SpacePHARER: Sensitive identification of phages from CRISPR spacers in prokaryotic hosts

Comparison of phage and plasmid populations in the gut microbiota between Parkinson's disease patients and controls

The aging population worldwide is on the rise, leading to a higher number of Parkinson's disease (PD) cases each year. PD is presently the second most prevalent neurodegenerative disease, affecting an estimated 7-10 million individuals globally. This research aimed to identify mobile genetic elements in human fecal samples using a shotgun metagenomics approach. We identified over 44,000 plasmid contigs and compared plasmid populations between PD patients (n = 68) and controls (n = 68). Significant associations emerged between groups (control vs PD) based on plasmid alpha and beta diversity. Moreover, the gene populations present on plasmids displayed marked differences in alpha and beta diversity between PD patients and controls. We identified a considerable number of phage contigs that were differentially abundant in the two groups. We also developed a predictive machine learning model based on phage abundance data, achieving a mean Area Under the Curve (AUC) of 0.74 with a standard deviation of 0.105 and a mean F1 score of 0.68 with a standard deviation of 0.14 across cross-validation folds, indicating moderate discriminatory power. Additionally, when tested on external data, the model yielded an AUC of 0.74 and an F1 score of 0.8, further demonstrating the predictive potential of phage populations in Parkinson's disease. Further, we improved the continuity and identification of the protein coding regions of the phage contigs by implementing alternative genetic codes.

Gut phages and their interactions with bacterial and mammalian hosts

The mammalian gut microbiome is a dense and diverse community of microorganisms that reside in the distal gastrointestinal tract. In recent decades, the bacterial members of the gut microbiome have been the subject of intense research. Less well studied is the large community of bacteriophages that reside in the gut, which number in the billions of viral particles per gram of feces, and consist of considerable unknown viral "dark matter." This community of gut-residing bacteriophages, called the gut "phageome," plays a central role in the gut microbiome through predation and transformation of native gut bacteria, and through interactions with their mammalian hosts. In this review, we will summarize what is known about the composition and origins of the gut phageome, as well as its role in microbiome homeostasis and host health. Furthermore, we will outline the interactions of gut phages with their bacterial and mammalian hosts, and plot a course for the mechanistic study of these systems.

Phage biocontrol in water treatment and reuse systems: a nascent field with significant innovation opportunities

While the use of phages in the food and biomedical sectors occurs commercially, their application in the water sector is less common and is typically demonstrated at a lower technological readiness level. This is so despite the potential that phages have to enhance the control of problematic bacteria (including pathogens) and protect infrastructure within the water sector. Fulfilling the great potential of this nascent field requires more research and development. Here, we highlight innovation opportunities and discern critical knowledge gaps and research needs to facilitate the use of phages as precise biocontrol agents in the water sector. First, while the advent of sequencing technologies made it easier to identify bacterial communities and understand their functional roles, identifying and cultivating the appropriate phages that can be effective against the bacterial target requires more research. The large volumes of water to be spiked with phages also require optimizing the phage biocontrol strategy, minimizing the associated costs and enhancing scaling up. In addition, bacterial hosts may gain phage resistance after long-term exposure, which is common in most water-engineered systems, and strategies to minimize or delay resistance must be considered. In this opinion, we provide an overview of pertinent literature and bioinformatic tools that help identify appropriate bacterial hosts and phages for water systems applications. We then discuss strategies that can aid in prolonging the efficacy and enhancing the feasibility of phage biocontrol approaches.

Are You My Host? An Overview of Methods Used to Link Bacteriophages with Hosts

Until recently, the only methods for finding out if a particular strain or species of bacteria could be a host for a particular bacteriophage was to see if the bacteriophage could infect that bacterium and kill it, releasing progeny phages. Establishing the host range of a bacteriophage thus meant infecting many different bacteria and seeing if the phage could kill each one. Detection of bacterial killing can be achieved on solid media (plaques, spots) or broth (culture clearing). More recently, additional methods to link phages and hosts have been developed. These include methods to show phage genome entry into host cells (e.g., PhageFISH); proximity of phage and host genomes (e.g., proximity ligation, polonies, viral tagging); and analysis of genomes and metagenomes (e.g., CRISPR spacer analysis, metagenomic co-occurrence). These methods have advantages and disadvantages. They also are not measuring the same interactions. Host range can be divided into multiple host ranges, each defined by how far the phage can progress in the infection cycle. For example, the ability to effect genome entry (penetrative host range) is different than the ability to produce progeny (productive host range). These different host ranges reflect bacterial defense mechanisms that block phage growth and development at various stages in the infection cycle. Here, I present a comparison of the various methods used to identify bacteriophage-host relationships with a focus on what type of host range is being measured or predicted.

Synoptic Variation Drives Genetic Diversity and Transmission Mode of Airborne DNA Viruses in Urban Space

Airborne viruses are ubiquitous and play critical roles in maintaining ecosystem balance, however, they remain unexplored. Here, it is aimed to demonstrate that highly diverse airborne viromes carry out specific metabolic functions and use different transmission modes under different air quality conditions. A total of 263.5-Gb data are collected from 13 air samples for viral metagenomic analysis. After assembly and curation, a total of 12 484 viral contigs (1.5-184.2 kb) are assigned to 221 genus-level clades belonging to 47 families, 19 orders, and 15 classes. The composition of viral communities is influenced by weather conditions, with the main biomarker being Caudoviricetes. The most dominant viruses in these air samples belong to the dsDNA Caudoviricetes (54.0%) and ssDNA Repensiviricetes (31.2%) classes. Twelve novel candidate viruses are identified at the order/family/genus levels by alignment of complete genomes and core genes. Notably, Caudoviricetes are highly prevalent in cloudy and smoggy air, whereas Repensiviricetes are highly dominant in sunny and rainy air. Diverse auxiliary metabolic genes of airborne viruses are mainly involved in deoxynucleotide synthesis, implying their unique roles in atmosphere ecosystem. These findings deepen the understanding of the meteorological impacts on viral composition, transmission mode, and ecological roles in the air that we breathe.

Unveiling host-parasite relationships through conserved MITEs in prokaryote and viral genomes

Transposable elements (TEs) play a pivotal role in the evolution of genomes across all life domains. 'Miniature Inverted-repeat Transposable-Elements' (MITEs) are non-autonomous TEs mainly located in intergenic regions, relying on external transposases for mobilization. The extent of MITEs' mobilome was explored across nearly 1700 prokaryotic genera, 183 232 genomes, revealing a broad distribution. MITEs were identified in 56.5% of genomes, totaling over 1.4 million cMITEs (cellular MITEs). Cluster analysis revealed that 97.4% of cMITEs were specific within genera boundaries, with up to 23% being species-specific. Subsequently, this genus-specificity was evaluated as a method to link microbial host to their viruses. A total of 51 655 cMITEs had counterparts in viral sequences, termed vMITEs (viral MITEs), resulting in the identification of 2500 viral sequences with them. Among these, 1501 sequences were positively assigned to a previously known host (41.8% were isolated viruses and 12.3% were assigned through CRISPR data), while 379 new host-virus associations were predicted. Deeper analysis in Neisseria and Bacteroidota groups allowed the association of 242 and 530 new viral sequences, respectively. MITEs are proposed as a novel approach to establishing valid virus-host relationships.

PHPGAT: predicting phage hosts based on multimodal heterogeneous knowledge graph with graph attention network

Antibiotic resistance poses a significant threat to global health, making the development of alternative strategies to combat bacterial pathogens increasingly urgent. One such promising approach is the strategic use of bacteriophages (or phages) to specifically target and eradicate antibiotic-resistant bacteria. Phages, being among the most prevalent life forms on Earth, play a critical role in maintaining ecological balance by regulating bacterial communities and driving genetic diversity. Accurate prediction of phage hosts is essential for successfully applying phage therapy. However, existing prediction models may not fully encapsulate the complex dynamics of phage-host interactions in diverse microbial environments, indicating a need for improved accuracy through more sophisticated modeling techniques. In response to this challenge, this study introduces a novel phage-host prediction model, PHPGAT, which leverages a multimodal heterogeneous knowledge graph with the advanced GATv2 (Graph Attention Network v2) framework. The model first constructs a multimodal heterogeneous knowledge graph by integrating phage-phage, host-host, and phage-host interactions to capture the intricate connections between biological entities. GATv2 is then employed to extract deep node features and learn dynamic interdependencies, generating context-aware embeddings. Finally, an inner product decoder is designed to compute the likelihood of interaction between a phage and host pair based on the embedding vectors produced by GATv2. Evaluation results using two datasets demonstrate that PHPGAT achieves precise phage host predictions and outperforms other models. PHPGAT is available at https://github.com/ZhaoZMer/PHPGAT.

Expanded genome and proteome reallocation in a novel, robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars

Bacillus coagulans, a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of B. coagulans' robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, B. coagulans B-768. Genome sequencing revealed that B-768 has the largest B. coagulans genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced B. coagulans strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes B. coagulans a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%-65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.IMPORTANCEThe robustness of B. coagulans makes it a valuable microorganism for biotechnology applications; yet, this phenotype is not well understood at the cellular level. Through phenotypic characterization and systems analysis, this study elucidates the functional genomics and robustness of a novel, undomesticated strain, B. coagulans B-768, capable of utilizing inhibitory switchgrass biomass hydrolysates. The genome of B-768, enriched with carbohydrate metabolism genes, demonstrates high regulatory capacity. The coordination of proteome reallocation in Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) is critical for effective cell growth, sugar utilization, and lactate production via overflow metabolism. Overall, B-768 is a novel, robust, and promising B. coagulans strain that can be harnessed as a microbial biomanufacturing platform to produce chemicals and fuels from biomass hydrolysates.

CRISPR spacers acquired from plasmids primarily target backbone genes, making them valuable for predicting potential hosts and host range

In recent years, there has been a surge in metagenomic studies focused on identifying plasmids in environmental samples. Although these studies have unearthed numerous novel plasmids, enriching our understanding of their environmental roles, a significant gap remains: the scarcity of information regarding the bacterial hosts of these newly discovered plasmids. Furthermore, even when plasmids are identified within bacterial isolates, the reported host is typically limited to the original isolate, with no insights into alternative hosts or the plasmid's potential host range. Given that plasmids depend on hosts for their existence, investigating plasmids without the knowledge of potential hosts offers only a partial perspective. This study introduces a method for identifying potential hosts and host ranges for plasmids through alignment with CRISPR spacers. To validate the method, we compared the PLSDB plasmids database with the CRISPR spacers database, yielding host predictions for 46% of the plasmids. When compared with reported hosts, our predictions achieved 84% concordance at the family level and 99% concordance at the phylum level. Moreover, the method frequently identified multiple potential hosts for a plasmid, thereby enabling predictions of alternative hosts and the host range. Notably, we found that CRISPR spacers predominantly target plasmid backbone genes while sparing functional genes, such as those linked to antibiotic resistance, aligning with our hypothesis that CRISPR spacers are acquired from plasmid-specific regions rather than insertion elements from diverse sources. Finally, we illustrate the network of connections among different bacterial taxa through plasmids, revealing potential pathways for horizontal gene transfer.IMPORTANCEPlasmids are notorious for their role in distributing antibiotic resistance genes, but they may also carry and distribute other environmentally important genes. Since plasmids are not free-living entities and rely on host bacteria for survival and propagation, predicting their hosts is essential. This study presents a method for predicting potential hosts for plasmids and offers insights into the potential paths for spreading functional genes between different bacteria. Understanding plasmid-host relationships is crucial for comprehending the ecological and clinical impact of plasmids and implications for various biological processes.

Prediction of virus-host associations using protein language models and multiple instance learning

Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep learning method that predicts the host species for viruses from viral sequences only. It also identifies important viral proteins that significantly contribute to host prediction. The method combines a pre-trained large protein language model (ESM) and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than sequence composition features, including amino acids, physiochemical properties, and DNA k-mers. In multi-host prediction tasks, EvoMIL achieves median F1 score improvements of 10.8%, 16.2%, and 4.9% in prokaryotic hosts, and 1.7%, 6.6% and 11.5% in eukaryotic hosts. EvoMIL binary classifiers achieve impressive AUC over 0.95 for all prokaryotic hosts and range from roughly 0.8 to 0.9 for eukaryotic hosts. Furthermore, EvoMIL identifies important proteins in the prediction task, capturing key functions involved in virus-host specificity.

Differentiation of the Anammox core microbiome: Unraveling the evolutionary impetus of scalable gene flow

Anaerobic ammonium oxidation bacteria (AAOB), distinguished by their unique autotrophic nitrogen metabolism, hold pivotal positions in the global nitrogen cycle and environmental biotechnologies. However, the ecophysiology and evolution of AAOB remain poorly understood, attributed to the absence of monocultures. Hence, a comprehensive elucidation of the AAOB-dominated core microbiome, anammox core, is imperative to further completing the theory of engineered nitrogen removal and ecological roles of anammox. Performing taxonomic and phylogenetic analyses on collected genome repertoires, we show here that Candidatus Brocadia and Candidatus Kuenenia possesses a more compact core than Candidatus Jettenia, which partly explains why the latter has a less common ecological presence. Evidence of gene flow is particularly striking in functions related to biosynthesis and oxygen detoxification, underscoring the evolutionary forces driving lineage and core differentiation. Furthermore, CRISPR spacer traceback of the AAOB metagenome-assembled genomes (MAGs) reveals a series of genetic traces for the concealed phages. By reconceptualizing the functional divergence of AAOB with the historical role of phages, we ultimately propose a coevolutionary framework to understand the evolutionary trajectory of anammox microecology. The discoveries provided in this study offer new insights into understanding the evolution of AAOB and the ecology of anammox.

Decoupling of strain- and intrastrain-level interactions of microbiomes in a sponge holobiont

Holobionts are highly organized assemblages of eukaryotic hosts, cellular microbial symbionts, and viruses, whose interactions and evolution involve complex biological processes. It is largely unknown which specific determinants drive similarity or individuality in genetic diversity between holobionts. Here, we combine short- and long-read sequencing and DNA-proximity-linkage technologies to investigate intraspecific diversity of the microbiomes, including host-resolved viruses, in individuals of a model marine sponge. We find strong impacts of the sponge host and the cellular hosts of viruses on strain-level organization of the holobiont, whereas substantial overlap in nucleotide diversity between holobionts suggests frequent exchanges of microbial cells and viruses at intrastrain level in the local sponge population. Immune-evasive arms races likely restricted virus-host co-evolution at the intrastrain level, generated holobiont-specific genome variations, and linked virus-host genetics through recombination. Our work shows that a decoupling of strain- and intrastrain-level interactions is a key factor in the genetic diversification of holobionts.

Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic and viral multi-omics from either short- or long-read sequencing

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.

Multiomics Analysis Reveals Gut Virome-Bacteria-Metabolite Interactions and Their Associations with Symptoms in Patients with IBS-D

The gut microbiota is involved in the pathogenesis of diarrhea-predominant irritable bowel syndrome (IBS-D), but few studies have focused on the role of the gut virome in IBS-D. We aimed to explore the characteristics of the gut virome in patients with IBS-D, its interactions with bacteria and metabolites, and the associations between gut multiomics profiles and symptoms. This study enrolled twelve patients with IBS-D and eight healthy controls (HCs). The stool samples were subjected to metavirome sequencing, 16S rRNA gene sequencing, and untargeted metabolomic analysis. The participants completed relevant scales to assess the severity of their gastrointestinal symptoms, depression, and anxiety. The results revealed unique DNA and RNA virome profiles in patients with IBS-D with significant alterations in the abundance of contigs from Siphoviridae, Podoviridae, Microviridae, Picobirnaviridae, and Tombusviridae. Single-omics co-occurrence network analyses demonstrated distinct differences in the gut virus, bacteria, and metabolite network patterns between patients with IBS-D and HCs. Multiomics networks revealed that short-chain fatty acid-producing bacteria occupied more core positions in IBS-D networks, but had fewer links to viruses. Amino acids and their derivatives exhibit unique connectivity patterns and centrality features within the IBS-D network. The gastrointestinal and psychological symptom factors of patients with IBS-D were highly clustered in the symptom-multiomics network compared with those of HCs. Machine learning models based on multiomics data can distinguish IBS-D patients from HCs and predict the scores of gastrointestinal and psychological symptoms. This study provides insights into the interactions among gut viruses, bacteria, metabolites, and clinical symptoms in patients with IBS-D, indicating further classification and personalized treatment for IBS-D.

Symbiotic virus-bacteria interactions in biological treatment of coking wastewater manipulating bacterial physiological activities

Biological treatment is commonly used in coking wastewater (CWW) treatment. Prokaryotic microbial communities in CWW treatment have been comprehensively studied. However, viruses, as the critical microorganisms affecting microbial processes and thus engineering parameters, still remain poorly understood in CWW treatment context. Employing viromics sequencing, the composition and function of the viral community in CWW treatment were discovered, revealing novel viral communities and key auxiliary metabolic functions. Caudovirales appeared to be the predominant viral order in the oxic-hydrolytic-oxic (OHO) CWW treatment combination, showing relative abundances of 62.47 %, 56.64 % and 92.20 % in bioreactors O1, H and O2, respectively. At the family level, Myoviridae, Podoviridae and Siphoviridae mainly prevailed in bioreactors O1 and H while Phycodnaviridae dominated in O2. A total of 56.23-92.24% of novel viral contigs defied family-level characterization in this distinct CWW habitat. The virus-host prediction results revealed most viruses infecting the specific functional taxa Pseudomonas, Acidovorax and Thauera in the entire OHO combination, demonstrating the viruses affecting bacterial physiology and pollutants removal from CWW. Viral auxiliary metabolic genes (AMGs) were screened, revealing their involvement in the metabolism of contaminants and toxicity tolerance. In the bioreactor O1, AMGs were enriched in detoxification and phosphorus ingestion, where glutathione S-transferase (GSTs) and beta-ketoadipyl CoA thiolase (fadA) participated in biodegradation of polycyclic aromatic hydrocarbons and phenols, respectively. In the bioreactors H and O2, the AMGs focused on cell division and epicyte formation of the hosts, where GDPmannose 4,6-dehydratase (gmd) related to lipopolysaccharides biosynthesis was considered to play an important role in the growth of nitrifiers. The diversities of viruses and AMGs decreased along the CWW treatment process, pointing to a reinforced virus-host adaptive strategy in stressful operation environments. In this study, the symbiotic virus-bacteria interaction patterns were proposed with a theoretical basis for promoting CWW biological treatment efficiency. The findings filled the gaps in the virus-bacteria interactions at the full-scale CWW treatment and provided great value for understanding the mechanism of biological toxicity and sludge activity in industrial wastewater treatment.

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.

Unveiling the Microbial Realm with VEBA 2.0: A modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic, and viral multi-omics from either short- or long-read sequencing

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible platform that bridges the gap between genomics and biotechnological solutions.

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.

Active prokaryotic and eukaryotic viral ecology across spatial scale in a deep-sea brine pool

Deep-sea brine pools represent rare, extreme environments, providing unique insight into the limits of life on Earth, and by analogy, the plausibility of life beyond it. A distinguishing feature of many brine pools is presence of thick microbial mats that develop at the brine-seawater interface. While these bacterial and archaeal communities have received moderate attention, viruses and their host interactions in these environments remain underexplored. To bridge this knowledge gap, we leveraged metagenomic and metatranscriptomic data from three distinct zones within the NEOM brine pool system (Gulf of Aqaba) to reveal the active viral ecology around the pools. We report a remarkable diversity and activity of viruses infecting microbial hosts in this environment, including giant viruses, RNA viruses, jumbo phages, and Polinton-like viruses. Many of these form distinct clades-suggesting presence of untapped viral diversity in this ecosystem. Brine pool viral communities exhibit zone-specific differences in infection strategy-with lysogeny dominating the bacterial mat further away from the pool's center. We linked viruses to metabolically important prokaryotes-including association between a jumbo phage and a key manganese-oxidizing and arsenic-metabolizing bacterium. These foundational results illuminate the role of viruses in modulating brine pool microbial communities and biogeochemistry through revealing novel viral diversity, host associations, and spatial heterogeneity in viral dynamics.

Viral diversity and host associations in microbial electrolysis cells

In microbial electrolysis cells (MECs), microbial communities catalyze conversions between dissolved organic compounds, electrical energy, and energy carriers such as hydrogen and methane. Bacteria and archaea, which catalyze reactions on the anode and cathode of MECs, interact with phages; however, phage communities have previously not been examined in MECs. In this study, we used metagenomic sequencing to study prokaryotes and phages in nine MECs. A total of 852 prokaryotic draft genomes representing 278 species, and 1476 phage contigs representing 873 phage species were assembled. Among high quality prokaryotic genomes (>95% completion), 55% carried a prophage, and the three Desulfobacterota spp. that dominated the anode communities all carried prophages. Geobacter anodireducens, one of the bacteria dominating the anode communities, carried a CRISPR spacer showing evidence of a previous infection by a Peduoviridae phage present in the liquid of some MECs. Methanobacteriaceae spp. and an Acetobacterium sp., which dominated the cathodes, had several associations with Straboviridae spp. The results of this study show that phage communities in MECs are diverse and interact with functional microorganisms on both the anode and cathode.

Revealing viral diversity in the Napahai plateau wetland based on metagenomics

We focused on exploring the diversity of viruses in the Napahai plateau wetland, a unique ecosystem located in Yunnan, China. While viruses in marine environments have been extensively studied for their influence on microbial metabolism and biogeochemical cycles, little is known about their composition and function in plateau wetlands. Metagenomic analysis was employed to investigate the viral diversity and biogeochemical impacts in the Napahai wetland. It revealed that the Caudoviricetes and Malgrandaviricetes class level was the most abundant viral category based on phylogenetic analysis. Additionally, a gene-sharing network highlighted the presence of numerous unexplored viruses and demonstrated their unique characteristics and significant variation within the viral community of the Napahai wetland. Furthermore, the study identified the auxiliary metabolic genes (AMGs). AMGs provide phages with additional functions, such as protection against host degradation and involvement in metabolic pathways, such as the pentose phosphate pathway and DNA biosynthesis. The viruses in the Napahai wetland were found to influence carbon, nitrogen, sulfur, and amino acid metabolism, indirectly contributing to biogeochemical cycling through these AMGs. Overall, the research sheds light on the diverse and unique viral communities in the Napahai plateau wetland and emphasizes the significant roles of viruses in microbial ecology. The findings contribute to a deeper understanding of the characteristics and ecological functions of viral communities in plateau wetland ecosystems.

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.

Phages are unrecognized players in the ecology of the oral pathogen Porphyromonas gingivalis

BACKGROUND

Porphyromonas gingivalis (hereafter "Pg") is an oral pathogen that has been hypothesized to act as a keystone driver of inflammation and periodontal disease. Although Pg is most readily recovered from individuals with actively progressing periodontal disease, healthy individuals and those with stable non-progressing disease are also colonized by Pg. Insights into the factors shaping the striking strain-level variation in Pg, and its variable associations with disease, are needed to achieve a more mechanistic understanding of periodontal disease and its progression. One of the key forces often shaping strain-level diversity in microbial communities is infection of bacteria by their viral (phage) predators and symbionts. Surprisingly, although Pg has been the subject of study for over 40 years, essentially nothing is known of its phages, and the prevailing paradigm is that phages are not important in the ecology of Pg.

RESULTS

Here we systematically addressed the question of whether Pg are infected by phages-and we found that they are. We found that prophages are common in Pg, they are genomically diverse, and they encode genes that have the potential to alter Pg physiology and interactions. We found that phages represent unrecognized targets of the prevalent CRISPR-Cas defense systems in Pg, and that Pg strains encode numerous additional mechanistically diverse candidate anti-phage defense systems. We also found that phages and candidate anti-phage defense system elements together are major contributors to strain-level diversity and the species pangenome of this oral pathogen. Finally, we demonstrate that prophages harbored by a model Pg strain are active in culture, producing extracellular viral particles in broth cultures.

CONCLUSION

This work definitively establishes that phages are a major unrecognized force shaping the ecology and intra-species strain-level diversity of the well-studied oral pathogen Pg. The foundational phage sequence datasets and model systems that we establish here add to the rich context of all that is already known about Pg, and point to numerous avenues of future inquiry that promise to shed new light on fundamental features of phage impacts on human health and disease broadly. Video Abstract.

Lysogenic bacteriophages encoding arsenic resistance determinants promote bacterial community adaptation to arsenic toxicity

Emerging evidence from genomics gives us a glimpse into the potential contribution of lysogenic bacteriophages (phages) to the environmental adaptability of their hosts. However, it is challenging to quantify this kind of contribution due to the lack of appropriate genetic markers and the associated controllable environmental factors. Here, based on the unique transformable nature of arsenic (the controllable environmental factor), a series of flooding microcosms was established to investigate the contribution of arsM-bearing lysogenic phages to their hosts' adaptation to trivalent arsenic [As(III)] toxicity, where arsM is the marker gene associated with microbial As(III) detoxification. In the 15-day flooding period, the concentration of As(III) was significantly increased, and this elevated As(III) toxicity visibly inhibited the bacterial population, but the latter quickly adapted to As(III) toxicity. During the flooding period, some lysogenic phages re-infected new hosts after an early burst, while others persistently followed the productive cycle (i.e., lytic cycle). The unique phage-host interplay contributed to the rapid spread of arsM among soil microbiota, enabling the quick recovery of the bacterial community. Moreover, the higher abundance of arsM imparted a greater arsenic methylation capability to soil microbiota. Collectively, this study provides experimental evidence for lysogenic phages assisting their hosts in adapting to an extreme environment, which highlights the ecological perspectives on lysogenic phage-host mutualism.

The association of prokaryotic antiviral systems and symbiotic phage communities in drinking water microbiomes

Prokaryotic antiviral systems are important mediators for prokaryote-phage interactions, which have significant implications for the survival of prokaryotic community. However, the prokaryotic antiviral systems under environmental stress are poorly understood, limiting the understanding of microbial adaptability. Here, we systematically investigated the profile of the prokaryotic antiviral systems at the community level and prokaryote-phage interactions in the drinking water microbiome. Chlorine disinfectant was revealed as the main ecological driver for the difference in prokaryotic antiviral systems and prokaryote-phage interactions. Specifically, the prokaryotic antiviral systems in the microbiome exhibited a higher abundance, broader antiviral spectrum, and lower metabolic burden under disinfectant stress. Moreover, significant positive correlations were observed between phage lysogenicity and enrichment of antiviral systems (e.g., Type IIG and IV restriction-modification (RM) systems, and Type II CRISPR-Cas system) in the presence of disinfection, indicating these antiviral systems might be more compatible with lysogenic phages and prophages. Accordingly, there was a stronger prokaryote-phage symbiosis in disinfected microbiome, and the symbiotic phages carried more auxiliary metabolic genes (AMGs) related to prokaryotic adaptability as well as antiviral systems, which might further enhance prokaryote survival in drinking water distribution systems. Overall, this study demonstrates that the prokaryotic antiviral systems had a close association with their symbiotic phages, which provides novel insights into prokaryote-phage interactions and microbial environmental adaptation.

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.

CRISPR detection in metagenome-assembled genomes (MAGs) of coal mine

Bacterial and archaeal CRISPR-Cas systems provide adaptive immune protection against foreign mobile genetic elements. When viruses infect bacteria, a small portion of the viral DNA is inserted into the bacterial DNA in a specific pattern to produce segments known as CRISPR arrays. Metagenome assembled genomes (MAGs) were used in our study to identify the CRISPR sequence for determining the interacted phage. Metagenomic data from a coal mine was used to perform a computational study. From raw reads, 206151 contigs were assembled. Then contigs were clustered into 150 Metagenome assembled genomes from which 78 non-redundant MAGs were selected. Using the CHECKM standard, seven MAGs were found to have >80 completeness and <20 contaminations. Those MAGs were analyzed for the presence of CRISPR elements. Out of seven MAGs, four MAGs have the CRISPR elements and are searched against the VIROblast database. CRISPR arrays have 4, 1, 3, and 7 spacer sequences in the MAGs of Burkholderia, Acinetobacter, Oxalobacteraceae, and Burkholderia multivorans respectively. The uncultured Caudovirales phage genomic regions were present in the genomes of Burkholderia, Oxalobacteriaceae, and Burkholderia multivorans. This study follows the unconventional metagenomics workflow to provide a better understanding of bacteria and phage interactions.

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.

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.

An ensemble method for prediction of phage-based therapy against bacterial infections

Phage therapy is a viable alternative to antibiotics for treating microbial infections, particularly managing drug-resistant strains of bacteria. One of the major challenges in designing phage-based therapy is to identify the most appropriate potential phage candidate to treat bacterial infections. In this study, an attempt has been made to predict phage-host interactions with high accuracy to identify the potential bacteriophage that can be used for treating a bacterial infection. The developed models have been created using a training dataset containing 826 phage- host interactions, and have been evaluated on a validation dataset comprising 1,201 phage-host interactions. Firstly, alignment-based models have been developed using similarity between phage-phage (BLASTPhage), host-host (BLASTHost) and phage-CRISPR (CRISPRPred), where we achieved accuracy between 42.4-66.2% for BLASTPhage, 55-78.4% for BLASTHost, and 43.7-80.2% for CRISPRPred across five taxonomic levels. Secondly, alignment free models have been developed using machine learning techniques. Thirdly, hybrid models have been developed by integrating the alignment-free models and the similarity-scores where we achieved maximum performance of (60.6-93.5%). Finally, an ensemble model has been developed that combines the hybrid and alignment-based models. Our ensemble model achieved highest accuracy of 67.9, 80.6, 85.5, 90, and 93.5% at Genus, Family, Order, Class, and Phylum levels on validation dataset. In order to serve the scientific community, we have also developed a webserver named PhageTB and provided a standalone software package (https://webs.iiitd.edu.in/raghava/phagetb/) for the same.

Reekeekee- and roodoodooviruses, two different Microviridae clades constituted by the smallest DNA phages

Small circular single-stranded DNA viruses of the Microviridae family are both prevalent and diverse in all ecosystems. They usually harbor a genome between 4.3 and 6.3 kb, with a microvirus recently isolated from a marine Alphaproteobacteria being the smallest known genome of a DNA phage (4.248 kb). A subfamily, Amoyvirinae, has been proposed to classify this virus and other related small Alphaproteobacteria-infecting phages. Here, we report the discovery, in meta-omics data sets from various aquatic ecosystems, of sixteen complete microvirus genomes significantly smaller (2.991-3.692 kb) than known ones. Phylogenetic analysis reveals that these sixteen genomes represent two related, yet distinct and diverse, novel groups of microviruses-amoyviruses being their closest known relatives. We propose that these small microviruses are members of two tentatively named subfamilies Reekeekeevirinae and Roodoodoovirinae. As known microvirus genomes encode many overlapping and overprinted genes that are not identified by gene prediction software, we developed a new methodology to identify all genes based on protein conservation, amino acid composition, and selection pressure estimations. Surprisingly, only four to five genes could be identified per genome, with the number of overprinted genes lower than that in phiX174. These small genomes thus tend to have both a lower number of genes and a shorter length for each gene, leaving no place for variable gene regions that could harbor overprinted genes. Even more surprisingly, these two Microviridae groups had specific and different gene content, and major differences in their conserved protein sequences, highlighting that these two related groups of small genome microviruses use very different strategies to fulfill their lifecycle with such a small number of genes. The discovery of these genomes and the detailed prediction and annotation of their genome content expand our understanding of ssDNA phages in nature and are further evidence that these viruses have explored a wide range of possibilities during their long evolution.

The complete and closed genome of the facultative generalist Candidatus Endoriftia persephone from deep-sea hydrothermal vents

The mutualistic interactions between Riftia pachyptila and its endosymbiont Candidatus Endoriftia persephone (short Endoriftia) have been extensively researched. However, the closed Endoriftia genome is still lacking. Here, by employing single-molecule real-time sequencing we present the closed chromosomal sequence of Endoriftia. In contrast to theoretical predictions of enlarged and mobile genetic element-rich genomes related to facultative endosymbionts, the closed Endoriftia genome is streamlined with fewer than expected coding sequence regions, insertion-, prophage-sequences and transposase-coding sequences. Automated and manually curated functional analyses indicated that Endoriftia is more versatile regarding sulphur metabolism than previously reported. We identified the presence of two identical rRNA operons and two long CRISPR regions in the closed genome. Additionally, pangenome analyses revealed the presence of three types of secretion systems (II, IV and VI) in the different Endoriftia populations indicating lineage-specific adaptations. The in depth mobilome characterization identified the presence of shared genomic islands in the different Endoriftia drafts and in the closed genome, suggesting that the acquisition of foreign DNA predates the geographical dispersal of the different endosymbiont populations. Finally, we found no evidence of epigenetic regulation in Endoriftia, as revealed by gene screenings and absence of methylated modified base motifs in the genome. As a matter of fact, the restriction-modification system seems to be dysfunctional in Endoriftia, pointing to a higher importance of molecular memory-based immunity against phages via spacer incorporation into CRISPR system. The Endoriftia genome is the first closed tubeworm endosymbiont to date and will be valuable for future gene oriented and evolutionary comparative studies.

Diversity of novel archaeal viruses infecting methanogens discovered through coupling of stable isotope probing and metagenomics

Diversity of viruses infecting non-extremophilic archaea has been grossly understudied. This is particularly the case for viruses infecting methanogenic archaea, key players in the global carbon biogeochemical cycle. Only a dozen of methanogenic archaeal viruses have been isolated so far. In the present study, we implemented an original coupling between stable isotope probing and complementary shotgun metagenomic analyses to identify viruses of methanogens involved in the bioconversion of formate, which was used as the sole carbon source in batch anaerobic digestion microcosms. Under our experimental conditions, the microcosms were dominated by methanogens belonging to the order Methanobacteriales (Methanobacterium and Methanobrevibacter genera). Metagenomic analyses yielded several previously uncharacterized viral genomes, including a complete genome of a head-tailed virus (class Caudoviricetes, proposed family Speroviridae, Methanobacterium host) and several near-complete genomes of spindle-shaped viruses. The two groups of viruses are predicted to infect methanogens of the Methanobacterium and Methanosarcina genera and represent two new virus families. The metagenomics results are in good agreement with the electron microscopy observations, which revealed the dominance of head-tailed virus-like particles and the presence of spindle-shaped particles. The present study significantly expands the knowledge on the viral diversity of viruses of methanogens.

Genomes of six viruses that infect Asgard archaea from deep-sea sediments

Asgard archaea are globally distributed prokaryotic microorganisms related to eukaryotes; however, viruses that infect these organisms have not been described. Here, using metagenome sequences recovered from deep-sea hydrothermal sediments, we characterize six relatively large (up to 117 kb) double-stranded DNA (dsDNA) viral genomes that infected two Asgard archaeal phyla, Lokiarchaeota and Helarchaeota. These viruses encode Caudovirales-like structural proteins, as well as proteins distinct from those described in known archaeal viruses. Their genomes contain around 1-5% of genes associated with eukaryotic nucleocytoplasmic large DNA viruses (NCLDVs) and appear to be capable of semi-autonomous genome replication, repair, epigenetic modifications and transcriptional regulation. Moreover, Helarchaeota viruses may hijack host ubiquitin systems similar to eukaryotic viruses. Genomic analysis of these Asgard viruses reveals that they contain features of both prokaryotic and eukaryotic viruses, and provides insights into their potential infection and host interaction mechanisms.

Three families of Asgard archaeal viruses identified in metagenome-assembled genomes

Asgardarchaeota harbour many eukaryotic signature proteins and are widely considered to represent the closest archaeal relatives of eukaryotes. Whether similarities between Asgard archaea and eukaryotes extend to their viromes remains unknown. Here we present 20 metagenome-assembled genomes of Asgardarchaeota from deep-sea sediments of the basin off the Shimokita Peninsula, Japan. By combining a CRISPR spacer search of metagenomic sequences with phylogenomic analysis, we identify three family-level groups of viruses associated with Asgard archaea. The first group, verdandiviruses, includes tailed viruses of the class Caudoviricetes (realm Duplodnaviria); the second, skuldviruses, consists of viruses with predicted icosahedral capsids of the realm Varidnaviria; and the third group, wyrdviruses, is related to spindle-shaped viruses previously identified in other archaea. More than 90% of the proteins encoded by these viruses of Asgard archaea show no sequence similarity to proteins encoded by other known viruses. Nevertheless, all three proposed families consist of viruses typical of prokaryotes, providing no indication of specific evolutionary relationships between viruses infecting Asgard archaea and eukaryotes. Verdandiviruses and skuldviruses are likely to be lytic, whereas wyrdviruses potentially establish chronic infection and are released without host cell lysis. All three groups of viruses are predicted to play important roles in controlling Asgard archaea populations in deep-sea ecosystems.

A closed Candidatus Odinarchaeum chromosome exposes Asgard archaeal viruses

Asgard archaea have recently been identified as the closest archaeal relatives of eukaryotes. Their ecology, and particularly their virome, remain enigmatic. We reassembled and closed the chromosome of Candidatus Odinarchaeum yellowstonii LCB_4, through long-range PCR, revealing CRISPR spacers targeting viral contigs. We found related viruses in the genomes of diverse prokaryotes from geothermal environments, including other Asgard archaea. These viruses open research avenues into the ecology and evolution of Asgard archaea.

Salmonella phage akira, infecting selected Salmonella enterica Enteritidis and Typhimurium strains, represents a new lineage of bacteriophages

Some serovars of Salmonella can cause life-threatening diarrhoeal diseases and bacteriemia. The emergence of multidrug-resistant strains has led to a need for alternative treatments such as phage therapy, which requires available, well-described, diverse, and suitable phages. Phage akira was found to lyse 19 out of 32 Salmonella enterica serovars and farm isolates tested, although plaque formation was observed with only two S. Enteritidis and one S. Typhimurium strain. Phage akira encodes anti-defence genes against type 1 R-M systems, is distinct (<65% nucleotide sequence identity) from related phages and has siphovirus morphology. We propose that akira represents a new genus in the class Caudoviricetes.

Computational Tools for the Analysis of Uncultivated Phage Genomes

Over a century of bacteriophage research has uncovered a plethora of fundamental aspects of their biology, ecology, and evolution. Furthermore, the introduction of community-level studies through metagenomics has revealed unprecedented insights on the impact that phages have on a range of ecological and physiological processes. It was not until the introduction of viral metagenomics that we began to grasp the astonishing breadth of genetic diversity encompassed by phage genomes. Novel phage genomes have been reported from a diverse range of biomes at an increasing rate, which has prompted the development of computational tools that support the multilevel characterization of these novel phages based solely on their genome sequences. The impact of these technologies has been so large that, together with MAGs (Metagenomic Assembled Genomes), we now have UViGs (Uncultivated Viral Genomes), which are now officially recognized by the International Committee for the Taxonomy of Viruses (ICTV), and new taxonomic groups can now be created based exclusively on genomic sequence information. Even though the available tools have immensely contributed to our knowledge of phage diversity and ecology, the ongoing surge in software programs makes it challenging to keep up with them and the purpose each one is designed for. Therefore, in this review, we describe a comprehensive set of currently available computational tools designed for the characterization of phage genome sequences, focusing on five specific analyses: (i) assembly and identification of phage and prophage sequences, (ii) phage genome annotation, (iii) phage taxonomic classification, (iv) phage-host interaction analysis, and (v) phage microdiversity.

Donor-dependent fecal microbiota transplantation efficacy against necrotizing enterocolitis in preterm pigs

The development of necrotizing enterocolitis (NEC), a life-threatening inflammatory bowel disease affecting preterm infants, is connected with gut microbiota dysbiosis. Using preterm piglets as a model for preterm infants we recently showed that fecal microbiota transplantation (FMT) from healthy suckling piglet donors to newborn preterm piglets decreased the NEC risk. However, in a follow-up study using donor stool from piglets recruited from another farm, this finding could not be replicated. This allowed us to study donor-recipient microbiota dynamics in a controlled model system with a clear difference in NEC phenotype. Preterm piglets (n = 38) were randomly allocated to receive control saline (CON), or rectal FMT using either the ineffective (FMT1) or the effective donor stool (FMT2). All animals were followed for four days before necropsy and gut pathological evaluation. Donor and recipient colonic gut microbiota (GM) were analyzed by 16 S rRNA gene amplicon sequencing and shotgun metagenomics. As expected, only FMT2 recipients were protected against NEC. Both FMT groups had shifted GM composition relative to CON, but FMT2 recipients had a higher lactobacilli relative abundance compared to FMT1. Limosilactobacillus reuteri and Lactobacillus crispatus strains of FMT recipients showed high phylogenetic similarity with their respective donors, indicating engraftment. Moreover, the FMT2 group had a higher lactobacilli replication rate and harbored specific glycosaminoglycan-degrading Bacteroides. In conclusion, subtle species-level donor differences translate to major changes in engraftment dynamics and the ability to prevent NEC. This could have implications for proper donor selection in future FMT trials for NEC prevention.

Caudovirales bacteriophages are associated with improved executive function and memory in flies, mice, and humans

Growing evidence implicates the gut microbiome in cognition. Viruses, the most abundant life entities on the planet, are a commonly overlooked component of the gut virome, dominated by the Caudovirales and Microviridae bacteriophages. Here, we show in a discovery (n = 114) and a validation cohort (n = 942) that subjects with increased Caudovirales and Siphoviridae levels in the gut microbiome had better performance in executive processes and verbal memory. Conversely, increased Microviridae levels were linked to a greater impairment in executive abilities. Microbiota transplantation from human donors with increased specific Caudovirales (>90% from the Siphoviridae family) levels led to increased scores in the novel object recognition test in mice and up-regulated memory-promoting immediate early genes in the prefrontal cortex. Supplementation of the Drosophila diet with the 936 group of lactococcal Siphoviridae bacteriophages resulted in increased memory scores and upregulation of memory-involved brain genes. Thus, bacteriophages warrant consideration as novel actors in the microbiome-brain axis.

Bacteriophages Roam the Wheat Phyllosphere

The phyllosphere microbiome plays an important role in plant fitness. Recently, bacteriophages have been shown to play a role in shaping the bacterial community composition of the phyllosphere. However, no studies on the diversity and abundance of phyllosphere bacteriophage communities have been carried out until now. In this study, we extracted, sequenced, and characterized the dsDNA and ssDNA viral community from a phyllosphere for the first time. We sampled leaves from winter wheat (Triticum aestivum), where we identified a total of 876 virus operational taxonomic units (vOTUs), mostly predicted to be bacteriophages with a lytic lifestyle. Remarkably, 848 of these vOTUs corresponded to new viral species, and we estimated a minimum of 2.0 × 10⁶ viral particles per leaf. These results suggest that the wheat phyllosphere harbors a large and active community of novel bacterial viruses. Phylloviruses have potential applications as biocontrol agents against phytopathogenic bacteria or as microbiome modulators to increase plant growth-promoting bacteria.

Phages in the Gut Ecosystem

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

Digital phagograms: predicting phage infectivity through a multilayer machine learning approach

Machine learning has been broadly implemented to investigate biological systems. In this regard, the field of phage biology has embraced machine learning to elucidate and predict phage-host interactions, based on receptor-binding proteins, (anti-)defense systems, prophage detection, and life cycle recognition. Here, we highlight the enormous potential of integrating information from omics data with insights from systems biology to better understand phage-host interactions. We conceptualize and discuss the potential of a multilayer model that mirrors the phage infection process, integrating adsorption, bacterial pan-immune components and hijacking of the bacterial metabolism to predict phage infectivity. In the future, this model can offer insights into the underlying mechanisms of the infection process, and digital phagograms can support phage cocktail design and phage engineering.

PHIST: fast and accurate prediction of prokaryotic hosts from metagenomic viral sequences

SUMMARY

Phage-Host Interaction Search Tool (PHIST) predicts prokaryotic hosts of viruses based on exact matches between viral and host genomes. It improves host prediction accuracy at species level over current alignment-based tools (on average by 3 percentage points) as well as alignment-free and CRISPR-based tools (by 14-20 percentage points). PHIST is also two orders of magnitude faster than alignment-based tools making it suitable for metagenomics studies.

AVAILABILITY AND IMPLEMENTATION

GNU-licensed C++ code wrapped in Python API available at: https://github.com/refresh-bio/phist.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Global overview and major challenges of host prediction methods for uncultivated phages

Bacterial communities play critical roles across all of Earth's biomes, affecting human health and global ecosystem functioning. They do so under strong constraints exerted by viruses, that is, bacteriophages or 'phages'. Phages can reshape bacterial communities' structure, influence long-term evolution of bacterial populations, and alter host cell metabolism during infection. Metagenomics approaches, that is, shotgun sequencing of environmental DNA or RNA, recently enabled large-scale exploration of phage genomic diversity, yielding several millions of phage genomes now to be further analyzed and characterized. One major challenge however is the lack of direct host information for these phages. Several methods and tools have been proposed to bioinformatically predict the potential host(s) of uncultivated phages based only on genome sequence information. Here we review these different approaches and highlight their distinct strengths and limitations. We also outline complementary experimental assays which are being proposed to validate and refine these bioinformatic predictions.

Going to extremes - a metagenomic journey into the dark matter of life

The Virus-X-Viral Metagenomics for Innovation Value-project was a scientific expedition to explore and exploit uncharted territory of genetic diversity in extreme natural environments such as geothermal hot springs and deep-sea ocean ecosystems. Specifically, the project was set to analyse and exploit viral metagenomes with the ultimate goal of developing new gene products with high innovation value for applications in biotechnology, pharmaceutical, medical, and the life science sectors. Viral gene pool analysis is also essential to obtain fundamental insight into ecosystem dynamics and to investigate how viruses influence the evolution of microbes and multicellular organisms. The Virus-X Consortium, established in 2016, included experts from eight European countries. The unique approach based on high throughput bioinformatics technologies combined with structural and functional studies resulted in the development of a biodiscovery pipeline of significant capacity and scale. The activities within the Virus-X consortium cover the entire range from bioprospecting and methods development in bioinformatics to protein production and characterisation, with the final goal of translating our results into new products for the bioeconomy. The significant impact the consortium made in all of these areas was possible due to the successful cooperation between expert teams that worked together to solve a complex scientific problem using state-of-the-art technologies as well as developing novel tools to explore the virosphere, widely considered as the last great frontier of life.

Exploring Viral Diversity in a Gypsum Karst Lake Ecosystem Using Targeted Single-Cell Genomics

Little is known about the diversity and distribution of viruses infecting green sulfur bacteria (GSB) thriving in euxinic (sulfuric and anoxic) habitats, including gypsum karst lake ecosystems. In this study, we used targeted cell sorting combined with single-cell sequencing to gain insights into the gene content and genomic potential of viruses infecting sulfur-oxidizing bacteria Chlorobium clathratiforme, obtained from water samples collected during summer stratification in gypsum karst Lake Kirkilai (Lithuania). In total, 82 viral contigs were bioinformatically identified in 62 single amplified genomes (SAGs) of C. clathratiforme. The majority of viral gene and protein sequences showed little to no similarity with phage sequences in public databases, uncovering the vast diversity of previously undescribed GSB viruses. We observed a high level of lysogenization in the C. clathratiforme population, as 87% SAGs contained intact prophages. Among the thirty identified auxiliary metabolic genes (AMGs), two, thiosulfate sulfurtransferase (TST) and thioredoxin-dependent phosphoadenosine phosphosulfate (PAPS) reductase (cysH), were found to be involved in the oxidation of inorganic sulfur compounds, suggesting that viruses can influence the metabolism and cycling of this essential element. Finally, the analysis of CRISPR spacers retrieved from the consensus C. clathratiforme genome imply persistent and active virus–host interactions for several putative phages prevalent among C. clathratiforme SAGs. Overall, this study provides a glimpse into the diversity of phages associated with naturally occurring and highly abundant sulfur-oxidizing bacteria.

Metaviromes Reveal the Dynamics of Pseudomonas Host-Specific Phages Cultured and Uncultured by Plaque Assay

Isolating single phages using plaque assays is a laborious and time-consuming process. Whether single isolated phages are the most lyse-effective, the most abundant in viromes, or those with the highest ability to make plaques in solid media is not well known. With the increasing accessibility of high-throughput sequencing, metaviromics is often used to describe viruses in environmental samples. By extracting and sequencing metaviromes from organic waste with and without exposure to a host-of-interest, we show a host-related phage community's shift, as well as identify the most enriched phages. Moreover, we isolated plaque-forming single phages using the same virome-host matrix to observe how enrichments in liquid media correspond to the metaviromic data. In this study, we observed a significant shift (p = 0.015) of the 47 identified putative Pseudomonas phages with a minimum twofold change above zero in read abundance when adding a Pseudomonas syringae DC3000 host. Surprisingly, it appears that only two out of five plaque-forming phages from the same organic waste sample, targeting the Pseudomonas strain, were highly abundant in the metavirome, while the other three were almost absent despite host exposure. Lastly, our sequencing results highlight how long reads from Oxford Nanopore elevates the assembly quality of metaviromes, compared to short reads alone.