Prokaryotic Virus Orthologous Groups (pVOGs): a resource for comparative genomics and protein family annotation

Treated wastewater: A hotspot for multidrug- and colistin-resistant Klebsiella pneumoniae

Wastewater treatment plants are hotspots for the release of antimicrobial resistant pathogenic bacteria into aquatic ecosystems, significantly contributing to the cycle of antimicrobial resistance. Special attention should be paid to antimicrobial resistant ESKAPE bacteria, which have been identified as high-priority targets for control measures. Among them, Klebsiella pneumoniae is particularly noteworthy. In this study, we collected wastewater samples from the inlet, sedimentation tank, and effluent water of a wastewater treatment plant in June, July, October, and November of 2018. We detected and characterized 42 K. pneumoniae strains using whole genome sequencing (15 from the inlet, 8 from the sedimentation tank, and 19 from the effluent). Additionally, the strains were tested for their antimicrobial resistance phenotype. Using whole genome sequencing no distinct patterns were observed in terms of their genetic profiles. All strains were resistant to tetracycline, meanwhile 60%, 47%, and 37.5% of strains isolated from the inlet, sedimentation tank, and effluent, respectively, were multidrug resistant. Some of the multidrug resistant isolates were also resistant to colistin, and nearly all tested positive for the eptB and arnT genes, which are associated with polymyxin resistance. Various antimicrobial resistance genes were linked to mobile genetic elements, and they did not correlate with detected virulence groups or defense systems. Overall, our results, although not quantitative, highlight that multidrug resistant K. pneumoniae strains, including those resistant to colistin and genetically unrelated, being discharged into aquatic ecosystems from wastewater treatment plants. This suggests the necessity of monitoring aimed at genetically characterizing these pathogenic bacteria.

Improving viral annotation with artificial intelligence

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environmental pressures. High-throughput sequencing approaches have begun to give us access to the diversity and range of phage populations in complex microbial community samples, and metagenomics is currently the primary tool with which we study phage populations. The study of phages by metagenomic sequencing, however, is fundamentally limited by viral diversity, which results in the vast majority of viral genomes and metagenome-annotated genomes lacking annotation. To harness bacteriophages for applications in human and environmental health and disease, we need new methods to organize and annotate viral sequence diversity. We recently demonstrated that methods that leverage self-supervised representation learning can supplement statistical sequence representations for remote viral protein homology detection in the ocean virome and propose that consideration of the functional content of viral sequences allows for the identification of similarity in otherwise sequence-diverse viruses and viral-like elements for biological discovery. In this review, we describe the potential and pitfalls of large language models for viral annotation. We describe the need for new approaches to annotate viral sequences in metagenomes, the fundamentals of what protein language models are and how one can use them for sequence annotation, the strengths and weaknesses of these models, and future directions toward developing better models for viral annotation more broadly.

Isolation and characterization of Septuagintavirus; a novel clade of Escherichia coli phages within the subfamily Vequintavirinae

Escherichia coli is a commensal inhabitant of the mammalian gut microbiota, frequently associated with various gastrointestinal diseases. There is increasing interest in comprehending the variety of bacteriophages (phages) that target this bacterium, as such insights could pave the way for their potential use in therapeutic applications. Here, we report the isolation and characterization of four newly identified E. coli infecting tailed phages (W70, A7-1, A5-4, and A73) that were found to constitute a novel genus, Septuagintavirus, within the subfamily Vequintavirinae. Genomes of these phages ranged from 137 kbp to 145 kbp, with a GC content of 41 mol%. They possess a maximum nucleotide similarity of 30% with phages of the closest phylogenetic genus, Certrevirus, while displaying limited homology to other genera of the Vequintavirinae family. Host range analysis showed that these phages have limited activity against a panel of E. coli strains, infecting 6 out of 16 tested isolates, regardless of their phylotype. Electrospray ionization-tandem mass spectrometry (ESI-MS/MS) was performed on the virion of phage W70, allowing the identification of 28 structural proteins, 19 of which were shared with phages of other genera of Vequintavirinae family. The greatest diversity was identified with proteins forming tail fiber structures, likely indicating the adaptation of virions of each phage genus of this subfamily for the recognition of their target receptor on host cells. The findings of this study provide greater insights into the phages of the subfamily Vequintavirinae, contributing to the pool of knowledge currently known about these phages.

IMPORTANCE

Escherichia coli is a well-known bacterium that inhabits diverse ecological niches, including the mammalian gut microbiota. Certain strains are associated with gastrointestinal diseases, and there is a growing interest in using bacteriophages, viruses that infect bacteria, to combat bacterial infections. Here, we describe the isolation and characterization of four novel E. coli bacteriophages that constitute a new genus, Septuagintavirus, within the subfamily Vequintavirinae. We conducted mass spectrometry on virions of a representative phage of this novel clade and compared it to other phages within the subfamily. Our analysis shows that virion structure is highly conserved among all phages, except for proteins related to tail fiber structures implicated in the host range. These findings provide greater insights into the phages of the subfamily Vequintavirinae, contributing to the existing pool of knowledge about these phages.

Anthropogenic pollution may enhance natural transformation in water, favouring the spread of antibiotic resistance genes

Aquatic ecosystems are crucial in the antimicrobial resistance cycle. While intracellular DNA has been extensively studied to understand human activity's impact on antimicrobial resistance gene (ARG) dissemination, extracellular DNA is frequently overlooked. This study examines the effect of anthropogenic water pollution on microbial community diversity, the resistome, and ARG dissemination. We analyzed intracellular and extracellular DNA from wastewater treatment plant effluents and lake surface water by shotgun sequencing. We also conducted experiments to evaluate anthropogenic pollution's effect on transforming extracellular DNA (using Gfp-plasmids carrying ARGs) within a natural microbial community. Chemical analysis showed treated wastewater had higher anthropogenic pollution-related parameters than lake water. The richness of microbial community, antimicrobial resistome, and high-risk ARGs was greater in treated wastewaters than in lake waters both for intracellular and extracellular DNA. Except for the high-risk ARGs, richness was significantly higher in intracellular than in extracellular DNA. Several ARGs were associated with mobile genetic elements and located on plasmids. Furthermore, Gfp-plasmid transformation within a natural microbial community was enhanced by anthropogenic pollution levels. Our findings underscore anthropogenic pollution's pivotal role in shaping microbial communities and their antimicrobial resistome. Additionally, it may facilitate ARG dissemination through extracellular DNA plasmid uptake.

VOGDB-Database of Virus Orthologous Groups

Computational models of homologous protein groups are essential in sequence bioinformatics. Due to the diversity and rapid evolution of viruses, the grouping of protein sequences from virus genomes is particularly challenging. The low sequence similarities of homologous genes in viruses require specific approaches for sequence- and structure-based clustering. Furthermore, the annotation of virus genomes in public databases is not as consistent and up to date as for many cellular genomes. To tackle these problems, we have developed VOGDB, which is a database of virus orthologous groups. VOGDB is a multi-layer database that progressively groups viral genes into groups connected by increasingly remote similarity. The first layer is based on pair-wise sequence similarities, the second layer is based on the sequence profile alignments, and the third layer uses predicted protein structures to find the most remote similarity. VOGDB groups allow for more sensitive homology searches of novel genes and increase the chance of predicting annotations or inferring phylogeny. VOGD B uses all virus genomes from RefSeq and partially reannotates them. VOGDB is updated with every RefSeq release. The unique feature of VOGDB is the inclusion of both prokaryotic and eukaryotic viruses in the same clustering process, which makes it possible to explore old evolutionary relationships of the two groups. VOGDB is freely available at vogdb.org under the CC BY 4.0 license.

Discarded diversity: Novel megaphages, auxiliary metabolic genes, and virally encoded CRISPR-Cas systems in landfills

Background

Viruses are the most abundant microbial entity on the planet, impacting microbial community structure and ecosystem services. Despite outnumbering Bacteria and Archaea by an order of magnitude, viruses have been comparatively underrepresented in reference databases. Metagenomic examinations have illustrated that viruses of Bacteria and Archaea have been specifically understudied in engineered environments. Here we employed metagenomic and computational biology methods to examine the diversity, host interactions, and genetic systems of viruses predicted from 27 samples taken from three municipal landfills across North America.

Results

We identified numerous viruses that are not represented in reference databases, including the third largest bacteriophage genome identified to date (~678 kbp), and note a cosmopolitan diversity of viruses in landfills that are distinct from viromes in other systems. Host-virus interactions were examined via host CRISPR spacer to viral protospacer mapping which captured hyper-targeted viral populations and six viral populations predicted to infect across multiple phyla. Virally-encoded auxiliary metabolic genes (AMGs) were identified with the potential to augment hosts' methane, sulfur, and contaminant degradation metabolisms, including AMGs not previously reported in literature. CRISPR arrays and CRISPR-Cas systems were identified from predicted viral genomes, including the two largest bacteriophage genomes to contain these genetic features. Some virally encoded Cas effector proteins appear distinct relative to previously reported Cas systems and are interesting targets for potential genome editing tools.

Conclusions

Our observations indicate landfills, as heterogeneous contaminated sites with unique selective pressures, are key locations for diverse viruses and atypical virus-host dynamics.

Utilizing profile hidden Markov model databases for discovering viruses from metagenomic data: a comprehensive review

Profile hidden Markov models (pHMMs) are able to achieve high sensitivity in remote homology search, making them popular choices for detecting novel or highly diverged viruses in metagenomic data. However, many existing pHMM databases have different design focuses, making it difficult for users to decide the proper one to use. In this review, we provide a thorough evaluation and comparison for multiple commonly used profile HMM databases for viral sequence discovery in metagenomic data. We characterized the databases by comparing their sizes, their taxonomic coverage, and the properties of their models using quantitative metrics. Subsequently, we assessed their performance in virus identification across multiple application scenarios, utilizing both simulated and real metagenomic data. We aim to offer researchers a thorough and critical assessment of the strengths and limitations of different databases. Furthermore, based on the experimental results obtained from the simulated and real metagenomic data, we provided practical suggestions for users to optimize their use of pHMM databases, thus enhancing the quality and reliability of their findings in the field of viral metagenomics.

Ligand cross-feeding resolves bacterial vitamin B12 auxotrophies

Cobalamin (vitamin B12, herein referred to as B12) is an essential cofactor for most marine prokaryotes and eukaryotes1,2. Synthesized by a limited number of prokaryotes, its scarcity affects microbial interactions and community dynamics2-4. Here we show that two bacterial B12 auxotrophs can salvage different B12 building blocks and cooperate to synthesize B12. A Colwellia sp. synthesizes and releases the activated lower ligand α-ribazole, which is used by another B12 auxotroph, a Roseovarius sp., to produce the corrin ring and synthesize B12. Release of B12 by Roseovarius sp. happens only in co-culture with Colwellia sp. and only coincidently with the induction of a prophage encoded in Roseovarius sp. Subsequent growth of Colwellia sp. in these conditions may be due to the provision of B12 by lysed cells of Roseovarius sp. Further evidence is required to support a causative role for prophage induction in the release of B12. These complex microbial interactions of ligand cross-feeding and joint B12 biosynthesis seem to be widespread in marine pelagic ecosystems. In the western and northern tropical Atlantic Ocean, bacteria predicted to be capable of salvaging cobinamide and synthesizing only the activated lower ligand outnumber B12 producers. These findings add new players to our understanding of B12 supply to auxotrophic microorganisms in the ocean and possibly in other ecosystems.

Discovery and description of novel phage genomes from urban microbiomes sampled by the MetaSUB consortium

Bacteriophages are recognized as the most abundant members of microbiomes and have therefore a profound impact on microbial communities through the interactions with their bacterial hosts. The International Metagenomics and Metadesign of Subways and Urban Biomes Consortium (MetaSUB) has sampled mass-transit systems in 60 cities over 3 years using metagenomics, throwing light into these hitherto largely unexplored urban environments. MetaSUB focused primarily on the bacterial community. In this work, we explored MetaSUB metagenomic data in order to recover and analyze bacteriophage genomes. We recovered and analyzed 1714 phage genomes with size at least 40 kbp, from the class Caudoviricetes, the vast majority of which (80%) are novel. The recovered genomes were predicted to belong to temperate (69%) and lytic (31%) phages. Thirty-three of these genomes have more than 200 kbp, and one of them reaches 572 kbp, placing it among the largest phage genomes ever found. In general, the phages tended to be site-specific or nearly so, but 194 genomes could be identified in every city from which phage genomes were retrieved. We predicted hosts for 48% of the phages and observed general agreement between phage abundance and the respective bacterial host abundance, which include the most common nosocomial multidrug-resistant pathogens. A small fraction of the phage genomes are carriers of antibiotic resistance genes, and such genomes tended to be particularly abundant in the sites where they were found. We also detected CRISPR-Cas systems in five phage genomes. This study expands the previously reported MetaSUB results and is a contribution to the knowledge about phage diversity, global distribution, and phage genome content.

Defence systems and horizontal gene transfer in bacteria

Horizontal gene transfer (HGT) is a fundamental process in prokaryotic evolution, contributing significantly to diversification and adaptation. HGT is typically facilitated by mobile genetic elements (MGEs), such as conjugative plasmids and phages, which often impose fitness costs on their hosts. However, a considerable number of bacterial genes are involved in defence mechanisms that limit the propagation of MGEs, suggesting they may actively restrict HGT. In our study, we investigated whether defence systems limit HGT by examining the relationship between the HGT rate and the presence of 73 defence systems across 12 bacterial species. We discovered that only six defence systems, three of which were different CRISPR-Cas subtypes, were associated with a reduced gene gain rate at the species evolution scale. Hosts of these defence systems tend to have a smaller pangenome size and fewer phage-related genes compared to genomes without these systems. This suggests that these defence mechanisms inhibit HGT by limiting prophage integration. We hypothesize that the restriction of HGT by defence systems is species-specific and depends on various ecological and genetic factors, including the burden of MGEs and the fitness effect of HGT in bacterial populations.

MetaCerberus: distributed highly parallelized HMM-based processing for robust functional annotation across the tree of life

MOTIVATION

MetaCerberus is a massively parallel, fast, low memory, scalable annotation tool for inference gene function across genomes to metacommunities. MetaCerberus provides an elusive HMM/HMMER-based tool at a rapid scale with low memory. It offers scalable gene elucidation to major public databases, including KEGG (KO), COGs, CAZy, FOAM, and specific databases for viruses, including VOGs and PHROGs, from single genomes to metacommunities.

RESULTS

MetaCerberus is 1.3× as fast on a single node than eggNOG-mapper v2 on 5× less memory using an exclusively HMM/HMMER mode. In a direct comparison, MetaCerberus provides better annotation of viruses, phages, and archaeal viruses than DRAM, Prokka, or InterProScan. MetaCerberus annotates more KOs across domains when compared to DRAM, with a 186× smaller database, and with 63× less memory. MetaCerberus is fully integrated for automatic analysis of statistics and pathways using differential statistic tools (i.e. DESeq2 and edgeR), pathway enrichment (GAGE R), and pathview R. MetaCerberus provides a novel tool for unlocking the biosphere across the tree of life at scale.

AVAILABILITY AND IMPLEMENTATION

MetaCerberus is written in Python and distributed under a BSD-3 license. The source code of MetaCerberus is freely available at https://github.com/raw-lab/metacerberus compatible with Python 3 and works on both Mac OS X and Linux. MetaCerberus can also be easily installed using bioconda: mamba create -n metacerberus -c bioconda -c conda-forge metacerberus.

Transmission and dynamics of mother-infant gut viruses during pregnancy and early life

Early development of the gut ecosystem is crucial for lifelong health. While infant gut bacterial communities have been studied extensively, the infant gut virome remains under-explored. To study the development of the infant gut virome over time and the factors that shape it, we longitudinally assess the composition of gut viruses and their bacterial hosts in 30 women during and after pregnancy and in their 32 infants during their first year of life. Using shotgun metagenomic sequencing applied to dsDNA extracted from Virus-Like Particles (VLPs) and bacteria, we generate 205 VLP metaviromes and 322 total metagenomes. With this data, we show that while the maternal gut virome composition remains stable during late pregnancy and after birth, the infant gut virome is dynamic in the first year of life. Notably, infant gut viromes contain a higher abundance of active temperate phages compared to maternal gut viromes, which decreases over the first year of life. Moreover, we show that the feeding mode and place of delivery influence the gut virome composition of infants. Lastly, we provide evidence of co-transmission of viral and bacterial strains from mothers to infants, demonstrating that infants acquire some of their virome from their mother's gut.

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

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

Dynamic nature of viral and bacterial communities in human faeces

Bacteriophages are a major component of the gut microbiome and are believed to play a role in establishment and stabilization of microbial communities by influencing taxonomic and functional diversity. We show that the activity of lytic and temperate phages can also significantly affect bacterial community structure in a model of extended colonic retention. Intact fresh human feces were incubated anaerobically at 37°C without homogenization and subjected to metagenomic sequencing. We observed subject-specific blooms and collapses of selected bacteriophage and bacterial populations within some individuals. Most notable were striking collapses of Prevotella populations accompanied by increases in specific bacteriophages. In a number of cases, we even observed a shift from one bacterial "enterotype" to another within 48 h. These results confirm that intact feces represents a highly dynamic ecological system and suggests that colonic retention time could have a profound effect on microbiome composition, including a significant impact by bacteriophages.

Defense systems and horizontal gene transfer in bacteria

Horizontal gene transfer (HGT) is a fundamental process in the evolution of prokaryotes, making major contributions to diversification and adaptation. Typically, HGT is facilitated by mobile genetic elements (MGEs), such as conjugative plasmids and phages that generally impose fitness costs on their hosts. However, a substantial fraction of bacterial genes is involved in defense mechanisms that limit the propagation of MGEs, raising the possibility that they can actively restrict HGT. Here we examine whether defense systems curb HGT by exploring the connections between HGT rate and the presence of 73 defense systems in 12 bacterial species. We found that only 6 defense systems, 3 of which are different CRISPR-Cas subtypes, are associated with the reduced gene gain rate on the scale of species evolution. The hosts of such defense systems tend to have a smaller pangenome size and harbor fewer phage-related genes compared to genomes lacking these systems, suggesting that these defense mechanisms inhibit HGT by limiting the integration of prophages. We hypothesize that restriction of HGT by defense systems is species-specific and depends on various ecological and genetic factors, including the burden of MGEs and fitness effect of HGT in bacterial populations.

Functional and evolutionary significance of unknown genes from uncultivated taxa

Many of the Earth's microbes remain uncultured and understudied, limiting our understanding of the functional and evolutionary aspects of their genetic material, which remain largely overlooked in most metagenomic studies1. Here we analysed 149,842 environmental genomes from multiple habitats2-6 and compiled a curated catalogue of 404,085 functionally and evolutionarily significant novel (FESNov) gene families exclusive to uncultivated prokaryotic taxa. All FESNov families span multiple species, exhibit strong signals of purifying selection and qualify as new orthologous groups, thus nearly tripling the number of bacterial and archaeal gene families described to date. The FESNov catalogue is enriched in clade-specific traits, including 1,034 novel families that can distinguish entire uncultivated phyla, classes and orders, probably representing synapomorphies that facilitated their evolutionary divergence. Using genomic context analysis and structural alignments we predicted functional associations for 32.4% of FESNov families, including 4,349 high-confidence associations with important biological processes. These predictions provide a valuable hypothesis-driven framework that we used for experimental validatation of a new gene family involved in cell motility and a novel set of antimicrobial peptides. We also demonstrate that the relative abundance profiles of novel families can discriminate between environments and clinical conditions, leading to the discovery of potentially new biomarkers associated with colorectal cancer. We expect this work to enhance future metagenomics studies and expand our knowledge of the genetic repertory of uncultivated organisms.

RVvictor: Virus RNA-directed molecular interactions for RNA virus infection

RNA viruses are major human pathogens that cause seasonal epidemics and occasional pandemic outbreaks. Due to the nature of their RNA genomes, it is anticipated that virus's RNA interacts with host protein (INTPRO), messenger RNA (INTmRNA), and non-coding RNA (INTncRNA) to perform their particular functions during their transcription and replication. In other words, thus, it is urgently needed to have such valuable data on virus RNA-directed molecular interactions (especially INTPROs), which are highly anticipated to attract broad research interests in the fields of RNA virus translation and replication. In this study, a new database was constructed to describe the virus RNA-directed interaction (INTPRO, INTmRNA, INTncRNA) for RNA virus (RVvictor). This database is unique in a) unambiguously characterizing the interactions between viruses RNAs and host proteins, b) providing, for the first time, the most systematic RNA-directed interaction data resources in providing clues to understand the molecular mechanisms of RNA viruses' translation, and replication, and c) in RVvictor, comprehensive enrichment analysis is conducted for each virus RNA based on its associated target genes/proteins, and the enrichment results were explicitly illustrated using various graphs. We found significant enrichment of a suite of pathways related to infection, translation, and replication, e.g., HIV infection, coronavirus disease, regulation of viral genome replication, and so on. Due to the devastating and persistent threat posed by the RNA virus, RVvictor constructed, for the first time, a possible network of cross-talk in RNA-directed interaction, which may ultimately explain the pathogenicity of RNA virus infection. The knowledge base might help develop new anti-viral therapeutic targets in the future. It's now free and publicly accessible at: https://idrblab.org/rvvictor/.

nail: software for high-speed, high-sensitivity protein sequence annotation

" Fast is fine, but accuracy is final. " -- Wyatt Earp.

Background

The extreme diversity of newly sequenced organisms and considerable scale of modern sequence databases lead to a tension between competing needs for sensitivity and speed in sequence annotation, with multiple tools displacing the venerable BLAST software suite on one axis or another. Alignment based on profile hidden Markov models (pHMMs) has demonstrated state of art sensitivity, while recent algorithmic advances have resulted in hyper-fast annotation tools with sensitivity close to that of BLAST.

Results

Here, we introduce a new tool that bridges the gap between advances in these two directions, reaching speeds comparable to fast annotation methods such as MMseqs2 while retaining most of the sensitivity offered by pHMMs. The tool, called nail, implements a heuristic approximation of the pHMM Forward/Backward (FB) algorithm by identifying a sparse subset of the cells in the FB dynamic programming matrix that contains most of the probability mass. The method produces an accurate approximation of pHMM scores and E-values with high speed and small memory requirements. On a protein benchmark, nail recovers the majority of recall difference between MMseqs2 and HMMER, with run time ~26x faster than HMMER3 (only ~2.4x slower than MMseqs2's sensitive variant). nail is released under the open BSD-3-clause license and is available for download at https://github.com/TravisWheelerLab/nail.

Large-scale genomic survey with deep learning-based method reveals strain-level phage specificity determinants

BACKGROUND

Phage therapy, reemerging as a promising approach to counter antimicrobial-resistant infections, relies on a comprehensive understanding of the specificity of individual phages. Yet the significant diversity within phage populations presents a considerable challenge. Currently, there is a notable lack of tools designed for large-scale characterization of phage receptor-binding proteins, which are crucial in determining the phage host range.

RESULTS

In this study, we present SpikeHunter, a deep learning method based on the ESM-2 protein language model. With SpikeHunter, we identified 231,965 diverse phage-encoded tailspike proteins, a crucial determinant of phage specificity that targets bacterial polysaccharide receptors, across 787,566 bacterial genomes from 5 virulent, antibiotic-resistant pathogens. Notably, 86.60% (143,200) of these proteins exhibited strong associations with specific bacterial polysaccharides. We discovered that phages with identical tailspike proteins can infect different bacterial species with similar polysaccharide receptors, underscoring the pivotal role of tailspike proteins in determining host range. The specificity is mainly attributed to the protein's C-terminal domain, which strictly correlates with host specificity during domain swapping in tailspike proteins. Importantly, our dataset-driven predictions of phage-host specificity closely match the phage-host pairs observed in real-world phage therapy cases we studied.

CONCLUSIONS

Our research provides a rich resource, including both the method and a database derived from a large-scale genomics survey. This substantially enhances understanding of phage specificity determinants at the strain level and offers a valuable framework for guiding phage selection in therapeutic applications.

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.

Comparative Analyses of Bacteriophage Genomes

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

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

IMPORTANCE

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

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

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

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.

Viromes vs. mixed community metagenomes: choice of method dictates interpretation of viral community ecology

Background

Viruses, the majority of which are uncultivated, are among the most abundant biological entities on Earth. From altering microbial physiology to driving community dynamics, viruses are fundamental members of microbiomes. While the number of studies leveraging viral metagenomics (viromics) for studying uncultivated viruses is growing, standards for viromics research are lacking. Viromics can utilize computational discovery of viruses from total metagenomes of all community members (hereafter metagenomes) or use physical separation of virus-specific fractions (hereafter viromes). However, differences in the recovery and interpretation of viruses from metagenomes and viromes obtained from the same samples remain understudied.

Results

Here, we compare viral communities from paired viromes and metagenomes obtained from 60 diverse samples across human gut, soil, freshwater, and marine ecosystems. Overall, viral communities obtained from viromes were more abundant and species rich than those obtained from metagenomes, although there were some exceptions. Despite this, metagenomes still contained many viral genomes not detected in viromes. We also found notable differences in the predicted lytic state of viruses detected in viromes vs metagenomes at the time of sequencing. Other forms of variation observed include genome presence/absence, genome quality, and encoded protein content between viromes and metagenomes, but the magnitude of these differences varied by environment.

Conclusions

Overall, our results show that the choice of method can lead to differing interpretations of viral community ecology. We suggest that the choice of whether to target a metagenome or virome to study viral communities should be dependent on the environmental context and ecological questions being asked. However, our overall recommendation to researchers investigating viral ecology and evolution is to pair both approaches to maximize their respective benefits.

Broad-range capsule-dependent lytic Sugarlandvirus against Klebsiella sp

IMPORTANCE

The emergence of multi-drug resistant bacteria is a global health problem. Among them, Klebsiella pneumoniae is considered a high-priority pathogen, making it necessary to develop new therapeutic tools to reduce the bacterial burden in an effective and sustainable manner. Phages, bacterial viruses, are very promising tools. However, phages are highy specific, rendering large-scale therapeutics costly to implement. This is especially certain in Klebsiella, a capsular bacterium in which phages have been shown to be capsular type dependent, infecting one or a few capsular types through specific enzymes called depolymerases. In this study, we have isolated and characterized novel phages with lytic ability against bacteria from a wide variety of capsular types, representing the Klebsiella phages with the widest range of infection described. Remarkably, these broad-range phages showed capsule dependency, despite the absence of depolymerases in their genomes, implying that infectivity could be governed by alternative mechanisms yet to be uncovered.

Genomic and proteomic characterization of vB_SauM-UFV_DC4, a novel Staphylococcus jumbo phage

Staphylococcus aureus is one of the most relevant mastitis pathogens in dairy cattle, and the acquisition of antimicrobial resistance genes presents a significant health issue in both veterinary and human fields. Among the different strategies to tackle S. aureus infection in livestock, bacteriophages have been thoroughly investigated in the last decades; however, few specimens of the so-called jumbo phages capable of infecting S. aureus have been described. Herein, we report the biological, genomic, and structural proteomic features of the jumbo phage vB_SauM-UFV_DC4 (DC4). DC4 exhibited a remarkable killing activity against S. aureus isolated from the veterinary environment and stability at alkaline conditions (pH 4 to 12). The complete genome of DC4 is 263,185 bp (GC content: 25%), encodes 263 predicted CDSs (80% without an assigned function), 1 tRNA (Phe-tRNA), multisubunit RNA polymerase, and an RNA-dependent DNA polymerase. Moreover, comparative analysis revealed that DC4 can be considered a new viral species belonging to a new genus DC4 and showed a similar set of lytic proteins and depolymerase activity with closely related jumbo phages. The characterization of a new S. aureus jumbo phage increases our understanding of the diversity of this group and provides insights into the biotechnological potential of these viruses. KEY POINTS: • vB_SauM-UFV_DC4 is a new viral species belonging to a new genus within the class Caudoviricetes. • vB_SauM-UFV_DC4 carries a set of RNA polymerase subunits and an RNA-directed DNA polymerase. • vB_SauM-UFV_DC4 and closely related jumbo phages showed a similar set of lytic proteins.

Identification of Huge Phages from Wastewater Metagenomes

Huge phages have genomes larger than 200 kilobases, which are particularly interesting for their genetic inventory and evolution. We screened 165 wastewater metagenomes for the presence of viral sequences. After identifying over 600 potential huge phage genomes, we reduced the dataset using manual curation by excluding viral contigs that did not contain viral protein-coding genes or consisted of concatemers of several small phage genomes. This dataset showed seven fully annotated huge phage genomes. The phages grouped into distinct phylogenetic clades, likely forming new genera and families. A phylogenomic analysis between our huge phages and phages with smaller genomes, i.e., less than 200 kb, supported the hypothesis that huge phages have undergone convergent evolution. The genomes contained typical phage protein-coding genes, sequential gene cassettes for metabolic pathways, and complete inventories of tRNA genes covering all standard and rare amino acids. Our study showed a pipeline for huge phage analyses that may lead to new enzymes for therapeutic or biotechnological applications.

Enhancing plant growth in biofertilizer-amended soil through nitrogen-transforming microbial communities

Biofertilizers have immense potential for enhancing agricultural productivity. However, there is still a need for clarification regarding the specific mechanisms through which these biofertilizers improve soil properties and stimulate plant growth. In this research, a bacterial agent was utilized to enhance plant growth and investigate the microbial modulation mechanism of soil nutrient turnover using metagenomic technology. The results demonstrated a significant increase in soil fast-acting nitrogen (by 46.7%) and fast-acting phosphorus (by 88.6%) upon application of the bacterial agent. This finding suggests that stimulated soil microbes contribute to enhanced nutrient transformation, ultimately leading to improved plant growth. Furthermore, the application of the bacterial agent had a notable impact on the accumulation of key genes involved in nitrogen cycling. Notably, it enhanced nitrification genes (amo, hao, and nar), while denitrification genes (nir and nor) showed a slight decrease. This indicates that ammonium oxidation may be the primary pathway for increasing fast-acting nitrogen in soils. Additionally, the bacterial agent influenced the composition and functional structure of the soil microbial community. Moreover, the metagenome-assembled genomes (MAGs) obtained from the soil microbial communities exhibited complementary metabolic processes, suggesting mutual nutrient exchange. These MAGs contained widely distributed and highly abundant genes encoding plant growth promotion (PGP) traits. These findings emphasize how soil microbial communities can enhance vegetation growth by increasing nutrient availability and regulating plant hormone production. This effect can be further enhanced by introducing inoculated microbial agents. In conclusion, this study provides novel insights into the mechanisms underlying the beneficial effects of biofertilizers on soil properties and plant growth. The significant increase in nutrient availability, modulation of key genes involved in nitrogen cycling, and the presence of MAGs encoding PGP traits highlight the potential of biofertilizers to improve agricultural practices. These findings have important implications for enhancing agricultural sustainability and productivity, with positive societal and environmental impacts.

Characterization of phage vB_EcoS-EE09 infecting E. coli DSM613 Isolated from Wastewater Treatment Plant Effluent and Comparative Proteomics of the Infected and Non-Infected Host

Phages influence microbial communities, can be applied in phage therapy, or may serve as bioindicators, e.g., in (waste)water management. We here characterized the Escherichia phage vB_EcoS-EE09 isolated from an urban wastewater treatment plant effluent. Phage vB_EcoS-EE09 belongs to the genus Dhillonvirus, class Caudoviricetes. It has an icosahedral capsid with a long non-contractile tail and a dsDNA genome with an approximate size of 44 kb and a 54.6% GC content. Phage vB_EcoS-EE09 infected 12 out of the 17 E. coli strains tested. We identified 16 structural phage proteins, including the major capsid protein, in cell-free lysates by protein mass spectrometry. Comparative proteomics of protein extracts of infected E. coli cells revealed that proteins involved in amino acid and protein metabolism were more abundant in infected compared to non-infected cells. Among the proteins involved in the stress response, 74% were less abundant in the infected cultures compared to the non-infected controls, with six proteins showing significant less abundance. Repressing the expression of these proteins may be a phage strategy to evade host defense mechanisms. Our results contribute to diversifying phage collections, identifying structural proteins to enable better reliability in annotating taxonomically related phage genomes, and understanding phage-host interactions at the protein level.

Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy

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

Distantly related Alteromonas bacteriophages share tail fibers exhibiting properties of transient chaperone caps

The host recognition modules encoding the injection machinery and receptor binding proteins (RBPs) of bacteriophages are predisposed to mutation and recombination to maintain infectivity towards co-evolving bacterial hosts. In this study, we reveal how Alteromonas mediterranea schitovirus A5 shares its host recognition module, including tail fiber and cognate chaperone, with phages from distantly related families including Alteromonas myovirus V22. While the V22 chaperone is essential for producing active tail fibers, here we demonstrate production of functional A5 tail fibers regardless of chaperone co-expression. AlphaFold-generated models of tail fiber and chaperone pairs from phages A5, V22, and other Alteromonas phages reveal how amino acid insertions within both A5-like proteins results in a knob domain duplication in the tail fiber and a chaperone β-hairpin "tentacle" extension. These structural modifications are linked to differences in chaperone dependency between the A5 and V22 tail fibers. Structural similarity between the chaperones and intramolecular chaperone domains of other phage RBPs suggests an additional function of these chaperones as transient fiber "caps". Finally, our identification of homologous host recognition modules from morphologically distinct phages implies that horizontal gene transfer and recombination events between unrelated phages may be a more common process than previously thought among Caudoviricetes phages.

Application of a novel phage LPCS28 for biological control of Cronobacter sakazakii in milk and reconstituted powdered infant formula

Contamination of infant formula with Cronobacter sakazakii (C. sakazakii) can cause fatal infections in neonates. Phages have emerged as promising antibacterial agents for food safety, but their effectiveness may be limited by thermal processing. In this study, we isolated 27 C. sakazakii phages from environmental water samples and selected LPCS28 due to its broad lysis spectrum. The titer of LPCS28 will not be significantly affected by heating at a temperature of 60 °C for one hour. In both reconstituted powdered infant formula (RPIF) and liquid milk, the pre-added LPCS28, after the thermal processing at 63 °C for 30 min, significantly inhibited the post-contaminated C. sakazakii (103 CFU/mL) and eventually reduced the number of C. sakazakii to below the limit of detection (<10 CFU/mL) within 9 h at 37 °C and significantly delayed the increase of bacterial concentration in the samples at 23 °C. The phylogenetic analysis revealed that LPCS28 belonged to a new genus, we proposed as Nanhuvirus, under the family Straboviridae. These findings suggest that phage LPCS28 is a promising biological control agent for pathogenic C. sakazakii in the dairy industry.

The phageome in normal and inflamed human skin

Dysbiosis of skin microbiota drives the progression of atopic dermatitis (AD). The contribution of bacteriophages to bacterial community compositions in normal and inflamed skin is unknown. Using shotgun metagenomics from skin swabs of healthy individuals and patients with AD, we found 13,586 potential viral contiguous DNA sequences, which could be combined into 164 putative viral genomes including 133 putative phages. The Shannon diversity index for the viral metagenome-assembled genomes (vMAGs) did not correlate with AD. In total, we identified 28 vMAGs that differed significantly between normal and AD skin. Quantitative polymerase chain reaction validation of three complete vMAGs revealed their independence from host bacterium abundance. Our data indicate that normal and inflamed skin harbor distinct phageomes and suggest a causative relationship between changing viral and bacterial communities as a driver of skin pathology.

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets

Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models

The study of viral communities has revealed the enormous diversity and impact these biological entities have on various ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterisation of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterisation of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities, a large metagenomics study, and a collection of publicly available viral genomic sequences from the human gut. The results showed that VIRify could identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an average accuracy of 86.6%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Finally, the use of VIRify led to a large expansion in the number of taxonomically classified human gut viral sequences and the improvement of outdated and shallow taxonomic classifications. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them.

zol & fai: large-scale targeted detection and evolutionary investigation of gene clusters

Many universally and conditionally important genes are genomically aggregated within clusters. Here, we introduce fai and zol, which together enable large-scale comparative analysis of different types of gene clusters and mobile-genetic elements (MGEs), such as biosynthetic gene clusters (BGCs) or viruses. Fundamentally, they overcome a current bottleneck to reliably perform comprehensive orthology inference at large scale across broad taxonomic contexts and thousands of genomes. First, fai allows the identification of orthologous or homologous instances of a query gene cluster of interest amongst a database of target genomes. Subsequently, zol enables reliable, context-specific inference of protein-encoding ortholog groups for individual genes across gene cluster instances. In addition, zol performs functional annotation and computes a variety of statistics for each inferred ortholog group. These programs are showcased through application to: (i) longitudinal tracking of a virus in metagenomes, (ii) discovering novel population-genetic insights of two common BGCs in a fungal species, and (iii) uncovering large-scale evolutionary trends of a virulence-associated gene cluster across thousands of genomes from a diverse bacterial genus.

MgCod: Gene Prediction in Phage Genomes with Multiple Genetic Codes

Massive sequencing of microbiomes has led to the discovery of a large number of phage genomes with intermittent stop codon recoding. We have developed a computational tool, MgCod, that identifies genomic regions (blocks) with distinct stop codon recoding simultaneously with the prediction of protein-coding regions. When MgCod was used to scan a large volume of human metagenomic contigs hundreds of viral contigs with intermittent stop codon recoding were revealed. Many of these contigs originated from genomes of known crAssphages. Further analyses had shown that intermittent recoding was associated with subtle patterns in the organization of protein-coding genes, such as 'single-coding' and 'dual-coding'. The dual-coding genes, clustered into blocks, could be translated by two alternative codes producing nearly identical proteins. It was observed that the dual-coded blocks were enriched with the early-stage phage genes, while the late-stage genes were residing in the single-coded blocks. MgCod can identify types of stop codon recoding in novel genomic sequences in parallel with gene prediction. It is available for download from https://github.com/gatech-genemark/MgCod.

Deciphering Phage-Host Specificity Based on the Association of Phage Depolymerases and Bacterial Surface Glycan with Deep Learning

Phage tailspike proteins are depolymerases that target diverse bacterial surface glycans with high specificity, determining the host-specificity of numerous phages. To address the challenge of identifying tailspike proteins due to their sequence diversity, we developed SpikeHunter, an approach based on the ESM-2 protein language model. Using SpikeHunter, we successfully identified 231,965 tailspike proteins from a dataset comprising 8,434,494 prophages found within 165,365 genomes of five common pathogens. Among these proteins, 143,035 tailspike proteins displayed strong associations with serotypes. Moreover, we observed highly similar tailspike proteins in species that share closely related serotypes. We found extensive domain swapping in all five species, with the C-terminal domain being significantly associated with host serotype highlighting its role in host range determination. Our study presents a comprehensive cross-species analysis of tailspike protein to serotype associations, providing insights applicable to phage therapy and biotechnology.

Evolutionary pathways for deep-sea adaptation in marine planktonic Actinobacteriota

The deep ocean, one of the largest ecosystems on earth, is dominated by microorganisms that are keystones in the regulation of biogeochemical cycles. However, the evolutionary pathways underlying the specific adaptations required (e.g., high pressure and low temperature) by this unique niche remain understudied. Here, we analyzed the first representatives belonging to the order Acidimicrobiales, a group of marine planktonic Actinobacteriota, that specifically inhabits the aphotic zone of the oceanic water column (>200 m). Compared with their epipelagic counterparts, deep-sea representatives showed the same evolution in genome architecture with higher GC content, longer intergenic spaces as well as higher nitrogen (N-ARSC) and lower carbon (C-ARSC) content in encoded amino acid residue side chains consistent with the higher nitrogen concentration and lower carbon concentration in deep waters compared to the photic zone. Metagenomic recruitment showed distribution patterns that allowed the description of different ecogenomic units within the three deep water-associated genera defined by our phylogenomic analyses (UBA3125, S20-B6 and UBA9410). The entire genus UBA3125 was found exclusively associated with oxygen minimum zones linked to the acquisition of genes involved in denitrification. Genomospecies of genus S20-B6 recruited in samples from both mesopelagic (200-1,000 m) and bathypelagic (1000-4,000 m) zones, including polar regions. Diversity in the genus UBA9410 was higher, with genomospecies widely distributed in temperate zones, others in polar regions, and the only genomospecies associated with abyssal zones (>4,000 m). At the functional level, groups beyond the epipelagic zone have a more complex transcriptional regulation including in their genomes a unique WhiB paralog. In addition, they showed higher metabolic potential for organic carbon and carbohydrate degradation as well as the ability to accumulate glycogen as a source of carbon and energy. This could compensate for energy metabolism in the absence of rhodopsins, which is only present in genomes associated with the photic zone. The abundance in deep samples of cytochrome P450 monooxygenases associated with the genomes of this order suggests an important role in remineralization of recalcitrant compounds throughout the water column.

Genomic diversity and ecological distribution of marine Pseudoalteromonas phages

Pseudoalteromonas, with a ubiquitous distribution, is one of the most abundant marine bacterial genera. It is especially abundant in the deep sea and polar seas, where it has been found to have a broad metabolic capacity and unique co-existence strategies with other organisms. However, only a few Pseudoalteromonas phages have so far been isolated and investigated and their genomic diversity and distribution patterns are still unclear. Here, the genomes, taxonomic features and distribution patterns of Pseudoalteromonas phages are systematically analyzed, based on the microbial and viral genomes and metagenome datasets. A total of 143 complete or nearly complete Pseudoalteromonas-associated phage genomes (PSAPGs) were identified, including 34 Pseudoalteromonas phage isolates, 24 proviruses, and 85 Pseudoalteromonas-associated uncultured viral genomes (UViGs); these were assigned to 47 viral clusters at the genus level. Many integrated proviruses (n = 24) and filamentous phages were detected (n = 32), suggesting the prevalence of viral lysogenic life cycle in Pseudoalteromonas. PSAPGs encoded 66 types of 249 potential auxiliary metabolic genes (AMGs) relating to peptidases and nucleotide metabolism. They may also participate in marine biogeochemical cycles through the manipulation of the metabolism of their hosts, especially in the phosphorus and sulfur cycles. Siphoviral and filamentous PSAPGs were the predominant viral lineages found in polar areas, while some myoviral and siphoviral PSAPGs encoding transposase were more abundant in the deep sea. This study has expanded our understanding of the taxonomy, phylogenetic and ecological scope of marine Pseudoalteromonas phages and deepens our knowledge of viral impacts on Pseudoalteromonas. It will provide a baseline for the study of interactions between phages and Pseudoalteromonas in the ocean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-022-00160-z.

VirClust-A Tool for Hierarchical Clustering, Core Protein Detection and Annotation of (Prokaryotic) Viruses

Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called "megataxonomy of viruses", recognizes six different viral realms, defined based on the presence of viral hallmark genes (VHGs). Within the realms, viruses are classified into hierarchical taxons, ideally defined by the phylogeny of their shared genes. To enable the detection of shared genes, viruses have first to be clustered, and there is currently a need for tools to assist with virus clustering and classification. Here, VirClust is presented. It is a novel, reference-free tool capable of performing: (i) protein clustering, based on BLASTp and Hidden Markov Models (HMMs) similarities; (ii) hierarchical clustering of viruses based on intergenomic distances calculated from their shared protein content; (iii) identification of core proteins and (iv) annotation of viral proteins. VirClust has flexible parameters both for protein clustering and for splitting the viral genome tree into smaller genome clusters, corresponding to different taxonomic levels. Benchmarking on a phage dataset showed that the genome trees produced by VirClust match the current ICTV classification at family, sub-family and genus levels. VirClust is freely available, as a web-service and stand-alone tool.

Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats

Many microbes in nature reside in dense, metabolically interdependent communities. We investigated the nature and extent of microbe-virus interactions in relation to microbial density and syntrophy by examining microbe-virus interactions in a biomass dense, deep-sea hydrothermal mat. Using metagenomic sequencing, we find numerous instances where phylogenetically distant (up to domain level) microbes encode CRISPR-based immunity against the same viruses in the mat. Evidence of viral interactions with hosts cross-cutting microbial domains is particularly striking between known syntrophic partners, for example those engaged in anaerobic methanotrophy. These patterns are corroborated by proximity-ligation-based (Hi-C) inference. Surveys of public datasets reveal additional viruses interacting with hosts across domains in diverse ecosystems known to harbour syntrophic biofilms. We propose that the entry of viral particles and/or DNA to non-primary host cells may be a common phenomenon in densely populated ecosystems, with eco-evolutionary implications for syntrophic microbes and CRISPR-mediated inter-population augmentation of resilience against viruses.

Unlocking the microbial studies through computational approaches: how far have we reached?

The metagenomics approach accelerated the study of genetic information from uncultured microbes and complex microbial communities. In silico research also facilitated an understanding of protein-DNA interactions, protein-protein interactions, docking between proteins and phyto/biochemicals for drug design, and modeling of the 3D structure of proteins. These in silico approaches provided insight into analyzing pathogenic and nonpathogenic strains that helped in the identification of probable genes for vaccines and antimicrobial agents and comparing whole-genome sequences to microbial evolution. Artificial intelligence, more precisely machine learning (ML) and deep learning (DL), has proven to be a promising approach in the field of microbiology to handle, analyze, and utilize large data that are generated through nucleic acid sequencing and proteomics. This enabled the understanding of the functional and taxonomic diversity of microorganisms. ML and DL have been used in the prediction and forecasting of diseases and applied to trace environmental contaminants and environmental quality. This review presents an in-depth analysis of the recent application of silico approaches in microbial genomics, proteomics, functional diversity, vaccine development, and drug design.

Systematic analysis of prophage elements in actinobacterial genomes reveals a remarkable phylogenetic diversity

Actinobacteria represent one of the largest bacterial phyla harboring many species of high medical, biotechnological and ecological relevance. Prophage elements are major contributors to bacterial genome diversity and were shown to significantly shape bacterial fitness and host-microbe interactions. In this study, we performed a systematic analysis of prophage elements in 2406 complete actinobacterial genomes. Overall, 2106 prophage elements were predicted to be present in about 50% (1172/2406) of the analyzed datasets. Interestingly, these identified sequences compose a high prevalence of cryptic prophage elements, indicating genetic decay and domestication. Analysis of the sequence relationship of predicted prophages with known actinobacteriophage genomes revealed an exceptional high phylogenetic diversity of prophage elements. As a trend, we observed a higher prevalence of prophage elements in vicinity to the terminus. Analysis of the prophage-encoded gene functions revealed that prophage sequences significantly contribute to the bacterial antiviral immune system, but no biosynthetic gene clusters involved in the synthesis of known antiphage molecules were identified in prophage genomes. Overall, the current study highlights the remarkable diversity of prophages in actinobacterial genomes, with highly divergent prophages in actinobacterial genomes and thus provides an important basis for further investigation of phage-host interactions in this important bacterial phylum.

Combine thermal processing with polyvalent phage LPEK22 to prevent the Escherichia coli and Salmonella enterica contamination in food

Thermal processing is the most frequently used method to destruct bacteria in food processing. However, insufficient thermal processing may lead to the outbreak of foodborne illness. This study combined thermal processing with thermostable phage to prevent food contamination. The thermostable phages were screened which can retain activity at 70 °C for 1 h. Among them, the polyvalent phage LPEK22 was obtained to lyse Escherichia coli and Salmonella enterica, especially several multi-drug resistant bacteria. In milk (liquid food matrix), LPEK22 significantly reduced the E. coli by 5.00 ± 0.18 log₁₀ CFU/mL and S. enterica by 4.20 ± 0.23 log₁₀ CFU/mL after thermal processing at 63 °C for 30 min. For beef sausage (solid food matrix), LPEK22 significantly reduced the E. coli by 2.34 ± 0.17 log₁₀ CFU/cm² and S. enterica by 1.54 ± 0.13 log₁₀ CFU/cm² after thermal processing at 66 °C for 90 s. Genome analysis revealed that LPEK22 was a novel phage with a unique tail spike protein belonging to the family of Ackermannviridae. LPEK22 did not contain lysogenic, drug-resistant, and virulent genes that may compromise the safety of food application. These results determined that LPEK22, a novel polyvalent Ackermannviridae phage, could combine with thermal processing to prevent drug-resistant E. coli and S. enterica both in vitro and in foods.

A clade of RHH proteins ubiquitous in Sulfolobales and their viruses regulates cell cycle progression

Cell cycle regulation is crucial for all living organisms and is often targeted by viruses to facilitate their own propagation, yet cell cycle progression control is largely underexplored in archaea. In this work, we reveal a cell cycle regulator (aCcr1) carrying a ribbon-helix-helix (RHH) domain and ubiquitous in the Thermoproteota of the order Sulfolobales and their viruses. Overexpression of several aCcr1 members including gp21 of rudivirus SIRV2 and its host homolog SiL_0190 of Saccharolobus islandicus LAL14/1 results in impairment of cell division, evidenced by growth retardation, cell enlargement and an increase in cellular DNA content. Additionally, both gp21 and SiL_0190 can bind to the motif AGTATTA conserved in the promoter of several genes involved in cell division, DNA replication and cellular metabolism thereby repressing or inducing their transcription. Our results suggest that aCcr1 silences cell division and drives progression to the S-phase in Sulfolobales, a function exploited by viruses to facilitate viral propagation.

PCR Assay for Rapid Taxonomic Differentiation of Virulent Staphylococcus aureus and Klebsiella pneumoniae Bacteriophages

Phage therapy is now seen as a promising way to overcome the current global crisis in the spread of multidrug-resistant bacteria. However, phages are highly strain-specific, and in most cases one will have to isolate a new phage or search for a phage suitable for a therapeutic application in existing libraries. At an early stage of the isolation process, rapid screening techniques are needed to identify and type potential virulent phages. Here, we propose a simple PCR approach to differentiate between two families of virulent Staphylococcus phages (Herelleviridae and Rountreeviridae) and eleven genera of virulent Klebsiella phages (Przondovirus, Taipeivirus, Drulisvirus, Webervirus, Jiaodavirus, Sugarlandvirus, Slopekvirus, Jedunavirus, Marfavirus, Mydovirus and Yonseivirus). This assay includes a thorough search of a dataset comprising S. aureus (n = 269) and K. pneumoniae (n = 480) phage genomes available in the NCBI RefSeq/GenBank database for specific genes that are highly conserved at the taxonomic group level. The selected primers showed high sensitivity and specificity for both isolated DNA and crude phage lysates, which permits circumventing DNA purification protocols. Our approach can be extended and applied to any group of phages, given the large number of available genomes in the databases.

High Level of Interaction between Phages and Bacteria in an Artisanal Raw Milk Cheese Microbial Community

Microbial starter cultures are used in the production of many cheeses around the world, such as Parmigiano-Reggiano, in Italy, Époisses, in France, and Canastra, in Brazil, providing many of the unique features of these cheeses. Bacteriophages (phages) are ubiquitous and well known to modulate the structure of bacterial communities, and recent data indicate that cheeses contain a high abundance of naturally occurring phages. Here, we analyze the viral and bacterial metagenomes of Canastra cheese: a traditional artisanal Brazilian cheese produced using an endogenous starter culture and raw milk. Over 1,200 viral operational taxonomic units were recovered using both isolated viral-like particles and complete metagenomic DNA. Common viral families identified included Siphoviridae and Myoviridae, with 40% of putative phage genomes unidentified at the family level of classification. We observed very high phage diversity, which varied greatly across different cheese producers, with 28% of phage genomes detected in only one producer. Several metagenome-assembled genomes were recovered for lactic acid-producing bacteria, as well as nonstarter bacterial species, and we identified several phage-bacterium interactions, at the strain level of resolution, varying across distinct cheese producers. We postulate that at least one bacterial strain detected could be endogenous and unique to the Canastra cheese-producing region in Brazil and that its growth seems to be modulated by autochthonous phages present in this artisanal production system. This phage-host relationship is likely to influence the fermentation dynamics and ultimately the sensorial profile of these cheeses, with implications for other similar cheese production systems around the world. IMPORTANCE Our work demonstrated a dynamic yet stable microbial ecosystem during cheese production using an endogenous starter culture. This was observed across several distinct producers and was marked by genomic evidence of continued phage-bacterium interactions, such as the presence of bacterial defense mechanisms. Furthermore, we provide evidence of unique microbial signatures for each individual cheese producer studied in the region, a fact that may have profound consequences on product traceability. This was the first effort to describe and understand the bacteriophage composition and ecological dynamics within the Brazilian Canastra cheese production system. The study of this prototypical backslopping production system provides a solid background for further mechanistic studies of the production of many cheeses around the world.