Alignment-free $d_2^*$ oligonucleotide frequency dissimilarity measure improves prediction of hosts from metagenomically-derived viral sequences

Viral communities in a pH>10 serpentinite-like environment: insight into diversity and potential roles in modulating the microbiomes by bioactive vitamin B9 synthesis

Viral communities exist in a variety of ecosystems and play significant roles in mediating biogeochemical processes, whereas viruses inhabiting strongly alkaline geochemical systems remain underexplored. In this study, the viral diversity, potential functionalities, and virus-host interactions in a strongly alkaline environment (pH = 10.4-12.4) exposed to the leachates derived from the serpentinization-like reactions of smelting slags were investigated. The viral populations (e.g., Herelleviridae, Queuovirinae, and Inoviridae) were closely associated with the dominating prokaryotic hosts (e.g., Meiothermus, Trueperaceae, and Serpentinomonas) in this ultrabasic environment. Auxiliary metabolic genes (AMGs) suggested that viruses may enhance hosts' fitness by facilitating cofactor biosynthesis, hydrogen metabolism, and carbon cycling. To evaluate the activity of synthesis of essential cofactor vitamin B9 by the viruses, a viral folA (vfolA) gene encoding dihydrofolate reductase (DHFR) was introduced into a thymidine-auxotrophic strain Escherichia coli MG1655 ΔfolA mutant, which restored the growth of the latter in the absence of thymidine. Notably, the homologs of the validated vDHFR were globally distributed in the viromes across various ecosystems. The present study sheds new light on the unique viral communities in hyperalkaline ecosystems and their potential beneficial impacts on the coexisting microbial consortia by supplying essential cofactors.

IMPORTANCE

This study presents a comprehensive investigation into the diversity, potential functionalities, and virus-microbe interactions in an artificially induced strongly alkaline environment. Functional validation of the detected viral folA genes encoding dihydrofolate reductase substantiated the synthesis of essential cofactors by viruses, which may be ubiquitous, considering the broad distribution of the viral genes associated with folate cycling.

Effects of vegetation cover and aquaculture pollution on viral assemblages in mangroves sediments

Mangrove forests, a critical coastal ecosystem, face numerous anthropogenic threats, particularly from aquaculture activities. Despite the acknowledged significance of viruses in local and global biogeochemical cycles, there is limited knowledge regarding the community structure, genomic diversity, and ecological roles of viruses in mangrove forests ecosystems, especially regarding their responses to aquaculture. In this study, we identified 17,755 viral operational taxonomic units (vOTUs) from nine sediments viromes across three distinct ecological regions of the mangrove forests ecosystem: mangrove, bare flat, and aquaculture regions. Viral assemblages varied among three regions, and the pathogenic viruses associated with marine animals, such as the white spot syndrome virus (WSSV) from Nimaviridae, were identified in this study. The relative abundance of Nimaviridae in the bare flat region was higher than in other regions. Furthermore, viruses in distinct mangrove forests sediments regions have adapted to their environments by adopting distinct survival strategies and encoding various auxiliary metabolic genes involved in carbon metabolism and antibiotic resistance. These adaptations may have profound impacts on biogeochemical cycles. This study provides the first insights into the effects of vegetation cover and aquaculture on the community structure and ecological roles of viruses in mangrove forests sediments. These findings are crucial for understanding the risks posed by anthropogenic threats to mangrove forests ecosystems and informing effective management strategies.

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.

Temporal turnover of viral biodiversity and functional potential in intertidal wetlands

As the central members of the microbiome networks, viruses regulate the composition of microbial communities and drive the nutrient cycles of ecosystems by lysing host cells. Therefore, uncovering the dynamic patterns and the underlying ecological mechanisms mediating the tiniest viral communities across space and through time in natural ecosystems is of crucial importance for better understanding the complex microbial world. Here, the temporal dynamics of intertidal viral communities were investigated via a time-series sampling effort. A total of 1911 viral operational taxonomic units were recovered from 36 bimonthly collected shotgun metagenomes. Functionally important auxiliary metabolic genes involved in carbohydrate, sulfur, and phosphorus metabolism were detected, some of which (e.g., cysH gene) were stably present within viral genomes over time. Over the sampling period, strong and comparable temporal turnovers were observed for intertidal viromes and their host microbes. Winter was determined as the pivotal point for the shifts in viral diversity patterns. Notably, the viral micro-diversity covaried with the macro-diversity, following similar temporal patterns. The relative abundances of viral taxa also covaried with their host prokaryotes. Meanwhile, the virus-host relationships at the whole community level were relatively stable. Further statistical analyses demonstrated that the dynamic patterns of viral communities were highly deterministic, for which temperature was the major driver. This study provided valuable mechanistic insights into the temporal turnover of viral communities in complex ecosystems such as intertidal wetlands.

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.

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.

Unsupervised AI reveals insect species-specific genome signatures

Insects are a highly diverse phylogeny and possess a wide variety of traits, including the presence or absence of wings and metamorphosis. These diverse traits are of great interest for studying genome evolution, and numerous comparative genomic studies have examined a wide phylogenetic range of insects. Here, we analyzed 22 insects belonging to a wide phylogenetic range (Endopterygota, Paraneoptera, Polyneoptera, Palaeoptera, and other insects) by using a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions in their genomic fragments (100-kb or 1-Mb sequences), which is an unsupervised machine learning algorithm that can extract species-specific characteristics of the oligonucleotide compositions (genome signatures). The genome signature is of particular interest in terms of the mechanisms and biological significance that have caused the species-specific difference, and can be used as a powerful search needle to explore the various roles of genome sequences other than protein coding, and can be used to unveil mysteries hidden in the genome sequence. Since BLSOM is an unsupervised clustering method, the clustering of sequences was performed based on the oligonucleotide composition alone, without providing information about the species from which each fragment sequence was derived. Therefore, not only the interspecies separation, but also the intraspecies separation can be achieved. Here, we have revealed the specific genomic regions with oligonucleotide compositions distinct from the usual sequences of each insect genome, e.g., Mb-level structures found for a grasshopper Schistocerca americana. One aim of this study was to compare the genome characteristics of insects with those of vertebrates, especially humans, which are phylogenetically distant from insects. Recently, humans seem to be the "model organism" for which a large amount of information has been accumulated using a variety of cutting-edge and high-throughput technologies. Therefore, it is reasonable to use the abundant information from humans to study insect lineages. The specific regions of Mb length with distinct oligonucleotide compositions have also been previously observed in the human genome. These regions were enriched by transcription factor binding motifs (TFBSs) and hypothesized to be involved in the three-dimensional arrangement of chromosomal DNA in interphase nuclei. The present study characterized the species-specific oligonucleotide compositions (i.e., genome signatures) in insect genomes and identified specific genomic regions with distinct oligonucleotide compositions.

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.

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.

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.

Diversities and interactions of phages and bacteria in deep-sea sediments as revealed by metagenomics

Phages are found virtually everywhere, even in extreme environments, and are extremely diverse both in their virion structures and in their genomic content. They are thought to shape the taxonomic and functional composition of microbial communities as well as their stability. A number of studies on laboratory culture and viral metagenomic research provide deeper insights into the abundance, diversity, distribution, and interaction with hosts of phages across a wide range of ecosystems. Although most of these studies focus on easily accessible samples, such as soils, lakes, and shallow oceans, little is known about bathypelagic phages. In this study, through analyzing the 16S rRNA sequencing and viral metagenomic sequencing data of 25 samples collected from five different bathypelagic ecosystems, we detected a high diversity of bacteria and phages, particularly in the cold seep and hydrothermal vent ecosystems, which have stable chemical energy. The relative abundance of phages in these ecosystems was higher than in other three abyssal ecosystems. The low phage/host ratios obtained from host prediction were different from shallow ecosystems and indicated the prevalence of prophages, suggesting the complexity of phage-bacteria interactions in abyssal ecosystems. In the correlation analysis, we revealed several phages-bacteria interaction networks of potential ecological relevance. Our study contributes to a better understanding of the interactions between bathypelagic bacteria and their phages.

High niche specificity and host genetic diversity of groundwater viruses

Viruses are key members of microbial communities that exert control over host abundance and metabolism, thereby influencing ecosystem processes and biogeochemical cycles. Aquifers are known to host taxonomically diverse microbial life, yet little is known about viruses infecting groundwater microbial communities. Here, we analysed 16 metagenomes from a broad range of groundwater physicochemistries. We recovered 1571 viral genomes that clustered into 468 high-quality viral operational taxonomic units. At least 15% were observed to be transcriptionally active, although lysis was likely constrained by the resource-limited groundwater environment. Most were unclassified (95%), and the remaining 5% were Caudoviricetes. Comparisons with viruses inhabiting other aquifers revealed no shared species, indicating substantial unexplored viral diversity. In silico predictions linked 22.4% of the viruses to microbial host populations, including to ultra-small prokaryotes, such as Patescibacteria and Nanoarchaeota. Many predicted hosts were associated with the biogeochemical cycling of carbon, nitrogen, and sulfur. Metabolic predictions revealed the presence of 205 putative auxiliary metabolic genes, involved in diverse processes associated with the utilization of the host's intracellular resources for biosynthesis and transformation reactions, including those involved in nucleotide sugar, glycan, cofactor, and vitamin metabolism. Viruses, prokaryotes overall, and predicted prokaryotic hosts exhibited narrow spatial distributions, and relative abundance correlations with the same groundwater parameters (e.g. dissolved oxygen, nitrate, and iron), consistent with host control over viral distributions. Results provide insights into underexplored groundwater viruses, and indicate the large extent to which viruses may manipulate microbial communities and biogeochemistry in the terrestrial subsurface.

Freshwater Viral Metagenome Analyses Targeting dsDNA Viruses

Viral metagenomics is one of the most widely used approaches to study viral population genomics. With the recent development of bioinformatic tools, the number of molecular biological methods, programs, and software to analyze viral metagenome data have greatly increased. Here, we describe the basic analysis workflow along with bioinformatic tools that can be used to analyze viral metagenome data. Although this chapter assumes that the viral metagenome data are prepared from the freshwater samples and are subjected to dsDNA sequencing, the protocol can be applied and modified for other types of metagenome data collected from a variety of sources.

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.

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.

Zea mays genotype influences microbial and viral rhizobiome community structure

Plant genotype is recognized to contribute to variations in microbial community structure in the rhizosphere, soil adherent to roots. However, the extent to which the viral community varies has remained poorly understood and has the potential to contribute to variation in soil microbial communities. Here we cultivated replicates of two Zea mays genotypes, parviglumis and B73, in a greenhouse and harvested the rhizobiome (rhizoplane and rhizosphere) to identify the abundance of cells and viruses as well as rhizobiome microbial and viral community using 16S rRNA gene amplicon sequencing and genome resolved metagenomics. Our results demonstrated that viruses exceeded microbial abundance in the rhizobiome of parviglumis and B73 with a significant variation in both the microbial and viral community between the two genotypes. Of the viral contigs identified only 4.5% (n = 7) of total viral contigs were shared between the two genotypes, demonstrating that plants even at the level of genotype can significantly alter the surrounding soil viral community. An auxiliary metabolic gene associated with glycoside hydrolase (GH5) degradation was identified in one viral metagenome-assembled genome (vOTU) identified in the B73 rhizobiome infecting Propionibacteriaceae (Actinobacteriota) further demonstrating the viral contribution in metabolic potential for carbohydrate degradation and carbon cycling in the rhizosphere. This variation demonstrates the potential of plant genotype to contribute to microbial and viral heterogeneity in soil systems and harbors genes capable of contributing to carbon cycling in the rhizosphere.

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.

Hi-C metagenome sequencing reveals soil phage-host interactions

Bacteriophages are abundant in soils. However, the majority are uncharacterized, and their hosts are unknown. Here, we apply high-throughput chromosome conformation capture (Hi-C) to directly capture phage-host relationships. Some hosts have high centralities in bacterial community co-occurrence networks, suggesting phage infections have an important impact on the soil bacterial community interactions. We observe increased average viral copies per host (VPH) and decreased viral transcriptional activity following a two-week soil-drying incubation, indicating an increase in lysogenic infections. Soil drying also alters the observed phage host range. A significant negative correlation between VPH and host abundance prior to drying indicates more lytic infections result in more host death and inversely influence host abundance. This study provides empirical evidence of phage-mediated bacterial population dynamics in soil by directly capturing specific phage-host interactions.

Weighted hypergraph learning and adaptive inductive matrix completion for SARS-CoV-2 drug repositioning

MOTIVATION

The outbreak of the human coronavirus (SARS-CoV-2) has placed a huge burden on public health and the world economy. Compared with de novo drug discovery, drug repurposing is a promising therapeutic strategy that facilitates rapid clinical treatment decisions, shortens the development process, and reduces costs.

RESULTS

In this study, we propose a weighted hypergraph learning and adaptive inductive matrix completion method, WHAIMC, for predicting potential virus-drug associations. Firstly, we integrate multi-source data to describe viruses and drugs from multiple perspectives, including drug chemical structures, drug targets, virus complete genome sequences, and virus-drug associations. Then, WHAIMC establishes an adaptive inductive matrix completion model to improve performance through adaptive learning of similarity relations. Finally, WHAIMC introduces weighted hypergraph learning into adaptive inductive matrix completion to capture higher-order relationships of viruses (or drugs). The results showed that WHAIMC had a strong predictive performance for new virus-drug associations, new viruses, and new drugs. The case study further demonstrates that WHAIMC is highly effective for repositioning antiviral drugs against SARS-CoV-2 and provides a new perspective for virus-drug association prediction. The code and data in this study is freely available at https://github.com/Mayingjun20179/WHAIMC.

Marine viruses disperse bidirectionally along the natural water cycle

Marine viruses in seawater have frequently been studied, yet their dispersal from neuston ecosystems at the air-sea interface towards the atmosphere remains a knowledge gap. Here, we show that 6.2% of the studied virus population were shared between air-sea interface ecosystems and rainwater. Virus enrichment in the 1-mm thin surface microlayer and sea foams happened selectively, and variant analysis proved virus transfer to aerosols collected at ~2 m height above sea level and rain. Viruses detected in rain and these aerosols showed a significantly higher percent G/C base content compared to marine viruses. CRISPR spacer matches of marine prokaryotes to foreign viruses from rainwater prove regular virus-host encounters at the air-sea interface. Our findings on aerosolization, adaptations, and dispersal support transmission of viruses along the natural water cycle.

The multi-kingdom microbiome of the goat gastrointestinal tract

BACKGROUND

Goat is an important livestock worldwide, which plays an indispensable role in human life by providing meat, milk, fiber, and pelts. Despite recent significant advances in microbiome studies, a comprehensive survey on the goat microbiomes covering gastrointestinal tract (GIT) sites, developmental stages, feeding styles, and geographical factors is still unavailable. Here, we surveyed its multi-kingdom microbial communities using 497 samples from ten sites along the goat GIT.

RESULTS

We reconstructed a goat multi-kingdom microbiome catalog (GMMC) including 4004 bacterial, 71 archaeal, and 7204 viral genomes and annotated over 4,817,256 non-redundant protein-coding genes. We revealed patterns of feeding-driven microbial community dynamics along the goat GIT sites which were likely associated with gastrointestinal food digestion and absorption capabilities and disease risks, and identified an abundance of large intestine-enriched genera involved in plant fiber digestion. We quantified the effects of various factors affecting the distribution and abundance of methane-producing microbes including the GIT site, age, feeding style, and geography, and identified 68 virulent viruses targeting the methane producers via a comprehensive virus-bacterium/archaea interaction network.

CONCLUSIONS

Together, our GMMC catalog provides functional insights of the goat GIT microbiota through microbiome-host interactions and paves the way to microbial interventions for better goat and eco-environmental qualities. Video Abstract.

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.

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/.

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.

Ecogenomics and cultivation reveal distinctive viral-bacterial communities in the surface microlayer of a Baltic Sea slick

Visible surface films, termed slicks, can extensively cover freshwater and marine ecosystems, with coastal regions being particularly susceptible to their presence. The sea-surface microlayer (SML), the upper 1-mm at the air-water interface in slicks (herein slick SML) harbors a distinctive bacterial community, but generally little is known about SML viruses. Using flow cytometry, metagenomics, and cultivation, we characterized viruses and bacteria in a brackish slick SML in comparison to non-slick SML as well as seawater below slick and non-slick areas (subsurface water = SSW). Size-fractionated filtration of all samples distinguished viral attachment to hosts and particles. The slick SML contained higher abundances of virus-like particles, prokaryotic cells, and dissolved organic carbon compared to non-slick SML and SSW. The community of 428 viral operational taxonomic units (vOTUs), 426 predicted as lytic, distinctly differed across all size fractions in the slick SML compared to non-slick SML and SSW. Specific metabolic profiles of bacterial metagenome-assembled genomes and isolates in the slick SML included a prevalence of genes encoding motility and carbohydrate-active enzymes (CAZymes). Several vOTUs were enriched in slick SML, and many virus variants were associated with particles. Nine vOTUs were only found in slick SML, six of them being targeted by slick SML-specific clustered-regularly interspaced short palindromic repeats (CRISPR) spacers likely originating from Gammaproteobacteria. Moreover, isolation of three previously unknown lytic phages for Alishewanella sp. and Pseudoalteromonas tunicata, abundant and actively replicating slick SML bacteria, suggests that viral activity in slicks contributes to biogeochemical cycling in coastal ecosystems.

Lower viral evolutionary pressure under stable versus fluctuating conditions in subzero Arctic brines

BACKGROUND

Climate change threatens Earth's ice-based ecosystems which currently offer archives and eco-evolutionary experiments in the extreme. Arctic cryopeg brine (marine-derived, within permafrost) and sea ice brine, similar in subzero temperature and high salinity but different in temporal stability, are inhabited by microbes adapted to these extreme conditions. However, little is known about their viruses (community composition, diversity, interaction with hosts, or evolution) or how they might respond to geologically stable cryopeg versus fluctuating sea ice conditions.

RESULTS

We used long- and short-read viromics and metatranscriptomics to study viruses in Arctic cryopeg brine, sea ice brine, and underlying seawater, recovering 11,088 vOTUs (~species-level taxonomic unit), a 4.4-fold increase of known viruses in these brines. More specifically, the long-read-powered viromes doubled the number of longer (≥25 kb) vOTUs generated and recovered more hypervariable regions by >5-fold compared to short-read viromes. Distribution assessment, by comparing to known viruses in public databases, supported that cryopeg brine viruses were of marine origin yet distinct from either sea ice brine or seawater viruses, while 94% of sea ice brine viruses were also present in seawater. A virus-encoded, ecologically important exopolysaccharide biosynthesis gene was identified, and many viruses (~half of metatranscriptome-inferred "active" vOTUs) were predicted as actively infecting the dominant microbial genera Marinobacter and Polaribacter in cryopeg and sea ice brines, respectively. Evolutionarily, microdiversity (intra-species genetic variations) analyses suggested that viruses within the stable cryopeg brine were under significantly lower evolutionary pressures than those in the fluctuating sea ice environment, while many sea ice brine virus-tail genes were under positive selection, indicating virus-host co-evolutionary arms races.

CONCLUSIONS

Our results confirmed the benefits of long-read-powered viromics in understanding the environmental virosphere through significantly improved genomic recovery, expanding viral discovery and the potential for biological inference. Evidence of viruses actively infecting the dominant microbes in subzero brines and modulating host metabolism underscored the potential impact of viruses on these remote and underexplored extreme ecosystems. Microdiversity results shed light on different strategies viruses use to evolve and adapt when extreme conditions are stable versus fluctuating. Together, these findings verify the value of long-read-powered viromics and provide foundational data on viral evolution and virus-microbe interactions in Earth's destabilized and rapidly disappearing cryosphere. Video Abstract.

Comparative analysis of gut DNA viromes in wild and captive Himalayan vultures

Introduction

Himalayan vultures (Gyps hinalayensis) are widely distributed on the Qinghai-Tibetan Plateau and play a crucial role in maintaining the ecological balance by feeding on decayed corpses of wild and domestic animals. Large-scale culture and metagenomics studies have broadened our understanding of viral diversity in animals' gastrointestinal tracts. However, despite the importance of gut viral communities in regulating bacterial diversity and performing symbiotic functions, no gut viral study has been conducted on Himalayan vultures. Furthermore, the impact of captivity on the gut virome of these vultures remains unknown.

Methods

In this study, metagenomic sequencing methods targeting DNA of virus-like particles enriched from feces were used to characterize the gut DNA viromes of wild and captive Himalayan vultures.

Results

In total, 22,938 unique viral operational taxonomic units (vOTUs) were identified and assigned to 140 viral genera in 41 viral families. These families included viruses associated with bacteria, animals, plants, insects, and archaea. Phage communities, including Siphoviridae, Microviridae, Myoviridae, Inoviridae, and Herelleviridae, dominated the gut virome of Himalayan vultures. Wild vultures exhibited higher viral richness and diversity compared with those in captivity. The functional capacity of the gut virome was characterized by identifying 93 KEGG pathways, which were significantly enriched in metabolism and genetic information processing. Abundant auxiliary metabolic genes, such as carbohydrate-active enzyme, and antibiotic resistance genes, were also found in the vultures' gut virome.

Discussion

Our findings reveal the complex and diverse viral community present in the gut virome of Himalayan vultures, which varies between wild, and captive states. The DNA virome dataset establishes a baseline for the vultures' gut virome and will serve as a reference for future virus isolation and cultivation. Understanding the impact of captivity on the gut virome contributes to our knowledge of vultures' response to captivity and aids in optimizing their rehabilitation and implementing protective measures.

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.

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/.

Exposing new taxonomic variation with inflammation - a murine model-specific genome database for gut microbiome researchers

BACKGROUND

The murine CBA/J mouse model widely supports immunology and enteric pathogen research. This model has illuminated Salmonella interactions with the gut microbiome since pathogen proliferation does not require disruptive pretreatment of the native microbiota, nor does it become systemic, thereby representing an analog to gastroenteritis disease progression in humans. Despite the value to broad research communities, microbiota in CBA/J mice are not represented in current murine microbiome genome catalogs.

RESULTS

Here we present the first microbial and viral genomic catalog of the CBA/J murine gut microbiome. Using fecal microbial communities from untreated and Salmonella-infected, highly inflamed mice, we performed genomic reconstruction to determine the impacts on gut microbiome membership and functional potential. From high depth whole community sequencing (~ 42.4 Gbps/sample), we reconstructed 2281 bacterial and 4516 viral draft genomes. Salmonella challenge significantly altered gut membership in CBA/J mice, revealing 30 genera and 98 species that were conditionally rare and unsampled in non-inflamed mice. Additionally, inflamed communities were depleted in microbial genes that modulate host anti-inflammatory pathways and enriched in genes for respiratory energy generation. Our findings suggest decreases in butyrate concentrations during Salmonella infection corresponded to reductions in the relative abundance in members of the Alistipes. Strain-level comparison of CBA/J microbial genomes to prominent murine gut microbiome databases identified newly sampled lineages in this resource, while comparisons to human gut microbiomes extended the host relevance of dominant CBA/J inflammation-resistant strains.

CONCLUSIONS

This CBA/J microbiome database provides the first genomic sampling of relevant, uncultivated microorganisms within the gut from this widely used laboratory model. Using this resource, we curated a functional, strain-resolved view on how Salmonella remodels intact murine gut communities, advancing pathobiome understanding beyond inferences from prior amplicon-based approaches. Salmonella-induced inflammation suppressed Alistipes and other dominant members, while rarer commensals like Lactobacillus and Enterococcus endure. The rare and novel species sampled across this inflammation gradient advance the utility of this microbiome resource to benefit the broad research needs of the CBA/J scientific community, and those using murine models for understanding the impact of inflammation on the gut microbiome more generally. 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.

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream

Although river ecosystems comprise less than 1% of Earth's total non-glaciated area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. As a result, the relevance of microbiome interactions and the impacts they have over time on biogeochemical cycles are poorly understood. To assess how viral and microbial communities change over time, we sampled surface water and pore water compartments of the wastewater-impacted River Erpe in Germany every 3 hours over a 48-hour period resulting in 32 metagenomes paired to geochemical and metabolite measurements. We reconstructed 6,500 viral and 1,033 microbial genomes and found distinct communities associated with each river compartment. We show that 17% of our vMAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to carbon and nitrogen cycling. Together, these findings demonstrate that microbial and viral communities in surface waters of this urban river can exist as stable communities along a flowing river; and raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

Microbial density-dependent viral dynamics and low activity of temperate phages in the activated sludge process

The ecological behavior of bacteriophages (phages), the most abundant biological entity in wastewater treatment systems, is poorly understood, especially that of temperate phages. Here, the temporal dynamics of lytic and temperate phages in a laboratory-scale activated sludge reactor with a sludge bulking issue was investigated using coupled sludge metagenomic and viromic analyses. The lysogenic fragments (prophages) identified were widely distributed in the reconstructed metagenome-assembled genomes (61.7%, n = 227). However, only 12.3% of the identified prophages experienced lysogenic-lytic switching, and the abundance contribution of prophages to free virus communities was only 0.02-0.3%, indicating low activity of temperate phages. Although the sludge community changed dramatically during reactor operation, no massive prophage induction events were detected. Statistical analyses showed strong correlations between sludge concentration and free virus and temperate phage communities, suggesting microbial density-dependent virus dynamics in the sludge microbiota.

Viruses Regulate Microbial Community Assembly Together with Environmental Factors in Acid Mine Drainage

Viruses are widespread in various ecosystems, and they play important roles in regulating the microbial community via host-virus interactions. Recently, metagenomic studies showed that there are extremely diverse viruses in different environments from the ocean to the human gut, but the influences of viral communities on microbial communities are poorly understood, especially in extreme environments. Here, we used metagenomics to characterize microbial communities and viral communities in acid mine drainage (AMD) and evaluated how viruses shape microbial community constrained by the harsh environments. Our results showed that AMD viral communities are significantly associated with the microbial communities, and viral diversity has positive correlations with microbial diversity. Viral community explained more variations of microbial community composition than environmental factors in AMD of a polymetallic mine. Moreover, we found that viruses harboring adaptive genes regulate a relative abundance of hosts under the modulation of environmental factors, such as pH. We also observed that viral diversity has significant correlations with the global properties of microbial cooccurrence networks, such as modularity. In addition, the results of null modeling analyses revealed that viruses significantly affect microbial community phylogeny and play important roles in regulating ecological processes of community assembly, such as dispersal limitation and homogenous dispersal. Together, these results revealed that AMD viruses are critical forces driving microbial network and community assembly via host-virus interactions. IMPORTANCE Viruses as mobile genetic elements play critical roles in the adaptive evolution of their hosts in extreme environments. However, how viruses further influence microbial community structure and assembly is still unclear. A recent metagenomic study observed diverse viruses unexplored in acid mine drainage, revealing the associations between the viral community and environmental factors. Here, we showed that viruses together with environmental factors can constrain the relative abundance of host and microbial community assembly in AMD of copper mines and polymetallic mines. Our results highlight the importance of viruses in shaping the microbial community from the individual host level to the community level.

CrAssphage May Be Viable Markers of Contamination in Pristine and Contaminated River Water

Viruses are the most biologically abundant entities and may be ideal indicators of fecal pollutants in water. Anthropogenic activities have triggered drastic ecosystem changes in rivers, leading to substantial shifts in chemical and biological attributes. Here, we evaluate the viability of using the presence of crAssphage as indicators of fecal contamination in South African rivers. Shotgun analysis revealed diverse crAssphage viruses in these rivers, which are impacted by chemical and biological pollution. Overall, the diversity and relative abundances of these viruses was higher in contaminated sites compared to pristine locations. In contrast to fecal coliform counts, crAssphage sequences were detected in pristine rivers, supporting the assertion that the afore mentioned marker may be a more accurate indicator of fecal contamination. Our data demonstrate the presence of diverse putative hosts which includes members of the phyla Bacteroidota, Pseudomonadota, Verrucomicrobiota, and Bacillota. Phylogenetic analysis revealed novel subfamilies, suggesting that rivers potentially harbor distinct and uncharacterized clades of crAssphage. These data provide the first insights regarding the diversity, distribution, and functional roles of crAssphage in rivers. Taken together, the results support the potential application of crAssphage as viable markers for water quality monitoring. IMPORTANCE Rivers support substantial populations and provide important ecosystem services. Despite the application of fecal coliform tests and other markers, we lack rapid and reproducible approaches for determining fecal contamination in rivers. Waterborne viral outbreaks have been reported even after fecal indicator bacteria (FIB) were suggested to be absent or below regulated levels of coliforms. This indicates a need to develop and apply improved indicators of pollutants in aquatic ecosystems. Here, we evaluate the viability of crAssphage as indicators of fecal contamination in two South African rivers. We assess the abundance, distribution, and diversity of these viruses in sites that had been predicted pristine or contaminated by FIB analysis. We show that crAssphage are ideal and sensitive markers for fecal contamination and describe novel clades of crAss-like phages. Known crAss-like subfamilies were unrepresented in our data, suggesting that the diversity of these viruses may reflect geographic locality and dependence.

Viral Community Structure and Potential Functions in the Dried-Out Aral Sea Basin Change along a Desiccation Gradient

The dried-out Aral Sea basin represents an extreme environment due to a man-made ecological disaster. Studies conducted in this unique environment revealed high levels of pollution and a specifically adapted microbiota; however, viral populations remained entirely unexplored. By employing an in-depth analysis based on the sequencing of metagenomic DNA recovered from rhizosphere samples of Suaeda acuminata (C. A. Mey.) Moq. along a desiccation gradient of 5, 10, and 40 years, we detected a diverse viral community comprising 674 viral populations (viral operational taxonomic units [vOTUs]) dominated by Caudovirales. Targeted analyses highlighted that viral populations in this habitat are subjected to certain dynamics that are driven mainly by the gradient of desiccation, the corresponding salinity, and the rhizosphere bacterial populations. In silico predictions linked the viruses to dominant prokaryotic taxa in the Aral Sea basin, such as Gammaproteobacteria, Actinomycetia, and Bacilli. The lysogenic lifestyle was predicted to be predominant in areas that dried out 5 years ago, representing the early revegetation phase. Metabolic prediction of viral auxiliary metabolic genes (AMGs) suggests that viruses may play a role in the biogeochemical cycles, stress resilience, and competitiveness of their hosts due to the presence of genes that are involved in biofilm formation. Overall, our study provides important insights into viral ecology in an extreme environment and expands our knowledge related to virus occurrence in terrestrial systems. IMPORTANCE Environmental viruses have added a wealth of knowledge to ecological studies with the emergence of metagenomic technology and approaches. They are also becoming recognized as important genetic repositories that underpin the functioning of terrestrial ecosystems but have remain moslty unexplored. Using shotgun metagenome sequencing and bioinformatic tools, we found that the viral community structure was affected during natural revegetation in the dried-up Aral Sea area, a model habitat for investigating natural ecological restoration but still understudied. In this study, we highlight the importance of viruses, elements that are overlooked, for their potential contribution to terrestrial ecosystems, i.e., nutrient cycles, stress resilience, and host competitiveness, during natural revegetation.

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.

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.

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.

Understanding Bacteriophage Tail Fiber Interaction with Host Surface Receptor: The Key “Blueprint” for Reprogramming Phage Host Range

Bacteriophages (phages), as natural antibacterial agents, are being rediscovered because of the growing threat of multi- and pan-drug-resistant bacterial pathogens globally. However, with an estimated 10³¹ phages on the planet, finding the right phage to recognize a specific bacterial host is like looking for a needle in a trillion haystacks. The host range of a phage is primarily determined by phage tail fibers (or spikes), which initially mediate reversible and specific recognition and adsorption by susceptible bacteria. Recent significant advances at single-molecule and atomic levels have begun to unravel the structural organization of tail fibers and underlying mechanisms of phage–host interactions. Here, we discuss the molecular mechanisms and models of the tail fibers of the well-characterized T4 phage’s interaction with host surface receptors. Structure–function knowledge of tail fibers will pave the way for reprogramming phage host range and will bring future benefits through more-effective phage therapy in medicine. Furthermore, the design strategies of tail fiber engineering are briefly summarized, including machine-learning-assisted engineering inspired by the increasingly enormous amount of phage genetic information.

Microbiome-phage interactions in inflammatory bowel disease

BACKGROUND

Inflammatory bowel diseases (IBD) constitute a group of auto-inflammatory disorders impacting the gastrointestinal tract and other systemic organs. The gut microbiome contributes to IBD pathology through multiple mechanisms. Bacteriophages (hence termed phages) are viruses that are able to specifically infect bacteria. Considered as part of the gut microbiome, phages may impact bacterial community structure in various clinical contexts. Additionally, exogenous phage administration may represent a means of suppressing IBD-associated pathobionts, yet utilization of phage therapy remains at an early developmental phase.

OBJECTIVES

Herein, we summarize the latest advances in understanding endogenous phage impacts on the gut microbiome in health and in IBD. We highlight the prospect of phage utilization as a targeted mode of pathobiont eradication, in preventing and treating IBD manifestations and complications.

SOURCES

Selected peer-reviewed publications regarding the role of phages in health and in IBD, published between 2013 and 2022.

CONTENT

The human gut microbiome is increasingly suggested to play a significant role in the onset and progression of multiple non-communicable diseases such as IBD. Several studies suggest that this effect may be mediated by discrete disease-contributing commensals. However, eradication of such pathogenic bacteria remains a daunting unmet task. Altered community structure in IBD may be influenced by blooms of phages within the gut bacterial ecosystem. Moreover, combinations of phages specifically targeting disease-contributing pathobiont strain clades may be harnessed as potential eradication treatment preventing and treating IBD, while bearing minimal adverse impacts on the surrounding bacterial microbiome.

IMPLICATIONS

Understanding endogenous phage-gut commensal interactions in health and in IBD may enable phage utilization in precision gut microbiome editing, towards treating IBD and other non-communicable microbiome-associated diseases. Nevertheless, developing phage combination-mediated IBD pathobiont eradication treatment modalities will likely necessitate better strain-level bacterial target identification and resolution of treatment-related challenges, such as phage delivery, off-target effects, and bacterial resistance.

Structural characterization of a soil viral auxiliary metabolic gene product - a functional chitosanase

Metagenomics is unearthing the previously hidden world of soil viruses. Many soil viral sequences in metagenomes contain putative auxiliary metabolic genes (AMGs) that are not associated with viral replication. Here, we establish that AMGs on soil viruses actually produce functional, active proteins. We focus on AMGs that potentially encode chitosanase enzymes that metabolize chitin - a common carbon polymer. We express and functionally screen several chitosanase genes identified from environmental metagenomes. One expressed protein showing endo-chitosanase activity (V-Csn) is crystalized and structurally characterized at ultra-high resolution, thus representing the structure of a soil viral AMG product. This structure provides details about the active site, and together with structure models determined using AlphaFold, facilitates understanding of substrate specificity and enzyme mechanism. Our findings support the hypothesis that soil viruses contribute auxiliary functions to their hosts.

Wildfire-dependent changes in soil microbiome diversity and function

Forest soil microbiomes have crucial roles in carbon storage, biogeochemical cycling and rhizosphere processes. Wildfire season length, and the frequency and size of severe fires have increased owing to climate change. Fires affect ecosystem recovery and modify soil microbiomes and microbially mediated biogeochemical processes. To study wildfire-dependent changes in soil microbiomes, we characterized functional shifts in the soil microbiota (bacteria, fungi and viruses) across burn severity gradients (low, moderate and high severity) 1 yr post fire in coniferous forests in Colorado and Wyoming, USA. We found severity-dependent increases of Actinobacteria encoding genes for heat resistance, fast growth, and pyrogenic carbon utilization that might enhance post-fire survival. We report that increased burn severity led to the loss of ectomycorrhizal fungi and less tolerant microbial taxa. Viruses remained active in post-fire soils and probably influenced carbon cycling and biogeochemistry via turnover of biomass and ecosystem-relevant auxiliary metabolic genes. Our genome-resolved analyses link post-fire soil microbial taxonomy to functions and reveal the complexity of post-fire soil microbiome activity.

Genome-Resolved Metaproteomics Decodes the Microbial and Viral Contributions to Coupled Carbon and Nitrogen Cycling in River Sediments

Rivers have a significant role in global carbon and nitrogen cycles, serving as a nexus for nutrient transport between terrestrial and marine ecosystems. Although rivers have a small global surface area, they contribute substantially to worldwide greenhouse gas emissions through microbially mediated processes within the river hyporheic zone. Despite this importance, research linking microbial and viral communities to specific biogeochemical reactions is still nascent in these sediment environments. To survey the metabolic potential and gene expression underpinning carbon and nitrogen biogeochemical cycling in river sediments, we collected an integrated data set of 33 metagenomes, metaproteomes, and paired metabolomes. We reconstructed over 500 microbial metagenome-assembled genomes (MAGs), which we dereplicated into 55 unique, nearly complete medium- and high-quality MAGs spanning 12 bacterial and archaeal phyla. We also reconstructed 2,482 viral genomic contigs, which were dereplicated into 111 viral MAGs (vMAGs) of >10 kb in size. As a result of integrating gene expression data with geochemical and metabolite data, we created a conceptual model that uncovered new roles for microorganisms in organic matter decomposition, carbon sequestration, nitrogen mineralization, nitrification, and denitrification. We show how these metabolic pathways, integrated through shared resource pools of ammonium, carbon dioxide, and inorganic nitrogen, could ultimately contribute to carbon dioxide and nitrous oxide fluxes from hyporheic sediments. Further, by linking viral MAGs to these active microbial hosts, we provide some of the first insights into viral modulation of river sediment carbon and nitrogen cycling. IMPORTANCE Here we created HUM-V (hyporheic uncultured microbial and viral), an annotated microbial and viral MAG catalog that captures strain and functional diversity encoded in these Columbia River sediment samples. Demonstrating its utility, this genomic inventory encompasses multiple representatives of dominant microbial and archaeal phyla reported in other river sediments and provides novel viral MAGs that can putatively infect these. Furthermore, we used HUM-V to recruit gene expression data to decipher the functional activities of these MAGs and reconstruct their active roles in Columbia River sediment biogeochemical cycling. Ultimately, we show the power of MAG-resolved multi-omics to uncover interactions and chemical handoffs in river sediments that shape an intertwined carbon and nitrogen metabolic network. The accessible microbial and viral MAGs in HUM-V will serve as a community resource to further advance more untargeted, activity-based measurements in these, and related, freshwater terrestrial-aquatic ecosystems.