages, play crucial roles in regulating microbial communities and have the potential for phage therapy applications. Accurate prediction of phage-host interactions is essential for understanding the dynamics of these viruses and their impacts on bacterial populations. Numerous computational methods have been developed to tackle this challenging task. However, most existing prediction models can be constrained due to the substantial number of unknown interactions in comparison to the constrained diversity of available training data. To solve the problem, we introduce a model for prokaryotic virus host prediction with graph contrastive augmentation (PHPGCA). Specifically, we construct a comprehensive heterogeneous graph by integrating virus-virus protein similarity and virus-host DNA sequence similarity information. As the backbone encoder for learning node representations in the virus-prokaryote graph, we employ LGCN, a state-of-the-art graph embedding technique. Additionally, we apply graph contrastive learning to augment the node representations without the need for additional labels. We further conducted two case studies aimed at predicting the host range of multi-species phages, helping to understand the phage ecology and evolution.

Novel virulent and temperate cyanophages predicted to infect Microcoleus associated with anatoxin-producing benthic mats

Cyanophages are crucial for regulating cyanobacterial populations, but their influence on anatoxin-producing Microcoleus mat dynamics remains unexplored. Here, we use metagenomics to explore phage presence in benthic mats from the Wolastoq|Saint John River (New Brunswick, Canada) and the Eel River (California, USA). We recovered multiple viral-like sequences associated with different putative bacterial hosts, including two cyanophage genomes with apparently different replication strategies. A temperate cyanophage was found integrated in the genomes of Microcoleus sp. 3 recovered from the Eel River and is phylogenetically related to Phormidium phages. We also recovered novel virulent cyanophage genomes from Wolastoq and Eel River mats that were dominated by anatoxin-producing Microcoleus species predicted to be the host. Despite the geographical distance, these genomes have similar sizes (circa 239 kbp) and share numerous orthologous genes with high sequence identity. A considerable reduction of the anatoxin-producing Microcoleus species in Wolastoq mats following the emergence of the virulent phage suggests that phage infections have an important role in limiting the abundance of this toxigenic cyanobacterium and releasing anatoxins into the surrounding water. Our results constitute the first report of cyanophages predicted to infect mat-forming Microcoleus species associated with anatoxin production.

HostNet: improved sequence representation in deep neural networks for virus-host prediction

BACKGROUND

The escalation of viruses over the past decade has highlighted the need to determine their respective hosts, particularly for emerging ones that pose a potential menace to the welfare of both human and animal life. Yet, the traditional means of ascertaining the host range of viruses, which involves field surveillance and laboratory experiments, is a laborious and demanding undertaking. A computational tool with the capability to reliably predict host ranges for novel viruses can provide timely responses in the prevention and control of emerging infectious diseases. The intricate nature of viral-host prediction involves issues such as data imbalance and deficiency. Therefore, developing highly accurate computational tools capable of predicting virus-host associations is a challenging and pressing demand.

RESULTS

To overcome the challenges of virus-host prediction, we present HostNet, a deep learning framework that utilizes a Transformer-CNN-BiGRU architecture and two enhanced sequence representation modules. The first module, k-mer to vector, pre-trains a background vector representation of k-mers from a broad range of virus sequences to address the issue of data deficiency. The second module, an adaptive sliding window, truncates virus sequences of various lengths to create a uniform number of informative and distinct samples for each sequence to address the issue of data imbalance. We assess HostNet's performance on a benchmark dataset of "Rabies lyssavirus" and an in-house dataset of "Flavivirus". Our results show that HostNet surpasses the state-of-the-art deep learning-based method in host-prediction accuracies and F1 score. The enhanced sequence representation modules, significantly improve HostNet's training generalization, performance in challenging classes, and stability.

CONCLUSION

HostNet is a promising framework for predicting virus hosts from genomic sequences, addressing challenges posed by sparse and varying-length virus sequence data. Our results demonstrate its potential as a valuable tool for virus-host prediction in various biological contexts. Virus-host prediction based on genomic sequences using deep neural networks is a promising approach to identifying their potential hosts accurately and efficiently, with significant impacts on public health, disease prevention, and vaccine development.

Coordinated proteome change precedes cell lysis and death in a mat-forming cyanobacterium

Cyanobacteria form dense multicellular communities that experience transient conditions in terms of access to light and oxygen. These systems are productive but also undergo substantial biomass turnover through cell death, supplementing heightened heterotrophic respiration. Here we use metagenomics and metaproteomics to survey the molecular response of a mat-forming cyanobacterium undergoing mass cell lysis after exposure to dark and anoxic conditions. A lack of evidence for viral, bacterial, or eukaryotic antagonism contradicts commonly held beliefs on the causative agent for cyanobacterial death during dense growth. Instead, proteogenomics data indicated that lysis likely resulted from a genetically programmed response triggered by a failure to maintain osmotic pressure in the wake of severe energy limitation. Cyanobacterial DNA was rapidly degraded, yet cyanobacterial proteins remained abundant. A subset of proteins, including enzymes involved in amino acid metabolism, peptidases, toxin-antitoxin systems, and a potentially self-targeting CRISPR-Cas system, were upregulated upon lysis, indicating possible involvement in the programmed cell death response. We propose this natural form of cell death could provide new pathways for controlling harmful algal blooms and for sustainable bioproduct production.

Host translation machinery is not a barrier to phages that interact with both CPR and non-CPR bacteria

IMPORTANCE

Here, we profiled putative phages of Saccharibacteria, which are of particular importance as Saccharibacteria influence some human oral diseases. We additionally profiled putative phages of Gracilibacteria and Absconditabacteria, two Candidate Phyla Radiation (CPR) lineages of interest given their use of an alternative genetic code. Among the phages identified in this study, some are targeted by spacers from both CPR and non-CPR bacteria and others by both bacteria that use the standard genetic code as well as bacteria that use an alternative genetic code. These findings represent new insights into possible phage replication strategies and have relevance for phage therapies that seek to manipulate microbiomes containing CPR bacteria.

Top-heavy trophic structure within benthic viral dark matter

A better understanding of system-specific viral ecology in diverse environments is needed to predict patterns of virus-host trophic structure in the Anthropocene. This study characterised viral-host trophic structure within coral reef benthic cyanobacterial mats-a globally proliferating cause and consequence of coral reef degradation. We employed deep longitudinal multi-omic sequencing to characterise the viral assemblage (ssDNA, dsDNA, and dsRNA viruses) and profile lineage-specific host-virus interactions within benthic cyanobacterial mats sampled from Bonaire, Caribbean Netherlands. We recovered 11,012 unique viral populations spanning at least 10 viral families across the orders Caudovirales, Petitvirales, and Mindivirales. Gene-sharing network analyses provided evidence for extensive genomic novelty of mat viruses from reference and environmental viral sequences. Analysis of coverage ratios of viral sequences and computationally predicted hosts spanning 15 phyla and 21 classes revealed virus-host abundance (from DNA) and activity (from RNA) ratios consistently exceeding 1:1, suggesting a top-heavy intra-mat trophic structure with respect to virus-host interactions. Overall, our article contributes a curated database of viral sequences found in Caribbean coral reef benthic cyanobacterial mats (vMAT database) and provides multiple lines of field-based evidence demonstrating that viruses are active members of mat communities, with broader implications for mat functional ecology and demography.

Combined virome analysis and metagenomic sequencing to reveal the viral communities and risk of virus-associated antibiotic resistance genes during composting

The issue of antibiotic resistance genes (ARGs) pollution in manure has garnered significant attention, with viruses now being recognized as crucial carriers and disseminators of ARGs. However, the virus-associated ARG profiles and potential health risks in composts are still unclear. In this study, the viral communities and associated ARGs in biogas residue and pig faeces composts were profiled by virome analysis. The viral communities were dominated by Caudovirales, and non-thermophilic viruses were inactivated during composting. The diversity and abundance of ARGs were lower in virome than in metagenome, while ARGs' risk was greater in virome than in metagenome. There were six bacterial genera identified as viral hosts at the genomic level, Pseudomonas and Clostridium carried high-risk ARGs. Virus-associated ARGs in viral hosts had a higher risk rank than non-virus-associated ARGs. Composting reduced the diversity, abundance and risk of viral ARGs. The risk of ARGs in biogas residues was significantly lower than that of pig faeces in the initial period of composting, and the two different substracts equally less harmful after composting. These results revealed that viruses play a non-negligible role in spreading ARGs, posing high risk to environmental and human health.

PTBGRP: predicting phage-bacteria interactions with graph representation learning on microbial heterogeneous information network

Identifying the potential bacteriophages (phage) candidate to treat bacterial infections plays an essential role in the research of human pathogens. Computational approaches are recognized as a valid way to predict bacteria and target phages. However, most of the current methods only utilize lower-order biological information without considering the higher-order connectivity patterns, which helps to improve the predictive accuracy. Therefore, we developed a novel microbial heterogeneous interaction network (MHIN)-based model called PTBGRP to predict new phages for bacterial hosts. Specifically, PTBGRP first constructs an MHIN by integrating phage-bacteria interaction (PBI) and six bacteria-bacteria interaction networks with their biological attributes. Then, different representation learning methods are deployed to extract higher-level biological features and lower-level topological features from MHIN. Finally, PTBGRP employs a deep neural network as the classifier to predict unknown PBI pairs based on the fused biological information. Experiment results demonstrated that PTBGRP achieves the best performance on the corresponding ESKAPE pathogens and PBI dataset when compared with state-of-art methods. In addition, case studies of Klebsiella pneumoniae and Staphylococcus aureus further indicate that the consideration of rich heterogeneous information enables PTBGRP to accurately predict PBI from a more comprehensive perspective. The webserver of the PTBGRP predictor is freely available at http://120.77.11.78/PTBGRP/.

Long-term CRISPR locus dynamics and stable host-virus co-existence in subsurface fractured shales

Viruses are the most ubiquitous biological entities on Earth. Even so, elucidating the impact of viruses on microbial communities and associated ecosystem processes often requires identification of unambiguous host-virus linkages-an undeniable challenge in many ecosystems. Subsurface fractured shales present a unique opportunity to first make these strong linkages via spacers in CRISPR-Cas arrays and subsequently reveal complex long-term host-virus dynamics. Here, we sampled two replicated sets of fractured shale wells for nearly 800 days, resulting in 78 metagenomes from temporal sampling of six wells in the Denver-Julesburg Basin (Colorado, USA). At the community level, there was strong evidence for CRISPR-Cas defense systems being used through time and likely in response to viral interactions. Within our host genomes, represented by 202 unique MAGs, we also saw that CRISPR-Cas systems were widely encoded. Together, spacers from host CRISPR loci facilitated 2,110 CRISPR-based viral linkages across 90 host MAGs spanning 25 phyla. We observed less redundancy in host-viral linkages and fewer spacers associated with hosts from the older, more established wells, possibly reflecting enrichment of more beneficial spacers through time. Leveraging temporal patterns of host-virus linkages across differing well ages, we report how host-virus co-existence dynamics develop and converge through time, possibly reflecting selection for viruses that can evade host CRISPR-Cas systems. Together, our findings shed light on the complexities of host-virus interactions as well as long-term dynamics of CRISPR-Cas defense among diverse microbial populations.

The gut virome and the relevance of temperate phages in human health

Alterations in the gut virome impact human health. Bacteriophages, viruses that infect bacteria, dominate the gut virome and are mainly composed by virulent and temperate phages. While virulent phages exclusively replicate within and lyse their bacterial host's cell, temperate phages switch from an integrated state residing within their bacterial host's chromosome to an induced free virion state via an induction event. How often do these induction events occur and what are their implications on gut homeostasis? Here, we summarize the current knowledge of the gut virome based on metagenomics and present how the proportion of induced temperate phages varies amongst individuals, age, and disease states. Finally, we highlight the importance of building upon classical culture-dependent techniques and sequencing approaches to improve our understanding of temperate phages to enable their potential therapeutic use.

Virus impacted community adaptation in oligotrophic groundwater environment revealed by Hi-C coupled metagenomic and viromic study

Viruses play a crucial role in microbial mortality, diversity and biogeochemical cycles. Groundwater is the largest global freshwater and one of the most oligotrophic aquatic systems on Earth, but how microbial and viral communities are shaped in this special habitat is largely unexplored. In this study, we collected groundwater samples from 23 to 60 m aquifers at Yinchuan Plain, China. In total, 1920 non-reductant viral contigs were retrieved from metagenomes and viromes constructed by Illumina and Nanopore hybrid sequencing. Only 3% of them could be clustered with known viruses, most of which were Caudoviricetes. Coupling 1.2 Tb Hi-C sequencing with CRISPR matching and homology search, we connected 469 viruses with their hosts while some viral clusters presented a broad-host-range trait. Meanwhile, a large proportion of biosynthesis related auxiliary metabolism genes were identified. Those characteristics might benefit viruses for a better survival in this special oligotrophic environment. Additionally, the groundwater virome showed genomic features distinct from those of the open ocean and wastewater treatment facilities in GC distribution and unannotated gene compositions. This paper expands the current knowledge of the global viromic records and serves as a foundation for a more thorough understanding of viruses in groundwater.

GSPHI: A novel deep learning model for predicting phage-host interactions via multiple biological information

Emerging evidence suggests that due to the misuse of antibiotics, bacteriophage (phage) therapy has been recognized as one of the most promising strategies for treating human diseases infected by antibiotic-resistant bacteria. Identification of phage-host interactions (PHIs) can help to explore the mechanisms of bacterial response to phages and provide new insights into effective therapeutic approaches. Compared to conventional wet-lab experiments, computational models for predicting PHIs can not only save time and cost, but also be more efficient and economical. In this study, we developed a deep learning predictive framework called GSPHI to identify potential phage and target bacterium pairs through DNA and protein sequence information. More specifically, GSPHI first initialized the node representations of phages and target bacterial hosts via a natural language processing algorithm. Then a graph embedding algorithm structural deep network embedding (SDNE) was utilized to extract local and global information from the interaction network, and finally, a deep neural network (DNN) was applied to accurately detect the interactions between phages and their bacterial hosts. In the drug-resistant bacteria dataset ESKAPE, GSPHI achieved a prediction accuracy of 86.65 % and AUC of 0.9208 under the 5-fold cross-validation technique, significantly better than other methods. In addition, case studies in Gram-positive and negative bacterial species demonstrated that GSPHI is competent in detecting potential Phage-host interactions. Taken together, these results indicate that GSPHI can provide reasonable candidate sensitive bacteria to phages for biological experiments. The webserver of the GSPHI predictor is freely available at http://120.77.11.78/GSPHI/.

New Bacteriophages Members of the Ackermannviridae Family Specific for Klebsiella pneumoniae ST258

Background

Carbapenem-resistant Klebsiella pneumoniae, particularly isolates classified as sequence-type 258 (ST258), are multidrug-resistant strains that are strongly associated with poor-prognosis nosocomial infections, as current therapeutic options are limited and ineffective. In recent years, phage therapy has emerged as a promising treatment option for these scenarios.

Methodology and Results

We report the isolation and characterization of three new phages against Klebsiella pneumoniae ST258 strains recovered from Machángara river wastewater. These new members of the Ackermannviridae family showed stability over a wide temperature and pH range and burst sizes ranging from 6 to 44 plaque-forming units per bacteria. Their genomes were about 157 kilobases, with an average guanine-cytosine content of 46.4% and showed presence of several transfer RNAs, which also allowed us to predict in silico a lytic replicative cycle due to the presence of endolysins and lysozymes.

Conclusion

Three lytic phages of Ackermannviridae family were recovered against Klebsiella pneumoniae ST258 strains from sewage; however, further characterization is needed for future consideration as therapeutic alternatives.

Highly diverse and unknown viruses may enhance Antarctic endoliths' adaptability

BACKGROUND

Rock-dwelling microorganisms are key players in ecosystem functioning of Antarctic ice free-areas. Yet, little is known about their diversity and ecology, and further still, viruses in these communities have been largely unexplored despite important roles related to host metabolism and nutrient cycling. To begin to address this, we present a large-scale viral catalog from Antarctic rock microbial communities.

RESULTS

We performed metagenomic analyses on rocks from across Antarctica representing a broad range of environmental and spatial conditions, and which resulted in a predicted viral catalog comprising > 75,000 viral operational taxonomic units (vOTUS). We found largely undescribed, highly diverse and spatially structured virus communities which had predicted auxiliary metabolic genes (AMGs) with functions indicating that they may be potentially influencing bacterial adaptation and biogeochemistry.

CONCLUSION

This catalog lays the foundation for expanding knowledge of virosphere diversity, function, spatial ecology, and dynamics in extreme environments. This work serves as a step towards exploring adaptability of microbial communities in the face of a changing climate. Video Abstract.

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.

Pathogens and Passengers: Roles for Crustacean Zooplankton Viruses in the Global Ocean

Viruses infect all living organisms, but the viruses of most marine animals are largely unknown. Crustacean zooplankton are a functional lynchpin in marine food webs, but very few have been interrogated for their associated viruses despite the profound potential effects of viral infection. Nonetheless, it is clear that the diversity of viruses in crustacean zooplankton is enormous, including members of all realms of RNA viruses, as well as single- and double-stranded DNA viruses, in many cases representing deep branches of viral evolution. As there is clear evidence that many of these viruses infect and replicate in zooplankton species, we posit that viral infection is likely responsible for a significant portion of unexplained non-consumptive mortality in this group. In turn, this infection affects food webs and alters biogeochemical cycling. In addition to the direct impacts of infection, zooplankton can vector economically devastating viruses of finfish and other crustaceans. The dissemination of these viruses is facilitated by the movement of zooplankton vertically between epi- and mesopelagic communities through seasonal and diel vertical migration (DVM) and across long distances in ship ballast water. The large potential impact of viruses on crustacean zooplankton emphasises the need to clearly establish the relationships between specific viruses and the zooplankton they infect and investigate disease and mortality for these host-virus pairs. Such data will enable investigations into a link between viral infection and seasonal dynamics of host populations. We are only beginning to uncover the diversity and function of viruses associated with crustacean zooplankton.

Benzo[a]pyrene stress impacts adaptive strategies and ecological functions of earthworm intestinal viromes

The earthworm gut virome influences the structure and function of the gut microbiome, which in turn influences worm health and ecological functions. However, despite its ecological and soil quality implications, it remains elusive how earthworm intestinal phages respond to different environmental stress, such as soil pollution. Here we used metagenomics and metatranscriptomics to investigate interactions between the worm intestinal phages and their bacteria under different benzo[a]pyrene (BaP) concentrations. Low-level BaP (0.1 mg kg^-1) stress stimulated microbial metabolism (1.74-fold to control), and enhanced the antiphage defense system (n = 75) against infection (8 phage-host pairs). Low-level BaP exposure resulted in the highest proportion of lysogenic phages (88%), and prophages expressed auxiliary metabolic genes (AMGs) associated with nutrient transformation (e.g., amino acid metabolism). In contrast, high-level BaP exposure (200 mg kg^-1) disrupted microbial metabolism and suppressed the antiphage systems (n = 29), leading to the increase in phage-bacterium association (37 phage-host pairs) and conversion of lysogenic to lytic phages (lysogenic ratio declined to 43%). Despite fluctuating phage-bacterium interactions, phage-encoded AMGs related to microbial antioxidant and pollutant degradation were enriched, apparently to alleviate pollution stress. Overall, these findings expand our knowledge of complex phage-bacterium interactions in pollution-stressed worm guts, and deepen our understanding of the ecological and evolutionary roles of phages.

Recent advances in phage defense systems and potential overcoming strategies

Bacteriophages are effective in the prevention and control of bacteria, and many phage products have been permitted and applied in the field. Because bacteriophages are expected to replace other antimicrobial agents like antibiotics, the antibacterial effect of bacteriophage has attracted widespread attention. Recently, the diversified defense systems discovered in the target host have become potential threats to the continued effective application of phages. Therefore, a systematic summary and in-depth illustration of the interaction between phages and bacteria is conducive to the development of this biological control approach. In this review, we introduce different defense systems in bacteria against phages and emphasize newly discovered defense mechanisms in recent years. Additionally, we draw attention to the striking resemblance between defense system genes and antibiotic resistance genes, which raises concerns about the potential transfer of phage defense systems within bacterial populations and its future impact on phage efficacy. Thus, attention should be given to the effects of phage defense genes in practical applications. This article is not exhaustive, but strategies to overcome phage defense systems are also discussed to further promote more efficient use of phages.

CRISPR-resolved virus-host interactions in a municipal landfill include non-specific viruses, hyper-targeted viral populations, and interviral conflicts

Viruses are the most abundant microbial guild on the planet, impacting microbial community structure and ecosystem services. Viruses are specifically understudied in engineered environments, including examinations of their host interactions. We examined host-virus interactions via host CRISPR spacer to viral protospacer mapping in a municipal landfill across two years. Viruses comprised ~ 4% of both the unassembled reads and assembled basepairs. A total of 458 unique virus-host connections captured hyper-targeted viral populations and host CRISPR array adaptation over time. Four viruses were predicted to infect across multiple phyla, suggesting that some viruses are far less host-specific than is currently understood. We detected 161 viral elements that encode CRISPR arrays, including one with 187 spacers, the longest virally-encoded CRISPR array described to date. Virally-encoded CRISPR arrays targeted other viral elements in interviral conflicts. CRISPR-encoding proviruses integrated into host chromosomes were latent examples of CRISPR-immunity-based superinfection exclusion. The bulk of the observed virus-host interactions fit the one-virus-one-host paradigm, but with limited geographic specificity. Our networks highlight rare and previously undescribed complex interactions influencing the ecology of this dynamic engineered system. Our observations indicate landfills, as heterogeneous contaminated sites with unique selective pressures, are key locations for atypical virus-host dynamics.

Bacteriophages of the Order Crassvirales: What Do We Currently Know about This Keystone Component of the Human Gut Virome?

The order Crassvirales comprises dsDNA bacteriophages infecting bacteria in the phylum Bacteroidetes that are found in a variety of environments but are especially prevalent in the mammalian gut. This review summarises available information on the genomics, diversity, taxonomy, and ecology of this largely uncultured viral taxon. With experimental data available from a handful of cultured representatives, the review highlights key properties of virion morphology, infection, gene expression and replication processes, and phage-host dynamics.

An Overview of the Public Health Challenges in Diagnosing and Controlling Human Foodborne Pathogens

Pathogens found in food are believed to be the leading cause of foodborne illnesses; and they are considered a serious problem with global ramifications. During the last few decades, a lot of attention has been paid to determining the microorganisms that cause foodborne illnesses and developing new methods to identify them. Foodborne pathogen identification technologies have evolved rapidly over the last few decades, with the newer technologies focusing on immunoassays, genome-wide approaches, biosensors, and mass spectrometry as the primary methods of identification. Bacteriophages (phages), probiotics and prebiotics were known to have the ability to combat bacterial diseases since the turn of the 20th century. A primary focus of phage use was the development of medical therapies; however, its use quickly expanded to other applications in biotechnology and industry. A similar argument can be made with regards to the food safety industry, as diseases directly endanger the health of customers. Recently, a lot of attention has been paid to bacteriophages, probiotics and prebiotics most likely due to the exhaustion of traditional antibiotics. Reviewing a variety of current quick identification techniques is the purpose of this study. Using these techniques, we are able to quickly identify foodborne pathogenic bacteria, which forms the basis for future research advances. A review of recent studies on the use of phages, probiotics and prebiotics as a means of combating significant foodborne diseases is also presented. Furthermore, we discussed the advantages of using phages as well as the challenges they face, especially given their prevalent application in food safety.

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.

Prevalence of Viral Frequency-Dependent Infection in Coastal Marine Prokaryotes Revealed Using Monthly Time Series Virome Analysis

Viruses infecting marine prokaryotes have a large impact on the diversity and dynamics of their hosts. Model systems suggest that viral infection is frequency dependent and constrained by the virus-host encounter rate. However, it is unclear whether frequency-dependent infection is pervasive among the abundant prokaryotic populations with different temporal dynamics. To address this question, we performed a comparison of prokaryotic and viral communities using 16S rRNA amplicon and virome sequencing based on samples collected monthly for 2 years at a Japanese coastal site, Osaka Bay. Concurrent seasonal shifts observed in prokaryotic and viral community dynamics indicated that the abundance of viruses correlated with that of their predicted host phyla (or classes). Cooccurrence network analysis between abundant prokaryotes and viruses revealed 6,423 cooccurring pairs, suggesting a tight coupling of host and viral abundances and their "one-to-many" correspondence. Although stable dominant species, such as SAR11, showed few cooccurring viruses, a fast succession of their viruses suggests that viruses infecting these populations changed continuously. Our results suggest that frequency-dependent viral infection prevails in coastal marine prokaryotes regardless of host taxa and temporal dynamics. IMPORTANCE There is little room for doubt that viral infection is prevalent among abundant marine prokaryotes regardless of their taxa or growth strategy. However, comprehensive evaluations of viral infections in natural prokaryotic communities are still technically difficult. In this study, we examined viral infection in abundant prokaryotes by monitoring the monthly dynamics of prokaryotic and viral communities at a eutrophic coastal site, Osaka Bay. We compared the community dynamics of viruses with those of their putative hosts based on genome-based in silico host prediction. We observed frequent cooccurrence among the predicted virus-host pairs, suggesting that viral infection is prevalent in abundant prokaryotes regardless of their taxa or temporal dynamics. This likely indicates that frequent lysis of the abundant prokaryotes via viral infection has a considerable contribution to the biogeochemical cycling and maintenance of prokaryotic community diversity.

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.

The Human Gut Virome and Its Relationship with Nontransmissible Chronic Diseases

The human gastrointestinal tract contains large communities of microorganisms that are in constant interaction with the host, playing an essential role in the regulation of several metabolic processes. Among the gut microbial communities, the gut bacteriome has been most widely studied in recent decades. However, in recent years, there has been increasing interest in studying the influences that other microbial groups can exert on the host. Among them, the gut virome is attracting great interest because viruses can interact with the host immune system and metabolic functions; this is also the case for phages, which interact with the bacterial microbiota. The antecedents of virome-rectification-based therapies among various diseases were also investigated. In the near future, stool metagenomic investigation should include the identification of bacteria and phages, as well as their correlation networks, to better understand gut microbiota activity in metabolic disease progression.

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

The rise of global temperature causes the degradation of the substantial reserves of carbon (C) stored in tundra soils, in which microbial processes play critical roles. Viruses are known to influence the soil C cycle by encoding auxiliary metabolic genes and infecting key microorganisms, but their regulation of microbial communities under climate warming remains unexplored. In this study, we evaluated the responses of viral communities for about 5 years of experimental warming at two depths (15 to 25 cm and 45 to 55 cm) in the Alaskan permafrost region. Our results showed that the viral community and functional gene composition and abundances (including viral functional genes related to replication, structure, infection, and lysis) were significantly influenced by environmental conditions such as total nitrogen (N), total C, and soil thawing duration. Although long-term warming did not impact the viral community composition at the two depths, some glycoside hydrolases encoded by viruses were more abundant at both depths of the warmed plots. With the continuous reduction of total C, viruses may alleviate methane release by altering infection strategies on methanogens. Importantly, viruses can adopt lysogenic and lytic lifestyles to manipulate microbial communities at different soil depths, respectively, which could be one of the major factors causing the differences in microbial responses to warming. This study provides a new ecological perspective on how viruses regulate the responses of microbes to warming at community and functional scales. IMPORTANCE Permafrost thawing causes microbial release of greenhouse gases, exacerbating climate warming. Some previous studies examined the responses of the microbial communities and functions to warming in permafrost region, but the roles of viruses in mediating the responses of microbial communities to warming are poorly understood. This study revealed that warming induced changes in some viral functional classes and in the virus/microbe ratios for specific lineages, which might influence the entire microbial community. Furthermore, differences in viral communities and functions, along with soil depths, are important factors influencing microbial responses to warming. Collectively, our study revealed the regulation of microbial communities by viruses and demonstrated the importance of viruses in the microbial ecology research.

Four principles to establish a universal virus taxonomy

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., "arboviruses"), infecting a certain type of host (e.g., "mycoviruses," "bacteriophages") or displaying specific pathogenicity (e.g., "human immunodeficiency viruses"), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

High-resolution metagenomic reconstruction of the freshwater spring bloom

BACKGROUND

The phytoplankton spring bloom in freshwater habitats is a complex, recurring, and dynamic ecological spectacle that unfolds at multiple biological scales. Although enormous taxonomic shifts in microbial assemblages during and after the bloom have been reported, genomic information on the microbial community of the spring bloom remains scarce.

RESULTS

We performed a high-resolution spatio-temporal sampling of the spring bloom in a freshwater reservoir and describe a multitude of previously unknown taxa using metagenome-assembled genomes of eukaryotes, prokaryotes, and viruses in combination with a broad array of methodologies. The recovered genomes reveal multiple distributional dynamics for several bacterial groups with progressively increasing stratification. Analyses of abundances of metagenome-assembled genomes in concert with CARD-FISH revealed remarkably similar in situ doubling time estimates for dominant genome-streamlined microbial lineages. Discordance between quantitations of cryptophytes arising from sequence data and microscopic identification suggested the presence of hidden, yet extremely abundant aplastidic cryptophytes that were confirmed by CARD-FISH analyses. Aplastidic cryptophytes are prevalent throughout the water column but have never been considered in prior models of plankton dynamics. We also recovered the first metagenomic-assembled genomes of freshwater protists (a diatom and a haptophyte) along with thousands of giant viral genomic contigs, some of which appeared similar to viruses infecting haptophytes but owing to lack of known representatives, most remained without any indication of their hosts. The contrasting distribution of giant viruses that are present in the entire water column to that of parasitic perkinsids residing largely in deeper waters allows us to propose giant viruses as the biological agents of top-down control and bloom collapse, likely in combination with bottom-up factors like a nutrient limitation.

CONCLUSION

We reconstructed thousands of genomes of microbes and viruses from a freshwater spring bloom and show that such large-scale genome recovery allows tracking of planktonic succession in great detail. However, integration of metagenomic information with other methodologies (e.g., microscopy, CARD-FISH) remains critical to reveal diverse phenomena (e.g., distributional patterns, in situ doubling times) and novel participants (e.g., aplastidic cryptophytes) and to further refine existing ecological models (e.g., factors affecting bloom collapse). This work provides a genomic foundation for future approaches towards a fine-scale characterization of the organisms in relation to the rapidly changing environment during the course of the freshwater spring bloom. Video Abstract.

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.