Exponential increases in microbial and viral genomic data demand transformational advances in scalable, generalizable frameworks for their interpretation. Standard homology-based functional analyses are hindered by the rapid divergence of microbial and especially viral genomes and proteins that significantly decreases the volume of usable data. Here, we present Protein Set Transformer (PST), a protein-based genome language model that models genomes as sets of proteins without considering sparsely available functional labels. Trained on >100k viruses, PST outperformed other homology- and language model-based approaches for relating viral genomes based on shared protein content. Further, PST demonstrated protein structural and functional awareness by clustering capsid-fold-containing proteins with known capsid proteins and uniquely clustering late gene proteins within related viruses. Our data establish PST as a valuable method for diverse viral genomics, ecology, and evolutionary applications. We posit that the PST framework can be a foundation model for microbial genomics when trained on suitable data.

Mosquitoes can transmit several pathogenic viruses to humans, but their natural viral community is also composed of a myriad of other viruses such as insect-specific viruses (ISVs) and those that infect symbiotic microorganisms. Besides a growing number of studies investigating the mosquito virome, the majority are focused on few urban species, and relatively little is known about the virome of sylvatic mosquitoes, particularly in high biodiverse biomes such as the Brazilian biomes. Here, we characterized the RNA virome of 10 sylvatic mosquito species from Atlantic forest remains at a sylvatic-urban interface in Northeast Brazil employing a metatranscriptomic approach. A total of 16 viral families were detected. The phylogenetic reconstructions of 14 viral families revealed that the majority of the sequences are putative ISVs. The phylogenetic positioning and, in most cases, the association with a high RNA-dependent RNA polymerase amino acid divergence from other known viruses suggests that the viruses characterized here represent at least 34 new viral species. Therefore, the sylvatic mosquito viral community is predominantly composed of highly divergent viruses highlighting the limited knowledge we still have about the natural virome of mosquitoes in general. Moreover, we found that none of the viruses recovered were shared between the species investigated, and only one showed high identity to a virus detected in a mosquito sampled in Peru, South America. These findings add further in-depth understanding about the interactions and coevolution between mosquitoes and viruses in natural environments.
OBJECTIVE: Mosquitoes are medically important insects as they transmit pathogenic viruses to humans and animals during blood feeding. However, their natural microbiota is also composed of a diverse set of viruses that cause no harm to the insect and other hosts, such as insect-specific viruses. In this study, we characterized the RNA virome of sylvatic mosquitoes from Northeast Brazil using unbiased metatranscriptomic sequencing and in-depth bioinformatic approaches. Our analysis revealed that these mosquitoes species harbor a diverse set of highly divergent viruses, and the majority comprises new viral species. Our findings revealed many new virus lineages characterized for the first time broadening our understanding about the natural interaction between mosquitoes and viruses. Finally, it also provided several complete genomes that warrant further assessment for mosquito and vertebrate host pathogenicity and their potential interference with pathogenic arboviruses.

Bats are natural hosts of multiple viruses, many of which have clear zoonotic potential. The search for emerging viruses has been aided by the implementation of metagenomic tools, which have also enabled the detection of unprecedented viral diversity. Currently, this search is mainly focused on RNA viruses, which are largely over-represented in databases. To compensate for this research bias, we analyzed fecal samples from 189 Spanish bats belonging to 22 different species using viral metagenomics. This allowed us to identify 52 complete or near-complete viral genomes belonging to the families Adenoviridae, Circoviridae, Genomoviridae, Papillomaviridae, Parvoviridae, Polyomaviridae and Smacoviridae. Of these, 30 could constitute new species, doubling the number of viruses currently described in Europe. These findings open the door to a more thorough analysis of bat DNA viruses and their zoonotic potential.
OBJECTIVE: Metagenomics has become a fundamental tool to characterize the global virosphere, allowing us not only to understand the existing viral diversity and its ecological implications but also to identify new and emerging viruses. RNA viruses have a higher zoonotic potential, but this risk is also present for some DNA virus families. In our study, we analyzed the DNA fraction of fecal samples from 22 Spanish bat species, identifying 52 complete or near-complete genomes of different viral families with zoonotic potential. This doubles the number of genomes currently described in Europe. Metagenomic data often produce partial genomes that can be difficult to analyze. Our work, however, has characterized a large number of complete genomes, thus facilitating their taxonomic classification and enabling different analyses to be carried out to evaluate their zoonotic potential. For example, recombination studies are relevant since this phenomenon could play a major role in cross-species transmission.

The majority of bacteriophage diversity remains uncharacterized, and new intriguing mechanisms of their biology are being continually described. Members of some phage lineages, such as the Crassvirales, repurpose stop codons to encode an amino acid by using alternate genetic codes. Here, we investigated the prevalence of stop codon reassignment in phage genomes and its subsequent impacts on functional annotation. We predicted 76 genomes within INPHARED and 712 vOTUs from the Unified Human Gut Virome Catalogue (UHGV) that repurpose a stop codon to encode an amino acid. We re-annotated these sequences with modified versions of Pharokka and Prokka, called Pharokka-gv and Prokka-gv, to automatically predict stop codon reassignment prior to annotation. Both tools significantly improved the quality of annotations, with Pharokka-gv performing best. For sequences predicted to repurpose TAG to glutamine (translation table 15), Pharokka-gv increased the median gene length (median of per genome median) from 287 to 481 bp for UHGV sequences (67.8% increase) and from 318 to 550 bp for INPHARED sequences (72.9% increase). The re-annotation increased median coding capacity from 66.8% to 90.0% and from 69.0% to 89.8% for UHGV and INPHARED sequences predicted to use translation table 15. Furthermore, the proportion of genes that could be assigned functional annotation increased, including an increase in the number of major capsid proteins that could be identified. We propose that automatic prediction of stop codon reassignment before annotation is beneficial to downstream viral genomic and metagenomic analyses.

BACKGROUND: Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases\' pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited.
METHODS: Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization.
RESULTS: Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed.
CONCLUSIONS: By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology.

UNASSIGNED: IDS presented pathognomonic dilatation of the jejunum up to Meckel\'s diverticulum.IDS caused weight loss, decreased egg production, and increased culling and mortality.Chicken parvovirus (ChPV) was consistently detected through PCR assays.Chicken megrivirus (ChMV) was consistently detected through viral metagenomics.

We are entering a \'Platinum Age of Virus Discovery\', an era marked by exponential growth in the discovery of virus biodiversity, and driven by advances in metagenomics and computational analysis. In the ecosystem of a human (or any animal) there are more species of viruses than simply those directly infecting the animal cells. Viruses can infect all organisms constituting the microbiome, including bacteria, fungi, and unicellular parasites. Thus the complexity of possible interactions between host, microbe, and viruses is unfathomable. To understand this interaction network we must employ computationally assisted virology as a means of analyzing and interpreting the millions of available samples to make inferences about the ways in which viruses may intersect human health. From a computational viral screen of human neuronal datasets, we identified a novel narnavirus Apocryptovirus odysseus (Ao) which likely infects the neurotropic parasite Toxoplasma gondii. Previously, several parasitic protozoan viruses (PPVs) have been mechanistically established as triggers of host innate responses, and here we present in silico evidence that Ao is a plausible pro-inflammatory factor in human and mouse cells infected by T. gondii. T. gondii infects billions of people worldwide, yet the prognosis of toxoplasmosis disease is highly variable, and PPVs like Ao could function as a hitherto undescribed hypervirulence factor. In a broader screen of over 7.6 million samples, we explored phylogenetically proximal viruses to Ao and discovered nineteen Apocryptovirus species, all found in libraries annotated as vertebrate transcriptome or metatranscriptomes. While samples containing this genus of narnaviruses are derived from sheep, goat, bat, rabbit, chicken, and pigeon samples, the presence of virus is strongly predictive of parasitic Apicomplexa nucleic acid co-occurrence, supporting the fact that Apocryptovirus is a genus of parasite-infecting viruses. This is a computational proof-of-concept study in which we rapidly analyze millions of datasets from which we distilled a mechanistically, ecologically, and phylogenetically refined hypothesis. We predict that this highly diverged Ao RNA virus is biologically a T. gondii infection, and that Ao, and other viruses like it, will modulate this disease which afflicts billions worldwide.

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.

The advent of viral metagenomics, or viromics, has improved our knowledge and understanding of global viral diversity. High-throughput sequencing technologies enable explorations of the ecological roles, contributions to host metabolism, and the influence of viruses in various environments, including the human intestinal microbiome. However, bacterial metagenomic studies frequently have the advantage. The adoption of advanced technologies like long-read sequencing has the potential to be transformative in refining viromics and metagenomics. Here, we examined the effectiveness of long-read and hybrid sequencing by comparing Illumina short-read and Oxford Nanopore Technology (ONT) long-read sequencing technologies and different assembly strategies on recovering viral genomes from human faecal samples. Our findings showed that if a single sequencing technology is to be chosen for virome analysis, Illumina is preferable due to its superior ability to recover fully resolved viral genomes and minimise erroneous genomes. While ONT assemblies were effective in recovering viral diversity, the challenges related to input requirements and the necessity for amplification made it less ideal as a standalone solution. However, using a combined, hybrid approach enabled a more authentic representation of viral diversity to be obtained within samples.

The rising prevalence of liver diseases related to obesity and excessive use of alcohol is fuelling an increasing demand for accurate biomarkers aimed at community screening, diagnosis of steatohepatitis and significant fibrosis, monitoring, prognostication and prediction of treatment efficacy. Breakthroughs in omics methodologies and the power of bioinformatics have created an excellent opportunity to apply technological advances to clinical needs, for instance in the development of precision biomarkers for personalised medicine. Via omics technologies, biological processes from the genes to circulating protein, as well as the microbiome - including bacteria, viruses and fungi, can be investigated on an axis. However, there are important barriers to omics-based biomarker discovery and validation, including the use of semi-quantitative measurements from untargeted platforms, which may exhibit high analytical, inter- and intra-individual variance. Standardising methods and the need to validate them across diverse populations presents a challenge, partly due to disease complexity and the dynamic nature of biomarker expression at different disease stages. Lack of validity causes lost opportunities when studies fail to provide the knowledge needed for regulatory approvals, all of which contributes to a delayed translation of these discoveries into clinical practice. While no omics-based biomarkers have matured to clinical implementation, the extent of data generated has enabled the hypothesis-free discovery of a plethora of candidate biomarkers that warrant further validation. To explore the many opportunities of omics technologies, hepatologists need detailed knowledge of commonalities and differences between the various omics layers, and both the barriers to and advantages of these approaches.